Corrado Fagnani1, Michael C Neale2, Lorenza Nisticò3, Maria A Stazi3, Vito A Ricigliano4, Maria C Buscarinu4, Marco Salvetti4, Giovanni Ristori4. 1. National Centre for Epidemiology, Surveillance and Health Promotion, Istituto Superiore di Sanità, Rome, Italy corrado.fagnani@iss.it. 2. Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, USA. 3. National Centre for Epidemiology, Surveillance and Health Promotion, Istituto Superiore di Sanità, Rome, Italy. 4. Centre for Experimental Neurological Therapies (CENTERS), Neurology and Department of Neurosciences, Mental Health and Sensory Organs (NESMOS), 'Sapienza' University of Rome, Italy.
Abstract
BACKGROUND: Most twin studies of multiple sclerosis (MS) are inconclusive regarding the impact of genes and environment on disease susceptibility. In particular, high uncertainty exists about whether shared environmental factors are aetiologically relevant. OBJECTIVE: To disentangle, with a reasonable degree of confidence, the relative contributions of heritability and of shared and unique environmental components of MS susceptibility. METHODS: We performed a meta-analysis of previous twin studies. After a MEDLINE search, we selected eight twin studies in France, UK, Canada, Denmark, North America, Italy, Finland and Sweden. We conducted a biometric multi-group analysis under the liability-threshold model, by taking account of the study-specific ascertainment strategies and the population-specific prevalence rates of MS. RESULTS: The meta-analytic estimates of tetrachoric correlations were 0.71 (95% confidence interval (CI): 0.67-0.74) in monozygotic pairs and 0.46 (95% CI: 0.41-0.50) in dizygotic pairs. The biometric multi-group model provided meta-analytic estimates of 0.50 (95% CI: 0.39-0.61) for heritability, 0.21 (95% CI: 0.11-0.30) for shared environmental component and 0.29 (95% CI: 0.26-0.33) for unique environmental component. CONCLUSION: Our results support the continuing efforts to identify unknown genetic factors that fill the gap of 'missing heritability'; moreover, a 'missing environmentality' deserves future investigations into the role of non-heritable components that act as both shared and individual-specific exposures.
BACKGROUND: Most twin studies of multiple sclerosis (MS) are inconclusive regarding the impact of genes and environment on disease susceptibility. In particular, high uncertainty exists about whether shared environmental factors are aetiologically relevant. OBJECTIVE: To disentangle, with a reasonable degree of confidence, the relative contributions of heritability and of shared and unique environmental components of MS susceptibility. METHODS: We performed a meta-analysis of previous twin studies. After a MEDLINE search, we selected eight twin studies in France, UK, Canada, Denmark, North America, Italy, Finland and Sweden. We conducted a biometric multi-group analysis under the liability-threshold model, by taking account of the study-specific ascertainment strategies and the population-specific prevalence rates of MS. RESULTS: The meta-analytic estimates of tetrachoric correlations were 0.71 (95% confidence interval (CI): 0.67-0.74) in monozygotic pairs and 0.46 (95% CI: 0.41-0.50) in dizygotic pairs. The biometric multi-group model provided meta-analytic estimates of 0.50 (95% CI: 0.39-0.61) for heritability, 0.21 (95% CI: 0.11-0.30) for shared environmental component and 0.29 (95% CI: 0.26-0.33) for unique environmental component. CONCLUSION: Our results support the continuing efforts to identify unknown genetic factors that fill the gap of 'missing heritability'; moreover, a 'missing environmentality' deserves future investigations into the role of non-heritable components that act as both shared and individual-specific exposures.
Authors: Anthony L Traboulsee; A Dessa Sadovnick; Mary Encarnacion; Cecily Q Bernales; Irene M Yee; Maria G Criscuoli; Carles Vilariño-Güell Journal: Hum Genet Date: 2017-03-23 Impact factor: 4.132
Authors: Patrick K A Kearns; Sarah J Martin; Jessie Chang; Rozanna Meijboom; Elizabeth N York; Yingdi Chen; Christine Weaver; Amy Stenson; Katarzyna Hafezi; Stacey Thomson; Elizabeth Freyer; Lee Murphy; Adil Harroud; Peter Foley; David Hunt; Margaret McLeod; Jonathon O'Riordan; F J Carod-Artal; Niall J J MacDougall; Sergio E Baranzini; Adam D Waldman; Peter Connick; Siddharthan Chandran Journal: BMJ Open Date: 2022-06-29 Impact factor: 3.006
Authors: Zhe Wang; A Dessa Sadovnick; Anthony L Traboulsee; Jay P Ross; Cecily Q Bernales; Mary Encarnacion; Irene M Yee; Madonna de Lemos; Talitha Greenwood; Joshua D Lee; Galen Wright; Colin J Ross; Si Zhang; Weihong Song; Carles Vilariño-Güell Journal: Neuron Date: 2016-06-01 Impact factor: 17.173
Authors: A Dessa Sadovnick; Anthony L Traboulsee; Cecily Q Bernales; Jay P Ross; Amanda L Forwell; Irene M Yee; Lena Guillot-Noel; Bertrand Fontaine; Isabelle Cournu-Rebeix; Antonio Alcina; Maria Fedetz; Guillermo Izquierdo; Fuencisla Matesanz; Kelly Hilven; Bénédicte Dubois; An Goris; Ianire Astobiza; Iraide Alloza; Alfredo Antigüedad; Koen Vandenbroeck; Denis A Akkad; Orhan Aktas; Paul Blaschke; Mathias Buttmann; Andrew Chan; Joerg T Epplen; Lisa-Ann Gerdes; Antje Kroner; Christian Kubisch; Tania Kümpfel; Peter Lohse; Peter Rieckmann; Uwe K Zettl; Frauke Zipp; Lars Bertram; Christina M Lill; Oscar Fernandez; Patricia Urbaneja; Laura Leyva; Jose Carlos Alvarez-Cermeño; Rafael Arroyo; Aroa M Garagorri; Angel García-Martínez; Luisa M Villar; Elena Urcelay; Sunny Malhotra; Xavier Montalban; Manuel Comabella; Thomas Berger; Franz Fazekas; Markus Reindl; Mascha C Schmied; Alexander Zimprich; Carles Vilariño-Güell Journal: G3 (Bethesda) Date: 2016-07-07 Impact factor: 3.154