EpiDOCK:a molecular docking-based tool for MHC class II binding prediction

Cellular peptide vaccines contain T-cell epitopes. The main prerequisite for a peptide to act as a T-cell epitope is that it binds to a major histocompatibility complex (MHC) protein. Peptide MHC binder identification is an extremely costly experimental challenge since human MHCs, named human leukocyte antigen, are highly polymorphic and polygenic. Here we present EpiDOCK, the first structure-based server for MHC class II binding prediction. EpiDOCK predicts binding to the 23 most frequent human, MHC class II proteins. It identifies 90% of true binders and 76% of true non-binders, with an overall accuracy of 83%. EpiDOCK is freely accessible at http://epidock.ddg-pharmfac. net. © The Author 2013. Published by Oxford University Press. All rights reserved.

Genetic markers, birth characteristics, and childhood leukemia risk

The cause for childhood acute lymphoblastic leukemia (ALL) remains unknown, but male gender is a risk factor, and among ethnicities, Hispanics have the highest risk. In this dissertation, we explored correlations among genetic polymorphisms, birth characteristics, and the risk of childhood ALL in a multi-ethnic sample in 161 cases and 231 controls recruited contemporaneously (2007-2012) in Houston, TX. We first examined three lymphoma risk markers, since lymphoma and ALL both stem from lymphoid cells. Of these, rs2395185 showed a risk association in non-Hispanic White males (OR=2.8, P=0.02; P interaction=0.03 for gender), but not in Hispanics. We verified previously known risk associations to validate the case-control sample. Mutations of HFE (C282Y, H63D) were genotyped to test whether iron-regulatory gene (IRG) variants known to elevate iron levels increase childhood ALL risk. Being positive for either polymorphism yielded only a modestly elevated OR in males, which increased to 2.96 (P=0.01) in the presence of a particular transferrin receptor (TFRC) genotype for rs3817672 (Pinteraction=0.04). SNP rs3817672 itself showed an ethnicity-specific association (P interaction=0.02 for ethnicity). We then examined additional IRG SNPs (rs422982, rs855791, rs733655), which showed risk associations in males (ORs=1.52 to 2.60). A polygenic model based on the number of polymorphic alleles in five IRG SNPs revealed a linear increase in risk (OR=2.00 per incremental change; P=0.002). Having three or more alleles compared with none was associated with increased risk in males (OR=4.12; P=0.004). Significant risk associations with childhood ALL was found with birth length (OR=1.18 per inch, P=0.04), high birth weight (>4,000g) (OR=1.93, P=0.01), and with gestational age (OR=1.10 per week, P=0.04). We observed a negative correlation between HFE SNP rs9366637 and gestational age (P=0.005), again, stronger in males ( P=0.001) and interacting with TFRC (P interaction=0.05). Our results showed that (i) ALL risk markers do not show universal associations across ethnicities or between genders, (ii) IRG SNPs modify ALL risk presumably by their effects on iron levels, (iii) a negative correlation between an HFE SNP and gestational age exists, which implicates an iron-related mechanism. The results suggest that currently unregulated supplemental iron intake may have implications on childhood ALL development.

The Genetics of Success: How Single-Nucleotide Polymorphisms Associated With Educational Attainment Relate to Life-Course Development.

A previous genome-wide association study (GWAS) of more than 100,000 individuals identified molecular-genetic predictors of educational attainment. We undertook in-depth life-course investigation of the polygenic score derived from this GWAS using the four-decade Dunedin Study (N = 918). There were five main findings. First, polygenic scores predicted adult economic outcomes even after accounting for educational attainments. Second, genes and environments were correlated: Children with higher polygenic scores were born into better-off homes. Third, children's polygenic scores predicted their adult outcomes even when analyses accounted for their social-class origins; social-mobility analysis showed that children with higher polygenic scores were more upwardly mobile than children with lower scores. Fourth, polygenic scores predicted behavior across the life course, from early acquisition of speech and reading skills through geographic mobility and mate choice and on to financial planning for retirement. Fifth, polygenic-score associations were mediated by psychological characteristics, including intelligence, self-control, and interpersonal skill. Effect sizes were small. Factors connecting DNA sequence with life outcomes may provide targets for interventions to promote population-wide positive development.

The genetic basis of psychological traits in infancy: Implications for understanding the causes of developmental psychopathology

This chapter reviews genetic studies that have aimed to identify genes influencing psychological traits in infancy (from birth to age 12 months), and considers how this research informs us about the causes of developmental psychopathology. Specifically, this chapter systematically reviews findings from studies that associated common genetic variants with individual variation in infants’ attention, temperament and behaviour, and attachment disorganisation. DRD4 and 5-HTTLPR genes were the most frequently studied candidate genes. Possibly the most coherent set of results relates to the L-DRD4 genotype, which is significantly associated with infant attention, temperament, and attachment style. Research in infant genetics has been strengthened by a careful focus on uniform age ranges within studies, by several longitudinal studies, and by exploration of gene-environment interactions between genes and maternal characteristics. However there is also considerable inconsistency in results in this field and possible reasons for this are discussed. The chapter outlines the main genetic methods that have been used and what new genetic approaches such as polygenic risk scoring could offer infant genetics. Recent findings suggest that some traits during infancy predict individual differences in developmental psychopathology in childhood. It is argued that infant genetic research has considerable potential for the identification of populations at risk for psychopathology in later life, and this remains an area open for future research.

Identification des gènes modifiant l’âge d’apparition du glaucome primaire à angle-ouvert dans une famille canadienne-française fondatrice.

Le glaucome est un groupe hétérogène de maladies qui sont caractérisées par l’apoptose des cellules ganglionnaires de la rétine et la dégénérescence progressive du nerf optique. Il s’agit de la première cause de cécité irréversible, qui touche environ 60 millions de personnes dans le monde. Sa forme la plus commune est le glaucome à angle ouvert (GAO), un trouble polygénique causé principalement par une prédisposition génétique, en interaction avec d’autres facteurs de risque tels que l’âge et la pression intraoculaire élevée (PIO). Le GAO est une maladie génétique complexe, bien que certaines formes sévères sont autosomiques dominantes. Dix-sept loci ont été liés à la maladie et acceptés par la « Human Genome Organisation » (HUGO) et cinq gènes ont été identifiés à ces loci (MYOC, OPTN, WDR36, NTF4, ASB10). Récemment, des études d’association sur l’ensemble du génome ont identifié plus de 20 facteurs de risque fréquents, avec des effets relativement faibles. Depuis plus de 50 ans, notre équipe étudie 749 membres de la grande famille canadienne-française CA où la mutation MYOCK423E cause une forme autosomale dominante de GAO dont l’âge de début est fortement variable. Premièrement, il a été montré que cette variabilité de l’âge de début de l’hypertension intraoculaire possède une importante composante génétique causée par au moins un gène modificateur. Ce modificateur interagit avec la mutation primaire et altère la sévérité du glaucome chez les porteurs de MYOCK423E. Un gène modificateur candidat WDR36 a été génotypé dans 2 grandes familles CA et BV. Les porteurs de variations non-synonymes de WDR36 ainsi que de MYOCK423E de la famille CA ont montré une tendance à développer la maladie plus jeune. Un outil de forage de données a été développé pour représenter des informations connues relatives à la maladie et faciliter la priorisation des gènes candidats. Cet outil a été appliqué avec succès à la dépression bipolaire et au glaucome. La suite du projet consiste à finaliser un balayage de génome sur la famille CA et à séquencer les loci afin d’identifier les variations modificatrices du glaucome. Éventuellement, ces variations permettront d’identifier les individus dont le glaucome risque d’être plus agressif.

Increasing the power of genome wide association studies in natural populations using repeated measures : evaluation and implementation

1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful. 2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden. 3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response. 4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

Gene-environment interactions in Autism Spectrum Disorders (ASD)

Spectrum Disorder (ASD), is a heterogeneous neurodevelopmental disorder with na estimated global prevalence rate of 17:10000, and a male to female ratio of 4:1. Patients with ASD presente language and communication difficulties and stereotyped behaviours. Comorbidity with other disorders, such as Intelectual Disability, Fragile-X syndrome (FXS) epilepsy and tuberous sclerosis frequently occurs. ASD presents amultifactorial etiopathology, and genetic factos alone are not suficiente to explain how the syndrome arises, with recente studies establishing ASD heritability at approximately 50%. Pre-, peri- and post-natal exposure to toxic environmental factos has been implicated in the development of ASD. Involvement of epigenetic regulatory mechanisms has been suggested, supported by the occurrence of autistic symptoms in patients with disorders aris ing from epigenetic mutations, such as FXS. A polygenic and epistatic model is a strong hypothesis to explain ASD. The main goal of this project is to identify specific exposure patterns to environmental toxicants in children diagnosed with ASD and integrate the results with genetic and epigenetic data.

Familial Hypercholesterolemia in Portugal: analysis of biomarkers

Aims of the study: 1) Cardiovascular risk assessment of a cohort of children with a clinical diagnosis of FH; 2) Identification of biomarkers to distinguish between monogenic and polygenic/environmental dyslipidemia in clinical settings; 3) Clinical criteria improvement to identify FH children.

Predictive ability of Genomic Estimated Family Values (GEFV).

Genomic selection (GS) has been used to compute genomic estimated breeding values (GEBV) of individuals; however, it has only been applied to animal and major plant crops due to high costs. Besides, breeding and selection is performed at the family level in some crops. We aimed to study the implementation of genome-wide family selection (GWFS) in two loblolly pine (Pinus taeda L.) populations: i) the breeding population CCLONES composed of 63 families (5-20 individuals per family), phenotyped for four traits (stem diameter, stem rust susceptibility, tree stiffness and lignin content) and genotyped using an Illumina Infinium assay with 4740 polymorphic SNPs, and ii) a simulated population that reproduced the same pedigree as CCLONES, 5000 polymorphic loci and two traits (oligogenic and polygenic). In both populations, phenotypic and genotypic data was pooled at the family level in silico. Phenotypes were averaged across replicates for all the individuals and allele frequency was computed for each SNP. Marker effects were estimated at the individual (GEBV) and family (GEFV) levels with Bayes-B using the package BGLR in R and models were validated using 10-fold cross validations. Predicted ability, computed by correlating phenotypes with GEBV and GEFV, was always higher for GEFV in both populations, even after standardizing GEFV predictions to be comparable to GEBV. Results revealed great potential for using GWFS in breeding programs that select families, such as most outbreeding forage species. A significant drop in genotyping costs as one sample per family is needed would allow the application of GWFS in minor crops.