Prioritization of candidate genes for attention deficit hyperactivity disorder by computational analysis of multiple data sources

Maternal Immune Activation Induces Neuroinflammation and Cortical Synaptic Deficits in the Adolescent Rat Offspring

Maternal immune activation (MIA), induced by infection during pregnancy, is an important risk factor for neuro-developmental disorders, such as autism. Abnormal maternal cytokine signaling may affect fetal brain development and contribute to neurobiological and behavioral changes in the offspring. Here, we examined the effect of lipopolysaccharide-induced MIA on neuro-inflammatory changes, as well as synaptic morphology and key synaptic protein level in cerebral cortex of adolescent male rat offspring. Adolescent MIA offspring showed elevated blood cytokine levels, microglial activation, increased pro-inflammatory cytokines expression and increased oxidative stress in the cerebral cortex. Moreover, pathological changes in synaptic ultrastructure of MIA offspring was detected, along with presynaptic protein deficits and down-regulation of postsynaptic scaffolding proteins. Consequently, ability to unveil MIA-induced long-term alterations in synapses structure and protein level may have consequences on postnatal behavioral changes, associated with, and predisposed to, the development of neuropsychiatric disorders.

NOS1 and SNAP25 polymorphisms are associated with Attention-Deficit/Hyperactivity Disorder symptoms in adults but not in children

Several investigations documented that Attention-Deficit/Hyperactivity Disorder (ADHD) is better conceptualized as a dimensional disorder. At the same time, the disorder seems to have different neurobiological underpinnings and phenotypic presentation in children compared to adults. Neurodevelopmental genes could explain, at least partly these differences. The aim of the present study was to examine possible associations between polymorphisms in SNAP25, MAP1B and NOS1 genes and ADHD symptoms in Brazilian samples of children/adolescents and adults with ADHD. The youth sample consisted of 301 patients whereas the adult sample comprises 485 individuals with ADHD. Diagnoses of ADHD and comorbidities were based on the Diagnostic and Statistical Manual of Mental Disorders-4th edition criteria. The Swanson, Nolan and Pelham Scale-Version IV (SNAP-IV) was applied by psychiatrists blinded to genotype. The total SNAP-IV scores were compared between genotypes. Impulsivity SNAP-IV scores were also compared according to NOS1 genotypes. Adult patients homozygous for the C allele at SNAP25 rs8636 showed significantly higher total SNAP-IV scores (F = 11.215; adjusted P-value = 0.004). Impulsivity SNAP-IV scores were also significantly different according to NOS1 rs478597 polymorphisms in adults with ADHD (F = 6.282; adjusted P-value = 0.026). These associations were not observed in children and adolescents with ADHD. These results suggest that SNAP25 and NOS1 genotypes influence ADHD symptoms only in adults with ADHD. Our study corroborates previous evidences for differences in the genetic contribution to adult ADHD compared with childhood ADHD.

Should we keep on? Looking into pharmacogenomics of ADHD in adulthood from a different perspective

A considerable proportion of adults with attention-deficit/hyperactivity disorder (ADHD) do not respond to the treatment with methylphenidate. This scenario could be due to inherited interindividual differences that may alter pharmacologic treatment response. In this sense, in 2012 we conducted a systematic search on PUBMED-indexed literature for articles containing information about pharmacogenomics of ADHD in adults. Five studies were found on methylphenidate pharmacogenomics and the only significant association was reported by one particular study. However, this single association with the SLC6A3 gene was not replicated in two subsequent reports. In the present review, although we could not find additional pharmacogenomics studies, we discuss these up-to-date findings and suggest new approaches for this field. Additionally, using systeomic-oriented databases, we provide a broad picture of new possible candidate genes as well as potential gene-gene interactions to be investigated in pharmacogenomics of persistent ADHD.

Integrative data mining highlights candidate genes for monogenic myopathies

Inherited myopathies are a heterogeneous group of disabling disorders with still barely understood pathological mechanisms. Around 40% of afflicted patients remain without a molecular diagnosis after exclusion of known genes. The advent of high-throughput sequencing has opened avenues to the discovery of new implicated genes, but a working list of prioritized candidate genes is necessary to deal with the complexity of analyzing large-scale sequencing data. Here we used an integrative data mining strategy to analyze the genetic network linked to myopathies, derive specific signatures for inherited myopathy and related disorders, and identify and rank candidate genes for these groups. Training sets of genes were selected after literature review and used in Manteia, a public web-based data mining system, to extract disease group signatures in the form of enriched descriptor terms, which include functional annotation, human and mouse phenotypes, as well as biological pathways and protein interactions. These specific signatures were then used as an input to mine and rank candidate genes, followed by filtration against skeletal muscle expression and association with known diseases. Signatures and identified candidate genes highlight both potential common pathological mechanisms and allelic disease groups. Recent discoveries of gene associations to diseases, like B3GALNT2, GMPPB and B3GNT1 to congenital muscular dystrophies, were prioritized in the ranked lists, suggesting a posteriori validation of our approach and predictions. We show an example of how the ranked lists can be used to help analyze high-throughput sequencing data to identify candidate genes, and highlight the best candidate genes matching genomic regions linked to myopathies without known causative genes. This strategy can be automatized to generate fresh candidate gene lists, which help cope with database annotation updates as new knowledge is incorporated.

Molecular genetic studies of ADHD and its candidate genes: a review

Attention-deficit/hyperactivity disorder (ADHD) is a common childhood-onset psychiatric disorder with high heritability. In recent years, numerous molecular genetic studies have been published to investigate susceptibility loci for ADHD. These results brought valuable candidates for further research, but they also presented great challenge for profound understanding of genetic data and general patterns of current molecular genetic studies of ADHD since they are scattered and heterogeneous. In this review, we presented a retrospective review of more than 300 molecular genetic studies for ADHD from two aspects: (1) the main achievements of various studies were summarized, including linkage studies, candidate-gene association studies, genome-wide association studies and genome-wide copy number variation studies, with a special focus on general patterns of study design and common sample features; (2) candidate genes for ADHD have been systematically evaluated in three ways for better utilization. The thorough summary of the achievements from various studies will provide an overview of the research status of molecular genetics studies for ADHD. Meanwhile, the analysis of general patterns and sample characteristics on the basis of these studies, as well as the integrative review of candidate ADHD genes, will propose new clues and directions for future experiment design.

Prioritization of candidate genes for periodontitis using multiple computational tools

BACKGROUND

Both genetic and environmental factors contribute to the development of periodontitis. Genetic studies identified a variety of candidate genes for periodontitis. The aim of the present study is to identify the most promising candidate genes for periodontitis using an integrative gene ranking method.

METHODS

Seed genes that were confirmed to be associated with periodontitis were identified using text mining. Three types of candidate genes were then extracted from different resources (expression profiles, genome-wide association studies). Combining the seed genes, four freely available bioinformatics tools (ToppGene, DIR, Endeavour, and GPEC) were integrated for prioritization of candidate genes. Candidate genes that identified with at least three programs and ranked in the top 20 by each program were considered the most promising.

RESULTS

Prioritization analysis resulted in 21 promising genes involved or potentially involved in periodontitis. Among them, IL18 (interleukin 18), CD44 (CD44 molecule), CXCL1 (chemokine [CXC motif] ligand 1), IL6ST (interleukin 6 signal transducer), MMP3 (matrix metallopeptidase 3), MMP7, CCR1 (chemokine [C-C motif] receptor 1), MMP13, and TLR9 (Toll-like receptor 9) had been associated with periodontitis. However, the roles of other genes, such as CSF3 (colony stimulating factor 3 receptor), CD40, TNFSF14 (tumor necrosis factor receptor superfamily, member 14), IFNB1 (interferon-β1), TIRAP (toll-interleukin 1 receptor domain containing adaptor protein), IL2RA (interleukin 2 receptor α), ETS1 (v-ets avian erythroblastosis virus E26 oncogene homolog 1), GADD45B (growth arrest and DNA-damage-inducible 45 β), BIRC3 (baculoviral IAP repeat containing 3), VAV1 (vav 1 guanine nucleotide exchange factor), COL5A1 (collagen, type V, α1), and C3 (complement component 3), have not been investigated thoroughly in the process of periodontitis. These genes are mainly involved in bacterial infection, immune response, and inflammatory reaction, suggesting that further characterizing their roles in periodontitis will be important.

CONCLUSIONS

A combination of computational tools will be useful in mining candidate genes for periodontitis. These theoretical results provide new clues for experimental biologists to plan targeted experiments.

Evidence of association between SNAP25 gene and attention deficit hyperactivity disorder in a Latin American sample

Attention deficit hyperactivity disorder (ADHD) is one of the most highly heritable behavioral disorders in childhood, with heritability estimates between 60 and 90 %. Family, twin and adoption studies have indicated a strong genetic component in the susceptibility to ADHD. The synaptosomal-associated protein of molecular weight 25 kDa (SNAP25) is a plasma membrane protein known to be involved in synaptic and neural plasticity. Animal model studies have shown that SNAP25 gene is responsible for hyperkinetic behavior in the coloboma mouse. In recent studies, several authors reported an association between SNAP25 and ADHD. In this study, we used a case-control approach to analyze the possible association of two polymorphisms of SNAP25 for possible association with ADHD in a sample of 73 cases and 152 controls in a Colombian children population. Polymorphisms are located in 3' untranslated region of SNAP25, positions T1065G and T1069C. We found a significant association with the GT haplotype (rs3746554|rs1051312) of SNAP25 (p = 0.001). Evidence of association was also found for the G/G genotype of rs3746554 (p = 0.002) and C/C genotype of rs1051312 (p = 0.009). This is the first study in a Latin American population. Similar to other studies, we found evidence of the association of SNAP25 and ADHD.

BDgene: a genetic database for bipolar disorder and its overlap with schizophrenia and major depressive disorder

BACKGROUND

Bipolar disorder (BD) is a common psychiatric disorder with complex genetic architecture. It shares overlapping genetic influences with schizophrenia (SZ) and major depressive disorder (MDD). Large numbers of genetic studies of BD and cross-disorder studies between BD and SZ/MDD have accumulated numerous genetic data. There is a growing need to integrate the data to provide a comprehensive data set to facilitate the genetic study of BD and its highly relevant diseases.

METHODS

BDgene database was developed to integrate BD-related genetic factors and shared ones with SZ/MDD from profound literature reading. On the basis of data from the literature, in-depth analyses were performed for further understanding of the data, including gene prioritization, pathway-based analysis, intersection analysis of multidisease candidate genes, and pathway enrichment analysis.

RESULTS

BDgene includes multiple types of literature-reported genetic factors of BD with both positive and negative results, including 797 genes, 3119 single nucleotide polymorphisms, and 789 regions. Shared genetic factors such as single nucleotide polymorphisms, genes, and regions from published cross-disorder studies among BD and SZ/MDD were also presented. In-depth data analyses identified 43 BD core genes; 70 BD candidate pathways; and 127, 79, and 107 new potential cross-disorder genes for BD-SZ, BD-MDD, and BD-SZ-MDD, respectively.

CONCLUSIONS

As a central genetic database for BD and the first cross-disorder database for BD and SZ/MDD, BDgene provides not only a comprehensive review of current genetic research but also high-confidence candidate genes and pathways for understanding of BD mechanism and shared etiology among its relevant diseases. BDgene is freely available at http://bdgene.psych.ac.cn.

Progress and challenges in the computational prediction of gene function using networks: 2012-2013 update

In an opinion published in 2012, we reviewed and discussed our studies of how gene network-based guilt-by-association (GBA) is impacted by confounds related to gene multifunctionality. We found such confounds account for a significant part of the GBA signal, and as a result meaningfully evaluating and applying computationally-guided GBA is more challenging than generally appreciated. We proposed that effort currently spent on incrementally improving algorithms would be better spent in identifying the features of data that do yield novel functional insights. We also suggested that part of the problem is the reliance by computational biologists on gold standard annotations such as the Gene Ontology. In the year since, there has been continued heavy activity in GBA-based research, including work that contributes to our understanding of the issues we raised. Here we provide a review of some of the most relevant recent work, or which point to new areas of progress and challenges.