Identification of a DNA methylation episignature for recurrent constellations of embryonic malformations

The term "recurrent constellations of embryonic malformations" (RCEM) is used to describe a number of multiple malformation associations that affect three or more body structures. The causes of these disorders are currently unknown, and no diagnostic marker has been identified. Consequently, providing a definitive diagnosis in suspected individuals is challenging. In this study, genome-wide DNA methylation analysis was conducted on DNA samples obtained from the peripheral blood of 53 individuals with RCEM characterized by clinical features recognized as VACTERL and/or oculoauriculovertebral spectrum association. We identified a common DNA methylation episignature in 40 out of the 53 individuals. Subsequently, a sensitive and specific binary classifier was developed based on the DNA methylation episignature. This classifier can facilitate the use of RCEM episignature as a diagnostic biomarker in a clinical setting. The study also investigated the functional correlation of RCEM DNA methylation relative to other genetic disorders with known episignatures, highlighting the common genomic regulatory pathways involved in the pathophysiology of RCEM.

Generative artificial intelligence to produce high-fidelity blastocyst-stage embryo images

STUDY QUESTION

Can generative artificial intelligence (AI) models produce high-fidelity images of human blastocysts?

SUMMARY ANSWER

Generative AI models exhibit the capability to generate high-fidelity human blastocyst images, thereby providing substantial training datasets crucial for the development of robust AI models.

WHAT IS KNOWN ALREADY

The integration of AI into IVF procedures holds the potential to enhance objectivity and automate embryo selection for transfer. However, the effectiveness of AI is limited by data scarcity and ethical concerns related to patient data privacy. Generative adversarial networks (GAN) have emerged as a promising approach to alleviate data limitations by generating synthetic data that closely approximate real images.

STUDY DESIGN, SIZE, DURATION

Blastocyst images were included as training data from a public dataset of time-lapse microscopy (TLM) videos (n = 136). A style-based GAN was fine-tuned as the generative model.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We curated a total of 972 blastocyst images as training data, where frames were captured within the time window of 110-120 h post-insemination at 1-h intervals from TLM videos. We configured the style-based GAN model with data augmentation (AUG) and pretrained weights (Pretrained-T: with translation equivariance; Pretrained-R: with translation and rotation equivariance) to compare their optimization on image synthesis. We then applied quantitative metrics including Fréchet Inception Distance (FID) and Kernel Inception Distance (KID) to assess the quality and fidelity of the generated images. Subsequently, we evaluated qualitative performance by measuring the intelligence behavior of the model through the visual Turing test. To this end, 60 individuals with diverse backgrounds and expertise in clinical embryology and IVF evaluated the quality of synthetic embryo images.

MAIN RESULTS AND THE ROLE OF CHANCE

During the training process, we observed consistent improvement of image quality that was measured by FID and KID scores. Pretrained and AUG + Pretrained initiated with remarkably lower FID and KID values compared to both Baseline and AUG + Baseline models. Following 5000 training iterations, the AUG + Pretrained-R model showed the highest performance of the evaluated five configurations with FID and KID scores of 15.2 and 0.004, respectively. Subsequently, we carried out the visual Turing test, such that IVF embryologists, IVF laboratory technicians, and non-experts evaluated the synthetic blastocyst-stage embryo images and obtained similar performance in specificity with marginal differences in accuracy and sensitivity.

LIMITATIONS, REASONS FOR CAUTION

In this study, we primarily focused the training data on blastocyst images as IVF embryos are primarily assessed in blastocyst stage. However, generation of an array of images in different preimplantation stages offers further insights into the development of preimplantation embryos and IVF success. In addition, we resized training images to a resolution of 256 × 256 pixels to moderate the computational costs of training the style-based GAN models. Further research is needed to involve a more extensive and diverse dataset from the formation of the zygote to the blastocyst stage, e.g. video generation, and the use of improved image resolution to facilitate the development of comprehensive AI algorithms and to produce higher-quality images.

WIDER IMPLICATIONS OF THE FINDINGS

Generative AI models hold promising potential in generating high-fidelity human blastocyst images, which allows the development of robust AI models as it can provide sufficient training datasets while safeguarding patient data privacy. Additionally, this may help to produce sufficient embryo imaging training data with different (rare) abnormal features, such as embryonic arrest, tripolar cell division to avoid class imbalances and reach to even datasets. Thus, generative models may offer a compelling opportunity to transform embryo selection procedures and substantially enhance IVF outcomes.

STUDY FUNDING/COMPETING INTEREST(S)

This study was supported by a Horizon 2020 innovation grant (ERIN, grant no. EU952516) and a Horizon Europe grant (NESTOR, grant no. 101120075) of the European Commission to A.S. and M.Z.E., the Estonian Research Council (grant no. PRG1076) to A.S., and the EVA (Erfelijkheid Voortplanting & Aanleg) specialty program (grant no. KP111513) of Maastricht University Medical Centre (MUMC+) to M.Z.E.

TRIAL REGISTRATION NUMBER

Not applicable.

An interconnected data infrastructure to support large-scale rare disease research

The Solve-RD project brings together clinicians, scientists, and patient representatives from 51 institutes spanning 15 countries to collaborate on genetically diagnosing ("solving") rare diseases (RDs). The project aims to significantly increase the diagnostic success rate by co-analyzing data from thousands of RD cases, including phenotypes, pedigrees, exome/genome sequencing, and multiomics data. Here we report on the data infrastructure devised and created to support this co-analysis. This infrastructure enables users to store, find, connect, and analyze data and metadata in a collaborative manner. Pseudonymized phenotypic and raw experimental data are submitted to the RD-Connect Genome-Phenome Analysis Platform and processed through standardized pipelines. Resulting files and novel produced omics data are sent to the European Genome-Phenome Archive, which adds unique file identifiers and provides long-term storage and controlled access services. MOLGENIS "RD3" and Café Variome "Discovery Nexus" connect data and metadata and offer discovery services, and secure cloud-based "Sandboxes" support multiparty data analysis. This successfully deployed and useful infrastructure design provides a blueprint for other projects that need to analyze large amounts of heterogeneous data.

Systematic analysis of paralogous regions in 41,755 exomes uncovers clinically relevant variation

The short lengths of short-read sequencing reads challenge the analysis of paralogous genomic regions in exome and genome sequencing data. Most genetic variants within these homologous regions therefore remain unidentified in standard analyses. Here, we present a method (Chameleolyser) that accurately identifies single nucleotide variants and small insertions/deletions (SNVs/Indels), copy number variants and ectopic gene conversion events in duplicated genomic regions using whole-exome sequencing data. Application to a cohort of 41,755 exome samples yields 20,432 rare homozygous deletions and 2,529,791 rare SNVs/Indels, of which we show that 338,084 are due to gene conversion events. None of the SNVs/Indels are detectable using regular analysis techniques. Validation by high-fidelity long-read sequencing in 20 samples confirms >88% of called variants. Focusing on variation in known disease genes leads to a direct molecular diagnosis in 25 previously undiagnosed patients. Our method can readily be applied to existing exome data.

Multicenter clinical and functional evidence reclassifies a recurrent noncanonical filamin C splice-altering variant

BACKGROUND

Truncating variants in filamin C (FLNC) can cause arrhythmogenic cardiomyopathy (ACM) through haploinsufficiency. Noncanonical splice-altering variants may contribute to this phenotype.

OBJECTIVE

The purpose of this study was to investigate the clinical and functional consequences of a recurrent FLNC intronic variant of uncertain significance (VUS), c.970-4A>G.

METHODS

Clinical data in 9 variant heterozygotes from 4 kindreds were obtained from 5 tertiary health care centers. We used in silico predictors and functional studies with peripheral blood and patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). Isolated RNA was studied by reverse transcription polymerase chain reaction. iPSC-CMs were further characterized at baseline and after nonsense-mediated decay (NMD) inhibition, using quantitative polymerase chain reaction (qPCR), RNA-sequencing, and cellular electrophysiology. American College of Medical Genetics and Genomics (ACMG) criteria were used to adjudicate variant pathogenicity.

RESULTS

Variant heterozygotes displayed a spectrum of disease phenotypes, spanning from mild ventricular dysfunction with palpitations to severe ventricular arrhythmias requiring device shocks or progressive cardiomyopathy requiring heart transplantation. Consistent with in silico predictors, the c.970-4A>G FLNC variant activated a cryptic splice acceptor site, introducing a 3-bp insertion containing a premature termination codon. NMD inhibition upregulated aberrantly spliced transcripts by qPCR and RNA-sequencing. Patch clamp studies revealed irregular spontaneous action potentials, increased action potential duration, and increased sodium late current in proband-derived iPSC-CMs. These findings fulfilled multiple ACMG criteria for pathogenicity.

CONCLUSION

Clinical, in silico, and functional evidence support the prediction that the intronic c.970-4A>G VUS disrupts splicing and drives ACM, enabling reclassification from VUS to pathogenic.

Intraarticular steroids as DMARD-sparing agents for juvenile idiopathic arthritis flares: Analysis of the Childhood Arthritis and Rheumatology Research Alliance Registry

BACKGROUND

Children with juvenile idiopathic arthritis (JIA) who achieve a drug free remission often experience a flare of their disease requiring either intraarticular steroids (IAS) or systemic treatment with disease modifying anti-rheumatic drugs (DMARDs). IAS offer an opportunity to recapture disease control and avoid exposure to side effects from systemic immunosuppression. We examined a cohort of patients treated with IAS after drug free remission and report the probability of restarting systemic treatment within 12 months.

METHODS

We analyzed a cohort of patients from the Childhood Arthritis and Rheumatology Research Alliance (CARRA) Registry who received IAS for a flare after a period of drug free remission. Historical factors and clinical characteristics and of the patients including data obtained at the time of treatment were analyzed.

RESULTS

We identified 46 patients who met the inclusion criteria. Of those with follow up data available 49% had restarted systemic treatment 6 months after IAS injection and 70% had restarted systemic treatment at 12 months. The proportion of patients with prior use of a biologic DMARD was the only factor that differed between patients who restarted systemic treatment those who did not, both at 6 months (79% vs 35%, p < 0.01) and 12 months (81% vs 33%, p < 0.05).

CONCLUSION

While IAS are an option for all patients who flare after drug free remission, it may not prevent the need to restart systemic treatment. Prior use of a biologic DMARD may predict lack of success for IAS. Those who previously received methotrexate only, on the other hand, are excellent candidates for IAS.

At age 9, the methylome of assisted reproductive technology children that underwent embryo culture in different media is not significantly different on a genome-wide scale

STUDY QUESTION

Can we detect DNA methylation differences between ART children that underwent embryo culture in different media?

SUMMARY ANSWER

We identified no significant differences in site-specific or regional DNA methylation between the different culture medium groups.

WHAT IS KNOWN ALREADY

Embryo culture in G3 or K-SICM medium leads to differences in embryonic, neonatal and childhood outcomes, including growth and weight. The methylome may mediate this association as the period of in vitro culture of ART treatments coincides with epigenetic reprogramming.

STUDY DESIGN, SIZE, DURATION

This study was conducted as a follow-up to a previous culture medium comparison study in which couples were pseudo-randomized to embryo culture in G3 or K-SICM medium. Of the resultant singletons, 120 (n = 65 G3, n = 55 K-SICM), were recruited at age 9.

PARTICIPANTS/MATERIALS, SETTING, METHODS

The ART children provided a saliva sample from which the methylome was analysed using the Infinium MethylationEPIC array. After quality and context filtering, 106 (n = 57 G3, n = 49 K-SICM) samples and 659 708 sites were retained for the analyses. Differential methylation analyses were conducted using mixed effects linear models corrected for age, sex, sample plate and cell composition. These were applied to all cytosine-guanine dinucleotide (CpG) sites, various genomic regions (genes, promoters, CpG Islands (CGIs)) and as a targeted analysis of imprinted genes and birth weight-associated CpG sites. Differential variance was assessed using the improved epigenetic variable outliers for risk prediction analysis (iEVORA) algorithm and methylation outliers were identified using a previously defined threshold (upper or lower quartile plus or minus three times the interquartile range, respectively).

MAIN RESULTS AND THE ROLE OF CHANCE

After correcting for multiple testing, we did not identify any significantly differentially methylated CpG sites, genes, promoters or CGIs between G3 and K-SICM children despite a lenient corrected P-value threshold of 0.1. Targeted analyses of (sites within) imprinted genes and birth weight-associated sites also did not identify any significant differences. The number of DNA methylation outliers per sample was comparable between the culture medium groups. iEVORA identified 101 differentially variable CpG sites of which 94 were more variable in the G3 group.

LARGE SCALE DATA

Gene Expression Omnibus (GEO) GSE196432.

LIMITATIONS, REASONS FOR CAUTION

To detect significant methylation differences with a magnitude of <10% between the groups many more participants would be necessary; however, the clinical relevance of such small differences is unclear.

WIDER IMPLICATIONS OF THE FINDINGS

The results of this study are reassuring, suggesting that if there is an effect of the culture medium on DNA methylation (and methylation-mediated diseases risk), it does not differ between the two media investigated here. The findings concur with other methylome studies of ART neonates and children that underwent embryo culture in different media, which also found no significant methylome differences.

STUDY FUNDING/COMPETING INTEREST(S)

Study funded by March of Dimes (6-FY13-153), EVA (Erfelijkheid Voortplanting & Aanleg) specialty programme (grant no. KP111513) of Maastricht University Medical Centre (MUMC+) and the Horizon 2020 innovation (ERIN) (grant no. EU952516) of the European Commission. The authors do not report any conflicts of interest relevant to this study.

TRIAL REGISTRATION NUMBER

Dutch Trial register-NL4083.

Methylome-wide analysis of IVF neonates that underwent embryo culture in different media revealed no significant differences

A growing number of children born are conceived through in vitro fertilisation (IVF), which has been linked to an increased risk of adverse perinatal outcomes, as well as altered growth profiles and cardiometabolic differences in the resultant individuals. Some of these outcomes have also been shown to be influenced by the use of different IVF culture media and this effect is hypothesised to be mediated epigenetically, e.g. through the methylome. As such, we profiled the umbilical cord blood methylome of IVF neonates that underwent preimplantation embryo development in two different IVF culture media (G5 or HTF), using the Infinium Human Methylation EPIC BeadChip. We found no significant methylation differences between the two groups in terms of: (i) systematic differences at CpG sites or regions, (ii) imprinted sites/genes or birth weight-associated sites, (iii) stochastic differences presenting as DNA methylation outliers or differentially variable sites, and (iv) epigenetic gestational age acceleration.

OP0221 EFFICACY OF SECUKINUMAB IN ENTHESITIS-RELATED ARTHRITIS: RESULTS FROM A RANDOMISED, DOUBLE-BLIND, PLACEBO-CONTROLLED, TREATMENT WITHDRAWAL, PHASE 3 STUDY (JUNIPERA)

Background

Enthesitis-related Arthritis (ERA) is a category of juvenile idiopathic arthritis (JIA) characterised by heterogeneous and insidious manifestations comprising axial and/or peripheral arthritis, and enthesitis.1 Secukinumab (SEC) demonstrated efficacy and safety in both ERA and juvenile psoriatic arthritis (JPsA) in the JUNIPERA trial.2

Objectives

To evaluate the rate of flare risk reduction and efficacy of SEC on axial and peripheral manifestations in patients (pts) with active ERA.

Methods

ERA pts (2 to <18 years of age) with active disease (both ≥3 active joints and ≥1 active enthesitis site) were included. In the open-label (OL) treatment-period (TP)1, s.c. SEC (75/150 mg in pts <50/ ≥50 kg) was administered at baseline (BL), and at Week (Wk) 1–4, 8 and 12. Pts who achieved at least JIA-ACR30 response at Wk 12 were randomised into the double-blinded TP2 to continue SEC or placebo (PBO) every 4 wk until a disease flare, or up to Wk 100. The primary endpoint was time to flare in ERA and JPsA pts. The juvenile spondyloarthritis disease activity Index (JSpADA) is a disease activity assessment tool that contains 8 items to measure axial and peripheral disease activity.3 Evaluation of axial and peripheral manifestations at the end of TP1 and TP2 in pts who experienced these symptoms at BL included modified Schober test (lumbar flexion), inflammatory back pain, FABER (Flexion, ABduction, External Rotation) test, JIA-ACR responses, Juvenile Arthritis Disease Activity Score (JADAS)-27, and resolution of enthesitis and dactylitis for peripheral disease. These outcomes were also used to assess JIA disease course at the end of TP2.

Results

A total of 52/86 (60.5%) pts with ERA were enrolled in the OL period TP1 (mean age, 13.7 years; male, 78.8%). In total, 51/52 (98.1%) pts completed TP1 and 41/44 (93.2%) completed TP2. At BL, mean JADAS-27 was 14.8, mean JSpADA index was 3.9, mean enthesitis and dactylitis counts were 2.7 and 0.4, respectively, mean number of active joints was 6.2 and of mean joints with limited range of motion 4.9. The relative risk reduction of experiencing a disease flare in TP2 was 55% (HR 0.45, 95% CI: 0.16–1.28, p=0.075) in ERA pts (Figure 1). The overall axial and peripheral disease symptoms improved over time and are presented in the Table 1. At the end of TP1, 84.6% (44/52) of pts achieved JIA-ACR 30 and 65.4% (34/52) achieved JIA-ACR 70. Clinically relevant reduction of functional ability as assessed by Childhood Health Assessment Questionnaire (CHAQ) also occurred (see Table 1).

Table 1.

Resolution of axial and peripheral disease symptoms and JIA ACR responses at the end of TP1 and 2

Clinical response, mean (SD) change from BL (unless otherwise stated)TP1-Wk 12End of TP2*SEC (N=52)SEC (N=22)PBO (N=22)JSpADA index−2.4 (1.7)−2.7 (1.7)−2.3 (2.1)JSpADA Schöber, %58.3100.0100.0Inflammatory back pain, %77.8100.050.0FABER test, %52.6100.083.3Clinical sacroiliitis, %53.3100.050.0Enthesitis−2.2 (1.9)−2.5 (2.1)−1.3 (1.8)Dactylitis−0.2 (0.8)−0.2 (1)−0.1 (0.4)JIA ACR30, %84.690.968.2JIA ACR50, %78.881.868.2JIA ACR70, %65.468.254.5JIA ACR90, %32.745.550.0JIA ACR100, %26.936.445.5Inactive disease, %38.550.050.0CHAQ−0.5 (0.5)−0.6 (0.7)−0.4 (0.5)CRP, median (SD) change from BL−1.8 (38.7)−5.8 (38.3)0 (35.9)JADAS-27−9.6 (7.5)−11.0 (8.9)−7.6 (8.9)Resolution of enthesitis#, %72.378.683.3Resolution of dactylitis#, %5066.70

*End of TP2 is based on individual pts’ last visit at TP2. #At BL, in TP1, enthesitis (n= 46); dactylitis (n=5). In TP2, no. of pts who had presence at BL and showed complete resolution at the end of TP2: enthesitis, SEC 14, PBO 18; dactylitis, SEC 3, PBO, 0. CRP, C-reactive protein

Conclusion

In pts with ERA, SEC demonstrated longer time to disease flare vs PBO and exhibited rapid and sustained improvement of axial and peripheral manifestations up to Wk 104.

References

[1]Pagnini I, et al. Front Med 2021;8:6673052.

[2]Brunner H, et al. Arthritis Rheumatol 2021;73 (suppl 10).

[3]Weiss PF, et al. Arthritis Care Res 2014;66:1775-82.

Disclosure of Interests

Nicolino Ruperto Speakers bureau: Eli Lilly, GlaxoSmith and Kline, Pfizer, SOBI and UCB, Paid instructor for: Eli Lilly and Pfizer, Consultant of: Ablynx, Amgen, Astrazeneca-Medimmune, Aurinia, Bayer, Bristol Myers and Squibb, Cambridge Healthcare Research (CHR), Celegene, Domain therapeutic, Eli Lilly, EMD Serono, GlaxoSmith and Kline, Idorsia, Janssen, Novartis, Pfizer, SOBI and UCB, Grant/research support from: Bristol Myers and Squibb, Eli Lilly, F Hoffmann-La Roche, Novartis, Pfizer and SOBI, Elena Chertok: None declared, Joke Dehoorne Speakers bureau: Abbvie, Roche, Consultant of: Abbvie, Roche, Pfizer, Grant/research support from: Abbvie, Roche, Gerd Horneff Speakers bureau: Novartis, Pfizer, Janssen, Grant/research support from: Pfizer, Novartis, Roche, MSD, Tilmann Kallinich Speakers bureau: Roche, Ingrid Louw Speakers bureau: Pfizer, Abbvie, BMS, Consultant of: Pfizer, Abbvie, Janssen, Amgen and Cipla, Sandrine Compeyrot-Lacassagne: None declared, Bernard Lauwerys Employee of: UCB Pharma, Neil Martin: None declared, Katherine Marzan Grant/research support from: Novartis, Sanofi, William Knibbe Speakers bureau: Novartis, Amgen, UCB, Abbvie, Ruvie Martin Shareholder of: Novartis, Employee of: Novartis, Xuan Zhu Shareholder of: Novartis, Employee of: Novartis, sarah whelan Shareholder of: Novartis, Employee of: Novartis, Luminita Pricop Shareholder of: Novartis, Employee of: Novartis, Alberto Martini Speakers bureau: Aurinia, Bristol Myers and Squibb, Eli Lilly, EMD, Janssen, Pfizer, Roche and Serono, Consultant of: Aurinia, Bristol Myers and Squibb, Eli Lilly and EMD, Daniel J Lovell Consultant of: Astra Zeneca, Boehringer Ingelheim, GSK, Hoffman LaRoche, Novartis, UBC, Grant/research support from: Astra Zeneca, Boehringer Ingelheim, GSK, Hoffman LaRoche, Novartis, UBC, Hermine Brunner Consultant of: Novartis, Grant/research support from: Novartis

POS0739 THE RENAL ACTIVITY INDEX FOR LUPUS (RAIL) DIFFERENTIATES ACTIVE AND INACTIVE NEPHRITIS IN ADULT PATIENTS WITH SYSTEMIC LUPUS ERYTHEMATOSUS (SLE)

Background

Lupus nephritis (LN) confers a poor prognosis, with lack of effective laboratory tests to diagnose and evaluate therapies. We have demonstrated that the RAIL score, based on a set of six urinary biomarkers (NGAL, KIM-1, MCP-1, adiponectin, hemopexin, ceruloplasmin) is sensitive and specific in adult patients with active LN, using renal biopsy as reference.1,2 RAIL has been shown in the pediatric population to be effective in distinguishing inactive vs active LN with no effect from mycophenolate mofetil (MMF) treatment. A comparable study has not been conducted in an adult population.

Objectives

To assess the ability of RAIL to discriminate patients with active LN vs active non-renal SLE and to evaluate if RAIL performance varies by MMF treatment using urine samples from adult LN patients.

Methods

Urine samples were obtained at baseline in two clinical trials: a phase 2 study in adult patients with biopsy-proven active Class III and IV LN (NCT02547922) and a subset of patients from the phase 3 trial in adults with active non-renal SLE (NCT02446912) who had baseline renal BILAG scores C, D, or E. RAIL biomarkers were assayed using single-plex assays. Patient demographics and clinical characteristics were compared between studies. Wilcoxon rank sum test was performed comparing the urinary biomarkers between the two studies and RAIL score was then calculated. Receiver operating characteristic (ROC) analyses were conducted assessing the ability for RAIL scores to distinguish patients with renal activity and involvement.

Results

Comparison of the patient demographic, clinical characteristics, and biomarkers is in the Table 1. Wilcoxon rank sum test showed the six urinary biomarkers were significantly different between two groups of patients as demonstrated (Table 1). Each of the RAIL biomarker concentrations and the creatinine-adjusted median score were higher in the active LN group than the SLE group (P<0.001). ROC analyses including RAIL score showed an area under the ROC curve of 0.8 (Figure 1), with odds ratio of log-transformed RAIL 2.027 (95% CI [1.587, 2.589]). There were no significant interactions between RAIL and MMF. RAIL remained significant after adjusting for estimated glomerular filtration rate (eGFR), which was not statistically significant.

Table 1.

Study Demographics and Biomarkers

VariablesLN study (N=131)SLE study (N=59)Observed NObserved Median (IQR) or %Observed NObserved Median (IQR) or %DemographicsAge13134 (25, 42)5936 (28, 44)Sex, Female10983.21%5593.22%Race, White5642.75%4576.27%Ethnicity, Hispanic or Latino6146.56%915.25%OCS use, yes12797.69%5796.61%MMF use, yes9572.52%2135.59%Spot UPCR (mg/mg)1282.13 (1.22, 4.04)591.11 (0.55, 2.61)eGFR13091.8 (63.1, 125)5998.06 (81.91, 116.54)Non-renal SLEDAI-2K score1304 (4, 6)5912 (9, 13)Renal SLEDAI-2K score1304 (4, 8)590 (0, 0)BiomarkersNGAL (ng/mL)12833.33 (17.55, 56.7)5819.47 (11.37, 42.05)MCP-1 (pg/mL)128658.24 (271.58, 1049.95)58275.62 (106.09, 481.99)Ceruloplasmin (ng/mL)12893.55 (44.5, 311.25)5847.2 (13.05, 231.25)Adiponectin (ng/mL)12842.45 (16.71, 139.64)589.33 (3.35, 25.51)Hemopexin (ng/mL)1281876.8 (745.07, 4743.4)58513.4 (236.36, 1388.74)KIM-1 (pg/mL)1281673.5 (772.5, 2767)58864 (394, 1480)Creatinine (mg/mL)1280.7 (0.46, 1.3)580.99 (0.46, 1.74)Adult RAIL score (creatinine adjusted)1285.59 (4.31, 6.47)583.57 (2.78, 4.47)

eGFR, estimated glomerular filtration rate; IQR, interquartile range; KIM, kidney injury molecule; LN, lupus nephritis; MCP, monocyte chemotactic protein; MMF, mycophenolate mofetil; NGAL, neutrophil gelatinase-associated lipocalin; OCS, oral corticosteroid; SLEDAI-2K, SLE Disease Activity Index 2000; UPCR, urine protein/creatinine ratio.

Conclusion

The analyses performed suggest that creatinine-corrected RAIL discriminates between active LN and non-renal adult SLE, with RAIL scores not influenced by MMF use.

References

[1]Brunner HI. Arthritis Care Res (Hoboken). 2016;68:1003–11.

[2]Gulati G. Lupus. 2017;26:927–36.

Acknowledgements

Writing assistance by Kelly M. Hunter, PhD (Fishawack). This study was sponsored by AstraZeneca.

Disclosure of Interests

Ellen Cody: None declared, Hermine Brunner Speakers bureau: Novartis, Pfizer, GSK, Consultant of: AbbVie, Astra Zeneca-Medimmune, Biogen, Boehringer, Bristol Myers Squibb, Celgene, Lilly,EMD Serono, Idorsia, Cerocor, Janssen, GSK, F. Hoffmann-La Roche, Merck, Novartis, R-Pharm, Sanofi, Grant/research support from: Pfizer, Bin Huang: None declared, Tingting Qiu: None declared, Prasad Devarajan Speakers bureau: Reata, Alnylam, Dicerna, Consultant of: BioPorto Inc, Madhu Ramaswamy Shareholder of: AstraZeneca, Employee of: AstraZeneca, Dominic Sinibaldi Shareholder of: AstraZeneca, Employee of: AstraZeneca, Philip Z Brohawn Shareholder of: AstraZeneca, Employee of: AstraZeneca, Jacob Knagenhjelm Shareholder of: AstraZeneca, Employee of: AstraZeneca, Frederick Jones Shareholder of: AstraZeneca, Employee of: AstraZeneca, Raj Tummala Shareholder of: AstraZeneca, Employee of: AstraZeneca, Catharina Lindholm Employee of: AstraZeneca, Wendy White Shareholder of: AstraZeneca, Employee of: AstraZeneca

LB0002 BARICITINIB IN JUVENILE IDIOPATHIC ARTHRITIS: A PHASE 3, DOUBLE-BLIND, PLACEBO-CONTROLLED, WITHDRAWAL, EFFICACY AND SAFETY STUDY

Background

Baricitinib is a JAK1/2 selective inhibitor approved for the treatment of rheumatoid arthritis. Juvenile idiopathic arthritis (JIA) is a group of diseases characterized by immune mediated chronic arthritis which often requires treatment with conventional synthetic or biologic disease-modifying antirheumatic drugs (cs or b-DMARDs).

Objectives

To investigate baricitinib efficacy and safety in pediatric patients with JIA and an inadequate response to cs or b-DMARDs.

Methods

This Phase 3 multicenter, double-blind, withdrawal, efficacy, and safety study, enrolled patients (pts) age 2 to <18 years with extended oligo- or poly-articular JIA, ERA, or JPsA, per ILAR criteria, and an inadequate response to ≥1 cs and/or b-DMARDs (NCT03773978). There were 3 periods: a 2-week (wk) pharmacokinetic/safety assessment (PKS), a 12-wk open-label lead-in (OLLI), and an up-to 32-wk double-blind withdrawal (DBW). Dosage and safety were confirmed in the PKS and then pts, including those from the PKS, enrolled in the OLLI, receiving age-based, oral, once daily doses of baricitinib. Pts with a JIA-ACR30 response at wk12, end of OLLI, entered the DBW to be randomized 1:1 to continued baricitinib or newly started placebo (PBO) and remained until flare or up to wk32. Primary endpoint was time to flare during the DBW. Secondary endpoints included JIA-ACR30/50/70/90 response rates at wk12, and proportion of pts with a flare during the DBW. Survival curves were estimated using the Kaplan-Meier method.

Results

Of 220 pts enrolled, 29 participated in the PKS, 219 entered the OLLI, and 163 entered the DBW. The JIA-ACR30/50/70/90 response at wk12 was 76.3%/63.5%/46.1%/20.1%, respectively. During the DBW, time of flare was significantly shorter with PBO vs baricitinib (hazard ratio 0.24 [95% CI 0.13,0.45], p<0.001; Figure 1). The proportion of pts with a flare during the DBW was significantly lower for baricitinib vs PBO (14 (17.1%) vs. 41 (50.6%), p<0.001). In the PKS and OLLI periods, 126 (57.3%) pts reported ≥1 treatment emergent adverse event (TEAE), while 6 (2.7%) reported ≥1 serious adverse event (SAE); Table 1. In the DBW, 38 (46.9%) and 54 (65.9%) pts reported ≥1 TEAE for PBO and baricitinib, respectively, whereas those with ≥1 SAE were 3 (3.7%) and 4 (4.9%). The mean wks of exposure was higher in the baricitinib vs PBO group during DBW (26.34 vs 18.91) due to study design. There were no deaths, cardiovascular events or uveitis and 1 case of herpes zoster. Table 1.

Conclusion

Baricitinib significantly reduced time to and frequency of JIA flares in pts with JIA versus PBO, and improved JIA-ACR scores in the majority of pts within 12wks. Safety findings were consistent with the known safety profile in adult rheumatoid arthritis indications. These findings support baricitinib as a treatment for signs and symptoms of JIA with an inadequate response to cs or b-DMARDs.

References

[1]Giannini EH, et. al. Preliminary definition of improvement in juvenile arthritis. Arthritis Rheum 1997; 40: 1202-1209.

[2]Brunner HI, et. al. Preliminary definition of disease flare in juvenile rheumatoid arthritis. J Rheumatol 2002; 29(5):1058-64.

Disclosure of Interests

Athimalaipet Ramanan Consultant of: Eli Lilly and Company, Abbvie, Roche, UCB, Novartis, Pfizer, and Sobi, Grant/research support from: Eli Lilly and Company, Pierre Quartier Consultant of: Eli Lilly and Company, Abbvie, Amgen, BMS, Novartis, Novimmune, Pfizer, Swedish Orphan Biovitrum, SANOFI, Speakers bureau: Abbvie, Novartis, Pfizer, Swedish Orphan Biovitrum, Nami Okamoto Consultant of: Swedish Orphan Biovitrum, Eli Lilly and Company, Speakers bureau: AbbVie, Eli Lilly and Company, Sanofi, Asahi Kasei Medical, Mitsubishi Tanabe Pharma, Bristol Myers Squibb, Pfizer Japan, Ayumi Pharma, Eisai, Torii Pharma, GlaxoSmithKline, Kyorin Pharma, Novartis, Chugai Pharmaceutical, Teijin Pharma, Gabriella Meszaros Employee of: Eli Lilly and Company, Joana Araujo Employee of: Eli Lilly and Company, Zhongkai Wang Employee of: Eli Lilly and Company, Ran Liao Employee of: Eli Lilly and Company, Brenda Crowe Employee of: Eli Lilly and Company, Xin Zhang Employee of: Eli Lilly and Company, Rodney Decker Employee of: Eli Lilly and Company, Stuart Keller Employee of: Eli Lilly and Company, Hermine Brunner Consultant of: AbbVie, Astra Zeneca-Medimmune, Biogen, Boehringer, Bristol-Myers Squibb, Celgene, Eli Lilly, EMD Serono, Idorsia, Cerocor, Janssen, GlaxoSmithKline, F. Hoffmann-La Roche, Merck, Novartis, R-Pharm, Sanofi, Speakers bureau: Novartis, Pfizer, GlaxoSmithKline, Nicolino Ruperto Consultant of: Eli Lilly and Company, Ablynx, Amgen, Astrazeneca-Medimmune, Aurinia, Bayer, Bristol Myers and Squibb, Cambridge Healthcare Research (CHR), Celgene, Domain therapeutic, Eli-Lilly, EMD Serono, Glaxo Smith and Kline, Idorsia, Janssen, Novartis, Pfizer, Sobi, UCB, Speakers bureau: Eli Lilly and Company, Glaxo Smith and Kline, Pfizer, Sobi, UCB

POS1303 METHOTREXATE RESPONSE IN PEDIATRIC NON-INFECTIOUS UVEITIS

Background

Children with chronic non-infectious uveitis (NIU) are at risk for sight-threatening complications. Methotrexate (MTX) is the preferred first-line systemic treatment. Initial therapeutic response takes 3-6 months to achieve NIU control, leading to prolonged glucocorticoid use. Moreover, at least 50-70% of children fail to fully respond and may accrue ocular damage while awaiting MTX response.

Objectives

To identify features of children with NIU that are associated with MTX failure.

Methods

We included children who started MTX monotherapy for NIU. We collected demographics, NIU features (type, location, & complications), ANA status, and clinical examination. We characterized children as MTX responders or non-responders. MTX responders are those whose NIU was controlled, defined by: 1) inactive graded by SUN criteria, 2) absence of new or worsening complications, and 3) requirement for ≤2 drops of prednisolone acetate and no oral glucocorticoids.

Results

Of 47 NIU children, 68% were MTX non-responders (Table 1), having a longer duration of NIU (Odds Ratio [OR]=1.28, [CI=1.03-1.8], p =0.023) and developing more ocular complications (OR=1.95 [CI=1.23-3.38], p=0.017), (ROC Area Under the Curve = 0.85). MTX non-responders were more likely to have anterior and/or posterior synechiae (p = 0.001), cataracts (p=0.015), and ocular hypertension (p=0.039). Treatment included adalimumab: 27, infliximab: 14, tocilizumab: 5, golimumab: 4, etanercept: 3, and abatacept: 2.

Table 1.

Comparison of children with NIU based on MTX response.

Responders n=15Non-responders n=32Caucasian14 (93)27 (84)Hispanic or Latino0 (0)3 (9)Female12 (80)23 (72)Age of NIU onset, yrs, median (IQR)4.3 (2.9 – 12.3)4.6 (2.8 - 7.0)Duration of NIU, yrs, median, (IQR)4.1 (2.6 – 5.3)8.2 (4.7 - 11.3)JIA-NIU10 (67)25 (78)Idiopathic CAU2 (13)3 (9)Other3 (20)4 (12)Bilateral disease12 (80)23 (72)Anterior12 (86)29 (91)Presenting BCVA (LogMAR) worst eye, median (IQR)0.2 (0.1 – 0.3)0.1 (0.0 - 0.2)Average # of total complications/person, median (IQR)1 (0 – 2)2.5 (1.0 – 5.5)ANA positive10 (67)26 (81)Earliest ESR8 (6– 18)12 (8 - 18)Earliest Vitamin D32 (26 – 35)31 (23 - 35)Time on MTX, months, median (IQR)35 (19 - 64)19 (7 - 74)Time from systemic or NIU onset to MTX, yrs, median (IQR)0.3 (0.1 – 0.5)0.2 (0.0 - 0.8)MTX PO6 (40)19 (59)MTX SC13 (87)31 (97)

We performed a sub analysis of children with idiopathic chronic anterior NIU (CAU) and JIA-associated NIU that included children who failed MTX due to intolerance/toxicity (Figure 1). Using Cox proportional hazard regression, 8 idiopathic CAU failed MTX earlier than 38 JIA-associated NIU (HR 2.77, [CI-=1.06-7.27], p=0.039). Results were similar with the inclusion of other types of NIU (p=0.088) (e.g., HLA-B27, non-anterior idiopathic or with systemic disease).

Figure 1.

Kaplan-Meier curve showing freedom from TNFi (mos) stratified by diagnosis

Conclusion

Two out of three children with NIU fail initial MTX monotherapy, exposing them to increased accrual of ocular complications prior to biologic starts. The risk for delay in starting tumor necrosis factor α inhibitors (TNFi) seems higher with CAU. Future studies will examine risk factors that predict MTX response in NIU.

References

[1]McCracken C, Angeles-Han ST, et.al. Timing of infliximab and adalimumab initiation despite methotrexate in children with chronic non-infectious anterior uveitis. Eye (Lond). 2019;33(4):629-39.

[2]Henderson LA, Angeles-Han ST, et.al., Medication use in juvenile uveitis patients enrolled in the Childhood Arthritis and Rheumatology Research Alliance Registry. Pediatr Rheumatol Online J. 2016;14(1):9.

[3]Cooper A, et.al., Failure of methotrexate monotherapy and subsequent response to tumor necrosis factor inhibitors in pediatric non-infectious uveitis (abstract). Arthritis Rheumatol. 2020:72 (suppl 4).

Disclosure of Interests

Sheila Angeles-Han: None declared, Amy Cassedy: None declared, Theresa Hennard: None declared, Mekibib Altaye: None declared, Hermine Brunner Consultant of: Dr. Brunner’s affiliation Cincinnati Children’s Hospital Medical Center has received consulting fees or other remuneration from AstraZeneca, Boehringer Ingelheim, GSK, Roche, Novartis, Pfizer Inc, Takeda, and UBC for the work of Dr. Brunner. Dr. Brunner is a DSMB member for Janssen Pharmaceutical’s trial of ustekinumab pediatric Crohn and Ulcerative colitis., Grant/research support from: Dr. Brunner’s affiliation Cincinnati Children’s Hospital Medical Center has received research grants from BMS, Janssen, Novartis, Pfizer Inc, Roche, and UBC., Eniolami Dosunmu: None declared, Alexei Grom: None declared, Michael Henrickson: None declared, Jennifer Huggins: None declared, Sarah Lopper: None declared, Daniel J Lovell Consultant of: AstraZeneca, Boehringer Ingelheim, GSK, Roche, Novartis, Pfizer Inc, Takeda, and UBC, Grant/research support from: BMS, Janssen, Novartis, Pfizer Inc, Roche, and UBC, Robert Sisk Consultant of: AGTC, Gyroscope, and Leica, Tracy Ting: None declared, Adam Kaufman Consultant of: Consultant for Alcon, Bausch & Lomb, and 1800contacts, not related or relevant to study content., Virginia Utz: None declared

POS0340 PREDICTORS OF CLINICAL RESPONSE TO ABATACEPT IN CHILDREN WITH POLYARTICULAR JUVENILE IDIOPATHIC ARTHRITIS

Background

For children with polyarticular juvenile idiopathic arthritis (pJIA) and inadequate response or intolerance to initial treatment with MTX, treatment options include abatacept.1 Abatacept, a selective T-cell co-stimulation modulator, has a distinct mechanism of action from other current treatments for rheumatic diseases,2 and factors predicting clinical response can help determine optimal treatment strategy. Two phase 3 studies demonstrated the efficacy and safety of IV and SC abatacept in patients with pJIA and an inadequate response to other DMARDs.2,3

Objectives

To determine baseline and post-baseline factors that may predict a clinical response in children and adolescents with pJIA treated with abatacept for 2 years.

Methods

Baseline demographic and disease characteristics and post-baseline factors (50% and 70% improvement in ACR criteria [ACR50, ACR70] at days 57 and 85) were analyzed using data from 2 phase 3 studies of abatacept in patients with JIA aged 2–17 years (SC administration) and 6–17 years (IV administration). Efficacy endpoints were Juvenile Arthritis Disease Activity Score in 10 joints based on CRP (JADAS10-CRP) inactive disease (ID; score of ≤ 2.7),4 and remission, defined as 6 consecutive months of post-baseline JADAS10-CRP ID. Data were analyzed over the entire 2-year study period. The earliest time point at which patients achieved these outcomes was reported. The aforementioned study factors were subjected to a time-to-event analysis, including Cox proportional hazards univariate regression analysis and Cox proportional hazards multivariate regression analysis using stepwise regression; results of the multivariate analysis are reported. Kaplan–Meier analysis was used to estimate time to achieve clinical response. Receiver operating characteristic curves were used to determine threshold values for continuous variables.

Results

Overall, 347 patients were included in the analysis (SC, n = 219; IV, n = 128; 73.8% female; mean [SD] age, 11.3 [4.0] years). Following abatacept treatment, both time to JADAS10-CRP ID and time to JADAS10-CRP remission were predicted (nominal P ≤ 0.05) by age (≤ 11 years: hazard ratio [HR], 1.52 [95% CI, 1.14–2.02] and ≤ 10 years: HR, 1.73 [95% CI, 1.20–2.48], respectively), high-sensitivity CRP (hsCRP; ≤ 0.6 mg/dL: HR, 1.67 [95% CI, 1.22–2.28] and ≤ 0.21 mg/dL: HR, 1.67 [95% CI, 1.15–2.42], respectively), Parent/Patient Global Assessment of well-being (≤ 35.86: HR, 1.88 [95% CI, 1.41–2.51] and ≤ 43.16: HR, 2.05 [95% CI, 1.35–3.10], respectively), and Childhood HAQ-DI (CHAQ-DI; ≤ 1.63: HR, 2.23 [95% CI, 1.47–3.39] and ≤ 0.75: HR, 1.84 [95% CI, 1.24–2.73], respectively) (remission data shown in Figure 1). Disease duration ≤ 2 years from baseline (HR, 1.66 [95% CI, 1.25–2.21]) and SC route of administration (HR, 2.05 [95% CI, 1.45–2.91]) also predicted ID. Among the post-baseline factors, ACR50 at days 57 and 85 predicted both ID (HR, 1.57 [95% CI, 1.04–2.36] and HR, 1.88 [95% CI, 1.41–2.51], respectively) and remission (HR, 1.96 [95% CI, 1.11–3.45] and HR, 3.05 [95% CI, 1.47–6.34], respectively); ACR70 at day 57 also predicted ID (data not shown). Patients with predictive factors for age, hsCRP, Parent/Patient Global Assessment of well-being, and CHAQ-DI, and with lower disease activity achieved ID and/or remission earlier than patients with high disease activity.

Conclusion

We identified baseline and post-baseline factors that predicted JADAS10-CRP ID and remission in patients with pJIA treated with abatacept for 2 years. Screening of abatacept-treated patients with pJIA for such factors may help predict earlier achievement of ID and/or remission.

References

[1]Ringold S, et al. Arthritis Rheumatol 2019;71:846–63.

[2]Brunner HI, et al. Arthritis Rheumatol 2018;70:1144–54.

[3]Ruperto N, et al. Lancet 2008;372:383–91.

[4]Trincianti C, et al. Arthritis Rheumatol 2021;73:1966–75.

Acknowledgements

This study was sponsored by Bristol Myers Squibb. Writing and editorial assistance were provided by Candice Judith Dcosta, MSc, of Caudex, funded by Bristol Myers Squibb. We would like to acknowledge Mara Becker, Duke Clinical Research Institute, Durham, NC, USA, for her contribution to the study analysis.

Disclosure of Interests

Nicolino Ruperto Speakers bureau: Honoraria for consultancies or speaker bureaus from the following pharmaceutical companies in the past 3 years: 2 Bridge, Amgen, AstraZeneca, Aurinia, Bayer, Brystol Myers Squibb, Cambridge Healthcare Research, Celgene, Domain Therapeutic, Eli Lilly, EMD Serono, GlaxoSmithKline, Idorsia, inMed, Janssen, Novartis, Pfizer, Sobi, UCB, Consultant of: Honoraria for consultancies or speaker bureaus from the following pharmaceutical companies in the past 3 years: 2 Bridge, Amgen, AstraZeneca, Aurinia, Bayer, Brystol Myers Squibb, Cambridge Healthcare Research, Celgene, Domain Therapeutic, Eli Lilly, EMD Serono, GlaxoSmithKline, Idorsia, inMed, Janssen, Novartis, Pfizer, Sobi, UCB, Hermine Brunner Speakers bureau: GlaxoSmithKline, Novartis, Pfizer, Consultant of: AbbVie, AstraZeneca-Medimmune, Biogen, Boehringer, Bristol Myers Squibb, Celgene, Cerocor, Eli Lilly, EMD Serono, F. Hoffmann-La Roche, GlaxoSmithKline, Idorsia, Janssen, Merck, Novartis, R-Pharm, Sanofi, Grant/research support from: The Cincinnati Children’s Hospital, where HIB works as a full-time public employee, has received contributions from the following industries in the past 3 years: Bristol Myers Squibb, F. Hoffmann-La Roche, Janssen, Novartis, and Pfizer. This funding has been reinvested for the research activities of the hospital in a fully independent manner, without any commitment to third parties, Alberto Berman Grant/research support from: AbbVie, Amgen, Bristol Myers Squibb, Lilly, Novartis, Pfizer, Roche, Francisco Avila Zapata: None declared, Gerd Horneff Speakers bureau: AbbVie, Chugai, Janssen, Novartis, Pfizer, Grant/research support from: AbbVie, Chugai, MSD, Novartis, Pfizer, Roche, Linda Wagner-Weiner Grant/research support from: Abbott, Bristol Myers Squibb, Merck, Pfizer, UCB, Alexander Belot Speakers bureau: Chugai, GlaxoSmithKline, Novartis, Roche (punctual scientific intervention), Grant/research support from: Boehringer Ingelheim, Merck (joint research project), Ruben Burgos-Vargas: None declared, Maria Luz Gámir Gámir: None declared, Claudia Goldenstein-Schainberg Speakers bureau: AbbVie, Janssen, Novartis, Consultant of: AbbVie, Janssen, Novartis, Maria T. Terreri: None declared, Margarita Askelson Consultant of: Acerta Pharma, Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Robert Wong Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Alberto Martini Consultant of: AbbVie, Eli Lilly, EMD Serono, Idorsia, Janssen, Novartis, Pfizer, Daniel J Lovell Consultant of: AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Hoffman LaRoche, Novartis, UBC (all contracts with employer, CCHMC), Grant/research support from: Bristol Myers Squibb, Janssen, Pfizer, Roche (all contracts with employer, CCHMC); NIH grants: NIAMS, NICHD

Brunner syndrome associated MAOA mutations result in NMDAR hyperfunction and increased network activity in human dopaminergic neurons

Monoamine neurotransmitter abundance affects motor control, emotion, and cognitive function and is regulated by monoamine oxidases. Among these, Monoamine oxidase A (MAOA) catalyzes the degradation of dopamine, norepinephrine, and serotonin into their inactive metabolites. Loss-of-function mutations in the X-linked MAOA gene have been associated with Brunner syndrome, which is characterized by various forms of impulsivity, maladaptive externalizing behavior, and mild intellectual disability. Impaired MAOA activity in individuals with Brunner syndrome results in bioamine aberration, but it is currently unknown how this affects neuronal function, specifically in dopaminergic (DA) neurons. Here we generated human induced pluripotent stem cell (hiPSC)-derived DA neurons from three individuals with Brunner syndrome carrying different mutations and characterized neuronal properties at the single cell and neuronal network level in vitro. DA neurons of Brunner syndrome patients showed reduced synaptic density but exhibited hyperactive network activity. Intrinsic functional properties and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR)-mediated synaptic transmission were not affected in DA neurons of individuals with Brunner syndrome. Instead, we show that the neuronal network hyperactivity is mediated by upregulation of the GRIN2A and GRIN2B subunits of the N-methyl-d-aspartate receptor (NMDAR), resulting in increased NMDAR-mediated currents. By correcting a MAOA missense mutation with CRISPR/Cas9 genome editing we normalized GRIN2A and GRIN2B expression, NMDAR function and neuronal population activity to control levels. Our data suggest that MAOA mutations in Brunner syndrome increase the activity of dopaminergic neurons through upregulation of NMDAR function, which may contribute to the etiology of Brunner syndrome associated phenotypes.

Esteki M. P–381 Deciphering the genetic cause of recurrent and sporadic pregnancy loss

Study question

To investigate the prevalence and effect of (mosaic) de novo genomic aberrations in recurrent pregnancy loss (RPL) and sporadic abortion (SA).

Summary answer

Prevalence of maternal uniparental disomies (UPDs) was high in both cohorts. While chromosomal UPDs were found in both cohorts, genome wide UPDs were RPL specific.

What is known already

Spontaneous abortion occurs in 10–15% of clinically recognized pregnancies and recurrent pregnancy loss in 1–3%. SA and RPL are associated with reduced quality of life. Multiple factors contribute to SA and RPL, such as uterine malformations and parental/fetal chromosomal abnormalities. However, in ∼60% of SA and RPL the cause remains unknown. UPD is defined as the presence of two homologues chromosomes originating from a single parent. This phenomenon can lead to imprinting disorders that are characterised by clinical features affecting growth, development and metabolism in liveborn offspring. However, it could also be responsible for pregnancy loss.

Study design, size, duration

We recruited 32 families with pregnancy loss (n = 16 RPL cohort, n = 16 SA cohort) with no known genetic predispositions and normal karyotyping results in both parents and the fetus. Average maternal age was 28.68 years (SD = 5.43), paternal age 30.3 years (SD = 5.53), and the gestational age at pregnancy loss was 8.65 weeks (SD = 2.47). The average number of miscarriages in the RPL group was 3.57 (SD = 0.84). We profiled the genomic landscape of both cohorts using SNP typing.

Participants/materials, setting, methods

We isolated DNA from blood of both parents and the placental tissues from the miscarried products of conception. The placenta tissues were sampled from two distinct extraembryonic and embryonic germ layers, the extraembryonic mesoderm and the chorionic villi cytotrophoblast. Subsequently, we performed SNP-genotyping using Illumina’s Global-Screening Array–24 v2.0 BeadChips and applied haplarithmisis to delineate allelic architecture of fetal tissues of both cohorts. This allowed us to detect large de novo copy-number and -neutral (&gt;10kb) changes.

Main results and the role of chance

In this pilot study, we have analyzed 132 DNA samples (n = 32 families), of which 16 families were in the RPL cohort and 16 in the SA cohort. Within the RPL cohort, we found: one family with mosaic genome wide hexaploidy both in the extraembryonic mesoderm and chorionic villi, one family with a non-mosaic genome wide hetero UPD of the chorionic villi tissue, one family with a mosaic UPD of chromosome 14 in both tissues and tetraploidy exclusively in the chorionic villi, one family with a mosaic UPD of chromosome 16 in both tissues, one family with a mosaic UPD of chromosome 6 in both tissues, and another family with a mosaic UPD of chromosome 5 in the extraembryonic mesoderm. Within the SA group, one family showed a UPD of chromosome 7 and another family showed a segmental UPD of chromosome 5 in both tissues. Strikingly, all the UPDs found in this study were maternal in origin.

Limitations, reasons for caution

The main limitation of this study is the resolution of detecting copy-neutral and copy-number variations, which is an inherent limiting factor of SNP-array technology. In addition, in the sample in which we observed non-mosaic genome wide UPD, maternal contamination is likely that can be investigated by other technologies.

Wider implications of the findings: Multiple genome wide UPDs are found in the RPL group but none in the SA group, indicating an association between genome wide mosaic UPD and RPL. These findings could lead to a better understanding of causative factors for SA and RPL and the need for a SNP-based non-invasive prenatal testing.

Trial registration number

Not applicable

O-074 No methylome differences observed in IVF children born after embryo culture in different culture media

Study question

Does human embryo culture in different IVF culture media lead to DNA methylation alterations in IVF offspring?

Summary answer

Genome-wide analyses identified no significant DNA methylation differences between culture medium groups in IVF children (neonates or 9-year olds) from two culture media studies.

What is known already

During in vitro fertilisation (IVF) treatments, embryos undergo preimplantation development in an artificial environment, while concurrently undergoing epigenetic reprogramming. Adversity during this period, such as peri-conception calorie restriction, has been linked to persistent DNA methylation aberrations and increased risk of cardiometabolic disease. Early environmental adversity is suspected in IVF offspring as they are born with lower birthweights and show increased risk of cardiometabolic dysfunction in adulthood as compared to their naturally-conceived counterparts. This is further supported by the observation from two culture media trials (MEDIUM0 and MEDIUM1) that embryo culture in different culture media leads to differences in birthweight.

Study design, size, duration

We recruited singleton offspring from two IVF culture media trials. The MEDIUM0 study, a pseudo-randomized trial comparing G3 (Vitrolife) and K-SICM (Cook), was conducted from 2003-2006. At the 9-year follow-up, saliva was collected (cohort-A). The MEDIUM1 study, a multi-center randomized controlled trial comparing G5 (Vitrolife) and HTF (Lonza), was conducted from 2010-2012. Umbilical cord blood (UCB) was collected at birth (cohort-B).

Participants/materials, setting, methods

DNA methylation was analysed in 120 saliva samples (65 G3, 55 Cook) and 106 UCB samples (47 HTF, 59 G5) using the Infinium MethylationEPIC array (Illumina). Mixed effects linear models, correcting for (gestational) age, sex, sample composition and batch effects alongside maternal age, pregnancy complications and IVF centre for cohort-B, were implemented at single or aggregated sites. Methylation outliers were defined as values over three interquartile ranges below or above 25th and 75th percentiles respectively.

Main results and the role of chance

111 of the 120 saliva samples (60 G3, 51 Cook) and 105 of the 106 UCB samples (47 HTF, 58 G5) passed our quality control criteria. We filtered sites on sex chromosomes, and based on quality, proximity to single-nucleotide polymorphisms, and proportion of missing values, leaving 650,000-700,000 of the 850,000 sites included on the EPIC array for our analyses. To account for heterogeneity in the cellular composition of our samples we estimated their cell compositions using a reference-based approach. First, we investigated individual CpG sites, finding no differentially methylated sites in either cohort after correction for multiple testing (false discovery rate adjusted p. value threshold &lt; 0.1). Sites were then aggregated into regions based on their allocations to genes, promoters and CpG islands. No differentially methylated regions were identified in either cohort. A targeted analysis of DNA methylation of imprinting genes showed no differentially methylated sites or regions. To examine the contribution of stochastic epigenetic alterations we quantified the number of methylation outliers per sample. Although this revealed a predominance of hypomethylation outliers, there was no difference in the total number or distribution of DNA methylation outliers between the two culture media groups of cohort-A and cohort-B.

Limitations, reasons for caution

This analysis is currently limited by the lack of comparison to a naturally-conceived control group. As such, we cannot yet conclude whether IVF embryo culture, in any medium, is associated with DNA methylation aberrations. Additionally, given the large number of comparisons, we may lack power to detect small differences.

Wider implications of the findings

Although there are disparities in birth weight and childhood growth after embryo culture in different media, we observed no DNA methylation alterations preserved postnatally. Whether DNA methylation of these individuals deviates from that of naturally-conceived individuals will be determined in the near future.

Trial registration number

MEDIUM1: NTR 1979 /NL1866 (Netherlands Trial Registry)

LB0004 EFFICACY AND SAFETY OF SECUKINUMAB IN ENTHESITIS-RELATED ARTHRITIS AND JUVENILE PSORIATIC ARTHRITIS: PRIMARY RESULTS FROM A RANDOMISED, DOUBLE-BLIND, PLACEBO-CONTROLLED, TREATMENT WITHDRAWAL, PHASE 3 STUDY (JUNIPERA)

Background:

Enthesitis-related arthritis (ERA) and juvenile psoriatic arthritis (JPsA) are two ILAR categories of juvenile idiopathic arthritis (JIA) and represent paediatric correlates of axial spondyloarthritis (axSpA) and adult psoriatic arthritis (PsA), respectively.1,2 Secukinumab (SEC) has demonstrated efficacy and safety in adult patients (pts) with PsA, ankylosing spondylitis and non-radiographic axSpA.3-5

Objectives:

Evaluate efficacy and safety of SEC using a flare prevention design in pts with active ERA and JPsA.

Methods:

This 2-yr study consisted of an open-label (OL) s.c. SEC (75/150 mg in pts <50/ ≥50 kg) at baseline (BL), and at Weeks (Wk) 1, 2, 3, 4, 8 and 12 in treatment-period (TP) 1. Responder pts who achieved at least JIA ACR 30 response at Wk 12 were randomised into the double-blinded TP2 to continue SEC or placebo (PBO) q4w until a disease flare, or up to Wk 100. Pts (aged 2 to <18 yrs) classified as ERA or JPsA according to ILAR criteria of ≥6 months duration with active disease were included. Primary endpoint was time to flare in TP2 and key secondary endpoints were JIA ACR 30/50/70/90/100, inactive disease, JADAS, enthesitis count and safety. Analysis of time to flare in TP2 included proportion of disease flare, Kaplan-Meier (KM) estimate of median time to flare in days, hazard ratio (95% CI) from Cox model, and P-value for the Stratified log-rank test. KM estimates of the probability to disease flare by treatment groups in TP2 were plotted against days. Observed data were used in all analyses. Post-hoc analyses using non-responder imputation (NRI) were performed for JIA ACR 30/50/70/90/100 responses.

Results:

86/97 (89%) pts were enrolled in the OL period TP1 (mean age, 13.1 yrs; female, 33.7%; ERA, n=52; JPsA, n=34). At BL, mean JADAS-27 score was 15.1 and enthesitis count was 2.6. At the end of TP1, 90.4% (75/83) of pts achieved JIA ACR 30 and 69.9% (58/83) achieved JIA ACR 70. There were 21 and 10 flares in TP2, respectively in PBO and SEC treated pts with a significantly longer time to flare and 72% risk of flare reduction in SEC treatment vs PBO (HR: 0.28; 95% CI: 0.13–0.63; P<0.001) (Figure 1). JIA ACR responses, disease activity and enthesitis count are reported in Table 1. NRI analyses showed that 87.2%, 83.7%, 67.4%, 38.4% and 24.4% of pts achieved JIA ACR 30/50/70/90/100, respectively. Rates of adverse events (AEs; 91.7% vs 92.1%) and serious AEs (14.6% vs 10.5%) in SEC and PBO groups were comparable in the entire TP. No new safety signals were observed.

Table 1.

Efficacy of secukinumab in Treatment Periods 1 and 2 (Key secondary endpoints)

Efficacy Outcomes, %TP1TP2¥SEC (N=83)^SEC (N=37)PBO (N=37)P-valueJIA ACR 3090.489.264.90.014JIA ACR 5086.778.462.20.152JIA ACR 7069.967.643.20.042JIA ACR 9039.851.440.50.431JIA ACR 10025.343.237.80.745Inactive disease#36.147.237.80.500JADAS-27, mean (SD)15.1 (7.2)14.6 (8.1)13.3 (5.8)NAEnthesitis count, mean change from BL (SD)−1.8 (2.3)−2.1 (2.0)−1.9 (1.2)NA

P-values: Cochran-Mantel-Haenszel test, adjusted for analysis factors: JIA category (ERA/ JPsA) and MTX use at BL

¥The N numbers are values at the end of TP2

^Efficacy outcomes (%) in TP1 calculated in patients with evaluable data at Wk 12 (N=83)

#Inactive disease: Definition adapted from JIA ACR criteria of Wallace et al., 2011. N=36 for SEC at the end of TP2

JADAS, Juvenile Arthritis Disease Activity Score; N, total number of patients in the treatment group; NA, data not available

Figure 1.

Time to flare in Treatment Period 2 (Primary Endpoint)

Conclusion:

In children and adolescents with ERA and JPsA, efficacy of SEC was demonstrated with a significantly longer time to flare vs PBO with sustained improvement of signs and symptoms up to Wk 104 and a favourable safety profile.

References:

[1]Colbert RA. Nat Rev Rheumatol. 2010;6:477–85.

[2]Martini A, et al. J Rheumatol. 2019;46:190–7.

[3]McInnes IB, et al. Lancet. 2015;386:1137–46.

[4]Baeten D, et al. N Engl J Med. 2015;373:2534–48.

[5]Deodhar A, et al. Arthritis Rheumatol. 2021;73:110–20.

Disclosure of Interests:

Nicolino Ruperto Consultant of: Ablynx, Astrazeneca-Medimmune, Bayer, Biogen, Boehringer, Bristol Myers and Squibb, Celgene, Eli-Lilly, EMD Serono, Glaxo Smith and Kline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sinergie, Sobi and UCB, Grant/research support from: BMS, Eli-Lilly, GlaxoSmithKline, F Hoffmann-La Roche, Janssen, Novartis, Pfizer, Sobi, Speakers bureau: Ablynx, Astrazeneca-Medimmune, Bayer, Biogen, Boehringer, Bristol Myers and Squibb, Celgene, Eli-Lilly, EMD Serono, Glaxo Smith and Kline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sinergie, Sobi and UCB, Ivan Foeldvari Consultant of: Novartis, Speakers bureau: Novartis, Ekaterina Alexeeva Grant/research support from: Novartis, Pfizer, Sanofi, MSD, AMGEN, Eli Lilly, Roche, Speakers bureau: Novartis, Pfizer, Sanofi, MSD, AMGEN, Eli Lilly, Roche, NURAY AKTAY AYAZ: None declared, Inmaculada Calvo Consultant of: Sobi, Novartis, Abbvie, GlaxoSmithKline, Pfizer, Amgen, Clementia, Speakers bureau: Sobi, Novartis, Abbvie, GlaxoSmithKline, Pfizer, Amgen, Clementia, Ozgur KASAPCOPUR: None declared, Vyacheslav Chasnyk: None declared, Markus Hufnagel Grant/research support from: Astellas, F. Hoffmann-La Roche, Novartis, Zbigniew Żuber: None declared, Grant Schulert Consultant of: Sobi, Novartis, Seza Ozen: None declared, Artem Popov: None declared, Athimalaipet Ramanan Speakers bureau: Roche, Sobi, Eli Lilly, UCB, Novartis, Christiaan Scott: None declared, Betül Sözeri: None declared, Elena Zholobova Grant/research support from: Pfizer, Novartis, Speakers bureau: Abbvie, Pfizer, Roche, Novartis, Xuan Zhu Employee of: Novartis, sarah whelan Employee of: Novartis, Shareholder of: Novartis, Luminita Pricop Employee of: Novartis, Shareholder of: Novartis, Angelo Ravelli Consultant of: Abbvie, Bristol-Myers Squibb, Pfizer, Hoffmann-LaRoche, Novartis, Centocor, Angelini Holding, Reckitt Benckiser, Speakers bureau: Abbvie, Bristol-Myers Squibb, Pfizer, Hoffmann-LaRoche, Novartis, Centocor, Angelini Holding, Reckitt Benckiser, Alberto Martini Consultant of: Eli Lilly, EMD Serono, Janssen, Novartis, Pfizer, Abbvie, Speakers bureau: Eli Lilly, EMD Serono, Janssen, Novartis, Pfizer, Abbvie, Daniel J Lovell Consultant of: AstraZeneca, Wyeth, Amgen, Abbott, Pfizer, Hoffmann-La Roche, Novartis, UBC, Takeda, Janssen, GlaxoSmithKline, Boehringer Ingelheim, Celgene, Bristol Myers Squibb, AbbVie, Forest Research, Speakers bureau: AstraZeneca, Wyeth, Amgen, Abbott, Pfizer, Hoffmann-La Roche, Novartis, UBC, Takeda, Janssen, GlaxoSmithKline, Boehringer Ingelheim, Celgene, Bristol Myers Squibb, AbbVie, Forest Research, Hermine Brunner Consultant of: Aurina, AbbVie, Astra Zeneca-Medimmune, Biogen, Boehringer, Bristol-Myers Squibb, Celgene, Eli Lilly, EMD Serono, GlaxoSmithKline, F. Hoffmann-La Roche, Merck, Novartis, R-Pharm, Sanofi, Pfizer, Grant/research support from: Bristol-Myers Squibb, Eli Lilly, GlaxoSmithKline, F. Hoffmann-La Roche, Janssen, Novartis, and Pfizer, Speakers bureau: Pfizer, Roche and GlaxoSmithKline

POS0076 S100A8/A9 AND S100A12 AS POTENTIAL PREDICTIVE BIOMARKERS OF ABATACEPT RESPONSE IN POLYARTICULAR JUVENILE IDIOPATHIC ARTHRITIS

Background:

The calcium-binding proteins S100A8/A9 (calprotectin) and S100A12 (extracellular newly identified receptor for advanced glycation end-products binding protein [EN-RAGE]) are involved in multiple signalling pathways to mediate inflammation, can be secreted by activated monocytes/macrophages and exhibit cytokine-like extracellular functions. Circulating levels of these proteins have been associated with disease and clinical responses in systemic juvenile idiopathic arthritis (sJIA), including treatment response.1 Studies suggest that serum S100A8/A9 and S100A12, which are released at inflammation sites, are more specific biomarkers of local inflammation (e.g. in the synovium) than systemic biomarkers such as CRP and ESR.2,3

Objectives:

To investigate if baseline S100A8/A9 and S100A12 predict clinical response to abatacept treatment in polyarticular JIA (pJIA), and to assess whether changes from baseline in S100A8/A9 or S100A12 can be better prognostic markers for response to abatacept treatment than CRP in pJIA.

Methods:

Data are from a phase III trial of SC abatacept for the treatment of pJIA (NCT01844518).4 This 24-month, single-arm, open-label, international, multicentre, two-part study included male and female patients with pJIA aged 2–17 years. This analysis examined the correlation between biomarkers (S100A8/A9, S100A12 and high-sensitivity CRP [hsCRP]) and disease activity (measured using Juvenile Arthritis Disease Activity Score [JADAS]) at baseline, baseline biomarker values as predictors of future treatment response (ACR and JADAS endpoints), and the correlation between change from baseline in biomarker values and treatment response at Day 113.

Results:

Of 219 total patients, 158 (72%) had S100A8/A9 values and 155 (71%) had S100A12 values at baseline. Median S100A8/A9 and S100A12 values were 3295 ng/mL (normal range, 716–3004 ng/mL) and 176 ng/mL (normal range, 32–385 ng/mL), respectively. S100A8/A9, S100A12 and hsCRP (median 0.20 mg/dL; normal ≤0.6 mg/dL) had a low-to-moderate but significant association with disease activity at baseline; coefficients for associations between JADAS71-CRP low disease activity (LDA) and the biomarkers S100A8/A9, S100A12 and hsCRP were 0.23 (p=0.0038), 0.16 (p=0.0448) and 0.26 (p=0.0001), respectively. Baseline S100A8/A9 level above the median was associated with lower odds of ACR100 at Day 113 (p=0.0052). Figure 1 shows the associations of baseline biomarker values with Day 113 ACR and JADAS scores in the overall population. Baseline S100A8/A9 or S100A12 did not significantly influence ACR50 or ACR70 responses at Day 113, but high baseline values were associated with reduced odds of ACR90 (p=0.01), ACR100 (p=0.005), ACR-inactive disease (ID) (p=0.0001), and JADAS71-CRP (LDA) (p=0.02). By Day 477, elevated baseline S100A12 was still significantly associated with lower odds of ACR100 overall (0.467; p=0.0248) but baseline S100A8/A9 was not; at Day 645, neither was significantly associated with ACR100 response. At Day 113, changes from baseline in S100A8/A9 and S100A12 were correlated with ACR100 (coefficients of 0.22 [p=0.0082] and 0.26 [p=0.0015], respectively) and with ACR-ID (0.22 [p=0.0067] and 0.26 [p=0.0014], respectively); change in hsCRP was not significantly correlated with disease response.

Conclusion:

S100A8/A9 and S100A12 may serve as prognostic biomarkers to predict response to abatacept treatment at Day 113. Changes from baseline S100A8/A9 and S100A12 levels were more highly correlated with efficacy outcomes including ACR100 and ACR-ID at Day 113 compared with hsCRP.

References:

[1]Aljaberi N, et al. Pediatr Rheumatol Online J 2020;18:7.

[2]Hammer H, et al. Arthritis Res Ther 2011;13:R178.

[3]Nordal HH, et al. BMC Musculoskelet Disord 2014;15:335.

[4]Brunner H, et al. Arthritis Rheumatol 2018;70:1144–1154.

Acknowledgements:

Professional medical writing and editorial assistance was provided by Rob Coover, MPH, at Caudex and was funded by Bristol Myers Squibb.

Disclosure of Interests:

Nicolino Ruperto Speakers bureau: NR has received honoraria for consultancies or speaker bureaus (< 10.000 USD each) from the following pharmaceutical companies in the past 3 years: Ablynx, Astrazeneca-Medimmune, Bayer, Biogen, Boehringer, Bristol Myers Squibb, Celgene, Eli Lilly, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sinergie, Sobi and UCB, Consultant of: NR has received honoraria for consultancies or speaker bureaus (< 10.000 USD each) from the following pharmaceutical companies in the past 3 years: Ablynx, Astrazeneca-Medimmune, Bayer, Biogen, Boehringer, Bristol Myers Squibb, Celgene, Eli Lilly, EMD Serono, GlaxoSmithKline, Hoffmann-La Roche, Janssen, Merck, Novartis, Pfizer, R-Pharma, Sinergie, Sobi and UCB, Grant/research support from: The IRCCS Istituto Giannina Gaslini (IGG), where NR works as full-time public employee has received contributions (>10.000 USD each) from the following industries in the last 3 years: Bristol Myers Squibb, Eli Lilly, F Hoffmann-La Roche, GlaxoSmithKline, Janssen, Novartis, Pfizer, Sobi. This funding has been reinvested for the research activities of the hospital in a fully independent manner, without any commitment with third parties., Grant Schulert Speakers bureau: Novartis, Consultant of: SOBI, Alyssa Sproles: None declared, Sherry Thornton: None declared, Gabriel Vega Cornejo Speakers bureau: AbbVie, Grant/research support from: Bristol Myers Squibb, Eli Lilly, Janssen, Parexel, Sanofi, Jordi Anton Speakers bureau: AbbVie, Gebro, GlaxoSmithKline, Novartis, Pfizer, Roche, Sobi, Consultant of: AbbVie, Gebro, GlaxoSmithKline, Novartis, Pfizer, Roche, Sobi, Grant/research support from: AbbVie, Amgen, Gebro, GlaxoSmithKline, Lilly, Novartis, Novimmune, Pfizer, Roche, Sanofi, Sobi, Ruben Cuttica Speakers bureau: AbbVie, Bristol Myers Squibb, GlaxoSmithKline, Lilly, Novartis, Pfizer, Roche, UCB, Paid instructor for: AbbVie, Novartis, Pfizer, Roche, Consultant of: AbbVie, Bristol Myers Squibb, GlaxoSmithKline, Lilly, Novartis, Pfizer, Roche, UCB, Michael Henrickson: None declared, Ivan Foeldvari Consultant of: Bristol Myers Squibb, Gilead, Hexal, MEDAC, Novartis, Pfizer, Sanofi, Daniel Kingsbury Consultant of: Pfizer, Margarita Askelson Consultant of: Currently working for Syneos Health providing services to Bristol Myers Squibb, Jinqi Liu Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Sumanta Mukherjee Shareholder of: Bristol Myers Squibb, GlaxoSmithKline, Employee of: Bristol Myers Squibb, GlaxoSmithKline, Robert Wong Shareholder of: Bristol Myers Squibb, Employee of: Bristol Myers Squibb, Daniel J Lovell Speakers bureau: Genentech, Wyeth Pharm, Consultant of: Abbott, Amgen, AstraZeneca, Boehringer Ingelheim, Celgene, GlaxoSmithKline, Hoffman-La Roche, Novartis, Pfizer, Regeneron, Takeda, UBC, Wyeth Pharma, Xoma, Alberto Martini Speakers bureau: AbbVie, Novartis, Consultant of: AbbVie, Eli Lilly, EMD Serono, Idorsia, Janssen, Novartis, Pfizer, Alexei Grom Consultant of: AB2Bio, Novartis, Sobi (NovImmune), Grant/research support from: AB2Bio, Novartis, Sobi (NovImmune), Hermine Brunner Speakers bureau: GlaxoSmithKline, Novartis, Pfizer, Roche, Paid instructor for: Novartis, Pfizer (funds go to CCHMC/employer), Consultant of: Boehringer Ingelheim, Bristol Myers Squibb, GlaxoSmithKline, Janssen, Merck, Novartis, Pfizer, Roche, UCB (funds go to CCHMC/employer), Grant/research support from: Bristol Myers Squibb, Pfizer (funds go to CCHMC/employer).

Overarching control of autophagy and DNA damage response by CHD6 revealed by modeling a rare human pathology

Members of the chromodomain-helicase-DNA binding (CHD) protein family are chromatin remodelers implicated in human pathologies, with CHD6 being one of its least studied members. We discovered a de novo CHD6 missense mutation in a patient clinically presenting the rare Hallermann-Streiff syndrome (HSS). We used genome editing to generate isogenic iPSC lines and model HSS in relevant cell types. By combining genomics with functional in vivo and in vitro assays, we show that CHD6 binds a cohort of autophagy and stress response genes across cell types. The HSS mutation affects CHD6 protein folding and impairs its ability to recruit co-remodelers in response to DNA damage or autophagy stimulation. This leads to accumulation of DNA damage burden and senescence-like phenotypes. We therefore uncovered a molecular mechanism explaining HSS onset via chromatin control of autophagic flux and genotoxic stress surveillance.

Comparison of human and rodent cell models to study myocardial lipid-induced insulin resistance

Isolated or cultured cells have proven to be valuable model systems to investigate cellular (patho)biology and for screening of the efficacy of drugs or their possible side-effects. Pluripotent stem cells (PSC) can be readily obtained from healthy individuals as well as from diseased patients, and protocols have been developed to differentiate these cells into cardiomyocytes. Hence, these cellular models are moving center stage for a broader application. In this review, we focus on comparing mouse HL-1 cardiomyocytes, isolated adult rat cardiomyocytes, human embryonic stem cell-derived cardiomyocytes (hESC-CMs) and human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) for the study of metabolic aspects of cardiac functioning in health and disease. Various studies have reported that these cellular models are suitable for assessing substrate uptake and utilization, in that each display an adequate and similar response to physiological triggers, in particular the presence of insulin. Likewise, disease conditions, such as excess lipid supply, similarly affect each of these rodent and human cardiomyocyte models. It is concluded that PSC-CMs obtained from patients with cardiogenetic abnormalities are promising models to evaluate the functional consequence of gene variants with unknown significance.

Clinical delineation, sex differences, and genotype-phenotype correlation in pathogenic KDM6A variants causing X-linked Kabuki syndrome type 2

Purpose

The variant spectrum and the phenotype of X-linked Kabuki syndrome type 2 (KS2) are poorly understood.

Methods

Genetic and clinical details of new and published individuals with pathogenic KDM6A variants were compiled and analyzed.

Results

Sixty-one distinct pathogenic KDM6A variants (50 truncating, 11 missense) from 80 patients (34 males, 46 females) were identified. Missense variants clustered in the TRP 2, 3, 7 and Jmj-C domains. Truncating variants were significantly more likely to be de novo. Thirteen individuals had maternally inherited variants and one had a paternally inherited variant. Neonatal feeding difficulties, hypoglycemia, postnatal growth retardation, poor weight gain, motor delay, intellectual disability (ID), microcephaly, congenital heart anomalies, palate defects, renal malformations, strabismus, hearing loss, recurrent infections, hyperinsulinism, seizures, joint hypermobility, and gastroesophageal reflux were frequent clinical findings. Facial features of over a third of patients were not typical for KS. Males were significantly more likely to be born prematurely, have shorter stature, and severe developmental delay/ID.

Conclusion

We expand the KDM6A variant spectrum and delineate the KS2 phenotype. We demonstrate that the variability of the KS2 phenotypic depends on sex and the variant type. We also highlight the overlaps and differences between the phenotypes of KS2 and KS1.