Rheumatoid arthritis and the risk of major cardiometabolic diseases: a Mendelian randomization study

Autoimmune diseases and atherosclerotic cardiovascular disease

Autoimmune diseases are associated with a dramatically increased risk of atherosclerotic cardiovascular disease and its clinical manifestations. The increased risk is consistent with the notion that atherogenesis is modulated by both protective and disease-promoting immune mechanisms. Notably, traditional cardiovascular risk factors such as dyslipidaemia and hypertension alone do not explain the increased risk of cardiovascular disease associated with autoimmune diseases. Several mechanisms have been implicated in mediating the autoimmunity-associated cardiovascular risk, either directly or by modulating the effect of other risk factors in a complex interplay. Aberrant leukocyte function and pro-inflammatory cytokines are central to both disease entities, resulting in vascular dysfunction, impaired resolution of inflammation and promotion of chronic inflammation. Similarly, loss of tolerance to self-antigens and the generation of autoantibodies are key features of autoimmunity but are also implicated in the maladaptive inflammatory response during atherosclerotic cardiovascular disease. Therefore, immunomodulatory therapies are potential efficacious interventions to directly reduce the risk of cardiovascular disease, and biomarkers of autoimmune disease activity could be relevant tools to stratify patients with autoimmunity according to their cardiovascular risk. In this Review, we discuss the pathophysiological aspects of the increased cardiovascular risk associated with autoimmunity and highlight the many open questions that need to be answered to develop novel therapies that specifically address this unmet clinical need.

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases

BACKGROUND

Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD.

METHODS

Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets.

RESULTS

Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure.

CONCLUSIONS

This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Rapid ethnographic appraisal of community concepts of and responses to joint pain in Kilimanjaro, Tanzania

INTRODUCTION

Musculoskeletal disorders, experienced as joint pain, are a significant global health problem, but little is known about how joint pain is categorised and understood in Tanzania. Understanding existing conceptualisations of and responses to joint pain is important to ensure both research and interventions are equitable and avoid biomedical imposition.

METHODS

Rapid ethnographic appraisal was conducted in a periurban and rural community in Kilimanjaro, documenting language used to describe joint pain, ideas about causes, understandings of who experiences such pain, the impacts pain has and how people respond to it. We conducted 66 interviews with community leaders, traditional healers, community members and pharmacists.Photographs were taken and included in fieldnotes to supplement the interview data and develop thick descriptions. Data were analysed by constant comparison using QDA Miner software.

RESULTS

Across the sample, dominant concepts of joint pain were named ugonjwa wa baridi, cold disease; ugonjwa wa uzee, old age disease; rimatizim, disease of the joints; and gauti, gout. Causes mentioned included exposure to the cold, old age, alcohol and red meat consumption, witchcraft, demons and injuries/falls. Age, gender and occupation were seen as important factors for developing joint pain. Perceived impacts of joint pain included loss of mobility, economic and family problems, developing new health conditions, death, reduction in sexual functioning and negative self-perceptions. Responses to joint pain blended biomedical treatments, herbal remedies, consultations with traditional healers and religious rituals.

CONCLUSIONS

Conceptualisations of and responses to joint pain in the two communities were syncretic, mixing folk and biomedical practices. Narratives about who is affected by joint pain mirror emerging epidemiological findings, suggesting a strong 'lay epidemiology' in these communities. Anthropological methods can support the decolonisation of global health by decentring the imposition of English language biomedicine and pursuing synthetic, dignified languages of care.

Causal factors underlying diabetes risk informed by Mendelian randomisation analysis: evidence, opportunities and challenges

Diabetes and its complications cause a heavy disease burden globally. Identifying exposures, risk factors and molecular processes causally associated with the development of diabetes can provide important evidence bases for disease prevention and spur novel therapeutic strategies. Mendelian randomisation (MR), an epidemiological approach that uses genetic instruments to infer causal associations between an exposure and an outcome, can be leveraged to complement evidence from observational and clinical studies. This narrative review aims to summarise the evidence on potential causal risk factors for diabetes by integrating published MR studies on type 1 and 2 diabetes, and to reflect on future perspectives of MR studies on diabetes. Despite the genetic influence on type 1 diabetes, few MR studies have been conducted to identify causal exposures or molecular processes leading to increased disease risk. In type 2 diabetes, MR analyses support causal associations of somatic, mental and lifestyle factors with development of the disease. These studies have also identified biomarkers, some of them derived from the gut microbiota, and molecular processes leading to increased disease risk. These studies provide valuable data to better understand disease pathophysiology and explore potential therapeutic targets. Because genetic association studies have mostly been restricted to participants of European descent, multi-ancestry cohorts are needed to examine the role of different types of physical activity, dietary components, metabolites, protein biomarkers and gut microbiome in diabetes development.

Relationship between rheumatoid arthritis and cardiovascular comorbidity, causation or co-occurrence: A Mendelian randomization study

Background

In recent years, the incidence rates of rheumatoid arthritis (RA) and heart disease (HD) have noticeably increased worldwide. Previous studies have found that patients with RA are more likely to develop HD, while the cause and effect have still remained elusive. In this study, Mendelian randomization (MR) analysis was used to indicate whether there was a potential association between RA and HD.

Methods

Data of RA, ischemic heart disease (IHD), myocardial infarction (MI), atrial fibrillation (AF), and arrhythmia were based on the genome-wide association study (GWAS) dataset. No disease group was intersected. Inverse-variance weighted (IVW) method was used to calculate MR estimates, and sensitivity analysis was performed.

Results

The primary MR analysis showed that genetic susceptibility to RA was significantly associated with the risk of IHD and MI, rather than with AF and arrhythmia. Besides, there was no heterogeneity and horizontal pleiotropy between the primary and replicated analyses. There was a significant correlation between RA and the risk of IHD (odds ratio (OR), 1.0006; 95% confidence interval (CI), 1.000244–1.00104; P = 0.001552), meanwhile, there was a significant correlation between RA and the risk of MI (OR, 1.0458; 95% CI, 1.07061–1.05379; P = 0.001636). The results were similar to those of sensitivity analysis, and the sensitivity analysis also verified the conclusion. Furthermore, sensitivity and reverse MR analyses suggested that no heterogeneity, horizontal pleiotropy or reverse causality was found between RA and cardiovascular comorbidity.

Conclusion

RA was noted to be causally associated with IHD and MI, rather than with AF and arrhythmia. This MR study might provide a new genetic basis for the causal relationship between RA and the risk of CVD. The findings suggested that the control of RA activity might reduce the risk of cardiovascular disease.

Asthma and atopic dermatitis as risk factors for rheumatoid arthritis: a bidirectional mendelian randomization study

BACKGROUND

Previous observational studies have shown an association between asthma, atopic dermatitis (AD) and rheumatoid arthritis (RA). However, the bidirectional cause-effect chain between asthma and AD and RA has not been proven yet.

METHODS

We performed bidirectional two-sample Mendelian randomization (TSMR) and selected single nucleotide polymorphisms (SNPs) associated with asthma, AD, and RA as instrumental variables. All of the SNPs were obtained from the latest genome-wide association study in Europeans. Inverse variance weighted (IVW) was the main method used in MR analysis. MR-Egger, weighted model, simple model, and weighted median were used for quality control. The robustness of the results was tested by sensitivity analysis.

RESULTS

Asthma was found to be the largest effect size for RA susceptibility using the IVW method (OR, 1.35;95%CI, 1.13-1.60; P, 0.001), followed by AD (OR, 1.10;95%CI, 1.02-1.19; P, 0.019). In contrast, there was no causal relationship between RA and asthma (IVW: P = 0.673) or AD (IVW: P = 0.342). No pleiotropy or heterogeneity was found in the sensitivity analysis.

CONCLUSION

Findings from this study showed a causal relationship between genetic susceptibility to asthma or AD and increased risk of RA, but do not support a causal relationship between genetic susceptibility to RA and asthma or AD.

Bidirectional two-sample Mendelian randomization study of causality between rheumatoid arthritis and myocardial infarction

Background

Epidemiological evidence suggests an association between rheumatoid arthritis (RA) and myocardial infarction (MI). However, causality remains uncertain. Therefore, this study aimed to explore the causal association between RA and MI.

Methods

Using publicly available genome-wide association study summary datasets, bidirectional two-sample Mendelian randomization (TSMR) was performed using inverse-variance weighted (IVW), weighted median, MR-Egger regression, simple mode, and weighted mode methods.

Results

The MR results for the causal effect of RA on MI (IVW, odds ratio [OR] = 1.041, 95% confidence interval [CI]: 1.007-1.076, P = 0.017; weighted median, OR = 1.027, 95% CI: 1.006-1.049, P = 0.012) supported a causal association between genetic susceptibility to RA and an increased risk of MI. MR results for the causal effect of MI on RA (IVW, OR = 1.012, 95% CI: 0.807-1.268, P = 0.921; weighted median, OR = 1.069, 95% CI: 0.855-1.338, P = 0.556) indicated that there was no causal association between genetic susceptibility to MI and an increased risk of RA.

Conclusion

Bidirectional TSMR analysis supports a causal association between genetic susceptibility to RA and an increased risk of MI but does not support a causal association between genetic susceptibility to MI and an increased risk of RA.