Brain perivascular spaces and autism: clinical and pathogenic implications from an innovative volumetric MRI study

IntroductionOur single-center case–control study aimed to evaluate the unclear glymphatic system alteration in autism spectrum disorder (ASD) through an innovative neuroimaging tool which allows to segment and quantify perivascular spaces in the white matter (WM-PVS) with filtering of non-structured noise and increase of the contrast-ratio between perivascular spaces and the surrounding parenchyma.MethodsBriefly, files of 65 ASD and 71 control patients were studied. We considered: ASD type, diagnosis and severity level and comorbidities (i.e., intellectual disability, attention-deficit hyperactivity disorder, epilepsy, sleep disturbances). We also examined diagnoses other than ASD and their associated comorbidities in the control group.ResultsWhen males and females with ASD are included together, WM-PVS grade and WM-PVS volume do not significantly differ between the ASD group and the control group overall. We found, instead, that WM-PVS volume is significantly associated with male sex: males had higher WM-PVS volume compared to females (p = 0.01). WM-PVS dilation is also non-significantly associated with ASD severity and younger age (< 4 years). In ASD patients, higher WM-PVS volume was related with insomnia whereas no relation was found with epilepsy or IQ.DiscussionWe concluded that WM-PVS dilation can be a neuroimaging feature of male ASD patients, particularly the youngest and most severe ones, which may rely on male-specific risk factors acting early during neurodevelopment, such as a transient excess of extra-axial CSF volume. Our findings can corroborate the well-known strong male epidemiological preponderance of autism worldwide

Analytic Tools for Post-traumatic Epileptogenesis Biomarker Search in Multimodal Dataset of an Animal Model and Human Patients

Epilepsy is among the most common serious disabling disorders of the brain, and the global burden of epilepsy exerts a tremendous cost to society. Most people with epilepsy have acquired forms of the disorder, and the development of antiepileptogenic interventions could potentially prevent or cure epilepsy in many of them. However, the discovery of potential antiepileptogenic treatments and clinical validation would require a means to identify populations of patients at very high risk for epilepsy after a potential epileptogenic insult, to know when to treat and to document prevention or cure. A fundamental challenge in discovering biomarkers of epileptogenesis is that this process is likely multifactorial and crosses multiple modalities. Investigators must have access to a large number of high quality, well-curated data points and study subjects for biomarker signals to be detectable above the noise inherent in complex phenomena, such as epileptogenesis, traumatic brain injury (TBI), and conditions of data collection. Additionally, data generating and collecting sites are spread worldwide among different laboratories, clinical sites, heterogeneous data types, formats, and across multi-center preclinical trials. Before the data can even be analyzed, these data must be standardized. The Epilepsy Bioinformatics Study for Antiepileptogenic Therapy (EpiBioS4Rx) is a multi-center project with the overarching goal that epileptogenesis after TBI can be prevented with specific treatments. The identification of relevant biomarkers and performance of rigorous preclinical trials will permit the future design and performance of economically feasible full-scale clinical trials of antiepileptogenic therapies. We have been analyzing human data collected from UCLA and rat data collected from the University of Eastern Finland, both centers collecting data for EpiBioS4Rx, to identify biomarkers of epileptogenesis. Big data techniques and rigorous analysis are brought to longitudinal data collected from humans and an animal model of TBI, epilepsy, and their interaction. The prolonged continuous data streams of intracranial, cortical surface, and scalp EEG from humans and an animal model of epilepsy span months. By applying our innovative mathematical tools via supervised and unsupervised learning methods, we are able to subject a robust dataset to recently pioneered data analysis tools and visualize multivariable interactions with novel graphical methods

Prevalence of Dementia and Mild Cognitive Impairment in Indigenous Bolivian Forager-Horticulturalists

Introduction We evaluated the prevalence of dementia and mild cognitive impairment (MCI) in indigenous Tsimane and Moseten, who lead a subsistence lifestyle. Methods Participants from population-based samples ≥ 60 years of age (n = 623) were assessed using adapted versions of the Modified Mini-Mental State Examination, informant interview, longitudinal cognitive testing and brain computed tomography (CT) scans. Results Tsimane exhibited five cases of dementia (among n = 435; crude prevalence = 1.2%, 95% confidence interval [CI]: 0.4, 2.7); Moseten exhibited one case (among n = 169; crude prevalence = 0.6%, 95% CI: 0.0, 3.2), all age ≥ 80 years. Age-standardized MCI prevalence was 7.7% (95% CI: 5.2, 10.3) in Tsimane and 9.8% (95% CI: 4.9, 14.6) in Moseten. Cognitive impairment was associated with visuospatial impairments, parkinsonian symptoms, and vascular calcification in the basal ganglia. Discussion The prevalence of dementia in this cohort is among the lowest in the world. Widespread intracranial medial arterial calcifications suggest a previously unrecognized, non-Alzheimer\u27s disease (AD) dementia phenotype

A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms.

Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research

Chronic Stroke Sensorimotor Impairment Is Related to Smaller Hippocampal Volumes: An ENIGMA Analysis

Background. Persistent sensorimotor impairments after stroke can negatively impact quality of life. The hippocampus is vulnerable to poststroke secondary degeneration and is involved in sensorimotor behavior but has not been widely studied within the context of poststroke upper‐limb sensorimotor impairment. We investigated associations between non‐lesioned hippocampal volume and upper limb sensorimotor impairment in people with chronic stroke, hypothesizing that smaller ipsilesional hippocampal volumes would be associated with greater sensorimotor impairment. Methods and Results. Cross‐sectional T1‐weighted magnetic resonance images of the brain were pooled from 357 participants with chronic stroke from 18 research cohorts of the ENIGMA (Enhancing NeuoImaging Genetics through Meta‐Analysis) Stroke Recovery Working Group. Sensorimotor impairment was estimated from the FMA‐UE (Fugl‐Meyer Assessment of Upper Extremity). Robust mixed‐effects linear models were used to test associations between poststroke sensorimotor impairment and hippocampal volumes (ipsilesional and contralesional separately; Bonferroni‐corrected, P<0.025), controlling for age, sex, lesion volume, and lesioned hemisphere. In exploratory analyses, we tested for a sensorimotor impairment and sex interaction and relationships between lesion volume, sensorimotor damage, and hippocampal volume. Greater sensorimotor impairment was significantly associated with ipsilesional (P=0.005; β=0.16) but not contralesional (P=0.96; β=0.003) hippocampal volume, independent of lesion volume and other covariates (P=0.001; β=0.26). Women showed progressively worsening sensorimotor impairment with smaller ipsilesional (P=0.008; β=−0.26) and contralesional (P=0.006; β=−0.27) hippocampal volumes compared with men. Hippocampal volume was associated with lesion size (P<0.001; β=−0.21) and extent of sensorimotor damage (P=0.003; β=−0.15). Conclusions. The present study identifies novel associations between chronic poststroke sensorimotor impairment and ipsilesional hippocampal volume that are not caused by lesion size and may be stronger in women.S.-L.L. is supported by NIH K01 HD091283; NIH R01 NS115845. A.B. and M.S.K. are supported by National Health and Medical Research Council (NHMRC) GNT1020526, GNT1045617 (A.B.), GNT1094974, and Heart Foundation Future Leader Fellowship 100784 (A.B.). P.M.T. is supported by NIH U54 EB020403. L.A.B. is supported by the Canadian Institutes of Health Research (CIHR). C.M.B. is supported by NIH R21 HD067906. W.D.B. is supported by the Heath Research Council of New Zealand. J.M.C. is supported by NIH R00HD091375. A.B.C. is supported by NIH R01NS076348-01, Hospital Israelita Albert Einstein 2250-14, CNPq/305568/2016-7. A.N.D. is supported by funding provided by the Texas Legislature to the Lone Star Stroke Clinical Trial Network. Its contents are solely the responsibility of the authors and do not necessarily represent the of ficial views of the Government of the United States or the State of Texas. N.E.-B. is supported by Australian Research Council NIH DE180100893. W.F. is sup ported by NIH P20 GM109040. F.G. is supported by Wellcome Trust (093957). B.H. is funded by and NHMRC fellowship (1125054). S.A.K is supported by NIH P20 HD109040. F.B. is supported by Italian Ministry of Health, RC 20, 21. N.S. is supported by NIH R21NS120274. N.J.S. is supported by NIH/National Institute of General Medical Sciences (NIGMS) 2P20GM109040-06, U54-GM104941. S.R.S. is supported by European Research Council (ERC) (NGBMI, 759370). G.S. is supported by Italian Ministry of Health RC 18-19-20-21A. M.T. is sup ported by National Institute of Neurological Disorders and Stroke (NINDS) R01 NS110696. G.T.T. is supported by Temple University sub-award of NIH R24 –NHLBI (Dr Mickey Selzer) Center for Experimental Neurorehabilitation Training. N.J.S. is funded by NIH/National Institute of Child Health and Human Development (NICHD) 1R01HD094731-01A1

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke

BACKGROUND AND OBJECTIVES: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. METHODS: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage. RESULTS: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (β = 0.21; 95% CI 0.04-0.38, DISCUSSION: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets

Blood–brain barrier link to human cognitive impairment and Alzheimer’s disease

Vascular dysfunction is frequently seen in disorders associated with cognitive impairment, dementia and Alzheimer’s disease (AD). Recent advances in neuroimaging and fluid biomarkers suggest that vascular dysfunction is not an innocent bystander only accompanying neuronal dysfunction. Loss of cerebrovascular integrity, often referred to as breakdown in the blood-brain barrier (BBB), has recently shown to be an early biomarker of human cognitive dysfunction and possibly underlying mechanism of age-related cognitive decline. Damage to the BBB may initiate or further invoke a range of tissue injuries causing synaptic and neuronal dysfunction and cognitive impairment that may contribute to AD. Therefore, better understanding of how vascular dysfunction caused by BBB breakdown interacts with amyloid-β and tau AD biomarkers to confer cognitive impairment may lead to new ways of thinking about pathogenesis, and possibly treatment and prevention of early cognitive impairment, dementia and AD, for which we still do not have effective therapies