The minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor, is associated with several cardiometabolic phenotypes in Polynesian peoples. To better understand the variant, we tested the association of rs373863828 with a panel of correlated phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) using multivariate Bayesian association and network analyses in a Samoa cohort (n = 1632), Aotearoa New Zealand cohort (n = 1419), and combined cohort (n = 2976). An expanded set of phenotypes (adding estimated fat and fat‐free mass, abdominal circumference, hip circumference, and abdominal‐hip ratio) was tested in the Samoa cohort (n = 1496). In the Samoa cohort, we observed significant associations (log10 Bayes Factor [BF] ≥ 5.0) between rs373863828 and the overall phenotype panel (8.81), weight (8.30), and BMI (6.42). In the Aotearoa New Zealand cohort, we observed suggestive associations (1.5 < log10BF < 5) between rs373863828 and the overall phenotype panel (4.60), weight (3.27), and BMI (1.80). In the combined cohort, we observed concordant signals with larger log10BFs. In the Samoa‐specific expanded phenotype analyses, we also observed significant associations between rs373863828 and fat mass (5.65), abdominal circumference (5.34), and hip circumference (5.09). Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI.
Background The Pacific-specific minor allele of rs373863828, a missense variant in CREB3 Regulatory Factor (CREBRF), is associated with several cardiometabolic phenotypes in Polynesian peoples, but the variant's function remains poorly understood. To broaden our understanding of this variant, we used joint multivariate and network analyses to examine the relationships between rs373863828 and a panel of correlated anthropometric and lipid phenotypes. Methods We tested the association of rs373863828 with a panel of phenotypes (body mass index [BMI], weight, height, HDL cholesterol, triglycerides, and total cholesterol) under a multivariate Bayesian association model in a cohort from Samoa (N = 1632), a Maori and Pacific Island (Polynesian) cohort from Aotearoa New Zealand (N = 1419), and the combined cohort (N = 2976). An expanded set of phenotypes (adding estimated fat and fat-free mass, abdominal circumference, hip circumference, and abdominal-hip ratio) was also tested in the Samoa cohort (N = 1496). Bayesian networks were learned to further understand the structure of the relationships. Results In the Samoa cohort, significant associations (log10 Bayes factor >=5.0) were found between rs373863828 and the overall phenotype panel (7.97), weight (8.35) and BMI (6.39). In the Aotearoa New Zealand cohort, suggestive associations (log10 Bayes factor between 1.5 and 5) were found between rs373863828 and the overall phenotype panel (3.64), weight (3.30), and BMI (1.79). In the combined cohort, concordant signals with stronger magnitudes were observed. In the expanded phenotype analyses among the Samoa cohort, significant associations were also observed between rs373863828 and fat mass (5.68), abdominal circumference (5.37), and hip circumference (5.15). Bayesian networks provided evidence for a direct association of rs373863828 with weight and indirect associations with height and BMI. Conclusions When correlation structures were considered, multivariate Bayesian analyses provided additional evidence of rs373863828's pleiotropic effects and highlighted a strong direct effect only on weight.
Current understanding of lipid genetics has come mainly from studies in European-ancestry populations; limited effort has focused on Polynesian populations, whose unique population history and high prevalence of dyslipidemia may provide insight into the biological foundations of variation in lipid levels. Here we performed an association study to fine map a suggestive association on 5q35 with high-density lipoprotein cholesterol (HDL-C) seen in Micronesian and Polynesian populations. Fine-mapping analyses in a cohort of 2,851 Samoan adults highlighted an association between a stop-gain variant (rs200884524; c.652C>T, p.R218*; posterior probability = 0.9987) in BTNL9 and both lower HDL-C and greater triglycerides (TG). Meta-analysis across this and several other cohorts of Polynesian ancestry from Samoa, American Samoa, and Aotearoa New Zealand confirmed the presence of this association (β.HDL-C = -1.60 mg/dL, p.HDL-C = 7.63 x 10-10; β.TG = 12.00 mg/dL, p.TG = 3.82 x 10-7). While this variant appears to be Polynesian-specific, there is also evidence of association from other multi-ancestry analyses in this region. This work provides evidence of a previously unexplored contributor to the genetic architecture of lipid levels and underscores the importance of genetic analyses in understudied populations
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