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A correlation study between multiple sclerosis and type 1 diabetes incidences and geochemical data in Europe


Paolo Valera1, Patrizia Zavattari2Stefano Albanese3, Domenico Cicchella4Enrico Dinelli5Annamaria Lima3Benedetto De Vivo3

1Department of Civil-Environmental Engineering and Architecture, University of Cagliari, Via Marengo 3, 09123 Cagliari, Italy
2 Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, SP 8, Km 0.700, 09042 Cagliari, Italy
3 Dipartimento di Scienze della Terra, dell’Ambiente e delle Risorse, Università degli Studi di Napoli Federico II, Largo San Marcellino 10, 80138 Napoli, Italy Department of Biological, 4Geological and Environmental Sciences, University of Sannio, Via dei Mulini 59/A, Benevento, Italy
5Department of Earth Science, University of Bologna, Piazza di Porta San Donato 1, 40126 Bologna, Italy
Environ Geochem Health (2014) 36:79–98
Complex multifactorial disorders usually arise in individuals genetically at risk in the presence of permissive environmental factors. For many of these diseases, predisposing gene variants are partly known while the identification of the environmental component is much more difficult. This study aims to investigate whether there are correlations between the incidence of two complex traits, multiple sclerosis and type 1 diabetes, and some chemical elements and compounds present in soils and stream sediments in Europe. Data were obtained from the published literature and analyzed by calculating the mean values of each element and of disease incidence for each Country, respectively, 17 for multiple sclerosis and 21 for type 1 diabetes. Correlation matrices and regression analyses were used in order to compare incidence data and geochemical data. R correlation index and significance were evaluated. The analyses performed in this study have revealed significant positive correlations between barium and sodium oxide on one hand and multiple sclerosis and diabetes incidences on the other hand that may suggest interactions to be evaluated between silicon-rich lithologies and/or marine environments. The negative correlations shown by cobalt, chromium and nickel (typical of silicon-poor environment), which in this case can be interpreted as protective effects against the two diseases onset, make the split between favorable and protective environments even more obvious. In conclusion, if other studies will confirm the involvement of the above elements and compounds in the etiology of these pathologies, then it will be possible to plan strategies to reduce the spread of these serious pandemics.  
Key-words: Type 1 diabetes, Multiple sclerosis, Elements and compounds, Correlation studies