Serum MicroRNAs As Biomarkers For Early Diagnosis Of Alzheimer’s Disease

Background and objectiveAlzheimer’s disease(AD)is the most common form of dementia.This disease not only seriously endangers the physical and mental health of the elderly,but also brings a heavy social and economical burdens.AD is a progressive neurodegeneration,which is characterized by progressive memory decline,cognitive impairment,and altered behavior.The main pathological changes are the accumulation of amyloid-P(Aβ)plaques and the formation of neurofibrillary tangle(NFT).The clinical diagnosis of AD is based on medical history,clinical examination,neuropsychological testing,imaging examination and laboratory assessments.However,these methods have not yet proved sensitive and specific enough for the definitive diagnosis of AD,especially at the early stages of the disease.Therefore,there is an urgent need for reliable biomarkers for the early diagnosis of AD.microRNAs(miRNAs)are highly conserved small non-coding RNAs that regulate gene expression at the posttranscriptional level.Previous studies have found that miRNAs abundantly expressed in the central nervous system,showed a high degree of temporal and spatial specificity and were mainly involved in neuronal formation,differentiation and synaptic plasticity.Furthermore,some studies indicated that the microvesicles containing miRNAs can be released into peripheral blood through the blood-brain barrier.Serum is an appealing source of biomarkers due to its easy collection with minimal discomfort to the patient,encouraging greater compliance in clinical trials and frequent testing.Therefore,serum miRNAs have the potential to be used as biomarkers for the early detect of AD.Recently,with the development of high-throughput next-generation sequencing(NGS),researchers are able to analyze miRNAs of serum in a genome-wide scale for the discovery of AD biomarkers.However,there were no NGS studies on miRNAs screens for biomarkers to monitor the progression of AD,particularly at its early stages.Therefore,the primary aim of this study is to investigate whether serum miRNAs of AD patients can be used as diagnostic biomarkers,particularly in its presymptomatic and early stage,and monitor the progression of disease.We obtained the miRNA profiles of human serum by using the NGS approach from three groups of AD(mild,moderate,and severe AD)and healthy controls(HC).After validation of quantitative Real-time PCR(qRT-PCR)results in the larger cohort of participants,9 miRNAs that showed an association with the clinical stages of AD were relevant to use as biomarkers for the early diagnosis of AD.Methods1.The clinical diagnosis of Alzheimer’s disease(AD)fulfilled the criteria set by the National Institute of Neurological and the Communicative Diseases and Stroke-Alzheimer’s Disease and Related Disorders Association(NINCDS-ADRDA).According to Mini-Mental State Examination(MMSE)and the Clinical Dementia Rating(CDR),we divided the participants into four groups.The serum was collected within 2 hours after blood was isolated from patients,the serum samples hemolyzed were removed.2.Serum samples from 28 participants(9 controls,6 mild,7 moderate,and 6 severe AD cases)were selected for NGS.The dataset of NGS was normalized and removed adapter dimers,junk,common RNA families(rRNA,tRNA,snRNA,snoRNA)and repeats.Unique sequences were mapped in miRBase 21.0 to identify known miRNAs and novel miRNAs.In order to find AD progression-dependent serum miRNAs,we compared the miRNA expression levels of four groups(HC,mild AD,moderate AD,and severe AD)by using ANOVA with Bonferroni’s post-hoc test for multiple comparison.3.The differentially expressed candidate miRNAs were validated using qRT-PCR on a larger cohort of serum samples from 207 participants(86 controls,31 mild,52 moderate,and 38 severe AD cases)were selected for NGS.The fold change of deregulated miRNA was calculated by the equation 2-△△Ct.Compared the expression analysis results(fold changes)obtained by NGS and qRT-PCR.We analyzed the potential correlation between the levels of serum miRNAs and MMSE score.We established the combined miRNAs by the binary logistic regression model,and evaluated the diagnostic performance of each miRNAs and the combined miRNAs by the area under the receiver operating characteristic(ROC)curve(AUC).The miRNA expression levels of four groups(HC,mild AD,moderate AD,and severe AD)were compared using ANOVA with Bonferroni’s post-hoc test for multiple comparison.To facilitate the prediction of the miRNA target gene,Gene Ontology(GO)analysis were assembled.A network of miRNAs and mRNAs of target genes is presented.Results1.Base on the results of ANOVA,we selected 13 miRNAs with altered expression(Table 2),which were differential expression in comparison between all groups.Among the 13 miRNAs,6 miRNAs(hsa-miR-26a-5p,hsa-miR-181c-3p,hsa-miR-584,hsa-miR-126-5p,hsa-miR-22-3p,hsa-miR-148b-5p)were down-regulated and 7 miRNA(hsa-miR-221-3p,hsa-miR-106b-3p,hsa-miRNA-144-5p,hsa-miR-6119-5p,hsa-miR-1388-3p,hsa-miR-1246,hsa-miR-660-5p)were up-regulated.2.The 13 candidate miRNAs were validated using qRT-PCR on a larger cohort of serum samples.Comparison of the expression analysis results obtained by NGS and qRT-PCR,revealed that 9 miRNAs had a similar differential expression pattern.3.The ROC curve analysis highlighted remaining 9-miRNA signatures as potential biomarkers for AD diagnosis.The area under the ROC curve(AUC)was between 70.0%and 85.3%.Hsa-miR-22-3p has the best sensitivity(81.8%)and specificity(70.9%).4.We established the miR-panel(hsa-miR-26a-5p/hsa-miR-181 c-3p/hsa-miR-22-3p/hsa-miR-148b-5p/hsa-miR-106b-3p/hsa-miR-6119-5p/hsa-miR-660-5p)by the binary logistic regression model.The miR-panel showed higher accuracy of AUC(98.6%),higher sensitivity(81.8%),and higher specificity(70.9%).5.We analyzed the potential correlation between the levels of 9 serum miRNAs and MMSE score.The results of Pearson correlation analysis showed that 5 miRNAs(hsa-miR-26a-5p,hsa-miR-181 c-3p,hsa-miR-126-5p,hsa-miR-22-3p,hsa-miR-148b-5p)were positively correlated to MMSE score and 4 miRNAs(hsa-miR-106b-3p,hsa-miR-6119-5p,hsa-miR-1246,hsa-miR-660-5p)were negatively correlated to MMSE score.6.The miRNA expression levels of four groups(HC,mild AD,moderate AD,and severe AD)were compared using ANOVA with Bonferroni’s post-hoc test for multiple comparison.The results of ANOVA showed that the 9 miRNAs were all differential expression in comparison between all groups,and the results of Bonferroni’s post-hoc test showed that the 9 miRNAs have obvious difference among mild AD,moderate AD,severe AD and HC.7.To identify the possible mechanisms and genes targeted by the 9 miRNAs,we predicted the target genes ascertained from the Gene Ontology database.We identified significant enrichment of miRNA targets in GO categories associated with nervous system development and neuronal cell body.A total of 135 target gene transcripts were identified for the 9 miRNAs identified in GO category of nervous system development.A total of 40 target gene transcripts were identified for the 8 miRNAs identified in GO category of neuronal cell body.ConclusionIn this study,we report 9 serum miRNAs(hsa-miR-26a-5p,hsa-miR-181c-3p,hsa-miR-126-5p,hsa-miR-22-3p,hsa-miR-148b-5p,hsa-miR-106b-3p,hsa-miR-6119-5p,hsa-miR-1246 and the hsa-miR-660-5p)that showed an association with the clinical stages of AD were relevant to use as biomarkers for the early diagnosis of AD.A possible future direction could be building a miRNA library from serum samples of AD patients,and combining these serum miRNA signatures with other clinical detection methods to establish a more comprehensive patient’s diagnosis and treatment strategy,should these novel findings help establishing new AD prognosis strategies with increased efficacy.