Polygenic risk scores are associated with radiographic progression in patients with rheumatoid arthritis

Genetically transitional disease: conceptual understanding and applicability to rheumatic disease

In genomic medicine, the concept of genetically transitional disease (GTD) refers to cases in which gene mutation is necessary but not sufficient to cause disease. In this Perspective, we apply this novel concept to rheumatic diseases, which have been linked to hundreds of genetic variants via association studies. These variants are in the 'grey zone' between monogenic variants with large effect sizes and common susceptibility alleles with small effect sizes. Among genes associated with rare autoinflammatory diseases, many low-frequency and/or low-penetrance variants are known to increase susceptibility to systemic inflammation. In autoimmune diseases, hundreds of HLA and non-HLA genetic variants have been revealed to be modest- to moderate-risk alleles. These diseases can be reclassified as GTDs. The same concept could apply to many other human diseases. GTD could improve the reporting of genetic testing results, diagnostic yields, genetic counselling and selection of therapy, as well as facilitating research using a novel approach to human genetic diseases.

Pathophysiology and stratification of treatment-resistant rheumatoid arthritis

Early diagnosis and timely therapeutic intervention are clinical challenges of rheumatoid arthritis (RA), especially for treatment-resistant or difficult-to-treat patients. Little is known about the immunological mechanisms involved in refractory RA. In this review, we summarize previous research findings on the immunological mechanisms of treatment-resistant RA. Genetic prediction of treatment-resistant RA is challenging. Patients with and without anti-cyclic citrullinated peptide autoantibodies are considered part of distinct subgroups, especially regarding long-term clinical prognosis and treatment responses. B cells, T cells and other immune cells and fibroblasts are of pathophysiological importance and are associated with treatment responses. Finally, we propose a new hypothesis that stratifies patients with RA into two subgroups with distinct immunological pathologies based on our recent immunomics analysis of RA. One RA subgroup with a favorable prognosis is characterized by increased interferon signaling. Another subgroup with a worse prognosis is characterized by enhanced acquired immune responses. Increases in dendritic cell precursors and diversified autoreactive anti-modified protein antibodies may have pathophysiological roles, especially in the latter subgroup. These findings that improve treatment response predictions might contribute to future precision medicine for RA.

Effectiveness and safety of treat-to-target strategy for methotrexate-naïve rheumatoid arthritis patients >75 years of age

Objectives

To identify differences in effectiveness and safety of a treat-to-target (T2T) strategy comparing late-onset MTX-naïve RA patients (LORA) ≥75 or <75 years of age.

Methods

Treatment was adjusted to target low disease activity with conventional synthetic DMARDs followed by biologic DMARDs (bDMARDs) in LORA ≥75 years (n = 98, mean age 80.0 years) and LORA <75 years (n = 99) with moderate-high disease activity. Achievement of Simplified Disease Activity Index (SDAI) remission at week 156 by non-responder imputation analysis was evaluated as a primary outcome.

Results

LORA ≥75 years had more comorbidities than LORA <75 years, but SDAI and ACPA positivity were similar at baseline. Of the LORA ≥75 years, 70.4% started MTX and 34.1% and 37.1% received a bDMARD at week 52 and 156, respectively (very similar to the LORA <75 years). Glucocorticoid use was more frequent in the LORA ≥75 years than in the LORA <75 years. Comorbidities/adverse events more frequently contributed to the reasons for non-adherence to T2T in the LORA ≥75 than in the LORA <75. At week 156, 32.7% of the LORA ≥75 and 66.7% of the LORA <75 achieved SDAI remission (P < 0.001). The cumulative incidence of serious adverse events (SAEs) over 156 weeks was 42.8% in the LORA ≥75 and 22.1% in the LORA <75. Multivariable analysis indicated an increased risk of SDAI non-remission at week 156 in the LORA ≥75 [odds ratio 2.82 (95% CI 1.29. 6.14)] after adjusting for comorbidities at baseline, non-adherence to T2T and SAEs.

Conclusions

It was more difficult to achieve remission in the LORA ≥75 patients than in the LORA <75 patients due to both poor treatment response and safety issues.

Genome-wide polygenic risk score for rheumatoid arthritis prediction in postmenopausal women

BACKGROUND

Rheumatoid arthritis (RA), a common autoimmune disease, exhibits a vital genetic component. Polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) offer potential utility in predicting disease susceptibility. The present study aimed to develop and validate a PRS for predicting RA risk in postmenopausal women.

METHODS

The study developed a novel PRS using 225,000 genetic variants from a GWAS dataset. The PRS was developed in a cohort of 8967 postmenopausal women and validated in an independent cohort of 6269 postmenopausal women. Among the development cohort, approximately 70% were Hispanic and approximately 30% were African American. The testing cohort comprised approximately 50% Hispanic and 50% Caucasian individuals. Stratification according to PRS quintiles revealed a pronounced gradient in RA prevalence and odds ratios.

RESULTS

High PRS was significantly associated with increased RA risk in individuals aged 60-70 years, ≥ 70 years, and overweight and obese participants. Furthermore, at age 65 years, individuals in the bottom 5% of the PRS distribution have an absolute risk of RA at 30.6% (95% confidence interval = 18.5%-42.6%). The risk increased to 53.8% (95% confidence interval = 42.8%-64.9%) for those in the top 5% of the PRS distribution.

CONCLUSIONS

The PRS developed in the present study is significantly associated with RA risk, showing the potential for early screening of RA in postmenopausal women. This work demonstrates the feasibility of personalized medicine in identifying high-risk individuals for RA, indicating the need for further studies to test the utility of PRS in other populations.

The Application of Genetic Risk Scores in Rheumatic Diseases: A Perspective

Modest effect sizes have limited the clinical applicability of genetic associations with rheumatic diseases. Genetic risk scores (GRSs) have emerged as a promising solution to translate genetics into useful tools. In this review, we provide an overview of the recent literature on GRSs in rheumatic diseases. We describe six categories for which GRSs are used: (a) disease (outcome) prediction, (b) genetic commonalities between diseases, (c) disease differentiation, (d) interplay between genetics and environmental factors, (e) heritability and transferability, and (f) detecting causal relationships between traits. In our review of the literature, we identified current lacunas and opportunities for future work. First, the shortage of non-European genetic data restricts the application of many GRSs to European populations. Next, many GRSs are tested in settings enriched for cases that limit the transferability to real life. If intended for clinical application, GRSs are ideally tested in the relevant setting. Finally, there is much to elucidate regarding the co-occurrence of clinical traits to identify shared causal paths and elucidate relationships between the diseases. GRSs are useful instruments for this. Overall, the ever-continuing research on GRSs gives a hopeful outlook into the future of GRSs and indicates significant progress in their potential applications.

Does polygenic risk for substance-related traits predict ages of onset and progression of symptoms?

BACKGROUND AND AIMS

Genetic risk can influence disease progression. We measured the impact of genetic risk for substance use disorders (SUDs) on substance use onset and progression of symptoms.

DESIGN, SETTING, PARTICIPANTS

Using findings from genome-wide association studies (GWASs) of alcohol use disorder (AUD), opioid use disorder (OUD) and smoking trajectory (SMK) as discovery samples, we calculated polygenic risk scores (PRSs) in a deeply phenotyped independent target sample. Participants in the target sample were recruited from 2000 to 2020 from US inpatient or outpatient settings or through advertisements and comprised 5692 European-ancestry individuals (EUR) (56.2% male) and 4918 African-ancestry individuals (AFR) (54.9% male).

MEASUREMENTS

This study measured age of first substance use, regular use, reported problems and dependence diagnosis and progression from regular use to onset of problems and dependence for alcohol, opioids and smoking. We examined the contribution of PRS to each milestone and progression measure.

FINDINGS

EUR and males reported an earlier onset and shorter progression times than AFR and females, respectively. Among EUR, higher AUD PRS predicted earlier onset and more rapid progression to alcohol-related milestones (P < 0.001). Although the AUD PRS was a stronger moderator of problem onset among females (P = 0.017), it was more predictive of the progression to problems among males (P = 0.005). OUD and SMK PRS in EUR also predicted earlier onset of the respective milestones (P < 0.001). Among AFR, where power is lower due to the smaller discovery sample, AUD PRS predicted age of regular alcohol use (P = 0.039) and dependence (P = 0.001) and progression from regular use to diagnosis (P = 0.045), while SMK PRS predicted earlier age of initiation (P = 0.036).

CONCLUSIONS

Genetic risk for SUDs appears to predict substance use milestones and symptom progression among European-ancestry individuals and, to a lesser extent, African-ancestry individuals.

Matrix Metalloproteinase-9 Level in Synovial Fluid-Association with Joint Destruction in Early Rheumatoid Arthritis

Background and objective: Matrix metalloproteinases (MMPs) are the key enzymes in the pathogenesis of cartilage and joint damage and potentially a new biomarker of the early erosive form of rheumatoid arthritis (RA). Firstly, the study aimed to compare the level of MMP-9 in plasma (PL) and synovial fluid (SF) of patients with RA and osteoarthritis (OA). Secondly, the goal was to examine the association of MMP-9 level in PL and SF with early erosive changes in RA, and finally, to determine the association of MMP-9 level with serological parameters of the disease (rheumatoid factor-RF and anti-citrulline protein antibodies-ACPA). Materials and Methods: A total of 156 subjects were involved in this study (84 patients with RA and 72 patients with OA, who were involved as a control group). MMP-9 level was measured in PL and SF of all subjects by the sandwich enzyme-linked immunosorbent assay (ELISA) method. Standard radiographs of the hands and feet were used to detect joint damage and classification into erosive or non-erosive RA. The Larsen score (LS) was used for the quantitative assessment of joint damage, and its annual change (∆ LS) was used to assess the radiographic progression of the disease. Results: MMP-9 level in PL and SF was significantly higher in RA compared to controls (PL: 19.26 ± 7.54 vs. 14.57 ± 3.11 ng/mL, p< 0.01; SF: 16.17 ± 12.25 vs. 0.75 ± 0.53 ng/mL, p < 0.001) as well as in SF of patients with erosive compared to non-erosive RA (18.43 ± 12.87 vs. 9.36 ± 7.72; p < 0.05). Faster radiographic progression was recorded in erosive compared to non-erosive early RA (11.14 ± 4.75 vs. 6.13 ± 2.72; p < 0.01). MMP-9 level in SF, but not in PL, significantly correlates with the radiographic progression in both erosive and non-erosive RA (ρ = 0.38 and ρ = 0.27). We did not find a significant association between RF and MMP-9 level in early RA, but the ACPA level significantly correlates with MMP-9 level in SF (r = 0.48). Conclusion: The level of MMP-9 in plasma and synovial fluid of patients with RA is significantly higher compared to patients with osteoarthritis. The level of MMP-9 in synovial fluid is significantly higher in erosive than non-erosive early RA. It is significantly associated with the radiographic progression of the disease and the level of anti-citrulline protein antibodies.

Genetic susceptibility to autoimmunity-Current status and challenges

Autoimmune diseases (ADs) often arise from a combination of genetic and environmental triggers that disrupt the immune system's capability to properly tolerate body self-antigens. Familial studies provided the earliest insights into the risk loci of such diseases, while genome-wide association studies (GWAS) significantly broadened the horizons. A drug targeting a prominent pathological pathway can be applied to multiple indications sharing overlapping mechanisms. Advances in genomic technologies used in genetic studies provide critical insights into future research on gene-environment interactions in autoimmunity. This Review summarizes the history and recent advances in the understanding of genetic susceptibility to ADs and related immune disorders, including coronavirus disease 2019 (COVID-19), and their indications for the development of diagnostic or prognostic markers for translational applications.

Genetic basis of defects in immune tolerance underlying the development of autoimmunity

Genetic variants associated with susceptibility to autoimmune disease have provided important insight into the mechanisms responsible for the loss of immune tolerance and the subsequent development of autoantibodies, tissue damage, and onset of clinical disease. Here, we review how genetic variants shared across multiple autoimmune diseases have contributed to our understanding of global tolerance failure, focusing on variants in the human leukocyte antigen region, PTPN2 and PTPN22, and their role in antigen presentation and T and B cell homeostasis. Variants unique to a specific autoimmune disease such as those in PADI2 and PADI4 that are associated with rheumatoid arthritis are also discussed, addressing their role in disease-specific immunopathology. Current research continues to focus on determining the functional consequences of autoimmune disease-associated variants but has recently expanded to variants in the non-coding regions of the genome using novel approaches to investigate the impact of these variants on mechanisms regulating gene expression. Lastly, studying genetic risk variants in the setting of autoimmunity has clinical implications, helping predict who will develop autoimmune disease and also identifying potential therapeutic targets.