Analysis of Ficus hirta Fig Endosymbionts Diversity and Species Composition

Endosymbionts living in plants and insects are pervasive. Ficus (Moraceae) has very special inflorescences (which we also call figs) enclosed like an urn, and such inflorescence is usually parasitized by fig wasps. Ficus breeds fig wasp larvae in its figs and adult fig wasps pollinate for Ficus, Ficus and its obligated pollinator formed fig-fig wasp mutualism. Previous studies have found that this confined environment in figs may have provided protection for fig wasps and that this has left some imprints on the genome of fig wasps during the coevolution history of figs and fig wasps. Research on the diversity of both bacteria and fungi in figs are fewer. Our study explored the diversity of endosymbionts in Ficus hirta figs. We utilized high-throughput sequencing and biological database to identify the specific microorganism in figs, then conducted microorganism communities’ diversity analysis and function annotation analysis. As a result, we identified the dominant endosymbionts in figs, mainly some insect internal parasitic bacteria and fungi, plant pathogen, endophytes, and saprotroph. Then we also found bacteria in Ficus hirta figs were more diversified than fungi, and bacteria communities in female figs and functional male figs were different. These findings may give us more insight into the coevolution and interaction among endosymbiont, fig, and fig wasp.

Automatic consistency assurance for literature-based gene ontology annotation

Background Literature-based gene ontology (GO) annotation is a process where expert curators use uniform expressions to describe gene functions reported in research papers, creating computable representations of information about biological systems. Manual assurance of consistency between GO annotations and the associated evidence texts identified by expert curators is reliable but time-consuming, and is infeasible in the context of rapidly growing biological literature. A key challenge is maintaining consistency of existing GO annotations as new studies are published and the GO vocabulary is updated. Results In this work, we introduce a formalisation of biological database annotation inconsistencies, identifying four distinct types of inconsistency. We propose a novel and efficient method using state-of-the-art text mining models to automatically distinguish between consistent GO annotation and the different types of inconsistent GO annotation. We evaluate this method using a synthetic dataset generated by directed manipulation of instances in an existing corpus, BC4GO. We provide detailed error analysis for demonstrating that the method achieves high precision on more confident predictions. Conclusions Two models built using our method for distinct annotation consistency identification tasks achieved high precision and were robust to updates in the GO vocabulary. Our approach demonstrates clear value for human-in-the-loop curation scenarios.

Conventional Synthetic Dmards in Psoriatic Arthritis: Changing Practice in Biologic Era; Real-Life Results from HURBIO-PsA Registry

Objectives: Psoriatic arthritis is a chronic musculoskeletal disorder which may affect skin, joints, bone and enthesis. Conventional synthetic disease modifying anti-rheumatic drugs are first-line treatment options and biologic disease modifying anti-rheumatic drugs are recommended in psoriatic arthritis patients who are intolerant/not controlled well with conventional synthetic disease modifying anti-rheumatic drugs. Although survival data of the conventional synthetic disease modifying anti-rheumatic drugs without concomitant biologic disease modifying anti-rheumatic drugs are available, the effect of biologic disease modifying anti-rheumatic drugs on the retention of conventional synthetic disease modifying anti-rheumatic drugs is still a question of interest. Materials and Methods: Psoriatic arthritis patients who received at least 1 dose of biologic disease modifying anti-rheumatic drugs, using at least 1 conventional synthetic disease modifying anti-rheumatic drugs (methotrexate, leflunomide, hydroxychloroquine and sulfasalazine) at the time of biologic disease modifying anti-rheumatic drugs starting visit and registered in the Hacettepe University BIOlogical Database-Psoriatic Arthritis were included in this retrospective longitudinal analysis. Demographic and disease-specific data at first and last follow-up visit were collected. Unadjusted retention rate of each conventional synthetic disease modifying anti-rheumatic drugs was assessed. Overall prescription of conventional synthetic disease modifying anti-rheumatic drugs at first and last follow-up visit were compared. Results: A total of 266 (191(71.8%) female) patients was included. Median follow-up duration under biologic treatment was 43.4 (19.4-80.1) months. Median retention duration of each conventional synthetic disease modifying anti-rheumatic drugs were similar. Between the first and last visit; there was a 29.3% decrease in methotrexate use (61.7% vs. 43.6%; p<0.001), 8.4% decrease in leflunomide use (31.2% vs. 28.6%; p=0.30), 30.0% decrease in sulfasalazine use (11.3% vs. 7.9%; p=0.05), 31.1% decrease in hydroxychloroquine use (16.9% vs. 11.7%; p=0.001), 12.5 % decrease in glucocorticoids use (51.1% vs. 44.7%; p=0.015). At last visit, 59 (22.2%) patients were conventional synthetic disease modifying anti-rheumatic drugs -free: 20 (7.5%) patients were using only glucocorticoids, 39 (14.7%) patients were conventional synthetic disease modifying anti-rheumatic drugs + glucocorticoid-free. Conclusion: Although conventional synthetic disease modifying anti-rheumatic drugs were significantly discontinued in an important percent of patients after the initiation of biologic disease modifying anti-rheumatic drugs, percentage of patients using glucocorticoids at last visit was still high. Studies aiming to demonstrate when, in whom and how to discontinue conventional synthetic disease modifying anti-rheumatic drugs are needed.

Computational Method Using Heterogeneous Graph Convolutional Network Model Combined With Reinforcement Layer For MiRNA-Disease Association Prediction

Background: A large number of evidences from biological experiments have confirmed that miRNAs play an important role in the progression and development of various human complex diseases. However, the traditional experiment methods are expensive and time-consuming. Therefore, it is a challenging task that how to develop more accurate and efficient methods for predicting potential associations between miRNA and disease. Results: In the study, we developed a computational model that combined Heterogeneous Graph Convolutional Network with Enhanced Layer for miRNA-Disease Association prediction (HGCNELMDA). The major improvement of our method lies in through restarting the random walk optimized the original features of nodes and adding a Reinforcement layer to the hidden layer of graph convolutional network retained similar information between nodes in the feature space. In addition, the proposed approach recalculated the influence of neighborhood nodes on target nodes by introducing the attention mechanism. The reliable performance of the HGCNELMDA was certified by the AUC of 93.47% in global leave-one-out cross-validation (LOOCV), and the average AUCs of 93.01% in fivefold cross-validation. Meanwhile, we compared the HGCNELMDA with the state‑of‑the‑art methods. Comparative results indicated that o the HGCNELMDA is very promising and may provide a cost‑effective alternative for miRNA-Disease Association prediction. Moreover, we applied HGCNELMDA to 3 different case studies to predict potential miRNAs related to lung cancer, prostate cancer, and pancreatic cancer. Results showed that 48, 50, and 50 of the top 50 predicted miRNAs were supported by experimental association evidence. Therefore, the HGCNELMDA is a reliable method for predicting disease-related miRNAs. Conclusions: The results of the HGCNELMDA method in the LOOCV (leave-one-out cross validation, LOOCV) and 5-cross validations were 93.47% and 93.01%, respectively. Compared with other typical methods, the performance of HGGCNMA is higher. Three cases of lung cancer, prostate cancer, and pancreatic cancer were studied. Among the predicted top 50 candidate miRNAs, 48, 50, and 50 were verified in the biological database HDMMV2.0.Therefore; this further confirms the feasibility and effectiveness of our method. To facilitate extensive studies for future disease-related miRNAs research, we developed a freely available web server called HGCNELMDA is available at http://132.232.17.50:8080/HGCNELMDA.jsp.

Cloning Method for Stress-Resistant Gene of Conringia planisiliqua under Drought Stress

The low temperature, drought, high salt, and other environments influence crop production and development directly, so the gene cloning method has become an effective biological means. In order to effectively improve the cloning effect, a gene cloning method for Conringia planisiliqua based on mRNA differential display technology was proposed. Based on mRNA differential display technology, the gene of Conringia planisiliqua was transcribed. The present study expects gene cloning to be better than the traditional method. This will lay the basis for gene cloning and functional verification of the transcription and disease-resistant proteins in Conringia planisiliqua. According to homologous identification results, the homologous drought-resistant genes were determined and screened. The data of Conringia planisiliqua in the existing biological database were used to extract ESTs data of Conringia planisiliqua. Then, the heating environment was established and the concept of integral function was introduced to express the influence of growth environment of different genomes. The mass, momentum, energy, and turbulent flow situation of stress-resistant gene of Conringia planisiliqua during the growth were satisfied. Finally, the data search was carried out in the NCBI database and gene cloning was achieved by ESTs data sequence. Experimental results show that the proposed method can effectively reduce the gene data fitting and improve the quantity of gene fragments cloned in a cycle, so the overall cloning effect is better.

Automatic Consistency Assurance for Literature-based Gene Ontology Annotation

Background: Literature-based gene ontology (GO) annotation is a process where expert curators use uniform expressions to describe gene functions reported in research papers, creating computable representations of information about biological systems. Manual assurance of consistency between GO annotations and the associated evidence texts identified by expert curators is reliable but time-consuming, and is infeasible in the context of rapidly growing biological literature. A key challenge is maintaining consistency of existing GO annotations as new studies are published and the GO vocabulary is updated. Method: In this work, we introduce a formalisation of biological database annotation inconsistencies, identifying four distinct types of inconsistency. We propose a novel and efficient method using state-of-the-art text mining models to automatically distinguish between consistent GO annotation and the different types of inconsistent GO annotation. We evaluate this method using a synthetic dataset generated by directed manipulation of instances in an existing corpus, BC4GO. Results and Conclusion: Two models built using our method for distinct annotation consistency identification tasks achieved high precision and were robust to updates in the GO vocabulary. We provide detailed error analysis for demonstrating that the method achieves high precision on more confident predictions. Our approach demonstrates clear value for human-in-the-loop curation scenarios

OP0098 POLYPHARMACY IS ASSOCIATED WITH A POORER TREATMENT RESPONSE AND INCREASED RISK OF ADVERSE EVENTS IN EARLY RHEUMATOID ARTHRITIS

Background:Polypharmacy is steadily increasing in patients with rheumatoid arthritis (RA). They may interfere with treatment response and the occurrence of serious adverse events. Medications taken by a patient may reflect active comorbidities, whereas comorbidity indices usually used include past or current diseases.Objectives:To evaluate whether polypharmarcy is associated with treatment response and adverse events in an early RA cohort and to establish whether polypharmacy could represent a substitute of comorbidities.Methods:We used data from the French cohort ESPOIR, including 813 patients with early onset arthritis. Patients included the current study had to start their first disease modifying anti-rheumatic drug (DMARD) within 24 months of inclusion in the cohort. Disease activity data were collected at one, five and ten years from the initiation of the first DMARD. For each patient, treatments were collected at baseline and at five years. Medications count included all specialties other than background RA therapy, analgesics/NSAIDs and topicals. Polypharmacy was defined as a categorical variable based on the median and tertiles of distribution in the cohort. Treatment response was assessed by achieving DAS28 ESR remission (REM) at 1 year, 5 years and 10 years from the initiation of the first DMARD. The occurrence of severe adverse events (SAE) was measured by the occurrence of severe infection, hospitalization, or death during the 10-year follow-up. The association between patient’s characteristics and achievement of REM and occurrence of SAE were tested in univariate analysis. A logistic regression model was used to evaluate associations between polypharmacy and REM at 1 year, 5 years and 10 years (we used baseline polypharmacy for the 1-year analysis and five years polypharmacy for the 5- and 10-years analyses). Multivariate adjustment was made for age, sex, BMI, duration of disease, initial DAS28 ESR, initial HAQ, smoking status, rheumatic disease comorbidity index (RDCI).Results:The proportion of patients who achieved REM one year after the initiation of the first DMARD was 32.1% in the polypharmacy according to the median group (patients taken ≥2 medication) versus 67.9% in the non-polypharmacy group (p=0.07). At 5 years after the first DMARD, the proportion of patients with REM was 45.0% in the polypharmacy group versus 56.3% in the non-polypharmacy group (p=0.03). At 10 years the proportion of patients with REM was 32.5% in the polypharmacy group versus 67.5% (p=0.06). Patients who take greater or equal to 2 medications had a 40% lower probability of achieving REM (OR = 0.60 [0.38-0.94] p = 0.03) at 5 years from the first DMARD (if RDCI index was not included in the model). At 10 years, patients receiving multiple medications had a 43% lower probability of achieving REM (OR = 0.57 [0.34-0.94] p = 0.02). SAE incidence was 61 per 1000 patient-years. For patients who developed SAE all causes 71.4% where in the polypharmacy group versus 57.8% were in the non-polypharmacy group (p = 0.03; univariate analysis). These results are no longer significant after adjustment for comorbidities indices.Conclusion:In this early RA cohort, polypharmacy is associated with a poorer treatment response and increased risk of adverse events. Polypharmacy may represent a good substitute of comorbidities for epidemiological studies.Acknowledgements:We are grateful to Nathalie Rincheval (Montpellier) who did expert monitoring and data management and all theinvestigators who recruited and followed the patients (F. Berenbaum, Paris-Saint Antoine; MC. Boissier, Paris-Bobigny; A. Cantagrel, Toulouse; B. Combe, Montpellier; M. Dougados, Paris-Cochin; P. Fardellone and P. Boumier, Amiens; B. Fautrel, Paris-La Pitié; RM. Flipo, Lille; Ph. Goupille, Tours; F. Liote, Paris- Lariboisière; O. Vittecoq, Rouen; X. Mariette, Paris-Bicêtre; P. Dieude, Paris Bichat; A. Saraux, Brest; T. Schaeverbeke, Bordeaux; and J. Sibilia, Strasbourg).The work reported on in the manuscript did not benefit from any financial support. The ESPOIR cohort is sponsored by the French Society for Rheumatology. An unrestricted grant from Merck Sharp and Dohme (MSD) was allocated for the first 5 years. Two additional grants from INSERM were obtained to support part of the biological database. Pfizer, Abbvie, Lilly and more recently Fresenius and Biogen also supported the ESPOIR cohort.Disclosure of Interests:Soraya Benamar: None declared, Cédric Lukas Speakers bureau: Abbvie, Amgen, Janssen, Lilly, MSD, Novartis, Pfizer, Roche-Chugai, UCB, Consultant of: Abbvie, Amgen, Janssen, Lilly, MSD, Novartis, Pfizer, Roche-Chugai, UCB, Grant/research support from: Pfizer, Novartis and Roche-Chugai, Claire Daien Speakers bureau: AbbVie, Abivax, BMS, MSD, Roche, Chugai, Novartis, Pfizer, Sandoz, Lilly, Consultant of: AbbVie, Abivax, BMS, MSD, Roche, Chugai, Novartis, Pfizer, Sandoz, Lilly, Cécile Gaujoux-Viala Speakers bureau: Abbvie, BMS, Celgene, Janssen, Medac, MSD, Nordic Pharma, Novartis, Pfizer, Sanofi, Roche-Chugai, UCB, Consultant of: Abbvie, BMS, Celgene, Janssen, Medac, MSD, Nordic Pharma, Novartis, Pfizer, Sanofi, Roche-Chugai, UCB, Grant/research support from: Pfizer, Laure Gossec Speakers bureau: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis et UCB, Consultant of: AbbVie, Amgen, Biogen, Celgene, Janssen, Lilly, Novartis, Pfizer, Sandoz, Sanofi-Aventis et UCB, Anne-Christine Rat Speakers bureau: Pfizer, Lilly, Consultant of: Pfizer, Lilly, Bernard Combe Speakers bureau: AbbVie; Bristol-Myers Squibb; Gilead; Janssen; Lilly; Merck; Novartis; Pfizer; Roche-Chugai; and Sanofi;, Consultant of: AbbVie; Bristol-Myers Squibb; Gilead; Janssen; Lilly; Merck; Novartis; Pfizer; Roche-Chugai; and Sanofi;, Grant/research support from: Novartis, Pfizer, and Roche-Chugai., Jacques Morel Speakers bureau: Abbvie, BMS, Lilly, Médac, MSD, Nordic Pharma, Pfizer, UCB, Consultant of: Abbvie, BMS, Lilly, Médac, MSD, Nordic Pharma, Pfizer, UCB, Grant/research support from: BMS, Pfizer

POS1070 ANXIETY IN PSORIATIC ARTHRITIS PATIENTS: RESULTS FROM THE HUR-BIO BIOLOGIC REGISTRY

Background:Anxiety is commonly observed, underestimated problem in patients with psoriatic arthritis (PsA). Overall rate has been reported around 20% [1]. However the data on anxiety in PsA patients requiring advanced treatment and change in response to therapy is scarce.Objectives:Our aim was to understand the frequency of anxiety before starting biologic agents and change in the anxiety scores with the treatment.Methods:PsA patients from the Hacettepe University biological database (HUR-BIO) were assessed for anxiety (score ≥ 4) using the patient self-reported measure of anxiety on a 0-10 numerical scale, included in the Psoriatic Arthritis Impact of Disease questionnaire (PSAID-12) [2]. The anxiety rate and scores were determined before starting biologic agents and at first visit in 6 months. Change in the scores were compared between patients according to the favourable treatment responses (Table 1). The correlation between the score-changes in anxiety and treatment response parameters was assessed by spearman correlation analysis.Results:From 520 patients registered, 147 [mean (SD) age 43.3 (12.4) years, 70.7% female] had anxiety score registered both at baseline and first visit in 6 months. Both the frequency and mean (SD) score of anxiety decreased at first visit [63.9% vs 41.4 %, 4.8(3.4) vs 3.2 (3.1) respectively, p<0.001 for both] after a mean (SD) follow-up of 105.7 (22.2) days. There was a statistically significant difference between changes in the anxiety scores in patients with/without treatment responses in pain, PGA, BASDAI, HAQ-DI and DAS-28. A positive correlation between the change in anxiety and all treatment response parameters was observed (Table 1, Figure 1).Table 1.Patient characteristics at baseline and changes in the anxiety score according to treatment responseConclusion:Anxiety is a more frequent problem at the time of biologic initiation compared to rates observed in general PsA population which could be related to the high disease activity. The rates are still high in 6 months under treatment, however both the frequency and score of anxiety showed a decreasing trend parallel to the treatment response.References:[1]Zusman EZ, Howren AM, Park JYE,et. al (2020) Epidemiology of depression and anxiety in patients with psoriatic arthritis: A systematic review and meta-analysis. Semin Arthritis Rheum 50 (6):1481-1488.[2]Gossec L, de Wit M, Kiltz U, Braun J, et al (2014) A patient-derived and patient-reported outcome measure for assessing psoriatic arthritis: elaboration and preliminary validation of the Psoriatic Arthritis Impact of Disease (PsAID) questionnaire, a 13-country EULAR initiative. Ann Rheum Dis 73 (6):1012-1019.Figure 1.Correlation between the score changesDisclosure of Interests:None declared.

Effects of microRNA-103 on the Proliferation and Apoptosis of Pancreatic Cancer Cells via Targeting Phosphatase and Tensin Homolog Deleted on Chromosome Ten (PTEN) and Activating Phosphoinositide 3-Kinase/A Serine/Threonine Kinase (PI3K/Akt) Signaling Pathway

Objective: To investigate whether micro ribonucleic acid (miR)-103 affects pancreatic cancer (PaCa) cells via PTEN-activated PI3K/Akt signaling pathway. Methods: Differences in miR-103 expression in 35 pairs of PaCa tissues and cell lines (SW1990 and PATU8988S) were detected by RT-qPCR. miR-103 inhibitor was transfected into PaCa PATU8988S cell followed by analysis of proliferation and apoptosis of PaCa cells by MTT assay and flow cytometry, respectively. Results: MiR-103 exhibited a significantly high expression in PaCa tissues and cell lines (p < 0.05). Besides, the exogenous inhibition of miR-103 expression in PATU8988S cells significantly inhibited cell proliferation and migration but increased apoptosis activity (p < 0.05). According to the prediction of TargetScan biological database, miR-103 could bind PTEN 3′ untranslated region (3′UTR) and miR-103 was confirmed to suppress PTEN expression in a targeted way (p<0.05). Furthermore, down-regulation of PTEN activated PI3K/Akt signaling to affect the proliferation and apoptosis of PaCa cells (p < 0.05 or p <0.01). Conclusion: MiR-103 displays a significantly increased expression in PaCa cells and targets PTEN to activate PI3K/Akt signaling pathway, thus promoting malignant phenotype formation.

The EPICURE study: a pilot prospective cohort study of heterogeneous and massive data integration in metastatic breast cancer patients

Background Breast cancer is the most common cancer in women and the first cancer concerning mortality. Metastatic breast cancer remains a disease with a poor prognosis and about 30% of women diagnosed with an early stage will have a secondary progression. Metastatic breast cancer is an incurable disease despite significant therapeutic advances in both supportive cares and targeted specific therapies. In the management of a metastatic patient, each clinician follows a highly complex and strictly personal decision making process. It is based on a number of objective and subjective parameters which guides therapeutic choice in the most individualized or adapted manner. Methods/design The main objective is to integrate massive and heterogeneous data concerning the patient’s environment, personal and familial history, clinical and biological data, imaging, histological results (with multi-omics data), and microbiota analysis. These characteristics are multiple and in dynamic interaction overtime. With the help of mathematical units with biological competences and scientific collaborations, our project is to improve the comprehension of treatment response, based on health clinical and molecular heterogeneous big data investigation. Discussion Our project is to prove feasibility of creation of a clinico-biological database prospectively by collecting epidemiological, socio-economic, clinical, biological, pathological, multi-omic data and to identify characteristics related to the overall survival status before treatment and within 15 years after treatment start from a cohort of 300 patients with a metastatic breast cancer treated in the institution. Trial registration ClinicalTrials.gov identifier (NCT number): NCT03958136. Registration 21st of May, 2019; retrospectively registered.