Volume: 1 Issue: 1
Year: 2024, Page: 12-15, Doi: https://doi.org/10.71325/ajjms.v1i1.arora
Received: Dec. 20, 2024 Accepted: Dec. 23, 2024 Published: Dec. 30, 2024
Multiomics is a high-throughput technology with multilayered system biology approach incorporating bioinformatic analysis of the data. At present it includes genomics, epigenomics, transcriptomics, proteomics, metabolomics, and gut microbiomics with advancement to the level of single cell analysis. Multiomics is an advancing approach (1) to understand the pathobiology of disease, (2) to identify sensitive biomarkers for the diagnosis of diseases as well as in monitoring and (3) to identify disease specific targets to treat the patient in the context of precision medicine as targeted therapeutics. In the present review, a brief account of various multiomic techniques is considered and relevant examples are pondered to reflect their applications in both preclinical and clinical translational research.
Keywords: Multiomics, Genomics, Proteomics, Metabolomics, Pathobiology
Wei S, Tang W, Chen D, Xiong J, Xue L, Dai Y. Multiomics insights into the female reproductive aging. Ageing Res Rev. 2024;95(102245). Available from: https://doi.org/10.1016/j.arr.2024.102245
Chen C, Wang J, Pan D, Wang X, Xu Y, Yan J. Applications of multi-omics analysis in human diseases. MedComm. 1931;4(4):e315. Available from: https://doi.org/10.1002/mco2.315
MoTrPAC Study Group; Lead Analysts; MoTrPAC Study Group. Temporal dynamics of the multiomic response to endurance exercise training. Nature. 2024;629(8010):174–183. Available from: https://doi.org/10.1038/s41586-023-06877-w
Liang G, Cao W, Tang D, Zhang H, Yu Y, Ding J, et al. NanomedomicsClick to copy article link. ACS Nano. 2024;18(17):10979–11024. Available from: https://doi.org/10.1021/acsnano.3c11154
Lopez-Lee C, Torres E, Carling G, Gan L. Mechanisms of sex differences in Alzheimer's disease. Neuron. 2024;112(8):1208–1221. Available from: https://doi.org/10.1016/j.neuron.2024.01.024
Mackowiak B, Fu Y, Maccioni L, Gao B. Alcohol-associated liver disease. J Clin Invest. 2024;134(3):e176345. Available from: https://doi.org/10.1172/jci176345
Yan C, Bao J, JJ. Exploring the interplay of gut microbiota, inflammation, and LDL-cholesterol: a multiomics Mendelian randomization analysis of their causal relationship in acute pancreatitis and non-alcoholic fatty liver disease. J Transl Med. 2024;22(1):179. Available from: https://doi.org/10.1186/s12967-024-04996-0
Cui H, Wang C, Maan H, Pang K, Luo F, Duan N. scGPT: toward building a foundation model for single-cell multi-omics using generative AI. Nat Methods. 2024;21(8):1470–1480. Available from: https://doi.org/10.1038/s41592-024-02201-0
Ewald JD, Zhou G, Lu Y, Kolic J, Ellis C, Johnson JD, et al. Web-based multi-omics integration using the Analyst software suite. Nature Protocol. 2024;19(5):1467–1497. Available from: https://doi.org/10.1038/s41596-023-00950-4
Roehrig A, Hirsch TZ, Pire A, Morcrette G, Gupta B, Marcaillou C, et al. Single-cell multiomics reveals the interplay of clonal evolution and cellular plasticity in hepatoblastoma. Nature Communications. 2024;15(1):3031. Available from: https://doi.org/10.1038/s41467-024-47280-x
Wang C, Qiu J, Liu M, Wang Y, Yu Y, Liu H, et al. Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics andExosomes. Adv Sci (Weinh). 2024;11(28):e2401263. Available from: https://doi.org/10.1002/advs.202401263
Lim J, Park C, Kim M, Kim H, Kim J, Lee DS. Advances in single-cell omics and multiomics for high-resolution molecular profiling. Exp Mol Med. 2024;56(3):515–526. Available from: https://doi.org/10.1038/s12276-024-01186-2
Madden EB, Hindorff LA, Bonham VL, Akintobi TH, Burchard EG, Baker KE, et al. Advancing genomics to improve health equity. Nat Genet. 2024;56(5):752–757. Available from: https://doi.org/10.1038/s41588-024-01711-z
Scarano C, Veneruso I, RRDS, GDB, AS, D'Argenio V. The Third-Generation Sequencing Challenge: Novel Insights for the Omic Sciences. Biomolecules. 2024;14(5):568. Available from: https://doi.org/10.3390/biom14050568
Jain S, Eadon MT. Spatial transcriptomics in health and disease. Nat Rev Nephrol. 2024;20(10):659–671. Available from: https://doi.org/10.1038/s41581-024-00841-1
Zhang T, Zhao F, Lin Y, Liu M, Zhou H, Cui F, et al. Integrated analysis of single-cell and bulk transcriptomics develops a robust neuroendocrine cell-intrinsic signature to predict prostate cancer progression. Theranostics. 2024;14(3):1065–1080. Available from: https://doi.org/10.7150/thno.92336
Cilento MA, Sweeney CJ, Butler LM. Spatial transcriptomics in cancer research and potential clinical impact: a narrative review. J Cancer Res Clin Oncol. 2024;150(6):296. Available from: https://doi.org/10.1007/s00432-024-05816-0
Li H, Li D, Ledru N, Xuanyuan Q, Wu H, Asthana A, et al. Transcriptomic, epigenomic, and spatial metabolomic cell profiling redefines regional human kidney anatomy. Cell Metab. 2024;36(5):1105–1125. Available from: https://doi.org/10.1016/j.cmet.2024.02.015
Armingol E, Baghdassarian HM, Lewis NE. The diversification of methods for studying cell-cell interactions and communication. Nat Rev Genet. 2024;25(6):381–400. Available from: https://doi.org/10.1038/s41576-023-00685-8
Mathur R, Wang Q, Schupp PG, Nikolic A, Hilz S, Hong C, et al. Glioblastoma evolution and heterogeneity from a 3D whole-tumor perspective. Cell. 2024;187(2):446–463. Available from: https://doi.org/10.1016/j.cell.2023.12.013
Villiger L, Joung J, Koblan L, Weissman J, Abudayyeh OO, Gootenberg JS. CRISPR technologies for genome, epigenome and transcriptome editing. Nat Rev Mol Cell Biol. 2024;25(6):464–487. Available from: https://doi.org/10.1038/s41580-023-00697-6
Kiri S, Ryba T. Cancer, metastasis, and the epigenome. Mol Cancer. 2024;23(1):154. Available from: https://doi.org/10.1186/s12943-024-02069-w
Wu Z, Qu J, Zhang W, Liu GH. Stress, epigenetics, and aging: Unraveling the intricate crosstalk. Molecular Cell. 2024;84(1):34–54. Available from: https://dx.doi.org/10.1016/j.molcel.2023.10.006
Pietzner M, Uluvar B, Kolnes KJ, Jeppesen PB, Frivold SV, Skattebo Ø, et al. Systemic proteome adaptions to 7-day complete caloric restriction in humans. Nature Metabolism. 2024;6(4):764–777. Available from: https://dx.doi.org/10.1038/s42255-024-01008-9
Tholey A, Schlüter H. Top-down proteomics and proteoforms - special issue. Proteomics. 2024;24(3-4):2200375. Available from: https://doi.org/10.1002/pmic.202200375
Shen L, Zhang Z, Wu P, Yang J, Cai Y, Chen K, et al. Mechanistic insight into glioma through spatially multidimensional proteomics. Science Advances. 2024;10(7):1721. Available from: https://dx.doi.org/10.1126/sciadv.adk1721
Strauss MT, Bludau I, Zeng WFF, Voytik E, Ammar C, Schessner JP, et al. AlphaPept, a modern and open framework for MS-based proteomics. Nat Commun. 2009;15(1):2168. Available from: https://doi.org/10.1038/s41467-024-46485-4
Fedorov II, Protasov SA, Tarasova IA, Gorshkov MV. Ultrafast Proteomics. Biochemistry (Moscow). 2024;89(8):1349–1361. Available from: https://dx.doi.org/10.1134/s0006297924080017
Tao J, Li J, Fan X, Jiang C, Wang Y, Qin M, et al. Unraveling the protein post-translational modification landscape: Neuroinflammation and neuronal death after stroke. Ageing Research Reviews. 2024;101:102489. Available from: https://dx.doi.org/10.1016/j.arr.2024.102489
Zhang N, Wu J, Zheng Q. Chemical proteomics approaches for protein post-translational modification studies. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics. 2024;1872(4):141017. Available from: https://dx.doi.org/10.1016/j.bbapap.2024.141017
Greenblatt JF, Alberts BM, Krogan NJ. Discovery and significance of protein-protein interactions in health and disease. Cell. 2024;187(23):6501–6517. Available from: https://dx.doi.org/10.1016/j.cell.2024.10.038
Si S, Liu H, Xu L, Zhan S. Identification of novel therapeutic targets for chronic kidney disease and kidney function by integrating multi-omics proteome with transcriptome. Genome Medicine. 2024;16(1):84. Available from: https://dx.doi.org/10.1186/s13073-024-01356-x
Zhang S, Wang Z, Wang Y, Zhu Y, Zhou Q, Jian X, et al. A metabolomic profile of biological aging in 250,341 individuals from the UK Biobank. Nat Commun. 2024;15(1):8081. Available from: https://doi.org/10.1038/s41467-024-52310-9
Luo YQ, Zhang CY, Nong XZ, Gao Y, Wang L, Ji G, et al. Metabolomics incirrhosis: Recent advances and opportunities. Clin Chim Acta. 2024;557:117886. Available from: https://doi.org/10.1016/j.cca.2024.117886
Yang S, Liu R, Xin Z, Zhu Z, Chu J, Zhong P, et al. Plasma Metabolomics Identifies Key Metabolites and Improves Prediction of Diabetic Retinopathy: Development and Validation across Multinational Cohorts. Ophthalmology. 2024;131(12):1436–1446. Available from: https://doi.org/10.1016/j.ophtha.2024.07.004
Berrell N, Sadeghirad H, Blick T, Bidgood C, Leggatt GR, O'Byrne K, et al. Metabolomics at the tumor microenvironment interface: Decoding cellular conversations. Med Res Rev. 2024;44(3):1121–1146. Available from: https://doi.org/10.1002/med.22010
Vicari M, Mirzazadeh R, Nilsson A, Shariatgorji R, Bjärterot P, Larsson L, et al. Spatial multimodal analysis of transcriptomes and metabolomes in tissues. Nat Biotechnol. 2024;42(7):1046–1050. Available from: https://doi.org/10.1038/s41587-023-01937-y
Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016;17(7):451–459. Available from: https://doi.org/10.1038/nrm.2016.25
Wang R, Li B, Lam SM, Shui G. Integration of lipidomics and metabolomics for in-depth understanding of cellular mechanism and disease progression. J Genet Genomics. 2020;47(2):69–83. Available from: https://doi.org/10.1016/j.jgg.2019.11.009
Bujak R, Struck-Lewicka W, Markuszewski MJ, Kaliszan R. Metabolomics for laboratory diagnostics. J Pharm Biomed Anal. 2015;113:108–120. Available from: https://doi.org/10.1016/j.jpba.2014.12.017
Khamis MM, Adamko DJ, El-Aneed A. Mass spectrometric based approaches in urine metabolomics and biomarker discovery. Mass Spectrom Rev. 2017;36(2):115–134. Available from: https://doi.org/10.1002/mas.21455
Papalexi E, Satija R. Single-cell RNA sequencing to explore immune cell heterogeneity. Nat Rev Immunol. 2018;18(1):35–45. Available from: https://doi.org/10.1038/nri.2017.76
Han X, Zhou Z, Fei L, Sun H, Wang R, Chen Y, et al. Construction of a human cell landscape at single-cell level. Nature. 2020;581(7808):303–309. Available from: https://doi.org/10.1038/s41586-020-2157-4
Collin J, Queen R, Zerti D, Bojic S, Dorgau B, Moyse N, et al. A single cell atlas of human cornea that defines its development, limbal progenitor cells and their interactions with the immune cells. Ocul Surf. 2021;21:279–298. Available from: https://doi.org/10.1016/j.jtos.2021.03.010
Ferchen K, Song B, Grimes L, H. A primer on single-cell genomics in myeloid biology. Curr Opin Hematol. 2021;28(1):11–17. Available from: https://doi.org/10.1097/MOH.0000000000000623
Chang JG, Tu SJ, Huang CM, Chen YC, Chiang HS, Lee YT, et al. Single-cell RNA sequencing of immune cells in patients with acute gout. Sci Rep. 2022;12:22130. Available from: https://doi.org/10.1038/s41598-022-25871-2
Shiao SL, KHG, NI, AH, RB, Shah A, et al. Single-cell and spatial profiling identify three response trajectories to pembrolizumab and radiation therapy in triple negative breast cancer. Cancer Cell. 2024;42(1):70–84. Available from: https://doi.org/10.1016/j.ccell.2023.12.012
Bandyopadhyay S, Duffy MP, Ahn KJ, Sussman JH, Pang M, Smith D, et al. Mapping th cellular biogeography of human bone marrow niches using single-cell transcriptomics and proteomic imaging. Cell. 2024;187(12):3120–3140. Available from: https://doi.org/10.1016/j.cell.2024.04.013
Hu J, Wang SG, Hou Y, Chen Z, Liu L, Li R, et al. Multiomic profiling of clear cell renal cell carcinoma identifies metabolic reprogramming associated with disease progression. Nat Genet. 2024;56(3):442–457. Available from: https://doi.org/10.1038/s41588-024-01662-5
Desai TA, Hedman ÅK, Dimitriou M, Koprulu M, Figiel S, Yin W, et al. Identifying proteomic risk factors for overall, aggressive, and early onset prostate cancer using Mendelian Randomisation and tumour spatial transcriptomics. eBioMedicine. 2024;105:105168. Available from: https://dx.doi.org/10.1016/j.ebiom.2024.105168
Patel AG, Ashenberg O, Collins NB, Segerstolpe Å, Jiang S, Slyper M, et al. A spatial cell atlas of neuroblastoma reveals developmental, epigenetic and spatial axis of tumor heterogeneity. bioRxiv. 2024. Available from: https://doi.org/10.1101/2024.01.07.574538
Sul WJ. Host-Associated Microbiome. J Microbiol. 2024;62(3):135–136. Available from: https://doi.org/10.1007/s12275-024-00135-y
Ratiner K, Ciocan D, Abdeen SK, Elinav E. Utilization of the microbiome in personalized medicine. Nat Rev Microbiol. 2024;22(5):291–308. Available from: https://doi.org/10.1038/s41579-023-00998-9
RL, JL, Zhou X. Lung microbiome: new insights into the pathogenesis of respiratory diseases. Signal Transduct Target Ther. 2024;17(1):19. Available from: https://doi.org/10.1038/s41392-023-01722-y
White MT, Sears CL. The microbial landscape of colorectal cancer. Nat Rev Microbiol. 2024;22(4):240–254. Available from: https://doi.org/10.1038/s41579-023-00973-4
Verdegaal AA, Goodman AL. Integrating the gut microbiome and pharmacology. Sci Transl Med. 2024;16(732):eadg8357. Available from: https://doi.org/10.1126/scitranslmed.adg8357
Matsuoka T, Yashiro M. Bioinformatics Analysis and Validation of Potential Markers Associated with Prediction and Prognosis of Gastric Cancer. Int J Mol Sci. 2024;25(11):5880. Available from: https://doi.org/10.3390/ijms25115880
Li C, Lin X, Lin Q, Lin Y, Lin H. Jiangu granules ameliorate postmenopausal osteoporosis via rectifying bone homeostasis imbalance: A network pharmacology analysis based on multi-omics validation. Phytomedicine. 2024;122:155137.
Yang S, Wei Z, Luo J, Wang X, Chen G, Guan X, et al. Integrated bioinformatics and multiomics reveal Liupao tea extract alleviatin NAFLD via regulating hepatic lipid metabolism and gut microbiota. Phytomedicine. 2024;132:155834. Available from: https://doi.org/10.1016/j.phymed.2024.155834
Gu Y, Li Z, Li H, Yi X, Liu X, Zhang Y, et al. Exploring the efficacious constituents and underlying mechanisms of sini decoction for sepsis treatment through network pharmacology and multi-omics. Phytomedicine. 2024;123:155212. Available from: https://doi.org/10.1016/j.phymed.2023.155212
Chen J, Ruan X, Sun Y, Lu S, Hu S, Yuan S. Multi-omic insight into the molecular networks of mitochondrial dysfunction in the pathogenesis of inflammatory bowel disease. EBioMedicine. 2024;99:104934. Available from: https://doi.org/10.1016/j.ebiom.2023.104934
Daskalakis NP, Iatrou A, Chatzinakos C, Jajoo A, Snijders C, Wylie D, et al. Systems biology dissection of PTSD and MDD across brain regions, cell types, and blood. Science. 2024;384(6698):3707. Available from: https://doi.org/10.1126/science.adh3707
© 2024 Published by Laxmi Memorial Education Trust. This is an open-access article under CC BY 4.0 license. (https://creativecommons.org/licenses/by/4.0/)
A R Aroor. Multiomics: Concepts, Methods and Applications. AJ J Med Sci 2024;1(1):12–15