Polygenic risk scores: from research tools to clinical instruments

Lewis, Cathryn M.; Vassos, Evangelos

doi:10.1186/s13073-020-00742-5

Cited by 851 publications

(846 citation statements)

References 98 publications

Supporting

Mentioning

763

Contrasting

Order By: Relevance

“…In Europeans, individuals in the top 10% of PRS had an OR of 3.6 for BD, compared with individuals with average PRS (middle decile), which translates into a modest absolute lifetime risk of the disorder (7.2% based on PRS alone). While PRS are invaluable tools in research settings, the current BD PRS lack sufficient power to separate individuals into clinically meaningful risk categories, and therefore have no clinical utility at present 85,86 . PRS from this European BD meta-analysis yield higher R 2 values in diverse ancestry samples than PRS based on any currently available BD GWAS within the same ancestry 57 .…”

Section: Discussionmentioning

confidence: 99%

Genome-wide association study of over 40,000 bipolar disorder cases provides new insights into the underlying biology

Mullins¹,

Aj²,

Ks³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Bipolar disorder (BD) is a heritable mental illness with complex etiology. We performed a genome-wide association study (GWAS) of 41,917 BD cases and 371,549 controls, which identified 64 associated genomic loci. BD risk alleles were enriched in genes in synaptic and calcium signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers and antiepileptics. Integrating eQTL data implicated 15 genes robustly linked to BD via gene expression, including druggable genes such as HTR6, MCHR1, DCLK3 and FURIN. This GWAS provides the best-powered BD polygenic scores to date, when applied in both European and diverse ancestry samples. Together, these results advance our understanding of the biological etiology of BD, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

show abstract

Section: Discussionmentioning

confidence: 99%

Genome-wide association study of over 40,000 bipolar disorder cases provides new insights into the underlying biology

Mullins¹,

Aj²,

Ks³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…While PRS only explain a relatively small proportion of the variance of BD, the results of our study indicate that BD-PRS may be still useful for early identification and risk stratification in the future. Currently, the predictive power of psychiatric PRS is still too limited for clinical application (61). However, future, exponentially larger GWAS will substantially increase the signal reliably captured and increase the predictive power of PRS (39).…”

Section: Resultsmentioning

confidence: 99%

Risk Stratification for Bipolar Disorder Using Polygenic Risk Scores Among Young High-Risk Adults

et al. 2020

View full text Add to dashboard Cite

Identifying high-risk groups with an increased genetic liability for bipolar disorder (BD) will provide insights into the etiology of BD and contribute to early detection of BD. We used the BD polygenic risk score (PRS) derived from BD genome-wide association studies (GWAS) to explore how such genetic risk manifests in young, high-risk adults. We postulated that BD-PRS would be associated with risk factors for BD. Methods: A final sample of 185 young, high-risk German adults (aged 18-35 years) were grouped into three risk groups and compared to a healthy control group (n = 1,100). The risk groups comprised 117 cases with attention deficit hyperactivity disorder (ADHD), 45 with major depressive disorder (MDD), and 23 help-seeking adults with early recognition symptoms [ER: positive family history for BD, (sub)threshold affective symptomatology and/or mood swings, sleeping disorder]. BD-PRS was computed for each participant. Logistic regression models (controlling for sex, age, and the first five ancestry principal components) were used to assess associations of BD-PRS and the high-risk phenotypes. Results: We observed an association between BD-PRS and combined risk group status (OR = 1.48, p < 0.001), ADHD diagnosis (OR = 1.32, p = 0.009), MDD diagnosis (OR = 1.96, p < 0.001), and ER group status (OR = 1.7, p = 0.025; not significant after correction for multiple testing) compared to healthy controls. Biere et al. Risk Stratification for Bipolar Disorder Conclusions: In the present study, increased genetic risk for BD was a significant predictor for MDD and ADHD status, but not for ER. These findings support an underlying shared risk for both MDD and BD as well as ADHD and BD. Improving our understanding of the underlying genetic architecture of these phenotypes may aid in early identification and risk stratification.

show abstract

“…Most current genetic risk scores are derived from single nucleotide polymorphisms (SNPs) identified by genome wide association studies [10][11][12][13][14][15]. These tests, called polygenic risk scores, construct a score based on a linear combination of the value of a collection of SNPs.…”

Section: Introductionmentioning

confidence: 99%

Genetic Risk Score for Ovarian Cancer Based on Chromosomal-scale Length Variation

Toh

Brody

2020

Preprint

View full text Add to dashboard Cite

Introduction.Twin studies indicate thata substantial fraction of ovarian cancers should be predictable from genetic testing. Genetic risk scores can stratify women into different classes of risk. Higher risk women can be treated or screened for ovarian cancer, which should reduce overall death rates due to ovarian cancer. However, current ovarian cancer genetic risk scores, based on SNPs, do not work that well. We developed a genetic risk score based on structural variation, quantified by variations in the length of chromosomes.Methods. We evaluated this genetic risk score using data collected by The Cancer Genome Atlas. From this dataset, we synthesized a dataset of 414 women who had ovarian serous carcinoma and 4225 women who had no form of ovarian cancer. We characterized each woman by 22 numbers, representing the length of each chromosome in their germ line DNA. We used a gradient boosting machine, a machine learning algorithm, to build a classifier that can predict whether a woman had been diagnosed with ovarian cancer in this dataset.Results. The genetic risk score based on chromosomal-scale length variation could stratify women such that the highest 20% had a 160x risk (95% confidence interval 50x-450x) compared to the lowest 20%. The genetic risk score we developed had an area under the curve of the receiver operating characteristic curve of 0.88 (estimated 95% confidence interval 0.86-0.91).Conclusion. A genetic risk score based on chromosomal-scale length variation of germ line DNA provides an effective means of predicting whether or not a woman will develop ovarian cancer.

show abstract

Polygenic risk scores: from research tools to clinical instruments

Cited by 851 publications

References 98 publications

Genome-wide association study of over 40,000 bipolar disorder cases provides new insights into the underlying biology

Genome-wide association study of over 40,000 bipolar disorder cases provides new insights into the underlying biology

Risk Stratification for Bipolar Disorder Using Polygenic Risk Scores Among Young High-Risk Adults

Genetic Risk Score for Ovarian Cancer Based on Chromosomal-scale Length Variation

Contact Info

Product

Resources

About