scholarly journals 1036Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Julia Steinberg ◽  
Jin Yee Lee ◽  
Harry Wang ◽  
Matthew Law ◽  
Amelia Smit ◽  
...  
Keyword(s):  
Early Detection ◽  
Meta Analysis ◽  
External Validation ◽  
Risk Scores ◽  
Melanoma Risk ◽  
Genetic Score ◽  
Discriminative Ability ◽  
Polygenic Risk ◽  
Melanoma Incidence ◽  
Age And Sex

Abstract Background To improve melanoma early detection, tools to predict personal risk based on genetic information (polygenic risk scores, PRS) have been developed, but require external validation. Methods We analysed invasive melanoma incidence in UK Biobank (UKB; n = 395,647; 1,651 cases) and the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4,765; 303 cases). Three PRS were evaluated: 68 genetic variants (SNPs) at 54 loci from a 2020 meta-analysis (PRS68); 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50); 45 SNPs at 21 loci known pre-2020 (PRS45). 10-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment. Results All PRS were strongly associated with melanoma incidence, including after adjustment for age, sex, ethnicity, and ease of tanning. Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in UKB (ratio expected/observed cases E/O=0.65, 95% confidence interval 0.62-0.68) and MCCS (E/O=0.65, 0.57-0.73). For UKB, this was reduced by PRS-adjustment, e.g. PRS50-adjusted risks E/O=0.91 (0.87-0.95). Discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (deltaAUC 0.07-0.1, p < 0.0001), and higher than for PRS45-adjusted risks (deltaAUC 0.02-0.04, p < 0.001). Conclusions A PRS derived from a larger, more diverse meta-analysis improves melanoma risk prediction compared to an earlier PRS. Re-calibration of absolute risks may be necessary for application to specific populations. Key messages A genetic score can improve prediction of melanoma risk and might help tailor melanoma prevention and early detection strategies to different risk levels.

scholarly journals Effect of polygenic risk scores on depression in childhood trauma

2014 ◽  
Vol 205 (2) ◽  
pp. 113-119 ◽  
Author(s):  
Wouter J. Peyrot ◽  
Yuri Milaneschi ◽  
Abdel Abdellaoui ◽  
Patrick F. Sullivan ◽  
Jouke J. Hottenga ◽  
...  
Keyword(s):  
Childhood Trauma ◽  
Meta Analysis ◽  
Genetic Effect ◽  
Risk Scores ◽  
Environment Interaction ◽  
Polygenic Risk ◽  
Gene Environment Interaction ◽  
Gene Environment ◽  
Genome Wide ◽  
Direct Genetic Effect

BackgroundResearch on gene×environment interaction in major depressive disorder (MDD) has thus far primarily focused on candidate genes, although genetic effects are known to be polygenic.AimsTo test whether the effect of polygenic risk scores on MDD is moderated by childhood trauma.MethodThe study sample consisted of 1645 participants with a DSM-IV diagnosis of MDD and 340 screened controls from The Netherlands. Chronic or remitted episodes (severe MDD) were present in 956 participants. The occurrence of childhood trauma was assessed with the Childhood Trauma Interview and the polygenic risk scores were based on genome-wide meta-analysis results from the Psychiatric Genomics Consortium.ResultsThe polygenic risk scores and childhood trauma independently affected MDD risk, and evidence was found for interaction as departure from both multiplicativity and additivity, indicating that the effect of polygenic risk scores on depression is increased in the presence of childhood trauma. The interaction effects were similar in predicting all MDD risk and severe MDD risk, and explained a proportion of variation in MDD risk comparable to the polygenic risk scores themselves.ConclusionsThe interaction effect found between polygenic risk scores and childhood trauma implies that (1) studies on direct genetic effect on MDD gain power by focusing on individuals exposed to childhood trauma, and that (2) individuals with both high polygenic risk scores and exposure to childhood trauma are particularly at risk for developing MDD.

scholarly journals Global biobank analyses provide lessons for computing polygenic risk scores across diverse cohorts

2021 ◽  
Author(s):  
Ying Wang ◽  
Shinichi Namba ◽  
Esteban Lopera ◽  
Sini Kerminen ◽  
Kristin Tsuo ◽  
...  
Keyword(s):  
Best Practices ◽  
Prediction Accuracy ◽  
Disease Risk ◽  
Association Studies ◽  
Meta Analysis ◽  
European Ancestry ◽  
Risk Scores ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Polygenic Risk

SummaryWith the increasing availability of biobank-scale datasets that incorporate both genomic data and electronic health records, many associations between genetic variants and phenotypes of interest have been discovered. Polygenic risk scores (PRS), which are being widely explored in precision medicine, use the results of association studies to predict the genetic component of disease risk by accumulating risk alleles weighted by their effect sizes. However, limited studies have thoroughly investigated best practices for PRS in global populations across different diseases. In this study, we utilize data from the Global-Biobank Meta-analysis Initiative (GBMI), which consists of individuals from diverse ancestries and across continents, to explore methodological considerations and PRS prediction performance in 9 different biobanks for 14 disease endpoints. Specifically, we constructed PRS using heuristic (pruning and thresholding, P+T) and Bayesian (PRS-CS) methods. We found that the genetic architecture, such as SNP-based heritability and polygenicity, varied greatly among endpoints. For both PRS construction methods, using a European ancestry LD reference panel resulted in comparable or higher prediction accuracy compared to several other non-European based panels; this is largely attributable to European descent populations still comprising the majority of GBMI participants. PRS-CS overall outperformed the classic P+T method, especially for endpoints with higher SNP-based heritability. For example, substantial improvements are observed in East-Asian ancestry (EAS) using PRS-CS compared to P+T for heart failure (HF) and chronic obstructive pulmonary disease (COPD). Notably, prediction accuracy is heterogeneous across endpoints, biobanks, and ancestries, especially for asthma which has known variation in disease prevalence across global populations. Overall, we provide lessons for PRS construction, evaluation, and interpretation using the GBMI and highlight the importance of best practices for PRS in the biobank-scale genomics era.

S81INFLUENCES OF POLYGENIC RISK SCORES AND SCHIZOPHRENIA ASSOCIATED CNVS ON BROADLY AND NARROWLY DEFINED PSYCHOSES: PROSPECTIVE STUDY AND META-ANALYSIS

2019 ◽  
Vol 29 ◽  
pp. S155
Author(s):  
Eirini Zartaloudi ◽  
Johan Thygesen ◽  
Aritz Irizar ◽  
Karoline Kuchenbaecker ◽  
Stella Calafato ◽  
...  
Keyword(s):  
Prospective Study ◽  
Meta Analysis ◽  
Risk Scores ◽  
Polygenic Risk

P.0882 A meta-analysis of polygenic risk scores for mood disorders, neuroticism, and schizophrenia in antidepressant response

2021 ◽  
Vol 53 ◽  
pp. S646-S647
Author(s):  
G. Fanelli ◽  
C. Fabbri ◽  
K. Domschke ◽  
A. Minelli ◽  
M. Gennarelli ◽  
...  
Keyword(s):  
Mood Disorders ◽  
Meta Analysis ◽  
Risk Scores ◽  
Antidepressant Response ◽  
Polygenic Risk

scholarly journals Systematic review of risk prediction scores for surgical site infection or periprosthetic joint infection following joint arthroplasty

2017 ◽  
Vol 145 (9) ◽  
pp. 1738-1749 ◽  
Author(s):  
S. K. KUNUTSOR ◽  
M. R. WHITEHOUSE ◽  
A. W. BLOM ◽  
A. D. BESWICK
Keyword(s):  
Systematic Review ◽  
Risk Prediction ◽  
Prediction Models ◽  
Joint Infection ◽  
External Validation ◽  
Surgical Site Infections ◽  
Predictive Performance ◽  
Risk Scores ◽  
Accurate Identification ◽  
Discriminative Ability

SUMMARYAccurate identification of individuals at high risk of surgical site infections (SSIs) or periprosthetic joint infections (PJIs) influences clinical decisions and development of preventive strategies. We aimed to determine progress in the development and validation of risk prediction models for SSI or PJI using a systematic review. We searched for studies that have developed or validated a risk prediction tool for SSI or PJI following joint replacement in MEDLINE, EMBASE, Web of Science and Cochrane databases; trial registers and reference lists of studies up to September 2016. Nine studies describing 16 risk scores for SSI or PJI were identified. The number of component variables in a risk score ranged from 4 to 45. The C-index ranged from 0·56 to 0·74, with only three risk scores reporting a discriminative ability of >0·70. Five risk scores were validated internally. The National Healthcare Safety Network SSIs risk models for hip and knee arthroplasties (HPRO and KPRO) were the only scores to be externally validated. Except for HPRO which shows some promise for use in a clinical setting (based on predictive performance and external validation), none of the identified risk scores can be considered ready for use. Further research is urgently warranted within the field.

scholarly journals Polygenic risk scores for major depressive disorder and neuroticism as predictors of antidepressant response: meta-analysis of three treatment cohorts

2018 ◽  
Author(s):  
Joey Ward ◽  
Nicholas Graham ◽  
Rona Strawbridge ◽  
Amy Ferguson ◽  
Gregory Jenkins ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Meta Analysis ◽  
Antidepressant Medication ◽  
Research Network ◽  
Risk Scores ◽  
Antidepressant Response ◽  
Major Depressive ◽  
Polygenic Risk ◽  
Therapeutic Drugs

AbstractThere are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 783). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, β = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, β = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts.

scholarly journals Association between substance use disorder and polygenic liability to schizophrenia

2017 ◽  
Author(s):  
Sarah M. Hartz ◽  
Amy Horton ◽  
Mary Oehlert ◽  
Caitlin E. Carey ◽  
Arpana Agrawal ◽  
...  
Keyword(s):  
Substance Use ◽  
Substance Use Disorder ◽  
Meta Analysis ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Individual Substance ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Individual Dataset ◽  
Shared Genetic

AbstractBackgroundThere are high levels of comorbidity between schizophrenia and substance use disorder, but little is known about the genetic etiology of this comorbidity.MethodsHere, we test the hypothesis that shared genetic liability contributes to the high rates of comorbidity between schizophrenia and substance use disorder. To do this, polygenic risk scores for schizophrenia derived from a large meta-analysis by the Psychiatric Genomics Consortium were computed in three substance use disorder datasets: COGEND (ascertained for nicotine dependence n=918 cases, 988 controls), COGA (ascertained for alcohol dependence n=643 cases, 384 controls), and FSCD (ascertained for cocaine dependence n=210 cases, 317 controls). Phenotypes were harmonized across the three datasets and standardized analyses were performed. Genome-wide genotypes were imputed to 1000 Genomes reference panel.ResultsIn each individual dataset and in the mega-analysis, strong associations were observed between any substance use disorder diagnosis and the polygenic risk score for schizophrenia (mega-analysis pseudo R2 range 0.8%-3.7%, minimum p=4×10-23).ConclusionsThese results suggest that comorbidity between schizophrenia and substance use disorder is partially attributable to shared polygenic liability. This shared liability is most consistent with a general risk for substance use disorder rather than specific risks for individual substance use disorders and adds to increasing evidence of a blurred boundary between schizophrenia and substance use disorder.

scholarly journals Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Klaus Oliver Schubert ◽  
Anbupalam Thalamuthu ◽  
Azmeraw T. Amare ◽  
Joseph Frank ◽  
Fabian Streit ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Treatment Response ◽  
Molecular Mechanisms ◽  
Lithium Treatment ◽  
Meta Analysis ◽  
Risk Scores ◽  
Poor Responders ◽  
Genetic Trait ◽  
Polygenic Risk ◽  
Lithium Response

AbstractLithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

scholarly journals Polygenic risk scores for schizophrenia are associated with oculomotor endophenotypes

2021 ◽  
pp. 1-9
Author(s):  
Annabell Coors ◽  
Mohammed-Aslam Imtiaz ◽  
Meta M. Boenniger ◽  
N. Ahmad Aziz ◽  
Monique M. B. Breteler ◽  
...  
Keyword(s):  
General Population ◽  
Smooth Pursuit ◽  
Association Studies ◽  
Meta Analysis ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Pursuit Velocity ◽  
Oculomotor Function ◽  
Multivariable Regression Models

Abstract Background Schizophrenia is a heterogeneous disorder with substantial heritability. The use of endophenotypes may help clarify its aetiology. Measures from the smooth pursuit and antisaccade eye movement tasks have been identified as endophenotypes for schizophrenia in twin and family studies. However, the genetic basis of the overlap between schizophrenia and these oculomotor markers is largely unknown. Here, we tested whether schizophrenia polygenic risk scores (PRS) were associated with oculomotor performance in the general population. Methods Analyses were based on the data of 2956 participants (aged 30–95) of the Rhineland Study, a community-based cohort study in Bonn, Germany. Genotyping was performed on Omni-2.5 exome arrays. Using summary statistics from a recent meta-analysis based on the two largest schizophrenia genome-wide association studies to date, we quantified genetic risk for schizophrenia by creating PRS at different p value thresholds for genetic markers. We examined associations between PRS and oculomotor performance using multivariable regression models. Results Higher PRS were associated with higher antisaccade error rate and latency, and lower antisaccade amplitude gain. PRS showed inconsistent patterns of association with smooth pursuit velocity gain and were not associated with saccade rate during smooth pursuit or performance on a prosaccade control task. Conclusions There is an overlap between genetic determinants of schizophrenia and oculomotor endophenotypes. Our findings suggest that the mechanisms that underlie schizophrenia also affect oculomotor function in the general population.

scholarly journals Promise of Risk Stratification for Multicancer Screening with Liquid Biopsy Tests

2021 ◽  
Author(s):  
Nilanjan Chatterjee ◽  
Sungwon Kim ◽  
Montserrat Garcia-Closas ◽  
Rob Scharpf ◽  
Kala Visvanathan ◽  
...  
Keyword(s):  
Early Detection ◽  
Cancer Risk ◽  
Risk Stratification ◽  
Liquid Biopsy ◽  
Absolute Risk ◽  
Risk Scores ◽  
Predictive Values ◽  
Cancer Risk Factors ◽  
Polygenic Risk ◽  
The Uk

Abstract Noninvasive multicancer liquid biopsy tests are rapidly emerging for early detection, but implementation will require risk stratification to enhance risk-benefit balance. Using data from the UK Biobank study, we trained and validated a model that allows estimation of absolute risk of developing at least one of the eight common cancers among women. We found that pan-cancer risk scores (PCRSs), defined by the combination of body mass index, smoking, family history of cancer, and cancer-specific polygenic risk scores, were strongly associated with the risk of developing at least one cancer (hazard ratio = 1.40 per sd unit, 95% CI: 1.35 - 1.46, 5-year AUC = 0.61). Projections using recently reported diagnostic accuracy for a multicancer screening test show that positive predictive values of it is expected to vary widely across strata defined by age and PCRS due to differences in underlying absolute risks. Our study suggests that risk-stratification, based on age, emerging polygenic risk scores, and other important cancer risk factors, have significant potential to increase risk-benefit balance of early detection through multicancer liquid biopsy tests.

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