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Jin S, Choi EJ, Choi YJ, Min WK, Park JY, Yoon SZ. Relationship between Arachidonate 5-Lipoxygenase-Activating Protein Gene and Peripheral Arterial Disease in Elderly Patients Undergoing General Surgery: A Retrospective Observational Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:1027. [PMID: 36673783 PMCID: PMC9858772 DOI: 10.3390/ijerph20021027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 01/01/2023] [Accepted: 01/04/2023] [Indexed: 06/17/2023]
Abstract
Patients with peripheral arterial disease (PAD) are at a higher risk of developing postoperative complications. Arachidonate 5-lipoxygenase-activating protein (ALOX5AP) plays an important role in atherosclerosis pathogenesis. In this study, the relationship between PAD and several single nucleotide polymorphisms (SNPs) of ALOX5AP (rs17216473, rs10507391, rs4769874, rs9551963, rs17222814, and rs7222842) was investigated in elderly patients undergoing general surgery. The medical records of 129 patients aged > 55 years who underwent elective general surgery between May 2018 and August 2019 were retrospectively reviewed. The A/A in rs17216473, A/A in rs10507391, G/G in rs4769874, and A/A in rs9551963 were calculated as 0 points and the rest as 1 point to define the genetic risk score. The prevalence of PAD tended to increase with higher genetic risk scores (patients had less ALOX5AP gene polymorphism of A/A in rs17216473, A/A in rs10507391, G/G in rs4769874, or A/A in rs9551963) (p = 0.005). Multivariate logistic regression analysis revealed that the genetic risk score (p = 0.009) and age (p = 0.007) were positively correlated with the prevalence of PAD. Genetic polymorphisms of ALOX5AP and age were associated with the prevalence of PAD in this study.
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Affiliation(s)
- Sejong Jin
- Department of Neuroscience, Korea University College of Medicine, Seoul 02841, Republic of Korea
| | - Eun-Ji Choi
- Department of Dental Anesthesia and Pain Medicine, School of Dentistry, Pusan National University, Dental Research Institute, Yangsan 50612, Republic of Korea
| | - Yoon Ji Choi
- Department of Anesthesiology and Pain Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Seoul 02841, Republic of Korea
| | - Won Kee Min
- Department of Anesthesiology and Pain Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Seoul 02841, Republic of Korea
| | - Ju Yeon Park
- Department of Anesthesiology and Pain Medicine, Daedong Hospital, Busan 47737, Republic of Korea
| | - Seung Zhoo Yoon
- Department of Anesthesiology and Pain Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul 02841, Republic of Korea
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You C, Wu S, Zheng SC, Zhu T, Jing H, Flagg K, Wang G, Jin L, Wang S, Teschendorff AE. A cell-type deconvolution meta-analysis of whole blood EWAS reveals lineage-specific smoking-associated DNA methylation changes. Nat Commun 2020; 11:4779. [PMID: 32963246 PMCID: PMC7508850 DOI: 10.1038/s41467-020-18618-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 08/31/2020] [Indexed: 02/06/2023] Open
Abstract
Highly reproducible smoking-associated DNA methylation changes in whole blood have been reported by many Epigenome-Wide-Association Studies (EWAS). These epigenetic alterations could have important implications for understanding and predicting the risk of smoking-related diseases. To this end, it is important to establish if these DNA methylation changes happen in all blood cell subtypes or if they are cell-type specific. Here, we apply a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven large EWAS. We find that most of the highly reproducible smoking-associated hypomethylation signatures are more prominent in the myeloid lineage. A meta-analysis further identifies a myeloid-specific smoking-associated hypermethylation signature enriched for DNase Hypersensitive Sites in acute myeloid leukemia. These results may guide the design of future smoking EWAS and have important implications for our understanding of how smoking affects immune-cell subtypes and how this may influence the risk of smoking related diseases. Smoking-associated DNA methylation changes in whole blood have been reported by many EWAS. Here, the authors use a cell-type deconvolution algorithm to identify cell-type specific DNA methylation signals in seven EWAS, identifying lineage-specific smoking-associated DNA methylation changes.
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Affiliation(s)
- Chenglong You
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Sijie Wu
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.,Human Phenome Institute, Fudan University, 825 Zhangheng Road, Shanghai, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Shijie C Zheng
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.,Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Tianyu Zhu
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Han Jing
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China
| | - Ken Flagg
- Guangzhou Regenerative Medicine Guangdong Laboratory, Guangzhou, China
| | - Guangyu Wang
- Department of Computer Science and Technology, Tsinghua University, Beijing, China
| | - Li Jin
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China.,Human Phenome Institute, Fudan University, 825 Zhangheng Road, Shanghai, China.,State Key Laboratory of Genetic Engineering and Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China
| | - Sijia Wang
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650223, China.
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institute for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, 320 Yue Yang Road, Shanghai, 200031, China. .,UCL Cancer Institute, Paul O'Gorman Building, University College London, 72 Huntley Street, London, WC1E 6BT, UK.
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Zheng JH, Ning GL, Xu WH, Wu XC, Ma XC. Lack of association between ALOX5AP genetic polymorphisms and risk of ischemic stroke: evidence from meta-analyses. Neuropsychiatr Dis Treat 2019; 15:357-367. [PMID: 30774347 PMCID: PMC6354695 DOI: 10.2147/ndt.s182674] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND In recent years, there has been substantial research evaluating the relationship between arachidonate 5-lipoxygenase-activating protein (ALOX5AP) polymorphisms and ischemic stroke (IS). The objective of this study was to systematically review and analyze the existing evidence. METHODS A comprehensive search of major electronic databases for studies published between 1990 and 2018 was carried out. Data were synthesized as OR and 95% CI using fixed-effects and random-effects models. RESULTS A total of 30 studies were available for analysis. The aggregate sample size across all studies was 32,782 (16,294 cases and 16,488 controls). We found no association of the ALOX5AP rs10507391 (OR=1.03 for A allele vs T allele; 95% CI: 0.93-1.14; P=0.557), rs4769874 (OR=1.13 for A allele vs G allele; 95% CI: 1.00-1.28; P=0.050), rs9551963 (OR=1.03 for A allele vs C allele; 95% CI: 0.96-1.11; P=0.372), rs17222814 (OR=1.09 for A allele vs G allele; 95% CI: 0.96-1.24; P=0.195), rs17222919 (OR=0.89 for G allele vs T allele; 95% CI: 0.75-1.06; P=0.175), and rs4073259 (OR=1.20 for A allele vs G allele; 95% CI: 1.00-1.45; P=0.056) polymorphisms with IS risk. Haplotype analysis also did not yield significant findings for the HapA (rs17222814G-rs10507391T-rs4769874G-rs9551963A; OR=1.20; 95% CI: 0.91-1.56; P=0.192) and HapB (rs17216473A-rs10507391A-rs9315050A-rs17222842G; OR=1.11; 95% CI: 0.90-1.38; P=0.339) haplotypes. CONCLUSION Current evidence does not support an association of rs10507391, rs4769874, rs9551963, rs17222814, rs17222919, rs4073259, and HapA and HapB with IS risk.
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Affiliation(s)
- Jing-Hui Zheng
- Department of Cardiology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China,
| | - Gui-Lan Ning
- Department of Cardiology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China,
| | - Wen-Hua Xu
- Department of Cardiology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China,
| | - Xin-Cheng Wu
- Department of Cardiology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China,
| | - Xiao-Cong Ma
- Department of Cardiology, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning 530011, China,
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