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

AbstractCoronavirus 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 individual’s 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=5.7×10−4), 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=5.5×10−4). 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.