Elias Salfati

Meta-analysis identifies common and rare variants influencing blood pressure and overlapping with metabolic trait loci

Meta-analyses of association results for blood pressure using exome-centric single-variant and gene-based tests identified 31 new loci in a discovery stage among 146,562 individuals, with follow-up and meta-analysis in 180,726 additional individuals (total n = 327,288). These blood pressure–associated loci are enriched for known variants for cardiometabolic traits. Associations were also observed for the aggregation of rare and low-frequency missense variants in three genes, NPR1, DBH, and PTPMT1. In addition, blood pressure associations at 39 previously reported loci were confirmed. The identified variants implicate biological pathways related to cardiometabolic traits, vascular function, and development. Several new variants are inferred to have roles in transcription or as hubs in protein–protein interaction networks. Genetic risk scores constructed from the identified variants were strongly associated with coronary disease and myocardial infarction. This large collection of blood pressure–associated loci suggests new therapeutic strategies for hypertension, emphasizing a link with cardiometabolic risk.

Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms

Coronary artery disease (CAD) is a leading cause of morbidity and mortality worldwide. Although 58 genomic regions have been associated with CAD thus far, most of the heritability is unexplained, indicating that additional susceptibility loci await identification. An efficient discovery strategy may be larger-scale evaluation of promising associations suggested by genome-wide association studies (GWAS). Hence, we genotyped 56,309 participants using a targeted gene array derived from earlier GWAS results and performed meta-analysis of results with 194,427 participants previously genotyped, totaling 88,192 CAD cases and 162,544 controls. We identified 25 new SNP–CAD associations (P < 5 × 10−8, in fixed-effects meta-analysis) from 15 genomic regions, including SNPs in or near genes involved in cellular adhesion, leukocyte migration and atherosclerosis (PECAM1, rs1867624), coagulation and inflammation (PROCR, rs867186 (p.Ser219Gly)) and vascular smooth muscle cell differentiation (LMOD1, rs2820315). Correlation of these regions with cell-type-specific gene expression and plasma protein levels sheds light on potential disease mechanisms.

Menopause accelerates biological aging

Significance Within an evolutionary framework, aging and reproduction are intrinsically linked. Although both laboratory and epidemiological studies have observed associations between the timing of reproductive senescence and longevity, it is not yet known whether differences in the age of menopause are reflected in biomarkers of aging. Using our recently developed biomarker of aging, the “epigenetic clock,” we examined whether age at menopause is associated with epigenetic age of blood, saliva, and buccal epithelium. This is a definitive study that shows an association between age of menopause and biological aging (measured using the epigenetic clock). Our results also indicate menopause may accelerate the epigenetic aging process in blood and that age at menopause and epigenetic age acceleration share a common genetic signature. Although epigenetic processes have been linked to aging and disease in other systems, it is not yet known whether they relate to reproductive aging. Recently, we developed a highly accurate epigenetic biomarker of age (known as the “epigenetic clock”), which is based on DNA methylation levels. Here we carry out an epigenetic clock analysis of blood, saliva, and buccal epithelium using data from four large studies: the Womens Health Initiative (n = 1,864); Invecchiare nel Chianti (n = 200); Parkinsons disease, Environment, and Genes (n = 256); and the United Kingdom Medical Research Council National Survey of Health and Development (n = 790). We find that increased epigenetic age acceleration in blood is significantly associated with earlier menopause (P = 0.00091), bilateral oophorectomy (P = 0.0018), and a longer time since menopause (P = 0.017). Conversely, epigenetic age acceleration in buccal epithelium and saliva do not relate to age at menopause; however, a higher epigenetic age in saliva is exhibited in women who undergo bilateral oophorectomy (P = 0.0079), while a lower epigenetic age in buccal epithelium was found for women who underwent menopausal hormone therapy (P = 0.00078). Using genetic data, we find evidence of coheritability between age at menopause and epigenetic age acceleration in blood. Using Mendelian randomization analysis, we find that two SNPs that are highly associated with age at menopause exhibit a significant association with epigenetic age acceleration. Overall, our Mendelian randomization approach and other lines of evidence suggest that menopause accelerates epigenetic aging of blood, but mechanistic studies will be needed to dissect cause-and-effect relationships further.

DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases

BackgroundChronic low-grade inflammation reflects a subclinical immune response implicated in the pathogenesis of complex diseases. Identifying genetic loci where DNA methylation is associated with chronic low-grade inflammation may reveal novel pathways or therapeutic targets for inflammation.ResultsWe performed a meta-analysis of epigenome-wide association studies (EWAS) of serum C-reactive protein (CRP), which is a sensitive marker of low-grade inflammation, in a large European population (n = 8863) and trans-ethnic replication in African Americans (n = 4111). We found differential methylation at 218 CpG sites to be associated with CRP (P < 1.15 × 10–7) in the discovery panel of European ancestry and replicated (P < 2.29 × 10–4) 58 CpG sites (45 unique loci) among African Americans. To further characterize the molecular and clinical relevance of the findings, we examined the association with gene expression, genetic sequence variants, and clinical outcomes. DNA methylation at nine (16%) CpG sites was associated with whole blood gene expression in cis (P < 8.47 × 10–5), ten (17%) CpG sites were associated with a nearby genetic variant (P < 2.50 × 10–3), and 51 (88%) were also associated with at least one related cardiometabolic entity (P < 9.58 × 10–5). An additive weighted score of replicated CpG sites accounted for up to 6% inter-individual variation (R2) of age-adjusted and sex-adjusted CRP, independent of known CRP-related genetic variants.ConclusionWe have completed an EWAS of chronic low-grade inflammation and identified many novel genetic loci underlying inflammation that may serve as targets for the development of novel therapeutic interventions for inflammation.

Simple, standardized incorporation of genetic risk into non-genetic risk prediction tools for complex traits: coronary heart disease as an example.

Purpose: Genetic risk assessment is becoming an important component of clinical decision-making. Genetic Risk Scores (GRSs) allow the composite assessment of genetic risk in complex traits. A technically and clinically pertinent question is how to most easily and effectively combine a GRS with an assessment of clinical risk derived from established non-genetic risk factors as well as to clearly present this information to patient and health care providers. Materials and Methods: We illustrate a means to combine a GRS with an independent assessment of clinical risk using a log-link function. We apply the method to the prediction of coronary heart disease (CHD) in the Atherosclerosis Risk in Communities (ARIC) cohort. We evaluate different constructions based on metrics of effect change, discrimination, and calibration. Results: The addition of a GRS to a clinical risk score (CRS) improves both discrimination and calibration for CHD in ARIC. Results are similar regardless of whether external vs. internal coefficients are used for the CRS, risk factor single nucleotide polymorphisms (SNPs) are included in the GRS, or subjects with diabetes at baseline are excluded. We outline how to report the construction and the performance of a GRS using our method and illustrate a means to present genetic risk information to subjects and/or their health care provider. Conclusion: The proposed method facilitates the standardized incorporation of a GRS in risk assessment.

Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci

To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including “growth factor binding,” “matrix interaction,” and “smooth muscle contraction.” We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.

Direct Estimates of the Genomic Contributions to Blood Pressure Heritability within a Population-Based Cohort (ARIC)

Blood pressure (BP) is a heritable trait with multiple environmental and genetic contributions, with current heritability estimates from twin and family studies being ~ 40%. Here, we use genome-wide polymorphism data from the Atherosclerosis Risk in Communities (ARIC) study to estimate BP heritability from genomic relatedness among cohort members. We utilized data on 6,365,596 and 9,578,528 genotyped and imputed common single nucleotide polymorphisms (SNPs), in 8,901 European ancestry (EA) and 2,860 African Ancestry (AA) ARIC participants, respectively, and a mixed linear model for analyses, to make four observations. First, for BP measurements, the heritability is ~20%/~50% and ~27%/~39% for systolic (SBP)/diastolic (DBP) blood pressure in European and African ancestry individuals, respectively, consistent with prior studies. Second, common variants with allele frequency >10% recapitulate most of the BP heritability in these data. Third, the vast majority of BP heritability varies by chromosome, depending on its length, and is largely concentrated in noncoding genomic regions annotated as DNaseI hypersensitive sites (DHSs). Fourth, the majority of this heritability arises from loci not harboring currently known cardiovascular and renal genes. Recent meta-analyses of large-scale genome-wide association studies (GWASs) and admixture mapping have identified ~50 loci associated with BP and hypertension (HTN), and yet they account for only a small fraction (~2%) of the heritability.

Contemporary Considerations for Constructing a Genetic Risk Score: An Empirical Approach.

Genetic risk scores are an increasingly popular tool for summarizing the cumulative risk of a set of Single Nucleotide Polymorphisms (SNPs) with disease. Typically only the set of the SNPs that have reached genome‐wide significance compose these scores. However recent work suggests that including additional SNPs may aid risk assessment. In this paper, we used the Atherosclerosis Risk in Communities (ARIC) Study cohort to illustrate how one can choose the optimal set of SNPs for a genetic risk score (GRS). In addition to P‐value threshold, we also examined linkage disequilibrium, imputation quality, and imputation type. We provide a variety of evaluation metrics. Results suggest that P‐value threshold had the greatest impact on GRS quality for the outcome of coronary heart disease, with an optimal threshold around 0.001. However, GRSs are relatively robust to both linkage disequilibrium and imputation quality. We also show that the optimal GRS partially depends on the evaluation metric and consequently the way one intends to use the GRS. Overall the implications highlight both the robustness of GRS and a means to empirically choose the best set of GRSs.

Susceptibility Loci for Clinical Coronary Artery Disease and Subclinical Coronary Atherosclerosis Throughout the Life-Course.

Background—Recent genome-wide association studies have identified 49 single nucleotide polymorphisms associated with clinical coronary artery disease. The mechanism by which these loci influence risk remains largely unclear. Methods and Results—We examined the association between a genetic risk score composed of high-risk alleles at the 49 single nucleotide polymorphisms and the degree of subclinical coronary atherosclerosis in 7798 participants from 6 studies stratified into 4 age groups at the time of assessment (15–34, 35–54, 55–74, and >75 years). Atherosclerosis was quantified by staining and direct visual inspection of the right coronary artery in the youngest group and by scanning for coronary artery calcification in the remaining groups. We defined cases as subjects within the top quartile of degree of atherosclerosis in 3 groups and as subjects with a coronary artery calcium score >0 in the fourth (35–54 years) where less than one quarter had any coronary artery calcium. In our meta-analysis of all strata, we found 1-SD increase in the genetic risk score increased the risk of advanced subclinical coronary atherosclerosis by 36% (P=8.3×10−25). This increase in risk was significant in all 4 age groups including the youngest group where atherosclerosis consisted primarily of raised lesions without macroscopic evidence of plaque rupture or thrombosis. Results were similar when we restricted the genetic risk score to 32 single nucleotide polymorphisms not associated with traditional risk factors or when we adjusted for traditional risk factors. Conclusions—A genetic risk score for clinical coronary artery disease is associated with advanced subclinical coronary atherosclerosis throughout the life-course. This association is apparent even at the earliest, uncomplicated stages of atherosclerosis.

Leveraging information from genetic risk scores of coronary atherosclerosis

Purpose of review Genome-wide association studies (GWAS) have identified ∼60 loci for coronary artery disease (CAD). Through genetic risk scores (GRSs), investigators are leveraging this genomic information to gain insights on both the fundamental mechanisms driving these associations as well as their utility in improving risk prediction. Recent findings GRSs of CAD track with the earliest atherosclerosis lesions in the coronary including fatty streaks and uncomplicated raised lesions. In multiple cohort studies, they predict incident CAD events independent of all traditional and lifestyle risk factors. The incorporation of SNPs with suggestive but not genome-wide association in GWAS into GRSs often increases the strength of these associations. GRS may also predict recurrent events and identify patients most likely to respond to statins. The effect of the GRS on discrimination metrics remains modest but the minimal degree of improvement needed for clinical utility is unknown. Summary Most novel loci for CAD identified through GWAS facilitate the formation of coronary atherosclerosis and stratify individuals based on their underlying burden of coronary atherosclerosis. GRSs may one day be routinely used in clinical practice to not only assess the risk of incident events but also to predict who will respond best to established prevention strategies.