Association Between Inflammation, Incident Heart Failure, and Heart Failure Subtypes in Patients With Rheumatoid Arthritis

Cardiovascular complications of rheumatoid arthritis

PURPOSE OF REVIEW

Rheumatoid arthritis (RA) patients remain at higher cardiovascular (CV) risk compared to non-RA patients, driven by accelerated atherosclerosis, leading to plaque rupture and acute CV events (CVE), including heart failure (HF). It has been hypothesized that chronic inflammation is the main driving force behind such outcomes. We summarize the current evidence supporting this hypothesis, focusing on arterial disease and myocardial disease.

RECENT FINDINGS

RA patients demonstrate higher prevalence of subclinical atherosclerosis (high risk plaque and arterial inflammation) compared to non-RA patients, with RA disease activity correlating independently with CVE and death. Nonischemic HF with preserved ejection fraction (HFpEF) is more common in RA compared to non-RA, with subclinical myocardial structural and functional alterations also more prevalent in RA. HFpEF and myocardial remodeling and dysfunction bear a strong and independent association with inflammatory correlates.

SUMMARY

All of this suggests that inflammation contributes to enhanced risk of CVE in RA. A more accurate and specific CV risk stratification tool for RA, incorporating biomarkers or imaging, is needed. Likewise, more prospective studies outlining the trajectory from preclinical to clinical HF, incorporating biomarkers and imaging, are also needed.

Lipid profile and NT-proBNP changes from pre-clinical to established rheumatoid arthritis: A 12 years follow-up explorative study

OBJECTIVES

The aim of the current study was to explore the changes in lipid and NT-proBNP levels in rheumatoid arthritis (RA) patients through different phases of the disease: from the pre-clinical stage and RA onset up to the treatment phase with biological disease-modifying anti-rheumatic drugs (bDMARDS).

METHODS

Thirty-eight consecutive patients, initially with arthralgia and rheumatoid factor and/or anti-citrullinated protein antibodies without arthritis, who later developed RA and eventually started treatment with bDMARDs, were included. Lipid spectrum and N-terminal pro-brain natriuretic peptide (NT-proBNP) levels were measured longitudinally from several months before diagnosis through treatment with bDMARDs.

RESULTS

From baseline, C-reactive protein (CPR) initially increased sharply, decreasing with the start of biological treatment. Low-density lipoprotein-cholesterol (LDL-c) remained stable, high-density lipoprotein-cholesterol (HDL-c) increased, apolipoprotein A1 (ApoA1 and lipoprotein (a) (Lp(a)), and total cholesterol (TC)/HDL-c ratio and apolipoprotein B (ApoB) decreased during follow-up. NT-proBNP closely followed progression of CRP. TC, LDL-c, TC/HDL-c ratio, ApoA and ApoB inverse correlated with CRP, while Lp(a) positively correlated. HDL-c and triglycerides showed no correlation.

CONCLUSION

Changes in the lipid profile and NT-proBNP in RA patients seem to be related to inflammation, with changes reflecting an increase in CVD risk occurring along with rises in CRP levels. These changes seem to already be present at diagnosis, indicating the need for timely control of inflammation.

Factors associated with incident cardiovascular disease in patients with rheumatoid arthritis: A scoping review

INTRODUCTION

Rheumatoid arthritis (RA) is the most common form of autoimmune inflammatory arthritis and is associated with various comorbidities including cardiovascular disease (CVD). This scoping review summarizes the current evidence on longitudinal cohort studies assessing potential factors associated with the incidence of cardiovascular events among patients with RA.

METHODS

Scopus, PubMed, Ovid MEDLINE and Cochrane databases were used to identify longitudinal cohort studies investigating the incidence of CVD among RA patients. Using predetermined inclusion and exclusion criteria, two reviewers screened and extracted the relevant studies independently to map the existing literature on this topic. The extracted data included study characteristics, demographics, comorbidities, behavioural and RA-related factors.

RESULTS

Thirty-three research papers were included with a mean follow-up duration of 7.8 years. The sample size of the studies ranged from 182 to 4,311,022 subjects, the mean age from 46.1 to 72.3 years, and on average, 34.6% of the participants were male. The following factors were reported to be associated with a higher incidence of CVD in RA patients: older age, male sex, co-morbid hypertension, diabetes, and/or dyslipidemia, the presence of rheumatoid factor (RF) and/or acute phase reactants. Among RA treatments, glucocorticoids were shown to increase CVD incidence while DMARDs, especially methotrexate, were associated with a lower incidence of CVD.

CONCLUSION

This review offers a comprehensive summary of the current literature reporting on risk factors for CVD incidence among RA patients. Future research should focus on the less studied factors, including socioeconomic status, physical inactivity, alcohol consumption, sleep habits and dietary patterns as well as some RA-related factors such as anti-citrullinated protein antibodies and functional impairment.

LATTE: Label-efficient incident phenotyping from longitudinal electronic health records

Electronic health record (EHR) data are increasingly used to support real-world evidence studies but are limited by the lack of precise timings of clinical events. Here, we propose a label-efficient incident phenotyping (LATTE) algorithm to accurately annotate the timing of clinical events from longitudinal EHR data. By leveraging the pre-trained semantic embeddings, LATTE selects predictive features and compresses their information into longitudinal visit embeddings through visit attention learning. LATTE models the sequential dependency between the target event and visit embeddings to derive the timings. To improve label efficiency, LATTE constructs longitudinal silver-standard labels from unlabeled patients to perform semi-supervised training. LATTE is evaluated on the onset of type 2 diabetes, heart failure, and relapses of multiple sclerosis. LATTE consistently achieves substantial improvements over benchmark methods while providing high prediction interpretability. The event timings are shown to help discover risk factors of heart failure among patients with rheumatoid arthritis.

A network medicine approach to study comorbidities in heart failure with preserved ejection fraction

BACKGROUND

Comorbidities are expected to impact the pathophysiology of heart failure (HF) with preserved ejection fraction (HFpEF). However, comorbidity profiles are usually reduced to a few comorbid disorders. Systems medicine approaches can model phenome-wide comorbidity profiles to improve our understanding of HFpEF and infer associated genetic profiles.

METHODS

We retrospectively explored 569 comorbidities in 29,047 HF patients, including 8062 HFpEF and 6585 HF with reduced ejection fraction (HFrEF) patients from a German university hospital. We assessed differences in comorbidity profiles between HF subtypes via multiple correspondence analysis. Then, we used machine learning classifiers to identify distinctive comorbidity profiles of HFpEF and HFrEF patients. Moreover, we built a comorbidity network (HFnet) to identify the main disease clusters that summarized the phenome-wide comorbidity. Lastly, we predicted novel gene candidates for HFpEF by linking the HFnet to a multilayer gene network, integrating multiple databases. To corroborate HFpEF candidate genes, we collected transcriptomic data in a murine HFpEF model. We compared predicted genes with the murine disease signature as well as with the literature.

RESULTS

We found a high degree of variance between the comorbidity profiles of HFpEF and HFrEF, while each was more similar to HFmrEF. The comorbidities present in HFpEF patients were more diverse than those in HFrEF and included neoplastic, osteologic and rheumatoid disorders. Disease communities in the HFnet captured important comorbidity concepts of HF patients which could be assigned to HF subtypes, age groups, and sex. Based on the HFpEF comorbidity profile, we predicted and recovered gene candidates, including genes involved in fibrosis (COL3A1, LOX, SMAD9, PTHL), hypertrophy (GATA5, MYH7), oxidative stress (NOS1, GSST1, XDH), and endoplasmic reticulum stress (ATF6). Finally, predicted genes were significantly overrepresented in the murine transcriptomic disease signature providing additional plausibility for their relevance.

CONCLUSIONS

We applied systems medicine concepts to analyze comorbidity profiles in a HF patient cohort. We were able to identify disease clusters that helped to characterize HF patients. We derived a distinct comorbidity profile for HFpEF, which was leveraged to suggest novel candidate genes via network propagation. The identification of distinctive comorbidity profiles and candidate genes from routine clinical data provides insights that may be leveraged to improve diagnosis and identify treatment targets for HFpEF patients.

Integrative Mendelian randomization reveals the soluble receptor for advanced glycation end products as protective in relation to rheumatoid arthritis

Rheumatoid arthritis (RA) is a risk factor for atherosclerotic cardiovascular diseases (CVD). Given the critical roles of the immune system and inflammatory signals in the pathogenesis of CVD, we hypothesized that interrogation of CVD-related proteins using integrative genomics might provide new insights into the pathophysiology of RA. We utilized two-sample Mendelian randomization (MR) for causal inference between circulating protein levels and RA by incorporating genetic variants, followed by colocalization to characterize the causal associations. Genetic variants from three sources were obtained: those associated with 71 CVD-related proteins measured in nearly 7000 Framingham Heart Study participants, a published genome-wide association study (GWAS) of RA (19 234 cases, 61 565 controls), and GWAS of rheumatoid factor (RF) levels from the UK Biobank (n = 30 565). We identified the soluble receptor for advanced glycation end products (sRAGE), a critical inflammatory pathway protein, as putatively causal and protective for both RA (odds ratio per 1-standard deviation increment in inverse-rank normalized sRAGE level = 0.364; 95% confidence interval 0.342-0.385; P = 6.40 × 10-241) and RF levels (β [change in RF level per sRAGE increment] = - 1.318; SE = 0.434; P = 0.002). Using an integrative genomic approach, we highlight the AGER/RAGE axis as a putatively causal and promising therapeutic target for RA.

Researchers in rheumatology should avoid categorization of continuous predictor variables

BACKGROUND

Rheumatology researchers often categorize continuous predictor variables. We aimed to show how this practice may alter results from observational studies in rheumatology.

METHODS

We conducted and compared the results of two analyses of the association between our predictor variable (percentage change in body mass index [BMI] from baseline to four years) and two outcome variable domains of structure and pain in knee and hip osteoarthritis. These two outcome variable domains covered 26 different outcomes for knee and hip combined. In the first analysis (categorical analysis), percentage change in BMI was categorized as ≥ 5% decrease in BMI, < 5% change in BMI, and ≥ 5% increase in BMI, while in the second analysis (continuous analysis), it was left as a continuous variable. In both analyses (categorical and continuous), we used generalized estimating equations with a logistic link function to investigate the association between the percentage change in BMI and the outcomes.

RESULTS

For eight of the 26 investigated outcomes (31%), the results from the categorical analyses were different from the results from the continuous analyses. These differences were of three types: 1) for six of these eight outcomes, while the continuous analyses revealed associations in both directions (i.e., a decrease in BMI had one effect, while an increase in BMI had the opposite effect), the categorical analyses showed associations only in one direction of BMI change, not both; 2) for another one of these eight outcomes, the categorical analyses suggested an association with change in BMI, while this association was not shown in the continuous analyses (this is potentially a false positive association); 3) for the last of the eight outcomes, the continuous analyses suggested an association of change in BMI, while this association was not shown in the categorical analyses (this is potentially a false negative association).

CONCLUSIONS

Categorization of continuous predictor variables alters the results of analyses and could lead to different conclusions; therefore, researchers in rheumatology should avoid it.

Risk factors associated with relapse after methotrexate dose reduction in patients with rheumatoid arthritis receiving golimumab and methotrexate combination therapy

AIM

To identify risk factors for relapse after methotrexate (MTX) dose reduction in rheumatoid arthritis (RA) patients receiving golimumab (GLM)/MTX combination therapy.

METHOD

Data on RA patients ≥20 years old receiving GLM (50 mg) + MTX for ≥6 months were retrospectively collected. MTX dose reduction was defined as a reduction of ≥12 mg from the total dose within 12 weeks of the maximum dose (≥1 mg/wk average). Relapse was defined as Disease Activity Score in 28 joints using C-reactive protein level (DAS28-CRP) score ≥3.2 or sustained (≥ twice) increase of ≥0.6 from baseline.

RESULTS

A total of 304 eligible patients were included. Among the MTX-reduction group (n = 125), 16.8% of patients relapsed. Age, duration from diagnosis to the initiation of GLM, baseline MTX dose, and DAS28-CRP were comparable between relapse and no-relapse groups. The adjusted odds ratio (aOR) of relapse after MTX reduction was 4.37 (95% CI 1.16-16.38, P = 0.03) for prior use of non-steroidal anti-inflammatory drugs (NSAIDs), and the aORs for cardiovascular disease (CVD), gastrointestinal disease and liver disease were 2.36, 2.28, and 3.03, respectively. Compared to the non-reduction group, the MTX-reduction group had a higher proportion of patients with CVD (17.6% vs 7.3%, P = 0.02) and a lower proportion of prior use of biologic disease-modifying antirheumatic drugs (11.2% vs. 24.0%, P = 0.0076).

CONCLUSION

Attention should be given to RA patients with history of CVD, gastrointestinal disease, liver disease, or prior NSAIDs-use when considering MTX dose reduction to ensure benefits outweigh the risks of relapse.