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A researcher in the Division of Clinical Neurology has won a major award for his intelligent glasses that can help blind people to 'see'.
Genetic basis of lacunar stroke: a pooled analysis of individual patient data and genome-wide association studies.
BACKGROUND: The genetic basis of lacunar stroke is poorly understood, with a single locus on 16q24 identified to date. We sought to identify novel associations and provide mechanistic insights into the disease. METHODS: We did a pooled analysis of data from newly recruited patients with an MRI-confirmed diagnosis of lacunar stroke and existing genome-wide association studies (GWAS). Patients were recruited from hospitals in the UK as part of the UK DNA Lacunar Stroke studies 1 and 2 and from collaborators within the International Stroke Genetics Consortium. Cases and controls were stratified by ancestry and two meta-analyses were done: a European ancestry analysis, and a transethnic analysis that included all ancestry groups. We also did a multi-trait analysis of GWAS, in a joint analysis with a study of cerebral white matter hyperintensities (an aetiologically related radiological trait), to find additional genetic associations. We did a transcriptome-wide association study (TWAS) to detect genes for which expression is associated with lacunar stroke; identified significantly enriched pathways using multi-marker analysis of genomic annotation; and evaluated cardiovascular risk factors causally associated with the disease using mendelian randomisation. FINDINGS: Our meta-analysis comprised studies from Europe, the USA, and Australia, including 7338 cases and 254 798 controls, of which 2987 cases (matched with 29 540 controls) were confirmed using MRI. Five loci (ICA1L-WDR12-CARF-NBEAL1, ULK4, SPI1-SLC39A13-PSMC3-RAPSN, ZCCHC14, ZBTB14-EPB41L3) were found to be associated with lacunar stroke in the European or transethnic meta-analyses. A further seven loci (SLC25A44-PMF1-BGLAP, LOX-ZNF474-LOC100505841, FOXF2-FOXQ1, VTA1-GPR126, SH3PXD2A, HTRA1-ARMS2, COL4A2) were found to be associated in the multi-trait analysis with cerebral white matter hyperintensities (n=42 310). Two of the identified loci contain genes (COL4A2 and HTRA1) that are involved in monogenic lacunar stroke. The TWAS identified associations between the expression of six genes (SCL25A44, ULK4, CARF, FAM117B, ICA1L, NBEAL1) and lacunar stroke. Pathway analyses implicated disruption of the extracellular matrix, phosphatidylinositol 5 phosphate binding, and roundabout binding (false discovery rate <0·05). Mendelian randomisation analyses identified positive associations of elevated blood pressure, history of smoking, and type 2 diabetes with lacunar stroke. INTERPRETATION: Lacunar stroke has a substantial heritable component, with 12 loci now identified that could represent future treatment targets. These loci provide insights into lacunar stroke pathogenesis, highlighting disruption of the vascular extracellular matrix (COL4A2, LOX, SH3PXD2A, GPR126, HTRA1), pericyte differentiation (FOXF2, GPR126), TGF-β signalling (HTRA1), and myelination (ULK4, GPR126) in disease risk. FUNDING: British Heart Foundation.
Cortical Gyrification Morphology in Individuals with ASD and ADHD across the Lifespan: A Systematic Review and Meta-Analysis.
Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are common neurodevelopmental disorders (NDDs) that may impact brain maturation. A number of studies have examined cortical gyrification morphology in both NDDs. Here we review and when possible pool their results to better understand the shared and potentially disorder-specific gyrification features. We searched MEDLINE, PsycINFO, and EMBASE databases, and 24 and 10 studies met the criteria to be included in the systematic review and meta-analysis portions, respectively. Meta-analysis of local Gyrification Index (lGI) findings across ASD studies was conducted with SDM software adapted for surface-based morphometry studies. Meta-regressions were used to explore effects of age, sex, and sample size on gyrification differences. There were no significant differences in gyrification across groups. Qualitative synthesis of remaining ASD studies highlighted heterogeneity in findings. Large-scale ADHD studies reported no differences in gyrification between cases and controls suggesting that, similar to ASD, there is currently no evidence of differences in gyrification morphology compared with controls. Larger, longitudinal studies are needed to further clarify the effects of age, sex, and IQ on cortical gyrification in these NDDs.
OBJECTIVE: We sought to identify an abbreviated test of impaired olfaction, amenable for use in busy clinical environments in prodromal (isolated REM sleep Behavior Disorder (iRBD)) and manifest Parkinson's disease (PD). METHODS: 890 PD and 313 control participants in the Discovery cohort study underwent Sniffin' stick odour identification assessment. Random forests were initially trained to distinguish individuals with poor (functional anosmia/hyposmia) and good (normosmia/super-smeller) smell ability using all 16 Sniffin' sticks. Models were retrained using the top 3 sticks ranked by order of predictor importance. One randomly selected 3-stick model was tested in a second independent PD dataset (n=452) and in two iRBD datasets (Discovery n=241; Marburg n=37) before being compared to previously described abbreviated Sniffin' stick combinations. RESULTS: In differentiating poor from good smell ability, the overall area under the curve (AUC) value associated with the top 3 sticks (Anise/Licorice/Banana) was 0.95 in the development dataset (sensitivity:90%, specificity:92%, positive predictive value:92%, negative predictive value:90%). Internal and external validation confirmed AUCs≥0.90. The combination of 3-stick model determined poor smell and an RBD screening questionnaire score of ≥5, separated iRBD from controls with a sensitivity, specificity, PPV and NPV of 65%, 100%, 100% and 30%. CONCLUSIONS: Our 3-Sniffin'-stick model holds potential utility as a brief screening test in the stratification of individuals with PD and iRBD according to olfactory dysfunction. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that a 3-Sniffin'-stick model distinguishes individuals with poor and good smell ability and can be used to screen for individuals with iRBD.
Primary progressive aphasia (PPA) is characterised by predominant language and communication impairment. However, behavioural changes, such as apathy, are increasingly recognised. Apathy is defined as a reduction in motivation and goal-directed behaviour. Recent theoretical models have suggested that apathy can be delineated into multiple dimensions: executive apathy (i.e., deficits in maintaining goals and organisation), emotional apathy (i.e., emotional blunting and indifference) and initiation apathy (i.e., reduced self-initiation). Whether the nature of apathy differs between clinical variants of PPA, and across early and late disease stages, remains to be established. Here, carers/informants of 20 semantic variant PPA (svPPA), 15 non-fluent variant PPA (nfvPPA), 16 logopenic variant PPA (lvPPA) and 25 healthy older controls completed the Dimensional Apathy Scale to quantify executive, emotional and initiation apathy. Voxel-based morphometry was used to identify associations between dimensions of apathy and regions of grey matter intensity decrease. Our behavioural results showed greater executive and initiation apathy in late svPPA than in late nfvPPA patients, while late svPPA had greater emotional apathy than both late nfvPPA and late lvPPA groups. Executive and initiation apathy were significantly higher than premorbid levels in all PPA subtypes, while elevated emotional apathy was only seen in early and late svPPA. Distinct neural correlates were identified across apathy dimensions. Executive apathy correlated with grey matter intensity of the left dorsolateral prefrontal and inferior parietal cortices; emotional apathy with the left medial prefrontal, insular and cerebellar regions; and initiation apathy with right parietal areas. Our findings are the first to reveal evidence of the dimensional nature of apathy in PPA, with different clinical signatures observed for each subtype. From a clinical standpoint, these results will inform the development of targeted interventions for specific aspects of apathy which emerge in PPA.
White matter hyperintensities classified according to intensity and spatial location reveal specific associations with cognitive performance.
White matter hyperintensities (WMHs) on T<sub>2</sub>-weighted images are radiological signs of cerebral small vessel disease. As their total volume is variably associated with cognition, a new approach that integrates multiple radiological criteria is warranted. Location may matter, as periventricular WMHs have been shown to be associated with cognitive impairments. WMHs that appear as hypointense in T<sub>1</sub>-weighted images (T<sub>1</sub>w) may also indicate the most severe component of WMHs. We developed an automatic method that sub-classifies WMHs into four categories (periventricular/deep and T<sub>1</sub>w-hypointense/nonT<sub>1</sub>w-hypointense) using MRI data from 684 community-dwelling older adults from the Whitehall II study. To test if location and intensity information can impact cognition, we derived two general linear models using either overall or subdivided volumes. Results showed that periventricular T<sub>1</sub>w-hypointense WMHs were significantly associated with poorer performance in the trail making A (p = 0.011), digit symbol (p = 0.028) and digit coding (p = 0.009) tests. We found no association between total WMH volume and cognition. These findings suggest that sub-classifying WMHs according to both location and intensity in T<sub>1</sub>w reveals specific associations with cognitive performance.
Network Analysis of the CSF Proteome Characterizes Convergent Pathways of Cellular Dysfunction in ALS.
Background: Amyotrophic lateral sclerosis is a clinical syndrome with complex biological determinants, but which in most cases is characterized by TDP-43 pathology. The identification in CSF of a protein signature of TDP-43 network dysfunction would have the potential to inform the identification of new biomarkers and therapeutic targets. Methods: We compared CSF proteomic data from patients with ALS (n = 41), Parkinson's disease (n = 19) and healthy control participants (n = 20). Weighted correlation network analysis was used to identify modules within the CSF protein network and combined with gene ontology enrichment analysis to functionally annotate module proteins. Analysis of module eigenproteins and differential correlation analysis of the CSF protein network was used to compare ALS and Parkinson's disease protein co-correlation with healthy controls. In order to monitor temporal changes in the CSF proteome, we performed longitudinal analysis of the CSF proteome in a subset of ALS patients. Results: Weighted correlation network analysis identified 10 modules, including those enriched for terms involved in gene expression including nucleic acid binding, RNA metabolism and translation; humoral immune system function, including complement pathways; membrane proteins, axonal outgrowth and adherence; and glutamatergic synapses. Immune system module eigenproteins were increased in ALS, whilst axonal module eigenproteins were decreased in ALS. The 19 altered protein correlations in ALS were enriched for gene expression (OR 3.05, p = 0.017) and membrane protein modules (OR 17.48, p = 0.011), including intramodular hub proteins previously identified as TDP-43 interactors. Proteins decreasing over longitudinal analysis ALS were enriched in glutamatergic synapse and axonal outgrowth modules. Protein correlation network disruptions in Parkinson's disease showed no module enrichment. Conclusions: Alterations in the co-correlation network in CSF samples identified a set of pathways known to be associated with TDP-43 dysfunction in the pathogenesis of ALS, with important implications for therapeutic targeting and biomarker development.
Targeted next generation sequencing and family survey enable correct genetic diagnosis in CRX associated macular dystrophy - a case report.
BACKGROUND: We present 3 members of a family with macular dystrophy, originally diagnosed as Stargardt disease, with a significantly variable age at onset, caused by a heterozygous mutation in CRX. CASE PRESENTATION: A 43-year-old female with bull's eye maculopathy, whose sister was diagnosed with Stargardt disease previously at another centre, was found to have a single ABCA4 variant. Further examination of the family revealed that the asymptomatic father was also affected, indicating a dominant pattern of inheritance. In addition, the ABCA4 variant was not identified in the sister originally diagnosed with Stargardt disease. Next generation sequencing identified a heterozygous c.121C > T, p.R41W missense mutation in CRX in all 3 affected members. CONCLUSIONS: We describe a common phenotype, but with variable age at onset, with autosomal dominant inheritance and reduced penetrance in a family found to have a pathogenic sequence variant in CRX. This illustrates the importance of panel based molecular genetic testing accompanied by family studies to establish a definitive diagnosis.
Machine Learning Quantitation of Cardiovascular and Cerebrovascular Disease: A Systematic Review of Clinical Applications
<jats:p>Research into machine learning (ML) for clinical vascular analysis, such as those useful for stroke and coronary artery disease, varies greatly between imaging modalities and vascular regions. Limited accessibility to large diverse patient imaging datasets, as well as a lack of transparency in specific methods, are obstacles to further development. This paper reviews the current status of quantitative vascular ML, identifying advantages and disadvantages common to all imaging modalities. Literature from the past 8 years was systematically collected from MEDLINE® and Scopus database searches in January 2021. Papers satisfying all search criteria, including a minimum of 50 patients, were further analysed and extracted of relevant data, for a total of 47 publications. Current ML image segmentation, disease risk prediction, and pathology quantitation methods have shown sensitivities and specificities over 70%, compared to expert manual analysis or invasive quantitation. Despite this, inconsistencies in methodology and the reporting of results have prevented inter-model comparison, impeding the identification of approaches with the greatest potential. The clinical potential of this technology has been well demonstrated in Computed Tomography of coronary artery disease, but remains practically limited in other modalities and body regions, particularly due to a lack of routine invasive reference measurements and patient datasets.</jats:p>
Global proteomic analysis of extracellular matrix in mouse and human brain highlights relevance to cerebrovascular disease.
The extracellular matrix (ECM) is a key interface between the cerebrovasculature and adjacent brain tissues. Deregulation of the ECM contributes to a broad range of neurological disorders. However, despite this importance, our understanding of the ECM composition remains very limited mainly due to difficulties in its isolation. To address this, we developed an approach to extract the cerebrovascular ECM from mouse and human post-mortem normal brain tissues. We then used mass spectrometry with off-line high-pH reversed-phase fractionation to increase the protein detection. This identified more than 1000 proteins in the ECM-enriched fraction, with > 66% of the proteins being common between the species. We report 147 core ECM proteins of the human brain vascular matrisome, including collagens, laminins, fibronectin and nidogens. We next used network analysis to identify the connection between the brain ECM proteins and cerebrovascular diseases. We found that genes related to cerebrovascular diseases, such as COL4A1, COL4A2, VCAN and APOE were significantly enriched in the cerebrovascular ECM network. This provides unique mechanistic insight into cerebrovascular disease and potential drug targets. Overall, we provide a powerful resource to study the functions of brain ECM and highlight a specific role for brain vascular ECM in cerebral vascular disease.
BACKGROUND: Coronavirus disease 2019 (COVID-19) has placed a tremendous strain on healthcare services. This study, prepared by a large international panel of stroke experts, assesses the rapidly growing research and personal experience with COVID-19 stroke and offers recommendations for stroke management in this challenging new setting: modifications needed for prehospital emergency rescue and hyperacute care; inpatient intensive or stroke units; posthospitalization rehabilitation; follow-up including at-risk family and community; and multispecialty departmental developments in the allied professions. SUMMARY: The severe acute respiratory syndrome coronavirus 2 uses spike proteins binding to tissue angiotensin-converting enzyme (ACE)-2 receptors, most often through the respiratory system by virus inhalation and thence to other susceptible organ systems, leading to COVID-19. Clinicians facing the many etiologies for stroke have been sobered by the unusual incidence of combined etiologies and presentations, prominent among them are vasculitis, cardiomyopathy, hypercoagulable state, and endothelial dysfunction. International standards of acute stroke management remain in force, but COVID-19 adds the burdens of personal protections for the patient, rescue, and hospital staff and for some even into the postdischarge phase. For pending COVID-19 determination and also for those shown to be COVID-19 affected, strict infection control is needed at all times to reduce spread of infection and to protect healthcare staff, using the wealth of well-described methods. For COVID-19 patients with stroke, thrombolysis and thrombectomy should be continued, and the usual early management of hypertension applies, save that recent work suggests continuing ACE inhibitors and ARBs. Prothrombotic states, some acute and severe, encourage prophylactic LMWH unless bleeding risk is high. COVID-19-related cardiomyopathy adds risk of cardioembolic stroke, where heparin or warfarin may be preferable, with experience accumulating with DOACs. As ever, arteritis can prove a difficult diagnosis, especially if not obvious on the acute angiogram done for clot extraction. This field is under rapid development and may generate management recommendations which are as yet unsettled, even undiscovered. Beyond the acute management phase, COVID-19-related stroke also forces rehabilitation services to use protective precautions. As with all stroke patients, health workers should be aware of symptoms of depression, anxiety, insomnia, and/or distress developing in their patients and caregivers. Postdischarge outpatient care currently includes continued secondary prevention measures. Although hoping a COVID-19 stroke patient can be considered cured of the virus, those concerned for contact safety can take comfort in the increasing use of telemedicine, which is itself a growing source of patient-physician contacts. Many online resources are available to patients and physicians. Like prior challenges, stroke care teams will also overcome this one. Key Messages: Evidence-based stroke management should continue to be provided throughout the patient care journey, while strict infection control measures are enforced.
Erratum to: Tackling challenges in care of Alzheimer's disease and other dementias amid the COVID-19 pandemic, now and in the future (Alzheimer's & Dementia, (2020), 16, 11, (1571-1581), 10.1002/alz.12143)
In the paper by Mok et al. (“Tackling challenges in care of Alzheimer's disease and other dementias amid the COVID-19 pandemic, now and in the future.”Alzheimer's Dement. 2020; 16: 1571-1581. https://doi.org/10.1002/alz.12143), an error occurred in the preparation of the paper for publication, requiring the following correction. In the initial publication of this article, Vorapun Senanarong, BSc, MD, was inadvertently omitted from the author group. The corrected author group and affiliations list appear above. We regret the error.