Multi-trait analysis for genome-wide association study of five psychiatric disorders

Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Cortico-striatal differences in the epigenome in attention-deficit/ hyperactivity disorder

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.

Unsupervised deep representation learning enables phenotype discovery for genetic association studies of brain imaging

Understanding the genetic architecture of brain structure is challenging, partly due to difficulties in designing robust, non-biased descriptors of brain morphology. Until recently, brain measures for genome-wide association studies (GWAS) consisted of traditionally expert-defined or software-derived image-derived phenotypes (IDPs) that are often based on theoretical preconceptions or computed from limited amounts of data. Here, we present an approach to derive brain imaging phenotypes using unsupervised deep representation learning. We train a 3-D convolutional autoencoder model with reconstruction loss on 6130 UK Biobank (UKBB) participants' T1 or T2-FLAIR (T2) brain MRIs to create a 128-dimensional representation known as Unsupervised Deep learning derived Imaging Phenotypes (UDIPs). GWAS of these UDIPs in held-out UKBB subjects (n = 22,880 discovery and n = 12,359/11,265 replication cohorts for T1/T2) identified 9457 significant SNPs organized into 97 independent genetic loci of which 60 loci were replicated. Twenty-six loci were not reported in earlier T1 and T2 IDP-based UK Biobank GWAS. We developed a perturbation-based decoder interpretation approach to show that these loci are associated with UDIPs mapped to multiple relevant brain regions. Our results established unsupervised deep learning can derive robust, unbiased, heritable, and interpretable brain imaging phenotypes.

Validation of Enhancer Regions in Primary Human Neural Progenitor Cells using Capture STARR-seq

Genome-wide association studies (GWAS) and expression analyses implicate noncoding regulatory regions as harboring risk factors for psychiatric disease, but functional characterization of these regions remains limited. We performed capture STARR-sequencing of over 78,000 candidate regions to identify active enhancers in primary human neural progenitor cells (phNPCs). We selected candidate regions by integrating data from NPCs, prefrontal cortex, developmental timepoints, and GWAS. Over 8,000 regions demonstrated enhancer activity in the phNPCs, and we linked these regions to over 2,200 predicted target genes. These genes are involved in neuronal and psychiatric disease-associated pathways, including dopaminergic synapse, axon guidance, and schizophrenia. We functionally validated a subset of these enhancers using mutation STARR-sequencing and CRISPR deletions, demonstrating the effects of genetic variation on enhancer activity and enhancer deletion on gene expression. Overall, we identified thousands of highly active enhancers and functionally validated a subset of these enhancers, improving our understanding of regulatory networks underlying brain function and disease.

Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders

We characterized the genetic architecture of the attention-deficit hyperactivity disorder-substance use disorder (ADHD-SUD) relationship by investigating genetic correlation, causality, pleiotropy, and common polygenic risk. Summary statistics from genome-wide association studies (GWAS) were used to investigate ADHD (Neff = 51,568), cannabis use disorder (CanUD, Neff = 161,053), opioid use disorder (OUD, Neff = 57,120), problematic alcohol use (PAU, Neff = 502,272), and problematic tobacco use (PTU, Neff = 97,836). ADHD, CanUD, and OUD GWAS meta-analyses included cohorts with case definitions based on different diagnostic criteria. PAU GWAS combined information related to alcohol use disorder, alcohol dependence, and the items related to alcohol problematic consequences assessed by the alcohol use disorders identification test. PTU GWAS was generated a multi-trait analysis including information regarding Fagerström Test for Nicotine Dependence and cigarettes per day. Linkage disequilibrium score regression analyses indicated positive genetic correlation with CanUD, OUD, PAU, and PTU. Genomic structural equation modeling showed that these genetic correlations were related to two latent factors: one including ADHD, CanUD, and PTU and the other with OUD and PAU. The evidence of a causal effect of PAU and PTU on ADHD was stronger than the reverse in the two-sample Mendelian randomization analysis. Conversely, similar strength of evidence was found between ADHD and CanUD. CADM2 rs62250713 was a pleiotropic SNP between ADHD and all SUDs. We found seven, one, and twenty-eight pleiotropic variants between ADHD and CanUD, PAU, and PTU, respectively. Finally, OUD, CanUD, and PAU PRS were associated with increased odds of ADHD. Our findings demonstrated the contribution of multiple pleiotropic mechanisms to the comorbidity between ADHD and SUDs.

Cerebrospinal fluid proteomic signatures are associated with symptom severity of first-episode psychosis

Apart from their diagnostic, monitoring, or prognostic utility in clinical settings, molecular biomarkers may be instrumental in understanding the pathophysiology of psychiatric disorders, including schizophrenia. Using untargeted metabolomics, we recently identified eight cerebrospinal fluid (CSF) metabolites unique to first-episode psychosis (FEP) subjects compared to healthy controls (HC). In this study, we sought to investigate the CSF proteomic signatures associated with FEP. We employed 16-plex tandem mass tag (TMT) mass spectrometry (MS) to examine the relative protein abundance in CSF samples of 15 individuals diagnosed with FEP and 15 age-and-sex-matched healthy controls (HC). Multiple linear regression model (MLRM) identified 16 differentially abundant CSF proteins between FEP and HC at p < 0.01. Among them, the two most significant CSF proteins were collagen alpha-2 (IV) chain (COL4A2: standard mean difference [SMD] = -1.12, p = 1.64 × 10-4) and neuron-derived neurotrophic factor (NDNF: SMD = -1.03, p = 4.52 × 10-4) both of which were down-regulated in FEP subjects compared to HC. We also identified several potential CSF proteins associated with the pathophysiology and the symptom profile and severity in FEP subjects, including COL4A2, NDNF, hornerin (HRNR), contactin-6 (CNTN6), voltage-dependent calcium channel subunit alpha-2/delta-3 (CACNA2D3), tropomyosin alpha-3 chain (TPM3 and TPM4). Moreover, several protein signatures were associated with cognitive performance. Although the results need replication, our exploratory study suggests that CSF protein signatures can be used to increase the understanding of the pathophysiology of psychosis.

The role of thyroid function in borderline personality disorder and schizophrenia: a Mendelian Randomisation study

BACKGROUND

Genome-wide association studies have reported a genetic overlap between borderline personality disorder (BPD) and schizophrenia (SCZ). Epidemiologically, the direction and causality of the association between thyroid function and risk of BPD and SCZ are unclear. We aim to test whether genetically predicted variations in TSH and FT4 levels or hypothyroidism are associated with the risk of BPD and SCZ.

METHODS

We employed Mendelian Randomisation (MR) analyses using genetic instruments associated with TSH and FT4 levels as well as hypothyroidism to examine the effects of genetically predicted thyroid function on BPD and SCZ risk. Bidirectional MR analyses were employed to investigate a potential reverse causal association.

RESULTS

Genetically predicted higher FT4 was not associated with the risk of BPD (OR: 1.18; P = 0.60, IVW) or the risk of SCZ (OR: 0.93; P = 0.19, IVW). Genetically predicted higher TSH was not associated with the risk of BPD (OR: 1.11; P = 0.51, IVW) or SCZ (OR: 0.98, P = 0.55, IVW). Genetically predicted hypothyroidism was not associated with BPD or SCZ. We found no evidence for a reverse causal effect between BPD or SCZ on thyroid function.

CONCLUSIONS

We report evidence for a null association between genetically predicted FT4, TSH or hypothyroidism with BPD or SCZ risk. There was no evidence for reverse causality.

Identifying risk loci for obsessive-compulsive disorder and shared genetic component with schizophrenia: A large-scale multi-trait association analysis with summary statistics

Due to limited samples, no genetic loci have been identified for obsessive-compulsive disorder (OCD) in genome-wide association studies. Additionally, although co-morbidities between OCD and schizophrenia (SCZ) were observed, their common genetic etiology was not completely known. Here, we conducted a comprehensive investigation regarding the genetic architecture of OCD and the common genetic foundation shared by OCD and SCZ using summary statistics data (2688 cases and 7037 controls for OCD; 53,386 cases and 77,258 controls for SCZ). We discovered significant genetic correlation between OCD and SCZ (r̂g=0.296, P = 2.82 × 10-11). We then performed two multi-trait association analyses to detect OCD-associated loci and colocalization analysis to detect causal variants. Parallel gene-level analyses were also implemented. We identified 323 OCD-relevant variants located within 12 loci, with four loci shared the same causal variants between OCD and SCZ. Further, the gene-level analyses discovered 8 OCD-associated genes. Finally, multiple functional analyses at both SNP and gene levels showed that these genetic association signals had significant enrichments in the regions of left ventricle and anterior cingulate cortex, and suggested an important role of pathways involving regulation of telomere maintenance, histone phosphorylation, and GnRH secretion. Overall, this study identified new genetic loci for OCD and provided substantial evidence supporting common genetic foundation underlying OCD and SCZ. The findings advanced our understanding of genetic architecture and pathophysiology of OCD as well as shedding light on shared genetic etiology of the two disorders.

Dynamic subtype- and context-specific subcellular RNA regulation in growth cones of developing neurons of the cerebral cortex

Molecular mechanisms that cells employ to compartmentalize function via localization of function-specific RNA and translation are only partially elucidated. We investigate long-range projection neurons of the cerebral cortex as highly polarized exemplars to elucidate dynamic regulation of RNA localization, stability, and translation within growth cones (GCs), leading tips of growing axons. Comparison of GC-localized transcriptomes between two distinct subtypes of projection neurons- interhemispheric-callosal and corticothalamic- across developmental stages identifies both distinct and shared subcellular machinery, and intriguingly highlights enrichment of genes associated with neurodevelopmental and neuropsychiatric disorders. Developmental context-specific components of GC-localized transcriptomes identify known and novel potential regulators of distinct phases of circuit formation: long-distance growth, target area innervation, and synapse formation. Further, we investigate mechanisms by which transcripts are enriched and dynamically regulated in GCs, and identify GC-enriched motifs in 3' untranslated regions. As one example, we identify cytoplasmic adenylation element binding protein 4 (CPEB4), an RNA binding protein regulating localization and translation of mRNAs encoding molecular machinery important for axonal branching and complexity. We also identify RNA binding motif single stranded interacting protein 1 (RBMS1) as a dynamically expressed regulator of RNA stabilization that enables successful callosal circuit formation. Subtly aberrant associative and integrative cortical circuitry can profoundly affect cortical function, often causing neurodevelopmental and neuropsychiatric disorders. Elucidation of context-specific subcellular RNA regulation for GC- and soma-localized molecular controls over precise circuit development, maintenance, and function offers generalizable insights for other polarized cells, and might contribute substantially to understanding neurodevelopmental and behavioral-cognitive disorders and toward targeted therapeutics.

Joint analysis of proteome, transcriptome, and multi-trait analysis to identify novel Parkinson's disease risk genes

Genome-wide association studies (GWAS) have identified multiple risk variants for Parkinson's disease (PD). Nevertheless, how the risk variants confer the risk of PD remains largely unknown. We conducted a proteome-wide association study (PWAS) and summary-data-based mendelian randomization (SMR) analysis by integrating PD GWAS with proteome and protein quantitative trait loci (pQTL) data from human brain, plasma and CSF. We also performed a large transcriptome-wide association study (TWAS) and Fine-mapping of causal gene sets (FOCUS), leveraging joint-tissue imputation (JTI) prediction models of 22 tissues to identify and prioritize putatively causal genes. We further conducted PWAS, SMR, TWAS, and FOCUS using a multi-trait analysis of GWAS (MTAG) to identify additional PD risk genes to boost statistical power. In this large-scale study, we identified 16 genes whose genetically regulated protein abundance levels were associated with Parkinson's disease risk. We undertook a large-scale analysis of PD and correlated traits, through TWAS and FOCUS studies, and discovered 26 casual genes related to PD that had not been reported in previous TWAS. 5 genes (CD38, GPNMB, RAB29, TMEM175, TTC19) showed significant associations with PD at both the proteome-wide and transcriptome-wide levels. Our study provides new insights into the etiology and underlying genetic architecture of PD.

Replication of previous autism-GWAS hits suggests the association between NAA1, SORCS3, and GSDME and autism in the Han Chinese population

Background

Autism is a severe neurodevelopmental disorder characterized by social interaction deficits, impairments in communication, and restricted and repetitive stereotyped behavior and activities. Family and twin studies suggested an essential role of genetic factors in the etiology of autism spectrum disorder (ASD). Also, other studies found SORCS3 and GSDME (DFNA5) might be involved in brain development and susceptible to ASD.

Methods

In this study, 17 genome-wide significant SNPs reported in previous ASD genome-wide association studies (GWAS) and 7 SNPs in strong linkage disequilibrium with known ASD GWAS hits were selected to investigate the association between these SNPs and autism in the Han Chinese population. Then, 10 tagSNPs in SORCS3 and 11 tagSNPs in GSDME were selected to analyze the association between these SNPs and autism. The selected 24 SNPs and tagSNPs were genotyped using the Agena MassARRAY SNP genotyping assay in 757 Han Chinese autism trios.

Results

Rs1484144 in NAA11 was significantly associated with autism; significance remained after the Bonferroni correction (P < 0.0022). Also, rs79879286, rs12154597, and rs12540919 near GSDME, as well as rs9787523 and rs3750261 in SORCS3, were nominally associated with autism.

Conclusion

Our study suggests that rs1484144 in NAA11 is a significant SNP for autism in the Han Chinese population, while SORCS3 and GSDME might be the susceptibility genes for autism in this population.

Alpha 2-Macroglobulin Polymorphisms and Susceptibility to Alzheimer's Disease: A Comprehensive Meta-Analysis Based on 62 Studies

Background

The relationship between alpha 2-macroglobulin (A2M) gene and Alzheimer's disease (AD) has been widely studied across populations; however, the results are inconsistent.

Objective

This study aimed to evaluate the association of A2M gene with AD by the application of meta-analysis.

Methods

Relevant studies were identified by comprehensive searches. The quality of each study was assessed using the Newcastle-Ottawa Scale. Allele and genotype frequencies were extracted from each of the included studies. Odds ratio (OR) with corresponding 95% confidence intervals (CI) was calculated using a random-effects or fixed-effects model. The Cochran Q statistic and I2 metric was used to evaluate heterogeneity, and Egger's test and Funnel plot were used to assess publication bias.

Results

A total of 62 studies were identified and included in the current meta-analysis. The G allele of rs226380 reduced AD risk (OR: 0.64, 95% CI: 0.47-0.87, pFDR = 0.012), but carrier with the TT genotype was more likely to develop AD in Asian populations (OR: 1.56, 95% CI: 1.12-2.19, pFDR = 0.0135). The V allele of the A2M-I/V (rs669) increased susceptibility to AD in female population (OR, 95% CI: 2.15, 1.38-3.35, pFDR = 0.0024); however, the II genotype could be a protective factor in these populations (OR, 95% CI: 0.43, 0.26-0.73, pFDR = 0.003). Sensitivity analyses confirmed the reliability of the original results.

Conclusions

Existing evidence indicate that A2M single nucleotide polymorphisms (SNPs) may be associated with AD risk in sub-populations. Future studies with larger sample sizes will be necessary to confirm the results.

Causal associations between COVID-19 and childhood mental disorders

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can invade both the peripheral and central nervous systems and impact the function of the brain. Therefore, it is necessary to evaluate the mutual influences between COVID-19 outcomes and childhood mental disorders.

METHODS

We examined genetic correlations and potential causalities between three childhood mental disorders and three COVID-19 phenotypes by genetically proxied analyses. The three mental disorders included attention-deficit/hyperactivity disorder (ADHD, N = 292,548), Tourette's syndrome (TS, N = 14,307), and autism spectrum disorder (ASD, N = 46,350). The three COVID-19 traits included SARS-CoV-2 infection (N = 2,597,856), hospitalized COVID-19 (N = 2,095,324), and critical COVID-19 (N = 1,086,211). Literature-based analysis was used to build gene-based pathways connecting ADHD and COVID-19.

RESULTS

ADHD was positively correlated with the three COVID-19 outcomes (Rg: 0.22 ~ 0.30). Our Mendelian randomization (MR) analyses found that ADHD confers a causal effect on hospitalized COVID-19 (odds ratio (OR): 1.36, 95% confidence interval (CI): 1.10-1.69). TS confers a causal effect on critical COVID-19 (OR: 1.14, 95% CI: 1.04-1.25). Genetic liability to the COVID-19 outcomes may not increase the risk for the childhood mental disorders. Pathway analysis identified several immunity-related genes that may link ADHD to COVID-19, including CRP, OXT, IL6, PON1, AR, TNFSF12, and IL10.

CONCLUSIONS

Our study suggests that both ADHD and TS may augment the severity of COVID-19 through immunity-related pathways. However, our results did not support a causal role of COVID-19 in the risk for the childhood mental disorders.

Glycosyltransferase 8 domain-containing protein 1 (GLT8D1) is a UDP-dependent galactosyltransferase

Glycosyltransferases (GTs) are enzymes that catalyze the formation of glycosidic bonds and hundreds of GTs have been identified so far in humans. Glycosyltransferase 8 domain-containing protein 1 (GLT8D1) has been associated with central nervous system diseases and cancer. However, evidence on its enzymatic properties, including its substrates, has been scarcely described. In this paper, we have produced and purified recombinant secretory GLT8D1. The enzyme was found to be N-glycosylated. Differential scanning fluorimetry was employed to analyze the stabilization of GLT8D1 by Mn2+ and nucleotides, revealing UDP as the most stabilizing nucleotide scaffold. GLT8D1 displayed glycosyltransferase activity from UDP-galactose onto N-acetylgalactosamine but with a low efficiency. Modeling of the structure revealed similarities with other GT-A fold enzymes in CAZy family GT8 and glycosyltransferases in other families with galactosyl-, glucosyl-, and xylosyltransferase activities, each with retaining catalytic mechanisms. Our study provides novel structural and functional insights into the properties of GLT8D1 with implications in pathological processes.

miR-9-5p deficiency contributes to schizophrenia

MicroRNA-9-5p (miR-9-5p) is highly expressed in the brain and has been implicated in the risk of schizophrenia. We compared the expression levels of miR-9-5p in schizophrenia cases and healthy controls and evaluated whether regulatory targets of miR-9-5p are enriched in schizophrenia genome-wide risk genes. Literature-based analysis was conducted to construct molecular pathways connecting miR-9-5p and schizophrenia. We found that the expression levels of miR-9-5p were down-regulated in the peripheral blood of schizophrenia patients compared with those in healthy controls. miR-9-5p can regulate 24 out of the 1136 genome-wide risk genes of schizophrenia, which was higher than by chance (hypergeometric test P = 4.09E-06). The literature-based analysis showed that quantitative genetic changes driven by miR-9 exert more inhibitory (the IL1B, ABCB1, FGFR1 genes) than promoting (the INS gene) effects on schizophrenia, suggesting that miR-9 may protect against schizophrenia. Our results suggest that miR-9-5p deficiency may contribute to the development of schizophrenia.

Mapping the scientific research on bipolar disorder: A scientometric study of hotspots, bursts, and trends

Bipolar disorder (BD) is a severe psychiatric illness with an increasing prevalence worldwide. Although the pathological mechanism of and pharmacological interventions for BD have been extensively investigated in preclinical and clinical studies, a scientometric analysis of the developmental trends, interdisciplinary frontiers, and research hotspots in this field has not yet been conducted. Therefore, we performed a comprehensive scientometric review of 55,358 published studies on BD over the past two decades (2002-2021) to identify the most frequently used keywords and explore research hotspots and trajectories. The present findings revealed the main distribution, knowledge structure, topic evolution, and emerging topics of BD research. Analysing the risk factors, pathogenesis, key brain regions, comorbid conditions, and treatment strategies for BD contributed to understanding of the aetiology, progression, and treatment of this disorder. These findings provided substantial support for continued research in this area.

Internally tagged Vps10p-domain receptors reveal uptake of the neurotrophin BDNF

The Vps10p-domain (Vps10p-D) receptor family consists of Sortilin, SorLA, SorCS1, SorCS2, and SorCS3. They mediate internalization and intracellular sorting of specific cargo in various cell types, but underlying molecular determinants are incompletely understood. Deciphering the dynamic intracellular itineraries of Vps10p-D receptors is crucial for understanding their role in physiological and cytopathological processes. However, studying their spatial and temporal dynamics by live imaging has been challenging so far, as terminal tagging with fluorophores presumably impedes several of their protein interactions and thus functions. Here, we addressed the lack of appropriate tools and developed functional versions of all family members internally tagged in their ectodomains. We predict folding of the newly designed receptors by bioinformatics and show their exit from the endoplasmic reticulum. We examined their subcellular localization in immortalized cells and primary cultured neurons by immunocytochemistry and live imaging. This was, as far as known, identical to that of wt counterparts. We observed homodimerization of fluorophore-tagged SorCS2 by coimmunoprecipitation and fluorescence lifetime imaging, suggesting functional leucine-rich domains. Through ligand uptake experiments, live imaging and fluorescence lifetime imaging, we show for the first time that all Vps10p-D receptors interact with the neurotrophin brain-derived neurotrophic factor and mediate its uptake, indicating functionality of the Vps10p-Ds. In summary, we developed versions of all Vps10p-D receptors, with internal fluorophore tags that preserve several functions of the cytoplasmic and extracellular domains. These newly developed fluorophore-tagged receptors are likely to serve as powerful functional tools for accurate live studies of the individual cellular functions of Vps10p-D receptors.

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.

Peripheral S100B Protein Levels in Five Major Psychiatric Disorders: A Systematic Review

Five major psychiatric disorders: schizophrenia, major depressive disorder, bipolar disorder, autistic spectrum disorder, and attention-deficit/hyperactivity disorder, show a shared genetic background and probably share common pathobiological mechanisms. S100B is a calcium-binding protein widely studied in psychiatric disorders as a potential biomarker. Our systematic review aimed to compare studies on peripheral S100B levels in five major psychiatric disorders with shared genetic backgrounds to reveal whether S100B alterations are disease-specific. EMBASE, Web of Science, and PubMed databases were searched for relevant studies published until the end of July 2023. This study was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analysis Protocols (PRISMA) guidelines. Overall, 1215 publications were identified, of which 111 full-text articles were included in the systematic review. Study designs are very heterogeneous, performed mostly on small groups of participants at different stages of the disease (first-episode or chronic, drug-free or medicated, in the exacerbation of symptoms or in remission), and various clinical variables are analyzed. Published results are inconsistent; most reported elevated S100B levels across disorders included in the review. Alterations in S100B peripheral levels do not seem to be disease-specific.

ADuLT: An efficient and robust time-to-event GWAS

Proportional hazards models have been proposed to analyse time-to-event phenotypes in genome-wide association studies (GWAS). However, little is known about the ability of proportional hazards models to identify genetic associations under different generative models and when ascertainment is present. Here we propose the age-dependent liability threshold (ADuLT) model as an alternative to a Cox regression based GWAS, here represented by SPACox. We compare ADuLT, SPACox, and standard case-control GWAS in simulations under two generative models and with varying degrees of ascertainment as well as in the iPSYCH cohort. We find Cox regression GWAS to be underpowered when cases are strongly ascertained (cases are oversampled by a factor 5), regardless of the generative model used. ADuLT is robust to ascertainment in all simulated scenarios. Then, we analyse four psychiatric disorders in iPSYCH, ADHD, Autism, Depression, and Schizophrenia, with a strong case-ascertainment. Across these psychiatric disorders, ADuLT identifies 20 independent genome-wide significant associations, case-control GWAS finds 17, and SPACox finds 8, which is consistent with simulation results. As more genetic data are being linked to electronic health records, robust GWAS methods that can make use of age-of-onset information will help increase power in analyses for common health outcomes.

Dysfunction of cAMP-Protein Kinase A-Calcium Signaling Axis in Striatal Medium Spiny Neurons: A Role in Schizophrenia and Huntington's Disease Neuropathology

Background

Striatal medium spiny neurons (MSNs) are preferentially lost in Huntington's disease. Genomic studies also implicate a direct role for MSNs in schizophrenia, a psychiatric disorder known to involve cortical neuron dysfunction. It remains unknown whether the two diseases share similar MSN pathogenesis or if neuronal deficits can be attributed to cell type-dependent biological pathways. Transcription factor BCL11B, which is expressed by all MSNs and deep layer cortical neurons, was recently proposed to drive selective neurodegeneration in Huntington's disease and identified as a candidate risk gene in schizophrenia.

Methods

Using human stem cell-derived neurons lacking BCL11B as a model, we investigated cellular pathology in MSNs and cortical neurons in the context of these disorders. Integrative analyses between differentially expressed transcripts and published genome-wide association study datasets identified cell type-specific disease-related phenotypes.

Results

We uncover a role for BCL11B in calcium homeostasis in both neuronal types, while deficits in mitochondrial function and PKA (protein kinase A)-dependent calcium transients are detected only in MSNs. Moreover, BCL11B-deficient MSNs display abnormal responses to glutamate and fail to integrate dopaminergic and glutamatergic stimulation, a key feature of striatal neurons in vivo. Gene enrichment analysis reveals overrepresentation of disorder risk genes among BCL11B-regulated pathways, primarily relating to cAMP-PKA-calcium signaling axis and synaptic signaling.

Conclusions

Our study indicates that Huntington's disease and schizophrenia are likely to share neuronal pathophysiology where dysregulation of intracellular calcium homeostasis is found in both striatal and cortical neurons. In contrast, reduction in PKA signaling and abnormal dopamine/glutamate receptor signaling is largely specific to MSNs.

A multivariate genome-wide association study of psycho-cardiometabolic multimorbidity

Coronary artery disease (CAD), type 2 diabetes (T2D) and depression are among the leading causes of chronic morbidity and mortality worldwide. Epidemiological studies indicate a substantial degree of multimorbidity, which may be explained by shared genetic influences. However, research exploring the presence of pleiotropic variants and genes common to CAD, T2D and depression is lacking. The present study aimed to identify genetic variants with effects on cross-trait liability to psycho-cardiometabolic diseases. We used genomic structural equation modelling to perform a multivariate genome-wide association study of multimorbidity (Neffective = 562,507), using summary statistics from univariate genome-wide association studies for CAD, T2D and major depression. CAD was moderately genetically correlated with T2D (rg = 0.39, P = 2e-34) and weakly correlated with depression (rg = 0.13, P = 3e-6). Depression was weakly correlated with T2D (rg = 0.15, P = 4e-15). The latent multimorbidity factor explained the largest proportion of variance in T2D (45%), followed by CAD (35%) and depression (5%). We identified 11 independent SNPs associated with multimorbidity and 18 putative multimorbidity-associated genes. We observed enrichment in immune and inflammatory pathways. A greater polygenic risk score for multimorbidity in the UK Biobank (N = 306,734) was associated with the co-occurrence of CAD, T2D and depression (OR per standard deviation = 1.91, 95% CI = 1.74-2.10, relative to the healthy group), validating this latent multimorbidity factor. Mendelian randomization analyses suggested potentially causal effects of BMI, body fat percentage, LDL cholesterol, total cholesterol, fasting insulin, income, insomnia, and childhood maltreatment. These findings advance our understanding of multimorbidity suggesting common genetic pathways.

Psychiatric polygenic risk as a predictor of COVID-19 risk and severity: insight into the genetic overlap between schizophrenia and COVID-19

Despite the high contagion and mortality rates that have accompanied the coronavirus disease-19 (COVID-19) pandemic, the clinical presentation of the syndrome varies greatly from one individual to another. Potential host factors that accompany greater risk from COVID-19 have been sought and schizophrenia (SCZ) patients seem to present more severe COVID-19 than control counterparts, with certain gene expression similarities between psychiatric and COVID-19 patients reported. We used summary statistics from the last SCZ, bipolar disorder (BD), and depression (DEP) meta-analyses available on the Psychiatric Genomics Consortium webpage to calculate polygenic risk scores (PRSs) for a target sample of 11,977 COVID-19 cases and 5943 subjects with unknown COVID-19 status. Linkage disequilibrium score (LDSC) regression analysis was performed when positive associations were obtained from the PRS analysis. The SCZ PRS was a significant predictor in the case/control, symptomatic/asymptomatic, and hospitalization/no hospitalization analyses in the total and female samples; and of symptomatic/asymptomatic status in men. No significant associations were found for the BD or DEP PRS or in the LDSC regression analysis. SNP-based genetic risk for SCZ, but not for BD or DEP, may be associated with higher risk of SARS-CoV-2 infection and COVID-19 severity, especially among women; however, predictive accuracy barely exceeded chance level. We believe that the inclusion of sexual loci and rare variations in the analysis of genomic overlap between SCZ and COVID-19 will help to elucidate the genetic commonalities between these conditions.

Genome-wide DNA methylation association study of recent and cumulative marijuana use in middle aged adults

Marijuana is a widely used psychoactive substance in the US and medical and recreational legalization has risen over the past decade. Despite the growing number of individuals using marijuana, studies investigating the association between epigenetic factors and recent and cumulative marijuana use remain limited. We therefore investigated the association between recent and cumulative marijuana use and DNA methylation levels. Participants from the Coronary Artery Risk Development in Young Adults Study with whole blood collected at examination years (Y) 15 and Y20 were randomly selected to undergo DNA methylation profiling at both timepoints using the Illumina MethylationEPIC BeadChip. Recent use of marijuana was queried at each examination and used to estimate cumulative marijuana use from Y0 to Y15 and Y20. At Y15 (n = 1023), we observed 22 and 31 methylation markers associated (FDR P ≤ 0.05) with recent and cumulative marijuana use and 132 and 16 methylation markers at Y20 (n = 883), respectively. We replicated 8 previously reported methylation markers associated with marijuana use. We further identified 640 cis-meQTLs and 198 DMRs associated with recent and cumulative use at Y15 and Y20. Differentially methylated genes were statistically overrepresented in pathways relating to cellular proliferation, hormone signaling, and infections as well as schizophrenia, bipolar disorder, and substance-related disorders. We identified numerous methylation markers, pathways, and diseases associated with recent and cumulative marijuana use in middle-aged adults, providing additional insight into the association between marijuana use and the epigenome. These results provide novel insights into the role marijuana has on the epigenome and related health conditions.

Implications from proteomic studies investigating circadian rhythm disorder-regulated neurodegenerative disease pathology

Neurodegenerative diseases (NDs) affect 15% of the world's population and are becoming an increasingly common cause of morbidity and mortality worldwide. Circadian rhythm disorders (CRDs) have been reported to be involved in the pathogenic regulation of various neurologic diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, multiple sclerosis and amyotrophic lateral sclerosis. Proteomic technology is helpful to explore treatment targets for CRDs in patients with NDs. Here, we review the key differentially expressed (DE) proteins identified in previous proteomic studies investigating NDs, CRDs and associated models and the related pathways identified by enrichment analysis. Furthermore, we summarize the advantages and disadvantages of the above studies and propose new proteomic technologies for the precise study of circadian disorder-mediated regulation of ND pathology. This review provides a theoretical and technical reference for the precise study of circadian disorder-mediated regulation of ND pathology.

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Smoking behaviors and alcohol use disorder (AUD), both moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to co-occurring smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N = 318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 17 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1, and near DRD2. Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C, and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly co-occuring phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD.

Genes implicated by a methylome-wide schizophrenia study in neonatal blood show differential expression in adult brain samples

Schizophrenia is a disabling disorder involving genetic predisposition in combination with environmental influences that likely act via dynamic alterations of the epigenome and the transcriptome but its detailed pathophysiology is largely unknown. We performed cell-type specific methylome-wide association study of neonatal blood (N = 333) from individuals who later in life developed schizophrenia and controls. Suggestively significant associations (P < 1.0 × 10-6) were detected in all cell-types and in whole blood with methylome-wide significant associations in monocytes (P = 2.85 × 10-9-4.87 × 10-9), natural killer cells (P = 1.72 × 10-9-7.82 × 10-9) and B cells (P = 3.8 × 10-9). Validation of methylation findings in post-mortem brains (N = 596) from independent schizophrenia cases and controls showed significant enrichment of transcriptional differences (enrichment ratio = 1.98-3.23, P = 2.3 × 10-3-1.0 × 10-5), with specific highly significant differential expression for, for example, BDNF (t = -6.11, P = 1.90 × 10-9). In addition, expression difference in brain significantly predicted schizophrenia (multiple correlation = 0.15-0.22, P = 3.6 × 10-4-4.5 × 10-8). In summary, using a unique design combining pre-disease onset (neonatal) blood methylomic data and post-disease onset (post-mortem) brain transcriptional data, we have identified genes of likely functional relevance that are associated with schizophrenia susceptibility, rather than confounding disease associated artifacts. The identified loci may be of clinical value as a methylation-based biomarker for early detection of increased schizophrenia susceptibility.

Pleiotropic loci for cannabis use disorder severity in multi-ancestry high-risk populations

Cannabis use disorder (CUD) is common and has in part a genetic basis. The risk factors underlying its development likely involve multiple genes that are polygenetic and interact with each other and the environment to ultimately lead to the disorder. Co-morbidity and genetic correlations have been identified between CUD and other disorders and traits in select populations primarily of European descent. If two or more traits, such as CUD and another disorder, are affected by the same genetic locus, they are said to be pleiotropic. The present study aimed to identify specific pleiotropic loci for the severity level of CUD in three high-risk population cohorts: American Indians (AI), Mexican Americans (MA), and European Americans (EA). Using a previously developed computational method based on a machine learning technique, we leveraged the entire GWAS catalog and identified 114, 119, and 165 potentially pleiotropic variants for CUD severity in AI, MA, and EA respectively. Ten pleiotropic loci were shared between the cohorts although the exact variants from each cohort differed. While majority of the pleiotropic genes were distinct in each cohort, they converged on numerous enriched biological pathways. The gene ontology terms associated with the pleiotropic genes were predominately related to synaptic functions and neurodevelopment. Notable pathways included Wnt/β-catenin signaling, lipoprotein assembly, response to UV radiation, and components of the complement system. The pleiotropic genes were the most significantly differentially expressed in frontal cortex and coronary artery, up-regulated in adipose tissue, and down-regulated in testis, prostate, and ovary. They were significantly up-regulated in most brain tissues but were down-regulated in the cerebellum and hypothalamus. Our study is the first to attempt a large-scale pleiotropy detection scan for CUD severity. Our findings suggest that the different population cohorts may have distinct genetic factors for CUD, however they share pleiotropic genes from underlying pathways related to Alzheimer's disease, neuroplasticity, immune response, and reproductive endocrine systems.

Genome-wide association study of population-standardised cognitive performance phenotypes in a rural South African community

Cognitive function is an indicator for global physical and mental health, and cognitive impairment has been associated with poorer life outcomes and earlier mortality. A standard cognition test, adapted to a rural-dwelling African community, and the Oxford Cognition Screen-Plus were used to capture cognitive performance as five continuous traits (total cognition score, verbal episodic memory, executive function, language, and visuospatial ability) for 2,246 adults in this population of South Africans. A novel common variant, rs73485231, reached genome-wide significance for association with episodic memory using data for ~14 million markers imputed from the H3Africa genotyping array data. Window-based replication of previously implicated variants and regions of interest support the discovery of African-specific associated variants despite the small population size and low allele frequency. This African genome-wide association study identifies suggestive associations with general cognition and domain-specific cognitive pathways and lays the groundwork for further genomic studies on cognition in Africa.

Independent Associated SNPs at SORCS3 and Its Protein Interactors for Multiple Brain-Related Disorders and Traits

Sortilin-related vacuolar protein sorting 10 (VPS10) domain containing receptor 3 (SORCS3) is a neuron-specific transmembrane protein involved in the trafficking of proteins between intracellular vesicles and the plasma membrane. Genetic variation at SORCS3 is associated with multiple neuropsychiatric disorders and behavioural phenotypes. Here, we undertake a systematic search of published genome-wide association studies to identify and catalogue associations between SORCS3 and brain-related disorders and traits. We also generate a SORCS3 gene-set based on protein-protein interactions and investigate the contribution of this gene-set to the heritability of these phenotypes and its overlap with synaptic biology. Analysis of association signals at SORSC3 showed individual SNPs to be associated with multiple neuropsychiatric and neurodevelopmental brain-related disorders and traits that have an impact on the experience of feeling, emotion or mood or cognitive function, while multiple LD-independent SNPs were associated with the same phenotypes. Across these SNPs, alleles associated with the more favourable outcomes for each phenotype (e.g., decreased risk of neuropsychiatric illness) were associated with increased expression of the SORCS3 gene. The SORCS3 gene-set was enriched for heritability contributing to schizophrenia (SCZ), bipolar disorder (BPD), intelligence (IQ) and education attainment (EA). Eleven genes from the SORCS3 gene-set were associated with more than one of these phenotypes at the genome-wide level, with RBFOX1 associated with SCZ, IQ and EA. Functional annotation revealed that the SORCS3 gene-set is enriched for multiple ontologies related to the structure and function of synapses. Overall, we find many independent association signals at SORCS3 with brain-related disorders and traits, with the effect possibly mediated by reduced gene expression, resulting in a negative impact on synaptic function.

Impact on the Risk and Severity of Childhood Onset Schizophrenia of Schizophrenia Risk Genetic Variants at the DRD2 and ZNF804A Loci

The study explored whether schizophrenia risk alleles of the DRD2 rs2514218 and ZNF804A rs1344706 polymorphisms also influenced the risk and severity of childhood-onset schizophrenia (COS) and differentiated it from autism spectrum disorders (ASD). We compared 75 children with COS to 75 children with ASD, 150 patients with adult-onset schizophrenia and 150 healthy individuals. Frequency of the DRD2 T-allele, assumed to be protective against schizophrenia overall, was higher in COS compared to adult-onset schizophrenia and healthy controls. The risk allele A of ZNF804A was associated with greater severity of negative symptoms in COS. The latter result is consistent with the involvement of ZNF804A in the development of severe forms of schizophrenia. The findings regarding DRD2 suggest that the same genetic variants may play different roles in schizophrenia with childhood and adult onset. This warrants further research, since D2 receptor blockade is a general pharmacodynamic property of antipsychotics.

Autism Spectrum Disorder: A Review

IMPORTANCE

Autism spectrum disorder (ASD), characterized by deficits in social communication and the presence of restricted, repetitive behaviors or interests, is a neurodevelopmental disorder affecting approximately 2.3% children aged 8 years in the US and approximately 2.2% of adults. This review summarizes evidence on the diagnosis and treatment of ASD.

OBSERVATIONS

The estimated prevalence of ASD has been increasing in the US, from 1.1% in 2008 to 2.3% in 2018, which is likely associated with changes in diagnostic criteria, improved performance of screening and diagnostic tools, and increased public awareness. No biomarkers specific to the diagnosis of ASD have been identified. Common early signs and symptoms of ASD in a child's first 2 years of life include no response to name when called, no or limited use of gestures in communication, and lack of imaginative play. The criterion standard for the diagnosis of ASD is a comprehensive evaluation with a multidisciplinary team of clinicians and is based on semistructured direct observation of the child's behavior and semistructured caregiver interview focused on the individual's development and behaviors using standardized measures, such as the Autism Diagnostic Observation Schedule-Second Edition and the Autism Diagnostic Interview. These diagnostic measures have sensitivity of 91% and 80% and specificity of 76% and 72%, respectively. Compared with people without ASD, individuals with ASD have higher rates of depression (20% vs 7%), anxiety (11% vs 5%), sleep difficulties (13% vs 5%), and epilepsy (21% with co-occurring intellectual disability vs 0.8%). Intensive behavioral interventions, such as the Early Start Denver Model, are beneficial in children 5 years or younger for improvement in language, play, and social communication (small to medium effect size based on standardized mean difference). Pharmacotherapy is indicated for co-occurring psychiatric conditions, such as emotion dysregulation or attention-deficit/hyperactivity disorder. Risperidone and aripiprazole can improve irritability and aggression (standardized mean difference of 1.1, consistent with a large effect size) compared with placebo. Psychostimulants are effective for attention-deficit/hyperactivity disorder (standardized mean difference of 0.6, consistent with a moderate effect size) compared with placebo. These medications are associated with adverse effects including, most commonly, changes in appetite, weight, and sleep.

CONCLUSIONS AND RELEVANCE

ASD affects approximately 2.3% of children aged 8 years and approximately 2.2% of adults in the US. First-line therapy consists of behavioral interventions, while co-occurring psychiatric conditions, such as anxiety or aggression, may be treated with specific behavioral therapy or medication.

A four-lncRNA risk signature for prognostic prediction of osteosarcoma

Aim: Osteosarcoma is the most common primary malignant tumor of bone. However, our understanding of the prognostic indicators and the genetic mechanisms of the disease progression are still incomplete. The aim of this study was to identify a long noncoding RNA (lncRNA) risk signature for osteosarcoma survival prediction. Methods: RNA sequencing data and relevant clinical information of osteosarcoma patients were downloaded from the database of Therapeutically Applicable Research to Generate Effective Treatments (TARGET). We analyzed the differentially expressed lncRNAs between deceased and living patients by univariate and multivariate Cox regression analysis to identify a risk signature. We calculated a prognostic risk score for each sample according to this prognosis signature, and divided patients into high-risk and low-risk groups according to the median value of the risk score (0.975). Kaplan-Meier analysis and receiver operating characteristic (ROC) curve statistics were used to evaluate the performance of the signature. Next, we analyzed the signature's potential function through Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene-set enrichment analysis (GSEA). Lastly, qRT-PCR was used to validate the expression levels of the four lncRNAs in clinical samples. Results: Twenty-six differentially expressed lncRNAs were identified between deceased and living patients. Four of these lncRNAs (CTB-4E7.1, RP11-553A10.1, RP11-24N18.1, and PVRL3-AS1) were identified as independent prognostic factors, and a risk signature of these four lncRNAs for osteosarcoma survival prediction was constructed. Kaplan-Meier analysis showed that the five-year survival time in high-risk and low-risk groups was 33.1% and 82.5%, and the area under the curve (AUC) of the ROC was 0.784, which demonstrated that the prognostic signature was reliable and had the potential to predict the survival of patients with osteosarcoma. The expression level of the four lncRNAs in osteosarcoma tissues and cells was determined by qRT-PCR. Functional enrichment analysis suggested that the signature might be related to osteosarcoma through regulation of the MAPK signaling pathway, the PI3K-Akt signaling pathway, and the extracellular matrix and also provided new insights into the study of osteosarcoma, including the role of papillomavirus infection, olfactory receptor activity, and olfactory transduction in osteosarcoma. Conclusion: We constructed a novel lncRNA risk signature that served as an independent biomarker for predicting the prognosis of osteosarcoma patients.

Methylation in MAD1L1 is associated with the severity of suicide attempt and phenotypes of depression

Depression is a multifactorial disorder representing a significant public health burden. Previous studies have linked multiple single nucleotide polymorphisms with depressive phenotypes and suicidal behavior. MAD1L1 is a mitosis metaphase checkpoint protein that has been linked to depression in GWAS. Using a longitudinal EWAS approach in an adolescent cohort at two time points (n = 216 and n = 154), we identified differentially methylated sites that were associated with depression-related genetic variants in MAD1L1. Three methylation loci (cg02825527, cg18302629, and cg19624444) were consistently hypomethylated in the minor allele carriers, being cross-dependent on several SNPs. We further investigated whether DNA methylation at these CpGs is associated with depressive psychiatric phenotypes in independent cohorts. The first site (cg02825527) was hypomethylated in blood (exp(β) = 84.521, p value ~ 0.003) in participants with severe suicide attempts (n = 88). The same locus showed increased methylation in glial cells (exp(β) = 0.041, p value ~ 0.004) in the validation cohort, involving 29 depressed patients and 29 controls, and showed a trend for association with suicide (n = 40, p value ~ 0.089) and trend for association with depression treatment (n = 377, p value ~ 0.075). The second CpG (cg18302629) was significantly hypomethylated in depressed participants (exp(β) = 56.374, p value ~ 0.023) in glial cells, but did not show associations in the discovery cohorts. The last methylation site (cg19624444) was hypomethylated in the whole blood of severe suicide attempters; however, this association was at the borderline for statistical significance (p value ~ 0.061). This locus, however, showed a strong association with depression treatment in the validation cohort (exp(β) = 2.237, p value ~ 0.003) with 377 participants. The direction of associations between psychiatric phenotypes appeared to be different in the whole blood in comparison with brain samples for cg02825527 and cg19624444. The association analysis between methylation at cg18302629 and cg19624444 and MAD1L1 transcript levels in CD¹⁴⁺ cells shows a potential link between methylation at these CpGs and MAD1L1 expression. This study suggests evidence that methylation at MAD1L1 is important for psychiatric health as supported by several independent cohorts.

Shared genetics and bidirectional causal relationships between type 2 diabetes and attention-deficit/hyperactivity disorder

Background

Type 2 diabetes (T2D) is a chronic metabolic disorder with high comorbidity with mental disorders. The genetic links between attention-deficit/hyperactivity disorder (ADHD) and T2D have yet to be elucidated.

Aims

We aim to assess shared genetics and potential associations between ADHD and T2D.

Methods

We performed genetic correlation, two-sample Mendelian randomisation and polygenic overlap analyses between ADHD and T2D. The genome-wide association study (GWAS) summary results of T2D (80 154 cases and 853 816 controls), ADHD2019 (20 183 cases and 35 191 controls from the 2019 GWAS ADHD dataset) and ADHD2022 (38 691 cases and 275 986 controls from the 2022 GWAS ADHD dataset) were used for the analyses. The T2D dataset was obtained from the DIAGRAM Consortium. The ADHD datasets were obtained from the Psychiatric Genomics Consortium. We compared genome-wide association signals to reveal shared genetic variation between T2D and ADHD using the larger ADHD2022 dataset. Moreover, molecular pathways were constructed based on large-scale literature data to understand the connection between ADHD and T2D.

Results

T2D has positive genetic correlations with ADHD2019 (r_g=0.33) and ADHD2022 (r_g=0.31). Genetic liability to ADHD2019 was associated with an increased risk for T2D (odds ratio (OR): 1.30, p<0.001), while genetic liability to ADHD2022 had a suggestive causal effect on T2D (OR: 1.30, p=0.086). Genetic liability to T2D was associated with a higher risk for ADHD2019 (OR: 1.05, p=0.001) and ADHD2022 (OR: 1.03, p<0.001). The polygenic overlap analysis showed that most causal variants of T2D are shared with ADHD2022. T2D and ADHD2022 have three overlapping loci. Molecular pathway analysis suggests that ADHD and T2D could promote the risk of each other through inflammatory pathways.

Conclusions

Our study demonstrates substantial shared genetics and bidirectional causal associations between ADHD and T2D.

Genetic Relationships between Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, and Intelligence

INTRODUCTION

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) commonly co-occur; both traits exert an influence on intelligence scores. Genetic relationships between these three traits are far from being clear.

METHODS

The summary results of genome-wide association studies of ADHD (20,183 cases and 35,191 controls), ASD (18,381 cases and 27,969 controls), and intelligence (269,867 participants) were used for the analyses. Local genetic correlation analysis and polygenic overlap analysis were used to explore the shared genetic components between ADHD, ASD, and intelligence. Mendelian randomization (MR) analysis was used to examine the causal associations between ADHD, ASD, and intelligence. A cross-trait meta-analysis was performed to identify pleiotropic genetic variants across the three traits.

RESULTS

Our results showed that intelligence has a positive and negative genetic correlation with ASD and ADHD, respectively, including three hub genomic regions showing correlated genetic effects across the three traits. Polygenic overlap analysis indicated that all the risk variants contributing to ADHD are overlapped with half of those for intelligence, and the majority of the shared variants have opposite effect directions between them. The majority of risk variants (80%) of ASD are overlapped with almost all the risk variants of intelligence (97%). Notably, some ASD/intelligence overlapping variants displayed opposing effects on these two conditions. MR analysis showed that the genetic liability to higher intelligence was associated with an increased risk for ASD (OR = 1.12) and a decreased risk for ADHD (OR = 0.78). Cross-trait meta-analyses identified 170 pleiotropic genomic loci across the three traits, including 12 novel loci. Functional analyses of the novel genes support their potential involvement in neurodevelopment.

CONCLUSION

Our results suggest that ADHD is associated with inheriting a reduced set of low-intelligence alleles, whereas ASD results from incongruous effects from a mixture of high-intelligence and low-intelligence contributing alleles summed up with additional, ASD-specific risk variants not associated with intelligence.

Identification of a de novo mutation of the FOXG1 gene and comprehensive analysis for molecular factors in Chinese FOXG1-related encephalopathies

Background

FOXG1-related encephalopathy, also known as FOXG1 syndrome or FOXG1-related disorder, affects most aspects of development and causes microcephaly and brain malformations. This syndrome was previously considered to be the congenital variant of Rett syndrome. The abnormal function or expression of FOXG1, caused by intragenic mutations, microdeletions or microduplications, was considered to be crucial pathological factor for this disorder. Currently, most of the FOXG1-related encephalopathies have been identified in Europeans and North Americans, and relatively few Chinese cases were reported.

Methods

Array-Comparative Genomic Hybridization (Array-CGH) and whole-exome sequencing (WES) were carried out for the proband and her parent to detect pathogenic variants.

Results

A de novo nonsense mutation (c.385G>T, p.Glu129Ter) of FOXG1 was identified in a female child in a cohort of 73 Chinese children with neurodevelopmental disorders/intellectual disorders (NDDs/IDs). In order to have a comprehensive view of FOXG1-related encephalopathy in China, relevant published reports were browsed and twelve cases with mutations in FOXG1 or copy number variants (CNVs) involving FOXG1 gene were involved in the analysis eventually. Feeding difficulties, seizures, delayed speech, corpus callosum hypoplasia and underdevelopment of frontal and temporal lobes occurred in almost all cases. Out of the 12 cases, eight patients (66.67%) had single-nucleotide mutations of FOXG1 gene and four patients (33.33%) had CNVs involving FOXG1 (3 microdeletions and 1 microduplication). The expression of FOXG1 could also be potentially disturbed by deletions of several brain-active regulatory elements located in intergenic FOXG1-PRKD1 region. Further analysis indicated that PRKD1 might be a cooperating factor to regulate the expression of FOXG1, MECP2 and CDKL5 to contribute the RTT/RTT-like disorders.

Discussion

This re-analysis would broaden the existed knowledge about the molecular etiology and be helpful for diagnosis, treatment, and gene therapy of FOXG1-related disorders in the future.

A Genome-Wide Association Study Reveals a BDNF-Centered Molecular Network Associated with Alcohol Dependence and Related Clinical Measures

At least 50% of factors predisposing to alcohol dependence (AD) are genetic and women affected with this disorder present with more psychiatric comorbidities, probably indicating different genetic factors involved. We aimed to run a genome-wide association study (GWAS) followed by a bioinformatic functional annotation of associated genomic regions in patients with AD and eight related clinical measures. A genome-wide significant association of rs220677 with AD (p-value = 1.33 × 10^-8 calculated with the Yates-corrected χ² test under the assumption of dominant inheritance) was discovered in female patients. Associations of AD and related clinical measures with seven other single nucleotide polymorphisms listed in previous GWASs of psychiatric and addiction traits were differently replicated in male and female patients. The bioinformatic analysis showed that regulatory elements in the eight associated linkage disequilibrium blocks define the expression of 80 protein-coding genes. Nearly 68% of these and of 120 previously published coding genes associated with alcohol phenotypes directly interact in a single network, where BDNF is the most significant hub gene. This study indicates that several genes behind the pathogenesis of AD are different in male and female patients, but implicated molecular mechanisms are functionally connected. The study also reveals a central role of BDNF in the pathogenesis of AD.

Regulation of DNA Methylation by Cannabidiol and Its Implications for Psychiatry: New Insights from In Vivo and In Silico Models

Cannabidiol (CBD) is a non-psychotomimetic compound present in cannabis sativa. Many recent studies have indicated that CBD has a promising therapeutic profile for stress-related psychiatric disorders, such as anxiety, schizophrenia and depression. Such a diverse profile has been associated with its complex pharmacology, since CBD can target different neurotransmitter receptors, enzymes, transporters and ion channels. However, the precise contribution of each of those mechanisms for CBD effects is still not yet completely understood. Considering that epigenetic changes make the bridge between gene expression and environment interactions, we review and discuss herein how CBD affects one of the main epigenetic mechanisms associated with the development of stress-related psychiatric disorders: DNA methylation (DNAm). Evidence from in vivo and in silico studies indicate that CBD can regulate the activity of the enzymes responsible for DNAm, due to directly binding to the enzymes and/or by indirectly regulating their activities as a consequence of neurotransmitter-mediated signaling. The implications of this new potential pharmacological target for CBD are discussed in light of its therapeutic and neurodevelopmental effects.

Identifying pleiotropic genes for major psychiatric disorders with GWAS summary statistics using multivariate adaptive association tests

BACKGROUND

Genome wide association studies (GWAS) have discovered a few of single nucleotide polymorphisms (SNPs) related to major psychiatric disorders. However, it is not completely clear which genes play a pleiotropic role in multiple disorders. The study aimed to identify the pleiotropic genes across five psychiatric disorders using multivariate adaptive association tests.

METHODS

Summary statistics of five psychiatric disorders were downloaded from Psychiatric Genomics Consortium. We applied linkage disequilibrium score regression (LDSC) to estimate genetic correlation and conducted tissue and cell type specificity analyses based on Multi-marker Analysis of GenoMic Annotation (MAGMA). Then, we identified the pleiotropic genes using MTaSPUsSet and aSPUs tests. We ultimately performed the functional analysis for pleiotropic genes.

RESULTS

We confirmed the significant genetic correlation and brain tissue and neuron specificity among five disorders. 100 pleiotropic genes were detected to be significantly associated with five psychiatric disorders, of which 55 were novel genes. These genes were functionally enriched in neuron differentiation and synaptic transmission.

LIMITATIONS

The effect direction of pleiotropic genes couldn't be distinguished due to without individual-level data.

CONCLUSION

We identified pleiotropic genes using multivariate adaptive association tests and explored their biological function. The findings may provide novel insight into the development and implementation of prevention and treatment as well as targeted drug discovery in practice.

Functional assessment of heart-specific enhancers by integrating ChIP-seq data

BACKGROUND

Identification and functional annotations of regulatory sequences play a pivotal role in heart development and function.

METHODS

To generate a map of human heart-specific enhancers, we performed an integrative analysis of 148 chromatin immunoprecipitation coupled to massively parallel sequencing (ChIP-seq) samples with enhancer-associated epigenetic marks from the heart, liver, brain, and kidney. Functional validation of heart-specific enhancer activity was then performed using cultured cells.

RESULTS

A 144.6-Mb candidate heart-specific enhancer compendium was generated by integrating the analysis of 148 epigenomic data sets from human and mouse hearts and control tissues. To validate in vivo enhancer activity, we tested 12 of these sequences around 45 CHD-related genes in cultured cells and found that 8 (67%) have reproducible heart-specific enhancer activity. A functional analysis demonstrated that the identified human heart-specific enhancer wf1 regulates the FBN1 gene which is involved in heart disease.

CONCLUSIONS

Our study provides an integrative analysis pipeline for ChIP-seq data and identified a comprehensive catalog of human heart-specific enhancers for clinical CHD-related studies.

IMPACT

Establishing an efficient way to analyze regulatory regions in CHD is very important. A highly qualified heart-specific enhancer compendium was generated by integrating 148 online ChIP-seq samples. Sixty-seven percent of predicted regulatory sequences have reproducible heart-specific enhancer activity in vivo. Human heart-specific enhancer wf1 regulates the CHD-related FBN1 gene.

General intelligence and executive functioning are overlapping but separable at genetic and molecular pathway levels: An analytical review of existing GWAS findings

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)–another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p<5x10^-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation.

Four common vitamin D receptor polymorphisms and coronary artery disease susceptibility: A trial sequential analysis

Background

Studies on the susceptibility of vitamin D receptor (VDR) polymorphisms to coronary artery disease (CAD) reached controversial results. We performed this study for a more accurate evaluation between the VDR polymorphisms and CAD susceptibility.

Methods

PubMed, Embase, CNKI, Wan Fang, and VIP databases were searched. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were used to evaluate the associations. Trial sequential analysis (TSA) was introduced to estimate the positive associations. The potential functions of the VDR polymorphisms were analyzed based on the SNPinfo and ENSEMBL databases.

Results

Thirteen studies were finally included. In the overall analysis, increased CAD risks were observed in the VDR rs1544410 polymorphism and verified by the TSA; for the rs2228570 and rs731236 polymorphisms, significant associations with high heterogeneity were detected; decreased risk was remarkably observed for the rs7975232 polymorphism. In the subgroup analysis, wide associations with reduced heterogeneity were observed in the rs2228570, rs1544410, and rs731236 polymorphisms. The RNAfold analysis indicated the mutant G allele of the rs1544410 polymorphism was easier to disperse from the DNA double helix structure and may have a potential crucial role in the VDR transcription process.

Conclusions

Our analysis supports the role of the rs1544410 polymorphism in the VDR gene as a risk factor for CAD. The VDR rs2228570 and rs731236 polymorphisms were associated with increased CAD risks in the White population. Restrict decreased CAD risk was firstly discovered in the rs7975232 polymorphism.

Limitations

Firstly, the language was restricted to English and Chinese, which will cause the limited number of studies included; secondly, other unknown polymorphisms in VDR polymorphisms could also be associated the CAD susceptibility, and more case-control studies with comprehensive clinical outcomes and GWAS studies were required; thirdly, the rs1544410, rs7975232 and rs731236 polymorphism are in strong LD, haploid factors with CAD risk need to be considered; fourthly, the mechanisms of the VDR polymorphism on the VDR gene or RNA or protein were not discussed enough, further mechanistic studies are required; at last, genetic factor was the one side for CAD susceptibility, the interaction between environmental risk factors should be considered.

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.

Acupuncture in treating obesity combined with type 2 diabetes mellitus: A systematic review and meta-analysis of randomized controlled clinical trials

BACKGROUND

and purpose: Most type 2 diabetes mellitus (T2DM) patients are accompanied by overweight or obesity, and it is difficult to concurrently solve these two issues with conventional treatment regimens without experiencing adverse effects. While clinical practice demonstrates that acupuncture is beneficial in treating obesity combined with T2DM, there is a lack of evidence-based medicine to support this claim. The study aims to systematically evaluate the efficacy and safety of acupuncture in treating obesity combined with T2DM.

METHODS

By searching eight electronic databases, we collected randomized controlled trials on acupuncture in treating obesity combined with T2DM. Two reviewers independently screened the literature, extracted the data, and assessed the risk of bias in the included studies. Meta-analysis was then performed using RevMan 5.4 software.

RESULTS

A total of 13 randomized controlled trials (RCTs) involving 993 patients were eventually included. Meta-analysis results demonstrated the effective rate of clinical symptoms: [RR = 1.19, 95% CI: 1.11, 1.28, P < 0.00001]; body mass index: [MD = -2.11, 95% CI: -2.56, -1.66, P < 0.00001]; fasting plasma glucose: [MD = -1.09, 95% CI: -1.60, -0.59, P < 0.00001]; haemoglobin A1c: [MD = -0.58, 95% CI: -0.95, -0.20, P = 0.002]; triglyceride: [MD = -0.29, 95% CI: -0.46, -0.11, P = 0.001]; waist circumference: [MD = -5.36, 95% CI: -8.68, -2.05, P = 0.002]; body fat rate: [MD = -3.59, 95% CI: -4.28, -2.90, P < 0.00001].

CONCLUSION

Current evidence suggests that acupuncture has advantages in treating obesity combined with T2DM. However, due to low-quality evidence of included research, additional large-sample and high-quality research are required to validate the findings of this study.

Shared genetics between autism spectrum disorder and attention-deficit/hyperactivity disorder and their association with extraversion

BACKGROUND

Deciphering the genetic relationships between autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) may uncover underlining shared pathophysiology as well as inform treatment.

METHODS

The summary results of genome-wide association studies on ADHD, ASD, and extraversion were utilized for the analyzes. Genetic correlations between ADHD, ASD, and extraversion were tested using linkage disequilibrium score regression. Causal relationships between ADHD, ASD, and extraversion were investigated using Mendelian randomization (MR) analysis. Novel pleiotropic genomic loci shared by ADHD and ASD were identified using a cross-trait meta-analysis.

RESULTS

Extraversion was positively correlated with ADHD (r_g = 0.205) and negatively correlated with ASD (r_g = -0.193). The MR analysis showed that ADHD confers a causal effect on ASD (OR: 1.35, 95% confidence interval (CI):1.20-1.52) and vice versa (1.46, 1.38-1.55). Extraversion exerts a causal effect on ADHD only (1.19, 1.05-1.33). The cross-trait meta-analysis identified three novel pleiotropic genomic loci for ADHD and ASD, involving two pleiotropic genes, LINC00461 and KIZ.

CONCLUSIONS

Our study provides new insights into the shared genetics of ADHD and ASD and their connections with extraversion.

Patterns of Convergence and Divergence Between Bipolar Disorder Type I and Type II: Evidence From Integrative Genomic Analyses

Aim: Genome-wide association studies (GWAS) analyses have revealed genetic evidence of bipolar disorder (BD), but little is known about the genetic structure of BD subtypes. We aimed to investigate the genetic overlap and distinction of bipolar type I (BD I) & type II (BD II) by conducting integrative post-GWAS analyses.

Methods: We utilized single nucleotide polymorphism (SNP)–level approaches to uncover correlated and distinct genetic loci. Transcriptome-wide association analyses (TWAS) were then approached to pinpoint functional genes expressed in specific brain tissues and blood. Next, we performed cross-phenotype analysis, including exploring the potential causal associations between two BD subtypes and lithium responses and comparing the difference in genetic structures among four different psychiatric traits.

Results: SNP-level evidence revealed three genomic loci, SLC25A17, ZNF184, and RPL10AP3, shared by BD I and II, and one locus (MAD1L1) and significant gene sets involved in calcium channel activity, neural and synapsed signals that distinguished two subtypes. TWAS data implicated different genes affecting BD I and II through expression in specific brain regions (nucleus accumbens for BD I). Cross-phenotype analyses indicated that BD I and II share continuous genetic structures with schizophrenia and major depressive disorder, which help fill the gaps left by the dichotomy of mental disorders.

Conclusion: These combined evidences illustrate genetic convergence and divergence between BD I and II and provide an underlying biological and trans-diagnostic insight into major psychiatric disorders.

Characterizing the polygenic overlaps of bipolar disorder subtypes with schizophrenia and major depressive disorder

BACKGROUND

Large-scale studies have shown that bipolar I disorder (BD-I) and bipolar II disorder (BD-II) have differences in genetic association with schizophrenia (SCZ) and major depressive disorder (MDD). However, the underlying shared genetic architectures between BD subtypes and both SCZ and MDD remain largely unknown.

METHODS

We applied univariate and bivariate causal mixture models (MiXeR) to estimate the polygenicity and polygenic overlaps on large GWASs summary statistics of BD-I (n = 25,060), BD-II (n = 6781), SCZ (n = 69,369) and MDD (n = 170,756). Then, conjunctional false discovery rate approach was used to identify specific shared genetic loci between BD subtypes and both SCZ and MDD.

RESULTS

Univariate MiXeR revealed that BD-II was substantially more polygenic (22.37 K causal variants) as compared to BD-I, SCZ and MDD (7.87-12.43 K causal variants). Bivariate MiXeR revealed substantial polygenic overlaps between BD-I and SCZ (Dice-coefficient = 0.83) and between BD-I and MDD (Dice-coefficient = 0.76), which are beyond the genetic correlation (rg = 0.71 and 0.36). Conjunctional FDR analysis identified 236 distinct shared loci between BD-I and BD-II (2 loci), BD-I and SCZ (227 loci), BD-I and MDD (19 loci), BD-II and SCZ (1 locus), and BD-II and MDD (3 loci). Most of these shared loci have concordant effect directions among BD subtypes, SCZ and MDD.

LIMITATIONS

The bivariate MiXeR model was not applied for the BD-II because of insufficient power and inadequate model fit.

CONCLUSIONS

These findings provide evidence for extensive polygenic effects across BD subtypes, SCZ and MDD, which further our understanding of the potential genetic basis for the comorbid symptoms across these disorders.

Cerebral organoids containing an AUTS2 missense variant model microcephaly

Variants in the AUTS2 gene are associated with a broad spectrum of neurological conditions characterized by intellectual disability, microcephaly, and congenital brain malformations. Here, we use a human cerebral organoid model to investigate the pathophysiology of a heterozygous de novo missense AUTS2 variant identified in a patient with multiple neurological impairments including primary microcephaly and profound intellectual disability. Proband cerebral organoids exhibit reduced growth, deficits in neural progenitor cell (NPC) proliferation and disrupted NPC polarity within ventricular zone-like regions compared to control cerebral organoids. We used CRISPR-Cas9-mediated gene editing to correct this variant and demonstrate rescue of impaired organoid growth and NPC proliferative deficits. Single-cell RNA sequencing revealed a marked reduction of G1/S transition gene expression and alterations in WNT-β-catenin signalling within proband NPCs, uncovering a novel role for AUTS2 in NPCs during human cortical development. Collectively, these results underscore the value of cerebral organoids to investigate molecular mechanisms underlying AUTS2 syndrome.