Biology subjects

Morris, D. W.

Publications and source records attributed to Morris, D. W..

11 recordsLinked to original sources

bioRxiv2026

Co-expression-based models improve eQTL predictions and highlightnovel transcriptome-wide genes associated with schizophrenia

Non-coding genetic variants statistically associated with complex heritability phenotypes are thought to act primarily through transcriptome regulatory mechanisms. Predictions of gene expression in tissue like the human brain traditionally rely primarily on cis-eQTLs. Here, we introduce INGENE and MODULE, trans-eQTLs models designed to enhance the prediction of gene expression by capturing the collective impact of candidate trans-eQTLs acting within co-expression networks. Exploiting RNA-seq data in six post-mortem brain regions (amygdala, caudate nucleus, dorsal/subgenual anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus), we validate our models on two testing datasets, demonstrating increased gene predictability compared to both an original cis-based model and to EpiXcan, the leading benchmark in cis-model performance. Integration of cis- and trans-predictions significantly improves gene-level expression imputation (MLE = 0.05) for 18,744 genes across the six brain regions considered. Applying cis and trans models to PGC wave 3 genotypes identifies 766 SCZ-associated genes across brain regions (pFDR < .01), emphasizing the complementary nature of cis and trans predictions in trait association discovery. Of these genes, 641 represent novel transcriptome-wide associations with schizophrenia, highlighting the role of trans-heritability and genetic interactions underlying risk for this disorder, in addition to further supporting 125 previous candidates.

genomics↗

bioRxiv2025

The Dynamic Nature of Genetic Risk for Schizophrenia Within Genes Regulated by FOXP1 During Neurodevelopment

FOXP1 (Forkhead-box protein P1) is a crucial transcription factor in neural development and is associated with schizophrenia (SCZ). FOXP1-regulated genes may contribute to genetic risk of SCZ and this may vary across different stages of neurodevelopment. We analyzed transcriptomic data from mouse and human models of FOXP1 loss-of-function across prenatal and postnatal developmental stages, including neural stem cells from embryonic mice (E14.5) and human brain organoids (equivalent to second trimester), and cortical tissues from different mouse postnatal stages P0, P7, and P47. P0 in mice corresponds to the third trimester in humans, while P7 and P47 represent early childhood and adolescence, respectively. The effect of FOXP1 disruption on gene expression in cortical tissues/cells was assayed using RNA-seq, including time-course and pairwise gene expression analysis. Linkage disequilibrium score regression assessed if FOXP1-regulated genes were enriched for SCZ heritability. Gene-set enrichment analysis investigated if FOXP1-regulated genes were enriched for SCZ-associated genes reported as differentially expressed in single cortical cell studies. SynGO analysis mapped FOXP1-regulated genes to synaptic locations and functions. FOXP1-regulated genes are enriched for SCZ heritability, with significant results for E14.5, P7 and P47 but not P0. The P7 gene-set showed the strongest enrichment for SCZ-associated genes from single cortical cell studies. FOXP1-regulated genes at both P7 and P47 were involved in multiple synaptic functions and were mainly enriched within glutamatergic excitatory neurons, with P47 also showing enrichment within GABAergic inhibitory neurons across regions of the postnatal cortex. Prenatal FOXP1-regulated genes were enriched in progenitor cells and also mapped to the synapse. Genetic risk for SCZ within FOXP1-regulated genes follows a dynamic trajectory across developmental stages, showing stronger effects at timepoints that map to early childhood, followed by adolescence and second trimester. Author SummarySchizophrenia is a complex disorder caused by many genes. While existing treatments can help manage some positive symptoms, such as hallucinations and delusions, they are not effective in treating other life-limiting symptom areas. As a result, individuals with schizophrenia continue to face significant challenges, including disability, unemployment, homelessness, and social isolation. Genome-wide association studies of schizophrenia have been effective at identifying individual SNPs and genes that contribute to these phenotypes but have struggled to immediately uncover the bigger picture of the underlying biology of the disorder. Here we take an individual gene associated with schizophrenia risk, FOXP1, which is an important regulator of brain development. Using functional genomics data from models where FOXP1 has been disrupted, we identified sets of genes regulated by FOXP1 across different developmental stages, focusing on the cortical region of the brain. Our findings reveal that FOXP1-regulated genes are most strongly associated with schizophrenia during early childhood and adolescence. These genes are associated with synaptic components, including presynaptic and postsynaptic structures. By integrating developmental timing, cell type specificity, and functional pathways, this study provides valuable insights into the molecular mechanisms underlying schizophrenia.

genomics↗

bioRxiv2025

Spatial profiling identifies regionally distinct microenvironments and targetable immunosuppressive mechanisms in pediatric osteosarcoma pulmonary metastases.

Osteosarcoma is the most common malignant bone tumor in young patients and remains a significant clinical challenge, particularly in the context of metastatic disease. Despite extensive documentation of genomic alterations in osteosarcoma, studies detailing the immunosuppressive mechanisms within the metastatic osteosarcoma microenvironment are lacking. Our objective was to characterize the spatial transcriptional landscape of metastatic osteosarcoma to reveal these immunosuppressive mechanisms and identify promising therapeutic targets. Here, we performed spatial transcriptional profiling on a cohort of osteosarcoma pulmonary metastases from pediatric patients. We reveal a conserved spatial gene expression pattern resembling a foreign body granuloma, characterized by peripheral inflammatory signaling, fibrocollagenous encapsulation, lymphocyte exclusion, and peritumoral macrophage accumulation. We also show that the intratumoral microenvironment of these lesions lack inflammatory signaling. Additionally, we identified CXCR4 as an actionable immunomodulatory target that bridges both the intratumoral and extratumoral microenvironments and highlights the spatial heterogeneity and complexity of this pathway. Collectively, this study reveals that metastatic osteosarcoma specimens are comprised of multiple regionally distinct immunosuppressive microenvironments.

cancer biology↗

bioRxiv2023

Direct targets of MEF2C are enriched for genes associated with schizophrenia and cognitive function and are involved in neurogenesis and mitochondrial function

Myocyte Enhancer Factor 2C (MEF2C) is a transcription factor that plays a crucial role in neurogenesis and synapse development. Genetic studies have identified MEF2C as a gene that influences cognition and risk for neuropsychiatric disorders, including autism spectrum disorder (ASD) and schizophrenia (SCZ). Here, we investigated the involvement of MEF2C in these phenotypes using human-derived neural stem cells (NSCs) and induced neurons (iNs), which represented early and late neurodevelopmental stages. For these cellular models, MEF2C function had previously been disrupted, either by direct or indirect mutation, and gene expression assayed using RNA-seq. We integrated these RNA-seq data with MEF2C ChIP-seq data to identify dysregulated direct target genes of MEF2C in the NSCs and iNs models. Several MEF2C direct target gene-sets were enriched for SNP-based heritability for intelligence, educational attainment and SCZ, as well as being enriched for genes containing rare de novo mutations reported in ASD and/or developmental disorders. These gene-sets are enriched in both excitatory and inhibitory neurons in the hippocampus and cortex and are involved in a wide range of biological processes including neurogenesis, metabolic processes, protein modifications, as well as mitochondrial function and energy production. We observed a trans expression quantitative trait locus (eQTL) effect of a single SNP at MEF2C (rs6893807, which is associated with IQ) on the expression of a target gene, BNIP3L. BNIP3L is a prioritized risk gene from the largest genome-wide association study of SCZ and has a function in mitophagy in mitochondria. Overall, our analysis reveals that either direct or indirect disruption of MEF2C dysregulates sets of genes that contain multiple alleles associated with SCZ risk and cognitive function and implicates neurogenesis and mitochondrial function in the etiology of these phenotypes. Author SummarySchizophrenia is a complex disorder caused by many genes. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability, leading to unemployment, homelessness and social isolation. Genome-wide association studies of schizophrenia and cognitive function have been effective at identifying individual SNPs and genes that contribute to these phenotypes but have struggled to immediately uncover the bigger picture of the underlying biology of the disorder. Here we take an individual gene associated with schizophrenia and cognitive function called MEF2C, which on its own is a very important regulator of brain development. We use functional genomics data from studies where MEF2C has been mutated to identify sets of other genes that are influenced by MEF2C in developing and mature neurons. We show that several of these gene-sets are enriched for common variants associated with schizophrenia and cognitive function, and for rare variants that increase risk of various neurodevelopmental disorders. These gene-sets are involved in neurogenesis and mitochondrial function, providing evidence that these biological processes may be important in the context of the molecular mechanisms that underpin schizophrenia and cognitive function.

genetics↗

bioRxiv2023

Social isolation-induced transcriptomic changes in mouse hippocampus impact the synapse and show convergence with human genetic risk for neurodevelopmental phenotypes

Early life stress (ELS) can impact brain development and is a risk factor for neurodevelopmental disorders such as schizophrenia. Post-weaning social isolation (SI) is used to model ELS in animals, using isolation stress to disrupt a normal developmental trajectory. We aimed to investigate how SI affects the expression of genes in mouse hippocampus and to investigate how these changes related to the genetic basis of neurodevelopmental phenotypes. BL/6J mice were exposed to post-weaning SI (PD21-25) or treated as group-housed controls (n = 7-8 per group). RNA sequencing was performed on tissue samples from the hippocampus of adult male and female mice. Four hundred and 1,215 differentially-expressed genes (DEGs) at a false discovery rate of < 0.05 were detected between SI and control samples for males and females respectively. DEGS for both males and females were significantly overrepresented in gene ontologies related to synaptic structure and function, especially the post-synapse. DEGs were enriched for common variant (SNP) heritability in humans that contributes to risk of neuropsychiatric disorders (schizophrenia, bipolar disorder) and to cognitive function. DEGs were also enriched for genes harbouring rare de novo variants that contribute to autism spectrum disorder and other developmental disorders. Finally, cell type analysis revealed populations of hippocampal astrocytes that were enriched for DEGs, indicating effects in these cell types as well as neurons. Overall, these data suggest a convergence between genes dysregulated by the SI stressor in the mouse and genes associated with neurodevelopmental disorders and cognitive phenotypes in humans. Author SummaryEarly life stress increases risk of developing neuropsychiatric and neurodevelopmental disorders. Early life stress can be modelled in animals using social isolation (SI) where animals are separated from others after they have stopped weaning and are housed individually rather than in groups. Here, we investigated the effect of SI on gene expression in the hippocampus, a brain region that regulates stress response and emotion, and how this relates to the known genetic aetiology of neuropsychiatric disorders and traits such as cognitive function. We found that genes altered by SI play a role in how synapses form and function - these are the connection points between nerve cells in the brain. We also found these altered genes are also the genes where common changes in the DNA code can increase risk for schizophrenia, bipolar disorder and influence cognitive ability, and where rare changes in the DNA code increase risk for autism spectrum disorder and developmental disorder. Finally, these genes altered by SI are also highly expressed in astrocytes, cells that help nerve cells to function in the hippocampus. Overall, these data suggest a convergence between genes affected by SI, the environmental stressor, and the genes associated with neurodevelopmental disorders and cognition.

genomics↗

bioRxiv2022

SATB2 organizes the 3D genome architecture of cognition in cortical neurons

SATB2 is genetically associated with human intelligence. Since SATB2 protein structure predicts a function in DNA looping, we analyzed the impact of SATB2 on 3D genome architecture and chromatin accessibility in cortical neurons. Our data reveal strong effects of SATB2 on chromatin looping between enhancers and promoters of neuronal activity-regulated genes, which closely correlate with gene expression. We furthermore identify SATB2-dependent alterations at all 3D genome architectural levels, including compartments, Topologically Associated Domains and Frequently Interacting Regions. Genes linked to SATB2-dependent 3D genome changes are implicated in highly specialized neuronal functions and contribute to cognitive ability and risk for neuropsychiatric and neurodevelopmental disorders. The altered non-coding regions are enriched for common variants associated with educational attainment, intelligence and schizophrenia. Our data establish SATB2 as a 3D genome organizer, which operates both independently and in cooperation with CTCF to set up the chromatin landscape of pyramidal neurons for cognitive processes.

neuroscience↗

bioRxiv2022

Comparing the XGBoost machine learning algorithm to polygenic scoring for the prediction of intelligence based on genotype data

A polygenic score (PGS) is a linear combination of effects from a GWAS that represents and can be used to predict genetic predisposition to a particular phenotype. A key limitation of the PGS method is that it assumes additive and independent SNP effects, when it is known that epistasis (gene interactions) can contribute to complex traits. Machine learning methods can potentially overcome this limitation by virtue of their ability to capture nonlinear interactions in high dimensional data. Intelligence is a complex trait for which PGS prediction currently explains up to 5.2% of the variance, a relatively small proportion of the heritability estimate of 50% obtained from twin studies. Here, we use gradient boosting, a machine learning technique based on an ensemble of weak prediction models, to predict intelligence from genotype data. We found that while gradient boosting did not outperform the PGS method in predicting intelligence based on SNP data, it was capable of achieving similar predictive performance with less than a quarter of the SNPs with the top SNPs identified as being important for predictive performance being biologically meaningful. These results indicate that ML methods may be useful in interpreting the biological meaning underpinning SNP-phenotype associations due to the smaller number of SNPs required in the ML model as opposed to the standard PGS method based on GWAS.

bioinformatics↗

bioRxiv2021

Identification of 13 independent genetic loci associated with cognitive resilience in healthy aging in 330,097 individuals in the UK Biobank.

Cognitive resilience is the ability to withstand the negative effects of stress on cognitive functioning and is important for maintaining quality of life while aging. UK Biobank (UKB) does not have direct measurements of the same cognitive phenotype at distal timepoints. Therefore, we used number of education years (EY) as a proxy phenotype for past cognitive performance. Current cognitive performance was determined based on processing speed. This approach captured an average time span of 40 years between past and current cognitive performance in 330,097 individuals. A confounding factor was that EY is highly polygenic and masked the genetics of resilience. To overcome this, we employed Genomics Structural Equation Modelling (GenomicSEM) to perform a GWAS-by-subtraction using two GWAS, one GWAS of EY and resilience and a second GWAS of EY but not resilience. Subtracting one from the other generated a GWAS of Resilience. Replication of this approach was shown using independent discovery and replication samples within UKB and the full UKB GWAS results show significant genetic correlation with a GWAS of cognitive change in the independent Health and Retirement Study (N=9,526; P=1.5x10-3). We found 13 independent genetic loci for Resilience. Functional analyses showed enrichment in several brain regions and involvement of specific cell types, including GABAergic neurons (P=6.59x10-8) and glutamatergic neurons (P=6.98x10-6) in the cortex. Gene-set analyses implicated the biological process "neuron differentiation" (P=9.7x10-7) and the cellular component "synaptic part" (P=2.14x10-6). Mendelian randomization analysis showed a causative effect of white matter volume on cognitive resilience. These results enhance neurobiological understanding of resilience.

genomics↗

bioRxiv2020

Controlling for off-target genetic effects using polygenic scores improves the power of genome-wide association studies

Ongoing increases in the size of human genotype and phenotype collections offer the promise of improved understanding of the genetics of complex diseases. In addition to the biological insights that can be gained from the nature of the variants that contribute to the genetic component of complex trait variability, these data bring forward the prospect of predicting complex traits and the risk of complex genetic diseases from genotype data. Here we show that advances in phenotype prediction can be applied to improve the power of genome-wide association studies. We demonstrate a simple and efficient method to model genetic background effects using polygenic scores derived from SNPs that are not on the same chromosome as the target SNP. Using simulated and real data we found that this can result in a substantial increase in the number of variants passing genome-wide significance thresholds. This increase in power to detect trait-associated variants also translates into an increase in the accuracy with which the resulting polygenic score predicts the phenotype from genotype data. Our results suggest that advances in methods for phenotype prediction can be exploited to improve the control of background genetic effects, leading to more accurate GWAS results and further improvements in phenotype prediction.

genomics↗

bioRxiv2019

Genes influenced by MEF2C contribute to neurodevelopmental disease via gene expression changes that affect multiple types of cortical excitatory neurons

Myocyte enhancer factor 2 C (MEF2C) is an important transcription factor during neurodevelopment. Mutation or deletion of MEF2C causes intellectual disability (ID) and common variants within MEF2C are associated with cognitive function and schizophrenia risk. We investigated if genes influenced by MEF2C during neurodevelopment are enriched for genes associated with neurodevelopmental phenotypes, and if this can be leveraged to identify biological mechanisms and individual brain cell types affected. We used a set of 1,052 genes that were differentially expressed in the adult mouse brain following early embryonic deletion of Mef2c in excitatory cortical neurons. Using GWAS data, we found these differentially expressed genes (DEGs) to be enriched for genes associated with schizophrenia, intelligence and educational attainment but not autism spectrum disorder (ASD). Using sequencing data from trios studies, we found these DEGs to be enriched for genes containing de novo mutations reported in ASD and ID, but not schizophrenia. Using single cell RNA-seq data, we identified that a number of different excitatory glutamatergic neurons in the cortex were enriched for these DEGs including deep layer pyramidal cells and cells in the retrosplenial cortex, entorhinal cortex and subiculum. These data indicate that genes influenced by MEF2C during neurodevelopment contribute to cognitive function and risk of neurodevelopmental disorders. Within excitatory neurons, common SNPs in these genes contribute to cognition and SZ risk via an effect on synaptic function based on gene ontology analysis. In contrast, rare mutations contribute to earlier onset ASD and ID via an effect on cell morphogenesis. Author SummarySchizophrenia is a complex disorder caused by many genes. Current drugs for schizophrenia are only partially effective and do not treat cognitive deficits, which are key factors for explaining disability. Here we take an individual gene identified in genetic studies of schizophrenia and cognition called MEF2C, which on its own is a very important regulator of brain development. We use data from a mouse study where MEF2C has been stopped from functioning or knocked out during brain development. The effect of that knock out has been measured when the mice reach adulthood, in the form of a set of differentially expressed genes (DEGs) from the somatosensory cortex. We found that this set of DEGs contains more genes than expected by chance that are associated with schizophrenia and cognition or contain rare new (de novo) mutations reported in autism and intellectual disability. Using gene expression data from single brain cells, we identified that a number of specific excitatory glutamatergic neurons in the cortex were enriched for these DEGs. This study provides evidence that the molecular mechanisms that underpin schizophrenia and cognitive function include disruption of cell types influenced by MEF2C.

genomics↗

bioRxiv2018

Association between schizophrenia and both loss of function and missense mutations in paralog conserved sites of voltage-gated sodium channels

Sequencing studies have highlighted candidate sets of genes involved in schizophrenia, including activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Two genes, SETD1A and RBM12, have also been associated with robust statistical evidence. Larger samples and novel methods for identifying disease-associated missense variants are needed to reveal novel genes and biological mechanisms associated with schizophrenia. We sequenced 187 genes, selected for prior evidence of association with schizophrenia, in a new dataset of 5,207 cases and 4,991 controls. Included were members of ARC and NMDAR post-synaptic protein complexes, as well as voltage-gated sodium and calcium channels. We observed a significant case excess of rare (<0.1% in frequency) loss-of-function (LoF) mutations across all 187 genes (OR = 1.36; Pcorrected = 0.0072) but no individual gene was associated with schizophrenia after correcting for multiple testing. We found novel evidence that LoF and missense variants at paralog conserved sites were enriched in sodium channels (OR = 1.26; P = 0.0035). Meta-analysis of our new data with published sequencing data (11,319 cases, 15,854 controls and 1,136 trios) supported and refined this association to sodium channel alpha subunits (P = 0.0029). Meta-analysis also confirmed association between schizophrenia and rare variants in ARC (P = 4.0 x 10-4) and NMDAR (P = 1.7 x 10-5) synaptic genes. No association was found between rare variants in calcium channels and schizophrenia.\n\nIn one of the largest sequencing studies of schizophrenia to date, we provide novel evidence that multiple voltage-gated sodium channels are involved in schizophrenia pathogenesis, and increase the evidence for association between rare variants in ARC and NMDAR post-synaptic complexes and schizophrenia. Larger samples are required to identify specific genes and variants driving these associations.\n\nAuthor SummaryCommon and rare genetic variations are known to play a substantial role in the development of schizophrenia. Recently, sequencing studies have started to highlight specific sets of genes that are enriched for rare variation in schizophrenia, such as the synaptic gene sets ARC and NMDAR, as well as voltage-gated sodium and calcium channels. To confirm the role of these gene sets in schizophrenia, and identify specific risk genes, we sequenced 187 genes in a new sample of 5,207 schizophrenia cases and 4,991 controls. We find an excess of protein truncating mutations with a frequency <0.1% in all 187 targeted genes, and provide novel evidence that mutations altering amino acids conserved across sodium channel proteins are risk factors for schizophrenia. Through meta-analysing our new data with previously published sequencing data sets, for a total of 11,319 cases, 15,854 controls and 1,136 trios, we increase the evidence for association between rare coding variants and schizophrenia in voltage-gated sodium channels, as well as in synaptic gene sets ARC and NMDAR. Although no individual gene was associated with schizophrenia, these findings suggest larger studies will identify the specific genes driving these associations.

genetics↗