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Associations of NLRP3 and CARD8 gene polymorphisms with alcohol dependence and commonly related psychiatric disorders: a preliminary study


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Chronic excessive alcohol consumption leads to neuroinflammation and may result in cognitive dysfunction and behavioural changes, as alcohol rapidly diffuses through the blood-brain barrier, alters neurotransmission, contributes to neurodegeneration, and impairs regeneration by activating microglia and astrocytes, but our understanding of the mechanisms by which alcohol triggers inflammation in the brain is still limited (1). What we do know is that peripheral endotoxemia induced by alcohol may lead to increased secretion of pro-inflammatory cytokines such as TNF-α, interleukin (IL)-1β, IL-6, and interferon gamma (2). We also know that astrocyte activation may be mediated by the Toll-like receptor 4 pathway (TLR4), which activates downstream signalling molecules and cytokine secretion (1, 3). One study on mice has shown that ethanol directly triggers TLR4-mediated activation of the nucleotide-binding oligomerisation domain (NOD), leucine-rich repeats (LRR), and pyrin domain-containing protein 3 (NLRP3) inflammasome in glia cells (4). Another study on human and mouse cells suggests that the hyper-activation of the NLRP3 inflammasome may also be related to prolonged exposure to the products of ethanol metabolism (5).

The NLRP3 inflammasome is a cytoplasmic complex of intracellular sensors such as NOD-like receptors coupled with procaspase-1 and the apoptosis-associated speck-like protein containing a caspase-associated recruitment domain (ASC) (6). Molecular damage triggers the assembly of the NLRP3 inflammasome leading to and IL-1β secretion and caspase-1 activation (7), which has been associated with early development of atherosclerosis in cerebral vessels and other heritable and acquired inflammatory diseases (8).

As NLRP3 gene mutations may result in increased inflammasome activation and higher secretion of IL-1β (7), genetic variability of the genes coding for the NLRP3 inflammasome components was investigated in several diseases with an inflammatory component, such as Alzheimer’s disease, atherosclerosis, inflammatory bowel disease, rheumatoid arthritis, and type 1 diabetes (9). One of the most commonly investigated single nucleotide polymorphisms (SNPs) coding for overactive NLRP3 inflammasome is the nonsynonymous gain-of-function polymorphism p.Q705K (rs35829419) in the NLRP3 gene (10). Another polymorphism extensively studied is p.C10X (rs 2043211) in the CARD8 gene, which codes for a nonfunctional protein and leads to loss of CARD8 inhibition of caspase-1. This polymorphic allele has been associated with increased cell death, although the actual role of CARD8 remains unclear (11). These two polymorphisms were not studied extensively in mental disorders, with a few exceptions (12, 13), even though it is known that alcohol dependence entails a 30–75 % higher risk of co-occurring mental disorders (14, 15, 16), including depression, anxiety, aggression, personality disorders, and dependence on other psychoactive substances (17, 18, 19, 20, 21).

However, up to date no human study has investigated the association between NLRP3 polymorphisms and alcohol dependence, and the aim of our study was to fill that gap by investigating the association between the above two polymorphisms, namely NLPR3 rs35829419 and CARD8 rs2043211, and alcohol dependence and symptoms of its usual comorbidities, i.e. anxiety, depression, and obsessive-compulsive or aggressive behaviour.

Participants and methods

The study included only male participants (to exclude the influence of sex differences, see ref. 22) aged from 18 to 65 years from the Slovenian (Caucasian) population. The first group (group 1; N=88) included hospitalised alcohol-dependent patients who met the criteria of alcohol dependence of the 4th edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-IV) (23) and were no longer having major abstinence symptoms (after having spent at least two weeks in respective departments/units for addiction treatment). The second group (group 2; N=99) included abstinent alcohol-dependent individuals recruited from support group meetings who had maintained full abstinence for more than two years. Participants of either group were excluded if they had a history of abuse or dependence of psychoactive substances other than nicotine and other major mental or neurological disorders or significant medical illnesses in their medical records. The third group (group 3; N=94) included healthy controls recruited from blood donors, who answered a short structured clinical questionnaire through interview to exclude DSM-IV Axis I disorders or clinical problems with alcohol consumption.

All participants also gave information about their residence (rural or urban), partnership status (single or in partnership: either married or living in the extramarital union), and years of education and signed informed consent.

The following questionnaires were employed: Zung Depression (24) and Anxiety (25) scale and Brief Social Phobia Scale (BSPS) (26) to rate depression and anxiety symptoms, Alcohol Use Disorders Identification Test (AUDIT) (27) to define drinking habits and severity of alcohol problems and dependence, Yale-Brown Obsessive Compulsive Scale (YBOCS) (28) and Obsessive Compulsive Drinking Scale (OCDS) (29) to rate obsessive-compulsive traits, and Buss-Durkee Hostility Inventory (BDHI) (30) to rate symptoms of aggression and hostility. All the questionnaires were administered at the entry into the study by the same rater, who was blinded to the genotyping results.

The study was approved by the Slovenian National Medical Ethics Committee (approval No. 117/06/10 and 148/02/1011) and followed the latest version of the Declaration of Helsinki (31). Each participant received a code to protect all the personal and medical information. All biological and DNA samples were processed and analysed under these codes.

Blood sampling and DNA extraction

DNA was isolated from either 5 mL of whole blood collected by venepuncture from groups 1 and 3 (hospitalised patients and healthy controls, respectively) or from a buccal swabs collected from group 2 (abstinents). Whole blood was collected into ethylenediaminetetraacetic acid (EDTA) tubes as part of regular blood testing (group 1) or donation (group 3) and stored at +4 °C until extraction. For DNA extraction from blood samples we used the QIAamp Blood Mini Kit and for the extraction from buccal swabs the QIAamp Mini Kit (Qiagen GmbH, Hilden, Germany) following manufacturer’s instructions (32).

NLRP3 rs35829419 (c.2113C>A, p.Gln705Lys) and CARD8 rs2043211 (c.304A>T, p.Phe102Ile, p.Cys10Ter) were genotyped using fluorescence-based competitive allele-specific PCR (KASP) amplification combined with a KASP reporting system. Briefly, we added the universal KASP Master mix and SNP-specific KASP Genotyping Assay (KBioscience, Hoddesdon, Herts, UK) to the extracted DNA samples on transparent 96-well PCR plates. Thermal cycling reaction was performed according to the manufacturer’s instructions and followed by end-point fluorescence detection. Genotyping was blind to any clinical data and was randomly repeated in 20 % of the samples to check for reliability. These repetitions confirmed initial findings in all such samples.

Statistical analysis

Pearson’s chi-squared test was used to compare SNP frequencies between the three groups and their effects on categorical variables, i.e. total scores on applied questionnaires. One-way analysis of variance (ANOVA) was used to assess SNP effects and continuous variables in each of the three groups separately. The associations between each SNP and continuous variables (genotype-phenotype associations) were compared between the groups with the factorial ANOVA. The level of statistical significance was set at 0.05. The study had sufficient power (0.80) to detect small-to-medium effect sizes (f2=0.021 and d=0.355). All statistics were run on the Statistica package, version 7.0 for Windows® (StatSoft Italia, Vigonza, Padua, Italy).

Results

Table 1 shows participant demographic characteristics of interest. Hospitalised and abstinent alcohol-dependent patients were significantly older (P<0.001; df=2; F=46.080) and had fewer years of education than controls (P<0.001; df=2; F=46.080). Significantly more abstinent alcohol dependents and controls were in partnership than hospitalised alcohol dependents (P=0.004; df=2; F=5.601).

Socio-demographic characteristics of study participants

Characteristics Hospitalised alcohol- dependent patients (n=88) Abstinent alcohol-dependent participants (n=99) Controls (n=94) p-value
Age (years) 45.8±10.0 49.1±8.1 34.4±11.7 0.003
Education (years) 11.3±2.2 11.7±2.4 12.7±1.9 0.001
Single 38 (43 %) 22 (22 %) 24 (25 %) 0.004
In partnership 50 (56 %) 77 (78 %) 70 (75 %)
Rural residents 45 (51 %) 48 (48 %) 36 (38 %) 0.293
Urban residents 43 (49 %) 51 (52 %) 58 (62 %)

Means ± standard deviations are given for continuous or the number of participants for categorical variables. Partnership means marital or extramarital union. p-value is shown for the comparison between all three groups

Genotype distribution of CARD8 did not deviate significantly from the Hardy-Weinberg equilibrium (HWE), but we found a deviation for NLPR3 in controls (Table 2). The three groups significantly differed in the distribution of the CARD8 rs2043211 genotypes (P=0.049; chi-squared=9.557; df=4) but not in the distribution of the NLPR3 rs35829419 genotypes.

NLPR3 rs35829419 and CARD8 rs2043211 genotype distribution by groups

Genotypes Hospitalised alcohol-dependent patients (n=88) Abstinent alcohol- dependent participants (n=99) Controls (n=94) p-value1 Merged alcohol- dependents (n=185) p-value2
NLPR3 0.838 0.500
CC 78 (88 %) 87 (88 %) 87 (93 %) 165 (88 %)
AC 9 (11 %) 11 (11 %) 6 (6 %) 20 (11 %)
AA 1 (1 %) 1 (1 %) 1 (1 %) 2 (1 %)
CARD8 0.049 0.055
AA 34 (39 %) 52 (53 %) 45 (48 %) 86 (46 %)
AT 44 (51 %) 42 (42 %) 34 (36 %) 86 (46 %)
TT 9 (10 %) 5 (5 %) 15 (16 %) 14 (8 %)

p-1 comparison between all three groups. p-2 comparison between the merged groups of alcohol-dependents and controls. Bolded p-values are statistically significant (p<0.05)

No significant association was found between the NLPR3 genotypes and selected mental disorder symptoms (Table 3). On the other hand, CARD8 rs2043211 genotypes were significantly associated with Zung Anxiety Scale scoring among abstinent alcohol-dependent participants (P=0.048; df=2, F=3.140). In this group, CARD8 rs2043211 TT genotype carriers reached the highest mean scores on the Zung Anxiety Scale (Table 4). In controls the CARD8 rs2043211 genotype was associated with OCDS scoring (P=0.027; df=2; F=3.744). However, because control candidates with clinical problems with alcohol consumption were excluded from the study and because OCDS measures obsessive-compulsive symptoms related to alcohol drinking, this result may be considered a chance finding that has no clinical importance.

Associations between NLPR3 rs35829419 genotypes and alcohol-related mental disorders

Mental disorders NLPR3 genotype Hospitalised alcohol-dependent patients Abstinent alcohol-dependent participants Controls
Mean score±SD p-value Mean score±SD p-value Mean score±SD p-value
Obsession (YBOCS) CC 4.2±4.6 0.742 1.8±2.2 0.661 1.7±1.5 0.498
AC 3.6±4.4 1.3±2.5 1.0±0.0
AA 1.0 1.0 1.0
Compulsion (YBOCS) CC 2.9±3.1 0.787 1.4±1.8 0.810 1.3±0.9 0.644
AC 3.2±3.3 1.1±0.3 1.0±0.0
AA 1.0 1.0 1.0
Social (BSPS) phobia CC 12.9±11.0 0.555 12.1±10.1 0.353 10.5±7.2 0.615
AC 8.8±10.9 16.5±11.1 8.7±1.3
AA 10.0 18.0 5.0
Obsessive-compulsive drinking (OCDS) CC 18.9±11.1 0.681 3.2±2.3 0.757 3.5±1.7 0.926
AC 15.8±13.2 3.7±3.3 3.3±0.8
AA 14.0 3.0 4.0
Depression (Zung) CC 35.9±11.0 0.881 31.1±7.4 0.653 23.0±3.8 0.311
AC 34.9±11.5 29.3±6.1 21.8±2.4
AA 31.0 27.0 28.0
Anxiety (Zung) CC 34.9±8.4 0.535 30.1±6.9 0.886 22.6±3.1 0.742
AC 31.9±7.1 31.1±5.6 22.7±3.4
AA 31.0 29.0 25.0
Aggression (BDHI) CC 24.3±10.8 0.853 20.5±10.3 0.735 14.8±8.8 0.220
AC 26.0±7.2 19.6±7.4 10.2±4.1
AA 21.0 13.0 25.0
Alcohol dependence – severity (AUDIT) CC 23.0±6.8 0.069
AC 28.4±4.0
AA 23.0

AUDIT – Alcohol Use Disorders Identification Test; BDHI – Buss-Durkee Hostility Inventory; BSPS – Brief Social Phobia Scale; OCDS – Obsessive Compulsive Drinking Scale; YBOCS – Yale-Brown Obsessive Compulsive Scale

Associations between CARD8 rs2043211 genotypes and alcohol-related mental disorders

Mental disorder CARD8 genotype Hospitalised alcohol-dependent patients Abstinent alcohol-dependent subjects Controls
Mean score±SD p-value Mean score±SD p-value Mean score±SD p-value
Obsession (YBOCS) AA 3.6±4.0 0.244 1.4±1.9 0.203 1.5±1.3 0.591
AT 2.7±5.1 2.0±2.0 1.8±1.7
TT 2.2±2.2 2.8±4.0 1.8±1.3
Compulsion (YBOCS) AA 2.9±3.5 0.481 1.3±1.9 0.960 1.2±0.6 0.406
AT 3.0±2.9 1.5±1.3 1.4±1.2
TT 1.7±1.7 1.4±0.9 1.3±0.6
Social phobia (BSPS) AA 10.2±8.8 0.291 11.7±8.2 0.567 10.9±7.7 0.695
AT 12.7±11.5 13.9±12.3 10.2±7.0
TT 16.0±10.3 13.2±10.8 9.1±4.4
Obsessive-compulsive drinking (OCDS) AA 16.2±11.6 0.161 3.5±2.7 0.401 3.5±1.4 0.027
AT 18.9±10.9 2.9±2.0 3.9±2.0
TT 24.1±10.8 2.5±0.9 2.6±0.8
Depression (Zung) AA 34.1±8.3 0.560 30.0±6.7 0.418 23.5±4.3 0.201
AT 36.6±11.7 31.5±8.0 22.1±3.3
TT 37.1±16.3 33.6±6.5 23.4±3.7
Anxiety (Zung) AA 32.9±6.2 0.320 29.1±5.6 0.048 23.0±3.5 0.477
AT 35.5±9.1 30.8±7.4 22.1±2.7
TT 36.1±10.6 36.4±9.5 22.5±2.5
Aggression (BDHI) AA 26.0±8.7 0.534 19.8±8.3 0.758 15.0±9.0 0.970
AT 23.3±11.6 20.7±11.9 14.2±9.3
TT 23.4±11.6 23.0±10.3 14.3±6.5
Alcohol dependence – severity (AUDIT) AA 23.4±6.5 0.818
AT 23.9±7.2
TT 22.3±5.4

Bolded p-values are statistically significant (p<0.05). AUDIT – Alcohol Use Disorders Identification Test; BDHI – Buss-Durkee Hostility Inventory; BSPS – Brief Social Phobia Scale; OCDS – Obsessive Compulsive Drinking Scale; YBOCS – Yale-Brown Obsessive Compulsive Scale

Discussion

We found that CARD8 rs2043211 was associated with the risk of alcohol dependence, but found no such association for NLPR3 rs35829419. However, our findings are limited only to males. A recent study on rodents (22) reported NLPR3 inflammasome-dependent differences in alcohol consumption between male and female mice, but there are no reports of similar kind in humans.

Another significant association we did observe is the one between CARD8 rs2043211 and anxiety in abstinent alcohol-dependent participants. This finding supports the hypothesis that inflammasome could contribute to the development of psychiatric disorders associated with alcohol dependence (33, 34, 35). To the best of our knowledge, this is the first such finding, as no human study conducted so far reported a direct association between CARD8 and anxiety in alcohol dependents.

The limitation of our study is a relatively small but ethnically homogeneous sample. The advantage is that all the questionnaires were applied by the same rater.

In conclusion, our findings point to a link between the genes of the innate immune system and alcohol dependence. However, further studies with larger cohorts are required to confirm these preliminary findings.

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