A causal relationship between childhood obesity and risk of osteoarthritis: results from a two-sample Mendelian randomization analysis

Cao, Zehong; Wu, Yudi; Li, Qiangxiang; Li, Yajia; Wu, Jianhuang

doi:10.1080/07853890.2022.2085883

Cited by 63 publications

(42 citation statements)

References 39 publications

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“…The random-effects inverse variance weighted (IVW) was used as the main analytical method, while MR Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. Our MR analysis results followed the results of the random-effects IVW (40)(41)(42). The random-effects IVW allowed for each SNP to have different mean effects (43).…”

Section: Discussionmentioning

confidence: 94%

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Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

et al. 2023

Front. Endocrinol.

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ObjectiveThe occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective.MethodsGenome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran’s Q statistic and Rucker’s Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis.ResultsThe random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05).ConclusionOnly AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.

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Section: Discussionmentioning

confidence: 94%

“…R 2 was calculated using the formula: R 2 = 2×MAF×(1-MAF) Beta 2 ( 39 ). Sixth, palindromic SNPs with intermediate allele frequencies were excluded to guarantee that the impact of SNPs on exposures corresponded to the same allele as that providing the effect on outcomes ( 40 ).…”

Section: Methodsmentioning

confidence: 99%

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

et al. 2023

Front. Endocrinol.

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“…F statistics were calculated using the formula F = R 2 (N − K − 1)/K(1 − R 2 ), and R 2 was calculated using the formula R 2 = (2 × EAF × (1 − EAF) × Beta 2 )/[(2 × EAF × (1 − EAF) × Beta 2 ) + (2 × EAF × (1 − EAF) × N × SE 2 )] [ 46 , 47 ]. Sixth, for ensuring the accuracy of the results, palindromic SNPs with intermediary allele frequencies were deleted [ 48 ]. Seventh, in the case that SNPs in GWAS were not obtainable, proxy SNPs were obtained by the LDlink online platform ( ).…”

Section: Methodsmentioning

confidence: 99%

No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study

et al. 2023

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Objective: Ankylosing spondylitis (AS) is associated with a variety of gut microbiotas. We aim to analyze the causal relationship between the two at the genetic level. Methods: Mendelian randomization (MR) is a type of instrumental variables (IVs) analysis; MR follows the Mendelian genetic rule of “parental alleles are randomly assigned to offspring” and takes genetic variation as IVs to infer the causal association between exposure factors and study outcome in observational studies. Genome-wide association study (GWAS) summary data of AS were from the FinnGen consortium, and the gut microbiota (Bacteroides, Streptococcus, Proteobacteria, Lachnospiraceae) were from the MiBioGen consortium. The TwoSampleMR and MRPRESSO packages of the R were used to perform a two-sample MR study. Random-effects inverse variance weighted (IVW) was the main analysis method, and MR Egger, weighted median, simple mode, and weighted mode were used as supplementary methods. We examined heterogeneity and horizontal pleiotropy, and examined whether the analysis results were influenced by a single SNP. We applied radial variants of the IVW and MR-Egger model for the improved visualization of the causal estimate. We further examined the causal relationship between AS and gut microbiota, and the robustness of the analysis results. Finally, we performed maximum likelihood, penalized weighted median, and IVW (fixed effects) to further identify the potential causal association. Results: The random-effects IVW results showed that Bacteroides (p = 0.965, OR 95% confidence interval [CI] = 0.990 [0.621–1.579]), Streptococcus (p = 0.591, OR 95% CI = 1.120 [0.741–1.692]), Proteobacteria (p = 0.522, OR 95% CI = 1.160 [0.737–1.826]), and Lachnospiraceae (p = 0.717, OR 95% CI = 1.073 [0.732–1.574]) have no genetic causal relationship with AS. There was no heterogeneity, horizontal pleiotropy or outliers, and results were normally distributed. The MR analysis results were not driven by a single SNP. Conclusion: This study showed that Bacteroides, Streptococcus, Proteobacteria and Lachnospiraceae, four common gut microbiotas associated with AS, had no causal relationship with AS at the genetic level. This study makes a positive contribution to the genetics of AS, but the insufficient number of gut microbiota included is a limitation.

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“…Because strong linkage disequilibrium (LD) among the selected SNPs may lead to biased results, the clumping process ( r 2 < 0.001, clumping distance = 10,000 kb) was carried out to eliminate the LD between the included IVs ( Chen et al, 2022 ). Furthermore, palindromic SNPs with intermediate allele frequencies were excluded to guarantee that the impact of SNPs on exposure corresponded to the same allele as the effect on outcome ( Cao et al, 2022 ). In addition, we applied the PhenoScanner database ( http://www.phenoscanner.medschl.cam.ac.uk/phenoscanner ) to assess whether the selected SNPs were associated with other traits at the genome-wide significance levels ( Shu et al, 2022 ).…”

Section: Methodsmentioning

confidence: 99%

“…The “TwoSampleMR” package of the R software (version 4.1.2) was used to perform two-sample MR analysis of exposure and outcome. We used a random-effects variance-weighted model (IVW), MR-Egger, weighted median, simple mode, and weighted mode to perform MR analysis ( Cao et al, 2022 ). With random-effects IVW as the main method and weighted median, simple mode, and weighted mode as supplementary methods.…”

Section: Methodsmentioning

confidence: 99%

Type 2 diabetes and glycemic traits are not causal factors of delirium: A two-sample mendelian randomization analysis

Yang²,

Luo³

et al. 2023

Front. Genet.

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This study aims to explore the genetic causal association between type 2 diabetes (T2D) and glycemic traits (fasting glucose [FG], fasting insulin [FI], and glycated hemoglobin [HbA1c]) on delirium using Mendelian randomization (MR). Genome-wide association studies (GWAS) summary data for T2D and glycemic traits were obtained from the IEU OpenGWAS database. GWAS summary data for delirium were obtained from the FinnGen Consortium. All the participants were of European ancestry. In addition, we used T2D, FG, FI, and HbA1c as exposures and delirium as outcomes. A random-effects variance-weighted model (IVW), MR Egger, weighted median, simple mode, and weighted mode were used to perform MR analysis. In addition, MR-IVW and MR-Egger analyses were used to detect heterogeneity in the MR results. Horizontal pleiotropy was detected using MR-Egger regression and MR pleiotropy residual sum and outliers (MR-PRESSO). MR-PRESSO was also used to assess outlier single nucleotide polymorphisms (SNPs). The “leave one out” analysis was used to investigate whether the MR analysis results were influenced by a single SNP and evaluate the robustness of the results. In this study, we conducted a two-sample MR analysis, and there was no evidence of a genetic causal association between T2D and glycemic traits (T2D, FG, FI, and HbA1c) on delirium (all p > 0.05). The MR-IVW and MR-Egger tests showed no heterogeneity in our MR results (all p values >0.05). In addition, The MR-Egger and MR-PRESSO tests showed no horizontal pleiotropy in our MR results (all p > 0.05). The MR-PRESSO results also showed that there were no outliers during the MR analysis. In addition, the “leave one out” test did not find that the SNPs included in the analysis could affect the stability of the MR results. Therefore, our study did not support the causal effects of T2D and glycemic traits (FG, FI, and HbA1c) on delirium risk.

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A causal relationship between childhood obesity and risk of osteoarthritis: results from a two-sample Mendelian randomization analysis

Cited by 63 publications

References 39 publications

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

Genetic causal relationship between age at menarche and benign oesophageal neoplasia identified by a Mendelian randomization study

No Evidence of a Genetic Causal Relationship between Ankylosing Spondylitis and Gut Microbiota: A Two-Sample Mendelian Randomization Study

Type 2 diabetes and glycemic traits are not causal factors of delirium: A two-sample mendelian randomization analysis

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