Novel signals and polygenic score for height are associated with pubertal growth traits in Southwestern American Indians.

Most genetic variants associated with adult height have been identified through large genome-wide association studies (GWASs) in European-ancestry cohorts. However, it is unclear how these variants influence linear growth during adolescence. This study uses anthropometric and genotypic data from a longitudinal study conducted in an American Indian community in Arizona between 1965-2007. Growth parameters (i.e. height, velocity, and timing of growth spurt) were derived from the Preece-Baines growth model, a parametric growth curve fitted to longitudinal height data, in 787 participants with height measurements spanning the whole period of growth. Heritability estimates suggested that genetic factors could explain 25% to 71% of the variance of pubertal growth traits. We performed a GWAS of growth parameters, testing their associations with 5 077 595 imputed or directly genotyped variants. Six variants associated with height at peak velocity (P < 5 × 10-8, adjusted for sex, birth year and principal components). Implicated genes include NUDT3, previously associated with adult height, and PACSIN1. Two novel variants associated with duration of growth spurt (P < 5 × 10-8) in LOC105375344, an uncharacterized gene with unknown function. We finally examined the association of growth parameters with a polygenic score for height derived from 9557 single nucleotide polymorphisms (SNPs) identified in the GIANT meta-analysis for which genotypic data were available for the American Indian study population. Height polygenic score was correlated with the magnitude and velocity of height growth that occurred before and at the peak of the adolescent growth spurt, indicating overlapping genetic architecture, with no influence on the timing of adolescent growth.

Epistasis Between HLA-DRB1*16:02:01 and SLC16A11 T-C-G-T-T Reduces Odds for Type 2 Diabetes in Southwest American Indians.

We sought to identify genetic/immunologic contributors of type 2 diabetes in an indigenous American community by genotyping all study participants for both high resolution HLA-DRB1 alleles and SLC16A11 to test their risk and/or protection for T2D. These genes were selected based on independent reports that HLA-DRB1*16:02:01 is protective for T2D and that SLC16A11 associates with T2D in individuals with BMI<35kg/m2, and here test the interaction of the two loci with a more complete dataset and perform a BMI sensitivity test. We define the risk-protection haplotype of SLC16A11, T-C-G-T-T, as allele "2" of a di-allelic genetic model with three genotypes, SLC16A11*11, *12, and *22, where allele "1" is the wildtype. Both earlier findings were confirmed. Together in the same logistic model with BMI≥35, DRB1*16:02:01 remains protective, 0.73, while SLC16A11 switches from risk to protection OR = 0.57 (*22) and 0.78 (*12), respectively; an added interaction term was statistically significant (OR = 0.49 with *12). Bootstrapped (b=10,000) statistical power of interaction, 0.4801, yielded mean OR = 0.43. Sensitivity analysis demonstrated the interaction significant in BMI range 30-41. To investigate the epistasis we used the primary function of the HLA-DRB1 molecule, peptide binding and presentation, to search the entire array of 15mer peptides for both the wildtype and ancient human SLC16A11 molecules for a pattern of strong binding that was associated with risk and protection for T2D. Applying computer binding algorithms suggests the core peptide at SLC16A11 D127G, FSAFASGLL, might be key for moderating risk for T2D with potential implications for T1D.

Diagnostic criteria and etiopathogenesis of type 2 diabetes and its complications: Lessons from the Pima Indians.

The Phoenix Epidemiology and Clinical Research Branch of the National Institute of Diabetes and Digestive and Kidney Diseases has conducted prospective studies of diabetes and its complications in the Pima Indians living in Arizona, USA for over 50 years. In this review we highlight areas in which these studies provided vital insights into the criteria used to diagnose type 2 diabetes, the pathophysiologic changes that accompany the development of type 2 diabetes, and the course and determinants of diabetes complications-focusing specifically on diabetic kidney disease. We include data from our longitudinal population-based study of diabetes and its complications, studies on the role of insulin resistance and insulin secretion in the pathophysiology of type 2 diabetes, and in-depth studies of diabetic kidney disease that include measures of glomerular function and research kidney biopsies. We also focus on the emerging health threat posed by youth-onset type 2 diabetes, which was first seen in the Pima Indians in the 1960s and is becoming an increasing issue worldwide.

The power of TOPMed imputation for the discovery of Latino-enriched rare variants associated with type 2 diabetes.

AIMS/HYPOTHESIS: The Latino population has been systematically underrepresented in large-scale genetic analyses, and previous studies have relied on the imputation of ungenotyped variants based on the 1000 Genomes (1000G) imputation panel, which results in suboptimal capture of low-frequency or Latino-enriched variants. The National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) released the largest multi-ancestry genotype reference panel representing a unique opportunity to analyse rare genetic variations in the Latino population. We hypothesise that a more comprehensive analysis of low/rare variation using the TOPMed panel would improve our knowledge of the genetics of type 2 diabetes in the Latino population. METHODS: We evaluated the TOPMed imputation performance using genotyping array and whole-exome sequence data in six Latino cohorts. To evaluate the ability of TOPMed imputation to increase the number of identified loci, we performed a Latino type 2 diabetes genome-wide association study (GWAS) meta-analysis in 8150 individuals with type 2 diabetes and 10,735 control individuals and replicated the results in six additional cohorts including whole-genome sequence data from the All of Us cohort. RESULTS: Compared with imputation with 1000G, the TOPMed panel improved the identification of rare and low-frequency variants. We identified 26 genome-wide significant signals including a novel variant (minor allele frequency 1.7%; OR 1.37, p=3.4 × 10-9). A Latino-tailored polygenic score constructed from our data and GWAS data from East Asian and European populations improved the prediction accuracy in a Latino target dataset, explaining up to 7.6% of the type 2 diabetes risk variance. CONCLUSIONS/INTERPRETATION: Our results demonstrate the utility of TOPMed imputation for identifying low-frequency variants in understudied populations, leading to the discovery of novel disease associations and the improvement of polygenic scores. DATA AVAILABILITY: Full summary statistics are available through the Common Metabolic Diseases Knowledge Portal ( https://t2d.hugeamp.org/downloads.html ) and through the GWAS catalog ( https://www.ebi.ac.uk/gwas/ , accession ID: GCST90255648). Polygenic score (PS) weights for each ancestry are available via the PGS catalog ( https://www.pgscatalog.org , publication ID: PGP000445, scores IDs: PGS003443, PGS003444 and PGS003445).

The utility of a type 2 diabetes polygenic score in addition to clinical variables for prediction of type 2 diabetes incidence in birth, youth and adult cohorts in an Indigenous study population.

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.

Identification and characterization of the long non-coding RNA NFIA-AS2 as a novel locus for body mass index in American Indians.

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 < 10-3 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.

Effects of the ABCC8 R1420H loss-of-function variant on beta-cell function, diabetes incidence, and retinopathy.

INTRODUCTION: The ABCC8 gene regulates insulin secretion and plays a critical role in glucose homeostasis. The effects of an ABCC8 R1420H loss-of-function variant on beta-cell function, incidence of type 2 diabetes, and age-at-onset, prevalence, and progression of diabetes complications were assessed in a longitudinal study in American Indians. RESEARCH DESIGN AND METHODS: We analyzed beta-cell function through the relationship between insulin secretion and insulin sensitivity in members of this population without diabetes aged ≥5 years using standard major axis regression. We used hierarchical logistic regression models to study cross-sectional associations with diabetes complications including increased albuminuria (albumin-to-creatinine ratio (ACR) ≥30 mg/g), severe albuminuria (ACR ≥300 mg/g), reduced estimated glomerular filtration rate (eGFR <60 mL/min/1.73 m2), and retinopathy. This study included 7675 individuals (254 variant carriers) previously genotyped for the R1420H with available phenotypic data and with a median follow-up time of 13.5 years (IQR 4.5-26.8). RESULTS: Variant carriers had worse beta-cell function than non-carriers (p=0.0004; on average estimated secretion was 22% lower, in carriers), in children and adults, with no difference in insulin sensitivity (p=0.50). At any body mass index and age before 35 years, carriers had higher type 2 diabetes incidence. This variant did not associate with prevalence of increased albuminuria (OR 0.87, 95% CI 0.66 to 1.16), severe albuminuria (OR 0.96, 95% CI 0.55 to 1.68), or reduced eGFR (OR 0.44, 95% CI 0.18 to 1.06). By contrast, the variant significantly associated with higher retinopathy prevalence (OR 1.74, 95% CI 1.19 to 2.53) and this association was only partially mediated (<11%) by glycemia, duration of diabetes, risk factors of retinopathy, or insulin use. Retinopathy prevalence in carriers was higher regardless of diabetes presence. CONCLUSIONS: The ABCC8 R1420H variant is associated with increased risks of diabetes and of retinopathy, which may be partially explained by higher glycemia levels and worse beta-cell function.

Association of protein function-altering variants with cardiometabolic traits: the strong heart study.

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 ß-cell proliferation and survival, and TRPM3 protein mediates calcium signaling in pancreatic ß-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.

Functional characterization of a novel p.Ser76Thr variant in IGFBP4 that associates with body mass index in American Indians.

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/m2 for Thr-allele homozygotes combined with heterozygotes vs. 36.2 kg/m2 for Ser-allele homozygotes, ß = 6.7% per Thr-allele, p = 8.0 × 10-5, adjusted for age, sex, birth-year and the first five genetic principal components) and the maximum age- and sex-adjusted BMI z-score measured during childhood/adolescence (z-score 0.70 SD for Thr-allele heterozygotes vs. 0.32 SD for Ser-allele homozygotes, ß = 0.37 SD per Thr-allele, p = 8.8 × 10-6). In vitro functional studies showed that IGFBP4 with the Thr-allele (BMI-increasing) had a 55% decrease (p = 0.0007) in FOXO-induced transcriptional activity, reflecting increased activation of the PI3K/AKT pathway mediated through increased IGF signaling. Over-expression and knock-down of IGFBP4 in OP9 cells during differentiation showed that IGFBP4 upregulates adipogenesis through PPARγ, CEBPα, AGPAT2 and SREBP1 expression. We propose that this American Indian specific variant in IGFBP4 affects obesity via an increase of IGF signaling.

Generation of Isogenic hiPSCs with Targeted Edits at Multiple Intronic SNPs to Study the Effects of the Type 2 Diabetes Associated KCNQ1 Locus in American Indians.

The top genetic association signal for type 2 diabetes (T2D) in Southwestern American Indians maps to intron 15 of KCNQ1, an imprinted gene. We aim to understand the biology whereby variation at this locus affects T2D specifically in this genomic background. To do so, we obtained human induced pluripotent stem cells (hiPSC) derived from American Indians. Using these iPSCs, we show that imprinting of KCNQ1 and CDKN1C during pancreatic islet-like cell generation from iPSCs is consistent with known imprinting patterns in fetal pancreas and adult islets and therefore is an ideal model system to study this locus. In this report, we detail the use of allele-specific guide RNAs and CRISPR to generate isogenic hiPSCs that differ only at multiple T2D associated intronic SNPs at this locus which can be used to elucidate their functional effects. Characterization of these isogenic hiPSCs identified a few aberrant cell lines; namely cell lines with large hemizygous deletions in the putative functional region of KCNQ1 and cell lines hypomethylated at the KCNQ1OT1 promoter. Comparison of an isogenic cell line with a hemizygous deletion to the parental cell line identified CDKN1C and H19 as differentially expressed during the endocrine progenitor stage of pancreatic-islet development.

Functional variants in cytochrome b5 type A (CYB5A) are enriched in Southwest American Indian individuals and associate with obesity.

OBJECTIVE: This study aimed to identify genetic variants enriched in Southwest American Indian (SWAI) individuals that associate with BMI. METHODS: 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). RESULTS: A 5' untranslated region variant in cytochrome b5 type A (CYB5A), rs548402150, met the enrichment criteria and associated with increased BMI (ß = 2%, p = 0.004). Functionally, rs548402150 decreased luciferase expression by 30% (p = 0.003) and correlated with decreased skeletal muscle CYB5A expression (ß = -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 (ß = 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. CONCLUSIONS: Further studies on the effects of CYB5A on 24-h EE and BMI may provide insights into obesity-related physiology.

A missense variant Arg611Cys in LIPE which encodes hormone sensitive lipase decreases lipolysis and increases risk of type 2 diabetes in American Indians.

AIMS: Hormone sensitive lipase (HSL), encoded by the LIPE gene, is involved in lipolysis. Based on prior animal and human studies, LIPE was analysed as a candidate gene for the development of type 2 diabetes (T2D) in a community-based sample of American Indians. MATERIALS AND METHODS: Whole-exome sequence data from 6782 participants with longitudinal clinical measures were used to identify variation in LIPE. RESULTS: Amongst the 16 missense variants identified, an Arg611Cys variant (rs34052647; Cys-allele frequency = 0.087) significantly associated with T2D (OR [95% CI] = 1.38 [1.17-1.64], p = 0.0002, adjusted for age, sex, birth year, and the first five genetic principal components) and an earlier onset age of T2D (HR = 1.22 [1.09-1.36], p = 0.0005). This variant was further analysed for quantitative traits related to T2D. Amongst non-diabetic American Indians, those with the T2D risk Cys-allele had increased insulin levels during an oral glucose tolerance test (0.07 SD per Cys-allele, p = 0.04) and a mixed meal test (0.08 log10 µU/ml per Cys-allele, p = 0.003), and had increased lipid oxidation rates post-absorptively and during insulin infusion (0.07 mg [kg estimated metabolic body size {EMBS}]-1  min-1 per Cys-allele for both, p = 0.01 and 0.009, respectively), compared to individuals with the non-risk Arg-allele. In vitro functional studies showed that cells expressing the Cys-allele had a 17.2% decrease in lipolysis under isoproterenol stimulation (p = 0.03) and a 21.3% decrease in lipase enzyme activity measured by using p-nitrophenyl butyrate as a substrate (p = 0.04) compared to the Arg-allele. CONCLUSION: The Arg611Cys variant causes a modest impairment in lipolysis, thereby affecting glucose homoeostasis and risk of T2D.

Next generation sequencing for HLA loci in full heritage Pima Indians of Arizona, Part II: HLA-A, -B, and -C with selected non-classical loci at 4-field resolution from whole genome sequences.

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.

Exome Sequencing of 21 Bardet-Biedl Syndrome (BBS) Genes to Identify Obesity Variants in 6,851 American Indians.

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 < 10 individuals) were analyzed for mean BMI of carriers. Functional assessment of variants' effect on signal transducer and activator of transcription 3 (STAT3) activity was performed in vitro. RESULTS: One common variant, rs59252892 (Thr549Ile) in BBS9, was associated with BMI (P = 0.0008, ß = 25% increase per risk allele). Among rare variants for which carriers had severe obesity (mean BMI > 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.

Whole genome sequence analyses of eGFR in 23,732 people representing multiple ancestries in the NHLBI trans-omics for precision medicine (TOPMed) consortium.

BACKGROUND: Genetic factors that influence kidney traits have been understudied for low frequency and ancestry-specific variants. METHODS: We combined whole genome sequencing (WGS) data from 23,732 participants from 10 NHLBI Trans-Omics for Precision Medicine (TOPMed) Program multi-ethnic studies to identify novel loci for estimated glomerular filtration rate (eGFR). Participants included European, African, East Asian, and Hispanic ancestries. We applied linear mixed models using a genetic relationship matrix estimated from the WGS data and adjusted for age, sex, study, and ethnicity. FINDINGS: When testing single variants, we identified three novel loci driven by low frequency variants more commonly observed in non-European ancestry (PRKAA2, rs180996919, minor allele frequency [MAF] 0.04%, P = 6.1 × 10-11; METTL8, rs116951054, MAF 0.09%, P = 4.5 × 10-9; and MATK, rs539182790, MAF 0.05%, P = 3.4 × 10-9). We also replicated two known loci for common variants (rs2461702, MAF=0.49, P = 1.2 × 10-9, nearest gene GATM, and rs71147340, MAF=0.34, P = 3.3 × 10-9, CDK12). Testing aggregated variants within a gene identified the MAF gene. A statistical approach based on local ancestry helped to identify replication samples for ancestry-specific variants. INTERPRETATION: This study highlights challenges in studying variants influencing kidney traits that are low frequency in populations and more common in non-European ancestry.

Assessment of the potential role of natural selection in type 2 diabetes and related traits across human continental ancestry groups: comparison of phenotypic with genotypic divergence.

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 (FST) was calculated across all markers as a measure of genetic divergence among ancestry groups. The phenotypic divergence index (PST) 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 PST = FST, while for traits under differential selection PST is expected to be significantly greater than FST. A bootstrap procedure was used to test the hypothesis PST = FST. 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/m2, 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). FST across all markers was 0.130, while PST for liability to diabetes, adjusted for age and sex, was 0.149 (p = 0.35 for difference with FST). PST 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 (PST-MAX = 0.22, p = 0.37, and PST-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. Graphical abstract.

Exome Sequencing Identifies A Nonsense Variant in DAO Associated With Reduced Energy Expenditure in American Indians.

BACKGROUND: Obesity and energy expenditure (EE) are heritable and genetic variants influencing EE may contribute to the development of obesity. We sought to identify genetic variants that affect EE in American Indians, an ethnic group with high prevalence of obesity. METHODS: Whole-exome sequencing was performed in 373 healthy Pima Indians informative for 24-hour EE during energy balance. Genetic association analyses of all high-quality exonic variants (≥5 carriers) was performed, and those predicted to be damaging were prioritized. RESULTS: Rs752074397 introduces a premature stop codon (Cys264Ter) in DAO and demonstrated the strongest association for 24-hour EE, where the Ter allele associated with substantially lower 24-hour EE (mean lower by 268 kcal/d) and sleeping EE (by 135 kcal/d). The Ter allele has a frequency = 0.5% in Pima Indians, whereas is extremely rare in most other ethnic groups (frequency < 0.01%). In vitro functional analysis showed reduced protein levels for the truncated form of DAO consistent with increased protein degradation. DAO encodes D-amino acid oxidase, which is involved in dopamine synthesis which might explain its role in modulating EE. CONCLUSION: Our results indicate that a nonsense mutation in DAO may influence EE in American Indians. Identification of variants that influence energy metabolism may lead to new pathways to treat human obesity. CLINICAL TRIAL REGISTRATION NUMBER: NCT00340132.

Characterization of Exome Variants and Their Metabolic Impact in 6,716 American Indians from the Southwest US.

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.

Assessing established BMI variants for a role in nighttime eating behavior in robustly phenotyped Southwestern American Indians.

BACKGROUND/OBJECTIVES: Nighttime eating (NE) behavior has a genetic component and predicts weight gain. We hypothesized that some genetic variants, which affect NE would also show an effect on body mass index (BMI). We aimed to determine which known BMI variants associate with NE in Southwestern American Indians (SWAIs), who are at elevated risk for obesity. METHODS: Known BMI variants from the GIANT-UK Biobank meta-analysis (N = 700,000) were analysed in SWAIs characterized for NE during an inpatient 3-day protocol. Variants were analysed for association with NE using whole-genome sequence data from 50 SWAIs (23 cases and 27 controls) and selected variants were genotyped in an additional 32 SWAIs (13 NE cases and 19 controls). Variants associated with NE in a meta-analysis of the two SWAI samples were further analysed for association with nightly caloric intake and functionality in hypothalamus, pituitary, and adrenal tissues. RESULTS: Variants were identified where the allele that associated with increased BMI in the GIANT-UK Biobank meta-analysis (P ≤ 1 × 10-8) also had a P < 0.01 for increased NE in the SWAI meta-analysis. These variants were captured by six tagSNPs. Comparison of the nightly calorie intake by genotype and eQTL data from relevant tissues highlighted rs3753612 upstream of HCRTR1. CONCLUSIONS: Our strategy led to the HCRTR1 locus, which has previously been linked to sleep regulation and feeding. Although this is an intriguing candidate gene for NE, further studies in larger samples and different populations are required to validate the role of HCRTR1 in NE.

Weight tracking in childhood and adolescence and type 2 diabetes risk.

AIMS/HYPOTHESIS: The aim of this work was 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 were selected from a 43 year longitudinal study of American Indians to represent three growth periods: pre-adolescence (birth to ~8 years); early adolescence (~8 to ~13 years); and late adolescence (~13 to ~18 years). Age-, sex- and height-standardised weight z score mean and weight z score velocity (change/year) were computed for each period. Participants were followed for up to 25 years from the end of each growth period until they developed diabetes. Associations of weight z score mean or weight z score velocity with diabetes incidence were determined with sex-, birth date- and maternal diabetes-adjusted Poisson regression models. RESULTS: Among 2100 participants representing the pre-adolescence growth period, 1558 representing the early adolescence period and 1418 representing the late adolescence period, there were 290, 315 and 380 incident diabetes cases, respectively. During the first 10 years of follow-up, the diabetes incidence rate ratio (95% CI) was 1.72 (1.40, 2.11)/SD of log10 weight z score mean in pre-adolescence, 2.09 (1.68, 2.60)/SD of log10 weight z score mean in early adolescence and 1.85 (1.58, 2.17)/SD of log10 weight z score mean in late adolescence. The diabetes incidence rate ratio (95% CI) was 1.79 (1.49, 2.17)/SD of log10 weight z score velocity in pre-adolescence, 1.13 (0.91, 1.41)/SD of log10 weight z score velocity in early adolescence and 1.29 (1.09, 1.51)/SD of log10 weight z score velocity in late adolescence. There were strong correlations in the weight z score means and weak correlations in the weight z score velocities between successive periods. CONCLUSIONS/INTERPRETATION: Higher weight and accelerated weight gain in all growth periods associate with increased type 2 diabetes risk. Importantly, higher weight and greater weight velocity during pre-adolescence jointly associate with the highest type 2 diabetes risk. Graphical abstract.