Cohort profile for the Tongji Cardiovascular Health Study: a prospective multiomics cohort study.

Purpose: The Tongji Cardiovascular Health Study aimed to further explore the onset and progression mechanisms of cardiovascular disease (CVD) through a combination of traditional cohort studies and multiomics analysis, including genomics, metabolomics and metagenomics.

Study Design And Participants: This study included participants aged 20-70 years old from the Geriatric Health Management Centre of Tongji Hospital of Tongji Medical College of Huazhong University of Science and Technology. After enrollment, each participant underwent a comprehensive series of traditional and novel cardiovascular risk factor assessments at baseline, including questionnaires, physical examinations, laboratory tests, cardiovascular health assessments and biological sample collection for subsequent multiomics analysis (whole genome sequencing, metabolomics study from blood samples and metagenomics study from stool samples).

Sex-specific equations to estimate body composition: Derivation and validation of diagnostic prediction models using UK Biobank.

Background & Aims: Body mass index and waist circumference are simple measures of obesity. However, they do not distinguish between visceral and subcutaneous fat, or muscle, potentially leading to biased relationships between individual body composition parameters and adverse health outcomes. The purpose of this study was to develop and validate prediction models for volumetric adipose and muscle.

A population-based study of precision health assessments using multi-omics network-derived biological functional modules.

Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm.

Machine learning improves risk stratification of coronary heart disease and stroke.

Background: Coronary heart disease (CHD) and cerebral ischemic stroke (CIS) are two major types of cardiovascular disease (CVD) that are increasingly exerting pressure on the healthcare system worldwide. Machine learning holds great promise for improving the accuracy of disease prediction and risk stratification in CVD. However, there is currently no clinically applicable risk stratification model for the Asian population.

Development and validation of a cardiovascular diseases risk prediction model for Chinese males (CVDMCM).

Background: Death due to cardiovascular diseases (CVD) increased significantly in China. One possible way to reduce CVD is to identify people at risk and provide targeted intervention. We aim to develop and validate a CVD risk prediction model for Chinese males (CVDMCM) to help clinicians identify those males at risk of CVD and provide targeted intervention.

Association Between Thromboelastography and Coronary Heart Disease.

BACKGROUND Thromboelastography (TEG) is a novel blood viscoelasticity detection method revealing blood coagulation status and has been reported to be helpful in predicting clinical outcomes in patients with cardiovascular diseases (CVD). In this study, we aimed to investigate the association between TEG and CVD. MATERIAL AND METHODS A single-center case-control study was performed.

Clinical perspectives and concerns of metformin as an anti-aging drug.

As percentages of elderly people rise in many societies, age-related diseases have become more prevalent than ever. Research interests have been shifting to delaying age-related diseases by delaying or reversing aging itself. We use metformin as an entry point to talk about the important molecular and genetic longevity-regulating mechanisms that have been extensively studied with it.

Single-cell transcriptomic landscape of nucleated cells in umbilical cord blood.

Background: For both pediatric and adult patients, umbilical cord blood (UCB) transplant is a therapeutic option for a variety of hematologic diseases, such as blood cancers, myeloproliferative disorders, genetic diseases, and metabolic disorders. However, the level of cellular heterogeneity and diversity of nucleated cells in UCB has not yet been assessed in an unbiased and systemic fashion. In the present study, nucleated cells from UCB were subjected to single-cell RNA sequencing to simultaneously profile the gene expression signatures of thousands of cells, generating a rich resource for further functional studies.

Evolution and Comprehensive Analysis of DNaseI Hypersensitive Sites in Regulatory Regions of Primate Brain-Related Genes.

How the human brain differs from those of non-human primates is largely unknown and the complex drivers underlying such differences at the genomic level remain unclear. In this study, we selected 243 brain-related genes, based on Gene Ontology, and identified 184,113 DNaseI hypersensitive sites (DHSs) within their regulatory regions. To performed comprehensive evolutionary analyses, we set strict filtering criteria for alignment quality and filtered 39,132 DHSs for inclusion in the investigation and found that 2,397 (~6%) exhibited evidence of accelerated evolution (aceDHSs), which was a much higher proportion that DHSs genome-wide.