Abstract
Many genetic loci and SNPs associated with many common complex human diseases and traits are now identified. The total genetic variance explained by these loci for a trait or disease, however, has often been very small. Much of the "missing heritability" has been revealed to be hidden in the genome among the large number of variants with small effects. Several recent studies have reported the presence of multiple independent SNPs and genetic heterogeneity in trait-associated loci. It is therefore reasonable to speculate that such a phenomenon could be common among loci known to be associated with a complex trait or disease. For testing this hypothesis, a total of 117 loci known to be associated with rheumatoid arthritis (RA), Crohn disease (CD), type 1 diabetes (T1D), or type 2 diabetes (T2D) were selected. The presence of multiple independent effects was assessed in the case-control samples genotyped by the Wellcome Trust Case Control Consortium study and imputed with SNP genotype information from the HapMap Project and the 1000 Genomes Project. Eleven loci with evidence of multiple independent effects were identified in the study, and the number was expected to increase at larger sample sizes and improved statistical power. The variance explained by the multiple effects in a locus was much higher than the variance explained by the single reported SNP effect. The results thus significantly improve our understanding of the allelic structure of these individual disease-associated loci, as well as our knowledge of the general genetic mechanisms of common complex traits and diseases.
Highlights
Many genetic loci and SNPs associated with many common complex human diseases and traits are identified
Over the past few years, genome-wide association studies (GWASs) have been used for identifying a large number of common genetic loci for many common complex traits and diseases. These loci, contribute only a small proportion of the disease variability, leaving a large amount of disease heritability unexplained.[1]. This so-called ‘‘missing heritability’’ issue has been partly demystified through methods that take into account genetic information of common variants accumulated across biological pathways[2] or across the entire genome among the large numbers of variants of small effects,[3,4] rather than just the individual confirmed disease-susceptibility loci
With human height, a complex trait with an estimated heritability of 80%, it was shown that genomewide information of common variants could explain 45% of heritability, whereas only 5% could be explained by the 50 confirmed associated loci at the time[3] and about 10% could be explained by the hundreds of variants clustered in genomic loci and biological pathways affecting the trait.[5]
Summary
Presence of Multiple Independent Effects in Risk Loci of Common Complex Human Diseases. It has been noticed that for the majority of individual associated loci, there is usually only a single common SNP or allele to be identified and reported It is highly possible, that multiple independent effects could be present in a gene or locus that is associated with a trait. The penalized and conditional regression-analysis procedures were applied to several disease-associated loci known to have multiple independent associations This included the RA-associated locus OLIG3-TNFAIP3.8,9 The independent effects of rs6920220 and rs10499194 were first reported by Plenge et al.[8] and later confirmed by Orozco et al.[9] in a different population sample of 3,962 RA patients and 3,531 healthy controls (in this latter study, rs13207033 was used as a surrogate for rs104991949). The independence between rs6920220 and rs10499194/rs13207033 was not significant under the regression analysis, indicating that the current sample set was not sufficiently powerful for detecting such
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