Causal association between body mass index and risk of rheumatoid arthritis: A Mendelian randomization study

Sang Cheol Bae, Young Ho Lee

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Objective: This study aimed to examine whether body mass index (BMI) is causally associated with rheumatoid arthritis (RA). Method: A two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) meta-analyses for BMI in individuals of European descent (n = 322 154; GIANT consortium) as the exposure and a GWAS for noncancer illness code self-reported: RA from the individuals included in the UK Biobank (total n = 337 159; case = 7480, control = 329 679) as the outcome. Results: We selected 68 single nucleotide polymorphisms at genome-wide significance from GWASs on BMI as the instrumental variables. The IVW method showed evidence to support a causal association between BMI and RA (beta = 0.003, SE = 0.001, P = 0.033). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = −3.54E-05; P = 0.736), but it showed no causal association between BMI and RA (beta = 0.004, SE = 0.004, P = 0.302). However, the weighted median approach yielded evidence of a causal association between BMI and RA (beta = 0.006, SE = 0.002, P = 0.004). Cochran's Q test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy. Conclusion: The results of MR analysis support that BMI may be causally associated with an increased risk of RA.

Original languageEnglish
Article numbere13076
JournalEuropean Journal of Clinical Investigation
DOIs
Publication statusPublished - 2019 Jan 1

Fingerprint

Random Allocation
Rheumatoid Arthritis
Body Mass Index
Genes
Mendelian Randomization Analysis
Polymorphism
Genome-Wide Association Study
Nucleotides
Statistics
Single Nucleotide Polymorphism
Meta-Analysis
Genome

Keywords

  • BMI
  • mendelian randomization
  • rheumatoid arthritis

ASJC Scopus subject areas

  • Biochemistry
  • Clinical Biochemistry

Cite this

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title = "Causal association between body mass index and risk of rheumatoid arthritis: A Mendelian randomization study",
abstract = "Objective: This study aimed to examine whether body mass index (BMI) is causally associated with rheumatoid arthritis (RA). Method: A two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) meta-analyses for BMI in individuals of European descent (n = 322 154; GIANT consortium) as the exposure and a GWAS for noncancer illness code self-reported: RA from the individuals included in the UK Biobank (total n = 337 159; case = 7480, control = 329 679) as the outcome. Results: We selected 68 single nucleotide polymorphisms at genome-wide significance from GWASs on BMI as the instrumental variables. The IVW method showed evidence to support a causal association between BMI and RA (beta = 0.003, SE = 0.001, P = 0.033). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = −3.54E-05; P = 0.736), but it showed no causal association between BMI and RA (beta = 0.004, SE = 0.004, P = 0.302). However, the weighted median approach yielded evidence of a causal association between BMI and RA (beta = 0.006, SE = 0.002, P = 0.004). Cochran's Q test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy. Conclusion: The results of MR analysis support that BMI may be causally associated with an increased risk of RA.",
keywords = "BMI, mendelian randomization, rheumatoid arthritis",
author = "Bae, {Sang Cheol} and Lee, {Young Ho}",
year = "2019",
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T1 - Causal association between body mass index and risk of rheumatoid arthritis

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AU - Bae, Sang Cheol

AU - Lee, Young Ho

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N2 - Objective: This study aimed to examine whether body mass index (BMI) is causally associated with rheumatoid arthritis (RA). Method: A two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) meta-analyses for BMI in individuals of European descent (n = 322 154; GIANT consortium) as the exposure and a GWAS for noncancer illness code self-reported: RA from the individuals included in the UK Biobank (total n = 337 159; case = 7480, control = 329 679) as the outcome. Results: We selected 68 single nucleotide polymorphisms at genome-wide significance from GWASs on BMI as the instrumental variables. The IVW method showed evidence to support a causal association between BMI and RA (beta = 0.003, SE = 0.001, P = 0.033). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = −3.54E-05; P = 0.736), but it showed no causal association between BMI and RA (beta = 0.004, SE = 0.004, P = 0.302). However, the weighted median approach yielded evidence of a causal association between BMI and RA (beta = 0.006, SE = 0.002, P = 0.004). Cochran's Q test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy. Conclusion: The results of MR analysis support that BMI may be causally associated with an increased risk of RA.

AB - Objective: This study aimed to examine whether body mass index (BMI) is causally associated with rheumatoid arthritis (RA). Method: A two-sample Mendelian randomization (MR) analysis using the inverse-variance weighted (IVW), weighted median and MR-Egger regression methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) meta-analyses for BMI in individuals of European descent (n = 322 154; GIANT consortium) as the exposure and a GWAS for noncancer illness code self-reported: RA from the individuals included in the UK Biobank (total n = 337 159; case = 7480, control = 329 679) as the outcome. Results: We selected 68 single nucleotide polymorphisms at genome-wide significance from GWASs on BMI as the instrumental variables. The IVW method showed evidence to support a causal association between BMI and RA (beta = 0.003, SE = 0.001, P = 0.033). MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = −3.54E-05; P = 0.736), but it showed no causal association between BMI and RA (beta = 0.004, SE = 0.004, P = 0.302). However, the weighted median approach yielded evidence of a causal association between BMI and RA (beta = 0.006, SE = 0.002, P = 0.004). Cochran's Q test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy. Conclusion: The results of MR analysis support that BMI may be causally associated with an increased risk of RA.

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