In the original article, there was an error where the description of Type 2 Diabetes Miletus (T2DM) under Data Sources, Outcomes was not clear. In this study, the T2DM data “restricted to European UK Biobank participants” was used.
A correction has been made to Data Sources, Outcomes:
“We also included cardiovascular risk factors as secondary outcomes, including blood pressure [systolic blood pressure (SBP), diastolic blood pressure (DBP) (Mitchell et al., 2019)], body mass index (BMI) (Yengo et al., 2018), glycaemic traits [fasting glucose (FG) (Lagou et al., 2021), glycated hemoglobin (HbA1c) (Wheeler et al., 2017)], and T2DM (restricted to European UK Biobank participants) (Mahajan et al., 2018),”
In addition, there were mistakes in Table 1, Supplementary Table S6, and Supplementary Figure S1 as published when describing the genetic data used for T2DM. The sample size number of T2DM (restricted to European UK Biobank participants) including case and control number was incorrect. The corrected Table 1, Supplementary Table S6, and Supplementary Figure S1 appear below.
TABLE 1
| Outcome | Abbreviation | Unit | Consortium | PMID | Sample size (case/control number) | Covariate adjustment | Ancestry |
|---|---|---|---|---|---|---|---|
| Major cardiovascular diseases | |||||||
| Coronary artery disease (Nikpay et al., 2015) | CAD | log OR | CARDIoGRAMplusC4D 1000 Genomes-based GWAS | 26343387 | 184,305 (N case = 60,801, N control = 123,504) | Study-specific covariates and genomic control | Mixed |
| Myocardial infarction (Nikpay et al., 2015) | MI | log OR | CARDIoGRAMplusC4D 1000 Genomes-based GWAS | 26343387 | 166,065 (N case = 42,561, N control = 123,504) | Study-specific covariates and genomic control | Mixed |
| Heart failure (Shah et al., 2020) | HF | log OR | HERMES | 31919418 | 977,323 (N case = 47,309, N control = 930,014) | Age, sex (except for single-sex studies) and principal components | European |
| Atrial fibrillation (Roselli et al., 2018) | AF | log OR | 2018 AF HRC GWAS | 29892015 | 537,409 (N case = 55,114, N control = 482,295) | Sex, age at first visit, genotyping array and the first ten principal components | European |
| Cardiovascular risk factors—glycaemic traits | |||||||
| Fasting glucose (Lagou et al., 2021) | FG | mmol/L | MAGIC | 33402679 | 140,595 | Gge, study site (if applicable), and principal components | European |
| Glycated hemoglobin (Wheeler et al., 2017) | HbA1c | % | MAGIC | 28898252 | 123,665 | Age, sex, and study-specific covariates | European |
| Type 2 diabetes mellitus (Mahajan et al., 2018) | T2DM | log OR | DIAMANTE T2D GWAS (restricted to European UK Biobank participants) | 29632382 | 442,817 (N case = 19,119, N control = 423,698) | Study-specific covariates | European |
| Cardiovascular risk factors—blood pressure traits | |||||||
| Systolic blood pressure (Mitchell et al., 2019) | SBP | SD | GWAS of UK Biobank | NA | 436,419 | Genotype array, sex and the first 10 principal components | European |
| Diastolic blood pressure (Mitchell et al., 2019) | DBP | SD | GWAS of UK Biobank | NA | 436,424 | Genotype array, sex and the first 10 principal components | European |
| Cardiovascular risk factors—BMI | |||||||
| Body mass index (Yengo et al., 2018) | BMI | SD | GIANT | 30124842 | 681,275 | Age, sex, recruitment centre, genotyping batches and 10 principal components | European |
| Kidney function | |||||||
| Creatinine-based estimation of GFR (Wuttke et al., 2019) | eGFRcrea | log ml/min/1.73 m2 | CKDGen | 31152163 | 567,460 | Sex, age, study site, genetic principal components, relatedness and other study-specific features | European |
| Cystatin C–based estimation of GFR (Gorski et al., 2017) | eGFRcys | log ml/min/1.73 m2 | CKDGen | 28452372 | 24,063 | Sex, age, study-specific features such as study site or genetic principal components, and relatedness (if family-based studies) | European |
| Urinary albumin-to-creatinine ratio (Teumer et al., 2019) | UACR | log mg/g | CKDGen | 31511532 | 547,361 | Sex, age, study-specific features such as study site or genetic principal components, and relationship of the individuals (if family-based studies) | European |
| Chronic kidney disease (Wuttke et al., 2019) | CKD | log OR | CKDGen | 31152163 | 480,698 (N case = 41,395, N control = 439,303) | Sex, age, study site, genetic principal components, relatedness and other study-specific features | European |
| Longevity | |||||||
| Parental attained age (Pilling et al., 2017) | — | SD | GWAS of UK Biobank | 29227965 | 389,166 | Offspring age, sex, and genetic principal components 1–5 | European |
| Longevity (age ≥ 90th percentile) (Deelen et al., 2019) | Longevity 90th | log OR | CHARGE | 31413261 | 36,745 (N case = 11,262, N control = 25,483) | Clinical site, known family relationships, and/or the first four principal components (if applicable, and genomic control | European |
Information of outcomes included in the study.
SNP, single nucleotide polymorphism; CARDIoGRAMplusC4D, Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) plus The Coronary Artery Disease (C4D) Genetics consortium; GWAS, genome-wide association study; HERMES, The HEart failure Molecular Epidemiology for Therapeutic Targets; HRC, Haplotype Reference Consortium; MAGIC, Meta-Analyses of Glucose and Insulin-related traits Consortium; DIAMANTE, DIAbetes Meta-ANalysis of Trans-Ethnic association studies; MRC-IEU, Medical Research Council-Integrative Epidemiology Unit; GIANT, Genetic Investigation of ANthropometric Traits; CKDGen, Chronic Kidney Disease Genetics; CHARGE, Cohorts for Health and Aging in genomic Epidemiology; CVD, cardiovascular diseases; CAD, coronary artery disease; MI, myocardial infarction; HF, heart failure; AF, atrial fibrillation; FG, fasting glucose; HbA1c, glycated hemoglobin; T2DM, type 2 diabetes mellitus; SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; eGFRcrea, estimated glomerular filtration rate based on creatinine; eGFRcys, estimated glomerular filtration rate based on cystatin C; UACR, urinary albumin-to-creatinine ratio; CKD, chronic kidney disease.
The authors apologize for these errors and state that this does not change the scientific conclusions of the article in any way. The original article has been updated.
Statements
Publisher’s note
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Supplementary material
The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fgene.2021.699455/full#supplementary-material
Supplementary Figure S1Study design of this Mendelian randomization study of genetically predicted FGF23 and cardiovascular diseases, their risk factors, kidney function and longevity. SNP, single nucleotide polymorphism; LD, linkage disequilibrium; CARDIoGRAMplusC4D, Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) plus The Coronary Artery Disease (C4D) Genetics consortium; GWAS, genome-wide association study; HERMES, The Heart Failure Molecular Epidemiology for Therapeutic Targets; HRC, Haplotype Reference Consortium; MAGIC, Meta-Analyses of Glucose and Insulin-related traits Consortium; DIAMANTE, DIAbetes Meta-ANalysis of Trans-Ethnic association studies; MRC-IEU, Medical Research Council-Integrative Epidemiology Unit; GIANT, Genetic Investigation of ANthropometric Traits; CKDGen, Chronic Kidney Disease Genetics; CHARGE, Cohorts for Health and Aging in genomic Epidemiology; CVD, cardiovascular diseases; CAD, coronary artery disease; MI, myocardial infarction; HF, heart failure; AF, atrial fibrillation; FG, fasting glucose; HbA1c, glycated hemoglobin; T2DM, type 2 diabetes mellitus; SBP, systolic blood pressure; DBP, diastolic blood pressure; BMI, body mass index; eGFRcrea, estimated glomerular filtration rate based on creatinine; eGFRcys, estimated glomerular filtration rate based on cystatin C; UACR, urinary albumin-to-creatinine ratio; CKD, chronic kidney disease.
Supplementary Table S6Participant overlap between the FGF23 genome wide association studies (GWAS) and the outcome GWAS.
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Summary
Keywords
FGF23, cardiovascular disease, cardiovascular risk factor, type 2 diabetes mellitus, longevity, kidney disease, Mendelian randomization
Citation
Liang Y, Luo S, Schooling CM and Au Yeung SL (2021) Corrigendum: Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study. Front. Genet. 12:794246. doi: 10.3389/fgene.2021.794246
Received
13 October 2021
Accepted
20 October 2021
Published
11 November 2021
Volume
12 - 2021
Edited and reviewed by
Hui-Qi Qu, Children’s Hospital of Philadelphia, United States
Updates
Copyright
© 2021 Liang, Luo, Schooling and Au Yeung.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Shiu Lun Au Yeung, ayslryan@hku.hk
This article was submitted to Applied Genetic Epidemiology, a section of the journal Frontiers in Genetics
Disclaimer
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.