Influences on assortative mating

Height associated variants demonstrate assortative mating in human populations

Understanding human mating patterns, which can affect population genetic structure, is important for correctly modeling populations and performing genetic association studies. Prior studies of assortative mating in humans focused on trait similarity among spouses and relatives via phenotypic correlations. Limited research has quantified the genetic consequences of assortative mating. The degree to which the non-random mating influences genetic architecture remains unclear. Here, we studied genetic variants associated with human height to assess the degree of height-related assortative mating in European-American and African-American populations. We compared the inbreeding coefficient estimated using known height associated variants with that calculated from frequency matched sets of random variants. We observed significantly higher inbreeding coefficients for the height associated variants than from frequency matched random variants (P < 0.05), demonstrating height-related assortative mating in both populations.

Structured mating: Patterns and implications

Genetic similarity of spouses can reflect factors influencing mate choice, such as physical/behavioral characteristics, and patterns of social endogamy. Spouse correlations for both genetic ancestry and measured traits may impact genotype distributions (Hardy Weinberg and linkage equilibrium), and therefore genetic association studies. Here we evaluate white spouse-pairs from the Framingham Heart Study (FHS) original and offspring cohorts (N = 124 and 755, respectively) to explore spousal genetic similarity and its consequences. Two principal components (PCs) of the genome-wide association (GWA) data were identified, with the first (PC1) delineating clines of Northern/Western to Southern European ancestry and the second (PC2) delineating clines of Ashkenazi Jewish ancestry. In the original (older) cohort, there was a striking positive correlation between the spouses in PC1 (r = 0.73, P = 3x10^-22) and also for PC2 (r = 0.80, P = 7x10^-29). In the offspring cohort, the spouse correlations were lower but still highly significant for PC1 (r = 0.38, P = 7x10^-28) and for PC2 (r = 0.45, P = 2x10^-39). We observed significant Hardy-Weinberg disequilibrium for single nucleotide polymorphisms (SNPs) loading heavily on PC1 and PC2 across 3 generations, and also significant linkage disequilibrium between unlinked SNPs; both decreased with time, consistent with reduced ancestral endogamy over generations and congruent with theoretical calculations. Ignoring ancestry, estimates of spouse kinship have a mean significantly greater than 0, and more so in the earlier generations. Adjusting kinship estimates for genetic ancestry through the use of PCs led to a mean spouse kinship not different from 0, demonstrating that spouse genetic similarity could be fully attributed to ancestral assortative mating. These findings also have significance for studies of heritability that are based on distantly related individuals (kinship less than 0.05), as we also demonstrate the poor correlation of kinship estimates in that range when ancestry is or is not taken into account.

We analyzed three generations of whites from the Framingham Heart Study (FHS) using genome-wide genotype data to characterize their genetic ancestry. By examination of spouse-pairs, we observed that individuals of Northern/Western European, Southern European and Ashkenazi ancestry preferentially chose spouses of the same ancestry, however, the degree of endogamy decreased in each successive generation, especially between Northern/Western and Southern Europeans. We then showed that the mating pattern results in Hardy-Weinberg disequilibrium (HWD) at ancestrally-informative SNPs, and also results in linkage disequilibrium (LD) between unlinked loci. The HWD and LD decrease as theoretically expected with the decrease in endogamy noted in each generation. In the FHS sample, spouse genetic similarity can be explained by ancestry-related assortative mating.

Phenotypic assortative mating in segregation analysis

A model of phenotypic assortative mating was developed for application in segregation analysis. The model assumed a constant spouse correlation across the range of a quantitative trait or the liability to a discrete trait. Four traits were analyzed to evaluate: 1) the feasibility of applying likelihood analysis to pedigree data in order to distinguish between assortative mating and shared environmental effects as the source of spouse correlation; and 2) the impact on segregation analysis of the failure to account for either assortative mating or shared environmental effects, as appropriate. Height ratio (the ratio of sitting to standing height) and eye color comprised the traits for which the observed spouse correlation reflected assortative mating; serum cholesterol and peptic ulcers (with genotypes defined by the ABO blood group) comprised the traits for which the observed spouse correlation reflected shared environmental effects. For all four traits the test statistics agreed with the known cause of spouse correlation; however, significance was not attained for height ratio or serum cholesterol. The ability to distinguish between the causes of spouse correlation in pedigree data presumably depends on trait and sample characteristics which remain to be delineated. Despite significant spouse correlation, its omission from the segregation analysis model did not undermine the inference of major locus inheritance for any of the four traits. However, the lack of an impact for these traits does not preclude an impact for other traits of ignoring the appropriate spouse correlation in segregation analysis.