跳到主要內容

臺灣博碩士論文加值系統

(44.192.94.177) 您好!臺灣時間:2024/07/16 23:59
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:楊承昊
研究生(外文):YANG, CHENG-HAO
論文名稱:骨質疏鬆症之全基因體關聯研究及代謝路徑分析
論文名稱(外文):Genome-wide association study and metabolic pathway analysis of osteoporosis
指導教授:陳光琦陳光琦引用關係
指導教授(外文):CHEN, KUANG-CHI
口試委員:陳紹基陳光琦温淑惠
口試委員(外文):CHEN, SHAW-JICHEN, KUANG-CHIWEN, SHU-HUI
口試日期:2024-02-23
學位類別:碩士
校院名稱:慈濟大學
系所名稱:醫學資訊學系碩士班
學門:醫藥衛生學門
學類:醫學技術及檢驗學類
論文種類:學術論文
論文出版年:2024
畢業學年度:112
語文別:中文
論文頁數:77
中文關鍵詞:全基因體關聯分析臺灣生物資料庫骨質疏鬆症蛋白質交互作用網路代謝路徑
外文關鍵詞:genome-wide association studyTaiwan Biobankosteoporosisprotein-protein interaction networkmetabolic pathway
相關次數:
  • 被引用被引用:0
  • 點閱點閱:1
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0
骨質疏鬆症 (osteoporosis) 是骨骼脆弱而容易折斷的狀況,是全身性骨骼疾病,危險因子包含年紀、性別、遺傳、吸菸、過量飲酒、嚼檳榔、維他命 D 缺乏、雌激素缺乏和運動太少,也可能因為疾病或治療所導致。
本研究使用臺灣生物資料庫 (Taiwan Biobank, TWB) 的生活習慣、環境因子、身體檢查及全基因體資料,在考慮骨質疏鬆症的危險因子,對骨質疏鬆症及全基因體定型資料之單核苷酸多型性 (single nucleotide polymorphism, SNP) 建構多元羅吉斯迴歸,得到統計顯著的 SNPs,然後判斷領導 SNPs 及其所在或鄰近基因。進一步將這些基因對應到蛋白質,搜尋與這些蛋白質交互作用的其他蛋白質,建構蛋白質交互作用 (protein-protein interaction, PPI) 網路,並辨識與 PPI 網路基因富集顯著的代謝路徑。
經由資料篩選及品質控管 TWBv2.0,得到 70,457 人及 453,277 個 SNPs,其中骨質正常者 62,127 人 (女性 43,860 人),骨質疏鬆者 8,330 人 (女性 5,187 人)。透過多元羅吉斯迴歸得到 178 個統計顯著 SNPs,然後應用 LocusZoom 得到 33 個領導 SNPs 及位於或鄰近的 35 個基因,其中最顯著的領導 SNP rs2908007 鄰近基因 WNT16,第二顯著的領導 SNP rs7741021 鄰近基因 RSPO3。進一步搜尋 STRING 資料庫建構 PPI 網路,並應用 Cytoscpae 分析網路。結果顯示基因 CTNNB1 是瓶頸-中心蛋白,參與 Wnt 訊號路徑、肝細胞癌等代謝路徑,其中,腫瘤會產生多種生長因子,如 TGF-β、VEGF、IGF 等,增加破骨細胞調控,進而導致骨質更加流失。
根據 GWAS 得到的顯著 SNPs,進一步得到相對應基因、蛋白質及代謝路徑,有助於瞭解骨質疏鬆症的致病機制,並為進一步研究骨質疏鬆症提供線索。

Osteoporosis is a systemic skeletal disease characterized by fragile bones that easily fractured. Risk factors include age, gender, genetics, smoking, excessive alcohol consumption, betel nut chewing, vitamin D deficiency, estrogen deficiency, lack of exercise, and certain diseases or treatments.
In this study, we analyzed lifestyle habits, environmental factors, physical examinations, and whole genome data from the Taiwan Biobank (TWB). By considering known osteoporosis risk factors, we constructed multiple logistic regression models for osteoporosis and each single nucleotide polymorphism (SNP) from the whole genome genotyping data to identify statistically significant SNPs and determined the lead SNPs and their corresponding genes. We then mapped these genes to proteins, identified other interacting proteins to construct a protein-protein interaction (PPI) network, and pinpointed metabolic pathways significantly enriched in the PPI network.
After data filtering and quality control, 70,457 individuals and 453,277 SNPs were obtained, including 62,127 individuals with normal bone density (43,860 females) and 8,330 individuals with osteoporosis (5,187 females). Using multiple logistic regression for osteoporosis and each SNP, accounting for several risk factors, we identified 178 statistically significant SNPs. LocusZoom was then applied to identify 33 lead SNPs and 35 genes in or near them. The most significant lead SNP, rs2908007, is close to the gene WNT6, and the second most significant lead SNP, rs7741021, is near the gene RSPO3.
Moreover, 35 genes were mapped to proteins and used as the input proteins for the STRING database to construct a PPI network. The PPI network was analyzed using Cytoscape, revealing that the gene CTNNB1 is a bottleneck-central protein, involved in the Wnt signaling pathway, hepatocellular carcinoma and other metabolic pathways. Tumors can produce various growth factors, such as TGF-β, VEGF, and IGF, which enhance osteoclast regulation, leading to bone loss.
Based on the significant SNPs obtained by GWAS, we not only discovered lead SNPs, corresponding genes, bottleneck-central proteins, and metabolic pathways related to osteoporosis, but also provided significant insights into the pathogenic mechanisms of osteoporosis. These findings might make a valuable contribution to the understanding of osteoporosis and provide a promising directions for further research into the disease.

致謝 I
摘要 II
ABSTRACT IV
目錄 VI
表目錄 VII
圖目錄 VIII
第 1 章 緒論 1
1.1 研究背景 1
1.2 研究動機 5
1.3 研究目的 5
第 2 章 文獻回顧 7
2.1 骨質疏鬆症 7
2.2 全基因體關聯研究 9
2.3 骨質疏鬆症之臺灣漢人族群 GWAS 研究 12
2.4 PPI 網路與代謝路徑分析 13
第 3 章 研究資料及方法 22
3.1 研究資料 22
3.2 資料處理 22
3.3 研究方法 23
第 4 章 實驗結果與分析 28
4.1 資料處理結果 28
4.2 TWB 參與者之問卷分析結果 29
4.3 GWAS 分析 32
4.4 PPI 建構和網路分析 38
4.5 代謝路徑與骨幹網路 40
第 5 章 討論與結論 46
5.1 TWB 參與者之問卷 46
5.2 TWB 參與者之全基因體關聯分析 46
5.3 TWB 性別參與者之全基因體關聯分析 48
5.4 PPI 網路、網路分析和代謝路徑分析 48
第 6 章 未來展望 53
參考文獻 54
附錄 63
1.Kanis JA, Melton LJ, 3rd, Christiansen C, Johnston CC, Khaltaev N. The diagnosis of osteoporosis. J Bone Miner Res. Aug 1994;9(8):1137-41. doi:10.1002/jbmr.5650090802
2.Prevention WHOSGot, Management of O. Prevention and management of osteoporosis : report of a WHO scientific group. Geneva: World Health Organization; 2003.
3.Lin YC, Pan WH. Bone mineral density in adults in Taiwan: results of the Nutrition and Health Survey in Taiwan 2005-2008 (NAHSIT 2005-2008). Asia Pac J Clin Nutr. Jun 2011;20(2):283-91.
4.Hwang JS, Chan DC, Chen JF, et al. Clinical practice guidelines for the prevention and treatment of osteoporosis in Taiwan: summary. J Bone Miner Metab. Jan 2014;32(1):10-6. doi:10.1007/s00774-013-0495-0
5.Nitta K, Yajima A, Tsuchiya K. Management of osteoporosis in chronic kidney disease. Intern Med. Dec 15 2017;56(24):3271-3276. doi:10.2169/internalmedicine.8618-16
6.Misra M, Klibanski A. Anorexia nervosa and osteoporosis. Rev Endocr Metab Disord. Jun 2006;7(1-2):91-9. doi:10.1007/s11154-006-9005-1
7.Cheraghi Z, Doosti-Irani A, Almasi-Hashiani A, et al. The effect of alcohol on osteoporosis: A systematic review and meta-analysis. Drug Alcohol Depend. Apr 1 2019;197:197-202. doi:10.1016/j.drugalcdep.2019.01.025
8.Bassett JH, O'Shea PJ, Sriskantharajah S, et al. Thyroid hormone excess rather than thyrotropin deficiency induces osteoporosis in hyperthyroidism. Mol Endocrinol. May 2007;21(5):1095-107. doi:10.1210/me.2007-0033
9.Xu W, Wu W, Yang S, et al. Risk of osteoporosis and fracture after hysterectomies without oophorectomies: a systematic review and pooled analysis. Osteoporos Int. Aug 2022;33(8):1677-1686. doi:10.1007/s00198-022-06383-1
10.Choi HG, Jung YJ, Lee SW. Increased risk of osteoporosis with hysterectomy: A longitudinal follow-up study using a national sample cohort. Am J Obstet Gynecol. Jun 2019;220(6):573 e1-573 e13. doi:10.1016/j.ajog.2019.02.018
11.Meier C, Kraenzlin ME. Antiepileptics and bone health. Ther Adv Musculoskelet Dis. Oct 2011;3(5):235-43. doi:10.1177/1759720X11410769
12.Pirker-Fruhauf UM, Friesenbichler J, Urban EC, Obermayer-Pietsch B, Leithner A. Osteoporosis in children and young adults: a late effect after chemotherapy for bone sarcoma. Clin Orthop Relat Res. Oct 2012;470(10):2874-85. doi:10.1007/s11999-012-2448-7
13.Fournier MR, Targownik LE, Leslie WD. Proton pump inhibitors, osteoporosis, and osteoporosis-related fractures. Maturitas. Sep 20 2009;64(1):9-13. doi:10.1016/j.maturitas.2009.07.006
14.Reid IR. Glucocorticoid osteoporosis--mechanisms and management. Eur J Endocrinol. Sep 1997;137(3):209-17. doi:10.1530/eje.0.1370209
15.Compston J. Glucocorticoid-induced osteoporosis: an update. Endocrine. Jul 2018;61(1):7-16. doi:10.1007/s12020-018-1588-2
16.Khosla S, Riggs BL. Pathophysiology of age-related bone loss and osteoporosis. Endocrinol Metab Clin North Am. Dec 2005;34(4):1015-30, xi. doi:10.1016/j.ecl.2005.07.009
17.Aloia JF, Cohn SH, Vaswani A, Yeh JK, Yuen K, Ellis K. Risk factors for postmenopausal osteoporosis. Am J Med. Jan 1985;78(1):95-100. doi:10.1016/0002-9343(85)90468-1
18.Siris ES, Miller PD, Barrett-Connor E, et al. Identification and fracture outcomes of undiagnosed low bone mineral density in postmenopausal women: results from the National Osteoporosis Risk Assessment. J Am Med Assoc. Dec 12 2001;286(22):2815-22. doi:10.1001/jama.286.22.2815
19.Waugh EJ, Lam MA, Hawker GA, et al. Risk factors for low bone mass in healthy 40-60 year old women: a systematic review of the literature. Osteoporos Int. Jan 2009;20(1):1-21. doi:10.1007/s00198-008-0643-x
20.Sinnesael M, Claessens F, Boonen S, Vanderschueren D. Novel insights in the regulation and mechanism of androgen action on bone. Curr Opin Endocrinol Diabetes Obes. Jun 2013;20(3):240-4. doi:10.1097/MED.0b013e32835f7d04
21.Ralston SH. Osteoporosis as an hereditary disease. Clin Rev Bone Miner Metab. Jun 2010;8(2):68-76. doi:10.1007/s12018-010-9073-3
22.Cheung CL, Xiao SM, Kung AW. Genetic epidemiology of age-related osteoporosis and its clinical applications. Nat Rev Rheumatol. Sep 2010;6(9):507-17. doi:10.1038/nrrheum.2010.106
23.Holbrook TL, Barrett-Connor E. A prospective study of alcohol consumption and bone mineral density. Br Med J. Jun 5 1993;306(6891):1506-9. doi:10.1136/bmj.306.6891.1506
24.Rapuri PB, Gallagher JC, Balhorn KE, Ryschon KL. Alcohol intake and bone metabolism in elderly women. Am J Clin Nutr. Nov 2000;72(5):1206-13. doi:10.1093/ajcn/72.5.1206
25.Poole KE, Compston JE. Osteoporosis and its management. Br Med J. Dec 16 2006;333(7581):1251-6. doi:10.1136/bmj.39050.597350.47
26.Berg KM, Kunins HV, Jackson JL, et al. Association between alcohol consumption and both osteoporotic fracture and bone density. Am J Med. May 2008;121(5):406-18. doi:10.1016/j.amjmed.2007.12.012
27.Hollenbach KA, Barrett-Connor E, Edelstein SL, Holbrook T. Cigarette smoking and bone mineral density in older men and women. Am J Public Health. Sep 1993;83(9):1265-70. doi:10.2105/ajph.83.9.1265
28.Kanis JA, Johnell O, Oden A, et al. Smoking and fracture risk: a meta-analysis. Osteoporos Int. Feb 2005;16(2):155-62. doi:10.1007/s00198-004-1640-3
29.Wong PK, Christie JJ, Wark JD. The effects of smoking on bone health. Clin Sci (Lond). Sep 2007;113(5):233-41. doi:10.1042/CS20060173
30.Yoon V, Maalouf NM, Sakhaee K. The effects of smoking on bone metabolism. Osteoporos Int. Aug 2012;23(8):2081-92. doi:10.1007/s00198-012-1940-y
31.Agoons DD, Agoons BB, Emmanuel KE, Matawalle FA, Cunningham JM. Association between electronic cigarette use and fragility fractures among US adults. Am J Med Open. Jan 2021;1-6:100002. doi:10.1016/j.ajmo.2021.100002
32.Yang CY, Cheng-Yen Lai J, Huang WL, Hsu CL, Chen SJ. Effects of sex, tobacco smoking, and alcohol consumption osteoporosis development: Evidence from Taiwan biobank participants. Tob Induc Dis. 2021;19:52. doi:10.18332/tid/136419
33.Lu YH, Geng JH, Wu DW, Chen SC, Hung CH, Kuo CH. Betel nut chewing decreased calcaneus ultrasound T-score in a large Taiwanese population follow-up study. Nutrients. Oct 19 2021;13(10):3655. doi:10.3390/nu13103655
34.Nieves JW. Osteoporosis: the role of micronutrients. Am J Clin Nutr. May 2005;81(5):1232S-1239S. doi:10.1093/ajcn/81.5.1232
35.Gielen E, Boonen S, Vanderschueren D, et al. Calcium and vitamin D supplementation in men. J Osteoporos. 2011;2011:875249. doi:10.4061/2011/875249
36.Teucher B, Dainty JR, Spinks CA, et al. Sodium and bone health: impact of moderately high and low salt intakes on calcium metabolism in postmenopausal women. J Bone Miner Res. Sep 2008;23(9):1477-85. doi:10.1359/jbmr.080408
37.Howe TE, Shea B, Dawson LJ, et al. Exercise for preventing and treating osteoporosis in postmenopausal women. Cochrane Database Syst Rev. Jul 6 2011;(7):CD000333. doi:10.1002/14651858.CD000333.pub2
38.Chang CF, Lee JI, Huang SP, Geng JH, Chen SC. Regular exercise decreases the risk of osteoporosis in postmenopausal women. Front Public Health. June 2022;10:897363. doi:10.3389/fpubh.2022.897363
39.Bolam KA, van Uffelen JG, Taaffe DR. The effect of physical exercise on bone density in middle-aged and older men: a systematic review. Osteoporos Int. Nov 2013;24(11):2749-62. doi:10.1007/s00198-013-2346-1
40.Lampropoulos CE, Papaioannou I, D'Cruz DP. Osteoporosis--a risk factor for cardiovascular disease? Nat Rev Rheumatol. Oct 2012;8(10):587-98. doi:10.1038/nrrheum.2012.120
41.Richmond J, Aharonoff GB, Zuckerman JD, Koval KJ. Mortality risk after hip fracture. J Orthop Trauma. 2003;17(8):S2-S5.
42.Brookes AJ. The essence of SNPs. Gene. Jul 8 1999;234(2):177-86. doi:10.1016/s0378-1119(99)00219-x
43.Savas S, Tuzmen S, Ozcelik H. Human SNPs resulting in premature stop codons and protein truncation. Hum Genomics. Mar 2006;2(5):274-86. doi:10.1186/1479-7364-2-5-274
44.Uffelmann E, Huang QQ, Munung NS, et al. Genome-wide association studies. Nat Rev Methods Primers. Aug 2021;1(1):59. doi:10.1038/s43586-021-00056-9
45.Hirschhorn JN, Daly MJ. Genome-wide association studies for common diseases and complex traits. Nat Rev Genet. Feb 2005;6(2):95-108. doi:10.1038/nrg1521
46.Tam V, Patel N, Turcotte M, Bosse Y, Pare G, Meyre D. Benefits and limitations of genome-wide association studies. Nat Rev Genet. Aug 2019;20(8):467-484. doi:10.1038/s41576-019-0127-1
47.Visscher PM, Wray NR, Zhang Q, et al. 10 years of GWAS discovery: biology, function, and translation. Am J Hum Genet. Jul 6 2017;101(1):5-22. doi:10.1016/j.ajhg.2017.06.005
48.Visscher PM, Yengo L, Cox NJ, Wray NR. Discovery and implications of polygenicity of common diseases. Science. Sep 24 2021;373(6562):1468-1473. doi:10.1126/science.abi8206
49.Feng YA, Chen CY, Chen TT, et al. Taiwan Biobank: A rich biomedical research database of the Taiwanese population. Cell Genom. Nov 9 2022;2(11):100197. doi:10.1016/j.xgen.2022.100197
50.Taiwan Biobank. https://www.twbiobank.org.tw/
51.Oti M, Snel B, Huynen MA, Brunner HG. Predicting disease genes using protein-protein interactions. J Med Genet. Aug 2006;43(8):691-8. doi:10.1136/jmg.2006.041376
52.Rual JF, Venkatesan K, Hao T, et al. Towards a proteome-scale map of the human protein-protein interaction network. Nature. Oct 20 2005;437(7062):1173-8. doi:10.1038/nature04209
53.Rao VS, Srinivas K, Sujini GN, Kumar GN. Protein-protein interaction detection: methods and analysis. Int J Proteomics. Feb 2014;2014:147648. doi:10.1155/2014/147648
54.Fiehn O. Metabolomics – the link between genotypes and phenotypes. PLANT MOL BIOL. 2002/01/01 2002;48(1/2):155-171. doi:10.1023/a:1013713905833
55.Rajvanshi M, Venkatesh KV. Metabolic pathway analysis. In: Dubitzky W, Wolkenhauer O, Cho K-H, Yokota H, eds. Encyclopedia of Systems Biology. Springer New York; 2013:1267-1271:chap Chapter 1083.
56.Song Z, Yan A, Guo Z, et al. Targeting metabolic pathways: a novel therapeutic direction for type 2 diabetes. Front Cell Infect Microbiol. 2023;13:1218326. doi:10.3389/fcimb.2023.1218326
57.Zhang A, Sun H, Wang P, Han Y, Wang X. Modern analytical techniques in metabolomics analysis. 10.1039/C1AN15605E. Analyst. Jan 21 2012;137(2):293-300. doi:10.1039/c1an15605e
58.Marees AT, de Kluiver H, Stringer S, et al. A tutorial on conducting genome-wide association studies: Quality control and statistical analysis. Int J Methods Psychiatr Res. Jun 2018;27(2):e1608. doi:10.1002/mpr.1608
59.Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. Jan 8 2019;47(D1):D607-D613. doi:10.1093/nar/gky1131
60.Szklarczyk D, Kirsch R, Koutrouli M, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res. Jan 6 2023;51(D1):D638-D646. doi:10.1093/nar/gkac1000
61.Ran J, Li H, Fu J, et al. Construction and analysis of the protein-protein interaction network related to essential hypertension. BMC Syst Biol. Apr 12 2013;7:32. doi:10.1186/1752-0509-7-32
62.Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. Oct 25 2005;102(43):15545-50. doi:10.1073/pnas.0506580102
63.Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. Jan 1 2000;28(1):27-30. doi:10.1093/nar/28.1.27
64.Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res. Jan 4 2017;45(D1):D353-D361. doi:10.1093/nar/gkw1092
65.Ryan DP, Matthews JM. Protein-protein interactions in human disease. Curr Opin Struct Biol. Aug 2005;15(4):441-6. doi:10.1016/j.sbi.2005.06.001
66.Felson DT, Zhang Y, Hannan MT, Kiel DP, Wilson PW, Anderson JJ. The effect of postmenopausal estrogen therapy on bone density in elderly women. N Engl J Med. Oct 14 1993;329(16):1141-6. doi:10.1056/NEJM199310143291601
67.Gensler LS. Glucocorticoids: complications to anticipate and prevent. Neurohospitalist. Apr 2013;3(2):92-7. doi:10.1177/1941874412458678
68.Chen YC, Sosnoski DM, Mastro AM. Breast cancer metastasis to the bone: mechanisms of bone loss. Breast Cancer Res. Dec 2010;12(6):215. doi:10.1186/bcr2781
69.Norton SA. Betel: consumption and consequences. J Am Acad Dermatol. Jan 1998;38(1):81-8. doi:10.1016/s0190-9622(98)70543-2
70.Lin WY, Chiu TY, Lee LT, Lin CC, Huang CY, Huang KC. Betel nut chewing is associated with increased risk of cardiovascular disease and all-cause mortality in Taiwanese men. Am J Clin Nutr. May 2008;87(5):1204-11. doi:10.1093/ajcn/87.5.1204
71.Ozaki K, Ohnishi Y, Iida A, et al. Functional SNPs in the lymphotoxin-alpha gene that are associated with susceptibility to myocardial infarction. Nat Genet. Dec 2002;32(4):650-4. doi:10.1038/ng1047
72.Richards JB, Rivadeneira F, Inouye M, et al. Bone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study. Lancet. May 3 2008;371(9623):1505-12. doi:10.1016/S0140-6736(08)60599-1
73.Zhu X, Bai W, Zheng H. Twelve years of GWAS discoveries for osteoporosis and related traits: advances, challenges and applications. Bone Res. Apr 29 2021;9(1):23. doi:10.1038/s41413-021-00143-3
74.Styrkarsdottir U, Halldorsson BV, Gretarsdottir S, et al. Multiple genetic loci for bone mineral density and fractures. N Engl J Med. May 29 2008;358(22):2355-65. doi:10.1056/NEJMoa0801197
75.Yang TL, Chen XD, Guo Y, et al. Genome-wide copy-number-variation study identified a susceptibility gene, UGT2B17, for osteoporosis. Am J Hum Genet. Dec 2008;83(6):663-74. doi:10.1016/j.ajhg.2008.10.006
76.Guo Y, Tan LJ, Lei SF, et al. Genome-wide association study identifies ALDH7A1 as a novel susceptibility gene for osteoporosis. PLoS Genet. Jan 8 2010;6(1):e1000806. doi:10.1371/journal.pgen.1000806
77.Kung AW, Xiao SM, Cherny S, et al. Association of JAG1 with bone mineral density and osteoporotic fractures: a genome-wide association study and follow-up replication studies. Am J Hum Genet. Feb 12 2010;86(2):229-39. doi:10.1016/j.ajhg.2009.12.014
78.Kou I, Takahashi A, Urano T, et al. Common variants in a novel gene, FONG on chromosome 2q33.1 confer risk of osteoporosis in Japanese. PLoS One. May 6 2011;6(5):e19641. doi:10.1371/journal.pone.0019641
79.Hwang JY, Lee SH, Go MJ, et al. Meta-analysis identifies a MECOM gene as a novel predisposing factor of osteoporotic fracture. J Med Genet. Apr 2013;50(4):212-9. doi:10.1136/jmedgenet-2012-101156
80.Hwang JY, Kim YJ, Choi BY, Kim BJ, Han BG. Meta analysis identifies a novel susceptibility locus associated with heel bone strength in the Korean population. Bone. Mar 2016;84:47-51. doi:10.1016/j.bone.2015.12.005
81.Zhang X, Ehrlich KC, Yu F, et al. Osteoporosis- and obesity-risk interrelationships: an epigenetic analysis of GWAS-derived SNPs at the developmental gene TBX15. Epigenetics. Jun-Jul 2020;15(6-7):728-749. doi:10.1080/15592294.2020.1716491
82.Sollis E, Mosaku A, Abid A, et al. The NHGRI-EBI GWAS Catalog: knowledgebase and deposition resource. Nucleic Acids Res. Jan 6 2023;51(D1):D977-D985. doi:10.1093/nar/gkac1010
83.Feng S, Wang H, Yan Y, Su X, Ao J, Chen W. Regulatory SNP of RREB1 is associated with bone mineral density in Chinese postmenopausal osteoporosis patients. Front Genet. Nov 2021;12:756957. doi:10.3389/fgene.2021.756957
84.Lu HF, Hung KS, Chu HW, et al. Meta-analysis of genome-wide association studies identifies three loci associated with stiffness index of the calcaneus. J Bone Miner Res. Jul 2019;34(7):1275-1283. doi:10.1002/jbmr.3703
85.Hsu TL, Tantoh DM, Chou YH, et al. Association between osteoporosis and menopause in relation to SOX6 rs297325 variant in Taiwanese women. Menopause. Aug 2020;27(8):887-892. doi:10.1097/GME.0000000000001544
86.Tsai DJ, Fang WH, Wu LW, et al. The polymorphism at PLCB4 promoter (rs6086746) changes the binding affinity of RUNX2 and affects osteoporosis susceptibility: an analysis of bioinformatics-based case-control study and functional validation. Front Endocrinol (Lausanne). Nov 2021;12:730686. doi:10.3389/fendo.2021.730686
87.Wu CL, Nfor ON, Tantoh DM, Lu WY, Liaw YP. Associations between body mass index, WNT16 rs2908004 and osteoporosis: findings from Taiwan Biobank. J Multidiscip Healthc. 2022;15:2751-2758. doi:10.2147/JMDH.S391587
88.Wu CL, Nfor ON, Lu WY, Manli Tantoh D, Liaw YP. Relationship between coffee consumption and osteoporosis risk determined by the ESR1 polymorphism rs2982573. J Nutr Health Aging. Jun 2022;26(6):558-563. doi:10.1007/s12603-022-1796-6
89.Su SL, Huang YH, Chen YH, et al. A case-control study coupling with meta-analysis elaborates decisive association between IGF-1 rs35767 and osteoporosis in Asian postmenopausal females. Aging (Albany NY). Jan 3 2023;15(1):134-147. doi:10.18632/aging.204464
90.He H, Cao S, Niu T, et al. Network-based meta-analyses of associations of multiple gene expression profiles with bone mineral density variations in women. PLoS One. 2016;11(1):e0147475. doi:10.1371/journal.pone.0147475
91.Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets--update. Nucleic Acids Res. Jan 2013;41(Database issue):D991-5. doi:10.1093/nar/gks1193
92.Sarkans U, Gostev M, Athar A, et al. The BioStudies database-one stop shop for all data supporting a life sciences study. Nucleic Acids Res. Jan 4 2018;46(D1):D1266-D1270. doi:10.1093/nar/gkx965
93.Lu HF, Wong HS, Chen BK, et al. Integrative genomic analysis for the functional roles of ITPKC in bone mineral density. Biosci Rep. Dec 21 2018;38(6)doi:10.1042/BSR20181481
94.Liu T, Huang J, Xu D, Li Y. Identifying a possible new target for diagnosis and treatment of postmenopausal osteoporosis through bioinformatics and clinical sample analysis. Ann Transl Med. Jul 2021;9(14):1154. doi:10.21037/atm-21-3098
95.Zhu M, Yin P, Hu F, et al. Integrating genome-wide association and transcriptome prediction model identifies novel target genes for osteoporosis. Osteoporos Int. Dec 2021;32(12):2493-2503. doi:10.1007/s00198-021-06024-z
96.Sudlow C, Gallacher J, Allen N, et al. UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age. PLoS Med. Mar 2015;12(3):e1001779. doi:10.1371/journal.pmed.1001779
97.Chen IC, Kuo PH, Yang AC, et al. CUX2, BRAP and ALDH2 are associated with metabolic traits in people with excessive alcohol consumption. Sci Rep. Oct 22 2020;10(1):18118. doi:10.1038/s41598-020-75199-y
98.Whelton PK, Carey RM, Aronow WS, et al. 2017 ACC/AHA/AAPA/ABC/ACPM/AGS/APhA/ASH/ASPC/NMA/PCNA guideline for the prevention, detection, evaluation, and management of high blood pressure in adults: a report of the American college of cardiology/American heart association task force on clinical practice guidelines. Hypertension. Jun 2018;71(6):e13-e115. doi:10.1161/HYP.0000000000000065
99.Peterson RE, Kuchenbaecker K, Walters RK, et al. Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. Cell. Oct 17 2019;179(3):589-603. doi:10.1016/j.cell.2019.08.051
100.Chang CC, Chow CC, Tellier LC, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4(1):7. doi:10.1186/s13742-015-0047-8
101.Manichaikul A, Mychaleckyj JC, Rich SS, Daly K, Sale M, Chen WM. Robust relationship inference in genome-wide association studies. Bioinformatics. Nov 15 2010;26(22):2867-73. doi:10.1093/bioinformatics/btq559
102.Virtanen P, Gommers R, Oliphant TE, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods. Mar 2020;17(3):261-272. doi:10.1038/s41592-019-0686-2
103.Skipper Seabold JP. Statsmodels: econometric and statistical modeling with Python. In: Proceedings of the 9th Python in Science Conference. 2010:92 - 96.
104.Boughton AP, Welch RP, Flickinger M, et al. LocusZoom.js: interactive and embeddable visualization of genetic association study results. Bioinformatics. Sep 29 2021;37(18):3017-3018. doi:10.1093/bioinformatics/btab186
105.Jones S, Thornton JM. Principles of protein-protein interactions. Proc Natl Acad Sci U S A. Jan 9 1996;93(1):13-20. doi:10.1073/pnas.93.1.13
106.Otasek D, Morris JH, Boucas J, Pico AR, Demchak B. Cytoscape Automation: empowering workflow-based network analysis. Genome Biol. Sep 2 2019;20(1):185. doi:10.1186/s13059-019-1758-4
107.Vidal M, Cusick ME, Barabasi AL. Interactome networks and human disease. Cell. Mar 18 2011;144(6):986-98. doi:10.1016/j.cell.2011.02.016
108.Gursoy A, Keskin O, Nussinov R. Topological properties of protein interaction networks from a structural perspective. Biochem Soc Trans. Dec 2008;36(Pt 6):1398-403. doi:10.1042/BST0361398
109.Chen SJ, Cheng JL, Lee SA, Wang TY, Jang JY, Chen KC. Elucidate multidimensionality of type 1 diabetes mellitus heterogeneity by multifaceted information. Sci Rep. Oct 25 2021;11(1):20965. doi:10.1038/s41598-021-00388-2
110.Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc Series B Stat Methodol. 2018;57(1):289-300. doi:10.1111/j.2517-6161.1995.tb02031.x
111.Zhang L, Zheng YL, Wang R, Wang XQ, Zhang H. Exercise for osteoporosis: A literature review of pathology and mechanism. Review. Front Immunol. Sep 2022;13:1005665. doi:10.3389/fimmu.2022.1005665
112.Manolagas SC. Wnt signaling and osteoporosis. Maturitas. Jul 2014;78(3):233-7. doi:10.1016/j.maturitas.2014.04.013
113.Li L, Zhou X, Zhang JT, et al. Exosomal miR-186 derived from BMSCs promote osteogenesis through hippo signaling pathway in postmenopausal osteoporosis. J Orthop Surg Res. Jan 7 2021;16(1):23. doi:10.1186/s13018-020-02160-0
114.Phetfong J, Sanvoranart T, Nartprayut K, et al. Osteoporosis: the current status of mesenchymal stem cell-based therapy. Cell Mol Biol Lett. 2016/08/12 2016;21(1):12. doi:10.1186/s11658-016-0013-1
115.Chen J, Long F. mTOR signaling in skeletal development and disease. Bone Res. Jan 2018;6(1):1. doi:10.1038/s41413-017-0004-5
116.Wu M, Chen G, Li YP. TGF-beta and BMP signaling in osteoblast, skeletal development, and bone formation, homeostasis and disease. Bone Res. Apr 2016;4(1):16009. doi:10.1038/boneres.2016.9
117.Ballhause TM, Jiang S, Baranowsky A, et al. Relevance of Notch signaling for bone metabolism and regeneration. Int J Mol Sci. Jan 29 2021;22(3)doi:10.3390/ijms22031325
118.Manolagas SC. Steroids and osteoporosis: the quest for mechanisms. J Clin Invest. May 2013;123(5):1919-21. doi:10.1172/JCI68062
119.Drake MT. Osteoporosis and cancer. Curr Osteoporos Rep. Sep 2013;11(3):163-70. doi:10.1007/s11914-013-0154-3
120.Trepanowski N, Yim RM, Wetstone R, et al. Vitiligo progression in a patient undergoing romosozumab treatment for osteoporosis. JAAD Case Rep. Dec 2023;42:26-30. doi:10.1016/j.jdcr.2023.09.033
121.Lamoureux F, Baud'huin M, Duplomb L, Heymann D, Redini F. Proteoglycans: key partners in bone cell biology. Bioessays. Aug 2007;29(8):758-71. doi:10.1002/bies.20612
122.Ng PY, Brigitte Patricia Ribet A, Pavlos NJ. Membrane trafficking in osteoclasts and implications for osteoporosis. Biochem Soc Trans. Apr 30 2019;47(2):639-650. doi:10.1042/BST20180445
123.Stevens CM, Bhusal K, Levine SN, Dhawan R, Jain SK. The association of vitamin C and vitamin D status on bone mineral density and VCAM-1 levels in female diabetic subjects: Is combined supplementation with vitamin C and vitamin D potentially more successful in improving bone health than supplementation with vitamin D alone? Hum Nutr Metab. 2023/12/01/ 2023;34:200221. doi:10.1016/j.hnm.2023.200221
124.Zhao Y-X, Song Y-W, Zhang L, et al. Association between bile acid metabolism and bone mineral density in postmenopausal women. Clinics. 2020;75
125.Yee MMF, Chin KY, Ima-Nirwana S, Wong SK. Vitamin A and bone health: a review on current evidence. Molecules. Mar 21 2021;26(6)doi:10.3390/molecules26061757
126.Wang W, Wang Y, Hu J, et al. Untargeted metabolomics reveal the protective effect of bone marrow mesenchymal stem cell transplantation against ovariectomy-induced osteoporosis in mice. Cell Transplant. Jan-Dec 2022;31:9636897221079745. doi:10.1177/09636897221079745
127.Kang YS, Park SY, Yim CH, et al. The CYP3A4*18 genotype in the cytochrome P450 3A4 gene, a rapid metabolizer of sex steroids, is associated with low bone mineral density. Clin Pharmacol Ther. Mar 2009;85(3):312-8. doi:10.1038/clpt.2008.215
128.Chypre M, Madel MB, Chaloin O, Blin-Wakkach C, Morice C, Mueller CG. Porphyrin derivatives inhibit the interaction between receptor activator of NF-κB and its ligand. ChemMedChem. Oct 20 2017;12(20):1697-1702. doi:10.1002/cmdc.201700462
129.Liu ZW, Luo ZH, Meng QQ, Zhong PC, Hu YJ, Shen XL. Network pharmacology-based investigation on the mechanisms of action of Morinda officinalis How. in the treatment of osteoporosis. Comput Biol Med. Dec 2020;127:104074. doi:10.1016/j.compbiomed.2020.104074
130.Fu YH, Liu WJ, Lee CL, Wang JS. Associations of insulin resistance and insulin secretion with bone mineral density and osteoporosis in a general population. Original Research. Front Endocrinol (Lausanne). Sep 2022;13:971960. doi:10.3389/fendo.2022.971960
131.Ramaswamy B, Shapiro CL. Osteopenia and osteoporosis in women with breast cancer. Semin Oncol. Dec 2003;30(6):763-75. doi:10.1053/j.seminoncol.2003.08.028
132.Jeong SM, Shin DW, Lee JE, Jin SM, Kim S. Increased risk of osteoporosis in gastric cancer survivors compared to general population control: a study with representative Korean population. Cancer Res Treat. Apr 2019;51(2):530-537. doi:10.4143/crt.2018.164
133.Wang D, Dang CX, Hao YX, Yu X, Liu PF, Li JS. Relationship between osteoporosis and Cushing syndrome based on bioinformatics. Medicine (Baltimore). Oct 28 2022;101(43):e31283. doi:10.1097/MD.0000000000031283
134.Schlaht KM, Sas DJ, Davis DMR, Hand JL. An investigation of metabolic disturbances, including urinary stone disease, hypothyroidism, and osteoporosis in basal cell nevus syndrome. Pediatr Dermatol. Sep 2022;39(5):713-717. doi:10.1111/pde.15022
135.Ma KS, Chin NC, Tu TY, et al. Human papillomavirus infections and increased risk of incident osteoporosis: a nationwide population-based cohort study. Viruses. Apr 21 2023;15(4):1021. doi:10.3390/v15041021
136.Miyachi Y, Kaido T, Yao S, et al. Bone mineral density as a risk factor for patients undergoing surgery for hepatocellular carcinoma. World J Surg. Mar 2019;43(3):920-928. doi:10.1007/s00268-018-4861-x
137.Chen YH, Lo RY. Alzheimer's disease and osteoporosis. Ci Ji Yi Xue Za Zhi. Jul-Sep 2017;29(3):138-142. doi:10.4103/tcmj.tcmj_54_17
138.Soroko SB, Barrett-Connor E, Edelstein SL, Kritz-Silverstein D. Family history of osteoporosis and bone mineral density at the axial skeleton: the Rancho Bernardo Study. J Bone Miner Res. Jun 1994;9(6):761-9. doi:10.1002/jbmr.5650090602
139.Varenna M, Manara M, Galli L, Binelli L, Zucchi F, Sinigaglia L. The association between osteoporosis and hypertension: the role of a low dairy intake. Calcif Tissue Int. Jul 2013;93(1):86-92. doi:10.1007/s00223-013-9731-9
140.Hofbauer LC, Brueck CC, Singh SK, Dobnig H. Osteoporosis in patients with diabetes mellitus. J Bone Miner Res. Sep 2007;22(9):1317-28. doi:10.1359/jbmr.070510
141.Leidig-Bruckner G, Ziegler R. Diabetes mellitus a risk for osteoporosis? Exp Clin Endocrinol Diabetes. 2001;109 Suppl 2:S493-514. doi:10.1055/s-2001-18605
142.Abdulameer SA, Sulaiman SA, Hassali MA, Subramaniam K, Sahib MN. Osteoporosis and type 2 diabetes mellitus: what do we know, and what we can do? Patient Prefer Adherence. Jun 2012;6(null):435-48. doi:10.2147/PPA.S32745
143.Mullin BH, Zhao JH, Brown SJ, et al. Genome-wide association study meta-analysis for quantitative ultrasound parameters of bone identifies five novel loci for broadband ultrasound attenuation. Hum Mol Genet. Jul 15 2017;26(14):2791-2802. doi:10.1093/hmg/ddx174
144.Morris JA, Kemp JP, Youlten SE, et al. An atlas of genetic influences on osteoporosis in humans and mice. Nat Genet. Feb 2019;51(2):258-266. doi:10.1038/s41588-018-0302-x
145.Hendrickx G, Boudin E, Fijałkowski I, et al. Variation in the Kozak sequence of WNT16 results in an increased translation and is associated with osteoporosis related parameters. Bone. 2014/02/01/ 2014;59:57-65. doi:10.1016/j.bone.2013.10.022
146.Correa-Rodriguez M, Schmidt Rio-Valle J, Rueda-Medina B. The RSPO3 gene as genetic markers for bone mass assessed by quantitative ultrasound in a population of young adults. Ann Hum Genet. May 2018;82(3):143-149. doi:10.1111/ahg.12235
147.Rocha-Braz MG, Ferraz-de-Souza B. Genetics of osteoporosis: searching for candidate genes for bone fragility. Arch Endocrinol Metab. Aug 2016;60(4):391-401. doi:10.1590/2359-3997000000178
148.Martinez-Gil N, Roca-Ayats N, Atalay N, et al. Functional assessment of coding and regulatory variants from the DKK1 locus. JBMR Plus. Dec 2020;4(12):e10423. doi:10.1002/jbm4.10423
149.Liaw YC, Matsuda K, Liaw YP. Identification of an novel genetic variant associated with osteoporosis: insights from the Taiwan Biobank Study. JBMR Plus. May 2024;8(5):ziae028. doi:10.1093/jbmrpl/ziae028
150.Beasley HK, Rodman TA, Collins GV, Hinton A, Jr., Exil V. TMEM135 is a novel regulator of mitochondrial dynamics and physiology with implications for human health conditions. Cells. Jul 11 2021;10(7)doi:10.3390/cells10071750
151.Kim SK. Identification of 613 new loci associated with heel bone mineral density and a polygenic risk score for bone mineral density, osteoporosis and fracture. PLoS One. 2018;13(7):e0200785. doi:10.1371/journal.pone.0200785
152.Kichaev G, Bhatia G, Loh PR, et al. Leveraging polygenic functional enrichment to improve GWAS power. Am J Hum Genet. Jan 3 2019;104(1):65-75. doi:10.1016/j.ajhg.2018.11.008
153.Hu Y, Tan A, Yu L, et al. A phenomics-based approach for the detection and interpretation of shared genetic influences on 29 biochemical indices in southern Chinese men. BMC Genomics. Dec 16 2019;20(1):983. doi:10.1186/s12864-019-6363-0
154.Ettinger B. Prevention of osteoporosis: treatment of estradiol deficiency. Obstet Gynecol. Nov 1988;72(5 Suppl):12S-17S.
155.MacDonald BT, Tamai K, He X. Wnt/beta-catenin signaling: components, mechanisms, and diseases. Dev Cell. Jul 2009;17(1):9-26. doi:10.1016/j.devcel.2009.06.016
156.Zou M, Al-Yahya S, Al-Alwan M, et al. beta-catenin attenuation leads to up-regulation of activating NKG2D ligands and tumor regression in Braf(V600E)-driven thyroid cancer cells. Front Immunol. 2023;14:1171816. doi:10.3389/fimmu.2023.1171816
157.He S, Lu Y, Liu X, et al. Wnt3a: functions and implications in cancer. Chin J Cancer. Sep 14 2015;34(12):554-62. doi:10.1186/s40880-015-0052-4
158.Zhang Y, Wang N, Ma J, Chen XC, Li Z, Zhao W. Expression profile analysis of new candidate genes for the therapy of primary osteoporosis. Eur Rev Med Pharmacol Sci. 2016;20(3):433-40.
159.Wang CG, Hu YH, Su SL, Zhong D. LncRNA DANCR and miR-320a suppressed osteogenic differentiation in osteoporosis by directly inhibiting the Wnt/beta-catenin signaling pathway. Exp Mol Med. Aug 2020;52(8):1310-1325. doi:10.1038/s12276-020-0475-0
160.Vlashi R, Zhang X, Wu M, Chen G. Wnt signaling: Essential roles in osteoblast differentiation, bone metabolism and therapeutic implications for bone and skeletal disorders. Genes Dis. Jul 2023;10(4):1291-1317. doi:10.1016/j.gendis.2022.07.011
161.Varelas X, Miller BW, Sopko R, et al. The Hippo pathway regulates Wnt/beta-catenin signaling. Dev Cell. Apr 20 2010;18(4):579-91. doi:10.1016/j.devcel.2010.03.007
162.Li CT, Liu JX, Yu B, Liu R, Dong C, Li SJ. Notch signaling represses hypoxia-inducible factor-1alpha-induced activation of Wnt/beta-catenin signaling in osteoblasts under cobalt-mimicked hypoxia. Mol Med Rep. Jul 2016;14(1):689-96. doi:10.3892/mmr.2016.5324
163.de Jong DS, Steegenga WT, Hendriks JM, van Zoelen EJ, Olijve W, Dechering KJ. Regulation of Notch signaling genes during BMP2-induced differentiation of osteoblast precursor cells. Biochem Biophys Res Commun. Jul 16 2004;320(1):100-7. doi:10.1016/j.bbrc.2004.05.150
164.Zhou S. TGF-beta regulates beta-catenin signaling and osteoblast differentiation in human mesenchymal stem cells. J Cell Biochem. Jun 2011;112(6):1651-60. doi:10.1002/jcb.23079
165.Lai P, Song Q, Yang C, et al. Loss of Rictor with aging in osteoblasts promotes age-related bone loss. Cell Death Dis. Oct 13 2016;7(10):e2408. doi:10.1038/cddis.2016.249
166.Rahaman SH, Jyotsna VP, Kandasamy D, Shreenivas V, Gupta N, Tandon N. Bone health in patients with cushing's syndrome. Indian J Endocrinol Metab. Nov-Dec 2018;22(6):766-769. doi:10.4103/ijem.IJEM_160_18
167.Ge X, Zhou G. Protective effects of naringin on glucocorticoid-induced osteoporosis through regulating the PI3K/Akt/mTOR signaling pathway. Am J Transl Res. 2021;13(6):6330-6341.
168.Napoli N, Conte C, Pedone C, et al. Effect of insulin resistance on BMD and fracture risk in older adults. J Clin Endocrinol Metab. Aug 1 2019;104(8):3303-3310. doi:10.1210/jc.2018-02539
169.Nguyen TV, Center JR, Eisman JA. Association between breast cancer and bone mineral density: the Dubbo Osteoporosis Epidemiology Study. Maturitas. Jul 31 2000;36(1):27-34. doi:10.1016/s0378-5122(00)00133-x
170.Lipton A, Uzzo R, Amato RJ, et al. The science and practice of bone health in oncology: managing bone loss and metastasis in patients with solid tumors. J Natl Compr Canc Netw. Oct 2009;7 Suppl 7(Suppl 7):S1-29; quiz S30. doi:10.6004/jnccn.2009.0080
171.Jin J, Robinson AV, Hallowell PT, Jasper JJ, Stellato TA, Wilhem SM. Increases in parathyroid hormone (PTH) after gastric bypass surgery appear to be of a secondary nature. Surgery. Dec 2007;142(6):914-20; discussion 914-20. doi:10.1016/j.surg.2007.09.023
172.Recker RR. Calcium absorption and achlorhydria. N Engl J Med. Jul 11 1985;313(2):70-3. doi:10.1056/NEJM198507113130202
173.Ginaldi L, De Martinis M. Osteoimmunology and beyond. Curr Med Chem. 2016;23(33):3754-3774. doi:10.2174/0929867323666160907162546
174.Aditya S, Rattan A. Sclerostin inhibition: a novel target for the treatment of postmenopausal osteoporosis. J Midlife Health. Oct-Dec 2021;12(4):267-275. doi:10.4103/jmh.JMH_106_20
175.Li Y, Li A, Strait K, Zhang H, Nanes MS, Weitzmann MN. Endogenous TNFalpha lowers maximum peak bone mass and inhibits osteoblastic Smad activation through NF-kappaB. J Bone Miner Res. May 2007;22(5):646-55. doi:10.1359/jbmr.070121
176.Singh S, Hoque S, Zekry A, Sowmya A. Radiological diagnosis of chronic liver disease and hepatocellular carcinoma: a review. J Med Syst. Jul 11 2023;47(1):73. doi:10.1007/s10916-023-01968-7
177.Yang YJ, Kim DJ. An overview of the molecular mechanisms contributing to musculoskeletal disorders in chronic liver disease: osteoporosis, sarcopenia, and osteoporotic sarcopenia. Int J Mol Sci. Mar 5 2021;22(5):2604. doi:10.3390/ijms22052604
178.Xiang T, Deng Z, Yang C, et al. Bile acid metabolism regulatory network orchestrates bone homeostasis. Pharmacol Res. Oct 2023;196:106943. doi:10.1016/j.phrs.2023.106943
179.Id Boufker H, Lagneaux L, Fayyad-Kazan H, et al. Role of farnesoid X receptor (FXR) in the process of differentiation of bone marrow stromal cells into osteoblasts. Bone. Dec 2011;49(6):1219-31. doi:10.1016/j.bone.2011.08.013
180.Ahn TK, Kim KT, Joshi HP, et al. Therapeutic potential of tauroursodeoxycholic acid for the treatment of osteoporosis. Int J Mol Sci. Jun 16 2020;21(12):4274. doi:10.3390/ijms21124274
181.Cornelius C, Koverech G, Crupi R, et al. Osteoporosis and Alzheimer pathology: Role of cellular stress response and hormetic redox signaling in aging and bone remodeling. Front Pharmacol. Jun 2014;5:120. doi:10.3389/fphar.2014.00120
182.Li S, Liu B, Zhang L, Rong L. Amyloid beta peptide is elevated in osteoporotic bone tissues and enhances osteoclast function. Bone. Apr 2014;61:164-75. doi:10.1016/j.bone.2014.01.010
183.Friedman SM, Menzies IB, Bukata SV, Mendelson DA, Kates SL. Dementia and hip fractures: development of a pathogenic framework for understanding and studying risk. Geriatr Orthop Surg Rehabil. Nov 2010;1(2):52-62. doi:10.1177/2151458510389463
184.Yang B, Li S, Chen Z, et al. Amyloid beta peptide promotes bone formation by regulating Wnt/beta-catenin signaling and the OPG/RANKL/RANK system. FASEB J. Mar 2020;34(3):3583-3593. doi:10.1096/fj.201901550R
185.Lin E, Kuo PH, Lin WY, Liu YL, Yang AC, Tsai SJ. Prediction of probable major depressive disorder in the Taiwan biobank: an integrated machine learning and genome-wide analysis approach. J Pers Med. Jun 24 2021;11(7):597. doi:10.3390/jpm11070597
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top