Diagnostic value of miRNAs for Alzheimer’s disease: a meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

LIU Jing , WANG Xueli ,  HAN Xu

Geriatric Department, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, P. R. China;

Corresponding author：

HAN Xu, Email: hanxu9998@126.com

Keywords：

Alzheimer’s disease; miRNA; Diagnosis; Meta-analysis

DOI：

10.7507/1672-2531.202112070

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

Objective To systematically review the diagnostic value of miRNAs for Alzheimer’s disease (AD).Methods PubMed, Web of Science, EMbase, The Cochrane Library, CNKI, WanFang Data, VIP, and CBM databases were electronically searched to collect diagnostic tests of miRNAs for AD from inception to October 31, 2020. Two researchers independently screened literature, extracted data, and assessed the risk of bias of the included studies. RevMan 5.3 and Stata 14.0 software were used for meta-analysis. Results A total of 22 studies involving 4 006 subjects were included. The meta-analysis results showed that the pooled sensitivity, specificity, positive and negative likelihood ratios, diagnostic odds ratio, and the areas under the working characteristic curve of miRNA in AD diagnosis were 0.83 (95%CI 0.79 to 0.87), 0.80 (95%CI 0.76 to 0.83), 4.07 (95%CI 3.37 to 4.92), 0.21 (95%CI 0.17 to 0.27), 19.20 (95%CI 12.96 to 28.48) and 0.88 (95%CI 0.85 to 0.90), respectively. Conclusion The current evidence shows that miRNAs have a high diagnostic value for AD. However, because of the limited quality and quantity of the included studies, more high-quality studies are required to verify the above conclusion.

Citation： LIU Jing, WANG Xueli, HAN Xu. Diagnostic value of miRNAs for Alzheimer’s disease: a meta-analysis. Chinese Journal of Evidence-Based Medicine, 2022, 22(5): 537-543. doi: 10.7507/1672-2531.202112070 Copy

1.	Gauthier S, Rosa-Neto P, Morais JA, et al. World Alzheimer Report 2021: journey through the diagnosis of dementia. London: Alzheimer’s Disease International, 2021.
2.	Zetterberg H, Burnham SC. Blood-based molecular biomarkers for Alzheimer's disease. Mol Brain, 2019, 12(1): 26.
3.	Chen L, Heikkinen L, Wang C, et al. Trends in the development of miRNA bioinformatics tools. Brief Bioinform, 2019, 20(5): 1836-1852.
4.	Ferrante M, Conti GO. Environment and neurodegenerative diseases: an update on miRNA role. Microrna, 2017, 6(3): 157-165.
5.	Mishra S, Yadav T, Rani V. Exploring miRNA based approaches in cancer diagnostics and therapeutics. Crit Rev Oncol Hematol, 2016, 98: 12-23.
6.	Swarbrick S, Wragg N, Ghosh S, et al. Systematic review of miRNA as biomarkers in Alzheimer's disease. Mol Neurobiol, 2019, 56(9): 6156-6167.
7.	Cardoso AL, Guedes JR. Quantifying miRNA deregulation in Alzheimer's disease. Methods Mol Biol, 2018, 1750: 307-319.
8.	Jaber VR, Zhao Y, Sharfman NM, et al. Addressing Alzheimer's disease (AD) neuropathology using anti-microRNA (AM) strategies. Mol Neurobiol, 2019, 56(12): 8101-8108.
9.	Zhao Y, Pogue AI, Lukiw WJ. MicroRNA (miRNA) signaling in the human CNS in sporadic Alzheimer's disease (AD)-novel and unique pathological features. Int J Mol Sci, 2015, 16(12): 30105-30116.
10.	McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement, 2011, 7(3): 263-269.
11.	McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of department of health and human services task force on Alzheimer's disease. Neurology, 1984, 34(7): 939-944.
12.	Yang B, Mallett S, Takwoingi Y, et al. QUADAS-C: a tool for assessing risk of bias in comparative diagnostic accuracy studies. Ann Intern Med, 2021, 174(11): 1592-1599.
13.	邬兰, 张永, 曾宪涛. QUADAS-2在诊断准确性研究的质量评价工具中的应用. 湖北医药学院学报, 2013, 32(3): 201-208.
14.	Cao F, Liu Z, Sun G. Diagnostic value of miR-193a-3p in Alzheimer's disease and miR-193a-3p attenuates amyloid-β induced neurotoxicity by targeting PTEN. Exp Gerontol, 2020, 130: 110814.
15.	Cheng L, Doecke JD, Sharples RA, et al. Prognostic serum miRNA biomarkers associated with Alzheimer's disease shows concordance with neuropsychological and neuroimaging assessment. Mol Psychiatry, 2015, 20(10): 1188-1196.
16.	Cosín-Tomás M, Antonell A, Lladó A, et al. Plasma miR-34a-5p and miR-545-3p as early biomarkers of Alzheimer's disease: potential and limitations. Mol Neurobiol, 2017, 54(7): 5550-5562.
17.	Giuliani A, Gaetani S, Sorgentoni G, et al. Circulating inflamma-miRs as potential biomarkers of cognitive impairment in patients affected by Alzheimer’s disease. Front Aging Neuro Sci, 2021, 13: 647015.
18.	Guo R, Fan G, Zhang J, et al. A 9-microRNA signature in serum serves as a noninvasive biomarker in early diagnosis of Alzheimer’s disease. J Alzheimers Dis, 2017, 60(4): 1365-1377.
19.	Huang P, Xu M, He YX. MicroRNA-146a regulates the expression of the A beta (1-42) protein in Alzheimer's disease. Eur Rev Med Pharmacol Sci, 2021, 25(4): 2003-2012.
20.	Müller M, Jäkel L, Bruinsma IB, et al. MicroRNA-29a is a candidate biomarker for Alzheimer’s disease in cell-free cerebrospinal fluid. Mol Neurobiol, 2016, 53(5): 2894-2899.
21.	Nagaraj S, Laskowska-Kaszub K, Dębski KJ, et al. Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer's disease patients from non-demented subjects. Oncotarget, 2017, 8(10): 16122-16143.
22.	Tan L, Yu JT, Liu QY, et al. Circulating miR-125b as a biomarker of Alzheimer's disease. J Neurol Sci, 2014, 336(1-2): 52-56.
23.	Tan L, Yu JT, Tan MS, et al. Genome-wide serum microRNA expression profiling identifies serum biomarkers for Alzheimer's disease. J Alzheimers Dis, 2014, 40(4): 1017-1027.
24.	Yang TT, Liu CG, Gao SC, et al. The serum exosome derived microRNA-135a, -193b, and -384 were potential Alzheimer’s disease biomarkers. Biomed Environ Sci, 2018, 31(2): 87-96.
25.	Xie B, Liu Z, Jiang L, et al. Increased serum miR-206 level predicts conversion from amnestic mild cognitive impairment to Alzheimer’s disease: a 5-year follow-up study. J Alzheimers Dis, 2017, 55(2): 509-520.
26.	Zhang M, Han W, Xu Y, et al. Serum miR-128 serves as a potential diagnostic biomarker for Alzheimer’s disease. Neuropsychiatr Dis Treat, 2021, 17: 269-275.
27.	Zirnheld AL, Shetty V, Chertkow H, et al. Distinguishing mild cognitive impairment from Alzheimer's disease by increased expression of key circulating microRNAs. Current Neurobiol, 2016, 7(2): 38-50.
28.	李容英. 血清外泌体microRNA在阿尔茨海默病中的表达差异性研究. 太原: 山西医科大学, 2021.
29.	刘春兴, 万瑛, 高永辉, 等. 阿尔茨海默病患者血浆微小RNA-18a表达及与白细胞介素6的关系. 中华老年心脑血管病杂志, 2021, 23(3): 289-292.
30.	马腾, 孙学华, 孙顺昌, 等. 外周全血miR-29a/101在阿尔茨海默病中诊断价值的研究. 中华行为医学与脑科学杂志, 2016, 25(11): 1010-1014.
31.	潘晓峰, 刘文娟. 痴呆患者血清miR-9, miR-34c表达变化及意义. 山东医药, 2019, 59(25): 13-17.
32.	肖建廷, 于杨, 谭兰, 等. 阿尔茨海默病患者血清miR-9水平变化及意义. 山东医药, 2014, (38): 8-10.
33.	于明, 钱胜男, 徐宇浩, 等. 血清miR-711, miR-203对阿尔茨海默病的诊断效能评估. 医学研究杂志, 2020, 49(5): 136-140.
34.	张蕾, 邹旺辉, 李欢. 老年痴呆患者血清miR-9, M-CSF及Hcy水平变化及其意义. 实验与检验医学, 2020, 38(3): 547-549.
35.	张群, 侯莉芳, 钟月红, 等. MiR-320a作为阿尔茨海默氏病的诊断生物标志物对β淀粉样蛋白诱导的神经毒性具有保护作用. 临床医学进展, 2021, 11(2): 646-654.
36.	Hane FT, Robinson M, Lee BY, et al. Recent progress in Alzheimer’s disease research, part 3: diagnosis and treatment. J Alzheimers Dis, 2017, 57(3): 645-665.
37.	Eratne D, Loi SM, Farrand S, et al. Alzheimer's disease: clinical update on epidemiology, pathophysiology and diagnosis. Australas Psychiatry, 2018, 26(4): 347-357.
38.	Silvestro S, Bramanti P, Mazzon E. Role of miRNAs in Alzheimer's disease and possible fields of application. Int J Mol Sci, 2019, 20(16): 3979.
39.	曾宪涛, 何明武. 诊断准确性试验Meta分析软件一本通. 北京: 军事医学科学出版, 2014.
40.	Zhang WT, Zhang GX, Gao SS. The potential diagnostic accuracy of circulating microRNAs for Alzheimer's disease: a meta-analysis. Neurologia (Engl Ed), 2021, S0213-4853(21): 00103-1.

1. Gauthier S, Rosa-Neto P, Morais JA, et al. World Alzheimer Report 2021: journey through the diagnosis of dementia. London: Alzheimer’s Disease International, 2021.
2. Zetterberg H, Burnham SC. Blood-based molecular biomarkers for Alzheimer's disease. Mol Brain, 2019, 12(1): 26.
3. Chen L, Heikkinen L, Wang C, et al. Trends in the development of miRNA bioinformatics tools. Brief Bioinform, 2019, 20(5): 1836-1852.
4. Ferrante M, Conti GO. Environment and neurodegenerative diseases: an update on miRNA role. Microrna, 2017, 6(3): 157-165.
5. Mishra S, Yadav T, Rani V. Exploring miRNA based approaches in cancer diagnostics and therapeutics. Crit Rev Oncol Hematol, 2016, 98: 12-23.
6. Swarbrick S, Wragg N, Ghosh S, et al. Systematic review of miRNA as biomarkers in Alzheimer's disease. Mol Neurobiol, 2019, 56(9): 6156-6167.
7. Cardoso AL, Guedes JR. Quantifying miRNA deregulation in Alzheimer's disease. Methods Mol Biol, 2018, 1750: 307-319.
8. Jaber VR, Zhao Y, Sharfman NM, et al. Addressing Alzheimer's disease (AD) neuropathology using anti-microRNA (AM) strategies. Mol Neurobiol, 2019, 56(12): 8101-8108.
9. Zhao Y, Pogue AI, Lukiw WJ. MicroRNA (miRNA) signaling in the human CNS in sporadic Alzheimer's disease (AD)-novel and unique pathological features. Int J Mol Sci, 2015, 16(12): 30105-30116.
10. McKhann GM, Knopman DS, Chertkow H, et al. The diagnosis of dementia due to Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement, 2011, 7(3): 263-269.
11. McKhann G, Drachman D, Folstein M, et al. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of department of health and human services task force on Alzheimer's disease. Neurology, 1984, 34(7): 939-944.
12. Yang B, Mallett S, Takwoingi Y, et al. QUADAS-C: a tool for assessing risk of bias in comparative diagnostic accuracy studies. Ann Intern Med, 2021, 174(11): 1592-1599.
13. 邬兰, 张永, 曾宪涛. QUADAS-2在诊断准确性研究的质量评价工具中的应用. 湖北医药学院学报, 2013, 32(3): 201-208.
14. Cao F, Liu Z, Sun G. Diagnostic value of miR-193a-3p in Alzheimer's disease and miR-193a-3p attenuates amyloid-β induced neurotoxicity by targeting PTEN. Exp Gerontol, 2020, 130: 110814.
15. Cheng L, Doecke JD, Sharples RA, et al. Prognostic serum miRNA biomarkers associated with Alzheimer's disease shows concordance with neuropsychological and neuroimaging assessment. Mol Psychiatry, 2015, 20(10): 1188-1196.
16. Cosín-Tomás M, Antonell A, Lladó A, et al. Plasma miR-34a-5p and miR-545-3p as early biomarkers of Alzheimer's disease: potential and limitations. Mol Neurobiol, 2017, 54(7): 5550-5562.
17. Giuliani A, Gaetani S, Sorgentoni G, et al. Circulating inflamma-miRs as potential biomarkers of cognitive impairment in patients affected by Alzheimer’s disease. Front Aging Neuro Sci, 2021, 13: 647015.
18. Guo R, Fan G, Zhang J, et al. A 9-microRNA signature in serum serves as a noninvasive biomarker in early diagnosis of Alzheimer’s disease. J Alzheimers Dis, 2017, 60(4): 1365-1377.
19. Huang P, Xu M, He YX. MicroRNA-146a regulates the expression of the A beta (1-42) protein in Alzheimer's disease. Eur Rev Med Pharmacol Sci, 2021, 25(4): 2003-2012.
20. Müller M, Jäkel L, Bruinsma IB, et al. MicroRNA-29a is a candidate biomarker for Alzheimer’s disease in cell-free cerebrospinal fluid. Mol Neurobiol, 2016, 53(5): 2894-2899.
21. Nagaraj S, Laskowska-Kaszub K, Dębski KJ, et al. Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer's disease patients from non-demented subjects. Oncotarget, 2017, 8(10): 16122-16143.
22. Tan L, Yu JT, Liu QY, et al. Circulating miR-125b as a biomarker of Alzheimer's disease. J Neurol Sci, 2014, 336(1-2): 52-56.
23. Tan L, Yu JT, Tan MS, et al. Genome-wide serum microRNA expression profiling identifies serum biomarkers for Alzheimer's disease. J Alzheimers Dis, 2014, 40(4): 1017-1027.
24. Yang TT, Liu CG, Gao SC, et al. The serum exosome derived microRNA-135a, -193b, and -384 were potential Alzheimer’s disease biomarkers. Biomed Environ Sci, 2018, 31(2): 87-96.
25. Xie B, Liu Z, Jiang L, et al. Increased serum miR-206 level predicts conversion from amnestic mild cognitive impairment to Alzheimer’s disease: a 5-year follow-up study. J Alzheimers Dis, 2017, 55(2): 509-520.
26. Zhang M, Han W, Xu Y, et al. Serum miR-128 serves as a potential diagnostic biomarker for Alzheimer’s disease. Neuropsychiatr Dis Treat, 2021, 17: 269-275.
27. Zirnheld AL, Shetty V, Chertkow H, et al. Distinguishing mild cognitive impairment from Alzheimer's disease by increased expression of key circulating microRNAs. Current Neurobiol, 2016, 7(2): 38-50.
28. 李容英. 血清外泌体microRNA在阿尔茨海默病中的表达差异性研究. 太原: 山西医科大学, 2021.
29. 刘春兴, 万瑛, 高永辉, 等. 阿尔茨海默病患者血浆微小RNA-18a表达及与白细胞介素6的关系. 中华老年心脑血管病杂志, 2021, 23(3): 289-292.
30. 马腾, 孙学华, 孙顺昌, 等. 外周全血miR-29a/101在阿尔茨海默病中诊断价值的研究. 中华行为医学与脑科学杂志, 2016, 25(11): 1010-1014.
31. 潘晓峰, 刘文娟. 痴呆患者血清miR-9, miR-34c表达变化及意义. 山东医药, 2019, 59(25): 13-17.
32. 肖建廷, 于杨, 谭兰, 等. 阿尔茨海默病患者血清miR-9水平变化及意义. 山东医药, 2014, (38): 8-10.
33. 于明, 钱胜男, 徐宇浩, 等. 血清miR-711, miR-203对阿尔茨海默病的诊断效能评估. 医学研究杂志, 2020, 49(5): 136-140.
34. 张蕾, 邹旺辉, 李欢. 老年痴呆患者血清miR-9, M-CSF及Hcy水平变化及其意义. 实验与检验医学, 2020, 38(3): 547-549.
35. 张群, 侯莉芳, 钟月红, 等. MiR-320a作为阿尔茨海默氏病的诊断生物标志物对β淀粉样蛋白诱导的神经毒性具有保护作用. 临床医学进展, 2021, 11(2): 646-654.
36. Hane FT, Robinson M, Lee BY, et al. Recent progress in Alzheimer’s disease research, part 3: diagnosis and treatment. J Alzheimers Dis, 2017, 57(3): 645-665.
37. Eratne D, Loi SM, Farrand S, et al. Alzheimer's disease: clinical update on epidemiology, pathophysiology and diagnosis. Australas Psychiatry, 2018, 26(4): 347-357.
38. Silvestro S, Bramanti P, Mazzon E. Role of miRNAs in Alzheimer's disease and possible fields of application. Int J Mol Sci, 2019, 20(16): 3979.
39. 曾宪涛, 何明武. 诊断准确性试验Meta分析软件一本通. 北京: 军事医学科学出版, 2014.
40. Zhang WT, Zhang GX, Gao SS. The potential diagnostic accuracy of circulating microRNAs for Alzheimer's disease: a meta-analysis. Neurologia (Engl Ed), 2021, S0213-4853(21): 00103-1.

Chinese Journal of Evidence-Based Medicine

Diagnostic value of miRNAs for Alzheimer’s disease: a meta-analysis

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content