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

Abstract

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.