“Gap hunting” to characterize clustered probe signals in Illumina methylation array data

Additional file 6: Figures S26–S31. All remaining SBE site scenarios. Each additional scenario of a SBE site-mapping SNP delimited in Fig. 4 not including the scenario shown in Fig. 5. Each of these figures contains 4 plots, showing every combination of CpG site interrogations on the forward and reverse strand as well as which nucleotide is the reference nucleotide

An Erythroid Differentiation Signature Predicts Response to Lenalidomide in Myelodysplastic Syndrome

Background: Lenalidomide is an effective new agent for the treatment of patients with myelodysplastic syndrome (MDS), an acquired hematopoietic disorder characterized by ineffective blood cell production and a predisposition to the development of leukemia. Patients with an interstitial deletion of Chromosome 5q have a high rate of response to lenalidomide, but most MDS patients lack this deletion. Approximately 25% of patients without 5q deletions also benefit from lenalidomide therapy, but response in these patients cannot be predicted by any currently available diagnostic assays. The aim of this study was to develop a method to predict lenalidomide response in order to avoid unnecessary toxicity in patients unlikely to benefit from treatment. Methods and Findings: Using gene expression profiling, we identified a molecular signature that predicts lenalidomide response. The signature was defined in a set of 16 pretreatment bone marrow aspirates from MDS patients without 5q deletions, and validated in an independent set of 26 samples. The response signature consisted of a cohesive set of erythroid-specific genes with decreased expression in responders, suggesting that a defect in erythroid differentiation underlies lenalidomide response. Consistent with this observation, treatment with lenalidomide promoted erythroid differentiation of primary hematopoietic progenitor cells grown in vitro. Conclusions: These studies indicate that lenalidomide-responsive patients have a defect in erythroid differentiation, and suggest a strategy for a clinical test to predict patients most likely to respond to the drug. The experiments further suggest that the efficacy of lenalidomide, whose mechanism of action in MDS is unknown, may be due to its ability to induce erythroid differentiation

Artificial feeding synchronizes behavioral, hormonal, metabolic and neural parameters in mother‐deprived neonatal rabbit pups

Nursing in the rabbit is under circadian control, and pups have a daily anticipatory behavioral arousal synchronized to this unique event, but it is not known which signal is the main entraining cue. In the present study, we hypothesized that food is the main entraining signal. Using mother‐deprived pups, we tested the effects of artificial feeding on the synchronization of locomotor behavior, plasma glucose, corticosterone, c‐Fos (FOS) and PERIOD1 (PER1) rhythms in suprachiasmatic, supraoptic, paraventricular and tuberomammillary nuclei. At postnatal day 1, an intragastric tube was placed by gastrostomy. The next day and for the rest of the experiment, pups were fed with a milk formula through the cannula at either 02:00 h or 10:00 h [feeding time = zeitgeber time (ZT)0]. At postnatal days 5–7, pups exhibited behavioral arousal, with a significant increase in locomotor behavior 60 min before feeding. Glucose levels increased after feeding, peaking at ZT4–ZT12 and then declining. Corticosterone levels were highest around the time of feeding, and then decreased to trough concentrations at ZT12–ZT16, increasing again in anticipation of the next feeding bout. In the brain, the suprachiasmatic nucleus had a rhythm of FOS and PER1 that was not significantly affected by the feeding schedule. Conversely, the supraoptic, paraventricular and tuberomammillary nuclei had rhythms of both FOS and PER1 induced by the time of scheduled feeding. We conclude that the nursing rabbit pup is a natural model of food entrainment, as food, in this case milk formula, is a strong synchronizing signal for behavioral, hormonal, metabolic and neural parameters. Nursing in the rabbit is under circadian control, and pups have a daily anticipatory behavioral arousal synchronized to this unique event, but it is not known which signal is the main entraining cue. In the present study, we hypothesized that food is the main entraining signal.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/88087/1/j.1460-9568.2011.07898.x.pd

Genome-wide association study identifies peanut allergy-specific loci and evidence of epigenetic mediation in US children

Food allergy (FA) affects 2%-10% of US children and is a growing clinical and public health problem. Here we conduct the first genome-wide association study of well-defined FA, including specific subtypes (peanut, milk and egg) in 2,759 US participants (1,315 children and 1,444 parents) from the Chicago Food Allergy Study, and identify peanut allergy (PA)-specific loci in the HLA-DR and -DQ gene region at 6p21.32, tagged by rs7192 (P=5.5 × 10 -8) and rs9275596 (P=6.8 × 10 -10), in 2,197 participants of European ancestry. We replicate these associations in an independent sample of European ancestry. These associations are further supported by meta-analyses across the discovery and replication samples. Both single-nucleotide polymorphisms (SNPs) are associated with differential DNA methylation levels at multiple CpG sites (

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia.

To access publisher's full text version of this article, please click on the hyperlink in Additional Links field or click on the hyperlink at the top of the page marked FilesOver the past decade genome-wide association studies (GWAS) have been applied to aid in the understanding of the biology of traits. The success of this approach is governed by the underlying effect sizes carried by the true risk variants and the corresponding statistical power to observe such effects given the study design and sample size under investigation. Previous ASD GWAS have identified genome-wide significant (GWS) risk loci; however, these studies were of only of low statistical power to identify GWS loci at the lower effect sizes (odds ratio (OR) <1.15).We conducted a large-scale coordinated international collaboration to combine independent genotyping data to improve the statistical power and aid in robust discovery of GWS loci. This study uses genome-wide genotyping data from a discovery sample (7387 ASD cases and 8567 controls) followed by meta-analysis of summary statistics from two replication sets (7783 ASD cases and 11359 controls; and 1369 ASD cases and 137308 controls).We observe a GWS locus at 10q24.32 that overlaps several genes including PITX3, which encodes a transcription factor identified as playing a role in neuronal differentiation and CUEDC2 previously reported to be associated with social skills in an independent population cohort. We also observe overlap with regions previously implicated in schizophrenia which was further supported by a strong genetic correlation between these disorders (Rg = 0.23; P = 9 × 10(-6)). We further combined these Psychiatric Genomics Consortium (PGC) ASD GWAS data with the recent PGC schizophrenia GWAS to identify additional regions which may be important in a common neurodevelopmental phenotype and identified 12 novel GWS loci. These include loci previously implicated in ASD such as FOXP1 at 3p13, ATP2B2 at 3p25.3, and a 'neurodevelopmental hub' on chromosome 8p11.23.This study is an important step in the ongoing endeavour to identify the loci which underpin the common variant signal in ASD. In addition to novel GWS loci, we have identified a significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4.National Institutes of Mental Health (NIMH, USA) ACE Network Autism Genetic Resource Exchange (AGRE) is a program of Autism Speaks (USA) The Autism Genome Project (AGP) from Autism Speaks (USA) Canadian Institutes of Health Research (CIHR), Genome Canada Health Research Board (Ireland) Hilibrand Foundation (USA) Medical Research Council (UK) National Institutes of Health (USA) Ontario Genomics Institute University of Toronto McLaughlin Centre Simons Foundation Johns Hopkins Autism Consortium of Boston NLM Family foundation National Institute of Health grants National Health Medical Research Council Scottish Rite Spunk Fund, Inc. Rebecca and Solomon Baker Fund APEX Foundation National Alliance for Research in Schizophrenia and Affective Disorders (NARSAD) endowment fund of the Nancy Pritzker Laboratory (Stanford) Autism Society of America Janet M. Grace Pervasive Developmental Disorders Fund The Lundbeck Foundation universities and university hospitals of Aarhus and Copenhagen Stanley Foundation Centers for Disease Control and Prevention (CDC) Netherlands Scientific Organization Dutch Brain Foundation VU University Amsterdam Trinity Centre for High Performance Computing through Science Foundation Ireland Autism Genome Project (AGP) from Autism Speak

Polygenic transmission disequilibrium confirms that common and rare variation act additively to create risk for autism spectrum disorders

Autism spectrum disorder (ASD) risk is influenced by common polygenic and de novo variation. We aimed to clarify the influence of polygenic risk for ASD and to identify subgroups of ASD cases, including those with strongly acting de novo variants, in which polygenic risk is relevant. Using a novel approach called the polygenic transmission disequilibrium test and data from 6,454 families with a child with ASD, we show that polygenic risk for ASD, schizophrenia, and greater educational attainment is over-transmitted to children with ASD. These findings hold independent of proband IQ. We find that polygenic variation contributes additively to risk in ASD cases who carry a strongly acting de novo variant. Lastly, we show that elements of polygenic risk are independent and differ in their relationship with phenotype. These results confirm that the genetic influences on ASD are additive and suggest that they create risk through at least partially distinct etiologic pathways

Accelerated epigenetic age at birth and child emotional and behavioural development in early childhood: a meta-analysis of four prospective cohort studies in ECHO

Background: ‘Epigenetic clocks’ have been developed to accurately predict chronologic gestational age and have been associated with child health outcomes in prior work. Methods: We meta-analysed results from four prospective U.S cohorts investigating the association between epigenetic age acceleration estimated using blood DNA methylation collected at birth and preschool age Childhood Behavior Checklist (CBCL) scores. Results: Epigenetic ageing was not significantly associated with CBCL total problem scores (β = 0.33, 95% CI: −0.95, 0.28) and DSM-oriented pervasive development problem scores (β = −0.23, 95% CI: −0.61, 0.15). No associations were observed for other DSM-oriented subscales. Conclusions: The meta-analysis results suggest that epigenetic gestational age acceleration is not associated with child emotional and behavioural functioning for preschool age group. These findings may relate to our study population, which includes two cohorts enriched for ASD and one preterm birth cohort.; future work should address the role of epigenetic age in child health in other study populations

Presence of an epigenetic signature of prenatal cigarette smoke exposure in childhood

Prenatal exposure to tobacco smoke has lifelong health consequences. Epigenetic signatures such as differences in DNA methylation (DNAm) may be a biomarker of exposure and, further, might have functional significance for how in utero tobacco exposure may influence disease risk. Differences in infant DNAm associated with maternal smoking during pregnancy have been identified. Here we assessed whether these infant DNAm patterns are detectible in early childhood, whether they are specific to smoking, and whether childhood DNAm can classify prenatal smoke exposure status. Using the Infinium 450 K array, we measured methylation at 26 CpG loci that were previously associated with prenatal smoking in infant cord blood from 572 children, aged 3–5, with differing prenatal exposure to cigarette smoke in the Study to Explore Early Development (SEED). Striking concordance was found between the pattern of prenatal smoking associated DNAm among preschool aged children in SEED and those observed at birth in other studies. These DNAm changes appear to be tobacco-specific. Support vector machine classification models and 10-fold cross-validation were applied to show classification accuracy for childhood DNAm at these 26 sites as a biomarker of prenatal smoking exposure. Classification models showed prenatal exposure to smoking can be assigned with 81% accuracy using childhood DNAm patterns at these 26 loci. These findings support the potential for blood-derived DNAm measurements to serve as biomarkers for prenatal exposure