# Integrating spatial multi-omics and clinical covariates to identify mechanisms of disease in ALS-FTD > **NIH NIH R01** · NEW YORK GENOME CENTER · 2022 · $787,330 ## Abstract Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are part of a fatal and untreatable disease spectrum that is unified by a diverse presentation of TDP-43 aggregation across central nervous system (CNS) tissue. Up to 50% of patients with motor dysfunction also present with cognitive deficits and 15% have frank FTD, but the molecular mechanisms underlying diverse clinical and pathological presentations remain poorly understood. In our recent work, we have shown that the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) is a good clinical predictor of extra-motor TDP-43 pathology. Specifically, ECAS subdomain scores correlate with the distribution of TDP-43 inclusions in brain regions corresponding to the affected cognitive domains. However, the presence of TDP-43 pathology in a region is not predictive of cognitive deficits associated with that region. We posit that there may be other, more sensitive, neuropathological correlates of cognitive involvement that remain to be identified, and hypothesize that additional pathological features--including nucleocytoplasmic protein mislocalization, perturbations in gene expression, and dysfunctional cell-cell interactions--may correlate more closely with domain-specific cognitive impairment corresponding to a particular region of the frontal cortex. We will test this hypothesis through a comprehensive multi-omic analysis of post- mortem tissue that identifies 1) how differences in cell type-specific subpopulations and intercellular interactions between ALS-FTD cases and controls relate to protein aggregation and mislocalization and 2) how these differences relate to cognitive impairment in ALS-FTD. We will accomplish these goals using spatially resolved proteomic (Aim 1) and transcriptomic (Aim 2) measurements to analyze clinico-pathologically stratified dorsolateral prefrontal cortical tissue samples (specifically, Brodmann areas BA44 and BA46) from cognitively impaired ALS patients and age/gender matched controls. By using a combination of approaches to simultaneously map the spatial transcriptome and proteome of all interacting cellular subpopulations in these regions, our aim is to elucidate the origins and temporal dynamics of inter- and intra-cellular activities that may reveal novel diagnostic and therapeutic targets. We have previously implemented Spatial Transcriptomics (ST) on the spinal cord to identify regional differences within subpopulations of various cell types that vary as a function of disease dynamics. These data will be directly tied to measures of pathology (e.g., pathognomonic inclusions). To integrate and analyze relationships between data across modalities, we will develop a computational framework for harmonized analysis of multi-modal, multi-omic measures of disease burden (Aim 2). Finally, we will implement highly multiplexed immuno-imaging to validate our findings in an independent ALS- FTD cohort (Aim 3). Our integrated analysis across experimental moda... ## Key facts - **NIH application ID:** 10378653 - **Project number:** 5R01NS118183-03 - **Recipient organization:** NEW YORK GENOME CENTER - **Principal Investigator:** Christopher Jackson - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $787,330 - **Award type:** 5 - **Project period:** 2020-08-15 → 2025-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10378653 ## Citation > US National Institutes of Health, RePORTER application 10378653, Integrating spatial multi-omics and clinical covariates to identify mechanisms of disease in ALS-FTD (5R01NS118183-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10378653. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*