Polymorphisms in the CTLA-4 gene are known to be important in several autoimmune diseases, including multiple sclerosis (MS). Previous studies on the impact of CTLA-4 +49 A/G gene polymorphism have given contradictory results. We investigated the possible influence of this polymorphism on MS susceptibility and disease behaviour in Croatian and Slovenian populations. Genotyping was performed in 367 patients with MS and 480 control subjects using PCR-RFLP method. The G allele was present in 216 (58.9%) patients with MS vs. 282 (58.7%) healthy controls (P = 0.975, OR = 1.01, 95% CI = 0.76-1.32). No significant differences were observed in CTLA-4 +49 A or G allele distribution between patients and controls, indicating that this polymorphism does not influence susceptibility to MS in the surveyed populations. No correlation was observed between G allele carrier status and age at disease onset, disease course or severity.
Histamine is a central neurotransmitter degraded by histamine-N-methyltransferase (HNMT). Several abnormalities in the histaminergic system were found in patients with Parkinson's disease (PD), thus we tested the possible association of a Thr105Ile functional polymorphism in HNMT with PD. A total of 913 patients with PD and 958 controls were genotyped using a TaqMan RT-PCR Genotyping Assay (Foster City, California, USA). Lower frequency of HNMT Ile105 allele that is associated with decreased enzymatic activity was found in patients compared with controls (χ(2) = 11.65; p = 0.0006). We performed meta-analysis to confirm the association of Thr105Ile functional polymorphism with PD. Our results indicate that lower HNMT activity plays a role in the pathogenesis of PD.
Recent abundance of data from studies employing high-throughput technologies to reveal alterations in human disease on genomic, transcriptomic, proteomic and other levels, offer the possibility to integrate this information into a comprehensive picture of molecular events occurring in human disease. We present a novel approach for integration of such multi-origin data based on positions of genetic alterations occurring in human diseases. Parkinson's disease (PD) was chosen as a model for evaluation of our methodology. Datasets from various types of studies in PD (linkage, genome-wide association, transcriptomic and proteomic studies) were obtained from online repositories or were extracted from available research papers. Subsequently, human genome assembly was subdivided into 10 kb regions, and significant signals from aforementioned studies were arranged into their corresponding regions according to their genomic position. . Identified regions with significant accumulation of signals contained 29 plausible candidate genes for PD. In conclusion, we present a novel approach for identification of candidate regions and genes for various human disorders, based on the positional integration of data across various types of omic studies.