Biology subjects

Kellis, M.

Publications and source records attributed to Kellis, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

PRISM: ancestry-aware integration of tissue-specific genomic annotations enhances the transferability of polygenic scores

The limited transferability of polygenic scores (PGS) across populations constrains their clinical utility and risks exacerbating health disparities, given challenges in multi-ancestry training, fine-mapping, and variant prioritization using genomic annotations, particularly when biologically relevant reference resources are sparse or unavailable for the target population. Here, we introduce PRISM, a transfer learning approach that jointly addresses these challenges to enhance PGS transferability. Applying PRISM to 7352 fine-mapped variants, 414 ENCODE annotations, and 406,659 individuals from the UK Biobank, we demonstrate that ancestry-aware integration of tissue-specific annotations yields the largest gains in predictive performance for African ancestry, with an average improvement of 13.10% (p=1.6x10-5) over annotation-agnostic multi-ancestry PGS. Notably, the best-performing model uses 102-fold fewer annotations than non-specific models, with contributions from broad categories of annotations. Overall, PRISM complements ongoing data diversification efforts by providing an immediately applicable strategy based on the integration of biologically aligned, best-available resources to address genomic health equity.

genetics↗

bioRxiv2025

CONCERT predicts niche-aware perturbation responses in spatial transcriptomics

Spatial perturbation transcriptomics measures how genetic or chemical edits alter gene expression while preserving tissue context. Perturbation outcomes depend on a cells intrinsic state and also on how effects propagate across cellular microenvironments. We present CONCERT, a niche-aware generative model that embeds perturbation context and learns spatial kernels with a Gaussian process variational autoencoder to predict perturbation effects across tissue. We formalize three tasks: patch, border, and niche, predicting responses in nearby unperturbed regions, at tissue interfaces, and as a function of surrounding microenvironments. We evaluate CONCERT on Perturb-map lung datasets. CONCERT outperforms state-of-the-art models (dissociated counterfactuals, spatialized perturbation models, and kNN), reducing E-distance by up to 33.77% (patch), 26.05% (border), and 33.74% (niche) versus the next best, with mean absolute error down by up to 23.28% and Pearson correlation up by up to 9.10%. Two case studies go beyond benchmarking. In dextran sodium sulfate-induced colitis, CONCERT reconstructs spatial gene expression at unmeasured time points, produces longitudinal comparisons across unpaired mice, resolves intermouse heterogeneity, and recovers consistent temporal declines of inflammation-associated genes across regions. In ischemic stroke, CONCERT predicts responses under variable lesion sizes and in a 3D formulation across brain sections, capturing lesion-core and peri-lesion patterns. CONCERT performs niche-aware counterfactual prediction, reconstructs missing spatial data, and models perturbation responses across tissues.

bioinformatics↗

bioRxiv2025

A chromatin fiber model explains cell-free DNA fragmentation signatures of active regulatory elements

Circulating cell-free DNA (cfDNA) assays are being widely adopted in oncology and maternal-fetal medicine. Patterns of cfDNA fragmentation can provide useful information about gene regulation and expression in human disease from a blood draw. Here, we demonstrate that enhancer RNA expression - a marker of enhancer activity - can be inferred from local patterns of cfDNA fragmentation. We define a transcriptional activation score (TAS) that predicts expression of enhancers and genes based on cfDNA fragment sizes and positions near transcriptional start sites (TSSs). The TAS identifies activity of cancer-associated enhancers in patients with cancer, distinguishes clinically relevant cancer subtypes, and identifies activation of enhancers associated with treatment resistance and therapy response. We propose a simple model to account for our findings based on chromatin fiber structure and the depletion of H1 histone proteins near active TSSs. Our model provides a unified framework that reconciles seemingly conflicting observations from prior fragmentomics studies. Broadly, this work enables blood-based assessments of gene regulation in cancer and non-oncologic diseases to inform pathobiology, diagnosis, and treatment selection.

genomics↗

bioRxiv2025

Intraspecific sequence variation and complete genomes refine the identification of rapidly evolved regions in humans

Summary Humans exhibit significant phenotypic differences from other great apes, yet pinpointing the underlying genetic changes has been limited by incomplete reference genomes and a reliance on single assemblies to represent a species. We aligned 20 telomere-to-telomere (T2T) assemblies spanning great ape divergence and variation to define 1,596 Consensus HAQERs (consensus human ancestor quickly evolved regions), regions that diverged rapidly between the human-chimpanzee ancestor and an ancestral node of modern humans. Unlike prior HAQER sets, Consensus HAQERs incorporate population variation, reducing the likelihood of intraspecies variation appearing as interspecies divergence. Consensus HAQERs exhibit signatures of elevated mutation rates, ancient positive selection, bivalent regulatory function, are enriched in disease-linked loci, and often emerged in previously inaccessible repetitive DNA. Through multiplex, single-cell enhancer assays, we identify HAQERs as active enhancers in the developing brain and cardiomyocytes, highlighting their potential contributions to human-specific gene regulation across multiple tissues. Highlights[bullet] Telomere-to-telomere alignments of diverse human and great ape genomes identify 1,596 Consensus HAQERs, regions of rapid sequence divergence separating human ancestors from other great apes. [bullet]Consensus HAQERs exhibit signatures of both elevated mutation rates and ancient positive selection. [bullet]HAQERs are enriched in bivalent regulatory elements and disease-linked loci. [bullet]Multiplex, single-cell gene regulatory assays identify HAQERs as enhancers in the developing heart and brain.

genomics↗

bioRxiv2025

Type 2 Diabetes and Obesity Alter Exercise Training-Induced Transcriptional Adaptations to Subcutaneous White Adipose Tissue

White adipose tissue (WAT) dysfunction contributes to obesity-associated metabolic disease and type 2 diabetes (T2D). Rodent studies have demonstrated that exercise training improves WAT function, but molecular studies investigating exercise training effects on WAT in humans have been limited, particularly in the context of metabolic disease. Here, we defined the subcutaneous WAT (scWAT) transcriptome in middle-aged adults (10 male, 19 female) that were classified by lower BMI (<27 kg/m2), higher BMI ([≥]27 kg/m2), and T2D status before and after a 10-week endurance exercise regimen. At baseline, 624 genes were significantly upregulated and 112 genes downregulated in the scWAT from higher BMI participants compared to lower BMI. There was a spectrum of pathway dysregulation in scWAT in higher BMI individuals, ranging from increased markers of extracellular matrix (ECM) deposition and inflammation to decreased circadian rhythm gene expression. In people with T2D, there were additional transcriptomic differences such as translation-related pathways, selenoamino acid metabolism, and proteoglycans. Exercise training had robust effects on the transcriptome regardless of metabolic status, and notably, for the high BMI and T2D groups, training reversed several of the detrimental gene expression patterns in a cell-type-specific manner. These beneficial exercise-induced transcriptomic adaptations significantly correlated with lower levels of free fatty acids and blood pressure, particularly in participants with higher BMI and T2D. By integrating our exercise training-modulated genes with GWAS meta-analysis of physical activity, genes influenced by exercise training in the higher BMI group showed a significant enrichment in genetic associations of exercise traits in the population. A circadian rhythm-related transcription factor NR1D1 was enriched in enhancers linked with both the exercise differentially expressed genes (DEGs) and GWAS signals, suggesting a link between the circadian rhythm and training-induced adaptations. These findings demonstrate that obesity and T2D result in marked, progressive alterations in cell-type specific gene transcription in scWAT, while endurance exercise training reverses many of the metabolic disease-associated adaptations. Identification of novel molecular pathways regulated by exercise training can lead to therapeutic targets for obesity and metabolic disease.

molecular biology↗

bioRxiv2025

Interpretable deep generative ensemble learning for single-cell omics with Hydra

Single-cell omics enable the dissection of cellular heterogeneity, yet the high dimensionality, inherent noise, and sparsity present significant challenges. These challenges are amplified for rare cell populations, which are often difficult to annotate reliably but can be central to development and disease. As single-cell assays increasingly capture multiple molecular layers, the integrative analysis of such multimodal data further increases complexity. Here, we propose Hydra, a deep generative framework based on an ensemble of variational autoencoders for effective learning of unimodal and multimodal single-cell omics data. Hydra implements interpretable modules for capturing cell type-specific molecular signatures. The ensemble of such interpretable modules enables reproducible feature selection and robust cell type annotation, with particular effectiveness for rare populations. We benchmarked Hydra on a repertoire of 21 datasets, including unimodal and multimodal single-cell omics data. Our results demonstrate that Hydra offers comparable to superior performance to several state-of-the-art methods. Finally, we highlight the utility of Hydra in robustly annotating brain cellular subtypes and preserving disease-relevant signatures using our previously published dataset that profiles Alzheimers disease.

bioinformatics↗

bioRxiv2025

Context-dependent regulatory variants in Alzheimer's disease

Noncoding genetic variants underlie many complex diseases, yet identifying and interpreting their functional impacts remains challenging. Late-onset Alzheimers disease (LOAD), a polygenic neurodegenerative disorder, exemplifies this challenge. The disease is strongly associated with noncoding variation, including common variants enriched in microglial enhancers and rare variants nominated at loci implicated in neurodevelopment and synaptic function. These variants may perturb regulatory sequences by disrupting transcription factor (TF) motifs or altering local regulatory sequence context, with potential consequences for gene expression and chromatin accessibility. However, assessing their impact is complicated by the context-dependent functions of regulatory sequences, underscoring the need to systematically examine variant effects across diverse tissues, cell types, and cellular states. Here, we combined in vitro and in vivo massively parallel reporter assays (MPRAs) with interpretable machine-learning models to systematically characterize common and rare variants across myeloid and neuron-enriched neural contexts. Parallel profiling of variants in four immune states in vitro and three mouse brain regions in vivo revealed that individual variants can differentially and even oppositely modulate reporter activity across cellular contexts, while a subset showed immune-state-dependent effects. Within the assayed candidate set, the relative effect sizes of common and rare variants reversed between contexts, with common variants showing larger effects in THP-1 macrophages and rare variants in brain tissue. Interpretable sequence-to-function models prioritized context-biased variants and generated motif-level hypotheses, including predicted transcription-factor motif disruption and subtler changes in local motif context. To probe endogenous consequences at a prioritized locus, we used CRISPR interference to perturb a rare-variant-containing enhancer at the SEC63-OSTM1 locus, revealing metabolic and biosynthetic transcriptional programs resembling those induced by SEC63 promoter perturbation, together with a stimulation-specific interferon response. These findings show that LOAD-associated noncoding variants exhibit context-dependent effects on reporter activity and predicted chromatin accessibility, and provide a framework for linking genetic association to regulatory activity, sequence grammar and endogenous transcriptional state.

genomics↗

bioRxiv2025

An expanded reference catalog of translated open reading frames for biomedical research

Non-canonical (i.e., unannotated) open reading frames (ncORFs) have until recently been omitted from reference genome annotations, despite evidence of their translation, limiting their incorporation into biomedical research. To address this, in 2022, we initiated the TransCODE consortium and built the first community-driven consensus catalog of human ncORFs, which was openly distributed to the research community via Ensembl-GENCODE. While this catalog represented a starting point for reference ncORF annotation, major technical and scientific issues remained. In particular, this initial catalogue had no standardized framework to judge the evidence of translation for individual ncORFs. Here, we present an expanded and refined catalog of the human reference annotation of ncORFs. By incorporating more datasets and by lifting constraints on ORF length and start-codon, we define a comprehensive set of 28,359 ncORFs that is nearly four times the size of the previous catalog. Furthermore, to aid users who wish to work with ncORFs with the strongest and most reproducible signals of translation, we utilized a data-driven framework (i.e. translation signature scores) to assess the accumulated evidence for any individual ncORF. Using this approach, we derive a subset of 7,888 ncORFs with translation evidence on par with canonical protein-coding genes, which we refer to as the Primary set. This set can serve as a reliable reference for downstream analyses and validation, with a particular emphasis on high quality. Overall, this update reflects continual community-driven efforts to make ncORFs accessible and actionable to the broader research public and further iterations of the catalog will continue to expand and refine this resource.

genomics↗

bioRxiv2025

Epilogos: information-theoretic navigation of multi-tissue functional genomic annotations

Functional genomics data, such as chromatin state maps, provide critical insights into biological processes, but are hard to navigate and interpret. We present Epilogos to address this challenge by offering a simple information-theoretic framework for large-scale visualization, navigation and interpretation of functional genomics annotations, and apply it to over 2,000 genome-wide chromatin state maps in human and mouse. We construct intuitive visualizations of multi-tissue chromatin state maps, prioritize salient genomic regions, identify group-wise differential regions, and enable rapid similarity search given a region of interest. To facilitate usability, we provide a purpose-built web-based browser interface (http://epilogos.net) alongside open-source software for community access and adoption.

genomics↗

bioRxiv2025

Cellular and Regional Vulnerability Shapes the Molecular Landscape of Psychosis in Alzheimers Disease

Approximately 40 percent of Alzheimers disease patients develop psychosis (AD+P), yet the molecular and cellular basis of these symptoms remains poorly understood. Here we profiled single-nucleus transcriptomes and epigenomes from 48 postmortem Alzheimers brains stratified by psychiatric diagnosis. Across cell types, AD+P was distinguished by transcriptional programs in upper-layer cortical pyramidal neurons consistent with re-engagement of developmental and structural plasticity pathways. These neurons exhibited greater loss in AD+P cortex, indicating that such programs emerge in a context of heightened vulnerability. Integrating these findings with functional perturbation screens in stem-cell-derived brain organoids, we found that activation of these programs alters cortico-cortical network connectivity and can exacerbate network dysfunction. Our data suggest that compensatory neuronal plasticity, shaped by glial inflammatory responses, may paradoxically contribute to circuit instability and selective vulnerability underlying neuropsychiatric symptoms in dementia. HighlightsO_LICell-type- and brain-region-specific transcriptional changes in AD with psychosis (AD+P) C_LIO_LIUpper-layer pyramidal dysfunction and metabolic vulnerability marks the pathophysiology of AD+P C_LIO_LICircuit wiring programs are evoked in AD+P as maladaptive compensatory responses C_LIO_LIAD+P-associated IL-6 signaling impairs neuronal network function in brain organoids C_LI

neuroscience↗

bioRxiv2025

Cell type-specific contributions to impaired blood-brain barrier and cerebral metabolism in presymptomatic 5XFAD mice

Altered cerebral metabolism and blood-brain barrier (BBB) dysfunction are emerging as critical contributors to the preclinical phase of Alzheimers disease (AD), underscoring their role in early pathogenesis. To identify sensitive biomarkers before irreversible neuronal loss and cognitive decline, we examined 5XFAD mice at 3 months of age by applying multiple advanced MRI techniques. Arterial spin tagging based MRI revealed increased BBB permeability and water extraction fraction, indicating compromised BBB integrity at the early stage of pathogenesis in 5xFAD mice. Despite preserved cerebral blood flow, a decreased unit mass cerebral metabolic rate of oxygen (CMRO2) was evident in the same cohorts of 5XFAD mice. Interestingly, a region-specific decrease of tissue pH values was detected in the hippocampus of these 5XFAD mice by creatine chemical exchange saturation transfer MRI. Elevated neuronal H4K12 lactylation in the hippocampus supports the reduced pH values. To further dissect the cellular and molecular mechanisms underlying these MRI-detectable changes in 5XFAD mice, we conducted single-nucleus RNA sequencing (snRNA-Seq) with optimized blood vessel enrichment protocols. Our results revealed cell type-specific transcriptomic changes in the hippocampus of 3-month-old 5XFAD mice, including downregulation of synaptogenesis and synaptic transmission genes in the CA1 and dentate gyrus excitatory neurons, impaired endothelial gene expression linked to brain barrier function and angiogenesis, altered innate immune response genes in astrocytes, as well as upregulation of cholesterol biosynthesis and metabolism genes in the CA1 excitatory neurons. These findings underlie the intricate interplay between BBB disruption and metabolic dysregulation before the onset of cognitive decline in AD. Our study demonstrates that BBB dysfunction and cerebral metabolic alterations preceded brain hypoperfusion and cognitive decline, emphasizing potential molecular pathways for early intervention. These findings, once validated in human studies, could significantly enhance early diagnosis and inform novel therapeutic strategies targeting early AD pathogenesis.

neuroscience↗

bioRxiv2025

Combined CSF1R Inhibition and Sensory Gamma Stimulation Provide Protective Effects in a Mouse Model of Alzheimers Disease

The CSF1R inhibitor PLX3397, an FDA-approved treatment for a rare cancer, has been shown to reduce microglia count, lower inflammation, and increase synaptic markers in mouse models of Alzheimers disease (AD). However, the effects of PLX3397 on neural function in AD remain largely unknown. Here, we characterized the effects of PLX3397 treatment in 5xFAD mice. While PLX3397 increased synaptic density, it reduced the percentage of neurons phase-locked to gamma oscillations. This neural decoupling was closely associated with gene expression changes related to synapse organization. We investigated whether Gamma ENtrainment Using Sensory (GENUS) stimulation could counterbalance the neural circuit alterations induced by PLX3397. GENUS + PLX3397 restored gamma phase-locking, reshaped gene expression signatures, and improved learning and memory better than either treatment alone in 5xFAD mice. These findings suggest that CSF1R inhibitors like PLX3397 may benefit from a multimodal approach combining microglial targeting with non-invasive sensory stimulation to support neural physiology and improve cognitive function in AD.

neuroscience↗

bioRxiv2025

Molecular hallmarks of excitatory and inhibitory neuronal resilience and resistance to Alzheimer's disease

BackgroundA significant proportion of individuals maintain healthy cognitive function despite having extensive Alzheimers disease (AD) pathology, known as cognitive resilience. Understanding the molecular mechanisms that protect these individuals can identify therapeutic targets for AD dementia. This study aims to define molecular and cellular signatures of cognitive resilience, protection and resistance, by integrating genetics, bulk RNA, and single-nucleus RNA sequencing data across multiple brain regions from AD, resilient, and control individuals. MethodsWe analyzed data from the Religious Order Study and the Rush Memory and Aging Project (ROSMAP), including bulk (n=631) and multi-regional single nucleus (n=48) RNA sequencing. Subjects were categorized into AD, resilient, and control based on {beta}-amyloid and tau pathology, and cognitive status. We identified and prioritized protected cell populations using whole genome sequencing-derived genetic variants, transcriptomic profiling, and cellular composition distribution. ResultsTranscriptomic results, supported by GWAS-derived polygenic risk scores, place cognitive resilience as an intermediate state in the AD continuum. Tissue-level analysis revealed 43 genes enriched in nucleic acid metabolism and signaling that were differentially expressed between AD and resilience. Only GFAP (upregulated) and KLF4 (downregulated) showed differential expression in resilience compared to controls. Cellular resilience involved reorganization of protein folding and degradation pathways, with downregulation of Hsp90 and selective upregulation of Hsp40, Hsp70, and Hsp110 families in excitatory neurons. Excitatory neuronal subpopulations in the entorhinal cortex (ATP8B1+ and MEF2Chigh) exhibited unique resilience signaling through neurotrophin (modulated by LINGO1) and angiopoietin (ANGPT2/TEK) pathways. We identified MEF2C, ATP8B1, and RELN as key markers of resilient excitatory neuronal populations, characterized by selective vulnerability in AD. Protective rare variant enrichment highlighted vulnerable populations, including somatostatin (SST) inhibitory interneurons, validated through immunofluorescence showing co-expression of rare variant associated RBFOX1 and KIF26B in SST+ neurons in the dorsolateral prefrontal cortex. The maintenance of excitatory-inhibitory balance emerges as a key characteristic of resilience. ConclusionsWe identified molecular and cellular hallmarks of cognitive resilience, an intermediate state in the AD continuum. Resilience mechanisms include preservation of neuronal function, maintenance of excitatory/inhibitory balance, and activation of protective signaling pathways. Specific excitatory neuronal populations appear to play a central role in mediating cognitive resilience, while a subset of vulnerable SST interneurons likely provide compensation against AD-associated dysregulation. This study offers a framework to leverage natural protective mechanisms to mitigate neurodegeneration and preserve cognition in AD.

neuroscience↗

bioRxiv2024

CellMemory: Hierarchical Interpretation of Out-of-Distribution Cells Using Bottlenecked Transformer

Identifying the genetic and molecular drivers of phenotypic heterogeneity among individuals is vital for understanding human health and for diagnosing, monitoring, and treating diseases. To this end, international consortia such as the Human Cell Atlas and the Tabula Sapiens are creating comprehensive cellular references. Due to the massive volume of data generated, machine learning methods, especially transformer architectures, have been widely employed in related studies. However, applying machine learning to cellular data presents several challenges. One such challenge is making the methods interpretable with respect to both the input cellular information and its context. Another less explored challenge is the accurate representation of cells outside existing references, referred to as out-of-distribution (OOD) cells. The out-of-distribution could be attributed to various physiological conditions, such as comparing diseased cells, particularly tumor cells, with healthy reference data, or significant technical variations, such as using transfer learning from single-cell reference to spatial query data. Inspired by the global workspace theory in cognitive neuroscience, we introduce CellMemory, a bottlenecked Transformer with improved generalization capabilities designed for the hierarchical interpretation of OOD cells unseen during reference building. Even without pre-training, it exceeds the performance of large language models pre-trained with tens of millions of cells. In particular, when deciphering spatially resolved single-cell transcriptomics data, CellMemory demonstrates the ability to interpret data at the granule level accurately. Finally, we harness CellMemorys robust representational capabilities to elucidate malignant cells and their founder cells in different patients, providing reliable characterizations of the cellular changes caused by the disease.

bioinformatics↗

bioRxiv2024

ProCyon: A multimodal foundation model for protein phenotypes

Characterizing human proteins remains a major challenge: approximately 29% of human proteins lack experimentally validated functions and even well-annotated proteins often lack context-specific phenotypic insights. To enable universal modeling of protein phenotypes, we present PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW, a multimodal foundation model that utilizes protein sequence, structure, and natural language for generating and predicting protein phenotypes across diverse knowledge domains. PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW is trained on our novel dataset, PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW-IO_SCPLOWNSTRUCTC_SCPLOW, with 33 million protein phenotype instructions. On dozens of benchmarking tasks, PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW performs competitively against single-modal and multimodal models. Further, PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW conditionally retrieves proteins via mechanisms of action of small molecule drugs and disease contexts, and it generates candidate phenotypic descriptions for poorly characterized proteins, including those implicated in Parkinsons disease that were identified after PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOWs knowledge cutoff date. We experimentally confirm PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOWs predictions in multiple sclerosis using post-mortem brain RNA-seq, identifying novel MS genes and elucidating associated pathway mechanisms consistent with cortical pathology. PO_SCPLOWROC_SCPLOWCO_SCPLOWYONC_SCPLOW paves the way toward a general approach to generate functional insights into the human proteome.

bioinformatics↗

bioRxiv2024

GENCODE: massively expanding the lncRNA catalog through capture long-read RNA sequencing

Accurate and complete gene annotations are indispensable for understanding how genome sequences encode biological functions. For more than twenty years, the GENCODE consortium has developed reference annotations for the human and mouse genomes, becoming a foundation for biomedical and genomics communities worldwide. Nevertheless, collections of important yet poorly-understood gene classes like long non-coding RNAs (lncRNAs) remain incomplete and scattered across multiple, uncoordinated catalogs. To address this, GENCODE has undertaken the most comprehensive lncRNA annotation effort to date. This is founded on the manually supervised computational annotation of full-length targeted long-read sequencing, on matched embryonic and adult tissues, of orthologous regions in human and mouse. Altogether 17,931 human genes (140,268 transcripts) and 22,784 mouse genes (136,169 transcripts) have been added to the GENCODE catalog representing a 2-fold and 6-fold growth in transcripts, respectively - the greatest increase in the number of annotated human genes since the sequencing of the human genome. Our targeted design assigned human-mouse orthologs at a rate beyond previous studies, tripling the number of human disease-associated lncRNAs that have mouse orthologs. Novel lncRNA genes consistently exhibit biological signals of functionality, and they greatly enhance the functional interpretability of the human genome. While poorly expressed in bulk RNA-Seq samples, many of them are highly expressed in specific cell populations, maybe even contributing to cell-type determination. The expanded GENCODE lncRNA annotations mark a critical step toward deciphering the human and mouse genomes.

genomics↗

bioRxiv2024

Stratified analysis identifies HIF-2α as a therapeutic target for highly immune-infiltrated melanomas

While immune-checkpoint blockade (ICB) has revolutionized treatment of metastatic melanoma over the last decade, the identification of broadly applicable robust biomarkers has been challenging, driven in large part by the heterogeneity of ICB regimens and patient and tumor characteristics. To disentangle these features, we performed a standardized meta-analysis of eight cohorts of patients treated with anti-PD-1 (n=290), anti-CTLA-4 (n=175), and combination anti-PD-1/anti-CTLA-4 (n=51) with RNA sequencing of pre-treatment tumor and clinical annotations. Stratifying by immune-high vs -low tumors, we found that surprisingly, high immune infiltrate was a biomarker for response to combination ICB, but not anti-PD-1 alone. Additionally, hypoxia-related signatures were associated with non-response to anti-PD-1, but only amongst immune infiltrate-high melanomas. In a cohort of scRNA-seq of patients with metastatic melanoma, hypoxia also correlated with immunosuppression and changes in tumor-stromal communication in the tumor microenvironment (TME). Clinically actionable targets of hypoxia signaling were also uniquely expressed across different cell types. We focused on one such target, HIF-2, which was specifically upregulated in endothelial cells and fibroblasts but not in immune cells or tumor cells. HIF-2 inhibition, in combination with anti-PD-1, enhanced tumor growth control in pre-clinical models, but only in a more immune-infiltrated melanoma model. Our work demonstrates how careful stratification by clinical and molecular characteristics can be leveraged to derive meaningful biological insights and lead to the rational discovery of novel clinical targets for combination therapy.

cancer biology↗

bioRxiv2024

Multisensory gamma stimulation enhances adult neurogenesis and improves cognitive function in a mouse model of Down syndrome

Down syndrome (DS) has been linked with deficits in hippocampal dependent cognitive tasks and adult neurogenesis, yet treatment options are still very limited. We and others previously showed that a non-invasive multisensory gamma stimulation using light and sound at 40 Hz ameliorated Alzheimers disease pathology and symptoms in mouse models. In this study, we tested the effects of 40 Hz multisensory stimulation in the Ts65Dn mice, a mouse model of DS. For three weeks, mice were exposed daily to one hour of stimulation or one hour of ambient light and sound. Mice receiving the stimulation showed improved object recognition and spatial working memory. Using single nuclei RNA-seq and experimental validations in mouse hippocampal samples, we identified underlying expression changes in gene regulatory networks and demonstrated increased adult neurogenesis and reorganization of synapses as potential mechanisms for these improved cognitive phenotypes. Together, our data reveal a novel effect of multisensory gamma stimulation on adult neurogenesis and beneficial effects of 40 Hz treatment on cognitive function in DS model mice. Significance StatementWe present strong evidence, using a well-characterized mouse model, that the cognitive and neurogenesis deficits in Down syndrome can be improved through non-invasive multi-sensory gamma stimulation. Employing a systems biology approach, we provide extensive hippocampal single-cell resolution gene expression signatures and changes in gene regulatory networks in response to sensory gamma stimulation.

neuroscience↗