scholarly journals Moving beyond neurons: the role of cell type-specific gene regulation in Parkinson’s disease heritability

2018 ◽  
Author(s):  
Regina H Reynolds ◽  
Juan Botía ◽  
Mike A Nalls ◽  
John Hardy ◽  
Sarah A Gagliano ◽  
...  

AbstractParkinson’s disease (PD), with its characteristic loss of nigrostriatal dopaminergic neurons and deposition of α-synuclein in neurons, is often considered a neuronal disorder. However, in recent years substantial evidence has emerged to implicate glial cell types, such as astrocytes and microglia. In this study, we used stratified LD score regression and expression-weighted cell-type enrichment together with several brain-related and cell-type-specific genomic annotations to connect human genomic PD findings to specific brain cell types. We found that PD heritability does not enrich in global and regional brain annotations or brain-related cell-type-specific annotations. Likewise, we found no enrichment of PD susceptibility genes in brain-related cell types. In contrast, we demonstrated a significant enrichment of PD heritability in a curated lysosomal gene set specifically expressed in astrocytic and microglial subtypes. Our results suggest that PD risk loci do not lie in specific cell types or individual brain regions, but rather in global cellular processes to which cell types may have varying vulnerability.

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Kai Kang ◽  
Caizhi Huang ◽  
Yuanyuan Li ◽  
David M. Umbach ◽  
Leping Li

Abstract Background Biological tissues consist of heterogenous populations of cells. Because gene expression patterns from bulk tissue samples reflect the contributions from all cells in the tissue, understanding the contribution of individual cell types to the overall gene expression in the tissue is fundamentally important. We recently developed a computational method, CDSeq, that can simultaneously estimate both sample-specific cell-type proportions and cell-type-specific gene expression profiles using only bulk RNA-Seq counts from multiple samples. Here we present an R implementation of CDSeq (CDSeqR) with significant performance improvement over the original implementation in MATLAB and an added new function to aid cell type annotation. The R package would be of interest for the broader R community. Result We developed a novel strategy to substantially improve computational efficiency in both speed and memory usage. In addition, we designed and implemented a new function for annotating the CDSeq estimated cell types using single-cell RNA sequencing (scRNA-seq) data. This function allows users to readily interpret and visualize the CDSeq estimated cell types. In addition, this new function further allows the users to annotate CDSeq-estimated cell types using marker genes. We carried out additional validations of the CDSeqR software using synthetic, real cell mixtures, and real bulk RNA-seq data from the Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) project. Conclusions The existing bulk RNA-seq repositories, such as TCGA and GTEx, provide enormous resources for better understanding changes in transcriptomics and human diseases. They are also potentially useful for studying cell–cell interactions in the tissue microenvironment. Bulk level analyses neglect tissue heterogeneity, however, and hinder investigation of a cell-type-specific expression. The CDSeqR package may aid in silico dissection of bulk expression data, enabling researchers to recover cell-type-specific information.


2012 ◽  
Vol 40 (5) ◽  
pp. 1152-1157 ◽  
Author(s):  
Elizabeth M. Hartfield ◽  
Hugo J.R. Fernandes ◽  
Jane Vowles ◽  
Sally A. Cowley ◽  
Richard Wade-Martins

iPSCs (induced pluripotent stem cells) offer an unparalleled opportunity to generate and study physiologically relevant cell types in culture. iPSCs can be generated by reprogramming almost any somatic cell type using pluripotency factors such as Oct4, SOX2, Nanog and Klf4. By reprogramming cells from patients carrying disease-associated mutations, and subsequent differentiation into the cell type of interest, researchers now have the opportunity to study disease-specific cell types which were previously inaccessible. In the case of PD (Parkinson's disease), reprogramming is advancing rapidly, and cell lines have been generated from patients carrying mutations in several disease-associated genes, including SNCA (α-synuclein), PARK2 (parkin), PINK1 (phosphatase and tensin homologue deleted on chromosome 10-induced putative kinase 1), PARK7 (DJ-1) and LRRK2 (leucine-rich repeat kinase 2), as well as idiopathic cases. Functional dopaminergic neurons have been differentiated from these cells and their physiology has been compared with control neurons. Human dopaminergic neurons had been previously inaccessible until post-mortem, when the disease is generally highly progressed into pathology. In comparison, iPSCs provide a living cell model with the potential to study early molecular changes which accumulate in cells and ultimately result in neurodegeneration. Although clear phenotypes have not yet been unambiguously identified in patient-derived dopaminergic neurons, there are suggested aberrations in cellular pathways involved in neurodegeneration. Overall, these cells offer a unique opportunity to study dopaminergic neurons carrying a ‘Parkinsonian genome’. The present review discusses the advances in cellular reprogramming technologies and studies that have been carried out on PD-derived iPSCs and differentiated dopaminergic neurons.


Proteomes ◽  
2018 ◽  
Vol 6 (4) ◽  
pp. 51 ◽  
Author(s):  
Rashaun S. Wilson ◽  
Angus C. Nairn

Cell-type-specific analysis has become a major focus for many investigators in the field of neuroscience, particularly because of the large number of different cell populations found in brain tissue that play roles in a variety of developmental and behavioral disorders. However, isolation of these specific cell types can be challenging due to their nonuniformity and complex projections to different brain regions. Moreover, many analytical techniques used for protein detection and quantitation remain insensitive to the low amounts of protein extracted from specific cell populations. Despite these challenges, methods to improve proteomic yield and increase resolution continue to develop at a rapid rate. In this review, we highlight the importance of cell-type-specific proteomics in neuroscience and the technical difficulties associated. Furthermore, current progress and technological advancements in cell-type-specific proteomics research are discussed with an emphasis in neuroscience.


2016 ◽  
Author(s):  
B. Ogan Mancarci ◽  
Lilah Toker ◽  
Shreejoy J Tripathy ◽  
Brenna Li ◽  
Brad Rocco ◽  
...  

AbstractEstablishing the molecular diversity of cell types is crucial for the study of the nervous system. We compiled a cross-laboratory database of mouse brain cell type-specific transcriptomes from 36 major cell types from across the mammalian brain using rigorously curated published data from pooled cell type microarray and single cell RNA-sequencing studies. We used these data to identify cell type-specific marker genes, discovering a substantial number of novel markers, many of which we validated using computational and experimental approaches. We further demonstrate that summarized expression of marker gene sets in bulk tissue data can be used to estimate the relative cell type abundance across samples. To facilitate use of this expanding resource, we provide a user-friendly web interface at Neuroexpresso.org.Significance StatementCell type markers are powerful tools in the study of the nervous system that help reveal properties of cell types and acquire additional information from large scale expression experiments. Despite their usefulness in the field, known marker genes for brain cell types are few in number. We present NeuroExpresso, a database of brain cell type specific gene expression profiles, and demonstrate the use of marker genes for acquiring cell type specific information from whole tissue expression. The database will prove itself as a useful resource for researchers aiming to reveal novel properties of the cell types and aid both laboratory and computational scientists to unravel the cell type specific components of brain disorders.


Immuno ◽  
2021 ◽  
Vol 1 (2) ◽  
pp. 78-90
Author(s):  
Johannes Burtscher ◽  
Grégoire P. Millet

Like in other neurodegenerative diseases, protein aggregation, mitochondrial dysfunction, oxidative stress and neuroinflammation are hallmarks of Parkinson’s disease (PD). Differentiating characteristics of PD include the central role of α-synuclein in the aggregation pathology, a distinct vulnerability of the striato-nigral system with the related motor symptoms, as well as specific mitochondrial deficits. Which molecular alterations cause neurodegeneration and drive PD pathogenesis is poorly understood. Here, we summarize evidence of the involvement of three interdependent factors in PD and suggest that their interplay is likely a trigger and/or aggravator of PD-related neurodegeneration: hypoxia, acidification and inflammation. We aim to integrate the existing knowledge on the well-established role of inflammation and immunity, the emerging interest in the contribution of hypoxic insults and the rather neglected effects of brain acidification in PD pathogenesis. Their tight association as an important aspect of the disease merits detailed investigation. Consequences of related injuries are discussed in the context of aging and the interaction of different brain cell types, in particular with regard to potential consequences on the vulnerability of dopaminergic neurons in the substantia nigra. A special focus is put on the identification of current knowledge gaps and we emphasize the importance of related insights from other research fields, such as cancer research and immunometabolism, for neurodegeneration research. The highlighted interplay of hypoxia, acidification and inflammation is likely also of relevance for other neurodegenerative diseases, despite disease-specific biochemical and metabolic alterations.


Author(s):  
Hee-Dae Kim ◽  
Jing Wei ◽  
Tanessa Call ◽  
Nicole Teru Quintus ◽  
Alexander J. Summers ◽  
...  

AbstractDepression is the leading cause of disability and produces enormous health and economic burdens. Current treatment approaches for depression are largely ineffective and leave more than 50% of patients symptomatic, mainly because of non-selective and broad action of antidepressants. Thus, there is an urgent need to design and develop novel therapeutics to treat depression. Given the heterogeneity and complexity of the brain, identification of molecular mechanisms within specific cell-types responsible for producing depression-like behaviors will advance development of therapies. In the reward circuitry, the nucleus accumbens (NAc) is a key brain region of depression pathophysiology, possibly based on differential activity of D1- or D2- medium spiny neurons (MSNs). Here we report a circuit- and cell-type specific molecular target for depression, Shisa6, recently defined as an AMPAR component, which is increased only in D1-MSNs in the NAc of susceptible mice. Using the Ribotag approach, we dissected the transcriptional profile of D1- and D2-MSNs by RNA sequencing following a mouse model of depression, chronic social defeat stress (CSDS). Bioinformatic analyses identified cell-type specific genes that may contribute to the pathogenesis of depression, including Shisa6. We found selective optogenetic activation of the ventral tegmental area (VTA) to NAc circuit increases Shisa6 expression in D1-MSNs. Shisa6 is specifically located in excitatory synapses of D1-MSNs and increases excitability of neurons, which promotes anxiety- and depression-like behaviors in mice. Cell-type and circuit-specific action of Shisa6, which directly modulates excitatory synapses that convey aversive information, identifies the protein as a potential rapid-antidepressant target for aberrant circuit function in depression.


2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jinting Guan ◽  
Yiping Lin ◽  
Yang Wang ◽  
Junchao Gao ◽  
Guoli Ji

Abstract Background Genome-wide association studies have identified genetic variants associated with the risk of brain-related diseases, such as neurological and psychiatric disorders, while the causal variants and the specific vulnerable cell types are often needed to be studied. Many disease-associated genes are expressed in multiple cell types of human brains, while the pathologic variants affect primarily specific cell types. We hypothesize a model in which what determines the manifestation of a disease in a cell type is the presence of disease module comprised of disease-associated genes, instead of individual genes. Therefore, it is essential to identify the presence/absence of disease gene modules in cells. Methods To characterize the cell type-specificity of brain-related diseases, we construct human brain cell type-specific gene interaction networks integrating human brain nucleus gene expression data with a referenced tissue-specific gene interaction network. Then from the cell type-specific gene interaction networks, we identify significant cell type-specific disease gene modules by performing statistical tests. Results Between neurons and glia cells, the constructed cell type-specific gene networks and their gene functions are distinct. Then we identify cell type-specific disease gene modules associated with autism spectrum disorder and find that different gene modules are formed and distinct gene functions may be dysregulated in different cells. We also study the similarity and dissimilarity in cell type-specific disease gene modules among autism spectrum disorder, schizophrenia and bipolar disorder. The functions of neurons-specific disease gene modules are associated with synapse for all three diseases, while those in glia cells are different. To facilitate the use of our method, we develop an R package, CtsDGM, for the identification of cell type-specific disease gene modules. Conclusions The results support our hypothesis that a disease manifests itself in a cell type through forming a statistically significant disease gene module. The identification of cell type-specific disease gene modules can promote the development of more targeted biomarkers and treatments for the disease. Our method can be applied for depicting the cell type heterogeneity of a given disease, and also for studying the similarity and dissimilarity between different disorders, providing new insights into the molecular mechanisms underlying the pathogenesis and progression of diseases.


Author(s):  
Samina Momtaz ◽  
Belen Molina ◽  
Luwanika Mlera ◽  
Felicia Goodrum ◽  
Jean M. Wilson

AbstractHuman cytomegalovirus (HCMV), while highly restricted for the human species, infects an unlimited array of cell types in the host. Patterns of infection are dictated by the cell type infected, but cell type-specific factors and how they impact tropism for specific cell types is poorly understood. Previous studies in primary endothelial cells showed that HCMV infection induces large multivesicular-like bodies that incorporate viral products including dense bodies and virions. Here we define the nature of these large vesicles using a recombinant virus where UL32, encoding the pp150 tegument protein, is fused in frame with green fluorescent protein (GFP, TB40/E-UL32-GFP). Cells were fixed and labeled with antibodies against subcellular compartment markers and imaged using confocal and super-resolution microscopy. In fibroblasts, UL32-GFP-positive vesicles were marked with classical markers of MVBs, including CD63 and lysobisphosphatidic acid (LBPA), both classical MVB markers, as well as the clathrin and LAMP1. Unexpectedly, UL32-GFP-positive vesicles in endothelial cells were not labeled by CD63, and LBPA was completely lost from infected cells. We defined these UL32-positive vesicles in endothelial cells using markers for the cis-Golgi (GM130), lysosome (LAMP1), and autophagy (LC3B). These findings suggest that virus-containing MVBs in fibroblasts are derived from the canonical endocytic pathway and takeover classical exosomal release pathway. Virus containing MVBs in HMVECs are derived from the early biosynthetic pathway and exploit a less characterized early Golgi-LAMP1-associated non-canonical secretory autophagy pathway. These results reveal striking cell-type specific membrane trafficking differences in host pathways that are exploited by HCMV.ImportanceHuman cytomegalovirus (HCMV) is a herpesvirus that, like all herpesvirus, that establishes a life long infection. HCMV remains a significant cause of morbidity and mortality in the immunocompromised and HCMV seropositivity is associated with increased risk vascular disease. HCMV infects many cells in the human and the biology underlying the different patterns of infection in different cell types is poorly understood. Endothelial cells are important target of infection that contribute to hematogenous spread of the virus to tissues. Here we define striking differences in the biogenesis of large vesicles that incorporate virions in fibroblasts and endothelial cells. In fibroblasts, HCMV is incorporated into canonical MVBs derived from an endocytic pathway, whereas HCMV matures through vesicles derived from the biosynthetic pathway in endothelial cells. This work defines basic biological differences between these cell types that may impact the outcome of infection.


2021 ◽  
Vol 12 ◽  
Author(s):  
Megan E. Barefoot ◽  
Netanel Loyfer ◽  
Amber J. Kiliti ◽  
A. Patrick McDeed ◽  
Tommy Kaplan ◽  
...  

Detection of cellular changes in tissue biopsies has been the basis for cancer diagnostics. However, tissue biopsies are invasive and limited by inaccuracies due to sampling locations, restricted sampling frequency, and poor representation of tissue heterogeneity. Liquid biopsies are emerging as a complementary approach to traditional tissue biopsies to detect dynamic changes in specific cell populations. Cell-free DNA (cfDNA) fragments released into the circulation from dying cells can be traced back to the tissues and cell types they originated from using DNA methylation, an epigenetic regulatory mechanism that is highly cell-type specific. Decoding changes in the cellular origins of cfDNA over time can reveal altered host tissue homeostasis due to local cancer invasion and metastatic spread to distant organs as well as treatment responses. In addition to host-derived cfDNA, changes in cancer cells can be detected from cell-free, circulating tumor DNA (ctDNA) by monitoring DNA mutations carried by cancer cells. Here, we will discuss computational approaches to identify and validate robust biomarkers of changed tissue homeostasis using cell-free, methylated DNA in the circulation. We highlight studies performing genome-wide profiling of cfDNA methylation and those that combine genetic and epigenetic markers to further identify cell-type specific signatures. Finally, we discuss opportunities and current limitations of these approaches for implementation in clinical oncology.


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