Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale

Neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations...

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Main Authors: Nicolas Ruffini, Susanne Klingenberg, Susann Schweiger, Susanne Gerber
Format: Article
Language:English
Published: MDPI AG 2020-12-01
Series:Cells
Subjects:
Online Access:https://www.mdpi.com/2073-4409/9/12/2642
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spelling doaj-ff447e5ca4bc42ba971cc91d1b72ecd92020-12-09T00:04:52ZengMDPI AGCells2073-44092020-12-0192642264210.3390/cells9122642Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics ScaleNicolas Ruffini0Susanne Klingenberg1Susann Schweiger2Susanne Gerber3Institute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, GermanyInstitute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, GermanyInstitute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, GermanyInstitute for Human Genetics, University Medical Center, Johannes Gutenberg University, 55131 Mainz, GermanyNeurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.https://www.mdpi.com/2073-4409/9/12/2642multi-omicsAlzheimer’s diseaseParkinson’s diseaseHuntington’s diseaseamyotrophic lateral sclerosisneurodegeneration
collection DOAJ
language English
format Article
sources DOAJ
author Nicolas Ruffini
Susanne Klingenberg
Susann Schweiger
Susanne Gerber
spellingShingle Nicolas Ruffini
Susanne Klingenberg
Susann Schweiger
Susanne Gerber
Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
Cells
multi-omics
Alzheimer’s disease
Parkinson’s disease
Huntington’s disease
amyotrophic lateral sclerosis
neurodegeneration
author_facet Nicolas Ruffini
Susanne Klingenberg
Susann Schweiger
Susanne Gerber
author_sort Nicolas Ruffini
title Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
title_short Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
title_full Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
title_fullStr Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
title_full_unstemmed Common Factors in Neurodegeneration: A Meta-Study Revealing Shared Patterns on a Multi-Omics Scale
title_sort common factors in neurodegeneration: a meta-study revealing shared patterns on a multi-omics scale
publisher MDPI AG
series Cells
issn 2073-4409
publishDate 2020-12-01
description Neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS) are heterogeneous, progressive diseases with frequently overlapping symptoms characterized by a loss of neurons. Studies have suggested relations between neurodegenerative diseases for many years (e.g., regarding the aggregation of toxic proteins or triggering endogenous cell death pathways). We gathered publicly available genomic, transcriptomic, and proteomic data from 177 studies and more than one million patients to detect shared genetic patterns between the neurodegenerative diseases on three analyzed omics-layers. The results show a remarkably high number of shared differentially expressed genes between the transcriptomic and proteomic levels for all conditions, while showing a significant relation between genomic and proteomic data between AD and PD and AD and ALS. We identified a set of 139 genes being differentially expressed in several transcriptomic experiments of all four diseases. These 139 genes showed overrepresented gene ontology (GO) Terms involved in the development of neurodegeneration, such as response to heat and hypoxia, positive regulation of cytokines and angiogenesis, and RNA catabolic process. Furthermore, the four analyzed neurodegenerative diseases (NDDs) were clustered by their mean direction of regulation throughout all transcriptomic studies for this set of 139 genes, with the closest relation regarding this common gene set seen between AD and HD. GO-Term and pathway analysis of the proteomic overlap led to biological processes (BPs), related to protein folding and humoral immune response. Taken together, we could confirm the existence of many relations between Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis on transcriptomic and proteomic levels by analyzing the pathways and GO-Terms arising in these intersections. The significance of the connection and the striking relation of the results to processes leading to neurodegeneration between the transcriptomic and proteomic data for all four analyzed neurodegenerative diseases showed that exploring many studies simultaneously, including multiple omics-layers of different neurodegenerative diseases simultaneously, holds new relevant insights that do not emerge from analyzing these data separately. Furthermore, the results shed light on processes like the humoral immune response that have previously been described only for certain diseases. Our data therefore suggest human patients with neurodegenerative diseases should be addressed as complex biological systems by integrating multiple underlying data sources.
topic multi-omics
Alzheimer’s disease
Parkinson’s disease
Huntington’s disease
amyotrophic lateral sclerosis
neurodegeneration
url https://www.mdpi.com/2073-4409/9/12/2642
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