Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson’s disease: a comparison of 33 human and animal studies

Oerton, Erin

doi:10.1186/s12883-017-0838-x

Cited by 32 publications

(24 citation statements)

References 53 publications

(76 reference statements)

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“…the substantia nigra, have identified several molecular mechanisms underlying PD pathology, including synaptic vesicle endocytosis 9–11 . However, post-mortem human brain tissue of well-characterized PD patients and controls is scarce, usually focuses on a select number of brain regions, and have a limited coverage of patients with different Braak LB stages, resulting in low concordance of findings across different studies 12 .…”

Section: Introductionmentioning

confidence: 99%

Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease

Keo

Mahfouz

Ingrassia

et al. 2019

Preprint

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25The molecular mechanisms underlying the caudal-to-rostral progression of Lewy body pathology in 26Parkinson's disease (PD) remain poorly understood. Here, we aimed to unravel transcriptomic signatures 27 across brain regions involved in Braak Lewy body stages in non-neurological controls and PD donors. 28Using human postmortem brain datasets of non-neurological adults from the Allen Human Brain Atlas, we 29 identified expression patterns related to PD progression, including genes found in PD genome-wide 30 associations studies: SNCA, ZNF184, BAP1, SH3GL2, ELOVL7, and SCARB2. We confirmed these 31 patterns in two datasets of non-neurological subjects (Genotype-Tissue Expression project and UK Brain 32 Expression Consortium) and found altered patterns in two datasets of PD patients. Additionally, co-33 expression analysis across vulnerable regions identified two modules associated with dopamine 34 synthesis, the motor and immune system, blood-oxygen transport, and contained microglial and 35 endothelial cell markers, respectively. Alterations in genes underlying these region-specific functions may 36 contribute to the selective regional vulnerability in PD brains. 37 38 3 Background 39 Parkinson's disease (PD) is characterized by a temporal caudal-rostral progression of Lewy body (LB) 40 pathology across a selected set of nuclei in the brain 1 . The distribution pattern of LB pathology is divided 41 into six Braak stages based on accumulation of the protein α-synucleinthe main component of LBs and 42 Lewy neuritesin the brainstem, limbic and neocortical regions 1 . Different hypotheses have been 43 brought forward to explain the evolving LB pathology across the brain, including: retrograde transport of 44 pathological α-synuclein via neuroanatomical networks, α-synuclein's prion-like behavior, and cell-or 45 region-autonomous factors 2,3 . Yet, the mechanisms underlying the selective vulnerability of brain regions 46 to LB pathology remains poorly understood, limiting the ability to diagnose and treat PD. 47 Multiplications of the SNCA gene encoding α-synuclein are relatively common in autosomal dominant PD 48and SNCA dosage has been linked to the severity of PD 4,5 . For other PD-associated variants, e.g. GBA 49and LRRK2, their role in progressive α-synuclein accumulation is less clear, although they have been 50 associated with mitochondrial (dys)function and/or protein degradation pathways [6][7][8] . On the other hand, 51 transcriptomic changes between PD and non-neurological controls of selected brain regions, e.g. the 52 substantia nigra, have identified several molecular mechanisms underlying PD pathology, including 53 synaptic vesicle endocytosis [9][10][11] . However, post-mortem human brain tissue of well-characterized PD 54 patients and controls is scarce, usually focuses on a select number of brain regions, and have a limited 55 coverage of patients with different Braak LB stages, resulting in low concordance of findings across 56 different studies 12 . 57Spatial gene expression patterns in the human ...

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Section: Introductionmentioning

confidence: 99%

Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease

Keo

Mahfouz

Ingrassia

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…On the other hand, transcriptomic changes between PD patients and non-neurological controls of selected brain regions, e.g., the substantia nigra, have identified several molecular mechanisms underlying PD pathology, including synaptic vesicle endocytosis [9][10][11] . However, postmortem human brain tissue of well-characterized PD patients and controls is scarce, usually focuses on a select number of brain regions, and have a limited coverage of patients with different Braak LB stages, resulting in low concordance of findings across different studies 12 .…”

mentioning

confidence: 99%

Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease

et al. 2020

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The molecular mechanisms underlying caudal-to-rostral progression of Lewy body pathology in Parkinson's disease remain poorly understood. Here, we identified transcriptomic signatures across brain regions involved in Braak Lewy body stages in non-neurological adults from the Allen Human Brain Atlas. Among the genes that are indicative of regional vulnerability, we found known genetic risk factors for Parkinson's disease: SCARB2, ELOVL7, SH3GL2, SNCA, BAP1, and ZNF184. Results were confirmed in two datasets of nonneurological subjects, while in two datasets of Parkinson's disease patients we found altered expression patterns. Co-expression analysis across vulnerable regions identified a module enriched for genes associated with dopamine synthesis and microglia, and another module related to the immune system, blood-oxygen transport, and endothelial cells. Both were highly expressed in regions involved in the preclinical stages of the disease. Finally, alterations in genes underlying these region-specific functions may contribute to the selective regional vulnerability in Parkinson's disease brains.

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“…Analysing multiple datasets provides generalized information across different studies [37][54]. The cancer field was a pioneer in combining several works [55] [56] and other fields, such as neurodegenerative diseases [57][58] and regulatory genomics have successfully adopted this strategy [59]. The multidimensional approach presented here offers increased power, due to the higher sample size and increased robustness, by highlighting variations in individual studies results [36][60].…”

Section: Discussionmentioning

confidence: 99%

Comparison of multiple transcriptomes exposes unified and divergent features of quiescent and activated skeletal muscle stem cells

Pietrosemoli

Mella

Yennek

et al. 2017

Preprint

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BackgroundSkeletal muscle stem cells (MuSCs) are quiescent in adult mice and can undergo multiple rounds of proliferation and self-renewal following muscle injury. Several labs have profiled transcripts of myogenic cells during developmental and adult myogenesis with the aim of identifying quiescent markers. Here, we focused on the quiescent cell state and generated new transcriptome profiles that include subfractionations of adult MuSC populations, and an artificially induced prenatal quiescent state, to identify core signatures for quiescent and proliferating MuSCs.MethodsComparison of available data offered challenges related to the inherent diversity of datasets and biological conditions. We developed a standardized workflow to homogenize the normalization, filtering, quality control steps for the analysis of gene expression profiles allowing the identification up- and down-regulated genes and the subsequent gene set enrichment analysis. To share the analytical pipeline of this work, we developed Sherpa, an interactive Shiny server that allows multiscale comparisons for extraction of desired gene sets from the analysed datasets. This tool is adaptable to cell populations in other contexts and tissues.ResultsA multiscale analysis comprising eight datasets of quiescent MuSCs had 207 and 542 genes commonly up- and down-regulated, respectively. Shared up-regulated gene sets include an over-representation of the TNFa pathway via NFKb signaling, Il6-Jak-Stat3 signaling, and the apical surface processes, while shared down-regulated gene sets exhibited an over-representation of Myc and E2F targets, and genes associated to the G2M checkpoint and oxidative phosphorylation. However, virtually all datasets contained genes that are associated with activation or cell cycle entry, such as the immediate early stress response genes Fos and Jun. Empirical examination of fixed and isolated MuSCs showed that these and other genes were absent in vivo, but activated during procedural isolation of cells.ConclusionsThrough the systematic comparison and individual analysis of diverse transcriptomic profiles, we identified genes that were consistently differentially expressed among the different datasets and common underlying biological processes key to the quiescent cell state. Our findings provide impetus to define and distinguish transcripts associated with true in vivo quiescence from those that are first responding genes due to disruption of the stem cell niche.

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Concordance analysis of microarray studies identifies representative gene expression changes in Parkinson’s disease: a comparison of 33 human and animal studies

Cited by 32 publications

References 53 publications

Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease

Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease

Transcriptomic signatures of brain regional vulnerability to Parkinson’s disease

Comparison of multiple transcriptomes exposes unified and divergent features of quiescent and activated skeletal muscle stem cells

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