Biology subjects

Weinberger, D.

Publications and source records attributed to Weinberger, D..

16 recordsLinked to original sources

bioRxiv2026

Distinct cellular DNA methylation mechanisms underlie common and rare genetic risk for brain disorders

Noncoding genetic variation contributes to brain disorder risk, but the mechanisms through which it acts in specific brain cell types remain unclear. DNA methylation (DNAm), a highly cell type-specific regulatory layer in the brain, may mediate noncoding genetic risk, yet whether methylation at CG (mCG) and neuron-enriched non-CG (mCH) dinucleotides contribute differently to that risk remains unknown. Here we develop a deep learning framework that predicts DNAm from DNA sequence and estimates variant effects across 186 brain cell subtypes in both mCG and mCH, leveraging single-nucleus DNAm profiles from 46 brain regions. The models reveal distinct transcription factor (TF) programs underlying the two methylation contexts, with mCH-associated TFs showing stronger evolutionary constraint. Predicted variant effects agree closely with cell type-matched mQTLs in both direction and magnitude. Common variants predicted to affect mCG, particularly in excitatory neurons, show substantially greater heritability enrichment for brain-related traits than variants affecting mCH. By contrast, noncoding de novo mutations in autism preferentially perturb mCH, but not mCG, at conserved neuronal regulatory regions. This pattern is replicated across two independent cohorts totaling 5,782 probands and 4,053 unaffected siblings. Together, these findings indicate that common and rare noncoding variants contribute to brain disorders through distinct DNA methylation mechanisms.

genetics↗

bioRxiv2025

Genes with disrupted connectivity in the architecture of schizophrenia gene co-expression networks highlight atypical neuronal-glial interactions

Dysconnectivity in schizophrenia is a pervasive trait across various levels of systems biology. To better understand disrupted patterns of molecular connectivity distinguishing schizophrenia from control non-clinical populations, we applied novel approaches to gene co-expression networks in large samples of postmortem brains from multiple regions relevant to schizophrenia: the dorso-lateral prefrontal cortex- (DLPFC) (Ndonors=297), hippocampus (Ndonors=250) and caudate (Ndonors=349). We identified differentially connected genes (DCGs) in schizophrenia networks that deviated from architectural relationships characteristic of control gene co-expression networks, by assessing three network metrics - total connectivity (K), clustering coefficient (C), and intra-module degree (kIn) determined by projecting the modular community structure of the control networks onto the schizophrenia co-expression networks. Genes showing significant absolute case-control differences for these metrics (i.e., irrespective of difference directionality) were then tested for their relationships with common genetic variants conferring risk of schizophrenia and their biological significance through post-GWAS analyses (stratified LDSC and MAGMA), gene ontology annotations and enrichment in schizophrenia-relevant gene sets. We identified multiple DCGs, with case-control differences of connectivity metrics, consistent across brain regions. When parsed by parameter specificity, these genes show shared and specific enrichment in schizophrenia genetic signal, biological ontologies and selected cell-type markers. Notably these findings revealed widespread disturbances in co-expression connectivity affecting both neuronal and glial cells, particularly oligodendrocytes. Overall, our results highlight disrupted co-expression network architecture in schizophrenia, implicating disrupted neuronal-glial crosstalk and its effect on synaptic transmission.

neuroscience↗

bioRxiv2025

Lower cortical FKBP5 DNA methylation at key enhancer sites is associated with older age and higher gene expression in schizophrenia

An increasingly compelling body of literature indicates the glucocorticoid receptor cochaperone FK506-binding protein 51 (FKBP51) is a promising target for novel psychiatric therapeutics. However, the mechanisms regulating the corresponding FKBP5 gene directly in the human brain remain largely unknown yet are needed to facilitate the development of precise mechanism-based treatment approaches. Here, we examined FKBP5 DNA methylation patterns in postmortem human brain samples from the dorsolateral prefrontal cortex of individuals who lived with a major psychiatric disorder (schizophrenia, major depression, or bipolar disorder; n=329) and controls n=231. We identified that cytosine-phosphate-guanine-dinucleotide (CpG) specific FKBP5 DNA methylation is altered in psychiatric disorders across the FKBP5 locus, and that these changes are differentially associated with age and genotype (rs1360780 CC vs CT/TT). Individuals with schizophrenia had significantly lower levels of DNA methylation in the proximal enhancer of FKBP5, which also negatively correlated with FKBP5 gene expression. These changes were also associated with predicted glucocorticoid response elements (GREs) in the proximal enhancer, but not other transcription factor binding sites. This evidence supports that in the human cortex, FKBP5 DNA methylation is associated with both genetic and ageing effects, and that the associations between these factors vary at a diagnosis-specific level in psychopathology. This may have implications for developing FKBP5-targeted therapeutics and defining a subgroup of patients who will benefit from such treatments.

neuroscience↗

bioRxiv2024

scMeFormer: a transformer-based deep learning model for imputing DNA methylation states in single cells enhances the detection of epigenetic alterations in schizophrenia

DNA methylation (DNAm), a crucial epigenetic mark, plays a key role in gene regulation, mammalian development, and various human diseases. Single-cell technologies enable the profiling of DNAm states at cytosines within the DNA sequence of individual cells, but they often suffer from limited coverage of CpG sites. In this study, we introduce scMeFormer, a transformer-based deep learning model designed to impute DNAm states for each CpG site in single cells. Through comprehensive evaluations, we demonstrate the superior performance of scMeFormer compared to alternative models across four single-nucleus DNAm datasets generated by distinct technologies. Remarkably, scMeFormer exhibits high-fidelity imputation, even when dealing with significantly reduced coverage, as low as 10% of the original CpG sites. Furthermore, we applied scMeFormer to a single-nucleus DNAm dataset generated from the prefrontal cortex of four schizophrenia patients and four neurotypical controls. This enabled the identification of thousands of differentially methylated regions associated with schizophrenia that would have remained undetectable without imputation and added granularity to our understanding of epigenetic alterations in schizophrenia within specific cell types. Our study highlights the power of deep learning in imputing DNAm states in single cells, and we expect scMeFormer to be a valuable tool for single-cell DNAm studies.

genomics↗

bioRxiv2024

Deep learning predicts DNA methylation regulatory variants in specific brain cell types and enhances fine mapping for brain disorders

DNA methylation (DNAm) is essential for brain development and function and potentially mediates the effects of genetic risk variants underlying brain disorders. We present INTERACT, a transformer-based deep learning model to predict regulatory variants impacting DNAm levels in specific brain cell types, leveraging existing single-nucleus DNAm data from the human brain. We show that INTERACT accurately predicts cell type-specific DNAm profiles, achieving an average area under the Receiver Operating Characteristic curve of 0.98 across cell types. Furthermore, INTERACT predicts cell type-specific DNAm regulatory variants, which reflect cellular context and enrich the heritability of brain-related traits in relevant cell types. Importantly, we demonstrate that incorporating predicted variant effects and DNAm levels of CpG sites enhances the fine mapping for three brain disorders--schizophrenia, depression, and Alzheimers disease--and facilitates mapping causal genes to particular cell types. Our study highlights the power of deep learning in identifying cell type-specific regulatory variants, which will enhance our understanding of the genetics of complex traits. TeaserDeep learning reveals genetic variations impacting brain cell type-specific DNA methylation and illuminates genetic bases of brain disorders

genetics↗

bioRxiv2023

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [18F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a bench to bedside translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.

neuroscience↗

bioRxiv2022

Ventral forebrain organoids derived from individuals with schizophrenia recapitulate perturbed striatal gene expression dynamics of the donor's brains

Schizophrenia (SCZ) is a brain disorder originating during neurodevelopment with complex genetic and environmental etiologies. Despite decades of clinical evidence of altered striatal function in affected patients, its cellular and molecular underpinnings remain unclear. Here, to explore neurodevelopmental alterations in the striatum associated with SCZ, we established a method for the differentiation of iPS cells into ventral forebrain organoids. Given substantial genetic heterogeneity among individuals, which can obscure disease-associated phenotypes, we generated organoids from postmortem dural fibroblast-derived iPS cells of 3 patients and 4 healthy control individuals with nonoverlapping polygenic risk score (PRS) for SCZ and whose genotype and postmortem caudate transcriptomic data were profiled in the Brainseq neurogenomics consortium. Single cell RNA sequencing (scRNA-seq) analyses of the organoids revealed differences in developmental trajectory between SCZ cases and controls in which inhibitory neurons from patients exhibited accelerated maturation. Furthermore, we found a significant overlap of genes upregulated in the inhibitory neurons in SCZ organoids with upregulated genes in postmortem caudate tissues from patients with SCZ compared with control individuals, including the donors of our iPS cell cohort. Our findings suggest that striatal neurons in the patients with SCZ carry abnormalities that originated during early brain development and a ventral forebrain striatal organoid model can recapitulate those neurodevelopmental phenotypes in a dish.

neuroscience↗

bioRxiv2022

Variation in TAF1 expression in female carrier induced pluripotent stem cells and human brain ontogeny has implications for adult neostriatum vulnerability in X-linked Dystonia Parkinsonism

X-linked Dystonia-Parkinsonism (XDP) is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. The mechanisms underlying regional differences in degeneration and age of onset are unknown. Developing therapeutics that target XDP-related mechanisms requires a deeper understanding of how XDP-relevant features vary in health and disease. XDP is due, in part, to either a partial loss of TAF1 function and/or a SVA-driven pathological gain of function. A disease-specific SINE-VNTR-Alu (SVA) retrotransposon insertion occurs within intron 32 of TAF1, a subunit of TFIID involved in transcription initiation. While all XDP males are usually clinically affected, females are heterozygous carriers generally not manifesting the full syndrome. As a resource for disease modeling, we characterized eight iPSC lines from XDP female carrier individuals, and identified isogenic lines where one clonal iPSC line expressed the wild-type X, and the two other clonal iPSC lines expressed the XDP haplotype. Furthermore, we characterized XDP-relevant transcript expression variation in humans, and found that SVA-F expression decreases slightly after 30 years of age in the neurotypical human brain and that TAF1 is modestly decreased in the majority of female samples. Uniquely in the caudate nucleus, TAF1 expression is not sexually dymorphic and decreased after 15 years of age. These findings indicate that regional-, age- and sex-specific mechanisms regulate TAF1, highlighting the importance of disease-relevant models and postmortem tissue analysis. We propose that the decreased TAF1 expression in the adult caudate may synergize with the XDP-specific partial loss of TAF1 function in patients, thereby passing a minimum threshold of TAF1 function, and triggering degeneration in the neostriatum. Significance StatementXDP is an inherited, X-linked, adult-onset movement disorder characterized by degeneration in the neostriatum. No therapeutics alter disease progression. Developing therapeutics requires a deeper understanding of how XDP-relevant features vary in health and disease. XDP is possibly due to a partial loss of TAF1 function. While all XDP males are usually affected, females are heterozygous carriers generally not manifesting the full syndrome. As a resource for disease modeling, we characterized eight stem cell lines from XDP female carrier individuals. Furthermore, we found that, uniquely in the caudate nucleus, TAF1 expression decreases after adolescence in healthy humans. We hypothesize that the decrease of TAF1 after adolescence in human caudate, in general, may underlie the vulnerability of the adult neostriatum in XDP.

neuroscience↗

bioRxiv2021

Genotype and age influence cortical-FKBP5 at multiple regulatory and single-cell-type levels in severe psychiatric disorders

Identification and characterisation of novel targets for treatment is a priority in the field of psychiatry. FKBP5 is a gene with decades of evidence suggesting its pathogenic role in a subset of psychiatric patients, with potential to be leveraged as a therapeutic target for these individuals. While it is widely reported that FKBP5/FKBP51 mRNA/protein (FKBP5/1) expression is impacted by psychiatric disease state, risk genotype and age, it is not known in which cell-types and sub-anatomical areas of the human brain this occurs. This knowledge is critical to propel FKBP5/1-targeted treatment development. Here, we performed an extensive, large-scale postmortem study (n=1024) of FKBP5/1 examining prefrontal cortex (BA9, BA11, BA24) derived from subjects that lived with schizophrenia, major depression or bipolar disorder. With an extensive battery of RNA (bulk RNA sequencing, single-nucleus RNA sequencing, microarray, qPCR, RNAscope) and protein (immunoblot, immunohistochemistry) analysis approaches, we thoroughly investigated the effects of disease-state, aging and genotype on cortical FKBP5/1 expression including in a cell-type specific manner. We identified consistently heightened FKBP5/1 levels in psychopathology and with age, but not genotype, with these effects strongest in schizophrenia. Using single-nucleus RNA sequencing (snRNAseq) and targeted histology, we established that these disease- and aging-effects on FKBP5/1 expression were most pronounced in excitatory supragranular neurons. We then found that this increase in FKBP5 levels likely impacts on synaptic plasticity, as FKBP5 gex levels strongly and inversely correlated with dendritic mushroom spine density and brain-derived neurotrophic factor (BDNF) levels in supragranular neurons. These findings pinpoint a novel cellular and molecular mechanism that has significant potential to open a new avenue of FKBP51 drug development to treat cognitive symptoms in psychiatric disorders.

neuroscience↗

bioRxiv2020

Strategies for cellular deconvolution in human brain RNA sequencing data

Statistical deconvolution strategies have emerged over the past decade to estimate the proportion of various cell populations in homogenate tissue sources like brain using gene expression data. Here we show that several existing deconvolution algorithms which estimate the RNA composition of homogenate tissue, relates to the amount of RNA attributable to each cell type, and not the cellular composition relating to the underlying fraction of cells. Incorporating "cell size" parameters into RNA-based deconvolution algorithms can successfully recover cellular fractions in homogenate brain RNA-seq data. We lastly show that using both cell sizes and cell type-specific gene expression profiles from brain regions other than the target/user-provided bulk tissue RNA-seq dataset consistently results in biased cell fractions. We report several independently constructed cell size estimates as a community resource and extend the MuSiC framework to accommodate these cell size estimates (https://github.com/xuranw/MuSiC/).

genomics↗

bioRxiv2019

Characterizing the dynamic and functional DNA methylation landscape in the developing human cortex

DNA methylation (DNAm) is a key epigenetic regulator of gene expression across development. The developing prenatal brain is a highly dynamic tissue, but our understanding of key drivers of epigenetic variability across development is limited. We therefore assessed genomic methylation at over 39 million sites in the prenatal cortex using whole genome bisulfite sequencing and found loci and regions in which methylation levels are dynamic across development. We saw that DNAm at these loci was associated with nearby gene expression and enriched for enhancer chromatin states in prenatal brain tissue. Additionally, these loci were enriched for genes associated with psychiatric disorders and genes involved with neurogenesis. We also found autosomal differences in DNAm between the sexes during prenatal development, though these have less clear functional consequences. We lastly confirmed that the dynamic methylation at this critical period is specifically CpG methylation, with very low levels of CpH methylation. Our findings provide detailed insight into prenatal brain development as well as clues to the pathogenesis of psychiatric traits seen later in life.

neuroscience↗

bioRxiv2019

Parietal prefrontal feedforward connectivity in association with schizophrenia genetic risk and delusions

BackgroundConceptualizations of delusion formation implicate, in part, deficits at feed-forward information transfer across posterior to prefrontal cortices, resulting in dysfunctional integration of new information in favor of over-familiar prior beliefs. Here, we used functional MRI and machine learning models to examine feedforward parietal-prefrontal information transfer in schizophrenia patients in relation to delusional thinking, and polygenic risk for schizophrenia.\n\nMethodsWe studied 66 schizophrenia patients and 143 healthy controls as they performed context updating during working memory (WM). Dynamic causal models of effective connectivity were focused on prefrontal and parietal cortex, where we examined parietal-prefrontal connectivity in relation to delusions in patients. We further tested for an effect of polygenic risk for schizophrenia on connectivity in healthy individuals. We then leveraged support vector regression models to define optimal normalized target connectivity tailored for each patient, and tested the extent to which deviation from this target predicted individual variation in delusion severity.\n\nResultsIn schizophrenia patients, updating and manipulating context information was disproportionately less accurate than was WM maintenance, with a task accuracy-by-diagnosis interaction. Also, patients with delusions tended to have relatively reduced feedforward effective connectivity during context updating in WM manipulation. The same parietal-prefrontal feedforward prefrontal effective connectivity was adversely influenced by polygenic risk for schizophrenia in healthy subjects. Individual patients deviation from predicted normal feedforward connectivity based on the support vector models correlated with delusional severity.\n\nConclusionsThese computationally-derived observations support a role for feed-forward parietal-prefrontal information processing deficits in delusional psychopathology, and in genetic risk for schizophrenia.

neuroscience↗

bioRxiv2019

Characterizing the nuclear and cytoplasmic transcriptomes in developing and mature human cortex uncovers new insight into psychiatric disease gene regulation

Transcriptome compartmentalization by the nuclear membrane provides both stochastic and functional buffering of transcript activity in the cytoplasm and has recently been implicated in neurodegenerative disease processes. Although many mechanisms regulating transcript compartmentalization are also prevalent in brain development, the extent to which subcellular localization differs as the brain matures has yet to be addressed. To characterize the nuclear and cytoplasmic transcriptomes during brain development, we sequenced both RNA fractions from homogenate prenatal and adult human postmortem cortex using PolyA+ and RiboZero library preparation methods. We find that while many genes are differentially expressed by fraction and developmental expression changes are similarly detectable in nuclear and cytoplasmic RNA, the compartmented transcriptomes become more distinct as the brain matures, perhaps reflecting increased utilization of nuclear retention as a regulatory strategy in adult brain. We examined potential mechanisms of this developmental divergence including alternative splicing, RNA editing, nuclear pore composition, RNA binding protein motif enrichment, and RNA secondary structure. Intron retention is associated with greater nuclear abundance in a subset of transcripts, as is enrichment for several splicing factor binding motifs. Finally, we examined disease association with fraction-regulated gene sets and found nuclear-enriched genes were also preferentially enriched in gene sets associated with neurodevelopmental psychiatric diseases. These results suggest that although gene-level expression is globally comparable between fractions, nuclear retention of transcripts may play an underappreciated role in developmental regulation of gene expression in brain, particularly in genes whose dysregulation is related to neuropsychiatric disorders.

neuroscience↗

bioRxiv2018

Differences in Pneumococcal Serotype Replacement in Individuals with and without Underlying Medical Conditions

BackgroundPneumococcal conjugate vaccines (PCVs) have had a well-documented impact on the incidence of invasive pneumococcal disease (IPD) worldwide. However, declines in IPD due to vaccine-targeted serotypes have been partially offset by increases in IPD due to non-vaccine serotypes. The goal of this study was to quantify serotype-specific changes in the incidence of IPD that occurred in different age groups, with or without certain co-morbidities, following the introduction of PCV7 and PCV13 in the childhood vaccination program in Denmark.\n\nMethodsWe used nationwide surveillance data for IPD in Denmark and a hierarchical Bayesian regression framework to estimate changes in the incidence of IPD associated with the introduction of PCV7 (2007) and PCV13 (2010) while controlling for serotype-specific epidemic cycles and unrelated secular trends.\n\nResults and ConclusionsFollowing the introduction of PCV7 and 13 in children, the net impact of serotype replacement varied considerably by age group and the presence of comorbid conditions. Serotype replacement offset a greater fraction of the decline in vaccine-targeted serotypes following the introduction of PCV7 compared with the period following the introduction of PCV13. Differences in the magnitude of serotype replacement were due to variations in the incidence of non-vaccine serotypes in the different risk groups before the introduction of PCV7 and PCV13. The relative increases in the incidence of IPD caused by non-vaccine serotypes did not differ appreciably in the post-vaccination period. Serotype replacement offset a greater proportion of the benefit of PCVs in strata in which the non-vaccine serotypes comprised a larger proportion of cases prior to the introduction of the vaccines. These findings could help to predict the impact of next-generation conjugate vaccines in specific risk groups.

epidemiology↗

bioRxiv2018

Long-read sequencing reveals the splicing profile of the calcium channel gene CACNA1C in human brain

RNA splicing is a key mechanism linking genetic variation with psychiatric disorders. Splicing profiles are particularly diverse in brain and difficult to accurately identify and quantify. We developed a new approach to address this challenge, combining long-range PCR and nanopore sequencing with a novel bioinformatics pipeline. We identify the full-length coding transcripts of CACNA1C in human brain. CACNA1C is a psychiatric risk gene that encodes the voltage-gated calcium channel CaV1.2. We show that CACNA1Cs transcript profile is substantially more complex than appreciated, identifying 38 novel exons and 241 novel transcripts. Importantly, many of the novel variants are abundant, and predicted to encode channels with altered function. The splicing profile varies between brain regions, especially in cerebellum. We demonstrate that human transcript diversity (and thereby protein isoform diversity) remains under-characterised, and provide a feasible and cost-effective methodology to address this. A detailed understanding of isoform diversity will be essential for the translation of psychiatric genomic findings into pathophysiological insights and novel psychopharmacological targets.

neuroscience↗

bioRxiv2018

Association of a lincRNA postmortem with suicide by violent means and in vivo with aggressive phenotypes

ObjectivePrevious findings suggest that differences in brain expression of a human-specific long intergenic non-coding RNA (LINC01268; GRCh37/hg19: LOC285758) may be linked to aggressive behavior and suicide. The authors sought to replicate and extend these findings in a new sample, and translate the results to the behavioral level in living healthy subjects.\n\nMethodThe authors examined RNA sequencing data in human brain to confirm the prior postmortem association of the lincRNA specifically with suicide by violent means. In addition, they used a genetic variant associated with LINC01268 expression to detect association with in vivo prefrontal physiology related to behavioral control. They finally performed weighted gene co-expression network analysis (WGCNA) and gene-ontology analysis to identify biological processes associated with a LINC01268 co-expression network.\n\nResultsIn the replication sample, prefrontal expression of LINC01268 was again higher in suicides by violent means (N=65) than both non-suicides (N=78; 1.29e-06) and suicides by non-violent means (N=46; p=1.4e-06). In a living cohort, carriers of the minor allele of a SNP associated with increased LINC01268 expression in brain scored higher on a lifetime aggression questionnaire and show diminished engagement of prefrontal cortex (BA10) when viewing angry faces during fMRI. WGCNA highlighted the immune response.\n\nConclusionsThese results suggest that LINC01268 influences emotional regulation, aggressive behavior and suicide by violent means; the underlying biological dynamics may include modulation of genes potentially engaged in the immune response.

neuroscience↗