Dataset Information

CRY1 Variations Impacts on the Depressive Relapse Rate in a Sample of Bipolar Patients.

ABSTRACT:

Objective

A relevant part of the social and personal burden caused by Bipolar Disorder (BD) is related to depressive phases. Authors investigated the genetic impact of a set of variations located in CRY1, a gene involved in the control of the circadian rhythms, towards depressive episodes in a sample of bipolar patients from the STEP-BD sample. As a secondary analysis, CYR1 variations were analyzed as predictors of sleep disruption.

Methods

654 bipolar patients were included in the analysis. Data were available genome-wide. The part of the genome coding for the CRY1 was imputed and pruned according to standards in the field. 7 SNPs were available for the analysis. A correction for multitesting was applied and we had sufficient power (0.80) to detect a small-medium effect size (0.22) between two allelic frequencies each one represented by at least 300 subjects.

Results

Intronic rs10861688 was associated with the number of depressive events corrected for the times patients were assessed during the period of observation. In particular, AA subjects (n=21) had 4.46±3.15 events, AG (n=141) had 3.08±3.17 and GG (n=342) 2.65±2.97 (p=0.0048, beta=-0.22). No other significant associations were reported.

Conclusion

We bring further evidence that genes involved in the regulation of circadian rhythms may be relevant to depressive bipolar phases. Independent confirmation analyses are mandatory.

SUBMITTER: Drago A

PROVIDER: S-EPMC4310909 | biostudies-literature | 2015 Jan

REPOSITORIES: biostudies-literature

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Publications

CRY1 Variations Impacts on the Depressive Relapse Rate in a Sample of Bipolar Patients.

Drago Antonio A Monti Barbara B De Ronchi Diana D Serretti Alessandro A

Psychiatry investigation 20150112 1

<h4>Objective</h4>A relevant part of the social and personal burden caused by Bipolar Disorder (BD) is related to depressive phases. Authors investigated the genetic impact of a set of variations located in CRY1, a gene involved in the control of the circadian rhythms, towards depressive episodes in a sample of bipolar patients from the STEP-BD sample. As a secondary analysis, CYR1 variations were analyzed as predictors of sleep disruption.<h4>Methods</h4>654 bipolar patients were included in th ...[more]

PMID: 25670954

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Project description:Introduction Bipolar disorder (BD) is a chronic hereditary disorder. Trial and error principles and long period of untreated disorder mandate further research. Relatively recent advances in statistical computing and techniques introduced Polygenic risk scores (PRS) as predictors of the genetic susceptibility to diseases. Although they provide an estimate of the risk of developing specific pathologies, they are a genome-wide measure. PRS do not provide specific information on the biological meaning of the variants. The use of subsets of risk variants (limited to one or few related biological pathways) to calculate pathway-PRS (pPRS) may provide an estimate of the functioning of specific molecular cascades. Objectives In the present study we calculated pPRS and tested them as potential predictive factors which, together with other clinical/environmental features, may estimate the treatment outcome of BD individuals in a clinical realistic treatment environment. Methods 1538 BD (41.39+/-12.66 years, 59.17% females) individuals from STEP-BD were included in the analysis. A latent class analysis identified three groups of patients according to the YMRS and MADRS scores variations during ˜ 1 year (308.47+/-293.83 days YMRS, 357.78+/-367.76 days MADRS). A GWAS analysis with clinical covariates provided the input for pPRS calculation. SNPs with best nominal significance and biologic relevance were prioritized through GTEx. A molecular pathway analysis (MPA) based on the interaction network of drugs used for treatment provided the genetic data needed for pPRS calculation. A Neural network was built using pPRS as features together with other variables (including Sex, Age, Scores at baseline) to predict the 3 groups previously identified. Performance was evaluated through 5-fold cross-validation, Python, R and Bash served for environments. Gene Ontology, ReactomePA and Bioconductor were key packages together with Cytoscape, Plink, impute and gtool. Results Ten biological networks were retrieved from MPA: 1)GO:0016705 + GO:0016641, 2)GO:0019585, 3)GO:003018, 4)GO:0099589 + GO:1904014, 5)GO:0015464 + GO:1905144, 6)GO:0004935 + GO:0004364 + GO:00031690, 7)GO:1903351 + GO:1903350, 8)GO:0016917 + GO:0007214, 9)GO:0008066 + GO:0007215, 10)GO:0048016. Risk variants within the genes contained in each group were used to compute pPRS. The ten pPRS were used to compute a neural network to predict treatment outcomes. Conclusions BD treatment is influenced by socio-demographic, clinical and genetic factors. To tackle this complexity, we tried to implement an approach where the multivariate analysis encompasses clinical analysis and the biologic background of treatment response. As a result, we can infer through a hypothesis-free approach potential pathways whose alterations may estimate treatment. At the time of writing the analyses are still undergoing, the final results will be presented and discussed at the congress. Disclosure of Interest None Declared

Project description:BackgroundNumerous bio-psychosocial factors play a role in the etiology of psychiatric disorders. In this regard, the relationship between parents and their children is significantly involved in developing the offspring mental health. However, there is no clear-cut answer as to which parental bonding style is more strongly associated with psychiatric diseases of patients. This study aimed to compare parental bonding styles in patients with schizophrenia, depression, and bipolar disorder in Bushehr province, Iran in 2018.MethodsIn this cross-sectional comparative study, 130 patients with schizophrenia, depression, and bipolar disorder who referred to four outpatients psychiatric centers in Bushehr were selected using quota sampling. The patients were assessed and compared in terms of parental bonding styles. Data were collected using a valid and reliable parental bonding instrument (PBI). Data were analyzed using SPSS software (ver. 22), Chi-square and Kruskal-Wallis tests at a significant level of 0.05.ResultsResults showed that the optimal parental bonding style (low control, high care) in bipolar disorder (43.05%), major depression (47.7%), and schizophrenia (38.5%) was the most prevalent style of parental bonding; however, 62.30% of the above patients suffered from inefficient paternal bonding styles and 51.53% from inefficient maternal bonding styles. Furthermore, the patients' maternal bonding styles were significantly different (p = 0.007) while their paternal bonding styles did not show any significant differences (p = 0.848).ConclusionsMost of the patients with psychiatric disorders were affected by ineffective parenting styles. The results also confirmed that despite the several bio-psycho-social factors involved in the development of psychiatric disorders, the crucial roles of parents, especially mothers, should not be ignored. It was further suggested that parents and parental bonding were important and fundamental factors for mental health promotion.

Dataset Information

CRY1 Variations Impacts on the Depressive Relapse Rate in a Sample of Bipolar Patients.

Objective

Methods

Results

Conclusion

Publications

CRY1 Variations Impacts on the Depressive Relapse Rate in a Sample of Bipolar Patients.

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