ASD and genetic associations with receptors for oxytocin and vasopressin – AVPR1A, AVPR1B, and OXTR

Background: There are limited treatments available for autism spectrum disorder (ASD). Studies have reported significant associations between the receptor genes of oxytocin (OT) and vasopressin (AVP) and ASD diagnosis, as well as, ASD-related phenotypes. Researchers have also found the manipulation of these systems affect social and repetitive behaviors, core characteristics of ASD. Consequently, research involving the oxytocin/vasopressin pathways as intervention targets has increased. Therefore, further examination into the relationship between these neuropeptides and ASD was undertaken. In this study, we examined associations between variants in the receptor genes of vasopressin (AVPR1A, AVPR1B), oxytocin (OXTR) and ASD diagnosis along with related subphenotypes.Methods: Probands were assessed using Autism Diagnostic Interview-Revised, Autism Diagnostic Observation Schedule, and clinical DSM-IV-TR criteria. Single nucleotide polymorphisms (SNPs) in AVPR1B and OXTR, and microsatellites in AVPR1A were genotyped in ~200 families with a proband with ASD. Family-based association testing (FBAT) was utilized to determine associations between variants and ASD. Haplotypes composed of OXTR SNPs (i.e. rs53576-rs2254298-rs2268493) were also analyzed due to previously published associations.Results: Using the additive inheritance model in FBAT we found associations between AVPR1B SNPs (rs28632197, p=0.005, rs35369693, p=0.025) and diagnosis. As in other studies, OXTR rs2268493 (p=0.050) was associated with diagnosis. rs2268493 was also associated with ASD subphenotypes of social withdrawal (p=0.013) and insistence on sameness (p=0.039). Further analyses demonstrated that the haplotype, rs2254298-rs2268493 was found to be significantly associated with diagnosis (A-T; p=0.026). FBAT was also used to analyze AVPR1A microsatellites (RS1 and RS3). Both length variants were found to be associated with restrictive, repetitive behaviors, but not overall diagnosis. Correction for multiple comparisons was performed for SNPs tested in each gene region, only AVPR1B SNPs remained significantly associated with ASD diagnosis.Conclusions: Autism is a heterogeneous disorder with many genes and pathways that contribute to its development. SNPs and microsatellites in the receptor genes of OT and AVP are associated with ASD diagnosis and measures of social behavior as well as restricted repetitive behaviors. We reported a novel association with ASD and AVPR1B SNPs. Understanding of genotype-phenotype relationships may be helpful in the development of pharmacological interventions for the OT/AVP system

Neurotoxic 1-deoxysphingolipids and paclitaxel-induced peripheral neuropathy

Peripheral neuropathy is a major dose-limiting side effect of paclitaxel and cisplatin chemotherapy. In the current study, we tested the involvement of a novel class of neurotoxic sphingolipids, the 1-deoxysphingolipids. 1-Deoxysphingolipids are produced when the enzyme serine palmitoyltransferase uses l-alanine instead of l-serine as its amino acid substrate. We tested whether treatment of cells with paclitaxel (250 nM, 1 µM) and cisplatin (250 nM, 1 µM) would result in elevated cellular levels of 1-deoxysphingolipids. Our results revealed that paclitaxel, but not cisplatin treatment, caused a dose-dependent elevation of 1-deoxysphingolipids levels and an increase in the message and activity of serine palmitoyltransferase (P < 0.05). We also tested whether there is an association between peripheral neuropathy symptoms [evaluated by the European Organization for Research and Treatment of Cancer (EORTC) QLQ-chemotherapy-induced peripheral neuropathy-20 (CIPN20) instrument] and the 1-deoxysphingolipid plasma levels (measured by mass spectrometry) in 27 patients with breast cancer who were treated with paclitaxel chemotherapy. Our results showed that there was an association between the incidence and severity of neuropathy and the levels of very-long-chain 1-deoxyceramides such as C24 (P < 0.05), with the strongest association being with motor neuropathy (P < 0.001). Our data from cells and from patients with breast cancer suggest that 1-deoxysphingolipids, the very-long-chain in particular, play a role as molecular intermediates of paclitaxel-induced peripheral neuropathy.-Kramer, R., Bielawski, J., Kistner-Griffin, E., Othman, A., Alecu, I., Ernst, D., Kornhauser, D., Hornemann, T., Spassieva, S. Neurotoxic 1-deoxysphingolipids and paclitaxel-induced peripheral neuropathy

Study of functional infrared imaging for early detection of mucositis in locally advanced head and neck cancer treated with chemoradiotherapy

Background and purposeChemoradiotherapy (CRT) has led to improved efficacy in treating locally advanced squamous cell carcinoma of the head and neck (LA-SCCHN) but has led to almost universal in-field mucositis. Patients treated with the same regimen often have differences in mucositis occurrence and severity. Mucositis induced via radiation is known to represent an intense inflammatory response histologically. We hypothesized that patients destined to display severe mucocutaneous toxicity would demonstrate greater alterations in thermal intensity early in therapy than identically treated counterparts. This will allow identification of patients that will require more intensive supportive care using thermal imaging technology.Materials and methodsSubjects with LA-SCCHN (oral cavity or oropharynx) being treated with the identical chemoradiotherapy regimen underwent baseline and weekly thermal imaging. Changes in skin temperature caused by mucositis and dermatitis compared with a reference area (ΔT were calculated and correlated to grade of mucositis based on NCI-CTCAE 3.0.ResultsThirty-four subjects were enrolled. Grade 3 mucositis and dermatitis was observed in 53% and 21%, respectively. We observed a statistically significant positive association between an early rise in ΔT and mucositis grade (p value=0.03).ConclusionsThermal imaging is able to detect small and early changes in skin surface temperature that may be associated with development of mucositis in patients being treated with chemoradiotherapy

LBoost: A Boosting Algorithm with Application for Epistasis Discovery

<div><p>Many human diseases are attributable to complex interactions among genetic and environmental factors. Statistical tools capable of modeling such complex interactions are necessary to improve identification of genetic factors that increase a patient's risk of disease. Logic Forest (LF), a bagging ensemble algorithm based on logic regression (LR), is able to discover interactions among binary variables predictive of response such as the biologic interactions that predispose individuals to disease. However, LF's ability to recover interactions degrades for more infrequently occurring interactions. A rare genetic interaction may occur if, for example, the interaction increases disease risk in a patient subpopulation that represents only a small proportion of the overall patient population. We present an alternative ensemble adaptation of LR based on boosting rather than bagging called LBoost. We compare the ability of LBoost and LF to identify variable interactions in simulation studies. Results indicate that LBoost is superior to LF for identifying genetic interactions associated with disease that are infrequent in the population. We apply LBoost to a subset of single nucleotide polymorphisms on the PRDX genes from the Cancer Genetic Markers of Susceptibility Breast Cancer Scan to investigate genetic risk for breast cancer. LBoost is publicly available on CRAN as part of the LogicForest package, <a href="http://cran.r-project.org/">http://cran.r-project.org/</a>.</p> </div

Recovery of the dominant-dominant interactions and for MAFs of 0.1, 0.3, and 0.5.

<p>Each panel shows the proportion of times in 500 simulation runs the DD PIs and are recovered among the top 20 PIs by each method for different MAFs. Specifically, Panels A) and B) show the proportion of times each method recovers and respectively when MAFs for and are 0.1 and MAFs for and are 0.1. Panels C) and D) show the proportion of times each method recovers and respectively when MAFs for and are 0.3 and MAFs for and are 0.1. Panels E) and F) show the proportion of times each methods recovers and respectively when MAFs for and are 0.5 and MAFs for and are 0.1. Error bars represent 95% confidence intervals.</p

Two-locus interaction models.

<p>Type 1 represents a DD interaction between SNPs a and b while Type 2 represents RR interaction between a and b. A value of 1 indicates SNP combinations conferring increased risk of disease.</p

Population values for simulation parameters^†.

†<p>The disease prevalence is set at 0.1 and heritability is set a 0.02 for all simulations.</p>‡<p>MAFs are the same for risk alleles in an epistatic interaction. Prob(PI+) is the probability that a subject has the PI. Prob(D+PI+) and Prob(D+PI−) are the probabilities a subject has disease given that they have the PI and do not have the PI respectively. OR is the population odds ratio given the model, MAF, and heritability.</p

Loci nominally associated with autism from genome-wide analysis show enrichment of brain expression quantitative trait loci but not lymphoblastoid cell line expression quantitative trait loci

Abstract Background Autism spectrum disorder is a severe early onset neurodevelopmental disorder with high heritability but significant heterogeneity. Traditional genome-wide approaches to test for an association of common variants with autism susceptibility risk have met with limited success. However, novel methods to identify moderate risk alleles in attainable sample sizes are now gaining momentum. Methods In this study, we utilized publically available genome-wide association study data from the Autism Genome Project and annotated the results (P P-value indicating statistically significant enrichment of expression quantitative trait loci in top results from the autism genome-wide association study. Results Our findings show a global enrichment of brain expression quantitative trait loci, but not lymphoblastoid cell line expression quantitative trait loci, among top single nucleotide polymorphisms from an autism genome-wide association study. Additionally, the data implicates individual genes SLC25A12, PANX1 and PANX2 as well as pathways previously implicated in autism. Conclusions These findings provide supportive rationale for the use of annotation-based approaches to genome-wide association studies.</p