Genetic forms of frontotemporal dementia (gFTD) are rare but devastating conditions, with the most prevalent mutations occurring in genes C9ORF72, GRN or MAPT. Clinical manifestations can be highly variable, particularly in those with expansions of the C9ORF72 gene. Crucial to the development and trialling of any novel disease-modifying therapy is the ability to accurately and objectively stage the condition of interest. Defining the clinical stages of FTD is challenging, in particular pinning down the exact point of clinical symptom onset. This impacts our ability to provide accurate prognostic advice to mutation carriers and on clinical trials of novel therapies.
Brain structural changes in frontotemporal dementia (FTD) can occur decades before symptom onset. Precise characterisation of grey matter changes is necessary for developing models of biomarker progression, while better understanding the trajectory of the pathology is invaluable for prognosis and detecting treatment effects as we enter the era of clinical trials.
Cortical and subcortical grey matter volume and thickness from structural MRI were assessed in a large cohort of 892 participants including presymptomatic and symptomatic carriers of mutations within the three main genetic causes of FTD (C9 open reading-frame 72 (C9orf72), progranulin (GRN) and microtubule-associated protein tau (MAPT)) compared with mutation-negative relatives (controls). We compared the distribution of grey matter changes of each metric at different stages of the disease cross sectionally. We aimed to identify grey matter composites for each genetic group which would show the earliest changes and which separated presymptomatic carriers from controls.
While C9orf72 mutation carriers showed widespread presymptomatic grey matter changes, MAPT and particularly GRN mutation carriers showed changes more proximally to symptom onset. Our composite grey matter signatures, which discriminate asymptomatic/prodromal carriers from controls with high to very high areas under the curve, involved bilateral thalami volumes, precuneus and postcentral thickness in C9orf72; left caudal middle frontal thickness, frontal pole and pars orbitalis volumes in GRN; right temporal pole volume and left insula thickness in MAPT mutation carriers.
We propose the use of cortical thickness and volume measurements combined from multiple regions into a composite region of interest for each FTD genetic group to identify the earliest changes and track disease progression. Our quasi-longitudinal design illustrates that these regions continue to evolve throughout the symptomatic stages. Investigating how our selected composites progress and validating these in longitudinal samples will be invaluable for future clinical trials.
Brain atrophy is increasingly used as an outcome measure in clinical trials in relapsing-remitting multiple sclerosis (RRMS), but little is known about how chronological age interacts with MS-specific effects. For instance, while annual brain atrophy rates typically increase with age in healthy individuals, MS patients tend to exhibit decreasing atrophy rates over time.
We investigated the relationship between age and brain volume in a large dataset of 4241 trial participants with RRMS. We used pooled individual-participant data from phase 3 clinical trials with 96 weeks follow-up, which included both active treatment and placebo/comparator arms. Participants were categorised into seven groups based on chronological age (18–24 years, 25–30 years, 31–35 years, 36–40 years, 41–45 years, 46–50 years, 51–56 years). We performed multilevel linear mixed-effects regression analyses to examine differences between age groups in normalised whole brain volume (NWBV), thalamus grey matter volume (NThGMV), grey matter volume (NGMV) and white matter volume at baseline and their changes over follow-up. We also studied how disease duration influenced these relationships using similar models.
Older participants showed significantly lower NWBV, NGMV and NThGMV at baseline than younger participants. Most importantly, older participants exhibited lower rates of atrophy during follow-up, particularly in the thalamus. This association was consistent across all disease duration subgroups.
Older participants had more severe atrophy when enrolled into trials, but slower (thalamic) atrophy rates, independent of disease duration over time. Together, these findings emphasise that age should be taken into account when designing clinical trials that use brain atrophy as an outcome measure.
This Tysabri Observational Program (TOP) final analysis evaluated the 15-year safety and effectiveness of natalizumab treatment in patients with relapsing-remitting multiple sclerosis (RRMS).
This multinational, real-world observational study assessed natalizumab-associated serious adverse events, annualised relapse rates (ARRs) and disability progression/improvement in patients with RRMS. These outcomes were evaluated in subpopulations receiving short- (1–2 years) versus long-term (≥10 years) natalizumab and in patients who switched from intravenous to subcutaneous (SC) natalizumab formulation. The probability of conversion to non-active secondary progressive multiple sclerosis (SPMS) was assessed in patients who remained on versus discontinued natalizumab after ≥1 year.
As of November 2023, TOP enrolled 6319 patients. Median time on natalizumab was 4.13 years. There were no new safety signals after up to 15 years of treatment. Marked, sustained reductions in pretreatment ARR occurred with natalizumab independent of baseline disease indicators (eg, Expanded Disability Status Scale score). On natalizumab, the ARR decreased by 91.5% after 15 years, relative to the year before baseline. At 15.5 years, cumulative probabilities of 24-week confirmed disability progression and improvement were 48.5% and 38.8%, respectively. Long-term natalizumab treatment significantly decreased ARR compared with short-term treatment. Switching from intravenous to SC formulation did not affect ARR after 1 year post-switch. The cumulative probability of converting to non-active SPMS was significantly lower in patients remaining on natalizumab compared with those who discontinued (0.22 vs 0.29, respectively).
Follow-up of over 15 years did not reveal new safety concerns and confirmed sustained real-world effectiveness of natalizumab in patients with RRMS (NCT00493298).
Increased healthcare use precedes classical multiple sclerosis (MS) symptom onset. Limited evidence exists on sex and age variation. We assessed physician visit patterns pre-MS onset by sex and age.
Using data from British Columbia, Canada, we compared annual physician visit rates (overall, by reason and specialty) in the 15 years before the neurologist-determined MS symptom onset date (index) and a matched non-MS cohort, stratified by sex and age (<30, 30–49, ≥50).
We included 2038 MS and 10 182 non-MS persons (74% female). Mean age (years) at index was 37.6 (females) and 38.7 (males). Compared with matched non-MS persons, females with MS showed earlier and more consistent elevations in physician visits (years –14 to –1), while males had sporadic elevations (years –5, –3 and –1). Females also had longer periods of elevated rate ratios (RRs) for ill-defined signs/symptoms (years –15 to –1), mental disorders (years –14 to –1 except year –7) and musculoskeletal conditions (years –6 to –1). Females exhibited sustained elevated visits by specialty, including general practice (all years; RR ≥1.1), psychiatry (years –12 to –1 except –8 to –6; RRs ≥1.6) and ophthalmology (years –9 to –1 except –2; RRs ≥1.4). Compared with matched non-MS counterparts, those aged 30–49 years had sustained higher RRs for psychiatry visits (years –12 to –1 except –8 and –6; RRs ≥1.9) and ophthalmology (years –9 to –1; RRs ≥1.4). Other age groups had fewer elevated RRs preindex. Across comparisons, RRs were of similar magnitude across sex and age groups.
Sex-specific and age-specific differences in physician visits extended up to 15 years pre-MS onset, suggesting a durable prodromal signature, most evident in females and those aged 30–49 years.
Multiple sclerosis (MS) shows marked geographic and ethnic variation, but the contribution of migration status and region of origin to long-term outcomes remains uncertain. We aimed to examine disability, cognitive and patient-reported outcomes across these dimensions.
We analysed 4008 individuals with incident relapsing-onset MS from two nationwide Swedish case-control studies (2005–2019), with registry-based follow-up through April 2022. Repeated measures of expanded disability status scale (EDSS), symbol digit modalities test (SDMT) and MS impact scale (MSIS-29) were obtained prospectively. Cox regression compared outcomes by migration status (Swedish-born with Swedish parents, first-generation immigrants, Swedish-born with immigrant parent/s) and region of origin (Sweden, Nordic countries, non-Nordic Europe, Middle East and North Africa (MENA) and other).
Compared with Swedish-born individuals with Swedish parents, first-generation immigrants had higher risks of confirmed disease worsening (CDW) (HR 1.36, 95% CI 1.18 to 1.56) and reaching EDSS 3 (HR 1.25, 95% CI 1.03 to 1.52), whereas Swedish-born individuals with immigrant parents did not differ from the reference group. By region of origin, participants of MENA origin had higher risks of CDW (HR 1.45, 95% CI 1.15 to 1.82), EDSS 3 (HR 1.46, 95% CI 1.07 to 2.00), EDSS 4 (HR 1.82, 95% CI 1.19 to 2.80), SDMT worsening (HR 1.79, 95% CI 1.26 to 2.51) and MSIS-29 worsening.
Within a universal-access health system, first-generation immigration into Sweden was associated with faster disability progression, and MENA origin showed consistent excess risks across disability, cognitive and patient-reported outcomes. The overall pattern points to a combination of migration-related and origin-linked influences on MS progression, supporting early risk stratification and culturally adapted care strategies.
Early after stroke, the upper limb is impaired in ~50% of patients who had a stroke, posing a significant and restrictive challenge to their daily lives. It is unknown how many subacute stroke patients regain good upper limb use in everyday life (ie, performance) during inpatient neurorehabilitation and which clinical and stroke-related neuroanatomical factors are associated with recovery. This study explores these questions using real-world clinical data.
Analysis of data prospectively collected on a weekly basis in the clinical routine of patients who had a subacute stroke admitted to a Swiss inpatient neurorehabilitation centre (January 2016–October 2023). Multivariable logistic regression was applied to determine predictors for return of good upper limb performance. Voxel-based lesion symptom mapping (VLSM) was used to determine neuroanatomical correlates for successful return.
794 out of 1169 patients who had a stroke (67.9%) did not have a good upper limb performance at a median of 8 days poststroke. Of these, 394 (49.6%) regained good upper limb performance during the subsequent 36 (quartile 1=27, quartile 3=52.75) days. Multivariable logistic regression showed that a younger age, fewer neglect symptoms and better dexterity, stereognosis and general cognition were associated with regaining good upper limb performance. VLSM revealed that less stroke-related injury in the corticospinal tract, right hemispheric attention networks, superior longitudinal fasciculus II and III, insula and putamen was associated with return of good outcome.
These findings underline that in addition to sensorimotor functioning and intact motor tracts, cognitive functioning and spared attentional networks are essential for recovery of everyday use of the affected upper limb after stroke.
We aimed to evaluate the impact of implementing an artificial intelligence (AI)-enabled acute ischaemic stroke triage system on workflow efficiency and transfer optimisation in a large academic healthcare network.
A prospectively maintained database was reviewed comparing equivalent time periods before and after AI-enabled triage platform implementation (January 2021–December 2022). The primary analysis compared workflow metrics between AI-enabled and non-AI spokes during the same calendar period (2022) to control for temporal confounding. Benjamini-Hochberg correction was applied for multiple comparisons, and analyses were adjusted for age and baseline National Institutes of Health Stroke Scale. Evaluated outcomes included door-in-door-out (DIDO) times, door-to-puncture (DTP) times, endovascular therapy (EVT) utilisation rates, cost analysis and clinical outcomes at discharge.
The study included 4548 admissions with 844 EVT patients (394 pre-implementation, 450 post-implementation) across four hub centres. In the primary same-period analysis (2022), AI-enabled spokes demonstrated significantly shorter DIDO times compared with non-AI spokes (median 103 (92–118) vs 134 (103–162) min; adjusted difference –41.6 min (95% CI –60.9 to –24.1); p<0.001, Q<0.001) and shorter DTP times (21 (14–43) vs 40 (18–65) min; adjusted difference –10.9 min (95% CI –17.9 to –3.7); p=0.003, Q=0.009). A difference-in-differences analysis demonstrated that DIDO improvements were specific to AI-enabled spokes (–27 min; 95% CI –62 to –4; p=0.029). EVT utilisation was also significantly higher in AI-enabled versus non-AI spokes where AI-enabled spokes had increased EVT rates by +17.8% (39.3% to 57.1%) compared with +1.1% in non-AI spokes (41.3% to 42.4%, Pinteraction=0.006). DTP improvements were more pronounced at community hubs (86 (48–108) to 51 (22–77) min; adjusted difference –24.9 min; p=0.021, Q=0.041) compared with academic hubs (60 (23–87) to 55 (22–73) min; adjusted difference –15.5 min; p<0.001, Q=0.002). Subgroup analyses demonstrated consistent DIDO benefits across age, stroke severity and sex strata with no significant treatment effect heterogeneity (all P-interaction >0.05). Probabilistic cost analysis estimated savings of $3.6 million (95% CI $1.5M to $6.1M) per 1000 AI-enabled spoke transfers. Clinical outcomes, including functional status and mortality at discharge, were similar between groups (all Q>0.05).
Implementation of an AI-enabled triage platform was associated with significant reductions in workflow times and increased EVT utilisation, with effects specific to AI-enabled spokes rather than secular trends alone. The proportion of transfers who did not proceed to EVT decreased in AI-enabled spokes, though counterfactual outcomes for non-transferred patients remain unknown. Clinical outcomes at discharge were unchanged.
The relevance of covert cerebrovascular disease (CCD) in practice is uncertain, partly because estimation of risk in whole clinical populations is difficult. Studies have had success extracting CCD from clinical text using natural language processing (NLP), though they have been limited to specific CCD phenotypes. Here, we used NLP to measure multiple clinically-reported CCD phenotypes in a large clinical cohort and estimated subsequent disease risk in health record data.
From all people with brain imaging in Scotland (2010–2018), we selected people with no prior hospitalisation for neurological disease (n=367 988). NLP of imaging reports identified: white matter hypoattenuation or hyperintensities (WMH), lacunes, cortical infarcts and cerebral atrophy. Adjusted HRs (aHRs) were estimated between each phenotype and stroke, dementia and Parkinson’s disease (conditions previously associated with CCD), epilepsy and colorectal cancer (control conditions).
For each phenotype, the aHR of stroke was WMH 1.4 (95% CI 1.3–1.4), lacunes 1.6 (1.5–1.6), cortical infarct 1.8 (1.7–1.9) and cerebral atrophy 1.1 (1.0–1.1). The aHR of dementia was WMH 1.3 (1.3–1.3), lacunes 1.0 (0.9–1.0), cortical infarct 1.1 (1.1–1.2) and cerebral atrophy 1.7 (1.7–1.8). The aHR of Parkinson’s disease was WMH 1.1 (1.0–1.2), lacunes 1.1 (0.9–1.2), cortical infarct 0.7 (0.6–0.9) and cerebral atrophy 1.4 (1.3–1.5). The aHRs between CCD phenotypes and epilepsy and colorectal cancer were around the null.
CCD and atrophy have implications for future disease risk and can be identified at scale using NLP of clinical reports. Prevention of neurological disease in people with CCD should be a priority for healthcare policy makers.
Despite advances in epilepsy surgery, seizure freedom is achieved in only ~50–70% of cases, highlighting the need to better understand factors driving surgical success.
A preregistered systematic review and individual patient data meta-analysis was conducted on studies reporting clinical outcomes in epilepsy surgery, based on a comprehensive literature search through August 2024. Data were extracted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Unique patient data from 385 studies were pooled, yielding 5588 patients with outcomes, localisation, demographics, pathology and other findings. Surgical success rates (% Engel 1/ILAE 1–2) were reported with 95% Wald CIs. Associations with patient- and disease-specific factors were assessed using chi-squared tests (p<0.05), effect sizes with Cramer’s V, and post hoc comparisons adjusted using the false discovery rate.
Surgical success varied by lobar anatomy (²=52, p<0.001, V=0.12), with the highest success rates in temporal (68.6% (67.0% to 70.1%)) and insular lobes (66.2% (55.4% to 77.0%)). Multilobar resections had lower success rates, with outcomes varying by lobar combination (²=25, p=0.02, V=0.22). Variability in outcomes was influenced by histopathology and MRI findings (²=121, p<0.001, V=0.16; highest success in tumours (78.2% (74.9% to 81.6%))) and by surgical intervention (²=30.5, p<0.001, V=0.07; lowest success with corpus callosotomy (43.4% (35.4% to 51.5%))). Overall surgical success rates remained stable over time (r=0.25, p=0.13), despite surgery being extended to more complex patients.
These findings inform surgical planning for drug-resistant epilepsy, emphasising individual patient characteristics to guide personalised treatment, improve outcomes and reflect the growing complexity of intersecting factors.
CRD42024530397.
Apathy, depression and anhedonia are clinically overlapping constructs, which hinders diagnostic clarity and treatment development. This study aimed to comprehensively characterise these syndromes to identify a core set of non-redundant symptoms that maximally dissociate them and to investigate the psychological nature of key distinguishing features.
Data from seven datasets (N=4578) of healthy individuals and patients with major depressive disorder were analysed using the Apathy Motivation Index, Beck Depression Inventory and Snaith-Hamilton Pleasure Scale. A machine-learning algorithm identified the most informative, non-redundant items for dissociating ‘pure’ apathy, depression and anhedonia. The nature of emotional apathy was further investigated with follow-up studies.
Although substantial symptom overlap existed, ‘pure’ syndromes were present. Factor analysis revealed a robust five-factor structure, separating depression, anhedonia and three distinct apathy domains (behavioural, social and emotional). Machine learning identified 10 core symptoms that differentiated the pure syndromes with high accuracy (area under the curve >0.90) and could also identify well the presence of each syndrome in individuals suffering from two or more syndromes. Emotional apathy negatively correlated with depression and was specifically associated with reduced affective empathy and a diminished sensitivity to the intensity of negative facial emotions, rather than with alexithymia or antidepressant-induced emotional blunting.
Apathy, depression and anhedonia are dissociable constructs with distinct symptom signatures. Emotional apathy is a unique dimension which provides a novel target for research. A 10-item Apathy-Depression-Anhedonia Measure developed here provides a pragmatic tool for rapid, precise phenotyping to guide more personalised therapeutic strategies.
Recent revisions of Alzheimer’s Disease (AD) definitions by two leading research groups—the Alzheimer’s Association and the International Working Group—reflect divergent approaches: the former promotes a strictly biological definition, while the latter promotes a clinicalbiological construct. We contend that this emerging controversy is not merely semantic, but scientifically, clinically, and politically significant. Drawing on philosophical tools and situating the current debate within a broader historical context from the reconceptualization of AD in the 1970s onwards, we explore how definitions can serve as transformative instruments, acting as strategic bets that reshape scientific fields and clinical practices. Ultimately, we draw from the AD case study to argue for a critical reflection on the risks and promises of such definitional acts. We also propose a renewed attention to the 'ethics of stipulating' in the field of contemporary biomedical sciences.
In response to advances in diagnostics and therapeutics, two...]]>