BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

BACKGROUND:Studies have shown that rheumatoid arthritis and osteoporosis are positively correlated,but the causal relationship and related mechanisms have not yet been confirmed.With the cross-fertilization of computer science and life sciences,Mendelian randomization and bioinformatics analyses based on genome-wide association study(GWAS)and transcriptome sequencing data can assess the causal relationship between two diseases,explore the related mechanisms,and mine the therapeutic targets,which will be beneficial to the precision treatment of rheumatoid arthritis combined with osteoporosis.OBJECTIVE:To explore the causal relationship between rheumatoid arthritis and osteoporosis using two-sample Mendelian randomization and to mine potential co-morbid targets and potential targeted drugs through summary-data-based Mendelian randomization and bioinformatics analyses,aiming to provide theoretical basis for mechanism exploration and precision treatment in the field of rheumatoid arthritis combined with osteoporosis.METHODS:(1)Firstly,GWAS data of rheumatoid arthritis,osteoporosis,and cis-expression quantitative trait locus(cis-eQTL)in Asian and European populations were downloaded from the GWAS Catalog,IEU Open GWAS,FinnGen,and eQTLGen databases,and were used for two-sample Mendelian randomization analysis and summary-data-based Mendelian randomization analysis.(2)Transcriptome sequencing data of rheumatoid arthritis(GSE93272 and GSE15573)were downloaded from the GEO database for bioinformatics analysis.(3)Subsequently,forward and inverse Mendelian randomization analyses between rheumatoid arthritis and osteoporosis were performed,and inverse variance weighted was used as the main metric for the analyses,and the results were corroborated with MR Egger,simple mode,weighted median and weighted mode.(4)Then,the genes closely related to rheumatoid arthritis and osteoporosis were identified based on the summary-data-based Mendelian randomization analysis,and the co-disease targets of rheumatoid arthritis and osteoporosis were mined based on cross-analysis.Meanwhile,the biological functions of the co-morbid targets were verified based on bioinformatics analysis and cellular experiments.(5)In addition,a rheumatoid arthritis risk prediction nomogram was constructed based on DYRK2,and its prediction performance was verified by receiver operating characteristic curve,correction curve and decision curve.Finally,the target potential drugs were mined based on Enrichr database and molecular docking was performed.RESULTS AND CONCLUSION:(1)Forward Mendelian randomization analysis of rheumatoid arthritis and osteoporosis showed statistically significant results except for GCST90044540 and GCST90086118,and all other results indicated a significant causal relationship and positive correlation between rheumatoid arthritis and osteoporosis.(2)Inverse Mendelian randomization analysis suggested that no significant causal relationship was seen between osteoporosis and rheumatoid arthritis.(3)Summary-data-based Mendelian randomization analysis identified a total of 412 and 344 genes positively associated with rheumatoid arthritis and osteoporosis,and 421 and 347 genes negatively associated.Based on the cross-analysis,26 co-morbid genes were subsequently obtained.Among them,DYRK2 was a potential therapeutic target,and subsequent bioinformatics analysis and cellular experiments confirmed its important role in the progression of rheumatoid arthritis and osteoporosis.(4)Furthermore,the constructed nomogram has excellent predictive performance.Finally,four potential DYRK2-targeting drugs(undecanoic acid,metyrapone,JNJ-38877605,and ACA)were discovered and molecular docking also demonstrated reliable targeting ability.(5)In conclusion,based on GWAS data from Asian and European populations,we successfully demonstrated that rheumatoid arthritis and osteoporosis are causally related at the genetic level,DYRK2 is a potential therapeutic target,and four small molecules are potential target drugs.

Objective:To assess the influencing factors of glycemic control among type 2 diabetes mellitus (T2DM) patients, in particular the correlations between peripheral blood eosinophils and metabolic indicators such as glucose, lipids, and uric acid (UA) in these patients.Methods:T2DM patients who were regularly followed up in the Intensive Diabetes Mellitus Clinic of Peking Union Medical College Hospital from January 2016 to September 2024 were prospectively selected as the research subjects. The clinical data of these patients at their first visit and at the 3rd, 6th, 9th, and 12th months of follow-up were collected. The potential correlations of peripheral blood eosinophils with blood glucose control, lipid metabolism, UA metabolism, and inflammation as well as their influencing factors were analyzed.Results:A total of 161 T2DM patients were included. The glycated hemoglobin A1c (HbA1c) compliance rate was significantly higher during the follow-up visits (3, 6, 9, and 12 months) than baseline (all P<0.05) but showed no significant correlation with the count or percentage of peripheral blood eosinophils. Spearman correlation analysis showed that the percentage of peripheral blood eosinophils was negatively correlated with Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) ( P=0.049) and high-density lipoprotein cholesterol (HDL-C) ( P=0.002) and positively with serum triglyceride (TG) ( P=0.034) and UA levels ( P<0.001). A further linear regression model analysis of these four variables and the percentage of eosinophils revealed that the percentage of peripheral blood eosinophils was only linearly correlated with serum UA level ( P<0.001). Conclusion:The percentage of peripheral blood eosinophils in T2DM patients is independently correlated with serum UA level, and monitoring serum UA level is important in T2DM management. Early identification and intervention of hyperuricemia can help provide more comprehensive and precise medical interventions for T2DM patients.

OBJECTIVE: To investigate the associations between eight serum per- and polyfluoroalkyl substances (PFASs) and regional fat depots, we analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2011-2018 cycles. METHODS: Multiple linear regression models were developed to explore the associations between serum PFAS concentrations and six fat compositions along with a fat distribution score created by summing the concentrations of the six fat compositions. The associations between structurally grouped PFASs and fat distribution were assessed, and a prediction model was developed to estimate the ability of PFAS exposure to predict obesity risk. RESULTS: Among females aged 39-59 years, trunk fat mass was positively associated with perfluorooctane sulfonate (PFOS). Higher concentrations of PFOS, perfluorohexane sulfonate (PFHxS), perfluorodecanoate (PFDeA), perfluorononanoate (PFNA), and n-perfluorooctanoate (n-PFOA) were linked to greater visceral adipose tissue in this group. In men, exposure to total perfluoroalkane sulfonates (PFSAs) and long-chain PFSAs was associated with reductions in abdominal fat, while higher abdominal fat in women aged 39-59 years was associated with short-chain PFSAs. The prediction model demonstrated high accuracy, with an area under the curve (AUC) of 0.9925 for predicting obesity risk. CONCLUSION PFAS exposure is associated with regional fat distribution, with varying effects based on age, sex, and PFAS structure. The findings highlight the potential role of PFAS exposure in influencing fat depots and obesity risk, with significant implications for public health. The prediction model provides a highly accurate tool for assessing obesity risk related to PFAS exposure.
Humans ; Fluorocarbons/blood* ; Female ; Adult ; Middle Aged ; Male ; Environmental Pollutants/blood* ; Abdominal Fat ; Nutrition Surveys ; Alkanesulfonic Acids/blood* ; Obesity ; Environmental Exposure

This paper reported a type 1 diabetes patient who had severe diabetic nephropathy, retinopathy, hypertension, and hypothyroidism before pregnancy. The patient's blood glucose control was poor before pregnancy, and the complications were not properly treated. This was an unintended pregnancy, with a pre-pregnancy glycated hemoglobin A1c of 7.8% and early pregnancy urine protein of 3.81-4.53 g/24 h. Considering the patient's poor blood glucose control before pregnancy and the lack of proper treatment for multiple complications including nephropathy, a multidisciplinary consultation at an external hospital recommended termination of the pregnancy. However, the patient was determined to continue the pregnancy and was referred to Peking University First Hospital. Through strict blood glucose control, monitoring and evaluation of complications, and comprehensive management, the patient's blood glucose and blood pressure were well controlled during pregnancy. Regular monitoring of urine protein, renal function, and ocular fundus was conducted. At 31 weeks and 4 days of gestation, the patient's 24-hour urine protein significantly increased. After promoting fetal lung maturity, a cesarean section was performed at 34 weeks and 1 day of gestation, resulting in a successful delivery with good maternal and neonatal outcomes. At the 42-day postpartum follow-up, the patient's blood glucose and blood pressure were stable, urine protein returned to pre-pregnancy levels, and the infant was in good general condition.

This study aims to prepare monoclonal antibody to S1 protein of porcine epidemic diar-rhea virus(PEDV).E.coli expression system and affinity chromatography were used to success-fully obtain purified recombinant PEDV S1 protein.After immunizing BALB/c mice,hybridoma technology and indirect ELISA were used to prepare and screen positive hybridoma cells.Finally,ascites antibodies were prepared by in vivo induction method.ELISA results showed that a total of 4 hybridoma cell lines with anti-PEDV S1 monoclonal antibody were screened,and they were named E6,G3,H6 and F2.The supernatant titers of all 4 hybridoma cell lines reached 1∶6 400.The monoclonal antibody H6 with higher antibody titers and more stable antibody secretion was selected for antibody type identification.It was found that monoclonal antibody H6 belongs to the IgG1 subclass and the light chain is the λ chain.The antibody titers that induced mouse ascites were 1∶106 and without cross-reaction with other proteins.Western blot results showed that the monoclonal antibody exhibited specific bands at 38 kDa with the recombinant S1 protein,PEDV QY2016,and PEDV CV777 strains.The IFA results also showed that the monoclonal antibody reacted with cells infected with PEDV QY2016 and PEDV CV777 strains,exhibiting a green fluo-rescent signal.The affinity constant of monoclonal antibody H6 was K=1.75×107 moL/L,indica-ting that the H6 strain had a good affinity and could be used for the development of subsequent di-agnostic antibodies.In summary,this study successfully prepared monoclonal antibodies that can specifically recognize PEDV S1 protein,which can be used for the antigen detection of PEDV and providing important test materials for the research of PEDV detection methods.

Objective:To assess the influencing factors of glycemic control among type 2 diabetes mellitus (T2DM) patients, in particular the correlations between peripheral blood eosinophils and metabolic indicators such as glucose, lipids, and uric acid (UA) in these patients.Methods:T2DM patients who were regularly followed up in the Intensive Diabetes Mellitus Clinic of Peking Union Medical College Hospital from January 2016 to September 2024 were prospectively selected as the research subjects. The clinical data of these patients at their first visit and at the 3rd, 6th, 9th, and 12th months of follow-up were collected. The potential correlations of peripheral blood eosinophils with blood glucose control, lipid metabolism, UA metabolism, and inflammation as well as their influencing factors were analyzed.Results:A total of 161 T2DM patients were included. The glycated hemoglobin A1c (HbA1c) compliance rate was significantly higher during the follow-up visits (3, 6, 9, and 12 months) than baseline (all P<0.05) but showed no significant correlation with the count or percentage of peripheral blood eosinophils. Spearman correlation analysis showed that the percentage of peripheral blood eosinophils was negatively correlated with Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) ( P=0.049) and high-density lipoprotein cholesterol (HDL-C) ( P=0.002) and positively with serum triglyceride (TG) ( P=0.034) and UA levels ( P<0.001). A further linear regression model analysis of these four variables and the percentage of eosinophils revealed that the percentage of peripheral blood eosinophils was only linearly correlated with serum UA level ( P<0.001). Conclusion:The percentage of peripheral blood eosinophils in T2DM patients is independently correlated with serum UA level, and monitoring serum UA level is important in T2DM management. Early identification and intervention of hyperuricemia can help provide more comprehensive and precise medical interventions for T2DM patients.

BACKGROUND: Diabetic foot is a complex condition with high incidence, recurrence, mortality, and disability rates. Current treatments for diabetic foot ulcers are often insufficient. This study was conducted to identify potential therapeutic targets for diabetic foot. METHODS: Datasets related to diabetic foot and diabetic skin were retrieved from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using R software. Enrichment analysis was conducted to screen for critical gene functions and pathways. A protein interaction network was constructed to identify node genes corresponding to key proteins. The DEGs and node genes were overlapped to pinpoint target genes. Plasma and chronic ulcer samples from diabetic and non-diabetic individuals were collected. Western blotting, immunohistochemistry, and enzyme-linked immunosorbent assays were performed to verify the S100 calcium binding protein A9 (S100A9), inflammatory cytokine, and related pathway protein levels. Hematoxylin and eosin staining was used to measure epidermal layer thickness. RESULTS: In total, 283 common DEGs and 42 node genes in diabetic foot ulcers were identified. Forty-three genes were differentially expressed in the skin of diabetic and non-diabetic individuals. The overlapping of the most significant DEGs and node genes led to the identification of S100A9 as a target gene. The S100A9 level was significantly higher in diabetic than in non-diabetic plasma (178.40 ± 44.65 ng/mL vs. 40.84 ± 18.86 ng/mL) and in chronic ulcers, and the wound healing time correlated positively with the plasma S100A9 level. The levels of inflammatory cytokines (tumor necrosis factor-α, interleukin [IL]-1, and IL-6) and related pathway proteins (phospho-extracellular signal regulated kinase [ERK], phospho-p38, phospho-p65, and p-protein kinase B [Akt]) were also elevated. The epidermal layer was notably thinner in chronic diabetic ulcers than in non-diabetic skin (24.17 ± 25.60 μm vs. 412.00 ± 181.60 μm). CONCLUSIONS S100A9 was significantly upregulated in diabetic foot and was associated with prolonged wound healing. S100A9 may impair diabetic wound healing by disrupting local inflammatory responses and skin re-epithelialization.
Calgranulin B/therapeutic use* ; Diabetic Foot/metabolism* ; Humans ; Datasets as Topic ; Computational Biology ; Mice, Inbred C57BL ; Animals ; Mice ; Protein Interaction Maps ; Immunohistochemistry

This study aims to investigate the effect of Chaijin Jieyu Anshen Formula on the neuroinflammation of rats with insomnia complicated with depression through the regulation of triggering receptor expressed on myeloid cells 2(TREM2)/complement protein C1q signaling pathway. Rats were randomly divided into a normal group, a model group, a positive drug group, as well as a high, medium, and low-dose groups of Chaijin Jieyu Anshen Formula, with 10 rats in each group. Except for the normal group, the other groups were injected with p-chlorophenylalanine and exposed to chronic unpredictable mild stress to establish the rat model of insomnia complicated with depression. The sucrose preference experiment, open field experiment, and water maze test were performed to evaluate the depression in rats. Enzyme-linked immunosorbent assay was employed to detect serum 5-hydroxytryptamine(5-HT), dopamine(DA), and norepinephrine(NE) levels. Hematoxylin and eosin staining and Nissl staining were used to observe the damage in nucleus accumbens neurons. Western blot and immunofluorescence were performed to detect TREM2, C1q, postsynaptic density 95(PSD-95), and synaptophysin 1(SYN1) expressions in rat nucleus accumbens, respectively. Golgi-Cox staining was utilized to observe the synaptic spine density of nucleus accumbens neurons. The results show that, compared with the model group, Chaijin Jieyu Anshen Formula can significantly increase the sucrose preference as well as the distance and number of voluntary activities, shorten the immobility time in forced swimming test and the successful incubation period of positioning navigation, and prolong the stay time of space exploration in the target quadrant test. The serum 5-HT, DA, and NE contents in the model group are significantly lower than those in the normal group, with the above contents significantly increased after the intervention of Chaijin Jieyu Anshen Formula. In addition, Chaijin Jieyu Anshen Formula can alleviate pathological damages such as swelling and loose arrangement of tissue cells in the nucleus accumbens, while increasing the Nissl body numbers. Chaijin Jieyu Anshen Formula can improve synaptic damage in the nucleus accumbens and increase the synaptic spine density. Compared to the normal group, the expression of C1q protein was significantly higher in the model group, while the expression of TREM2 protein was significantly lower. Compared to the model group, the intervention with Chaijin Jieyu Anshen Formula significantly downregulated the expression of C1q protein and significantly upregulated the expression of TREM2. Compared with the model group, the PSD-95 and SYN1 fluorescence intensity is significantly increased in the groups receiving different doses of Chaijin Jieyu Anshen Formula. In summary, Chaijin Jieyu Anshen Formula can reduce the C1q protein expression, relieve the TREM2 inhibition, and promote the synapse-related proteins PSD-95 and SNY1 expression. Chaijin Jieyu Anshen Formula improves synaptic injury of the nucleus accumbens neurons, thereby treating insomnia complicated with depression.
Animals ; Male ; Rats ; Nucleus Accumbens/metabolism* ; Drugs, Chinese Herbal/administration & dosage* ; Depression/complications* ; Membrane Glycoproteins/genetics* ; Rats, Sprague-Dawley ; Sleep Initiation and Maintenance Disorders/complications* ; Neurons/metabolism* ; Receptors, Immunologic/genetics* ; Signal Transduction/drug effects* ; Synapses/metabolism*