Dietary eggs, egg nutrients, polygenic score for body mass index, "Western pattern" diet, and weight change, a prospective analysis in the Women's health initiative.

BACKGROUND & AIMS: Eggs contain nutrients which could help enrich the diets of postmenopausal women. Egg consumption and elevated body weight have been associated with elevated risk of serious chronic disease. It is possible that elevated body weight mediates between egg consumption and serious chronic disease. However, few studies exist on the link between egg consumption and body weight in post-menopausal women, and none of them accounted for genetic weight gain predispositions. Our objective was to examine associations between egg consumption, body weight, and genetic predisposition for an elevated Body Mass Index (BMI), in postmenopausal women. METHODS: We analyzed data from 4439 healthy Women's Health Initiative participants of European descent during a 6-year follow up using multivariable generalized linear mixed models to prospectively evaluate egg and egg-nutrient intake (measured by a food frequency questionnaire) against body weight and a BMI polygenic score (PGS-BMI) derived from GWAS meta-analysis effect-allele frequencies. RESULTS: We found a positive prospective association between change in egg intake and body weight during the 6-year follow up. For instance, at year 3, women whose intake had increased by 2.0 eggs/week had gained 0.70 kg (95%CI: 0.34, 1.07, p = 0.0002) more than women whose intake had decreased by 2.4 eggs/week, p-linear <0.0001. Cholesterol-intake and choline-intake, but not betaine-intake, showed similar significant associations. Exploratory analysis revealed that: 1) women only demonstrated these significant associations if they exhibited higher intakes of "Western-pattern" foods including processed and red meats, French fries, sweets and deserts, sugar-sweetened beverages, fried foods, and dietary fat, and dietary energy; and 2) there was a significant positive prospective association between PGS-BMI and body-weight change, but only in the top quintile of egg-intake change. CONCLUSIONS: We found significant positive prospective associations between weight change and changes in egg intake, cholesterol intake, and choline intake among healthy postmenopausal women of European ancestry in the Women's Health Initiative. Exploratory analyses revealed that: 1) these significant associations only obtained among women who ate large amounts of "Western-pattern" foods; and 2) women with a higher genetic susceptibility for an elevated BMI gained more weight only if they increased their egg intake considerably. Our results require confirmation.

The role of gene-environment interaction in the formation of risk attitudes.

Understanding the formation of risk preferences is crucial for elucidating the roots of economic, social, and health inequalities. However, this area remains inadequately explored. This study employs a risk preference measure directly linked to the labor market to examine whether previous experiences with high unemployment rates influence current risk decision-making among the elderly, and whether this impact varies by genotype. The findings indicate that individuals with low genetic predispositions for risk tolerance are more significantly influenced by historical fluctuations in unemployment rates than those with high genetic predispositions for risk tolerance. Consequently, this paper identifies genetic endowment as a crucial moderating factor that shapes how past experiences impact current decision-making processes. This disparity in how past experiences shape risk preferences based on genetic predisposition may further amplify inequalities in health, wealth, income, and other outcomes associated with risk preferences.

Cost-effectiveness of population-wide genomic screening for Lynch Syndrome and Polygenic Risk Scores to inform Colorectal Cancer screening.

INTRODUCTION: Genomic screening to identify individuals with Lynch Syndrome (LS) and those with a high polygenic risk score (PRS) promises to personalize Colorectal Cancer (CRC) screening. Understanding its clinical and economic impact is needed to inform screening guidelines and reimbursement policies. METHODS: We developed a Markov model to simulate individuals over a lifetime. We compared LS+PRS genomic screening to standard of care (SOC) for a cohort of US adults at age 30. The Markov model included health states of "no CRC", CRC stages (A-D) and death. We estimated incidence, mortality, and discounted economic outcomes of the population under different interventions. RESULTS: Screening 1000 individuals for LS+PRS resulted in 1.36 fewer CRC cases and 0.65 fewer deaths compared to SOC. The incremental cost-effectiveness ratio (ICER) was $124,415 per quality-adjusted life-year (QALY); screening had a 69% probability of being cost-effective using a willingness to pay threshold of $150,000/QALY. Setting the PRS threshold at the 90th percentile of the LS+PRS screening program to define individuals at high risk was most likely to be cost-effective compared to 95th, 85th, and 80th percentiles. CONCLUSION: Population-level LS+PRS screening is marginally cost-effective and a threshold of 90th percentile is more likely to be cost-effective than other thresholds.

History of Peripartum Depression Moderates the Association Between Estradiol Polygenic Risk Scores and Basal Ganglia Volumes in Major Depressive Disorder.

BACKGROUND: The neurobiological differences between women who have experienced a peripartum episode and those who have only had episodes outside of this period are not well understood. METHODS: 64 parous female patients with major depressive disorder that have either a positive (n=30) or negative (n=34) history of peripartum depression (PPD) underwent MRI acquisition to obtain structural brain images. An independent two-sample t-test comparing patients with and without a history of PPD was performed using voxel-based morphometry analysis (VBM). Additionally, polygenic risk scores (PRSs) for estradiol were calculated and a moderation analysis was conducted between 3 estradiol PRSs and PPD history status on extracted cluster volumes using IBM SPSS PROCESS macro. RESULTS: The VBM analysis identified larger grey matter volumes in bilateral clusters encompassing the putamen, pallidum, caudate, and thalamus in patients with PPD history compared to patients without a history. The moderation analysis identified a significant interaction of 2 estradiol PRSs and PPD history on grey matter cluster volumes with a positive effect in PPD women and a negative effect in women with no history of PPD. CONCLUSIONS: Our findings demonstrate that women who have experienced a peripartum episode are neurobiologically distinct from women who have no history of PPD in a cluster within the basal ganglia, an area important for motivation, decision-making, and emotional processing. Furthermore, we show that the genetic load for estradiol has a differing effect in this area based on PPD status which supports the claim that PPD is associated with sensitivity to sex steroid hormones.

Breeding for brown plant hopper resistance in rice: recent updates and future perspectives.

Rice yield is often threatened by various stresses caused by biotic and abiotic agents. Many biotic stress factors are known to cause crop growth and yield from seedling to maturity. The brown plant hopper (BPH) can potentially reduce the rice yield to an extent of up to 80%. Intensive research efforts in 1972 led to a better understanding of pathogens/insect and host-plant resistance. This resulted in the identification of about 70 BPH-resistant genes and quantitative trait loci (QTLs) from diversified sources including wild germplasm. However, the BPH-resistant improved varieties with a single resistant gene lose the effectiveness of the gene because of the evolution of new biotypes. This review inferred that the level of resistance durable when incorporating multiple 'R' gene combinations when compared to a single gene. Breeding tools like wide hybridization, biparental crosses, marker-assisted introgression, pyramiding, and genetic engineering have been widely employed to breed rice varieties with single or combination of 'R' genes conferring durable resistance to BPH. Many other genes like receptor-like kinase genes, transcriptional factors, etc., were also found to be involved in the resistant mechanisms of 'R' genes. Due to this, the durability of the resistance can be improved and the level of resistance of the 'R' genes can be increased by adopting newer breeding tools like genome editing which hold promise to develop rice varieties with stable resistance.

A genome-wide Association study of the Count of Codeine prescriptions.

Opioid prescription records in existing electronic health record (EHR) databases are a potentially useful, high-fidelity data source for opioid use-related risk phenotyping in genetic analyses. Prescriptions for codeine derived from EHR records were used as targeting traits by screening 16 million patient-level medication records. Genome-wide association analyses were then conducted to identify genomic loci and candidate genes associated with different count patterns of codeine prescriptions. Both low- and high-prescription counts were captured by developing 8 types of phenotypes with selected ranges of prescription numbers to reflect potentially different levels of opioid risk severity. We identified one significant locus associated with low-count codeine prescriptions (1, 2 or 3 prescriptions), while up to 7 loci were identified for higher counts (≥ 4, ≥ 5, ≥6, or ≥ 7 prescriptions), with a strong overlap across different thresholds. We identified 9 significant genomic loci with all-count phenotype. Further, using the polygenic risk approach, we identified a significant correlation (Tau = 0.67, p = 0.01) between an externally derived polygenic risk score for opioid use disorder and numbers of codeine prescriptions. As a proof-of-concept study, our research provides a novel and generalizable phenotyping pipeline for the genomic study of opioid-related risk traits.

Pancreatitis polygenic risk score is independently associated with all-cause acute pancreatitis risk in the UK Biobank.

BACKGROUND AND AIM: Acute pancreatitis (AP) is a complex disease most commonly caused by gallstones, alcohol intake, or hypertriglyceridemia. Even in subjects with hypertriglyceridemia, the risk of AP is heterogeneous. Identifying individuals with a high genetic susceptibility to AP could contribute to a better risk stratification in the clinic. This study aimed to determine if a weighted polygenic risk score (PRS) of common variants in pancreatitis susceptibility genes can independently predict all-cause AP incidence in the general population. METHODS: A weighted PRS was calculated for 484 932 individuals from the UK Biobank, including 3346 individuals who developed AP during follow-up. The PRS included eight single nucleotide polymorphisms in known pancreatitis susceptibility genes. RESULTS: Individuals with a pancreatitis PRS above the 90th percentile had a 1.21-fold (1.03-1.43; P = 0.02) increased risk of AP compared with those with a pancreatitis PRS below the 90th percentile. When comparing individuals in the third tertile versus the first tertile, the risk of AP was 1.13-fold (1.00-1.28; P = 0.06) higher. Individuals with both a high triglyceride (TG) level and a high pancreatitis PRS (third tertile) had a 2.31-fold (1.83-2.93; P = 3.4 × 10-12) increased risk of AP compared with those with a low pancreatitis PRS and a low TG level (first tertile). Overall, the association between pancreatitis PRS and incident AP was independent of baseline TG level. CONCLUSIONS: Results of this study suggest that the accumulation of common variants in pancreatitis susceptibility genes is associated with all-cause AP incidence. Pancreatitis PRS could help clinicians identify patients who may be at higher risk of AP and who may benefit from more aggressive treatment.

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

BACKGROUND AND AIMS: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

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.

Development and validation of a lung cancer polygenic risk score incorporating susceptibility variants for risk factors.

Incorporating susceptibility genetic variants of risk factors has been reported to enhance the risk prediction of polygenic risk score (PRS). However, it remains unclear whether this approach is effective for lung cancer. Hence, we aimed to construct a meta polygenic risk score (metaPRS) of lung cancer and assess its prediction of lung cancer risk and implication for risk stratification. Here, a total of 2180 genetic variants were used to develop nine PRSs for lung cancer, three PRSs for different histopathologic subtypes, and 17 PRSs for lung cancer-related risk factors, respectively. These PRSs were then integrated into a metaPRS for lung cancer using the elastic-net Cox regression model in the UK Biobank (N = 442,508). Furthermore, the predictive effects of the metaPRS were assessed in the prostate, lung, colorectal, and ovarian (PLCO) cancer screening trial (N = 108,665). The metaPRS was associated with lung cancer risk with a hazard ratio of 1.33 (95% confidence interval: 1.27-1.39) per standard deviation increased. The metaPRS showed the highest C-index (0.580) compared with the previous nine PRSs (C-index: 0.513-0.564) in PLCO. Besides, smokers in the intermediate risk group predicted by the clinical risk model (1.34%-1.51%) with the intermediate-high genetic risk had a 6-year average absolute lung cancer risk that exceeded the clinical risk model threshold (≥1.51%). The addition of metaPRS to the clinical risk model showed continuous net reclassification improvement (continuous NRI = 6.50%) in PLCO. These findings suggest the metaPRS can improve the predictive efficiency of lung cancer compared with the previous PRSs and refine risk stratification for lung cancer.

GWAS and polygenic risk score of severe COVID-19 in Eastern Europe.

Background: COVID-19 disease has infected more than 772 million people, leading to 7 million deaths. Although the severe course of COVID-19 can be prevented using appropriate treatments, effective interventions require a thorough research of the genetic factors involved in its pathogenesis. Methods: We conducted a genome-wide association study (GWAS) on 7,124 individuals (comprising 6,400 controls who had mild to moderate COVID-19 and 724 cases with severe COVID-19). The inclusion criteria were acute respiratory distress syndrome (ARDS), acute respiratory failure (ARF) requiring respiratory support, or CT scans indicative of severe COVID-19 infection without any competing diseases. We also developed a polygenic risk score (PRS) model to identify individuals at high risk. Results: We identified two genome-wide significant loci (P-value <5 × 10-8) and one locus with approximately genome-wide significance (P-value = 5.92 × 10-8-6.15 × 10-8). The most genome-wide significant variants were located in the leucine zipper transcription factor like 1 (LZTFL1) gene, which has been highlighted in several previous GWAS studies. Our PRS model results indicated that individuals in the top 10% group of the PRS had twice the risk of severe course of the disease compared to those at median risk [odds ratio = 2.18 (1.66, 2.86), P-value = 8.9 × 10-9]. Conclusion: We conducted one of the largest studies to date on the genetics of severe COVID-19 in an Eastern European cohort. Our results are consistent with previous research and will guide further epidemiologic studies on host genetics, as well as for the development of targeted treatments.

Brain structures with stronger genetic associations are not less associated with family- and state-level economic contexts.

We investigate whether neural, cognitive, and psychopathology phenotypes that are more strongly related to genetic differences are less strongly associated with family- and state-level economic contexts (N = 5374 individuals with 1KG-EUR-like genotypes with 870 twins, from the Adolescent Behavior and Cognitive Development study). We estimated the twin- and SNP-based heritability of each phenotype, as well as its association with an educational attainment polygenic index (EA PGI). We further examined associations with family socioeconomic status (SES) and tested whether SES-related differences were moderated by state cost of living and social safety net programs (Medicaid expansion and cash assistance). SES was broadly associated with cognition, psychopathology, brain volumes, and cortical surface areas, even after controlling for the EA PGI. Brain phenotypes that were more heritable or more strongly associated with the EA PGI were not, overall, less related to SES, nor were SES-related differences in these phenotypes less moderated by macroeconomic context and policy. Informing a long-running theoretical debate, and contra to widespread lay beliefs, results suggest that aspects of child brain development that are more strongly related to genetic differences are not, in general, less associated with socioeconomic contexts and policies.

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

BACKGROUND: According 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. METHODS: The 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. RESULTS: No 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. DISCUSSION: Our 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.

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.

Unraveling the shared genetics of common epilepsies and general cognitive ability.

PURPOSE: Cognitive impairment is prevalent among individuals with epilepsy, and increasing evidence indicates that genetic factors can underlie this relationship. However, the extent to which epilepsy subtypes differ in their genetic relationship with cognitive function, and information about the specific genetic variants involved remain largely unknown. METHODS: We investigated the genetic relationship between epilepsies and general cognitive ability (COG) using complementary statistical tools, including linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR). We analyzed genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), as well as specific subtypes. We functionally annotated the identified loci using several biological resources and validated the results in independent samples. RESULTS: Using MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for MiXeR analysis. We quantified extensive genetic overlap between COG and epilepsy types, but with varying negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 3.62 × 10-7; 'all epilepsy': p = 2.58 × 10-3). CONCLUSION: Our study further dissects the substantial genetic basis shared between epilepsies and COG and identifies novel shared loci. An improved understanding of the genetic relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

Association between polygenic risk scores combined with clinical characteristics and antidepressant efficacy.

BACKGROUND: While millions of people suffer from major depressive disorder (MDD), research has shown that individual differences in antidepressant efficacy exist, potentially attributable to various factors. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response are seldom reported. Here, we examined whether PRSs for MDD and schizophrenia (SCZ) are associated with antidepressant effectiveness and the influence of other factors. METHODS: A total of 999 patients were included, and the PRSs for the MDD and SCZ were calculated. The main outcome was a change in the 17-item Hamilton Depression Rating Scale (HAMD17) scores from before to after 2-week treatment. The Mann-Whitney test, Spearman correlation analysis, multiple stepwise linear regression analysis, and interaction analysis were used for statistical analysis. RESULTS: In the 912 subjects passing quality control, a difference in the HAM-D17 score reduction rate between the MDD phenotype PRS (MDD-PRS) high-risk and the low-risk groups was discovered (P = 0.009), and a correlation was found between the MDD-PRS and the HAM-D17 score reduction rate (r = -0.075, P = 0.024). Moreover, antidepressant efficacy was related to MDD-PRS (ß = -4.086, P = 0.039), the Snaith-Hamilton Pleasure Scale-total score (ß = -0.009, P = 0.005), and non-first episode (ß = -0.039, P < 0.001). However, the result of the interaction analysis was nonsignificant. LIMITATIONS: The main limitation was that only 1309 targeted genes were selected based on pathways known to be involved in MDD and/or antidepressant effects. CONCLUSION: These findings suggest a difference in antidepressant efficacy between patients in different MDD-PRS groups. Moreover, the MDD-PRS combined with clinical characteristics partially explained inter-individual differences in antidepressant efficacy.

Mediation of genetic susceptibility to obesity through eating behaviours in children.

BACKGROUND/OBJECTIVES: Few studies have examined the putative mediating role of eating behaviours linking genetic susceptibility and body weight. The goal of this study was to investigate the extent to which two polygenic scores (PGSs) for body mass index (BMI), based on child and adult data, predicted BMI through over-eating and fussy eating across childhood. SUBJECTS/METHODS: The study sample involved 692 participants from a birth cohort study. Height and weight were measured on six occasions between ages 6 and 13 years. Over-eating and fussy eating behaviours were assessed five times between ages 2 and 6 years. Longitudinal growth curve mediation analysis was used to estimate the contributions of the PGSs to BMI z-scores mediated by over-eating and fussy eating. RESULTS: Both PGSs predicted BMI z-scores (PGSchild: ß = 0.26, 95% CI: 0.19-0.33; PGSadult: ß = 0.34, 95% CI: 0.27-0.41). Over-eating significantly mediated these associations, but this mediation decreased over time from 6 years (PGSchild: 18.0%, 95% CI: 3.1-32.9, p-value = 0.018; PGSadult: 14.2%, 95% CI: 2.8-25.5, p-value = 0.014) to 13 years (PGSchild: 11.4%, 95% CI: -0.4-23.1, p-value = 0.057; PGSadult: 6.2%, 95% CI: 0.4-12.0, p-value = 0.037). Fussy eating did not show any mediation. CONCLUSIONS: Our results support the view that appetite is key to translating genetic susceptibility into changes in body weight.

The efficacy of different biomarkers and endpoints to refine referrals for suspected prostate cancer: the TARGET study (Tiered integrAted tests for eaRly diaGnosis of clinically significant ProstatE Tumours).

BACKGROUND: The majority of men referred with a raised PSA for suspected prostate cancer will receive unnecessary tertiary investigations including MRI and biopsy. Here, we compared different types of biomarkers to refine tertiary referrals and when different definitions of clinically significant cancer were used. METHODS: Data and samples from 798 men referred for a raised PSA (≥ 3 ng/mL) and investigated through an MRI-guided biopsy pathway were accessed for this study. Bloods were acquired pre-biopsy for liquid biomarkers and germline DNA. Variables explored included PSA + Age (base model), free/total PSA (FTPSA), Prostate Health Index (phi), PSA density (PSAd), polygenic risk score (PRS) and MRI (≥ LIKERT 3). Different diagnostic endpoints for significant cancer (≥ grade group 2 [GG2], ≥ GG3, ≥ Cambridge Prognostic Group 2 [CPG2], ≥ CPG3) were tested. The added value of each biomarker to the base model was evaluated using logistic regression models, AUC and decision curve analysis (DCA) plots. RESULTS: The median age and PSA was 65 years and 7.13 ng/mL respectively. Depending on definition of clinical significance, ≥ grade group 2 (GG2) was detected in 57.0% (455/798), ≥ GG3 in 27.5% (220/798), ≥ CPG2 in 61.6% (492/798) and ≥ CPG3 in 42.6% (340/798). In the pre-MRI context, the PSA + Age (base model) AUC for prediction of ≥ GG2, ≥ GG3, ≥ CPG2 and ≥ CPG3 was 0.66, 0.68, 0.70 and 0.75 respectively. Adding phi and PSAd to base model improved performance across all diagnostic endpoints but was notably better when the composite CPG prognostic score was used: AUC 0.82, 0.82, 0.83, 0.82 and AUC 0.74, 0.73, 0.79, 0.79 respectively. In contrast, neither FTPSA or PRS scores improved performance especially in detection of ≥ GG3 and ≥ CPG3 disease. Combining biomarkers did not alter results. Models using phi and PSAd post-MRI also improved performances but again benefit varied with diagnostic endpoint. In DCA analysis, models which incorporated PSAd and phi in particular were effective at reducing use of MRI and/or biopsies especially for ≥ CPG3 disease. CONCLUSION: Incorporating phi or PSAd can refine and tier who is referred for tertiary imaging and/or biopsy after a raised PSA test. Incremental value however varied depending on the definition of clinical significance and was particularly useful when composite prognostic endpoints are used.

Optimizing and benchmarking polygenic risk scores with GWAS summary statistics.

BACKGROUND: Polygenic 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. RESULTS: We 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. CONCLUSIONS: Our 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.

Leveraging large-scale datasets and single cell omics data to develop a polygenic score for cisplatin-induced ototoxicity.

BACKGROUND: Cisplatin-induced ototoxicity (CIO), characterized by irreversible and progressive bilateral hearing loss, is a prevalent adverse effect of cisplatin chemotherapy. Alongside clinical risk factors, genetic variants contribute to CIO and genome-wide association studies (GWAS) have highlighted the polygenicity of this adverse drug reaction. Polygenic scores (PGS), which integrate information from multiple genetic variants across the genome, offer a promising tool for the identification of individuals who are at higher risk for CIO. Integrating large-scale hearing loss GWAS data with single cell omics data holds potential to overcome limitations related to small sample sizes associated with CIO studies, enabling the creation of PGSs to predict CIO risk. RESULTS: We utilized a large-scale hearing loss GWAS and murine inner ear single nuclei RNA-sequencing (snRNA-seq) data to develop two polygenic scores: a hearing loss PGS (PGSHL) and a biologically informed PGS for CIO (PGSCIO). The PGSCIO included only variants which mapped to genes that were differentially expressed within cochlear cells that showed differential abundance in the murine snRNA-seq data post-cisplatin treatment. Evaluation of the association of these PGSs with CIO in our target CIO cohort revealed that PGSCIO demonstrated superior performance (P = 5.54 × 10- 5) relative to PGSHL (P = 2.93 × 10- 3). PGSCIO was also associated with CIO in our test cohort (P = 0.04), while the PGSHL did not show a significant association with CIO (P = 0.52). CONCLUSION: This study developed the first PGS for CIO using a large-scale hearing loss dataset and a biologically informed filter generated from cisplatin-treated murine inner ear snRNA-seq data. This innovative approach offers new avenues for developing PGSs for pharmacogenomic traits, which could contribute to the implementation of tailored therapeutic interventions. Further, our approach facilitated the identification of specific cochlear cells that may play critical roles in CIO. These novel insights will guide future research aimed at developing targeted therapeutic strategies to prevent CIO.