Ancestry Matters: Lack of Representation of Human Genetic Diversity in Genomic Databases
I was delighted to have been invited as one of the guest speakers for this series of talks, followed by an in-person discussion in Boston.
American Society of Human Genetics (ASHG) Trainee Paper Spotlight
Hosts, Andrew Marderstein and Lucia Hindorff, chat with Bárbara Bitarello on her work, " Polygenic Scores for Height in Admixed Populations" and what led to her career path. Check out the written interview by visiting the ASHG website. Read the paper here: “Polygenic Scores for Height in Admixed Populations” Listen here
Boinformatics: Chatting about polygenic risk scores
Listen here. Polygenic risk scores (PRS) rely on the genome-wide association studies (GWAS) to predict the phenotype based on the genotype. However, the prediction accuracy suffers when GWAS from one population are used to calculate PRS within a different population, which is a problem because the majority of the GWAS are done on cohorts of European ancestry. In this episode, Bárbara Bitarello helps us understand how PRS work and why they don’t transfer well across populations.
Theoretical and empirical quantification of the accuracy of polygenic scores in ancestry divergent populations
This week in Journal Club at the Mathieson Lab we discussed the recently published paper by Wang et. al (2020) on the theoretical aspects of the transferability of polygenic risk scores across ancestries.
Polygenic Risk Scores performance in diverse ancestry populations
Investigations on different methods for PRS calculation, the effects of different modelling and pruning approaches, and transferability of PRS across ancestries
Low transferability of height polygenic risk scores in admixed ancestry populations
Abstract Polygenic risk scores (PRS) summarize the results of GWAS into a single number that can predict quantitative phenotype or disease risk. One barrier to the use of PRS in clinical practice is that the majority of GWAS come from cohorts of European ancestry, and predictive power is lower in non-European ancestry cohorts. There are many possible reasons for this decrease; here we show that differences in allele frequencies, LD patterns, and phenotypic variance across ancestries are unlikely to be driving this pattern.
Polygenic risk scores perform poorly across populations
Abstract | The vast majority of genome-wide association studies (GWAS) are performed in cohorts of European ancestry. Systematic differences in polygenic risk scores (PRS) between European and non-European ancestry populations are believed to be largely spurious. However, it is not clear whether they are completely inaccurate nor how much individual-level predictive power is lost by applying PRS based on European-ancestry GWAS to non-European ancestry populations. Finally, a quantitative understanding of the biological or statistical basis for the poor performance of PRS in non-European-ancestry populations is lacking.