Rheumatoid Arthritis and Cardio-Cerebrovascular Disease: A Mendelian Randomization Study

Rheumatoid arthritis and diabetic retinopathy: A two-sample Mendelian randomization study

Diabetic retinopathy (DR) is a common and highly blinding disease. Many clinical studies have shown a causal relationship between Rheumatoid arthritis (RA) and DR, but the results are contradictory. In addition, some clinical results and pathological inferences have certain paradoxes, and the influence of RA on the pathogenesis and development of DR Is unclear. Our research assessed the causal association between RA and the development of DR using a 2-sample Mendelian randomization method. Single nucleotide polymorphisms (SNPs) relevant to the study were extracted and filtered from genome-wide association study (GWAS) data. A DR GWAS with a sample size of 190,594 and an RA GWAS with a sample size of 58,284 were obtained. Inverse variance weighted (IVW) method was used to analyze the results, and Mendelian randomization (MR)-Egger regression method and weighted median method were used to evaluate the robustness. Sensitivity analysis was performed using pleiotropy test, heterogeneity test, leave-one-out test to ensure that the results were unbiased. Confounding factors were eliminated to ensure robustness. A total of 83 related SNPs were screened. IVW method showed a positive correlation between RA and the increased relative risk of diabetic retinopathy (OR = 1.06, 95%CI: 1.04-1.23). The same trend was shown by MR-Egger regression method and weighted median method. Sensitivity analysis showed that there was no heterogeneity in SNPs, and the results were less likely to be affected by potential bias. After removing SNPs linked to confounders, the MR results remained significant and stable in direction. There is a positive causal association between rheumatoid arthritis and diabetic retinopathy. It is important to strengthen retina-related screening and prevention in diabetic patients with RA to reduce the risk of DR In RA patients.

Genetic relationship between rheumatoid arthritis and cardiovascular diseases : A systematic review of Mendelian randomization studies

OBJECTIVE

Rheumatoid arthritis (RA) is recognized as a chronic autoimmune disorder with systemic inflammation and joint damage. Its potential role as a risk factor for cardiovascular diseases (CVD) is increasingly noted. This review delves into the causal relationship between RA and CVD, with Mendelian randomization (MR) offering a genetic perspective.

METHODS

An extensive search was conducted in PubMed, Cochrane and Web of Science to identify MR studies addressing the RA-CVD link. Out of 530 studies, 9 met the inclusion criteria, which were rigorously assessed using a critical appraisal checklist. These were further stratified by a sensitivity analysis into categories reflecting the strength of their evidence, from not evaluable to robust.

RESULTS

From the nine included studies, eight supported a causal association between RA and an increased risk of CVD, specifically coronary artery disease (CAD) and one did not support a link between RA and heart failure. The results suggest that genetic factors associated with RA may contribute to an elevated risk for CVD. Chronic inflammation, prevalent in RA, emerges as a key mediator in this connection.

CONCLUSION

The systematic review corroborates a genetic causal link between RA and CVD, as evidenced by eight of the nine MR studies reviewed. This suggests a need for integrated cardiovascular risk management in the treatment of RA patients. The findings advocate considering anti-inflammatory treatment that can reduce cardiovascular risk. The overarching evidence signifies a potential direction for new therapeutic strategies aimed at enhancing cardiovascular health in RA patients.

Association Between Rheumatoid Arthritis and Clonal Hematopoiesis: A Mendelian Randomization Study

Immunity activation and inflammation are the main characteristics of rheumatoid arthritis and clonal hematopoiesis. However, it remains unclear whether rheumatoid arthritis increase the risk of clonal hematopoiesis. Here, a Mendelian randomization (MR) analysis was conduct to explore the causal effects of rheumatoid arthritis on clonal hematopoiesis. Summary statistics data of rheumatoid arthritis (13,838 cases and 33,742 controls) and clonal hematopoiesis (10,203 cases and 173,918 controls) derived from a genomewide association study were selected to analyze. We selected inverse-variance weighted, MR-Egger, weighted median, simple mode, and weighted mode to evaluate the causal effect of rheumatoid arthritis on clonal hematopoiesis. The two-sample MR analysis suggested a strong causal relationship between rheumatoid arthritis and clonal hematopoiesis by inverse-variance weighted (OR = 1.002311673, 95% CI [1.000110757, 1.004517433], p = .039706) and weighted median (OR = 1.002311673, 95% CI [1.000110757, 1.004517433], p = .039518447) methods. No significant pleiotropy or heterogeneity was found in the sensitivity analysis. These results supported a potentially causal relationship between rheumatoid arthritis and clonal hematopoiesis, and the exposure of rheumatoid arthritis increased the risks of clonal hematopoiesis. Our findings highlight the importance of how chronic inflammation and immune activation induced rheumatoid arthritis enhances the risks of clonal hematopoiesis, and that early intervention with rheumatoid arthritis patients might reduce the clonal hematopoiesis risks in rheumatoid arthritis patients. Moreover, our study provides clues for prediction of risk factors and potential mechanisms of clonal hematopoiesis.

Rheumatoid arthritis increases the risk of heart failure: results from the cross-sectional study in the US population and mendelian randomization analysis in the European population

Objective

Rheumatoid arthritis (RA) is a chronic systemic autoimmune disease. Among its various complications, heart failure (HF) has been recognized as the second leading cause of cardiovascular death in RA patients. The objective of this study was to investigate the relationship between RA and HF using epidemiological and genetic approaches.

Methods

The study included 37,736 participants from the 1999-2020 National Health and Nutrition Examination Survey. Associations between RA and HF in the US population were assessed with weighted multivariate logistic regression analysis. A two-sample Mendelian randomization (MR) analysis was employed to establish the causal relationship between the two variables. The primary analysis method utilized was inverse variance weighting (IVW). Additionally, horizontal pleiotropy and heterogeneity were assessed to account for potential confounding factors. In cases where multiple independent datasets were accessible during MR analysis, we combined the findings through a meta-analytical approach.

Results

In observational studies, the prevalence of HF in combination with RA reached 7.11% (95%CI 5.83 to 8.39). RA was positively associated with an increased prevalence of HF in the US population [odds ratio (OR):1.93, 95% confidence interval (CI):1.47-2.54, P < 0.0001]. In a MR analysis utilizing a meta-analytical approach to amalgamate the results of the IVW method, we identified a significant causal link between genetically predicted RA and a heightened risk of HF (OR = 1.083, 95% CI: 1.028-1.141; P = 0.003). However, this association was not deemed significant for seronegative RA (SRA) (OR = 1.028, 95% CI: 0.992-1.065; P = 0.126). These findings were consistent across sensitivity analyses and did not indicate any horizontal pleiotropy.

Conclusion

RA correlates with an elevated prevalence of HF within the US population. Furthermore, genetic evidence derived from European populations underscores a causal link between RA and the risk of HF. However this association was not significant in SRA.

MYLK*FLNB and DOCK1*LAMA2 gene-gene interactions associated with rheumatoid arthritis in the focal adhesion pathway

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease caused by a combination of genetic and environmental factors. Rare variants with low predicted effects in genes participating in the same biological function might be involved in developing complex diseases such as RA. From whole-exome sequencing (WES) data, we identified genes containing rare non-neutral variants with complete penetrance and no phenocopy in at least one of nine French multiplex families. Further enrichment analysis highlighted focal adhesion as the most significant pathway. We then tested if interactions between the genes participating in this function would increase or decrease the risk of developing RA disease. The model-based multifactor dimensionality reduction (MB-MDR) approach was used to detect epistasis in a discovery sample (19 RA cases and 11 healthy individuals from 9 families and 98 unrelated CEU controls from the International Genome Sample Resource). We identified 9 significant interactions involving 11 genes (MYLK, FLNB, DOCK1, LAMA2, RELN, PIP5K1C, TNC, PRKCA, VEGFB, ITGB5, and FLT1). One interaction (MYLK*FLNB) increasing RA risk and one interaction decreasing RA risk (DOCK1*LAMA2) were confirmed in a replication sample (200 unrelated RA cases and 91 GBR unrelated controls). Functional and genomic data in RA samples or relevant cell types argue the key role of these genes in RA.

The Effect of Rheumatoid Arthritis on Features Associated with Sarcopenia: A Mendelian Randomization Study

Previous epidemiological evidence suggests rheumatoid arthritis is associated with sarcopenia-related features. However, most of the current evidence is from cross-sectional studies, and the causal link of this association is still to be determined. Therefore, this study was committed to a two-sample Mendelian randomization analysis to assess the causal effect of rheumatoid arthritis on sarcopenia-related features. In this two-sample Mendelian randomization study, instrumental variables for rheumatoid arthritis were obtained from the Non-Cancer Disease Study, and data for the five relevant characteristics of sarcopenia were pooled from UKBiobank. Inverse variance weighting is the primary analysis method for assessing causal effects. MR-Egger regression and weighted median are complementary analysis methods for causal effects. Leave-one-out analysis, horizontal pleiotropy test, and Heterogeneity test are applied as a sensitivity analysis to assess the robustness of causal effect estimates. The inverse variance weighted results for the five characteristics associated with sarcopenia and rheumatoid arthritis were: hand grip strength (right) (beta = - 2.309, se = 0.206, p = 3.340E-29), hand grip strength (left) (beta = - 2.046, se = 0.205, p = 2.166E-23), whole body lean mass (beta = - 0.843, se = 0.135, p = 4.67E-10), appendicular lean mass (beta = - 2.444, se = 0.208, p = 6.069E-32), Usual walking pace (OR 0.340, 95% CI (0.238, 0.484), p = 2.471E-09). The sensitivity analyses did not support that horizontal pleiotropy distorted causal effect estimates. The beta coefficient quantifies the number of standard deviations of the continuous outcome variables (hand grip strength, whole body lean mass, and appendicular lean mass) that change on average with each increase in the standard deviation of the binary exposure variable (rheumatoid arthritis). The odds ratios indicate the increased risk of the binary outcome variable (usual walking pace) per rheumatoid arthritis standard deviation increase. This study has demonstrated a negative causal effect of rheumatoid arthritis with five major sarcopenia-related features in a European population.

Genome-wide analysis reveals extensive genetic overlap between childhood phenotypes and later-life type 2 diabetes

Observational studies have indicated a potential influence of childhood phenotypes on the later development of type 2 diabetes (T2D). However, the underlying biological mechanisms remain unclear. In this study, we conducted a comprehensive genome-wide analysis to investigate the shared genetic architecture and genetic loci between nine childhood phenotypes (N = 4202-620,26) and later-life T2D (N = 80,154) using genetic correlation, mendelian randomization (MR), and conjunctional false discovery rate (conjFDR) statistical frameworks. Our findings demonstrated substantial genetic correlations and pleiotropic enrichment between childhood obesity, body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), and later-life T2D. Childhood obesity exhibited a significant association with increased later-life T2D risk through 10 mediators, 6 of which were adulthood obesity-related phenotypes. Additionally, we identified 69, 83, 3, 5, 10, 5, 3, and 7 loci shared between childhood obesity, BMI, SBP, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), apolipoprotein A-I (ApoA-I), apolipoprotein B (ApoB), and T2D at conjFDR <0.05, with the majority of these loci being novel discoveries. Overall, our study reveals extensive genetic overlap between childhood obesity-related phenotypes and T2D with concordant effect directions, shedding new light on variants and phenotypes with lifelong effects.

Vitamin D levels and five cardiovascular diseases: A Mendelian randomization study

Cardiovascular disease is the leading cause of death worldwide, whilst vitamin D levels have been found to be associated with cardiovascular disease. To investigate the causal relationship between vitamin D levels and five cardiovascular diseases, a genome-wide association study (GWAS) was carried out using data on vitamin D levels (sample size = 79366), angina pectoris (18168 cases and 187840 controls), coronary heart disease (21012 cases and 197780 controls), lacunar stroke (6030 cases and 248929 controls), heart attack (10693 cases and 451187 controls), and hypertension (55917 cases and 162837 controls), with a Mendelian randomization (MR) analysis being subsequently performed. Six single nucleotide polymorphisms were used as instrumental variables (IVs). In addition, sensitivity analysis was performed to verify the reliability of the MR results here. The results showed a causal relationship between vitamin D levels and angina pectoris (OR = 0.51, 95 % CI: 0.28-0.93, P = 0.03), coronary heart disease (OR = 0.53, 95 % CI: 0.34-0.81, P = 0.004), and lacunar stroke (OR = 0.41, 95 % CI: 0.20-0.86, P = 0.02), but no causal relationship with heart attacks (OR = 1.00, 95 % CI: 0.99-1.01, P = 0.76) or hypertension (OR = 0.99, 95 % CI: 0.73-1.34, P = 0.94). Additionally, our IVs data showed no heterogeneity or pleiotropy, whilst the results of the MR analysis were reliable. This study contributes to the prevention and treatment of these five cardiovascular diseases.

Mendelian randomization study supports the causal effects of air pollution on longevity via multiple age-related diseases

Growing evidence suggests that exposure to fine particulate matter (PM2.5) may reduce life expectancy; however, the causal pathways of PM2.5 exposure affecting life expectancy remain unknown. Here, we assess the causal effects of genetically predicted PM2.5 concentration on common chronic diseases and longevity using a Mendelian randomization (MR) statistical framework based on large-scale genome-wide association studies (GWAS) (>400,000 participants). After adjusting for other types of air pollution and smoking, we find significant causal relationships between PM2.5 concentration and angina pectoris, hypercholesterolaemia and hypothyroidism, but no causal relationship with longevity. Mediation analysis shows that although the association between PM2.5 concentration and longevity is not significant, PM2.5 exposure indirectly affects longevity via diastolic blood pressure (DBP), hypertension, angina pectoris, hypercholesterolaemia and Alzheimer's disease, with a mediated proportion of 31.5, 70.9, 2.5, 100, and 24.7%, respectively. Our findings indicate that public health policies to control air pollution may help improve life expectancy.

Integration of multiple-omics data to reveal the shared genetic architecture of educational attainment, intelligence, cognitive performance, and Alzheimer's disease

Growing evidence suggests the effect of educational attainment (EA) on Alzheimer's disease (AD), but less is known about the shared genetic architecture between them. Here, leveraging genome-wide association studies (GWAS) for AD (N = 21,982/41,944), EA (N = 1,131,881), cognitive performance (N = 257,828), and intelligence (N = 78,308), we investigated their causal association with the linkage disequilibrium score (LDSC) and Mendelian randomization and their shared loci with the conjunctional false discovery rate (conjFDR), transcriptome-wide association studies (TWAS), and colocalization. We observed significant genetic correlations of EA (rg = -0.22, p = 5.07E-05), cognitive performance (rg = -0.27, p = 2.44E-05), and intelligence (rg = -0.30, p = 3.00E-04) with AD, and a causal relationship between EA and AD (OR = 0.74, 95% CI: 0.58-0.94, p = 0.013). We identified 13 shared loci at conjFDR <0.01, of which five were novel, and prioritized three causal genes. These findings inform early prevention strategies for AD.

Genetically Determined Rheumatoid Arthritis May Not Affect Heart Failure: Insights from Mendelian Randomization Study

Background

Evidence from observational epidemiological studies indicated that rheumatoid arthritis (RA) increased the risk of heart failure (HF). However, there is a possibility that the correlation is not explained as a causative role for RA in the pathogenesis of HF. A two-sample Mendelian randomization (MR) framework was designed to explore the potential etiological role of RA in HF to identify the target to improve the burden of HF disease.

Methods

To assess the causal association between RA and HF, we analyzed summary statistics from genome-wide association studies (GWASs) for individuals of European descent. Genetic instruments for RA were identified at a genome-wide significance threshold (p < 5 × 10-8). Corresponding data were obtained from a GWAS meta-analysis (95,524 cases and 1,270,968 controls) to identify genetic variants underlying HF. MR estimates were pooled using the inverse variance weighted method. Complementary analyses were conducted to assess the robustness of the results.

Results

There was no evidence of a causal association between genetically predicted RA and HF [odds ratio (OR), 1.00; 95% confidence interval (CI), 0.99-1.02; P = 0.60]. Various sensitivity analyses suggested no pleiotropy detected (all p > 0.05).

Conclusion

Our findings did not support the causal role of RA in the etiology of HF. As such, therapeutics targeted at the control of RA may have a lower likelihood of effectively controlling the occurrence of HF.

Rheumatoid arthritis increases the risk of heart failure-current evidence from genome-wide association studies

Background

Numerous studies have demonstrated that rheumatoid arthritis (RA) is related to increased incidence of heart failure (HF), but the underlying association remains unclear. In this study, the potential association of RA and HF was clarified using Mendelian randomization analysis.

Methods

Genetic tools for RA, HF, autoimmune disease (AD), and NT-proBNP were acquired from genome-wide studies without population overlap. The inverse variance weighting method was employed for MR analysis. Meanwhile, the results were verified in terms of reliability by using a series of analyses and assessments.

Results

According to MR analysis, its genetic susceptibility to RA may lead to increased risk of heart failure (OR=1.02226, 95%CI [1.005495-1.039304], P=0.009067), but RA was not associated with NT-proBNP. In addition, RA was a type of AD, and the genetic susceptibility of AD had a close relation to increased risk of heart failure (OR=1.045157, 95%CI [1.010249-1.081272], P=0.010825), while AD was not associated with NT-proBNP. In addition, the MR Steiger test revealed that RA was causal for HF and not the opposite (P = 0.000).

Conclusion

The causal role of RA in HF was explored to recognize the underlying mechanisms of RA and facilitate comprehensive HF evaluation and treatment of RA.

The Association Between Rheumatoid Arthritis and Atrial Fibrillation: Epidemiology, Pathophysiology and Management

Atrial fibrillation (AF) is the most common cardiac arrhythmia with a significant increase in morbidity and mortality worldwide. Rheumatoid arthritis (RA), as a systemic inflammatory disease, affecting 0.5-1.0% of the adult population, is associated with increased incidence of cardiac arrhythmias such as AF. Several epidemiologic studies find that the risk of AF is increased in RA when compared with the general population. Other studies are inconsistent. Considering that inflammation plays an important role in AF, RA may be involved in the occurrence and development of AF. This review summarizes the epidemiology, pathophysiology, and management of AF in patients with RA.

Genetic correlation, causal relationship, and shared loci between vitamin D and COVID-19: A genome-wide cross-trait analysis

Observational studies have shown that vitamin D supplementation reduces the risk of COVID-19 infection, yet little is known about the shared genomic architectures between them. Leveraging large-scale genome-wide association study (GWAS) summary statistics, we investigated the genetic correlation and causal relationship between genetically determined vitamin D and COVID-19 using linkage disequilibrium score regression and Mendelian randomization (MR) analyses, and conducted a cross-trait GWAS meta-analysis to identify the overlapping susceptibility loci of them. We observed a significant genetic correlation between genetically predicted vitamin D and COVID-19 (r_g  = -0.143, p = 0.011), and the risk of COVID-19 infection would decrease by 6% for every 0.76 nmol L^-1 increase of serum 25 hydroxyvitamin D (25OHD) concentrations in generalized MR (OR = 0.94, 95% CI: 0.89-0.99, p = 0.019). We identified rs4971066 (EFNA1) as a risk locus for the joint phenotype of vitamin D and COVID-19. In conclusion, genetically determined vitamin D is associated with COVID-19. Increased levels of serum 25OHD concentration may benefit the prevention and treatment of COVID-19.

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.

Does Having Rheumatoid Arthritis Increase the Dose of Depression Medications? A Mendelian Randomization Study

BACKGROUND

Rheumatoid arthritis (RA) increases the risk of depression. However, studies on the effects of RA on the dose of depression medications are limited. Therefore, in this study, we used two-sample Mendelian randomization (MR) to explore whether RA increases the dose of depression medications and gain a more comprehensive understanding of the relationship between RA and depression.

METHODS

Two-sample MR was used to evaluate the causal effect of RA on the dose of depression medications. The aggregated data on RA originated from extensive genome-wide association studies (GWASs) of European descent (14,361 cases and 42,923 controls). The summary GWAS data for the dose of depression medications were derived from the FinnGen consortium (58,842 cases and 59,827 controls). Random effects inverse-variance weighted (IVW), MR-Egger regression, weighted median, and fixed effects IVW methods were used for the MR analysis. Random effects IVW was the primary method. The heterogeneity of the MR results was detected using the IVW Cochran's Q test. The pleiotropy of the MR results was detected using MR-Egger regression and the MR pleiotropy residual sum and outlier (MR-PRESSO) test. Finally, a leave-one-out analysis was performed to determine whether the MR results were affected by a specific single-nucleotide polymorphism (SNP).

RESULTS

The primary method, random effects IVW, revealed that genetically predicted RA had a positive causal association with the dose of depression medications (Beta, 0.035; 95% confidence interval (CI), 0.007-0.064; p = 0.015). The IVW Cochran's Q test results revealed no heterogeneity in the MR analysis (p > 0.05). The MR-Egger regression and MR-PRESSO tests revealed that there was no pleiotropy in our MR analysis. The leave-one-out analysis confirmed that a single SNP did not affect the MR results, indicating the study's robustness.

CONCLUSION

Using MR techniques, we discovered that having RA increases the dose of depression medications; however, the exact mechanisms and pathways still need to be further explored.

Genetic link between rheumatoid arthritis and autoimmune liver diseases: A two-sample Mendelian randomization study

BACKGROUND

An association between rheumatoid arthritis (RA) and autoimmune liver diseases (AILDs) was found in observational studies. However, neither the direction nor the cause-effect chain was clear. This study aimed to assess the causal associations between AILDs and RA.

METHODS

We performed a two-sample Mendelian randomization (MR) analysis. Following a strict assessment, genome-wide association study (GWAS) datasets were used to select potential candidate single-nucleotide polymorphisms. The inverse-variance weighted (IVW) was used as the primary analysis approach, supplemented with four sensitive analysis methods applied to assess the robustness of the results.

RESULTS

We discovered that a genetically increased primary biliary cholangitis (PBC) risk had a positive causal effect on RA (IVW OR=1.149, 95% CI=1.063-1.241, P<0.001). According to the MR-Egger regression, horizontal pleiotropy was unlikely to impact causality (intercept = -0.028, P = 0.263). Using the leave-one-out strategy, sensitivity studies revealed that the MR analysis results were robust and reliable. Genetically determined primary sclerosing cholangitis (PSC) was not linked with the risk of RA (IVW OR=1.071, 95%CI=0.984-1.166, P = 0.111). The results of the MR analysis were further validated by sensitivity analyses utilizing the leave-one-out approach. In the other direction, there was no causal relationship between RA and PBC (OR=1.132, 95% CI=0.881-1.454, P = 0.333) or PSC (OR=1.067, 95% CI=0.891-1.279, P = 0.088).

CONCLUSIONS

Using a two-sample MR analysis, we investigated the relationship between AILDs and RA and revealed first that PBC increases the risk of RA. Large-scale cross-disease GWAS are required to further illuminate the genomic landscape of AILDs and RA.

FEATURES OF THE DAILY PROFILE OF ARTERIAL BLOOD PRESSURE IN PATIENTS WITH RHEUMATOID ARTHRITIS IN COMBINATION WITH ARTERIAL HYPERTENSION

OBJECTIVE

The aim: To determine the features of daily shifts in blood pressure (BP), the influence of the presence of rheumatoid arthritis (RA) on BP control and identify factors that affect BP among patients with RA in combination with resistant hypertension (RH).

PATIENTS AND METHODS

Materials and methods: All material for writing this scientific work were the results of a comprehensive survey of 201 people with RH and RA, hypertension (H) and RA, RA without H, H without RA and relatively healthy individuals. A laboratory study was performed: rheumatoid factor, C-reactive protein (CRP), K+ serum, and creatinine levels. All patients underwent office BP measurement and ambulatory BP monitoring for 24 hours. Statistical processing of the study results was carried out using "IBM SPSS Statistics 22".

RESULTS

Results: Among patients with RA in combination with RH non-dippers (38.7%) are the most common type of BP profile. Patients with RH in combination with RA are characterized by an increase in BP more at night (p <0.003), which corresponds to the high frequency of night-peackers (17.7%). The presence of RA determines worse control of diastolic BP (p <0.01) and more vascular overload on organs and systems during the night (p <0.05).

CONCLUSION

Conclusions: An increase in BP in patients with RA in combination with RH is more significant at night, characterized by poorer BP control and greater vascular load at night indicating the need for tighter control of BP during sleep. Non-dippers are most often detected among patients with RA in combination with RH, which is prognostically unfavorable for the development of nocturnal "vascular accidents".

Assessment of the causal association between celiac disease and cardiovascular diseases

BACKGROUND

Epidemiological studies have reported inconsistent results of the association between celiac disease (CD) and cardiovascular diseases. Moreover, the causality remains largely unknown. Therefore, we aimed to investigate whether CD is causally associated cardiovascular diseases, including ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke, coronary heart disease, myocardial infarction, angina, heart failure, atrial fibrillation, and venous thromboembolism using an mendelian randomization (MR) approach.

METHODS

Summary-level data for CD were derived from a large-sample genome-wide association study (GWAS) including 12,041 CD cases and 12,228 controls of European ancestry. The corresponding data for ischemic stroke (34,217 cases and 406,111 controls), large artery stroke (4,373 cases and 406,111 controls), cardioembolic stroke (7,193 cases and 406,111 controls), small vessel stroke (5,386 cases and 192,662 controls), coronary heart disease (22,233 cases and 64,762 controls), myocardial infarction (11,622 cases and 187,840 controls), angina (18,168 cases and 187,840 controls), heart failure (47,309 cases and 930,014 controls), atrial fibrillation (60,620 cases and 970,216 controls), and venous thromboembolism (9,176 cases and 209,616 controls) were obtained from the IEU GWAS database. We calculated the causal effect using the inverse variance weighted method. Sensitivity analyses and leave-one-out analyses were performed to ensure the consistency and robustness of causal estimates.

RESULTS

The MR inverse variance weighted estimates indicated no causal effect of genetically predicted CD on ischemic stroke (OR = 1.001, 95% CI: 0.984-1.018), large artery stroke (OR = 1.003, 95% CI: 0.961-1.048), cardioembolic stroke (OR = 1.009, 95% CI: 0.977-1.042), small vessel stroke (OR = 1.023, 95% CI: 0.981-1.066), coronary heart disease (OR = 0.995, 95% CI: 0.977-1.013), myocardial infarction (OR = 0.994, 95% CI: 0.959-1.030), angina (OR = 1.006, 95% CI: 0.981-1.032), heart failure (OR = 0.999, 95% CI: 0.982-1.016), atrial fibrillation (OR = 1.000, 95% CI: 0.990-1.011), and venous thromboembolism (OR = 1.001, 95% CI: 0.971-1.032). Sensitivity analyses using the MR-Egger, weighted median, and simple mode methods yielded similar results. No evidence of horizontal pleiotropy was identified (MR Pleiotropy Residual Sum and Outlier global test and MR-Egger intercept with P > 0.05).

CONCLUSION

Our findings do not support a causal contribution of CD itself to ischemic stroke, large artery stroke, cardioembolic stroke, small vessel stroke, coronary heart disease, myocardial infarction, angina, heart failure, atrial fibrillation, and venous thromboembolism risk.

Genetic Liability to Rheumatoid Arthritis in Relation to Coronary Artery Disease and Stroke Risk

OBJECTIVE

To assess the causality of the associations of rheumatoid arthritis (RA) with coronary artery disease (CAD) and stroke using the Mendelian randomization approach.

METHODS

Independent single-nucleotide polymorphisms strongly associated with RA (n = 70) were selected as instrumental variables from a genome-wide association meta-analysis including 14,361 RA patients and 43,923 controls of European ancestry. Summary-level data for CAD, all stroke, any ischemic stroke and its subtypes, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage were obtained from meta-analyses of genetic studies, international genetic consortia, the UK Biobank, and the FinnGen consortium. We obtained summary-level data for common cardiovascular risk factors and related inflammatory biomarkers to assess possible mechanisms.

RESULTS

Genetic liability to RA was associated with an increased risk of CAD and ICH. For a 1-unit increase in log odds of RA, the combined odds ratios were 1.02 (95% confidence interval [1.01, 1.03]; P = 0.003) for CAD and 1.05 (95% confidence interval [1.02, 1.08]; P = 0.001) for ICH. Genetic liability to RA was associated with increased levels of tumor necrosis factor and C-reactive protein (CRP). The association with CAD was attenuated after adjustment for genetically predicted CRP levels. There were no associations of genetic liability to RA with the other studied outcomes.

CONCLUSION

This study found that genetic liability to RA was associated with an increased risk of CAD and ICH and that the association with CAD might be mediated by CRP. The heightened cardiovascular risk should be actively monitored and managed in RA patients, and this may include dampening systemic inflammation.

Systemic Lupus Erythematosus and Cardiovascular Disease: A Mendelian Randomization Study

Background

Previous studies have shown that patients with systemic lupus erythematosus (SLE) tend to have a higher risk of cardiovascular disease (CVD), but the potential causal relationship between genetic susceptibility to SLE and CVD risk is not clear. This study systematically investigated the potential association between genetically determined SLE and the risk of CVD.

Methods

The genetic tools were obtained from genome-wide association studies of SLE and CVD, with no overlap between their participating populations. Mendelian randomization (MR) analysis was performed using inverse variance weighting as the primary method. Simultaneously, a series of repeated analyses, sensitivity analyses, and instrumental variable strength evaluations were performed to verify the reliability of our results.

Results

MR analysis showed that genetic susceptibility to SLE was associated with a higher risk of heart failure (OR=1.025, 95% CI [1.009-1.041], P=0.002), ischemic stroke (OR=1.020, 95% CI [1.005-1.034], P=0.009), and venous thromboembolism (OR=1.001, 95% CI [1.000-1.002], P=0.014). However, genetic susceptibility to SLE was negatively correlated with the risk of type 2 diabetes (OR=0.968, 95% CI [0.947-0.990], P=0.004). Sensitivity analysis found no evidence of horizontal pleiotropy or heterogeneity.

Conclusion

Our MR study explored the causal role of SLE in the etiology of CVD, which would help improve our understanding of the basic disease mechanisms of SLE and provide comprehensive CVD assessment and treatment for SLE patients.