Hongtao Guo

Dr. Hongtao Guo

orcid

Research Focus & Metrics

Academic Career Length

16Years (2011-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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23 June 2011 in BioData Mining
Verified
Journal Article
Open access
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GZGuang Zheng
Guang Zheng
MJMiao Jiang
Miao Jiang
XHXiaojuan He
Xiaojuan He
JZJing Zhao
Jing Zhao
HGHongtao Guo
Hongtao Guo
ALAiping Lu
Aiping Lu
Background: One important concept in traditional Chinese medicine (TCM) is "treating different diseases with the same therapy". In TCM practice, some patients with Rheumatoid Arthritis (RA) and some other patients with Coronary Heart Disease (CHD) can be treated with similar therapies. This suggests that there might be something commonly existed between RA and CHD, for example, biological networks or biological basis. As the amount of biomedical data in leading databases (i.e., PubMed, SinoMed, etc.) is growing at an exponential rate, it might be possible to get something interesting and meaningful through the techniques developed in data mining.Results: Based on the large data sets of Western medicine literature (PubMed) and traditional Chinese medicine literature (SinoMed), by applying data slicing algorithm in text mining, we retrieved some simple and meaningful networks. The Chinese herbs used in treatment of both RA and CHD, might affect the commonly existed networks between RA and CHD. This might support the TCM concept of treating different diseases with the same therapy.Conclusions: First, the data mining results might show the positive answer that there are biological basis/networks commonly existed in both RA and CHD. Second, there are basic Chinese herbs used in the treatment of both RA and CHD. Third, these commonly existed networks might be affected by the basic Chinese herbs. Forth, discrete derivative, the data slicing algorithm is feasible in mining out useful data from literature of PubMed and SinoMed.

Verified
Journal Article
Open access
PDF file
HGHongtao Guo
Hongtao Guo
XNXuyan Niu
Xuyan Niu
YGYan Gu
Yan Gu
CLCheng Lu
Cheng Lu
CXCheng Xiao
Cheng Xiao
ALAiping Lu
Aiping Lu
Pattern classification is a key approach in Traditional Chinese Medicine (TCM), and it is used to classify the patients for intervention selection accordingly. TCM cold and heat patterns, two main patterns of rheumatoid arthritis (RA) had been explored with systems biology approaches. Different regulations of apoptosis were found to be involved in cold and heat classification in our previous works. For this study, the metabolic profiling of plasma was explored in RA patients with typical TCM cold or heat patterns by integrating liquid chromatography/mass spectrometry (LC/MS) and gas chromatography/mass spectrometry (GC/MS) platforms in conjunction with the Ingenuity Pathway Analysis (IPA) software. Three main processes of metabolism, including amino acid, carbohydrate and lipid were focused on for function analysis. The results showed that 29 and 19 differential metabolites were found in cold and heat patterns respectively, compared with healthy controls. The perturbation of amino acid metabolism (increased essential amino acids), carbohydrate metabolism (galactose metabolism) and lipid metabolism, were found to be involved in both cold and heat pattern RA. In particular, more metabolic perturbations in protein and collagen breakdown, decreased glycolytic activity and aerobic oxidation, and increased energy utilization associated with RA cold pattern patients. These findings may be useful for obtaining a better understanding of RA pathogenesis and for achieving a better efficacy in RA clinical practice.

15 September 2013 in Information Technology Journal
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Journal Article
Closed access
RDRongfen Dong
Rongfen Dong
SSShanshan Shen
Shanshan Shen
BDBaojie Dong
Baojie Dong
LZLi Zhou
Li Zhou
HYHe Yang
He Yang
YWYaoxian Wang
Yaoxian Wang

28 July 2025
Verified
Journal Article
Open access
XDXuewei Dou
Xuewei Dou
WCWenfei Cui
Wenfei Cui
ZHZhenzhen Han
Zhenzhen Han
ZCZhiying Che
Zhiying Che
XLXiaobing Li
Xiaobing Li
HGHongtao Guo
Hongtao Guo
Rheumatoid arthritis (RA) imposes a heavy burden on individuals, families, and society. This study analyzed the incidence and mortality trends of RA in China from 1990 to 2023 to provide epidemiological evidence for precise prevention and control. Data on RA incidence, age-standardized incidence rate (ASIR), deaths, and age-standardized mortality rate (ASMR) in China by sex and age group from 1900 to 2021 were extracted from the Global Burden of Disease (GBD) 2021 database. Joinpoint regression was used to analyze trends in ASIR and ASMR. An age-period-cohort model was constructed using R4.3.1 to evaluate longitudinal age trends and estimate relative risk (RR) values for period and cohort effects. In 2021, the number of RA cases, ASIR, deaths, and ASMR in China were 247 300, 13.70 per 100 000, 10 300, and 0.54 per 100 000, respectively. From 1990 to 2021, the ASIR of RA increased annually among both females and males, with average annual percentage changes (AAPCs) of 0.44% and 0.72%, respectively. Over the same period, ASMR declined in the total population and among females, with AAPCs of -0.78% and -1.19%, while the change in males was not statistically significant. Age-period-cohort analysis showed that the peak incidence occurred in women aged 60-64 years and men aged 75-79 years, and mortality increased with age. The period effect for incidence rose in both sexes, reaching 1.10 [95% confidence interval (CI) 0.94 to 1.27] for females and 1.14 (95% CI 1.02 to 1.27) for males during 2017 to 2021, compared with 2002 to 2006. The mortality period effect RR exhibited a downward-upward-downward pattern, decreasing to 0.56 (95% CI 0.52 to 0.61) in females and 0.75 (95% CI 0.68 to 0.82) in males in 2017 to 2021. Cohort analysis indicated that the highest incidence risk occurred in individuals born during 2012 to 2016, while the cohort effect RR for female RA mortality showed a continuous decline beginning with the 1922 to 1926 birth cohort. The incidence and mortality risks of RA in China have continued to decline. However, with the aging of the population, the incidence and mortality risks among the elderly have increased. Middle-aged women and elderly men should receive focused attention. Health authorities should strengthen education, prevention, and screening among middle-aged women and enhance disease monitoring in elderly populations to reduce the national burden of RA.

19 March 2026 in Frontiers in Genetics
Verified
Journal Article
Open access
XHXu Han
Xu Han
ZHZhenzhen Han
Zhenzhen Han
SWSiyu Wang
Siyu Wang
YZYafei Zhang
Yafei Zhang
YLYing Liu
Ying Liu
MJMiao JIANG
Miao JIANG
Objective: To systematically synthesize Mendelian randomization (MR) evidence exploring causal associations between various exposures and rheumatoid arthritis (RA). Methods: Systematic searches were conducted to identify eligible two-sample MR studies evaluating causal links between exposures and RA. Data extraction encompassed exposure types, genetic instruments, and analytical methods. The quality of evidence was evaluated based on STROBE-MR guidelines and evidence strength grades. Meta-analyses were performed using random-effects model with restricted maximum likelihood estimation and Hartung-Knapp-Sidik-Jonkman confidence intervals to summarize causal estimates. Results: A total of 117 studies were included, comprising 496 MR associations across 248 unique exposures. Of these, 200 exposure-RA associations across 65 unique exposures were eligible for meta-analysis. The primary analysis identified smoking behavior (OR = 1.39, 95% CI 1.30–1.49) and hypothyroidism (OR = 1.55, 1.34–1.81) as significant risk factors with high-quality evidence. While television viewing (OR = 2.27, 1.77–2.90) and cholangitis (OR = 1.14, 1.06–1.23) showed nominal positive associations. Conversely, cognitive function (OR = 0.74, 0.68–0.81) and Interleukins-1 receptor antagonist (OR = 0.82, 95% CI 0.73–0.92) were identified as a nominally protective factor. In subtype analyses, basal metabolic rate emerged as a potential shared risk factor for both seropositive and seronegative RA. Overall, 7.66% and 26.01% of all associations were classified as providing Robust (I) and Probable (II) evidence, respectively. Conclusion: This comprehensive review clarifies the causal landscape of RA by distinguishing between significant causal drivers and potential associations. The findings highlight smoking cessation and thyroid function management as critical, evidence-based targets for RA prevention. However, the high proportion of low-quality evidence underscores the need for future high-quality MR studies to validate weaker signals. Systematic Review Registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024573056 , identifier CRD42024573056.

1 July 2013
Verified
Journal Article
Closed access
LZLin-Lin Zhang
Lin-Lin Zhang
HGHongtao Guo
Hongtao Guo
GZGuang Zheng
Guang Zheng
LLLi-Mei Liu
Li-Mei Liu
ZSZhi-Qian Song
Zhi-Qian Song
ZLZhenli Liu
Zhenli Liu