Weighted gene co-expression network analysis of the peripheral blood from Amyotrophic Lateral Sclerosis patients

Abstract

Background: Amyotrophic Lateral Sclerosis (ALS) is a lethal disorder characterized by progressive degeneration of motor neurons in the brain and spinal cord. Diagnosis is mainly based on clinical symptoms, and there is currently no therapy to stop the disease or slow its progression. Since access to spinal cord tissue is not possible at disease onset, we investigated changes in gene expression profiles in whole blood of ALS patients.

Results: Our transcriptional study showed dramatic changes in blood of ALS patients; 2,300 probes (9.4%) showed significant differential expression in a discovery dataset consisting of 30 ALS patients and 30 healthy controls. Weighted gene co-expression network analysis (WGCNA) was used to find disease-related networks (modules) and disease related hub genes. Two large co-expression modules were found to be associated with ALS. Our findings were replicated in a second (30 patients and 30 controls) and third dataset (63 patients and 63 controls), thereby demonstrating a highly significant and consistent association of two large co-expression modules with ALS disease status. Ingenuity Pathway Analysis of the ALS related module genes implicates enrichment of functional categories related to genetic disorders, neurodegeneration of the nervous system and inflammatory disease. The ALS related modules contain a number of candidate genes possibly involved in pathogenesis of ALS.

Conclusion: This first large-scale blood gene expression study in ALS observed distinct patterns between cases and controls which may provide opportunities for biomarker development as well as new insights into the molecular mechanisms of the disease.

Figure 1

Gene co-expression modules in human whole blood. Detection of gene co-expression modules in human whole blood datasets comprised of ALS patients and matched controls. (a) Branches of the cluster dendrogram of the most connected genes gave rise to five gene coexpression modules (Blue, Green, Red, Turquoise and Yellow). Genes that could not be clustered into one of these modules were assigned to the Grey module. Every gene represents a line in the hierarchical cluster. Distance between two genes is shown as height on the y-axis. (b) Boxplots showing gene significance per module. Module significance was calculated by taking the average of the absolute t statistics of all genes within a module. The Blue and Yellow module were the only modules that were significant at a Bonferroni corrected significance threshold of 0.05/5 in all 3 datasets.

Figure 2

Scatterplots showing strong preservation of gene significance across the three independent datasets. The scatterplots include the network genes colored by their module assignment in dataset 1. t-test statistic value for dataset 1 (x-axis) was compared to the t statistic value for dataset 2 (y-axis A) and dataset 3 (y-axis B). Genes that are highly differentially expressed in dataset 1 also tend to be differentially expressed in datasets 2 and 3. Note that Blue genes tend to be over-expressed in ALS patients while yellow genes tend to be under-expressed.

Figure 3

Network of hub genes in the Yellow module colored by gene ontology functional information. Hub genes are connected by an edge if the correlation between their expression profiles is significant.

Figure 4

Network of hub genes in the Blue module colored by gene ontology functional information. Hub genes are connected by an edge if the correlation between their expression profiles is significant.