Download Non-Mendelian Inheritance: Multifactoril, …

Spectrum of Human Characters
Non-Mendelian Inheritance:
Multifactoril, …
„ Traits/ diseases:
¾ Monogenic/ Mendelian
¾ Polygenic
¾ Environmental
¾ Multifactorial
Mohammad Keramatipour MD, PhD
„ Mode of inheritance:
¾ Mendelian/ monogenic
¾ Non
Non--classical monogenic
g
¾ Oligogenic (digenic),
polygenic
¾ Multifactorial
[email protected]
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Genetics Disorders
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Classical Monogenic Inheritance
„ Definition and classification??
„ Simple comparison of frequency of different types of genetic
di
disease
((population
l ti prevalence/1000
prevalence/
l
/1000))
/1000
„ Properties:
¾ Different phenotype result from alternative genotypes of a single
gene
¾ Number of genotypes & phenotypes are small
¾ Disorders due to genome and chromosome mutations: 3.8
¾ Single
Single--gene disorders: 20
¾ Disorders with multifactorial inheritance: ~ 600
8 Also known as complex
p
or common disorders
¾ Relationship between genotype and phenotype is simple
„ The main genetic contribution to morbidity and mortality is
through disorders with multifactorial inheritance
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¾ Well
Well--suited for analysis using crosses and pedigree
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NonNon
-classic Monogenic Inheritance
Multifactorial Inheritance
„ Multiple genetic and environmental factors are involved
¾ Environmental influence , much more than single gene traits
„ Monogenic
g
disorders with nonnon-classic ((non(non-mendelian))
inheritance
¾ Triplet
Triplet--repeat disorders (unstable repeat expansions)
„ Complex
p
inheritance:
¾ Single genotype: many possible phenotypes
¾ Single phenotype: caused by many possible genotypes
¾ Effects of segregation of alleles of one gene may be masked by
effects of other genes
¾ Such traits can not be studied with usual pedigree methods
¾ Disorders caused by mutations in mitochondrial genes
¾ Disorders associated with genomic imprinting
¾ Disorders associated with uniparental disomy
¾ Disorders associated with mosaicism
8 Somatic mosaicism
8 Germline mosaicism
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Traits with Complex Inheritance
Traits with Complex Inheritance
„ Three categories of traits show complex inheritance:
¾ Threshold traits (discontinuous,
discontinuous dichotomous,
dichotomous discrete
discrete,
¾ Continuous traits (quantitative):
8 No clear breaks between few discrete phenotypic variation
8 Measurable: blood pressure, body mass index, height, weight
qualitative):
8 Have onlyy two or few classes
8 Either present or absent (affected, nonnon-affected)
8 Each individual has an underlying risk or liability to express it
8 If the
th underlying
d l i liability
li bilit iis hi
high
h enough
h ((over th
the th
threshold),
h ld) th
the
trait will be expressed
¾ Meristic traits
traits::
8 Phenotype is found by counting
8 Such as number of fingerprint ridges, number of bristles on a fly
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A Bit of History
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A Bit of History
„ Galton experiments:
„ Around 1900
1900,, there were two
camps:
p ((1900
1900--1918)
1918)
¾ Francis Galton & studying family resemblances, quantifying
observation and applying statistical analysis
¾ “Hereditary
“
Talent and C
Character”,article
”
in 1865
1865,, and then a
book “Hereditary Genius” in 1869
¾ Biometricians:
8 Continuous
C i
or quantitative
i i traits
i
¾ Mendelians:
8 Discrete traits
¾ 1884
1884:: Galton compared the physical attributes of parents and
children and established of the degree of correlation between
relative
¾ By 1900 the idea of continuous or quantitative characters
introduced
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¾ Are quantitative traits inherited in
the same way as discrete traits?
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1918,, Reconciliation !
1918
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Polygenic Theory of Quantitative Traits
„ What does it say?
¾ Any character that depend on the additive action of a large
„ Reconciliation:
¾ Multiple loci (genes) contribute to variation
number of individually small independent causes (genes??)
shows a Normal (Gaussian) distribution in the population
„ R. A. Fisher, 1918:
1918:
¾ Traits governed by a large number of Mendelian factors
(polygenic) display the continuous nature, quantitative variation
and family correlation
¾ Falconer extended this model to dichotomous characters
„ A Normal distribution is characterized by two parameters:
¾ The mean:
mean: the value that is the peak of the curve
¾ The variance (or its square root, the standard deviation):
deviation): is a
measure of the degree of spread of values to either side of the
mean
¾ Results of Fisher’s and Falconer’s analysis: Polygenic Theory
„ The variance of a measured quantity in the population is called
the total phenotypic variance
of Inheritance for discrete traits
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Heights, A Quantitative Trait
Studying Quantitative Traits
„ Human heights
„ They show a continuum of phenotypic variation (range of
phenotype)
p
yp )
„ Can not be described by small number of discrete categories
„ Alternative way to describe a population is to use a frequency
distribution
¾ Shows the proportion of individuals that fall within a certain
range
g of p
phenotype
yp
¾ Frequency histogram
¾ Normal distribution
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Frequency Distribution
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The Normal Distribution
„ Type of frequency distribution
¾ Symmetric (bell(bell-shaped)
¾ Asymmetric (skewed)
„ The normal distribution curve:
¾ A distribution for an infinite sample in which the trait of interest
varies in a symmetric way around an average value
¾ First recognized in seventeenth century by an English
mathematician,
th
ti i
d
de M
Moivre
i
8 Positive
8 Negative
N
ti
¾ Bimodal symmetry
„ Normal distribution can be characterized by two parameters:
¾ The mean
¾ The variance (or its square root, the standard deviation)
deviation)
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Mean & Variance
Normal Distribution of Quantitative Traits
„ The figure shows a simple model for distribution in the population of a
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„ The mean shows what the average individual looks like
¾ But all individuals don’t
don t look the same
character determined by one, two, three or many loci:
¾ Mean value of the
character is 100 unit
„ Symbolically:
¾ All alleles have
„ The variance show how much individuals differ, or vary from
frequency of 0.5 and
additive/co--dominant
additive/co
effects
each other (indirectly by showing how much on average they
vary from the mean
„ The sum of squared deviation from the mean divided by the
degrees of freedom
¾ Each
E h upper case allele
ll l
adds 5 units to the
value and each lower
case allele subtracts 5
units
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X = ∑ƒi X / N
„ Symbolically:
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Vx = ∑ƒi (X – X ) 2 / (N
(N--1)
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Variance
Standard Deviation (SD)
„ SD is the square root of variance
„ Variances are additive
¾ Total variance for a trait can be
predicted by adding variances
for different factors contribute
to the trait
¾ But is difficult to use
„ Standard deviation shows the proportion of individuals in a
normal distribution with certain differences from the mean
„ Mean and variance can explain
a normal distribution
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The Normal Range
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Regression to the Mean
„ Comparing the heights of
sons and their fathers by
F
Francis
i G
Galton:
lt
„ The concept of normal range of physiological quantities are
fundamental to clinical medicine
„ Specially in assessing health status in children, height,
weight head circumference and … are compared with the
weight,
normal expected measurements for a child’s sex and age
„ Normal range of a quantitative trait is consider between the
two standard deviation above and below the population mean
„ In a Normal distribution approximately
pp
y 5% of p
population
p
will
have measurements more than 2 SD above or below the
population mean
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¾ Taller
Taller--thanthan-average
fathers tended to have
taller--than
taller
than--average sons
¾ The sons tended to be
nearer the
h average h
height
i h
of all men than their
fathers
„ He called this: “regression
Distribution
among children
to the mediocrity”
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Regression to the Mean
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Studying Quantitative Traits
„ From figure in previous slide:
¾ For each class of fathers, mean for the children is halfway
y
between the fathers value and the population mean
¾ For each class of children, mean for the fathers is half way
between the children
children’s
s value and the population mean
¾ The distribution in children is the same as the distribution in the
fathers
„ Main statistics and methods for studying quantitative traits:
¾ Heritability
¾ Familial correlation: r: correlation coefficient
¾ Regression analysis
„ Attention:
¾ This is an introduction to these only!!!
¾ We do not have enough time to discuss these in details
¾ The purpose is to make you just familiar with them
¾ Caution: regression to the mean is a purely statistical
phenomenon not a genetic mechanism
¾ Assumptions to this model:
8 Random mating
8 No dominance
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Distribution
among fathers
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Heritability (h2)
Partitioning Heritability
„ Definition: the proportion of phenotypic variation within a
group of individuals that is due to genetic variation
„ Heritability values are relevant only to particular groups raised
in a particular environment
„ Heritability values change between 0 to 1
„ Then: p
phenotypic
yp variance is due to the additive effects of
¾ 1 means all phenotypic variability is due to genetic variation
genetic variance and environmental variance
¾ 0 means all the variation is due to environmental effects
¾ [ V p = VE + VG ]
„ Aim: analysis of the genetic and environmental components
„ Heritability of a trait is the proportion of the total variance that
that affect quantitative traits
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„ Assumptions:
¾ Genetic and environmental factors are the only components that
determine a trait
¾ Genetic and environmental factors are independent of each
other
is genetic,
genetic that is VG / Vp
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Measuring Heritability
Heritability in Human
„ Comparing the variation in traits between genetically identical
„ Heritability of human traits can be estimated by comparing them
among relatives of known degrees of relatedness (parents,
children, MZ and DZ twins,…)
and g
genetically
y disparate
p
g
groups
p can determine VE and VG
„ Example:
¾ Inbreeding in mice to develop homogeneous strains
„ An example is using twin studies
¾ h2 = (Variance in DZ pairs - variance in MZ pairs) / Variance in DZ
pairs
¾ Examples: h2 = 0.8 for stature, & h2 = 0.70 - 0.80 for body mass
index
¾ When heritability is known, it is easy to determine VE
8 VG = 0, so Vp = VE
¾ Try an example:
8 Determine VE and VG for weight in mice
8 Any idea? Proposal for such study??
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Limitations of Heritability
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Examples of Heritabilities
„ Difficulties in measurement and interpretation
¾ Genetic and environmental factors are not independent
because genetic and social (environmental) disadvantages go
together and the equation [ Vp = VE + VG ], cannot be accurate
¾ Correlation between relatives may not simply reflect their
familial genetic relationship because they share their
environment as well as their genes
¾ It is not accurate to extend the h2 obtained from twins or from an
ethnic group to the whole population or to another population
¾ If socioeconomic conditions change, even h2 obtained from the
same group is not applicable again
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Regression Analysis
Familial Correlation of Quantitative Traits
„ Correlation coefficient:
coefficient: statistic that show how traits are
„ It determines the nature of the relationship (between the two
correlated
variables) and enables us to make prediction from that
¾ Correlation concerns the strength of association (relationship)
between the values of two variables (trait variable among two
groups of individuals)
„ One way is to reduce the data to a straight line, called “line of
best fit” or “regression line”
8 Example: comparing height between fathers and theirs sons
¾ Ranges from -1 to +
+1
1, ziro means no correlation
¾ Positive value: shows direct correlation
¾ Negative value: shows inverse correlation
¾ The absolute number measure the strength of correlation
¾ Correlations do not imply causecause-andand-effect
¾ Correlation
C
l ti reflects
fl t th
the iinfluence
fl
off both
b th heredity
h dit and
d common
environment
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SexSex
-specific Threshold
Polygenic Theory of Discontinuous Traits
„ Falconer’s Polygenic Threshold Model
„ Due ot Falconer theory If a disease
¾ Liability for a trait (disease) is multifactorial/polygenic and follow a
is more common in one sex that is
because of a lower threshold for
that sex and the higher threshold
for the other sex
„ Example: congenital pyloric
stenosis five times more common
stenosis,
in boys
Normal distribution in the population
¾ There is a threshold that whenever exceeded the trait expresses
¾ Medical applications:
8 Recurrence risk in relatives of a proband with such disorders
¾ Threshold is higher for girls than
boys
¾ Relatives of an affected girl have a
higher average susceptibility than
relatives fo an affected boy
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Measuring Familial Aggregation
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Measuring Familial Aggregation
„ The primary characteristic of diseases with complex
„ Case
Case--Control studies
(mutifactorial) inheritance is their familial aggregation
¾ The frequency of disease in families of the cases is compared
„ Assessing familial aggregation:
¾ Measuring relative risk ratio (λr)
¾ Case
Case--control studies
with the its frequency among families of suitable controls who
do not have the disease
8 Parkinson disease: in a study frequency of PD among first and
second degree
g
relatives of p
patients found to be 6.3, and 1.2
among relatives of controls
„ Measuring relative risk ratio (λr)
¾ λr = prevalence of the disease in a relative “r” of a proband /
¾ Limitations:
8 Ascertainment bias
8 Association does not prove causation
population
l i prevalence
l
off the
h di
disease
8 Autism: λ = 2000 for MZ twins & λ = 150 for siblings
g
8 Type 1 diabetes mellitus: λ = 80 for MZ twins & λ = 12 for
siblings
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Genes/Environment Contribution
Complex Disorders in Pedigree
„ Assessing the relative contribution of genes and environment
to complex disease trait
„ Do not follow simple mendelian pattern of inheritance
¾ Concordance among relatives
¾ Comparison of disease incidence in biological relatives to
„ Demonstrate familial aggregation
„ Disease is more common among the close relative of the
unrelated family members
¾ Twin studies
proband
b d and
db
become lless common iin relatives
l i
who
h are lless
closely related
„ Greater concordance for disease is expected among MZ
versus DZ twins
„ Pairs of relatives who share diseasedisease-predisposing genotypes
at relevant loci may still be discordant for phenotype because
of the crucial role of nonnon-genetic factors
8 Disease concordance in MZ twins
8 Comparing concordance of MZ versus DZ twins
8 Twin reared apart
¾ Limitations of twin studies
8 MZ twins do not have precisely identical gene expression
8 Environmental exposure may not be the same
8 Measuring
g disease concordance in MZ twins g
gives an average
g
estimate only
8 Ascertainment bias
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Counseling for Complex Diseases
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Empiric Risk/ General Points
„ Assessment of recurrent risk: empiric risks
„ Empiric
p
risks obtained through
g p
population
p
surveys
y not based
„ Some g
general rules in empiric
p
risk assessments:
¾ Risk to first
first--degree relatives equates to the square
square--root of the
population incidence
¾ Risk
Ri k to sibs
ib and
d offspring
ff i should
h ld b
be about
b
equall
¾ Risk to more distant relatives declines rapidly
¾ Risk increases when there are multiple affected family members
¾ Risk increases with the severity of the disorders
¾ Risk is greater among relatives of the more rarely affected sex
on inheritance theory
„ Empiric risk depend on the specific condition
„ General
G
l considerations:
id ti
¾ Relationship to the affected individual
¾ Severity of the disorder in the proband
„ Example: Pyloric stenosis
„
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Empiric Risk For Complex Disorders
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Thank You For Your Attention!!!
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