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Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response.
Singh, Priyanka; Srivastava, Ankit; Philip, Lini; Ahuja, Simranpreet Kaur; Rawat, Chitra; Kutum, Rintu; Yadav, Jyoti; Sood, Mamta; Chadda, Rakesh Kumar; Dash, Debasis; Vohora, Divya; Kukreti, Ritushree.
Afiliação
  • Singh P; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
  • Srivastava A; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi 110062, India.
  • Philip L; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India.
  • Ahuja SK; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India.
  • Shivangi; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Department of Biotechnology, Delhi Technological University, Shahbad Daulatpur, Main Bawana Road, New Delhi 110042, India.
  • Rawat C; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
  • Kutum R; Department of Computer Science, Ashoka University, Haryana 131029, India.
  • Yadav J; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India.
  • Sood M; Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India.
  • Chadda RK; Department of Psychiatry, All India Institute of Medical Sciences, Ansari Nagar, New Delhi 110029, India.
  • Dash D; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India.
  • Vohora D; Department of Pharmacology, School of Pharmaceutical Education and Research, Jamia Hamdard, New Delhi 110062, India.
  • Kukreti R; Genomics and Molecular Medicine Unit, Council of Scientific and Industrial Research (CSIR) - Institute of Genomics and Integrative Biology (IGIB), New Delhi 110007, India; Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India. Electronic address: ritus@igib.res.in.
Genomics ; 116(1): 110772, 2024 01.
Article em En | MEDLINE | ID: mdl-38158140
ABSTRACT
Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transtorno Depressivo Maior Limite: Humans Idioma: En Revista: Genomics Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Transtorno Depressivo Maior Limite: Humans Idioma: En Revista: Genomics Ano de publicação: 2024 Tipo de documento: Article