A new test for trait mean and variance detects unreported loci for blood-pressure variation.

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci

Contribution of neutral processes to the assembly of gut microbial communities in the zebrafish over host development

Despite their importance to host health and development, the communities of microorganisms associated with humans and other animals are characterized by a large degree of unexplained variation across individual hosts. The processes that drive such inter-individual variation are not well understood. To address this, we surveyed the microbial communities associated with the intestine of the zebrafish, Danio rerio, over developmental time. We compared our observations of community composition and distribution across hosts with that predicted by a neutral assembly model, which assumes that community assembly is driven solely by chance and dispersal. We found that as hosts develop from larvae to adults, the fit of the model to observed microbial distributions decreases, suggesting that the relative importance of non-neutral processes, such as microbe-microbe interactions, active dispersal, or selection by the host, increases as hosts mature. We also observed that taxa which depart in their distributions from the neutral prediction form ecologically distinct sub-groups, which are phylogenetically clustered with respect to the full metacommunity. These results demonstrate that neutral processes are sufficient to generate substantial variation in microbiota composition across individual hosts, and suggest that potentially unique or important taxa may be identified by their divergence from neutral distributions

Genome-Wide Interaction with Insulin Secretion Loci Reveals Novel Loci for Type 2 Diabetes in African Americans

Type 2 diabetes (T2D) is the result of metabolic defects in insulin secretion and insulin sensitivity, yet most T2D loci identified to date influence insulin secretion. We hypothesized that T2D loci, particularly those affecting insulin sensitivity, can be identified through interaction with insulin secretion loci. To test this hypothesis, single nucleotide polymorphisms (SNPs) associated with acute insulin response to glucose (AIRg), a dynamic measure of first-phase insulin secretion, were identified in African Americans from the Insulin Resistance Atherosclerosis Family Study (IRASFS; n = 492 subjects). These SNPs were tested for interaction, individually and jointly as a genetic risk score (GRS), using genome-wide association study (GWAS) data from five cohorts (ARIC, CARDIA, JHS, MESA, WFSM; n = 2,725 cases, 4,167 controls) with T2D as the outcome. In single variant analyses, suggestively significant (Pinteraction<5×10-6) interactions were observed at several loci including LYPLAL1 (rs10746381), CHN2 (rs7796525), and EXOC1 (rs4289500). Notable AIRg GRS interactions were observed with SAMD4A (rs11627203) and UTRN (rs17074194). These data support the hypothesis that additional genetic factors contributing to T2D risk can be identified by interactions with insulin secretion loci

Evidence of Novel Susceptibility Variants for Prostate Cancer and a Multiancestry Polygenic Risk Score Associated with Aggressive Disease in Men of African Ancestry.

BACKGROUND: Genetic factors play an important role in prostate cancer (PCa) susceptibility. OBJECTIVE: To discover common genetic variants contributing to the risk of PCa in men of African ancestry. DESIGN, SETTING, AND PARTICIPANTS: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness. RESULTS AND LIMITATIONS: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4). CONCLUSIONS: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry. PATIENT SUMMARY: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease