Performance of Validated MicroRNA Biomarkers for Alzheimer's Disease in Mild Cognitive Impairment.

BACKGROUND Cerebrospinal fluid (CSF) microRNA (miRNA) biomarkers of Alzheimer's disease (AD) have been identified, but have not been evaluated in prodromal AD, including mild cognitive impairment (MCI). OBJECTIVE To assess whether a set of validated AD miRNA biomarkers in CSF are also sensitive to early-stage pathology as exemplified by MCI diagnosis. METHODS We measured the expression of 17 miRNA biomarkers for AD in CSF samples from AD, MCI, and cognitively normal controls (NC). We then examined classification performance of the miRNAs individually and in combination. For each miRNA, we assessed median expression in each diagnostic group and classified markers as trending linearly, nonlinearly, or lacking any trend across the three groups. For trending miRNAs, we assessed multimarker classification performance alone and in combination with apolipoprotein E ɛ4 allele (APOEɛ4) genotype and amyloid-β42 to total tau ratio (Aβ42:T-Tau). We identified predicted targets of trending miRNAs using pathway analysis. RESULTS Five miRNAs showed a linear trend of decreasing median expression across the ordered diagnoses (control to MCI to AD). The trending miRNAs jointly predicted AD with area under the curve (AUC) of 0.770, and MCI with AUC of 0.705. Aβ42:T-Tau alone predicted MCI with AUC of 0.758 and the AUC improved to 0.813 (p = 0.051) after adding the trending miRNAs. Multivariate correlation of the five trending miRNAs with Aβ42:T-Tau was weak. CONCLUSION Selected miRNAs combined with Aβ42:T-Tau improved classification performance (relative to protein biomarkers alone) for MCI, despite a weak correlation with Aβ42:T-Tau. Together these data suggest that that these miRNAs carry novel information relevant to AD, even at the MCI stage. Preliminary target prediction analysis suggests novel roles for these biomarkers.

[1]  Xiaowei Wang,et al.  miRDB: an online database for prediction of functional microRNA targets , 2019, Nucleic Acids Res..

[2]  M. Kim,et al.  A novel kit for early diagnosis of Alzheimer’s disease using a fluorescent nanoparticle imaging , 2019, Scientific Reports.

[3]  S. Kushner,et al.  A functional variant in the miR‐142 promoter modulating its expression and conferring risk of Alzheimer disease , 2019, Human mutation.

[4]  Xiaowei Wang,et al.  Prediction of functional microRNA targets by integrative modeling of microRNA binding and target expression data , 2019, Genome Biology.

[5]  J. Cummings The National Institute on Aging—Alzheimer's Association Framework on Alzheimer's disease: Application to clinical trials , 2018, Alzheimer's & Dementia.

[6]  D. Galasko,et al.  Validation of MicroRNA Biomarkers for Alzheimer's Disease in Human Cerebrospinal Fluid. , 2019, Journal of Alzheimer's disease : JAD.

[7]  R. D'Hooge,et al.  Deregulation of neuronal miRNAs induced by amyloid-β or TAU pathology , 2018, Molecular Neurodegeneration.

[8]  M. Buffelli,et al.  Rac1 activation links tau hyperphosphorylation and Aβ dysmetabolism in Alzheimer’s disease , 2018, Acta Neuropathologica Communications.

[9]  H. Vanderstichele,et al.  Relevance of Aβ42/40 Ratio for Detection of Alzheimer Disease Pathology in Clinical Routine: The PLMR Scale , 2018, Front. Aging Neurosci..

[10]  B. Miller,et al.  MicroRNA Expression Levels Are Altered in the Cerebrospinal Fluid of Patients with Young-Onset Alzheimer’s Disease , 2018, Molecular Neurobiology.

[11]  H. Heidbuchel,et al.  MicroRNA profiling in plasma samples using qPCR arrays: Recommendations for correct analysis and interpretation , 2018, PloS one.

[12]  P. Reddy,et al.  MicroRNA-455-3p as a Potential Biomarker for Alzheimer's Disease: An Update , 2018, Front. Aging Neurosci..

[13]  Ronald C. Petersen,et al.  Practice guideline update summary: Mild cognitive impairment , 2018, Neurology.

[14]  Hsien-Da Huang,et al.  miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions , 2017, Nucleic Acids Res..

[15]  Tian Wang,et al.  Cerebrospinal fluid CD4+ T lymphocyte-derived miRNA-let-7b can enhances the diagnostic performance of Alzheimer's disease biomarkers. , 2018, Biochemical and biophysical research communications.

[16]  Q. Lu,et al.  Rho GTPases as therapeutic targets in Alzheimer’s disease , 2017, Alzheimer's Research & Therapy.

[17]  P. Reddy,et al.  MicroRNA-455-3p as a potential peripheral biomarker for Alzheimer’s disease , 2017, Human molecular genetics.

[18]  Chun Zhou,et al.  Lower Serum Levels of miR-29c-3p and miR-19b-3p as Biomarkers for Alzheimer's Disease. , 2017, The Tohoku journal of experimental medicine.

[19]  N. Lemke,et al.  Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses , 2017, Front. Genet..

[20]  J. Kuźnicki,et al.  Profile of 6 microRNA in blood plasma distinguish early stage Alzheimer’s disease patients from non-demented subjects , 2017, Oncotarget.

[21]  Julie A Saugstad,et al.  MicroRNAs in Human Cerebrospinal Fluid as Biomarkers for Alzheimer's Disease. , 2016, Journal of Alzheimer's disease : JAD.

[22]  P. Reddy,et al.  MicroRNAs as Peripheral Biomarkers in Aging and Age-Related Diseases. , 2017, Progress in molecular biology and translational science.

[23]  Juan Fortea,et al.  Plasma miR-34a-5p and miR-545-3p as Early Biomarkers of Alzheimer’s Disease: Potential and Limitations , 2017, Molecular Neurobiology.

[24]  J. Satoh,et al.  Plasma microRNA biomarker detection for mild cognitive impairment using differential correlation analysis , 2016, Biomarker Research.

[25]  Wen-Juan Ni,et al.  Dynamic miRNA–mRNA paradigms: New faces of miRNAs , 2015, Biochemistry and biophysics reports.

[26]  Lukasz A. Kurgan,et al.  Comprehensive overview and assessment of computational prediction of microRNA targets in animals , 2015, Briefings Bioinform..

[27]  D. Bartel,et al.  Predicting effective microRNA target sites in mammalian mRNAs , 2015, eLife.

[28]  Christine S. Siegismund,et al.  MicroRNA Profiling of CSF Reveals Potential Biomarkers to Detect Alzheimer`s Disease , 2015, PloS one.

[29]  D. Wong,et al.  Extracellular RNAs: development as biomarkers of human disease , 2015, Journal of extracellular vesicles.

[30]  Hiroyuki Arai,et al.  MicroRNAs in plasma and cerebrospinal fluid as potential markers for Alzheimer's disease. , 2014, Journal of Alzheimer's disease : JAD.

[31]  H. Arrighi,et al.  Rate of Conversion from Prodromal Alzheimer's Disease to Alzheimer's Dementia: A Systematic Review of the Literature , 2013, Dementia and Geriatric Cognitive Disorders Extra.

[32]  W. Lukiw,et al.  microRNA (miRNA) speciation in Alzheimer's disease (AD) cerebrospinal fluid (CSF) and extracellular fluid (ECF). , 2012, International journal of biochemistry and molecular biology.

[33]  David D Shin,et al.  Effect of Mild Cognitive Impairment and APOE Genotype on Resting Cerebral Blood Flow and its Association with Cognition , 2012, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[34]  Giuliano Binetti,et al.  Cerebrospinal Fluid Biomarkers for Alzheimer’s Disease: The Present and the Future , 2011, Neurodegenerative Diseases.

[35]  Min Liu,et al.  MicroRNA‐142‐3p, a new regulator of RAC1, suppresses the migration and invasion of hepatocellular carcinoma cells , 2011, FEBS letters.

[36]  Nick C Fox,et al.  The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[37]  J. Morris,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 , 2011, Alzheimer's & Dementia.

[38]  Denise C. Park,et al.  Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease , 2011, Alzheimer's & Dementia.

[39]  Yu Wang,et al.  Cerebrospinal fluid biomarkers for Parkinson disease diagnosis and progression , 2011, Annals of neurology.

[40]  A. Mitchell,et al.  Rate of progression of mild cognitive impairment to dementia – meta‐analysis of 41 robust inception cohort studies , 2009, Acta psychiatrica Scandinavica.

[41]  D. Bartel MicroRNAs: Target Recognition and Regulatory Functions , 2009, Cell.

[42]  J. H. Boo,et al.  Rac1 changes the substrate specificity of gamma-secretase between amyloid precursor protein and Notch1. , 2008, Biochemical and biophysical research communications.

[43]  A. Roses,et al.  Identification of miRNA Changes in Alzheimer's Disease Brain and CSF Yields Putative Biomarkers and Insights into Disease Pathways , 2008 .

[44]  C. Burge,et al.  Conserved Seed Pairing, Often Flanked by Adenosines, Indicates that Thousands of Human Genes are MicroRNA Targets , 2005, Cell.

[45]  D. Bennett,et al.  Subicular dendritic arborization in Alzheimer's disease correlates with neurofibrillary tangle density. , 2003, The American journal of pathology.

[46]  M. Pepe The Statistical Evaluation of Medical Tests for Classification and Prediction , 2003 .

[47]  D. Drachman,et al.  Apolipoprotein E ε4 allele and the lifetime risk of Alzheimer's disease : what physicians know, and what they should know , 1995 .

[48]  Anthony S. Bryk,et al.  Hierarchical Linear Models: Applications and Data Analysis Methods , 1992 .

[49]  D. T. Vernier,et al.  Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. , 1990, Journal of lipid research.

[50]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease , 1984, Neurology.

[51]  M. Folstein,et al.  The Mini-Mental State Examination. , 1983, Archives of general psychiatry.