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BackgroundThe 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.MethodsWe 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 = 1 632), a Māori and Pacific Island (Polynesian) cohort from Aotearoa New Zealand (N = 1 419), and the combined cohort (N = 2 976). 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 = 1 496). Bayesian networks were learned to further understand the structure of the relationships.ResultsIn 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.ConclusionsWhen 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 (βHDL-C = -1.60 mg/dL, pHDL-C = 7.63 × 10−10; βTG = 12.00 mg/dL, pTG = 3.82 × 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.

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.652CT, p.R218∗; posterior probability = 0.9987) in

The CREBRF missense variant (p.Arg457Gln) is paradoxically associated with lower risk of type 2 diabetes, yet higher body mass index (BMI). Here we sought to determine whether this CREBRF variant might be associated with adult height. Linear regression was used to analyse the association of the CREBRF minor (A) allele with height in 2286 Māori and Pacific adults living in Aotearoa/New Zealand. A potential type 2 diabetes index event was corrected to account for a bias that may be the cause of paradoxical association between the CREBRF diabetes-protective allele and higher BMI and height. The CREBRF protective allele was associated with increased adult height (s = 1.25 cm, P = 3.9 × 10−6), with the effect being more pronounced in males. The lower odds of diabetes remained similar when analyses were adjusted for height (OR = 0.67–0.65). We found no evidence of a diabetes index event bias to explain the paradoxical effect of CREBRF with either BMI or height and diabetes. The orthologous CREBRF p.Arg457Gln variant was created in knock-in mice to independently assess the effect of the variant, and length was found to be greater in male mice at 8 weeks of age. These data taken together indicate that CREBRF p.Arg457Gln is associated with taller stature in Māori and Pacific adults.

ObjectiveThe minor allele of rs373863828 in CREBRF is associated with higher BMI, lower fasting glucose, and lower odds of type 2 diabetes. We examined the associations between BMI and rs373863828 on type 2 diabetes and fasting glucose with a large sample of adult Polynesians from Samoa, American Samoa and Aotearoa New Zealand and estimated direct and indirect (via BMI) effects of rs373863828 on type 2 diabetes and fasting glucose.Research Design and MethodsWe regressed type 2 diabetes and fasting glucose on BMI and rs373863828 stratified by obesity, regressed type 2 diabetes and fasting glucose on BMI stratified by rs373863828 genotype, and assessed the effects of rs373863828 on type 2 diabetes and fasting glucose with path analysis.ResultsAssociation of BMI with fasting glucose was greater in those without obesity than in those with obesity. We did not observe evidence of differences by genotype. In the path analysis, the minor allele has direct negative and indirect positive effects on type 2 diabetes risk and fasting glucose, with the indirect effect mediated through a direct positive effect on BMI.ConclusionsThere may be a stronger effect of BMI on fasting glucose in Polynesians without obesity than in those with obesity. Carrying the rs373863828 minor allele does not decouple higher BMI from odds of type 2 diabetes. Given the current cost of genotyping compared to the accessibility of measuring BMI, including rs373863828 as a clinical predictor of type 2 diabetes may not be indicated.

Prostate cancer is one of the most significant health concerns for men worldwide. Numerous researchers carrying out molecular diagnostics have indicated that genetic interactions with biological and behavioral factors play an important role in the overall risk and prognosis of this disease. Single nucleotide polymorphisms (SNPs) are increasingly becoming strong biomarker candidates to identify susceptibility to prostate cancer. We carried out a gene × environment interaction analysis linked to aggressive and non-aggressive prostate cancer (PCa) with a number of SNPs. By using this method, we identified the susceptible alleles in a New Zealand population, and examined the interaction with environmental factors. We have identified a number of SNPs that have risk associations both with and without environmental interaction. The results indicate that certain SNPs are associated with disease vulnerability based on behavioral factors. The list of genes with SNPs identified as being associated with the risk of PCa in a New Zealand population is provided in the graphical abstract.

The CREBRF missense variant (p.Arg457Gln) is paradoxically associated with lower risk of type 2 diabetes, yet higher body mass index (BMI). Here we sought to determine whether this CREBRF variant might be associated with adult height.Linear regression was used to analyse the association of the CREBRF minor (A) allele with height in 2286 Māori and Pacific adults living in Aotearoa/New Zealand. A potential type 2 diabetes index event was corrected to account for a bias that may be the cause of paradoxical association between the CREBRF diabetes-protective allele and higher BMI and height.The CREBRF protective allele was associated with increased adult height (ß = 1.25 cm, P = 3.9 × 10These data taken together indicate that CREBRF p.Arg457Gln is associated with taller stature in Māori and Pacific adults.

The A (minor) allele of CREBRF rs373863828 has been associated with increased BMI and reduced risk of type 2 diabetes in the Samoan populations of Samoa and American Samoa. Our aim was to test rs373863828 for associations with BMI and the odds of type 2 diabetes, gout and chronic kidney disease (CKD) in Māori and Pacific (Polynesian) people living in Aotearoa/New Zealand. Linear and logistic regression models were used to analyse the association of the A allele of CREBRF rs373863828 with BMI, log-transformed BMI, waist circumference, type 2 diabetes, gout and CKD in 2286 adults. The primary analyses were adjusted for age, sex, the first four genome-wide principal components and (where appropriate) BMI, waist circumference and type 2 diabetes. The primary analysis was conducted in ancestrally defined groups and association effects were combined using meta-analysis. For the A allele of rs373863828, the effect size was 0.038 (95% CI 0.022, 0.055, p = 4.8 × 10−6) for log-transformed BMI, with OR 0.59 (95% CI 0.47, 0.73, p = 1.9 × 10−6) for type 2 diabetes. There was no evidence for an association of genotype with variance in BMI (p = 0.13), and nor was there evidence for associations with serum urate (β = 0.012 mmol/l, pcorrected = 0.10), gout (OR 1.00, p = 0.98) or CKD (OR 0.91, p = 0.59). Our results in New Zealand Polynesian adults replicate, with very similar effect sizes, the association of the A allele of rs373863828 with higher BMI but lower odds of type 2 diabetes among Samoan adults living in Samoa and American Samoa.

Aim/HypothesesThe minor allele of CREBRF rs373863828 associates with increased body mass index (BMI) and reduced risk of type 2 diabetes (T2D) in the Samoan population of Samoa and American Samoa. Our aim was to test rs373863828 for association with BMI and odds of T2D, gout and chronic kidney disease (CKD) in Māori and Pacific (Polynesian) people living in Aotearoa New Zealand in 2,286 adults.MethodsAssociation analyses were performed by linear and logistic regression with BMI, log-transformed BMI, waist circumference, T2D, gout and CKD. Analyses were adjusted for age, sex, the first four genome-wide principal components, and (when appropriate) BMI, waist circumference and T2D.ResultsFor the minor allele of rs373863828 the effect size for log-transformed BMI was 0.038 (95% CI [0.022-0.055], P=4.8x10−6) and for T2D was OR=0.59 (95% CI [0.47-0.73], P=1.9x10−6). There was no evidence for association of genotype with variance in BMI (P=0.13). Nor was there evidence for association with serum urate (β=0.012 mmol/L, Pc=0.10), gout (OR=1.00, P=0.98) or CKD (OR=0.91, P=0.59).Conclusions/interpretationOur results replicated, with very similar effect sizes, association of the minor allele of rs373863828 with higher BMI but lower odds of T2D among New Zealand Polynesian adults, as in Samoan adults living in Samoa and American Samoa.

Purpose: The decline of physical activity in children is considered an important determinant to explain the rising rates of obesity. However, this risk may be augmented in children who are genetically susceptible to increased weight gain. We hypothesized that a sedentary lifestyle and moderate activity will interact with genetic loci, resulting in differential effects in relation to obesity risk. Methods: We recruited 643 European children born to participants in the New Zealand-based Screening for Pregnancy Endpoints (SCOPE) study. Seventy gene variants were evaluated by the Sequenom assay. Interaction analyses were performed between the genetic variants and the activity type derived from actigraphy, in relation to percentage body fat. Results: We found a statistically significant association between increased proportions of sedentary activity with increased percentage body fat scores (P = .012). The OLFM4-9568856 (P = .01) and GNPDA2-rs10938397 (P = .044) gene variants showed genotype differences with proportions of sedentary activity. Similarly, the OLFM4-9568856 (P = .021), CLOCK-rs4864548 (P = .029), and LEPR-1045895 (P = .047) showed genotype differences with proportions of moderate activity. We found evidence for unadjusted gene-by-activity interactions of SPACA3/SPRASA-rs16967845, PFKP-rs6602024, and SH2B1-rs7498665 on percentage body fat scores. Conclusions: These findings indicate a differential effect of physical activity in relation to obesity risk, suggesting that children genetically predisposed to increased weight gain may benefit from higher levels of moderate activity.

Childhood obesity is a public health problem, which is associated with a long-term increased risk of cardiovascular disease and premature mortality. Several gene variants have previously been identified that have provided novel insights into biological factors that contribute to the development of obesity. As obesity tracks through childhood into adulthood, identification of the genetic factors for obesity in early life is important. The objective of this study was to identify putative associations between genetic variants and obesity traits in children at 6 years of age. We recruited 1208 children of mothers from the New Zealand centre of the international Screening for Pregnancy Endpoints (SCOPE) study. Eighty common genetic variants associated with obesity traits were evaluated by the Sequenom assay. Body mass index standardised scores (BMI z-scores) and percentage body fat (PBF; measured by bio-impedance assay (BIA)) were used as anthropometric measures of obesity. A positive correlation was found between BMI z-scores and PBF (p < 0.001, r = 0.756). Two subsets of gene variants were associated with BMI z-scores (HOXB5-rs9299, SH2B1-rs7498665, NPC1-rs1805081 and MSRA-rs545854) and PBF (TMEM18-rs6548238, NPY-rs17149106, ETV-rs7647305, NPY-rs16139, TIMELESS-rs4630333, FTO-rs9939609, UCP2-rs659366, MAP2K5-rs2241423 and FAIM2-rs7138803) in the genotype models. However, there was an absence of overlapping association between any of the gene variants with BMI z-scores and PBF. A further five variants were associated with BMI z-scores (TMEM18-rs6548238, FTO-rs9939609 and MC4R-rs17782313) and PBF (SH2B1-rs7498665 and FTO-rs1421085) once separated by genetic models (additive, recessive and dominant) of inheritance. This study has identified significant associations between numerous gene variants selected on the basis of prior association with obesity and obesity traits in New Zealand European children.

Objectives Modern technology may have desensitised the ‘biological clock’ to environmental cues, disrupting the appropriate co-ordination of metabolic processes. Susceptibility to misalignment of circadian rhythms may be partly genetically influenced and effects on sleep quality and duration could predispose to poorer health outcomes. Shorter sleep duration is associated with obesity traits, which are brought on by an increased opportunity to eat and/or a shift of hormonal profile promoting hunger. We hypothesised that increased sleep duration will offset susceptible genetic effects, resulting in reduced obesity risk. Methods We recruited 643 (male: 338; female: 305) European children born to participants in the New Zealand centre of the International Screening for Pregnancy Endpoints sleep study. Ten genes directly involved in the circadian rhythm machinery and a further 20 genes hypothesised to be driven by cyclic oscillations were evaluated by Sequenom assay. Multivariable regression was performed to test the interaction between gene variants and average sleep length (derived from actigraphy), in relation to obesity traits (body mass index (BMI) z-scores and percentage body fat (PBF)). Results No association was found between average sleep length and BMI z-scores ( p = 0.056) or PBF ( p = 0.609). Uncorrected genotype associations were detected between STAT-rs8069645 ( p = 0.0052) and ADIPOQ-rs266729 ( p = 0.019) with differences in average sleep duration. Evidence for uncorrected gene-by-sleep interactions of the CLOCK-rs4864548 ( p = 0.0039), PEMT-936108 ( p = 0.016) and GHRELIN-rs696217 ( p = 0.046) were found in relation to BMI z-scores but not for PBF. Conclusion Our results indicate that children may have different genetic susceptibility to the effects of sleep duration on obesity. Further confirmatory studies are required in other population cohorts of different age groups.