Inspiration

Individuals infected with the SARS-CoV-2 virus respond to the infection with an extreme range of symptoms, spanning a complete lack of the latter to serious disease and death. In addition, the severity of the infection, although predispositions exist, cannot be predicted in a credible manner. As a result, states and health care decision-makers resort in drastic and aggressive measures such as social distancing and lockdowns to avoid the overwhelming of national health systems. Although effective, these measures are devastating for economies and people’s mental health.

The risk and the severity of infection depend on various factors including age, population density, existing co-morbidities, obesity exposure to the virus, and several biomarkers. However, in other cases, there may be no clear reason why a healthy person should develop severe disease and die. In such cases, it is very likely that human genomics plays a significant role. DNA mutations, rare or not, may affect the immune response of otherwise healthy people and impair or overload their antiviral response. This has been observed in H1N1 patients who developed excessive lung inflammation leading to organ impairment and death.

The landscape may be even more complicated: after entering the lung, the virus must also penetrate the lung cells in order to spread. The level of penetrance depends on cell membrane elements called “receptors”, proteins whose functionality may be impaired by DNA mutations. Again, the role of the human genome and its variations may offer the answer to COVID-19 susceptibility and allow policy makers derive more educated and actionable decisions.

It is therefore evident, that genomics will significantly contribute to the COVID-19 pandemic by quickly determining genetic risk factors contributing to SARS-CoV-2 infection and subsequent immune response. The first results are already published! Tens to hundreds of biomedical research cases are under quick review and will soon lead to better insights.

What it does

Geniasis offers all the necessary components to scale and adapt efficiently and rapidly to increased needs, new methods of DNA analysis and new knowledge so that it can very effectively keep its customers up to speed with the most recent validated methods of analysis and interpretation. Geniasis and its associated DNA Mutations Knowledge Base will rapidly transform human genome sequencing data from various sources (whole genomes, whole exomes, gene panels) into reports with actionable DNA mutations in genes related to COVID-19. These reports can be used by clinicians and decision-makers to better understand the risk of individuals and make personalized medicine decisions. The COVID-19 personalized medicine approach will not only offer insights to treatment but will also relieve the burden of health systems by offering additional information on the risk of a patient as well as hospitalization costs and moral outcomes.

How we built it

Geniasis is a product of HybridStat Predictive Analytics. Through this Hackathon we identified its use for DNA analytics for COVID-19 infection susceptibility and immune response effectiveness.

Challenges we ran into

Identifying genes related to COVID-19. However, the first initiatives for the systematic discovery of human mutations related to COVID-19 severity have already been formed and have started producing results – COVID-19 hg initiative Europe is actively participating in the COVID-19 hg initiative.

Accomplishments that we are proud of

Geniasis is already a fully functioning system. We are proud that we identified a novel use for supporting DNA analytics for COVID-19 infection susceptibility and immune response effectiveness.

What we learned

Slight modifications and repurposing of an existing product can provide great impact to the society.

What's next for Geniasis

Update the DNA knowledge base with information related to for COVID-19 infection susceptibility and immune response effectiveness and provide the platform to hospitals and labs performing related tests and DNA data analytics.

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