Characterization and Solubilization of Pyrrole–Imidazole Polyamide Aggregates

To optimize the biological activity of pyrrole–imidazole polyamide DNA-binding molecules, we characterized the aggregation propensity of these compounds through dynamic light scattering and fractional solubility analysis. Nearly all studied polyamides were found to form measurable particles 50–500 nm in size under biologically relevant conditions, while HPLC-based analyses revealed solubility trends in both core sequences and peripheral substituents that did not correlate with overall ionic charge. The solubility of both hairpin and cyclic polyamides was increased upon addition of carbohydrate solubilizing agents, in particular, 2-hydroxypropyl-β-cyclodextrin (HpβCD). In mice, the use of HpβCD allowed for improved injection conditions and subsequent investigations of the availability of polyamides in mouse plasma to human cells. The results of these studies will influence the further design of Py-Im polyamides and facilitate their study in animal models

Assessing the health and development of ART-conceived young adults: A study of feasibility, parent recall, and acceptability

<p>Abstract</p> <p>Background</p> <p>Assisted reproductive technologies (ART) to treat infertility have been available for nearly three decades. There have been a number of systematic comparisons of the health and development of ART-conceived with spontaneously-conceived (SC) children. Data are equivocal, some finding no differences and others that there are more health and developmental problems in the ART group. It is agreed that perinatal mortality and morbidity are worse after assisted than spontaneous conception and the impact of the hormonally altered intrauterine environment on puberty and later fertility of offspring are unknown. To date however, there has been no investigation of the health and development of ART-conceived young adults, including from the world's few prospective cohorts of ART conceived children. Obtaining these data requires contact to be made with people at least twenty years after discharge from the treating service. Given the ethical difficulties of approaching families to participate in research up to two decades after cessation of treatment, the aim of this exploratory qualitative investigation was to assess the feasibility and acceptability of approaching mothers treated for infertility prior to 1988, and their recall of the health and development of their ART-conceived young adult children.</p> <p>Methods</p> <p>Mothers treated for infertility at the Royal Women's Hospital Reproductive Biology Unit in Melbourne, Australia prior to 1988 were approached by a senior clinician and invited to participate in individual semi-structured interviews which could include their partners and/or young adult children if they wished. Recruitment continued until theoretic saturation had been reached.</p> <p>Results</p> <p>Ten mothers, two of their husbands and five young adults participated in interviews, and the health and development of 15 ART-conceived young adults were described. The experience of conception, pregnancy, birth and the health and development of the children were recalled vividly and in detail. Families were pleased to have been approached and supported the need for systematic data collection. Mode of conception had been disclosed from childhood to all the offspring.</p> <p>Conclusion</p> <p>With careful and sensitive recruitment strategies it is feasible and acceptable to contact women treated for infertility at least two decades ago and their families, to assess the health and development of ART-conceived young adults.</p

Population Differences in Transcript-Regulator Expression Quantitative Trait Loci

Gene expression quantitative trait loci (eQTL) are useful for identifying single nucleotide polymorphisms (SNPs) associated with diseases. At times, a genetic variant may be associated with a master regulator involved in the manifestation of a disease. The downstream target genes of the master regulator are typically co-expressed and share biological function. Therefore, it is practical to screen for eQTLs by identifying SNPs associated with the targets of a transcript-regulator (TR). We used a multivariate regression with the gene expression of known targets of TRs and SNPs to identify TReQTLs in European (CEU) and African (YRI) HapMap populations. A nominal p-value of <1×10−6 revealed 234 SNPs in CEU and 154 in YRI as TReQTLs. These represent 36 independent (tag) SNPs in CEU and 39 in YRI affecting the downstream targets of 25 and 36 TRs respectively. At a false discovery rate (FDR) = 45%, one cis-acting tag SNP (within 1 kb of a gene) in each population was identified as a TReQTL. In CEU, the SNP (rs16858621) in Pcnxl2 was found to be associated with the genes regulated by CREM whereas in YRI, the SNP (rs16909324) was linked to the targets of miRNA hsa-miR-125a. To infer the pathways that regulate expression, we ranked TReQTLs by connectivity within the structure of biological process subtrees. One TReQTL SNP (rs3790904) in CEU maps to Lphn2 and is associated (nominal p-value = 8.1×10−7) with the targets of the X-linked breast cancer suppressor Foxp3. The structure of the biological process subtree and a gene interaction network of the TReQTL revealed that tumor necrosis factor, NF-kappaB and variants in G-protein coupled receptors signaling may play a central role as communicators in Foxp3 functional regulation. The potential pleiotropic effect of the Foxp3 TReQTLs was gleaned from integrating mRNA-Seq data and SNP-set enrichment into the analysis

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Abstract: Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Inherited determinants of Crohn's disease and ulcerative colitis phenotypes: a genetic association study

Crohn's disease and ulcerative colitis are the two major forms of inflammatory bowel disease; treatment strategies have historically been determined by this binary categorisation. Genetic studies have identified 163 susceptibility loci for inflammatory bowel disease, mostly shared between Crohn's disease and ulcerative colitis. We undertook the largest genotype association study, to date, in widely used clinical subphenotypes of inflammatory bowel disease with the goal of further understanding the biological relations between diseases

IBD risk loci are enriched in multigenic regulatory modules encompassing putative causative genes.

GWAS have identified >200 risk loci for Inflammatory Bowel Disease (IBD). The majority of disease associations are known to be driven by regulatory variants. To identify the putative causative genes that are perturbed by these variants, we generate a large transcriptome data set (nine disease-relevant cell types) and identify 23,650 cis-eQTL. We show that these are determined by ∼9720 regulatory modules, of which ∼3000 operate in multiple tissues and ∼970 on multiple genes. We identify regulatory modules that drive the disease association for 63 of the 200 risk loci, and show that these are enriched in multigenic modules. Based on these analyses, we resequence 45 of the corresponding 100 candidate genes in 6600 Crohn disease (CD) cases and 5500 controls, and show with burden tests that they include likely causative genes. Our analyses indicate that ≥10-fold larger sample sizes will be required to demonstrate the causality of individual genes using this approach