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. 2021 Nov 11;12:794246. doi: 10.3389/fgene.2021.794246

Corrigendum: Genetically Predicted Fibroblast Growth Factor 23 and Major Cardiovascular Diseases, Their Risk Factors, Kidney Function, and Longevity: A Two-Sample Mendelian Randomization Study

Ying Liang 1, Shan Luo 1, C Mary Schooling 1,2, Shiu Lun Au Yeung 1,*
PMCID: PMC8632056  PMID: 34858490

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.

Information of outcomes included in the study.

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
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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.

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 S1

Study 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 S6

Participant overlap between the FGF23 genome wide association studies (GWAS) and the outcome GWAS.

Click here for additional data file. (1.2MB, pdf)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Figure S1

Study 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 S6

Participant overlap between the FGF23 genome wide association studies (GWAS) and the outcome GWAS.

Click here for additional data file. (1.2MB, pdf)

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