Petrucelli, Leonard

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.

Background TAR DNA-binding protein 43 (TDP-43) proteinopathy contributes to Alzheimer's disease progression, but diagnosis remains autopsy-dependent. Objective This study aimed to develop a predictive model using FDG-PET imaging to identify brain regions associated with TDP-43 pathology in vivo. Methods Penalized logistic regression analyzed data from 294 participants and a subset of 159 with Braak and Thal ≥4. Features included FDG standard uptake value ratios (SUVRs) from 123 brain regions and age. Participants were split into training (90%) and testing (10%) datasets, with significant predictors identified by non-zero coefficients at optimal lambda. Results The model achieved 68% accuracy (AUC = 0.70) in 294 participants, highlighting the middle temporal gyrus, parahippocampal gyrus, and hippocampus. In the subset (n = 159), accuracy was 65% (AUC = 0.71), with the medial amygdala and precentral gyrus as key predictors of TDP-43 pathology. Conclusions This study suggests a moderate predictive accuracy of FDG-PET to identify brain regions associated with Alzheimer's disease-related TDP-43 proteinopathy.

GGGGCC (G 4 C 2 ) repeat expansion in C9ORF72 is the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Toxicity is thought to result from the accumulation of either repeat RNAs and/or dipeptide repeat proteins (DPRs) translated from repeat-containing transcripts through repeat-associated non-AUG (RAN) translation. To disentangle RNA from DPR toxicity, we mutated a CUG codon predominantly used to initiate DPR translation from all three reading frames. This mutation disrupted DPR synthesis while preserving the expression of repeat-containing RNAs. Despite the accumulation of RNA foci, behavioral deficits and pathological abnormalities, including p-TDP-43 inclusions, STING activation, motor neuron loss, neuroinflammation, and increased plasma neurofilament concentration, were alleviated in C9ORF72 mice. Base editing of the CUG codon also improved molecular phenotypes and survival in patient induced pluripotent stem cell–derived neurons, which highlights the potential of therapeutically targeting DPR production rather than repeat RNAs.

ABSTRACT Objective This study aims to identify both fluid and neuroimaging biomarkers for CSF1R‐RD that can inform the optimal timing of treatment administration to maximize therapeutic benefit, while also providing sensitive quantitative measurements to monitor disease progression. Methods Our study compared neuroimaging and fluid (plasma and cerebrospinal fluid (CSF)) biomarkers across three distinct populations: asymptomatic CSF1R pathogenic variant carriers ( N = 14), symptomatic CSF1R pathogenic variant carriers ( N = 17), and healthy controls ( N = 30). We evaluated biomarker correlations with both an established (Montreal Cognitive Assessment (MoCA)) and a novel (CSF1R Clinical Severity Score (CCSS)) clinical diagnostic scale to investigate potential clinical utility. Additionally, we tested the relationship between select biomarkers and cortical thickness using 3D T1‐weighted MPRAGE scans, providing a highly valuable physiological component to our analyses. Results Our results demonstrate that while plasma glial fibrillary acidic protein (GFAP) displays a high sensitivity for distinguishing early‐stage CSF1R‐RD patients from healthy controls, plasma neurofilament light chain (NfL) is more effective for tracking disease progression following the onset of symptoms. Interpretation Overall, our study provides evidence for plasma NfL and GFAP as valuable biomarkers of earliest symptom onset and disease progression for CSF1R‐RD.

Abstract Background TMEM106B encodes a lysosomal protein and is a genetic susceptibility factor for frontotemporal lobar degeneration (FTLD). Aptamer‐based proteomics quantifies TMEM106B protein levels in CSF. The associations of CSF TMEM106B with measures of disease severity have not been previously evaluated, and the value of CSF TMEM106B as a clinical biomarker is unknown. Method CSF TMEM106B and NfL protein levels were quantified with aptamer‐based proteomics in participants from two independent cohorts: sporadic FTLD with neuropathology‐confirmed FTLD‐tau and FTLD‐TDP, clinically diagnosed PSP‐Richardson Syndrome, and controls (UCSF MAC, n = 95; mean age = 69 ± 6 yrs; 48% female) and familial FTLD comprised of presymptomatic and symptomatic FTLD mutation carriers with family non‐carrier controls (ALLFTD, n = 179; mean age = 49 ± 13 yrs; 53% female). The association between biomarkers and diverse measures of disease severity, including the CDR®+NACC‐FTLD and CDR®+NACC‐FTLD sum of boxes, were determined with linear regressions or mixed linear models. Associations with brain volumes were determined within the framework of voxel‐based morphometry. Result In both cohorts, at baseline, CSF TMEM106B did not differ by sex, age, FTLD phenotype, or CSF NfL. CSF TMEM106B was lower in cases with worse disease severity (Figure 1) and in participants with the protective TMEM106B rs1990622 G/G genotype, regardless of pathological diagnosis or FTLD‐causing mutation. Low CSF TMEM106B was associated with more severe longitudinal worsening in FTLD disease severity (Figure 2), basic and instrumental function, global cognition, executive function, and depression scores. These associations were weaker than those of NfL. Low CSF TMEM106B was associated with low brain volumes in frontal, parietal, and temporal regions (FWE‐corrected p < 0.05) (Figure 3A). CSF NfL negatively correlated (FWE‐corrected p < 0.05) with brain volumes in frontotemporal regions (Figure 3B). Conclusion CSF TMEM106B concentrations are influenced by the TMEM106B rs1990622 genotype, and correlate with disease severity and brain volume in both genetic and sporadic FTLD. Lower levels of CSF TMEM106B correlate with more severe disease and brain atrophy. Disease severity is more strongly associated with CSF NfL, while brain volumes are more strongly associated with CSF TMEM106B. CSF TMEM106B may have value as a biomarker of neurodegeneration in FTLD.

Abstract Background Recent technological advances have enhanced the precision of blood‐based multiplex proteomics and their application in Alzheimer's disease. However, these approaches remain underutilized in frontotemporal lobar degeneration (FTLD). Familial FTLD cohorts offer a unique opportunity to study presymptomatic periods of disease that cannot be studied in sporadic cases. We leveraged NUcleic acid Linked Immuno‐Sandwich Assay (NULISAseq) to identify blood‐detectable proteins that change prior to symptom onset in familial FTLD. Method 120 FTLD mutation carriers (40 C9orf72 , 40 GRN , 40 MAPT ) and 40 age and sex‐matched noncarrier controls from the ALLFTD Consortium completed blood draws and clinical assessment. Targeted plasma proteomics was performed via NUcleic acid Linked Immuno‐Sandwich Assay (NULISAseq; 132 proteins). Disease age estimates measuring predicted symptom onset were derived from a validated model incorporating FTLD gene‐specific clinical, neuroimaging, and biomarker data. Mass linear regression models identified disease age ‘thresholds’ where individual proteins significantly diverged between each mutation carrier group and controls. NULISAseq targets were validated against orthogonal assays, specifically Simoa (plasma) and SomaScan (cerebrospinal fluid [CSF]). Result Compared to controls, 14 plasma proteins significantly diverged ( p <.05) in C9orf72 , 24 in GRN , and 13 in MAPT . Beyond NEFL, 10 additional proteins significantly diverged in more than one mutation group, including markers of synaptic function (NPTX2, NPTXR) and vascular integrity (PGF) that deviated prior to estimated symptom onset (disease age range: ‐30 to 0). Proteins with gene‐specific signals included GFAP (increased in GRN at disease age ‐17), ENO2 (decreased in C9orf72 at disease age ‐7), and FLT1 (increased in MAPT at disease age ‐6). Plasma NULISA‐based NEFL and GFAP showed strong concordance when measured via plasma Simoa ( r s>0.88) and were among 38 targets with significant concordance when measured via CSF SomaScan ( r range: 0.16 to 0.75, p s<.05). Conclusion Alterations in plasma protein abundance are measurable in familial FTLD prior to predicted symptom onset. The validity and brain‐based relevance of blood‐detectable NULISA targets is bolstered by the observed convergence with plasma Simoa and CSF SomaScan. Replication of top hits in larger familial and sporadic FTLD sample sizes is warranted to determine generalizability and suitability for clinical trials.

Abstract Background Genome‐wide association studies (GWAS) linked TMEM106B variants to susceptibility for neurodegenerative diseases, but the causal genetic elements remain unclear. Method We used genotyping data from 5,792 Alzheimer disease cases and controls, and applied COJO to identify haplotypes in the TMEM106B locus that independently associated with AD. Then, we used long‐read sequencing data from 513 individuals to annotate these haplotypes with structural variations that map into them. Results Analysis of the genotyping data revealed that the TMEM106B locus consists of four major haplotypes: HA/Ha (covering the coding region), and HB/Hb (covering the upstream regulatory region). These combine into four combinations with varying population‐frequencies: HAB (57%), HaB (34%), Hab (9%), and HAb (<1%). Long‐read sequencing of 513 individuals showed that HA haplotypes (marked by 185‐Threonine) carry unique methylated CpG sites and an AluYb8‐retrotransposon in the 3' UTR, while the Ha haplotypes are marked by the 185‐Serine allele. Hb haplotypes carry several structural variants (SVs) in nearby distal enhancers, including a 19 Kbp rearrangement, absent in all other haplotypes. Joint association models revealed that the HAB combination (AluYb8+185‐Threonine) is risk‐increasing, while Hab (SVs+185‐Serine) confers the protective effect. HaB (185‐Serine only) is neutral, while HAb was too rare to assess. Relative to middle‐aged non‐demented controls, cognitively healthy centenarians were more enriched with Hab (OR=1.49, padj=2.18×10‐2) than with HaB (OR=1.23, padj=5.06×10‐2). Proteomic analysis of temporal cortex tissues ( n = 182) indicated that relative to the neutral HaB combination, the protective Hab is associated with 1.1‐fold lower TMEM106B C‐terminal peptide abundance, while the risk‐increasing HAB is associated with 1.16‐fold higher abundance. Conclusion Our data indicates that the genetic structure underlying the association of the TMEM106B locus with neurodegenerative diseases is driven by the effect of multiple haplotypes.

Abstract Background Although Alzheimer's disease (AD) is classically defined by the accumulation of tau neurofibrillary tangles and Aβ plaques, a large proportion of cases are also positive for inclusions containing TAR DNA binding protein of 43 kDa (TDP‐43) – and evidence shows that these cases generally have a more aggressive disease course marked by worse memory and increased hippocampal atrophy. As we advance towards precision medicine in AD, it is imperative that we understand the contribution of TDP‐43 proteinopathy to pathogenesis and develop tools to track this pathology in living patients. Methods In affected neurons, TDP‐43 nuclear clearance triggers mRNA misprocessing events including cryptic exon inclusion and alternative polyadenylation. We aim to exploit these events to develop sensitive biomarkers that can serve as proxy measures for TDP‐43 dysfunction. As we identify misprocessed TDP‐43 targets that accumulate in affected brain regions in AD, we also explore the impact of these aberrant transcripts on molecular processes and pathways in the brain to gain insight into disease pathomechanisms. Results We have developed tools to measure a promising biomarker of TDP‐43 dysfunction, a cryptic form of the protein HDGFL2, and verified that it can be detected in post‐mortem AD patient tissue specifically in brain regions marked by mixed pathology. We have also uncovered a connection between TDP‐43 dysfunction and compromised endolysosomal activity. In fact, we find that artificially severing the endolysosomal pathway via expression of a constitutively active Rab5 can induce TDP‐43 pathology and neurodegeneration in vivo in mice, and we are using this tool to map the consequences of endolysosomal dysfunction in the brain and its potential connection to mixed pathology formation in AD. Conclusions TDP‐43 co‐pathology has a profound effect on AD pathogenesis that may be intrinsically linked to a disruption of the endolysosomal pathway in neurons. Exploring the consequences of TDP‐43 dysfunction in the brain can open new avenues for AD biomarker and therapeutic development.

Abstract Background Some cases of Alzheimer's Disease (AD) and Frontotemporal Dementia (FTD) feature the mislocalization of the normally nuclear TAR DNA binding protein (TDP‐43) to the cytoplasm where it is incorporated into inclusions in affected brain regions. TDP‐43 plays a crucial role in the suppression of cryptic exons in the mature RNA of many targets in both AD and FTD. One such target, Stathmin‐2 (STMN2), is misspliced in the absence of TDP‐43 leading to a reduction of STMN2 RNA and protein while the levels of the cryptic splice variant is increased. Cryptic exons are not conserved across species, meaning previous Tdp‐43 models did not capture Stmn2 processing defects and Stmn2 loss of function (LOF). We hypothesize that STMN2 LOF contributes to cognitive phenotypes observed in AD and FTD. Method We have generated a novel mouse that more accurately models human disease mechanisms by expressing short‐hairpin (shRNA) via adeno associated virus in the central nervous system of a recently described humanized Stmn2 mouse model in which Stmn2 splicing is dependent on Tdp‐43. In this mouse we will simultaneously model Tdp‐43 loss of function and aberrant Stmn2 splicing. Result Our preliminary experiments demonstrate that humanized Stmn2 mice expressing shRNA against Tardbp have a reduction of Tardbp RNA and TDP‐43 protein compared to mice expressing a non‐targeting shRNA. Tdp‐43 knock‐down is accompanied by cryptic splicing of endogenous mouse targets, Sortilin 1 and Translin . As anticipated, we also detected cryptic Stmn2 splicing, suggesting that correct Stmn2 splicing is dependent on Tdp‐43 in this model. We will further characterize motor and cognitive functions in addition to neurodegeneration and gliosis in these animals. Conclusion We anticipate this novel model, and our subsequent studies will identify relevant disease mechanisms and provide an invaluable tool with which to investigate therapies for AD and FTD.