Faculty Bibliography

OBJECTIVE:To characterize patients with Systemic Lupus Erythematosus (SLE) affected by COVID-19 and to analyze associations of comorbidities and medications on infection outcomes. METHODS:Patients with SLE and RT-PCR-confirmed COVID-19 were identified through an established New York University lupus cohort, query of two hospital systems, and referrals from rheumatologists. Data were prospectively collected via a web-based questionnaire and review of medical records. Baseline characteristics were obtained for all patients with COVID-19 to analyze risk factors for hospitalization. Data were also collected from asymptomatic patients and those with COVID-19-like symptoms who tested negative or were not tested. Statistical analyses were limited to confirmed COVID-19-positive patients. RESULTS:A total of 226 SLE patients were included: 41 patients with confirmed COVID-19; 19 patients who tested negative for COVID-19; 42 patients with COVID-19-like symptoms who did not get tested; and 124 patients who remained asymptomatic without testing. Of those SLE patients with COVID-19, 24 (59%) required hospitalization, four required intensive care unit-level of care, and four died. Hospitalized patients tended to be older, non-white, Hispanic, have higher BMI, history of nephritis, and at least one comorbidity. An exploratory (due to limited sample size) logistic regression analysis identified race, presence of at least one comorbidity, and BMI as independent predictors of hospitalization. CONCLUSION/CONCLUSIONS:In general, the variables predictive of hospitalization in our SLE patients were similar to those identified in the general population. Further studies are needed to understand additional risk factors for poor COVID-19 outcomes in patients with SLE.

OBJECTIVE:To examine the construct validity of Routine Assessment of Patient Index Data (RAPID3) and Psoriatic Arthritis Impact of Disease (PSAID) in patients with psoriatic arthritis (PsA). In examining construct validity, we also addressed scores among subgroups with severe psoriasis, polyarticular disease, enthesitis and dactylitis and evaluated influences of sociodemographic factors and comorbidities (contextual factors) on these patient-reported outcomes (PROs). METHODS:Patients with PsA were enrolled in the Psoriatic Arthritis Research Consortium (PARC) between 2014-2016. PARC is a longitudinal observational cohort study conducted at four United States institutions. In this cross-sectional study, construct validity was assessed by examining Spearman's correlation coefficients for RAPID3 and PSAID with physician-reported disease activity measures and other PROs (e.g., Short Form 12 (SF12-PCS/-MCS), Functional Assessment of Chronic Illness Therapy (FACIT)-Fatigue). Contextual factors and disease subgroups were assessed in multivariable linear regression models with RAPID3 or PSAID12 as outcomes of interest and the hypothesized contextual factors as covariates. RESULTS:Among 401 patients enrolled in PARC, 347 completed RAPID3 or PSAID12. Of these, most were Caucasian females with a mean age of 51.74 (SD 14.02). RAPID3 and PSAID were highly correlated (r=0.90). These measures were also correlated with the SF12-PCS (r=-0.67) and FACIT-Fatigue (r=-0.77). Important contextual factors and disease subgroups included enthesitis, joint counts, education, insurance type, and depression. CONCLUSION/CONCLUSIONS:RAPID3 and PSAID12 have excellent construct validity in PsA and are strongly correlated despite differing items. Contextual factors (i.e., the presence of depression and obesity) should be considered when interpreting raw scores of the RAPID3 and PSAID12.

Background/Purpose: Disparities have been reported during the coronavirus disease (COVID-19) outbreak. Systemic lupus erythematosus (SLE) patients represent a unique group that is affected by clinical, treatment, demographic, and socioeconomic (SES) risk factors for severe COVID-19 disease. The Neighborhood Deprivation Index has been associated with non-communicable disease as well as communicable disease outcomes. We conducted this study to identify neighborhood SES factors influencing SLE COVID-19 outcomes.
Method(s): Patients with SLE and COVID-19 (confirmed by RT-PCR testing), were identified through a longitudinal survey of an established NYU lupus cohort, query of NYU Langone Health and Bellevue Hospitals systems and referrals from rheumatologists at those institutions. All patients were age 18 or older and met SLE classification criteria or carried a clinical diagnosis of SLE. Baseline characteristics along with zip code neighborhood data including COVID-19 case rates and neighborhood characteristics were obtained using the Hopkins COVID database and the American Community Surveys (ACS 2014-2018) respectively. A principal component analysis was performed to identify contributory neighborhood characteristics. Then a logistic regression analysis identified predictors of testing positive for COVID-19 and COVID-19 hospitalization.
Result(s): A total of 59 SLE patients (41+ and 18-) were tested for COVID-19 by RT-PCR. The patients were predominantly female, aged 46+/-16, and racially/ethnically diverse. Roughly 140 neighborhood data points were recorded and categorized as follows: population density, race and ethnicity, household type, household size, education level, employment type and status, income and poverty, transportation method, and insurance status. COVID-19 positive patients tended to live in neighborhoods with more single parent households, households with >4 residents, higher unemployment rate, higher high school dropout rate, more public transit use, and more employment in retail, construction, and personal care services. These variables were directly proportional to principal component 1 (PC1) and accounted for 88% of the variance in neighborhood characteristics. A logistic regression model identified that PC1 (OR= 1.3; 95% CI: 1.0-1.8) and taking immune suppressants (IS) (taking vs not taking OR= 2.1; 95% CI: 1.5 to 23.3) independently correlated with having a positive COVID-19 test when controlling for hydroxychloroquine (HCQ), glucocorticoids (GC), and previous lupus nephritis (LN). Only PC1 independently correlated with COVID-19 hospitalization (OR= 1.4; 95% CI: 1.1-1.9) upon controlling for taking IS, HCQ, GCs, and LN. PC1 associated with African American (AA) or Hispanic patient race/ethnicity (OR= 1.6, 95% CI: 1.2-2.2).
Conclusion(s): In addition to SLE disease, neighborhood characteristics and SES are important risk factors both for contracting COVID-19 and developing severe disease. Neighborhood deprivation may mediate the reported relationship between AA and Hispanic race/ethnicity and COVID-19. Given that a plurality of SLE patients are of AA and/or Hispanic backgrounds, care teams must formulate strategies to address socioeconomic stress in our patients

Background/Purpose: Patients with systemic lupus erythematosus (SLE) represent a unique population in considering risk for coronavirus disease 2019 (COVID-19) with biologic, genetic, demographic, clinical and treatment issues all at play. By the nature of their chronic inflammatory autoimmune condition and regular use of immunosuppressive medications, these individuals would traditionally be considered at high risk of contracting the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and having a worse prognosis. Accordingly, we aimed to characterize patients with SLE affected by COVID-19 in New York City (NYC) and analyze associations of comorbidities and medications on outcomes.
Method(s): Patients with SLE and COVID-19 (confirmed by RT-PCR testing), were identified through a longitudinal survey of an established NYU lupus cohort, query of New York University Langone Health and Bellevue Hospitals systems and referrals from rheumatologists at those institutions. All patients were age 18 or older and met SLE classification criteria or carried a rheumatologist's diagnosis of SLE. Only English-, Spanish- or Mandarin-speaking patients were included in the study. Data were prospectively collected via a web-based questionnaire and review of electronic medical records. Baseline characteristics and medications were compared between the hospitalized and ambulatory patients with COVID-19. A logistic regression analysis was performed to identify independent predictors of hospital admission.
Result(s): A total of 41 SLE patients were confirmed COVID-19 positive by RT-PCR. The patients were predominantly female and encompassed the major racial/ethnic demographics seen in NYC. The most common symptoms of COVID-19+ patients were cough (78.4%), fever (64.9%), and shortness of breath (64.9%). Of those SLE patients with COVID-19, 24 (59%) were hospitalized, 4 required ICU level of care, and 4 died, all of hypoxic respiratory failure, Table 1. Hospitalized patients tended to be older, non-white, Hispanic, and have higher BMI, antiphospholipid syndrome, a history of lupus nephritis and at least one medical comorbidity, Table 2. There was no difference between the groups in use of hydroxychloroquine, systemic steroids or immunosuppressants. Logistic regression analysis identified the following independent predictors of being hospitalized with COVID-19: race (OR = 7.78 for non-white vs. white; 95% CI: 1.13 to 53.58; p=0.037), the presence of at least one comorbidity (OR=4.66; 95% CI: 1.02 to 21.20; p=0.047), and BMI (OR = 1.08 per increase in kg/m2; 95% CI: 0.99 to 1.18; p=0.096).
Conclusion(s): Patients with SLE and COVID-19 have a high rate of hospitalization but similar mortality rate to the general population in NYC. Risk factors such as non-white race, higher BMI, and the presence of one or more comorbidities were identified as independent predictors of hospitalization in SLE patients who develop COVID-19. The use of hydroxychloroquine and immunosuppressants did not appear to influence the outcomes of patients with SLE in the setting of COVID-19. Further studies are needed to understand additional risk factors for poor COVID-19 outcomes in patients with SLE

Background/Purpose: For psoriatic arthritis (PsA), several different composite instruments are available to define low disease activity (LDA) and remission (REM) targets for treatment. Patient-reported outcomes (PROs) may also be useful in assessing disease activity and may be more practical than composite indices in some settings. In this study, we examined the ability of PROs to differentiate between states of low disease activity and remission treatment targets (LDA and REM), using composite indices as the reference standards.
Method(s): This cross-sectional study was performed with the Psoriatic Arthritis Research Consortium between 2016-2019. PROs included Patient-Reported Outcomes Measurement Information System [PROMIS] instruments, EULAR Psoriatic Arthritis Impact of Disease [PSAID12], and Routine Assessment of Patient Index Data 3 [RAPID3]). Participants (pts) were classified as LDA if they fulfilled composite index criteria for Minimal Disease Activity (MDA), Clinical Disease Activity Index (CDAI)-LDA, or Disease Activity in Psoriatic Arthritis (cDAPSA)-LDA and REM if they fulfilled composite index criteria for Very Low Disease Activity (VLDA), CDAI-REM, or cDAPSA-REM. PROs were evaluated by determining 1) score differences between pts in LDA vs. REM, 2) correlations with composite indices scores, and 3) percentages of pts in LDA and REM who fulfilled PRO criteria for low disease states (in PROs with previously established low disease state criteria). PROs were compared between groups using t-tests or Wilcoxon rank sum test, depending on their distributions. The categorical versions of RAPID3 and PSAID12 were compared between groups using Chi-Squared test or Fisher's exact test, when appropriate. Correlations were calculated with Spearman's rank correlation. Data was analyzed using R software (Version 3.5; Vienna, Austria).
Result(s): 227 PsA pts were included (52.2% female, average age 52.7+/-14 years). Compared to pts in LDA, pts in REM had significantly more favorable PROMIS Physical, PROMIS Mental, PROMIS Fatigue, and PSAID12 scores (Figure 1). Correlations were strong between the composite indices and PROMIS GH physical health (r=0.65- 0.69) and between the composite indices and PSAID12 (r=-0.77- 0.79) (Figure 2). RAPID3 Low Severity and Near-Remission were reported by >98% of patients in REM, but only up to 54% of patients in LDA (Table 1). PSAID12 Patient AccepTable State occurred more frequently in pts in DAPSA-REM than pts in DAPSA-LDA (Table 1).
Conclusion(s): PROMIS and PSAID12 instruments correlated well with composite indices and differentiated between states of LDA vs REM. RAPID3 Near-Remission may be the most rigorous PRO criteria (including only the lowest states of disease activity), while PSAID Patient AccepTable State may identify a broader range of low states of disease activity. These data contribute to the construct validity of using PROs to measure low states of disease activity that may be considered for additional treatment targets in PsA

PURPOSE OF REVIEW/OBJECTIVE:To provide a general overview of the organizations dedicated to advance clinical and translational research in the field of psoriatic disease and to describe the current and future opportunities for team science approaches to overcome unmet needs in the field. Descriptions of initiatives from the NPF, PPACMAN, and GRAPPA are summarized. RECENT FINDINGS/RESULTS:Program projects have recently identified areas of knowledge gaps in diagnosis, treatment, and prevention of psoriasis and psoriatic arthritis (PsA). NPF's Psoriasis Prevention Initiative aims to identify interventions that can prevent the onset and relapse of psoriatic disease or related comorbidities. The Psorcast Study is a joint venture between PPACMAN and Sage Bionetworks based on patient-generated smartphone measurements of psoriatic disease. Similarly, GRAPPA is involved in a number of projects related to axial PsA, enthesitis prevalence, and biomarker discoveries. As important initiatives bring new targets for diagnosis and therapeutics in psoriatic disease, supra-endeavors such as the NIH-Accelerating Medicines Partnership (AMP) and the European Innovative Medicines Initiative (IMI) are promising public-private partnerships that can significantly catapult the field forward.

From birth, humans coexist and coevolve with trillions of micro-organisms inhabiting most body surfaces and cavities, referred to as the human microbiome. Advances in sequencing technologies and computational methods have propelled the exploration of the microbiome's contribution to human health and disease, spearheaded by massive efforts such as the Human Microbiome Project and the Europe-based MetaHit Consortium. Yet, despite the accumulated body of literature and a growing awareness among patients, microbiome research in rheumatology has not had a key impact on clinical practice. Herein, we describe some of the landmark microbiome studies in autoimmunity and rheumatology, the challenges and opportunities of microbiome research and how to navigate them, advances in related fields that have overcome these pitfalls, and future directions of harnessing the microbiome for diagnostic and therapeutic purposes.

Precision medicine, propelled by advances in multi-omics methods and analytics, aims to revolutionize patient care by using clinically-actionable molecular markers to guide diagnostic and therapeutic decisions. We describe the applications of precision medicine in risk stratification, drug selection, and treatment response prediction in psoriatic arthritis, for which targeted, personalized approaches are steadily emerging.