Anatomy and Neuroscience - 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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    Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data
    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 (BMC, 2011)
    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 other hand, a significant difference (F = 2.75, P = 0.04) was detected for age of disease onset between the affected misclassified as controls (mean = 36 years) and the other three groups (high, 33.5 years; medium, 33.4 years; low, 33.1 years). CONCLUSIONS: The results are consistent with the polygenic model of inheritance. The cumulative genetic risk established using currently available genome-wide association data provides important insights into disease heterogeneity and completeness of current knowledge in MS genetics.
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    Closing the case of APOE in multiple sclerosis: no association with disease risk in over 29 000 subjects
    Lill, CM ; Liu, T ; Schjeide, B-MM ; Roehr, JT ; Akkad, DA ; Damotte, V ; Alcina, A ; Ortiz, MA ; Arroyo, R ; Lopez de lapuente, A ; Blaschke, P ; Winkelmann, A ; Gerdes, L-A ; Luessi, F ; Fernadez, O ; Izquierdo, G ; Antigueedad, A ; Hoffjan, S ; Cournu-Rebeix, I ; Gromoeller, S ; Faber, H ; Liebsch, M ; Meissner, E ; Chanvillard, C ; Touze, E ; Pico, F ; Corcia, P ; Doerner, T ; Steinhagen-Thiessen, E ; Baeckman, L ; Heekeren, HR ; Li, S-C ; Lindenberger, U ; Chan, A ; Hartung, H-P ; Aktas, O ; Lohse, P ; Kuempfel, T ; Kubisch, C ; Epplen, JT ; Zettl, UK ; Fontaine, B ; Vandenbroeck, K ; Matesanz, F ; Urcelay, E ; Bertram, L ; Zipp, F (BMJ PUBLISHING GROUP, 2012-09)
    BACKGROUND: Single nucleotide polymorphisms (SNPs) rs429358 (ε4) and rs7412 (ε2), both invoking changes in the amino-acid sequence of the apolipoprotein E (APOE) gene, have previously been tested for association with multiple sclerosis (MS) risk. However, none of these studies was sufficiently powered to detect modest effect sizes at acceptable type-I error rates. As both SNPs are only imperfectly captured on commonly used microarray genotyping platforms, their evaluation in the context of genome-wide association studies has been hindered until recently. METHODS: We genotyped 12 740 subjects hitherto not studied for their APOE status, imputed raw genotype data from 8739 subjects from five independent genome-wide association studies datasets using the most recent high-resolution reference panels, and extracted genotype data for 8265 subjects from previous candidate gene assessments. RESULTS: Despite sufficient power to detect associations at genome-wide significance thresholds across a range of ORs, our analyses did not support a role of rs429358 or rs7412 on MS susceptibility. This included meta-analyses of the combined data across 13 913 MS cases and 15 831 controls (OR=0.95, p=0.259, and OR 1.07, p=0.0569, for rs429358 and rs7412, respectively). CONCLUSION: Given the large sample size of our analyses, it is unlikely that the two APOE missense SNPs studied here exert any relevant effects on MS susceptibility.
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    Comparing genotyping algorithms for Illumina's Infinium whole-genome SNP BeadChips
    Ritchie, ME ; Liu, R ; Carvalho, BS ; Irizarry, RA (BMC, 2011-03-08)
    BACKGROUND: Illumina's Infinium SNP BeadChips are extensively used in both small and large-scale genetic studies. A fundamental step in any analysis is the processing of raw allele A and allele B intensities from each SNP into genotype calls (AA, AB, BB). Various algorithms which make use of different statistical models are available for this task. We compare four methods (GenCall, Illuminus, GenoSNP and CRLMM) on data where the true genotypes are known in advance and data from a recently published genome-wide association study. RESULTS: In general, differences in accuracy are relatively small between the methods evaluated, although CRLMM and GenoSNP were found to consistently outperform GenCall. The performance of Illuminus is heavily dependent on sample size, with lower no call rates and improved accuracy as the number of samples available increases. For X chromosome SNPs, methods with sex-dependent models (Illuminus, CRLMM) perform better than methods which ignore gender information (GenCall, GenoSNP). We observe that CRLMM and GenoSNP are more accurate at calling SNPs with low minor allele frequency than GenCall or Illuminus. The sample quality metrics from each of the four methods were found to have a high level of agreement at flagging samples with unusual signal characteristics. CONCLUSIONS: CRLMM, GenoSNP and GenCall can be applied with confidence in studies of any size, as their performance was shown to be invariant to the number of samples available. Illuminus on the other hand requires a larger number of samples to achieve comparable levels of accuracy and its use in smaller studies (50 or fewer individuals) is not recommended.
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    Multiple Sclerosis Susceptibility-Associated SNPs Do Not Influence Disease Severity Measures in a Cohort of Australian MS Patients
    Jensen, CJ ; Stankovich, J ; Van der Walt, A ; Bahlo, M ; Taylor, BV ; van der Mei, IAF ; Foote, SJ ; Kilpatrick, TJ ; Johnson, LJ ; Wilkins, E ; Field, J ; Danoy, P ; Brown, MA ; Rubio, JP ; Butzkueven, H ; Kleinschnitz, C (PUBLIC LIBRARY SCIENCE, 2010-04-02)
    Recent association studies in multiple sclerosis (MS) have identified and replicated several single nucleotide polymorphism (SNP) susceptibility loci including CLEC16A, IL2RA, IL7R, RPL5, CD58, CD40 and chromosome 12q13-14 in addition to the well established allele HLA-DR15. There is potential that these genetic susceptibility factors could also modulate MS disease severity, as demonstrated previously for the MS risk allele HLA-DR15. We investigated this hypothesis in a cohort of 1006 well characterised MS patients from South-Eastern Australia. We tested the MS-associated SNPs for association with five measures of disease severity incorporating disability, age of onset, cognition and brain atrophy. We observed trends towards association between the RPL5 risk SNP and time between first demyelinating event and relapse, and between the CD40 risk SNP and symbol digit test score. No associations were significant after correction for multiple testing. We found no evidence for the hypothesis that these new MS disease risk-associated SNPs influence disease severity.
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    Genome-wide association study identifies new multiple sclerosis susceptibility loci on chromosomes 12 and 20
    Bahlo, M ; Booth, DR ; Broadley, SA ; Brown, MA ; Foote, SJ ; Griffiths, LR ; Kilpatrick, TJ ; Lechner-Scott, J ; Moscato, P ; Perreau, VM ; Rubio, JP ; Scott, RJ ; Stankovich, J ; Stewart, GJ ; Taylor, BV ; Wiley, J ; Clarke, G ; Cox, MB ; Csurhes, PA ; Danoy, P ; Drysdale, K ; Field, J ; Foote, SJ ; Greer, JM ; Guru, P ; Hadler, J ; McMorran, BJ ; Jensen, CJ ; Johnson, LJ ; McCallum, R ; Merriman, M ; Merriman, T ; Pryce, K ; Tajouri, L ; Wilkins, EJ ; Browning, BL ; Browning, SR ; Perera, D ; Butzkueven, H ; Carroll, WM ; Chapman, C ; Kermode, AG ; Marriott, M ; Mason, D ; Heard, RN ; Pender, MP ; Slee, M ; Tubridy, N ; Willoughby, E (NATURE PUBLISHING GROUP, 2009-07)
    To identify multiple sclerosis (MS) susceptibility loci, we conducted a genome-wide association study (GWAS) in 1,618 cases and used shared data for 3,413 controls. We performed replication in an independent set of 2,256 cases and 2,310 controls, for a total of 3,874 cases and 5,723 controls. We identified risk-associated SNPs on chromosome 12q13-14 (rs703842, P = 5.4 x 10(-11); rs10876994, P = 2.7 x 10(-10); rs12368653, P = 1.0 x 10(-7)) and upstream of CD40 on chromosome 20q13 (rs6074022, P = 1.3 x 10(-7); rs1569723, P = 2.9 x 10(-7)). Both loci are also associated with other autoimmune diseases. We also replicated several known MS associations (HLA-DR15, P = 7.0 x 10(-184); CD58, P = 9.6 x 10(-8); EVI5-RPL5, P = 2.5 x 10(-6); IL2RA, P = 7.4 x 10(-6); CLEC16A, P = 1.1 x 10(-4); IL7R, P = 1.3 x 10(-3); TYK2, P = 3.5 x 10(-3)) and observed a statistical interaction between SNPs in EVI5-RPL5 and HLA-DR15 (P = 0.001).
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    A Polymorphism in the HLA-DPB1 Gene Is Associated with Susceptibility to Multiple Sclerosis
    Field, J ; Browning, SR ; Johnson, LJ ; Danoy, P ; Varney, MD ; Tait, BD ; Gandhi, KS ; Charlesworth, JC ; Heard, RN ; Stewart, GJ ; Kilpatrick, TJ ; Foote, SJ ; Bahlo, M ; Butzkueven, H ; Wiley, J ; Booth, DR ; Taylor, BV ; Brown, MA ; Rubio, JP ; Stankovich, J ; Andreu, AL (PUBLIC LIBRARY SCIENCE, 2010-10-26)
    We conducted an association study across the human leukocyte antigen (HLA) complex to identify loci associated with multiple sclerosis (MS). Comparing 1927 SNPs in 1618 MS cases and 3413 controls of European ancestry, we identified seven SNPs that were independently associated with MS conditional on the others (each P ≤ 4 x 10(-6)). All associations were significant in an independent replication cohort of 2212 cases and 2251 controls (P ≤ 0.001) and were highly significant in the combined dataset (P ≤ 6 x 10(-8)). The associated SNPs included proxies for HLA-DRB1*15:01 and HLA-DRB1*03:01, and SNPs in moderate linkage disequilibrium (LD) with HLA-A*02:01, HLA-DRB1*04:01 and HLA-DRB1*13:03. We also found a strong association with rs9277535 in the class II gene HLA-DPB1 (discovery set P = 9 x 10(-9), replication set P = 7 x 10(-4), combined P = 2 x 10(-10)). HLA-DPB1 is located centromeric of the more commonly typed class II genes HLA-DRB1, -DQA1 and -DQB1. It is separated from these genes by a recombination hotspot, and the association is not affected by conditioning on genotypes at DRB1, DQA1 and DQB1. Hence rs9277535 represents an independent MS-susceptibility locus of genome-wide significance. It is correlated with the HLA-DPB1*03:01 allele, which has been implicated previously in MS in smaller studies. Further genotyping in large datasets is required to confirm and resolve this association.
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    Polymorphisms in the Receptor Tyrosine Kinase MERTK Gene Are Associated with Multiple Sclerosis Susceptibility
    Ma, GZM ; Stankovich, J ; Kilpatrick, TJ ; Binder, MD ; Field, J ; Krahe, R (PUBLIC LIBRARY SCIENCE, 2011-02-08)
    Multiple sclerosis (MS) is a debilitating, chronic demyelinating disease of the central nervous system affecting over 2 million people worldwide. The TAM family of receptor tyrosine kinases (TYRO3, AXL and MERTK) have been implicated as important players during demyelination in both animal models of MS and in the human disease. We therefore conducted an association study to identify single nucleotide polymorphisms (SNPs) within genes encoding the TAM receptors and their ligands associated with MS. Analysis of genotype data from a genome-wide association study which consisted of 1618 MS cases and 3413 healthy controls conducted by the Australia and New Zealand Multiple Sclerosis Genetics Consortium (ANZgene) revealed several SNPs within the MERTK gene (Chromosome 2q14.1, Accession Number NG_011607.1) that showed suggestive association with MS. We therefore interrogated 28 SNPs in MERTK in an independent replication cohort of 1140 MS cases and 1140 healthy controls. We found 12 SNPs that replicated, with 7 SNPs showing p-values of less than 10(-5) when the discovery and replication cohorts were combined. All 12 replicated SNPs were in strong linkage disequilibrium with each other. In combination, these data suggest the MERTK gene is a novel risk gene for MS susceptibility.
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    Identity-by-Descent Mapping to Detect Rare Variants Conferring Susceptibility to Multiple Sclerosis
    Lin, Rui ; Charlesworth, Jac ; Stankovich, Jim ; PERREAU, VICTORIA ; Brown, Matthew ; TAYLOR, BRUCE ( 2012)