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Wu X, Lin J, Xue N, Teng J, Wang Y, Li Y, Xu X, Shen Z, Ding X, Fang Y. Relationship Between Gene Polymorphism of Methylenetetrahydrofolate Reductase C677T and Left Ventricular Hypertrophy in Chinese Patients with Chronic Kidney Disease. Lab Med 2021; 52:519-527. [PMID: 33693817 DOI: 10.1093/labmed/lmab004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE This study aimed to investigate the relationship between the gene polymorphism of methylenetetrahydrofolate reductase (MTHFR) C677T and left ventricular hypertrophy (LVH) in patients with chronic kidney disease (CKD). METHODS A total of 763 Chinese patients with CKD undergoing genetic testing were included in the study. The association between the gene polymorphism of MTHFR C677T and echocardiographic parameters was analyzed through univariate and multivariate analyses. RESULTS We found a remarkably positive association between MTHFR C677T gene polymorphism and LVH indexes, including interventricular septal thickness (F = 3.8; P = .022), left ventricular posterior wall thickness (F = 3.0; P = .052), left ventricular mass (F = 3.9; P = .022), and left ventricular mass index (F = 2.6; P = .075). After adjusting for the potential confounders linking the polymorphism,we found that the positive association between the polymorphism and LVH indexes still existed in patients with CKD in some multiple linear regression models (P <.05). CONCLUSION MTHFR C677T gene polymorphism may be a genetic susceptibility marker for the development of LVH in patients with CKD.
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Affiliation(s)
- Xie Wu
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jing Lin
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ning Xue
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jie Teng
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yaqiong Wang
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yang Li
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xunhui Xu
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Ziyan Shen
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xiaoqiang Ding
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yi Fang
- Department of Nephrology, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Key Laboratory of Kidney and Blood Purification, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Medical Center of Kidney Disease, Zhongshan Hospital, Fudan University, Shanghai, China.,Shanghai Institute of Kidney and Dialysis, Zhongshan Hospital, Fudan University, Shanghai, China
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Price EM, Robinson WP. Adjusting for Batch Effects in DNA Methylation Microarray Data, a Lesson Learned. Front Genet 2018; 9:83. [PMID: 29616078 PMCID: PMC5864890 DOI: 10.3389/fgene.2018.00083] [Citation(s) in RCA: 51] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2017] [Accepted: 02/27/2018] [Indexed: 11/15/2022] Open
Abstract
It is well-known, but frequently overlooked, that low- and high-throughput molecular data may contain batch effects, i.e., systematic technical variation. Confounding of experimental batches with the variable(s) of interest is especially concerning, as a batch effect may then be interpreted as a biologically significant finding. An integral step toward reducing false discovery in molecular data analysis includes inspection for batch effects and accounting for this signal if present. In a 30-sample pilot Illumina Infinium HumanMethylation450 (450k array) experiment, we identified two sources of batch effects: row and chip. Here, we demonstrate two approaches taken to process the 450k data in which an R function, ComBat, was applied to adjust for the non-biological signal. In the "initial analysis," the application of ComBat to an unbalanced study design resulted in 9,612 and 19,214 significant (FDR < 0.05) DNA methylation differences, despite none present prior to correction. Suspicious of this dramatic change, a "revised processing" included changes to our analysis as well as a greater number of samples, and successfully reduced batch effects without introducing false signal. Our work supports conclusions made by an article previously published in this journal: though the ultimate antidote to batch effects is thoughtful study design, every DNA methylation microarray analysis should inspect, assess and, if necessary, account for batch effects. The analysis experience presented here can serve as a reminder to the broader community to establish research questions a priori, ensure that they match with study design and encourage communication between technicians and analysts.
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Affiliation(s)
- E. M. Price
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, BC, Canada
| | - Wendy P. Robinson
- BC Children’s Hospital Research Institute, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
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Rai V. Association of methylenetetrahydrofolate reductase (MTHFR) gene C677T polymorphism with autism: evidence of genetic susceptibility. Metab Brain Dis 2016; 31:727-35. [PMID: 26956130 DOI: 10.1007/s11011-016-9815-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2015] [Accepted: 02/23/2016] [Indexed: 01/18/2023]
Abstract
Autism (MIM 209850) is a heterogeneous neurodevelopmental disease that manifests within the first 3 years of life. Numerous articles reported that dysfunctional folate-methionine pathway enzymes may play an important role in the pathophysiology of autism. Methylenetetrahydrofolate reductase (MTHFR) is a critical enzyme of this pathway and MTHFR C677T polymorphism reported as risk factor for autism in several case control studies. However, controversial reports were also published. Hence the present meta-analysis was designed to investigate the relationship of the MTHFR C677T polymorphism with the risk of autism. Electronic databases were searched for case control studies with following search terms - 'MTHFR', 'C677T', in combination with 'Autism'. Pooled OR with its corresponding 95 % CI was calculated and used as association measure to investigate the association between MTHFR C677T polymorphism and risk of autism. Total of thirteen studies were found suitable for the inclusion in the present meta-analysis, which comprises 1978 cases and 7257 controls. Meta-analysis using all four genetic models showed significant association between C677T polymorphism and autism (ORTvs.C = 1.48; 95 % CI: 1.18-1.86; P = 0.0007; ORTT + CT vs. CC = 1.70, 95 % CI = 0.96-2.9, p = 0.05; ORTT vs. CC = 1.84, 95 % CI = 1.12-3.02, p = 0.02; ORCT vs.CC = 1.60, 95 % CI = 1.2-2.1, p = 0.003; ORTT vs.CT+CC = 1.5, 95 % CI = 1.02-2.2, p = 0.03). In total 13 studies, 9 studies were from Caucasian population and 4 studies were from Asian population. The association between C677T polymorphism and autism was significant in Caucasian (ORTvs.C = 1.43; 95 % CI = 1.1-1.87; p = 0.009) and Asian population (ORTvs.C = 1.68; 95 % CI = 1.02-2.77; p = 0.04) using allele contrast model. In conclusion, present meta-analysis strongly suggested a significant association of the MTHFR C677T polymorphism with autism.
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Affiliation(s)
- Vandana Rai
- VBS Purvanchal University, Jaunpur, 222003, UP, India.
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Kim H, Park J, Chae H, Lee GD, Lee SY, Lee JM, Oh YS, Kim M, Kim Y. Potential Risk Factors Associated With Vascular Diseases in Patients Receiving Treatment for Hypertension. Ann Lab Med 2016; 36:215-22. [PMID: 26915609 PMCID: PMC4773261 DOI: 10.3343/alm.2016.36.3.215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2015] [Revised: 02/02/2016] [Accepted: 02/11/2016] [Indexed: 11/19/2022] Open
Abstract
Background Currently, the hypertension (HTN) patients undergo appropriate medical treatment, and traditional risk factors are highly controlled. Therefore, potential risk factors of atherosclerotic vascular diseases (AVD) and venous thromboembolisms (VTE) in HTN should be reconsidered. We investigated thrombophilic genetic mutations and existing biomarkers for AVD or VTE in HTN patients receiving treatment. Methods A total of 183 patients were enrolled: AVD with HTN (group A, n=45), VTE with HTN (group B, n=62), and HTN patients without any vascular diseases (group C, n=76). The lipid profile, homocysteine (Hcy) levels, D-dimers, fibrinogen, antithrombin, lupus anticoagulant, and anti-cardiolipin antibody (aCL) were evaluated. Prothrombin G20210A, Factor V G1691A, and methylenetetrahydrofolate reductase (MTHFR) C677T and A1298C were analyzed. Results All patients revealed wild type prothrombin G20210A and Factor V G1691A polymorphisms. The frequency of MTHFR polymorphisms was 677CT (n=84, 45.9%); 677TT (n=46, 25.1%); 1298AC (n=46, 25.1%); and 1298CC (n=2, 1.1%). The MTHFR 677TT genotype tended to increase the odds ratio (OR) to AVD events in HTN patients (OR 2.648, confidence interval 0.982-7.143, P=0.05). The group A demonstrated significantly higher Hcy levels (P=0.009), fibrinogen (P=0.004), and platelet counts (P=0.04) than group C. Group B had significantly higher levels of D-dimers (P=0.0001), platelet count (P=0.0002), and aCL (P=0.02) frequency than group C. Conclusions The MTHFR 677TT genotype and Hcy level could be potential risk factors associated with development of AVD in HTN patients receiving treatment. D-dimer and aCL might be useful to estimate the occurrence of VTE in them.
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Affiliation(s)
- Hyunjung Kim
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Joonhong Park
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Catholic Genetic Laboratory Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Hyojin Chae
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Catholic Genetic Laboratory Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Gun Dong Lee
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Catholic Genetic Laboratory Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Sang Yoon Lee
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Catholic Genetic Laboratory Center, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jong Min Lee
- Division of Cardiology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Yong Seog Oh
- Division of Cardiology, Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Myungshin Kim
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Catholic Genetic Laboratory Center, College of Medicine, The Catholic University of Korea, Seoul, Korea.
| | - Yonggoo Kim
- Department of Laboratory Medicine, College of Medicine, The Catholic University of Korea, Seoul, Korea.,Catholic Genetic Laboratory Center, College of Medicine, The Catholic University of Korea, Seoul, Korea.
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