Addiction
Research & Therapy
Cocchi et al., J Addict Res Ther 2014, 5:2 http://dx.doi.org/10.4172/2155-6105.1000177
Open Access
Research Article
Sulfur Amino Acid Metabolic Process Pathway may Modulate Bipolar Disorder with Alcohol Dependence Comorbidity Enrico Cocchi1, Antonio Drago2* and Alessandro Serretti1 1 2
Department of Biomedical and NeuroMotor Sciences, University of Bologna, Italy IRCCS Centro S. Giovanni di Dio, Fatebenefratelli, Brescia, Italy
Abstract Background: A relationship between alcohol use disorder and Bipolar Disorder (BD) has far been detected. A record of alcohol dependence may worsen the course of BD. Nevertheless, the genetic underpinnings of this comorbidity have not been completely elucidated. Authors investigated the impact of a set of genetic variations as possible risk factors for the pathological mood swings in bipolar patients with a record of alcohol dependence. Methods: A list of candidate genes identified as risk loci by GWAS studies in last 10 years were tested in a sample of 802 bipolar patients from the public available STEP-BD study. Variations harbored by these genes were checked for quality, imputed and pruned. A set of 260 genes embedded in 160 different pathways were analyzed as predictors of the frequency of severe (YMRS>11) manic events and depressive phases (MADRS>19) during the period of observation (1139 days for manic records and 1856 for depressive records). Their effect was tested in combination with alcohol comorbidity. Clinical and sociodemographic variables entered the study as covariates when significantly associated with the phenotypes. Results: We found an impact of alcohol dependence positive record with a higher frequency of severe manic (p=0.02) and depressive (p=0.0006) records. A positive association between a pathway related to the Sulfur amino acid metabolic process (GO:0000096) and an increased frequency of severe depressive records was detected for BD subjects with a record of alcohol dependence. Discussion: We found an association between GO: 0000096 (Sulfur amino acid metabolic process pathway) and severe depressive episodes in BD patients with a record of alcohol dependence in their clinical story.
Keywords: Alcohol; Dependence; Bipolar disorder; Genetics; Pathway; Severity Introduction Alcohol comorbidity in Bipolar Disorder (BD) attracted much attention during the last years [1] because of its relevant impact on prognosis. Co-occurrence of alcohol misuse during BD is common [2,3] and patients with both types of disorder are typically more difficult to treat than patients who have either problem alone [4]. BD shows a 1% prevalence worldwide, which rises up to 6.4% when subthreshold cases are, included [5]. Its costs were estimated to be $45.2 billion in 1991 (in the U.S.) [6]. Alcohol use disorders concern 25% of adults in the U.S. [7] overall economic cost was estimated to be $148 billion for 1992, $166.6 billion in 1995 and $184.6 billion in 1998 [8]. Moreover, alcohol use is the third leading preventable cause of death [9]. Thus, the costs of the combination of BD and alcohol use disorders are extremely high [10] and projected to increase. In this prospective alcohol dependence is one of the biggest problems related to alcohol [11] and its impact is particularly high in BD patients. Studies showed that 27.6% of any BD and especially 31.5% of BD type I patients suffered of alcohol dependence [12]. This comorbidity resulted in an increased risk for suicide attempt, greater severity of symptoms and impaired functioning. Compared with the lower rate of patients that suffer comorbidity of alcohol dependence with unipolar depression (11.6%) or with any mood disorder (4.9%), BD and alcohol dependence reveals a even stronger relationship [12]. As a consequence, the proper treatment of BD patients and the identification of subjects at risk is a priority. Consistently, a brain degeneration during BD is reported to be a late-phase characteristic that depends on the number of episodes of illness [13] and alcohol dependence could play a role in worsening this relapses number. Moreover, a proper treatment following the identification of BD patients at risk for alcohol dependence could J Addict Res Ther ISSN:2155-6105 JART an open access journal
successfully decrease the number of bipolar relapses through life and their severity. As genetics reveals, both BD and alcohol dependence are heritable [14,15]. Interestingly, in BD, there are lines of evidence that 71% of the genetic variance for mania was not shared with depression [15]. Several attempts tried to elucidate the genetic background leading alcohol dependence but results are not conclusive so far. Aldehyde dehydrogenase 2 (ALDH2), alcohol dehydrogenase 1B (ADH1B), gamma-aminobutyric acid (GABA) A receptor, and the GABA alpha 2 (GABRA2) receptors pathway were recently reported to be central to alcohol misbehavior [16]. Nevertheless, there is sufficient evidence to say that the genetic liability to BD and alcohol dependence is derived from the orchestrated activity of a set of genes and not by a single one. Starting from this perspective, we 1) collected all the genes identified as possible risk loci for alcohol dependence in the last 10 years of GWAS studies in the field and 2) described the biological pathways they are relate to 3) analyzed the influence of the variations on the genes that code for the proteins that are embedded in these pathways on the frequency of both severe (Young Mania Rating Scale (YMRS) overall score>11) manic events and depressive phases (Montgomery-
*Corresponding author: Antonio Drago, Institute of Psychiatry, University of Bologna, Viale Carlo Pepoli 5, 40123 Bologna, Italy, Tel +39 051 6584233, +39 320 4269332, +39 347 3024020; Fax +39 051 521030; E-mail:
[email protected] Received January 16, 2014; Accepted March 29, 2014; Published March 31, 2014 Citation: Cocchi E, Drago A, Serretti A (2014) Sulfur Amino Acid Metabolic Process Pathway may Modulate Bipolar Disorder with Alcohol Dependence Comorbidity. J Addict Res Ther 5: 177. doi: 10.4172/2155-6105.1000177 Copyright: © 2014 Cocchi E, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Volume 5 • Issue 2 • 1000177
Citation: Cocchi E, Drago A, Serretti A (2014) Sulfur Amino Acid Metabolic Process Pathway may Modulate Bipolar Disorder with Alcohol Dependence Comorbidity. J Addict Res Ther 5: 177. doi: 10.4172/2155-6105.1000177
Page 2 of 9 Asberg Depression Scale (MADRS) overall score >19) in BD patients. Considering the enormous difference in GWAS results, we also enriched our initial subset of genes with Cytoscape [17] in order to considering the major number of associated genes and pathways in the analysis. As a clear clinical conclusion, the definition of the genetic impact on alcohol dependence and BD comorbidity could be instrumental to the early diagnosis and even to primary prevention of BD in patients who also present with alcohol dependence.
Methods Sample under investigation The sample under investigation was retrieved from the public available STEP-BD protocol [18]. During the study, bipolar patients of every subtype with age ≥ 15 years are accessioned into a study registry. All patients receive a systematic assessment battery at entry and are treated by a psychiatrist (trained to deliver care and measure outcomes in patients with BD) using a series of model practice procedures consistent with expert recommendations. At every follow-up visit, the treating psychiatrist completes a standardized assessment and assigns an operationalized clinical status based on DSM-IV criteria. Patients have independent evaluations at regular intervals throughout the study and remain under the care of the same treating psychiatrist while making transitions between randomized care studies and the standard care treatment pathways. We were able to identify 802 patients assessed with the MADRS and YMRS scales. Characteristics of the samples under analysis is reported in Table 1.
Definition of phenotype The phenotype under analysis was the number of severe manic phases (manic relapses with an overall YMRS [19] point>11) and severe depressive episodes (depressive episodes with MADRS [20] total score >19) corrected for the number of observations during the STEP-BD period of observation. We took these thresholds (YMRS>11 and MADRS>19) accordingly to the standard YMRS and MADRS interpretation to defining manic phases [19] and depressive ones [21] severity in order to avoid stratification factors due to different interpretation of these assessment scales. This particular phenotype was chosen to limit the impact of missing values in order to increase the power of the study. Care was taken to control for a possible clinical bias: more severe patients might have been seen more often compared to less severe ones. In order to do so, the correlations between the phenotype
of choice and a set of other phenotypes calculated at standard time points (number of manic/depressive phases from 30-90- 120 and so forth days from the beginning of the study) - a more classical approach to this kind of studies - were calculated. We had confirmation that the phenotype under analyses significantly correlated with almost all the phenotypes at different timepoints, with the advantage of having 0% of missing values. Results are reported in Table 2 (mania) and Table 3 (depression). The only timepoint at which the correlation was not significant was after 30 days from the beginning of the study for the manic relapses. Nevertheless, the number of missing information for this timepoint (43.89%) may be held accountable for the lack of association. Subjects were labeled as alcohol dependent when there was a record of alcohol dependence in the past. This variable was used instead of alcohol dependence during the manic/depressive phase to distinguish the hedonistic use of alcohol during manic/depressive phases vs. a record of alcohol dependence which was deemed to be more related to a chronic habit. The alcohol dependence record in STEP-BD was assessed using the Mini Mental State Evaluation as the presence of clearly symptoms of alcohol dependence (not only alcohol abuse) during the last 12 months [19].
Study of stratification factors The sociodemographic and clinical variables were investigated as possible stratification factors. Age and gender were included in the analysis as covariates. Gender of patients resulted to be significantly associated with the phenotype (p=0.001). Ethnicity was not included as covariate because all patients resulted to be Caucasian. Table 1 reports the characteristics of the sample and the strength of association between the sociodemographic variables and the record of alcohol dependence in the past in bipolar subjects.
Power of the study and correction for multiple testing We had sufficient power (0.80) to detect a medium effect size of 0.09 with a significance level of 0.05 between two alleles represented in a sample of 401 subjects each. Both a Bonferroni correction (p 11 manic episode frequency / times observed
0.16 ± 0.24
0.19 ± 0.26
0.14 ± 0.23
T = -2.3327 df = 445.442 p-value = 0.02011
MADRS > 19 episode frequency / times observed
0.31 ± 0.33
0.37 ± 0.34
0.28 ± 0.32
T = -3.4181 df = 474.914 p-value = 0.0006848
Ethnicity
WhiteorCaucasian=802(100.0%)
WhiteorCaucasian=257(100.0%)
WhiteorCaucasian=545(100.0%)
/
The table is a resumen of the clinical characteristics of the patients taken into account for the study. YMRS=Young Mania Rating Scale MADRS=Montgomery Asberg Depression Rating Scale SD=Standard Deviation Table 1: Sample under analysis.
J Addict Res Ther ISSN:2155-6105 JART an open access journal
Volume 5 • Issue 2 • 1000177
Citation: Cocchi E, Drago A, Serretti A (2014) Sulfur Amino Acid Metabolic Process Pathway may Modulate Bipolar Disorder with Alcohol Dependence Comorbidity. J Addict Res Ther 5: 177. doi: 10.4172/2155-6105.1000177
Page 3 of 9 days from baseline
manic relapses per time
missing (%)*
mean manic relapses per visit unit
p
t
conf 1
0
0.18
43.89
0.16 ± 0.24
0.18
-1.35
-0.09
conf 2 0.02
30
0.18
8.98
0.16 ± 0.24
0.02
-2.27
-0.09
-0.01
60
0.18
2.87
0.16 ± 0.24
0.02
-2.33
-0.09
-0.01
90
0.18
2.49
0.16 ± 0.24
0.02
-2.33
-0.09
-0.01
120
0.18
1.62
0.16 ± 0.24
0.02
-2.41
-0.09
-0.01
150
0.17
1.37
0.16 ± 0.24
0.02
-2.39
-0.09
-0.01
180
0.17
1.37
0.16 ± 0.24
0.02
-2.39
-0.09
-0.01
210
0.17
0.75
0.16 ± 0.24
0.02
-2.34
-0.08
-0.01
240
0.17
0.5
0.16 ± 0.24
0.02
-2.27
-0.08
-0.01
270
0.17
0.37
0.16 ± 0.24
0.02
-2.29
-0.08
-0.01
300
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
330
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
360
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
390
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
420
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
450
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
480
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
510
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
540
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
570
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
600
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
630
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
660
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
690
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
720
0.18
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
750
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
780
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
810
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
840
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
870
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
900
0.17
0.12
0.16 ± 0.24
0.02
-2.32
-0.08
-0.01
930
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
960
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
990
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
1020
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
1050
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
1080
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
1110
0.17
0
0.16 ± 0.24
0.02
-2.33
-0.08
-0.01
The table shows the statistics of association between the analyzed phenotype of the patients (total number of severe manic relapses corrected for the total number of observation for each patient) and the number of manic relapses at specific timepoints (every 30 days from the beginning of the study) that is a more classical approach for these kind of studies but is related to a bigger number of missings (totally avoided with our phenotype) and clinical bias (e.g. more severe patients might have been seen more often compared to less severe ones.). Table 2: Study of the correlation between the phenotype under analysis and the number of manic relapses at specific timepoints. days from baseline
depressive phases per time
missing (%)*
mean depressive phases per visit unit
p
t
conf 1
conf 2
0
0.54
43.64
0.31 ± 0.33
0.02
-2.35
-0.15
-0.01
30
0.58
8.48
0.31 ± 0.33
0.002
-3.03
-0.13
-0.03
60
0.58
2.74
0.31 ± 0.33
0.001
-3.13
-0.13
-0.03
90
0.58
2.37
0.31 ± 0.33
0.001
-3.22
-0.13
-0.03
120
0.59
1.5
0.31 ± 0.33
0.001
-3.17
-0.13
-0.03
150
0.59
1.25
0.31 ± 0.33
0.001
-3.28
-0.14
-0.03
180
0.59
1.12
0.31 ± 0.33
0.001
-3.26
-0.14
-0.03
210
0.58
0.75
0.31 ± 0.33
