Dataset Information

Intra- and Inter-individual Variability of microRNA Levels in Human Cerebrospinal Fluid: Critical Implications for Biomarker Discovery.

ABSTRACT: MicroRNAs are emerging as promising biomarkers for diagnosis of various diseases. Notably, cerebrospinal fluid (CSF) contains microRNAs that may serve as biomarkers for neurological diseases. However, there has been a lack of consistent findings among CSF microRNAs studies. Although such inconsistent results have been attributed to various technical issues, inherent biological variability has not been adequately considered as a confounding factor. To address this critical gap in our understanding of microRNA variability, we evaluated intra-individual variability of microRNAs by measuring their levels in the CSF from healthy individuals at two time points, 0 and 48?hours. Surprisingly, the levels of most microRNAs were stable between the two time points. This suggests that microRNAs in CSF may be a good resource for the identification of biomarkers. However, the levels of 12 microRNAs (miR-19a-3p, miR-19b-3p, miR-23a-3p, miR-25a-3p, miR-99a-5p, miR-101-3p, miR-125b-5p, miR-130a-3p, miR-194-5p, miR-195-5p, miR-223-3p, and miR-451a) were significantly altered during the 48?hours interval. Importantly, miRNAs with variable expression have been identified as biomarkers in previous studies. Our data strongly suggest that these microRNAs may not be reliable biomarkers given their intrinsic variability even within the same individual. Taken together, our results provide a critical baseline resource for future microRNA biomarker studies.

SUBMITTER: Yoon H

PROVIDER: S-EPMC5629256 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature

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Intra- and Inter-individual Variability of microRNA Levels in Human Cerebrospinal Fluid: Critical Implications for Biomarker Discovery.

Yoon Hyejin H Belmonte Krystal C KC Kasten Tom T Bateman Randall R Kim Jungsu J

Scientific reports 20171005 1

MicroRNAs are emerging as promising biomarkers for diagnosis of various diseases. Notably, cerebrospinal fluid (CSF) contains microRNAs that may serve as biomarkers for neurological diseases. However, there has been a lack of consistent findings among CSF microRNAs studies. Although such inconsistent results have been attributed to various technical issues, inherent biological variability has not been adequately considered as a confounding factor. To address this critical gap in our understandin ...[more]

PMID: 28983117

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Project description:BackgroundBiomarkers are required for pre-symptomatic diagnosis, treatment, and monitoring of neurodegenerative diseases such as Alzheimer's disease. Cerebrospinal fluid (CSF) is a favored source because its proteome reflects the composition of the brain. Ideal biomarkers have low technical and inter-individual variability (subject variance) among control subjects to minimize overlaps between clinical groups. This study evaluates a process of multi-affinity fractionation (MAF) and quantitative label-free liquid chromatography tandem mass spectrometry (LC-MS/MS) for CSF biomarker discovery by (1) identifying reparable sources of technical variability, (2) assessing subject variance and residual technical variability for numerous CSF proteins, and (3) testing its ability to segregate samples on the basis of desired biomarker characteristics.Methods/resultsFourteen aliquots of pooled CSF and two aliquots from six cognitively normal individuals were randomized, enriched for low-abundance proteins by MAF, digested endoproteolytically, randomized again, and analyzed by nano-LC-MS. Nano-LC-MS data were time and m/z aligned across samples for relative peptide quantification. Among 11,433 aligned charge groups, 1360 relatively abundant ones were annotated by MS2, yielding 823 unique peptides. Analyses, including Pearson correlations of annotated LC-MS ion chromatograms, performed for all pairwise sample comparisons, identified several sources of technical variability: i) incomplete MAF and keratins; ii) globally- or segmentally-decreased ion current in isolated LC-MS analyses; and iii) oxidized methionine-containing peptides. Exclusion of these sources yielded 609 peptides representing 81 proteins. Most of these proteins showed very low coefficients of variation (CV<5%) whether they were quantified from the mean of all or only the 2 most-abundant peptides. Unsupervised clustering, using only 24 proteins selected for high subject variance, yielded perfect segregation of pooled and individual samples.ConclusionsQuantitative label-free LC-MS/MS can measure scores of CSF proteins with low technical variability and can segregate samples according to desired criteria. Thus, this technique shows potential for biomarker discovery for neurological diseases.

Project description:BackgroundThe mechanisms behind formation and filling of intracranial arachnoid cysts (AC) are poorly understood. The aim of this study was to evaluate AC fluid by proteomics to gain further knowledge about ACs. Two goals were set: 1) Comparison of AC fluid from individual patients to determine whether or not temporal AC is a homogenous condition; and 2) Evaluate the protein content of a pool of AC fluid from several patients and qualitatively compare this with published protein lists of cerebrospinal fluid (CSF) and plasma.MethodsAC fluid from 15 patients with temporal AC was included in this study. In the AC protein comparison experiment, AC fluid from 14 patients was digested, analyzed by LC-MS/MS using a semi-quantitative label-free approach and the data were compared by principal component analysis (PCA) to gain knowledge of protein homogeneity of AC. In the AC proteome evaluation experiment, AC fluid from 11 patients was pooled, digested, and fractionated by SCX chromatography prior to analysis by LC-MS/MS. Proteins identified were compared to published databases of proteins identified from CSF and plasma. AC fluid proteins not found in these two databases were experimentally searched for in lumbar CSF taken from neurologically-normal patients, by a targeted protein identification approach called MIDAS (Multiple Reaction Monitoring (MRM) initiated detection and sequence analysis).ResultsWe did not identify systematic trends or grouping of data in the AC protein comparison experiment, implying low variability between individual proteomic profiles of AC.In the AC proteome evaluation experiment, we identified 199 proteins. When compared to previously published lists of proteins identified from CSF and plasma, 15 of the AC proteins had not been reported in either of these datasets. By a targeted protein identification approach, we identified 11 of these 15 proteins in pooled CSF from neurologically-normal patients, demonstrating that the majority of abundant proteins in AC fluid also can be found in CSF. Compared to plasma, as many as 104 proteins in AC were not found in the list of 3017 plasma proteins.ConclusionsBased on the protein content of AC fluid, our data indicate that temporal AC is a homogenous condition, pointing towards a similar AC filling mechanism for the 14 patients examined. Most of the proteins identified in AC fluid have been identified in CSF, indicating high similarity in the qualitative protein content of AC to CSF, whereas this was not the case between AC and plasma. This indicates that AC is filled with a liquid similar to CSF. As far as we know, this is the first proteomics study that explores the AC fluid proteome.

Dataset Information

Intra- and Inter-individual Variability of microRNA Levels in Human Cerebrospinal Fluid: Critical Implications for Biomarker Discovery.

Publications

Intra- and Inter-individual Variability of microRNA Levels in Human Cerebrospinal Fluid: Critical Implications for Biomarker Discovery.

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