Evaluating empirical bounds on complex disease genetic architecture

Abstract

The genetic architecture of human diseases governs the success of genetic mapping and the future of personalized medicine. Although numerous studies have queried the genetic basis of common disease, contradictory hypotheses have been advocated about features of genetic architecture (e.g., the contribution of rare vs. common variants). We developed an integrated simulation framework, calibrated to empirical data, to enable systematic evaluation of such hypotheses. For type 2 diabetes (T2D), two simple parameters – (a) the target size for causal mutation and (b) the coupling between selection and phenotypic effect – define a broad space of architectures. While extreme models are excluded, many models remain consistent with epidemiology, linkage, and genome-wide association studies for T2D, including those where rare variants explain little (<25%) or most (>80%) of heritability. Ongoing sequencing and genotyping studies will further constrain architecture, but very large samples (e.g., >250K unselected individuals) will be required to localize most of the heritability underlying traits like T2D.

A model of compound heterozygous, loss-of-function alleles is broadly consistent with observations from complex-disease GWAS datasets

“…Rather, this correlation is context dependent, varying according to the current genetic burden of the population, the genetic background in which the variant is present and random environmental noise. However, if we re-parameterized our model in terms of [18], then we would have τ 0.5 (Gaussian function is greater than or equal to its quadratic approximation), which is consistent with recent attempts at estimating that parameter [20,65]. Our approach is reflective of weak selection acting directly on the complex disease phenotype, but the degree to which selection acts on genotype is an outcome of the model.…”

“…The exact relationship between rare alleles [4,17,26,62,63], and the demographic and/or selective scenarios from which they arose [21,22,64], and the genetic architecture of common complex diseases in humans is an active area of research. An important parameter dictating the relationships between demography, natural selection, and complex disease risk is the degree of correlation between a variants effect on the disease trait and its effect on fitness [18,[20][21][22]. In our simulations, we do not impose an explicit degree of correlation between the phenotypic and fitness effects of a variant.…”

“…A complementary approach is to estimate the heritability explained by genotyped (and imputed) markers (SNPs) under different population sampling schemes [14,15]. Stratifying markers by minor allele frequency (MAF) prior to performing SNP-based heritability estimation allows the partitioning of genetic variation across the allele frequency spectrum to be estimated [16], which is an important summary of the genetic architecture of a complex trait [16][17][18][19][20][21][22][23]. This approach has inferred a contribution of rare alleles to genetic variance in both human height and body mass index (BMI) [16], consistent with theoretical work showing that rare alleles will have large effect sizes if fitness effects and trait effects are correlated [18,[20][21][22][23][24][25].…”

Genetic Architecture of Type 2 Diabetes

“…Range of simulated disease models-Following our previously published framework 40 , we conducted population genetic simulations of T2D architecture using the forward simulation program ForSim 86 . We assumed T2D prevalence 8% and heritability ~45%, and chose the mutation rate, recombination rate, a gamma distribution of selection coefficients, and other parameters of demographic history by fitting the simulated site frequency spectrum to empirical high coverage exome sequence data from GoT2D.…”

“…We simulated genotypes for a current population of effective size 500,000 individuals 40 and selected potential disease risk variants from those under selection appropriate to the intended target size. Each risk variant received a diseasespecific effect size depending on the selection coefficient under which it evolved and the assumed degree of dependence between selection and effect size.…”