Common mitochondrial DNA (mtDNA) deletions are large structural variants in the mitochondrial genome that accumulate in metabolically active tissues with age and have been investigated in various diseases. We applied the Splice-Break2 pipeline (designed for high-throughput quantification of mtDNA deletions) to human RNA-Seq datasets and describe the methodological considerations for evaluating common deletions in bulk, single-cell, and spatial transcriptomics datasets. A robust evaluation of 1570 samples from 14 RNA-Seq studies showed: (i) the abundance of some common deletions detected in PCR-amplified mtDNA correlates with levels observed in RNA-Seq data; (ii) RNA-Seq library preparation method has a strong effect on deletion detection; (iii) deletions had a significant, positive correlation with age in brain and muscle; (iv) deletions were enriched in cortical grey matter, specifically in layers 3 and 5; and (v) brain regions with dopaminergic neurons (i.e., substantia nigra, ventral tegmental area, and caudate nucleus) had remarkable enrichment of common mtDNA deletions.

Transcription factors (TFs) orchestrate gene expression programs crucial for brain function, but we lack detailed information about TF binding in human brain tissue. We generated a multiomic resource (ChIP-seq, ATAC-seq, RNA-seq, DNA methylation) on bulk tissues and sorted nuclei from several postmortem brain regions, including binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of high TF occupancy regions. Further, predictive TF binding models demonstrate a bias for these high-occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Binding sites for TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. This work, titled BrainTF, is a powerful resource for future studies seeking to understand the roles of specific TFs in regulating gene expression in the human brain.

Transcription Factors (TFs) influence gene expression by facilitating or disrupting the formation of transcription initiation machinery at particular genomic loci. Because genomic localization of TFs is in part driven by TF recognition of DNA sequence, variation in TF binding sites can disrupt TF-DNA associations and affect gene regulation. To identify variants that impact TF binding in human brain tissues, we quantified allele bias for 93 TFs analyzed with ChIP-seq experiments of multiple structural brain regions from two donors. Using graph genomes constructed from phased genomic sequence data, we compared ChIP-seq signal between alleles at heterozygous variants within each tissue sample from each donor. Comparison of results from different brain regions within donors and the same regions between donors provided measures of allele bias reproducibility. We identified thousands of DNA variants that show reproducible bias in ChIP-seq for at least one TF. We found that alleles that are rarer in the general population were more likely than common alleles to exhibit large biases, and more frequently led to reduced TF binding. Combining ChIP-seq with RNA-seq, we identified TF-allele interaction biases with RNA bias in a phased allele linked to 6,709 eQTL variants identified in GTEx data, 3,309 of which were found in neural contexts. Our results provide insights into the effects of both common and rare variation on gene regulation in the brain. These findings can facilitate mechanistic understanding of cis-regulatory variation associated with biological traits, including disease.

Objective: This study assessed the proteomic profiles of cytokines and chemokines in individuals with moderate to severe depression, with or without comorbid medical disorders, compared to healthy controls. Two proteomic multiplex platforms were employed for this purpose. Metods: An immunofluorescent multiplex platform and an aptamer-based method were used to evaluate 32 protein analytes from 153 individuals with moderate to severe major depressive disorder (MDD) and healthy controls (HCs). The study focused on determining the level of agreement between the two platforms and evaluating the ability of individual analytes and principal components (PCs) to differentiate between the MDD and HC groups. Additionally, the study investigated the relationship between PCs consisting of chemokines and cytokines and comorbid inflammatory and cardiometabolic diseases. Findings: Analysis revealed a small or moderate correlation between 47% of the analytes measured by the two platforms. Two proteomic profiles were identified that differentiated individuals with moderate to severe MDD from HCs. High eotaxin, age, BMI, IP-10, or IL-10 characterized profile 1. This profile was associated with several cardiometabolic risk factors, including hypertension, hyperlipidemia, and type 2 diabetes. Profile 2 is characterized by higher age, BMI, interleukins, and a strong negative loading for eotaxin. This profile was associated with inflammation but not cardiometabolic risk factors. Conclusion: This study provides further evidence that proteomic profiles can be used to identify potential biomarkers and pathways associated with MDD and comorbidities. Our findings suggest that MDD is associated with distinct profiles of proteins that are also associated with cardiometabolic risk factors, inflammation, and obesity. In particular, the chemokines eotaxin and IP-10 appear to play a role in the relationship between MDD and cardiometabolic risk factors. These findings suggest that a focus on the interplay between MDD and comorbidities may be useful in identifying potential targets for intervention and improving overall health outcomes.

Transcription factors (TFs) orchestrate gene expression programs crucial for cell physiology, but our knowledge of their function in the brain is limited. Using bulk tissues and sorted nuclei from multiple human post-mortem brain regions, we generated a multi-omic resource (1121 total experiments) that includes binding maps for more than 100 TFs. We demonstrate improved measurements of TF activity, including motif recognition and gene expression modeling, upon identification and removal of regions of high TF occupancy. Further, we find that predictive TF binding models demonstrate a bias for these high occupancy sites. Neuronal TFs SATB2 and TBR1 bind unique regions depleted for such sites and promote neuronal gene expression. Several TFs, including TBR1 and PKNOX1, are enriched for risk variants associated with neuropsychiatric disorders, predominantly in neurons. These data are a powerful resource for future studies seeking to understand the role of TFs in epigenetic regulation in the human brain.

Mitochondrial dysfunction is a neurobiological phenomenon implicated in the pathophysiology of schizophrenia and bipolar disorder that can synergistically affect synaptic neurotransmission. We hypothesized that schizophrenia and bipolar disorder share molecular alterations at the mitochondrial and synaptic levels. Mitochondria DNA (mtDNA) copy number (CN), mtDNA common deletion (CD), mtDNA total deletion, complex I activity, synapse number, and synaptic mitochondria number were studied in the postmortem human dorsolateral prefrontal cortex (DLPFC), superior temporal gyrus (STG), primary visual cortex (V1), and nucleus accumbens (NAc) of controls (CON), and subjects with schizophrenia (SZ), and bipolar disorder (BD). The results showed (i) the mtDNA CN is significantly higher in DLPFC of both SZ and BD, decreased in the STG of BD, and unaltered in V1 and NAc of both SZ and BD; (ii) the mtDNA CD is significantly higher in DLPFC of BD while unaltered in STG, V1, and NAc of both SZ and BD; (iii) The total deletion burden is significantly higher in DLPFC in both SZ and BD while unaltered in STG, V1, and NAc of SZ and BD; (iv) Complex I activity is significantly lower in DLPFC of both SZ and BD, which is driven by the presence of medications, with no alteration in STG, V1, and NAc. In addition, complex I protein concentration, by ELISA, was decreased across three cortical regions of SZ and BD subjects; (v) The number of synapses is decreased in DLPFC of both SZ and BD, while the synaptic mitochondria number was significantly lower in female SZ and female BD compared to female controls. Overall, these findings will pave the way to understand better the pathophysiology of schizophrenia and bipolar disorder for therapeutic interventions.

Every year ~800,000 individuals worldwide and 48,000 in the United States (US) alone lose their lives to suicide (Centers for Disease Control and Prevention).In the US, suicide rates have dramatically increased by 35% since 2016 [1] despite efforts to curve the suicide epidemic.These statistics underscore that suicide is a major public health issue requiring increased attention and the urgent need for the development of rapid, novel, and reliable strategies for the identification of individuals at high risk for suicide early enough to intervene in a timely manner.Major depressive disorder (MDD) is the most common psychiatric diagnosis among suicide victims [2] but only a subset of depressed patients ever actually commit suicide [3].Approximately 45% of suicide victims visit a clinician in the month preceding their suicide and a third see a healthcare professional within the week of death [4].There is a lack of easily available, reliable, and fast tools to determine suicide risk throughout these visits and a bloodbased suicide biomarker screen could be of great use to identify at risk patients.Previous biomarker investigations have been conducted in subjects who died by suicide with various psychiatric diagnoses and investigated either blood or brain.Using both brain tissue and blood from a postmortem cohort consisting of MDD patients who died by suicide (MDD-S), MDD patients who died of other causes (MDD-NS), and non-psychiatric controls (C) we explored gene expression differences unique to suicide victims [5].We used a custom NanoString assay, a technology not affected by RNA degradation, which is a concern with non-preserved blood and postmortem brain tissue.We identified 14 highly significant genes to be differentially expressed (DEG) in the blood of depressed suicides, with four of these also showing significant changes in the brain of MDD-S when compared to MDD-NS.The top six DEGs in suicide blood are: PER3, MTPAP, SLC25A26, CD19, SOX9, and GAR1.Of course, our identified biomarker will require validation in prospective clinical cohorts, and its ability to classify clinical gene expression profiles for assessing suicide risk needs to be evaluated using predictive algorithms in larger samples.The use of nonpreserved blood is of critical importance because many labs, clinics, and/or coroners offices may not have access to blood tubes specific for RNA preservation or may already have previously collected blood tubes that can be used for a posteriori prediction studies.Our findings clearly show that within the context of MDD, suicide victims have a gene expression signature distinct from non-suicides, which includes genes involved in stress response, polyamine metabolism, immune response, and telomere maintenance.While encouraging, future studies using cell-specific gene expression profiling, in brain and blood, may uncover additional suicide-specific molecular phenotypes since our findings suggest alterations in suicides that are specific to immune cell populations.Brain-blood comparisons of molecular signatures are particularly useful for the development of clinical biomarkers for neuropsychiatric disorders.These results bring us one step closer to the development of a molecular test to identify patients at highest risk for suicide.

Suicides have increased to over 48,000 deaths yearly in the United States. Major depressive disorder (MDD) is the most common diagnosis among suicides, and identifying those at the highest risk for suicide is a pressing challenge. The objective of this study is to identify changes in gene expression associated with suicide in brain and blood for the development of biomarkers for suicide. Blood and brain were available for 45 subjects (53 blood samples and 69 dorsolateral prefrontal cortex (DLPFC) samples in total). Samples were collected from MDD patients who died by suicide (MDD-S), MDDs who died by other means (MDD-NS) and non-psychiatric controls. We analyzed gene expression using RNA and the NanoString platform. In blood, we identified 14 genes which significantly differentiated MDD-S versus MDD-NS. The top six genes differentially expressed in blood were: PER3, MTPAP, SLC25A26, CD19, SOX9, and GAR1. Additionally, four genes showed significant changes in brain and blood between MDD-S and MDD-NS; SOX9 was decreased and PER3 was increased in MDD-S in both tissues, while CD19 and TERF1 were increased in blood but decreased in DLPFC. To our knowledge, this is the first study to analyze matched blood and brain samples in a well-defined population of MDDs demonstrating significant differences in gene expression associated with completed suicide. Our results strongly suggest that blood gene expression is highly informative to understand molecular changes in suicide. Developing a suicide biomarker signature in blood could help health care professionals to identify subjects at high risk for suicide.

Introduction: Large somatic deletions of mitochondrial DNA (mtDNA) accumulate with aging in metabolically active tissues such as the brain. We have cataloged the breakpoints and frequencies of large mtDNA deletions in the human brain. Methods: We quantified 112 high-frequency mtDNA somatic deletions across four human brain regions with the Splice-Break2 pipeline. In addition, we utilized PLINK/Seq to test the association of mitochondrial genotypes with the abundance of these high-frequency mtDNA deletions. A conservative p value threshold of 5E−08 was used to find the significant loci. Results: One mtDNA SNP (T14798C) was significantly associated with mtDNA deletions in two brain regions, the dorsolateral prefrontal cortex (DLPFC) and the superior temporal gyrus. Since the DLPFC showed the most robust association between T14798C and two deletion breakpoints (7816–14807 and 5462–14807), this association was tested in the DLPFC of a replication sample and validated the first results. Incorporating the C allele at 14,798 bp increased the perfect/imperfect length of the repeat at the 3′ breakpoint of the two associated deletions. Conclusion: This is the first study to identify the association of mtDNA SNP with large mtDNA deletions in the human brain. The T14798C allele located in the MT-CYB gene is a common polymorphism that occurs in several mitochondrial haplogroups. We hypothesize that the T14798C association with two deletions occurs by extending the repeat length around the 3′ deletion breakpoints. This simple mechanism suggests that mtDNA SNPs can affect the mitochondrial genome structure, especially in brain where high levels of reactive oxygen species lead to deletion accumulation with aging.

The effects of smoking in the human brain were explored at the molecular level in the nucleus accumbens (NAcc), a key brain region involved in tobacco addiction. Gene expression data from post-mortem NAcc were analyzed according to smoking habits: Never smokers, Former smokers and Current smokers at the time of death. The effect of smoking was determined using an ANCOVA model, controlling for potential confounders (psychiatric diagnosis, gender, age, post-mortem interval, and brain pH) followed by pair-wise post-hoc comparisons. Q-values (false discovery rate adjusted p-values) < 0.05 were used in combination with a fold change of > ±1.3 to identify the most relevant genes. The greatest number of differentially expressed genes (DEGs) were found in subjects with a recent history of smoking (Current smokers) compared to either Former or Never smokers. Only two genes were differentially expressed between Former and Never smokers, suggesting that the effects of smoking on gene expression in the brain may be transient. Ingenuity Pathway Analysis (IPA) of DEGs identified a significant over-representation of neurotransmitter system genes (glutamate, GABA) in Current smokers. IPA also revealed many genes associated with cancer in Current smokers compared to Former and Never smokers despite no known cancer in any subjects. Genes associated with neoplasms, glioblastoma, gliomas and tumor regulations are among the top 10 transcripts.Our findings show that active smokers have a significant increase in cancer-related genes and alterations in glutamate and GABA neurotransmitter systems in the NAcc. To our knowledge this is the first study to identify cancer-related genes in the NAcc in Current smokers who have no evidence of cancer. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement The study was funded by the Pritzker Family Philanthropic Fund, and the American Foundation for Suicide Prevention Standard Research Grant SRG-0-121-18 (to A.S.) The authors declare no other financial or non-financial competing interests. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The Institutional Review Board of the University of California, Irvine gave ethical approval for this work. I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data produced in the present study are available upon reasonable request to the authors.

The study of postsynaptic excitation to inhibition (E/I ratio) imbalances in human brain diseases, is a highly relevant functional measurement poorly investigated due to postmortem degradation of synaptic receptors. We show that near-simultaneous recording of microtransplanted synaptic receptors after simulated morgue conditions allows the determination of the postsynaptic E/I ratio for at least 120 h after death, expanding the availability and use of human diseased tissue stored in brain banks.

Clinical and preclinical studies suggest that some of the behavioral alterations observed in schizophrenia (SZ) may be mechanistically linked to synaptic dysfunction of glutamatergic signaling. Recent genetic and proteomic studies suggest alterations of cortical glutamate receptors of the AMPA-type (AMPARs), which are the predominant ligand-gated ionic channels of fast transmission at excitatory synapses. The impact of gene and protein alterations on the electrophysiological activity of AMPARs is not known in SZ. In this proof of principle work, using human postmortem brain synaptic membranes isolated from the dorsolateral prefrontal cortex (DLPFC), we combined electrophysiological analysis from microtransplanted synaptic membranes (MSM) with transcriptomic (RNA-Seq) and label-free proteomics data in 10 control and 10 subjects diagnosed with SZ. We observed in SZ a reduction in the amplitude of AMPARs currents elicited by kainate, an agonist of AMPARs that blocks the desensitization of the receptor. This reduction was not associated with protein abundance but with a reduction in kainate's potency to activate AMPARs. Electrophysiologically-anchored dataset analysis (EDA) was used to identify synaptosomal proteins that linearly correlate with the amplitude of the AMPARs responses, gene ontology functional annotations were then used to determine protein-protein interactions. Protein modules associated with positive AMPARs current increases were downregulated in SZ, while protein modules that were upregulated in SZ were associated with decreased AMPARs currents. Our results indicate that transcriptomic and proteomic alterations, frequently observed in the DLPFC in SZ, converge at the synaptic level producing a functional electrophysiological impairment of AMPARs.

Neuronal cholinergic circuits have been implicated in cognitive function and neurological disease, but the role of cholinergic signaling in other cellular populations within the brain has not been as fully defined. Here, we show that cholinergic signaling mechanisms are involved in mediating the function of the choroid plexus, the brain structure responsible for generating CSF and releasing various factors into the brain. The choroid plexus was found to express markers of endogenous cholinergic signaling, including multiple nicotinic acetylcholine receptor (nAChR) subtypes in a region-specific manner, and application of nicotine was found to induce cellular activation, as evidenced by calcium influx in primary tissue. During intravenous nicotine self-administration in male rats, nicotine increased expression of transthyretin, a protein selectively produced and released by the choroid plexus, and microRNA-204 (mir-204), a transcript found in high levels in the choroid plexus and CSF. Finally, human choroid plexus tissue from both sexes was found to exhibit similar nAChR, transthyretin and mir-204 expression profiles, supporting the translational relevance of the findings. Together, these studies demonstrate functionally active cholinergic signaling mechanisms in the choroid plexus, the resulting effects on transthyretin and mir-204 expression, and reveal the direct mechanism by which nicotine modulates function of this tissue.

Altered expression of GABA receptors (GABAARs) has been implicated in neurological and psychiatric disorders, but limited information about region-specific GABAAR subunit expression in healthy human brains, heteromeric assembly of major isoforms, and their collective organization across healthy individuals, are major roadblocks to understanding their role in non-physiological states. Here, by using microarray and RNA-Seq datasets-from single cell nuclei to global brain expression-from the Allen Institute, we find that transcriptional expression of GABAAR subunits is anatomically organized according to their neurodevelopmental origin. The data show a combination of complementary and mutually-exclusive expression patterns that delineate major isoforms, and which is highly stereotypical across brains from control donors. We summarize the region-specific signature of GABAR subunits per subject and its variability in a control population sample that can be used as a reference for remodeling changes during homeostatic rearrangements of GABAAR subunits after physiological, pharmacological or pathological challenges.

Polyamines have fundamental roles in brain homeostasis as key modulators of cellular excitability. Several studies have suggested alterations in polyamine metabolism in stress related disorders, suicide, depression, and neurodegeneration, making the pharmacological modulation of polyamines a highly appealing therapeutic strategy. Polyamines are small aliphatic molecules that can modulate cationic channels involved in neuronal excitability. Previous indirect evidence has suggested that polyamines can modulate anionic GABAA receptors (GABAARs), which mediate inhibitory signaling and provide a direct route to reduce hyperexcitability. Here, we attempted to characterize the effect that spermine, the polyamine with the strongest reported effect on GABAARs, has on human postmortem native GABAARs. We microtransplanted human synaptic membranes from the dorsolateral prefrontal cortex of four cases with no history of mental or neurological disorders, and directly recorded spermine effects on ionic GABAARs responses on microtransplanted oocytes. We show that in human synapses, inhibition of GABAARs by spermine was better explained by alkalization of the extracellular solution. Additionally, spermine had no effect on the potentiation of GABA-currents by diazepam, indicating that even if diazepam binding is enhanced by spermine, it does not translate to changes in functional activity. Our results clearly demonstrate that while extracellular spermine does not have direct effects on human native synaptic GABAARs, spermine-mediated shifts of pH inhibit GABAARs. Potential spermine-mediated increase of pH in synapses in vivo may therefore participate in increased neuronal activity observed during physiological and pathological states, and during metabolic alterations that increase the release of spermine to the extracellular milieu.

The biological fingerprint of environmental adversity may be key to understanding health and disease, as it encompasses the damage induced as well as the compensatory reactions of the organism. Metabolic and hormonal changes may be an informative but incomplete window into the underlying biology. We endeavored to identify objective blood gene expression biomarkers for psychological stress, a subjective sensation with biological roots. To quantify the stress perception at a particular moment in time, we used a simple visual analog scale for life stress in psychiatric patients, a high-risk group. Then, using a stepwise discovery, prioritization, validation, and testing in independent cohort design, we were successful in identifying gene expression biomarkers that were predictive of high-stress states and of future psychiatric hospitalizations related to stress, more so when personalized by gender and diagnosis. One of the top biomarkers that survived discovery, prioritization, validation, and testing was FKBP5, a well-known gene involved in stress response, which serves as a de facto reassuring positive control. We also compared our biomarker findings with telomere length (TL), another well-established biological marker of psychological stress and show that newly identified predictive biomarkers such as NUB1, APOL3, MAD1L1, or NKTR are comparable or better state or trait predictors of stress than TL or FKBP5. Over half of the top predictive biomarkers for stress also had prior evidence of involvement in suicide, and the majority of them had evidence in other psychiatric disorders, providing a molecular underpinning for the effects of stress in those disorders. Some of the biomarkers are targets of existing drugs, of potential utility in patient stratification, and pharmacogenomics approaches. Based on our studies and analyses, the biomarkers with the best overall convergent functional evidence (CFE) for involvement in stress were FKBP5, DDX6, B2M, LAIR1, RTN4, and NUB1. Moreover, the biomarker gene expression signatures yielded leads for possible new drug candidates and natural compounds upon bioinformatics drug repurposing analyses, such as calcium folinate and betulin. Our work may lead to improved diagnosis and treatment for stress disorders such as PTSD, that result in decreased quality of life and adverse outcomes, including addictions, violence, and suicide.

Deletions in the 16.6kb mitochondrial genome have been implicated in numerous disorders that often display muscular and/or neurological symptoms due to the high-energy demands of these tissues. We describe a catalogue of 4489 putative mitochondrial DNA (mtDNA) deletions, including their frequency and relative read rate, using a combinatorial approach of mitochondria-targeted PCR, next-generation sequencing, bioinformatics, post-hoc filtering, annotation, and validation steps. Our bioinformatics pipeline uses MapSplice, an RNA-seq splice junction detection algorithm, to detect and quantify mtDNA deletion breakpoints rather than mRNA splices. Analyses of 93 samples from postmortem brain and blood found (i) the 4977bp common deletion' was neither the most frequent deletion nor the most abundant; (ii) brain contained significantly more deletions than blood; (iii) many high frequency deletions were previously reported in MitoBreak, suggesting they are present at low levels in metabolically active tissues and are not exclusive to individuals with diagnosed mitochondrial pathologies; (iv) many individual deletions (and cumulative metrics) had significant and positive correlations with age and (v) the highest deletion burdens were observed in major depressive disorder brain, at levels greater than Kearns-Sayre Syndrome muscle. Collectively, these data suggest the Splice-Break pipeline can detect and quantify mtDNA deletions at a high level of resolution.

BackgroundThe genetic risk factors of schizophrenia (SCZ), a severe psychiatric disorder, are not yet fully understood. Multiple lines of evidence suggest that mitochondrial dysfunction may play a role in SCZ, but comprehensive association studies are lacking. We hypothesized that variants in nuclear-encoded mitochondrial genes influence susceptibility to SCZ.MethodsWe conducted gene-based and gene-set analyses using summary association results from the Psychiatric Genomics Consortium Schizophrenia Phase 2 (PGC-SCZ2) genome-wide association study comprising 35,476 cases and 46,839 control subjects. We applied the MAGMA method to three sets of nuclear-encoded mitochondrial genes: oxidative phosphorylation genes, other nuclear-encoded mitochondrial genes, and genes involved in nucleus-mitochondria crosstalk. Furthermore, we conducted a replication study using the iPSYCH SCZ sample of 2290 cases and 21,621 control subjects.ResultsIn the PGC-SCZ2 sample, 1186 mitochondrial genes were analyzed, among which 159 had p values < .05 and 19 remained significant after multiple testing correction. A meta-analysis of 818 genes combining the PGC-SCZ2 and iPSYCH samples resulted in 104 nominally significant and nine significant genes, suggesting a polygenic model for the nuclear-encoded mitochondrial genes. Gene-set analysis, however, did not show significant results. In an in silico protein-protein interaction network analysis, 14 mitochondrial genes interacted directly with 158 SCZ risk genes identified in PGC-SCZ2 (permutation p = .02), and aldosterone signaling in epithelial cells and mitochondrial dysfunction pathways appeared to be overrepresented in this network of mitochondrial and SCZ risk genes.ConclusionsThis study provides evidence that specific aspects of mitochondrial function may play a role in SCZ, but we did not observe its broad involvement even using a large sample.

The hypothalamus contains neurons that integrate hunger and satiety endocrine signals from the periphery and are implicated in the pathophysiology of obesity. The limited availability of human hypothalamic neurons hampers our understanding of obesity disease mechanisms. To address this, we generated human induced pluripotent stem cells (hiPSCs) from multiple normal body mass index (BMI; BMI ≤ 25) subjects and super-obese (OBS) donors (BMI ≥ 50) with polygenic coding variants in obesity-associated genes. We developed a method to reliably differentiate hiPSCs into hypothalamic-like neurons (iHTNs) capable of secreting orexigenic and anorexigenic neuropeptides. Transcriptomic profiling revealed that, although iHTNs maintain a fetal identity, they respond appropriately to metabolic hormones ghrelin and leptin. Notably, OBS iHTNs retained disease signatures and phenotypes of high BMI, exhibiting dysregulated respiratory function, ghrelin-leptin signaling, axonal guidance, glutamate receptors, and endoplasmic reticulum (ER) stress pathways. Thus, human iHTNs provide a powerful platform to study obesity and gene-environment interactions.