Genome-wide Polygenic Scores Research Articles

Polygenic Liability to Depression Is Associated With Multiple Medical Conditions in the Electronic Health Record: Phenome-wide Association Study of 46,782 Individuals

BackgroundMajor depressive disorder (MDD) is a leading cause of disease-associated disability, with much of the increased burden due to psychiatric and medical comorbidity. This comorbidity partly reflects common genetic influences across conditions. Integrating molecular-genetic tools with health records enables tests of association with the broad range of physiological and clinical phenotypes. However, standard phenome-wide association studies analyze associations with individual genetic variants. For polygenic traits such as MDD, aggregate measures of genetic risk may yield greater insight into associations across the clinical phenome. MethodsWe tested for associations between a genome-wide polygenic risk score for MDD and medical and psychiatric traits in a phenome-wide association study of 46,782 unrelated, European-ancestry participants from the Michigan Genomics Initiative. ResultsThe MDD polygenic risk score was associated with 211 traits from 15 medical and psychiatric disease categories at the phenome-wide significance threshold. After excluding patients with depression, continued associations were observed with respiratory, digestive, neurological, and genitourinary conditions; neoplasms; and mental disorders. Associations with tobacco use disorder, respiratory conditions, and genitourinary conditions persisted after accounting for genetic overlap between depression and other psychiatric traits. Temporal analyses of time-at-first-diagnosis indicated that depression disproportionately preceded chronic pain and substance-related disorders, while asthma disproportionately preceded depression. ConclusionsThe present results can inform the biological links between depression and both mental and systemic diseases. Although MDD polygenic risk scores cannot currently forecast health outcomes with precision at the individual level, as molecular-genetic discoveries for depression increase, these tools may augment risk prediction for medical and psychiatric conditions.

Association of Genome-Wide Polygenic Risk Score for Body Mass Index With Cardiometabolic Health From Childhood Through Midlife.

Genetic information may help to identify individuals in childhood who are at increased risk for cardiometabolic disease. We included 1201 BHS (Bogalusa Heart Study) participants (832 White participants and 369 Black participants) who were followed up to 42.3 years, starting at a mean age of 9.8 years. A validated genome-wide polygenic risk score (PRS) was tested for association with midlife body mass index (BMI), fasting plasma glucose, and systolic blood pressure using multiple linear regression models. Cox proportional hazards models tested associations of the PRS with incident obesity, diabetes, and hypertension. All analyses were conducted according to race and adjusted for baseline age, sex, ancestry, and BMI. The constructed PRS was significantly and modestly correlated with midlife BMI in both White and Black participants, with correlation coefficients of 0.27 (P=1.94×10-8) and 0.16 (P=5.50×10-3), respectively. In White participants, per SD increase of PRS was associated with an average 1.29 kg/m2 higher BMI (P=4.44×10-9), 2.82 mg/dL higher fasting plasma glucose (P=1.17×10-3), and 1.09 mm Hg higher systolic blood pressure (P=3.57×10-2) at midlife. The PRS also conferred a 26% higher increased risk of obesity (P=3.50×10-6) in White participants. In addition, the variance in midlife BMI explained increased from 0.1973 to 0.2293 when PRS was added to the model including age, sex, principal components, and baseline BMI (P<0.0001). No associations were observed in Black participants. Adiposity-related genetic information independently predicted cardiometabolic health in White BHS participants. Null associations observed in Black BHS participants highlight the urgent need for PRS development in multi-ancestry populations.

Associations of Genome-Wide Polygenic Risk Score and Risk Factors With Hypertension in a Japanese Population.

Although many polygenic risk scores (PRS) for cardiovascular traits have been developed in European populations, it is an urgent task to construct a PRS and to evaluate its ability in non-European populations. We developed a genome-wide PRS for blood pressure in a Japanese population and examined the associations between this PRS and hypertension prevalence. We performed a cross-sectional study in 11 252 Japanese individuals who participated in the J-MICC (Japan Multi-Institutional Collaborative Cohort) study. Using publicly available GWAS summary statistics from Biobank Japan, we developed the PRS in the target data (n=7876). With >30 000 single nucleotide polymorphisms, we evaluated PRS performance in the test data (n=3376). Hypertension was defined as systolic blood pressure of 130 mm Hg or more, or diastolic blood pressure of 85 mm Hg or more, or taking an antihypertensive drug. Compared with the middle PRS quintile, the prevalence of hypertension at the top PRS quintile was higher independently from traditional risk factors (odds ratio, 1.73 [95% CI, 1.32-2.27]). The difference of mean systolic blood pressure and diastolic blood pressure between the middle and the top PRS quintile was 4.55 (95% CI, 2.26-6.85) and 2.32 (95% CI, 0.86-3.78) mm Hg, respectively. Subgroups reflecting combinations of Japanese PRS and modifiable lifestyles and factors (smoking, alcohol intake, sedentary time, and obesity) were associated with the prevalence of hypertension. A European-derived PRS was not associated with hypertension in our participants. A PRS for blood pressure was significantly associated with hypertension and BP traits in a general Japanese population. Our findings also highlighted the importance of a combination of PRS and risk factors for identifying high-risk subgroups.

Contribution of Genome-Wide Polygenic Score to Risk of Coronary Artery Disease in Childhood Cancer Survivors

BackgroundAdverse cardiovascular outcomes such as coronary artery disease (CAD) are the leading noncancer causes of morbidity and mortality among childhood cancer survivors. ObjectivesThe aim of this study was to assess the role of a genome-wide polygenic score (GPS) for CAD, well validated in the general population, and its interplay with cancer-related risk factors among childhood cancer survivors. MethodsIn a cohort study of 2,472 5-year childhood cancer survivors from the St. Jude Lifetime Cohort, the association between the GPS and the risk of CAD was performed using Cox regression models adjusted for age at cancer diagnosis, sex, cumulative dose of anthracyclines, and mean heart radiation dose. ResultsAmong survivors of European ancestry, the GPS was significantly associated with the risk of CAD (HR per 1 SD of the GPS: 1.25; 95% CI: 1.04-1.49; P = 0.014). Compared with the first tertile, survivors in the upper tertile had a greater risk of CAD (1.51-fold higher HR of CAD [95% CI: 0.96-2.37; P = 0.074]), although the difference was not statistically significant. The GPS-CAD association was stronger among survivors diagnosed with cancer at age <10 years exposed to >25 Gy heart radiation (HR top vs. bottom tertile of GPS: 15.49; 95% CI: 5.24-45.52; Ptrend = 0.005) but not among those diagnosed at age ≥10 years (Ptrend ≥ 0.77) and not among those diagnosed at age <10 years exposed to ≤25 Gy heart radiation (Ptrend = 0.23). Among high-risk survivors, defined by an estimated relative hazard ≥3.0 from fitted Cox models including clinical risk factors alone, the cumulative incidence of CAD at 40 years from diagnosis was 29% (95% CI: 13%-45%). After incorporating the GPS into the model, the cumulative incidence increased to 48% (95% CI: 26%-69%). ConclusionsChildhood cancer survivors are at risk for premature CAD. A GPS may help identify those who may benefit from targeted screening and personalized preventive interventions.

The sexual brain, genes, and cognition: A machine‐predicted brain sex score explains individual differences in cognitive intelligence and genetic influence in young children

Sex impacts the development of the brain and cognition differently across individuals. However, the literature on brain sex dimorphism in humans is mixed. We aim to investigate the biological underpinnings of the individual variability of sexual dimorphism in the brain and its impact on cognitive performance. To this end, we tested whether the individual difference in brain sex would be linked to that in cognitive performance that is influenced by genetic factors in prepubertal children (N = 9,658, ages 9–10 years old; the Adolescent Brain Cognitive Development study). To capture the interindividual variability of the brain, we estimated the probability of being male or female based on the brain morphometry and connectivity features using machine learning (herein called a brain sex score). The models accurately classified the biological sex with a test ROC–AUC of 93.32%. As a result, a greater brain sex score correlated significantly with greater intelligence (p fdr < .001, ηp2 = .011–.034; adjusted for covariates) and higher cognitive genome‐wide polygenic scores (GPSs) (p fdr < .001, ηp2 < .005). Structural equation models revealed that the GPS‐intelligence association was significantly modulated by the brain sex score, such that a brain with a higher maleness score (or a lower femaleness score) mediated a positive GPS effect on intelligence (indirect effects = .006–.009; p = .002–.022; sex‐stratified analysis). The finding of the sex modulatory effect on the gene–brain–cognition relationship presents a likely biological pathway to the individual and sex differences in the brain and cognitive performance in preadolescence.

Racial Discrimination and Alcohol Problems: Examining Interactions with Genetic Risk and Impulsivity among African American Young Adults.

Experiences of racial discrimination have been shown to increase risk for alcohol problems. Some individuals may be particularly vulnerable to the negative effects of racial discrimination. However, little research has examined interaction effects between racial discrimination and individual characteristics, such as genetic predispositions and personality, in relation to alcohol outcomes. This study examined whether genetic risk and dimensions of impulsivity moderate the association between racial discrimination and alcohol problems among African American young adults (n = 383, Mage = 20.65, SD = 2.28; 81% female). Participants completed online surveys and provided a saliva sample for genotyping. Results from multiple regression analyses indicated that both blatant and subtle forms of racial discrimination (i.e., experience of racist events and racial microaggressions) were associated with more alcohol problems. Racial microaggressions interacted with dimensions of impulsivity in relation to alcohol problems, such that racial microaggressions were associated with more alcohol problems when negative urgency was high or when sensation seeking was low. There was no significant interaction between alcohol use disorder genome-wide polygenic score and experience of racist events or racial microaggression in relation to alcohol problems, which may partly reflect low power due in part to limited representation of African-Americans in genetic research. The findings highlight the need to increase the representation of African Americans in genetically-informed research in order to better characterize genetic risk and understand gene-environment interaction in this understudied population, as well as the importance of examining impulsivity as a multidimensional construct that interacts with racial discrimination in relation to alcohol outcomes.

A Family and a Genome-Wide Polygenic Risk Score Are Independently Associated With Stroke in a Population-Based Study

Positive family history and genetic risk scores have been shown to independently capture those individuals with high risk for stroke. The aim of our study was to evaluate the amount of shared information between family history and genetic risk and to investigate their combined effect on the association with prevalent and incident stroke cases. We obtained a family risk score (FamRS), weighted for disease onset and family size as well as genome-wide polygenic risk score (PGS) including over 3.2 million single-nucleotide polymorphisms in the population-based prospective KORA F3 (Cooperative Health Research in the Region of Augsburg) study (n=3071) from Southern Germany. FamRS and PGS were evaluated separately and combined. The measures were once treated as continuous variables but also divided in the highest 20%, 10%, 5%, and 1% percentiles. Odds ratios via logistic regression and hazard ratios via Cox regression were estimated. A stroke event was defined as a hospitalization for stroke that was self-reported in a standardized interview by certified and supervised personnel. The FamRS outperformed other simplified family measures such as affected parents or number of affected family members. FamRS and PGS were not correlated, and no individuals were observed with both very high FamRS and very high PGS (top 1% percentile). In a combined model, both FamRS and PGS were independently from each other associated with risk of stroke, also independent of other traditional risk factors (p [FamRS]=0.02, p [PGS]=0.005). Individuals in the top 1% of either FamRS or PGS were found to have >5-fold risk for stroke (odds ratios, 5.82 [95% CI, 2.08-14]; P=0.0002). The results for incident stroke events showed the same trend but were not significant. Our study shows that a family risk score and PGS capture different information concerning individual stroke risk. Combining the risk measures FamRS and PGS increases predictive power, as demonstrated in a population-based study.

Genome-wide variants and polygenic risk scores for cognitive impairment following blood or marrow transplantation.

Cognitive impairment is prevalent in blood or marrow transplantation (BMT) recipients, albeit with inter-individual variability. We conducted a genome-wide association study of objective cognitive function assessed longitudinally in 239 adult BMT recipients for discovery and replicated in an independent cohort of 540 BMT survivors. Weighted genome-wide polygenic risk scores (PRS) were constructed using linkage disequilibrium pruned significant SNPs. Forty-four genome-wide significant SNPs were identified using additive (n = 3); codominant (n = 20) and genotype models (n = 21). Each additional copy of a risk allele was associated with a 0.28-point (p = 1.07 × 10-8) to a 1.82-point (p = 6.7 × 10-12) increase in a global deficit score. We replicated two SNPs (rs11634183 and rs12486041) with links to neural integrity. Patients in the top PRS quintile were at increased risk of cognitive impairment in discovery (RR = 1.95, 95%CI: 1.28-2.96, p = 0.002) and replication cohorts (OR = 1.84, 95%CI, 1.02-3.32, p = 0.043). Associations were stronger among individuals with lowest clinical risk for cognitive impairment. These findings support potential utility of PRS-based risk classification in the development of targeted interventionsaimed at improving cognitive outcomes in BMT survivors.

Genome-wide risk prediction of common diseases across ancestries in one million people

SummaryPolygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate. All four PRSs had similar accuracy across European and Asian populations, with poorer transferability in the smaller group of individuals of African ancestry. The PRSs had highly similar effect sizes in different populations of European ancestry, and in early- and late-settlement regions with different recent population bottlenecks in Finland. Comparing genome-wide PRSs to PRSs containing a smaller number of variants, the highly polygenic, genome-wide PRSs generally displayed higher effect sizes and better transferability across global ancestries. Our findings indicate that in the populations investigated, the current genome-wide polygenic scores for common diseases have potential for clinical utility within different health-care settings for individuals of European ancestry, but that the utility in individuals of African ancestry is currently much lower.

Evolutionary Trajectories of Complex Traits in European Populations of Modern Humans.

Humans have a great diversity in phenotypes, influenced by genetic, environmental, nutritional, cultural, and social factors. Understanding the historical trends of physiological traits can shed light on human physiology, as well as elucidate the factors that influence human diseases. Here we built genome-wide polygenic scores for heritable traits, including height, body mass index, lipoprotein concentrations, cardiovascular disease, and intelligence, using summary statistics of genome-wide association studies in Europeans. Subsequently, we applied these scores to the genomes of ancient European populations. Our results revealed that after the Neolithic, European populations experienced an increase in height and intelligence scores, decreased their skin pigmentation, while the risk for coronary artery disease increased through a genetic trajectory favoring low HDL concentrations. These results are a reflection of the continuous evolutionary processes in humans and highlight the impact that the Neolithic revolution had on our lifestyle and health.

Development of a polygenic risk score to improve detection of peripheral artery disease.

Peripheral artery disease (PAD) is a major cause of cardiovascular morbidity and mortality, yet timely diagnosis is elusive. Larger genome-wide association studies (GWAS) have now provided the ability to evaluate whether genetic data, in the form of genome-wide polygenic risk scores (PRS), can help improve our ability to identify patients at high risk of having PAD. Using summary statistic data from the largest PAD GWAS from the Million Veteran Program, we developed PRSs with genome data from UK Biobank. We then evaluated the clinical utility of adding the best-performing PRS to a PAD clinical risk score. A total of 487,320 participants (5759 PAD cases) were included in our final genetic analysis. Compared to participants in the lowest 10% of PRS, those in the highest decile had 3.1 higher odds of having PAD (95% CI, 3.06-3.21). Additionally, a PAD PRS was associated with increased risk of having coronary artery disease, congestive heart failure, and cerebrovascular disease. The PRS significantly improved a clinical risk model (Net Reclassification Index = 0.07, p < 0.001), with most of the performance seen in downgrading risk of controls. Combining clinical and genetic data to detect risk of PAD resulted in a model with an area under the curve of 0.76 (95% CI, 0.75-0.77). We demonstrate that a genome-wide PRS can discriminate risk of PAD and other cardiovascular diseases. Adding a PAD PRS to clinical risk models may help improve detection of prevalent, but undiagnosed disease.

Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes

Large-scale biobank initiatives and commercial repositories store genomic data collected from millions of individuals, and tools to leverage the rapidly growing pool of health and genomic data in disease prevention are needed. Here, we describe the derivation and validation of genomics-enhanced risk tools for two common cardiometabolic diseases, coronary heart disease and type 2 diabetes. Data used for our analyses include the FinnGen study (N = 309,154) and the UK Biobank project (N = 343,672). The risk tools integrate contemporary genome-wide polygenic risk scores with simple questionnaire-based risk factors, including demographic, lifestyle, medication, and comorbidity data, enabling risk calculation across resources where genome data is available. Compared to routinely used clinical risk scores for coronary heart disease and type 2 diabetes prevention, the risk tools show at least equivalent risk discrimination, improved risk reclassification (overall net reclassification improvements ranging from 3.7 [95% CI 2.8–4.6] up to 6.2 [4.6–7.8]), and capacity to be improved even further with standard lipid and blood pressure measurements. Without the need for blood tests or evaluation by a health professional, the risk tools provide a powerful yet simple method for preliminary cardiometabolic risk assessment for individuals with genome data available.

Association of Genome-Wide Polygenic Scores for Multiple Psychiatric and Common Traits in Preadolescent Youths at Risk of Suicide

Suicide is the second leading cause of death among youths worldwide, but no available means exist to identify the risk of suicide in this population. To assess whether genome-wide polygenic scores for psychiatric and common traits are associated with the risk of suicide among preadolescent children and to investigate whether and to what extent the interaction between early life stress (a major environmental risk factor) and polygenic factors is associated with suicidal thoughts and behaviors among youths. This cohort study analyzed the genotype-phenotype data of 11 869 preadolescent children aged 9 to 10 years from the Adolescent Brain and Cognitive Development study. Data were collected from September 1, 2016, to October 21, 2018, and analyzed from August 1, 2020, to January 3, 2021. Using machine learning approaches, genome-wide polygenic scores of 24 complex traits were estimated to investigate their phenome-wide associations and utility for assessing risk of suicidal thoughts and behaviors (suicidal ideation [active, passive, and overall] and suicide attempt). Genome-wide polygenic scores were used to measure 24 traits, including psychiatric disorders, cognitive capacity, and personality and psychological characteristics. The Child Behavior Checklist was used to measure early life stress, and the Family Environment Scale was used to assess family environment. Suicidal ideation and suicide attempts were derived from the computerized version of the Kiddie Schedule for Affective Disorders and Schizophrenia. Among 11 869 preadolescent children in the US, complete data for phenotypic outcomes, genotypes, and covariates were available for 7140 participants in the multiethnic cohort (mean [SD] age, 9.9 [0.6] years; 3588 girls [50.3%]), including 925 participants with suicidal ideation and 63 participants with suicide attempts. Among those 7140 participants, 729 had African ancestry (self-reported race or ethnicity: 569 Black, 71 Hispanic, and 89 other), 276 had admixed American ancestry (self-reported race or ethnicity: 265 Hispanic, 3 White, and 8 other), 150 had East Asian ancestry (self-reported race or ethnicity: 67 Asian, 18 Hispanic, and 65 other), 5718 had European ancestry (self-reported race or ethnicity: 7 Asian, 39 Black, 1142 Hispanic, 3934 White, and 596 other), and 267 had other ancestries (self-reported race or ethnicity: 70 Asian, 13 Black, 126 Hispanic, 48 White, and 10 other). Three genome-wide polygenic scores were significantly associated (false discovery rate P < .05) with suicidal thoughts and behaviors among all participants: attention-deficit/hyperactivity disorder (odds ratio [OR], 1.12; 95% CI, 1.05-1.21; P = .001), schizophrenia (OR, 1.50; 95% CI, 1.17-1.93; P = .002), and general happiness (OR, 0.89; 95% CI, 0.83-0.96; P = .002). In the analysis including only children with European ancestry, 3 additional genome-wide polygenic scores with false discovery rate significance were associated with suicidal thoughts and behaviors: autism spectrum disorder (OR, 1.18; 95% CI, 1.06-1.31; P = .002), major depressive disorder (OR, 1.12; 95% CI, 1.04-1.21; P = .003), and posttraumatic stress disorder (OR, 1.12; 95% CI, 1.04-1.21; P = .004). A significant interaction between genome-wide polygenic scores and environment was found, with genetic risk factors for autism spectrum disorder and the level of early life stress associated with increases in the risk of overall suicidal ideation and overall suicidal thoughts and behaviors (OR, 1.20; 95% CI, 1.07-1.35; P = .002). A machine learning model using multitrait genome-wide polygenic scores and additional self-reported questionnaire data (Child Behavior Checklist and Family Environment Scale) produced a moderately accurate estimate of overall suicidal thoughts and behaviors (area under the receiver operating characteristic curve [AUROC], 0.77; 95% CI, 0.73-0.81; accuracy, 0.67) and suicidal ideation (AUROC, 0.76; 95% CI, 0.72-0.80; accuracy, 0.66) among children with European ancestry only. Among all children in the multiethnic cohort, the integrated model also outperformed the baseline model in estimating the risk of overall suicidal thoughts and behaviors (AUROC, 0.71; 95% CI, 0.67-0.75; accuracy, 0.68) and suicidal ideation (AUROC, 0.75; 95% CI, 0.71-0.78; accuracy, 0.67). In this cohort study of preadolescent youths in the US, higher genome-wide polygenic scores for psychiatric disorders, such as attention-deficit/hyperactivity disorder, autism spectrum disorder, posttraumatic stress disorder, and schizophrenia, were significantly associated with a greater risk of suicidal ideation and suicide attempt. The findings and quantitative models from this study may help to identify children with a high risk of suicide, potentially assisting with early screening, intervention, and prevention.

Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study.

Improved identification of individuals with type 2 diabetes at high cardiovascular (CV) risk could help in selection of newer CV risk-reducing therapies. The aim of this study was to determine whether retinal vascular parameters, derived from retinal screening photographs, alone and in combination with a genome-wide polygenic risk score for coronary heart disease (CHD PRS) would have independent prognostic value over traditional CV risk assessment in patients without prior CV disease. Patients in the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) study were linked to retinal photographs, prescriptions, and outcomes. Retinal photographs were analyzed using VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina) software, a semiautomated artificial intelligence platform, to compute arterial and venous fractal dimension, tortuosity, and diameter. CHD PRS was derived from previously published data. Multivariable Cox regression was used to evaluate the association between retinal vascular parameters and major adverse CV events (MACE) at 10 years compared with the pooled cohort equations (PCE) risk score. Among 5,152 individuals included in the study, a MACE occurred in 1,017 individuals. Reduced arterial fractal dimension and diameter and increased venous tortuosity each independently predicted MACE. A risk score combining these parameters significantly predicted MACE after adjustment for age, sex, PCE, and the CHD PRS (hazard ratio 1.11 per SD increase, 95% CI 1.04-1.18, P = 0.002) with similar accuracy to PCE (area under the curve [AUC] 0.663 vs. 0.658, P = 0.33). A model incorporating retinal parameters and PRS improved MACE prediction compared with PCE (AUC 0.686 vs. 0.658, P < 0.001). Retinal parameters alone and in combination with genome-wide CHD PRS have independent and incremental prognostic value compared with traditional CV risk assessment in type 2 diabetes.

The Latent Structure of Negative Symptoms in the General Population in Adolescence and Emerging Adulthood.

Negative symptoms predict adverse outcomes within psychotic disorders, in individuals at high-risk for psychosis, and in young people in the community. There is considerable interest in the dimensional structure of negative symptoms in clinical samples, and accumulating evidence suggests a 5-factor structure. Little is known about the underlying structure of negative symptoms in young people despite the importance of this developmental stage for mental health. We used confirmatory factor analysis to test the structure of parent-reported negative symptoms at mean ages 16.32 (SD 0.68, N = 4974), 17.06 (SD 0.88, N = 1469) and 22.30 (SD 0.93, N = 5179) in a community sample. Given previously reported associations between total negative symptoms and genome-wide polygenic scores (GPS) for major depressive disorder (MDD) and schizophrenia in adolescence, we assessed associations between individual subdomains and these GPSs. A 5-factor model of flat affect, alogia, avolition, anhedonia, and asociality provided the best fit at each age and was invariant over time. The results of our linear regression analyses showed associations between MDD GPS with avolition, flat affect, anhedonia, and asociality, and between schizophrenia GPS with avolition and flat affect. We showed that a 5-factor structure of negative symptoms is present from ages 16 to 22 in the community. Avolition was most consistently associated with polygenic liability to MDD and schizophrenia, and alogia was least associated. These findings highlight the value of dissecting negative symptoms into psychometrically derived subdomains and may offer insights into early manifestation of genetic risk for MDD and schizophrenia.

Abstract PO-163: Genome-wide polygenic risk score of prostate cancer in African and European ancestry men

Abstract Genome-wide polygenic risk scores (PRS) are reported to have higher performance than standard genome-wide significant PRS across numerous complex traits. We evaluated the ability of genome-wide PRS to evaluate prostate cancer risk compared to our recently developed and highly predictive multi-ancestry PRS of 269 fine-mapped and established prostate cancer risk variants. Genome-wide PRS approaches included LDpred2, PRS-CSx, and EB-PRS. Models were trained using the largest and most diverse prostate cancer GWAS to date of 107,247 cases and 127,006 controls, which was previously used to develop the multi-ancestry PRS of 269 variants. For each approach, we constructed the PRS using population-specific weights (i.e., African or European) and multi-ancestry weights, which were calculated across men from African, European, East Asian, and Hispanic populations in our previous GWAS. Resulting models were tested in independent samples of 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,045 cases and 191,835 controls of European ancestry from the UK Biobank. Across all approaches, multi-ancestry weighted PRS had either similar or stronger performance compared to population-specific weighted PRS, both in terms of area under the curve (AUC) and odds of prostate cancer. Among the genome-wide PRS approaches, PRS-CSx constructed with multi-ancestry weights had the best performance, with AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men. Based on PRS-CSx, African and European ancestry men in the top 90-100% PRS decile relative to men in the median 40-60% PRS category had odds of prostate cancer of 2.67 (95% CI=2.00-3.55) and 4.17 (95% CI=3.87-4.50), respectively. However, the PRS constructed using 269 fine-mapped variants had larger AUCs in both African (0.679, 95% CI=0.659-0.700) and European ancestry men (0.845, 95% CI=0.841-0.849), with African and European ancestry men in the top PRS decile having larger odds of prostate cancer (3.53, 95% CI=2.66-4.69 and 4.20, 95% CI=3.89-4.53, respectively). We are currently further validating these findings in diverse men from Million Veteran's Program. This investigation suggests that genome-wide PRS may not improve the ability to distinguish prostate cancer compared to our genome-wide significant PRS and that a multi-ancestry approach to constructing PRS leads to similar or better performance than a population-specific approach. Citation Format: Burcu F. Darst, Ravi K Madduri, Alexis A. Rodriguez, Xin Sheng, Rosalind A. Eeles, Zsofia Kote-Jarai, John M. Gaziano, Amy C. Justice, David V. Conti, Christopher A. Haiman. Genome-wide polygenic risk score of prostate cancer in African and European ancestry men [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-163.

Pupil size and pupillary light reflex in early infancy: heritability and link to genetic liability to schizophrenia.

Measures based on pupillometry, such as the pupillary light reflex (PLR) and baseline pupil size, reflect physiological responses linked to specific neural circuits that have been implicated as atypical in some psychiatric and neurodevelopmental conditions. We investigated the contribution of genetic and environmental factors to the baseline pupil size and the PLR in 510 infant twins assessed at 5 months of age (281 monozygotic and 229 dizygotic pairs), and its associations with common genetic variants associated with neurodevelopmental (autism spectrum disorder and attention deficit hyperactivity disorder) and mental health (bipolar disorder, major depressive disorder and schizophrenia) conditions using genome-wide polygenic scores (GPSs). Univariate twin modelling showed high heritability at 5 months for both pupil size (h2 = .64) and constriction in response to light (h2 = .62), and bivariate twin modeling indicated substantial independence between the genetic factors influencing each (rG = .38). A statistically significant positive association between infant tonic pupil size and the GPS for schizophrenia was found (β = .15, p = .024), while there was no significant association with the GPS for autism or any other GPSs. This study shows that some pupil measures are highly heritable in early infancy, although substantially independent in their genetic etiologies, and associated with common genetic variants linked to schizophrenia. It illustrates how genetically informed studies of infants may help us understand early physiological responses associated with psychiatric disorders which emerge much later in life.

Common Genetic Variants Contribute to Risk of Transposition of the Great Arteries.

Dextro-transposition of the great arteries (D-TGA) is a severe congenital heart defect which affects approximately 1 in 4,000 live births. While there are several reports of D-TGA patients with rare variants in individual genes, the majority of D-TGA cases remain genetically elusive. Familial recurrence patterns and the observation that most cases with D-TGA are sporadic suggest a polygenic inheritance for the disorder, yet this remains unexplored. We sought to study the role of common single nucleotide polymorphisms (SNPs) in risk for D-TGA. We conducted a genome-wide association study in an international set of 1,237 patients with D-TGA and identified a genome-wide significant susceptibility locus on chromosome 3p14.3, which was subsequently replicated in an independent case-control set (rs56219800, meta-analysis P=8.6x10-10, OR=0.69 per C allele). SNP-based heritability analysis showed that 25% of variance in susceptibility to D-TGA may be explained by common variants. A genome-wide polygenic risk score derived from the discovery set was significantly associated to D-TGA in the replication set (P=4x10-5). The genome-wide significant locus (3p14.3) co-localizes with a putative regulatory element that interacts with the promoter of WNT5A, which encodes the Wnt Family Member 5A protein known for its role in cardiac development in mice. We show that this element drives reporter gene activity in the developing heart of mice and zebrafish and is bound by the developmental transcription factor TBX20. We further demonstrate that TBX20 attenuates Wnt5a expression levels in the developing mouse heart. This work provides support for a polygenic architecture in D-TGA and identifies a susceptibility locus on chromosome 3p14.3 near WNT5A. Genomic and functional data support a causal role of WNT5A at the locus.

Modeling Interaction and Dispersion Effects in the Analysis of Gene-by-Environment Interaction.

Genotype-by-environment interaction (GxE) studies probe heterogeneity in response to risk factors or interventions. Popular methods for estimation of GxE examine multiplicative interactions between individual genetic and environmental measures. However, risk factors and interventions may modulate the total variance of an epidemiological outcome that itself represents the aggregation of many other etiological components. We expand the traditional GxE model to directly model genetic and environmental moderation of the dispersion of the outcome. We derive a test statistic, [Formula: see text], for inferring whether an interaction identified between individual genetic and environmental measures represents a more general pattern of moderation of the total variance in the phenotype by either the genetic or the environmental measure. We validate our method via extensive simulation, and apply it to investigate genotype-by-birth year interactions for Body Mass Index (BMI) with polygenic scores in the Health and Retirement Study (N = 11,586) and individual genetic variants in the UK Biobank (N = 380,605). We find that changes in the penetrance of a genome-wide polygenic score for BMI across birth year are partly representative of a more general pattern of expanding BMI variation across generations. Three individual variants found to be more strongly associated with BMI among later born individuals, were also associated with the magnitude of variability in BMI itself within any given birth year, suggesting that they may confer general sensitivity of BMI to a range of unmeasured factors beyond those captured by birth year. We introduce an expanded GxE regression model that explicitly models genetic and environmental moderation of the dispersion of the outcome under study. This approach can determine whether GxE interactions identified are specific to the measured predictors or represent a more general pattern of moderation of the total variance in the outcome by the genetic and environmental measures.

Polygenic Risk Scores for Kidney Function and Their Associations with Circulating Proteome, and Incident Kidney Diseases.

Genome-wide association studies (GWAS) have revealed numerous loci for kidney function (eGFR). The relationship between polygenic predictors of eGFR, risk of incident adverse kidney outcomes, and the plasma proteome is not known. We developed a genome-wide polygenic risk score (PRS) for eGFR by applying the LDpred algorithm to summary statistics generated from a multiethnic meta-analysis of CKDGen Consortium GWAS ( n =765,348) and UK Biobank GWAS (90% of the cohort; n =451,508), followed by best-parameter selection using the remaining 10% of UK Biobank data ( n =45,158). We then tested the association of the PRS in the Atherosclerosis Risk in Communities (ARIC) study ( n =8866) with incident CKD, ESKD, kidney failure, and AKI. We also examined associations between the PRS and 4877 plasma proteins measured at middle age and older adulthood and evaluated mediation of PRS associations by eGFR. The developed PRS showed a significant association with all outcomes. Hazard ratios per 1 SD lower PRS ranged from 1.06 (95% CI, 1.01 to 1.11) to 1.33 (95% CI, 1.28 to 1.37). The PRS was significantly associated with 132 proteins at both time points. The strongest associations were with cystatin C, collagen α -1(XV) chain, and desmocollin-2. Most proteins were higher at lower kidney function, except for five proteins, including testican-2. Most correlations of the genetic PRS with proteins were mediated by eGFR. A PRS for eGFR is now sufficiently strong to capture risk for a spectrum of incident kidney diseases and broadly influences the plasma proteome, primarily mediated by eGFR.