Investigation of Multiple Susceptibility Loci for Inflammatory Bowel Disease in an Italian Cohort of Patients

BACKGROUND: Recent GWAs and meta-analyses have outlined about 100 susceptibility genes/loci for inflammatory bowel diseases (IBD). In this study we aimed to investigate the influence of SNPs tagging the genes/loci PTGER4, TNFSF15, NKX2-3, ZNF365, IFNG, PTPN2, PSMG1, and HLA in a large pediatric- and adult-onset IBD Italian cohort. METHODS: Eight SNPs were assessed in 1,070 Crohn's disease (CD), 1,213 ulcerative colitis (UC), 557 of whom being diagnosed at the age of ≤16 years, and 789 healthy controls. Correlations with sub-phenotypes and major variants of NOD2 gene were investigated. RESULTS: The SNPs tagging the TNFSF15, NKX2-3, ZNF365, and PTPN2 genes were associated with CD (P values ranging from 0.037 to 7×10(-6)). The SNPs tagging the PTGER4, NKX2-3, ZNF365, IFNG, PSMG1, and HLA area were associated with UC (P values 0.047 to 4×10(-5)). In the pediatric cohort the associations of TNFSF15, NKX2-3 with CD, and PTGER4, NKX2-3, ZNF365, IFNG, PSMG1 with UC, were confirmed. Association with TNFSF15 and pediatric UC was also reported. A correlation with NKX2-3 and need for surgery (P  =  0.038), and with HLA and steroid-responsiveness (P  =  0.024) in UC patients was observed. Moreover, significant association in our CD cohort with TNFSF15 SNP and colonic involvement (P  =  0.021), and with ZNF365 and ileal location (P  =  0.024) was demonstrated. CONCLUSIONS: We confirmed in a large Italian cohort the associations with CD and UC of newly identified genes, both in adult and pediatric cohort of patients, with some influence on sub-phenotypes

Unraveling multiple MHC gene associations with systemic lupus erythematosus: model choice indicates a role for HLA alleles and non-HLA genes in Europeans.

We have performed a meta-analysis of the major-histocompatibility-complex (MHC) region in systemic lupus erythematosus (SLE) to determine the association with both SNPs and classical human-leukocyte-antigen (HLA) alleles. More specifically, we combined results from six studies and well-known out-of-study control data sets, providing us with 3,701 independent SLE cases and 12,110 independent controls of European ancestry. This study used genotypes for 7,199 SNPs within the MHC region and for classical HLA alleles (typed and imputed). Our results from conditional analysis and model choice with the use of the Bayesian information criterion show that the best model for SLE association includes both classical loci (HLA-DRB1(∗)03:01, HLA-DRB1(∗)08:01, and HLA-DQA1(∗)01:02) and two SNPs, rs8192591 (in class III and upstream of NOTCH4) and rs2246618 (MICB in class I). Our approach was to perform a stepwise search from multiple baseline models deduced from a priori evidence on HLA-DRB1 lupus-associated alleles, a stepwise regression on SNPs alone, and a stepwise regression on HLA alleles. With this approach, we were able to identify a model that was an overwhelmingly better fit to the data than one identified by simple stepwise regression either on SNPs alone (Bayes factor [BF] > 50) or on classical HLA alleles alone (BF > 1,000)

Genetic determinants of risk and progression in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease that represents a primary cause of neurological disability in the young adult population. Converging evidence support the importance of genetic determinants for MS etiology. However, with the exception of the major histocompatibility complex, their nature has been elusive for more than 20 years. In the last decade, the advent of large genome-wide association studies has significantly improved our understanding of the disease, leading to the golden era of MS genetic research. To date more than 110 genetic variants have been firmly associated to an increased risk of developing MS. A large part of these variants tag genes involved in the regulation of immune response and several of them are shared with other autoimmune diseases, suggesting a common etiological root for this class of disorders. Despite the impressive body of data obtained in the last years, we are still far from fully decoding MS genetic complexity. For example, we ignore how these genetic factors interact with each other and with the environment. Thus, the biggest challenge for the next era of MS research will consist in identifying and characterizing the molecular mechanisms and the cellular pathways in which these risk variants play a role

Unraveling Multiple MHC Gene Associations with Systemic Lupus Erythematosus:Model Choice Indicates a Role for HLA Alleles and Non-HLA Genes in Europeans

We have performed a meta-analysis of the major-histocompatibility-complex (MHC) region in systemic lupus erythematosus (SLE) to determine the association with both SNPs and classical human-leukocyte-antigen (HLA) alleles. More specifically, we combined results from six studies and well-known out-of-study control data sets, providing us with 3,701 independent SLE cases and 12,110 independent controls of European ancestry. This study used genotypes for 7,199 SNPs within the MHC region and for classical HLA alleles (typed and imputed). Our results from conditional analysis and model choice with the use of the Bayesian information criterion show that the best model for SLE association includes both classical loci (HLA-DRB1(∗)03:01, HLA-DRB1(∗)08:01, and HLA-DQA1(∗)01:02) and two SNPs, rs8192591 (in class III and upstream of NOTCH4) and rs2246618 (MICB in class I). Our approach was to perform a stepwise search from multiple baseline models deduced from a priori evidence on HLA-DRB1 lupus-associated alleles, a stepwise regression on SNPs alone, and a stepwise regression on HLA alleles. With this approach, we were able to identify a model that was an overwhelmingly better fit to the data than one identified by simple stepwise regression either on SNPs alone (Bayes factor [BF] > 50) or on classical HLA alleles alone (BF > 1,000)