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

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 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, and this GWAS benefits from the larger sample size to provide 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, we recommend repeatedly collecting data of disease-related symptoms.

The Lifelines COVID-19 Cohort: a questionnaire-based study to investigate COVID-19 infection and its health and societal impacts in a Dutch population-based cohort

The COVID-19 pandemic has affected billions of people around the world not only through the infection itself but also through its wider impact on public health and daily life. To assess the effects of the pandemic, a team of researchers across a wide range of disciplines developed and implemented the Lifelines COVID-19 questionnaire, leading to the development of the Lifelines COVID-19 cohort. This cohort is recruited from participants of the Lifelines prospective population cohort and the Lifelines NEXT birth cohort, and participants were asked to fill out detailed questionnaires about their physical and mental health and experiences on a weekly basis starting in late March of 2020 and on a bi-weekly basis staring in June 2020. The Lifelines region covers the three Northern provinces of the Netherlands-- Drenthe, Groningen and Friesland--which together account for [~]10% of the Dutch population. To date, >70,000 people have responded to the questionnaires at least once, and the questionnaire program is still ongoing. Data collected by the questionnaires will be used to address four aspects of the outbreak: (1) how the COVID-19 pandemic developed in the three northern provinces of the Netherlands, (2) which environmental risk factors predict disease susceptibility and severity, (3) which genetic risk factors predict disease susceptibility and severity and (4) what are the psychological and societal impacts of the crisis. Informed consentAll Lifelines and Lifelines NEXT participants have provided informed consent that provide the opportunity for add-on research. Research involving human participantsBoth the Lifelines and the Lifelines NEXT studies were approved by the ethics committee of the University Medical Center Groningen.

Lack of association between genetic variants at ACE2 and TMPRSS2 genes involved in SARS-CoV-2 infection and human quantitative phenotypes

Coronavirus disease 2019 (COVID-19) shows a wide variation in expression and severity of symptoms, from very mild or no symptomes, to flu-like symptoms, and in more severe cases, to pneumonia, acute respiratory distress syndrome and even death. Large differences in outcome have also been observed between males and females. The causes for this variability are likely to be multifactorial, and to include genetics. The SARS-CoV-2 virus responsible for the infection uses the human receptor angiotensin converting enzyme 2 (ACE2) for cell invasion, and the serine protease TMPRSS2 for S protein priming. Genetic variation in these two genes may thus modulate an individuals genetic predisposition to infection and virus clearance. While genetic data on COVID-19 patients is being gathered, we carried out a phenome-wide association scan (PheWAS) to investigate the role of these genes in other human phenotypes in the general population. We examined 178 quantitative phenotypes including cytokines and cardio-metabolic biomarkers, as well as 58 medications in 36,339 volunteers from the Lifelines population biobank, in relation to 1,273 genetic variants located in or near ACE2 and TMPRSS2. While none reached our threshold for significance, we observed a suggestive association of polymorphisms within the ACE2 gene with (1) the use of angiotensin II receptor blockers (ARBs) combination therapies (p=5.7x10-4), an association that is significantly stronger in females (pdiff=0.01), and (2) with the use of non-steroid anti-inflammatory and antirheumatic products (p=5.5x10-4). While these associations need to be confirmed in larger sample sizes, they suggest that these variants play a role in diseases such as hypertension and chronic inflammation that are often observed in the more severe COVID-19 cases. Further investigation of these genetic variants in the context of COVID-19 is thus promising for better understanding of disease variability. Full results are available at https://covid19research.nl.