Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study.
The biological pathways involved in amyotrophic lateral sclerosis (ALS) remain elusive and diagnostic decision-making can be challenging. Gene expression studies are valuable in overcoming such challenges since they can shed light on differentially regulated pathways and may ultimately identify valu...
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doaj-b3e99309fc2a4f96ac6fbd36980e6fab2020-11-25T01:24:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032018-01-01136e019887410.1371/journal.pone.0198874Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study.Wouter van RheenenFrank P DiekstraOliver HarschnitzHenk-Jan WestenengKristel R van EijkChristiaan G J SarisEwout J N GroenMichael A van EsHylke M BlauwPaul W J van VughtJan H VeldinkLeonard H van den BergThe biological pathways involved in amyotrophic lateral sclerosis (ALS) remain elusive and diagnostic decision-making can be challenging. Gene expression studies are valuable in overcoming such challenges since they can shed light on differentially regulated pathways and may ultimately identify valuable biomarkers. This two-stage transcriptome-wide study, including 397 ALS patients and 645 control subjects, identified 2,943 differentially expressed transcripts predominantly involved in RNA binding and intracellular transport. When batch effects between the two stages were overcome, three different models (support vector machines, nearest shrunken centroids, and LASSO) discriminated ALS patients from control subjects in the validation stage with high accuracy. The models' accuracy reduced considerably when discriminating ALS from diseases that mimic ALS clinically (N = 75), nor could it predict survival. We here show that whole blood transcriptome profiles are able to reveal biological processes involved in ALS. Also, this study shows that using these profiles to differentiate between ALS and mimic syndromes will be challenging, even when taking batch effects in transcriptome data into account.http://europepmc.org/articles/PMC6016933?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wouter van Rheenen Frank P Diekstra Oliver Harschnitz Henk-Jan Westeneng Kristel R van Eijk Christiaan G J Saris Ewout J N Groen Michael A van Es Hylke M Blauw Paul W J van Vught Jan H Veldink Leonard H van den Berg |
spellingShingle |
Wouter van Rheenen Frank P Diekstra Oliver Harschnitz Henk-Jan Westeneng Kristel R van Eijk Christiaan G J Saris Ewout J N Groen Michael A van Es Hylke M Blauw Paul W J van Vught Jan H Veldink Leonard H van den Berg Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study. PLoS ONE |
author_facet |
Wouter van Rheenen Frank P Diekstra Oliver Harschnitz Henk-Jan Westeneng Kristel R van Eijk Christiaan G J Saris Ewout J N Groen Michael A van Es Hylke M Blauw Paul W J van Vught Jan H Veldink Leonard H van den Berg |
author_sort |
Wouter van Rheenen |
title |
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study. |
title_short |
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study. |
title_full |
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study. |
title_fullStr |
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study. |
title_full_unstemmed |
Whole blood transcriptome analysis in amyotrophic lateral sclerosis: A biomarker study. |
title_sort |
whole blood transcriptome analysis in amyotrophic lateral sclerosis: a biomarker study. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2018-01-01 |
description |
The biological pathways involved in amyotrophic lateral sclerosis (ALS) remain elusive and diagnostic decision-making can be challenging. Gene expression studies are valuable in overcoming such challenges since they can shed light on differentially regulated pathways and may ultimately identify valuable biomarkers. This two-stage transcriptome-wide study, including 397 ALS patients and 645 control subjects, identified 2,943 differentially expressed transcripts predominantly involved in RNA binding and intracellular transport. When batch effects between the two stages were overcome, three different models (support vector machines, nearest shrunken centroids, and LASSO) discriminated ALS patients from control subjects in the validation stage with high accuracy. The models' accuracy reduced considerably when discriminating ALS from diseases that mimic ALS clinically (N = 75), nor could it predict survival. We here show that whole blood transcriptome profiles are able to reveal biological processes involved in ALS. Also, this study shows that using these profiles to differentiate between ALS and mimic syndromes will be challenging, even when taking batch effects in transcriptome data into account. |
url |
http://europepmc.org/articles/PMC6016933?pdf=render |
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