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Polygenic risk prediction is a widely investigated topic because of its promising clinical applications. Genetic variants in functional regions of the genome are enriched for complex trait heritability. Here, we introduce a method for polygenic prediction, LDpred-funct, that leverages trait-specific functional priors to increase prediction accuracy. We fit priors using the recently developed baseline-LD model, including coding, conserved, regulatory, and LD-related annotations. We analytically estimate posterior mean causal effect sizes and then use cross-validation to regularize these estimates, improving prediction accuracy for sparse architectures. We applied LDpred-funct to predict 21 highly heritable traits in the UK Biobank (avg N = 373 K as training data). LDpred-funct attained a +4.6% relative improvement in average prediction accuracy (avg prediction R 2 = 0.144; highest R 2 = 0.413 for height) compared to SBayesR (the best method that does not incorporate functional information). For height, meta-analyzing training data from UK Biobank and 23andMe cohorts ( N = 1107 K) increased prediction R 2 to 0.431. Our results show that incorporating functional priors improves polygenic prediction accuracy, consistent with the functional architecture of complex traits. Incorporating functional information has shown promise for improving polygenic risk prediction of complex traits. Here, the authors describe polygenic prediction method LDpred-funct, and demonstrate its utility across 21 heritable traits in the UK Biobank.

We trained and validated risk prediction models for the three major types of skin cancer— basal cell carcinoma (BCC), squamous cell carcinoma (SCC), and melanoma—on a cross-sectional and longitudinal dataset of 210,000 consented research participants who responded to an online survey covering personal and family history of skin cancer, skin susceptibility, and UV exposure. We developed a primary disease risk score (DRS) that combined all 32 identified genetic and non-genetic risk factors. Top percentile DRS was associated with an up to 13-fold increase (odds ratio per standard deviation increase >2.5) in the risk of developing skin cancer relative to the middle DRS percentile. To derive lifetime risk trajectories for the three skin cancers, we developed a second and age independent disease score, called DRSA. Using incident cases, we demonstrated that DRSA could be used in early detection programs for identifying high risk asymptotic individuals, and predicting when they are likely to develop skin cancer. High DRSA scores were not only associated with earlier disease diagnosis (by up to 14 years), but also with more severe and recurrent forms of skin cancer. Predicting who will develop skin cancer is difficult. Here, the authors from 23andMe developed a polygenic risk score for skin cancer based on a questionnaire and genetic data from more than 210,000 individuals and suggest that the score could be used in early screening programmes.

The “antidepressant efficacy” survey (AES) was deployed to > 50,000 23andMe, Inc. research participants to investigate the genetic basis of treatment-resistant depression (TRD) and non-treatment-resistant depression (NTRD). Genome-wide association studies (GWAS) were performed, including TRD vs. NTRD, selective serotonin reuptake inhibitor (SSRI) responders vs. non-responders, serotonin-norepinephrine reuptake inhibitor (SNRI) responders vs. non-responders, and norepinephrine-dopamine reuptake inhibitor responders vs. non-responders. Only the SSRI association reached the genome-wide significance threshold ( p  < 5 × 10 −8 ): one genomic region in RNF219-AS1 (SNP rs4884091, p  = 2.42 × 10 −8 , OR = 1.21); this association was also observed in the meta-analysis (13,130 responders vs. 6,610 non-responders) of AES and an earlier “antidepressant efficacy and side effects” survey (AESES) cohort. Meta-analysis for SNRI response phenotype derived from AES and AESES (4030 responders vs. 3049 non-responders) identified another genomic region (lead SNP rs4955665, p  = 1.62 × 10 −9 , OR = 1.25) in an intronic region of MECOM passing the genome-wide significance threshold. Meta-analysis for the TRD phenotype (31,068 NTRD vs 5,714 TRD) identified one additional genomic region (lead SNP rs150245813, p  = 8.07 × 10 −9 , OR = 0.80) in 10p11.1 passing the genome-wide significance threshold. A stronger association for rs150245813 was observed in current study ( p  = 7.35 × 10 −7 , OR = 0.79) than the previous study ( p  = 1.40 × 10 −3 , OR = 0.81), and for rs4955665, a stronger association in previous study ( p  = 1.21 × 10 −6 , OR = 1.27) than the current study ( p  = 2.64 × 10 −4 , OR = 1.21). In total, three novel loci associated with SSRI or SNRI (responders vs. non-responders), and NTRD vs TRD were identified; gene level association and gene set enrichment analyses implicate enrichment of genes involved in immune process.

Localization of specific mRNAs is an important mechanism through which cells achieve polarity and direct asymmetric growth. Based on a framework established in Saccharomyces cerevisiae, we describe a She3-dependent RNA transport system in Candida albicans, a fungal pathogen of humans that grows as both budding (yeast) and filamentous (hyphal and pseudohyphal) forms. We identify a set of 40 mRNAs that are selectively transported to the buds of yeast-form cells and to the tips of hyphae, and we show that many of the genes encoded by these mRNAs contribute to hyphal development, as does the transport system itself. Although the basic system of mRNA transport is conserved between S. cerevisiae and C. albicans, we find that the cargo mRNAs have diverged considerably, implying that specific mRNAs can easily move in and out of transport control over evolutionary timescales. The differences in mRNA cargos likely reflect the distinct selective pressures acting on the two species.

Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank ( n  = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort ( n  = 541,333). Findings include missense variants in established drug targets for sleep disorders ( HCRTR1 , HCRTR2 ), genes with roles in arousal ( TRPC6 , PNOC ), and genes suggesting an obesity-hypersomnolence pathway ( PNOC, PATJ ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference. The genetic basis of daytime napping and the directional effect of daytime napping on cardiometabolic health are unknown. Here, the authors perform a genome-wide association study on self-reported daytime napping in the UK Biobank and Mendelian randomization to explore causal associations.

Neuroticism is an important risk factor for psychiatric traits, including depression 1 , anxiety 2 , 3 , and schizophrenia 4 – 6 . At the time of analysis, previous genome-wide association studies 7 – 12 (GWAS) reported 16 genomic loci associated to neuroticism 10 – 12 . Here we conducted a large GWAS meta-analysis ( n  = 449,484) of neuroticism and identified 136 independent genome-wide significant loci (124 new at the time of analysis), which implicate 599 genes. Functional follow-up analyses showed enrichment in several brain regions and involvement of specific cell types, including dopaminergic neuroblasts ( P  = 3.49 × 10 −8 ), medium spiny neurons ( P  = 4.23 × 10 −8 ), and serotonergic neurons ( P  = 1.37 × 10 −7 ). Gene set analyses implicated three specific pathways: neurogenesis ( P  = 4.43 × 10 −9 ), behavioral response to cocaine processes ( P  = 1.84 × 10 −7 ), and axon part ( P  = 5.26 × 10 −8 ). We show that neuroticism’s genetic signal partly originates in two genetically distinguishable subclusters 13 (‘depressed affect’ and ‘worry’), suggesting distinct causal mechanisms for subtypes of individuals. Mendelian randomization analysis showed unidirectional and bidirectional effects between neuroticism and multiple psychiatric traits. These results enhance neurobiological understanding of neuroticism and provide specific leads for functional follow-up experiments. A meta-analysis of genome-wide association studies for neuroticism identifies novel loci, pathways and potential drug targets. Further analysis implicates specific brain regions and evaluates genetic overlap with other neuropsychiatric traits.

Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated ( P  < 5 × 10 −8 ) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression. The UK Biobank provides data for three depression-related phenotypes. Here, Howard et al. perform a genome-association study for broad depression, probable major depressive disorder (MDD) and hospital record-coded MDD in up to 322,580 UK Biobank participants which highlights excitatory synaptic pathways.

Polygenic risk scores (PRSs) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning. We evaluated CT-SLEB and nine alternative methods with large-scale simulated genome-wide association studies (~19 million common variants) and datasets from 23andMe, Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank, involving 5.1 million individuals of diverse ancestry, with 1.18 million individuals from four non-European populations across 13 complex traits. Results demonstrated that CT-SLEB significantly improves PRS performance in non-European populations compared with simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offered insights into sample size requirements and SNP density effects on multiancestry risk prediction. CT-SLEB, a powerful and scalable method, improves the performance of multiancestry polygenic prediction by generating polygenic risk scores based on GWAS summary statistics in diverse populations.

Delay discounting (DD), the tendency to discount the value of delayed versus current rewards, is elevated in a constellation of diseases and behavioral conditions. We performed a genome-wide association study of DD using 23,127 research participants of European ancestry. The most significantly associated single-nucleotide polymorphism was rs6528024 (P = 2.40 × 10−8), which is located in an intron of the gene GPM6B. We also showed that 12% of the variance in DD was accounted for by genotype and that the genetic signature of DD overlapped with attention-deficit/hyperactivity disorder, schizophrenia, major depression, smoking, personality, cognition and body weight.

Background Clinical genetic testing for inherited predisposition to venous thromboembolism (VTE) is common among patients and their families. However, there is incomplete consensus about which individuals should receive testing, and the relative risks and benefits. Methods We assessed outcomes of receiving direct‐to‐consumer (DTC) results for the two most common genetic risk factors for VTE, factor V Leiden in the F5 gene (FVL) and prothrombin 20210G>A in the F2 gene (PT). Two thousand three hundred fifty‐four customers (1244 variant‐positive and 1110 variant‐negative individuals) of the personal genetics company 23andMe, Inc., who had received results online for F5 and F2 variants, participated in an online survey‐based study. Participants responded to questions about perception of VTE risk, discussion of results with healthcare providers (HCPs) and recommendations received, actions taken to control risk, emotional responses to receiving risk results, and perceived value of the information. Results Most participants (90% of variant‐positive individuals, 99% of variant‐negative individuals) had not previously been tested for F5 and/or F2 variants. The majority of variant‐positive individuals correctly perceived that they were at higher than average risk for developing VTE. These individuals reported moderate rates of discussing results with HCPs (41%); receiving prevention advice from HCPs (31%), and making behavioral changes to control risk (e.g., exercising more, 30%). A minority (36%) of variant‐positive individuals worried more after receiving VTE results. Nevertheless, most participants reported that knowing their risk had been an advantage (78% variant‐positive and 58% variant‐negative) and were satisfied knowing their genetic probability for VTE (81% variant‐positive and 67% variant‐negative). Conclusion Consumers reported moderate rates of behavioral change and perceived personal benefit from receiving DTC genetic results for VTE risk. We assessed the consumer experience receiving direct‐to‐consumer (DTC) genetic risk for venous thromboembolism (VTE). 2354 customers (1244 variant‐positive and 1110 variant‐negative individuals) of the personal genetics company 23andMe, Inc., who had received results online for risk variants in clotting factor genes F2 and F5, participated in an online survey‐based study. Participants responded to questions about perception of VTE risk, discussion of results with healthcare providers and recommendations received, actions taken to control risk, emotional responses to receiving risk results, and perceived value of the information.