Absolute risk and predictors of the growth of acute spontaneous intracerebral haemorrhage: a systematic review and meta-analysis of individual patient data.

Background Intracerebral haemorrhage growth is associated with poor clinical outcome and is a therapeutic target for improving outcome. We aimed to determine the absolute risk and predictors of intracerebral haemorrhage growth, develop and validate prediction models, and evaluate the added value of CT angiography. Methods In a systematic review of OVID MEDLINE—with additional hand-searching of relevant studies' bibliographies— from Jan 1, 1970, to Dec 31, 2015, we identified observational cohorts and randomised trials with repeat scanning protocols that included at least ten patients with acute intracerebral haemorrhage. We sought individual patient-level data from corresponding authors for patients aged 18 years or older with data available from brain imaging initially done 0·5–24 h and repeated fewer than 6 days after symptom onset, who had baseline intracerebral haemorrhage volume of less than 150 mL, and did not undergo acute treatment that might reduce intracerebral haemorrhage volume. We estimated the absolute risk and predictors of the primary outcome of intracerebral haemorrhage growth (defined as >6 mL increase in intracerebral haemorrhage volume on repeat imaging) using multivariable logistic regression models in development and validation cohorts in four subgroups of patients, using a hierarchical approach: patients not taking anticoagulant therapy at intracerebral haemorrhage onset (who constituted the largest subgroup), patients taking anticoagulant therapy at intracerebral haemorrhage onset, patients from cohorts that included at least some patients taking anticoagulant therapy at intracerebral haemorrhage onset, and patients for whom both information about anticoagulant therapy at intracerebral haemorrhage onset and spot sign on acute CT angiography were known. Findings Of 4191 studies identified, 77 were eligible for inclusion. Overall, 36 (47%) cohorts provided data on 5435 eligible patients. 5076 of these patients were not taking anticoagulant therapy at symptom onset (median age 67 years, IQR 56–76), of whom 1009 (20%) had intracerebral haemorrhage growth. Multivariable models of patients with data on antiplatelet therapy use, data on anticoagulant therapy use, and assessment of CT angiography spot sign at symptom onset showed that time from symptom onset to baseline imaging (odds ratio 0·50, 95% CI 0·36–0·70; p<0·0001), intracerebral haemorrhage volume on baseline imaging (7·18, 4·46–11·60; p<0·0001), antiplatelet use (1·68, 1·06–2·66; p=0·026), and anticoagulant use (3·48, 1·96–6·16; p<0·0001) were independent predictors of intracerebral haemorrhage growth (C-index 0·78, 95% CI 0·75–0·82). Addition of CT angiography spot sign (odds ratio 4·46, 95% CI 2·95–6·75; p<0·0001) to the model increased the C-index by 0·05 (95% CI 0·03–0·07). Interpretation In this large patient-level meta-analysis, models using four or five predictors had acceptable to good discrimination. These models could inform the location and frequency of observations on patients in clinical practice, explain treatment effects in prior randomised trials, and guide the design of future trials

Recommendations from the international stroke genetics consortium, part 2: Biological sample collection and storage

The revolution in human genetics, catalyzed by the sequencing of the human genome in 2003 and the development of genome-wide genotyping technologies, has led to the identification of >2000 trait-associated genetic variants. Because most of these variants have individually small effects on disease risk, successful gene discovery efforts have required large sample sizes (involving thousands, tens, or hundreds of thousands of cases and controls) to achieve sufficient study power. Amassing such sample sizes has depended on international collaboration on a scale never seen before in human genetics or even in clinical research. Disease-specific consortia bringing together many individual sites and collaborators have now evolved for many major diseases. Each consortium has faced with ≥2 fundamental questions: how to assemble a study sample of sufficient size, homogeneity, and phenotypic quality and how to retain and analyze, sometimes repeatedly over several years, biological samples from enrolled subjects

Damage in concrete and geomaterials

Risk and clinical outcome of stroke, as for nearly all complex conditions, is polygenic. Discovering influential genetic variants offers the promise of new and personalized treatments that will substantially reduce the devastating effects of stroke on global health. Adequate power to detect multiple genetic risk alleles requires large sample sizes. Although stroke is the second leading cause of death worldwide and a major contributor to adult disability, no individual center can collect sufficient samples on its own. Recognizing this challenge, in 2007, stroke researchers from around the world formed the International Stroke Genetics Consortium (ISGC, http://www.strokegenetics.org). The ISGC mission is to identify genetic factors influencing stroke risk, prognosis, and treatment response by studying patients enrolled at centers around the globe. Although there has been notable early success, much work remains not only to achieve the ultimate goal of personalized medicine in stroke, finding genetic risk alleles, but also, more importantly, to develop comprehensive stroke risk assessments with actionable clinical results. Judging from developments in other complex diseases, such as diabetes mellitus and coronary artery disease, sample sizes of the order of 100 000 to 200 000 will be needed to identify the full range of genetic variation involved in stroke. Achieving such sample sizes requires even larger collaboration

Common variation in COL4A1/COL4A2 is associated with sporadic cerebral small vessel disease

Objectives:We hypothesized that common variants in the collagen genes COL4A1/COL4A2 are associated with sporadic forms of cerebral small vessel disease.Methods:We conducted meta-analyses of existing genotype data among individuals of European ancestry to determine associations of 1,070 common single nucleotide polymorphisms (SNPs) in the COL4A1/COL4A2 genomic region with the following: intracerebral hemorrhage and its subtypes (deep, lobar) (1,545 cases, 1,485 controls); ischemic stroke and its subtypes (cardioembolic, large vessel disease, lacunar) (12,389 cases, 62,004 controls); and white matter hyperintensities (2,733 individuals with ischemic stroke and 9,361 from population-based cohorts with brain MRI data). We calculated a statistical significance threshold that accounted for multiple testing and linkage disequilibrium between SNPs (p 0.9 between SNPs). Although SNPs associated with deep intracerebral hemorrhage did not reach our significance threshold for association with lacunar ischemic stroke (lead SNP OR 1.10, 95% CI 1.03-1.18, p = 0.0073), and with white matter hyperintensity volume in symptomatic ischemic stroke patients (lead SNP OR 1.07, 95% CI 1.01-1.13, p = 0.016), the direction of association was the same. There was no convincing evidence of association with white matter hyperintensities in population-based studies or with non-small vessel disease cerebrovascular phenotypes.Conclusions:Our results indicate an association between common variation in the COL4A2 gene and symptomatic small vessel disease, particularly deep intracerebral hemorrhage. These findings merit replication studies, including in ethnic groups of non-European ancestry

Relative effects of LDL-C on ischemic stroke and coronary disease A Mendelian randomization study

OBJECTIVE: To examine the causal relevance of lifelong differences in low-density lipoprotein cholesterol (LDL-C) for ischemic stroke (IS) relative to that for coronary heart disease (CHD) using a Mendelian randomization approach. METHODS: We undertook a 2-sample Mendelian randomization, based on summary data, to estimate the causal relevance of LDL-C for risk of IS and CHD. Information from 62 independent genetic variants with genome-wide significant effects on LDL-C levels was used to estimate the causal effects of LDL-C for IS and IS subtypes (based on 12,389 IS cases from METASTROKE) and for CHD (based on 60,801 cases from CARDIoGRAMplusC4D). We then assessed the effects of LDL-C on IS and CHD for heterogeneity. RESULTS: A 1 mmol/L higher genetically determined LDL-C was associated with a 50% higher risk of CHD (odds ratio [OR] 1.49, 95% confidence interval [CI] 1.32-1.68, p = 1.1 × 10-8). By contrast, the causal effect of LDL-C was much weaker for IS (OR 1.12, 95% CI 0.96-1.30, p = 0.14; p for heterogeneity = 2.6 × 10-3) and, in particular, for cardioembolic stroke (OR 1.06, 95% CI 0.84-1.33, p = 0.64; p for heterogeneity = 8.6 × 10-3) when compared with that for CHD. CONCLUSIONS: In contrast with the consistent effects of LDL-C-lowering therapies on IS and CHD, genetic variants that confer lifelong LDL-C differences show a weaker effect on IS than on CHD. The relevance of etiologically distinct IS subtypes may contribute to the differences observed