ANK3 rs10994336 and ZNF804A rs7597593 polymorphisms: genetic interaction for emotional and behavioral symptoms of alcohol withdrawal syndrome.
Humans
Male
Polymorphism, Single Nucleotide
/ genetics
Ankyrins
/ genetics
Adult
Kruppel-Like Transcription Factors
/ genetics
Middle Aged
Substance Withdrawal Syndrome
/ genetics
Alcoholism
/ genetics
Aggression
/ psychology
Anxiety
/ genetics
Epistasis, Genetic
Behavioral Symptoms
/ genetics
Genetic Predisposition to Disease
/ genetics
Alleles
ANK3
ZNF804A
Alcohol withdrawal syndrome
Gene-gene interaction
Journal
BMC psychiatry
ISSN: 1471-244X
Titre abrégé: BMC Psychiatry
Pays: England
ID NLM: 100968559
Informations de publication
Date de publication:
03 May 2024
03 May 2024
Historique:
received:
14
11
2023
accepted:
24
04
2024
medline:
4
5
2024
pubmed:
4
5
2024
entrez:
3
5
2024
Statut:
epublish
Résumé
Alcohol withdrawal syndrome (AWS) is a complex condition associated with alcohol use disorder (AUD), characterized by significant variations in symptom severity among patients. The psychological and emotional symptoms accompanying AWS significantly contribute to withdrawal distress and relapse risk. Despite the importance of neural adaptation processes in AWS, limited genetic investigations have been conducted. This study primarily focuses on exploring the single and interaction effects of single-nucleotide polymorphisms in the ANK3 and ZNF804A genes on anxiety and aggression severity manifested in AWS. By examining genetic associations with withdrawal-related psychopathology, we ultimately aim to advance understanding the genetic underpinnings that modulate AWS severity. The study involved 449 male patients diagnosed with alcohol use disorder. The Self-Rating Anxiety Scale (SAS) and Buss-Perry Aggression Questionnaire (BPAQ) were used to assess emotional and behavioral symptoms related to AWS. Genomic DNA was extracted from peripheral blood, and genotyping was performed using PCR. Single-gene analysis revealed that naturally occurring allelic variants in ANK3 rs10994336 (CC homozygous vs. T allele carriers) were associated with mood and behavioral symptoms related to AWS. Furthermore, the interaction between ANK3 and ZNF804A was significantly associated with the severity of psychiatric symptoms related to AWS, as indicated by MANOVA. Two-way ANOVA further demonstrated a significant interaction effect between ANK3 rs10994336 and ZNF804A rs7597593 on anxiety, physical aggression, verbal aggression, anger, and hostility. Hierarchical regression analyses confirmed these findings. Additionally, simple effects analysis and multiple comparisons revealed that carriers of the ANK3 rs10994336 T allele experienced more severe AWS, while the ZNF804A rs7597593 T allele appeared to provide protection against the risk associated with the ANK3 rs10994336 mutation. This study highlights the gene-gene interaction between ANK3 and ZNF804A, which plays a crucial role in modulating emotional and behavioral symptoms related to AWS. The ANK3 rs10994336 T allele is identified as a risk allele, while the ZNF804A rs7597593 T allele offers protection against the risk associated with the ANK3 rs10994336 mutation. These findings provide initial support for gene-gene interactions as an explanation for psychiatric risk, offering valuable insights into the pathophysiological mechanisms involved in AWS.
Identifiants
pubmed: 38702695
doi: 10.1186/s12888-024-05787-z
pii: 10.1186/s12888-024-05787-z
doi:
Substances chimiques
Ankyrins
0
ANK3 protein, human
0
Kruppel-Like Transcription Factors
0
ZNF804A protein, human
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
335Subventions
Organisme : Technology Support Project of Xinjiang
ID : 2017E0267
Organisme : Natural Science Foundation of Xinjiang Uyghur Autonomous Region
ID : 2018D01C228
Organisme : Tianshan Youth Project-Outstanding Youth Science and Technology Talents of Xinjiang
ID : 2017Q007
Organisme : Beijing Municipal Natural Science Foundation
ID : 7152074
Organisme : Science and Technology Program of Wenzhou
ID : Y20190098
Informations de copyright
© 2024. The Author(s).
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