Teresa Fazia1, Roberta Pastorino1, Luisa Foco2, Lide Han3, Mark Abney3, Ashley Beecham4, Athena Hadjixenofontos4, Hui Guo5, Davide Gentilini6, Charalampos Papachristou7, Pier Paolo Bitti8, Anna Ticca9, Carlo Berzuini5, Jacob L McCauley4, Luisa Bernardinelli1. 1. Department of Brain and Behavioral Science, University of Pavia, Pavia, Italy. 2. Department of Brain and Behavioral Science, University of Pavia, Pavia, Italy; Institute for Biomedicine, Eurac Research, Affiliated Institute of the University of Lübeck, Bolzano, Italy. 3. Department of Human Genetics, The University of Chicago, Chicago, IL, USA. 4. John P. Hussmann Institute for Human Genomics and Dr John Macdonald Foundation, Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA. 5. Center for Biostatistics, Institute of Population Health, The University of Manchester, Manchester, UK. 6. Unità di Bioinformatica e Statistica Genomica, Istituto Auxologico Italiano-IRCCS, Milano, Italy. 7. Department of Mathematics, Rowan University, Glassboro, NJ, USA. 8. Immunoematologia e Medicina Trasfusionale, Ospedale "San Francesco" Nuoro, ASSL Nuoro, Azienda Tutela Salute Sardegna, Nuoro, Italy. 9. Neurologia e Stroke Unit, Ospedale "San Francesco" Nuoro, ASSL Nuoro, Azienda Tutela Salute Sardegna, Nuoro, Italy.
Abstract
BACKGROUND: A wealth of single-nucleotide polymorphisms (SNPs) responsible for multiple sclerosis (MS) susceptibility have been identified; however, they explain only a fraction of MS heritability. OBJECTIVES: We contributed to discovery of new MS susceptibility SNPs by studying a founder population with high MS prevalence. METHODS: We analyzed ImmunoChip data from 15 multiplex families and 94 unrelated controls from the Nuoro Province, Sardinia, Italy. We tested each SNP for both association and linkage with MS, the linkage being explored in terms of identity-by-descent (IBD) sharing excess and using gene dropping to compute a corresponding empirical p-value. By targeting regions that are both associated and in linkage with MS, we increase chances of identifying interesting genomic regions. RESULTS: We identified 486 MS-associated (p < 1 × 10-4) and 18,426 MS-linked (p < 0.05) SNPs. A total of 111 loci were both linked and associated with MS, 18 of them pointing to 14 non-major histocompatibility complex (MHC) genes, and 93 of them located in the MHC region. CONCLUSION: We discovered new suggestive signals and confirmed some previously identified ones. We believe this to represent a significant step toward an understanding of the genetic basis of MS.
BACKGROUND: A wealth of single-nucleotide polymorphisms (SNPs) responsible for multiple sclerosis (MS) susceptibility have been identified; however, they explain only a fraction of MS heritability. OBJECTIVES: We contributed to discovery of new MS susceptibility SNPs by studying a founder population with high MS prevalence. METHODS: We analyzed ImmunoChip data from 15 multiplex families and 94 unrelated controls from the Nuoro Province, Sardinia, Italy. We tested each SNP for both association and linkage with MS, the linkage being explored in terms of identity-by-descent (IBD) sharing excess and using gene dropping to compute a corresponding empirical p-value. By targeting regions that are both associated and in linkage with MS, we increase chances of identifying interesting genomic regions. RESULTS: We identified 486 MS-associated (p < 1 × 10-4) and 18,426 MS-linked (p < 0.05) SNPs. A total of 111 loci were both linked and associated with MS, 18 of them pointing to 14 non-major histocompatibility complex (MHC) genes, and 93 of them located in the MHC region. CONCLUSION: We discovered new suggestive signals and confirmed some previously identified ones. We believe this to represent a significant step toward an understanding of the genetic basis of MS.
Authors: Andrea Nova; Teresa Fazia; Ashley Beecham; Valeria Saddi; Marialuisa Piras; Jacob L McCauley; Carlo Berzuini; Luisa Bernardinelli Journal: Life (Basel) Date: 2022-01-20
Authors: Teresa Fazia; Andrea Nova; Davide Gentilini; Ashley Beecham; Marialuisa Piras; Valeria Saddi; Anna Ticca; Pierpaolo Bitti; Jacob L McCauley; Carlo Berzuini; Luisa Bernardinelli Journal: Front Bioeng Biotechnol Date: 2020-05-05
Authors: Giorgio Broccia; Jonathan Carter; Cansu Ozsin-Ozler; Federico Meloni; Sara De Matteis; Pierluigi Cocco Journal: PLoS One Date: 2022-02-02 Impact factor: 3.240