International Journal of Molecular Medical Science, 2025, Vol.15, No.5, 205-213 http://medscipublisher.com/index.php/ijmms 211 The lack of a unified detection standard, coupled with the poor results of repeated research, remain the main problems that prevent the widespread use of AD biomarkers in clinical practice. Factors such as the methods of sample processing, the detection techniques used, and the different populations may all affect the accuracy and stability of marker measurements. Therefore, it is necessary to set uniform technical rules in different practical scenarios and conduct sufficient verification. At the same time, it is also necessary to address core challenges such as cost, availability of equipment, and related ethical issues (such as the notification and communication of test results) to ensure that this technology can be used fairly and effectively in clinical practice. Combining biomarker information from multiple aspects such as body fluids, imaging, genetics and digital health with artificial intelligence and machine learning technologies is expected to further enhance the accuracy of AD screening and management. Such integrated methods help achieve more comprehensive risk stratification, early identification and dynamic disease monitoring, thereby laying the foundation for individualized prevention and precise intervention, and ultimately improving the treatment effect of patients and rationally allocating AD medical resources. Acknowledgments The author extends sincere thanks to Dr Luo for his feedback on the manuscript. Conflict of Interest Disclosure The author affirms that this research was conducted without any commercial or financial relationships that could be construed as a potential conflict of interest. References AlMansoori M., Jemimah S., Abuhantash F., and AlShehhi A., 2024, Predicting early Alzheimer’s with blood biomarkers and clinical features, Scientific Reports, 14(1): 6039. https://doi.org/10.1038/s41598-024-56489-1 Altomare D., Stampacchia S., Ribaldi F., Tomczyk S., Chevalier C., Poulain G., Asadi S., Bancila B., Marizzoni M., Martins M., Lathuilière A., Scheffler M., Ashton N., Zetterberg H., Blennow K., Kern I., Frias M., Garibotto V., and Frisoni G., 2023, Plasma biomarkers for Alzheimer’s disease: a field-test in a memory clinic, Journal of Neurology Neurosurgery and Psychiatry, 94: 420-427. https://doi.org/10.1136/jnnp-2022-330619 Arafah A., Khatoon S., Rasool I., Khan A., Rather M., Abujabal K., Faqih Y., Rashid H., Rashid S., Ahmad S., Alexiou A., and Rehman M., 2023, The future of precision medicine in the cure of Alzheimer’s disease, Biomedicines, 11(2): 335. https://doi.org/10.3390/biomedicines11020335 Arslan B., Zetterberg H., and Ashton N., 2024, Blood-based biomarkers in Alzheimer’s disease-moving towards a new era of diagnostics, Clinical Chemistry and Laboratory Medicine, 62: 1063-1069. https://doi.org/10.1515/cclm-2023-1434 Ashton N., Janelidze S., Mattsson-Carlgren N., Binette A., Strandberg O., Brum W., Karikari T., González-Ortiz F., Di Molfetta G., Meda F., Jonaitis E., Koscik R., Cody K., Betthauser T., Li Y., Vanmechelen E., Palmqvist S., Stomrud E., Bateman R., Zetterberg H., Johnson S., Blennow K., and Hansson O., 2022, Differential roles of Aβ42/40 p-tau231 and p-tau217 for Alzheimer’s trial selection and disease monitoring, Nature Medicine, 28: 2555-2562. https://doi.org/10.1038/s41591-022-02074-w Bhalala O., Watson R., and Yassi N., 2024, Multi-omic blood biomarkers as dynamic risk predictors in late-onset Alzheimer’s disease, International Journal of Molecular Sciences, 25(2): 1231. https://doi.org/10.3390/ijms25021231 Blennow K., and Zetterberg H., 2018, Biomarkers for Alzheimer's disease: current status and prospects for the future, Journal of Internal Medicine, 284 643-663. https://doi.org/10.1111/joim.12816 Bouteloup V., Pellegrin I., Dubois B., Chêne G., Planche V., and Dufouil C., 2024, Explaining the variability of Alzheimer disease fluid biomarker concentrations in memory clinic patients without dementia, Neurology, 102(8): e209219. https://doi.org/10.1212/wnl.0000000000209219 Chae H., Kim H., Kim Y., Ji H., Oh E., and Yang D., 2025, Diagnostic performance of eight blood-based biomarkers in a well-characterized Korean cohort of preclinical Alzheimer’s disease, Annals of Laboratory Medicine, 45: 428-436. https://doi.org/10.3343/alm.2024.0498 Chang C., Lin C., and Lane H., 2021, Machine learning and novel biomarkers for the diagnosis of Alzheimer’s disease, International Journal of Molecular Sciences, 22(5): 2761. https://doi.org/10.3390/ijms22052761
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