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Causal Association Between Anemia and Cardiovascular Disease: A 2‐Sample Bidirectional Mendelian Randomization Study
BACKGROUND: Although previous observational studies have shown an association between anemia and cardiovascular disease (CVD), the underlying causal relationship between anemia and CVD remains uncertain. METHODS AND RESULTS: We conducted a 2‐sample bidirectional Mendelian randomization (MR) study to...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10356041/ https://www.ncbi.nlm.nih.gov/pubmed/37301769 http://dx.doi.org/10.1161/JAHA.123.029689 |
Sumario: | BACKGROUND: Although previous observational studies have shown an association between anemia and cardiovascular disease (CVD), the underlying causal relationship between anemia and CVD remains uncertain. METHODS AND RESULTS: We conducted a 2‐sample bidirectional Mendelian randomization (MR) study to assess the causal association between anemia and CVD. We extracted summary statistics data for anemia, heart failure (HF), coronary artery disease (CAD), atrial fibrillation, any stroke, and any ischemic stroke (AIS) from relevant published genome‐wide association studies. After rigorous quality control steps, independent single‐nucleotide polymorphisms for each disease were selected as instrumental variables. Inverse‐variance weighting was used as the primary method to estimate the causal association between anemia and CVD in the 2‐sample MR analysis. Simultaneously, we performed a series of multiple methods analyses (median weighting, maximum likelihood [MR robust adjusted profile score]), sensitivity analyses (Cochran's Q test and MR‐Egger intercept, leave‐one‐out test [MR pleiotropy residual sum and outlier]), instrumental variable strength evaluations (F statistic), and statistic power estimates to verify the robustness and reliability of our results. Furthermore, the associations between anemia and CVD from different studies, including the UK Biobank and FinnGen studies, were combined by meta‐analysis. The MR analysis showed that genetically predicted anemia was significantly associated with HF risk at the Bonferroni‐corrected significance level (odds ratio [OR], 1.11 [95% CI, 1.04–1.18]; P=0.002) and was suggestively associated with CAD risk (OR, 1.11 [95% CI, 1.02–1.22]; P=0.020). However, the associations between anemia and atrial fibrillation, any stroke, or AIS were not statistically significant. In the reverse MR analysis, we found that genetic susceptibility to HF, CAD, and AIS was significantly associated with anemia risk. The ORs of HF, CAD, and AIS were 1.64 (95% CI, 1.39–1.94; P=7.60E‐09), 1.16 (95% CI, 1.08–1.24; P=2.32E‐05), and 1.30 (95% CI, 1.11–1.52; P=0.001), respectively. Genetically predicted atrial fibrillation was suggestively associated with anemia (OR, 1.06 [95% CI, 1.01–1.12]; P=0.015). Sensitivity analyses found weak evidence of horizontal pleiotropy and heterogeneity, which ensured the robustness and reliability of the results. Meta‐analysis also showed the statistically significant association between anemia and HF risk. CONCLUSIONS: Our study supports bidirectional causality between anemia and HF and significant associations between genetic predisposition to CAD and AIS with anemia, which contributes to the clinical management of both diseases. |
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