Effects Of Polygenic Risk Score Research Articles

Effects of polygenic risk score, childhood trauma and resilience on depressive symptoms in Chinese adolescents in a three-year cohort study

BackgroundPolygenic risk score (PRS) is a method of revealing multiple genes effect. The study of PRS and childhood trauma (CT) and resilience on adolescent depressive symptoms are fewer reported, especially the functional mechanism of resilience among them. Methods718 Chinese adolescents aged 10-14 years were surveyed including CT, resilience, depressive symptoms, and phenotype data in three years of the cohort study. PRS was calculated by the weighted accumulation effects of alleles on depressive symptoms. Their relationships were analyzed by the mediation and moderation models. ResultsPRS and CT were risk factors for depressive symptoms. Interaction (PRS × CT) on depressive symptoms had no statistical significance. Resilience acted as the protective mediator from CT (emotional abuse, emotional neglect, physical neglect) to depressive symptoms and moderator from CT (emotional abuse) to depressive symptoms. LimitationsThe sample size was a little small so that the inference were drawn prudently. Except gene data, other were collected by self-reported questionnaire instruments which inevitably brought recall bias. ConclusionsPRS and CT could have adverse impact on depressive symptoms, resilience could alleviate these risk effects as a moderator and a mediator. The findings have important implications for prevention and intervention in adolescent depressive symptoms.

The influence of common polygenic risk and gene sets on social skills group training response in autism spectrum disorder

Social skills group training (SSGT) is a frequently used behavioral intervention in autism spectrum disorder (ASD), but the effects are moderate and heterogeneous. Here, we analyzed the effect of polygenic risk score (PRS) and common variants in gene sets on the intervention outcome. Participants from the largest randomized clinical trial of SSGT in ASD to date were selected (N = 188, 99 from SSGT, 89 from standard care) to calculate association between the outcomes in the SSGT trial and PRSs for ASD, attention-deficit hyperactivity disorder (ADHD), and educational attainment. In addition, specific gene sets were selected to evaluate their role on intervention outcomes. Among all participants in the trial, higher PRS for ADHD was associated with significant improvement in the outcome measure, the parental-rated Social Responsiveness Scale. The significant association was due to better outcomes in the standard care group for individuals with higher PRS for ADHD (post-intervention: β = −4.747, P = 0.0129; follow-up: β = −5.309, P = 0.0083). However, when contrasting the SSGT and standard care group, an inferior outcome in the SSGT group was associated with higher ADHD PRS at follow-up (β = 6.67, P = 0.016). Five gene sets within the synaptic category showed a nominal association with reduced response to interventions. We provide preliminary evidence that genetic liability calculated from common variants could influence the intervention outcomes. In the future, larger cohorts should be used to investigate how genetic contribution affects individual response to ASD interventions.

Greater effect of polygenic risk score for Alzheimer's disease among younger cases who are apolipoprotein E-ε4 carriers

To evaluate how age and apolipoprotein E-ε4 (APOE4) status interact with APOE-independent polygenic risk score (PRSnon-APOE), we estimated PRSnon-APOE in superagers (age ≥ 90 years, N = 346), 89− controls (age 60–89, N = 2930), and Alzheimer's disease (AD) cases (N = 1760). Using superagers, we see a nearly 5 times greater odds ratio (OR) for AD comparing the top PRSnon-APOE decile to the lowest decile (OR = 4.82, p = 2.5 × 10−6), which is twice the OR as using 89− controls (OR = 2.38, p = 4.6 × 10−9). Thus PRSnon-APOE is correlated with age, which in turn is associated with APOE. Further exploring these relationships, we find that PRSnon-APOE modifies age at onset among APOE4 carriers, but not among noncarriers. More specifically, PRSnon-APOE in the top decile predicts an age at onset 5 years earlier compared with the lowest decile (70.1 vs. 75.0 years; t-test p = 2.4 × 10−5) among APOE4 carriers. This disproportionally large PRSnon-APOE among younger APOE4-positive cases is reflected in a significant statistical interaction between APOE4 status and age at onset (β = −0.02, p = 4.8 × 10−3) as a predictor of PRSnon-APOE. Thus, the known AD risk variants are particularly detrimental in young APOE4 carriers.

Genetic factors underlying the bidirectional relationship between autoimmune and mental disorders – Findings from a Danish population-based study

BackgroundPrevious studies have indicated the bidirectionality between autoimmune and mental disorders. However, genetic studies underpinning the co-occurrence of the two disorders have been lacking. In this study, we examined the potential genetic contribution to the association between autoimmune and mental disorders and investigated the genetic basis of overall autoimmune disease. MethodsWe used diagnostic information from patients with seven autoimmune diseases and six mental disorders from the Danish population-based case-cohort sample (iPSYCH2012). We explored the epidemiological association using survival analysis and modelled the effect of polygenic risk scores (PRSs) on autoimmune and mental diseases. Genetic factors were investigated using GWAS and imputed HLA alleles in the iPSYCH cohort. ResultsOf 64,039 individuals, a total of 43,902 (68.6%) were diagnosed with mental disorders and 1383 (2.2%) with autoimmune diseases. There was a significant comorbidity between the two disease classes (P = 2.67 × 10−7, OR = 1.38, 95%CI = 1.22–1.56), with an overall bidirectional association, wherein individuals with autoimmune diseases had an increased risk of subsequent mental disorders (HR = 1.13, 95%CI: 1.07–1.21, P = 7.95 × 10−5) and vice versa (HR = 1.27, 95%CI = 1.16–1.39, P = 8.77 × 10−15). Adding PRSs to these adjustment models did not have an impact on the associations. PRSs for autoimmune diseases were only slightly associated with increased risk of mental disorders (HR = 1.01, 95%CI: 1.00–1.02, p = 0.038), whereas PRSs for mental disorders were not associated with autoimmune diseases overall. Our GWAS highlighted 12 loci on chromosome 6 (minimum P = 2.74 × 10−36, OR = 1.80, 95% CI: 1.64–1.96), which were implicated in gene regulation through bioinformatic functional analyses, thereby identifying new candidate genes for overall autoimmune disease. Moreover, we observed 20 human leukocyte antigen (HLA) alleles strongly associated, either positively or negatively, with overall autoimmune disease, but we did not find significant evidence of their associations with overall mental disorders. A GWAS of a comorbid diagnosis of an autoimmune disease and a mental disorder identified a genome-wide significant locus on chromosome 7 as well (P = 1.43 × 10−8, OR = 10.65, 95%CI = 3.21–35.36). ConclusionsOur findings confirm the overall comorbidity and bidirectionality between autoimmune diseases and mental disorders and identify HLA genes which are significantly associated with overall autoimmune disease. Additionally, we identified several new candidate genes for overall autoimmune disease and ranked them based on their association with the investigated diseases.

GENE-OBESOGENIC ENVIRONMENT INTERACTIONS ON BODY MASS INDICES ACROSS RACE AND SEX AMONG OLDER ADULTS

Gene-obesogenic environment interactions influence body mass index (BMI) across the life-course; however, limited research examines how these interactions may differ by race and sex. Utilizing mixed-effects models, we examined interaction effects of polygenic risk score (PGS) generated from 97 single nucleotide polymorphisms, and environmental factors, including age and physical activity, on measured longitudinal BMI from the Health and Retirement Study (HRS). HRS is a population representative survey study of older adults aged 50-years or older in the U.S. This study used a sub-sample of genotyped Black (N=1,796) and White (N=4,925) males and females. The association between PGS and mean BMI weakened as individuals aged among White males (Pinteraction=0.038) and White females (Pinteraction=0.054). The mean BMI difference between the highest and lowest PGS quintiles was 4.25 kg/m2 among 50-year old White males but 3.11 kg/m2 among the 70-year old’s, i.e. a decrease of 1.14 kg/m2 (95%CI: -0.06,2.65) over 20 years. Similarly, the decrease among 50- and 70-year old White females was 1.33 kg/m2 (95%CI: 0.07,3.45). Additionally, the association between physical activity and BMI was stronger among White females with higher PGS (Pinteraction=0.038). Vigorous physical activity (compared to never) was associated with a 1.71 kg/m2 (95%CI: 1.08,2.35) decrease in mean BMI among those in the highest PGS quintile, compared to a 0.80 kg/m2 (95%CI: 0.32,1.27) decrease among those in the lowest. Overall, we found unique interaction effects across race and sex within an older population; findings reinforce the importance of physical activity among those with an elevated genetic risk.

BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors

PurposeBreast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs). MethodsBOADICEA incorporates the effects of truncating variants inBRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information. ResultsAmong all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with14.7% of women predicted to have a lifetime risk of ≥17–<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk). ConclusionThis comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

Abstract 4177: The joint effects of polygenic risk scores and pathogenic variants in cancer predisposition genes on breast cancer risk in the general population: results from the CARRIERS study

Abstract Background: Understanding the joint effect on breast cancer risk of rare pathogenic variants in cancer predisposition genes and polygenic risk scores (PRS) from common variants can enable a precision approach to breast cancer management. Previous work found that PRS were associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers recruited from cancer genetics clinics (Kuchenbaecker et al. JNCI 2017). The joint effects of pathogenic variants and PRS have not been studied in samples drawn from the general population. There is also no existing study evaluating the effect of PRS in mutation carriers in genes other than BRCA1/2. Here we evaluate the joint effects of PRS and pathogenic mutations in established cancer predisposition genes in a population-based case-control sample. Method: We analyzed 53,199 European-ancestry individuals (20,730 controls and 21,272 cases) drawn from 7 cohorts and 2 population-based case-control studies in the CAnceR RIsk Estimates Related to Susceptibility” (CARRIERS) consortium. Targeted sequencing was performed using dual bar-coded QIAseq. Mutation calling was conducted with Haplotype Caller and Vardict. We sequenced 18 breast cancer predisposition genes: ATM, BARD1, BRCA1, BRCA2, BRIP1, CDH1, CDKN2A, CHECK2, FANCC, MLH1, MSH2, MSH6, NF1, PALB2, PTEN, RAD51C, RAD51D and TP53. The PRS was calculated based on 128 common variants using effect estimates from the largest published breast cancer GWAS. The PRS was standardized to a mean of 0 and standard deviation of 1. Logistic regression was performed to assess the combined effect of identified mutation and common variants (including main and interaction effects for carrier status and PRS). Results: A total of 1,770 pathogenic mutations were observed. About 1% of the study sample had mutations in either BRCA1 (n=209) or BRCA2 gene (n=305), and 2.2% had mutations in other genes (n=1,176). The effect of PRS in BRCA1 carriers was OR= 0.97 (95%CI: 0.62, 1.52); however, this is not statistically significantly different from the PRS in non-carriers [OR=1.23 (95%CI: 1.20, 1.25)] or previous estimates in carriers [OR: 1.14, 95%CI: 1.11-1.17]. The effect of PRS in BRCA2 carriers was OR=1.87 (95%CI: 1.31, 2.78) which was statistically significantly different from that of the non-carriers. Among the mutation carriers in genes other than BRCA, the effect of PRS on breast cancer was OR=1.00 (95%CI: 0.88,1.15). Conclusion: Consistent with previous studies, we did not find evidence that the effect of the PRS among BRCA1 carriers was statistically significantly different than non-carriers. We found some evidence that the PRS effect may be larger among BRCA2 carriers than non-carriers. Our results also suggest that PRS may not have a strong effect on breast cancer risk in mutation carriers of other predisposition genes; further work is needed for verification. Citation Format: Chi Gao, Chunling Hu, Steven N. Hart, Rohan Gnanaolivu, Kun Y. Lee, Jenna Lilyquist, Nicholas J. Boddicker, Bruce Eckloff, Raed Samara, Josh Klebba, Paul Auer, Leslie Bernstein, Mia Gaudet, Hoda Anton-Culver, Amy Trentham-Dietz, Julie R. Palmer, Song Yao, Christopher Haiman, Janet E. Olson, Susan Domchek, Jeffrey Weitzel, David Goldgar, Katherine L. Nathanson, Eric C. Polley, Fergus J. Couch, Peter Kraft. The joint effects of polygenic risk scores and pathogenic variants in cancer predisposition genes on breast cancer risk in the general population: results from the CARRIERS study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4177.

Polygenic risk score increases schizophrenia liability through cognition-relevant pathways.

Cognitive deficit is thought to represent, at least in part, genetic mechanisms of risk for schizophrenia, with recent evidence from statistical modelling of twin data suggesting direct causality from the former to the latter. However, earlier evidence was based on inferences from twin not molecular genetic data and it is unclear how much genetic influence 'passes through' cognition on the way to diagnosis. Thus, we included direct measurements of genetic risk (e.g. schizophrenia polygenic risk scores) in causation models to assess the extent to which cognitive deficit mediates some of the effect of polygenic risk scores on the disorder. Causal models of family data tested relationships among key variables and allowed parsing of genetic variance components. Polygenic risk scores were calculated from summary statistics from the current largest genome-wide association study of schizophrenia and were represented as a latent trait. Cognition was also modelled as a latent trait. Participants were 1313 members of 1078 families: 416 patients with schizophrenia, 290 unaffected siblings, and 607 controls. Modelling supported earlier findings that cognitive deficit has a putatively causal role in schizophrenia. In total, polygenic risk score explained 8.07% [confidence interval (CI) 5.45-10.74%] of schizophrenia risk in our sample. Of this, more than a third (2.71%, CI 2.41-3.85%) of the polygenic risk score influence was mediated through cognition paths, exceeding the direct influence of polygenic risk score on schizophrenia risk (1.43%, CI 0.46-3.08%). The remainder of the polygenic risk score influence (3.93%, CI 2.37-4.48%) reflected reciprocal causation between schizophrenia liability and cognition (e.g. mutual influences in a cyclical manner). Analysis of genetic variance components of schizophrenia liability indicated that 26.87% (CI 21.45-32.57%) was associated with cognition-related pathways not captured by polygenic risk score. The remaining variance in schizophrenia was through pathways other than cognition-related and polygenic risk score. Although our results are based on inference through statistical modelling and do not provide an absolute proof of causality, we find that cognition pathways mediate a significant part of the influence of cumulative genetic risk on schizophrenia. We estimate from our model that 33.51% (CI 27.34-43.82%) of overall genetic risk is mediated through influences on cognition, but this requires further studies and analyses as the genetics of schizophrenia becomes better characterized.

A longitudinal approach to biological psychiatric research: The PsyCourse study.

In current diagnostic systems, schizophrenia and bipolar disorder are still conceptualized as distinct categorical entities. Recently, both clinical and genomic evidence have challenged this Kraepelinian dichotomy. There are only few longitudinal studies addressing potential overlaps between these conditions. Here, we present design and first results of the PsyCourse study (N = 891 individuals at baseline), an ongoing transdiagnostic study of the affective‐to‐psychotic continuum that combines longitudinal deep phenotyping and dimensional assessment of psychopathology with an extensive collection of biomaterial. To provide an initial characterization of the PsyCourse study sample, we compare two broad diagnostic groups defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM‐IV) classification system, that is, predominantly affective (n = 367 individuals) versus predominantly psychotic disorders (n = 524 individuals). Depressive, manic, and psychotic symptoms as well as global functioning over time were contrasted using linear mixed models. Furthermore, we explored the effects of polygenic risk scores for schizophrenia on diagnostic group membership and addressed their effects on nonparticipation in follow‐up visits. While phenotypic results confirmed expected differences in current psychotic symptoms and global functioning, both manic and depressive symptoms did not vary between both groups after correction for multiple testing. Polygenic risk scores for schizophrenia significantly explained part of the variability of diagnostic group. The PsyCourse study presents a unique resource to research the complex relationships of psychopathology and biology in severe mental disorders not confined to traditional diagnostic boundaries and is open for collaborations.

Polygenic risk has an impact on the structural plasticity of hippocampal subfields during aerobic exercise combined with cognitive remediation in multi-episode schizophrenia

Preliminary studies suggest that, besides improving cognition, aerobic exercise might increase hippocampal volume in schizophrenia patients; however, results are not consistent. Individual mechanisms of volume changes are unknown but might be connected to the load of risk genes. Genome-wide association studies have uncovered the polygenic architecture of schizophrenia. The secondary analysis presented here aimed to determine the modulatory role of schizophrenia polygenic risk scores (PRSs) on volume changes in the total hippocampus and cornu ammonis (CA) 1, CA2/3, CA4/dentate gyrus (DG) and subiculum over time. We studied 20 multi-episode schizophrenia patients and 23 healthy controls who performed aerobic exercise (endurance training) combined with cognitive remediation for 3 months and 21 multi-episode schizophrenia patients allocated to a control intervention (table soccer) combined with cognitive remediation. Magnetic resonance imaging-based assessments were performed at baseline and after 3 months with FreeSurfer. No effects of PRSs were found on total hippocampal volume change. Subfield analyses showed that the volume changes between baseline and 3 months in the left CA4/DG were significantly influenced by PRSs in schizophrenia patients performing aerobic exercise. A larger genetic risk burden was associated with a less pronounced volume increase or a decrease in volume over the course of the exercise intervention. Results of exploratory enrichment analyses reinforced the notion of genetic risk factors modulating biological processes tightly related to synaptic ion channel activity, calcium signaling, glutamate signaling and regulation of cell morphogenesis. We hypothesize that a high polygenic risk may negatively influence neuroplasticity in CA4/DG during aerobic exercise in schizophrenia.

Interplay between Schizophrenia Polygenic Risk Score and Childhood Adversity in First-Presentation Psychotic Disorder: A Pilot Study.

A history of childhood adversity is associated with psychotic disorder, with an increase in risk according to number or severity of exposures. However, it is not known why only some exposed individuals go on to develop psychosis. One possibility is pre-existing genetic vulnerability. Research on gene-environment interaction in psychosis has primarily focused on candidate genes, although the genetic effects are now known to be polygenic. This pilot study investigated whether the effect of childhood adversity on psychosis is moderated by the polygenic risk score for schizophrenia (PRS). Data were utilised from the Genes and Psychosis (GAP) study set in South London, UK. The GAP sample comprises 285 first-presentation psychosis cases and 256 unaffected controls with information on childhood adversity. We studied only white subjects (80 cases and 110 controls) with PRS data, as the PRS has limited predictive ability in patients of African ancestry. The occurrence of childhood adversity was assessed with the Childhood Experience of Care and Abuse Questionnaire (CECA.Q) and the PRS was based on genome-wide meta-analysis results for schizophrenia from the Psychiatric Genomics Consortium. Higher schizophrenia PRS and childhood adversities each predicted psychosis status. Nevertheless, no evidence was found for interaction as departure from additivity, indicating that the effect of polygenic risk scores on psychosis was not increased in the presence of a history of childhood adversity. These findings are compatible with a multifactorial threshold model in which both genetic liability and exposure to environmental risk contribute independently to the etiology of psychosis.

Influence of Polygenic Risk Scores on the Association Between Infections and Schizophrenia

BackgroundSeveral studies have suggested an important role of infections in the etiology of schizophrenia; however, shared genetic liability toward infections and schizophrenia could influence the association. We therefore investigated the possible effect of polygenic risk scores (PRSs) for schizophrenia on the association between infections and the risk of schizophrenia. MethodsWe conducted a nested case-control study on a Danish population-based sample born after 1981 comprising of 1692 cases diagnosed with schizophrenia between 1994 and 2008 and 1724 matched controls. All individuals were linked utilizing nationwide population-based registers with virtually complete registration of all hospital contacts for infections. PRSs were calculated using discovery effect size estimates weights from an independent meta-analysis (34,600 cases and 45,968 control individuals). ResultsA prior hospital contact with infection had occurred in 41% of the individuals with schizophrenia and increased the incidence rate ratio (IRR) of schizophrenia by 1.43 (95% confidence interval [CI] = 1.22–1.67). Adding PRS, which was robustly associated with schizophrenia (by an IRR of 1.46 [95% CI = 1.34–1.60] per standard deviation of the score), did not alter the association with infections and the increased risk of schizophrenia remained (IRR = 1.41; 95% CI = 1.20–1.66). Furthermore, there were no interactions between PRS and infections on the risk of developing schizophrenia (p = .554). Neither did PRS affect the risk of acquiring infections among patients with schizophrenia (odds ratio = 1.00; 95% CI = 0.89–1.12) nor among controls (odds ratio = 1.09; 95% CI: 0.96–1.24). ConclusionsPRS and a history of infections have independent effects on the risk for schizophrenia, and the common genetic risk measured by PRS did not account for the association with infection in this sample.

A four-center study on the effect of polygenic risk score on cerebrospinal fluid markers and memory decline in mild cognitive impairment patients

A four-center study on the effect of polygenic risk score on cerebrospinal fluid markers and memory decline in mild cognitive impairment patients

Effect of polygenic risk scores on depression in childhood trauma.

Research 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. To test whether the effect of polygenic risk scores on MDD is moderated by childhood trauma. The 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. The 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. The 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.

Polygenic risk scores of lipid-spectra associate with increased risk of cardiovascular events in patients that underwent carotid endarterectomy

Objectives: Unfavourable lipid spectra have been shown to influence the risk of cardiovascular disease. Recent international efforts have found 157 loci implicated as genetic determinants of lipid spectra. Although the effects of a single SNP may be negligible, the combined effects of multiple risk loci may pose a significant increase of risk. Therefore, we sought to investigate the effects of Polygenic Risk Scores (PRS) of lipid-spectra, on carotid plaque phenotype and the risk of secondary manifestations of disease in a cohort of patients that underwent carotid endarterectomy

Genetic susceptibility for bipolar disorder and response to antidepressants in major depressive disorder

The high heterogeneity of response to antidepressant treatment in major depressive disorder (MDD) makes individual treatment outcomes currently unpredictable. It has been suggested that resistance to antidepressant treatment might be due to undiagnosed bipolar disorder or bipolar spectrum features. Here, we investigate the relationship between genetic susceptibility for bipolar disorder and response to treatment with antidepressants in MDD. Polygenic scores indexing risk for bipolar disorder were derived from the Psychiatric Genomics Consortium Bipolar Disorder whole genome association study. Linear regressions tested the effect of polygenic risk scores for bipolar disorder on proportional reduction in depression severity in two large samples of individuals with MDD, treated with antidepressants, NEWMEDS (n=1,791) and STAR*D (n=1,107). There was no significant association between polygenic scores for bipolar disorder and response to treatment with antidepressants. Our data indicate that molecular measure of genetic susceptibility to bipolar disorder does not aid in understanding non-response to antidepressants.

Germline SNP analysis as a biomarker for the prediction response to therapy in breast cancer

Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).BOADICEA incorporates the effects of truncating variants inBRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with14.7% of women predicted to have a lifetime risk of ≥17–<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk).This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.

Menopause and Sexual Function

Breast cancer (BC) risk prediction allows systematic identification of individuals at highest and lowest risk. We extend the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) risk model to incorporate the effects of polygenic risk scores (PRS) and other risk factors (RFs).BOADICEA incorporates the effects of truncating variants inBRCA1, BRCA2, PALB2, CHEK2, and ATM; a PRS based on 313 single-nucleotide polymorphisms (SNPs) explaining 20% of BC polygenic variance; a residual polygenic component accounting for other genetic/familial effects; known lifestyle/hormonal/reproductive RFs; and mammographic density, while allowing for missing information.Among all factors considered, the predicted UK BC risk distribution is widest for the PRS, followed by mammographic density. The highest BC risk stratification is achieved when all genetic and lifestyle/hormonal/reproductive/anthropomorphic factors are considered jointly. With all factors, the predicted lifetime risks for women in the UK population vary from 2.8% for the 1st percentile to 30.6% for the 99th percentile, with14.7% of women predicted to have a lifetime risk of ≥17–<30% (moderate risk according to National Institute for Health and Care Excellence [NICE] guidelines) and 1.1% a lifetime risk of ≥30% (high risk).This comprehensive model should enable high levels of BC risk stratification in the general population and women with family history, and facilitate individualized, informed decision-making on prevention therapies and screening.