Attention deficit hyperactivity disorder (ADHD) is a highly heritable neuropsychiatric disorder. In the present study, the authors investigated the presence of genomic convergence in the top findings ...of the five published genome-wide association studies (GWASs) of ADHD.
The authors carried out bioinformatics pathway analyses, using the Ingenuity and BiNGO tools, as well as a systematic literature analysis of 85 genes from the five published GWASs containing single nucleotide polymorphisms associated with ADHD at a p value <0.0001.
Findings revealed that 45 of the 85 top-ranked ADHD candidate genes encode proteins that fit into a neurodevelopmental network involved in directed neurite outgrowth. Data on copy number variations in patients with ADHD and data from animal studies provide further support for the involvement of this network in ADHD etiology. Several network proteins are also directly modulated by stimulants, the most commonly used psychopharmacological treatment for ADHD.
The authors have identified a protein network for ADHD that contributes to our understanding of the molecular basis of the disorder. In addition, the data suggest new candidate genes for ADHD and provide clues to future research into psychopharmacological ADHD treatments.
Genome-wide significant findings for psychiatric disorders - including neurodevelopmental disorders - are sparse, and replication of these findings has only been achieved through large international ...collaborations (such as the Psychiatric Genomics Consortium) using very large sample sizes (with tens of thousands of cases and controls). These enormous samples are required due to phenotypic heterogeneity, polygenicity, and generally small effect sizes of individual (common) genetic variants. This has severely hampered progress in understanding the genetic etiology of psychiatric disorders. Additionally, cross-disorder genetic overlap shows that diagnostic categories for those disorders do not follow the underlying biology well.
There is now substantial evidence from phenotypic studies that psychiatric and neurodevelopmental disorders represent the extreme ends of normal distributions of disorder-like traits within the general population. For some disorders, it has also been demonstrated that there is genetic overlap between the disorder and disorders-like traits. This strengthens the hypothesis that using (genome-wide) genetic association studies of disorder-like population traits for gene discovery in psychiatric/neurodevelopmental disorders could offer immense opportunities to our field, as we can greatly increase our sample sizes at relatively little cost. Additionally, such population traits can occur across different (co-morbid) psychiatric/neurodevelopmental disorders, which can provide insight into genetic and biological susceptibility factors that are common to multiple disorders.
The proposed symposium aims to provide an overview of recently conducted genetic studies of psychiatric disorder-like traits in population-based samples and, linked to this, how these studies could aid gene discovery in psychiatric genetics. More specifically, we will show how using genome-wide genetic data together with the ever-increasing amount of phenotypic trait data from very large population samples can lead to the identification of novel genes and biological mechanisms for several, clinically overlapping psychiatric disorders. In the first talk, Christie Burton (the Hospital of Sick Children, Toronto, Canada) will explain how she and her colleagues have used a trait-based approach in a large population-based childhood cohort for which they collected genetic, behavioral and cognitive data from children visiting the Ontario Science Centre. She will discuss the feasibility and power of using a quantitative trait in community samples to elucidate genetic contributors to psychiatric disorders. Secondly, Joanna Martin (Karolinska Institutet, Stockholm, Sweden) will discuss recent findings on the association of polygenic risk scores for 8 psychiatric disorders with disorder-related traits in a population sample of Swedish twins. In the third talk, Lucy Riglin (Cardiff university, Cardiff, UK) will discuss her findings of association between the genetic risk for certain psychiatric disorders and (ab)normal childhood neurodevelopment, using general population samples. All three talks will highlight the potential of trait genetics for gene finding in psychiatric disorders. In the final talk, Janita Bralten (Radboud University Medical Centre, Nijmegen, the Netherlands) will give an example of a trait-based approach that was used for discovering novel genetic and biological risk factors for autism spectrum disorders (ASDs).
The gene-gene associations in functional genomics are typically operationalized through correlational or information-theoretical measures: as an undirected graph of pairwise interactions between ...genes, where nodes represent genes and edges represent associations between pairs of genes. Such a functional connectivity can be uninformative as expression of genes tend to be very densely correlated. Moreover, functional connectivity does not contain information about the causal, or directed, interactions between genes. Causal inference would allow to answer the question whether phenotypes are a product of multiple gene-gene interactions or rather, if there are epicentres in the genome, leading to the phenotypes by influencing a number of genes in the network.
We use open-access data from study by Jaffe et al. (2014), reporting the expression of genes within the Dorsolateral Pre-Frontal Cortex (DLPFC) in post-mortem humans. We selected the data from 239 genes that were found to be associated with Obsessive Compulsive Disorder (OCD) in this study, as well as a random selection of 239 genes that were not found to be associated with OCD. In order to avoid confounders, we only consider the control cohort of N=102 participants. The data were normalized using log-transform, first gene-wise and then subject-wise.
The method is based on definition of causality (Pearl, 2000): if a high expression level in gene 1 is associated with high functional link between gene 1 and gene 2, we can infer that gene 1 has certain causal effect on gene 2. This influence can be established by windowing the data. The confidence intervals are then computed through permutation testing.
The results demonstrate that, as opposed to functional connectivity, the directed connectivity clearly differentiates gene co-expression network associated with OCD from an exemplary co-expression network unrelated with OCD. Although inhibition in the network is potentially possible (as influence of a value lower than zero), it was not found. The highest significance was found for the following: MED9 -> SLC25A3, MED9 -> RALB, CTSZ -> GAD1, RGS7 -> DOK1, DCLK1 -> C6ORF57. These results are interesting since MED9 takes part in creating new mRNA, therefore its increase can indeed influence the transcription of new mRNA.
Also, most connections appear relatively symmetrical, although symmetry is now imposed by the method. However, one particular gene, Calcium/calmodulin-dependent protein kinase type II subunit beta (CAMK2B), has substantially higher influence on the most of the other genes in the network than the feedback influence of these genes on CAMK2B. This suggests that CAMK2B might be a key component of the gene-expression network underlying OCD.
Classic interventional studies can be problematic in causal research in the gene co-expression networks as often dozens to thousands of genes underlie one phenotype. In this work, we propose a framework which addresses this issue and quantifies causal interactions without the need to employ any experimental manipulation. This can help in understanding hierarchy in gene co-expression networks, and possibly, in localizing the genes lying at the beginning of a causal chain leading to a particular phenotype. The method proposed in this study is novel, model-free and nonparametric, and the preliminary results when applied to the gene co-expression network of OCD in DLPFC are very promising. Therefore, we believe that it should be further tested, and validated in larger cohorts.
NK/T-cell ratios predict disease activity in relapsing remitting multiple sclerosis (RRMS). We investigated in 50 RRMS patients whether interleukin-2 receptor alpha-chain (IL-2Rα) expression and ...shedding associates with NK/T-cell balance, as suggested by daclizumab-trials in RRMS. A subsample (N = 31) was genotyped for IL2RA-associated MS risk SNPs. CD56bright NK-cell/IL-17A+CD4+ T-cell ratios correlated negatively with plasma and PBMC-culture supernatant sIL-2Rα-levels R = -0.209; p = 0.038 and R = -0.254; p = 0.012, resp., and with CD4+ T-cell CD25 MFI R = -0.341; p = 0.001. Carriers of the rs3118470 risk-allele showed higher sIL-2Rα-levels (P = 0.031) and a lower CD56bright NK-cell/IL-17A+CD4+ T-cell ratio (P = 0.038). Therefore, IL-2Rα may be involved in the interplay between NK-cells and T-cells.
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•NK/T ratios predict disease activity in relapsing remitting multiple sclerosis.•NK/IL-17A+CD4+ T ratios correlate negatively with serum sIL-2Rα levels.•Similar correlation found with IL-2Rα shedding in in vitro stimulated CD4+ T cells.•IL-2Rα on nonTreg CD4+ T cells correlates negatively with NK/IL-17A+CD4+ T ratios.•IL2RA risk allele is associated with lower CD56brightNK/IL-17A+CD4+ T ratio.
The mismatch repair gene MSH3 has been implicated as a genetic modifier of the CAG·CTG repeat expansion disorders Huntington's disease and myotonic dystrophy type 1. A recent Huntington's disease ...genome-wide association study found rs557874766, an imputed single nucleotide polymorphism located within a polymorphic 9 bp tandem repeat in MSH3/DHFR, as the variant most significantly associated with progression in Huntington's disease. Using Illumina sequencing in Huntington's disease and myotonic dystrophy type 1 subjects, we show that rs557874766 is an alignment artefact, the minor allele for which corresponds to a three-repeat allele in MSH3 exon 1 that is associated with a reduced rate of somatic CAG·CTG expansion (P = 0.004) and delayed disease onset (P = 0.003) in both Huntington's disease and myotonic dystrophy type 1, and slower progression (P = 3.86 × 10-7) in Huntington's disease. RNA-Seq of whole blood in the Huntington's disease subjects found that repeat variants are associated with MSH3 and DHFR expression. A transcriptome-wide association study in the Huntington's disease cohort found increased MSH3 and DHFR expression are associated with disease progression. These results suggest that variation in the MSH3 exon 1 repeat region influences somatic expansion and disease phenotype in Huntington's disease and myotonic dystrophy type 1, and suggests a common DNA repair mechanism operates in both repeat expansion diseases.
Reduced top-down control by cortical areas is assumed to underlie pathological forms of aggression. While the precise underlying molecular mechanisms are still elusive, it seems that balancing the ...excitatory and inhibitory tones of cortical brain areas has a role in aggression control. The molecular mechanisms underpinning aggression control were examined in the BALB/cJ mouse model. First, these mice were extensively phenotyped for aggression and anxiety in comparison to BALB/cByJ controls. Microarray data was then used to construct a molecular landscape, based on the mRNAs that were differentially expressed in the brains of BALB/cJ mice. Subsequently, we provided corroborating evidence for the key findings from the landscape through 1H-magnetic resonance imaging and quantitative polymerase chain reactions, specifically in the anterior cingulate cortex (ACC). The molecular landscape predicted that altered GABA signalling may underlie the observed increased aggression and anxiety in BALB/cJ mice. This was supported by a 40% reduction of 1H-MRS GABA levels and a 20-fold increase of the GABA-degrading enzyme Abat in the ventral ACC. As a possible compensation, Kcc2, a potassium-chloride channel involved in GABA-A receptor signalling, was found increased. Moreover, we observed aggressive behaviour that could be linked to altered expression of neuroligin-2, a membrane-bound cell adhesion protein that mediates synaptogenesis of mainly inhibitory synapses. In conclusion, Abat and Kcc2 seem to be involved in modulating aggressive and anxious behaviours observed in BALB/cJ mice through affecting GABA signalling in the ACC.
Myotonic dystrophy type 1 is the most common form of muscular dystrophy in adults and leads to severe fatigue, substantial physical functional impairment, and restricted social participation. In this ...study, we aimed to determine whether cognitive behavioural therapy optionally combined with graded exercise compared with standard care alone improved the health status of patients with myotonic dystrophy type 1.
We did a multicentre, single-blind, randomised trial, at four neuromuscular referral centres with experience in treating patients with myotonic dystrophy type 1 located in Paris (France), Munich (Germany), Nijmegen (Netherlands), and Newcastle (UK). Eligible participants were patients aged 18 years and older with a confirmed genetic diagnosis of myotonic dystrophy type 1, who were severely fatigued (ie, a score of ≥35 on the checklist-individual strength, subscale fatigue). We randomly assigned participants (1:1) to either cognitive behavioural therapy plus standard care and optional graded exercise or standard care alone. Randomisation was done via a central web-based system, stratified by study site. Cognitive behavioural therapy focused on addressing reduced patient initiative, increasing physical activity, optimising social interaction, regulating sleep–wake patterns, coping with pain, and addressing beliefs about fatigue and myotonic dystrophy type 1. Cognitive behavioural therapy was delivered over a 10-month period in 10–14 sessions. A graded exercise module could be added to cognitive behavioural therapy in Nijmegen and Newcastle. The primary outcome was the 10-month change from baseline in scores on the DM1-Activ-c scale, a measure of capacity for activity and social participation (score range 0–100). Statistical analysis of the primary outcome included all participants for whom data were available, using mixed-effects linear regression models with baseline scores as a covariate. Safety data were presented as descriptives. This trial is registered with ClinicalTrials.gov, number NCT02118779.
Between April 2, 2014, and May 29, 2015, we randomly assigned 255 patients to treatment: 128 to cognitive behavioural therapy plus standard care and 127 to standard care alone. 33 (26%) of 128 assigned to cognitive behavioural therapy also received the graded exercise module. Follow-up continued until Oct 17, 2016. The DM1-Activ-c score increased from a mean (SD) of 61·22 (17·35) points at baseline to 63·92 (17·41) at month 10 in the cognitive behavioural therapy group (adjusted mean difference 1·53, 95% CI −0·14 to 3·20), and decreased from 63·00 (17·35) to 60·79 (18·49) in the standard care group (−2·02, −4·02 to −0·01), with a mean difference between groups of 3·27 points (95% CI 0·93 to 5·62, p=0·007). 244 adverse events occurred in 65 (51%) patients in the cognitive behavioural therapy group and 155 in 63 (50%) patients in the standard care alone group, the most common of which were falls (155 events in 40 31% patients in the cognitive behavioural therapy group and 71 in 33 26% patients in the standard care alone group). 24 serious adverse events were recorded in 19 (15%) patients in the cognitive behavioural therapy group and 23 in 15 (12%) patients in the standard care alone group, the most common of which were gastrointestinal and cardiac.
Cognitive behavioural therapy increased the capacity for activity and social participation in patients with myotonic dystrophy type 1 at 10 months. With no curative treatment and few symptomatic treatments, cognitive behavioural therapy could be considered for use in severely fatigued patients with myotonic dystrophy type 1.
The European Union Seventh Framework Programme.
Abstract
Background
Aging is associated with the accumulation of somatic mutations in post‐mitotic neurons. While this idea is not new, recent advances in single‐cell sequencing techniques have now ...made it possible to not only unequivocally prove that these mutations occur but also to estimate their occurrence rates. Here, we aimed to investigate whether somatic mutations are associated with Alzheimer’s disease (AD) and gain insight into the potential pathophysiological consequences of such mutations in the brain.
Method
Starting from the average annual somatic variation rate of healthy neurons, we modeled the likelihood of a gene being affected by somatic mutations over time, based on the transcribed length of that gene. Subsequently, we investigated the gene length distribution of genes that are affected by somatic mutations in AD brains and we analyzed differential mRNA expression data from eight AD brain areas, including pathway analysis.
Result
Our model predicted that
CNTNAP2
, the largest gene in the human genome, has a 50% chance of having acquired at least one somatic mutation by the age of 65, which is in sharp contrast with average‐sized genes, in which there is only 1% chance of somatic mutations at 65. We also found that genes affected by somatic mutations are (much) longer than average and that larger genes are more likely to be reduced in their expression levels in AD‐vulnerable brain regions. Lastly, we found that these larger genes are predominantly expressed in neurons and are involved in synaptogenesis and synaptic adhesion, pathways that are predicted to be inhibited in AD based on the transcriptomic data.
Conclusion
Our findings implicate somatic mutations in large genes as potential contributors to AD pathology through their effect on synaptic function.
Background
Aging is associated with the accumulation of somatic mutations in post‐mitotic neurons. While this idea is not new, recent advances in single‐cell sequencing techniques have now made it ...possible to not only unequivocally prove that these mutations occur but also to estimate their occurrence rates. Here, we aimed to investigate whether somatic mutations are associated with Alzheimer’s disease (AD) and gain insight into the potential pathophysiological consequences of such mutations in the brain.
Method
Starting from the average annual somatic variation rate of healthy neurons, we modeled the likelihood of a gene being affected by somatic mutations over time, based on the transcribed length of that gene. Subsequently, we investigated the gene length distribution of genes that are affected by somatic mutations in AD brains and we analyzed differential mRNA expression data from eight AD brain areas, including pathway analysis.
Result
Our model predicted that CNTNAP2, the largest gene in the human genome, has a 50% chance of having acquired at least one somatic mutation by the age of 65, which is in sharp contrast with average‐sized genes, in which there is only 1% chance of somatic mutations at 65. We also found that genes affected by somatic mutations are (much) longer than average and that larger genes are more likely to be reduced in their expression levels in AD‐vulnerable brain regions. Lastly, we found that these larger genes are predominantly expressed in neurons and are involved in synaptogenesis and synaptic adhesion, pathways that are predicted to be inhibited in AD based on the transcriptomic data.
Conclusion
Our findings implicate somatic mutations in large genes as potential contributors to AD pathology through their effect on synaptic function.
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