Dataset Information

Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

ABSTRACT: Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power. To identify potential pleiotropic genes for these three disorders, we performed a systematic analysis by incorporating GWAS (genome-wide associated study) datasets of six correlated traits related to type 2 diabetes, obesity and dyslipidemia using Meta-CCA (meta-analysis using canonical correlation analysis). Meta-CCA is an emerging method to systematically identify potential pleiotropic genes using GWAS summary statistics of multiple correlated traits. 2,720 genes were identified as significant genes after multiple testing (Bonferroni corrected p value < 0.05). Further, to refine the identified genes, we tested their relationship to the six correlated traits using VEGAS-2 (versatile gene-based association study-2). Only the genes significantly associated (Bonferroni corrected p value < 0.05) with more than one trait were kept. Finally, 25 genes (including two confirmed pleiotropic genes and eleven novel pleiotropic genes) were identified as potential pleiotropic genes. They were enriched in 5 pathways including the statin pathway and the PPAR (peroxisome proliferator-activated receptor) Alpha pathway. In summary, our study identified potential pleiotropic genes and pathways of type 2 diabetes, obesity and dyslipidemia, which may shed light on the common biological etiology and pathogenesis of these three disorders and provide promising insights for new therapies.

SUBMITTER: Chen YC

PROVIDER: S-EPMC6093635 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Chen Yuan-Cheng YC Xu Chao C Zhang Ji-Gang JG Zeng Chun-Ping CP Wang Xia-Fang XF Zhou Rou R Lin Xu X Ao Zeng-Xin ZX Lu Jun-Min JM Shen Jie J Deng Hong-Wen HW

PloS one 20180815 8

Previous studies have demonstrated the genetic correlations between type 2 diabetes, obesity and dyslipidemia, and indicated that many genes have pleiotropic effects on them. However, these pleiotropic genes have not been well-defined. It is essential to identify pleiotropic genes using systematic approaches because systematically analyzing correlated traits is an effective way to enhance their statistical power. To identify potential pleiotropic genes for these three disorders, we performed a s ...[more]

PMID: 30110382

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Project description:BackgroundClinical trials have demonstrated an increased risk of cardiotoxicity in patients with breast cancer (bca) receiving trastuzumab-based therapy. Diabetes, dyslipidemia, and obesity are known risk factors for cardiovascular disease. Studies have yielded conflicting results about whether those factors increase the risk of cardiotoxicity in patients with bca receiving trastuzumab.MethodsIn this retrospective cohort study, data were collected for 243 patients with bca positive for her2 (the human epidermal growth factor receptor 2) who were receiving trastuzumab and who were referred to The Ottawa Hospital Cardio-oncology Referral Clinic between 2008 and 2013. The data collected included patient demographics, reason for referral, cardiac function, chemotherapy regimen (including anthracycline use), and 3 comorbidities (diabetes, dyslipidemia, obesity). Rates of symptomatic cancer treatment-related cardiac dysfunction (sctcd) and asymptomatic decline in left ventricular ejection fraction (adlvef) were calculated for patients with and without the comorbidities of interest.ResultsOf the 243 identified patients, 104 had either diabetes, dyslipidemia, or obesity. In that population, the most likely reason for referral to the cardio-oncology clinic was adlvef. The combination of 2 or 3 comorbidities significantly increased the incidence of sctcd in our population, reaching a rate of 67% for patients with obesity and dyslipidemia [relative risk (rr): 2.2; p = 0.04], 69% for patients with obesity and diabetes (rr: 2.3; p = 0.02), and 72% for patients with all 3 risk factors (rr: 2.4; p = 0.08).ConclusionsThe combination of 2 or 3 comorbidities significantly increases the incidence of symptomatic cancer treatment-related cardiotoxicity. Patients with bca experiencing cancer treatment-related cardiotoxicity who have a history of diabetes, dyslipidemia, and obesity might require more proactive strategies for prevention, detection, and treatment of cardiotoxicity while receiving trastuzumab-based treatment.

Project description:Cardiovascular disease and diabetes represent a major public health concern. The former is the most frequent cause of death and disability in patients with type 2 diabetes, where left ventricular dysfunction is highly prevalent. Moreover, diabetic retinopathy is becoming a dominant cause of visual impairment and blindness. The complex relation between cardiovascular disease and diabetic retinopathy as a function of ageing, obesity and hypertension remains to be clarified. Here, we investigated such relations in patients with diabetes type 2, in subjects with neither overt heart disease nor advanced proliferative diabetic retinopathy. We studied 47 patients and 50 controls, aged between 45 and 65 years, equally distributed according to gender. From the 36 measures regarding visual structure and function, and the 11 measures concerning left ventricle function, we performed data reduction to obtain eight new derived variables, seven of which related to the eye, adjusted for age, gender, body mass index and high blood pressure using both discriminant analysis (DA) and logistic regression (LR). We found moderate to strong correlation between left ventricle function and the eye constructs: minimum correlation was found for psychophysical motion thresholds (DA: 0.734; LR: 0.666), while the maximum correlation was achieved with structural volume density in the neural retina (DA: 0.786; LR: 0.788). Controlling the effect of pairwise correlated visual constructs, the parameters that were most correlated to left ventricle function were volume density in retina and thickness of the retinal nerve fiber layers (adjusted multiple R2 is 0.819 and 0.730 for DA and LR), with additional contribution of psychophysical loss in achromatic contrast discrimination. We conclude that visual structural and functional changes in type 2 diabetes are related to heart dysfunction, when the effects of clinical, demographic and associated risk factors are taken into account, revealing a genuine relation between cardiac and retinal diabetic phenotypes.

Dataset Information

Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Publications

Multivariate analysis of genomics data to identify potential pleiotropic genes for type 2 diabetes, obesity and dyslipidemia using Meta-CCA and gene-based approach.

Similar Datasets

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