Rank concordance of polygenic indices

Muslimova, Dilnoza; Pereira, Rita Dias; Hinke, Stephanie von; Kippersluis, Hans van; Rietveld, Cornelius A.; Meddens, S. Fleur W.

doi:10.1038/s41562-023-01544-6

Cited by 14 publications

(1 citation statement)

References 53 publications

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“…Even when accumulated across thousands of loci in polygenic scores, the application of polygenic scores is plagued by problems with portability because of effects of both real biological complexity and methodological artifacts (Kaplan & Fullerton, 2022;Matthews, 2022). These issues, in addition to the generally low predictive power, render polygenic scores of little to no use at the individual level (Fusar-Poli, Rutten, van Os, Aguglia, & Guloksuz, 2022; Morris, Davies, & Smith, 2020) and a large amount of uncertainty of estimates appears to hinder the ability to even accurately and consistently stratify individuals into high-risk groups (Ding et al, 2022;Muslimova et al, 2023;Schultz et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

Building causal knowledge in behavior genetics

Madole

Harden

2022

Behav Brain Sci

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Behavior genetics is a controversial science. For decades, scholars have sought to understand the role of heredity in human behavior and life-course outcomes. Recently, technological advances and the rapid expansion of genomic databases have facilitated the discovery of genes associated with human phenotypes like educational attainment and substance use disorders. To maximize the potential of this flourishing science, and to minimize potential harms, careful analysis of what it would mean for genes to be causes of human behavior is needed. In this paper, we advance a framework for identifying instances of genetic causes, interpreting those causal relationships, and applying them to advance causal knowledge more generally in the social sciences. Central to thinking about genes as causes is counterfactual reasoning, the cornerstone of causal thinking in statistics, medicine, and philosophy. We argue that within-family genetic effects represent the product of a counterfactual comparison in the same way as average treatment effects from randomized controlled trials (RCTs). Both average treatment effects from RCTs and within-family genetic effects are shallow causes: they operate within intricate causal systems (non-unitary), produce heterogeneous effects across individuals (non-uniform), and are not mechanistically informative (non-explanatory). Despite these limitations, shallow causal knowledge can be used to improve understanding of the etiology of human behavior and to explore sources of heterogeneity and fade-out in treatment effects.

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Section: Introductionmentioning

confidence: 99%

Building causal knowledge in behavior genetics

Madole

Harden

2022

Behav Brain Sci

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Evaluating Performance and Agreement of Coronary Heart Disease Polygenic Risk Scores

Abramowitz,

Boulier,

Keat

et al. 2024

JAMA

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ImportancePolygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease susceptibility remains incompletely characterized.ObjectiveTo characterize the individual-level agreement of CHD PRSs that perform similarly at the population level.Design, Setting, and ParticipantsCross-sectional study of participants from diverse backgrounds enrolled in the All of Us Research Program (AOU), Penn Medicine BioBank (PMBB), and University of California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record and genotyping data.ExposuresPolygenic risk for CHD from published PRSs and new PRSs developed separately from testing samples.Main Outcomes and MeasuresPRSs that performed population-level prediction similarly were identified by comparing calibration and discrimination of models of prevalent CHD. Individual-level agreement was tested with intraclass correlation coefficient (ICC) and Light κ.ResultsA total of 48 PRSs were calculated for 171 095 AOU participants. The mean (SD) age was 56.4 (16.8) years. A total of 104 947 participants (61.3%) were female. A total of 35 590 participants (20.8%) were most genetically similar to an African reference population, 29 801 (17.4%) to an admixed American reference population, 100 493 (58.7%) to a European reference population, and the remaining to Central/South Asian, East Asian, and Middle Eastern reference populations. There were 17 589 participants (10.3%) with and 153 506 participants without (89.7%) CHD. When included in a model of prevalent CHD, 46 scores had practically equivalent Brier scores and area under the receiver operator curves (region of practical equivalence ±0.02). Twenty percent of participants had at least 1 score in both the top and bottom 5% of risk. Continuous agreement of individual predictions was poor (ICC, 0.373 [95% CI, 0.372-0.375]). Light κ, used to evaluate consistency of risk assignment, did not exceed 0.56. Analysis among 41 193 PMBB and 53 092 ATLAS participants yielded different sets of equivalent scores, which also lacked individual-level agreement.Conclusions and RelevanceCHD PRSs that performed similarly at the population level demonstrated highly variable individual-level estimates of risk. Recognizing that CHD PRSs may generate incongruent individual-level risk estimates, effective clinical implementation will require refined statistical methods to quantify uncertainty and new strategies to communicate this uncertainty to patients and clinicians.

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