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Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies.
Monson, Eric T; Colbert, Sarah M C; Andreassen, Ole A; Ayinde, Olatunde O; Bejan, Cosmin A; Ceja, Zuriel; Coon, Hilary; DiBlasi, Emily; Izotova, Anastasia; Kaufman, Erin A; Koromina, Maria; Myung, Woojae; Nurnberger, John I; Serretti, Alessandro; Smoller, Jordan W; Stein, Murray B; Zai, Clement C; Aslan, Mihaela; Barr, Peter B; Bigdeli, Tim B; Harvey, Philip D; Kimbrel, Nathan A; Patel, Pujan R; Ruderfer, Douglas; Docherty, Anna R; Mullins, Niamh; Mann, J John.
Afiliação
  • Monson ET; Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine.
  • Colbert SMC; Huntsman Mental Health Institute.
  • Andreassen OA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai.
  • Ayinde OO; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai.
  • Bejan CA; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai.
  • Ceja Z; Division of Mental Health and Addiction, Oslo University Hospital.
  • Coon H; NORMENT Centre, University of Oslo.
  • DiBlasi E; Department of Psychiatry, College of Medicine, University of Ibadan.
  • Izotova A; Department of Biomedical Informatics, Vanderbilt University Medical Center.
  • Kaufman EA; Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute.
  • Koromina M; School of Biomedical Sciences, Faculty of Medicine, The University of Queensland.
  • Myung W; Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine.
  • Nurnberger JI; Huntsman Mental Health Institute.
  • Serretti A; Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine.
  • Smoller JW; Huntsman Mental Health Institute.
  • Stein MB; Nic Waals Institute, Lovisenberg Diaconal Hospital.
  • Zai CC; PsychGen Centre for Genetic Epidemiology and Mental Health, Norwegian Institute of Public Health.
  • Aslan M; Department of Psychiatry, University of Utah Spencer Fox Eccles School of Medicine.
  • Barr PB; Huntsman Mental Health Institute.
  • Bigdeli TB; Department of Psychiatry, Icahn School of Medicine at Mount Sinai.
  • Harvey PD; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai.
  • Kimbrel NA; Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai.
  • Patel PR; Department of Neuropsychiatry, Seoul National University Bundang Hospital.
  • Ruderfer D; Department of Psychiatry, Indiana University School of Medicine.
  • Docherty AR; Department of Medical & Molecular Genetics, Indiana University.
  • Mullins N; Department of Medicine and Surgery, Kore University of Enna, Italy.
  • Mann JJ; Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital.
medRxiv ; 2024 Jul 29.
Article em En | MEDLINE | ID: mdl-39132474
ABSTRACT

Background:

Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation.

Methods:

A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394).

Results:

Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported.

Conclusions:

Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article