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INTRODUCTION: Serum phenotyping of elite cyclists regarding cortisol, IGF1 and testosterone is a way to detect endocrine disruptions possibly explained by exercise overload, non-balanced diet or by doping. This latter disruption-driven approach is supported by fundamental physiology although without any evidence of any metabolic markers. OBJECTIVES: Serum samples were distributed through Low, High or Normal endocrine classes according to hormone concentration. A 1H NMR metabolomic study of 655 serum obtained in the context of the longitudinal medical follow-up of 253 subjects was performed to discriminate the three classes for every endocrine phenotype. METHODS: An original processing algorithm was built which combined a partial-least squares-based orthogonal correction of metabolomic signals and a shrinkage discriminant analysis (SDA) to get satisfying classifications. An extended validation procedure was used to plan in larger size cohorts a minimal size to get a global prediction rate (GPR), i.e. the product of the three class prediction rates, higher than 99.9%. RESULTS: Considering the 200 most SDA-informative variables, a sigmoidal fitting of the GPR gave estimates of a minimal sample size to 929, 2346 and 1408 for cortisol, IGF1 and testosterone, respectively. Analysis of outliers from cortisol and testosterone Normal classes outside the 97.5%-confidence limit of score prediction revealed possibly (i) an inadequate protein intake for outliers or (ii) an intake of dietary ergogenics, glycine or glutamine, which might explain the significant presence of heterogeneous metabolic profiles in a supposedly normal cyclists subgroup. CONCLUSION: In a next validation metabolomics study of a so-sized cohort, anthropological, clinical and dietary metadata should be recorded in priority at the blood collection time to confirm these functional hypotheses.
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Hidrocortisona , Metabolómica , Dieta , Humanos , Espectroscopía de Resonancia Magnética , TestosteronaRESUMEN
INTRODUCTION: During the night of February 27 and the early morning of February 28, 2010, 15 coastal municipalities situated in two French departments, Vendée and Charente-Maritime, were violently stricken by a severe windstorm named "Xynthia." This storm caused the death of 12 individuals in Charente-Maritime and 29 people in Vendée. Houses, agricultural fields, and shellfish companies were severely flooded with seawater. Several thousand people temporarily had to leave their homes. The objective of this study was to estimate the short-term mental health impact of Xynthia, in terms of psychotropic drug delivery, on the resident population of the 15 coastal municipalities severely hit by the flooding. METHODS: The French national health insurance database was used to calculate a daily number of new psychotropic treatments from September 1, 2008 through December 24, 2010. New treatments were calculated for each of the following European Pharmaceutical Marketing Research Association (EphMRA) classes: tranquilizers (N05C), hypnotics (N05B), and antidepressants (N06A). A period of three weeks following the storm was defined as the exposure period. A generalized additive model with a Poisson distribution that allows for over-dispersion was used to analyze the correlation between the Xynthia variable and the number of new psychotropic treatments. RESULTS: With a relative risk (RR) of 1.54 (95% CI, 1.39-1.62) corresponding to an estimate of 409 new deliveries of psychotropic drugs during the three weeks following the storm, this study confirms the importance of the psychological impact of Xynthia. This impact is seen on all three classes of psychotropic drugs studied. The impact is greater for tranquilizers (RR of 1.78; 95% CI, 1.59-1.89) than for hypnotics (RR of 1.53; 95% CI, 1.31-1.67) and antidepressants (RR of 1.26; 95% CI, 1.06-1.40). The RR was higher for females than for males. CONCLUSION: This study shows the importance of the psychological impact of the storm as observed clinically by health workers who intervened in the field during the aftermath of Xynthia. It confirms that administrative databases can be used to show a health impact of a disaster even at a local level. This is one more step in the direction of a comprehensive strategy of collecting information to allow the assessment of the health impact of an extreme event, the detection of vulnerable populations, and the orientation of the short-, mid- and long-term public health response.