UNASSIGNED: In this study, we employed a bidirectional Mendelian randomization (MR) analysis to explore the potential causal relationship between obesity and the risk of PAD.
UNASSIGNED: To investigate these causal relationships, we conducted bidirectional MR analysis using publicly available genome-wide association study (GWAS) data. Effect estimates were calculated using the random-effects inverse variance-weighted (IVW) method.
UNASSIGNED: We identified eight independent single nucleotide polymorphisms (SNPs) associated with obesity in 218,735 samples involving 16,380,465 SNPs, all of which met the genome-wide significance threshold (p < 5 × 10-⁸). The IVW analysis indicates a significant positive association between genetic obesity and multiple datasets with PAD as the outcome: Queue-1 (GWAS ID: finn-b-I9_PAD) (OR = 1.138, 95% CI: 1.027-1.261, p = 0.013), Queue-2 (GWAS ID: bbj-a-144) (OR = 1.190, 95% CI: 1.019-1.390, p = 0.028), Queue-3 (GWAS ID: ebi-a-GCST90018670) (OR = 1.174, 95% CI: 1.014-1.360, p = 0.032), and Queue-4 (GWAS ID: ebi-a-GCST90018890) (OR = 1.194, 95% CI: 1.099-1.296, p < 0.001). However, we did not observe a significant genetic-level association between obesity and PAD for Queue-5 (GWAS ID: ukb-d-I9_PAD) (OR = 1.001, 95% CI: 1.000-1.002, p = 0.071). Furthermore, we conducted a reverse causal MR analysis to explore the potential reverse causal relationship between obesity and PAD. This comprehensive analysis did not provide evidence of a reverse causal association between these two factors.
UNASSIGNED: In summary, our study offers genetic evidence suggesting a possible causal link between obesity and PAD. While we did not find evidence supporting the \"obesity paradox\", prudent weight management remains crucial, as lower weight does not necessarily guarantee better outcomes. As with any study, caution is required in interpreting the findings. Further research is essential to assess the clinical relevance of weight in preventing PAD, which could inform the development of more precise intervention strategies.
■在这项研究中,我们采用双向孟德尔随机化(MR)分析,探讨肥胖与PAD风险之间的潜在因果关系.
■为了调查这些因果关系,我们使用公开的全基因组关联研究(GWAS)数据进行了双向MR分析.使用随机效应逆方差加权(IVW)方法计算效应估计值。
■我们在218,735个样本中鉴定出8个与肥胖相关的独立单核苷酸多态性(SNPs),涉及16,380,465个SNPs,所有这些都符合全基因组显著性阈值(p<5×10-bar)。IVW分析表明,遗传性肥胖与以PAD为结果的多个数据集之间存在显着正相关:Queue-1(GWASID:finn-b-I9_PAD)(OR=1.138,95%CI:1.027-1.261,p=0.013),队列2(GWASID:bbj-a-144)(OR=1.190,95%CI:1.019-1.390,p=0.028),Queue-3(GWASID:ebi-a-GCST90018670)(OR=1.174,95%CI:1.014-1.360,p=0.032),和队列-4(GWASID:ebi-a-GCST90018890)(OR=1.194,95%CI:1.099-1.296,p<0.001)。然而,对于Queue-5(GWASID:Ukb-d-I9_PAD),我们没有观察到肥胖与PAD之间的显著遗传水平关联(OR=1.001,95%CI:1.000-1.002,p=0.071).此外,我们进行了反向因果MR分析,以探讨肥胖与PAD之间潜在的反向因果关系.这一综合分析没有提供这两个因素之间反向因果关系的证据。
■总之,我们的研究提供了遗传证据,提示肥胖和PAD之间可能存在因果关系.虽然我们没有找到支持“肥胖悖论”的证据谨慎的体重管理仍然至关重要,因为较低的体重不一定能保证更好的结果。和任何研究一样,在解释调查结果时需要谨慎。进一步的研究对于评估体重在预防PAD中的临床相关性至关重要。这可以为制定更精确的干预策略提供信息。