Plausbility is a theoretical framework that allows to conduct exact inference in general parametric families. We introduce R-packages plausibility that implements this framework for a wide class of regression models. Plausibility can also be used to test penalized regression models such as estimated by package glmnet. We illustrate the package using a number of R data sets Through a class-based mechanism, the package can be easily extended. We illustrate and discuss computation aspects of the implementation and their impact on real-data analysis.

BACKGROUND:Risk of irinotecan-related severe toxicity is significantly higher in patients carrying 2 dysfunctional UGT1A1 gene variants, characterized as poor metabolizers (PMs), following standard irinotecan dosing. Since 2020, we implemented UGT1A1 genotype-guided dosing of irinotecan in routine clinical practice to reduce toxicity in PMs. This study evaluates its impact on severe toxicity in a real-world cohort. PATIENTS AND METHODS:Our study cohort included adult patients who received UGT1A1 genotype-guided irinotecan dosing at 6 Dutch hospitals between December 2020 and April 2024. Patients were included in the primary analysis if irinotecan was dosed according to UGT1A1 genotype (ie, 100% ±10% dose intensity for intermediate and normal metabolizers [IM/NMs] and 70% ±10% for PMs) in at least cycle 1. Toxicities, hospitalizations, and treatment alterations were collected for cycles 1-3 and graded according to CTCAE version 5.0. Endpoints were compared between PMs with a 70% starting dose and fully dosed IM/NMs. RESULTS:A total of 501 patients were included in the primary analysis; 54 of whom were PMs (10.8%). Baseline characteristics were evenly distributed between groups. The incidences of overall severe toxicity (29.6% vs 34.0%; P=.52), febrile neutropenia (3.7% vs 5.8%; P=.76), severe neutropenia (17.0% vs 17.8%; P=.88), severe diarrhea (13.0% vs 15.0%; P=.69), and toxicity-related hospitalization (14.8% vs 21.7%; P=.24) were comparable between dose-reduced PMs and fully dosed IM/NMs. In a secondary analysis, 9 UGT1A1 PMs who received an unintended full irinotecan dose experienced more severe toxicity than PMs with a 70% starting dose (overall severe toxicity: 77.8% vs 29.6%; P=.009). CONCLUSIONS:UGT1A1 genotype-guided dosing of irinotecan improves patient safety and treatment tolerability of irinotecan. A 70% starting dose of irinotecan for UGT1A1 PMs is necessary to normalize the risk of severe toxicity to that of IM/NMs.

Objectives To investigate whether in undifferentiated arthritis (UA) it is beneficial to start early treatment with disease-modifying antirheumatic drugs (DMARDs) compared with symptomatic therapy.Methods The Induction of Cure in Early Arthritis study is a 3-month multicentre single-blinded randomised controlled trial followed by a 9-month observational period. Patients with early DMARD-naïve UA (arthritis ≥2 joints, not fulfilling American College of Rheumatology (ACR)/European Alliance of Associations for Rheumatology (EULAR) 2010 Rheumatoid Arthritis criteria) received a glucocorticoid injection (40 mg intra-articular or intramuscular) and were randomised (1:1:1) to a 3-month intervention with (1) non-steroidal anti-inflammatory drugs (NSAIDs) in standard daily dose or (2) methotrexate (MTX) 15 mg/week increased to 25 mg/week or (3) baricitinib 4 mg/day. Primary endpoint was Disease Activity Score (DAS) (44/53 joints) improvement at 3 months. Differences between treatment arms were assessed with analysis of covariance, adjusted for baseline DAS.Results Patients were randomised to NSAID (n=29), MTX (n=28) or baricitinib (n=28). After 3 months, baricitinib gave a significant improvement in DAS compared with NSAIDs: adjusted mean change in DAS: −0.52 (95% CI −0.93 to −0.11; p=0.01). MTX gave a numerically similar improvement: −0.39 (95% CI −0.84 to 0.06, p=0.09). Although non-significant, at 12 months DAS was lowest in the MTX treatment arm 1.3 (SD 0.7), NSAID 1.6 (SD 0.9), baricitinib 1.7 (SD 0.9), p=0.38. Incidence rates of severe adverse events remained low during the study across all treatment arms.Conclusions In patients with UA, early DMARD treatment led to greater improvement in disease activity over 3 months compared with NSAIDs, with the improvement for baricitinib reaching statistical significance. Over 12 months, disease activity was not significantly different across treatment arms, with overall favourable outcomes.

BACKGROUND:The TREAT EARLIER trial showed that a time-limited intervention with 12 months of methotrexate in individuals with arthralgia at risk of rheumatoid arthritis improved inflammatory burden but did not prevent rheumatoid arthritis after 2 years. Long-term follow-up is needed to assess the durability of the effects. In addition, heterogeneity in pathophysiological subtype (with or without anti-citrullinated protein antibodies [ACPA]) and disease risk was not considered in the 2-year analysis. Therefore, we investigated the long-term effect of methotrexate in reducing disease burden and progression to rheumatoid arthritis in ACPA-positive and ACPA-negative individuals at increased risk of rheumatoid arthritis. METHODS:The TREAT EARLIER trial was a randomised, placebo-controlled trial of participants aged 18 years or older, with clinically suspect arthralgia and subclinical joint inflammation. Participants were recruited from 13 rheumatology outpatient clinics in the Netherlands and randomly assigned (1:1) to a single intramuscular glucocorticoid injection (methylprednisolone 120 mg) followed by a 1-year course of methotrexate (up to 25 mg/week), or placebo (single injection and tablets for 1 year). Participants and investigators were masked to group assignment for at least 2 years. Follow-up continued for 5 years. The two primary endpoints in this 5-year follow-up analysis were disease burden (physical disability) and development of rheumatoid arthritis, assessed on an intention-to-treat basis. Patients were stratified for ACPA; only those at increased predicted risk (>10%) were included in the 5-year analysis. People with lived experience of clinically suspect arthralgia or rheumatoid arthritis were involved in the study design. This trial is registered with EudraCT (2014-004472-35) and the Netherlands Trial Register (NTR4853-trial-NL4599), and is complete. FINDINGS:Between April 16, 2015, and Sept 11, 2019, we enrolled 236 participants; 119 were assigned to active treatment and 117 to placebo. 215 (91%) participants completed the 5-year follow-up. 120 participants at increased predicted risk of rheumatoid arthritis were analysed at 5 years, of whom 66 (55%) were ACPA-negative and 54 (45%) were ACPA-positive. Mean age was 48 (SD 12) years, 72 (60%) of 120 participants were female, and 48 (40%) were male. Over 5 years, ACPA-negative participants in the active treatment group (n=35) had sustained improvement in physical disability compared with ACPA-negative participants in the placebo group (n=31; mean difference in Health Assessment Questionnaire disability index [HAQ] -0·16 [95% CI -0·29 to -0·04], p=0·0082) whereas, in ACPA-positive participants, the previously reported benefit in physical disability at 2 years in the treatment group versus placebo group was not sustained (-0·12 [-0·26 to 0·03], p=0·12). Three (9%) of 35 ACPA-negative participants in the treatment group developed rheumatoid arthritis compared with ten (32%) of 31 in the placebo group over 5 years (hazard ratio [HR] 0·24 [95% CI 0·07 to 0·87], p=0·018), corresponding to a number needed to treat of four. In ACPA-positive participants, 18 (58%) of 31 in the treatment group developed rheumatoid arthritis versus 15 (65%) of 23 in the placebo group (HR 0·75 [0·38-1·49], p=0·41). In the full trial cohort of 236 participants, physical disability in the treatment group improved durably over 5 years compared with the placebo group (mean difference in HAQ -0·06 [95% CI -0·14 to -0·05], p=0·048), though development of rheumatoid arthritis was not prevented, with 26 (22%) of 119 participants developing rheumatoid arthritis in the treatment group and 31 (27%) of 117 in the placebo group (HR 0·79 [95% CI 0·47 to 1·34], p=0·38). INTERPRETATION:Secondary prevention with a single intramuscular glucocorticoid injection and 1 year of methotrexate has different long-term effects on developing rheumatoid arthritis in ACPA-positive participants and in ACPA-negative participants. ACPA-negative participants had a long-term reduction in inflammatory disease burden and development of rheumatoid arthritis whereas there was no sustained improvement with ACPA-positive participants. These results imply that different treatment strategies are needed for ACPA-positive and ACPA-negative individuals with arthralgia who are at risk of rheumatoid arthritis. FUNDING:Dutch Research Council (NWO), Dutch Arthritis Society.

AIMS:Voriconazole is commonly used to prevent fungal infections after haematopoietic stem cell transplantation (HSCT). Although its metabolism is influenced by CYP2C19 genetics and inflammation, their combined effect is rarely considered in clinical practice, and integrated analyses remain limited. METHODS:We retrospectively analysed how inflammation and CYP2C19-predicted drug-metaboliser phenotypes affect voriconazole exposure and therapeutic range attainment in 126 HSCT patients. C-reactive protein (CRP) ≥ 10 mg/L defined inflammation. A linear mixed model (LMM) assessed associations between dose-corrected voriconazole concentrations, inflammation and CYP2C19-predicted drug-metaboliser phenotype. RESULTS:Dose-corrected voriconazole trough concentrations were associated with CYP2C19-predicted drug-metaboliser phenotype (LMM p = <2e-16, effect size of CYP2C19-phenotype: β = -5.99e-02-mg/L per mg voriconazole, standard error (SE) = 2.75e-02-mg/L per mg voriconazole, p = 0.0315; effect size of CRP: β = 1.54e-03-mg/L per mg voriconazole, SE = 2.79E-04-mg/L per mg voriconazole, p = 5.49e-08) and were higher during inflammation. Inflammation increased supra-therapeutic concentrations and reduced subtherapeutic levels (p = 0.0080). This effect was most pronounced for intermediate metabolisers (n = 18 with and n = 31 without inflammation) and rapid metabolisers (n = 20 with and n = 28 without inflammation), with supra-therapeutic concentration of 33% vs. 3%, and 15% vs. 0%, respectively (p = 0.02). Finally, in a longitudinal subset (n = 25), concentrations tracked inflammatory status across prior-, during and post-inflammation timepoints. CONCLUSIONS:This study demonstrates inflammation and CYP2C19 genotype jointly influence voriconazole exposure and target attainment in clinical practice. These findings support intensified therapeutic drug monitoring with concurrent CRP assessment, particularly for intermediate and rapid metabolisers, to reduce the risk of supra-therapeutic voriconazole concentrations during inflammation.

Abstract Inflammatory bowel disease (IBD) requires the use of immunosuppressive therapies. Thiopurines (azathioprine and 6-mercaptopurine) are among the therapeutic options. However, adverse drug reactions (ADRs) affect 25% of patients, causing treatment discontinuation in 17% of cases. Thiopurine-induced pancreatitis, defined by meeting ≥2 criteria of amylase/lipase >3× upper reference limit, abdominal pain, or radiological abnormalities, represents a serious ADR. While genetic variants in TPMT/NUDT15 predict myelotoxicity, the genetic basis of pancreatitis remains unclear. We conducted a genome-wide association studies examining pancreatitis cases (N=13), amylase elevation, and amylase concentration in thiopurine-treated IBD patients (n=722). Suggestive associations (p<10⁻⁵) were found in genes involved in cell signaling and development: DSCAM, MACF1, PTPRD, MGAT4C, ELDR, and LRP1B. Given evidence that thiopurine-induced pancreatitis is immune-mediated, these candidates may modulate cellular responses affecting susceptibility to pancreatitis. If validated in larger cohorts, our findings may provide potential genetic markers for thiopurine-induced pancreatitis.

Background Rheumatoid arthritis (RA) is a heterogeneous disease. Patients vary in symptoms, prognosis and treatment response, demonstrating the need for a more refined taxonomy. Objective To identify distinct phenotypic subsets of RA patients based on baseline clinical data, in order to advance understanding of disease etiology and treatment strategies. Methods We collected hematological, serological, and clinical data from RA-patients in the Leiden Rheumatology clinic(n = 1,387), and combined multimodal deep learning techniques with clustering to identify phenotypically distinct RA subsets. These clusters were tested for associations in clinical outcomes. Findings were replicated in clinical trial data (n = 307) and independent secondary care (9 clinics, n = 515), and further explored for histological differences in synovial tissue (n = 194). Results Four distinct RA subsets with different Joint Involvement Patterns (JIP), emerged: 1) foot-predominant arthritis, 2) seropositive oligoarticular disease, 3) seronegative hand arthritis, and 4) polyarthritis. We found high cluster stability, no physician influence, significant difference in remission rates (P = 0.007) and methotrexate failure ( P < 0.001) in initial and replication sets. The JIP-hand subgroup had significantly better outcomes. This was largest in the ACPA-positive stratum (JIP-hand versus JIP-foot (HR:0.37 (95%CI: 0.15–0.60) P < 0.001), JIP-hand versus JIP-poly HR:0.33 (95%CI: 0.15–0.72) P = 0.005). This was independent of baseline disease activity, clinical markers (RF, ACPA, Sex, Age), and symptom duration. Synovial histology showed both JIP-poly and JIP-hand had increased synovial lining and inflammatory infiltrate, with JIP-hand showing notably high stromal density. JIP-feet scored evenly across categories without standing out, while JIP-oligo had lower synovitis degree. Conclusions We identified and validated four distinct RA phenotypes characterized by joint involvement patterns, which associate with treatment outcomes and synovial histology. These findings may allow for targeted research into RA mechanisms and therapies.

Pharmacogenomic research has historically focused on individuals of European ancestry, leading to the underrepresentation of genetic variants common in non-European populations. This bias is exemplified by CYP3A5*6, a functionally consequential variant common in individuals of African ancestry (MAF: 11-19%) but virtually absent in Europeans (MAF: 0.15%). We conducted a retrospective, longitudinal cohort study using real-world data from 1,461 adult kidney transplant recipients across 67 countries, analyzing 4,293 dose-normalized 24-hour area-under-the-curve (AUC0-24) measurements of tacrolimus. Patients with CYP3A5*1/*1 were excluded. Linear mixed-effects models (LME) were used to assess the association between CYP3A5*6 carriage and tacrolimus exposure, adjusting for clinical factors and ancestry using both HLA-based principal components and country of birth. CYP3A5*6 carriers had a 17% lower dose-normalized AUC0-24 than CYP3A5*3 carriers (P = 0.015). Sensitivity analyses using dose-normalized trough concentrations (C0) confirmed these findings, with a 20% lower exposure in CYP3A5*6 carriers (P = 0.011). An interval-based analysis demonstrated persistently lower tacrolimus exposure across the first post-transplant year. All CYP3A5*6-containing genotypes showed significantly lower dose-normalized AUC0-24 compared to CYP3A5*3/*3, the most common genotype in European populations, with the largest reductions observed in CYP3A5*1/*6 (-39%; P < 0.001) and CYP3A5*3/*6 (-18%; P = 0.006). African origin, defined by country of birth, was independently associated with a 23% higher AUC0-24 (P < 0.001). This is the first study to demonstrate a differential effect on tacrolimus exposure between the CYP3A5*6 and CYP3A5*3 loss-of-function alleles. Our results may help bridge the ethnicity gap, advance the applicability of pharmacogenomic findings, and promote health equity.

In various missing data problems, values are not entirely missing, but are coarsened. For coarsened observations, instead of observing the true value, a subset of values - strictly smaller than the full sample space of the variable - is observed to which the true value belongs. In our motivating example for patients with endometrial carcinoma, the degree of lymphovascular space invasion (LVSI) can be either absent, focally present, or substantially present. For a subset of individuals, however, LVSI is reported as being present, which includes both non-absent options. In the analysis of such a dataset, difficulties arise when coarsened observations are to be used in an imputation procedure. To our knowledge, no clear-cut method has been described in the literature on how to handle an observed subset of values, and treating them as entirely missing could lead to biased estimates. Therefore, in this paper, we evaluated the best strategy to deal with coarsened and missing data in multiple imputation. We tested a number of plausible ad hoc approaches, possibly already in use by statisticians. Additionally, we propose a principled approach to this problem, consisting of an adaptation of the SMC-FCS algorithm (SMC-FCS   CoCo $$ {}_{\mathrm{CoCo}} $$ : Coarsening compatible), that ensures that imputed values adhere to the coarsening information. These methods were compared in a simulation study. This comparison shows that methods that prevent imputations of incompatible values, like the SMC-FCS   CoCo $$ {}_{\mathrm{CoCo}} $$ method, perform consistently better in terms of a lower bias and RMSE, and achieve better coverage than methods that ignore coarsening or handle it in a more naïve way. The analysis of the motivating example shows that the way the coarsening information is handled can matter substantially, leading to different conclusions across methods. Overall, our proposed SMC-FCS   CoCo $$ {}_{\mathrm{CoCo}} $$ method outperforms other methods in handling coarsened data, requires limited additional computation cost and is easily extendable to other scenarios.

Missing data problems are common in biological, high-dimensional data, where data can be partially or completely missing. Algorithms have been developed to reconstruct the missing values by means of imputation or expectation-maximization algorithms. For missing data problems, it has been suggested that the regression model of interest should be incorporated into the imputation procedure to reduce bias of the regression coefficients. We here consider a challenging missing data problem, where diplotypes of the KIR loci are to be reconstructed. These loci are difficult to genotype, resulting in ambiguous genotype calls. We extend a previously proposed expectation-maximization algorithm by incorporating a potentially high-dimensional regression model to model the outcome. Three strategies are evaluated: (1) only allelic predictors, (2) allelic predictors and forward-backward selection on haplotype predictors, and (3) penalized regression on a saturated model. In a simulation study, we compared these strategies with a baseline expectation-maximization algorithm without outcome model. For extreme choices of effect sizes and missingness levels, the outcome-based expectation-maximization algorithms outperformed the no-outcome expectation-maximization algorithm. However, in all other cases, the no-outcome expectation-maximization algorithm performed either superior or comparable to the three strategies, suggesting the outcome model can have a harmful effect. In a data analysis concerning death after allogeneic hematopoietic stem cell transplantation as a function of donor KIR genes, expectation-maximization algorithms with and without outcome showed very similar results. In conclusion, outcome based missing data models in the high-dimensional setting have to be used with care and are likely to lead to biased results.

Background:Pharmacogenetics (PGx) aims to revolutionize healthcare by individualizing drug doses and medication choices. However, clinical uptake will require positive evaluation evidence of both clinical utility and cost-effectiveness. We have recently demonstrated the clinical utility of this approach, using a panel-based PGx-guided treatment of patients from various indications recruited in seven countries (PREPARE study). Methods:Here, we provide economic evidence from a multinational cost-utility analysis of PGx-guided treatment in 6930 patients participating in the PREPARE study. The study was conducted from March 2017 to June 2020. We used the national healthcare system's perspective in each participating country, including only direct medical costs that budget holders cover. A Visual Analog Scale was used to measure utility and the quality of life was estimated by averaging the Visual Analog Scale scores of participants over four specific time points in the study, namely baseline visit (day 1), week 4, week 12, and 18 months from the baseline visit. Findings:Our analysis showed that the PGx-guided treatment is marginally cost-effective at the threshold of €11,000 QALYs. Cost drivers were hospitalization and ADRs costs, accounting for most of the resources used in both groups (46% and 37.5% in the PGx-guided group versus 49% and 48% in the control group, respectively), as a result of the average duration of hospitalization [1.51 days (95% CI: 1.23-1.82) for the PGx-guided group and 2.37 days (95% CI: 1.95-2.89) for the control group, resulting in a mean difference of 0.86 days (95% CI: 0.37-1.44). The difference in QALYs gained was 0.00178 (95% CI: 0.00176-0.00180). The ICER was €12,020 (95% CI: €10,957-€13,356) per QALY on average (SD: €116). When comparing cost and effectiveness of actionable PGx-guided versus actionable control patients, the total cost for the PGx-guided group was €491 (95% CI: €384-€613), versus €767 (95% CI: €583-€982) in the control group, with an incremental cost difference of €276 (95% CI: €62-€511), favoring the PGx-guided group. Also, the difference in effectiveness was 0.007 QALYs (95% CI: -0.021 to 0.033). Lastly, the difference in the mean total cost was estimated to be €21.4 (95% CI: €19.5-€23.8), while without considering the PGx test cost, indicative of a pre-emptive genetic testing approach, the PGx-guided treatment becomes a cost-saving option, with an estimated savings of approximately €103.6 (€124-€21.4) per patient. Interpretation:These data suggest that panel-based PGx testing is cost-effective, which, together with the clinically beneficial outcomes already demonstrated in the PREPARE study, provides additional evidence of the need to implement PGx into clinical practice. Funding:European Union Horizon 2020.

The Ubiquitous Pharmacogenomics consortium (www.upgx.eu) has recently completed and published the Preemptive Pharmacogenomic Testing for Preventing Adverse Drug Reactions (PREPARE) study on the implementation of panel-based pharmacogenetic testing. PREPARE has provided interesting lessons for the design, execution, and interpretation of future clinical implementation studies. In this paper, we share our experience and lessons learned from the PREPARE study for future pharmacogenetic implementation studies. Issues addressed are the study population, intervention, endpoint, randomization, blinding, crossover, ethics, real-world changes during the study, and data analysis and reporting.

Rheumatoid arthritis (RA) is a heterogeneous disease with variable symptoms, prognosis, and treatment response, necessitating refined patient classification. We applied multimodal deep learning and clustering to identify distinct RA phenotypes using baseline clinical data from 1,387 patients in the Leiden Rheumatology clinic. Four Joint Involvement Patterns (JIP) emerged: foot-predominant arthritis, seropositive oligoarticular disease, seronegative hand arthritis, and polyarthritis. Findings were validated in clinical trial data (n = 307) and an independent secondary care cohort (n = 515). Clusters showed high stability and significant differences in remission rates (P = 0.007) and methotrexate failure (P < 0.001). JIP-hand patients had superior outcomes (particularly in ACPA-positive patients) versus JIP-foot (HR:0.37, P < 0.001) and JIP-poly (HR:0.33, P = 0.005), independent of baseline disease activity and clinical markers. Synovial histology analysis (n = 194) revealed distinct inflammatory patterns across clusters, hinting at different underlying biological mechanisms. These validated RA phenotypes based on joint involvement patterns may enable targeted research into disease mechanisms and personalized treatment strategies.

PURPOSE:Although the European Medicines Agency approved durvalumab post-chemoradiation (CRT) only for stage III unresectable non-small cell lung cancer (UR-NSCLC) patients with PD-L1 tumor proportion scores (TPS) ≥ 1%, the Netherlands offers reimbursement irrespective of PD-L1 status. This real-world study compares survival between durvalumab-treated patients with PD-L1 TPS < 1% vs. ≥ 1%, and also evaluates its effectiveness against a historic-cohort. PATIENTS AND METHODS:This multicenter retrospective study included 2 patient cohorts with stage III UR-NSCLC: a durvalumab cohort and a historic CRT-only cohort. The durvalumab cohort was divided into PD-L1 TPS subgroups: < 1%, ≥ 1%, and unknown. Overall survival (OS) and progression-free survival (PFS) were compared between (1) durvalumab-treated patients with PD-L1 TPS < 1% vs. ≥ 1%, and (2) durvalumab cohort (including PD-L1 subgroups) vs. historic-cohort. RESULTS:229 and 339 patients were included in the durvalumab- and historic-cohorts, respectively. Although not statistically significant, durvalumab-treated patients with PD-L1 TPS ≥ 1% experienced a modestly greater benefit in OS (2-year OS 74.3% vs. 66.5%) and PFS (2-year PFS 55.5% vs. 36.2%) compared to those with PD-L1 TPS < 1%. Survival outcomes favored durvalumab over the historic cohort across PD-L1 subgroups, though PFS improvement was not statistically significant for PD-L1 TPS < 1%. CONCLUSIONS:Given these findings, patients with PD-L1 TPS < 1% may also benefit from durvalumab treatment in stage III UR-NSCLC.

Background: Studying which biological pathways are involved in reaching remission in auto-immune diseases could highlight possible targetable mechanisms. Rheumatoid arthritis (RA) is the ideal model disease to study this hypothesis due to well-defined and widely-used measures of disease activity. Objectives: To increase understanding of the mechanisms and biological pathways underlying autoimmune disease remission through GWAS directed functional studies. Methods: The RTCure network collected genetic data of 5,622 deeply phenotyped treatment naive RA patients with longitudinal disease activity data. Data were uniformly QC’ed and imputed using the Haplotype Reference Consortium reference panel. We carried out a GWAS per dataset with DAS28-CRP below 2.6 at 6 months as our outcome, including top 10 principal components, age and sex as covariates. We combined the results using a fixed-effect meta-analysis. SNPs were mapped to genes using Open Targets Genetics. We assessed gene expression using single cell RNAseq of synovial biopsies (AMP-I [1], PEAC [2], Zurich and Queensland) and eQTL data of circulating CD4+ T-cells from untreated RA patients (NEAC) [3]. To investigate the role of Ca2+ induced endoplasmic reticulum (ER) stress on FKBP7, Rheumatoid Arthritis fibroblast-like synoviocytes (RA-FLS) HPRT-knockout cells were stimulated with 400nM thapsigargin (Tg) for 24 hours and cell lysate was collected for RNA analysis. Relative mRNA expression of FKBP7 and stress-related genes CHOP, Grp78 and sXBP1 was calculated against the housekeeper β-actin. Results: Our top hit (P < 5 x 10-8), rs16866400 (Figure 1A-B), has the strongest e-, p- and sQTL association with FK506 binding protein 7 (FKBP7), whose relevance to auto-immunity is understudied. The association was not driven by CCP status, HLA or DMARD usage. The FKBP7 protein is an ER resident chaperone regulating the folding of proteins. Both public and proprietary data show that FKBP7 is differentially overexpressed in a key RA tissue, fibroblast-like synoviocytes (FLS), rather than in circulating B- and T-cells(Figure 1C-E). FKBP7 expression in blood associated both with baseline and change in DAS28-CRP. (Figure 1F) Our studies show that in response to Tg induced Ca2+ ER stress, but not other stressors such as tunicamycin or pro-inflammatory cytokines, FKBP7 was upregulated in RA FLS (Figure 2). FKBP7 has been found to regulate the NOD2 pathway[4]. As this is strongly associated with inflammatory immune responses in Crohn’s Disease (CD), we checked published Crohn’s progression GWAS data for colonic FKPB7 eQTLs.[5] 22% of the colonic FKBP7 eQTLs (GTEx) included in the CD GWAS were significantly (P < 0.05) associated with CD severity. Conclusion: We found the ER resident molecular chaperone encoding gene FKBP7 to link to both RA remission and CD severity. Our functional studies demonstrate a role for the chaperone in the regulation of Ca2+ ER stress and highlights FKBP7 as an interesting gene for further research related to the induction of remission. Elucidating the underlying mechanisms will both increase our understanding of auto-immune pathophysiology as well as facilitate the discovery of novel treatment targets. REFERENCES: [1] Zhang et al, 2019, Nat Imm.[2] Lewis et al, 2019, Cell Rep.[3] Thalayasingam et al, 2018, A&R.[4] Warner et al, 2013, Sci. Signal.[5] Lee, J. C., Biasci, D., et al., 2017, Nat Genet. Acknowledgements: We would like to acknowledge support by SPIDeRR Horizon EU (grant 101080711), RTCure, the IMI2 JU (grant 777357), ZonMW (grant 90719069), MRC/Versus Arthritis MATURA Consortium, Versus Arthritis Inflammatory Arthritis Centre Versus Arthritis, NIHR Newcastle Biomedical Research Centre, NIHR Leeds BioMedical Research Centre, UK Medical Research Council (TACERA) and Pfizer. Disclosure of Interests: Marc P. Maurits: None declared, Amy Cameron: None declared, Scott Jelinsky No conflict of interest applies to this abstract, Stephan Blüml: None declared, Lydia Abasolo: None declared, Johan Askling: None declared, Anne Barton: None declared, Stefan Böhringer: None declared, Andrew Cope: None declared, Saurav De No conflict of interest applies to this abstract, Paul Emery: None declared, Stephen Eyre: None declared, Vasanthi Priyadarshini Gaddi: None declared, Isidoro González-Álvaro: None declared, Carl S Goodyear: None declared, Xinli Hu No conflict of interest applies to this abstract, Tom Huizinga: None declared, Martina Johannesson: None declared, Samantha Jurado-Zapata: None declared, Lars Klareskog: None declared, Dennis Lendrem: None declared, Paul Martin: None declared, Iain B. Mc Innes: None declared, Raphael Micheroli: None declared, Ann Morgan: None declared, Fraser Morton: None declared, Najib Naamane: None declared, Yasuo Nagafuchi: None declared, Gisela Orozco: None declared, Leonid Padyukov: None declared, Caron Paterson: None declared, Costantino Pitzalis: None declared, Darren Plant: None declared, Duncan Porter: None declared, Louise Reynard: None declared, Luis Rodriguez Rodriguez: None declared, Daniela Sieghart: None declared, Paul Studenic: None declared, John Taylor: None declared, Rene E.M. Toes: None declared, Erik B. van den Akker: None declared, Annette H.M. van der Helm – van Mil: None declared, Lotta Vaskimo: None declared, Suzanne Verstappen: None declared, Helga Westerlind: None declared, John Isaacs: None declared, Myles Lewis: None declared, Arthur Pratt: None declared, Caroline Ospelt: None declared, Aaron Winkler No conflict of interest applies to this abstract, Ranjeny Thomas: None declared, Rachel Knevel: None declared.Figure 1(A) Manhattan plot, dashed line at p = 5 x 10-8, (B) forest plot of rs16866400 locus, (C) FKBP7 expression in fibroblasts, monocytes, T-cells and B-cells in RA, osteoarthritis and healthy participants [1] (n = 55 RA patients), (D-E) expression across cell types in arthritis patients (n=355 RA patients and n = 26 synovial tissues of 5 arthritides respectively) and (F) association between FKBP7 levels in blood and DAS28-CRP (response). Figure 2Thapsigargin treated (24h) vs untreated RA-FLS HPRTKO. Relative mRNA expression of (a) FKBP7 and stress genes (b) CHOP, (c) Grp78 and (d) sXBP1 calculated against β-actin. n=8/group

Tamoxifen is part of the standard of care of endocrine therapy for adjuvant treatment of breast cancer. However, survival outcomes with tamoxifen are highly variable. The concentration of endoxifen, the 30-100 times more potent metabolite of tamoxifen and bioactivated by the CYP2D6 enzyme, has been described as the most relevant metabolite of tamoxifen metabolism. A genome-wide association study (GWAS) was performed with the objective to identify genetic polymorphisms associated with endoxifen serum concentration levels and clinical outcome in early-stage breast cancer patients receiving tamoxifen. A GWAS was conducted in 608 women of the CYPTAM study (NTR1509/PMID: 30120701). Germline DNA and clinical and survival characteristics were readily available. Genotyping was performed on Infinium Global Screening Array (686,082 markers) and single nucleotide polymorphism (SNP) imputation by using 1000 Genomes. Relapse-free survival during tamoxifen (RFSt) was defined the primary clinical outcome. Endoxifen serum concentration was analyzed as a continuous variable. Several genetic variants reached genome-wide significance (P value: ≤5 × 10-8). Endoxifen concentrations analysis identified 430 variants, located in TCF20 and WBP2NL genes (chromosome 22), which are in strong linkage disequilibrium with CYP2D6 variants. In the RFSt analysis, several SNP were identified (LPP gene: rs77693286, HR 18.3, 95% CI: 15.2-21.1; rs6790761, OR 18.2, 95% CI: 15.5-21.1). Endoxifen concentrations have a strong association with the chromosome 22, which contains the CYP2D6 gene.