Predictive drivers of new onset, relapse, and progression of human autoimmunity in skin

人类皮肤自身免疫新发、复发和进展的预测驱动因素

• 批准号: 10658149
• 负责人: Manuel Garber
• 金额: $ 126.5万
• 依托单位: UNIV OF MASSACHUSETTS MED SCH WORCESTER
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-20 至 2028-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10658149
• 关键词: Affect; Age of Onset; Autoantibodies; Autoimmune Diseases; Autoimmunity; Biological Markers; Blood; Blood capillaries; Cells; Clinical; Clinical Management; Collection; Cutaneous Lupus Erythematosus; Data; Dermatologist; Development; Devices; Diagnosis; Disease; Disease Marker; Disease Progression; Engineering; Enrollment; Epithelial Cells; Exhibits; Face; Family member; Future; Gene Expression; Genetic; Genotype; Hazard Models; High Prevalence; Home; Human; Immune; Individual; Interferon Type I; Liquid substance; Longitudinal cohort; Lupus; Methods; Modeling; Molecular; Monitor; Morbidity - disease rate; Needles; Onset of illness; Organ; Participant; Patients; Physicians; Population; Populations at Risk; Prevalence; Property; Proteins; Proteomics; Public Health; Punch Biopsy; Questionnaires; Recurrent disease; Relapse; Reporting; Research Personnel; Risk; Sampling; Scientist; Scourge; Serum; Severity of illness; Skin; Statistical Models; Systemic Lupus Erythematosus; Systemic disease; Testing; Time; Tissue Sample; Tissues; UV induced; Vitiligo; Woman; biomarker identification; clinical diagnosis; cohort; design; health disparity; innovation; insight; interstitial; minimally invasive; mortality; multidisciplinary; multiple omics; pre-clinical; predictive modeling; prevent; response; sample collection; single-cell RNA sequencing; skin color; skin disorder; tool; transcriptome sequencing

ABSTRACT Autoimmune diseases affect up to 8% of the US population and their prevalence is rising, setting the stage for an impending public health crisis that we do not yet understand and are not prepared to face. Many autoimmune diseases disproportionately affect women and those with skin of color, potentially worsening existing health disparities within our population. We must define the mechanisms that drive this growing risk for autoimmunity so that we can better manage, or even prevent, a scourge of severe morbidity and mortality. Skin diseases are among the most prevalent autoimmune diseases and are simple to study due to the ability to diagnose and track the progression of disease through direct observation and sampling using minimally invasive tools. Thus, skin diseases provide unique insight into mechanisms of autoimmunity that are difficult to determine when studying other organs and tissues. We will leverage a multidisciplinary team of investigators, cutting edge tools designed for at-home, longitudinal tissue sampling, and an innovative strategy to discover how autoimmunity begins, relapses, and spreads in a large population of at-risk individuals. We and others have determined that unaffected, non-lesional skin from patients with autoimmunity exists in a disease-specific “preclinical” state, but whether this predisposes the patient to develop disease is an open question. We hypothesize that a molecular immune signature drives a preclinical state within the skin that predisposes to disease initiation and advancement of autoimmunity to other organs. To test this, we will use two ideally suited models of autoimmunity. To predict development of autoimmunity de novo as well as disease relapse, we will take advantage of the unique properties of vitiligo: a strong genetic component, early age of onset (majority <30 years old), strong association with other autoimmune diseases, high prevalence (>1%), and rapid relapse after stopping therapy. We will longitudinally monitor 200 individuals with vitiligo for disease relapse and 800 of their relatives who are “at-risk” for developing new onset disease. To predict the “progression” of autoimmunity to other organs we will monitor a cohort of patients with cutaneous lupus erythematosus (CLE): up to 20% of patients who initially exhibit skin-limited lupus eventually develop systemic disease, with a median time to progression of two years. We will monitor 50 subjects with CLE to detect disease progression to internal organs. We will use these innovative tools on a large scale through “population multiomics” to define immune drivers of autoimmunity in patients and their family members over time. To test our hypothesis, we will use computational integration of clinical, genetic, and molecular data points to define a “preclinical signature” of autoimmunity and use it to predict disease initiation and systemic progression. This approach will provide insight into autoimmunity that will help physicians better manage, or even prevent, devastating consequences of these diseases in the future.

摘要 自身免疫性疾病影响高达8%的美国人口，其患病率正在上升，为 一场我们还不了解也没有准备好面对的迫在眉睫的公共卫生危机。许多 自身免疫性疾病不成比例地影响女性和有色皮肤的人， 我们人口中存在的健康差距。我们必须定义驱动这种增长的机制 这样我们就可以更好地管理，甚至预防， and mortality.皮肤病是最普遍的自身免疫性疾病之一，研究起来也很简单 由于能够通过直接观察和采样来诊断和跟踪疾病的进展 使用微创工具。因此，皮肤病提供了独特的洞察机制的自身免疫 在研究其他器官和组织时很难确定。 我们将利用一个多学科的调查团队，为家庭，纵向 组织取样，以及一种创新的策略，以发现自身免疫如何开始，复发和传播， 大量高危人群。我们和其他人已经确定， 自身免疫患者存在于疾病特异性的“临床前”状态，但这是否会导致 病人是否会患病是一个悬而未决的问题。我们假设一种分子免疫信号 皮肤内的一种临床前状态，易导致疾病的发生和发展， 对其他器官的自身免疫为了验证这一点，我们将使用两种理想的自身免疫模型。预测 发展自身免疫从头以及疾病复发，我们将利用独特的 白癜风的特点：遗传成分强，发病年龄早（大多数<30岁）， 与其他自身免疫性疾病相关，患病率高（>1%），停止治疗后迅速复发。 我们将纵向监测200名白癜风患者的疾病复发情况和800名他们的亲属， “处于”发展为新发疾病的风险中。为了预测自身免疫对其他器官的“进展”，我们将 监测皮肤红斑狼疮（CLE）患者队列：高达20%的患者最初 表现出皮肤局限性狼疮的患者最终发展为全身性疾病，进展的中位时间为两年。 我们将监测50例CLE受试者，以检测疾病进展至内脏器官。 我们将通过“群体多组学”大规模使用这些创新工具， 随着时间的推移，患者及其家人的自身免疫驱动因素。为了验证我们的假设，我们将 使用临床、遗传和分子数据点的计算整合来定义“临床前 并将其用于预测疾病的发生和全身性进展。这 这种方法将提供对自身免疫的深入了解，这将有助于医生更好地管理，甚至预防， 这些疾病在未来的灾难性后果。