was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.The copyright holder for this preprint (which . http://dx.doi.org/10.1101/143933 doi: bioRxiv preprint first posted online Jul. 13, 2017; 2 Abstract:We assembled and analyzed genetic data of 47,351 multiple sclerosis (MS) subjects and 68,284 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 independent associations within the extended MHC. We used an ensemble of methods to prioritize up to 551 potentially associated MS susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we do find enrichment for MS genes in these brain-resident immune cells. Thus, while MS is most likely initially triggered by perturbation of peripheral immune responses the functional responses of microglia and other brain cells are also altered and may have a role in targeting an autoimmune process to the central nervous system.

SummaryMultiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

ObjectivesThe clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time consuming. We evaluated natural language processing techniques applied to electronic medical records (EMR) to identify MS patients and the key clinical traits of their disease course.Materials and methodsWe used four algorithms based on ICD-9 codes, text keywords, and medications to identify individuals with MS from a de-identified, research version of the EMR at Vanderbilt University. Using a training dataset of the records of 899 individuals, algorithms were constructed to identify and extract detailed information regarding the clinical course of MS from the text of the medical records, including clinical subtype, presence of oligoclonal bands, year of diagnosis, year and origin of first symptom, Expanded Disability Status Scale (EDSS) scores, timed 25-foot walk scores, and MS medications. Algorithms were evaluated on a test set validated by two independent reviewers.ResultsWe identified 5789 individuals with MS. For all clinical traits extracted, precision was at least 87% and specificity was greater than 80%. Recall values for clinical subtype, EDSS scores, and timed 25-foot walk scores were greater than 80%.Discussion and conclusionThis collection of clinical data represents one of the largest databases of detailed, clinical traits available for research on MS. This work demonstrates that detailed clinical information is recorded in the EMR and can be extracted for research purposes with high reliability.

Multiple sclerosis (MS) is a disease of the central nervous system treated with disease-modifying therapies, including the biologic, interferon-β (IFN-β). Up to 60% of IFN-β-exposed MS patients develop abnormal biochemical liver test results, and 1 in 50 experiences drug-induced liver injury. Since genomic variation contributes to other forms of drug-induced liver injury, we aimed to identify biomarkers of IFN-β-induced liver injury using a two-stage genome-wide association study. The rs2205986 variant, previously linked to differential expression of IRF6, surpassed genome-wide significance in the combined two-stage analysis (P = 2.3 × 10, odds ratio = 8.3, 95% confidence interval = 3.6-19.2). Analysis of an independent cohort of IFN-β-treated MS patients identified via electronic medical records showed that rs2205986 was also associated with increased peak levels of aspartate aminotransferase (P = 7.6 × 10) and alkaline phosphatase (P = 4.9 × 10). We show that these findings may be applicable to predicting IFN-β-induced liver injury, offering insight into its safer use.

Refractive error (RE) is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness) and hyperopia (farsightedness), which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25×10−8), which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE) refractive error. We observed two genome-wide significant associations with hyperopia. These regions overlapped with loci on 15q14 (minimum p value = 9.11×10−11) and 8q12 (minimum p value 1.82×10−11) previously reported for MSE and myopia age at onset. We also used an intermarker linkage- disequilibrium-based method for calculating the effective number of tests in targeted regional replication analyses. We analyzed myopia (which represents the closest phenotype in our data to the one used by Kiefer et al.) and showed replication of 10 additional loci associated with myopia previously reported by Kiefer et al. This is the first replication of these loci using myopia as the trait under analysis. “Replication-level” association was also seen between hyperopia and 12 of Kiefer et al.'s published loci. For the loci that show evidence of association to both myopia and hyperopia, the estimated effect of the risk alleles were in opposite directions for the two traits. This suggests that these loci are important contributors to variation of refractive error across the distribution.

No abstract

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.

In addition to the well characterized function of chemokines in mediating the homing and accumulation of leukocytes to tissues, some chemokines also exhibit potent antimicrobial activity. Little is known of the potential role of chemokines in bovine mammary gland health and disease. The chemokine CCL28 has previously been shown to play a key role in the homing and accumulation of IgA antibody secreting cells to the lactating murine mammary gland. CCL28 has also been shown to act as an antimicrobial peptide with activity demonstrated against a wide range of pathogens including bacteria, fungi and protozoans. Here we describe the cloning and function of bovine CCL28 and document the concentration of this chemokine in bovine milk. Bovine CCL28 was shown to mediate cellular chemotaxis via the CCR10 chemokine receptor and exhibited antimicrobial activity against a variety of bovine mastitis causing organisms. The concentration of bovine CCL28 in milk was found to be highly correlated with the lactation cycle. Highest concentrations of CCL28 were observed soon after parturition, with levels decreasing over time. These results suggest a potential role for CCL28 in the prevention/resolution of bovine mastitis.