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Aims/hypothesis There is limited information on how polygenic scores (PSs), based on variants from genome-wide association studies (GWASs) of type 2 diabetes, add to clinical variables in predicting type 2 diabetes incidence, particularly in non-European-ancestry populations. Methods For participants in a longitudinal study in an Indigenous population from the Southwestern USA with high type 2 diabetes prevalence, we analysed ten constructions of PS using publicly available GWAS summary statistics. Type 2 diabetes incidence was examined in three cohorts of individuals without diabetes at baseline. The adult cohort, 2333 participants followed from age ≥20 years, had 640 type 2 diabetes cases. The youth cohort included 2229 participants followed from age 5–19 years (228 cases). The birth cohort included 2894 participants followed from birth (438 cases). We assessed contributions of PSs and clinical variables in predicting type 2 diabetes incidence. Results Of the ten PS constructions, a PS using 293 genome-wide significant variants from a large type 2 diabetes GWAS meta-analysis in European-ancestry populations performed best. In the adult cohort, the AUC of the receiver operating characteristic curve for clinical variables for prediction of incident type 2 diabetes was 0.728; with the PS, 0.735. The PS’s HR was 1.27 per SD (p=1.6 × 10−8; 95% CI 1.17, 1.38). In youth, corresponding AUCs were 0.805 and 0.812, with HR 1.49 (p=4.3 × 10−8; 95% CI 1.29, 1.72). In the birth cohort, AUCs were 0.614 and 0.685, with HR 1.48 (p=2.8 × 10−16; 95% CI 1.35, 1.63). To further assess the potential impact of including PS for assessing individual risk, net reclassification improvement (NRI) was calculated: NRI for the PS was 0.270, 0.268 and 0.362 for adult, youth and birth cohorts, respectively. For comparison, NRI for HbA1c was 0.267 and 0.173 for adult and youth cohorts, respectively. In decision curve analyses across all cohorts, the net benefit of including the PS in addition to clinical variables was most pronounced at moderately stringent threshold probability values for instituting a preventive intervention. Conclusions/interpretation This study demonstrates that a European-derived PS contributes significantly to prediction of type 2 diabetes incidence in addition to information provided by clinical variables in this Indigenous study population. Discriminatory power of the PS was similar to that of other commonly measured clinical variables (e.g. HbA1c). Including type 2 diabetes PS in addition to clinical variables may be clinically beneficial for identifying individuals at higher risk for the disease, especially at younger ages. Graphical abstract

Background Genome-wide association studies have shown that body mass index (BMI), an estimate of obesity, is highly polygenic. Individual variants typically have small effect sizes, making it challenging to identify unique loci in under-represented ethnic groups which lack statistical power due to their small sample size. Yet obesity is a major health disparity and is particularly prevalent in southwestern American Indians. Here, we identify and characterize a new locus for BMI that was detected by analyzing moderate associations with BMI obtained in a population-based sample of southwestern American Indians together with the well-powered GIANT dataset. Methods Genotypes for 10.5 million variants were tested for association with BMI in 5870 American Indians and 2600 variants that showed an association P −3 in the American Indian sample were combined in a meta-analysis with the BMI data reported in GIANT (N = 240,608). The newly identified gene, NFIA-AS2 was functionally characterized, and the impact of its lead associated variant rs1777538 was studied both in-silico and in-vitro. Results Rs1777538 (T/C; C allele frequency = 0.16 in American Indians and 0.04 in GIANT, meta-analysis P = 5.0 × 10−7) exhibited a large effect in American Indians (1 kg/m2 decrease in BMI per copy of C allele). NFIA-AS2 was found to be a nuclear localized long non-coding RNA expressed in tissues pertinent to human obesity. Analysis of this variant in human brown preadipocytes showed that NFIA-AS2 transcripts carrying the C allele had increased RNA degradation compared to the T allele transcripts (half-lives = 9 h, 13 h respectively). During brown adipogenesis, NFIA-AS2 featured a stage-specific regulation of nearby gene expression where rs1777538 demonstrated an allelic difference in regulation in the mature adipocytes (the strongest difference was observed for L1TD1, P = 0.007). Conclusion Our findings support a role for NFIA-AS2 in regulating pathways that impact BMI.

Context Insulin secretion and sensitivity regulate glycemia, with inadequately compensated deficiencies leading to diabetes. Objective We investigated effects of weight loss, an intensive lifestyle intervention (ILS), and metformin on the relationship between insulin secretion and sensitivity using repository data from 2931 participants in the Diabetes Prevention Program clinical trial in adults at high risk of developing type 2 diabetes. Methods Insulin secretion and sensitivity were estimated from insulin and glucose concentrations in fasting and 30-minute postload serum samples at baseline and 1, 2, and 3 years after randomization, during the active intervention phase. The nonlinear relationship of secretion and sensitivity was evaluated by standardized major axis regression to account for variability in both variables. Insulin secretory demand and compensatory insulin secretion were characterized by distances along and away from the regression line, respectively. Results ILS and metformin decreased secretory demand while increasing compensatory insulin secretion, with greater effects of ILS. Improvements were directly related to weight loss; decreased weight significantly reduced secretory demand (b=−0.144 SD; 95% CI (−0.162, −0.125)/5 kg loss) and increased compensatory insulin secretion (b = 0.287 SD, 95% CI (0.261, 0.314)/5 kg loss). In time-dependent hazard models, increasing compensatory insulin secretion (hazard ratio [HR] = 0.166 per baseline SD, 95% CI 0.133, 0.206) and weight loss (HR = 0.710 per 5 kg loss, 95% CI 0.613, 0.819) predicted lower diabetes risk. Conclusion Diabetes risk reduction was directly related to the amount of weight loss, an effect mediated by lowered insulin secretory demand (due to increased insulin sensitivity) coupled with improved compensatory insulin secretion.

Growth abnormalities in childhood have been related to later cardiometabolic risks, but little is known about these associations in populations at high risk of type 2 diabetes.We examined the associations of patterns of growth, including weight and height at ages 1-59 months, with cardiometabolic risk factors at ages 5-16 years.We linked anthropometric data collected at ages 1-59 months to cardiometabolic data obtained from a longitudinal study in a southwestern American Indian population at high risk of diabetes. Analyses included 701 children with ≥1 follow-up examination at ages 5-16 years. We derived age- and sex-specific weight-for-height z-scores (WHZ) and height-for-age z-scores (HAZ) at ages 1-59 months. We selected the highest observed WHZ and the lowest observed HAZ at ages 1-59 months and analyzed associations of z-scores and categories of WHZ and HAZ with cardiometabolic outcomes at ages 5-16 years. We used linear mixed-effects models to account for repeated measures.Overweight/obesity (WHZ 2) at ages 1-59 months was significantly associated with increased BMI, fasting and 2-hour postload plasma glucose, fasting and 2-hour insulin, triglycerides, systolic blood pressure, diastolic blood pressure, and decreased HDL cholesterol at ages 5-16 years relative to normal weight (WHZ ≤1). For example, at ages 5-9 years, 2-hour glucose was 10.4 mg/dL higher (95% CI: 5.6-15.3 mg/dL) and fasting insulin was 4.29 μU/mL higher (95% CI: 2.96-5.71 μU/mL) in those with overweight/obesity in early childhood. Associations were attenuated and no longer significant when adjusted for concurrent BMI. A low height-for-age (HAZ-2) at ages 1-59 months was associated with 5.37 mg/dL lower HDL (95% CI: 2.57-8.17 mg/dL) and 27.5 μU/mL higher 2-hour insulin (95% CI: 3.41-57.6 μU/mL) at ages 10-16 years relative to an HAZ ≥0.In this American Indian population, findings suggest a strong contribution of overweight/obesity in early childhood to cardiometabolic risks in later childhood and adolescence, mediated through persistent overweight/obesity into later ages. Findings also suggest potential adverse effects of low height-for-age, which require confirmation.

Insulin-like growth factor binding protein 4 (IGFBP4) is involved in adipogenesis, and IGFBP4 null mice have decreased body fat through decreased PPAR-γ expression. In the current study, we assessed whether variation in the IGFBP4 coding region influences body mass index (BMI) in American Indians who are disproportionately affected by obesity. Whole exome sequence data from a population-based sample of 6779 American Indians with longitudinal measures of BMI were used to identify variation in IGFBP4 that associated with BMI. A novel variant that predicts a p.Ser76Thr in IGFBP4 (Thr-allele frequency = 0.02) was identified which associated with the maximum BMI measured during adulthood (BMI 39.8 kg/m

Early puberty onset is associated with higher risk of diabetes, but most studies have not accounted for childhood factors that may confound the association. Using data from a study conducted in an Indigenous community in Arizona (1965-2007) we examined associations of timing and velocity of the adolescent growth spurt with type 2 diabetes, and whether these associations are mediated by childhood BMI and insulinemia. Adolescent growth parameters were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, in 861 participants with height measurements spanning the whole period of growth. In males, older age at take-off, age at peak velocity and age at maturation were associated with decreased prevalence of diabetes (odds ratio [OR]=0.43 per year, 95% CI 0.27-0.69; OR=0.50, 95% CI 0.35-0.72; OR=0.58, 95% CI, 0.41-0.83, respectively), while higher velocity at take-off was associated with increased risk (OR=3.47 per cm/yr, 95% CI 1.87-6.42) adjusting for age, birth year and maternal diabetes. Similar results were observed with incident diabetes. Our findings suggest that an early and accelerated adolescent growth spurt is a risk factor for diabetes, at least in males. These associations are only partially explained by measures of adiposity and insulinemia.

INTRODUCTION: We estimated the effects of cardiorespiratory fitness (CRF) and body mass index (BMI) at baseline on mortality and cardiovascular disease events in people with type 2 diabetes that participated in the Look AHEAD randomized clinical trial. METHODS: Look AHEAD compared effects of an intensive lifestyle intervention with diabetes support and education on cardiovascular disease events in 5,145 adults aged 45–76 years with overweight/obesity and type 2 diabetes. In 4,773 participants, we performed a secondary analysis of the association of baseline CRF during maximal treadmill test (expressed as metabolic equivalents, METs) on mortality and cardiovascular disease events during mean follow-up of 9.2 years. RESULTS: The mean (SD) CRF was 7.2 (2.0) METs. Adjusted for age, sex, race/ethnicity, body mass index, intervention group, and β-blocker use, all-cause mortality rate was 30% lower per SD greater METs (hazard ratio, HR=0.70, 95% CI 0.60–0.81; rate difference, RD=−2.71 deaths/1000 person-years, 95% CI −3.79 to −1.63). Similarly, a SD greater METs predicted lower cardiovascular disease mortality (HR=0.45, RD =−1.65 cases/1000 person-years) and a composite cardiovascular outcome (HR= 0.72; RD=−6.38). Effects of METs were homogeneous on the HR scale for most baseline variables and outcomes but heterogeneous for many on the RD scale, with greater RDs in subgroups at greater risk of the outcomes. For example, all-cause mortality was lower by 7.6 deaths/1000 person-years per SD greater METs in those with a history of cardiovascular disease at baseline but lower by only 1.6 in those without such history. BMI adjusted for CRF had little or no effect on these outcomes. CONCLUSIONS: Greater CRF is associated with reduced risks of mortality and cardiovascular disease events.

This study aimed to identify genetic variants enriched in Southwest American Indian (SWAI) individuals that associate with BMI.Whole genome sequencing data (n = 296) were used to identify potentially functional variants that are common in SWAI individuals (minor allele frequency ≥10%) but rare in other ethnic groups (minor allele frequency 0.1%). Enriched variants were tested for association with BMI in 5,870 SWAI individuals. One variant was studied using a luciferase reporter, and haplotypes that included this variant were analyzed for association with various measures of obesity (n = 917-5,870), 24-hour energy expenditure (24-h EE; n = 419), and skeletal muscle biopsy expression data (n = 207).A 5' untranslated region variant in cytochrome b5 type A (CYB5A), rs548402150, met the enrichment criteria and associated with increased BMI (β = 2%, p = 0.004). Functionally, rs548402150 decreased luciferase expression by 30% (p = 0.003) and correlated with decreased skeletal muscle CYB5A expression (β = -0.5 SD, p = 0.0008). Combining rs548402150 with two splicing quantitative trait loci in CYB5A identified a haplotype carried almost exclusively in SWAI individuals that associated with increased BMI (β = 3%, p = 0.0003) and decreased CYB5A expression, whereas the most common haplotype in all ethnic groups associated with lower BMI and percentage of body fatness, increased 24-h EE, and increased CYB5A expression.Further studies on the effects of CYB5A on 24-h EE and BMI may provide insights into obesity-related physiology.

Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not replicated in the Diabetes Prevention Program (DPP). To assess pharmacogenetic interactions in pre-diabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in metformin (MET, n=876) and placebo (PBO, n=887) arms. Multiple linear regression assessed association with one-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes incidence. We identified four genome-wide significant variants after correcting for correlated traits (pENOSF1 (minor allele frequency [MAF]AFR=0.07, MAFEUR=0.002) was associated with an increase in % glycated hemoglobin (per minor allele β=0.39 [95% CI 0.28, 0.50], p=2.8×10-12). Rs145591055 near OMSR (MAF=0.10 in American Indians), was associated with weight loss (kg) (per G allele β=-7.55 [95% CI -9.88, -5.22], p=3.2×10-10) in MET. Neither variant was significant in PBO; gene-by-treatment interaction was significant for both variants (p(G×T)

Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not replicated in the Diabetes Prevention Program (DPP). To assess pharmacogenetic interactions in pre-diabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in metformin (MET, n=876) and placebo (PBO, n=887) arms. Multiple linear regression assessed association with one-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes incidence. We identified four genome-wide significant variants after correcting for correlated traits (p

While the samples and data from the Pima Indians of the Gila River Indian Community have been included in many international HLA workshops and conferences and have been the focus of numerous population reports and the source of novel alleles at the classical HLA loci, they have not been studied for the non-classical loci. In order to expand our HLA-disease association studies, we typed over 300 whole genome sequences from full Pima heritage members, controlled for first degree relationship, and employed recently developed computer algorithms to resolve HLA alleles. Both classical-HLA-A, -B, and -C- and non-classical- HLA-E, -F, -G, -J, -L, -W, -Y, -DPA2, -DPB2, -DMA, -DMB, -DOA, -DRB2, -DRB9, TAP1- loci were typed at the 4-field level of resolution. We present allele and selected haplotype frequencies, test the genotype distributions for population structure, discuss the issues that are created for tests of Hardy-Weinberg equilibrium over the four sample spaces of high resolution HLA typing, and address the implications for the evolution of non-classical pseudogenes that are no longer expressed in a phenotype subject to natural selection.

Clinical and biomarker phenotypic associations for carriers of protein function-altering variants may help to elucidate gene function and health effects in populations. We genotyped 1127 Strong Heart Family Study participants for protein function-altering single nucleotide variants (SNV) and indels selected from a low coverage whole exome sequencing of American Indians. We tested the association of each SNV/indel with 35 cardiometabolic traits. Among 1206 variants (average minor allele count = 20, range of 1 to 1064), ~ 43% were not present in publicly available repositories. We identified seven SNV-trait significant associations including a missense SNV at ABCA10 (rs779392624, p = 8 × 10–9) associated with fasting triglycerides, which gene product is involved in macrophage lipid homeostasis. Among non-diabetic individuals, missense SNVs at four genes were associated with fasting insulin adjusted for BMI (PHIL, chr6:79,650,711, p = 2.1 × 10–6; TRPM3, rs760461668, p = 5 × 10–8; SPTY2D1, rs756851199, p = 1.6 × 10–8; and TSPO, rs566547284, p = 2.4 × 10–6). PHIL encoded protein is involved in pancreatic β-cell proliferation and survival, and TRPM3 protein mediates calcium signaling in pancreatic β-cells in response to glucose. A genetic risk score combining increasing insulin risk alleles of these four genes was associated with 53% (95% confidence interval 1.09, 2.15) increased odds of incident diabetes and 83% (95% confidence interval 1.35, 2.48) increased odds of impaired fasting glucose at follow-up. Our study uncovered novel gene-trait associations through the study of protein-coding variants and demonstrates the advantages of association screenings targeting diverse and high-risk populations to study variants absent in publicly available repositories.

Background: Some studies suggest that earlier pubertal development is associated with obesity and metabolic disorders in adulthood, but whether accelerated adolescent linear growth spurt influences type 2 diabetes (T2D) in populations at high risk of diabetes is unclear. Aim: To examine associations of age at initiation of the adolescent growth spurt (i.e., take-off) (ATO) , velocity at take-off (VTO) , and age at peak velocity (APV) with T2D incidence. Methods: Height measurements obtained from a longitudinal study of diabetes in American Indians were used to estimate biological growth parameters using the Preece-Baines growth model I, a parametric model of the human growth curve. Diabetes incidence was analyzed among individuals who had ≥ 4 height examinations at ages 5-17 years and who remained nondiabetic at first examination after age 18. Participants were followed until diabetes developed or last examination. Associations of growth parameters with diabetes incidence were analyzed by Poisson regression. Results: Among 649 originally nondiabetic participants, 135 females and 82 males developed diabetes in a median follow-up of years. With adjustment for age, birth date and maternal diabetes, younger ATO and APV were associated with T2D incidence in males (incidence rate ratio (IRR) =1.75 per year, 95% CI, 1.23, 2.50; and IRR=1.33, 95% CI, 1.01, 1.75, respectively) but not in females (IRR=0.93, 95% CI, 0.75, 1.16; and IRR=1.04, 95% CI, 0.86, 1.26, respectively) . Higher VTO was associated with T2D incidence in males (IRR=1.80 per cm/y, 95% CI, 1.15, 2.81) but not in females (IRR=1.15, 95% CI, 0.88, 1.50) . With further adjustment for adult and childhood BMI and fasting insulin, the associations were attenuated for APV and VTO but remained significant for ATO in males. Conclusion: Our findings suggest that an early and accelerated adolescent growth spurt is a risk factor for T2D, at least in males. These associations are only partially explained by measures of adiposity and insulinemia. Disclosure M.J.Ramirez-luzuriaga: n/a. S.Kobes: None. M.Sinha: None. W.C.Knowler: None. R.L.Hanson: None.

Insulin secretion and sensitivity regulate glycemia, with inadequately compensated deficiencies in either or both leading to diabetes. Using data from 2931 participants in the DPP repository, we investigate the effects of lifestyle and metformin interventions and of weight loss on the relationship between insulin secretion and sensitivity. Insulin secretion and sensitivity were estimated from insulin concentrations in fasting and 30-minute post-load serum samples at baseline and at 1, 2, and 3 years after randomization during the active intervention phase of the DPP. The relationship of secretion and sensitivity was evaluated by standardized major axis regression and was found to change over time for participants in the lifestyle and metformin interventions. Distances along and away from the regression line were taken to characterize insulin secretory demand and insulin secretion in compensation to the demand, respectively. Both the metformin and lifestyle interventions decreased secretory demand while increasing compensatory insulin secretion, with greater effects of the lifestyle intervention. Improvements were directly related to the amount of weight loss; decreases in weight significantly reduced secretory demand [b=-0.088 SD (-0.102, -0.074) /5 kg loss] and increased compensatory insulin secretion [b=0.169 SD (0.149, 0.189) /5 kg loss]. In time-dependent hazard models, increasing secretory demand associated with increased diabetes risk [hazard ratio (HR) =1.189 per baseline SD (1.004, 1.413) ] while increasing compensatory insulin secretion associated with lower risk [HR=0.1 (0.080, 0.145) ]. These results are consistent with earlier observations in the DPP that diabetes risk reduction was directly related to the amount of weight loss and suggest that this effect is mediated by lowered insulin secretory demand coupled with improved compensatory insulin secretion. Disclosure W.C. Knowler: None. R.L. Hanson: None.

Gut microbial composition is associated with metabolic risk and differs markedly between industrialized (IND) and non-industrialized (non-IND) populations. Objective: To characterize the gut microbiome of American Indian (AI) children with overweight/obesity relative to IND and non-IND individuals (including ancient AI gut microbiomes) . Methods: Stool samples were from 7-10-year-old AI children with overweight/obesity enrolled in a lifestyle intervention trial on diabetes risk factors (2019-21) . Metagenomic analysis was performed on 39 samples from 25 individuals and compared to samples from age-matched (5-12-year-old) non-AI children in IND (N=380) or non-IND (N=90) populations. Results: Mean age was 8.4 years (SD 1.11) , 44% were male. Mean age-sex-adjusted BMI z-score was 2.12 (SD 0.45) . By principal coordinates analysis, AI samples clustered in an intermediate position between the IND and non-IND samples (Figure 1) . AI children shared microbes with non-IND children that are rare in IND populations but common in ancient AI individuals (Prevotella copri, Coprococcus catus) . Conclusions: The gut microbiome in a subset of AI children is distinct from the non-AI American gut microbiome. Further, AI children may have "inherited" gut microbes from their AI ancestors, which may contribute to differences in their metabolism relative to non-AI children. Disclosure A.Kostic: None. R.L.Hanson: None. M.Sinha: None. Funding American Diabetes Association (1-17-INI-13) ; National Institutes of Health (P30DK036836)

Polygenic scores (PS) for type 2 diabetes (T2D) associate strongly with disease status. Since T2D is heterogenous, using “partitioned” PS (pPS) that capture distinct etiological processes may improve clinical utility. A previous study in Europeans identified 6 pPS from genetic clusters (GCs) based on association patterns across traits, among 3T2D-associated variants: adiposity (GC1) , lipids (GC2) , insulin action (GC3) , beta cell function (GC4, GC5) , and mixed features (GC6) . Few data exist on how pPS associate with T2D and subphenotypes in non-European populations. The current analysis reconstructed these pPS using genotypes for 245 of the 3variants captured in a genome-wide association study in an Indigenous study population from the Southwest US. pPS associations were analyzed with T2D (N=7659) , % body fat (PFAT, non-diabetic only, n=557) , insulin action from hyperinsulinemic-euglycemic “clamp” (logM, non-diabetic only, n=557) , and acute insulin response from an IVGTT (lgAIR, normal glucose tolerance only, n=404) . Results (table) show that T2D pPS strongly associate with the subphenotype corresponding to the putative etiologic mechanism. These results demonstrate transferability of the phenotypic classifications of the T2D pPS and suggest that genetic influences on adiposity, insulin action, and insulin secretion contribute to development of T2D in this population. Disclosure L.E.Wedekind: None. W.Hsueh: None. S.Kobes: None. L.Baier: None. C.Bogardus: None. W.C.Knowler: None. A.Mahajan: Employee; Genentech, Inc. M.Mccarthy: Employee; Genentech, Inc. R.L.Hanson: None.

Microbial resistance to currently available antibiotics poses a great threat in the global fight against infections. An important step in determining bacterial antibiotic resistance can be selective DNA sequence capture and fluorescence labeling. In this paper, we demonstrate the fabrication of simple, robust, inexpensive microfluidic devices for DNA capture and fluorescence detection of a model antibiotic resistance gene sequence. We laser micromachined polymethyl methacrylate microchannels and enclosed them using pressure-sensitive adhesive tapes. We then formed porous polymer monoliths with DNA capture probes in these microchannels and used them for sequence-specific capture, fluorescent labeling, and laser-induced fluorescence detection of picomolar (pM) concentrations of synthetic and plasmid antibiotic resistance gene targets. The relative fluorescence for the elution peaks increased with loaded target DNA concentration. We observed higher fluorescence signal and percent recovery for synthetic target DNA compared to plasmid DNA at the same loaded target concentration. A non-target gene was used for control experiments and produced 3% capture relative to the same concentration of target. The full analysis process including device fabrication was completed in less than 90 min with a limit of detection of 30 pM. The simplicity of device fabrication and good DNA capture selectivity demonstrated herein have potential for application with processes for bacterial plasmid DNA extraction and single-particle counting to facilitate determination of antibiotic susceptibility. Graphical abstract.

AIMS/HYPOTHESIS: Prevalence of type 2 diabetes differs among human ancestry groups, and many hypotheses invoke differential natural selection to account for these differences. We sought to assess the potential role of differential natural selection across major continental ancestry groups for diabetes and related traits, by comparison of genetic and phenotypic differences. METHODS: This was a cross-sectional comparison among 734 individuals from an urban sample (none of whom was more closely related to another than third-degree relatives), including 83 African Americans, 523 American Indians and 128 European Americans. Participants were not recruited based on diabetes status or other traits. BMI was calculated, and diabetes was diagnosed by a 75 g oral glucose tolerance test. In those with normal glucose tolerance (n=434), fasting insulin and 30 min post-load insulin, adjusted for 30 min glucose, were taken as measures of insulin resistance and secretion, respectively. Whole exome sequencing was performed, resulting in 97,388 common (minor allele frequency >5%) variants; the coancestry coefficient (F(ST)) was calculated across all markers as a measure of genetic divergence among ancestry groups. The phenotypic divergence index (P(ST)) was also calculated from the phenotypic differences and heritability (which was estimated from genetic relatedness calculated empirically across all markers in 761 American Indian participants prior to the exclusion of close relatives). Under evolutionary neutrality, the expectation is P(ST)=F(ST), while for traits under differential selection P(ST) is expected to be significantly greater than F(ST.) A bootstrap procedure was used to test the hypothesis P(ST)=F(ST.) RESULTS: With adjustment for age and sex, prevalence of type 2 diabetes was 34.0% in American Indians, 12.4% in African Americans and 10.4% in European Americans (p=2.9×10(−10) for difference among groups). Mean BMI was 36.3, 33.4 and 33.0 kg/m(2), respectively (p=1.9×10(−7)). Mean fasting insulin was 63.8, 48.4 and 45.2 pmol/l (p=9.2×10(−5)), while mean 30 min insulin was 559.8, 553.5 and 358.8 pmol/l, respectively (p=5.7×10(−8)). F(ST) across all markers was 0.130, while P(ST) for liability to diabetes, adjusted for age and sex, was 0.149 (p=0.35 for difference with F(ST)). P(ST) was 0.094 for BMI (p=0.54), 0.095 for fasting insulin (p=0.54) and 0.216 (p=0.18) for 30 min insulin. For type 2 diabetes and BMI, the maximum divergence between populations was observed between American Indians and European Americans (P(ST-MAX)=0.22, p=0.37, and P(ST-MAX)=0.14, p=0.61), which suggests that a relatively modest 22% or 14% of the genetic variance, respectively, can potentially be explained by differential selection (assuming the absence of neutral drift). CONCLUSIONS/INTERPRETATION: These analyses suggest that while type 2 diabetes and related traits differ significantly among continental ancestry groups, the differences are consistent with neutral expectations based on heritability and genetic distances. While these analyses do not exclude a modest role for natural selection, they do not support the hypothesis that differential natural selection is necessary to explain the phenotypic differences among these ancestry groups.

Applying exome sequencing to populations with unique genetic architecture has the potential to reveal novel genes and variants associated with traits and diseases. We sequenced and analyzed the exomes of 6,716 individuals from a Southwestern American Indian (SWAI) population with well-characterized metabolic traits. We found that the SWAI population has distinct allelic architecture compared to populations of European and East Asian ancestry, and there were many predicted loss-of-function (pLOF) and nonsynonymous variants that were highly enriched or private in the SWAI population. We used pLOF and nonsynonymous variants in the SWAI population to evaluate gene-burden associations of candidate genes from European genome-wide association studies (GWASs) for type 2 diabetes, body mass index, and four major plasma lipids. We found 19 significant gene-burden associations for 11 genes, providing additional evidence for prioritizing candidate effector genes of GWAS signals. Interestingly, these associations were mainly driven by pLOF and nonsynonymous variants that are unique or highly enriched in the SWAI population. Particularly, we found four pLOF or nonsynonymous variants in APOB, APOE, PCSK9, and TM6SF2 that are private or enriched in the SWAI population and associated with low-density lipoprotein (LDL) cholesterol levels. Their large estimated effects on LDL cholesterol levels suggest strong impacts on protein function and potential clinical implications of these variants in cardiovascular health. In summary, our study illustrates the utility and potential of exome sequencing in genetically unique populations, such as the SWAI population, to prioritize candidate effector genes within GWAS loci and to find additional variants in known disease genes with potential clinical impact.

AIMS: To examine the associations of average weight and weight velocity in three growth periods from birth through adolescence with type 2 diabetes incidence. METHODS: Child participants representing three growth periods- pre-adolescence (birth to ~8 years), early adolescence (~8 to ~13 years), and late adolescence (~13 to ~18 years) -were selected from a 43-year longitudinal study of American Indians. Age-sex-height-standardized average weight z score and weight z score velocity (change/year) were computed in each period. Participants were followed for up to 25 years from the end of each growth period until they developed diabetes. Associations of average weight z score or weight z score velocity with diabetes incidence were determined with sex-, birth date- and maternal diabetes-adjusted Poisson regression models. RESULTS: Among 2,100 participants representing the pre-adolescence growth period, 1,558 representing the early adolescence period, and 1,418 representing the late adolescence period, there were 290, 315, and 380 incident diabetes cases, respectively. During the first 10 years of follow-up, diabetes incidence rate ratio was 1.72 (95% CI 1.40–2.11)/standard deviation (SD) of log(10)weight z score mean in pre-adolescence, 2.09 (1.68–2.60)/SD of log(10)weight z score mean in early adolescence, and 1.85 (1.58–2.17)/SD of log(10)weight z score mean in late adolescence. Diabetes incidence rate ratio was 1.79 (1.49–2.17)/SD of log(10)weight z score velocity pre-adolescence, 1.13 (0.91–1.41)/SD log(10)weight z score velocity in early adolescence, and 1.29 (1.09–1.51)/SD log(10)weight z score velocity in late adolescence. There were strong correlations in the average weight z scores and weak correlations in the weight z score velocities between successive periods. CONCLUSIONS: Higher weight and accelerated weight gain in all growth periods associates with increased type 2 diabetes risk. Importantly, higher weight and greater weight velocity pre-adolescence jointly associate with the highest type 2 diabetes risk.

The Pima Indians of the Gila River Indian Community in Arizona have participated in a long-range study of type 2 diabetes mellitus since 1965 and have been the subject of HLA typing and population studies since the early days of serological assays. These data have been in numerous HLA workshops and conferences and have been the source of at least five novel alleles at the classical HLA loci. In recent time nearly the entire study group was subject to next generation sequencing by whole genome or exome technologies, which has allowed us to HLA type over 3000 full heritage persons with recently developed computer algorithms. We present here the results for the classical HLA Loci: HLA-A, B, C, DRA, DRB1, DRB3, DRB4, DRB5, DPA1, DPB1, DQA1, and DQB1 to the third field of resolution for synonymous alleles and type the likely four field resolution alleles from the subset of whole genome sequences. Allele frequencies, and haplotype frequencies at up to five loci, are presented as well as measures of population structure and heterozygosity. We define a core set of HLA variation that approximates the distribution for the Paleo-Indians and impute nine-locus, 4-field haplotypes that are expected to be common in full heritage peoples.

PURPOSE OF REVIEW: The present review focuses on the epidemiology of type 2 diabetes (T2D) in Indigenous communities in the continental United States (U.S.)—including disease prevention and management—and discusses special considerations in conducting research with Indigenous communities. RECENT FINDINGS: Previous studies have reported the disparately high prevalence of diabetes, especially T2D, among Indigenous peoples in the U.S. The high prevalence and incidence of early-onset T2D in Indigenous youth relative to that of all youth in the U.S. population poses challenges to the prevention of complications of diabetes. SUMMARY: Behavioral, dietary, lifestyle and genetic factors associated with T2D in Indigenous communities are often investigated. More limited is discussion of the historical and ongoing consequences of colonization and displacement that impact the aforementioned risk factors. Future research is necessary to assess community-specific needs with respect to diabetes prevention and management across the diversity of Indigenous communities in the U.S.

We assessed whether the relationship between insulin secretion and sensitivity predicted development of type 2 diabetes in American Indians participating in a longitudinal epidemiologic study. At baseline, when all subjects did not have diabetes, 1566 participants underwent oral tests and 420 had intravenous measures of glucose regulation with estimates of insulin secretion and sensitivity. Standardized major axis regression was used to study the relationship of secretion and sensitivity. Distances away from and along the regression line estimated compensatory insulin secretion and secretory demand, respectively. This relationship differed according to glucose tolerance and BMI categories. The distance away from the line is similar to the disposition index (DI) defined as the product of estimated secretion and sensitivity, but the regression line may differ from a line with constant DI (i.e., it is not necessarily hyperbolic). Subjects with the same DI but different levels of insulin secretion and sensitivity had different incidence rates of diabetes; lower sensitivity with higher secretory demand was associated with greater diabetes risk. Insulin secretion and insulin sensitivity, analyzed together, predict diabetes better than DI alone. Physiologically, this may reflect long-term risk associated with increased allostatic load resulting from the stimulation of insulin hypersecretion by increased glycemia.

We assessed whether the relationship between insulin secretion and sensitivity predicted development of type 2 diabetes in American Indians participating in a longitudinal epidemiologic study. At baseline, when all participants did not have diabetes, 1,566 underwent oral tests and 420 had intravenous measures of glucose regulation, with estimates of insulin secretion and sensitivity. Standardized major axis regression was used to study the relationship between secretion and sensitivity. Distances away from and along the regression line estimated compensatory insulin secretion and secretory demand, respectively. This relationship differed according to glucose tolerance and BMI category. The distance away from the line is similar to the disposition index (DI), defined as the product of estimated secretion and sensitivity, but the regression line may differ from a line with constant DI (i.e., it is not necessarily hyperbolic). Participants with the same DI but different levels of insulin secretion and sensitivity had different incidence rates of diabetes; lower sensitivity with higher secretory demand was associated with greater diabetes risk. Insulin secretion and insulin sensitivity, analyzed together, predict diabetes better than DI alone. Physiologically, this may reflect long-term risk associated with increased allostatic load resulting from the stimulation of insulin hypersecretion by increased glycemia.

Emerging antimicrobial drug resistance is increasing the complexity involved in treating critical conditions such as bacterial induced sepsis. Methods for diagnosing specific drug resistance tend to be rapid or sensitive, but not both. Detection methods like sequence-specific single-molecule analysis could address this concern if they could be adapted to work on smaller targets similar to those produced in traditional clinical situations. In this work we demonstrate that a 120 bp double stranded polynucleotide with an overhanging single stranded 25 bp probe sequence can be created by immobilizing DNA with a biotin/streptavidin magnetic bead system, labeling with SYBR Gold, and rinsing the excess away while the probe retains multiple fluorophores. These probes with multiple fluorophores can then be used to label a bacterial plasmid target in a sequence-specific manner. These probes enabled the detection of 1 pM plasmid samples containing a portion of an antibiotic resistance gene sequence. This system shows the possibility of improving capture and fluorescence labeling of small nucleic acid fragments, generating lower limits of detection for clinically relevant samples while maintaining rapid processing times.

There is considerable evidence that birth weight is associated with increased risk of type 2 diabetes (T2D) in adulthood. However, evidence from populations with high prevalence of T2D on the genetic relationships between birth weight and T2D is limited. Data were obtained from a genome-wide association study (GWAS) in an Indigenous population from the Southwest US with high prevalence of T2D in which the relationship of T2D with birth weight is “U-shaped." Weighted polygenic scores (PSs) were constructed using imputed genotypes for genome-wide significant single-nucleotide polymorphisms (SNPs) from GWAS meta-analyses for birth weight (EGG Consortium, 126 SNPs) and T2D (DIAGRAM Consortium, 293 SNPs). Associations of birth weight PS and T2D PS with T2D and birth weight were calculated, accounting for participants’ pairwise relationships, using linear mixed models. Birth weight data (n=3700) were normalized separately by sex and analyzed for associations, adjusted for birth year, gestational age and the first 5 genetic principal components (PCs). T2D (n=7659) data were analyzed for associations, adjusted for age, sex, birth year and the first 5 genetic PCs. Birth weight PS had a significant, positive association with birth weight (β=0.134 SD birth weight per SD PS (95% CI 0.101, 0.168); p=4.1×10-15). The T2D PS was likewise significantly, positively associated with T2D (OR=1.48 per SD (1.38, 1.58); p=8.1×10-31). The birth weight PS was significantly, inversely associated with T2D (OR=0.91 (0.85, 0.97); p=0.0043); we found no evidence for a non-linear relationship between birth weight PS and T2D (p=0.80). The T2D PS was not significantly associated with birth weight (β=-0.005 (-0.040, 0.030); p=0.80). Results indicate that genetic variants that associate with birth weight and T2D from larger European GWAS largely also influence these traits in this Indigenous population. Current findings also support the notion that many variants conferring susceptibility to low birth weight also confer susceptibility to T2D. Disclosure L. E. Wedekind: None. W. Hsueh: None. M. Olaiya: None. S. Kobes: None. L. Baier: None. W. C. Knowler: None. A. Mahajan: Employee; Self; Genentech, Inc. M. Mccarthy: Employee; Self; Genentech, Inc. R. L. Hanson: None.

Background: Growth abnormalities in early childhood have been related to later metabolic risk, but little is known about these associations in populations at high risk of diabetes. Methods: We linked anthropometric data collected at ages 0- Results: In age and sex-adjusted models, overweight and obesity (WHZ > 2) at ages 0- Conclusion: These analyses suggest that both overweight/obesity and low height-for-age in early childhood can influence subsequent metabolic risk in American Indian children and adolescents. Disclosure M. J. Ramirez-luzuriaga: None. S. Kobes: None. M. Sinha: None. W. C. Knowler: None. R. L. Hanson: None.

Genome-wide significant (GWS) loci for glycemic response to MET in type 2 diabetes (T2D) reported elsewhere have not replicated in the DPP. Thus, to assess whether pharmacogenetic interactions may differ in impaired glucose tolerance (IGT), we conducted a GWAS in the DPP for MET response, defined by diabetes incidence and change in quantitative traits (fasting glucose, 2-hour glucose on oral glucose tolerance test, hemoglobin A1c [HbA1c], fasting insulin, insulin sensitivity index, and weight). Samples were genotyped on the Illumina HumanCore Exome array and imputed on the 1000 Genomes Phase3 panel. Cox proportional hazards models tested associations with diabetes incidence in MET (n=876) and placebo (PBO, n=887) arms. Multiple linear regression using an additive model evaluated for association with 1-year change in quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-environment (G×E) interaction between MET and PBO. Results were filtered to minor allele frequency (MAF) >1% and imputation score >0.7. We identified 3 GWS variants after correcting for correlated traits (P In summary, a GWAS for MET response in participants with IGT revealed novel associations that require validation in ancestry-specific populations and may have implications for tailored therapy. Disclosure J. H. Li: None. R. L. Hanson: None. S. E. Kahn: Advisory Panel; Self; Bayer AG, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck & Co., Inc., Novo Nordisk, Pfizer Inc. W. C. Knowler: None. T. I. Pollin: None. J. C. Florez: Consultant; Self; Goldfinch Bio, Inc., Other Relationship; Self; Novo Nordisk. D. Research group: None. J. A. Perry: None. K. A. Jablonski: None. L. Chen: None. S. Srinivasan: None. J. N. Todd: None. M. Harden: None. J. M. Mercader: None. P. W. Franks: Advisory Panel; Self; Zoe Global Limited, Consultant; Self; Eli Lilly and Company, Novo Nordisk. Funding National Institute of Diabetes and Digestive and Kidney Diseases (U01DK048489)

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Background In type 2 diabetes (T2DM), the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation for estimated glomerular filtration rate (eGFR) systematically underestimates the measured adjusted glomerular filtration rate (aGFR) when aGFR is high. We studied the extent to which glycemic variables associate with kidney function, and developed equations including these variables that estimate aGFR in people with T2DM. Methods Diabetic Pima people had aGFR measured from iothalamate clearance divided by body surface area. eGFRs 2 were excluded. Multivariate linear regression identified variables correlated with kidney function. We constructed equations for approximating aGFR. Correlation analysis and 10-fold cross-validation were used to compare the CKD-EPI equation and the new approximating equations to the measured aGFR. Ability to detect hyperfiltration, defined as aGFR > 120 ml/min/1.73m2, was compared by analysis of receiver-operating (ROC) curves. Results aGFR was measured 2798 times in 269 individuals. HbA1c, fasting plasma glucose (FPG), age, and serum creatinine (SCR) were significantly associated with aGFR. The best equations for approximating aGFR used HbA1c and FPG in addition to age and SCR. They approximate aGFR in this cohort of obese people with T2DM more precisely than the CKD-EPI equation. Analysis of ROC curves show that these equations detect hyperfiltration better than does the CKD-EPI equation. Conclusions HbA1c, FPG, age, and SCR yielded the best equations for estimating aGFR in these subjects. The new equations identify hyperfiltration better than the CKD-EPI equation in this cohort and may inform clinical decisions regarding hyperfiltration in individuals with T2DM.

Preterm birth (PTB) related health problems take over one million lives each year, and currently, no clinical analysis is available to determine if a fetus is at risk for PTB. Here, we describe the preparation of a key PTB risk biomarker, thrombin-antithrombin (TAT), and characterize it using dot blots, mass spectrometry, and microchip electrophoresis (μCE). The pH for fluorescently labeling TAT was also optimized using spectrofluorometry and spectrophotometry. The LOD of TAT was measured in μCE. Lastly, TAT was combined with six other PTB risk biomarkers and separated in μCE. The ability to make and characterize TAT is an important step toward the development of an integrated microfluidic diagnostic for PTB risk.

Epigenetic changes might provide the biological explanation for the long-lasting impact of metabolic alterations of diabetic kidney disease development. Here we examined cytosine methylation of human kidney tubules using Illumina Infinium 450 K arrays from 91 subjects with and without diabetes and varying degrees of kidney disease using a cross-sectional design. We identify cytosine methylation changes associated with kidney structural damage and build a model for kidney function decline. We find that the methylation levels of 65 probes are associated with the degree of kidney fibrosis at genome wide significance. In total 471 probes improve the model for kidney function decline. Methylation probes associated with kidney damage and functional decline enrich on kidney regulatory regions and associate with gene expression changes, including epidermal growth factor (EGF). Altogether, our work shows that kidney methylation differences can be detected in patients with diabetic kidney disease and improve kidney function decline models indicating that they are potentially functionally important., Patients with diabetes commonly develop diabetic kidney disease (DKD). Here Gluck et al. identify a set of probes differentially methylated in renal samples from patients with DKD, and find that inclusion of these methylation probes improves current prediction models of renal function decline.

IntroductionSouth Asians (SA) and Pima Indians have high prevalence of diabetes but differ markedly in body size. We hypothesize that young SA will have higher diabetes incidence than Pima Indians at comparable body mass index (BMI) levels.Research design and methodsWe used prospective cohort data to estimate age-specific, sex, and BMI-specific diabetes incidence in SA aged 20–44 years living in India and Pakistan from the Center for Cardiometabolic Risk Reduction in South Asia Study (n=6676), and compared with Pima Indians, from Pima Indian Study (n=1852).ResultsAt baseline, SA were considerably less obese than Pima Indians (BMI (kg/m2): 24.4 vs 33.8; waist circumference (cm): 82.5 vs 107.0). Age-standardized diabetes incidence (cases/1000 person-years, 95% CI) was lower in SA than in Pima Indians (men: 14.2, 12.2–16.2 vs 37.3, 31.8–42.8; women: 14.8, 13.0–16.5 vs 46.1, 41.2–51.1). Risk of incident diabetes among 20–24-year-old Pima men and women was six times (relative risk (RR), 95% CI: 6.04, 3.30 to 12.0) and seven times (RR, 95% CI: 7.64, 3.73 to 18.2) higher as compared with SA men and women, respectively. In those with BMI 2, however, the risk of diabetes was over five times in SA men than in Pima Indian men. Among those with BMI ≥30 kg/m2, diabetes incidence in SA men was nearly as high as in Pima men. SA and Pima Indians had similar magnitude of association between age, sex, BMI, and insulin secretion with diabetes. The effect of family history was larger in SA, whereas that of insulin resistance was larger in Pima IndiansConclusionsIn the background of relatively low insulin resistance, higher diabetes incidence in SA is driven by poor insulin secretion in SA men. The findings call for research to improve insulin secretion in early natural history of diabetes.

Insulin is an essential hormone that regulates glucose homeostasis and metabolism. Insulin resistance (IR) arises when tissues fail to respond to insulin, and it leads to serious health problems including Type 2 Diabetes (T2D). Obesity is a major contributor to the development of IR and T2D. We previously showed that gene expression of alcohol dehydrogenase 1B (ADH1B) was inversely correlated with obesity and IR in subcutaneous adipose tissue of Mexican Americans. In the current study, a meta-analysis of the relationship between ADH1B expression and BMI in Mexican Americans, African Americans, Europeans, and Pima Indians verified that BMI was increased with decreased ADH1B expression. Using established human subcutaneous pre-adipocyte cell lines derived from lean (BMI −2) or obese (BMI ≥ 30 kg m−2) donors, we found that ADH1B protein expression increased substantially during differentiation, and overexpression of ADH1B inhibited fatty acid binding protein expression. Mature adipocytes from lean donors expressed ADH1B at higher levels than obese donors. Insulin further induced ADH1B protein expression as well as enzyme activity. Knockdown of ADH1B expression decreased insulin-stimulated glucose uptake. Our findings suggest that ADH1B is involved in the proper development and metabolic activity of adipose tissues and this function is suppressed by obesity.

Background: There is limited information on how polygenic scores (PSs) — based on variants from genome-wide association studies (GWAS) of T2D — add to clinical variables in predicting T2D incidence. Methods: For participants in a longitudinal study in an Indigenous population from the Southwest United States (US) with high T2D prevalence, we analyzed 10 constructions of PS using publicly available GWAS summary statistics. T2D incidence was examined in three cohorts of individuals without T2D at baseline. The adult cohort, comprised of 2333 participants followed from age≥20y, had 640 T2D cases. The youth cohort was comprised of 2229 participants followed from age 5-19y (228 cases). The birth cohort was comprised of 2894 participants followed from birth (438 cases). We assessed contributions of the PS and clinical variables in predicting T2D incidence. Results: Of the 10 PS constructions, a PS using 293 genome-wide significant variants from a large T2D GWAS meta-analysis in European-ancestry populations performed best. In the adult cohort, area under the receiver operating characteristic curve (AUC) for clinical variables for prediction of T2D incidence was 0·728; with the PS, 0·735. The PS’s hazard ratio (HR) was 1.27 per SD (p=1·6×10-8; 95% CI 1·17-1·38). In the youth cohort, the analogous model’s AUC was 0·805; with the PS, 0·812. The PS’s HR was 1·49 (p=4·3×10-8; 95% CI 1·29-1·72). In the birth cohort, AUC for the clinical variables was 0·614; with the PS, 0·685. The PS’s HR was 1·48 (p=2·8×10-16; 95% CI 1·35-1·63). To further assess the potential impact of including PS for assessing individual T2D risk, the net reclassification improvement (NRI) was calculated: NRI for the PS was 0·264, 0·249, and 0·309 for adult, youth, and birth cohorts, respectively. For comparison, NRI for HbA1c was 0·292 and 0·150 for adult and youth cohorts, respectively. Across all cohorts, as estimated using decision curve analyses, the net benefit of including the PS in addition to clinical variables was most pronounced at moderately stringent threshold probability (pt) values for instituting a preventive intervention. Discussion: This study demonstrates that the PS contributes significantly to prediction of T2D incidence in addition to the information provided by clinical factors; however, overall improvement of the prediction model was modest. Discriminatory power of the PS for predicting incident T2D was similar to that of other commonly measured clinical factors (e.g. HbA1c). Including T2D PS in addition to clinical factors may be clinically beneficial for identifying individuals at higher risk for T2D, especially at younger ages. Funding Statement: This study used computational resources of the Biowulf system at the National Institutes of Health (NIH), Bethesda, MD. The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Intramural Research Program provided support for NIDDK-based coauthors. The NIH Oxford-Cambridge Scholars Program provided funding support for L.E.W.’s doctoral programme. M.I.M. was a Wellcome Senior Investigator and an NIHR Senior Investigator. This work was funded in Oxford by the Wellcome Trust (098381, 106130, 203141), NIH (U01- DK105535; U01-DK085545) and National Institute for Health Research (NIHR) (NF-SI-0617- 10090) and Oxford Biomedical Research Centre (BRC). Declaration of Interests: The views expressed in this article are those of the author(s) and not necessarily those of NIH, NHS, NIHR, or UK Department of Health. M.I.M. has served on advisory panels for Pfizer, Novo Nordisk, and Zoe Global; has received honoraria from Merck, Pfizer, Novo Nordisk, and Eli Lilly; and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, M.I.M. and A.M. are employees of Genentech and holders of Roche stock. Ethics Approval Statement: Protocols were approved by the institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases.

Objective In an ongoing effort to identify the genetic variation that contributes to obesity in American Indians, known Bardet–Biedl syndrome (BBS) genes were analyzed for an effect on BMI and leptin signaling. Methods Potentially deleterious variants (Combined Annotation Dependent Depletion score > 20) in BBS genes were identified in whole‐exome sequence data from 6,851 American Indians informative for BMI. Common variants (detected in ≥ 10 individuals) were analyzed for association with BMI; rare variants (detected in 40 kg/m2), four were in BBS9. In vitro analysis of BBS9 found the Ile allele at Thr549Ile had a 20% increase in STAT3 activity compared with the Thr allele (P = 0.01). Western blot analysis showed the Ile allele had a 15% increase in STAT3 phosphorylation (P = 0.006). Comparable functional results were observed with Ser545Gly and Val209Leu but not Leu665Phe and Lys810Glu. Conclusions Potentially functional variants in BBS genes in American Indians are reported. However, functional evidence supporting a causal role for BBS9 in obesity is inconclusive.

Bacterial pathogens resistant to antibiotics have become a serious health threat. Those species which have developed resistance against multiple drugs such as the carbapenems, are more lethal as these are last line therapy antibiotics. Current diagnostic tests for these resistance traits are based on singleplex target amplification techniques which can be time consuming and prone to errors. Here, we demonstrate a chip based optofluidic system with single molecule sensitivity for amplification-free, multiplexed detection of plasmids with genes corresponding to antibiotic resistance, within one hour. Rotating disks and microfluidic chips with functionalized polymer monoliths provided the upstream sample preparation steps to selectively extract these plasmids from blood spiked with E. coli DH5α cells. Waveguide-based spatial multiplexing using a multi-mode interference waveguide on an optofluidic chip was used for parallel detection of three different carbapenem resistance genes. These results point the way towards rapid, amplification-free, multiplex analysis of antibiotic-resistant pathogens.

Southwest American Indians (SAI) suffer from a high obesity prevalence. We previously reported that rs7238987, in cytochrome B5 type A (CYB5A), strongly associated with increased body mass index (BMI) in a population-based study of SAI. CYB5A plays a role in fatty acid oxidation (FAO) and reductions in FAO have been linked to weight gain. However, in vitro studies did not confirm a functional effect of this variant. Therefore, the goal of the current study was to assess variation across the entire CYB5A locus to identify the causal variant contributing to obesity in this population. Genotypic data from a custom Axiom genotyping array on 7,700 SAI was merged with whole-genome sequence data from 335 SAI to impute variation within and 10,000 bp surrounding the CYB5A gene. This region contained 316 variants with a minor allele frequency >0.01; 3 variants had a Combined Annotation Dependent Depletion (CADD) score >10 (top 10% most likely to be deleterious) and a BMI association P ≤ 0.001 (adjusted for age, sex, birth year and the first 5 genetic principle components). Among these potentially deleterious variants, the obesity-risk T-allele in rs548402150, also significantly associated (P = 0.00003) with decreased CYB5A expression in skeletal muscle from biopsy data (n=207). Therefore, rs548402150 was prioritized for functional studies. This C/T variation falls within a CTCF consensus site in the 5’-UTR, which could have the ability to effect gene expression levels. In vitro luciferase reporter assays were used to assess altered promoter activity in human skeletal muscle cells. A 30% decrease in luciferase expression was identified for the promoter carrying the obesity-risk T-allele compared to the non-risk C-allele (P = 0.003). In summary, the further exploration of CYB5A using imputed data has identified a potential casual variant for the observed decreased CYB5A expression and increased risk of obesity in this population. Disclosure S.E. Day: None. M. Traurig: None. P. Piaggi: None. P. Kumar: None. S. Kobes: None. R.L. Hanson: None. C. Bogardus: None. L. Baier: None.

Our recent genome-wide association study (GWAS) identified variants strongly associated with type 2 diabetes (T2D) on chromosome 11p15 in American Indians at KCNQ1 (index variant rs2237895, P=2.5×10-8) and TH (rs11564707, P=3.8×10-8). To assess whether these variants influence epigenetic variation we analyzed associations with DNA methylation. Participants included 7659 American Indians (33% with T2D) who had participated in the GWAS, 842 of whom had DNA methylation measured in peripheral blood. Methylation was measured with the Infinium 450k array (Illumina, San Diego, CA). To identify local CpG sites associated with index variants, we analyzed associations for sites within 1 Mb of each gene (2162 sites for KCNQ1, 2325 for TH). Strong associations were identified: the diabetes risk allele at rs2237895 associated with decreased methylation at cg14637411 (β= 1.35 SD per copy, P=2.6×10-169), and the risk allele at rs11564707 associated with increased methylation at cg19878200 (β=0.46 SD, P=1.1×10-21). We further conducted Bayesian functional fine-mapping association of T2D and statistical colocalization of association of methylation at these sites with T2D using CAVIAR- including 1943 variants for KCNQ1 and 2954 variants for TH. Potentially causal variants for T2D were identified for each gene (30 for KCNQ1 and 33 for TH with posterior probability of causality >0.01); all were in strong linkage disequilibrium with the index variant. Strong evidence for colocalization of the association of T2D with methylation at cg14637411 (colocalization posterior probability >0.01, suggesting both traits are influenced by the same causal variants) was seen with 4 KCNQ1 variants: rs60808706, rs2299620, rs2237896 and rs2237897. Evidence for colocalization was weak for cg19878200 and T2D at TH variants. These results support the notion that KCNQ1 variants may influence T2D risk via an epigenetic effect, and they identify candidate functional variants. Disclosure R.L. Hanson: None. S. Kobes: None. W. Hsueh: None. Y.L. Muller: None. W.C. Knowler: None. L. Baier: None. Funding American Diabetes Association (1-12-DNP-01 to R.L.H.)

Ecological studies have shown different risks for diabetes (DM) among many ethnic groups, but whether they are due to genetic or non-genetic factors is hard to dissect. We conducted a community-based study aimed at identifying risk factors for DM and related traits in Pacific Islanders from Guam and Saipan. We analyzed the genetic structure of our sample and estimated individual-level admixture using genome-wide SNP data (49,300 variants). We found that genetic ancestry largely derived from 5 populations, representing Marianas Islanders (MI) (mean % heritage, or μ=43%), East Asians (EA, μ=22%), Micronesians (MC, μ=19%), Europeans (EU, μ=13%), and Melanesians (ML, μ=3%). We then tested the association of ancestry estimates with DM, fasting glucose and fasting insulin levels in study participants (n=1,853). Covariates included age, sex and end-stage kidney disease. For fasting insulin, only nondiabetic subjects were used in analyses. All 3 traits were associated with genetic ancestry (p In summary, there were large and statistically significant differences in DM-related traits among Pacific Islanders with different genetic ancestral backgrounds. Although genetic ancestry estimates may still be confounded by shared environmental factors, the present findings suggest that admixture mapping may be a potentially powerful approach for identifying unique DM loci in Pacific Islanders. Disclosure W. Hsueh: None. P. Kumar: None. S. Safabakhsh: None. L. Jones: None. J. Curran: None. W.C. Knowler: None. R.G. Nelson: None. R.L. Hanson: None.

To identify variants that potentially impact human body fat via a role in adipogenesis, we analyzed whole-exome sequence data from a population-based sample of 6809 American Indians with longitudinal measures of BMI. A total of 623,236 exonic variants were detected and those that met the following criteria were prioritized for functional analysis: 1) non-synonymous, stop-gain or frameshift that occurred in ≥5 individuals; 2) a Combined Annotation Dependent Depletion (CADD) score ≥10 (top 10% of deleterious variants); 3) evidence for association with maximum BMI in adulthood (n=6002) or maximum BMI z-score in childhood (n=4882) (P In conclusion, whole-exome sequencing followed by in vitro analysis of lipid accumulation in OP9 cells has identified coding variants that may impact BMI via a role in adipogenesis. Disclosure Y.L. Muller: None. S.E. Day: None. C. Koroglu: None. S. Kobes: None. R.L. Hanson: None. W.C. Knowler: None. H. Kim: Employee; Self; Regeneron Pharmaceuticals. C. Van Hout: Employee; Self; Regeneron Genetics Center. N. Gosalia: None. A.R. Shuldiner: Employee; Self; Regeneron Genetics Center. Stock/Shareholder; Self; Regeneron Pharmaceuticals. C. Bogardus: None. L. Baier: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases