Proof-of-concept study of a multi-gene risk score in adolescent bipolar disorder.
Adolescent
Bipolar Disorder
/ genetics
Case-Control Studies
Female
Genetic Predisposition to Disease
/ genetics
Genetic Testing
/ statistics & numerical data
Glutathione Peroxidase
/ genetics
Humans
Interleukin-1beta
/ genetics
Male
Nerve Tissue Proteins
/ genetics
Phenotype
Proof of Concept Study
Receptors, Dopamine D4
/ genetics
Regression Analysis
Risk Assessment
Risk Factors
Saliva
/ metabolism
Young Adult
Adolescent
Bipolar disorder
Genetic risk score
Genetics
Journal
Journal of affective disorders
ISSN: 1573-2517
Titre abrégé: J Affect Disord
Pays: Netherlands
ID NLM: 7906073
Informations de publication
Date de publication:
01 02 2020
01 02 2020
Historique:
received:
07
06
2019
revised:
07
10
2019
accepted:
02
11
2019
pubmed:
16
11
2019
medline:
20
1
2021
entrez:
16
11
2019
Statut:
ppublish
Résumé
Few studies have examined multiple genetic variants concurrently for the purpose of classifying bipolar disorder (BD); the literature among youth is particularly sparse. We selected 35 genetic variants, previously implicated in BD or associated characteristics, from which to identify the most robustly predictive group of genes. 215 Caucasian adolescents (114 BD and 101 healthy controls (HC), ages 13-20 years) were included. Psychiatric diagnoses were determined based on semi-structured diagnostic interviews. Genomic DNA was extracted from saliva for genotyping. Two models were used to calculate a multi-gene risk score (MGRS). Model 1 used forward and backward regressions, and model 2 used a PLINK generated method. In model 1, GPX3 rs3792797 was significant in the forward regression, DRD4 exonIII was significant in the backward regression; IL1β rs16944 and DISC1 rs821577 were significant in both the forward and backward regressions. These variants are involved in dopamine neurotransmission; inflammation and oxidative stress; and neuronal development. Model 1 MGRS did not significantly discriminate between BD and HC. In model 2, ZNF804A rs1344706 was significantly associated with BD; however, this association did not predict diagnosis when entered into the weighted model. This study was limited by the number of genetic variants examined and the modest sample size. Whereas regression approaches identified four genetic variants that significantly discriminated between BD and HC, those same variants no longer discriminated between BD and HC when computed as a MGRS. Future larger studies are needed evaluating intermediate phenotypes such as neuroimaging and blood-based biomarkers.
Sections du résumé
BACKGROUND
Few studies have examined multiple genetic variants concurrently for the purpose of classifying bipolar disorder (BD); the literature among youth is particularly sparse. We selected 35 genetic variants, previously implicated in BD or associated characteristics, from which to identify the most robustly predictive group of genes.
METHODS
215 Caucasian adolescents (114 BD and 101 healthy controls (HC), ages 13-20 years) were included. Psychiatric diagnoses were determined based on semi-structured diagnostic interviews. Genomic DNA was extracted from saliva for genotyping. Two models were used to calculate a multi-gene risk score (MGRS). Model 1 used forward and backward regressions, and model 2 used a PLINK generated method.
RESULTS
In model 1, GPX3 rs3792797 was significant in the forward regression, DRD4 exonIII was significant in the backward regression; IL1β rs16944 and DISC1 rs821577 were significant in both the forward and backward regressions. These variants are involved in dopamine neurotransmission; inflammation and oxidative stress; and neuronal development. Model 1 MGRS did not significantly discriminate between BD and HC. In model 2, ZNF804A rs1344706 was significantly associated with BD; however, this association did not predict diagnosis when entered into the weighted model.
LIMITATIONS
This study was limited by the number of genetic variants examined and the modest sample size.
CONCLUSIONS
Whereas regression approaches identified four genetic variants that significantly discriminated between BD and HC, those same variants no longer discriminated between BD and HC when computed as a MGRS. Future larger studies are needed evaluating intermediate phenotypes such as neuroimaging and blood-based biomarkers.
Identifiants
pubmed: 31727397
pii: S0165-0327(19)31470-3
doi: 10.1016/j.jad.2019.11.009
pii:
doi:
Substances chimiques
DISC1 protein, human
0
DRD4 protein, human
0
IL1B protein, human
0
Interleukin-1beta
0
Nerve Tissue Proteins
0
Receptors, Dopamine D4
137750-34-6
GPX3 protein, human
EC 1.11.1.-
Glutathione Peroxidase
EC 1.11.1.9
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
211-222Subventions
Organisme : CIHR
Pays : Canada
Informations de copyright
Copyright © 2019. Published by Elsevier B.V.