Literature DB >> 20362272

Evidence for polygenic susceptibility to multiple sclerosis--the shape of things to come.

William S Bush, Stephen J Sawcer, Philip L de Jager, Jorge R Oksenberg, Jacob L McCauley, Margaret A Pericak-Vance, Jonathan L Haines.   

Abstract

It is well established that the risk of developing multiple sclerosis is substantially increased in the relatives of affected individuals and that most of this increase is genetically determined. The observed pattern of familial recurrence risk has long suggested that multiple variants are involved, but it has proven difficult to identify individual risk variants and little has been established about the genetic architecture underlying susceptibility. By using data from two independent genome-wide association studies (GWAS), we demonstrate that a substantial proportion of the thousands of variants that individually fail to show statistically significant evidence of association have allele frequencies in cases that are skewed away from the null distribution through the effects of multiple as-yet-unidentified risk loci. The collective effect of 12,627 SNPs with Cochran-Mantel-Haenszel test (p < 0.2) in our discovery GWAS set optimally explains approximately 3% of the variance in MS risk in our independent target GWAS set, estimated by Nagelkerke's pseudo-R(2). This model has a highly significant fit (p = 9.90E-19). These results statistically demonstrate a polygenic component to MS susceptibility and suggest that the risk alleles identified to date represent just the tip of an iceberg of risk variants likely to include hundreds of modest effects and possibly thousands of very small effects. (c) 2010 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 20362272      PMCID: PMC2850422          DOI: 10.1016/j.ajhg.2010.02.027

Source DB:  PubMed          Journal:  Am J Hum Genet        ISSN: 0002-9297            Impact factor:   11.025


  27 in total

Review 1.  Genome-wide association studies: theoretical and practical concerns.

Authors:  William Y S Wang; Bryan J Barratt; David G Clayton; John A Todd
Journal:  Nat Rev Genet       Date:  2005-02       Impact factor: 53.242

2.  A high-density screen for linkage in multiple sclerosis.

Authors:  Stephen Sawcer; Maria Ban; Mel Maranian; Tai Wai Yeo; Alastair Compston; Andrew Kirby; Mark J Daly; Philip L De Jager; Emily Walsh; Eric S Lander; John D Rioux; David A Hafler; Adrian Ivinson; Jacqueline Rimmler; Simon G Gregory; Silke Schmidt; Margaret A Pericak-Vance; Eva Akesson; Jan Hillert; Pameli Datta; Annette Oturai; Lars P Ryder; Hanne F Harbo; Anne Spurkland; Kjell-Morten Myhr; Mikko Laaksonen; David Booth; Robert Heard; Graeme Stewart; Robin Lincoln; Lisa F Barcellos; Stephen L Hauser; Jorge R Oksenberg; Shannon J Kenealy; Jonathan L Haines
Journal:  Am J Hum Genet       Date:  2005-07-29       Impact factor: 11.025

3.  Linkage strategies for genetically complex traits. I. Multilocus models.

Authors:  N Risch
Journal:  Am J Hum Genet       Date:  1990-02       Impact factor: 11.025

4.  Age-adjusted recurrence risks for relatives of patients with multiple sclerosis.

Authors:  N P Robertson; M Fraser; J Deans; D Clayton; N Walker; D A Compston
Journal:  Brain       Date:  1996-04       Impact factor: 13.501

Review 5.  Genetics of multiple sclerosis.

Authors:  A D Sadovnick; G C Ebers
Journal:  Neurol Clin       Date:  1995-02       Impact factor: 3.806

6.  The British Isles survey of multiple sclerosis in twins.

Authors:  C J Mumford; N W Wood; H Kellar-Wood; J W Thorpe; D H Miller; D A Compston
Journal:  Neurology       Date:  1994-01       Impact factor: 9.910

Review 7.  Genetic epidemiology of multiple sclerosis.

Authors:  A D Sadovnick; D Dyment; G C Ebers
Journal:  Epidemiol Rev       Date:  1997       Impact factor: 6.222

8.  Familial recurrence rates and genetic models of multiple sclerosis.

Authors:  J William Lindsey
Journal:  Am J Med Genet A       Date:  2005-05-15       Impact factor: 2.802

Review 9.  Finding the missing heritability of complex diseases.

Authors:  Teri A Manolio; Francis S Collins; Nancy J Cox; David B Goldstein; Lucia A Hindorff; David J Hunter; Mark I McCarthy; Erin M Ramos; Lon R Cardon; Aravinda Chakravarti; Judy H Cho; Alan E Guttmacher; Augustine Kong; Leonid Kruglyak; Elaine Mardis; Charles N Rotimi; Montgomery Slatkin; David Valle; Alice S Whittemore; Michael Boehnke; Andrew G Clark; Evan E Eichler; Greg Gibson; Jonathan L Haines; Trudy F C Mackay; Steven A McCarroll; Peter M Visscher
Journal:  Nature       Date:  2009-10-08       Impact factor: 49.962

10.  Recommended diagnostic criteria for multiple sclerosis: guidelines from the International Panel on the diagnosis of multiple sclerosis.

Authors:  W I McDonald; A Compston; G Edan; D Goodkin; H P Hartung; F D Lublin; H F McFarland; D W Paty; C H Polman; S C Reingold; M Sandberg-Wollheim; W Sibley; A Thompson; S van den Noort; B Y Weinshenker; J S Wolinsky
Journal:  Ann Neurol       Date:  2001-07       Impact factor: 10.422

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  81 in total

1.  Mammographic breast density and breast cancer: evidence of a shared genetic basis.

Authors:  Jajini S Varghese; Deborah J Thompson; Kyriaki Michailidou; Sara Lindström; Clare Turnbull; Judith Brown; Jean Leyland; Ruth M L Warren; Robert N Luben; Ruth J Loos; Nicholas J Wareham; Johanna Rommens; Andrew D Paterson; Lisa J Martin; Celine M Vachon; Christopher G Scott; Elizabeth J Atkinson; Fergus J Couch; Carmel Apicella; Melissa C Southey; Jennifer Stone; Jingmei Li; Louise Eriksson; Kamila Czene; Norman F Boyd; Per Hall; John L Hopper; Rulla M Tamimi; Nazneen Rahman; Douglas F Easton
Journal:  Cancer Res       Date:  2012-01-19       Impact factor: 12.701

Review 2.  Multiple sclerosis genetics--is the glass half full, or half empty?

Authors:  Jorge R Oksenberg; Sergio E Baranzini
Journal:  Nat Rev Neurol       Date:  2010-07-13       Impact factor: 42.937

3.  Genetics and neuropsychology: A merger whose time has come.

Authors:  William S Kremen; Matthew S Panizzon; Tyrone D Cannon
Journal:  Neuropsychology       Date:  2016-01       Impact factor: 3.295

4.  Polygenic approaches to detect gene-environment interactions when external information is unavailable.

Authors:  Wan-Yu Lin; Ching-Chieh Huang; Yu-Li Liu; Shih-Jen Tsai; Po-Hsiu Kuo
Journal:  Brief Bioinform       Date:  2019-11-27       Impact factor: 11.622

Review 5.  Mechanisms of neurodegeneration shared between multiple sclerosis and Alzheimer's disease.

Authors:  Hans Lassmann
Journal:  J Neural Transm (Vienna)       Date:  2011-03-05       Impact factor: 3.575

6.  Explicit Modeling of Ancestry Improves Polygenic Risk Scores and BLUP Prediction.

Authors:  Chia-Yen Chen; Jiali Han; David J Hunter; Peter Kraft; Alkes L Price
Journal:  Genet Epidemiol       Date:  2015-05-21       Impact factor: 2.135

7.  Human Demographic History Impacts Genetic Risk Prediction across Diverse Populations.

Authors:  Alicia R Martin; Christopher R Gignoux; Raymond K Walters; Genevieve L Wojcik; Benjamin M Neale; Simon Gravel; Mark J Daly; Carlos D Bustamante; Eimear E Kenny
Journal:  Am J Hum Genet       Date:  2017-03-30       Impact factor: 11.025

8.  The emergence of neuroepidemiology, neurovirology and neuroimmunology: the legacies of John F. Kurtzke and Richard 'Dick' T. Johnson.

Authors:  Eric J Kildebeck; Ram Narayan; Avindra Nath; Howard Weiner; Shin Beh; Peter A Calabresi; Lawrence Steinman; Eugene O Major; Teresa C Frohman; Elliot M Frohman
Journal:  J Neurol       Date:  2016-10-12       Impact factor: 4.849

Review 9.  Therapeutic approaches for celiac disease.

Authors:  Nicholas M Plugis; Chaitan Khosla
Journal:  Best Pract Res Clin Gastroenterol       Date:  2015-05-09       Impact factor: 3.043

Review 10.  The immunogenetic architecture of autoimmune disease.

Authors:  An Goris; Adrian Liston
Journal:  Cold Spring Harb Perspect Biol       Date:  2012-03-01       Impact factor: 10.005

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