Genome-wide association study of Lp-PLA(2) activity and mass in the Framingham Heart Study.

Lipoprotein-associated phospholipase A(2) (Lp-PLA(2)) is an emerging risk factor and therapeutic target for cardiovascular disease. The activity and mass of this enzyme are heritable traits, but major genetic determinants have not been explored in a systematic, genome-wide fashion. We carried out a genome-wide association study of Lp-PLA(2) activity and mass in 6,668 Caucasian subjects from the population-based Framingham Heart Study. Clinical data and genotypes from the Affymetrix 550K SNP array were obtained from the open-access Framingham SHARe project. Each polymorphism that passed quality control was tested for associations with Lp-PLA(2) activity and mass using linear mixed models implemented in the R statistical package, accounting for familial correlations, and controlling for age, sex, smoking, lipid-lowering-medication use, and cohort. For Lp-PLA(2) activity, polymorphisms at four independent loci reached genome-wide significance, including the APOE/APOC1 region on chromosome 19 (p = 6 x 10(-24)); CELSR2/PSRC1 on chromosome 1 (p = 3 x 10(-15)); SCARB1 on chromosome 12 (p = 1x10(-8)) and ZNF259/BUD13 in the APOA5/APOA1 gene region on chromosome 11 (p = 4 x 10(-8)). All of these remained significant after accounting for associations with LDL cholesterol, HDL cholesterol, or triglycerides. For Lp-PLA(2) mass, 12 SNPs achieved genome-wide significance, all clustering in a region on chromosome 6p12.3 near the PLA2G7 gene. Our analyses demonstrate that genetic polymorphisms may contribute to inter-individual variation in Lp-PLA(2) activity and mass.

Metaprotein expression modeling for label-free quantitative proteomics.

BACKGROUND: Label-free quantitative proteomics holds a great deal of promise for the future study of both medicine and biology. However, the data generated is extremely intricate in its correlation structure, and its proper analysis is complex. There are issues with missing identifications. There are high levels of correlation between many, but not all, of the peptides derived from the same protein. Additionally, there may be systematic shifts in the sensitivity of the machine between experiments or even through time within the duration of a single experiment. RESULTS: We describe a hierarchical model for analyzing unbiased, label-free proteomics data which utilizes the covariance of peptide expression across samples as well as MS/MS-based identifications to group peptides-a strategy we call metaprotein expression modeling. Our metaprotein model acknowledges the possibility of misidentifications, post-translational modifications and systematic differences between samples due to changes in instrument sensitivity or differences in total protein concentration. In addition, our approach allows us to validate findings from unbiased, label-free proteomics experiments with further unbiased, label-free proteomics experiments. Finally, we demonstrate the clinical/translational utility of the model for building predictors capable of differentiating biological phenotypes as well as for validating those findings in the context of three novel cohorts of patients with Hepatitis C. CONCLUSIONS: Mass-spectrometry proteomics is quickly becoming a powerful tool for studying biological and translational questions. Making use of all of the information contained in a particular set of data will be critical to the success of those endeavors. Our proposed model represents an advance in the ability of statistical models of proteomic data to identify and utilize correlation between features. This allows validation of predictors without translation to targeted assays in addition to informing the choice of targets when it is appropriate to generate those assays.

Pleiotropy and allelic heterogeneity in the TOMM40-APOE genomic region related to clinical and metabolic features of hepatitis C infection.

Hepatitis C virus (HCV) modulates host lipid metabolism as part of its lifecycle and is dependent upon VLDL for co-assembly and secretion. HCV dyslipidemia is associated with steatosis, insulin resistance, IL28B genotype and disease progression. Apolipoprotein E (ApoE) is an important lipid transport protein, a key constituent of VLDL, and is involved in immunomodulation. Our aims were to determine the role of APOE regional polymorphisms on host lipids, IL28B genotype and disease severity in chronic HCV (CHC) patients. The study cohort included 732 CHC patients with available DNA for genotype determination of four polymorphisms in the chromosome 19 region that encompasses the TOMM40, APOE and APOC1 genes. Serum lipid analysis and apolipoproteins levels were measured using an immunoturbidimetric assay. APOE rs7412 polymorphism (capturing the ε2 isoform) was significantly associated with serum ApoE levels in both Caucasians and African-American patients (p = 2.3 × 10(-11)) and explained 7 % of variance in serum ApoE. Among IL28B-CC patients (n = 196), the rs429358 (defines ε4 isoform) and TOMM40 '523' S polymorphisms were associated with 12 % of variance in ApoB levels. Patients homozygous for the APOE ε3 isoform had a greater than twofold increased odds of F2-F4 fibrosis (p = 1.8 × 10(-5)), independent of serum lipid and lipoprotein levels. There were no associations between APOE polymorphisms and serum HDL-C, APO-CIII and triglycerides. In CHC patients, genetic heterogeneity in the APOE/TOMM40 genomic region is significantly associated with variation in serum ApoE and ApoB levels, and also with fibrosis suggesting a pleiotropic attribute of this genomic region.

High predictive accuracy of an unbiased proteomic profile for sustained virologic response in chronic hepatitis C patients.

UNLABELLED: Chronic hepatitis C (CHC) infection is a leading cause of endstage liver disease. Current standard-of-care (SOC) interferon-based therapy results in sustained virological response (SVR) in only one-half of patients, and is associated with significant side effects. Accurate host predictors of virologic response are needed to individualize treatment regimens. We applied a label-free liquid chromatography mass spectrometry (LC-MS)-based proteomics discovery platform to pretreatment sera from a well-characterized and matched training cohort of 55 CHC patients, and an independent validation set of 41 CHC genotype 1 patients with characterized IL28B genotype. Accurate mass and retention time methods aligned samples to generate quantitative peptide data, with predictive modeling using Bayesian sparse latent factor regression. We identified 105 proteins of interest with two or more peptides, and a total of 3,768 peptides. Regression modeling selected three identified metaproteins, vitamin D binding protein, alpha 2 HS glycoprotein, and Complement C5, with a high predictive area under the receiver operator characteristic curve (AUROC) of 0.90 for SVR in the training cohort. A model averaging approach for identified peptides resulted in an AUROC of 0.86 in the validation cohort, and correctly identified virologic response in 71% of patients without the favorable IL28B "responder" genotype. CONCLUSION: Our preliminary data indicate that a serum-based protein signature can accurately predict treatment response to current SOC in most CHC patients.

The effect of SNCA 3' region on the levels of SNCA-112 splicing variant.

Genetic variability at the 3' region of SNCA locus has been repeatedly associated with susceptibility to sporadic Parkinson's disease (PD). Accumulated evidence emphasizes the importance of SNCA dosage and expression levels in PD pathogenesis. However, the mechanism through which the 3' region of SNCA gene modulates the risk to develop sporadic PD remained elusive. We studied the effect of PD risk-associated variants at SNCA 3' regions on SNCA112-mRNA (exon 5 in-frame skipping) levels in vivo in 117 neuropathologically normal, human brain frontal cortex samples. SNPs tagging the SNCA 3' showed significant effects on the relative levels of SNCA112-mRNA from total SNCA transcripts levels. The "risk" alleles were correlated with increased expression ratio of SNCA112-mRNA from total. We provide evidence for functional consequences of PD-associated SNCA gene variants at the 3' region, suggesting that genetic regulation of SNCA splicing plays an important role in the development of the disease. Further studies to determine the definite functional variant/s within SNCA 3'and to establish their association with PD pathology are necessary.

Beneficial IL28B genotype associated with lower frequency of hepatic steatosis in patients with chronic hepatitis C.

BACKGROUND & AIMS: IL28B polymorphisms have been associated with both treatment induced and spontaneous clearance of hepatitis C virus (HCV). We previously found that LDL cholesterol levels were higher in chronic hepatitis C (CHC) patients with the CC genotype at the rs12979860 polymorphism, located proximal to the IL28 gene. Here we analyzed the association of steatosis with IL28B genotype in treatment naïve patients with CHC. METHODS: Two independent cohorts of 145 genotype 1 infected patients from an antifibrotic study and 180 genotype 1 patients from Duke were analyzed for the presence and severity of steatosis in relation to the rs12979860 polymorphism at the IL28B locus. TaqMan assay based genotyping classified three groups CC, CT, and TT. RESULTS: CC genotype was associated with a lower prevalence of steatosis. In the antifibrotic study, steatosis was found in 47.6% (50/105) of IL28B non-CC vs. 22.5% (9/40; p=0.008) in CC patients. Similarly, steatosis was found in 67.4% (89/132) of non-CC patients compared to only 39.6% (19/48; p=0.001) of CC patients in the Duke cohort. CONCLUSIONS: IL28B CC genotype is associated with less pronounced disturbances of lipid metabolism, as reflected both in serum lipoprotein levels and hepatic steatosis, in HCV infection.

Replicated association between an IL28B gene variant and a sustained response to pegylated interferon and ribavirin.

BACKGROUND & AIMS: Patients with chronic hepatitis C virus (HCV) infections are treated with pegylated interferon and ribavirin (PEG-IFN/RBV), which is effective in less than 50% of those infected with HCV genotype 1. Genome-wide association studies have linked response to PEG-IFN/RBV with common single nucleotide polymorphisms in the vicinity of interferon (IFN)-lambda genes on chromosome 19. We investigated the association between the polymorphism rs12979860 and treatment response in a diverse cohort of chronic HCV patients. METHODS: A cross-sectional study of 1021 consecutive patients enrolled in the Duke Hepatology Clinic Research Database and Biorepository. We analyzed DNA, clinical and demographic data, along with validated data of the response of 231 subjects to PEG-IFN/RBV. The study included Caucasians (n = 178), African Americans (n = 53), and HCV genotypes 1 (n = 186) and 2/3 (n = 45). The rs12979860 genotype was tested for an association with sustained virologic response, defined as undetectable levels of HCV RNA 24 weeks after treatment ended. RESULTS: The rs12979860 CC genotype (found in approximately 40% of Caucasians) predicted a sustained virologic response to therapy among Caucasians (odds ratio, 5.79; 95% confidence interval, 2.67-12.57; P = 9.0 x 10(-6)), independent of HCV genotype and other covariates. Rs12979860 CC predicted a sustained response with 78% specificity and 65% sensitivity in patients infected with HCV genotype 1). CONCLUSIONS: rs12979860 genotype is a significant independent predictor of response to PEG-IFN/RBV in patients with chronic HCV infection; tests for this genotype might be used to determine the best course of treatment for patients considering antiviral therapy.

A polymorphism near IL28B is associated with spontaneous clearance of acute hepatitis C virus and jaundice.

BACKGROUND & AIMS: A single nucleotide polymorphism (SNP) upstream of the IL28B gene has been associated with response of patients with chronic hepatitis C to therapy with pegylated interferon and ribavirin and also with spontaneous clearance of acute hepatitis C in a heterogeneous population. We analyzed the association between IL28B and the clinical presentation of acute hepatitis C virus (HCV) infection in a homogeneous population. METHODS: We analyzed the SNP rs12979860 in 190 women from the German anti-D cohort (infected with HCV genotype 1b via contaminated rhesus prophylaxis) and its association with spontaneous clearance. Clinical data were available in 136 women with acute infection who were also evaluated for IL28B genotype. Based on results of a TaqMan polymerase chain reaction assay, the rs12979860 SNP genotypes studied were C/C, C/T, or T/T. RESULTS: Spontaneous clearance was more common in patients with the C/C genotype (43/67; 64%) compared with C/T (22/90; 24%) or T/T (2/33; 6%) (P < .001). Jaundice during acute infection was more common among patients with C/C genotype (32.7%) than non-C/C patients (with C/T or T/T) (16.1%; P = .032). In C/C patients, jaundice during acute infection was not associated with an increased chance of spontaneous clearance (56.3%) compared with those without jaundice (60.6%). In contrast, in non-C/C patients, jaundice was associated with a higher likelihood of spontaneous clearance (42.9%) compared with those without jaundice (13.7%). CONCLUSIONS: The SNP rs12979860 upstream of IL28B is associated with spontaneous clearance of HCV. Women with the C/T or T/T genotype who did not develop jaundice had a lower chance of spontaneous clearance of HCV infection.

Interferon-lambda genotype and low serum low-density lipoprotein cholesterol levels in patients with chronic hepatitis C infection.

UNLABELLED: Recently, genetic polymorphisms occurring in the interferon (IFN)-lambda gene region were associated with response to IFN-based treatment of hepatitis C infection. Both infection with the hepatitis C virus and IFN therapy are associated with decreased serum cholesterol and high cholesterol has been associated with increased likelihood to respond to IFN. We sought to determine if the IFN-lambda gene variant was also associated with serum lipid levels in chronic hepatitis C patients. We compared genotypes of the rs12979860 polymorphism, located proximal to the IL28 gene, with serum lipid and apolipoprotein levels in 746 subjects with chronic hepatitis C virus infection, not currently undergoing treatment, using multivariable analysis of variance. Levels of total cholesterol (P = 6.0 x 10(-4)), apolipoprotein B (P = 1.3 x 10(-6)) and low-density lipoprotein (LDL) cholesterol (P = 8.9 x 10(-10)) were significantly higher in subjects carrying the rs12979860 CC responder genotype compared with those with the CT or TT genotype. Levels of triglycerides (P = 0.03), apolipoprotein A-I (P = 0.06), and apolipoprotein E (P = 0.01) were slightly lower in the rs12979860 CC genotype group, whereas levels of high-density lipoprotein cholesterol (P = 0.78) and apolipoprotein C-III (P = 0.74) did not vary by rs12979860 genotype. CONCLUSION: Our results suggest that low levels of LDL cholesterol in chronic hepatitis C patients may be a marker of host endogenous IFN response to hepatitis C and that subjects with the rs12979860 CC responder genotype may have a lower endogenous IFN response to the virus.

Artificial intelligence enables comprehensive genome interpretation and nomination of candidate diagnoses for rare genetic diseases.

BACKGROUND: Clinical interpretation of genetic variants in the context of the patient's phenotype is becoming the largest component of cost and time expenditure for genome-based diagnosis of rare genetic diseases. Artificial intelligence (AI) holds promise to greatly simplify and speed genome interpretation by integrating predictive methods with the growing knowledge of genetic disease. Here we assess the diagnostic performance of Fabric GEM, a new, AI-based, clinical decision support tool for expediting genome interpretation. METHODS: We benchmarked GEM in a retrospective cohort of 119 probands, mostly NICU infants, diagnosed with rare genetic diseases, who received whole-genome or whole-exome sequencing (WGS, WES). We replicated our analyses in a separate cohort of 60 cases collected from five academic medical centers. For comparison, we also analyzed these cases with current state-of-the-art variant prioritization tools. Included in the comparisons were trio, duo, and singleton cases. Variants underpinning diagnoses spanned diverse modes of inheritance and types, including structural variants (SVs). Patient phenotypes were extracted from clinical notes by two means: manually and using an automated clinical natural language processing (CNLP) tool. Finally, 14 previously unsolved cases were reanalyzed. RESULTS: GEM ranked over 90% of the causal genes among the top or second candidate and prioritized for review a median of 3 candidate genes per case, using either manually curated or CNLP-derived phenotype descriptions. Ranking of trios and duos was unchanged when analyzed as singletons. In 17 of 20 cases with diagnostic SVs, GEM identified the causal SVs as the top candidate and in 19/20 within the top five, irrespective of whether SV calls were provided or inferred ab initio by GEM using its own internal SV detection algorithm. GEM showed similar performance in absence of parental genotypes. Analysis of 14 previously unsolved cases resulted in a novel finding for one case, candidates ultimately not advanced upon manual review for 3 cases, and no new findings for 10 cases. CONCLUSIONS: GEM enabled diagnostic interpretation inclusive of all variant types through automated nomination of a very short list of candidate genes and disorders for final review and reporting. In combination with deep phenotyping by CNLP, GEM enables substantial automation of genetic disease diagnosis, potentially decreasing cost and expediting case review.

Impact of gene variants on sex-specific regulation of human Scavenger receptor class B type 1 (SR-BI) expression in liver and association with lipid levels in a population-based study.

BACKGROUND: Several studies have noted that genetic variants of SCARB1, a lipoprotein receptor involved in reverse cholesterol transport, are associated with serum lipid levels in a sex-dependent fashion. However, the mechanism underlying this gene by sex interaction has not been explored. METHODS: We utilized both epidemiological and molecular methods to study how estrogen and gene variants interact to influence SCARB1 expression and lipid levels. Interaction between 35 SCARB1 haplotype-tagged polymorphisms and endogenous estradiol levels was assessed in 498 postmenopausal Caucasian women from the population-based Rancho Bernardo Study. We further examined associated variants with overall and SCARB1 splice variant (SR-BI and SR-BII) expression in 91 human liver tissues using quantitative real-time PCR. RESULTS: Several variants on a haplotype block spanning intron 11 to intron 12 of SCARB1 showed significant gene by estradiol interaction affecting serum lipid levels, the strongest for rs838895 with HDL-cholesterol (p=9.2x10(-4)) and triglycerides (p=1.3x10(-3)) and the triglyceride:HDL cholesterol ratio (p=2.7x10(-4)). These same variants were associated with expression of the SR-BI isoform in a sex-specific fashion, with the strongest association found among liver tissue from 52 young women<45 years old (p=0.002). CONCLUSIONS: Estrogen and SCARB1 genotype may act synergistically to regulate expression of SCARB1 isoforms and impact serum levels of HDL cholesterol and triglycerides. This work highlights the importance of considering sex-dependent effects of gene variants on serum lipid levels.

Racial differences in the interaction between family history and risk factors associated with diabetes in the National Health and Nutritional Examination Survey, 1999-2004.

PURPOSE: We sought to determine whether the association between family history, a surrogate for genetic predisposition, and diabetes was modified by any known diabetes risk factors and if these relationships were constant across different ethnic groups. METHODS: We examined 10,899 adults from the National Health and Nutrition Examination Survey (1999 -2004) to identify interactions between family history and clinical, demographic, and lifestyle variables for the outcome of diabetes using logistic regression analysis in racial/ethnic subgroups. RESULTS: There was significant heterogeneity by race/ethnicity in the interaction between covariates and family history in relation to diabetes. In black (P = 0.0001) and Hispanic (P = 0.013), but not white (P = 0.75) subgroups, high-familial risk was a strong risk factor for diabetes among lean individuals but less so among overweight or obese subjects.Among blacks, high-familial risk conferred a 20-fold increased odds of diabetes among lean subjects and only a sixfold increased odds among obese individuals. CONCLUSIONS: These findings suggest possible race/ethnic-specific differences in gene by environment interaction and identify body mass index as an important effect modifier of familial risk in diabetes in non-white populations. These findings may help guide future genetic studies and improve the utility of family history as a public health screening tool.

Transforming the practice of medicine using genomics.

Recent studies have demonstrated the use of genomic data, particularly gene expression signatures, as clinical prognostic factors in complex diseases. Such studies herald the future for genomic medicine and the opportunity for personalized prognosis in a variety of clinical contexts that utilize genomescale molecular information. Several key areas represent logical and critical next steps in the use of complex genomic profiling data towards the goal of personalized medicine. First, analyses should be geared toward the development of molecular profiles that predict future events - such as major clinical events or the response, resistance, or adverse reaction to therapy. Secondly, these must move into actual clinical practice by forming the basis for the next generation of clinical trials that will employ these methodologies to stratify patients. Lastly, there remain formidable challenges is in the translation of genomic technologies into clinical medicine that will need to be addressed: professional and public education, health outcomes research, reimbursement, regulatory oversight and privacy protection.

Gene by sex interaction in the etiology of coronary heart disease and the preceding metabolic syndrome.

BACKGROUND: Despite decades of research, the genetic basis of coronary heart disease and its metabolic risk factors is poorly understood. Few studies consider that sex may modify the effect of gene variants on disease. Investigation of gene by sex interaction may help to elucidate underlying genetic susceptibilities and explain the sexual dimorphism of these complex traits. AIMS: The aim of this review is to summarize evidence for gene by sex interaction in the etiology of coronary heart disease and the metabolic syndrome. DATA SYNTHESIS: Published literature was examined in the areas of familial aggregation of coronary heart disease; heritability of body mass, insulin resistance, hypertension and dyslipidemia; genome-wide linkage analysis in humans and rodents; and large-scale genetic association studies. Possible mechanisms of gene by sex interaction are discussed including X-linked inheritance, confounding by risk factors and the effect of sex hormones. CONCLUSIONS: The strongest evidence for gene by sex interaction in relation to coronary heart disease and the metabolic syndrome is in the etiology of body mass, insulin resistance and possibly dyslipidemia. Genetic studies of these traits would benefit from taking sex differences into account. Alternative mechanisms underlying gene by sex interaction, besides obvious sex hormone differences, should be considered.

Toward clinical genomics in everyday medicine: perspectives and recommendations.

Precision or personalized medicine through clinical genome and exome sequencing has been described by some as a revolution that could transform healthcare delivery, yet it is currently used in only a small fraction of patients, principally for the diagnosis of suspected Mendelian conditions and for targeting cancer treatments. Given the burden of illness in our society, it is of interest to ask how clinical genome and exome sequencing can be constructively integrated more broadly into the routine practice of medicine for the betterment of public health. In November 2014, 46 experts from academia, industry, policy and patient advocacy gathered in a conference sponsored by Illumina, Inc. to discuss this question, share viewpoints and propose recommendations. This perspective summarizes that work and identifies some of the obstacles and opportunities that must be considered in translating advances in genomics more widely into the practice of medicine.

Modification of the effects of estrogen therapy on HDL cholesterol levels by polymorphisms of the HDL-C receptor, SR-BI: the Rancho Bernardo Study.

BACKGROUND: Previous studies have found polymorphisms of the HDL receptor, SR-BI, to be associated with plasma HDL-C in women, but not men, suggesting a modifying role of estrogen. We examined whether the association between SR-BI genotypes and HDL-C is modified by use of unopposed estrogen in community-dwelling postmenopausal Caucasian women. METHODS: Common polymorphisms in Intron5 and Exon8 of the SR-BI gene were evaluated in 689 women from the Rancho Bernardo Study. Multiple linear regression analysis was carried out adjusting for confounders. RESULTS: HDL-C levels did not differ significantly by genotype in the aggregate population. However, significant interaction was found between estrogen use and Exon8 (p=0.03), Intron5 (p=0.03) and Intron5/Exon8 diplotypes (p=0.01). SR-BI genotype was associated with HDL-C levels only among estrogen users (p=0.05) and explained 5.3% of the variance in HDL-C in this group. Consistent with prior studies, individuals heterozygous at both Intron5 and Exon8 loci had the lowest HDL-C levels. Among women with symptomatic CHD, the interaction between estrogen use and SR-BI genotype became even stronger. CONCLUSIONS: The effect that unopposed estrogen use has on HDL-C may depend on a woman's SR-BI genotype.

Aspirin resistance and a single gene.

This study examined the association of single nucleotide polymorphisms in 4 candidate genes in a cohort of subjects with aspirin resistance. Aspirin resistance was significantly associated with genetic variation in the platelet surface adenosine 5-diphosphate receptor gene P2Y1.

Atherosclerotic risk genotypes and recurrent coronary events after myocardial infarction.

The association of a group of prespecified atherosclerotic risk genotypes with recurrent coronary events (coronary-related death, nonfatal myocardial infarction, or unstable angina) was investigated in a cohort of 1,008 patients after infarction during an average follow-up of 28 months. We used a carrier-ship approach with time-dependent survivorship analysis to evaluate the average risk of each carried genotype. Contrary to expectation, the hazard ratio for recurrent coronary events per carried versus noncarried genotype was 0.89 (95% confidence interval 0.80 to 0.99, p = 0.03) after adjustment for relevant genetic, clinical, and environmental covariates. This hazard ratio, derived from the 7 prespecified genotypes, indicated an average 11% reduction in the risk of recurrent coronary events per carried versus noncarried genotype. At 1 year after hospital discharge, the cumulative probability of recurrent coronary events was 26% in those who carried < or =1, 20% for those with 2 to 4, and 13% for those with > or =5 of these genotypes (p = 0.02). This unexpected risk reversal is a likely consequence of changes in the mix of risk factors in pre- and postinfarction populations. In conclusion, this under appreciated, population-based, risk-reversal phenomenon may explain the inconsistent associations of genetic risk factors with outcome events in previous reports involving coronary populations with different risk attributes.