Biology subjects

Dong, S.-S.

Publications and source records attributed to Dong, S.-S..

10 recordsLinked to original sources

bioRxiv2026

A modular architecture of human cellular aging across organs and diseases

Aging is a heterogeneous biological process in which different cellular systems undergo molecular remodeling at distinct rates, yet whether human cellular aging follows an organized architecture across organs remains unclear. Here, we integrate a multi-organ human single-cell transcriptomic atlas with plasma proteomic profiles from approximately 50,000 participants to reconstruct cellular aging states at population scale. By projecting cell-type-enriched molecular signatures onto circulating proteins, we characterize aging patterns across 128 organ-cell type pairs and identify 14 cellular aging modules comprising conserved cross-organ programs and organ-specific aging states. These modules reveal cellular identity as a dominant organizing axis of human aging that transcends anatomical boundaries. Module-level aging states uncover substantial inter-individual heterogeneity, with 34% of individuals exhibiting extreme aging deviation in at least one cellular module. Cellular aging modules exhibit distinct temporal trajectories, with structural and tissue-resident modules showing earlier remodeling than immune lineages. The modular organization of cellular aging is reflected in disease susceptibility, with accelerated aging of specific modules, particularly epithelial aging, showing broad associations with disease burden and mortality. Longitudinal analyses further demonstrate the stability and clinical relevance of cellular aging states, whereas lifestyle, metabolic and pharmacological factors show selective relationships with individual aging programs. Together, our study establishes a modular framework for understanding human cellular aging and reveals an organization of biological aging that may help explain individual differences in healthspan.

cell biology↗

bioRxiv2024

Comprehensive profiling of transcriptional regulation in cartilage reveals pathogenesis of osteoarthritis

Cartilage damage is a leading cause of osteoarthritis (OA) etiology, however, the underlying mechanism governing gene expression regulation in this progress is poorly understood. Here, we described a comprehensive profiling of transcriptional regulation of 235 primary human cartilage samples. We identified 3,352 independent significant expression quantitative trait loci (eQTLs) for 3,109 genes. We explored the candidate casual SNP and its underlying regulatory mechanism using our established functional fine-mapping pipeline by integrating the cartilage-specific ATAC-seq data. We identified 117 causal eQTLs that display allele-specific open chromatin (ASoC) and 547 transcription factor binding-disruption (TBD) eQTLs. We conducted cell type-interaction eQTL (ci-eQTL) analyses based on speculated chondrocyte subtype proportions and revealed the regulation relationship of 120 eQTL-gene pairs showed cell type dependency. Further, by integrating with genome-wide association studies (GWASs) data of OA, we nominated 43 candidate effector genes for OA risk loci. We verified that the T allele of the OA risk variant rs11750646 increased the AR binding affinity to an open chromatin region and promoted the expression of an OA-related gene PIK3R1. Altogether, our findings provide new insights into the unique regulatory landscape of cartilage and elucidate potential mechanisms underlying the OA pathogenesis.

genetics↗

bioRxiv2021

Novel Roles of G-quadruplexes on Enhancers in human chromatin

G-quadruplexes (G4), stable four-stranded non-canonical DNA structures, are highly related to function of promoters and initiation of gene transcription. We found that G4 structures were also enriched in the enhancers across different cell lines. However, the relationship between G4 structures and enhancer activity remains unknown. Here, we proved that G4 structures on enhancers lead to the re-positioning of nucleosomes create nucleosome depleted regions (NDRs). Moreover, stable NDRs and special secondary structures of G4 help enhancers to recruit abundant TFs to co-bind, especially for architectural proteins including CTCF, RAD21, and SMC3. These architectural proteins, which play critical roles in the formation of higher-order chromatin organization, further influenced the chromatin interactions of G4 enhancers. Additionally, we revealed that G4 enhancers harbored significantly higher enrichment of eQTLs than typical enhancers, suggesting G4 enhancers displayed more enhancer regulatory activity. We found that most super enhancers (SEs) contain G4 structures. Even though the enrichment of chromatin accessibility and histone modifications around G4-containing SEs are not significantly higher than those around other SEs, G4-containing SEs still possess much more TFs across different cell lines. According to these results, we proposed a model in which the formation of G4 structures on enhancer exclude nucleosome occupancy and recruit abundant TFs which lead to the stable chromatin interaction between G4 enhancers and their target genes. Because of the relevance between G4 structures and enhancers, we hypothesized that G4 structures may be a potential markers indicating enhancer regulatory activity.

bioinformatics↗

bioRxiv2021

Brain image-derived phenotypes yield insights into causal risk of psychiatric disorders using a Mendelian randomization study

Brain imaging-derived phenotypes (IDPs) serve as underlying functional intermediates in psychiatric disorders, both of which are highly polygenic and heritable. Observational studies have elucidated the correlation between IDPs and psychiatric disorders, yet no systematic screening of IDPs to confer the causal liability in such disorders. We conducted a bidirectional two-sample Mendelian randomization framework to explore the causality of 1,901 IDPs on 10 psychiatric disorders and established the BrainMR database (http://brainmr.online/idp2psy/Index.php). We identified 17 causalities in forward MR analyses and 14 causalities in reverse MR analyses, which all rigorously examined them through various sensitivity analyses. The top significant relationship in forward was a unit lower volume of right central lateral of the thalamic nuclei, which was causally associated with an increased anorexia nervosa risk with an estimated OR of 0.52 (95% CI 0.41-0.64, P = 3.32 x 10-9). In reverse, the top significant IDP to be affected was the area of superior segment of the circular sulcus of the insula in the right hemisphere, which was increased by the reason of SCZ risk with an estimated association effect size of 0.068 (95% CI 0.046-0.090, P = 1.12 x 10-6). Overall, our study provides unique insights into causal pathways of psychiatric disorders at the imaging levels.

neuroscience↗

bioRxiv2020

LDBlockShow: a fast and convenient tool for visualizing linkage disequilibrium and haplotype blocks based on variant call format files

The triangular correlation heatmap aiming to visualize the linkage disequilibrium (LD) pattern and haplotype block structure of SNPs is ubiquitous component of population-based genetic studies. However, current tools suffered from the problem of time and memory consuming, and direct calculation from variant call format (VCF) files is not supported. Here we developed LDBlockShow, an open source software, for visualizing LD and haplotype blocks from VCF files. It is time and memory saving. In a test dataset with 100 SNPs from 60,000 subjects, it was at least 429.03 times faster and used only 0.04% - 20.00% of physical memory as compared to other tools. In addition, it could generate figures that simultaneously display additional statistical context (e.g., association P values) and genomic region annotations. It can also compress the SVG files with large number of SNPs and support subgroup analysis. This fast and convenient tool would facilitate the visualization of LD and haplotype blocks for geneticists.

bioinformatics↗

bioRxiv2020

Phenome-wide investigation of the causal associations between childhood BMI and adult outcomes: A two-sample Mendelian randomization study

BackgroundCompelling observational studies have reported that childhood obesity is associated with the risk of many complex diseases in adulthood. However, results from observational studies are unable to fully account for confounding factors. The causal effects of childhood obesity have not been systematically characterized. We aimed to assess the causal associations between childhood body mass index (BMI) and various adult traits/diseases using two-sample Mendelian randomization (MR). Methods and findingsOver 5,000 datasets for adult outcomes were obtained from various resources. After data filtering, 269 adult traits genetically correlated with childhood BMI (P < 0.05) were subjected to MR analyses. The number of independent outcomes was 148, setting the significant threshold as P < 3.38 x 10-4. Inverse-variance weighted method, MR-Egger, weighted median method, and weighted mode method were used to estimate the causal effects. We identified potential causal effects of childhood obesity on 60 adult traits (27 disease-related traits, 27 lifestyle factors, and 6 other traits). Higher childhood BMI was associated with a reduced overall health rating ({beta} = -0.10, 95% CI: -0.13 to -0.07, P = 6.26 x 10-11). Findings on diseases included some novel effects, such as the adverse effects of higher childhood BMI on cholelithiasis (OR = 1.26, 95% CI: 1.18 to 1.35, P = 3.29 x 10-5). For dietary habits, we found that higher childhood BMI was positively associated adult diet portion size ({beta} = 0.26, 95% CI: 0.18 to 0.34, P = 7.34 x 10-11). Different from the conventional impression, our results showed that higher childhood BMI was positively associated with low calorie density food intake. With 76 adult BMI single-nucleotide polymorphisms (SNPs) as instruments, we confirmed that adulthood BMI was positively associated with heel bone mineral density. However, the association no longer present after excluding the SNPs existing in or in linkage disequilibrium (LD) with childhood BMI. Network MR analyses suggested that past tobacco smoking and portion size mediated 6.39% and 10.90% of the associations between childhood BMI and type 2 diabetes, respectively. The main study limitation is that it is difficult to tease out the independent effects of childhood BMI due to the strong correlation between childhood and adulthood BMI. ConclusionsIn summary, we provided a phenome-wide view of the effects of childhood BMI on adult traits. Our results highlight the need to intervene in childhood to reduce obesity from a young age and its later-life effects. Author summaryWhy was this study done? O_LIChildhood obesity is a worldwide public health problem. The prevalence has increased at an alarming rate. C_LIO_LIObservational epidemiological studies have reported that childhood obesity is associated with the risk of many complex diseases in adulthood, such as coronary artery disease (CAD) and diabetes. However, observational studies are limited in explaining causality because of possible bias from unmeasured confounding factors. C_LI What did the researchers do and find? O_LIA Mendelian randomization (MR) approach was used to provide a phenome-wide view of the causal associations between childhood BMI and adult outcomes. Potential causal effects of childhood obesity on 60 adult traits were identified. C_LIO_LIHigher childhood BMI was associated with reduced overall health rating, and caused increased risk of some diseases, such as cholelithiasis, hypothyroidism, CAD, and type 2 diabetes (T2D). In contrast, childhood BMI was positively associated with adult heel bone mineral density and low calorie density food intake. C_LIO_LIPortion size and smoking behavior might mediate the association between childhood BMI and T2D risk. C_LI What do these findings mean? O_LIOur results highlight the importance to address rising childhood obesity prevalence rate and early interventions on obesity might help to promote health equity in later life. C_LI

genetics↗

bioRxiv2020

3D chromatin organization changes modulate adipogenesis and osteogenesis

Human mesenchymal stem cells (hMSCs) can be differentiated into adipocytes and osteoblasts. While the transcriptomic and epigenomic changes during adipogenesis and osteogenesis have been characterized, what happens to the chromatin loops is hardly known. Here we induced hMSCs to adipogenic and osteogenic differentiation, and performed 2 kb resolution Hi-C experiments for loop detection and generated RNA-seq, histone modification ChIP-seq and ATAC-seq data for integrative analysis before and after differentiation. We quantitatively identified differential contact loops and unique loops. After integrating with multi-omics data, we demonstrate that strengthened loops after differentiation are associated with gene expression activation. Specially, unique loops are linked with cell fate determination. We also proposed loop-mediated regulatory networks and identified IRS2 and RUNX2 as being activated by cell-specific loops to facilitate adipocytes and osteoblasts commitment, respectively. These results are expected to help better understand the long-range regulation in controlling hMSC differentiation, and provide novel targets for studying adipocytes and osteoblasts determination.

genetics↗

bioRxiv2019

Dissecting molecular regulatory mechanisms underlying noncoding susceptibility SNPs associated with 19 autoimmune diseases using multi-omics integrative analysis

The genome-wide association studies (GWAS) have identified hundreds of susceptibility loci associated with autoimmune diseases. However, over 90% of risk variants are located in the noncoding regions, leading to great challenges in deciphering the underlying causal functional variants/genes and biological mechanisms. Previous studies focused on developing new scoring method to prioritize functional/disease-relevant variants. However, they principally incorporated annotation data across all cells/tissues while omitted the cell-specific or context-specific regulation. Moreover, limited analyses were performed to dissect the detailed molecular regulatory circuits linking functional GWAS variants to disease etiology. Here we devised a new analysis frame that incorporate hundreds of immune cell-specific multi-omics data to prioritize functional noncoding susceptibility SNPs with gene targets and further dissect their downstream molecular mechanisms and clinical applications for 19 autoimmune diseases. Most prioritized SNPs have genetic associations with transcription factors (TFs) binding, histone modification or chromatin accessibility, indicating their allelic regulatory roles on target genes. Their target genes were significantly enriched in immunologically related pathways and other immunologically related functions. We also detected long-range regulation on 90.7% of target genes including 132 ones exclusively regulated by distal SNPs (eg, CD28, IL2RA), which involves several potential key TFs (eg, CTCF), suggesting the important roles of long-range chromatin interaction in autoimmune diseases. Moreover, we identified hundreds of known or predicted druggable genes, and predicted some new potential drug targets for several autoimmune diseases, including two genes (NFKB1, SH2B3) with known drug indications on other diseases, highlighting their potential drug repurposing opportunities. In summary, our analyses may provide unique resource for future functional follow-up and drug application on autoimmune diseases, which are freely available at http://fngwas.online/. Author SummaryAutoimmune diseases are groups of complex immune system disorders with high prevalence rates and high heritabilities. Previous studies have unraveled thousands of SNPs associated with different autoimmune diseases. However, it remains largely unknown on the molecular mechanisms underlying these genetic associations. Striking, over 90% of risk SNPs are located in the noncoding region. By leveraging multiple immune cell-specific multi-omics data across genomic, epigenetic, transcriptomic and 3D chromatin interaction information, we systematically analyzed the functional variants/genes and biological mechanisms underlying genetic association on 19 autoimmune diseases. We found that most functional SNPs may affect target gene expression through altering transcription factors (TFs) binding, histone modification or chromatin accessibility. Most target genes had known immunological functions. We detected prevailing long-range chromatin interaction linking distal functional SNPs to target genes. We also identified many known drug targets and predicted some new drug target genes for several autoimmune diseases, suggesting their potential clinical applications. All analysis results and tools are available online, which may provide unique resource for future functional follow-up and drug application. Our study may help reduce the gap between traditional genetic findings and biological mechanistically exploration of disease etiologies as well as clinical drug development.

immunology↗

bioRxiv2019

An allele-specific functional SNP associated with two autoimmune diseases modulates IRF5 expression by long-range chromatin loop formation

Both Systemic Lupus Erythematosus (SLE) and Systemic Sclerosis (SSc) are autoimmune diseases sharing similar genetic backgrounds. Genome-wide association studies (GWASs) have constantly disclosed numerous genetic variants conferring to both disease risks at 7q32.1, but the functional mechanisms underlying them are still largely unknown. Through combining fine-mapping and functional epigenomic analyses, we prioritized a potential independent functional SNP (rs13239597) within TNPO3 promoter region, residing in a putative enhancer element. Functional analysis integrating expression quantitative trait locus (eQTL) and high-throughput chromatin interaction (Hi-C) demonstrated that IRF5 is the distal target gene (~118kb) of rs13239597, which is a key regulator of pathogenic autoantibody dysregulation increased risk of both SLE and SSc. We experimentally validated the long-range chromatin interactions between rs13239597 and IRF5 using chromosome conformation capture (3C) assay. We further demonstrated that rs13239597-A acted as an allele-specific enhancer regulating IRF5 expression, independently of TNPO3 by using dual-luciferase reporter assays and CRISPR-Cas9. Particularly, the transcription factor EVI1 could preferentially bind to rs13239597-A allele and increase the enhancer activity to regulate IRF5 expression. Taken together, our results uncovered the mechanistic insight connecting between a noncoding functional variant with a distal immunologically pathogenic gene IRF5, which might obligate in understanding the complex genetic architectures of SLE and SSc pathogenesis.

genetics↗

bioRxiv2018

Modeling circRNAs expression pattern with integrated sequence and epigenetic features identifies H3K79me2 as regulators for circRNAs expression

Circular RNAs (circRNAs) are an abundant class of noncoding RNAs with widespread, cell/tissue specific pattern. Because of their involvement in the pathogenesis of multiple disease, they are receiving increasing attention. Previous work suggested that epigenetic features might be related to circRNA expression. However, current algorithms for circRNAs prediction neglect these features, leading to constant results across different cells.\n\nHere we built a machine learning framework named CIRCScan, to predict expression status and expression levels of circRNAs in various cell lines based on sequence and epigenetic features. Both expression status and expression levels can be accurately predicted by different groups of features. For expression status, the top features were similar in different cells. However, the top features for predicting expression levels were different in different cells. Noteworthy, the importance of H3K79me2 ranked high in predicting both circRNAs expression status and levels across different cells, indicating its important role in regulating circRNAs expression. Further validation experiment in K562 confirmed that knock down of H3K79me2 did result in reduction of circRNA production.\n\nOur study offers new insights into the regulation of circRNAs by incorporating epigenetic features in prediction models in different cellular contexts.

bioinformatics↗