We built a way to create anonymous, auditable, incentivised, repeat consent genomic queries. Were they a success?

GenomesDAO
4 min readSep 18, 2023

When individuals participate in genomic research, they typically provide initial informed consent. This consent outlines the scope of the research, how their data will be used, and any potential risks or benefits. What is often lacking is the ability to go back and ask more questions of the subject and the data. In our beta test, we wanted to prove that this is doable in an anonymous manner. We have done this.

Our alpha test was 3 fold

  • Can we get the full stack working?
  • What rate will people respond at?
  • What can we find out genomically?

Genomic data is valuable for a wide range of research purposes, and researchers often use existing data for new studies. This raises ethical questions about whether individuals should be asked for their consent again when their data is used in ways not originally anticipated.

In some cases, there may be situations where re-consent is deemed necessary or ethically appropriate. For example:

  • Change in Research Scope: If the research project significantly changes its scope or goals, re-consent may be required to ensure that participants are aware of and agree to the new uses of their data.
  • Sensitive Information: If new research reveals sensitive information about participants (e.g., predisposition to a severe medical condition), re-consent may be needed to provide participants with updated information and choices.

Our beta queries were based on the ‘COVID-19 Host Genetics Initiative’. This initiative brings together the human genetics community to generate, share, and analyse data to learn the genetic determinants of COVID-19 susceptibility, severity, and outcomes. The kind of results we generated are important and useful for many reasons:

  • Genetic Variants & Disease Association: Genetic variants can have significant clinical implications. Depending on the nature of the variant, its location, and the gene affected, it may be associated with specific diseases or conditions. For example, certain genetic mutations are known to increase the risk of cancers, metabolic disorders, or other diseases.
  • Personalized Medicine: Understanding the genetic makeup of a patient can lead to more personalized medical decisions. For instance, certain medications may work better for individuals with specific genetic profiles. Additionally, knowledge of specific genetic risks can lead to preventative measures or early detection strategies.
  • Genetic Counseling: If a particular harmful variant is identified, genetic counseling may be recommended for the individual and potentially their family members. This can provide information about the risks, potential implications, and choices available regarding reproductive decisions or managing health risks.
  • Research Implications: Identifying common variants among a group of individuals with a shared medical condition can provide insights into the genetic factors contributing to that condition. This can be valuable for research and the development of new therapeutic strategies.

Response Rate

Many people have suggested to us that even if you offer rewards to users to anonymously query their genome, many would not be interested.

We can report that after 2 weeks, more than 75% of users have ran the query, and this continues to grow.

This is an astonishing result.

Here is a snapshot view at the frequencies of data we can observe whilst keeping individual identity private

  • The dataset highlights specific genetic variants that have a statistically significant association with severe respiratory outcomes in COVID-19 patients.
  • These variants can serve as potential genetic markers to identify individuals at increased risk of severe outcomes if infected with the virus.
  • Understanding these associations can be crucial for risk stratification, targeted interventions, and therapeutic developments.

Variants such as 3_45848429_A_T have extremely strong statistical significance (very low p-value) and an odds ratio of 1.870433, suggesting that individuals with this variant have an increased risk of severe respiratory outcomes with COVID-19.

We aim to dig deeper into this data to demonstrate to pharma companies how we can help them get better genomic data for their studies, with repeat consent built into the protocol. If you are a pharmaceutical company or research organisation that would liek to learn more, please reach out to info@genomes.io.

If you have any questions about this or anything else — join over 2500 people in the Discord: https://discord.com/invite/bYvqcNDrvC or jump into the Telegram group: https://t.me/+TblGWLX6Nul3ClGw

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GenomesDAO

GenomesDAO is a genomic data security company that democratizes and decentralizes genomics in Healthcare