Publications by authors named "Fengji Liang"

13 Publications

  • Page 1 of 1

Mining the Selective Remodeling of DNA Methylation in Promoter Regions to Identify Robust Gene-Level Associations With Phenotype.

Front Mol Biosci 2021 26;8:597513. Epub 2021 Mar 26.

Lab of Epigenetics and Advanced Health Technology, Space Science and Technology Institute, Shenzhen, China.

Epigenetics is an essential biological frontier linking genetics to the environment, where DNA methylation is one of the most studied epigenetic events. In recent years, through the epigenome-wide association study (EWAS), researchers have identified thousands of phenotype-related methylation sites. However, the overlaps of identified phenotype-related DNA methylation sites between various studies are often quite small, and it might be due to the fact that methylation remodeling has a certain degree of randomness within the genome. Thus, the identification of robust gene-phenotype associations is crucial to interpreting pathogenesis. How to integrate the methylation values of different sites on the same gene and to mine the DNA methylation at the gene level remains a challenge. A recent study found that the DNA methylation difference of the gene body and promoter region has a strong correlation with gene expression. In this study, we proposed a Statistical difference of DNA Methylation between Promoter and Other Body Region (SIMPO) algorithm to extract DNA methylation values at the gene level. First, by choosing to smoke as an environmental exposure factor, our method led to significant improvements in gene overlaps (from 5 to 17%) between different datasets. In addition, the biological significance of phenotype-related genes identified by SIMPO algorithm is comparable to that of the traditional probe-based methods. Then, we selected two disease contents (e.g., insulin resistance and Parkinson's disease) to show that the biological efficiency of disease-related gene identification increased from 15.43 to 44.44% (-value = 1.20e-28). In summary, our results declare that mining the selective remodeling of DNA methylation in promoter regions can identify robust gene-level associations with phenotype, and the characteristic remodeling of a given gene's promoter region can reflect the essence of disease.
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http://dx.doi.org/10.3389/fmolb.2021.597513DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8034267PMC
March 2021

Blood Cell DNA Methylation of Aging-Related Ubiquitination Gene Can Predict the Onset of Early Stage Colorectal Cancer.

Front Oncol 2020 27;10:544330. Epub 2020 Nov 27.

Lab of Epigenetics and Advanced Health Technology, Space Science and Technology Institute (Shenzhen), Shenzhen, China.

There is a body of evidence that the aging immune system is linked to cancer. In this study, with aging- and immune-related DNA methylation data, we investigated the DNA methylation regulation changes in promoters with other regions of genes during aging and their association with the immune-cell proportion in the circulating whole blood of individuals. The analyses for aging- and CD4+ T cell proportion-derived differential genes showed that ubiquitination plays an important role in the aging immune system and tumorigenesis. Therefore, starting from a set of pre-annotated ubiquitination genes, we found that among the differentially ubiquitinated genes, , an E3 ubiquitin ligase with no reports on its function in immune cells and tumorigenesis, was significantly associated with both aging (P-value = 3.86e-06) and CD4+ T cell proportion (P-value = 1.97e-05) in circulating blood. By collecting a cohort of 100 colon cancer patients and 50 healthy individuals, we validated that the 1 exon DNA methylation of could predict the onset of early stage (AUC = 0.833, OR = 8.82) and all pTNM stages of colorectal cancer (AUC = 0.782, OR = 5.70). Thus, the epigenetically regulated ubiquitination machine plays an important role in immune aging and tumorigenesis.
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http://dx.doi.org/10.3389/fonc.2020.544330DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7729090PMC
November 2020

Physiological Acclimatization of the Liver to 180-Day Isolation and the Mars Solar Day.

Biomed Res Int 2020 21;2020:2796510. Epub 2020 Mar 21.

State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, 26 Beiqing Road, Haidian District, Beijing, China.

Physiological changes in humans are evident under environmental conditions similar to those on a Mars mission involving both a space factor (long-term isolation) and a time factor (the Mars solar day). However, very few studies have investigated the response of the liver to those conditions. Serum protein levels, bilirubin levels, aminotransferase activities, blood alkaline phosphatase, gamma-glutamyltransferase, lipid levels, and serum cytokines interleukin-6 and interferon- levels were analyzed 30 days before the mock mission; on days 2, 30, 60, 75, 90, 105, 120, 150, and 175 of the mission; and 30 days after the mission, in four subjects in 4-person 180-day Controlled Ecological Life Support System Experiment. Serum protein levels (total protein and globulin) decreased and bilirubin increased under the isolation environment from day 2 and exhibited chronic acclimatization from days 30 to 175. Effects of the Mars solar day were evident on day 75. Blood lipid levels were somewhat affected. No obvious peak in any enzyme level was detected during the mission. The change tendency of these results indicated that future studies should explore whether protein parameters especially globulin could serve as indicators of immunological function exposure to the stress of a Mars mission.
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http://dx.doi.org/10.1155/2020/2796510DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7115137PMC
January 2021

Insulin-resistance and depression cohort data mining to identify nutraceutical related DNA methylation biomarker for type 2 diabetes.

Genes Dis 2021 Sep 27;8(5):669-676. Epub 2020 Jan 27.

Lab of Epigenetics and Advanced Health Technology, SPACEnter Space Science and Technology Institute, Shenzhen, Guangdong Province, 518117, PR China.

Insulin-resistance (IR) is one of the most important precursors of type 2 diabetes (T2D). Recent evidence suggests an association of depression with the onset of T2D. Accumulating evidence shows that depression and T2D share common biological origins, and DNA methylation examination might reveal the link between lifestyle, disease risk, and potential therapeutic targets for T2D. Here we hypothesize that integrative mining of IR and depression cohort data will facilitate predictive biomarkers identification for T2D. We utilized a newly proposed method to extract gene-level information from probe level data on genome-wide DNA methylation array. We identified a set of genes associated with IR and depression in clinical cohorts. By overlapping the IR-related nutraceutical-gene network with depression networks, we identified a common subnetwork centered with Vitamin D Receptor (VDR) gene. Preliminary clinical validation of gene methylation set in a small cohort of T2D patients and controls was established using the Sequenome matrix-assisted laser desorption ionization-time flight mass spectrometry. A set of sites in the promoter regions of VDR showed a significant difference between T2D patients and controls. Using a logistic regression model, the optimal prediction performance of these sites was AUC = 0.902,and an odds ratio = 19.76. Thus, monitoring the methylation status of specific VDR promoter region might help stratify the high-risk individuals who could potentially benefit from vitamin D dietary supplementation. Our results highlight the link between IR and depression, and the DNA methylation analysis might facilitate the search for their shared mechanisms in the etiology of T2D.
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http://dx.doi.org/10.1016/j.gendis.2020.01.013DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278533PMC
September 2021

Personalized Epigenome Remodeling Under Biochemical and Psychological Changes During Long-Term Isolation Environment.

Front Physiol 2019 31;10:932. Epub 2019 Jul 31.

State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, China.

It has been reported that several aspects of human health could be disturbed during a long-term isolated environment (for instance, the Mars-500 mission), including psychiatric disorders, circadian disruption, temporal dynamics of gut microbiota, immune responses, and physical-activity-related neuromuscular performance. Nevertheless, the mechanisms underlying these disturbances and the interactions among different aspects of human adaptation to extreme environments remain to be elucidated. Epigenetic features, like DNA methylation, might be a linking mechanism that explains the involvement of environmental factors between the human genome and the outcome of health. We conducted an exploration of personalized longitudinal DNA methylation patterns of the peripheral whole blood cells, profiling six subjects across six sampling points in the Mars-500 mission. Specifically, we developed a Personalized Epigenetic-Phenotype Synchronization Analysis (PeSa) algorithm to explore glucose- and mood-state-synchronized DNA methylation sites, focusing on finding the dynamic associations between epigenetic patterns and phenotypes in each individual, and exploring the underling epigenetic connections between glucose and mood-state disturbance. Results showed that DMPs (differentially methylated-probes) were significantly enriched in pathways related to glucose metabolism (Type II diabetes mellitus pathway), mood state (Long-term depression) and circadian rhythm (Circadian entrainment pathway) during the mission. Furthermore, our data revealed individualized glucose-synchronized and mood-state-synchronized DNA methylation sites, and PTPRN2 was found to be associated with both glucose and mood state disturbances across all six subjects. Our findings suggest that personalized phenotype-synchronized epigenetic features could reflect the effects on the human body, including the disturbances of glucose and mood-states. The association analysis of DNA methylation and phenotypes, like the PeSa analysis, could provide new possibilities in understanding the intrinsic relationship between phenotypic changes of the human body adapting to long-term isolation environmental factors.
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http://dx.doi.org/10.3389/fphys.2019.00932DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684777PMC
July 2019

Integrated Analysis of DNA Methylation and Biochemical/Metabolic Parameter During the Long-Term Isolation Environment.

Front Physiol 2019 24;10:917. Epub 2019 Jul 24.

State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, China.

Numerous studies have shown that changes in the epigenome are an important cause of human biochemical or metabolic parameter changes. Biochemical/metabolic parameter disorders of the human body are usually closely related to the occurrence of disease. Therefore, constructing credible DNA methylation site-biochemical/metabolic parameter associations are key in interpreting the pathogenesis of diseases. However, there is a lack of research on systematic integration analysis of DNA methylation with biochemical/metabolic parameter and diseases. In this study, we attempted to use the four-people, multiple time point detected data from the long-term isolation experiment to conduct a correlation analysis. We used the biclustering algorithm FABIA to cluster the DNA methylation site-parameter correlation matrixes into 28 biclusters. The results of the biological function analysis for these biclusters were consistent with the biochemical/metabolic parameter change characteristics of the human body during long-term isolation, demonstrating the reliability of the biclusters identified by our method. In addition, from these biclusters, we obtained highly credible biochemical/metabolic parameter-disease associations, which is supported by several studies. Our results indicate that there is an overlap of biochemical/metabolic parameter-disease associations derived from a small sample, multiple time point data in healthy populations and the associations obtained from a large sample data in patients during disease development. These findings provide insights into understanding the role of the epigenome in biochemical/metabolic parameter change and disease development and has potential applications in biology and medicine research.
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http://dx.doi.org/10.3389/fphys.2019.00917DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6676193PMC
July 2019

Expression profiles and functional annotation analysis of mRNAs in suprachiasmatic nucleus of Clock mutant mice.

Gene 2018 Mar 5;647:107-114. Epub 2018 Jan 5.

State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing 100094, China. Electronic address:

The core circadian clock gene, Clock, is a positive component of the transcription/translation feedback loop in the master pacemaker suprachiasmatic nucleus (SCN) in mammals. The robust daytime peak of some clock genes in the wild-type SCN is absent in Clock mutant mice. However, very little is known about the impact of Clock mutation on the expression of other functional genes in SCN. Here, we performed cDNA microarray and found 799 differentially expressed genes (DEGs) at zeitgeber time 2 (ZT2) and 1289 DEGs at ZT14 in SCN of Clock mutant mice. KEGG pathway analysis showed that the changed mRNAs were highly associated with hedgehog signaling pathway, retinol metabolism, allograft rejection, drug metabolism, hematopoietic cell lineage and neuroactive ligand-receptor interaction. The top 14 and 71 hub genes were identified from the protein-protein interaction (PPI) network at ZT2 and ZT14, respectively. The sub-networks revealed hub genes were involved in olfactory transduction and neuroactive ligand-receptor interaction pathways. These results demonstrate the Clock mutation alters the expression of various genes involved in a wide spectrum of biological function in mouse SCN, which are helpful for better understanding the function of Clock and potential regulatory mechanisms.
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http://dx.doi.org/10.1016/j.gene.2017.12.056DOI Listing
March 2018

Circulating microRNAs Correlated with Bone Loss Induced by 45 Days of Bed Rest.

Front Physiol 2017 14;8:69. Epub 2017 Feb 14.

State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center Beijing, China.

The purpose of this study was to find the circulating microRNAs (miRNAs) co-related with bone loss induced by bed rest, and testify whether the selected miRNAs could reflect the bone mineral status of human after bed-rest. We analyzed plasma miRNA levels of 16 subjects after 45 days of -6° head-down tilt bed rest, which is a reliable model for the simulation of microgravity. We characterize the circulating miRNA profile in individuals after bed rest and identify circulating miRNAs which can best reflect the level of bone loss induced by bed rest. Expression profiling of circulating miRNA revealed significant downregulation of 37 miRNAs and upregulation of 2 miRNAs, while only 11 of the downregulated miRNAs were further validated in a larger volunteer cohort using qPCR. We found that 10 of these 11 miRNAs (miR-103, 130a, 1234, 1290, 151-5p, 151-3p, 199a-3p, 20a, 363, and 451a) had ROC curve that distinguished the status after bed rest. Importantly, significant positive correlations were identified between bone loss parameters and several miRNAs, eventually miR-1234 showed clinical significance in detecting the bone loss of individuals after 45 days of bed rest.
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http://dx.doi.org/10.3389/fphys.2017.00069DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5306370PMC
February 2017

Functional constraints on adaptive evolution of protein ubiquitination sites.

Sci Rep 2017 01 5;7:39949. Epub 2017 Jan 5.

State Key Laboratory of Proteomics, Beijing Proteome Research Center, Beijing Institute of Radiation Medicine, 27 Taiping Road, Beijing 100850, China.

It is still unclear whether there exist functional constraints on the evolution of protein ubiquitination sites, because most previous studies regarded all protein ubiquitination sites as a whole or only focused on limited structural properties. We tried to clarify the relation between functional constraints and ubiquitination sites evolution. We investigated the evolutionary conservation of human ubiquitination sites in a broad evolutionary scale from G. gorilla to S. pombe, and we found that in organisms originated after the divergence of vertebrate, ubiquitination sites are more conserved than their flanking regions, while the opposite tendency is observed before this divergence time. By grouping the ubiquitination proteins into different functional categories, we confirm that many functional constraints like certain molecular functions, protein tissue expression specificity and protein connectivity in protein-protein interaction network enhance the evolutionary conservation of ubiquitination sites. Furthermore, by analyzing the gains of ubiquitination sites at different divergence time and their functional characters, we validate that the emergences of ubiquitination sites at different evolutionary time were also affected by the uncovered functional constraints. The above results suggest that functional constraints on the adaptive evolution of ubiquitination sites increase the opportunity for ubiquitination to synthetically regulate various cellular and developmental processes during evolution.
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http://dx.doi.org/10.1038/srep39949DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5215434PMC
January 2017

Activation of HIF-1α and its downstream targets in rat hippocampus after long-term simulated microgravity exposure.

Biochem Biophys Res Commun 2017 Apr 14;485(3):591-597. Epub 2016 Dec 14.

State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center, Beijing, 100094, China. Electronic address:

Microgravity has many detrimental impact on brain functions, however the underlying mechanism remain unclear. In present study, 28 days of tail-suspension (30°) was used to simulate microgravity in rats. We showed that oxidative stress in hippocampus was increased after 28 days of simulated microgravity in consideration of the decreased expression of NF-E2-related factor 2 (Nrf2) and the declined activities of total superoxide dismutase (T-SOD), CuZn-SOD, glutathione peroxidase (GSH-PX) and total antioxidant capacity (T-AOC). Using RNA-seq, we further investigated the effect of simulated microgravity on the expression of genes in hippocampus, and 849 genes were found to be differentially expressed. According to pathway analysis, the differentially expressed genes involved in cytoskeleton, metabolism, immunity, transcription regulation, etc. It is interesting to note that the differentially expressed genes were involved in hypoxia-associated pathway. In agreement with this, the expression of hypoxia induced factor-1α (HIF-1α), the master regulator of oxygen homeostasis, was significantly increased. Meanwhile, HIF-2α, a HIF-1α paralog, was elevated compared with the control group. The expression of pyruvate dehydrogenase kinase 1 (PDK1), lactate dehydrogenase A (LDHA) and vascular endothelial growth factor (VEGF), three well-defined downstream targets of HIF-1α, were up-regulated in hippocampus after 28 days of simulated microgravity exposure. Additionally, brain oxygen saturation (SO) and blood flow analyzed by the tissue oxygen analysis system were also significantly reduced. These findings indicate that simulated microgravity might cause an alteration in oxygen homeostasis, providing novel insight into better understanding of how simulated microgravity affects the function of hippocampus and a new direction to the development of countermeasure for brain dysfunction during spaceflight (actual microgravity).
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http://dx.doi.org/10.1016/j.bbrc.2016.12.078DOI Listing
April 2017

Comparison of the Prognostic Utility of the Diverse Molecular Data among lncRNA, DNA Methylation, microRNA, and mRNA across Five Human Cancers.

PLoS One 2015 25;10(11):e0142433. Epub 2015 Nov 25.

State Key Laboratory of Space Medicine Fundamentals and Application, Space Institute of Southern China, China Astronaut Research and Training Center, Beijing, China.

Introduction: Advances in high-throughput technologies have generated diverse informative molecular markers for cancer outcome prediction. Long non-coding RNA (lncRNA) and DNA methylation as new classes of promising markers are emerging as key molecules in human cancers; however, the prognostic utility of such diverse molecular data remains to be explored.

Materials And Methods: We proposed a computational pipeline (IDFO) to predict patient survival by identifying prognosis-related biomarkers using multi-type molecular data (mRNA, microRNA, DNA methylation, and lncRNA) from 3198 samples of five cancer types. We assessed the predictive performance of both single molecular data and integrated multi-type molecular data in patient survival stratification, and compared their relative importance in each type of cancer, respectively. Survival analysis using multivariate Cox regression was performed to investigate the impact of the IDFO-identified markers and traditional variables on clinical outcome.

Results: Using the IDFO approach, we obtained good predictive performance of the molecular datasets (bootstrap accuracy: 0.71-0.97) in five cancer types. Impressively, lncRNA was identified as the best prognostic predictor in the validated cohorts of four cancer types, followed by DNA methylation, mRNA, and then microRNA. We found the incorporating of multi-type molecular data showed similar predictive power to single-type molecular data, but with the exception of the lncRNA + DNA methylation combinations in two cancers. Survival analysis of proportional hazard models confirmed a high robustness for lncRNA and DNA methylation as prognosis factors independent of traditional clinical variables.

Conclusion: Our study provides insight into systematically understanding the prognostic performance of diverse molecular data in both single and aggregate patterns, which may have specific reference to subsequent related studies.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0142433PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4659652PMC
June 2016

Predicting response to preoperative chemotherapy agents by identifying drug action on modeled microRNA regulation networks.

PLoS One 2014 21;9(5):e98140. Epub 2014 May 21.

State Key Lab of Space Medicine Fundamentals and Application (SMFA), China Astronaut Research and Training Center (ACC), Beijing, P. R. China; The CUHK-ACC Space Medicine Centre on Health Maintenance of Musculoskeletal System, The Chinese University of Hong Kong Shenzhen Research Institute, Shenzhen, China.

Identifying patients most responsive to specific chemotherapy agents in neoadjuvant settings can help to maximize the benefits of treatment and minimize unnecessary side effects. Metagene approaches that predict response based on gene expression signatures derived from an associative analysis of clinical data can identify chance associations caused by the heterogeneity of a tumor, leading to reproducibility issues in independent validations. In this study, to incorporate information from drug mechanisms of action, we explore the potential of microRNA regulation networks as a new feature space for identifying predictive markers. We introduce a measure we term the CoMi (Context-specific-miRNA-regulation) pattern to represent a descriptive feature of the miRNA regulation network in the transcriptome. We examine whether the modifications to the CoMi pattern on specific biological processes are a useful representation of drug action by predicting the response to neoadjuvant Paclitaxel treatment in breast cancer and show that the drug counteracts the CoMi network dysregulation induced by tumorigenesis. We then generate a quantitative testbed to investigate the ability of the CoMi pattern to distinguish FDA approved breast cancer drugs from other FDA approved drugs not related to breast cancer. We also compare the ability of the CoMi and metagene methods to predict response to neoadjuvant Paclitaxel treatment in clinical cohorts. We find the CoMi method outperforms the metagene method, achieving area under curve (AUC) values of 0.78 and 0.66 respectively. Furthermore, several of the predicted CoMi features highlight the network-based mechanism of drug resistance. Thus, our study suggests that explicitly modeling the drug action using network biology provides a promising approach for predictive marker discovery.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0098140PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4029965PMC
January 2015
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