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Proneural transcription factors establish molecular cascades to orchestrate neuronal diversity. One such transcription factor, Atonal homolog 1 (Atoh1), gives rise to cerebellar excitatory neurons and over 30 distinct nuclei in the brainstem critical for hearing, breathing, and balance. Although Atoh1 lineage neurons have been qualitatively described, the transcriptional programs that drive their fate decisions and the full extent of their diversity remain unknown. Here, we analyzed single-cell RNA sequencing and ATOH1 DNA binding in Atoh1 lineage neurons of the developing mouse hindbrain. This high-resolution dataset identified markers for specific brainstem nuclei and demonstrated that transcriptionally heterogeneous progenitors require ATOH1 for proper migration. Moreover, we identified a sizable population of proliferating unipolar brush cell progenitors in the mouse Atoh1 lineage, previously described in humans as the origin of one medulloblastoma subtype. Collectively, our data provide insights into the developing mouse hindbrain and markers for functional assessment of understudied neuronal populations.
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Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico , Linaje de la Célula , Neuronas , Rombencéfalo , Análisis de la Célula Individual , Transcriptoma , Animales , Rombencéfalo/metabolismo , Rombencéfalo/citología , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/metabolismo , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genética , Ratones , Neuronas/metabolismo , Neuronas/citología , Linaje de la Célula/genética , Análisis de la Célula Individual/métodos , Transcriptoma/genética , Diferenciación Celular , Regulación del Desarrollo de la Expresión Génica , Neurogénesis/genética , Movimiento CelularRESUMEN
Telomeres protect chromosome ends from damage and their length is linked with human disease and aging. We developed a joint telomere length metric, combining quantitative PCR and whole-genome sequencing measurements from 462,666 UK Biobank participants. This metric increased SNP heritability, suggesting that it better captures genetic regulation of telomere length. Exome-wide rare-variant and gene-level collapsing association studies identified 64 variants and 30 genes significantly associated with telomere length, including allelic series in ACD and RTEL1. Notably, 16% of these genes are known drivers of clonal hematopoiesis-an age-related somatic mosaicism associated with myeloid cancers and several nonmalignant diseases. Somatic variant analyses revealed gene-specific associations with telomere length, including lengthened telomeres in individuals with large SRSF2-mutant clones, compared with shortened telomeres in individuals with clonal expansions driven by other genes. Collectively, our findings demonstrate the impact of rare variants on telomere length, with larger effects observed among genes also associated with clonal hematopoiesis.
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The etiology of prostate cancer, the second most common cancer in men globally, has a strong heritable component. While rare coding germline variants in several genes have been identified as risk factors from candidate gene and linkage studies, the exome-wide spectrum of causal rare variants remains to be fully explored. To more comprehensively address their contribution, we analysed data from 37,184 prostate cancer cases and 331,329 male controls from five cohorts with germline exome/genome sequencing and one cohort with imputed array data from a population enriched in low-frequency deleterious variants. Our gene-level collapsing analysis revealed that rare damaging variants in SAMHD1 as well as genes in the DNA damage response pathway (BRCA2, ATM and CHEK2) are associated with the risk of overall prostate cancer. We also found that rare damaging variants in AOX1 and BRCA2 were associated with increased severity of prostate cancer in a case-only analysis of aggressive versus non-aggressive prostate cancer. At the single-variant level, we found rare non-synonymous variants in three genes (HOXB13, CHEK2, BIK) significantly associated with increased risk of overall prostate cancer and in four genes (ANO7, SPDL1, AR, TERT) with decreased risk. Altogether, this study provides deeper insights into the genetic architecture and biological basis of prostate cancer risk and severity.
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The ongoing expansion of human genomic datasets propels therapeutic target identification; however, extracting gene-disease associations from gene annotations remains challenging. Here, we introduce Mantis-ML 2.0, a framework integrating AstraZeneca's Biological Insights Knowledge Graph and numerous tabular datasets, to assess gene-disease probabilities throughout the phenome. We use graph neural networks, capturing the graph's holistic structure, and train them on hundreds of balanced datasets via a robust semi-supervised learning framework to provide gene-disease probabilities across the human exome. Mantis-ML 2.0 incorporates natural language processing to automate disease-relevant feature selection for thousands of diseases. The enhanced models demonstrate a 6.9% average classification power boost, achieving a median receiver operating characteristic (ROC) area under curve (AUC) score of 0.90 across 5220 diseases from Human Phenotype Ontology, OpenTargets, and Genomics England. Notably, Mantis-ML 2.0 prioritizes associations from an independent UK Biobank phenome-wide association study (PheWAS), providing a stronger form of triaging and mitigating against underpowered PheWAS associations. Results are exposed through an interactive web resource.
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Redes Neurales de la Computación , Humanos , Algoritmos , Biología Computacional/métodos , Bases de Datos Genéticas , Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo/métodos , Genómica/métodos , Fenómica/métodos , Fenotipo , Biobanco del Reino Unido , Reino UnidoRESUMEN
Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets1-4. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort5. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.
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Bancos de Muestras Biológicas , Proteínas Sanguíneas , Estudios de Asociación Genética , Genómica , Proteómica , Humanos , Alelos , Biomarcadores/sangre , Proteínas Sanguíneas/análisis , Proteínas Sanguíneas/genética , Bases de Datos Factuales , Exoma/genética , Hematopoyesis , Mutación , Plasma/química , Reino UnidoRESUMEN
Heterozygous de novo loss-of-function mutations in the gene expression regulator HNRNPU cause an early-onset developmental and epileptic encephalopathy. To gain insight into pathological mechanisms and lay the potential groundwork for developing targeted therapies, we characterized the neurophysiologic and cell-type-specific transcriptomic consequences of a mouse model of HNRNPU haploinsufficiency. Heterozygous mutants demonstrated global developmental delay, impaired ultrasonic vocalizations, cognitive dysfunction and increased seizure susceptibility, thus modeling aspects of the human disease. Single-cell RNA-sequencing of hippocampal and neocortical cells revealed widespread, yet modest, dysregulation of gene expression across mutant neuronal subtypes. We observed an increased burden of differentially-expressed genes in mutant excitatory neurons of the subiculum-a region of the hippocampus implicated in temporal lobe epilepsy. Evaluation of transcriptomic signature reversal as a therapeutic strategy highlights the potential importance of generating cell-type-specific signatures. Overall, this work provides insight into HNRNPU-mediated disease mechanisms and provides a framework for using single-cell RNA-sequencing to study transcriptional regulators implicated in disease.
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Haploinsuficiencia , Transcriptoma , Animales , Humanos , Ratones , Haploinsuficiencia/genética , Ribonucleoproteínas Nucleares Heterogéneas/metabolismo , Neuronas/metabolismo , ARN/metabolismo , Convulsiones/genética , Transcriptoma/genéticaRESUMEN
In the effort to treat Mendelian disorders, correcting the underlying molecular imbalance may be more effective than symptomatic treatment. Identifying treatments that might accomplish this goal requires extensive and up-to-date knowledge of molecular pathways-including drug-gene and gene-gene relationships. To address this challenge, we present "parsing modifiers via article annotations" (PARMESAN), a computational tool that searches PubMed and PubMed Central for information to assemble these relationships into a central knowledge base. PARMESAN then predicts putatively novel drug-gene relationships, assigning an evidence-based score to each prediction. We compare PARMESAN's drug-gene predictions to all of the drug-gene relationships displayed by the Drug-Gene Interaction Database (DGIdb) and show that higher-scoring relationship predictions are more likely to match the directionality (up- versus down-regulation) indicated by this database. PARMESAN had more than 200,000 drug predictions scoring above 8 (as one example cutoff), for more than 3,700 genes. Among these predicted relationships, 210 were registered in DGIdb and 201 (96%) had matching directionality. This publicly available tool provides an automated way to prioritize drug screens to target the most-promising drugs to test, thereby saving time and resources in the development of therapeutics for genetic disorders.
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PubMed , Humanos , Bases de Datos FactualesRESUMEN
De novo mutations in GNB1, encoding the Gß1 subunit of G proteins, cause a neurodevelopmental disorder with global developmental delay and epilepsy, GNB1 encephalopathy. Here, we show that mice carrying a pathogenic mutation, K78R, recapitulate aspects of the disorder, including developmental delay and generalized seizures. Cultured mutant cortical neurons also display aberrant bursting activity on multi-electrode arrays. Strikingly, the antiepileptic drug ethosuximide (ETX) restores normal neuronal network behavior in vitro and suppresses spike-and-wave discharges (SWD) in vivo. ETX is a known blocker of T-type voltage-gated Ca2+ channels and G protein-coupled potassium (GIRK) channels. Accordingly, we present evidence that K78R results in a gain-of-function (GoF) effect by increasing the activation of GIRK channels in cultured neurons and a heterologous model (Xenopus oocytes)-an effect we show can be potently inhibited by ETX. This work implicates a GoF mechanism for GIRK channels in epilepsy, identifies a new mechanism of action for ETX in preventing seizures, and establishes this mouse model as a pre-clinical tool for translational research with predicative value for GNB1 encephalopathy.
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Pontine nuclei (PN) neurons mediate the communication between the cerebral cortex andthe cerebellum to refine skilled motor functions. Prior studies showed that PN neurons fall into two subtypes based on their anatomic location and region-specific connectivity, but the extent of their heterogeneity and its molecular drivers remain unknown. Atoh1 encodes a transcription factor that is expressed in the PN precursors. We previously showed that partial loss of Atoh1 function in mice results in delayed PN development and impaired motor learning. In this study, we performed single-cell RNA sequencing to elucidate the cell state-specific functions of Atoh1 during PN development and found that Atoh1 regulates cell cycle exit, differentiation, migration, and survival of PN neurons. Our data revealed six previously not known PN subtypes that are molecularly and spatially distinct. We found that the PN subtypes exhibit differential vulnerability to partial loss of Atoh1 function, providing insights into the prominence of PN phenotypes in patients with ATOH1 missense mutations.
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Cerebelo , Neuronas , Animales , Ratones , Diferenciación Celular , Ciclo Celular , División Celular , Factores de Transcripción con Motivo Hélice-Asa-Hélice Básico/genéticaRESUMEN
Genome-wide association studies (GWASs) have established the contribution of common and low-frequency variants to metabolic blood measurements in the UK Biobank (UKB). To complement existing GWAS findings, we assessed the contribution of rare protein-coding variants in relation to 355 metabolic blood measurements-including 325 predominantly lipid-related nuclear magnetic resonance (NMR)-derived blood metabolite measurements (Nightingale Health Plc) and 30 clinical blood biomarkers-using 412,393 exome sequences from four genetically diverse ancestries in the UKB. Gene-level collapsing analyses were conducted to evaluate a diverse range of rare-variant architectures for the metabolic blood measurements. Altogether, we identified significant associations (p < 1 × 10-8) for 205 distinct genes that involved 1,968 significant relationships for the Nightingale blood metabolite measurements and 331 for the clinical blood biomarkers. These include associations for rare non-synonymous variants in PLIN1 and CREB3L3 with lipid metabolite measurements and SYT7 with creatinine, among others, which may not only provide insights into novel biology but also deepen our understanding of established disease mechanisms. Of the study-wide significant clinical biomarker associations, 40% were not previously detected on analyzing coding variants in a GWAS in the same cohort, reinforcing the importance of studying rare variation to fully understand the genetic architecture of metabolic blood measurements.
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Predisposición Genética a la Enfermedad , Estudio de Asociación del Genoma Completo , Humanos , Bancos de Muestras Biológicas , Biomarcadores , Lípidos , Reino Unido , Polimorfismo de Nucleótido SimpleRESUMEN
Synonymous mutations change the DNA sequence of a gene without affecting the amino acid sequence of the encoded protein. Although some synonymous mutations can affect RNA splicing, translational efficiency, and mRNA stability, studies in human genetics, mutagenesis screens, and other experiments and evolutionary analyses have repeatedly shown that most synonymous variants are neutral or only weakly deleterious, with some notable exceptions. Based on a recent study in yeast, there have been claims that synonymous mutations could be as important as nonsynonymous mutations in causing disease, assuming the yeast findings hold up and translate to humans. Here, we argue that there is insufficient evidence to overturn the large, coherent body of knowledge establishing the predominant neutrality of synonymous variants in the human genome.
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Evolución Biológica , Saccharomyces cerevisiae , Humanos , Mutación/genética , Secuencia de Aminoácidos , Genoma Humano/genéticaRESUMEN
We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes (P = 5.7 × 10-10) and had lower glycosylated hemoglobin (ß = -0.14 SD units, P = 1.1 × 10-24). These associations were independent of body mass index, suggesting protection against insulin resistance even in the setting of obesity. We replicated these findings in 96,811 Admixed Americans in the Mexico City Prospective Study (P < 0.05)Moreover, the protective effect of MAP3K15 variants was stronger in individuals who did not carry the Latino-enriched SLC16A11 risk haplotype (P = 6.0 × 10-4). Separately, we identified a Finnish-enriched MAP3K15 protein-truncating variant associated with decreased odds of both type 1 and type 2 diabetes (P < 0.05) in FinnGen. No adverse phenotypes were associated with protein-truncating MAP3K15 variants in the UKB, supporting this gene as a therapeutic target for diabetes.
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Diabetes Mellitus Tipo 2 , Quinasas Quinasa Quinasa PAM , Humanos , Diabetes Mellitus Tipo 2/genética , Predisposición Genética a la Enfermedad , Transportadores de Ácidos Monocarboxílicos/genética , Obesidad/genética , Estudios Prospectivos , Quinasas Quinasa Quinasa PAM/genéticaRESUMEN
The druggability of targets is a crucial consideration in drug target selection. Here, we adopt a stochastic semi-supervised ML framework to develop DrugnomeAI, which estimates the druggability likelihood for every protein-coding gene in the human exome. DrugnomeAI integrates gene-level properties from 15 sources resulting in 324 features. The tool generates exome-wide predictions based on labelled sets of known drug targets (median AUC: 0.97), highlighting features from protein-protein interaction networks as top predictors. DrugnomeAI provides generic as well as specialised models stratified by disease type or drug therapeutic modality. The top-ranking DrugnomeAI genes were significantly enriched for genes previously selected for clinical development programs (p value < 1 × 10-308) and for genes achieving genome-wide significance in phenome-wide association studies of 450 K UK Biobank exomes for binary (p value = 1.7 × 10-5) and quantitative traits (p value = 1.6 × 10-7). We accompany our method with a web application ( http://drugnomeai.public.cgr.astrazeneca.com ) to visualise the druggability predictions and the key features that define gene druggability, per disease type and modality.
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Aprendizaje Automático , Programas Informáticos , Humanos , Sistemas de Liberación de MedicamentosRESUMEN
Large reference datasets of protein-coding variation in human populations have allowed us to determine which genes and genic subregions are intolerant to germline genetic variation. There is also a growing number of genes implicated in severe Mendelian diseases that overlap with genes implicated in cancer. We hypothesized that cancer-driving mutations might be enriched in genic subregions that are depleted of germline variation relative to somatic variation. We introduce a new metric, OncMTR (oncology missense tolerance ratio), which uses 125,748 exomes in the Genome Aggregation Database (gnomAD) to identify these genic subregions. We demonstrate that OncMTR can significantly predict driver mutations implicated in hematologic malignancies. Divergent OncMTR regions were enriched for cancer-relevant protein domains, and overlaying OncMTR scores on protein structures identified functionally important protein residues. Last, we performed a rare variant, gene-based collapsing analysis on an independent set of 394,694 exomes from the UK Biobank and find that OncMTR markedly improves genetic signals for hematologic malignancies.
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Mutación de Línea Germinal , Neoplasias Hematológicas , Células Germinativas , Neoplasias Hematológicas/genética , HumanosRESUMEN
Trigeminal neuralgia, historically dubbed the "suicide disease," is an exceedingly painful neurologic condition characterized by sudden episodes of intense facial pain. Unfortunately, the only U.S. Food and Drug Administration (FDA)-approved medication for trigeminal neuralgia carries substantial side effects, with many patients requiring surgery. Here, we identify the NRF2 transcriptional network as a potential therapeutic target. We report that cerebrospinal fluid from patients with trigeminal neuralgia accumulates reactive oxygen species, several of which directly activate the pain-transducing channel TRPA1. Similar to our patient cohort, a mouse model of trigeminal neuropathic pain also exhibits notable oxidative stress. We discover that stimulating the NRF2 antioxidant transcriptional network is as analgesic as inhibiting TRPA1, in part by reversing the underlying oxidative stress. Using a transcriptome-guided drug discovery strategy, we identify two NRF2 network modulators as potential treatments. One of these candidates, exemestane, is already FDA-approved and may thus be a promising alternative treatment for trigeminal neuropathic pain.
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Synapses connect discrete neurons into vast networks that send, receive, and encode diverse forms of information. Synaptic function and plasticity, the neuronal process of adapting to diverse and variable inputs, depend on the dynamic nature of synaptic molecular components, which is mediated in part by cell adhesion signaling pathways. Here, we found that the enzyme biliverdin reductase (BVR) physically links together key focal adhesion signaling molecules at the synapse. BVR-null (BVR-/-) mice exhibited substantial deficits in learning and memory on neurocognitive tests, and hippocampal slices in which BVR was postsynaptically depleted showed deficits in electrophysiological responses to stimuli. RNA sequencing, biochemistry, and pathway analyses suggested that these deficits were mediated through the loss of focal adhesion signaling at both the transcriptional and biochemical level in the hippocampus. Independently of its catalytic function, BVR acted as a bridge between the primary focal adhesion signaling kinases FAK and Pyk2 and the effector kinase Src. Without BVR, FAK and Pyk2 did not bind to and stimulate Src, which then did not phosphorylate the N-methyl-d-aspartate (NMDA) receptor, a critical posttranslational modification for synaptic plasticity. Src itself is a molecular hub on which many signaling pathways converge to stimulate NMDAR-mediated neurotransmission, thus positioning BVR at a prominent intersection of synaptic signaling.