Advancing our understanding of schizophrenia: insights from recent research, emerging therapies, and future directions
Tolutope Adebimpe Oso , Olalekan John Okesanya , Uthman Okikiola Adebayo , Khalifat Boluwatife Obadeyi , Shuaibu Saidu Musa , Mohamed Mustaf Ahmed , Ayantunde Kayode Ayankola , Adebimpe Busola Ogundele , Joseph Olaloluwa Oso , Gilbert Eshun , Don Eliseo Lucero-Prisno
Exploration of Neuroscience ›› 2025, Vol. 4 ›› Issue (1) : 1006112
Schizophrenia (SZ) is a complex psychiatric disorder characterized by disruptions in cognition, perception, and behavior, contributing significantly to the global burden of psychiatric disorders and necessitating ongoing research into its pathophysiology, diagnosis, and treatment. This narrative review explores recent insights into SZ research, highlighting the genetic, neurochemical, and neurodevelopmental factors that contribute to the disorder. Emerging evidence underscores the dynamic interplay between neurotransmitter imbalances, particularly involving dopamine, glutamate, and gamma-aminobutyric acid (GABA), and neuroinflammation, oxidative stress, and immune dysregulation in the pathophysiology of SZ. Neuroimaging, clinical staging models, and multi-omics technologies have deepened our understanding of structural and functional brain abnormalities, identifying potential biomarkers for early detection and subtyping. This has refined diagnostic frameworks and informed precision psychiatry approaches. Advances in pharmacological treatments, including trace amine-associated receptor 1 agonists, glutamatergic modulators, psychedelics, and anti-inflammatory agents, offer new therapeutic possibilities beyond conventional dopamine antagonists. Novel targets, such as N-methyl-D-aspartate (NMDA) receptor modulation and neuroprotective strategies, are also being explored to address negative and cognitive symptoms. Additionally, non-pharmacological interventions, such as neuromodulation techniques, digital therapeutics, and psychosocial interventions, are promising complementary strategies. Digital phenotyping, machine learning (ML), and artificial intelligence (AI)-driven tools enable real-time symptom tracking, early risk prediction, and personalized care delivery. Despite these advancements, challenges remain in early diagnosis, treatment adherence, and equitable access to mental health care, particularly in low-resource settings. Therefore, addressing these barriers requires interdisciplinary collaboration, public health education, and the integration of scalable, culturally sensitive, and AI-based mental health innovations. Future research should prioritize multi-omics integration, longitudinal and transdiagnostic studies, biomarker validation, and the real-world implementation of personalized interventions to improve outcomes and quality of life for individuals living with SZ.
schizophrenia / psychiatric disorders / neurotransmitter imbalance / neuroinflammation / genetics
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