Wnt Signaling Interactor WTIP (Wilms Tumor Interacting Protein) Underlies Novel Mechanism for Cardiac Hypertrophy

BACKGROUND

The study of hypertrophic cardiomyopathy (HCM) can yield insight into the mechanisms underlying the complex trait of cardiac hypertrophy. To date, most genetic variants associated with HCM have been found in sarcomeric genes. Here, we describe a novel HCM-associated variant in the noncanonical Wnt signaling interactor WTIP (Wilms tumor interacting protein) and provide evidence of a role for WTIP in complex disease.

METHODS

In a family affected by HCM, we used exome sequencing and identity-by-descent analysis to identify a novel variant in WTIP (p.Y233F). We knocked down WTIP in isolated neonatal rat ventricular myocytes with lentivirally delivered short hairpin ribonucleic acids and in Danio rerio via morpholino injection. We performed weighted gene coexpression network analysis for WTIP in human cardiac tissue, as well as association analysis for WTIP variation and left ventricular hypertrophy. Finally, we generated induced pluripotent stem cell-derived cardiomyocytes from patient tissue, characterized size and calcium cycling, and determined the effect of verapamil treatment on calcium dynamics.

RESULTS

WTIP knockdown caused hypertrophy in neonatal rat ventricular myocytes and increased cardiac hypertrophy, peak calcium, and resting calcium in D rerio. Network analysis of human cardiac tissue indicated WTIP as a central coordinator of prohypertrophic networks, while common variation at the WTIP locus was associated with human left ventricular hypertrophy. Patient-derived WTIP p.Y233F-induced pluripotent stem cell-derived cardiomyocytes recapitulated cellular hypertrophy and increased resting calcium, which was ameliorated by verapamil.

CONCLUSIONS

We demonstrate that a novel genetic variant found in a family with HCM disrupts binding to a known Wnt signaling protein, misregulating cardiomyocyte calcium dynamics. Further, in orthogonal model systems, we show that expression of the gene WTIP is important in complex cardiac hypertrophy phenotypes. These findings, derived from the observation of a rare Mendelian disease variant, uncover a novel disease mechanism with implications across diverse forms of cardiac hypertrophy.

Rare Protein-Truncating Variants in APOB, Lower Low-Density Lipoprotein Cholesterol, and Protection Against Coronary Heart Disease

Supplemental Digital Content is available in the text.

Background

Familial hypobetalipoproteinemia is a genetic disorder caused by rare protein-truncating variants (PTV) in the gene encoding APOB (apolipoprotein B), the major protein component of LDL (low-density lipoprotein) and triglyceride-rich lipoprotein particles. Whether heterozygous APOB deficiency is associated with decreased risk for coronary heart disease (CHD) is uncertain. We combined family-based and large scale gene-sequencing to characterize the association of rare PTVs in APOB with circulating LDL-C (LDL cholesterol), triglycerides, and risk for CHD.

Methods

We sequenced the APOB gene in 29 Japanese hypobetalipoproteinemia families, as well as 57 973 individuals derived from 12 CHD case-control studies—18 442 with early-onset CHD and 39 531 controls. We defined PTVs as variants that lead to a premature stop, disrupt canonical splice-sites, or lead to insertions/deletions that shift reading frame. We tested the association of rare APOB PTV carrier status with blood lipid levels and CHD.

Results

Among 29 familial hypobetalipoproteinemia families, 8 families harbored APOB PTVs. Carrying 1 APOB PTV was associated with 55 mg/dL lower LDL-C (P=3×10^-5) and 53% lower triglyceride level (P=2×10^-4). Among 12 case-control studies, an APOB PTV was present in 0.038% of CHD cases as compared to 0.092% of controls. APOB PTV carrier status was associated with a 43 mg/dL lower LDL-C (P=2×10^-7), a 30% decrease in triglycerides (P=5×10^-4), and a 72% lower risk for CHD (odds ratio, 0.28; 95% CI, 0.12–0.64; P=0.002).

Conclusions

Rare PTV mutations in APOB which are associated with lower LDL-C and reduced triglycerides also confer protection against CHD.

Loss-of-Function ABCC8 Mutations in Pulmonary Arterial Hypertension

BACKGROUND

In pulmonary arterial hypertension (PAH), pathological changes in pulmonary arterioles progressively raise pulmonary artery pressure and increase pulmonary vascular resistance, leading to right heart failure and high mortality rates. Recently, the first potassium channelopathy in PAH, because of mutations in KCNK3, was identified as a genetic cause and pharmacological target.

METHODS

Exome sequencing was performed to identify novel genes in a cohort of 99 pediatric and 134 adult-onset group I PAH patients. Novel rare variants in the gene identified were independently identified in a cohort of 680 adult-onset patients. Variants were expressed in COS cells and function assessed by patch-clamp and rubidium flux analysis.

RESULTS

We identified a de novo novel heterozygous predicted deleterious missense variant c.G2873A (p.R958H) in ABCC8 in a child with idiopathic PAH. We then evaluated all individuals in the original and a second cohort for rare or novel variants in ABCC8 and identified 11 additional heterozygous predicted damaging ABCC8 variants. ABCC8 encodes SUR1 (sulfonylurea receptor 1)-a regulatory subunit of the ATP-sensitive potassium channel. We observed loss of ATP-sensitive potassium channel function for all ABCC8 variants evaluated and pharmacological rescue of all channel currents in vitro by the SUR1 activator, diazoxide.

CONCLUSIONS

Novel and rare missense variants in ABCC8 are associated with PAH. Identified ABCC8 mutations decreased ATP-sensitive potassium channel function, which was pharmacologically recovered.

Genomics-First Evaluation of Heart Disease Associated With Titin-Truncating Variants

BACKGROUND

Truncating variants in the Titin gene (TTNtvs) are common in individuals with idiopathic dilated cardiomyopathy (DCM). However, a comprehensive genomics-first evaluation of the impact of TTNtvs in different clinical contexts, and the evaluation of modifiers such as genetic ancestry, has not been performed.

METHODS

We reviewed whole exome sequence data for >71 000 individuals (61 040 from the Geisinger MyCode Community Health Initiative (2007 to present) and 10 273 from the PennMedicine BioBank (2013 to present) to identify anyone with TTNtvs. We further selected individuals with TTNtvs in exons highly expressed in the heart (proportion spliced in [PSI] >0.9). Using linked electronic health records, we evaluated associations of TTNtvs with diagnoses and quantitative echocardiographic measures, including subanalyses for individuals with and without DCM diagnoses. We also reviewed data from the Jackson Heart Study to validate specific analyses for individuals of African ancestry.

RESULTS

Identified with a TTNtv in a highly expressed exon (hiPSI) were 1.2% individuals in PennMedicine BioBank and 0.6% at Geisinger. The presence of a hiPSI TTNtv was associated with increased odds of DCM in individuals of European ancestry (odds ratio [95% CI]: 18.7 [9.1-39.4] {PennMedicine BioBank} and 10.8 [7.0-16.0] {Geisinger}). hiPSI TTNtvs were not associated with DCM in individuals of African ancestry, despite a high DCM prevalence (odds ratio, 1.8 [0.2-13.7]; P=0.57). Among 244 individuals of European ancestry with DCM in PennMedicine BioBank, hiPSI TTNtv carriers had lower left ventricular ejection fraction (β=-12%, P=3×10^-7), and increased left ventricular diameter (β=0.65 cm, P=9×10^-3). In the Geisinger cohort, hiPSI TTNtv carriers without a cardiomyopathy diagnosis had more atrial fibrillation (odds ratio, 2.4 [1.6-3.6]) and heart failure (odds ratio, 3.8 [2.4-6.0]), and lower left ventricular ejection fraction (β=-3.4%, P=1×10^-7).

CONCLUSIONS

Individuals of European ancestry with hiPSI TTNtv have an abnormal cardiac phenotype characterized by lower left ventricular ejection fraction, irrespective of the clinical manifestation of cardiomyopathy. Associations with arrhythmias, including atrial fibrillation, were observed even when controlling for cardiomyopathy diagnosis. In contrast, no association between hiPSI TTNtvs and DCM was discerned among individuals of African ancestry. Given these findings, clinical identification of hiPSI TTNtv carriers may alter clinical management strategies.

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Association Between Titin Loss-of-Function Variants and Early-Onset Atrial Fibrillation

IMPORTANCE

Atrial fibrillation (AF) is the most common arrhythmia affecting 1% of the population. Young individuals with AF have a strong genetic association with the disease, but the mechanisms remain incompletely understood.

OBJECTIVE

To perform large-scale whole-genome sequencing to identify genetic variants related to AF.

DESIGN, SETTING, AND PARTICIPANTS

The National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine Program includes longitudinal and cohort studies that underwent high-depth whole-genome sequencing between 2014 and 2017 in 18 526 individuals from the United States, Mexico, Puerto Rico, Costa Rica, Barbados, and Samoa. This case-control study included 2781 patients with early-onset AF from 9 studies and identified 4959 controls of European ancestry from the remaining participants. Results were replicated in the UK Biobank (346 546 participants) and the MyCode Study (42 782 participants).

EXPOSURES

Loss-of-function (LOF) variants in genes at AF loci and common genetic variation across the whole genome.

MAIN OUTCOMES AND MEASURES

Early-onset AF (defined as AF onset in persons <66 years of age). Due to multiple testing, the significance threshold for the rare variant analysis was P = 4.55 × 10-3.

RESULTS

Among 2781 participants with early-onset AF (the case group), 72.1% were men, and the mean (SD) age of AF onset was 48.7 (10.2) years. Participants underwent whole-genome sequencing at a mean depth of 37.8 fold and mean genome coverage of 99.1%. At least 1 LOF variant in TTN, the gene encoding the sarcomeric protein titin, was present in 2.1% of case participants compared with 1.1% in control participants (odds ratio [OR], 1.76 [95% CI, 1.04-2.97]). The proportion of individuals with early-onset AF who carried a LOF variant in TTN increased with an earlier age of AF onset (P value for trend, 4.92 × 10-4), and 6.5% of individuals with AF onset prior to age 30 carried a TTN LOF variant (OR, 5.94 [95% CI, 2.64-13.35]; P = 1.65 × 10-5). The association between TTN LOF variants and AF was replicated in an independent study of 1582 patients with early-onset AF (cases) and 41 200 control participants (OR, 2.16 [95% CI, 1.19-3.92]; P = .01).

CONCLUSIONS AND RELEVANCE

In a case-control study, there was a statistically significant association between an LOF variant in the TTN gene and early-onset AF, with the variant present in a small percentage of participants with early-onset AF (the case group). Further research is necessary to understand whether this is a causal relationship.

Genetics of blood lipids among ~300,000 multi-ethnic participants of the Million Veteran Program

The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of U.S. military veterans. We genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least 1 blood lipid measurement including 57,332 blacks and 24,743 Hispanics, we tested up to ~32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total N > 600,000). Through a focus on mutations predicted to result in a loss of gene function and a phenome-wide association study, we propose novel indications for pharmaceutical inhibitors targeting PCSK9 (abdominal aortic aneurysm), ANGPTL4 (type 2 diabetes), and PDE3B (triglycerides and coronary disease).

Exome Sequencing-Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants

IMPORTANCE

Detection of disease-associated variants in the BRCA1 and BRCA2 (BRCA1/2) genes allows for cancer prevention and early diagnosis in high-risk individuals.

OBJECTIVES

To identify pathogenic and likely pathogenic (P/LP) BRCA1/2 variants in an unselected research cohort, and to characterize the features associated with P/LP variants.

DESIGN, SETTING, AND PARTICIPANTS

This is a cross-sectional study of adult volunteers (n = 50 726) who underwent exome sequencing at a single health care system (Geisinger Health System, Danville, Pennsylvania) from January 1, 2014, to March 1, 2016. Participants are part of the DiscovEHR cohort and were identified through the Geisinger MyCode Community Health Initiative. They consented to a research protocol that included sequencing and return of actionable test results. Clinical data from electronic health records and clinical visits were correlated with variants. Comparisons were made between those with (cases) and those without (controls) P/LP variants in BRCA1/2.

MAIN OUTCOMES

Prevalence of P/LP BRCA1/2 variants in cohort, proportion of variant carriers not previously ascertained through clinical testing, and personal and family history of relevant cancers among BRCA1/2 variant carriers and noncarriers.

RESULTS

Of the 50 726 health system patients who underwent exome sequencing, 50 459 (99.5%) had no expected pathogenic BRCA1/2 variants and 267 (0.5%) were BRCA1/2 carriers. Of the 267 cases (148 [55.4%] were women and 119 [44.6%] were men with a mean [range] age of 58.9 [23-90] years), 183 (68.5%) received clinically confirmed results in their electronic health record. Among the 267 participants with P/LP BRCA1/2 variants, 219 (82.0%) had no prior clinical testing, 95 (35.6%) had BRCA1 variants, and 172 (64.4%) had BRCA2 variants. Syndromic cancer diagnoses were present in 11 (47.8%) of the 23 deceased BRCA1/2 carriers and in 56 (20.9%) of all 267 BRCA1/2 carriers. Among women, 31 (20.9%) of 148 variant carriers had a personal history of breast cancer, compared with 1554 (5.2%) of 29 880 noncarriers (odds ratio [OR], 5.95; 95% CI, 3.88-9.13; P < .001). Ovarian cancer history was present in 15 (10.1%) of 148 variant carriers and in 195 (0.6%) of 29 880 variant noncarriers (OR, 18.30; 95% CI, 10.48-31.4; P < .001). Among 89 BRCA1/2 carriers without prior testing but with comprehensive personal and family history data, 44 (49.4%) did not meet published guidelines for clinical testing.

CONCLUSIONS AND RELEVANCE

This study found that compared with previous clinical care, exome sequencing-based screening identified 5 times as many individuals with P/LP BRCA1/2 variants. These findings suggest that genomic screening may identify BRCA1/2-associated cancer risk that might otherwise remain undetected within health care systems and may provide opportunities to reduce morbidity and mortality in patients.

Rare variants in SOX17 are associated with pulmonary arterial hypertension with congenital heart disease

BACKGROUND

Pulmonary arterial hypertension (PAH) is a rare disease characterized by distinctive changes in pulmonary arterioles that lead to progressive pulmonary arterial pressures, right-sided heart failure, and a high mortality rate. Up to 30% of adult and 75% of pediatric PAH cases are associated with congenital heart disease (PAH-CHD), and the underlying etiology is largely unknown. There are no known major risk genes for PAH-CHD.

METHODS

To identify novel genetic causes of PAH-CHD, we performed whole exome sequencing in 256 PAH-CHD patients. We performed a case-control gene-based association test of rare deleterious variants using 7509 gnomAD whole genome sequencing population controls. We then screened a separate cohort of 413 idiopathic and familial PAH patients without CHD for rare deleterious variants in the top association gene.

RESULTS

We identified SOX17 as a novel candidate risk gene (p = 5.5e-7). SOX17 is highly constrained and encodes a transcription factor involved in Wnt/β-catenin and Notch signaling during development. We estimate that rare deleterious variants contribute to approximately 3.2% of PAH-CHD cases. The coding variants identified include likely gene-disrupting (LGD) and deleterious missense, with most of the missense variants occurring in a highly conserved HMG-box protein domain. We further observed an enrichment of rare deleterious variants in putative targets of SOX17, many of which are highly expressed in developing heart and pulmonary vasculature. In the cohort of PAH without CHD, rare deleterious variants of SOX17 were observed in 0.7% of cases.

CONCLUSIONS

These data strongly implicate SOX17 as a new risk gene contributing to PAH-CHD as well as idiopathic/familial PAH. Replication in other PAH cohorts and further characterization of the clinical phenotype will be important to confirm the precise role of SOX17 and better estimate the contribution of genes regulated by SOX17.

Genetic inactivation of ANGPTL4 improves glucose homeostasis and is associated with reduced risk of diabetes

Angiopoietin-like 4 (ANGPTL4) is an endogenous inhibitor of lipoprotein lipase that modulates lipid levels, coronary atherosclerosis risk, and nutrient partitioning. We hypothesize that loss of ANGPTL4 function might improve glucose homeostasis and decrease risk of type 2 diabetes (T2D). We investigate protein-altering variants in ANGPTL4 among 58,124 participants in the DiscovEHR human genetics study, with follow-up studies in 82,766 T2D cases and 498,761 controls. Carriers of p.E40K, a variant that abolishes ANGPTL4 ability to inhibit lipoprotein lipase, have lower odds of T2D (odds ratio 0.89, 95% confidence interval 0.85–0.92, p = 6.3 × 10⁻¹⁰), lower fasting glucose, and greater insulin sensitivity. Predicted loss-of-function variants are associated with lower odds of T2D among 32,015 cases and 84,006 controls (odds ratio 0.71, 95% confidence interval 0.49–0.99, p = 0.041). Functional studies in Angptl4-deficient mice confirm improved insulin sensitivity and glucose homeostasis. In conclusion, genetic inactivation of ANGPTL4 is associated with improved glucose homeostasis and reduced risk of T2D.

Genetic variation in ANGPTL4 is associated with lipid traits. Here, the authors find that predicted loss-of-function variants in ANGPTL4 are associated with glucose homeostasis and reduced risk of type 2 diabetes and that Angptl4^−/− mice on a high-fat diet show improved insulin sensitivity.

A Protein-Truncating HSD17B13 Variant and Protection from Chronic Liver Disease

BACKGROUND

Elucidation of the genetic factors underlying chronic liver disease may reveal new therapeutic targets.

METHODS

We used exome sequence data and electronic health records from 46,544 participants in the DiscovEHR human genetics study to identify genetic variants associated with serum levels of alanine aminotransferase (ALT) and aspartate aminotransferase (AST). Variants that were replicated in three additional cohorts (12,527 persons) were evaluated for association with clinical diagnoses of chronic liver disease in DiscovEHR study participants and two independent cohorts (total of 37,173 persons) and with histopathological severity of liver disease in 2391 human liver samples.

RESULTS

A splice variant (rs72613567:TA) in HSD17B13, encoding the hepatic lipid droplet protein hydroxysteroid 17-beta dehydrogenase 13, was associated with reduced levels of ALT (P=4.2×10^-12) and AST (P=6.2×10^-10). Among DiscovEHR study participants, this variant was associated with a reduced risk of alcoholic liver disease (by 42% [95% confidence interval {CI}, 20 to 58] among heterozygotes and by 53% [95% CI, 3 to 77] among homozygotes), nonalcoholic liver disease (by 17% [95% CI, 8 to 25] among heterozygotes and by 30% [95% CI, 13 to 43] among homozygotes), alcoholic cirrhosis (by 42% [95% CI, 14 to 61] among heterozygotes and by 73% [95% CI, 15 to 91] among homozygotes), and nonalcoholic cirrhosis (by 26% [95% CI, 7 to 40] among heterozygotes and by 49% [95% CI, 15 to 69] among homozygotes). Associations were confirmed in two independent cohorts. The rs72613567:TA variant was associated with a reduced risk of nonalcoholic steatohepatitis, but not steatosis, in human liver samples. The rs72613567:TA variant mitigated liver injury associated with the risk-increasing PNPLA3 p.I148M allele and resulted in an unstable and truncated protein with reduced enzymatic activity.

CONCLUSIONS

A loss-of-function variant in HSD17B13 was associated with a reduced risk of chronic liver disease and of progression from steatosis to steatohepatitis. (Funded by Regeneron Pharmaceuticals and others.).

Rare variants in drug target genes contributing to complex diseases, phenome-wide

The DrugBank database consists of ~800 genes that are well characterized drug targets. This list of genes is a useful resource for association testing. For example, loss of function (LOF) genetic variation has the potential to mimic the effect of drugs, and high impact variation in these genes can impact downstream traits. Identifying novel associations between genetic variation in these genes and a range of diseases can also uncover new uses for the drugs that target these genes. Phenome Wide Association Studies (PheWAS) have been successful in identifying genetic associations across hundreds of thousands of diseases. We have conducted a novel gene based PheWAS to test the effect of rare variants in DrugBank genes, evaluating associations between these genes and more than 500 quantitative and dichotomous phenotypes. We used whole exome sequencing data from 38,568 samples in Geisinger MyCode Community Health Initiative. We evaluated the results of this study when binning rare variants using various filters based on potential functional impact. We identified multiple novel associations, and the majority of the significant associations were driven by functionally annotated variation. Overall, this study provides a sweeping exploration of rare variant associations within functionally relevant genes across a wide range of diagnoses.

Genome-wide Study of Atrial Fibrillation Identifies Seven Risk Loci and Highlights Biological Pathways and Regulatory Elements Involved in Cardiac Development

Atrial fibrillation (AF) is a common cardiac arrhythmia and a major risk factor for stroke, heart failure, and premature death. The pathogenesis of AF remains poorly understood, which contributes to the current lack of highly effective treatments. To understand the genetic variation and biology underlying AF, we undertook a genome-wide association study (GWAS) of 6,337 AF individuals and 61,607 AF-free individuals from Norway, including replication in an additional 30,679 AF individuals and 278,895 AF-free individuals. Through genotyping and dense imputation mapping from whole-genome sequencing, we tested almost nine million genetic variants across the genome and identified seven risk loci, including two novel loci. One novel locus (lead single-nucleotide variant [SNV] rs12614435; p = 6.76 × 10^-18) comprised intronic and several highly correlated missense variants situated in the I-, A-, and M-bands of titin, which is the largest protein in humans and responsible for the passive elasticity of heart and skeletal muscle. The other novel locus (lead SNV rs56202902; p = 1.54 × 10^-11) covered a large, gene-dense chromosome 1 region that has previously been linked to cardiac conduction. Pathway and functional enrichment analyses suggested that many AF-associated genetic variants act through a mechanism of impaired muscle cell differentiation and tissue formation during fetal heart development.

APPLICATIONS OF GENETICS, GENOMICS AND BIOINFORMATICS IN DRUG DISCOVERY

As the impact of genetics, genomics, and bioinformatics on drug discovery has been increasingly recognized, this session of the 2018 Pacific Symposium on Biocomputing (PSB) aims to facilitate scientific discussions between academia and pharmaceutical industry on how to best apply genetics, genomics and bioinformatics to enable drug discovery. The selected papers focus on developing and applying computational approaches to understand drug mechanisms of action and develop drug combination strategies, to enable in silico drug screening, and to further delineate disease pathways for target identification and validation.

MAPPIN: a method for annotating, predicting pathogenicity and mode of inheritance for nonsynonymous variants

Nonsynonymous single nucleotide variants (nsSNVs) constitute about 50% of known disease-causing mutations and understanding their functional impact is an area of active research. Existing algorithms predict pathogenicity of nsSNVs; however, they are unable to differentiate heterozygous, dominant disease-causing variants from heterozygous carrier variants that lead to disease only in the homozygous state. Here, we present MAPPIN (Method for Annotating, Predicting Pathogenicity, and mode of Inheritance for Nonsynonymous variants), a prediction method which utilizes a random forest algorithm to distinguish between nsSNVs with dominant, recessive, and benign effects. We apply MAPPIN to a set of Mendelian disease-causing mutations and accurately predict pathogenicity for all mutations. Furthermore, MAPPIN predicts mode of inheritance correctly for 70.3% of nsSNVs. MAPPIN also correctly predicts pathogenicity for 87.3% of mutations from the Deciphering Developmental Disorders Study with a 78.5% accuracy for mode of inheritance. When tested on a larger collection of mutations from the Human Gene Mutation Database, MAPPIN is able to significantly discriminate between mutations in known dominant and recessive genes. Finally, we demonstrate that MAPPIN outperforms CADD and Eigen in predicting disease inheritance modes for all validation datasets. To our knowledge, MAPPIN is the first nsSNV pathogenicity prediction algorithm that provides mode of inheritance predictions, adding another layer of information for variant prioritization.

Genomic diagnostics within a medically underserved population: efficacy and implications

PurposeWe integrated whole-exome sequencing (WES) and chromosomal microarray analysis (CMA) into a clinical workflow to serve an endogamous, uninsured, agrarian community.MethodsSeventy-nine probands (newborn to 49.8 years) who presented between 1998 and 2015 remained undiagnosed after biochemical and molecular investigations. We generated WES data for probands and family members and vetted variants through rephenotyping, segregation analyses, and population studies.ResultsThe most common presentation was neurological disease (64%). Seven (9%) probands were diagnosed by CMA. Family WES data were informative for 37 (51%) of the 72 remaining individuals, yielding a specific genetic diagnosis (n = 32) or revealing a novel molecular etiology (n = 5). For five (7%) additional subjects, negative WES decreased the likelihood of genetic disease. Compared to trio analysis, "family" WES (average seven exomes per proband) reduced filtered candidate variants from 22 ± 6 to 5 ± 3 per proband. Nineteen (51%) alleles were de novo and 17 (46%) inherited; the latter added to a population-based diagnostic panel. We found actionable secondary variants in 21 (4.2%) of 502 subjects, all of whom opted to be informed.ConclusionCMA and family-based WES streamline and economize diagnosis of rare genetic disorders, accelerate novel gene discovery, and create new opportunities for community-based screening and prevention in underserved populations.

Genetic and Pharmacologic Inactivation of ANGPTL3 and Cardiovascular Disease

BACKGROUND

Loss-of-function variants in the angiopoietin-like 3 gene (ANGPTL3) have been associated with decreased plasma levels of triglycerides, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol. It is not known whether such variants or therapeutic antagonism of ANGPTL3 are associated with a reduced risk of atherosclerotic cardiovascular disease.

METHODS

We sequenced the exons of ANGPTL3 in 58,335 participants in the DiscovEHR human genetics study. We performed tests of association for loss-of-function variants in ANGPTL3 with lipid levels and with coronary artery disease in 13,102 case patients and 40,430 controls from the DiscovEHR study, with follow-up studies involving 23,317 case patients and 107,166 controls from four population studies. We also tested the effects of a human monoclonal antibody, evinacumab, against Angptl3 in dyslipidemic mice and against ANGPTL3 in healthy human volunteers with elevated levels of triglycerides or LDL cholesterol.

RESULTS

In the DiscovEHR study, participants with heterozygous loss-of-function variants in ANGPTL3 had significantly lower serum levels of triglycerides, HDL cholesterol, and LDL cholesterol than participants without these variants. Loss-of-function variants were found in 0.33% of case patients with coronary artery disease and in 0.45% of controls (adjusted odds ratio, 0.59; 95% confidence interval, 0.41 to 0.85; P=0.004). These results were confirmed in the follow-up studies. In dyslipidemic mice, inhibition of Angptl3 with evinacumab resulted in a greater decrease in atherosclerotic lesion area and necrotic content than a control antibody. In humans, evinacumab caused a dose-dependent placebo-adjusted reduction in fasting triglyceride levels of up to 76% and LDL cholesterol levels of up to 23%.

CONCLUSIONS

Genetic and therapeutic antagonism of ANGPTL3 in humans and of Angptl3 in mice was associated with decreased levels of all three major lipid fractions and decreased odds of atherosclerotic cardiovascular disease. (Funded by Regeneron Pharmaceuticals and others; ClinicalTrials.gov number, NCT01749878 .).

Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study

The DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System couples high-throughput sequencing to an integrated health care system using longitudinal electronic health records (EHRs). We sequenced the exomes of 50,726 adult participants in the DiscovEHR study to identify ~4.2 million rare single-nucleotide variants and insertion/deletion events, of which ~176,000 are predicted to result in a loss of gene function. Linking these data to EHR-derived clinical phenotypes, we find clinical associations supporting therapeutic targets, including genes encoding drug targets for lipid lowering, and identify previously unidentified rare alleles associated with lipid levels and other blood level traits. About 3.5% of individuals harbor deleterious variants in 76 clinically actionable genes. The DiscovEHR data set provides a blueprint for large-scale precision medicine initiatives and genomics-guided therapeutic discovery.

Protein-Truncating Variants at the Cholesteryl Ester Transfer Protein Gene and Risk for Coronary Heart Disease

RATIONALE

Therapies that inhibit CETP (cholesteryl ester transfer protein) have failed to demonstrate a reduction in risk for coronary heart disease (CHD). Human DNA sequence variants that truncate the CETP gene may provide insight into the efficacy of CETP inhibition.

OBJECTIVE

To test whether protein-truncating variants (PTVs) at the CETP gene were associated with plasma lipid levels and CHD.

METHODS AND RESULTS

We sequenced the exons of the CETP gene in 58 469 participants from 12 case-control studies (18 817 CHD cases, 39 652 CHD-free controls). We defined PTV as those that lead to a premature stop, disrupt canonical splice sites, or lead to insertions/deletions that shift frame. We also genotyped 1 Japanese-specific PTV in 27561 participants from 3 case-control studies (14 286 CHD cases, 13 275 CHD-free controls). We tested association of CETP PTV carrier status with both plasma lipids and CHD. Among 58 469 participants with CETP gene-sequencing data available, average age was 51.5 years and 43% were women; 1 in 975 participants carried a PTV at the CETP gene. Compared with noncarriers, carriers of PTV at CETP had higher high-density lipoprotein cholesterol (effect size, 22.6 mg/dL; 95% confidence interval, 18-27; P<1.0×10-4), lower low-density lipoprotein cholesterol (-12.2 mg/dL; 95% confidence interval, -23 to -0.98; P=0.033), and lower triglycerides (-6.3%; 95% confidence interval, -12 to -0.22; P=0.043). CETP PTV carrier status was associated with reduced risk for CHD (summary odds ratio, 0.70; 95% confidence interval, 0.54-0.90; P=5.1×10-3).

CONCLUSIONS

Compared with noncarriers, carriers of PTV at CETP displayed higher high-density lipoprotein cholesterol, lower low-density lipoprotein cholesterol, lower triglycerides, and lower risk for CHD.

Electronic health record phenotype in subjects with genetic variants associated with arrhythmogenic right ventricular cardiomyopathy: a study of 30,716 subjects with exome sequencing

Purpose

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart disease. Clinical follow-up of incidental findings in ARVC-associated genes is recommended. We aimed to determine the prevalence of disease thus ascertained.

Methods

30,716 individuals underwent exome sequencing. Variants in PKP2, DSG2, DSC2, DSP, JUP, TMEM43, or TGFβ3 that were database-listed as pathogenic or likely pathogenic were identified and evidence-reviewed. For subjects with putative loss-of-function (pLOF) variants or variants of uncertain significance (VUS), electronic health records (EHR) were reviewed for ARVC diagnosis, diagnostic criteria, and International Classification of Diseases (ICD-9) codes.

Results

18 subjects had pLOF variants; none had an EHR diagnosis of ARVC. Of 14 patients with an electrocardiogram (ECG), one had a minor diagnostic criterion, 13 were normal. 184 subjects had VUSs; none had an ARVC diagnosis. In subjects with VUSs, there was no difference in the proportion with major (4%) or minor (13%) ECG diagnostic criteria compared to variant-negative controls. ICD-9 codes showed no difference in defibrillator utilization, electrophysiologic abnormalities or non-ischemic cardiomyopathies in patients with pLOF or VUSs compared to controls.

Conclusion

pLOF variants in an unselected cohort were not associated with ARVC phenotypes based on EHR review. The negative predictive value of EHR review remains uncertain.

Association of Rare and Common Variation in the Lipoprotein Lipase Gene With Coronary Artery Disease

IMPORTANCE

The activity of lipoprotein lipase (LPL) is the rate-determining step in clearing triglyceride-rich lipoproteins from the circulation. Mutations that damage the LPL gene (LPL) lead to lifelong deficiency in enzymatic activity and can provide insight into the relationship of LPL to human disease.

OBJECTIVE

To determine whether rare and/or common variants in LPL are associated with early-onset coronary artery disease (CAD).

DESIGN, SETTING, AND PARTICIPANTS

In a cross-sectional study, LPL was sequenced in 10 CAD case-control cohorts of the multinational Myocardial Infarction Genetics Consortium and a nested CAD case-control cohort of the Geisinger Health System DiscovEHR cohort between 2010 and 2015. Common variants were genotyped in up to 305 699 individuals of the Global Lipids Genetics Consortium and up to 120 600 individuals of the CARDIoGRAM Exome Consortium between 2012 and 2014. Study-specific estimates were pooled via meta-analysis.

EXPOSURES

Rare damaging mutations in LPL included loss-of-function variants and missense variants annotated as pathogenic in a human genetics database or predicted to be damaging by computer prediction algorithms trained to identify mutations that impair protein function. Common variants in the LPL gene region included those independently associated with circulating triglyceride levels.

MAIN OUTCOMES AND MEASURES

Circulating lipid levels and CAD.

RESULTS

Among 46 891 individuals with LPL gene sequencing data available, the mean (SD) age was 50 (12.6) years and 51% were female. A total of 188 participants (0.40%; 95% CI, 0.35%-0.46%) carried a damaging mutation in LPL, including 105 of 32 646 control participants (0.32%) and 83 of 14 245 participants with early-onset CAD (0.58%). Compared with 46 703 noncarriers, the 188 heterozygous carriers of an LPL damaging mutation displayed higher plasma triglyceride levels (19.6 mg/dL; 95% CI, 4.6-34.6 mg/dL) and higher odds of CAD (odds ratio = 1.84; 95% CI, 1.35-2.51; P < .001). An analysis of 6 common LPL variants resulted in an odds ratio for CAD of 1.51 (95% CI, 1.39-1.64; P = 1.1 × 10-22) per 1-SD increase in triglycerides.

CONCLUSIONS AND RELEVANCE

The presence of rare damaging mutations in LPL was significantly associated with higher triglyceride levels and presence of coronary artery disease. However, further research is needed to assess whether there are causal mechanisms by which heterozygous lipoprotein lipase deficiency could lead to coronary artery disease.

Systems Genomics Identifies a Key Role for Hypocretin/Orexin Receptor-2 in Human Heart Failure

BACKGROUND

The genetic determinants of heart failure (HF) and response to medical therapy remain unknown. We hypothesized that identifying genetic variants of HF that associate with response to medical therapy would elucidate the genetic basis of cardiac function.

OBJECTIVES

This study sought to identify genetic variations associated with response to HF therapy.

METHODS

This study compared extremes of response to medical therapy in 866 HF patients using a genome-wide approach that informed the systems-based design of a customized single nucleotide variant array. The effect of genotype on gene expression was measured using allele-specific luciferase reporter assays. Candidate gene transcription-deficient mice underwent echocardiography and treadmill exercise. The ability of the target gene agonist to rescue mice from chemically-induced HF was assessed with echocardiography.

RESULTS

Of 866 HF patients, 136 had an ejection fraction improvement of 20% attributed to resynchronization (n = 83), revascularization (n = 7), tachycardia resolution (n = 2), alcohol cessation (n = 1), or medications (n = 43). Those with the minor allele for rs7767652, upstream of hypocretin (orexin) receptor-2 (HCRTR2), were less likely to have improved left ventricular function (odds ratio: 0.40 per minor allele; p = 3.29 × 10(-5)). In a replication cohort of 798 patients, those with a minor allele for rs7767652 had a lower prevalence of ejection fraction >35% (odds ratio: 0.769 per minor allele; p = 0.021). In an HF model, HCRTR2-deficient mice exhibited poorer cardiac function, worse treadmill exercise capacity, and greater myocardial scarring. Orexin, an HCRTR2 agonist, rescued function in this HF mouse model.

CONCLUSIONS

A systems approach identified a novel genetic contribution to human HF and a promising therapeutic agent efficacious in an HF model.

Inactivating Variants in ANGPTL4 and Risk of Coronary Artery Disease

BACKGROUND

Higher-than-normal levels of circulating triglycerides are a risk factor for ischemic cardiovascular disease. Activation of lipoprotein lipase, an enzyme that is inhibited by angiopoietin-like 4 (ANGPTL4), has been shown to reduce levels of circulating triglycerides.

METHODS

We sequenced the exons of ANGPTL4 in samples obtain from 42,930 participants of predominantly European ancestry in the DiscovEHR human genetics study. We performed tests of association between lipid levels and the missense E40K variant (which has been associated with reduced plasma triglyceride levels) and other inactivating mutations. We then tested for associations between coronary artery disease and the E40K variant and other inactivating mutations in 10,552 participants with coronary artery disease and 29,223 controls. We also tested the effect of a human monoclonal antibody against ANGPTL4 on lipid levels in mice and monkeys.

RESULTS

We identified 1661 heterozygotes and 17 homozygotes for the E40K variant and 75 participants who had 13 other monoallelic inactivating mutations in ANGPTL4. The levels of triglycerides were 13% lower and the levels of high-density lipoprotein (HDL) cholesterol were 7% higher among carriers of the E40K variant than among noncarriers. Carriers of the E40K variant were also significantly less likely than noncarriers to have coronary artery disease (odds ratio, 0.81; 95% confidence interval, 0.70 to 0.92; P=0.002). K40 homozygotes had markedly lower levels of triglycerides and higher levels of HDL cholesterol than did heterozygotes. Carriers of other inactivating mutations also had lower triglyceride levels and higher HDL cholesterol levels and were less likely to have coronary artery disease than were noncarriers. Monoclonal antibody inhibition of Angptl4 in mice and monkeys reduced triglyceride levels.

CONCLUSIONS

Carriers of E40K and other inactivating mutations in ANGPTL4 had lower levels of triglycerides and a lower risk of coronary artery disease than did noncarriers. The inhibition of Angptl4 in mice and monkeys also resulted in corresponding reductions in these values. (Funded by Regeneron Pharmaceuticals.).

INTEGRATING CLINICAL LABORATORY MEASURES AND ICD-9 CODE DIAGNOSES IN PHENOME-WIDE ASSOCIATION STUDIES

Electronic health records (EHR) provide a comprehensive resource for discovery, allowing unprecedented exploration of the impact of genetic architecture on health and disease. The data of EHRs also allow for exploration of the complex interactions between health measures across health and disease. The discoveries arising from EHR based research provide important information for the identification of genetic variation for clinical decision-making. Due to the breadth of information collected within the EHR, a challenge for discovery using EHR based data is the development of high-throughput tools that expose important areas of further research, from genetic variants to phenotypes. Phenome-Wide Association studies (PheWAS) provide a way to explore the association between genetic variants and comprehensive phenotypic measurements, generating new hypotheses and also exposing the complex relationships between genetic architecture and outcomes, including pleiotropy. EHR based PheWAS have mainly evaluated associations with case/control status from International Classification of Disease, Ninth Edition (ICD-9) codes. While these studies have highlighted discovery through PheWAS, the rich resource of clinical lab measures collected within the EHR can be better utilized for high-throughput PheWAS analyses and discovery. To better use these resources and enrich PheWAS association results we have developed a sound methodology for extracting a wide range of clinical lab measures from EHR data. We have extracted a first set of 21 clinical lab measures from the de-identified EHR of participants of the Geisinger MyCodeTM biorepository, and calculated the median of these lab measures for 12,039 subjects. Next we evaluated the association between these 21 clinical lab median values and 635,525 genetic variants, performing a genome-wide association study (GWAS) for each of 21 clinical lab measures. We then calculated the association between SNPs from these GWAS passing our Bonferroni defined p-value cutoff and 165 ICD-9 codes. Through the GWAS we found a series of results replicating known associations, and also some potentially novel associations with less studied clinical lab measures. We found the majority of the PheWAS ICD-9 diagnoses highly related to the clinical lab measures associated with same SNPs. Moving forward, we will be evaluating further phenotypes and expanding the methodology for successful extraction of clinical lab measurements for research and PheWAS use. These developments are important for expanding the PheWAS approach for improved EHR based discovery.

Sequence to Medical Phenotypes: A Framework for Interpretation of Human Whole Genome DNA Sequence Data

High throughput sequencing has facilitated a precipitous drop in the cost of genomic sequencing, prompting predictions of a revolution in medicine via genetic personalization of diagnostic and therapeutic strategies. There are significant barriers to realizing this goal that are related to the difficult task of interpreting personal genetic variation. A comprehensive, widely accessible application for interpretation of whole genome sequence data is needed. Here, we present a series of methods for identification of genetic variants and genotypes with clinical associations, phasing genetic data and using Mendelian inheritance for quality control, and providing predictive genetic information about risk for rare disease phenotypes and response to pharmacological therapy in single individuals and father-mother-child trios. We demonstrate application of these methods for disease and drug response prognostication in whole genome sequence data from twelve unrelated adults, and for disease gene discovery in one father-mother-child trio with apparently simplex congenital ventricular arrhythmia. In doing so we identify clinically actionable inherited disease risk and drug response genotypes in pre-symptomatic individuals. We also nominate a new candidate gene in congenital arrhythmia, ATP2B4, and provide experimental evidence of a regulatory role for variants discovered using this framework.

Technological advances have dramatically reduced the cost of sequencing the human genome. Tools for analyzing such data across families including annotation of clinically important variants and aggregation of variants for personalizing drug prescriptions have been developed but few are publically available. Here we describe such tools then demonstrate their application in several distinct data sets. In particular, we use the tools to define the genetic basis of a new congenital arrhythmia syndrome.

CLAMMS: a scalable algorithm for calling common and rare copy number variants from exome sequencing data

MOTIVATION

Several algorithms exist for detecting copy number variants (CNVs) from human exome sequencing read depth, but previous tools have not been well suited for large population studies on the order of tens or hundreds of thousands of exomes. Their limitations include being difficult to integrate into automated variant-calling pipelines and being ill-suited for detecting common variants. To address these issues, we developed a new algorithm--Copy number estimation using Lattice-Aligned Mixture Models (CLAMMS)--which is highly scalable and suitable for detecting CNVs across the whole allele frequency spectrum.

RESULTS

In this note, we summarize the methods and intended use-case of CLAMMS, compare it to previous algorithms and briefly describe results of validation experiments. We evaluate the adherence of CNV calls from CLAMMS and four other algorithms to Mendelian inheritance patterns on a pedigree; we compare calls from CLAMMS and other algorithms to calls from SNP genotyping arrays for a set of 3164 samples; and we use TaqMan quantitative polymerase chain reaction to validate CNVs predicted by CLAMMS at 39 loci (95% of rare variants validate; across 19 common variant loci, the mean precision and recall are 99% and 94%, respectively). In the Supplementary Materials (available at the CLAMMS Github repository), we present our methods and validation results in greater detail.

AVAILABILITY AND IMPLEMENTATION

https://github.com/rgcgithub/clamms (implemented in C).

CONTACT

jeffrey.reid@regeneron.com

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Molecular diagnosis of long QT syndrome at 10 days of life by rapid whole genome sequencing

BACKGROUND

The advent of clinical next generation sequencing is rapidly changing the landscape of rare disease medicine. Molecular diagnosis of long QT syndrome (LQTS) can affect clinical management, including risk stratification and selection of pharmacotherapy on the basis of the type of ion channel affected, but results from the current gene panel testing requires 4-16 weeks before return to clinicians.

OBJECTIVE

A term female infant presented with 2:1 atrioventricular block and ventricular arrhythmias consistent with perinatal LQTS, requiring aggressive treatment including epicardial pacemaker and cardioverter-defibrillator implantation and sympathectomy on day of life 2. We sought to provide a rapid molecular diagnosis for the optimization of treatment strategies.

METHODS

We performed Clinical Laboratory Improvement Amendments-certified rapid whole genome sequencing (WGS) with a speed-optimized bioinformatics platform to achieve molecular diagnosis at 10 days of life.

RESULTS

We detected a known pathogenic variant in KCNH2 that was demonstrated to be paternally inherited by follow-up genotyping. The unbiased assessment of the entire catalog of human genes provided by WGS revealed a maternally inherited variant of unknown significance in a novel gene.

CONCLUSION

Rapid clinical WGS provides faster and more comprehensive diagnostic information at 10 days of life than does standard gene panel testing. In selected clinical scenarios such as perinatal LQTS, rapid WGS can provide more timely and clinically actionable information than can a standard commercial test.

Clinical interpretation and implications of whole-genome sequencing

IMPORTANCE

Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication.

OBJECTIVES

To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings.

DESIGN, SETTING, AND PARTICIPANTS

An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings.

MAIN OUTCOMES AND MEASURES

Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up.

RESULTS

Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001).

CONCLUSIONS AND RELEVANCE

In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.

Personal omics profiling reveals dynamic molecular and medical phenotypes

Personalized medicine is expected to benefit from combining genomic information with regular monitoring of physiological states by multiple high-throughput methods. Here, we present an integrative personal omics profile (iPOP), an analysis that combines genomic, transcriptomic, proteomic, metabolomic, and autoantibody profiles from a single individual over a 14 month period. Our iPOP analysis revealed various medical risks, including type 2 diabetes. It also uncovered extensive, dynamic changes in diverse molecular components and biological pathways across healthy and diseased conditions. Extremely high-coverage genomic and transcriptomic data, which provide the basis of our iPOP, revealed extensive heteroallelic changes during healthy and diseased states and an unexpected RNA editing mechanism. This study demonstrates that longitudinal iPOP can be used to interpret healthy and diseased states by connecting genomic information with additional dynamic omics activity.

Phased whole-genome genetic risk in a family quartet using a major allele reference sequence

Whole-genome sequencing harbors unprecedented potential for characterization of individual and family genetic variation. Here, we develop a novel synthetic human reference sequence that is ethnically concordant and use it for the analysis of genomes from a nuclear family with history of familial thrombophilia. We demonstrate that the use of the major allele reference sequence results in improved genotype accuracy for disease-associated variant loci. We infer recombination sites to the lowest median resolution demonstrated to date (<1,000 base pairs). We use family inheritance state analysis to control sequencing error and inform family-wide haplotype phasing, allowing quantification of genome-wide compound heterozygosity. We develop a sequence-based methodology for Human Leukocyte Antigen typing that contributes to disease risk prediction. Finally, we advance methods for analysis of disease and pharmacogenomic risk across the coding and non-coding genome that incorporate phased variant data. We show these methods are capable of identifying multigenic risk for inherited thrombophilia and informing the appropriate pharmacological therapy. These ethnicity-specific, family-based approaches to interpretation of genetic variation are emblematic of the next generation of genetic risk assessment using whole-genome sequencing.

An individual's genetic profile plays an important role in determining risk for disease and response to medical therapy. The development of technologies that facilitate rapid whole-genome sequencing will provide unprecedented power in the estimation of disease risk. Here we develop methods to characterize genetic determinants of disease risk and response to medical therapy in a nuclear family of four, leveraging population genetic profiles from recent large scale sequencing projects. We identify the way in which genetic information flows through the family to identify sequencing errors and inheritance patterns of genes contributing to disease risk. In doing so we identify genetic risk factors associated with an inherited predisposition to blood clot formation and response to blood thinning medications. We find that this aligns precisely with the most significant disease to occur to date in the family, namely pulmonary embolism, a blood clot in the lung. These ethnicity-specific, family-based approaches to interpretation of individual genetic profiles are emblematic of the next generation of genetic risk assessment using whole-genome sequencing.

Gene coexpression network topology of cardiac development, hypertrophy, and failure

BACKGROUND

Network analysis techniques allow a more accurate reflection of underlying systems biology to be realized than traditional unidimensional molecular biology approaches. Using gene coexpression network analysis, we define the gene expression network topology of cardiac hypertrophy and failure and the extent of recapitulation of fetal gene expression programs in failing and hypertrophied adult myocardium.

METHODS AND RESULTS

We assembled all myocardial transcript data in the Gene Expression Omnibus (n=1617). Because hierarchical analysis revealed species had primacy over disease clustering, we focused this analysis on the most complete (murine) dataset (n=478). Using gene coexpression network analysis, we derived functional modules, regulatory mediators, and higher-order topological relationships between genes and identified 50 gene coexpression modules in developing myocardium that were not present in normal adult tissue. We found that known gene expression markers of myocardial adaptation were members of upregulated modules but not hub genes. We identified ZIC2 as a novel transcription factor associated with coexpression modules common to developing and failing myocardium. Of 50 fetal gene coexpression modules, 3 (6%) were reproduced in hypertrophied myocardium and 7 (14%) were reproduced in failing myocardium. One fetal module was common to both failing and hypertrophied myocardium.

CONCLUSIONS

Network modeling allows systems analysis of cardiovascular development and disease. Although we did not find evidence for a global coordinated program of fetal gene expression in adult myocardial adaptation, our analysis revealed specific gene expression modules active during both development and disease and specific candidates for their regulation.

Clinical assessment incorporating a personal genome

BACKGROUND

The cost of genomic information has fallen steeply, but the clinical translation of genetic risk estimates remains unclear. We aimed to undertake an integrated analysis of a complete human genome in a clinical context.

METHODS

We assessed a patient with a family history of vascular disease and early sudden death. Clinical assessment included analysis of this patient's full genome sequence, risk prediction for coronary artery disease, screening for causes of sudden cardiac death, and genetic counselling. Genetic analysis included the development of novel methods for the integration of whole genome and clinical risk. Disease and risk analysis focused on prediction of genetic risk of variants associated with mendelian disease, recognised drug responses, and pathogenicity for novel variants. We queried disease-specific mutation databases and pharmacogenomics databases to identify genes and mutations with known associations with disease and drug response. We estimated post-test probabilities of disease by applying likelihood ratios derived from integration of multiple common variants to age-appropriate and sex-appropriate pre-test probabilities. We also accounted for gene-environment interactions and conditionally dependent risks.

FINDINGS

Analysis of 2.6 million single nucleotide polymorphisms and 752 copy number variations showed increased genetic risk for myocardial infarction, type 2 diabetes, and some cancers. We discovered rare variants in three genes that are clinically associated with sudden cardiac death-TMEM43, DSP, and MYBPC3. A variant in LPA was consistent with a family history of coronary artery disease. The patient had a heterozygous null mutation in CYP2C19 suggesting probable clopidogrel resistance, several variants associated with a positive response to lipid-lowering therapy, and variants in CYP4F2 and VKORC1 that suggest he might have a low initial dosing requirement for warfarin. Many variants of uncertain importance were reported.

INTERPRETATION

Although challenges remain, our results suggest that whole-genome sequencing can yield useful and clinically relevant information for individual patients.

FUNDING

National Institute of General Medical Sciences; National Heart, Lung And Blood Institute; National Human Genome Research Institute; Howard Hughes Medical Institute; National Library of Medicine, Lucile Packard Foundation for Children's Health; Hewlett Packard Foundation; Breetwor Family Foundation.

Hemoglobin levels predict exercise performance, ST-segment depression, and outcome in patients referred for routine exercise treadmill testing

BACKGROUND

While the role of hemoglobin in heart failure and renal disease has been investigated, little is known about its effect on clinical exercise test performance and mortality in patients referred for routine exercise treadmill testing (ETT).

HYPOTHESIS

Patients with low hemoglobin will have poor exercise capacity and would be at increased risk of mortality and cardiovascular (CV) events.

METHODS

Clinical variables, laboratory values, and exercise treadmill data were obtained for 1,799 patients referred for routine ETT from 1997 to 2004. All-cause mortality was obtained from the United States Social Security death index and autopsy reports or clinical notes were used to determine CV events and mortality. P values < 0.05 were considered significant.

RESULTS

Our population had a mean age of 58 +/- 12 years, 16% had diabetes, 53% had hypertension, 35% had hypercholesterolemia, and 67% had a history of smoking. During follow-up, 10.3% of patients died, 3.9% of patients died of CV causes, and 11.6% had cardiovascular events. Anemic patients (hemoglobin [Hgb] < 13 g/dL) achieved lower metabolic equivalents (METs) than nonanemic patients and had more ST-segment depression (15.5% versus 8.6%, p < 0.004). Proportional hazard analysis demonstrated that hemoglobin was significantly associated with all-cause mortality (p < 0.0007), CV mortality (p < 0.009), and CV events (p < 0.01). Kaplan-Meier survival analysis demonstrated that anemic patients had significantly higher mortality and CV events.

CONCLUSION

Hemoglobin is significantly associated with exercise performance, ST-segment depression during ETT, mortality, and cardiovascular events. The incorporation of hemoglobin may add diagnostic and prognostic information to ETT.

Electrocardiographic predictors of atrial fibrillation

BACKGROUND

Atrial fibrillation (AF) is the most prevalent arrhythmia in the United States and accounts for more than 750,000 strokes per year. Noninvasive predictors of AF may help identify patients at risk of developing AF. Our objective was to identify the electrocardiographic characteristics associated with onset of AF.

METHODS

This was a retrospective cohort analysis of 42,751 patients with electrocardiograms (ECGs) ordered by physician's discretion and analyzed using a computerized system. The population was followed for detection of AF on subsequent ECGs. Cox proportional hazard regression analysis was performed to test the association between these ECG characteristics and development of AF.

RESULTS

For a mean follow-up of 5.3 years, 1,050 (2.4%) patients were found to have AF on subsequent ECG recordings. Several ECG characteristics, such as P-wave dispersion (the difference between the widest and narrowest P waves), premature atrial contractions, and an abnormal P axis, were predictive of AF with hazard ratio of approximately 2 after correcting for age and sex. P-wave index, the SD of P-wave duration across all leads, was one of the strongest predictors of AF with a concordance index of 0.62 and a hazard ratio of 2.7 (95% CI 2.1-3.3) for a P-wave index >35. These were among the several independently predictive markers identified on multivariate analysis.

CONCLUSIONS

Several ECG markers are independently predictive of future onset of AF. The P index, a measurement of disorganized atrial depolarization, is one of the strongest predictors of AF. The ECG contains valuable prognostic information that can identify patients at risk of AF.

Added value of a resting ECG neural network that predicts cardiovascular mortality

BACKGROUND

The resting 12-lead electrocardiogram (ECG) remains the most commonly used test in evaluating patients with suspected cardiovascular disease. Prognostic values of individual findings on the ECG have been reported but may be of limited use.

METHODS

The characteristics of 45,855 ECGs ordered by physician's discretion were first recorded and analyzed using a computerized system. Ninety percent of these ECGs were used to train an artifical neural network (ANN) to predict cardiovascular mortality (CVM) based on 132 ECG and four demographic characteristics. The ANN generated a Resting ECG Neural Network (RENN) score that was then tested in the remaining ECGs. The RENN score was finally assessed in a cohort of 2189 patients who underwent exercise treadmill testing and were followed for CVM.

RESULTS

The RENN score was able to better predict CVM compared to individual ECG markers or a traditional Cox regression model in the testing cohort. Over a mean of 8.6 years, there were 156 cardiovascular deaths in the treadmill cohort. Among the patients who were classified as intermediate risk by Duke Treadmill Scoring (DTS), the third tertile of the RENN score demonstrated an adjusted Cox hazard ratio of 5.4 (95% CI 2.0-15.2) compared to the first RENN tertile. The 10-year CVM was 2.8%, 8.6% and 22% in the first, second and third RENN tertiles, respectively.

CONCLUSIONS

An ANN that uses the resting ECG and demographic variables to predict CVM was created. The RENN score can further risk stratify patients deemed at moderate risk on exercise treadmill testing.

Age and double product (systolic blood pressure x heart rate) reserve-adjusted modification of the Duke Treadmill Score nomogram in men

The Duke Treadmill Score (DTS) is an established clinical tool for risk stratification. Our aim was to determine if other variables could improve the prognostic power of the DTS and if so, to modify the DTS nomogram. From a total of 1,959 patients referred for exercise testing at the Palo Alto VA Medical Center from 1997 to 2006 (a mean follow-up of 5.4 years), we studied 1,759 male veterans (age 57 +/- 12 years) free of heart failure. Double product (DP) was calculated by multiplying systolic blood pressure and heart rate; variables and their products were subtracted to obtain the differences between at rest and maximal exercise (reserve) and recovery. Of all the hemodynamic measurements, DP reserve was the strongest predictor of cardiovascular death (CVD) (Wald Z-score -3.84, p <0.001) after adjustment for potential confounders. When the components of DTS were entered in the Cox hazard model with DP reserve and age, only DP reserve and age were chosen (p <0.00001). Using the Cox coefficients, a score calculated by [age - DTS - 3 x (DP reserve/1,000)] yielded an area under the curve of 0.84 compared with 0.76 for the DTS. Using this equation, a nomogram was constructed by adding age and DP reserve to the original DTS nomogram improving estimation of annual CVD. In conclusion, we propose an age and DP reserve-adjusted DTS nomogram that improves the prognostic estimates of average annual CVD over the DTS alone.

Prediction of cardiovascular death using a novel heart rate recovery parameter

INTRODUCTION

Reassertion of vagal tone after exercise is an important component in mediating heart rate recovery (HRR), and both vagal tone and HRR have been associated with mortality. HRR is strongly related to the increase in HR from resting to peak exercise. We hypothesized that a score normalized for HR increase would better isolate the vagal influences in recovery from the sympathetic influences supporting maximal exercise.

METHODS

HRR data from 1959 veterans were analyzed. During a mean follow-up of 5.3 years, 187 (9.5%) subjects died-70 (37%) due to cardiovascular (CV) causes. A method was developed to compare HRR curve shapes normalized for differences in HR increase. Differences in the slopes of the normalized curves over the range 50-70 s were observed between the survivors and nonsurvivors, and a prognostic measurement, HRRS50-70, was developed. The incremental increases in predictive power and discriminative accuracy provided by Duke Treadmill Score (DTS), clinical parameters, HR increase, recovery variables, and HRRS50-70 were assessed.

RESULTS

In the age-adjusted Cox analysis, the only significant exercise indices associated with CV mortality were HR increase (P < 0.0001), HRRS50-70 (P = 0.01), and DTS (P < 0.001). The increased risk for patients in the lowest tertile for all three indices, relative to those with normal scores, was 22 (95% CI, 7.9-63; P < 0.0001).

CONCLUSIONS

HRRS50-70 is independent of and complementary to HR increase and DTS. Patients with abnormal HRRS50-70 and abnormal DTS and/or HR increase are at substantially increased risk of CV mortality.

Prognostic value of double product reserve

Background

Although the prognostic power of exercise capacity has been demonstrated, the relative prognostic potential of other hemodynamic responses has not been thoroughly investigated. We aimed to assess the prognostic power of double product (DP) parameters in patients referred for standard exercise testing.

Design

A retrospective cohort study.

Methods

Analyses were performed on 1959 patients referred for exercise testing at the Palo Alto Veterans Affairs Medical Center from 1997 to 2006. After removal of female and heart failure patients, 1759 male veterans (mean age 57 ± 12 years) remained. DP was calculated by multiplying systolic blood pressure (SBP) and heart rate (HR); variables and their products were subtracted to obtain the differences between rest and maximal exercise (reserve), and recovery.

Results

Multivariate Cox survival analysis was performed for 157 all-cause and 53 cardiovascular deaths during a mean follow-up of 5.4 ± 2.1 years. Although most of the hemodynamic variables were individually significant in Cox survival analysis, when age, DP reserve, exercise capacity (in metabolic equivalents), and HR recovery were entered together, only age and DP reserve were chosen. Of all hemodynamic measurements considered, DP reserve was the strongest predictor of cardiovascular prognosis after adjustment for age (Wald Z-score,-5.12; P < 0.0001) and when considering other potential confounders such as age, β-blocker use, and the Duke treadmill Score (Wald Z-score, –3.84; P < 0.0001).

Conclusion

In this study population, DP reserve had greater prognostic power than metabolic equivalents, maximal HR or systolic blood pressure, or HR recovery.

Age-adjusted modification of the Duke Treadmill Score nomogram

BACKGROUND

The Duke Treadmill Score (DTS) is an established clinical tool for risk stratification of patients referred for exercise testing, but it does not consider age. We aimed to determine if age could improve the prognostic power of the DTS and if so, to modify the DTS nomogram to include age.

METHODS

Of 1,959 patients referred for exercise testing from 1997 to 2006, 1,759 male veterans (age range 23-86 years) remained after exclusion of female and patients with heart failure. Cardiovascular mortality was the main outcome considered.

RESULTS

Cox survival analysis was performed entering age and the DTS; both were significant (P <or= .002) with similar Wald Z values (5.4 and -3.1) and regression coefficients but opposite signs. The score: age-DTS yielded an area under the receiver operating characteristic curve of 0.80 compared with 0.76 for the DTS (P < .001). Using this equation, a nomogram was constructed by adding age to the original DTS nomogram. The point at which the age-DTS line intersects the drawing line from the DTS to the corresponding value for age indicates average annual cardiovascular (CV) mortality adjusted for age. For a DTS associated with a 2.5% annual CV mortality, an age of 30 compared with 70 decreased CV risk by a factor of 10 to less than 0.2% (P < .05, log-rank test).

CONCLUSIONS

We propose an age-adjusted DTS nomogram that improves the prognostic estimates of average annual CV mortality over the DTS alone. This nomogram requires external validation and extension to women.

Does size matter? Clinical applications of scaling cardiac size and function for body size

Extensive evidence is available that cardiovascular structure and function, along with other biological properties that span the range of organism size and speciation, scale with body size. Although appreciation of such factors is commonplace in pediatrics, cardiovascular measurements in the adult population, with similarly wide variation in body size, are rarely corrected for body size. In this review, we describe the critical role of body size measurements in cardiovascular medicine. Using examples, we illustrate the confounding effects of body size. Current cardiovascular scaling practices are reviewed, as are limitations and alternative relationships between body and cardiovascular dimensions. The experimental evidence, theoretical basis, and clinical application of scaling of various functional parameters are presented. Appropriately scaled parameters aid diagnostic and therapeutic decision making in specific disease states such as hypertrophic cardiomyopathy and congestive heart failure. Large-scale studies in clinical populations are needed to define normative relationships for this purpose. Lack of appropriate consideration of body size in the evaluation of cardiovascular structure and function may adversely affect recognition and treatment of cardiovascular disease states in the adult patient.