Elucidating potential molecular signatures through host-microbe interactions for reactive arthritis and inflammatory bowel disease using combinatorial approach

Gut microbiota in multiple sclerosis and animal models

Multiple sclerosis (MS) is a chronic central nervous system (CNS) neurodegenerative and neuroinflammatory disease marked by a host immune reaction that targets and destroys the neuronal myelin sheath. MS and correlating animal disease models show comorbidities, including intestinal barrier disruption and alterations of the commensal microbiome. It is accepted that diet plays a crucial role in shaping the microbiota composition and overall gastrointestinal (GI) tract health, suggesting an interplay between nutrition and neuroinflammation via the gut-brain axis. Unfortunately, poor host health and diet lead to microbiota modifications that could lead to significant responses in the host, including inflammation and neurobehavioral changes. Beneficial microbial metabolites are essential for host homeostasis and inflammation control. This review will highlight the importance of the gut microbiota in the context of host inflammatory responses in MS and MS animal models. Additionally, microbial community restoration and how it affects MS and GI barrier integrity will be discussed.

Ankylosing spondylitis coexisting with Clonorchis sinensis infection: A case report

BACKGROUND

Ankylosing spondylitis (AS) is a chronic immune-mediated inflammatory disease. The prevailing theory links AS onset to infections in susceptible individuals. Furthermore, infections may impair the immune responses. Numerous studies have investigated links between AS and various infections-bacterial, viral, fungal, and other microorganism infections. However, limited attention has been given to the association between AS and Clonorchis sinensis (C. sinensis) infection.

CASE SUMMARY

A 27-year-old male with a 10-yr history of AS presented to our hospital with inflammatory lower back pain as the primary manifestation. Ten years ago, the patient had achieved a stable condition after treatment with biological agents. However, he experienced a recurrence of lumbosacral pain with an unexplained cause 10 d before hospital admission. A lumbosacral magnetic resonance imaging (MRI) scan revealed bone marrow edema in the left sacroiliac joint, and laboratory indicators were elevated. Moreover, the presence of C. sinensis eggs was detected in the stool. The patient was prescribed praziquantel, resulting in the disappearance of C. sinensis eggs in subsequent routine stool tests and relief from lumbosacral pain. A follow-up MRI scan performed after 4 months revealed a reduction in bone marrow edema around the left sacroiliac joint.

CONCLUSION

C. sinensis infections could potentially trigger the exacerbation of AS. Clinicians should pay attention to investigating the presence of infections.

The bridge of the gut–joint axis: Gut microbial metabolites in rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by joint destruction, synovitis, and pannus formation. Gut microbiota dysbiosis may exert direct pathogenic effects on gut homeostasis. It may trigger the host’s innate immune system and activate the “gut–joint axis”, which exacerbates the RA. However, although the importance of the gut microbiota in the development and progression of RA is widely recognized, the mechanisms regulating the interactions between the gut microbiota and the host immune system remain incompletely defined. In this review, we discuss the role of gut microbiota-derived biological mediators, such as short-chain fatty acids, bile acids, and tryptophan metabolites, in maintaining intestinal barrier integrity, immune balance and bone destruction in RA patients as the bridge of the gut–joint axis.

Quo vadis reactive arthritis?

PURPOSE OF REVIEW

We provide an overview of recent articles which describe new thinking regarding HLA-B27-associated reactive arthritis (ReA), including those additional infection-related arthritides triggered by microbes that often are grouped under the term ReA.

RECENT FINDINGS

With the advent and continuation of the pandemic, an increasing number of cases and case series of post-COVID-19 arthritis have been reported and classified as ReA. Further, arthritis after COVID-19 vaccination is a new entity included within the spectrum of ReA. New causative microorganisms identified in case reports include Clostridium difficile, Mycoplasma pneumoniae, Giardia lamblia, Leptospira , and babesiosis. SARS-CoV-2 is emerging as a significant etiologic agent for apparent ReA.

SUMMARY

It is now clear that comprehensive clinical and laboratory investigations, synovial fluid analyses, and close follow-up of patients all are essential to differentiate ReA from diseases that may present with similar clinical attributes. Further, and importantly, additional research is required to define the wide diversity in causative agents, epidemiology, and rare case presentations of these arthritides. Finally, new classification and diagnostic criteria, and updated treatment recommendations, are essential to the advancement of our understanding of ReA.

Comparison of immune checkpoint inhibitor-induced arthritis and reactive arthritis to inform therapeutic strategy

INTRODUCTION

Immune checkpoint inhibitor-induced inflammatory arthritis (ICI-IA) is a relatively new disease entity caused by ICI agents during cancer therapy. Reactive arthritis (ReA) is a well-known disease entity caused by urogenital or gastrointestinal bacterial infection or pneumonia. In this sense, ICI-IA and ReA are both defined by a reaction to a well-specified causal event. As a result, comparing these diseases may help to determine therapeutic strategies.

METHODS

We compared ICI-IA and ReA with special focus on pharmacological management. Specifically regarding treatment, we conducted a literature search of studies published in the PubMed database. Inclusion criteria were studies on treatment with non-steroidal anti-inflammatory drugs (NSAIDs), glucocorticoids (GC), or disease modifying antirheumatic drugs (DMARDs) in ICI-IA or ReA. During systematic selection, 21 studies evaluating ICI-IA and 14 studies evaluating ReA were included.

RESULTS

In ICI-IA, prospective and retrospective studies have shown effects of non-steroidal anti-inflammatory drugs (NSAIDs), glucocorticoid (GC), sulfasalazine (SSZ), methotrexate (MTX), hydroxychloroquine (HCQ) and TNFi. In ReA, retrospective studies evaluated NSAIDs and GC. A randomized controlled trial reported the effect of SSZ, and a retrospective study reported the effect of MTX and SSZ in combination with tumor necrosis factor alpha inhibition (TNFi). For both entities, small case reports show treatment effects of interleukin 6 receptor inhibition (IL-6Ri).

DISCUSSION

This literature review identified both similarities and differences regarding the pathogenesis and clinical features of ReA and ICI-IA. Studies on treatment reported effectiveness of NSAIDs, GC, MTX, SSZ and TNFi in both diseases. Further, small case reports showed effects of IL-6Ri.

Machine learning based predictive model and systems-level network of host-microbe interactions in post-COVID-19 mucormycosis

Mucormycosis, a rare infection is caused by fungi Mucorales. The affiliation of mucormycosis with Coronavirus disease (COVID-19) is a rising issue of concern in India. There have been numerous case reports of association of rhino-cerebral-orbital, angioinvasive, pulmonary, respiratory and gastrointestinal tract related mucormycosis in patients with history of COVID-19. The immune dysregulation, preposterous use of steroids, interleukin-6-directed therapies and mechanical ventilation in COVID-19 immunocompromised individuals hypothesizes and predisposes to advancement of mucormycosis. The gaps in mode of presentation, disease course, diagnosis and treatment of post-COVID-19 mucormycosis requires critical analysis in order to control its morbidity and incidence and for prevention and management of opportunistic infections in COVID-19 patients.

Our study performs machine learning, systems biology and bioinformatics analysis of post-COVID-19 mucormycosis in India incorporating multitudinous techniques. Text mining identifies candidate characteristics of post-COVID-19 mucormycosis cases including city, gender, age, symptoms, clinical parameters, microorganisms and treatment. The characteristics are incorporated in a machine learning based disease model resulting in predictive potentiality of characteristics of post-COVID-19 mucormycosis. The characteristics are used to create a host-microbe interaction disease network comprising of interactions between microorganism, host-microbe proteins, non-specific markers, symptoms and drugs resulting in candidate molecules. R1A (Replicase polyprotein 1a) and RPS6 (Ribosomal Protein S6) are yielded as potential drug target and biomarker respectively via potentiality analysis and expression in patients. The potential risk factors, drug target and biomarker can serve as prognostic, early diagnostic and therapeutic molecules in post-COVID-19 mucormycosis requiring further experimental validation and analysis on post-COVID-19 mucormycosis cases.

Reactive Arthritis Update: Spotlight on New and Rare Infectious Agents Implicated as Pathogens

Purpose of Review

This article presents a comprehensive narrative review of reactive arthritis (ReA) with focus on articles published between 2018 and 2020. We discuss the entire spectrum of microbial agents known to be the main causative agents of ReA, those reported to be rare infective agents, and those reported to be new candidates causing the disease. The discussion is set within the context of changing disease terminology, definition, and classification over time. Further, we include reports that present at least a hint of effective antimicrobial therapy for ReA as documented in case reports or in double-blind controlled studies. Additional information is included on microbial products detected in the joint, as well as on the positivity of HLA-B27.

Recent Findings

Recent reports of ReA cover several rare causative microorganism such as Neisseria meningitides, Clostridium difficile, Escherichia coli, Hafnia alvei, Blastocytosis, Giardia lamblia, Cryptosporidium, Cyclospora cayetanensis, Entamoeba histolytica/dispar, Strongyloides stercoralis, β-haemolytic Streptococci, Mycobacterium tuberculosis, Mycoplasma pneumoniae, Mycobacterium bovis bacillus Calmette-Guerin, and Rickettsia rickettsii. The most prominent new infectious agents implicated as causative in ReA are Staphylococcus lugdunensis, placenta- and umbilical cord–derived Wharton’s jelly, Rothia mucilaginosa, and most importantly the SARS-CoV-2 virus.

Summary

In view of the increasingly large spectrum of causative agents, diagnostic consideration for the disease must include the entire panel of post-infectious arthritides termed ReA. Diagnostic procedures cannot be restricted to the well-known HLA-B27-associated group of ReA, but must also cover the large number of rare forms of arthritis following infections and vaccinations, as well as those elicited by the newly identified members of the ReA group summarized herein. Inclusion of these newly identified etiologic agents must necessitate increased research into the pathogenic mechanisms variously involved, which will engender important insights for treatment and management of ReA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11926-021-01018-6.