Polygenic scores and their applications in kidney disease

Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications.

Relationship between stress and coronary artery disease: A comprehensive review

Coronary artery disease (CAD) poses a substantial public health challenge. This review examines the intricate relationship between psychological stress and CAD, drawing from recent research spanning the last 5 to 10 years. The literature review is organized around critical themes. It includes an analysis of genetic loci in CAD susceptibility and underscores the role of green environments in reducing cardiovascular risk. A quantitative analysis presents numerical findings for clarity, while pathophysiological mechanisms are elucidated through informative figures and diagrams. The review engages with controversies and disparities in the literature, offering a balanced perspective. A tabular comparative analysis outlines the strengths and limitations of existing approaches, emphasizing conflicting findings, and environmental factors. The review concludes by distilling key takeaways for healthcare professionals and researchers. Practical implications are explored, and lessons learned from the research process are reflected upon. The conclusion also suggests avenues for further study in understanding stress's impact on CAD.

Evolutionary Action-Machine Learning Model Identifies Candidate Genes Associated With Early-Onset Coronary Artery Disease

Background Coronary artery disease is a primary cause of death around the world, with both genetic and environmental risk factors. Although genome-wide association studies have linked >100 unique loci to its genetic basis, these only explain a fraction of disease heritability. Methods and Results To find additional gene drivers of coronary artery disease, we applied machine learning to quantitative evolutionary information on the impact of coding variants in whole exomes from the Myocardial Infarction Genetics Consortium. Using ensemble-based supervised learning, the Evolutionary Action-Machine Learning framework ranked each gene's ability to classify case and control samples and identified 79 significant associations. These were connected to known risk loci; enriched in cardiovascular processes like lipid metabolism, blood clotting, and inflammation; and enriched for cardiovascular phenotypes in knockout mouse models. Among them, INPP5F and MST1R are examples of potentially novel coronary artery disease risk genes that modulate immune signaling in response to cardiac stress. Conclusions We concluded that machine learning on the functional impact of coding variants, based on a massive amount of evolutionary information, has the power to suggest novel coronary artery disease risk genes for mechanistic and therapeutic discoveries in cardiovascular biology, and should also apply in other complex polygenic diseases.

A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets

Identification of gene-by-environment interactions (GxE) is crucial to understand the interplay of environmental effects on complex traits. However, current methods evaluating GxE on biobank-scale datasets have limitations. We introduce MonsterLM, a multiple linear regression method that does not rely on model specification and provides unbiased estimates of variance explained by GxE. We demonstrate robustness of MonsterLM through comprehensive genome-wide simulations using real genetic data from 325,989 individuals. We estimate GxE using waist-to-hip-ratio, smoking, and exercise as the environmental variables on 13 outcomes (N = 297,529-325,989) in the UK Biobank. GxE variance is significant for 8 environment-outcome pairs, ranging from 0.009 - 0.071. The majority of GxE variance involves SNPs without strong marginal or interaction associations. We observe modest improvements in polygenic score prediction when incorporating GxE. Our results imply a significant contribution of GxE to complex trait variance and we show MonsterLM to be well-purposed to handle this with biobank-scale data.

Advances and Challenges for GWAS Analysis in Cardiac Diseases: A Focus on Coronary Artery Disease (CAD)

The achievement of genome-wide association studies (GWAS) has rapidly progressed our understanding of the etiology of coronary artery disease (CAD). It unlocks new strategies to strengthen the stalling of CAD drug development. In this review, we highlighted the recent drawbacks, mainly pointing out those involved in identifying causal genes and interpreting the connections between disease pathology and risk variants. We also benchmark the novel insights into the biological mechanism behind the disease primarily based on outcomes of GWAS. Furthermore, we also shed light on the successful discovery of novel treatment targets by introducing various layers of "omics" data and applying systems genetics strategies. Lastly, we discuss in-depth the significance of precision medicine that is helpful to improve through GWAS analysis in cardiovascular research.

Genome-wide search identified DNA methylation sites that regulate the metabolome

Background: Identifying DNA methylation sites that regulate the metabolome is important for several purposes. In this study, publicly available GWAS data were integrated to find methylation sites that impact metabolome through a discovery and replication scheme and by using Mendelian randomization. Results: The outcome of analyses revealed 107 methylation sites associated with 84 metabolites at the genome-wide significance level (p<5e^-8) at both the discovery and replication stages. A large percentage of the observed associations (85%) were with lipids, significantly higher than expected (p = 0.0003). A number of CpG (methylation) sites showed specificity e.g., cg20133200 within PFKP was associated with glucose only and cg10760299 within GATM impacted the level of creatinine; in contrast, there were sites associated with numerous metabolites e.g., cg20102877 on the 2p23.3 region was associated with 39 metabolites. Integrating transcriptome data enabled identifying genes (N = 82) mediating the impact of methylation sites on the metabolome and cardiometabolic traits. For example, PABPC4 mediated the impact of cg15123755-HDL on type-2 diabetes. KCNK7 mediated the impact of cg21033440-lipids on hypertension. POC5, ILRUN, FDFT1, and NEIL2 mediated the impact of CpG sites on obesity through metabolic pathways. Conclusion: This study provides a catalog of DNA methylation sites that regulate the metabolome for downstream applications.

Genetic Polymorphisms Associated with Prothrombin Time and Activated Partial Thromboplastin Time in Chinese Healthy Population

(1) Background: The purpose of this study was to evaluate the effect of gene polymorphisms on prothrombin time (PT) and activated partial thromboplastin time (APTT) in a healthy Chinese population. (2) Methods: A total of 403 healthy volunteers from a series of novel oral anticoagulants (NOACs) bioequivalence trials in China were included. Coagulation tests for PT and APTT were performed in the central lab at Peking University First Hospital. Whole-exome sequencing (WES) and genome-wide association analysis were performed. (3) Results: In the correlation analysis of PT, 105 SNPs from 84 genes reached the genome-wide significance threshold (p < 1 × 10−5). Zinc Finger Protein 594 (ZNF594) rs184838268 (p = 4.50 × 10−19) was most significantly related to PT, and Actinin Alpha 1 (ACTN1) was found to interact most with other candidate genes. Significant associations with previously reported candidate genes Aurora Kinase B (AURKB), Complement C5(C5), Clock Circadian Regulator (CLOCK), and Histone Deacetylase 9(HDAC9) were detected in our dataset (p < 1 × 10−5). PiggyBac Transposable Element Derived 2(PGBD2) rs75935520 (p = 4.49 × 10−6), Bromodomain Adjacent To Zinc Finger Domain 2A(BAZ2A) rs199970765 (p = 5.69 × 10−6) and Protogenin (PRTG) rs80064850 (p = 8.69 × 10−6) were significantly correlated with APTT (p < 1 × 10−5). The heritability values of PT and APTT were 0.83 and 0.64, respectively; (4) Conclusion: The PT and APTT of healthy populations are affected by genetic polymorphisms. ZNF594 and ACTN1 variants could be novel genetic markers of PT, while PRTG polymorphisms might be associated with APTT levels. The findings could be attributed to ethnic differences, and need further investigation.

Serum level of total histone 3, H3K4me3, and H3K27ac after non-emergent cardiac surgery suggests the persistence of smoldering inflammation at 3 months in an adult population

Background

Despite clinical relevance of immunological activation due to histone leakage into the serum following cardiac surgery, long-term data describing their longitudinal dynamic are lacking. Therefore, this study examines the serum levels of histone 3 (tH3) and its modifications (H3K4me3 and H3K27ac) alongside immune system activation during the acute and convalescence phases of cardiac surgery.

Methods

Blood samples from fifty-nine individuals were collected before non-emergent cardiac surgery (t_pre-op) and 24 h (t_24hr), seven days (t_7d), and three months (t_3m) post-procedure to examine serum levels of tH3, H3K4me3, and H3K27ac. Serum heat shock protein-60 (HSP-60) was a surrogate of the cellular damage marker. Serum C-reactive protein (CRP) and interleukin 6 (IL-6) assessed smoldering inflammation. TNFα and IL-6 production by whole blood in response to lipopolysaccharide (LPS) evaluated immunological activation. Electronic medical records provided demographic, peri-operative, and clinical information. Paired longitudinal analyses were employed with data expressed as mean and standard deviation (X ± SD) or median and interquartile range (Me[IQ25; 75%].

Results

Compared to pre-operative levels (tH3_Pre-op = 1.6[0.33;2.4]), post-operative serum tH3 significantly (p > 0.0001) increased after heart surgery (tH3_24hr = 2.2[0.3;28]), remained elevated at 7 days (tH3_7d = 2.4[0.37;5.3]), and at 3 months (tH3_3m = 2.0[0.31;2.9]). Serum H3K27ac was elevated at 24 h (H3K27ac_24hr = 0.66 ± 0.51; p = 0.025) and seven days (H3K27ac_7d = 0.94 ± 0.95; p = 0.032) as compared to baseline hours (H3K27ac_Pre-op = 0.55 ± 0.54). Serum H3K4me3 was significantly diminished at three months (H3K4me3_Pre-op = 0.94 ± 0.54 vs. H3K27ac_3m = 0.59 ± 0.89; p = 0.008). tH3 correlated significantly with the duration of anesthesia (r² = 0.38). In contrast, HSP-60 normalized seven days after surgery. Peri-operative intake of acetaminophen, but no acetylsalicylic acid (ASA), acid, ketorolac or steroids, resulted in the significant depression of serum H3K4me3 at 24 h (H3K4me3_acetom- = 1.26[0.71; 3.21] vs H3K4me3_acetom+ = 0.54[0.07;1.01]; W[50] = 2.26; p = 0.021). CRP, but not IL-6, remained elevated at 3 months compared to pre-surgical levels and correlated with tH3_24hrs (r² = 0.43), tH3_7d (r² = 0.71; p < 0.05), H3K4me3_7d (r² = 0.53), and H3K27ac_7d (r² = 0.49). Production of TNFα by whole blood in response to LPS was associated with serum tH3_24hrs (r² = 0.67). Diminished H3K4me3_24hrs, H3K27ac_24hrs, and H3K27ac_3m, accompanied the emergence of liver failure.

Conclusions

We demonstrated a prolonged elevation in serum histone 3 three months after cardiac surgery. Furthermore, histone 3 modifications had a discrete time evolution indicating differential immune activation.

Targeting skeletal muscle mitochondrial health in obesity

Metabolic demands of skeletal muscle are substantial and are characterized normally as highly flexible and with a large dynamic range. Skeletal muscle composition (e.g., fiber type and mitochondrial content) and metabolism (e.g., capacity to switch between fatty acid and glucose substrates) are altered in obesity, with some changes proceeding and some following the development of the disease. Nonetheless, there are marked interindividual differences in skeletal muscle composition and metabolism in obesity, some of which have been associated with obesity risk and weight loss capacity. In this review, we discuss related molecular mechanisms and how current and novel treatment strategies may enhance weight loss capacity, particularly in diet-resistant obesity.

C Deletion at the re74650330 Locus of the SLC39A8 Gene (rs74650330) Increases the Risk of Coronary Artery Disease in Individuals with Low-Density Lipoprotein Cholesterol Levels

Background: Genetic variants of the SLC39A8 gene are associated with several cardiovascular disease risk factors, including body mass index, systolic blood pressure (SBP), diastolic blood pressure (DBP), N-terminal pro-B-type natriuretic peptide (NT-proBNP) and high-density lipoprotein cholesterol (HDL-C) levels. The present study aimed to investigate the association between the SLC39A8 SNPs rs13107325 and rs74650330 and CAD in the Han population in Jiangsu (China). Methods: Genotyping of these SNPs was performed in 258 patients with CAD and 170 healthy controls using the base-quenched probe technique. The association between the alleles of the rs74650330 locus and blood lipid and glucose profiles was investigated. Receiver operating characteristic (ROC) curve analysis was used to quantify the optimal thresholds for lipid and FBG levels and the risk factors for CAD were estimated by logistic regression analysis. Results: The rs13107325 polymorphism was not found in the 428 Chinese individuals enrolled in the current study. For rs74650330, individuals harboring the C allele had significantly higher HDL levels than those without this allele in the control group (p = 0.039), while the opposite was true for low-density lipoprotein cholesterol (LDL-C) levels (p = 0.046). Further analysis indicated that when LDL-C levels were lower than 2.365 mmol/L, subjects with C/del and del/del had a 7.293-fold increased risk of CAD compared with that of controls without the mutation (odds ratio: 7.293; 95% confidence interval: 0.953-55.79). Conclusions: The susceptibility of SLC39A8 polymorphisms to CAD were studied and revealed a possible role for the deletion variant of rs74650330 in increasing the risk of CAD among the Chinese Han population.

Joint association between education and polygenic risk score for incident coronary heart disease events: a longitudinal population-based study of 26 203 men and women

BACKGROUND

Genetic vulnerability to coronary heart disease (CHD) is well established, but little is known whether these effects are mediated or modified by equally well-established social determinants of CHD. We estimate the joint associations of the polygenetic risk score (PRS) for CHD and education on CHD events.

METHODS

The data are from the 1992, 1997, 2002, 2007 and 2012 surveys of the population-based FINRISK Study including measures of social, behavioural and metabolic factors and genome-wide genotypes (N=26 203). Follow-up of fatal and non-fatal incident CHD events (N=2063) was based on nationwide registers.

RESULTS

Allowing for age, sex, study year, region of residence, study batch and principal components, those in the highest quartile of PRS for CHD had strongly increased risk of CHD events compared with the lowest quartile (HR=2.26; 95% CI: 1.97 to 2.59); associations were also observed for low education (HR=1.58; 95% CI: 1.32 to 1.89). These effects were largely independent of each other. Adjustment for baseline smoking, alcohol use, body mass index, igh-density lipoprotein (HDL) and total cholesterol, blood pressure and diabetes attenuated the PRS associations by 10% and the education associations by 50%. We do not find strong evidence of interactions between PRS and education.

CONCLUSIONS

PRS and education predict CHD events, and these associations are independent of each other. Both can improve CHD prediction beyond behavioural risks. The results imply that observational studies that do not have information on genetic risk factors for CHD do not provide confounded estimates for the association between education and CHD.

ABCA1, TCF7, NFATC1, PRKCZ, and PDGFA DNA methylation as potential epigenetic-sensitive targets in acute coronary syndrome via network analysis

Acute coronary syndrome (ACS) is the most severe clinical manifestation of coronary heart disease.We performed an epigenome-wide analysis of circulating CD4⁺ and CD8⁺ T cells isolated from ACS patients and healthy subjects (HS), enrolled in the DIANA clinical trial, by reduced-representation bisulphite sequencing (RRBS). In CD4⁺ T cells, we identified 61 differentially methylated regions (DMRs) associated with 57 annotated genes (53% hyper- and 47% hypo-methylated) by comparing ACS patients vs HS. In CD8⁺ T cells, we identified 613 DMRs associated with 569 annotated genes (28% hyper- and 72% hypo-methylated) in ACS patients as compared to HS. In CD4⁺ vs CD8⁺ T cells of ACS patients we identified 175 statistically significant DMRs associated with 157 annotated genes (41% hyper- and 59% hypo-methylated). From pathway analyses, we selected six differentially methylated hub genes (NFATC1, TCF7, PDGFA, PRKCB, PRKCZ, ABCA1) and assessed their expression levels by q-RT-PCR. We found an up-regulation of selected genes in ACS patients vs HS (P < 0.001). ABCA1, TCF7, PDGFA, and PRKCZ gene expression was positively associated with CK-MB serum concentrations (r = 0.75, P = 0.03; r = 0.760, P = 0.029; r = 0.72, P = 0.044; r = 0.74, P = 0.035, respectively).This pilot study is the first single-base resolution map of DNA methylome by RRBS in CD4⁺ and CD8⁺ T cells and provides specific methylation signatures to clarify the role of aberrant methylation in ACS pathogenesis, thus supporting future research for novel epigenetic-sensitive biomarkers in the prevention and early diagnosis of this pathology.

Precision Medicine Approaches to Vascular Disease: JACC Focus Seminar 2/5

In this second of a 5-part Focus Seminar series, we focus on precision medicine in the context of vascular disease. The most common vascular disease worldwide is atherosclerosis, which is the primary cause of coronary artery disease, peripheral vascular disease, and a large proportion of strokes and other disorders. Atherosclerosis is a complex genetic disease that likely involves many hundreds to thousands of single nucleotide polymorphisms, each with a relatively modest effect for causing disease. Conversely, although less prevalent, there are many vascular disorders that typically involve only a single genetic change, but these changes can often have a profound effect that is sufficient to cause disease. These are termed "Mendelian vascular diseases," which include Marfan and Loeys-Dietz syndromes. Given the very different genetic basis of atherosclerosis versus Mendelian vascular diseases, this article was divided into 2 parts to cover the most promising precision medicine approaches for these disease types.

Convergence of biomarkers and risk factor trait loci of coronary artery disease at 3p21.31 and HLA region

Here we seek to identify molecular biomarkers that mediate the effect of risk factors on coronary artery disease (CAD). We perform a SNP-based multiomics data analysis to find biomarkers (probes) causally associated with the risk of CAD within known genomic loci for its risk factors. We identify 78 biomarkers, the majority (64%) of which are methylation probes. We detect the convergence of several CNS and lifestyle trait loci and their biomarkers at the 3p21.31 and human leukocyte antigen (HLA) regions. The 3p21.31 locus was the most populated region in the convergence of biomarkers and risk factors. In this region, we noted as the BSN gene becomes methylated the level of stomatin (STOM) in blood increases and this contributes to higher risk of CAD. In the HLA locus, we identify several methylation biomarkers associated with various CAD risk factors. SNPs in the CFB gene display a trans-regulatory impact on the GRIA4 protein level. A methylation site upstream of the APOE gene is associated with a higher protein level of S100A13 which in turn leads to higher LDL-C and greater CAD risk. We find UHRF1BP1 and ILRUN mediate the effect of obesity on CAD whereas methylation sites within NOS3 and CKM mediate the effect of their associated-risk factors on CAD. This study provides further insight into the biology of CAD and identifies a list of biomarkers that mediate the impact of risk factors on CAD. A SNP-based initiative can unite data from various fields of omics into a single network of knowledge.

Multiomics Screening Identifies Molecular Biomarkers Causally Associated With the Risk of Coronary Artery Disease

BACKGROUND

In this study, we aimed to investigate functional mechanisms underlying coronary artery disease (CAD) loci and find molecular biomarkers for CAD.

METHODS

We devised a multiomics data analysis approach based on Mendelian randomization and utilized it to search for molecular biomarkers causally associated with the risk of CAD within genomic regions known to be associated with CAD.

RESULTS

Through our CAD-centered multiomics data analysis approach, we identified 33 molecular biomarkers (probes) that were causally associated with the risk of CAD. The majority of these (N=19) were methylation probes; moreover, methylation was often behind the causal effect of expression/protein probes. We identified a number of novel loci that have a causal impact on CAD including C5orf38, SF3A3, DHX36, and MRPL33. Furthermore, by integrating the risk factors of CAD in our analysis, we were able to investigate the clinical pathways whereby several of our probes exert their effect. We found that the SELE protein level in the blood is under the trans-regulatory impact of methylation sites within the ABO gene and that SELE exerts its effect on CAD through immune, glycemic, and lipid metabolism, making it a candidate of interest for therapeutic interventions. We found the methylation site, cg05126514 within the BSN gene exert its effect on CAD through central nervous system-lifestyle risk factors. Finally, genes with a transcriptional regulatory role (SF3A3, ILF3, and N4BP2L2) exert their effect on CAD through height.

CONCLUSIONS

We demonstrate that multiomics data analysis is a powerful approach to unravel the functional mechanisms underlying CAD loci and to identify novel molecular biomarkers. Our results indicate epigenetic modifications are important in the pathogenesis of CAD and identifying and targeting these sites is of potential therapeutic interest to address the detrimental effects of both environmental and genetic factors.

SGCG rs679482 Associates With Weight Loss Success in Response to an Intensively Supervised Outpatient Program

Weight loss in response to energy restriction is highly variable, and identification of genetic contributors can provide insights into underlying biology. Leveraging 1000 Genomes imputed genotypes, we carried out genome-wide association study (GWAS) analysis in 551 unrelated obese subjects of European ancestry who participated in an intensively supervised weight loss program with replication of promising signals in an independent sample of 1,331 obese subjects who completed the program at a later date. By single nucleotide polymorphism-based and sib-pair analysis, we show that that weight loss is a heritable trait, with estimated heritability (h ² = 0.49) within the range reported for obesity. We find rs679482, intronic to SGCG (sarcoglycan γ), highly expressed in skeletal muscle, to concordantly associate with weight loss in discovery and replication samples reaching GWAS significance in the combined meta-analysis (β = -0.35, P = 1.7 × 10^-12). Located in a region of open chromatin, rs679482 is predicted to bind DMRT2, and allele-specific transcription factor binding analysis indicates preferential binding of DMRT2 to rs679482-A. Concordantly, rs679482-A impairs native repressor activity and increases basal and DMRT2-mediated enhancer activity. These findings confirm that weight loss is a heritable trait and provide evidence by which a novel variant in SGCG, rs679482, leads to impaired diet response.

Network Medicine: A Clinical Approach for Precision Medicine and Personalized Therapy in Coronary Heart Disease

Early identification of coronary atherosclerotic pathogenic mechanisms is useful for predicting the risk of coronary heart disease (CHD) and future cardiac events. Epigenome changes may clarify a significant fraction of this "missing hereditability", thus offering novel potential biomarkers for prevention and care of CHD. The rapidly growing disciplines of systems biology and network science are now poised to meet the fields of precision medicine and personalized therapy. Network medicine integrates standard clinical recording and non-invasive, advanced cardiac imaging tools with epigenetics into deep learning for in-depth CHD molecular phenotyping. This approach could potentially explore developing novel drugs from natural compounds (i.e. polyphenols, folic acid) and repurposing current drugs, such as statins and metformin. Several clinical trials have exploited epigenetic tags and epigenetic sensitive drugs both in primary and secondary prevention. Due to their stability in plasma and easiness of detection, many ongoing clinical trials are focused on the evaluation of circulating miRNAs (e.g. miR-8059 and miR-320a) in blood, in association with imaging parameters such as coronary calcifications and stenosis degree detected by coronary computed tomography angiography (CCTA), or functional parameters provided by FFR/CT and PET/CT. Although epigenetic modifications have also been prioritized through network based approaches, the whole set of molecular interactions (interactome) in CHD is still under investigation for primary prevention strategies.

Predictive Accuracy of a Polygenic Risk Score-Enhanced Prediction Model vs a Clinical Risk Score for Coronary Artery Disease

Importance

The incremental value of polygenic risk scores in addition to well-established risk prediction models for coronary artery disease (CAD) is uncertain.

Objective

To examine whether a polygenic risk score for CAD improves risk prediction beyond pooled cohort equations.

Design, Setting, and Participants

Observational study of UK Biobank participants enrolled from 2006 to 2010. A case-control sample of 15 947 prevalent CAD cases and equal number of age and sex frequency-matched controls was used to optimize the predictive performance of a polygenic risk score for CAD based on summary statistics from published genome-wide association studies. A separate cohort of 352 660 individuals (with follow-up to 2017) was used to evaluate the predictive accuracy of the polygenic risk score, pooled cohort equations, and both combined for incident CAD.

Exposures

Polygenic risk score for CAD, pooled cohort equations, and both combined.

Main Outcomes and Measures

CAD (myocardial infarction and its related sequelae). Discrimination, calibration, and reclassification using a risk threshold of 7.5% were assessed.

Results

In the cohort of 352 660 participants (mean age, 55.9 years; 205 297 women [58.2%]) used to evaluate the predictive accuracy of the examined models, there were 6272 incident CAD events over a median of 8 years of follow-up. CAD discrimination for polygenic risk score, pooled cohort equations, and both combined resulted in C statistics of 0.61 (95% CI, 0.60 to 0.62), 0.76 (95% CI, 0.75 to 0.77), and 0.78 (95% CI, 0.77 to 0.79), respectively. The change in C statistic between the latter 2 models was 0.02 (95% CI, 0.01 to 0.03). Calibration of the models showed overestimation of risk by pooled cohort equations, which was corrected after recalibration. Using a risk threshold of 7.5%, addition of the polygenic risk score to pooled cohort equations resulted in a net reclassification improvement of 4.4% (95% CI, 3.5% to 5.3%) for cases and -0.4% (95% CI, -0.5% to -0.4%) for noncases (overall net reclassification improvement, 4.0% [95% CI, 3.1% to 4.9%]).

Conclusions and Relevance

The addition of a polygenic risk score for CAD to pooled cohort equations was associated with a statistically significant, yet modest, improvement in the predictive accuracy for incident CAD and improved risk stratification for only a small proportion of individuals. The use of genetic information over the pooled cohort equations model warrants further investigation before clinical implementation.

Phenome-wide screening for traits causally associated with the risk of coronary artery disease

Using two independent approaches, Mendelian randomization and Polygenic risk score in a sample of 6194 CAD cases and 4287 controls of European ancestry, we did a comprehensive phenome-wide search (PheWAS) for traits that causally associated with the risk of CAD. We found 46 risk factors that represented diverse categories including cardiovascular, CNS (central nervous system), diabetes, lipids, immune, anthropometry, and life style features; moreover, we noted numerous evidences of genetic correlations and causal associations between risk factors from different categories. Among the identified risk factors, CAD showed highest genetic relatedness with thrombotic conditions. The most represented category was life style features (29%) with evidence of strong genetic overlap with CNS traits. Genetic variants associated with higher cognition were associated with life style characteristics and cardiometabolic features that lower the risk of CAD. Conditional analysis indicated this trend is in part attributed to higher age of first sexual intercourse (AFS) in those with higher cognition. Lower AFS was concordantly associated with higher risk of CAD in males, females, and the combined sample; furthermore, lower AFS was causally associated with several CAD-risk factors including, higher fasting insulin, fasting glucose, LDL, immature reticulocyte fraction, HbA1c levels, as well as, higher risk of T2D and pulmonary embolism but lower levels of HDL. These results indicate CAD is the outcome of several phenotypically distinct but genetically interrelated sources; moreover, we identified lower AFS as an independent causal risk factor of CAD and revealed its role in mediating the effect of other risk factors.

2018 George Lyman Duff Memorial Lecture: Genetics and Genomics of Coronary Artery Disease: A Decade of Progress

Recent studies have led to a broader understanding of the genetic architecture of coronary artery disease and demonstrate that it largely derives from the cumulative effect of multiple common risk alleles individually of small effect size rather than rare variants with large effects on coronary artery disease risk. The tools applied include genome-wide association studies encompassing over 200 000 individuals complemented by bioinformatic approaches including imputation from whole-genome data sets, expression quantitative trait loci analyses, and interrogation of ENCODE (Encyclopedia of DNA Elements), Roadmap Epigenetic Project, and other data sets. Over 160 genome-wide significant loci associated with coronary artery disease risk have been identified using the genome-wide association studies approach, 90% of which are situated in intergenic regions. Here, I will describe, in part, our research over the last decade performed in collaboration with a series of bright trainees and an extensive number of groups and individuals around the world as it applies to our understanding of the genetic basis of this complex disease. These studies include computational approaches to better understand missing heritability and identify causal pathways, experimental approaches, and progress in understanding at the molecular level the function of the multiple risk loci identified and potential applications of these genomic data in clinical medicine and drug discovery.

A decade of genome-wide association studies for coronary artery disease: the challenges ahead

In this review, we summarize current knowledge on the genetics of coronary artery disease, based on 10 years of genome-wide association studies. The discoveries began with individual studies using 200K single nucleotide polymorphism arrays and progressed to large-scale collaborative efforts, involving more than a 100 000 people and up to 40 Mio genetic variants. We discuss the challenges ahead, including those involved in identifying causal genes and deciphering the links between risk variants and disease pathology. We also describe novel insights into disease biology based on the findings of genome-wide association studies. Moreover, we discuss the potential for discovery of novel treatment targets through the integration of different layers of 'omics' data and the application of systems genetics approaches. Finally, we provide a brief outlook on the potential for precision medicine to be enhanced by genome-wide association study findings in the cardiovascular field.

Partitioning the Pleiotropy Between Coronary Artery Disease and Body Mass Index Reveals the Importance of Low Frequency Variants and Central Nervous System-Specific Functional Elements

BACKGROUND

The objective of this study is to investigate the extent and nature of pleiotropy between coronary artery disease (CAD) and body mass index (BMI).

METHODS

We examined the contribution of genome-wide single-nucleotide polymorphisms (minor allele frequency ≥0.01) to co-occurrence of CAD and BMI in a sample of genetically unrelated 8041 subjects (genetic resemblance ≤0.025) of European ancestry using mixed-linear-models. We further partitioned the estimated pleiotropy according to biological features to gain insight into the nature of pleiotropy between CAD and BMI.

RESULTS

We found significant (P<0.0001) positive genetic correlation between CAD and BMI (r_g =0.60). The estimated pleiotropy explained 68% of phenotypic correlation, and it was not proportionally distributed across the chromosomes; notably, chromosome 10 contributed more; whereas, chromosomes 11 and 14 contributed less to pleiotropy than expected given their chromosomal length. We noted that a large proportion (63%; P=0.002) of the pleiotropy is attributed to single-nucleotide polymorphisms with low allele frequency (minor allele frequency <0.05). Of note, pleiotropy was enriched among central nervous system genes and genes of metabolic pathways. Further analyses revealed that these effects are more pronounced in the proopiomelanocortin pathway and genes involved in carbohydrate metabolism. After genome-wide association study meta-analysis, only single-nucleotide polymorphisms downstream of the MC4R gene were found concordantly associated with (P<5×10^-8) BMI and CAD with lead single-nucleotide polymorphism being rs663129 (combined P=2.7×10^-65). Finally, partitioning the pleiotropy according to functional elements pointed to the importance of superenhancers and notably brain-specific superenhancers.

CONCLUSIONS

Genome-wide pleiotropy substantially contributes to co-occurrence of CAD and obesity, and it is highly enriched among low frequency variants and central nervous system-specific functional elements.

Regulation of MFGE8 by the intergenic coronary artery disease locus on 15q26.1

BACKGROUND AND AIMS

A recently identified locus for coronary artery disease (CAD) tagged by rs8042271 is in a region of tight linkage disequilibrium (LD) between 2 genes (MFGE8, ABHD2) previously linked to atherosclerosis. Here we have explored the regulatory framework of this region to identify its functional relationship to CAD.

METHODS

The CAD Associated Region between MFGE8 and ABHD2 (CARMA) was investigated by bioinformatic approaches and transcriptional reporter assays to prioritize target genes and identify putative causal variants. Findings were integrated with publicly available gene expression datasets. MFGE8 silencing was performed in cell models relevant to CAD.

RESULTS

The regulatory potential of CARMA is disseminated sparsely over the entire region. CARMA contains multiple eQTL that regulate MFGE8 in coronary artery and coronary artery smooth muscle cell (CoSMC). SNPs that predict the expression of MFGE8 in artery are concordantly associated with higher risk of CAD (pval = 0.0014). Targeting CARMA by CRISPR/Cas9 in a cellular model increased MFGE8 expression. MFGE8 silencing was found to reduce CoSMC and monocyte (THP-1) but not endothelial cell proliferation.

CONCLUSIONS

These findings support a mechanistic link between a GWAS identified CAD risk locus and atherosclerosis. The intergenic locus CARMA regulates MFGE8 in a haplotype dependent manner. Individuals genetically susceptible to increased MFGE8 expression exhibit greater CAD risk. Suppressing MFGE8 expression reduced SMC and THP-1 proliferation. These data support an atherogenic contribution of CARMA/MFGE8 that may be linked to cell proliferation and/or improved survival of CAD relevant cell types.

Genome-wide identification of circulating-miRNA expression quantitative trait loci reveals the role of several miRNAs in the regulation of cardiometabolic phenotypes

Aims

To identify genetic variants that have a regulatory impact on circulating microRNAs (miRNAs) and to connect genetic risk to blood traits/biomarkers through the circulating miRNAs.

Methods and results

Leveraging miRNA-Seq data and the 1000 Genomes imputed genotypes, we carried out genome-wide association analysis for SNPs that regulate the expression of circulating miRNAs in a sample of 710 unrelated subjects of European ancestry. Wherever possible, we used data from the Framingham and the Geuvadis studies to replicate our findings. We found at least one genome-wide significant (P < 5e−8) miRNA-eQTL (mirQTL) for 143 circulating miRNAs. Overall each mirQTL explained a small portion (<1%) of variation in miRNA levels; however, we identified a few mirQTLs that explained 4% to 20% of variation in miRNA levels in plasma. Unlike trans-mirQTLs (P = 0.7), cis-mirQTLs tend to be also associated with their counterpart mature miRNAs (P < 0.0001), this suggests trans-mirQTLs exert their effect through processes that affect the stability of mature miRNAs; whereas, cis-mirQTLs mainly regulate the expression of primary-miRNAs. Next, we used the identified mirQTLs to investigate the links between circulating miRNAs with blood traits/biomarkers through Mendelian randomization analysis. We found miR-1908-5p plays an important role in regulating low-density lipoprotein (LDL), total cholesterol (TC), fasting glucose, HbA1c, and several lipid-metabolites in blood, whereas, miR-10b-5p mediates the trans-regulatory effect of the ABO locus on several blood proteins, coronary artery disease, and TC. Moreover, we demonstrated that a higher plasma level of miR-199a is causally associated with lower levels of LDL and TC. Finally, we found miR-143-3p and miR-145-5p are functionally related and mediate the effect of ZFPM2 on a number of its protein targets in blood including VEGFA, SERPINE1, and PDGFs.

Conclusions

This study identifies SNPs that have a regulatory impact on circulating miRNAs, and underlines the role of several circulating miRNAs in mediating the effect of a number of GWAS loci on cardiometabolic phenotypes.

Stress and Inflammation in Coronary Artery Disease: A Review Psychoneuroendocrineimmunology-Based

Recent findings have deeply changed the current view of coronary heart disease, going beyond the simplistic model of atherosclerosis as a passive process involving cholesterol build-up in the subintimal space of the arteries until their final occlusion and/or thrombosis and instead focusing on the key roles of inflammation and the immune system in plaque formation and destabilization. Chronic inflammation is a typical hallmark of cardiac disease, worsening outcomes irrespective of serum cholesterol levels. Low-grade chronic inflammation correlates with higher incidence of several non-cardiac diseases, including depression, and chronic depression is now listed among the most important cardiovascular risk factors for poor prognosis among patients with myocardial infarction. In this review, we include recent evidence describing the immune and endocrine properties of the heart and their critical roles in acute ischaemic damage and in post-infarct myocardial remodeling. The importance of the central and autonomic regulation of cardiac functions, namely, the neuro-cardiac axis, is extensively explained, highlighting the roles of acute and chronic stress, circadian rhythms, emotions and the social environment in triggering acute cardiac events and worsening heart function and metabolism in chronic cardiovascular diseases. We have also included specific sections related to stress-induced myocardial ischaemia measurements and stress cardiomyopathy. The complex network of reciprocal interconnections between the heart and the main biological systems we have presented in this paper provides a new vision of cardiovascular science based on psychoneuroendocrineimmunology.

Diabetes, Hypertension, and Cardiovascular Disease: Clinical Insights and Vascular Mechanisms

Hypertension and type 2 diabetes are common comorbidities. Hypertension is twice as frequent in patients with diabetes compared with those who do not have diabetes. Moreover, patients with hypertension often exhibit insulin resistance and are at greater risk of diabetes developing than are normotensive individuals. The major cause of morbidity and mortality in diabetes is cardiovascular disease, which is exacerbated by hypertension. Accordingly, diabetes and hypertension are closely interlinked because of similar risk factors, such as endothelial dysfunction, vascular inflammation, arterial remodelling, atherosclerosis, dyslipidemia, and obesity. There is also substantial overlap in the cardiovascular complications of diabetes and hypertension related primarily to microvascular and macrovascular disease. Common mechanisms, such as upregulation of the renin-angiotensin-aldosterone system, oxidative stress, inflammation, and activation of the immune system likely contribute to the close relationship between diabetes and hypertension. In this article we discuss diabetes and hypertension as comorbidities and discuss the pathophysiological features of vascular complications associated with these conditions. We also highlight some vascular mechanisms that predispose to both conditions, focusing on advanced glycation end products, oxidative stress, inflammation, the immune system, and microRNAs. Finally, we provide some insights into current therapies targeting diabetes and cardiovascular complications and introduce some new agents that may have vasoprotective therapeutic potential in diabetes.

The performance of a new local false discovery rate method on tests of association between coronary artery disease (CAD) and genome-wide genetic variants

The maximum entropy (ME) method is a recently-developed approach for estimating local false discovery rates (LFDR) that incorporates external information allowing assignment of a subset of tests to a category with a different prior probability of following the null hypothesis. Using this ME method, we have reanalyzed the findings from a recent large genome-wide association study of coronary artery disease (CAD), incorporating biologic annotations. Our revised LFDR estimates show many large reductions in LFDR, particularly among the genetic variants belonging to annotation categories that were known to be of particular interest for CAD. However, among SNPs with rare minor allele frequencies, the reductions in LFDR were modest in size.