Polygenic Risk Scores in Clinical Psychology: Bridging Genomic Risk to Individual Differences.
paper
Cited
Public
- Authors
- Bogdan, Ryan; Baranger, David A A; Agrawal, Arpana
- Year
- 2018
- Journal
- Annual review of clinical psychology
- PMID
- 29579395
- DOI
- 10.1146/annurev-clinpsy-050817-084847
- PMCID
- PMC7772939
Genomewide association studies (GWASs) across psychiatric phenotypes have shown that common genetic variants generally confer risk with small effect sizes (odds ratio < 1.1) that additively contribute to polygenic risk. Summary statistics derived from large discovery GWASs can be used to generate polygenic risk scores (PRS) in independent, target data sets to examine correlates of polygenic disorder liability (e.g., does genetic liability to schizophrenia predict cognition?). The intuitive appeal and generalizability of PRS have led to their widespread use and new insights into mechanisms of polygenic liability. However, when currently applied across traits they account for small amounts of variance (<3%), are relatively uninformative for clinical treatment, and, in isolation, provide no insight into molecular mechanisms. Larger GWASs are needed to increase the precision of PRS, and novel approaches integrating various data sources (e.g., multitrait analysis of GWASs) may improve the utility of current PRS.
Practicalities of PRS computation.Here, we exemplify using statistics from the most recent Psychiatric Genetics Consortium GWAS of schizophrenia (Schizophrenia Working Group, 2014) in which a discovery GWAS of 34,241 schizophrenia cases and 45,604 controls (initial discovery not including replication due to shared summary statistics). The effect allele and effect size for each SNP from the discovery GWAS is applied to each individual in a target dataset to create a unique person-specific polygenic risk score. We illustrate the approach using 4 SNPs. Summary statistics may be obtained here: https://www.med.unc.edu/pgc/results-and-downloads
Schizophrenia PRS Effect Sizes Across 6 domains.Plotted here is the range of the maximal percentage of variance explained by PGC SCZ2 PRS (Schizophrenia Working Group of the Psychiatric Genomics, 2014) in each study. Studies using other summary statistics are not included. Notably, as these are the maximal amount of variance explained and many studies reporting null effects did not report effect sizes, these estimates should be viewed as optimistic. The percentage of variance explained by Schizophrenia PRS in related traits ranges from 0.001 to 40% with 0.5–1.0% being most common. All = all identified Schizophrenia PRS studies. Course of illness = studies assessing course of illness. Psychiatric disorders and traits = studies evaluating other psychaitic disorders (e.g., bipolar disorder) or traits (e.g., neuroticism). Cognition = cognitive phenotypes (e.g., working memory). Brain-related = imaging phenotypes (e.g., cortical thickness), Health and immune function = immune (CRP levels) and reported health (e.g., physical health). Other = various other phenotypes related to schizophrenia (e.g., urbanicity). Individual studies contributing to this are summarized and * in Tables 1–6.
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| High Polygenic Risk Scores Are Associated With Early Age of Onset of Alcohol Use Disorder in Adolescents and Young Adults at Risk. | 2022 | 36324664 |
External
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| High Polygenic Risk Scores Are Associated With Early Age of Onset of Alcohol Use Disorder in Adolescents and Young Adults at Risk. | Nurnberger JI et al. | — | 2022 | → |
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| Using genetic designs to identify likely causal environmental contributions to psychopathology. | Sellers R et al. | — | 2022 | → |
| Using multivariate endophenotypes to identify psychophysiological mechanisms associated with polygenic scores for substance use, schizophrenia, and education attainment. | Harper J et al. | — | 2022 | → |
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| Great Expectations: A Critical Review of and Suggestions for the Study of Reward Processing as a Cause and Predictor of Depression. | Nielson DM et al. | — | 2021 | → |
| Mapping Pathways by Which Genetic Risk Influences Adolescent Externalizing Behavior: The Interplay Between Externalizing Polygenic Risk Scores, Parental Knowledge, and Peer Substance Use. | Kuo SI et al. | — | 2021 | → |
| Marital Satisfaction as a Moderator of Molecular Genetic Influences on Mental Health. | South SC et al. | — | 2021 | → |
| Multi-Polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry. | Risner VA et al. | — | 2021 | → |
| Pathways to well-being: Untangling the causal relationships among biopsychosocial variables. | Karunamuni N et al. | — | 2021 | → |
| Polygenic risk scores for alcohol involvement relate to brain structure in substance-naïve children: Results from the ABCD study. | Hatoum AS et al. | — | 2021 | → |
| Polygenic Scores for ADHD: A Meta-Analysis. | Li JJ et al. | — | 2021 | → |
| Systematic Review: How the Attention-Deficit/Hyperactivity Disorder Polygenic Risk Score Adds to Our Understanding of ADHD and Associated Traits. | Ronald A et al. | — | 2021 | → |
| The ABCD study: understanding the development of risk for mental and physical health outcomes. | Karcher NR et al. | — | 2021 | → |
| The continuity of effect of schizophrenia polygenic risk score and patterns of cannabis use on transdiagnostic symptom dimensions at first-episode psychosis: findings from the EU-GEI study. | Quattrone D et al. | — | 2021 | → |
| The positive end of the polygenic score distribution for ADHD: a low risk or a protective factor? | Li JJ | — | 2021 | → |
| Twin studies to GWAS: there and back again. | Friedman NP et al. | — | 2021 | → |
| Using a developmental perspective to examine the moderating effects of marriage on heavy episodic drinking in a young adult sample enriched for risk. | Cho SB et al. | — | 2021 | → |
| Advances in early identification of children and adolescents at risk for psychiatric illness. | Raballo A et al. | — | 2020 | → |
| Assessing the Relationship Between Leukocyte Telomere Length and Cancer Risk/Mortality in UK Biobank and TCGA Datasets With the Genetic Risk Score and Mendelian Randomization Approaches. | Gao Y et al. | — | 2020 | → |
| Early Environmental Exposures and Contaminants: a Design Framework for Biospecimen Collection and Analysis for a Prospective National Birth Cohort. | Croff JM et al. | — | 2020 | → |
| Electronic health records and polygenic risk scores for predicting disease risk. | Li R et al. | — | 2020 | → |
| Interpersonal childhood adversity and stress generation in adolescence: Moderation by HPA axis multilocus genetic variation. | Huang M et al. | — | 2020 | → |
| Looking at Intergenerational Risk Factors in Schizophrenia Spectrum Disorders: New Frontiers for Early Vulnerability Identification? | Poletti M et al. | — | 2020 | → |
| Maternal environmental risk factors and the development of internalizing and externalizing problems in childhood: The complex role of genetic factors. | Ensink JBM et al. | — | 2020 | → |
| Prospective study of polygenic risk, protective factors, and incident depression following combat deployment in US Army soldiers. | Choi KW et al. | — | 2020 | → |
| Sibling comparisons elucidate the associations between educational attainment polygenic scores and alcohol, nicotine and cannabis. | Salvatore JE et al. | — | 2020 | → |
| Stability in effects of different smoking-related polygenic risk scores over age and smoking phenotypes. | Deutsch AR et al. | — | 2020 | → |
| Associations between an educational attainment polygenic score with educational attainment in an African American sample. | Rabinowitz JA et al. | — | 2019 | → |
| Cortisol awakening response and additive serotonergic genetic risk interactively predict depression in two samples: The 2019 Donald F. Klein Early Career Investigator Award Paper. | Vrshek-Schallhorn S et al. | — | 2019 | → |
| Exploring the relationship between polygenic risk for cannabis use, peer cannabis use and the longitudinal course of cannabis involvement. | Johnson EC et al. | — | 2019 | → |
| Genes, Roommates, and Residence Halls: A Multidimensional Study of the Role of Peer Drinking on College Students' Alcohol Use. | Smith RL et al. | — | 2019 | → |
| Genome-wide association studies of alcohol dependence, DSM-IV criterion count and individual criteria. | Lai D et al. | — | 2019 | → |
| Impaired Corollary Discharge in Psychosis and At-Risk States: Integrating Neurodevelopmental, Phenomenological, and Clinical Perspectives. | Poletti M et al. | — | 2019 | → |
| Polygenic risk for alcohol misuse is moderated by romantic partnerships. | Barr PB et al. | — | 2019 | → |
| Polygenic Risk Scores for Psychiatric Disorders Reveal Novel Clues About the Genetics of Disordered Gambling. | Piasecki TM et al. | — | 2019 | → |
| Serotonergic multilocus genetic variation moderates the association between major interpersonal stress and adolescent depressive symptoms: Replication and candidate environment specification. | Starr LR et al. | — | 2019 | → |
| Spatial genome exploration in the context of cognitive and neurological disease. | Rajarajan P et al. | — | 2019 | → |
| The Genetic Relationship Between Alcohol Consumption and Aspects of Problem Drinking in an Ascertained Sample. | Johnson EC et al. | — | 2019 | → |
| The Role of Emergence in Genetically Informed Relationships Research: A Methodological Analysis. | Salvatore JE et al. | — | 2019 | → |
| The Utility of Event-Related Potentials in Clinical Psychology. | Hajcak G et al. | — | 2019 | → |
| Unpacking Genetic Risk Pathways for College Student Alcohol Consumption: The Mediating Role of Impulsivity. | Ksinan AJ et al. | — | 2019 | → |
| Neuron-specific signatures in the chromosomal connectome associated with schizophrenia risk. | Rajarajan P et al. | — | 2018 | → |
| Understanding Mechanisms of Genetic Risk for Adolescent Internalizing and Externalizing Problems: The Mediating Role of Parenting and Personality. | Su J et al. | — | 2018 | → |