Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis

Christina Vasilopoulou; Stephanie Duguez; William Duddy; Tadashi Kaname

doi:10.3390/jpm12111932

Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis

Christina Vasilopoulou
, Stephanie Duguez
, William Duddy
, Tadashi Kaname (Editor)

Research output: Contribution to journal › Review article › peer-review

2 Citations (Scopus)

59 Downloads (Pure)

Abstract

The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.

Original language	English
Article number	1932
Number of pages	17
Journal	Journal of Personalized Medicine
Volume	12
Issue number	11
Early online date	20 Nov 2022
DOIs	https://doi.org/10.3390/jpm12111932
Publication status	Published online - 20 Nov 2022

Bibliographical note

Funding: This work was financed by the European Union Regional Development Fund (ERDF) EU Sustainable Competitiveness Programme for N. Ireland, Northern Ireland Public Health Agency (HSC R&D) & Ulster University. C.V. was the recipient of a DfE international scholarship from Ulster University

Funding

Funding: This work was financed by the European Union Regional Development Fund (ERDF) EU Sustainable Competitiveness Programme for N. Ireland, Northern Ireland Public Health Agency (HSC R&D) & Ulster University. C.V. was the recipient of a DfE international scholarship from Ulster University

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

amyotrophic lateral sclerosis
genome-wide association studies
ALS pathology
gene-set analysis
functional genomics
Genome-wide Association Studies
Gene-set Analysis
Amyotrophic Lateral Sclerosis
Als Pathology
Functional genomics

Access to Document

10.3390/jpm12111932Licence: CC BY

jpm-12-01932-v2.pdfFinal published version, 601 KBLicence: CC BY

A software pipeline for the analysis of genomic data, and functional genomic approaches to explore the molecular mechanisms of amyotrophic lateral sclerosis
Vasilopoulou, C. (Author), Shukla, P. (Supervisor), Duddy, W. (Supervisor) & Duguez, S. (Supervisor), Oct 2022
Student thesis: Doctoral Thesis

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Cite this

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title = "Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis",

abstract = "The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.",

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author = "Christina Vasilopoulou and Stephanie Duguez and William Duddy and Tadashi Kaname",

note = "Funding: This work was financed by the European Union Regional Development Fund (ERDF) EU Sustainable Competitiveness Programme for N. Ireland, Northern Ireland Public Health Agency (HSC R\&D) \& Ulster University. C.V. was the recipient of a DfE international scholarship from Ulster University",

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N1 - Funding: This work was financed by the European Union Regional Development Fund (ERDF) EU Sustainable Competitiveness Programme for N. Ireland, Northern Ireland Public Health Agency (HSC R&D) & Ulster University. C.V. was the recipient of a DfE international scholarship from Ulster University

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N2 - The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.

AB - The rapid increase in the number of genetic variants identified to be associated with Amyotrophic Lateral Sclerosis (ALS) through genome-wide association studies (GWAS) has created an emerging need to understand the functional pathways that are implicated in the pathology of ALS. Gene-set analysis (GSA) is a powerful method that can provide insight into the associated biological pathways, determining the joint effect of multiple genetic markers. The main contribution of this review is the collection of ALS GSA studies that employ GWAS or individual-based genotype data, investigating their methodology and results related to ALS-associated molecular pathways. Furthermore, the limitations in standard single-gene analyses are summarized, highlighting the power of gene-set analysis, and a brief overview of the statistical properties of gene-set analysis and related concepts is provided. The main aims of this review are to investigate the reproducibility of the collected studies and identify their strengths and limitations, in order to enhance the experimental design and therefore the quality of the results of future studies, deepening our understanding of this devastating disease.

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KW - Genome-wide Association Studies

KW - Gene-set Analysis

KW - Amyotrophic Lateral Sclerosis

KW - Als Pathology

KW - Functional genomics

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DO - 10.3390/jpm12111932

M3 - Review article

C2 - 36422108

SN - 2075-4426

VL - 12

JO - Journal of Personalized Medicine

JF - Journal of Personalized Medicine

IS - 11

M1 - 1932

ER -

Genome-Wide Gene-Set Analysis Approaches in Amyotrophic Lateral Sclerosis

Abstract

Bibliographical note

Funding

UN SDGs

Keywords

Access to Document

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Student theses

A software pipeline for the analysis of genomic data, and functional genomic approaches to explore the molecular mechanisms of amyotrophic lateral sclerosis

Cite this