Genome-wide significant risk loci for mood disorders in the Old Order Amish founder population.

Genome-wide association studies (GWAS) of mood disorders in large case-control cohorts have identified numerous risk loci, yet pathophysiological mechanisms remain elusive, primarily due to the very small effects of common variants. We sought to discover risk variants with larger effects by conducting a genome-wide association study of mood disorders in a founder population, the Old Order Amish (OOA, n = 1,672). Our analysis revealed four genome-wide significant risk loci, all of which were associated with >2-fold relative risk. Quantitative behavioral and neurocognitive assessments (n = 314) revealed effects of risk variants on sub-clinical depressive symptoms and information processing speed. Network analysis suggested that OOA-specific risk loci harbor novel risk-associated genes that interact with known neuropsychiatry-associated genes via gene interaction networks. Annotation of the variants at these risk loci revealed population-enriched, non-synonymous variants in two genes encoding neurodevelopmental transcription factors, CUX1 and CNOT1. Our findings provide insight into the genetic architecture of mood disorders and a substrate for mechanistic and clinical studies.

Clinical case study meets population cohort: identification of a BRCA1 pathogenic founder variant in Orcadians.

We multiply ascertained the BRCA1 pathogenic missense variant c.5207T > C; p.Val1736Ala (V1736A) in clinical investigation of breast and ovarian cancer families from Orkney in the Northern Isles of Scotland, UK. We sought to investigate the frequency and clinical relevance of this variant in those of Orcadian ancestry as an exemplar of the value of population cohorts in clinical care, especially in isolated populations. Oral history and birth, marriage and death registrations indicated genealogical linkage of the clinical cases to ancestors from the Isle of Westray, Orkney. Further clinical cases were identified through targeted testing for V1736A in women of Orcadian ancestry attending National Health Service (NHS) genetic clinics for breast and ovarian cancer family risk assessments. The variant segregates with female breast and ovarian cancer in clinically ascertained cases. Separately, exome sequence data from 2088 volunteer participants with three or more Orcadian grandparents, in the ORCADES research cohort, was interrogated to estimate the population prevalence of V1736A in Orcadians. The effects of the variant were assessed using Electronic Health Record (EHR) linkage. Twenty out of 2088 ORCADES research volunteers (~1%) carry V1736A, with a common haplotype around the variant. This allele frequency is ~480-fold higher than in UK Biobank participants. Cost-effectiveness of population screening for BRCA1 founder pathogenic variants has been demonstrated at a carrier frequency below the ~1% observed here. Thus we suggest that Orcadian women should be offered testing for the BRCA1 V1736A founder pathogenic variant, starting with those with known Westray ancestry.

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.

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.

Biallelic truncating variants in the muscular A-type lamin-interacting protein (MLIP) gene cause myopathy with hyperCKemia.

BACKGROUND AND PURPOSE: Muscular A-type lamin-interacting protein (MLIP) is most abundantly expressed in cardiac and skeletal muscle. In vitro and animal studies have shown its regulatory role in myoblast differentiation and in organization of myonuclear positioning in skeletal muscle, as well as in cardiomyocyte adaptation and cardiomyopathy. We report the association of biallelic truncating variation in the MLIP gene with human disease in five individuals from two unrelated pedigrees. METHODS: Clinical evaluation and exome sequencing were performed in two unrelated families with elevated creatine kinase level. RESULTS: Family 1. A 6-year-old girl born to consanguineous parents of Arab-Muslim origin presented with myalgia, early fatigue after mild-to-moderate physical exertion, and elevated creatine kinase levels up to 16,000 U/L. Exome sequencing revealed a novel homozygous nonsense variant, c.2530C>T; p.Arg844Ter, in the MLIP gene. Family 2. Three individuals from two distantly related families of Old Order Amish ancestry presented with elevated creatine kinase levels, one of whom also presented with abnormal electrocardiography results. On exome sequencing, all showed homozygosity for a novel nonsense MLIP variant c.1825A>T; p.Lys609Ter. Another individual from this pedigree, who had sinus arrhythmia and for whom creatine kinase level was not available, was also homozygous for this variant. CONCLUSIONS: Our findings suggest that biallelic truncating variants in MLIP result in myopathy characterized by hyperCKemia. Moreover, these cases of MLIP-related disease may indicate that at least in some instances this condition is associated with muscle decompensation and fatigability during low-to-moderate intensity muscle exertion as well as possible cardiac involvement.

Genetic and functional evidence links a missense variant in B4GALT1 to lower LDL and fibrinogen.

Increased blood levels of low-density lipoprotein cholesterol (LDL-C) and fibrinogen are independent risk factors for cardiovascular disease. We identified associations between an Amish-enriched missense variant (p.Asn352Ser) in a functional domain of beta-1,4-galactosyltransferase 1 (B4GALT1) and 13.9 milligrams per deciliter lower LDL-C (P = 4.1 × 10­19) and 29 milligrams per deciliter lower plasma fibrinogen (P = 1.3 × 10­5). B4GALT1 gene­based analysis in 544,955 subjects showed an association with decreased coronary artery disease (odds ratio = 0.64, P = 0.006). The mutant protein had 50% lower galactosyltransferase activity compared with the wild-type protein. N-linked glycan profiling of human serum found serine 352 allele to be associated with decreased galactosylation and sialylation of apolipoprotein B100, fibrinogen, immunoglobulin G, and transferrin. B4galt1 353Ser knock-in mice showed decreases in LDL-C and fibrinogen. Our findings suggest that targeted modulation of protein galactosylation may represent a therapeutic approach to decreasing cardiovascular disease.

The burden of pathogenic variants in clinically actionable genes in a founder population.

Founder populations may be enriched with certain genetic variants of high clinical impact compared to nonfounder populations due to bottleneck events and genetic drift. Using exome sequencing (ES), we quantified the load of pathogenic variants that may be clinically actionable in 6136 apparently healthy adults living in the Lancaster, PA Old Order Amish settlement. We focused on variants in 78 genes deemed clinically actionable by the American College of Medical Genetics and Genomics (ACMG) or Geisinger's MyCode Health Initiative. ES revealed 3191 total variants among these genes including 480 nonsynonymous variants. After quality control and filtering, we applied the ACMG/AMP guidelines for variant interpretation and classified seven variants, across seven genes, as either pathogenic or likely pathogenic. Through genetic drift, all seven variants, are highly enriched in the Amish compared to nonfounder populations. In total, 14.7% of Lancaster Amish individuals carry at least one of these variants, largely explained by the 13% who harbor a copy of a single variant in APOB. Other studies report combined frequencies of pathogenic/likely pathogenic (P/LP) variants in actionable genes between 2.0% and 6.2% in outbred populations. The Amish population harbors fewer actionable variants compared to similarly characterized nonfounder populations but have a higher frequency of each variant identified, offering opportunities for efficient and cost-effective targeted precision medicine.

Genome-wide association analysis of serum alanine and aspartate aminotransferase, and the modifying effects of BMI in 388k European individuals.

Serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) are biomarkers for liver health. Here we report the largest genome-wide association analysis to date of serum ALT and AST levels in over 388k people of European ancestry from UK biobank and DiscovEHR. Eleven million imputed markers with a minor allele frequency (MAF) ≥ 0.5% were analyzed. Overall, 300 ALT and 336 AST independent genome-wide significant associations were identified. Among them, 81 ALT and 61 AST associations are reported for the first time. Genome-wide interaction study identified 9 ALT and 12 AST independent associations significantly modified by body mass index (BMI), including several previously reported potential liver disease therapeutic targets, for example, PNPLA3, HSD17B13, and MARC1. While further work is necessary to understand the effect of ALT and AST-associated variants on liver disease, the weighted burden of significant BMI-modified signals is significantly associated with liver disease outcomes. In summary, this study identifies genetic associations which offer an important step forward in understanding the genetic architecture of serum ALT and AST levels. Significant interactions between BMI and genetic loci not only highlight the important role of adiposity in liver damage but also shed light on the genetic etiology of liver disease in obese individuals.

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.

Mutation spectrum of NOD2 reveals recessive inheritance as a main driver of Early Onset Crohn's Disease.

Inflammatory bowel disease (IBD), clinically defined as Crohn's disease (CD), ulcerative colitis (UC), or IBD-unclassified, results in chronic inflammation of the gastrointestinal tract in genetically susceptible hosts. Pediatric onset IBD represents ≥ 25% of all IBD diagnoses and often presents with intestinal stricturing, perianal disease, and failed response to conventional treatments. NOD2 was the first and is the most replicated locus associated with adult IBD, to date. However, its role in pediatric onset IBD is not well understood. We performed whole-exome sequencing on a cohort of 1,183 patients with pediatric onset IBD (ages 0-18.5 years). We identified 92 probands with biallelic rare and low frequency NOD2 variants accounting for approximately 8% of our cohort, suggesting a Mendelian inheritance pattern of disease. Additionally, we investigated the contribution of recessive inheritance of NOD2 alleles in adult IBD patients from a large clinical population cohort. We found that recessive inheritance of NOD2 variants explains ~ 7% of cases in this adult IBD cohort, including ~ 10% of CD cases, confirming the observations from our pediatric IBD cohort. Exploration of EHR data showed that several of these adult IBD patients obtained their initial IBD diagnosis before 18 years of age, consistent with early onset disease. While it has been previously reported that carriers of more than one NOD2 risk alleles have increased susceptibility to Crohn's Disease (CD), our data formally demonstrate that recessive inheritance of NOD2 alleles is a mechanistic driver of early onset IBD, specifically CD, likely due to loss of NOD2 protein function. Collectively, our findings show that recessive inheritance of rare and low frequency deleterious NOD2 variants account for 7-10% of CD cases and implicate NOD2 as a Mendelian disease gene for early onset Crohn's Disease.

Heterozygosity for a Pathogenic Variant in SLC12A3 That Causes Autosomal Recessive Gitelman Syndrome Is Associated with Lower Serum Potassium.

BACKGROUND: Potassium levels regulate multiple physiologic processes. The heritability of serum potassium level is moderate, with published estimates varying from 17% to 60%, suggesting genetic influences. However, the genetic determinants of potassium levels are not generally known. METHODS: A whole-exome sequencing association study of serum potassium levels in 5812 subjects of the Old Order Amish was performed. A dietary salt intervention in 533 Amish subjects estimated interaction between p.R642G and sodium intake. RESULTS: A cluster of variants, spanning approximately 537 kb on chromosome 16q13, was significantly associated with serum potassium levels. Among the associated variants, a known pathogenic variant of autosomal recessive Gitelman syndrome (p.R642G SLC12A3) was most likely causal; there were no homozygotes in our sample. Heterozygosity for p.R642G was also associated with lower chloride levels, but not with sodium levels. Notably, p.R642G showed a novel association with lower serum BUN levels. Heterozygotes for p.R642G had a two-fold higher rate of self-reported bone fractures and had higher resting heart rates on a low-salt diet compared with noncarriers. CONCLUSIONS: This study provides evidence that heterozygosity for a pathogenic variant in SLC12A3 causing Gitelman syndrome, a canonically recessive disorder, contributes to serum potassium concentration. The findings provide insights into SLC12A3 biology and the effects of heterozygosity on electrolyte homeostasis and related subclinical phenotypes that may have implications for personalized medicine and nutrition.

Leveraging phenotypic variability to identify genetic interactions in human phenotypes.

Although thousands of loci have been associated with human phenotypes, the role of gene-environment (GxE) interactions in determining individual risk of human diseases remains unclear. This is partly because of the severe erosion of statistical power resulting from the massive number of statistical tests required to detect such interactions. Here, we focus on improving the power of GxE tests by developing a statistical framework for assessing quantitative trait loci (QTLs) associated with the trait means and/or trait variances. When applying this framework to body mass index (BMI), we find that GxE discovery and replication rates are significantly higher when prioritizing genetic variants associated with the variance of the phenotype (vQTLs) compared to when assessing all genetic variants. Moreover, we find that vQTLs are enriched for associations with other non-BMI phenotypes having strong environmental influences, such as diabetes or ulcerative colitis. We show that GxE effects first identified in quantitative traits such as BMI can be used for GxE discovery in disease phenotypes such as diabetes. A clear conclusion is that strong GxE interactions mediate the genetic contribution to body weight and diabetes risk.

Genome-wide survey of parent-of-origin-specific associations across clinical traits derived from electronic health records.

Parent-of-origin (PoO) effects refer to the differential phenotypic impacts of genetic variants dependent on their parental inheritance due to imprinting. While PoO effects can influence complex traits, they may be poorly captured by models that do not differentiate the parental origin of the variant. The aim of this study was to conduct a genome-wide screen for PoO effects on a broad range of clinical traits derived from electronic health records (EHR) in the DiscovEHR study enriched with familial relationships. Using pairwise kinship estimates from genetic data and demographic data, we identified 22,051 offspring among 134,049 individuals in the DiscovEHR study. PoO of ~9 million variants was assigned in the offspring by comparing offspring and parental genotypes and haplotypes. We then performed genome-wide PoO association analyses across 154 quantitative and 611 binary traits extracted from EHR. Of the 732 significant PoO associations identified (p < 5 × 10-8), we attempted to replicate 274 PoO associations in the UK Biobank study with 5,015 offspring and replicated 9 PoO associations (p < 0.05). In summary, our study implements a bioinformatic and statistical approach to examine PoO effects genome-wide in a large population study enriched with familial relationships and systematically characterizes PoO effects on hundreds of clinical traits derived from EHR. Our results suggest that, while the statistical power to detect PoO effects remains modest yet, accurately modeling PoO effects has the potential to find new associations that may have been missed by the standard additive model, further enhancing the mechanistic understanding of genetic influence on complex traits.

KCNQ1 and Long QT Syndrome in 1/45 Amish: The Road From Identification to Implementation of Culturally Appropriate Precision Medicine.

BACKGROUND: In population-based research exome sequencing, the path from variant discovery to return of results is not well established. Variants discovered by research exome sequencing have the potential to improve population health. METHODS: Population-based exome sequencing and agnostic ExWAS were performed 5521 Amish individuals. Additional phenotyping and in vitro studies enabled reclassification of a KCNQ1 variant from variant of unknown significance to pathogenic. Results were returned to participants in a community setting. RESULTS: A missense variant was identified in KCNQ1 (c.671C>T, p.T224M), a gene associated with long QT syndrome type 1, which can cause syncope and sudden cardiac death. The p.T224M variant, present in 1/45 Amish individuals is rare in the general population (1/248 566 in gnomAD) and was highly associated with QTc on electro-cardiogram (P=5.53E-24, ß=20.2 ms/allele). Because of the potential importance of this variant to the health of the population, additional phenotyping was performed in 88 p.T224M carriers and 54 noncarriers. There was stronger clinical evidence of long QT syndrome in carriers (38.6% versus 5.5%, P=0.0006), greater history of syncope (32% versus 17%, P=0.020), and higher rate of sudden cardiac death in first degree relatives

Exome sequencing and characterization of 49,960 individuals in the UK Biobank.

The UK Biobank is a prospective study of 502,543 individuals, combining extensive phenotypic and genotypic data with streamlined access for researchers around the world1. Here we describe the release of exome-sequence data for the first 49,960 study participants, revealing approximately 4 million coding variants (of which around 98.6% have a frequency of less than 1%). The data include 198,269 autosomal predicted loss-of-function (LOF) variants, a more than 14-fold increase compared to the imputed sequence. Nearly all genes (more than 97%) had at least one carrier with a LOF variant, and most genes (more than 69%) had at least ten carriers with a LOF variant. We illustrate the power of characterizing LOF variants in this population through association analyses across 1,730 phenotypes. In addition to replicating established associations, we found novel LOF variants with large effects on disease traits, including PIEZO1 on varicose veins, COL6A1 on corneal resistance, MEPE on bone density, and IQGAP2 and GMPR on blood cell traits. We further demonstrate the value of exome sequencing by surveying the prevalence of pathogenic variants of clinical importance, and show that 2% of this population has a medically actionable variant. Furthermore, we characterize the penetrance of cancer in carriers of pathogenic BRCA1 and BRCA2 variants. Exome sequences from the first 49,960 participants highlight the promise of genome sequencing in large population-based studies and are now accessible to the scientific community.

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.

Angiopoietin-like protein 3 governs LDL-cholesterol levels through endothelial lipase-dependent VLDL clearance.

Angiopoietin-like protein (ANGPTL)3 regulates plasma lipids by inhibiting LPL and endothelial lipase (EL). ANGPTL3 inactivation lowers LDL-C independently of the classical LDLR-mediated pathway and represents a promising therapeutic approach for individuals with homozygous familial hypercholesterolemia due to LDLR mutations. Yet, how ANGPTL3 regulates LDL-C levels is unknown. Here, we demonstrate in hyperlipidemic humans and mice that ANGPTL3 controls VLDL catabolism upstream of LDL. Using kinetic, lipidomic, and biophysical studies, we show that ANGPTL3 inhibition reduces VLDL-lipid content and size, generating remnant particles that are efficiently removed from the circulation. This suggests that ANGPTL3 inhibition lowers LDL-C by limiting LDL particle production. Mechanistically, we discovered that EL is a key mediator of ANGPTL3's novel pathway. Our experiments revealed that, although dispensable in the presence of LDLR, EL-mediated processing of VLDL becomes critical for LDLR-independent particle clearance. In the absence of EL and LDLR, ANGPTL3 inhibition perturbed VLDL catabolism, promoted accumulation of atypical remnants, and failed to reduce LDL-C. Taken together, we uncover ANGPTL3 at the helm of a novel EL-dependent pathway that lowers LDL-C in the absence of LDLR.

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.

U-PASS: unified power analysis and forensics for qualitative traits in genetic association studies.

SUMMARY: Despite the availability of existing calculators for statistical power analysis in genetic association studies, there has not been a model-invariant and test-independent tool that allows for both planning of prospective studies and systematic review of reported findings. In this work, we develop a web-based application U-PASS (Unified Power analysis of ASsociation Studies), implementing a unified framework for the analysis of common association tests for binary qualitative traits. The application quantifies the shared asymptotic power limits of the common association tests, and visualizes the fundamental statistical trade-off between risk allele frequency and odds ratio. The application also addresses the applicability of asymptotics-based power calculations in finite samples, and provides guidelines for single-SNP-based association tests. In addition to designing prospective studies, U-PASS enables researchers to retrospectively assess the statistical validity of previously reported associations. AVAILABILITY AND IMPLEMENTATION: U-PASS is an open-source R Shiny application. A live instance is hosted at https://power.stat.lsa.umich.edu. Source is available on https://github.com/Pill-GZ/U-PASS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.