Faculty Bibliography

Background Nearly 20% of pregnancies in patients with Systemic lupus erythematosus (SLE) result in an adverse pregnancy outcome (APO); early identification of women with SLE who are at high risk of APO is vital. We previously examined several regression and machine learning (ML) predictive models for APO using data from the PROMISSE Study, a large multi-center, multi-ethnic/racial study of APO in women with mild/moderate SLE and/or aPL. Penalized logistic regression (LASSO), as well as several black box ML algorithms (Random Forest, Support Vector Machine, and Super Learner) each achieved good internal cross-validated performance, with area under the receiver operating curve (AUC) of 0.77-0.78. The goal of this study was to externally validate the performance of these promising APO risk models using three independent, external cohorts. Methods The PROMISSE data set used to develop the initial APO prediction models consisted of N=385 pregnancies, 71 APO events (18.4%), and 32 known or potential APO risk factors that are routinely measured in clinical practice early in pregnancy. APO was defined as preterm delivery due to placental insufficiency or preeclampsia, fetal or neonatal death, or fetal growth restriction. Three independent prospective cohorts were provided by a team of international investigators with expertise in SLE pregnancy (Bronx, NY: N=96; NYC, NY: N=62; Pisa, Italy: N=152). Patient demographics were summarized for each cohort and missing data handled using multiple imputation with chained equations. Using the APO risk models developed with the PROMISSE data, we computed for each cohort: 1) the standard deviation (SD) of predicted risk scores to summarize the degree of heterogeneity in patient characteristics and 2) the area under the receiver operating curve (AUC) to summarize the ability of each model to discriminate patients with and without APO. Results The three external cohorts and the PROMISSE development cohort showed distributional differences in previously identified APO risk factors (table 1). Non-Hispanic White comprised 49.3% of the PROMISSE, compared to 98.7% in Pisa, 27.4% in NYC, and 0% in the Bronx. LAC positivity varied from 8.1% in PROMISSE to 22.6% in the NYC cohort, while PGA > 1 varied from 10.6% in the development cohort to 4.4% in the Bronx, NY cohort. Current antihypertensive use was 8.6% in PROMISSE, higher in the Bronx cohort (12.6%), and lower in the NYC (4.8%) and Pisa (5.3%) cohorts. APO rates were the same in PROMISSE and Pisa (18.4%) and higher in the Bronx (24%) and NYC cohorts (25.8%). Prediction risk score SD indicated similar levels of heterogeneity within each external cohort compared to the PROMISSE cohort. Model performance in external validation cohorts varied depending on the algorithm used. As expected, AUCs in the external cohorts were generally lower than cross-validated internal estimates, but still indicated satisfactory performance of the different models with the independent data sets (table 2). Super Learner, the highest performing algorithm in PROMISSE, performed well across all three external cohorts, with a minimum AUC of 0.63 in the NYC cohort and a maximum of 0.71 in the Pisa cohort (table 2). LASSO also maintained consistent external performance with minimum AUC of 0.60 and maximum of 0.66. Overall, performance was highest using data from the Pisa cohort, which was the largest and most complete of the three external validation data sets. Conclusions Penalized regression and ML approaches using variables obtained early in pregnancy show potential in discriminating pregnancies with high APO risk from those pregnancies with lower risk. This study provides confirmation of the geographic transportability of the best performing algorithms developed with PROMISSE. While Super Learner showed the most satisfactory performance across external cohorts, LASSO also performed well and yielded a parsimonious model that may be easier and more efficient to use as a risk assessment tool in practice. Data from additional external cohorts from the US and abroad will be obtained in the future for further validation and refinement of our APO prediction models

Background Mitochondria are intracellular organelles derived from the endosymbiosis between an a-proteobacterium and a primitive eukaryotic cell. Mitochondria thus display proinflammatory and antigenic properties, when released into the extracellular milieu. Several cross-sectional studies reported increased levels of anti-mitochondrial antibodies (AMAs) in patients with systemic lupus erythematosus (SLE) and the antiphospholipid syndrome (APS). These autoantibodies also displayed correlations with the SLE disease activity index 2000 (SLEDAI-2K) and associations with various clinical manifestations (e.g. lupus nephritis, thromboses, carotid plaque). In the present study, we aim to detect AMAs against either whole organelles (AwMA), mitochondrial DNA (mtDNA) or RNA (mtRNA) through time in samples from patients included in the SLICC cohort. Methods Clinically relevant variables (e.g., sociodemographic variables, disease-specific outcomes including death and arterial vascular events (AVE)) were documented and biosamples were harvested upon patient enrolment in the SLICC cohort, as well as at each follow-up visit. AMA levels were measured by in-house direct ELISAs whereas SLE autoantibodies were detected by clinical laboratories. Healthy individuals, defined as having no known illnesses and infectious symptoms at the time of the blood draw, were recruited. 90% confidence intervals were calculated for both limits of the 95% nonparametric two-sided reference intervals for values measured in healthy donors. AMA values were segregated into 3 categories: Normal values were determined as within the inner limits of the range while values outside this range were characterized as abnormal, either lower or higher than the reference interval. (figure 1). Marginal Cox models with AMAs in 3 categories were adjusted for covariables and are presented as [hazard ratio (95% CI)]. Interactions with sex were tested in models with the AMAs as continuous variables. Results Sera from healthy individuals (n=126) or SLE patients included in the SLICC cohort, from their inclusion, up to 7 years of follow-up (n=1114 patients at baseline, 3577 samples in total). AwMA displayed lower correlations with antibodies to mitochondrial nucleic acids (versus AmtDNA: rs=0.37, and vs AmtRNA: rs=0.38), while antibodies to mitochondrial DNA or RNA shown higher correlations (rs=0.59). During our preliminary analyses on the distribution of the variables, We made intriguing observations regarding patients with AMA levels that were either lower or higher than those of healthy individuals. This information led us to categorize SLE patients as described in the methods and in figure 1. For each of the three antibodies assessed, SLE patients displayed more abnormal AMA levels at baseline than controls. The percentage of patients with higher levels of AwMA and AmtRNA increased at subsequent follow-up visits, while a slight decrease was observed for AmtDNA (figure 2). SLE patients with higher levels of AwMA showed higher risks of death [2.12 (1.18-3.83)]. It is of interest that an inverse relationship was found between AmtRNA and AVEs, with a small subset of patients with low levels of AmtRNA (n = 4), this autoantibody was associated with increased risks of this manifestation [4.46 (1.71-11.66)]. Additionally, patients with higher levels of AmtDNA and AmtRNA displayed increased risks of lupus nephritis [respectively: 3.05(2.05-4.54), and 1.56(1.12-2.18)]. Interestingly, there was an interaction with sex for AmtRNA levels effect on AVEs [males: 0.32 (0.11-0.99). Females: 1.56 (1.11-2.19)], and AmtDNA association with nephritis was only significant in female patients [4.00 (2.51-6.36)] (table 1). Conclusion These results show that AMAs display different associations with disease manifestations in various clusters of patients. These results prompt for further analyses by machine-learning in order to delineate clusters of clinical interests by adding AMAs in the routine serological assessment of SLE autoantibodies. Acknowledgements We acknowledge the contribution of the study participants, individual center support staff as well as investigators of the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort project who for the past 20 years have made this study possible. LAY ABSTRACT The mitochondrion is a part of the cell that controls various biological mechanisms (e.g., energy supply, whether the cell should live or die, control, or produce various cellular components). They are derived, through evolution, from a microbe. Mitochondria may sometimes be jettisoned out of their host cell and subsequently elicit immune reactions - including the production of antibodies. Previous studies indicated that patients with autoimmune conditions such as systemic lupus erythematosus (SLE) and the antiphospholipid syndrome (APS) have antibodies against mitochondria in their blood stream. Presence of these antibodies was associated with increased disease activity and clinical manifestations of these diseases (e.g. kidney disease, arterial vessel disease). In this study, we studied blood samples harvested by an international group dedicated to the study of SLE [i.e., the SLE International Collaborating Clinics (SLICC) cohort] and observed that patients may be clustered into groups, upon their levels of antibodies and/or sex, allowing to have a better appreciation of their risks of death, vascular events, and kidney disease. These results might lead to improved diagnosis and/or prognosis in SLE and thus, in improved care and quality of life for the people living with lupus

OBJECTIVE:In systemic lupus erythematosus (SLE), disease activity and glucocorticoid (GC) exposure are known to contribute to irreversible organ damage. We aimed to examine the association between GC exposure and organ damage occurrence. METHODS:We conducted a literature search (PubMed (Medline), Embase and Cochrane January 1966-October 2021). We identified original longitudinal observational studies reporting GC exposure as the proportion of users and/or GC use with dose information as well as the occurrence of new major organ damage as defined in the Systemic Lupus International Collaborating Clinics/American College of Rheumatology Damage Index. Meta-regression analyses were performed. Reviews, case-reports and studies with <5 years of follow-up, <50 patients, different outcomes and special populations were excluded. RESULTS:We selected 49 articles including 16 224 patients, 14 755 (90.9%) female with a mean age and disease duration of 35.1 years and of 37.1 months. The mean follow-up time was 104.9 months. For individual damage items, the average daily GC dose was associated with the occurrence of overall cardiovascular events and with osteoporosis with fractures. A higher average cumulative dose adjusted (or not)/number of follow-up years and a higher proportion of patients on GC were associated with the occurrence of osteonecrosis. CONCLUSIONS:We confirm associations of GC use with three specific damage items. In treating patients with SLE, our aim should be to maximise the efficacy of GC and to minimise their harms.

High levels of autoimmune antibodies are observed in COVID-19 patients but their specific contribution to disease severity and clinical manifestations remains poorly understood. We performed a retrospective study of 115 COVID-19 hospitalized patients with different degrees of severity to analyze the generation of autoimmune antibodies to common antigens: a lysate of erythrocytes, the lipid phosphatidylserine (PS) and DNA. High levels of IgG autoantibodies against erythrocyte lysates were observed in a large percentage (up to 36%) of patients. Anti-DNA and anti-PS antibodies determined upon hospital admission correlated strongly with later development of severe disease, showing a positive predictive value of 85.7% and 92.8%, respectively. Patients with positive values for at least one of the two autoantibodies accounted for 24% of total severe cases. Statistical analysis identified strong correlations between anti-DNA antibodies and markers of cell injury, coagulation, neutrophil levels and erythrocyte size. Anti-DNA and anti-PS autoantibodies may play an important role in the pathogenesis of COVID-19 and could be developed as predictive biomarkers for disease severity and specific clinical manifestations.

Background/Purpose: Congenital Heart Block (CHB) complicates 2% of anti-Ro/ SSA antibody positive pregnancies and carries substantial perinatal morbidity and mortality. Almost all survivors require lifelong pacing. Data suggests the potential of anti-inflammatory treatment of 1degree and 2degree CHB in preventing progression to immutable complete block. However, the optimal surveillance strategy to detect rapidly transitioning and potentially reversible conduction disease is unknown. This study addresses the feasibility, acceptance and accuracy of the fetal heart rate and rhythm technique (FHRM) in high risk mothers.
Method(s): Prospective data from the Surveillance To Prevent AV Block Likely to Occur Quickly (STOP BLOQ) study were leveraged. Mothers referred to the study all had commercially positive anti-Ro/ SSA antibodies and were stratified into high and low titers of anti-Ro60 and Ro52 based on a research ELISA which used a threshold cutoff defined as the titer above or below that obtained for 50 mothers with a previous CHB offspring. Mothers with anti-Ro60 or 52 antibodies at or above 1,000 I.U or with a previous CHB offspring, were trained to perform FHRM with an educational video and personal instruction from a pediatric cardiologist. From 17-25 weeks of gestation, FHRM was completed 3x/day in addition to weekly or biweekly fetal echocardiograms (echo). Mothers texted all FHRM sounds to the study's data coordinating center. For those FHRM deemed abnormal by the mothers, texts were immediately sent to an on call pediatric cardiologist who either reassured if FHRM was normal or referred for emergency fetal echo in < 6 hours if abnormal. Postnatal electrocardiograms were evaluated for CHB.
Result(s): Fifty-six mothers with commercial anti-Ro/ SSA positivity were consented to the study. Of these, 37 (inclusive of 6 with previous CHB) performed FRHM since they had high titer anti-Ro60 (n=8) or 52 antibodies (n=7) or both (n=21), albeit one mother had unexpectedly low titer antibodies to both Ro60 and 52 and a child with incomplete CHB 4 yrs prior to enrollment. In total 3,360 FHRM audiotexts were received during the monitoring period. Of these, 39 recordings from 5 concerned mothers prompted an immediate call with the cardiologist. All but 2 recordings were deemed to be normal based on review of the audiotext alone; the cardiologist requested that the patient send repeat recordings after review as part of re-training and to provide additional reassurance. In the 2 cases an emergency echo was completed in < 6 hrs. In both there were premature atrial contractions which confirmed the mother's perception of the FHRM abnormality. However, there was no evidence of conduction disease. All surveillance echoes were normal. Thus, the overall rate of false positive recordings for the concern of a conduction defect perceived by the mothers was 1.1% (38/3360). There were no cases of CHB at birth.
Conclusion(s): These data support that FHRM is feasible and accurate. Mothers can be empowered to detect rhythm abnormalities with very few false perceptions thus supporting this technique to substantially enhance the management of anti-Ro/ SSA pregnancies