Doyle Alysa E, Bearden Carrie E, Gur Raquel E, Ledbetter David H, Martin Christa L, McCoy Thomas H, Pasaniuc Bogdan, Perlis Roy H, Smoller Jordan W, Davis Lea K
Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts; Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.
Departments of Psychiatry and Biobehavioral Sciences & Psychology, University of California at Los Angeles, Los Angeles, California.
Biol Psychiatry. 2025 Mar 1;97(5):450-460. doi: 10.1016/j.biopsych.2024.10.006. Epub 2024 Oct 16.
Genome-wide studies are yielding a growing catalog of common and rare variants that confer risk for psychopathology. However, despite representing unprecedented progress, emerging data also indicate that the full promise of psychiatric genetics-including understanding pathophysiology and improving personalized care-will not be fully realized by targeting traditional dichotomous diagnostic categories. The current article provides reflections on themes that emerged from a 2021 National Institute of Mental Health-sponsored conference convened to address strategies for the evolving field of psychiatric genetics. As anticipated by the National Institute of Mental Health's Research Domain Criteria framework, multilevel investigations of dimensional and transdiagnostic phenotypes, particularly when integrated with biobanks and big data, will be critical to advancing knowledge. The path forward will also require more diverse representation in source studies. Additionally, progress will be catalyzed by a range of converging approaches, including capitalizing on computational methods, pursuing biological insights, working within a developmental framework, and engaging health care systems and patient communities.
全基因组研究正在生成越来越多的常见和罕见变异目录，这些变异会增加精神病理学风险。然而，尽管取得了前所未有的进展，但新出现的数据也表明，仅针对传统的二分法诊断类别，无法完全实现精神遗传学的全部前景，包括理解病理生理学和改善个性化护理。本文对2021年美国国立精神卫生研究所主办的一次会议上出现的主题进行了思考，该会议旨在探讨精神遗传学不断发展领域的策略。正如美国国立精神卫生研究所的研究领域标准框架所预期的那样，对维度和跨诊断表型进行多层次研究，尤其是与生物样本库和大数据相结合时，对于推进知识至关重要。未来的道路还需要在源研究中有更多样化的代表性。此外，一系列融合方法将推动进展，包括利用计算方法、寻求生物学见解、在发育框架内开展工作，以及与医疗保健系统和患者群体合作。
