Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools

Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whethe...

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Main Authors: Heejin Jin, Sanghun Lee, Sungho Won
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-12-01
Series:Frontiers in Genetics
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fgene.2020.597420/full
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spelling doaj-c1b17cecbc7743118e2545cb21e5ac2d2020-12-21T15:17:18ZengFrontiers Media S.A.Frontiers in Genetics1664-80212020-12-011110.3389/fgene.2020.597420597420Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization ToolsHeejin Jin0Heejin Jin1Sanghun Lee2Sungho Won3Sungho Won4Sungho Won5Department of Public Health Sciences, Seoul National University, Seoul, South KoreaDepartment of Biostatistics, Medical Research Collaborating Center, Seoul National University Boramae Hospital, Seoul, South KoreaDepartment of Medical Consilience, Graduate School, Dankook University, Yongin-si, South KoreaDepartment of Public Health Sciences, Seoul National University, Seoul, South KoreaInstitute of Health and Environment, Seoul National University, Seoul, South KoreaRexSoft Corp., Seoul, South KoreaMultiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mendelian randomization (MR). The summary statistics for FPG, 2h-PG, and HbA1c level were obtained through meta-analyses of large-scale genome-wide association studies that included data from 133,010 nondiabetic individuals from collaborating Meta-analysis of Glucose and Insulin Related Traits Consortium studies. Thereafter, based on the statistical assumptions for MR analyses, the most reliable approaches including inverse-variance-weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation (SIMEX), weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were applied to identify traits affected by FPG, 2h-PG, and HbAlc. We found that coronary artery disease is affected by FPG, as per the IVW [log odds ratio (logOR): 0.21; P = 0.012], MR-Egger (SIMEX) (logOR: 0.22; P = 0.014), MR-PRESSO (logOR: 0.18; P = 0.045), and weighted median (logOR: 0.29; P < 0.001) methods but not as per the MR-Egger (logOR: 0.13; P = 0.426) approach. Furthermore, low-density lipoprotein cholesterol levels are affected by HbA1c, as per the IVW [beta (B): 0.23; P = 0.015), MR-Egger (B: 0.45; P = 0.046), MR-Egger (SIMEX) (B: 0.27; P = 0.007), MR-PRESSO (B; 0.14; P = 0.010), and the weighted median (B: 0.15; P = 0.012] methods. Further studies of the associated biological mechanisms are required to validate and understand the disease-specific differences identified in the TD2-related causal effects of each trait.https://www.frontiersin.org/articles/10.3389/fgene.2020.597420/fullmendelian randomizationinstrumental variables analysiscausal relationshiprisk factorfasting glucose2-h postload glucose
collection DOAJ
language English
format Article
sources DOAJ
author Heejin Jin
Heejin Jin
Sanghun Lee
Sungho Won
Sungho Won
Sungho Won
spellingShingle Heejin Jin
Heejin Jin
Sanghun Lee
Sungho Won
Sungho Won
Sungho Won
Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools
Frontiers in Genetics
mendelian randomization
instrumental variables analysis
causal relationship
risk factor
fasting glucose
2-h postload glucose
author_facet Heejin Jin
Heejin Jin
Sanghun Lee
Sungho Won
Sungho Won
Sungho Won
author_sort Heejin Jin
title Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools
title_short Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools
title_full Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools
title_fullStr Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools
title_full_unstemmed Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools
title_sort causal evaluation of laboratory markers in type 2 diabetes on cancer and vascular diseases using various mendelian randomization tools
publisher Frontiers Media S.A.
series Frontiers in Genetics
issn 1664-8021
publishDate 2020-12-01
description Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mendelian randomization (MR). The summary statistics for FPG, 2h-PG, and HbA1c level were obtained through meta-analyses of large-scale genome-wide association studies that included data from 133,010 nondiabetic individuals from collaborating Meta-analysis of Glucose and Insulin Related Traits Consortium studies. Thereafter, based on the statistical assumptions for MR analyses, the most reliable approaches including inverse-variance-weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation (SIMEX), weighted median, and MR-pleiotropy residual sum and outlier (MR-PRESSO) methods were applied to identify traits affected by FPG, 2h-PG, and HbAlc. We found that coronary artery disease is affected by FPG, as per the IVW [log odds ratio (logOR): 0.21; P = 0.012], MR-Egger (SIMEX) (logOR: 0.22; P = 0.014), MR-PRESSO (logOR: 0.18; P = 0.045), and weighted median (logOR: 0.29; P < 0.001) methods but not as per the MR-Egger (logOR: 0.13; P = 0.426) approach. Furthermore, low-density lipoprotein cholesterol levels are affected by HbA1c, as per the IVW [beta (B): 0.23; P = 0.015), MR-Egger (B: 0.45; P = 0.046), MR-Egger (SIMEX) (B: 0.27; P = 0.007), MR-PRESSO (B; 0.14; P = 0.010), and the weighted median (B: 0.15; P = 0.012] methods. Further studies of the associated biological mechanisms are required to validate and understand the disease-specific differences identified in the TD2-related causal effects of each trait.
topic mendelian randomization
instrumental variables analysis
causal relationship
risk factor
fasting glucose
2-h postload glucose
url https://www.frontiersin.org/articles/10.3389/fgene.2020.597420/full
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