heritability

Speed D, Hemani G, Johnson MR & Balding DJ 2012 Improved heritability estimation from genome-wide SNPs. Am J Hum Genet 91:1011-1021.

• over half the heritability of human height can be attributed to the ~300,000 SNPs on a genome-wide genotyping array
• only 5%–10% can be explained by SNPs reaching genome-wide significance
• contributions to h² are overestimated from causal variants in regions of high LD and are underestimated in regions of low LD
• our LD adjustment revises downward the h² estimate for immune-related diseases, as expected because of high LD in the major-histocompatibility region, but increases it for some nonimmune diseases

• patterns of LD are strongly linked to MAF
• the signals from low-frequency variants are less replicated than those from high-frequency variants
• h² will be too low for traits with predominantly low-frequency causal variants and will be too high for those with predominantly high-frequency causal variants
• we propose a different adjustment in which SNPs are weighted according to how well they are tagged by their neighbors
• we reanalyzed the height data⁵ with our LD-adjusted kinship matrix
• ĥ² changed only slightly
• any underestimation of contributions to h² in low-LD regions is balanced by overestimation elsewhere
• for both hypertension and type 2 diabetes, ĥ² increased by nearly a quarter when we used our LD-adjusted kinships instead of a standard kinship matrix
• these traits' causal variants tend to be poorly tagged and thus have a lower-than-average MAF
• for rheumatoid arthritis, ĥ² was reduced by one-tenth when we used LD-adjusted kinships
• this disease, along with type 1 diabetes, has major-histocompatibility-complex (MHC) risk variants that tend to be well tagged
• the estimated heritability attributed to chromosome 6 was substantially reduced for both these diseases