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OBEKON
Consortium
Investigation of the genomic background
of obesity using single nucleotide
polymorphism analysis in candidate genes
Csaba Szalai, Ágnes F. Semsei, Ildikó Ungvári,
Petra Kiszel, Péter Antal, András Falus
02 October 2009
CECON II. Budapest
1
Genetics of obesity
 The majority is multifactorial
 Concordance in monozygotic twins: 0.7-0.9
 In dizygotic twins: 0.35-0.45
 λs = 3.5
 Heritability rate of fat mass and fat
distribution: 40-70%
 Food preference, activity etc.
 Most associated genes
expressed in CNS
Aim of the study
 What SNPs can contribute to the susceptibility to
obesity in the Hungarian population?
 Candidate gene association study.
Patients
1337 Hungarian adults (873 women
and 464 men)
838 obese (BMI>30)
500 controls (BMI<25)
Genes
ADIPOQ
ADRB2
AGRP
FTO
GHRELIN
INSIG2
LEP, LEPR
MC4R
NPY
POMC
PPARG
PYY
SLC6A14
TNF
UCP1,2,3
Function
Adiponectin modulates glucose regulation and
fatty acid catabolism.
Delay digestion during fight-or-flight response
Increases appetite and decreases metabolism and
energy expenditure
Fat mass and obesity associated
Selection of
55 candidate
genes for
obesity
increases food intake and increases fat mass
insulin induced gene 2
leptin levels reflect individual energy balance
involved in feeding behaviour, the regulation of
metabolism
increases food intake and decreases physical
activity
polypeptide hormone precursor giving rise to
peptides with roles in pain and energy
homeostasis
regulates fatty acid storage and glucose
metabolism.
In humans it appears to reduce appetite.
Tryptophan transporter in the brain
Suppressing appetite in the hypothalamus
generate heat by non-shivering thermogenesis
Some examples of
the selected
candidate genes
Selection of 120 SNPs in the candidate genes
Gene
rs
Position
Alleles
Function
Panels
ADIPOQ
rs17300539
chr3:188042162
A/G
-514CT
48_plex_AG_panel1
ADIPOQ
rs266729
chr3:188042176
C/G
-11377G>C
12plex C/G
ADIPOQ
rs1501299
chr3:188053825
A/C
intron (boundary)
12plex A/C
ADRB1
rs2484294
chr10:115782052
A/G
512C>T
48_plex_AG_panel2
ADRB2
rs1042711
chr5:148186541
C/T
5' UTR
48_plex_AG_panel2
ADRB2
rs1042713
chr5:148186633
A/G
Gln223Arg
48_plex_AG_panel2
ADRB2
rs1042714
chr5:148186666
C/G
Gln27Glu
12plex C/G
ADRB2
rs1800888
chr5:148187078
C/T
Thr164Tyr
48_plex_AG_panel1
AGRP
rs5030980
chr16:66074446
A/G
5' UTR
48_plex_AG_panel1
COMT
rs4680
chr22:18325825
A/G
Val158Met
48_plex_AG_panel2
DRD2
rs1801028
chr11:112788694
C/G
Cys282Ser
12plex C/G
DRD2
rs2471857
chr11:112803539
A/G
intron
48_plex_AG_panel1
ENPP1
rs1044498
chr6:132214061
A/C
Lys121Gln
12plex A/C
ENPP1
rs7754561
chr6:132254387
A/G
Downstream
48_plex_AG_panel2
ESR1
rs2234693
chr6:152255449
C/T
intron
48_plex_AG_panel2
FABP2
rs1799883
chr4:120599505
C/T
Pro55Ser
48_plex_AG_panel2
FOXC2
rs34221221
chr16:85157931
C/T
5' near gene
48_plex_AG_panel1
FTO
rs1421085
chr16:52358454
C/T
intron
48_plex_AG_panel2
FTO
rs17817288
chr16:52365264
A/G
intron
48_plex_AG_panel2
FTO
rs8050136
chr16:52373776
A/C
intron
12plex A/C
FTO
rs7201850
chr16:52379362
C/T
intron
48_plex_AG_panel2
GAD2
rs2236418
chr10:26545502
A/G
intron
48_plex_AG_panel1
GAD2
rs992990
chr10:26607187
A/C
intron
12plex A/C
GHRELIN
rs696217
chr3:10306457
G/T
Leu72Met
12plex A/C
GHRELIN
rs34911341
chr3:10306519
C/T
intron
48_plex_AG_panel1
Genotyping method
 Multiplex PCR, single base extension
 Beckman GenomeLab SNPstream Genotyping System
Anneal
Extend
Detect
Gedeon Richter Ltd.-Semmelweis University
SNP Core facility (http://www.dgci.sote.hu/en )
Beckman GenomeLab SNPstream Genotyping System
Throughput
4,608 to 800,000 genotypes in 24 hours (12 plex)
18,432 to 3,200,000 genotypes in 24 hours (48 plex)
Multiplex level
12 –48 plex PCR and Primer extension
Statistical analysis
 Two steps:
 Standard statistical methods: logistic regression,
chi square
 Bayesian Multilevel Analysis
Results
Genes and SNPs associated with obesity in the whole
population (9 SNPs in 6 genes)
Gene
rs
Position
Allele
Function
ALOX5
rs7913948
chr10:45188895
A/G
5-lipoxygenase
ALOX5
rs745986
chr10:45198914
A/G
5-lipoxygenase
A/G
Fat mass and obesity associated
FTO
rs17817288 chr16:52365264
Fat mass and obesity associated
FTO
rs8050136
chr16:52373776
A/C
FTO
rs7201850
chr16:52379362
C/T
HSD11B1
rs2235543
chr1:206249063
C/T
hydroxysteroid 11-beta dehydrogenase 1
IGF2
rs680
chr11:2110210
A/G
Insulin like growth factor 2
TNF
rs361525
chr6:31651080
A/G
Tumor necrosis factor
ZFP90
rs864741
chr16:67134078
A/G
Zinc finger protein 90
Fat mass and obesity associated
Different results in men and women
 Only in women: ALOX5, ALOX5AP, ZFP90, ACE,
UCP3
 Only in men: HSD11B
 In both: FTO
Heritability is gender specific
 Girls whose mothers are classified as clinically obese
are significantly more likely obese in childhood, with a
similar relationship existing between obese fathers
and their sons.
 Trend does not exist between mothers and their sons
and fathers and their daughters
FTO = fat mass and obesity associated
OR = 3.0 (2.1-4.2) P<5x10-10!
OR = 0.33 (0.23-0.47)
 All obesity GWA identified FTO
 Exact function is not known
 Expressed in CNS (esp.: hippocampus, cerebellum and
hypothalamus)
 FTO mutant mice:
 reduced fat mass
 increased energy expenditure
 unchanged physical activity.
ALOX5 OR=1.5 (1.1-1.9);
OR = 0.43 (0.,25-0.74)
 Synthesis of leukotrienes from arachidonic
acid.
 Alox5 −/− mice had significantly increased
fat mass, plasma leptin levels and fasting
glucose levels, but lower fasting insulin
levels
IGF2
OR = 1.5 (1.1-2.2)
 This gene encodes a member of the insulin
family of polypeptide growth factors that is
involved in development and growth.
 It is an imprinted gene and is expressed
only from the paternally inherited allele.
 It is a candidate gene for eating disorders
Zfp90
OR = 1.72 (1.03-2.88)
 These preliminary data suggest that Zfp90 may
have an uncharacterized role in the regulation of
obesity traits.
 Mice with extra copies of ZFP90 had higher
overall fat levels than wild-type controls.
 ZFP90 could be antagonized to treat obesity
Next
 Bayesian Multilevel
Analysis (BMLA)
 BMLA enables the
analysis of relevance at
different abstraction
levels: model-based
pairwise relevance,
relevance of variable
sets, and interaction
models of relevant
variables.
50 clinical parameters , 120
SNPs and expression data
Summary
 Genetic polymorphisms play an important role in the
susceptibility of obesity in the Hungarian
population.
 There are considerable differences between men
and women in the genetic background.
 Those genes and pathways associated with obesity
are potential targets for tailoring therapy for a
healthier body weight.