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DNA Methylation of Repeat Regions in Human Cancer and Metabolic Disease
By Haley L. Cash
MPH, Brown University, 2011
B.S., Southampton College, 2006
A Dissertation Submitted in partial Fulfillment of the
Requirements for degree of Doctor of Philosophy
In the Division of Biology and Medicine
At Brown University
Providence, Rhode Island
May 2011
© Copyright 2011 by Haley L. Cash
This dissertation by Haley L. Cash is accepted in its present form by the
Division of Biology and Medicine as satisfying the dissertation requirements for the
Degree of Doctor of Philosophy.
Date_______________
___________________________________
Karl T. Kelsey, M.D., M.O.H., Advisor
Recommended to the Graduate Council
Date_______________
___________________________________
Margaret R. Karagas, Ph.D., Outside Reader
Date_______________
___________________________________
Carmen J. Marsit, Ph.D., Chair
Date_______________
___________________________________
E. Andrés Houseman, Sc.D., Reader
Date_______________
___________________________________
Stephen T. McGarvey, Ph.D., MPH, Reader
Approved by the Graduate Council
Date_______________
___________________________________
Peter Weber, Ph.D.
Dean of the Graduate School
iii
CIRRICULUM VITAE
MAY 2011
Haley L. Cash
Brown University
Box G-E5
Providence, RI 02903
E-mail: [email protected]
Date of birth: April 3, 1986
Place of birth: Woonsocket, RI
Education
Ph.D., Pathobiology, 2011, Brown University, Providence, RI
MPH, 2011, Brown University, Providence, RI
B.S., Environmental Science, Magna Cum Laude, 2006, Southampton College, Southampton, NY
Journal Publications
Cash HL, McGarvey ST, Houseman, EA, Marsit CJ, Hawley, NL, Kelsey, KT. (2011) Metabolic and cardiovascular
disease risk factors and DNA methylation at the LINE-1 repeat region in peripheral blood from Samoan Islanders, J Clin
Endocr Metab, submitted.
Cash HL, Tao L, Yuan JM, Marsit CJ, Houseman EA, Xiang YB, Gao YT, Nelson HH, Kelsey KT. (2011) LINE-1
hypomethylation is associated with bladder cancer risk among non-smoking Chinese. International Journal of Cancer, in
press.
Hawley NL, Menard HL, Viali S, Quested C, Reupena Muagututia S, McGarvey ST. (2011) Genome-Wide Association
Study of Adiposity in Samoan: Prevalence of Non-Communicable Disease and Associated Risk factors. Samoa Medical
Journal, under review.
Hawley NL, Menard HL, Agha G, McGarvey ST. (2010) Preliminary blood lipid, lipoprotein, and glucose findings from
the Genome Wide Association Study of Adiposity in Samoans. Samoa Medical Journal, 2:2; 11-16.
Zecevic A, Menard H, Gurel V, Hagan E, Decaro R, Zhitkovich A. (2009) WRN helicase promotes repair of DNA
double-strand breaks caused by aberrant mismatch repair of chromium-DNA adducts. Cell Cycle, 8:17; 1-10
Reynolds MF, Peterson-Roth EC, Bespalov IA, Johnston T, Gurel VM, Menard HL, Zhitkovich A. (2009) Rapid DNA
double-strand breaks resulting from processing of Cr-DNA crosslinks by both MutS dimers. Cancer Research, 69; 10711079.
Honors and Awards
2009
2008
2008
2006- 2009
2005
2005- 2006
2003- 2006
Brown University, Framework in Global Health Scholarship
Brown University, Healthy Communities Scholarship
Genetic Toxicology Association, Student Travel Award
U.S. Dept. of Health and Human Services, Training Grant Fellowship
Southampton College, Environmental Science Academic Honor Award
Britta A. Mast female excellence in chemistry Scholarship
Southampton College Academic Provost Scholarship
Conference Abstracts
Cash HL, Kelsey KT, Weeks DE, Deka R, Laumoli TS, Viali S, McGarvey ST. (2011). DNA global methylation in
American Samoa and Samoa. The Human Biology Association. Minneapolis, MN.
Menard HL, Yuan JM, Marsit CJ, Wilhelm C, Nelson HH, Kelsey KT. (2010). Body mass index interacts with DNA global
methylation levels to predict bladder cancer in the Shanghai Bladder Cancer Study. American Association for Cancer
Research. Washington, D.C.
Menard HL, Reynolds M, Zhitkovich A. (2008). Formaldehyde induces p53-dependent apoptosis and cell cycle changes in
human lung H460 cells. Genetic Toxicology Association. Newark, DE.
Menard HL, Reynolds M, Zhitkovich A. (2008). Formaldehyde induces toxicity via a p53-dependent signaling pathway.
Society of Toxicology. Seattle, WA.
Menard HL, Reynolds M, Zhitkovich A. (2007). Cell cycle and apoptotic responses of human lung cells to formaldehyde.
Superfund Basic Research Program. Durham, NC.
Menard HL, Marien A, DiPalma K, Rasoulpour T, Hixon M. (2006). DNA damage signaling in the testis. Northeastern
Society of Toxicology. Worcester, MA.
iv
PREFACE
The sum of this work presented in this Ph.D. dissertation, including experiments, analysis, and
discussion as presented herein, have been executed by me. This work is the product of critical
collaborations which have been acknowledged appropriately in Chapters 2, 3, and 4.
v
ACKNOWLEDGEMENTS
I extend my sincere gratitude to Dr. Karl Kelsey, my primary advisor on this
dissertation. The knowledge attained during my work on this project far exceeds the words
written in this dissertation.
I also express great thanks to my committee members, Dr. Carmen Marsit, Dr.
E.Andrés Houseman, and Dr. Margaret Karagas for their patient mentoring and guidance
throughout my graduate career. I especially thank Dr. Stephen McGarvey for the opportunity to
participate in field work in Samoa, an experience that I will always remember fondly.
Additionally, I warmly thank the members of the Kelsey lab, in particular, Dr. Rondi
Butler, Ashley Smith, and Billy Accomando for all of their hard work and support, as well as
the countless laughs and tequila. I especially thank Dr. Graham Poage, who has provided
invaluable advice and encouragement, and perhaps talked me off the ledge a time or two.
Finally, I would like to convey my immense appreciation to my friends and family for all
of their love and support, and for so many great memories over throughout the years. A special
thank you goes out to all of my Providence ladies for a fabulous five years of good times and
unforgettable stories; and to the Providence Women’s Rugby Team for an endless supply of
people to beat up. Above all, I thank my amazing and loving husband, Lt. Eric Cash, for always
believing in me and being there for me.
vi
Table of Contents
Abstract……………………………………………………………………
1
Chapter 1: Introduction…………………………………………………..
3
Thesis Overview……………………………………………………………
4
Bladder Cancer: Epidemiology…………………………………………….
6
Bladder Cancer: presentation, diagnosis, treatment, and survival…………
6
Bladder Cancer: environmental factors……………………………………
8
Bladder Cancer: genetic factors……………………………………………
10
Obesity: definition and epidemiology……………………………………..
11
Obesity: risk factors and health outcomes…………………………………
13
Cardiovascular disease.................................................................................
14
Diabetes……………………………………………………………………
14
American Samoa and Samoa: The history of the “thrifty gene”……….….
15
American Samoa and Samoa: Obesity…………………………………….
16
American Samoa and Samoa: Obesity-related disease……………………
16
Epigenetics………………………………………………………………...
17
DNA methylation………………………………………………….………
18
DNA repeat sequence methylation………………………………………..
19
LINE-1 methylation……………………………………………………….
19
DNA methylation: Cancer………………………………………………...
19
DNA methylation: Bladder Cancer………………………………….…….
20
DNA methylation: Obesity…………………………………………….….
22
DNA methylation: Cardiovascular disease……………………….……….
23
DNA methylation: Diabetes…………………………………………….…
25
Conclusion...................................................................................................
26
References…………………………………………………………………
27
vii
Chapter 2: LINE-1 hypomethylation is associated with bladder
cancer risk among non-smoking Chinese………………………………
45
Abstract.......................................................................................................
47
Introduction……………………………………………………………….
48
Materials and Methods……………………………………………………
49
Results…………………………………………………………………….
55
Discussion…………………………………………………………………
57
Acknowledgements……………………………………………………….
61
References…………………………………………………………………
62
Chapter 3: Metabolic and cardiovascular disease risk factors and
DNA methylation at the LINE-1 repeat region in peripheral blood
from Samoan Islanders………………………………………………….
70
Abstract…………………………………………………………………..
72
Introduction...............................................................................................
74
Materials and Methods…………………………………………………..
76
Results……………………………………………………………………
81
Discussion………………………………………………………………..
83
Acknowledgements………………………………………………………
86
References………………………………………………………………..
87
Chapter 4: PSCA variant rs2294008 is associated with nearby
CpG Methylation in populations from New Hampshire
and Shanghai…………………………………………………………….
98
Abstract…………………………………………………………………..
100
Introduction………………………………………………………………
101
Materials and Methods……………………………………………………
102
viii
Results…………………………………………………………………....
105
Discussion………………………………………………………………...
107
References………………………………………………………………..
111
Chapter 5: Discussion……………………………………………………
120
References…………………………………………………………………
132
ix
List of Tables
Chapter 2
Table 1. Distributions of selected characteristics in patients with
bladder cancer (cases) and control subjects………………………………
66
Table 2. The association between LINE-1 levels and potential risk
factors among control subjects only………………………………………
67
Table 3. LINE-1 levels in relation to risk of bladder cancer……………..
68
Table 4. LINE-1 levels in relation to risk of bladder cancer by
GSTM1 and GSTT1 genotypes……………………………………………
69
Chapter 3
Table 1. Distributions of selected characteristics in study sample
participants…………………………………………………………….....
93
Table 2. Association of LINE-1 methylation with the characteristics of the
participants, stratified by location and gender…………………..………..
94
Table 3. Association of LINE-1 methylation with characteristics
among men………………………………………………………………..
95
Table 4. Association of LINE-1 methylation with characteristics among
women………………………………………………….…………………
96
Table 5. Association of LINE-1 methylation with characteristics among a
restricted female sample with available testosterone level data (N=278)
to examine hormonal affects on LINE-1 methylation levels……………...
97
Chapter 4
Table 1. Characteristics of the participants from New Hampshire
and Shanghai………………………………………………………………
117
Table 2. Methylation class in relation to PSCA status................................
118
Table 3. PSCA status in relation to mean β methylation values of
cg13446199 in New Hampshire and Shanghai……………………………
120
x
List of Figures
Chapter 4
Figure 1. Association of previously defined DNA methylation profiles
and PSCA status among controls…………………………………………
115
Figure 2. Association of DNA methylation profiles defined by
a panel of 10 loci and PSCA status among controls………………………
116
xi
Abstract of DNA Methylation of Repeat Regions in Human Cancer and Metabolic
Disease by Haley L. Cash, Ph.D., MPH, Brown University, May 2011
Non-communicable diseases have recently surpassed communicable diseases as
the number one cause of death globally. These conditions not only lead to increased rates
of mortality, but also contribute to global disability that can greatly impede development.
Although many environmental and genetic risk factors have been associated with these
conditions, epigenetic mechanisms have yet to be properly explored in these diseases.
This thesis aimed to further understand the relationships between DNA methylation and
environmental factors as well as genetic factors in relation to various non-communicable
diseases. When examining the relationships between LINE-1 methylation, bladder
cancer, and risk factors in the Shanghai Bladder Cancer Study, LINE-1 hypomethylation
was found to be significantly associated with increased risk of bladder cancer among
non-smokers; risk was greatest among these individuals with null glutathione-stransferase genoytypes. In this study we also found that CYP1A2 phenotype among
smokers, cruciferous vegetable intake, and glutathione-s-transferase genotypes
significantly influenced LINE-1 methylation among controls. Additionally, men had
significantly higher levels of LINE-1 methylation than women. This LINE-1 gender
difference was also observed in The Samoan Family Study of Overweight and Obese
when LINE-1 methylation was measured in this population. Additionally, LINE-1
methylation was found to be negatively associated with age as well as HDL in men;
whereas insulin and testosterone levels were associated with LINE-1 methylation among
women. Finally, the effects of bladder cancer risk genetic variants within the PSCA gene
(rs2294008) on CpG methylation was evaluated by examining array based DNA
1
methylation profiles. Upon investigation, there were not array-wide methylation
associations with variation; however, methylation of a CpG within the PSCA gene was
significantly associated with SNP status in a dose-response fashion, in which there was a
positive relationship between risk allele quantity and CpG methylation. Overall, this
work demonstrates the importance of DNA methylation in non-communicable diseases.
Additionally, this work suggests that complex relationships exist between environmental
factors, genetics, and epigenetics, advocating the need for further investigations in order
to more effectively understand the role of DNA methylation in non-communicable
disease.
2
Chapter 1
Thesis Overview and Introduction
3
Thesis Overview
Epigenetics depicts heritable alterations in gene expression that do not involve
changes to the genomic sequence, yet result in significant phenotypic outcomes.
Epigenetic regulation of the human genome is essential for proper development and
biologic stability. Epigenetic patterns are initially established in utero, but may be
altered throughout one’s life by aging, exposures, and disease. Epigenetic dysregulation
is thought to play a critical role in the etiology of various diseases, though the majority of
existing research has been conducted in the field of cancer.
DNA methylation at CpG dinucleotides is an important type of epigenetic
regulation that modifies gene expression by altering transcription factor binding
accessibility through conformation changes in chromatin. CpG dinucleotides are highly
underrepresented throughout the genome, and more often than not occur in CpG islands.
CpG islands are associated with almost 50% of all described genes, and are generally
located within the promoter region of these genes. DNA methylation is easily
measurable, and has therefore become a valuable tool in the field of epigenetic research.
The methylation of specific tumor suppressor genes is of great interest among the
cancer research community. A great deal of work has been done that illustrates the
importance of tumor suppressor gene silencing by hypermethylation in almost all types of
cancers. Also recognized, yet not as well understood is the phenomenon of genome-wide
or “global” hypomethylation that occurs in various cancers, often demonstrated by
measurement of DNA repetitive sequences which make up almost half of the human
genome, and are generally silenced through DNA hypermethylation.
4
One aim of this thesis was to understand the relationship between DNA
hypomethylation of repetitive sequences, specifically at long-interspersed nuclear
elements (LINE-1) and bladder cancer, as well as to determine the influence of both
environmental and genetic risk factors on this relationship. Additionally, this thesis
aimed to explore the association between LINE-1 methylation and risk factors associated
with metabolic and cardiovascular diseases. Finally, this thesis aimed to further
understand genetic-epigenetic interactions by examining how single-nucleotide
polymorphisms (SNPs) impact gene-specific methylation. These goals were
accomplished through molecular epidemiologic methods, using data and human
peripheral blood samples collected from the Shanghai Bladder Cancer Study, the Samoan
Family Study of Overweight and Obese, and the New Hampshire Bladder Cancer Study.
This thesis begins with a broad introduction of bladder cancer, obesity,
cardiovascular disease, diabetes, and the study populations examined. Additionally,
previous research conducted in this line of work is outlined. Chapter two details the
associations found between LINE-1 methylation levels (determined using quantitatively
pyrosequenced peripheral blood samples) and risk of bladder cancer, as well as the
impact of selected bladder cancer risk factors on LINE-1 methylation levels within the
Shanghai Bladder Cancer Study. Chapter three provides an overview of the associations
found between metabolic and cardiovascular disease risk factors and LINE-1 methylation
using peripheral blood samples from the Samoan Family Study of Overweight and
Obese. Chapter four summarizes the effects of PSCA genetic variants on CpG
methylation levels (using data from a genome-wide methylation in array) in the New
Hampshire Bladder Cancer Study and the Shanghai Bladder Cancer Study. Finally,
5
chapter five summarizes the work of previous chapters, and discusses the potential future
directions of these projects.
Bladder Cancer: epidemiology
The first disease for which DNA methylation was investigated in this thesis was
bladder cancer. Bladder cancer is the ninth most common form of cancer in the world,
with men being three to four times more at risk than women1. More than 357,000 new
cases of bladder cancer occurred globally in 2002, of which 274,000 were in men and
83,000 were in women2. The worldwide age standardized incidence rate was 10.1 per
100,000 in men, and 2.5 per 10,000 in women 3. In this same global investigation, there
were an estimated 145,000 deaths attributed to bladder cancer, making it the 13th most
frequent cause of death from cancer1, 2. However, there is a 14-fold variation in
international incidence due primarily to differences in exposure to risk factors that will be
described later2.
Bladder Cancer: presentation, diagnosis, treatment, and survival
About three-quarters of bladder cancer patients present with painless, irregular
haematuria, and about 80% of patients initially presenting with disease will have early
stage superficial non-muscle-invasive bladder cancers (stage Ta or T1), whereas the
remaining patients will present with bladder cancer tumors invading the muscularis
propria of the bladder or further (stage T2-T4)4, 5. More than 90% of bladder cancer
6
cases are urothelial transitional cell carcinoma (TCC), and about 5% are squamous cell
carcinoma (SCC)6. TCCs are associated with less-aggressive disease in comparison with
SCCs, resulting in higher mortality of SCC patients than in TCCs7, 8.
Diagnosis of bladder cancer is done by cytoscopy, but further imaging, generally
by computed tomography (CT) or magnetic resonance imaging (MRI) is often performed
to assess stage of disease6. The transurethral resection of bladder tumor (TURBT) is
diagnostic, prognostic, and often therapeutic, and is crucial in determining staging and
course of treatment9. For nonmuscle-invasive disease, TURBT is generally followed by
intravesicle chemotherapy, most frequently involving mitomycin C (MMC) or thiotepa
treatment and/or intravesicle immunotherapy using Bacillus Calmette-Guerin (BCG)10, 11.
Following tumor resection and treatment, surveillance via cytoscopy is essential due to
high frequency of recurrence. This procedure is suggested every three months for the
first 1-2 years, then intermittently after two years6, 10.
Patients with muscle-invasive disease are likely to undergo radical cystectomy10.
This is a major procedure that involves urinary diversion, most commonly using a
neobladder or conduit, both of which are associated with post-operative decreased quality
of life12. These patients often undergo perioperative systemic chemotherapy to treat
metastases that are likely to be present13, 14. Post-treatment patients with muscleinvasive bladder cancer must undergo even more rigorous surveillance than nonmuscleinvasive patients. These individuals require frequent urine screenings, pelvis imaging
every 3-12 months for at least 2 years, urethral washing every 6-12 months, and annual
vitamin B12 level checks for patients with continent diversion10.
7
Relative 5-year survival rates in the United States are dependent upon stage of
diagnosis, and are currently as follows: Ta: 98%, T1:88%, T2:63%, T3:46%, T4:15%15.
In order to attain optimal survival, proper surveillance and follow-up is necessary to
monitor and treat for recurrence. This long term care comes with a substantial financial
burden, making bladder cancer an extremely expensive cancer to properly treat. A recent
study conducted in the United States found that the average cost of bladder cancer was
$65,15816.
Bladder Cancer: environmental factors
Over 50% of TCCs are attributed to tobacco smoke17. Carcinogens in tobacco
smoke such as aromatic arylamines result in DNA adducts that are associated with altered
tumor suppressor gene expression, such as mutations in p53 that are commonly seen in
bladder cancer18. Bladder cancer patients that are smokers generally present with higher
grade and stage tumors, resulting in greater rates of mortality among these individuals19.
Occupational exposures are thought to be responsible for approximately 20% of
bladder cancers19. This is due to occupational contact with a wide variety of industrially
produced, DNA-damaging compounds. For example, exposure to carcinogenic aromatic
chemical compounds such as aromatic amines that are present in aniline dyes and other
industrial chemicals are known to be associated with risk of bladder cancer19, 20.
Additionally, polycyclic aromatic hydrocarbons (PAHs) released from the combustion of
carbon-containing compounds have also been related to the development of bladder
cancer21. Additionally, dry cleaners exposed to perchloroethylene are also known to be at
8
increased risk for bladder cancer22. The most high-risk occupations include painters,
textile workers, and hairdressers, as well as rubber and leather industry workers19.
Other exposures that have been associated with risk for bladder cancer include
chemicals commonly found in drinking water, such as water chlorination byproducts and
inorganic arsenic23-26. Additionally, pelvic radiotherapy is well known to be associated
with risk of bladder cancer27, 28. Also, dietary nitrates/nitrites are controversially
associated with risk of bladder cancer, as data from different studies are conflicting29, 30.
Chronic inflammation caused by urinary tract irritation and infection is also
known to create an increased risk of developing TCC31, 32. Recently, obesity has also
been associated with an increased risk of bladder cancer, presumably from increased
systemic inflammation associated with obesity33. This type of inflammation should not
be confused with that caused by Schistosomiasis haematobium, which is well
documented as the primary risk factor for squamaous cell carcinoma (SCC).
Rates of bladder cancer are highest among developing countries in which
Schistosomiasis haematobium infection is endemic, such as Egypt, Iraq, and Sudan34.
Bladder cancer in these nations differs greatly from bladder cancer found in Western
countries. Schistosomiasis haematobium infection is well known to be associated with
etiology of bladder cancer due irritation and inflammation, chronic bacterial infection,
and high N-nitrosamines levels caused by nitrate-reducing bacteria34-37. These factors
produce DNA mutations and physical damage to the urothelium and mucosa that result in
consequential high-grade SCCs that tend to be more aggressive than TCCs38.
9
Bladder Cancer: genetic factors
Although environmental factors, particularly tobacco smoke, are associated with
bladder cancer, the magnitude of risk can vary greatly among individuals of equal
exposure based on certain genetic factors39. Specifically, genetic polymorphisms
involved in carcinogenetic detoxification are known to significantly alter the impact of
bladder cancer associated risk factors. Recently, genome-wide association studies
(GWAS) have led to the discovery of multiple genetic variants whose functions are not
well known, yet are significantly associated with risk of bladder cancer40-43.
Glutathione s-transferases (GSTs) are a family of enzymes that catalyze the
addition of glutathione to harmful chemicals within the body in order to detoxify these
compounds. GST enzyme deletions are common in the general population, and a great
deal of work has been done to examine the effect of GST deletion on bladder cancer risk.
Multiple studies have shown that GST deletion is associated with increased prevalence of
bladder cancer when compared to individuals with non-null GSTs39, 44, 45. Evidence
exists to suggest that this relationship is due to the role that GSTs play in detoxification
of DNA-damaging compounds associated with bladder cancer45.
N-acetyltransferase 2 (NAT2) is an enzyme that is responsible for the
detoxification of arylamines, the most important class of carcinogens that are found in
tobacco smoke46, 47. Individuals that are classified as NAT2 slow acetylators have been
found to be at increased risk for bladder cancer 48. This association is highly significant
among smokers49-51. There also evidence to suggest that the effect of NAT2 slow
10
acteylation on risk of bladder cancer is even stronger among individuals with null
GSTs44, 45.
Arylamines found in cigarette smoke require metabolic activation in order to exert
their carcinogenic effects. Cytochrome P4501A2 is a key phase I enzyme that is known
to activate arylamines from tobacco smoke. High CYP1A2 phenotype, in which there is
an increased activity of CYP1A2, is associated with increased risk of various cancers,
especially among smokers52. This relationship is known to exist with bladder cancer,
particularly among smokers, as well as those exposed to environmental tobacco smoke53.
Polymorphisms of CYP1A2 known to alter CYP1A2 activity have recently been shown
to modify risk of bladder cancer among smokers54.
Although several genetic variations are known to alter bladder cancer risk, many
single nucleotide polymorphisms (SNPs) have recently been discovered using genomewide associations studies (GWAS)40-43. One specific single nucleotide polymorphism
(SNP), rs2294008 (C>T), has been shown to increase risk of bladder cancer in various
studies study population55-57. This particular SNP is located in exon 1 of the prostate
stem cell antigen (PSCA) gene. The precise function of this gene and its association with
SNP variation, as well as mechanisms driving excess bladder cancer risk remain
unknown.
Obesity: definition and epidemiology
Another condition of interest in relation to DNA methylation in this thesis was
obesity, as defined by adult Body Mass Index (BMI). BMI is calculated according to a
11
person’s height and weight and is considered to be an accurate measure of body fat.
According to standard BMI measurement, a BMI below 18.5 is considered underweight,
between 18.5-24.9 is normal, 25-29.9 is overweight, and over 30.0 is classified as obese.
These BMI cutoffs may vary slightly for different ethnic populations to account for
different body structures. Childhood BMI is determined by BMI-for-age growth charts
that are based on specific populations.
Globally, there are more than 1 billion adults that are overweight, and at least 300
million of these individuals can be classified as clinically obese58. Childhood obesity
has grown to epidemic proportions in many parts of the world and continues to grow at a
dangerously rapid pace58. It has been estimated that 17.6 million children under five
years old are overweight worldwide58. This is particularly worrisome because obese
children are more likely to become obese adults, thus adding to the already high rates of
adult obesity59. Although many factors contribute to obesity, overconsumption of more
energy-dense, nutrient-poor foods, combined with reduced physical output have lead to
high incidence of obesity60.
Obesity is not equally distributed globally. Obesity tends to be prevalent in more
developed nations. For example, The United States currently has one of the highest rates
of obesity in the world, and both adult and childhood obesity rates continue to rise at
alarming rates61, 62. According to the Centers for Disease Control and Prevention (CDC),
as of 2006 33.3% of men, 35.3% of women, and 16.3% of children in the United States
were classified as being obese63. Today, 65% of all people age 20 and older are
overweight or obese64. It has been predicted that obesity will cause the current
generation of American children to be the first to live shorter lives than their parents63.
12
Obesity: risk factors and health outcomes
The United States obesity epidemic is reflective of most developed, and many
developing nations. As countries become more developed there is generally an
associated disease transition that takes place. These countries commonly shift from high
infectious disease burdens to high chronic disease burdens, including obesity and its
associated maladies65. These high rates of obesity are mostly attributed to modernization
and its associated nutrition transition, which occurs when developing nations begin
consuming more calorie-rich foods and expending less energy66. This transition occurs
due to various factors associated with development. Generally, as incomes rise and
technologies become available, there is consumption of more processed food that tends to
be more calorie-dense than traditional foods, and rates of physical activity decrease65, 66.
As obesity rates increase in developing nations, so do rates of certain chronic
diseases, specifically cardiovascular disease and diabetes60. These conditions lead to
lowered life expectancies and greater rates of morbidity, including both physical and
mental disability67. Obesity and obesity-related conditions are not only burdensome on
an individual level, but can also be detrimental to developing communities as a whole.
These obese individuals are a financial burden to developing nations. Obese
patients strain healthcare systems that are often weak and poorly funded in developing
nations68. This is because obese individuals require long-term care for chronic conditions
that result from being obese, and these conditions are new to many developing countries,
so they lack the infrastructure and skills to handle such conditions68.
High rates of
disability also lead to decreased productivity, which can delay development, because
13
obese individuals with physical and mental disabilities may be prevented them from
work, and must be supported by others69. This is a heavy burden that can be very
detrimental in developing societies that rely on productivity for development.
Overall, obesity and obesity-related disease are serious threats to developing
nations. As these nations grow economically and living conditions and life expectancies
improve, obesity can greatly impede development. Obesity creates new, chronic health
conditions that disable individuals and result in premature death. These conditions lead
to increased healthcare expenditure, as well as decreased productivity.
Cardiovascular disease
Obesity is commonly associated with cardiovascular disease. Cardiovascular
disease (CVD) is a class of conditions that involve the cardiovascular system in which
narrowing of blood vessels occurs by atherosclerosis. CVD is the leading cause of death
worldwide, causing approximately 16.7 deaths annually, primarily due to heart attacks
and stroke70. It is estimated that about 128 million people globally suffer from
cardiovascular disease71. Well known risk factors for developing CVD include older age,
elevated blood cholesterol levels, obesity, hypertension, and smoking72.
Diabetes
Individuals suffering from cardiovascular disease and/or obesity are also likely to
suffer from type 2 diabetes. Type 2 diabetes is a condition defined by abnormal glucose
14
homeostasis that occurs when the body cannot properly respond to insulin which is
responsible for glucose metabolism. This causes levels of glucose to build in the blood
stream, often triggering the body to produce excess insulin. Risk factors for developing
type 2 diabetes include older age, obesity, elevated blood cholesterol, and hypertension73.
Chronically elevated glucose levels from type 2 diabetes frequently leads to
microvascular complications including nephropathy, retinopathy, neuropathy, and small
vessel vasculopathy73. The global prevalence of type 2 diabetes is estimated to be about
220 million, and is a significant cause of premature mortality74. In 2004, the WHO
estimated diabetes-related deaths among men to be 508,000 (1.6% of all deaths), and
633,000 among women (2.3% of all deaths)74.
American Samoa and Samoa: The history of the “thrifty gene”
The Samoan islands have some of the highest rates of obesity, cardiovascular
disease, and diabetes in the world, making Samoans an ideal population for our
investigations. The Samoan islands are located in the South Pacific, and were originally
settled by a small number of founders of Polynesian decent who were thought to have
survived a difficult voyage to the Samoan islands and to have endured very cold
temperatures75. Once settled, food shortages would have been likely due to natural
disaster. Ultimately, survivors would have been those with the ability to store large
amounts of body fat.
The concept of a heritable pre-disposition to obesity is based upon the theory of
“thrifty genes”, which are thought to be an evolutionary response to food scarcity,
15
enabling humans to more effectively store and expend energy76-78. In current times where
food scarcity is rare in the developed world, individuals with these “thrifty genes” are
hypothesized to be more likely to develop obese phenotypes79.
American Samoa and Samoa: Obesity
Prevalence of obesity is high among people of the Samoan islands; in fact they
even have a higher range of BMI classifications80. In addition to the theory of “thrify
genes”, these developing island nations are experiencing dietary and physical activity
shifts, which have ultimately resulted in a chronic positive energy balance81-83. These
two factors combined have led to obesity rates of epidemic proportion. American Samoa
is the more developed of the Samoas with approximately 71% of women and 59% of men
defined as being obese, whereas in Samoa 29% of men and 53% of women are obese
based on data collected between 2002-200375.
American Samoa and Samoa: Obesity-related disease
These high rates of obesity have greatly contributed to rapid rises in obesityrelated diseases such as cardiovascular disease (CVD) and diabetes84. Rates of these
obesity-related illnesses are higher in more-developed American Samoa, than in lessdeveloped Samoa, yet rates are increasing in both nations75. From the 2002-2003 study
period that was previously mentioned, 46% of American Samoan men and 31% of
American Samoan women were reported as being hypertensive, whereas 30% of Samoan
16
men and 29% of Samoan women were hypertensive75. In this same study, 22% of
American Samoan men and 18% of American Samoan women were reported as having
type 2 diabetes, in comparison to the 9% of Samoan men and 13% of Samoan women75.
Cardiovascular and metabolic diseases threaten the health of adults, as well as children in
both Samoan nations, and are predicted to cause a decline in health expectancies among
Samoans75.
Epigenetics
This thesis aimed to investigate epigenetic alterations in bladder cancer and in
association with metabolic and cardiovascular risk factors. Epigenetic alterations are
DNA modifications that do not involve changes in the DNA sequence, but can still alter
genomic regulation85. The three major forms of epigenetic regulation include DNA
methylation, histone modifications, and small RNAs. DNA methylation and histone
modification occur at the level of transcription by altering chromatin conformation.
Compact chromatin cannot allow for binding of transcriptional factors and therefore is
transcriptionally inactive, whereas relaxed or open chromatin allows for transcriptional
factor binding and concordant transcription86, 87. Small regulatory RNAs act at the level
of translation, and interact with proteins to inhibit that translation of protein-coding
mRNA88.
These epigenetic processes are vital for individual gene regulation, as well as
overall genome maintenance and stability. When epigenetic processes become
dysregulated, they can greatly contribute to the etiology of various human diseases. Both
17
environmental and genetic factors have been found to alter epigenetic mechanisms to
contribute to disease susceptibility89-91.
DNA methylation
An essential mechanism of epigenetic regulation is through the process of DNA
methylation. DNA methylation-based gene silencing occurs through catalytic transfer of
methyl groups to the 5-carbon of cytosine in a CpG dinucleotide92. The addition of
methyl groups to cytosine is catalyzed by methyltransferase enzymes that recruit
methylcytosine binding proteins (MBPs)92, 93. These MBPs form complexes with histone
deacetylases (HDACs) resulting in deacetylation of local histones, causing nucleosomes
to become highly compacted, therefore making them inaccessible to transcriptional
activation93, 94. Therefore, when DNA becomes heavily methylated, or
“hypermethylated”, transcription becomes inactive and gene silencing occurs.
Conversely, when there is little methylation, DNA becomes “hypomethylated”, allowing
transcription to occur, and genes become active.
DNA methylation can be easily measured, and is therefore a valuable tool in
studying epigenetics. Measuring DNA methylation involves sodium bisulfite conversion
of DNA. Sodium bisulfite is a chemical which converts deaminated unmethylated
cytosines to uracil, and allowing methylated cytosines remain as cytosines95. This
process permits straight-forward assessment of DNA methylation by distinguishing
between a C or T residue by any genotyping platform.
18
DNA repeat sequence methylation
DNA methylation of repeat sequences throughout the genome is an important tool
in epigenetic research. It is estimated that almost half of DNA within the human genome
is made up of repetitive sequences such as transposons, retrotransposons, and endogenous
retroviruses96. These sequences are generally non-transcribed due to their constant
heterochromatin state maintained by hypermethylation. Examination of methylation at
these repeat sequences has become an important tool in disease research, and is often
referred to as “global” methylation.
LINE-1 methylation
There are several types of repeat sequences in the human genome that are
measured in research. Long Interspersed Nuclear Elements (LINE-1) are
restrotransposon sequences that make up approximately 17% of the human genome96.
Measuring methylation at LINE-1 sequences in lymphocyte-derived DNA is a wellrecognized method for examining genome-wide, or “global” methylation97-99.
DNA methylation: Cancer
DNA methylation has been found to play an important role in cancer etiology.
Overall levels of DNA methylation within non-coding repeat sequences (such as LINE-1)
throughout the genome are an important tool in disease research, and have been primarily
used in cancer research100. DNA repeat sequence hypomethylation is frequently observed
19
in cancerous tissue, and can be used in many cases as a biomarker of cancer100, 101. DNA
hypomethylation has been proposed as a mechanism for cancer development due to the
potential for gene overexpression (which occurs when genes become hypomethylated),
and activation of transposable elements that result in genetic mutations100, 102. There is
also evidence suggesting that carcinogen exposure may be correlated with repeat
sequence hypomethylation103. Additionally, many dietary factors are thought to play
essential roles in DNA methylation85.
DNA methylation takes place at cytosines preceding guanines (CpGs) which
occur at an unexpectedly low rate throughout the genome, and tend to be enriched at gene
promoter regions in order for transcriptional control by DNA methylation to happen94.
Although patterns of overall DNA global hypomethylation are generally associated with
cancer, certain CpG islands located in promoter regions of specific genes are often
dysregulated through promoter hypermethylation of tumor suppressor genes85, 92. This
mechanism is thought to play a significant role in tumor formation according to
Knudson’s two hit hypothesis104. CpG methylation is known to influenced by
environmental as well as genetic factors although these mechanisms are presently
incompletely understood105-108.
DNA methylation: Bladder Cancer
Bladder carcinomas have long been known to exhibit genetic alterations, and
recently, research has begun to explore epigenetic alterations associated with bladder
cancer. DNA methylation alterations at both the repeat sequence and CpG-specific level
20
have been found to be important in the development, progression, and treatment of
bladder cancer. Additionally, risk factors associated with bladder cancer have been found
to alter DNA methylation patterns.
DNA hypomethylation of repeat regions in peripheral blood, including
methylation at LINE-1, has been found to be associated with increased risk of bladder
cancer in multiple studies, including populations from Spain and New Hampshire99, 109.
This association was found to be most profound in never smokers109.
Alterations of DNA methylation at non-repeat CpGs are also known to occur in
association with bladder cancer. Using genome-wide DNA methylation profiling, casecontrol specific patterns of CpG methylation in peripheral blood have been established
110
. When examining tumor-specific DNA, CpG profiles were also found to be
associated with invasiveness of disease111. Methylation of specific gene promoters is also
associated with bladder cancer, as well as with invasiveness and aggressiveness of the
disease105, 112, 113.
Environmental exposures such as tobacco smoke and arsenic are correlated with
promoter hypermethylation of tumor suppressor genes in bladder cancer patients114.
Additionally, exposure to arsenic has been associated with lower levels of LINE-1
methylation99. Genetic polymorphisms associated with risk of bladder cancer have also
been found to alter levels of promoter methylation in bladder cancer. 115. In addition,
polymorphisms in the one-carbon metabolism pathway have been shown to alter bladder
cancer risk116.
21
DNA methylation: Obesity
DNA methylation has been explored in cancer more than any other disease, yet
evidence exists to suggest that DNA methylation alterations occur in cardiovascular and
metabolic diseases, and may be influenced by risk factors for these conditions, such as
obesity. Obesity is caused from a variety of factors such as diet, physical activity,
genetics, and hormones117. Certain genetic mutations and polymorphisms have been
associated with obesity, yet epigenetic mechanisms are not yet well understood118. It is
known that dietary factors can influence gene expression through DNA methylation, and
is therefore likely that obesity can alter DNA methylation, which could potentially help to
explain how obesity leads to certain chronic diseases119.
One reason that it has been proposed that diet and obesity can alter DNA
methylation is based on the fact that both overweight and underweight pregnant women
put their children at certain risks for obesity and obesity-related disease120. This
association is thought to be due to epigenetic control of fetal gene expression121. A recent
study found that maternal nutrient restriction is associated with altered fetal DNA
methylation in baboons122. A similar study found that maternal nutrient supplementation
can alter fetal DNA methylation levels in mice123. These studies taken together suggest
that diet can influence not only obesity, but also levels of DNA methylation, especially
during fetal programming. These studies were both conducted in animal models,
therefore human epidemiological studies are necessary to fully determine the association
between maternal diet, obesity, and fetal methylation programming.
22
It has also been suggested that obesity can alter methylation due to the
physiological micro-environmental conditions that obesity creates. Obesity is associated
with increased levels of inflammation, oxidative stress, and hypoxia, which have all been
found to be associated with altered levels of DNA methylation124-126. Very little research
has been conducted to examine the effects of obesity microenvironments on DNA
methylation, however one study found that DNA methylation of inflammation-related
genes was altered in obese mice127. This evidence suggests that chronic obesity has the
potential to alter DNA methylation, though further studies are necessary in order to fully
understand the physiological mechanisms that allow obesity microenvironments to alter
DNA methylation.
DNA methylation: Cardiovascular disease
Recently, research has begun to focus on understanding the role of epigenetics in
cardiovascular disease. Onset of cardiovascular disease is associated with various
environmental and genetic risk factors. DNA methylation has been suggested as playing
an important role in cardiovascular disease128, due to the fact that CVD patients are
known to have altered levels of homocysteine129, a key regulator of DNA methylation
therefore suggesting a relationship between these two processes100.
Global hypomethylation has recently been examined in cardiovascular disease
case-control studies. Two different studies that examined global DNA methylation by
cytosine extension128 found varied results. Sharma et al. reported higher levels of global
methylation in patients with coronary artery disease130, and that DNA methylation levels
23
were positively correlated with plasma homocysteine levels. Conversely, Castro et al.
reported lowered level of global methylation in vascular disease patients, however, they
also found DNA methylation levels to be positively correlated with homocysteine
levels131. It should be noted that neither of these studies examined cardiovascular risk
factors in association with global DNA methylation.
More recent work examining repeat sequence methylation has also yielded
conflicting results. A study conducted by Kim et al. reported higher levels of repeat
methylation at the ALU and satellite 2 (AS) elements in individuals with cardiovascular
disease, and those at risk for developing CVD among men132. Another study conducted
by Baccarelli et al. found that lower level of LINE-1 were associated prevalent ischemic
heart disease and stroke, and was predictive of incident cases of ischemic heart disease
and stroke among men133. An important difference between these two studies is the
repeat sequence used, and could potentially account for the dissimilar trends that were
observed.
Studies examining risk factors associated with cardiovascular disease have found
that there may be a relationship between hypertension and repeat DNA methylation, as
well as promoter methylation. Smolarek et al. examined 5-methylcytosine content in
blood-derived DNA, and found lower levels in hypertensive patients when compared to
healthy controls134. Another study conducted by Friso et al. found that elevated 11 betahydroxysteroid dehydrogenase 2 promoter methylation in blood-derived DNA was
associated with hypertension135. These studies in addition to the previous work
mentioned support the role of DNA methylation in cardiovascular disease, though more
24
work is necessary, particularly in understanding mechanisms of epigenetic regulation that
may explain these reported differences.
DNA methylation: Diabetes
Another disease in which epigenetics may critical is type 2 diabetes. Type 2
diabetes is another condition in which obesity is a major risk factor, although genetics
also plays an important role in this disease. Many genes have been found to be
dysregulated in diabetes, contributing to the etiology of type 2 diabetes136. In addition,
prenatal maternal glucose levels and maternal obesity have been shown to alter risk of
developing type 2 diabetes later in life, suggesting that there is cellular memory involved
in insulin resistance137.
There is also preliminary work that suggests that promoter methylation is
important in type 2 diabetes. A recent study found that methylation patterns of specific
insulin-related genes are controlled epigenetically through DNA methylation in both mice
and humans 138. Another study demonstrated genotype-epigenotype interactions in the
context of type 2 diabetes by demonstrating that diabetes-specific risk alleles were
associated with altered DNA methylation on the FTO type 2 diabetes and obesity
susceptibility locus 106. This evidence taken together motivates further work in order to
fully understand the epigenetic alterations involved in type 2 diabetes.
25
Conclusion
Bladder cancer, cardiovascular, and metabolic diseases are globally burdensome
conditions in which epigenetic alterations may play a vital role. It is evident that more
research is needed in order to understand the relationships between DNA methylation and
disease. Of particular interest in the affect of environmental and genetic disease risk
factors on DNA methylation levels. This thesis aimed to epidemiologically explore these
relationships using DNA methylation data collected utilizing quantitative laboratory
techniques and extensive risk factor field data from diverse populations across the world.
26
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Chapter 2
LINE-1 hypomethylation is associated with bladder cancer risk among non-smoking
Chinese
Haley L. Cash, Li Tao, Jian-Min Yuan, Carmen J. Marsit, E. Andres Houseman, YongBing Xiang, Yu-Tang Gao, Heather H. Nelson, Karl T. Kelsey
International Journal of Cancer 2011
45
LINE-1 hypomethylation is associated with bladder cancer risk among non-smoking
Chinese
Haley L. Cash* 1,2, Li Tao*3, Jian-Min Yuan3, Carmen J. Marsit2, E. Andres
Houseman1,2, Yong-Bing Xiang4, Yu-Tang Gao4, Heather H. Nelson3, and Karl T.
Kelsey1,2
Departments of 1Community Health Center for Environmental Health and Technology
and 2Pathology and Laboratory Medicine, Brown University, Providence, RI; 3Masonic
Cancer Center, University of Minnesota, Minneapolis, Minnesota. 4 Department of
Epidemiology, Shanghai Cancer Institute, Shanghai, People’s Republic of China
*these authors contributed equally to this work
46
Abstract
Reduced levels of global DNA methylation, assessed in peripheral blood, have
been associated with bladder cancer risk in European and American populations. Similar
data are lacking in Asian populations where genetic differences, lifestyle factors, and
different environmental exposures may affect DNA methylation and its risk relationship
with bladder cancer. The association between global DNA methylation measured at long
interspersed nuclear element (LINE-1) repeat regions through bisulfite pyrosequencing in
lymphocyte DNA and bladder cancer risk was examined in a case-control study of 510
bladder cancer patients and 528 healthy control subjects in Shanghai, China. In an initial
analysis restricted to control subjects, LINE-1 methylation was elevated among men,
those who frequently consumed cruciferous vegetables, and those with a null genotype
for either glutathione S-transferase M1 (GSTM1) or GSTT1. In contrast, reduced LINE-1
methylation was found in current smokers with a high cytochrome P450 1A2 (CYP1A2)
phenotype index. In a case-control analysis, there was no significant association of
LINE-1 methylation with case status, although reduced LINE-1 methylation was
associated with increased risk of bladder cancer among never smokers (P for trend =
0.03); analysis by tertile revealed odds ratios (ORs) of 1.91 (lowest tertile; 95% CI =
1.17-3.13) and 1.34 (middle tertile; 95% CI = 0.79-2.28) when compared to the highest
tertile. This association was strongest among nonsmokers null for either the GSTM1 or
GSTT1 genotype (P for trend = 0.006). Further research is needed to understand the
relationships between methyl group availability and LINE-1 methylation in relation to
bladder cancer risk.
47
Introduction
Bladder cancer is the ninth most common form of cancer in the world, with men
having three to four times the risk of women1. The major known risk factors include
exposure to tobacco smoke, aromatic hydrocarbons, water chlorination byproducts,
inorganic arsenic, and (in the case of squamous cell bladder cancer) Schistosoma
hematobium infection1,2. Genetic variants in enzymes that metabolize bladder
carcinogens such as N-acetlytransferase (NAT), cytochrome P450 (CYP) 1A2, and
glutathione S-transferases (GSTM1, GSTT1) have been reported to modify the association
of carcinogen exposure with bladder cancer risk1,3,4. Specifically, increased risk of
bladder cancer is associated with GSTM1 and GSTT1 null genotypes and elevated
CYP1A2 activity 2,3,5,6.
Bladder carcinomas exhibit somatic genetic and epigenetic alterations. Genetic
changes are common and include point mutations as well as gene amplification and
deletion7. Epigenetic alterations are heritable DNA modifications that do not involve
changes in the DNA sequence. Epigenetic changes are associated with alterations in gene
expression and are important in maintaining genomic stability8,9,10 . DNA methylationassociated gene silencing occurs in tandem with modifications of chromatin, involving
specifically the catalytic transfer of methyl groups to the 5-carbon of cytosine in a CpG
dinucleotide9. Dietary folate and one-carbon compounds are an important source for
methyl groups that are necessary for DNA methylation11,12.
It has long been known that global DNA hypomethylation, reflected in reduced
levels of methylation in repeat regions, occurs in target tissues undergoing carcinogenic
48
de-differentiation and can be used as a biomarker of malignant disease13,14. DNA
hypomethylation and its coordinate epigenetic changes have been proposed as an integral
component of cancer development, contributing to both the loss of genomic stability in
regions that are generally heavily methylated, as well as being associated with alterations
in gene expression (which can occur when gene promoter regions become abnormally
hypomethylated). Finally, activation of transposable elements can occur upon reduced
DNA methylation, resulting in insertional genetic mutations 9,10,13,15. In addition, global
DNA methylation levels, assessed in repeat regions from lymphocyte-derived DNA, have
been associated with risk of malignant solid tumors13,16, including bladder cancer in
Spanish and American populations 17,18. Previous work suggests that the level of global
DNA methylation in lymphocytes may be a surrogate for systemic global DNA
methylation19,20. Here, we have investigated the relationship between LINE-1 DNA
methylation, a measure of global methylation, and risk of bladder cancer in a Chinese
population in Shanghai, China. In addition, we examined the association between LINE1 methylation and potential risk factors for bladder cancer including tobacco smoking,
genetic polymorphisms, and certain dietary exposures, as well as their modifying effect
on the LINE-1-bladder cancer risk estimate.
Materials and Methods
Subjects
The present study included participants of the Shanghai Bladder Cancer Study.
The study design has been described in detail elsewhere21. Briefly, bladder cancer cases
were Han Chinese aged 25-74 at the time of diagnosis who were permanent residents of
49
the city of Shanghai, China. All cases diagnosed between 1st July 1995 and 30th June
1998 who were registered in the Shanghai Cancer Registry were eligible for the Shanghai
Bladder Cancer Study. Among 708 bladder cancer cases identified, 56 were either
deceased or too ill to be interviewed, 29 refused to participate in the study, and 42 were
unable to be located. The remaining 581 (82%) eligible patients were interviewed
between July 1996 and June 1999. The diagnosis of bladder cancer for 531 (91%)
patients was made based on histopathological evidence whereas the remaining 50 (9%)
patients’ diagnoses were based on positive computerized axial tomography scan and/or
ultrasonograph with consistent clinical history.
Control subjects were randomly selected from the urban population of Shanghai
through the Residents Registry of the Shanghai Municipal Government. The control
subjects were chosen to match the frequency distribution by sex and 5-year age groups of
bladder cancer patients as ascertained by the Shanghai Cancer Registry during 19901994. Among the 750 potential control subjects chosen, 74 subjects could not be located
due to change of home addresses. Seventy-two subjects refused to participate in the
study. The remaining 604 (81%) subjects were interviewed during the same time period
as the cases. All subjects provided informed consent following procedures approved by
the appropriate institutional review boards.
Data Collection
An in-person interview with each eligible study subject was conducted for
approximately one hour by a trained interviewer using a structured questionnaire in the
subject’s home. The questionnaire gathered information on subject demographics,
50
history of tobacco use, secondhand smoke (for lifelong nonsmokers only), history of
beverage consumption (coffee, tea, soda, alcohol, and water), use of hormones (for
women only), medical history, dietary history, and occupational history, two years prior
to the diagnosis of bladder cancer for case patients and two years prior to the date of
interview for control subjects (reference date). For lifelong nonsmokers, the questionnaire
further asked for the smoking history of their mother, father, spouse(s), and other
relatives who ever lived in the same household with the subject, as well as the smoking
habits of coworkers in an indoor environment. For each subject, a composite index
denoting total environmental tobacco smoke (ETS) exposure based on the 5 sources of
ETS over subject’s lifetime was constructed and described in detail previously21.
All subjects were asked to donate blood and urine samples at the end of the inperson interview. A total of 513 (88%) of cases and 534 (88%) of controls provided a
blood sample. Blood samples were collected in heparinized (10 ml) and non-heparinized
(4 ml) tubes. Heparinized samples were fractioned into plasma, buffy coat, and
erythrocytes on the day of the sample collection, and were stored at -80oC. Forty-six case
patients and 61 control subjects refused to donate overnight urine samples. Prior to the
collection of an overnight urine sample, each consenting subject was given two packets
of Nestle instant coffee or two cans of Coca-Cola Classic drink (about 70 mg of caffeine)
to be consumed between 3 and 6 pm. The subject then collected an overnight urine
sample (ending with the first morning void) into a plastic jar that was picked up by the
same interviewer in the following morning. The urine samples were processed, acidified
(400 mg of ascorbic acid per 20 mg of urine), and stored at –80°C on the same day of
urine pickup until analysis
51
Laboratory measurements
Genotyping DNA was extracted from peripheral blood buffy coats using QIAmp
DNA mini kit according to manufacturer’s protocol (Qiagen, Valencia, CA). A standard,
multiplex polymerase chain reaction protocol was used to analyze for the presence or
absence of the glutathione S-transferase M1 (GSTM1) and GSTT1 genes, as described in
detail previously3. For subjects with available blood samples, we obtained GSTM1
genotype on 504 cases and 529 controls, and GSTT1 genotype on 503 cases and 528
controls.
Phenotyping Urinary caffeine metabolites, namely 5-acetylamino-6-amino-3methyluracil (AAMU), 1-methylxanthin (MX), 1-methyluric acid (MU) and 1,7dimethylxanthin (17X), were measured by the following methods. Levels of AAMU in
urine were determined by a modified procedure that was previously described22, using
high-performance size exclusion chromatography. Quantification of MX, MU, and 17X
in urine was performed according to a modified procedure23. These assays were
performed with appropriate internal standards. Calibration curves were created during
the analysis and used for calculation of concentrations of all analytes. Quality control
urine samples spiked with a low, intermediate, and high range of the calibration
concentrations were analyzed intermittently during the sample runs. The CYP1A2
phenotype scores were determined based on ratios of urinary caffeine metabolites, i.e.
(AAMU + MX + MU)/17X. Higher ratio values of the CYP1A2 phenotype score reflect
higher CYP1A2 activities. We used the median value of the CYP1A2 phenotype score in
all control subjects to classify subjects into low (≤5.53) or high (>5.53) CYP1A2
52
phenotypic activity status. Of all urine samples, we were unable to detect caffeine
metabolites in 45 samples (13 from case patients and 32 from control subjects).
DNA LINE-1 Methylation One µg of peripheral lymphocyte DNA was sodium
bisulfite modified using the EZ DNA Methylation Kit according to manufacturer’s
protocol (Zymo Research, Orange, CA). LINE-1 region methylation extent was
quantified using quantitative bisulfite Pyrosequencing24 as previously described25, which
examines the cytosine methylation status at 4 CpG sites in the LINE-1 region. All PCR
reactions were performed using Qiagen Hot Star Taq polymerase, and each batch
included a no template control, unmodified DNA control, and a standardized methylation
control. Each sample was run in triplicate, and each pyrosequencing reaction used 20µl
of PCR product, and was run according to instrument/manufacturer’s protocols on a
PyroMark™MD System (Qiagen). The standard error of the averaged individual repeats
was found to be the same as the standard error for each replicate, so the average measure
(percentage) of LINE-1 methylation across the 4 CpG sites for each replicate was used to
calculate an average of the replicates for each sample. The measure of methyl cytosine at
position is relative to the total cytosine and thymine at that position in the amplified
repeats. The assays for LINE-1 failed on 9 samples (3 cases and 6 controls).
Statistical Methods
For the present analysis, we included 510 (88% of eligible) case patients and 528
(87% of eligible) control subjects with available LINE-1 measurement. In the analyses
stratified by CYP1A2 phenotypic status, we excluded an additional 13 cases and 32
controls with unknown CYP1A2 phenotype scores. In the analyses stratified by GSTM1
53
and GSTT1 genotypes, we excluded 9 cases and 4 controls with unknown GSTM1 and/or
GSTT1 genotypes.
Chi-square test was used to examine the differences in the distributions of
categorical variables and t-test for the differences in means of continuous variables
between case patients and control subjects. The analysis of covariance (ANCOVA)
method was applied to evaluate the effect of smoking, dietary, and other environmental
factors and genetic determinants on LINE-1 methylation scores among control subjects
only, separately for men and women.
Unconditional logistic regression models were used to examine the association
between LINE-1 methylation scores and risk of bladder cancer. Study subjects were
classified into tertiles based on the distributions of LINE-1 scores among all control
subjects only. The strength of the association between exposure and bladder cancer risk
was measured by odds ratios (ORs) and their corresponding 95% confidence intervals
(CIs) and P values. The association between the LINE-1 scores and bladder cancer risk
was examined in total subjects as well as subgroups defined by gender and cigarette
smoking status. Additional analyses for the association between LINE-1 score and
bladder cancer risk were conducted in subjects stratified by intake frequency of
cruciferous vegetables dichotomized to represent the lowest 10% of consumption (<4 or
≥4 times per week), the joint genotypes of GSTM1 and GSTT1, and CYP1A2 phenotype
status. We did not show the null results from the latter subgroup analyses in tables.
Gender, age at reference date (years) and family history of cancer (no, yes) were included
in all logistic regression models. The composite index of ETS exposure was added to the
covariate list when the analysis was restricted to nonsmokers only.
54
Statistical analyses were performed using SAS version 9.1 (SAS Institute, Cary,
NC) statistical software package. All P values are two sided. P values less than 0.05
were considered statistically significant.
Results
Men accounted for 78% of cases and 77% of controls. The mean age (±standard
deviation) of case patients at diagnosis of bladder cancer was 62.18 (±9.9) years while the
mean age of control subjects at interview was 60.80 (±10.1) years (P=0.03). As
expected, bladder cancer patients were more likely to smoke cigarettes than control
subjects (Table 1). Case patients also were more likely to have an elevated level of
CYP1A2 activity and a null genotype of both GSTM1 and GSTT1 (Table 1).
The overall range of DNA LINE-1 methylation was 73.3% to 93.3%, with a mean
of 82.1% for men and 81.5% for women in the control subjects. The difference between
the two sexes was statistically significant (P= 0.004), and as a result, further analyses
were stratified by gender or gender was included in the models (Table 2). Among male
controls, high cruciferous vegetable intake (≥4 times/week) was associated with
significantly elevated LINE-1 methylation levels (P = 0.002). Cigarette smoking was not
associated with levels of LINE-1 methylation in this population (data not shown). In
stratified analysis however, smokers with higher CYP1A2 phenotype scores (above
median value of 5.53) had significantly reduced levels of LINE-1 methylation compared
to smokers with lower CYP1A2 phenotype scores (P = 0.001 for both men and women
combined with adjustment for gender). There was no statistically significant different
difference in LINE-1 methylation between higher and lower CYP1A2 phenotype scores
55
among nonsmokers at the time of urine sample collection. Men with GSTM1 null and/or
GSTT1 null genotype had elevated LINE-1 methylation levels compared to men with nonnull genotype of both GSTM1 and GSTT1 (P = 0.005). We did not observe a statistically
significant relationship between LINE-1 methylation and age, body mass index, level of
education, smoking intensity and duration, consumption of alcoholic beverage, tea and
coffee, or N-acetyltransferase 2 acetylation status (data not shown).
The mean percentage LINE-1 methylation values (±standard deviation) were
comparable in cases (81.86±1.82) and controls (81.96±1.89) (Table 1; P = 0.38).
Compared with the highest tertile of LINE-1, individuals in the lowest tertile of LINE-1
methylation had a statistically non-significant 28% increased risk of bladder cancer
(Table 3). This inverse association between LINE-1 and bladder cancer risk was stronger
in women than in men although neither association was significant. In a stratified
analysis by smoking status, a statistically significant inverse association between LINE-1
methylation and bladder cancer risk was seen among nonsmokers (P for trend = 0.03).
Compared with the highest tertile of LINE-1 methylation, the OR for bladder cancer was
1.91 (95% CI = 1.17-3.13) for the lowest tertile of LINE-1 methylation, and 1.34 (95% CI
= 0.79-2.28) for the middle tertile of LINE-1 methylation after controlling for age,
gender, family history of cancer, and ETS. There was no statistically significant
association between LINE-1 methylation and bladder cancer risk among current or former
smokers (Table 3). Further adjustment for CYP1A2 phenotype score (high versus low),
combined genotypes of GSTM1 and GSTT1 (null of either one gene versus non-null of
both genes), and intake frequency of cruciferous vegetables (≥4 versus <4 times per
week) simultaneously did not materially alter the association between LINE-1
56
methylation and bladder cancer risk in all subjects as well as in subgroups stratified by
gender or smoking status (data not shown).
We next examined the LINE-1-bladder cancer association in high risk groups. In
stratified analyses, we did not find any statistically significant associations between
LINE-1 methylation and bladder cancer risk in subgroups of individuals regardless of
intake frequency of cruciferous vegetables and CYP1A2 phenotype level (data not
shown). There was a statistically borderline significant inverse association between
LINE-1 value and bladder cancer risk among individuals with either the GSTM1 null or
GSTT1 null genotype (P for trend = 0.054). This inverse association became stronger in
lifelong nonsmokers. ORs (95% CIs) of bladder cancer for the middle and lowest tertile
of LINE-1 methylation were 1.26 (0.69-2.29) and 2.36 (1.34-4.14) after adjustment for
multiple potential confounders, respectively, compared with the highest tertile of LINE-1
methylation (P for trend = 0.006) among lifelong nonsmokers with null genotype of
either GSTM1 or GSTT1 (Table 4). The interaction between LINE-1 methylation and
GSTM1/GSTT1genotypes on bladder cancer risk was statistically significant among total
subjects (P for interaction= 0.03) and borderline significant among lifelong nonsmokers
(P for interaction= 0.07).
Discussion
The present study demonstrated a statistically significant, inverse relationship
between LINE-1 methylation and bladder cancer risk among lifelong nonsmokers in a
Chinese population. This is consistent with Moore et al., although they employed a
different measure of global methylation17. However, in our data there was a lack of
57
association between DNA methylation at LINE-1 and bladder cancer risk in former or
current smokers, which differs somewhat from what was previously observed in
Caucasian populations17,18. GSTM1 and GSTT1 genotype modify this inverse
relationship among lifelong nonsmokers (P for interaction= 0.07). The reasons for these
differences in LINE-1 methylation level-bladder cancer risk associations between the
Chinese and Caucasian populations are unknown, but may be due to the different
lifestyle, environmental exposures, and/or the different genetic backgrounds between the
two populations.
The LINE-1 DNA methylation levels observed in the present study population
(mean 81.9%, ranging from 75.9% to 93.1%) were considerably higher than those in U.S.
whites (mean 79.6%, ranging from 57.9% to 92.0%)18. Given the high incidence rate of
bladder cancer in the latter than the former population, one could speculate that global
hypomethylation, if confirmed as an underlying risk factor for bladder cancer, may
contribute to the higher rates of bladder cancer in non-Hispanic whites in the U.S. than in
Chinese in China26. This high level of global DNA methylation in the present study
population may explain the lack of an overall association between LINE-1 methylation
and bladder cancer risk given the fact that no subjects had a LINE-1 methylation value
below 74.25%, a threshold level for elevated risk of bladder cancer found in a previous
study conducted in New Hampshire which had 6% of controls and 14.4% of bladder
cancer cases with such low level of LINE-1 methylation18. Although batch effects could
play a role in these differences, the fact that samples from studies displaying these
differences were processed in the same lab with identical protocol and technique makes
these effects less likely to account for these differences.
58
The difference in global DNA methylation levels between populations also could
be due to different environmental exposures, including diet. Associations of these
exposures with LINE-1 methylation were examined in this study among controls only to
avoid potential influence of bladder carcinogenesis on LINE-1 alterations. In the present
study, a high intake of cruciferous vegetables was associated with an increased level of
LINE-1 methylation. Thus, the higher LINE-1 methylation levels in Chinese in China
compared to Caucasians in the U.S. could be in part due to the high consumption of
cruciferous vegetables in the former than the latter population based on self-reported
weekly consumption27.
The present study also showed that smokers with elevated CYP1A2 phenotype
score, a risk factor for bladder cancer in this population21, had reduced LINE-1
methylation levels, further supporting a role of DNA hypomethylation in bladder
carcinogenesis. The modifying effect of GSTM1 and GSTT1 genotype on LINE-1
methylation could be due to the impact of these genes on the available pool of
glutathione. Glutathione depletion negatively impacts methylation, and perhaps the
deletion of GSTM1 and GSTT1 alters the methyl donor pool sufficiently to impact LINE1 methylation levels28.
Further studies are warranted to elucidate the underlying
mechanism of genetic factors and one-carbon metabolites on global DNA methylation as
well as on their modifying role in the global DNA methylation and bladder cancer
association.
Consistent with previous studies, the present study found a significantly elevated
level of LINE-1 methylation in men when compared to women18,29. Although the
mechanism for this difference is unknown, LINE-1 activity has been linked to the process
59
of X chromosome inactivation, which may account for these differences30. Further
studies are necessary to fully understand LINE-1 methylation gender differences.
The present study did not show a difference in LINE-1 methylation between
smokers and nonsmokers. These findings were consistent with those in a similar study in
the New Hampshire population18. Given that smoking can only account for
approximately 50% of bladder cancer case burdens in the U.S. and other developed
countries, the findings of the present study of the association between global DNA
hypomethylation in LINE-1 and bladder cancer risk among lifelong nonsmokers shed
some light on the biological mechanism of non-tobacco related bladder carcinogenesis.
Although the etiologic agents causing bladder cancer for non-smokers remain to be
ascertained, our data suggest that these agents are likely to be associated with altering the
overall epigenetic state, thereby contributing to the risk of bladder cancer. Therefore,
identification of factors that alter global DNA methylation would help to discover
potential etiological factors for bladder cancer, especially among nonsmokers.
Strengths of this study included the population-based study design, quantitative
pyrosequencing to determine LINE-1 methylation, relatively large sample size, and
comprehensively collected data on environmental exposure and genetic determinants of
study subjects. The chief limitation of the present study was the retrospective nature of
the study design, i.e., the collection of blood samples and information on exposure from
bladder cancer patients took place after their cancer diagnosis, and in some cases,
therapeutic treatment for cancer. If the carcinogenesis process and/or therapeutic
treatment had any direct or indirect impact on global DNA methylation through changing
60
subject’s lifestyle or environmental exposure, we could have observed a confounded or
biased association between LINE-1 methylation and bladder cancer risk.
In conclusion, the findings of the present study support DNA hypomethylation as
a potential risk factor for bladder cancer, especially for lifelong nonsmokers.
Consumption of cruciferous vegetables and certain genetically determined factors such as
CYP1A2 and GSTs may have impact on global DNA methylation, whereby exerting their
effect on bladder cancer risk.
Acknowledgements
We thank Charlotte Wilhelm and Devin Koestler for assistance with statistical
methods, as well as Graham Poage for helpful discussions. We also thank the
participants of the Shanghai Bladder Cancer Study. This study was funded by the NIH
(R01 CA65726 3R01 and CA121147-04S1).
61
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65
Table 1. Distributions of selected characteristics in patients with bladder cancer
(cases) and control subjects
The Shanghai Bladder Cancer Case-Control Study
Total subjects
Age at reference year
<50
50-<60
60-<70
≥70
Gender
Male
Female
Education
No formal schooling
Primary school
Middle school
College and above
Body mass index, kg/m2
<18.5 (underweight)
18.5-<25 (normal)
≥25 (overweight and obese)
Smoking status at reference date
Nonsmokers
Former smokers
Current smokers
CYP1A2 phenotypic score levels
Low (≤5.53)
High (>5.53)
Intake of total cruciferous vegetables ∗
Less than 4 times/week
≥ 4 times/week
GSTM1/GSTT1 genotypes
Both Non-null
Others
Both null
LINE-1 methylation in tertiles
1st (≥82.52)
2nd (81.22-<82.52)
3rd (<81.22)
Mean (SD)
*
No. cases (%)
No. controls (%)
2-sided P
510 (100)
528 (100)
0.312
0.016
83 (16.3)
76 (14.9)
275 (53.9)
76 (14.9)
59 (11.2)
94 (17.8)
270 (51.1)
105 (19.9)
400 (78.4)
110 (21.6)
405 (76.7)
123 (23.3)
43 (8.4)
122 (23.9)
283 (55.5)
62 (12.2)
39 (7.4)
135 (25.6)
301 (57.0)
53 (10.0)
44 (8.6)
364 (71.4)
102 (20.0)
48 (9.1)
400 (75.8)
80 (15.2)
178 (34.9)
79 (15.5)
253 (49.6)
236 (44.7)
89 (16.9)
203 (38.5)
216 (42.4)
281 (55.1)
248 (47.0)
248 (47.0)
66 (12.9)
444 (87.1)
55 (10.4)
473 (89.6)
95 (18.6)
233 (45.7)
173 (33.9)
113 (21.4)
272 (51.5)
139 (26.3)
154 (30.2)
165 (32.3)
191 (37.5)
81.86 (1.82)
177 (33.5)
176 (33.3)
175 (33.1)
81.96 (1.89)
0.505
0.615
0.121
0.001
0.003
0.205
0.020
0.310
0.382
Cruciferous vegetables include bokchoi, cabbage, and cauliflower.
66
Table 2. The association between LINE-1 levels and potential risk factors among
control subjects only,
The Shanghai Bladder Cancer Case-Control Study
Men
Mean (95% CI)
No.
405
82.09 (78.42-85.76)
123
81.53 (77.79-85.26)
0.004
46
359
81.31 (80.77-81.84)
82.20 (82.00-82.39)
0.002
9
114
81.94 (80.69-83.19)
81.50 (81.14-81.85)
0.505
182
203
82.30 (82.03-82.57)
81.95 (81.69-82.20)
0.066
66
45
81.46 (81.00-81.93)
81.80 (81.24-82.37)
0.362
68
119
82.50 (82.09-82.91)
81.74 (81.43-82.05)
0.004
3
4
82.54 (80.72-84.36)
79.56 (77.98-81.13)
0.059
114
84
82.18 (81.81-82.55)
82.23 (81.81-82.66)
0.848
63
41
81.41 (80.94-81.88)
82.02 (81.44-82.60)
0.111
89
208
105
81.54 (81.15-81.92)
82.31 (82.05-82.56)
82.16 (81.80-82.51)
0.005
24
64
34
81.21 (80.44-81.97)
81.49 (81.02-81.96)
81.84 (81.20-82.49)
0.448
No.
Total subjects
P
Intake of total cruciferous vegetables
Less than 4 times/week
≥ 4 times/week
P
CYP1A2 phenotypic score levels
Among total control subjects
Low (≤5.53)
High (>5.53)
P
Among current smokers at urine collection
only
Low (≤5.53)
High (>5.53)
P
Among nonsmokers at urine collection
only
Low (≤5.53)
High (>5.53)
P
GSTM1/GSTT1 genotypes
Both Non-null
Others
Both null
P
Women
Mean (95% CI)
67
Table 3. LINE-1 levels in relation to risk of bladder cancer,
The Shanghai Bladder Cancer Case-Control Study
LINE-1 in tertiles among total subjects
1st (≥82.52)
2nd (81.22-<82.52)
3rd (<81.22)
Total Subjects
No. cases/no. controls
OR (95% CI) ∗
By gender
Men
No. cases/no. controls
OR (95% CI) ∗
Women
No. cases/no. controls
OR (95% CI) ∗
By smoking status at reference date
Nonsmokers
No. cases/no. controls
OR (95% CI) ∗
Former smokers
No. cases/no. controls
OR (95% CI) ∗
Current smokers
No. cases/no. controls
OR (95% CI) ∗
Ptrend
154/177
1.00
(reference)
165/176
1.10 (0.81-1.50)
191/175
1.28 (0.95-1.73)
0.268
132/143
1.00
(reference)
134/143
1.03 (0.73-1.42)
134/119
1.23 (0.87-1.73)
0.455
22/34
1.00
(reference)
31/33
1.57 (0.74-3.31)
57/56
1.58 (0.82-3.04)
0.360
40/75
1.00
(reference)
50/74
1.34 (0.79-2.28)
88/87
1.91 (1.17-3.13)
0.032
25/33
1.00
(reference)
32/31
1.37 (0.66-2.83)
22/25
1.10 (0.50-2.43)
0.682
89/69
1.00
(reference)
83/71
0.93 (0.59-1.45)
81/63
0.99 (0.63-1.56)
0.938
*
All odds ratios (ORs) were adjusted for age at reference date (continuous) and family history of cancer
(yes/no); regression models for total subjects and by smoking status were also adjusted for gender
(male/female); regression models for nonsmoking subjects at reference date were also adjusted for ETS
exposure status (yes/no).
68
Table 4. LINE-1 levels in relation to risk of bladder cancer by GSTM1 and GSTT1
genotypes,
The Shanghai Bladder Cancer Case-Control Study
LINE-1 in tertiles among total subjects
1st (≥82.52)
2nd (81.22-<82.52)
3rd (<81.22)
By GSTM1/GSTT1 genotypes
Both Non-null genes
No. cases/no. controls
OR (95% CI)
One or both null genes
No. cases/no. controls
OR (95% CI)
One null gene only
No. cases/no. controls
OR (95% CI)
Both null genes
No. cases/no. controls
OR (95% CI)
Lifelong nonsmokers with one
Or both null genes
No. cases/no. controls
OR (95% CI)
P trend
30/23
1.00 (reference)
30/40
0.60 (0.28-1.25)
35/50
0.51 (0.25-1.04)
0.169
123/153
1.00 (reference)
132/135
1.23 (0.87-1.72)
151/123
1.58 (1.12-2.22)
0.054
73/99
1.00 (reference)
70/96
1.02 (0.66-1.58)
90/77
1.66 (1.07-2.57)
0.037
50/54
1.00 (reference)
62/39
1.65 (0.94-2.90)
61/46
1.49 (0.85-2.59)
0.175
31/60
1.00 (reference)
38/59
1.26 (0.69-2.29)
70/58
2.36 (1.34-4.14)
0.006
*
All odds ratios (ORs) were adjusted for age at reference date (continuous) and family history of cancer
(yes/no); regression models for total subjects and by smoking status were also adjusted for gender
(male/female); regression models for nonsmoking subjects at reference date were also adjusted for ETS
exposure status (yes/no).
69
Chapter 3
Metabolic and cardiovascular disease risk factors and DNA methylation at the
LINE-1 repeat region in peripheral blood from Samoan Islanders
Haley L. Cash, Stephen T. McGarvey, E. Andres Houseman, Carmen J. Marsit, Geralyn
M. Lambert-Messerlian, Nicola L. Hawley, Satupaitea Viali, John Tuitele, Karl T. Kelsey
70
Metabolic and cardiovascular disease risk factors and DNA methylation at the
LINE-1 repeat region in peripheral blood from Samoan Islanders
Haley L. Cash1,2, Stephen T. McGarvey2, E. Andres Houseman3, Carmen J. Marsit1,
Geralyn M. Lambert-Messerlian4, Nicola L. Hawley2, Satupaitea Viali5, John Tuitele6,
Karl T. Kelsey2
Departments of 1Pathology and Laboratory Medicine, 2International Health Institute, and
3
4
Center for Environmental Health and Technology, Brown University, Providence, RI,
Departments of Pathology and Laboratory Medicine, Women and Infants Hospital and,
Alpert Medical School, Providence, RI, 5Ministry of Health, Government of Samoa,
Apia, Samoa, 6Department of Health, American Samoa Government, Pago Pago,
American Samoa
71
Abstract
Lower levels of LINE-1 methylation in peripheral blood have been previously
associated with risk of developing non-communicable conditions, the most well-explored
of these being cancer. Studies examining LINE-1 methylation in association with
metabolic and cardiovascular chronic conditions are lacking, despite evidence suggesting
that these associations are important. We examined the relationship between LINE-1
methylation and factors associated with metabolic and cardiovascular diseases. We
measured LINE-1 methylation through quantitative bisulfite pyrosequencing in DNA
from peripheral blood samples from participants of the Samoan Family Study of
Overweight and Diabetes (2002-03). The study included 366 adult Samoans (88 men and
278 women) from both American Samoa and Samoa. DNA samples that were previously
collected for a genome-wide association study were analyzed for LINE-1 methylation.
Men had significantly higher LINE-1 levels than women (p=0.03), and lower levels of
LINE-1 methylation were found in men with lower levels of HDL cholesterol (p=0.009),
adjusting for age, insulin, cigarette smoking, and alcohol consumption. In women only,
LINE-1 was associated with insulin (p=0.02) and testosterone (p=0.05) when levels were
adjusted for age, HDL, and cigarette smoking. The findings from this study suggest that
specific hormone levels are associated with LINE-1 DNA methylation differences
between men and women. Additionally, these findings strongly argue for the need for
further research in order to understand the relationships between LINE-1 DNA
methylation and metabolic and cardiovascular disease.
72
Introduction
The Samoan islands, composed of the independent nation of Samoa and the U.S.
territory of American Samoa, are geographical neighbors that are currently experiencing
economic development and its associated nutritional transition at different rates, although
both populations are characterized by alarmingly high prevalences of obesity1. American
Samoa has a higher prevalence of obesity compared to Samoa with approximately 71%
of women and 59% of men defined as obese (using Polynesian standards of BMI
≥32),
relative to 29% of men and 53% of women in Samoa1. These high prevalences of
obesity have lead to rapid rises in obesity-related diseases such as cardiovascular disease
(CVD) and type 2 diabetes2 .
The rapid temporal rise of Samoan obesity and obesity-related diseases have been
attributed to modernization and its associated nutritional transition, in which these
developing nations are consuming more calorie-rich foods and expending less energy1.
Although these behavioral factors are linked to obesity and obesity-related disease,
genetic factors have also been shown to play an important role in Samoan obesity and
obesity-related risk factors3-6.
Both Samoan islands were settled by Polynesian settlers approximately 3,000
years ago7. Genetic evidence suggests that these island nations were originally settled by
small groups of voyagers7,8. These original settlers may have endured food shortages and
cold night-time open-ocean temperatures, perhaps favoring those with the ability to store
body fat and those with efficient energy metabolism, thus suggesting a role for a thrifty
genotype9. Although certain genetic loci have been associated with obesity phenotypes
73
in Samoans, studies examining potential links of epigenetic alterations with these extreme
metabolic phenotypes are currently lacking in this population.
Epigenetic alterations are DNA modifications that do not involve changes to the
sequence, yet alter gene expression10. Epigenetic regulation of gene expression is based
upon complex alterations in histone proteins, affecting chromatin conformation. These
changes have been associated with coordinate changes in DNA methylation of cytosine
bases in the context of CG dinucleotide pairs that often reside in gene promoter regions
(CpG islands) or in DNA repeat regions11. The detailed evaluation of the profile of DNA
methylation in affected tissues, as well as in the peripheral blood, has recently become an
important tool in cancer research, and the potential for epigenetic change to affect a
multitude of other diseases has lead to an interest in evaluating the association of changes
in DNA methylation with risk factors for other conditions12. Certain chronic disease risk
factors have been associated with altered levels of DNA methylation in DNA sequence
repeat regions in separate tissues, as well as in peripheral blood, and there are now many
studies that report diminished levels of DNA methylation in repeat regions to be
associated with risk of cancer13,14. Relationships between DNA methylation at repeat
regions (such as LINE-1 regions) and obesity, as well as obesity-related diseases have
been poorly studied, yet evidence exists that suggests that these relationships are likely to
exist15.
DNA hypomethylation occurring in cancerous tissue and peripheral blood has
been proposed to be a contributing mechanism for cancer development due both to the
potential for the abnormal expression of oncogenic genes, as well as the associated
genomic instability that results when DNA is hypomethylated at repeat regions16,17.
74
There is also evidence to suggest that environmental exposures are related to DNA
hypomethylation at these repeat regions18. The methyl groups that are substrates for
DNA methylation are provided by diet and, therefore, dietary factors are candidates for
playing an essential role in maintenance and regulation of DNA methylation 13, 19.
Preliminary studies have suggested that DNA methylation and associated epigenetic
alterations may play a role in chronic diseases other than cancer; specifically,
cardiovascular disease and diabetes20-25. Here, we investigated several risk factors for
non-communicable diseases by assessing their relationship with LINE-1 DNA
methylation in women selected for a study of menstrual patterns and their spouses from a
larger sample from American Samoa and Samoa.
Materials and Methods
Subjects
Subjects in this study were part of large pedigrees who participated in the Samoan
Family Study of Overweight and Diabetes, with data collected in 2002-03, and described
previously in detail3,4,6. Briefly, recruitment began in American Samoa based on random
selection of probands who participated in the 1990-94 cohort study, and had at least two
adult siblings alive and residing in American Samoa. Recruitment in Samoa began in
2003, and first involved participants who were members of American Samoan families
involved in the 2002 recruitment. Further villages were then selected throughout the
nation to achieve geographic and economic diversity, and families were chosen based on
maximum number of available adult siblings. Protocols for this study were approved by
75
the Brown University Institutional Review Board, the Government of Samoa, the Samoan
Ministry of Health, and the Samoan Health Research committee. Written informed
consent was obtained from all participants.
The women included in this analysis were part of a previously defined subsample,
derived from the Samoan Family Study of Overweight and Diabetes, which was designed
to investigate patterns of menstrual irregularity reported by Samoan women and examine
the relationship to adiposity and hormone levels26. This subsample included all women
between 18-39 years old who did not report hysterectomy, ovariectomy, or other
unspecified pelvic surgery. Subjects were further excluded if their serum samples could
not be located, or menstrual data were missing. One additional woman was removed due
to an extreme outlier mullerian inhibiting substance (MIS) value (45 ng/ml) suggestive of
an ovarian tumor or other possible pathologic process. The study subsample totaled N =
336 women (N = 173 from Samoa and N = 163 from American Samoa).
We further excluded women who did not have DNA available for analysis
(N=43). Men included in this analysis were spouses of the female subsample with
available DNA (N=97). This male selection technique was used to minimize relatedness
of subjects. Two men and two women were excluded due to parental relationships with
women in the subsample in order to control for direct relationships within the sample, as
heritable factors may potentially play a role in DNA methylation profiles27. Individuals
on medication for high blood pressure and/or diabetes (N=20) were removed from these
models to control for confounding factors, although similar results were obtained when
the full sample was included in the models; the models presented are for the reduced
sample. Therefore, from the original 71 pedigrees containing 1,164 genotyped adults (at
76
least 18 years old), (534 men and 630 women) we included 366 in the present sample (88
men and 278 women). Of the subjects included in the sample, 78 (21.3%) had at least
one sibling relationship within the sample.
Data Collection and Measurements
An in-person interview with each eligible study subject was conducted by a
trained Samoan field worker using a structured questionnaire. The questionnaire
gathered information on subject demographics, history of tobacco and alcohol use,
medical history, physical activity, occupational history, and dietary intake. Standard
anthropometric techniques were used to measure height, weight, and body
circumferences, and to calculate body mass index (BMI) by dividing weight (kg) by
height squared (m). Blood pressure was measured 3 times after participants were seated
for 5 minutes. The mean of 3 measurements was used for analyses. Fasting blood
specimens were drawn following a 10-hour minimum overnight fast, serum was
separated by centrifugation in the field and stored at -40°C until shipped on dry ice. The
following assays of sera were completed: serum leptin by radioimmunoassay (RIA) using
a kit from ALPCO (Windham, NH); serum insulin using standard RIA kits from
Diagnostic Products Inc.; serum glucose using an automatic analyzer, Beckman CX4;
serum adiponectin using RIA kits form Linco Inc. (St. Charles, MI). Total cholesterol
and triglycerides were measured by enzymatic assays on Gilford Impact 400 computer
directed analyzer. HDL cholesterol was measured after precipitation of VLDL and LDL
with heparin-Mn2+ reagent. Frozen serum specimens for women only in this study
sample were thawed and assayed for total testosterone (TT) using the Siemens Immulite
instrument (Los Angeles, CA)26.
Buffy coats were prepared from 10ml of
77
ethylenediamine-tetraacetic acid blood samples in the field, kept at -40°C, then shipped to
Cincinnati, OH. Genomic DNA was isolated using the Puregene Kit (Gentra Systems,
Inc., Minneapolis, MN) and quantified, and shipped to Providence, RI for DNA
methylation analysis.
One µg of peripheral lymphocyte DNA was sodium bisulfite modified using the
EZ DNA Methylation Kit according to manufacturer’s protocol (Zymo Research, Orange,
CA). LINE-1 region methylation extent was quantified using quantitative bisulfite
Pyrosequencing28 as previously described29, which examines the cytosine methylation
status at 4 CpG sites in the LINE-1 region. All PCR reactions were performed using
Qiagen Hot Star Taq polymerase, and each batch included a no template control,
unmodified DNA control, and a standardized methylation control. Each sample was run
in triplicate, and each pyrosequencing reaction used 20µl of PCR product, and was run
according to instrument/manufacturer’s protocols on a PyroMark™MD System (Qiagen).
The standard error of the averaged individual repeats was found to be the same as the
standard error for each replicate, so the average measure (percentage) of LINE-1
methylation across the 4 CpG sites for each replicate was used to calculate an average of
the replicates for each sample.
Statistical Methods
The Chi-square test was used to examine the differences in the distributions of
categorical variables and t-test for the differences in means of continuous variables
between Samoans and American Samoans as well as between men and women. Variable
distributions were analyzed using categorical values.
78
Age was divided into approximate 10yr age groups (<20,20-<30, 30-<40, 40-<50)
and education was dichotomized into those who did and did not complete a secondary
education. BMI was categorized based upon previously published standard Polynesian
cutoffs for normal weight (<26 kg/m2), overweight (26-<32 kg/m2), obesity (32-<40
kg/m2), and morbid obesity (≥40 kg/m 2)30. Smoking and drinking were assessed based
upon participant’s response to their current status (yes/no). Blood pressure values were
dichotomized at by the American Heart Association standards for high blood pressure,
which is defined as a systolic blood pressure (sbp) ≥140 and/or a diastolic blood pressure
(dbp) ≥9031. Fasting blood glucose was dichotomized at >126mg/dL, the standard
classification for abnormal glucose32. Fasting insulin levels were dichotomized at
9.24ųIu/m, the median value of the entire population, or into population quartiles.
Fasting high-density lipoprotein (HDL) cholesterol was dichotomized at <40mg/dL for
women and <50mg/dL for men, the American Heart Association’s definition of low HDL
cholesterol which is associated with elevated risk for heart disease31. Fasting low-density
lipoprotein (LDL) cholesterol was dichotomized at ≥160mg/dL, the American Heart
Association’s definition for high LDL cholesterol which is associated with elevated risk
for heart disease31. Total testosterone was characterized into quartiles calculated among
all women with available data.
In order to control for sample plate variability bias, mixed linear models were
used to assess the relationship between LINE-1 methylation level and selected variables.
Age, BMI, glucose, insulin, HDL and LDL cholesterol, and total testosterone were
modeled as continuous variables. Location, gender, education, hypertension, and current
drinking and smoking status were modeled as categorical values. Bivariate models were
79
used to calculate unadjusted p-values, whereas multivariate mixed models were used to
calculate adjusted p-values. Mean LINE-1 values by sociodemographic, behavioral and
biological factors and stratified by location and sex are presented in Table 2. Mean
LINE-1 values presented in Tables 3-5 were derived from multivariate mixed linear
models. All models included a random effect to account for plate variability of LINE-1
measurement. Intraplate variability was controlled for by including a fixed regional
effect and regional x plate (random) interaction coefficient within all models to account
for small position effects of LINE-1 measurement.
Statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary,
NC) statistical software package. All P values are two sided. P values less than 0.05
were considered statistically significant.
Results
Socio-demographic characteristics of the study sample are shown in Table 1. The
subjects were made up of slightly more American Samoans than Samoans (55.7% and
44.3%, respectively). The mean age among American Samoans was 31.5 years (+/-7.0)
and 31.1 years (+/-7.3) among Samoans. Men were significantly older than women in
both American Samoa (p<0.0001) and Samoa (p<0.0001). Among both men and women,
American Samoans were more likely to have at least a secondary education, higher than
normal BMIs, higher levels of insulin, and lower levels of HDL cholesterol. There was a
higher proportion of men in American Samoa reporting alcohol consumption than in
Samoa (p=0.02), as well as a higher proportion of men with elevated blood pressure
(p=0.03).
80
In both locations, women were more likely to have higher BMIs than men, though
this trend was only significant in Samoa (p=0.02). Men were significantly more likely to
be current drinkers than women (p<0.0001 American Samoa; p=0.0003 Samoa) or
current smokers (p=0.02 American Samoa; p<0.0001 Samoa), as well as being likely to
have lowered levels of HDL cholesterol (p<0.0001 American Samoa; p=0.0001 Samoa).
Samoan women had higher levels of insulin than Samoan men (p=0.0002), American
Samoan men were more likely to have elevated blood pressure than American Samoan
women (p=0.0001), and Samoan men were more likely to have higher levels of LDL
cholesterol than Samoan women (0.02).
The overall range of DNA LINE-1 methylation was 75.9% to 90.2% with a mean
of 83.1% and 82.5% for men and women in American Samoa, respectively, and 83.3%
and 83.1% among men and women from Samoa. LINE-1 methylation was significantly
higher in men than in women among the entire sample (p=0.03; data not shown). Due to
these trends and the fact that characteristics differed so greatly between men and women
as well as between American Samoans and Samoans, associations between LINE-1 levels
and characteristics (Table 2) were examined in a population stratified by both location
and gender. There was a negative association between age and LINE-1 among men,
although this relationship was only significant in American Samoa men (p=0.02; Table
2). Additionally, there was a negative association among men between HDL cholesterol
and LINE-1 (p=0.08 in American Samoan men and p=0.02 in Samoan men). In this
analysis there were no clear associations across all participants between LINE-1
methylation education, BMI, smoking, drinking, glucose, insulin, LDL cholesterol, or
current hypertension.
81
When multivariable models were used to control for possible confounding, LINE1 methylation was significantly associated with HDL cholesterol in men (Table 3).
LINE-1 levels were lower among men with lower HDL cholesterol levels (vs. normal)
(p=0.009). In similar multivariate models among women only, LINE-1 methylation was
significantly associated with insulin levels (p=0.03; Table 4).
Additional data on testosterone levels were available for women only in this
sample who had been previously evaluated for menstrual patterns and endocrine status.
In this subgroup, when we added total testosterone level to the mixed model there was an
association between LINE-1 and total testosterone (p=0.05; Table 5). In this subset there
was also a significant association of LINE-1 with insulin (p=0.02).
These same associations in all models were observed when identical models were
run in subsample populations in which related individuals were removed (data not
shown).
Discussion
The present study examined one ethnic group, Samoans, characterized by high
prevalence of obesity and non-communicable diseases risk factors residing in two
different nations with different patterns of economic development and changes in way of
life. The most consistent association (in significance and magnitude) found with levels of
LINE-1 DNA methylation was sex of the participant. At the same time, there were
significant associations between LINE-1 methylation and HDL cholesterol among men,
and between LINE-1 methylation and insulin among women in a Samoan population
82
from American Samoa and Samoa. In a sub-analysis restricted to women evaluated for
menstrual patterns and risk of PCOS, we also observed a novel association of total serum
testosterone level with LINE-1 DNA methylation.
Higher levels of LINE-1 methylation in men than in women have been previously
reported13,14,33,34. It has been suggested that this difference may be due to X-chromosome
inactivation but it is not possible to definitively demonstrate whether or not this is the
case35. Of course, hormonal differences between men and women might also contribute
to this difference in LINE-1 methylation, and in the subset of women for whom we had
data, serum testosterone was positively associated with LINE-1 methylation. It is wellestablished that women with lowered levels of estrogen, such as post-menopausal
women, have higher levels of homocysteine, thus putting these women at increased risk
for cardiovascular disease36. Homocysteine plays an essential role in the DNA
methylation pathway, in which elevated levels of homocysteine are associated with
increased levels of DNA methylation22.
Due to the fact that male hormones have been
associated with higher levels of homocysteine in women37, hence, we believe that further
work is necessary to fully explore this potentially important relationship.
We also found that there was a significant association of lower LINE-1
methylation levels associated with lowered HDL cholesterol levels among men. Low
levels of HDL cholesterol are a well established risk factor for cardiovascular disease38.
This finding is consistent with a recent study that found that baseline healthy men with
lowered levels of LINE-1 methylation were more likely to develop ischemic heart
disease. Further work is necessary to explore the relationship between cardiovascular
disease and DNA global hypomethylation, but these findings suggest that lowered LINE83
1 methylation may be associated with elevated risk of developing cardiovascular disease.
However, this trend may not be applicable to all DNA repeat sequences, but rather
specific to LINE-1 due to findings from a study which found elevated DNA repetitive
sequences (ALU and AS) to be positively associated with risk of cardiovascular
disease20.
Among women, we found that higher levels of LINE-1 methylation were
associated with highest levels of fasting serum insulin levels. This finding is consistent
with an in vitro study that found higher levels of cellular insulin to be associated with
higher levels of homocysteine. As mentioned previously, higher levels of homocysteine
are associated with higher levels of DNA methylation22. It must however be noted that
insulin levels are hard to interpret in the presence of type 2 diabetes and hyperglycemia,
due to insulin resistance and beta cell fatigue. Similar results were observed in all models
when individuals with elevated glucose levels were removed (≥100mg/dL and
≥126mg/dL).
The role of epigenetic factors in cardiovascular and metabolic disease is
beginning to be well recognized22,25,39,40. Our findings suggest that metabolic factors
affect levels of LINE-1 methylation, and may potentially play a role in regulating
epigenetic states that could contribute to cardiovascular disease, diabetes, and other
complex metabolic disease phenotypes. Our data motivates future work including casecontrol studies of metabolic disease, evaluating the association of DNA methylation with
these conditions.
84
Strengths of this study included the population-based study design, quantitative
pyrosequencing to determine LINE-1 methylation, and comprehensively collected data on
a wide variety of population characteristics. The limitation of this study was the fact that
a small portion of this sample were related which could possibly affect LINE-1 levels,
although our analysis did not suggest that this was a significant source of variability.
Sensitivity analyses showed very similar model results between the full study sample and
smaller sample removing one or more members of the sibling pairs or triplets. The true
heritability of LINE-1 DNA methylation remains unknown.
In conclusion, we have shown that sex, serum levels of HDL cholesterol in men,
serum levels of insulin in women, and (in a subsample) testosterone are important
determinants of LINE-1 methylation. These findings may be due to genetic factors,
environmental exposures, or the combination of both. Our work supports the role of
environmental factors in impacting LINE-1 methylation, though further work is necessary
in order to determine the heritability of LINE-1 methylation.
Acknowledgements
We thank Devin Koestler for statistical assistance, Graham Poage for helpful
discussions, and Dr. Ranjan Deka for preparation and shipment of DNA samples. We
also thank the participants of the Samoan Family Study of Overweight and Diabetes.
This study was funded by the NIH (NIH DK59642, HL093093, CA65726, and
CA121147-04S1).
85
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91
Table 1- Distributions of selected characteristics in study sample participants
Variable
Age (years)
<20
20-<30
30-<40
40-<50
Education
<Secondary
≥Secondary
Missing
BMI (kg/m2)
Normal (<26)
Overweight (26-<32)
Obese (32-<40)
Morbidly obese (≥40)
Current smoking
No
Yes
Missing
Current drinking
No
Yes
Missing
Fasting glucose (mg/dL)
Normal (<126)
Impaired (≥126)
Missing
Fasting insulin (ųIu/m)
<Median (<9.24)
≥Median (≥9.24)
Missing
Fasting HDL (mg/dL)
Normal (≥40 w / ≥50 m)
Low (<40 w / <50 m)
Missing
Fasting LDL (mg/dL)
Normal (<160)
High (≥160)
Missing
Blood Pressure
sbp<140 and dbp<90
sbp≥140 and/or dbp≥90
American Samoa (N=204)
Men (%)
Women (%)
p-value*
8 (14.0%)
38 (66.7%)
11 (19.3%)
18 (12.2%)
49 (33.3%)
80 (54.4%)
-
<0.0001
8 (14.0%)
45 (78.9%)
4 (7.0%)
12 (8.2%)
128 (87.1%)
7 (4.8%)
5 (8.8%)
16 (28.1%)
24 (42.1%)
12 (21.1%)
Samoa (N=162)
Men (%)
Women (%)
p-value*
2 (6.5%)
16 (51.6%)
13 (41.9%)
7 (5.3%)
62 (57.3%)
62 (47.3%)
-
<0.0001
0.18
25 (80.7%)
6 (19.4%)
-
92 (70.2%)
39 (29.8%)
-
22 (15.0%)
32 (21.8%)
49 (33.3%)
44 (29.9%)
0.27
12 (38.7%)
14 (45.2%)
3 (9.7%)
2 (6.5%)
31 (54.4%)
21 (36.8%)
5 (8.8%)
110 (74.8%)
33 (22.4%)
4 (2.7%)
0.02
17 (29.8%)
31 (54.4%)
9 (15.8%)
115 (78.2%)
16 (10.9%)
16 (10.9%)
52 (91.2%)
4 (7.0%)
1 (1.8%)
A. Samoa vs. Samoa
Pmale*
Pfemale*
0.06
0.02
0.24
<0.0001
<0.0001
29 (22.1%)
45 (34.4%)
50 (38.2%)
7 (5.3%)
0.02
0.0001
<0.0001
14 (45.2%)
14 (45.2%)
3 (9.7%)
91 (69.5%)
16 (12.2%)
24 (18.3%)
<0.0001
0.41
0.11
<0.0001
17 (54.8%)
10 (32.3%)
4 (12.9%)
97 (74.0%)
10 (7.6%)
24 (18.3%)
0.0003
0.02
0.48
144 (98.0%)
3 (2.0%)
-
0.08
30 (96.8%)
1 (3.2%)
-
128 (97.7%)
4 (2.3%)
-
0.76
0.45
0.89
24 (42.1%)
32 (56.1%)
1 (1.8%)
58 (39.5%)
89 (60.5%)
-
0.66
26 (83.9%)
5 (16.1%)
-
74 (56.5%)
57 (43.5%)
-
0.005
0.0002
0.005
6 (10.5%)
49 (86.0%)
2 (3.5%)
92 (62.6%)
55 (37.4%)
-
<0.0001
15 (48.4%)
16 (51.6%)
-
107 (81.7%)
24 (18.3%)
-
0.0001
0.0001
0.0004
46 (80.7%)
4 (7.0%)
7 (12.3%)
141 (95.9%)
5 (3.4%)
1 (0.7%)
0.18
25 (80.7%)
6 (19.4%)
-
123 (93.9%)
8 (6.1%)
-
0.02
0.13
0.29
35 (61.4%)
22 (40.6%)
126 (85.7%)
21 (14.3%)
0.0001
26 (83.9%)
5 (16.1%)
113 (86.3%)
18 (13.7%)
0.73
0.03
0.90
*p-values are derived from χ2 tests to examine differences between men vs. women in American Samoa,
men vs. women in Samoa, American Samoan men vs. Samoan men, and American Samoan women vs.
Samoan women.
92
Table 2- Association of LINE-1 methylation with the characteristics of the participants, stratified
by location and gender
Men
LINE-1% A. Samoa
83.02
LINE-1% Samoa
83.51
p-value
0.25
p-value
American Samoa
LINE-1% Men
LINE-1% Women
83.05
82.57
0.048
Variable
Age (years)*
<20
20-<30
30-<40
40-<50
p-value
Education
<Secondary
≥Secondary
p-value
BMI (kg/m2)*
Normal (<26)
Overweight/obese (26-<32)
Obese (32-<40)
Morbidly obese (≥40)
p-value
Current smoking
No
Yes
p-value
Current drinking
No
Yes
p-value
Fasting glucose (mg/dL)*
Normal (<126)
Impaired (≥126)
p-value
Fasting insulin (ųIu/m)*
<4.29
4.29-<9.24
9.24-<17.90
17.90+
p-value
Fasting HDL (mg/dL)*
Normal (≥40 w / ≥50 m)
Low (<40 w / <50 m)
p-value
Fasting LDL (mg/dL)*
Normal (<160)
High (≥160)
P-value
Hypertension
No
Yes
p-value
Women
LINE-1% A. Samoa
LINE-1% Samoa
82.58
83.15
0.13
LINE-1% Men
83.52
Samoa
LINE-1% Women
83.18
0.35
LINE-1% AS Men
LINE-1% AS Women
LINE-1% S Men
LINE-1% S Women
84.77
83.05
82.31
0.02
82.79
82.51
82.42
0.21
83.70
83.45
83.11
0.38
82.51
83.01
83.48
0.11
83.62
83.08
0.39
81.62
82.54
0.04
83.53
82.60
0.32
83.28
83.00
0.42
82.47
83.46
82.90
83.50
0.82
81.73
82.56
82.51
82.95
0.06
83.56
83.72
81.97
81.56
0.19
83.55
83.05
83.12
83.35
0.69
83.00
83.50
0.29
82.40
82.72
0.29
83.26
83.71
0.45
83.27
82.93
0. 51
83.02
83.54
0.32
82.56
82.13
0.29
83.45
83.57
0.86
83.23
82.94
0.64
83.20
82.56
0.75
82.45
84.77
0.05
83.42
80.91
0.89
83.20
83.46
0.96
83.70
82.64
82.94
83.27
0.74
82.11
82.47
82.41
82.80
0.08
83.60
83.02
83.63
80.94
0.25
83.45
83.00
83.24
83.14
0.88
84.14
83.02
0.08
82.50
82.50
0.66
84.14
82.69
0.02
83.21
83.17
0.92
83.15
84.11
0.09
82.51
81.71
0.17
83.88
81.15
0.02
83.14
84.18
0.84
83.24
83.01
0.62
82.47
82.70
0.52
83.68
81.62
0.04
83.29
82.64
0.16
*Age, BMI, glucose, insulin, HDL, and LDL are modeled as continuous variables to calculate p-values.
p-values and mean LINE-1 values are derived from bivariate mixed linear models. All models are adjusted
for individual LINE-1 assay plate variability and intraplate variability.
93
Table 3- Association of LINE-1 methylation with characteristics among men
Variable
Age (years)*
N
LINE-1%
∆ LINE-1%
<30
10
85.09
30-<40
54
83.57
-1.52%
40-<50
24
83.27
-0.30%
Current smoking
45
83.84
Yes
35
84.11
<2.59
21
84.49
22
83.94
7.20-<16.57
22
83.48
-0.46%
≥16.57
22
83.99
+0.51%
Low (<40 w / <50 m)
Current drinking
0.05
0.17
0.14
0.56
0.69
0.0002
0.009
0.83
0.73
N=87
2.59-<7.20
Normal (≥40 w / ≥50 m)
0.01
+0.27%
-0.55%
HDL (mg/dL)*
p-value (adj)
N=80
No
Insulin (ųIu/m)*
p-value (unadj)
N=88
N=86
21
65
84.36
83.59
-0.77%
N=75
No
34
83.93
Yes
41
84.02
-0.09%
*Age, insulin, and HDL were modeled as continuous variables in mixed models.
Bivariate and multivariate mixed linear models were used to calculate unadjusted and adjusted pvalues. LINE-1% mean values presented are adjusted for all other variables presented in Table 3.
All models are adjusted for individual LINE-1 assay plate variability and intraplate variability.
94
Table 4- Association of LINE-1 methylation with characteristics among women
Variable
Age (years)*
n
LINE-1%
∆ LINE-1%
<20
25
82.67
20-<30
111
82.61
-0.06%
30-<40
142
82.73
+0.12%
Current smoking
201
82.61
Yes
49
82.73
0.88
0.72
0.45
0.03
0.03
0.62
0.23
0.27
0.35
N=278
69
82.55
4.97-<9.71
70
82.79
9.71-<18.6
69
82.43
-0.36%
≥18.6
70
82.90
+0.47%
+0.24%
N=278
Normal (≥40 w / ≥50 m)
199
82.75
Low (<40 w / <50 m)
79
82.59
Current drinking
0.73
+0.12%
<4.97
HDL (mg/dL)*
p-value (adj)
N=250
No
Insulin*
p-value (unadj)
N=278
-0.16%
N=238
No
212
82.88
Yes
26
82.46
-0.42%
*Age, insulin, and HDL were modeled as continuous variables in mixed models.
Bivariate and multivariate mixed linear models were used to calculate unadjusted and adjusted pvalues. LINE-1% mean values presented are adjusted for all other variables presented in Table 4.
All models are adjusted for individual LINE-1 assay plate variability and intraplate variability.
95
Table 5- Association of LINE-1 methylation with characteristics among a restricted female
sample with available testosterone level data (N=278) to examine hormonal affects on LINE-1
methylation levels
Variable
Age*
n
LINE-1%
∆ LINE-1%
25
82.62
20-<30
111
82.58
-0.04%
30-<40
142
82.74
+0.16%
201
82.60
Yes
49
82.69
82.55
4.97-<9.71
70
82.79
+0.24%
9.71-<18.6
69
82.40
-0.39%
≥18.6
70
82.85
+0.45%
0.48
0.03
0.02
0.62
0.17
0.27
0.40
0.11
0.05
N=278
Normal (≥40 w / ≥50 m)
199
82.71
Low (<40 w / <50 m)
79
82.59
-0.12%
N=238
No
212
82.86
Yes
26
82.43
Total testosterone (ng/dL)*
0.72
N=278
69
Current drinking
0.62
+0.09%
<4.97
HDL (mg/dL)*
0.73
N=250
No
Fasting insulin (ųIu/m)*
p-value (adj)
N=278
<20
Current smoking
p-value (unadj)
-0.43%
N=278
<44.5
67
82.47
44.5-<67.1
71
82.74
+0.27%
67.1-<92.9
≥92.9
72
68
82.62
82.76
-0.12%
+0.14%
*Age, insulin, HDL, and testosterone were modeled as continuous variables in mixed models
Univariate and multivariate mixed models were used to calculate unadjusted and adjusted pvalues. LINE-1% mean values presented are adjusted for all other variables presented in Table 5.
All models are adjusted for individual LINE-1 assay plate variability and intraplate variability.
96
Chapter 4
PSCA variant rs2294008 is associated with nearby CpG methylation in populations
from New Hampshire and Shanghai
Haley L. Cash, Graham M. Poage, Devin C. Koestler, E. Andres Houseman, Carmen J.
Marsit, Heather H. Nelson, Brock C. Christensen, Margaret R. Karagas, Jian-Min Yuan,
Karl T. Kelsey
97
PSCA variant rs2294008 is associated with nearby CpG methylation in populations
from New Hampshire and Shanghai
Haley L. Cash1, Graham M. Poage2, Devin C. Koestler3 , E. Andres Houseman3, Carmen
J. Marsit1, Heather H. Nelson4, Brock C. Christensen1,3, Margaret R. Karagas5, Jian-Min
Yuan4, Karl T. Kelsey1,3
1 Departments of Pathology and Laboratory Medicine, 2Molecular Pharmacology and
Physiology, and 3Community Health, Center for Environmental Health and Technology,
Brown University, Providence, RI; 4 Masonic Cancer Center, Division of Epidemiology
and Community Health, University of Minnesota, Minneapolis, MN; 5Section of
Biostatistics and Epidemiology, Department of Community and Family Medicine,
Dartmouth Medical School, Lebanon, NH
98
Abstract
Genetic and epigenetic factors are known to play important roles in the etiology of
bladder cancer.
Recently, a small number of SNPs have been identified to be
significantly associated with risk of bladder cancer, one of these being rs2294008 (C>T)
within the PSCA gene. Previous work suggests that certain SNP alleles may influence
CpG methylation of the SNP-associated gene. In this study, we aimed to explore the
relationship between rs2294008 alleles and CpG methylation at the genome-wide profile
and gene-specific CpG level using data obtained from Infinium DNA methylation arrays
conducted in New Hampshire and Shanghai. Although there were not genome-wide
profile differences between alleles, methylation of a CpG within the PSCA gene was
shown to be increased with risk T alleles in a dose-dependent manner in individuals from
New Hampshire (p<0.0001) and Shanghai (p<0.0001). This association is consistent
with previously reported data indicating that PSCA mRNA transcription levels are lower
in individuals with at least one T allele. Our findings suggest that genetic variation may
result in epigenetic alterations including allele-specific methylation that could potentially
play an important role in development of bladder cancer as well as various other cancers
and diseases.
99
Introduction
Genetic factors have long been known to modify risk of various cancers including
bladder cancer. The most well known genotypes associated with risk of bladder cancer
involve enzymes that metabolize bladder carcinogens such as N-acetlytransferase (NAT),
cytochrome P450 (CYP) 1A2, and glutathione S-transferases (GSTM1)1-3. Recently,
genome-wide association studies (GWAS) have identified common variants that are
associated with risk of bladder cancer4-7. One specific single nucleotide polymorphism
(SNP), rs2294008 (C>T), has been shown to increase risk of bladder cancer in various
studies involving different ethnic populations8-10. This SNP is located in exon 1 of the
prostate stem cell antigen (PSCA) gene; the precise function of this gene and this SNP in
generating excess bladder cancer risk remains unknown.
Epigenetic mechanisms involved in bladder cancer have recently been explored,
although much of this research is in early stages. Epigenetic alterations including DNA
methylation are acquired DNA modifications that do not involve changes to the DNA
sequence, yet may be associated with changes in gene expression and are crucial to
maintaining genomic stability11,12. DNA methylation-based gene silencing is associated
with through catalytic transfer of methyl groups to the 5-carbon of cytosine of the CpG
dinucleotide, most often found in the gene promoter regions12. DNA hypomethylation of
repeat sequences has been associated with multiple studies to be associated with risk of
bladder cancer13-15. Additionally, epigenetic silencing of tumor suppressor promoters via
hypermethylation is known to occur in bladder cancer patients, though the relationship
between these epigenetic events and genetic determinants has not yet been investigated1618
.
100
The relationship between genetic variation and variation in DNA methylation has
not been well studied, although evidence exists to suggest that these two factors are in
fact related. This relationship is of particular interest in respect to SNPs due to the fact
that regions surrounding SNPs tend to be abundant with CpG dinucleotides that are prone
to DNA methylation, and allele-specific methylation has been associated with some
heterozygous SNPs in genes that are prone to silencing. A recent study found that the T
allele of a SNP within the MGMT promoter region, rs16906252 (C>T) that is known to
be associated with several cancers was strongly associated with promoter methylation of
the MGMT gene in blood of normal individuals.
Our work sought to investigate the relationship between the bladder cancerassociated SNP, rs2294008, and DNA methylation of CpGs on a genome-wide
methylation profile level, as well as a local CpG level in peripheral blood samples from
healthy controls from two case-control bladder cancer studies conducted in New
Hampshire and Shanghai.
Materials and Methods
Subjects
The present study included healthy control participants that were part of bladder
cancer case-control studies in New Hampshire and Shanghai.
The New Hampshire study population has been described previously19. Briefly,
incident bladder cancer cases were identified from 1994-1998 from the New Hampshire
101
state cancer registry, and histopathologic diagnosis was verified by a single study
pathologist. Controls under 65 years of age were chosen from New Hampshire
Department of Transportation records, and controls older than 65 were chosen from the
Health Care Financing Administration’s Medicare Program. Controls were frequency
matched to cases by sex and 10-year age groups.
Individuals from Shanghai were part of the Shanghai Bladder Cancer Study which
has been described elsewhere20. Briefly, incident bladder cancer cases were identified
based on a diagnosis between 1995-1998 according to registration in the Shanghai Cancer
Registry. Control subjects were randomly selected from the urban population of
Shanghai using the Residents Registry of the Shanghai Municipal Government to match
the frequency distribution of cases by sex and 5-year age groups.
Only controls with available genotyping and Infinium data were used in the
analyses presented in this work (New Hampshire, N=228; Shanghai, N=72). All subjects
from both studies provided informed consent following procedures approved by the
appropriate institutional review boards.
Data Collection
Subjects from both studies participated in an in-person interview to gather
information on demographics, tobacco use, and other information not included in this
study. A blood sample was also taken from each participant that was used for DNA
extraction.
Laboratory Methods
102
DNA was extracted from peripheral-blood buffy coats using the QIAmp DNA
mini kit according to the manufacturer’s protocol (Qiagen, Valencia, CA), and 1µg of
DNA was sodium bisulfite modified using the EZ DNA Methylation Kit according to the
manufacturer’s protocol (Zymo Research, Orange, CA). Methylation profiling was
performed using the Illumina Infinium Methylation27 Bead Array at the University of
California, San Francisco Institute for Human Genetics Genomic Core Facility.
Additional DNA was whole-genome-amplified using Repli-g mini kit from
Qiagen for genotyping. Genotyping for rs2294008 was performed using a TaqMan assay
from Applied Biosystems. For quality control, 5% of the samples were duplicated. For
allele scoring, we used an ABI 7900HT Sequence Detection and Scoring System.
Statistical Methods
The Chi-square test was used to examine the differences in the distributions of
categorical variables. Characteristic distributions between SNP status in New Hampshire
and Shanghai were analyzed using categorical values.
We used recursively partitioned model mixture (RPMM) strategy of Houseman et
al. to model the Illumina array data 21. Training and testing sets were obtained by
randomly sampling within participants categorized by binary SNP status of no risk alleles
(CC) vs. at least one risk allele (CT or TT) among controls only from New Hampshire.
We used the Semi-Supervised Recursively Partitioned Mixture Models (SS-RPMM)
procedures to identify DNA methylation profiles associated with binary-coded SNP
status. A permutation-based χ2 test was used to evaluate the relationship between binary
SNP status and class membership.
103
Unconditional logistic regression models were used to examine the association
between methylation profile class membership (based on classes by Marsit et al.22) and
SNP status (CC/CT/TT). Age (continuous), gender (male/female), and smoking status
(never/former/current) were included in all models to control for confounding. The
strength of association between SNP status and class membership was measured by odds
ratios (ORs) and their corresponding 95% confidence intervals (CIs) and p-values.
In order to control for bead chip variability bias, mixed linear models were used
to assess the relationship between arcsine square-root transformed methylation β values
at cg13446199 and SNP status (CC, CT, TT) in the New Hampshire and Shanghai control
populations separately.
Statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary,
NC) statistical software package and R statistical software package (http://www.rproject.org). All p values are two sided, and p values less than 0.05 were considered
statistically significant.
Results
Characteristics of the two study populations from New Hampshire and Shanghai
are shown in Table 1. Age, gender, and smoking status were not found to be significantly
different by PSCA status (CC/CT/TT) in either population.
We first used DNA methylation array profiles previously defined from the New
Hampshire data that were obtained by Marsit et al using Semi-Supervised Recursively
104
Partitioned Mixture Models (SS-RPMM) that were determined from the nine loci most
significantly associated with bladder cancer case rather than control22. These classes
were found by Marsit et al to be significantly associated with case-control prevalence
(p<0.0001), in which right classes (those beginning with rR) were more likely to contain
cases than left classes (those beginning with rL)22. Using these classes, we examined the
association between class membership and PSCA status among controls and found that
there was a significant association (p=0.03) (Figure 1). We determined the odds of class
membership based on SNP allele combination among controls in models controlling for
age, sex, and smoking status (Table 2). The only significant association found using
these models was that TT homozygous risk individuals were 6.7 (2.3-20.0) times more
likely to belong to class rRLL (a high case-containing class) when compared to CC
homozygous non-risk individuals.
The same DNA methylation Illumina array data from Figure 1 were used among
controls only in New Hampshire with the semi-supervised (SS-RPMM) strategy to
identify profiles of DNA methylation associated with binary (no risk alleles vs. at least
one risk allele) PSCA SNP status (CC vs. CT/TT). Following quality assurance
procedures, the data set was split into training and testing series. Characteristics did not
differ significantly between training and testing sets (data not shown). The first step of
our semi-supervised strategy was to identify those CpG loci whose methylation state was
most significantly associated with having at least one risk allele (CT or TT) rather than
no risk alleles (CC). To do this, we fit a series of linear mixed-effects models using the
training data only for the 26,486 CpGs in the data set. Therefore, each methylation value
was modeled as the dependent variable, with random effect for plate based on a single
105
normalization sample run on all plates and a fixed effect for PSCA status. The absolute
value of the t statistics derived from the model were used to rank the CpG loci, and the
top 10 loci were chosen based on the cross validation procedure to be included in RPMM
23
. These 10 loci were used to cluster the samples based on the methylation profiles
within the training data set. To predict class membership among the testing set data, only
these 10 loci were used in combination with an empirical Bayes procedure. The
methylation classes obtained from this procedure are shown in Figure 2A, along with the
prevalence of PSCA SNP status within in class. In the testing set, we observed that class
membership was not significantly associated with PSCA status (p=0.25) (Figure 2B).
DNA methylation was next examined in CpGs on the Infinium DNA methylation
array that are located within the PSCA gene. There were two CpGs that were identified,
one of which was in a CpG island. When DNA methylation of these two CpGs was
examined in relation to PSCA SNP status, the CpG that was within a CpG island
(cg13446199), 935 base pairs downstream from rs2294008 was significantly associated
with PSCA SNP status in New Hampshire (p<0.0001) (Table 3). When this same CpG
was examined in relation to PSCA SNP status in controls from a bladder cancer case
control study from Shanghai, China the same association was observed in this population,
and was also highly significant (p<0.0001).
Discussion
The present study aimed to determine the effects of SNP risk variants on arraywide DNA methylation profiles as well as nearby CpG methylation. To do this, we
106
examined the PSCA SNP rs2294008 in which the T allele is associated with risk of
bladder cancer. We used DNA from peripheral blood from control subjects collected
during case-control bladder cancer studies taking place in New Hampshire and Shanghai.
When first examining data from New Hampshire, we did not find array-wide associations
with SNP status, however we did find that methylation of a local CpG (cg13446199)
within the PSCA gene was associated with SNP status in a dose-response relationship.
This trend was validated in data from the Shanghai study in which a similar significant
positive correlation between risk allele quantity and cg13446199 methylation.
We first explored methylation classes determined by Marsit et al. that predicted
case-control status in the New Hampshire data to determine if SNP status was associated
with the classes due to the fact that risk T alleles are predictive of bladder cancer22. We
hypothesized that controls within case-predicting classes may be more likely to contain
individuals with risk alleles, as they are more likely to develop disease. This association
was only true in one class (rRLL), but led us to examine array-wide DNA methylation
patterns associated with SNP status.
A previous study conducted by our group found a significant association between
GSTM1/GSTT1 and DNA methylation at LINE-1 repeat sequences, motivating us to
explore whether or not SNP status could influence DNA methylation profiles15. To do
this, we implemented SS-RPMM methods to determine the most variable loci between
individuals with no risk alleles (CC) and individuals with at least on risk allele (CT or
TT) in half of New Hampshire controls (training set), then tested these loci in the other
half of New Hampshire controls (testing set) to determine their efficacy. The ten most
variable loci (N=10 determined by cross-validation procedure as described previously)
107
could not significantly cluster the data into profiles associated with SNP status within the
testing set, suggesting that SNP variants do not affect genome-wide CpG methylation
patterns.
Although SNP status did not affect overall DNA methylation profiles, previous
work led us to believe that local CpG methylation could vary by allele24. We examined
the two CpGs with available data from the Infinium array that were within the PSCA
gene. We found that methylation of the CpG that was part of a CpG island within the
PSCA gene, cg13446199, was positively associated with number of risk alleles
(p<0.0001). This phenomenon was validated in controls from a Shanghai bladder cancer
study (p<0.0001). This finding is consistent with work that demonstrated mRNA
expression to be decreased in individuals with at least one risk allele (CT/TT) compared
to those with no risk allele (CC)8. As PSCA is known to have tumor suppressor
properties, it is possible that the risk allele could assert bladder cancer risk through
epigenetic mechanisms in which PSCA gene transcription may be silenced by DNA
methylation.
Our findings that were consistent in two entirely different populations strongly
suggest that genetic variants could influence localized CpG methylation, thus influencing
disease risk by altering transcriptional activity of tumor suppressors. More work is
necessary to validate this finding and to determine the biological relevance of this
association. Future work will involve pyrosequencing this CpG in samples from New
Hampshire and Shanghai, as well as examining mRNA in heterozygous individuals in
order to assess cDNA sequences in order to determine whether or not allele-specific
silencing is occurring. Overall, we found a novel association between PSCA SNP status
108
and nearby CpG methylation suggesting that genetic-epigenetic interactions could play a
vital role in cancer development and progression.
109
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Garcia-Closas R, Chanock S, Tardon A, Serra C, Carrato A, Dosemeci M, et al. Genomic
DNA hypomethylation as a biomarker for bladder cancer susceptibility in the Spanish
Bladder Cancer Study: a case-control study. Lancet Oncol 2008;9:359-66.
14. Wilhelm CS, Kelsey KT, Butler R, Plaza S, Gagne L, Zens MS, Andrew AS,
Morris S, Nelson HH, Schned AR, Karagas MR, Marsit CJ. Implications of LINE1
methylation for bladder cancer risk in women. Clin Cancer Res 2010;16:1682-9.
111
15. Cash HL, Tao L, Yuan JM, Marsit CJ, Houseman EA, Xiang YB, Gao YT,
Nelson HH, Kelsey KT. LINE-1 hypomethylation is associated with bladder cancer risk
among non-smoking Chinese. Int J Cancer 2011;in press.
16. Marsit CJ, Karagas MR, Schned A, Kelsey KT. Carcinogen exposure and
epigenetic silencing in bladder cancer. Ann N Y Acad Sci 2006;1076:810-21.
17. Marsit CJ, Karagas MR, Danaee H, Liu M, Andrew A, Schned A, Nelson HH,
Kelsey KT. Carcinogen exposure and gene promoter hypermethylation in bladder cancer.
Carcinogenesis 2006;27:112-6.
18. Marsit CJ, Karagas MR, Andrew A, Liu M, Danaee H, Schned AR, Nelson
HH, Kelsey KT. Epigenetic inactivation of SFRP genes and TP53 alteration act jointly as
markers of invasive bladder cancer. Cancer Res 2005;65:7081-5.
19. Karagas MR, Tosteson TD, Blum J, Morris JS, Baron JA, Klaue B. Design of
an epidemiologic study of drinking water arsenic exposure and skin and bladder cancer
risk in a U.S. population. Environ Health Perspect 1998;106 Suppl 4:1047-50.
20. Tao L, Xiang YB, Wang R, Nelson HH, Gao YT, Chan KK, Yu MC, Yuan
JM. Environmental tobacco smoke in relation to bladder cancer risk--the Shanghai
bladder cancer study. Cancer Epidemiol Biomarkers Prev 2010;19:3087-95.
21. Houseman EA, Christensen BC, Yeh RF, Marsit CJ, Karagas MR, Wrensch
M, Nelson HH, Wiemels J, Zheng S, Wiencke JK, Kelsey KT. Model-based clustering of
DNA methylation array data: a recursive-partitioning algorithm for high-dimensional
data arising as a mixture of beta distributions. BMC Bioinformatics 2008;9:365.
112
22. Marsit CJ, Koestler DC, Christensen BC, Karagas MR, Houseman EA, Kelsey
KT. DNA methylation array analysis identifies profiles of blood-derived DNA
methylation associated with bladder cancer. J Clin Oncol 2011;29:1133-9.
23. Koestler DC, Marsit CJ, Christensen BC, Karagas MR, Bueno R, Sugarbaker
DJ, Kelsey KT, Houseman EA. Semi-supervised recursively partitioned mixture models
for identifying cancer subtypes. Bioinformatics 2010;26:2578-85.
24. Candiloro IL, Dobrovic A. Detection of MGMT promoter methylation in
normal individuals is strongly associated with the T allele of the rs16906252 MGMT
promoter single nucleotide polymorphism. Cancer Prev Res (Phila) 2009;2:862-7.
113
Figure 1. Association of previously defined DNA methylation profiles and PSCA status among controls.
The prevalence of PSCA status (y-axis) in each of the predicted classes among control participants only in
training and testing sets (N=227). χ2 test suggests that PSCA status prevalence is significantly different by
methylation class (P=0.03).
114
Figure 2. Association of DNA methylation profiles defined by a panel of 10 loci and PSCA status among
controls. (A) The recursively partitioned mixture model-based classification of methylation of 10 loci
(columns) in the peripheral blood-derived DNA of the 114 controls in the testing dataset is depicted in the
heat map, with the four classes separated by red lines. PSCA status prevalence is presented in the table to
the right of the heat map (B) The prevalence of PSCA status (CT/TT vs. CC) (y-axis) in each of the
predicted classes (x-axis). A permutation-based χ2 test suggests that PSCA SNP prevalence is not
significantly different by methylation class (P=0.25).
115
Table 1. Characteristics of the participants from New Hampshire and Shanghai
New Hampshire (N=228)
CC
CT
TT
N (%)
N (%)
N (%)
<50
10 (15.4%)
13 (11.7%)
8 (15.4%)
50-<60
10 (15.4%)
20 (18.0%)
13 (25.0%)
60-<70
29 (44.6%)
46 (41.4%)
20 (38.5%)
≥70
16 (24.6%)
32 (28.8%)
11 (21.2%)
Characteristic
Age
p
0.78
Gender
Male
46 (70.8%)
70 (63.1%)
34 (65.4%)
Female
19 (29.2%)
41 (36.9%)
18 (34.6%)
p
0.58
Smoking Status
Never
24 (36.9%)
26 (23.4%)
20 (38.5%)
Former
33 (50.8%)
63 (56.8%)
25 (48.1%)
Current
8 (12.3%)
22 (19.8%)
7 (13.5%)
p
Shanghai (N=72)
0.19
CC
CT
TT
N (%)
N (%)
N (%)
<50
2 (6.1%)
5 (16.1%)
-
50-<60
6 (18.2%)
7 (22.6%)
-
60-<70
23 (69.7%)
12 (38.7%)
6 (75.0%)
2 (6.1%)
7 (22.6%)
2 (25.0%)
Characteristic
Age
≥70
p
0.09
Gender
Male
23 (69.7%)
23 (74.2%)
7 (87.5%)
Female
10 (30.3%)
8 (25.8%)
1 (12.5%)
p
0.59
Smoking Status
Never
7 (21.2%)
7 (22.6%)
2 (25.0%)
Former
16 (48.5%)
12 (38.7%)
2 (25.0%)
Current
10 (30.3%)
12 (38.7%)
4 (50.0%)
p
0.77
p-values are derived from χ2 tests to examine differences between characteristics and PSCA status in the
New Hampshire and Shanghai populations separately
116
Table 2. Methylation class in relation to PSCA status
CC
N=64 (28.2%)
CT
N=111 (48.9%)
TT (risk)
N=52 (22.9%)
3 (30.0%)
7 (70%)
-
ref
1.3 (0.3-5.3)
-
P-value
-
0.73
0.96
N (%)
6 (25.0%)
13 (54.2%)
5 (20.8%)
ref
1.1 (0.4-3.3)
1.1 (0.3-3.7)
P-value
-
0.80
0.94
N (%)
11 (36.7%)
15 (50.0%)
4 (13.3%)
ref
0.7 (0.3-1.7)
0.4 (0.1-1.4)
P-value
-
0.47
0.14
N (%)
16 (25.0%)
33 (51.6%)
15 (23.4%)
ref
1.2 (0.6-2.4)
1.2 (0.5-2.7)
P-value
-
0.63
0.68
N (%)
5 (12.2%)
18 (43.9%)
18 (43.9%)
ref
2.4 (0.8-6.8)
6.7 (2.3-20.0)
P-value
-
0.11
0.0006
N (%)
14 (40.0%)
14 (40.0%)
7 (20.0%)
ref
0.6 (0.3-1.4)
0.6 (0.2-1.5)
P-value
-
0.22
0.25
N (%)
9 (39.1%)
11 (47.8%)
3 (13.0%)
ref
0.7 (0.3-1.9)
0.4 (0.1-1.4)
-
0.50
0.14
Class
rLLL
(N=10)
rLLR
(N=24)
rLRL
(N=30)
rLRR
(N=64)
rRLL
(N=41)
rRLR
(N=35)
rRR
(N=23)
N (%)
OR (95% CI)
OR (95% CI)
OR (95% CI)
OR (95% CI)
OR (95% CI)
OR (95% CI)
OR (95% CI)
P-value
Odds ratios and p-values obtained from unconditional logistic models controlling for age, gender, and
smoking status
117
Table 3. PSCA status in relation to mean β methylation values of cg13446199 in New
Hampshire and Shanghai
Mean β methylation values (SE) of cg13446199
SNP Status
CC
New Hampshire
N=65
0.51 (0.01)
N= 33
0.58 (0.02)
CT
N=111
0.62 (0.01)
N= 31
0.69 (0.02)
TT
N=52
0.74 (0.01)
N= 8
0.81 (0.03)
p
<0.0001
Shanghai
<0.0001
Mean β values presented are arcsine square-root transformed and are derived from mixed models adjusted
for bead chip variability
118
Chapter 5
Discussion
119
Non-communicable diseases have recently surpassed communicable diseases as
the number one cause of death globally, accounting for about 60% of deaths, worldwide1,
2
. Coronary heart disease alone caused 7.2 million deaths in 2004, accounting for 12.2%
of all deaths3. Rates of non-communicable disease are highest in developed nations, yet
are rapidly growing among developed nations4. These non-communicable diseases not
only contribute greatly to global mortality rates, but they are often chronic conditions that
create a great deal of disability, and require long-term care5. Loss of productivity and
high health care costs associated with these diseases are burdensome to nations,
particularly among less developed countries1, 2.
These non-communicable conditions are quite often attributed to tobacco smoking
and obesity-related risk factors, such as high blood pressure, high cholesterol levels, and
high circulating insulin levels6. However, even in these situations, the underlying
mechanisms leading to disease development and progression are not fully understood.
Various genetic factors associated with these conditions have been elucidated after
decades of research. Recently, the scientific community has begun to explore epigenetic
mechanisms involved in non-communicable diseases including cancer, cardiovascular
diseases, and metabolic conditions such as type 2 diabetes.
Epigenetic regulation of the genome involves heritable changes that do not alter
the DNA sequence, but may affect the transcription and translation of genes7.
Modification of gene function occurs through chemical modifications to CpG
dinucleotides or histone proteins that alter chromatin structure, thereby influencing
transcription factor binding capability8. Epigenetic mechanisms influencing translation
120
of genes involve that transcription of short, non-coding RNAs that inhibit translation of
protein-coding mRNA9.
DNA methylation is a type of epigenetic regulation that involves the covalent
binding of methyl groups onto the carbon-5 position of a cytosine residue by enzymatic
DNA methyltransferases that result in the recruitment of methylcytosine binding proteins
(MBPs) that form complexes with histone deacetylases (HDACs), ultimately causing
histone deacetylation and conformational changes in chromatin10, 11. Therefore, as DNA
becomes heavily methylated (known as “hypermethylation”), chromatin becomes
compact, preventing transcription factor binding, thus being transcriptionally inactive10.
Conversely, when DNA is unmethylated, or “hypomethylated”, chromatin remains open,
permitting transcription factor binding, and is therefore transcriptionally active10. DNA
methylation is a normal process in human cells, essential for biologic maintenance, and is
primarily responsible for host-defense suppression of exogenous nucleic acids, genomic
imprinting, female X-linked inactivation, and cell differentiation12, 13. DNA methylation
is known to be disrupted in a variety of diseases, the most well-investigated being
cancer14.
Overall genome-wide, or “global” DNA hypomethylation of repeat regions is
frequently observed in cancerous tissues compared to normal cells, and peripheral blood
of individuals with cancer have higher levels of global hypomethylation than healthy
individuals, and may be used in many cases as a biomarker of cancer15. Approximately
half of the genome is made up of repetitive sequences that are generally non-transcribed
due to their constant heterochromatin state that is maintained by DNA hypermethylation.
Therefore, hypomethylation of these sequences is a sign of dysregulation16. Global DNA
121
hypomethylation is proposed as a mechanism for cancer development due to potential for
abnormal gene expression, specifically including oncogenes, and activation of
transposable elements that lead to genetic mutations15, 17. Evidence exists to suggest that
environmental and dietary exposures can alter global DNA methylation levels, potentially
contributing to cancer etiology18, 19.
DNA methylation occurs at CpG sites which exist at much lower than expected
frequencies throughout the genome, but tend to be enriched to gene promoter sites to
allow for transcriptional gene control10. Dysregulation of CpG promoter methylation is a
well established phenomenon that is known to take place in most cancers, the most
common dysregulation being hypermethylation of tumor suppressor gene promoter
regions which is thought to play a critical role in silencing these genes and thereby
promoting malignant degeneration18, 20, 21. CpG promoter methylation is known to be
influenced by environmental, dietary, and genetic factors, although these mechanisms are
not yet fully understood22-25.
Bladder cancer is known to exhibit alterations in DNA methylation both globally
at the repeat sequence level, as well as involving specific CpG gene promoters. DNA
hypomethylation of repeat regions in peripheral blood of bladder cancer patients has been
demonstrated in two different populations, in which this association may be influenced
by exposures such as cigarette smoking and arsenic exposure26, 27. Bladder cancerspecific patterns of CpG methylation have also been shown to exist when comparing
patients to healthy controls; these patterns were also found to correlate with invasiveness
and aggressiveness of bladder cancer22, 28, 29. Additionally, methylation of specific CpG
122
promoter regions is known to be influenced by various exposures such as cigarette smoke
and arsenic30.
Previous studies reporting an association between global hypomethylation in
peripheral blood and bladder cancer risk were conducted in Caucasian populations26, 27,
thus in Chapter two of this thesis, we sought to investigate this relationship among a
Chinese population using LINE-1 methylation as quantified by pyrosequencing31 as a
surrogate for global methylation. In addition, we explored the relationship between
LINE-1 methylation a risk factors associated with bladder cancer, including tobacco
smoking, genetic polymorphisms, and certain dietary exposures, as well as their potential
for modifying the effect of the LINE-1 bladder cancer risk estimate.
Upon initial investigation of LINE-1 and risk of bladder cancer, we found a
statistically significant, inverse relationship between LINE-1 methylation and bladder
cancer risk among lifelong non-smokers. This finding is consistent with a study by
Moore et al. that found hypomethylation-associated risk of bladder cancer to be strongest
among never smokers26, however this group also demonstrated hypomethylationassociated risk among former and current smokers. Another study conducted by Wilhelm
et al. found that there was hypomethylation-associated risk of bladder cancer among the
entire population, although this association was only significant among women when the
population was stratified by gender27. Given that tobacco smoke only accounts for
approximately 50% of bladder cancers globally; our findings could perhaps help to
explain biological mechanisms of non-tobacco related bladder carcinogenesis. However,
among controls only, we found that smokers with high phenotypic scores of cytochrome
P450 (CYP) 1A2 (≥median) had lower levels of LINE-1 methylation than smokers with
123
low (<median) CYP1A2 scores, suggesting that carcinogen exposures still play an
important role in altering the repeat region DNA methylation levels in bladder cancer,
supporting previous work that found that tobacco smoke is associated with specific tumor
suppressor methylation 22.
This analysis indicates the need for finding factors that alter
global DNA methylation in order to discover potential etiological factors for nonsmoking related bladder cancer.
When examining the association of LINE-1 methylation and risk factors of
bladder cancer among controls in this population, we found that women had significantly
lower levels of LINE-1 methylation than men, a finding consistent with other work27, 32,
33
. It has been suggested that this difference could be potentially due to differences in
the distribution of LINE-1 elements on the X-chromosome, or perhaps hormonal
differences that can affect circulating levels of homocysteine, which is a key player in the
methylation pathway, and has been positively associated with DNA methylation is
previous work34-36.
Additionally, we also found that LINE-1 was elevated among those who
frequently consumed cruciferous vegetables, and those with a null genotype for either
glutathione-s-transferase M1 (GSTM1) or GSTT1. Both vegetable intake and
GSTM1/GSTT1 genotypes are important contributors to the one-carbon pathway, thus
having the potential to influence DNA methylation. Cruciferous vegetables are high in
dietary folate, a rich source of methyl groups necessary for DNA methylation37, 38, hence
providing a plausible explanation for elevated LINE-1 methylation in individuals with
higher vegetable intake. Glutathione-s-transferases are responsible for conjugation of
glutathione onto compounds to aid in detoxification, and as a result, have the ability to
124
deplete glutathione pools, a process known to negatively impact DNA methylation39.
Our data suggests that individuals with null glutathione-s-transferases likely have higher
pools of available glutathione, and therefore higher capacity to methylate DNA.
However, there was a significant interaction between LINE-1 hypomethylation and
GSTM1/GSTT1 genotypes in predicting bladder cancer, where hypomethylationassociated risk of bladder cancer among non-smokers was greatest among individuals
null for either the GSTM1 or GSTT1 genotype. Due to the fact that null glutathione-stransferase genotypes are well known risk factors associated with bladder cancer, this
relationship with hypomethylation seems quite reasonable40.
Overall, our findings from this study support DNA hypomethylation as a risk
factor for bladder cancer. Additionally, we found that environmental factors and genetic
factors, specifically, tobacco smoking and glutathione-s-transferase genotypes, may
influence this relationship. We also found that dietary and genetic risk factors are
associated with levels of LINE-1 methylation among controls only. These findings
together suggest that hypomethylation-associated risk of bladder cancer may be
attributable to the interaction of multiple risk factors, working in concert to alter global
methylation levels. More work is necessary in order to further understand how
environmental exposures and genetic components affect LINE-1 methylation levels, and
the affect of these LINE-1 alterations on risk of disease.
Findings from the bladder cancer study in Shanghai, as well as previously
published work, led us to hypothesize that risk factors associated with other noncommunicable conditions may also have the ability to alter levels of LINE-1 methylation
in peripheral blood. In chapter three we explored the relationships between risk factors
125
associated with cardiovascular and metabolic disease and LINE-1 methylation as
quantified by pyrosequencing31. Additionally, we examined LINE-1 methylation in
association with male hormone levels in a subset of women for which these data were
available. The peripheral blood samples and field data used in chapter three were
collected from the Samoan Family Study of Overweight and Obese, a population with
high prevalence of obesity and obesity-related risk factors for cardiovascular and
metabolic diseases.
Among the Samoans examined in our analysis, the most significant association
found with levels of LINE-1 methylation was sex of the participant. Consistent with
other findings, including those from chapter two, men had significantly higher levels of
LINE-1 methylation than women27, 32, 33. In a subset of women from this study of whom
we had data, serum testosterone was positively associated with LINE-1 methylation.
Women with lowered levels of estrogen, such as post-menopausal women have
significantly higher levels of homocysteine, an important factor in the DNA methylation
pathway that has been positively associated with levels of DNA methylation. Levels of
homocysteine in women have also been positively correlated with male hormones among
women, including testosterone. This finding strongly suggests that gender differences
observed regarding LINE-1 methylation are hormone-related, although more work is
necessary in order to fully establish this relationship.
While investigating relationships between LINE-1 methylation and risk factors
associated with cardiovascular and metabolic disease, we found that high density
lipoprotein (HDL) was most significantly associated with LINE-1 among men, whereas
insulin was most significantly associated with LINE-1 among women. Both of these
126
findings support the role of epigenetics in cardiovascular and metabolic diseases, for
which preliminary evidence already exists36, 41-43.
Specifically, we found that among men, lower LINE-1 levels were associated with
lower levels of HDL, an established risk factor for cardiovascular disease44. This finding
was consistent with a recent study by Baccarelli et al. that found that baseline healthy
men with lower levels of LINE-1 methylation were more likely to develop ischemic heart
disease45. Future work is necessary in order to fully understand this relationship, yet it is
becoming clearer that epigenetic processes are important in cardiovascular diseases.
Among women, higher levels of LINE-1 methylation were associated with the highest
levels of fasting serum insulin levels, consistent with work done by Chiang et al. that
observed a positive association between cellular insulin levels and higher levels of
homocysteine46. It must be noted however, that insulin levels are difficult to interpret in
the presence of type 2 diabetes and hyperglycemia due to insulin resistance and beta cell
fatigue. Regardless, this finding suggests the need for further explorations regarding
underlying epigenetic mechanisms involved in type 2 diabetes.
Overall, findings from this work suggest that DNA methylation may play a vital
role in the etiology of cardiovascular and metabolic diseases. Recent studies have
demonstrated that hypermethylation of certain gene promoters are involved in these
conditions, yet repeat methylation such as LINE-1 is much less understood23, 47. Due to
the fact that repeat region methylation dysregulation is associated with genomic
instability, it is important that these relationships be further explored.
127
In chapters two and three we show that risk factors, both environmental and
genetic, are associated with various non-communicable diseases are correlated with
levels of LINE-1 methylation. The relationship between genetic variation and its affect
on DNA methylation has not been well studied, but evidence exists to suggest that there
may be a relationship between these two factors. This relationship is of particular interest
due to the fact that regions surrounding SNPs are abundant with CpG dinucleotides that
are prone to DNA methylation48, and allele-specific methylation has been associated with
some heterozygous SNPs in genes that are prone to silencing49, 50. A recent study
conducted by Candiloro et al. found that the T allele of a SNP within the MGMT
promoter region that is known to be associated with several cancers, was strongly
associated with MGMT gene promoter methylation in blood of healthy individuals24.
In chapter four we aimed to examine the relationship between genetic variants
associated with risk of bladder cancer and CpG methylation, in order to fully understand
the relationship between environmental factors, genetic components, and DNA
methylation. In order to do this, we used CpG methylation data from infinium arrays
carried out on participant control peripheral blood samples from bladder cancer casecontrol studies conducted in New Hampshire and Shanghai.
We determined the effects of PSCA SNP rs2294008 variants associated with risk
of bladder cancer on CpG methylation by examining array based genome profiles, as well
as methylation of local CpGs. We did not find array-wide methylation associations with
PSCA SNP status, however we did find that methylation of a local CpG (cg13446199)
was associated with SNP status of rs2294008 in a dose-response relationship, in which
there was a positive correlation between risk allele quantity (number of T alleles) and
128
cg13446199 methylation. The same relationship was observed in control participants
from both studies examined (New Hampshire and Shanghai). These finding were
consistent with work done by Wang et al. who demonstrated that mRNA expression is
decreased in individuals with at least one risk allele (CT/TT) compared with no risk
alleles (CC).
The relationship between SNP variants and cancer risk is not well understood, yet
our work suggests that DNA methylation may play a vital role in this association. This
consistent finding in two very different populations strongly support the notion that
genetic variants may influence transcription of tumor suppressor genes by
hypermethylation. In order to validate our finding, methylation of cg13446199 should be
assessed in both New Hampshire and Shanghai population control individuals by
pyrosequencing of the CpG of interest, and perhaps surrounding CpGs that were not on
the array. Additionally, it would be interesting to extract mRNA from individuals
heterozygous for rs2294008, reverse transcribe it into cDNA, and sequence cDNA of the
PSCA gene to determine if one or both alleles were transcribed to determine whether or
not allele-specific methylation of PSCA affects gene transcription. If the allele-specific
methylation differences that we observed in both studies affect PSCA transcription, there
would be strong evidence to suggest genetic-epigenetic interactions, resulting in
imprinting of the PSCA gene, which would motivate a great deal of work in this field.
In summary, we have shown that DNA methylation is important in noncommunicable diseases such as cancer, cardiovascular, and metabolic disease.
Additionally, we have demonstrated that environmental and genetic factors may alter
DNA methylation of repeat sequences, therefore making the relationship between
129
environment, genetics, and epigenetics rather complex. We also provide evidence that
genetic variants may alter DNA methylation of local CpG islands, therefore having the
potential to alter gene transcription. It is known that methylation-based gene silencing
occurs in non-communicable disease, and that environmental exposures may alter these
relationships, although mechanisms remain largely unknown; and even less is understood
regarding genome-epigenome interactions. It is clear that more work is necessary in
order to fully understand how environmental exposures and genetic variants result in
epigenetic alterations leading to the development and progression of non-communicable
disease. The more that we begin to understand these relationships, the more effectively
we can diagnose and treat these burdensome conditions.
130
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