A gut aging clock using microbiome multi-view profiles is associated with health and frail risk

References

• Reveles KR, Young EH, Zeidan AR, Dong Q. Microbiome changes in aging. In: Musi N, Hornsby PJ, editors. Handbook of the biology of aging. Academic Press;2021. p. 367–18. doi:10.1016/B978-0-12-815962-0.00017-2.
   Google Scholar
• Zhang X, Zhong H, Li Y, Shi Z, Ren H, Zhang Z, Zhou X, Tang S, Han X, Lin Y, et al. Sex- and age-related trajectories of the adult human gut microbiota shared across populations of different ethnicities. Nat Aging. 2021;1(1):87–100. doi:10.1038/s43587-020-00014-2.
   PubMedGoogle Scholar
• DeJong EN, Surette MG, Bowdish DM. The gut microbiota and unhealthy aging: disentangling cause from consequence. Cell Host & Microbe. 2020;28(2):180–9. doi:10.1016/j.chom.2020.07.013.
   PubMed Web of Science ®Google Scholar
• Buford TW. (Dis)trust your gut: the gut microbiome in age-related inflammation, health, and disease. Microbiome. 2017;5(1):1–11. doi:10.1186/s40168-017-0296-0.
   PubMedGoogle Scholar
• Chen J, Pitmon E, Wang K. Microbiome, inflammation and colorectal cancer. Semin Immunol. 2017;32:43–53. doi:10.1016/j.smim.2017.09.006.
   Google Scholar
• Nichols RG, Davenport ER. The relationship between the gut microbiome and host gene expression: a review. Hum Genet. 2020;140(5):1–14.
   Web of Science ®Google Scholar
• Zhao L, Zhang F, Ding X, Wu G, Lam YY, Wang X, Fu H, Xue X, Lu C, Ma J, et al. Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Sci. 2018;359(6380):1151–6. doi:10.1126/science.aao5774.
   PubMed Web of Science ®Google Scholar
• Huang S, Haiminen N, Carrieri A-P, Hu R, Jiang L, Parida L, Russell B, Allaband C, Zarrinpar A, Vázquez-Baeza Y, et al. Human skin, oral, and gut microbiomes predict chronological age. mSystems. 2020;5(1):e00630–19. doi:10.1128/mSystems.00630-19.
   PubMed Web of Science ®Google Scholar
• Galkin F, Mamoshina P, Aliper A, Putin E, Moskalev V, Gladyshev VN, Zhavoronkov A. Human gut microbiome aging clock based on taxonomic profiling and deep learning. Iscience. 2020;23(6):101199. doi:10.1016/j.isci.2020.101199.
   PubMed Web of Science ®Google Scholar
• Uhr GT, Dohnalová L, Thaiss CA. The dimension of time in host-microbiome interactions. mSystems. 2019;4(1):e00216–18. doi:10.1128/mSystems.00216-18.
   PubMed Web of Science ®Google Scholar
• DiMucci D, Kon M, Segrè D, Typas N. Machine learning reveals missing edges and putative interaction mechanisms in microbial ecosystem networks. mSystems. 2018;3(5):e00181–18. doi:10.1128/mSystems.00181-18.
   PubMed Web of Science ®Google Scholar
• Chen Y, Wang H, Lu W, Wu T, Yuan W, Zhu J, Lee YK, Zhao J, Zhang H, Chen W, et al. Human gut microbiome aging clocks based on taxonomic and functional signatures through multi-view learning. Gut Microbes. 2022;14(1):2025016. doi:10.1080/19490976.2021.2025016.
   PubMed Web of Science ®Google Scholar
• Sato H, Takado Y, Toyoda S, Tsukamoto-Yasui M, Minatohara K, Takuwa H, Urushihata T, Takahashi M, Shimojo M, Ono M, et al. Neurodegenerative processes accelerated by protein malnutrition and decelerated by essential amino acids in a tauopathy mouse model. Sci Adv. 2021;7(43):eabd5046. doi:10.1126/sciadv.abd5046.
   PubMed Web of Science ®Google Scholar
• Richardson NE, Konon EN, Schuster HS, Mitchell AT, Boyle C, Rodgers AC, Finke M, Haider LR, Yu D, Flores V, et al. Lifelong restriction of dietary branched-chain amino acids has sex-specific benefits for frailty and life span in mice. Nat Aging. 2021;1(1):73–86. doi:10.1038/s43587-020-00006-2.
   PubMedGoogle Scholar
• Ghosh TS, Das M, Jeffery IB, O’Toole PW. Adjusting for age improves identification of gut microbiome alterations in multiple diseases. Elife. 2020;9:e50240. doi:10.7554/eLife.50240.
   PubMed Web of Science ®Google Scholar
• Hindmarch I, Lehfeld H, Jongh PD, Erzigkeit H. The bayer activities of daily living scale (B-ADL). Dement Geriatr Cogn Disord. 1998;9(Suppl. 2):20–6. doi:10.1159/000051195.
   PubMed Web of Science ®Google Scholar
• Nasreddine ZS, Phillips NA, Bédirian V, Charbonneau S, Whitehead V, Collin I, Cummings JL, Chertkow H. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–9. doi:10.1111/j.1532-5415.2005.53221.x.
   PubMed Web of Science ®Google Scholar
• Moon SJ, Lee WY, Hwang JS, Hong YP, Morisky DE, Reboldi G. Accuracy of a screening tool for medication adherence: a systematic review and meta-analysis of the morisky medication adherence scale-8. PLoS ONE. 2017;12(11):e0187139. doi:10.1371/journal.pone.0187139.
   PubMed Web of Science ®Google Scholar
• Kabootari M, Raee MR, Akbarpour S, Asgari S, Azizi F, Hadaegh F. Serum alkaline phosphatase and the risk of coronary heart disease, stroke and all-cause mortality: Tehran lipid and glucose study. BMJ Open. 2018;8(11):e023735. doi:10.1136/bmjopen-2018-023735.
   PubMed Web of Science ®Google Scholar
• Chen L, Zheng T, Yang Y, Chaudhary P, Teh J, Cheon B, Moses D, Schuster SC, Schlundt J, Li J, et al. Integrative multiomics analysis reveals host-microbe-metabolite interplays associated with the aging process in Singaporeans. Gut Microbes. 2022;14(1):2070392. doi:10.1080/19490976.2022.2070392.
   PubMed Web of Science ®Google Scholar
• Jang H, Mason J, Choi S. Genetic and epigenetic interactions between folate and aging in carcinogenesis. J Nutr. 2005;135(12):2967S–71S. doi:10.1093/jn/135.12.2967S.
   PubMed Web of Science ®Google Scholar
• Lv X, Wang X, Wang Y, Zhou D, Li W, Wilson J, Chang H, Huang G. Folic acid delays age-related cognitive decline in senescence-accelerated mouse prone 8: alleviating telomere attrition as a potential mechanism. Aging. 2019;11(22):10356–10373. doi:10.18632/aging.102461.
   PubMedGoogle Scholar
• Keisuke Y, Keisuke O, Takashi N. NAD metabolism: implications in aging and longevity. Ageing Res Rev. 2018;47:1–17. doi:10.1016/j.arr.2018.05.006.
   PubMed Web of Science ®Google Scholar
• Liu S, Wang Y, Zhao L, Sun X, Feng Q. Microbiome succession with increasing age in three oral sites. Aging. 2020;12(9):7874.
   PubMedGoogle Scholar
• Hideki O, Mayumi I, Nozomu U, Shintani D, Nishikawa T, Hasegawa K, Fujiwara K, Akechi T. Subclinical thiamine deficiency identified by preoperative evaluation in an ovarian cancer patient: diagnosis and the need for preoperative thiamine measurement. Palliat Support Care. 2018;17(5):609–610. doi:10.1017/S1478951518000615.
   Web of Science ®Google Scholar
• Onishi H, Ishida M, Tanahashi I, Takahashi T, Taji Y, Ikebuchi K, Furuya D, Akechi T. Subclinical thiamine deficiency in patients with abdominal cancer. Palliat Support Care. 2018;16(4):497–499. doi:10.1017/S1478951517000992.
   PubMed Web of Science ®Google Scholar
• Choo SW, Mohammed WK, Mutha NV, Rostami N, Ahmed H, Krasnogor N, Tan GYA, Jakubovics NS. Transcriptomic Responses to Coaggregation between Streptococcus gordonii and Streptococcus oralis. Appl Environ Microb. 2021;87(22):e01558–21. doi:10.1128/AEM.01558-21.
   PubMed Web of Science ®Google Scholar
• Obata J, Fujishima K, Nagata E, Oho T. Pathogenic mechanisms of cariogenic Propionibacterium acidifaciens. Arch Oral Biol. 2019;105:46–51. doi:10.1016/j.archoralbio.2019.06.005.
   PubMed Web of Science ®Google Scholar
• Delorme C, Abraham A-L, Renault P, Guédon E. Genomics of Streptococcus salivarius, a major human commensal. Infect Genet Evol. 2015;33:381–92. doi:10.1016/j.meegid.2014.10.001.
   PubMed Web of Science ®Google Scholar
• Sayed N, Huang Y, Nguyen K, Krejciova-Rajaniemi Z, Grawe AP, Gao T, Tibshirani R, Hastie T, Alpert A, Cui L, et al. An inflammatory aging clock (iAge) based on deep learning tracks multimorbidity, immunosenescence, frailty and cardiovascular aging. Nat Aging. 2021;1(7):598–615. doi:10.1038/s43587-021-00082-y.
   PubMedGoogle Scholar
• Sato Y, Atarashi K, Plichta DR, Arai Y, Sasajima S, Kearney SM, Suda W, Takeshita K, Sasaki T, Okamoto S, et al. Novel bile acid biosynthetic pathways are enriched in the microbiome of centenarians. Nature. 2021;599(7885):1–7.
   Web of Science ®Google Scholar
• Pasolli E, Schiffer L, Manghi P, Renson A, Obenchain V, Truong DT, Beghini F, Malik F, Ramos M, Dowd JB, et al. Accessible, curated metagenomic data through ExperimentHub. Nat Methods. 2017;14(11):1023–4. doi:10.1038/nmeth.4468.
   PubMed Web of Science ®Google Scholar
• Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. doi:10.1093/bioinformatics/btu170.
   PubMed Web of Science ®Google Scholar
• Langmead B, Salzberg SL. Fast gapped-read alignment with bowtie 2. Nat Methods. 2012;9(4):357–9. doi:10.1038/nmeth.1923.
   PubMed Web of Science ®Google Scholar
• Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25(16):2078–2079. doi:10.1093/bioinformatics/btp352.
   PubMed Web of Science ®Google Scholar
• Quinlan AR, Hall IM. Bedtools: a flexible suite of utilities for comparing genomic features. Bioinformatics. 2010;26(6):841–2. doi:10.1093/bioinformatics/btq033.
   PubMed Web of Science ®Google Scholar
• Beghini F, McIver LJ, Blanco-Míguez A, Dubois L, Asnicar F, Maharjan S, Mailyan A, Manghi P, Scholz M, Thomas AM, et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. Elife. 2021;10:e65088. doi:10.7554/eLife.65088.
   PubMed Web of Science ®Google Scholar
• McInnes L, Healy J, Saul N, Großberger L. UMAP: uniform manifold approximation and projection. J Open Source Softw. 2018;3(29):3. doi:10.21105/joss.00861.
   Google Scholar
• Oksanen J, Kindt R, Legendre P, O’Hara B, Stevens MHH, Oksanen MJ, Suggests, MA. The vegan package. Commun Eco Package. 2007;10(631–637):719.
   Google Scholar
• Pedregosa F, Varoquaux G, Gramfort A, Michel V, Thirion B, Grisel O, Blondel M, Prettenhofer P, Weiss R, Dubourg V, et al. Scikit-learn: machine learning in Python. J Mach Learn Res. 2011;12:2825–2830.
   Web of Science ®Google Scholar
• Chen T, He T, Benesty M, Khotilovich V, Tang Y, Cho H. Xgboost: extreme gradient boosting. R Package Version 0 4-2 2015;1(4):1–4.
   Google Scholar
• Ke G, Meng Q, Finley T, Wang T, Chen W, Ma W, Ye Q, Liu, TY. Lightgbm: a highly efficient gradient boosting decision tree. Adv Neural Inf Process Syst. 2017;30:3146–3154.
   Google Scholar
• Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, Burovski E, Peterson P, Weckesser W, Bright J, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat Methods. 2020;17(3):261–72. doi:10.1038/s41592-019-0686-2.
   PubMed Web of Science ®Google Scholar
• Klaise J, Van Looveren A, Vacanti G, Coca A. Alibi Explain: algorithms for explaining machine learning models. J Mach Learn Res. 2021;22:1–7.
   Web of Science ®Google Scholar
• Beghini F, McIver L, Blanco-Míguez A, Dubois L, Asnicar F, Maharjan S, Mailyan A, Manghi P, Scholz M, Thomas AM, et al. Integrating taxonomic, functional, and strain-level profiling of diverse microbial communities with bioBakery 3. eLife. 2021;10:e65088. doi:10.7554/eLife.65088.
   PubMed Web of Science ®Google Scholar