Anna Yakovchik , Aleksandra Mamchur , Daria Kashtanova , Mikhail Ivanov , Elena Zelenova , Maria Bruttan , Lorena Matkava , Mikhail Terekhov , Aleksandra Nekrasova , Aleksander Nekrasov , Sergey Mitrofanov , Vasilisa Astafieva , Andrey Shingaliev , Konstantin Pavlov , Olga Pavlova , Kira Nebogina , Anna Morozova , Aleksander Kozlov , Vladimir Yudin , Valentin Makarov , Veronika Skvortsova
{"title":"Enhancing genetic discovery through narrow phenotyping in schizophrenia","authors":"Anna Yakovchik , Aleksandra Mamchur , Daria Kashtanova , Mikhail Ivanov , Elena Zelenova , Maria Bruttan , Lorena Matkava , Mikhail Terekhov , Aleksandra Nekrasova , Aleksander Nekrasov , Sergey Mitrofanov , Vasilisa Astafieva , Andrey Shingaliev , Konstantin Pavlov , Olga Pavlova , Kira Nebogina , Anna Morozova , Aleksander Kozlov , Vladimir Yudin , Valentin Makarov , Veronika Skvortsova","doi":"10.1016/j.jpsychires.2024.11.033","DOIUrl":null,"url":null,"abstract":"<div><h3>Background</h3><div>Schizophrenia varies greatly from person to person, mainly because of its polygenic nature. Consequently, schizophrenia patients form distinct subphenotypes of schizophrenia, with specific symptom patterns and outcomes.</div></div><div><h3>Methods</h3><div>This study included 4257 adults, with long-term schizophrenia (control - 8955 individuals) who were assessed for schizophrenia with potentially severe outcomes based on following criteria: disability in functional and/or physical domains before the age of 40; severe negative symptoms (present in infancy or shortly after onset); a continuous course of the disease. Additionally, the time of the onset and aggressive/antisocial tendencies were assessed as one the predictors of potentially severe outcomes. A total of 817 participants met at least three of these criteria, i.e., had disruptive schizophrenia. A genome-wide and transcriptome-wide association study was conducted using linear regression and the PrediXcan algorithm. The obtained data were used to develop a polygenic risk model for early risk prediction of schizophrenia with potentially severe outcomes.</div></div><div><h3>Results</h3><div>Significant associations were found between schizophrenia and variants in <em>CAMTA1</em>, <em>TRHDE</em>, <em>NELFE</em>, and others. The PRS model demonstrated high performance in training, internal and external validation (ROC AUC of 0.9, 0.89, and 0.68, respectively). The functional pathway analysis highlighted pathways involved in ATP metabolism, myeloid cell differentiation, and apoptotic processes.</div></div><div><h3>Conclusion</h3><div>Subphenotyping schizophrenia may enhance the discovery of genetic factors affecting its development and progression. The GWAS and TWAS findings revealed general mechanisms involved in the development of schizophrenia with potentially severe outcomes, such as synapse regulation, inflammation, and apoptosis.</div></div>","PeriodicalId":16868,"journal":{"name":"Journal of psychiatric research","volume":"181 ","pages":"Pages 55-63"},"PeriodicalIF":3.7000,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of psychiatric research","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0022395624006617","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHIATRY","Score":null,"Total":0}
引用次数: 0
Abstract
Background
Schizophrenia varies greatly from person to person, mainly because of its polygenic nature. Consequently, schizophrenia patients form distinct subphenotypes of schizophrenia, with specific symptom patterns and outcomes.
Methods
This study included 4257 adults, with long-term schizophrenia (control - 8955 individuals) who were assessed for schizophrenia with potentially severe outcomes based on following criteria: disability in functional and/or physical domains before the age of 40; severe negative symptoms (present in infancy or shortly after onset); a continuous course of the disease. Additionally, the time of the onset and aggressive/antisocial tendencies were assessed as one the predictors of potentially severe outcomes. A total of 817 participants met at least three of these criteria, i.e., had disruptive schizophrenia. A genome-wide and transcriptome-wide association study was conducted using linear regression and the PrediXcan algorithm. The obtained data were used to develop a polygenic risk model for early risk prediction of schizophrenia with potentially severe outcomes.
Results
Significant associations were found between schizophrenia and variants in CAMTA1, TRHDE, NELFE, and others. The PRS model demonstrated high performance in training, internal and external validation (ROC AUC of 0.9, 0.89, and 0.68, respectively). The functional pathway analysis highlighted pathways involved in ATP metabolism, myeloid cell differentiation, and apoptotic processes.
Conclusion
Subphenotyping schizophrenia may enhance the discovery of genetic factors affecting its development and progression. The GWAS and TWAS findings revealed general mechanisms involved in the development of schizophrenia with potentially severe outcomes, such as synapse regulation, inflammation, and apoptosis.
期刊介绍:
Founded in 1961 to report on the latest work in psychiatry and cognate disciplines, the Journal of Psychiatric Research is dedicated to innovative and timely studies of four important areas of research:
(1) clinical studies of all disciplines relating to psychiatric illness, as well as normal human behaviour, including biochemical, physiological, genetic, environmental, social, psychological and epidemiological factors;
(2) basic studies pertaining to psychiatry in such fields as neuropsychopharmacology, neuroendocrinology, electrophysiology, genetics, experimental psychology and epidemiology;
(3) the growing application of clinical laboratory techniques in psychiatry, including imagery and spectroscopy of the brain, molecular biology and computer sciences;