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genome wide association

Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used.

Impact of body composition on COVID-19 susceptibility and severity: A two-sample multivariable Mendelian randomization study

genome wide association

We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls).

Evaluation of glycemic traits in susceptibility to COVID-19 risk: a Mendelian randomization study

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Genetics Initiative sentence examples within Host Genetics Initiative

Host Genetics Initiative

Effect estimates of those IVs on COVID-19 severity were gathered from the GWAS meta-analysis by the COVID-19 Host Genetics Initiative (4,336 cases & 623,902 controls).

Shared genetic etiology between idiopathic pulmonary fibrosis and COVID-19 severity

Host Genetics Initiative

Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used.

Impact of body composition on COVID-19 susceptibility and severity: A two-sample multivariable Mendelian randomization study

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Nervosa Genetics Initiative

Examples of this include the Anorexia Nervosa Genetics Initiative, the Australian Sample of Depression, and the Genetic Links to Anxiety and Depression (GLAD) study [4–6].

The Validity of Brief Phenotyping in Population Biobanks for Psychiatric Genome-Wide Association Studies on the Biobank Scale

Nervosa Genetics Initiative

Goal We and collaborators from the Genetic Consortium for Anorexia Nervosa/Wellcome Trust Case Control Consortium-3 (GCAN/WTCCC3), the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED), are currently investigating molecular biology and physiology in AN patients, subjects in remission and healthy control women in the goal to identify and characterize biomarkers of diagnosis and prognosis of AN to propose precision medicine and adapted treatments.

Exome & precision medicine in eating disorders

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10.1159/000516884

aDepartment of Pediatrics, Division of Neurology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA; bEpilepsy Neurogenetics Initiative, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA; cDepartment of Neurology, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; dDepartment of Neuroscience, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; eDepartment of Physiology and Neurobiology, University of Connecticut, Storrs, CT, USA Received: April 6, 2021 Accepted: April 8, 2021 Published online: June 17, 2021.

Towards Targeted Therapy for Neurodevelopmental Disorders Symposium

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10.1371/journal.pgen.1009214

1 Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America, 2 The Epilepsy NeuroGenetics Initiative (ENGIN), Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America, 3 Department of Biomedical and Health Informatics (DBHi), Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America, 4 Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, 5 Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America.

The dose makes the poison—Novel insights into Dravet syndrome and SCN1A regulation through nonproductive splicing

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Genetics Initiative - aDepartment of Pediatrics, Division of Neurology, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA; bEpilepsy Neurogenetics Initiative, The Children’s Hospital of Philadelphia, Philadelphia, PA, USA; cDepartment of Neurology, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; dDepartment of Neuroscience, The University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; eDepartment of Physiology and Neurobiology, University of Connecticut, Storrs, CT, USA Received: April 6, 2021 Accepted: April 8, 2021 Published online: June 17, 2021. [1] 1 Division of Neurology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America, 2 The Epilepsy NeuroGenetics Initiative (ENGIN), Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America, 3 Department of Biomedical and Health Informatics (DBHi), Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, United States of America, 4 Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America, 5 Department of Neuroscience, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America. [2]

genome wide association

Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used. [1] We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). [2] We further incorporated 1401 genotyped and 948 sequenced ancestry-matched population controls, and tested genome-wide association on 1072 severe cases versus 3875 mild or population controls, followed by trans-ethnic meta-analysis with summary statistics of 3199 hospitalized cases and 897,488 population controls from the COVID-19 Host Genetics Initiative. [3] Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. [4] We performed an in-depth genetic analysis of chromosome 21 exploiting the genome-wide association study data, including 6,406 individuals hospitalized for COVID-19 and 902,088 controls with European genetic ancestry from the COVID-19 Host Genetics Initiative. [5] Here, we integrate a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n = 18,502). [6] Genetic variants associated with critical illness (n=48) or hospitalization (n=39) due to COVID-19 from COVID-19 Host Genetics Initiative genome-wide association studies. [7] We used Bayesian colocalization (COLOC) and summary-based Mendelian randomization to combine gene expression quantitative trait loci (eQTLs) from the Lung eQTL ( n  = 1,038) and eQTLGen ( n  = 31,784) studies with published COVID-19 genome-wide association study (GWAS) data from the COVID-19 Host Genetics Initiative. [8] We applied single nucleotide polymorphisms (SNPs) that were associated with plasma vitamin C, in a recent genome-wide association study (GWAS) as genetic instruments to the GWAS of severe COVID-19, COVID-19 hospitalisation and any infection in the COVID-19 host genetics initiative and the GWAS of pneumonia in the UK Biobank, to assess whether people with genetically predicted higher levels of plasma vitamin C had lower risk of severe COVID-19 and pneumonia. [9] Here, we performed an in-depth genetic analysis of chromosome 21 exploiting the genome-wide association study data including 6,406 individuals hospitalized for COVID-19 and 902,088 controls with European genetic ancestry from the COVID-19 Host Genetics Initiative. [10]

Host Genetics Initiative

Effect estimates of those IVs on COVID-19 severity were gathered from the GWAS meta-analysis by the COVID-19 Host Genetics Initiative (4,336 cases & 623,902 controls). [1] Summary statistics of genome-wide association studies (GWASs) for these body composition measures were drawn from the GIANT consortium and UK Biobank, while for susceptibility and severity due to COVID-19 disease data from the COVID-19 Host Genetics Initiative was used. [2] 1,644,784 controls) obtained from the COVID-19 Host Genetics Initiative (HGI). [3] The latest GWAS summary statistics from the COVID-19 Host Genetics Initiative was used, which comprised comparisons of general population controls with critically ill, hospitalized and any infected cases. [4] We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). [5] The aim of COVID-19 Host Genetics Initiative (HGI) research collaboration is to identify human genetic variation that influences responses to SARS-CoV-2 infection and its subsequent disease, COVID-19. [6] Setting: Summary data from genome-wide analyses in the population-based UK Biobank and SUNLIGHT Consortium, applied to meta-analyzed results of genome-wide analyses in the COVID-19 Host Genetics Initiative. [7] The GWAS statistics of COVID-19 is from COVID-19 Host Genetics Initiative. [8] GWASs of COVID-19 outcomes (susceptibility, hospitalization and very severe disease) were obtained from the COVID-19 Host Genetics Initiative. [9] Setting Summary data from genome-wide analyses in the population-based UK Biobank and SUNLIGHT Consortium, applied to meta-analysed results of genome-wide analyses in the COVID-19 Host Genetics Initiative. [10] None of the five variants showed effects on a similarly-defined phenotype in a lookup in the COVID-19 Host Genetics Initiative. [11] First, we applied cross-methylome omnibus (CMO) test and leveraged data from the COVID-19 Host Genetics Initiative (HGI) comparing 9,986 hospitalized COVID-19 patients and 1,877,672 population controls. [12] Funding: Funded by private donors for the Host Genetics Research Project, the Intesa San Paolo for 2020 charity fund, and the Host Genetics Initiative. [13] In view of the genetic association of the TGF‐β1 activator THBS3 with severe COVID‐19 identified by the COVID‐19 Host Genetics Initiative, this study suggests TGF‐β1 may play a key role in COVID‐19. [14] Using inverse-variance weighted Mendelian Randomization (MR), we investigated the impact of NAFLD on human disease-related phenotypes in the UK Biobank and FinnGen cohorts as well as in the COVID-19 host genetics initiative. [15] We further incorporated 1401 genotyped and 948 sequenced ancestry-matched population controls, and tested genome-wide association on 1072 severe cases versus 3875 mild or population controls, followed by trans-ethnic meta-analysis with summary statistics of 3199 hospitalized cases and 897,488 population controls from the COVID-19 Host Genetics Initiative. [16] Using protein quantitative trait loci (pQTL) data from the SCALLOP consortium, involving meta-analysis of up to 26,494 individuals, and COVID-19 genome-wide association data from the Host Genetics Initiative, we performed MR for 157 COVID-19 severity protein biomarkers. [17] The latest summary data of COVID-19 that shared on Jan 18, 2021 by the COVID-19 Host Genetics Initiative was used. [18] After accounting for multiple testing, we did not identify any clear associations with rare variants either exome-wide or when specifically focusing on (i) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19; (ii) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative; or (iii) 32 additional genes of immunologic relevance and/or therapeutic potential. [19] Using summary statistics from the Host Genetics Initiative and the Million Veteran Program, we studied 7,554 patients hospitalized with COVID-19 and >1 million controls. [20] We performed an in-depth genetic analysis of chromosome 21 exploiting the genome-wide association study data, including 6,406 individuals hospitalized for COVID-19 and 902,088 controls with European genetic ancestry from the COVID-19 Host Genetics Initiative. [21] Here, we integrate a genome-wide association study of COVID-19 hospitalization (7,885 cases and 961,804 controls from COVID-19 Host Genetics Initiative) with mRNA expression, splicing, and protein levels (n = 18,502). [22] In addition, based on COVID-19 severity GWAS data from the COVID-19 Host Genetics Initiative round 5, we observed that VWF is the only coagulation factor that exhibited genetic causal associations with the incidence of COVID-19 severity (PIVW= 0. [23] Here, we applied colocalization to compare summary statistics for 16 GWASs from the COVID-19 Host Genetics Initiative to investigate similarities and differences in their genetic signals. [24] The effect of each SNP on the outcome of COVID-19 severity risk was obtained from the GWAS summary data of 1,059,456 participants of European ancestry gathered from the COVID-19 Host Genetics Initiative. [25] GWASs of COVID-19 susceptibility, hospitalization, and severe disease from the COVID-19 Host Genetics Initiative were used as outcome GWASs. [26] Genetic variants associated with critical illness (n=48) or hospitalization (n=39) due to COVID-19 from COVID-19 Host Genetics Initiative genome-wide association studies. [27] We used Bayesian colocalization (COLOC) and summary-based Mendelian randomization to combine gene expression quantitative trait loci (eQTLs) from the Lung eQTL ( n  = 1,038) and eQTLGen ( n  = 31,784) studies with published COVID-19 genome-wide association study (GWAS) data from the COVID-19 Host Genetics Initiative. [28] Objectives: To assess whether rs35705950-T confers differential risk for clinical outcomes associated with COVID-19 infection among participants in the Million Veteran Program (MVP) and COVID-19 Host Genetics Initiative (HGI). [29] We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. [30] We applied single nucleotide polymorphisms (SNPs) that were associated with plasma vitamin C, in a recent genome-wide association study (GWAS) as genetic instruments to the GWAS of severe COVID-19, COVID-19 hospitalisation and any infection in the COVID-19 host genetics initiative and the GWAS of pneumonia in the UK Biobank, to assess whether people with genetically predicted higher levels of plasma vitamin C had lower risk of severe COVID-19 and pneumonia. [31] We employed the latest GWAS summary statistics from the COVID-19 Host Genetics Initiative. [32] We extracted data on the lead single nucleotide polymorphism in chromosome-3 (rs35081325;wild-type: A;risk variant: T) identified in the COVID-19 Host Genetics Initiative's analysis A2 (COVID-19 with severe respiratory failure). [33] 2021; The Severe COVID-19 GWAS Group 2020), and rs11385942 variant from this region also shows the lowest heterogenous P value in a worldwide cohort of 49 studies from 19 countries (The COVID-19 Host Genetics Initiative and Ganna 2021). [34] We then performed two sample MR using publically available summary data for the association of the genetic instrument with serum vitamin D in the UK Biobank and with COVID-19 outcomes, including infection, severe respiratory infection, and hospitalization, in the COVID-19 Host Genetics Initiative. [35] Here, we performed an in-depth genetic analysis of chromosome 21 exploiting the genome-wide association study data including 6,406 individuals hospitalized for COVID-19 and 902,088 controls with European genetic ancestry from the COVID-19 Host Genetics Initiative. [36] Methods: Summary statistics of COVID-19 susceptibility and severity was retrieved from the COVID-19 Host Genetics Initiative and used as outcomes in this study. [37]

Nervosa Genetics Initiative

Examples of this include the Anorexia Nervosa Genetics Initiative, the Australian Sample of Depression, and the Genetic Links to Anxiety and Depression (GLAD) study [4–6]. [1] Goal We and collaborators from the Genetic Consortium for Anorexia Nervosa/Wellcome Trust Case Control Consortium-3 (GCAN/WTCCC3), the Anorexia Nervosa Genetics Initiative (ANGI) and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED), are currently investigating molecular biology and physiology in AN patients, subjects in remission and healthy control women in the goal to identify and characterize biomarkers of diagnosis and prognosis of AN to propose precision medicine and adapted treatments. [2] Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. [3] Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. [4]