Transcriptomic analyses reveal neuronal specificity of Leigh syndrome associated genes

Leigh syndrome is a rare inherited, complex, neurometabolic disorder with genetic and clinical heterogeneity. Features present in affected patients range from classical stepwise developmental regression to ataxia, seizures, tremor, and occasionally psychiatric manifestations. Currently, more than 100 monogenic causes of Leigh syndrome have been identified, yet, the pathophysiology remains unknown. Here, we sought to determine the cellular specificity within the brain of all genes currently associated with Leigh syndrome. Further, we aimed to investigate potential genetic commonalities between Leigh syndrome and other disorders with overlapping clinical features. Enrichment of our target genes within the brain was evaluated with co-expression (CoExp) network analyses constructed using existing UK Brain Expression Consortium data. To determine the cellular specificity of the Leigh associated genes, we employed expression weighted cell type enrichment (EWCE) analysis of single cell RNA-Seq data. Finally, CoExp network modules demonstrating enrichment of Leigh syndrome associated genes were then utilised for synaptic gene ontology analysis and heritability analysis. CoExp network analyses revealed that Leigh syndrome associated genes exhibit the highest levels of expression in brain regions most affected on MRI in affected patients. EWCE revealed significant enrichment of target genes in hippocampal and somatosensory pyramidal neurons and interneurons of the brain. Analysis of CoExp modules enriched with our target genes revealed preferential association with pre-synaptic structures. Heritability studies suggested some common enrichment between Leigh syndrome and Parkinson disease and epilepsy. Our findings suggest a primary mitochondrial dysfunction as the underlying basis of Leigh syndrome with associated genes primarily expressed in neuronal cells

Cortically evoked motor responses in patients with Xp22.3-linked Kallmann's syndrome and in female gene carriers

Patients with Kallmann's syndrome show hypothalamic hypogonadism, hyposmia, and congenital mirror movements. As a correlate, a defect of gonadotropic neuron migration into the brain was recently detected. Considering abnormal outgrowth of neurons also as a possible substrate underlying mirror movements, we studied 3 patients and 2 asymptomatic female gene carriers from a kindred with proven linkage to Xp22.3, using focal transcranial magnetic stimulation of motor cortex hand areas with a figure-eight coil. In all 3 affected brothers, bilateral responses could be evoked almost simultaneously in their thenar muscles (slight latency differences were statistically insignificant). In contrast, the mother and the maternal aunt showed only unilateral, normal thenar responses, even with maximum tolerable stimulator output and high signal amplification. Correspondingly, mirror movements were present in the patients, but not in the gene carriers. Bilaterality of cortically evoked hand muscle responses and mirror movements, therefore, behaved as X-chromosomal recessive traits. A likely cause might be a disorder of neuronal outgrowth in the motor system, particularly of inhibitory callosal fibers. For normal anatomical development of the motor system, one intact Xp22.3 gene seems necessary

Multidimensional Dynamics of the Proteome in the Neurodegenerative and Aging Mammalian Brain

Neurodegenerative diseases are characterized by the abnormal accumulation of aggregated proteins in the brain. Using in vivo pulse isotope labeling, we screened the proteome for changes in protein turnover and abundance in multiple mouse models of neurodegeneration. These data suggest that the disease state of pathologically affected tissue is characterized by a proteome-wide increase in protein turnover and repair. In contrast, in healthy wild-type mice, aging in the mammalian brain is associated with a global slowdown in protein turnover.Peer reviewe

Architecture of the Mouse Brain Synaptome

Synapses are found in vast numbers in the brain and contain complex proteomes. We developed genetic labeling and imaging methods to examine synaptic proteins in individual excitatory synapses across all regions of the mouse brain. Synapse catalogs were generated from the molecular and morphological features of a billion synapses. Each synapse subtype showed a unique anatomical distribution, and each brain region showed a distinct signature of synapse subtypes. Whole-brain synaptome cartography revealed spatial architecture from dendritic to global systems levels and previously unknown anatomical features. Synaptome mapping of circuits showed correspondence between synapse diversity and structural and functional connectomes. Behaviorally relevant patterns of neuronal activity trigger spatiotemporal postsynaptic responses sensitive to the structure of synaptome maps. Areas controlling higher cognitive function contain the greatest synapse diversity, and mutations causing cognitive disorders reorganized synaptome maps. Synaptome technology and resources have wide-ranging application in studies of the normal and diseased brain

Architecture of the Mouse Brain Synaptome

Synapses are found in vast numbers in the brain and contain complex proteomes. We developed genetic labeling and imaging methods to examine synaptic proteins in individual excitatory synapses across all regions of the mouse brain. Synapse catalogs were generated from the molecular and morphological features of a billion synapses. Each synapse subtype showed a unique anatomical distribution, and each brain region showed a distinct signature of synapse subtypes. Whole-brain synaptome cartography revealed spatial architecture from dendritic to global systems levels and previously unknown anatomical features. Synaptome mapping of circuits showed correspondence between synapse diversity and structural and functional connectomes. Behaviorally relevant patterns of neuronal activity trigger spatiotemporal postsynaptic responses sensitive to the structure of synaptome maps. Areas controlling higher cognitive function contain the greatest synapse diversity, and mutations causing cognitive disorders reorganized synaptome maps. Synaptome technology and resources have wide-ranging application in studies of the normal and diseased brain

Genetic identification of cell types underlying brain complex traits yields insights into the etiology of Parkinson's disease.

Genome-wide association studies have discovered hundreds of loci associated with complex brain disorders, but it remains unclear in which cell types these loci are active. Here we integrate genome-wide association study results with single-cell transcriptomic data from the entire mouse nervous system to systematically identify cell types underlying brain complex traits. We show that psychiatric disorders are predominantly associated with projecting excitatory and inhibitory neurons. Neurological diseases were associated with different cell types, which is consistent with other lines of evidence. Notably, Parkinson's disease was genetically associated not only with cholinergic and monoaminergic neurons (which include dopaminergic neurons) but also with enteric neurons and oligodendrocytes. Using post-mortem brain transcriptomic data, we confirmed alterations in these cells, even at the earliest stages of disease progression. Our study provides an important framework for understanding the cellular basis of complex brain maladies, and reveals an unexpected role of oligodendrocytes in Parkinson's disease

Artificial intelligence for dementia genetics and omics

Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine

Transcriptional regulatory networks underlying gene expression changes in Huntington's disease

Abstract Transcriptional changes occur presymptomatically and throughout Huntington's disease (HD), motivating the study of transcriptional regulatory networks (TRNs) in HD. We reconstructed a genome‐scale model for the target genes of 718 transcription factors (TFs) in the mouse striatum by integrating a model of genomic binding sites with transcriptome profiling of striatal tissue from HD mouse models. We identified 48 differentially expressed TF‐target gene modules associated with age‐ and CAG repeat length‐dependent gene expression changes in Htt CAG knock‐in mouse striatum and replicated many of these associations in independent transcriptomic and proteomic datasets. Thirteen of 48 of these predicted TF‐target gene modules were also differentially expressed in striatal tissue from human disease. We experimentally validated a specific model prediction that SMAD3 regulates HD‐related gene expression changes using chromatin immunoprecipitation and deep sequencing (ChIP‐seq) of mouse striatum. We found CAG repeat length‐dependent changes in the genomic occupancy of SMAD3 and confirmed our model's prediction that many SMAD3 target genes are downregulated early in HD