This study provides the first evidence that circulating miRNAs are deregulated in prepubertal obese children. Thus, the very early detection of an abnormal circulating miRNA profile may be a promising strategy to identify obese children who may suffer from metabolic abnormalities.

Essential trace elements possess vital functions at molecular, cellular, and physiological levels in health and disease, and they are tightly regulated in the human body. In order to assess variability and potential adaptive evolution of trace element homeostasis, we quantified 18 trace elements in 150 liver samples, together with the expression levels of 90 genes and abundances of 40 proteins involved in their homeostasis. Additionally, we genotyped 169 single nucleotide polymorphism (SNPs) in the same sample set. We detected significant associations for 8 protein quantitative trait loci (pQTL), 10 expression quantitative trait loci (eQTLs), and 15 micronutrient quantitative trait loci (nutriQTL). Six of these exceeded the false discovery rate cutoff and were related to essential trace elements: 1) one pQTL for GPX2 (rs10133290); 2) two previously described eQTLs for HFE (rs12346) and SELO (rs4838862) expression; and 3) three nutriQTLs: The pathogenic C282Y mutation at HFE affecting iron (rs1800562), and two SNPs within several clustered metallothionein genes determining selenium concentration (rs1811322 and rs904773). Within the complete set of significant QTLs (which involved 30 SNPs and 20 gene regions), we identified 12 SNPs with extreme patterns of population differentiation (FST values in the top 5% percentile in at least one HapMap population pair) and significant evidence for selective sweeps involving QTLs at GPX1, SELENBP1, GPX3, SLC30A9, and SLC39A8. Overall, this detailed study of various molecular phenotypes illustrates the role of regulatory variants in explaining differences in trace element homeostasis among populations and in the human adaptive response to environmental pressures related to micronutrients.

While most patients affected by the influenza A(H1N1) pandemic experienced mild symptoms, a small fraction required hospitalization, often without concomitant factors that could explain such a severe course. We hypothesize that host genetic factors could contribute to aggravate the disease. To test this hypothesis, we compared the allele frequencies of 547,296 genome-wide single nucleotide polymorphisms (SNPs) between 49 severe and 107 mild confirmed influenza A cases, as well as against a general population sample of 549 individuals. When comparing severe vs. mild influenza A cases, only one SNP was close to the conventional p = 5×10−8. This SNP, rs28454025, sits in an intron of the GSK233 gene, which is involved in a neural development, but seems not to have any connections with immunological or inflammatory functions. Indirectly, a previous association reported with CD55 was replicated. Although sample sizes are low, we show that the statistical power in our design was sufficient to detect highly-penetrant, quasi-Mendelian genetic factors. Hence, and assuming that rs28454025 is likely to be a false positive, no major genetic factor was detected that could explain poor influenza A course.