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Dave, Kuldip D.

0009-0008-3467-0260

A5056880670 | I2802461698

Mayo Clinic

Amyotrophic Lateral Sclerosis Association

Citations 11

TDP-43–Associated Neurodegenerative Disease Conceptualization and Integrated Staging

JAMA Neurology | August 24, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jamaneurol.2026.2812 | PMID 42636000

Importance Classifying disease based on underlying pathobiology rather than clinical phenotype has implications for the development of biomarkers and therapy development. Observations Transactive response DNA-binding protein 43 kDa (TDP-43) pathology is observed across a range of clinically defined neurodegenerative disorders including limbic predominant age-related encephalopathy (LATE), most cases of amyotrophic lateral sclerosis (ALS), inclusion body myositis, multisystem proteinopathy, and approximately half the cases of frontotemporal dementia (FTD). Despite this shared biology, the current nosology for these neurodegenerative disorders is based on their distinct clinical phenotypes. An alternative approach recognizes the central role of TDP-43 pathology in disease pathogenesis, reserving the use of clinical terms like ALS, FTD, or LATE to describe phenotypic manifestations of underlying pathobiology. This approach also recognizes the converging biomarker and neuropathological data indicating that pathology begins presymptomatically, before the overt clinical manifestations of disease appear. Conclusions and Relevance In proposing a pathobiological definition of disease, the goal is to provide a road map for developing biomarkers that accurately reflect the underlying pathobiology of disease and for advancing therapeutic candidates that effectively target fundamental disease mechanisms.
Design considerations for C9orf72 disease prevention trials

Brain | August 3, 2025 | Volume: 148 | Issue: 11 | Pages: 3844-3855

10.1093/brain/awaf290 | PMID 40794569

Abstract The idea that it might be possible to prevent some forms of amyotrophic lateral sclerosis and frontotemporal dementia has finally come of age. The hexanucleotide repeat expansion in the C9orf72 gene accounts for ∼10% of all amyotrophic lateral sclerosis and 10%–15% of all frontotemporal dementia diagnoses, with the two clinical syndromes co-manifesting in a significant number of patients. As a result, clinically unaffected carriers of pathogenic C9orf72 repeat expansions are currently the largest identifiable population at significantly elevated risk for both amyotrophic lateral sclerosis and frontotemporal dementia, and in whom it might be possible to prevent the emergence of clinically manifest disease. Strategies for the design of disease prevention trials among clinically unaffected C9orf72 carriers have begun to emerge separately in the amyotrophic lateral sclerosis and frontotemporal dementia fields. However, recognition of the need to define neurodegenerative diseases based on biology underscores the need to consider all potential clinical manifestations of a C9orf72 repeat expansion together, rather than the traditional siloed approach of focusing on only amyotrophic lateral sclerosis or only frontotemporal dementia. Indeed, emerging clinical and biological markers that might be used to quantify pre-symptomatic disease progression and to predict the short-term risk of phenoconversion to clinically manifest disease are shared across the phenotypic spectrum. Given the anticipated progress in the development of therapeutic strategies to target the C9orf72 repeat expansion, and the enthusiasm for prevention trials among the unaffected C9orf72 repeat expansion carrier population, now is the time to begin work on the design of disease prevention trials. To this end, The Association for Frontotemporal Degeneration and The ALS Association supported a multi-stakeholder workshop (in Washington D.C., June 2024) to unify efforts to design a prevention trial for the population at elevated genetic risk for the phenotypic spectrum of C9orf72 disease. Here we describe recommendations emanating from this workshop for the selection of outcome measures, delineation of eligibility criteria, optimal use of biomarkers and digital health technologies, potential analytic frameworks and relevant regulatory considerations related to C9orf72 disease prevention trials. We also emphasize the importance of the amyotrophic lateral sclerosis and frontotemporal dementia communities working together in partnership with the C9orf72 repeat expansion carrier community, the regulatory authorities and the broader drug development community.
Contributions of neurologists to diagnostic timelines of ALS and thinkALS as an early referral instrument for clinicians

Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration | December 10, 2024 | Volume: 26 | Issue: 3-4 | Pages: 215-224

10.1080/21678421.2024.2432034 | PMID 39654532

Clinician Education Initiatives for General Neurologists on ALS: Why It Is Needed and ThinkALS, a Possible Solution (P5-11.008)

Neurology | April 9, 2024 | Volume: 102 | Issue: 7_supplement_1 | Pages: No page available

10.1212/wnl.0000000000205100

Feasibility and Safety of Multisite Tissue and Biofluid Sampling for Synuclein in Parkinson’s Disease: The Systemic Synuclein Sampling Study (S4) (P1.013)

Neurology | December 7, 2023 | Volume: 88 | Issue: 16_supplement | Pages: No page available

10.1212/wnl.88.16_supplement.p1.013

Preventing amyotrophic lateral sclerosis: insights from pre-symptomatic neurodegenerative diseases

Brain | October 19, 2021 | Volume: 145 | Issue: 1 | Pages: 27-44

10.1093/brain/awab404 | PMID 34677606

Abstract Significant progress has been made in understanding the pre-symptomatic phase of amyotrophic lateral sclerosis. While much is still unknown, advances in other neurodegenerative diseases offer valuable insights. Indeed, it is increasingly clear that the well-recognized clinical syndromes of Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, spinal muscular atrophy and frontotemporal dementia are also each preceded by a pre-symptomatic or prodromal period of varying duration, during which the underlying disease process unfolds, with associated compensatory changes and loss of inherent system redundancy. Key insights from these diseases highlight opportunities for discovery in amyotrophic lateral sclerosis. The development of biomarkers reflecting amyloid and tau has led to a shift in defining Alzheimer’s disease based on inferred underlying histopathology. Parkinson’s disease is unique among neurodegenerative diseases in the number and diversity of non-genetic biomarkers of pre-symptomatic disease, most notably REM sleep behaviour disorder. Huntington’s disease benefits from an ability to predict the likely timing of clinically manifest disease based on age and CAG-repeat length alongside reliable neuroimaging markers of atrophy. Spinal muscular atrophy clinical trials have highlighted the transformational value of early therapeutic intervention, and studies in frontotemporal dementia illustrate the differential role of biomarkers based on genotype. Similar advances in amyotrophic lateral sclerosis would transform our understanding of key events in pathogenesis, thereby dramatically accelerating progress towards disease prevention. Deciphering the biology of pre-symptomatic amyotrophic lateral sclerosis relies on a clear conceptual framework for defining the earliest stages of disease. Clinically manifest amyotrophic lateral sclerosis may emerge abruptly, especially among those who harbour genetic mutations associated with rapidly progressive amyotrophic lateral sclerosis. However, the disease may also evolve more gradually, revealing a prodromal period of mild motor impairment preceding phenoconversion to clinically manifest disease. Similarly, cognitive and behavioural impairment, when present, may emerge gradually, evolving through a prodromal period of mild cognitive impairment or mild behavioural impairment before progression to amyotrophic lateral sclerosis. Biomarkers are critically important to studying pre-symptomatic amyotrophic lateral sclerosis and essential to efforts to intervene therapeutically before clinically manifest disease emerges. The use of non-genetic biomarkers, however, presents challenges related to counselling, informed consent, communication of results and limited protections afforded by existing legislation. Experiences from pre-symptomatic genetic testing and counselling, and the legal protections against discrimination based on genetic data, may serve as a guide. Building on what we have learned—more broadly from other pre-symptomatic neurodegenerative diseases and specifically from amyotrophic lateral sclerosis gene mutation carriers—we present a road map to early intervention, and perhaps even disease prevention, for all forms of amyotrophic lateral sclerosis.
Screening peripheral biopsies for alpha‐synuclein pathology using deep machine learning

Alzheimer's & Dementia | December 7, 2020 | Volume: 16 | Issue: S5 | Pages: No page available

10.1002/alz.047358

AbstractBackgroundPost‐mortem assessment remains the only option and a gold standard for a definitive diagnosis of Parkinson’s disease (PD). The antemortem diagnosis is challenging due to a variable clinical presentation and the abundance of mimicking conditions, obscuring the clinical picture and delaying the treatment. It is well established that while PD pathologically manifests in central nervous system with aggregation of α‐synuclein as Lewy bodies and Lewy neurites, this pathology is also found in the peripheral nervous system. Peripheral Lewy‐type synucleinopathy (LTS) is present in early PD, suggesting its utility as a diagnostic and prognostic biomarker. We have previously confirmed that detection of LTS in submandibular gland (SMG) biopsies is sensitive (.75) and specific (.90) for early PD. However, the assessment by a neuropathologist of multiple levels of such biopsy is laborious and time‐consuming.MethodHere work we applied two Convolutional Neural Networks (CNN) for detection of LTS on 283 digital whole slide images (WSI) from 95 unique SMG biopsies. A total number of 8,386 LTS were annotated following the interrater reliability study with kappa=.7. We used transfer learning to train a CNN model to classify image patches (40‐by‐40 pixels at 20x) with and without presence of LTS objects.ResultThe trained CNNs showed the following performance on image patches: sensitivity: .982/.988, specificity: .998/.999, precision: .852/.950, accuracy: .995/.998, and F‐1 score .912/.968 for ResNet30/InceptionV4 respectively. On test WSI the sensitivity in detecting LTS was .963/.971 respectively.ConclusionThis work is first to demonstrate the practical utility of an CNN for screening for LTS, which can further translate into a practical screening tool facilitating the antemortem diagnosis of PD. We further plan to develop neural networks for accurate and precise detection and quantification of LTS in antemortem SMG biopsies. This, altogether, would offer a screening, confirmatory, prognostic, and quantitative tool for clinical assessment of early PD.
In vivo distribution of α-synuclein in multiple tissues and biofluids in Parkinson disease

Neurology | August 3, 2020 | Volume: 95 | Issue: 9 | Pages: No page available

10.1212/wnl.0000000000010404 | PMID 32747521

Feasibility and Safety of Multicenter Tissue and Biofluid Sampling for α -Synuclein in Parkinson’s Disease: The Systemic Synuclein Sampling Study (S4)

Journal of Parkinson’s Disease | September 21, 2018 | Volume: 8 | Issue: 4 | Pages: 517-527

10.3233/jpd-181434 | PMID 30248065

Background: α-synuclein is a lead Parkinson’s disease (PD) biomarker. There are conflicting reports regarding accuracy of α-synuclein in different tissues and biofluids as a PD biomarker, and the within-subject anatomical distribution of α-synuclein is not well described. The Systemic Synuclein Sampling Study (S4) aims to address these gaps in knowledge. The S4 is a multicenter, cross-sectional, observational study evaluating α-synuclein in multiple tissues and biofluids in PD and healthy controls (HC). Objective: To describe the baseline characteristics of the S4 cohort and safety and feasibility of this study. Methods: Participants underwent motor and non-motor clinical assessments, dopamine transporter SPECT, biofluid collection (cerebrospinal fluid, saliva, and blood), and tissue biopsies (skin, sigmoid colon, and submandibular gland). Biopsy adequacy was determined based on presence of adequate target tissue. Tissue sections were stained with the 5C12 monoclonal antibody against unmodified α-synuclein. All specimens were acquired and processed in a standardized manner. Adverse events were systematically recorded. Results: The final cohort consists of 82 participants (61 PD, 21 HC). In 68 subjects (83%), all types of specimens were obtained but only 50 (61%) of subjects had all specimens both collected and evaluable for α-synuclein. Mild adverse events were common, especially for submandibular gland biopsy, but only 1 severe adverse event occurred. Conclusion: Multicenter tissue and biofluid sampling for α-synuclein is feasible and generally safe. S4 will inform understanding of the concurrent distribution of α-synuclein pathology and biomarkers in biofluids and peripheral nervous system in PD.
Immunohistochemical Method and Histopathology Judging for the Systemic Synuclein Sampling Study (S4)

Journal of Neuropathology & Experimental Neurology | August 13, 2018 | Volume: 77 | Issue: 9 | Pages: 793-802

10.1093/jnen/nly056 | PMID 30107604