My background in Medicine, Immunology, and Genetics make a unique combination and provide me with the tools I need to carry out this project successfully. For over 20 years of my research career, I have focused on the identification of the genetic basis of SLE as a first building block toward understanding how such genes lead to cellular abnormalities that eventually lead to clinical disease. In this context, animal models provide possibilities where human studies have limitations. The main goal of my research is to understand the mechanisms behind disease pathogenesis, identify new biomarkers for disease, find new therapeutic targets, understand the mechanisms of response and non-response to therapies, and define the heterogeneity of SLE. I am totally committed to the work for lupus and other autoimmune diseases, and I believe that only through careful longitudinal analysis of the patients, and proper molecular analyses, will we be able to understand this disease. I am focusing importantly on systems biology approaches, -omics data integration and clustering, scRNASeq, and other omics methods and bioinformatics approaches to the understanding of SLE.
With the advent of genome-wide association arrays and the creation of the SLEGEN consortium, new possibilities opened for the study of the genetics of lupus and the identification of genes for the disease. As a founder member of SLEGEN, I participated in the GWAS that identified several new genes, but also had an independent study that allowed my identification of BANK1, and participated in the identification of ITGAM. These papers were all published in the same issue of Nat Genet. In collaboration with Tim Vyse and John Rioux we embarked on a larger GWAS in Europeans that resulted in a top publication in Nat Genet and we have done the same by publishing the first GWAS in the Hispanic admixed population focusing on the Native American ancestry. More recently our transancestral immunochip study was published. Recently, I focused on rare variants: through exome sequencing of families with multiple cases of lupus, and using very stringent imputation approaches and aggregate analyses to identify candidate genes.
From here, my work has derived from the use of genomics methods for the reclassification of systemic autoimmune diseases and systems biology approaches with the idea that autoimmune diseases are a clinical constellation of the same or nearly similar disease processes. Our most recent publications point towards those approaches by creating software and performing analyses of gene expression data to identify drug targets and learning systems medicine methods for clustering patients. Our first work focuses on lupus, but is planned to extend to other related autoimmune diseases. As PI of the PRECISESADS project, a high degree of coordination has been necessary. In this role, I have acquired enormous experience in the organization of large projects and recruitment of patients, most recent ethical rules. I have also acquired learning on the subject of machine learning bioinformatic methods, clustering and classification of autoimmune diseases, and QTL analyses across autoimmune diseases.
A second path relates to the use of animal models for testing potential new drug targets, new genes, and specific hypotheses. We have now obtained extensive experience in such models and are defining those that may be more effective in testing given systems. We have focused on TLR7 due to the importance of this pathway in autoimmunity and in the genes we have studied, such as BANK1. We have also used biochemistry to understand the function of BANK1.