Objective: The clinical characteristics of multiple sclerosis (MS) are not well defined in Hispanic populations. We hypothesized that disease presentation in Hispanic white (HW) patients will be different from non-Hispanic white (NHW) patients given their ancestral background and reported lower disease prevalence. This study was undertaken to compare HW of primarily Caribbean ancestry to NHW on clinical characteristics of MS. Methods: We assessed 312 HW and 312 NHW patients with definite MS for clinical disease characteristics obtained through consented review of medical records. In order to assess the relationship between age-related phenotypes and ethnicity, linear regression was used. Logistic regression was used to assess the relationship between ethnicity and descriptors of disease presentation and severity as well as presence of neurological symptoms. Results: We observed a significantly younger age at diagnosis (p = 1.38E-02) and age at exam (p = 2.36E-05) in HW. However, age at first symptom did not differ significantly between the two groups. Furthermore, within HW, the mean age at first symptom and age at diagnosis was significantly younger in those born in the United States (p < 1.00E-03 for both). Interestingly, we noted an increase in ambulatory disability in HW patients, primarily among those with relapsing disease (p = 4.18E-03). Conclusions: We found several differences in age-related phenotypes and disease severity between HW of primarily Caribbean origin and NHW patients. To our knowledge, this is the largest study to date that examined the clinical characteristics of MS in Hispanic patients of largely Caribbean origin.
Genome-wide association studies (GWASs) perform per-SNP association tests to identify variants involved in disease or trait susceptibility. However, such an approach is not powerful enough to unravel genes that are not individually contributing to the disease/trait, but that may have a role in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNP association P-values from eight multiple sclerosis (MS) GWAS data sets, we performed a candidate pathway analysis for MS susceptibility by considering genes interacting in the cell adhesion molecule (CAMs) biological pathway using Cytoscape software. This network is a strong candidate, as it is involved in the crossing of the blood-brain barrier by the T cells, an early event in MS pathophysiology, and is used as an efficient therapeutic target. We drew up a list of 76 genes belonging to the CAM network. We highlighted 64 networks enriched with CAM genes with low P-values. Filtering by a percentage of CAM genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted five networks associated with MS susceptibility. One of them, constituted of ITGAL, ICAM1 and ICAM3 genes, could be of interest to develop novel therapeutic targets. Abstract:Typically Genome-Wide Association Studies (GWASs) perform per-SNP association tests to identify variants involved in disease or trait susceptibility. However, such an approach is not powerful enough to unravel genes that are not individually contributing to the disease/trait but that may play a role in interaction with other genes as a group. Pathway analysis is an alternative way to highlight such group of genes. Using SNPs association p-values from 8Multiple Sclerosis (MS) GWAS datasets, we performed a candidate pathway analysis for MS susceptibility considering genes interacting in cell adhesion molecules (CAMs) biological pathway using Cytoscape software. This network is a strong candidate since it is involved in the crossing of the blood brain barrier by the T cells, an early event in MS pathophysiology, and used as an efficient therapeutic target. We drew up a list of 76 genes belonging to the CAMs network. We highlighted 64 networks enriched with CAMs genes with low p-values.Filtering by a percentage of CAMs genes up to 50% and rejecting enriched signals mainly driven by transcription factors, we highlighted 5 networks associated with MS susceptibility.One of them, constituted of ITGAL, ICAM1 and ICAM3 genes could be of interest to develop novel therapeutic targets.
SUMMARY Despite the increasing speculation that oxidative stress and abnormal energy metabolism may play a role in Autism Spectrum Disorders (ASD), and the observation that patients with mitochondrial defects have symptoms consistent with ASD, there are no comprehensive published studies examining the role of mitochondrial variation in autism. Therefore, we have sought to comprehensively examine the role of mitochondrial DNA (mtDNA) variation with regard to ASD risk, employing a multi-phase approach. In phase 1 of our experiment, we examined 132 mtDNA single-nucleotide polymorphisms (SNPs) genotyped as part of our genome-wide association studies of ASD. In phase 2 we genotyped the major European mitochondrial haplogroup-defining variants within an expanded set of autism probands and controls. Finally in phase 3, we resequenced the entire mtDNA in a subset of our Caucasian samples (~400 proband-father pairs). In each phase we tested whether mitochondrial variation showed evidence of association to ASD. Despite a thorough interrogation of mtDNA variation, we found no evidence to suggest a major role for mtDNA variation in ASD susceptibility. Accordingly, while there may be attractive biological hints suggesting the role of mitochondria in ASD our data indicate that mtDNA variation is not a major contributing factor to the development of ASD.
We discovered new suggestive signals and confirmed some previously identified ones. We believe this to represent a significant step toward an understanding of the genetic basis of MS.
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