Natalia Vilor-Tejedor

New suggestive genetic loci and biological pathways for attention function in adult attention‐deficit/hyperactivity disorder

Attention deficit is one of the core symptoms of the attention‐deficit/hyperactivity disorder (ADHD). However, the specific genetic variants that may be associated with attention function in adult ADHD remain largely unknown. The present study aimed to identifying SNPs associated with attention function in adult ADHD and tested whether these associations were enriched for specific biological pathways. Commissions, hit‐reaction time (HRT), the standard error of HRT (HRTSE), and intraindividual coefficient variability (ICV) of the Conners Continuous Performance Test (CPT‐II) were assessed in 479 unmedicated adult ADHD individuals. A Genome‐Wide Association Study (GWAS) was conducted for each outcome and, subsequently, gene set enrichment analyses were performed. Although no SNPs reached genome‐wide significance (P < 5E−08), 27 loci showed suggestive evidence of association with the CPT outcomes (P < E−05). The most relevant associated SNP was located in the SORCS2 gene (P = 3.65E−07), previously associated with bipolar disorder (BP), Alzheimer disease (AD), and brain structure in elderly individuals. We detected other genes suggested to be involved in synaptic plasticity, cognitive function, neurological and neuropsychiatric disorders, and smoking behavior such as NUAK1, FGF20, NETO1, BTBD9, DLG2, TOP3B, and CHRNB4. Also, several of the pathways nominally associated with the CPT outcomes are relevant for ADHD such as the ubiquitin proteasome, neurodegenerative disorders, axon guidance, and AD amyloid secretase pathways. To our knowledge, this is the first GWAS and pathway analysis of attention function in patients with persistent ADHD. Overall, our findings reinforce the conceptualization of attention function as a potential endophenotype for studying the molecular basis of adult ADHD.

A genome-wide association study of attention function in a population-based sample of children

Background Attention function filters and selects behaviorally relevant information. This capacity is impaired in some psychiatric disorders and has been proposed as an endophenotype for Attention-Deficit/Hyperactivity Disorder; however, its genetic basis remains largely unknown. This study aimed to identify single nucleotide polymorphism (SNPs) associated with attention function. Materials and Methods The discovery sample included 1655 children (7–12 years) and the replication sample included 546 children (5–8 years). Five attention outcomes were assessed using the computerized Attentional Network Test (ANT): alerting, orienting, executive attention, Hit Reaction time (HRT) and the standard error of HRT (HRTSE). A Genome-wide Association Study was conducted for each outcome. Gene set enrichment analyses were performed to detect biological pathways associated with attention outcomes. Additional neuroimaging analyses were conducted to test neural effects of detected SNPs of interest. Results Thirteen loci showed suggestive evidence of association with attention function (P<10−5) in the discovery sample. One of them, the rs4321351 located in the PID1 gene, was nominally significant in the replication sample although it did not survive multiple testing correction. Neuroimaging analysis revealed a significant association between this SNP and brain structure and function involving the frontal-basal ganglia circuits. The mTOR signaling and Alzheimer disease-amyloid secretase pathways were significantly enriched for alerting, orienting and HRT respectively (FDR<5%). Conclusion These results suggest for the first time the involvement of the PID1 gene, mTOR signaling and Alzheimer disease-amyloid secretase pathways, in attention function during childhood. These genes and pathways have been proposed to play a role in neuronal plasticity, memory and neurodegenerative disease.

A genome-wide association meta-analysis of diarrhoeal disease in young children identifies FUT2 locus and provides plausible biological pathways

More than a million childhood diarrhoeal episodes occur worldwide each year, and in developed countries a considerable part of them are caused by viral infections. In this study, we aimed to search for genetic variants associated with diarrhoeal disease in young children by meta-analyzing genome-wide association studies, and to elucidate plausible biological mechanisms. The study was conducted in the context of the Early Genetics and Lifecourse Epidemiology (EAGLE) consortium. Data about diarrhoeal disease in two time windows (around 1 year of age and around 2 years of age) was obtained via parental questionnaires, doctor interviews or medical records. Standard quality control and statistical tests were applied to the 1000 Genomes imputed genotypic data. The meta-analysis (N = 5758) followed by replication (N = 3784) identified a genome-wide significant association between rs8111874 and diarrhoea at age 1 year. Conditional analysis suggested that the causal variant could be rs601338 (W154X) in the FUT2 gene. Children with the A allele, which results in a truncated FUT2 protein, had lower risk of diarrhoea. FUT2 participates in the production of histo-blood group antigens and has previously been implicated in the susceptibility to infections, including Rotavirus and Norovirus Gene-set enrichment analysis suggested pathways related to the histo-blood group antigen production, and the regulation of ion transport and blood pressure. Among others, the gastrointestinal tract, and the immune and neuro-secretory systems were detected as relevant organs. In summary, this genome-wide association meta-analysis suggests the implication of the FUT2 gene in diarrhoeal disease in young children from the general population.

Assessment of Susceptibility Risk Factors for ADHD in Imaging Genetic Studies.

Objective: ADHD consists of a count of symptoms that often presents heterogeneity due to overdispersion and excess of zeros. Statistical inference is usually based on a dichotomous outcome that is underpowered. The main goal of this study was to determine a suited probability distribution to analyze ADHD symptoms in Imaging Genetic studies. Method: We used two independent population samples of children to evaluate the consistency of the standard probability distributions based on count data for describing ADHD symptoms. Results: We showed that the zero-inflated negative binomial (ZINB) distribution provided the best power for modeling ADHD symptoms. ZINB reveals a genetic variant, rs273342 (Microtubule-Associated Protein [MAPRE2]), associated with ADHD (p value = 2.73E-05). This variant was also associated with perivascular volumes (Virchow–Robin spaces; p values < 1E-03). No associations were found when using dichotomous definition. Conclusion: We suggest that an appropriate modeling of ADHD symptoms increases statistical power to establish significant risk factors.

Efficient and Powerful Method for Combining P-Values in Genome-Wide Association Studies

The goal of Genome-wide Association Studies (GWAS) is the identification of genetic variants, usually single nucleotide polymorphisms (SNPs), that are associated with disease risk. However, SNPs detected so far with GWAS for most common diseases only explain a small proportion of their total heritability. Gene set analysis (GSA) has been proposed as an alternative to single-SNP analysis with the aim of improving the power of genetic association studies. Nevertheless, most GSA methods rely on expensive computational procedures that make unfeasible their implementation in GWAS. We propose a new GSA method, referred as globalEVT, which uses the extreme value theory to derive gene-level p-values. GlobalEVT reduces dramatically the computational requirements compared to other GSA approaches. In addition, this new approach improves the power by allowing different inheritance models for each genetic variant as illustrated in the simulation study performed and allows the existence of correlation between the SNPs. Real data analysis of an Attention-deficit/hyperactivity disorder (ADHD) study illustrates the importance of using GSA approaches for exploring new susceptibility genes. Specifically, the globalEVT method is able to detect genes related to Cyclophilin A like domain proteins which is known to play an important role in the mechanisms of ADHD development.

Imaging genetics in attention-deficit/hyperactivity disorder and related neurodevelopmental domains: state of the art

Joint analysis of genetic and neuroimaging data, known as Imaging Genetics (IG), offers an opportunity to deepen our knowledge of the biological mechanisms of neurodevelopmental domains. There has been exponential growth in the literature on IG studies, which challenges the standardization of analysis methods in this field. In this review we give a complete up-to-date account of IG studies on attention deficit hyperactivity disorder (ADHD) and related neurodevelopmental domains, which serves as a reference catalog for researchers working on this neurological disorder. We searched MEDLINE/Pubmed and identified 37 articles on IG of ADHD that met our eligibility criteria. We carefully cataloged these articles according to imaging technique, genes and brain region, and summarized the main results and characteristics of each study. We found that IG studies on ADHD generally focus on dopaminergic genes and the structure of basal ganglia using structural Magnetic Resonance Imaging (MRI). We found little research involving multiple genetic factors and brain regions because of the scarce use of multivariate strategies in data analysis. IG of ADHD and related neurodevelopmental domains is still in its early stages, and a lack of replicated findings is one of the most pressing challenges in the field.

Global adaptive rank truncated product method for gene‐set analysis in association studies

Gene set analysis (GSA) aims to assess the overall association of a set of genetic variants with a phenotype and has the potential to detect subtle effects of variants in a gene or a pathway that might be missed when assessed individually. We present a new implementation of the Adaptive Rank Truncated Product method (ARTP) for analyzing the association of a set of Single Nucleotide Polymorphisms (SNPs) in a gene or pathway. The new implementation, referred to as globalARTP, improves the original one by allowing the different SNPs in the set to have different modes of inheritance. We perform a simulation study for exploring the power of the proposed methodology in a set of scenarios with different numbers of causal SNPs with different effect sizes. Moreover, we show the advantage of using the gene set approach in the context of an Alzheimers disease case-control study where we explore the endocytosis pathway. The new method is implemented in the R function globalARTP of the globalGSA package available at http://cran.r-project.org.

Interaction between airborne copper exposure and ATP7B polymorphisms on inattentiveness in scholar children

Recent research indicates that airborne copper exposure in scholar children negatively affects brain functioning. These effects are likely to be influenced by the efficiency of copper metabolism, which is partly regulated by the ATPase copper transporting beta (ATP7B) gene. We investigated whether indoor and outdoor airborne copper exposure is differentially associated with child inattentiveness depending on genetic variation within the ATP7B gene in 1645 scholar children from the BREATHE project. Outdoor (courtyard) and indoor (classroom) air pollution levels were measured during class hours in each school. Inattentiveness was assessed through a follow-up with four measurements via the Attentional Network Test (4475 observations). Linear mixed models considering repeated measures were conducted to assess genetic and exposure main and interaction effects. Two interactions were detected indicating that ATP7B-rs1061472 (P for interaction 0.016) and ATP7B-rs1801243 (P for interaction 0.003) polymorphisms modified the association between indoor copper exposure and inattentiveness. Stratified analysis by genotypes revealed that both outdoor and indoor copper exposure increased inattentiveness in rs1061472-CC and rs1801243-CC carriers. These findings suggest that the genetic background promotes the association between airborne copper exposure at school with inattentiveness in children.Recent research indicates that airborne copper exposure in scholar children negatively affects brain functioning. These effects are likely to be influenced by the efficiency of copper metabolism, which is partly regulated by the ATPase copper transporting beta (ATP7B) gene. We investigated whether indoor and outdoor airborne copper exposure is differentially associated with child inattentiveness depending on genetic variation within the ATP7B gene in 1645 scholar children from the BREATHE project. Outdoor (courtyard) and indoor (classroom) air pollution levels were measured during class hours in each school. Inattentiveness was assessed through a follow-up with four measurements via the Attentional Network Test (4475 observations). Linear mixed models considering repeated measures were conducted to assess genetic and exposure main and interaction effects. Two interactions were detected indicating that ATP7B-rs1061472 (P for interaction 0.016) and ATP7B-rs1801243 (P for interaction 0.003) polymorphisms modified the association between indoor copper exposure and inattentiveness. Stratified analysis by genotypes revealed that both outdoor and indoor copper exposure increased inattentiveness in rs1061472-CC and rs1801243-CC carriers. These findings suggest that the genetic background promotes the association between airborne copper exposure at school with inattentiveness in children.

Strategies for integrated analysis in imaging genetics studies

HighlightsWhat is the key question?Despite the increasing volume of research on Imaging Genetics, it is unclear how to statistically analyze the results of these studies.What is the bottom line?Establish a clear consensus on the analytical procedures and methods implemented in Imaging Genetics.Why read on?This systematic review will help catalog methods and strategies that can serve as a reference for researchers in the field. ABSTRACT Imaging Genetics (IG) integrates neuroimaging and genomic data from the same individual, deepening our knowledge of the biological mechanisms behind neurodevelopmental domains and neurological disorders. Although the literature on IG has exponentially grown over the past years, the majority of studies have mainly analyzed associations between candidate brain regions and individual genetic variants. However, this strategy is not designed to deal with the complexity of neurobiological mechanisms underlying behavioral and neurodevelopmental domains. Moreover, larger sample sizes and increased multidimensionality of this type of data represents a challenge for standardizing modeling procedures in IG research. This review provides a systematic update of the methods and strategies currently used in IG studies, and serves as an analytical framework for researchers working in this field. To complement the functionalities of the Neuroconductor framework, we also describe existing R packages that implement these methodologies. In addition, we present an overview of how these methodological approaches are applied in integrating neuroimaging and genetic data.

Sparse multiple factor analysis to integrate genetic data, neuroimaging features, and attention-deficit/hyperactivity disorder domains

We proposed the application of a multivariate cross‐sectional framework based on a combination of a variable selection method and a multiple factor analysis (MFA) in order to identify complex meaningful biological signals related to attention‐deficit/hyperactivity disorder (ADHD) symptoms and hyperactivity/inattention domains.