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Luo J, Wang W, Li J, Duan H, Xu C, Tian X, Zhang D. Epigenome-wide association study identifies DNA methylation loci associated with handgrip strength in Chinese monozygotic twins. Front Cell Dev Biol 2024; 12:1378680. [PMID: 38633108 PMCID: PMC11021642 DOI: 10.3389/fcell.2024.1378680] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Accepted: 03/22/2024] [Indexed: 04/19/2024] Open
Abstract
Background: The decline in muscle strength and function with aging is well recognized, but remains poorly characterized at the molecular level. Here, we report the epigenetic relationship between genome-wide DNA methylation and handgrip strength (HGS) among Chinese monozygotic (MZ) twins. Methods: DNA methylation (DNAm) profiling was conducted in whole blood samples through Reduced Representation Bisulfite Sequencing method. Generalized estimating equation was applied to regress the DNAm of each CpG with HGS. The Genomic Regions Enrichment of Annotations Tool was used to perform enrichment analysis. Differentially methylated regions (DMRs) were detected using comb-p. Causal inference was performed using Inference about Causation through Examination of Familial Confounding method. Finally, we validated candidate CpGs in community residents. Results: We identified 25 CpGs reaching genome-wide significance level. These CpGs located in 9 genes, especially FBLN1, RXRA, and ABHD14B. Many enriched terms highlighted calcium channels, neuromuscular junctions, and skeletal muscle organ development. We identified 21 DMRs of HGS, with several DMRs within FBLN1, SLC30A8, CST3, and SOCS3. Causal inference indicated that the DNAm of 16 top CpGs within FBLN1, RXRA, ABHD14B, MFSD6, and TYW1B might influence HGS, while HGS influenced DNAm at two CpGs within FBLN1 and RXRA. In validation analysis, methylation levels of six CpGs mapped to FLBN1 and one CpG mapped to ABHD14B were negatively associated with HGS weakness in community population. Conclusion: Our study identified multiple DNAm variants potentially related to HGS, especially CpGs within FBLN1 and ABHD14B. These findings provide new clues to the epigenetic modification underlying muscle strength decline.
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Affiliation(s)
- Jia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
| | - Jingxian Li
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong, China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong, China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Xiaocao Tian
- Qingdao Municipal Centre for Disease Control and Prevention, Qingdao, Shandong, China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Qingdao University, Qingdao, Shandong, China
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Tordai DZ, Hajdú N, Rácz R, Istenes I, Békeffy M, Vági OE, Kempler M, Körei AE, Tóbiás B, Illés A, Pikó H, Kósa JP, Árvai K, Papp M, Lakatos PA, Kempler P, Putz Z. Genetic Factors Associated with the Development of Neuropathy in Type 2 Diabetes. Int J Mol Sci 2024; 25:1815. [PMID: 38339094 PMCID: PMC10855482 DOI: 10.3390/ijms25031815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/25/2024] [Accepted: 01/31/2024] [Indexed: 02/12/2024] Open
Abstract
Neuropathy is a serious and frequent complication of type 2 diabetes (T2DM). This study was carried out to search for genetic factors associated with the development of diabetic neuropathy by whole exome sequencing. For this study, 24 patients with long-term type 2 diabetes with neuropathy and 24 without underwent detailed neurological assessment and whole exome sequencing. Cardiovascular autonomic function was evaluated by cardiovascular reflex tests. Heart rate variability was measured by the triangle index. Sensory nerve function was estimated by Neurometer and Medoc devices. Neuropathic symptoms were characterized by the neuropathy total symptom score (NTSS). Whole exome sequencing (WES) was performed on a Thermo Ion GeneStudio S5 system determining the coding sequences of approximately 32,000 genes comprising 50 million base pairs. Variants were detected by Ion Reporter software and annotated using ANNOVAR, integrating database information from dbSNP, ClinVar, gnomAD, and OMIM. Integrative genomics viewer (IGV) was used for visualization of the mapped reads. We have identified genetic variants that were significantly associated with increased (22-49-fold) risk of neuropathy (rs2032930 and rs2032931 of recQ-mediated genome instability protein 2 (RMI2) gene), rs604349 of myosin binding protein H like (MYBPHL) gene and with reduced (0.07-0.08-fold) risk (rs917778 of multivesicular body subunit 12B (MVB12B) and rs2234753 of retinoic acid X receptor alpha (RXRA) genes). The rs2032930 showed a significant correlation with current perception thresholds measured at 5 Hz and 250 Hz for n. medianus (p = 0.042 and p = 0.003, respectively) and at 5 Hz for n. peroneus (p = 0.037), as well as the deep breath test (p = 0.022) and the NTSS (p = 0.023). The rs2032931 was associated with current perception thresholds (p = 0.003 and p = 0.037, respectively), deep breath test (p = 0.022), and NTSS (p = 0.023). The rs604349 correlated with values measured at 2000 (p = 0.049), 250 (p = 0.018), and 5 Hz (p = 0.005) for n. medianus, as well as warm perception threshold measured by Medoc device (p = 0.042). The rs2234753 showed correlations with a current perception threshold measured at 2000 Hz for n. medianus (p = 0.020), deep breath test (p = 0.040), and NTSS (p = 0.003). There was a significant relationship between rs91778 and cold perception threshold (p = 0.013). In our study, genetic variants have been identified that may have an impact on the risk of neuropathy developing in type 2 diabetic patients. These results could open up new opportunities for early preventive measures and might provide targets for new drug developments in the future.
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Affiliation(s)
- Dóra Zsuszanna Tordai
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Noémi Hajdú
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Ramóna Rácz
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Ildikó Istenes
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Magdolna Békeffy
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Orsolya Erzsébet Vági
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Miklós Kempler
- Department of Internal Medicine and Hematology, Semmelweis University, 1085 Budapest, Hungary;
| | - Anna Erzsébet Körei
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Bálint Tóbiás
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
- PentaCore Laboratory, 1134 Budapest, Hungary;
- Vascular Diagnostics Ltd., 1026 Budapest, Hungary
- Eötvös Lóránd Scientific Network ENDOMOLPAT, Semmelweis University, 1085 Budapest, Hungary
| | - Anett Illés
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
- PentaCore Laboratory, 1134 Budapest, Hungary;
- Eötvös Lóránd Scientific Network ENDOMOLPAT, Semmelweis University, 1085 Budapest, Hungary
| | - Henriett Pikó
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
- PentaCore Laboratory, 1134 Budapest, Hungary;
- Eötvös Lóránd Scientific Network ENDOMOLPAT, Semmelweis University, 1085 Budapest, Hungary
| | - János Pál Kósa
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
- PentaCore Laboratory, 1134 Budapest, Hungary;
- Vascular Diagnostics Ltd., 1026 Budapest, Hungary
- Eötvös Lóránd Scientific Network ENDOMOLPAT, Semmelweis University, 1085 Budapest, Hungary
| | - Kristóf Árvai
- PentaCore Laboratory, 1134 Budapest, Hungary;
- Vascular Diagnostics Ltd., 1026 Budapest, Hungary
| | - Márton Papp
- Centre for Bioinformatics, University of Veterinary Medicine, 1078 Budapest, Hungary;
| | - Péter András Lakatos
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
- PentaCore Laboratory, 1134 Budapest, Hungary;
- Vascular Diagnostics Ltd., 1026 Budapest, Hungary
- Eötvös Lóránd Scientific Network ENDOMOLPAT, Semmelweis University, 1085 Budapest, Hungary
| | - Péter Kempler
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
| | - Zsuzsanna Putz
- Department of Internal Medicine and Oncology, Semmelweis University, 1083 Budapest, Hungary; (N.H.); (I.I.); (M.B.); (O.E.V.); or (A.E.K.); (B.T.); (A.I.); (H.P.); (J.P.K.); (P.A.L.); (P.K.); or (Z.P.)
- Eötvös Lóránd Scientific Network ENDOMOLPAT, Semmelweis University, 1085 Budapest, Hungary
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Li R, Zhao M, Miao C, Shi X, Lu J. Identification and validation of key biomarkers associated with macrophages in nonalcoholic fatty liver disease based on hdWGCNA and machine learning. Aging (Albany NY) 2023; 15:15451-15472. [PMID: 38147020 PMCID: PMC10781485 DOI: 10.18632/aging.205374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Accepted: 11/21/2023] [Indexed: 12/27/2023]
Abstract
BACKGROUND NAFLD has attracted increasing attention because of its high prevalence and risk of progression to cirrhosis or even hepatocellular carcinoma. Therefore, research into the root causes and molecular indicators of NAFLD is crucial. METHODS We analyzed scRNA-seq data and RNA-seq data from normal and NAFLD liver samples. We utilized hdWGCNA to find module-related genes associated with the phenotype. Multiple machine learning algorithms were used to validate the model diagnostics and further screen for genes that are characteristic of NAFLD. The NAFLD mouse model was constructed using the MCD diet to validate the diagnostic effect of the genes. RESULTS We identified a specific macrophage population called NASH-macrophages by single-cell sequencing analysis. Cell communication analysis and Pseudo-time trajectory analysis revealed the specific role and temporal distribution of NASH-macrophages in NAFLD. The hdWGCNA screening yielded 30 genes associated with NASH-macrophages, and machine learning algorithms screened and obtained two genes characterizing NAFLD. The immune infiltration indicated that these genes were highly associated with macrophages. Notably, we verified by RT-qPCR, IHC, and WB that MAFB and CX3CR1 are highly expressed in the MCD mouse model and may play important roles. CONCLUSIONS Our study revealed a macrophage population that is closely associated with NAFLD. Using hdWGCNA analysis and multiple machine learning algorithms, we identified two NAFLD signature genes that are highly correlated with macrophages. Our findings may provide potential feature markers and therapeutic targets for NAFLD.
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Affiliation(s)
- Ruowen Li
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Mingjian Zhao
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Chengxu Miao
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Xiaojia Shi
- School of Medicine, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
| | - Jinghui Lu
- Department of General Surgery, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong Province, China
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