Nonsteroidal anti-inflammatory drug "allergy" labeling is associated with increased postpartum opioid utilization.

BACKGROUND: Current guidelines recommend a stepwise approach to postpartum pain management, beginning with acetaminophen and nonsteroidal anti-inflammatory drugs (NSAIDs), with opioids added only if needed. Report of a prior NSAID-induced adverse drug reaction (ADR) may preclude use of first-line analgesics, despite evidence that many patients with this allergy label may safely tolerate NSAIDs. OBJECTIVE: We assessed the association between reported NSAID ADRs and postpartum opioid utilization. METHODS: We performed a retrospective cohort study of birthing people who delivered within an integrated health system (January 1, 2017, to December 31, 2020). Study outcomes were postpartum inpatient opioid administrations and opioid prescriptions at discharge. Statistical analysis was performed on a propensity score-matched sample, which was generated with the goal of matching to the covariate distributions from individuals with NSAID ADRs. RESULTS: Of 38,927 eligible participants, there were 883 (2.3%) with an NSAID ADR. Among individuals with reported NSAID ADRs, 49.5% received inpatient opioids in the postpartum period, compared to 34.5% of those with no NSAID ADRs (difference = 15.0%, 95% confidence interval 11.4-18.6%). For patients who received postpartum inpatient opioids, those with NSAID ADRs received a higher total cumulative dose between delivery and hospital discharge (median 30.0 vs 22.5 morphine milligram equivalents [MME] for vaginal deliveries; median 104.4 vs 75.0 MME for cesarean deliveries). The overall proportion of patients receiving an opioid prescription at the time of hospital discharge was higher for patients with NSAID ADRs compared to patients with no NSAID ADRs (39.3% vs 27.2%; difference = 12.1%, 95% confidence interval 8.6-15.6%). CONCLUSION: Patients with reported NSAID ADRs had higher postpartum inpatient opioid utilization and more frequently received opioid prescriptions at hospital discharge compared to those without NSAID ADRs, regardless of mode of delivery.

Association of Physical Activity With Bioactive Lipids and Cardiovascular Events.

BACKGROUND: To clarify the mechanisms underlying physical activity (PA)-related cardioprotection, we examined the association of PA with plasma bioactive lipids (BALs) and cardiovascular disease (CVD) events. We additionally performed genome-wide associations. METHODS: PA-bioactive lipid associations were examined in VITAL (VITamin D and OmegA-3 TriaL)-clinical translational science center (REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT01169259; N=1032) and validated in JUPITER (Justification for the Use of statins in Prevention: an Intervention Trial Evaluating Rosuvastatin)-NC (REGISTRATION: URL: https://www. CLINICALTRIALS: gov; Unique identifier: NCT00239681; N=589), using linear models adjusted for age, sex, race, low-density lipoprotein-cholesterol, total-C, and smoking. Significant BALs were carried over to examine associations with incident CVD in 2 nested CVD case-control studies: VITAL-CVD (741 case-control pairs) and JUPITER-CVD (415 case-control pairs; validation). RESULTS: We detected 145 PA-bioactive lipid validated associations (false discovery rate <0.1). Annotations were found for 6 of these BALs: 12,13-diHOME, 9,10-diHOME, lysoPC(15:0), oxymorphone-3b-D-glucuronide, cortisone, and oleoyl-glycerol. Genetic analysis within JUPITER-NC showed associations of 32 PA-related BALs with 22 single-nucleotide polymorphisms. From PA-related BALs, 12 are associated with CVD. CONCLUSIONS: We identified a PA-related bioactive lipidome profile out of which 12 BALs also had opposite associations with incident CVD events.

Hydroxychloroquine and Chloroquine-Induced Cardiac Arrhythmias and Sudden Cardiac Death in Patients with Systemic Autoimmune Rheumatic Diseases: A Systematic Review and Meta-Analysis.

Hydroxychloroquine (HCQ) and chloroquine (CQ) are foundational treatments for several systemic autoimmune rheumatic diseases, including systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA). Concerns regarding the risk of cardiac arrhythmia and death have been raised, yet the burden of HCQ and CQ-related cardiac toxicities remains unclear. A systematic literature search was conducted in the MEDLINE and Embase databases for articles published between the earliest date and April 2023 reporting cardiac conduction abnormalities in patients with systemic autoimmune rheumatic diseases taking HCQ or CQ. Meta-analysis was performed to calculate the difference in mean QTc and odds ratio of prolonged QTc in those taking HCQ or CQ versus not. Of 2673 unique records, 34 met the inclusion criteria, including 70,609 subjects. Thirty-three studies reported outcomes in HCQ and 9 in CQ. Five studies reported outcomes in RA, 11 in SLE, and 18 in populations with mixed rheumatic diseases. Eleven studies reported mean QTc and OR for prolonged QTc for meta-analysis, all reporting outcomes in HCQ. There was a significant increase in mean QTc among HCQ users in patients with RA (10.29 ms, p = 0.458). There was no difference in mean QTc between HCQ and non-HCQ users in other systemic autoimmune rheumatic diseases. When rheumatic diseases were pooled, HCQ users were more likely to have prolonged QTc (odds ratio 1.57, 95%CI: 1.19, 2.08). QTc prolongation was more likely in patients with systemic autoimmune rheumatic diseases. Clinicians should be aware of potential adverse cardiac events of HCQ and consider QTc monitoring.

Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes.

OBJECTIVES: A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes. METHODS: Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset. RESULTS: Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2. CONCLUSION: Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.

The link between post-traumatic stress disorder and systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a heterogeneous, multisystem autoimmune disorder characterized by unpredictable disease flares. Although the pathogenesis of SLE is complex, an epidemiologic link between posttraumatic stress disorder (PTSD) and the development of SLE has been identified, suggesting that stress-related disorders alter the susceptibility to SLE. Despite the strong epidemiologic evidence connecting PTSD and SLE, gaps remain in our understanding of how the two may be connected. Perturbations in the autonomic nervous system, neuroendocrine system, and at the genomic level may cause and sustain immune dysregulation that could lower the threshold for the development and propagation of SLE. We first describe shared risk factors for SLE and PTSD. We then describe potential biological pathways which may facilitate excessive inflammation in the context of PTSD. Among those genetically predisposed to SLE, systemic inflammation that accompanies chronic stress may fan the flames of smoldering SLE by priming immune pathways. Further studies on the connection between trauma and inflammation will provide important data on pathogenesis, risk factors, and novel treatments for SLE.

Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes.

AIMS/HYPOTHESIS: Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes. METHODS: Within three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified. RESULTS: We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05). CONCLUSIONS/INTERPRETATION: Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.

The role of environmental exposures and gene-environment interactions in the etiology of systemic lupus erythematous.

Systemic lupus erythematosus (SLE) is a complex, chronic autoimmune disease, whose etiology includes both genetic and environmental factors. Individual genetic risk factors likely only account for about one-third of observed heritability among individuals with a family history of SLE. A large portion of the remaining risk may be attributable to environmental exposures and gene-environment interactions. This review focuses on SLE risk associated with environmental factors, ranging from chemical and physical environmental exposures to lifestyle behaviors, with the weight of evidence supporting positive associations between SLE and occupational exposure to crystalline silica, current smoking, and exogenous estrogens (e.g., oral contraceptives and postmenopausal hormones). Other risk factors may include lifestyle behaviors (e.g., dietary intake and sleep) and other exposures (e.g., ultraviolet [UV] radiation, air pollution, solvents, pesticides, vaccines and medications, and infections). Alcohol use may be associated with decreased SLE risk. We also describe the more limited body of knowledge on gene-environment interactions and SLE risk, including IL-10, ESR1, IL-33, ITGAM, and NAT2 and observed interactions with smoking, UV exposure, and alcohol. Understanding genetic and environmental risk factors for SLE, and how they may interact, can help to elucidate SLE pathogenesis and its clinical heterogeneity. Ultimately, this knowledge may facilitate the development of preventive interventions that address modifiable risk factors in susceptible individuals and vulnerable populations.

Longitudinal analysis of ANA in the Systemic Lupus International Collaborating Clinics (SLICC) Inception Cohort.

OBJECTIVES: A perception derived from cross-sectional studies of small systemic lupus erythematosus (SLE) cohorts is that there is a marked discrepancy between antinuclear antibody (ANA) assays, which impacts on clinicians' approach to diagnosis and follow-up. We compared three ANA assays in a longitudinal analysis of a large international incident SLE cohort retested regularly and followed for 5 years. METHODS: Demographic, clinical and serological data was from 805 SLE patients at enrolment, year 3 and 5. Two HEp-2 indirect immunofluorescence assays (IFA1, IFA2), an ANA ELISA, and SLE-related autoantibodies were performed in one laboratory. Frequencies of positivity, titres or absorbance units (AU), and IFA patterns were compared using McNemar, Wilcoxon and kappa statistics, respectively. RESULTS: At enrolment, ANA positivity (≥1:80) was 96.1% by IFA1 (median titre 1:1280 (IQR 1:640-1:5120)), 98.3% by IFA2 (1:2560 (IQR 1:640-1:5120)) and 96.6% by ELISA (176.3 AU (IQR 106.4 AU-203.5 AU)). At least one ANA assay was positive for 99.6% of patients at enrolment. At year 5, ANA positivity by IFAs (IFA1 95.2%; IFA2 98.9%) remained high, while there was a decrease in ELISA positivity (91.3%, p<0.001). Overall, there was >91% agreement in ANA positivity at all time points and ≥71% agreement in IFA patterns between IFA1 and IFA2. CONCLUSION: In recent-onset SLE, three ANA assays demonstrated commutability with a high proportion of positivity and titres or AU. However, over 5 years follow-up, there was modest variation in ANA assay performance. In clinical situations where the SLE diagnosis is being considered, a negative test by either the ELISA or HEp-2 IFA may require reflex testing.

Advances in SLE classification criteria.

This year, the American College of Rheumatology (ACR) 1982 classification criteria for systemic lupus erythematosus (SLE) celebrate their 40th anniversary. From this start, the quest for optimal SLE criteria has led to the 1997 ACR update, the 2012 publication of the Systemic Lupus International Collaborating Clinics (SLICC) criteria, and, in 2019, the European League Against Rheumatism (EULAR)/ACR classification criteria. The latter have since been externally validated in more than two dozen studies and have become the gold standard inclusion criterion of SLE clinical trials. This comprehensive review attempts to follow the evolving success story of SLE classification, highlighting relevant decisions and their rationale, and discussing consequences for the way SLE is defined and managed.

Long-term weight changes and risk of rheumatoid arthritis among women in a prospective cohort: a marginal structural model approach.

OBJECTIVE: To examine the association of long-term weight change with RA risk in a large prospective cohort study. METHODS: The Nurses' Health Study II started in 1989 (baseline); after exclusions, we studied 108 505 women 25-42 years old without RA. Incident RA was reported by participants and confirmed by medical record review. Body weight was reported biennially through 2015. We investigated two time-varying exposures: weight changes from baseline and from age 18; change was divided into five categories. We used a marginal structural model approach to account for time-varying weight change and covariates. RESULTS: Over 2 583 266 person-years, with a median follow-up time of 25.3 years, 541 women developed RA. Compared with women with stable weight from baseline, weight change was significantly associated with increased RA risk [weight gain 2-<10 kg: RR = 1.98 (95% CI 1.38, 2.85); 10-<20 kg: RR = 3.28 (95% CI 2.20, 4.89); ≥20 kg: RR = 3.81 (95% CI 2.39, 6.07); and weight loss >2 kg: RR = 2.05 (95% CI 1.28, 3.28)]. Weight gain of 10 kg or more from age 18 compared with stable weight was also associated with increased RA risk [10-< 20 kg: RR = 2.12 (95% CI 1.37, 3.27), ≥20 kg: RR = 2.31 (95% CI 1.50, 3.56)]. Consistent findings were observed for seropositive and seronegative RA. CONCLUSION: Long-term weight gain was strongly associated with increased RA risk in women, with weight gain of ≥20 kg associated with more than a three-fold increased RA risk. Maintenance of healthy weight may be a strategy to prevent or delay RA.

Exploration of machine learning methods to predict systemic lupus erythematosus hospitalizations.

OBJECTIVES: Systemic lupus erythematosus (SLE) is a heterogeneous disease characterized by disease flares which can require hospitalization. Our objective was to apply machine learning methods to predict hospitalizations for SLE from electronic health record (EHR) data. METHODS: We identified patients with SLE in a longitudinal EHR-based cohort with ≥2 outpatient rheumatology visits between 2012 and 2019. We applied multiple machine learning methods to predict hospitalizations with a primary diagnosis code for SLE, including decision tree, random forest, naive Bayes, logistic regression, and an ensemble method. Candidate predictors were derived from structured EHR features, including demographics, laboratory tests, medications, ICD-9/10 codes for SLE manifestations, and healthcare utilization. We used two approaches to assess these variables over longitudinal follow-up, including the incorporation of lagged features to capture changes over time of clinical data. The performance of each model was evaluated by overall accuracy, the F statistic, and the area under the receiver operator curve (AUC). RESULTS: We identified 1996 patients with SLE. 4.6% were hospitalized for SLE in their most recent year of follow-up. Random forest models had highest performance in predicting SLE hospitalizations, with AUC 0.751 and AUC 0.772 for two approaches (averaging and progressive), respectively. The leading predictors of SLE hospitalizations included dsDNA positivity, C3 level, blood cell counts, and inflammatory markers as well as age and albumin. CONCLUSION: We have demonstrated that machine learning methods can predict SLE hospitalizations. We identified key predictors of these events including known markers of SLE disease activity; further validation in external cohorts is warranted.

Real-world impact of flaring on patient-reported outcomes and healthcare resource utilisation in systemic lupus erythematosus.

OBJECTIVES: We investigated the association of SLE flares with patient-reported outcomes (PRO) and healthcare resource utilisation (HCRU) using real-world data. METHODS: Rheumatologists from the USA, France, Germany, Spain, Italy provided demographic, clinical, and HCRU data for patients with SLE, who provided PRO data. "Flaring" was defined as ≥1 rheumatologist-reported flare in the past 12 months. Demographic/clinical data were analysed descriptively, and findings compared statistically by flaring status. Logistic regression estimated a propensity score for flaring based on ethnicity, disease duration, and severity at diagnosis. Propensity score-matched flaring and non-flaring patients were compared for their HCRU, PROs, income loss and treatment satisfaction. RESULTS: Physicians (n=263) provided data for 1,278 patients (408 flaring/870 non-flaring); 729 patients (241 flaring/488 non-flaring) provided matched patient data. Patients had a mean 2.1 flares in the previous 12 months. Propensity score matched analyses indicated worse outcomes and greater HCRU in the past 12 months in flaring than non-flaring patients: EuroQoL 5D-3L Utility Index: 0.72 vs. 0.83; Functional Assessment of Chronic Illness Therapy-Fatigue scale: 30.06 vs. 36.48; Work Productivity and Activity Impairment Index: absenteeism 5.87% vs. 2.53% / presenteeism 33.44% vs. 19.16% / overall work impairment 35.98% vs. 20.66% / total activity impairment 42.47% vs. 30.23%; healthcare consultations (8.10 vs. 6.41), hospitalisations (24.26 vs. 7.63), emergency department visits (20.83 vs. 4.19), tests (46.59 vs. 38.90); current medications (2.76 vs. 2.19) (all p<0.001 except absenteeism, p=0.004). CONCLUSIONS: Similar flaring SLE patients had worse PROs and higher HCRU than non-flaring patients, underscoring the need for more effective strategies and treatments to alleviate or prevent flaring.

Prevalence of ECG testing and characteristics among new hydroxychloroquine and chloroquine users within a multi-center tertiary care center.

COVID-19 raised concern regarding cardiotoxicity and QTc prolongation of hydroxychloroquine (HCQ) and chloroquine (CQ). We examined the frequency and patient factors associated with ECG testing and the detection of prolonged QTc among new HCQ/CQ users in a large academic medical system. 10,248 subjects with a first HCQ/CQ prescription (1/2015-3/2020) were included. We assessed baseline (1 year prior to and including day of initiation of HCQ/CQ through 2 months after initial HCQ/CQ prescription) and follow-up (10 months after the baseline period) patient characteristics and ECGs obtained from electronic health records. Among 8384 female HCQ/CQ new users, ECGs were obtained for 22.3%, 14.3%, and 7.6%, at baseline, follow, and both periods, respectively. Among 1864 male HCQ/CQ new users, ECGs were obtained more frequently at baseline (29.7%), follow-up (18.0%), and both periods (11.3%). Female HCQ/CQ users with a normal QTc at baseline but prolonged QTc (> 470 ms) at follow-up (13.1%) were older at HCQ/CQ initiation [mean 64.7 (SD 16.5) vs. 58.7 (SD 16.9) years, p = 0.004] and more likely to have history of myocardial infarction (41.0% vs. 21.6%, p = 0.0003) compared to those who had normal baseline and follow-up QTc. The frequency of prolonged QTc development was similar (12.4%) among male HCQ/CQ new users (> 450 ms). Prior to COVID-19, ECG testing before and after HCQ/CQ prescription was infrequent, particularly for females who are disproportionately affected by rheumatic diseases and were just as likely to develop prolonged QTc (> 1/10 new users). Prospective studies are needed to guide future management of HCQ/CQ therapy in rheumatic populations.

Impact of reported NSAID "allergies" on opioid use disorder in back pain.

BACKGROUND: It is crucial to identify patients at highest risk for opioid use disorder (OUD) and to address challenges in reducing opioid use. Reported nonsteroidal anti-inflammatory drug (NSAID) allergies may predispose to use of stronger pain medications and potentially to OUD. OBJECTIVE: We sought to investigate the clinical impact of reported NSAID allergy on OUD in patients with chronic back pain. METHODS: We conducted a retrospective study of adults receiving care at a tertiary health care system from January 1, 2013, to December 31, 2018. Back pain and OUD were identified using administrative data algorithms. We used propensity score matching and logistic regression to estimate the impact of self-reported NSAID adverse drug reactions (ADRs) on risk of OUD, adjusting for other relevant clinical information. RESULTS: Of 47,114 patients with chronic back pain, 3,620 (7.7%) had a reported NSAID ADR. In an adjusted propensity score-matched analysis, patients with NSAID ADRs had higher odds (odds ratio, 1.34; 95% CI, 1.07-1.67) of developing OUD as compared with those without NSAID ADRs. Additional risk factors for OUD included younger age, male sex, Medicaid insurance, Medicare insurance, higher number of inpatient and outpatient visits in the previous year, and comorbid anxiety and depression. Patients with listed NSAID ADRs also had higher odds of a documented opioid prescription during the study period (odds ratio, 1.22; 95% CI, 1.11-1.34). CONCLUSIONS: Adults with chronic back pain and reported NSAID ADRs are at a higher risk of developing OUD and receiving opioid analgesics, even after accounting for comorbidities and health care utilization. Allergy evaluation is critical for potential delabeling of patients with reported NSAID allergies and chronic pain.

Circulating blood metabolite trajectories and risk of rheumatoid arthritis among military personnel in the Department of Defense Biorepository.

OBJECTIVES: We sought to identify metabolic changes potentially related to rheumatoid arthritis (RA) pathogenesis occurring in the blood prior to its diagnosis. METHODS: In a US military biorepository, serum samples collected at two timepoints prior to a diagnosis of RA were identified. These were matched to controls who did not develop RA by subject age, race and time between sample collections and RA diagnosis time to stored serum samples. Relative abundances of 380 metabolites were measured using liquid chromatography-tandem mass spectrometry. We determined whether pre-RA case versus control status predicted metabolite concentration differences and differences over time (trajectories) using linear mixed models, assessing for interactions between time, pre-RA status and metabolite concentrations. We separately examined pre-RA and pre-seropositive RA cases versus matched controls and adjusted for smoking. Multiple comparison adjustment set the false discovery rate to 0.05. RESULTS: 291 pre-RA cases (80.8% pre seropositive RA) were matched to 292 controls, all with two serum samples (2.7±1.6 years; 1.0±0.9 years before RA/matched date). 52.0% were women; 52.8% were White, 26.8% Black and 20.4% other race. Mean age was 31.2 (±8.1) years at earliest blood draw. Fourteen metabolites had statistically significant trajectory differences among pre-RA subjects versus controls, including sex steroids, amino acid/lipid metabolism and xenobiotics. Results were similar when limited to pre seropositive RA and after adjusting for smoking. CONCLUSIONS: In this military case-control study, metabolite concentration trajectory differences in pre-RA cases versus controls implicated steroidogenesis, lipid/amino acid metabolism and xenobiotics in RA pathogenesis. Metabolites may have potential as biomarkers and/or therapeutic targets preceding RA diagnosis.

Comparative risks of cardiovascular disease events among SLE patients receiving immunosuppressive medications.

OBJECTIVES: SLE patients have elevated cardiovascular disease (CVD) risk, but it is unclear whether this risk is affected by choice of immunosuppressive drug. We compared CVD risks among SLE patients starting MMF, CYC or AZA. METHODS: Using Medicaid Analytic eXtract (2000-2012), adult SLE patients starting MMF, CYC or AZA were identified and propensity scores (PS) were estimated for receipt of MMF vs CYC and MMF vs AZA. We examined rates of first CVD event (primary outcome), all-cause mortality, and a composite of first CVD event and all-cause mortality (secondary outcomes). After 1:1 PS-matching, Fine-Gray regression models estimated subdistribution hazard ratios (HRs.d.) for risk of CVD events. Cox regression models estimated HRs for all-cause mortality. The primary analysis was as-treated; 6- and 12-month intention-to-treat (ITT) analyses were secondary. RESULTS: We studied 680 PS-matched pairs of patients with SLE initiating MMF vs CYC and 1871 pairs initiating MMF vs AZA. Risk of first CVD event was non-significantly reduced for MMF vs CYC [HRs.d 0.72 (95% CI: 0.37, 1.39)] and for MMF vs AZA [HRs.d 0.88 (95% CI: 0.59, 1.32)] groups. In the 12-month ITT, first CVD event risk was lower among MMF than AZA new users [HRs.d 0.68 (95% CI: 0.47, 0.98)]. CONCLUSION: In this head-to-head PS-matched analysis, CVD event risks among SLE patients starting MMF vs CYC or AZA were not statistically reduced except in one 12-month ITT analysis of MMF vs AZA, suggesting longer-term use may convey benefit. Further studies of potential cardioprotective benefit of MMF are necessary.

A prospective study of reproductive factors in relation to risk of systemic lupus erythematosus among black women.

OBJECTIVE: Systemic lupus erythematosus (SLE) occurs most commonly among reproductive age women, compatible with a potential role of reproductive factors, although past studies including women of mainly European ancestry have yielded conflicting results. We assessed relationships of reproductive factors to SLE risk among black women. METHODS: We followed 58,243 participants in the Black Women's Health Study (BWHS) from 1995 - 2015 using biennial health questionnaires, on which participants reported reproductive and other factors. Self-reported incident SLE cases were confirmed as meeting 1997 American College of Rheumatology SLE classification criteria by medical record review. Cox proportional hazards regression models were used to estimate hazard ratios (HR) and 95% confidence intervals (95% CI) for SLE for several reproductive factors, controlling for potential confounders. RESULTS: During 954,476 person-years of follow-up, 125 incident cases of SLE were confirmed. Later age at menarche and longer duration of breast feeding were associated with increased risk of SLE. The multivariable HRs were 2.31 (95% CI, 1.30-4.11) for age at menarche ≥15 relative to age 12, and 1.73 (95% CI, 1.01-2.94) for breast feeding ≥6 months relative to none. There were no clear associations with parity, age at first birth, menopausal status, hysterectomy, age at menopause, or history of endometriosis. CONCLUSION: Our results suggest that later menarchal age and breastfeeding of infants for ≥6 months vs. none may be associated with increased SLE risk among black women, while other reproductive factors did not appear related. The biological mechanisms underlying these potential associations should be pursued.

Patient experiences and strategies for coping with SLE: A qualitative study.

OBJECTIVE: This study explored challenges that patients with systemic lupus erythematosus (SLE) and childhood-onset SLE (cSLE) face to identify modifiable influences and coping strategies in patient experiences. METHODS: Participants were recruited from two academic medical centers through a Lupus Registry of individuals ≥18 years old and ≥4 1997 ACR classification criteria for SLE and a centralized data repository of cSLE patients, and participated in three focus groups. Transcripts were coded thematically and adjudicated by two independent reviewers. RESULTS: Thirteen adults, 7 (54%) with cSLE, participated in focus groups. Themes were categorized into two domains: (1) challenges with SLE diagnosis and management; and (2) patient coping strategies and modifiable factors of the SLE experience. Participants identified five primary challenges: diagnostic odyssey, public versus private face of SLE, SLE-related stresses, medication adherence, and transitioning from pediatric to adult care. Coping strategies and modifiable factors included social support, open communication about SLE, and strong patient-provider relationships. Several participants highlighted positive lessons learned through their experiences with SLE, including empathy, resilience, and self-care skills. CONCLUSIONS: Patients with cSLE and SLE identified common challenges, modifying influences and coping strategies based on personal experiences. A strong patient-provider relationship and trust in the medical team emerged as key modifiable factors. Deriving optimism from experiences with SLE was unique to several patients diagnosed as children or young adults. Leveraging factors that improved the participants' experiences living with SLE may be used in future studies to address vulnerabilities in care.

The Mediterranean diet, plasma metabolome, and cardiovascular disease risk.

AIMS: To investigate whether metabolic signature composed of multiple plasma metabolites can be used to characterize adherence and metabolic response to the Mediterranean diet and whether such a metabolic signature is associated with cardiovascular disease (CVD) risk. METHODS AND RESULTS: Our primary study cohort included 1859 participants from the Spanish PREDIMED trial, and validation cohorts included 6868 participants from the US Nurses' Health Studies I and II, and Health Professionals Follow-up Study (NHS/HPFS). Adherence to the Mediterranean diet was assessed using a validated Mediterranean Diet Adherence Screener (MEDAS), and plasma metabolome was profiled by liquid chromatography-tandem mass spectrometry. We observed substantial metabolomic variation with respect to Mediterranean diet adherence, with nearly one-third of the assayed metabolites significantly associated with MEDAS (false discovery rate < 0.05). Using elastic net regularized regressions, we identified a metabolic signature, comprised of 67 metabolites, robustly correlated with Mediterranean diet adherence in both PREDIMED and NHS/HPFS (r = 0.28-0.37 between the signature and MEDAS; P = 3 × 10-35 to 4 × 10-118). In multivariable Cox regressions, the metabolic signature showed a significant inverse association with CVD incidence after adjusting for known risk factors (PREDIMED: hazard ratio [HR] per standard deviation increment in the signature = 0.71, P < 0.001; NHS/HPFS: HR = 0.85, P = 0.001), and the association persisted after further adjustment for MEDAS scores (PREDIMED: HR = 0.73, P = 0.004; NHS/HPFS: HR = 0.85, P = 0.004). Further genome-wide association analysis revealed that the metabolic signature was significantly associated with genetic loci involved in fatty acids and amino acids metabolism. Mendelian randomization analyses showed that the genetically inferred metabolic signature was significantly associated with risk of coronary heart disease (CHD) and stroke (odds ratios per SD increment in the genetically inferred metabolic signature = 0.92 for CHD and 0.91 for stroke; P < 0.001). CONCLUSIONS: We identified a metabolic signature that robustly reflects adherence and metabolic response to a Mediterranean diet, and predicts future CVD risk independent of traditional risk factors, in Spanish and US cohorts.

Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes.

Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.