Intrauterine growth pattern and birthweight discordance in twin pregnancies: a retrospective study

Background: Twins, compared to singletons, have an increased risk of perinatal mortality and morbidity, due mainly to a higher prevalence of preterm birth and low birthweight. Intrauterine growth restriction (IUGR) is also common and can affect one or both fetuses. In some cases, however, one twin is much smaller than the other (growth discordance). Usually, high birthweight discordance is associated with increased perinatal morbidity. The aim of this study is to describe the epidemiological features of a population of twins at birth, with particular reference to the interpretation and clinical effects of birthweight discordance. Methods: We evaluated retrospectively the clinical features of 70 infants born from twin pregnancies and assessed birthweight discordance in 31 pregnancies where both twins were followed at our institution. Discordance was treated both as a continuous and a categorical variable, using a cutoff of 18%. Possible relationships between birthweight discordance and other variables, such as maternal age, gestational age, birthweight percentile, number of SGA newborns in the pair, Hematocrit (Ht) discordance and neonatal anemia, prevalence of malformations, neonatal morbidity and death, were analyzed. Results: In our cohort birthweight percentile decreased slightly with increasing gestational age. Birthweight discordance, on the contrary, increased slightly with the increase of gestational age. A high discordance is associated to the presence of one SGA twin, with the other AGA or LGA. In our population, all 6 pregnancies in which discordance exceeded 18% belonged to this category (one SGA twin). Ht discordance at birth is associated to the presence of neonatal anemia in a twin, but it is not significantly related to weight discordance. Finally, in our case history, weight discordance is not associated in any way with the prevalence of malformations, morbidity and mortality. Conclusions: Birthweight discordance is an important indicator of complications that act asymmetrically on the two fetuses, affecting intrauterine growth in one of them, and usually determining the birth of a SGA infant. Our case history shows a significant statistical association between pair discordance and IUGR in one of the twins, but we could not demonstrate any relationship between discordance and the prevalence of malformations, morbidity and mortality

Imputation reliability on DNA biallelic markers for drug metabolism studies

Imputation is a statistical process used to predict genotypes of loci not directly assayed in a sample of individuals. Our goal is to measure the performance of imputation in predicting the genotype of the best known gene polymorphisms involved in drug metabolism using a common SNP array genotyping platform generally exploited in genome wide association studies.METHODS:Thirty-nine (39) individuals were genotyped with both Affymetrix Genome Wide Human SNP 6.0 (AFFY) and Affymetrix DMET Plus (DMET) platforms. AFFY and DMET contain nearly 900000 and 1931 markers respectively. We used a 1000 Genomes Pilot + HapMap 3 reference panel. Imputation was performed using the computer program Impute, version 2. SNPs contained in DMET, but not imputed, were analysed studying markers around their chromosome regions. The efficacy of the imputation was measured evaluating the number of successfully imputed SNPs (SSNPs).RESULTS:The imputation predicted the genotypes of 654 SNPs not present in the AFFY array, but contained in the DMET array. Approximately 1000 SNPs were not annotated in the reference panel and therefore they could not be directly imputed. After testing three different imputed genotype calling threshold (IGCT), we observed that imputation performs at its best for IGCT value equal to 50%, with rate of SSNPs (MAF > 0.05) equal to 85%.CONCLUSIONS:Most of the genes involved in drug metabolism can be imputed with high efficacy using standard genome-wide genotyping platforms and imputing procedures

Refining the accuracy of validated target identification through coding variant fine-mapping in type 2 diabetes.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition

Gene sequence variations of the platelet P2Y12 receptor are associated with coronary artery disease

<p>Abstract</p> <p>Background</p> <p>The platelet P2Y₁₂receptor plays a key role in platelet activation. The H2 haplotype of the P2Y₁₂receptor gene (<it>P2RY12</it>) has been found to be associated with maximal aggregation response to adenosine diphosphate (ADP) and with increased risk for peripheral arterial disease. No data are available on its association with coronary artery disease (CAD).</p> <p>Methods </p> <p>The H2 haplotype of the <it>P2RY12 </it>was determined in 1378 unrelated patients of both sexes selected according to the presence of significant coronary artery disease (CAD group) or having normal coronary angiogram at cardiac catheterization (CAD-free group). Significant coronary artery disease was angiographically determined, and was defined as a greater than 50% visually estimated luminal diameter stenosis in at least one major epicardial coronary artery.</p> <p>Results</p> <p>In the studied population 71.9% had CAD (n = 991) and 28.1% had normal coronary angiogram (n = 387). H2 haplotype carriers were more frequent in the CAD group (p = 0.03, OR = 1.36, 95%CI = 1.02–1.82). The H2 haplotype was significantly associated with CAD in non-smokers (p = 0.007, OR = 1.83 95%CI = 1.17–2.87), but not in smokers. The association remained significant after adjustment for other covariates (age, triglycerides, HDL, hypertension, diabetes) by multivariate logistic regression (p = 0.004, OR = 2.32 95%CI = 1.30–4.15).</p> <p>Conclusion</p> <p>Gene sequence variations of the P2Y₁₂receptor gene are associated with the presence of significant CAD, particularly in non-smoking individuals.</p

CACNA1E Variants Affect Beta Cell Function in Patients with Newly Diagnosed Type 2 Diabetes. The Verona Newly Diagnosed Type 2 Diabetes Study (VNDS) 3

Background: Genetic variability of the major subunit (CACNA1E) of the voltage-dependent Ca 2+ channel Ca V2.3 is associated to risk of type 2 diabetes, insulin resistance and impaired insulin secretion in nondiabetic subjects. The aim of the study was to test whether CACNA1E common variability affects beta cell function and/or insulin sensitivity in patients with newly diagnosed type 2 diabetes. Methodology/Principal Findings: In 595 GAD-negative, drug naïve patients (mean6SD; age: 58.5610.2 yrs; BMI: 29.965 kg/m 2, HbA1c: 7.061.3) with newly diagnosed type 2 diabetes we: 1. genotyped 10 tag SNPs in CACNA1E region reportedly covering,93 % of CACNA1E common variability: rs558994, rs679931, rs2184945, rs10797728, rs3905011, rs12071300, rs175338, rs3753737, rs2253388 and rs4652679; 2. assessed clinical phenotypes, insulin sensitivity by the euglycemic insulin clamp and beta cell function by state-of-art modelling of glucose/C-peptide curves during OGTT. Five CACNA1E tag SNPs (rs10797728, rs175338, rs2184945, rs3905011 and rs4652679) were associated with specific aspects of beta cell function (p,0.0520.01). Both major alleles of rs2184945 and rs3905011 were each (p,0.01 and p,0.005, respectively) associated to reduced proportional control with a demonstrable additive effect (p,0.005). In contrast, only the major allele of rs2253388 was related weakly to more severe insulin resistance (p,0.05). Conclusions/Significance: In patients with newly diagnosed type 2 diabetes CACNA1E common variability is strongl

Intranasal “painless” Human Nerve Growth Factors Slows Amyloid Neurodegeneration and Prevents Memory Deficits in App X PS1 Mice

Nerve Growth Factor (NGF) is being considered as a therapeutic candidate for Alzheimer's disease (AD) treatment but the clinical application is hindered by its potent pro-nociceptive activity. Thus, to reduce systemic exposure that would induce pain, in recent clinical studies NGF was administered through an invasive intracerebral gene-therapy approach. Our group demonstrated the feasibility of a non-invasive intranasal delivery of NGF in a mouse model of neurodegeneration. NGF therapeutic window could be further increased if its nociceptive effects could be avoided altogether. In this study we exploit forms of NGF, mutated at residue R100, inspired by the human genetic disease HSAN V (Hereditary Sensory Autonomic Neuropathy Type V), which would allow increasing the dose of NGF without triggering pain. We show that “painless” hNGF displays full neurotrophic and anti-amyloidogenic activities in neuronal cultures, and a reduced nociceptive activity in vivo. When administered intranasally to APPxPS1 mice ( n = 8), hNGFP61S/R100E prevents the progress of neurodegeneration and of behavioral deficits. These results demonstrate the in vivo neuroprotective and anti-amyloidogenic properties of hNGFR100 mutants and provide a rational basis for the development of “painless” hNGF variants as a new generation of therapeutics for neurodegenerative diseases

Multiscale modelling for fusion and fission materials: the M4F project

The M4F project brings together the fusion and fission materials communities working on the prediction of radiation damage production and evolution and its effects on the mechanical behaviour of irradiated ferritic/martensitic (F/M) steels. It is a multidisciplinary project in which several different experimental and computational materials science tools are integrated to understand and model the complex phenomena associated with the formation and evolution of irradiation induced defects and their effects on the macroscopic behaviour of the target materials. In particular the project focuses on two specific aspects: (1) To develop physical understanding and predictive models of the origin and consequences of localised deformation under irradiation in F/M steels; (2) To develop good practices and possibly advance towards the definition of protocols for the use of ion irradiation as a tool to evaluate radiation effects on materials. Nineteen modelling codes across different scales are being used and developed and an experimental validation programme based on the examination of materials irradiated with neutrons and ions is being carried out. The project enters now its 4th year and is close to delivering high-quality results. This paper overviews the work performed so far within the project, highlighting its impact for fission and fusion materials science.This work has received funding from the Euratom research and training programme 2014-2018 under grant agreement No. 755039 (M4F project)

Improved imputation of low-frequency and rare variants using the UK10K haplotype reference panel

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants