Evidence map›Paper›PMID 38062485›Full record

ArticleTranslational neurodegeneration2023

Novel data-driven subtypes and stages of brain atrophy in the ALS-FTD spectrum.

Ting Shen, Jacob W Vogel, Jeffrey Duda, Jeffrey S Phillips, Philip A Cook, James Gee, Lauren Elman, Colin Quinn, Defne A Amado, Michael Baer and 4 more

Open access · goldAbstract read
In one paragraph

Article in Translational neurodegeneration, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 16 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

14 authors at 2 institutions in 2 countries.

Ting ShenPenn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Jacob W VogelDepartment of Clinical Sciences, SciLifeLab, Lund University, 222 42, Lund, Sweden.
Jeffrey DudaPenn Image Computing and Science Lab (PICSL), Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Jeffrey S PhillipsPenn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Philip A CookPenn Image Computing and Science Lab (PICSL), Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
James GeePenn Image Computing and Science Lab (PICSL), Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Lauren ElmanDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Colin QuinnDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Defne A AmadoDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Michael BaerDepartment of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Lauren MassimoPenn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Murray GrossmanPenn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
David J IrwinPenn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Corey T McMillanPenn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA. mcmillac@pennmedicine.upenn.edu.
University of Pennsylvania · USScience for Life Laboratory · SE

Funding

Research Education ComponentP30AG072979 · NIA · UNIVERSITY OF PENNSYLVANIA · PI DAVID A WOLK · 2021 to 2026
$24.8M
Understanding Environmental Contributions to Heterogeneity in bvFTD.P01AG066597 · NIA · UNIVERSITY OF PENNSYLVANIA · PI Lauren M Massimo · 2020 to 2026
$18.8M
Microscopic and Large-Scale Networks of Molecular Pathology in Frontotemporal Lobar DegenerationR01NS109260 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI IRWIN, DAVID JOHN · 2019 to 2023
$3.8M
Viral-based Therapeutic Approaches for Reversal of ALS PathologyK08NS114106 · NINDS · UNIVERSITY OF PENNSYLVANIA · PI AMADO, DEFNE AUDREY · 2020 to 2024
$1.1M
NIA NIH HHS P01 AG066597NIA NIH HHS P30 AG072979NINDS NIH HHS K08 NS114106NINDS NIH HHS R01 NS109260
6 · The paper itself

Abstract

backgroundTDP-43 proteinopathies represent a spectrum of neurological disorders, anchored clinically on either end by amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The ALS-FTD spectrum exhibits a diverse range of clinical presentations with overlapping phenotypes, highlighting its heterogeneity. This study was aimed to use disease progression modeling to identify novel data-driven spatial and temporal subtypes of brain atrophy and its progression in the ALS-FTD spectrum.

methodsWe used a data-driven procedure to identify 13 anatomic clusters of brain volume for 57 behavioral variant FTD (bvFTD; with either autopsy-confirmed TDP-43 or TDP-43 proteinopathy-associated genetic variants), 103 ALS, and 47 ALS-FTD patients with likely TDP-43. A Subtype and Stage Inference (SuStaIn) model was trained to identify subtypes of individuals along the ALS-FTD spectrum with distinct brain atrophy patterns, and we related subtypes and stages to clinical, genetic, and neuropathological features of disease.

resultsSuStaIn identified three novel subtypes: two disease subtypes with predominant brain atrophy in either prefrontal/somatomotor regions or limbic-related regions, and a normal-appearing group without obvious brain atrophy. The limbic-predominant subtype tended to present with more impaired cognition, higher frequencies of pathogenic variants in TBK1 and TARDBP genes, and a higher proportion of TDP-43 types B, E and C. In contrast, the prefrontal/somatomotor-predominant subtype had higher frequencies of pathogenic variants in C9orf72 and GRN genes and higher proportion of TDP-43 type A. The normal-appearing brain group showed higher frequency of ALS relative to ALS-FTD and bvFTD patients, higher cognitive capacity, higher proportion of lower motor neuron onset, milder motor symptoms, and lower frequencies of genetic pathogenic variants. The overall SuStaIn stages also correlated with evidence for clinical progression including longer disease duration, higher King's stage, and cognitive decline. Additionally, SuStaIn stages differed across clinical phenotypes, genotypes and types of TDP-43 pathology.

conclusionsOur findings suggest distinct neurodegenerative subtypes of disease along the ALS-FTD spectrum that can be identified in vivo, each with distinct brain atrophy, clinical, genetic and pathological patterns.

Indexed as

Amyotrophic Lateral SclerosisFrontotemporal DementiaNeurodegenerative DiseasesAtrophyBrainDNA-Binding ProteinsHumansDNA-Binding ProteinsAmyotrophic lateral sclerosisDisease heterogeneityFrontotemporal degenerationSuStaIn model

Identifiers

PMID38062485
PMCPMC10701950
OpenAlexW4389452169

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.