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Treatment-resistant depression (TRD) is a severe form of major depressive disorder (MDD) with substantial public health impact and poor treatment outcome. Treatment outcome in MDD is significantly heritable, but genome-wide association studies have failed to identify replicable common marker alleles, suggesting a potential role for uncommon variants. Here we investigated the hypothesis that uncommon, putatively functional genetic variants are associated with TRD. Whole-exome sequencing data was obtained from 182 TRD cases and 2021 psychiatrically healthy controls. After quality control, the remaining 149 TRD cases and 1976 controls were analyzed with tests designed to detect excess burdens of uncommon variants. At the gene level, 5 genes, ZNF248 , PRKRA , PYHIN1 , SLC7A8 , and STK19 each carried exome-wide significant excess burdens of variants in TRD cases (q < 0.05). Analysis of 41 pre-selected gene sets suggested an excess of uncommon, functional variants among genes involved in lithium response. Among the genes identified in previous TRD studies, ZDHHC3 was also significant in this sample after multiple test correction. ZNF248 and STK19 are involved in transcriptional regulation, PHYIN1 and PRKRA are involved in immune response, SLC7A8 is associated with thyroid hormone transporter activity, and ZDHHC3 regulates synaptic clustering of GABA and glutamate receptors. These results implicate uncommon, functional alleles in TRD and suggest promising novel targets for future research.

Bipolar disorder (BD) is one of the most heritable mental illnesses, but the elucidation of its genetic basis has proven to be a very challenging endeavor. Genome-Wide Association Studies (GWAS) have transformed our understanding of BD, providing the first reproducible evidence of specific genetic markers and a highly polygenic architecture that overlaps with that of schizophrenia, major depression, and other disorders. Individual GWAS markers appear to confer little risk, but common variants together account for about 25% of the heritability of BD. A few higher-risk associations have also been identified, such as a rare copy number variant on chromosome 16p11.2. Large scale next-generation sequencing studies are actively searching for other alleles that confer substantial risk. As our understanding of the genetics of BD improves, there is growing optimism that some clear biological pathways will emerge, providing a basis for future studies aimed at molecular diagnosis and novel therapeutics.

Despite strong evidence of heritability and growing discovery of genetic markers for major mental illness, little is known about how gene expression in the brain differs across psychiatric diagnoses, or how known genetic risk factors shape these differences. Here we investigate expressed genes and gene transcripts in postmortem subgenual anterior cingulate cortex (sgACC), a key component of limbic circuits linked to mental illness. RNA obtained postmortem from 200 donors diagnosed with bipolar disorder, schizophrenia, major depression, or no psychiatric disorder was deeply sequenced to quantify expression of over 85,000 gene transcripts, many of which were rare. Case–control comparisons detected modest expression differences that were correlated across disorders. Case–case comparisons revealed greater expression differences, with some transcripts showing opposing patterns of expression between diagnostic groups, relative to controls. The ~250 rare transcripts that were differentially-expressed in one or more disorder groups were enriched for genes involved in synapse formation, cell junctions, and heterotrimeric G-protein complexes. Common genetic variants were associated with transcript expression (eQTL) or relative abundance of alternatively spliced transcripts (sQTL). Common genetic variants previously associated with disease risk were especially enriched for sQTLs, which together accounted for disproportionate fractions of diagnosis-specific heritability. Genetic risk factors that shape the brain transcriptome may contribute to diagnostic differences between broad classes of mental illness.

As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the “Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders” consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals.

Many psychiatric disorders are heritable, but the molecular consequences of genetic risk remain difficult to resolve, in part due to environmental confounds and the complexity of transcriptomic data. This challenge impedes therapeutic development, which relies on integrating genetic and genomic insights. Here, we integrate diagnosis, toxicological exposure, and gene expression to clarify disease-associated transcriptomic patterns in the subgenual anterior cingulate cortex (sgACC), a brain region implicated in affective regulation and psychiatric illness. We applied group regularized canonical correlation analysis (GRCCA)—a multivariate regression method that models interdependent features—to deeply sequenced bulk RNA-seq data from individuals with bipolar disorder (BD; N  = 35), major depression (MDD; N  = 51), schizophrenia (SCZ; N  = 44), and controls ( N  = 55). Toxicology data from 17 known compounds were included to assess the relative contribution of known environmental exposures. Case-control expression changes were also analyzed using traditional differential gene expression (DGE) analysis to compare biological interpretability across methods. Gene set enrichment analyses evaluated enrichments for neuropsychiatric risk genes, gene ontology pathways, and cell type markers. GRCCA identified a latent variable significantly associated with schizophrenia ( p perm  = 0.001). This expression pattern was enriched for upregulated neuronal pathways, downregulated immune processes, and genes within loci associated with schizophrenia by GWAS. While DGE results were correlated ( r  = 0.43; p perm  = 1.0 × 10 −4 ) and enriched for similar functional pathways, GRCCA showed stronger alignment with schizophrenia risk genes implicated by genome-wide association studies. Together, these findings define a schizophrenia-associated expression gradient in the sgACC and illustrate how multivariate integration can refine transcriptomic signals in the context of complex psychiatric disease.

Recent postmortem transcriptomic studies of schizophrenia (SCZ) have shown hundreds of differentially expressed genes. However, the extent to which these gene expression changes reflect antipsychotic drug (APD) exposure remains uncertain. We compared differential gene expression in the prefrontal cortex of SCZ patients who tested positive for APDs at the time of death with SCZ patients who did not. APD exposure was associated with numerous changes in the brain transcriptome, especially among SCZ patients on atypical APDs. Brain transcriptome data from macaques chronically treated with APDs showed that APDs affect the expression of many functionally relevant genes, some of which show expression changes in the same directions as those observed in SCZ. Co-expression modules enriched for synaptic function showed convergent patterns between SCZ and some of the APD effects, while those associated with inflammation and glucose metabolism exhibited predominantly divergent patterns between SCZ and APD effects. In contrast, major cell-type shifts inferred in SCZ were primarily unaffected by APD use. These results show that APDs may confound SCZ-associated gene expression changes in postmortem brain tissue. Disentangling these effects will help identify causal genes and improve our neurobiological understanding of SCZ.

Genome-wide association studies (GWAS) have identified several common variants associated with bipolar disorder (BD), but the biological meaning of these findings remains unclear. Integrative genomics-the integration of GWAS signals with gene expression data-may illuminate genes and gene networks that have key roles in the pathogenesis of BD. We applied weighted gene co-expression network analysis (WGCNA), which exploits patterns of co-expression among genes, to brain transcriptome data obtained by sequencing of poly-A RNA derived from postmortem dorsolateral prefrontal cortex from people with BD, along with age- and sex-matched controls. WGCNA identified 33 gene modules. Many of the modules corresponded closely to those previously reported in human cortex. Three modules were associated with BD, enriched for genes differentially expressed in BD, and also enriched for signals in prior GWAS of BD. Functional analysis of genes within these modules revealed significant enrichment of several functionally related sets of genes, especially those involved in the postsynaptic density (PSD). These results provide convergent support for the hypothesis that dysregulation of genes involved in the PSD is a key factor in the pathogenesis of BD. If replicated in larger samples, these findings could point toward new therapeutic targets for BD.

Treatment-resistant depression (TRD) is associated with worse clinical outcomes and longer course of illness. However, TRD is more difficult to model in animal phenotypes, suggesting that other experimental and translational models must be considered to properly address and research novel therapeutics. Reelin, an endogenous glycoprotein downregulated in depression, has shown rapid antidepressant-like effects akin to those of the N-methyl-D-aspartate receptor (NMDAR) antagonist ketamine. Interestingly, the antidepressant-like effects of both ketamine and reelin affect mechanistic target of rapamycin complex 1 (mTORC1) activity and that of its related downstream signalers. (2  R ,6  R )-hydroxynorketamine (HNK) is a major metabolite of ketamine that, at therapeutic levels, appears to activate mTORC1 without antagonizing NMDARs. To model the effects of (2  R ,6  R )-HNK and reelin on neurons from TRD participants, induced pluripotent stem cells (iPSCs) were reprogrammed from peripheral blood mononuclear cells collected from five females with TRD (mean=40.2 yrs) and then differentiated into cortical neurons. In iPSC-derived neurons from TRD participants, 50 nM reelin and 1 µM (2  R ,6  R )-HNK had similar effects on the protein expression of GluA1, PSD-95, Dab1, Synapsin I, and p-ERK, with concentration-dependent increases observed at one hour that significantly decreased by 24 h. RNA sequencing revealed similar changes in gene expression between 50 nM reelin and 1 µM (2  R ,6  R )-HNK at one hour, although only reelin upregulated mTORC1 signaling. While this work remains preliminary, the results suggest that iPSC-derived neurons could provide a valuable in vitro model to study TRD and hold promise for evaluating novel therapeutics such as (2  R ,6  R )-HNK and reelin. Clinicaltrials.gov : NCT02484456

As large-scale genome sequencing technology advances, concerns surrounding the reporting of individual findings to study volunteers have grown and fueled controversy. This is especially true in mental health research, where the clinical importance of sequencing results is particularly unclear. The ethical, legal, and social issues are being widely debated, but less is known about the attitudes of actual study volunteers toward sequencing studies or what they wish to learn about their DNA sequence and its health implications. This study provides information on psychiatric research volunteers' attitudes, beliefs, and concerns with respect to participation in DNA sequencing studies and reporting of individual results. We conducted a pilot study using a questionnaire that we developed to assess what information volunteers in an ongoing family study of bipolar disorder would like to receive if they underwent genome sequencing, what they would do with that information, and what concerns they may have. Almost all of the respondents were willing to participate in genome sequencing. Most respondents wished to be informed about all their health-related genetic risks, including risks for diseases without known prevention or treatment. However, few respondents felt well informed about the nature of genome sequencing or its implications for their health, insurability, or offspring. Despite generally positive attitudes toward genome sequencing among study volunteers, most are not fully aware of the special issues raised by genome sequencing. The attitudes of study volunteers should be considered in the debate about the reporting of individual findings from genome sequencing.

Genome-wide (GWAS) and copy number variant (CNV) association studies have reproducibly identified numerous risk alleles associated with bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ), but biological characterization of these alleles lags gene discovery, owing to the inaccessibility of live human brain cells and inadequate animal models for human psychiatric conditions. Human-derived induced pluripotent stem cells (iPSCs) provide a renewable cellular reagent that can be differentiated into living, disease-relevant cells and 3D brain organoids carrying the full complement of genetic variants present in the donor germline. Experimental studies of iPSC-derived cells allow functional characterization of risk alleles, establishment of causal relationships between genes and neurobiology, and screening for novel therapeutics. Here we report the creation and availability of an iPSC resource comprising clinical, genomic, and cellular data obtained from genetically isolated families with BD and related conditions. Results from the first 324 study participants, 61 of whom have validated pluripotent clones, show enrichment of rare single nucleotide variants and CNVs overlapping many known risk genes and pathogenic CNVs. This growing iPSC resource is available to scientists pursuing functional genomic studies of BD and related conditions.