Genome-Wide Association Meta-Analysis Using a Recessive Model Illuminates Genetic Architecture of Type 2 Diabetes

Objective: Most genome-wide association studies (GWAS) of complex traits are performed using models with additive allelic effects. Hundreds of loci associated with type 2 diabetes have been identified using this approach. Additive models, however, can miss loci with recessive effects, thereby leaving potentially important genes undiscovered. Research Design and Methods: We conducted the largest GWAS meta-analysis using a recessive model for type 2 diabetes. Our discovery sample included 33,139 cases and 279,507 controls from seven European-ancestry cohorts including the UK Biobank. We then used two additional cohorts, FinnGen and a Danish cohort, for replication. For the most significant recessive signal, we conducted a phenome-wide association study across hundreds of traits to make inferences about the pathophysiology underlying the increased risk seen in homozygous carriers. Results: We identified 51 loci associated with type 2 diabetes, including five variants with recessive effects undetected by prior additive analyses. Two of the five had minor allele frequency less than 5% and were each associated with more than doubled risk. We replicated three of the variants, including one of the low-frequency variants, rs115018790, which had an odds ratio in homozygous carriers of 2.56 (95% CI 2.05-3.19, P=1×10-16) and a stronger effect in men than in women (interaction P=7×10-7). Colocalization analysis linked this signal to reduced expression of the nearby PELO gene, and the signal was associated with multiple diabetes-related traits, with homozygous carriers showing a 10% decrease in LDL and a 20% increase in triglycerides. Conclusions: Our results demonstrate that recessive models, when compared to GWAS using the additive approach, can identify novel loci, including large-effect variants with pathophysiological consequences relevant to type 2 diabetes.

Long runs of homozygosity are associated with Alzheimer’s disease

Long runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimer’s disease (AD); however, their search has been poorly assessed to date. To investigate homozygosity in AD, here we performed a fine-scale ROH analysis using 10 independent cohorts of European ancestry (11,919 AD cases and 9181 controls.) We detected an increase of homozygosity in AD cases compared to controls [βAVROH (CI 95%) = 0.070 (0.037–0.104); P = 3.91 × 10−5; βFROH (CI95%) = 0.043 (0.009–0.076); P = 0.013]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 × 10−16). A significant ROH association with AD risk was detected upstream the HS3ST1 locus (chr4:11,189,482‒11,305,456), (β (CI 95%) = 1.09 (0.48 ‒ 1.48), p value = 9.03 × 10−4), previously related to AD. Next, to search for recessive candidate variants in ROHs, we constructed a homozygosity map of inbred AD cases extracted from an outbred population and explored ROH regions in whole-exome sequencing data (N = 1449). We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.

Variants in the FTO and CDKAL1 loci have recessive effects on risk of obesity and type 2 diabetes respectively

Genome-wide association studies have identified hundreds of common genetic variants associated with obesity and Type 2 diabetes. These studies have focused on additive association tests. Identifying deviations from additivity may provide new biological insights and explain some of the missing heritability for these diseases. To identify non-additive associations we performed a genome-wide association study using a dominance deviation model for BMI, obesity and Type 2 diabetes (4,040 cases) in 120,286 individuals of British ancestry from the UK Biobank study. Known obesity-associated variants in FTO showed strong evidence for deviation from additivity (P=3x10-5) through a recessive effect of the BMI-increasing allele. The average BMI of individuals carrying 0, 1 or 2 BMI-raising alleles was 27.27kg/m2 (95% CI:27.22-27.31), 27.54kg/m2 (95% CI:27.50-27.58), and 28.07kg/m2 (95% CI:28.0-28.14), respectively. A similar effect was observed in 105,643 individuals from the GIANT consortium (P=0.003; Pmeta-analysis=1x10-7). We also detected a recessive effect (Pdomdev=5x10-4) at CDKAL1 for Type 2 diabetes risk. Homozygous risk allele carriers had an OR=1.48 (95% CI:1.32-1.65) in comparison to the heterozygous group that had an OR=1.06 (95% CI:0.99-1.14), a result consistent with a previous study. We did not identify any novel genome-wide associations. In conclusion, although we find no evidence for widespread non-additive effects contributing to the genetic risk of obesity and Type 2 diabetes, we find robust examples of recessive effects at the FTO and CDKAL1 loci.

Partitioning Reference Intervals by Use of Genetic Information

BACKGROUND Reference intervals that incorporate genetic information could reduce the misidentification of unusual test results caused by non–disease-associated genetic variation and increase the detection of results indicating underlying pathology. Subdividing reference groups by genetic effects, however, may lead to increased uncertainty around reference interval endpoints (because of the smaller subgroup sample sizes), thus offsetting any benefits. METHODS We evaluated CLSI guidelines to develop a method appropriate for partitioning reference intervals on the basis of genetic variants with dominant or recessive effects. This method uses information available before reference samples are recruited, thus allowing a preliminary decision regarding partitioning to be made before sampling. We used this method to evaluate the example of Gilbert syndrome. RESULTS The decision point for partitioning occurs when the percentage of total variance attributable to a dominant or recessive genetic polymorphism exceeds 4%. Similarly, partitioning decision curves are presented based on difference in means between 2 subgroups, sample SD, and subgroup or allele frequency. Laboratory-specific partitioned reference intervals for Gilbert syndrome appear to be statistically warranted for white and African-American populations, but not for Asian populations. CONCLUSIONS We present a simple method to evaluate whether partitioning based on dominant or recessive genetic effects is statistically justified. Important limitations remain that, in many situations, will preclude integration of genetic, laboratory, and clinical information. As society moves toward personalized medicine, additional research is needed on how to evaluate patient normality while accounting for additive genetic, multigenic, and other multifactorial effects.

Regeneration of the variance of metric traits by spontaneous mutation in a Drosophila population

SummaryIn the C1 population of Drosophila melanogaster of moderate effective size (≈500), which was genetically invariant in its origin, we studied the regeneration by spontaneous mutation of the genetic variance for two metric traits [abdominal (AB) and sternopleural (ST) bristle number] and that of the concealed mutation load for viability, together with their temporal stability, using alternative selection models based on mutational parameters estimated in the C1 genetic background. During generations 381–485 of mutation accumulation (MA), the additive variances of AB and ST approached the levels observed in standing laboratory populations, fluctuating around their expected equilibrium values under neutrality or under relatively weak causal stabilizing selection. This type of selection was required to simultaneously account for the observed additive variance in our population and for those previously reported in natural and laboratory populations, indicating that most mutations affecting bristle traits would only be subjected to weak selective constraints. Although gene action for bristles was essentially additive, transient situations occurred where inbreeding resulted in a depression of the mean and an increase of the additive variance. This was ascribed to the occasional segregation of mutations of large recessive effects. On the other hand, the observed non-lethal inbreeding depression for viability must be explained by the segregation of alleles of considerable and largely recessive deleterious effects, and the corresponding load concealed in the heterozygous condition was found to be temporally stable, as expected from tighter constraints imposed by natural selection.