Metabolic habitat imaging with hemodynamic heterogeneity predicts individual progression-free survival in high-grade glioma

AIM

We design a feasibility study to obtain a set of metabolic-hemodynamic habitats for tackling tumor spatial metabolic patterns with hemodynamic information.

MATERIALS AND METHODS

Preoperative data from 69 high-grade gliomas (HGG) patients with subsequent histologic confirmation of HGG were prospectively collected (January 2016 to March 2020) after concurrent chemoradiotherapy (CCRT). Four vascular habitats were automatically segmented by multiparametric magnetic resonance imaging (MRI). The metabolic information, either at enhancing or edema tumor regions, was obtained by two neuroradiologists. The relative habitat volumes were used for weight estimation procedures for computing the coefficients of a linear regression model using weighted least squares (WLS) for metabolite semiquantifications (i.e. the Cho/NAA ratio and the Cho/Cr ratio) at vascular habitats. Multivariate Cox proportional hazard regression analyses are used to obtain the odds ratio (OR) and develop a nomogram using weighted estimators corresponding to each covariate derived from Cox regression coefficients.

RESULTS

There was a strongly correlation between perfusion indexes and the Cho/Cr ratio (rCBV, r=0.71) or Cho/NAA ratio (rCBV, r=0.66) at high-angiogenic enhancing tumor habitats (HAT) habitat. Compared isocitrate dehydrogenase (IDH) mutation to their wild type, the IDH wild type had significantly decreased Cho/Cr ratio (IDH mutation: Cho/Cr ratio = 2.44 ± 0.33, IDH wildtype: Cho/Cr ratio = 2.66 ± 0.36, p=0.02) and Cho/NAA ratio (IDH mutation: Cho/Cr ratio = 4.59 ± 0.61, IDH wildtype: Cho/Cr ratio = 4.99 ± 0.66, p=0.022) at the HAT. The C-index for the median progression-free survival (PFS) prediction was 0.769 for the Cho/NAA nomogram and 0.747 for the Cho/Cr nomogram through 1000 bootstrapping validation.

CONCLUSIONS

Our findings suggest that spatial metabolism combined with hemodynamic heterogeneity is associated with individual PFS to HGG patients post-CCRT.

Corrigendum: Screening and identification of hub genes in the development of early diabetic kidney disease based on weighted gene co-expression network analysis

[This corrects the article DOI: 10.3389/fendo.2022.883658.].

Multimodel habitats constructed by perfusion and/or diffusion MRI predict isocitrate dehydrogenase mutation status and prognosis in high-grade gliomas

AIM

To determine whether tumour vascular and cellular heterogeneity of high-grade glioma (HGG) is predictive of isocitrate dehydrogenase (IDH) mutation status and overall survival (OS) by using tumour habitat-based analysis constructed by perfusion and/or diffusion magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Seventy-eight HGG patients that met the 2021 World Health Organization WHO Classification of Tumors of the Central Nervous System, 5th edition (WHO CNS5), were enrolled to predict IDH mutation status, of which 32 grade 4 patients with unmethylated O6-methylguanine-DNA methyltransferase (MGMT) promoter were enrolled for prognostic analysis. The deep-learning-based model nnU-Net and K-means clustering algorithm were applied to construct the Traditional Habitat, Vascular Habitat (VH), Cellular Density Habitat (DH), and their Combined Habitat (CH). Quantitative parameters were extracted and compared between IDH-mutant and IDH-wild-type patients, respectively, and the prediction potential was evaluated by receiver operating characteristic (ROC) curve analysis. OS was analysed using Kaplan-Meier survival analysis and the log-rank test.

RESULTS

Compared with IDH-mutants, median relative cerebral blood volume (rCBVmedian) values in the whole enhancing tumour (WET), VH1, VH3, CH1-4 habitats were significantly increased in IDH-wild-type HGGs (all p<0.05). Additionally, the accuracy of rCBVmedian values in CH1 outperformed other habitats in identifying IDH mutation status (p<0.001) at a cut-off value of 4.83 with AUC of 0.815. Kaplan-Meier survival analysis highlighted significant differences in OS between the populations dichotomised by the median of rCBVmedian in WET, VH1, CH1-3 habitats (all p<0.05).

CONCLUSIONS

The habitat imaging technique may improve the accuracy of predicting IDH mutation status and prognosis, and even provide a new direction for subsequent personalised precision treatment.

Secondary analysis of newly diagnosed type 2 diabetes subgroups and treatment responses in the MARCH cohort

OBJECTIVE

To incorporate new clusters in the MARCH (Metformin and AcaRbose in Chinese patients as the initial Hypoglycemic treatment) cohort of newly diagnosed type 2 diabetes (T2D) patients and compare the anti-glycemic effects of metformin and acarbose across different clusters.

METHODS

K-means cluster analysis was performed based on six clinical indicators. The diabetic clusters in the MARCH cohort were retrospectively associated with the response to metformin and acarbose.

RESULTS

A total of 590 newly diagnosed T2D patients were classified by data-driven clusters into the MARD (mild obesity-related diabetes) (34.1 %), MOD (mild obesity-related diabetes) (34.1 %), SIDD (severe insulin-deficient diabetes) (20.3 %) and SIRD (severe insulin-resistant diabetes) (11.5 %) subgroups at baseline. At 24 and 48 weeks, 346 participants had finished the follow-up. After the adjustment of age, gender, weight, baseline HbA1c, baseline fasting glucose and 2-h postprandial blood glucose (2hPG), metformin mainly decreased the fasting glucose (0.07 ± 0.89 vs -0.26 ± 0.83, P = 0.043) in the MARD subgroup presented with OGTT (oral glucose tolerance test) results compared with acarbose group at 24 weeks. Acarbose led to a greater decrease in 2hPG in the MOD subgroup compared with metformin group (0.08 ± 0.86 vs -0.24 ± 0.92, P = 0.037) at 24 weeks. There was a also significant interaction between cluster and treatment efficacy in HbA1c (glycated hemoglobin) reduction in metformin and acarbose groups at 24 and 48 weeks (pinteraction<0.001).

CONCLUSIONS

Metformin and acarbose affected different metabolic variables depending on the diabetes subtype.

A comparison of different approaches for the analysis of 36Cl in graphite samples

This study compares different approaches for the quantification of the massic activity of 36Cl in graphite samples. All approaches consisted of a combustion step in combination with a trapping solution to collect the volatile elements. Two different resins were used to separate 36Cl from the matrix (CL resin and PS resin). Liquid scintillation counting (LSC), scintillation counting (SC) and tandem inductively coupled plasma mass spectrometry (ICP-MS/MS) were used to quantify 36Cl activity. The chemical yield in all approaches was determined by means of ion chromatography (IC). In addition, the methods were applied to a real activated graphite sample.

CTP-based estimated ischemic core: A comparative multicenter study between Olea and RAPID software

BACKGROUND AND PURPOSE

CTP is increasingly used to assess eligibility for endovascular therapy (EVT) in patients with large vessel occlusions (LVO). There remain variability and inconsistencies between software packages for estimation of ischemic core. We aimed to use heterogenous data from four stroke centers to perform a comparative analysis for CTP-estimated ischemic core between RAPID (iSchemaView) and Olea (Olea Medical).

METHODS

In this retrospective multicenter study, patients with anterior circulation LVO who underwent pretreatment CTP, successful EVT (defined TICI ≥ 2b), and follow-up MRI included. Automated CTP analysis was performed using Olea platform [rCBF < 25% and differential time-to-peak (dTTP)>5s] and RAPID (rCBF < 30%). The CTP estimated core volumes were compared against the final infarct volume (FIV) on post treatment MRI-DWI.

RESULTS

A total of 151 patients included. The CTP-estimated ischemic core volumes (mean ± SD) were 18.7 ± 18.9 mL on Olea and 10.5 ± 17.9 mL on RAPID significantly different (p < 0.01). The correlation between CTP estimated core and MRI final infarct volume was r = 0.38, p < 0.01 for RAPID and r = 0.39, p < 0.01 for Olea. Both software platforms demonstrated a strong correlation with each other (r = 0.864, p < 0.001). Both software overestimated the ischemic core volume above 70 mL in 4 patients (2.6%).

CONCLUSIONS

Substantial variation between Olea and RAPID CTP-estimated core volumes exists, though rates of overcalling of large core were low and identical. Both showed comparable core volume correlation to MRI infarct volume.

A Phase 2 Trial of Efficacy and Safety of Intraoperative Radiation Therapy for Locally Advanced Laryngocarcinoma

PURPOSE/OBJECTIVE(S)

For locally advanced laryngeal cancer (LAL), the local recurrence rate remains 19-40% after radical surgery with postoperative radiotherapy alone or with concurrent chemoradiotherapy in patients with unfavorable prognostic factors. We evaluate local control and acute toxicity of intraoperative radiation therapy (IORT) as a tumor bed boost for locally advanced laryngeal cancer in this prospective phase 2 trial.

MATERIALS/METHODS

This phase II clinical study in which a total of 63 LAL patients (T2N1-3/T3N0-3/T4N0-3) were selected and received IORT (T2: 8-10Gy, T3,4:12-15 Gy) as a tumor bed boost during radical surgery, then received external-beam radiation therapy (EBRT) at a total dose of 54-60Gy within 6 weeks after surgery, 5 times per week, 1.8-2Gy per time, 30 times in total. The median follow-up time was 20 months (7 -39 months). The primary outcome was the local control (LC) and 2 - year survival rate determined using the Kaplan-Meier method. This study is registered with ClinicalTrials.gov, NCT04278638.

RESULTS

A total of 63 patients consented to participate in the study; 59 males and 4 females, median age was 61 years (40-81 years), 14 patients had supraglottic LAL, 44 patients had glottic LAL and 5 patients had subglottic LAL. 10 patients showed high differentiation and 44 patients showed moderate differentiation and 9 patients showed low differentiation with laryngeal squamous cell carcinoma. 3 patients were in T2N1-2 stage, 40 patients in T3N0-2 stage, and 20 patients in T4N0-2 stage, 48 patients received total laryngectomy and 15 patients received hemilaryngectomy; 16 patients were lymph node-positive and 1 patient developed vascular tumor thrombus after surgery. After surgery combined with IORT and EBRT, the 1- and 2- year LC rates were 98.2% and 93.1 %, respectively, 2-year overall survival rate was 97.4%. Pharyngeal fistula was observed in 1 patient (1. 6 %) and wound infection in 3 patients (4.8%). Radiation Therapy Oncology Group (RTOG) grade 3 pain and RTOG grade 4 dyspnea were noted in one patient (1.6%) and 2 patients (3.2 %), respectively.

CONCLUSION

In summary, our prospective phase II trial proved that the addition of intraoperative radiotherapy as a tumor bed boost to postoperative radiotherapy provided local therapeutic benefit to patients with locally advanced laryngeal cancer. Our data support the safety of this combined therapy. Additional investigation is warranted to determine the role of intraoperative radiotherapy in the local treatment of locally advanced laryngeal cancer.

Data-driven subgroups of newly diagnosed type 2 diabetes and the relationship with cardiovascular diseases at genetic and clinical levels in Chinese adults

BACKGROUND

To subgroup Chinese patients with newly diagnosed type 2 diabetes (T2D) by K-means cluster analysis on clinical indicators, and to explore whether these subgroups represent different genetic features and calculated cardiovascular risks.

METHODS

The K-means clustering analysis was performed on two cohorts (n = 590 and 392), both consisting of Chinese participants with newly diagnosed T2D. To assess genetic risks, multiple polygenic risk scores (PRSs) and mitochondrial DNA copy numbers (mtDNA-CN) were calculated for all participants. Furthermore, Framingham risk scores (FRS) of cardiovascular diseases in two cohorts were also calculated to verify the genetic risks.

RESULTS

Four clusters were identified including the mild age-related diabetes (MARD)(35.08%), mild obesity-related diabetes (MOD) (34.41%), severe autoimmune diabetes (SAID) 19.15%, and severe insulin-resistant diabetes (SIRD) 11.36% subgroups in the MARCH (metformin, and acarbose in Chinese patients as the initial hypoglycemic treatment) cohort. There was a significant difference in PRS for cardiovascular diseases (CVD) across four subgroups in the MARCH cohort (p < 0.05). Compared with the SIDD and SIRD subgroups, patients in the MOD subgroup had a relatively lower PRS for CVD (p < 0.05) in the MARCH cohort. Females had a higher PRS compared to males, with no significant difference in FRS across the four clusters. The MOD subgroup had a significantly lower FRS which was consistent with the results of PRS. Similar results of PRS and FRS were also replicated in the CONFIDENCE (comparison of glycemic control and b-cell function among newly diagnosed patients with type 2 diabetes treated with exenatide, insulin or pioglitazone) cohort.

CONCLUSION

There are different CVD risks in diabetic subgroups based on clinical and genetic evidence which may promote precision medicine.

Relationship between dietary patterns and diabetic microvascular complications in patients with type 2 diabetes mellitus

OBJECTIVE

This study aimed to investigate the relationship between different dietary patterns and diabetic microvascular complications in patients with type 2 diabetes mellitus.

PATIENTS AND METHODS

This study was conducted based on the Chinese Chronic Disease and its Risk Factor Surveillance System. A multi-stage stratified sampling method was used to randomly select two districts (Henghualing District, Taiyuan City, and Yuzi District, Jinzhong City) and two counties (Huguan County, Changzhi City, and Jiang County, Yuncheng City) from the chronic disease surveillance sites in Shanxi Province to collect general information, dietary records, physical measurements, and laboratory tests. In total, 1,227 patients were enrolled according to the study criteria. Factor analysis was performed to construct six dietary patterns, and the relationship between dietary pattern scores and type 2 diabetic microvascular complications was analysed using binary logistic regression after correcting for confounders.

RESULTS

(1) Regarding the prevalence of type 2 diabetic microvascular complications and dietary characteristics, the prevalence of microvascular complications in patients with type 2 diabetes mellitus was 55.3% and was higher in urban than in rural areas. The prevalence of diabetic kidney disease (DKD), diabetic retinopathy, and diabetic peripheral neuropathy (DPN) were 21.4%, 12.7%, and 38.0%, respectively. (2) Six dietary patterns were constructed, namely, 'animal protein', 'coarse grains and plant protein', 'nuts and fruits', 'refined grains and vegetables', 'dairy', and 'added sugars', with factor contributions of 15.42%, 9.99%, 8.23%, 8.16%, 7.56%, and 7.28% respectively, explaining 56.64% of the total dietary variation. (3) After adjusting for confounding variables, the results of binary logistic regression indicated that patients in the highest quartile of dietary pattern scores for 'nuts and fruits' experienced a 43.3% lower risk of DKD compared to those in the lowest quartile [odds ratio (OR) = 0.567; 95% confidence interval (CI), 0.359-0.894; p < 0.001]. Similarly, patients in the highest quartile of dietary pattern scores for 'animal protein' had a 42.8% lower risk of DPN compared with those in the lowest quartile (OR = 0.572; 95% CI, 0.388-0.843; p < 0.05).

CONCLUSIONS

The results of this study suggest that in patients with type 2 diabetes mellitus, a 'nuts and fruits' dietary pattern reduces the risk of DKD and an 'animal protein' dietary pattern reduces the risk of DPN.

Evaluating the long-term cost-effectiveness of fixed-ratio combination insulin degludec/liraglutide (IDegLira) versus other treatment regimens in the chinese type 2 diabetes patients

BACKGROUND AND AIMS

To assess the cost-effectiveness of utilizing IDegLira in comparison to other treatment regimens ( liraglutide and degludec) in managing type 2 diabetes, taking into account the Chinese healthcare system's perspective.

METHODS

The clinical data were obtained from the randomized controlled trials (RCTs) of the DUAL I and DUAL II evidence studies that took place in China. To estimate the lifetime quality-adjusted life-years (QALYs) and direct medical costs of patients receiving different treatment strategies from a long-term perspective, the IQVIA CORE Diabetes Model version 9.0 (IQVIA, Basel, Switzerland) was utilized. The costs were evaluated from the perspective of the China National Health System. Future costs and clinical benefits were discounted annually at 5%, and sensitivity analyses were conducted.

RESULTS

IDegLira was projected to reduce the incidence of diabetes-related complications and improve quality-adjusted life expectancy (QALE) versus liraglutide and degludec. A survival benefit was observed with IDegLira over Liraglutide (0.073 years). Lifetime costs were lower by Chinese yuan (CNY) 27,945 on IDegLira than on Liraglutide therapy. A similar survival benefit was observed with IDegLira over degludec (0.068 years). Lifetime costs were lower by CNY 1196 on IDegLira than on degludec therapy. Therefore, IDegLira was found to be cost-effective versus liraglutide and degludec with incremental cost-effectiveness ratios of Dominant per QALY gained, respectively, under the threshold of three times the gross domestic product (GDP) per capita in China.

CONCLUSION

IDegLira is a cost-effective hypoglycemic treatment option that delivers positive clinical outcomes while also reducing costs for Chinese patients living with type 2 diabetes.

[Comparison of intraoperative neurophysiological monitoring between patients with arthrogryposis multiplex congenita and adolescent idiopathic scoliosis]

Objective: To compare the intraoperative neurophysiological monitoring (IONM) results between patients with arthrogryposis multiplex congenita (AMC) and adolescent idiopathic scoliosis (AIS) and to analyze the influence of congenital spinal deformity on IONM in AMC patients, thus to evaluate the efficiency of IONM in AMC patients. Methods: A cross-sectional study. The clinical data of 19 AMC patients underwent correction surgery from July 2013 to January 2022 in Nanjing Drum Tower Hospital were retrospectively reviewed. There were 13 males and 6 females with a mean age of (15.2±5.6) years, and the average Cobb angle of main curve was 60.8°±27.7°. And 57 female AIS patients of similar age and curve type with the AMC patients during the same period were selected as the control group, with an average age of (14.6±4.4) years and a mean Cobb angle of 55.2°±14.2°. The latency and amplitude of samatosensory evoked potentials (SSEPs) and transcranial electric motor evoked potentials (TCeMEPs) were compared between the two groups. The difference in IONM data between AMC patients with and without congenital spinal deformity was also evaluated. Results: The success rates of SSEPs and TCeMEPs were 100% and 14/19 for AMC patients, 100% and 100% for AIS patients. The SSEPs-P40 latency, SSEPs-N50 latency, SSEPs-amplitude, TCeMEPs-latency, TCeMEPs-amplitude showed no significant difference between AMC patients and AIS patients (P>0.05 for all). The side-difference of TCeMEPs-amplitude showed an increasing trend in AMC patients when compared with that in AIS patients, but there was no statistical difference between the two groups [(147.0±185.6) μV vs (68.1±311.4) μV, P=0.198]. The SSEPs-amplitude value was (1.4±1.1) μV on concave side in AMC patients with congenital spinal deformity, and it was (2.6±1.2) μV on concave side in AMC patients without congenital spinal deformity (P=0.041). The SSEPs-amplitude value was (1.4±0.8) μV on convex side in AMC patients with congenital spinal deformity, and it was (2.6±1.3) μV on convex side in AMC patients without congenital spinal deformity (P=0.028). Conclusions: The values of SSEPs-P40 latency, SSEPs-N50 latency, SSEPs-amplitude, TCeMEPs-latency and TCeMEPs-amplitude are similar in AMC and AIS patients. The SSEPs-amplitude of AMC patients with congenital spinal deformity is lower than that of AMC patients without congenital spinal deformity.

Single-scan ultrafast laser inscription of waveguides in IG2 for type-I and type-II operation in the mid-infrared

We demonstrate, for the first time to our knowledge, single-scan ultrafast laser inscription and performance of mid-infrared waveguiding in IG2 chalcogenide glass in the type-I and type-II configurations. The waveguiding properties at 4550 nm are studied as a function of pulse energy, repetition rate, and additionally separation between the two inscribed tracks for type-II waveguides. Propagation losses of ∼1.2 dB/cm in a type-II waveguide and ∼2.1 dB/cm in a type-I waveguide have been demonstrated. For the latter type, there is an inverse relation between the refractive index contrast and the deposited surface energy density. Notably, type-I and type-II waveguiding have been observed at 4550 nm within and between the tracks of two-track structures. In addition, although type-II waveguiding has been observed in the near infrared (1064 nm) and mid infrared (4550 nm) in two-track structures, type-I waveguiding within each track has only been observed in the mid infrared.

[Clinical study of serum human-βeta-defensin-1 level for evaluating short-term prognosis in patients with acute-on-chronic liver failure]

Objective: To evaluate the diagnostic value of serum human-βeta-defensin-1 level (HBD-1) for short-term (28-day) prognosis in patients with acute-on-chronic liver failure (ACLF). Methods: Fifty cases diagnosed with ACLF were selected. 20 cases with decompensated cirrhosis and 20 cases with compensated cirrhosis who were admitted at the same time were included. Age, gender, serum HBD-1 level, C-reactive protein (CRP), procalcitonin (PCT), neutrophil count/lymphocyte ratio (NLR), blood routine, coagulation function, liver function, kidney function, and other indicators from the three groups of patients were collected. Patients with ACLF were screened for indicators related to the short-term (28-day) prognosis. Patients were divided into an improvement group and a worsening group according to the 28-day disease outcome. The serum HBD-1 level and other above-mentioned indicators were compared between the two patient groups. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic efficacy of serum HBD-1 levels for short-term prognosis in patients with ACLF. PCT, NLR, and prothrombin activity (PTA) application as a mono indicator and HBD-1 in combination with NLR, PCT, and PTA were compared to evaluate diagnostic efficacy for short-term prognosis in patients with ACLF. The intergroup mean of measurement data was determined using a t-test or analysis of variance. χ (2) test was used for comparison of count data. Spearman's rank correlation analysis was used for correlation analysis. Results: There was no statistically significant difference in age and gender among the three groups: ACLF, decompensated cirrhosis, and compensated cirrhosis (P > 0.05). The expression levels of serum HBD-1 in the ACLF group, decompensated cirrhosis group, and compensated cirrhosis group were (319.1 ± 44.4) ng/ml, (264.5 ± 46.5) ng/ml and (240.1 ± 35.4) ng/ml, respectively, while the ACLF group expression levels were significantly increased, with statistical significance (P < 0.01).The serum HBD-1 level was significantly higher in the ACLF worsening group (346.2 ± 43.6) ng/ml than that in the improvement group (308.5 ± 40.6) ng/ml, and the difference was statistically significant (P < 0.05). Correlation analysis showed that HBD-1, NLR, PCT, prothrombin time (PT), and international standardized ratio (INR) were negatively correlated with the 28-day disease outcome (improvement) of patients (P < 0.05). PTA was positively correlated with 28-day disease outcome (improvement) (P < 0.05). The area under the receiver operating characteristic curve (AUC) for evaluating HBD-1's diagnostic efficacy for short-term prognosis in patients with ACLF was 0.774, with a sensitivity of 0.750, a specificity of 0.786, and a cut-off point of 337.96 ng/ml. PCT, NLR, and PTA had greater diagnostic efficacy. HBD-1 combined with PTA had the highest diagnostic efficacy, with an AUC of 0.802, a sensitivity of 0.778, and a specificity of 0.786. The diagnostic efficacy of HBD-1+PCT, HBD-1+NLR and HBD-1, PCT, and NCR was superior to PTA mono. Conclusion: The serum HBD-1 level gradually increases with the aggravation of liver function injury and is negatively correlated with the short-term prognosis in patients with ACLF. Serum HBD-1 level has high sensitivity and specificity in predicting short-term prognosis in patients with ACLF, and its diagnostic efficacy is superior to that of PCT, NLR, and PTA. The combined application of HBD-1 and PTA has higher diagnostic efficacy; however, when the serum HBD-1 level is greater than 337.96ng/ml, it indicates poor prognosis in patients.

Investigation of a new approach for 36Cl determination in solid samples using plastic scintillators

This work reports a new approach for the determination of ³⁶Cl in radioactive waste samples from nuclear decommissioning, wherein novel plastic scintillator (PS) materials were used for the concentration of ³⁶Cl prior to the detection with scintillation counting. Different plastic scintillator (PS) materials were tested for their selective absorption and detection of ³⁶Cl activity in solid samples. PS microspheres (PSm), cross-linked PSm (CPSm) and PS resin have been investigated. PS resin was identified as the most suitable material for ³⁶Cl analysis. Pyrolysis and subsequent trapping of the volatile elements in a bubbler was used. The trapping solution was finally loaded onto a cartridge of the PS resin. Scintillation counting and ion chromatography were used to determine the activity concentration and the chemical recovery, respectively.

Long-Term Cost-Effectiveness of Subcutaneous Once-Weekly Semaglutide Versus Polyethylene Glycol Loxenatide for Treatment of Type 2 Diabetes Mellitus in China

OBJECTIVE

This study aimed to evaluate the long-term cost-effectiveness of once-weekly subcutaneous semaglutide versus polyethylene glycol loxenatide (PEG-loxenatide) in patients with type 2 diabetes uncontrolled on metformin, from a Chinese healthcare systems perspective.

METHODS

The study applied the Swedish Institute of Health Economics Diabetes Cohort Model to evaluate the long-term clinical and economic outcomes of once-weekly treatment of semaglutide at 0.5 mg and 1.0 mg, respectively, versus PEG-loxenatide 0.2 mg, over a 40-year time horizon. Baseline cohort characteristics were collected from the SUSTAIN China trial. A network meta-analysis was conducted to obtain comparative treatment effects of once-weekly semaglutide and PEG-loxenatide based on two phase 3a clinical trials. Drug costs were sourced from the national bidding price of China. Outcomes were discounted at 5.0% per annum. One-way sensitivity analysis and probabilistic sensitivity analysis were conducted to assess the uncertainty of the base-case results.

RESULTS

When compared with PEG-loxenatide 0.2 mg, the projections of outcomes over the 40-year time horizon in patients with type 2 diabetes uncontrolled on metformin showed that treatment with once-weekly semaglutide 0.5 mg and 1.0 mg were associated with improved discounted life expectancy by 0.08 and 0.12 years, and improved discounted quality-adjusted life expectancy by 0.16 and 0.22 quality-adjusted life-years, respectively. Once-weekly semaglutide 0.5 mg and 1.0 mg were achieved at lifetime cost savings of 19,309 China Yuan (CNY) and 10,179 CNY, respectively. Sensitivity analyses verified the robustness of the results.

CONCLUSION

From the perspective of Chinese healthcare systems, treatment with once-weekly subcutaneous semaglutide represents a dominant option versus PEG-loxenatide for patients with type 2 diabetes uncontrolled on metformin.

Screening and Identification of Hub Genes in the Development of Early Diabetic Kidney Disease Based on Weighted Gene Co-Expression Network Analysis

Objective

The study aimed to screen key genes in early diabetic kidney disease (DKD) and predict their biological functions and signaling pathways using bioinformatics analysis of gene chips interrelated to early DKD in the Gene Expression Omnibus database.

Methods

Gene chip data for early DKD was obtained from the Gene Expression Omnibus expression profile database. We analyzed differentially expressed genes (DEGs) between patients with early DKD and healthy controls using the R language. For the screened DEGs, we predicted the biological functions and relevant signaling pathways by enrichment analysis of Gene Ontology (GO) biological functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways. Using the STRING database and Cytoscape software, we constructed a protein interaction network to screen hub pathogenic genes. Finally, we performed immunohistochemistry on kidney specimens from the Beijing Hospital to verify the above findings.

Results

A total of 267 differential genes were obtained using GSE142025, namely, 176 upregulated and 91 downregulated genes. GO functional annotation enrichment analysis indicated that the DEGs were mainly involved in immune inflammatory response and cytokine effects. KEGG pathway analysis indicated that C-C receptor interactions and the IL-17 signaling pathway are essential for early DKD. We identified FOS, EGR1, ATF3, and JUN as hub sites of protein interactions using a protein-protein interaction network and module analysis. We performed immunohistochemistry (IHC) on five samples of early DKD and three normal samples from the Beijing Hospital to label the proteins. This demonstrated that FOS, EGR1, ATF3, and JUN in the early DKD group were significantly downregulated.

Conclusion

The four hub genes FOS, EGR1, ATF3, and JUN were strongly associated with the infiltration of monocytes, M2 macrophages, and T regulatory cells in early DKD samples. We revealed that the expression of immune response or inflammatory genes was suppressed in early DKD. Meanwhile, the FOS group of low-expression genes showed that the activated biological functions included mRNA methylation, insulin receptor binding, and protein kinase A binding. These genes and pathways may serve as potential targets for treating early DKD.

POS0811 CHARACTERISTICS OF INTESTINAL MICROBIOTA AND ITS RELATIONSHIP WITH LYMPHOCYTE SUBSETS AND CYTOKINES IN PATIENTS WITH VASCULITIS

Background

Vasculitis include a group of autoimmune inflammatory diseases with clinical heterogeneous characterized by inflammation of vascular wall, inflammation of perivascular tissues, and cell-like necrosis[1]. Disorder of gut microbiota, which plays a crucial role in regulating immune cells such as Th1, Th17 and Treg, is associated with other autoimmune diseases[2], and may also be involved in the pathogenesis of vasculitis.

Objectives

To investigate the changes of intestinal microbiota and its correlation with peripheral lymphocyte subsets and inflammatory factors levels in patients with vasculitis.

Methods

Combined with clinical manifestations and laboratory examination, 33 patients with vasculitis who met the 2012 revised International Chapel Hill Consensus Conference Nomenclature of Vasculitides[3] and 33 of age- and gender- matched healthy controls (HCs) were selected from the Second Hospital of Shanxi Medical University. The demographic characteristics, general laboratory indicators such as erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), levels of peripheral lymphocyte subpopulations and serum cytokines detected by modified flow cytometry. Fecal microbiota detected by 16S rRNA gene sequencing and compiled and processed using Qiime2 and OTU-profiling tables were collected and analyzed in this study.

Results

Compared with HCs, the richness and diversity of intestinal flora in patients with vasculitis tended to decrease with a statistically significant difference in β diversity (P = 0.025, Figure 1 A and B). More specifically, vasculitis patients had a lower frequency of Firmicutes while higher Proteobacteria and Bacteroidota at the phylum level (P < 0.001, Figure 1C). In vasculitis patients, the relative abundances of 23 bacteria differed from HCs at the genus level was all decreased, including Gemella, Anaeroglobus, Campylobacter, Fournierella, et al (P < 0.001, Figure 1D and E). More importantly, the relative abundance of Muribaculaceae were positively correlated with the absolute count of Th2 and the proportions of Th1 and CD4+T cells and negatively correlated with CRP and ESR, while relative abundance of [Eubacterium]_ventriosum were positively associated with the absolute number of Treg cells and negatively correlated with the percentages of Th2 and CD8+T cells (Figure 1F).

Figure 1.

Differences in α diversity (A), β diversity (B), phylum (C), genus (D), and microbial composition (E) between vasculitis patients and HC and correlation analysis between differential microflora and clinical data in patients with vasculitis (F).

Conclusion

Disturbance of intestinal flora, mainly manifested by decreased diversity and richness, may be involved in the occurrence and development of vasculitis by inducing disroders in lymphocyte subsets and cytokines. Consequently, further studies on the immune mechanisms and influencing factors of intestinal flora may provide new ideas for the diagnosis and treatment of the disease for vasculitis patients.

References

[1]Aierken X, Zhu Q, Wu T, et al. Increased Urinary CD163 Levels in Systemic Vasculitis with Renal Involvement[J]. Biomed Res Int, 2021, 2021: 6637235. DOI: 10.1155/2021/6637235.

[2]Zhang X, Zhang D, Jia H, et al. The oral and gut microbiomes are perturbed in rheumatoid arthritis and partly normalized after treatment[J]. Nat Med, 2015, 21(8): 895-905. DOI: 10.1038/nm.3914.

[3]Jennette JC, Falk RJ, Bacon PA, et al. 2012 revised International Chapel Hill Consensus Conference Nomenclature of Vasculitides[J]. Arthritis Rheum, 2013, 65(1): 1-11. DOI: 10.1002/art.37715.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No.82001740).

Disclosure of Interests

None declared

AB0202 GUT MICROBIOTA DYSBIOSIS WERE CLOSELY CORRELATED WITH LYMPHOCYTE SUBSETS AND CYTOKINES IN PATIENTS WITH INFLAMMATORY ARTHRITIS

Background

Inflammatory arthritis includes a group of chronic conditions, particularly rheumatoid arthritis (RA), ankylosing spondylitis (AS) and psoriatic arthritis (PsA)[1].Growing evidences link gut microbiota dysbiosis with the development of inflammatory arthritis[2].

Objectives

The aim of this study was to discover the characters of microbiota in inflammatory arthritis patients and compare the relationship between the microbiota and peripheral lymphocyte subsets and cytokines.

Methods

Fecal samples were collected from 73 arthritis patients (13 PsA, 30 AS, 30 RA patients) and 140 sex- and age-matched healthy controls (HCs). The gut microbiota was studied by sequencing the V3-V4 variable regions of bacterial 16S rRNA genes by the Illumina Miseq PE300 system. Peripheral lymphocyte subsets in these participants were assessed by flow cytometry. Measures of disease activity such as erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) were recorded. Alpha and Beta diversity was assessed using results from QIIME2 and gut microbiome profiles were compared using linear discriminant analysis (LDA) effect size (LEfSe). R (version 4.0.1) was used for comparative statistics, using pearson correlation analysis to assess the correlation between the relative abundance of genus in the sample and clinical parameters.

Results

Compared with HCs, the richness of gut microbiota (ACE and Chao 1) was significantly lower (p < 0.05) in arthritis patients, and bacterial diversity including Shannon and Simpson indices (p < 0.001) was also significant in arthritis decreased (Figure 1A). β-diversity analysis based on Bray-curtis distance revealed significant differences in microbial communities between arthritis and HCs (Figure 1B, r=0.098, p=0.001, ANOSIM). In addition, compared with HCs at the genus level, 9 bacterial groups were significantly different in PsA (p < 0.05), 19 bacterial groups in AS (p < 0.05), and 17 bacterial groups in RA(p < 0.05) (Figure 1C). There was a significant positive correlation between CD4+T and Prevotella(p<0.01), T and Prevotella(p<0.05), Blautia(p<0.05) as well as Megamonas(p<0.05), Th17 and Prevotella(p<0.01), CD8+T and Megamonas(p<0.01), Th1 and Megamonas(p<0.05), Prevotella(p<0.01),Coprococcus(p<0.05), B and Erysipelotricbaceae_UCG-003(p<0.01), and Erysipelotricbaceae_UCG-003(p<0.01), Anaerostipes(p<0.01), CRP and Fusobacterium(p<0.05) as well as Roseburia(p<0.05). There were negative correlations between T and Erysipelotricbaceae_UCG-003 (p<0.05),CD8+T and Fusobacterium(p<0.01), CD4+T and Fusobacterium(p<0.05), NK and Fusicatenibacter(p<0.05).

Conclusion

The gut microbiota of patients with inflammatory arthritis differs from HC and also varies among individual arthritis, which was closely related to lymphocyte subsets.

References

[1]Wu X. Innate Lymphocytes in Inflammatory Arthritis[J]. Front Immunol, 2020, 11: 565275.DOI: 10.3389/fimmu.2020.565275

[2]Breban M. Gut microbiota and inflammatory joint diseases[J]. Joint Bone Spine, 2016, 83(6): 645-649.DOI: 10.1016/j.jbspin.2016.04.005

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0021 CHANGES OF GUT MICROBIOTA IN CONNECTIVE TISSUE DISEASE AND ITS RELATIONSHIP WITH LYMPHOCYTE SUBSETS AND CYTOKINES

Background

Connective tissue disease (CTD) is a group of autoimmune diseases characterized by the damage of connective tissue components in various parts of the body, which involved multiple organs and systems. Dysbiosis in the gut microbiome is associated with various autoimmune diseases such as CTD.

Objectives

To explore the characters of gut microbiota and their relationship with peripheral lymphocyte subsets and cytokines in patients with CTD.

Methods

Stool samples were collected from 63 CTD patients and 63 age- and sex-matched healthy controls(HCs). Microbial genomes were extracted for 16S rRNA gene sequencing. Gut microbiota characters (alpha diversity, beta diversity, and microbial composition) were analysed by R (version 4.0.1). Peripheral lymphocyte subsets were assessed by flow cytometry. Pearson correlation analysis was used to detect the correlation between the relative abundance of genus in the sample and the activity index; correlations with p < 0.05 were considered significant.

Results

Shannon and Simpson index revealed a decreased alpha diversity in CTD compared with that of HCs (p < 0.05), though not significantly difference in ACE and Chao1 parameters (p > 0.05, Figure 1A). Bray curtis distance-based beta-diversity analysis indicated significant differences in microbial communities between CTD and HCs (p = 0.0014, ANOSIM, Figure 1B). At the genus level, CTD patients had higher abundances of Terrisporobacter (p<0.01), Paraprevotella (p<0.01), CAG−352 (p<0.01), et al. but lower abundances of Streptococcus (p<0.01), Pseudomonas (p<0.01), Bacteroides(p<0.01), et al (Figure 1D). IgM was positively correlated with Lactococcus (p<0.05), Family_XIII_AD3011_group (p<0.05), Streptococcus (p<0.05). Th17 was positively correlated with Pseudomonas (p<0.01). Th2 was positively correlated with Christensenellaceae_R−7_group (p<0.001), UCG−010 (p<0.001) was positively correlated. Treg and Th2 were positively correlated with Christensenellaceae_R−7_group (p<0.01), UCG−010 (p<0.01). Treg was positively correlated with Lachnoclostridium (p<0.05) (Figure 1E).

Conclusion

Pattients with CTD had disbiosis of gut microbiota charaterized by impared diversity and abnomal composition,which was closely correlated with peripheral lymphocyte subsets.

References

[1]Laura Ghezzi,Claudia Cantoni,Gabriela V Pinget,et al.Targeting the gut to treat multiple sclerosis.J Clin Invest.2021 Jul 1;131(13):e143774. doi: 10.1172/JCI143774.

[2]Yoshihiko Tomofuji,Toshihiro Kishikawa,Yuichi Maeda,et al.Whole gut virome analysis of 476 Japanese revealed a link between phage and autoimmune disease.Ann Rheum Dis. 2022 Feb;81(2):278-288. doi: 10.1136/annrheumdis-2021-221267. Epub 2021 Dec 8.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0745 GUT DYSBIOSIS ASSOCIATED WITH PERIPHERAL LYMPHOCYTES AND CYTOKINES IN PATIENTS WITH SJÖGREN’S SYNDROME

Background

Primary Sjögren’s syndrome (pSS) is a systemic autoimmune disease characterized by disorders of lymphocyte subpopulations with various cytokines and auto-antibodies1. Growing evidences suggest that gut microbiome dysbiosis may contribute to the development of pSS2.

Objectives

To investigate the alterations to the gut microbiome and the correlation with peripheral lymphocytes and serum cytokines as well as inflammatory factors in pSS patients.

Methods

A total of 101 pSS patients and 101 age- and sex- matched healthy controls (HCs) were enrolled in this study from The Second Hospital of Shanxi Medical University (Taiyuan, Shanxi, China). Patients fulfilled the 2019 ACR/EULAR classification criteria. We conducted 16S rRNA gene sequencing using fecal microbiota samples and analyzed the peripheral lymphocyte subsets by flow cytometry. Serum cytokines, erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), unstimulated and stimulated whole saliva (UWS and SWS) secretion rate was also collected, respectively. Sequence data were compiled and processed using Qiime2 and OTU-profiling tables were constructed. Correlations between different taxa and gut microbiome, as well as clinical variables, were calculated by Spearman’s rank test.

Results

Patients with pSS exhibited a significant reduction in the richness and diversity of gut microbiota compared with those of HCs (Figure 1A-B, p < 0.05). Detailly, at the phylum level, pSS patients had a lower frequency of Firmicutes while higher Proteobacteria (Figure 1C, p < 0.05). Compared with HCs, 11 species of flora were discovered to be distinctly different at the genus level (p < 0.05). Patients presented fewer Faecalibacterium and Roseburia but more Lactobacillus (Figure 1D, p < 0.05). Lactobacillus negatively correlated with T cells (r=-0.407), CD8+T (r=-0.417) and Th2 (r=-0.323). There was a significant positive correlation between Faecalibacterium and IL-2(r=0.312), IFN-γ(r=0.338), TNF-α levels(r=0.322) (Figure 1E, p < 0.05). As for clinical disease measures, IL-6 increases were in line with ESR and CRP, while IL-2 levels inversely related to CRP. Additional UWS secretion rate and SWS secretion rate had negative correlation with ESR (Figure 1F, p < 0.05).

Conclusion

The structural disorder of gut microbiota was distinct in pSS which were associated with peripheral lymphocyte subsets and cytokines. Disorders of gut microbiota and immune systems may contribute to the occurrence and development of pSS.

References

[1]Mariette X, Criswell LA. Primary Sjogren’s Syndrome. N Engl J Med 2018;378(10):931-39. doi: 10.1056/NEJMcp1702514

[2]Trujillo-Vargas CM, Schaefer L, Alam J, et al. The gut-eye-lacrimal gland-microbiome axis in Sjogren Syndrome. Ocul Surf 2020;18(2):335-44. doi: 10.1016/j.jtos.2019.10.006

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0449 CHARACTERISTICS OF GUT MICROBIOTA AND ITS RELATIONSHIP WITH LYMPHOCYTE SUBSETS AND CYTOKINES IN PATIENTS WITH UNDIFFERENTIATED SPONDYLOARTHRITIS

Background

Gastrointestinal microbiota, particularly dysbiosis of gut microbiota composition have been correlated with the progression of autoimmune disorders, such as undifferentiated spondyloarthritis (USPA).

Objectives

This study aimed to identify the changed gut microbiota and its relationship with lymphocyte subsets and cytokines in USPA Patients.

Methods

A total of 210 participants were recruited in this study, comprising 105 USPA patients and 105 age and sex-matched healthy controls (HCs). Microbial genome was extracted from approximately 250mg fresh fecal samples from all participants using QIAamp PowerFecal DNA Kit (Qiagen). The V3-V4 variable regions of bacterial 16S rRNA genes were sequenced with the Illumina Miseq PE300 system. QIIME2 was used to process representative sequence clusters with a similarity cutoff of 100% (ASVs)1. Microbial diversity was estimated by the alpha diversity (observed, chao1, ACE, shannon, simpson, and ivsimpson) and beta diversity (bray distance). Biomarker species were identified based on STEMP between USPA and HC group. Correlations were analyzed with the Spearman rank correlation test.

Results

The alpha-diversity indices have no significant different between two groups (P >0.05, Figure 1A). Gut microbial community structure differed between USPA and HC, as revealed by ASV Bray–Curtis distances (P <0.05, Figure 1B). As for composition of gut microbiota, there were the increased levels of Escherichia_Shigella, Flavonifractor, Hungatella in the USPA group, and Lachnospirales, Roseburia, and Lachnospiraceae in HCs (Figure 1C). The relative abundance of Lachnospiraceae_UCG_001 and Enterobacter was negatively correlated with the absolute numbers of Th17 (P<0.05). Bifidobacterium was positively correlated with the absolute number of Th1 and Tregs (P<0.01, Figure 1D). The relative abundance of Fusobacterium, Incertae_Sedis, and Colidextribacter were negatively correlated with the absolute numbers of Il-10, IL-4, and IL-2 (P<0.05). Prevotella and Enterobacter were positively correlated with the absolute number of IL-6 and IL-4 respectively (P<0.05, Figure 1E). Bifidobacterium and Bilophila were neagtively correlated with the absolute number of NK cell (P<0.05, Figure 1F).

Figure 1.

(A) Comparison of alpha-diversity indexs between HC and USPA groups was shown using boxplot. (B) β diversity of the gut microbiome in USPA patients and HCs. Principal coordinate analysis plot generated from the bray distance analyse. (C) STEMP was used to detect difference in Flora according to USPA and HC. (D-F) Relationship between gut microbiota, and Lymphocyte subsets as well as cytokines. *P<0.05, **P<0.01.

Conclusion

Gut dysbiosis in USPA patients mainly characterized by reduced the diversity and impaired abundance of the intestinal flora, which was closely related to the disturbance of lymphocyte subpopulations and cytokines.

References

[1]Han L, Zhao K, Li Y, et al. A gut microbiota score predicting acute graft-versus-host disease following myeloablative allogeneic hematopoietic stem cell transplantation. Am J Transplant 2020;20(4):1014-27. doi: 10.1111/ajt.15654 [published Online First: 2019/10/13]

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared.

POS0330 DIFFERENCES IN GUT MICROBIOTA ASSOCIATED WITH LYMPHOCYTE SUBSETS, CYTOKINES AND DISEASE ACTIVITY IN ANKYLOSING SPONDYLITIS

Background

Ankylosing spondylitis (AS), a common chronic inflammatory disease, is a prototype of spondyloarthritis affecting sacroiliac joints and spine with or without peripheral arthritis and other systemic symptoms[1]. Environmental factors, especially microorganisms have been suggested to implicate with AS pathogenesis[2].

Objectives

Utilizing 16S rRNA genes sequencing on the feces of untreated AS patients and healthy controls (HCs), our study aimed to provide an in-depth understanding of AS gut microbiota and identifying a feasible diagnostic strategy for AS.

Methods

Fecal samples were collected from 62 AS patients and 62 age-and-gender- matched HCs. Microbial genome was extracted from approximately 250mg fresh fecal samples from all participants using QIAamp PowerFecal DNA Kit (Qiagen). The V3-V4 variable regions of bacterial 16S rRNA genes were sequenced with the Illumina Miseq PE300 system. QIIME2 based pipeline was used to process the raw sequence data. Alpha and beta diversities were assessed using result from QIIME2, and comparisons of gut microbiome profile were performed using linear discriminant analysis (LDA) effect size (LEfSe) to examine differences between AS and HCs. R (version 4. 0.1) was used for comparative statistics, and pearson’s correlation was used to assess the correlations between the relative abundances of bacterial genera and clinical parameters; correlations with p<0.05 were considered significant.

Results

AS for alpha-diversity, ACE and Chao1 indices were lower in AS compared with those HCs(Figure 1A, p<0.05), though no significant differences observed in Shannon and Simpson index. Bray curtis distance-based beta-diversity analysis revealed significant differences in the microbial community between AS and HCs (Figure 1B, p=0.003, ANOSIM). Fecal microbial communities in AS differed significantly from those in HCs, driven by higher abundances of Escherichia-Shigella, Turicibacter, Enterococcus, et al. and a lower abundance of Agathobacter, Roseburia, Eubacterium_eligens_group, et al (Figure 1C, p<0.05). There was a significant positive correlation between ESR and Klebsiella, Butyricicoccus, Roseburia, CRP and Faecalibacterium, Muribaculaceae, ASDAS-CRP score and Faecalibacterium, Ruminococcus, total lymphocyte cells and Agathobacter, Ruminococcus, T cell and Agathobacter, CD4+T cell and Agathobacter, B cell and Agathobacter, Streptococcus, Th1 and Prevotella, CAG−352, Th2 and Agathobacter, Th17 and Prevotella, Agathobacter, IL-2 and Agathobacter, IL-4 and Agathobacter, IL-6 and Lachnospiraceae_UCG−004, Muribaculaceae, IL-17 and Eubacterium_hallii_group, IFN-gama and Phascolarctobacterium.There were negative correlations between total lymphocytes and Escherichia−Shigella, CD4+T cell and Enterobacteriaceae, Th2 cell and Escherichia−Shigella, IL-10 and CAG−352, Ruminococcus (Figure 2, p<0.05).

Figure 1.

Feature of gut microbiota in AS patients and HCs. (A) Alpha-diversity assessed by richness (Chao1, ACE) and diversity (Shannon, Simpson), Median estimates compared across cohorts. (B) PCoA plot based on the Bray curtis distance of gut microbiota samples from AS patients vs. HC group(p=0.003, ANOSIM). (C) Panel demonstrated the average relative abundance of different genus in AS and HCs. (D) Distribution of gut microbiota at genus level.

Figure 2.

Correlations between the relative abundance of significantly different bacteria and clinical variables. *p<0.05, **p < 0.01, ***p <0 .001, ****p < 0.0001.

Conclusion

Human gut microbiome in patients with AS differed from that of the HCs. Characters of bacteria communities were associated with disease activity.

References

[1]Simone D, Al Mossawi M H, Bowness P. Progress in our understanding of the pathogenesis of ankylosing spondylitis [J]. Rheumatology (Oxford), 2018, 57(suppl_6): vi4-vi9.

[2]Zhou C, Zhao H, Xiao X Y, et al. Metagenomic profiling of the pro-inflammatory gut microbiota in ankylosing spondylitis [J]. J Autoimmun, 2020, 107(102360.

Acknowledgements

This project was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS1353 COMPOSITION AND ASSOCIATIONS OF THE GUT MICROBIOTA IN BECHET’S DISEASE WITH PERIPHERAL LYMPHOCYTE SUBSETS AND CYTOKINES

Background

Bechet’s disease (BD) is a chronic multisystemic vasculitis with genetic and abnormal immune response. Growing evidences suggests gut microbiota compositional alteration may have an association with immune dysfunction in patients with BD.

Objectives

This study aims to investigate the gut microbiota between BD and healthy controls (HCs) and analyse relevancy between bacterial and peripheral lymphocyte subsets and cytokines.

Methods

Fecal samples obtained from 22 BD patients and 22 normal-age and gender-matched HCs in this study. The gut microbiota were assessed with 16s rRNA sequencing and the flow cytometry was used to dectect peripheral lymphocyte subsets. C-reaction protein (CRP), Erythrocyte sedimentation rate (ESR), complement C3 and C4 were also assigned for disease activity measure. The edgeR package was used for differential abundance analysis. Difference of alpha diversity indices, bacterial abundances, and the F/B ratio were carried out using the Wilcoxon rank-sum test (R v.4.0.1). The differential abundance of flora and CRP, ESR, C3 and C4 between BD patients and HCs was assessed by pearson’s correlation analysis.

Results

As for alpha diversity, the Shannon (p < 0.05) and Simpsonance analysis. Difference of alpha diversity indices, bacterial abundances, and the F/B ratio were carried out using the Wilcoxon rank-sum test (R v.4.0.1). The differential abundamicrobial community structures between BD and HCs (R = 0.053, p = 0.051; Figure 1B). The gut microbiota compositions of BD differed form those of HCs (Figure 1C). Four species of flora distinctly difference were found in BD (p < 0.05; Figure 1D). There was significant positive correlations between Tregs and Verrucomicrobiota (p < 0.05), and Proteobacteria (p < 0.05), Th1 and Proteobacteria (p < 0.05), ESR and Verrucomicrobiota (p < 0.01), but negatives correlation between TNF-α and Desulfobactbiota (p < 0.05; Figure 1E).

Conclusion

Pattients with CTD had disbiosis of gut microbiota charaterized by impared diversity and abnomal composition, which was closely correlated with peripheral lymphocyte subsets and disease activity measures.

References

[1]Margaret Alexander, Qi Yan Ang, Renuka R Nayak, et al. Human gut bacterial metabolism drives Th17 activation and colitis. Cell Host Microbe. 2022 Jan 12;30(1):17-30.e9. doi: 10.1016/j.chom.2021.11.001. Epub 2021 Nov 24.

[2]Yi-Wen Tsai, Jia-Ling Dong, Yun-Jie Jian, et al. Gut Microbiota-Modulated Metabolomic Profiling Shapes the Etiology and Pathogenesis of Autoimmune Diseases. Microorganisms. 2021 Sep 10;9(9):1930. doi: 10.3390/microorganisms9091930.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0492 INTESTINAL MICROBIOLOGICAL DISORDER CLOSELY ASSOCIATED WITH PERIPHERAL LYMPHOCYTE SUBSETS AND CYTOKINES IN SYSTEMIC LUPUS ERYTHEMATOSUS

Background

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by widespread inflammation and tissue damage in multiple organs[1]. Microbiome is one of environmental factors that has been suggested to contribute to the occurrence and development of SLE[2].

Objectives

This study aims to the understanding of the pathogenesis of SLE from the perspective of intestinal microorganisms and investigate the associations between flora and peripheral lymphocyte subpopulations and cytokines in SLE patients.

Methods

Fecal samples were collected from 96 patients with SLE, and 96 sex-and age-matched healthy controls (HCs). The gut microbiota were investigated via 16s rRNA sequencing and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. Indicators of disease activity such as erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), complement C3 and C4 were recorded. Differential abundance analysis was carried out using the edgeR algorithm. The Wilcoxon rank-sum test was used to compare alpha diversity indices, bacterial abundances, and the F/B ratio between groups. R (version 4.0.1) was used for comparative statistics, and pearson’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and serum levels of ESR, CRP, C3 and C4 in the samples; correlations with p < 0.05 were considered significant.

Results

The alpha estimators of richness (ACE and Chao 1) were significantly reduced in SLE feces samples compared with those of HCs (p < 0.0001). Bacterial diversity estimators, including the Shannon (p < 0.001) and Simpson’s (p < 0.01) indices, were also significantly lower in SLE (Figure 1A-D). The microbial community structures of the SLE and HCs could be separated by unweighted UnFrac-based principal coordinates analysis (PCoA) (R = 0.186, and p = 0.001; Figure 1E). Significant differences in gut microbiota composition between SLE and HCs were found using the edgeR algorithm. Compared with HCs, 24 species of flora were discovered to be distinctly different(p < 0.05). Moreover, there was a significant positive correlation between Tregs and Corynebacterium(p < 0.05), CD8+T and Corynebacterium (p < 0.05), CD4+T and Corynebacterium (p < 0.05), T and Corynebacterium (p < 0.05), Th1 and Escherichia−Shigella (p < 0.01), Th2 and Dielma (P<0.001) as well as Eubacterium eligens group (p < 0.05), NK and Faecalibacterium (p < 0.01). as well as Corynebacterium (p < 0.001), IL-6 and Coprococcus (p < 0.05), IL-10 and Eubacterium eligens group (p < 0.001) as well as Veillonella (p < 0.05). and Lachnospira (p < 0.01). As for clinical disease measures, there were positive correlations between CRP and Eubacterium ventriosum (p < 0.05). and Coprococcus (p < 0.05), C4 and the abundance of Corynebacterium (p < 0.05) (Figure 1F).

Conclusion

Patients with gut dysbiosis that mainly characterized by reduced the diversity and impaired abundance of the intestinal flora. Abnormality of T cell subsets and cytokines, especially the level of CD4+T, CD8+T, NK, Treg, Th, IL-6 and IL-10 cells contributes to the occurrence and progression of SLE, which may be related to the disturbance of gut microbiota. The discovery of the associated intestinal microbiota of SLE may provide a new idea for treatment.

References

[1]Fava A, Petri M. Systemic lupus erythematosus: diagnosis and clinical management. J Autoimmun. (2019) 96:1–13. 10.1016/j.jaut.2018.11.001

[2]He Z, Shao T, Li H, Xie Z, Wen C: Alterations of the gut microbiome in Chinese patients with systemic lupus erythematosus. Gut pathogens 2016, 8:64.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS0556 ALTERATION OF THE GUT MICROBIOTA IN CHINESE POPULATION WITH RHEUMATOID ARTHRITIS

Background

Rheumatoid arthritis (RA) is an aggressive immune-mediated joint disease characterized by synovial proliferation and inflammation, cartilage destruction, and joint destruction. Growing evidences suggests a chronic inflammatory response induced by gut microbiome critically contribute to the development of rheumatoid arthritis.

Objectives

The aim of this study was to evaluate and quantify differences in the composition of gut microbiota in RA patients and investigate the associations between flora and clinical variables in RA patients.

Methods

Fecal samples from 145 RA patients and 145 age- and gender- matched healthy controls (HCs) were collected for bacterial 16S rRNA genes sequencing. The alpha-diversity, beta-diversity and the microbial composition (at the phylum and genus level) analysis of the gut microbiome were used to define the difference of gut microbiota profiles between RA patients and HCs. The peripheral lymphocytes of these patients were assessed by flow cytometry, and inflammatory biomarkers (ESR, CRP), auto-antibodies(ACPA, MCV) and cytokines measured by ELISA were recorded. Correlations between different taxa and clinical variables, were calculated by Spearman’s rank test.

Results

Consistent with trends observed for diversity, patients with RA had a lower richness compared with those of HCs (p < 0.01, Figure 1a), suggesting gut microbiome was markedly less diverse in composition in RA. Bray curtis distance-based beta diversity analysis revealed significant differences in the microbial community between RA and HCs (ANOSIM, R2=0.061, p=0.001, Figure 1b). Ten selected taxonomic biomarkers at different phylogenetic levels showed great discriminant ability, with Log10 LDA score > 4.0 (Figure 1e-g). Detailly, at the phylum level, RA patients had a lower frequency of Firmicutes while higher Proteobacteria. RA patients presented fewer Faecalibacterium but more Escherichia_Shigella at the genus level (Figure 1c-d). PICRUSt analysis found that in the KEGG pathways, the microbial gene functions related to Propanoate metabolism were higher in the fecal microbiome of RA patients (Figure 1h). Escherichia_Shigella positively correlated with ACPA antibodies (r=0.176, p < 0.05) and IL-4 (r=0.204, p < 0.05, Figure 1i), wheras Faecalibacterium as a probiotic showed no significant correlation with our clinical measures.

Figure 1.

Conclusion

Specific gut microbiota played an important role in the pathogenesis of RA, which may aid in the diagnosis or determination of the susceptibility of individuals to RA via detection of the gut microbiome.

References

[1]de Oliveira GLV, Leite AZ, Higuchi BS, et al. Intestinal dysbiosis and probiotic applications in autoimmune diseases. Immunology 2017;152(1):1-12. doi: 10.1111/imm.12765

[2]Chen J, Wright K, Davis JM, et al. An expansion of rare lineage intestinal microbes characterizes rheumatoid arthritis. Genome Med 2016;8(1):43. doi: 10.1186/s13073-016-0299-7

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared.

POS0143 COMPOSITION AND ASSOCIATIONS OF THE GUT MICROBIOTAWITH PERIPHERAL LYMPHOCYTE SUBSETS AND CYTOKINES IN IDIOPATHIC INFLAMMATORY MYOPATHIES

Background

The idiopathic inflammatory myopathies (IIM) are a group of acquired myopathies characterized by inflammatory lymphocytes infiltrates in muscle tissue1.Gut microbiota serves as a critical environmental component of autoimmune disease pathogenesis such as IIM2.

Objectives

This study sought to investigate the composition of gut microbiota and the relationship between microbiota structure and lymphocyte subpopulations and cytokines in IIM patients to recommend feasible intervention strategies.

Methods

Faecal samples were taken from 37 IIM patients and 37 age- and gender- matched healthy controls (HCs) in a sterile environment placed into the Second Hospital of Shanxi Medical University. Microbiome profiling was performed by sequencing of the V3-V4 variable regions of the 16S rRNA gene and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. The clinical laboratory data such as erythrocyte sedimentation rate (ESR), C-reactive protein (CRP) and immunoglobulin were also determined. In terms of gut microbia, the diversity and richness was evaluated from two aspects: alpha diversity and beta diversity with the indices of ACE, Chao1, Shannon and Simpson. Analyses were conducted using R version 4.0.1. Pearson correlation was applied to assess the relationship between the relative abundances of bacterial genera and clinical parameters, and p < 0.05 was considered to be statistically significant.

Results

The α-diversity analysis of the richness (Chao1) and diversity (Shannon and Simpson) were reduced in IIM samples compared with those of HCs (Figure 1A, p < 0.05). Bray curtis distance-based beta diversity analysis revealed significant differences in the microbial community between IIM and HCs (Figure 1B, p = 0.001, ANOSIM). Detailly, at the genera level, IIM patients had a higher abundance of Enterococcus, Veillonella, Streptococcus, et al. and a lower abundance of Roseburia, Lachnospira, Klebsiella, et al(Figure 1D, p < 0.05). In IIM patients, Fusobacteriota correlated positively with the ratio of Th1 cells (Figure 1E, p < 0.01), and there was a significant positive correlation between Synergistota and B lymphocyte (Figure 1E, p < 0.01). Besides, Euryarchaeota and Cyanobacteria were both positively and significantly related to IL-6, IFN-γ and C-reactive protein (CRP) (Figure 1E, p < 0.001).

Conclusion

Richness and diversity of intestinal flora in IIM patients were impaired, which might participate in the pathogenesis of IIM by disturbing lymphocyte subpopulations and cytokines. Regulating intestinal flora and restoring homeostasis might become a critical therapeutic methods of IIM.

References

[1]Xu Y, Sun J, Wan K, et al. Multiparametric cardiovascular magnetic resonance characteristics and dynamic changes in myocardial and skeletal muscles in idiopathic inflammatory cardiomyopathy. J Cardiovasc Magn Reson 2020;22(1):22. doi: 10.1186/s12968-020-00616-0.

[2]Mariampillai K, Granger B, Amelin D, et al. Development of a New Classification System for Idiopathic Inflammatory Myopathies Based on Clinical Manifestations and Myositis-Specific Autoantibodies. JAMA Neurol 2018;75(12):1528-1537. doi: 10.1001/jamaneurol.2018.2598.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0500 THE LEVEL OF PERIPHERAL BLOOD LYMPHOCYTE SUBSETS IN PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS WITH RESPIRATORY TRACT INFECTION AND ITS CLINICAL SIGNIFICANCE

Background

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disorder. Infections are a most common cause of morbidity and mortality in this patient population[1] and at least 50% of patients with SLE are suffered with infections during the course of their disease [2]. Lymphocytes and Natural killer (NK) cells play an important role in the occurrence and development of SLE[3]. In this study, peripheral blood lymphocyte subsets were detected in these patients, providing reference for early diagnosis and treatment of SLE patients with respiratory tract infection.

Objectives

To analyze the detection level and clinical significance of peripheral blood lymphocyte subsets in patients with SLE with respiratory tract infection.

Methods

A total of 333 SLE patients with no recent infection, 95 SLE patients with respiratory tract infection, and 132 healthy individuals matched in age and sex were enrolled in the second Hospital of Shanxi Medical University from July 2014 to December 2016. The characteristics of lymphocyte subsets in the three groups were compared and receiver operating characteristic (ROC) curves were drawn to analyze the predictive value of lymphocyte subsets in SLE patients with respiratory tract infection.

Results

The counts of T, B, CD4 + T, CD8 + T, NK, Th1, Th2, Th17 and Tregs in SLE non-infection group and SLE infection group were [(1094.235 ± 574.495) / (702.781 ± 432.152), t= -7.169, P < 0.001], [(208.338 ± 210.448) / (177.55 ± 170.256), t = -1.306, P = 0.192], [(503.382 ± 303.498) / (304.075 ± 215.497), t = -7.168, P < 0.001], [(536.705 ± 344.218) / (358.034 ± 235.234), t = -5.802, P < 0.001], [(113.898 ± 101.48) / (61.768 ± 50.127), t = -6.831, P < 0.001], [(86.268 ± 89.081) / (47.92 ± 54.174), t = -3.367, P = 0.001], [(11.363 ± 9.834) / (6.628 ± 6.434), t = -3.622, P < 0.001], [(9.537 ± 10.12) / (5.346 ± 4.731), t = -3.646, P < 0.001], [(25.736 ± 27.013) / (20.78 ± 28.083), t =-1.037,P=0.301] (Figure 1).The above indexes in SLE infection group were lower than those in SLE non-infection groups. When lymphocyte subsets predict pulmonary infection in SLE, the AUC value of CD4 + count is the highest, and the cut-off is 387/ μ l(Table 1). The sensitivity and specificity of predicting SLE pulmonary infection were 75.8% and 38.6%(Figure 2).

Table 1.

Predictive value of peripheral blood lymphocyte subsets in SLE complicated with respiratory tract infection

IndicatorAUCP valueJordan indexcut-offSusceptibilitySpecificity(%)(%)B0.5690.04083.99500.1830.4210.238CD40.714<0.0010.3723870.7580.386CD80.682<0.0010.3254050.7260.401CD4+ T /CD8+ T0.5690.0410.0000.7850.5370.370NK0.687<0.0010.30982.50.7680.460

Conclusion

The absolute number of these subsets in infected SLE patients is significantly lower than that in uninfected patients, which indicates that the low absolute number of these cells can be used as an indicator of high infection risk in SLE patients. CD4 + T lymphocytes and NK cells in patients with respiratory tract infection are significantly lower, and can play a certain predictive value for SLE respiratory tract infection to a certain extent.

References

[1]Kedves M, Kosa F, Kunovszki P, Takacs P, Szabo MZ, et al. 2020. Large-scale mortality gap between SLE and control population is associated with increased infection-related mortality in lupus. Rheumatology (Oxford) 59:3443-51

[2]Wang J, Niu R, Jiang L, Wang Y, Shao X, et al. 2019. The diagnostic values of C-reactive protein and procalcitonin in identifying systemic lupus erythematosus infection and disease activity. Medicine (Baltimore) 98:e16798

[3]Luo Q, Kong Y, Fu B, Li X, Huang Q, et al. 2021. Increased TIM-3(+)PD-1(+) NK cells are associated with the disease activity and severity of systemic lupus erythematosus. Clin. Exp. Med.

Disclosure of Interests

None declared

POS0212 THE REDUCTION OF TURICIBACTER IN GUT MICROBIOTA ASSOCIATED WITH SJOGREN’S SYNDROME SECONDARY TO RHEUMATOID ARTHRITIS

Background

Secondary Sjogren’s syndrome(SS) is a common extra-articular manifestation of rheumatoid arthritis (RA)[1]. RA patients combined with SS have different outcomes from those without SS[2]. However, the studies investigated the characteristics of gut microbiota in patients with RA and SS is limited.

Objectives

To investigate the characteristics of gut microbiome and the associations between flora and peripheral lymphocyte subpopulations in RA patients with or without Sjogren’s syndrome.

Methods

A total of 326 samples from 145 RA patients without SS, 23 RA combined with SS patients(RA-SS) and 168 healthy controls (HCs) were recruit in this study from The Second Hospital of Shanxi Medical University (Taiyuan, Shanxi, China). The gut microbiota were investigated via 16s rRNA sequencing and the peripheral T lymphocyte subsets of these participants were assessed by flow cytometry. The Wilcoxon rank-sum test was used to compare alpha diversity indicesbetween groups. Differential abundance analysis was carried out the STAMP software. Spearman’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and clinical meatures.

Results

Patients with RA and RA-SS exhibited a significant reduction in the richness and diversity of gut microbiota compared with those of HCs (Figure 1 A-B, p < 0.05), whereas there was no significant difference between RA and RA-SS patients. Principal co-ordinates analyses based on bray curtis distance suggested that these there microbiota states explained a definable proportion of observed variance in microbiota composition (ANOSIM R2 = 0.074, p < 0.001; Figure 1 C). Compared with HCs, 58 species of flora were discovered to be distinctly different in RA patients without SS at the genus level of which 6 species of flora unique to RA-SS patients were presented much fewer ([Eubacterium]_hallii_group, Anaerostipes, CAG-56, Fusobacterium, Turicibacter and Enterococcus). Among these RA-SS patients‘ unique species of flora, it seems that Turicibacter is the key species of flora, owing to whose has a positive correlation with most of lymphocytes such as T, B, CD4+T, CD8+T and NK cells suggesting a close association with intestinal immunity.(Figure 1 F-G,P<0.05)

Conclusion

RA patients with deficiency of Turicibacter in flora had higer occurrence of Sjögren’s syndrome sjogren’s syndrome complication, which was correlated with peripherial lymphocyte subpopulations and cytokines.

References

[1]Chen Y, Ma C, Liu L, He J, Zhu C, Zheng F, Dai W, Hong X, Liu D, Tang D et al: Analysis of gut microbiota and metabolites in patients with rheumatoid arthritis and identification of potential biomarkers. Aging 2021, 13(20):23689-23701.

[2]Brown LE, Frits ML, Iannaccone CK, Weinblatt ME, Shadick NA, Liao KP: Clinical characteristics of RA patients with secondary SS and association with joint damage. Rheumatology (Oxf) 2015, 54(5):816-820.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0523 THE ENTEROTYPES OF THE GUT MICROBIOTA IN CHINESE POPULATION WITH AUTOIMMUNE DISEASE

Background

An increasing number of autoimmune disorders (AD) have been associated with microbial dysbiosis[1, 2]. However, this dysbiosis is difficult to characterize for individual patients owing to the high heterogeneity of the gut microbiota. Thus, researchers must find an accurate method of characterizing the AD gut microbiota that is meaningful to clinical diagnosis.

Objectives

The aim of this study was to investigate the enterotype characters of intestinal flora in AD and their associations with peripheral lymphocyte subpopulations and cytokines.

Methods

A total of 339 AD patients and 339 age- and sex- matched healthy controls (HCs) were enrolled in this study. Mathematical modeling using Dirichlet multinomial mixtures (DMM) was applied to describe the variability in the microbiome data and cluster samples into enterotypes. The peripheral lymphocyte subsets were detected by flow cytometry and the cytokines were assessed by ELISA. Differential abundance analysis was carried out the STAMP software. R (version 4.1.0) was used for comparative statistics, and spearman’s correlation analysis was used to assess the correlations between the relative abundances of bacterial genera and clinical variables.

Results

Laplace approximation of DMM suggested gut microbiota of AD patients and HCs both can be divided into two distinct enterotypes (Figure 1 A-B), and AD E1 and HC E1 were primarily dominated by Prevotella while AD E2 and HC E2 by Bacteroides. Interestingly, the Prevotella-enriched enterotype (AD E1 and HC E1) had a higher alpha diversity than The Bacteroides-enriched enterotype (AD E2 and HC E2). Patients with AD always had a lower richness and diversity compared with those of HCs in each enterotype (p< 0.001), suggesting gut microbiome was markedly less diverse in composition in AD. Bray curtis distance-based beta-diversity were also different (P<0.001, ANOSIM.R =0.23, Figure 1 C-H). Significant differences in gut microbiota composition at the genus level between AD patients and HCs were found using the STAMP software in each enterotype. Compared with HCs, 37 species in AD E1 patients and 40 species in AD E2 patients of flora were discovered to be distinctly different. In the co-upregulated flora of both enterotypes, Lactobacillus was inversely associated with a variety of lymphocytes such as T, CD4+T, NK, Th2, Th17, Treg cells(P<0.05), and positive correlation with IL-10 and IFN-γ(P<0.05,Figure 1 I). However, in the co-downregulated floras Coprococcus had a positive correlation with B, NK and Treg cells, and anaerostipes had a negativate corrleation with IL-2 and IL-4(P<0.05,Figure 1 J).

Conclusion

There were both two enterotypes in patients and HCs with autoimmune disease, E2 exhibited a loss of Prevotella but a growth of Bacteroides, while E1 presented the opposite results, which were closely correlated with peripheral lymphocyte subsets and cytokines.

References

[1]Levy M, Thaiss CA, Zeevi D, Dohnalová L, Zilberman-Schapira G, Mahdi JA, David E, Savidor A, Korem T, Herzig Y et al: Microbiota-Modulated Metabolites Shape the Intestinal Microenvironment by Regulating NLRP6 Inflammasome Signaling. Cell 2015, 163(6):1428-1443.

[2]Belkaid Y, Hand TW: Role of the microbiota in immunity and inflammation. Cell 2014, 157(1):121-141.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

POS1153 CHARACTERISTICS OF GUT MICROBIOME AND THEIR ASSOCIATIONS WITH PERIPHERAL LYMPHOCYTE SUBPOPULATIONS AND CYTOKINES IN RHEUMATOID ARTHRITIS PATIENTS COMPLICATED WITH OSTEOPOROSIS

Background

Osteoporosis(OP) is one of the major comorbidities of rheumatoid arthritis(RA) which is associated with immune disorders[1]. The gut microbiota has been highlighted to be an important environmental factor to influence immune system in maintaining bone health and regulating bone remodeling[2]. However, the alterations of intestinal flora and its relationship with immune system in RA patients with OP are unclear.

Objectives

To investigate the characteristics of gut microbiome as well as the associations between flora and peripheral lymphocyte subpopulations and cytokines in rheumatoid arthritis patients complicated with osteoporosis.

Methods

Total 28 RA patients were divided into 14 RA-non-OP and 14 gender- and age-matched RA-OP groups according to their bone mineral density (BMD) and the history of fragility fracture. Gut microbiota of participants were investigated by 16s rRNA and peripheral lymphocyte subsets and cytokines were assessed via flow cytometry. Indicators like erythrocyte sedimentation rate (ESR), C-reaction protein (CRP), anti-cyclic citrullinated peptide antibody (ACPA) and anti-mutated citrullinated vimentin (MCV) antibody were recorded meanwhile. Alpha diversity (ACE, Chao1, Simpson, Shannon) and beta diversity indices were analyzed using QIIME2. Biomarker species were recognized based on STEMP. Spearman analysis was adopted for correlation of two variables. All P-values reported herein were two-tailed and P-value<0.05 was taken as statistically significant.

Results

The alpha-diversity have no significant difference between RA-non-OP and RA-OP groups (P >0.05, Figure 1A). The community structure of microflora differed between two groups (P <0.05, Figure 1B). As for the composition of intestinal flora at genus level, Faecalibacterium, Proteus, Catenibacterium, Enterobacter and Erysipelatoclostridium in RA-OP group as well as Lachnospiraceae_ND3007_group, Parasutterella, Megasphaera, Tyzzerella, UCG-005, Clostridium_sensu_stricto_1, UCG-002, Lachnospiraceae_NK4A136_group, Christensenellaceae_R-7_group, Prevotella, Parabacteroides in RA-non-OP group were significantly increased (Figure 1C). There were positive correlations between Lachnospiraceae_NK4A136_group and the level of T, Th1 and Th17 cells, but negative relevance with ESR, CRP and IL-10 (P <0.05). The relative abundance of Faecalibacterium was negatively correlated with IL-2, IL-4, TNF-α and positively with MCV (P <0.05). Clostridium_sensu_stricto_1 and Lachnospiraceae_ND3007_group were negatively correlated with ACPA and MCV respectively as well as IL-2 (P <0.05, Figure 1D-E).

Conclusion

Abnormality of immune system may contribute directly or indirectly to OP in RA, which may be related to the disturbance of gut microbiota.

References

[1]Horta-Baas G, Romero-Figueroa MDS, Montiel-Jarquín AJ, et al. Intestinal Dysbiosis and Rheumatoid Arthritis: A Link between Gut Microbiota and the Pathogenesis of Rheumatoid Arthritis. J Immunol Res. 2017;2017:4835189.

[2]Raterman HG, Bultink IE, Lems WF. Osteoporosis in patients with rheumatoid arthritis: an update in epidemiology, pathogenesis, and fracture prevention. Expert Opin Pharmacother. 2020 Oct;21(14):1725-1737.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

AB0844 Characterizing Gut Microbial Enterotypes in undifferentiated spondyloarthritis

Background

The presence of dysbiosis in the gut microbiome is responsible for the initiation of autoinflammatory and autoimmune diseases. However, such dysbiosis is difficult to characterize in sweeping generalization owing to the high dimensional complexity of the gut microbiota.

Objectives

This study designed to characterize the gut microbial enterotype in patients with undifferentiated spondyloarthritis (USpA) from lower dimensionality and describe the dysbiosis.

Methods

The Fecal samples of 105 patients were diagnosed with USpA and gender- and age- matched 105 healthy controls (HC) were included in the intestinal microbiota composition analyses via Illumina sequencing of bacterial 16S rRNA genes. Microbiota-derived clustering was performed using Dirichlet multinomial mixtures (DMM) modeling. To identify discriminative features in abundance between enterotypes, the Linear Discriminant Analysis Effect Size (LEfSe) algorithm was used with the online interface Galaxy (Log10 LDA score > 4.0). The phyloseq R package to compute alpha diversity (ACE, Chao1, Shannon and Simpson indices), beta diversity (Bray-Curtis dissimilarity) and the microbial composition (at the genus level) to describe the richness and diversity of the microbiota between two enterotypes.

Results

As showed in Figure 1A and C, by evaluating the Laplace approximation to the negative log mode, 2 distinctly enterotypes were identified in the USpA and HC microbiota dataset. LEfSe Analysis indicated the distinctive abundant microbial clades between the 2 enterotypes (LDA score >4) in both the USpA and HC group respectively. At the genus level, Faecalibacterium and Prevotella was the driving genus of enterotype 1 and Bacteroides contributed to enterotype 2 (Figure 1B, D). The alpha-diversity and beta diversity between the distinctive enterotypes was highly significantly different (P < 0.01, Figure 1E, F). Distinct bacterial profiles were also observed in enterotype 1 and 2 (Figure 1G). Interestingly, no significant differences were found between USpA patients and HC for the corresponding same intestinal type. This may be because USpA was at a comparatively early stage of spondyloarthritis (SpA).

Conclusion

Two significantly distinct bacterial microbiota structures existed in the USpA patients which was consistent with the general healthy population.

References

[1]Belkaid Y, Hand TW: Role of the microbiota in immunity and inflammation. Cell 2014, 157(1):121-141.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared

OP0087 INTEGRATED SYSTEMS ANALYSIS OF THE GUT MICROBIOTA PHENOTYPES IN THE RHEUMATOID ARTHRITIS

Background

Patients with rheumatoid arthritis (RA) displays extreme dysbiosis in microbiota. However, such dysbiosis is difficult to characterize owing to the high dimensional complexity of the gut microbiota1,2.

Objectives

The aim of this study was to discover the enterotype characters of intestinal flora in RA.

Methods

Fecal samples from 145 RA patients were collected for bacterial 16S rRNA genes sequencing. Mathematical modeling using Dirichlet multinomial mixtures (DMM) was applied to describe the variability in the microbiome data and cluster samples into enterotypes. The alpha-diversity, beta-diversity and the microbial composition analysis of the gut microbiome were used to define the difference of gut microbiota profiles between different enterotypes. The nonredundant taxonomic biomarkers for each enterotype were selected by using LEfSe. Inflammatory biomarkers (ESR, CRP), auto-antibodies(ACPA, MCV), peripheral lymphocytes subsets and cytokines were analyzed in our cohort using the Kruskal-Wallis test.

Results

Laplace approximation of DMM indicated two significantly distinct bacterial microbiota structures (RAE1 and RA E2) existed in the dataset (Figure 1a). Principal co-ordinates analyses confirmed that these two microbiota states explained a reasonable proportion of observed variance in microbiota composition(ANOSIM R2 = 0.267, p = 0.001; Figure 1b), with distinct bacterial genus distribution of in each enterotype (Figure 1c). RA E1 were primarily dominated by Prevotella while RA E2 by Bacteroides. Interestingly, Chao1, ACE, Shannon and Simpson revealed a higher alpha diversity in Prevotella-enriched enterotype (p< 0.001, Figure 1d). Fourteen selected taxonomic biomarkers at different phylogenetic levels showed great discriminant ability, with Log10 LDA score > 4.0 (Figure 1e-g). Further, inflammatory biomarkers (ESR, CRP) and auto-antibodies(ACPA, MCV) as well as the number of T, B and CD4+T, Th1, Th2, Th17, and Treg were consistent in RA E1 and RA E2 (p > 0.05, Figure 2h). But CD8+T were significantly higher in RA E2 than in RA E2 (p < 0.05).

Conclusion

Despite RA gut microbiota being of different dysbiosis, two patterns of dysbiosis, designated as RA-enterotypes, were predominant among the RA patient cohort. RA E2 exhibited a loss of Prevotella but a growth of Bacteroides, while RA E1 presented the opposite results.

References

[1]Arumugam M, Raes J, Pelletier E, et al. Enterotypes of the human gut microbiome. Nature 2011;473(7346):174-80. doi: 10.1038/nature09944

[2]Costea PI, Hildebrand F, Arumugam M, et al. Enterotypes in the landscape of gut microbial community composition. Nat Microbiol 2018;3(1):8-16. doi: 10.1038/s41564-017-0072-8

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 82001740).

Disclosure of Interests

None declared.

Effects of Unsuppressed Endogenous Insulin on Pharmacokinetics and/or Pharmacodynamics of Study Insulin in the Healthy: A Retrospective Study

C‐peptide, a marker of endogenous insulin, should be consistently inhibited during euglycemic clamping, while an elevated postdosing C‐peptide (CP_postdosing) is not an occasional phenomenon. This was a retrospective study that included 33 men who underwent a manual euglycemic clamp with a subcutaneous injection of insulin aspart (IAsp) aiming to describe the effects of insufficient suppression of endogenous insulin on estimates of the pharmacokinetics and pharmacodynamics of injected insulin. The time profiles of whole blood glucose, human insulin, glucose infusion rate (GIR), and C‐peptide were recorded. The subjects were divided into 2 groups at a ratio of 2:1: group A ([CP_postdosing]_max>baseline CP [CP_baseline]), group B ([CP_postdosing]_max ≤ CP_baseline). The endogenous insulin was approximately equal to the measured value of human insulin or calculated from the C‐peptide. The basal glucose, CP_baseline, basal human insulin, homeostatic model assessment of insulin resistance, IAsp dose, and demographic statistics were all comparable between the 2 groups except the “clamped” glucose. The average clamped glucose was 99.7% (group A) and 94.9% (group B) of baseline. After correction for clamped glucose, GIR area under the concentration‐time curve from time 0 to 8 hours was higher in group A (P < .05) under comparable IAsp exposure. Endogenous insulin area under the concentration‐time curve from time 0 to 8 hours calculated from C‐peptide was different from that measured from human insulin in group A (P < .05), whereas no statistical difference between these measures was observed in group B. Hence, blood glucose should be controlled below the baseline to ensure the inhibition of endogenous insulin. Unsuppressed endogenous insulin may contribute to observed GIR, and the endogenous insulin–corrected pharmacokinetics estimated by C‐peptide may be inaccurate with insufficient endogenous insulin suppression.

Medications and medical costs for diabetes patients with or without chronic respiratory disease in Beijing, China: A retrospective study

AIMS

The cost of drug regimens prescribed to Chinese patients has not been evaluated. This study aims to evaluate the medical costs and hypoglycemic agents for diabetes mellitus patients with or without chronic respiratory disease in Beijing, and to investigate the changes in the costs and number of antidiabetic medications used for diabetes patients with chronic respiratory disease from 2016 to 2018.

METHODS

This observational, retrospective study included diabetes patients with outpatient medication records from Beijing Medical Insurance between 2016 and 2018. The medications, including hypoglycemic and nonhypoglycemic drugs, insulin dosage, comorbidities, diabetes-related complications, treatment strategies, and annual medical costs, were recorded.

RESULTS

This study included 2,853,036 diabetes patients from 2016 to 2018. About 18.95%-20.53% of patients with chronic respiratory disease were predominantly distributed among those aged 45-84 years (88.7%-89.1%). Diabetes patients with chronic respiratory disease used more medications (4.48 ± 2.41 vs. 3.76 ± 2.33) and had higher total annual drug costs (¥12,286 ± 10,385 vs. ¥9700 ± 9202) to treat more comorbidities (2.52 ± 1.53 vs. 2.05 ± 1.85) than those without chronic respiratory disease (p <.0001, respectively). From 2016 to 2018, diabetes patients with chronic respiratory disease had a 4.2% increase in medication, a 1.9% decrease in comorbidities, and a 5.4% decrease in total annual drug costs.

CONCLUSIONS

In summary, diabetes patients with chronic respiratory disease had more comorbidities, required more hypoglycemic drugs, and had higher medical costs. During 2016-2018, diabetes patients with chronic respiratory disease used more medications and spent less money on medical care.

[Susceptibility factors, types and management of infection in patients with liver cirrhosis]

Patients with liver cirrhosis are prone to infection due to various reasons such as weakened immunity and intestinal bacteria translocation. Among them, bacterial infections are the most common and are the main cause for liver failure progression, leading to increased mortality, while fungal infections, mainly caused by Candida mycoderma bacteria (Candida), are usually related to delayed diagnosis. Therefore, high vigilance, timely diagnosis and treatment of infection are important means to improve the treatment effectiveness in patients with end-stage liver disease. This paper focuses on the main characteristics and treatment methods of bacterial and fungal infections in patients with liver cirrhosis.

O-110 A randomised, controlled, assessor-blind trial assessing clinical outcomes of individualised dosing with follitropin delta in Asian IVF/ICSI patients

Study question

To evaluate the efficacy and safety of individualised dosing with follitropin delta versus conventional dosing with follitropin alfa in an Asian population undergoing ovarian stimulation.

Summary answer

Individualised dosing with follitropin delta results in significantly higher live birth rate and fewer early OHSS and/or preventive interventions compared to conventional follitropin alfa dosing.

What is known already

Previous randomised controlled trials conducted in Europe, North- and South America mainly including Caucasian IVF/ICSI patients as well as in Japan have demonstrated that ovarian stimulation with the individualised follitropin delta dosing regimen based on serum AMH level and body weight modulated the ovarian response and reduced the risk of OHSS without compromising pregnancy and live birth rates.

Study design, size, duration

Randomised, controlled, assessor-blind trial conducted in 1,009 Asian patients from mainland China, South Korea, Vietnam and Taiwan, undergoing their first IVF/ICSI cycle. Randomisation was stratified by age (&lt;35, 35-37, 38-40 years). The primary endpoint was ongoing pregnancy assessed 10-11 weeks after transfer (non-inferiority limit -10.0%; analysis adjusted for age strata). Patients &lt;35 years underwent single embryo transfer if a good-quality embryo was available, otherwise double embryo transfer. Patients ≥35 years underwent double embryo transfer.

Participants/materials, setting, methods

Follitropin delta (Rekovelle, Ferring Pharmaceuticals) daily treatment consisted of a fixed dose individualised according to each patient’s initial AMH level (&lt;15 pmol/L: 12 μg; ≥15 pmol/L: 0.19 to 0.10 μg/kg; min-max 6-12 μg) and body weight. Follitropin alfa (Gonal-f, Merck Serono) dose was 150 IU/day for the first five days with subsequent potential dose adjustments according to individual response. A GnRH antagonist protocol was applied. OHSS was classified based on Golan’s system.

Main results and the role of chance

The ongoing pregnancy rate was 31.3% with follitropin delta and 25.7% with follitropin alfa (adjusted difference 5.4% [95% CI: -0.2%; 11.0%]). The live birth rate was significantly higher at 31.3% with follitropin delta compared to 24.7% with follitropin alfa (adjusted difference 6.4% [95% CI: 0.9%; 11.9%]; p &lt; 0.05). Live birth rates per age stratum were as follows for follitropin delta and follitropin alfa; &lt;35 years: 31.0% versus 25.0%, 3537 years: 35.3% versus 26.7%, 38-40 years: 20.0% versus 14.3%. Early OHSS risk, evaluated as the incidence of early OHSS and/or preventive interventions, was significantly (p &lt; 0.01) reduced from 9.6% with follitropin alfa to 5.0% with follitropin delta. The number of oocytes was 10.0±6.1 with follitropin delta and 12.4±7.3 with follitropin alfa. Individualised follitropin delta dosing compared to conventional follitropin alfa dosing resulted in 2 more oocytes (9.6±5.3 versus 7.6±3.5) in potential low responders (AMH &lt;15 pmol/L) and 3 fewer oocytes (10.1±6.3 versus 13.8±7.5) in potential high responders (AMH ≥15 pmol/L). Among patients with AMH ≥15 pmol/L, excessive response occurred less frequently with individualised than conventional dosing (≥15 oocytes: 20.2% versus 39.1%; ≥20 oocytes: 6.7% versus 18.5%). Total gonadotropin dose was reduced from 109.9±32.9 μg with follitropin alfa to 77.5±24.4 μg with follitropin delta.

Limitations, reasons for caution

The trial only covered the clinical outcome of one treatment cycle with fresh cleavage-stage embryo transfers.

Wider implications of the findings

The present trial implies that in addition to reducing the early OHSS risk, individualised dosing has the potential to improve the take-home baby rate in fresh cycles across all ages and with a lower gonadotropin consumption. The benefits in outcomes appear to be explained by the modulation of ovarian response.

Trial registration number

NCT03296527

The usefulness of the combined high-dose dexamethasone suppression test and desmopressin stimulation test in establishing the source of ACTH secretion in ACTH-dependent Cushing's syndrome

Bilateral inferior petrosal sinus sampling (BIPSS) is the current gold standard test for differentially diagnosing ACTH-dependent Cushing's syndrome (CS). However, BIPSS is an invasive procedure, and its availability is limited. We retrospectively analysed the 24-hour urinary free cortisol (UFC) level during the high-dose dexamethasone suppression test (HDDST) and plasma ACTH/cortisol levels after the desmopressin stimulation test (DDAVP test) in subjects with confirmed Cushing's disease (CD) (n = 92) and ectopic ACTH-dependent CS (EAS) (n = 16), and evaluated the positive predictive value (PPV) of the two combined-tests in the aetiological diagnosis of ACTH-dependent CS. The percent changes in UFC levels after the HDDST and in ACTH/cortisol levels after DDAVP administration relative to the corresponding basal levels and the area under the receiver operating characteristic (ROC) curve (AUC) were analysed. UFC suppression below 62.7% suggested a pituitary origin with a sensitivity (SE) of 80% (95% CI: 70-88) and a specificity (SP) of 80% (95% CI: 52-96). A threshold increase in the ACTH level after DDAVP stimulation of 44.6% identified CD with an SE of 91% (95% CI: 83-97) and an SP of 75% (95% CI: 48-93). The combination of both tests yielded an SE of 95.5% and PPV of 98.4% for CD, and significantly improved the efficiency of the differential diagnosis between CD and EAS. These dual non-invasive endocrine tests may substantially reduce the need for BIPSS in the etiological investigation of ACTH-dependent CS.

[Incidence and trend of severe postpartum hemorrhage between 2016 and 2019 in China]

Objective: To investigate the incidence and trend of severe postpartum hemorrhage (sPPH) in China, and to provide basic data for the development and evaluation of sPPH prevention and control strategy. Methods: Obstetric data was extracted from annual national representative sampling surveys based on the National Clinical Improvement System. From 2016 to 2019, 2 978, 3 400, 4 576 and 4 594 maternity hospitals with sPPH cases were included for statistics. The annual incidence of sPPH was calculated according to province and type of medical institutions and generalized linear model was emplyed to identify the determinants affecting sPPH incidence. Results: In China, sPPH incidence increased from 0.62% in 2016 to 0.93% in 2018, and was 0.92% in 2019. Eighteen provinces had an inverted U-shaped trend of sPPH over time and most of them had the highest incidence in 2018; ten provinces had an upward trend of sPPH and 3 provinces had a U-shaped trend. In 2019, the top five provinces with the highest sPPH incidence were Yunnan (1.88%), Beijing (1.45%), Jiangsu (1.31%), Guizhou (1.26%), and Ningxia Hui Autonomous Region (1.22%); the top five provinces with the lowest incidence were Henan (0.55%), Jiangxi (0.60%), Inner Mongolia Autonomous Region (0.64%), Liaoning (0.64%) and Gansu (0.69%). In 2019, the sPPH incidence in different types of medical institutions were as follows: tertiary public general hospital (1.15%), tertiary public specialized hospital (1.02%), secondary public general hospital (0.81%), private hospital (0.61%) and secondary public specialized hospital (0.58%). sPPH incidence was positively associated with proportion of twin pregnancies, macrosomia, primipara, and puerpera aged ≥35 years in maternity hospitals (P<0.05). Conclusions: sPPH incidence generally showes an increasing trend from 2016 and is stable at a high level in recent two years in China. It is warranted to further strengthen the monitoring of postpartum hemorrhage, and improve the capability of hierarchical management and treatment in maternity institutions and regions, in order to reduce sPPH incidence and maternal mortality.

POS0109 IDENTIFICATION OF PRIMARY SJOGREN’S SYNDROME SUBTYPES BY MACHINE LEARNING

Background:

Sjogren’s syndrome(pSS) is a chronic, progressive, and systematic autoimmune disease characterized by lymphocytic infiltration of exocrine glands 1 2. Sicca symptoms and abnormal fatigue are the main clinical presentation, but those symptoms are non-specific to patients, which lead to delayed diagnosis 1 3. The heterogeneous of clinical manifestation raise challenges regarding diagnosis and therapy in pSS, thus it’s necessary for us to sub-classify pSS.

Objectives:

To explore new biomarkers for diagnosis and subtypes of pSS based on Machine Learning Primary.

Methods:

All microarray raw datas (CEL files) were screened and downloaded from Gene Expression Omnibus (GEO). Meta-analysis to identify the consistent DEGs by MetaOmics. Weighted gene co-expression network analysis (WGCNA) was used to the modules related to SS for further analysis. Subclasses were computed using a consensus Non-negative Matrix Factorization (NMF) clustering method. Immune cell infiltration was used to evaluate the expression of immune cells and obtain various immune cell proportions from samples. P value < 0.05 were considered statistically significant. All the analyses were conducted under R environment (version 4.03).

Results:

A total of 3715 consistent DEGs were identified from the four datasets, including 1748 up-regulated and 1967 down-regulated genes. Tour meaningful modules, including yellow, turquoise, grey60 and bule, were identified (Figure 1A,1B). And 183 overlapping gene were screened from the DEGs and the Hub genes in the four modles for further analysis. We final divided pSS patients into three subtypes, of which yellow and turquoise in Sub1, grey60 in Sub2 and blue in Sub3. Sub1 and Sub3 were related to cell metabolism, while Sub2 had connection with virus infection (Figure 1C,1D). Infiltrated immune cells were also different among these three types (Figure 1E,1F).

Conclusion:

Patients with pSS could be classified into 3 subtypes, this classification might help for assessing prognosis and guiding precise treatment.

References:

[1]Ramos-Casals M, Brito-Zerón P, Sisó-Almirall A, et al. Primary Sjogren syndrome. BMJ (Clinical research ed) 2012;344:e3821. doi: 10.1136/bmj.e3821 [published Online First: 2012/06/16].

[2]Brito-Zeron P, Baldini C, Bootsma H, et al. Sjogren syndrome. Nat Rev Dis Primers 2016;2:16047. doi: 10.1038/nrdp.2016.47 [published Online First: 2016/07/08].

[3]Segal B, Bowman SJ, Fox PC, et al. Primary Sjogren’s Syndrome: health experiences and predictors of health quality among patients in the United States. Health Qual Life Outcomes 2009;7:46. doi: 10.1186/1477-7525-7-46 [published Online First: 2009/05/29].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0847 IDENTIFICATION OF MOLECULAR PHENOTYPES IN SYSTEMIC SCLEROSIS BY INTEGRATIVE SYSTEMS ANALYSIS

Background:

Systemic sclerosis (scleroderma, SSc) is a systemic autoimmune disease characterized by inflammation, fibrosis and vasculopathy and associated with high mortality and high morbidity1. Stratification based on whole-genome gene expression data could provide a new basis for clinical diagnosis from a micro perspective2.

Objectives:

The objective of this study is to stratify patients with SSc, combine with clinical skin scores and clinical features, and provide a preliminary assessment and novel insights for assessing disease severity, and treatment design.

Methods:

The original data mRNA expression profiles of GSE95065 (including 18 SSc patients and 4 healthy controls) and GSE130955 (including 58 SSc patients and 33 healthy controls) were downloaded from the public Gene Expression Omnibus (GEO) database. After batch correction, background adjustment, and other pre-processing, a large gene matrix was obtained to identify the differently expressed genes (DEGs) of SSc compared with healthy controls. Then the gene expression matrix decomposition was used to identify SSc subtypes by NMF algorithm. The cluster-based signature genes were applied to pathway enrichment analysis by Metascape3. Immune infiltrating cells and clinical skin scores were evaluated in all SSc subtypes.

Results:

Total 325 DEGs were imputed to NMF unsupervised machine learning algorithm. Patients were divided into 2 subtypes (Figure 1A), one of which (sub1) was mostly enriched in the defense response to bacterium and cellular response to lipopolysaccharide pathway and another subtype (sub2) was enriched in the PPAR signaling and alcohol metabolic process pathway (Figure 1B-C). According to immune infiltration, sub1 had higher level of immune cells such as B cells, CD4+T cells, DC cells, Th2 cells and Tregs compared with sub2 (P < 0.01). Sub2 had more skin-related cells, including Epithelial cells, Fibroblasts and Sebocytes (P < 0.05). Interestingly, combined with clinical information, sub1 showed a severe clinical skin score over those of Sub2 patients (P < 0.05)(Figure 1D-E).

Conclusion:

Our findings indicated that SSc patients could be stratified into 2 subtypes which had different molecular profiles of disease progression and clinical disease activities. This result could serve as a template for future studies to design stratified approaches for SSc patients.

References:

[1]Xu X, Ramanujam M, Visvanathan S, et al. Transcriptional insights into pathogenesis of cutaneous systemic sclerosis using pathway driven meta-analysis assisted by machine learning methods. PLoS One 2020;15(11):e0242863. doi: 10.1371/journal.pone.0242863 [published Online First: 2020/12/01].

[2]Xu C, Meng LB, Duan YC, et al. Screening and identification of biomarkers for systemic sclerosis via microarray technology. Int J Mol Med 2019;44(5):1753-70. doi: 10.3892/ijmm.2019.4332 [published Online First: 2019/09/24].

[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

OP0184 PHENOTYPING OF MOLECULAR SIGNATURES IN THE SYNOVIAL TISSUE OF RHEUMATOID ARTHRITIS BY INTEGRATIVE SYSTEMS ANALYSIS

Background:

Rheumatoid arthritis (RA) is an aggressive immune-mediated joint disease characterized by synovial proliferation and inflammation, cartilage destruction, and joint destruction1. Despite efforts to characterize the disease subsets and to predict the differential prognosis in RA patients, disease heterogeneity is not adequately translated into the current clinical subclassification2.

Objectives:

To develop and validate an integrative system approach for stratifying patients with RA according to disease status and whole-genome gene expression data.

Methods:

An RNA sequencing dataset of synovial tissues from 124 RA patients (including 57 patients with early RA, 95 with established RA) and 15 healthy controls (HC) was imported from the Gene Expression Omnibus (GEO) database (GSE89408) by software package R (version 4.0.3). After filtrating of differentially expressed genes (DEGs) between RA and HC, non-negative matrix factorization, functional enrichment, and immune cell infiltration were applied to illustrate the landscapes of these patients for classification. Clinical features (age, gender, and auto-antibodies) were also compared to discover the signatures of these classifications.

Results:

A matrix of 576 DEGs from RA samples was classified into 5 subtypes (early/C1–C3, established/C4-C5) with distinct molecular and cellular signatures and two sub-groups (S1 and S2) (Figure 1A-1D). New-onset patients (early C2) and established C4 patients were named as S1, they shared similar gene signatures mainly characterized by prominent immune cells and proinflammatory signatures, and enriched in the chemokine-mediated signaling pathway, lymphocyte activation, response to bacterium and Primary immunodeficiency. S2(C1, C3 and C5) were more occupied by synovial fibroblasts of destructive phenotype. They were mainly enriched in the response to external factors and PPAR signaling pathway (Figure 1E-1H). Interestingly, combined with clinical information, S1 and S2 had no significance in age and gender (P > 0.05). But patients in S1 had a stronger association with the presence of anti-citrullinated protein antibodies (ACPA) (P < 0.05) (Figure 1I-1J).

Conclusion:

We successfully deconvoluted RA synovial tissues into pathobiological discrete subsets using an unsupervised machine learning method and described their distinct molecular and cellular characteristics. These results provide important insights into divergent and shared mechanistic features of RA and serve as a template for future studies to guide drug tar-get discovery by synovial molecular signatures and de-sign stratified approaches for patients with RA.

References:

[1]Smolen JS, Aletaha D, McInnes IB. Rheumatoid arthritis. Lancet 2016;388(10055):2023-38. doi: 10.1016/S0140-6736(16)30173-8 [published Online First: 2016/10/30]

[2]Jung SM, Park KS, Kim KJ. Deep phenotyping of synovial molecular signatures by integrative systems analysis in rheumatoid arthritis. Rheumatology (Oxford) 2020 doi: 10.1093/rheumatology/keaa751 [published Online First: 2020/11/25]

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0199 TIME-SERIES ANALYSIS IN MODERATE TO SEVERE PLAQUE PSORIASIS UNDER DIFFERENT BIOLOGICS TREATMENTS

Background:

Moderate to Severe Plaque Psoriasis is an inflammatory skin disease that is associated with multiple comorbidities and substantially diminishes patients’ quality of life. As one of the most significant therapeutic advancements in the field of dermatology, Biologics such as TNF inhibitors, IL-12/23 inhibitor, IL-17 inhibitors, and IL-23 inhibitors, have higher efficacy compared with oral medications or phototherapy1. However, the previous studies did not focus on the simultaneous comparison of molecular changes in different classes of biologics. The identification of time-series genes (TSGs) could help to uncover the mechanisms underlying transcriptional regulation2.

Objectives:

In this study, we aimed to compare the differences in expression patterns and functions of time-series genes in Moderate to Severe Plaque Psoriasis under different biologics treatments.

Methods:

The transcription profile of GSE117239 and GSE51440 were obtained from the Gene Expression Omnibus database (GEO). The GSE117239 included 19 samples treated with Etanercept (TNF inhibitors) and 16 samples treated with Ustekinumab (IL-12/23 inhibitor). The GSE51440 included 4 samples treated with Guselkumab (IL-23 inhibitors). Skin biopsy samples (LS: lesion, NL: non-lesion) were collected at baseline, weeks 1 and 12, respectively. After background adjustment and other pre-procession, differentially expressed genes (DEGs) were extracted from LS skin biopsy and untreated NL skin biopsy at different times after three different biologics treatments, respectively. The Short Time-series Expression Miner (STEM) software was used to cluster and compare average DEGs with coherent changes. Afterward, the different expression patterns of TSGs under the three treatment groups were compared. GO analysis and KEGG pathway enrichment analysis of TSGs were performed by Metascape.

Results:

Different DEGs varied in LS skin compared with those of NL skin biopsy: 976 genes in Ustekinumab group, 996 genes in Etanercept group, and 601 genes in Guselkumab group detailly (P < 0.05 and [log FC] > 1). Gene landscapes suggested the signatures of LS gradually changed during the treatment process, and gradually converge to NL signatures (Fig.1a, 2a,3a). Time-series genes in the three treatment groups had different expression patterns and functions. In the Ustekinumab group, a total of 448 TSGs in profile 3 showed a stable-stable-decreasing expression trend and significantly associated with mitotic nuclear division and defense response to other organism, whereas in profile 4 represented a stable-stable-increasing expression trend and significantly associated with positive regulation of cellular response to organic 9 compound (Fig.1). With the treatment of Etanercept, 22 TSGs had a stable-increasing-increasing expression tendency and closely associated with fatty acid metabolism and steroid metabolic process (Fig.2). After Guselkumab treatment, 13 TSGs also represented a stable-increasing-increasing expression tendency that mainly characterized by defense response to other organism and epidermis development (Fig.3). Interestingly, both Ustekinumab and Guselkumab treatment dramatically influenced defense response to other organism-related genes, while Etanercept mainly affected genes involved in fatty acid metabolism and steroid metabolic process.

Conclusion:

Biologics effectively reconstituted the gene signatures of psoriasis in different aspects. TSG features could be one of indicator for precise intervention for psoriasis.

References:

[1]Armstrong AW, Read C. Pathophysiology, Clinical Presentation, and Treatment of Psoriasis: A Review. Jama 2020;323(19):1945-60. doi: 10.1001/jama.2020.4006 [published Online First: 2020/05/20]

[2]Ernst J, Bar-Joseph Z. STEM: a tool for the analysis of short time series gene expression data. BMC Bioinformatics 2006;7:191. doi: 10.1186/1471-2105-7-191 [published Online First: 2006/04/07]

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0363 IDENTIFICATION OF MOLECULAR PHENOTYPES AND IMMUNE CELL INFILTRATION IN PSORIATIC ARTHRITIS PATIENTS’ SKIN TISSUES BY INTEGRATED BIOINFORMATICS ANALYSIS

Background:

Psoriatic arthritis (PsA) is an inflammatory musculoskeletal disease associated with cutaneous psoriasis1. Heterogeneity of clinical manifestation often makes differential diagnosis difficult 2. Thus, the underlying molecular pathogenesis of PsA need to be further studied to diagnose early and ensure optimal management of arthritis and key comorbidities.

Objectives:

This research was conducted to identify molecular phenotypes and immune infiltration in the skin tissues of psoriatic arthritis patients according to bioinformatics analysis.

Methods:

The mRNA expression profiles of GSE13355 (116 samples), GSE14905 (56 samples) and GSE30999 (162 samples) were obtained from the publicly GEO databases. Non-negative matrix factorization (NMF), functional enrichment and cibersort algorithm were applied to illustrate the conditions of PsA patients’ skin tissues for classification after screening the differentially expressed genes (DEGs) between lesion biopsy and non-lesion biopsy.

Results:

Two subsets (Sub1 and Sub2) were identified and validated by NMF typing of 612 detected DEGs (Figure 1a). A total of 54 signature genes (18 in Sub1 and 36 in Sub2) were obtained (Figure 1b). GO and KEGG enrichment analysis showed the signature genes in Sub1 were mainly involved in proliferation and differentiation of immune cells, whereas genes in Sub2 were related to humoral immune response mediated by antimicrobial peptide (Figure 1c.1d). Further, immune cell infiltration results revealed Sub2 had higher levels of resting NK cells (P<0.001), macrophages M1(P<0.001), resting mast cells (P<0.001) and regulatory T cells (P<0.001) but lower concentrations of activated CD4+ memory T cells (P<0.001), activated NK cells (P<0.05), activated dendritric cells(P<0.001), eosinophils (P<0.05) and neutrophil (P<0.001) (Figure 1e).

Conclusion:

The pathogenesis of psoriatic arthritis is related to both cellular immunity and humoral immunity. It is indispensable to adjust the treatment strategies according to patient’s immune status.

References:

[1]Ritchlin CT, Colbert RA, Gladman DD. Psoriatic Arthritis. The New England journal of medicine 2017;376(10):957-70. doi: 10.1056/NEJMra1505557 [published Online First: 2017/03/09].

[2]Veale DJ, Fearon U. The pathogenesis of psoriatic arthritis. Lancet (London, England) 2018;391(10136):2273-84. doi: 10.1016/s0140-6736(18)30830-4 [published Online First: 2018/06/13].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared

POS0743 GENE EXPRESSION MICROARRAY IN LUPUS NEPHRITIS BY BIOINFORMATIC ANALYSIS

Background:

Nephritis is one of the predominant causes of morbidity and mortality in patients with lupus1 2.The lack of understanding regarding the molecular mechanisms of lupus nephritis(LN) hinders the development of specific targeted therapy for this progressive disease3.

Objectives:

In this study, we use bioinformatics method to analyze the genes involved in regulating the potential pathogenesis of LN.

Methods:

The expression profile of LN(GSE104948 and GSE32591) was obtained from the GEO database.GSE104948 was a memory chip, which included 32 LN glomerular biopsy tissues and 3 glomerular tissues from living donors.GSE32591 dataset included 32 LN glomerular biopsy tissues and 15 glomerular tissues from living donors. The Oligo package was used to process the data to obtain the expression matrix files of all the related genes.P<0.05 and |log2(FC)|>2 were setted as cut-off criteria for the DEGs.Ggplot2, heatmap packages were used to DEGs visualization. Metascape online tool was used to annotating DEGs for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis performed.We used STRING online database to construct protein-protein interaction (PPI) network. Hub genes were identified by Cytoscape.

Results:

In differential expression analysis,357 DEGs were identified,including 248 up-regulated genes and 109 down-regulated genes (Figure 1A,B).GO enrichment showed that these DEGs were primarily enriched in biological pathways, cell localization and molecular function and revealed that LN-related genes mainly involved in immune response.KEGG pathway annotation enrichment analysis revealed these DEGs were closely associated with Staphylococcus aureus infection,Complement and coagulation cascades (Figure 1D). Fourteen hub genes(IFT3,IRF7,OAS3,GBP2,RSAD2,MX1,IFIT2,IFI6,MX2,ISF15,IFIT1,QAS2,OASL,OAS1) were identified from PPI network (Figure 1C,E).

Conclusion:

Illuminating the molecular mechanisms of LN was help for deep understanding of LN.

References:

[1]Song J, Zhao L, Li Y. Comprehensive bioinformatics analysis of mRNA expression profiles and identification of a miRNA-mRNA network associated with lupus nephritis. Lupus 2020;29(8):854-61. doi: 10.1177/0961203320925155 [published Online First: 2020/05/22].

[2]Yao F, Sun L, Fang W, et al. HsamiR3715p inhibits human mesangial cell proliferation and promotes apoptosis in lupus nephritis by directly targeting hypoxiainducible factor 1alpha. Mol Med Rep 2016;14(6):5693-98. doi: 10.3892/mmr.2016.5939 [published Online First: 2016/11/24].

[3]Dall’Era M. Treatment of lupus nephritis: current paradigms and emerging strategies. Curr Opin Rheumatol 2017;29(3):241-47. doi: 10.1097/BOR.0000000000000381 [published Online First: 2017/02/17].

Acknowledgements:

This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).

Disclosure of Interests:

None declared