Equity-focussed Research Presentations
Attention Presenters - please review the Speaker Information Page available
here
Presentation Overview: Show
The role of race in medical decision-making has been a contentious issue. Insights from history and population genetic studies suggest considerations of race as a differentiating marker for medical practices can be influenced by systemic bias, leading to serious errors. This might impact treatment of complex diseases such as cardiovascular disease (CVD).
We seek to identify instrumental variables and test whether diagnoses (Dx) and treatments impacting coronary thrombosis (CT) are racially linked. Using data from UK Biobank, we found minimal, non-significant racial differences in odds ratio (OR) between cardiac fatalities and among CVD diagnoses in living patients. Genetic classification vs. racial identification of Black British (BB) showed no significant differences in CVD treatment. Among hyperlipidemia patients, BB tended to suppress prescription for statins and fibrates, even among older patients (OR=0.615, 95%CI: 0.385-0.983, p-value=0.04), but lipids-level differences immediately prior to the first prescription showed no significant racial bias. Using polygenic risk scores (PRS) for CT yielded higher OR (2.198, 95%CI: 1.725-2.801, p-value=1.8×10^-10) for BB for higher PRS deciles compared to CT Dx OR for BB. Higher PRS deciles also showed increased risk for BB. Therefore, PRS can be a useful proxy for Dx yielding better predictive power for underrepresented minorities.
Presentation Overview: Show
CRISPR/Cas9 is a genome editing tool widely used in biological and clinical research. Naturally-occurring human genomic variations, through altering the sequence context of CRISPR/Cas9 targets, can significantly affect its editing outcomes. However, these effects have not been systematically studied or documented. Herein, we present CROTONdb, a database that enables fast and comprehensive investigations of single nucleotide variant (SNV) effects on CRISPR/Cas9 outcomes. CROTONdb leverages state-of-the-art machine-learning predictors to evaluate unbiased SNV effects on CRISPR/Cas9 outcomes. As a case study, we investigated a candidate Cas9 target in oncogene FGFR3 that is sensitive to SNV effect of rs2305181. The minor allele of rs2305181 was predicted to substantially decrease the knockout efficacy from 83.8% to 62.5%. Importantly, rs2305181 has a minor allele frequency of 29.7% and 0.7% in the African and European populations, respectively. If CRISPR/Cas9 is programmed to target this region in primary human cells or in clinical settings, the population stratification of this Cas9-altering variant may lead to health disparities. Similarly, we predicted large SNV effects in Cas9 targets used in preclinical animal experiments and early-phase clinical trials. This highlights the ubiquitous Cas9-altering SNV effects that are made easily accessible by CROTONdb.
Presentation Overview: Show
Motivation: Biodiversity is proposed as a sustainable alternative for the economic development of high-biodiversity regions. Especially in the field of biodiversity genomics, the development of low-cost DNA sequencing opens an opportunity for new actors beyond academia to engage in genomic sequencing. However, it is challenging to adequately compensate local population for their contribution to the innovation process, preventing better bioeconomy development. Although many repositories register genomic data to support biodiversity research, they do not facilitate the fair sharing of economical benefits.
Results: In this work, we propose the creation of the Amazon Biobank, a community-based genetic database. By combining blockchain and smart contract technologies, it provides adequate benefit-sharing among all participants who collect, insert, process, store and validate genomic data. It also provides traceability and auditability, allowing easy association between biotechnological research and DNA data.
Availability and Implementation:https://github.com/amazon-biobank/biobank
Presentation Overview: Show
Science journalism shapes the public’s view of scientific findings and legitimizes sources as experts. Even if unintentional, biases may influence who is identified and ultimately included as an expert. To identify possible biases, we analyzed 22,001 non-research articles published by Nature. Our analysis considered two possible sources of disparity: gender and name origin (a proxy for author nationality). We extracted cited authors’ names as well as names of quoted speakers to predict gender and name origin.
To quantify the disparity in representation between science journalism and scientific publications, we chose first and last authors within primary research articles in Nature and a subset of Springer Nature articles in the same time period as our comparator. We found a skew towards male quotation in Nature science journalism-related articles, but is trending toward equal representation at a faster rate than academic publishing. Our name origin analysis found a significant over-representation of names with predicted Celtic/English origin and under-representation of names with a predicted East Asian origin in extracted quotes. Through our comprehensive analysis, we were able to quantify how recognized persons in news journalism vary by name origin and gender and compare these rates to scientific publishing background rates.