Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans
Abstract
:1. Introduction
2. Results
2.1. Overview of the Analysis Process
2.2. Gene Signature of Sarcopenia Based on the Transcriptomic Differential Analysis in Humans
2.3. Gene Signature of Sarcopenia Based on the WGCNA
2.4. Differential Analysis and WGCNA of Mouse Gene Expression Data
2.5. Transcriptome-Based Drug Repurposing
2.6. Literature and Experimental Validation of Drug-Repurposing Results
3. Discussion
4. Methods
4.1. Data Collection
4.2. Gene Differential Analysis and Co-Expression Analysis
4.3. Drug Repurposing with Differential Analysis
4.4. Drug Repurposing with Gene2drug
4.5. Drug Repurposing with the Pathway Enrichment Analysis
4.6. Rank Aggregation
4.7. Cell Culture and Treatments
4.8. Measurement of Cell Diameter
4.9. Western Blotting (WB)
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Beard, J.R.; Officer, A.M.; Cassels, A.K. The World Report on Ageing and Health. Gerontologist 2016, 56, S163–S166. [Google Scholar] [CrossRef] [PubMed]
- Chen, L.K.; Woo, J.; Assantachai, P.; Auyeung, T.W.; Chou, M.Y.; Iijima, K.; Jang, H.C.; Kang, L.; Kim, M.; Kim, S.; et al. Asian Working Group for Sarcopenia: 2019 Consensus Update on Sarcopenia Diagnosis and Treatment. J. Am. Med. Dir. Assoc. 2020, 21, 300–307.e302. [Google Scholar] [CrossRef] [PubMed]
- Pinedo-Villanueva, R.; Westbury, L.D.; Syddall, H.E.; Sanchez-Santos, M.T.; Dennison, E.M.; Robinson, S.M.; Cooper, C. Health Care Costs Associated With Muscle Weakness: A UK Population-Based Estimate. Calcif. Tissue Int. 2019, 104, 137–144. [Google Scholar] [CrossRef] [PubMed]
- Goates, S.; Du, K.; Arensberg, M.B.; Gaillard, T.; Guralnik, J.; Pereira, S.L. Economic Impact of Hospitalizations in Us Adults with Sarcopenia. J. Frailty Aging 2019, 8, 93–99. [Google Scholar] [CrossRef] [PubMed]
- Lo, J.H.T.; Pong, U.K.; Yiu, T.; Ong, M.T.Y.; Lee, W.Y.W. Sarcopenia: Current treatments and new regenerative therapeutic approaches. J. Orthop. Transl. 2020, 23, 38–52. [Google Scholar] [CrossRef]
- Bunout, D.; Barrera, G.; De La Maza, P.; AvendañO, M.; Gattas, V.; Petermann, M.; Hirsch, S. The Impact of Nutritional Supplementation and Resistance Training on the Health Functioning of Free-Living Chilean Elders: Results of 18 Months of Follow-up. J. Nutr. 2001, 131, 2441S–2446S. [Google Scholar] [CrossRef]
- Liguori, I.; Russo, G.; Aran, L.; Bulli, G.; Curcio, F.; Della-Morte, D.; Gargiulo, G.; Testa, G.; Cacciatore, F.; Bonaduce, D.; et al. Sarcopenia: Assessment of disease burden and strategies to improve outcomes. Clin. Interv. Aging 2018, 13, 913–927. [Google Scholar] [CrossRef]
- Dillon, E.L.; Sheffield-Moore, M.; Paddon-Jones, D.; Gilkison, C.; Sanford, A.P.; Casperson, S.L.; Jiang, J.; Chinkes, D.L.; Urban, R.J. Amino Acid Supplementation Increases Lean Body Mass, Basal Muscle Protein Synthesis, and Insulin-Like Growth Factor-I Expression in Older Women. J. Clin. Endocrinol. Metab. 2009, 94, 1630–1637. [Google Scholar] [CrossRef]
- Ahmed, M.H.; Hassan, A. Dexamethasone for the Treatment of Coronavirus Disease (COVID-19): A Review. SN Compr. Clin. Med. 2020, 2, 2637–2646. [Google Scholar] [CrossRef]
- Pushpakom, S.; Iorio, F.; Eyers, P.A.; Escott, K.J.; Hopper, S.; Wells, A.; Doig, A.; Guilliams, T.; Latimer, J.; McNamee, C.; et al. Drug repurposing: Progress, challenges and recommendations. Nat. Rev. Drug Discov. 2019, 18, 41–58. [Google Scholar] [CrossRef]
- Misselbeck, K.; Parolo, S.; Lorenzini, F.; Savoca, V.; Leonardelli, L.; Bora, P.; Morine, M.J.; Mione, M.C.; Domenici, E.; Priami, C. A network-based approach to identify deregulated pathways and drug effects in metabolic syndrome. Nat. Commun. 2019, 10, 5215. [Google Scholar] [CrossRef] [PubMed]
- Cheng, F.; Lu, W.; Liu, C.; Fang, J.; Hou, Y.; Handy, D.E.; Wang, R.; Zhao, Y.; Yang, Y.; Huang, J.; et al. A genome-wide positioning systems network algorithm for in silico drug repurposing. Nat. Commun. 2019, 10, 3476. [Google Scholar] [CrossRef] [PubMed]
- Morselli Gysi, D.; do Valle, I.; Zitnik, M.; Ameli, A.; Gan, X.; Varol, O.; Ghiassian, S.D.; Patten, J.J.; Davey, R.A.; Loscalzo, J.; et al. Network medicine framework for identifying drug-repurposing opportunities for COVID-19. Proc. Natl. Acad. Sci. USA 2021, 118, e2025581118. [Google Scholar] [CrossRef]
- Zitnik, M.; Sosič, R.; Leskovec, J. Prioritizing network communities. Nat. Commun. 2018, 9, 2544. [Google Scholar] [CrossRef]
- Migliavacca, E.; Tay, S.K.H.; Patel, H.P.; Sonntag, T.; Civiletto, G.; McFarlane, C.; Forrester, T.; Barton, S.J.; Leow, M.K.; Antoun, E.; et al. Mitochondrial oxidative capacity and NAD(+) biosynthesis are reduced in human sarcopenia across ethnicities. Nat. Commun. 2019, 10, 5808. [Google Scholar] [CrossRef] [PubMed]
- Zhou, Y.; Zhou, B.; Pache, L.; Chang, M.; Khodabakhshi, A.H.; Tanaseichuk, O.; Benner, C.; Chanda, S.K. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat. Commun. 2019, 10, 1523. [Google Scholar] [CrossRef]
- Bader, G.D.; Hogue, C.W. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform. 2003, 4, 2. [Google Scholar] [CrossRef]
- Larsson, L.; Degens, H.; Li, M.; Salviati, L.; Lee, Y.I.; Thompson, W.; Kirkland, J.L.; Sandri, M. Sarcopenia: Aging-Related Loss of Muscle Mass and Function. Physiol. Rev. 2019, 99, 427–511. [Google Scholar] [CrossRef]
- Gan, Z.; Fu, T.; Kelly, D.P.; Vega, R.B. Skeletal muscle mitochondrial remodeling in exercise and diseases. Cell Res. 2018, 28, 969–980. [Google Scholar] [CrossRef]
- Korotkevich, G.; Sukhov, V.; Budin, N.; Shpak, B.; Artyomov, M.N.; Sergushichev, A. Fast Gene Set Enrichment Analysis; Cold Spring Harbor Laboratory: New York, NY, USA, 2016. [Google Scholar]
- Van Dijk, M.; Nagel, J.; Dijk, F.J.; Salles, J.; Verlaan, S.; Walrand, S.; van Norren, K.; Luiking, Y. Sarcopenia in older mice is characterized by a decreased anabolic response to a protein meal. Arch. Gerontol. Geriat. 2017, 69, 134–143. [Google Scholar] [CrossRef]
- Börsch, A.; Ham, D.J.; Mittal, N.; Tintignac, L.A.; Migliavacca, E.; Feige, J.N.; Rüegg, M.A.; Zavolan, M. Molecular and phenotypic analysis of rodent models reveals conserved and species-specific modulators of human sarcopenia. Commun. Biol. 2021, 4, 194. [Google Scholar] [CrossRef] [PubMed]
- Dudley, J.T.; Sirota, M.; Shenoy, M.; Pai, R.K.; Roedder, S.; Chiang, A.P.; Morgan, A.A.; Sarwal, M.M.; Pasricha, P.J.; Butte, A.J. Computational repositioning of the anticonvulsant topiramate for inflammatory bowel disease. Sci. Transl. Med. 2011, 3, 96ra76. [Google Scholar] [CrossRef] [PubMed]
- Jahchan, N.S.; Dudley, J.T.; Mazur, P.K.; Flores, N.; Yang, D.; Palmerton, A.; Zmoos, A.F.; Vaka, D.; Tran, K.Q.T.; Zhou, M.; et al. A Drug Repositioning Approach Identifies Tricyclic Antidepressants as Inhibitors of Small Cell Lung Cancer and Other Neuroendocrine Tumors. Cancer Discov. 2013, 3, 1364–1377. [Google Scholar] [CrossRef] [PubMed]
- Duan, Y.; Evans, D.S.; Miller, R.A.; Schork, N.J.; Cummings, S.R.; Girke, T. SignatureSearch: Environment for gene expression signature searching and functional interpretation. Nucleic Acids Res. 2020, 48, e124. [Google Scholar] [CrossRef]
- Carvalho-Silva, D.; Pierleoni, A.; Pignatelli, M.; Ong, C.; Fumis, L.; Karamanis, N.; Carmona, M.; Faulconbridge, A.; Hercules, A.; McAuley, E.; et al. Open Targets Platform: New developments and updates two years on. Nucleic Acids Res. 2019, 47, D1056–D1065. [Google Scholar] [CrossRef]
- Piñero, J.; Ramírez-Anguita, J.M.; Saüch-Pitarch, J.; Ronzano, F.; Centeno, E.; Sanz, F.; Furlong, L.I. The DisGeNET knowledge platform for disease genomics: 2019 update. Nucleic Acids Res. 2020, 48, D845–D855. [Google Scholar] [CrossRef]
- Szklarczyk, D.; Santos, A.; von Mering, C.; Jensen, L.J.; Bork, P.; Kuhn, M. STITCH 5: Augmenting protein-chemical interaction networks with tissue and affinity data. Nucleic Acids Res. 2016, 44, D380–D384. [Google Scholar] [CrossRef]
- Napolitano, F.; Carrella, D.; Mandriani, B.; Pisonero-Vaquero, S.; Sirci, F.; Medina, D.L.; Brunetti-Pierri, N.; di Bernardo, D. gene2drug: A computational tool for pathway-based rational drug repositioning. Bioinformatics 2017, 34, 1498–1505. [Google Scholar] [CrossRef]
- Szklarczyk, D.; Gable, A.L.; Nastou, K.C.; Lyon, D.; Kirsch, R.; Pyysalo, S.; Doncheva, N.T.; Legeay, M.; Fang, T.; Bork, P.; et al. The STRING database in 2021: Customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021, 49, D605–D612. [Google Scholar] [CrossRef]
- McIntyre, R.L.; Daniels, E.G.; Molenaars, M.; Houtkooper, R.H.; Janssens, G.E. From molecular promise to preclinical results: HDAC inhibitors in the race for healthy aging drugs. EMBO Mol. Med. 2019, 11, e9854. [Google Scholar] [CrossRef]
- Mehta-Shah, N.; Horwitz, S.M.; Ansell, S.; Ai, W.Z.; Barnes, J.; Barta, S.K.; Clemens, M.W.; Dogan, A.; Fisher, K.; Goodman, A.M.; et al. NCCN Guidelines Insights: Primary Cutaneous Lymphomas, Version 2.2020. J. Natl. Compr. Cancer Netw. 2020, 18, 522–536. [Google Scholar] [CrossRef] [PubMed]
- Bruce, R.; Lees, B.; Whitcroft, S.I.J.; McSweeney, G.; Shaw, R.W.; Stevenson, J.C. Changes in body composition with danazol therapy**Supported in part by Sterling Winthrop Laboratories, Guildford, United Kingdom, and by the Heart Disease and Diabetes Research Trust, London, United Kingdom. Fertil. Steril. 1991, 56, 574–576. [Google Scholar] [CrossRef] [PubMed]
- Nagai, S.; Ikeda, K.; Horie-Inoue, K.; Shiba, S.; Nagasawa, S.; Takeda, S.; Inoue, S. Estrogen modulates exercise endurance along with mitochondrial uncoupling protein 3 downregulation in skeletal muscle of female mice. Biochem. Biophys. Res. Commun. 2016, 480, 758–764. [Google Scholar] [CrossRef] [PubMed]
- Hicks, M.R.; Hiserodt, J.; Paras, K.; Fujiwara, W.; Eskin, A.; Jan, M.; Xi, H.; Young, C.S.; Evseenko, D.; Nelson, S.F.; et al. ERBB3 and NGFR mark a distinct skeletal muscle progenitor cell in human development and hPSCs. Nat. Cell Biol. 2018, 20, 46–57. [Google Scholar] [CrossRef] [PubMed]
- Landi, F.; Marzetti, E.; Liperoti, R.; Pahor, M.; Russo, A.; Martone, A.M.; Colloca, G.; Capoluongo, E.; Bernabei, R. Nonsteroidal anti-inflammatory drug (NSAID) use and sarcopenia in older people: Results from the ilSIRENTE study. J. Am. Med. Dir. Assoc. 2013, 14, e613–e629. [Google Scholar] [CrossRef]
- Cerquone Perpetuini, A.; Giuliani, G.; Reggio, A.; Cerretani, M.; Santoriello, M.; Stefanelli, R.; Palma, A.; Vumbaca, S.; Harper, S.; Castagnoli, L.; et al. Janus effect of glucocorticoids on differentiation of muscle fibro/adipogenic progenitors. Sci. Rep. 2020, 10, 5363. [Google Scholar] [CrossRef]
- Marzetti, E.; Leeuwenburgh, C. Skeletal muscle apoptosis, sarcopenia and frailty at old age. Exp. Gerontol. 2006, 41, 1234–1238. [Google Scholar] [CrossRef]
- García-Prat, L.; Sousa-Victor, P.; Muñoz-Cánoves, P. Functional dysregulation of stem cells during aging: A focus on skeletal muscle stem cells. FEBS J. 2013, 280, 4051–4062. [Google Scholar] [CrossRef]
- Li, C.W.; Yu, K.; Shyh-Chang, N.; Li, G.X.; Jiang, L.J.; Yu, S.L.; Xu, L.Y.; Liu, R.J.; Guo, Z.J.; Xie, H.Y.; et al. Circulating factors associated with sarcopenia during ageing and after intensive lifestyle intervention. J. Cachexia Sarcopenia Muscle 2019, 10, 586–600. [Google Scholar] [CrossRef]
- Mittal, K.R.; Logmani, F.H. Age-related reduction in 8th cervical ventral nerve root myelinated fiber diameters and numbers in man. J. Gerontol. 1987, 42, 8–10. [Google Scholar] [CrossRef]
- Pannérec, A.; Springer, M.; Migliavacca, E.; Ireland, A.; Piasecki, M.; Karaz, S.; Jacot, G.; Métairon, S.; Danenberg, E.; Raymond, F.; et al. A robust neuromuscular system protects rat and human skeletal muscle from sarcopenia. Aging 2016, 8, 712–729. [Google Scholar] [CrossRef] [PubMed]
- Kimoloi, S.; Sen, A.; Guenther, S.; Braun, T.; Brügmann, T.; Sasse, P.; Wiesner, R.J.; Pla-Martín, D.; Baris, O.R. Combined fibre atrophy and decreased muscle regeneration capacity driven by mitochondrial DNA alterations underlie the development of sarcopenia. J. Cachexia Sarcopenia Muscle 2022, 13, 2132–2145. [Google Scholar] [CrossRef]
- Chen, J.C.; Goldhamer, D.J. Skeletal muscle stem cells. Reprod. Biol. Endocrinol. 2003, 1, 101. [Google Scholar] [CrossRef] [PubMed]
- Sen, P.; Shah, P.P.; Nativio, R.; Berger, S.L. Epigenetic Mechanisms of Longevity and Aging. Cell 2016, 166, 822–839. [Google Scholar] [CrossRef] [PubMed]
- Cole, J.J.; Robertson, N.A.; Rather, M.I.; Thomson, J.P.; McBryan, T.; Sproul, D.; Wang, T.; Brock, C.; Clark, W.; Ideker, T.; et al. Diverse interventions that extend mouse lifespan suppress shared age-associated epigenetic changes at critical gene regulatory regions. Genome Biol. 2017, 18, 58. [Google Scholar] [CrossRef] [PubMed]
- Walsh, M.E.; Van Remmen, H. Emerging roles for histone deacetylases in age-related muscle atrophy. Nutr. Healthy Aging 2016, 4, 17–30. [Google Scholar] [CrossRef] [PubMed]
- Galmozzi, A.; Mitro, N.; Ferrari, A.; Gers, E.; Gilardi, F.; Godio, C.; Cermenati, G.; Gualerzi, A.; Donetti, E.; Rotili, D.; et al. Inhibition of class I histone deacetylases unveils a mitochondrial signature and enhances oxidative metabolism in skeletal muscle and adipose tissue. Diabetes 2013, 62, 732–742. [Google Scholar] [CrossRef]
- Iezzi, S.; Cossu, G.; Nervi, C.; Sartorelli, V.; Puri, P.L. Stage-specific modulation of skeletal myogenesis by inhibitors of nuclear deacetylases. Proc. Natl. Acad. Sci. USA 2002, 99, 7757–7762. [Google Scholar] [CrossRef]
- Richon, V.M.; Garcia-Vargas, J.; Hardwick, J.S. Development of vorinostat: Current applications and future perspectives for cancer therapy. Cancer Lett. 2009, 280, 201–210. [Google Scholar] [CrossRef]
- Renzini, A.; D’Onghia, M.; Coletti, D.; Moresi, V. Histone Deacetylases as Modulators of the Crosstalk Between Skeletal Muscle and Other Organs. Front. Physiol. 2022, 13, 706003. [Google Scholar] [CrossRef]
- Yakabe, M.; Hosoi, T.; Akishita, M.; Ogawa, S. Updated concept of sarcopenia based on muscle-bone relationship. J. Bone Miner. Metab. 2020, 38, 7–13. [Google Scholar] [CrossRef] [PubMed]
- Ellingsgaard, H.; Hauselmann, I.; Schuler, B.; Habib, A.M.; Baggio, L.L.; Meier, D.T.; Eppler, E.; Bouzakri, K.; Wueest, S.; Muller, Y.D.; et al. Interleukin-6 enhances insulin secretion by increasing glucagon-like peptide-1 secretion from L cells and alpha cells. Nat. Med. 2011, 17, 1481–1489. [Google Scholar] [CrossRef] [PubMed]
- Serrano, A.L.; Baeza-Raja, B.; Perdiguero, E.; Jardí, M.; Muñoz-Cánoves, P. Interleukin-6 is an essential regulator of satellite cell-mediated skeletal muscle hypertrophy. Cell Metab. 2008, 7, 33–44. [Google Scholar] [CrossRef] [PubMed]
- Rosendal, L.; Søgaard, K.; Kjaer, M.; Sjøgaard, G.; Langberg, H.; Kristiansen, J. Increase in interstitial interleukin-6 of human skeletal muscle with repetitive low-force exercise. J. Appl. Physiol. 2005, 98, 477–481. [Google Scholar] [CrossRef]
- Jacques, M.; Hiam, D.; Craig, J.; Barrès, R.; Eynon, N.; Voisin, S. Epigenetic changes in healthy human skeletal muscle following exercise- a systematic review. Epigenetics 2019, 14, 633–648. [Google Scholar] [CrossRef]
- Renzini, A.; Marroncelli, N.; Noviello, C.; Moresi, V.; Adamo, S. HDAC4 Regulates Skeletal Muscle Regeneration via Soluble Factors. Front. Physiol. 2018, 9, 1387. [Google Scholar] [CrossRef]
- Mozzetta, C.; Consalvi, S.; Saccone, V.; Tierney, M.; Diamantini, A.; Mitchell, K.J.; Marazzi, G.; Borsellino, G.; Battistini, L.; Sassoon, D.; et al. Fibroadipogenic progenitors mediate the ability of HDAC inhibitors to promote regeneration in dystrophic muscles of young, but not old Mdx mice. EMBO Mol. Med. 2013, 5, 626–639. [Google Scholar] [CrossRef]
- Mankhong, S.; Kim, S.; Moon, S.; Kwak, H.B.; Park, D.H.; Kang, J.H. Experimental Models of Sarcopenia: Bridging Molecular Mechanism and Therapeutic Strategy. Cells 2020, 9, 1385. [Google Scholar] [CrossRef]
- Cirillo, F.; Mangiavini, L.; La Rocca, P.; Piccoli, M.; Ghiroldi, A.; Rota, P.; Tarantino, A.; Canciani, B.; Coviello, S.; Messina, C.; et al. Human Sarcopenic Myoblasts Can Be Rescued by Pharmacological Reactivation of HIF-1α. Int. J. Mol. Sci. 2022, 23, 7114. [Google Scholar] [CrossRef]
- Cruz-Jentoft, A.J.; Sayer, A.A. Sarcopenia. Lancet 2019, 393, 2636–2646. [Google Scholar] [CrossRef]
- Kuleshov, M.V.; Jones, M.R.; Rouillard, A.D.; Fernandez, N.F.; Duan, Q.; Wang, Z.; Koplev, S.; Jenkins, S.L.; Jagodnik, K.M.; Lachmann, A.; et al. Enrichr: A comprehensive gene set enrichment analysis web server 2016 update. Nucleic Acids Res. 2016, 44, W90–W97. [Google Scholar] [CrossRef] [PubMed]
- Love, M.I.; Huber, W.; Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014, 15, 550. [Google Scholar] [CrossRef] [PubMed]
- Langfelder, P.; Horvath, S. WGCNA: An R package for weighted correlation network analysis. BMC Bioinform. 2008, 9, 559. [Google Scholar] [CrossRef] [PubMed]
- Keenan, A.B.; Jenkins, S.L.; Jagodnik, K.M.; Koplev, S.; He, E.; Torre, D.; Wang, Z.; Dohlman, A.B.; Silverstein, M.C.; Lachmann, A.; et al. The Library of Integrated Network-Based Cellular Signatures NIH Program: System-Level Cataloging of Human Cells Response to Perturbations. Cell Syst. 2018, 6, 13–24. [Google Scholar] [CrossRef] [PubMed]
- Napolitano, F.; Sirci, F.; Carrella, D.; di Bernardo, D. Drug-set enrichment analysis: A novel tool to investigate drug mode of action. Bioinformatics 2016, 32, 235–241. [Google Scholar] [CrossRef] [PubMed]
Drug | Target | CRank | D1 | D2 | D3 | Reference Article |
---|---|---|---|---|---|---|
Danazol | AR; CCL2; CYP2C8; ESR1; GNRHR; GNRHR2; PGR; PLG; PROS1; SERPINA6; SERPINC1; SERPING1; SHBG; TNF | 5 | 67 | 1 | 6 | Danazol increases lean tissue mass [33] |
estradiol-benzoate | ESR1 | 6 | 18 | 23 | 41 | Estrogen recovers exercise endurance in female mice [34] |
SB-431542 | ACVR1B; ACVR1C; TGFBR1 | 8 | 2 | 11 | 109 | SB-431542 could increase Human pluripotent stem cells myotube fusion [35] |
diclofenac | AKR1C3; ALOX5; ASIC1; ASIC3; CYP2C8; CYP2C9; KCNQ2; KCNQ3; LTF; PLA2G2A; PPARG; SCN4A; TF; TNF; ZADH2 | 11 | 61 | 60 | 30 | The utilization of NSAIDs revealed a decreased susceptibility to sarcopenia in users as compared to non-users. (OR 0.26, 95% CI: 0.08–0.81) [36] |
budesonide | BGLAP; CCL11; CCL5; CSF2; CYP3A5; CYP3A7; ICAM1; IL4; IL5; IL8; NR3C1 | 16 | 27 | 53 | 102 | Budesonide promotes the terminal differentiation of satellite cells [37] |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Liang, S.; Liu, D.; Xiao, Z.; Greenbaum, J.; Shen, H.; Xiao, H.; Deng, H. Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans. Pharmaceuticals 2023, 16, 607. https://doi.org/10.3390/ph16040607
Liang S, Liu D, Xiao Z, Greenbaum J, Shen H, Xiao H, Deng H. Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans. Pharmaceuticals. 2023; 16(4):607. https://doi.org/10.3390/ph16040607
Chicago/Turabian StyleLiang, Shuang, Danyang Liu, Zhengwu Xiao, Jonathan Greenbaum, Hui Shen, Hongmei Xiao, and Hongwen Deng. 2023. "Repurposing Approved Drugs for Sarcopenia Based on Transcriptomics Data in Humans" Pharmaceuticals 16, no. 4: 607. https://doi.org/10.3390/ph16040607