Chetana Movva

Ms. Chetana Movva


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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Verified
Journal Article
Open access
PDF file
JFJoshua Frank
Joshua Frank
NNNicole Nesterovitch
Nicole Nesterovitch
CMChetana Movva
Chetana Movva
NKNancy Klimas
Nancy Klimas
LNLubov Nathanson
Lubov Nathanson
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex, multi-system disease characterized by a multitude of symptoms across various organ systems. Diagnosis has relied heavily on heterogeneous clinical symptom presentation and evolving case definitions, with treatment focused on addressing presenting symptoms due to the paucity of validated biomarkers. Meanwhile, advances have been made in understanding the underlying pathophysiology through strong epidemiologic, clinical, and basic science studies. This narrative review synthesizes recent advances that are likely to drive a shift in understanding from symptom-based classification toward a molecularly defined understanding of the disease. This shift in understanding will likely provide the foundation for future research efforts focused on targeting diagnosis and treatment more effectively. Specifically, we reference the identification of rare genetic risk variants through the HEAL2 deep learning framework, the large-scale DecodeME genome-wide association study, and dynamic epigenetic markers of disease state. In addition, the findings revealed the downstream consequences of this genetic and epigenetic priming: chronic innate immune activation, CD8+ T cell exhaustion characterized by upregulation of the exhaustion-driving transcription factors Thymocyte Selection-Associated HMG Box (TOX) and Eomesodermin (EOMES), and a cellular energy crisis centered on mitochondrial dysfunction. Furthermore, results of recent studies have revealed sex-specific transcriptomic and proteomic signatures of maladaptive recovery. We also highlight the role of machine learning and artificial intelligence integrations in translating high-dimensional multi-omics data into actionable biological insights, including the identification of monocyte subsets via Positive Unlabeled Learning, circulating cell-free RNA diagnostic signatures, and integrated multi-modal disease models such as BioMapAI. The combination of these findings, which highlight multiple identifiable mechanisms of molecular activity, support the feasibility of molecular subtyping, precision diagnostics, and targeted therapeutic strategies for ME/CFS.

Verified
Journal Article
Open access
PDF file
LTLily Tehrani
Lily Tehrani
CMChetana Movva
Chetana Movva
JFJoshua Frank
Joshua Frank
SNStephanie Nagy
Stephanie Nagy
RDRiya Davar
Riya Davar
LNLubov Nathanson
Lubov Nathanson
Gulf War Illness (GWI) is a neuroinflammation- and immune-dysfunction-related chronic disease. Corticosteroids, a class of steroid hormones with potent anti-inflammatory and immunosuppressive properties, have been studied for their role in GWI pathophysiology. Eight corticosteroid effect studies were evaluated in this systematic review. Preclinical models showed exacerbation of neuroinflammation, oxidative stress, and epigenetic changes with exposure to CORT in addition to Gulf War neurotoxicants, which induced pro-inflammatory cytokine expression (Tumor Necrosis Factor Alpha (TNF-α), Interleukin-6 (IL-6), C-C motif chemokine ligand 2 (CCL2)). Such findings suggest that corticosteroids can exacerbate symptoms of GWI and need further clinical research to clarify their role in neuroinflammatory processes.