Tobacco use and risk of acute stroke in 32 countries in the INTERSTROKE study: a case-control study.

Background: Smoking is a major risk factor for the global burden of stroke. We have previously reported a global population attributable risk (PAR) of stroke of 12.4% associated with current smoking. In this study we aimed to explore the association of current tobacco use with different types of tobacco exposure and environmental tobacco smoke (ETS) exposure on the risk of stroke and stroke subtypes, and by regions and country income levels. Methods: The INTERSTROKE study is a case-control study of acute first stroke and was undertaken with 13,462 stroke cases and 13,488 controls recruited between January 11, 2007 and August 8, 2015 in 32 countries worldwide. Association of risk of tobacco use and ETS exposure were analysed with overall stroke, ischemic and intracerebral hemorrhage (ICH), and with TOAST etiological stroke subtypes (large vessel, small vessel, cardioembolism, and undetermined). Findings: Current smoking was associated with an increased risk of all stroke (odds ratio [OR] 1.64, 95% CI 1.46-1.84), and had a stronger association with ischemic stroke (OR 1.85, 95% CI 1.61-2.11) than ICH (OR 1.19 95% CI 1.00-1.41). The OR and PAR of stroke among current smokers varied significantly between regions and income levels with high income countries (HIC) having the highest odds (OR 3.02 95% CI 2.24-4.10) and PAR (18.6%, 15.1-22.8%). Among etiological subtypes of ischemic stroke, the strongest association of current smoking was seen for large vessel stroke (OR 2.16, 95% CI 1.63-2.87) and undetermined cause (OR 1.97, 95% CI 1.55-2.50). Both filtered (OR 1.73, 95% CI 1.50-1.99) and non-filtered (OR 2.59, 95% CI 1.79-3.77) cigarettes were associated with stroke risk. ETS exposure increased the risk of stroke in a dose-dependent manner, exposure for more than 10 h per week increased risk for all stroke (OR 1.95, 95% CI 1.69-2.27), ischemic stroke (OR 1.89, 95% CI 1.59-2.24) and ICH (OR 2.00, 95% CI 1.60-2.50). Interpretation: There are significant variations in the magnitude of risk and PAR of stroke according to the types of tobacco used, active and ETS exposure, and countries with different income levels. Specific strategies to discourage tobacco use by any form and to build a smoke free environment should be implemented to ease the global burden of stroke. Funding: The Canadian Institutes of Health Research, Heart and Stroke Foundation of Canada, Canadian Stroke Network, Swedish Research Council, Swedish Heart and Lung Foundation, The Health & Medical Care Committee of the Regional Executive Board, Region Västra Götaland, and through unrestricted grants from several pharmaceutical companies with major contributions from Astra Zeneca, Boehringer Ingelheim (Canada), Pfizer (Canada), MERCK, Sharp and Dohme, Swedish Heart and Lung Foundation, UK Chest, and UK Heart and Stroke.

A versatile, fast and unbiased method for estimation of gene-by-environment interaction effects on biobank-scale datasets.

Identification of gene-by-environment interactions (GxE) is crucial to understand the interplay of environmental effects on complex traits. However, current methods evaluating GxE on biobank-scale datasets have limitations. We introduce MonsterLM, a multiple linear regression method that does not rely on model specification and provides unbiased estimates of variance explained by GxE. We demonstrate robustness of MonsterLM through comprehensive genome-wide simulations using real genetic data from 325,989 individuals. We estimate GxE using waist-to-hip-ratio, smoking, and exercise as the environmental variables on 13 outcomes (N = 297,529-325,989) in the UK Biobank. GxE variance is significant for 8 environment-outcome pairs, ranging from 0.009 - 0.071. The majority of GxE variance involves SNPs without strong marginal or interaction associations. We observe modest improvements in polygenic score prediction when incorporating GxE. Our results imply a significant contribution of GxE to complex trait variance and we show MonsterLM to be well-purposed to handle this with biobank-scale data.

Barrier materials for prevention of surgical adhesions: systematic review.

BACKGROUND: Postoperative surgical adhesions constitute a major health burden internationally. A wide range of materials have been evaluated, but despite constructive efforts and the obvious necessity, there remains no specific barrier widely utilized to prevent postoperative adhesion formation. The aim of this study was to highlight and characterize materials used for prevention of postoperative surgical adhesions in both animal and human studies. METHODS: A systematic review was performed of all original research articles presenting data related to the prevention of postoperative adhesions using a barrier agent. All available observational studies and randomized trials using animal models or human participants were included, with no restrictions related to type of surgery. PubMed and Embase databases were searched using key terms from inception to August 2019. Standardized data collection forms were used to extract details for each study and assess desirable characteristics of each barrier and success in animal and/or human studies. RESULTS: A total of 185 articles were identified for inclusion in the review, with a total of 67 unique adhesion barrier agents (37 natural and 30 synthetic materials). Desirable barrier characteristics of an ideal barrier were identified on review of the literature. Ten barriers achieved the primary outcome of reducing the incidence of postoperative adhesions in animal studies followed with positive outputs in human participants. A further 48 materials had successful results from animal studies, but with no human study performed to date. DISCUSSION: Multiple barriers showed promise in animal studies, with several progressing to success, and fulfilment of desirable qualities, in human trials. No barrier is currently utilized commonly worldwide, but potential barriers have been identified to reduce the burden of postoperative adhesions and associated sequelae.

GWAS and ExWAS of blood mitochondrial DNA copy number identifies 71 loci and highlights a potential causal role in dementia.

Background: Mitochondrial DNA copy number (mtDNA-CN) is an accessible blood-based measurement believed to capture underlying mitochondrial (MT) function. The specific biological processes underpinning its regulation, and whether those processes are causative for disease, is an area of active investigation. Methods: We developed a novel method for array-based mtDNA-CN estimation suitable for biobank-scale studies, called 'automatic mitochondrial copy (AutoMitoC).' We applied AutoMitoC to 395,781 UKBiobank study participants and performed genome- and exome-wide association studies, identifying novel common and rare genetic determinants. Finally, we performed two-sample Mendelian randomization to assess whether genetically low mtDNA-CN influenced select MT phenotypes. Results: Overall, genetic analyses identified 71 loci for mtDNA-CN, which implicated several genes involved in rare mtDNA depletion disorders, deoxynucleoside triphosphate (dNTP) metabolism, and the MT central dogma. Rare variant analysis identified SAMHD1 mutation carriers as having higher mtDNA-CN (beta = 0.23 SDs; 95% CI, 0.18-0.29; p=2.6 × 10-19), a potential therapeutic target for patients with mtDNA depletion disorders, but at increased risk of breast cancer (OR = 1.91; 95% CI, 1.52-2.40; p=2.7 × 10-8). Finally, Mendelian randomization analyses suggest a causal effect of low mtDNA-CN on dementia risk (OR = 1.94 per 1 SD decrease in mtDNA-CN; 95% CI, 1.55-2.32; p=7.5 × 10-4). Conclusions: Altogether, our genetic findings indicate that mtDNA-CN is a complex biomarker reflecting specific MT processes related to mtDNA regulation, and that these processes are causally related to human diseases. Funding: No funds supported this specific investigation. Awards and positions supporting authors include: Canadian Institutes of Health Research (CIHR) Frederick Banting and Charles Best Canada Graduate Scholarships Doctoral Award (MC, PM); CIHR Post-Doctoral Fellowship Award (RM); Wellcome Trust Grant number: 099313/B/12/A; Crasnow Travel Scholarship; Bongani Mayosi UCT-PHRI Scholarship 2019/2020 (TM); Wellcome Trust Health Research Board Irish Clinical Academic Training (ICAT) Programme Grant Number: 203930/B/16/Z (CJ); European Research Council COSIP Grant Number: 640580 (MO); E.J. Moran Campbell Internal Career Research Award (MP); CISCO Professorship in Integrated Health Systems and Canada Research Chair in Genetic and Molecular Epidemiology (GP).

Our cells are powered by small internal compartments known as mitochondria, which host several copies of their own 'mitochondrial' genome. Defects in these semi-autonomous structures are associated with a range of severe, and sometimes fatal conditions: easily checking the health of mitochondria through cheap, quick and non-invasive methods can therefore help to improve human health. Measuring the concentration of mitochondrial DNA molecules in our blood cells can help to estimate the number of mitochondrial genome copies per cell, which in turn act as a proxy for the health of the compartment. In fact, having lower or higher concentration of mitochondrial DNA molecules is associated with diseases such as cancer, stroke, or cardiac conditions. However, current approaches to assess this biomarker are time and resource-intensive; they also do not work well across people with different ancestries, who have slightly different versions of mitochondrial genomes. In response, Chong et al. developed a new method for estimating mitochondrial DNA concentration in blood samples. Called AutoMitoC, the automated pipeline is fast, easy to use, and can be used across ethnicities. Applying this method to nearly 400,000 individuals highlighted 71 genetic regions for which slight sequence differences were associated with changes in mitochondrial DNA concentration. Further investigation revealed that these regions contained genes that help to build, maintain, and organize mitochondrial DNA. In addition, the analyses yield preliminary evidence showing that lower concentration of mitochondrial DNA may be linked to a higher risk of dementia. Overall, the work by Chong et al. demonstrates that AutoMitoC can be used to investigate how mitochondria are linked to health and disease in populations across the world, potentially paving the way for new therapeutic approaches.

Household-level lifestyle interventions for the prevention of cognitive decline; A Systematic review.

BACKGROUND: Lifestyle interventions targeting households may be an effective means of promoting healthier cognitive function in later life, with extended benefit to other household members. In this systematic review and meta-analysis, we sought to assess the effect of targeting lifestyle behaviours of households on cognitive outcomes METHODS: An electronic search strategy was designed to identify randomised controlled trials (RCTs) where households were randomised to receive a lifestyle intervention for the prevention of cognitive decline, from database inception until April 2020. Our initial search identified no eligible studies, so we revised our search strategy to include trials enroling dyads. We reported the cognitive outcomes, functional outcomes, caregiver outcomes and long-term care (LTC) admissions for eligible studies. FINDINGS: We identified no RCTs which randomised households to receive a lifestyle intervention for preventing cognitive decline. We identified five RCTs (n = 1721, with mean follow-up of 9.6 months) which randomised dyads, which evaluated diet (two trials) and physical activity (three trials). CONCLUSION: Trials evaluating dietary and exercise interventions in dyads were identified. No trial demonstrated a significant association of interventions with change in cognitive testing, functional outcomes or long-term care admissions, although trials were small with short-term follow-up. Future studies should consider targeting lifestyle behaviours of households for prevention of dementia.

Virtual geriatric clinics and the COVID-19 catalyst: a rapid review.

BACKGROUND: During the current COVID-19 health crisis virtual geriatric clinics have become increasingly utilised to complete outpatient consultations, although concerns exist about feasibility of such virtual consultations for older people. The aim of this rapid review is to describe the satisfaction, clinic productivity, clinical benefit, and costs associated with the virtual geriatric clinic model of care. METHODS: A rapid review of PubMed, MEDLINE and CINAHL databases was conducted up to April 2020. Two independent reviewers extracted the information. Four subdomains were focused on: satisfaction with the virtual geriatric clinic, clinic productivity, clinical benefit to patients, costs and any challenges associated with the virtual clinic process. RESULTS: Nine studies with 975 patients met our inclusion criteria. All were observational studies. Seven studies reported patients were satisfied with the virtual geriatric clinic model of care. Productivity outcomes included reports of cost-effectiveness, savings on transport, and improved waiting list metrics. Clinical benefits included successful polypharmacy reviews, and reductions in acute hospitalisation rates. Varying challenges were reported for both clinicians and patients in eight of the nine studies. Hearing impairments and difficulty with technology added to anxieties experienced by patients. Physicians missed the added value of a thorough physical examination and had concerns about confidentiality. CONCLUSION: Virtual geriatric clinics demonstrate evidence of productivity, benefit to patients, cost effectiveness and patient satisfaction with the treatment provided. In the current suboptimal pandemic climate, virtual geriatric clinics may allow Geriatricians to continue to provide an outpatient service, despite the encountered inherent challenges.

Introducing a novel and robust technique for determining lymph node status in colorectal cancer.

OBJECTIVE: This study aims to harness the potential of public gene expression repositories, to develop gene expression profiles that could accurately determine nodal status in colorectal cancer. BACKGROUND: Currently, techniques that determine lymph node positivity (before resection) have poor sensitivity and specificity. The ability to determine lymph node status, based on preoperative biopsies, would greatly assist in planning treatment in colorectal cancer. This is particularly relevant in polyp-detected cancers. METHODS: Public gene expression repositories were screened for experiments comparing metastatic and nonmetastatic colorectal cancer. A customized graphic user interface was developed to extract genes dysregulated across most identified studies (ie, consensus profiles). The utility of consensus profiles was tested by determining whether classifiers could be derived that determined nodal positivity or negativity. Consensus profiles-derived classifiers were tested on separate Affymetrix- and Illumina-based experiments, and collated outputs were compiled in summary receiver operator curve characteristic format, with area under the curve (AUC) reflecting accuracy. The association between classification and oncologic outcome was determined using an additional, independent data set. Final validation was conducted using the Ingenuity network-linkage environment. RESULTS: Four consensus profiles were generated from which classifiers were derived that accurately determined node positive and negative status (pooled AUC were 0.79 ± 0.04 and 0.8 ± 0.03 for nodal positivity and negativity, respectively). Overall AUC ranged from 0.73 to 0.86, demonstrating high accuracy across consensus profile type, classification technique, and array platform used. As consensus profile enabled classification of nodal status, survival outcomes could be compared for those predicted node negative or positive. Patterns of disease-free and overall survival were identical to those observed for standard histopathologic nodal status. Genes contained within consensus profiles were strongly linked to the metastatic process and included (among others) FYN, WNT5A, COL8A1, BMP, and SMAD family members. CONCLUSIONS: Microarray expression data available in public gene expression repositories can be harnessed to generate consensus profiles. The latter are a source of classifiers that have prognostic and predictive properties.