MetALS SIGNED
Investigating the pharmacokinetic properties of toxic metals and heat shock proteins as risk factors in Amyotrophic Lateral Sclerosis
Total Cost €
0EC-Contrib. €
0Partnership
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Project "MetALS" data sheet
The following table provides information about the project.
| Coordinator |
LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN
Organization address contact info |
| Coordinator Country | Germany [DE] |
| Total cost | 162˙806 € |
| EC max contribution | 162˙806 € (100%) |
| Programme |
1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility) |
| Code Call | H2020-MSCA-IF-2018 |
| Funding Scheme | MSCA-IF-EF-ST |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-10-01 to 2021-09-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN | DE (MUENCHEN) | coordinator | 162˙806.00 |
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Project objective
Background: Exposure to toxic metals are proposed as risk factors for amyotrophic lateral sclerosis (ALS). Despite this, evidence remains mixed, with only evidence for lead exposure supported by recent meta-analysis. Many studies neglected that biomarkers may be affected by kidney and liver function. Additionally, the heat shock protein (HSP) response is triggered by toxic metal exposures, and there is evidence for altered HSP metabolism in ALS. Methods: Using available samples (105 ALS cases, 307 controls), blood HSP’s and toxic metal exposures will be measured primarily in urine (inorganic Hg, lead, chromium, aluminium, selenium, zinc, cadmium, copper and manganese). Confounding variables such as kidney and liver function, and bone turnover will be measured. In addition, prospective recruitment of a further 100 cases and 100 controls will be carried out. For prospectively enrolees, repeat blood and urine samples will be taken three-monthly. Statistical analysis: Multivariable logistic regression will be used to compare HSP’s at baseline, while Bayesian models will be used to model correlations between HSP’s and multiple toxic metals. Longitudinal trends will be modelled using Bayesian mixed effects models. Ordinary differential equations will be used to construct elimination kinetics models. Power calculations indicate 90% power to detect an odds ratio of 2.0 at baseline, and 87% to detect longitudinal differences in trend of 15% or more between cases and controls. Impact: MetALS will employ new methodology to generate fresh insights into the role of toxic metals in ALS. MetALS will confirm or refute the finding of HSP’s as biomarkers in ALS, and provide the first insights into longitudinal behaviour of HSP’s as the disease progresses. MetALS will also provide the first combined study of both HSP’s and toxic metal exposure in an ALS cohort. These novel enquiries are expected to provide fresh insights into HSP’s and toxic metal metabolism in ALS.
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