POS0506 DIFFERENT BIOACTIVE LIPID PROFILES PREDICT RESPONSE TO TNF OR IL6 INHIBITORS IN RHEUMATOID ARTHRITIS: RESULT OF THE CorEvitas CERTAIN COMPARATIVE EFFECTIVENESS STUDY

Background

Circulating bioactive lipids can provide information about the pathogenesis of specific diseases and potentially help predict therapeutic response. Choosing the right biological therapy earlier in the course of rheumatoid arthritis (RA) could help reach the goal of remission.

Objectives

We hypothesized that circulating bioactive lipids at baseline would identify specific metabolic profiles that predict patient response to therapy and define elements of metabolic pathobiology in arthritis.

Methods

Bioactive lipids were measured in plasma from two cohorts of RA patients from the CorEvitas (formerly known as Corrona) CERTAIN registry (1) at baseline prior to treatment with TNF inhibitors (all biologic naïve, N=102) or anti-IL6 (all previously exposed to biologics, N=114). Response to treatment was categorized by minimal clinically important difference (MCID) in Clinical Disease Activity Index (CDAI) (2) at 6 months after treatment initiation. Patients had to have a 6 month follow up visit and plasma available at both the baseline and the f/u time points. Liquid chromatography (LC) system coupled with high resolution QExactive orbitrap mass spectrometer (LC/MS) was used for bioactive lipids profiling. Around 300 spectral features were identified as potential oxylipins by searching against an in-house MS/MS library. Logistic regression analyses adjusted for gender, age and BMI was perfomed using R software.

Results

102 patients (average age 54, standard deviation [SD] 12.6, 82% female [83], average BMI 29.7, SD 6.7, average CDAI 27.1, SD 13.7) starting anti-TNF therapy and 114 patients (average age 57, SD 13, 90% female [102], average BMI 30.5, SD 7.4, average CDAI 28.7, SD 13.8) starting tocilizumab were analyzed. Twenty-five bioactive metabolites discriminated between RA patients classified as anti-TNF responders (R, n = 74) and non-responders (NR, n = 28). Among these, the anti-inflammatory oxylipin maresin 2 was higher in R while the pro-inflammatory oxylipins 15d PGJ2 and 5,6-diHETE were higher in NR. Twenty different metabolites discriminated anti-IL6 R (n=73) and NR (n=41) as shown in Figure 1. The anti-inflammatory oxylipin 14-15EET was higher in R while the pro-inflammatory oxylipins 16-HETE and 5S-HpETE were higher in NR.

Figure 1.

Volcano plots visualizing baseline metabolites associated with responders vs. non responders in a) anti-TNF and b) anti IL-6 therapy groups. Results are derived from multivariate logistic regression analysis of baseline metabolites and response to treatment categorized by MCID. Data plotted as the metabolite against its statistical significance, respectively reported as odds ratio (OR) and -log10(pvalue).

Conclusion

Circulating bioactive lipid analysis using LC/MS provided a rapid analysis of a wide range of metabolites and can be used to describe metabolic signatures that predict response to therapies. These results lay the groundwork for more deliberate investigations novel metabolic-based interventions to predict response to therapy and reduce arthritis morbidity.

References

[1]Pappas DA, Kremer JM, Reed G, Greenberg JD, Curtis JR. Design characteristics of the CORRONA CERTAIN study: a comparative effectiveness study of biologic agents for rheumatoid arthritis patients. BMC Musculoskeletal Disord 2014; 15: 113

[2]Curtis JR, Yang S, Chen L, Pope JE, Keystone EC, Haraoui B, Boire G, Thorne JC, Tin D, Hitchon CA, Bingham CO 3rd, Bykerk VP. Determining the Minimally Important Difference in the Clinical Disease Activity Index for Improvement and Worsening in Early Rheumatoid Arthritis Patients. Arthritis Care Res (Hoboken). 2015 Oct;67(10):1345-53. doi: 10.1002/acr.22606. PMID: 25988705; PMCID: PMC4580563.

Disclosure of Interests

Mona Alotaibi: None declared, Roxana Coras: None declared, Dimitrios A Pappas Speakers bureau: Sanofi, Novartis, Paid instructor for: Novartis, Consultant of: Roche, Sanofi, Joel M Kremer Speakers bureau: Pfizer, Consultant of: BMS, Geoffrey Thiele: None declared, Ted Mikuls Consultant of: Pfizer, Gilead, BMS, Sanofi, Mohit Jain Employee of: Sapient Bio, Monica Guma Grant/research support from: Pfizer, Novartis.

[Update on collaborative autopsy-based research in German pathology, neuropathology, and forensic medicine]

BACKGROUND

Autopsies are a valuable tool for understanding disease, including COVID-19.

MATERIALS AND METHODS

The German Registry of COVID-19 Autopsies (DeRegCOVID), established in April 2020, serves as the electronic backbone of the National Autopsy Network (NATON), launched in early 2022 following DEFEAT PANDEMIcs.

RESULTS

The NATON consortium's interconnected, collaborative autopsy research is enabled by an unprecedented collaboration of 138 individuals at more than 35 German university and non-university autopsy centers through which pathology, neuropathology, and forensic medicine autopsy data including data on biomaterials are collected in DeRegCOVID and tissue-based research and methods development are conducted. More than 145 publications have now emerged from participating autopsy centers, highlighting various basic science and clinical aspects of COVID-19, such as thromboembolic events, organ tropism, SARS-CoV‑2 detection methods, and infectivity of SARS-CoV-2 at autopsy.

CONCLUSIONS

Participating centers have demonstrated the high value of autopsy and autopsy-derived data and biomaterials to modern medicine. The planned long-term continuation and further development of the registry and network, as well as the open and participatory design, will allow the involvement of all interested partners.

THU0065 OXYLIPIN PROFILING DURING THE VERY EARLY PHASE OF RHEUMATOID ARTHRITIS: ASSOCIATIONS WITH DISEASE STAGE, CLINICAL FEATURES AND TREATMENT RESPONSE

Background:

traditional approaches and lipidomics support the relevance of eicosanoids in rheumatic conditions, such as rheumatoid arthritis (RA). Previous studies from our group and others have revealed altered levels of arachidonic acid in RA, pointing to a possible consumption or enhanced metabolisation. However, the potential alterations of its actual metabolites are difficult to assess with conventional approaches, and new, untargeted, high-throughput technologies are needed. More importantly, whether these alterations are related to the disease course and could be found at the very early stage of the disease is unknown.

Objectives:

to characterize the eicosanoid profiles during the earliest stages of RA and their potential clinical associations.

Methods:

60 very early RA patients (50 recruited at diagnosis and treatment-naïve) fulfilling 2010 ACR/EULAR criteria, 11 clinical suspect arthralgia (CSA) individuals and 28 healthy controls (HC) were recruited. Samples were collected at the moment of the diagnosis. Serum oxylipins profiles were analyzed by mass spectrometry (LC-MS/MS). Treatment-naïve patients underwent csDMARD treatment and were followed for 6 (n=49) and 12 months (n=38). Data analysis was performed in R and MetaboAnalyst.

Results:

A total of 75 oxylipins, mostly derived from arachidonic (AA), eicosapentanoic (EPA) and linoleic (LA) acid, were identified. No effect was observed for age, gender or BMI. Correlation and network analyses revealed different patterns among oxylipins across RA patients, CSA and HC (Figure 1A). The 8-HETrE, PGE3 and 20-HETE showed the pattern (linear increase) HC→CSA→RA (p=1.47·10-4, 5.34·10-4 and 5.68·10-4, respectively; and adjusted FDR<0.050) (Figure 1B). A PLS-DA (explaining 12.3% of the total variance, with a 71.0% cross-validation accuracy and permutation p=5·10-4) confirmed that oxylipins profiles differ among groups, although a certain overlap existed. A total of 22 oxylipins had VIP scores>1 (Figure 1C), which allowed the identification of two clusters (I and II). Cluster usage (I/II) differed among groups (p=0.003): HC (27/1), CSA (7/4) and RA (37/23). Patients exhibiting cluster II showed higher VAS global assessment (p=0.016) and pain (p=0.003) than their cluster I-counterparts. More importantly, cluster II patients were less likely to achieve DAS28 remission at 6 (12/17 vs 10/32, p=0.008) and 12 months (6/9 vs 9/29, p=0.066) upon conventional DMARD treatment compared to those showing cluster I.

OPLS-DA analyses revealed a good discrimination between CSA and HC groups, and 7 compounds (13-HODE, PGB2, 9-oxo-ODE, 12-oxo-ETE, 19,20-di-HDPA, 5-HETrE and 15-HEPE) were associated with the course HC->CSA. Different precursors (2 LA, 3 AAA, 1 EPA and 1 DHA) and pathways were noted (3 LOX, 4 CYP450). Regarding RA subsets, differences were noted by seropositivity. Whereas 9 compounds were associated with the pattern HC→seronegative RA (8-HETrE, PGE3, 20-HETE, 19,20-di-HDPA, PGEM, PGJ2, 12-oxo-LTB4, 14,15-EET and LTB4), a distinct set was observed for the pattern HC→seropositive RA (PGE3, 20-oh-PGE2, 5-HETE, PGE2, 12-oxo-ETE, 20-HETE, PGEM, 4-HDoHE, LTB4, 9-oxo-ODE, 12-oxo-LTB4, 8,9-EET). No differences in the major pathways were noted.

Conclusion:

Oxylipin networks differ across disease stages during the very early phase of RA, and can inform on specific signatures related to the disease progression. Oxylipins can delineate profiles with clinical relevance and are able to predict treatment response.

Figure:

Disclosure of Interests:

None declared

Review: Challenges in the histopathological classification of ganglioglioma and DNT: microscopic agreement studies and a preliminary genotype-phenotype analysis

Low-grade epilepsy-associated brain tumours (LEAT) are the second most common cause for drug-resistant, focal epilepsy, that is ganglioglioma (GG) and dysembryoplastic neuroepithelial tumours (DNT). However, molecular pathogenesis, risk factors for malignant progression and their frequent association with drug-resistant focal seizures remain poorly understood. This contrasts recent progress in understanding the molecular-genetic basis and targeted treatment options in diffuse gliomas. The Neuropathology Task Force of the International League Against Epilepsy examined available literature to identify common obstacles in diagnosis and research of LEAT. Analysis of 10 published tumour series from epilepsy surgery pointed to poor inter-rater agreement for the histopathology diagnosis. The Task Force tested this hypothesis using a web-based microscopy agreement study. In a series of 30 LEAT, 25 raters from 18 countries agreed in only 40% of cases. Highest discordance in microscopic diagnosis occurred between GG and DNT variants, when oligodendroglial-like cell patterns prevail, or ganglion cells were difficult to discriminate from pre-existing neurons. Suggesting new terminology or major histopathological criteria did not satisfactorily increase the yield of histopathology agreement in four consecutive trials. To this end, the Task Force applied the WHO 2016 strategy of integrating phenotype analysis with molecular-genetic data obtained from panel sequencing and 450k methylation arrays. This strategy was helpful to distinguish DNT from GG variants in all cases. The Task Force recommends, therefore, to further develop diagnostic panels for the integration of phenotype-genotype analysis in order to reliably classify the spectrum of LEAT, carefully characterize clinically meaningful entities and make better use of published literature.

The relevance of neuropsychiatric symptoms and cognitive problems in new-onset epilepsy - Current knowledge and understanding

Neurobehavioral and cognition problems are highly prevalent in epilepsy, but most research studies to date have not adequately addressed the precise nature of the relationship between these comorbidities and seizures. To address this complex issue and to facilitate collaborative, innovative research in the rising field of neurobehavioral comorbidities and cognition disturbances in new-onset epilepsy, international epilepsy experts met at the 3rd Halifax International Epilepsy Conference & Retreat at White Point, South Shore, Nova Scotia, Canada from September 18 to 20, 2014. This Conference Proceedings provides a summary of the conference proceedings. Specifically, the following topics are discussed: (i) role of comorbidities in epilepsy diagnosis and management, (ii) role of antiepileptic medications in understanding the relationship between epilepsy and neurobehavioral and cognition problems, and (iii) animal data and diagnostic approaches. Evidence to date, though limited, strongly suggests a bidirectional relationship between epilepsy and cognitive and psychiatric comorbidities. In fact, it is likely that seizures and neurobehavioral problems represent different symptoms of a common etiology or network-wide disturbance. As a reflection of this shared network, psychiatric comorbidities and/or cognition problems may actually precede the seizure occurrence and likely get often missed if not screened.