An Observational Study of Blood Concentrations and Kinetics of Methyl- and Propyl-Parabens in Neonates

Purpose: Systemic exposure to parabens in the neonatal population, in particular propyl-parabens (PPB), remains a concern. Blood concentrations and kinetics of methyl-parabens (MPB) and PPB were therefore determined in neonates receiving medicines containing these excipients.

Methods: A multi-centre, non-interventional, observational study of excipient-kinetics in neonates. ‘Dried Blood Spot’ samples were collected opportunistically at the same time as routine samples and the observations modelled using a non-linear mixed effects approach.

Results: A total of 841 blood MPB and PPB concentration data were available for evaluation from 181 pre- and term-neonates. Quantifiable blood concentrations of MPB and PPB were observed in 99% and 49% of patients, and 55% and 25% of all concentrations were above limit of detection (10 ng/ml), respectively. Only MPB data was amenable to modelling. Oral bioavailability was influenced by type of formulation and disposition was best described by a two compartment model with clearance (CL) influenced by post natal age (PNA); CL_{PNA<21 days} 0.57 versus CL_PNA>21days 0.88 L/h.

Conclusions: Daily repeated administration of parabens containing medicines can result in prolonged systemic exposure to the parent compound in neonates. Animal toxicology studies of PPB that specifically address the neonatal period are required before a permitted daily exposure for this age group can be established.

The NOTCH signaling pathway in normal and malignant blood cell production

The NOTCH pathway is an evolutionarily conserved signalling network, which is fundamental in regulating developmental processes in invertebrates and vertebrates (Gazave et al. in BMC Evol Biol 9:249, 2009). It regulates self-renewal (Butler et al. in Cell Stem Cell 6:251–264, 2010), differentiation (Auderset et al. in Curr Top Microbiol Immunol 360:115–134, 2012), proliferation (VanDussen et al. in Development 139:488–497, 2012) and apoptosis (Cao et al. in APMIS 120:441–450, 2012) of diverse cell types at various stages of their development. NOTCH signalling governs cell-cell interactions and the outcome of such responses is highly context specific. This makes it impossible to generalize about NOTCH functions as it stimulates survival and differentiation of certain cell types, whereas inhibiting these processes in others (Meier-Stiegen et al. in PLoS One 5:e11481, 2010). NOTCH was first identified in 1914 in Drosophila and was named after the indentations (notches) present in the wings of the mutant flies (Bigas et al. in Int J Dev Biol 54:1175–1188, 2010). Homologs of NOTCH in vertebrates were initially identified in Xenopus (Coffman et al. in Science 249:1438–1441, 1990) and in humans NOTCH was first identified in T-Acute Lymphoblastic Leukaemia (T-ALL) (Ellisen et al. in Cell 66:649–61, 1991). NOTCH signalling is integral in neurogenesis (Mead and Yutzey in Dev Dyn 241:376–389, 2012), myogenesis (Schuster-Gossler et al. in Proc Natl Acad Sci U S A 104:537–542, 2007), haematopoiesis (Bigas et al. in Int J Dev Biol 54:1175–1188, 2010), oogenesis (Xu and Gridley in Genet Res Int 2012:648207, 2012), differentiation of intestinal cells (Okamoto et al. in Am J Physiol Gastrointest Liver Physiol 296:G23–35, 2009) and pancreatic cells (Apelqvist et al. in Nature 400:877–881, 1999). The current review will focus on NOTCH signalling in normal and malignant blood cell production or haematopoiesis.

Minor allele frequency of myeloproliferative neoplasm mutations in the Irish blood donor population

Myeloproliferative neoplasms (MPNs) are rare diseases that include classic entities; polycythaemia vera, essential thrombocythaemia and primary myelofibrosis. In this short report, minor allele frequencies of common MPN mutations are compared between the Irish blood donor population and other populations of European descent using data from the Haplotype Map project. The Affymetrix array 6.0 platform was utilised identifying nine single nucleotide polymorphisms (SNPs) and six proxy SNPs. The variability of allele frequencies for MPN mutations could account for the different incidence rates seen between populations of European ancestry, giving a better understanding of the genetic predisposition to MPNs. 

Distinct methylation patterns in genes that affect mitochondrial function are associated with kidney disease in blood-derived DNA from individuals with Type 1 diabetes

AIMS: Epigenetic modifications, such as DNA methylation, can influence the risk of developing kidney disease. We studied methylation profiles in genes related to mitochondrial function to assess whether differences in these epigenetic features were associated with diabetic kidney disease in people with Type 1 diabetes.

METHODS: A case-control association study was undertaken (n = 196 individuals with diabetic kidney disease vs. n = 246 individuals without renal disease). Participants were White and diagnosed with Type 1 diabetes before 31 years of age. Genes that encode mitochondrial proteins (n = 780) were downloaded from mitoproteome. org. DNA methylation profiles from blood-derived DNA were generated using the Illumina Infinium HumanMethylation450 (262 samples) and Illumina Infinium HumanMethylation27 (192 samples) arrays. Beta values (β) were calculated and quality control was conducted, including evaluating blind duplicate DNA samples.

RESULTS: Fifty-four Cytosine-phosphate-Guanine probes across 51 unique genes were significantly associated (P ≤ 10(-8) ) with diabetic kidney disease across both the 450K and the 27K methylation arrays. A subanalysis, employing the 450K array, identified 755 Cytosine-phosphate-Guanine probes in 374 genes that were significantly associated (P ≤ 10(-8) ) with end-stage renal disease. Forty-six of the top-ranked variants for diabetic kidney disease were also identified as being differentially methylated in individuals with end-stage renal disease. The largest change in methylation (Δβ = 0.2) was observed for cg03169527 in the TAMM41 gene, chromosome 3p25.2. Three genes, PMPCB, TSFM and AUH, were observed with differential methylation at multiple Cytosine-phosphate-Guanine sites each (P < 10(-12) ).

CONCLUSIONS: Differential methylation in genes that influence mitochondrial function are associated with kidney disease in individuals with Type 1 diabetes.