Medicine (RMH) - Research Publications

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    Fine-Mapping the Genetic Association of the Major Histocompatibility Complex in Multiple Sclerosis: HLA and Non-HLA Effects
    Patsopoulos, NA ; Barcellos, LF ; Hintzen, RQ ; Schaefer, C ; Van Duijn, CM ; Noble, JA ; Raj, T ; Gourraud, P-A ; Stranger, BE ; Oksenberg, J ; Olsson, T ; Taylor, BV ; Sawcer, S ; Hafler, DA ; Carrington, M ; De Jager, PL ; De Bakker, PIW ; Gibson, G (PUBLIC LIBRARY SCIENCE, 2013-11)
    The major histocompatibility complex (MHC) region is strongly associated with multiple sclerosis (MS) susceptibility. HLA-DRB1*15:01 has the strongest effect, and several other alleles have been reported at different levels of validation. Using SNP data from genome-wide studies, we imputed and tested classical alleles and amino acid polymorphisms in 8 classical human leukocyte antigen (HLA) genes in 5,091 cases and 9,595 controls. We identified 11 statistically independent effects overall: 6 HLA-DRB1 and one DPB1 alleles in class II, one HLA-A and two B alleles in class I, and one signal in a region spanning from MICB to LST1. This genomic segment does not contain any HLA class I or II genes and provides robust evidence for the involvement of a non-HLA risk allele within the MHC. Interestingly, this region contains the TNF gene, the cognate ligand of the well-validated TNFRSF1A MS susceptibility gene. The classical HLA effects can be explained to some extent by polymorphic amino acid positions in the peptide-binding grooves. This study dissects the independent effects in the MHC, a critical region for MS susceptibility that harbors multiple risk alleles.
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    Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis
    Lin, R ; Charlesworth, J ; Stankovich, J ; Perreau, VM ; Brown, MA ; Taylor, BV ; Toland, AE (PUBLIC LIBRARY SCIENCE, 2013-03-05)
    Genome-wide association studies (GWAS) have identified around 60 common variants associated with multiple sclerosis (MS), but these loci only explain a fraction of the heritability of MS. Some missing heritability may be caused by rare variants that have been suggested to play an important role in the aetiology of complex diseases such as MS. However current genetic and statistical methods for detecting rare variants are expensive and time consuming. 'Population-based linkage analysis' (PBLA) or so called identity-by-descent (IBD) mapping is a novel way to detect rare variants in extant GWAS datasets. We employed BEAGLE fastIBD to search for rare MS variants utilising IBD mapping in a large GWAS dataset of 3,543 cases and 5,898 controls. We identified a genome-wide significant linkage signal on chromosome 19 (LOD = 4.65; p = 1.9×10(-6)). Network analysis of cases and controls sharing haplotypes on chromosome 19 further strengthened the association as there are more large networks of cases sharing haplotypes than controls. This linkage region includes a cluster of zinc finger genes of unknown function. Analysis of genome wide transcriptome data suggests that genes in this zinc finger cluster may be involved in very early developmental regulation of the CNS. Our study also indicates that BEAGLE fastIBD allowed identification of rare variants in large unrelated population with moderate computational intensity. Even with the development of whole-genome sequencing, IBD mapping still may be a promising way to narrow down the region of interest for sequencing priority.
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    Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis
    Lee, SH ; Harold, D ; Nyholt, DR ; Goddard, ME ; Zondervan, KT ; Williams, J ; Montgomery, GW ; Wray, NR ; Visscher, PM (OXFORD UNIV PRESS, 2013-02-15)
    Common diseases such as endometriosis (ED), Alzheimer's disease (AD) and multiple sclerosis (MS) account for a significant proportion of the health care burden in many countries. Genome-wide association studies (GWASs) for these diseases have identified a number of individual genetic variants contributing to the risk of those diseases. However, the effect size for most variants is small and collectively the known variants explain only a small proportion of the estimated heritability. We used a linear mixed model to fit all single nucleotide polymorphisms (SNPs) simultaneously, and estimated genetic variances on the liability scale using SNPs from GWASs in unrelated individuals for these three diseases. For each of the three diseases, case and control samples were not all genotyped in the same laboratory. We demonstrate that a careful analysis can obtain robust estimates, but also that insufficient quality control (QC) of SNPs can lead to spurious results and that too stringent QC is likely to remove real genetic signals. Our estimates show that common SNPs on commercially available genotyping chips capture significant variation contributing to liability for all three diseases. The estimated proportion of total variation tagged by all SNPs was 0.26 (SE 0.04) for ED, 0.24 (SE 0.03) for AD and 0.30 (SE 0.03) for MS. Further, we partitioned the genetic variance explained into five categories by a minor allele frequency (MAF), by chromosomes and gene annotation. We provide strong evidence that a substantial proportion of variation in liability is explained by common SNPs, and thereby give insights into the genetic architecture of the diseases.
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    Resequencing and fine-mapping of the chromosome 12q13-14 locus associated with multiple sclerosis refines the number of implicated genes
    Cortes, A ; Field, J ; Glazov, EA ; Hadler, J ; Stankovich, J ; Brown, MA (OXFORD UNIV PRESS, 2013-06-01)
    Multiple sclerosis (MS) is a common chronic inflammatory disease of the central nervous system. Susceptibility to the disease is affected by both environmental and genetic factors. Genetic factors include haplotypes in the histocompatibility complex (MHC) and over 50 non-MHC loci reported by genome-wide association studies. Amongst these, we previously reported polymorphisms in chromosome 12q13-14 with a protective effect in individuals of European descent. This locus spans 288 kb and contains 17 genes, including several candidate genes which have potentially significant pathogenic and therapeutic implications. In this study, we aimed to fine-map this locus. We have implemented a two-phase study: a variant discovery phase where we have used next-generation sequencing and two target-enrichment strategies [long-range polymerase chain reaction (PCR) and Nimblegen's solution phase hybridization capture] in pools of 25 samples; and a genotyping phase where we genotyped 712 variants in 3577 healthy controls and 3269 MS patients. This study confirmed the association (rs2069502, P = 9.9 × 10(-11), OR = 0.787) and narrowed down the locus of association to an 86.5 kb region. Although the study was unable to pinpoint the key-associated variant, we have identified a 42 (genotyped and imputed) single-nucleotide polymorphism haplotype block likely to harbour the causal variant. No evidence of association at previously reported low-frequency variants in CYP27B1 was observed. As part of the study we compared variant discovery performance using two target-enrichment strategies. We concluded that our pools enriched with Nimblegen's solution phase hybridization capture had better sensitivity to detect true variants than the pools enriched with long-range PCR, whilst specificity was better in the long-range PCR-enriched pools compared with solution phase hybridization capture enriched pools; this result has important implications for the design of future fine-mapping studies.
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    Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
    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 ; Sondergaard, 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 ; Franke, A ; Freeman, C ; Frohlich, IY ; Galimberti, D ; Gieger, C ; Gourraud, P-A ; 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 ; Jelcic, 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 ; Leppa, V ; Liberatore, G ; Lie, BA ; Lill, CM ; Linden, M ; Link, J ; Luessi, F ; Lycke, J ; Macciardi, F ; Mannisto, S ; Manrique, CP ; Martin, R ; Martinelli, V ; Mason, D ; Mazibrada, G ; McCabe, C ; Mero, I-L ; Mescheriakova, J ; Moutsianas, L ; Myhr, K-M ; 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, PS ; 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, JS ; 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 ; McCauley, JL (NATURE PUBLISHING GROUP, 2013-11)
    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.