Polygenic Scores Research Articles

Breast cancer risk assessment based on susceptibility genes and polygenic risk score in Vietnamese women

BackgroundBreast screening recommendation based on individual risk assessment is emerging as an alternative approach to improve compliance and efficiency to detect breast cancer (BC) early. In Vietnam, prior knowledge to stratify risk based on genetic factors is currently lacking.MethodsThis study recruited 892 BC patients and 735 healthy Vietnamese women from 2016 to 2021. DNA from blood samples of BC patients was first analyzed for pathogenic variants associated with hereditary breast and ovarian cancer syndrome (HBOC). For patients with no HBOC and healthy participants, DNA was genotyped for 398 BC susceptibility single-nucleotide polymorphism (SNPs) by next-generation sequencing to identify significantly associated SNPs and construct a polygenic risk score (PRS).ResultsThe prevalence of HBOC predisposition gene mutations in Vietnamese women with BC was 5.4%. HBOC cases were significantly younger and enriched in the age group of 20–39 years old. In patients with no HBOC, we found 36 SNPs significantly associated with BC that were mostly similar to other Asian ethnicities; 34 of them were used to build a PRS model achieving an area under the receiver operating characteristics curve of 0.61 (95% CI: 0.56–0.68). Women in the top 1% PRS percentile had an odds ratio of 5.09 (95% CI: 3.10–7.86) while those in the bottom 1% had an odds ratio of 0.21 (95% CI: 0.09–0.39) to develop BC.ConclusionsThis study provides the first large datasets for HBOC gene analysis, BC susceptibility SNP association testing, and PRS modeling for Vietnamese women. Together, these data could aid the development of personalized BC screening recommendations for women in Vietnam.

Epigenetic and Genetic Profiling of Comorbidity Patterns among Substance Dependence Diagnoses.

This study investigated the genetic and epigenetic mechanisms underlying the comorbidity patterns of five substance dependence diagnoses (SDs; alcohol, AD; cannabis, CaD; cocaine, CoD; opioid, OD; tobacco, TD). A latent class analysis (LCA) was performed on 31,197 individuals (average age 42±11 years; 49% females) from six cohorts to identify comorbid DSM-IV SD patterns. In subsets of this sample, we tested SD-latent classes with respect to polygenic burden of psychiatric and behavioral traits and epigenome-wide changes in three population groups. An LCA identified four latent classes related to SD comorbidities: AD+TD, CoD+TD, AD+CoD+OD+TD (i.e., polysubstance use, PSU), and TD. In the epigenome-wide association analysis, SPATA4 cg02833127 was associated with CoD+TD, AD+TD, and PSU latent classes. AD+TD latent class was also associated with CpG sites located on ARID1B , NOTCH1 , SERTAD4, and SIN3B , while additional epigenome-wide significant associations with CoD+TD latent class were observed in ANO6 and MOV10 genes. PSU-latent class was also associated with a differentially methylated region in LDB1 . We also observed shared polygenic score (PGS) associations for PSU, AD+TD, and CoD+TD latent classes (i.e., attention-deficit hyperactivity disorder, anxiety, educational attainment, and schizophrenia PGS). In contrast, TD-latent class was exclusively associated with posttraumatic stress disorder-PGS. Other specific associations were observed for PSU-latent class (subjective wellbeing-PGS and neuroticism-PGS) and AD+TD-latent class (bipolar disorder-PGS). We identified shared and unique genetic and epigenetic mechanisms underlying SD comorbidity patterns. These findings highlight the importance of modeling the co-occurrence of SD diagnoses when investigating the molecular basis of addiction-related traits.

Optimizing and benchmarking polygenic risk scores with GWAS summary statistics

BackgroundPolygenic risk score (PRS) is a major research topic in human genetics. However, a significant gap exists between PRS methodology and applications in practice due to often unavailable individual-level data for various PRS tasks including model fine-tuning, benchmarking, and ensemble learning.ResultsWe introduce an innovative statistical framework to optimize and benchmark PRS models using summary statistics of genome-wide association studies. This framework builds upon our previous work and can fine-tune virtually all existing PRS models while accounting for linkage disequilibrium. In addition, we provide an ensemble learning strategy named PUMAS-ensemble to combine multiple PRS models into an ensemble score without requiring external data for model fitting. Through extensive simulations and analysis of many complex traits in the UK Biobank, we demonstrate that this approach closely approximates gold-standard analytical strategies based on external validation, and substantially outperforms state-of-the-art PRS methods.ConclusionsOur method is a powerful and general modeling technique that can continue to combine the best-performing PRS methods out there through ensemble learning and could become an integral component for all future PRS applications.

Genome-wide scan of Flortaucipir PET levels finds JARID2 associated with cerebral tau deposition.

Genetic research on Alzheimer's disease (AD) has primarily focused on amyloid-β (Aβ) pathogenesis, with fewer studies exploring tau pathology. Elucidating the genetic basis of tau pathology could identify novel pathways in AD. We conducted a genome-wide association study of tau standard uptake value ratios (SUVRs) from [18] F-flortaucipir positron emission tomography (PET) images to identify genetic variants underlying Tau pathology. Genetic data and tau-SUVRs from [18] F-flortaucipir PET images were acquired from the A4 (311 with preclinical AD) and ADNI (280 cognitively normal, 76 with mild cognitive impairment, and 19 AD patients) studies. Circulating plasma proteins in UK Biobank Pharma Proteomics Project (UKBPPP, N=54,129) were used to validate genetic findings. SNP genotypes were tested for association with Tau-SUVR levels adjusting for age, sex and population substructure variables. AD association of polygenic risk scores (PRS) of tau and amyloid-SUVRs were assessed. Causal effect of plasma protein levels on Tau pathology were tested using Mendelian randomization analyses. GWAS of tau-SUVR revealed two significant loci: rs78636169 ( P =5.76×10 -10 ) in JARID2 and rs7292124 ( P =2.20×10 -8 ) near ISX . Gene-based analysis of tau deposition highlighted APOE ( P =2.55×10 -6 ), CTNNA3 ( P =2.86×10 -6 ) and JARID2 ( P =1.23×10 -4 ), a component of the PRC2 multi-protein complex which regulates gene expression. Mendelian randomization analysis of available circulating plasma proteins in the UK Biobank Pharma Proteomics Project (UKBPPP) identified LRRFIP1, a protein that binds with PRC2 multi-protein complex, as potentially causally linked to tau pathology. Genes associated with both amyloid and tau pathologies were enriched in endocytosis and signal transduction pathways. AD polygenic risk score (PRS) was associated with amyloid-SUVR but not with tau-SUVR. Amyloid-SUVR PRS had a notable association with AD clinical status, particularly in younger APOE -ε4 carriers, whereas tau-SUVR PRS showed a stronger association in older carriers. We identified a novel potential therapeutic target, JARID2 in the PRC2 multi-protein complex, for tau pathology. Furthermore, gene pathway analysis clarified the distinct roles of Aβ and tau in AD progression, underscoring the complexity of genetic influences across different stages of the disease.

Interaction between tea consumption and genes on activities of daily living disability in older adults.

The effects of tea consumption on delaying aging and the onset of age-related disabilities have been reported; however, it is unclear whether these benefits are impacted by genes. This study aimed to examine the associations between tea consumption and activities of daily living (ADL) and explore the role of genetic factors. Data from 46,487 older adults aged 64-105 who participated in at least one data wave of the Chinese Longitudinal Healthy Longevity Survey (CLHLS) conducted in 2002, 2005, 2008, 2011, 2014, and 2018 were analyzed. Genetic data were produced using the Affymetrix Axiom™myDesign™ (384-format) Human Genotyping Array. The generalized estimation equation and multiple logistic regression models were constructed to examine the effects of tea consumption, polygenic risk score, and their interactions on ADL. Tea consumption was related to reduced ADL decline-the effect was statistically significant among men but not women. A significant interaction between tea consumption and polygenic risk score (PRS) was observed. Tea consumption was associated with a decreased risk of ADL disability only among individuals with a low PRS. These findings indicate that tea consumption plays a role in preventing disability in older adults with low polygenic risk.

Effects and interaction of single nucleotide polymorphisms at the pharmacokinetic/pharmacodynamic site: insights from the Rotterdam study into metformin clinical response and dose titration.

Our study investigated the impact of genetic variations on metformin glycemic response in a cohort from the Rotterdam Study, comprising 14,926 individuals followed for up to 27 years. Among 1285 metformin users of European ancestry, using linear mixed models, we analyzed the association of single nucleotide polymorphisms (SNPs) and a Polygenic Risk Score (PRS) with glycemic response, measured by changes in metformin dosage or HbA1c levels. While individual genetic variants showed no significant association, rs622342 on SLC2A1 correlated with increased glycemic response only in metformin monotherapy patients (β = -2.09, P-value < 0.001). The collective effect of variants, as represented by PRS, weakly correlated with changes in metformin dosage (β = 0.023, P-value = 0.027). Synergistic interaction was observed between rs7124355 and rs8192675. Our findings suggest that while higher PRS correlates with increased metformin dosage, its modest effect size limits clinical utility, emphasizing the need for future research in diverse populations to refine genetic risk models.

Genome-wide association testing beyond SNPs.

Decades of genetic association testing in human cohorts have provided important insights into the genetic architecture and biological underpinnings of complex traits and diseases. However, for certain traits, genome-wide association studies (GWAS) for common SNPs are approaching signal saturation, which underscores the need to explore other types of genetic variation to understand the genetic basis of traits and diseases. Copy number variation (CNV) is an important source of heritability that is well known to functionally affect human traits. Recent technological and computational advances enable the large-scale, genome-wide evaluation of CNVs, with implications for downstream applications such as polygenic risk scoring and drug target identification. Here, we review the current state of CNV-GWAS, discuss current limitations in resource infrastructure that need to be overcome to enable the wider uptake of CNV-GWAS results, highlight emerging opportunities and suggest guidelines and standards for future GWAS for genetic variation beyond SNPs at scale.

Clinical Utility of Genetic Variants in PNPLA3 and TM6SF2 to Predict Liver-Related Events in Metabolic Dysfunction-Associated Steatotic Liver Disease.

Fibrosis-4 (FIB-4) index and genetic polymorphisms have been used in assessing the risk of liver-related events (LRE) in metabolic dysfunction-associated steatotic liver disease (MASLD). To establish a more efficient prediction strategy for LRE, we investigated a combined approach that uses the FIB-4 index and genetic polymorphisms. We enrolled 1304 Japanese patients with biopsy-proven MASLD in this longitudinal multicenter cohort study. PNPLA3, TM6SF2, GCKR and MBOAT7 genotypes were genotyped, and polygenic risk score high fat content (PRS-HFC) were calculated. During the follow-up period of 8.1 year, 96 LRE occurred and 53 patients died. PNPLA3, TM6SF2 and GCKR genotypes were associated with LRE development. We divided patients into three groups based on the FIB-4 index and PNPLA3 and TM6SF2 genotype. The cumulative LRE development rate in each group was 2.1%/28.9%/53.5%, respectively, at 10 years. Multivariate analysis revealed hazard ratios (HRs) for LRE of 10.72 in the high-risk group and 4.80 in the intermediate-risk group. Overall survival in each group was 98.8%/85.2%/72.4%, respectively, at 10 years. HRs for prognosis were 8.74 in the high-risk group and 5.62 in the intermediate-risk group. Patients with FIB-4 index > 2.67 and high PRS-HFC had HR of 6.70 for LRE development and HR of 6.07 for prognosis compared to patients with FIB-4 ≤ 2.67. The approach of measuring the FIB-4 index first followed by assessment of genetic polymorphisms efficiently detected patients at high risk of developing LRE. Therefore, this two-step strategy could be used as a screening method in large populations of patients with MASLD.

Genetic architecture reconciles linkage and association studies of complex traits.

Linkage studies have successfully mapped loci underlying monogenic disorders, but mostly failed when applied to common diseases. Conversely, genome-wide association studies (GWASs) have identified replicable associations between thousands of SNPs and complex traits, yet capture less than half of the total heritability. In the present study we reconcile these two approaches by showing that linkage signals of height and body mass index (BMI) from 119,000 sibling pairs colocalize with GWAS-identified loci. Concordant with polygenicity, we observed the following: a genome-wide inflation of linkage test statistics; that GWAS results predict linkage signals; and that adjusting phenotypes for polygenic scores reduces linkage signals. Finally, we developed a method using recombination rate-stratified, identity-by-descent sharing between siblings to unbiasedly estimate heritability of height (0.76 ± 0.05) and BMI (0.55 ± 0.07). Our results imply that substantial heritability remains unaccounted for by GWAS-identified loci and this residual genetic variation is polygenic and enriched near these loci.

GWASBrewer: An R Package for Simulating Realistic GWAS Summary Statistics.

Many statistical genetics analysis methods make use of GWAS summary statistics. Best statistical practice requires evaluating these methods in realistic simulation experiments. However, simulating summary statistics by first simulating individual genotype and phenotype data is extremely computationally demanding. This high cost may force researchers to conduct overly simplistic simulations that fail to accurately measure method performance. Alternatively, summary statistics can be simulated directly from their theoretical distribution. Although this is a common need among statistical genetics researchers, no software packages exist for comprehensive GWAS summary statistic simulation. We present GWASBrewer, an open source R package for direct simulation of GWAS summary statistics. We show that statistics simulated by GWASBrewer have the same distribution as statistics generated from individual level data, and can be produced at a fraction of the computational expense. Additionally, GWASBrewer can simulate standard error estimates, something that is typically not done when sampling summary statistics directly. GWASBrewer is highly flexible, allowing the user to simulate data for multiple traits connected by causal effects and with complex distributions of effect sizes. We demonstrate example uses of GWASBrewer for evaluating Mendelian randomization, polygenic risk score, and heritability estimation methods.

6715 Short Adult Height in Childhood Cancer Survivors: Prevalence, Risk Factors, and Genetic Contribution

Abstract Disclosure: T. Yoshida: None. J. Baedke: None. F. Wang: None. W. Moon: None. Y. Sapkota: None. J. Miguel Martínez: None. T.E. Merchant: None. C.L. Wilson: None. K.K. Ness: None. M.M. Hudson: None. Y. Yasui: None. A. Delaney: None. Background: Survivors of childhood cancer are at elevated risk for short adult height (SAH) due to cancer and/or its treatment. In the general population, height is a highly polygenic trait; heritability is estimated to be 70-80%. However, the contribution of genetic factors to SAH among childhood cancer survivors is unknown. In addition, the contribution of chemotherapy agents to risk of SAH among survivors has not been established. We assessed: 1) prevalence of SAH; 2) contribution of genetic factors; and 3) impact of cancer therapy including chemotherapy, on SAH in a large cohort of childhood cancer survivors. Methods: Participants included 4461 childhood cancer survivors aged ≥18 years (female 47.5%, mean age 33.2 years old) with measured height information. SAH was defined as height &amp;lt;3rd percentile for age and sex based on the Centers for Disease Control growth charts. Cancer and treatment history were extracted from medical records. We calculated multi-ancestry height polygenic score (PGS) using the latest methodology developed from 5.4 million individuals of diverse ancestries with more than 1 million variants, where lower score associates with shorter height. With a random sample of 75% of survivors, we fit a multivariable logistic regression model for SAH with the PGS, chemotherapy exposures/doses, corticosteroid exposures/doses, and established risk factors for SAH (e.g., age at cancer diagnosis, radiotherapy exposure) as covariates (main model). The remaining 25% of survivors served for validation of the main model and for the calculation of the population attributable fractions (PAF) of the PGS and cancer treatments. Results: The prevalence of SAH was 8.9% among all survivors (9.3% in males; 8.5% in females) and differed widely by primary cancer diagnosis. SAH was associated with lower PGS [odds ratio (OR) 0.47, 95% confidence interval (CI) 0.40-0.55 for a one standard deviation increase], alkylating agent exposure of &amp;gt;12000 mg/m2 (OR 2.19, 95% CI 1.41-3.38, vs. non-exposure), and spinal radiotherapy (OR 3.65, 95% CI 2.23-6.00, vs. non-exposure). Radiotherapy exposure to the hypothalamic-pituitary region and younger age at cancer diagnosis was also associated with SAH in a dose-response manner. The area under the ROC curve of the main model in the validation dataset was 0.80 (95% CI 0.74-0.87), suggesting good predictive ability for SAH by the model. The PAF of SAH calculated from the multiplicative logistic regression model of SAH was 85.7% for cancer treatments and 30.2% and 60.2% for having PGS below the median and the 90th percentile, respectively. Conclusions: Cancer treatments are the primary contributor to SAH risk among survivors with a PAF of 85.7%. Exposure to high-dose alkylating agents contributes to this along with radiotherapy. Inherited genetic factors also affect SAH among survivors but to a much lesser degree than cancer treatments. Presentation: 6/3/2024

9240 Role Of Genetics In The Age-Related Testosterone Decline In Men: A UK Biobank Study

Abstract Disclosure: L. Ogoniak: None. S. Sandmann: None. J. Varghese: None. A.S. Busch: None. Background: Age-related decline in circulating serum testosterone concentrations is a well-established phenomenon in men. While the decline is partially linked to comorbidities such as obesity, type 2 diabetes (T2D), and cardiovascular disease (CVD), healthy ageing men present with rather stable levels. Recent genetic mapping studies demonstrated a large influence of common genetic variation on testosterone levels in men. However, increasing incidence rates of comorbidities in the ageing population are posing a challenge for the disentanglement of effects. Objective: Our study aims to investigate the genetic component of age-dependent testosterone decline in men. We hypothesize that the decline in testosterone levels in ageing men is primarily influenced by comorbidities, without significant alterations in the genetic architecture of testosterone levels. Material and Methods: We included 6,406 men with baseline and follow-up measurements of circulating serum concentrations of total testosterone (T), bioavailable testosterone (BAT) and sex hormone-binding globulin (SHBG) representing an independent sub-cohort of the UK Biobank study. We 1) assessed the association of baseline levels with the decline in sex steroids and 2) developed and verified polygenic risk score (PRS) models for T, BAT and SHBG based on 183,909 men from the UK Biobank (sub cohorts: 70% base, 15% target and 15% validation, follow-up cohort excluded for PRS development). Results: In the follow-up sub cohort, mean age (SD) at baseline was 58.2 yrs ( 7.5) and mean (SD) follow-up period was 4.3 (1.0) yrs. Mean (SD) BAT at baseline were 5.2 (1.32) nmol/L with a mean (SD) decline of 1.6 (24.4) % at follow-up. Baseline BAT, T and SHBG levels were significantly associated with the relative change of the respective biomarker at follow-up (-7.8, -2.9 and -0.4% per nmol/L, respectively, all p &amp;lt;0.001). After correcting for age at baseline, follow-up period and principal components 1-10, PGSTestosterone and PGSBAT were not associated with relative decline of the respective biomarker (both p = n.s.). Conclusion: Our study did not find evidence supporting a genetic component in the age-related decline of circulating serum T or BAT concentrations. Instead, in accordance to previous observational studies, our results suggest that rather non-genetic factors, e.g. increasing incidence rates of comorbidities, drive the age-related decline in sex steroid levels in men. Our study contributes to understanding the intricate relationship between genetic and non-genetic factors with age-related testosterone decline in men and offers valuable insights for potential interventions targeting age-related hormonal changes and associated health outcomes. Presentation: 6/2/2024

7515 Plasma proteomic signatures for type 2 diabetes mellitus and related traits in the UK Biobank

Abstract Disclosure: T. Gupte: None. Z. Azizi: None. K. Nzenkue: None. P. Kho: None. M. Chen: None. J. Zhou: None. R. Guarischi-Sousa: None. D.J. Panyard: None. F. Abbasi: None. K. Watson: None. S. Clarke: None. P.S. Tsao: None. T.L. Assimes: None. Background: The plasma proteome holds promise as a future diagnostic and prognostic tool that can accurately reflect complex human traits and disease processes. We assessed the ability of plasma proteins to associate with two primary risk factors of type 2 diabetes mellitus (T2DM) and to predict incident T2DM. Methods: Clinical, genetic, and high-throughput proteomic data from three subcohorts of 5586, 5584, and 36339 individuals in the UK Biobank were analyzed for association with DXA-measured truncal fat, maximum VO2, and incident T2DM, respectively. Exclusion criteria included prevalent T2DM, history of T1DM, or elevated A1c (&amp;gt;48 mmol/mol) values. We used LASSO to assess relative ability of 13 clinical variables including the Q-Diabetes (Q-D) score, 36 polygenic risk scores (PRSs), and 2923 proteins to associate with each trait by comparing variances explained (R2) and AUC statistics between data types. Stability selection with randomized LASSO identified the most robustly associated proteins for each trait. The benefit of proteomic signatures (PSs) over the Q-D score was evaluated through the derivation of Δ AUC values. Separate case-control groups were developed to evaluate T2DM prediction in the adiposity and fitness cohorts. Results: Across all three subcohorts, the mean age was 56.6 years, 54.9% were female, and 5.4% developed T2DM over a median follow-up of 7.7 years. In the adiposity cohort, a protein-only LASSO model explained 73.2% of the variance in truncal fat and GLIPR1, CLMP, LEP, FABP4, and FAM3C were among the top proteins selected. In the fitness cohort, a protein-only LASSO model explained 61.9% of the variance in maximum VO2 and LEP, CD99, AGRN, ELN, and CA14 were among the top proteins selected. LASSO-derived PSs increased the R2 of truncal fat and maximum VO2 over clinical and genetic factors by 13% and 1%, respectively, with the former also improving risk prediction of T2DM over Q-D [Δ AUC: 0.026 (95% CI -0.007, 0.060)]. In the T2DM cohort, a protein-only LASSO model returned an AUC of 0.856 (95% CI 0.840, 0.871) and PLXNB2, PODXL, PLA2G7, FGFR2, and NFASC were among the top proteins selected. We observed a similar improvement in T2DM prediction over Q-D [Δ AUC: 0.015 (95% CI 0.009, 0.023)] when using a PS derived strictly from the T2DM outcome and augmented with non-overlapping proteins associated with fat and fitness. A few proteins (ranging between 15-33 for each trait) identified by stability selection algorithms offered most of the improvement in risk prediction. Conclusion: Plasma PS modestly improves the prediction of T2DM over that possible with clinical and genetic factors. Further studies are warranted to better elucidate the clinical utility of these signatures in predicting T2DM risk over the standard practice of using the Q-D score. Presentation: 6/2/2024

8393 Low Polygenic Risk Score For Autoimmune Addison’s Disease Identifies Misdiagnosed Cases of Monogenic Primary Adrenal Insufficiency

Abstract Disclosure: M. Aranda Guillen: None. I. Botusan: None. V. Fernando: None. E. Røyrvik: None. A. Bøe Wolff: None. S. Johansson: None. E.S. Husebye: None. S. Bensing: None. O. Kampe: None. D. Eriksson: None. Background: Primary adrenal insufficiency (PAI) is sometimes misdiagnosed as autoimmune Addison's disease (AAD), affecting clinical management and genetic counselling. We tested a polygenic risk score (PRS) for AAD (PRS14AAD) as a tool to reevaluate disease etiology and identify patients misdiagnosed with AAD. Methods: We calculated the PRS14AAD in a cohort of patients diagnosed with AAD but lacking 21-hydroxylase autoantibodies (n=124). Patients with low genetic susceptibility to AAD were selected for whole-genome sequencing to detect potential monogenic causes (n=35). Results: Among the 35 patients, monogenic PAI was diagnosed in 5 (14%) and suspected in 3 additional cases (9%). Three out of the 5 patients diagnosed with monogenic PAI developed the disease in adulthood, indicating late-onset monogenic disease associated with hypomorphic genetic variants. Conclusion: A PRS for AAD can help identify potential monogenic cases, regardless of the age at diagnosis. Early identification of the underlying cause of PAI enables accurate management and correct genetic counselling. Presentation: 6/2/2024

8039 Role Of Genetics In The Age-Related Testosterone Decline In Men: A UK Biobank Study

Abstract Disclosure: L. Ogoniak: None. S. Sandmann: None. J. Varghese: None. A.S. Busch: None. Background: Age-related decline in circulating serum testosterone concentrations is a well-established phenomenon in men. While the decline is partially linked to comorbidities such as obesity, type 2 diabetes (T2D), and cardiovascular disease (CVD), healthy ageing men present with rather stable levels. Recent genetic mapping studies demonstrated a large influence of common genetic variation on testosterone levels in men. However, increasing incidence rates of comorbidities in the ageing population are posing a challenge for the disentanglement of effects. Objective: Our study aims to investigate the genetic component of age-dependent testosterone decline in men. We hypothesize that the decline in testosterone levels in ageing men is primarily influenced by comorbidities, without significant alterations in the genetic architecture of testosterone levels. Material and Methods: We included 6,406 men with baseline and follow-up measurements of circulating serum concentrations of total testosterone (T), bioavailable testosterone (BAT) and sex hormone-binding globulin (SHBG) representing an independent sub-cohort of the UK Biobank study. We 1) assessed the association of baseline levels with the decline in sex steroids and 2) developed and verified polygenic risk score (PRS) models for T, BAT and SHBG based on 183,909 men from the UK Biobank (sub cohorts: 70% base, 15% target and 15% validation, follow-up cohort excluded for PRS development). Results: In the follow-up sub cohort, mean age (SD) at baseline was 58.2 yrs ( 7.5) and mean (SD) follow-up period was 4.3 (1.0) yrs. Mean (SD) BAT at baseline were 5.2 (1.32) nmol/L with a mean (SD) decline of 1.6 (24.4) % at follow-up. Baseline BAT, T and SHBG levels were significantly associated with the relative change of the respective biomarker at follow-up (-7.8, -2.9 and -0.4% per nmol/L, respectively, all p &amp;lt;0.001). After correcting for age at baseline, follow-up period and principal components 1-10, PGSTestosterone and PGSBAT were not associated with relative decline of the respective biomarker (both p = n.s.). Conclusion: Our study did not find evidence supporting a genetic component in the age-related decline of circulating serum T or BAT concentrations. Instead, in accordance to previous observational studies, our results suggest that rather non-genetic factors, e.g. increasing incidence rates of comorbidities, drive the age-related decline in sex steroid levels in men. Our study contributes to understanding the intricate relationship between genetic and non-genetic factors with age-related testosterone decline in men and offers valuable insights for potential interventions targeting age-related hormonal changes and associated health outcomes. Presentation: 6/2/2024

9240 Role Of Genetics In The Age-Related Testosterone Decline In Men: A UK Biobank Study

Abstract Disclosure: L. Ogoniak: None. S. Sandmann: None. J. Varghese: None. A.S. Busch: None. Background: Age-related decline in circulating serum testosterone concentrations is a well-established phenomenon in men. While the decline is partially linked to comorbidities such as obesity, type 2 diabetes (T2D), and cardiovascular disease (CVD), healthy ageing men present with rather stable levels. Recent genetic mapping studies demonstrated a large influence of common genetic variation on testosterone levels in men. However, increasing incidence rates of comorbidities in the ageing population are posing a challenge for the disentanglement of effects. Objective: Our study aims to investigate the genetic component of age-dependent testosterone decline in men. We hypothesize that the decline in testosterone levels in ageing men is primarily influenced by comorbidities, without significant alterations in the genetic architecture of testosterone levels. Material and Methods: We included 6,406 men with baseline and follow-up measurements of circulating serum concentrations of total testosterone (T), bioavailable testosterone (BAT) and sex hormone-binding globulin (SHBG) representing an independent sub-cohort of the UK Biobank study. We 1) assessed the association of baseline levels with the decline in sex steroids and 2) developed and verified polygenic risk score (PRS) models for T, BAT and SHBG based on 183,909 men from the UK Biobank (sub cohorts: 70% base, 15% target and 15% validation, follow-up cohort excluded for PRS development). Results: In the follow-up sub cohort, mean age (SD) at baseline was 58.2 yrs ( 7.5) and mean (SD) follow-up period was 4.3 (1.0) yrs. Mean (SD) BAT at baseline were 5.2 (1.32) nmol/L with a mean (SD) decline of 1.6 (24.4) % at follow-up. Baseline BAT, T and SHBG levels were significantly associated with the relative change of the respective biomarker at follow-up (-7.8, -2.9 and -0.4% per nmol/L, respectively, all p &amp;lt;0.001). After correcting for age at baseline, follow-up period and principal components 1-10, PGSTestosterone and PGSBAT were not associated with relative decline of the respective biomarker (both p = n.s.). Conclusion: Our study did not find evidence supporting a genetic component in the age-related decline of circulating serum T or BAT concentrations. Instead, in accordance to previous observational studies, our results suggest that rather non-genetic factors, e.g. increasing incidence rates of comorbidities, drive the age-related decline in sex steroid levels in men. Our study contributes to understanding the intricate relationship between genetic and non-genetic factors with age-related testosterone decline in men and offers valuable insights for potential interventions targeting age-related hormonal changes and associated health outcomes. Presentation: 6/2/2024

8039 Role Of Genetics In The Age-Related Testosterone Decline In Men: A UK Biobank Study

Abstract Disclosure: L. Ogoniak: None. S. Sandmann: None. J. Varghese: None. A.S. Busch: None. Background: Age-related decline in circulating serum testosterone concentrations is a well-established phenomenon in men. While the decline is partially linked to comorbidities such as obesity, type 2 diabetes (T2D), and cardiovascular disease (CVD), healthy ageing men present with rather stable levels. Recent genetic mapping studies demonstrated a large influence of common genetic variation on testosterone levels in men. However, increasing incidence rates of comorbidities in the ageing population are posing a challenge for the disentanglement of effects. Objective: Our study aims to investigate the genetic component of age-dependent testosterone decline in men. We hypothesize that the decline in testosterone levels in ageing men is primarily influenced by comorbidities, without significant alterations in the genetic architecture of testosterone levels. Material and Methods: We included 6,406 men with baseline and follow-up measurements of circulating serum concentrations of total testosterone (T), bioavailable testosterone (BAT) and sex hormone-binding globulin (SHBG) representing an independent sub-cohort of the UK Biobank study. We 1) assessed the association of baseline levels with the decline in sex steroids and 2) developed and verified polygenic risk score (PRS) models for T, BAT and SHBG based on 183,909 men from the UK Biobank (sub cohorts: 70% base, 15% target and 15% validation, follow-up cohort excluded for PRS development). Results: In the follow-up sub cohort, mean age (SD) at baseline was 58.2 yrs ( 7.5) and mean (SD) follow-up period was 4.3 (1.0) yrs. Mean (SD) BAT at baseline were 5.2 (1.32) nmol/L with a mean (SD) decline of 1.6 (24.4) % at follow-up. Baseline BAT, T and SHBG levels were significantly associated with the relative change of the respective biomarker at follow-up (-7.8, -2.9 and -0.4% per nmol/L, respectively, all p &amp;lt;0.001). After correcting for age at baseline, follow-up period and principal components 1-10, PGSTestosterone and PGSBAT were not associated with relative decline of the respective biomarker (both p = n.s.). Conclusion: Our study did not find evidence supporting a genetic component in the age-related decline of circulating serum T or BAT concentrations. Instead, in accordance to previous observational studies, our results suggest that rather non-genetic factors, e.g. increasing incidence rates of comorbidities, drive the age-related decline in sex steroid levels in men. Our study contributes to understanding the intricate relationship between genetic and non-genetic factors with age-related testosterone decline in men and offers valuable insights for potential interventions targeting age-related hormonal changes and associated health outcomes. Presentation: 6/2/2024

Multi-ancestry GWAS meta-analyses of lung cancer reveal susceptibility loci and elucidate smoking-independent genetic risk

Lung cancer remains the leading cause of cancer mortality, despite declining smoking rates. Previous lung cancer GWAS have identified numerous loci, but separating the genetic risks of lung cancer and smoking behavioral susceptibility remains challenging. Here, we perform multi-ancestry GWAS meta-analyses of lung cancer using the Million Veteran Program cohort (approximately 95% male cases) and a previous study of European-ancestry individuals, jointly comprising 42,102 cases and 181,270 controls, followed by replication in an independent cohort of 19,404 cases and 17,378 controls. We then carry out conditional meta-analyses on cigarettes per day and identify two novel, replicated loci, including the 19p13.11 pleiotropic cancer locus in squamous cell lung carcinoma. Overall, we report twelve novel risk loci for overall lung cancer, lung adenocarcinoma, and squamous cell lung carcinoma, nine of which are externally replicated. Finally, we perform PheWAS on polygenic risk scores for lung cancer, with and without conditioning on smoking. The unconditioned lung cancer polygenic risk score is associated with smoking status in controls, illustrating a reduced predictive utility in non-smokers. Additionally, our polygenic risk score demonstrates smoking-independent pleiotropy of lung cancer risk across neoplasms and metabolic traits.

Sex-specific association between schizophrenia polygenic risk and subclinical schizophrenia-related traits

BackgroundAccording to the dimensional view of psychiatric disorders, psychosis is expressed as a continuum in the general population. However, the investigation of the putative genetic aetiological continuity between its clinical and subclinical phenotypes has yielded mixed results. We aimed to replicate previous findings regarding the association of polygenic risk for schizophrenia with subclinical traits (i.e., schizotypy traits and psychotic-like experiences), and to examine the role of sex in this association in a large nonclinical sample. MethodsThe Multidimensional Schizotypy Scale and the Community Assessment of Psychic Experiences were assessed in 919 nonclinical participants. Polygenic Risk Scores for schizophrenia (SZ-PRSs) were computed using the PRS-CS method based on the latest genome-wide association study of schizophrenia. Summary statistics derived from the total GWAS sample and stratified by sex were used. Linear regression analyses tested the associations of the SZ-PRSs with the psychometric variables, both in the total sample and by sex. ResultsNo associations were found between the SZ-PRSs and the positive, negative or disorganized dimensions of schizotypy in the total sample. Likewise, no associations were found with psychotic-like experiences. However, the sex-stratified analyses revealed a male-specific association with positive schizotypy. Similar results were obtained with the PRSs derived from the sex-stratified summary statistics. DiscussionOur results are consistent with the lack of clear evidence of an association between SZ common genetic risk and its subclinical phenotypes. Nevertheless, the male-specific association found suggests that this PRS might explain better the male phenotype, as reported in previous studies. Future studies should put a focus on the role of sex in this association to unravel its sex specificities.

Age, anticoagulants, hypertension and cardiovascular genetic traits predict cranial ischaemic complications in patients with giant cell arteritis

ObjectivesThis project aimed to determine whether cranial ischaemic complications at the presentation of giant cell arteritis (GCA) were associated with pre-existing cardiovascular (CV) risk factors, CV disease or genetic risk...