Connectome-based modelling of neurodegenerative diseases: towards precision medicine and mechanistic insight

Nature reviews. Neuroscience, Journal Year: 2023, Volume and Issue: 24(10), P. 620 - 639

Published: Aug. 24, 2023

Language: Английский

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The evolution of Big Data in neuroscience and neurology

Journal Of Big Data, Journal Year: 2023, Volume and Issue: 10(1)

Published: July 10, 2023

Neurological diseases are on the rise worldwide, leading to increased healthcare costs and diminished quality of life in patients. In recent years, Big Data has started transform fields Neuroscience Neurology. Scientists clinicians collaborating global alliances, combining diverse datasets a massive scale, solving complex computational problems that demand utilization increasingly powerful resources. This revolution is opening new avenues for developing innovative treatments neurological diseases. Our paper surveys Data's impact patient care, as exemplified through work done comprehensive selection areas, including Connectomics, Alzheimer's Disease, Stroke, Depression, Parkinson's Pain, Addiction (e.g., Opioid Use Disorder). We present an overview research methodologies utilizing each area, well their current limitations technical challenges. Despite potential benefits, full these currently remains unrealized. close with recommendations future aimed at optimizing use Neurology improved outcomes.The online version contains supplementary material available 10.1186/s40537-023-00751-2.

Language: Английский

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Machine Learning for Detecting Parkinson’s Disease by Resting-State Functional Magnetic Resonance Imaging: A Multicenter Radiomics Analysis

Frontiers in Aging Neuroscience, Journal Year: 2022, Volume and Issue: 14

Published: March 3, 2022

Parkinson's disease (PD) is one of the most common progressive degenerative diseases, and its diagnosis challenging on clinical grounds. Clinically, effective quantifiable biomarkers to detect PD are urgently needed. In our study, we analyzed data from two centers, primary set was used train model, independent external validation validate model. We applied amplitude low-frequency fluctuation (ALFF)-based radiomics method extract features (including first- high-order features). Subsequently,

Language: Английский

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Band‐Specific Altered Cortical Connectivity in Early Parkinson's Disease and its Clinical Correlates

Movement Disorders, Journal Year: 2023, Volume and Issue: 38(12), P. 2197 - 2208

Published: Oct. 20, 2023

Abstract Background Functional connectivity (FC) has shown promising results in assessing the pathophysiology and identifying early biomarkers of neurodegenerative disorders, such as Parkinson's disease (PD). Objectives In this study, we aimed to assess possible resting‐state FC abnormalities early‐stage PD patients using high‐density electroencephalography (EEG) detect their clinical relationship with motor non‐motor symptoms. Methods We enrolled 26 levodopa naïve a group 20 healthy controls (HC). Data were recorded 64‐channels EEG system source‐reconstruction method was used identify brain‐region activity. calculated weighted phase‐lag index θ, α, β bands. Additionally, quantified unbalancing between lower frequencies through novel (β‐functional ratio [FR]). Statistical analysis conducted network‐based statistical approach. Results showed hypoconnected networks θ α band, involving prefrontal‐limbic‐temporal frontoparietal areas, respectively, hyperconnected network frequency sensorimotor‐frontal areas. The negatively related Non‐Motor Symptoms Scale scores Movement Disorder Society‐Sponsored Revision Unified Disease Rating part III gait subscore, whereas β‐FR positively linked bradykinesia subscore. Changes substantial reliability high accuracy, precision, sensitivity, specificity discriminating HC. Conclusions Frequency‐specific changes likely reflect dysfunction distinct cortical networks, which occur from stage disease. These are involved specific symptoms, including gait, bradykinesia, mood, cognition. © 2023 International Parkinson Society.

Language: Английский

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Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson’s Disease

Journal of Parkinson s Disease, Journal Year: 2024, Volume and Issue: 14(s2), P. S353 - S365

Published: Feb. 6, 2024

Assessing imaging biomarker in the prodromal and early phases of Parkinson’s disease (PD) is great importance to ensure an safe diagnosis. In last decades, modalities advanced are now able assess many different aspects neurodegeneration PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT with Ioflupane, more specific PET tracers degeneration dopaminergic system available. Furthermore, metabolic patterns be used anticipate a phenoconversion PD manifest this regard, it worth mentioning that inflammation will gain significance. Molecular neurotransmitters like serotonin, noradrenaline acetylcholine shed light on non-motor symptoms. Outside brain, molecular heart gut PD-related autonomous nervous system. Moreover, optical coherence tomography noninvasively detect retinal fibers as potential review, we describe these state-of-the-art point out how far techniques future pave way towards biomarker-based staging

Language: Английский

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Functional connectome automatically differentiates multiple system atrophy (parkinsonian type) from idiopathic Parkinson's disease at early stages

Human Brain Mapping, Journal Year: 2023, Volume and Issue: 44(6), P. 2176 - 2190

Published: Jan. 20, 2023

Abstract Differentiating the parkinsonian variant of multiple system atrophy (MSA‐P) from idiopathic Parkinson's disease (IPD) is challenging, especially in early stages. This study aimed to investigate differences and similarities brain functional connectomes IPD MSA‐P patients use machine learning methods explore diagnostic utility these features. Resting‐state fMRI data were acquired 88 healthy controls, 76 patients, 53 using a 3.0 T scanner. The whole‐brain connectome was constructed by thresholding Pearson correlation matrices 116 regions, topological properties evaluated through graph theory approaches. Connectome measurements used as features models (random forest [RF]/logistic regression [LR]/support vector machine) distinguish patients. Regarding metrics, shared network properties. Both patient groups showed connectivity disruptions within cerebellum‐basal ganglia‐cortical network, but disconnections mainly cortico‐thalamo‐cerebellar circuits basal ganglia‐thalamo‐cortical Among parameters, t tests combined with RF method identified 15 features, which LR classifier achieved best performance on validation set (accuracy = 92.31%, sensitivity 90.91%, specificity 93.33%, area under receiver operating characteristic curve 0.89). show similar alterations. primarily affects cerebellar nodes, ganglia nodes; both conditions disrupt network. Moreover, parameters outstanding value differential diagnosis IPD.

Language: Английский

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Early effect of onabotulinumtoxinA on EEG‐based functional connectivity in patients with chronic migraine: A pilot study

Headache The Journal of Head and Face Pain, Journal Year: 2024, Volume and Issue: 64(7), P. 825 - 837

Published: June 4, 2024

Abstract Objective In this pilot prospective cohort study, we aimed to evaluate, using high‐density electroencephalography (HD‐EEG), the longitudinal changes in functional connectivity (FC) patients with chronic migraine (CM) treated onabotulinumtoxinA (OBTA). Background OBTA is a treatment for CM. Several studies have shown modulatory action of on central nervous system; however, research limited. Methods This study was conducted at Neurology Unit “Policlinico Tor Vergata,” Rome, Italy, and included 12 adult CM 15 healthy controls (HC). Patients underwent clinical scales enrollment (T0) 3 months (T1) from start treatment. HD‐EEG recorded 64‐channel system T0 T1. A source reconstruction method used identify brain activity. FC δ‐θ‐α‐β‐low‐γ bands analyzed weighted phase‐lag index. between HCs T1 were assessed cross‐validation methods estimate results’ reliability. Results Compared T0, showed hyperconnected networks δ ( p = 0.046, area under receiver operating characteristic curve [AUC: 0.76‐0.98], Cohen's κ [0.65‐0.93]) β 0.031, AUC [0.68‐0.95], [0.51‐0.84]), mainly involving orbitofrontal, occipital, temporal pole superior temporal, cingulate areas, hypoconnected α band 0.029, [0.80‐0.99], [0.42‐0.77]), predominantly cingulate, pole, precuneus. T1, compared 0.032, [0.73‐0.99], [0.53‐0.90]) 0.048, [0.58‐0.93], [0.37‐0.78]), sensorimotor, cortex. Conclusion These preliminary results that presented disrupted EEG‐FC restored by single session treatment, suggesting primary OBTA.

Language: Английский

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Insular and limbic abnormal functional connectivity in early-stage Parkinson’s disease patients with autonomic dysfunction

Cerebral Cortex, Journal Year: 2024, Volume and Issue: 34(7)

Published: July 1, 2024

Abstract Autonomic symptoms in Parkinson’s disease result from variable involvement of the central and peripheral systems, but many aspects remain unclear. The analysis functional connectivity has shown promising results assessing pathophysiology disease. This study aims to investigate association between autonomic cortical early patients using high-density EEG. 53 (F/M 18/35) 49 controls 20/29) were included. evaluated Scales for Outcomes disease–Autonomic Dysfunction score. Data recorded with a 64-channel EEG system. We analyzed connectivity, based on weighted phase-lag index, θ-α-β-low-γ bands. A network-based statistic was used perform linear regression score patients. observed positive relation α-functional (network τ = 2.8, P 0.038). Regions higher degrees insula limbic lobe. Moreover, we found correlations mean this network gastrointestinal, cardiovascular, thermoregulatory domains Dysfunction. Our revealed abnormal specific areas greater symptoms. Insula play significant role regulation Increased these regions might represent compensatory mechanism dysfunction

Language: Английский

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Aberrant functional connectome gradient and its neurotransmitter basis in Parkinson's disease

Neurobiology of Disease, Journal Year: 2025, Volume and Issue: unknown, P. 106821 - 106821

Published: Jan. 1, 2025

Language: Английский

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A signature combining brain functional connectivity with executive and motor function for general cognitive decline in Parkinson’s disease

Frontiers in Neurology, Journal Year: 2025, Volume and Issue: 16

Published: Feb. 19, 2025

Cognitive decline is common in Parkinson's disease (PD). Reliance on neuropsychological testing alone can lead to delayed identification, and an objective comprehensive approach needed clinical practice. We assessed brain functional connectivity during PD-MCI (mild cognitive impairment) PD-NC (normal cognition) patients, healthy controls (HC) completing the Stroop color-word test (SCWT) using near-infrared spectroscopy (fNIRS), explored predictive value of combining relevant function behavioral information for general PD. Nineteen patients with PD-MCI, 21 33 age-matched HC were recruited. Group differences executive performance prefrontal analyzed. Receiver operating characteristic analysis was used measure motor predicting PD-MCI. During incongruent test, had significantly lower correct rate than patients. Meanwhile, exhibited increased regional strength left right cortex (RSl, RSr), global efficiency HC, compared PD-NC, showed higher RSr. For PD MMSE score negatively associated RSr after adjusting education level age. After combined RSr, MDS-UPDRS III score, diagnostic sensitivity specificity reached 0.737 0.810, respectively, area under curve 0.830. proposed a signature PD, which could provide new insights into early detection intervention this problem.

Language: Английский

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