Deep immunophenotyping of circulating immune cells in major depressive disorder patients reveals immune correlates of clinical course and treatment response DOI Creative Commons

Fabiola Stolfi,

Claudio Brasso, Davide Raineri

et al.

Brain Behavior & Immunity - Health, Journal Year: 2024, Volume and Issue: 43, P. 100942 - 100942

Published: Dec. 31, 2024

Major Depressive Disorder (MDD) is a widespread psychiatric condition impacting social and occupational functioning, making it leading cause of disability. The diagnosis MDD remains clinical, based on the Diagnostic Statistical Manual Mental Disorders (DSM)-5 criteria, as biomarkers have not yet been validated for diagnostic purposes or predictors treatment response. Traditional strategies often follow one-size-fits-all approach obtaining suboptimal outcomes many patients who fail to experience response recovery. Several studies reported an association between immune system dysregulation, but few focused deep characterization circulating cells, during acute phase MDD. This work aimed at immunophenotyping peripheral blood cells in relapse disorder, identify relevant cell populations clinical monitoring patients. Multiparametric analysis was performed 60 using flow cytometry lymphocytes (naïve/effector, memory, regulatory) myeloid (dendritic monocytes). We studied associations immunophenotype depressive symptoms, working subjective quality life after three months treatment. Multivariate showed that CD4+ terminally differentiated effector memory (TEMRA) were associated with more symptoms particular emphasis anhedonic features worse functioning life. CD8+ TEMRA those related hopelessness. Conversely, ICOS + Tregs low-intensity suicidal ideation, suggestive protective role. Baseline T (EM) negative predictor reduction treatment, whilst plasmacytoid dendritic (pDC) predicting These results confirm involvement demonstrate existence immunological signatures severity major episodes could guide future personalized therapies.

Language: Английский

Genes y depresión: búsqueda de biomarcadores asociados a la depresión en una población joven DOI
Manuel Alejandro Castellano García, Maydelin Lorenzo Díaz

Published: Jan. 16, 2025

INTRODUCCIÓN: La depresión constituye una de las principales causas suicidio personas jóvenes en México, por lo que es importante identificar los biomarcadores asociados a esta enfermedad población joven. El presente artículo revisión sistematizado nos señala propuestos la FDA y NIH, integrando medicina traduccional tecnologías “ómicas”. OBJETIVO: Se realizó un con base metaanálisis literatura científica para delimitación pacientes presentan identificación marcadores biomoleculares más comunes, enfoque el trastorno depresivo mayor sus consecuencias largo plazo. MÉTODO: diseño del estudio observacional, analítico, descriptivo. Para proceso se utilizaron bases datos académicas reconocidas como Google Académico, PubMed, SciELO, Medline Elsevier. filtraron artículos relevantes publicados entre 2020 2024 palabras clave “depresión”, “omics”, “marcadores biomoleculares”, “gen” “jóvenes”; criterios selección relacionados prefijo “omics” características trastornos depresivos “metabolómico, proteómico, transcriptómica, epigenético genómico” excluyendo repetidos otra adultos mayores, niños embarazadas, obtuvieron 16 su estudio. RESULTADOS Y CONCLUSIONES: Los son esenciales biológico, especialmente omics al demostrar estar tan sí propiedades específicas respuesta normal, patógena o reactiva procesos farmacológicos u otras intervenciones terapéuticas, cumple objetivo esencial prevención mentales población, específicamente joven, previene desarrollo patología compleja futuro mayor. Sin embargo, aún encuentran numerosas limitaciones uso debido necesidad investigaciones probar eficacia. PALABRAS CLAVE: Depresión, omics, biomoleculares, gen, jóvenes.

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Advancing Antidepressive Agents: Drug Discovery and Polymer-Based Drug Delivery Systems for Improved Treatment Outcome DOI Creative Commons
Yufei Zhang, Zhiguang Song, Hongxi Zhang

et al.

Biomedicines, Journal Year: 2025, Volume and Issue: 13(5), P. 1081 - 1081

Published: April 29, 2025

Depressive disorder (a subclass of mental disorders) is characterized by persistent affective symptoms. Without timely therapeutic intervention, it leads to clinical deterioration manifested as reduced quality life and may increase suicide risk in severe cases. Given its complex etiology, intertwined with intrinsic factors such genetics environment, impacted various issues first-pass effect blood-brain barrier, the efficacy many antidepressant medications limited for patients. Therefore, delving into exploration novel drugs biomaterials, this review aims offer fresh perspectives that facilitate discovery innovative enhance their outcomes. Notably, highlights polymers’ crucial role enhancing antidepressants’ pharmacological pharmacokinetic properties optimizing parameters, they will undoubtedly become powerful tools improving antidepressive outcomes future research.

Language: Английский

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0
Advances in biomarkers for optic neuritis and neuromyelitis optica spectrum disorders: a multi-omics perspective DOI Creative Commons
Lidong Liu, Kai Guo, Dayong Yang

et al.

Frontiers in Neurology, Journal Year: 2025, Volume and Issue: 16

Published: May 6, 2025

Optic neuritis (ON) and neuromyelitis optica spectrum disorders (NMOSD) are inflammatory neuro-ophthalmological conditions characterized by significant visual impairment diverse clinical manifestations. Advances in diagnostic biomarkers have improved disease identification, including aquaporin-4 immunoglobulin G (AQP4-IgG) myelin oligodendrocyte glycoprotein (MOG-IgG). However, some patients remain biomarker-negative, complicating differential diagnosis personalized treatment. Multi-omics approaches provided valuable insights into critical molecular pathways, novel biomarkers, the shared distinct features of ON NMOSD. This review highlights recent advancements biomarker research for NMOSD, emphasizes potential multi-omics integration, identifies existing challenges, proposes future directions. These findings aim to enhance accuracy, improve prognostic capabilities, support development precision medicine strategies

Language: Английский

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0
Neuroinflammation and Natural Antidepressants: Balancing Fire with Flora DOI Creative Commons
Ana Leonor Pardo Campos Godoy,

Fernanda Fortes Frota,

Larissa Parreira Araújo

et al.

Biomedicines, Journal Year: 2025, Volume and Issue: 13(5), P. 1129 - 1129

Published: May 7, 2025

Background/Objectives: Major depressive disorder (MDD) is a major global health concern that intimately linked to neuroinflammation, oxidative stress, mitochondrial dysfunction, and complicated metabolic abnormalities. Traditional antidepressants frequently fall short, highlighting the urgent need for new, safer, more acceptable therapeutic techniques. Phytochemicals, i.e., natural derived from plants, are emerging as powerful plant-based therapies capable of targeting many pathogenic pathways at same time. Summary: This narrative review synthesizes evidence preclinical clinical studies on efficacy phytochemicals such curcumin, polyphenols, flavonoids, alkaloids in lowering depressed symptoms. Consistent data show these substances have neuroprotective, anti-inflammatory, antioxidant properties, altering neuroimmune interactions, reducing damage, improving resilience. Particularly, polyphenols flavonoids great potential because their capacity penetrate blood–brain barrier, inhibit cytokine activity, encourage neuroplasticity mediated by brain-derived neurotrophic factor (BDNF). Despite promising results, heterogeneity study designs, phytochemical formulations, patient demographics highlights importance thorough, standardized studies. Conclusions: identifies compelling adjuvant or independent depression treatment, providing multimodal mechanisms enhanced tolerability. Additional research into improved dosage, pharmacokinetics, long-term safety, integrative therapy approaches essential. Using phytotherapeutics could considerably improve holistic customized care, encouraging new routes neuroscience psychiatry.

Language: Английский

Citations

0
Technology, Artificial Intelligence, and the Era of Information in Healthcare and Allied Sciences DOI
Sudrita Roy Choudhury, Khusboo Singh,

Samarpita Koner

et al.

IGI Global eBooks, Journal Year: 2025, Volume and Issue: unknown, P. 461 - 490

Published: May 16, 2025

This chapter examines the transformative impact of technology, artificial intelligence (AI), and information proliferation on healthcare allied sciences. It explores advancements in telemedicine, wearable devices, AI applications diagnostics drug discovery. The role big data analytics identifying health trends informing policy is discussed, alongside ethical considerations AI-driven healthcare. also addresses future trends, including genomics-AI integration quantum computing development. overview illuminates how these interconnected forces are reshaping healthcare, driving precision medicine, evolving roles professionals an increasingly tech-driven landscape.

Language: Английский

Citations

0
Microbes and mood: innovative biomarker approaches in depression DOI

Miranda Green,

Madhukar H. Trivedi, Jane A. Foster

et al.

Trends in Molecular Medicine, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 1, 2024

Language: Английский

Citations

0
Combining Clinical Data With Neuro Images to Identify the Treatment Resistant in Depression by NLP DOI
Santosh Reddy,

P. K. Sreelatha,

Ashwini R. Malipatil

et al.

Practice, progress, and proficiency in sustainability, Journal Year: 2024, Volume and Issue: unknown, P. 203 - 220

Published: Oct. 4, 2024

Predicting treatment-resistant depression (TRD) is difficult, even though 21% of individuals with who get therapy do not achieve remission. The purpose this research to use structured data from electronic health records, brain morphology, & natural language processing create a multimodal forecast model for TRD that can be explained. A total 248 patients recently had period were included. Combining topic probability clinical notes separate components-map weights T1-weighted MRI, and chose tabular dataset attributes, TRD-predictive models created. All the used five-fold cross-validation apply XGBoost algorithm. area under receiver's operating characteristic was 0.795 utilized all sources, then MRI together, finally medical records separately. (0.771), (0.763) plus data, (0.729) notes, (0.704)

Language: Английский

Citations

0
RNA Editing Signatures Powered by Artificial Intelligence: A New Frontier in Differentiating Schizophrenia, Bipolar, and Schizoaffective Disorders DOI Open Access

Francisco Jesus Checa-Robles,

Nicolas Salvetat,

Christopher Cayzac

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(23), P. 12981 - 12981

Published: Dec. 3, 2024

Mental health disorders are devastating illnesses, often misdiagnosed due to overlapping clinical symptoms. Among these conditions, bipolar disorder, schizophrenia, and schizoaffective disorder particularly difficult distinguish, as they share alternating positive negative mood Accurate timely diagnosis of diseases is crucial ensure effective treatment tailor therapeutic management each individual patient. In this context, it essential move beyond standard assessment employ innovative approaches identify new biomarkers that can be reliably quantified. We previously identified a panel RNA editing capable differentiating healthy controls from depressed patients and, among patients, those with major depressive disorder. study, we integrated Adenosine-to-Inosine blood data through machine learning algorithms establish specific signatures for schizophrenia spectrum disorders. This groundbreaking study paves the way application in other psychiatric disorders, such It represents first proof-of-concept provides compelling evidence establishment an signature conditions.

Language: Английский

Citations

0
Precision Medicine in View of Genomic Biomarker Discovery DOI
Abhidha Kohli, Sonia Verma, Neeraj Agarwal

et al.

Advances in medical technologies and clinical practice book series, Journal Year: 2024, Volume and Issue: unknown, P. 185 - 216

Published: Dec. 13, 2024

Precision Medicine encompasses decision making about prevention, diagnosis, and treatment of a particular disease in patient tailored based on the information derived from patient's genetic profile, environment, lifestyle. It is patient-specific their specific clinical biological characteristics with minimum side effects. With advancements DNA sequencing technology, this concept gained attention among scientists. The projects like Human Genome Project International HapMap provided deep insight into human genomics disease-associated gene variants. Moreover, pharmacogenetics pharmacogenomics have helped understanding molecular basis diseases corresponding therapeutic strategy designed for individuals drug effect multiple variations genome treatment, helping biomarker identification, influencing pathogen effects body, establishing need genomic biomarkers discovery designing modalities disease.

Language: Английский

Citations

0
Deep immunophenotyping of circulating immune cells in major depressive disorder patients reveals immune correlates of clinical course and treatment response DOI Creative Commons

Fabiola Stolfi,

Claudio Brasso, Davide Raineri

et al.

Brain Behavior & Immunity - Health, Journal Year: 2024, Volume and Issue: 43, P. 100942 - 100942

Published: Dec. 31, 2024

Major Depressive Disorder (MDD) is a widespread psychiatric condition impacting social and occupational functioning, making it leading cause of disability. The diagnosis MDD remains clinical, based on the Diagnostic Statistical Manual Mental Disorders (DSM)-5 criteria, as biomarkers have not yet been validated for diagnostic purposes or predictors treatment response. Traditional strategies often follow one-size-fits-all approach obtaining suboptimal outcomes many patients who fail to experience response recovery. Several studies reported an association between immune system dysregulation, but few focused deep characterization circulating cells, during acute phase MDD. This work aimed at immunophenotyping peripheral blood cells in relapse disorder, identify relevant cell populations clinical monitoring patients. Multiparametric analysis was performed 60 using flow cytometry lymphocytes (naïve/effector, memory, regulatory) myeloid (dendritic monocytes). We studied associations immunophenotype depressive symptoms, working subjective quality life after three months treatment. Multivariate showed that CD4+ terminally differentiated effector memory (TEMRA) were associated with more symptoms particular emphasis anhedonic features worse functioning life. CD8+ TEMRA those related hopelessness. Conversely, ICOS + Tregs low-intensity suicidal ideation, suggestive protective role. Baseline T (EM) negative predictor reduction treatment, whilst plasmacytoid dendritic (pDC) predicting These results confirm involvement demonstrate existence immunological signatures severity major episodes could guide future personalized therapies.

Language: Английский

Citations

0