Plasma exosomal miRNAs in persons with and without Alzheimer disease: Altered expression and prospects for biomarkers

Giovanni Lugli, Aaron Cohen, David A. Bennett, Raj C. Shah, Christopher J. Fields, Alvaro G. Hernandez, Neil R. Smalheiser

Research output: Contribution to journalArticle

103 Citations (Scopus)

Abstract

To assess the value of exosomal miRNAs as biomarkers for Alzheimer disease (AD), the expression of microRNAs was measured in a plasma fraction enriched in exosomes by differential centrifugation, using Illumina deep sequencing. Samples from 35 persons with a clinical diagnosis of AD dementia were compared to 35 age and sex matched controls. Although these samples contained less than 0.1 microgram of total RNA, deep sequencing gave reliable and informative results. Twenty miRNAs showed significant differences in the AD group in initial screening (miR-23b-3p, miR-24-3p, miR-29b-3p, miR-125b-5p, miR-138-5p, miR-139-5p, miR-141-3p, miR-150-5p, miR-152-3p, miR-185-5p, miR-338-3p, miR- 342-3p, miR-342-5p, miR-548at-5p, miR-659-5p, miR-3065-5p, miR-3613-3p, miR-3916, miR-4772-3p, miR-5001-3p), many of which satisfied additional biological and statistical criteria, and among which a panel of seven miRNAs were highly informative in a machine learning model for predicting AD status of individual samples with 83-89% accuracy. This performance is not due to over-fitting, because a) we used separate samples for training and testing, and b) similar performance was achieved when tested on technical replicate data. Perhaps the most interesting single miRNA was miR-342-3p, which was a) expressed in the AD group at about 60% of control levels, b) highly correlated with several of the other miRNAs that were significantly down-regulated in AD, and c) was also reported to be downregulated in AD in two previous studies. The findings warrant replication and follow-up with a larger cohort of patients and controls who have been carefully characterized in terms of cognitive and imaging data, other biomarkers (e.g., CSF amyloid and tau levels) and risk factors (e.g., apoE4 status), and who are sampled repeatedly over time. Integrating miRNA expression data with other data is likely to provide informative and robust biomarkers in Alzheimer disease.

Original languageEnglish (US)
Article numbere0139233
JournalPLoS One
Volume10
Issue number10
DOIs
StatePublished - Oct 1 2015

Fingerprint

Biomarkers
Alzheimer disease
MicroRNAs
biomarkers
Alzheimer Disease
Plasmas
microRNA
High-Throughput Nucleotide Sequencing
exosomes
Apolipoprotein E4
sampling
Exosomes
RNA Sequence Analysis
Centrifugation
dementia
artificial intelligence
Level control
amyloid
Amyloid
centrifugation

ASJC Scopus subject areas

  • Agricultural and Biological Sciences(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Medicine(all)

Cite this

Lugli, G., Cohen, A., Bennett, D. A., Shah, R. C., Fields, C. J., Hernandez, A. G., & Smalheiser, N. R. (2015). Plasma exosomal miRNAs in persons with and without Alzheimer disease: Altered expression and prospects for biomarkers. PLoS One, 10(10), [e0139233]. https://doi.org/10.1371/journal.pone.0139233

Plasma exosomal miRNAs in persons with and without Alzheimer disease : Altered expression and prospects for biomarkers. / Lugli, Giovanni; Cohen, Aaron; Bennett, David A.; Shah, Raj C.; Fields, Christopher J.; Hernandez, Alvaro G.; Smalheiser, Neil R.

In: PLoS One, Vol. 10, No. 10, e0139233, 01.10.2015.

Research output: Contribution to journalArticle

Lugli, Giovanni ; Cohen, Aaron ; Bennett, David A. ; Shah, Raj C. ; Fields, Christopher J. ; Hernandez, Alvaro G. ; Smalheiser, Neil R. / Plasma exosomal miRNAs in persons with and without Alzheimer disease : Altered expression and prospects for biomarkers. In: PLoS One. 2015 ; Vol. 10, No. 10.
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abstract = "To assess the value of exosomal miRNAs as biomarkers for Alzheimer disease (AD), the expression of microRNAs was measured in a plasma fraction enriched in exosomes by differential centrifugation, using Illumina deep sequencing. Samples from 35 persons with a clinical diagnosis of AD dementia were compared to 35 age and sex matched controls. Although these samples contained less than 0.1 microgram of total RNA, deep sequencing gave reliable and informative results. Twenty miRNAs showed significant differences in the AD group in initial screening (miR-23b-3p, miR-24-3p, miR-29b-3p, miR-125b-5p, miR-138-5p, miR-139-5p, miR-141-3p, miR-150-5p, miR-152-3p, miR-185-5p, miR-338-3p, miR- 342-3p, miR-342-5p, miR-548at-5p, miR-659-5p, miR-3065-5p, miR-3613-3p, miR-3916, miR-4772-3p, miR-5001-3p), many of which satisfied additional biological and statistical criteria, and among which a panel of seven miRNAs were highly informative in a machine learning model for predicting AD status of individual samples with 83-89{\%} accuracy. This performance is not due to over-fitting, because a) we used separate samples for training and testing, and b) similar performance was achieved when tested on technical replicate data. Perhaps the most interesting single miRNA was miR-342-3p, which was a) expressed in the AD group at about 60{\%} of control levels, b) highly correlated with several of the other miRNAs that were significantly down-regulated in AD, and c) was also reported to be downregulated in AD in two previous studies. The findings warrant replication and follow-up with a larger cohort of patients and controls who have been carefully characterized in terms of cognitive and imaging data, other biomarkers (e.g., CSF amyloid and tau levels) and risk factors (e.g., apoE4 status), and who are sampled repeatedly over time. Integrating miRNA expression data with other data is likely to provide informative and robust biomarkers in Alzheimer disease.",
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