Weighted gene co-expression based biomarker discovery for psoriasis detection

Sundarrajan, Sudharsana; Arumugam, Mohanapriya

doi:10.1016/j.gene.2016.08.021

Cited by 27 publications

(31 citation statements)

References 42 publications

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“…Transcripts were combined into a single network, which was divided into modules of highly correlated genes by weighted gene co-expression analysis (WGCNA) [25, 55]. WGCNA is an established method for module detection within gene co-expression networks and has been previously applied in biomarker development [48]. WGCNA analysis revealed 82 network modules of between 35 and 515 transcripts (Additional file 1: Figure S3, Additional file 2: Table S1).…”

Section: Resultsmentioning

confidence: 99%

“…Data-driven methods employing transcriptomics have successfully identified biomarkers in other clinically and genetically heterogeneous disease states, including breast and gastric cancers, psoriasis and progressive supranuclear palsy [26, 43, 48, 54]. To achieve a similar goal we planned an approach with a discovery phase followed by a biomarker phase.…”

Section: Introductionmentioning

confidence: 99%

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A data-driven approach links microglia to pathology and prognosis in amyotrophic lateral sclerosis

Cooper‐Knock

Green

Altschuler

et al. 2017

acta neuropathol commun

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Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disease that lacks a predictive and broadly applicable biomarker. Continued focus on mutation-specific upstream mechanisms has yet to predict disease progression in the clinic. Utilising cellular pathology common to the majority of ALS patients, we implemented an objective transcriptome-driven approach to develop noninvasive prognostic biomarkers for disease progression. Genes expressed in laser captured motor neurons in direct correlation (Spearman rank correlation, p < 0.01) with counts of neuropathology were developed into co-expression network modules. Screening modules using three gene sets representing rate of disease progression and upstream genetic association with ALS led to the prioritisation of a single module enriched for immune response to motor neuron degeneration. Genes in the network module are important for microglial activation and predict disease progression in genetically heterogeneous ALS cohorts: Expression of three genes in peripheral lymphocytes - LILRA2, ITGB2 and CEBPD – differentiate patients with rapid and slowly progressive disease, suggesting promise as a blood-derived biomarker. TREM2 is a member of the network module and the level of soluble TREM2 protein in cerebrospinal fluid is shown to predict survival when measured in late stage disease (Spearman rank correlation, p = 0.01). Our data-driven systems approach has, for the first time, directly linked microglia to the development of motor neuron pathology. LILRA2, ITGB2 and CEBPD represent peripherally accessible candidate biomarkers and TREM2 provides a broadly applicable therapeutic target for ALS.Electronic supplementary materialThe online version of this article (doi:10.1186/s40478-017-0424-x) contains supplementary material, which is available to authorized users.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A data-driven approach links microglia to pathology and prognosis in amyotrophic lateral sclerosis

Cooper‐Knock

Green

Altschuler

et al. 2017

acta neuropathol commun

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“…Though many genes have been found be involved in SLE, but the gene networks associated with the etiology of SLE has not been clearly defined. WGCNA is an excellent bioinformatics tool to gain deepening insights into the aberrantly changes of genome‐wide gene expressions occurring in diseases at a systems level, which have been widely used to explore the molecular mechanisms of various diseases including autoimmune diseases (Riquelme Medina & Lubovac‐Pilav, ; Sundarrajan & Arumugam, ; Teitsma et al, ). In this study, the expressions of 632 SLE associated genes obtained from the RRA analysis were used in the WGCNA analysis, and they were classified into 11 coexpression biologically functional modules (Figure b), which highlighted some new insights into the pathogenesis of SLE at a systems level.…”

Section: Discussionmentioning

confidence: 99%

Key genes and functional coexpression modules involved in the pathogenesis of systemic lupus erythematosus

Yan

Wang

Gao

et al. 2018

Journal Cellular Physiology

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We performed a systematic review of genome-wide gene expression datasets to identify key genes and functional modules involved in the pathogenesis of systemic lupus erythematosus (SLE) at a systems level. Genome-wide gene expression datasets involving SLE patients were searched in Gene Expression Omnibus and ArrayExpress databases. Robust rank aggregation (RRA) analysis was used to integrate those public datasets and identify key genes associated with SLE. The weighted gene coexpression network analysis (WGCNA) was adapted to identify functional modules involved in SLE pathogenesis, and the gene ontology enrichment analysis was utilized to explore their functions. The aberrant expressions of several randomly selected key genes were further validated in SLE patients through quantitative real-time polymerase chain reaction. Fifteen genome-wide gene expression datasets were finally included, which involved a total of 1,778 SLE patients and 408 healthy controls. A large number of significantly upregulated or downregulated genes were identified through RRA analysis, and some of those genes were novel SLE gene signatures and their molecular roles in etiology of SLE remained vague. WGCNA further successfully identified six main functional modules involved in the pathogenesis of SLE. The most important functional module involved in SLE included 182 genes and mainly enriched in biological processes, including defense response to virus, interferon signaling pathway, and cytokine-mediated signaling pathway. This study identifies a number of key genes and functional coexpression modules involved in SLE, which provides deepening insights into the molecular mechanism of SLE at a systems level and also provides some promising therapeutic targets.

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“…Within the 11 702 studies identified from the search strategy no clinical examination‐based diagnostic criteria for psoriasis in adults or children were found. Only 23 studies met the inclusion criteria; they presented a broad range of diagnostic criteria including genetic, molecular, dermoscopy, confocal microscopy, histopathology, questionnaire‐based, computer‐aided and traditional Chinese medicine criteria (Table S1; see Supporting Information). Sixteen studies were of a case–control design, five studies were case series, one study was cross‐sectional and one study was a Delphi consensus study.…”

Section: Resultsmentioning

confidence: 99%

“…Seven studies were of a case–control design and one was a cross‐sectional study. Sensitivity and specificity results of the criteria were presented or available on request for five studies; the sensitivity values ranged from 65·6% to 98% and specificity from 58·2% to 100% . Diagnostic accuracy results were often reported as area under the curve, and three studies reported a value ≥0·7 .…”

Section: Resultsmentioning

confidence: 99%

A systematic review of diagnostic criteria for psoriasis in adults and children: evidence from studies with a primary aim to develop or validate diagnostic criteria

et al. 2018

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Weighted gene co-expression based biomarker discovery for psoriasis detection

Cited by 27 publications

References 42 publications

A data-driven approach links microglia to pathology and prognosis in amyotrophic lateral sclerosis

A data-driven approach links microglia to pathology and prognosis in amyotrophic lateral sclerosis

Key genes and functional coexpression modules involved in the pathogenesis of systemic lupus erythematosus

A systematic review of diagnostic criteria for psoriasis in adults and children: evidence from studies with a primary aim to develop or validate diagnostic criteria

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