A brief report: de novo copy number variants in children with attention deficit hyperactivity disorder

Rare de novo damaging DNA variants are enriched in attention-deficit/hyperactivity disorder and implicate risk genes

Research demonstrates the important role of genetic factors in attention-deficit/hyperactivity disorder (ADHD). DNA sequencing of families provides a powerful approach for identifying de novo (spontaneous) variants, leading to the discovery of hundreds of clinically informative risk genes for other childhood neurodevelopmental disorders. This approach has yet to be extensively leveraged in ADHD. We conduct whole-exome DNA sequencing in 152 families, comprising a child with ADHD and both biological parents, and demonstrate a significant enrichment of rare and ultra-rare de novo gene-damaging mutations in ADHD cases compared to unaffected controls. Combining these results with a large independent case-control DNA sequencing cohort (3206 ADHD cases and 5002 controls), we identify lysine demethylase 5B (KDM5B) as a high-confidence risk gene for ADHD and estimate that 1057 genes contribute to ADHD risk. Using our list of genes harboring ultra-rare de novo damaging variants, we show that these genes overlap with previously reported risk genes for other neuropsychiatric conditions and are enriched in several canonical biological pathways, suggesting early neurodevelopmental underpinnings of ADHD. This work provides insight into the biology of ADHD and demonstrates the discovery potential of DNA sequencing in larger parent-child trio cohorts.

Copy number variations and their effect on the plasma proteome

Structural variations, including copy number variations (CNVs), affect around 20 million bases in the human genome and are common causes of rare conditions. CNVs are rarely investigated in complex disease research because most CNVs are not targeted on the genotyping arrays or the reference panels for genetic imputation. In this study, we characterize CNVs in a Swedish cohort (N = 1,021) using short-read whole-genome sequencing (WGS) and use long-read WGS for validation in a subcohort (N = 15), and explore their effect on 438 plasma proteins. We detected 184,182 polymorphic CNVs and identified 15 CNVs to be associated with 16 proteins (P < 8.22×10-10). Of these, 5 CNVs could be perfectly validated using long-read sequencing, including a CNV which was associated with measurements of the osteoclast-associated immunoglobulin-like receptor (OSCAR) and located upstream of OSCAR, a gene important for bone health. Two other CNVs were identified to be clusters of many short repetitive elements and another represented a complex rearrangement including an inversion. Our findings provide insights into the structure of common CNVs and their effects on the plasma proteome, and highlights the importance of investigating common CNVs, also in relation to complex diseases.

Genetic architecture of ADHD and overlap with other psychiatric disorders and cognition-related phenotypes

Attention-deficit/hyperactivity disorder (ADHD) co-occurs with many other psychiatric disorders and traits. In this review, we summarize and interpret the existing literature on the genetic architecture of these comorbidities based on hypothesis-generating approaches. Quantitative genetic studies indicate that genetic factors play a substantial role in the observed co-occurrence of ADHD with many different disorders and traits. Molecular genetic correlations derived from genome-wide association studies and results of studies based on polygenic risk scores confirm the general pattern but provide effect estimates that are smaller than those from twin studies. The identification of the specific genetic variants and biological pathways underlying co-occurrence using genome-wide approaches is still in its infancy. The first analyses of causal inference using genetic data support causal relationships between ADHD and comorbid disorders, although bidirectional effects identified in some instances point to complex relationships. While several issues in the methodology and inferences from the results are still to be overcome, this review shows that the co-occurrence of ADHD with many psychiatric disorders and traits is genetically interpretable.

Update on genetics of attention deficit/hyperactivity disorder: current status 2023

PURPOSE OF REVIEW

Attention deficit/hyperactivity disorder (ADHD) shows consistently high heritability in genetic research. In this review article, we give an overview of the analysis of common and rare variants and some insight into current genetic methodology and their link to clinical practice.

RECENT FINDINGS

The heritability of about 80% is also high in comparison to other psychiatric diseases. However, recent studies estimate the proportion of heritability based on single nucleotide variants at 22%. The hidden heritability is an ongoing question in ADHD genetics. Common variants derived from mega genome-wide association analyses (GWAS) and subsequent meta-analyses usually display small effect sizes and explain only a small fraction of phenotypic variance. Rare variants, on the contrary, not only display large effect sizes but also rather explain, due to their rareness, a small fraction on phenotypic variance. Applying polygenic risk score (PRS) analysis is an improved approach of combining effect sizes of many common variants with clinically relevant measures in ADHD.

SUMMARY

We provide a concise overview on how genetic analysis, with a focus on GWAS and PRS, can help explain different behavioural phenotypes in ADHD and how they can be used for diagnosis and therapy prediction. Increased sample sizes of GWAS, meta-analyses and use of PRS is increasingly informative and sets the course for a new era in genetics of ADHD.

Investigating Direct and Indirect Genetic Effects in Attention-Deficit/Hyperactivity Disorder Using Parent-Offspring Trios

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is highly heritable, but little is known about the relative effects of transmitted (i.e., direct) and nontransmitted (i.e., indirect) common variant risks. Using parent-offspring trios, we tested whether polygenic liability for neurodevelopmental and psychiatric disorders and lower cognitive ability is overtransmitted to ADHD probands. We also tested for indirect or genetic nurture effects by examining whether nontransmitted ADHD polygenic liability is elevated. Finally, we examined whether complete trios are representative of the clinical ADHD population.

METHODS

Polygenic risk scores (PRSs) for ADHD, anxiety, autism, bipolar disorder, depression, obsessive-compulsive disorder, schizophrenia, Tourette syndrome, and cognitive ability were calculated in UK control subjects (n = 5081), UK probands with ADHD (n = 857), their biological parents (n = 328 trios), and also a replication sample of 844 ADHD trios.

RESULTS

ADHD PRSs were overtransmitted and cognitive ability and obsessive-compulsive disorder PRSs were undertransmitted. These results were independently replicated. Overtransmission of polygenic liability was not observed for other disorders. Nontransmitted alleles were not enriched for ADHD liability compared with control subjects. Probands from incomplete trios had more hyperactive-impulsive and conduct disorder symptoms, lower IQ, and lower socioeconomic status than complete trios. PRS did not vary by trio status.

CONCLUSIONS

The results support direct transmission of polygenic liability for ADHD and cognitive ability from parents to offspring, but not for other neurodevelopmental/psychiatric disorders. They also suggest that nontransmitted neurodevelopmental/psychiatric parental alleles do not contribute indirectly to ADHD via genetic nurture. Furthermore, ascertainment of complete ADHD trios may be nonrandom, in terms of demographic and clinical factors.

The Evolution of tRNA Copy Number and Repertoire in Cellular Life

tRNAs are universal decoders that bridge the gap between transcriptome and proteome. They can also be processed into small RNA fragments with regulatory functions. In this work, we show that tRNA copy number is largely controlled by genome size in all cellular organisms, in contrast to what is observed for protein-coding genes that stop expanding between ~20,000 and ~35,000 loci per haploid genome in eukaryotes, regardless of genome size. Our analyses indicate that after the bacteria/archaea split, the tRNA gene pool experienced the evolution of increased anticodon diversity in the archaeal lineage, along with a tRNA gene size increase and mature tRNA size decrease. The evolution and diversification of eukaryotes from archaeal ancestors involved further expansion of the tRNA anticodon repertoire, additional increase in tRNA gene size and decrease in mature tRNA length, along with an explosion of the tRNA gene copy number that emerged coupled with accelerated genome size expansion. Our findings support the notion that macroscopic eukaryotes with a high diversity of cell types, such as land plants and vertebrates, independently evolved a high diversity of tRNA anticodons along with high gene redundancy caused by the expansion of the tRNA copy number. The results presented here suggest that the evolution of tRNA genes played important roles in the early split between bacteria and archaea, and in eukaryogenesis and the later emergence of complex eukaryotes, with potential implications in protein translation and gene regulation through tRNA-derived RNA fragments.

Attention-deficit/hyperactive disorder updates

Background

Attention-deficit/hyperactive disorder (ADHD) is a neurodevelopmental disorder that commonly occurs in children with a prevalence ranging from 3.4 to 7.2%. It profoundly affects academic achievement, well-being, and social interactions. As a result, this disorder is of high cost to both individuals and society. Despite the availability of knowledge regarding the mechanisms of ADHD, the pathogenesis is not clear, hence, the existence of many challenges especially in making correct early diagnosis and provision of accurate management.

Objectives

We aimed to review the pathogenic pathways of ADHD in children. The major focus was to provide an update on the reported etiologies in humans, animal models, modulators, therapies, mechanisms, epigenetic changes, and the interaction between genetic and environmental factors.

Methods

References for this review were identified through a systematic search in PubMed by using special keywords for all years until January 2022.

Results

Several genes have been reported to associate with ADHD: DRD1, DRD2, DRD4, DAT1, TPH2, HTR1A, HTR1B, SLC6A4, HTR2A, DBH, NET1, ADRA2A, ADRA2C, CHRNA4, CHRNA7, GAD1, GRM1, GRM5, GRM7, GRM8, TARBP1, ADGRL3, FGF1, MAOA, BDNF, SNAP25, STX1A, ATXN7, and SORCS2. Some of these genes have evidence both from human beings and animal models, while others have evidence in either humans or animal models only. Notably, most of these animal models are knockout and do not generate the genetic alteration of the patients. Besides, some of the gene polymorphisms reported differ according to the ethnic groups. The majority of the available animal models are related to the dopaminergic pathway. Epigenetic changes including SUMOylation, methylation, and acetylation have been reported in genes related to the dopaminergic pathway.

Conclusion

The dopaminergic pathway remains to be crucial in the pathogenesis of ADHD. It can be affected by environmental factors and other pathways. Nevertheless, it is still unclear how environmental factors relate to all neurotransmitter pathways; thus, more studies are needed. Although several genes have been related to ADHD, there are few animal model studies on the majority of the genes, and they do not generate the genetic alteration of the patients. More animal models and epigenetic studies are required.

Genetics of Attention-Deficit Hyperactivity Disorder

Attention-Deficit Hyperactivity Disorder (ADHD) has long been recognized as being a highly heritable condition and our understanding of the genetic contributions to ADHD has grown over the past few decades. This chapter will discuss the studies that have examined its heritability and the efforts to identify specific genetic risk-variants at the molecular genetic level. We outline the various techniques that have been used to characterize genetic contributions to ADHD, describing what we have learnt so far, what there is still to learn and the methodologies that can be used to further our knowledge. In doing so we will discuss research into rare and common genetic variants, polygenic risk scores, and gene-environment interplay, while also describing what genetic studies have revealed about the biological processes involved in ADHD and what they have taught us about the overlap between ADHD and other psychiatric and somatic disorders. Finally, we will discuss the strengths and limitations of the current methodologies and clinical implications of genetic research to date.

Aggregative trans-eQTL analysis detects trait-specific target gene sets in whole blood

Large scale genetic association studies have identified many trait-associated variants and understanding the role of these variants in the downstream regulation of gene-expressions can uncover important mediating biological mechanisms. Here we propose ARCHIE, a summary statistic based sparse canonical correlation analysis method to identify sets of gene-expressions trans-regulated by sets of known trait-related genetic variants. Simulation studies show that compared to standard methods, ARCHIE is better suited to identify "core"-like genes through which effects of many other genes may be mediated and can capture disease-specific patterns of genetic associations. By applying ARCHIE to publicly available summary statistics from the eQTLGen consortium, we identify gene sets which have significant evidence of trans-association with groups of known genetic variants across 29 complex traits. Around half (50.7%) of the selected genes do not have any strong trans-associations and are not detected by standard methods. We provide further evidence for causal basis of the target genes through a series of follow-up analyses. These results show ARCHIE is a powerful tool for identifying sets of genes whose trans-regulation may be related to specific complex traits.

NeuroSCORE is a genome-wide omics-based model that identifies candidate disease genes of the central nervous system

To identify candidate disease genes of central nervous system (CNS) phenotypes, we created the Neurogenetic Systematic Correlation of Omics-Related Evidence (NeuroSCORE). We identified five genome-wide metrics highly associated with CNS phenotypes to score 19,601 protein-coding genes. Genes scored one point per metric (range: 0-5), identifying 8298 scored genes (scores ≥ 1) and 1601 "high scoring" genes (scores ≥ 3). Using logistic regression, we determined the odds ratio that genes with a NeuroSCORE from 1 to 5 would be associated with known CNS-related phenotypes compared to genes that scored zero. We tested NeuroSCORE using microarray copy number variants (CNVs) in case-control cohorts and aggregate mouse model data. High scoring genes are associated with CNS phenotypes (OR = 5.5, p < 2E-16), enriched in case CNVs, and mouse ortholog genes that cause behavioral and nervous system abnormalities. We identified 1058 high scoring genes with no disease association in OMIM. Transforming the logistic regression results indicates high scoring genes have an 84-92% chance of being associated with a CNS phenotype. Top scoring genes include GRIA1, MAP4K4, SF1, TNPO2, and ZSWIM8. Finally, we interrogated CNVs in the Clinical Genome Resource, finding the majority of clinically significant CNVs contain high scoring genes. These findings can direct future research and improve molecular diagnostics.

Fully exploiting SNP arrays: a systematic review on the tools to extract underlying genomic structure

Single nucleotide polymorphisms (SNPs) are the most abundant type of genomic variation and the most accessible to genotype in large cohorts. However, they individually explain a small proportion of phenotypic differences between individuals. Ancestry, collective SNP effects, structural variants, somatic mutations or even differences in historic recombination can potentially explain a high percentage of genomic divergence. These genetic differences can be infrequent or laborious to characterize; however, many of them leave distinctive marks on the SNPs across the genome allowing their study in large population samples. Consequently, several methods have been developed over the last decade to detect and analyze different genomic structures using SNP arrays, to complement genome-wide association studies and determine the contribution of these structures to explain the phenotypic differences between individuals. We present an up-to-date collection of available bioinformatics tools that can be used to extract relevant genomic information from SNP array data including population structure and ancestry; polygenic risk scores; identity-by-descent fragments; linkage disequilibrium; heritability and structural variants such as inversions, copy number variants, genetic mosaicisms and recombination histories. From a systematic review of recently published applications of the methods, we describe the main characteristics of R packages, command-line tools and desktop applications, both free and commercial, to help make the most of a large amount of publicly available SNP data.

Insights into attention-deficit/hyperactivity disorder from recent genetic studies

Attention-deficit/hyperactivity disorder (ADHD) is a common and highly heritable neurodevelopmental disorder (NDD). In this narrative review, we summarize recent advances in quantitative and molecular genetic research from the past 5-10 years. Combined with large-scale international collaboration, these advances have resulted in fast-paced progress in understanding the etiology of ADHD and how genetic risk factors map on to clinical heterogeneity. Studies are converging on a number of key insights. First, ADHD is a highly polygenic NDD with a complex genetic architecture encompassing risk variants across the spectrum of allelic frequencies, which are implicated in neurobiological processes. Second, genetic studies strongly suggest that ADHD diagnosis shares a large proportion of genetic risks with continuously distributed traits of ADHD in the population, with shared genetic risks also seen across development and sex. Third, ADHD genetic risks are shared with those implicated in many other neurodevelopmental, psychiatric and somatic phenotypes. As sample sizes and the diversity of genetic studies continue to increase through international collaborative efforts, we anticipate further success with gene discovery, characterization of how the ADHD phenotype relates to other human traits and growing potential to use genomic risk factors for understanding clinical trajectories and for precision medicine approaches.

Copy number variation and neuropsychiatric illness

Copy number variants (CNVs) at specific loci have been identified as important risk factors for several neuropsychiatric disorders, such as schizophrenia, autism spectrum disorder, intellectual disability (ID) and depression. These CNVs are individually rare (<0.5% frequency), have high effect sizes, and show pleiotropic effects for multiple neuropsychiatric disorders, which implies a shared aetiology. Neuropsychiatric CNVs are also associated with cognitive impairment and other medical morbidities, such as heart defects and obesity. As most neuropsychiatric CNVs are multigenic, it has been challenging to map their effects onto specific biological processes, although gene-set analyses have implicated genes related to the synapse and chromatin regulation. However, future whole-genome sequencing studies have potential for identifying novel single-gene CNV associations, which could provide insights into the pathophysiology underlying neuropsychiatric disorders.

A descriptive analysis of the data availability statements accompanying medRxiv preprints and a comparison with their published counterparts

OBJECTIVE

To determine whether medRxiv data availability statements describe open or closed data-that is, whether the data used in the study is openly available without restriction-and to examine if this changes on publication based on journal data-sharing policy. Additionally, to examine whether data availability statements are sufficient to capture code availability declarations.

DESIGN

Observational study, following a pre-registered protocol, of preprints posted on the medRxiv repository between 25th June 2019 and 1st May 2020 and their published counterparts.

MAIN OUTCOME MEASURES

Distribution of preprinted data availability statements across nine categories, determined by a prespecified classification system. Change in the percentage of data availability statements describing open data between the preprinted and published versions of the same record, stratified by journal sharing policy. Number of code availability declarations reported in the full-text preprint which were not captured in the corresponding data availability statement.

RESULTS

3938 medRxiv preprints with an applicable data availability statement were included in our sample, of which 911 (23.1%) were categorized as describing open data. 379 (9.6%) preprints were subsequently published, and of these published articles, only 155 contained an applicable data availability statement. Similar to the preprint stage, a minority (59 (38.1%)) of these published data availability statements described open data. Of the 151 records eligible for the comparison between preprinted and published stages, 57 (37.7%) were published in journals which mandated open data sharing. Data availability statements more frequently described open data on publication when the journal mandated data sharing (open at preprint: 33.3%, open at publication: 61.4%) compared to when the journal did not mandate data sharing (open at preprint: 20.2%, open at publication: 22.3%).

CONCLUSION

Requiring that authors submit a data availability statement is a good first step, but is insufficient to ensure data availability. Strict editorial policies that mandate data sharing (where appropriate) as a condition of publication appear to be effective in making research data available. We would strongly encourage all journal editors to examine whether their data availability policies are sufficiently stringent and consistently enforced.

From Rare Copy Number Variants to Biological Processes in ADHD

OBJECTIVE

Attention deficit hyperactivity disorder (ADHD) is a highly heritable psychiatric disorder. The objective of this study was to define ADHD-associated candidate genes and their associated molecular modules and biological themes, based on the analysis of rare genetic variants.

METHODS

The authors combined data from 11 published copy number variation studies in 6,176 individuals with ADHD and 25,026 control subjects and prioritized genes by applying an integrative strategy based on criteria including recurrence in individuals with ADHD, absence in control subjects, complete coverage in copy number gains, and presence in the minimal region common to overlapping copy number variants (CNVs), as well as on protein-protein interactions and information from cross-species genotype-phenotype annotation.

RESULTS

The authors localized 2,241 eligible genes in the 1,532 reported CNVs, of which they classified 432 as high-priority ADHD candidate genes. The high-priority ADHD candidate genes were significantly coexpressed in the brain. A network of 66 genes was supported by ADHD-relevant phenotypes in the cross-species database. Four significantly interconnected protein modules were found among the high-priority ADHD genes. A total of 26 genes were observed across all applied bioinformatic methods. Lookup in the latest genome-wide association study for ADHD showed that among those 26 genes, POLR3C and RBFOX1 were also supported by common genetic variants.

CONCLUSIONS

Integration of a stringent filtering procedure in CNV studies with suitable bioinformatics approaches can identify ADHD candidate genes at increased levels of credibility. The authors' analytic pipeline provides additional insight into the molecular mechanisms underlying ADHD and allows prioritization of genes for functional validation in validated model organisms.