Study uncovers hidden proteins responsible for heart disease and stroke

Research is revealing potential drug targets for the treatment of heart disease and stroke, using a combination of genetic and observational data to separate causal from non-causal proteins.

Letter: Measured and genetically predicted protein levels and cardiovascular disease in the UK Biobank and China Kadoorie Biobank. Image source: Lightspring / Shutterstock

In a recent study published in the journal Cardiovascular research in natureinvestigators assessed the association between 2,919 different plasma proteins and cardiovascular disease (CVD) outcomes in the UK Biobank (UKB) and China Kadoorie Biobank (CKB), identifying potential causative proteins for new drug targets.

Background

Many studies have measured plasma protein levels in people with cardiovascular disease. However, due to the interconnected nature of proteins, it is often difficult in observational studies to identify those that have true causal significance.

One way to address this issue is through Mendelian randomization (MR) and genetic analyzes to test whether genetic loci that regulate protein levels are also associated with CVD outcomes.

Previous research has found hundreds of proteins associated with myocardial infarction (MI) (a heart attack caused by blockage of blood flow to the heart), ischemic stroke (IS) (stroke caused by blockage of blood vessels supplying the brain) and the heart. heart failure (HF) (a condition in which the heart is unable to pump blood effectively), with a limited number of cases showing evidence of a causal relationship.

Further research is needed to better understand these causal relationships and discover new therapeutic targets for the treatment of CVD.

About the study

UKB is a large, multicentre, prospective cohort study conducted in the UK between 2006 and 2010, which included over 500,000 people aged 40–69. Data from 52,164 participants with valid proteomic data were included. The North West Multicenter Research Ethics Committee (UK) and the Swedish Ethical Review Board provided ethical approval and participants provided written informed consent. Baseline measurements were collected, including plasma glucose, cholesterol, and creatinine levels, blood pressure, and estimated glomerular filtration rate (eGFR).

Participants’ ethnicity was categorized and socioeconomic status was assessed using the Townsend Index of Social Deprivation. Smoking status was recorded as never, former, or current smoker. Disease outcomes, including myocardial infarction, IS, and HF, were classified using International Classification of Diseases (ICD-10) codes. Plasma levels of 2,923 proteins were initially measured using the Olink EXPLORE assay, and 2,919 proteins passed quality control.

The CKB study covered 512,000 Chinese adults employed between 2004 and 2008. Data on smoking, medical history, and education were collected. Plasma proteins were measured using the same analytical platform as UKB. Key findings from UKB were successfully replicated in CKB, strengthening the study’s findings.

Research results

In UKB, 126 proteins were found to be significantly associated with all three CVD outcomes. Of these, 118 were associated with at least one CVD outcome in the replication phase performed at CKB. Of these, 87 proteins were associated with more than one CVD, and 31 proteins were associated with all three CVD outcomes (MI, IS, and HF) at the significance level of P

Using Mendelian randomization (MR) analysis, genetically predicted levels of 33 proteins were associated with coronary heart disease (CHD), with the most important proteins being lipoprotein(a) (LPA), EGF-cadherin LAG seven-pass G-type receptor 2 (CELSR2), apolipoprotein E (APOE), feline sarcoma oncogene (FES), and vesicle-associated membrane protein 5 (VAMP5). Four proteins have been associated with IS, while 18 proteins have been associated with HF, with LPA, CELSR2 and fibroblast growth factor 5 (FGF5) emerging as key players in CHD and HF. Sensitivity analyzes using multiple cis-SNPs for MR analysis yielded results consistent with initial findings, increasing the robustness of these associations.

Colocalization analysis provided further evidence by showing that 10 proteins had strong common causal variants with CVD outcomes. Of note, CELSR2 and FGF5 were associated with both CHD and HF, while FURIN was associated with both CHD and stroke. These proteins, especially FURIN, have been identified as promising targets for future drug development, supported by additional discoveries regarding subclinical markers of CVD.

Interestingly, observational analyzes showed a weaker association between protein levels and CVD results compared with MRI results. In observational analyses, only 6% of proteins associated with CVD outcomes were found to be causal in MR analysis, suggesting that many observational associations are not causal. This discrepancy is likely due to systematic errors such as residual confounding and reverse causality in observational studies.

Proteins such as FGF5, protein C receptor (PROCR), and FURIN have shown consistent evidence of a causal association with CVD outcomes in both observational and genetic analyses, highlighting their potential as therapeutic targets. FGF5 has been associated with hypertension and carotid artery dilatation, while FURIN, a protease involved in protein activation, has been associated with both myocardial infarction and IS.

Conclusions

In summary, the study identified many proteins associated with CVD outcomes, but genetic analyzes showed that only a small subset demonstrated a causal association. Key proteins such as FGF5, PROCR, and FURIN have emerged as potential targets for CVD prevention and treatment.

The findings highlight the importance of distinguishing between observational and causal associations in protein research. Although many of the observational associations were not causal, the use of Mendelian randomization and colocalization analyzes improved our understanding of which proteins may play a direct role in the pathogenesis of CVD, offering promising directions for future drug development.