Non-Coding RNAs in the Etiology and Control of Major and Neglected Human Tropical Diseases

A systematic review and meta-analysis of circulating serum and plasma microRNAs in TB diagnosis

BACKGROUND

Tuberculosis (TB) ranks as the second leading cause of death globally among all infectious diseases. This problem is likely due to the lack of biomarkers to differentiate the heterogeneous spectrum of infection. Therefore, the first step in solving this problem is to identify biomarkers to distinguish the different disease states of an individual and treat them accordingly. Circulating microRNA (miRNA) biomarkers are promising candidates for various diseases. In fact, we are yet to conceptualize how miRNA expression influences and predicts TB disease outcomes. Thus, this systematic review and meta-analysis aimed to assess the diagnostic efficacy of circulating miRNAs in Latent TB (LTB) and Active Pulmonary TB (PTB).

METHODS

Literature published between 2012 and 2021 was retrieved from PubMed, Web of Science, Cochrane, Scopus, Embase, and Google Scholar. Articles were screened based on inclusion and exclusion criteria, and their quality was assessed using the QUADAS-2 tool. Funnel plots and forest plots were generated to assess the likelihood of study bias and heterogeneity, respectively.

RESULTS

After the screening process, seven articles were selected for qualitative analysis. The study groups, which consisted of Healthy Control (HC) vs. TB and LTB vs. TB, exhibited an overall sensitivity of 81.9% (95% CI: 74.2, 87.7) and specificity of 68.3% (95% CI: 57.8, 77.2), respectively. However, our meta-analysis results highlighted two potentially valuable miRNA candidates, miR-197 and miR-144, for discriminating TB from HC. The miRNA signature model (miR197-3p, miR-let-7e-5p, and miR-223-3p) has also been shown to diagnose DR-TB with a sensitivity of 100%, but with a compromised specificity of only 75%.

CONCLUSION

miRNA biomarkers show a promising future for TB diagnostics. Further multicentre studies without biases are required to identify clinically valid biomarkers for different states of the TB disease spectrum.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO (CRD42022302729).

Linking Environmental Chemicals to Neuroinflammation and Autism Spectrum Disorder: Mechanisms and Implications for Prevention

This article explores the potential link between endocrine-disrupting chemicals (EDCs), neuroinflammation, and the development of autism spectrum disorder (ASD). Neuroinflammation refers to the immune system's response to injury, infection, or disease in the central nervous system. Studies have shown that exposure to EDCs, such as bisphenol A and phthalates, can disrupt normal immune function in the brain, leading to chronic or excessive neuroinflammation. This disruption of immune function can contribute to developing neurological disorders, including ASD. Furthermore, EDCs may activate microglia, increasing pro-inflammatory cytokine production and astroglia-mediated oxidative stress, exacerbating neuroinflammation. EDCs may also modulate the epigenetic profile of cells by methyltransferase expression, thereby affecting neurodevelopment. This article also highlights the importance of reducing exposure to EDCs and advocating for policies and regulations restricting their use. Further research is needed to understand better the mechanisms underlying the link between EDCs, neuroinflammation, and ASD and to develop new treatments for ASD.

Long noncoding RNAs as potential diagnostic biomarkers for diabetes mellitus and complications: A systematic review and meta-analysis

AIMS

Long noncoding RNAs (lncRNAs) may be associated with the development of type 2 diabetes mellitus and its complications; however, the findings remain controversial. We aimed to synthesize the available data to assess the diagnostic utility of lncRNAs for identification of type 2 diabetes mellitus and its consequences.

MATERIALS AND METHODS

We performed a systematic review and meta-analysis, searching PubMed, Embase, and Web of Science for articles published from September 11, 2015 to December 27, 2022. We evaluated human case-control or cohort studies on differential lncRNA expression in type 2 diabetes mellitus or its associated comorbidities. We excluded studies if they were non-peer reviewed or published in languages other than English. From 2387 identified studies, we included 17 (4685 participants).

RESULTS

Analysis of the pooled data showed that lncRNAs had a diagnostic area under the curve (AUC) of 0.84 (95% CI: 0.80-0.87), with a sensitivity of 0.79 (95% CI: 0.74-0.83) and a specificity of 0.75 (95% CI: 0.69-0.80). LncRNAs had an AUC of 0.65 for the diagnosis of prediabetes, with 82% sensitivity and 65% specificity.

CONCLUSIONS

LncRNAs may be promising diagnostic markers for type 2 diabetes mellitus and its complications.

Pulmonary tuberculosis biomarker miR-215-5p inhibits autophagosome-lysosome fusion in macrophages

The normal autophagy flux is beneficial for the rapid elimination of phagocytic pathogens by macrophages. However, Mycobacterium tuberculosis interferes with the autophagy flux of macrophages to weaken their immune function and evade immune surveillance. In this study, we found that miRNA-215-5p was downregulated in tuberculosis patients. A potential diagnostic model for tuberculosis was established by combining miRNA-215-5p with three others differentially expressed microRNAs (miRNA-145-5p, miRNA-486-5p and miRNA-628-3p). Furthermore, we discovered that the up-regulated miRNA-215-5p could inhibit the maturation of autophagy by preventing the fusion of autophagosomes with lysosomes in macrophages. The role of TB-specific miRNA-215-5p in inhibiting auto-lysosome formation provides evidence of its potential role in Host-directed therapy for tuberculosis.

LncRNA Linc00173 may be a potential prognostic biomarker in human solid tumors: a meta-analysis and bioinformatics analysis

Despite advances in diagnostic techniques and treatments, cancer remains one of the leading causes of death worldwide.Therefore, finding new biomarkers and therapeutic targets is crucial for improving the diagnosis and treatment of human cancer.LncRNA Linc00173 is a newly identified tumor marker, and in this study, we aimed to explore the relationship between Linc00173 and clinicopathological features and patient prognosis. By using The Cochrane Library, EMbase, Web of Science, PubMed, OVID, we conducted a complete and thorough literature search from its inception to November 10, 2022.Meta-analysis was performed using Stata SE16.0 software. Nine studies involving 1102 patients were included.Meta-analysis showed that the overexpression of Linc00173 was significantly associated with poorer OS (HR = 1.76,95%CI:1.36-2.26, P < 0.001) and shorter DFS (HR = 1.89, 95%CI:1.49-2.40,P < 0.001),and was significantly associated with gender (male) (OR = 1.31,95% CI:1.01-1.69, P = 0.042), tumor size (large) (OR = 1.34,95% CI:1.01-1.78, P = 0.045), and lymph node metastasis (positive) (OR = 1.72,95% CI:1.03-2.88, P = 0.038). Overexpression of Linc00173 is associated with poor prognosis in cancer patients and is a potential prognostic biomarker and therapeutic target.

SHIP1 modulates antimalarial immunity by bridging the crosstalk between type I IFN signaling and autophagy

Stringent control of the type I interferon (IFN-I) signaling is critical for host immune defense against infectious diseases, yet the molecular mechanisms that regulate this pathway remain elusive. Here, we show that Src homology 2 containing inositol phosphatase 1 (SHIP1) suppresses IFN-I signaling by promoting IRF3 degradation during malaria infection. Genetic ablation of Ship1 in mice leads to high levels of IFN-I and confers resistance to Plasmodium yoelii nigeriensis (P.y.) N67 infection. Mechanistically, SHIP1 promotes the selective autophagic degradation of IRF3 by enhancing K63-linked ubiquitination of IRF3 at lysine 313, which serves as a recognition signal for NDP52-mediated selective autophagic degradation. In addition, SHIP1 is downregulated by IFN-I-induced miR-155-5p upon P.y. N67 infection and severs as a feedback loop of the signaling crosstalk. This study reveals a regulatory mechanism between IFN-I signaling and autophagy, and verifies SHIP1 can be a potential target for therapeutic intervention against malaria and other infectious diseases. IMPORTANCE Malaria remains a serious disease affecting millions of people worldwide. Malaria parasite infection triggers tightly controlled type I interferon (IFN-I) signaling that plays a critical role in host innate immunity; however, the molecular mechanisms underlying the immune responses are still elusive. Here, we discover a host gene [Src homology 2-containing inositol phosphatase 1 (SHIP1)] that can regulate IFN-I signaling by modulating NDP52-mediated selective autophagic degradation of IRF3 and significantly affect parasitemia and resistance of Plasmodium-infected mice. This study identifies SHIP1 as a potential target for immunotherapies in malaria and highlights the crosstalk between IFN-I signaling and autophagy in preventing related infectious diseases. SHIP1 functions as a negative regulator during malaria infection by targeting IRF3 for autophagic degradation.

miR-27a-5p alleviates periodontal inflammation by targeting phosphatase and tensin homolog deleted on chromosome ten

INTRODUCTION

MicroRNAs (miRNAs), a type of non-coding RNA, have been demonstrated to be essential posttranscriptional modulators in oral diseases and inflammatory responses. However, the specific role of miR-27a-5p in periodontitis requires further investigation. In this study, we used both cellular and animal models to determine how miR-27a-5p affects the pathogenesis of periodontitis and its associated biological functions.

METHODS

Quantitative real-time polymerase chain reaction and western blotting were used to analyze the expression of cytokines, phosphatase and tensin homolog deleted on chromosome ten (PTEN), and miR-27a-5p transcription. Investigation of alveolar bone resorption and inflammation of the periodontium in ligature-induced periodontitis in mice was performed using micro-computed tomography (micro-CT), hematoxylin-eosin (HE) staining, and tartrate-resistant acid phosphatase (TRAP) staining. The binding of miR-27a-5p and PTEN was predicted using the TargetScan database and experimentally confirmed using dual luciferase reporter gene assays.

RESULTS

The inflamed gingiva showed lower levels of miR-27a-5p. Macrophages from miR-27a-5p^-/- mice produced much higher quantities of pro-inflammatory cytokines owing to the stimulation of Porphyromonas gingivalis lipopolysaccharide, and miR-27a-5p^-/- mice with ligature-induced periodontitis also exhibited more severe alveolar bone resorption and damage to the periodontium. Target validation assays identified PTEN as a direct target of bona. Blocking PTEN expression partially reduced inflammation, both in vitro and in vivo.

CONCLUSIONS

miR-27a-5p alleviated the inflammatory response in periodontitis by targeting PTEN.

Advances in computational frameworks in the fight against TB: The way forward

Around 1.6 million people lost their life to Tuberculosis in 2021 according to WHO estimates. Although an intensive treatment plan exists against the causal agent, Mycobacterium Tuberculosis, evolution of multi-drug resistant strains of the pathogen puts a large number of global populations at risk. Vaccine which can induce long-term protection is still in the making with many candidates currently in different phases of clinical trials. The COVID-19 pandemic has further aggravated the adversities by affecting early TB diagnosis and treatment. Yet, WHO remains adamant on its "End TB" strategy and aims to substantially reduce TB incidence and deaths by the year 2035. Such an ambitious goal would require a multi-sectoral approach which would greatly benefit from the latest computational advancements. To highlight the progress of these tools against TB, through this review, we summarize recent studies which have used advanced computational tools and algorithms for-early TB diagnosis, anti-mycobacterium drug discovery and in the designing of the next-generation of TB vaccines. At the end, we give an insight on other computational tools and Machine Learning approaches which have successfully been applied in biomedical research and discuss their prospects and applications against TB.

p50-associated Cyclooxygenase-2 Extragenic RNA (PACER) and Long Non-coding RNA 13 (LNC13) as potential biomarkers for monitoring tuberculosis treatment

Gaps in early and accurate diagnosis, effective drug control, and treatment monitoring are hindering the global eradication effort of tuberculosis. This infectious disease has become the deadliest worldwide before the outbreak of Covid-19. The search for new molecular biomarkers of tuberculosis will help to reverse this trend. Long non-coding RNAs (lncRNAs) have emerged as important regulators of the host immune response to infection, hence their link with the etiology and diagnosis of tuberculosis has attracted some attention from the research community. However, very little is known about their potential for the monitoring of tuberculosis treatment. This study aimed at assessing the potential of two lncRNAs: p50-associated Cyclooxygenase-2 Extragenic RNA (PACER) and Long Non-coding RNA 13 (LNC13) in the monitoring of tuberculosis treatment. This was a cross-sectional study carried out in Douala, Cameroon from December 2020 to August 2021. A quantitative real-time polymerase chain reaction followed by Cq analysis using the Livak method were performed to measure the relative expression levels of PACER and LNC13 in whole blood of healthy controls, patients with active pulmonary tuberculosis at the initiation of treatment, after two, five, and six months into treatment. Receiver Operating Characteristic curves analysis was used to assess the ability of targeted lncRNAs to discriminate among those groups. The study showed that the lncRNAs PACER and LNC13 were significantly upregulated in patients with active pulmonary tuberculosis at the initiation of treatment than in healthy controls. The expression levels of the two lncRNAs were significantly downregulated in patients during the treatment as compared to the active pulmonary tuberculosis patients. However, the expression levels of the lncRNAs PACER and LNC13 in whole blood of patients after six months of treatment were similar to those in healthy controls. Similarly, lncRNAs PACER and LNC13 showed very good performance in distinguishing between active tuberculosis patients and healthy controls as well as in differentiating between newly diagnosed active tuberculosis patients and those under treatment. Interestingly, those lncRNAs could not discriminate healthy controls from patients after six months of treatment. The lncRNAs PACER and LNC13 are therefore potential biomarkers for the monitoring of tuberculosis treatment.

Noncoding RNome as Enabling Biomarkers for Precision Health

Noncoding RNAs (ncRNAs), in the form of structural, catalytic or regulatory RNAs, have emerged to be critical effectors of many biological processes. With the advent of new technologies, we have begun to appreciate how intracellular and circulatory ncRNAs elegantly choreograph the regulation of gene expression and protein function(s) in the cell. Armed with this knowledge, the clinical utility of ncRNAs as biomarkers has been recently tested in a wide range of human diseases. In this review, we examine how critical factors govern the success of interrogating ncRNA biomarker expression in liquid biopsies and tissues to enhance our current clinical management of human diseases, particularly in the context of cancer. We also discuss strategies to overcome key challenges that preclude ncRNAs from becoming standard-of-care clinical biomarkers, including sample pre-analytics standardization, data cross-validation with closer attention to discordant findings, as well as correlation with clinical outcomes. Although harnessing multi-modal information from disease-associated noncoding RNome (ncRNome) in biofluids or in tissues using artificial intelligence or machine learning is at the nascent stage, it will undoubtedly fuel the community adoption of precision population health.

Non-Coding RNAs in Tuberculosis Epidemiology: Platforms and Approaches for Investigating the Genome's Dark Matter

A growing amount of information about the different types, functions, and roles played by non-coding RNAs (ncRNAs) is becoming available, as more and more research is done. ncRNAs have been identified as potential therapeutic targets in the treatment of tuberculosis (TB), because they may be essential regulators of the gene network. ncRNA profiling and sequencing has recently revealed significant dysregulation in tuberculosis, primarily due to aberrant processes of ncRNA synthesis, including amplification, deletion, improper epigenetic regulation, or abnormal transcription. Despite the fact that ncRNAs may have a role in TB characteristics, the detailed mechanisms behind these occurrences are still unknown. The dark matter of the genome can only be explored through the development of cutting-edge bioinformatics and molecular technologies. In this review, ncRNAs' synthesis and functions are discussed in detail, with an emphasis on the potential role of ncRNAs in tuberculosis. We also focus on current platforms, experimental strategies, and computational analyses to explore ncRNAs in TB. Finally, a viewpoint is presented on the key challenges and novel techniques for the future and for a wide-ranging therapeutic application of ncRNAs.