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Article ; Online: Sex differences in leukocyte profile in ST-elevation myocardial infarction patients.

van Blokland, Irene V / Groot, Hilde E / Hendriks, Tom / Assa, Solmaz / van der Harst, Pim

2020 Volume 10, Issue 1, Page(s) 6851

Abstract: Background: Whether sex differences exist in the inflammatory response after ST-elevation myocardial infarction (STEMI) remains to be elucidated. We studied leukocyte profiles and their prognostic value in men and women presenting with STEMI.: Methods! ...

Abstract	Background: Whether sex differences exist in the inflammatory response after ST-elevation myocardial infarction (STEMI) remains to be elucidated. We studied leukocyte profiles and their prognostic value in men and women presenting with STEMI. Methods: From a total of 552 consecutive STEMI patients, blood samples were collected at hospital admission. Linear regression was used to assess the relationship between leukocyte profiles and enzymatic infarct size. Cox regression was used to assess the association between leukocyte profiles and one-year mortality. Results: Women presented with higher lymphocyte counts (2.3·10 Conclusion: At admission for STEMI, women present with higher lymphocyte count and LMR. Higher LMR is associated with smaller infarct size and decreased one-year mortality risk and could be used as a biomarker to predict outcome.
MeSH term(s)	Aged ; Disease-Free Survival ; Female ; Humans ; Lymphocyte Count ; Lymphocytes ; Male ; Middle Aged ; Monocytes ; Risk Factors ; ST Elevation Myocardial Infarction/blood ; ST Elevation Myocardial Infarction/mortality ; Sex Characteristics ; Survival Rate
Language	English
Publishing date	2020-04-22
Publishing country	England
Document type	Journal Article ; Observational Study
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-020-63185-3
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Translational insights from single-cell technologies across the cardiovascular disease continuum.

van Blokland, Irene V / Groot, Hilde E / Franke, Lude H / van der Wijst, Monique G P / van der Harst, Pim

Trends in cardiovascular medicine

2021 Volume 32, Issue 3, Page(s) 127–135

Abstract: Cardiovascular disease is the leading cause of death worldwide. The societal health burden it represents can be reduced by taking preventive measures and developing more effective therapies. Reaching these goals, however, requires a better understanding ... ...

Abstract	Cardiovascular disease is the leading cause of death worldwide. The societal health burden it represents can be reduced by taking preventive measures and developing more effective therapies. Reaching these goals, however, requires a better understanding of the pathophysiological processes leading to and occurring in the diseased heart. In the last 5 years, several biological advances applying single-cell technologies have enabled researchers to study cardiovascular diseases with unprecedented resolution. This has produced many new insights into how specific cell types change their gene expression level, activation status and potential cellular interactions with the development of cardiovascular disease, but a comprehensive overview of the clinical implications of these findings is lacking. In this review, we summarize and discuss these recent advances and the promise of single-cell technologies from a translational perspective across the cardiovascular disease continuum, covering both animal and human studies, and explore the future directions of the field.
MeSH term(s)	Animals ; Cardiovascular Diseases/diagnosis ; Cardiovascular Diseases/genetics ; Cardiovascular Diseases/therapy ; Heart ; Humans ; Protein Processing, Post-Translational ; Sequence Analysis, RNA ; Single-Cell Analysis
Language	English
Publishing date	2021-03-02
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	1097434-9
ISSN	1873-2615 ; 1050-1738
ISSN (online)	1873-2615
ISSN	1050-1738
DOI	10.1016/j.tcm.2021.02.009
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Article ; Online: Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data.

Li, Shuang / Schmid, Katharina T / de Vries, Dylan H / Korshevniuk, Maryna / Losert, Corinna / Oelen, Roy / van Blokland, Irene V / Groot, Hilde E / Swertz, Morris A / van der Harst, Pim / Westra, Harm-Jan / van der Wijst, Monique G P / Heinig, Matthias / Franke, Lude

Genome biology

2023 Volume 24, Issue 1, Page(s) 80

Abstract: Background: Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co- ...

Abstract	Background: Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals. Results: We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases. Conclusion: Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms.
MeSH term(s)	Humans ; Leukocytes, Mononuclear ; Gene Expression Regulation ; Quantitative Trait Loci ; Ribosomal Proteins/genetics ; Autoimmune Diseases/genetics ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study
Chemical Substances	Ribosomal Proteins
Language	English
Publishing date	2023-04-18
Publishing country	England
Document type	Meta-Analysis ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2040529-7
ISSN	1474-760X ; 1474-760X
ISSN (online)	1474-760X
ISSN	1474-760X
DOI	10.1186/s13059-023-02897-x
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Article: Association of epicardial adipose tissue with different stages of coronary artery disease: A cross-sectional UK Biobank cardiovascular magnetic resonance imaging substudy.

van Meijeren, Anne Ruth / Ties, Daan / de Koning, Marie-Sophie L Y / van Dijk, Randy / van Blokland, Irene V / Lizana Veloz, Pablo / van Woerden, Gijs / Vliegenthart, Rozemarijn / Pundziute, Gabija / Westenbrink, Daan B / van der Harst, Pim

International journal of cardiology. Heart & vasculature

2022 Volume 40, Page(s) 101006

Abstract: Objective: Increased epicardial adipose tissue (EAT) has been identified as a risk factor for the development of coronary artery disease (CAD). However, the exact role of EAT in the development of CAD is unclear. This study aims to compare EAT volumes ... ...

Abstract	Objective: Increased epicardial adipose tissue (EAT) has been identified as a risk factor for the development of coronary artery disease (CAD). However, the exact role of EAT in the development of CAD is unclear. This study aims to compare EAT volumes between healthy controls and individuals with stable CAD and a history of myocardial infarction (MI). Furthermore, associations between clinical and biochemical parameters with EAT volumes are examined. Methods: This retrospective cross-sectional study included 171 participants from the United Kingdom Biobank (56 healthy controls; 60 stable CAD; 55 post MI), whom were balanced for age, sex and body mass index (BMI). EAT volumes were quantified on end-diastolic cardiac magnetic resonance (CMR) imaging short-axis slices along the left and right ventricle and indexed for body surface area (iEAT) and iEAT volumes were compared between groups. Results: iEAT volumes were comparable between control, CAD and MI cases (median [IQR]: 66.1[54.4-77.0] vs. 70.9[55.8-85.5] vs. 67.6[58.6-82.3] mL/m Conclusions: No significant differences in iEAT volumes were observed between patients with CAD, MI and healthy controls. Our results indicate the importance of correcting for confounding by CVD risk factors, including circulating lipid levels, when studying the relationship between EAT volume and CAD. Further mechanistic studies on causal pathways and the role of EAT composition are warranted.
Language	English
Publishing date	2022-03-29
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	2818464-6
ISSN	2352-9067
ISSN	2352-9067
DOI	10.1016/j.ijcha.2022.101006
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Article ; Online: Leukocyte profiles across the cardiovascular disease continuum: A population-based cohort study.

Groot, Hilde E / van Blokland, Irene V / Lipsic, Erik / Karper, Jacco C / van der Harst, Pim

Journal of molecular and cellular cardiology

2019 Volume 138, Page(s) 158–164

Abstract: Introduction: Inflammation plays a pivotal role across all stadia of the cardiovascular disease (CVD) continuum, i.e. non-obstructive coronary artery disease (CAD), myocardial infarction (MI), and ischemic heart failure (iHF). However, inflammation ... ...

Abstract	Introduction: Inflammation plays a pivotal role across all stadia of the cardiovascular disease (CVD) continuum, i.e. non-obstructive coronary artery disease (CAD), myocardial infarction (MI), and ischemic heart failure (iHF). However, inflammation across CVD continuum has not been studied yet within one population. Therefore, we mapped leukocyte profiles across the continuum within the UK Biobank. Methods: The UK Biobank cohort study includes >500,000 participants aged 40 to 70 years who were recruited from 22 assessment centers across the United Kingdom from 2006 to 2010. A total of 333,218 individuals with available laboratory measurements at baseline were included in this study. These consisted of controls and individuals who had progression of CVD during follow-up (i.e. who developed CAD, MI, or iHF during follow-up). We investigated whether leukocytes and subtypes of leukocytes at baseline differed among the CVD continuum. Furthermore, we studied the possible interactions between sex and CVD on leukocytes. Results: Of 333,218 individuals, 325,054 (97.5%) individuals were categorized as controls, and 8164 (2.5%) individuals had progression of CVD during follow-up. Of those 8164 individuals, 4552 (1.4%) developed CAD during follow-up, 2839 (0.9%) MI, and 773 (0.2%) in iHF. Compared to controls, mean leukocyte levels at baseline increased across the CVD continuum from 6.8·10 Conclusion: Overall leukocyte count increased across the CVD continuum, which mainly depended on the increase in neutrophil count. High leukocytes in individuals not having CAD at baseline were predictive for the development of CAD during follow-up. Women had a greater increase of lymphocytes across the CVD continuum compared to men. Understanding which cells are key players in which stadium, could serve as a starting point for the identification of new potential therapeutic targets in CVD.
MeSH term(s)	Adult ; Aged ; Cardiovascular Diseases/immunology ; Cardiovascular Diseases/pathology ; Cohort Studies ; Disease Progression ; Female ; Follow-Up Studies ; Humans ; Incidence ; Leukocytes/metabolism ; Male ; Middle Aged ; Pneumonia/epidemiology ; Prognosis ; Sex Characteristics
Language	English
Publishing date	2019-12-06
Publishing country	England
Document type	Journal Article
ZDB-ID	80157-4
ISSN	1095-8584 ; 0022-2828
ISSN (online)	1095-8584
ISSN	0022-2828
DOI	10.1016/j.yjmcc.2019.11.156
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Zs.A 426: Show issues

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Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

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Article ; Online: Sex differences in leukocyte profile in ST-elevation myocardial infarction patients

Irene V. van Blokland / Hilde E. Groot / Tom Hendriks / Solmaz Assa / Pim van der Harst

Scientific Reports, Vol 10, Iss 1, Pp 1-

2020 Volume 8

Abstract: Abstract Background: Whether sex differences exist in the inflammatory response after ST-elevation myocardial infarction (STEMI) remains to be elucidated. We studied leukocyte profiles and their prognostic value in men and women presenting with STEMI. ... ...

Abstract	Abstract Background: Whether sex differences exist in the inflammatory response after ST-elevation myocardial infarction (STEMI) remains to be elucidated. We studied leukocyte profiles and their prognostic value in men and women presenting with STEMI. Methods: From a total of 552 consecutive STEMI patients, blood samples were collected at hospital admission. Linear regression was used to assess the relationship between leukocyte profiles and enzymatic infarct size. Cox regression was used to assess the association between leukocyte profiles and one-year mortality. Results: Women presented with higher lymphocyte counts (2.3·109 cells/L (IQR 1.6–3.1) vs. 1.8·109 cells/L (IQR 1.4–2.5), p = 3.00 ∙ 10−4) and percentages (21.1% (IQR 14.4–28.1) vs. 17.1% (IQR 12.3–24.3), p = 0.004). Lymphocyte to monocyte ratio (LMR) was also higher in women (3.25 (IQR 2.56–4.5) vs. 2.68 (IQR 2.08–3.59), p = 7.28 ∙ 10−7). Higher LMR was associated with lower peak CK-MB (β = −0.27 (95% CI: −0.50, −0.03), p = 0.026), lower peak troponin T (β = −0.45 (95% CI: −0.77, −0.13), p = 0.006) and lower one-year mortality risk (HR 0.35 (95% CI: 0.13, 0.96), p = 0.042). Conclusion: At admission for STEMI, women present with higher lymphocyte count and LMR. Higher LMR is associated with smaller infarct size and decreased one-year mortality risk and could be used as a biomarker to predict outcome.
Keywords	Medicine ; R ; Science ; Q
Subject code	610
Language	English
Publishing date	2020-04-01T00:00:00Z
Publisher	Nature Publishing Group
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility.

van Blokland, Irene V / Lanting, Pauline / Ori, Anil P S / Vonk, Judith M / Warmerdam, Robert C A / Herkert, Johanna C / Boulogne, Floranne / Claringbould, Annique / Lopera-Maya, Esteban A / Bartels, Meike / Hottenga, Jouke-Jan / Ganna, Andrea / Karjalainen, Juha / Hayward, Caroline / Fawns-Ritchie, Chloe / Campbell, Archie / Porteous, David / Cirulli, Elizabeth T / Schiabor Barrett, Kelly M /

Riffle, Stephen / Bolze, Alexandre / White, Simon / Tanudjaja, Francisco / Wang, Xueqing / Ramirez, Jimmy M / Lim, Yan Wei / Lu, James T / Washington, Nicole L / de Geus, Eco J C / Deelen, Patrick / Boezen, H Marike / Franke, Lude H

PloS one

2021 Volume 16, Issue 8, Page(s) e0255402

Abstract: Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported ... ...

Abstract	Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
MeSH term(s)	Area Under Curve ; COVID-19/genetics ; COVID-19/pathology ; COVID-19/virology ; Cross-Sectional Studies ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Phenotype ; Polymorphism, Single Nucleotide ; ROC Curve ; SARS-CoV-2/isolation & purification
Language	English
Publishing date	2021-08-11
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2267670-3
ISSN	1932-6203 ; 1932-6203
ISSN (online)	1932-6203
ISSN	1932-6203
DOI	10.1371/journal.pone.0255402
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article ; Online: Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility

Irene V. van Blokland / Pauline Lanting / Anil P. S. Ori / Judith M. Vonk / Robert C. A. Warmerdam / Johanna C. Herkert / Floranne Boulogne / Annique Claringbould / Esteban A. Lopera-Maya / Meike Bartels / Jouke-Jan Hottenga / Andrea Ganna / Juha Karjalainen / Lifelines COVID-19 cohort study / The COVID-19 Host Genetics Initiative / Caroline Hayward / Chloe Fawns-Ritchie / Archie Campbell / David Porteous /

Elizabeth T. Cirulli / Kelly M. Schiabor Barrett / Stephen Riffle / Alexandre Bolze / Simon White / Francisco Tanudjaja / Xueqing Wang / Jimmy M. Ramirez / Yan Wei Lim / James T. Lu / Nicole L. Washington / Eco J. C. de Geus / Patrick Deelen / H. Marike Boezen / Lude H. Franke

PLoS ONE, Vol 16, Iss

2021 Volume 8

Abstract	Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility.

Irene V van Blokland / Pauline Lanting / Anil P S Ori / Judith M Vonk / Robert C A Warmerdam / Johanna C Herkert / Floranne Boulogne / Annique Claringbould / Esteban A Lopera-Maya / Meike Bartels / Jouke-Jan Hottenga / Andrea Ganna / Juha Karjalainen / Lifelines COVID-19 cohort study / COVID-19 Host Genetics Initiative / Caroline Hayward / Chloe Fawns-Ritchie / Archie Campbell / David Porteous /

Elizabeth T Cirulli / Kelly M Schiabor Barrett / Stephen Riffle / Alexandre Bolze / Simon White / Francisco Tanudjaja / Xueqing Wang / Jimmy M Ramirez / Yan Wei Lim / James T Lu / Nicole L Washington / Eco J C de Geus / Patrick Deelen / H Marike Boezen / Lude H Franke

PLoS ONE, Vol 16, Iss 8, p e

2021 Volume 0255402

Abstract	Epidemiological and genetic studies on COVID-19 are currently hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict COVID-19 cases using cross-sectional self-reported disease-related symptoms. Here, we demonstrate that this COVID-19 prediction model has reasonable and consistent performance across multiple independent cohorts and that our attempt to improve upon this model did not result in improved predictions. Using the existing COVID-19 prediction model, we then conducted a GWAS on the predicted phenotype using a total of 1,865 predicted cases and 29,174 controls. While we did not find any common, large-effect variants that reached genome-wide significance, we do observe suggestive genetic associations at two SNPs (rs11844522, p = 1.9x10-7; rs5798227, p = 2.2x10-7). Explorative analyses furthermore suggest that genetic variants associated with other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. This study represents a first effort that uses a symptom-based predicted phenotype as a proxy for COVID-19 in our pursuit of understanding the genetic susceptibility of the disease. We conclude that the inclusion of symptom-based predicted cases could be a useful strategy in a scenario of limited testing, either during the current COVID-19 pandemic or any future viral outbreak.
Keywords	Medicine ; R ; Science ; Q
Subject code	006
Language	English
Publishing date	2021-01-01T00:00:00Z
Publisher	Public Library of Science (PLoS)
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Using symptom-based case predictions to identify host genetic factors that contribute to COVID-19 susceptibility

van Blokland, Irene V / Lanting, Pauline / Ori, Anil PS / Vonk, Judith M / Warmerdam, Robert CA / Herkert, Johanna C / Boulogne, Floranne / Claringbould, Annique / Lopera-Maya, Esteban A / Bartels, Meike / Hottenga, Jouke-Jan / Ganna, Andrea / Karjalainen, Juha / Lifelines COVID-19 cohort study / The COVID-19 Host Genetics Initiative / Hayward, Caroline / Fawns-Ritchie, Chloe / Campbell, Archie / Porteous, David /

Cirulli, Elizabeth T / Schiabor Barrett, Kelly M / Riffle, Stephen / Bolze, Alexandre / White, Simon / Tanudjaja, Francisco / Wang, Xueqing / Ramirez, Jimmy M / Lim, Yan Wei / Lu, James T / Washington, Nicole L / de Geus, Eco JC / Deelen, Patrick / Boezen, H Marike / Franke, Lude H

medRxiv

Abstract: Epidemiological and genetic studies on COVID-19 are hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict potential COVID-19 cases using cross-sectional self-reported ... ...

Abstract	Epidemiological and genetic studies on COVID-19 are hindered by inconsistent and limited testing policies to confirm SARS-CoV-2 infection. Recently, it was shown that it is possible to predict potential COVID-19 cases using cross-sectional self-reported disease-related symptoms. Using a previously reported COVID-19 prediction model, we show that it is possible to conduct a GWAS on predicted COVID-19 which benefits from a larger sample size in order to gain new insights into the genetic susceptibility of the disease. Furthermore, we find suggestive evidence that genetic variants for other viral infectious diseases do not overlap with COVID-19 susceptibility and that severity of COVID-19 may have a different genetic architecture compared to COVID-19 susceptibility. Our findings demonstrate the added value of using self-reported symptom assessments to quickly monitor novel endemic viral outbreaks in a scenario of limited testing. Should there be another outbreak of a novel infectious disease, then we recommend repeatedly collecting data of disease-related symptoms.
Keywords	covid19
Language	English
Publishing date	2020-08-24
Publisher	Cold Spring Harbor Laboratory Press
Document type	Article ; Online
DOI	10.1101/2020.08.21.20177246
Database	COVID19

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