Integration of Multi-omics Data Based on Deep Learning for Subtyping of Low-Grade Glioma.

Low-grade gliomas (LGGs) represent a complex and aggressive category of brain tumors. Despite recent advancements in molecular subtyping and characterization, the necessity to identify additional molecular subtypes and biomarkers remains. To delineate survival subtypes in LGG, we propose a deep learning (DL)-based multi-omics SurvivalNet (MOST) model.

Massively parallel characterization of non-coding de novo mutations in autism spectrum disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder where de novo mutations play a significant role. Although coding mutations in ASD have been extensively characterized, the impact of non-coding de novo mutations (ncDNMs) remains less understood. Here, we integrate cortex cell-specific cis-regulatory element annotations, a deep learning-based variant prediction model, and massively parallel reporter assays to systematically evaluate the functional impact of 227,878 ncDNMs from Simons Simplex Collection (SSC) and Autism Speaks MSSNG resource (MSSNG) cohorts.

Ultra-processed foods, biological ageing, and all-cause mortality risk: a prospective cohort study using 172,225 participants from UK Biobank.

Ultra-processed foods (UPF) are increasingly linked to negative health outcomes, including chronic diseases and mortality. Recent evidence suggests that UPF may accelerate biological ageing, potentially explaining their harmful effects. Therefore, this study was aimed to investigate associations between UPF intake categories and mortality risk, examining biological ageing's mediating and modifying effects.

Discovery and Validation of Novel Biomarkers for Colorectal Neoplasia Detection via Plasma Metabolomics.

Metabolic disturbance plays a critical role in the initiation of colorectal cancer (CRC), yet the identification of metabolites that are useful for early detection of CRC and its precursor lesions remains elusive. We conducted an untargeted plasma metabolomic profiling by liquid chromatography-mass spectrometry in a two-stage case-control study, including 219 CRC cases, 164 colorectal adenoma (CRA) cases, and 219 normal controls (NC) as a training set, and 91 CRC, 115 CRA, and 109 NC as a validation set. Among 891 named metabolites, 239 were significantly altered in CRC versus NC, 26 in CRA versus NC, and 88 in CRC versus CRA within the training set.

Comprehensive Characterization of Somatic Mutation Timing Reveals the Evolutionary Trajectory of Lung Adenocarcinoma in Chinese Patients.

Unlabelled: Lung adenocarcinoma (LUAD) is a heterogeneous disease with substantial genomic differences between individuals of Chinese and European ancestries. Deciphering the timing of driver mutations may lead to insights into tumor evolution that can inform diagnostic and therapeutic approaches for LUAD. In this study, we conducted whole-genome sequencing on LUAD samples from 251 patients with Chinese ancestry to reconstruct the evolutionary trajectories of somatic alterations, especially those across the noncoding regions.

Genomic Analyses Reveal the Evolving Characteristics of Intestinal Metaplasia and Gastric Cancer.

Unlabelled: Intestinal metaplasia (IM) represents a precancerous condition associated with an increased risk of gastric cancer. A better understanding of whether and how precancerous lesions progress to gastric cancer is crucial for patient stratification and personalized prevention. In this study, we reconstruct evolutionary trajectories of genomic alterations in 330 multiregion matched samples of IM and tumors from 93 patients with gastric cancer.

Single-cell eQTL mapping reveals cell-type-specific genes associated with the risk of gastric cancer.

Most expression quantitative trait locus (eQTL) analyses have been conducted in heterogeneous gastric tissues, limiting understanding of cell-type-specific regulatory mechanisms. Here, we employed a pooled multiplexing strategy to profile 399,683 gastric cells from 203 Chinese individuals using single-cell RNA sequencing (scRNA-seq). We identified 19 distinct gastric cell types and performed eQTL analyses, uncovering 8,498 independent eQTLs, with a considerable fraction (81%, 6,909/8,498) exhibiting cell-type-specific effects.

Polygenic risk scores for pan-cancer risk prediction in the Chinese population: A population-based cohort study based on the China Kadoorie Biobank.

Background: Polygenic risk scores (PRSs) have been extensively developed for cancer risk prediction in European populations, but their effectiveness in the Chinese population remains uncertain.

Methods And Findings: We constructed 80 PRSs for the 13 most common cancers using seven schemes and evaluated these PRSs in 100,219 participants from the China Kadoorie Biobank (CKB). The optimal PRSs with the highest discriminatory ability were used to define genetic risk, and their site-specific and cross-cancer associations were assessed.

Development and validation of a transcription factor regulatory network-based signature for individualized prognostic risk in lung adenocarcinoma.

Despite significant progress in diagnostic and therapeutic modalities, lung adenocarcinoma (LUAD) still exhibits a high recurrence risk and a low 5-year survival rate. Reliable prognostic signatures are imperative for risk stratification in LUAD patients. This study encompassed 2740 patients from 23 LUAD cohorts, including one single-cell RNA sequencing (scRNA-seq) dataset, five bulk RNA-seq datasets, and 17 microarray datasets.

Effect of Long-Term Fine Particulate Matter Exposure on Lung Cancer Incidence and Mortality in Chinese Nonsmokers.

The association between fine particulate matter (particulate matter ⩽2.5 μm in aerodynamic diameter, PM) and lung cancer incidence in nonsmokers (LCINS) remains inconsistent. To investigate the association between long-term PM exposure and LCINS in a Chinese population and to assess the modifying effect of genetic factors.

Massively parallel variant-to-function mapping determines functional regulatory variants of non-small cell lung cancer.

Genome-wide association studies have identified thousands of genetic variants associated with non-small cell lung cancer (NSCLC), however, it is still challenging to determine the causal variants and to improve disease risk prediction. Here, we applied massively parallel reporter assays to perform NSCLC variant-to-function mapping at scale. A total of 1249 candidate variants were evaluated, and 30 potential causal variants within 12 loci were identified.

Development and validation of a novel artificial intelligence algorithm for precise prediction the postoperative prognosis of esophageal squamous cell carcinoma.

Background: Esophageal squamous cell carcinoma (ESCC) is a highly aggressive malignancy, and current postoperative prognostic assessment methods remain unsatisfactory, underlining the urgent to develop a reliable approach for precision medicine. Given the similarities with gametogenesis, cancer/testis genes (CTGs) are acknowledged for regulation unrestrained multiplication and immune microenvironment during oncogenic processes. These processes are associated with advanced disease and poorer prognosis, indicating that CTGs could serve as ideal prognostic biomarkers in ESCC.

Novel Genetic Loci Associated with PhenoAge Acceleration - Changzhou City, Jiangsu Province, China, 2012-2019.

What Is Already Known About This Topic?: China is rapidly encountering population aging, yet studies on aging are limited by the traditional aging measure: chronological age, particularly in the field of genomics. Several promising aging measures have been proposed, but they lack comparative evaluation.

What Is Added By This Report?: PhenoAge was identified as a measure of aging that demonstrated greater applicability in contemporary populations.

The Association Between Plasma Fatty Acids and Risk of Lung Cancer: A Prospective Cohort Study of the UK Biobank.

Context: Fatty acids (FAs) have emerged as significant contributors to tumorigenesis, yet prospective evidence regarding their specific effects on lung cancer risk remains scarce.

Objective: To investigate the association between plasma FAs and lung cancer incidence, as well as a potential modification effect of genetic susceptibility on lung cancer risk.

Methods: A cohort study was conducted involving 112 547 cancer-free participants from the UK Biobank, with measurements of plasma FAs, including saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (PUFAs), at baseline (2006-2010).

Development and evaluation of a risk prediction tool for risk-adapted screening of colorectal cancer in China.

Risk prediction tools for colorectal cancer (CRC) have potential to improve the efficiency of population-based screening by facilitating risk-adapted strategies. However, such an applicable tool has yet to be established in the Chinese population. In this study, a risk score was created using data from the China Kadoorie Biobank (CKB), a nationwide cohort study of 409,854 eligible participants.

Associations of combined phenotypic aging and genetic risk with incident cancer: A prospective cohort study.

Background: Age is the most important risk factor for cancer, but aging rates are heterogeneous across individuals. We explored a new measure of aging-Phenotypic Age (PhenoAge)-in the risk prediction of site-specific and overall cancer.

Methods: Using Cox regression models, we examined the association of Phenotypic Age Acceleration (PhenoAgeAccel) with cancer incidence by genetic risk group among 374,463 participants from the UK Biobank.

DNA methylation marker identification and poly-methylation risk score in prediction of healthspan termination.

To elucidate the epigenetic consequences of DNA methylation in healthspan termination (HST), considering the current limited understanding. Genetically predicted DNA methylation models were established (n = 2478). These models were applied to genome-wide association study data on HST.

Associations between sleep-behavioral traits and healthspan: A one-sample Mendelian randomization study based on 388,909 participants of the UK-Biobank.

Background: Although the association between sleep behavior and morbidity and mortality risk has been reported before, there is still uncertainty whether the observed associations are causal or confounding. Therefore, we investigated the causal relationships between sleep-behavioral traits and terminated healthspan risk using Mendelian randomization (MR).

Methods: We conducted a one-sample MR analysis to evaluate causality between six sleep-behavioral traits (sleep duration, chronotype/morningness, napping, sleeplessness/insomnia, and getting up from bed) and risk of healthspan termination among 388, 909 UK Biobank (UKB) participants.

Identification of genetically predicted DNA methylation markers associated with non-small cell lung cancer risk among 34,964 cases and 448,579 controls.

Background: Although the associations between genetic variations and lung cancer risk have been explored, the epigenetic consequences of DNA methylation in lung cancer development are largely unknown. Here, the genetically predicted DNA methylation markers associated with non-small cell lung cancer (NSCLC) risk by a two-stage case-control design were investigated.

Methods: The genetic prediction models for methylation levels based on genetic and methylation data of 1595 subjects from the Framingham Heart Study were established.