Serum from Older Adults Increases Apoptosis and Molecular Aging Markers in Human Hippocampal Progenitor Cells.

Age-related alteration in neural stem cell function is linked to neurodegenerative conditions and cognitive decline. In rodents, this can be reversed by exposure to a young systemic milieu and conversely, the old milieu can inhibit stem cell function in young rodents. In this study, we investigated the in vitro effect of the human systemic milieu on human hippocampal progenitor cells (HPCs) using human serum from early adulthood, mid-life and older age. We showed that neuroblast number following serum treatment is predictive of larger dentate gyrus, CA3, CA4 and whole hippocampus volumes and that allogeneic human serum from asymptomatic older individuals induced a two-fold increase in apoptotic cell death of HPCs compared with serum from young adults. General linear models revealed that variability in markers of proliferation and differentiation was partly attributable to use of antihypertensive medication and very mild cognitive decline among older subjects. Finally, using an endophenotype approach and whole-genome expression arrays, we showed upregulation of established and novel ageing molecular hallmarks in response to old serum. Serum from older subjects induced a wide range of cellular and molecular phenotypes, likely reflecting a lifetime of environmental exposures. Our findings support a role for the systemic enviroment in neural stem cell maintenance and are in line with others highlighting a distinction between neurobiological and chronological ageing. Finally, the herein described serum assay can be used by future studies to further analyse the effect of environmental exposures as well as to determine the role of the systemic environment in health and disease.

Distinct Effects of Heparin and Interleukin-4 Functionalization on Macrophage Polarization and In Situ Arterial Tissue Regeneration Using Resorbable Supramolecular Vascular Grafts in Rats.

Two of the greatest challenges for successful application of small-diameter in situ tissue-engineered vascular grafts are 1) preventing thrombus formation and 2) harnessing the inflammatory response to the graft to guide functional tissue regeneration. This study evaluates the in vivo performance of electrospun resorbable elastomeric vascular grafts, dual-functionalized with anti-thrombogenic heparin (hep) and anti-inflammatory interleukin 4 (IL-4) using a supramolecular approach. The regenerative capacity of IL-4/hep, hep-only, and bare grafts is investigated as interposition graft in the rat abdominal aorta, with follow-up at key timepoints in the healing cascade (1, 3, 7 days, and 3 months). Routine analyses are augmented with Raman microspectroscopy, in order to acquire the local molecular fingerprints of the resorbing scaffold and developing tissue. Thrombosis is found not to be a confounding factor in any of the groups. Hep-only-functionalized grafts resulted in adverse tissue remodeling, with cases of local intimal hyperplasia. This is negated with the addition of IL-4, which promoted M2 macrophage polarization and more mature neotissue formation. This study shows that with bioactive functionalization, the early inflammatory response can be modulated and affect the composition of neotissue. Nevertheless, variability between graft outcomes is observed within each group, warranting further evaluation in light of clinical translation.

Aging biological markers in a cohort of antipsychotic-naïve first-episode psychosis patients.

Schizophrenia is a severe and multifactorial disorder with an unknown causative pathophysiology. Abnormalities in neurodevelopmental and aging processes have been reported. Relative telomere length (RTL) and DNA methylation age (DMA), well-known biomarkers for estimating biological age, are both commonly altered in patients with schizophrenia compared to healthy controls. However, few studies investigated these aging biomarkers in first-episode psychosis (FEP) and in antipsychotic-naïve patients. To cover the existing gap regarding DMA and RTL in FEP and antipsychotic treatment, we aimed to verify whether those aging markers could be associated with psychosis and treatment response. Thus, we evaluated these measures in the blood of FEP antipsychotic-naïve patients and healthy controls (HC), as well as the response to antipsychotics after 10 weeks of treatment with risperidone. RTL was measured in 392 subjects, being 80 FEP and 312 HC using qPCR, while DMA was analyzed in a subset of 60 HC, 60 FEP patients (antipsychotic-naïve) and 59 FEP-10W (after treatment) using the "Multi-tissue Predictor"and the Infinium HumanMethylation450 BeadChip Kit. We observed diminished DMA and longer RTL in FEP patients before treatment compared to healthy controls, indicating a decelerated aging process in those patients. We found no statistical difference between responder and non-responder patients at baseline for both markers. An increased DMA was observed in patients after 10 weeks of treatment, however, after adjusting for blood cell composition, no significant association remained. Our findings indicate a decelerated aging process in the early phases of the disease.

Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses.

We performed a transcriptome-wide meta-analysis and gene co-expression network analysis to identify genes and gene networks dysregulated in the peripheral blood of bipolar disorder (BD) cases relative to unaffected comparison subjects, and determined the specificity of the transcriptomic signatures of BD and schizophrenia (SZ). Nineteen genes and 4 gene modules were significantly differentially expressed in BD cases. Thirteen gene modules were shown to be differentially expressed in a combined case-group of BD and SZ subjects called "major psychosis", including genes biologically linked to apoptosis, reactive oxygen, chromatin remodeling, and immune signaling. No modules were differentially expressed between BD and SZ cases. Machine-learning classifiers trained to separate diagnostic classes based solely on gene expression profiles could distinguish BD cases from unaffected comparison subjects with an area under the curve (AUC) of 0.724, as well as BD cases from SZ cases with AUC = 0.677 in withheld test samples. We introduced a novel and straightforward method called "polytranscript risk scoring" that could distinguish BD cases from unaffected subjects (AUC = 0.672) and SZ cases (AUC = 0.607) significantly better than expected by chance. Taken together, our results highlighted gene expression alterations common to BD and SZ that involve biological processes of inflammation, oxidative stress, apoptosis, and chromatin regulation, and highlight disorder-specific changes in gene expression that discriminate the major psychoses.

A Supramolecular Platform for the Introduction of Fc-Fusion Bioactive Proteins on Biomaterial Surfaces.

Bioorthogonal chemistry is an excellent method for functionalization of biomaterials with bioactive molecules, as it allows for decoupling of material processing and bioactivation. Here, we report on a modular system created by means of tetrazine/trans-cyclooctene (Tz/TCO) click chemistry undergoing an inverse electron demand Diels-Alder cycloaddition. A reactive supramolecular surface based on ureido-pyrimidinones (UPy) is generated via a UPy-Tz additive, in order to introduce a versatile TCO-protein G conjugate for immobilization of Fc-fusion proteins. As a model bioactive protein, we introduced Fc-Jagged1, a Notch ligand, to induce Notch signaling activity on the material. Interestingly, HEK293 FLN1 cells expressing the Notch1 receptor were repelled by films modified with TCO-protein G but adhered and spread on functionalized electrospun meshes. This indicates that the material processing method influences the biocompatibility of the postmodification. Notch signaling activity was upregulated 5.6-fold with respect to inactive controls on electrospun materials modified with TCO-protein G/Fc-Jagged1. Furthermore, downstream effects of Notch signaling were detected on the gene level in vascular smooth muscle cells expressing the Notch3 receptor. Taken together, our results demonstrate the successful use of a modular supramolecular system for the postprocessing modification of solid materials with functional proteins.

Genome-wide Burden of Rare Short Deletions Is Enriched in Major Depressive Disorder in Four Cohorts.

BACKGROUND: Major depressive disorder (MDD) is moderately heritable, with a high prevalence and a presumed high heterogeneity. Copy number variants (CNVs) could contribute to the heritable component of risk, but the two previous genome-wide association studies of rare CNVs did not report significant findings. METHODS: In this meta-analysis of four cohorts (5780 patients and 6626 control subjects), we analyzed the association of MDD to 1) genome-wide burden of rare deletions and duplications, partitioned by length (<100 kb or >100 kb) and other characteristics, and 2) individual rare exonic CNVs and CNV regions. RESULTS: Patients with MDD carried significantly more short deletions than control subjects (p = .0059) but not long deletions or short or long duplications. The confidence interval for long deletions overlapped with that for short deletions, but long deletions were 70% less frequent genome-wide, reducing the power to detect increased burden. The increased burden of short deletions was primarily in intergenic regions. Short deletions in cases were also modestly enriched for high-confidence enhancer regions. No individual CNV achieved thresholds for suggestive or significant association after genome-wide correction. p values < .01 were observed for 15q11.2 duplications (TUBGCP5, CYFIP1, NIPA1, and NIPA2), deletions in or near PRKN or MSR1, and exonic duplications of ATG5. CONCLUSIONS: The increased burden of short deletions in patients with MDD suggests that rare CNVs increase the risk of MDD by disrupting regulatory regions. Results for longer deletions were less clear, but no large effects were observed for long multigenic CNVs (as seen in schizophrenia and autism). Further studies with larger sample sizes are warranted.

Liprin alfa 2 gene expression is increased by cannabis use and associated with neuropsychological function.

The relation of heavy cannabis use with decreased neuropsychological function has frequently been described but the underlying biological mechanisms are still largely unknown. This study investigates the relation of cannabis use with genome wide gene expression and subsequently examines the relations with neuropsychological function. Genome-wide gene expression in whole blood was compared between heavy cannabis users (N = 90) and cannabis naïve participants (N = 100) that were matched for psychotic like experiences. The results were validated using quantitative real-time PCR. Psychotic like experiences were assessed using the Comprehensive Assessment of Psychotic Experiences (CAPE). Neuropsychological function was estimated using four subtasks of the Wechsler Adult Intelligence Scale (WAIS). Subsequent in vitro studies in monocytes and a neuroblastoma cell line investigated expression changes in response to two major psychotropic components of cannabis; tetrahydrocannabinol (THC) and cannabidiol (CBD). mRNA expression of Protein Tyrosine Phosphatase Receptor Type F Polypeptide-Interacting-Protein Alpha-2 (PPFIA2) was significantly higher in cannabis users (LogFold Change 0.17) and confirmed by qPCR analysis. PPFIA2 expression level was negatively correlated with estimated intelligence (B=-22.9, p = 0.002) also in the 100 non-users (B=-28.5, p = 0.037). In vitro exposure of monocytes to CBD led to significant increase in PPFIA2 expression. However, exposure of monocytes to THC and neuroblastoma cells to THC or CBD did not change PPFIA2 expression. Change in PPFIA2 gene expression in response to cannabinoids is a putative mechanism by which cannabis could influence neuropsychological functions. The findings warrant further exploration of the role of PPFIA2 in cannabis induced changes of neuropsychological function, particularly in relation to CBD.

Gene expression over the course of schizophrenia: from clinical high-risk for psychosis to chronic stages.

The study of patients with schizophrenia (SZ) at different clinical stages may help clarify what effects could be due to the disease itself, to the pharmacological treatment, or to the disease progression. We compared expression levels of targeted genes in blood from individuals in different stages of SZ: clinical high risk for psychosis (CHR), first episode of psychosis (FEP), and chronic SZ (CSZ). Then, we further verified whether single-nucleotide polymorphisms (SNPs) could be related to gene expression differences. We investigated 12 genes in 394 individuals (27 individuals with CHR, 70 antipsychotic-naive individuals with FEP, 157 CSZ patients, and 140 healthy controls (HCs)). For a subsample, genotype data were also available, and we extracted SNPs that were previously associated with the expression of selected genes in whole blood or brain tissue. We generated a mediation model in which a putative cause (SNP) is related to a presumed effect (disorder) via an intermediate variable (gene expression). MBP and NDEL1 were upregulated in FEP compared to all other groups; DGCR8 was downregulated in FEP compared to HC and CHR; DGCR2 was downregulated in CSZ compared to FEP and HCs; DISC1 was upregulated in schizophrenia compared to controls or FEP, possibly induced by the rs3738398 and rs10864693 genotypes, which were associated with DISC1 expression; and UFD1 was upregulated in CSZ and CHR compared to FEP and HC. Our results indicated changes in gene expression profiles throughout the different clinical stages of SZ, reinforcing the need for staging approaches to better capture SZ heterogeneity.

The polygenic nature of telomere length and the anti-ageing properties of lithium.

Telomere length is a promising biomarker for age-related disease and a potential anti-ageing drug target. Here, we study the genetic architecture of telomere length and the repositioning potential of lithium as an anti-ageing medication. LD score regression applied to the largest telomere length genome-wide association study to-date, revealed SNP-chip heritability estimates of 7.29%, with polygenic risk scoring capturing 4.4% of the variance in telomere length in an independent cohort (p = 6.17 × 10-5). Gene-enrichment analysis identified 13 genes associated with telomere length, with the most significant being the leucine rich repeat gene, LRRC34 (p = 3.69 × 10-18). In the context of lithium, we confirm that chronic use in a sample of 384 bipolar disorder patients is associated with longer telomeres (p = 0.03). As complementary evidence, we studied three orthologs of telomere length regulators in a Caenorhabditis elegans model of lithium-induced extended longevity and found all transcripts to be affected post-treatment (p < 0.05). Lithium may therefore confer its anti-ageing effects by moderating the expression of genes responsible for normal telomere length regulation. This is supported by our bipolar disorder sample, which shows that polygenic risk scores explain a higher proportion of the variance in telomere length amongst chronic lifetime lithium users (variance explained = 8.9%, p = 0.01), compared to non-users (p > 0.05). Consequently, this suggests that lithium may be catalysing the activity of endogenous mechanisms that promote telomere lengthening, whereby its efficacy eventually becomes limited by each individual's inherent telomere maintenance capabilities. Our work indicates a potential use of polygenic risk scoring for the prediction of adult telomere length and consequently lithium's anti-ageing efficacy.

Telomere length as a predictor of emotional processing in the brain.

Shorter telomere length (TL) has been associated with the development of mood disorders as well as abnormalities in brain morphology. However, so far, no studies have considered the role TL may have on brain function during tasks relevant to mood disorders. In this study, we examine the relationship between TL and functional brain activation and connectivity, while participants (n = 112) perform a functional magnetic resonance imaging (fMRI) facial affect recognition task. Additionally, because variation in TL has a substantial genetic component we calculated polygenic risk scores for TL to test if they predict face-related functional brain activation. First, our results showed that TL was positively associated with increased activation in the amygdala and cuneus, as well as increased connectivity from posterior regions of the face network to the ventral prefrontal cortex. Second, polygenic risk scores for TL show a positive association with medial prefrontal cortex activation. The data support the view that TL and genetic loading for shorter telomeres, influence the function of brain regions known to be involved in emotional processing.

The Alkaline Phosphatase (ALPL) Locus Is Associated with B6 Vitamer Levels in CSF and Plasma.

The active form of vitamin B6, pyridoxal phosphate (PLP), is essential for human metabolism. The brain is dependent on vitamin B6 for its neurotransmitter balance. To obtain insight into the genetic determinants of vitamin B6 homeostasis, we conducted a genome-wide association study (GWAS) of the B6 vitamers pyridoxal (PL), PLP and the degradation product of vitamin B6, pyridoxic acid (PA). We collected a unique sample set of cerebrospinal fluid (CSF) and plasma from the same healthy human subjects of Dutch ancestry (n = 493) and included concentrations and ratios in and between these body fluids in our analysis. Based on a multivariate joint analysis of all B6 vitamers and their ratios, we identified a genome-wide significant association at a locus on chromosome 1 containing the ALPL (alkaline phosphatase) gene (minimal p = 7.89 × 10-10, rs1106357, minor allele frequency (MAF) = 0.46), previously associated with vitamin B6 levels in blood. Subjects homozygous for the minor allele showed a 1.4-times-higher ratio between PLP and PL in plasma, and even a 1.6-times-higher ratio between PLP and PL in CSF than subjects homozygous for the major allele. In addition, we observed a suggestive association with the CSF:plasma ratio of PLP on chromosome 15 (minimal p = 7.93 × 10-7, and MAF = 0.06 for rs28789220). Even though this finding is not reaching genome-wide significance, it highlights the potential of our experimental setup for studying transport and metabolism across the blood⁻CSF barrier. This GWAS of B6 vitamers identifies alkaline phosphatase as a key regulator in human vitamin B6 metabolism in CSF as well as plasma. Furthermore, our results demonstrate the potential of genetic studies of metabolites in plasma and CSF to elucidate biological aspects underlying metabolite generation, transport and degradation.

Applying polygenic risk scoring for psychiatric disorders to a large family with bipolar disorder and major depressive disorder.

Psychiatric disorders are thought to have a complex genetic pathology consisting of interplay of common and rare variation. Traditionally, pedigrees are used to shed light on the latter only, while here we discuss the application of polygenic risk scores to also highlight patterns of common genetic risk. We analyze polygenic risk scores for psychiatric disorders in a large pedigree (n ~ 260) in which 30% of family members suffer from major depressive disorder or bipolar disorder. Studying patterns of assortative mating and anticipation, it appears increased polygenic risk is contributed by affected individuals who married into the family, resulting in an increasing genetic risk over generations. This may explain the observation of anticipation in mood disorders, whereby onset is earlier and the severity increases over the generations of a family. Joint analyses of rare and common variation may be a powerful way to understand the familial genetics of psychiatric disorders.

Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition.

Psychiatric illnesses are complex and polygenic. They are associated with widespread alterations in the brain, which are partly influenced by genetic factors. There have been some attempts to relate polygenic risk scores (PRS) - a measure of the overall genetic risk an individual carries for a disorder - to brain structure using univariate methods. However, PRS are likely associated with distributed and covarying effects across the brain. We therefore used multivariate machine learning in this proof-of-principle study to investigate associations between brain structure and PRS for four psychiatric disorders; attention deficit-hyperactivity disorder (ADHD), autism, bipolar disorder and schizophrenia. The sample included 213 individuals comprising patients with depression (69), bipolar disorder (33), and healthy controls (111). The five psychiatric PRSs were calculated based on summary data from the Psychiatric Genomics Consortium. T1-weighted magnetic resonance images were obtained and voxel-based morphometry was implemented in SPM12. Multivariate relevance vector regression was implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo). Across the whole sample, a multivariate pattern of grey matter significantly predicted the PRS for autism (r = 0.20, pFDR = 0.03; MSE = 4.20 × 10-5, pFDR = 0.02). For the schizophrenia PRS, the MSE was significant (MSE = 1.30 × 10-5, pFDR = 0.02) although the correlation was not (r = 0.15, pFDR = 0.06). These results lend support to the hypothesis that polygenic liability for autism and schizophrenia is associated with widespread changes in grey matter concentrations. These associations were seen in individuals not affected by these disorders, indicating that this is not driven by the expression of the disease, but by the genetic risk captured by the PRSs.

Polygenic risk score analyses of symptoms and treatment response in an antipsychotic-naive first episode of psychosis cohort.

In this study, we aimed to test if the schizophrenia (SCZ) polygenic risk score (PRS) was associated with clinical symptoms in (a) the first episode of psychosis pre-treatment (FEP), (b) at nine weeks after initiation of risperidone treatment (FEP-9W) and (c) with the response to risperidone. We performed a detailed clinical assessment of 60 FEP patients who were antipsychotic-naive and, again, after nine weeks of standardized treatment with risperidone. After blood collection and DNA isolation, the samples were genotyped using the Illumina PsychArrayChip and then imputed. To calculate PRS, we used the latest available GWAS summary statistics from the Psychiatric Genomics Consortium wave-2 SCZ group as a training set. We used Poisson regression to test association between PRS and clinical measurements correcting for the four principal components (genotyping). We considered a p-value < 0.0014 (Bonferroni correction) as significant. First, we verified that the schizophrenia PRS was also able to distinguish cases from controls in this south-eastern Brazilian sample, with a similar variance explained to that seen in Northern European populations. In addition, within-cases analyses, we found that PRS is significantly correlated with baseline (pre-treatment) symptoms, as measured by lower clinical global assessment of functioning (-GAF), higher depressive symptoms and higher scores on a derived excitement factor. After standardized treatment for nine weeks, the correlation with GAF and the excitement factor disappeared while depressive symptoms became negatively associated with PRS. We conclude that drug (and other treatments) may confound attempts to understand the aetiological influence on symptomatology of polygenic risk scores. These results highlight the importance of studying schizophrenia, and other disorders, pre-treatment to understand the relationship between polygenic risk and phenotypic features.

Development of multivariable models to predict change in Body Mass Index within a clinical trial population of psychotic individuals.

Many antipsychotics promote weight gain, which can lead to non-compliance and relapse of psychosis. By developing models that accurately identify individuals at greater risk of weight gain, clinicians can make informed treatment decisions and target intervention measures. We examined clinical, genetic and expression data for 284 individuals with psychosis derived from a previously published randomised controlled trial (IMPACT). These data were used to develop regression and classification models predicting change in Body Mass Index (BMI) over one year. Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and exercise, physical and mental health, medication and BMI outcome measures. We included genetic polygenic risk scores (PRS) for schizophrenia, bipolar disorder, BMI, waist-hip-ratio, insulin resistance and height, as well as gene co-expression modules generated by Weighted Gene Co-expression Network Analysis (WGCNA). The best performing predictive models for BMI and BMI gain after one year used clinical data only, which suggests expression and genetic data do not improve prediction in this cohort.

The genome-wide expression effects of escitalopram and its relationship to neurogenesis, hippocampal volume, and antidepressant response.

Antidepressant-induced hippocampal neurogenesis (AHN) is hypothesized to contribute to increases in hippocampal volume among major depressive disorder patients after long-term treatment. Furthermore, rodent studies suggest AHN may be the cellular mechanism mediating the therapeutic benefits of antidepressants. Here, we perform the first investigation of genome-wide expression changes associated with AHN in human cells. We identify gene expression networks significantly activated during AHN, and we perform gene set analyses to probe the molecular relationship between AHN, hippocampal volume, and antidepressant response. The latter were achieved using genome-wide association summary data collected from 30,717 individuals as part of the ENIGMA Consortium (genetic predictors of hippocampal volume dataset), and data collected from 1,222 major depressed patients as part of the NEWMEDS Project (genetic predictors of response to antidepressants dataset). Our results showed that the selective serotonin reuptake inhibitor, escitalopram evoked AHN in human cells; dose-dependently increasing the differentiation of cells into neuroblasts, as well as increasing gliogenesis. Activated genome-wide expression networks relate to axon and microtubule formation, and ribosomal biogenesis. Gene set analysis revealed that gene expression changes associated with AHN were nominally enriched for genes predictive of hippocampal volume, but not for genes predictive of therapeutic response.

Separate and combined effects of genetic variants and pre-treatment whole blood gene expression on response to exposure-based cognitive behavioural therapy for anxiety disorders.

OBJECTIVES: Exposure-based cognitive behavioural therapy (eCBT) is an effective treatment for anxiety disorders. Response varies between individuals. Gene expression integrates genetic and environmental influences. We analysed the effect of gene expression and genetic markers separately and together on treatment response. METHODS: Adult participants (n ≤ 181) diagnosed with panic disorder or a specific phobia underwent eCBT as part of standard care. Percentage decrease in the Clinical Global Impression severity rating was assessed across treatment, and between baseline and a 6-month follow-up. Associations with treatment response were assessed using expression data from 3,233 probes, and expression profiles clustered in a data- and literature-driven manner. A total of 3,343,497 genetic variants were used to predict treatment response alone and combined in polygenic risk scores. Genotype and expression data were combined in expression quantitative trait loci (eQTL) analyses. RESULTS: Expression levels were not associated with either treatment phenotype in any analysis. A total of 1,492 eQTLs were identified with q < 0.05, but interactions between genetic variants and treatment response did not affect expression levels significantly. Genetic variants did not significantly predict treatment response alone or in polygenic risk scores. CONCLUSIONS: We assessed gene expression alone and alongside genetic variants. No associations with treatment outcome were identified. Future studies require larger sample sizes to discover associations.

The polygenic risk for bipolar disorder influences brain regional function relating to visual and default state processing of emotional information.

Genome-wise association studies have identified a number of common single-nucleotide polymorphisms (SNPs), each of small effect, associated with risk to bipolar disorder (BD). Several risk-conferring SNPs have been individually shown to influence regional brain activation thus linking genetic risk for BD to altered brain function. The current study examined whether the polygenic risk score method, which models the cumulative load of all known risk-conferring SNPs, may be useful in the identification of brain regions whose function may be related to the polygenic architecture of BD. We calculated the individual polygenic risk score for BD (PGR-BD) in forty-one patients with the disorder, twenty-five unaffected first-degree relatives and forty-six unrelated healthy controls using the most recent Psychiatric Genomics Consortium data. Functional magnetic resonance imaging was used to define task-related brain activation patterns in response to facial affect and working memory processing. We found significant effects of the PGR-BD score on task-related activation irrespective of diagnostic group. There was a negative association between the PGR-BD score and activation in the visual association cortex during facial affect processing. In contrast, the PGR-BD score was associated with failure to deactivate the ventromedial prefrontal region of the default mode network during working memory processing. These results are consistent with the threshold-liability model of BD, and demonstrate the usefulness of the PGR-BD score in identifying brain functional alternations associated with vulnerability to BD. Additionally, our findings suggest that the polygenic architecture of BD is not regionally confined but impacts on the task-dependent recruitment of multiple brain regions.

Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia.

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n=315) and from ex-vivo blood tissues (n=578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.