Tissue- specific DNA methylation profiles in newborns

Experimental and epidemiological studies demonstrate that fetal growth restriction and low birth weight enhance the risk of chronic diseases in adulthood. Derangements in tissue-specific epigenetic programming of fetal and placental tissues are a suggested mechanism of which DNA methylation is best understood. DNA methylation profiles in human tissue are mostly performed in DNA from white blood cells. The objective of this study was to assess DNA methylation profiles of IGF2 DMR and H19 in DNA derived from four tissues of the newborn. We obtained from 6 newborns DNA from fetal placental tissue (n = 5), umbilical cord CD34+ hematopoietic stem cells (HSC) and CD34- mononuclear cells (MNC) (n = 6), and umbilical cord Wharton jelly (n = 5). HCS were isolated using magnetic-activated cell separation. DNA methylation of the imprinted fetal growth genes IGF2 DMR and H19 was measured in all tissues using quantitative mass spectrometry. ANOVA testing showed tissue-specific differences in DNA methylation of IGF2 DMR (p value 0.002) and H19 (p value 0.001) mainly due to a higher methylation of IGF2 DMR in Wharton jelly (mean 0.65, sd 0.14) and a lower methylation of H19 in placental tissue (mean 0.25, sd 0.02) compared to other tissues. This study demonstrates the feasibility of the assessment of differential tissue specific DNA methylation. Although the results have to be confirmed in larger sample sizes, our approach gives opportunities to investigate epigenetic profiles as underlying mechanism of associations between pregnancy exposures and outcome, and disease risks in later life.

Clinical prediction of occupational and non-specific low back pain

Non-specific Occupational Low Back Pain (NOLBP) is a health condition that generates a high absenteeism and disability. Due to multifactorial causes is difficult to determine accurate diagnosis and prognosis. The clinical prediction of NOLBP is identified as a series of models that integrate a multivariate analysis to determine early diagnosis, course, and occupational impact of this health condition. Objective: to identify predictor factors of NOLBP, and the type of material referred to in the scientific evidence and establish the scopes of the prediction. Materials and method: the title search was conducted in the databases PubMed, Science Direct, and Ebsco Springer, between1985 and 2012. The selected articles were classified through a bibliometric analysis allowing to define the most relevant ones. Results: 101 titles met the established criteria, but only 43 metthe purpose of the review. As for NOLBP prediction, the studies varied in relation to the factors for example: diagnosis, transition of lumbar pain from acute to chronic, absenteeism from work, disability and return to work. Conclusion: clinical prediction is considered as a strategic to determine course and prognostic of NOLBP, and to determine the characteristics that increase the risk of chronicity in workers with this health condition. Likewise, clinical prediction rules are tools that aim to facilitate decision making about the evaluation, diagnosis, prognosis and intervention for low back pain, which should incorporate risk factors of physical, psychological and social.