Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.

This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-remitting multiple sclerosis (RRMS) and explore potential therapeutic applications leveraging machine learning (ML). An ensemble approach was developed using differential gene expression analysis and competitive ML methods, interrogating total RNA-sequencing data sets from peripheral whole blood of treatment-naïve patients with RRMS and NMO and healthy individuals. Pathway analysis of candidate biomarkers informed the biological context of disease, transcription factor activity, and small-molecule therapeutic potential. ML models differentiated between patients with NMO and RRMS, with the performance of certain models exceeding 90% accuracy. RNA biomarkers driving model performance were associated with ribosomal dysfunction and viral infection. Regulatory networks of kinases and transcription factors identified biological associations and identified potential therapeutic targets. Small-molecule candidates capable of reversing perturbed gene expression were uncovered. Mitoxantrone and vorinostat-two identified small molecules with previously reported use in patients with NMO and experimental autoimmune encephalomyelitis-reinforced discovered expression signatures and highlighted the potential to identify new therapeutic candidates. Putative RNA biomarkers were identified that accurately distinguish NMO from RRMS and healthy individuals. The application of multivariate approaches in analysis of RNA-sequencing data further enhances the discovery of unique RNA biomarkers, accelerating the development of new methods for disease detection, monitoring, and therapeutics. Integrating biological understanding further enhances detection of disease-specific signatures and possible therapeutic targets.

Influence of social determinants of health and county vaccination rates on machine learning models to predict COVID-19 case growth in Tennessee.

INTRODUCTION: The SARS-CoV-2 (COVID-19) pandemic has exposed health disparities throughout the USA, particularly among racial and ethnic minorities. As a result, there is a need for data-driven approaches to pinpoint the unique constellation of clinical and social determinants of health (SDOH) risk factors that give rise to poor patient outcomes following infection in US communities. METHODS: We combined county-level COVID-19 testing data, COVID-19 vaccination rates and SDOH information in Tennessee. Between February and May 2021, we trained machine learning models on a semimonthly basis using these datasets to predict COVID-19 incidence in Tennessee counties. We then analyzed SDOH data features at each time point to rank the impact of each feature on model performance. RESULTS: Our results indicate that COVID-19 vaccination rates play a crucial role in determining future COVID-19 disease risk. Beginning in mid-March 2021, higher vaccination rates significantly correlated with lower COVID-19 case growth predictions. Further, as the relative importance of COVID-19 vaccination data features grew, demographic SDOH features such as age, race and ethnicity decreased while the impact of socioeconomic and environmental factors, including access to healthcare and transportation, increased. CONCLUSION: Incorporating a data framework to track the evolving patterns of community-level SDOH risk factors could provide policy-makers with additional data resources to improve health equity and resilience to future public health emergencies.

Predictive Modeling of COVID-19 Case Growth Highlights Evolving Demographic Risk Factors in Tennessee and Georgia.

The COVID-19 pandemic has exposed the need to understand the unique risk drivers that contribute to uneven morbidity and mortality in US communities. Addressing the community-specific social determinants of health that correlate with spread of SARS-CoV-2 provides an opportunity for targeted public health intervention to promote greater resilience to viral respiratory infections in the future. Our work combined publicly available COVID-19 statistics with county-level social determinants of health information. Machine learning models were trained to predict COVID-19 case growth and understand the unique social, physical and environmental risk factors associated with higher rates of SARS-CoV-2 infection in Tennessee and Georgia counties. Model accuracy was assessed comparing predicted case counts to actual positive case counts in each county. The predictive models achieved a mean r-squared (R2) of 0.998 in both states with accuracy above 90% for all time points examined. Using these models, we tracked the social determinants of health, with a specific focus on demographics, that were strongly associated with COVID-19 case growth in Tennessee and Georgia counties. The demographic results point to dynamic racial trends in both states over time and varying, localized patterns of risk among counties within the same state. Identifying the specific risk factors tied to COVID-19 case growth can assist public health officials and policymakers target regional interventions to mitigate the burden of future outbreaks and minimize long-term consequences including emergence or exacerbation of chronic diseases that are a direct consequence of infection.

Illuminating an Invisible Epidemic: A Systemic Review of the Clinical and Economic Benefits of Early Diagnosis and Treatment in Inflammatory Disease and Related Syndromes.

Healthcare expenditures in the United States are growing at an alarming level with the Centers for Medicare and Medicaid Services (CMS) projecting that they will reach $5.7 trillion per year by 2026. Inflammatory diseases and related syndromes are growing in prevalence among Western societies. This growing population that affects close to 60 million people in the U.S. places a significant burden on the healthcare system. Characterized by relatively slow development, these diseases and syndromes prove challenging to diagnose, leading to delayed treatment against the backdrop of inevitable disability progression. Patients require healthcare attention but are initially hidden from clinician's view by the seemingly generalized, non-specific symptoms. It is imperative to identify and manage these underlying conditions to slow disease progression and reduce the likelihood that costly comorbidities will develop. Enhanced diagnostic criteria coupled with additional technological innovation to identify inflammatory conditions earlier is necessary and in the best interest of all healthcare stakeholders. The current total cost to the U.S. healthcare system is at least $90B dollars annually. Through unique analysis of financial cost drivers, this review identifies opportunities to improve clinical outcomes and help control these disease-related costs by 20% or more.

Endogenous double-stranded Alu RNA elements stimulate IFN-responses in relapsing remitting multiple sclerosis.

Various sensors that detect double-stranded RNA, presumably of viral origin, exist in eukaryotic cells and induce IFN-responses. Ongoing IFN-responses have also been documented in a variety of human autoimmune diseases including relapsing-remitting multiple sclerosis (RRMS) but their origins remain obscure. We find increased IFN-responses in leukocytes in relapsing-remitting multiple sclerosis at distinct stages of disease. Moreover, endogenous RNAs isolated from blood cells of these same patients recapitulate this IFN-response if transfected into naïve cells. These endogenous RNAs are double-stranded RNAs, contain Alu and Line elements and are transcribed from leukocyte transcriptional enhancers. Thus, transcribed endogenous retrotransposon elements can co-opt pattern recognition sensors to induce IFN-responses in RRMS.

Longitudinal changes in the expression of IL-33 and IL-33 regulated genes in relapsing remitting MS.

OBJECTIVE: We tested the hypothesis that the expression of IL-33 in MS is dynamic and is likely to reflect the clinical and radiological changes during the course of RRMS. METHODS: MS with either clinical or radiological relapses were recruited for the study and followed for one year. IL-33 and a panel of genes was measured by q PCR and flow cytometry at different time points. RESULTS: Among 22 RRMS patients, 4 patients showed highest levels of IL-33 at the time they were recruited to the study (Month 0); in 14 patients highest levels of IL-33 were seen between 6-11 months after relapse and in 4 patients maximal levels of IL-33 were seen 12 months after relapse. A similar pattern of IL-33 kinetics was seen when IL-33 was measured by flow cytometry in an additional cohort of 12 patients. The timing of the improvement clinically did not correlate with IL-33 expression with highest expression levels either preceding or following clinical recovery. From our whole genome RNA-sequencing data we found a strong correlation between expression levels of IL-33 and a ~2000 mRNA genes. However, none of these genes encoded proteins involved in either innate or adaptive immunity. Rather, many of the genes that correlated highly with IL-33 encoded to proteins involved in DNA repair or mitochondrial function and mRNA splicing pathways. INTERPRETATION: Given the neuro-reparative and remodeling functions attributed to IL-33, it is likely that some of the novel genes we have uncovered may be involved in repair and recovery of the CNS in MS.

Divergent lncRNA GATA3-AS1 Regulates GATA3 Transcription in T-Helper 2 Cells.

Long non-coding RNAs (lncRNAs) possess a diverse array of regulatory functions including activation and silencing of gene transcription, regulation of splicing, and coordinating epigenetic modifications. GATA3-AS1 is a divergent lncRNA gene neighboring GATA3. GATA3 is considered the master regulator of TH2 lineage commitment enabling TH2 effector cells to efficiently transcribe genes encoding cytokines IL-4, IL-5, and IL-13. Here, we show that the GATA3-AS1 lncRNA is selectively expressed under TH2 polarizing conditions and is necessary for efficient transcription of GATA3, IL5, and IL13 genes, while being sufficient for GATA3 transcription. GATA3-AS1 is required for formation of permissive chromatin marks, H3K27 acetylation and H3K4 di/tri-methylation, at the GATA3-AS1-GATA3 locus. Further, GATA3-AS1 binds components of the MLL methyltransferase and forms a DNA-RNA hybrid (R-loop) thus tethering the MLL methyltransferase to the gene locus. Our results indicate a novel regulatory function for a divergent lncRNA and provide new insight into the function of lncRNAs in T helper cell differentiation.

Profiles of Long Noncoding RNAs in Human Naive and Memory T Cells.

We employed whole-genome RNA-sequencing to profile mRNAs and both annotated and novel long noncoding RNAs (lncRNAs) in human naive, central memory, and effector memory CD4+ T cells. Loci transcribing both lineage-specific annotated and novel lncRNA are adjacent to lineage-specific protein-coding genes in the genome. Lineage-specific novel lncRNA loci are transcribed from lineage-specific typical- and supertranscriptional enhancers and are not multiexonic, thus are more similar to enhancer RNAs. Novel enhancer-associated lncRNAs transcribed from the IFNG locus bind the transcription factor NF-κB and enhance binding of NF-κB to the IFNG genomic locus. Depletion of the annotated lncRNA, IFNG-AS1, or one IFNG enhancer-associated lncRNA abrogates IFNG expression by memory T cells, indicating these lncRNAs have biologic function.

Biogenesis and Transcriptional Regulation of Long Noncoding RNAs in the Human Immune System.

The central dogma of molecular biology states that DNA makes RNA makes protein. Discoveries over the last quarter of a century found that the process of DNA transcription into RNA gives rise to a diverse array of functional RNA species, including genes that code for protein and noncoding RNAs. For decades, the focus has been on understanding how protein-coding genes are regulated to influence protein expression. However, with the completion of the Human Genome Project and follow-up ENCODE data, it is now appreciated that only 2-3% of the genome codes for protein-coding gene exons and that the bulk of the transcribed genome, apart from ribosomal RNAs, is at the level of noncoding RNA genes. In this article, we focus on the biogenesis and regulation of a distinct class of noncoding RNA molecules termed long, noncoding RNAs in the context of the immune system.

Long noncoding RNAs in T lymphocytes.

Long noncoding RNAs are recently discovered regulatory RNA molecules that do not code for proteins but influence a vast array of biologic processes. In vertebrates, the number of long noncoding RNA genes is thought to greatly exceed the number of protein-coding genes. It is also thought that long noncoding RNAs drive the biologic complexity observed in vertebrates compared with that in invertebrates. Evidence of this complexity has been found in the T-lymphocyte compartment of the adaptive immune system. In the present review, we describe our current level of understanding of the expression of specific long or large intergenic or intervening long noncoding RNAs during T-lymphocyte development in the thymus and differentiation in the periphery and highlight the mechanisms of action that specific long noncoding RNAs employ to regulate T-lymphocyte function, both in vitro and in vivo.

Long non-coding RNAs in innate and adaptive immunity.

Long noncoding RNAs (lncRNAs) represent a newly discovered class of regulatory molecules that impact a variety of biological processes in cells and organ systems. In humans, it is estimated that there may be more than twice as many lncRNA genes than protein-coding genes. However, only a handful of lncRNAs have been analyzed in detail. In this review, we describe expression and functions of lncRNAs that have been demonstrated to impact innate and adaptive immunity. These emerging paradigms illustrate remarkably diverse mechanisms that lncRNAs utilize to impact the transcriptional programs of immune cells required to fight against pathogens and maintain normal health and homeostasis.

Cutting Edge: Chronic NF-κB Activation in CD4+ T Cells in Rheumatoid Arthritis Is Genetically Determined by HLA Risk Alleles.

Of identified genetic variants, HLA polymorphisms confer the greatest risk for developing autoimmune diseases, including rheumatoid arthritis (HLA-DRB1*04). There are strong influences of HLA polymorphisms on cell type-specific gene expression in B cells and monocytes. Their influence on gene expression in CD4(+) T cells is not known. We determined transcript and proteins levels of target genes in lymphocyte/monocyte subsets in healthy controls and rheumatoid arthritis subjects as a function of HLA-DRB1*04 haplotype. We identified gene expression dependent on HLA-DRB1*04 genotype in CD4(+) T cells. NF-κB activity in CD4(+) T cells was also dependent on HLA-DRB1*04 genotype, and blocking HLA-DR inhibited NF-κB activity in CD4(+) T cells and normalized gene expression, as did pharmacologic inhibition of NF-κB. We conclude that interactions between TCR and MHC class II encoded by HLA-DRB1*04 create a proinflammatory "hum" altering CD4(+) T cell phenotype.

Expression and functions of long noncoding RNAs during human T helper cell differentiation.

Long noncoding RNAs (lncRNAs) regulate an array of biological processes in cells and organ systems. Less is known about their expression and function in lymphocyte lineages. Here we have identified >2000 lncRNAs expressed in human T-cell cultures and those that display a TH lineage-specific pattern of expression and are intragenic or adjacent to TH lineage-specific genes encoding proteins with immunologic functions. One lncRNA cluster selectively expressed by the effector TH2 lineage consists of four alternatively spliced transcripts that regulate the expression of TH2 cytokines, IL-4, IL-5 and IL-13. Genes encoding this lncRNA cluster in humans overlap the RAD50 gene and thus are contiguous with the previously described TH2 locus control region (LCR) in the mouse. Given its genomic synteny with the TH2-LCR, we refer to this lncRNA cluster as TH2-LCR lncRNA.

Defective structural RNA processing in relapsing-remitting multiple sclerosis.

BACKGROUND: Surveillance of integrity of the basic elements of the cell including DNA, RNA, and proteins is a critical element of cellular physiology. Mechanisms of surveillance of DNA and protein integrity are well understood. Surveillance of structural RNAs making up the vast majority of RNA in a cell is less well understood. Here, we sought to explore integrity of processing of structural RNAs in relapsing remitting multiple sclerosis (RRMS) and other inflammatory diseases. RESULTS: We employed mononuclear cells obtained from subjects with RRMS and cell lines. We used quantitative-PCR and whole genome RNA sequencing to define defects in structural RNA surveillance and siRNAs to deplete target proteins. We report profound defects in surveillance of structural RNAs in RRMS exemplified by elevated levels of poly(A) + Y1-RNA, poly(A) + 18S rRNA and 28S rRNAs, elevated levels of misprocessed 18S and 28S rRNAs and levels of the U-class of small nuclear RNAs. Multiple sclerosis is also associated with genome-wide defects in mRNA splicing. Ro60 and La proteins, which exist in ribonucleoprotein particles and play different roles in quality control of structural RNAs, are also deficient in RRMS. In cell lines, silencing of the genes encoding Ro60 and La proteins gives rise to these same defects in surveillance of structural RNAs. CONCLUSIONS: Our results establish that profound defects in structural RNA surveillance exist in RRMS and establish a causal link between Ro60 and La proteins and integrity of structural RNAs.

Methotrexate-mediated inhibition of nuclear factor κB activation by distinct pathways in T cells and fibroblast-like synoviocytes.

OBJECTIVES: Nuclear factor κB (NF-κB) is a critical activator of inflammatory processes and MTX is one of the most commonly prescribed DMARDs for treatment of RA. We sought to determine whether MTX inhibited NF-κB activity in RA and in lymphocytes and fibroblast-like synoviocytes (FLSs) and to define underlying mechanisms of action. METHODS: An NF-κB luciferase reporter plasmid was used to measure NF-κB activation across experimental stimuli. Flow cytometry was used to quantify changes in intracellular protein levels, measure levels of reactive oxygen species and determine apoptosis. Quantitative RT-PCR was used to identify changes in MTX target genes. RESULTS: In T cell lines, MTX (0.1 µM) inhibited activation of NF-κB via depletion of tetrahydrobiopterin (BH4) and increased Jun-N-terminal kinase (JNK)-dependent p53 activity. Inhibitors of BH4 activity or synthesis also inhibited NF-κB activation and, similar to MTX, increased JNK, p53, p21 and JUN activity. Patients with RA expressed increased levels of phosphorylated or active RelA (p65) compared with controls. Levels of phosphorylated RelA were reduced in patients receiving low-dose MTX therapy. In contrast, inhibition of NF-κB activation by MTX was not mediated via BH4 depletion and JNK activation in FLSs, but rather was completely prevented by adenosine receptor antagonists. CONCLUSION: Our findings support a model whereby distinct pathways are activated by MTX in T cells and FLSs to inhibit NF-κB activation.

Expression of IL-33 and its epigenetic regulation in Multiple Sclerosis.

We examined the expression of IL-33 as an indicator of an innate immune response in relapsing remitting MS (RRMS) and controls. Based on our previous studies we proposed a link between the expression of IL-33 and IL-33 regulated genes to histone deacetylase (HDAC) activity and in particular HDAC3, an enzyme that plays a role in the epigenetic regulation of a number of genes including those which regulate inflammation. Our studies showed that intracellular expressions of IL-33 and IL-33 regulated genes are increased in patients with RRMS. In addition, following in vitro culture with TLR agonist lipopolysaccharide (LPS), there is increased induction of both IL-33 and HDAC3 in RRMS patients over that seen in controls. Also, culture of PBMC with IL-33 led to the expression of genes which overlapped with that seen in RRMS patients suggesting that the gene expression signature seen in RRMS may be driven by innate immune pathways. Expression of levels of IL-33 but not IL-1ß (another gene regulated by TLR agonists) is completely inhibited by Trichostatin A (TSA) establishing a closer regulation of IL-33 but not IL-1ß with HDAC. These results demonstrate the over expression of innate immune genes in RRMS and offer a causal link between the epigenetic regulation by HDAC and the induction of IL-33.

Methotrexate inhibits NF-κB activity via long intergenic (noncoding) RNA-p21 induction.

OBJECTIVE: To determine interrelationships between the expression of long intergenic (noncoding) RNA-p21 (lincRNA-p21), NF-κB activity, and responses to methotrexate (MTX) in rheumatoid arthritis (RA) by analyzing patient blood samples and cell culture models. METHODS: Expression levels of long noncoding RNA and messenger RNA (mRNA) were determined by quantitative reverse transcription-polymerase chain reaction. Western blotting and flow cytometry were used to quantify levels of intracellular proteins. Intracellular NF-κB activity was determined using an NF-κB luciferase reporter plasmid. RESULTS: Patients with RA expressed reduced basal levels of lincRNA-p21 and increased basal levels of phosphorylated p65 (RelA), a marker of NF-κB activation. Patients with RA who were not treated with MTX expressed lower levels of lincRNA-p21 and higher levels of phosphorylated p65 compared with RA patients treated with low-dose MTX. In cell culture using primary cells and transformed cell lines, MTX induced lincRNA-p21 through a DNA-dependent protein kinase catalytic subunit (DNA PKcs)-dependent mechanism. Deficiencies in the levels of PRKDC mRNA in patients with RA were also corrected by MTX in vivo. Furthermore, MTX reduced NF-κB activity in tumor necrosis factor α-treated cells through a DNA PKcs-dependent mechanism via induction of lincRNA-p21. Finally, we observed that depressed levels of TP53 and lincRNA-p21 increased NF-κB activity in cell lines. Decreased levels of lincRNA-p21 did not alter NFKB1 or RELA transcripts; rather, lincRNA-p21 physically bound to RELA mRNA. CONCLUSION: Our findings support a model whereby depressed levels of lincRNA-p21 in RA contribute to increased NF-κB activity. MTX decreases basal levels of NF-κB activity by increasing lincRNA-p21 levels through a DNA PKcs-dependent mechanism.

Methotrexate induces production of IL-1 and IL-6 in the monocytic cell line U937.

INTRODUCTION: Methotrexate (MTX) has been for decades a standard treatment in a wide range of conditions, from malignancies to rheumatoid arthritis (RA). Despite this long experience, the mechanisms of action of MTX remain incompletely understood. Reported immunologic effects of MTX include induction of increased production of some cytokines, an effect that seems to be at odds with the generally anti-inflammatory effects of this drug in diseases like RA. To further elucidate these immune activities, we examined effects of MTX on the human monocytic cell line U937. METHODS: The U937 cell line was treated in vitro with pharmacologic-range concentrations of MTX and effects on production of interleukin (IL)-1, IL-6 and TNF alpha were measured. Changes in gene expression for IL-1 and IL-6 and specificities in the Jun-N-terminal kinase (JNK) signaling pathway including JNK 1, JNK2, JUN and FOS were also determined. The contribution of NF-kB, folate and adenosine pathways to the observed effects was determined by adding appropriate inhibitors to the MTX cultures. RESULTS: MTX mediated a dose-dependent increase in IL-1 and IL-6 in U937 cells, as measured by secreted proteins and levels of gene expression. The increased cytokine expression was inhibited by addition of parthenolide and folinic acid, but not by caffeine and theophylline, suggesting that NF-kB and folates, but not adenosine, were involved in mediating the observed effects. When U937 cells were cultured with MTX, upregulated expression of JUN and FOS, but not JNK 1 or 2, also was observed. CONCLUSIONS: MTX induces expression of proinflammatory cytokines in U937 monocytic cells. These effects might mediate the known toxicities of MTX including pneumonitis, mucositis and decreased bone mineral density.

Methotrexate increases expression of cell cycle checkpoint genes via JNK activation.

OBJECTIVE: To assess defects in expression of critical cell cycle checkpoint genes and proteins in patients with rheumatoid arthritis (RA) relative to presence or absence of methotrexate (MTX) treatment, and to investigate the role of JNK in induction of these genes by MTX. METHODS: Flow cytometric analysis was used to quantify changes in levels of intracellular proteins, measure reactive oxygen species (ROS), and determine apoptosis in different lymphoid populations. Quantitative reverse transcription-polymerase chain reaction was used to identify changes in cell cycle checkpoint target genes. RESULTS: RA patients expressed reduced baseline levels of MAPK9, TP53, CDKN1A, CDKN1B, CHEK2, and RANGAP1 messenger RNA (mRNA) and JNK total protein. The reduction in expression of mRNA for MAPK9, TP53, CDKN1A, and CDKN1B was greater in patients not receiving MTX than in those receiving low-dose MTX, with no difference in expression levels of CHEK2 and RANGAP1 mRNA between MTX-treated and non-MTX-treated patients. Further, JNK levels were inversely correlated with C-reactive protein levels in RA patients. In tissue culture, MTX induced expression of both p53 and p21 by JNK-2- and JNK-1-dependent mechanisms, respectively, while CHEK2 and RANGAP1 were not induced by MTX. MTX also induced ROS production, JNK activation, and sensitivity to apoptosis in activated T cells. Supplementation with tetrahydrobiopterin blocked these MTX-mediated effects. CONCLUSION: Our findings support the notion that MTX restores some, but not all, of the proteins contributing to cell cycle checkpoint deficiencies in RA T cells, via a JNK-dependent pathway.

Increased sensitivity to apoptosis induced by methotrexate is mediated by JNK.

OBJECTIVE: Low-dose methotrexate (MTX) is an effective therapy for rheumatoid arthritis (RA), yet its mechanism of action is incompletely understood. The aim of this study was to explore the induction of apoptosis by MTX. METHODS: Flow cytometry was performed to assess changes in the levels of intracellular proteins, reactive oxygen species (ROS), and apoptosis. Quantitative polymerase chain reaction was performed to assess changes in the transcript levels of select target genes in response to MTX. RESULTS: MTX did not directly induce apoptosis but rather "primed" cells for markedly increased sensitivity to apoptosis via either mitochondrial or death receptor pathways, by a JNK-dependent mechanism. Increased sensitivity to apoptosis was mediated, at least in part, by MTX-dependent production of ROS, JNK activation, and JNK-dependent induction of genes whose protein products promote apoptosis. Supplementation with tetrahydrobiopterin blocked these MTX-induced effects. Patients with RA who were receiving low-dose MTX therapy expressed elevated levels of the JNK target gene, jun. CONCLUSION: Our results support a model whereby MTX inhibits reduction of dihydrobiopterin to tetrahydrobiopterin, resulting in increased production of ROS, increased JNK activity, and increased sensitivity to apoptosis. The finding of increased jun levels in patients with RA receiving low-dose MTX supports the notion that this pathway is activated by MTX in vivo and may contribute to the efficacy of MTX in inflammatory disease.