NCAM1-TTC12-ANKK1-DRD2 gene cluster and the clinical and genetic heterogeneity of adults with ADHD

A Local Genetic Correlation Analysis Provides Biological Insights Into the Shared Genetic Architecture of Psychiatric and Substance Use Phenotypes

BACKGROUND

Global genetic correlation analysis has provided valuable insight into the shared genetic basis between psychiatric and substance use disorders. However, little is known about which regions disproportionately contribute to the global correlation.

METHODS

We used Local Analysis of [co]Variant Annotation to calculate bivariate local genetic correlations across 2495 approximately equal-sized, semi-independent genomic regions for 20 psychiatric and substance use phenotypes. We performed a transcriptome-wide association study using expression weights from the prefrontal cortex to identify risk genes for each phenotype, followed by probabilistic fine-mapping to prioritize credible causal genes within each bivariate locus.

RESULTS

We detected 80 significant (p < 2.08 × 10-6) bivariate local genetic correlations across 61 loci. The expression effect directions for risk genes within each bivariate locus were largely consistent with the local correlation coefficients, suggesting that genetically regulated gene expression may be used in the functional interpretation of local genetic correlations. Probabilistic fine-mapping identified several genes that may drive pleiotropic mechanisms for genetically correlated phenotypes. For example, we confirmed a local genetic correlation between schizophrenia and smoking behavior at 15q25 and prioritized PSMA4 as the most credible gene candidate underlying both phenotypes.

CONCLUSIONS

Our study reveals previously unreported local bivariate genetic correlations between psychiatric and substance use phenotypes, which we fine-mapped to identify shared credible causal genes underlying genetically correlated phenotypes.

An integrated framework for local genetic correlation analysis

Genetic correlation (r_g) analysis is used to identify phenotypes that may have a shared genetic basis. Traditionally, r_g is studied globally, considering only the average of the shared signal across the genome, although this approach may fail when the r_g is confined to particular genomic regions or in opposing directions at different loci. Current tools for local r_g analysis are restricted to analysis of two phenotypes. Here we introduce LAVA, an integrated framework for local r_g analysis that, in addition to testing the standard bivariate local r_gs between two phenotypes, can evaluate local heritabilities and analyze conditional genetic relations between several phenotypes using partial correlation and multiple regression. Applied to 25 behavioral and health phenotypes, we show considerable heterogeneity in the bivariate local r_gs across the genome, which is often masked by the global r_g patterns, and demonstrate how our conditional approaches can elucidate more complex, multivariate genetic relations.

Plasma Cell-Free DNA Methylomics of Bipolar Disorder With and Without Rapid Cycling

Rapid cycling (RC) burdens bipolar disorder (BD) patients further by causing more severe disability and increased suicidality. Because diagnosing RC can be challenging, RC patients are at risk of rapid decline due to delayed suitable treatment. Here, we aimed to identify the differences in the circulating cell-free DNA (cfDNA) methylome between BD patients with and without RC. The cfDNA methylome could potentially be developed as a diagnostic test for BD RC. We extracted cfDNA from plasma samples of BD1 patients (46 RC and 47 non-RC). cfDNA methylation levels were measured by 850K Infinium MethylationEPIC array. Principal component analysis (PCA) was conducted to assess global differences in methylome. cfDNA methylation levels were compared between RC groups using a linear model adjusted for age and sex. PCA suggested differences in methylation profiles between RC groups (p = 0.039) although no significant differentially methylated probes (DMPs; q > 0.15) were found. The top four CpG sites which differed between groups at p < 1E-05 were located in CGGPB1, PEX10, NR0B2, and TP53I11. Gene set enrichment analysis (GSEA) on top DMPs (p < 0.05) showed significant enrichment of gene sets related to nervous system tissues, such as neurons, synapse, and glutamate neurotransmission. Other top notable gene sets were related to parathyroid regulation and calcium signaling. To conclude, our study demonstrated the feasibility of utilizing a microarray method to identify circulating cfDNA methylation sites associated with BD RC and found the top differentially methylated CpG sites were mostly related to the nervous system and the parathyroid.

Novel characterization of the multivariate genetic architecture of internalizing psychopathology and alcohol use

Genetic correlations suggest that the genetic relationship of alcohol use with internalizing psychopathology depends on the measure of alcohol use. Problematic alcohol use (PAU) is positively genetically correlated with internalizing psychopathology, whereas alcohol consumption ranges from not significantly correlated to moderately negatively correlated with internalizing psychopathology. To explore these different genetic relationships of internalizing psychopathology with alcohol use, we performed a multivariate genome-wide association study of four correlated factors (internalizing psychopathology, PAU, quantity of alcohol consumption, and frequency of alcohol consumption) and then assessed genome-wide and local genetic covariance between these factors. We identified 14 significant regions of local, largely positive, genetic covariance between PAU and internalizing psychopathology and 12 regions of significant local genetic covariance (including both positive and negative genetic covariance) between consumption factors and internalizing psychopathology. Partitioned genetic covariance among functional annotations suggested that brain tissues contribute significantly to positive genetic covariance between internalizing psychopathology and PAU but not to the genetic covariance between internalizing psychopathology and quantity or frequency of alcohol consumption. We hypothesize that genome-wide genetic correlations between alcohol use and psychiatric traits may not capture the more complex shared or divergent genetic architectures at the locus or tissue specific level. This study highlights the complexity of genetic architectures of alcohol use and internalizing psychopathology, and the differing shared genetics of internalizing disorders with PAU compared to consumption.

Synergistic effects between ADORA2A and DRD2 genes on anxiety disorders in children with ADHD

The prevalence of anxiety disorders in patients with Attention Deficit/Hyperactivity Disorder (ADHD) is around 15-40%, three times higher than in the general population. The dopaminergic system, classically associated with ADHD, interacts directly with the adenosinergic system through adenosine A_2A receptors (A_2A) and dopamine D₂ receptors (D₂) forming A_2A-D₂ heterodimers. Both dopaminergic and adenosinergic systems are implicated in anxiety disorders. Therefore, the aims of this study were: a) to investigate the main effects of ADORA2A and DRD2 gene variants on anxiety disorders in an ADHD sample of children and adolescents; b) to test potential synergism between ADORA2A and DRD2 genes on the same outcome; c) to explore ADORA2A variants functionality using an in silico approach. The sample consists of 478 children and adolescents with ADHD and their parents, totalizing 1.239 individuals. An association between the ADORA2A rs2298383 TT genotype with the presence of anxiety disorders (P = .004) and an interaction between ADORA2A-DRD2 risk haplotypes with the same outcome (P = .005) was detected. The in silico analyses showed that rs2298383 has the highest score for regulatory function among all variants in the ADORA2A gene described up to date. Altogether, the present findings suggested that the ADORA2A gene and the interaction of ADORA2A and DRD2 genes may play a role in anxiety disorders in children and adolescents with ADHD.

Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions

Major depression is a debilitating psychiatric illness that is typically associated with low mood and anhedonia. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximize sample size, we meta-analyzed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 genesets associated with depression, including both genes and gene pathways associated with synaptic structure and neurotransmission. An enrichment analysis provided further evidence of the importance of prefrontal brain regions. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant after multiple testing correction. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding etiology and developing new treatment approaches.

Integrative analysis of genome-wide association study and chromosomal enhancer maps identified brain region related pathways associated with ADHD

Attention deficit/hyperactivity disorder (ADHD) is among the most common childhood onset psychiatric behavioral disorders, and the pathogenesis of ADHD is still unclear. Utilizing the latest genome wide association studies (GWAS) data and enhancer map, we explored the brain region related biological pathways associated with ADHD. The GWAS summary data of ADHD was driven from a published study, involving 20,183 ADHD cases and 35,191 healthy controls. The brain-related enhancer map was collected from ENCODE and Roadmap Epigenomics (ENCODE + Roadmap) including 489,581 enhancers. Firstly, the chromosomal enhancer maps of four brain regions were aligned with the ADHD GWAS summary data in order to obtain enhancer SNPs. Then the significant enhancers SNPs were subjected to the gene set enrichment analysis (GSEA) for identifying ADHD associated gene sets. A total of 866 pathways and 4 brain tissues were analyzed in this study. We detected several candidate genes for ADHD, such as AHI1, ALG2 and DNM1. We also detected several candidate biological pathways associated with ADHD, such as Reactome SEMA4D in semaphorin signaling and Reactome NCAM1 interactions. Our findings may provide a novel insight into the complex genetic mechanism of ADHD.

Further replication of the synergistic interaction between LPHN3 and the NTAD gene cluster on ADHD and its clinical course throughout adulthood

Attention-Deficit/Hyperactivity Disorder (ADHD) is a common and highly heritable neuropsychiatric disorder. Despite the high heritability, the unraveling of specific genetic factors related to ADHD is hampered by its considerable genetic complexity. Recent evidence suggests that gene-gene interactions can explain part of this complexity. We examined the impact of strongly supported interaction effects between the LPHN3 gene and the NTAD gene cluster (NCAM1-TTC12-ANKK1-DRD2) in a 7-year follow-up of a clinical sample of adults with ADHD, addressing associations with susceptibility, symptomatology and stability of diagnosis. The sample comprises 548 adults with ADHD and 643 controls. Entropy-based analysis indicated a potential interaction between the LPHN3-rs6551665 and TTC12-rs2303380 SNPs influencing ADHD symptom counts. Further analyses revealed significant interaction effects on ADHD total symptoms (p=0.002), and with hyperactivity/impulsivity symptom counts (p=0.005). In the group composed by predominantly hyperactive/impulsive and combined presentation, the presence of LPHN3-rs6551665 G allele was related to increased ADHD risk only in individuals carrying the TTC12-rs2303380 AA genotype (p=0.026). Also, the same allelic constellation is involved in maintenance of ADHD in a predominantly hyperactive/impulsive or combined presentation after a 7-year follow-up (p=0.008). These observations reinforce and replicate previous evidence suggesting that an interaction effect between the LPHN3 gene and the NTAD cluster may have a role in the genetic substrate associated to ADHD also in adults. Moreover, it is possible that the interactions between LPHN3 and NTAD are specific factors contributing to the development of an ADHD phenotype with increased hyperactivity/impulsivity that is maintained throughout adulthood.

Attention-deficit hyperactivity disorder in adults: A systematic review and meta-analysis of genetic, pharmacogenetic and biochemical studies

The adult form of attention-deficit/hyperactivity disorder has a prevalence of up to 5% and is the most severe long-term outcome of this common disorder. Family studies in clinical samples as well as twin studies suggest a familial liability and consequently different genes were investigated in association studies. Pharmacotherapy with methylphenidate (MPH) seems to be the first-line treatment of choice in adults with attention-deficit hyperactive disorder (ADHD) and some studies were conducted on the genes influencing the response to this drug. Finally some peripheral biomarkers were identified in ADHD adult patients. We believe this work is the first systematic review and meta-analysis of candidate gene association studies, pharmacogenetic and biochemical (metabolomics) studies performed in adults with ADHD to identify potential genetic, predictive and peripheral markers linked specifically to ADHD in adults. After screening 5129 records, we selected 87 studies of which 61 were available for candidate gene association studies, 5 for pharmacogenetics and 21 for biochemical studies. Of these, 15 genetic, 2 pharmacogenetic and 6 biochemical studies were included in the meta-analyses. We obtained an association between adult ADHD and the gene BAIAP2 (brain-specific angiogenesis inhibitor 1-associated protein 2), even after Bonferroni correction, with any heterogeneity in effect size and no publication bias. If we did not apply the Bonferroni correction, a trend was found for the carriers allele 9R of dopamine transporter SLC6A3 40 bp variable tandem repeat polymorphism (VNTR) and for 6/6 homozygotes of SLC6A3 30 bp VNTR. Negative results were obtained for the 9-6 haplotype, the dopamine receptor DRD4 48 bp VNTR, and the enzyme COMT SNP rs4680. Concerning pharmacogenetic studies, no association was found for the SLC6A3 40 bp and response to MPH with only two studies selected. For the metabolomics studies, no differences between ADHD adults and controls were found for salivary cortisol, whereas lower serum docosahexaenoic acid (DHA) levels were found in ADHD adults. This last association was significant even after Bonferroni correction and in absence of heterogeneity. Other polyunsaturated fatty acids (PUFAs) such as AA (arachidonic acid), EPA (eicosapentaenoic acid) and DyLA (dihomogammalinolenic acid) levels were not different between patients and controls. No publication biases were observed for these markers. Genes linked to dopaminergic, serotoninergic and noradrenergic signaling, metabolism (DBH, TPH1, TPH2, DDC, MAOA, MAOB, BCHE and TH), neurodevelopment (BDNF and others), the SNARE system and other forty genes/proteins related to different pathways were not meta-analyzed due to insufficient data. In conclusion, we found that there were not enough genetic, pharmacogenetic and biochemical studies of ADHD in adults and that more investigations are needed. Moreover we confirmed a significant role of BAIAP2 and DHA in the etiology of ADHD exclusively in adults. Future research should be focused on the replication of these findings and to assess their specificity for ADHD.