Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection

Interpretation of SNP combination effects on schizophrenia etiology based on stepwise deep learning with multi-precision data

Schizophrenia genome-wide association studies (GWAS) have reported many genomic risk loci, but it is unclear how they affect schizophrenia susceptibility through interactions of multiple SNPs. We propose a stepwise deep learning technique with multi-precision data (SLEM) to explore the SNP combination effects on schizophrenia through intermediate molecular and cellular functions. The SLEM technique utilizes two levels of precision data for learning. It constructs initial backbone networks with more precise but small amount of multilevel assay data. Then, it learns strengths of intermediate interactions with the less precise but massive amount of GWAS data. The learned networks facilitate identifying effective SNP interactions from the intractably large space of all possible SNP combinations. We have shown that the extracted SNP combinations show higher accuracy than any single SNPs and preserve the accuracy in an independent dataset. The learned networks also provide interpretations of molecular and cellular interactions of SNP combinations toward schizophrenia etiology.

Recent natural selection conferred protection against schizophrenia by non-antagonistic pleiotropy

Schizophrenia is a debilitating psychiatric disorder associated with a reduced fertility and decreased life expectancy, yet common predisposing variation substantially contributes to the onset of the disorder, which poses an evolutionary paradox. Previous research has suggested balanced selection, a mechanism by which schizophrenia risk alleles could also provide advantages under certain environments, as a reliable explanation. However, recent studies have shown strong evidence against a positive selection of predisposing loci. Furthermore, evolutionary pressures on schizophrenia risk alleles could have changed throughout human history as new environments emerged. Here in this study, we used 1000 Genomes Project data to explore the relationship between schizophrenia predisposing loci and recent natural selection (RNS) signatures after the human diaspora out of Africa around 100,000 years ago on a genome-wide scale. We found evidence for significant enrichment of RNS markers in derived alleles arisen during human evolution conferring protection to schizophrenia. Moreover, both partitioned heritability and gene set enrichment analyses of mapped genes from schizophrenia predisposing loci subject to RNS revealed a lower involvement in brain and neuronal related functions compared to those not subject to RNS. Taken together, our results suggest non-antagonistic pleiotropy as a likely mechanism behind RNS that could explain the persistence of schizophrenia common predisposing variation in human populations due to its association to other non-psychiatric phenotypes.

Multiple genes in a single GWAS risk locus synergistically mediate aberrant synaptic development and function in human neurons

The mechanistic tie between genome-wide association study (GWAS)-implicated risk variants and disease-relevant cellular phenotypes remains largely unknown. Here, using human induced pluripotent stem cell (hiPSC)-derived neurons as a neurodevelopmental model, we identify multiple schizophrenia (SZ) risk variants that display allele-specific open chromatin (ASoC) and are likely to be functional. Editing the strongest ASoC SNP, rs2027349, near vacuolar protein sorting 45 homolog (VPS45) alters the expression of VPS45, lncRNA AC244033.2, and a distal gene, C1orf54. Notably, the transcriptomic changes in neurons are associated with SZ and other neuropsychiatric disorders. Neurons carrying the risk allele exhibit increased dendritic complexity and hyperactivity. Interestingly, individual/combinatorial gene knockdown shows that these genes alter cellular phenotypes in a non-additive synergistic manner. Our study reveals that multiple genes at a single GWAS risk locus mediate a compound effect on neural function, providing a mechanistic link between a non-coding risk variant and disease-related cellular phenotypes.

Human microglia maturation is underpinned by specific gene regulatory networks

Microglia phenotypes are highly regulated by the brain environment, but the transcriptional networks that specify the maturation of human microglia are poorly understood. Here, we characterized stage-specific transcriptomes and epigenetic landscapes of fetal and postnatal human microglia and acquired corresponding data in induced pluripotent stem cell (iPSC)-derived microglia, in cerebral organoids, and following engraftment into humanized mice. Parallel development of computational approaches that considered transcription factor (TF) co-occurrence and enhancer activity allowed prediction of shared and state-specific gene regulatory networks associated with fetal and postnatal microglia. Additionally, many features of the human fetal-to-postnatal transition were recapitulated in a time-dependent manner following the engraftment of iPSC cells into humanized mice. These data and accompanying computational approaches will facilitate further efforts to elucidate mechanisms by which human microglia acquire stage- and disease-specific phenotypes.

Characterizing the phenotypic and genetic structure of psychopathology in UK Biobank

Mental conditions exhibit a higher-order transdiagnostic factor structure which helps to explain the widespread comorbidity observed in psychopathology. However, the phenotypic and genetic structures of psychopathology may differ, raising questions about the validity and utility of these factors. Here, we study the phenotypic and genetic factor structures of ten psychiatric conditions using UK Biobank and public genomic data. Although the factor structure of psychopathology was generally genetically and phenotypically consistent, conditions related to externalizing (e.g., alcohol use disorder) and compulsivity (e.g., eating disorders) exhibited cross-level disparities in their relationships with other conditions, plausibly due to environmental influences. Domain-level factors, especially thought disorder and internalizing factors, were more informative than a general psychopathology factor in genome-wide association and polygenic index analyses. Collectively, our findings enhance the understanding of comorbidity and shared etiology, highlight the intricate interplay between genes and environment, and offer guidance for psychiatric research using polygenic indices.

Copy Number Variations in Neuropsychiatric Disorders

Neuropsychiatric disorders are complex conditions that represent a significant global health burden with complex and multifactorial etiologies. Technological advances in recent years have improved our understanding of the genetic architecture of the major neuropsychiatric disorders and the genetic loci involved. Previous studies mainly investigated genome-wide significant SNPs to elucidate the cross-disorder and disorder-specific genetic basis of neuropsychiatric disorders. Although copy number variations represent a major source of genetic variations, they are known risk factors in developing a variety of human disorders, including certain neuropsychiatric diseases. In this review, we demonstrate the current understanding of CNVs contributing to liability for schizophrenia, bipolar disorder, and major depressive disorder.

Genomic findings in schizophrenia and their implications

There has been substantial progress in understanding the genetics of schizophrenia over the past 15 years. This has revealed a highly polygenic condition with the majority of the currently explained heritability coming from common alleles of small effect but with additional contributions from rare copy number and coding variants. Many specific genes and loci have been implicated that provide a firm basis upon which mechanistic research can proceed. These point to disturbances in neuronal, and particularly synaptic, functions that are not confined to a small number of brain regions and circuits. Genetic findings have also revealed the nature of schizophrenia's close relationship to other conditions, particularly bipolar disorder and childhood neurodevelopmental disorders, and provided an explanation for how common risk alleles persist in the population in the face of reduced fecundity. Current genomic approaches only potentially explain around 40% of heritability, but only a small proportion of this is attributable to robustly identified loci. The extreme polygenicity poses challenges for understanding biological mechanisms. The high degree of pleiotropy points to the need for more transdiagnostic research and the shortcomings of current diagnostic criteria as means of delineating biologically distinct strata. It also poses challenges for inferring causality in observational and experimental studies in both humans and model systems. Finally, the Eurocentric bias of genomic studies needs to be rectified to maximise benefits and ensure these are felt across diverse communities. Further advances are likely to come through the application of new and emerging technologies, such as whole-genome and long-read sequencing, to large and diverse samples. Substantive progress in biological understanding will require parallel advances in functional genomics and proteomics applied to the brain across developmental stages. For these efforts to succeed in identifying disease mechanisms and defining novel strata they will need to be combined with sufficiently granular phenotypic data.

Genetics of cell-type-specific post-transcriptional gene regulation during human neurogenesis

The function of some genetic variants associated with brain-relevant traits has been explained through colocalization with expression quantitative trait loci (eQTL) conducted in bulk post-mortem adult brain tissue. However, many brain-trait associated loci have unknown cellular or molecular function. These genetic variants may exert context-specific function on different molecular phenotypes including post-transcriptional changes. Here, we identified genetic regulation of RNA-editing and alternative polyadenylation (APA), within a cell-type-specific population of human neural progenitors and neurons. More RNA-editing and isoforms utilizing longer polyadenylation sequences were observed in neurons, likely due to higher expression of genes encoding the proteins mediating these post-transcriptional events. We also detected hundreds of cell-type-specific editing quantitative trait loci (edQTLs) and alternative polyadenylation QTLs (apaQTLs). We found colocalizations of a neuron edQTL in CCDC88A with educational attainment and a progenitor apaQTL in EP300 with schizophrenia, suggesting genetically mediated post-transcriptional regulation during brain development lead to differences in brain function.

Modeling psychotic disorders: Environment x environment interaction

Schizophrenia is a major psychotic disorder with multifactorial etiology that includes interactions between genetic vulnerability and environmental risk factors. In addition, interplay of multiple environmental adversities affects neurodevelopment and may increase the individual risk of developing schizophrenia. Consistent with the two-hit hypothesis of schizophrenia, we review rodent models that combine maternal immune activation as the first hit with other adverse environmental exposures as the second hit. We discuss the strengths and pitfalls of the current animal models of environment x environment interplay and propose some future directions to advance the field.

Mitochondrial DNA Copy Number and Heteroplasmy in Monozygotic Twins Discordant for Schizophrenia

Schizophrenia (SZ) is a severe, complex, and common mental disorder with high heritability (80%), an adult age of onset, and high discordance (∼50%) in monozygotic twins (MZ). Extensive studies on familial and non-familial cases have implicated a number of segregating mutations and de novo changes in SZ that may include changes to the mitochondrial genome. Yet, no single universally causal variant has been identified, highlighting its extensive genetic heterogeneity. This report specifically focuses on the assessment of changes in the mitochondrial genome in a unique set of monozygotic twins discordant (MZD) for SZ using blood. Genomic DNA from six pairs of MZD twins and two sets of parents (N = 16) was hybridized to the Affymetrix Human SNP Array 6.0 to assess mitochondrial DNA copy number (mtDNA-CN). Whole genome sequencing (WGS) and quantitative polymerase chain reaction (qPCR) was performed for a subset of MZD pairs and their parents and was also used to derive mtDNA-CN estimates. The WGS data were further analyzed to generate heteroplasmy (HP) estimates. Our results show that mtDNA-CN estimates for within-pair and mother-child differences were smaller than comparisons involving unrelated individuals, as expected. MZD twins showed discordance in mtDNA-CN estimates and displayed concordance in directionality of differences for mtDNA-CN across all technologies. Further, qPCR performed better than Affymetrix in estimating mtDNA-CN based on relatedness. No reliable differences in HP were detected between MZD twins. The within-MZD differences in mtDNA-CN observed represent postzygotic somatic changes that may contribute to discordance of MZ twins for diseases, including SZ.

Genome-wide analysis of anorexia nervosa and major psychiatric disorders and related traits reveals genetic overlap and identifies novel risk loci for anorexia nervosa

Anorexia nervosa (AN) is a heritable eating disorder (50-60%) with an array of commonly comorbid psychiatric disorders and related traits. Although significant genetic correlations between AN and psychiatric disorders and related traits have been reported, their shared genetic architecture is largely understudied. We investigated the shared genetic architecture of AN and schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), mood instability (Mood), neuroticism (NEUR), and intelligence (INT). We applied the conditional false discovery rate (FDR) method to identify novel risk loci for AN, and conjunctional FDR to identify loci shared between AN and related phenotypes, to summarize statistics from relevant genome-wide association studies (GWAS). Individual GWAS samples varied from 72,517 to 420,879 participants. Using conditional FDR we identified 58 novel AN loci. Furthermore, we identified 38 unique loci shared between AN and major psychiatric disorders (SCZ, BIP, and MD) and 45 between AN and psychological traits (Mood, NEUR, and INT). In line with genetic correlations, the majority of shared loci showed concordant effect directions. Functional analyses revealed that the shared loci are involved in 65 unique pathways, several of which overlapped across analyses, including the "signal by MST1" pathway involved in Hippo signaling. In conclusion, we demonstrated genetic overlap between AN and major psychiatric disorders and related traits, and identified novel risk loci for AN by leveraging this overlap. Our results indicate that some shared characteristics between AN and related disorders and traits may have genetic underpinnings.

Phenotypic and genetic factors associated with donation of DNA and consent to record linkage for prescription history in the Australian Genetics of Depression Study

Samples can be prone to ascertainment and attrition biases. The Australian Genetics of Depression Study is a large publicly recruited cohort (n = 20,689) established to increase the understanding of depression and antidepressant treatment response. This study investigates differences between participants who donated a saliva sample or agreed to linkage of their records compared to those who did not. We observed that older, male participants with higher education were more likely to donate a saliva sample. Self-reported bipolar disorder, ADHD, panic disorder, PTSD, substance use disorder, and social anxiety disorder were associated with lower odds of donating a saliva sample, whereas anorexia was associated with higher odds of donation. Male and younger participants showed higher odds of agreeing to record linkage. Participants with higher neuroticism scores and those with a history of bipolar disorder were also more likely to agree to record linkage whereas participants with a diagnosis of anorexia were less likely to agree. Increased likelihood of consent was associated with increased genetic susceptibility to anorexia and reduced genetic risk for depression, and schizophrenia. Overall, our results show moderate differences among these subsamples. Most current epidemiological studies do not search for attrition biases at the genetic level. The possibility to do so is a strength of samples such as the AGDS. Our results suggest that analyses can be made more robust by identifying attrition biases both on the phenotypic and genetic level, and either contextualising them as a potential limitation or performing sensitivity analyses adjusting for them.

Joint analysis of GWAS and multi-omics QTL summary statistics reveals a large fraction of GWAS signals shared with molecular phenotypes

Molecular quantitative trait loci (xQTLs) are often harnessed to prioritize genes or functional elements underpinning variant-trait associations identified from genome-wide association studies (GWASs). Here, we introduce OPERA, a method that jointly analyzes GWAS and multi-omics xQTL summary statistics to enhance the identification of molecular phenotypes associated with complex traits through shared causal variants. Applying OPERA to summary-level GWAS data for 50 complex traits (n = 20,833-766,345) and xQTL data from seven omics layers (n = 100-31,684) reveals that 50% of the GWAS signals are shared with at least one molecular phenotype. GWAS signals shared with multiple molecular phenotypes, such as those at the MSMB locus for prostate cancer, are particularly informative for understanding the genetic regulatory mechanisms underlying complex traits. Future studies with more molecular phenotypes, measured considering spatiotemporal effects in larger samples, are required to obtain a more saturated map linking molecular intermediates to GWAS signals.

Enrichment of self-domestication and neural crest function loci in the heritability of neurodevelopmental disorders

Self-domestication could contribute to shaping the biology of human brain and consequently the predisposition to neurodevelopmental disorders. Leveraging genome-wide data from the Psychiatric Genomics Consortium, we tested the enrichment of self-domestication and neural crest function loci with respect to the heritability of autism spectrum disorder, schizophrenia (SCZ in East Asian and European ancestries, EAS and EUR, respectively), attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, and Tourette's syndrome (TS). Considering only self-domestication and neural-crest-function annotations in the linkage disequilibrium score regression (LDSC) model, our partitioned heritability analysis revealed statistically significant enrichments across all disorders investigated. The estimates of the heritability enrichments for self-domestication loci were similar across neurodevelopmental disorders, ranging from 0.902 (EAS SCZ, p = 4.55 × 10-20) to 1.577 (TS, p = 5.85 × 10-5). Conversely, a wider spectrum of heritability enrichment estimates was present for neural crest function with the highest enrichment observed for TS (enrichment = 3.453, p = 2.88 × 10-3) and the lowest for EAS SCZ (enrichment = 1.971, p = 3.81 × 10-3). Although these estimates appear to be strong, the enrichments for self-domestication and neural crest function were null once we included additional annotations related to different genomic features. This indicates that the effect of self-domestication on the polygenic architecture of neurodevelopmental disorders is not independent of other functions of human genome.

Genetic Underpinnings of the Transition From Alcohol Consumption to Alcohol Use Disorder: Shared and Unique Genetic Architectures in a Cross-Ancestry Sample

OBJECTIVE

Recent genome-wide association studies (GWASs) of alcohol-related phenotypes have uncovered key differences in the underlying genetic architectures of alcohol consumption and alcohol use disorder (AUD), with the two traits having opposite genetic correlations with psychiatric disorders. Understanding the genetic factors that underlie the transition from heavy drinking to AUD has important theoretical and clinical implications.

METHODS

The authors used longitudinal data from the cross-ancestry Million Veteran Program sample to identify 1) novel loci associated with AUD and alcohol consumption (measured by the score on the consumption subscale of the Alcohol Use Disorders Identification Test [AUDIT-C]), 2) the impact of phenotypic variation on genetic discovery, and 3) genetic variants with direct effects on AUD that are not mediated through alcohol consumption.

RESULTS

The authors identified 26 loci associated with AUD and 22 loci associated with AUDIT-C score, including ancestry-specific and novel loci. In secondary GWASs that excluded individuals who report abstinence, the authors identified seven additional loci for AUD and eight additional loci for AUDIT-C score. Although the heterogeneity of the abstinent group biases the GWAS findings, unique variance between alcohol consumption and disorder remained after the abstinent group was excluded. Finally, using mediation analysis, the authors identified a set of variants with effects on AUD that are not mediated through alcohol consumption.

CONCLUSIONS

Differences in genetic architecture between alcohol consumption and AUD are consistent with their having different biological contributions. Genetic variants with direct effects on AUD are potentially relevant to understanding the transition from heavy alcohol consumption to AUD and may be targets for translational prevention and treatment efforts.

R-loop landscapes in the developing human brain are linked to neural differentiation and cell-type specific transcription

Here, we construct genome-scale maps for R-loops, three-stranded nucleic acid structures comprised of a DNA/RNA hybrid and a displaced single strand of DNA, in the proliferative and differentiated zones of the human prenatal brain. We show that R-loops are abundant in the progenitor-rich germinal matrix, with preferential formation at promoters slated for upregulated expression at later stages of differentiation, including numerous neurodevelopmental risk genes. RNase H1-mediated contraction of the genomic R-loop space in neural progenitors shifted differentiation toward the neuronal lineage and was associated with transcriptomic alterations and defective functional and structural neuronal connectivity in vivo and in vitro. Therefore, R-loops are important for fine-tuning differentiation-sensitive gene expression programs of neural progenitor cells.

Regional genetic correlations highlight relationships between neurodegenerative disease loci and the immune system

Neurodegenerative diseases, including Alzheimer's and Parkinson's disease, are devastating complex diseases resulting in physical and psychological burdens on patients and their families. There have been important efforts to understand their genetic basis leading to the identification of disease risk-associated loci involved in several molecular mechanisms, including immune-related pathways. Regional, in contrast to genome-wide, genetic correlations between pairs of immune and neurodegenerative traits have not been comprehensively explored, but could uncover additional immune-mediated risk-associated loci. Here, we systematically assess the role of the immune system in five neurodegenerative diseases by estimating regional genetic correlations between these diseases and immune-cell-derived single-cell expression quantitative trait loci (sc-eQTLs). We also investigate correlations between diseases and protein levels. We observe significant (FDR < 0.01) correlations between sc-eQTLs and neurodegenerative diseases across 151 unique genes, spanning both the innate and adaptive immune systems, across most diseases tested. With Parkinson's, for instance, RAB7L1 in CD4+ naïve T cells is positively correlated and KANSL1-AS1 is negatively correlated across all adaptive immune cell types. Follow-up colocalization highlight candidate causal risk genes. The outcomes of this study will improve our understanding of the immune component of neurodegeneration, which can warrant repurposing of existing immunotherapies to slow disease progression.

Effects of olanzapine on anhedonia in schizophrenia: mediated by complement factor H

Background

Anhedonia is a trans-diagnostic symptom in schizophrenia and MDD. Our recent work indicated that increased plasma level of complement factor H (CFH) is associated with anhedonia in major depressive disorder. This study hypothesized that CFH is likely to be a biomarker of anhedonia in schizophrenia.

Methods

A 12-week prospective study is performed to observe the effects of olanzapine on anhedonia and CFH. We used the Chinese version of Snaith-Hamilton Pleasure Scale (SHAPS) to evaluate anhedonic phenotype in patients with schizophrenia. Plasma levels of C-reactive protein (CRP), C3, C4 and CFH were measured.

Results

Of the recruited 152 samples, patients with anhedonia were found in 99/152 (65.13%). Patients with anhedonia had notably higher PANSS negative subscores, SHAPS total score and higher level of plasma CFH than those without anhedonia (Ps<0.05). Stepwise multivariate linear regression analysis showed that increasing level of plasma CFH was a risk factor for SHAPS total score (β = 0.18, p = 0.03). Of the 99 patients with anhedonia, 74 completed the 12-week follow-up. We observed significantly reduced scores of PANSS, SHAPS and decreased plasma CFH level, when the patients completed this study. The change of SHAPS total score is positively correlated with the level of CFH decrease (p = 0.02).

Conclusion

Our results implied that plasma CFH levels may be a biomarker for anhedonia in schizophrenia, and the effect of olanzapine on treating anhedonia is through decreasing plasma CFH levels.

150 risk variants for diverticular disease of intestine prioritize cell types and enable polygenic prediction of disease susceptibility

We conducted a genome-wide association study (GWAS) analysis of diverticular disease (DivD) of intestine within 724,372 individuals and identified 150 independent genome-wide significant DNA variants. Integration of the GWAS results with human gut single-cell RNA sequencing data implicated gut myocyte, mesothelial and stromal cells, and enteric neurons and glia in DivD development. Ninety-five genes were prioritized based on multiple lines of evidence, including SLC9A3, a drug target gene of tenapanor used for the treatment of the constipation subtype of irritable bowel syndrome. A DivD polygenic score (PGS) enables effective risk prediction (area under the curve [AUC], 0.688; 95% confidence interval [CI], 0.645-0.732) and the top 20% PGS was associated with ∼3.6-fold increased DivD risk relative to the remaining population. Our statistical and bioinformatic analyses suggest that the mechanism of DivD is through colon structure, gut motility, gastrointestinal mucus, and ionic homeostasis. Our analyses reinforce the link between gastrointestinal disorders and the enteric nervous system through genetics.

Developmental loss of ErbB4 in PV interneurons disrupts state-dependent cortical circuit dynamics

GABAergic inhibition plays an important role in the establishment and maintenance of cortical circuits during development. Neuregulin 1 (Nrg1) and its interneuron-specific receptor ErbB4 are key elements of a signaling pathway critical for the maturation and proper synaptic connectivity of interneurons. Using conditional deletions of the ERBB4 gene in mice, we tested the role of this signaling pathway at two developmental timepoints in parvalbumin-expressing (PV) interneurons, the largest subpopulation of cortical GABAergic cells. Loss of ErbB4 in PV interneurons during embryonic, but not late postnatal development leads to alterations in the activity of excitatory and inhibitory cortical neurons, along with severe disruption of cortical temporal organization. These impairments emerge by the end of the second postnatal week, prior to the complete maturation of the PV interneurons themselves. Early loss of ErbB4 in PV interneurons also results in profound dysregulation of excitatory pyramidal neuron dendritic architecture and a redistribution of spine density at the apical dendritic tuft. In association with these deficits, excitatory cortical neurons exhibit normal tuning for sensory inputs, but a loss of state-dependent modulation of the gain of sensory responses. Together these data support a key role for early developmental Nrg1/ErbB4 signaling in PV interneurons as a powerful mechanism underlying the maturation of both the inhibitory and excitatory components of cortical circuits.

Understanding the relationship between loneliness, substance use traits and psychiatric disorders: A genetically informed approach

Loneliness is a common, yet distressing experience associated with adverse outcomes including substance use problems and psychiatric disorders. To what extent these associations reflect genetic correlations and causal relationships is currently unclear. We applied Genomic Structural Equation Modelling (GSEM) to dissect the genetic architecture between loneliness and psychiatric-behavioural traits. Included were summary statistics from 12 genome-wide association analyses, including loneliness and 11 psychiatric phenotypes (range N: 9,537 - 807,553). We first modelled latent genetic factors amongst the psychiatric traits to then investigate potential causal effects between loneliness and the identified latent factors, using multivariate genome-wide association analyses and bidirectional Mendelian randomization. We identified three latent genetic factors, encompassing neurodevelopmental/mood conditions, substance use traits and disorders with psychotic features. GSEM provided evidence of a unique association between loneliness and the neurodevelopmental/mood conditions latent factor. Mendelian randomization results were suggestive of bidirectional causal effects between loneliness and the neurodevelopmental/mood conditions factor. These results imply that a genetic predisposition to loneliness may elevate the risk of neurodevelopmental/mood conditions, and vice versa. However, results may reflect the difficulty of distiguishing between loneliness and neurodevelopmental/mood conditions, which present in similar ways. We suggest, overall, the importance of addressing loneliness in mental health prevention and policy.

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.

Gene expression profiling of monocytes in recent-onset schizophrenia

Immune-related mechanisms have been suggested to be involved in schizophrenia. Various studies have shown changes in monocytes isolated from the blood of schizophrenia patients, including changes in monocyte numbers, as well as altered protein and transcript levels of important markers. However, validation of these findings and understanding how these results are related to immune-related changes in the brain and schizophrenia genetic risk factors, is limited. The goal of this study was to better understand changes observed in monocytes of patients with early-onset schizophrenia. Using RNA sequencing, we analyzed gene expression profiles of monocytes isolated from twenty patients with early-onset schizophrenia and seventeen healthy controls. We validated expression changes of 7 out of 29 genes that were differentially expressed in previous studies including TNFAIP3, DUSP2, and IL6. At a transcriptome-wide level, we found 99 differentially expressed genes. Effect sizes of differentially expressed genes were moderately correlated with differential expression in brain tissue (Pearson's r = 0.49). Upregulated genes were enriched for genes in NF-κB and LPS signaling pathways. Downregulated genes were enriched for glucocorticoid response pathways. These pathways have been implicated in schizophrenia before and play a role in regulating the activation of myeloid cells. Interestingly, they are also involved in several non-inflammatory processes in the central nervous system, such as neurogenesis and neurotransmission. Future studies are needed to better understand how dysregulation of the NF-κB and glucocorticoid pathways affects inflammatory and non-inflammatory processes in schizophrenia. The fact that dysregulation of these pathways is also seen in brain tissue, provides potential possibilities for biomarker development.

The relationship between case-control differential gene expression from brain tissue and genetic associations in schizophrenia

Large numbers of genetic loci have been identified that are known to contain common risk alleles for schizophrenia, but linking associated alleles to specific risk genes remains challenging. Given that most alleles that influence liability to schizophrenia are thought to do so by altered gene expression, intuitively, case-control differential gene expression studies should highlight genes with a higher probability of being associated with schizophrenia and could help identify the most likely causal genes within associated loci. Here, we test this hypothesis by comparing transcriptome analysis of the dorsolateral prefrontal cortex from 563 schizophrenia cases and 802 controls with genome-wide association study (GWAS) data from the third wave study of the Psychiatric Genomics Consortium. Genes differentially expressed in schizophrenia were not enriched for common allelic association statistics compared with other brain-expressed genes, nor were they enriched for genes within associated loci previously reported to be prioritized by genetic fine-mapping. Genes prioritized by Summary-based Mendelian Randomization were underexpressed in cases compared to other genes in the same GWAS loci. However, the overall strength and direction of expression change predicted by SMR were not related to that observed in the differential expression data. Overall, this study does not support the hypothesis that genes identified as differentially expressed from RNA sequencing of bulk brain tissue are enriched for those that show evidence for genetic associations. Such data have limited utility for prioritizing genes in currently associated loci in schizophrenia.

Characterization of loss of chromosome Y in peripheral blood cells in male Han Chinese patients with schizophrenia

BACKGROUND

Schizophrenia (SCZ) has a global prevalence of 1% and increases the risk of mortality, reducing life expectancy. There is growing evidence that the risk of this disorder is higher in males than in females and it tends to develop in early adulthood. The Y chromosome is thought to be involved in biological processes other than sex determination and spermatogenesis. Studies have shown that loss of chromosome Y (LOY) in peripheral blood cells is associated with a variety of diseases (including cancer) and increased all-cause mortality. An analysis of the relationship between LOY and schizophrenia is warranted.

METHODS

A total of 442 Chinese males (271 patients with schizophrenia vs. 171 controls) were included in this study. The copy numbers of the Y and X chromosomes were detected by positive droplets targeting the amelogenin gene (AMEL) on the Y chromosome and X chromosome (AMELY and AMELX, respectively), using droplet digital PCR (ddPCR). The LOY percentage was defined as the difference between the concentration of AMELX and the concentration of AMELY divided by the concentration of AMELX, denoted as (X - Y)/X.

RESULTS

In the Han Chinese population, the LOY percentage was higher in the schizophrenia group than in the control group (p < 0.05), although there was no significant difference in the presence of LOY between the two groups. A strong correlation was found between the average of the disease duration and the average of the LOY percentage (R² = 0.506, p = 0.032). The logistic regression analysis implied that the risk of LOY increases by 0.058 and 0.057 per year according to age at onset and duration of disease, respectively (p_onset = 0.013, p_duration = 0.017).

CONCLUSIONS

In the Han Chinese population, the LOY percentage of the disease group was significantly different from that of the control group. The age of onset and duration of schizophrenia might be risk factors for LOY in peripheral blood cells. A larger sample size and expanded clinical information are needed for more in-depth and specific analyses.

Cell type and condition specific functional annotation of schizophrenia associated non-coding genetic variants

Schizophrenia (SCZ) is a highly polygenic disease and genome wide association studies have identified thousands of genetic variants that are statistically associated with this psychiatric disorder. However, our ability to translate these associations into insights on the disease mechanisms has been challenging since the causal genetic variants, their molecular function and their target genes remain largely unknown. In order to address these questions, we established a functional genomics pipeline in combination with induced pluripotent stem cell technology to functionally characterize ~35,000 non-coding genetic variants associated with schizophrenia along with their target genes. This analysis identified a set of 620 (1.7%) single nucleotide polymorphisms as functional on a molecular level in a highly cell type and condition specific fashion. These results provide a high-resolution map of functional variant-gene combinations and offer comprehensive biological insights into the developmental context and stimulation dependent molecular processes modulated by SCZ associated genetic variation.

Shared genetic architecture between mental health and the brain functional connectome in the UK Biobank

Psychiatric disorders are complex clinical conditions with large heterogeneity and overlap in symptoms, genetic liability and brain imaging abnormalities. Building on a dimensional conceptualization of mental health, previous studies have reported genetic overlap between psychiatric disorders and population-level mental health, and between psychiatric disorders and brain functional connectivity. Here, in 30,701 participants aged 45-82 from the UK Biobank we map the genetic associations between self-reported mental health and resting-state fMRI-based measures of brain network function. Multivariate Omnibus Statistical Test revealed 10 genetic loci associated with population-level mental symptoms. Next, conjunctional FDR identified 23 shared genetic variants between these symptom profiles and fMRI-based brain network measures. Functional annotation implicated genes involved in brain structure and function, in particular related to synaptic processes such as axonal growth (e.g. NGFR and RHOA). These findings provide further genetic evidence of an association between brain function and mental health traits in the population.

Identifying potential risk genes and pathways for neuropsychiatric and substance use disorders using intermediate molecular mediator information

Neuropsychiatric and substance use disorders (NPSUDs) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait genetic correlations. Genome-wide association studies (GWAS) of NPSUDs yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and molecular mediators (transcript, protein, and methylation abundances) infer the effect of these mediators on risk for disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome-wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes (∼20,000) instead of millions of GWAS SNPs, which leads to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUDs by performing XWAS analyses in two tissues-blood and brain. First, to identify putative causal risk genes, we performed an XWAS using the Summary-data-based Mendelian randomization, which uses GWAS summary statistics, reference xQTL data, and a reference LD panel. Second, given the large comorbidities among NPSUDs and the shared cis-xQTLs between blood and the brain, we improved XWAS signal detection for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUDs. All XWAS signals i) were adjusted for heterogeneity in dependent instruments (HEIDI) (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the major histocompatibility complex region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (FURIN, NEK4, RERE, and ZDHHC5). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Our study revealed an enrichment of XWAS signals in vitamin D and omega-3 gene sets. So, including vitamin D and omega-3 in treatment plans may have a modest but beneficial effect on patients with bipolar disorder.

Interhemispheric differences of pyramidal cells in the primary motor cortices of schizophrenia patients investigated postmortem

Motor disturbances are observed in schizophrenia patients, but the neuroanatomical background is unknown. Our aim was to investigate the pyramidal cells of the primary motor cortex (BA 4) in both hemispheres of postmortem control and schizophrenia subjects-8 subjects in each group-with 2.5-5.5 h postmortem interval. The density and size of the Sternberger monoclonal incorporated antibody 32 (SMI32)-immunostained pyramidal cells in layer 3 and 5 showed no change; however, the proportion of larger pyramidal cells is decreased in layer 5. Giant pyramidal neurons (Betz cells) were investigated distinctively with SMI32- and parvalbumin (PV) immunostainings. In the right hemisphere of schizophrenia subjects, the density of Betz cells was decreased and their PV-immunopositive perisomatic input showed impairment. Part of the Betz cells contained PV in both groups, but the proportion of PV-positive cells has declined with age. The rat model of antipsychotic treatment with haloperidol and olanzapine showed no differences in size and density of SMI32-immunopositive pyramidal cells. Our results suggest that motor impairment of schizophrenia patients may have a morphological basis involving the Betz cells in the right hemisphere. These alterations can have neurodevelopmental and neurodegenerative explanations, but antipsychotic treatment does not explain them.

Structural covariances of prefrontal subregions selectively associate with dopamine-related gene coexpression and schizophrenia

Evidence highlights that dopamine (DA) system dysregulation and prefrontal cortex (PFC) dysfunction may underlie the pathophysiology of schizophrenia. However, the associations among DA genes, PFC morphometry, and schizophrenia have not yet been fully clarified. Based on the brain gene expression dataset from Allen Human Brain Atlas and structural magnetic resonance imaging data (NDIS = 1727, NREP = 408), we first identified 10 out of 22 PFC subregions whose gray matter volume (GMV) covariance profiles were reliably associated with their DA genes coexpression profiles, then four out of the identified 10 PFC subregions demonstrated abnormally increased GMV covariance with the hippocampus, insula, and medial frontal areas in schizophrenia patients (NCASE = 100; NCONTROL = 102). Moreover, based on a schizophrenia postmortem expression dataset, we found that the DA genes coexpression of schizophrenia was significantly reduced between the middle frontal gyrus and hippocampus, in which 21 DA genes showed significantly unsynchronized expression changes, and the 21 genes' brain expression were enriched in brain activity invoked by working memory, reward, speech production, and episodic memory. Our findings indicate the DA genes selectively regulate the structural covariance of PFC subregions by their coexpression profiles, which may underlie the disrupted GMV covariance and impaired cognitive functions in schizophrenia.

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

Cardiovascular health interacts with cognitive and mental health in complex ways, yet little is known about the phenotypic and genetic links of heart-brain systems. We quantified heart-brain connections using multiorgan magnetic resonance imaging (MRI) data from more than 40,000 subjects. Heart MRI traits displayed numerous association patterns with brain gray matter morphometry, white matter microstructure, and functional networks. We identified 80 associated genomic loci (P < 6.09 × 10-10) for heart MRI traits, which shared genetic influences with cardiovascular and brain diseases. Genetic correlations were observed between heart MRI traits and brain-related traits and disorders. Mendelian randomization suggests that heart conditions may causally contribute to brain disorders. Our results advance a multiorgan perspective on human health by revealing heart-brain connections and shared genetic influences.

Genetic patterning for child psychopathology is distinct from that for adults and implicates fetal cerebellar development

Childhood psychiatric symptoms are often diffuse but can coalesce into discrete mental illnesses during late adolescence. We leveraged polygenic scores (PGSs) to parse genomic risk for childhood symptoms and to uncover related neurodevelopmental mechanisms with transcriptomic and neuroimaging data. In independent samples (Adolescent Brain Cognitive Development, Generation R) a narrow cross-disorder neurodevelopmental PGS, reflecting risk for attention deficit hyperactivity disorder, autism, depression and Tourette syndrome, predicted psychiatric symptoms through early adolescence with greater sensitivity than broad cross-disorder PGSs reflecting shared risk across eight psychiatric disorders, the disorder-specific PGS individually or two other narrow cross-disorder (Compulsive, Mood-Psychotic) scores. Neurodevelopmental PGS-associated genes were preferentially expressed in the cerebellum, where their expression peaked prenatally. Further, lower gray matter volumes in cerebellum and functionally coupled cortical regions associated with psychiatric symptoms in mid-childhood. These findings demonstrate that the genetic underpinnings of pediatric psychiatric symptoms differ from those of adult illness, and implicate fetal cerebellar developmental processes that endure through childhood.

Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders

Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.

Altered Rbfox1-Vamp1 pathway and prefrontal cortical dysfunction in schizophrenia

Deficient gamma oscillations in prefrontal cortex (PFC) of individuals with schizophrenia appear to involve impaired inhibitory drive from parvalbumin-expressing interneurons (PVIs). Inhibitory drive from PVIs is regulated, in part, by RNA binding fox-1 homolog 1 (Rbfox1). Rbfox1 is spliced into nuclear or cytoplasmic isoforms, which regulate alternative splicing or stability of their target transcripts, respectively. One major target of cytoplasmic Rbfox1 is vesicle associated membrane protein 1 (Vamp1). Vamp1 mediates GABA release probability from PVIs, and the loss of Rbfox1 reduces Vamp1 levels which in turn impairs cortical inhibition. In this study, we investigated if the Rbfox1-Vamp1 pathway is altered in PVIs in PFC of individuals with schizophrenia by utilizing a novel strategy that combines multi-label in situ hybridization and immunohistochemistry. In the PFC of 20 matched pairs of schizophrenia and comparison subjects, cytoplasmic Rbfox1 protein levels were significantly lower in PVIs in schizophrenia and this deficit was not attributable to potential methodological confounds or schizophrenia-associated co-occurring factors. In a subset of this cohort, Vamp1 mRNA levels in PVIs were also significantly lower in schizophrenia and were predicted by lower cytoplasmic Rbfox1 protein levels across individual PVIs. To investigate the functional impact of Rbfox1-Vamp1 alterations in schizophrenia, we simulated the effect of lower GABA release probability from PVIs on gamma power in a computational model network of pyramidal neurons and PVIs. Our simulations showed that lower GABA release probability reduces gamma power by disrupting network synchrony while minimally affecting network activity. Finally, lower GABA release probability synergistically interacted with lower strength of inhibition from PVIs in schizophrenia to reduce gamma power non-linearly. Together, our findings suggest that the Rbfox1-Vamp1 pathway in PVIs is impaired in schizophrenia and that this alteration likely contributes to deficient PFC gamma power in the illness.

Inferring cell-type-specific causal gene regulatory networks during human neurogenesis

BACKGROUND

Genetic variation influences both chromatin accessibility, assessed in chromatin accessibility quantitative trait loci (caQTL) studies, and gene expression, assessed in expression QTL (eQTL) studies. Genetic variants can impact either nearby genes (cis-eQTLs) or distal genes (trans-eQTLs). Colocalization between caQTL and eQTL, or cis- and trans-eQTLs suggests that they share causal variants. However, pairwise colocalization between these molecular QTLs does not guarantee a causal relationship. Mediation analysis can be applied to assess the evidence supporting causality versus independence between molecular QTLs. Given that the function of QTLs can be cell-type-specific, we performed mediation analyses to find epigenetic and distal regulatory causal pathways for genes within two major cell types of the developing human cortex, progenitors and neurons.

RESULTS

We find that the expression of 168 and 38 genes is mediated by chromatin accessibility in progenitors and neurons, respectively. We also find that the expression of 11 and 12 downstream genes is mediated by upstream genes in progenitors and neurons. Moreover, we discover that a genetic locus associated with inter-individual differences in brain structure shows evidence for mediation of SLC26A7 through chromatin accessibility, identifying molecular mechanisms of a common variant association to a brain trait.

CONCLUSIONS

In this study, we identify cell-type-specific causal gene regulatory networks whereby the impacts of variants on gene expression were mediated by chromatin accessibility or distal gene expression. Identification of these causal paths will enable identifying and prioritizing actionable regulatory targets perturbing these key processes during neurodevelopment.

The shared genetic architecture of smoking behaviours and psychiatric disorders: evidence from a population-based longitudinal study in England

BACKGROUND

Considering the co-morbidity of major psychiatric disorders and intelligence with smoking, to increase our understanding of why some people take up smoking or continue to smoke, while others stop smoking without progressing to nicotine dependence, we investigated the genetic propensities to psychiatric disorders and intelligence as determinants of smoking initiation, heaviness of smoking and smoking cessation in older adults from the general population.

RESULTS

Having utilised data from the English Longitudinal Study of Ageing (ELSA), our results showed that one standard deviation increase in MDD-PGS was associated with increased odds of being a moderate-heavy smoker (odds ratio [OR] = 1.11, SE = 0.04, 95%CI = 1.00-1.24, p = 0.028). There were no other significant associations between SZ-PGS, BD-PGS, or IQ-PGS and smoking initiation, heaviness of smoking and smoking cessation in older adults from the general population in the UK.

CONCLUSIONS

Smoking is a behaviour that does not appear to share common genetic ground with schizophrenia, bipolar disorders, and intelligence in older adults, which may suggest that it is more likely to be modifiable by smoking cessation interventions. Once started to smoke, older adults with a higher polygenic predisposition to major depressive disorders are more likely to be moderate to heavy smokers, implying that these adults may require targeted smoking cessation services.

The genetic architecture of fornix white matter microstructure and their involvement in neuropsychiatric disorders

The fornix is a white matter bundle located in the center of the hippocampaldiencephalic limbic circuit that controls memory and executive functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out a genome-wide association analysis of 30,832 UK Biobank individuals of the six fornix diffusion magnetic resonance imaging (dMRI) traits. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the single nucleotide polymorphisms (SNP), locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in adolescent brain cognitive development (ABCD) cohort. The GWAS identified 63 independent significant variants within 20 genomic loci associated (P < 8.33 × 10^-9) with the six fornix dMRI traits. Geminin coiled-coil domain containing (GMNC) and NUAK family SNF1-like kinase 1 (NUAK1) gene were highlighted, which were found in UKB and replicated in ABCD. The heritability of the six traits ranged from 10% to 27%. Gene mapping strategies identified 213 genes, where 11 were supported by all of four methods. Gene-based analyses revealed pathways relating to cell development and differentiation, with astrocytes found to be significantly enriched. Pleiotropy analyses with eight neurological and psychiatric disorders revealed shared variants, especially with schizophrenia under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of fornix and their relevance in neurological and psychiatric disorders.

Whole transcriptome analysis reveals dysregulation of molecular networks in schizophrenia

To characterize the regulatory relationships between different types of transcripts and the altered molecular networks in schizophrenia (SCZ), we performed a whole transcriptome study by quantifying mRNAs, long noncoding RNAs (lncRNAs), miRNAs, and circular RNAs (circRNAs) in the same individuals simultaneously. A total of 807 dysregulated genes showed differential expression in SCZ cases compared with controls. Network-based analysis revealed dysregulation of molecular networks in SCZ. Finally, integration of the transcriptome data with published data identified promising SCZ candidate genes. Our study reveals that dysregulated molecular networks and regulatory relationships between different types of transcript may have a role in SCZ.

Single-cell and spatial transcriptomics: deciphering brain complexity in health and disease

In the past decade, single-cell technologies have proliferated and improved from their technically challenging beginnings to become common laboratory methods capable of determining the expression of thousands of genes in thousands of cells simultaneously. The field has progressed by taking the CNS as a primary research subject - the cellular complexity and multiplicity of neuronal cell types provide fertile ground for the increasing power of single-cell methods. Current single-cell RNA sequencing methods can quantify gene expression with sufficient accuracy to finely resolve even subtle differences between cell types and states, thus providing a great tool for studying the molecular and cellular repertoire of the CNS and its disorders. However, single-cell RNA sequencing requires the dissociation of tissue samples, which means that the interrelationships between cells are lost. Spatial transcriptomic methods bypass tissue dissociation and retain this spatial information, thereby allowing gene expression to be assessed across thousands of cells within the context of tissue structural organization. Here, we discuss how single-cell and spatially resolved transcriptomics have been contributing to unravelling the pathomechanisms underlying brain disorders. We focus on three areas where we feel these new technologies have provided particularly useful insights: selective neuronal vulnerability, neuroimmune dysfunction and cell-type-specific treatment response. We also discuss the limitations and future directions of single-cell and spatial RNA sequencing technologies.

Exploratory factor analysis of shared and specific genetic associations in depression and anxiety

BACKGROUND

Previous genetic studies of anxiety and depression were mostly based on independent phenotypes. This study aims to investigate the shared and specific genetic structure between anxiety and depression.

METHOD

To identify the underlying factors of Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-9 (PHQ-9), and their combined scale (joint scale), we employed exploratory factor analysis (EFA) using the eigenvalue of parallel analysis. Subsequently, we conducted a genome-wide association study (GWAS) for these factors. In addition, we utilized LD Score Regression (LDSC) to determine the genetic correlations between the identified factors and four common mental disorders, three sleep phenotypes, and other traits that have been previously linked to anxiety and depression.

RESULTS

The EFA uncovered two factors for the GAD-7 scale, namely nervousness and disturbance, two factors for the PHQ-9 scale, namely negative affect and sleep/appetite disturbance, and four factors for the joint scale, specifically nervousness, anhedonia, sleep/appetite disturbance, and fidget. We identified two genome-wide significant genomic loci, with overlap across GAD-7 factor 1 and joint scale factor 1: rs148579586 (P_GAD-7 = 1.365 × 10^-09, P_{Joint scale} = 1.434 × 1^0-09) and rs201074060 (P_GAD-7 = 3.672 × 10^-09, P_{Joint scale} = 3.824 × 10^-09). Genetic correlations in factors ranged from 0.722 to 1.000 (all p < 1.786 × 10^-3) with 27 of 28 correlations being significantly smaller than one. The genetic correlations with external phenotypes showed small variation across the eight factors.

CONCLUSION

Unidimensional structures can provide more precise scores, which can aid in identifying the shared and specific genetic associations between anxiety and depression. This is a crucial step in characterizing the genetic structure of these conditions and their co-occurrence.

The molecular pathology of schizophrenia: an overview of existing knowledge and new directions for future research

Despite enormous efforts employing various approaches, the molecular pathology in the schizophrenia brain remains elusive. On the other hand, the knowledge of the association between the disease risk and changes in the DNA sequences, in other words, our understanding of the genetic pathology of schizophrenia, has dramatically improved over the past two decades. As the consequence, now we can explain more than 20% of the liability to schizophrenia by considering all analyzable common genetic variants including those with weak or no statistically significant association. Also, a large-scale exome sequencing study identified single genes whose rare mutations substantially increase the risk for schizophrenia, of which six genes (SETD1A, CUL1, XPO7, GRIA3, GRIN2A, and RB1CC1) showed odds ratios larger than ten. Based on these findings together with the preceding discovery of copy number variants (CNVs) with similarly large effect sizes, multiple disease models with high etiological validity have been generated and analyzed. Studies of the brains of these models, as well as transcriptomic and epigenomic analyses of patient postmortem tissues, have provided new insights into the molecular pathology of schizophrenia. In this review, we overview the current knowledge acquired from these studies, their limitations, and directions for future research that may redefine schizophrenia based on biological alterations in the responsible organ rather than operationalized criteria.

Perturbed iron biology in the prefrontal cortex of people with schizophrenia

Despite loss of grey matter volume and emergence of distinct cognitive deficits in young adults diagnosed with schizophrenia, current treatments for schizophrenia do not target disruptions in late maturational reshaping of the prefrontal cortex. Iron, the most abundant transition metal in the brain, is essential to brain development and function, but in excess, it can impair major neurotransmission systems and lead to lipid peroxidation, neuroinflammation and accelerated aging. However, analysis of cortical iron biology in schizophrenia has not been reported in modern literature. Using a combination of inductively coupled plasma-mass spectrometry and western blots, we quantified iron and its major-storage protein, ferritin, in post-mortem prefrontal cortex specimens obtained from three independent, well-characterised brain tissue resources. Compared to matched controls (n = 85), among schizophrenia cases (n = 86) we found elevated tissue iron, unlikely to be confounded by demographic and lifestyle variables, by duration, dose and type of antipsychotic medications used or by copper and zinc levels. We further observed a loss of physiologic age-dependent iron accumulation among people with schizophrenia, in that the iron level among cases was already high in young adulthood. Ferritin, which stores iron in a redox-inactive form, was paradoxically decreased in individuals with the disorder. Such iron-ferritin uncoupling could alter free, chemically reactive, tissue iron in key reasoning and planning areas of the young-adult schizophrenia cortex. Using a prediction model based on iron and ferritin, our data provide a pathophysiologic link between perturbed cortical iron biology and schizophrenia and indicate that achievement of optimal cortical iron homeostasis could offer a new therapeutic target.

The contribution of Neanderthal introgression and natural selection to neurodegenerative diseases

Humans are thought to be more susceptible to neurodegeneration than equivalently-aged primates. It is not known whether this vulnerability is specific to anatomically-modern humans or shared with other hominids. The contribution of introgressed Neanderthal DNA to neurodegenerative disorders remains uncertain. It is also unclear how common variants associated with neurodegenerative disease risk are maintained by natural selection in the population despite their deleterious effects. In this study, we aimed to quantify the genome-wide contribution of Neanderthal introgression and positive selection to the heritability of complex neurodegenerative disorders to address these questions. We used stratified-linkage disequilibrium score regression to investigate the relationship between five SNP-based signatures of natural selection, reflecting different timepoints of evolution, and genome-wide associated variants of the three most prevalent neurodegenerative disorders: Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease. We found no evidence for enrichment of positively-selected SNPs in the heritability of Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease, suggesting that common deleterious disease variants are unlikely to be maintained by positive selection. There was no enrichment of Neanderthal introgression in the SNP-heritability of these disorders, suggesting that Neanderthal admixture is unlikely to have contributed to disease risk. These findings provide insight into the origins of neurodegenerative disorders within the evolution of Homo sapiens and addresses a long-standing debate, showing that Neanderthal admixture is unlikely to have contributed to common genetic risk of neurodegeneration in anatomically-modern humans.

Local genetic correlations exist among neurodegenerative and neuropsychiatric diseases

Genetic correlation ([Formula: see text]) between traits can offer valuable insight into underlying shared biological mechanisms. Neurodegenerative diseases overlap neuropathologically and often manifest comorbid neuropsychiatric symptoms. However, global [Formula: see text] analyses show minimal [Formula: see text] among neurodegenerative and neuropsychiatric diseases. Importantly, local [Formula: see text] s can exist in the absence of global relationships. To investigate this possibility, we applied LAVA, a tool for local [Formula: see text] analysis, to genome-wide association studies of 3 neurodegenerative diseases (Alzheimer's disease, Lewy body dementia and Parkinson's disease) and 3 neuropsychiatric disorders (bipolar disorder, major depressive disorder and schizophrenia). We identified several local [Formula: see text] s missed in global analyses, including between (i) all 3 neurodegenerative diseases and schizophrenia and (ii) Alzheimer's and Parkinson's disease. For those local [Formula: see text] s identified in genomic regions containing disease-implicated genes, such as SNCA, CLU and APOE, incorporation of expression quantitative trait loci identified genes that may drive genetic overlaps between diseases. Collectively, we demonstrate that complex genetic relationships exist among neurodegenerative and neuropsychiatric diseases, highlighting putative pleiotropic genomic regions and genes. These findings imply sharing of pathogenic processes and the potential existence of common therapeutic targets.

The functional and evolutionary impacts of human-specific deletions in conserved elements

Conserved genomic sequences disrupted in humans may underlie uniquely human phenotypic traits. We identified and characterized 10,032 human-specific conserved deletions (hCONDELs). These short (average 2.56 base pairs) deletions are enriched for human brain functions across genetic, epigenomic, and transcriptomic datasets. Using massively parallel reporter assays in six cell types, we discovered 800 hCONDELs conferring significant differences in regulatory activity, half of which enhance rather than disrupt regulatory function. We highlight several hCONDELs with putative human-specific effects on brain development, including HDAC5, CPEB4, and PPP2CA. Reverting an hCONDEL to the ancestral sequence alters the expression of LOXL2 and developmental genes involved in myelination and synaptic function. Our data provide a rich resource to investigate the evolutionary mechanisms driving new traits in humans and other species.

Brain transcriptome-wide association study implicates novel risk genes underlying schizophrenia risk

BACKGROUND

To identify risk genes whose expression are regulated by the reported risk variants and to explore the potential regulatory mechanism in schizophrenia (SCZ).

METHODS

We systematically integrated three independent brain expression quantitative traits (eQTLs) (CommonMind, GTEx, and BrainSeq Phase 2, a total of 1039 individuals) and GWAS data (56 418 cases and 78 818 controls), with the use of transcriptome-wide association study (TWAS). Diffusion magnetic resonance imaging was utilized to quantify the integrity of white matter bundles and determine whether polygenic risk of novel genes linked to brain structure was present in patients with first-episode antipsychotic SCZ.

RESULTS

TWAS showed that eight risk genes (CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, PCDHA8, THOC7, and TYW5) reached transcriptome-wide significance (TWS) level. These findings were confirmed by an independent integrative approach (i.e. Sherlock). We further conducted conditional analyses and identified the potential risk genes that driven the TWAS association signal in each locus. Gene expression analysis showed that several TWS genes (including CORO7, DDAH2, DDHD2, ELAC2, GLT8D1, THOC7 and TYW5) were dysregulated in the dorsolateral prefrontal cortex of SCZ cases compared with controls. TWS genes were mainly expressed on the surface of glutamatergic neurons, GABAergic neurons, and microglia. Finally, SCZ cases had a substantially greater TWS genes-based polygenic risk (PRS) compared to controls, and we showed that fractional anisotropy of the cingulum-hippocampus mediates the influence of TWS genes PRS on SCZ.

CONCLUSIONS

Our findings identified novel SCZ risk genes and highlighted the importance of the TWS genes in frontal-limbic dysfunctions in SCZ, indicating possible therapeutic targets.

Using allele scores to identify confounding by reverse causation: studies of alcohol consumption as an exemplar

BACKGROUND

Mendelian randomization (MR) is a form of instrumental variable analysis used to investigate causality using observational data. Another important, although less frequently applied, use of this technique is to investigate confounding due to reverse causality.

METHODS

We used a form of reverse MR and data from UK Biobank in a proof-of-principle study to investigate confounding due to reverse causation. Here we focus on the association between alcohol consumption (exposure) and outcomes including educational attainment, and physical and mental health. First, we examined the observational relationship between alcohol consumption and these outcomes. Allele scores were then derived for educational attainment, and physical and mental health, and the association with alcohol consumption (as the outcome) was explored. Sample sizes ranged from 114 941-336 473 in observational analyses and 142 093-336 818 in genetic analyses.

RESULTS

Conventional observational analyses indicated associations between alcohol consumption and a number of outcomes (e.g. neuroticism, body mass index, educational attainment). Analyses using allele scores suggested evidence of reverse causation for several of these relationships (in particular physical health and educational attainment).

CONCLUSION

Allele scores allow us to investigate reverse causation in observational studies. Our findings suggest that observed associations implying beneficial effects of alcohol consumption may be due to confounding by reverse causation in many cases.

Brain functional connectivity mirrors genetic pleiotropy in psychiatric conditions

Pleiotropy occurs when a genetic variant influences more than one trait. This is a key property of the genomic architecture of psychiatric disorders and has been observed for rare and common genomic variants. It is reasonable to hypothesize that the microscale genetic overlap (pleiotropy) across psychiatric conditions and cognitive traits may lead to similar overlaps at the macroscale brain level such as large-scale brain functional networks. We took advantage of brain connectivity, measured by resting-state functional MRI to measure the effects of pleiotropy on large-scale brain networks, a putative step from genes to behaviour. We processed nine resting-state functional MRI datasets including 32 726 individuals and computed connectome-wide profiles of seven neuropsychiatric copy-number-variants, five polygenic scores, neuroticism and fluid intelligence as well as four idiopathic psychiatric conditions. Nine out of 19 pairs of conditions and traits showed significant functional connectivity correlations (rFunctional connectivity), which could be explained by previously published levels of genomic (rGenetic) and transcriptomic (rTranscriptomic) correlations with moderate to high concordance: rGenetic-rFunctional connectivity = 0.71 [0.40-0.87] and rTranscriptomic-rFunctional connectivity = 0.83 [0.52; 0.94]. Extending this analysis to functional connectivity profiles associated with rare and common genetic risk showed that 30 out of 136 pairs of connectivity profiles were correlated above chance. These similarities between genetic risks and psychiatric disorders at the connectivity level were mainly driven by the overconnectivity of the thalamus and the somatomotor networks. Our findings suggest a substantial genetic component for shared connectivity profiles across conditions and traits, opening avenues to delineate general mechanisms-amenable to intervention-across psychiatric conditions and genetic risks.

Characterization of altered molecular mechanisms in Parkinson's disease through cell type-resolved multiomics analyses

Parkinson's disease (PD) is a progressive neurodegenerative disorder. However, cell type-dependent transcriptional regulatory programs responsible for PD pathogenesis remain elusive. Here, we establish transcriptomic and epigenomic landscapes of the substantia nigra by profiling 113,207 nuclei obtained from healthy controls and patients with PD. Our multiomics data integration provides cell type annotation of 128,724 cis-regulatory elements (cREs) and uncovers cell type-specific dysregulations in cREs with a strong transcriptional influence on genes implicated in PD. The establishment of high-resolution three-dimensional chromatin contact maps identifies 656 target genes of dysregulated cREs and genetic risk loci, uncovering both potential and known PD risk genes. Notably, these candidate genes exhibit modular gene expression patterns with unique molecular signatures in distinct cell types, highlighting altered molecular mechanisms in dopaminergic neurons and glial cells including oligodendrocytes and microglia. Together, our single-cell transcriptome and epigenome reveal cell type-specific disruption in transcriptional regulations related to PD.

Incorporating functional annotation with bilevel continuous shrinkage for polygenic risk prediction

Background

Genetic variants can contribute differently to trait heritability by their functional categories, and recent studies have shown that incorporating functional annotation can improve the predictive performance of polygenic risk scores (PRSs). In addition, when only a small proportion of variants are causal variants, PRS methods that employ a Bayesian framework with shrinkage can account for such sparsity. It is possible that the annotation group level effect is also sparse. However, the number of PRS methods that incorporate both annotation information and shrinkage on effect sizes is limited. We propose a PRS method, PRSbils, which utilizes the functional annotation information with a bilevel continuous shrinkage prior to accommodate the varying genetic architectures both on the variant-specific level and on the functional annotation level.

Results

We conducted simulation studies and investigated the predictive performance in settings with different genetic architectures. Results indicated that when there was a relatively large variability of group-wise heritability contribution, the gain in prediction performance from the proposed method was on average 8.0% higher AUC compared to the benchmark method PRS-CS. The proposed method also yielded higher predictive performance compared to PRS-CS in settings with different overlapping patterns of annotation groups and obtained on average 6.4% higher AUC. We applied PRSbils to binary and quantitative traits in three real world data sources (the UK Biobank, the Michigan Genomics Initiative (MGI), and the Korean Genome and Epidemiology Study (KoGES)), and two sources of annotations: ANNOVAR, and pathway information from the Kyoto Encyclopedia of Genes and Genomes (KEGG), and demonstrated that the proposed method holds the potential for improving predictive performance by incorporating functional annotations.

Conclusions

By utilizing a bilevel shrinkage framework, PRSbils enables the incorporation of both overlapping and non-overlapping annotations into PRS construction to improve the performance of genetic risk prediction. The software is available at https://github.com/styvon/PRSbils.