ProteoMutaMetrics: machine learning approaches for solute carrier family 6 mutation pathogenicity prediction

The solute carrier transporter family 6 (SLC6) is of key interest for their critical role in the transport of small amino acids or amino acid-like molecules. Their dysfunction is strongly associated with human diseases such as including schizophrenia, depression, and Parkinson's disease. Linking single point mutations to disease may support insights into the structure-function relationship of these transporters. This work aimed to develop a computational model for predicting the potential pathogenic effect of single point mutations in the SLC6 family. Missense mutation data was retrieved from UniProt, LitVar, and ClinVar, covering multiple protein-coding transcripts. As encoding approach, amino acid descriptors were used to calculate the average sequence properties for both original and mutated sequences. In addition to the full-sequence calculation, the sequences were cut into twelve domains. The domains are defined according to the transmembrane domains of the SLC6 transporters to analyse the regions' contributions to the pathogenicity prediction. Subsequently, several classification models, namely Support Vector Machine (SVM), Logistic Regression (LR), Random Forest (RF), and Extreme Gradient Boosting (XGBoost) with the hyperparameters optimized through grid search were built. For estimation of model performance, repeated stratified k-fold cross-validation was used. The accuracy values of the generated models are in the range of 0.72 to 0.80. Analysis of feature importance indicates that mutations in distinct regions of SLC6 transporters are associated with an increased risk for pathogenicity. When applying the model on an independent validation set, the performance in accuracy dropped to averagely 0.6 with high precision but low sensitivity scores.

The impact of circulating protein levels identified by affinity proteomics on short-term, overall breast cancer risk

OBJECTIVE

Current breast cancer risk prediction scores and algorithms can potentially be further improved by including molecular markers. To this end, we studied the association of circulating plasma proteins using Proximity Extension Assay (PEA) with incident breast cancer risk.

SUBJECTS

In this study, we included 1577 women participating in the prospective KARMA mammographic screening cohort.

RESULTS

In a targeted panel of 164 proteins, we found 8 candidates nominally significantly associated with short-term breast cancer risk (P < 0.05). Similarly, in an exploratory panel consisting of 2204 proteins, 115 were found nominally significantly associated (P < 0.05). However, none of the identified protein levels remained significant after adjustment for multiple testing. This lack of statistically significant findings was not due to limited power, but attributable to the small effect sizes observed even for nominally significant proteins. Similarly, adding plasma protein levels to established risk factors did not improve breast cancer risk prediction accuracy.

CONCLUSIONS

Our results indicate that the levels of the studied plasma proteins captured by the PEA method are unlikely to offer additional benefits for risk prediction of short-term overall breast cancer risk but could provide interesting insights into the biological basis of breast cancer in the future.

Evaluation of circulating plasma proteins in breast cancer using Mendelian randomisation

Biomarkers for early detection of breast cancer may complement population screening approaches to enable earlier and more precise treatment. The blood proteome is an important source for biomarker discovery but so far, few proteins have been identified with breast cancer risk. Here, we measure 2929 unique proteins in plasma from 598 women selected from the Karolinska Mammography Project to explore the association between protein levels, clinical characteristics, and gene variants, and to identify proteins with a causal role in breast cancer. We present 812 cis-acting protein quantitative trait loci for 737 proteins which are used as instruments in Mendelian randomisation analyses of breast cancer risk. Of those, we present five proteins (CD160, DNPH1, LAYN, LRRC37A2 and TLR1) that show a potential causal role in breast cancer risk with confirmatory results in independent cohorts. Our study suggests that these proteins should be further explored as biomarkers and potential drug targets in breast cancer.

Identifying proteomic risk factors for overall, aggressive and early onset prostate cancer using Mendelian randomization and tumor spatial transcriptomics

Background

Understanding the role of circulating proteins in prostate cancer risk can reveal key biological pathways and identify novel targets for cancer prevention.

Methods

We investigated the association of 2,002 genetically predicted circulating protein levels with risk of prostate cancer overall, and of aggressive and early onset disease, using cis-pQTL Mendelian randomization (MR) and colocalization. Findings for proteins with support from both MR, after correction for multiple-testing, and colocalization were replicated using two independent cancer GWAS, one of European and one of African ancestry. Proteins with evidence of prostate-specific tissue expression were additionally investigated using spatial transcriptomic data in prostate tumor tissue to assess their role in tumor aggressiveness. Finally, we mapped risk proteins to drug and ongoing clinical trials targets.

Results

We identified 20 proteins genetically linked to prostate cancer risk (14 for overall [8 specific], 7 for aggressive [3 specific], and 8 for early onset disease [2 specific]), of which a majority were novel and replicated. Among these were proteins associated with aggressive disease, such as PPA2 [Odds Ratio (OR) per 1 SD increment = 2.13, 95% CI: 1.54-2.93], PYY [OR = 1.87, 95% CI: 1.43-2.44] and PRSS3 [OR = 0.80, 95% CI: 0.73-0.89], and those associated with early onset disease, including EHPB1 [OR = 2.89, 95% CI: 1.99-4.21], POGLUT3 [OR = 0.76, 95% CI: 0.67-0.86] and TPM3 [OR = 0.47, 95% CI: 0.34-0.64]. We confirm an inverse association of MSMB with prostate cancer overall [OR = 0.81, 95% CI: 0.80-0.82], and also find an inverse association with both aggressive [OR = 0.84, 95% CI: 0.82-0.86] and early onset disease [OR = 0.71, 95% CI: 0.68-0.74]. Using spatial transcriptomics data, we identified MSMB as the genome-wide top-most predictive gene to distinguish benign regions from high grade cancer regions that had five-fold lower MSMB expression. Additionally, ten proteins that were associated with prostate cancer risk mapped to existing therapeutic interventions.

Conclusion

Our findings emphasize the importance of proteomics for improving our understanding of prostate cancer etiology and of opportunities for novel therapeutic interventions. Additionally, we demonstrate the added benefit of in-depth functional analyses to triangulate the role of risk proteins in the clinical aggressiveness of prostate tumors. Using these integrated methods, we identify a subset of risk proteins associated with aggressive and early onset disease as priorities for investigation for the future prevention and treatment of prostate cancer.

Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets

Circulating proteins have important functions in inflammation and a broad range of diseases. To identify genetic influences on inflammation-related proteins, we conducted a genome-wide protein quantitative trait locus (pQTL) study of 91 plasma proteins measured using the Olink Target platform in 14,824 participants. We identified 180 pQTLs (59 cis, 121 trans). Integration of pQTL data with eQTL and disease genome-wide association studies provided insight into pathogenesis, implicating lymphotoxin-α in multiple sclerosis. Using Mendelian randomization (MR) to assess causality in disease etiology, we identified both shared and distinct effects of specific proteins across immune-mediated diseases, including directionally discordant effects of CD40 on risk of rheumatoid arthritis versus multiple sclerosis and inflammatory bowel disease. MR implicated CXCL5 in the etiology of ulcerative colitis (UC) and we show elevated gut CXCL5 transcript expression in patients with UC. These results identify targets of existing drugs and provide a powerful resource to facilitate future drug target prioritization.

An atlas of genetic scores to predict multi-omic traits

The use of omic modalities to dissect the molecular underpinnings of common diseases and traits is becoming increasingly common. But multi-omic traits can be genetically predicted, which enables highly cost-effective and powerful analyses for studies that do not have multi-omics1. Here we examine a large cohort (the INTERVAL study2; n = 50,000 participants) with extensive multi-omic data for plasma proteomics (SomaScan, n = 3,175; Olink, n = 4,822), plasma metabolomics (Metabolon HD4, n = 8,153), serum metabolomics (Nightingale, n = 37,359) and whole-blood Illumina RNA sequencing (n = 4,136), and use machine learning to train genetic scores for 17,227 molecular traits, including 10,521 that reach Bonferroni-adjusted significance. We evaluate the performance of genetic scores through external validation across cohorts of individuals of European, Asian and African American ancestries. In addition, we show the utility of these multi-omic genetic scores by quantifying the genetic control of biological pathways and by generating a synthetic multi-omic dataset of the UK Biobank3 to identify disease associations using a phenome-wide scan. We highlight a series of biological insights with regard to genetic mechanisms in metabolism and canonical pathway associations with disease; for example, JAK-STAT signalling and coronary atherosclerosis. Finally, we develop a portal ( https://www.omicspred.org/ ) to facilitate public access to all genetic scores and validation results, as well as to serve as a platform for future extensions and enhancements of multi-omic genetic scores.

Unraveling Neuro-Proteogenomic Landscape and Therapeutic Implications for Human Behaviors and Psychiatric Disorders

Understanding the genetic basis of neuro-related proteins is essential for dissecting the molecular basis of human behavioral traits and the disease etiology of neuropsychiatric disorders. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-related proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-related traits such as sleeping, smoking, feelings, alcohol intake, mental health, and psychiatric disorders. Integrating with established drug information, we validated 13 out of 13 matched combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets. This consortium effort provides a large-scale proteogenomic resource for biomedical research on human behaviors and other neuro-related phenotypes.

Genetic mechanisms of 184 neuro-related proteins in human plasma

Understanding the genetic basis of neuro-related proteins is essential for dissecting the disease etiology of neuropsychiatric disorders and other complex traits and diseases. Here, the SCALLOP Consortium conducted a genome-wide association meta-analysis of over 12,500 individuals for 184 neuro-reiated proteins in human plasma. The analysis identified 117 cis-regulatory protein quantitative trait loci (cis-pQTL) and 166 trans-pQTL. The mapped pQTL capture on average 50% of each protein's heritability. Mendelian randomization analyses revealed multiple proteins showing potential causal effects on neuro-reiated traits as well as complex diseases such as hypertension, high cholesterol, immune-related disorders, and psychiatric disorders. Integrating with established drug information, we validated 13 combinations of protein targets and diseases or side effects with available drugs, while suggesting hundreds of re-purposing and new therapeutic targets for diseases and comorbidities. This consortium effort provides a large-scale proteogenomic resource for biomedical research.

Fibroblast Growth Factor-23 and Risk of Cardiovascular Diseases: A Mendelian Randomization Study

BACKGROUND

Fibroblast growth factor-23 (FGF-23) is associated with a range of cardiovascular and noncardiovascular diseases in conventional epidemiological studies, but substantial residual confounding may exist. Mendelian randomization approaches can help control for such confounding.

METHODS

SCALLOP Consortium data of 19,195 participants were used to generate an FGF-23 genetic score. Data from 337,448 UK Biobank participants were used to estimate associations between higher genetically predicted FGF-23 concentration and the odds of any atherosclerotic cardiovascular disease (n=26,266 events), nonatherosclerotic cardiovascular disease (n=12,652), and noncardiovascular diseases previously linked to FGF-23. Measurements of carotid intima-media thickness and left ventricular mass were available in a subset. Associations with cardiovascular outcomes were also tested in three large case-control consortia: CARDIOGRAMplusC4D (coronary artery disease, n=181,249 cases), MEGASTROKE (stroke, n=34,217), and HERMES (heart failure, n=47,309).

RESULTS

We identified 34 independent variants for circulating FGF-23, which formed a validated genetic score. There were no associations between genetically predicted FGF-23 and any of the cardiovascular or noncardiovascular outcomes. In UK Biobank, the odds ratio (OR) for any atherosclerotic cardiovascular disease per 1-SD higher genetically predicted logFGF-23 was 1.03 (95% confidence interval [95% CI], 0.98 to 1.08), and for any nonatherosclerotic cardiovascular disease, it was 1.01 (95% CI, 0.94 to 1.09). The ORs in the case-control consortia were 1.00 (95% CI, 0.97 to 1.03) for coronary artery disease, 1.01 (95% CI, 0.95 to 1.07) for stroke, and 1.00 (95% CI, 0.95 to 1.05) for heart failure. In those with imaging, logFGF-23 was not associated with carotid or cardiac abnormalities.

CONCLUSIONS

Genetically predicted FGF-23 levels are not associated with atherosclerotic and nonatherosclerotic cardiovascular diseases, suggesting no important causal link.

PODCAST

This article contains a podcast at https://dts.podtrac.com/redirect.mp3/www.asn-online.org/media/podcast/CJASN/2023_01_10_CJN05080422.mp3.

The genetic regulation of protein expression in cerebrospinal fluid

Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P < 1.25 × 10^-10 , 117 cis-pQTLs and 59 trans-pQTLs). Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs. pQTLs for CSF and plasma proteins were overall correlated, but CSF-specific pQTLs were also observed. Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP-10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease. CSF levels of GRN, MMP-10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively. These findings point to pathways to be explored for novel therapies. The novel finding that ventricular volume confounded pQTLs has implications for design of future studies of the genetic regulation of the CSF proteome.

Genetic Landscape of the ACE2 Coronavirus Receptor

BACKGROUND

SARS-CoV-2, the causal agent of COVID-19, enters human cells using the ACE2 (angiotensin-converting enzyme 2) protein as a receptor. ACE2 is thus key to the infection and treatment of the coronavirus. ACE2 is highly expressed in the heart and respiratory and gastrointestinal tracts, playing important regulatory roles in the cardiovascular and other biological systems. However, the genetic basis of the ACE2 protein levels is not well understood.

METHODS

We have conducted the largest genome-wide association meta-analysis of plasma ACE2 levels in >28 000 individuals of the SCALLOP Consortium (Systematic and Combined Analysis of Olink Proteins). We summarize the cross-sectional epidemiological correlates of circulating ACE2. Using the summary statistics-based high-definition likelihood method, we estimate relevant genetic correlations with cardiometabolic phenotypes, COVID-19, and other human complex traits and diseases. We perform causal inference of soluble ACE2 on vascular disease outcomes and COVID-19 severity using mendelian randomization. We also perform in silico functional analysis by integrating with other types of omics data.

RESULTS

We identified 10 loci, including 8 novel, capturing 30% of the heritability of the protein. We detected that plasma ACE2 was genetically correlated with vascular diseases, severe COVID-19, and a wide range of human complex diseases and medications. An X-chromosome cis-protein quantitative trait loci-based mendelian randomization analysis suggested a causal effect of elevated ACE2 levels on COVID-19 severity (odds ratio, 1.63 [95% CI, 1.10-2.42]; P=0.01), hospitalization (odds ratio, 1.52 [95% CI, 1.05-2.21]; P=0.03), and infection (odds ratio, 1.60 [95% CI, 1.08-2.37]; P=0.02). Tissue- and cell type-specific transcriptomic and epigenomic analysis revealed that the ACE2 regulatory variants were enriched for DNA methylation sites in blood immune cells.

CONCLUSIONS

Human plasma ACE2 shares a genetic basis with cardiovascular disease, COVID-19, and other related diseases. The genetic architecture of the ACE2 protein is mapped, providing a useful resource for further biological and clinical studies on this coronavirus receptor.

Abstract 420: Proprotein Convertase Subtilisin/Kexin 6 Is Involved In Lipid Metabolism In Liver

Introduction: PCSK6 is a protease that activates cytokines and growth factors and strongly enriched in healthy human liver, however its function in this context has not been explored. We have previously shown that PCSK6 is induced in atherosclerotic plaques from patients with symptoms of stroke and important for regulating several cell types in this context. Here, we aimed to investigate the role of PCSK6 in lipid metabolism in liver, particularly in the context of atherosclerosis and non-alcoholic fatty liver disease (NAFLD).

Methods: We used publically available datasets and several atherosclerosis biobanks to investigate the expression of PCSK6 in healthy and diseased human tissues. In addition, we used full Pcsk6 -/- mice as well as liver specific conditional Pcsk6 -/- knockout mice compared to littermate controls, to investigate the effects of PCSK6 ablation on lipid metabolism.

Results: Genetic analyses of the PCSK6 locus identified a variant, rs7181043, that was significantly associated with PCSK6 mRNA expression in healthy human adipose tissue, liver and in atherosclerotic plaques. The same variant was associated specifically with plaque fat content and atherosclerotic patient’s plasma LDL levels. In addition, PCSK6 mRNA expression in plaques was positively correlated with total plasma cholesterol and LDL levels in atherosclerotic patients as well as lipid metabolism associated pathways within the carotid plaque. Microarray comparison of the livers from Pcsk6 -/- mice and controls showed that VLDL particle assembly was one of the upregulated processes. I n vivo studies showed that Pcsk6 -/- mice have higher plasma cholesterol and LPL levels at baseline compared to controls, and lower levels of LDLR in their liver. These findings were further confirmed in liver specific conditional knockouts. Preliminary results show that liver specific knockout mice develop increased liver steatosis and fibrosis on a modified western diet.

Conclusions: Our data suggests that PCSK6 is involved in cholesterol and metabolic control in liver. Breeding of liver specific Pcsk6 knockout mice on an ApoE -/- background is currently ongoing and will provide insight into the role of liver PCSK6 in atherosclerosis and NAFLD development.

Therapeutic Targets for Heart Failure Identified Using Proteomics and Mendelian Randomization

BACKGROUND

Heart failure (HF) is a highly prevalent disorder for which disease mechanisms are incompletely understood. The discovery of disease-associated proteins with causal genetic evidence provides an opportunity to identify new therapeutic targets.

METHODS

We investigated the observational and causal associations of 90 cardiovascular proteins, which were measured using affinity-based proteomic assays. First, we estimated the associations of 90 cardiovascular proteins with incident heart failure by means of a fixed-effect meta-analysis of 4 population-based studies, composed of a total of 3019 participants with 732 HF events. The causal effects of HF-associated proteins were then investigated by Mendelian randomization, using cis-protein quantitative loci genetic instruments identified from genomewide association studies in more than 30 000 individuals. To improve the precision of causal estimates, we implemented an Mendelian randomization model that accounted for linkage disequilibrium between instruments and tested the robustness of causal estimates through a multiverse sensitivity analysis that included up to 120 combinations of instrument selection parameters and Mendelian randomization models per protein. The druggability of candidate proteins was surveyed, and mechanism of action and potential on-target side effects were explored with cross-trait Mendelian randomization analysis.

RESULTS

Forty-four of ninety proteins were positively associated with risk of incident HF (P<6.0×10-4). Among these, 8 proteins had evidence of a causal association with HF that was robust to multiverse sensitivity analysis: higher CSF-1 (macrophage colony-stimulating factor 1), Gal-3 (galectin-3) and KIM-1 (kidney injury molecule 1) were positively associated with risk of HF, whereas higher ADM (adrenomedullin), CHI3L1 (chitinase-3-like protein 1), CTSL1 (cathepsin L1), FGF-23 (fibroblast growth factor 23), and MMP-12 (matrix metalloproteinase-12) were protective. Therapeutics targeting ADM and Gal-3 are currently under evaluation in clinical trials, and all the remaining proteins were considered druggable, except KIM-1.

CONCLUSIONS

We identified 44 circulating proteins that were associated with incident HF, of which 8 showed evidence of a causal relationship and 7 were druggable, including adrenomedullin, which represents a particularly promising drug target. Our approach demonstrates a tractable roadmap for the triangulation of population genomic and proteomic data for the prioritization of therapeutic targets for complex human diseases.

Circulating proteins reveal prior use of menopausal hormonal therapy and increased risk of breast cancer

Accessible risk predictors are crucial for improving the early detection and prognosis of breast cancer. Blood samples are widely available and contain proteins that provide important information about human health and disease, however, little is still known about the contribution of circulating proteins to breast cancer risk prediction. We profiled EDTA plasma samples collected before diagnosis from the Swedish KARMA breast cancer cohort to evaluate circulating proteins as molecular predictors. A data-driven analysis strategy was applied to the molecular phenotypes built on 700 circulating proteins to identify and annotate clusters of women. The unsupervised analysis of 183 future breast cancer cases and 366 age-matched controls revealed five stable clusters with distinct proteomic plasma profiles. Among these women, those in the most stable cluster (N = 19; mean Jaccard index: 0.70 ± 0.29) were significantly more likely to have used menopausal hormonal therapy (MHT), get a breast cancer diagnosis, and were older compared to the remaining clusters. The circulating proteins associated with this cluster (FDR < 0.001) represented physiological processes related to cell junctions (F11R, CLDN15, ITGAL), DNA repair (RBBP8), cell replication (TJP3), and included proteins found in female reproductive tissue (PTCH1, ZP4). Using a data-driven approach on plasma proteomics data revealed the potential long-lasting molecular effects of menopausal hormonal therapy (MHT) on the circulating proteome, even after women had ended their treatment. This provides valuable insights concerning proteomics efforts to identify molecular markers for breast cancer risk prediction.

Mapping the serum proteome to neurological diseases using whole genome sequencing

Despite the increasing global burden of neurological disorders, there is a lack of effective diagnostic and therapeutic biomarkers. Proteins are often dysregulated in disease and have a strong genetic component. Here, we carry out a protein quantitative trait locus analysis of 184 neurologically-relevant proteins, using whole genome sequencing data from two isolated population-based cohorts (N = 2893). In doing so, we elucidate the genetic landscape of the circulating proteome and its connection to neurological disorders. We detect 214 independently-associated variants for 107 proteins, the majority of which (76%) are cis-acting, including 114 variants that have not been previously identified. Using two-sample Mendelian randomisation, we identify causal associations between serum CD33 and Alzheimer's disease, GPNMB and Parkinson's disease, and MSR1 and schizophrenia, describing their clinical potential and highlighting drug repurposing opportunities.

The genomics of heart failure: design and rationale of the HERMES consortium

Aims

The HERMES (HEart failure Molecular Epidemiology for Therapeutic targetS) consortium aims to identify the genomic and molecular basis of heart failure.

Methods and results

The consortium currently includes 51 studies from 11 countries, including 68 157 heart failure cases and 949 888 controls, with data on heart failure events and prognosis. All studies collected biological samples and performed genome‐wide genotyping of common genetic variants. The enrolment of subjects into participating studies ranged from 1948 to the present day, and the median follow‐up following heart failure diagnosis ranged from 2 to 116 months. Forty‐nine of 51 individual studies enrolled participants of both sexes; in these studies, participants with heart failure were predominantly male (34–90%). The mean age at diagnosis or ascertainment across all studies ranged from 54 to 84 years. Based on the aggregate sample, we estimated 80% power to genetic variant associations with risk of heart failure with an odds ratio of ≥1.10 for common variants (allele frequency ≥ 0.05) and ≥1.20 for low‐frequency variants (allele frequency 0.01–0.05) at P < 5 × 10⁻⁸ under an additive genetic model.

Conclusions

HERMES is a global collaboration aiming to (i) identify the genetic determinants of heart failure; (ii) generate insights into the causal pathways leading to heart failure and enable genetic approaches to target prioritization; and (iii) develop genomic tools for disease stratification and risk prediction.

Inflammation-related plasma protein levels and association with adiposity measurements in young adults

Obesity-related inflammation is associated with cardiovascular, metabolic, and pulmonary diseases. The aim of this study was to demonstrate associations between adiposity measurements and levels of inflammation-related plasma proteins in a population of young adults. Subjects from a population-based birth cohort with a mean age of 22.5 years were included in the study population (n = 2074). Protein levels were analyzed using the Olink Proseek Multiplex Inflammation panel. Percentage body fat (%BF) and visceral fat rating (VFR) measurements were collected using Tanita MC 780 body composition monitor. Linear regression of standardized values was used to investigate associations. Potential effect modifications by sex and BMI category were assessed. Of 71 investigated proteins, 54 were significantly associated with all adiposity measurements [%BF, body mass index (BMI), VFR and waist circumference]. Among proteins associated with %BF, seven showed a larger or unique association in overweight/obese subjects and three showed a significant effect modification by sex. Fourteen proteins more strongly associated with VFR in females compared to males. Adipose-associated systemic inflammation was observed in this young adult population. Sex and adiposity localization influenced some of the associations. Our results highlight specific proteins as suitable biomarkers related to adiposity.

Plasma Protein Profile of Carotid Artery Atherosclerosis and Atherosclerotic Outcomes: Meta-Analyses and Mendelian Randomization Analyses

[Figure: see text].

Mendelian randomisation identifies alternative splicing of the FAS death receptor as a mediator of severe COVID-19

Severe COVID-19 is characterised by immunopathology and epithelial injury. Proteomic studies have identified circulating proteins that are biomarkers of severe COVID-19, but cannot distinguish correlation from causation. To address this, we performed Mendelian randomisation (MR) to identify proteins that mediate severe COVID-19. Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. We identified significant MR results for five proteins: FAS, TNFRSF10A, CCL2, EPHB4 and LGALS9. Further evaluation of these candidates using sensitivity analyses and colocalization testing provided strong evidence to implicate the apoptosis-associated cytokine receptor FAS as a causal mediator of severe COVID-19. This effect was specific to severe disease. Using RNA-seq data from 4,778 individuals, we demonstrate that the pQTL at the FAS locus results from genetically influenced alternate splicing causing skipping of exon 6. We show that the risk allele for very severe COVID-19 increases the proportion of transcripts lacking exon 6, and thereby increases soluble FAS. Soluble FAS acts as a decoy receptor for FAS-ligand, inhibiting apoptosis induced through membrane-bound FAS. In summary, we demonstrate a novel genetic mechanism that contributes to risk of severe of COVID-19, highlighting a pathway that may be a promising therapeutic target.

Genetic Variants Associated with Non-Alcoholic Fatty Liver Disease Do Not Associate with Measures of Sub-Clinical Atherosclerosis: Results from the IMPROVE Study

Non-alcoholic fatty liver disease (NAFLD) and atherosclerosis-related cardiovascular diseases (CVD) share common metabolic pathways. We explored the association between three NAFLD-associated single nucleotide polymorphisms (SNPs) rs738409, rs10401969, and rs1260326 with sub-clinical atherosclerosis estimated by the carotid intima-media thickness (c-IMT) and the inter-adventitia common carotid artery diameter (ICCAD) in patients free from clinically overt NAFLD and CVD. The study population is the IMPROVE, a multicenter European study (n = 3711). C-IMT measures and ICCAD were recorded using a standardized protocol. Linear regression with an additive genetic model was used to test for association of the three SNPs with c-IMT and ICCAD. In secondary analyses, the association of the three SNPs with c-IMT and ICCAD was tested after stratification by alanine aminotransferase levels (ALT). No associations were found between rs738409, rs1260326, rs10401969, and c-IMT or ICCAD. Rs738409-G and rs10401969-C were associated with ALT levels (p < 0.001). In patients with ALT levels above 28 U/L (highest quartile), we observed an association between rs10401969-C and c-IMT measures of c-IMT_max and c-IMT_mean-max (p = 0.018 and 0.021, respectively). In conclusion, NAFLD-associated SNPs do not associate with sub-clinical atherosclerosis measures. However, our results suggest a possible mediating function of impaired liver function on atherosclerosis development.

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

The plasma protein profile and cardiovascular risk differ between intima-media thickness of the common carotid artery and the bulb: A meta-analysis and a longitudinal evaluation

BACKGROUND AND AIMS

Genetic loci associated with CHD show different relationships with intima-media thickness in the common carotid artery (IMT-CCA) and in the bulb (IMT-bulb). We evaluated if IMT-CCA and IMT-bulb differ also with respect to circulating protein profiles and risk of incident atherosclerotic disease.

METHODS

In three Swedish cohorts (MDC, IMPROVE, PIVUS, total n > 7000), IMT-CCA and IMT-bulb were assessed by ultrasound at baseline, and 86 cardiovascular-related proteins were analyzed. In the PIVUS study only, IMT-CCA and IMT-bulb were investigated in relation to incident atherosclerotic disease over 10 years of follow-up.

RESULTS

In a meta-analysis of the analysis performed separately in the cohorts, three proteins, matrix metalloproteinase-12 (MMP-12), hepatocyte growth factor (HGF) and N-terminal pro-B-type natriuretic peptide (NT-proBNP), were associated with IMT-CCA when adjusted for traditional cardiovascular risk factors. Five proteins were associated with IMT-bulb (MMP-12, growth/differentiation factor 15 (GDF-15), osteoprotegerin, growth hormone and renin). Following adjustment for cardiovascular risk factors, IMT-bulb was significantly more closely related to incident stroke or myocardial infarction (total number of cases, 111) than IMT-CCA in the PIVUS study (HR 1.51 for 1 SD, 95%CI 1.21-1.87, p < 0.001 vs HR 1.17, 95%CI 0.93-1.47, p = 0.16). MMP-12 levels were related to this combined end-point (HR 1.30, 95%CI 1.08-1.56, p = 0.0061).

CONCLUSIONS

Elevated levels of MMP-12 were associated with both IMT-CCA and IMT-bulb, but other proteins were significantly related to IMT in only one of these locations. The finding that IMT-bulb was more closely related to incident atherosclerotic disease than IMT-CCA emphasizes a difference between these measurements of IMT.

Identification of novel pheno-groups in heart failure with preserved ejection fraction using machine learning

Objective

Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome. We aimed to derive HFpEF phenotype-based groups ('phenogroups') based on clinical and echocardiogram data using machine learning, and to compare clinical characteristics, proteomics and outcomes across the phenogroups.

Methods

We applied model-based clustering to 32 echocardiogram and 11 clinical and laboratory variables collected in stable condition from 320 HFpEF outpatients in the Karolinska-Rennes cohort study (56% female, median 78 years (IQR: 71–83)). Baseline proteomics and the composite end point of all-cause mortality or heart failure (HF) hospitalisation were used in secondary analyses.

Results

We identified six phenogroups, for which significant differences in the prevalence of concomitant atrial fibrillation (AF), anaemia and kidney disease were observed (p<0.05). Fifteen out of 86 plasma proteins differed between phenogroups (false discovery rate, FDR<0.05), including biomarkers of HF, AF and kidney function. The composite end point was significantly different between phenogroups (log-rank p<0.001), at short-term (100 days), mid-term (18 months) and longer-term follow-up (1000 days). Phenogroup 2 was older, with poorer diastolic and right ventricular function and higher burden of risk factors as AF (85%), hypertension (83%) and chronic obstructive pulmonary disease (30%). In this group a third experienced the primary outcome to 100 days, and two-thirds to 18 months (HR (95% CI) versus phenogroups 1, 3, 4, 5, 6: 1.5 (0.8–2.9); 5.7 (2.6–12.8); 2.9 (1.5–5.6); 2.7 (1.6–4.6); 2.1 (1.2–3.9)).

Conclusions

Using machine learning we identified distinct HFpEF phenogroups with differential characteristics and outcomes, as well as differential levels of inflammatory and cardiovascular proteins.

Associations of Circulating Protein Levels With Lipid Fractions in the General Population

Objective- Revealing patterns of associations between circulating protein and lipid levels could improve biological understanding of cardiovascular disease (CVD). In this study, we investigated the associations between proteins related to CVD and triglyceride (TG), total cholesterol, LDL (low-density lipoprotein), and HDL (high-density lipoprotein) cholesterol levels in individuals from the general population. Approach and Results- We measured plasma protein levels using the Olink ProSeek CVD I or II+III arrays and analyzed 57 proteins available in 3 population-based cohorts: EpiHealth (n=2029; 52% women; median age, 61 years), PIVUS (Prospective Study of the Vasculature in Uppsala Seniors; n=790; 51% women; all aged 70 years), and ULSAM (Uppsala Longitudinal Study of Adult Men; n=551; all men aged 77 years). A discovery analysis was performed in EpiHealth in a regression framework (adjusted for sex, age, body mass index, smoking, glucose levels, systolic blood pressure, blood pressure medication, diabetes mellitus medication, and CVD history), and associations with false discovery rate <0.05 were further tested in PIVUS and ULSAM, where a P value of 0.05 was considered a successful replication (validation false discovery rate of 0.1%). We used summary statistics from a genome-wide association study on each protein biomarker (meta-analysis of EpiHealth, PIVUS, ULSAM, and IMPROVE [Carotid Intima-Media Thickness and IMT-Progression as Predictors of Vascular Events in a High-Risk European Population]) and publicly available data from Global Lipids Genetics Consortium to perform Mendelian randomization analyses to address possible causality of protein levels. Of 57 tested proteins, 42 demonstrated an association with at least 1 lipid fraction; 35 were associated with TG, 15 with total cholesterol, 9 with LDL cholesterol, and 24 with HDL cholesterol. Among these associations, we found KIM-1 (kidney injury molecule-1), TNFR (TNF [tumor necrosis factor] receptor) 1 and 2, TRAIL-R2 (TRAIL [TNF-related apoptosis-inducing ligand] receptor 2), and RETN (resistin) to be associated with all 4 lipid fractions. Further, 15 proteins were related to both TG and HDL cholesterol in a consistent and biologically expected manner, that is, higher TG and lower HDL cholesterol or vice versa. Another common pattern of associations was concomitantly higher TG, total cholesterol, and LDL cholesterol, which is associated with higher CVD risk. We did not find evidence of causal links for protein levels. Conclusions- Our comprehensive analysis of plasma proteins and lipid fractions of 3370 individuals from the general population provides new information about lipid metabolism.

Integrative studies implicate matrix metalloproteinase-12 as a culprit gene for large-artery atherosclerotic stroke

BACKGROUND

Ischaemic stroke and coronary heart disease are important contributors to the global disease burden and share atherosclerosis as the main underlying cause. Recent evidence from a genome-wide association study (GWAS) suggested that single nucleotide polymorphisms (SNP) near the MMP12 gene at chromosome 11q22.3 were associated with large-vessel ischaemic stroke. Here, we evaluated and extended these results by examining the relationship between MMP12 and atherosclerosis in clinical and experimental studies.

METHODS AND RESULTS

Plasma concentrations of MMP12 were measured at baseline in 3394 subjects with high-risk for cardiovascular disease (CVD) using the Olink ProSeek CVD I array. The plasma MMP12 concentration showed association with incident cardiovascular and cerebrovascular events (130 and 67 events, respectively, over 36 months) and carotid intima-media thickness progression (P = 3.6 × 10^-5 ). A GWAS of plasma MMP12 concentrations revealed that SNPs rs499459, rs613084 and rs1892971 at chr11q22.3 were independently associated with plasma MMP12 (P < 5 × 10^-8 ). The lead SNPs showed associations with mRNA levels of MMP12 and adjacent MMPs in atherosclerotic plaques. MMP12 transcriptomic and proteomic levels were strongly significantly increased in carotid plaques compared with control arterial tissue and in plaques from symptomatic versus asymptomatic patients. By combining immunohistochemistry and proximity ligation assay, we demonstrated that MMP12 localizes to CD68 + macrophages and interacts with elastin in plaques. MMP12 silencing in human THP-1-derived macrophages resulted in reduced macrophage migration.

CONCLUSIONS

Our study supports the notion that MMP12 is implicated in large-artery atherosclerotic stroke, functionally by enhancing elastin degradation and macrophage invasion in plaques.

Webinar | Proteogenomic strategies to advance drug development and precision medicine

The genomics era has had a profound impact on life science research, leading to significant developments such as the use of expression quantitative trait loci (eQTLs), which link polymorphisms in single genes to quantifiable changes in gene expression associated with specific diseases. As the end products and biological effectors of gene expression, proteins are crucial for improving our understanding of human biology, developing new and better drugs, and advancing precision medicine. Proteomics technologies have lagged behind their genomics counterparts, but recent breakthroughs are now combining these methods in powerful ways. The journey to clinical utility, however, remains challenging. Association of a protein biomarker with any given disease process, for example, needs to be assessed in terms of disease-independent, confounding factors that may modulate protein expression levels among different individuals. Moreover, understanding whether an associated protein is causally involved in (or merely reflects) a disease process is extremely valuable information for identifying new drug targets. Our panelists will discuss how multi-omics and epidemiological approaches are accelerating important advances in the use of protein biomarkers for clinical research and pharmaceutical development.

Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease

Recent advances in highly multiplexed immunoassays have allowed systematic large-scale measurement of hundreds of plasma proteins in large cohort studies. In combination with genotyping, such studies offer the prospect to 1) identify mechanisms involved with regulation of protein expression in plasma, and 2) determine whether the plasma proteins are likely to be causally implicated in disease. We report here the results of genome-wide association (GWA) studies of 83 proteins considered relevant to cardiovascular disease (CVD), measured in 3,394 individuals with multiple CVD risk factors. We identified 79 genome-wide significant (p<5e-8) association signals, 55 of which replicated at P<0.0007 in separate validation studies (n = 2,639 individuals). Using automated text mining, manual curation, and network-based methods incorporating information on expression quantitative trait loci (eQTL), we propose plausible causal mechanisms for 25 trans-acting loci, including a potential post-translational regulation of stem cell factor by matrix metalloproteinase 9 and receptor-ligand pairs such as RANK-RANK ligand. Using public GWA study data, we further evaluate all 79 loci for their causal effect on coronary artery disease, and highlight several potentially causal associations. Overall, a majority of the plasma proteins studied showed evidence of regulation at the genetic level. Our results enable future studies of the causal architecture of human disease, which in turn should aid discovery of new drug targets.

Several proteins that circulate in blood have been linked to cardiovascular disease through the use of classic epidemiology and correlation studies. If individuals with higher risk of disease have higher levels of a protein, the protein may be associated with disease. However, this does not necessarily mean that the protein causes disease; it may merely be an innocent bystander or a consequence of the disease process. To establish whether a protein causes disease, a genetic approach, insensitive to reverse causation, can be used. Instead of correlating the levels of the protein itself, gene variants that regulate the protein levels are used in the analysis. This approach requires prior knowledge of which genetic variants are linked to individual proteins. Therefore we completed a map of how common genetic variants affect the blood concentration levels of 83 proteins that have been implicated in cardiovascular disease. By using this map of cause-to-effect findings, we gained insights into the regulation of a majority of the proteins under study and how they relate to risk of coronary artery disease. This study provides a map of genetic regulation of important cardiovascular plasma proteins, insights into their upstream regulatory environment, as well as novel leads for cardiovascular drug development.

Abstract 318: Matrix Metalloproteinase 12 is Causally Implicated in Cardiovascular Disease

Recent evidence suggests that single nucleotide polymorphisms (SNPs) in the matrix metalloproteinase (MMP) gene cluster located at chromosome 11q22.3 are associated with large-vessel stroke. In the present study, we evaluated and extended the reported association by examining the relationship between MMPs and vascular disease in both clinical and experimental samples. Plasma concentrations of MMP-1, MMP-3, MMP-7, MMP-10 and MMP-12 were measured in 3 394 subjects with high-risk for cardiovascular disease (CVD) using the Olink ProSeek CVD array. Plasma MMP-12 concentration showed association with incident cardiovascular events (199 events over 36 months) and intima-media thickness progression over time (p=3.6x10 -5 ). The SNP variant rs1892971 was strongly associated with plasma MMP-12 concentration (p=8x10 -29 ) and weakly with susceptibility to coronary heart disease in the CardiogramplusC4D consortium study (p=8.8x10 -5 ). The same SNP was also significantly associated with MMP-12 gene expression in peripheral blood mononuclear cells using microarrays from patients with carotid atherosclerosis (n=96; p=1.8x10 -4 ). Expression of MMP-12 was strongly increased in carotid plaques (n=127) compared with undiseased arteries (n=10; p<0.0001) and in plaques from symptomatic (n=87) compared to asymptomatic patients (n=40; p=0.03) and localised to CD68+ macrophages. Using proximity ligation assay MMP-12 and elastin was demonstrated to co-interact in plaques in situ, particularly in regions with moderate to strong MMP-12 expression. Silencing of MMP-12 using siRNA in differentiated THP-1 cells indicated that MMP-12 has a role in macrophage migration. In conclusion, our study suggests that MMP-12 is a causal factor in CVD that is highly upregulated in human atherosclerotic plaques where it interacts with elastin and appears to enhance macrophage invasion.

Circulating Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Predicts Future Risk of Cardiovascular Events Independently of Established Risk Factors

BACKGROUND

The secreted protein proprotein convertase subtilisin/kexin type 9 (PCSK9) is a promising new target for lowering plasma low-density lipoprotein cholesterol and preventing cardiovascular disease (CVD). The relationship between circulating PCSK9 and incident CVD in the general population is unknown. We investigated whether serum PCSK9 concentration is associated with incident CVD in a prospective cohort study of 4232 men and women 60 years of age at the time of recruitment.

METHODS AND RESULTS

Incident CVD was recorded by matching to national registries. After 15 years of follow-up, a total of 491 incident events (fatal and nonfatal myocardial infarctions, unstable angina, deaths from coronary heart disease, fatal and nonfatal ischemic strokes) were recorded. Cox proportional hazards model was used to calculate hazard ratios with 95% confidence intervals. Baseline serum PCSK9 concentration predicted incident CVD; concentration in quartile 4 compared with quartile 1 was associated with a hazard ratio of 1.69 (95% confidence interval, 1.30-2.19) after adjustment for sex. Further adjustment for low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipoprotein(a), triglycerides, hypertension, diabetes mellitus, smoking, overweight, obesity, physical inactivity, and statin use resulted in a decrease in the hazard ratio to 1.48 (95% confidence interval, 1.12-1.95).

CONCLUSIONS

Serum PCSK9 concentration is associated with future risk of CVD even after adjustments for established CVD risk factors. Further studies are needed to confirm this observation.

Genome-wide association analysis of self-reported events in 6135 individuals and 252 827 controls identifies 8 loci associated with thrombosis

Thrombotic diseases are among the leading causes of morbidity and mortality in the world. To add insights into the genetic regulation of thrombotic disease, we conducted a genome-wide association study (GWAS) of 6135 self-reported blood clots events and 252 827 controls of European ancestry belonging to the 23andMe cohort of research participants. Eight loci exceeded genome-wide significance. Among the genome-wide significant results, our study replicated previously known venous thromboembolism (VTE) loci near the F5, FGA-FGG, F11, F2, PROCR and ABO genes, and the more recently discovered locus near SLC44A2 In addition, our study reports for the first time a genome-wide significant association between rs114209171, located upstream of the F8 structural gene, and thrombosis risk. Analyses of expression profiles and expression quantitative trait loci across different tissues suggested SLC44A2, ILF3 and AP1M2 as the three most plausible candidate genes for the chromosome 19 locus, our only genome-wide significant thrombosis-related locus that does not harbor likely coagulation-related genes. In addition, we present data showing that this locus also acts as a novel risk factor for stroke and coronary artery disease (CAD). In conclusion, our study reveals novel common genetic risk factors for VTE, stroke and CAD and provides evidence that self-reported data on blood clots used in a GWAS yield results that are comparable with those obtained using clinically diagnosed VTE. This observation opens up the potential for larger meta-analyses, which will enable elucidation of the genetics of thrombotic diseases, and serves as an example for the genetic study of other diseases.

No evidence for genome-wide interactions on plasma fibrinogen by smoking, alcohol consumption and body mass index: results from meta-analyses of 80,607 subjects

Plasma fibrinogen is an acute phase protein playing an important role in the blood coagulation cascade having strong associations with smoking, alcohol consumption and body mass index (BMI). Genome-wide association studies (GWAS) have identified a variety of gene regions associated with elevated plasma fibrinogen concentrations. However, little is yet known about how associations between environmental factors and fibrinogen might be modified by genetic variation. Therefore, we conducted large-scale meta-analyses of genome-wide interaction studies to identify possible interactions of genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentration. The present study included 80,607 subjects of European ancestry from 22 studies. Genome-wide interaction analyses were performed separately in each study for about 2.6 million single nucleotide polymorphisms (SNPs) across the 22 autosomal chromosomes. For each SNP and risk factor, we performed a linear regression under an additive genetic model including an interaction term between SNP and risk factor. Interaction estimates were meta-analysed using a fixed-effects model. No genome-wide significant interaction with smoking status, alcohol consumption or BMI was observed in the meta-analyses. The most suggestive interaction was found for smoking and rs10519203, located in the LOC123688 region on chromosome 15, with a p value of 6.2×10⁻⁸. This large genome-wide interaction study including 80,607 participants found no strong evidence of interaction between genetic variants and smoking status, alcohol consumption or BMI on fibrinogen concentrations. Further studies are needed to yield deeper insight in the interplay between environmental factors and gene variants on the regulation of fibrinogen concentrations.

Common genetic determinants of lung function, subclinical atherosclerosis and risk of coronary artery disease

Chronic obstructive pulmonary disease (COPD) independently associates with an increased risk of coronary artery disease (CAD), but it has not been fully investigated whether this co-morbidity involves shared pathophysiological mechanisms. To identify potential common pathways across the two diseases, we tested all recently published single nucleotide polymorphisms (SNPs) associated with human lung function (spirometry) for association with carotid intima-media thickness (cIMT) in 3,378 subjects with multiple CAD risk factors, and for association with CAD in a case-control study of 5,775 CAD cases and 7,265 controls. SNPs rs2865531, located in the CFDP1 gene, and rs9978142, located in the KCNE2 gene, were significantly associated with CAD. In addition, SNP rs9978142 and SNP rs3995090 located in the HTR4 gene, were associated with average and maximal cIMT measures. Genetic risk scores combining the most robustly spirometry–associated SNPs from the literature were modestly associated with CAD, (odds ratio (OR) (95% confidence interval (CI₉₅) = 1.06 (1.03, 1.09); P-value = 1.5×10⁻⁴, per allele). In conclusion, our study suggests that some genetic loci implicated in determining human lung function also influence cIMT and susceptibility to CAD. The present results should help elucidate the molecular underpinnings of the co-morbidity observed across COPD and CAD.

The HLA locus contains novel foetal susceptibility alleles for congenital heart block with significant paternal influence

OBJECTIVE

The main aim of this study was to identify foetal susceptibility genes on chromosome six for Ro/SSA autoantibody-mediated congenital heart block.

SUBJECTS AND DESIGN

Single nucleotide polymorphism (SNP) genotyping of individuals in the Swedish Congenital Heart Block (CHB) study population was performed. Low-resolution HLA-A, -Cw and -DRB1 allele typing was carried out in 86 families comprising 339 individuals (86 Ro/SSA autoantibody-positive mothers, 71 fathers, 87 CHB index cases and 95 unaffected siblings).

RESULTS

A case-control comparison between index cases and population-based out-of-study controls (n = 1710) revealed association of CHB with 15 SNPs in the 6p21.3 MHC locus at a chromosome-wide significance of P < 2.59 × 10(-6) (OR 2.21-3.12). In a family-based analysis of association of SNP markers as well as distinct MHC class I and II alleles with CHB, HLA-DRB1*04 and HLA-Cw*05 variants were significantly more frequently transmitted to affected individuals (P < 0.03 and P < 0.05, respectively), whilst HLA-DRB1*13 and HLA-Cw*06 variants were significantly less often transmitted to affected children (P < 0.04 and P < 0.03). We further observed marked association of increased paternal (but not maternal) HLA-DRB1*04 transmission to affected offspring (P < 0.02).

CONCLUSIONS

HLA-DRB1*04 and HLA-Cw*05 were identified as novel foetal HLA allele variants that confer susceptibility to CHB in response to Ro/SSA autoantibody exposure, whilst DRB1*13 and Cw*06 emerged as protective alleles. Additionally, we demonstrated a paternal contribution to foetal susceptibility to CHB for the first time.

Common genetic loci influencing plasma homocysteine concentrations and their effect on risk of coronary artery disease

BACKGROUND

The strong observational association between total homocysteine (tHcy) concentrations and risk of coronary artery disease (CAD) and the null associations in the homocysteine-lowering trials have prompted the need to identify genetic variants associated with homocysteine concentrations and risk of CAD.

OBJECTIVE

We tested whether common genetic polymorphisms associated with variation in tHcy are also associated with CAD.

DESIGN

We conducted a meta-analysis of genome-wide association studies (GWAS) on tHcy concentrations in 44,147 individuals of European descent. Polymorphisms associated with tHcy (P < 10(⁻⁸) were tested for association with CAD in 31,400 cases and 92,927 controls.

RESULTS

Common variants at 13 loci, explaining 5.9% of the variation in tHcy, were associated with tHcy concentrations, including 6 novel loci in or near MMACHC (2.1 × 10⁻⁹), SLC17A3 (1.0 × 10⁻⁸), GTPB10 (1.7 × 10⁻⁸), CUBN (7.5 × 10⁻¹⁰), HNF1A (1.2 × 10⁻¹²)), and FUT2 (6.6 × 10⁻⁹), and variants previously reported at or near the MTHFR, MTR, CPS1, MUT, NOX4, DPEP1, and CBS genes. Individuals within the highest 10% of the genotype risk score (GRS) had 3-μmol/L higher mean tHcy concentrations than did those within the lowest 10% of the GRS (P = 1 × 10⁻³⁶). The GRS was not associated with risk of CAD (OR: 1.01; 95% CI: 0.98, 1.04; P = 0.49).

CONCLUSIONS

We identified several novel loci that influence plasma tHcy concentrations. Overall, common genetic variants that influence plasma tHcy concentrations are not associated with risk of CAD in white populations, which further refutes the causal relevance of moderately elevated tHcy concentrations and tHcy-related pathways for CAD.

Multiethnic meta-analysis of genome-wide association studies in >100 000 subjects identifies 23 fibrinogen-associated Loci but no strong evidence of a causal association between circulating fibrinogen and cardiovascular disease

BACKGROUND

Estimates of the heritability of plasma fibrinogen concentration, an established predictor of cardiovascular disease, range from 34% to 50%. Genetic variants so far identified by genome-wide association studies explain only a small proportion (<2%) of its variation.

METHODS AND RESULTS

We conducted a meta-analysis of 28 genome-wide association studies including >90 000 subjects of European ancestry, the first genome-wide association meta-analysis of fibrinogen levels in 7 studies in blacks totaling 8289 samples, and a genome-wide association study in Hispanics totaling 1366 samples. Evaluation for association of single-nucleotide polymorphisms with clinical outcomes included a total of 40 695 cases and 85 582 controls for coronary artery disease, 4752 cases and 24 030 controls for stroke, and 3208 cases and 46 167 controls for venous thromboembolism. Overall, we identified 24 genome-wide significant (P<5×10(-8)) independent signals in 23 loci, including 15 novel associations, together accounting for 3.7% of plasma fibrinogen variation. Gene-set enrichment analysis highlighted key roles in fibrinogen regulation for the 3 structural fibrinogen genes and pathways related to inflammation, adipocytokines, and thyrotrophin-releasing hormone signaling. Whereas lead single-nucleotide polymorphisms in a few loci were significantly associated with coronary artery disease, the combined effect of all 24 fibrinogen-associated lead single-nucleotide polymorphisms was not significant for coronary artery disease, stroke, or venous thromboembolism.

CONCLUSIONS

We identify 23 robustly associated fibrinogen loci, 15 of which are new. Clinical outcome analysis of these loci does not support a causal relationship between circulating levels of fibrinogen and coronary artery disease, stroke, or venous thromboembolism.

Tumour-derived adhesion factor in colorectal cancer

Tumour-derived adhesion factor (TAF) has been shown to be associated with breast, prostate and colorectal cancer (CRC), acting as tumour suppressor or tumour promoter by mechanisms not as yet understood. Here, we comparatively analyzed the expression profile of TAF in plasma, tumour and paired normal tissue from patients with CRC. In addition, we investigated the relationship between TAF and systemic inflammation, mirrored by the elevation of interleukin-6 (IL-6) and TAF levels in plasma. Levels of TAF and IL-6 were determined by ELISA. Immunohistochemistry was performed to investigate the site of TAF expression. We also used a TaqMan system to investigate a TAF single nucleotide polymorphism (rs2041437) with a potential effect on CRC. TAF protein levels were significantly (P<0.001) higher in colorectal tumours than in normal tissue, and were increased in patients with Dukes' stages B and C compared to A. Immunohistochemistry revealed heterogeneous TAF expression mainly in the epithelial cells of the cancer and normal tissue. The plasma TAF level was reduced in CRC patients compared with the controls (P=0.002), independent of the inflammatory marker IL-6. Regarding genotype and allelic distributions, significant differences between CRC patients and control subjects or associations between clinical characteristics and TAF levels in tissue and plasma were not observed. In conclusion, altered TAF protein expression in cancer tissue may be a potential biomarker in colorectal carcinogenesis. Further research exploring the regulation of TAF is required to evaluate whether TAF is linked to clinical outcome.

Common and Low-Frequency Genetic Variants in the PCSK9 Locus Influence Circulating PCSK9 Levels

Objective —

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a circulating protein that influences plasma low-density lipoprotein concentration and susceptibility to coronary heart disease. Circulating PCSK9 levels show considerable interindividual differences, but the factors responsible for this variation are largely unknown.

Methods and Results—

We analyzed circulating PCSK9 levels in 4 cohorts of healthy, middle-aged Swedes (n=5722) and found that PCSK9 levels varied over ≈50-fold range, showed a positive relationship with plasma low-density lipoprotein–cholesterol concentration, and were associated with plasma triglyceride, fibrinogen, insulin, and glucose concentrations. A genome-wide association study conducted in 2 cohorts (n=1215) failed to uncover common genetic variants robustly associated with variation in circulating PCSK9 level. As expected, the minor allele of the PCSK9 R46L variant was in all cohorts associated with reduced PCSK9 levels and decreased plasma low-density lipoprotein–cholesterol concentrations, but no relationship was observed with the plasma triglyceride concentration. Further mapping of the PCSK9 locus revealed a common polymorphism (rs2479415, minor allele frequency 43.9%), located ≈6 kb upstream from PCSK9 , which is independently associated with increased circulating PCSK9 levels.

Conclusion—

Common and low-frequency genetic variants in the PCSK9 locus influence the pronounced interindividual variation in circulating PCSK9 levels in healthy, middle-aged white (predominantly Swedish) subjects.

Combined chromatin and expression analysis reveals specific regulatory mechanisms within cytokine genes in the macrophage early immune response

Macrophages play a critical role in innate immunity, and the expression of early response genes orchestrate much of the initial response of the immune system. Macrophages undergo extensive transcriptional reprogramming in response to inflammatory stimuli such as Lipopolysaccharide (LPS).To identify gene transcription regulation patterns involved in early innate immune responses, we used two genome-wide approaches--gene expression profiling and chromatin immunoprecipitation-sequencing (ChIP-seq) analysis. We examined the effect of 2 hrs LPS stimulation on early gene expression and its relation to chromatin remodeling (H3 acetylation; H3Ac) and promoter binding of Sp1 and RNA polymerase II phosphorylated at serine 5 (S5P RNAPII), which is a marker for transcriptional initiation. Our results indicate novel and alternative gene regulatory mechanisms for certain proinflammatory genes. We identified two groups of up-regulated inflammatory genes with respect to chromatin modification and promoter features. One group, including highly up-regulated genes such as tumor necrosis factor (TNF), was characterized by H3Ac, high CpG content and lack of TATA boxes. The second group, containing inflammatory mediators (interleukins and CCL chemokines), was up-regulated upon LPS stimulation despite lacking H3Ac in their annotated promoters, which were low in CpG content but did contain TATA boxes. Genome-wide analysis showed that few H3Ac peaks were unique to either +/-LPS condition. However, within these, an unpacking/expansion of already existing H3Ac peaks was observed upon LPS stimulation. In contrast, a significant proportion of S5P RNAPII peaks (approx 40%) was unique to either condition. Furthermore, data indicated a large portion of previously unannotated TSSs, particularly in LPS-stimulated macrophages, where only 28% of unique S5P RNAPII peaks overlap annotated promoters. The regulation of the inflammatory response appears to occur in a very specific manner at the chromatin level for specific genes and this study highlights the level of fine-tuning that occurs in the immune response.

Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes

OBJECTIVE

Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology.

RESEARCH DESIGN AND METHODS

We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates.

RESULTS

Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets.

CONCLUSIONS

We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.

Plasma CD93 concentration is a potential novel biomarker for coronary artery disease

OBJECTIVES

A common nonsynonymous single nucleotide polymorphism (SNP) in the CD93 gene (rs3746731, Pro541Ser) has been associated with risk of coronary artery disease (CAD). CD93 is a transmembrane glycoprotein, which is detectable in soluble form in human plasma. We investigated whether the concentration of soluble CD93 in plasma is related to risk of myocardial infarction (MI) and CAD, using a case-control study of premature MI (n = 764) and a nested case-control analysis of a longitudinal cohort study of 60-year-old subjects (analysis comprising 844 of 4232 subjects enrolled at baseline). In addition, SNPs in the CD93 gene were studied in relation to plasma CD93 concentration and CD93 mRNA expression.

METHODS AND RESULTS

A sensitive and specific enzyme-linked immunosorbent assay was established for determination of the plasma CD93 concentration. Subjects were divided into three groups according to tertiles of the distribution of CD93 concentration. Lower odds ratios for risk of MI and incidence of CAD were observed in the middle CD93 tertile (142-173 μg L(-1) ): odds ratio (95% confidence interval), 0.69 (0.49-0.97) and 0.61 (0.40-0.94), respectively. These associations were independent of traditional CAD risk factors. The minor allele of a SNP in the 3' untranslated region of CD93 (rs2749812) was associated with increased plasma CD93 concentrations (P = 0.03) and increased CD93 mRNA expression levels (P = 0.02).

CONCLUSION

The results of the present study suggest that the concentration of soluble CD93 in plasma is a potential novel biomarker for CAD, including MI.

A candidate gene study of the type I interferon pathway implicates IKBKE and IL8 as risk loci for SLE

Systemic Lupus Erythematosus (SLE) is a systemic autoimmune disease in which the type I interferon pathway has a crucial role. We have previously shown that three genes in this pathway, IRF5, TYK2 and STAT4, are strongly associated with risk for SLE. Here, we investigated 78 genes involved in the type I interferon pathway to identify additional SLE susceptibility loci. First, we genotyped 896 single-nucleotide polymorphisms in these 78 genes and 14 other candidate genes in 482 Swedish SLE patients and 536 controls. Genes with P<0.01 in the initial screen were then followed up in 344 additional Swedish patients and 1299 controls. SNPs in the IKBKE, TANK, STAT1, IL8 and TRAF6 genes gave nominal signals of association with SLE in this extended Swedish cohort. To replicate these findings we extracted data from a genomewide association study on SLE performed in a US cohort. Combined analysis of the Swedish and US data, comprising a total of 2136 cases and 9694 controls, implicates IKBKE and IL8 as SLE susceptibility loci (P_meta=0.00010 and P_meta=0.00040, respectively). STAT1 was also associated with SLE in this cohort (P_meta=3.3 × 10⁻⁵), but this association signal appears to be dependent of that previously reported for the neighbouring STAT4 gene. Our study suggests additional genes from the type I interferon system in SLE, and highlights genes in this pathway for further functional analysis.

Common variants at 10 genomic loci influence hemoglobin A₁(C) levels via glycemic and nonglycemic pathways

OBJECTIVE

Glycated hemoglobin (HbA₁(c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA₁(c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA₁(c) levels.

RESEARCH DESIGN AND METHODS

We studied associations with HbA₁(c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA₁(c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.

RESULTS

Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10⁻²⁶), HFE (rs1800562/P = 2.6 × 10⁻²⁰), TMPRSS6 (rs855791/P = 2.7 × 10⁻¹⁴), ANK1 (rs4737009/P = 6.1 × 10⁻¹²), SPTA1 (rs2779116/P = 2.8 × 10⁻⁹) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10⁻⁹), and four known HbA₁(c) loci: HK1 (rs16926246/P = 3.1 × 10⁻⁵⁴), MTNR1B (rs1387153/P = 4.0 × 10⁻¹¹), GCK (rs1799884/P = 1.5 × 10⁻²⁰) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10⁻¹⁸). We show that associations with HbA₁(c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA₁(c)) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA₁(c).

CONCLUSIONS

GWAS identified 10 genetic loci reproducibly associated with HbA₁(c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA₁(c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA₁(c).

Novel associations of multiple genetic loci with plasma levels of factor VII, factor VIII, and von Willebrand factor: The CHARGE (Cohorts for Heart and Aging Research in Genome Epidemiology) Consortium

BACKGROUND

Plasma levels of coagulation factors VII (FVII), VIII (FVIII), and von Willebrand factor (vWF) influence risk of hemorrhage and thrombosis. We conducted genome-wide association studies to identify new loci associated with plasma levels.

METHODS AND RESULTS

The setting of the study included 5 community-based studies for discovery comprising 23 608 European-ancestry participants: Atherosclerosis Risk In Communities Study, Cardiovascular Health Study, British 1958 Birth Cohort, Framingham Heart Study, and Rotterdam Study. All subjects had genome-wide single-nucleotide polymorphism (SNP) scans and at least 1 phenotype measured: FVII activity/antigen, FVIII activity, and vWF antigen. Each study used its genotype data to impute to HapMap SNPs and independently conducted association analyses of hemostasis measures using an additive genetic model. Study findings were combined by meta-analysis. Replication was conducted in 7604 participants not in the discovery cohort. For FVII, 305 SNPs exceeded the genome-wide significance threshold of 5.0x10(-8) and comprised 5 loci on 5 chromosomes: 2p23 (smallest P value 6.2x10(-24)), 4q25 (3.6x10(-12)), 11q12 (2.0x10(-10)), 13q34 (9.0x10(-259)), and 20q11.2 (5.7x10(-37)). Loci were within or near genes, including 4 new candidate genes and F7 (13q34). For vWF, 400 SNPs exceeded the threshold and marked 8 loci on 6 chromosomes: 6q24 (1.2x10(-22)), 8p21 (1.3x10(-16)), 9q34 (<5.0x10(-324)), 12p13 (1.7x10(-32)), 12q23 (7.3x10(-10)), 12q24.3 (3.8x10(-11)), 14q32 (2.3x10(-10)), and 19p13.2 (1.3x10(-9)). All loci were within genes, including 6 new candidate genes, as well as ABO (9q34) and VWF (12p13). For FVIII, 5 loci were identified and overlapped vWF findings. Nine of the 10 new findings were replicated.

CONCLUSIONS

New genetic associations were discovered outside previously known biological pathways and may point to novel prevention and treatment targets of hemostasis disorders.

Novel associations of CPS1, MUT, NOX4, and DPEP1 with plasma homocysteine in a healthy population: a genome-wide evaluation of 13 974 participants in the Women's Genome Health Study

BACKGROUND

Homocysteine is a sulfur amino acid whose plasma concentration has been associated with the risk of cardiovascular diseases, neural tube defects, and loss of cognitive function in epidemiological studies. Although genetic variants of MTHFR and CBS are known to influence homocysteine concentration, common genetic determinants of homocysteine remain largely unknown.

METHODS AND RESULTS

To address this issue comprehensively, we performed a genome-wide association analysis, testing 336 469 single-nucleotide polymorphisms in 13 974 healthy white women. Although we confirm association with MTHFR (1p36.22; rs1801133; P=8.1 x 10(-35)) and CBS (21q22.3; rs6586282; P=3.2 x 10(-10)), we found novel associations with CPS1 (2q34; rs7422339; P=1.9 x 10(-11)), MUT (6p12.3; rs4267943; P=2.0 x 10(-9)), NOX4 (11q14.3; rs11018628; P=9.6 x 10(-12)), and DPEP1 (16q24.3; rs1126464; P=1.2 x 10(-12)). The associations at MTHFR, DPEP1, and CBS were replicated in an independent sample from the PROCARDIS study, whereas the association at CPS1 was only replicated among the women.

CONCLUSIONS

These associations offer new insight into the biochemical pathways involved in homocysteine metabolism and provide opportunities to better delineate the role of homocysteine in health and disease.

Forty-three loci associated with plasma lipoprotein size, concentration, and cholesterol content in genome-wide analysis

While conventional LDL-C, HDL-C, and triglyceride measurements reflect aggregate properties of plasma lipoprotein fractions, NMR-based measurements more accurately reflect lipoprotein particle concentrations according to class (LDL, HDL, and VLDL) and particle size (small, medium, and large). The concentrations of these lipoprotein sub-fractions may be related to risk of cardiovascular disease and related metabolic disorders. We performed a genome-wide association study of 17 lipoprotein measures determined by NMR together with LDL-C, HDL-C, triglycerides, ApoA1, and ApoB in 17,296 women from the Women's Genome Health Study (WGHS). Among 36 loci with genome-wide significance (P<5×10⁻⁸) in primary and secondary analysis, ten (PCCB/STAG1 (3q22.3), GMPR/MYLIP (6p22.3), BTNL2 (6p21.32), KLF14 (7q32.2), 8p23.1, JMJD1C (10q21.3), SBF2 (11p15.4), 12q23.2, CCDC92/DNAH10/ZNF664 (12q24.31.B), and WIPI1 (17q24.2)) have not been reported in prior genome-wide association studies for plasma lipid concentration. Associations with mean lipoprotein particle size but not cholesterol content were found for LDL at four loci (7q11.23, LPL (8p21.3), 12q24.31.B, and LIPG (18q21.1)) and for HDL at one locus (GCKR (2p23.3)). In addition, genetic determinants of total IDL and total VLDL concentration were found at many loci, most strongly at LIPC (15q22.1) and APOC-APOE complex (19q13.32), respectively. Associations at seven more loci previously known for effects on conventional plasma lipid measures reveal additional genetic influences on lipoprotein profiles and bring the total number of loci to 43. Thus, genome-wide associations identified novel loci involved with lipoprotein metabolism—including loci that affect the NMR-based measures of concentration or size of LDL, HDL, and VLDL particles—all characteristics of lipoprotein profiles that may impact disease risk but are not available by conventional assay.

Genome-wide association studies (GWAS) of plasma lipoprotein fractions hold great promise for understanding lipid metabolism and its central role in cardiovascular disease and related disorders. Conventional assays for lipoprotein status determine total cholesterol content of low- or high-density lipoprotein particles (LDL-C or HDL-C, respectively) or total plasma triglyceride content (as an estimate of very-low density lipoprotein particle concentration [VLDL]). All three measures have been targets for recent GWAS. However, a more precise target for GWAS of lipoprotein metabolism would be the concentration of the individual lipoprotein particles according to class (LDL, HDL, VLDL) and size (small, medium, and large), all of which can be measured by NMR-based methods. In a population of 17,296 women of European ancestry from the Women's Genome Health Study, we have performed a GWAS for 22 lipoprotein measures derived from NMR-based and conventional assays. We find 43 genetic loci involved in lipoprotein metabolism, including 10 novel loci. The results offer a clearer picture of common genetic influences on lipoprotein metabolism than available previously, including genetic effects on the distribution of LDL, HDL, and VLDL particle size, as well as on IDL and VLDL particle concentration, neither of which can be assessed by conventional measures.

Genetic variants of tumor necrosis factor superfamily, member 4 (TNFSF4), and risk of incident atherothrombosis and venous thromboembolism

BACKGROUND

Recent data have implicated tumor necrosis factor (ligand) superfamily, member 4 (TNFSF4) gene variation in myocardial infarction in women; however, no prospective data are available on either incident arterial or venous disorders.

METHODS

We evaluated 2 previously characterized TNFSF4 gene variants (-921C>T and dbSNP rs3850641) with a) incident arterial events using a prospective case-cohort design with 344 incident CVD cases and 2254 control participants, all white, drawn from the Women's Health Study cohort with 10 years of follow-up, and b) venous thromboembolism (VTE) risk using a nested, matched case-control design of 108 white male pairs (drawn from the Physicians' Health Study cohort) and a case-cohort design of white female participants consisting of 125 cases and 2269 controls (drawn from the Women's Health Study cohort), analyzed separately.

RESULTS

Genotype distributions were in Hardy-Weinberg equilibrium. Results from a marker-by-marker regression analysis, adjusting for traditional risk factors, showed a significant association of -921C>T with an increased risk of VTE in women (additive: odds ratio 1.86; 95% CI 1.17-2.92, P = 0.008) in women. Furthermore, using a haplotype-based regression analysis, haplotype C-G was associated with a reduced risk of VTE relative to the referent haplotype, C-A (odds ratio 0.50; 95% CI 0.27-0.92; P = 0.02). In contrast, we found little evidence for an association of the variants/haplotypes with risk of VTE in men or CVD risk in women (as previously reported).

CONCLUSIONS

Our present findings, if corroborated in other prospective investigations, suggest that the TNFSF4 variants tested may be useful indicators for assessing the risk of venous thromboembolism.

Variants of the interferon regulatory factor 5 gene regulate expression of IRF5 mRNA in atherosclerotic tissue but are not associated with myocardial infarction

BACKGROUND

Signaling events after activation of toll-like receptors (TLRs) are important mechanisms promoting inflammation in the atherosclerotic plaque. INF regulatory factor 5 (IRF5) is one of the mediators of downstream effects of TLRs. Several single nucleotide polymorphisms (SNPs) in the IRF5 gene have been found to be associated with systemic lupus erythematosus.

METHODS AND RESULTS

We examined IRF5 mRNA expression in carotid atherosclerotic tissue (n=99) and the case-control association between SNPs in the IRF5 gene with myocardial infarction (MI) (n=376+387) and unstable coronary artery disease (CAD) (n=3101+445). Among unstable CAD patients, association of IRF5 SNPs with recurrent coronary events (n=401) was also investigated. The IRF5 mRNA expression was increased in atherosclerotic tissue compared with control tissue (P<0.001). Significant associations with IRF5 expression was observed for 6 of 10 SNPs in the study. However, the IRF5 SNPs examined were neither associated with the risk of precocious MI, nor with unstable CAD or risk of recurrent cardiovascular events in unstable CAD patients.

CONCLUSIONS

IRF5 mRNA is expressed in cells in atherosclerotic tissue and its expression is modified by SNPs in the IRF5 gene. Genetic variation at the IRF5 locus was, however, not associated with CAD or related phenotypes.