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Disease-causing variants in key immune homeostasis genes can lead to monogenic autoimmune diabetes. Some individuals carrying disease-causing variants do not develop autoimmune diabetes, even though they develop another autoimmune disease. We aimed to determine whether type 1 diabetes polygenic risk contributes to phenotypic presentation in monogenic autoimmune diabetes. We used a 67 single nucleotide polymorphism type 1 diabetes genetic risk score (T1D-GRS) to determine polygenic risk in 62 individuals with monogenic autoimmune diabetes and 180 control individuals with nonautoimmune neonatal diabetes (NDM). We used population-based control participants (n = 10,405) and individuals with type 1 diabetes (n = 285) as a comparator. Individuals with monogenic autoimmune diabetes had higher T1D-GRSs compared with individuals with nonautoimmune NDM (mean 11.3 vs. 9.8; P = 1.7 × 10−5) and controls (mean 10.3; P = 7.5 × 10−6), but the levels were markedly lower than those for individuals with type 1 diabetes (14.9; P = 3.3 × 10−21). These differences were explained by individuals with monogenic autoimmune diabetes having higher class II HLA genetic risk, specifically from the DRB1* 03:01 -DQA1 *05:01 -DQB1 *02:01 haplotype (DR3-DQ2) (P < 0.01). In the presence of monogenic autoimmunity, the polygenic class II HLA susceptibility contributes to development of autoimmune diabetes. This suggests a role of class II HLA in targeting the dysregulated immune response toward the β-cell. Article Highlights: There is variability in early-onset autoimmune diabetes presentation in individuals with monogenic autoimmunity; the mechanism(s) underlying this is unclear. We examined whether type 1 diabetes (T1D) polygenic risk contributes to clinical phenotype in monogenic autoimmune diabetes. Individuals with monogenic autoimmune diabetes had higher T1D genetic risk scores compared with control cohorts, driven largely by increased presence of T1D-risk DR3-DQ2 haplotype. Established T1D polygenic risk alleles, particularly class II HLA genes, contribute to clinical presentation in monogenic autoimmunity. [ABSTRACT FROM AUTHOR]

There is well-established evidence of reduced neurocognitive performance in adults and youth with bipolar disorder (BD). However, little is known about the polygenic underpinnings of neurocognition in individuals with BD, particularly in youth. The current study aimed to examine the association between polygenic risk score for BD (BD-PRS) and neurocognition among youth with BD and healthy controls (HC). 129 youth of European ancestry (72 BD, 57 HC), ages 13–20 years, were included. Six neurocognitive tasks within the Cambridge Neuropsychological Test Automated Battery were assessed. General linear models were used to examine the association between BD-PRS and neurocognitive composite scores, controlling for age, sex, IQ, and two genetic principal components. In the overall sample, higher BD-PRS was associated with significantly poorer affective processing (β = −0.25, p = 0.01), decision-making (β = −0.23, p = 0.02), and sustained attention (β = −0.28, p = 0.002). Secondary analyses revealed that higher BD-PRS was associated with significantly poorer sustained attention within the BD group (β = −0.27, p = 0.04), and with significantly poorer affective processing within the HC group (β = −0.29, p = 0.04). Cross-sectional design. Modest sample size may have reduced power to detect smaller effect sizes. The current study found that higher BD-PRS generated based on adult GWAS was associated with poorer neurocognitive performance in youth with BD and HC. Future longitudinal studies incorporating repeated neurocognitive assessments would further inform whether the associations of BD-PRS with neurocognition vary from youth to adulthood, and whether BD-PRS is associated with differential neurodevelopmental trajectories in individuals with and without BD. • Bipolar disorder is highly heritable and polygenic. • Higher bipolar disorder polygenic risk score was associated with poorer neurocognition in youth with and without BD. • Implicated neurocognitive domains included affective processing, decision-making, and sustained attention. [ABSTRACT FROM AUTHOR]

Key Points: Question: Is prediction of an individual's genetic risk for coronary heart disease (CHD) consistent across polygenic risk scores (PRSs) that perform equivalently at a population level? Findings: Forty-six scores with similar population-level performance produced discordant individual-level estimates of risk in the All of Us Research Program. Twenty percent of participants had PRSs in both the top and bottom 5th percentile at least once across the 46 nearly equivalent PRSs. Meaning: CHD PRSs with similar population-level performance characteristics may not provide consistent individual risk estimates. Personalized applications and clinical interpretations of CHD PRSs should consider the uncertainty of risk predictions at the individual level. Importance: Polygenic risk scores (PRSs) for coronary heart disease (CHD) are a growing clinical and commercial reality. Whether existing scores provide similar individual-level assessments of disease susceptibility remains incompletely characterized. Objective: To characterize the individual-level agreement of CHD PRSs that perform similarly at the population level. Design, Setting, and Participants: Cross-sectional study of participants from diverse backgrounds enrolled in the All of Us Research Program (AOU), Penn Medicine BioBank (PMBB), and University of California, Los Angeles (UCLA) ATLAS Precision Health Biobank with electronic health record and genotyping data. Exposures: Polygenic risk for CHD from published PRSs and new PRSs developed separately from testing samples. Main Outcomes and Measures: PRSs that performed population-level prediction similarly were identified by comparing calibration and discrimination of models of prevalent CHD. Individual-level agreement was tested with intraclass correlation coefficient (ICC) and Light κ. Results: A total of 48 PRSs were calculated for 171 095 AOU participants. The mean (SD) age was 56.4 (16.8) years. A total of 104 947 participants (61.3%) were female. A total of 35 590 participants (20.8%) were most genetically similar to an African reference population, 29 801 (17.4%) to an admixed American reference population, 100 493 (58.7%) to a European reference population, and the remaining to Central/South Asian, East Asian, and Middle Eastern reference populations. There were 17 589 participants (10.3%) with and 153 506 participants without (89.7%) CHD. When included in a model of prevalent CHD, 46 scores had practically equivalent Brier scores and area under the receiver operator curves (region of practical equivalence ±0.02). Twenty percent of participants had at least 1 score in both the top and bottom 5% of risk. Continuous agreement of individual predictions was poor (ICC, 0.373 [95% CI, 0.372-0.375]). Light κ, used to evaluate consistency of risk assignment, did not exceed 0.56. Analysis among 41 193 PMBB and 53 092 ATLAS participants yielded different sets of equivalent scores, which also lacked individual-level agreement. Conclusions and Relevance: CHD PRSs that performed similarly at the population level demonstrated highly variable individual-level estimates of risk. Recognizing that CHD PRSs may generate incongruent individual-level risk estimates, effective clinical implementation will require refined statistical methods to quantify uncertainty and new strategies to communicate this uncertainty to patients and clinicians. This study aims to characterize the individual-level agreement of polygenic risk scores for coronary heart disease that perform similarly at the population level. [ABSTRACT FROM AUTHOR]

Women carrying pathogenic/likely pathogenic (P/LP) variants in moderate- or high-penetrance genes have an increased risk of developing breast cancer. However, most P/LP variants associated with breast cancer risk show incomplete penetrance. Age, gender, family history, polygenic risk, lifestyle, reproductive, hormonal, and environmental factors can affect the expressivity and penetrance of the disease. However, there are gaps in translating how individual genomic variation affects phenotypic presentation. The expansion of criteria for genetic testing and the increasing utilization of comprehensive genetic panels may enhance the identification of individuals carrying P/LP variants linked to hereditary breast cancer. Individualized risk assessment could facilitate the implementation of personalized risk-reduction strategies for these individuals. Preventive interventions encompass lifestyle modifications, chemoprevention, enhanced surveillance through breast imaging, and risk-reducing surgeries. This review addresses the current literature's inconsistencies and limitations, particularly regarding risk factors and the intensity of preventive strategies for women with P/LP variants in moderate- and high-penetrance genes. In addition, it synthesizes the latest evidence on risk assessment and primary and secondary prevention in women at high risk of breast cancer. [ABSTRACT FROM AUTHOR]

Schizophrenia varies greatly from person to person, mainly because of its polygenic nature. Consequently, schizophrenia patients form distinct subphenotypes of schizophrenia, with specific symptom patterns and outcomes. This study included 4257 adults, with long-term schizophrenia (control - 8955 individuals) who were assessed for schizophrenia with potentially severe outcomes based on following criteria: disability in functional and/or physical domains before the age of 40; severe negative symptoms (present in infancy or shortly after onset); a continuous course of the disease. Additionally, the time of the onset and aggressive/antisocial tendencies were assessed as one the predictors of potentially severe outcomes. A total of 817 participants met at least three of these criteria, i.e., had disruptive schizophrenia. A genome-wide and transcriptome-wide association study was conducted using linear regression and the PrediXcan algorithm. The obtained data were used to develop a polygenic risk model for early risk prediction of schizophrenia with potentially severe outcomes. Significant associations were found between schizophrenia and variants in CAMTA1 , TRHDE , NELFE , and others. The PRS model demonstrated high performance in training, internal and external validation (ROC AUC of 0.9, 0.89, and 0.68, respectively). The functional pathway analysis highlighted pathways involved in ATP metabolism, myeloid cell differentiation, and apoptotic processes. Subphenotyping schizophrenia may enhance the discovery of genetic factors affecting its development and progression. The GWAS and TWAS findings revealed general mechanisms involved in the development of schizophrenia with potentially severe outcomes, such as synapse regulation, inflammation, and apoptosis. [Display omitted] • Narrow subphenotypes offer significant advantages for studying the genetic architecture of schizophrenia. • GWAS revealed new significant associations between schizophrenia and variants in CAMTA1 , TRHDE , NELFE. • PRS demonstrated high performance in training, internal and external validation for narrow subphenotype of schizophrenia. • The functional pathway analysis highlighted pathways involved in ATP metabolism, myeloid cell differentiationand apoptosis. • GWAS and TWAS findings revealed general mechanisms of schizophrenia development: synapse regulation, inflammation, apoptosis. [ABSTRACT FROM AUTHOR]

Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications. Polygenic scores model the combined risk of multiple variants across the genome to identify individuals at inherited risk of complex diseases. This Review discusses evolving methods for developing polygenic scores and describes examples across a spectrum of disease traits. Key points: A polygenic score is a numerical measure of inherited susceptibility conveyed by multiple genetic risk variants for a particular trait or disease and is computed by summing the effects of thousands (or millions) of risk alleles across the genome. Family history and polygenic risk contribute independently to susceptibility for most common complex traits and diseases. Additive effects of monogenic and polygenic risk have been demonstrated for breast and colorectal cancer, cardiovascular disease and chronic kidney disease. An integrative genomic risk predictor combines monogenic, polygenic, family history, environmental and clinical risk factors into a single risk prediction framework. The key limitation of existing polygenic scores is their partial cross-ancestry transferability or diminished predictive performance in various non-European populations currently underrepresented in genome-wide association studies. [ABSTRACT FROM AUTHOR]

Nasopharyngeal carcinoma (NPC) presents a substantial clinical challenge due to the limited understanding of its genetic underpinnings. Here we conduct the largest scale whole-exome sequencing association study of NPC to date, encompassing 6,969 NPC cases and 7,100 controls. We unveil 3 germline genetic variants linked to NPC susceptibility: a common rs2276868 in RPL14, a rare rs5361 in SELE, and a common rs1050462 in HLA-B. We also underscore the critical impact of rare genetic variants on NPC heritability and introduce a refined composite polygenic risk score (rcPRS), which outperforms existing models in predicting NPC risk. Importantly, we reveal that the polygenic risk for NPC is mediated by EBV infection status. Utilizing a comprehensive multiomics approach that integrates both bulk-transcriptomic (n = 356) and single-cell RNA sequencing (n = 56) data with experimental validations, we demonstrate that the RPL14 variant modulates the EBV life cycle and NPC pathogenesis. Furthermore, our data indicate that the SELE variant contributes to modifying endothelial cell function, thereby facilitating NPC progression. Collectively, our study provides crucial insights into the intricate genetic architecture of NPC, spotlighting the vital interplay between genetic variations and tumor microenvironment components, including EBV and endothelial cells, in predisposing to NPC. This study opens new avenues for advancements in personalized risk assessments, early diagnosis, and targeted therapies for NPC. [ABSTRACT FROM AUTHOR]

Introduction: Research has yet to examine the interplay between indices of environmental risk and resilience processes and genetic predisposition for epigenetic aging in predicting early adolescent depressive symptoms. In the current study we examine whether adverse life events and parental acceptance moderate polygenic predisposition for GrimAge epigenetic aging in predicting trajectories of depressive symptoms across early adolescence. Method: Using data from the Adolescent Brain Development Study (ABCD, N = 11,875), we created polygenic scores for GrimAge, and examined whether exposure to adverse life events and parental acceptance moderated the relation between genetic risk and depressive symptom trajectories from age 10/11 to 12/13 using growth mixture modelling. We examined models separately in European American (EA), African American (AA), and Latinx (LX) subgroups of ABCD. Results: In the EA and AA subgroups, adverse life events moderated polygenic scores for GrimAge such that there was increased likelihood of membership in a higher vs. lower depression trajectory. Discussion: We extend literature by identifying genetic contributions to epigenetic aging as a depression diathesis in adolescence. Findings also highlight the detrimental role of adverse life events in exacerbating genetic risk for the development of depression in adolescence. [ABSTRACT FROM AUTHOR]

Myelomeningocele (MMC) is the most severe and disabling form of spina bifida with chronic health multisystem complications and social and economic family and health systems burden. In the present study, we aimed to investigate the genetic risk estimate for MMC in a cohort of 203 Mexican nuclear families with discordant siblings for the defect. Utilizing a custom Illumina array, we analyzed 656 single nucleotide polymorphisms (SNPs) of 395 candidate genes to identify a polygenic risk profile for MMC. Through a family-based analysis employing the transmission disequilibrium test (TDT) and Bayesian analysis, we assessed risk alleles transmission and calculated conditional probabilities estimating a polygenic risk for MMC. Our findings reveal significant associations of six genes related to neural tube closure (PSMB4, ATIC, DKK2, PSEN2, C2CD3, and PLCB2), showing differences in risk allele transmission between affected and unaffected siblings. Bayesian analysis identified changes in the risk profile after initiating folic acid fortification in Mexico, showing an evident decline in the conditional risk from 1/156 to 1/304 respectively. Despite the decline, this represents a 5.84-fold increase in risk before fortification and a 2.99-fold increase post-fortification compared to the baseline risk level (1/910). Our study highlights the advantage of incorporating a Bayesian analytical methodology in families with discordant sib-pairs, offering insights into the polygenic risk estimate for MMC and, most probably, for other congenital malformations. [ABSTRACT FROM AUTHOR]

Glaucoma is the leading cause of irreversible blindness with early detection and intervention critical to slowing disease progression. However, half of those affected are undiagnosed. This is largely due to the early stages of disease being asymptomatic; current population-based screening measures being unsupported; and a lack of current efficient prediction models. Research investigating polygenic risk scores (PRS) for glaucoma have shown predictive ability to identify individuals at higher risk. Potential clinical applications include identification of high-risk individuals, resulting in earlier diagnosis and treatment to prevent glaucoma blindness, and adjusted monitoring for low-risk individuals. However, the psychological impact of receiving glaucoma PRS is unknown. There is a critical need to evaluate risk information communication and assess the impact of receiving results, to support clinical implementation of glaucoma PRS testing. In this prospective study, 300 individuals from the GRADE (Genetic Risk Assessment of Degenerative Eye disease) study will be recruited to investigate the psychosocial impact of disclosing polygenic risk results for glaucoma. GRADE aimed to apply PRS testing on 1,000 unexamined individuals aged 50 years or older from the general population and examine a subset of these individuals to assess the clinical validity of PRS to detect glaucoma. In this study, individuals each from the bottom decile (10%), top decile (10%), and middle (45–55%) of the PRS distributions will be invited to receive research glaucoma PRS results. Participants who choose to receive their results will complete up to four questionnaires (prior to receiving their results, and subsequently two-weeks, six- and 12-months after receiving their result). The questionnaires will include health belief model measures and assess glaucoma anxiety, general anxiety and depression, test-related distress, decisional regret, and recall and understanding of results. This research will provide guidance for the implementation of polygenic risk testing into clinical practice and inform delivery strategies. [ABSTRACT FROM AUTHOR]

Bovine spastic syndrome (SS) is a progressive, adult-onset neuromuscular disorder (NMD). SS is inherited but the mode of inheritance is unclear. The aim of this study was to characterize the phenotype and to identify a possible genetic cause of SS by whole-genome sequencing (WGS) and focusing on protein-changing variants. Seven affected unrelated Holstein cattle of both sexes were referred for SS at a mean age of 5.3 years (S.D.±1.1) showing intermittent spasm of the skeletal muscles of the pelvic girdle. Assuming monogenic recessive inheritance, analysis of the WGS data did not reveal any private variants common to all cases. Searching for homozygous rare variants considering each case individually, allowed the identification of a rare recessive likely pathogenic missense variant in TOR3A for one case with an allele frequency of 1.69% in a global Holstein population. In the remaining six SS cases, we identified seven potentially dominant de novo mutations or inherited alleles as private heterozygous, mostly missense, variants of uncertain significance involving seven different NMD candidate genes: MPEG1, LHX8, WHAMM, NGRN, TTN, ATP1A1, PCDH1. All eight candidate causal variants identified were predicted to be deleterious. This study describes for the first time WGS findings in confirmed cases of bovine SS and provides evidence for a heterogeneous genetic cause of SS in cattle. [ABSTRACT FROM AUTHOR]

We assessed the association of prescription data with clinical manifestations and polygenic risk scores (PRS) in patients with bipolar I disorder. We enrolled 1471 individuals with BID and divided them into several groups according to treatment options and clinical manifestations. BD-PRS of each patient was calculated using the Psychiatric Genomics Consortium data. Data on single nucleotide polymorphisms, clinical manifestations, and prescriptions were extracted from BiGS. Chronicity, suicidality, substance misuse, mixed symptoms, and deterioration of life functioning were significantly more severe in the group that was not prescribed any mood stabilizers (MS). Chronicity, psychotic symptoms, suicidality, and deterioration of life functioning were significantly severe in the group that received two or more antipsychotics (APs). BD-PRS between the group with AP(s) only and that with other treatment options significantly differed. BD-PRS of the group with AP(s) only was significantly lower than that with other treatment options. Our linear regression results showed that high severity of particular clinical aspects, lower BD-PRS, and prescriptions with fewer MSs or more APs were independently associated with poor life functioning. This study had a cross-sectional design, without differentiating the bipolar phase, which could influence our results. Poor life functioning in patients with BID was associated with a high severity of particular clinical aspects, BD-PRS, and prescriptions including fewer MSs or more APs. BD-PRS was significantly higher in the group receiving only AP(s) than that in the groups receiving other drugs. • Particular clinical aspects were significantly more severe in the group that was not prescribed any mood stabilizers (MS). • Particular clinical aspects were significantly severe in the group that received two or more antipsychotics (APs). • Poor life functioning was associated with a high severity of particular clinical aspects, BD-PRS, and some prescriptions. • BD-PRS was higher in the group receiving only AP(s) than that in the groups receiving other drugs. [ABSTRACT FROM AUTHOR]

By improving disease risk prediction, polygenic risk scores (PRSs) could have a significant impact on health promotion and disease prevention. Due to the historical oversampling of populations with European ancestry for genome-wide association studies, PRSs perform less well in other, understudied populations, leading to concerns that clinical use in their current forms could widen health care disparities. The PRIMED Consortium was established to develop methods to improve the performance of PRSs in global populations and individuals of diverse genetic ancestry. To this end, PRIMED is aggregating and harmonizing multiple phenotype and genotype datasets on AnVIL, an interoperable secure cloud-based platform, to perform individual- and summary-level analyses using population and statistical genetics approaches. Study sites, the coordinating center, and representatives from the NIH work alongside other NHGRI and global consortia to achieve these goals. PRIMED is also evaluating ethical and social implications of PRS implementation and investigating the joint modeling of social determinants of health and PRS in computing disease risk. The phenotypes of interest are primarily cardiometabolic diseases and cancer, the leading causes of death and disability worldwide. Early deliverables of the consortium include methods for data sharing on AnVIL, development of a common data model to harmonize phenotype and genotype data from cohort studies as well as electronic health records, adaptation of recent guidelines for population descriptors to global cohorts, and sharing of PRS methods/tools. As a multisite collaboration, PRIMED aims to foster equity in the development and use of polygenic risk assessment. [Display omitted] To lessen health and healthcare disparities and extend advances in genomic medicine to all, the PRIMED Consortiumis bringing together investigators and datasets from across the globe to develop PRS methods and improve their performance across diverse populations. We present Consortium objectives and design, ongoing activities, and initial products. [ABSTRACT FROM AUTHOR]

Background: Effective clinical implementation of polygenic risk testing for glaucoma relies on healthcare professionals' attitudes and knowledge of the test. Given the emerging applications of the test, it will likely impact a range of healthcare professionals and will require competency in polygenic risk scores concepts for all those involved in patient care. To our knowledge, this is the first study to assess healthcare professionals' views towards polygenic testing for glaucoma. Methods: An online cross‐sectional questionnaire was distributed to healthcare professionals via relevant professional organisations in Australia. The questionnaire assessed experience and confidence with genetic testing, glaucoma and genetic knowledge, recommendations for the tests, and factors affecting the decision. Results: A total of 94 participants completed the questionnaire. The sample was composed of ophthalmologists (36%), optometrists (21%), orthoptists (17%), general practitioners (16%) and clinical geneticists/genetic counsellors (10%). Although familiarity with polygenic risk scores for glaucoma was low overall (11%), the majority reported a positive attitude towards recommending testing based on known risk factors such as family history (91%) and older age (57%). Over 95% indicated that ophthalmologists would be the most appropriate group to order polygenic risk testing and communicate results. The majority felt they would benefit from more training on polygenic risk scores (93%). Conclusions: Our findings indicated that multiple groups of healthcare professionals were neither familiar nor confident with the concept of glaucoma polygenic risk testing, and identified training and education needs to support the implementation of testing into clinical practice. [ABSTRACT FROM AUTHOR]

Background: Neurodevelopmental disorders (NDDs) affect approximately 15% of children and adolescents worldwide. This group of disorders is often polygenic with varying risk factors, with many associated genes converging on shared molecular pathways, including chromatin regulation and transcriptional control. Understanding how NDD-associated chromatin regulators and protein complexes orchestrate these regulatory pathways is crucial for elucidating NDD pathogenesis and developing targeted therapeutic strategies. Recently, the TCF20/PHF14 chromatin complex was identified in the mammalian brain, expanding the list of chromatin regulatory remodelers implicated in NDDs. This complex—which includes MeCP2, RAI1, TCF20, PHF14, and HMG20A—plays a vital role in epigenetic and transcriptional regulation. Methods: We review and summarize current research and clinical reports pertaining to the different components of the MeCP2-interacting TCF20/PHF14 complex. We examine the NDDs associated with the TCF20/PHF14 complex, explore the molecular and neuronal functions of its components, and discuss emerging therapeutic strategies targeting this complex to mitigate symptoms, with broader applicability to other NDDs. Results: Mutations in the genes encoding the components of the MeCP2-interacting TCF20/PHF14 complex have been linked to various NDDs, underscoring its critical contribution to brain development and NDD pathogenesis. Conclusions: The MeCP2-interacting TCF20/PHF14 complex and its associated NDDs could serve as a model system to provide insight into the interplay between epigenetic regulation and NDD pathogenesis. [ABSTRACT FROM AUTHOR]

To compare aneuploidy rates among in vitro fertilization (IVF) cycles using preimplantation genetic testing for monogenic disorders (PGT-M) and aneuploidy (PGT-A) compared with IVF cycles using PGT-A alone, and to determine the likelihood of obtaining at least one usable embryo in cycles using PGT-M+PGT-A compared with cycles using PGT-A alone. Retrospective cohort study. Single genetics laboratory. All IVF cycles for patients aged 18–45 undergoing PGT-A with or without concurrent PGT-M at a single genetics laboratory from November 2019 to March 2023. Use of PGT-M+PGT-A vs. use of PGT-A alone. Per cycle aneuploidy rate stratified by age, and per cycle likelihood of obtaining at least one usable embryo stratified by age and inheritance pattern of monogenic disease. A total of 72,522 IVF cycles were included; 4,255 cycles (5.9%) using PGT-M+PGT-A and 68,267 cycles (94.1%) using PGT-A alone. The PGT-M+PGT-A group was younger than the PGT-A alone group (<35 years old: 56.1% vs. 30.5%). The majority of PGT-M cycles were performed for autosomal dominant pathogenic variants (42.4%), followed by autosomal recessive (36.5%), X-linked dominant (13.3%), and X-linked recessive (7.5%). The median number of embryos biopsied was higher in PGT-A alone compared with PGT-M+PGT-A cycles for patients aged <35, but it was equivalent in all other age groups. Age stratified aneuploidy rates did not significantly differ between PGT-M+PGT-A compared with PGT-A alone cycles. The probability of having a usable embryo declined with increasing age across all inheritance patterns. Compared with PGT-A alone, PGT-M+PGT-A cycles for patients aged ≤40 across all inheritance patterns were significantly less likely to yield a usable embryo, except in cycles for autosomal recessive diseases in the 38–40 age group and X-linked recessive diseases in the 35–37 age group. There were no consistent differences seen between groups in patients over 40. Cycles for patients with autosomal dominant diseases had the lowest likelihood of yielding a usable embryo for patients aged <43. In vitro fertilization cycles using PGT-M+PGT-A have similar age-specific aneuploidy rates to those using PGT-A alone. Cycles for patients ≤40 using PGT-M+PGT-A are significantly less likely to yield a usable embryo compared with those using PGT-A alone. [ABSTRACT FROM AUTHOR]

Two cultivars of okra were selected based on different pod colours to investigate the inheritance of pigmentation in pods. Direct crosses were made among green and red cultivars of okra to generate the F1's in the 2021 Kharif season. In Kharif 2022, the F1's were planted to generate the F2 generation and backcrosses (B1 and B2) were attempted. The parents, F1, F2, B1 and B2 generations were evaluated on the field in summer 2022 farming season at Experimental Farm, Department of Vegetable Science, Dr Yashwant Singh Parmar University of Horticulture and Forestry, Nauni, Solan, Himachal Pradesh, India using randomized complete block design, with three replications. The Chi-square Test of goodness assessed the phenotypic segregation pattern to fit. F1 pods were always equal to the phenotype of the male parent. F2 populations resulted in a 3:1 ratio producing red and green pods indicating dominant or single gene control for this trait. This study also revealed a monogenic/monohybrid pattern for the inheritance of pod pigmentation with the pigmented parent dominant over the non-pigmented parent. The genotype of the male parent influenced all the populations. The paternal effect resulted from the transfer of gene products from paternal to offspring, with evidence of the effect of a single gene with a dominant allele for the red phenotype. [ABSTRACT FROM AUTHOR]

Genome-wide studies are yielding a growing catalog of common and rare variants that confer risk for psychopathology. However, despite representing unprecedented progress, emerging data also indicate that the full promise of psychiatric genetics—including understanding pathophysiology and improving personalized care—will not be fully realized by targeting traditional dichotomous diagnostic categories. The current article provides reflections on themes that emerged from a 2021 National Institute of Mental Health–sponsored conference convened to address strategies for the evolving field of psychiatric genetics. As anticipated by the National Institute of Mental Health's Research Domain Criteria framework, multilevel investigations of dimensional and transdiagnostic phenotypes, particularly when integrated with biobanks and big data, will be critical to advancing knowledge. The path forward will also require more diverse representation in source studies. Additionally, progress will be catalyzed by a range of converging approaches, including capitalizing on computational methods, pursuing biological insights, working within a developmental framework, and engaging health care systems and patient communities. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Optical coherence tomography and electroretinography studies have revealed structural and functional retinal alterations in individuals with schizophrenia spectrum disorders (SSDs). However, it remains unclear which specific retinal layers are affected; how the retina, brain, and clinical symptomatology are connected; and how alterations of the visual system are related to genetic disease risk. Optical coherence tomography, electroretinography, and brain magnetic resonance imaging were applied to comprehensively investigate the visual system in a cohort of 103 patients with SSDs and 130 healthy control individuals. The sparse partial least squares algorithm was used to identify multivariate associations between clinical disease phenotype and biological alterations of the visual system. The association of the revealed patterns with individual polygenic disease risk for schizophrenia was explored in a post hoc analysis. In addition, covariate-adjusted case-control comparisons were performed for each individual optical coherence tomography and electroretinography parameter. The sparse partial least squares analysis yielded a phenotype-eye-brain signature of SSDs in which greater disease severity, longer duration of illness, and impaired cognition were associated with electrophysiological alterations and microstructural thinning of most retinal layers. Higher individual loading onto this disease-relevant signature of the visual system was significantly associated with elevated polygenic risk for schizophrenia. In case-control comparisons, patients with SSDs had lower macular thickness, thinner retinal nerve fiber and inner plexiform layers, less negative a-wave amplitude, and lower b-wave amplitude. This study demonstrates multimodal microstructural and electrophysiological retinal alterations in individuals with SSDs that are associated with disease severity and individual polygenic burden. [ABSTRACT FROM AUTHOR]

Vitiligo is a common autoimmune disease characterized by patches of depigmented skin and overlying hair due to destruction of melanocytes in the involved regions. We investigated the relationship between vitiligo risk and vitiligo age of onset (AOO) using a vitiligo polygenic risk score that incorporated the most significant SNPs from genome-wide association studies. We find that vitiligo genetic risk and AOO are strongly inversely correlated; subjects with higher common-variant polygenic risk tend to develop vitiligo at an earlier age. Nevertheless, the correlation is not simple. In individuals who carry a single high-risk major histocompatibility complex class II haplotype, the effect of additional polygenic risk on vitiligo AOO is reduced. Particularly among those with early-AOO vitiligo (onset ≤ 12 years of age), genetic risk can reflect contributions from high common-variant burden but also rare variants of high effect and sometimes both. While the heritability of vitiligo is relatively high, and we here show that genetic risk factors predict vitiligo AOO, vitiligo is never congenital, and thus environmental triggers also play an important role in disease onset. People with a higher burden of common genetic risk variants tend to experience earlier onset of autoimmune vitiligo, revealing a genetic link to disease timing. These insights may enhance our understanding of other polygenic diseases where genetic risk might also influence the timing of symptom onset. [ABSTRACT FROM AUTHOR]

Inherited retinal diseases (IRDs) are a clinically and genetically diverse group of progressive degenerative disorders that can result in severe visual impairment or complete blindness. Despite their predominantly monogenic inheritance patterns, the genetic complexity of over 300 identified disease-causing genes presents a significant challenge in correlating clinical phenotypes with genotypes. Achieving a molecular diagnosis is crucial for providing patients with definitive diagnostic clarity and facilitating access to emerging gene-based therapies and ongoing clinical trials. Recent advances in next-generation sequencing technologies have markedly enhanced our ability to identify genes and genetic defects leading to IRDs, thereby propelling the development of gene-based therapies. The clinical success of voretigene neparvovec (Luxturna), the first approved retinal gene therapy for RPE65-associated Leber congenital amaurosis (LCA), has spurred considerable research and development in gene-based therapies, highlighting the importance of reviewing the current status of gene therapy for IRDs, particularly those utilizing adeno-associated virus (AAV)-based therapies. As novel disease-causing mutations continue to be discovered and more targeted gene therapies are developed, integrating these treatment opportunities into the standard care for IRD patients becomes increasingly critical. This review provides an update on the diverse phenotypic–genotypic landscape of IRDs, with a specific focus on recent advances in the understanding of IRDs in children with infantile nystagmus syndrome (INS). We highlight the complexities of the genotypic–phenotypic landscape of INS-associated IRDs, including conditions such as achromatopsia, LCA, congenital stationary night blindness, and subtypes of retinitis pigmentosa. Additionally, we provide an updated overview of AAV-based gene therapies for these diseases and discuss the potential of gene-based therapies for underlying IRDs that lead to INS, offering a valuable resource for pediatric patients potentially eligible for ongoing clinical trials. [ABSTRACT FROM AUTHOR]

Background Methods Results Conclusions Symptoms related to mood and anxiety disorders (emotional disorders) often present in childhood and adolescence. Some of the genetic liability for mental disorders, and emotional and behavioral difficulties seems to be shared. Yet, it is unclear how genetic liability for emotional disorders and related traits influence trajectories of childhood behavioral and emotional difficulties, and if specific developmental patterns are associated with higher genetic liability for these disorders.This study uses data from a genotyped sample of children (n = 54,839) from the Norwegian Mother, Father, and Child Cohort Study (MoBa). We use latent growth models (1.5–5 years) and latent profile analyses (1.5–8 years) to quantify childhood trajectories and profiles of emotional and behavioral difficulties and diagnoses. We examine associations between these trajectories and profiles with polygenic scores for bipolar disorder (PGSBD), anxiety (PGSANX), depression (PGSDEP), and neuroticism (PGSNEUR).Associations between PGSDEP, PGSANX, and PGSNEUR, and emotional and behavioral difficulties in childhood were more persistent than age‐specific across early childhood (1.5–5 years). Higher PGSANX and PGSDEP were associated with steeper increases in behavioral difficulties across early childhood. Latent profile analyses identified five profiles with different associations with emotional disorder diagnosis. All PGS were associated with the probability of classification into profiles characterized by some form of difficulties (vs. a normative reference profile), but only PGSBD was uniquely associated with a single developmental profile.Genetic risk for mood disorders and related traits contribute to both a higher baseline level of, and a more rapid increase in, emotional and behavioral difficulties across early and middle childhood, with some indications for disorder‐specific profiles. Our findings may inform research on developmental pathways to emotional disorders and the improvement of initiatives for early identification and targeted intervention. [ABSTRACT FROM AUTHOR]

Given the great interest in identifying reliable predictors of the response to antidepressant drugs, the present study investigated whether polygenic scores (PGS) for Major Depressive Disorder (MDD) and antidepressant treatment response (ADR) were related to the complex trait of antidepressant response in the Early Medication Change (EMC) cohort. In this secondary analysis of the EMC trial (N = 889), 481 MDD patients were included and compared to controls from a population-based cohort. Patients were treated over eight weeks within a pre-defined treatment-algorithm. We investigated patients' genetic variation associated with MDD and ADR, using PGS and examined the association of PGS with treatment outcomes (early improvement, response, remission). Additionally, the influence of two cytochrome P450 drug-metabolizing enzymes (CYP2C19, CYP2D6) was determined. PGS for MDD was significantly associated with disorder status (NkR2 = 2.48 %, p < 1*10−12), with higher genetic burden in EMC patients compared to controls. The PGS for ADR did not explain remission status. The PGS for MDD and ADR were also not associated with treatment outcomes. In addition, there were no effects of common CYP450 gene variants on ADR. The study was limited by variability in the outcome parameters due to differences in treatment and insufficient sample size in the used ADR genome-wide association study (GWAS). The present study confirms a polygenic contribution to MDD burden in the EMC patients. Larger GWAS with homogeneity in antidepressant treatments are needed to explore the genetic variation associated with ADR and realize the potential of PGS to contribute to specific response subtypes. • Polygenic risk for MDD was higher in EMC patients than in population-based controls. • Depressive episodes might be linked with higher genetic burden for the disorder. • No significant association between ADR-PGS and treatment response could be found. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Polygenic risk score (PRS) and rare monogenic variant screening are valuable tools for predicting cancer risk and identifying individuals at high risk. Integrating both common and rare genetic variants is crucial for accurate risk assessment. However, estimating the impacts of rare variants on cancer and combining them with PRS remains challenging. Here, we analyze 454,711 exome sequencing and 487,409 array UK Biobank samples, focusing on breast and prostate cancers. We introduce an expanded PRS (EPRS) approach, yielding a systematic model for more effective risk stratification. By prioritizing and clustering genes with cancer-specific rare variants based on odds ratios and population-attributable fraction, we refine risk stratification by combining both monogenic and polygenic effects. Individuals in high-PRS groups with rare high-impact gene variants show up to 15- and 22-fold higher risk for breast and prostate cancers, respectively, compared to those in the intermediate-PRS groups without rare variants. Combined risk profiles vary across distinct rare variant clusters within the same PRS group for both cancers. Our EPRS approach enhances risk stratification for breast and prostate cancers, offering important insights for future research and potential applications to other cancer types. An expanded PRS (EPRS) approach combining polygenic risk scores and rare variant clustering enhances cancer risk stratification for breast and prostate cancers. High-PRS groups with rare high-impact gene variants have up to 15- and 22-fold higher risk for breast and prostate cancers, respectively, compared to intermediate-PRS groups without rare variants. [ABSTRACT FROM AUTHOR]

Cognitive decline is a public health concern affecting about 50 million individuals worldwide. Neuroticism, defined as the trait disposition to experience intense and frequent negative emotions, has been associated with an increased risk of late-life cognitive decline. However, the underlying biological mechanisms of this association remain unknown. This study investigated the relationship between genetic predisposition to neuroticism, computed by polygenic risk score (PRS), and performance in cognitive domains of reasoning, processing speed, visual attention, and memory in individuals over age 60. The sample consisted of UK Biobank participants with genetic and cognitive data available (N = 10,737, 4686 females; mean age = 63.4 ± 2.71). The cognitive domains were assessed at baseline for all participants and seven years later for a subset (N = 645, 262 females; mean age = 62.9 ± 2.44). Neuroticism PRS was not associated cross-sectionally with cognitive measures (p > 0.05). However, the trajectory of change for processing speed (β = 0.020; 95% CI = [0.006, 0.035], adjusted p = 0.0148), visual attention (β = −0.077; 95% CI = [−0.0985, −0.0553], adjusted p = 1.412 × 10−11), and memory (β = −0.033; 95% CI = [−0.0535, −0.0131], adjusted p = 0.005) was significantly associated with neuroticism PRS. Specifically, a higher genetic predisposition to neuroticism was associated with less decline in these cognitive domains. This trend persisted after sensitivity analysis using complete cases, although it only remained nominally significant for visual attention. [ABSTRACT FROM AUTHOR]

ABSTRACT In maize, sex is determined by the formation of staminate and pistillate florets from an initially bisexual floral meristem through action of Silkless1 (Sk1), Tasselseed1 (Ts1) and Tasselseed2 (Ts2) genes. In this study, separate temperate donors having mutant sk1 (EC904829 and EC904831), ts1 (EC904827) and ts2 (EC904824) genes were crossed with sub‐tropical inbreds (HKI323 and HKI1105) to investigate the genetics and interaction of silkless and tasselseed traits. The monogenic and nuclear inheritance of sk1, ts1 and ts2 genes was established in a standard Mendelian principles in both monohybrid and dihybrid crosses irrespective of genetic background. About 444 F2 progenies across digenic population ‐A, ‐B and ‐C segregated as 239 normal: 109 silkless: 96 tasselseed, and 377 progenies of digenic populations ‐D, ‐E and ‐F segregated with 214 normal: 79 silkless: 84 tasselseed plants revealing recessive epistatic interaction (9:3:4) of sk1 with two ts mutations (ts1 and ts2). No progeny with both silkless and tasselseed phenotype was observed. The double mutants (sk1sk1/ts1ts1 and sk1sk1/ts2ts2) were identified through progeny testing. Our study emphasize the untapped potential of these mutants, providing a renewed focus for maize breeders worldwide. [ABSTRACT FROM AUTHOR]

Background and objectives: Amyotrophic lateral sclerosis (ALS) causes profound impairments in neurological function, and a cure for this devastating disease remains elusive. This study aimed to identify pre-disposing genetic, phenotypic, and exposure-related factors for amyotrophic lateral sclerosis using multi-modal data and assess their joint predictive potential. Methods: Utilizing data from the UK (United Kingdom) Biobank, we analyzed an unrelated set of 292 ALS cases and 408,831 controls of European descent. Two polygenic risk scores (PRS) are constructed: "GWAS Hits PRS" and "PRS-CS," reflecting oligogenic and polygenic ALS risk profiles, respectively. Time-restricted phenome-wide association studies (PheWAS) were performed to identify pre-existing conditions increasing ALS risk, integrated into phenotypic risk scores (PheRS). A poly-exposure score ("PXS") captures the influence of environmental exposures measured through survey questionnaires. We evaluate the performance of these scores for predicting ALS incidence and stratifying risk, adjusting for baseline demographic covariates. Results: Both PRSs modestly predicted ALS diagnosis but with increased predictive power when combined (covariate-adjusted receiver operating characteristic [AAUC] = 0.584 [0.525, 0.639]). PheRS incorporated diagnoses 1 year before ALS onset (PheRS1) modestly discriminated cases from controls (AAUC = 0.515 [0.472, 0.564]). The "PXS" did not significantly predict ALS. However, a model incorporating PRSs and PheRS1 improved the prediction of ALS (AAUC = 0.604 [0.547, 0.667]), outperforming a model combining all risk scores. This combined risk score identified the top 10% of risk score distribution with a fourfold higher ALS risk (95% CI [2.04, 7.73]) versus those in the 40%–60% range. Discussion: By leveraging UK Biobank data, our study uncovers pre-disposing ALS factors, highlighting the improved effectiveness of multi-factorial prediction models to identify individuals at highest risk for ALS. [ABSTRACT FROM AUTHOR]

Psoriasis is a chronic, immune-mediated inflammatory skin disease associated with a polygenic mode of inheritance. There are few studies that explore the association of a psoriasis Polygenic Risk Score (PRS) with patient clinical characteristics, and to our knowledge there are no studies examining psoriasis PRS associations across different ethnicities. In this study, we used a multi-racial psoriasis cohort to investigate PRS associations with clinical phenotypes including age of onset, psoriatic arthritis, other comorbidities, psoriasis body location, psoriasis subtype, environmental triggers, and response to therapies. We collected patient data and Affymetrix genome-wide SNP data from a cohort of 607 psoriasis patients and calculated an 88-loci PRS (PRS-ALL), also partitioned between genetic loci within the HLA region (PRS-HLA; 11 SNPS) and loci outside the HLA region (PRS-NoHLA; 77 SNPS). We used t-test and logistic regression to analyze the association of PRS with clinical phenotypes. We found that PRS-HLA and PRS-noHLA had differing effects on psoriasis age of onset, psoriatic arthritis, psoriasis located on the ears, genitals, nails, soles of feet, skin folds, and palms, skin injury as an environmental trigger, cardiovascular comorbidities, and response to phototherapy. In some cases these PRS associations were ethnicity specific. Overall, these results show that the genetic basis for clinical manifestations of psoriasis are driven by distinct HLA and non-HLA effects, and that these PRS associations can be dependent on ethnicity. [ABSTRACT FROM AUTHOR]

Background: Oral squamous cell carcinoma (OSCC) is a prevalent and aggressive oral cancer with a poor prognosis. Its polygenic risk is likely influenced by complex transcriptional disorders involving networks of co-expressed and functionally related genes, though such investigations are limited in OSCC. Methods: We analyzed the GSE37991 dataset, comprising 40 OSCC and 40 normal oral tissue samples from the Gene Expression Omnibus. Tumor-specific modules were identified using weighted correlation network analysis (WGCNA), leading to the selection of hub mRNAs and lncRNAs. These lncRNAs were used to construct lncRNA–mRNA and competing endogenous RNA networks. We further examined the expression profiles and survival data of these genes from the Cancer Genome Atlas. Prognostic markers were identified and validated through 5-year survival analysis and Cox proportional hazards modeling. RT-qPCR was used to validate the expression levels in clinical OSCC tissues. Results: We identified 1847 differentially expressed genes in OSCC tissues. WGCNA revealed four OSCC-specific modules, screening 120 hub mRNAs and five hub lncRNAs. Two prognostic markers (AQP5, IL-26) from hub mRNAs and three (FRMD5, INHBB, GUCY1A3) from the lncRNA–mRNA network were associated with survival. Validation showed lower expression of AQP5 and GUCY1A3, and higher expression of FRMD5 and INHBB in OSCC compared to normal tissues. Conclusion: This study enhances our understanding of transcriptional dysregulation in OSCC and may highlights AQP5, IL-26, FRMD5, INHBB, and GUCY1A3 as promising prognostic biomarkers. [ABSTRACT FROM AUTHOR]

BACKGROUND The genetic composition of embryos generated by in vitro fertilization (IVF) can be examined with preimplantation genetic testing (PGT). Until recently, PGT was limited to detecting single-gene, high-risk pathogenic variants, large structural variants, and aneuploidy. Recent advances have made genome-wide genotyping of IVF embryos feasible and affordable, raising the possibility of screening embryos for their risk of polygenic diseases such as breast cancer, hypertension, diabetes, or schizophrenia. Despite a heated debate around this new technology, called polygenic embryo screening (PES; also PGT-P), it is already available to IVF patients in some countries. Several articles have studied epidemiological, clinical, and ethical perspectives on PES; however, a comprehensive, principled review of this emerging field is missing. OBJECTIVE AND RATIONALE This review has four main goals. First, given the interdisciplinary nature of PES studies, we aim to provide a self-contained educational background about PES to reproductive specialists interested in the subject. Second, we provide a comprehensive and critical review of arguments for and against the introduction of PES, crystallizing and prioritizing the key issues. We also cover the attitudes of IVF patients, clinicians, and the public towards PES. Third, we distinguish between possible future groups of PES patients, highlighting the benefits and harms pertaining to each group. Finally, our review, which is supported by ESHRE, is intended to aid healthcare professionals and policymakers in decision-making regarding whether to introduce PES in the clinic, and if so, how, and to whom. SEARCH METHODS We searched for PubMed-indexed articles published between 1/1/2003 and 1/3/2024 using the terms 'polygenic embryo screening', 'polygenic preimplantation', and 'PGT-P'. We limited the review to primary research papers in English whose main focus was PES for medical conditions. We also included papers that did not appear in the search but were deemed relevant. OUTCOMES The main theoretical benefit of PES is a reduction in lifetime polygenic disease risk for children born after screening. The magnitude of the risk reduction has been predicted based on statistical modelling, simulations, and sibling pair analyses. Results based on all methods suggest that under the best-case scenario, large relative risk reductions are possible for one or more diseases. However, as these models abstract several practical limitations, the realized benefits may be smaller, particularly due to a limited number of embryos and unclear future accuracy of the risk estimates. PES may negatively impact patients and their future children, as well as society. The main personal harms are an unindicated IVF treatment, a possible reduction in IVF success rates, and patient confusion, incomplete counselling, and choice overload. The main possible societal harms include discarded embryos, an increasing demand for 'designer babies', overemphasis of the genetic determinants of disease, unequal access, and lower utility in people of non-European ancestries. Benefits and harms will vary across the main potential patient groups, comprising patients already requiring IVF, fertile people with a history of a severe polygenic disease, and fertile healthy people. In the United States, the attitudes of IVF patients and the public towards PES seem positive, while healthcare professionals are cautious, sceptical about clinical utility, and concerned about patient counselling. WIDER IMPLICATIONS The theoretical potential of PES to reduce risk across multiple polygenic diseases requires further research into its benefits and harms. Given the large number of practical limitations and possible harms, particularly unnecessary IVF treatments and discarded viable embryos, PES should be offered only within a research context before further clarity is achieved regarding its balance of benefits and harms. The gap in attitudes between healthcare professionals and the public needs to be narrowed by expanding public and patient education and providing resources for informative and unbiased genetic counselling. [ABSTRACT FROM AUTHOR]

Recent decades have seen the increase of genome-wide analyses performed in the general population to compute the risk for multifactorial conditions. Polygenic risk tests, already available to clients via the direct-To-consumer (DTC) market, recently expanded to preimplantation genetic assessment of embryos in the context of fertility treatments (Preimplantation Polygenic Genetic Testing or PGT-P). While both kinds of tests rely on the same methodologies and are fueled by the promise of health optimization, they propose different interventions. Here, we compare the advertising strategies for companies offering DTC or PGT-P. We show that each company presents genotype–phenotype relationships to accommodate the intervention they propose and the clients' expectations. While DTC companies grant a greater role to the environment and to genotype–environment interaction on health, discourse on PGT-P neglects any such interaction and undermines environmental factors. In all cases analyzed, while it is recognized that risk is a group property, the estimate is presented as an individual trait, and sometimes confounded with health status. Moreover, all companies recognize the uncertainty of risk estimations but frame it as a result of the lack of detailed information, justifying the gathering of clients' data, and fueling promises of the betterment of future population health through individual action. [ABSTRACT FROM AUTHOR]

INTRODUCTION: Excess weight is an established risk factor of colorectal cancer (CRC). However, evidence is lacking on how its impact varies by polygenic risk at different stages of colorectal carcinogenesis. METHODS: We assessed the individual and joint associations of body mass index (BMI) and polygenic risk scores (PRSs) with findings of colorectal neoplasms among 4,784 participants of screening colonoscopy. Adjusted odds ratios (aORs) for excess weight derived by multiple logistic regression were converted to genetic risk equivalents (GREs) to quantify the impact of excess weight compared with genetic predisposition. RESULTS: Overweight and obesity (BMI 25-<30 and ≥30 kg/m²) were associated with increased risk of any colorectal neoplasm (aOR [95% confidence interval, CI] 1.26 [1.09-1.45] and 1.47 [1.24-1.75]). Obesity was associated with increased risk of advanced colorectal neoplasm (aOR [95% CI] 1.46 [1.16-1.84]). Dose-response relationships were seen for the PRS (stronger for advanced neoplasms than any neoplasms), with no interaction with BMI, suggesting multiplicative effects of both factors. Obese participants with a PRS in the highest tertile had a 2.3-fold (95% CI 1.7-3.1) and 2.9-fold (95% CI 1.9-4.3) increased risk of any colorectal neoplasm and advanced colorectal neoplasm, respectively. The aOR of obesity translated into a GRE of 38, meaning that its impact was estimated to be equivalent to the risk caused by 38 percentiles higher PRS for colorectal neoplasm. DISCUSSION: Excess weight and polygenic risk are associated with increased risk of colorectal neoplasms in a multiplicative manner. Maintaining normal weight is estimated to have an equivalent effect as having 38 percentiles lower PRS. [ABSTRACT FROM AUTHOR]

Key Points: Question: Which individual symptoms of psychopathology are associated with genetic risk? Findings: This cross-sectional study including a primary sample of 5521 individuals combined psychological network and polygenic score approaches and found polygenic scores for psychopathology-related traits were primarily associated with a restricted number of trait-relevant and cross-trait symptoms. Results were replicated in an independent sample of 4625 individuals following preregistered analyses. Meaning: A shift from thinking of psychopathology at the disorder level to thinking about individual transdiagnostic symptoms may be beneficial to uncover novel insights in the development and comorbidity of psychopathology; symptom-level analyses may be valuable in unraveling the complex (genetic) etiology of psychiatric conditions and avoiding pitfalls resulting from disorder heterogeneity. This cross-sectional study evaluates associations between polygenic scores with psychiatric disorder symptoms and relevant comorbid phenotypes. Importance: Studies on polygenic risk for psychiatric traits commonly use a disorder-level approach to phenotyping, implicitly considering disorders as homogeneous constructs; however, symptom heterogeneity is ubiquitous, with many possible combinations of symptoms falling under the same disorder umbrella. Focusing on individual symptoms may shed light on the role of polygenic risk in psychopathology. Objective: To determine whether polygenic scores are associated with all symptoms of psychiatric disorders or with a subset of indicators and whether polygenic scores are associated with comorbid phenotypes via specific sets of relevant symptoms. Design, Setting, and Participants: Data from 2 population-based cohort studies were used in this cross-sectional study. Data from children in the Avon Longitudinal Study of Parents and Children (ALSPAC) were included in the primary analysis, and data from children in the Twins Early Development Study (TEDS) were included in confirmatory analyses. Data analysis was conducted from October 2021 to January 2024. Pregnant women based in the Southwest of England due to deliver in 1991 to 1992 were recruited in ALSPAC. Twins born in 1994 to 1996 were recruited in TEDS from population-based records. Participants with available genetic data and whose mothers completed the Short Mood and Feelings Questionnaire and the Strength and Difficulties Questionnaire when children were 11 years of age were included. Main Outcomes and Measures: Psychopathology relevant symptoms, such as hyperactivity, prosociality, depression, anxiety, and peer and conduct problems at age 11 years. Psychological networks were constructed including individual symptoms and polygenic scores for depression, anxiety, attention-deficit/hyperactivity disorder (ADHD), body mass index (BMI), and educational attainment in ALSPAC. Following a preregistered confirmatory analysis, network models were cross-validated in TEDS. Results: Included were 5521 participants from ALSPAC (mean [SD] age, 11.8 [0.14] years; 2777 [50.3%] female) and 4625 participants from TEDS (mean [SD] age, 11.27 [0.69] years; 2460 [53.2%] female). Polygenic scores were preferentially associated with restricted subsets of core symptoms and indirectly associated with other, more distal symptoms of psychopathology (network edges ranged between r = −0.074 and r = 0.073). Psychiatric polygenic scores were associated with specific cross-disorder symptoms, and nonpsychiatric polygenic scores were associated with a variety of indicators across disorders, suggesting a potential contribution of nonpsychiatric traits to comorbidity. For example, the polygenic score for ADHD was associated with a core ADHD symptom, being easily distracted (r = 0.07), and the polygenic score for BMI was associated with symptoms across disorders, including being bullied (r = 0.053) and not thinking things out (r = 0.041). Conclusions and Relevance: Genetic associations observed at the disorder level may hide symptom-level heterogeneity. A symptom-level approach may enable a better understanding of the role of polygenic risk in shaping psychopathology and comorbidity. [ABSTRACT FROM AUTHOR]

Early in the SARS-CoV2 pandemic, in this journal, Hou et al. (BMC Med 18:216, 2020) interpreted public genotype data, run through functional prediction tools, as suggesting that members of particular human populations carry potentially COVID-risk-increasing variants in genes ACE2 and TMPRSS2 far more often than do members of other populations. Beyond resting on predictions rather than clinical outcomes, and focusing on variants too rare to typify population members even jointly, their claim mistook a well known artifact (that large samples reveal more of a population's variants than do small samples) as if showing real and congruent population differences for the two genes, rather than lopsided population sampling in their shared source data. We explain that artifact, and contrast it with empirical findings, now ample, that other loci shape personal COVID risks far more significantly than do ACE2 and TMPRSS2—and that variation in ACE2 and TMPRSS2 per se unlikely exacerbates any net population disparity in the effects of such more risk-informative loci. [ABSTRACT FROM AUTHOR]

AbstractIn this work, we propose a Semi-supervised Triply Robust Inductive transFer LEarning (STRIFLE) approach, which integrates heterogeneous data from a label-rich source population and a label-scarce target population and uses a large amount of unlabeled data simultaneously to improve the learning accuracy in the target population. Specifically, we consider a high dimensional covariate shift setting and employ two nuisance models, a density ratio model and an imputation model, to combine transfer learning and surrogate-assisted semi-supervised learning strategies effectively and achieve triple robustness. While the STRIFLE approach assumes the target and source populations to share the same conditional distribution of outcome Y given both the surrogate features S and predictors X, it allows the true underlying model of Y⏧X to differ between the two populations due to the potential covariate shift in S and X. Different from double robustness, even if both nuisance models are misspecified or the distribution of Y⏧S,X is not the same between the two populations when the shifted source population and the target population share enough similarities, the triply robust STRIFLE estimator can still partially use the source population when the shifted source population and the target population share enough similarities. Moreover, it is guaranteed to be no worse than the target-only surrogate-assisted semi-supervised estimator with an additional error term from transferability detection. These desirable properties of our estimator are established theoretically and verified in finite samples via extensive simulation studies. We use the STRIFLE estimator to train a Type II diabetes polygenic risk prediction model for the African American target population by transferring knowledge from electronic health records linked genomic data observed in a larger European source population. Supplementary materials for this article are available online, including a standardized description of the materials available for reproducing the work. [ABSTRACT FROM AUTHOR]

According to various research, the risk of multiple sclerosis (MS) is strongly influenced by genetic variations. Population, familial, and molecular studies provide strong empirical support for a polygenic pattern of inheritance, mainly due to relatively common allelic variants in the general population. The strongest MS susceptibility locus, which was unmistakably identified in tested populations, is the major histocompatibility complex on chromosome 6p21.3. However, the effect of a given predisposing variant remains modest, so there is the possibility that multiple gene–gene and/or gene–environment interactions could significantly increase the contribution of specific variants to the overall genetic risk. Furthermore, as is known, susceptibility genes can be subject to epigenetic modifications, which greatly increase the complexity of MS heritability. Investigating epigenetic and environmental factors can provide new opportunities for the molecular basis of the MS, which shows complicated pathogenesis. Although studies of epigenetic changes in MS only began in the last decade, a growing body of literature suggests that these may be involved in the development of MS. Here, we summarize recent studies regarding epigenetic changes related to MS initiation and progression. Furthermore, we discuss how current studies address important clinical questions and how future studies could be used in clinical practice. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRS) enhance population risk stratification and advance personalized medicine, but existing methods face several limitations, encompassing issues related to computational burden, predictive accuracy, and adaptability to a wide range of genetic architectures. To address these issues, we propose Aggregated L0Learn using Summary-level data (ALL-Sum), a fast and scalable ensemble learning method for computing PRS using summary statistics from genome-wide association studies (GWAS). ALL-Sum leverages a L0L2 penalized regression and ensemble learning across tuning parameters to flexibly model traits with diverse genetic architectures. In extensive large-scale simulations across a wide range of polygenicity and GWAS sample sizes, ALL-Sum consistently outperformed popular alternative methods in terms of prediction accuracy, runtime, and memory usage by 10%, 20-fold, and threefold, respectively, and demonstrated robustness to diverse genetic architectures. We validated the performance of ALL-Sum in real data analysis of 11 complex traits using GWAS summary statistics from nine data sources, including the Global Lipids Genetics Consortium, Breast Cancer Association Consortium, and FinnGen Biobank, with validation in the UK Biobank. Our results show that on average, ALL-Sum obtained PRS with 25% higher accuracy on average, with 15 times faster computation and half the memory than the current state-of-the-art methods, and had robust performance across a wide range of traits and diseases. Furthermore, our method demonstrates stable prediction when using linkage disequilibrium computed from different data sources. ALL-Sum is available as a user-friendly R software package with publicly available reference data for streamlined analysis. [ABSTRACT FROM AUTHOR]

Portability of trans-ancestral polygenic risk scores is often confounded by differences in linkage disequilibrium and genetic architecture between ancestries. Recent literature has shown that prioritizing GWAS SNPs with functional genomic evidence over strong association signals can improve model portability. We leveraged three RegulomeDB-derived functional regulatory annotations—SURF, TURF, and TLand—to construct polygenic risk models across a set of quantitative and binary traits highlighting functional mutations tagged by trait-associated tissue annotations. Tissue-specific prioritization by TURF and TLand provide a significant improvement in model accuracy over standard polygenic risk score (PRS) models across all traits. We developed the Trans-ancestral Iterative Tissue Refinement (TITR) algorithm to construct PRS models that prioritize functional mutations across multiple trait-implicated tissues. TITR-constructed PRS models show increased predictive accuracy over single tissue prioritization. This indicates our TITR approach captures a more comprehensive view of regulatory systems across implicated tissues that contribute to variance in trait expression. Author summary: Polygenic risk score models leverage effect size estimates from ancestry-targeted GWAS to generate well-powered disease stratification models. When ancestry-targeted GWAS is unavailable for understudied populations, trans-ancestral PRS models may be implemented. However, transferring PRS models across ancestries results in limited predictive accuracy due to linkage differences between ancestries. Here we show that isolating GWAS variants with strong functional evidence identified from RegulomeDB-derived annotations in tissues enriched for trait heritability can improve portability of PRS models across distant ancestries. The motivation is mutations with evidence of regulatory impact are more likely to be shared between ancestries than genome-wide significant signals from ancestry-targeted GWAS. Further, we developed the novel TITR algorithm to aggregate functional GWAS mutations across multiple trait-implicated tissues to iteratively construct PRSs. These models provide a more comprehensive view of functional GWAS mutations that influence variation in complex disease expression and can help improve portability of PRS models in under-represented populations. [ABSTRACT FROM AUTHOR]

Individuals with schizophrenia and bipolar disorder are at an increased risk of cardiovascular disease (CVD), and a range of biomarkers related to CVD risk have been found to be abnormal in these patients. Common genetic factors are a putative underlying mechanism, alongside lifestyle factors and antipsychotic medication. However, the extent to which the altered CVD biomarkers are related to genetic factors involved in schizophrenia and bipolar disorder is unknown. In a sample including 699 patients with schizophrenia, 391 with bipolar disorder, and 822 healthy controls, we evaluated 8 CVD risk biomarkers, including BMI, and fasting plasma levels of CVD biomarkers from a subsample. Polygenic risk scores (PGRS) were obtained from genome-wide associations studies (GWAS) of schizophrenia and bipolar disorder from the Psychiatric Genomics Consortium. The CVD biomarkers were used as outcome variables in linear regression models including schizophrenia and bipolar disorder PGRS as predictors, age, sex, diagnostic category, batch and 10 principal components as covariates, controlling for multiple testing by Bonferroni correction for the number of independent tests. Bipolar disorder PGRS was significantly (p = 0.03) negatively associated with BMI after multiple testing correction, and schizophrenia PGRS was nominally negatively associated with BMI. There were no other significant associations between bipolar or schizophrenia PGRS, and other investigated CVD biomarkers. Despite a range of abnormal CVD risk biomarkers in psychotic disorders, we only found a significant negative association between bipolar disorder PGRS and BMI. This has previously been shown for schizophrenia PGRS and BMI, and warrants further exploration. [ABSTRACT FROM AUTHOR]

The Krüppel-like factor (KLF) family represents a group of transcription factors (TFs) performing different biological processes that are crucial for proper neuronal function, including neuronal development, synaptic plasticity, and neuronal survival. As reported, genetic variants within the KLF family have been associated with a wide spectrum of neurodevelopmental and psychiatric symptoms. In a patient exhibiting attention deficit hyperactivity disorder (ADHD) combined with both neurodevelopmental and psychiatric symptoms, whole-exome sequencing (WES) analysis revealed a de novo heterozygous variant within the Krüppel-like factor 13 (KLF13) gene, which belongs to the KLF family and regulates axonal growth, development, and regeneration in mice. Moreover, in silico analyses pertaining to the likely pathogenic significance of the variant and the impact of the mutation on the KLF13 protein structure suggested a potential deleterious effect. In fact, the variant was localized in correspondence to the starting residue of the N-terminal domain of KLF13, essential for protein–protein interactions, DNA binding, and transcriptional activation or repression. This study aims to highlight the potential involvement of the KLF13 gene in neurodevelopmental and psychiatric disorders. Nevertheless, we cannot rule out that excluded variants, those undetectable by WES, or the polygenic risk may have contributed to the patient's phenotype given ADHD's high polygenic risk. However, further functional studies are required to validate its potential contribution to these disorders. [ABSTRACT FROM AUTHOR]

Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (−). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A−T− status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T− status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T− status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A−T− to A+T−, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70–4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84–1.42; P = 0.53). Conversely, for the transition from A+T− to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05–2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27–2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05–6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87–3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions. [ABSTRACT FROM AUTHOR]

Education is essential for socioeconomic security and long-term mental health; however, mental disorders are often detrimental to the educational trajectory. Genetic correlations between mental disorders and educational attainment do not always align with corresponding phenotypic associations, implying heterogeneity in the genetic overlap. We unraveled this heterogeneity by investigating associations between polygenic risk scores for 6 mental disorders and fine-grained school outcomes: school grades in language and mathematics in ninth grade and high school, as well as educational attainment by age 25, using nationwide-representative data from established cohorts (N = 79,489). High polygenic liability of attention-deficit/hyperactivity disorder was associated with lower grades in language and mathematics, whereas high polygenic risk of anorexia nervosa or bipolar disorder was associated with higher grades in language and mathematics. Associations between polygenic risk and school grades were mixed for schizophrenia and major depressive disorder and neutral for autism spectrum disorder. Polygenic risk scores for mental disorders are differentially associated with language and mathematics school grades. [ABSTRACT FROM AUTHOR]

Purpose: Age-related hearing loss is the most common form of permanent hearing loss that is associated with various health traits, including Alzheimer's disease, cognitive decline, and depression. The present study aims to identify genetic comorbidities of age-related hearing loss. Past genome-wide association studies identified multiple genomic loci involved in common adult-onset health traits. Polygenic risk scores (PRS) could summarize the polygenic inheritance and quantify the genetic susceptibility of complex traits independent of trait expression. The present study conducted a PRS-based association analysis of age-related hearing difficulty in the UK Biobank sample (N = 425,240), followed by a replication analysis using hearing thresholds (HTs) and distortion-product otoacoustic emissions (DPOAEs) in 242 young adults with self-reported normal hearing. We hypothesized that young adults with genetic comorbidities associated with age-related hearing difficulty would exhibit subclinical decline in HTs and DPOAEs in both ears. Methods: A total of 111,243 participants reported age-related hearing difficulty in the UK Biobank sample (> 40 years). The PRS models were derived from the polygenic risk score catalog to obtain 2627 PRS predictors across the health spectrum. HTs (0.25–16 kHz) and DPOAEs (1–16 kHz, L1/L2 = 65/55 dB SPL, F2/F1 = 1.22) were measured on 242 young adults. Saliva-derived DNA samples were subjected to low-pass whole genome sequencing, followed by genome-wide imputation and PRS calculation. The logistic regression analyses were performed to identify PRS predictors of age-related hearing difficulty in the UK Biobank cohort. The linear mixed model analyses were performed to identify PRS predictors of HTs and DPOAEs. Results: The PRS-based association analysis identified 977 PRS predictors across the health spectrum associated with age-related hearing difficulty. Hearing difficulty and hearing aid use PRS predictors revealed the strongest association with the age-related hearing difficulty phenotype. Youth with a higher genetic predisposition to hearing difficulty revealed a subclinical elevation in HTs and a decline in DPOAEs in both ears. PRS predictors associated with age-related hearing difficulty were enriched for mental health, lifestyle, metabolic, sleep, reproductive, digestive, respiratory, hematopoietic, and immune traits. Fifty PRS predictors belonging to various trait categories were replicated for HTs and DPOAEs in both ears. Conclusion: The study identified genetic comorbidities associated with age-related hearing loss across the health spectrum. Youth with a high genetic predisposition to age-related hearing difficulty and other related complex traits could exhibit sub-clinical decline in HTs and DPOAEs decades before clinically meaningful age-related hearing loss is observed. We posit that effective communication of genetic risk, promoting a healthy lifestyle, and reducing exposure to environmental risk factors at younger ages could help prevent or delay the onset of age-related hearing difficulty at older ages. [ABSTRACT FROM AUTHOR]

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death in the Western world. The number of diagnosed cases and the mortality rate are almost equal as the majority of patients present with advanced disease at diagnosis. Between 4 and 10% of pancreatic cancer cases have an apparent hereditary background, known as hereditary pancreatic cancer (HPC) and familial pancreatic cancer (FPC), when the genetic basis is unknown. Surveillance of high-risk individuals (HRI) from these families by imaging aims to detect PDAC at an early stage to improve prognosis. However, the genetic basis is unknown in the majority of HRIs, with only around 10–13% of families carrying known pathogenic germline mutations. The aim of this study was to assess an individual's genetic cancer risk based on sex and personal and family history of cancer. The Best Linear Unbiased Prediction (BLUP) methodology was used to estimate an individual's predicted risk of developing cancer during their lifetime. The model uses different demographic factors in order to estimate heritability. A reliable estimation of heritability for pancreatic cancer of 0.27 on the liability scale, and 0.07 at the observed data scale as obtained, which is different from zero, indicating a polygenic inheritance pattern of PDAC. BLUP was able to correctly discriminate PDAC cases from healthy individuals and those with other cancer types. Thus, providing an additional tool to assess PDAC risk HRI with an assumed genetic predisposition in the absence of known pathogenic germline mutations. [ABSTRACT FROM AUTHOR]

Recently, the use of polygenic risk scores in embryo screening (PGT-P) has been introduced on the premise of reducing polygenic disease risk through embryo selection. However, it has been met with extensive critique: considered "technology-driven" rather than "evidence-based", concerns exist about its validity, utility, ethics, and societal effects. Its scientific foundations and criticisms thus need to be carefully considered. However, seeing as PGT-P is already offered in some settings, further questions need to be addressed, in order to give due diligence to various aspects of PGT-P. By examining the complexities of clinical introduction of PGT-P, we discuss whether PGT-P could be responsibly implemented in the first place, what elements need to be addressed if PGT-P is clinically implemented, and subsequently how counselling and decision-making of its users could be envisaged. By dissecting these elements, we provide an overview of important practical questions of PGT-P and emphasize elements of PGT-P that we think have yet to be given sufficient attention. These questions and elements are for example related to the potential target group, scope, and decision-making possibilities of PGT-P. The aspects we raise are crucial to consider by the scientific community and policy makers for the development of guidelines and/or an ethical framework for PGT-P. [ABSTRACT FROM AUTHOR]

Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases. We integrate PGS associations from seven studies in four countries (N = 1,197,129) with disease incidences from the Global Burden of Disease. PGS has a significant sex-specific effect for asthma, hip osteoarthritis, gout, coronary heart disease and type 2 diabetes (T2D), with all but T2D exhibiting a larger effect in men. PGS has a larger effect in younger individuals for 13 diseases, with effects decreasing linearly with age. We show for breast cancer that, relative to individuals in the bottom 20% of polygenic risk, the top 5% attain an absolute risk for screening eligibility 16.3 years earlier. Our framework increases the generalizability of results from biobank studies and the accuracy of absolute risk estimates by appropriately accounting for age- and sex-specific PGS effects. Our results highlight the potential of PGS as a screening tool which may assist in the early prevention of common diseases. Here the authors present a framework for estimating disease risk using PGS accounting for country, age and sex. They find that PGSs have a significant sex-specific effect on common diseases, and their effect is typically larger in young individuals. [ABSTRACT FROM AUTHOR]

Fruit rind patterns are vital commercial quality traits in melon, in which the spotted or striped fruit rinds contribute to the commercial value of melon and can directly affect the choice of consumers. Although the spotted or non-spotted fruit rind pattern was studied in several cultivated melon accessions, the inheritance and regulating locus of this trait in wild melons are still unknown. Therefore, in this study, the inheritance and regulating loci of the green spotted fruit rind in a wild melon accession XNM020 were explored with F2 segregating populations derived from crossing between XNM020 and a cultivated melon XNM125. Segregating ratios of phenotypic data indicated that the green spotted fruit rind in XNM020 has a monogenic dominant inheritance. BSA-Seq showed that two potential genomic regions on chromosomes 4 (from 0.00 to 2.97 Mb) and 5 (from 0.00 to 2.34 Mb) regulate the formation of the green spotted fruit rind in wild melon XNM020. According to the annotations of polymorphic SNPs (single-nucleotide polymorphisms) and small InDels (insertions and deletions) in target genomic regions and the predicted gene functions, four genes MELO3C003316, MELO3C003375, MELO3C003388, and MELO3C014660 regulating chloroplast development or chlorophyll biosynthesis may be the best candidate genes. The results of this study enriched the inheritances of spotted fruit rinds in melon and also provided target genomic regions for marker-assisted selection breeding of melon focusing on fruit rinds. [ABSTRACT FROM AUTHOR]