1 Imaging Genetics: Heritability, Linkage & Association David C. Glahn, PhD Olin Neuropsychiatry Research Center & Department of Psychiatry, Yale University July 17, 2011
2 Memory Activation & APOE ε4 Risk gene for Alzheimer s 16 APOE ε4 14 APOE ε3 Bookheimer et al., N Engl J Med, 2000
3 Fear Response & Serotonin Transporter Gene (SLC6A4) Hariri et al., Science, 2002
4 Human Genome 23 Chromosomes ~20-25,000 genes ~3 billion base pairs
5 Approaches to Genotyping Candidate genes: genotype only markers in genes potentially related to the trait. Pro: fast and easy, may be able to be more thorough with a higher density of markers Con: must get lucky in choice of genes, lower potential for something really novel Genome screen: genotype anonymous markers spanning the genome at regular intervals Pro: can identify previously unknown genes, covers all of the possibilities Con: slower and more expensive, may have lower marker density which could translate to less power
6 Questions for the Study of Complex Trait Genetics 1) Is this trait influenced by genetic factors? How strong are these genetic influences? 2) Which traits are influenced by the same genes? 3) Where are the genes that influence a trait? 4) What are the specific genes that influence the trait? 5) What specific genetic variants influence the trait and how do they interact with each other and with the environment?
7 Question 1: Heritability Is this trait influenced by genetic factors? How strong are these genetic influences?
9 Variance Decomposition σp=σg +σe σg=σa +σd µ σ 2 µ ^= Σx i / n σ^ 2 = Σ(x - µ) ^ 2 / n Almasy & Blangero, Am J Hum Genet, σe =σc +σeu σ 2 p = total phenotypic 2 = genetic σ g σ e 2 = environmental 2 = additive genetic σ a σ 2 d = dominance
10 Narrow-Sense Heritability (h 2 ) Heritability (h 2 ): the proportion of the phenotypic variance in a trait attributable to the additive effects of genes. 2 h 2 = σ a σ 2 p
11 Conceptualizing Heritability Heritability estimates vary between 0 and 1 0, genetic factors do not influence trait variance 1, trait variance is completely under genetic control If h 2 =0.5, then 50% of phenotypic variation is due to genetic variation. Not that the trait is 50% caused by genetics Stronger heritability does not imply simple genetics
12 Estimating Heritability with Twins Falconer s Method h 2 =2*(r MZ -r DZ ) r MZ = correlation between monozygotic co-twins r DZ = correlation between dizygotic co-twins
13 Variance Component Approach Modeling the Phenotype: p =µ+σβ i x i + µ Population mean a +d +e β Regression coefficients x Scaled covariates a Additive genetic effects d Dominance genetic effects e Random environmental effects
14 Simple Kinship Matrix Dad 1 2 Mom 3 D M D 1 0 ½ ½ ½ M 0 1 ½ ½ ½ 1 ½ ½ 1 ½ ½ 2 ½ ½ ½ 1 ½ 3 ½ ½ ½ ½ 1
18 Cortical Thickness & Surface Area Winkler et al., NeuroImage, family members
19 White-Matter Tracts (DTI) h 2 Kochunov et al., NeuroImage, family members
20 White-Matter Hyperintensity h 2 Total Cranial: 0.91 Brain Parenchyma: 0.92 WMH: 0.73 Carmelli et al., Stroke, MZ / 71 DZ pairs
21 Task Based fmri Heritability Koten et al., Science, MZ pairs / 10 sibs
22 Resting State fmri Heritability h 2 = Glahn et al., Proc Nat Sci USA, family members
23 Limitations of Heritability Estimates 1. Heritability is a population level parameter, summarizing the strength of genetic influences on variation in a trait among members of the population. It doesn t tell you anything about particular individuals. 2. Heritability is an aggregate of the effects of multiple genes. It tells you nothing about how many genes influence a phenotype. A high heritability is not necessarily better if it is due to many, many genes.
24 Question 2: Pleiotropy Which traits are influenced by the same genes?
25 Levels of Pleiotropy No Pleiotropy Trait 1 Trait 2 Partial Pleiotropy Trait 1 Trait 2 Full Pleiotropy Trait 1 Trait 2
26 Genetic Correlation (Pleiotropy) Genetic correlation (ρ g ): a measure of the overlap in genetic effects between traits. ρ g varies from -1 to 1 0 = no pleiotropy; -1 or 1 = complete pleiotropy
27 Cortical Thickness & Surface Area Schmitt et al., Cerebral Cortex, MZ / 47 DZ / 228 others Winkler et al., NeuroImage, family members
28 Cortical Thinning & IQ ρ g = 1.0/1.0 ρ g = 1.0/0.7 Brans et al., J Neurosci, MZ / 84 DZ pairs
29 White Matter Tracts & Working Memory Superior longitudinal fasciculus Spatial DRT: ρ g = Karlsgodt et al., J Neurosci, family members
30 Question 3: Localization Where are the genes that influence a trait?
31 Two Common Methods for Gene Localization Linkage analyses: test for co-segregation of phenotype and genotype within families - a function of physical connections of genes on chromosomes Association analyses: test for deviations of phenotype-genotype combinations from that predicted by their separate frequencies - a function of linkage disequilibrium created by population history
32 Association Studies Pro: Can be done with unrelated individuals. Statistical methods easy and fast. May be able to detect loci of smaller effect with a given sample size. Con: Requires disequilibrium, which may not be present, making power difficult to estimate. Susceptible to allelic heterogeneity.
33 Genome Wide Association Tests for correlation between genotype and phenotype Association analyses work when: 1) your genotyped marker is a functional polymorphism 2) your genotyped marker is in disequilibrium with a functional polymorphism Currently: 700K to 1.5Mil SNPs
34 Linkage Disequilibrium (LD) Linkage disequilibrium is the non-random association of alleles at two or more loci LD = the population frequency of allelic combinations the expected combinations from random formation of haplotypes Level of LD is influenced by a number of factors including genetic linkage, selection, the rate of recombination, the rate of mutation, genetic drift, non-random mating, and population structure. LD is unpredictable
35 Association, LD & Haplotypes Unlikely that functional variants are typed Association studies are dependent on LD between a genotyped marker and a functional variant. May change with complete sequencing
36 Multiple testing: p-values A p-value of 0.05 implies that 5% of the time we will reject the null hypothesis (i.e. conclude that we have an association) when the null hypothesis is actually correct If we test 100 SNPs and each time we use a p- value of 0.05 as our cutoff for significance, we would expect 5 of those SNPs to be significant (p < 0.05) just by chance
37 Multiple testing The simplest correction is the Bonferroni: multiply each p-value by the total number of tests, or divide the significance threshold required by the number of tests (0.05 / #). For 550K SNPs, requires p=1.2x10-7 This maintains an experiment-wide significance threshold, but may be too conservative when the tests are correlated, as they might be if some of the markers tested are in LD with each other.
38 Cortical Thickness GWA Association found at rs (p=4.0x10-10), chr 13q31, near SLIT- & NTRK-like family, member 6. SLITRKs are expressed predominantly in neural tissues and have neurite-modulating activity. Associated with Tourette's Syndrome Glahn et al., ACNP, 2009
41 Limitations of Association A QTL may be in equilibrium with the other polymorphisms surrounding it. Disequilibrium need not be present. Since LD need not be present, negative association results have implications only for the marker you have tested, lack of association does not exclude the gene or region. Population Stratification: If the sample contains multiple populations that differ in the trait of interest, any locus whose allele frequencies differ between the populations will show association
42 Example: Hypertension AB AB AB AA AA AA AB AB African Americans 70% A, 30% B AB AB BB BB AA AA AB AB European Americans 50% A, 50% B
43 Example: Hypertension AB AB AA AB Affected 64% A, 36% B AB AA AB AA AB AB BB BB AA AA AB AB Unaffected 56% A, 44% B
44 Minimizing Limitations of Association 1. Match cases and controls carefully or try to obtain subjects from a single well defined population. 2. Use one of a variety of statistical approaches designed to deal with population stratification (e.g. TDT, genomic control)
45 Linkage Studies Pro: Power to find a gene can be more easily quantified. Guaranteed to work if the sample size is large enough. Not influenced by allelic heterogeneity. Con: Need a large sample of related individuals. Large enough may be too large to be practical.
46 Genetic Linkage Defined Genetic loci that are physically close to one another tend to stay together during meiosis. Independent assortment occurs when the genes on different chromosomes are separated by a great enough distance on the same chromosome that recombination occurs at least half of the time. An exception to independent assortment develops when genes appear near one another on the same chromosome. When genes occur on the same chromosome, they are usually inherited as a single unit. Genes inherited in this way are said to be linked, and are referred to as "linkage groups.
47 Measuring Linkage: Lod Score LOD = log 10 (probability of birth sequence with a given linkage value/probability of birth sequence with no linkage) LOD = log 10 ((1-θ) NR x θ R )/0.5 NR+R NR denotes the number of non-recombinant offspring, R denotes the number of recombinant offspring. Theta = recombinant fraction= R / (NR + R) A LOD score >=3.0 is considered evidence for linkage A LOD score of 3 indicates 1000 to 1 odds that the linkage being observed did not occur by chance A LOD score <=-2.0 is considered evidence to exclude linkage
48 Linkage with White-Matter Hyperintensitites Bivariate linkage for subcortical & ependymal HWM volumes (log of odds=2.12) on chr 1 at 288 cm. Kochunov et al., Stroke, family members
49 Linkage with White-Matter Hyperintensitites/Blood Pressure LOD Kochunov et al., Stroke, family members
50 Linkage vs. Association Association: you re testing for an excess of a specific combination of alleles at two loci. The same alleles must be traveling together at a population level. Detects effects of common variants. Linkage: you re testing for an excess of the parental type. That parental type (i.e. the alleles traveling together) could be different in every family (i.e. linkage equilibrium) and you would still get linkage. Can detect cumulative effect of multiple variants (including rare variants).
51 Determining Linkage Power The power to map a QTL in a human linkage study is a function of: 1. locus-specific heritability (genetic signalto-noise ratio) 2. Sample size 3. Pedigree size and complexity
52 Sample size required for 80% power to detect linkage to a QTL at a LOD of 3
53 Question 4: Identification What specific genes influence the trait?
54 Identifying a Causal Gene Once a significant QTL is identified, additional genetic tests are needed to determine the exact identity of the gene Association: identifies a genomic region of ~500kb (250kb to either side of the association) determined by the general extent of linkage disequilibrium Linkage: detect the cumulative additive genetic signal of all functional variants within a much larger genomic region (e.g Mb)
55 VPS13A: A Candidate Gene for Brain Structure/Function VPS13A is a 73 exon gene localizing to chromosome 9q21 Involved in choreaacanthocytosis Schizophrenia OCD Frontal lobe functioning 3174 amino acid protein Bellis et al., ASHB, 2009
56 Association Analysis: VPS13A SNPs and Frontal Lobe Volume rs rs Bellis et al., ASHB, 2009
57 Take Home Message This may be the most important thing I say in this lecture. There is no one size fits all in genetic analysis of complex traits. Laura Almasy
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