CoChat
Sign Up
Cited by 145Dementia and Cognitive Impairment ResearchAmyotrophic Lateral Sclerosis ResearchAlzheimer's disease research and treatments

Temporal order of clinical and biomarker changes in familial frontotemporal dementia

Open access
Staffaroni, Adam M., Quintana, Melanie, Wendelberger, Barbara, Heuer, Hilary W., Russell, Lucy L., Cobigo, Yann, Wolf, Amy, Goh, Sheng-Yang Matt +240 more·2022·Nature Medicine
DOI 10.1038/s41591-022-01942-9PMC PMC9951811
Open this paper in CoChat — free accountOpen PDF

Abstract

Unlike familial Alzheimer's disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes and plasma neurofilament light chain (NfL) in 796 carriers and 412 noncarrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations using model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. f-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.

Integrity signals

Registry

Crossref · 10.1038/s41591-022-01942-9

Cites

63 of 63 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

18 of 24 cited sources checked · 7 supported · 1 flagged · accuracy not yet measured

  • Premisecitation

    Treating FTD is likely to be most effective when started early, ideally before symptoms appear.

    “Experience from Alzheimer’s disease (AD), spinal muscular atrophy (SMA),5 and amyotrophic lateral sclerosis (ALS)6 suggests treating FTD will be most successful if treatment is initiated early in the disease course, ideally prior to the onset of symptoms.”
    Quote in the paperSubstantial claim2 of 2 sources checked
    • cites [5] Mercuri, E. et al. Nusinersen versus sham control in later-onset spinal muscular atrophy. N. Engl. J. Med. 378, 625–635 (2018). source

      The Discussion reports the greatest motor-function improvements in children with SMA who received nusinersen soon after symptom onset, supporting the early-treatment rationale. It does not establish a benefit from treatment before symptoms appear; applying the SMA finding to FTD is the citing authors’ inference. (LLM, conf=0.88)

      Experimental — accuracy not yet measured
    • cites [6] Miller, T. et al. Phase 1-2 trial of antisense oligonucleotide tofersen for SOD1 ALS. N. Engl. J. Med. 383, 109–119 (2020). source

      The Characteristics of the Participants section says all trial participants had ALS symptoms at illness onset. The Exploratory Outcomes and discussion describe tofersen results but do not compare treatment started at different disease stages or address treatment before symptoms. Searches for presymptomatic and early treatment found no passage supporting the timing claim. (LLM, conf=0.76)

      Experimental — accuracy not yet measured
  • Premisecitation

    In GRN, familial age of onset accounts for just 14% of the variance in when individuals first show symptoms.

    “For example, in GRN, familial age of onset only explains 14% of the variability in individual age at symptom onset.12”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [12] Moore, K. M. et al. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study. Lancet Neurol. 19, 145–156 (2020). source

      The Results report that family membership explained 14% (95% CI 9–22) of the variability in age at symptom onset among people with GRN mutations. That is not the same as saying familial age at onset explained 14%: the paper analyzes mean family age at onset separately and reports a correlation of r=0.18 with individual age at onset (Abstract, Findings). (LLM, conf=0.88)

      Experimental — accuracy not yet measured
  • Interpretationcitation

    C9orf72 expansions might influence brain development early in life.

    “In C9orf72, the thalamus and most other brain regions were smaller than controls 10 to 40 years prior to onset, supporting the hypothesis that C9orf72 repeat expansions may affect early brain development.19,20”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [19] Lee, S. E. et al. Network degeneration and dysfunction in presymptomatic C9ORF72 expansion carriers. NeuroImage Clin. 14, 286–297 (2017). source
      Experimental — accuracy not yet measured
    • cites [20] Caverzasi, E. et al. Gyrification abnormalities in presymptomatic c9orf72 expansion carriers. J. Neurol. Neurosurg. Psychiatry 90, 1005–1010 (2019). source
      Experimental — accuracy not yet measured
  • Study design and conductcitation

    The analysis omitted known genetic modifiers of f-FTD progression, including MAPT-specific mutations and TMEM106B, which modifies GRN penetrance.

    “Known genetic modifiers of f-FTD disease progression were not included, such as specific mutations (for MAPT) and TMEM106B, a modifier of penetrance in GRN.2,40”
    Quote in the paperNot a substantial claim1 of 2 sources checked
    • cites [2] Greaves, C. V. & Rohrer, J. D. An update on genetic frontotemporal dementia. J. Neurol. 266, 2075–2086 (2019). source

      The Age at onset section (page unavailable) identifies TMEM106B as a genetic modifier in GRN carriers and suggests it may affect age-related penetrance. It does not identify specific MAPT mutations as modifiers of disease progression; instead, it says little is known about factors modifying age at onset in MAPT carriers. Whether the citing authors omitted these factors from their analysis is their own description, not a finding attributed to this review. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [40] Pottier, C. et al. Potential genetic modifiers of disease risk and age at onset in patients with frontotemporal lobar degeneration and GRN mutations: a genome-wide association study. Lancet Neurol. 17, 548–558 (2018). source
  • Findingown data

    For C9orf72 carriers, MRI was the earliest biomarker to show change.

    “In C9orf72, MRI was the first biomarker to change (Figures 2, 3, & Extended Data Figure 1; Tables 2, S2-S5), with visual inspection of the DPM curves suggesting that brain volumes deviate from controls up to 40 years before expected onset.”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 26
  • May combine two claims. 48

  • Classified as probably not a substantial claim.

    Premisecitation

    Fewer than a thousand mutation carriers are known globally, making f-FTD a rare disease.

    “F-FTD is rare, with only hundreds of mutation carriers known to exist worldwide.12”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [12] Moore, K. M. et al. Age at symptom onset and death and disease duration in genetic frontotemporal dementia: an international retrospective cohort study. Lancet Neurol. 19, 145–156 (2020). source

      The Results report 3,403 symptomatic mutation carriers in this international cohort alone, contrary to the claim that only hundreds are known worldwide. The Discussion says the analysis did not include carriers who had not developed symptoms, so this count is not a worldwide total. (LLM, conf=0.90)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    About one-fifth to one-third of FTD cases are caused by autosomal dominant mutations, most often in C9orf72, GRN, or MAPT.

    “Approximately 20–30% of FTD is caused by autosomal dominant mutations (familial, or f-FTD), usually in one of three genes: chromosome 9 open reading frame 72 (C9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT).2”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [2] Greaves, C. V. & Rohrer, J. D. An update on genetic frontotemporal dementia. J. Neurol. 266, 2075–2086 (2019). source

  • May combine two claims.

    Premisecitation

    Although clinical manifestations of f-FTD mutations are similar, the biology and neuropathology of C9orf72, GRN, and MAPT mutations are very different.

    “Although the clinical manifestations of the f-FTD mutations are similar, the biology and neuropathology associated with C9orf72, GRN, and MAPT mutations are vastly different.2”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [2] Greaves, C. V. & Rohrer, J. D. An update on genetic frontotemporal dementia. J. Neurol. 266, 2075–2086 (2019). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Prevention trials in dominantly inherited Alzheimer's disease have been helped by fluid and molecular PET biomarkers that measure treatment-related changes in AD pathology and neurodegeneration.

    “Prevention trials in DIAD have also been facilitated by fluid and molecular PET imaging biomarkers that allow for the measurement of treatment-related changes in AD pathologies and neurodegeneration.8”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [7] Bateman, R. J. et al. The DIAN-TU Next Generation Alzheimer’s prevention trial: adaptive design and disease progression model. Alzheimers Dement. 13, 8–19 (2017). source
    • cites [8] Salloway, S. et al. A trial of gantenerumab or solanezumab in dominantly inherited Alzheimer’s disease. Nat. Med. 27, 1187–1196 (2021). source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    In genetic familial frontotemporal dementia, known founder effects for C9orf72 and GRN mutations with European ancestry lead to strong associations with particular racial and ethnic groups.

    “in genetic f-FTD there are known founder effects for C9orf7245 and GRN mutations46 with European ancestry, leading to strong associations with particular racial and ethnic groups.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [45] Mok, K. et al. Chromosome 9 ALS and FTD locus is probably derived from a single founder. Neurobiol. Aging 33, 209.e3–8 (2012). source

      The Discussion (page not provided) links a likely single founder haplotype spanning C9orf72 to ALS and FTD, with the strongest association in populations with Northern European and Scandinavian ancestry. But the Introduction says the causative mutation had not been identified, so this paper does not establish a founder effect for a specific C9orf72 mutation. The separate GRN citation is not assessed here. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [46] van der Zee, J. et al. A Belgian ancestral haplotype harbours a highly prevalent mutation for 17q21-linked tau-negative FTLD. Brain 129, 841–852 (2006). source

      The Introduction (page not provided) reports a founder haplotype associated with a substantial fraction of familial FTLD in Belgium, supporting the general founder-effect point. But the paper does not identify the causal mutation as GRN, and it does not establish strong associations with particular racial or ethnic groups. The GRN and racial/ethnic claims therefore are not supported by this source. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Interpretationcitation

    CDR+NACC-FTLD-SB was statistically powerful for measuring change and, because it reflects informant-reported clinical status, could be considered a clinically meaningful outcome and an approvable endpoint from a regulatory perspective.

    “Not only was this measure statistically powerful for measuring change, but given that it reflects informant-reported clinical status, it could also be considered a clinically meaningful outcome and approvable endpoint from a regulatory perspective.15”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [15] Rentz, D. M. et al. Building clinically relevant outcomes across the Alzheimer’s disease spectrum. Alzheimer’s Dement. Transl. Res. Clin. Interv. 7, e12181 (2021). source

      The section on minimal clinically important differences discusses CDR-SB in Alzheimer’s disease, and the regulators’ perspective section gives general criteria for clinically meaningful outcomes. Neither addresses CDR+NACC-FTLD-SB or establishes its statistical power, informant-reported status, or suitability as an approvable endpoint (searched: FTLD, informant-reported clinical status, approvable endpoint). (LLM, conf=0.76)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Prior reports consistently find temporal lobe atrophy before symptoms in MAPT, and the insula may often atrophy early in MAPT.

    “Temporal lobe atrophy in presymptomatic MAPT has been consistently reported,16,18,23 and the insula may be a common region of early atrophy in MAPT.24”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [16] Staffaroni, A. M. et al. Rates of brain atrophy across disease stages in familial frontotemporal dementia associated with MAPT, GRN, and C9orf72 pathogenic variants. JAMA Netw. Open 3, e2022847 (2020). source

      Citation 24 is attached to the claim that the insula may be a common region of early atrophy in MAPT. The Results (Longitudinal Atrophy Rates; page unavailable) report presymptomatic temporal-lobe volume loss in MAPT carriers, but a search for “insula” found no passage addressing early insular atrophy. (LLM, conf=0.74)

      Experimental — accuracy not yet measured
    • cites [18] Chen, Q. et al. Rates of lobar atrophy in asymptomatic MAPT mutation carriers. Alzheimer’s Dement. Transl. Res. Clin. Interv. 5, 338–346 (2019). source

      Citation 24 is attached to the claim about early insular atrophy. The Discussion and Results describe early temporal-lobe atrophy in MAPT carriers, but the passages retrieved when searching for “insula” and “insular cortex” do not address insular atrophy. Our copy therefore does not verify the point attributed to this citation. (LLM, conf=0.75)

      Experimental — accuracy not yet measured
    • cites [24] Young, A. L. et al. Characterizing the clinical features and atrophy patterns of MAPT-related frontotemporal dementia with disease progression modeling. Neurology 97, e941–e952 (2021). source

  • May combine two claims.

    Interpretationown data

    The simulations indicate that trials for all three genotypes could be powered with CDR+NACC-FTLD-SB and neuropsychological tests, which are likely to be accepted by regulators as clinically meaningful.

    “Based on these simulations, it would be feasible to power trials for all three genetic groups using the CDR®+NACC-FTLD-SB and neuropsychological tests, measures most likely to be approvable by regulatory bodies as clinically meaningful endpoints.15”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [15] Rentz, D. M. et al. Building clinically relevant outcomes across the Alzheimer’s disease spectrum. Alzheimer’s Dement. Transl. Res. Clin. Interv. 7, e12181 (2021). source

      The Conclusions (page unavailable) say regulators consider cognition a meaningful endpoint in Alzheimer's prevention trials, which supports the general point about cognitive measures. The paper does not report simulations showing that trials in three genetic groups could be powered using the CDR®+NACC-FTLD-SB and neuropsychological tests, or assess regulatory acceptance of those specific measures. (LLM, conf=0.81)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Findingown data

    For MAPT, medial temporal atrophy was the earliest biomarker change, separating from controls around 10 years before symptoms and reaching one SD below controls 1.8 years before onset.

    “Medial temporal atrophy was the first observed biomarker change in MAPT, diverging from controls ~10 years before symptoms based on visual inspection (Figure 2), and reaching one SD below controls 1.8 years before onset (95%CI:-3.2,-0.5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For all genetic groups, neuropsychological and RSMS deficits relative to controls usually appeared only after symptoms began, and no measure fell one SD below controls before onset.

    “Visual inspections of the curves indicated that neuropsychological and Revised Self-Monitoring Scale (RSMS) impairments relative to controls were generally observed only after symptom onset for all genetic groups (Figure 2 & Table S5), and no measure reached one SD worse than controls until after symptom onset (Table S4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    As in an earlier study, MAPT showed medial temporal atrophy 15 years before onset, then insular atrophy.

    “Similar to the previous study, we detected medial temporal atrophy in MAPT 15 years prior to onset followed by atrophy of the insula.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In cases called presymptomatic despite CDR+NACC-FTLD-SB>0, other measures were usually average and either stable or improving over time.

    “Examining cases that the model estimated to be presymptomatic (DA<0) despite a CDR®+NACC-FTLD-SB>0, these participants tend to perform in the average range across other measures and stay stable or show improvements over time.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For GRN, baseline plasma NfL was significantly above control levels in every DA epoch and above all other genetic groups during the symptomatic phase.

    “Baseline plasma NfL concentrations in GRN were significantly elevated relative to controls in all DA epochs (Figure 3, Table S5) and elevated compared to all other genetic groups in the symptomatic phase (Table S6).”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingown data

    Baseline DA estimates spanned −40 to 21.

    “DA estimates at baseline ranged from −40 to 21.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    For MAPT, NfL diverged from controls nearer symptom onset than in C9orf72 or GRN, was significantly elevated only in symptomatic epochs, and did not reach one SD above controls until 4.6 years after predicted onset.

    “NfL levels began to diverge from controls closer to symptom onset in MAPT than C9orf72 or GRN, with mean values showing significant elevations during the symptomatic but not presymptomatic epochs (Extended Data Figure 1, Tables S5-6), and average values did not reach one SD above controls until 4.6 years after estimated symptom onset (95%CI:7.1,2.4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For those −10 to 0 years from onset, the average uncertainty decreased to +/−5.5 years, and after onset it was +/−0.9 years.

    “For those −10 to 0 years from onset, this uncertainty decreased to +/−5.5 years, and after onset, the average uncertainty of the estimate was +/−0.9 years.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    As DA increases, performance worsens on many measures, and decline from baseline to final visit becomes more common.

    “With increasing DA, performance is increasingly impaired across multiple measures, and there is a greater tendency for progressive impairment from baseline to final observations.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    GRN carriers scored below controls on Trails A in every epoch and on Trails B during the −10 to 0 epoch.

    “GRN performed worse than controls on Trails A at all epochs, and worse than controls on Trails B in the −10 to 0 epoch.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingreasoning

    People farthest from onset usually score normally on all measures, so the model depends heavily on chronological age priors to estimate DA.

    “However, individuals furthest from onset are typically within normal limits on all contributing measures forcing the model to rely heavily on prior information about participants’ chronological age to estimate DA.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For C9orf72, NfL was significantly above control levels in every DA epoch and reached one SD above controls three years before predicted onset.

    “NfL levels in C9orf72 were significantly higher than controls in all DA epochs and became elevated one SD above controls three years before estimated onset (95%CI:-0.7,-5.8).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    During the symptomatic stage in GRN, all ROIs lost volume faster than in other groups, with the frontal, temporal, medial temporal, insular, and striatal regions losing volume most quickly.

    “In the symptomatic stage, volume loss in all ROIs was more rapid than the other genetic groups, with the frontal, temporal, medial temporal, insular, and striatal ROIs losing volume most rapidly (Figure S3, Table S4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    How precise an individual DA estimate is depends on how close the person is to symptom onset and how long they were followed.

    “The precision of individual DA estimates depends on the proximity to symptom onset and follow-up duration.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Visual inspection of the curves revealed a rapid CDR+NACC-FTLD-SB increase after symptom onset, and all genetic groups had cross-sectional elevations before symptom onset.

    “Visual inspection of the curves revealed a rapid CDR®+NACC-FTLD-SB increase after symptom onset, and all genetic groups had cross-sectional elevations in CDR®+NACC-FTLD-SB prior to symptom onset (Figure 3, Table S5);”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For C9orf72, thalamic volume was significantly below control levels during the −40 to −10 epoch and showed the largest effect size of any ROI.

    “Thalamic volume in C9orf72 was significantly lower than controls in the −40 to −10 epoch, with the largest effect size of all regions of interest (ROIs) (Extended Data Figure 1 & Table S5).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    As in earlier work, GRN showed the fastest atrophy, with widespread brain involvement within a decade of onset.

    “Also consistent with prior work, the most rapid rates of atrophy occurred in GRN with widespread brain involvement within 10 years of onset.21,22”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In early symptomatic simulations, clinical measures performed well, and CDR+NACC-FTLD-SB as primary outcome gave feasible sample sizes for all three genotypes.

    “Fourth, clinical measures perform very well in the early symptomatic trial simulations, and sample sizes for trials using the CDR®+NACC-FTLD-SB as a primary outcome are feasible for all three genetic groups.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    During symptoms, the fastest longitudinal change versus controls occurred on Trails A and B for C9orf72; Trails A, MINT, and Benson Copy for GRN; and MINT and Trails B for MAPT.

    “Longitudinally, the most rapid change in the symptomatic stage relative to controls was observed for Trails A & B in C9orf72, Trails A, MINT, and Benson Copy in GRN, and the MINT and Trails B in MAPT (Table S4).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For people within 10 years of predicted onset, accuracy is about +/−5.5 years, close to familial age-of-onset estimates used in DIAD but unavailable for most f-FTD syndromes.

    “In subjects estimated to be within 10 years of symptom onset, the accuracy is +/- 5.5 years, which approaches the accuracy of familial age of onset-based estimates which are useful in DIAD,43 but not possible in most f-FTD syndromes.12”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In all groups, neuropsychological deficits versus age-matched controls usually appeared after symptoms, though a few measures were abnormal before onset.

    “Neuropsychological impairments relative to age-matched controls were typically observed after symptom onset in all groups, although abnormalities on a few measures were detected in the presymptomatic stages.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    As prior MRI work found, atrophy was the earliest biomarker change in C9orf72 and MAPT, but in GRN NfL rose a few years before atrophy.

    “Consistent with previous MRI studies demonstrating brain atrophy can be detected in presymptomatic f-FTD,16–19 MRI-measured brain atrophy was the first biomarker to change in C9orf72 and MAPT, but our models revealed that NfL elevations preceded atrophy by a few years in GRN.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    For GRN, NfL started to differ from controls around 15 years before symptom onset, with MRI following 5-10 years before onset.

    “In GRN, visual inspection suggested NfL begins to deviate from controls about 15 years prior to symptom onset, followed by MRI 5–10 years prior to onset (Figures 2, S1).”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    MAPT carriers showed Figure Copy deficits during the −10 to 0 epoch and a trend toward MINT impairment in that epoch.

    “MAPT mutation carriers exhibited impairments in the Figure Copy in the −10 to 0 epoch, with a trend towards impairment on the Multilingual Naming Test (MINT) in this epoch.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    In C9orf72, in the −10 to 0 epoch, the temporal lobe had the largest effect size and was the first ROI to deviate from controls by one SD at DA = −6.1, followed closely by parietal and frontal lobes.

    “In the −10 to 0 epoch, the temporal lobe showed the largest effect size (Extended Data Figure 1), and it was the first ROI to deviate from controls (Table S4; deviated at DA = −6.1, 95%CI:−9.4,−3.2) by one standard deviation (SD), followed closely by parietal (DA = −6.1, 95%CI:−9.2,−3.2) and frontal (DA = −4.9, 95%CI:−7.5,−2.7) lobes.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The FDA has encouraged innovative approaches such as disease progression models for selecting endpoints, enrollment criteria, and analyzing intervention effects in rare neurogenetic diseases.

    “In rare neurogenetic diseases such as f-FTD, the FDA has promoted the use of innovative approaches such as disease progression models (DPM) for selecting clinical trial endpoints, determining enrollment criteria, and analyzing the effects of novel interventions that might lead to deviations from expected disease progression,14”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [14] U.S. Food & Drug Administration. Human Gene Therapy for Neurodegenerative Diseases. Draft Guidance for Industry. FDA-2020-D-2101 (2021).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • May combine two claims.

    Premisecitation

    The age at which f-FTD symptoms begin varies even within a family, which makes it hard to identify people in late presymptomatic stages most likely to benefit from therapy.

    “Also, the age at which symptoms present is variable even within a family (e.g., onset in the thirties vs. seventies in one family),11 making it difficult to identify the individuals in late presymptomatic stages most likely to benefit from therapies.”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [11] Leverenz, J. B. et al. A novel progranulin mutation associated with variable clinical presentation and tau, TDP43 and alpha-synuclein pathology. Brain 130, 1360–1374 (2007). source

  • May combine two claims.

    Study design and conductreasoning

    Informative missing data affects the disease progression models and may bias them toward a smaller standard deviation from normal.

    “Such informative missing data also impacts the DPMs, potentially biasing the models towards a smaller standard deviation from normal; this is a limitation and a direction for future research.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    With FPI's estimated eligible pool and no extra recruitment, a two-year MRI trial seems feasible for GRN, while MAPT would need four years.

    “Based on the estimated number of eligible participants from the FPI dataset (assuming no additional recruitment efforts), two-year trials appear to be feasible for GRN if MRI is used as the outcome, whereas a four-year trial would be required for MAPT.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The number of eligible participants in the FPI dataset, assuming no additional recruitment, represents the pool available for f-FTD prevention trials.
    • Rests on an assumption: The FPI dataset provides a reliable estimate of the number of eligible participants for f-FTD prevention trials.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    The analysis used raw values, and a sensitivity analysis with nuisance covariates produced the same pattern.

    “Raw values were modeled. The same pattern of findings was observed (Figure S5) in a sensitivity analysis adjusting for nuisance covariates (details in online methods).”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationcitation

    The results support earlier suggestions that cognitive changes occur before f-FTD symptoms and that cognitive profiles differ by genotype.

    “These findings add to prior studies suggesting that cognitive changes can be detected in the presymptomatic phases of f-FTD and that there are genotype-specific cognitive profiles.34–37”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    The DPMs are limited by weaker clinical data early in disease and missing data late in disease.

    “The DPMs produced for the current study have additional limitations related to less informative clinical data at early stages of disease and missing data at late stages of disease.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Study design and conductown data

    A voxelwise sensitivity analysis supported the patterns observed using ROIs and indicated that the findings were not dependent on the DPMs.

    “We conducted a voxelwise sensitivity analysis in each DA epoch to complement the coarse-grained ROIs used in the DPMs and to illustrate the findings were not dependent on the DPMs. Results of this sensitivity analysis (Extended Data Figure 2, Figures S2-S4) supported the patterns observed using ROIs.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    Based on eligible participant counts, prevention trials look most feasible for MAPT and GRN, but because C9orf72 is the most common FTD/ALS mutation, the needed sample sizes may still be recruitable.

    “Second, prevention trials appear most feasible for MAPT and GRN relative to the estimated number of eligible participants based on our dataset, however, given that C9orf72 is the most common mutation causing FTD and ALS, recruiting the estimated sample sizes may be feasible.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationcitation

    The findings extend earlier fluid biomarker work indicating that NfL rises early in f-FTD, signals approaching symptoms, and increases fastest in GRN.

    “These results extend previous fluid biomarker studies showing NfL concentrations become elevated early in f-FTD, are harbingers of symptom onset, and rise most rapidly in GRN.25,27,30–32”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Premisecitation

    In symptomatic FTD, NfL is higher in plasma and CSF than in other neurological conditions.

    “We and others have previously shown that NfL concentrations are elevated in the plasma25–27 and CSF28,29 of symptomatic FTD patients compared to other neurological conditions.”
    Quote in the paperNot a substantial claim0 of 2 sources checked
    • cites [25] van der Ende, E. L. et al. Serum neurofilament light chain in genetic frontotemporal dementia: a longitudinal, multicentre cohort study. Lancet Neurol. 18, 1103–1111 (2019). source
    • cites [28] Bridel, C. et al. Diagnostic value of cerebrospinal fluid neurofilament light protein in neurology: a systematic review and meta-analysis. JAMA Neurol. 76, 1035–1048 (2019). source

  • May combine two claims.

    Study design and conductreasoning

    Defining onset as CDR+NACC-FTLD-SB=0.5 meant non-carrier controls all had baseline CDR+NACC-FTLD-SB=0, lowering variance and possibly inflating effect sizes versus measures with more control variance.

    “Because disease onset was defined as CDR®+NACC-FTLD-SB=0.5, non-carrier controls by definition had CDR®+NACC-FTLD-SB=0 at baseline, which reduced the variance in this measure, thereby potentially overestimating the effect size relative to other measures where there was more variance in the controls.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    The smaller samples from DA selection come with fewer eligible people, yet simulations suggest GRN and MAPT trials within five years of predicted onset are feasible given the current dataset's eligible pool.

    “This reduction in sample size must be balanced against the reduction in number of eligible participants (of that DA), but these simulations show that GRN and MAPT trials enrolling presymptomatic participants within five years of estimated onset would be feasible based on the estimated number of eligible participants from our current dataset.”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The number of eligible participants in the FPI dataset, assuming no additional recruitment, represents the pool available for f-FTD prevention trials.
    • Rests on an assumption: The FPI dataset provides a reliable estimate of the number of eligible participants for f-FTD prevention trials.

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    All available data were included in the statistical analyses; complete cases were not required and no imputation was conducted.

    “All available data were included in the statistical analyses. Complete cases were not required, and no imputation was conducted.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    The same image processing steps were performed on ALLFTD and GENFI data.

    “The same image processing steps were performed on ALLFTD and GENFI data.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Interpretationcitation

    The disease progression models will help plan familial frontotemporal dementia clinical trials by aiding selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.

    “In conclusion, these DPMs will facilitate the planning of f-FTD clinical trials, including selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.14”
    Quote in the paperSubstantial claim0 of 1 sources checked
    • cites [14] U.S. Food & Drug Administration. Human Gene Therapy for Neurodegenerative Diseases. Draft Guidance for Industry. FDA-2020-D-2101 (2021).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Classified as probably not a substantial claim.

    Interpretationreasoning

    The disease progression models provide a roadmap for developing new biomarkers and clinical endpoints that may improve power to detect effects in presymptomatic stages of disease.

    “and provide a roadmap for development of new biomarkers and clinical endpoints that may improve power to detect effects in presymptomatic stages of disease”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    A standard imaging protocol was used across all centers and was managed and reviewed for quality by a core group at the Mayo Clinic, Rochester.

    “A standard imaging protocol was used across all centers, managed, and reviewed for quality by a core group at the Mayo Clinic, Rochester.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    Before preprocessing, all T1-weighted images were visually inspected for quality control, and images with excessive motion or artifact were excluded.

    “Before any prepossessing of the images, all T1-weighted images were visually inspected for quality control. Images with excessive motion or image artifact were excluded.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Across all neurofilament light assays, the percent coefficient of variation of the mean neurofilament light concentration for inter-assay controls was below 10%.

    “Across all assays, the percent coefficient of variations of the mean NfL concentration for the inter-assay controls were below 10%.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Multiple comparisons were controlled for using the Tukey method.

    “Multiple comparisons were controlled for using the Tukey method.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductreasoning

    W-scores represent gray matter content as the number of standard deviations from the expected mean for a reference group, accounting for total intracranial volume and scanner platform.

    “Therefore, the W-score represents the gray matter content at that voxel as the number of standard deviations away from the expected mean for a reference group, accounting for TIV and scanner platform.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    Results from the disease progression model can be used to create evidence-based assumptions about rates of progression and variability of progression of each endpoint for a target population.

    “Results from the disease progression model can be used to create evidence-based assumptions about rates of progression and variability of progression of each endpoint for a target population.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Every step of the transformation from native space to the group template was carefully inspected.

    “Every step of the transformation was carefully inspected from the native space to the group template.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductnone given

    All scans were quality checked and those with movement or artifacts were removed.

    “All scans were quality checked and those with movements or artifacts were removed.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    All GENFI neurofilament light samples were quantifiable within the dynamic range of 0.69 to 2,000 pg/mL and had an average coefficient of variation below 10%.

    “All samples were quantifiable within the dynamic range of 0.69 to 2,000 pg/mL and with an average coefficient of variation below 10%.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Instrument operators were blinded to clinical and genetic information.

    “Instrument operators were blinded to clinical and genetic information.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Participants with moderate to severe vascular disease or other brain lesions were excluded from the analysis.

    “Furthermore, if any participants displayed moderate to severe vascular disease or any other brain lesions, they were also excluded from the analysis.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    Visual inspection suggested sufficient alignment between disease progression of all endpoints across the two consortia, and subsequent models combined both cohorts in a single analysis.

    “Visual inspection suggested sufficient alignment between disease progression of all endpoints across the two consortia and subsequent models combined both cohorts within a single analysis.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    All neurofilament light assays included five inter-assay controls in addition to the two kit quality control samples.

    “In addition to the two quality control samples provided with the kit, all assays included five inter-assay controls.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductnone given

    GENFI neurofilament light measures were completed in duplicate over six batches, each with an eight-point calibration curve tested in triplicate and two controls tested in duplicate.

    “Measures were completed in duplicate over a total of six batches, each with an eight-point calibration curve tested in triplicate and two controls tested in duplicate.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Plasma neurofilament light samples were tested in duplicate using kits from the same lot.

    “Samples were tested in duplicate using kits from the same lot.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).

    Interpretationnone given

    This study is the first comprehensive effort to combine clinical, imaging, and plasma biomarker data across consortia.

    “This study is the first comprehensive effort to combine clinical, imaging, and plasma biomarker data across consortia.”
    Quote in the paperNot a substantial claim
66 of 66

  • The authors state this as an assumption.

    The number of eligible participants in the FPI dataset, assuming no additional recruitment, represents the pool available for f-FTD prevention trials.

    “assuming no additional recruitment efforts”

  • The authors state this as an assumption.

    Abnormal global status in controls may reflect other brain pathologies that could obscure important findings.

    “Because abnormal global status may reflect other brain pathologies in the controls that could potentially obscure important findings, we believe that the requirement for CDR®+NACC-FTLD-SB=0 in controls was appropriate.”

  • The paper relies on this without support.

    The FPI dataset provides a reliable estimate of the number of eligible participants for f-FTD prevention trials.

    “Based on the estimated number of eligible participants from the FPI dataset”
3 of 3

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • MAPT atrophy is dated to both 10 and 15 years before onset

    Minor

    The Results place the first divergence of medial temporal atrophy in MAPT at approximately 10 years before symptoms, while the Discussion says this study detected it 15 years before onset. The two accounts give different timings for the same reported finding.

1 of 1

Cites

Flagged first, then by citations

12 of the 75 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Related

Authors
Staffaroni, A. M., Quintana, M., Wendelberger, B., Heuer, H. W., Russell, L. L., Cobigo, Y., Wolf, A., Goh, S.-Y. M., Petrucelli, L., Gendron, T. F., Heller, C., Clark, A. L., Taylor, J. C., Wise, A., Ong, E., Forsberg, L., Brushaber, D., Rojas, J. C., VandeVrede, L., Ljubenkov, P., Kramer, J., Casaletto, K. B., Appleby, B., Bordelon, Y., Botha, H., Dickerson, B. C., Domoto-Reilly, K., Fields, J. A., Foroud, T., Gavrilova, R., Geschwind, D., Ghoshal, N., Goldman, J., Graff-Radford, J., Graff-Radford, N., Grossman, M., Hall, M. G. H., Hsiung, G.-Y., Huey, E. D., Irwin, D., Jones, D. T., Kantarci, K., Kaufer, D., Knopman, D., Kremers, W., Lago, A. L., Lapid, M. I., Litvan, I., Lucente, D., Mackenzie, I. R., Mendez, M. F., Mester, C., Miller, B. L., Onyike, C. U., Rademakers, R., Ramanan, V. K., Ramos, E. M., Rao, M., Rascovsky, K., Rankin, K. P., Roberson, E. D., Savica, R., Tartaglia, M. C., Weintraub, S., Wong, B., Cash, D. M., Bouzigues, A., Swift, I. J., Peakman, G., Bocchetta, M., Todd, E. G., Convery, R. S., Rowe, J. B., Borroni, B., Galimberti, D., Tiraboschi, P., Masellis, M., Finger, E., van Swieten, J. C., Seelaar, H., Jiskoot, L. C., Sorbi, S., Butler, C. R., Graff, C., Gerhard, A., Langheinrich, T., Laforce, R., Sanchez-Valle, R., de Mendonça, A., Moreno, F., Synofzik, M., Vandenberghe, R., Ducharme, S., Le Ber, I., Levin, J., Danek, A., Otto, M., Pasquier, F., Santana, I., Kornak, J., Boeve, B. F., Rosen, H. J., Rohrer, J. D., Boxer, A. L., Frontotemporal Dementia Prevention Initiative (FPI) Investigators, ALLFTD Investigators, Apostolova, L., Barmada, S., Boeve, B., Boxer, A. L., Bozoki, A., Clark, D., Coppola, G., Darby, R., Dickson, D., Faber, K., Fagan, A., Galasko, D. R., Grant, I. M., Huang, E., Kerwin, D., Lapid, M., Lee, S., Leger, G., Masdeux, J. C., McGinnis, S., Mendez, M., Onyike, C., Pascual, M. B., Pressman, P., Rademakers, R., Ramanan, V., Ritter, A., Seeley, W. W., Syrjanen, J., Taylor, J. C., Weintraub, S., GENFI Investigators, Esteve, A. S., Nelson, A., Greaves, C. V., Thomas, D. L., Benotmane, H., Zetterberg, H., Nicholas, J., Samra, K., Shafei, R., Timberlake, C., Cope, T., Rittman, T., Benussi, A., Premi, E., Gasparotti, R., Archetti, S., Gazzina, S., Cantoni, V., Arighi, A., Fenoglio, C., Scarpini, E., Fumagalli, G., Borracci, V., Rossi, G., Giaccone, G., Di Fede, G., Caroppo, P., Prioni, S., Redaelli, V., Tang-Wai, D., Rogaeva, E., Castelo-Branco, M., Freedman, M., Keren, R., Black, S., Mitchell, S., Shoesmith, C., Bartha, R., Poos, J., Papma, J. M., Giannini, L., van Minkelen, R., Pijnenburg, Y., Nacmias, B., Ferrari, C., Polito, C., Lombardi, G., Bessi, V., Veldsman, M., Andersson, C., Thonberg, H., Öijerstedt, L., Jelic, V., Thompson, P., Lladó, A., Antonell, A., Olives, J., Balasa, M., Bargalló, N., Borrego-Ecija, S., Verdelho, A., Maruta, C., Ferreira, C. B., Miltenberger, G., Simões do Couto, F., Gabilondo, A., Gorostidi, A., Villanua, J., Cañada, M., Tainta, M., Zulaica, M., Barandiaran, M., Alves, P., Bender, B., Wilke, C., Graf, L., Vogels, A., Vandenbulcke, M., Van Damme, P., Bruffaerts, R., Poesen, K., Rosa-Neto, P., Gauthier, S., Camuzat, A., Brice, A., Bertrand, A., Funkiewiez, A., Rinaldi, D., Saracino, D., Colliot, O., Sayah, S., Prix, C., Wlasich, E., Wagemann, O., Loosli, S., Schönecker, S., Hoegen, T., Lombardi, J., Anderl-Straub, S., Rollin, A., Kuchcinski, G., Bertoux, M., Lebouvier, T., Deramecourt, V., Santiago, B., Duro, D., Leitão, M. J., Almeida, M. R., Tábuas-Pereira, M., & Afonso, S.
Affiliations
  • University of California, San Francisco (US)
  • Berry Consultants, LLC (United States) (US)
  • National Hospital for Neurology and Neurosurgery (GB)
  • Mayo Clinic in Florida (US)
  • Mayo Clinic (US)
  • Case Western Reserve University (US)
  • University of California, Los Angeles (US)
  • Harvard University (US)
  • Indiana University School of Medicine (US)
  • Washington University in St. Louis (US)
  • Columbia University (US)
  • University of Pennsylvania (US)
  • University of British Columbia (CA)
  • University of North Carolina at Chapel Hill (US)
  • University of California San Diego (US)
  • University of Alabama at Birmingham (US)
  • University of Toronto (CA)
  • MRC Cognition and Brain Sciences Unit (GB)
  • University of Brescia (IT)
  • University of Milan (IT)
  • Fondazione IRCCS Istituto Neurologico Carlo Besta (IT)
  • Sunnybrook Health Science Centre (CA)
  • Western University (CA)
  • Erasmus MC (NL)
  • Don Carlo Gnocchi Foundation (IT)
  • Karolinska University Hospital (SE)
  • University of Manchester (GB)
  • Salford Royal NHS Foundation Trust (GB)
  • Centre hospitalier universitaire de Québec (CA)
  • German Center for Neurodegenerative Diseases (DE)
  • Universitair Ziekenhuis Leuven (BE)
  • Montreal Neurological Institute and Hospital (CA)
  • Munich Cluster for Systems Neurology (DE)
  • Ludwig-Maximilians-Universität München (DE)
  • Universität Ulm (DE)
  • Inserm (FR)
  • Unidade Local de Saúde de Coimbra (PT)
  • Indiana University Indianapolis (US)
  • University of Michigan (US)
  • Vanderbilt University (US)
  • Northwestern University (US)
  • Houston Methodist (US)
  • Cleveland Clinic (US)
  • UK Dementia Research Institute (GB)
  • London School of Hygiene & Tropical Medicine (GB)
  • Azienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia (IT)
  • Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico (IT)
  • University Health Network (CA)
  • Amsterdam University Medical Centers (NL)
  • University of Florence (IT)
  • University of Oxford (GB)
  • Karolinska Institutet (SE)
  • Hospital Clínic de Barcelona (ES)
  • University of Lisbon (PT)
  • Donostiako Unibertsitate Ospitalea (ES)
  • Biogipuzkoa Health Research Institute (ES)
  • University of Tübingen (DE)
  • University of Antwerp (BE)
  • Centre National de la Recherche Scientifique (FR)
  • LabEx DISTALZ (FR)
  • Université de Lille (FR)
  • Centro de Neurociências e Biologia Celular (PT)
Corresponding author
Staffaroni, Adam M.
ORCID
Venue
Nature Medicine
Publisher
Springer Science and Business Media LLC
Published
2022-09-22
Volume
28
Issue
10
Pages
2194-2206
ISSN
  • 1078-8956 (ISSN-L)
  • 1546-170X
DOI
10.1038/s41591-022-01942-9
PMC
PMC9951811
OpenAlex
W4296690345
Cited by
140
References
75
Citations by year
2026: 29 · 2025: 44 · 2024: 39 · 2023: 26 · 2022: 2
FWCI
18.09
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Medicine (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Brunel University Research Archive (BURA) (Brunel University London) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • IUScholarWorks (Indiana University) (submittedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • HAL (submittedVersion)
  • ArTS Archivio della ricerca di Trieste (University of Trieste https://www.units.it/) (submittedVersion)
  • UCL Discovery (University College London) (submittedVersion)
  • Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion)
  • Florence Research (University of Florence) (submittedVersion, other-oa)
  • Institutional Research Information System (Università degli Studi di Brescia) (submittedVersion)
  • Institutional Research Information System (Università degli Studi di Trento) (submittedVersion, other-oa)
  • Lirias (KU Leuven) (submittedVersion)
  • DZNE Pub (submittedVersion)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
Funders
  • U.S. Department of Defense
  • Alzheimer's Association (U24AG021886, P30 AG062422)
  • Larry L. Hillblom Foundation (2018-A-025-FEL)
  • National Ataxia Foundation
  • Bristol-Myers Squibb
  • Association for Frontotemporal Degeneration
  • Eli Lilly and Company
  • Pfizer
  • AstraZeneca
  • Novartis
  • Biogen
  • Teva Pharmaceutical Industries
  • Vanderbilt University
  • University of Pennsylvania
  • Northwestern University
  • Cleveland Clinic
  • University of Washington
  • Université Laval
  • Johns Hopkins University
  • University of Texas Southwestern Medical Center
  • CurePSP
  • McGill University
  • Fondation Brain Canada
  • London School of Hygiene and Tropical Medicine
  • University Health Network
  • Wellcome Trust (220258, BRC-1215-20014, 220258/Z/20/Z)
  • Sunnybrook Research Institute
  • Università degli Studi di Milano
  • Weston Brain Institute
  • EU Joint Programme – Neurodegenerative Disease Research (2019-02248, 739510)
  • Ionis Pharmaceuticals
  • Brain Research UK (202021-32)
  • Buck Institute for Research on Aging
  • ACADIA Pharmaceuticals
  • Global Brain Health Institute
  • Université de Lille
  • National Brain Appeal (290173, RCN 290173)
  • Rainwater Charitable Foundation
  • Alzheimer's Society (AS-JF-19a-004-517)
  • Puma Biotechnology
  • TauRx Pharmaceuticals
  • National Institute for Health and Care Research (BRC1215-20014, BRC149/NS/MH, CL-2018-14-007)
  • Department of Health and Social Care
  • University of Cambridge (BRC-1215-20014)
  • Imperial College London
  • University College London
  • University of Oxford
  • Wolfson Foundation (20143810)
  • Deutsche Forschungsgemeinschaft (EXC 2145, EXC 2145SyNergy, 774/5‐1, 390857198, SCHR 774/5‐1)
  • Agence Nationale de la Recherche (ANR-11-LABX-0009)
  • Institut National de la Santé et de la Recherche Médicale
  • Toronto Rehabilitation Institute
  • Eberhard Karls Universität Tübingen
  • Bundesministerium für Bildung und Forschung (FKZ O1GI1007A, O1GI1007A)
  • Cambridge University Hospitals
  • Ministero della Salute (2018-)
  • University of Toronto
  • Eisai
  • KU Leuven
  • Karolinska Institutet
  • Stockholms Läns Landsting
  • Vetenskapsrådet (2018-, 2015-02926, 2018-02754)
  • Università degli Studi di Firenze
  • Centre National de la Recherche Scientifique
  • Deutsches Zentrum für Neurodegenerative Erkrankungen
  • Universidade de Coimbra
  • Göteborgs Universitet
  • Universidade de Lisboa
  • Universitat de Barcelona
  • Università degli Studi di Brescia
  • Universiteit Antwerpen
  • Fondazione I.R.C.C.S. Istituto Neurologico Carlo Besta
  • Universität Ulm
  • H. Lundbeck A/S
  • FONDATION ALZHEIMER
  • UK Dementia Research Institute
  • Sorbonne Université
  • National Institutes of Health (1r21ns114764-01a1, AG016976, AG019724, AG063911, AG062677, NS092089)
  • Genentech
  • University of California, Los Angeles
  • University of North Carolina at Chapel Hill
  • University of California, San Diego
  • University of California, San Francisco (AG019724)
  • Parkinsonfonden
  • School of Medicine, Indiana University
  • Faculté de Médecine, Université Laval
  • Houston Methodist Research Institute
  • Bayer Vital
  • Tau Consortium
  • Canadian Institutes of Health Research (20143810, 175242_1)
  • Medical Research Council (SUAG092 G116768, MR/M023664/1, G116768, MR/T046015/1, MR/M008525/1, MR/K010395/1, BRC-1215-20014)
  • Instituto de Salud Carlos III (20143810, PI20/00448)
  • Sahlgrenska Akademin
  • Robarts Research Institute
  • NIHR Cambridge Biomedical Research Centre ((BRC-1215-20014), BRC149/NS/MH)
  • National Institute on Aging (AG032306, AG 016976, R01AG058233, R01AG029577, K23AG059888, AG058233, U01AG016976, K23AG061253, RF1AG029577, L30 AG069301, NS092089, U01AG045390, R01AG032306, AG019724, AG062422, AG045390, AG021886, K24AG045333, R01AG038791, AG038791, U19AG063911, P01AG019724, P30AG062422, K23AG073514, P30AG062677, P30AG066509, U24AG072122, P30AG072977, U24AG021886)
  • National Institute of Neurological Disorders and Stroke (U01NS080818, U54NS092089, R25NS098999, U01NS100610)
  • National Center for Advancing Translational Sciences
  • Janssen Pharmaceuticals
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12HD001459)
  • David Geffen School of Medicine, University of California, Los Angeles
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Health Sciences › Medicine › Neurology › Amyotrophic Lateral Sclerosis Research
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
Keywords
familial frontotemporal dementia, presymptomatic mutation carriers, C9orf72, gene regulatory networks, MAPT, neurofilament light chain, brain atrophy, disease progression modeling, prevention trials, sample size determination, biomarkers, neuropsychological decline
MeSH terms
C9orf72 Protein, Clinical Trials as Topic, Humans, Mutation, Biomarkers, tau Proteins, Disease Progression, Frontotemporal Dementia

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read under definition version 3 (extract-v3) on 2026-09-28.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-09-28.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review