Genetics of common polygenic ischaemic stroke: current understanding and future challenges.

Stroke is the third commonest cause of death and the major cause of adult neurological disability worldwide. While much is known about conventional risk factors such as hypertension, diabetes and incidence of smoking, these environmental factors only account for a proportion of stroke risk. Up to 50% of stroke risk can be attributed to genetic risk factors, although to date no single risk allele has been convincingly identified as contributing to this risk. Advances in the field of genetics, most notably genome wide association studies (GWAS), have revealed genetic risks in other cardiovascular disease and these techniques are now being applied to ischaemic stroke. This paper covers previous genetic studies in stroke including candidate gene studies, discusses the genome wide association approach, and future techniques such as next generation sequencing and the post-GWAS era. The review also considers the overlap from other cardiovascular diseases and whether findings from these may also be informative in ischaemic stroke

Depression in small-vessel disease relates to white matter ultrastructural damage, not disability.

OBJECTIVE: To determine whether cerebral small-vessel disease (SVD) is a specific risk factor for depression, whether any association is mediated via white matter damage, and to study the role of depressive symptoms and disability on quality of life (QoL) in this patient group. METHODS: Using path analyses in cross-sectional data, we modeled the relationships among depression, disability, and QoL in patients with SVD presenting with radiologically confirmed lacunar stroke (n = 100), and replicated results in a second SVD cohort (n = 100). We then compared the same model in a non-SVD stroke cohort (n = 50) and healthy older adults (n = 203). In a further study, to determine the role of white matter damage in mediating the association with depression, a subgroup of patients with SVD (n = 101) underwent diffusion tensor imaging (DTI). RESULTS: Reduced QoL was associated with depression in patients with SVD, but this association was not mediated by disability or cognition; very similar results were found in the replication SVD cohort. In contrast, the non-SVD stroke group and the healthy older adult group showed a direct relationship between disability and depression. The DTI study showed that fractional anisotropy, a marker of white matter damage, was related to depressive symptoms in patients with SVD. CONCLUSION: These results suggest that in stroke patients without SVD, disability is an important causal factor for depression, whereas in SVD stroke, other factors specific to this stroke subtype have a causal role. White matter damage detected on DTI is one factor that mediates the association between SVD and depression

Structural network efficiency is associated with cognitive impairment in small-vessel disease.

To characterize brain network connectivity impairment in cerebral small-vessel disease (SVD) and its relationship with MRI disease markers and cognitive impairment.METHODS: A cross-sectional design applied graph-based efficiency analysis to deterministic diffusion tensor tractography data from 115 patients with lacunar infarction and leukoaraiosis and 50 healthy individuals. Structural connectivity was estimated between 90 cortical and subcortical brain regions and efficiency measures of resulting graphs were analyzed. Networks were compared between SVD and control groups, and associations between efficiency measures, conventional MRI disease markers, and cognitive function were tested.RESULTS: Brain diffusion tensor tractography network connectivity was significantly reduced in SVD: networks were less dense, connection weights were lower, and measures of network efficiency were significantly disrupted. The degree of brain network disruption was associated with MRI measures of disease severity and cognitive function. In multiple regression models controlling for confounding variables, associations with cognition were stronger for network measures than other MRI measures including conventional diffusion tensor imaging measures. A total mediation effect was observed for the association between fractional anisotropy and mean diffusivity measures and executive function and processing speed.CONCLUSIONS: Brain network connectivity in SVD is disturbed, this disturbance is related to disease severity, and within a mediation framework fully or partly explains previously observed associations between MRI measures and SVD-related cognitive dysfunction. These cross-sectional results highlight the importance of network disruption in SVD and provide support for network measures as a disease marker in treatment studies

Novel intelligent wavelet filtering of embolic signals from TCD ultrasound

Transcranial Doppler ultrasound can be used to detect emboli in blood flow for predicting stroke. Embolic signals have characteristic transient chirps suitable for wavelet analysis. We have implemented and evaluated the first on-line intelligent wavelet filter to amplify embolic signals building on our previous work in detection. Our intelligent wavelet amplifier uses the matching filter properties of the Daubechies 8th order wavelet to amplify embolic signals. Even the smallest embolic signal is enhanced without affecting the background blood flow signal. We show an increase of over 2db (on average) in embolic signal strength and an improvement in detection of 10-20%

Mendelian randomization study of the association between telomere length and risk of cancer and non-neoplastic diseases

$\textbf{Importance}$ The causal direction and magnitude of the association between telomere length and incidence of cancer and non-neoplastic diseases is uncertain, due to the susceptibility of observational studies to confounding and reverse causation. $\textbf{Objective}$ To conduct a Mendelian randomization study, using germline genetic variants as instrumental variables, to appraise the causal relevance of telomere length for risk of cancer and non-neoplastic diseases. $\textbf{Data Sources}$ Genome-wide association studies (GWAS) published up to January 15 2015. $\textbf{Study Selection}$ GWAS of non-communicable diseases that assayed germline genetic variation and did not select cohort or control participants on the basis of pre-existing diseases. Of 163 GWAS of non-communicable diseases identified, summary data from 103 were available. $\textbf{Data Extraction}$ Summary association statistics for single nucleotide polymorphisms (SNPs) that are strongly associated with telomere length in the general population. $\textbf{Main Outcomes}$ Odds ratios (ORs) for disease per standard deviation (SD) higher telomere length due to germline genetic variation. $\textbf{Results}$ Summary data were available for 35 cancers and 48 non-neoplastic diseases, corresponding to 420,081 cases (median 2,526 per disease) and 1,093,105 controls (median 6,789 per disease). Increased telomere length due to germline genetic variation was generally associated with increased risk for site-specific cancers. The strongest associations were observed for (ORs per 1-SD change in genetically increased telomere length): glioma 5.27 (3.15-8.81), serous low-malignant-potential ovarian cancer 4.35 (2.39-7.94), lung adenocarcinoma 3.19 (2.40-4.22), neuroblastoma 2.98 (1.92-4.62) , bladder cancer 2.19 (1.32-3.66), melanoma 1.87 (1.55-2.26), testicular cancer 1.76 (1.02- 3.04), kidney cancer 1.55 (1.08-2.23) and endometrial cancer 1.31 (1.07-1.61). Associations were stronger for rarer cancers and at tissue sites with lower rates of stem cell division (P<0.05). There was generally little evidence of association between genetically increased telomere length and risk of psychiatric, autoimmune, inflammatory, diabetic and other non-neoplastic diseases, except for coronary heart disease (0.78 [0.67-0.90]), abdominal aortic aneurysm (0.63 [0.49-0.81]), celiac disease (0.42 [0.28-0.61]) and interstitial lung disease (0.09 [0.05- 0.15]). $\textbf{Conclusions}$ It is likely that longer telomeres increase risk for several cancers but reduce risk for some non-neoplastic diseases, including cardiovascular diseases.This work was supported by CRUK grant number C18281/A19169 (the Integrative Cancer Epidemiology Programme). Dr Haycock is supported by CRUK Population Research Postdoctoral Fellowship C52724/A20138. The MRC Integrative Epidemiology Unit is supported by grants MC_UU_12013/1 and MC_UU_12013/2. Dr Martin is supported by the National Institute for Health Research (NIHR), the Bristol Nutritional Biomedical Research Unit and the University of Bristol

The Brief Memory and Executive Test (BMET) for detecting vascular cognitive impairment in small vessel disease: a validation study.

Cognitive impairment is common in patients with cerebral small vessel disease, but is not well detected using common cognitive screening tests which have been primarily devised for cortical dementias. We developed the Brief Memory and Executive Test (BMET); a rapid screening measure sensitive to the impaired executive function and processing speed characteristic of small vessel disease (SVD). To assess the BMET's validity for general use, we evaluated it when administered by non-psychologists in a multicentre study and collected control data to derive normative scores.The BMET study was funded by The Stroke Association (TSA2010/08). Recruitment to BMET was supported by the NIHR Stroke Clinical Research Network. Hugh Markus is supported by an NIHR Senior Investigator award and his work is supported by the Cambridge University Hospitals NIHR Comprehensive BRC. Matthew Hollocks is supported by a Stroke Association/British Heart Foundation Grant (TSA BHF 2010/01). Robin Morris receives consultancy fees for P1Vital Limited. The authors disclose no competing interests financial or otherwise

PET imaging of the neurovascular interface in cerebrovascular disease

Cerebrovascular disease encompasses a range of pathologies affecting different components of the cerebral vasculature and brain parenchyma. Large artery atherosclerosis, acute cerebral ischaemia, and intracerebral small vessel disease all demonstrate metabolic processes that are key to pathogenesis. Although structural imaging has been a mainstay of stroke clinical care and research, it has limited ability to detect these pathophysiological processes in vivo. Positron emission tomography (PET) provides a means to detect and quantify metabolic processes in each facet of cerebrovascular disease non-invasively. The use of PET has helped shape the understanding of key concepts in cerebrovascular medicine, including the vulnerable atherosclerotic plaque, salvageable ischaemic penumbra, neuroinflammation and selective neuronal loss after ischaemic insult, and the relationships between chronic hypoxia, neuroinflammation, and amyloid deposition in cerebral small vessel disease. This review considers how the ability to image these processes at the neurovascular interface has contributed to our understanding of cerebrovascular disease and facilitated translational research to advance clinical care.N.R.E. is supported by a research training fellowship from The Dunhill Medical Trust (grant number RTF44/0114). J.M.T. is supported by a Wellcome Trust research training fellowship (104492/Z/14/Z). J.H.F.R. is part-supported by the Higher Education Funding Council for England (HEFCE), the British Heart Foundation, and the Wellcome Trust. H.S.M. is supported by the Medical Research Council (MRC) as a National Institute for Health Research (NIHR) Senior Investigator. E.A.W. is supported by the British Heart Foundation. H.S.M., J.H.F.R., and E.A.W. are supported by the NIHR Cambridge Biomedical Research Centre

Cerebral Amyloid Angiopathy and the Fibrinolytic System: Is Plasmin a Therapeutic Target?

Cerebral amyloid angiopathy is a devastating cause of intracerebral hemorrhage for which there is no specific secondary stroke prevention treatment. Here we review the current literature regarding cerebral amyloid angiopathy pathophysiology and treatment, as well as what is known of the fibrinolytic pathway and its interaction with amyloid. We postulate that tranexamic acid is a potential secondary stroke prevention treatment agent in sporadic cerebral amyloid angiopathy, although further research is required

Stroke genetics: prospects for personalized medicine.

Epidemiologic evidence supports a genetic predisposition to stroke. Recent advances, primarily using the genome-wide association study approach, are transforming what we know about the genetics of multifactorial stroke, and are identifying novel stroke genes. The current findings are consistent with different stroke subtypes having different genetic architecture. These discoveries may identify novel pathways involved in stroke pathogenesis, and suggest new treatment approaches. However, the already identified genetic variants explain only a small proportion of overall stroke risk, and therefore are not currently useful in predicting risk for the individual patient. Such risk prediction may become a reality as identification of a greater number of stroke risk variants that explain the majority of genetic risk proceeds, and perhaps when information on rare variants, identified by whole-genome sequencing, is also incorporated into risk algorithms. Pharmacogenomics may offer the potential for earlier implementation of 'personalized genetic' medicine. Genetic variants affecting clopidogrel and warfarin metabolism may identify non-responders and reduce side-effects, but these approaches have not yet been widely adopted in clinical practice

Diffusion tensor image segmentation of the cerebrum provides a single measure of cerebral small vessel disease severity related to cognitive change.

Cerebral small vessel disease (SVD) is the primary cause of vascular cognitive impairment and is associated with decline in executive function (EF) and information processing speed (IPS). Imaging biomarkers are needed that can monitor and identify individuals at risk of severe cognitive decline. Recently there has been interest in combining several magnetic resonance imaging (MRI) markers of SVD into a unitary score to describe disease severity. Here we apply a diffusion tensor image (DTI) segmentation technique (DSEG) to describe SVD related changes in a single unitary score across the whole cerebrum, to investigate its relationship with cognitive change over a three-year period. 98 patients (aged 43-89) with SVD underwent annual MRI scanning and cognitive testing for up to three years. DSEG provides a vector of 16 discrete segments describing brain microstructure of healthy and/or damaged tissue. By calculating the scalar product of each DSEG vector in reference to that of a healthy ageing control we generate an angular measure (DSEG θ) describing the patients' brain tissue microstructural similarity to a disease free model of a healthy ageing brain. Conventional MRI markers of SVD brain change were also assessed including white matter hyperintensities, cerebral atrophy, incident lacunes, cerebral-microbleeds, and white matter microstructural damage measured by DTI histogram parameters. The impact of brain change on cognition was explored using linear mixed-effects models. Post-hoc sample size analysis was used to assess the viability of DSEG θ as a tool for clinical trials. Changes in brain structure described by DSEG θ were related to change in EF and IPS (p < 0.001) and remained significant in multivariate models including other MRI markers of SVD as well as age, gender and premorbid IQ. Of the conventional markers, presence of new lacunes was the only marker to remain a significant predictor of change in EF and IPS in the multivariate models (p = 0.002). Change in DSEG θ was also related to change in all other MRI markers (p < 0.017), suggesting it may be used as a surrogate marker of SVD damage across the cerebrum. Sample size estimates indicated that fewer patients would be required to detect treatment effects using DSEG θ compared to conventional MRI and DTI markers of SVD severity. DSEG θ is a powerful tool for characterising subtle brain change in SVD that has a negative impact on cognition and remains a significant predictor of cognitive change when other MRI markers of brain change are accounted for. DSEG provides an automatic segmentation of the whole cerebrum that is sensitive to a range of SVD related structural changes and successfully predicts cognitive change. Power analysis shows DSEG θ has potential as a monitoring tool in clinical trials. As such it may provide a marker of SVD severity from a single imaging modality (i.e. DTIs)