Biology subjects

Klei, L.

Publications and source records attributed to Klei, L..

14 recordsLinked to original sources

bioRxiv2026

Autism genes converge on three functional programs organized by neuronal subclass, developmental timing, and cortical patterning

Our companion sequencing study uncovered 253 genes robustly associated with autism spectrum disorder (ASD), yet the biological programs they impact, and the cellular, developmental, and spatial contexts in which they converge, remain unresolved. Here we systematically contextualize genes associated with ASD across neurodevelopment and cortical areas, integrating developmental single-cell and spatial atlases with gene- and isoform co-expression, regulatory, proteomic, and synaptic networks. Genetic burden concentrates within temporally-resolved neuronal subclasses: newborn excitatory neurons, immature interneurons, and maturing intratelencephalic lineages. Genes associated with ASD converge on three functional programs--gene regulation, neuronal morphogenesis, and synaptic transmembrane signaling machinery--resolved from 28 ASD-associated networks, several of which are directly regulated by ASD genes including MEF2C, SOX11, and FOXP2. These programs are spatially patterned, with risk genes exhibiting an increasing anterior-to-posterior cortical expression gradient, anchored in the primary visual cortex and driven by excitatory neuron gene-regulatory programs. Finally, ASD risk genes associated with more severe developmental phenotypes show broader excitatory neuron enrichment and less interneuron involvement. Together, these findings anchor ASD genetic vulnerability to specific neurodevelopmental lineages, epochs, and molecular substrates, and delineate the features that distinguish ASD from comorbidities with broader developmental impacts.

genomics↗

bioRxiv2026

Proteomic profiling across early postnatal development of midbrain dopamine axons innervating the dorsal striatum

Precise wiring and tuning of dopamine axons in the brain is crucial for normal development of basal ganglia circuits. This process takes place both pre and postnatally, with early postnatal windows reflecting important periods of terminal maturation. Protein expression and precise localization are vital to this process, underlying changes in axon structure and function. Yet, technical hurdles have prohibited mapping protein expression and localization as dopamine axons mature to form functional release sites. Here we employ targeted proximity labeling in midbrain dopamine neurons and track isolated distal axonal proteins in the striatum across development, from the neonatal period through adolescence. Our approach enabled high-precision evaluation of the axonal proteome, supported by a combination of Cre-recombinase based restriction and spatial separation. We map co-varying subpopulations of axonal proteins differentially expressed across development. Microtubule-associated proteins decreased over time, revealing temporal dynamics of dopaminergic axon stabilization at the proteomic level. Conversely, proteins supporting coordinated action potential firing increased over time, likely contributing to the characteristic tonic firing of dopamine neurons emerging over development. Intersecting our findings with recent GWAS of psychiatric and neurological disorders provided functional confirmation of disease and disorder risk. This analysis highlighted early expression and localization of risk gene products, providing spatial-temporal points of convergence for disease-associated variants specifically to the initial stages of postnatal neurodevelopment of dopamine neurons. Together, these findings provide the essential grounding for understanding postnatal dopaminergic axon development and contextualize neurodevelopmental functions for numerous risk gene products.

neuroscience↗

bioRxiv2026

Novel transplantable mouse cell line model recapitulates invasive lobular breast carcinoma (ILC) phenotype and immune microenvironment.

Invasive lobular breast carcinoma (ILC) is the most common special histological subtype of breast cancer, which accounts for 10-15% of all cases. To study the phenotype characteristics, metastatic growth kinetic and immune microenvironment of ILC, we developed an orthotopically transplantable cell line model from the spontaneous mammary fat pad tumor of CDH1-PTEN dual knockout C57BL/6 mouse with Cre-loxP system, designated CPT6. CPT6 recapitulates single-file growth pattern of human ILC, with pleomorphic features and a high mitotic index. RNA sequencing together with whole exome sequencing reveals a luminal A subtype with targetable driver mutations such as Kras G12C. As a novel orthotopically transplantable ILC model in immune competent mice, CPT6 shows robust in vivo growth and metastatic rate, and has moderate immunogenicity which appears to be T-cell independent. We also profiled the immune microenvironment of CPT6, revealing a myeloid-rich environment with dominant M2-macrophage population, which is concordant with human ILC. In summary, this model recapitulates human ILC phenotype and represents a valuable preclinical platform for evaluating immunotherapy and other therapeutic strategies for invasive lobular breast carcinoma.

cancer biology↗

bioRxiv2026

Estimating protein isoform abundances with PAQu

A single gene can encode multiple versions of a protein, dubbed isoforms, with varying functionality. Cellular control of isoform abundances is critical for multiple aspects of biology and is only partially regulated by transcript levels. While long-read sequencing facilitates transcript quantification, quantifying the resulting protein isoforms on a large scale is a major challenge, complicating biological interpretation of transcript alterations. Standard "bottom up" mass spectrometry can assess only short portions of isoforms called peptides, and these peptides often map onto more than one isoform. We introduce PAQu, a novel Bayesian method that leverages multiomic information from the peptidome and transcriptome to provide accurate estimates of isoform abundance even when peptide mapping is ambiguous. PAQu offers several advantages over existing methods in a unified framework. It provides uncertainty quantification, integrates multiomic information for improved accuracy, and provides a rigorous framework for hypothesis testing. Extensive simulations show that PAQu consistently outperforms competing methods in detecting differentially expressed protein isoforms and estimating their abundances. We use PAQu to investigate differences in isoform abundance levels between people with schizophrenia and control subjects, confirming a long held hypothesis that levels of the C4A isoform of Complement Component 4 are increased in schizophrenia while C4B is not. These results demonstrate that PAQu can identify significant variations in isoform abundance levels not previously possible.

genomics↗

bioRxiv2025

A framework to infer de novo exonic variants when parental genotypes are missing enhances association studies of autism

MotivationGene-damaging mutations are highly informative for studies seeking to discover genes underlying developmental disorders. Traditionally, these de novo variants are recognized by evaluating high-quality DNA sequence from affected offspring and parents. However, when parental sequence is unavailable, methods are required to infer de novo status and use this inference for association studies. ResultsWe use data from autism spectrum disorder to illustrate and evaluate methods. Separating de novo from rare inherited variants is challenging because the latter are far more common. Using a classifier for unbalanced data and variants of known inheritance class, we build an inheritance model and then a de novo score for variants when parental data are missing. Next, we propose a new Random Draw (RD) model to use this score for gene discovery. Built into an existing inferential framework, RD produces a more powerful gene-based association test and controls the false discovery rate. Availability and ImplementationThe implementation code and publicly available data are provided at: https://github.com/HaeunM/TADA-RD.

bioinformatics↗

bioRxiv2025

Transcriptomes of higher order thalamic nuclei in obsessive compulsive disorder

Obsessive-compulsive disorder (OCD) is a chronic psychiatric illness associated with altered function in cortico-striatal-thalamo-cortical (CSTC) circuits. In this pilot study, we examined differential RNA expression in the thalamus using postmortem human brain tissue samples from 11 subjects with OCD and 10 unaffected subjects. We individually dissected the mediodorsal magnocellular, mediodorsal parvocellular, and ventral anterior nuclei, which participate in orbitofrontal and anterior cingulate CSTC circuits most frequently associated with OCD, and the posterior ventrolateral nucleus, which participates in premotor and motor circuits that are increasingly implicated in OCD. Preselected GABAergic, glutamatergic and ion channel genes were analyzed via qPCR. Two genes required for GABA synthesis and release, GAD1 and SLC32A1, were found to be downregulated in OCD subjects across all nuclei, and potassium channel KCNN3 was upregulated. In parallel, we performed an exploratory total RNAseq differential expression analysis. We identified few (12 - 52) differentially expressed genes (DEGs) in each nucleus, and only one DEG in a pooled analysis of all nuclei. No DEGs were significant after correction for multiple comparisons. Investigation by model selection indicated that OCD diagnosis was not a useful factor in modelling gene expression in our dataset. OCD was also not associated with any modules of co-expressed genes identified using weighted gene correlation network analysis. Overall, we found minimal evidence of differential RNA expression in these thalamic nuclei in OCD. These findings contrast with our previous work including many of the same subjects where we found widespread differential mRNA expression in the orbitofrontal cortex and striatum in OCD.

neuroscience↗

bioRxiv2025

PACS1 syndrome variant alters proteomic landscape of developing cortical organoids

PACS1 syndrome is a neurodevelopmental disorder (NDD) resulting from a unique de novo p.R203W variant in Phosphofurin Acidic Cluster Sorting protein 1 (PACS1). PACS1 encodes a multifunctional sorting protein required for localizing furin to the trans-Golgi network. Although few studies have started to investigate the impact of the PACS1 p.R203W variant, the mechanisms by which the variant affects neurodevelopment are still poorly understood. In recent years, autism spectrum disorder (ASD) patient-derived brain organoids have been increasingly used to identify pathogenic mechanisms and possible therapeutic targets. While most of these studies evaluate the mechanisms by which ASD-risk genes affect the transcriptome, studies considering the proteome are limited. Here, we examine the effect of PACS1 p.R203W on the proteomic landscape of brain organoids using tandem mass tag (TMT) mass-spectrometry. Time series analysis between PACS1(+/+) and PACS1(+/R203W) organoids uncovered several proteins with dysregulated abundance or phosphorylation status, including known PACS1 interactors. Although we observed low overlap between proteins with altered expression and phosphorylation, the resulting dysregulated processes converged. The presence of the PACS1 p.R203W variant accelerated the emergence of proteins related to synaptogenesis and impaired vesicle loading and recycling. The earlier presence of these proteins and their related processes could lead to defective and/or incomplete synaptic function. Key dysregulated proteins observed in PACS1(+/R203W) organoids have been associated with several neurological diseases, and many are classified as NDD-causative and ASD-risk genes. Our results highlight that proteomic analyses not only enhance our understanding of general NDD mechanisms by complementing transcriptomic studies, but could also uncover additional targets, and therefore facilitate therapy development.

neuroscience↗

bioRxiv2024

MALT1 protease inhibition restrains glioblastoma progression by reversing tumor-associated macrophage-dependent immunosuppression

MALT1 protease is an intracellular signaling molecule that promotes tumor progression via cancer cell-intrinsic and cancer cell-extrinsic mechanisms. MALT1 has been mostly studied in lymphocytes, and little is known about its role in tumor-associated macrophages. Here, we show that MALT1 plays a key role in glioblastoma (GBM)-associated macrophages. Mechanistically, GBM tumor cells induce a MALT1-NF-{kappa}B signaling axis within macrophages, leading to macrophage migration and polarization toward an immunosuppressive phenotype. Inactivation of MALT1 protease promotes transcriptional reprogramming that reduces migration and restores a macrophage "M1-like" phenotype. Preclinical in vivo analysis shows that MALT1 inhibitor treatment results in increased immuno-reactivity of GBM-associated macrophages and reduced GBM tumor growth. Further, the addition of MALT1 inhibitor to temozolomide reduces immunosuppression in the tumor microenvironment, which may enhance the efficacy of this standard-of-care chemotherapeutic. Together, our findings suggest that MALT1 protease inhibition represents a promising macrophage-targeted immunotherapeutic strategy for the treatment of GBM. Graphical abstract. O_FIG O_LINKSMALLFIG WIDTH=196 HEIGHT=200 SRC="FIGDIR/small/614808v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@18c969eorg.highwire.dtl.DTLVardef@f48f0dorg.highwire.dtl.DTLVardef@1dbbbb1org.highwire.dtl.DTLVardef@ff8237_HPS_FORMAT_FIGEXP M_FIG The effects of tumor cell-induced CARD9-BCL10-MALT1 (CBM) activation (left) and MALT1 protease inhibition (right) on GBM associated macrophages in the tumor microenvironment. Cartoon of cellular components of a GBM tumor with an immunosuppressive TME characterized by "M2-like macrophages" (left) and conversion to a more immune-reactive tumor microenvironment characterized by "M1-like macrophages and increased effector T-cells (right) as a result of MALT1 protease inhibition. C_FIG

cancer biology↗

bioRxiv2023

Evaluating and Improving Health Equity and Fairness of Polygenic Scores

Polygenic scores (PGS) are quantitative metrics for predicting phenotypic values, such as human height or disease status. Some PGS methods require only summary statistics of a relevant genome-wide association study (GWAS) for their score. One such method is Lassosum, which inherits the model selection advantages of Lasso to select a meaningful subset of the GWAS single nucleotide polymorphisms as predictors from their association statistics. However, even efficient scores like Lassosum, when derived from European-based GWAS, are poor predictors of phenotype for subjects of non-European ancestry; that is, they have limited portability to other ancestries. To increase the portability of Lassosum, when GWAS information and estimates of linkage disequilibrium are available for both ancestries, we propose Joint-Lassosum. In the simulation settings we explore, Joint-Lassosum provides more accurate PGS compared with other methods, especially when measured in terms of fairness. Like all PGS methods, Joint-Lassosum requires selection of predictors, which are determined by data-driven tuning parameters. We describe a new approach to selecting tuning parameters and note its relevance for model selection for any PGS. We also draw connections to the literature on algorithmic fairness and discuss how Joint-Lassosum can help mitigate fairness-related harms that might result from the use of PGS scores in clinical settings. While no PGS method is likely to be universally portable, due to the diversity of human populations and unequal information content of GWAS for different ancestries, Joint-Lassosum is an effective approach for enhancing portability and reducing predictive bias.

genetics↗

bioRxiv2020

Transcriptome alterations are enriched for synapse-associated genes in the striatum of subjects with obsessive-compulsive disorder

BackgroundObsessive compulsive disorder (OCD) is a chronic and severe psychiatric disorder for which effective treatment options are limited. Structural and functional neuroimaging studies have consistently implicated the orbitofrontal cortex (OFC) and striatum in the pathophysiology of the disorder. Recent genetic evidence points to involvement of components of the excitatory synapse in the etiology of OCD. However, the transcriptional alterations that could link genetic risk to known structural and functional abnormalities remain mostly unknown. MethodsTo assess potential transcriptional changes in the OFC and two striatal regions (caudate nucleus and nucleus accumbens) of OCD subjects relative to unaffected comparison subjects, we sequenced messenger RNA transcripts from these brain regions. ResultsIn a joint analysis of all three regions, 904 transcripts were differentially expressed between 7 OCD versus 8 unaffected comparison subjects. Region-specific analyses highlight a smaller number of differences, which concentrate in caudate and nucleus accumbens. Pathway analyses of the 904 differentially expressed transcripts showed enrichment for genes involved in synaptic signaling, with these synapse-associated genes displaying lower expression in OCD subjects relative to unaffected comparison subjects. Finally, we estimate that cell type fractions of medium spiny neurons are lower whereas vascular cells and astrocyte fractions are higher in tissue of OCD subjects. ConclusionsTogether, these data provide the first unbiased examination of differentially expressed transcripts in both OFC and striatum of OCD subjects. These transcripts encode synaptic proteins more often than expected by chance, and thus implicate the synapse as a vulnerable molecular compartment for OCD.

neuroscience↗

bioRxiv2019

Whole-genome and RNA sequencing reveal variation and transcriptomic coordination in the developing human prefrontal cortex

Variation in gene expression underlies neurotypical development, while genomic variants contribute to neuropsychiatric disorders. BrainVar is a unique resource of paired whole-genome sequencing and bulk-tissue RNA-sequencing from the human dorsolateral prefrontal cortex of 176 neurotypical individuals across prenatal and postnatal development, providing the opportunity to assay genomic and transcriptomic variation in tandem. Leveraging this resource, we identified rare premature stop codons with commensurate reduced and allele-specific expression of corresponding genes, and common variants that alter gene expression (expression quantitative trait loci, eQTLs). Categorizing eQTLs by prenatal and postnatal effect, genes affected by temporally-specific eQTLs, compared to constitutive eQTLs, are enriched for haploinsufficiency, protein-protein interactions, and neuropsychiatric disorder risk loci. Expression levels of over 12,000 genes rise or fall in a concerted late-fetal transition, with the transitional genes enriched for cell type specific genes and neuropsychiatric disorder loci, underscoring the importance of cataloguing developmental trajectories in understanding cortical physiology and pathology.\n\nHighlightsO_LIWhole-genome and RNA-sequencing across human prefrontal cortex development in BrainVar\nC_LIO_LIGene-specific developmental trajectories characterize the late-fetal transition\nC_LIO_LIIdentification of constitutive, prenatal-specific, postnatal-specific, and rare eQTLs\nC_LIO_LIIntegrated analysis reveals genetic and developmental influences on CNS traits and disorders\nC_LI

neuroscience↗

bioRxiv2018

Novel genes for autism implicate both excitatory and inhibitory cell lineages in risk

We present the largest exome sequencing study to date focused on rare variation in autism spectrum disorder (ASD) (n=35,584). Integrating de novo and case-control variation with an enhanced Bayesian framework incorporating evolutionary constraint against mutation, we implicate 99 genes in ASD risk at a false discovery rate (FDR) [≤] 0.1. Of these 99 risk genes, 46 show higher frequencies of disruptive de novo variants in individuals ascertained for severe neurodevelopmental delay, while 50 show higher frequencies in individuals ascertained for ASD, and comparing ASD cases with disruptive mutations in the two groups shows differences in phenotypic presentation. Expressed early in brain development, most of the risk genes have roles in neuronal communication or regulation of gene expression, and 12 fall within recurrent copy number variant loci. In human cortex single-cell gene expression data, expression of the 99 risk genes is also enriched in both excitatory and inhibitory neuronal lineages, implying that disruption of these genes alters the development of both neuron types. Together, these insights broaden our understanding of the neurobiology of ASD.

genetics↗

bioRxiv2017

Common risk variants identified in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 ASD cases and 27,969 controls that identifies five genome-wide significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), seven additional loci shared with other traits are identified at equally strict significance levels. Dissecting the polygenic architecture we find both quantitative and qualitative polygenic heterogeneity across ASD subtypes, in contrast to what is typically seen in other complex disorders. These results highlight biological insights, particularly relating to neuronal function and corticogenesis and establish that GWAS performed at scale will be much more productive in the near term in ASD, just as it has been in a broad range of important psychiatric and diverse medical phenotypes.

genetics↗

bioRxiv2017

Limited contribution of rare, noncoding variation to autism spectrum disorder from sequencing of 2,076 genomes in quartet families

Genomic studies to date in autism spectrum disorder (ASD) have largely focused on newly arising mutations that disrupt protein coding sequence and strongly influence risk. We evaluate the contribution of noncoding regulatory variation across the size and frequency spectrum through whole genome sequencing of 519 ASD cases, their unaffected sibling controls, and parents. Cases carry a small excess of de novo (1.02-fold) noncoding variants, which is not significant after correcting for paternal age. Assessing 51,801 regulatory classes, no category is significantly associated with ASD after correction for multiple testing. The strongest signals are observed in coding regions, including structural variation not detected by previous technologies and missense variation. While rare noncoding variation likely contributes to risk in neurodevelopmental disorders, no category of variation has impact equivalent to loss-of-function mutations. Average effect sizes are likely to be smaller than that for coding variation, requiring substantially larger samples to quantify this risk.

genomics↗