Symptom-level modelling unravels the shared genetic architecture of anxiety and depression
Journal Article
Overview
publication date
- October 1, 2021
has subject area
- Anxiety
- Behavioral Symptoms
- Computing Methodologies - Latent Class Analysis
- Depression
- Disease Attributes - Genetic Predisposition to Disease
- Environment and Public Health - Comorbidity
- Environment and Public Health - Factor Analysis, Statistical
- Environment and Public Health - Genome-Wide Association Study
- Environment and Public Health - Genome-Wide Association Study
- Environment and Public Health - Latent Class Analysis
- Genetic Association Studies - Genome-Wide Association Study
- Genetic Techniques - Genome-Wide Association Study
- Genotype - Genetic Predisposition to Disease
- Health Care Evaluation Mechanisms - Factor Analysis, Statistical
- Health Care Evaluation Mechanisms - Latent Class Analysis
- Health Care Quality, Access, and Evaluation - Comorbidity
- Humans
- Investigative Techniques - Factor Analysis, Statistical
- Investigative Techniques - Genome-Wide Association Study
- Investigative Techniques - Genome-Wide Association Study
- Investigative Techniques - Latent Class Analysis
- Mathematical Concepts - Latent Class Analysis
- Neuroticism
- Sequence Analysis - Genome-Wide Association Study
- Symptom Assessment
has restriction
- green
Date in CU Experts
- May 5, 2021 12:33 PM
Full Author List
- Thorp JG; Campos AI; Grotzinger AD; Gerring ZF; An J; Ong J-S; Wang W; Shringarpure S; Byrne EM; MacGregor S
author count
- 14
citation count
- 29
published in
- Nature Human Behaviour Journal
Other Profiles
International Standard Serial Number (ISSN)
- 2397-3374
Digital Object Identifier (DOI)
Additional Document Info
start page
- 1432
end page
- U206
volume
- 5
issue
- 10