Ostrow, L. W. | bioRxiv Science

bioRxiv2019

MetroNome - a visual data exploration platform for integrating human genotypic and phenotypic data across diseases

MetroNome is a web-based visual data exploration platform which integrates de-identified genomic, transcriptomic, and phenotypic data sets. Users can define and compare cohorts constructed from multimodal data and share the data and analyses with outside tools. MetroNomes interactive visualization and analysis tools allow researchers to quickly form and explore novel hypotheses. The deidentified data is linked back to the source biosample inventories in multiple biobanks, enabling researchers to further investigate new ideas using the most relevant samples.

bioinformatics↗

bioRxiv2019

Postmortem Cortex Samples Identify Distinct Molecular Subtypes of ALS: Retrotransposon Activation, Oxidative Stress, and Activated Glia

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease characterized by the progressive loss of motor neurons. While several inherited pathogenic mutations have been identified as causative, the vast majority of cases are sporadic with no family history of disease. Thus, for the majority of ALS cases, a specific causal abnormality is not known and the disease may be a product of multiple inter-related pathways contributing to varying degrees in different ALS patients. Using unsupervised machine learning algorithms, we stratified the transcriptomes of 148 ALS decedent cortex tissue samples into three distinct and robust molecular subtypes. The largest cluster, identified in 61% of patient samples, displayed hallmarks of oxidative and proteotoxic stress. Another 20% of the ALS patient samples exhibited high levels of retrotransposon expression and other signatures of TDP-43 dysfunction. Finally, a third group showed predominant signatures of glial activation (19%). Together these results demonstrate that at least three distinct molecular signatures contribute to ALS disease. While multiple dysregulated components and pathways comprising these clusters have previously been implicated in ALS pathogenesis, unbiased analysis of this large survey demonstrated that sporadic ALS patient tissues can be segregated into distinct molecular subsets.

genomics↗