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

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Abstract

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.

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Abbreviations

MS:

Multiple sclerosis

T1D:

Type 1 diabetes

FOREGS:

Forum of European Geological Surveys

AR:

Aqua regia

XRF:

X-ray fluorescence spectrometry

ICP:

Inductively coupled plasma

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Acknowledgments

We wish to thank Salvatore Pretti and Luigi Minerba for their skillful contribution to the statistical analysis and critical discussion of the data. The authors wish to thank all the people who cooperated to produce the FOREGS geochemical database of Europe, of which this paper uses the stream sediment and top soil data.

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Authors and Affiliations

  1. Department of Civil-Environmental Engineering and Architecture, University of Cagliari, Via Marengo 3, 09123, Cagliari, Italy

    Paolo Valera

  2. Department of Biomedical Sciences, University of Cagliari, Cittadella Universitaria di Monserrato, SP 8, Km 0.700, 09042, Cagliari, Italy

    Patrizia Zavattari

  3. Dipartimento di Scienze della Terra, Università di Napoli Federico II, Via Mezzocannone 8, 80134, Naples, Italy

    Stefano Albanese, Annamaria Lima & Benedetto De Vivo

  4. Department of Biological, Geological and Environmental Sciences, University of Sannio, Via dei Mulini 59/A, Benevento, Italy

    Domenico Cicchella

  5. Department of Earth Science, University of Bologna, Piazza di Porta San Donato 1, 40126, Bologna, Italy

    Enrico Dinelli

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  1. Paolo Valera
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  2. Patrizia Zavattari
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  3. Stefano Albanese
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  4. Domenico Cicchella
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  7. Benedetto De Vivo
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Correspondence to Paolo Valera.

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Paolo Valera and Patrizia Zavattari: equal contributors.

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Valera, P., Zavattari, P., Albanese, S. et al. A correlation study between multiple sclerosis and type 1 diabetes incidences and geochemical data in Europe. Environ Geochem Health 36, 79–98 (2014). https://doi.org/10.1007/s10653-013-9520-4

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  • DOI: https://doi.org/10.1007/s10653-013-9520-4

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