Biological age (BA) has been proposed to evaluate the aging status instead of chronological age (CA). Our study shows evidence that there might be multiple "clocks" within the whole-body system: systemic aging drivers/clocks overlaid with organ/tissue-specific counterparts. We utilize multi-omics data, including clinical tests, immune repertoire, targeted metabolomic molecules, gut microbiomes, physical fitness examinations, and facial skin examinations, to estimate the BA of different organs (e.g., liver, kidney) and systems (immune and metabolic system). The aging rates of organs/systems are diverse. People's aging patterns are different. We also demonstrate several applications of organs/systems BA in two independent datasets. Mortality predictions are compared among organs' BA in the dataset of the United States National Health and Nutrition Examination Survey. Polygenic risk score of BAs constructed in the Chinese Longitudinal Healthy Longevity Survey cohort can predict the possibility of becoming centenarian.

Background: Single-cell resequencing (SCRS) provides many biomedical advances in variations detection at the single-cell level, but it currently relies on whole genome amplification (WGA). Three methods are commonly used for WGA: multiple displacement amplification (MDA), degenerate-oligonucleotide-primed PCR (DOP-PCR) and multiple annealing and looping-based amplification cycles (MALBAC). However, a comprehensive comparison of variations detection performance between these WGA methods has not yet been performed. Results: We systematically compared the advantages and disadvantages of different WGA methods, focusing particularly on variations detection. Low-coverage whole-genome sequencing revealed that DOP-PCR had the highest duplication ratio, but an even read distribution and the best reproducibility and accuracy for detection of copy-number variations (CNVs). However, MDA had significantly higher genome recovery sensitivity (~84 %) than DOP-PCR (~6 %) and MALBAC (~52 %) at high sequencing depth. MALBAC and MDA had comparable single-nucleotide variations detection efficiency, false-positive ratio, and allele drop-out ratio. We further demonstrated that SCRS data amplified by either MDA or MALBAC from a gastric cancer cell line could accurately detect gastric cancer CNVs with comparable sensitivity and specificity, including amplifications of 12p11.22 (KRAS) and 9p24.1 (JAK2, CD274, and PDCD1LG2). Conclusions: Our findings provide a comprehensive comparison of variations detection performance using SCRS amplified by different WGA methods. It will guide researchers to determine which WGA method is best suited to individual experimental needs at single-cell level.

Background. Cancers arise through an evolutionary process in which cell populations are subjected to selection; however, to date, the process of bladder

Background. Next generation sequencing (NGS) is now being used for detecting chromosomal abnormalities in blastocyst trophectoderm (TE) cells from in v

Neurodegenerative diseases encompass a wide variety of pathological conditions caused by a loss of neurons in the central nervous system (CNS) and are severely debilitating. Exosome contains bio-signatures of great diagnostic and therapeutic value. There is proof that exosomal proteins can be biomarkers for Alzheimer’s disease (AD) and Parkinson’s disease (PD). MicroRNAs in exosome has potential to be an important source of biomarkers for neurodegenerative diseases. Here, we report exosomal microRNA performance of human plasma in neurodegenerative diseases by small RNA sequencing. A wide range of altered exo-miRNA expression levels were detected in both AD and PD patients. Down-regulated miRNAs in AD samples were enriched in ECM-receptor interaction pathway and both up-/down-regulated miRNAs in PD samples were enriched in fatty acid biosynthesis pathway. Compared to the control, 8 miRNAs were found to be significantly elevated/declined in AD and PD samples, of which 4 miRNAs were newly identified. Additionally, two exosome isolating methods were compared and the reproducibility of plasma exo-miRNA expression was confirmed, suggesting the feasibility of large-scale clinical application of this method. This study revealed exo-miRNA expression levels in neurodegenerative diseases, proposed new biomarkers and their potential functional pathway for AD and PD, confirmed the reproductivity of exo-miRNA profiles by using a different exosome isolating method, and compared the results with plasma miRNA expression. Therefore, this study also provides a precedent for identifying exosomal biomarkers of neurodegenerative diseases in plasma by high-throughput sequencing and it could extend the therapeutic repertoire of exosomal biomarkers.

Epigenetic alterations, such as aberrant DNA methylation of promoter and enhancer regions, which lead to atypical gene expression, have been associated with carcinogenesis. In hepatocellular carcinoma (HCC), genome-wide analysis of methylation has only recently been used. For a better understanding of hepatocarcinogenesis, we applied an even higher resolution analysis of the promoter methylome to identify previously unknown regions and genes differentially methylated in HCC. Optimized liquid hybridization capture-based bisulfite sequencing (LHC-BS) was developed to quantitatively analyze 1.86 million CpG sites in individual samples from eight pairs of HCC and adjacent tissues. By linking the differentially methylated regions (DMRs) in promoters to the differentially expressed genes (DEGs), we identified 12 DMR-associated genes. We further utilized Illumina MiSeq combining the bisulfite sequencing PCR approach to validate the 12 candidate genes. Analysis of an additional 78 HCC pairs on the Illumina MiSeq platform confirmed that 7 genes showed either promoter hyper-methylation (SMAD6, IFITM1, LRRC4, CHST4, and TBX15) or hypo-methylation (CCL20 and NQO1) in HCC. Novel methylome profiling provides a cost-efficient approach to identifying candidate genes in human HCC that may contribute to hepatocarcinogenesis. Our work provides further information critical for understanding the epigenetic processes underlying tumorigenesis and development of HCC.