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1. The genetic diversity of multiple sclerosis risk among Hispanic and African American populations living in the United States.

Author

Beecham, AH, Amezcua, L, Chinea, A, Manrique, CP, Rubi, C, Isobe, N, Lund, BT, Santaniello, A, Beecham, GW, Burchard, EG, Comabella, M, Patsopoulos, N, Fitzgerald, K, Calabresi, PA, De Jager, P, Conti, DV, Delgado, SR, Oksenberg, JR, and McCauley, JL

Subjects
Humans, Multiple Sclerosis, Polymorphism, Single Nucleotide, Alleles, United States, Genetic Variation, Hispanic or Latino, Black or African American, Multiple sclerosis, admixture, allelic heterogeneity, genetics, locus heterogeneity, multi-ethnic, pathway analysis, risk score, Genetics, Neurodegenerative, Human Genome, Brain Disorders, Clinical Research, Autoimmune Disease, Genetic Testing, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Clinical Sciences, Neurology & Neurosurgery
Abstract

BackgroundSubstantial progress has been made toward unraveling the genetic architecture of multiple sclerosis (MS) within populations of European ancestry, but few genetic studies have focused on Hispanic and African American populations within the United States.ObjectiveWe sought to test the relevance of common European MS risk variants outside of the major histocompatibility complex (n = 200) within these populations.MethodsGenotype data were available on 2652 Hispanics (1298 with MS, 1354 controls) and 2435 African Americans (1298 with MS, 1137 controls). We conducted single variant, pathway, and cumulative genetic risk score analyses.ResultsWe found less replication than statistical power suggested, particularly among African Americans. This could be due to limited correlation between the tested and causal variants within the sample or alternatively could indicate allelic and locus heterogeneity. Differences were observed between pathways enriched among the replicating versus all 200 variants. Although these differences should be examined in larger samples, a potential role exists for gene-environment or gene-gene interactions which alter phenotype differentially across racial and ethnic groups. Cumulative genetic risk scores were associated with MS within each study sample but showed limited diagnostic capability.ConclusionThese findings provide a framework for fine-mapping efforts in multi-ethnic populations of MS.

Published
2020

2. The killer immunoglobulin-like receptor KIR3DL1 in combination with HLA-Bw4 is protective against multiple sclerosis in African Americans

Author

Hollenbach, JA, Pando, MJ, Caillier, SJ, Gourraud, P-A, and Oksenberg, JR

Subjects
Biomedical and Clinical Sciences, Immunology, Multiple Sclerosis, Brain Disorders, Neurosciences, Neurodegenerative, Autoimmune Disease, Genetics, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Black or African American, Alleles, Case-Control Studies, HLA-B Antigens, Humans, Linkage Disequilibrium, Receptors, KIR3DL1
Abstract

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

Published
2016

3. Mitochondrial DNA sequence variation in multiple sclerosis

Author

Tranah, GJ, Santaniello, A, Caillier, SJ, D'Alfonso, S, Boneschi, FM, Hauser, SL, and Oksenberg, JR

Subjects
Neurology & Neurosurgery, Clinical Sciences, Neurosciences, Cognitive Sciences
Abstract

Objective: To assess the influence of common mitochondrial DNA (mtDNA) sequence variation on multiple sclerosis (MS) risk in cases and controls part of an international consortium. Methods: We analyzed 115 high-quality mtDNA variants and common haplogroups from a previously published genome-wide association study among 7,391 cases from the International Multiple Sclerosis Genetics Consortium and 14,568 controls from the Wellcome Trust Case Control Consortium 2 project from 7 countries. Significant single nucleotide polymorphism and haplogroup associations were replicated in 3,720 cases and 879 controls from the University of California, San Francisco. Results: An elevated risk of MS was detected among haplogroup JT carriers from 7 pooled clinic sites (odds ratio [OR] = 1.15, 95% confidence interval [CI] = 1.07-1.24, p = 0.0002) included in the discovery study. The increased risk of MS was observed for both haplogroup T (OR = 1.17, 95% CI = 1.06-1.29, p = 0.002) and haplogroup J carriers (OR = 1.11, 95% CI = 1.01-1.22, p = 0.03). These haplogroup associations with MS were not replicated in the independent sample set. An elevated risk of primary progressive (PP) MS was detected for haplogroup J participants from 3 European discovery populations (OR = 1.49, 95% CI = 1.10-2.01, p = 0.009). This elevated risk was borderline significant in the US replication population (OR = 1.43, 95% CI = 0.99-2.08, p = 0.058) and remained significant in pooled analysis of discovery and replication studies (OR = 1.43, 95% CI = 1.14-1.81, p = 0.002). No common individual mtDNA variants were associated with MS risk. Conclusions: Identification and validation of mitochondrial genetic variants associated with MS and PPMS may lead to new targets for treatment and diagnostic tests for identifying potential responders to interventions that target mitochondria.

Published
2015

4. Whole genome sequences of 2 octogenarians with sustained cognitive abilities

Author

Nickles, D, Madireddy, L, Patel, N, Isobe, N, Miller, BL, Baranzini, SE, Kramer, JH, and Oksenberg, JR

Subjects
Clinical Sciences, Neurosciences, Neurology & Neurosurgery
Abstract

Although numerous genetic variants affecting aging and mortality have been identified, for example, apolipoprotein E ε4, the genetic component influencing cognitive aging has not been fully defined yet. A better knowledge of the genetics of aging will prove helpful in understanding the underlying biological processes. Here, we describe the whole genome sequences of 2 female octogenarians. We provide the repertoire of genomic variants that the 2 octogenarians have in common. We also describe the overlap with the previously reported genomes of 2 supercentenarians-individuals aged ≥110years. We assessed the genetic disease propensities of the octogenarians and non-aged control genomes and could not find support for the hypothesis that long-lived healthy individuals might exhibit greater genetic fitness than the general population. Furthermore, there is no evidence for an accumulation of previously described variants promoting longevity in the 2 octogenarians. These findings suggest that genetic fitness, as currently defined, is not the sole factor enabling an increased life span. We identified a number of healthy-cognitive-aging candidate genetic loci awaiting confirmation in larger studies.

Published
2015

5. Genetic associations with brain cortical thickness in multiple sclerosis

Author

Matsushita, T, Madireddy, L, Sprenger, T, Khankhanian, P, Magon, S, Naegelin, Y, Caverzasi, E, Lindberg, RLP, Kappos, L, Hauser, SL, Oksenberg, JR, Henry, R, Pelletier, D, and Baranzini, SE

Subjects
Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Multiple sclerosis (MS) is characterized by temporal and spatial dissemination of demyelinating lesions in the central nervous system. Associated neurodegenerative changes contributing to disability have been recognized even at early disease stages. Recent studies show the importance of gray matter damage for the accrual of clinical disability rather than white matter where demyelination is easily visualized by magnetic resonance imaging (MRI). The susceptibility to MS is influenced by genetic risk, but genetic factors associated with the disability are not known. We used MRI data to determine cortical thickness in 557 MS cases and 75 controls and in another cohort of 219 cases. We identified nine areas showing different thickness between cases and controls (regions of interest, ROI) (eight of them were negatively correlated with Kurtzke's expanded disability status scale, EDSS) and conducted genome-wide association studies (GWAS) in 464 and 211 cases available from the two data sets. No marker exceeded genome-wide significance in the discovery cohort. We next combined nominal statistical evidence of association with physical evidence of interaction from a curated human protein interaction network, and searched for subnetworks enriched with nominally associated genes and for commonalities between the two data sets. This network-based pathway analysis of GWAS detected gene sets involved in glutamate signaling, neural development and an adjustment of intracellular calcium concentration. We report here for the first time gene sets associated with cortical thinning of MS. These genes are potentially correlated with disability of MS. Common genetic variation is associated with cortical thickness in multiple sclerosis (MS) patients. Here we performed GWA on two independent cohorts of patients (n=675 in total). While no marker exceeded genome-wide significance, protein interaction based network analysis identified pathways involved in glutamate signaling, neural development and intracellular calcium concentration as significantly associated with cortical thickness in MS.

Published
2015

6. Transcriptional expression patterns triggered by chemically distinct neuroprotective molecules.

Author

Pappas, DJ, Gabatto, PA, Oksenberg, D, Khankhanian, P, Baranzini, SE, Gan, L, and Oksenberg, JR

Subjects
Cerebral Cortex, Neurons, Animals, Mice, Calcium, Mitogen-Activated Protein Kinases, Glutamic Acid, Receptors, N-Methyl-D-Aspartate, Neuroprotective Agents, Cell Adhesion, Signal Transduction, Cell Survival, Transcription, Genetic, RNA Interference, Gene Library, Toll-Like Receptors, Hypoxia-Inducible Factor 1, Genome-Wide Association Study, Data Mining, Real-Time Polymerase Chain Reaction, Transcriptome, Neurodegenerative, Genetics, Brain Disorders, Neurosciences, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Neurological, neuron, glutamate, NMDA, excitotoxicity, neuroprotection, microarray, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Glutamate-mediated excitotoxicity has been purported to underlie many neurodegenerative disorders. A subtype of glutamate receptors, namely N-methyl-d-aspartate (NMDA) receptors, has been recognized as potential targets for neuroprotection. To increase our understanding of the mechanisms that underlie this neuroprotection, we employed a mouse model of glutamate receptor-induced excitotoxic injury. Primary cortical neurons derived from postnatal day-0 CD-1 mice were cultured in the presence or absence of neuroprotective molecules and exposed to NMDA. Following a recovery period, whole genome expression was measured by microarray analysis. We used a combination of database and text mining, as well as systems modeling to identify signatures within the differentially expressed genes. While molecules differed in their mechanisms of action, we found significant overlap in the expression of a core group of genes and pathways. Many of these molecules have clear links to neuronal protection and survival, including ion channels, transporters, as well as signaling pathways including the mitogen-activated protein kinase (MAPK), the Toll-like receptor (TLR), and the hypoxic inducible factor (HIF). Within the TLR pathway, we also discovered a significant enrichment of interferon regulatory factor 7 (IRF7)-regulated genes. Knockdown of Irf7 by RNA interference resulted in reduced survival following NMDA treatment. Given the prominent role that IRF7 plays in the transduction of type-I interferons (IFNs), we also tested whether type-I IFNs alone functioned as neuroprotective agents and found that type-I IFNs were sufficient to promote neuronal survival. Our data suggest that the TLR/IRF7/IFN axis plays a significant role in recovery from glutamate-induced excitotoxicity.

Published
2012

7. In depth comparison of an individual's DNA and its lymphoblastoid cell line using whole genome sequencing

Author

Nickles, D, Madireddy, L, Yang, S, Khankhanian, P, Lincoln, S, Hauser, SL, Oksenberg, JR, and Baranzini, SE

Abstract

Background: A detailed analysis of whole genomes can be now achieved with next generation sequencing. Epstein Barr Virus (EBV) transformation is a widely used strategy in clinical research to obtain an unlimited source of a subject's DNA. Although the mechanism of transformation and immortalization by EBV is relatively well known at the transcriptional and proteomic level, the genetic consequences of EBV transformation are less well understood. A detailed analysis of the genetic alterations introduced by EBV transformation is highly relevant, as it will inform on the usefulness and limitations of this approach.Results: We used whole genome sequencing to assess the genomic signature of a low-passage lymphoblastoid cell line (LCL). Specifically, we sequenced the full genome (40X) of an individual using DNA purified from fresh whole blood as well as DNA from his LCL. A total of 217.33 Gb of sequence were generated from the cell line and 238.95 Gb from the normal genomic DNA. We determined with high confidence that 99.2% of the genomes were identical, with no reproducible changes in structural variation (chromosomal rearrangements and copy number variations) or insertion/deletion polymorphisms (indels).Conclusions: Our results suggest that, at this level of resolution, the LCL is genetically indistinguishable from its genomic counterpart and therefore their use in clinical research is not likely to introduce a significant bias. © 2012 Nickles et al.; licensee BioMed Central Ltd.

Published
2012

8. Evidence of novel fine-scale structural variation at autism spectrum disorder candidate loci

Author

Hedges, DJ, Hamilton-Nelson, KL, Sacharow, SJ, Nations, L, Beecham, GW, Kozhekbaeva, ZM, Butler, BL, Cukier, HN, Whitehead, PL, Ma, D, Jaworski, JM, Nathanson, L, Lee, JM, Hauser, SL, Oksenberg, JR, Cuccaro, ML, Haines, JL, Gilbert, JR, and Pericak-Vance, MA

Abstract

Background: Autism spectrum disorders (ASD) represent a group of neurodevelopmental disorders characterized by a core set of social-communicative and behavioral impairments. Gamma-aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the brain, acting primarily via the GABA receptors (GABR). Multiple lines of evidence, including altered GABA and GABA receptor expression in autistic patients, indicate that the GABAergic system may be involved in the etiology of autism. Methods. As copy number variations (CNVs), particularly rare and de novo CNVs, have now been implicated in ASD risk, we examined the GABA receptors and genes in related pathways for structural variation that may be associated with autism. We further extended our candidate gene set to include 19 genes and regions that had either been directly implicated in the autism literature or were directly related (via function or ancestry) to these primary candidates. For the high resolution CNV screen we employed custom-designed 244 k comparative genomic hybridization (CGH) arrays. Collectively, our probes spanned a total of 11 Mb of GABA-related and additional candidate regions with a density of approximately one probe every 200 nucleotides, allowing a theoretical resolution for detection of CNVs of approximately 1 kb or greater on average. One hundred and sixty-eight autism cases and 149 control individuals were screened for structural variants. Prioritized CNV events were confirmed using quantitative PCR, and confirmed loci were evaluated on an additional set of 170 cases and 170 control individuals that were not included in the original discovery set. Loci that remained interesting were subsequently screened via quantitative PCR on an additional set of 755 cases and 1,809 unaffected family members. Results: Results include rare deletions in autistic individuals at JAKMIP1, NRXN1, Neuroligin4Y, OXTR, and ABAT. Common insertion/deletion polymorphisms were detected at several loci, including GABBR2 and NRXN3. Overall, statistically significant enrichment in affected vs. unaffected individuals was observed for NRXN1 deletions. Conclusions: These results provide additional support for the role of rare structural variation in ASD. © 2012 Hedges et al; licensee BioMed Central Ltd.

Published
2012

9. A non-synonymous SNP within membrane metalloendopeptidase-like 1 (MMEL1) is associated with multiple sclerosis.

Author

Ban, M, McCauley, JL, Zuvich, R, Baker, A, Bergamaschi, L, Cox, M, Kemppinen, A, D'Alfonso, S, Guerini, FR, Lechner-Scott, J, Dudbridge, F, Wason, J, Robertson, NP, De Jager, PL, Hafler, DA, Barcellos, LF, Ivinson, AJ, Sexton, D, Oksenberg, JR, Hauser, SL, Pericak-Vance, MA, Haines, J, Compston, A, and Sawcer, S

Subjects
Humans, Multiple Sclerosis, Genetic Predisposition to Disease, Neprilysin, Kallikreins, ATP Citrate (pro-S)-Lyase, Nerve Tissue Proteins, Case-Control Studies, Chromosome Mapping, Genotype, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Adult, Genome-Wide Association Study, Cell Cycle Proteins, Cytoskeletal Proteins, multiple sclerosis, MMEL1, genetics, Polymorphism, Single Nucleotide, Immunology
Abstract

Several single-nucleotide polymorphism (SNP) genome-wide association studies (GWASs) have been completed in multiple sclerosis (MS). Follow-up studies of the variants with the most promising rankings, especially when supplemented by informed candidate gene selection, have proven to be extremely successful. In this study we report the results of a multi-stage replication analysis of the putatively associated SNPs identified in the Wellcome Trust Case Control Consortium non-synonymous SNP (nsSNP) screen. In total, the replication sample consisted of 3444 patients and 2595 controls. A combined analysis of the nsSNP screen and replication data provides evidence implicating a novel additional locus, rs3748816 in membrane metalloendopeptidase-like 1 (MMEL1; odds ratio=1.16, P=3.54 × 10⁻⁶) in MS susceptibility.

Published
2010

10. Multiple sclerosis susceptibility alleles in African Americans

Author

Johnson, BA, Wang, J, Taylor, EM, Caillier, SJ, Herbert, J, Khan, OA, Cross, AH, De Jager, PL, Gourraud, P-AF, Cree, BCA, Hauser, SL, and Oksenberg, JR

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Multiple Sclerosis, Neurosciences, Clinical Research, Prevention, Neurodegenerative, Autoimmune Disease, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Alleles, Black People, Female, Genetic Predisposition to Disease, Humans, Male, Polymorphism, Single Nucleotide, multiple sclerosis, genetics, African American, susceptibility, EVI5, Immunology
Abstract

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.

Published
2010

11. Follow-up examination of linkage and association to chromosome 1q43 in multiple sclerosis

Author

McCauley, JL, Zuvich, RL, Bradford, Y, Kenealy, SJ, Schnetz-Boutaud, N, Gregory, SG, Hauser, SL, Oksenberg, JR, Mortlock, DP, Pericak-Vance, MA, and Haines, JL

Subjects
Biological Sciences, Genetics, Prevention, Brain Disorders, Multiple Sclerosis, Human Genome, Arthritis, Autoimmune Disease, Neurosciences, Neurodegenerative, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Neurological, Alleles, Chromosomes, Human, Pair 1, Female, Follow-Up Studies, Gene Frequency, Genetic Linkage, Genetic Predisposition to Disease, Genotype, Humans, Male, Polymorphism, Single Nucleotide, RGS Proteins, multiple sclerosis, linkage, association, 1q43, RGS7, Immunology
Abstract

Multiple sclerosis (MS) is a debilitating neuroimmunological and neurodegenerative disease affecting >4,00,000 individuals in the United States. Population and family-based studies have suggested that there is a strong genetic component. Numerous genomic linkage screens have identified regions of interest for MS loci. Our own second-generation genome-wide linkage study identified a handful of non-major histocompatibility complex regions with suggestive linkage. Several of these regions were further examined using single-nucleotide polymorphisms (SNPs) with average spacing between SNPs of approximately 1.0 Mb in a dataset of 173 multiplex families. The results of that study provided further evidence for the involvement of the chromosome 1q43 region. This region is of particular interest given linkage evidence in studies of other autoimmune and inflammatory diseases including rheumatoid arthritis and systemic lupus erythematosus. In this follow-up study, we saturated the region with approximately 700 SNPs (average spacing of 10 kb per SNP) in search of disease-associated variation within this region. We found preliminary evidence to suggest that common variation within the RGS7 locus may be involved in disease susceptibility.

Published
2009

12. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

Author

Patsopoulos, NA, Baranzini, SE, Santaniello, A, Shoostari, P, Cotsapas, C, Wong, G, Beecham, AH, James, T, Replogle, J, Vlachos, IS, McCabe, C, Pers, TH, Brandes, A, White, C, Keenan, B, Cimpean, M, Winn, P, Panteliadis, IP, Robbins, A, Andlauer, TFM, Zarzycki, O, Dubois, B, Goris, A, Sondergaard, HB, Sellebjerg, F, Sorensen, PS, Ullum, H, Thorner, LW, Saarela, J, Cournu-Rebeix, I, Damotte, V, Fontaine, B, Guillot-Noel, L, Lathrop, M, Vukusic, S, Berthele, A, Pongratz, V, Gasperi, C, Graetz, C, Grummel, V, Hemmer, B, Hoshi, M, Knier, B, Korn, T, Lill, CM, Luessi, F, Muhlau, M, Zipp, F, Dardiotis, E, Agliardi, C, Amoroso, A, Barizzone, N, Benedetti, MD, Bernardinelli, L, Cavalla, P, Clarelli, F, Comi, G, Cusi, D, Esposito, F, Ferre, L, Galimberti, D, Guaschino, C, Leone, MA, Martinelli, V, Moiola, L, Salvetti, M, Sorosina, M, Vecchio, D, Zauli, A, Santoro, S, Mancini, N, Zuccala, M, Mescheriakova, J, van Duijn, C, Bos, SD, Celius, EG, Spurkland, A, Comabella, M, Montalban, X, Alfredsson, L, Bomfim, IL, Gomez-Cabrero, D, Hillert, J, Jagodic, M, Linden, M, Piehl, F, Jelcic, I, Martin, R, Sospedra, M, Baker, A, Ban, M, Hawkins, C, Hysi, P, Kalra, S, Karpe, F, Khadake, J, Lachance, G, Molyneux, P, Neville, M, Thorpe, J, Bradshaw, E, Caillier, SJ, Calabresi, P, Cree, BAC, Cross, A, Davis, M, de Bakker, PWI, Delgado, S, Dembele, M, Edwards, K, Fitzgerald, K, Frohlich, IY, Gourraud, PA, Haines, JL, Hakonarson, H, Kimbrough, D, Isobe, N, Konidari, I, Lathi, E, Lee, MH, Li, T, An, D, Zimmer, A, Madireddy, L, Manrique, CP, Mitrovic, M, Olah, M, Patrick, E, Pericak-Vance, MA, Piccio, L, Schaefer, C, Weiner, H, Lage, K, Scott, RJ, Lechner-Scott, J, Leal, R, Moscato, P, Booth, DR, Stewart, GJ, Vucic, S, Pame, G, BamettO, M, Mason, D, GriffithS, L, Broadley, S, Tajouri, L, Baxter, A, Slee, M, Taylor, BV, Charlesworth, J, Kilpatrick, TJ, Rubio, J, Jokubaitis, V, Wiley, J, Butzkueven, H, Leslie, S, Motyer, A, Stankovich, J, Carroll, WM, Kermode, AG, Edrin, M, Barclay, M, Peyrin-Biroulet, L, Chamaillard, M, Colombe, JF, Cottone, M, Croft, A, D'Inca, R, Halfvarson, J, Hanigan, K, Henderson, P, Hugot, JP, Karban, A, Kennedy, NA, Khan, MA, Lemann, M, Levine, A, Massey, D, Milla, M, Motoey, GW, Ng, SME, Oikonomnou, J, Peeters, H, Proctor, DD, Rahier, JF, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, KM, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, MH, Zhang, H, Zhang, W, Donnelly, P, Barroso, I, Blackwe, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Strange, A, Sul, Z, Vukcevic, DA, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Compston, A, Hafler, D, Harbo, HF, Hauser, SL, Stewart, G, D'Alfonso, S, Hadjigeorgiou, G, Taylor, B, Barcellos, LF, Booth, D, Hintzen, R, Kockum, I, Martinelli-Boneschi, F, McCauley, JL, Oksenberg, JR, Oturai, A, Sawcer, S, Ivinson, AJ, Olsson, T, De Jager, PL, Patsopoulos, Na, Baranzini, Se, Santaniello, A, Shoostari, P, Cotsapas, C, Wong, G, Beecham, Ah, James, T, Replogle, J, Vlachos, I, Mccabe, C, Pers, Th, Brandes, A, White, C, Keenan, B, Cimpean, M, Winn, P, Panteliadis, Ip, Robbins, A, Andlauer, Tfm, Zarzycki, O, Dubois, B, Goris, A, Sondergaard, Hb, Sellebjerg, F, Sorensen, P, Ullum, H, Thorner, Lw, Saarela, J, Cournu-Rebeix, I, Damotte, V, Fontaine, B, Guillot-Noel, L, Lathrop, M, Vukusic, S, Berthele, A, Pongratz, V, Gasperi, C, Graetz, C, Grummel, V, Hemmer, B, Hoshi, M, Knier, B, Korn, T, Lill, Cm, Luessi, F, Muhlau, M, Zipp, F, Dardiotis, E, Agliardi, C, Amoroso, A, Barizzone, N, Benedetti, Md, Bernardinelli, L, Cavalla, P, Clarelli, F, Comi, G, Cusi, D, Esposito, F, Ferre, L, Galimberti, D, Guaschino, C, Leone, Ma, Martinelli, V, Moiola, L, Salvetti, M, Sorosina, M, Vecchio, D, Zauli, A, Santoro, S, Mancini, N, Zuccala, M, Mescheriakova, J, van Duijn, C, Bos, Sd, Celius, Eg, Spurkland, A, Comabella, M, Montalban, X, Alfredsson, L, Bomfim, Il, Gomez-Cabrero, D, Hillert, J, Jagodic, M, Linden, M, Piehl, F, Jelcic, I, Martin, R, Sospedra, M, Baker, A, Ban, M, Hawkins, C, Hysi, P, Kalra, S, Karpe, F, Khadake, J, Lachance, G, Molyneux, P, Neville, M, Thorpe, J, Bradshaw, E, Caillier, Sj, Calabresi, P, Cree, Bac, Cross, A, Davis, M, de Bakker, Pwi, Delgado, S, Dembele, M, Edwards, K, Fitzgerald, K, Frohlich, Iy, Gourraud, Pa, Haines, Jl, Hakonarson, H, Kimbrough, D, Isobe, N, Konidari, I, Lathi, E, Lee, Mh, Li, T, An, D, Zimmer, A, Madireddy, L, Manrique, Cp, Mitrovic, M, Olah, M, Patrick, E, Pericak-Vance, Ma, Piccio, L, Schaefer, C, Weiner, H, Lage, K, Scott, Rj, Lechner-Scott, J, Leal, R, Moscato, P, Booth, Dr, Stewart, Gj, Vucic, S, Pame, G, Bametto, M, Mason, D, Griffiths, L, Broadley, S, Tajouri, L, Baxter, A, Slee, M, Taylor, Bv, Charlesworth, J, Kilpatrick, Tj, Rubio, J, Jokubaitis, V, Wiley, J, Butzkueven, H, Leslie, S, Motyer, A, Stankovich, J, Carroll, Wm, Kermode, Ag, Edrin, M, Barclay, M, Peyrin-Biroulet, L, Chamaillard, M, Colombe, Jf, Cottone, M, Croft, A, D'Inca, R, Halfvarson, J, Hanigan, K, Henderson, P, Hugot, Jp, Karban, A, Kennedy, Na, Khan, Ma, Lemann, M, Levine, A, Massey, D, Milla, M, Motoey, Gw, Ng, Sme, Oikonomnou, J, Peeters, H, Proctor, Dd, Rahier, Jf, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, Km, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, Mh, Zhang, H, Zhang, W, Donnelly, P, Barroso, I, Blackwe, Jm, Bramon, E, Brown, Ma, Casas, Jp, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, H, Mathew, Cg, Palmer, Cna, Plomin, R, Rautanen, A, Sawcer, Sj, Trembath, Rc, Viswanathan, Ac, Wood, Nw, Spencer, Cca, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Strange, A, Sul, Z, Vukcevic, Da, Langford, C, Hunt, Se, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Compston, A, Hafler, D, Harbo, Hf, Hauser, Sl, Stewart, G, D'Alfonso, S, Hadjigeorgiou, G, Taylor, B, Barcellos, Lf, Booth, D, Hintzen, R, Kockum, I, Martinelli-Boneschi, F, Mccauley, Jl, Oksenberg, Jr, Oturai, A, Sawcer, S, Ivinson, Aj, Olsson, T, De Jager, Pl, Neurology, and Immunology

Subjects
0301 basic medicine, Multiple Sclerosis, Quantitative Trait Loci, Inheritance Patterns, Cell Cycle Proteins, Genome-wide association study, Biology, Major histocompatibility complex, Polymorphism, Single Nucleotide, Major Histocompatibility Complex, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Immune system, Gene Frequency, Autoimmune Process, medicine, Humans, RNA-Seq, X chromosome, Genetics, Chromosomes, Human, X, Multidisciplinary, Microglia, Multiple sclerosis, GTPase-Activating Proteins, Chromosome Mapping, Genomics, medicine.disease, 3. Good health, 030104 developmental biology, medicine.anatomical_structure, Genetic Loci, Case-Control Studies, biology.protein, Genome-Wide Association Study, 030217 neurology & neurosurgery
Abstract

Genetic roots of multiple sclerosis The genetics underlying who develops multiple sclerosis (MS) have been difficult to work out. Examining more than 47,000 cases and 68,000 controls with multiple genome-wide association studies, the International Multiple Sclerosis Genetics Consortium identified more than 200 risk loci in MS (see the Perspective by Briggs). Focusing on the best candidate genes, including a model of the major histocompatibility complex region, the authors identified statistically independent effects at the genome level. Gene expression studies detected that every major immune cell type is enriched for MS susceptibility genes and that MS risk variants are enriched in brain-resident immune cells, especially microglia. Up to 48% of the genetic contribution of MS can be explained through this analysis. Science , this issue p. eaav7188 ; see also p. 1383

Published
2019

13. MHC-restricted recognition of immunogenic T cell epitopes of pertussis toxin reveals determinants in man distinct from the ADP-ribosylase active site.

Author

Oksenberg, JR, Judd, AK, Ko, C, Lim, M, Fernandez, R, Schoolnik, GK, and Steinman, L

Subjects
Biodefense, Infectious Diseases, Emerging Infectious Diseases, Prevention, Immunization, Vaccine Related, Biotechnology, Good Health and Well Being, Amino Acid Sequence, Antigen-Presenting Cells, Binding Sites, Epitopes, Histocompatibility Antigens Class II, Humans, In Vitro Techniques, Lymphocyte Activation, Major Histocompatibility Complex, Molecular Sequence Data, Oligopeptides, Pentosyltransferases, Pertussis Toxin, T-Lymphocytes, Vaccines, Synthetic, Virulence Factors, Bordetella, Medical and Health Sciences, Immunology
Abstract

The S1 subunit of Pertussis toxin (PT) is responsible for the reactogenicity and in part the immunogenicity of Bordetella pertussis vaccine. The critical residues associated with the immunomodulatory effects of PT were located around Glu140 in the S1 subunit. In man, T cell responses to PT are directed at S1 peptides distinct from Glu140. Two such epitopes, p64-75 and p151-161, are immunogenic in a panel of individuals covering a wide range of HLA genotypes. The response to PT peptides is HLA class II restricted. The response to p64-75 is blocked by an anti-HLA-DQ mAb, while that to p151-161 is blocked by an anti-HLA-DR mAb. These findings may allow for the development of a B. pertussis vaccine free from reactogenicity.

Published
1988

14. The genetic diversity of multiple sclerosis risk among Hispanic and African American populations living in the United States

Author

Beecham, AH, primary, Amezcua, L, additional, Chinea, A, additional, Manrique, CP, additional, Rubi, C, additional, Isobe, N, additional, Lund, BT, additional, Santaniello, A, additional, Beecham, GW, additional, Burchard, EG, additional, Comabella, M, additional, Patsopoulos, N, additional, Fitzgerald, K, additional, Calabresi, PA, additional, De Jager, P, additional, Conti, DV, additional, Delgado, SR, additional, Oksenberg, JR, additional, and McCauley, JL, additional

Published
2019
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15. Genetic overlap between autoimmune diseases and non-Hodgkin lymphoma subtypes

Author

Din, L, Sheikh, M, Kosaraju, N, Smedby, KE, Bernatsky, S, Berndt, S, Skibola, CF, Nieters, A, Wang, S, McKay, JD, Cocco, P, Maynadie, M, Foretova, L, Staines, A, Mack, TM, de Sanjose, S, Vyse, TJ, Padyukov, L, Monnereau, A, Arslan, AA, Moore, A, Brooks-Wilson, AR, Novak, AJ, Glimelius, B, Birmann, BM, Link, BK, Stewart, C, Vajdic, CM, Haioun, C, Magnani, C, Conti, D, Cox, DG, Casabonne, D, Albanes, D, Kane, E, Roman, E, Muzi, G, Salles, G, Giles, GG, Adami, H-O, Ghesquieres, H, De Vivo, I, Clavel, J, Cerhan, JR, Spinelli, JJ, Hofmann, J, Vijai, J, Curtin, K, Costenbader, KH, Onel, K, Offit, K, Teras, LR, Morton, L, Conde, L, Miligi, L, Melbye, M, Ennas, MG, Liebow, M, Purdue, MP, Glenn, M, Southey, MC, Din, M, Rothman, N, Camp, NJ, Doo, NW, Becker, N, Pradhan, N, Bracci, PM, Boffetta, P, Vineis, P, Brennan, P, Kraft, P, Lan, Q, Severson, RK, Vermeulen, RCH, Milne, RL, Kaaks, R, Travis, RC, Weinstein, SJ, Chanock, SJ, Ansell, SM, Slager, SL, Zheng, T, Zhang, Y, Benavente, Y, Taub, Z, Madireddy, L, Gourraud, P-A, Oksenberg, JR, Cozen, W, Hjalgrim, H, Khankhanian, P, Din, L, Sheikh, M, Kosaraju, N, Smedby, KE, Bernatsky, S, Berndt, S, Skibola, CF, Nieters, A, Wang, S, McKay, JD, Cocco, P, Maynadie, M, Foretova, L, Staines, A, Mack, TM, de Sanjose, S, Vyse, TJ, Padyukov, L, Monnereau, A, Arslan, AA, Moore, A, Brooks-Wilson, AR, Novak, AJ, Glimelius, B, Birmann, BM, Link, BK, Stewart, C, Vajdic, CM, Haioun, C, Magnani, C, Conti, D, Cox, DG, Casabonne, D, Albanes, D, Kane, E, Roman, E, Muzi, G, Salles, G, Giles, GG, Adami, H-O, Ghesquieres, H, De Vivo, I, Clavel, J, Cerhan, JR, Spinelli, JJ, Hofmann, J, Vijai, J, Curtin, K, Costenbader, KH, Onel, K, Offit, K, Teras, LR, Morton, L, Conde, L, Miligi, L, Melbye, M, Ennas, MG, Liebow, M, Purdue, MP, Glenn, M, Southey, MC, Din, M, Rothman, N, Camp, NJ, Doo, NW, Becker, N, Pradhan, N, Bracci, PM, Boffetta, P, Vineis, P, Brennan, P, Kraft, P, Lan, Q, Severson, RK, Vermeulen, RCH, Milne, RL, Kaaks, R, Travis, RC, Weinstein, SJ, Chanock, SJ, Ansell, SM, Slager, SL, Zheng, T, Zhang, Y, Benavente, Y, Taub, Z, Madireddy, L, Gourraud, P-A, Oksenberg, JR, Cozen, W, Hjalgrim, H, and Khankhanian, P

Abstract

Epidemiologic studies show an increased risk of non-Hodgkin lymphoma (NHL) in patients with autoimmune disease (AD), due to a combination of shared environmental factors and/or genetic factors, or a causative cascade: chronic inflammation/antigen-stimulation in one disease leads to another. Here we assess shared genetic risk in genome-wide-association-studies (GWAS). Secondary analysis of GWAS of NHL subtypes (chronic lymphocytic leukemia, diffuse large B-cell lymphoma, follicular lymphoma, and marginal zone lymphoma) and ADs (rheumatoid arthritis, systemic lupus erythematosus, and multiple sclerosis). Shared genetic risk was assessed by (a) description of regional genetic of overlap, (b) polygenic risk score (PRS), (c)"diseasome", (d)meta-analysis. Descriptive analysis revealed few shared genetic factors between each AD and each NHL subtype. The PRS of ADs were not increased in NHL patients (nor vice versa). In the diseasome, NHLs shared more genetic etiology with ADs than solid cancers (p = .0041). A meta-analysis (combing AD with NHL) implicated genes of apoptosis and telomere length. This GWAS-based analysis four NHL subtypes and three ADs revealed few weakly-associated shared loci, explaining little total risk. This suggests common genetic variation, as assessed by GWAS in these sample sizes, may not be the primary explanation for the link between these ADs and NHLs.

Published
2019

17. Genome-wide meta-analysis identifies novel multiple sclerosis susceptibility loci

Author

Patsopoulos NA, Esposito F, Reischl J, Lehr S, Bauer D, Heubach J, Sandbrink R, Pohl C, Edan G, Kappos L, Miller D, Montalbán X, Polman CH, Freedman MS, Hartung HP, Arnason BGW, COMI , GIANCARLO, Cook S, FILIPPI , MASSIMO, Goodin DS, Jeffery D, O'Connor P, Ebers GC, Langdon D, Reder AT, Traboulsee A, Zipp F, Schimrigk J, Hillert J, Bahlo M, Booth DR, BroadleyS, Brown MA, Browning BL, Browning SR, Butzkueven H, Carroll WM, Chapman C, Foote SJ, Griffiths L, Kermode AG, Kilpatrick TJ, Lechner Scott J, Marriott M, Mason D, Moscato P, Heard RN, Pender MP, Perreau VM, Perera D, Rubio JP, Scott RJ, Slee M, Stankovich J, Stewart GJ, Taylor BV, Tubridy N, Willoughby E, Wiley J, Matthews P, Boneschi F, Compston A, Haines J, Hauser SL, McCauley J, Ivinson A, Oksenberg JR, Pericak Vance M, Sawcer SJ, De Jager PL, Hafler DA, de Bakker PIW, the BSP MS Genetics working group, the steering committees of studies evaluating IFNb 1b, a. CCR1 antagonist, ANZgene Consortium, GeneMSA, International Multiple Sclerosis Genetics Consortium, Neurology, NCA - Multiple Sclerosis and Other Neuroinflammatory Diseases, Patsopoulos, Na, Esposito, F, Reischl, J, Lehr, S, Bauer, D, Heubach, J, Sandbrink, R, Pohl, C, Edan, G, Kappos, L, Miller, D, Montalbán, X, Polman, Ch, Freedman, M, Hartung, Hp, Arnason, Bgw, Comi, Giancarlo, Cook, S, Filippi, Massimo, Goodin, D, Jeffery, D, O'Connor, P, Ebers, Gc, Langdon, D, Reder, At, Traboulsee, A, Zipp, F, Schimrigk, J, Hillert, J, Bahlo, M, Booth, Dr, Broadleys, Brown, Ma, Browning, Bl, Browning, Sr, Butzkueven, H, Carroll, Wm, Chapman, C, Foote, Sj, Griffiths, L, Kermode, Ag, Kilpatrick, Tj, Lechner Scott, J, Marriott, M, Mason, D, Moscato, P, Heard, Rn, Pender, Mp, Perreau, Vm, Perera, D, Rubio, Jp, Scott, Rj, Slee, M, Stankovich, J, Stewart, Gj, Taylor, Bv, Tubridy, N, Willoughby, E, Wiley, J, Matthews, P, Boneschi, F, Compston, A, Haines, J, Hauser, Sl, Mccauley, J, Ivinson, A, Oksenberg, Jr, Pericak Vance, M, Sawcer, Sj, De Jager, Pl, Hafler, Da, de Bakker, Piw, the BSP MS Genetics working, Group, the steering committees of studies evaluating IFNb, 1b, A., CCR1 antagonist, Anzgene, Consortium, Genemsa, and International Multiple Sclerosis Genetics, Consortium

Subjects
Male, Encephalomyelitis, Autoimmune, Experimental, Multiple Sclerosis, Single-nucleotide polymorphism, Genome-wide association study, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Article, Major Histocompatibility Complex, Animals, Humans, Genetic Predisposition to Disease, International HapMap Project, Genetic association, 25-Hydroxyvitamin D3 1-alpha-Hydroxylase, Genetics, T-Lymphocytes, Helper-Inducer, Genetic architecture, Neurology, Mutation, Expression quantitative trait loci, Female, Disease Susceptibility, Neurology (clinical), Imputation (genetics)
Abstract

OBJECTIVE: To perform a 1-stage meta-analysis of genome-wide association studies (GWAS) of multiple sclerosis (MS) susceptibility and to explore functional consequences of new susceptibility loci. METHODS: We synthesized 7 MS GWAS. Each data set was imputed using HapMap phase II, and a per single nucleotide polymorphism (SNP) meta-analysis was performed across the 7 data sets. We explored RNA expression data using a quantitative trait analysis in peripheral blood mononuclear cells (PBMCs) of 228 subjects with demyelinating disease. RESULTS: We meta-analyzed 2,529,394 unique SNPs in 5,545 cases and 12,153 controls. We identified 3 novel susceptibility alleles: rs170934(T) at 3p24.1 (odds ratio [OR], 1.17; p = 1.6 × 10(-8)) near EOMES, rs2150702(G) in the second intron of MLANA on chromosome 9p24.1 (OR, 1.16; p = 3.3 × 10(-8)), and rs6718520(A) in an intergenic region on chromosome 2p21, with THADA as the nearest flanking gene (OR, 1.17; p = 3.4 × 10(-8)). The 3 new loci do not have a strong cis effect on RNA expression in PBMCs. Ten other susceptibility loci had a suggestive p < 1 × 10(-6) , some of these loci have evidence of association in other inflammatory diseases (ie, IL12B, TAGAP, PLEK, and ZMIZ1). INTERPRETATION: We have performed a meta-analysis of GWAS in MS that more than doubles the size of previous gene discovery efforts and highlights 3 novel MS susceptibility loci. These and additional loci with suggestive evidence of association are excellent candidates for further investigations to refine and validate their role in the genetic architecture of MS.

Published
2016
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18. Genome sequencing uncovers phenocopies in primary progressive multiple sclerosis

Author

Jia, X, Madireddy, L, Caillier, S, Santaniello, A, Esposito, F, Comi, G, Stuve, O, Zhou, Y, Taylor, B, Kilpatrick, T, Martinelli-Boneschi, F, Cree, BAC, Oksenberg, JR, Hauser, SL, Baranzini, SE, Jia, X, Madireddy, L, Caillier, S, Santaniello, A, Esposito, F, Comi, G, Stuve, O, Zhou, Y, Taylor, B, Kilpatrick, T, Martinelli-Boneschi, F, Cree, BAC, Oksenberg, JR, Hauser, SL, and Baranzini, SE

Abstract

OBJECTIVE: Primary progressive multiple sclerosis (PPMS) causes accumulation of neurological disability from disease onset without clinical attacks typical of relapsing multiple sclerosis (RMS). However, whether genetic variation influences the disease course remains unclear. We aimed to determine whether mutations causative of neurological disorders that share features with multiple sclerosis (MS) contribute to risk for developing PPMS. METHODS: We examined whole-genome sequencing (WGS) data from 38 PPMS and 81 healthy subjects of European ancestry. We selected pathogenic variants exclusively found in PPMS patients that cause monogenic neurological disorders and performed two rounds of replication genotyping in 746 PPMS, 3,049 RMS, and 1,000 healthy subjects. To refine our findings, we examined the burden of rare, potentially pathogenic mutations in 41 genes that cause hereditary spastic paraplegias (HSPs) in PPMS (n = 314), secondary progressive multiple sclerosis (SPMS; n = 587), RMS (n = 2,248), and healthy subjects (n = 987) genotyped using the MS replication chip. RESULTS: WGS and replication studies identified three pathogenic variants in PPMS patients that cause neurological disorders sharing features with MS: KIF5A p.Ala361Val in spastic paraplegia 10; MLC1 p.Pro92Ser in megalencephalic leukodystrophy with subcortical cysts, and REEP1 c.606 + 43G>T in Spastic Paraplegia 31. Moreover, we detected a significant enrichment of HSP-related mutations in PPMS patients compared to controls (risk ratio [RR] = 1.95; 95% confidence interval [CI], 1.27-2.98; p = 0.002), as well as in SPMS patients compared to controls (RR = 1.57; 95% CI, 1.18-2.10; p = 0.002). Importantly, this enrichment was not detected in RMS. INTERPRETATION: This study provides evidence to support the hypothesis that rare Mendelian genetic variants contribute to the risk for developing progressive forms of MS. Ann Neurol 2018;83:51-63.

Published
2018

20. A meta-analysis of genomic screens in multiple sclerosis. The Transatlantic Multiple Sclerosis Genetics Cooperative

Author

Pericak-Vance, MA, Rimmler, JB, Saunders, AM, Martin, ER, Haines, JL, Garcia, ME, Oksenberg, JR, Barcellos, LF, Lincoln, R, Goodkin, DE, Hauser, SL, Compston, DAS, Sawcer, SJ, Clayton, D, Jones, HB, Walker, N, Goodfellow, PPN, Bulman, D, Sadovnick, D, Ebers, GC, Dyment, D, Willer, C, Risch, N, and Transatlantic, MSG

Abstract

We combined the raw genotyping data from three large multiple sclerosis genome screens and performed a global meta-analysis in order to compare and summarize the linkage results from the different studies. In alphabetical order, the screens provided data from 442 markers typed in 52 multiplex families with a total of 133 affected individuals (the American screen), 314 markers typed in 128 families with 264 affecteds (the British screen) and 257 markers typed in 61 families with a total of 139 affected subjects (the Canadian screen). Multipoint analysis of these data was performed using the GENEHUNTER program. The highest non-parametric linkage (NPL) score in the meta-analysis was observed on chromosome 17q11 (NPL score 2.58), although this score falls short of genome-wide significance. A total of eight regions had NPL scores greater than 2.0. One of the regions with an NPL score greater than 2.0 was the HLA region on chromosome 6p21 (NPL=2.2). This region is known, from association studies, to be involved in MS susceptibility, but the modest linkage result observed here suggests the encoded susceptibility effect is not large compared with the high familial recurrence in MS (lambda approximately 20). Overall, our linkage results suggest that MS is likely to be multigenic in its genetic susceptibility.

Published
2016
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21. Genetic burden in multiple sclerosis families

Author

Isobe, N, Damotte, V, Ban, M, Pappas, D, Guillot Noel, L, Rebeix, I, Compston, A, Mack, T, Cozen, W, Fontaine, B, Hauser, SL, Oksenberg, JR, Sawcer, S, Gourraud, PA, LO RE, Vincenzina, Isobe, N, Damotte, V, Lo Re, V, Ban, M, Pappas, D, Guillot-Noel, L, Rebeix, I, Compston, A, Mack, T, Cozen, W, Fontaine, B, Hauser, SL, Oksenberg, JR, Sawcer, S, and Gourraud, PA

Subjects
multiple sclerosi, family study, genetic risk
Abstract

A previous study using cumulative genetic risk estimations in multiple sclerosis (MS) successfully tracked the aggregation of susceptibility variants in multi-case and single-case families. It used a limited description of susceptibility loci available at the time (17 loci). Even though the full roster of MS risk genes remains unavailable, we estimated the genetic burden in MS families and assess its disease predictive power using up to 64 single-nucleotide polymorphism (SNP) markers according to the most recent literature. A total of 708 controls, 3251 MS patients and their relatives, as well as 117 twin pairs were genotyped. We validated the increased aggregation of genetic burden in multi-case compared with single-case families (P¼4.14e03) and confirm that these data offer little opportunity to accurately predict MS, even within sibships (area under receiver operating characteristic (AUROC)¼0.59 (0.55, 0.53)). Our results also suggest that the primary progressive and relapsing-type forms of MS share a common genetic architecture (P¼0.368; difference being limited to that corresponding to ±2 typical MS-associated SNPs). We have confirmed the properties of individual genetic risk score in MS. Comparing with previous reference point for MS genetics (17 SNPs), we underlined the corrective consequences of the integration of the new findings from GWAS and meta-analysis.

Published
2013

22. High-density mapping of the MHC identifies a shared role for HLA-DRB1∗01:03 in inflammatory bowel diseases and heterozygous advantage in ulcerative colitis

Author

Goyette, P, Boucher, G, Mallon, D, Ellinghaus, E, Jostins, L, Huang, H, Ripke, S, Gusareva, ES, Annese, V, Hauser, SL, Oksenberg, JR, Thomsen, I, Leslie, S, Daly, MJ, Van Steen, K, Duerr, RH, Barrett, JC, McGovern, DPB, Schumm, LP, Traherne, JA, Carrington, MN, Kosmoliaptsis, V, Karlsen, TH, Franke, A, Rioux, JD, Abraham, C, Achkar, JP, Ahmad, T, Amininejad, L, Ananthakrishnan, AN, Andersen, V, Anderson, CA, Andrews, JM, Aumais, G, Baidoo, L, Baldassano, RN, Balschun, T, Bampton, PA, Barclay, M, Bayless, TM, Bethge, J, Bis, JC, Bitton, A, Brand, S, Brant, SR, Buning, C, Chew, A, Cho, JH, Cleynen, I, Cohain, A, Croft, A, D'Amato, M, Danese, S, De Jong, D, De Vos, M, Denapiene, G, Denson, LA, Devaney, KL, Dewit, O, D'Inca, R, Dubinsky, M, Edwards, C, Ellinghaus, D, Essers, J, Ferguson, LR, Festen, EA, Fleshner, P, Florin, T, Franchimont, D, Fransen, K, Gearry, R, Georges, M, Gieger, C, and Glas, J

Subjects
digestive system diseases
Abstract

© 2015 Nature America, Inc. All rights reserved. Genome-wide association studies of the related chronic inflammatory bowel diseases (IBD) known as Crohn's disease and ulcerative colitis have shown strong evidence of association to the major histocompatibility complex (MHC). This region encodes a large number of immunological candidates, including the antigen-presenting classical human leukocyte antigen (HLA) molecules. Studies in IBD have indicated that multiple independent associations exist at HLA and non-HLA genes, but they have lacked the statistical power to define the architecture of association and causal alleles. To address this, we performed high-density SNP typing of the MHC in >32,000 individuals with IBD, implicating multiple HLA alleles, with a primary role for HLA-DRB1∗01:03 in both Crohn's disease and ulcerative colitis. Noteworthy differences were observed between these diseases, including a predominant role for class II HLA variants and heterozygous advantage observed in ulcerative colitis, suggesting an important role of the adaptive immune response in the colonic environment in the pathogenesis of IBD.

Published
2015
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23. The HLA locus and multiple sclerosis in Sicily

Author

SALEMI, Giuseppe, BRASSAT D, BARCELLOS L, MCNEILL G, HAUSER, Sergio, OKSENBERG JR, PROIA, Patrizia, SAVETTIERI, Giovanni, SALEMI G, BRASSAT D, BARCELLOS L, MCNEILL G, HAUSER SL, OKSENBERG JR, PROIA P, and SAVETTIERI G

Published
2004

24. Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls

Author

Zipp, F, Ivinson, AJ, Haines, JL, Sawcer, S, Dejager, P, Hauser, SL, and Oksenberg, JR

Abstract

Multiple sclerosis (MS) is an inflammatory CNS disease with a substantial genetic component, originally mapped to only the human leukocyte antigen (HLA) region. In the last 5 years, a total of seven genome-wide association studies and one meta-analysis successfully identified 57 non-HLA susceptibility loci. Here, we merged nominal statistical evidence of association and physical evidence of interaction to conduct a protein-interaction-network-based pathway analysis (PINBPA) on two large genetic MS studies comprising a total of 15,317 cases and 29,529 controls. The distribution of nominally significant loci at the gene level matched the patterns of extended linkage disequilibrium in regions of interest. We found that products of genome-wide significantly associated genes are more likely to interact physically and belong to the same or related pathways. We next searched for subnetworks (modules) of genes (and their encoded proteins) enriched with nominally associated loci within each study and identified those modules in common between the two studies. We demonstrate that these modules are more likely to contain genes with bona fide susceptibility variants and, in addition, identify several high-confidence candidates (including BCL10, CD48, REL, TRAF3, and TEC). PINBPA is a powerful approach to gaining further insights into the biology of associated genes and to prioritizing candidates for subsequent genetic studies of complex traits. © 2013 The American Society of Human Genetics.

Published
2013
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25. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Author

Beecham, AH, Patsopoulos, NA, Xifara, DK, Davis, MF, Kemppinen, A, Cotsapas, C, Shah, TS, Spencer, C, Booth, D, Goris, A, Oturai, A, Saarela, J, Fontaine, B, Hemmer, B, Martin, C, Zipp, F, D'Alfonso, S, Martinelli-Boneschi, F, Taylor, B, Harbo, HF, Kockum, I, Hillert, J, Olsson, T, Ban, M, Oksenberg, JR, Hintzen, R, Barcellos, LF, Agliardi, C, Alfredsson, L, Alizadeh, M, Anderson, C, Andrews, R, Søndergaard, HB, Baker, A, Band, G, Baranzini, SE, Barizzone, N, Barrett, J, Bellenguez, C, Bergamaschi, L, Bernardinelli, L, Berthele, A, Biberacher, V, Binder, TMC, Blackburn, H, Bomfim, IL, Brambilla, P, Broadley, S, Brochet, B, Brundin, L, Buck, D, Butzkueven, H, Caillier, SJ, Camu, W, Carpentier, W, Cavalla, P, Celius, EG, Coman, I, Comi, G, Corrado, L, Cosemans, L, Cournu-Rebeix, I, Cree, BAC, Cusi, D, Damotte, V, Defer, G, Delgado, SR, Deloukas, P, Di Sapio, A, Dilthey, AT, Donnelly, P, Dubois, B, Duddy, M, Edkins, S, Elovaara, I, Esposito, F, Evangelou, N, Fiddes, B, Field, J, and Franke, A

Abstract

Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10 -4). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10 -8), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals. © 2013 Nature America, Inc. All rights reserved.

Published
2013
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26. The immunogenetics of multiple sclerosis: A comprehensive review

Author

Hollenbach, JA, Hollenbach, JA, Oksenberg, JR, Hollenbach, JA, Hollenbach, JA, and Oksenberg, JR

Abstract

© 2015. Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system and common cause of non-traumatic neurological disability in young adults. The likelihood for an individual to develop MS is strongly influenced by her or his ethnic background and family history of disease, suggesting that genetic susceptibility is a key determinant of risk. Over 100 loci have been firmly associated with susceptibility, whereas the main signal genome-wide maps to the class II region of the human leukocyte antigen (HLA) gene cluster and explains up to 10.5% of the genetic variance underlying risk. HLA-DRB1*15:01 has the strongest effect with an average odds ratio of 3.08. However, complex allelic hierarchical lineages, cis/trans haplotypic effects, and independent protective signals in the class I region of the locus have been described as well. Despite the remarkable molecular dissection of the HLA region in MS, further studies are needed to generate unifying models to account for the role of the MHC in disease pathogenesis. Driven by the discovery of combinatorial associations of Killer-cell Immunoglobulin-like Receptor (KIR) and HLA alleles with infectious, autoimmune diseases, transplantation outcome and pregnancy, multi-locus immunogenomic research is now thriving. Central to immunity and critically important for human health, KIR molecules and their HLA ligands are encoded by complex genetic systems with extraordinarily high levels of sequence and structural variation and complex expression patterns. However, studies to-date of KIR in MS have been few and limited to very low resolution genotyping. Application of modern sequencing methodologies coupled with state of the art bioinformatics and analytical approaches will permit us to fully appreciate the impact of HLA and KIR variation in MS.

Published
2015

27. APOBEC3H Haplotypes and HIV-1 Pro-Viral vif DNA Sequence Diversity in Early Untreated HIV-1 Infection

Author

Gourraud, PA, Karaouni, A, Woo, JM, Schmidt, T, Oksenberg, JR, Hecht, FM, Liegler, TJ, and Barbour, JD

Subjects
Adult, Genes, vif, Male, Base Sequence, viruses, Chromosomes, Human, Pair 22, virus diseases, Genetic Variation, HIV Infections, Sequence Analysis, DNA, Polymorphism, Single Nucleotide, Article, Immunity, Innate, Linkage Disequilibrium, Cytosine Deaminase, Haplotypes, Proviruses, Aminohydrolases, DNA, Viral, HIV-1, Leukocytes, Mononuclear, vif Gene Products, Human Immunodeficiency Virus, Humans, RNA, Viral, Female
Abstract

We examined single nucleotide polymorphisms (SNP) in the APOBEC3 locus on chromosome 22, paired to population sequences of pro-viral HIV-1 vif of peripheral blood mononuclear cells (PBMC), from 96 recently HIV-1 infected treatment naïve adults. We found evidence for the existence of an APOBEC3H linkage disequilibrium (LD) block associated with variation in GA->AA, or APOBEC3F signature, sequence changes in pro-viral HIV-1 vif sequence (top significant 10 SNPs with a top-significant p=4.8×10−3). We identified a common 5 position risk haplotype distal to APOBEC3H (A3Hrh). These markers were in high LD (D′ = 1; r2=0.98) to a previously described A3H ‘RED’ haplotype containing a variant (E121) with enhanced susceptibility to HIV-1 Vif (Zhen et al 2009 [1]). This association is confirmed by a haplotype analysis: Homozygote carriers of the A3Hrh had lower GA->AA (A3F) sequence editing on pro-viral HIV-1 vif sequence (p = 0.01), and lower HIV-1 RNA levels over time during early, untreated HIV-1 infection, (p = 0.015 mixed effects model). This effect may be due to enhanced susceptibility of A3H forms to HIV-1 Vif mediated viral suppression of sequence editing activity, slowing viral diversification and escape from immune responses.

Published
2010

28. Genetic determinants of risk and progression in multiple sclerosis

Author

Didonna, A, Didonna, A, Oksenberg, JR, Didonna, A, Didonna, A, and Oksenberg, JR

Abstract

© 2015 Elsevier B.V. Multiple sclerosis (MS) is an autoimmune disease that represents a primary cause of neurological disability in the young adult population. Converging evidence supports the importance of genetic determinants for MS etiology. However, with the exception of the major histocompatibility complex, their nature has been elusive for more than 20. years. In the last decade, the advent of large genome-wide association studies has significantly improved our understanding of the disease, leading to the golden era of MS genetic research. To date more than 110 genetic variants have been firmly associated to an increased risk of developing MS. A large part of these variants tag genes involved in the regulation of immune response and several of them are shared with other autoimmune diseases, suggesting a common etiological root for this class of disorders. Despite the impressive body of data obtained in the last years, we are still far from fully decoding MS genetic complexity. For example, we ignore how these genetic factors interact with each other and with the environment. Thus, the biggest challenge for the next era of MS research will consist in identifying and characterizing the molecular mechanisms and the cellular pathways in which these risk variants play a role.

Published
2014

29. Copy number variation in pediatric multiple sclerosis.

Author

McElroy, JP, McElroy, JP, Krupp, LB, Johnson, BA, McCauley, JL, Qi, Z, Caillier, SJ, Gourraud, PA, Yu, J, Nathanson, L, Belman, AL, Hauser, SL, Waubant, E, Hedges, DJ, Oksenberg, JR, McElroy, JP, McElroy, JP, Krupp, LB, Johnson, BA, McCauley, JL, Qi, Z, Caillier, SJ, Gourraud, PA, Yu, J, Nathanson, L, Belman, AL, Hauser, SL, Waubant, E, Hedges, DJ, and Oksenberg, JR

Abstract

BackgroundPediatric onset multiple sclerosis (MS) accounts for 2-4% of all MS. It is unknown whether the disease shares the same underlying pathophysiology found in adult patients or an extreme early onset phenotype triggered by distinct biological mechanisms. It has been hypothesized that copy number variations (CNVs) may result in extreme early onset diseases because CNVs can have major effects on many genes in large genomic regions.Objectives and methodsThe objective of the current research was to identify CNVs, with a specific focus on de novo CNVs, potentially causing early onset MS by competitively hybridizing 30 white non-Hispanic pediatric MS patients with each of their parents via comparative genomic hybridization (CGH) analysis on the Agilent 1M CGH array.Results and discussionWe identified 10 CNVs not overlapping with any CNV regions currently reported in the Database of Genomic Variants (DGV). Fifty-five putatively de novo CNVs were also identified: all but one common in the DGV. We found the single rare CNV was a private variation harboring the SACS gene. SACS mutations cause autosomal-recessive spastic ataxia of Charlevoix-Saguenay (ARSACS) disease. Additional clinical review revealed that the patient with the SACS gene CNV shared some features of both MS and ARSACS.ConclusionsThis is the first reported study analyzing pediatric MS CNVs. While not yielding causal variation in our initial pediatric dataset, our approach confirmed diagnosis of an ARSACS-like disease in addition to MS in the affected individual, which led to a more complete understanding of the patient's disease course and prognosis.

Published
2013

30. Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis

Author

Sawcer, S, Hellenthal, G, Pirinen, M, Spencer, CCA, Patsopoulos, NA, Moutsianas, L, Dilthey, A, Su, Z, Freeman, C, Hunt, SE, Edkins, S, Gray, E, Booth, DR, Potter, SC, Goris, A, Band, G, Oturai, AB, Strange, A, Saarela, J, Bellenguez, C, Fontaine, B, Gillman, M, Hemmer, B, Gwilliam, R, Zipp, F, Jayakumar, A, Martin, R, Leslie, S, Hawkins, S, Giannoulatou, E, D'alfonso, S, Blackburn, H, Boneschi, FM, Liddle, J, Harbo, HF, Perez, ML, Spurkland, A, Waller, MJ, Mycko, MP, Ricketts, M, Comabella, M, Hammond, N, Kockum, I, McCann, OT, Ban, M, Whittaker, P, Kemppinen, A, Weston, P, Hawkins, C, Widaa, S, Zajicek, J, Dronov, S, Robertson, N, Bumpstead, SJ, Barcellos, LF, Ravindrarajah, R, Abraham, R, Alfredsson, L, Ardlie, K, Aubin, C, Baker, A, Baker, K, Baranzini, SE, Bergamaschi, L, Bergamaschi, R, Bernstein, A, Berthele, A, Boggild, M, Bradfield, JP, Brassat, D, Broadley, SA, Buck, D, Butzkueven, H, Capra, R, Carroll, WM, Cavalla, P, Celius, EG, Cepok, S, Chiavacci, R, Clerget-Darpoux, F, Clysters, K, Comi, G, Cossburn, M, Cournu-Rebeix, I, Cox, MB, Cozen, W, Cree, BAC, Cross, AH, Cusi, D, Daly, MJ, Davis, E, de Bakker, PIW, Debouverie, M, D'hooghe, MB, Dixon, K, Dobosi, R, Dubois, B, Ellinghaus, D, Elovaara, I, Esposito, F, Fontenille, C, Foote, S, Franke, A, Galimberti, D, Ghezzi, A, Glessner, J, Gomez, R, Gout, O, Graham, C, Grant, SFA, Guerini, FR, Hakonarson, H, Hall, P, Hamsten, A, Hartung, H-P, Heard, RN, Heath, S, Hobart, J, Hoshi, M, Infante-Duarte, C, Ingram, G, Ingram, W, Islam, T, Jagodic, M, Kabesch, M, Kermode, AG, Kilpatrick, TJ, Kim, C, Klopp, N, Koivisto, K, Larsson, M, Lathrop, M, Lechner-Scott, JS, Leone, MA, Leppa, V, Liljedahl, U, Bomfim, IL, Lincoln, RR, Link, J, Liu, J, Lorentzen, AR, Lupoli, S, Macciardi, F, Mack, T, Marriott, M, Martinelli, V, Mason, D, McCauley, JL, Mentch, F, Mero, I-L, Mihalova, T, Montalban, X, Mottershead, J, Myhr, K-M, Naldi, P, Ollier, W, Page, A, Palotie, A, Pelletier, J, Piccio, L, Pickersgill, T, Piehl, F, Pobywajlo, S, Quach, HL, Ramsay, PP, Reunanen, M, Reynolds, R, Rioux, J, Rodegher, M, Roesner, S, Rubio, JP, Rueckert, I-M, Salvetti, M, Salvi, E, Santaniello, A, Schaefer, CA, Schreiber, S, Schulze, C, Scott, RJ, Sellebjerg, F, Selmaj, KW, Sexton, D, Shen, L, Simms-Acuna, B, Skidmore, S, Sleiman, PMA, Smestad, C, Sorensen, PS, Sondergaard, HB, Stankovich, J, Strange, RC, Sulonen, A-M, Sundqvist, E, Syvaenen, A-C, Taddeo, F, Taylor, B, Blackwell, JM, Tienari, P, Bramon, E, Tourbah, A, Brown, MA, Tronczynska, E, Casas, JP, Tubridy, N, Corvin, A, Vickery, J, Jankowski, J, Villoslada, P, Markus, HS, Wang, K, Mathew, CG, Wason, J, Palmer, CNA, Wichmann, H-E, Plomin, R, Willoughby, E, Rautanen, A, Winkelmann, J, Wittig, M, Trembath, RC, Yaouanq, J, Viswanathan, AC, Zhang, H, Wood, NW, Zuvich, R, Deloukas, P, Langford, C, Duncanson, A, Oksenberg, JR, Pericak-Vance, MA, Haines, JL, Olsson, T, Hillert, J, Ivinson, AJ, De Jager, PL, Peltonen, L, Stewart, GJ, Hafler, DA, Hauser, SL, McVean, G, Donnelly, P, Compston, A, Sawcer, S, Hellenthal, G, Pirinen, M, Spencer, CCA, Patsopoulos, NA, Moutsianas, L, Dilthey, A, Su, Z, Freeman, C, Hunt, SE, Edkins, S, Gray, E, Booth, DR, Potter, SC, Goris, A, Band, G, Oturai, AB, Strange, A, Saarela, J, Bellenguez, C, Fontaine, B, Gillman, M, Hemmer, B, Gwilliam, R, Zipp, F, Jayakumar, A, Martin, R, Leslie, S, Hawkins, S, Giannoulatou, E, D'alfonso, S, Blackburn, H, Boneschi, FM, Liddle, J, Harbo, HF, Perez, ML, Spurkland, A, Waller, MJ, Mycko, MP, Ricketts, M, Comabella, M, Hammond, N, Kockum, I, McCann, OT, Ban, M, Whittaker, P, Kemppinen, A, Weston, P, Hawkins, C, Widaa, S, Zajicek, J, Dronov, S, Robertson, N, Bumpstead, SJ, Barcellos, LF, Ravindrarajah, R, Abraham, R, Alfredsson, L, Ardlie, K, Aubin, C, Baker, A, Baker, K, Baranzini, SE, Bergamaschi, L, Bergamaschi, R, Bernstein, A, Berthele, A, Boggild, M, Bradfield, JP, Brassat, D, Broadley, SA, Buck, D, Butzkueven, H, Capra, R, Carroll, WM, Cavalla, P, Celius, EG, Cepok, S, Chiavacci, R, Clerget-Darpoux, F, Clysters, K, Comi, G, Cossburn, M, Cournu-Rebeix, I, Cox, MB, Cozen, W, Cree, BAC, Cross, AH, Cusi, D, Daly, MJ, Davis, E, de Bakker, PIW, Debouverie, M, D'hooghe, MB, Dixon, K, Dobosi, R, Dubois, B, Ellinghaus, D, Elovaara, I, Esposito, F, Fontenille, C, Foote, S, Franke, A, Galimberti, D, Ghezzi, A, Glessner, J, Gomez, R, Gout, O, Graham, C, Grant, SFA, Guerini, FR, Hakonarson, H, Hall, P, Hamsten, A, Hartung, H-P, Heard, RN, Heath, S, Hobart, J, Hoshi, M, Infante-Duarte, C, Ingram, G, Ingram, W, Islam, T, Jagodic, M, Kabesch, M, Kermode, AG, Kilpatrick, TJ, Kim, C, Klopp, N, Koivisto, K, Larsson, M, Lathrop, M, Lechner-Scott, JS, Leone, MA, Leppa, V, Liljedahl, U, Bomfim, IL, Lincoln, RR, Link, J, Liu, J, Lorentzen, AR, Lupoli, S, Macciardi, F, Mack, T, Marriott, M, Martinelli, V, Mason, D, McCauley, JL, Mentch, F, Mero, I-L, Mihalova, T, Montalban, X, Mottershead, J, Myhr, K-M, Naldi, P, Ollier, W, Page, A, Palotie, A, Pelletier, J, Piccio, L, Pickersgill, T, Piehl, F, Pobywajlo, S, Quach, HL, Ramsay, PP, Reunanen, M, Reynolds, R, Rioux, J, Rodegher, M, Roesner, S, Rubio, JP, Rueckert, I-M, Salvetti, M, Salvi, E, Santaniello, A, Schaefer, CA, Schreiber, S, Schulze, C, Scott, RJ, Sellebjerg, F, Selmaj, KW, Sexton, D, Shen, L, Simms-Acuna, B, Skidmore, S, Sleiman, PMA, Smestad, C, Sorensen, PS, Sondergaard, HB, Stankovich, J, Strange, RC, Sulonen, A-M, Sundqvist, E, Syvaenen, A-C, Taddeo, F, Taylor, B, Blackwell, JM, Tienari, P, Bramon, E, Tourbah, A, Brown, MA, Tronczynska, E, Casas, JP, Tubridy, N, Corvin, A, Vickery, J, Jankowski, J, Villoslada, P, Markus, HS, Wang, K, Mathew, CG, Wason, J, Palmer, CNA, Wichmann, H-E, Plomin, R, Willoughby, E, Rautanen, A, Winkelmann, J, Wittig, M, Trembath, RC, Yaouanq, J, Viswanathan, AC, Zhang, H, Wood, NW, Zuvich, R, Deloukas, P, Langford, C, Duncanson, A, Oksenberg, JR, Pericak-Vance, MA, Haines, JL, Olsson, T, Hillert, J, Ivinson, AJ, De Jager, PL, Peltonen, L, Stewart, GJ, Hafler, DA, Hauser, SL, McVean, G, Donnelly, P, and Compston, A

Abstract

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.

Published
2011

31. Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data

Author

Wang, JH, Pappas, D, De Jager, PL, Pelletier, D, de Bakker, PIW, Kappos, L, Polman, CH, Chibnik, LB, Hafler, DA, Matthews, PM, Hauser, SL, Baranzini, SE, Oksenberg, JR, Wang, JH, Pappas, D, De Jager, PL, Pelletier, D, de Bakker, PIW, Kappos, L, Polman, CH, Chibnik, LB, Hafler, DA, Matthews, PM, Hauser, SL, Baranzini, SE, and Oksenberg, JR

Abstract

BACKGROUND: Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed. METHODS: We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation dataset (3,606 samples). Analysis of covariance (ANCOVA) was implemented to compare clinical characteristics of individuals with various degrees of genetic risk. Gene ontology and pathway enrichment analysis was done using the DAVID functional annotation tool, the GO Tree Machine, and the Pathway-Express profiling tool. RESULTS: In the discovery dataset, the median cumulative genetic risk (P-Hat) was 0.903 and 0.007 in the case and control groups, respectively, together with 79.9% classification sensitivity and 95.8% specificity. The identified profile shows a significant enrichment of genes involved in the immune response, cell adhesion, cell communication/signaling, nervous system development, and neuronal signaling, including ionotropic glutamate receptors, which have been implicated in the pathological mechanism driving neurodegeneration. In the validation dataset, the median cumulative genetic risk was 0.59 and 0.32 in the case and control groups, respectively, with classification sensitivity 62.3% and specificity 75.9%. No differences in disease progression or T2-lesion volumes were observed among four levels of predicted genetic risk groups (high, medium, low, misclassified). On the othe

Published
2011

32. Characterization of the TCRB chain repertoire in the New World monkey Callithrix jacchus

Author

Antonio UCCELLI, Oksenberg, Jr, Jeong, Mc, Genain, Cp, Rombos, T., Jaeger, Eem, Giunti, D., Lanchbury, Js, and Hauser, Sl

Subjects
Primates, beta-Chain T-Cell Antigen Receptor, DNA, Complementary, Receptors, Antigen, T-Cell, alpha-beta, T-Lymphocytes, Molecular Sequence Data, Sequence Homology, immunology, Complementary, Sequence Homology, Nucleic Acid, Receptors, Immunology and Allergy, Animals, Humans, genetics, Amino Acid Sequence, Cloning, Molecular, Gene Rearrangement, beta-Chain T-Cell Antigen Receptor, Amino Acid Sequence, Animals, Base Sequence, Callithrix, immunology, Cloning, Molecular, DNA, genetics, Gene Rearrangement, beta-Chain T-Cell Antigen Receptor, Humans, Molecular Sequence Data, Phylogeny, Primates, immunology, Receptors, Antigen, T-Cell, alpha-beta, genetics, Sequence Alignment, Sequence Homology, Amino Acid, Sequence Homology, Nucleic Acid, T-Lymphocytes, Phylogeny, Gene Rearrangement, Nucleic Acid, Base Sequence, Sequence Homology, Amino Acid, Molecular, Callithrix, DNA, Amino Acid, Sequence Alignment, Cloning
Abstract

Callithrix jacchus is an outbred New World primate characterized by a naturally occurring bone marrow chimerism, restricted polymorphism at many MHC loci, and unusual susceptibility to viral pathogens, adenocarcinoma, colitis, and, following immunization with myelin antigens, a demyelinating disease of the central nervous system closely resembling human multiple sclerosis. Here we characterize the TCRB repertoire in this species, representing the first such analysis in a New World monkey. Two TCRBC, 13 BJ, 2 BD, and 15 BV genes were identified. Overall, a high degree of similarity with human TCRBV-D-J-C gene sequences was observed, indicating a close phylogenetic relationship. Biased usage in favor of genes from the TCRBC1-BJ1 cluster was present in 77% of sequences, in contrast to preferential usage of BC2-BJ2 genes known to occur in humans and mice. Complementarity-determining region 3 averaged 10 amino acids in length and were diverse. Framework regions of TCRBV genes were extensively conserved. Phylogenetic analysis of TCRBV sequences from different species indicated that TCR genes are highly stable across primates. Thus, a diverse TCRB repertoire is generated in C. jacchus despite the limited polymorphism of class I MHC loci. Extensive homology to human TCR genes, natural chimerism, and susceptibility to inflammatory disorders are characteristics of C. jacchus that create a useful model system for the study of human autoimmunity.

Published
1997

33. Copy number variation in pediatric multiple sclerosis

Author

McElroy, JP, primary, Krupp, LB, additional, Johnson, BA, additional, McCauley, JL, additional, Qi, Z, additional, Caillier, SJ, additional, Gourraud, PA, additional, Yu, J, additional, Nathanson, L, additional, Belman, AL, additional, Hauser, SL, additional, Waubant, E, additional, Hedges, DJ, additional, and Oksenberg, JR, additional

Published
2012
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37. Different patterns of associations with anti-citrullinated protein antibody-positive and anti-citrullinated protein antibody-negative rheumatoid arthritis in the extended major histocompatibility complex region.

Author

Ding B, Padyukov L, Lundström E, Seielstad M, Plenge RM, Oksenberg JR, Gregersen PK, Alfredsson L, and Klareskog L

Abstract

OBJECTIVE: To identify additional variants in the major histocompatibility complex (MHC) region that independently contribute to risk in 2 disease subsets of rheumatoid arthritis (RA) defined according to the presence or absence of antibodies to citrullinated protein antigens (ACPAs). METHODS: In a multistep analytical strategy using unmatched as well as matched analyses to adjust for HLA-DRB1 genotype, we analyzed 2,221 single-nucleotide polymorphisms (SNPs) spanning 10.7 Mb, from 6p22.2 to 6p21.31, across the MHC. For ACPA-positive RA, we analyzed samples from the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) and the North American Rheumatoid Arthritis Consortium (NARAC) studies (totaling 1,255 cases and 1,719 controls). For ACPA-negative RA, we used samples from the EIRA study (640 cases and 670 controls). Plink and SAS statistical packages were used to conduct all statistical analyses. RESULTS: A total of 299 SNPs reached locus-wide significance (P < 2.3 x 10(-5)) for ACPA-positive RA, whereas surprisingly, no SNPs reached this significance for ACPA-negative RA. For ACPA-positive RA, we adjusted for known DRB1 risk alleles and identified additional independent associations with SNPs near HLA-DPB1 (rs3117213; odds ratio 1.42 [95% confidence interval 1.17-1.73], P(combined) = 0.0003 for the strongest association). CONCLUSION: There are distinct genetic patterns of MHC associations in the 2 disease subsets of RA defined according to ACPA status. HLA-DPB1 is an independent risk locus for ACPA-positive RA. We did not identify any associations with SNPs within the MHC for ACPA-negative RA. [ABSTRACT FROM AUTHOR]

Published
2009
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40. New insights into the genetics of multiple sclerosis.

Author

Baranzini SE, Oksenberg JR, and Hauser SL

Abstract

Tissue injury in multiple sclerosis (MS) results from an abnormal immune response to one or more myelin antigens that develop in genetically susceptible individuals after exposure to a causal agent that is yet undefined. The genetic component of MS etiology is believed to result from the action of several genes of moderate effect. The incomplete penetrance of MS susceptibility alleles probably reflects interactions with other genes, posttranscriptional regulatory mechanisms, and significant environmental influences. Equally significant is that genetic heterogeneity also likely exists, meaning that specific genes influence susceptibility and pathogenesis in some affecteds but not in others. Some loci may be involved in the initial pathogenic events, while others could influence the development and progression of the disease. The past few years have seen significant progress in the developments of laboratory and analytical approaches to study non-Mendelian complex genetic disorders and to define the pathological basis of demyelination. These developments have set the stage for the final characterization of the genes involved in MS susceptibility and pathogenesis. The identification and characterization of the genes are likely to define the basic etiology of the disease, improve risk assessment, and influence therapeutics. [ABSTRACT FROM AUTHOR]

Published
2002

41. Differential display analysis of murine encephalitogenic mRNA.

Author

Jeong, MC, Izikson, L, Uccelli, A, Brocke, S, and Oksenberg, JR

Abstract

Experimental autoimmune encephalomyelitis (EAE) is an inflammatory demyelinating disease which can be induced by inoculation with activated CD4+ T lymphocytes specific for myelin proteins. It has been postulated that autoreactive Th1-type CD4+ cells are responsible for the lesions, whereas autoreactive Th2-type cells suppress or modulate the disease. However, the mechanisms involved in the development of inflammatory lesions and neurologic deficits in EAE have not been fully described, and probably involve a complex array of mediators and alternative or redundant pathways. To identify additional factors associated with the pathological role of T cells in EAE, we adapted the differential mRNA display technique to fingerprint the transcripts expressed by encephalitogenic and non-encephalitogenic T cells. Using 60 primer combinations, 21 differentially expressed cDNAs were identified. Among them 13 are known sequences, including IL-3 in non-encephalitogenic lymphocytes. Their relevance for the disease process is discussed. [ABSTRACT FROM PUBLISHER]

Published
1998
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42. Early editorial manuscript screening versus obligate peer review: a randomized trial.

Author

Johnston SC, Lowenstein DH, Ferriero DM, Messing RO, Oksenberg JR, and Hauser SL

Abstract

Peer review is a cornerstone of scientific publication. However, it is time consuming for reviewers and contributors, and must be balanced with editorial oversight for balance and bias. To test a more efficient method of reviewing manuscripts, we performed a randomized trial comparing traditional peer review for all manuscripts received by the Annals of Neurology with an early screening approach in which six editors rejected a manuscript without external review when the chance of acceptance was deemed very low. Of the 351 manuscripts entered into the trial, 88 were randomized to traditional external review and 263 to early screening. Rates of final acceptance were similar in the two groups (p = 0.41). Final decisions were more delayed for traditional review (mean 48 days versus 18 days with early screening; p < 0.0001) and more reviewers were required for each manuscript (mean 2.3 versus 0.7 with early screening; p < 0.0001). Among accepted manuscripts, reviewer ratings of scientific and clinical impact were similar. We conclude that a method of early screening of manuscripts for appropriateness for publication results in substantial decreases in the time between manuscript submission and publication decisions, and reduces the burden on reviewers with minimal impact on the quality of accepted manuscripts. Editorial screening is now journal policy. Ann Neurol 2007;61:A10-A12. [ABSTRACT FROM AUTHOR]

Published
2007
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43. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis

Author

Bénédicte Dubois, Lucia Corrado, Deborah F. Mason, Allan G. Kermode, Pentti J. Tienari, Annette Bang Oturai, Charles Hillier, Adrian J. Ivinson, Stephen L. Hauser, Ashley Beecham, Jeannette Lechner-Scott, Vincent Thijs, Jonathan L. Haines, Sarah Edkins, Alexander T. Dilthey, Daniele Cusi, Guy Nagels, David A. Hafler, Mark Slee, Petra Nilsson, James S. Wiley, Lou Brundin, Amy Strange, Elizabeth Visser, Mireia Sospedra, Athena Hadjixenofontos, Sergio E. Baranzini, Jenny Link, Robert Andrews, Viola Biberacher, Helle Bach Søndergaard, Vittorio Martinelli, Tomas Olsson, Gillian L Hall, Stephen Sawcer, Stacy J. Caillier, Per Soelberg Sørensen, Céline Bellenguez, Cornelia M. van Duijn, Frauke Zipp, Nikolaos A. Patsopoulos, Cristin McCabe, Colin Freeman, Simon Broadley, Luisa Bernardinelli, Margaret A. Pericak-Vance, Jan Hillert, Wassila Carpentier, Sandip Shaunak, Anne Spurkland, Barnaby Fiddes, Judith Field, Jan Lycke, Christina M. Lill, Federica Esposito, Ioanna Konidari, Elisabeth Gulowsen Celius, Christian Gieger, Helmut Butzkueven, Ling Shen, James F. Wilson, Magdalena Lindén, Tejas S. Shah, Amie Baker, Dionysia K. Xifara, Hong Quach, Laura Bergamaschi, Rogier Q. Hintzen, Jacob L. McCauley, Janna Saarela, J W Thorpe, Christine Lebrun-Frenay, Felix Luessi, Sandra D'Alfonso, B. E. Kendall, Helga Westerlind, Giancarlo Comi, Nathalie Schnetz-Boutaud, Paola Brambilla, Chris Cotsapas, Anders Hamsten, William Camu, Achim Berthele, Kjell-Morten Myhr, Clive Hawkins, Richard Nicholas, James Harley, Carl A. Anderson, Keijo Koivisto, Irene Coman, Neil Robertson, Hakon Hakonarson, Finn Sellebjerg, Fredrik Piehl, Alessia Di Sapio, Loukas Moutsianas, Mehdi Alizadeh, Lars Alfredsson, Catherine Schaefer, David Rog, Virpi Leppa, C. Martin, Bruce A.C. Cree, Christopher Halfpenny, Irina Elovaara, Filippo Martinelli-Boneschi, Cordelia Langford, Hanne F. Harbo, Wim Robberecht, Isabelle Cournu-Rebeix, Steve Vucic, Izaura Lima Bomfim, Irene Y. Frohlich, Michelle Lee, Bertrand Fontaine, Bernhard Hemmer, Eva Zindler, Chris C. A. Spencer, Malin Larsson, Simon Shields, Ilijas Jelcic, Juliane Winkelmann, Jorge R. Oksenberg, Alastair Wilkins, Silvia Delgado, Volker Siffrin, Helena C. Kronsbein, Bruno Brochet, Panos Deloukas, Daniela Galimberti, Nikos Evangelou, Rebecca C. Selter, Maja Jagodic, Martin Duddy, Timothy Harrower, Per Hall, Nadia Barizzone, Siân Price, Matti Pirinen, Pierre-Antoine Gourraud, Thomas M.C. Binder, Giuseppe Liberatore, Mark Lathrop, M.-M. Hoshi, Garrett Hellenthal, Melissa Sorosina, Thomas Korn, Clara Guaschino, Roland Martin, Jeremy Hobart, Marco Salvetti, Peter Donnelly, Ingrid Kockum, An Goris, Alastair Compston, Mariaemma Rodegher, Dorothea Buck, Clara P. Manrique, Christiane Graetz, Benedicte A. Lie, Trevor J. Kilpatrick, Andrew Graham, Anu Kemppinen, Maria Ban, Gil McVean, John Zajicek, Hannah Blackburn, Mary F. Davis, Emilie Sundqvist, Bruce V. Taylor, Maurizio Leone, Lisa F. Barcellos, Fabio Macciardi, Gilles Defer, Vincent Damotte, Satu Männistö, Graeme J. Stewart, Gordon Mazibrada, Inger Lise Mero, Andre Franke, Philip L. De Jager, Verena Grummel, Mauri Reunanen, David R. Booth, Anna Ticca, Angela Jochim, Leentje Cosemans, Julia Y Mescheriakova, Cristina Agliardi, Paola Cavalla, Jeffrey C. Barrett, Sarah E. Hunt, Gavin Band, School of Life Sciences, University of Technology Sydney (UTS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Profium Oy [Helsinki], Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institute of Clinical Medicine [Oslo], Faculty of Medicine [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Michigan Technological University (MTU), The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], The Wellcome Trust Sanger Institute [Cambridge], Génétique épidémiologique et structures des populations humaines (Inserm U535), Epidémiologie, sciences sociales, santé publique (IFR 69), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-École des hautes études en sciences sociales (EHESS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-École des hautes études en sciences sociales (EHESS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Service de neurologie [Bordeaux], CHU Bordeaux [Bordeaux]-Groupe hospitalier Pellegrin, Karolinska Institutet [Stockholm], Institut des Neurosciences de Montpellier - Déficits sensoriels et moteurs (INM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Plateforme Post-génomique de la Pitié-Salpêtrière (P3S), UMS omique (OMIQUE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Pierre et Marie Curie - Paris 6 - UFR de Médecine Pierre et Marie Curie (UPMC), Université Pierre et Marie Curie - Paris 6 (UPMC), Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service de Neurologie [CHU Caen], Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Department of Statistics [Oxford], Centro Dino Ferrari [Milano], Università degli Studi di Milano [Milano] (UNIMI)-Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, Epidémiologie et Analyses en Santé Publique : risques, maladies chroniques et handicap (LEASP), Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Medical Epidemiology and Biostatistics (MEB), University College of London [London] (UCL), Fondation Jean Dausset CEPH, Centre Hospitalier Universitaire de Nice (CHU Nice), Dublin Institute of Technology (DIT), University of California [Irvine] (UCI), University of California, Géosciences Environnement Toulouse (GET), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Kaiser Permanente, Universität Zürich [Zürich] = University of Zurich (UZH), University Hospitals Leuven [Leuven], Department Biostatistics University of North Carolina, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Institute of Bioinformatics and Systems Biology [München], Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Yale University School of Medicine, Big Data Institute, Department of Clinical Neurosciences [Cambridge], University of Cambridge [UK] (CAM), Faculty of Engineering, Neuroprotection & Neuromodulation, Internal Medicine Specializations, Neurology, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS), Institut des Neurosciences de Montpellier (INM), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Yale School of Medicine [New Haven, Connecticut] (YSM), University of Oxford, Università degli Studi di Milano = University of Milan (UNIMI)-Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, University of California [Irvine] (UC Irvine), University of California (UC), Cardiology, Epidemiology, Oral and Maxillofacial Surgery, International Multiple Sclerosis Genetics, Consortium, Beecham, Ah, Patsopoulos, Na, Xifara, Dk, Davis, Mf, Kemppinen, A, Cotsapas, C, Shah, T, Spencer, C, Booth, D, Goris, A, Oturai, A, Saarela, J, Fontaine, B, Hemmer, B, Martin, C, Zipp, F, D'Alfonso, S, Martinelli Boneschi, F, Taylor, B, Harbo, Hf, Kockum, I, Hillert, J, Olsson, T, Ban, M, Oksenberg, Jr, Hintzen, R, Barcellos, Lf, Wellcome Trust Case Control Consortium, 2, International IBD Genetics, Consortium, Agliardi, C, Alfredsson, L, Alizadeh, M, Anderson, C, Andrews, R, Søndergaard, Hb, Baker, A, Band, G, Baranzini, Se, Barizzone, N, Barrett, J, Bellenguez, C, Bergamaschi, L, Bernardinelli, L, Berthele, A, Biberacher, V, Binder, Tm, Blackburn, H, Bomfim, Il, Brambilla, P, Broadley, S, Brochet, B, Brundin, L, Buck, D, Butzkueven, H, Caillier, Sj, Camu, W, Carpentier, W, Cavalla, P, Celius, Eg, Coman, I, Comi, Giancarlo, Corrado, L, Cosemans, L, Cournu Rebeix, I, Cree, Ba, Cusi, D, Damotte, V, Defer, G, Delgado, Sr, Deloukas, P, di Sapio, A, Dilthey, At, Donnelly, P, Dubois, B, Duddy, M, Edkins, S, Elovaara, I, Esposito, F, Evangelou, N, Fiddes, B, Field, J, Franke, A, Freeman, C, Frohlich, Iy, Galimberti, D, Gieger, C, Gourraud, Pa, Graetz, C, Graham, A, Grummel, V, Guaschino, C, Hadjixenofontos, A, Hakonarson, H, Halfpenny, C, Hall, G, Hall, P, Hamsten, A, Harley, J, Harrower, T, Hawkins, C, Hellenthal, G, Hillier, C, Hobart, J, Hoshi, M, Hunt, Se, Jagodic, M, Jelčić, I, Jochim, A, Kendall, B, Kermode, A, Kilpatrick, T, Koivisto, K, Konidari, I, Korn, T, Kronsbein, H, Langford, C, Larsson, M, Lathrop, M, Lebrun Frenay, C, Lechner Scott, J, Lee, Mh, Leone, Ma, Leppä, V, Liberatore, G, Lie, Ba, Lill, Cm, Lindén, M, Link, J, Luessi, F, Lycke, J, Macciardi, F, Männistö, S, Manrique, Cp, Martin, R, Martinelli, V, Mason, D, Mazibrada, G, Mccabe, C, Mero, Il, Mescheriakova, J, Moutsianas, L, Myhr, Km, Nagels, G, Nicholas, R, Nilsson, P, Piehl, F, Pirinen, M, Price, Se, Quach, H, Reunanen, M, Robberecht, W, Robertson, Np, Rodegher, M, Rog, D, Salvetti, M, Schnetz Boutaud, Nc, Sellebjerg, F, Selter, Rc, Schaefer, C, Shaunak, S, Shen, L, Shields, S, Siffrin, V, Slee, M, Sorensen, P, Sorosina, M, Sospedra, M, Spurkland, A, Strange, A, Sundqvist, E, Thijs, V, Thorpe, J, Ticca, A, Tienari, P, van Duijn, C, Visser, Em, Vucic, S, Westerlind, H, Wiley, J, Wilkins, A, Wilson, Jf, Winkelmann, J, Zajicek, J, Zindler, E, Haines, Jl, Pericak Vance, Ma, Ivinson, Aj, Stewart, G, Hafler, D, Hauser, Sl, Compston, A, Mcvean, G, De Jager, P, Sawcer, Sj, and Mccauley, J. L.

Subjects
Multiple Sclerosis, Genotype, [SDV]Life Sciences [q-bio], European Continental Ancestry Group, Genome-wide association study, CLEC16A, Biology, multiple sclerosis, Major histocompatibility complex, Polymorphism, Single Nucleotide, Article, White People, 03 medical and health sciences, 0302 clinical medicine, Research Support, N.I.H., Extramural, Gene Frequency, Polymorphism (computer science), Journal Article, Genetics, medicine, Humans, Genetic Predisposition to Disease, Allele, Genotyping, Allele frequency, 030304 developmental biology, 0303 health sciences, Research Support, Non-U.S. Gov't, Multiple sclerosis, Chromosome Mapping, Genetic Variation, medicine.disease, 3. Good health, Genetic Loci, biology.protein, 030217 neurology & neurosurgery, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology, Genome-Wide Association Study
Abstract

International audience; Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.

Published
2016
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44. Power estimation for non-standardized multisite studies

Author

Till Sprenger, Massimo Filippi, David A. Hafler, Sara Llufriu, Gina Kirkish, Mona K. Beyer, Pablo Villoslada, Xavier Montalban, Sandra D'Alfonso, Anisha Keshavan, Philippe Demaerel, Claus Zimmer, Pradip M. Pattany, Mike P. Wattjes, Christiane Graetz, Ludwig Kappos, Alessandro Carriero, Jorge R. Oksenberg, Jacob L. McCauley, Roland G. Henry, Alyssa H. Zhu, Adriane Gröger, Michael Amann, An Goris, Laura Gaetano, Antje Bischof, Filippo Martinelli-Boneschi, Hanne F. Harbo, Sergiu Groppa, Alessandro Stecco, Stefano Magon, Margaret A. Pericak-Vance, Daniel Pelletier, Frauke Zipp, Regina Schlaeger, Alex Rovira, Nico Papinutto, Friedemann Paul, Albert Saiz, Maria A. Rocca, Isabelle Cournu-Rebeix, William A. Stern, Howard L. Weiner, Bernhard Hemmer, Russell T. Shinohara, Manuel Comabella, Bénédicte Dubois, Rohit Bakshi, Jason C. Crane, Vinzenz Fleischer, Bernard M. J. Uitdehaag, Jens Wuerfel, Stephen L. Hauser, Mark Mühlau, Kesshi M. Jordan, Bertrand Fontaine, Keshavan, A, Paul, F, Beyer, Mk, Zhu, Ah, Papinutto, N, Shinohara, Rt, Stern, W, Amann, M, Bakshi, R, Bischof, A, Carriero, A, Comabella, M, Crane, Jc, D'Alfonso, S, Demaerel, P, Dubois, B, Filippi, M, Fleischer, V, Fontaine, B, Gaetano, L, Goris, A, Graetz, C, Gröger, A, Groppa, S, Hafler, Da, Harbo, Hf, Hemmer, B, Jordan, K, Kappos, L, Kirkish, G, Llufriu, S, Magon, S, Martinelli-Boneschi, F, Mccauley, J, Montalban, X, Muhlau, M, Pelletier, D, Pattany, Pm, Pericak-Vance, M, Rebeix, I, Rocca, M, Rovira, A, Schlaeger, R, Saiz, A, Sprenger, T, Stecco, A, Uitdehaag, Bm, Villoslada, P, Wattjes, Mp, Weiner, H, Wuerfel, J, Zimmer, C, Zipp, F, International Multiple Sclerosis Genetics, Consortium, Hauser, S, Oksenberg, Jr, Henry, Rg, Bioengineering Graduate Program (joint degree with UCSF), Department of Bioengineering [Berkeley], University of California [Berkeley], University of California-University of California-University of California [Berkeley], University of California-University of California-University of California [San Francisco] (UCSF), University of California, Department of Neurology [San Francisco], University of California [San Francisco] (UCSF), University of California-University of California, Max Delbrueck Centre for Molecular Medicine, NeuroCure Clinical Research Center and Clinical and Experimental Multiple Sclerosis Research Center, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Department of Radiology and Nuclear Medicine, Oslo University Hospital [Oslo], Department of Biostatistics and Epidemiology [Philadelphia], Perelman School of Medicine, University of Pennsylvania [Philadelphia]-University of Pennsylvania [Philadelphia], Department of Neurology [Suisse], University Hospital Basel [Basel], Medical Image Analysis Center (MIAC AG), Brigham and Women's Hospital [Boston], Clinical Immunology, Department of Translational Medicine, UPO University, Vall d'Hebron University Hospital [Barcelona], Department of Radiology and Biomedical Imaging [San Francisco], Department of Health Sciences, UPO University, Department of Radiology[Leuven], University Hospitals Leuven [Leuven], Department of Neurosciences Leuven, University of Leuven K.U.Leuven, Institute of Experimental Neurology, Milan, University Medical Centre of the Johannes Gutenberg University Mainz, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), University Medical Centre of the Johannes Gutenberg-University Mainz, Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Departments of Neurology and Immunobiology [Yale], Yale University School of Medicine, Department of Neurology [Oslo], Akershus University Hospital [Lørenskog], Department Neurology of the Klinikum rechts der Isar, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Munich Cluster of Systems Neurology (SyNery), Center for Neuroimmunology, Service of Neurology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Neuroimaging Research Unit, Scientific Institute and University Hospital San Raffaele, Milan, John P. Hussman Institute for Human Genomics, University of Miami Leonard M. Miller School of Medicine (UMMSM), TUM–Neuroimaging Center, Department of Radiology [Miami], DKD Helios Klinik Wiesbaden, Section of Neuroradiology [Novara], Maggiore Hospital, VU University Medical Center [Amsterdam], Dept Neuroradiology [Munich], Klinikums rechts der Isar, University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC)-University of California [Berkeley] (UC Berkeley), University of California (UC)-University of California (UC)-University of California [San Francisco] (UC San Francisco), University of California (UC), University of California [San Francisco] (UC San Francisco), University of California (UC)-University of California (UC), University of Pennsylvania-University of Pennsylvania, Johannes Gutenberg - Universität Mainz = Johannes Gutenberg University (JGU), Yale School of Medicine [New Haven, Connecticut] (YSM), Neurology, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Radiology and nuclear medicine

Subjects
Computer science, Cognitive Neuroscience, computer.software_genre, Sensitivity and Specificity, 050105 experimental psychology, Imaging phantom, Article, Set (abstract data type), 03 medical and health sciences, 0302 clinical medicine, Distortion, Image Interpretation, Computer-Assisted, Calibration, medicine, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, Humans, 0501 psychology and cognitive sciences, Segmentation, Computer Simulation, 10. No inequality, Scaling, Models, Statistical, medicine.diagnostic_test, 05 social sciences, Contrast (statistics), Brain, Reproducibility of Results, Magnetic resonance imaging, Equipment Design, Scale factor, Image Enhancement, Magnetic Resonance Imaging, United States, Equipment Failure Analysis, Europe, Neurology, Ordinary least squares, Data mining, Function and Dysfunction of the Nervous System, Artifacts, computer, 030217 neurology & neurosurgery, Algorithms
Abstract

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this assumption, we provide a new statistical framework and derive a power equation to define inclusion criteria for a set of sites based on the variability of their scaling factors. We estimated the scaling factors of 20 scanners with heterogeneous hardware and sequence parameters by scanning a single set of 12 subjects at sites across the United States and Europe. Regional volumes and their scaling factors were estimated for each site using Freesurfer's segmentation algorithm and ordinary least squares, respectively. The scaling factors were validated by comparing the theoretical and simulated power curves, performing a leave-one-out calibration of regional volumes, and evaluating the absolute agreement of all regional volumes between sites before and after calibration. Using our derived power equation, we were able to define the conditions under which harmonization is not necessary to achieve 80% power. This approach can inform choice of processing pipelines and outcome metrics for multisite studies based on scaling factor variability across sites, enabling collaboration between clinical and research institutions. publisher: Elsevier articletitle: Power estimation for non-standardized multisite studies journaltitle: NeuroImage articlelink: http://dx.doi.org/10.1016/j.neuroimage.2016.03.051 content_type: article copyright: © 2016 The Authors. Published by Elsevier Inc. ispartof: NeuroImage vol:134 pages:281-294 ispartof: location:United States status: published

Published
2016
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45. Fine mapping and functional analysis of the multiple sclerosis risk gene CD6

Author

Rafael Arroyo, Bhairavi Swaminathan, Elena Urcelay, David Otaegui, Mª Jesus Pinto-Medel, Antonio Alcina, Koen Vandenbroeck, Alfredo Antigüedad, Fuencisla Matesanz, Miguel Lucas, María García-Barcina, María Fedetz, Oscar Fernandez, Eva Tolosa, Angelica Cuapio, Teresa Órpez, Javier Olascoaga, Miguel A. Ortiz, Iraide Alloza, Jorge R. Oksenberg, [Swaminathan,B, Alloza,I, Vandenbroeck,K] Neurogenomiks Laboratory, University of the Basque Country (UPV/EHU), Leioa, Spain. [Cuapio,A, Tolosa,E] Department of Immunology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. [Matesanz,F, Alcina,A, Fedetz,M] Instituto de Parasitología y Biomedicina 'López Neyra' Consejo Superior de Investigaciones Científicas (CSIC), Granada, Spain. [García-Barcina,M] Servicio de Genética, Hospital de Basurto, Bilbao, Spain. [Fernández,O] Department of Neurology, Institute of Clinical Neurosciences, Hospital Regional Universitario Carlos Haya, Málaga, Spain. [ Lucas,M] Unidad de Esclerosis Múltiple, Hospital Virgen Macarena, Sevilla, Spain. [Orpez,T, Pinto-Medel,MJ] Research Laboratory, Institute of Clinical Neurosciences, Hospital Regional Universitario Carlos Haya, Málaga, Spain. [Otaegui,D] Área de Neurociencias, Instituto de Investigación Sanitaria Biodonostia, San Sebastián, Spain. [ Olascoaga,J] Servicio de Neurología, Unidad de Esclerosis Múltiple, Hospital Donostia, San Sebastián, Spain. [Urcelay,E, Ortiz,MA] Immunology Department H. Clínico S. Carlos, Instituto de Investigación Sanitaria S. Carlos (IdISSC), Madrid, Spain. [Arroyo,R] Multiple Sclerosis Unit, Neurology Department H. Clínico S. Carlos, Instituto de Investigación Sanitaria S. Carlos (IdISSC), Madrid, Spain. [Oksenberg,JR] Department of Neurology, University of California San Francisco, San Francisco, California, United States of America. [Antigüedad,A] Servicio de Neurología, Hospital de Basurto, Bilbao, Spain. [Vandenbroeck,K] IKERBASQUE, Basque Foundation for Science, Bilbao, Spain, This work was supported from the European Community’s Seventh Framework Programme [FP7/2007–2013] under grant agreement no. 212877 (UEPHA*MS, and ref. IT512-10). UEPHA*MS (No 2121877). Ministerio de Ciencia e Innovación - FEDER (SAF2009-11491) and FIS_FEDER (CP10/00526), Junta de Andalucía-FEDER (P07-CVI-02551).

Subjects
Antigens, Differentiation, T-Lymphocyte, CD4-Positive T-Lymphocytes, Male, BIOCHEMISTRY AND MOLECULAR BIOLOGY, lcsh:Medicine, Genome-wide association study, Polimorfismo genético, CD8-Positive T-Lymphocytes, Lymphocyte Activation, Linkage Disequilibrium, Phenomena and Processes::Genetic Phenomena::Genotype::Haplotypes [Medical Subject Headings], Organisms::Eukaryota::Animals::Chordata::Vertebrates::Mammals::Primates::Haplorhini::Catarrhini::Hominidae::Humans [Medical Subject Headings], 0302 clinical medicine, Health Care::Environment and Public Health::Public Health::Epidemiologic Methods::Epidemiologic Research Design::Genome-Wide Association Study [Medical Subject Headings], Gene Order, Cluster Analysis, Cytotoxic T cell, lcsh:Science, Genetics, 0303 health sciences, Multidisciplinary, Genome-wide association, T Cells, Chromosome Mapping, Genomics, Helper 17 cells, Neurology, AGRICULTURAL AND BIOLOGICAL SCIENCES, Cytokines, Female, Haplotipos, Diseases::Immune System Diseases::Autoimmune Diseases::Autoimmune Diseases of the Nervous System::Demyelinating Autoimmune Diseases, CNS::Multiple Sclerosis [Medical Subject Headings], Research Article, Adult, Multiple Sclerosis, Immune Cells, Immunology, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, White People, Autoimmune Diseases, Central-nervous-system, Young Adult, 03 medical and health sciences, Antigen, Antigens, CD, Humans, SNP, Genetic Predisposition to Disease, Protein Interaction Domains and Motifs, 030304 developmental biology, Inflammation, MEDICINE, Haplotype, lcsh:R, Immunity, Timocitos, Phenomena and Processes::Genetic Phenomena::Genetic Variation::Polymorphism, Genetic [Medical Subject Headings], Haplotypes, Genetic Loci, Spain, Esclerosis múltiple, estudio de asociación genómica completa, Genetic Polymorphism, Anatomy::Cells::Thymocytes [Medical Subject Headings], Clinical Immunology, Cytokine secretion, lcsh:Q, Population Genetics, CD8, 030215 immunology, Anti-CD6 monoclonal-antibody
Abstract

Art. nº e62376; v. 8; issue 4, CD6 has recently been identified and validated as risk gene for multiple sclerosis (MS), based on the association of a single nucleotide polymorphism (SNP), rs17824933, located in intron 1. CD6 is a cell surface scavenger receptor involved in T-cell activation and proliferation, as well as in thymocyte differentiation. In this study, we performed a haptag SNP screen of the CD6 gene locus using a total of thirteen tagging SNPs, of which three were non-synonymous SNPs, and replicated the recently reported GWAS SNP rs650258 in a Spanish-Basque collection of 814 controls and 823 cases. Validation of the six most strongly associated SNPs was performed in an independent collection of 2265 MS patients and 2600 healthy controls. We identified association of haplotypes composed of two non-synonymous SNPs [rs11230563 (R225W) and rs2074225 (A257V)] in the 2nd SRCR domain with susceptibility to MS (Pmax(T) permutation=161024). The effect of these haplotypes on CD6 surface expression and cytokine secretion was also tested. The analysis showed significantly different CD6 expression patterns in the distinct cell subsets, i.e. – CD4+ naı¨ve cells, P = 0.0001; CD8+ naı¨ve cells, P,0.0001; CD4+ and CD8+ central memory cells, P = 0.01 and 0.05, respectively; and natural killer T (NKT) cells, P = 0.02; with the protective haplotype (RA) showing higher expression of CD6. However, no significant changes were observed in natural killer (NK) cells, effector memory and terminally differentiated effector memory T cells. Our findings reveal that this new MS-associated CD6 risk haplotype significantly modifies expression of CD6 on CD4+ and CD8+ T cells., doi:10.1371/journal.pone.0062376, European Community 212877; Gobierno Vasco (Grupos de Investigacion del Sistema Universitario Vasco) IT512-10;Ministerio de Ciencia e Innovacion - FEDER SAF2009-11491;FIS_FEDER CP10/00526 ;Junta de Andalucia-FEDER P07-CVI-02551

Published
2013

46. APOE epsilon variation in multiple sclerosis susceptibility and disease severity: some answers

Author

Reinhold Schmidt, Beata Zakrzewska-Pniewska, W. E. R. Ollier, Alastair Compston, Rita Cittadella, Helena Schmidt, Jonathan L. Haines, Stephen Sawcer, Richard M. Burwick, S. J. M. Weatherby, Hubert Kwieciński, Patricia P. Ramsay, Christian Enzinger, Lisa F. Barcellos, Masaaki Niino, Nikos Evangelou, Jacqueline Palace, Chris H. Polman, Seiji Kikuchi, Franz Fazekas, Aldo Quattrone, J. Zwemmer, Peter Høgh, Margaret A. Pericak-Vance, Jan Hillert, Bernard M. J. Uitdehaag, Stephen L. Hauser, Maria Edite Rio, Giovanni Savettieri, Silke Schmidt, Mónica Santos, Patrícia Maciel, Jorge R. Oksenberg, C. P. Hawkins, Thomas Masterman, [et al.], Universidade do Minho, Burwick, RM, Ramsay, PP, Haines, JL, Hauser, SL, Oksenberg, JR, Pericak-Vance, MA, Schmidt, S, Compston, A, Sawcer, S, Cittadella,R, Savettieri,G, Quattrone,A, Polman,CH, Uitdehaag, BM, Zwemmer, JN, Hawkins,CP, Ollier, WE, Weatherby, S, Enzinger, C, Fazekas, F, Schmidt, H, Schmidt, R, Hillert, J, Masterman, T, Hogh, P, Niino, M, Kikuchi,S, Maciel, P, Santos, M, Rio, ME, Kwiecinski, H, Zakrzewska-Pniewska, B, Evangelou, N, Palace, J, and Barcellos, LF.

Subjects
Apolipoprotein E, Oncology, Risk, medicine.medical_specialty, Pathology, Multiple Sclerosis, Genotype, Apolipoprotein E2, Apolipoprotein E4, Polymorphism, Single Nucleotide, Severity of Illness Index, Linkage Disequilibrium, Primary progressive, Central nervous system disease, 03 medical and health sciences, 0302 clinical medicine, Apolipoproteins E, Disease severity, Polymorphism (computer science), Internal medicine, medicine, Humans, Genetic Predisposition to Disease, 10. No inequality, Alleles, 030304 developmental biology, 0303 health sciences, Expanded Disability Status Scale, Polymorphism, Genetic, Science & Technology, business.industry, Multiple sclerosis, medicine.disease, 3. Good health, Pedigree, Phenotype, Case-Control Studies, Settore MED/26 - Neurologia, Neurology (clinical), business, Multiple Sclerosis, APOE, disease severity, meta-analysis, 030217 neurology & neurosurgery
Abstract

Background: Previous studies have examined the role of APOE variation in multiple sclerosis (MS), but have lacked the statistical power to detect modest genetic influences on risk and disease severity. The meta- and pooled analyses presented here utilize the largest collection, to date, of MS cases, controls, and families genotyped for the APOE epsilon polymorphism. Methods: Studies of MS and APOE were identified by searches of PubMed, Biosis, Web of Science, Cochrane Review, and Embase. When possible, authors were contacted for individual genotype data. Meta-analyses of MS case-control data and family-based analyses were performed to assess the association of APOE epsilon genotype with disease risk. Pooled analyses of MS cases were also performed to assess the influence of APOE epsilon genotype on disease severity. Results: A total of 22 studies (3,299 MS cases and 2,532 controls) were available for meta-analysis. No effect of e2 or e4 status on MS risk was observed (summary OR 1.14, 95% CI 0.96–1.34 and OR 0.89, 95% CI 0.78–1.01). Results obtained from analyses of APOE genotypes in 1,279 MS families were also negative ( p = 0.61). Finally, results from pooled analyses of 4,048 MS cases also argue strongly that APOE epsilon status does not distinguish a relapsing-remitting from primary progressive disease course, or influence disease severity, as measured by the Expanded Disability Status Scale and disease duration. Conclusion: Overall, these findings do not support a role for APOE in multiple sclerosis, and underscore the importance of using large sample sizes to detect modest genetic effects, particularly in studies of genotype-phenotype relationships.

Published
2006

47. Heterogeneity at the HLA-DRB1 locus and risk for multiple sclerosis

Author

Carolyn Deloa, Bruce C.A. Cree, Lisa F. Barcellos, Giovanni Savettieri, Antonio Uccelli, Stephen Sawcer, Jorge R. Oksenberg, Farren B.S. Briggs, Xavier Montalban, Patricia P. Ramsay, Margaret A. Pericak-Vance, Glenys Thomson, Pablo Villoslada, Ann B. Begovich, Robin R. Lincoln, Stephen L. Hauser, Jonathan L. Haines, Sergio E. Baranzini, Alastair Compston, BARCELLOS LF, SAWCER S, RAMSAY PP, BARANZINI SE, THOMSON G, BRIGGS F, CREE BC, BEGOVICH AB, VILLOSLADA P, MONTALBAN X, UCCELLI A, SAVETTIERI G, LINCOLN RR, DELOA C, HAINES JL, PERICAK-VANCE MA, COMPSTON A, HAUSER SL, and OKSENBERG JR

Subjects
Models, Molecular, Male, Sequence Homology, immune system diseases, Models, Risk Factors, Databases, Genetic, Adult, Alleles, Amino Acid Sequence, Databases, Genetic, Female, Genetic Variation, Genotype, HLA-DR Antigens, chemistry/genetics, HLA-DRB1 Chains, Humans, Male, Middle Aged, Models, Molecular, Molecular Sequence Data, Multiple Sclerosis, Chronic Progressive, genetics/immunology, Multiple Sclerosis, genetics/immunology, Phenotype, Risk Factors, Sequence Homology, Amino Acid, skin and connective tissue diseases, HLA-DRB1, Genetics (clinical), Genetics, General Medicine, Multiple Sclerosis, Chronic Progressive, Middle Aged, Phenotype, Female, musculoskeletal diseases, Adult, Multiple Sclerosis, Genotype, Molecular Sequence Data, Locus (genetics), Human leukocyte antigen, Biology, Databases, Alleles, phenotype, heterogeneity, human leukocyte antigens, age of onset, chromosomes, genes, genotype, haplotypes,multiple sclerosis, relapsing-remitting, genetics, disability, primary progressive multiple sclerosis, hla-drb1 gene, illness length, severity of illness, Genetic, Genetic variation, medicine, Humans, Amino Acid Sequence, Allele, Molecular Biology, Alleles, Sequence Homology, Amino Acid, Multiple sclerosis, Haplotype, Genetic Variation, Molecular, HLA-DR Antigens, medicine.disease, genetics/immunology, chemistry/genetics, Immunology, Age of onset, HLA-DRB1 Chains
Abstract

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

Published
2006

48. Characterizing the mechanisms of progression in multiple sclerosis. Evidence and new hypotheses for future directions

Author

JT Phillips, John R. Corboy, Bernhard Hemmer, Nitin J. Karandikar, H.-P. Hartung, Stephen G. Waxman, Elliot M. Frohman, Michael K. Racke, Stephen L. Hauser, Jorge R. Oksenberg, J. Wilken, Bruce A.C. Cree, J. De Keyser, Lawrence Steinman, Olaf Stuve, Nancy L. Monson, Claudia F. Lucchinetti, Massimo Filippi, Frohman, Em, Filippi, Massimo, Stuve, O, Waxman, Sg, Corboy, J, Phillips, Jt, Lucchinetti, C, Wilken, J, Karandikar, N, Hemmer, B, Monson, N, Dekeyser, J, Hartung, H, Steinman, L, Oksenberg, Jr, Cree, Bac, Hauser, S, Racke, Mk, and Gerontology

Subjects
Multiple Sclerosis, Signs and symptoms, Disease, CD8(+) T-CELLS, MYELIN BASIC-PROTEIN, EXPERIMENTAL ALLERGIC ENCEPHALOMYELITIS, Research Support, Models, Biological, Disease course, Multiple Sclerosis/genetics/*immunology/*pathology, Arts and Humanities (miscellaneous), ALTERED PEPTIDE LIGAND, Models, N.I.H, medicine, Humans, Disease process, genetics, Non-U.S. Gov't, TUMOR-NECROSIS-FACTOR, business.industry, Multiple sclerosis, Disease progression, Neurosciences, Extramural, APOLIPOPROTEIN-E GENOTYPE, medicine.disease, Biological, CNS WHITE-MATTER, RECEPTOR ANTAGONIST GENES, MAJOR HISTOCOMPATIBILITY COMPLEX, Treatment intervention, EXPERIMENTAL AUTOIMMUNE ENCEPHALOMYELITIS, Immune System, Inflammatory cascade, Disease Progression, Immune System/physiopathology, Neurology (clinical), business, Neuroscience
Abstract

Major advancements have been achieved in our ability to diagnose multiple sclerosis (MS) and to commence treatment intervention with agents that can favorably affect the disease course. Although MS exacerbations and the emergence of disability constitute the more conspicuous aspects of the disease process, evidence has confirmed that most of the disease occurs on a constitutive and occult basis. Disease-modifying therapies appear to be modest in the magnitude of their treatment effects, particularly in the progressive stage of the disease. Therapeutic strategies currently used for MS primarily target the inflammatory cascade. Several potential mechanisms appear to be involved in the progression of MS. Characterizing these mechanisms will result in a better understanding of the various forms of the disorder and how to effectively treat its clinical manifestations. It is our objective within this 2-part series on progression in MS to offer both evidence-based observations and hypothesis-driven expert perspectives on what constitutes the cause of progression in MS. We have chosen areas of inquiry that appear to have been most productive in helping us to better conceptualize the landscape of what MS looks like pathologically, immunologically, neuroscientifically, radiographically, and genetically. We have attempted to advance hypotheses focused on a deeper understanding of what contributes to the progression of this illness and to illustrate new technical capabilities that are catalyzing novel research initiatives targeted at achieving a more complete understanding of progression in MS.

Published
2005

49. The HLA locus and multiple sclerosis in Sicily

Author

David Brassat, G. Savettieri, L. F. Barcellos, Patrizia Proia, Stephen L. Hauser, G. McNeill, Giuseppe Salemi, Jorge R. Oksenberg, BRASSAT D, SALEMI G, BARCELLOS LF, MCNEILL G, PROIA P, HAUSER SL, OKSENBERG JR, and SAVETTIERI G

Subjects
Adult, Male, Risk, musculoskeletal diseases, Multiple Sclerosis, Adolescent, Genes, MHC Class II, Locus (genetics), Human leukocyte antigen, Biology, Severity of Illness Index, Linkage Disequilibrium, Cohort Studies, Disability Evaluation, Gene Frequency, immune system diseases, Multiple Sclerosis/epidemiology, Prevalence, medicine, Humans, Genetic Predisposition to Disease, Age of Onset, Allele, skin and connective tissue diseases, Sicily, Alleles, Genetic association, Genetics, HLA-D Antigens, Incidence, Multiple sclerosis, Haplotype, Gene Pool, medicine.disease, language.human_language, Settore BIO/18 - Genetica, Haplotypes, language, Female, Allelic heterogeneity, Settore MED/26 - Neurologia, Neurology (clinical), Sicilian
Abstract

The authors report the analysis of HLA-class II allelic heterogeneity in a well characterized multiple sclerosis (MS) Sicilian dataset. Family-based association analysis revealed evidence for excess transmission to affected individuals for alleles HLA-DRB1*1501, DRB1*04, and DQB1*0302. When analyzed as haplotypes, the authors observed excess transmission for the DRB1*0400-DQB1*0302 haplotype. Sicilian patients share the HLA-DRB1*1501 susceptibility allele with affecteds living in continental Italy, but also display the allelic heterogeneity that characterizes Mediterranean populations.

Published
2005

50. MHConstructor: a high-throughput, haplotype-informed solution to the MHC assembly challenge.

Author

Wade KJ, Suseno R, Kizer K, Williams J, Boquett J, Caillier S, Pollock NR, Renschen A, Santaniello A, Oksenberg JR, Norman PJ, Augusto DG, and Hollenbach JA

Subjects
Humans, Software, High-Throughput Nucleotide Sequencing methods, Algorithms, Haplotypes, Major Histocompatibility Complex genetics
Abstract

The extremely high levels of genetic polymorphism within the human major histocompatibility complex (MHC) limit the usefulness of reference-based alignment methods for sequence assembly. We incorporate a short-read, de novo assembly algorithm into a workflow for novel application to the MHC. MHConstructor is a containerized pipeline designed for high-throughput, haplotype-informed, reproducible assembly of both whole genome sequencing and target capture short-read data in large, population cohorts. To-date, no other self-contained tool exists for the generation of de novo MHC assemblies from short-read data. MHConstructor facilitates wide-spread access to high-quality, alignment-free MHC sequence analysis., (© 2024. The Author(s).)

Published
2024
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