The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Global, regional and national burdens of depression in adolescents and young adults aged 10-24 years, from 1990 to 2019: findings from the 2019 Global Burden of Disease study.

BACKGROUND: Depression is a significant mental health concern affecting the overall well-being of adolescents and young adults. Recently, the prevalence of depression has increased among young people. Nonetheless, there is little research delving into the longitudinal epidemiology of adolescent depression over time. AIMS: To investigate the longitudinal epidemiology of depression among adolescents and young adults aged 10-24 years. METHOD: Our research focused on young people (aged 10-24 years) with depression, using data from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019. We explored the age-standardised prevalence, incidence and disability-adjusted life-years (DALYs) of depression in different groups, including various regions, ages, genders and sociodemographic indices, from 1990 to 2019. RESULTS: The prevalence, incidence and DALYs of depression in young people increased globally between 1990 and 2019. Regionally, higher-income regions like High-Income North America and Australasia recorded rising age-standardised prevalence and incidence rates, whereas low- or middle-income regions mostly saw reductions. Nationally, countries such as Greenland, the USA and Palestine reported the highest age-standardised prevalence and incidence rates in 2019, whereas Qatar witnessed the largest growth over time. The burden disproportionately affected females across age groups and world regions. The most prominent age effect on incidence and prevalence rates was in those aged 20-24 years. The depression burden showed an unfavourable trend in younger cohorts born after 1980, with females reporting a higher cohort risk than males. CONCLUSIONS: Between 1990 and 2019, the general pattern of depression among adolescents varied according to age, gender, time period and generational cohort, across regions and nations.

Association between vitamin B2 intake and prostate-specific antigen in American men: 2003-2010 National Health and Nutrition Examination Survey.

BACKGROUND: Accumulating evidence suggests a pivotal role of vitamin B2 in the pathogenesis and progression of prostate cancer (PCa). Vitamin B2 intake has been postulated to modulate the screening rate for PCa by altering the concentration of prostate-specific antigen(PSA). However, the relationship between vitamin B2 and PSA remains indeterminate. Hence, we conducted a comprehensive evaluation of the association between vitamin B2 intake and PSA levels, utilizing data from the National Health and Nutrition Examination Survey (NHANES) database. METHODS: From a pool of 20,371 participants in the NHANES survey conducted between 2003 and 2010, a cohort of 2,323 participants was selected for the present study. The male participants were classified into four distinct groups based on their levels of vitamin B2 intake. We employed a multiple linear regression model and a non-parametric regression method to investigate the relationship between vitamin B2 and PSA levels. RESULTS: The study cohort comprised of 2,323 participants with a mean age of 54.95 years (± 11.73). Our findings revealed a statistically significant inverse correlation between vitamin B2 intake (mg) and PSA levels, with a reduction of 0.13 ng/ml PSA concentration for every unit increase in vitamin B2 intake. Furthermore, we employed a fully adjusted model to construct a smooth curve to explore the possible linear relationship between vitamin B2 intake and PSA concentration. CONCLUSIONS: Our study in American men has unveiled a notable inverse association between vitamin B2 intake and PSA levels, potentially posing a challenge for the identification of asymptomatic prostate cancer. Specifically, our findings suggest that individuals with higher vitamin B2 intake may be at a greater risk of being diagnosed with advanced prostate cancer in the future, possibly indicating a detection bias. These results may offer a novel explanation for the observed positive correlation between vitamin B2 intake and prostate cancer.

TopicNet: a framework for measuring transcriptional regulatory network change.

MOTIVATION: Recently, many chromatin immunoprecipitation sequencing experiments have been carried out for a diverse group of transcription factors (TFs) in many different types of human cells. These experiments manifest large-scale and dynamic changes in regulatory network connectivity (i.e. network 'rewiring'), highlighting the different regulatory programs operating in disparate cellular states. However, due to the dense and noisy nature of current regulatory networks, directly comparing the gains and losses of targets of key TFs across cell states is often not informative. Thus, here, we seek an abstracted, low-dimensional representation to understand the main features of network change. RESULTS: We propose a method called TopicNet that applies latent Dirichlet allocation to extract functional topics for a collection of genes regulated by a given TF. We then define a rewiring score to quantify regulatory-network changes in terms of the topic changes for this TF. Using this framework, we can pinpoint particular TFs that change greatly in network connectivity between different cellular states (such as observed in oncogenesis). Also, incorporating gene expression data, we define a topic activity score that measures the degree to which a given topic is active in a particular cellular state. And we show how activity differences can indicate differential survival in various cancers. AVAILABILITY AND IMPLEMENTATION: The TopicNet framework and related analysis were implemented using R and all codes are available at https://github.com/gersteinlab/topicnet. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Time-Sliced Thawed Gaussian Propagation Method for Simulations of Quantum Dynamics.

A rigorous method for simulations of quantum dynamics is introduced on the basis of concatenation of semiclassical thawed Gaussian propagation steps. The time-evolving state is represented as a linear superposition of closely overlapping Gaussians that evolve in time according to their characteristic equations of motion, integrated by fourth-order Runge-Kutta or velocity Verlet. The expansion coefficients of the initial superposition are updated after each semiclassical propagation period by implementing the Husimi Transform analytically in the basis of closely overlapping Gaussians. An advantage of the resulting time-sliced thawed Gaussian (TSTG) method is that it allows for full-quantum dynamics propagation without any kind of multidimensional integral calculation, or inversion of overlap matrices. The accuracy of the TSTG method is demonstrated as applied to simulations of quantum tunneling, showing quantitative agreement with benchmark calculations based on the split-operator Fourier transform method.

The congenital birth defects burden in children younger than 14 years of age, 1990 - 2019: An age-period-cohort analysis of the global burden of disease study.

Background: This study aims to delineate the burden of congenital birth defects (CBDs) in children under 14 years of age from 1990 to 2019, using an age-period-cohort framework to analyse data from the Global Burden of Disease Study (GBD). Methods: Data on prevalence cases, age-standardised prevalence rates (ASPRs), death cases, and age-standardised death rates (ASDRs) of congenital birth defects (CBDs) from 1990 to 2019 were obtained from GBD 2019. Using this data set, we conducted an age-period-cohort (APC) analysis to examine patterns and trends in mortality, prevalence, and disability-adjusted life years (DALYs) associated with CBDs, while exploring correlations with age, time periods, and generational birth cohorts. Furthermore, to quantify the temporal trends, we calculated the estimated annual percentage changes (EAPCs) for these parameters. Results: The global prevalence of CBDs decreased from 1404.22 to 1301.66 per 100 000 with an EAPC of -0.18% from 1990 to 2019. CBD mortality decreased by 42.52% between 1990 and 2019, with the global age-standardised death rate declining from 49.72 to 25.58 per 100 000. The age-standardised DALY rate decreased from 4529.16 to 2393.61 per 100 000. Prevalence declined most notably among older children. The risk of CBDs reached its lowest during adolescence (10-14 years) across all regions. The most recent period (2015-2019) showed a reduced risk of prevalence compared to 2000-2004. Earlier birth cohorts displayed declining tendencies followed by slight increases in risk. Conclusions: This study demonstrates encouraging global reductions in the burden of CBDs among children over the past three decades. Prevalence, mortality, and DALYs attributable to CBDs have exhibited downward trajectories, although regional disparities remain. APC analysis provides valuable insights to inform prevention and management strategies for pediatric CBDs.

Global, regional and national epidemiology of allergic disorders in children from 1990 to 2019: findings from the Global Burden of Disease study 2019.

OBJECTIVE: This modelling study aimed to estimate the burden for allergic diseases in children during a period of 30 years. DESIGN: Population-based observational study. MAIN OUTCOMES AND MEASURES: The data on the incidence, mortality and disability-adjusted life years (DALYs) for childhood allergic diseases, such as atopic dermatitis (AD) and asthma, were retrieved from the Global Burden of Disease study 2019 online database. This data set spans various groups, including different regions, ages, genders and Socio-Demographic Indices (SDI), covering the period from 1990 to 2019. RESULTS: In 2019, there were approximately 81 million children with asthma and 5.6 million children with AD worldwide. The global incidence of asthma in children was 20 million. Age-standardised incidence rates showed a decrease of 4.17% for asthma, from 1075.14 (95% uncertainty intervals (UI), 724.63 to 1504.93) per 100 000 population in 1990 to 1030.33 (95% UI, 683.66 to 1449.53) in 2019. Similarly, the rates for AD decreased by 5.46%, from 594.05 (95% UI, 547.98 to 642.88) per 100 000 population in 1990 to 561.61 (95% UI, 519.03 to 608.29) in 2019. The incidence of both asthma and AD was highest in children under 5 years of age, gradually decreasing with age. Interestingly, an increase in SDI was associated with a rise in the incidence of both conditions. However, the mortality rate and DALYs for asthma showed a contrasting trend. CONCLUSIONS: Over the past three decades, there has been a worldwide increase in new asthma and AD cases, even though mortality rates have significantly declined. However, the prevalence of these allergic diseases among children varies considerably across regions, countries and age groups. This variation highlights the need for precise prevalence assessments. These assessments are vital in formulating effective strategies for prevention and treatment.

Analysis of the global burden of disease study highlights the global, regional, and national trends of idiopathic epilepsy epidemiology from 1990 to 2019.

Epilepsy is a profound disorder, accounting for roughly 1% of the global disease burden. It can result in premature death and significant disability. To comprehensively understand the current dynamics and trends of idiopathic epilepsy, a deep insight into its epidemiological attributes is vital. We evaluated the incidence, prevalence, mortality, and disability-adjusted life years associated with idiopathic epilepsy from 1990 to 2019 using data and methodologies from the Global Burden of Disease Study. In 2019, there were approximately 2,898,222 individuals diagnosed with idiopathic epilepsy. Intriguingly, from 1990 to 2019, the age-standardized incidence rate of idiopathic epilepsy was consistently lower in women compared to men. Over these three decades, global mortality connected to idiopathic epilepsy increased by 13.95%. However, within the same period, age-standardized death rates for idiopathic epilepsy decreased from 1.94 per 100,000 population to 1.46 per 100,000 population. Predictions indicate an increase in the incidence of idiopathic epilepsy across all age brackets through 2035, especially among the elderly aged 80 and above. Mortality rates are projected to climb for those aged 80 and above while remaining relatively unchanged in other age demographics. Idiopathic epilepsy continues to be a significant contributor to both disability and death. The findings of our study underscore the critical importance of incorporating idiopathic epilepsy management into modern healthcare frameworks. Such strategic inclusion can enhance public awareness of relevant risk factors and the range of available therapeutic interventions.

An integrative ENCODE resource for cancer genomics.

ENCODE comprises thousands of functional genomics datasets, and the encyclopedia covers hundreds of cell types, providing a universal annotation for genome interpretation. However, for particular applications, it may be advantageous to use a customized annotation. Here, we develop such a custom annotation by leveraging advanced assays, such as eCLIP, Hi-C, and whole-genome STARR-seq on a number of data-rich ENCODE cell types. A key aspect of this annotation is comprehensive and experimentally derived networks of both transcription factors and RNA-binding proteins (TFs and RBPs). Cancer, a disease of system-wide dysregulation, is an ideal application for such a network-based annotation. Specifically, for cancer-associated cell types, we put regulators into hierarchies and measure their network change (rewiring) during oncogenesis. We also extensively survey TF-RBP crosstalk, highlighting how SUB1, a previously uncharacterized RBP, drives aberrant tumor expression and amplifies the effect of MYC, a well-known oncogenic TF. Furthermore, we show how our annotation allows us to place oncogenic transformations in the context of a broad cell space; here, many normal-to-tumor transitions move towards a stem-like state, while oncogene knockdowns show an opposing trend. Finally, we organize the resource into a coherent workflow to prioritize key elements and variants, in addition to regulators. We showcase the application of this prioritization to somatic burdening, cancer differential expression and GWAS. Targeted validations of the prioritized regulators, elements and variants using siRNA knockdowns, CRISPR-based editing, and luciferase assays demonstrate the value of the ENCODE resource.

Building a Hybrid Physical-Statistical Classifier for Predicting the Effect of Variants Related to Protein-Drug Interactions.

A key issue in drug design is how population variation affects drug efficacy by altering binding affinity (BA) in different individuals, an essential consideration for government regulators. Ideally, we would like to evaluate the BA perturbations of millions of single-nucleotide variants (SNVs). However, only hundreds of protein-drug complexes with SNVs have experimentally characterized BAs, constituting too small a gold standard for straightforward statistical model training. Thus, we take a hybrid approach: using physically based calculations to bootstrap the parameterization of a full model. In particular, we do 3D structure-based docking on ∼10,000 SNVs modifying known protein-drug complexes to construct a pseudo gold standard. Then we use this augmented set of BAs to train a statistical model combining structure, ligand and sequence features and illustrate how it can be applied to millions of SNVs. Finally, we show that our model has good cross-validated performance (97% AUROC) and can also be validated by orthogonal ligand-binding data.

Multi-platform discovery of haplotype-resolved structural variation in human genomes.

The incomplete identification of structural variants (SVs) from whole-genome sequencing data limits studies of human genetic diversity and disease association. Here, we apply a suite of long-read, short-read, strand-specific sequencing technologies, optical mapping, and variant discovery algorithms to comprehensively analyze three trios to define the full spectrum of human genetic variation in a haplotype-resolved manner. We identify 818,054 indel variants (<50 bp) and 27,622 SVs (≥50 bp) per genome. We also discover 156 inversions per genome and 58 of the inversions intersect with the critical regions of recurrent microdeletion and microduplication syndromes. Taken together, our SV callsets represent a three to sevenfold increase in SV detection compared to most standard high-throughput sequencing studies, including those from the 1000 Genomes Project. The methods and the dataset presented serve as a gold standard for the scientific community allowing us to make recommendations for maximizing structural variation sensitivity for future genome sequencing studies.