We investigated the role of the KIR loci and their HLA class I ligands in a large cohort of African American multiple sclerosis (MS) patients (N=907) and controls (N=1456). No significant differences in carrier frequencies for any KIR locus or haplotype were observed between cases and controls. However, examination of KIR in the context of their cognate HLA ligands revealed a strong protective effect for KIR3DL1 in combination with HLA-A and -B alleles bearing the Bw4 motif (P=10(-8); odds ratio (OR)=0.60, confidence interval (CI)=0.50-0.71) and the Bw4 ligand alone (P<10(-6); OR=0.63, CI=0.53-0.75). The observed effect cannot be explained by either a specific HLA-B allele or by linkage disequilibrium with HLA-DRB1 or HLA-A. The protective effect was observed only in individuals who were not positive for the MS risk allele HLA-DRB1*15:01 (P<10(-6); OR=0.61, CI=0.51-0.74). Our study, the first investigation of KIR and MS in African Americans, confirms and refines previous findings in a European cohort.

Non-Hodgkin lymphoma (NHL) and Hodgkin lymphoma (HL) represent a heterogeneous group of malignant lymphoid tumors, which have distinct histological and/or biological characteristics with preferential nodal involvement. However, none of the previous studies

Multiple sclerosis (MS) is an autoimmune demyelinating disease characterized by complex genetics and multifaceted gene-environment interactions. Compared to whites, African Americans have a lower risk for developing MS, but African Americans with MS have a greater risk of disability. These differences between African Americans and whites may represent differences in genetic susceptibility and/or environmental factors. SNPs from 12 candidate genes have recently been identified and validated with MS risk in white populations. We performed a replication study using 918 cases and 656 unrelated controls to test whether these candidate genes are also associated with MS risk in African Americans. CD6, CLEC16a, EVI5, GPC5, and TYK2 contained SNPs that are associated with MS risk in the African American data set. EVI5 showed the strongest association outside the major histocompatibility complex (rs10735781, OR=1.233, 95% CI=1.06-1.43, P-value=0.006). In addition, RGS1 seems to affect age of onset whereas TNFRSF1A seems to be associated with disease progression. None of the tested variants showed results that were statistically inconsistent with the effects established in whites. The results are consistent with shared disease genetic mechanisms among individuals of European and African ancestry.

Disability measures in multiple sclerosis (MS) rely heavily on ambulatory function, and current metrics fail to capture potentially important variability in walking behavior. We sought to determine whether remote step count monitoring using a consumer-friendly accelerometer (Fitbit Flex) can enhance MS disability assessment. 99 adults with relapsing or progressive MS able to walk ≥2-min were prospectively recruited. At 4 weeks, study retention was 97% and median Fitbit use was 97% of days. Substudy validation resulted in high interclass correlations between Fitbit, ActiGraph and manual step count tally during a 2-minute walk test, and between Fitbit and ActiGraph (ICC = 0.76) during 7-day home monitoring. Over 4 weeks of continuous monitoring, daily steps were lower in progressive versus relapsing MS (mean difference 2546 steps, p < 0.01). Lower average daily step count was associated with greater disability on the Expanded Disability Status Scale (EDSS) (p < 0.001). Within each EDSS category, substantial variability in step count was apparent (i.e., EDSS = 6.0 range 1097-7152). Step count demonstrated moderate-strong correlations with other walking measures. Lower average daily step count is associated with greater MS disability and captures important variability in real-world walking activity otherwise masked by standard disability scales, including the EDSS. These results support remote step count monitoring as an exploratory outcome in MS trials.

Four single nucleotide polymorphism (SNP)-based human leukocyte antigen (HLA) imputation methods (e-HLA, HIBAG, HLA*IMP:02 and MAGPrediction) were trained using 1000 Genomes SNP and HLA genotypes and assessed for their ability to accurately impute molecular HLA-A, -B, -C and -DRB1 genotypes in the Human Genome Diversity Project cell panel. Imputation concordance was high (>89%) across all methods for both HLA-A and HLA-C, but HLA-B and HLA-DRB1 proved generally difficult to impute. Overall, <27.8% of subjects were correctly imputed for all HLA loci by any method. Concordance across all loci was not enhanced via the application of confidence thresholds; reliance on confidence scores across methods only led to noticeable improvement (+3.2%) for HLA-DRB1. As the HLA complex is highly relevant to the study of human health and disease, a standardized assessment of SNP-based HLA imputation methods is crucial for advancing genomic research. Considerable room remains for the improvement of HLA-B and especially HLA-DRB1 imputation methods, and no imputation method is as accurate as molecular genotyping. The application of large, ancestrally diverse HLA and SNP reference data sets and multiple imputation methods has the potential to make SNP-based HLA imputation methods a tractable option for determining HLA genotypes.