A practical approach to curate clonal hematopoiesis of indeterminate potential in human genetic data sets.

Clonal hematopoiesis of indeterminate potential (CHIP) is a common form of age-related somatic mosaicism that is associated with significant morbidity and mortality. CHIP mutations can be identified in peripheral blood samples that are sequenced using approaches that cover the whole genome, the whole exome, or targeted genetic regions; however, differentiating true CHIP mutations from sequencing artifacts and germ line variants is a considerable bioinformatic challenge. We present a stepwise method that combines filtering based on sequencing metrics, variant annotation, and population-based associations to increase the accuracy of CHIP calls. We apply this approach to ascertain CHIP in ∼550 000 individuals in the UK Biobank complete whole exome cohort and the All of Us Research Program initial whole genome release cohort. CHIP ascertainment on this scale unmasks recurrent artifactual variants and highlights the importance of specialized filtering approaches for several genes, including TET2 and ASXL1. We show how small changes in filtering parameters can considerably increase CHIP misclassification and reduce the effect size of epidemiological associations. Our high-fidelity call set refines previous population-based associations of CHIP with incident outcomes. For example, the annualized incidence of myeloid malignancy in individuals with small CHIP clones is 0.03% per year, which increases to 0.5% per year among individuals with very large CHIP clones. We also find a significantly lower prevalence of CHIP in individuals of self-reported Latino or Hispanic ethnicity in All of Us, highlighting the importance of including diverse populations. The standardization of CHIP calling will increase the fidelity of CHIP epidemiological work and is required for clinical CHIP diagnostic assays.

Kidney Volume and Risk of Incident Kidney Outcomes.

BACKGROUND: Low total kidney volume (TKV) is a risk factor for chronic kidney disease (CKD). However, evaluations of nonlinear relationships, incident events, causal inference, and prognostic utility beyond traditional biomarkers are lacking. METHODS: TKV, height-adjusted TKV, and body surface area-adjusted TKV (BSA-TKV) of 34,595 White British ancestry participants were derived from the UK Biobank. Association with incident CKD, acute kidney injury (AKI), and cardiovascular events were assessed with Cox proportional hazard models. Prognostic thresholds for CKD risk stratification were identified using a modified Mazumdar method with bootstrap resampling. Two-sample Mendelian randomization was performed to assess the bidirectional association of genetically predicted TKV with kidney and cardiovascular traits. RESULTS: Adjusted for eGFR and albuminuria, a lower TKV of 10 mL was associated with a 6% higher risk of incident CKD (hazard ratio [HR] 1.06, 95% confidence interval [CI] 1.03 to 1.08, P = 5.8 x 10-6) in contrast to no association with incident AKI (HR 1.00, 95% CI 0.98 to 1.02, P = 0.66). Comparison of nested models demonstrated improved accuracy over the CKD Prognosis Consortium Incident CKD Risk Score with the addition of BSA-TKV or prognostic thresholds at 119 (10th percentile) and 145 mL/m2 (50th percentile). In Mendelian randomization, a lower genetically predicted TKV by 10 mL was associated with 10% higher CKD risk (odds ratio [OR] 1.10, 95% CI 1.06 to 1.14, P = 1.3 x 10-7). Reciprocally, an elevated risk of genetically predicted CKD by 2-fold was associated with a lower TKV by 7.88 mL (95% CI -9.81 to -5.95, P = 1.2 x 10-15). There were no significant observational or Mendelian randomization associations of TKV with cardiovascular complications. CONCLUSIONS: Kidney volume was associated with incident CKD independent of traditional risk factors including baseline eGFR and albuminuria. Mendelian randomization demonstrated a bidirectional relationship between kidney volume and CKD.

A novel multi-ancestry proteome-wide Mendelian randomization study implicates extracellular proteins, tubular cells, and fibroblasts in estimated glomerular filtration rate regulation.

Estimated glomerular filtration rate (eGFR) impacts the concentration of plasma biomarkers confounding biomarker association studies of eGFR with reverse causation. To identify biomarkers causally associated with eGFR, we performed a proteome-wide Mendelian randomization study. Genetic variants nearby biomarker coding genes were tested for association with plasma concentration of 1,161 biomarkers in a multi-ancestry sample of 12,066 participants from the Prospective Urban and Rural Epidemiological (PURE) study. Using two-sample Mendelian randomization, individual variants' effects on biomarker concentration were correlated with their effects on eGFR and kidney traits from published genome-wide association studies (GWAS). Genetically altered concentrations of 22 biomarkers were associated with eGFR above a Bonferroni-corrected significance threshold. Five biomarkers were previously identified by GWAS (UMOD, FGF5, LGALS7, NINJ1, COL18A1). Nine biomarkers were within 1 Mb of the lead GWAS variant but the gene for the biomarker was unidentified as the candidate for the GWAS signal (INHBC, TNFRSF11A, TCN2, PXN1, PRTN3, PSMD9, TFPI, ITGB6, CA3). Single-cell transcriptomic data indicated the 22 biomarkers are expressed in kidney tubules, collecting duct, fibroblasts, and immune cells. Pathway analysis showed significant enrichment of identified biomarkers in the extracellular kidney parenchyma. Thus, using genetic regulators of biomarker concentration via proteome-wide Mendelian randomization, we identified 22 biomarkers that appear to causally impact eGFR in either a beneficial or adverse manner. The current study provides rationale for novel therapeutic targets for eGFR and emphasized a role for extracellular proteins produced by tubular cells and fibroblasts for impacting eGFR.

Clonal Hematopoiesis of Indeterminate Potential and Kidney Function Decline in the General Population.

RATIONALE & OBJECTIVE: Clonal hematopoiesis of indeterminate potential (CHIP), defined by the age-related ontogenesis of expanded leukemogenic variants indicative of a genetically distinct clonal leukocyte population, is associated with risk of hematologic malignancy and cardiovascular disease. In experimental models, recapitulation of CHIP promotes kidney interstitial fibrosis with direct tissue infiltration of donor macrophages. We tested the hypothesis that CHIP is associated with kidney function decline in the general population. STUDY DESIGN: Cohort study. SETTING & PARTICIPANTS: 12,004 individuals from 3 community-based cohorts in the TOPMed Consortium. EXPOSURE: CHIP status from whole-genome sequences obtained from DNA extracted from peripheral blood. OUTCOME: Risk of 30% decline in estimated glomerular filtration rate (eGFR) and percent eGFR decline per year during the follow-up period. ANALYTICAL APPROACH: Cox proportional hazards models for 30% eGFR decline end point and generalized estimating equations for annualized relative change in eGFR with meta-analysis. Study-specific estimates were combined using fixed-effect meta-analysis. RESULTS: The median baseline eGFR was 84mL/min/1.73m2. The prevalence of CHIP was 6.6%, 9.0%, and 12.2% in persons aged 50-60, 60-70, and>70 years, respectively. Over a median follow-up period of 8 years, for the 30% eGFR outcome 205 events occurred among 1,002 CHIP carriers (2.1 events per 100 person-years) and 2,041 events in persons without CHIP (1.7 events per 100 person-years). In meta-analysis, CHIP was associated with greater risk of a 30% eGFR decline (17% [95% CI, 1%-36%] higher; P=0.04). Differences were not observed between those with baseline eGFR above or below 60mL/min/1.73m2, of age above or below 60 years, or with or without diabetes. LIMITATIONS: Small number of participants with moderate-to-advanced kidney disease and restricted set of CHIP driver variants. CONCLUSIONS: We report an association between CHIP and eGFR decline in 3 general population cohorts without known kidney disease. Further studies are needed to investigate this novel condition and its potential impact among individuals with overt kidney disease.

Association of Clonal Hematopoiesis of Indeterminate Potential with Worse Kidney Function and Anemia in Two Cohorts of Patients with Advanced Chronic Kidney Disease.

BACKGROUND: Clonal hematopoiesis of indeterminate potential (CHIP) is an inflammatory premalignant disorder resulting from acquired genetic mutations in hematopoietic stem cells. This condition is common in aging populations and associated with cardiovascular morbidity and overall mortality, but its role in CKD is unknown. METHODS: We performed targeted sequencing to detect CHIP mutations in two independent cohorts of 87 and 85 adults with an eGFR<60 ml/min per 1.73m2. We also assessed kidney function, hematologic, and mineral bone disease parameters cross-sectionally at baseline, and collected creatinine measurements over the following 5-year period. RESULTS: At baseline, CHIP was detected in 18 of 87 (21%) and 25 of 85 (29%) cohort participants. Participants with CHIP were at higher risk of kidney failure, as predicted by the Kidney Failure Risk Equation (KFRE), compared with those without CHIP. Individuals with CHIP manifested a 2.2-fold increased risk of a 50% decline in eGFR or ESKD over 5 years of follow-up (hazard ratio 2.2; 95% confidence interval, 1.2 to 3.8) in a Cox proportional hazard model adjusted for age, sex, and baseline eGFR. The addition of CHIP to 2-year and 5-year calibrated KFRE risk models improved ESKD predictions. Those with CHIP also had lower hemoglobin, higher ferritin, and higher red blood cell mean corpuscular volume versus those without CHIP. CONCLUSIONS: In this exploratory analysis of individuals with preexisting CKD, CHIP was associated with higher baseline KFRE scores, greater progression of CKD, and anemia. Further research is needed to define the nature of the relationship between CHIP and kidney disease progression.

Evolving role of genetic testing for the clinical management of autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is caused primarily by mutations of two genes, PKD1 and PKD2. In the presence of a positive family history of ADPKD, genetic testing is currently seldom indicated as the diagnosis is mostly based on imaging studies using well-established criteria. Moreover, PKD1 mutation screening is technically challenging due to its large size, complexity (i.e. presence of six pseudogenes with high levels of DNA sequence similarity) and extensive allelic heterogeneity. Despite these limitations, recent studies have delineated a strong genotype-phenotype correlation in ADPKD and begun to unravel the role of genetics underlying cases with atypical phenotypes. Furthermore, adaptation of next-generation sequencing (NGS) to clinical PKD genetic testing will provide a high-throughput, accurate and comprehensive screen of multiple cystic disease and modifier genes at a reduced cost. In this review, we discuss the evolving indications of genetic testing in ADPKD and how NGS-based screening promises to yield clinically important prognostic information for both typical as well as unusual genetic (e.g. allelic or genic interactions, somatic mosaicism, cystic kidney disease modifiers) cases to advance personalized medicine in the era of novel therapeutics for ADPKD.

Prevalence Estimates of Polycystic Kidney and Liver Disease by Population Sequencing.

BACKGROUND: Estimating the prevalence of autosomal dominant polycystic kidney disease (ADPKD) is challenging because of age-dependent penetrance and incomplete clinical ascertainment. Early studies estimated the lifetime risk of ADPKD to be about one per 1000 in the general population, whereas recent epidemiologic studies report a point prevalence of three to five cases per 10,000 in the general population. METHODS: To measure the frequency of high-confidence mutations presumed to be causative in ADPKD and autosomal dominant polycystic liver disease (ADPLD) and estimate lifetime ADPKD prevalence, we used two large, population sequencing databases, gnomAD (15,496 whole-genome sequences; 123,136 exome sequences) and BRAVO (62,784 whole-genome sequences). We used stringent criteria for defining rare variants in genes involved in ADPKD (PKD1, PKD2), ADPLD (PRKCSH, SEC63, GANAB, ALG8, SEC61B, LRP5), and potential cystic disease modifiers; evaluated variants for quality and annotation; compared variants with data from an ADPKD mutation database; and used bioinformatic tools to predict pathogenicity. RESULTS: Identification of high-confidence pathogenic mutations in whole-genome sequencing provided a lower boundary for lifetime ADPKD prevalence of 9.3 cases per 10,000 sequenced. Estimates from whole-genome and exome data were similar. Truncating mutations in ADPLD genes and genes of potential relevance as cyst modifiers were found in 20.2 cases and 103.9 cases per 10,000 sequenced, respectively. CONCLUSIONS: Population whole-genome sequencing suggests a higher than expected prevalence of ADPKD-associated mutations. Loss-of-function mutations in ADPLD genes are also more common than expected, suggesting the possibility of unrecognized cases and incomplete penetrance. Substantial rare variation exists in genes with potential for phenotype modification in ADPKD.

Exome sequencing of Saudi Arabian patients with ADPKD.

Purpose: Autosomal dominant polycystic kidney disease (ADPKD) is characterized by progressive development of kidney cysts and enlargement and dysfunction of the kidneys. The Consortium of Radiologic Imaging Studies of the Polycystic Kidney Disease (CRISP) cohort revealed that 89.1% had either a PKD1 or PKD2 mutation. Of the CRISP patients with a genetic cause detected, mutations in PKD1 accounted for 85%, while mutations in the PKD2 accounted for the remaining 15%. Here, we report exome sequencing of 16 Saudi patients diagnosed with ADPKD and 16 ethnically matched controls. Methods: Exome sequencing was performed using combinatorial probe-anchor synthesis and improved DNA Nanoballs technology on BGISEQ-500 sequencers (BGI, China) using the BGI Exome V4 (59 Mb) Kit. Identified variants were validated with Sanger sequencing. Results: With the exception of GC-rich exon 1, we obtained excellent coverage of PKD1 (mean read depth = 88) including both duplicated and non-duplicated regions. Of nine patients with typical ADPKD presentations (bilateral symmetrical kidney involvement, positive family history, concordant imaging, and kidney function), four had protein truncating PKD1 mutations, one had a PKD1 missense mutation, and one had a PKD2 mutation. These variants have not been previously observed in the Saudi population. In seven clinically diagnosed ADPKD cases but with atypical features, no PKD1 or PKD2 mutations were identified, but rare predicted pathogenic heterozygous variants were found in cystogenic candidate genes including PKHD1, PKD1L3, EGF, CFTR, and TSC2. Conclusions: Mutations in PKD1 and PKD2 are the most common cause of ADPKD in Saudi patients with typical ADPKD. Abbreviations: ADPKD: Autosomal dominant polycystic kidney disease; CFTR: Cystic fibrosis transmembrane conductance regulator; EGF: Epidermal growth factor; MCIC: Mayo Clinic Imaging Classification; PKD: Polycystic kidney disease; TSC2: Tuberous sclerosis complex 2.

HDL Cholesterol, LDL Cholesterol, and Triglycerides as Risk Factors for CKD: A Mendelian Randomization Study.

BACKGROUND: High-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglyceride concentrations are heritable risk factors for vascular disease, but their role in the progression of chronic kidney disease (CKD) is unclear. STUDY DESIGN: 2-sample Mendelian randomization analysis of data derived from the largest published lipid and CKD studies. SETTING & PARTICIPANTS: Effect of independent genetic variants significantly associated with lipid concentrations was obtained from the Global Lipids Genetics Consortium (n=188,577), and the effect of these same variants on estimated glomerular filtration rate (eGFR), CKD (defined as eGFR<60mL/min/1.73m2), and albuminuria was obtained from the CKD Genetics Consortium (n=133,814). FACTOR: Using conventional, multivariable, and Egger Mendelian randomization approaches, we assessed the causal association between genetically determined lipid concentrations and kidney traits. OUTCOME: eGFR, dichotomous eGFR<60mL/min/1.73m2, and albuminuria. RESULTS: In multivariable analysis, a 17-mg/dL higher HDL cholesterol concentration was associated with an 0.8% higher eGFR (95% CI, 0.4%-1.3%; P=0.004) and lower risk for eGFR<60mL/min/1.73m2 (OR, 0.85; 95% CI, 0.77-0.93; P<0.001), while Egger analysis showed no evidence of pleiotropy. There was no evidence for a causal relationship between LDL cholesterol concentration and any kidney disease measure. Genetically higher triglyceride concentrations appeared associated with higher eGFRs, but this finding was driven by a single pleiotropic variant in the glucokinase regulator gene (GCKR). After exclusion, genetically higher triglyceride concentration was not associated with any kidney trait. LIMITATIONS: Individual patient-level phenotype and genotype information were unavailable. CONCLUSIONS: 2-sample Mendelian randomization analysis of data from the largest lipid and CKD cohorts supports genetically higher HDL cholesterol concentration as causally associated with better kidney function. There was no association between genetically altered LDL cholesterol or triglyceride concentration and kidney function. Further analysis of CKD outcomes in HDL cholesterol intervention trials is warranted.

Assessing known chronic kidney disease associated genetic variants in Saudi Arabian populations.

BACKGROUND: Genome wide association studies of patients with European descent have identified common variants associated with risk of reduced estimated glomerular filtration rate (eGFR). A panel of eight variants were selected to evaluate their association and prevalence in a Saudi Arabian patient cohort with chronic kidney disease (CKD). METHODS: Eight genetic variants in four genes (SHROOM3, MYH9, SLC7A9, and CST3) were genotyped in 160 CKD patients and 189 ethnicity-matched healthy controls. Genetic variants were tested for association with the development of CKD (eGFR < 60 ml/min/1.73m2) and effects were compared with results obtained from 133,413 participants in the CKD genetics consortium. Multivariable regression was used to evaluate the role of these eight variants in improving prediction of CKD development. RESULTS: All eight variants were present in Saudi populations with minor allele frequency ranging from 16 to 46%. The risk variant in all four genes demonstrated the same direction of effect as observed in European populations. One variant, rs4821480, in MYH9 was significantly associated with increased risk of development of CKD (OR = 1.69, 95% CI 1.22-2.36, P = 0.002), but the additional variants were not statistically significant given our modest sample size. CONCLUSIONS: CKD risk variants identified in European populations are present in Saudis. We did not find evidence to suggest heterogeneity of effect size compared to previously published estimates in European populations. Multivariable logistic regression analysis showed a statistically significant improvement in predicting the CKD using models with either FGF23 and vitamin D or FGF23, vitamin D level, and MYH9 genotypes (AUC = 0.93, 95% CI 0.90-0.95, P <  0.0001).

Identifying gene-gene interactions that are highly associated with four quantitative lipid traits across multiple cohorts.

Genetic loci explain only 25-30 % of the heritability observed in plasma lipid traits. Epistasis, or gene-gene interactions may contribute to a portion of this missing heritability. Using the genetic data from five NHLBI cohorts of 24,837 individuals, we combined the use of the quantitative multifactor dimensionality reduction (QMDR) algorithm with two SNP-filtering methods to exhaustively search for SNP-SNP interactions that are associated with HDL cholesterol (HDL-C), LDL cholesterol (LDL-C), total cholesterol (TC) and triglycerides (TG). SNPs were filtered either on the strength of their independent effects (main effect filter) or the prior knowledge supporting a given interaction (Biofilter). After the main effect filter, QMDR identified 20 SNP-SNP models associated with HDL-C, 6 associated with LDL-C, 3 associated with TC, and 10 associated with TG (permutation P value <0.05). With the use of Biofilter, we identified 2 SNP-SNP models associated with HDL-C, 3 associated with LDL-C, 1 associated with TC and 8 associated with TG (permutation P value <0.05). In an independent dataset of 7502 individuals from the eMERGE network, we replicated 14 of the interactions identified after main effect filtering: 11 for HDL-C, 1 for LDL-C and 2 for TG. We also replicated 23 of the interactions found to be associated with TG after applying Biofilter. Prior knowledge supports the possible role of these interactions in the genetic etiology of lipid traits. This study also presents a computationally efficient pipeline for analyzing data from large genotyping arrays and detecting SNP-SNP interactions that are not primarily driven by strong main effects.

Causal effects of body mass index on cardiometabolic traits and events: a Mendelian randomization analysis.

Elevated body mass index (BMI) associates with cardiometabolic traits on observational analysis, yet the underlying causal relationships remain unclear. We conducted Mendelian randomization analyses by using a genetic score (GS) comprising 14 BMI-associated SNPs from a recent discovery analysis to investigate the causal role of BMI in cardiometabolic traits and events. We used eight population-based cohorts, including 34,538 European-descent individuals (4,407 type 2 diabetes (T2D), 6,073 coronary heart disease (CHD), and 3,813 stroke cases). A 1 kg/m(2) genetically elevated BMI increased fasting glucose (0.18 mmol/l; 95% confidence interval (CI) = 0.12-0.24), fasting insulin (8.5%; 95% CI = 5.9-11.1), interleukin-6 (7.0%; 95% CI = 4.0-10.1), and systolic blood pressure (0.70 mmHg; 95% CI = 0.24-1.16) and reduced high-density lipoprotein cholesterol (-0.02 mmol/l; 95% CI = -0.03 to -0.01) and low-density lipoprotein cholesterol (LDL-C; -0.04 mmol/l; 95% CI = -0.07 to -0.01). Observational and causal estimates were directionally concordant, except for LDL-C. A 1 kg/m(2) genetically elevated BMI increased the odds of T2D (odds ratio [OR] = 1.27; 95% CI = 1.18-1.36) but did not alter risk of CHD (OR 1.01; 95% CI = 0.94-1.08) or stroke (OR = 1.03; 95% CI = 0.95-1.12). A meta-analysis incorporating published studies reporting 27,465 CHD events in 219,423 individuals yielded a pooled OR of 1.04 (95% CI = 0.97-1.12) per 1 kg/m(2) increase in BMI. In conclusion, we identified causal effects of BMI on several cardiometabolic traits; however, whether BMI causally impacts CHD risk requires further evidence.

Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci.

Blood pressure (BP) is a heritable risk factor for cardiovascular disease. To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP), and pulse pressure (PP), we genotyped ~50,000 SNPs in up to 87,736 individuals of European ancestry and combined these in a meta-analysis. We replicated findings in an independent set of 68,368 individuals of European ancestry. Our analyses identified 11 previously undescribed associations in independent loci containing 31 genes including PDE1A, HLA-DQB1, CDK6, PRKAG2, VCL, H19, NUCB2, RELA, HOXC@ complex, FBN1, and NFAT5 at the Bonferroni-corrected array-wide significance threshold (p < 6 × 10(-7)) and confirmed 27 previously reported associations. Bioinformatic analysis of the 11 loci provided support for a putative role in hypertension of several genes, such as CDK6 and NUCB2. Analysis of potential pharmacological targets in databases of small molecules showed that ten of the genes are predicted to be a target for small molecules. In summary, we identified previously unknown loci associated with BP. Our findings extend our understanding of genes involved in BP regulation, which may provide new targets for therapeutic intervention or drug response stratification.

Clinical evaluation of a hemochromatosis next-generation sequencing gene panel.

BACKGROUND: Next-generation sequencing of an iron metabolism gene panel could identify pathogenic mutations, improving on standard hemochromatosis genetic testing and providing a molecular diagnosis in patients with suspected iron overload. METHODS: A next-generation sequencing panel of 15 genes with known roles in iron metabolism was constructed. A total of 190 patients were sequenced: 94 from a tertiary hemochromatosis clinic and 96 submitted for HFE testing with biochemical evidence of iron overload [elevated ferritin (>450 µg/L) or transferrin saturation (>55%)] obtained from a chart review. RESULTS: From the hemochromatosis clinic cohort, six patients were diagnosed with non-HFE hemochromatosis due to homozygous hemojuvelin (HFE2) mutations. Ten additional heterozygous pathogenic mutations were observed. From the chart review cohort, a C-terminus ferritin light chain (FTL) frameshift mutation was observed consistent with neuroferritinopathy. Heterozygous deletion of HFE2 and four additional rare pathogenic or likely pathogenic heterozygous mutations were identified in seven patients. CONCLUSIONS: An iron metabolism gene panel provided a molecular diagnosis in six patients with non-HFE iron overload and is suitable for diagnostic purposes in exceptional cases in specialized clinics. Further research will be required to assess the modifier effect of rare heterozygous mutations in iron metabolism genes.

Gene-centric meta-analyses for central adiposity traits in up to 57 412 individuals of European descent confirm known loci and reveal several novel associations.

Waist circumference (WC) and waist-to-hip ratio (WHR) are surrogate measures of central adiposity that are associated with adverse cardiovascular events, type 2 diabetes and cancer independent of body mass index (BMI). WC and WHR are highly heritable with multiple susceptibility loci identified to date. We assessed the association between SNPs and BMI-adjusted WC and WHR and unadjusted WC in up to 57 412 individuals of European descent from 22 cohorts collaborating with the NHLBI's Candidate Gene Association Resource (CARe) project. The study population consisted of women and men aged 20-80 years. Study participants were genotyped using the ITMAT/Broad/CARE array, which includes ∼50 000 cosmopolitan tagged SNPs across ∼2100 cardiovascular-related genes. Each trait was modeled as a function of age, study site and principal components to control for population stratification, and we conducted a fixed-effects meta-analysis. No new loci for WC were observed. For WHR analyses, three novel loci were significantly associated (P < 2.4 × 10(-6)). Previously unreported rs2811337-G near TMCC1 was associated with increased WHR (ß ± SE, 0.048 ± 0.008, P = 7.7 × 10(-9)) as was rs7302703-G in HOXC10 (ß = 0.044 ± 0.008, P = 2.9 × 10(-7)) and rs936108-C in PEMT (ß = 0.035 ± 0.007, P = 1.9 × 10(-6)). Sex-stratified analyses revealed two additional novel signals among females only, rs12076073-A in SHC1 (ß = 0.10 ± 0.02, P = 1.9 × 10(-6)) and rs1037575-A in ATBDB4 (ß = 0.046 ± 0.01, P = 2.2 × 10(-6)), supporting an already established sexual dimorphism of central adiposity-related genetic variants. Functional analysis using ENCODE and eQTL databases revealed that several of these loci are in regulatory regions or regions with differential expression in adipose tissue.

Mendelian randomization of blood lipids for coronary heart disease.

AIMS: To investigate the causal role of high-density lipoprotein cholesterol (HDL-C) and triglycerides in coronary heart disease (CHD) using multiple instrumental variables for Mendelian randomization. METHODS AND RESULTS: We developed weighted allele scores based on single nucleotide polymorphisms (SNPs) with established associations with HDL-C, triglycerides, and low-density lipoprotein cholesterol (LDL-C). For each trait, we constructed two scores. The first was unrestricted, including all independent SNPs associated with the lipid trait identified from a prior meta-analysis (threshold P < 2 × 10(-6)); and the second a restricted score, filtered to remove any SNPs also associated with either of the other two lipid traits at P ≤ 0.01. Mendelian randomization meta-analyses were conducted in 17 studies including 62,199 participants and 12,099 CHD events. Both the unrestricted and restricted allele scores for LDL-C (42 and 19 SNPs, respectively) associated with CHD. For HDL-C, the unrestricted allele score (48 SNPs) was associated with CHD (OR: 0.53; 95% CI: 0.40, 0.70), per 1 mmol/L higher HDL-C, but neither the restricted allele score (19 SNPs; OR: 0.91; 95% CI: 0.42, 1.98) nor the unrestricted HDL-C allele score adjusted for triglycerides, LDL-C, or statin use (OR: 0.81; 95% CI: 0.44, 1.46) showed a robust association. For triglycerides, the unrestricted allele score (67 SNPs) and the restricted allele score (27 SNPs) were both associated with CHD (OR: 1.62; 95% CI: 1.24, 2.11 and 1.61; 95% CI: 1.00, 2.59, respectively) per 1-log unit increment. However, the unrestricted triglyceride score adjusted for HDL-C, LDL-C, and statin use gave an OR for CHD of 1.01 (95% CI: 0.59, 1.75). CONCLUSION: The genetic findings support a causal effect of triglycerides on CHD risk, but a causal role for HDL-C, though possible, remains less certain.

Genetic meta-analysis of 15,901 African Americans identifies variation in EXOC3L1 is associated with HDL concentration.

Meta-analyses of European populations has successfully identified genetic variants in over 150 loci associated with lipid levels, but results from additional ethnicities remain limited. Previously, we reported two novel lipid loci identified in a sample of 7,657 African Americans using a gene-centric array including 50,000 SNPs in 2,100 candidate genes. Initial discovery and follow-up of signals with P < 10(-5) in additional African American samples confirmed CD36 and ICAM1. Using an additional 8,244 African American female samples from the Women's Health Initiative SNP Health Association Resource genome-wide association study dataset, we further examined the previous meta-analyses results by attempting to replicate 20 additional putative lipid signals with P < 10(-4). Replication confirmed rs868213, located in a splice donor region of exocyst complex component 3-like 1 (EXOC3L1) as a novel signal for HDL (additive allelic effect ß = 0.02; P = 1.4 × 10(-8); meta-analyses of discovery and replication). EXOC3L1 is strongly expressed in vascular endothelium and forms part of the exocyst complex, a key facilitator of the trafficking of lipid receptors. Increasing sample sizes for genetic studies in nonEuropean populations will continue to improve our understanding of lipid metabolism.