Risk prediction models for incident systemic lupus erythematosus among women in the Nurses' health study cohorts using genetics, family history, and lifestyle and environmental factors

Breaking research silos to achieve equitable precision medicine in rheumatology

Health disparities in rheumatic disease are well established and urgently need addressing. Obstacles to precision medicine equity span both the clinical and the research domains, with a focus placed on structural barriers limiting equitable health care access and inclusivity in research. Less articulated factors include the use of inaccurate population descriptors and the existence of research silos in rheumatology research, which creates a knowledge gap that precludes addressing the health disparities and fulfilling the goals of precision medicine to understand the 'full patient'. The biopsychosocial model is a research framework that intertwines layers of biological and environmental effects to understand disease. However, very limited rheumatology research bridges across molecular and epidemiological studies of environmental exposures, such as physical and social determinants of health. In this Review, we discuss clinical obstacles to health care equity, including access to health care and the use of inaccurate language when labelling population groups. We explore the goals and data needed for research under the biopsychosocial model. We describe results from a rheumatic disease literature search that highlights the paucity of studies investigating the molecular influences of systemic exposures. We conclude with a list of considerations and recommendations to help achieve equitable precision medicine.

Ultraprocessed Food Intake and Risk of Systemic Lupus Erythematosus Among Women Observed in the Nurses' Health Study Cohorts

OBJECTIVE

We assessed ultraprocessed food (UPF) intake and systemic lupus erythematosus (SLE) incidence within the prospective Nurses' Health Study (NHS) cohorts.

METHODS

A total of 204,175 women were observed (NHS 1984-2016; NHSII 1991-2017). Semiquantitative food frequency questionnaires were completed every two to four years. UPF intake was determined as per the Nova classification. Nurses self-reported new doctor-diagnosed SLE, confirmed by medical records. Time-varying Cox regressions estimated hazard ratios (HRs; 95% confidence intervals [CIs]) for patients with incident SLE and SLE by anti-double-stranded DNA (dsDNA) antibody at diagnosis, according to cumulatively updated daily (a) UPF servings, (b) total intake (in grams and milliliters), and (c) percentage of total intake. Analyses adjusted for age, race, cohort, caloric and alcohol intakes, household income, smoking, body mass index (BMI), physical activity, menarchal age, and oral contraceptive use. We tested for interaction with BMI and examined UPF categories.

RESULTS

Mean baseline age was ~50 years (NHS) and ~36 years (NHSII); 93% self-reported White race. A total of 212 patients with incident SLE were identified. SLE risk was higher in the third versus first UPF tertile (servings per day pooled multivariable [MV] HR 1.56, 95% CI 1.04-2.32; P = 0.03). Results were stronger for dsDNA antibody in patients with SLE (servings per day pooled MV HR 2.05, 95% CI 1.15-3.65; P = 0.01) and for absolute (servings or total) than percentage of total intake. Sugar-sweetened/artificially sweetened beverages were associated with SLE risk (third vs first tertile MV HR 1.45, 95% CI 1.01-2.09). No BMI interactions were observed.

CONCLUSION

Higher cumulative average daily UPF intake was associated with >50% increased SLE risk and with doubled risk for anti-dsDNA antibody in patients with SLE. Many deleterious effects on systemic inflammation and immunity are postulated.

[Between the normal and the pathological: The concept of pre-disease applied to systemic autoimmune rheumatic diseases]

The incidence of systemic autoimmune diseases is constantly rising. They are chronic diseases requiring prolonged treatment, with considerable psychosocial impact. While attention to the promising results obtained with CAR-T cells in refractory patients is justified, it seems important not to overlook the opportunities for prevention based on the identification of a pre-disease state. After clarifying the various stages that make up this pre-disease state, using the prototypical example of systemic lupus erythematosus, we will apply a transdisciplinary and transpathological approach to describe comparatively recent data obtained for other systemic autoimmune diseases (rheumatoid arthritis, Sjögren's syndrome and systemic scleroderma). We will then discuss the practical implications of this new paradigm in the typical consultation of a potentially "pre-sick" individual, and on the prospects opened up by this new paradigm in care and research.

Development of a predictive model for systemic lupus erythematosus incidence risk based on environmental exposure factors

OBJECTIVE

Systemic lupus erythematosus (SLE) is an autoimmune disease characterised by a loss of immune tolerance, affecting multiple organs and significantly impairing patients' health and quality of life. While hereditary elements are essential in the onset of SLE, external environmental influences are also significant. Currently, there are few predictive models for SLE that takes into account the impact of occupational and living environmental exposures. Therefore, we collected basic information, occupational background and living environmental exposure data from patients with SLE to construct a predictive model that facilitates easier intervention.

METHODS

We conducted a study comparing 316 individuals diagnosed with SLE and 851 healthy volunteers in a case-control design, collecting their basic information, occupational exposure history and environmental exposure data. Subjects were randomly allocated into training and validation groups using a 70/30 split. Using three-feature selection methods, we constructed four predictive models with multivariate logistic regression. Model performance and clinical utility were evaluated via receiver operating characteristic, calibration and decision curves. Leave-one-out cross-validation further validated the models. The best model was used to create a dynamic nomogram, visually representing the predicted relative risk of SLE onset.

RESULTS

The ForestMDG model demonstrated strong predictive ability, with an area under the curve of 0.903 (95% CI 0.880 to 0.925) in the training set and 0.851 (95% CI 0.809 to 0.894) in the validation set, as indicated by model performance evaluation. Calibration and decision curves demonstrated accurate results along with practical clinical value. Leave-one-out cross-validation confirmed that the ForestMDG model had the best accuracy (0.8338). Finally, we developed a dynamic nomogram for practical use, which is accessible via the following link: https://yingzhang99321.shinyapps.io/dynnomapp/.

CONCLUSION

We created a user-friendly dynamic nomogram for predicting the relative risk of SLE onset based on occupational and living environmental exposures.

TRIAL REGISTRATION NUMBER

ChiCTR2000038187.

Chimeric antigen receptor T cell therapy for autoimmune disease

Infusion of T cells engineered to express chimeric antigen receptors (CARs) that target B cells has proven to be a successful treatment for B cell malignancies. This success inspired the development of CAR T cells to selectively deplete or modulate the aberrant immune responses that underlie autoimmune disease. Promising results are emerging from clinical trials of CAR T cells targeting the B cell protein CD19 in patients with B cell-driven autoimmune diseases. Further approaches are being designed to extend the application and improve safety of CAR T cell therapy in the setting of autoimmunity, including the use of chimeric autoantibody receptors to selectively deplete autoantigen-specific B cells and the use of regulatory T cells engineered to express antigen-specific CARs for targeted immune modulation. Here, we highlight important considerations, such as optimal target cell populations, CAR construct design, acceptable toxicities and potential for lasting immune reset, that will inform the eventual safe adoption of CAR T cell therapy for the treatment of autoimmune diseases.

Immunopathogenesis of systemic lupus erythematosus: An update

Systemic lupus erythematosus (SLE) is a chronic systemic autoimmune disease characterized by dysregulated immune responses leading to widespread inflammation and damage in various organs. Environmental factors such as infections, hormonal influences and exposure to ultraviolet light can trigger the disease in genetically predisposed individuals. Genome-wide association studies have identified over 100 susceptibility loci linked to immune regulation, interferon (IFN) signaling and antigen presentation in SLE. In addition, rare cases of monogenic lupus have been instrumental in understanding critical underlying disease mechanisms. Several immunological abnormalities contribute to the loss of self-tolerance and the perpetuation of autoimmune responses in SLE. In particular, defective clearance of apoptotic cells due to defective phagocytosis and complement activation leads to accumulation of self-antigens. Dysregulated innate immune responses activate the adaptive immune system, amplifying the inflammatory response with an important role for type I IFNs. Abnormalities in B cell development and activation lead to the production of autoreactive antibodies, forming immune complexes that cause tissue damage. Similarly, disturbances in T-cell compartments, altered regulatory T-cell functions and altered cytokine production, particularly IFN-α, contribute to tissue damage. Understanding of the immunopathogenesis of SLE is evolving rapidly, with ongoing research identifying new molecular pathways and potential therapeutic targets. Future classifications of SLE are likely to be based on underlying biological pathways rather than clinical and serological signs alone. This review aims to provide a detailed update on the most recent findings regarding the immunopathogenesis of SLE, focusing on the variability of biological pathways and the implications for future therapeutic strategies, in particular chimeric antigen receptor T (CAR T) cells.

Environment and systemic autoimmune rheumatic diseases: an overview and future directions

Introduction

Despite progress in our understanding of disease pathogenesis for systemic autoimmune rheumatic diseases (SARD), these diseases are still associated with high morbidity, disability, and mortality. Much of the strongest evidence to date implicating environmental factors in the development of autoimmunity has been based on well-established, large, longitudinal prospective cohort studies.

Methods

Herein, we review the current state of knowledge on known environmental factors associated with the development of SARD and potential areas for future research.

Results

The risk attributable to any particular environmental factor ranges from 10-200%, but exposures are likely synergistic in altering the immune system in a complex interplay of epigenetics, hormonal factors, and the microbiome leading to systemic inflammation and eventual organ damage. To reduce or forestall the progression of autoimmunity, a better understanding of disease pathogenesis is still needed.

Conclusion

Owing to the complexity and multifactorial nature of autoimmune disease, machine learning, a type of artificial intelligence, is increasingly utilized as an approach to analyzing large datasets. Future studies that identify patients who are at high risk of developing autoimmune diseases for prevention trials are needed.

Predicting autoimmune diseases: A comprehensive review of classic biomarkers and advances in artificial intelligence

Autoimmune diseases comprise a spectrum of disorders characterized by the dysregulation of immune tolerance, resulting in tissue or organ damage and inflammation. Their prevalence has been on the rise, significantly impacting patients' quality of life and escalating healthcare costs. Consequently, the prediction of autoimmune diseases has recently garnered substantial interest among researchers. Despite their wide heterogeneity, many autoimmune diseases exhibit a consistent pattern of paraclinical findings that hold predictive value. From serum biomarkers to various machine learning approaches, the array of available methods has been continuously expanding. The emergence of artificial intelligence (AI) presents an exciting new range of possibilities, with notable advancements already underway. The ultimate objective should revolve around disease prevention across all levels. This review provides a comprehensive summary of the most recent data pertaining to the prediction of diverse autoimmune diseases and encompasses both traditional biomarkers and the latest innovations in AI.

Choosing to End African American Health Disparities in Patients With Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is three times more common and its manifestations are more severe in African American women compared to women of other races. It is not clear whether this is due to genetic differences or factors related to the physical or social environments, differences in health care, or a combination of these factors. Health disparities in patients with SLE between African American patients and persons of other races have been reported since the 1960s and are correlated with measures of lower socioeconomic status. Risk factors for these disparities have been demonstrated, but whether their mitigation improves outcomes for African American patients has not been tested except in self-efficacy. In 2002, the first true US population-based study of patients with SLE with death certificate records was conducted, which demonstrated a wide disparity between the number of African American women and White women dying from SLE. Five years ago, another study showed that SLE mortality rates in the United States had improved but that the African American patient mortality disparity persisted. Between 2014 and 2021, one study demonstrated racism's deleterious effects in patients with SLE. Racism may have been the unmeasured confounder, the proverbial "elephant in the room"-unnamed and unstudied. The etymology of "risk factor" has evolved from environmental risk factors to social determinants to now include structural injustice/structural racism. Racism in the United States has a centuries-long existence and is deeply ingrained in US society, making its detection and resolution difficult. However, racism being man made means Man can choose to change the it. Health disparities in patients with SLE should be addressed by viewing health care as a basic human right. We offer a conceptual framework and goals for both individual and national actions.

Abnormal presentation of pregnancy and postpartum initial-onset systemic lupus erythematosus combined with diffuse alveolar hemorrhage: A case report

Systemic lupus erythematosus (SLE) is an autoimmune disease that most commonly occurs in women of childbearing age. However, cases of SLE with abnormal pregnancy as the initial manifestation, involving the development of diffuse alveolar hemorrhage (DAH), have rarely been reported. Herein, we report the case of a young woman who underwent a cesarean section for fetal distress and growth restriction at 35 + 1 weeks' gestation. Following discharge, she experienced progressive worsening of anemia and chest tightness, which was later diagnosed as SLE complicated by DAH.

Differential impact of environmental factors on systemic and localized autoimmunity

The influence of environmental factors on the development of autoimmune disease is being broadly investigated to better understand the multifactorial nature of autoimmune pathogenesis and to identify potential areas of intervention. Areas of particular interest include the influence of lifestyle, nutrition, and vitamin deficiencies on autoimmunity and chronic inflammation. In this review, we discuss how particular lifestyles and dietary patterns may contribute to or modulate autoimmunity. We explored this concept through a spectrum of several autoimmune diseases including Multiple Sclerosis (MS), Systemic Lupus Erythematosus (SLE) and Alopecia Areata (AA) affecting the central nervous system, whole body, and the hair follicles, respectively. A clear commonality between the autoimmune conditions of interest here is low Vitamin D, a well-researched hormone in the context of autoimmunity with pleiotropic immunomodulatory and anti-inflammatory effects. While low levels are often correlated with disease activity and progression in MS and AA, the relationship is less clear in SLE. Despite strong associations with autoimmunity, we lack conclusive evidence which elucidates its role in contributing to pathogenesis or simply as a result of chronic inflammation. In a similar vein, other vitamins impacting the development and course of these diseases are explored in this review, and overall diet and lifestyle. Recent work exploring the effects of dietary interventions on MS showed that a balanced diet was linked to improvement in clinical parameters, comorbid conditions, and overall quality of life for patients. In patients with MS, SLE and AA, certain diets and supplements are linked to lower incidence and improved symptoms. Conversely, obesity during adolescence was linked with higher incidence of MS while in SLE it was associated with organ damage. Autoimmunity is thought to emerge from the complex interplay between environmental factors and genetic background. Although the scope of this review focuses on environmental factors, it is imperative to elaborate the interaction between genetic susceptibility and environment due to the multifactorial origin of these disease. Here, we offer a comprehensive review about the influence of recent environmental and lifestyle factors on these autoimmune diseases and potential translation into therapeutic interventions.