Hostname: page-component-cb9f654ff-5kfdg Total loading time: 0 Render date: 2025-08-20T19:30:32.229Z Has data issue: false hasContentIssue false
  • English
  • Français

Bidirectional Mediation of Cognition by DNA Methylation and Lean Body Mass in Chinese Monozygotic Twins

Published online by Cambridge University Press:  14 July 2025

Huihui Li ,
Tong Wang ,
Xiaocao Tian ,
Dongfeng Zhang Open the ORCID record for Dongfeng Zhang [Opens in a new window]  and
Weijing Wang Open the ORCID record for Weijing Wang [Opens in a new window]
Huihui Li
Affiliation:
Department of Epidemiology and Health Statistics, Public Health College, Qingdao University Qingdao, Shandong Province, China
Tong Wang
Affiliation:
Department of Epidemiology and Health Statistics, Public Health College, Qingdao University Qingdao, Shandong Province, China
Xiaocao Tian
Affiliation:
Qingdao Municipal Center for Disease Control and Prevention/Qingdao Institute of Preventive Medicine, Qingdao, Shandong, China
Dongfeng Zhang
Affiliation:
Department of Epidemiology and Health Statistics, Public Health College, Qingdao University Qingdao, Shandong Province, China
Weijing Wang*
Affiliation:
Department of Epidemiology and Health Statistics, Public Health College, Qingdao University Qingdao, Shandong Province, China
*
Corresponding author: Weijing Wang; Email: wangwj793@126.com
Get access

Abstract

This study explores whether DNA methylation (DNAm) mediates the association between lean body mass (LBM) and cognition, as well as whether LBM mediates the association between DNAm and cognition. Based on the data of 59 monozygotic twin pairs, mediation analyses were performed using causal inference test method and mediation analyses. Average causal mediation effect (ACME), average direct effect (ADE), and total effect (TE) were calculated. Among the CpGs associated with LBM, five located within PDGFRB and RP11 genes (ACME: −0.0972−0.0463, |ACME/ADE|: 10.44%−18.30%) negatively mediated the association between LBM and cognition, while one in the PAX2 gene (ACME: 0.3510, |ACME/TE|: 11.84%) positively mediated the association. Besides, the methylation risk score (MRS) of RP11 gene (ACME: −0.0517, |ACME/ADE|: 10.64%) and MRS of all CpGs (ACME: −0.0511, |ACME/ADE|: 10.53%) negatively mediated the association of LBM with cognition. For another, LBM negatively mediated the association between the DNAm level of one CpG within UBXN6 and cognition (ACME: −0.0732, |ACME/TE|: 20.78%), while positively mediated the association between the DNAm level of four CpGs within FOXI2 and cognition (ACME: 0.2812−0.4496, |ACME/TE|: 18.15%−27.29%). It was found the DNAm in PDGFRB, RP11 and PAX2 partially mediates the association between LBM and cognition, and the association between DNAm in UBXN6 and FOXI2 with cognition is also partially mediated by LBM.

Keywords

DNA methylationLean body massCognitionMonozygotic twinsMediation analyses

Information

Type
Article
Information
Twin Research and Human Genetics , First View , pp. 1 - 9
Check for updates
Copyright
© The Author(s), 2025. Published by Cambridge University Press on behalf of International Society for Twin Studies

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Arden, N. K., & Spector, T. D. (1997). Genetic influences on muscle strength, lean body mass, and bone mineral density: A twin study. Journal of Bone and Mineral Research, 12, 2076–2081. https://pubmed.ncbi.nlm.nih.gov/9421240 10.1359/jbmr.1997.12.12.2076CrossRefGoogle ScholarPubMed
Asea, A., Kraeft, S. K., Kurt-Jones, E. A., Stevenson, M. A., Chen, L. B., Finberg, R. W., Koo, G. C., & Calderwood, S. K. (2000). HSP70 stimulates cytokine production through a CD14-dependant pathway, demonstrating its dual role as a chaperone and cytokine. Nature Medicine, 6, 435–442. https://pubmed.ncbi.nlm.nih.gov/10742151 10.1038/74697CrossRefGoogle ScholarPubMed
Booranasuksakul, U., Macdonald, I. A., Stephan, B. C. M., & Siervo, M. (2024). Body Composition, Sarcopenic Obesity, and Cognitive Function in Older Adults: Findings From the National Health and Nutrition Examination Survey (NHANES) 1999–2002 and 2011–2014. Journal of the American Nutrition Association, 43, 539–552. https://doi.org/10.1080/27697061.2024.2333310 CrossRefGoogle ScholarPubMed
Briollais, L., Rustand, D., Allard, C., Wu, Y., Xu, J., Rajan, S. G., Hivert, M.-F., Doyon, M., Bouchard, L., McGowan, P. O., Matthews, S., & Lye, S. (2021). DNA methylation mediates the association between breastfeeding and early-life growth trajectories. Clinical Epigenetics, 13, 231. https://doi.org/10.1186/s13148-021-01209-z CrossRefGoogle ScholarPubMed
Chen, K.-L., Xu, Y., Chu, A.-Q., Ding, D., Liang, X.-N., Nasreddine, Z. S., Dong, Q., Hong, Z., Zhao, Q.-H., & Guo, Q.-H. (2016). Validation of the Chinese version of Montreal Cognitive Assessment Basic for Screening Mild Cognitive Impairment. Journal of the American Geriatrics Society, 64, e285–e290. https://doi.org/10.1111/jgs.14530 CrossRefGoogle ScholarPubMed
Chen, Z. (2016). Progress and prospects of long noncoding RNAs in lipid homeostasis. Molecular Metabolism, 5, 164–170. https://doi.org/10.1016/j.molmet.2015.12.003 CrossRefGoogle ScholarPubMed
Curto, G. G., Gard, C., & Ribes, V. (2015). Structures and properties of PAX linked regulatory networks architecting and pacing the emergence of neuronal diversity. Seminars In Cell & Developmental Biology, 44, 75–86. https://doi.org/10.1016/j.semcdb.2015.09.010 CrossRefGoogle ScholarPubMed
Divoux, A., Karastergiou, K., Xie, H., Guo, W., Perera, R. J., Fried, S. K., & Smith, S. R. (2014). Identification of a novel lncRNA in gluteal adipose tissue and evidence for its positive effect on preadipocyte differentiation. Obesity, 22, 1781–1785. https://doi.org/10.1002/oby.20793 CrossRefGoogle ScholarPubMed
Fan, Y., Sheng, S., Guo, C., Qiao, W., Jin, Y., Tan, L., Gao, Y., Zhang, L., Dong, X., Zhang, J., Li, X., Shen, H., Liao, Y., & Chang, Y. (2022). Forkhead box i2 transcription factor regulates systemic energy metabolism via neuropeptide AgRP. Diabetes, 71, 2106–2122. https://doi.org/10.2337/db22-0002 Google ScholarPubMed
Ferrer, A., Labad, J., Salvat-Pujol, N., Barrachina, M., Costas, J., Urretavizcaya, M., de Arriba-Arnau, A., Crespo, J. M., Soriano-Mas, C., Carracedo, Á., Menchón, J. M., & Soria, V. (2019). BDNF genetic variants and methylation: effects on cognition in major depressive disorder. Translational Psychiatry, 9, 265. https://doi.org/10.1038/s41398-019-0601-8 CrossRefGoogle ScholarPubMed
Forsberg-Nilsson, K., Behar, T. N., Afrakhte, M., Barker, J. L., & McKay, R. D. (1998). Platelet-derived growth factor induces chemotaxis of neuroepithelial stem cells. Journal of Neuroscience Research, 53, 521–530. https://pubmed.ncbi.nlm.nih.gov/9726423 10.1002/(SICI)1097-4547(19980901)53:5<521::AID-JNR2>3.0.CO;2-B3.0.CO;2-B>CrossRefGoogle ScholarPubMed
Ganji, R., Mukkavalli, S., Somanji, F., & Raman, M. (2018). The VCP-UBXN1 complex mediates triage of ubiquitylated cytosolic proteins bound to the BAG6 complex. Molecular and Cellular Biology, 38, e00154–00118. https://doi.org/10.1128/MCB.00154-18 CrossRefGoogle Scholar
Gao, Y., Zhang, Z., Song, J., Gan, T., Lin, Y., Hu, M., & Wu, I. X. (2024). Combined healthy lifestyle behaviours and incident dementia: A systematic review and dose-response meta-analysis of cohort studies. International Journal of Nursing Studies, 156, 104781. https://doi.org/10.1016/j.ijnurstu.2024.104781 CrossRefGoogle ScholarPubMed
Gong, H.-J., Tang, X., Chai, Y.-H., Qiao, Y.-S., Xu, H., Patel, I., Zhang, J.-Y., & Zhou, J.-B. (2023). Predicted lean body mass in relation to cognitive function in the older adults. Frontiers In Endocrinology, 14, 1172233. https://doi.org/10.3389/fendo.2023.1172233 CrossRefGoogle ScholarPubMed
Hao, S.-W., Li, T.-R., Han, C., Han, Y., & Cai, Y.-N. (2023). Associations between levels of peripheral NCAPH2 promoter methylation and different stages of Alzheimer’s disease: A cross-sectional study. Journal of Alzheimer’s Disease, 92, 899–909. https://doi.org/10.3233/JAD-221211 CrossRefGoogle ScholarPubMed
Hartl, F. U. (2017). Protein misfolding diseases. Annual Review of Biochemistry, 86, 21–26. https://doi.org/10.1146/annurev-biochem-061516-044518 CrossRefGoogle ScholarPubMed
Hebestreit, K., Dugas, M., & Klein, H.-U. (2013). Detection of significantly differentially methylated regions in targeted bisulfite sequencing data. Bioinformatics, 29, 1647–1653. https://doi.org/10.1093/bioinformatics/btt263 CrossRefGoogle ScholarPubMed
Hellström, M., Kalén, M., Lindahl, P., Abramsson, A., & Betsholtz, C. (1999). Role of PDGF-B and PDGFR-beta in recruitment of vascular smooth muscle cells and pericytes during embryonic blood vessel formation in the mouse. Development, 126, 3047–3055. https://pubmed.ncbi.nlm.nih.gov/10375497 10.1242/dev.126.14.3047CrossRefGoogle ScholarPubMed
Hu, Y., Peng, W., Ren, R., Wang, Y., & Wang, G. (2022). Sarcopenia and mild cognitive impairment among elderly adults: The first longitudinal evidence from CHARLS. Journal of Cachexia, Sarcopenia and Muscle, 13, 2944–2952. https://doi.org/10.1002/jcsm.13081 CrossRefGoogle ScholarPubMed
Hüls, A., & Czamara, D. (2020). Methodological challenges in constructing DNA methylation risk scores. Epigenetics, 15, 1–11. https://doi.org/10.1080/15592294.2019.1644879 CrossRefGoogle ScholarPubMed
Irwin, M. R., & Vitiello, M. V. (2019). Implications of sleep disturbance and inflammation for Alzheimer’s disease dementia. The Lancet. Neurology, 18, 296–306. https://doi.org/10.1016/S1474-4422(18)30450-2 CrossRefGoogle ScholarPubMed
Jaffe, A. E., & Irizarry, R. A. (2014). Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biology, 15, R31. https://doi.org/10.1186/gb-2014-15-2-r31 CrossRefGoogle ScholarPubMed
Joly-Amado, A., Denis, R. G. P., Castel, J., Lacombe, A., Cansell, C., Rouch, C., Kassis, N., Dairou, J., Cani, P. D., Ventura-Clapier, R., Prola, A., Flamment, M., Foufelle, F., Magnan, C., & Luquet, S. (2012). Hypothalamic AgRP-neurons control peripheral substrate utilization and nutrient partitioning. The EMBO Journal, 31, 4276–4288. https://doi.org/10.1038/emboj.2012.250 CrossRefGoogle ScholarPubMed
Juvinao-Quintero, D. L., Sharp, G. C., Sanderson, E. C. M., Relton, C. L., & Elliott, H. R. (2023). Investigating causality in the association between DNA methylation and type 2 diabetes using bidirectional two-sample Mendelian randomisation. Diabetologia, 66, 1247–1259. https://doi.org/10.1007/s00125-023-05914-7 CrossRefGoogle ScholarPubMed
Kalyani, R. R., Tra, Y., Egan, J. M., Ferrucci, L., & Brancati, F. (2014). Hyperglycemia is associated with relatively lower lean body mass in older adults. The Journal of Nutrition, Health & Aging, 18, 737–743. https://doi.org/10.1007/s12603-014-0445-0 CrossRefGoogle ScholarPubMed
Kanazawa, A., Tsukada, S., Kamiyama, M., Yanagimoto, T., Nakajima, M., & Maeda, S. (2005). Wnt5b partially inhibits canonical Wnt/beta-catenin signaling pathway and promotes adipogenesis in 3T3-L1 preadipocytes. Biochemical and Biophysical Research Communications, 330, 505–510. https://pubmed.ncbi.nlm.nih.gov/15796911 10.1016/j.bbrc.2005.03.007CrossRefGoogle ScholarPubMed
Krueger, F., & Andrews, S. R. (2011). Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics, 27, 1571–1572. https://doi.org/10.1093/bioinformatics/btr167 CrossRefGoogle Scholar
Lee, D. H., Keum, N., Hu, F. B., Orav, E. J., Rimm, E. B., Sun, Q., Willett, W. C., & Giovannucci, E. L. (2017). Development and validation of anthropometric prediction equations for lean body mass, fat mass and percent fat in adults using the National Health and Nutrition Examination Survey (NHANES) 1999–2006. The British Journal of Nutrition, 118, 858–866. https://doi.org/10.1017/S0007114517002665 CrossRefGoogle ScholarPubMed
Lee, D. H., Keum, N., Hu, F. B., Orav, E. J., Rimm, E. B., Willett, W. C., & Giovannucci, E. L. (2018). Predicted lean body mass, fat mass, and all cause and cause specific mortality in men: Prospective US cohort study. BMJ, 362, k2575. https://doi.org/10.1136/bmj.k2575 CrossRefGoogle ScholarPubMed
Lenglez, S., Sablon, A., Fénelon, G., Boland, A., Deleuze, J.-F., Boutoleau-Bretonnière, C., Nicolas, G., & Demoulin, J.-B. (2022). Distinct functional classes of PDGFRB pathogenic variants in primary familial brain calcification. Human Molecular Genetics, 31, 399–409. https://doi.org/10.1093/hmg/ddab258 CrossRefGoogle ScholarPubMed
Levéen, P., Pekny, M., Gebre-Medhin, S., Swolin, B., Larsson, E., & Betsholtz, C. (1994). Mice deficient for PDGF B show renal, cardiovascular, and hematological abnormalities. Genes & Development, 8, 1875–1887. https://pubmed.ncbi.nlm.nih.gov/7958863 10.1101/gad.8.16.1875CrossRefGoogle ScholarPubMed
Li, S., Jiao, H., Yang, J., Li, Y., Zhang, J., Liu, X., & Xue, Y. (2023). Association between lean body mass and hypertension: A cross-sectional study of 50 159 NHANES participants. Journal of Clinical Hypertension, 25, 957–964. https://doi.org/10.1111/jch.14710 CrossRefGoogle Scholar
Li, W., Christiansen, L., Hjelmborg, J., Baumbach, J., & Tan, Q. (2018). On the power of epigenome-wide association studies using a disease-discordant twin design. Bioinformatics, 34, 4073–4078. https://doi.org/10.1093/bioinformatics/bty532 CrossRefGoogle ScholarPubMed
Li, W., Zhang, D., Wang, W., Wu, Y., Mohammadnejad, A., Lund, J., Baumbach, J., Christiansen, L., & Tan, Q. (2019). DNA methylome profiling in identical twin pairs discordant for body mass index. International Journal of Obesity (2005), 43, 2491–2499. https://doi.org/10.1038/s41366-019-0382-4 CrossRefGoogle ScholarPubMed
Liu, F., Morderer, D., Wren, M. C., Vettleson-Trutza, S. A., Wang, Y., Rabichow, B. E., Salemi, M. R., Phinney, B. S., Oskarsson, B., Dickson, D. W., & Rossoll, W. (2022). Proximity proteomics of C9orf72 dipeptide repeat proteins identifies molecular chaperones as modifiers of poly-GA aggregation. Acta Neuropathologica Communications, 10, 22. https://doi.org/10.1186/s40478-022-01322-x CrossRefGoogle ScholarPubMed
Liu, J., Wang, W., Luo, J., Duan, H., Xu, C., Tian, X., Chen, S., Ge, L., & Zhang, D. (2024). Mediation role of DNA methylation in association between handgrip strength and cognitive function in monozygotic twins. Journal of Human Genetics, 69, 357–363. https://doi.org/10.1038/s10038-024-01247-4 CrossRefGoogle ScholarPubMed
Liu, M., Sun, X., Zhu, L., Zhu, M., Deng, K., Nie, X., Mo, H., Du, T., Huang, B., Hu, L., Liang, L., Wang, D., Luo, Y., Yi, J., Zhang, J., Zhong, X., Cao, C., & Chen, H. (2021). Long noncoding RNA RP11-115N4.1 promotes inflammatory responses by interacting with HNRNPH3 and enhancing the transcription of HSP70 in unexplained recurrent spontaneous abortion. Frontiers In Immunology, 12, 717785. https://doi.org/10.3389/fimmu.2021.717785 CrossRefGoogle ScholarPubMed
Loy, C. T., Schofield, P. R., Turner, A. M., & Kwok, J. B. J. (2014). Genetics of dementia. Lancet, 383, 828–840. https://doi.org/10.1016/S0140-6736(13)60630-3 CrossRefGoogle ScholarPubMed
Lv, N., Wang, Y., Liu, Y., Tang, J., Lei, Q., Wang, Y., & Wei, H. (2022). Decreased microglia in pax2 mutant mice leads to impaired learning and memory. ACS Chemical Neuroscience, 13, 2490–2502. https://doi.org/10.1021/acschemneuro.2c00352 CrossRefGoogle ScholarPubMed
Millstein, J., Chen, G. K., & Breton, C. V. (2016). cit: hypothesis testing software for mediation analysis in genomic applications. Bioinformatics, 32, 2364–2365. https://doi.org/10.1093/bioinformatics/btw135 CrossRefGoogle ScholarPubMed
Okekawa, A., Wada, T., Onogi, Y., Takeda, Y., Miyazawa, Y., Sasahara, M., Tsuneki, H., & Sasaoka, T. (2024). Platelet-derived growth factor signaling in pericytes promotes hypothalamic inflammation and obesity. Molecular Medicine, 30, 21. https://doi.org/10.1186/s10020-024-00793-z CrossRefGoogle ScholarPubMed
Onogi, Y., Wada, T., Kamiya, C., Inata, K., Matsuzawa, T., Inaba, Y., Kimura, K., Inoue, H., Yamamoto, S., Ishii, Y., Koya, D., Tsuneki, H., Sasahara, M., & Sasaoka, T. (2017). PDGFRβ regulates adipose tissue expansion and glucose metabolism via vascular remodeling in diet-induced obesity. Diabetes, 66, 1008–1021. https://doi.org/10.2337/db16-0881 CrossRefGoogle ScholarPubMed
Papadopoulos, C., Kirchner, P., Bug, M., Grum, D., Koerver, L., Schulze, N., Poehler, R., Dressler, A., Fengler, S., Arhzaouy, K., Lux, V., Ehrmann, M., Weihl, C. C., & Meyer, H. (2017). VCP/p97 cooperates with YOD1, UBXD1 and PLAA to drive clearance of ruptured lysosomes by autophagy. The EMBO Journal, 36, 135–150. https://doi.org/10.15252/embj.201695148 CrossRefGoogle ScholarPubMed
Pedersen, B. S., Schwartz, D. A., Yang, I. V., & Kechris, K. J. (2012). Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values. Bioinformatics, 28, 2986–2988. https://doi.org/10.1093/bioinformatics/bts545 CrossRefGoogle ScholarPubMed
Rahmani, E., Zaitlen, N., Baran, Y., Eng, C., Hu, D., Galanter, J., Oh, S., Burchard, E. G., Eskin, E., Zou, J., & Halperin, E. (2016). Sparse PCA corrects for cell type heterogeneity in epigenome-wide association studies. Nature Methods, 13, 443–445. https://doi.org/10.1038/nmeth.3809 CrossRefGoogle ScholarPubMed
Root, J., Merino, P., Nuckols, A., Johnson, M., & Kukar, T. (2021). Lysosome dysfunction as a cause of neurodegenerative diseases: Lessons from frontotemporal dementia and amyotrophic lateral sclerosis. Neurobiology of Disease, 154, 105360. https://doi.org/10.1016/j.nbd.2021.105360 CrossRefGoogle ScholarPubMed
Rossanti, R., Morisada, N., Nozu, K., Kamei, K., Horinouchi, T., Yamamura, T., Minamikawa, S., Fujimura, J., Nagano, C., Sakakibara, N., Ninchoji, T., Kaito, H., Ito, S., Tanaka, R., & Iijima, K. (2020). Clinical and genetic variability of PAX2-related disorder in the Japanese population. Journal of Human Genetics, 65, 541–549. https://doi.org/10.1038/s10038-020-0741-y CrossRefGoogle ScholarPubMed
Sassi, C., Guerreiro, R., Gibbs, R., Ding, J., Lupton, M. K., Troakes, C., Al-Sarraj, S., Niblock, M., Gallo, J.-M., Adnan, J., Killick, R., Brown, K. S., Medway, C., Lord, J., Turton, J., Bras, J., Morgan, K., Powell, J. F., Singleton, A., ¼ Hardy, J. (2014). Investigating the role of rare coding variability in Mendelian dementia genes (APP, PSEN1, PSEN2, GRN, MAPT, and PRNP) in late-onset Alzheimer’s disease. Neurobiology of Aging, 35, 2881–2886. https://doi.org/10.1016/j.neurobiolaging.2014.06.002 CrossRefGoogle ScholarPubMed
Semenova, E. I., Vlasov, I. N., Partevian, S. A., Rosinskaya, A. V., Rybolovlev, I. N., Slominsky, P. A., Shadrina, M. I., & Alieva, A. K. (2022). Transcriptome profiling reveals differential expression of circadian behavior genes in peripheral blood of monozygotic twins discordant for Parkinson’s disease. Cells, 11, 2599. https://doi.org/10.3390/cells11162599 CrossRefGoogle ScholarPubMed
Singh-Manoux, A., Dugravot, A., Shipley, M., Brunner, E. J., Elbaz, A., Sabia, S., & Kivimaki, M. (2018). Obesity trajectories and risk of dementia: 28 years of follow-up in the Whitehall II Study. Alzheimer’s & Dementia, 14, 178–186. https://doi.org/10.1016/j.jalz.2017.06.2637 CrossRefGoogle ScholarPubMed
Smits, A., Kato, M., Westermark, B., Nistér, M., Heldin, C. H., & Funa, K. (1991). Neurotrophic activity of platelet-derived growth factor (PDGF): Rat neuronal cells possess functional PDGF beta-type receptors and respond to PDGF. Proceedings of the National Academy of Sciences of the United States of America, 88, 8159–8163. https://pubmed.ncbi.nlm.nih.gov/1654560 10.1073/pnas.88.18.8159CrossRefGoogle ScholarPubMed
Soukkarieh, C., Agius, E., Soula, C., & Cochard, P. (2007). Pax2 regulates neuronal-glial cell fate choice in the embryonic optic nerve. Developmental Biology, 303, 800–813. https://pubmed.ncbi.nlm.nih.gov/17173889 10.1016/j.ydbio.2006.11.016CrossRefGoogle ScholarPubMed
Stingl, K. T., Kullmann, S., Ketterer, C., Heni, M., Häring, H.-U., Fritsche, A., & Preissl, H. (2012). Neuronal correlates of reduced memory performance in overweight subjects. NeuroImage, 60, 362–369. https://doi.org/10.1016/j.neuroimage.2011.12.012 CrossRefGoogle ScholarPubMed
Streit, W. J., Mrak, R. E., & Griffin, W. S. T. (2004). Microglia and neuroinflammation: A pathological perspective. Journal of Neuroinflammation, 1, 14. https://pubmed.ncbi.nlm.nih.gov/15285801 10.1186/1742-2094-1-14CrossRefGoogle ScholarPubMed
Thomas, M. A., & Xue, B. (2018). Mechanisms for AgRP neuron-mediated regulation of appetitive behaviors in rodents. Physiology & Behavior, 190, 34–42. https://doi.org/10.1016/j.physbeh.2017.10.006 CrossRefGoogle ScholarPubMed
Tian, H., Qiao, H., Han, F., Kong, X., Zhu, S., Xing, F., Duan, H., Li, W., Wang, W., Zhang, D., & Wu, Y. (2023). Genome-wide DNA methylation analysis of body composition in Chinese monozygotic twins. European Journal of Clinical Investigation, 53(11), e14055. https://doi.org/10.1111/eci.14055 CrossRefGoogle ScholarPubMed
Trusch, F., Matena, A., Vuk, M., Koerver, L., Knævelsrud, H., Freemont, P. S., Meyer, H., & Bayer, P. (2015). The N-terminal region of the ubiquitin regulatory X (UBX) domain-containing protein 1 (UBXD1) modulates interdomain communication within the valosin-containing protein p97. The Journal of Biological Chemistry, 290, 29414–29427. https://doi.org/10.1074/jbc.M115.680686 CrossRefGoogle ScholarPubMed
Wang, W., Li, W., Jiang, W., Lin, H., Wu, Y., Wen, Y., Xu, C., Tian, X., Li, S., Tan, Q., & Zhang, D. (2021). Genome-wide DNA methylation analysis of cognitive function in middle and old-aged Chinese monozygotic twins. Journal of Psychiatric Research, 136, 571–580. https://doi.org/10.1016/j.jpsychires.2020.10.031 CrossRefGoogle ScholarPubMed
Wang, W., Li, W., Wu, Y., Tian, X., Duan, H., Li, S., Tan, Q., & Zhang, D. (2021). Genome-wide DNA methylation and gene expression analyses in monozygotic twins identify potential biomarkers of depression. Translational Psychiatry, 11, 416. https://doi.org/10.1038/s41398-021-01536-y CrossRefGoogle ScholarPubMed
Wen, Z. L., & Ye, B. (2014). Analyses of mediating effects: The development of methods and models. Advances in Psychological Science, 22, 731–745. https://doi.org/10.3724/SP.J.1042.2014.00731 CrossRefGoogle Scholar
Wijchers, P. J. E. C., Hoekman, M. F. M., Burbach, J. P. H., & Smidt, M. P. (2005). Cloning and analysis of the murine Foxi2 transcription factor. Biochimica et Biophysica Acta, 1731, 133–138. https://pubmed.ncbi.nlm.nih.gov/16289364 10.1016/j.bbaexp.2005.09.003CrossRefGoogle ScholarPubMed
Wolfe, R. R. (2006). The underappreciated role of muscle in health and disease. The American Journal of Clinical Nutrition, 84, 475–482. https://pubmed.ncbi.nlm.nih.gov/16960159 10.1093/ajcn/84.3.475CrossRefGoogle ScholarPubMed
Xu, C., Sun, J., Duan, H., Ji, F., Tian, X., Zhai, Y., Wang, S., Pang, Z., Zhang, D., Zhao, Z., Li, S., Gue, M. M., Hjelmborg, J. V. B., Christensen, K., & Tan, Q. (2015). Gene, environment and cognitive function: a Chinese twin ageing study. Age and Ageing, 44, 452–457. https://doi.org/10.1093/ageing/afv015 CrossRefGoogle ScholarPubMed
Ye, K. X., Sun, L., Wang, L., Khoo, A. L. Y., Lim, K. X., Lu, G., Yu, L., Li, C., Maier, A. B., & Feng, L. (2023). The role of lifestyle factors in cognitive health and dementia in oldest-old: A systematic review. Neuroscience and Biobehavioral Reviews, 152, 105286. https://doi.org/10.1016/j.neubiorev.2023.105286 CrossRefGoogle ScholarPubMed
Zhang, B., Langa, K. M., Weuve, J., D’Souza, J., Szpiro, A., Faul, J., Mendes de Leon, C., Kaufman, J. D., Lisabeth, L., Hirth, R. A., & Adar, S. D. (2023). Hypertension and stroke as mediators of air pollution exposure and incident dementia. JAMA Network Open, 6, e2333470. https://doi.org/10.1001/jamanetworkopen.2023.33470 CrossRefGoogle ScholarPubMed
Zhang, T., Liu, H., Mao, R., Yang, H., Zhang, Y., Zhang, Y., Guo, P., Zhan, D., Xiang, B., & Liu, Y. (2020). The lncRNA RP11-142A22.4 promotes adipogenesis by sponging miR-587 to modulate Wnt5β expression. Cell Death & Disease, 11, 475. https://doi.org/10.1038/s41419-020-2550-9 CrossRefGoogle ScholarPubMed
Zhang, Y., Chen, S.-D., Deng, Y.-T., You, J., He, X.-Y., Wu, X.-R., Wu, B.-S., Yang, L., Zhang, Y.-R., Kuo, K., Feng, J.-F., Cheng, W., Suckling, J., David Smith, A., & Yu, J.-T. (2023). Identifying modifiable factors and their joint effect on dementia risk in the UK Biobank. Nature Human Behaviour, 7, 1185–1195. https://doi.org/10.1038/s41562-023-01585-x CrossRefGoogle ScholarPubMed
Supplementary material: File

Li et al. supplementary material

Li et al. supplementary material
Download Li et al. supplementary material(File)
File 321.5 KB