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The association between the CCDC88A gene polymorphism at rs1437396 and alcohol use disorder, with or without major depression disorder Cover

The association between the CCDC88A gene polymorphism at rs1437396 and alcohol use disorder, with or without major depression disorder

Open Access
|Jun 2023

Figures & Tables

Table 1

Demographic and clinical characteristics of alcohol use disorder (AUD) patients with or without major depressive disorder (AUD+MDD)

Demographic dataAUD+MDD N=53 (%)AUD only N=173 (%)p-value
Age49 (35)52 (48)0.178a
GenderFemale7 (13.2)27 (13.3)1c
Male46 (86.8)150 (86.7)
Living environmentUrban35 (66)99 (57.2)0.261c
Rural18 (34)74 (42.8)
EducationCollege8 (15)5 (2.9)0.003*b
High school20 (37.4)53 (30.6)
Vocational school15 (28.3)78 (45.1)
Elementary school10 (18.3)37 (21.4)
Marital statusWith a partner26 (49)101 (58.4)0.261c
Single27 (51)72 (41.6)
Family history of AUDYes34 (64.1)114 (65.9)0.867c
No19 (35.9)59 (34.1)
OccupationEmployed24 (45.3)58 (33.5)0.052b
Unemployed9 (17)52 (30.1)
Disability pension14 (26.4)29 (16.8)
Retirement due to age6 (11.3)34 (19.6)

1 Age (continuous variable) is presented as median with interquartile range in parentheses. Categorical variables are reported as number of participants with percentage in parenthesis.

1a Mann-Whitney U Test,

1b chi-squared test,

1c Fisher’s exact test. Statistically significant p-values are bolded and marked with asterisk. AUD – alcohol use disorder; MDD – major depressive disorder

Table 2

Distribution of genotype and allele frequency of the rs1437396 polymorphism in patients with alcohol use disorder (AUD) and healthy controls

ModelAUD N=226 (%)Controls N=391 (%)OR (95 % CI)p-value
AllelicT vs C120 (26.5)167 (21.4)1.33
332 (73.5)615 (78.6)(1.01–1.14)0.042*
Co-dominantTT vs CC15 (6.6)22 (5.63)1.38
121 (53.5)246 (62.9)(0.7–2.7)0.36
CT vs CC90 (39.8)123 (31.5)1.48
121 (53.5)246 (62.9)(1.05–2.1)0.031*
DominantTT+CT vs CC105 (46.4)145 (37)1.47
121 (53.6)246 (63)(1.05–2.05)0.026*
RecessiveTT vs CC+CT15 (6.6)22 (5.6)1.19
211 (63.4)369 (94.4)(0.6–2.34)0.6

1 p-values were determined by Fisher’s exact test. Statistically significant p-values are bolded and marked with the asterisk

Table 3

Distribution of genotype and allele frequency of the rs1437396 polymorphism in patients with alcohol use disorder and major depressive disorder (AUD+MDD) vs the AUD-only group

ModelAUD+MDD N=53 (%)AUD N=173 (%)OR (95 % CI)p-value
AllelicT vs C38 (35.85)82 (23.7)1.80.016*
68 (64.15)264 (76.3)(1.12–2.87)
Co-dominantTT vs CC6 (11.32)9 (5.2)3.170.077
21 (39.62)100 (57.8)(1.02–9.88)
CT vs CC26 (49.05)64 (37)1.930.065
21 (39.62)100 (57.8)(1–3.72)
DominantTT+CT vs CC32 (60.38)73 (42.2)2.080.027*
21 (39.62)100 (57.8)(1.11–3.91)
RecessiveTT vs CC+CT6 (11.32)9 (5.2)2.320.124
47 (88.68)164 (94.8)(0.78–6.67)

1 p-values were determined by Fisher’s exact test. Statistically significant p-values are bolded and marked with asterisk

Table 4

Logistic regression for the association between the rs1437396 polymorphism and alcohol use disorder and major depressive disorder (AUD+MDD) comorbidity (N=53)

VariablesBSEχ2dfOR (CI 95 %)p-value
rs1437396 (T allele)0.7790.3385.32612.17 (1.12–4.22)0.021*
Gender (male)0.0590.5090.01311.06 (0.39–2.87)0.908
Age−0.0180.0180.25810.98 (0.94–1.01)0.324
Living environment (urban)0.180.3550.25811.19 (0.59–2.4)0.611
Education (college)1.9230.7496.616.84 (1.57–29.67)0.010*
Marital status (with a partner)−0.3200.3730.73610.72 (0.34–1.5)0.391
Family history of AUD−0.0230.3770.00410.97 (0.46–2.04)0.951
Occupation (employed)0.0930.3650.06511.09 (0.53–2.24)0.799
Constant−0.9471.0340.83810.36

1 p-values were determined with logistic regression. Statistically significant p-values are bolded and marked with asterisk

DOI: https://doi.org/10.2478/aiht-2023-74-3690 | Journal eISSN: 1848-6312 (formerly 0004-1254) | Journal ISSN: 0004-1254
Language: English, Croatian
Page range: 127 - 133
Submitted on: Nov 1, 2022
Accepted on: May 1, 2023
Published on: Jun 26, 2023
Published by: Institute for Medical Research and Occupational Health
In partnership with: Paradigm Publishing Services

© 2023 Maria Bonea, Constantin-Ionut Coroama, Radu Anghel Popp, Ioana Valentina Miclutia, published by Institute for Medical Research and Occupational Health
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.