Biology subjects

Perneczky, R.

Publications and source records attributed to Perneczky, R..

8 recordsLinked to original sources

bioRxiv2026

Automated quantification of white matter hyperintensity confluence: A measure of spatial organisation beyond volume and visual rating scales

White matter hyperintensities (WMH) are a highly prevalent finding on FLAIR MRI scans and a prominent feature of white matter pathology across cerebrovascular and neurodegenerative diseases. Currently, WMH are assessed with visual rating scales such as the Fazekas scale or with their volume, as calculated from automatic or manual segmentations. Both methods have limitations: Visual rating scales are rater-dependent and coarse, while WMH volume does not take the confluence of lesions into account and thus disregards their spatial organisation. As an alternative, here we propose a novel automated method for quantifying the confluence of white matter hyperintensities on a continuous standardised scale between 0 and 1. The metric is based on WMH segmentations from routine MRI and quantifies the extent to which individual WMH merge into coherent lesions, independently of total lesion volume. We apply the method to QMIN-MC, a large UK memory clinic cohort, and show associations of the confluence metric with age, cognitive performance across domains, and Fazekas ratings. Participants with vascular and mixed dementia showed higher confluence than other diagnostic groups, whereas cognitively unimpaired participants showed lower confluence. However, confluence did not explain additional cognitive variance after accounting for log-transformed WMH volume. Findings were validated in DELCODE, an independent cohort of individuals with neurodegenerative disorders, replicating our original results. In this validation cohort, periventricular WMH confluence remained associated with cognition after adjustment for WMH volume. These findings introduce WMH confluence as a reproducible, automated, and fine-grained measure of lesion spatial organisation. It provides complementary information about morphological WMH severity beyond volume and is an alternative to visual rating scales. Although related to WMH volume in memory-clinic populations, confluence captures clinically interpretable information and may complement existing WMH measures for improved lesion characterisation in studies of white matter disease, ageing, and cognitive impairment.

neuroscience↗

bioRxiv2024

SMAS: Structural MRI-Based AD Score using Bayesian VAE

This study introduces the Structural MRI-based Alzheimers Disease Score (SMAS), a novel index intended to quantify Alzheimers Disease (AD)-related morphometric patterns using a deep learning Bayesian-supervised Variational Autoencoder (Bayesian-SVAE). SMAS index was constructed using baseline structural MRI data from the DELCODE study and evaluated longitudinally in two independent cohorts: DEL-CODE (n=415) and ADNI (n=190). Our findings indicate that SMAS has strong associations with cognitive performance (DELCODE: r=-0.83; ADNI: r=-0.62), age (DEL-CODE: r=0.50; ADNI: r=0.28), hippocampal volume (DEL-CODE: r=-0.44; ADNI: r=-0.66), and total grey matter volume (DELCODE: r=-0.42; ADNI: r=-0.47), suggesting its potential as a biomarker for AD-related brain atrophy. Moreover, our longitudinal studies suggest that SMAS may be useful for early identification and tracking of AD. The model demonstrated significant predictive accuracy in distinguishing cognitively healthy individuals from those with AD (DELCODE: AUC=0.971 at baseline, 0.833 at 36 months; ADNI: AUC=0.817 at baseline, improving to 0.903 at 24 months). Notably, over a 36-month period, SMAS index outperformed existing measures such as SPARE-AD and hippocampal volume. Relevance map analysis revealed significant morphological changes in key AD-related brain regions--including the hippocampus, posterior cingulate cortex, precuneus, and lateral parietal cortex--highlighting that SMAS is a sensitive and interpretable biomarker of brain atrophy, suitable for early AD detection and longitudinal monitoring of disease progression.

neuroscience↗

bioRxiv2023

Fornix fractional anisotropy mediates the association between Mediterranean diet adherence and memory four years later in older adults without dementia

Here, we investigated whether fractional anisotropy (FA) of hippocampus-relevant white-matter tracts mediates the association between baseline Mediterranean diet adherence (MeDiAd) and verbal episodic memory over four years. Participants were healthy older adults with and without subjective cognitive decline and patients with amnestic mild cognitive impairment from the DELCODE cohort study (n = 376; age: 71.47 {+/-} 6.09 years; 48.7% female). MeDiAd and diffusion data were obtained at baseline. Verbal episodic memory was assessed at baseline and four yearly follow-ups. The associations between baseline MeDiAd and white matter, and verbal episodic memorys mean and rate of change over four years were tested with latent growth curve modeling. Baseline MeDiAd was associated with verbal episodic memory four years later (95% confidence interval, CI [0.01, 0.32]) but not with its rate of change over this period. Baseline Fornix FA mediated - and, thus, explained - that association (95% CI [0.002, 0.09]). Fornix FA may be an appropriate response biomarker of Mediterranean diet interventions on verbal memory in older adults.

neuroscience↗

bioRxiv2022

Individualized Gaussian Process-based Prediction of Memory Performance and Biomarker Status in Ageing and Alzheimer's disease

Neuroimaging markers based on Magnetic Resonance Imaging (MRI) combined with various other measures (such as informative covariates, vascular risks, brain activity, neuropsychological test etc.,) might provide useful predictions of clinical outcomes during progression towards Alzheimers disease (AD). The Bayesian approach aims to provide a trade-off by employing relevant features combinations to build decision support systems in clinical settings where uncertainties are relevant. We tested the approach in the MRI data across 959 subjects, aged 59-89 years and 453 subjects with available neuropsychological test scores and CSF biomarker status (amyloid-beta (A{beta})42/40 & and phosphorylated tau (pTau)) from a large sample multi-centric observational cohort (DELCODE). In order to explore the beneficial combinations of information from different sources, we presented a MRI-based predictive modelling of memory performance and CSF biomarker status (positive or negative) in the healthy ageing group as well as subjects at risk of Alzheimers disease using a Gaussian process multikernel framework. Furthermore, we systematically evaluated predictive combinations of input feature sets and their model variations, i.e. (A) combinations of brain tissue classes and feature type (modulated vs. unmodulated), choices of filter size of smoothing (ranging from 0 to 15 mm full width at half maximum), and image resolution (1mm, 2mm, 4mm and 8mm); (B) incorporating demography and covariates (C) the impact of the size of the training data set (i.e., number of subjects); (D) the influence of reducing the dimensions of data and (E) choice of kernel types. Finally, the approach was tested to reveal individual cognitive scores at follow-up (up to 4 years) using the baseline features. The highest accuracy for memory performance prediction was obtained for a combination of neuroimaging markers, demographics, genetic information (ApoE4) and CSF-biomarkers explaining 57% of outcome variance in out of sample predictions. The best accuracy for A{beta}42/40 status classification was achieved for combination demographics, ApoE4 and memory score while usage of structural MRI improved the classification of individual patients pTau status.

neuroscience↗

bioRxiv2021

Multi-omics and 3D-imaging reveal bone heterogeneity and unique calvaria cells in neuroinflammation

The meninges of the brain are an important component of neuroinflammatory response. Diverse immune cells move from the calvaria marrow into the dura mater via recently discovered skull-meninges connections (SMCs). However, how the calvaria bone marrow is different from the other bones and whether and how it contributes to human diseases remain unknown. Using multi-omics approaches and whole mouse transparency we reveal that bone marrow cells are highly heterogeneous across the mouse body. The calvaria harbors the most distinct molecular signature with hundreds of differentially expressed genes and proteins. Acute brain injury induces skull-specific alterations including increased calvaria cell numbers. Moreover, TSPO-positron-emission-tomography imaging of stroke, multiple sclerosis and neurodegenerative disease patients demonstrate disease-associated uptake patterns in the human skull, mirroring the underlying brain inflammation. Our study indicates that the calvaria is more than a physical barrier, and its immune cells may present new ways to control brain pathologies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/473988v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@978194org.highwire.dtl.DTLVardef@bc45e8org.highwire.dtl.DTLVardef@91afdborg.highwire.dtl.DTLVardef@b06bc6_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIBone marrow across the mouse body display heterogeneity in their molecular profile C_LIO_LICalvaria cells have a distinct profile that is relevant to brain pathologies C_LIO_LIBrain native proteins are identified in calvaria in pathological states C_LIO_LITSPO-PET imaging of the human skull can be a proxy of neuroinflammation in the brain C_LI Supplementary Videos can be seen at: http://discotechnologies.org/Calvaria/

cell biology↗

bioRxiv2021

Lifelong musical activity is associated with multi-domain cognitive and brain benefits in older adults

1AO_SCPLOWBSTRACTC_SCPLOWRegular musical activity as a highly-stimulating lifestyle activity is proposed to be protective against age-related cognitive decline and Alzheimers disease (AD). This study investigated associations between lifelong regular musical instrument playing, late-life cognitive abilities and brain morphology in older adults. We show that musical activity over the life course is associated with better global cognition, working memory, executive functions, language, and visuospatial abilities accounting for reserve proxies. Playing music is not significantly associated with gray matter volume in regions most affected by aging and AD. Selectively in the musically active participants, multi-domain cognitive abilities were enhanced with preserved gray matter volume in frontal and temporal regions. Our correlational findings suggest that playing a musical instrument may improve the recruitment of existing brain resources to facilitate late-life cognitive capacities. We propose that engaging in regular musical activity could serve as a low-threshold multimodal enrichment strategy that may promote cognitive resilience in advanced age.

neuroscience↗

bioRxiv2018

Differential expression of microRNAs in Alzheimer’s disease brain, blood and cerebrospinal fluid: a systematic review and meta-analysis

INTRODUCTIONSeveral microRNAs (miRNAs) have been implicated in Alzheimers disease (AD) pathogenesis but the evidence from individual case-control-studies remains inconclusive.\n\nMETHODSA systematic literature review was performed, followed by standardised multi-stage data extraction, quality control, and meta-analyses on eligible data for brain, blood, and cerebrospinal fluid (CSF) specimens. Results were compared with miRNAs reported in the abstracts of eligible studies or recent qualitative reviews to assess novelty.\n\nRESULTSData from 147 independent datasets across 107 publications were quantitatively assessed in 461 meta-analyses. Twenty-five, five, and 32 miRNAs showed study-wide significant differential expression (<1.08x10-4) in brain, CSF, and blood-derived specimens, respectively, with 5 miRNAs showing differential expression in both brain and blood. Of these 57 miRNAs, 13 had not been reported in the abstracts of previous original or review articles.\n\nDISCUSSIONOur systematic assessment of differential miRNA expression is the first of its kind in AD and highlights miRNAs of relevance.

neuroscience↗

bioRxiv2018

Systematic meta-analyses identify differentially expressed microRNAs in Parkinson’s disease

ObjectiveMicroRNA-mediated (dys)regulation of gene expression has been implicated in Parkinsons disease (PD), although results of microRNA expression studies remain inconclusive. We aimed to identify microRNAs that show consistent differential expression across all published expression studies in PD.\n\nMethodsWe performed a systematic literature search on microRNA expression studies in PD and extracted data from eligible publications. After stratification for brain, blood, and cerebrospinal fluid (CSF)-derived specimen we performed meta-analyses across microRNAs assessed in three or more independent datasets. Meta-analyses were performed using effect-size and p-value based methods, as applicable.\n\nResultsAfter screening 599 publications we identified 47 datasets eligible for meta-analysis. On these, we performed 160 meta-analyses on microRNAs quantified in brain (n=125), blood (n=31), or CSF samples (n=4). Twenty-one meta-analyses were performed using effect sizes. We identified 13 significantly (Bonferroni-adjusted =3.13x10-4) differentially expressed microRNAs in brain (n=3) and blood (n=10) with consistent effect directions across studies. The most compelling findings were with hsa-miR-132-3p (p=6.37x10-5), hsa-miR-497-5p (p=1.35x10-4), and hsa-miR-133b (p=1.90x10-4) in brain, and with hsa-miR-221-3p (p=4.49x10-35), hsa-miR-214-3p (p=2.00x10-34), and hsa-miR-29c-3p (p=3.00x10-12) in blood. No significant signals were found in CSF. Analyses of GWAS data for target genes of brain microRNAs showed significant association (=9.40x10-5) of genetic variants in nine loci.\n\nInterpretationWe identified several microRNAs that showed highly significant differential expression in PD. Future studies may assess the possible role of the identified brain miRNAs in pathogenesis and disease progression as well as the potential of the top blood microRNAs as biomarkers for diagnosis, progression or prediction of PD.

genetics↗