Background: An increasing body of evidence suggests that serum albumin levels play a role in cardiovascular diseases. However, the specific causal relationship between serum albumin levels and cardiovascular disease remains partially unknown.
Methods: Mendelian randomization (MR) was employed in this study to examine potential causal relationships between instrumental variables and cardiovascular diseases. Specifically, we utilized genetic variants of serum albumin levels within the reference range as our instrumental variables. To acquire data on genetic associations with cardiovascular diseases, we sourced information from renowned genome-wide association studies such as UK BioBank, EMBL-EBI, and FinnGen. Notably, our study leveraged summary statistics from large cohorts that have been previously described.
Results: We explored the association between serum albumin levels and various conditions, including heart failure (HF), venous thromboembolism (VTE), stroke, atrial fibrillation (AF), coronary artery disease (CAD), type 2 diabetes (T2DM), and pulmonary heart disease (PHD). Genetically predicted serum albumin levels were associated with PHD (odds ratio = 0.737, 95% CI = 0.622 - 0.874, P < 0.001), AF (odds ratio = 0.922, 95% CI = 0.870 - 0.977, P = 0.006), VTE (odds ratio = 0.993, 95% CI = 0.991 - 0.995, P < 0.001), and Stroke (odds ratio = 0.997, 95% CI = 0.995 - 0.999, P = 0.002). However, genetically predicted serum albumin level traits were not associated with HF, CAD and T2DM.
Conclusion: Our study demonstrates a significant association between serum albumin levels and cardiovascular disease, underscoring the crucial role of low serum albumin as a predictive factor in patients with cardiovascular disease.
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http://dx.doi.org/10.1186/s12872-024-03873-4 | DOI Listing |
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Coarse-grained molecular dynamics simulation is widely accepted for assessment of a large complex biological system, but it may also lead to a misleading conclusion. The challenge is to simulate protein structural dynamics (such as folding-unfolding behavior) due to the lack of a necessary backbone flexibility. This study developed a standard coarse-grained model directly from the protein atomic structure and amino acid coarse-grained FF (such as MARTINI FF v2.
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Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA; Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH, USA. Electronic address:
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View Article and Find Full Text PDFFood Chem
December 2024
State Key Laboratory of Food Nutrition and Safety, Key Laboratory of Food Quality and Health of Tianjin, College of Food Science and Engineering, Tianjin University of Science and Technology, Tianjin 300457, China.
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