Current clinical use of polygenic scores will risk exacerbating health disparities

Ar, Martin; Kanai, Masahiro; Kamatani, Yoichiro; Okada, Yukinori; Neale, Benjamin M.; Daly, Mark J.

doi:10.1101/441261

Cited by 67 publications

(68 citation statements)

References 80 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Another limitation of our study was its restriction to individuals of European ancestry, but this decision was necessitated by the ancestry of patients in the meta-GWAS used to build the polygenic scores. The relevance of our findings to individuals of other ancestries, therefore, is unknown [44,45].…”

Section: Limitationsmentioning

confidence: 89%

Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease

et al. 2019

View full text Add to dashboard Cite

Major depressive disorder (MDD) and loneliness are phenotypically and genetically correlated with coronary artery disease (CAD), but whether these associations are explained by pleiotropic genetic variants or shared comorbidities is unclear. To tease apart these scenarios, we first assessed the medical morbidity pattern associated with genetic risk factors for MDD and loneliness by conducting a phenome-wide association study in 18,385 European-ancestry individuals in the Vanderbilt University Medical Center biobank, BioVU. Polygenic scores for MDD and loneliness were developed for each person using previously published meta-GWAS summary statistics, and were tested for association with 882 clinical diagnoses ascertained via billing codes in electronic health records. We discovered strong associations with heart disease diagnoses, and next embarked on targeted analyses of CAD in 3893 cases and 4197 controls. We found odds ratios of 1.11 (95% CI, 1.04-1.18; P 8.43 × 10 −4) and 1.13 (95% CI, 1.07-1.20; P 4.51 × 10 −6) per 1-SD increase in the polygenic scores for MDD and loneliness, respectively. Results were similar in patients without psychiatric symptoms, and the increased risk persisted in females even after adjusting for multiple conventional risk factors and a polygenic score for CAD. In a final sensitivity analysis, we statistically adjusted for the genetic correlation between MDD and loneliness and re-computed polygenic scores. The polygenic score unique to loneliness remained associated with CAD (OR 1.09, 95% CI 1.03-1.15; P 0.002), while the polygenic score unique to MDD did not (OR 1.00, 95% CI 0.95-1.06; P 0.97). Our replication sample was the Atherosclerosis Risk in Communities (ARIC) cohort of 7197 European-ancestry participants (1598 incident CAD cases). In ARIC, polygenic scores for MDD and loneliness were associated with hazard ratios of 1.07 (95% CI, 0.99-1.14; P = 0.07) and 1.07 (1.01-1.15; P = 0.03), respectively, and we replicated findings from the BioVU sensitivity analyses. We conclude that genetic risk factors for MDD and loneliness act pleiotropically to increase CAD risk in females.

show abstract

Section: Limitationsmentioning

confidence: 89%

Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease

et al. 2019

View full text Add to dashboard Cite

show abstract

“…PS could also potentially inform us about the role of genetics in geographic variability of traits and disease. However, a major challenge is that the geographic distribution of PS is a complex function of population genetic differences between the GWAS data and the target samples, complicating its interpretation (Scutari et al 2016;Martin et al 2017;Reisberg et al 2017;Martin et al 2018a). Here we studied the geographic distribution of several PS within Finland and assessed their robustness and possible biases in several ways.…”

Section: Discussionmentioning

confidence: 99%

Geographic variation and bias in polygenic scores of complex diseases and traits in Finland

Kerminen

Martin

Koskela

et al. 2018

Preprint

Self Cite

View full text Add to dashboard Cite

Polygenic scores (PS) are becoming a useful tool to identify individuals with high genetic risk for complex diseases and several projects are currently testing their utility for translational applications.It is also tempting to use PS to assess whether genetic variation can explain a part of the geographic distribution of a phenotype. However, it is not well known how population genetic properties of the training and target samples affect the geographic distribution of PS. Here, we evaluate geographic differences, and related biases, of PS in Finland with geographically well-defined sample of 2,376 individuals from the National FINRISK study. First, we detect geographic differences in PS for coronary artery disease (CAD), rheumatoid arthritis, schizophrenia, waits-hip ratio (WHR), bodymass index (BMI) and height, but not for Crohn's disease or ulcerative colitis. Second, we use height as a model trait to thoroughly assess the possible population genetic biases in PS and apply similar approaches to the other phenotypes. Most importantly, we detect suspiciously large accumulation of geographic differences for CAD, WHR, BMI and height, suggesting bias arising from population genetic structure rather than from a direct genotype-phenotype association. This work demonstrates how sensitive the geographic patterns of current PS are for small biases even within relatively homogenous populations and provides simple tools to identify such biases. A thorough understanding of the effects of population genetic structure on PS is essential for translational applications of PS.

show abstract

“…The observed statistically significant PGS effects were small, appeared only in the EA group, and were moderately weaker in the AA group. Most of the GWAS used to compute SNP weights came from GWAS of individuals of European ancestry and, therefore, would be expected to show weaker correlations in other ancestry groups (Martin et al, 2019). One of the concerns paramount in consideration use of polygenic scores in applied settings has been the inability to separate observed "genetic" associations from structural social mechanisms influencing a myriad of factors, including individual exposures to stress.…”

Section: R a F Tmentioning

confidence: 99%

Utility of Polygenic Scores in Capturing Resilience

Bucknor¹,

Derringer²

2020

Preprint

View full text Add to dashboard Cite

Stress is a well-known risk factor for the development of psychopathology (Harkness, Hayden, & Lopez-Duran, 2015). However, not everyone who is exposed to stress responds in the same way. Individual differences in resilience to stress reflect dynamic interpersonal and intrapersonal factors (Laird, Krause, Funes, & Lavretsky, 2019). Although resilience has been identified to be moderately heritable (30-50%; Boardman, Blalock, & Button, 2008), little is known about the genetic variants that may explain this heritability. While there has not yet been a robust genome-wide association study (GWAS) of resilience, existing GWAS of related phenotypes (proxies) may provide a starting point for developing our understanding of the molecular genetic underpinnings of the observed heritability of resilience. In a population sample of older US adults (N= 9,480), we examined the extent to which 32 polygenic proxy scores explained the variance in resilience. We then compared the utility of these existing genetic predictors to commonly examined demographic and psychological characteristics, such as socioeconomic status and social support. We found that the psychological correlates consistently and substantially outperformed existing polygenic scores. While psychological variables yielded substantial correlations with resilience, only four of the 32 polygenic scores reached significance but with relatively small effects. Our results indicate that existing polygenic scores are not sufficient to inform our understanding of resilience, nor would they be suitable predictors of individual differences in resilience outcomes. We conclude that a large-scale GWAS of resilience will be necessary to identify the specific genetics underlying the observed heritability of resilience.

show abstract

Current clinical use of polygenic scores will risk exacerbating health disparities

Abstract: 2 6 2 7

Cited by 67 publications

References 80 publications

Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease

Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease

Geographic variation and bias in polygenic scores of complex diseases and traits in Finland

Utility of Polygenic Scores in Capturing Resilience

Contact Info

Product

Resources

About