Online

Raza, Abbas

Cellular, Molecular, and Biomedical Sciences Graduate Program

2020

Ph. D.

Our understanding of genetic predisposition to inflammatory and autoimmune diseases has been enhanced by large scale quantitative trait loci (QTL) linkage mapping and genome-wide association studies (GWAS). However, the resolution and interpretation of QTL linkage mapping or GWAS findings are limited. In this work, we complement genetic predictions for several human diseases including multiple sclerosis (MS) and systemic capillary leakage syndrome (SCLS) with genetic and functional data in model organisms to associate genes with phenotypes and diseases. Focusing on MS, an autoimmune inflammatory disease of the central nervous system (CNS), we experimentally tested the effect of three of the GWAS candidate genes (SLAMF1, SLAMF2 and SLAMF7) in the experimental autoimmune encephalomyelitis (EAE) mouse model and found a male-specific locus distal to these loci regulating CNS autoimmune disease. Functional data in mouse suggests this male-specific locus modulates the frequency of immune cells including CD11b+, TCR[alpha beta]+CD4+Foxp3+, and TCR[alpha beta]+CD8+IL-17+ cells during EAE disease. Orchiectomy experiments demonstrate that this male specific phenotype is dependent on testis but not testosterone (T) or 5[alpha]-dihydrotestosterone (DHT). Using a bioinformatic approach, we identified SLAMF8 and SLAMF9 along with other differentially expressed genes in linkage with MS-GWAS predictions whose expression is testis-dependent, but not directly regulated by T or DHT, as potential positional candidates regulating CNS autoimmune disease. Further refinement of this locus is required to identify the causal gene(s) that may be targeted for prevention and/or treatment of MS in men. Using SCLS, an extremely rare disorder of unknown etiology characterized by recurrent episodes of vascular leakage, we identified and modeled this disease in an inbred mouse strain, SJL, using susceptibility to histamine- and infection-triggered vascular leak as the major phenotypic readout. This trait "Histamine hypersensitivity" (Histh/Histh) was mapped to a region on Chr 6. Remarkably, Histh is syntenic to the genomic locus most strongly associated with SCLS in humans (3p25.3). Subsequent studies found that the Histh locus is not unique to SJL but additional mouse strains also exhibit Histh phenotype. Considering GWAS studies in SCLS are limited by the small number of patients, we utilized interval-specific SNP-based association testing among Histh phenotyped mouse strains to predict Histh candidates. Furthermore, to dissect the complexity of Histh QTL, we developed network-based functional prediction methods to rank genes in this locus by predicting functional association with multiple Histh-related processes. The top-ranked genes include Cxcl12, Ret, Cacna1c, and Cntn3, all of which have strong functional associations and are proximal to SNPs segregating with Histh. Lastly, we utilized the power of integrating genetic and functional approaches to understand susceptibility to Bordetella pertussis and pertussis toxin (PTX) induced histamine sensitization (Bphs/Bphs), a sub-phenotype with an established role in autoimmunity. Congenic mapping in mice had earlier linked Bphs to histamine H1 receptor gene (Hrh1/H1R) and demonstrated that H1R differs at three amino acid residues in Bphs-susceptible and -resistant mice. Our subsequent studies identified eight inbred mouse strains that were susceptible to Bphs despite carrying a resistant H1R allele. Genetic analyses mapped the locus complementing Bphs to mouse Chr 6, in linkage disequilibrium with Hrh1; we have designated this Bphs-enhancer (Bphse). Similar to the approaches used for Histh, we utilized interval-specific SNP based association testing and network-based functional enrichment to predict nine candidate loci for Bphse including Atp2b2, Atg7, Pparg, Syn2, Ift122, Raf1, Mkrn2, Timp4 and Gt(ROSA)26Sor. Overall, these studies demonstrate the power of integrating genetic and functional methods in humans and animal models to predict highly plausible loci underlying QTL/GWAS data.