It is increasingly recognized that SARS-CoV-2 can produce long-term complications after recovery from the acute effects of infection. Here, we report the analysis of 32 self-reported short and long-term symptoms in a general adult population cohort comprised of 233 COVID-19+ cases, 3,652 SARS-CoV-2-negative controls, and 17,474 non-tested individuals. The majority of our COVID-19+ cases are mild, with only 8 of the 233 COVID-19+ cases having been hospitalized. Our results show that 43.4% of COVID-19+ cases have symptoms lasting longer than 30 days, and 24.1% still have at least one symptom after 90 days. These numbers are higher for COVID-19+ cases who were initially more ill, 59.4% at 30 days and 40.6% at 90 days, but even for very mild and initially asymptomatic cases, 14.3% have complications persist for 30 days or longer. In contrast, only 8.6% of participants from the general untested population develop new symptoms lasting longer than 30 days due to any illness during the same study period. The long-term symptoms most enriched in those with COVID-19 are anosmia, ageusia, difficulty concentrating, dyspnea, memory loss, confusion, headache, heart palpitations, chest pain, pain with deep breaths, dizziness, and tachycardia. We additionally observe that individuals who had an initial symptom of dyspnea are significantly more likely to develop long-term symptoms. Importantly, our study finds that the overall level of illness is an important variable to account for when assessing the statistical significance of symptoms that are associated with COVID-19. Our study provides a baseline from which to understand the frequency of COVID-19 long-term symptoms at the population level and demonstrates that, although those most likely to develop long-term COVID-19 complications are those who initially have more severe illness, even those with mild or asymptomatic courses of infection are at increased risk of long-term complications.

The practice of genetic counseling is going to be impacted by the public's expectation that goods, services, information, and experiences happen on demand, wherever and whenever people want them. Building from trends that are currently taking shape, this article looks just over a decade into the future—to 2030—to provide a description of how the field of genetics and genetic counseling will be changed, as well as advice for genetic counselors for how to prepare. We build from the prediction that a large portion of the general public will have access to their digitized whole genome sequence anytime, any place, on any device. We focus on five topics downstream of this prediction: public health, personal autonomy, polygenic scores (PGS), evolving clinical practices, and genetic privacy.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,048 severe disease cases and 571,009 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p=5.41×10-7). These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

No abstract

Lay summaryOur researchers took a look at a sequence of DNA known as the ACE2 gene. This gene is most well known for its role in regulating blood pressure. But in recent times, it’s drawn a lot of attention from the scientific community because it may also serve as a doorway of sorts, enabling viruses like SARS-CoV-2 to infect cells. Our researchers looked at the ACE2 gene in more than 200,000 people, comparing their exact DNA sequences to see where there are differences among people. Variation in the DNA sequence of a gene is common and is sometimes meaningless. But other times, small changes in the DNA sequence can alter the protein that is made from that gene. In this case the ACE2 gene makes the ACE2 protein, which is what the SARS-CoV-2 virus interacts with. We found a lot of variation between individuals and checked to see if that variation coincided with any traits (i.e., people with variant X tend to have high blood pressure more often than people without variant X). All of the traits we looked at were non-COVID-19-related traits, meaning we haven’t asked these people anything about COVID-19 yet (this is because these DNA sequences were collected before the pandemic).We found that there are a number of variations observed among people in a specific part of the ACE2 gene. These variations are expected to alter the shape or functionality of a specific part of the ACE2 protein: The part that interacts with the SARS-CoV-2 virus. We don’t yet know what the real-life significance of this variation is, but it’s possible that these variants decrease the protein’s ability to interact with the SARS-CoV-2 virus, thus decreasing the person’s likelihood of being infected. We can speculate that there will be a spectrum of vulnerability to COVID-19 among people, where some people are more vulnerable than others, and that variants in this part of the ACE2 gene may be one of the reasons. The research we presented here shines a light on this part of the ACE2 gene and may give future researchers a direction to go in as they try to figure out what makes people vulnerable to COVID-19 and similar viruses.

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.