Resumen
Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.
Idioma original | English (US) |
---|---|
Número de artículo | e1134 |
Publicación | Translational Psychiatry |
Volumen | 7 |
N.º | 5 |
DOI | |
Estado | Published - may 16 2017 |
Publicado de forma externa | Sí |
Huella dactilar
All Science Journal Classification (ASJC) codes
- Cellular and Molecular Neuroscience
- Psychiatry and Mental health
- Biological Psychiatry
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A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort. / Yu, C. Q.; Arcos-Burgos, M.; Licinio, Julio; Wong, Ma Li.
En: Translational Psychiatry, Vol. 7, N.º 5, e1134, 16.05.2017.Resultado de la investigación: Contribución a Revista › Artículo
TY - JOUR
T1 - A latent genetic subtype of major depression identified by whole-exome genotyping data in a Mexican-American cohort
AU - Yu, C. Q.
AU - Arcos-Burgos, M.
AU - Licinio, Julio
AU - Wong, Ma Li
PY - 2017/5/16
Y1 - 2017/5/16
N2 - Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.
AB - Identifying data-driven subtypes of major depressive disorder (MDD) is an important topic of psychiatric research. Currently, MDD subtypes are based on clinically defined depression symptom patterns. Although a few data-driven attempts have been made to identify more homogenous subgroups within MDD, other studies have not focused on using human genetic data for MDD subtyping. Here we used a computational strategy to identify MDD subtypes based on single-nucleotide polymorphism genotyping data from MDD cases and controls using Hamming distance and cluster analysis. We examined a cohort of Mexican-American participants from Los Angeles, including MDD patients (n=203) and healthy controls (n=196). The results in cluster trees indicate that a significant latent subtype exists in the Mexican-American MDD group. The individuals in this hidden subtype have increased common genetic substrates related to major depression and they also have more anxiety and less middle insomnia, depersonalization and derealisation, and paranoid symptoms. Advances in this line of research to validate this strategy in other patient groups of different ethnicities will have the potential to eventually be translated to clinical practice, with the tantalising possibility that in the future it may be possible to refine MDD diagnosis based on genetic data.
UR - http://www.scopus.com/inward/record.url?scp=85019457709&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019457709&partnerID=8YFLogxK
U2 - 10.1038/tp.2017.102
DO - 10.1038/tp.2017.102
M3 - Article
C2 - 28509902
AN - SCOPUS:85019457709
VL - 7
JO - Translational Psychiatry
JF - Translational Psychiatry
SN - 2158-3188
IS - 5
M1 - e1134
ER -