Variation in major histocompatibility complex genes on chromosome 6p21.3, specifically the human leukocyte antigen HLA-DR2 or DRB1*1501-DQB1*0602 extended haplotype, confers risk for multiple sclerosis (MS). Previous studies of DRB1 variation and both MS susceptibility and phenotypic expression have lacked statistical power to detect modest genotypic influences, and have demonstrated conflicting results. Results derived from analyses of 1339 MS families indicate DRB1 variation influences MS susceptibility in a complex manner. DRB1*15 was strongly associated in families (P=7.8x10(-31)), and a dominant DRB1*15 dose effect was confirmed (OR=7.5, 95% CI=4.4-13.0, P<0.0001). A modest dose effect was also detected for DRB1*03; however, in contrast to DRB1*15, this risk was recessive (OR=1.8, 95% CI=1.1-2.9, P=0.03). Strong evidence for under-transmission of DRB1*14 (P=5.7x10(-6)) even after accounting for DRB1*15 (P=0.03) was present, confirming a protective effect. In addition, a high risk DRB1*15 genotype bearing DRB1*08 was identified (OR=7.7, 95% CI=4.1-14.4, P<0.0001), providing additional evidence for trans DRB1 allelic interactions in MS. Further, a significant DRB1*15 association observed in primary progressive MS families (P=0.0004), similar to relapsing-remitting MS families, suggests that DRB1-related mechanisms are contributing to both phenotypes. In contrast, results obtained from 2201 MS cases argue convincingly that DRB1*15 genotypes do not modulate age of onset, or significantly influence disease severity measured using expanded disease disability score and disease duration. These results contribute substantially to our understanding of the DRB1 locus and MS, and underscore the importance of using large sample sizes to detect modest genetic effects, particularly in studies of genotype-phenotype relationships.

The Random Forests (RF) algorithm has become a commonly used machine learning algorithm for genetic association studies. It is well suited for genetic applications since it is both computationally efficient and models genetic causal mechanisms well. With its growing ubiquity, there has been inconsistent and less than optimal use of RF in the literature. The purpose of this review is to breakdown the theoretical and statistical basis of RF so that practitioners are able to apply it in their work. An emphasis is placed on showing how the various components contribute to bias and variance, as well as discussing variable importance measures. Applications specific to genetic studies are highlighted. To provide context, RF is compared to other commonly used machine learning algorithms.

Background: Folic acid taken in early pregnancy reduces risks for delivering offspring with several congenital anomalies. The mechanism by which folic acid reduces risk is unknown. Investigations into genetic variation that influences transport and metabolism of folate will help fill this data gap. We focused on 118 SNPs involved in folate transport and metabolism.

ObjectiveDetermine whether MS-specific DNA methylation profiles can be identified in whole blood or purified immune cells from untreated MS patients.MethodsWhole blood, CD4+ and CD8+ T cell DNA from 16 female, treatment naïve MS patients and 14 matched controls was profiled using the HumanMethylation450K BeadChip. Genotype data were used to assess genetic homogeneity of our sample and to exclude potential SNP-induced DNA methylation measurement errors.ResultsAs expected, significant differences between CD4+ T cells, CD8+ T cells and whole blood DNA methylation profiles were observed, regardless of disease status. Strong evidence for hypermethylation of CD8+ T cell, but not CD4+ T cell or whole blood DNA in MS patients compared to controls was observed. Genome-wide significant individual CpG-site DNA methylation differences were not identified. Furthermore, significant differences in gene DNA methylation of 148 established MS-associated risk genes were not observed.ConclusionWhile genome-wide significant DNA methylation differences were not detected for individual CpG-sites, strong evidence for DNA hypermethylation of CD8+ T cells for MS patients was observed, indicating a role for DNA methylation in MS. Further, our results suggest that large DNA methylation differences for CpG-sites tested here do not contribute to MS susceptibility. In particular, large DNA methylation differences for CpG-sites within 148 established MS candidate genes tested in our study cannot explain missing heritability. Larger studies of homogenous MS patients and matched controls are warranted to further elucidate the impact of CD8+ T cell and more subtle DNA methylation changes in MS development and pathogenesis.

; for the Cleveland Pre-Hospital Acute Stroke Treatment (PHAST) Group IMPORTANCE Mobile stroke treatment units (MSTUs) with on-site treatment teams that include a vascular neurologist can provide thrombolysis in the prehospital setting faster than treatment in the hospital. These units can be made more resource efficient if the need for an on-site neurologist can be eliminated by relying solely on telemedicine for physician presence. OBJECTIVE To test whether telemedicine is reliable and remote physician presence is adequate for acute stroke treatment using an MSTU.

Multiple Sclerosis (MS) is an autoimmune disorder where T cells attack neurons in the central nervous system (CNS) leading to demyelination and neurological deficits. A driver of increased MS risk is the soluble form of the interleukin-7 receptor alpha chain gene (sIL7R), produced by alternative splicing of IL7R exon 6. Here, we identified the RNA helicase DDX39B as a potent activator of this exon and consequently a repressor of sIL7R, and found strong genetic association of DDX39B with MS risk. Indeed, we showed that a genetic variant in the 5′ UTR of DDX39B reduces translation of DDX39B mRNAs and increases MS risk. Importantly, this DDX39B variant showed strong genetic and functional epistasis with allelic variants in IL7R exon 6. This study establishes the occurrence of biological epistasis in humans and provides mechanistic insight into the regulation of IL7R exon 6 splicing and its impact on MS risk.

Objective To investigate the association between obesity and multiple sclerosis (MS) while accounting for established genetic and environmental risk factors. Methods Participants included members of Kaiser Permanente Medical Care Plan, Northern California Region (KPNC) (1,235 MS cases and 697 controls). Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (95% CI). Body mass index (BMI) or body size was the primary predictor of each model. Both incident and prevalent MS cases were studied. Results In analyses stratified by gender, being overweight at age 10 and 20 were associated with MS in females (p<0.01). Estimates trended in the same direction for males, but were not significant. BMI in 20’s demonstrated a linear relationship with MS (p-trend=9.60 × 10−4), and a twofold risk of MS for females with a BMI ≥ 30 kg/m2 was observed (OR = 2.15, 95% CI 1.18, 3.92). Significant associations between BMI in 20’s and MS in males were not observed. Multivariate modeling demonstrated that significant associations between BMI or body size with MS in females persisted after adjusting for history of infectious mononucleosis and genetic risk factors, including HLA-DRB1*15:01 and established non-HLA risk alleles. Interpretation Results show that childhood and adolescence obesity confer increased risk of MS in females beyond established heritable and environmental risk factors. Strong evidence for a dose-effect of BMI in 20’s and MS was observed. The magnitude of BMI association with MS is as large as other known MS risk factors.

Genetic susceptibility to multiple sclerosis (MS) is associated with the MHC located on chromosome 6p21. This signal maps primarily to a 1-Mb region encompassing the HLA class II loci, and it segregates often with the HLA-DQB1*0602, -DQA1*0102, -DRB1*1501, -DRB5*0101 haplotype. However, the identification of the true predisposing gene or genes within the susceptibility haplotype has been handicapped by the strong linkage disequilibrium across the locus. African Americans have greater MHC haplotypic diversity and distinct patterns of linkage disequilibrium, which make this population particularly informative for fine mapping efforts. The purpose of this study was to establish the telomeric boundary of the HLA class II region affecting susceptibility to MS by assessing genetic association with the neighboring HLA-DRB5 gene as well as seven telomeric single nucleotide polymorphisms in a large, well-characterized African American dataset. Rare DRB5*null individuals were previously described in African populations. Although significant associations with both HLA-DRB1 and HLA-DRB5 loci were present, HLA-DRB1*1503 was associated with MS in the absence of HLA-DRB5, providing evidence for HLA-DRB1 as the primary susceptibility gene. Interestingly, the HLA-DRB5*null subjects appear to be at increased risk for developing secondary progressive MS. Thus, HLA-DRB5 attenuates MS severity, a finding consistent with HLA-DRB5’s proposed role as a modifier in experimental autoimmune encephalomyelitis. Additionally, conditional haplotype analysis revealed a susceptibility signal at the class III AGER locus independent of DRB1. The data underscore the power of the African American MS dataset to identify disease genes by association in a region of high linkage disequilibrium.