Integrative Omics Analysis for Amyotrophic Lateral Sclerosis Restricted; Files Only

Wang, Shihua (Spring 2019)

Permanent URL: https://etd.library.emory.edu/concern/etds/5999n456x?locale=en
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Abstract

Introduction: Integrative omics analysis is useful for investigating the complex problems of molecular interactions in a biological system. The R package, xMWAS provides an automated workflow for integrative analysis of more than two datasets, differential network analysis, and community detection. In our study, we utilized the integrative omics analysis to explore the etiology and pathophysiology of ALS (amyotrophic lateral sclerosis). 

Method: We applied the xMWAS package to analyze three types of omics data, microbiome, metabolites and cytokines, from 10 ALS patients and 10 control subjects. We conducted integrative omics analysis for all samples and then separately for patients and control subjects. We also generate 500 bootstrap samples from our data and repeated the same analysis to investigate the significant features that are associated with ALS. 

Result: There is one more community of features in ALS compared than control subjects. The communities for ALS patients are clearer and the nodes in the communities are more closely connected. There are some 87 features whose normalized centrality indices differ by more than 0.2 between patient and controls. From the bootstrap samples, we found that there are 12 features whose centrality features are significantly different between patients and control subjects. 

Discussion: Our result about microbiome verifies previous findings in the literature that gut microbiota has a significant association with ALS disease. The centrality change for cytokines can also be explained by an increased level of blood inflammatory cytokines for ALS patients. Future studies can focus on the association between ALS etiology and gut microbiota to address the decrease in centrality. 

Table of Contents

1 Introduction.............3

2 Method.............4

2.1 DataDescription...........................4

2.2 OverviewofxMWAS.........................5

2.2.1 StageI:IntegrativeandAssociationAnalysis........5

2.2.2 StageII:GeneratetheIntegrativeNetworkGraph......6

2.2.3 StageIII:CommunityDetection...............6

2.3 Bootstrapping.............................6

2.4 AnalyzingxMWASOutput......................7

3 Result.............8

3.1 NetworkandClustersofRealData..................8

3.1.1 NetworkVisualization....................8

3.1.2 ClusterAssignmentofPatientsandcontrolsubjects.....10

3.1.3 ComparingtheCentralityofPatientsandcontrolsubjects..11

3.2 ComparingRealDatatoBootstrapSamples.............14

4 Discussion.............17

5 Appendix.............20

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