ArticleFrontiers in immunology2024
Causal association between circulating inflammatory proteins and peripheral artery disease: a bidirectional two-sample Mendelian randomization study.
Article in Frontiers in immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Genetic Variation in the Chemokine Network and Atherosclerosis Risk.Current atherosclerosis reports · 2026Review
- Genetic Insights into Peripheral Artery Disease: A Narrative Review.Biomedicines · 2025Review
- Investigation of Growth Differentiation Factor 15 as a Prognostic Biomarker for Major Adverse Limb Events in Peripheral Artery Disease.Journal of clinical medicine · 2025Article
- Growth Differentiation Factor 15 Predicts Cardiovascular Events in Peripheral Artery Disease.Biomolecules · 2025Article
- Interferon Gamma and Tumor Necrosis Factor Alpha Are Inflammatory Biomarkers for Major Adverse Cardiovascular Events in Patients with Peripheral Artery Disease.Biomedicines · 2025Article
- Associations Between Gastroenteropancreatic Neuroendocrine Neoplasms and Inflammatory Factors: Insights From a Two-Sample Mendelian Randomization Analysis.Canadian journal of gastroenterology & hepatology · 2025Article
- Strength of Omics in Uncovering Sepsis Mechanisms-A Perspective.Current health sciences journalReview
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Authors and funding
5 authors.
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Abstract
Introduction: A growing body of research has shown a strong connection between circulating inflammatory proteins and Peripheral artery disease (PAD). However, the causal relationship between circulating inflammatory proteins and PAD is still not fully understood. To investigate this association, we conducted a bidirectional Mendelian randomization study. Materials and methods: Our study utilized genetic variation data obtained from genome-wide association studies (GWAS) datasets. Specifically, the GWAS dataset related to PAD (identifier: finn-b-I9_PAD) included 7,098 cases and 206,541 controls. Additionally, we extracted data on 91 inflammatory proteins from another GWAS dataset (identifiers: GCST90274758-GCST90274848), involving 14,824 participants. To assess the causal relationship between circulating inflammatory proteins and PAD development, we employed methodologies such as inverse variance weighting (IVW), MR Egger regression, and the weighted median approach. Furthermore, sensitivity analyses were conducted to ensure the reliability and robustness of our findings. Results: Two inflammatory proteins were found to be significantly associated with PAD risk: Natural killer cell receptor 2B4 levels (OR, 1.219; 95% CI,1.019~1.457; P=0.03), Fractalkine levels (OR, 0.755; 95% CI=0.591~0.965; P=0.025). PAD had statistically significant effects on 12 inflammatory proteins: C-C motif chemokine 19 levels (OR, 0.714; 95% CI, 0.585 to 0.872; P=0.001), T-cell surface glycoprotein CD5 levels (OR, 0.818; 95% CI, 0.713 to 0.938; P=0.004), CUB domain-containing protein 1 levels (OR, 0.889; 95% CI, 0.809 to 0.977; P=0.015), Fibroblast growth factor 23 levels (OR, 1.129; 95% CI, 1.009 to 1.264; P=0.034), Interferon gamma levels (OR, 1.124; 95% CI, (1.011 to 1.250); P=0.031),Interleukin-15 receptor subunit alpha levels (OR, 1.183; 95% CI,(1.005 to 1.392); P=0.044), Interleukin-17C levels (OR,1.186; 95% CI, (1.048 to 1.342); P=0.007), Interleukin-1-alpha levels (OR, 1.349; 95% CI, (1.032 to 1.765); P=0.029), Interleukin-5 levels (OR, 1.119; 95% CI,(1.003 to 1.248); P=0.043), Latency-associated peptide transforming growth factor beta 1 levels (OR,1.123; 95% CI, (1.020 to 1.236); P=0.018), Matrix metalloproteinase-10 levels (OR, 1.119; 95% CI,(1.015 to 1.233); P=0.024), Signaling lymphocytic activation molecule levels (OR, 0.823; 95% CI, (0.693 to 0.978); P=0.027). Conclusion: Our research expands on genetic studies exploring the strong association between circulating inflammatory proteins and PAD. This discovery has the potential to inform and shape future clinical and basic research endeavors in this area.
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