Quantitative Genetic & Heritability
What is the precise definition of heritability given in class?
Heritability is the proportion of phenotypic variance in a population that is accounted for by genetic differences among individuals.
Why are twin studies useful.
Considered a “natural experiment” because they leverage a naturally occurring difference in genetic relatedness between two types of twins who typically share very similar environments. Monozygotic (MZ) twins share 100% of their genes, whereas dizygotic (DZ) twins share, on average, 50%. Since both types are reared together, any excess similarity of MZ twins compared to DZ twins can be attributed to genetic influences rather than environmental ones.
Why are adoption studies quasi-interventions?
Because they naturally separate genetic and environmental influences without requiring an experimental manipulation. By placing genetically related children (who share genes with their biological parents) into different rearing environments, adoption acts as a kind of “natural experiment” that mimics random assignment.
What is a haplotype?
A group of alleles at different loci that are inherited together on the same chromosome.
What is missing heritability?
Refers to the observation that heritability estimates from twin and family studies are typically much higher than the proportion of variance explained by SNPs identified through genome–wide association studies (GWAS).
What is the difference between monochorionic and dichorionic twins?
Monochorionic (MC) twins share a single chorion (outer fetal membrane) and therefore a single placenta, while dichorionic (DC) twins each have their own chorion and placenta.
Equal Environnments Assumption
MZ and DZ twins experience equally similar environments relevant to the trait being studied.
Problem: If MZ twins are treated more similarly or share more similar environments in ways that affect the phenotype, their greater resemblance could be due to environment rather than genetics.
Evidence: Empirical research generally supports the EEA. When environmental similarity is measured directly (e.g., being dressed alike, sharing friends).
Gener environment interaction.
Occurs when the effect of an individual's genotype on a trait depends on the environment, or conversely, when the effect of an environmental exposure depends on genotype. In other words, genetic differences moderate sensitivity or responsiveness to environmental influences.
What is the candidate gene approach?
An early hypothesis-driven method for identifying genetic variants associated with complex traits or diseases. Researchers selected specific genes for study based on prior biological or theoretical reasoning – for example, genes thought to be involved in neurotransmission for psychiatric disorders – and tested whether variants within those genes were more common among affected individuals than controls.
What is meant by genetic architecture of complex/multifactorial traits?
Refers to the specific pattern and distribution of genetic variation that contributes to differences in that trait within a population.
Key features of genetic architecture include: (1) the number of contributing variants (2) their allele frequencies, (3) the magnitude and direction of their effects on the phenotype, and (4) the mechanisms by which they influence risk.
Definition of multifactorial/polygenic inheritance.
Phenotypes that are influenced by many genes of small, equal, additive effect, resulting in continuous quantitative variation
Implications of adoption studies.
If adopted children resemble their biological parents, this suggests that genetic factors contribute to the trait. If they resemble their adoptive parents, this indicates that shared environmental influences are important.
Basic function of MAO-A gene.
Responsible for breaking down neurotransmitters such as serotonin, dopamine, and norepinephrine in the brain. It helps regulate levels of these monoamines, which are involved in mood, arousal, and impulse control.
What is a genome wide association study?
An observational design used to identify statistical associations between genetic variants (usually SNPs) and a phenotype across the entire genome. Rather than focusing on specific candidate genes, GWAS scans millions of SNPs in large samples of unrelated individuals to find variants that occur more frequently in people with a given trait or disorder than in those without it.
What range of effect sizes do common variants identified in a GWAS typically have on the phenotype? What about rare variants?
Common variants almost always have very small effect sizes. Individual SNPs usually explain less than 0.1% of the variance in a quantitative trait.
By contrast, rare variants (minor allele frequencies < 1%) tend to have larger effect sizes on average, since deleterious mutations with strong effects are kept rare by natural selection.
Distinction between broad-sense heritability and narrow-sense heritability.
(H2) includes all genetic sources of variance
(h2N) includes only the additive genetic component (a2)
What are the basic findings of the Polderman et al. (2015) meta-analysis of twin studies?
The mean heritability across all traits was approximately 49%, indicating that about half of the variation in human characteristics can be attributed to genetic differences.
Reactive or evoactive rGE.
Occurs when an individual’s genetically influenced traits evoke specific responses from others. For example, a temperamentally irritable child may elicit more conflict or harsh discipline from parents.
Linkage disequilibrium.
Refers to the non-random, population-level association between alleles at linked loci – that is, certain combinations of alleles occur together more (or less) often than expected by chance. LD arises because new mutations appear on specific chromosomal backgrounds (haplotypes) and remain correlated with nearby loci until recombination gradually breaks down those associations over generations.
What is meant by the common disease common variant model and the common disease rare variant model?
The common disease–common variant (CDCV) model proposes that common, complex disorders are largely influenced by many common genetic variants.
The common disease–rare variant (CDRV) model, in contrast, suggests that complex disorders are caused primarily by many rare variants, each exerting a relatively large effect on risk.
GWAS is generally premised on the common disease–common variant model,
Biometric decomposition of a phenotype.
1.0 = (a2 + d2 + i2) + (c2 + e2)
Genetic components: a2 = additive genetic variance, d2 = dominance variance, i2 = epistatic (interaction) variance
Environmental components: c2 = shared environmental variance, e2 = non-shared (unique) environmental variance
Falconers equations.
Provide a way to estimate the proportions of variance due to additive genetic (A), shared environmental (C), and non-shared environmental (E) influences from twin correlations.
a2 = 2(rMZ − rDZ)
c2 = 2rDZ − rMZ
Difference between gene environment correlation and interaction.
A gene–environment correlation (rGE) occurs when genetic differences are associated with systematic differences in environmental exposure. In other words, people’s genotypes influence the kinds of environments they experience. This differs from a gene–environment interaction (G×E), in which genes and environments combine to influence a trait – rGE is about exposure to environments, while G×E is about responsiveness to them.
How are meiosis/recombination, number of generations, and physical distance in the genome are relevant to the concept of LD.
During meiosis, homologous chromosomes exchange segments through recombination. Each recombination event can break the association between alleles at different loci.
The number of generations also affects LD because recombination accumulates over time.
The longer a population has existed since a mutation first arose, the more opportunities recombination has had to erode the association between that mutation and its original haplotype.
Recombination events (due to distance or many generations) break it down.
How are polygenic risk scores computed?
The SNPs included are typically weighted by their association strength from the discovery GWAS, and the score often includes many more SNPs than those that reached genome–wide significance (e.g., all SNPs with p < .05).