Integrative and trans-ethnic study to understand psoriasis associated signals

了解银屑病相关信号的综合和跨种族研究

• 批准号: 10657973
• 负责人: Lam Cheung Tsoi
• 金额: $ 37.83万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-21 至 2028-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10657973
• 关键词: ATAC-seq; Affect; African American population; African ancestry; Alleles; American; Biological; Biological Assay; Biological Markers; Bromouridine sequencing; CRISPR/Cas technology; Cells; Chromatin; Chromosome Mapping; Chronic; Clinical; Complex; Data; Development; Direct Costs; Disease; Disease model; Epigenetic Process; Ethnic Origin; Etiology; European; Facilities and Administrative Costs; Functional disorder; Gene Frequency; Genetic; Genetic Models; Genetic Transcription; Genetic Variation; Genetic study; Genomics; Genotype; Goals; Haplotypes; Heterogeneity; Heterozygote; Hi-C; IL17 gene; Immune; Immune System Diseases; Immune signaling; Individual; Inflammation; Inflammatory; Inflammatory Response; Machine Learning; Maps; Mediating; Mediator; Mission; Modeling; Molecular; Multiomic Data; Nucleic Acid Regulatory Sequences; Outcome; Pathogenesis; Pathogenicity; Pathologic; Pathology; Pathway interactions; Patient-Focused Outcomes; Patients; Persons; Pharmaceutical Preparations; Play; Population; Population Heterogeneity; Predisposition; Prevalence; Psoriasis; Public Health; Quantitative Trait Loci; Regulation; Research; Resolution; Resources; Role; Shapes; Signal Transduction; Skin; Susceptibility Gene; TNF gene; United States National Institutes of Health; Variant; Work; causal variant; cohort; comorbidity; cost; cytokine; design; disease disparity; disease heterogeneity; functional genomics; genetic architecture; genetic variant; genome wide association study; genomic data; high risk; high throughput technology; human disease; improved; inflammatory modulation; innovation; inter-individual variation; interleukin-23; keratinocyte; multi-ethnic; multimodality; multiple omics; precision medicine; predict clinical outcome; promoter; response; skin disorder; transcriptome; transcriptomics

PROJECT SUMMARY Psoriasis is a chronic immune-mediated skin disease that has a significant impact on public health, with annual direct and indirect costs over $75 billion dollars in the US. Advancements in high throughput technology have enabled the identification of genetic and genomic components in the Th17/IL-23 and NF𝜅B axes, associated with psoriasis pathology. Although >80 psoriasis susceptibility regions have been revealed, considerable challenges remain in narrowing down the causal genetic variations and discerning their pathological mechanisms that shape disease etiology. Similarly, while NF𝜅B signaling is involved in psoriasis and different skin immune disorders, we have very limited understanding of the mechanistic role genetic variants play in NF𝜅B regulation. With the new extended psoriasis GWAS emerging, psoriasis can serve as an ideal skin disease model to study this phenomenon in keratinocytes. Psoriasis has a prevalence rate of 1.3% among African Americans (AA), however most US-established genomics studies of psoriasis have been conducted on European American (EA) populations. Our preliminary data show that the fine-mapping of components can be facilitated by integrating genetic, epigenetic, and genomic information in a multi-ethnic analysis design, especially when including individuals with African ancestry. We have illustrated elevated NF𝜅B signaling response in keratinocytes among AA individuals and that inter-individual variations in inflammatory signature can have significant clinical implications for the assessment of drug response. The long-term goal of this project is to identify biological mechanisms for disease heterogeneity among psoriatic patients, and our overall objective is to utilize a trans- ethnic design to advance the identification of psoriasis-associated regulatory mechanisms involved in the modulation of NF𝜅B signaling in keratinocytes. We will apply an integrative approach to study multi-omics data and leverage trans-ethnic information to fine-map the genetic/genomic components associated with inter- individual inflammatory responses, providing a model to understand disease disparity among psoriatic patients of different ethnicities. We will i) fine-map the response expression quantitative trait loci (reQTLs) modulating NF𝜅B and other inflammatory signaling in keratinocytes; ii) determine regulatory mechanisms of psoriasis signal that drive NF𝜅B signaling in keratinocytes at the cellular level using multi-modal genomic data; iii) utilize genetic and genomic components participating in NF𝜅B signaling, to model clinical presentations and outcomes for patients from an ongoing longitudinal psoriasis cohort. Successful completion of the project will have an important positive impact by providing enhanced resolution and power to identify determinants of inter-individual variations in inflammatory responses.

项目总结