Advancements in artificial intelligence and machine learning in revolutionising biomarker discovery
DOI:
https://doi.org/10.1590/Keywords:
Biomarkers;, Artificial Intelligence;, Machine Learning;, Multi-omics;, OmicsAbstract
The article explores the significance of biomarkers in clinical research and the advantages of utilizing artificial intelligence (AI) and machine learning (ML) in the discovery process. Biomarkers provide a more comprehensive understanding of disease progression and response to therapy compared to traditional indicators. AI and ML offer a new approach to biomarker discovery, leveraging large amounts of data to identify patterns and optimize existing biomarkers. Additionally, the article touches on the emergence of digital biomarkers, which use technology to assess an individual’s physiological and behavioural states, and the importance of properly processing omics and multi-omics data for efficient handling by computer systems. However, the article acknowledges the challenges posed by AI/ML in the identification of biomarkers, including potential biases in the data and the need for diversity in data representation. To address these challenges, the article suggests the importance of regulation and diversity in the development of AI/ML algorithms.
Downloads
References
bou L, Peters J, Wong E, Akers R, Dossou MS, Sosnoff JJ, et al. Gait and Balance Assessments using Smartphone Applications in Parkinson’s Disease: A Systematic Review. J Med Syst. 2021;45(9):87.
Al-Amrani S, Al-Jabri Z, Al-Zaabi A, Alshekaili J, Al-Khabori M. Proteomics: Concepts and applications in human medicine. World J Biol Chem. 2021;12(5):57-69.
Amruthnath N, Gupta T. A research study on unsupervised machine learning algorithms for early fault detection in predictive maintenance. In: Proceedings of the 2018 5th International Conference on Industrial Engineering and Applications (ICIEA); 2018; p. 355-361.
Attia ZI, Harmon DM, Behr ER, Friedman PA. Application of artificial intelligence to the electrocardiogram. Eur Heart J. 2021;42(46):4717-4730.
Biomarkers Definitions Working Group. Biomarkers and surrogate endpoints: preferred definitions and conceptual framework. Clin Pharmacol Ther. 2001;69(3):89-95.
Buchwald ZS, Tian S, Rossi M, Smith GH, Switchenko J, Hauenstein JE, et al. Genomic copy number variation correlates with survival outcomes in WHO grade IV glioma. Sci Rep. 2020;10(1):7355.
Cappozzo A, McCrory C, Robinson O, Freni Sterrantino A, Sacerdote C, Krogh V, et al. A blood DNA methylation biomarker for predicting short-term risk of cardiovascular events. Clinical Epigenetics. 2022;14(1):121.
Carr TF, Kraft M. Use of biomarkers to identify phenotypes and endotypes of severeasthma. Ann Allergy Asthma Immunol. 2018;121(4):414-420.
Chen J, Sun M, Shen B. Deciphering oncogenic drivers: from single genes to integrated pathways. Brief Bioinform. 2015;16(3):413-28.
Chen X, Chen DG, Zhao Z, Balko JM, Chen J. Artificial image objects for classification of breast cancer biomarkers with transcriptome sequencing data and convolutional neural network algorithms. Breast Cancer Res. 2021;23(1):96.
Chen Y, Li EM, Xu LY. Guide to Metabolomics Analysis: A Bioinformatics Workflow. Metabolites. 2022;12(4):357.
Chowdhury S, Schoen M. Research Paper Classification using Supervised Machine Learning Techniques. In: Proceedings of the 2020 International Conference on Innovative Trends in Computer Engineering (ITCE); 2020:1-6
Clark C, Dayon L, Masoodi M, Bowman GL, Popp J. An integrative multi-omics approach reveals new central nervous system pathway alterations in Alzheimer’s disease. Alzheimers Res Ther. 2021;13(1):71.
Coppetti T, Brauchlin A, Müggler S, Attinger TA, Templin C, Schönrath F, et al. Accuracy of smartphone apps for heart rate measurement. Eur J Prev Cardiol. 2017;24(12):1287-1293.
De Fazio R, Mattei V, Al-Naami B, De Vittorio M, Visconti P. Methodologies and Wearable Devices to Monitor Biophysical Parameters Related to Sleep Dysfunctions: An Overview. Micromachines. 2022;13(10):1335.
De Jong J, Cutcutache I, Page M, Elmoufti S, Dilley C, Fröhlich H, et al. Towards realizing the vision of precision medicine: AI-based prediction of clinical drug response. Brain. 2021;144(6):1738-1750.
Ding W, Chen G, Shi T. Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis. Epigenetics. 2019;14(1):67-80.
Draisma G, Etzioni R, Tsodikov A, Mariotto A, Wever EM, Wernert N, et al. Lead time and overdiagnosis in prostate-specific antigen screening: importance of methods and context. J Natl Cancer Inst. 2003;95(18):1375-84.
Edgar R, Domrachev M, Lash AE. Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002;30(1):207-10.
Fan M, Yang AC, Fuh JL, Chou CA. Topological pattern recognition of severe Alzheimer’s disease via regularized supervised learning of EEG complexity. Front Neurosci. 2018;12:685.
Fan Y, Kao C, Yang F, Wang F, Yin G, Wang Y, et al. Integrated Multi-Omics Analysis Model to Identify Biomarkers Associated with Prognosis of Breast Cancer. Front Oncol. 2022;12:899900.
Fu B, Du C, Wu Z, Li M, Zhao Y, Liu X, et al. Analysis of DNA methylation-driven genes for predicting the prognosis of patients with colorectal cancer. Aging (Albany NY). 2020;12(22):22814-22839.
Galderisi A, Zammataro L, Losiouk E, Lanzola G, Kraemer K, Facchinetti A, et al. Continuous Glucose Monitoring Linked to an Artificial Intelligence Risk Index: Early Footprints of Intraventricular Hemorrhage in Preterm Neonates. Diabetes Technol Ther. 2019;21(3):146-153.
Gauba V, Saldanha M, Vize C, Saleh GM. Thiopurine methyltransferase screening before azathioprine therapy. Br J Ophthalmol. 2006;90(7):923-924.
Gowda GA, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Rev Mol Diagn. 2008;8(5):617-633.
Gupta R, Alam MA, Agarwal P. Modified Support Vector Machine for Detecting Stress Level Using EEG Signals. In: Versaci M, editor. Computational Intelligence and Neuroscience. 2020:8860841.
Haider S, Pal R. Integrated analysis of transcriptomic and proteomic data. Curr Genomics. 2013;14(2):91-110.
Hammoudeh A. A concise introduction to reinforcement learning. Amman, Jordan: Princess Sumaya University for Technology. 2018.
Han M, Dai J, Zhang Y, Lin Q, Jiang M, Xu X, et al. Support vector machines coupled with proteomics approaches for detecting biomarkers predicting chemotherapy resistance in small cell lung cancer. Oncology Reports. 2012;28:2233-2238.
Haug K, Salek RM, Conesa P, Hastings J, Matos P, Rijnbeek M, et al. MetaboLights: an open-access general-purpose repository for metabolomics studies and associated metadata. Nucleic Acids Res. 2013;41(D1): D781-6.
Hijazo-Pechero S, Alay A, Marín R, Vilariño N, Muñoz-Pinedo C, Villanueva A, et al. Gene Expression Profiling as a Potential Tool for Precision Oncology in Non-Small Cell Lung Cancer. Cancers. 2021;13(19):4734.
Holmes B, Chitale D, Loving J, Tran M, Subramanian V, Berry A, et al. Customizable natural language processing biomarker extraction tool. JCO Clinical Cancer Informatics. 2021; 5:833-841.
Huseby CJ, Delvaux E, Brokaw DL, Coleman PD. Blood Transcript Biomarkers Selected by Machine Learning Algorithm Classify Neurodegenerative Diseases including Alzheimer’s Disease. Biomolecules. 2022;12(11):1592.
Jaffe AS, Babuin L, Clinton SK, Meijers JC, Apple FS. Troponin: the marker of the millennium in acute cardiac care. Circulation. 2000;102(10):1026-1029.
Jin X, Liu C, Xu T, Su L, Zhang X. Artificial intelligence biosensors: challenges and prospects. Biosens Bioelectron. 2020;165:112412.
Käll L, Canterbury JD, Weston J, Noble WS, MacCoss MJ. Semi-supervised learning for peptide identification from shotgun proteomics datasets. Nat Methods. 2007;4(11):923-925.
Kiebish AM, Cullen J, Mishra P, Ali A, Milliman E, Rodrigues LO, et al. multi-omic serum biomarkers for prognosis of disease progression in prostate cancer. J Transl Med. 2020;18:10.
Kim Y, Kim J, Son M, Lee J, Yeo I, Choi KY, et al. Plasma protein biomarker model for screening Alzheimer disease using multiple reaction monitoring-mass spectrometry. Sci Rep. 2022;12(1):1282.
Kyriazakos S, Pnevmatikakis A, Cesario A, Kostopoulou K, Boldrini L, Valentini V, et al. Discovering Composite Lifestyle Biomarkers with Artificial Intelligence from Clinical Studies to Enable Smart eHealth and Digital Therapeutic Services. Frontiers Digital Health. 2021;3.
Li W, Liu B, Wang W, Sun C, Che J, Yuan X, Zhai C. Lung Cancer Stage Prediction Using Multi-Omics Data. Comput Math Methods Med. 2022;2022:2279044.
Lin C, Liu X, Zheng B, Ke R, Tzeng CM. Liquid Biopsy, ctDNA Diagnosis through NGS. Life (Basel). 2021;11(9):890.
Lin Y, Qian F, Shen L, Chen F, Chen J, Shen B. Computer-aided biomarker discovery for precision medicine: data resources, models and applications. Briefings Bioinformatics. 2019;20(3):952-975.
Liu J, Huang L, Shi X, Gu C, Xu H, Liu S. Clinical parameters and metabolomic biomarkers that predict in-hospital outcomes in patients with ST-segment elevated myocardial infarctions. Frontiers Physiol. 2022; 12:820240.
Lok AS, Sterling RK, Everhart JE, Wright EC, Hoefs JC, Di Bisceglie AM, et al. HALT-C Trial Group. Des-gamma-carboxy prothrombin and alpha-fetoprotein as biomarkers for the early detection of hepatocellular carcinoma. Gastroenterology. 2010;138(2):493-502.
Lötsch J, Lerch F, Djaldetti R, Tegder I, Ultsch A. Identification of disease-distinct complex biomarker patterns by means of unsupervised machine-learning using an interactive R toolbox (Umatrix). Big Data Analytics. 2018;3(1):1-17.
Lowe R, Shirley N, Bleackley M, Dolan S, Shafee T. Transcriptomics technologies. PLoS Comput Biol. 2017;13(5):e1005457.
Luo H, Yang D, Barszczyk A, Vempala N, Wei J, Wu SJ, et al. Smartphone-Based Blood Pressure Measurement Using Transdermal Optical Imaging Technology. Circ Cardiovasc Imaging. 2019;12(8):e008857.
Maibach F, Sadozai H, Seyed Jafari SM, Hunger RE, Schenk M. Tumor-Infiltrating Lymphocytes and Their Prognostic Value in Cutaneous Melanoma. Front Immunol. 2020;11:2105.
Maisel AS, Krishnaswamy P, Nowak RM, McCord J, Hollander JE, Duc P, et al. Rapid measurement of B-type natriuretic peptide in the emergency diagnosis of heart failure. N Engl J Med. 2002;346(11):1015-1021.
Mandryk RL, Birk MV, Vedress S, Wiley K, Reid E, Berger P, et al. Remote Assessment of Depression Using Digital Biomarkers from Cognitive Tasks. Front Psychol. 2021;12:767507.
Milali MP, Kiware SS, Govella NJ, Okumu F, Bansal N, Bozdag S, et al. An autoencoder and artificial neural network-based method to estimate parity status of wild mosquitoes from near-infrared spectra. PLoS One. 2020;15(6):e0234557.
Molinski SV, Shahani VM, Subramanian AS, MacKinnon SS, Woollard G, Laforet M, et al. A Comprehensive mapping of cystic fibrosis mutations to CFTR protein identifies mutation clusters and molecular docking predicts corrector binding site. Proteins. 2018;86(8):833-843.
Nikitin A, Egorov S, Daraselia N, Mazo I. Pathway Studio - TShe analysis and navigation of molecular networks. Bioinformatics. 2003;19:2155-2157.
Ochoa D, Karim M, Ghoussaini M, Hulcoop DG, McDonagh E, Dunham I. Human genetics evidence supports two-thirds of the 2021 FDA-approved drugs. Nat Rev Drug Discov. 2022;21:551.
Pandey M, Mukhopadhyay A, Sharawat SK, Kumar S. Role of microRNAs in regulating cell proliferation, metastasis and chemoresistance and their applications as cancer biomarkers in small cell lung cancer. Biochimica et Biophysica Acta (BBA)-Reviews on Cancer. 2021;1876(1):188552.
Putcha G, Liu TY, Ariazi E, Bertin M, Drake A, Dzamba M, et al. Blood-based detection of early-stage colorectal cancer using multiomics and machine learning. In Abstract presented at: the American Society of Clinical Oncology (ASCO) GI Symposium 2020:23-25.
Que SJ, Chen QY, Zhong Q, Liu ZY, Wang JB, Lin JX, et al. Application of preoperative artificial neural network based on blood biomarkers and clinicopathological parameters for predicting long-term survival of patients with gastric cancer. World J Gastroenterol. 2019;25(43):6451-6464.
Razavi F, Tarokh MJ, Alborzi M. An intelligent Alzheimer’s disease diagnosis method using unsupervised feature learning. J Big Data. 2019;6:32.
Ridker PM, Rifai N, Rose L, Buring JE, Cook NR. Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events. N Engl J Med. 2002;347(20):1557-1565.
Rong S, Bao-wen Z. The research of regression model in machine learning field. MATEC Web of Conferences. 2018;176:01033.
Rustici G, Kolesnikov N, Brandizi M, Burdett T, Dylag M, Emam I, et al. ArrayExpress update--trends in database growth and links to data analysis tools. Nucleic Acids Res. 2012;41:D987-D990.
Rychkov D, Neely J, Oskotsky T, Yu S, Perlmutter N, Nititham J, et al. Cross-Tissue Transcriptomic Analysis Leveraging Machine Learning Approaches Identifies New Biomarkers for Rheumatoid Arthritis. Front Immunol. 2021;12:638066.
Saha S, Nassisi M, Wang M, Lindenberg S, Kanagasingam Y, Sadda S, et al. Automated detection and classification of early AMD biomarkers using deep learning. Scientific Reports. 2019;9(1):10990.
Saltz LB, Cox JV, Blanke CD, Rosen LS, Hecht JR, Fehrenbacher L, et al. Irinotecan plus fluorouracil and leucovorin for metastatic colorectal cancer. N Engl J Med. 2000;343(7):905-914.
Shao Z, Wang K, Zhang S, Yuan J, Liao X, et al. Ingenuity pathway analysis of differentially expressed genes involved in signaling pathways and molecular networks in RhoE gene-edited cardiomyocytes. Int J Mol Med. 2020;46(3):1225-1238.
Silverman GM, Sahoo HS, Ingraham NE, Lupei M, Puskarich MA, Usher M et al. NLP methods for extraction of symptoms from unstructured data for use in prognostic COVID-19 analytic models. J Artificial Intelligence Res. 2021;72:429-474.
Singhal A, Cowie MR. The role of wearables in heart failure. Curr Heart Failure Rep. 2020 Aug;17(4):125-132.
Smirnov KS, Maier TV, Walker A, Heinzmann SS, Forcisi S, Martinez I, et al. Challenges of metabolomics in human gut microbiota research. Int J Med Microbiol. 2016;306(5):266-79.
Smith CA, O’Maille G, Want EJ, Chuan Q, Sunia TA, Theodore BR, et al. METLIN: A metabolite mass spectral database. Ther Drug Monit. 2005;27:747-751.
Sonawane AR, Weiss ST, Glass K, Sharma A. Network Medicine in the Age of Biomedical Big Data. Front Genet. 2019;10.
Song Y, Kang K, Kim I, Kim T-J. Pathological Digital Biomarkers: Validation and Application. Appl Sci. 2022;12(19):9823.
Subbiah V. The next generation of evidence-based medicine. Nat Med. 2023;29(1):49-58.
Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005;102(27):15545-50.
Takeuchi T, Hattori-Kato M, Okuno Y, Iwai S, Mikami K. Prediction of prostate cancer by deep learning with multilayer artificial neural network. Can Urol Assoc J. 2019;13(5):E145.
Tang S, Yuan K, Chen L. Molecular biomarkers, network biomarkers, and dynamic network biomarkers for diagnosis and prediction of rare diseases. Fundam Res. 2022;2(6):894-902.
Tomczak K, Czerwińska P, Wiznerowicz M. Review The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge. Contemporary Oncology/Współczesna Onkologia, 2015;(1):68-77.
Tung NM, Garber JE. BRCA1/2 testing: therapeutic implications for breast cancer management. Br J Cancer. 2018;119(2):141-152.
van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C et al. Ten years of next-generation sequencing technology. Trends Genet. 2014;30:418-26.
van Engelen JE, Hoos HH. A survey on semi-supervised learning. Mach Learn. 2020;109:373-440.
Wacker C, Prkno A, Brunkhorst FM, Schlattmann P. Procalcitonin as a diagnostic marker for sepsis: a systematic review and meta-analysis. Lancet Infect Dis. 2013;13(5):426-35.
Wai CT, Greenson JK, Fontana RJ, Kalbfleisch JD, Marrero JA, Conjeevaram HS, et al. A simple noninvasive index can predict both significant fibrosis and cirrhosis in patients with chronic hepatitis C. Hepatology. 2003;37(1):40-6.
Wang YY, Sun YP, Luo YM, Peng DH, Li X, Yang BY, et al. Biomarkers for the Clinical Diagnosis of Alzheimer’s Disease: Metabolomics Analysis of Brain Tissue and Blood. Front Pharmacol. 2021;12.
Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, et al. HMDB 3.0-The human metabolome database in 2013. Nucleic Acids Res. 2013;41(D1):D801-7.
Yang N, Kaur S, Volinia S, Greshock J, Lassus H, Hasegawa H, et al. MicroRNA microarray identifies Let-7i as a novel biomarker and therapeutic target in human epithelial ovarian cancer. Cancer Res. 2008;68(24):10307-14.
Zare A, Postovit LM, Githaka JM. Robust inflammatory breast cancer gene signature using nonparametric random forest analysis. Breast Cancer Res. 2021;23(1):92.
Zeng T, Zhang W, Yu X, Liu X, Li M, Chen L. Big-data-based edge biomarkers: study on dynamical drug sensitivity and resistance in individuals. Brief Bioinform. 2016;17(4):576-592.
Zhang C, Zeng P, Tan J, Sun S, Zhao M, Cui J, et al. Relationship of problematic smartphone use, sleep quality, and daytime fatigue among quarantined medical students during the COVID-19 pandemic. Front Psychiatry. 2021a;12:755059.
Zhang R, Liu S, Jin H, Luo Y, Zheng Z, Gao F, et al. Noninvasive Electromagnetic Wave Sensing of Glucose. Sensors. 2019;19(5):1151.
Zhang W, Lin L, Xia L, Cai W, Dai W, Zou C, et al. Multi-omics analyses of human colorectal cancer revealed three mitochondrial genes potentially associated with poor outcomes of patients. J Transl Med. 2021a;19:273.
Zhou W, Dong J, Zhang Y, Sun X, Wang H, Zhang X, et al. Lymphocyte-to-monocyte ratio as a prognostic biomarker in various types of cancer: a systematic review and meta-analysis. Oncotarget. 2016;7(6):6479-88.
Downloads
Published
Issue
Section
License
Copyright (c) 2023 Brazilian Journal of Pharmaceutical Sciences
This work is licensed under a Creative Commons Attribution 4.0 International License.
All content of the journal, except where identified, is licensed under a Creative Commons attribution-type BY.
The on-line journal has open and free access.
