WHOLE GENOME TARGETED ENRICHMENT AND SEQUENCING OF HUMAN-INFECTING CRYPTOSPORIDIUM spp

Cryptosporidium spp. are protozoan parasites that cause severe illness in vulnerable human populations. Obtaining pure Cryptosporidium DNA from clinical and environmental samples is challenging because the oocysts shed in contaminated feces are limited in quantity, difficult to purify efficiently, may derive from multiple species, and yield limited DNA (<40 fg/oocyst). Here, we develop and validate a set of 100,000 RNA baits (CryptoCap_100k) based on six human-infecting Cryptosporidium spp. (C. cuniculus, C. hominis, C. meleagridis, C. parvum, C. tyzzeri, and C. viatorum) to enrich Cryptosporidium spp. DNA from a wide array of samples. We demonstrate that CryptoCap_100k increases the percentage of reads mapping to target Cryptosporidium references in a wide variety of scenarios, increasing the depth and breadth of genome coverage, facilitating increased accuracy of detecting and analyzing species within a given sample, while simultaneously decreasing costs, thereby opening new opportunities to understand the complex biology of these important pathogens.

Phylogenomic reconstruction of Cryptosporidium spp. captured directly from clinical samples reveals extensive genetic diversity

Cryptosporidium is a leading cause of severe diarrhea and mortality in young children and infants in Africa and southern Asia. More than twenty Cryptosporidium species infect humans, of which C. parvum and C. hominis are the major agents causing moderate to severe diarrhea. Relatively few genetic markers are typically applied to genotype and/or diagnose Cryptosporidium. Most infections produce limited oocysts making it difficult to perform whole genome sequencing (WGS) directly from stool samples. Hence, there is an immediate need to apply WGS strategies to 1) develop high-resolution genetic markers to genotype these parasites more precisely, 2) to investigate endemic regions and detect the prevalence of different genotypes, and the role of mixed infections in generating genetic diversity, and 3) to investigate zoonotic transmission and evolution. To understand Cryptosporidium global population genetic structure, we applied Capture Enrichment Sequencing (CES-Seq) using 74,973 RNA-based 120 nucleotide baits that cover ~92% of the genome of C. parvum. CES-Seq is sensitive and successfully sequenced Cryptosporidium genomic DNA diluted up to 0.005% in human stool DNA. It also resolved mixed strain infections and captured new species of Cryptosporidium directly from clinical/field samples to promote genome-wide phylogenomic analyses and prospective GWAS studies.

WHOLE GENOME TARGETED ENRICHMENT AND SEQUENCING OF HUMAN-INFECTING CRYPTOSPORIDIUM spp

Cryptosporidium spp. are protozoan parasites that cause severe illness in vulnerable human populations. Obtaining pure Cryptosporidium DNA from clinical and environmental samples is challenging because the oocysts shed in contaminated feces are limited in quantity, difficult to purify efficiently, may derive from multiple species, and yield limited DNA (<40 fg/oocyst). Here, we develop and validate a set of 100,000 RNA baits (CryptoCap_100k) based on six human-infecting Cryptosporidium spp. ( C. cuniculus , C. hominis , C. meleagridis , C. parvum , C. tyzzeri , and C. viatorum ) to enrich Cryptosporidium spp. DNA from a wide array of samples. We demonstrate that CryptoCap_100k increases the percentage of reads mapping to target Cryptosporidium references in a wide variety of scenarios, increasing the depth and breadth of genome coverage, facilitating increased accuracy of detecting and analyzing species within a given sample, while simultaneously decreasing costs, thereby opening new opportunities to understand the complex biology of these important pathogens.

POS0460 METABOLOMICS ACROSS AGE IDENTIFIES UNIQUE CHANGES IN THE SERUM METABOLIC PROFILE IN PATIENTS WITH SLE

Background

Cardiovascular disease (CVD) is a leading cause of mortality in patients with systemic lupus erythematosus (SLE, female:male ratio of 9:1) through accelerated atherosclerosis, the build-up of lipids and inflammation in the major artery walls, compared to age and sex matched healthy individuals. This is due to chronic inflammation, dyslipidaemia and other cardiometabolic defects that exacerbate with age (1). SLE in women aged of 35-44 increases the risk of coronary artery disease by 50 times and there is a 100-300-fold increased CVD-related mortality risk in young patients that develop SLE before the age of 18. Investigating metabolic defects in young patients and how they progress with age could help us understand the progressive mechanisms of atherosclerosis in SLE.

Objectives

This study investigated detailed changes in the metabolomic profile of female patients with SLE and matched healthy controls across age.

Methods

Serum NMR metabolomics (>250 metabolites, Nightingale) covering glycolysis metabolites, amino acids and 130 lipid measures was performed on serum from a cohort of female SLE patients (n=164, 13-72 years of age, median 35) and matched healthy controls (HCs, n=120, 15-76 years of age, median 36) and analysed by linear regression and Venn analysis. Multiple t-tests (corrected for multiple comparisons by false discovery rate) were used to assess unique metabolic changes by age group between SLE patients and HCs (≤25, n=62/43; 26-49, n=50/46; ≥50, n=52/31) and dysregulated metabolic pathways were assessed using metaboanalyst software. The metabolic impact of disease activity measures and treatments was assessed by Spearman correlations and unpaired t-tests respectively.

Results

Twenty-five metabolites were significantly altered in all SLE age groups compared to HCs, dominated by atheroprotective high density lipoprotein (HDL) subsets and their surface-bound peptide, apolipoprotein(Apo)A1, all of which were significantly decreased in SLE compared to HCs (p<0.0001 in ages combined). In addition, the concentration of glycoprotein acetyls (GlycA, inflammatory biomarker) was increased in SLE in all age groups compared to HCs (p<0.0001 in ages combined). Importantly, ApoA1 correlated negatively with disease activity measures (SLEDAI, p=0.005; BILAG, p=0.0009; dsDNA, p=0.003; ESR, p=0.0006) and positively with lymphocyte count (p=0.0005), whilst GlycA correlated positively with ESR (p<0.0001) and CRP (p<0.0001). Alternatively, metabolites unique to specific age groups in SLE compared to HCs included reduced amino acid subsets in the ≤25 age group, increased atherogenic very low density lipoproteins and reduced polyunsaturated fatty acids in the 26-49 age group, and increased atherogenic low density lipoproteins in the ≥50 age group.

Separately, metabolites associated with the glycolysis pathway (p=0.004, metaboanalyist), including acetone, citrate, creatinine, glycerol, lactate and pyruvate, had significant positive correlations with age in SLE patients, but not in HCs. These metabolites were not significantly associated with disease activity measures. However, pyruvate (p=0.01) and lactate (p=0.009) were significantly upregulated in prednisolone treated patients, whilst citrate (p=0.002) and creatinine (p= 0.005) were downregulated in hydroxychloroquine treated patients.

Conclusion

Increasing HDL (ApoA1) levels whilst maintaining low disease activity in patients with SLE from a young age could improve cardiometabolic risk outcomes. This could be achieved through improved nutrition, lipid targeted therapies and better treatment strategies. Focusing on understanding and monitoring biomarkers of the glycolytic pathway could aid treatment decisions and help avoid adverse metabolic effects of current anti-inflammatory therapies in SLE (1).

References

[1]Robinson G.A, Pineda-Torra I, Ciurtin C, Jury E.C. Lipid metabolism in autoimmune rheumatic disease: implications for modern and conventional therapies. J Clin Invest. 2022;132(2):e148552. https://doi.org/10.1172/JCI148552.

Acknowledgements

The authors would like to thank all of the patients and healthy blood donors, as well as Prof. Arne Akbar and Dr. Chris Wincup for additional patient and healthy donor samples.

Disclosure of Interests

None declared.

POS0039 MONOCYTE TRANSCRIPTOMICS AND TARGETED PROTEOMICS DEFINE HETEROGENEOUS SUBGROUPS IN WOMEN WITH SYSTEMIC LUPUS ERYTHEMATOSUS (SLE) AND SUBCLINICAL ATHEROSCLEROSIS

Background

Systemic lupus erythematosus (SLE), a chronic, inflammatory autoimmune disease, predominantly affects women with a 9:1 female:male incidence. Cardiovascular disease (CVD) is a leading cause of mortality in SLE via accelerated atherosclerosis: the build-up of cells and lipids in the vascular wall and the main pathology underlying CVD.

Objectives

To define molecular profiles of SLE with subclinical atherosclerosis using multi-omics data analysis and clinical data in a well-characterised cohort of CVD-free SLE women.

Methods

Multi-omics analyses were conducted to explore the molecular signatures of SLE patients with (SLE-P) and without (SLE-NP) subclinical atherosclerosis defined by non-invasive ultrasound scanning of the carotid and femoral arteries. SLE blood CD14+ monocyte transcriptomes were investigated by bulk RNA-sequencing (SLE-P N=13, SLE-NP N=8), and targeted serum cardiometabolic and cardiovascular proteomics (OLINK) were used to explore matched protein expression (SLE-P N=17, SLE-NP N=20) (no difference in disease activity between groups). Bioinformatics approaches, including pathway and disease module enrichment analyses and extended protein-protein interaction networks, further defined molecular profiles of SLE patients with atherosclerosis from patients that remained plaque free. Gene signature-derived interferon (IFN) scores were applied to investigate heterogeneous subgroups within the cohort as a measure of inflammation.

Results

Distinct monocyte gene and protein expression profiles were identified in SLE and enriched in biological pathways relating to extracellular mechanisms, including purinergic and cytokine signalling. Lipid regulatory mechanisms were enriched in SLE-P, whereas SLE-NP patient’s transcriptome and proteome profiles were defined by pathways relating to inflammation. Specifically, the type-I IFN pathway was exclusively reduced in SLE-P compared to SLE-NP. IFN scores derived from published IFN-responsive gene expression signatures stratified patients into significantly distinct subgroups (high versus low IFN-response, p=0.0001) with 66% (N=14) of patients showing high IFN expression across multiple signatures not associated with age, ethnicity, or disease activity. However, IFN scores did not predict the presence of sub-clinical atherosclerosis and further heterogeneity was revealed with 46% of SLE-P patients showing a low IFN response (N=6). Further, a measure of plaque lipid content (echogenicity) was inversely correlated with IFN score (grey scale median, p=0.03, r=-0.8) which may reflect distinct plaque phenotypes between these subgroups relating to clinical presentation and risk of cardiovascular events.

Conclusion

Lipid dysregulation is a key mechanism that drives atherosclerosis pathology and genes and proteins relating to lipid metabolism distinguished SLE patients with and without subclinical atherosclerosis. Differences in levels of interferons and other inflammatory molecules may contribute to unique patterns of gene expression between SLE patients. A distinct subset of SLE-P patients showed low interferon expression, which may be suggestive of a dampened immune response in early subclinical CVD. Further elucidating the complexity of lipid dysregulation, inflammation and immune function in atherosclerosis in SLE will help improve patient stratification towards investigating the efficacy of anti-atherosclerotic therapies.

Disclosure of Interests

None declared

Diagnostic accuracy of an automated artificial intelligence derived right ventricular to left ventricular diameter ratio tool on CT pulmonary angiography to predict pulmonary hypertension at right heart catheterisation

AIM

To determine the diagnostic accuracy of an automated artificial intelligence derived right ventricle/left ventricle diameter ratio (RV/LV) computed tomography pulmonary angiography (CTPA) analysis tool to detect pulmonary hypertension (PH) in patients with suspected PH referred to a specialist centre.

MATERIALS AND METHODS

The present study was a retrospective analysis of a prospectively maintained database of 202 consecutive patients with suspected PH, who underwent CTPA within 12 months of right heart catheterisation (RHC). Automated ventricular segmentation and RV/LV calculation (Imbio LLC, Minneapolis, MN, USA) was undertaken on the CTPA images. PH diagnosis was made using the RHC reference standard.

RESULTS

The automated RV/LV correlated more strongly with RHC metrics than main pulmonary artery (MPA) diameter and MPA to ascending aorta diameter ratio (MPA/AA) measured manually (mean pulmonary arterial pressure [mPAP] r=0.535, R² = 0.287 p<0.001; pulmonary vascular resistance [PVR] r=0.607, R² = 0.369 p<0.001). In the derivation cohort (n=100), the area under the receiver-operating curve for automated RV/LV discriminating PH was 0.752 (95% confidence interval [CI] 0.677-0.827, p<0.001). Using an optimised Youden's Index of ≥1.12 classified from derivation, automated RV/LV ratio analysis was more sensitive for the detection of PH with higher positive predictive value (PPV) when compared with manual MPA and MPA/AA in the validation cohort (n=102). Automated RV/LV compromise (1.12) and specific (1.335) thresholds were strongly predictive of mortality (log-rank 7.401, p=0.007 and log-rank 16.075, p<0.001 respectively).

CONCLUSION

In suspected PH, automated RV/LV diameter thresholds have high sensitivity for PH, outperform manual MPA and MPA/AA and can predict survival.

Pretreatment Normal WM Magnetization Transfer Ratio Predicts Risk of Radiation Necrosis in Patients with Medulloblastoma

BACKGROUND AND PURPOSE

Radiation necrosis, for which abnormal WM enhancement is a hallmark, is an uncommon complication of craniospinal irradiation in children with medulloblastoma. The magnetization transfer ratio measures macromolecular content, dominated by myelin in the WM. We investigated whether the pretreatment supratentorial (nonsurgical) WM magnetization transfer ratio could predict patients at risk for radiation necrosis after radiation therapy for medulloblastoma.

MATERIALS AND METHODS

Ninety-five eligible patients with medulloblastoma (41% female; mean age, 11.0 [SD, 5.4]  years) had baseline balanced steady-state free precession MR imaging before proton or photon radiation therapy. Associations among baseline supratentorial magnetization transfer ratio, radiation necrosis (spontaneously resolving/improving parenchymal enhancement within the radiation field)³, age, and the presence of visible brain metastases were explored by logistic regression and parametric/nonparametric techniques as appropriate.

RESULTS

Twenty-three of 95 (24.2%) children (44% female; mean age, 10.7 [SD, 6.7] years) developed radiation necrosis after radiation therapy (19 infratentorial, 1 supratentorial, 3 both). The mean pretreatment supratentorial WM magnetization transfer ratio was significantly lower in these children (43.18 versus 43.50, P = .03). There was no association between the supratentorial WM magnetization transfer ratio and age, sex, risk/treatment stratum, or the presence of visible brain metastases.

CONCLUSIONS

A lower baseline supratentorial WM magnetization transfer ratio may indicate underlying structural WM susceptibility to radiation necrosis and may identify children at risk for developing radiation necrosis after craniospinal irradiation for medulloblastoma.

Effect of Amoxicillin Dose and Treatment Duration on the Need for Antibiotic Re-treatment in Children With Community-Acquired Pneumonia: The CAP-IT Randomized Clinical Trial

IMPORTANCE

The optimal dose and duration of oral amoxicillin for children with community-acquired pneumonia (CAP) are unclear.

OBJECTIVE

To determine whether lower-dose amoxicillin is noninferior to higher dose and whether 3-day treatment is noninferior to 7 days.

DESIGN, SETTING, AND PARTICIPANTS

Multicenter, randomized, 2 × 2 factorial noninferiority trial enrolling 824 children, aged 6 months and older, with clinically diagnosed CAP, treated with amoxicillin on discharge from emergency departments and inpatient wards of 28 hospitals in the UK and 1 in Ireland between February 2017 and April 2019, with last trial visit on May 21, 2019.

INTERVENTIONS

Children were randomized 1:1 to receive oral amoxicillin at a lower dose (35-50 mg/kg/d; n = 410) or higher dose (70-90 mg/kg/d; n = 404), for a shorter duration (3 days; n = 413) or a longer duration (7 days; n = 401).

MAIN OUTCOMES AND MEASURES

The primary outcome was clinically indicated antibiotic re-treatment for respiratory infection within 28 days after randomization. The noninferiority margin was 8%. Secondary outcomes included severity/duration of 9 parent-reported CAP symptoms, 3 antibiotic-related adverse events, and phenotypic resistance in colonizing Streptococcus pneumoniae isolates.

RESULTS

Of 824 participants randomized into 1 of the 4 groups, 814 received at least 1 dose of trial medication (median [IQR] age, 2.5 years [1.6-2.7]; 421 [52%] males and 393 [48%] females), and the primary outcome was available for 789 (97%). For lower vs higher dose, the primary outcome occurred in 12.6% with lower dose vs 12.4% with higher dose (difference, 0.2% [1-sided 95% CI -∞ to 4.0%]), and in 12.5% with 3-day treatment vs 12.5% with 7-day treatment (difference, 0.1% [1-sided 95% CI -∞ to 3.9]). Both groups demonstrated noninferiority with no significant interaction between dose and duration (P = .63). Of the 14 prespecified secondary end points, the only significant differences were 3-day vs 7-day treatment for cough duration (median 12 days vs 10 days; hazard ratio [HR], 1.2 [95% CI, 1.0 to 1.4]; P = .04) and sleep disturbed by cough (median, 4 days vs 4 days; HR, 1.2 [95% CI, 1.0 to 1.4]; P = .03). Among the subgroup of children with severe CAP, the primary end point occurred in 17.3% of lower-dose recipients vs 13.5% of higher-dose recipients (difference, 3.8% [1-sided 95% CI, -∞ to10%]; P value for interaction = .18) and in 16.0% with 3-day treatment vs 14.8% with 7-day treatment (difference, 1.2% [1-sided 95% CI, -∞ to 7.4%]; P value for interaction = .73).

CONCLUSIONS AND RELEVANCE

Among children with CAP discharged from an emergency department or hospital ward (within 48 hours), lower-dose outpatient oral amoxicillin was noninferior to higher dose, and 3-day duration was noninferior to 7 days, with regard to need for antibiotic re-treatment. However, disease severity, treatment setting, prior antibiotics received, and acceptability of the noninferiority margin require consideration when interpreting the findings.

TRIAL REGISTRATION

ISRCTN Identifier: ISRCTN76888927.

Accuracy of echocardiographic doppler measures of pulmonary hypertension compared with right heart catheterisation in a real world population referred to a specialist centre

Introduction

Right heart catheterisation (RHC) is the gold standard investigation for the diagnosis of pulmonary hypertension (PH). Transthoracic echocardiography (TTE) allows non-invasive screening for PH. This retrospective audit sought to compare the accuracy of non-invasive Doppler estimates of pulmonary artery pressure and pulmonary vascular resistance (PVR) compared to RHC in a real world cohort referred to a shared care PH centre.

Method

Between 2010 and 2019, a total of 310 patients referred for initial assessment of PH underwent TTE followed by RHC (mean interval 31±30 days). Bland-Altman analysis was used to retrospectively investigate the accuracy of Doppler estimates of Pulmonary Artery Systolic Pressure (PASP), mean Pulmonary Artery Pressure (mPAP), Right Atrial Pressure (RAP) and PVR compared to RHC. TTE mPAP estimates were made using the pulmonary regurgitation velocity at the beginning of diastole (mPAP = 4(PRVBD)2 + RAP). TTE PVR estimates were calculated using the equation 10(TRV / RVOTVTI) + 0.16.

Results

Seventy-six percent of the cohort (n=235) had RHC diagnosed PH (average mPAP 42.8±11.7mmHg). The peak tricuspid regurgitation velocity (TRV) was measurable in 87% (n=269) and was unmeasurable in 8% (n=19) of those with confirmed RHC PH. Ten percent (n=30) had inadequate IVC imaging. TTE estimates of PASP (n=239) had a good correlation to RHC PASP (rs=0.82, 95% CI 0.75–0.84). TTE PASP estimates tended to underestimate RHC PASP (bias −3.7±15.2mmHg) with wide limits of agreement (95% limits of agreement −33.5–26.1mmHg) (figure 1); highlighting the imprecision of Doppler estimates alone. Only 44% of TTE PASP estimates were within 10mmHg of RHC PASP readings. Underestimation occurred more frequently accounting for 66% of inaccurate TTE PASP estimates. TTE RAP estimates (n=292) were weakly correlated to RHC RAP (rs=0.38, 95% CI 0.27–0.48).

TTE estimates of mPAP were only measurable in 81 patients and demonstrated moderate correlation to RHC mPAP (rs=0.58, 95% CI 0.4–0.71). TTE estimates tended to underestimate RHC mPAP (bias of −10±10.9mmHg) with wide limits of agreement (95% limits of agreement −31.3–11.3mmHg) (figure 1) suggesting poor accuracy and precision. Only 51% of TTE estimates were within 10mmHg of RHC mPAP with 93% of inaccuracies due to an underestimation of RHC mPAP. TTE PVR estimates (n=238) correlated well with RHC PVR measures (rs=0.68, 95% CI 0.6–0.74). However, Bland-Altman analysis (figure 2) demonstrated bias of −2.2±3.1WU with wide limits of agreement (95% limits of agreement −8.2–3.8WU), highlighting significant inaccuracy.

Conclusion

Doppler TTE measures to assess PH lack accuracy when compared with the gold standard RHC. Furthermore, the peak TRV was unmeasurable in 8% of those with confirmed RHC diagnosed PH. These findings further support the use of a multi parameter TTE approach for screening of PH.

Funding Acknowledgement

Type of funding sources: None.

POS0174 IMMUNOPHENOTYPE OF SJÖGREN´S SYNDROME AND SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS IDENTIFIED TWO ENDOTYPES WITH POTENTIAL THERAPEUTIC IMPLICATIONS

Background:

Primary Sjögren’s syndrome (pSS) and systemic lupus erythematosus (SLE) are chronic autoimmune rheumatic diseases (ARDs) that share a strong female gender bias, as well as genetic, clinical and serological characteristics.Although significant progress has been made in improving treatment and patient related outcomes in pSS and SLE, there is a need for improved early diagnosis, adequate therapy monitoring, treatment of refractory manifestations and strategies to address co-morbidities.However, the results of many clinical trials are disappointing, and nobiologic treatments are licensedin pSS, while few are available for SLE patients with refractory disease.

Objectives:

Identifying shared immunological features between patients with pSS and SLE that could lead to better treatment selection using a stratification approach.

Methods:

Immune-phenotyping of 29 immune-cell subsets in peripheral blood from patients with pSS (n=45), SLE (n=29) and secondary SS associated with SLE (SLE/SS) (n=14) with low disease activity or in clinical remission, and sex-matched healthy controls (n=31), was performed using flow cytometry. Data were analysed using logistic regression and multiple t-tests andsupervised machine learning (balanced random forest-BRF, sparse partial least squares discriminant analysis-sPLS-DA). Patients were stratified by k-means clustering. Clinical trajectories were analysed over 5 year follow-up.

Results:

Comparing the immune profile of pSS and SLE patients using a variety of statistical and machine learning (ML) approaches, identified very few statistically significant differences between the two cohorts despite patients having a different clinical presentation and diagnosis. Thus, we hypothesised that immune-based subtypes could be shared between pSS, SLE and SLE/SS patients. Unsupervised k-means clustering was applied to the immunological features of the combined patient cohorts and two distinct patient endotypes, were identified: Group-1 (n=49; pSS=24, SLE=19, SLE/SS=6) and Group-2 (n=39; pSS=21, SLE=10, SLE/SS=8). Significant differences in immune-cell phenotypes across B-cell and T-cell subsets were identified by logistic regression, BRF (AUC=0.9942, assessed by 10-fold cross-validation) and sPLS-DA analysis. Comparison of the multiple analysis approaches identified eight common immune-cell subsets, including total and memory CD4+ and CD8+ T-cell subsets but no B-cell subsets. Using this common immune-signature the stratification between the groups was maintained and slightly improved (AUC=0.9979 and accuracy 96.16%). Interestingly, patients in Group-2 had elevated disease activity measures at baseline and over a 5-year trajectory compared to Group-1. Finally, correlation analysis identifed correlations between disease activity markers and the top ranked immune features from the ML models.

Conclusion:

The identified immune-cell signatures could reflect the underlying disease pathogenesis that spans diagnositc criteria and could be used to select patients for targeted therapeutic approaches.

Acknowledgements:

LM-G is supported by a project grant from The Dunhill Medical Trust (RPGF1902\117); JP is supported by Versus Arthritis (21226). GAR is supported by Lupus UK, The Rosetrees Trust (M409) and Versus Arthritis (21593). MN is supported by NIHR UCLH Biomedical Research Centre (BRC525/III/CC/191350). HP has a Versus Arthritis PhD studentship (22203). This work was performed within the Centre for Adolescent Rheumatology Versus Arthritis at UCL UCLH and GOSH supported by grants from Versus Arthritis (21593 and 20164), GOSCC, and the NIHR-Biomedical Research Centres at both GOSH and UCLH.

We would like to thank Mr Jamie Evans for expert support with flow cytometry analysis and Ms Eve McLoughlin for support with patient recruitment.

Disclosure of Interests:

None declared

OP0013 SEX DIFFERENCES IN AUTOIMMUNE DISEASE SUSCEPTIBILITY; A MULTI-OMIC APPROACH

Background:

Males and females have altered immune responses resulting in variation in autoimmune and cardiovascular disease risk (CVR). Recently, these differences have played a role in the inflammatory response to COVID-19. Sex differences exist in the frequency and activity of immune-cell subsets but mechanisms underlying sexual dimorphism remain unknown. Juvenile-onset systemic lupus erythematosus (JSLE) is an autoimmune disorder that commonly emerges during puberty, has a strong female prevalence (female:male ratio, 4.5:1) and results in an increased CVR. JSLE is characterised by chronic inflammation and dyslipidaemia, where cardiovascular disease is a leading cause of mortality for patients. Our previous work identified a link between immune cell function and lipid metabolism in adult-onset SLE. We hypothesised that sex hormones could influence both lipid metabolism and immune cell function and this could determine sex-specific susceptibility to JSLE and associated CVR.

Objectives:

We investigated the role of sex hormones in modifying systemic lipid metabolism and inflammation.

Methods:

Nuclear magnetic resonance spectroscopy based serum metabolomics measuring over 130 lipoproteins (14-subsets with lipid compositions), flow cytometry measuring immune-cells, and RNA-sequencing were used to assess the metabolic and immune profile in young, pre/post-pubertal males (n=10/17) and females (n=10/23) and in individuals with gender-dysphoria (GD) under cross-hormone treatment (trans-male/female, n=26/25). This analysis was also performed on a cohort of post-pubertal male (n=12) and female (n=23) JSLE patients. Data was analysed by logistic regression, balanced random forest machine learning (BRF-ML), differential gene expression (DEG) and pathway analysis.

Results:

Post-pubertal males had significantly reduced cardio-protective high-density lipoprotein (HDL) subsets (p<0.0001) and increased cardio-pathogenic very-low-density lipoprotein subsets (p<0.0001) compared to females. These differences were not observed pre-puberty and were reversed significantly by cross-hormone treatment in GD individuals, suggesting that sex hormones regulate lipid metabolism in-vivo.

BRF-ML (28 immune-cell subsets) identified an increased frequency of anti-inflammatory regulatory T-cells (Tregs) in post-pubertal males compared to females (p=0.0097). These Tregs were also more suppressive in males compared to females. Differences in Treg frequency were seen pre-puberty and were not altered by sex hormone treatment in GD individuals. However, Treg DEGs and functional transcriptomic pathways altered between post-pubertal males and females, including those involved in inflammatory signalling, overlapped with those altered by hormones in GD, suggesting hormones may also drive Treg functional changes. In addition, HDL metabolites modified by hormones showed differential associations with Treg phenotypes between post-pubertal males and females.

Strikingly, sex differences in lipoproteins and Tregs were lost in JSLE, suggesting hormone signalling could be dysregulated in the pathogenesis of autoimmunity and could increase CVR for patients.

Conclusion:

Sex hormones drive altered lipoprotein metabolism and functional transcriptomic pathways in Tregs. Males have a lipoprotein profile associated with increased CVR, but a more anti-inflammatory immune profile compared to females. Together, this could explain sex differences in inflammatory disease susceptibilities and inform future sex-specific therapeutic strategies for the management of both JSLE and CVR.

Acknowledgements:

Lupus UK

Rosetrees Trust

Versus Arthritis

NIHR UCLH Biomedical Research Centre

Disclosure of Interests:

None declared

Analysis of Cryptosporidium spp. from clinical samples by matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry

AIM

To purify Cryptosporidium spp. oocysts from clinical stool samples and evaluate using an up-to-date mass spectrometry protocol producing high-quality reference spectra.

METHODS AND RESULTS

A refined purification protocol was developed for oocysts from stools, involving salt flotation and potassium bromide density centrifugation. Purified oocysts were prepared for matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) by formic acid extraction, and the extracts analysed using the Bruker MALDI Biotyper system. Individual spectral markers were identified by their specific mass peaks. Cryptosporidium parvum oocysts (Iowa strain) propagated in vivo, and C.  parvum (n = 2) and Cryptosporidium hominis (n = 1) oocysts from clinical stool samples produced distinct spectra that were considered specific to Cryptosporidium spp. with no evidence of contamination.

CONCLUSIONS

The production of distinct spectra demonstrated the utility of the purification method for oocysts from clinical stool samples and provided reference spectra.

SIGNIFICANCE AND IMPACT OF THE STUDY

The use of MALDI-TOF MS and other mass spectrometry techniques has been limited previously to C.  parvum oocysts propagated in vivo. Appropriate purification of oocysts can achieve sufficient biomass, enabling analysis by MALDI-TOF MS and potentially other mass spectrometry platforms, facilitating peptide and protein discovery and identification of biomarkers from a much wider range of Cryptosporidium spp. from natural infections.

COVID-19: looking beyond the peak. Challenges and tips for radiologists in follow-up of a novel patient cohort

As the coronavirus pandemic evolves, the focus of radiology departments has begun to change. The acute phase of imaging a new disease entity whilst rationalising radiology services in the face of lockdown has passed. Radiologists are now becoming familiar with the complications of COVID-19, particularly the lung parenchymal and pulmonary vascular sequelae and are considering the impact follow-up imaging may have on departments already struggling with a backlog of suspended imaging in the face of reduced capacity. This review from the British Society of Thoracic Imaging explores both the thoracic and extra-thoracic complications of COVID-19, recognising the importance of a holistic approach to patient follow-up. The British Thoracic Society guidelines for respiratory follow-up of COVID-19 will be discussed, together with newly developed reporting templates, which aim to provide consistency for clinicians as well as an opportunity for longer-term data collection.

OP0287 A MACHINE LEARNING APPROACH FOR PRECISION STRATIFICATION OF JUVENILE-ONSET SLE

Background:

Juvenile-onset systemic lupus erythematosus (JSLE) is a complex and heterogeneous disease characterised by diagnosis and treatment delays. An unmet need exists to better characterise the immunological profile of JSLE patients and investigate its links with the disease trajectory over time.

Objectives:

A machine learning (ML) approach was applied to explore new diagnostic signatures for JSLE based on immune-phenotyping data and stratify patients by specific immune characteristics to investigate longitudinal clinical outcome.

Methods:

Immune-phenotyping of 28 T-cell, B-cell and myeloid-cell subsets in 67 age and sex-matched JSLE patients and 39 healthy controls (HCs) was performed by flow cytometry. A balanced random forest (BRF) ML predictive model was developed (10,000 decision trees). 10-fold cross validation, Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA) and logistic regression was used to validate the model. Longitudinal clinical data were related to the immunological features identified by ML analysis.

Results:

The BRF-model discriminated JSLE patients from healthy controls with 91% prediction accuracy suggesting that JSLE patients could be distinguished from HCs with high confidence using immunological parameters. The top-ranked immunological features from the BRF-model were confirmed using sPLS-DA and logistic regression and included CD19+ unswitched memory B-cells, naïve B-cells, CD14+monocytes and total CD4+, CD8+and memory T-cell subsets.

K-mean clustering was applied to stratify patients using the validated signature. Four groups were identified, each with a distinct immune and clinical profile. Notably, CD8+T-cell subsets were important in driving patient stratification while B-cell markers were similarly expressed across the JSLE cohort. JSLE patients with elevated effector memory CD8+T-cell frequencies had more persistently active disease over time, and this was associated with increased treatment burden and prevalence of lupus nephritis. Finally, network analysis identified specific clinical features associated with each of the top JSLE immune-signature variables.

Conclusion:

Using a combined ML approach, a distinct immune signature was identified that discriminated between JSLE patients and HCs and further stratified patients. This signature could have diagnostic and therapeutic implications. Further immunological association studies are warranted to develop data-driven personalised medicine approaches for JSLE.

Acknowledgments:

Lupus UK, Rosetrees Trust, Versus Arthritis

Disclosure of Interests:

George Robinson: None declared, Junjie Peng: None declared, Pierre Dönnes: None declared, Leda Coelewij: None declared, Meena Naja: None declared, Anna Radziszewska: None declared, Chris Wincup: None declared, Hannah Peckham: None declared, David Isenberg Consultant of: Study Investigator and Consultant to Genentech, Yiannis Ioannou: None declared, Ines Pineda Torra: None declared, Coziana Ciurtin Grant/research support from: Pfizer, Consultant of: Roche, Modern Biosciences, Elizabeth Jury: None declared

OP0006 ABNORMAL IRON METABOLISM AND MITOCHONDRIAL DYSFUNCTION: INVESTIGATING A NOVEL PATHOLOGICAL MECHANISM IN SYSTEMIC LUPUS ERYTHEMATOSUS

Background:

Iron is vital for numerous essential physiological processes including erythropoiesis and energy metabolism (as iron is found in the mitochondrial electron transport chain, the central site of ATP production). Iron homeostasis is tightly controlled by a number of regulators including; 1. Hepcidin, which prevents iron release from stores (under the influence of IL6 and IL1β); 2. Ferritin, an iron storage protein; 3. Lipocalin-2 (LCN2), which is released upon innate immune activation that induces iron sequestration; 4. Transferrin, which binds circulating iron and enables its transport to effector cell targets; 5. Haptoglobin, which binds free haemoglobin and assisting iron recycling; 6. Erythropoietin (EPO), which stimulates erythropoiesis as a result of hypoxia.

Chronic inflammation may result in dysregulation of iron metabolism and in turn impair mitochondrial function yet little is known regarding how these processes change in systemic lupus erythematosus (SLE).

Objectives:

In this study, we investigated how dysregulation of iron metabolism may occur in SLE and subsequently sought to identify how a lack of iron may ultimately induce abnormal mitochondrial function.

Methods:

1. Investigating abnormal iron metabolism in SLE.Serum samples from patients with SLE (n=39) and healthy controls (HC, n=17) were assessed hepcidin, IL-1ß, IL-6, ferritin, LCN2, EPO, haptoglobin and transferrin levels by ELISA. Hierarchical cluster analysis of normalised data (converted to Z-scores) was performed using MeV software in order to characterise patient groups based upon iron metabolism profile. Anti-dsDNA antibody titres, complement C3 levels and SLEDAI-2K were excluded to limit the influence of these variables on cluster analysis. Results were presented as a heatmap.

2. Studying mitochondrial function in iron deficiency and SLE. Peripheral blood mononuclear cells (PBMCs) from HCs and patients with SLE were analysed using Seahorse Respirometry, which measures mitochondrial oxygen consumption rate (a measure of energy metabolism dependent upon oxidative phosphorylation). To assess differences between health, iron deficiency and SLE 3 groups were assessed; 1. PBMCs derived from HCs; 2. PBMCs from patients with SLE; 3. Healthy PBMCs cultured in iron deficient condition, in which cells were treated with the potent iron chelator, Deferiprone.

Results:

Figure 1a demonstrates that four groups were identified following cluster analysis. In spite of excluding markers of disease activity, these groups showed significant differences in SLEDAI-2K (shown in Figure 1b). In summary, patients with more active disease (Groups C and D) showed higher levels of hepcidin (which prevents the release of iron from stores, under the influence of IL-1ß and IL-6) and reduced transferrin thus suggesting that iron is inefficiently transported when compared with those with less active disease (in Groups A and B).

Figure 2a demonstrates that basal mitochondrial respiration is significantly reduced in PBMCs derived from healthy controls when grown in iron deficiency conditions (following treatment with Deferiprone and is lower still in those with SLE. Figure 2b shows that PBMCs from patients with SLE have reduced maximal mitochondrial respiration capacity that is comparable to the levels seen in iron deficient healthy PBMCs.

Conclusion:

Patients with SLE demonstrate abnormalities in iron metabolism that results in cellular iron deficiency as iron is not released from stores, nor adequately transported at the rate required to meet physiological demands. Furthermore, PBMCs derived from patients with SLE who impaired basal and maximal respiration that is comparable with healthy PBMCs treated potent iron chelation. This suggests that abnormal iron metabolism may in turn limit mitochondrial energy metabolism in SLE and represents a potential future therapeutic target.

References:

Nil

Acknowledgments:

Versus Arthritis (Grant No 594143) and LUPUS UK

Disclosure of Interests:

None declared