Biology subjects

Synofzik, M.

Publications and source records attributed to Synofzik, M..

At least 19 recordsLinked to original sources

bioRxiv2026

Machine-learning MRI stratification of genetic frontotemporal dementia for clinical trial enrichment

BACKGROUNDGenetic frontotemporal dementia (FTD) shows large differences in symptom profiles, brain atrophy patterns, and progression rate, making clinical trials difficult to design and power. There is a need for biomarkers that can model disease progression, identify biologically distinct groups, and support efficient trial enrichment. METHODSWe applied contrastive trajectory inference (cTI), a machine-learning method, to structural MRI, white matter hyperintensity, and demographic data from 736 participants in the GENFI cohort, including non-carriers and carriers of C9orf72, GRN, or MAPT mutations. cTI produced an individual "genetic FTD progression score" (0-1) and grouped mutation carriers into data-driven subtypes. We tested construct validity using correlations between progression score and cognitive/functional measures, examined subtype differences in brain-behavior coupling, plasma neurofilament light (NfL), and longitudinal decline, and compared cTI-based trial enrichment against age, cortical thickness and NfL using analytic and simulation-based power analyses. RESULTSGenetic FTD progression scores correlated strongly with global dementia severity and multiple cognitive domains (all p < 0.001), confirming robust clinical scoring. Two mutation-carrier subtypes emerged: a Progressive Track (Subtype 2) with strong associations between progression score and cognitive/functional impairment, rising NfL, and faster longitudinal decline; and a Dissociated Track (Subtype 3) with comparable levels of structural variation but weak or absent clinical and NfL changes, suggesting relative biological stability. Baseline subtype membership added prognostic value for future decline in processing speed and language beyond baseline severity. Notably, for C9orf72 and GRN, cTI-informed enrichment reduced required recruited sample size per arm by about 61-75% compared with unenriched designs, and outperformed enrichment using age, cortical thickness or NfL in both analytic and simulation-based power analyses. CONCLUSIONSMachine-learning stratification of genetic FTD reveals a progressive and a dissociated disease track and provides individualized progression scores that closely track clinical status. cTI progression scores offer a powerful tool for trial enrichment, enabling smaller, more efficient prevention and early-intervention trials than conventional MRI or NfL markers alone.

neuroscience↗

bioRxiv2026

Distinct TAF15 amyloid filament folds define multiple subtypes of FTLD-TAF15

Neurodegenerative diseases are characterised by the assembly of a limited number of disease-specific proteins into amyloid filaments, which form intracellular inclusions or extracellular deposits in the central nervous system (CNS)1,2. We previously found that amyloid filaments of TATA-binding protein-associated factor 15 (TAF15) characterise a subtype of frontotemporal lobar degeneration with FET protein-immunoreactive inclusions (FTLD-FET)3, termed atypical FTLD with ubiquitin-positive inclusions (aFTLD-U)4, which causes early-onset, rapidly progressive behavioural variant frontotemporal dementia (FTD). However, it was not clear if TAF15 proteinopathy was more widespread in neurodegenerative diseases. Two additional FTLD-FET subtypes have been proposed, neuronal intermediate filament inclusion body disease (NIFID) and basophilic inclusion body disease (BIBD)5,6, which have more heterogenous clinical presentations including FTD, motor neuron diseases (MND) and movement disorders. Here, we used electron cryo-microscopy (cryo-EM) to determine a total of 32 amyloid filament structures from the brains of 17 individuals encompassing all three proposed subtypes of FTLD-FET and their diverse clinical presentations. All cases were characterised by TAF15 filaments, in the absence of filaments of the other FET proteins, fused in sarcoma (FUS) and Ewings sarcoma (EWS). All three aFTLD-U cases had the previously-reported TAF15 fold3. Unexpectedly, we found four distinct TAF15 folds among 11 NIFID cases. Eight of these cases shared a common fold, while the remaining three were each distinct. Furthermore, we found distinct TAF15 folds for each of the three BIBD cases. Neuropathological reassessment of the neocortical TAF15 inclusion pathology of these cases distinguished the NIFID cases with the common fold from the others. Thus, TAF15 filament structures form the basis of a new, expanded classification of FTLD-FET subtypes. Moreover, we discovered a TAF15 Y38C variant in the filament fold of one of the individuals with BIBD. The structure is unable to incorporate wild-type TAF15, despite the individual being heterozygous, suggesting that this variant drives TAF15 filament assembly. This study provides structural and genetic evidence that TAF15 amyloid filaments underlie the diverse group of neurodegenerative diseases currently termed FTLD-FET, which we therefore rename FTLD-TAF15.

molecular biology↗

bioRxiv2025

SynTEF1 restores the functional disease phenotype of SCA27B in an hiPSC-derived neuronal disease model

Spinocerebellar Ataxia 27B (SCA27B), caused by a deep-intronic GAA repeat expansion in the first intron of the FGF14 gene, is one of the most frequent genetic ataxias. Its underlying disease mechanisms remain largely unknown, and disease-modifying therapies targeting upstream processes are lacking. Here we hypothesized that (i) SCA27B is driven by transcriptional repression of FGF14, which encodes a protein regulating ion channels at the axon initial segment (AIS), resulting in reduced Na+ channel availability and neuronal excitability, and that (ii) these defects can be restored by a synthetic elongation transcription factor (Syn-TEF1). We assessed FGF14 mRNA levels by qPCR and neuronal function by whole-cell patch-clamp recordings in iPSC-derived neurons from two SCA27B patients and two healthy controls. Patients carried GAA repeat expansions that were either monoallelic (391/16 repeats) or biallelic (315/290 repeats), exceeding the common pathogenicity threshold of >250 repeats. FGF14 mRNA levels were reduced approximately to 60% and 70% of control levels in monoallelic and biallelic SCA27B neurons, respectively. This was accompanied by impaired excitability, with cumulative action potential (AP) firing reduced to 38% and 45% of control levels in monoallelic and biallelic lines, respectively, and peak Na current density reduced to 46% and 41%, while voltage-dependent gating of Na channels remained unchanged. Treatment with Syn-TEF1 significantly increased FGF14 mRNA expression and restored cumulative AP firing to 83% and 135% of control levels in monoallelic and biallelic neurons, respectively, and Na peak current density to 95% and 138%. These findings strongly suggest that the pathophysiological cascade in SCA27B - from FGF14 repression to impaired Na+ currents and decreased neuronal excitability - can be reversed by an elongation transcription factor. Our results thus provide a rationale for further exploring Syn-TEF1 as a first gene-targeted, disease-modifying therapeutic approach for SCA27B.

neuroscience↗

bioRxiv2025

MRI-based classifier to identify close-to-onset cases in C9orf72 genetic frontotemporal dementia

Predicting symptom onset in genetic frontotemporal dementia (FTD) is crucial for advancing targeted interventions and clinical trial design. Brain changes begin years before clinical symptoms emerge, making neuroimaging a strong candidate for onset prediction. However, FTD is highly heterogeneous, encompassing diverse molecular pathologies, affected brain networks, and symptom trajectories. This variability limits the predictive power of any single imaging biomarker and underscores the need for an integrative, multimodal approach to improve prediction accuracy and generalizability. We used machine learning to integrate diverse neuroimaging features, identifying a robust signature for risk stratification. We analyzed T1-weighted and T2-weighted MRI scans from 71 symptomatic C9orf72 carriers, 90 presymptomatic carriers, and 69 healthy controls from the GENFI cohort. We used FreeSurfer to measure cortical thickness and subcortical volumes, and BISON to quantify white matter hyperintensities (WMH). We applied Principal Component Analysis for dimensionality reduction and trained a random forest classifier to distinguish symptomatic carriers from controls. The model was subsequently applied to the presymptomatic cohort to identify individuals whose brain patterns resembled those of symptomatic cases, under the hypothesis that greater similarity indicated a higher risk of conversion. We validated the model with neuropsychological data and a two-year longitudinal follow-up. The classifier distinguished symptomatic C9orf72 carriers from controls with 87.0% accuracy. When applied to presymptomatic carriers, the model identified 21.1% of the cohort as having brain features comparable to those of symptomatic cases. This "high-risk group" showed significant neuropsychological weaknesses in executive function, language and social cognition compared to the non high-risk group. The model accurately predicted clinical conversion within a two-year period with 84.5% accuracy, a 70% sensitivity and a 93.3% negative predictive value. Our findings demonstrate the utility of a machine learning approach using multi-modal MRI to identify presymptomatic C9orf72 carriers at high risk of disease onset within the next two years. By capturing subtle neuroanatomical patterns associated with disease processes, this approach offers a promising method for stratifying genetic FTD carriers prior to symptom onset. Such predictive models could optimize patient selection in future clinical trials.

neuroscience↗

bioRxiv2025

A Core Pattern of Cerebellar and Brainstem Degeneration and Reduced Cerebrocerebellar Structural Covariance in Spinocerebellar Ataxia Type 3 (SCA3): MRI Volumetrics from ENIGMA-Ataxia

ObjectiveSpinocerebellar ataxia type 3 (SCA3) is a rare, inherited neurodegenerative disease. Here, we profile the spatial spread of atrophy across the whole brain, determine whether brain degeneration preferentially maps onto specific functional networks, and investigate the relationship between cerebellar and cerebral anatomical changes. MethodsWhole-brain grey and white matter (GM and WM) voxel-based morphometry was performed on 408 individuals with SCA3 (82 pre-ataxic) and 293 controls. The SCA3 cohort was stratified by ataxia severity to investigate disease progression, with cerebellar GM atrophy mapped onto a task-based functional atlas. Volume was correlated with disease duration and intensity. Cerebrocerebellar volumetric covariance was assessed to determine whether atrophy was coupled between infra- and supratentorial regions. ResultsThe pattern of atrophy is spatially consistent but progressive in magnitude across the disease course. The greatest atrophy was found in the pons, cerebellar WM, and cerebellar peduncles; correlations with disease severity and duration were also strongest in these regions. Cerebellar GM atrophy was greatest in functional regions associated with motor execution and planning, attention, and emotional processing. Sparse cerebral cortical atrophy appears only in the most severe disease subgroup, while striatal atrophy begins in the earliest stages. Reduced cerebrocerebellar structural covariance is observed in SCA3 participants versus controls. InterpretationWhile cerebellar and brainstem atrophy become more severe, the pattern of atrophy remains largely consistent as SCA3 progresses. Cerebellar GM degeneration occurs in regions associated with motor, cognitive, and affective control, in line with clinical presentation. Cerebellar atrophy is not directly mirrored by cerebral changes.

neuroscience↗

bioRxiv2025

White Matter Hyperintensities Precede other Biomarkers in GRN Frontotemporal Dementia

INTRODUCTIONIncreased white matter hyperintensities (WMHs) have been reported in genetic frontotemporal dementia (FTD) in small studies, but the sequence of WMH abnormalities relative to other biomarkers is unclear. METHODSUsing a large dataset (n=763 GENFI2 participants), we measured WMHs and examined them across genetic FTD variants and stages. Cortical and subcortical volumes were parcellated, and serum neurofilament light chain (NfL) levels were measured. Biomarker progression was assessed with discriminative event-based and regression modeling. RESULTSSymptomatic GRN carriers showed elevated WMHs, primarily in the frontal lobe, while no significant increase was observed in C9orf72 or MAPT carriers. WMH abnormalities preceded NfL elevation, ventricular enlargement, and cortical atrophy. Longitudinally, baseline WMHs predicted subcortical changes, while subcortical volumes did not predict WMH changes, suggesting WMHs may precede neurodegeneration. DISCUSSIONWMHs are elevated in a subset of GRN-related FTD. When present, they appear early and should be considered in disease progression models. HighlightsO_LIElevated WMH volumes in symptomatic GRN carriers, but not in other mutations. C_LIO_LIWMH accumulation is mostly observed in the frontal lobe. C_LIO_LIWMH abnormalities appear early in GRN-FTD, before NfL, atrophy, and ventriculomegaly. C_LIO_LILongitudinally, WMH volumes can predict subcortical changes, but not vice versa. C_LIO_LIWMHs are key early markers in GRN-FTD and should be included in progression models. C_LI RESEARCH IN CONTEXTO_ST_ABSSystematic reviewC_ST_ABSWe systematically reviewed the literature on white matter hyperintensities (WMHs) in frontotemporal dementia (FTD) using PubMed. While a few small studies reported increased WMHs in GRN mutation carriers, their sample sizes were limited, and they did not assess the timing of WMHs within disease progression or their temporal relationship to other biomarkers. InterpretationWe identified a sequence of key biomarkers in GRN-related FTD and demonstrated that WMHs are among the earliest biomarkers, preceding cortical and subcortical atrophy as well as blood biomarkers. This aligns with neuropathological evidence of early white matter involvement in FTLD-GRN. Additionally, using a larger dataset, we validated previous reports of elevated WMHs in GRN carriers, confirming their reliability. Future directionsFuture studies should integrate WMHs into FTD progression models to enhance early diagnosis. Understanding why only a subset of GRN carriers exhibit high WMH volumes remains a key research priority.

neuroscience↗

bioRxiv2024

Most L1CAM is not associated with extracellular vesicles in human biofluids and iPSC-derived neurons

Transmembrane L1 cell adhesion molecule (L1CAM) is widely used as a marker to enrich for neuron-derived extracellular vesicles (EVs), especially in plasma. However, this approach lacks sufficient robust validation. This study aimed to assess whether human biofluids are indeed enriched for EVs, particularly neuron-derived EVs, by L1CAM immunoaffinity, utilizing multiple sources (plasma, CSF, conditioned media from iPSC-derived neurons [iNCM]) and different methods (mass spectrometry [MS], nanoparticle tracking analysis [NTA]). Following a systematic multi-step validation approach, we confirmed isolation of generic EV populations using size-exclusion chromatography (SEC) and polymer-aided precipitation (PPT) - two most commonly applied EV isolation methods - from all sources. Neurofilament light (NfL) was detected in both CSF and blood-derived EVs, indicating their neuronal origin. However, L1CAM immunoprecipitation did not yield enrichment of L1CAM in EV fractions. Instead, it was predominantly found in its free-floating form. Additionally, MS-based proteomic analysis of CSF-derived EVs also did not show L1CAM enrichment. Our study validates EV isolation from diverse biofluid sources by several isolation approaches and confirms that some EV subpopulations in human biofluids are of neuronal origin. Thorough testing across multiple sources by different orthogonal methods, however, does not support L1CAM as a marker to reliably enrich for a specific subpopulation of EVs, particularly of neuronal origin.

neuroscience↗

bioRxiv2024

The Pattern and Staging of Brain Atrophy in Spinocerebellar Ataxia Type 2 (SCA2): MRI Volumetrics from ENIGMA-Ataxia

ObjectiveSpinocerebellar ataxia type 2 (SCA2) is a rare, inherited neurodegenerative disease characterised by progressive deterioration in both motor coordination and cognitive function. Atrophy of the cerebellum, brainstem, and spinal cord are core features of SCA2, however the evolution and pattern of whole-brain atrophy in SCA2 remain unclear. We undertook a multi-site, structural magnetic resonance imaging (MRI) study to comprehensively characterize the neurodegeneration profile of SCA2. MethodsVoxel-based morphometry analyses of 110 participants with SCA2 and 128 controls were undertaken to assess groupwise differences in whole-brain volume. Correlations with clinical severity and genotype, and cross-sectional profiling of atrophy patterns at different disease stages, were also performed. ResultsAtrophy in SCA2 relative to controls was greatest (Cohens d>2.5) in the cerebellar white matter (WM), middle cerebellar peduncle, pons, and corticospinal tract. Very large effects (d>1.5) were also evident in the superior cerebellar, inferior cerebellar, and cerebral peduncles. In cerebellar grey matter (GM), large effects (d>0.8) mapped to areas related to both motor coordination and cognitive tasks. Strong correlations (|r|>0.4) between volume and disease severity largely mirrored these groupwise outcomes. Stratification by disease severity showed a degeneration pattern beginning in cerebellar and pontine WM in pre-clinical subjects; spreading to the cerebellar GM and cerebro-cerebellar/corticospinal WM tracts; then finally involving the thalamus, striatum, and cortex in severe stages. InterpretationThe magnitude and pattern of brain atrophy evolves over the course of SCA2, with widespread, non-uniform involvement across the brainstem, cerebellar tracts, and cerebellar cortex; and late involvement of the cerebral cortex and striatum.

neuroscience↗

bioRxiv2024

Small non-coding RNA content in plasma-derived extracellular vesicles distinguish ataxic SCA3 mutation carriers from pre-ataxic and control subjects

Spinocerebellar ataxia type 3 (SCA3), a neurodegenerative disorder caused by a CAG expansion in the ATXN3 gene, is the most common spinocerebellar ataxia subtype worldwide. Currently, there is no therapy to stop or prevent disease progression. Promising therapeutic strategies are emerging, but their translation into clinical practice requires sensitive and reliable biomarkers. Blood circulating extracellular vesicles constitute a promising source of biomarkers with potential to track alterations of the central nervous system due to their ability to cross the blood brain barrier. Here, we perform sequencing analysis of small RNAs from plasma-derived extracellular vesicles from SCA3 mutation carriers (10 pre-ataxic and 10 ataxic) and 12 control subjects to identify potential RNA biomarker candidates for this disease. Data showed that plasma-derived extracellular vesicles from ataxic SCA3 mutation carriers are enriched in mitochondrial, nuclear, and nucleolar RNA biotypes compared to pre-ataxic and control subjects. Moreover, ataxic mutation carriers could be discriminated from control and pre-ataxic subjects based on the miRNAs or piRNAs content, but not tRNA. Furthermore, we identified a subset of differentially expressed miRNAs and piRNAs that clearly differentiate ataxic mutation carriers from pre-ataxic and control subjects. These findings open new avenues for further investigation on the role of these RNAs in the pathogenesis of SCA3 and their potential as biomarkers for this disease.

neuroscience↗

bioRxiv2023

Neuropathy target esterase activity predicts retinopathy among PNPLA6 disorders

Biallelic pathogenic variants in the PNPLA6 gene cause a broad spectrum of disorders leading to gait disturbance, visual impairment, anterior hypopituitarism, and hair anomalies. PNPLA6 encodes Neuropathy target esterase (NTE), yet the role of NTE dysfunction on affected tissues in the large spectrum of associated disease remains unclear. We present a clinical meta-analysis of a novel cohort of 23 new patients along with 95 reported individuals with PNPLA6 variants that implicate missense variants as a driver of disease pathogenesis. Measuring esterase activity of 46 disease-associated and 20 common variants observed across PNPLA6-associated clinical diagnoses unambiguously reclassified 10 variants as likely pathogenic and 36 variants as pathogenic, establishing a robust functional assay for classifying PNPLA6 variants of unknown significance. Estimating the overall NTE activity of affected individuals revealed a striking inverse relationship between NTE activity and the presence of retinopathy and endocrinopathy. This phenomenon was recaptured in vivo in an allelic mouse series, where a similar NTE threshold for retinopathy exists. Thus, PNPLA6 disorders, previously considered allelic, are a continuous spectrum of pleiotropic phenotypes defined by an NTE genotype:activity:phenotype relationship. This relationship and the generation of a preclinical animal model pave the way for therapeutic trials, using NTE as a biomarker.

neuroscience↗

bioRxiv2023

A common flanking variant is associated with enhanced meiotic stability of the FGF14-SCA27B locus

The factors driving initiation of pathological expansion of tandem repeats remain largely unknown. Here, we assessed the FGF14-SCA27B (GAA)*(TTC) repeat locus in 2,530 individuals by long-read and Sanger sequencing and identified a 5-flanking 17-bp deletion-insertion in 70.34% of alleles (3,463/4,923). This common sequence variation was present nearly exclusively on alleles with fewer than 30 GAA-pure repeats and was associated with enhanced meiotic stability of the repeat locus.

genetics↗

bioRxiv2023

Blood neurofilament light chain levels are associated with disease progression in a transgenic SCA3 mouse model

Increased neurofilament light (NfL) protein in biofluids is reflective of neurodegeneration and has gained interest as a biomarker across neurodegenerative diseases. In spinocerebellar ataxia type 3 (SCA3), the most common dominantly inherited ataxia, patients exhibit progressive NfL increases in peripheral blood when becoming symptomatic, remaining stably elevated throughout further disease course. However, progressive NfL changes are not yet validated in relevant preclinical SCA3 animal models, hindering its application as a biomarker during therapeutic development. We used ultra-sensitive single-molecule array (Simoa) to measure blood NfL over disease progression in the YACQ84 mouse, assessing relationships with measures of disease severity including age, CAG repeat size, and magnetic resonance spectroscopy. We show that YACQ84 mice exhibit increased blood NfL, concomitant with ataxia-related motor deficits and correlated with neurometabolite abnormalities. Our findings establish natural history progression of NfL increases in the preclinical YACQ84 mouse, further supporting the utility of blood NfL as a peripheral neurodegeneration biomarker and informing coinciding timelines of different measures of SCA3 pathogenesis. Summary statementPeripheral blood of SCA3 YACQ84 mice exhibits increased abundance of neuronal-specific NfL protein directly associating with disease progression, providing an accessible disease biofluid biomarker to interrogate in preclinical therapeutic studies.

neuroscience↗

bioRxiv2021

Cerebellar and subcortical atrophy contribute to psychiatric symptoms in frontotemporal dementia

Recent studies have suggested that cerebellar and subcortical structures are impacted early in the disease progression of genetic frontotemporal dementia (FTD) due to microtubule-associated protein tau (MAPT), progranulin (GRN) and chromosome 9 open reading frame 72 (C9orf72). However, the clinical contribution of the structures involved in the cerebello-subcortical circuitry has been understudied in FTD given their potentially central role in cognition and behaviour processes. The present study aims to investigate whether there is an association between the atrophy of the cerebellar and subcortical structures, and neuropsychiatric symptoms (using the revised version of the Cambridge Behavioral Inventory, CBI-R) across genetic mutations and whether this association starts during the preclinical phase of the disease. Our study included 983 participants from the Genetic Frontotemporal dementia Initiative (GENFI) including mutation carriers (n=608) and non-carrier first-degree relatives of known symptomatic carriers (n= 375). Voxel-wise analysis of the thalamus, striatum, globus pallidus, amygdala, and the cerebellum was performed using deformation based morphometry (DBM) and partial least squares analyses (PLS) were used to link morphometry and behavioural symptoms. Our univariate results suggest that in this group of primarily presymptomatic subjects, volume loss in subcortical and cerebellar structure was primarily a function of aging, with only the C9orf72 group showing more pronounced volume loss in the thalamus compared to the non-carrier individuals. PLS analyses demonstrated that the cerebello-subcortical circuitry is related to all neuropsychiatric symptoms from the CBI-R, with significant overlap in brain/behaviour patterns, but also specificity for each genetic group. The biggest differences were in the extent of the cerebellar involvement (larger extent in C9orf72 group) and more prominent amygdalar contribution in the MAPT group. Finally, our findings demonstrated that C9orf72 and MAPT brain scores were related to estimated years before the age of symptom onset (EYO) in a second order relationship highlighting a steeper brain score decline 20 years before expected symptom onset, while GRN brain scores were related to age and not EYO. Overall, these results demonstrated the important role of the subcortical structures and especially of the cerebellum in genetic FTD symptom expression.

neuroscience↗

bioRxiv2021

Global network structure and local transcriptomic vulnerability shape atrophy in sporadic and genetic behavioral variant frontotemporal dementia

Connections among brain regions allow pathological perturbations to spread from a single source region to multiple regions. Patterns of neurodegeneration in multiple diseases, including behavioral variant of frontotemporal dementia (bvFTD), resemble the large-scale functional systems, but how bvFTD-related atrophy patterns relate to structural network organization remains unknown. Here we investigate whether neurodegeneration patterns in sporadic and genetic bvFTD are conditioned by connectome architecture. Regional atrophy patterns were estimated in both genetic bvFTD (75 patients, 247 controls) and sporadic bvFTD (70 patients, 123 controls). We first identify distributed atrophy patterns in bvFTD, mainly targeting areas associated with the limbic intrinsic network and insular cytoarchitectonic class. Regional atrophy was significantly correlated with atrophy of structurally- and functionally-connected neighbors, demonstrating that network structure shapes atrophy patterns. The anterior insula was identified as the predominant group epicenter of brain atrophy using data-driven and simulation-based methods, with some secondary regions in frontal ventromedial and anteromedial temporal areas. Finally, we find that FTD-related genes, namely C9orf72 and TARDBP, confer local transcriptomic vulnerability to the disease, effectively modulating the propagation of pathology through the connectome. Collectively, our results demonstrate that atrophy patterns in sporadic and genetic bvFTD are jointly shaped by global connectome architecture and local transcriptomic vulnerability.

neuroscience↗

bioRxiv2021

Turning movements in real life capture subtle longitudinal and preataxic changes in cerebellar ataxia

OBJECTIVESClinical and regulatory acceptance of upcoming molecular treatments in degenerative ataxias might greatly benefit from ecologically valid endpoints which capture change in ataxia severity in patients real life. This longitudinal study aimed to unravel quantitative motor biomarkers in degenerative ataxias in real life turning movements which are sensitive for changes both longitudinally and at the preataxic stage. METHODSCombined cross-sectional (n=30) and longitudinal (n=14, 1-year interval) observational study in degenerative cerebellar disease (including 8 pre-ataxic mutation carriers) compared to 23 healthy controls. Turning movements were assessed by three body-worn inertial sensors in three conditions: (1) instructed laboratory assessment, (2) supervised free walking, and (3) unsupervised real-life movements. RESULTSMeasures which quantified dynamic balance during turning - lateral velocity change (LVC) and outward acceleration -, but not general turning measures such as speed, allowed differentiating ataxic against healthy subjects in real life with high effect size ({delta}=0.68), with LVC also differentiating preataxic against healthy subjects ({delta}=0.53). LVC was highly correlated with clinical ataxia severity (SARA score, effect size {rho}=0.79) and subjective balance confidence (ABC score, {rho}=0.66). Moreover, LVC in real life - but not general turning measures, gait measures, or the SARA score - allowed detecting significant longitudinal change in one-year follow-up with high effect size (rprb=0.66). CONCLUSIONSMeasures of turning allow to capture specific changes of dynamic balance in degenerative ataxia in real life, with high sensitivity to longitudinal differences in ataxia severity and to the preataxic stage. They thus present promising ecologically valid motor biomarkers for capturing change in real life, even in the highly treatment-relevant early stages of degenerative cerebellar disease.

bioengineering↗

bioRxiv2020

Intrinsic neural timescales related to sensory processing: Evidence from abnormal behavioural states

The brain exhibits a complex temporal structure which translates into a hierarchy of distinct neural timescales. An open question is how these intrinsic timescales are related to sensory or motor information processing and whether these dynamics have common patterns in different behavioural states. We address these questions by investigating the brains intrinsic timescales in healthy controls, motor (amyotrophic lateral sclerosis, locked-in syndrome), sensory (anaesthesia, unresponsive wakefulness syndrome), and progressive reduction of sensory processing (from awake states over N1, N2, N3). We employed a combination of measures from EEG resting-state data: auto-correlation window (ACW), power spectral density (PSD), and power-law exponent (PLE). Prolonged neural timescales accompanied by a shift towards slower frequencies were observed in the conditions with sensory deficits, but not in conditions with motor deficits. Our results establish that the spontaneous activitys intrinsic neural timescale is related to specifically sensory rather than motor information processing in the healthy brain. HighlightsO_LIEEG resting-state shows a hierarchy of intrinsic neural timescales. C_LIO_LISensory deficits as in disorders of consciousness lead to prolonged intrinsic neuraltimescales. C_LIO_LIClinical conditions with motor deficits do not show changes in intrinsic neural timescales.20 C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/229161v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@1893c45org.highwire.dtl.DTLVardef@d4176dorg.highwire.dtl.DTLVardef@4dfaa8org.highwire.dtl.DTLVardef@183621e_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2019

Data-driven algorithm for the diagnosis of behavioral variant frontotemporal dementia

INTRODUCTIONBrain structural imaging is paramount for the diagnosis of behavioral variant of frontotemporal dementia (bvFTD), but it has low sensitivity leading to erroneous or late diagnosis. METHODSA total of 515 subjects from two different bvFTD databases (training and validation cohorts) were included to perform voxel-wise deformation-based morphometry analysis to identify regions with significant differences between bvFTD and controls. A random forest classifier was used to individually predict bvFTD from morphometric differences in isolation and together with bedside cognitive scores. RESULTSAverage ten-fold cross-validation accuracy was 89% (82% sensitivity, 93% specificity) using only MRI and 94% (89% sensitivity, 98% specificity) with the addition of semantic fluency. In a separate validation cohort of genetically confirmed bvFTD, accuracy was 88% (81% sensitivity, 92% specificity) with MRI and 91% (79% sensitivity, 96% specificity) with added cognitive scores. DISCUSSIONThe random forest classifier developed can accurately predict bvFTD at the individual subject level.

neuroscience↗

bioRxiv2019

Analysis of brain atrophy and local gene expression implicates astrocytes in Frontotemporal dementia

Frontotemporal dementia (FTD) is a heterogeneous neurodegenerative disorder characterized by neuronal loss in the frontal and temporal lobes. Despite progress in understanding which genes are associated with the aetiology of FTD, the biological basis of how mutations in these genes lead to cell loss in specific cortical regions remains unclear. In this work we combined gene expression data for 16,772 genes from the Allen Institute for Brain Science atlas with brain maps of gray matter atrophy in symptomatic C9orf72, GRN and MAPT mutation carriers obtained from the Genetic FTD Initiative study. No significant association was seen between (C9orf2, GRN and MAPT expression and the atrophy patterns in the respective genetic groups. Between 1,000 and 5,000 genes showed a negative or positive correlation with the atrophy pattern within each individual genetic group, with the most significantly associated genes being TREM2, SSBP3 and GPR158 (negative association in C9orf72, GRN and MAPT respectively) and RELN, MXRA8 and LPA (positive association in C9orf72, GRN and MAPT respectively). An overrepresentation analysis identified a negative correlation with genes involved in mitochondrial function, and a positive correlation with genes involved in vascular and glial cell function in each of the genetic groups. After adjusting for spatial autocorrelation, a set of 423 and 700 genes showed significant positive and negative correlation, respectively, with atrophy patterns in all three maps. The gene set with increased expression in spared cortical regions was enriched for neuronal and microglial genes, while the gene set with increased expression in atrophied regions was enriched for astrocyte and endothelial cell genes. Our analysis suggests that these cell types may play a more active role in the onset of neurodegeneration in FTD than previously assumed, and in the case of the positively-associated cell marker genes, potentially through emergence of neurotoxic astrocytes and alteration in the blood-brain barrier respectively. Abbreviated summaryAltmann et al. investigated the concordance between spatial cortical gene expression in healthy subjects and atrophy patterns in genetic frontotemporal dementia. They found that elevated gene expression of endothelial cell and astrocyte-related genes in regions with atrophy, suggesting a role of these cell types in the aetiology of frontotemporal dementia.

neuroscience↗