7 research outputs found

    Genotyping, sequencing and analysis of 140,000 adults from Mexico City

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    The Mexico City Prospective Study is a prospective cohort of more than 150,000 adults recruited two decades ago from the urban districts of Coyoacán and Iztapalapa in Mexico City1. Here we generated genotype and exome-sequencing data for all individuals and whole-genome sequencing data for 9,950 selected individuals. We describe high levels of relatedness and substantial heterogeneity in ancestry composition across individuals. Most sequenced individuals had admixed Indigenous American, European and African ancestry, with extensive admixture from Indigenous populations in central, southern and southeastern Mexico. Indigenous Mexican segments of the genome had lower levels of coding variation but an excess of homozygous loss-of-function variants compared with segments of African and European origin. We estimated ancestry-specific allele frequencies at 142 million genomic variants, with an effective sample size of 91,856 for Indigenous Mexican ancestry at exome variants, all available through a public browser. Using whole-genome sequencing, we developed an imputation reference panel that outperforms existing panels at common variants in individuals with high proportions of central, southern and southeastern Indigenous Mexican ancestry. Our work illustrates the value of genetic studies in diverse populations and provides foundational imputation and allele frequency resources for future genetic studies in Mexico and in the United States, where the Hispanic/Latino population is predominantly of Mexican descent

    A Cloud-Based Infrastructure for Cancer Genomics

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    The advent of new genomic approaches, particularly next generation sequencing (NGS) has resulted in explosive growth of biological data. As the size of biological data keeps growing at exponential rates, new methods for data management and data processing are becoming essential in bioinformatics and computational biology. Indeed, data analysis has now become the central challenge in genomics. NGS has provided rich tools for defining genomic alterations that cause cancer. The processing time and computing requirements have now become a serious bottleneck to the characterization and analysis of these genomic alterations. Moreover, as the adoption of NGS continues to increase, the computing power required often exceeds what any single institution can provide, leading to major restraints in the type and number of analyses that can be performed. Cloud computing represents a potential solution to this problem. On a cloud platform, computing resources can be available on-demand, thus allowing users to implement scalable and highly parallel methods. However, few centralized frameworks exist to allow the average researcher the ability to apply bioinformatics workflows using cloud resources. Moreover, bioinformatics approaches are associated with multiple processing challenges, such as the variability in the methods or data used and the reproducibility requirements of the research analysis. Here, we present CloudConductor, a software system that is specifically designed to harness the power of cloud computing to perform complex analysis pipelines on large biological datasets. CloudConductor was designed with five central features in mind: scalability, modularity, parallelism, reproducibility and platform agnosticism. We demonstrate the processing power afforded by CloudConductor on a real-world genomics problem. Using CloudConductor, we processed and analyzed 101 whole genome tumor-normal paired samples from Burkitt lymphoma subtypes to identify novel genomic alterations. We identified a total of 72 driver genes associated with the disease. Somatic events were identified in both coding and non-coding regions of nearly all driver genes, notably in genes IGLL5, BACH2, SIN3A, and DNMT1. We have developed the analysis framework by implementing a graphical user interface, a back-end database system, a data loader and a workflow management system.In this thesis, we develop the concepts and describe an implementation of automated cloud-based infrastructure to analyze genomics data, creating a fast and efficient analysis resource for genomics researchers.</p

    Analysis of rare genetic variation underlying cardiometabolic diseases and traits among 200,000 individuals in the UK Biobank

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    Cardiometabolic diseases are the leading cause of death worldwide. Despite a known genetic component, our understanding of these diseases remains incomplete. Here, we analyzed the contribution of rare variants to 57 diseases and 26 cardiometabolic traits, using data from 200,337 UK Biobank participants with whole-exome sequencing. We identified 57 gene-based associations, with broad replication of novel signals in Geisinger MyCode. There was a striking risk associated with mutations in known Mendelian disease genes, including MYBPC3, LDLR, GCK, PKD1 and TTN. Many genes showed independent convergence of rare and common variant evidence, including an association between GIGYF1 and type 2 diabetes. We identified several large effect associations for height and 18 unique genes associated with blood lipid or glucose levels. Finally, we found that between 1.0% and 2.4% of participants carried rare potentially pathogenic variants for cardiometabolic disorders. These findings may facilitate studies aimed at therapeutics and screening of these common disorders

    Safety and Outcome of Revascularization Treatment in Patients With Acute Ischemic Stroke and COVID-19: The Global COVID-19 Stroke Registry

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    BACKGROUND AND OBJECTIVES: COVID-19 related inflammation, endothelial dysfunction and coagulopathy may increase the bleeding risk and lower efficacy of revascularization treatments in patients with acute ischemic stroke. We aimed to evaluate the safety and outcomes of revascularization treatments in patients with acute ischemic stroke and COVID-19. METHODS: Retrospective multicenter cohort study of consecutive patients with acute ischemic stroke receiving intravenous thrombolysis (IVT) and/or endovascular treatment (EVT) between March 2020 and June 2021, tested for SARS-CoV-2 infection. With a doubly-robust model combining propensity score weighting and multivariate regression, we studied the association of COVID-19 with intracranial bleeding complications and clinical outcomes. Subgroup analyses were performed according to treatment groups (IVT-only and EVT). RESULTS: Of a total of 15128 included patients from 105 centers, 853 (5.6%) were diagnosed with COVID-19. 5848 (38.7%) patients received IVT-only, and 9280 (61.3%) EVT (with or without IVT). Patients with COVID-19 had a higher rate of symptomatic intracerebral hemorrhage (SICH) (adjusted odds ratio [OR] 1.53; 95% CI 1.16-2.01), symptomatic subarachnoid hemorrhage (SSAH) (OR 1.80; 95% CI 1.20-2.69), SICH and/or SSAH combined (OR 1.56; 95% CI 1.23-1.99), 24-hour (OR 2.47; 95% CI 1.58-3.86) and 3-month mortality (OR 1.88; 95% CI 1.52-2.33).COVID-19 patients also had an unfavorable shift in the distribution of the modified Rankin score at 3 months (OR 1.42; 95% CI 1.26-1.60). DISCUSSION: Patients with acute ischemic stroke and COVID-19 showed higher rates of intracranial bleeding complications and worse clinical outcomes after revascularization treatments than contemporaneous non-COVID-19 treated patients. Current available data does not allow direct conclusions to be drawn on the effectiveness of revascularization treatments in COVID-19 patients, or to establish different treatment recommendations in this subgroup of patients with ischemic stroke. Our findings can be taken into consideration for treatment decisions, patient monitoring and establishing prognosis

    Safety and Outcome of Revascularization Treatment in Patients With Acute Ischemic Stroke and COVID-19: The Global COVID-19 Stroke Registry.

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    BACKGROUND AND OBJECTIVES COVID-19 related inflammation, endothelial dysfunction and coagulopathy may increase the bleeding risk and lower efficacy of revascularization treatments in patients with acute ischemic stroke. We aimed to evaluate the safety and outcomes of revascularization treatments in patients with acute ischemic stroke and COVID-19. METHODS Retrospective multicenter cohort study of consecutive patients with acute ischemic stroke receiving intravenous thrombolysis (IVT) and/or endovascular treatment (EVT) between March 2020 and June 2021, tested for SARS-CoV-2 infection. With a doubly-robust model combining propensity score weighting and multivariate regression, we studied the association of COVID-19 with intracranial bleeding complications and clinical outcomes. Subgroup analyses were performed according to treatment groups (IVT-only and EVT). RESULTS Of a total of 15128 included patients from 105 centers, 853 (5.6%) were diagnosed with COVID-19. 5848 (38.7%) patients received IVT-only, and 9280 (61.3%) EVT (with or without IVT). Patients with COVID-19 had a higher rate of symptomatic intracerebral hemorrhage (SICH) (adjusted odds ratio [OR] 1.53; 95% CI 1.16-2.01), symptomatic subarachnoid hemorrhage (SSAH) (OR 1.80; 95% CI 1.20-2.69), SICH and/or SSAH combined (OR 1.56; 95% CI 1.23-1.99), 24-hour (OR 2.47; 95% CI 1.58-3.86) and 3-month mortality (OR 1.88; 95% CI 1.52-2.33).COVID-19 patients also had an unfavorable shift in the distribution of the modified Rankin score at 3 months (OR 1.42; 95% CI 1.26-1.60). DISCUSSION Patients with acute ischemic stroke and COVID-19 showed higher rates of intracranial bleeding complications and worse clinical outcomes after revascularization treatments than contemporaneous non-COVID-19 treated patients. Current available data does not allow direct conclusions to be drawn on the effectiveness of revascularization treatments in COVID-19 patients, or to establish different treatment recommendations in this subgroup of patients with ischemic stroke. Our findings can be taken into consideration for treatment decisions, patient monitoring and establishing prognosis
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