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- Title
Trends in big data analyses by multicenter collaborative translational research in psychiatry.
- Authors
Onitsuka, Toshiaki; Hirano, Yoji; Nemoto, Kiyotaka; Hashimoto, Naoki; Kushima, Itaru; Koshiyama, Daisuke; Koeda, Michihiko; Takahashi, Tsutomu; Noda, Yoshihiro; Matsumoto, Junya; Miura, Kenichiro; Nakazawa, Takanobu; Hikida, Takatoshi; Kasai, Kiyoto; Ozaki, Norio; Hashimoto, Ryota
- Abstract
The underlying pathologies of psychiatric disorders, which cause substantial personal and social losses, remain unknown, and their elucidation is an urgent issue. To clarify the core pathological mechanisms underlying psychiatric disorders, in addition to laboratory‐based research that incorporates the latest findings, it is necessary to conduct large‐sample‐size research and verify reproducibility. For this purpose, it is critical to conduct multicenter collaborative research across various fields, such as psychiatry, neuroscience, molecular biology, genomics, neuroimaging, cognitive science, neurophysiology, psychology, and pharmacology. Moreover, collaborative research plays an important role in the development of young researchers. In this respect, the Enhancing Neuroimaging Genetics through Meta‐Analysis (ENIGMA) consortium and Cognitive Genetics Collaborative Research Organization (COCORO) have played important roles. In this review, we first overview the importance of multicenter collaborative research and our target psychiatric disorders. Then, we introduce research findings on the pathophysiology of psychiatric disorders from neurocognitive, neurophysiological, neuroimaging, genetic, and basic neuroscience perspectives, focusing mainly on the findings obtained by COCORO. It is our hope that multicenter collaborative research will contribute to the elucidation of the pathological basis of psychiatric disorders.
- Subjects
PSYCHIATRIC research; TRANSLATIONAL research; BIG data; MENTAL illness; DATA analysis
- Publication
Psychiatry & Clinical Neurosciences, 2022, Vol 76, Issue 1, p1
- ISSN
1323-1316
- Publication type
Article
- DOI
10.1111/pcn.13311