scholarly journals Pathway Analysis Using Information from Allele-Specific Gene Methylation in Genome-Wide Association Studies for Bipolar Disorder

PLoS ONE ◽  
2013 ◽  
Vol 8 (1) ◽  
pp. e53092 ◽  
Author(s):  
Li-Chung Chuang ◽  
Chung-Feng Kao ◽  
Wei-Liang Shih ◽  
Po-Hsiu Kuo
Author(s):  
Tim B Bigdeli ◽  
Ayman H Fanous ◽  
Yuli Li ◽  
Nallakkandi Rajeevan ◽  
Frederick Sayward ◽  
...  

Abstract Background Schizophrenia (SCZ) and bipolar disorder (BIP) are debilitating neuropsychiatric disorders, collectively affecting 2% of the world’s population. Recognizing the major impact of these psychiatric disorders on the psychosocial function of more than 200 000 US Veterans, the Department of Veterans Affairs (VA) recently completed genotyping of more than 8000 veterans with SCZ and BIP in the Cooperative Studies Program (CSP) #572. Methods We performed genome-wide association studies (GWAS) in CSP #572 and benchmarked the predictive value of polygenic risk scores (PRS) constructed from published findings. We combined our results with available summary statistics from several recent GWAS, realizing the largest and most diverse studies of these disorders to date. Results Our primary GWAS uncovered new associations between CHD7 variants and SCZ, and novel BIP associations with variants in Sortilin Related VPS10 Domain Containing Receptor 3 (SORCS3) and downstream of PCDH11X. Combining our results with published summary statistics for SCZ yielded 39 novel susceptibility loci including CRHR1, and we identified 10 additional findings for BIP (28 326 cases and 90 570 controls). PRS trained on published GWAS were significantly associated with case-control status among European American (P < 10–30) and African American (P < .0005) participants in CSP #572. Conclusions We have demonstrated that published findings for SCZ and BIP are robustly generalizable to a diverse cohort of US veterans. Leveraging available summary statistics from GWAS of global populations, we report 52 new susceptibility loci and improved fine-mapping resolution for dozens of previously reported associations.


2019 ◽  
Vol 84 (6) ◽  
pp. 240-255
Author(s):  
Lei Zhang ◽  
Charalampos Papachristou ◽  
Pankaj K. Choudhary ◽  
Swati Biswas

<b><i>Background:</i></b> Pathway analysis allows joint consideration of multiple SNPs belonging to multiple genes, which in turn belong to a biologically defined pathway. This type of analysis is usually more powerful than single-SNP analyses for detecting joint effects of variants in a pathway. <b><i>Methods:</i></b> We develop a Bayesian hierarchical model by fully modeling the 3-level hierarchy, namely, SNP-gene-pathway that is naturally inherent in the structure of the pathways, unlike the currently used ad hoc ways of combining such information. We model the effects at each level conditional on the effects of the levels preceding them within the generalized linear model framework. To deal with the high dimensionality, we regularize the regression coefficients through an appropriate choice of priors. The model is fit using a combination of iteratively weighted least squares and expectation-maximization algorithms to estimate the posterior modes and their standard errors. A normal approximation is used for inference. <b><i>Results:</i></b> We conduct simulations to study the proposed method and find that our method has higher power than some standard approaches in several settings for identifying pathways with multiple modest-sized variants. We illustrate the method by analyzing data from two genome-wide association studies on breast and renal cancers. <b><i>Conclusion:</i></b> Our method can be helpful in detecting pathway association.


2016 ◽  
Author(s):  
Liping Hou ◽  
Sarah E. Bergen ◽  
Nirmala Akula ◽  
Jie Song ◽  
Christina M. Hultman ◽  
...  

ABSTRACTBipolar disorder (BD) is a genetically complex mental illness characterized by severe oscillations of mood and behavior. Genome-wide association studies (GWAS) have identified several risk loci that together account for a small portion of the heritability. To identify additional risk loci, we performed a two-stage meta-analysis of >9 million genetic variants in 9,784 bipolar disorder patients and 30,471 controls, the largest GWAS of BD to date. In this study, to increase power we used ~2,000 lithium-treated cases with a long-term diagnosis of BD from the Consortium on Lithium Genetics, excess controls, and analytic methods optimized for markers on the X-chromosome. In addition to four known loci, results revealed genome-wide significant associations at two novel loci: an intergenic region on 9p21.3 (rs12553324, p = 5.87×10−9; odds ratio = 1.12) and markers within ERBB2 (rs2517959, p = 4.53×10−9; odds ratio = 1.13). No significant X-chromosome associations were detected and X-linked markers explained very little BD heritability. The results add to a growing list of common autosomal variants involved in BD and illustrate the power of comparing well-characterized cases to an excess of controls in GWAS.


2009 ◽  
Vol 14 (4) ◽  
pp. 351-353 ◽  
Author(s):  
H M Ollila ◽  
P Soronen ◽  
K Silander ◽  
O M Palo ◽  
T Kieseppä ◽  
...  

2008 ◽  
Vol 13 (5) ◽  
pp. 466-467 ◽  
Author(s):  
A E Baum ◽  
M Hamshere ◽  
E Green ◽  
S Cichon ◽  
M Rietschel ◽  
...  

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