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IntroductionNational obesity prevention strategies may benefit from precision health approaches involving diverse participants in population health studies. We used cohort data from the National Institutes of Health All of Us Research Program (All of Us) Researcher Workbench to estimate population-level obesity prevalence.MethodsTo estimate state-level obesity prevalence we used data from physical measurements made during All of Us enrollment visits and data from participant electronic health records (EHRs) where available. Prevalence estimates were calculated and mapped by state for 2 categories of body mass index (BMI) (kg/m2): obesity (BMI >30) and severe obesity (BMI >35). We calculated and mapped prevalence by state, excluding states with fewer than 100 All of Us participants.ResultsData on height and weight were available for 244,504 All of Us participants from 33 states, and corresponding EHR data were available for 88,840 of these participants. The median and IQR of BMI taken from physical measurements data was 28.4 (24.4- 33.7) and 28.5 (24.5-33.6) from EHR data, where available. Overall obesity prevalence based on physical measurements data was 41.5% (95% CI, 41.3%-41.7%); prevalence of severe obesity was 20.7% (95% CI, 20.6-20.9), with large geographic variations observed across states. Prevalence estimates from states with greater numbers of All of Us participants were more similar to national population-based estimates than states with fewer participants.ConclusionAll of Us participants had a high prevalence of obesity, with state-level geographic variation mirroring national trends. The diversity among All of Us participants may support future investigations on obesity prevention and treatment in diverse populations.

Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify the loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC) and hip circumference (HIP) adjusted for body mass index (adjBMI) by using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban and Dominican) background residing in the USA. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for waist-to-hip ratio adjusted for body mass index (WHRadjBMI), 22 for waist circumference adjusted for body mass index (WCadjBMI) and 28 for hip circumference adjusted for body mass index (HIPadjBMI), which reached suggestive significance (P

Logistic regression is the primary analysis tool for binary traits in genome-wide association studies (GWAS). Multinomial regression extends logistic regression to multiple categories. However, many phenotypes more naturally take ordered, discrete values. Examples include (a) subtypes defined from multiple sources of clinical information and (b) derived phenotypes generated by specific phenotyping algorithms for electronic health records (EHR). GWAS of ordinal traits have been problematic. Dichotomizing can lead to a range of arbitrary cutoff values, generating inconsistent, hard to interpret results. Using multinomial regression ignores trait value hierarchy and potentially loses power. Treating ordinal data as quantitative can lead to misleading inference. To address these issues, we analyze ordinal traits with an ordered, multinomial model. This approach increases power and leads to more interpretable results. We derive efficient algorithms for computing test statistics, making ordinal trait GWAS computationally practical for Biobank scale data. Our method is available as a Julia package OrdinalGWAS.jl. Application to a COPDGene study confirms previously found signals based on binary case-control status, but with more significance. Additionally, we demonstrate the capability of our package to run on UK Biobank data by analyzing hypertension as an ordinal trait.

Scopen-3 polyunsaturated fatty acid (n-3 PUFA) intake is associated with protection from obesity; however, the mechanisms of protection remain poorly characterized. The stearoyl CoA desaturase (SCD), insulin-sensitive glucose transporter (SLC2A4), and sterol regulatory element binding protein (SREBF1) genes are transcriptionally regulated by n-3 PUFA intake and harbor polymorphisms associated with obesity. The present study investigated how consumption of n-3 PUFA modifies associations between SCD, SLC2A4, and SREBF1 polymorphisms and anthropometric variables and metabolic phenotypes.Materials and methodsAnthropometric variables and metabolic phenotypes were measured in a cross-sectional sample of Yup'ik individuals (n = 1135) and 33 polymorphisms were tested for main effects and interactions using linear models that account for familial correlations. n-3 PUFA intake was estimated using red blood cell nitrogen stable isotope ratios. SCD polymorphisms were associated with ApoA1 concentration and n-3 PUFA interactions with SCD polymorphisms were associated with reduced fasting cholesterol levels and waist-to-hip ratio. SLC2A4 polymorphisms were associated with hip circumference, high-density lipoprotein and ApoA1 concentrations. SREBF1 polymorphisms were associated with low-density lipoprotein and HOMA-IR and n-3 PUFA interactions were associated with reduced fasting insulin and HOMA-IR levels.ConclusionThe results suggest that an individual's genotype may interact with dietary n-3 PUFAs in ways that are associated with protection from obesity-related diseases in Yup'ik people.

BackgroundGenome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D), mainly among individuals of European ancestry. In the present study, we examined the frequency of these SNPs and their association with T2D-related traits in an Alaska Native study population with a historically low prevalence of T2D. We also investigated whether dietary characteristics that may protect against T2D, such as n-3 polyunsaturated fatty acid (PUFA) intake, modify these associations.MethodsIn 1144 Yup'ik people, we examined 17 SNPs repeatedly identified in GWAS for individual and cumulative associations with T2D-related traits. Cumulative associations were evaluated using a genetic risk score (GRS) calculated by summing risk alleles. Associations were tested for interactions with sex, body mass index (BMI), and n-3 PUFA intake.ResultsThe rs7754840 SNP in CDKAL1 is significantly associated with HbA1c (P = 0.00091). The rs5015480 SNP near HHEX is significantly associated (in opposite direction to that in Europeans) with a combined fasting glucose (FG) and HbA1c measure (P = 0.00046) and with homeostatic model assessment of β-cell function (HOMA-B; P = 0.0014). The GRS is significantly associated with FG and combined FG and HbA1c only when the HHEX SNP is dropped from the GRS. Associations are not modified by BMI or n-3 PUFA intake.ConclusionOur results highlight the potential importance of CDKAL1 and HHEX in glucose homeostasis in this Alaska Native population with a low prevalence of T2D, and suggest that these loci should be examined in greater detail in this population.

BackgroundGenome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D), mainly among individuals of European ancestry. In the present study, we examined the frequency of these SNPs and their association with T2D-related traits in an Alaska Native study population with a historically low prevalence of T2D. We also investigated whether dietary characteristics that may protect against T2D, such as n-3 polyunsaturated fatty acid (PUFA) intake, modify these associations.MethodsIn 1144 Yup'ik people, we examined 17 SNPs repeatedly identified in GWAS for individual and cumulative associations with T2D-related traits. Cumulative associations were evaluated using a genetic risk score (GRS) calculated by summing risk alleles. Associations were tested for interactions with sex, body mass index (BMI), and n-3 PUFA intake.ResultsThe rs7754840 SNP in CDKAL1 is significantly associated with HbA1c (P = 0.00091). The rs5015480 SNP near HHEX is significantly associated (in opposite direction to that in Europeans) with a combined fasting glucose (FG) and HbA1c measure (P = 0.00046) and with homeostatic model assessment of β-cell function (HOMA-B; P = 0.0014). The GRS is significantly associated with FG and combined FG and HbA1c only when the HHEX SNP is dropped from the GRS. Associations are not modified by BMI or n-3 PUFA intake.ConclusionOur results highlight the potential importance of CDKAL1 and HHEX in glucose homeostasis in this Alaska Native population with a low prevalence of T2D, and suggest that these loci should be examined in greater detail in this population.

ObjectivesTo identify genomic regions associated with fasting plasma lipid profiles, insulin, glucose, and glycosylated hemoglobin in a Yup'ik study population, and to evaluate whether the observed associations between genetic factors and metabolic traits were modified by dietary intake of marine derived omega-3 polyunsaturated acids (n-3 PUFA).MethodsA genome-wide linkage scan was conducted among 982 participants of the Center for Alaska Native Health Research study. n-3 PUFA intake was estimated using the nitrogen stable isotope ratio (δ(15) N) of erythrocytes. All genotyped SNPs located within genomic regions with LOD scores > 2 were subsequently tested for individual SNP associations with metabolic traits using linear models that account for familial correlation as well as age, sex, community group, and n-3 PUFA intake. Separate linear models were fit to evaluate interactions between the genotype of interest and n-3 PUFA intake.ResultsWe identified several chromosomal regions linked to serum apolipoprotein A2, high density lipoprotein-, low density lipoprotein-, and total cholesterol, insulin, and glycosylated hemoglobin. Genetic variants found to be associated with total cholesterol mapped to a region containing previously validated lipid loci on chromosome 19, and additional novel peaks of biological interest were identified at 11q12.2-11q13.2. We did not observe any significant interactions between n-3 PUFA intake, genotypes, and metabolic traits.ConclusionsWe have completed a whole genome linkage scan for metabolic traits in Native Alaskans, confirming previously identified loci, and offering preliminary evidence of novel loci implicated in chronic disease pathogenesis in this population.

Key Points: Question: Is there an association between sedentary behavior and risk of all-cause dementia in older adults? Findings: In this retrospective study of prospectively collected data of 49 841 adults participating in the UK Biobank, more time spent in sedentary behaviors (determined through a machine learning–based analysis of wrist-worn accelerometer data) was significantly associated with higher risk of incident dementia. Meaning: Among older adults, more time spent in sedentary behaviors was associated with higher risk of incident all-cause dementia. Importance: Sedentary behavior is associated with cardiometabolic disease and mortality, but its association with dementia is unclear. Objective: To investigate whether accelerometer-assessed sedentary behavior is associated with incident dementia. Design, Setting, and Participants: A retrospective study of prospectively collected data from the UK Biobank including 49 841 adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer and living in England, Scotland, or Wales. Follow-up began at the time of wearing the accelerometer (February 2013 to December 2015) and continued until September 2021 in England, July 2021 in Scotland, and February 2018 in Wales. Exposures: Mean daily sedentary behavior time (included in the primary analysis) and mean daily sedentary bout length, maximum daily sedentary bout length, and mean number of daily sedentary bouts (included in the secondary analyses) were derived from a machine learning–based analysis of 1 week of wrist-worn accelerometer data. Main Outcome and Measures: Incident all-cause dementia diagnosis from inpatient hospital records and death registry data. Cox proportional hazard models with linear and cubic spline terms were used to assess associations. Results: A total of 49 841 older adults (mean age, 67.19 [SD, 4.29] years; 54.7% were female) were followed up for a mean of 6.72 years (SD, 0.95 years). During this time, 414 individuals were diagnosed with incident all-cause dementia. In the fully adjusted models, there was a significant nonlinear association between time spent in sedentary behavior and incident dementia. Relative to a median of 9.27 hours/d for sedentary behavior, the hazard ratios (HRs) for dementia were 1.08 (95% CI, 1.04-1.12, P <.001) for 10 hours/d, 1.63 (95% CI, 1.35-1.97, P <.001) for 12 hours/d, and 3.21 (95% CI, 2.05-5.04, P <.001) for 15 hours/d. The adjusted incidence rate of dementia per 1000 person-years was 7.49 (95% CI, 7.48-7.49) for 9.27 hours/d of sedentary behavior, 8.06 (95% CI, 7.76-8.36) for 10 hours/d, 12.00 (95% CI, 10.00-14.36) for 12 hours/d, and 22.74 (95% CI, 14.92-34.11) for 15 hours/d. Mean daily sedentary bout length (HR, 1.53 [95% CI, 1.03-2.27], P =.04 and 0.65 [95% CI, 0.04-1.57] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 0.48 hours) and maximum daily sedentary bout length (HR, 1.15 [95% CI, 1.02-1.31], P =.02 and 0.19 [95% CI, 0.02-0.38] more dementia cases per 1000 person-years for a 1-hour increase from the mean of 1.95 hours) were significantly associated with higher risk of incident dementia. The number of sedentary bouts per day was not associated with higher risk of incident dementia (HR, 1.00 [95% CI, 0.99-1.01], P =.89). In the sensitivity analyses, after adjustment for time spent in sedentary behavior, the mean daily sedentary bout length and the maximum daily sedentary bout length were no longer significantly associated with incident dementia. Conclusions and Relevance: Among older adults, more time spent in sedentary behaviors was significantly associated with higher incidence of all-cause dementia. Future research is needed to determine whether the association between sedentary behavior and risk of dementia is causal. This study of prospectively collected data from the UK Biobank investigates whether accelerometer-assessed sedentary behavior is associated with incident dementia in adults aged 60 years or older without a diagnosis of dementia at the time of wearing the wrist accelerometer. [ABSTRACT FROM AUTHOR]

Introduction and Objectives: Various studies have identified single-nucleotide polymorphisms (SNPs) associated with nonalcoholic fatty liver disease (NAFLD) and related traits, including ones located in or near the LYPLAL1, GCKR, PPP1R3B, TM6SF2, MBOAT7, and PNPLA3 genes. However, these SNPs were identified primarily in populations of European ancestry. This study examined the associations of these previously identified SNPs with hepatic steatosis in a sample of Mexican-origin adults living in Southern Arizona. Materials and Methods: A total of 307 Mexican-origin adults between the ages of 18 and 64 with a body mass index (BMI) of 25 kg/m2 or higher were genotyped at the following SNPs: rs12137855 (LYPLAL1), rs1260326 (GCKR), rs4240624 (PPP1R3B), rs58542926 (TM6SF2), rs641738 (MBOAT7), and rs738409 (PNPLA3). Hepatic steatosis was assessed by transient elastography (FibroScan-) with controlled attenuation parameter. Regression models examined the association between each of the six SNPs and hepatic steatosis. BMI was examined as a potential modifier of the genetic associations. Results: Participants were, on average, 45 years old and mostly female (63%) with an overall mean hepatic steatosis of 288.1 dB/m. Models showed no associations between LYPLAL1, GCKR, PPP1R3B, TM6SF2, or MBOAT7 and hepatic steatosis. Only PNPLA3 was statistically significantly associated with hepatic steatosis in both unadjusted and adjusted models (p<0.01). There was no effect modification observed with BMI. Conclusions: SNPs associated with NAFLD in populations of European descent did not strongly contribute to hepatic steatosis in individuals of Mexican-origin, except for rs738409 (PNPLA3). Further efforts are necessary to explore additional SNPs that may be associated with NAFLD in this high-risk population. [ABSTRACT FROM AUTHOR]

Objective: This analysis assessed the putative causal association between genetically predicted percent body fat and areal bone mineral density (aBMD) and, more specifically, the association between genetically predicted metabolically "favorable adiposity" (MFA) and aBMD at clinically relevant bone sites. Methods: Mendelian randomization was used to assess the relationship of MFA and percent body fat with whole‐body, lumbar spine, femoral neck, and forearm aBMD. Sex‐stratified and age‐stratified exploratory analyses were conducted. Results: In all MR analyses, genetically predicted MFA was inversely associated with aBMD for the whole body (β = −0.053, p = 0.0002), lumbar spine (β = −0.075; p = 0.0001), femoral neck (β = −0.045; p = 0.008), and forearm (β = −0.115; p = 0.001). This negative relationship was strongest in older individuals and did not differ by sex. The relationship between genetically predicted percent body fat and aBMD was nonsignificant across all Mendelian randomization analyses. Several loci that were associated at a genome‐wide significance level (p < 5 × 10−8) in opposite directions with body fat and aBMD measures were also identified. Conclusions: This study did not support the hypothesis that MFA protects against low aBMD. Instead, it showed that MFA may result in lower aBMD. Further research is needed to understand how MFA affects aBMD and other components of bone health such as bone turnover, bone architecture, and osteoporotic fractures. [ABSTRACT FROM AUTHOR]

Abstract Type 2 diabetes represents an increasing health burden. Its prevalence is rising among younger age groups and differs among racial/ethnic groups. Little is known about its genetic basis, including whether there is a genetic basis for racial/ethnic disparities. We examined a multi-ethnic sample of 253 healthy children to evaluate associations between insulin-related phenotypes and 142 ancestry-informative markers (AIMs), while adjusting for sex, age, Tanner stage, genetic admixture, total body fat, height and socio-economic status. We also evaluated the effect of measurement errors in the estimation of the individual ancestry proportions on the regression results. We found that European genetic admixture is positively associated with insulin sensitivity (SI), and negatively associated with the acute insulin response to glucose, fasting insulin levels and the homeostasis model assessment of insulin resistance. Our analysis revealed associations between individual AIMs on chromosomes 2, 8 and 15 and these phenotypes. Most notably, marker rs3287 at chromosome 2p21 was found to be associated with SI (p = 5.8 × 10-5). This marker may be in admixture linkage disequilibrium with nearby loci (THADA and BCL11A) that previously have been reported to be associated with diabetes and diabetes-related phenotypes in several genome-wide association and linkage studies. Our results provide further evidence that variation in the 2p21 region containing THADA and BCL11A is associated with type 2 diabetes. Importantly, we have implicated this region in the early development of diabetes-related phenotypes, and in the genetic aetiology of population differences in these phenotypes.