Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2022

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global research in both academia and industry. With the explosively accumulated multi-omics data at ever-faster rates, CNCB-NGDC is constantly scaling up and updating its core database resources through big data archive, curation, integration and analysis. In the past year, efforts have been made to synthesize the growing data and knowledge, particularly in single-cell omics and precision medicine research, and a series of resources have been newly developed, updated and enhanced. Moreover, CNCB-NGDC has continued to daily update SARS-CoV-2 genome sequences, variants, haplotypes and literature. Particularly, OpenLB, an open library of bioscience, has been established by providing easy and open access to a substantial number of abstract texts from PubMed, bioRxiv and medRxiv. In addition, Database Commons is significantly updated by cataloguing a full list of global databases, and BLAST tools are newly deployed to provide online sequence search services. All these resources along with their services are publicly accessible at https://ngdc.cncb.ac.cn.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a suite of database resources to support worldwide research activities in both academia and industry. With the explosive growth of multi-omics data, CNCB-NGDC is continually expanding, updating and enriching its core database resources through big data deposition, integration and translation. In the past year, considerable efforts have been devoted to 2019nCoVR, a newly established resource providing a global landscape of SARS-CoV-2 genomic sequences, variants, and haplotypes, as well as Aging Atlas, BrainBase, GTDB (Glycosyltransferases Database), LncExpDB, and TransCirc (Translation potential for circular RNAs). Meanwhile, a series of resources have been updated and improved, including BioProject, BioSample, GWH (Genome Warehouse), GVM (Genome Variation Map), GEN (Gene Expression Nebulas) as well as several biodiversity and plant resources. Particularly, BIG Search, a scalable, one-stop, cross-database search engine, has been significantly updated by providing easy access to a large number of internal and external biological resources from CNCB-NGDC, our partners, EBI and NCBI. All of these resources along with their services are publicly accessible at https://bigd.big.ac.cn.

Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2023

The National Genomics Data Center (NGDC), part of the China National Center for Bioinformation (CNCB), provides a family of database resources to support global academic and industrial communities. With the explosive accumulation of multi-omics data generated at an unprecedented rate, CNCB-NGDC constantly expands and updates core database resources by big data archive, integrative analysis and value-added curation. In the past year, efforts have been devoted to integrating multiple omics data, synthesizing the growing knowledge, developing new resources and upgrading a set of major resources. Particularly, several database resources are newly developed for infectious diseases and microbiology (MPoxVR, KGCoV, ProPan), cancer-trait association (ASCancer Atlas, TWAS Atlas, Brain Catalog, CCAS) as well as tropical plants (TCOD). Importantly, given the global health threat caused by monkeypox virus and SARS-CoV-2, CNCB-NGDC has newly constructed the monkeypox virus resource, along with frequent updates of SARS-CoV-2 genome sequences, variants as well as haplotypes. All the resources and services are publicly accessible at https://ngdc.cncb.ac.cn.

EWAS Open Platform: integrated data, knowledge and toolkit for epigenome-wide association study

Epigenome-Wide Association Study (EWAS) has become a standard strategy to discover DNA methylation variation of different phenotypes. Since 2018, we have developed EWAS Atlas and EWAS Data Hub to integrate a growing volume of EWAS knowledge and data, respectively. Here, we present EWAS Open Platform (https://ngdc.cncb.ac.cn/ewas) that includes EWAS Atlas, EWAS Data Hub and the newly developed EWAS Toolkit. In the current implementation, EWAS Open Platform integrates 617 018 high-quality EWAS associations from 910 publications, covering 51 phenotypes, 275 diseases and 104 environmental factors. It also provides well-normalized DNA methylation array data and the corresponding metadata from 115 852 samples, which involve 707 tissues, 218 cell lines and 528 diseases. Taking advantage of integrated knowledge and data in EWAS Atlas and EWAS Data Hub, EWAS Open Platform equips with EWAS Toolkit, a powerful one-stop site for EWAS enrichment, annotation, and knowledge network construction and visualization. Collectively, EWAS Open Platform provides open access to EWAS knowledge, data and toolkit and thus bears great utility for a broader range of relevant research.

Reduction of false arterial blood pressure alarms using signal quality assessment and relationships between the electrocardiogram and arterial blood pressure

The paper presents an algorithm for reducing false alarms related to changes in arterial blood pressure (ABP) in intensive care unit (ICU) monitoring. The algorithm assesses the ABP signal quality, analyses the relationship between the electrocardiogram and ABP using a fuzzy logic approach and post-processes (accepts or rejects) ABP alarms produced by a commercial monitor. The algorithm was developed and evaluated using unrelated sets of data from the MIMIC database. By rejecting 98.2% (159 of 162) of the false ABP alarms produced by the monitor using the test set of data, the algorithm was able to reduce the false ABP alarm rate from 26.8% to 0.5% of ABP alarms, while accepting 99.8% (441 of 442) of true ABP alarms. The results show that the algorithm is effective and practical, and its use in future patient monitoring systems is feasible.

Phenotypic analysis of atopic dermatitis in children aged 1-12 months: elaboration of novel diagnostic criteria for infants in China and estimation of prevalence

BACKGROUND

Atopic dermatitis (AD) is the most common skin disorder in infancy. However, the diagnosis and definite significance of infantile AD remains a debated issue.

OBJECTIVE

To analyse the phenotypes of AD in infancy, to establish diagnostic criteria and to estimate the prevalence of this condition in China.

METHODS

This is a multicentric study, in which 12 locations were chosen from different metropolitan areas of China. Following careful and complete history-taking and skin examination, the definite diagnosis of AD was made and the severity based on the SCORAD index was determined by local experienced dermatologists. Based on the detailed phenotyping, the major and representative clinical features of infantile AD were selected to establish the diagnostic criteria and evaluate their diagnostic efficacy.

RESULTS

A total of 5967 infants were included in this study. The overall point prevalence of AD was 30.48%. The infantile AD developed as early as at the second month of life, and its incidence peaked in the third month of life at 40.81%. The proportion of mild, moderate and severe AD was 67.40%, 30.57% and 2.03%, respectively. The most commonly seen manifestations in the infantile AD were facial dermatitis (72.07%), xerosis (42.72%) and scalp dermatitis (27.93%). We established the novel diagnostic criteria of infants, which included: (i) onset after 2 weeks of birth; (ii) pruritus and/or irritability and sleeplessness comparable with lesions; and (iii) all two items above with one of the following items can reach a diagnosis of AD: (i) eczematous lesions distributed on cheeks and/or scalp and/or extensor limbs, and (ii) eczematous lesions on any other parts of body accompanied by xerosis.

CONCLUSIONS

In China, the prevalence of AD in infancy is 30.48% according to clinical diagnosis of dermatologists. The novel Chinese diagnostic criteria for AD in infants show a higher sensitivity and comparable specificity.

Contribution of visceral fat accumulation to carotid intima-media thickness in a Chinese population

Objective:

Recent observational studies have reported that body fat distribution might be differentially associated with subclinical atherosclerosis. We previously reported that visceral fat area (VFA) ⩾80 cm² is the optimal cutoff for identifying abdominal obesity in Chinese subjects. We examined whether VFA ⩾80 cm² reflects the association between abdominal obesity and subclinical atherosclerosis, and if determination of the visceral fat quantity is useful for assessing subclinical atherosclerosis in asymptomatic individuals.

Methods and results:

Participants (N=1005, men 515, women 490, 34–66 years) free of cardiovascular disease underwent magnetic resonance imaging and carotid ultrasound assessment to quantify VFA and carotid intima–media thickness (C-IMT). Overweight/obese subjects (body mass index (BMI) ⩾25.0 kg m⁻²) had a higher C-IMT than lean subjects (BMI <25.0 kg m⁻²) (P<0.01). Subjects with VFA ⩾80 cm² had significantly higher C-IMT than those without abdominal obesity regardless of BMI (P<0.01). By multivariate regression analysis adjusted for anthropometric measurements and cardiovascular risk factors, waist circumference but not BMI was independently correlated with C-IMT in men (P<0.001). Similar findings were observed with an accurate obesity indices adjusted model, which showed that VFA was an independent risk factor for increased C-IMT in men but not in women.

Conclusions:

VFA ⩾80 cm² effectively identified carotid atherosclerosis for both lean and obese individuals in middle-aged Chinese men.

Gene Expression Nebulas (GEN): a comprehensive data portal integrating transcriptomic profiles across multiple species at both bulk and single-cell levels

Transcriptomic profiling is critical to uncovering functional elements from transcriptional and post-transcriptional aspects. Here, we present Gene Expression Nebulas (GEN, https://ngdc.cncb.ac.cn/gen/), an open-access data portal integrating transcriptomic profiles under various biological contexts. GEN features a curated collection of high-quality bulk and single-cell RNA sequencing datasets by using standardized data processing pipelines and a structured curation model. Currently, GEN houses a large number of gene expression profiles from 323 datasets (157 bulk and 166 single-cell), covering 50 500 samples and 15 540 169 cells across 30 species, which are further categorized into six biological contexts. Moreover, GEN integrates a full range of transcriptomic profiles on expression, RNA editing and alternative splicing for 10 bulk datasets, providing opportunities for users to conduct integrative analysis at both transcriptional and post-transcriptional levels. In addition, GEN provides abundant gene annotations based on value-added curation of transcriptomic profiles and delivers online services for data analysis and visualization. Collectively, GEN presents a comprehensive collection of transcriptomic profiles across multiple species, thus serving as a fundamental resource for better understanding genetic regulatory architecture and functional mechanisms from tissues to cells.

scMethBank: a database for single-cell whole genome DNA methylation maps

Single-cell bisulfite sequencing methods are widely used to assess epigenomic heterogeneity in cell states. Over the past few years, large amounts of data have been generated and facilitated deeper understanding of the epigenetic regulation of many key biological processes including early embryonic development, cell differentiation and tumor progression. It is an urgent need to build a functional resource platform with the massive amount of data. Here, we present scMethBank, the first open access and comprehensive database dedicated to the collection, integration, analysis and visualization of single-cell DNA methylation data and metadata. Current release of scMethBank includes processed single-cell bisulfite sequencing data and curated metadata of 8328 samples derived from 15 public single-cell datasets, involving two species (human and mouse), 29 cell types and two diseases. In summary, scMethBank aims to assist researchers who are interested in cell heterogeneity to explore and utilize whole genome methylation data at single-cell level by providing browse, search, visualization, download functions and user-friendly online tools. The database is accessible at: https://ngdc.cncb.ac.cn/methbank/scm/.

Evaluation of back scatter interferometry, a method for detecting protein binding in solution

Back Scatter Interferometry (BSI) has been proposed to be a highly sensitive and versatile refractive index sensor usable for analytical detection of biomarker and protein interactions in solution. However the existing literature on BSI lacks a physical explanation of why protein interactions in general should contribute to the BSI signal. We have established a BSI system to investigate this subject in further detail. We contribute with a thorough analysis of the robustness of the sensor including unwanted contributions to the interferometric signal caused by temperature variation and dissolved gasses. We report a limit of the effective minimum detectability of refractive index at the 10(-7) level. Long term stability was examined by simultaneously monitoring the temperature inside the capillary revealing an average drift of 2.0 × 10(-7) per hour. Finally we show that measurements on protein A incubated with immunoglobulin G do not result in a signal that can be attributed to binding affinities as otherwise claimed in literature.

Cell Taxonomy: a curated repository of cell types with multifaceted characterization

Single-cell studies have delineated cellular diversity and uncovered increasing numbers of previously uncharacterized cell types in complex tissues. Thus, synthesizing growing knowledge of cellular characteristics is critical for dissecting cellular heterogeneity, developmental processes and tumorigenesis at single-cell resolution. Here, we present Cell Taxonomy (https://ngdc.cncb.ac.cn/celltaxonomy), a comprehensive and curated repository of cell types and associated cell markers encompassing a wide range of species, tissues and conditions. Combined with literature curation and data integration, the current version of Cell Taxonomy establishes a well-structured taxonomy for 3,143 cell types and houses a comprehensive collection of 26,613 associated cell markers in 257 conditions and 387 tissues across 34 species. Based on 4,299 publications and single-cell transcriptomic profiles of ∼3.5 million cells, Cell Taxonomy features multifaceted characterization for cell types and cell markers, involving quality assessment of cell markers and cell clusters, cross-species comparison, cell composition of tissues and cellular similarity based on markers. Taken together, Cell Taxonomy represents a fundamentally useful reference to systematically and accurately characterize cell types and thus lays an important foundation for deeply understanding and exploring cellular biology in diverse species.

MethBank 4.0: an updated database of DNA methylation across a variety of species

DNA methylation, as the most intensively studied epigenetic mark, regulates gene expression in numerous biological processes including development, aging, and disease. With the rapid accumulation of whole-genome bisulfite sequencing data, integrating, archiving, analyzing, and visualizing those data becomes critical. Since its first publication in 2015, MethBank has been continuously updated to include more DNA methylomes across more diverse species. Here, we present MethBank 4.0 (https://ngdc.cncb.ac.cn/methbank/), which reports an increase of 309% in data volume, with 1449 single-base resolution methylomes of 23 species, covering 236 tissues/cell lines and 15 biological contexts. Value-added information, such as more rigorous quality evaluation, more standardized metadata, and comprehensive downstream annotations have been integrated in the new version. Moreover, expert-curated knowledge modules of featured differentially methylated genes associated with biological contexts and methylation analysis tools have been incorporated as new components of MethBank. In addition, MethBank 4.0 is equipped with a series of new web interfaces to browse, search, and visualize DNA methylation profiles and related information. With all these improvements, we believe the updated MethBank 4.0 will serve as a fundamental resource to provide a wide range of data services for the global research community.

ASCancer Atlas: a comprehensive knowledgebase of alternative splicing in human cancers

Alternative splicing (AS) is a fundamental process that governs almost all aspects of cellular functions, and dysregulation in this process has been implicated in tumor initiation, progression and treatment resistance. With accumulating studies of carcinogenic mis-splicing in cancers, there is an urgent demand to integrate cancer-associated splicing changes to better understand their internal cross-talks and functional consequences from a global view. However, a resource of key functional AS events in human cancers is still lacking. To fill the gap, we developed ASCancer Atlas (https://ngdc.cncb.ac.cn/ascancer), a comprehensive knowledgebase of aberrant splicing in human cancers. Compared to extant databases, ASCancer Atlas features a high-confidence collection of 2006 cancer-associated splicing events experimentally proved to promote tumorigenesis, a systematic splicing regulatory network, and a suit of multi-scale online analysis tools. For each event, we manually curated the functional axis including upstream splicing regulators, splicing event annotations, downstream oncogenic effects, and possible therapeutic strategies. ASCancer Atlas also houses about 2 million computationally putative splicing events. Additionally, a user-friendly web interface was built to enable users to easily browse, search, visualize, analyze, and download all splicing events. Overall, ASCancer Atlas provides a unique resource to study the functional roles of splicing dysregulation in human cancers.

Knowledge-based and Data-driven Models in Arrhythmia Fuzzy Classification

Objectives: Fuzzy rules automatically derived from a set of training examples quite often produce better classification results than fuzzy rules translated from medical knowledge. This study aims to investigate the difference in domain representation between a knowledge-based and a data-driven fuzzy system applied to an electrocardiography classification problem.

Methods: For a three-class electrocardiographic arrhythmia classification task a set of fifteen fuzzy rules is derived from medical expertise on the basis of twelve electrocardiographic measures. A second set of fuzzy rules is automatically constructed on thirty-nine MIT-BIH database’s records. The performances of the two classifiers on thirteen different records are comparable and up to a certain extent complementary. The two fuzzy models are then analyzed, by using the concept of information gain to estimate the impact of each ECG measure on each fuzzy decision process.

Results: Both systems rely on the beat prematurity degree and the QRS complex width and neglect the P wave existence and the ST segment features. The PR interval is not well characterized across the fuzzy medical rules while it plays an important role in the data-driven fuzzy system. The T wave area shows a higher information gain in the knowledge based decision process, and is not very much exploited by the data-driven system.

Conclusions: The main difference between a human designed and a data driven ECG arrhythmia classifier is found about the PR interval and the T wave.

dc-Sheet resistance as sensitive monitoring tool of protein immobilization on thin metal films

The suitability of high resolution, in situ dc-sheet resistance monitoring (SRM) as a simplified and reliable sensing technique towards detection and tracking of protein immobilization has been explored. Non-specific adsorption of bovine serum albumin (BSA) onto a very thin gold film, acting as the sensing resistor, has been employed as a model system. For comparison, the novel sensing method was combined with surface plasmon resonance (SPR) spectroscopy, using the same flow cell and sensing surface. Two different, well known adsorption states, involving a composite layer of irreversibly and reversibly bound BSA, were clearly resolved by both methods. Clearly structured, pronounced and fully reproducible film resistance modulations have been resolved in the associated SRM data. The transition from reversibly bound BSA to the diluted protein phase is associated with an unusually large decrease in the dc-sheet resistance. The observed resistance modulation magnitude for an adsorbed BSA monolayer corresponds to approximately 1%, and up to 100 mOmega at a 10 Omega sensing resistor. The sheet resistance of irreversibly bound BSA was determined to 0.24 kOmega/cm2, and the associated specific resistivity estimated to 1-2x10(4) Omega cm.

Increment of 30-min post-challenge plasma glucose is associated with urine albumin excretion in men with normal glucose regulation

AIMS

The overwhelming majority of subjects with normal glucose regulation have the highest plasma glucose concentration at 30 minutes during oral glucose tolerance. We aimed to examine the association between increment of 30-min post-challenge glucose and albuminuria in participants with normal glucose regulation.

METHODS

A population-based cross-sectional study was conducted in six communities in Shanghai between 2007 and 2008. A total of 3508 subjects with normal glucose regulation had complete data and were enrolled into the analysis. Among the selected subjects, only 1525 individuals (581 men, 944 women) were examined for their serum insulin levels. We assessed post-challenge blood glucose and insulin at 0, 30 and 120 min, urinary albumin and creatinine. The 30-min post-challenge glucose increment (Δ) was calculated as 30-min post-challenge glucose minus fasting plasma glucose, and albumin/creatinine ratio was used to reflect urinary albumin excretion.

RESULTS

Multivariable logistic regression analysis revealed that the Δ30-min post-challenge glucose was independently associated with increased albumin/creatinine ratio in men with normal glucose regulation (OR = 1.08, P = 0.025), but not in women. Furthermore, multivariable linear regression analysis revealed that early-phase glucose disposition index was the main factor responsible for Δ30-min post-challenge glucose and explained 14-20% of the variance of Δ30-min post-challenge glucose in the two subgroups (P < 0.05). Notably, men had higher Δ30-min post-challenge glucose and lower early-phase glucose disposition index than women (all P < 0.001).

CONCLUSIONS

The 30-min post-challenge plasma glucose increment is associated with urine albumin excretion in men with normal glucose regulation.

Optical biosensor with dispersion compensation

Dispersion limits performance in many optical systems. In surface plasmon resonance (SPR) biosensors, the sensing area is an optical element in which the dispersion depends on the effective refractive index of the biochemical compounds to be measured. We report a method of compensating for wavelength dispersion in SPR biosensors employing two integrated diffractive optical coupling elements in a polymer substrate. The dispersion compensation is achieved over the whole dynamic measurement range and provides a biosensor more robust to wavelength fluctuations than prism-coupler SPR systems. The concept can readily be employed in other types of sensor measuring refractive-index changes.

A Comprehensive Benchmark of Transcriptomic Biomarkers for Immune Checkpoint Blockades

Immune checkpoint blockades (ICBs) have revolutionized cancer therapy by inducing durable clinical responses, but only a small percentage of patients can benefit from ICB treatments. Many studies have established various biomarkers to predict ICB responses. However, different biomarkers were found with diverse performances in practice, and a timely and unbiased assessment has yet to be conducted due to the complexity of ICB-related studies and trials. In this study, we manually curated 29 published datasets with matched transcriptome and clinical data from more than 1400 patients, and uniformly preprocessed these datasets for further analyses. In addition, we collected 39 sets of transcriptomic biomarkers, and based on the nature of the corresponding computational methods, we categorized them into the gene-set-like group (with the self-contained design and the competitive design, respectively) and the deconvolution-like group. Next, we investigated the correlations and patterns of these biomarkers and utilized a standardized workflow to systematically evaluate their performance in predicting ICB responses and survival statuses across different datasets, cancer types, antibodies, biopsy times, and combinatory treatments. In our benchmark, most biomarkers showed poor performance in terms of stability and robustness across different datasets. Two scores (TIDE and CYT) had a competitive performance for ICB response prediction, and two others (PASS-ON and EIGS_ssGSEA) showed the best association with clinical outcome. Finally, we developed ICB-Portal to host the datasets, biomarkers, and benchmark results and to implement the computational methods for researchers to test their custom biomarkers. Our work provided valuable resources and a one-stop solution to facilitate ICB-related research.

An automated, web-enabled and searchable database system for archiving electrogram and related data from implantable cardioverter defibrillators

The advent of implantable cardioverter defibrillators (ICDs) has resulted in significant reductions in mortality in patients at high risk for sudden cardiac death. Extensive related basic research and clinical investigation continue. ICDs typically record intracardiac electrograms and inter-beat intervals along with device settings during episodes of device delivery of therapy. Researchers wishing to study these data further have until now been limited to viewing paper plots. In support of multi-center clinical studies of patients with ICDs, we have developed a web based searchable ICD data archiving system, which allows users to use a web browser to upload ICD data from diskettes to a server where the data are automatically processed and archived. Users can view and download the archived ICD data directly via the web. The entire system is built from open source software. At present more than 500 patient ICD data sets have been uploaded to and archived in the system. This project will be of value not only to those who wish to conduct research using ICD data, but also to clinicians who need to archive and review ICD data collected from their patients.