High-yield identification of pathogenic NF1 variants by skin fibroblast transcriptome screening after apparently normal diagnostic DNA testing

Neurofibromatosis type 1 (NF1) is caused by inactivating mutations in NF1. Due to the size, complexity, and high mutation rate at the NF1 locus, the identification of causative variants can be challenging. To obtain a molecular diagnosis in 15 individuals meeting diagnostic criteria for NF1, we performed transcriptome analysis (RNA-seq) on RNA obtained from cultured skin fibroblasts. In each case, routine molecular DNA diagnostics had failed to identify a disease-causing variant in NF1. A pathogenic variant or abnormal mRNA splicing was identified in 13 cases: 6 deep intronic variants and 2 transposon insertions causing noncanonical splicing, 3 postzygotic changes, 1 branch point mutation and, in 1 case, abnormal splicing for which the responsible DNA change remains to be identified. These findings helped resolve the molecular findings for an additional 17 individuals in multiple families with NF1, demonstrating the utility of skin-fibroblast-based transcriptome analysis for molecular diagnostics. RNA-seq improves mutation detection in NF1 and provides a powerful complementary approach to DNA-based methods. Importantly, our approach is applicable to other genetic disorders, particularly those caused by a wide variety of variants in a limited number of genes and specifically for individuals in whom routine molecular DNA diagnostics did not identify the causative variant.</p

Transcriptional recapitulation and subversion of embryonic colon development by mouse colon tumor models and human colon cancer

Colon tumors from four independent mouse models and 100 human colorectal cancers all exhibited striking recapitulation of embryonic colon gene expression from embryonic days 13.5-18.5

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

10Kin1day: A Bottom-Up Neuroimaging Initiative.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain

Integration of metabolomics with genomics: Metabolic gene prioritization using metabolomics data and genomic variant (CADD) scores

The integration of metabolomics data with sequencing data is a key step towards improving the diagnostic process for finding the disease-causing genetic variant(s) in patients suspected of having an inborn error of metabolism (IEM). The measured metabolite levels could provide additional phenotypical evidence to elucidate the degree of pathogenicity for variants found in genes associated with metabolic processes. We present a computational approach, called Reafect, that calculates for each reaction in a metabolic pathway a score indicating whether that reaction is deficient or not. When calculating this score, Reafect takes multiple factors into account: the magnitude and sign of alterations in the metabolite levels, the reaction distances between metabolites and reactions in the pathway, and the biochemical directionality of the reactions. We applied Reafect to untargeted metabolomics data of 72 patient samples with a known IEM and found that in 81% of the cases the correct deficient enzyme was ranked within the top 5% of all considered enzyme deficiencies. Next, we integrated Reafect with Combined Annotation Dependent Depletion (CADD) scores (a measure for gene variant deleteriousness) and ranked the metabolic genes of 27 IEM patients. We observed that this integrated approach significantly improved the prioritization of the genes containing the disease-causing variant when compared with the two approaches individually. For 15/27 IEM patients the correct affected gene was ranked within the top 0.25% of the set of potentially affected genes. Together, our findings suggest that metabolomics data improves the identification of affected genes in patients suffering from IEM

An 8q24 Gain in Pancreatic Juice Is a Candidate Biomarker for the Detection of Pancreatic Cancer

Secretin-stimulated pancreatic juice (PJ), collected from the duodenum, presents a valuable biomarker source for the (earlier) detection of pancreatic cancer (PC). Here, we evaluate the feasibility and performance of shallow sequencing to detect copy number variations (CNVs) in cell-free DNA (cfDNA) from PJ for PC detection. First, we confirmed the feasibility of shallow sequencing in PJ (n = 4), matched plasma (n = 3) and tissue samples (n = 4, microarray). Subsequently, shallow sequencing was performed on cfDNA from PJ of 26 cases (25 sporadic PC, 1 high-grade dysplasia) and 19 controls with a hereditary or familial increased risk of PC. 40 of the 45 PJ samples met the quality criteria for cfDNA analysis. Nine individuals had an 8q24 gain (oncogene MYC; 23%; eight cases (33%) and one control (6%), p = 0.04); six had both a 2q gain (STAT1) and 5p loss (CDH10; 15%; four cases (7%) and two controls (13%), p = 0.72). The presence of an 8q24 gain differentiated the cases and controls, with a sensitivity of 33% (95% CI 16–55%) and specificity of 94% (95% CI 70–100%). The presence of either an 8q24 or 2q gain with a 5p loss was related to a sensitivity of 50% (95% CI 29–71%) and specificity of 81% (95% CI 54–96%). Shallow sequencing of PJ is feasible. The presence of an 8q24 gain in PJ shows promise as a biomarker for the detection of PC. Further research is required with a larger sample size and consecutively collected samples in high-risk individuals prior to implementation in a surveillance cohort

Congenital cytomegalovirus infection: contribution and best timing of prenatal MR imaging

Objective: To predict sensorineural hearing loss (SNHL) and neurological impairment in congenital cytomegalovirus (cCMV) infection using MR imaging and define the best timing in pregnancy for prenatal assessment. Methods: In 121 patients with confirmed cCMV infection, brain features at MR imaging were respectively graded from 1 to 5: normal; isolated frontal/parieto–occipital hyperintensity; temporal periventricular hyperintensity; temporal/occipital cysts and/or intraventricular septa; migration disorders. Grading was correlated with postnatal SNHL and neurological impairment using regression analysis. In 51 fetuses with MR examinations at 26.9 and 33.0 weeks, the predictive value of SNHL and neurological impairment was compared using ROC curves. Results: Postnatal follow-up showed SNHL in 18 infants and neurological impairment in 10. MR grading was predictive of SNHL and of neurological impairment (P < 0.001). In grade 1 or 2, none had SNHL and 1/74 had neurological impairment. The areas under ROC curves for prediction of postnatal SNHL and of neurological impairment from first and second MR examination were comparable. Conclusion: Our data suggest that in cCMV infection, prediction of SNHL and neurological impairment is feasible by fetal MR imaging with a high negative predictive value and can equally be done at 27 or 33 weeks of gestation. Key points: • In cCMV, isolated periventricular T2-weighted signal hyperintensity has a good postnatal prognosis. • In cCMV, SNHL and neurological impairment can be predicted at 27 or 33 weeks. • In cCMV, fetal MR has a high NPV in predicting SNHL. • In cCMV, fetal MR has a high NPV in predicting neurological impairment.SCOPUS: ar.jinfo:eu-repo/semantics/publishe