Walker, Alyssa C.

Abstract TAR DNA-binding protein 43 (TDP-43) pathology frequently co-occurs with Tau neurofibrillary tangles (NFTs) and amyloid β plaques in Alzheimer’s disease (AD), driving significant clinical heterogeneity. Whether TDP-43 engages autonomous molecular programs or instead amplifies Tau-driven neurodegeneration remains difficult to resolve, largely because these pathologies often co-occur. To separate these overlapping signatures, we generated regionally resolved transcriptomic profiles from cognitively normal controls (Controls), neuropathologically defined cohorts of AD, AD with limbic-predominant age-related TDP-43 encephalopathy (AD/LATE), and frontotemporal lobar degeneration (FTLD-TDP), categorizing them by their distinct TDP-43 subtypes (types α and β for AD/LATE; types A and B for FTLD-TDP). By integrating transcriptomic profiles with quantitative measures of phosphorylated TDP-43 (pTDP-43) and Tau (pTau), we separated pathology-associated signals within mixed disease contexts. We found that TDP-43 is linked to distinct transcriptomic programs in AD/LATE that are largely uncoupled from Tau burden and diverge from those observed in FTLD-TDP. These signatures showed regional specificity, with transcriptomic remodeling occurring in the amygdala across both diseases, whereas frontal cortex alterations were largely restricted to FTLD-TDP. Furthermore, by stratifying cases by TDP-43 morphological subtype, we unmasked specific biological trajectories, from immune activation to unique cellular vulnerabilities, that are not apparent in unstratified cohorts. Together, our findings provide a framework for decoupling mixed proteinopathies and demonstrate that TDP-43 shapes autonomous, subtype-dependent transcriptional landscapes in AD.

The role of the epigenome in age-related neurodegenerative disorders remains understudied. Here, we analyzed circulating cell-free DNA (cfDNA) from blood to detect methylation changes as a liquid biopsy for Amyotrophic Lateral Sclerosis (ALS). Our study included 20 patients with sporadic ALS, 10 patients with C9orf72-associated ALS, 10 asymptomatic carriers of the C9orf72 repeat expansion mutation, and 21 nondisease control individuals. Following targeted enzymatic methyl-sequencing (EM-seq) of approximately 4 million CpG sites, we detected numerous differentially methylated genes, including several implicated in ALS disease risk and pathogenesis. By integrating multiple epigenetic features, we delineated a distinct epigenetic signature, which achieved an average area under the curve (AUC) of 0.91 ± 0.10 upon receiver operator characteristic (ROC) analysis, which enabled detection of approximately 70% of patients with ALS with close to 100% specificity. Furthermore, we also identified a set of genes whose methylation status significantly correlated with clinical disease progression and cerebrospinal fluid (CSF) neurofilament levels. Our results reveal the potential of cfDNA-based biomarkers to accurately diagnose ALS and potentially predict disease progression.

Abstract The role of the epigenome in age-related neurodegenerative disorders remains understudied. Here, we analyzed circulating cell-free DNA (cfDNA) from blood to detect methylation changes as a liquid-biopsy for Amyotrophic Lateral Sclerosis (ALS). Our study included 20 patients with sporadic ALS, 10 patients with C9orf72-associated ALS, 10 asymptomatic carriers of the C9orf72 repeat expansion mutation, and 21 non-disease controls. Following targeted enzymatic methyl-sequencing (EM-seq) of ∼4 million CpG sites, we detected numerous differentially methylated genes, including several implicated in ALS disease risk and pathogenesis. By integrating multiple epigenetic features, we delineated a distinct epigenetic signature, which achieved an average area under the curve (AUC) of 0.91 ± 0.10 upon receiver operator characteristic (ROC) analysis, which enabled detection of ∼70% of ALS patients with close to 100% specificity. Furthermore, we also identified a set of genes whose methylation status significantly correlated with clinical disease progression and cerebrospinal fluid (CSF) neurofilament levels. Our results reveal the potential of cfDNA-based biomarkers to accurately diagnose ALS and potentially predict disease progression.