Cellular Composition Research Articles

Focal adhesion kinase regulates tendon cell mechanoresponse and physiological tendon development.

Tendons enable locomotion by transmitting high tensile mechanical forces between muscle and bone via their dense extracellular matrix (ECM). The application of extrinsic mechanical stimuli via muscle contraction is necessary to regulate healthy tendon function. Specifically, applied physiological levels of mechanical loading elicit an anabolic tendon cell response, while decreased mechanical loading evokes a degradative tendon state. Although the tendon response to mechanical stimuli has implications in disease pathogenesis and clinical treatment strategies, the cell signaling mechanisms by which tendon cells sense and respond to mechanical stimuli within the native tendon ECM remain largely unknown. Therefore, we explored the role of cell-ECM adhesions in regulating tendon cell mechanotransduction by perturbing the genetic expression and signaling activity of focal adhesion kinase (FAK) through both invitro and invivo approaches. We determined that FAK regulates tendon cell spreading behavior and focal adhesion morphology, nuclear deformation in response to applied mechanical strain, and mechanosensitive gene expression. In addition, our data reveal that FAK signaling plays an essential role in invivo tendon development and postnatal growth, as FAK-knockout mouse tendons demonstrated reduced tendon size, altered mechanical properties, differences in cellular composition, and reduced maturity of the deposited ECM. These data provide a foundational understanding of the role of FAK signaling as a critical regulator of insitu tendon cell mechanotransduction. Importantly, an increased understanding of tendon cell mechanotransductive mechanisms may inform clinical practice as well as lead to the discovery of diagnostic and/or therapeutic molecular targets.

Proteome-Scale Tissue Mapping Using Mass Spectrometry Based on Label-Free and Multiplexed Workflows

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in healthy and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in a whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ∼3500 proteins at a spatial resolution of 50 μm and the highest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables the identification of protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

Long-term acclimation to organic carbon enhances the production of loliolide from Scenedesmus deserticola

Production of functional biocompounds from microalgae has garnered interest from different industrial sectors; however, their overall productivity must be substantially improved for commercialization. Herein, long-term acclimation of Scenedesmus deserticola was conducted using glucose as an organic carbon source to enhance its heterotrophic capabilities and the production potential of loliolide. A year-long acclimation on agar plates led to the selection of S. deserticola HS4, which exhibited at least 2-fold increase in loliolide production potential; S. deserticola HS4 was subjected to further screening of its cultivation conditions and fed-batch cultivation was subsequently performed in liter-scale reactors. While S. deserticola HS4 exhibited shifts in cellular morphology and biochemical composition, the results suggested a substantial increase in its loliolide productivity regardless of trophic modes. Collectively, these results highlight the potential of long-term acclimation as an effective strategy for improving microalgal crops to align with industrial production practices.

Differential Secretomes of Processed Adipose Grafts, the Stromal Vascular Fraction, and Adipose-Derived Stem Cells.

There are multiple methods to prepare lipoaspirate for autologous fat transfer; however, graft retention remains unpredictable. The purpose of this study was to compare the cellular and protein composition of adipose grafts and the stromal vascular fraction (SVF) resulting from three common techniques to prepare adipose grafts. Adipose grafts were harvested from healthy donors and processed via three techniques: centrifugation (C), a single-filter (SF) device, and a double-filtration (DF) system. Part of each graft was analyzed or further processed to isolate the SVF. Cell viability, surface markers, cytokine, and growth factors were compared between the graft and SVF as well as adipose-derived stem cells (ASCs). Overall, we found variations across the three processing techniques and among the graft components (ASCs, SVF, and fat). Cell viability within the grafts was similar (94.6%, 92.3%, and 93.6%; P = 0.93). The trend was a greater percentage of ASCs from SF versus DF or centrifugation (6.95%, 4.63%, and 1.93%, respectively, P = 0.06). Adipogenic markers (adiponectin and leptin) were similar among all three grafts (P = 0.45). Markers of tissue remodeling were greatest in the SVF compared with fat and ASCs, regardless of processing technique. There was higher relative expression of MMP-9 (2×), Extracellular matrix metalloproteinase inducer (EMMPRIN) (2.5×), endoglin (5×), and IL-8 (1.5×) in the SVF (P < 0.005). Our study identified differences in cytokine expression in adipose grafts and the SVF, particularly in cytokines important in inflammation and wound healing. These secretomes may impact graft retention and fat necrosis and have the potential implications in cell-assisted lipotransfer. There were no significant differences between the final products of any of the processing techniques.

Identification of novel M2 macrophage-related molecule ATP6V1E1 and its biological role in hepatocellular carcinoma based on machine learning algorithms.

Hepatocellular carcinoma (HCC) remains the most prevalent form of primary liver cancer, characterized by late detection and suboptimal response to current therapies. The tumour microenvironment, especially the role of M2 macrophages, is pivotal in the progression and prognosis of HCC. We applied the machine learning algorithm-CIBERSORT, to quantify cellular compositions within the HCC TME, focusing on M2 macrophages. Gene expression profiles were analysed to identify key molecules, with ATP6V1E1 as a primary focus. We employed Gene Set Enrichment Analysis (GSEA) and Kaplan-Meier survival analysis to investigate the molecular pathways and prognostic significance of ATP6V1E1. A prognostic model was developed using multivariate Cox regression analysis based on ATP6V1E1-related molecules, and functional impacts were assessed through cell proliferation assays. M2 macrophages were the dominant cell type in the HCC TME, significantly correlating with adverse survival outcomes. ATP6V1E1 was robustly associated with advanced disease stages and poor prognostic features such as vascular invasion and elevated alpha-fetoprotein levels. GSEA linked high ATP6V1E1 expression to critical oncogenic pathways, including immunosuppression and angiogenesis, and reduced activity in metabolic processes like bile acid and fatty acid metabolism. The prognostic model stratified HCC patients into distinct risk categories, showing high predictive accuracy (1-year AUC = 0.775, 3-year AUC = 0.709 and 5-year AUC = 0.791). Invitro assays demonstrated that ATP6V1E1 knockdown markedly inhibited the proliferation of HCC cells. The study underscores the significance of M2 macrophages and ATP6V1E1 in HCC, highlighting their potential as therapeutic and prognostic targets.

S21-04 A microphysiological system of the liver that recapitulates the cellular composition and organization of the hepatic lobule

S21-04 A microphysiological system of the liver that recapitulates the cellular composition and organization of the hepatic lobule

Single-cell multi-modal chromatin profiles revealing epigenetic regulations of cells in hepatocellular carcinoma.

Various epigenetic regulations systematically govern gene expression in cells involving various biological processes. Dysregulation of the epigenome leads to aberrant transcriptional programs and subsequently results in diseases, such as cancer. Therefore, comprehensive profiling epigenomics is essential for exploring the mechanisms underlying gene expression regulation during development and disease. In this study, we developed single-cell chromatin proteins and accessibility tagmentation (scCPA-Tag), a multi-modal single-cell epigenetic profile capturing technique based on barcoded Tn5 transposases and a droplet microfluidics platform. scCPA-Tag enables the simultaneous capture of DNA profiles of histone modification and chromatin accessibility in the same cell. By applying scCPA-Tag to K562 cells and a hepatocellular carcinoma (HCC) sample, we found that the silence of several chromatin-accessible genes can be attributed to lysine-27-trimethylation of the histone H3 tail (H3K27me3) modification. We characterized the epigenetic features of the tumour cells and different immune cell types in the HCC tumour tissue by scCPA-Tag. Besides, a tumour cell subtype (C2) with more aggressive features was identified and characterized by high chromatin accessibility and a lower abundance of H3K27me3 on tumour-promoting genes. Our multi-modal scCPA-Tag provides a comprehensive approach for exploring the epigenetic landscapes of heterogeneous cell types and revealing the mechanisms of gene expression regulation during developmental and pathological processes at the single-cell level. scCPA-Tag offers a highly efficient and high throughput technique to simultaneously profile histone modification and chromatin accessibility within a single cell. scCPA-Tag enables to uncover multiple epigenetic modification features of cellular compositions within tumor tissues. scCPA-Tag facilitates the exploration of the epigenetic landscapes of heterogeneous cell types and provides the mechanisms governing gene expression regulation.

Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research.

Breast cancer is the most prevalent malignant tumor among women with high heterogeneity. Traditional techniques frequently struggle to comprehensively capture the intricacy and variety of cellular states and interactions within breast cancer. As global precision medicine rapidly advances, single-cell RNA sequencing (scRNA-seq) has become a highly effective technique, revolutionizing breast cancer research by offering unprecedented insights into the cellular heterogeneity and complexity of breast cancer. This cutting-edge technology facilitates the analysis of gene expression profiles at the single-cell level, uncovering diverse cell types and states within the tumor microenvironment. By dissecting the cellular composition and transcriptional signatures of breast cancer cells, scRNA-seq provides new perspectives for understanding the mechanisms behind tumor therapy, drug resistance and metastasis in breast cancer. In this review, we summarized the working principle and workflow of scRNA-seq and emphasized the major applications and discoveries of scRNA-seq in breast cancer research, highlighting its impact on our comprehension of breast cancer biology and its potential for guiding personalized treatment strategies.

Identification of clinical prognosis features and significant DNA methylation regulation in pineoblastoma.

Pineoblastoma (PB) represents a great challenge for clinical management due to lack of a specific therapeutic regimen. This study aims to identify relevant prognostic factors and potential treatment targets by mining public databases. The clinical characteristics and survival data of PB patients were obtained from the SEER database between 2000 and 2019 for Cox regression analysis and nomogram construction. The PB's DNA methylation data was acquired from two GEO datasets, GSE133801 and GSE215240, for bioinformatics analysis. Of 383PB patients, Cox univariate analysis unveiled that male gender (p = 0.017), age younger than 3years at diagnosis (p < 0.001) and absence of radiotherapy (p < 0.001) correlated with poorer overall survival (OS), the subsequent multivariate analysis confirmed sex (p = 0.036), age (p < 0.001) and radiotherapy (p = 0.005) as independent prognostic factors for OS. A nomogram showed robust predictive accuracy as evidenced by AUC values (1-year OS: 0.774, 3-year OS: 0.692, 5-year OS: 0.643). DNA methylation analysis observed tumor hypomethylation, notably in promoter regions. Later, the GO enrichment analysis of aberrantly methylated genes indicated associations with embryonic organ development, cellular membrane composition and DNA-binding transcription, while KEGG analysis revealed enrichment in tumor-associated MAPK, calcium and RAS signaling pathways. The prognosis of PB is closely associated with sex, age and receipt of radiotherapy, potentially linked to aberrations in the RAS and MAPK signaling pathways. The individual case suggests that dasatinib and trametinib are potential targeted therapies for improving PB prognosis.

Advances in understanding the cellular composition and molecular signatures of the adult Drosophila eye through single-cell RNA sequencing

Advances in understanding the cellular composition and molecular signatures of the adult Drosophila eye through single-cell RNA sequencing

Human efferent ductules and epididymis display unique cell lineages with motile and primary cilia.

Previous research has illustrated the role of cilia as mechanical and sensory antennae in various organs within the mammalian male reproductive system across different developmental stages. Despite their significance in both organ development and homeostasis, primary cilia in the human male reproductive excurrent duct have been overlooked due to limited access to human specimens. This study aimed to characterize the unique cellular composition of human efferent and epididymal ducts, with a focus on their association with primary cilia. Human efferent ductules/epididymides from five donors aged 32-47 years, were obtained through our local organ transplant program. Cell lineage specificity and primary cilia features were examined by immunofluorescent staining and confocal microscopy in the efferent ductules and the distinct segments of the epididymis. The epithelium of the human efferent duct exhibited estrogen receptor-positive cells with primary cilia, FoxJ1-positive multiciliated cells with numerous motile cilia, and non-ciliated intraepithelial immune cells. Notably, intraluminal macrophages, identified by CD163/CD68 positivity, were observed to engage in sperm phagocytosis. In all three segments of the human epididymis, primary cilia were found on the surface of principal and basal cells. Our research indicates that the human efferent ductules create a distinct environment, characterized by the presence of two types of ciliated cells that are in contact with immune cells. The discovery of sensory primary cilia exposed on the surface of reabsorptive cells in the efferent ductules, as well as on basal and principal cells in the epididymis, lays the foundation for complementary functional studies. This research uncovers novel characteristics exclusive to human efferent ductules and epididymides, providing a basis for exploring innovative approaches to male contraception and infertility treatment.

Automated multi-scale computational pathotyping (AMSCP) of inflamed synovial tissue

Rheumatoid arthritis (RA) is a complex immune-mediated inflammatory disorder in which patients suffer from inflammatory-erosive arthritis. Recent advances on histopathology heterogeneity of RA synovial tissue revealed three distinct phenotypes based on cellular composition (pauci-immune, diffuse and lymphoid), suggesting that distinct etiologies warrant specific targeted therapy which motivates a need for cost effective phenotyping tools in preclinical and clinical settings. To this end, we developed an automated multi-scale computational pathotyping (AMSCP) pipeline for both human and mouse synovial tissue with two distinct components that can be leveraged together or independently: (1) segmentation of different tissue types to characterize tissue-level changes, and (2) cell type classification within each tissue compartment that assesses change across disease states. Here, we demonstrate the efficacy, efficiency, and robustness of the AMSCP pipeline as well as the ability to discover novel phenotypes. Taken together, we find AMSCP to be a valuable cost-effective method for both pre-clinical and clinical research.

Single-cell transcriptome landscape of the kidney reveals potential innate immune regulation mechanisms in hybrid yellow catfish after Aeromonas hydrophila infection

Aeromonas hydrophila, the pathogen that is the causative agent of motile Aeromonas septicemia (MAS) disease, commonly attacks freshwater fishes, including yellow catfish (Pelteobagrus fulvidraco). Although the kidney is one of the most important organs involved in immunity in fish, its role in disease progression has not been fully elucidated. Understanding the cellular composition and innate immune regulation mechanisms of the kidney of yellow catfish is important for the treatment of MAS. In this study, single-cell RNA sequencing (scRNA-seq) was performed on the kidney of hybrid yellow catfish (Pelteobagrus fulvidraco ♀ × Pelteobagrus vachelli ♂) after A. hydrophila infection. Nine types of kidney cells were identified using marker genes, and a transcription module of marker genes in the main immune cells of hybrid yellow catfish kidney tissue was constructed using in-situ hybridization. In addition, the single-cell transcriptome data showed that the differentially expressed genes of macrophages were primarily enriched in the Toll-like receptor and Nod-like receptor signaling pathways. The expression levels of genes involved in these pathways were upregulated in macrophages following A. hydrophila infection. Transmission electron microscopy and TUNEL analysis revealed the cellular characteristics of macrophages before and after A. hydrophila infection. These data provide empirical support for in-depth research on the role of the kidney in the innate immune response of hybrid yellow catfish.

An integrated single-cell reference atlas of the human endometrium

The complex and dynamic cellular composition of the human endometrium remains poorly understood. Previous endometrial single-cell atlases profiled few donors and lacked consensus in defining cell types. We introduce the Human Endometrial Cell Atlas (HECA), a high-resolution single-cell reference atlas (313,527 cells) combining published and new endometrial single-cell transcriptomics datasets of 63 women with and without endometriosis. HECA assigns consensus and identifies previously unreported cell types, mapped in situ using spatial transcriptomics and validated using a new independent single-nuclei dataset (312,246 nuclei, 63 donors). In the functionalis, we identify intricate stromal–epithelial cell coordination via transforming growth factor beta (TGFβ) signaling. In the basalis, we define signaling between fibroblasts and an epithelial population expressing progenitor markers. Integration of HECA with large-scale endometriosis genome-wide association study data pinpoints decidualized stromal cells and macrophages as most likely dysregulated in endometriosis. The HECA is a valuable resource for studying endometrial physiology and disorders, and for guiding microphysiological in vitro systems development.

Community assessment of methods to deconvolve cellular composition from bulk gene expression

We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

A multidimensional analysis reveals distinct immune phenotypes and the composition of immune aggregates in pediatric acute myeloid leukemia

Because of the low mutational burden and consequently, fewer potential neoantigens, children with acute myeloid leukemia (AML) are thought to have a T cell-depleted or ‘cold’ tumor microenvironment and may have a low likelihood of response to T cell-directed immunotherapies. Understanding the composition, phenotype, and spatial organization of T cells and other microenvironmental populations in the pediatric AML bone marrow (BM) is essential for informing future immunotherapeutic trials about targetable immune-evasion mechanisms specific to pediatric AML. Here, we conducted a multidimensional analysis of the tumor immune microenvironment in pediatric AML and non-leukemic controls. We demonstrated that nearly one-third of pediatric AML cases has an immune-infiltrated BM, which is characterized by a decreased ratio of M2- to M1-like macrophages. Furthermore, we detected the presence of large T cell networks, both with and without colocalizing B cells, in the BM and dissected the cellular composition of T- and B cell-rich aggregates using spatial transcriptomics. These analyses revealed that these aggregates are hotspots of CD8+ T cells, memory B cells, plasma cells and/or plasmablasts, and M1-like macrophages. Collectively, our study provides a multidimensional characterization of the BM immune microenvironment in pediatric AML and indicates starting points for further investigations into immunomodulatory mechanisms in this devastating disease.

Prediction of in-hospital mortality in patients with myocardial infarction and type 2 diabetes: the role of cellular indices of systemic inflammation

Aim. To assess the value of cellular indices of systemic inflammation in the prognosis of in-hospital mortality in patients with ST-segment elevation myocardial infarction (MI) in combination with type 2 diabetes (T2D).Material and methods. The retrospective case-control study included 125 patients with myocardial infarction and T2D, 25 of whom died during the index hospitalization. The cellular composition of the blood and the level of high-sensitivity C-reactive protein (hsCRP) were determined on the first and third days of hospitalization. In the groups of deceased and surviving patients, cellular indices of systemic inflammation were calculated and compared (neutrophil-lymphocyte ratio (NLR), neutrophil-monocyte ratio (NMR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), systemic inflammation index (SII), systemic inflammation response index (SIRI)) and average hsCRP levels). The prognostic role of the studied parameters was assessed using univariate and multivariate logistic regression.Results. Deceased patients, compared with survived ones, had higher Killip class, body mass index, number of stents implanted, higher hsCRP levels, and lower left ventricular ejection fraction. Inhospital mortality was associated with hsCRP (odds ratio of 1,03 with 95% confidence interval of 1,003-1,05, p=0,029), NLR (2,56 [1,73-9,78], p&lt;0,001), NMR (1,16 [1,001-1,35], p=0,04), MLR (23,7 [3,1-182,6], p=0,002), SII (1,001 [1,0-1,001], p=0,028), SIRI (1,29 [1,09-1,52], p=0,003) 48 hours after admission, as well as with the degree of hsCRP change (1,03 [1,003-1,05], p=0,025), NLR (1,58 [1,21-2,06], p=0,001), SII (1,001 [1,0-1,001], p=0,028) during the first three days. Adjusted multivariate regression analysis identified a set of independent predictors with greatest accuracy in assessing the death probability: NLR, SII and SIRI 48 hours after admission, the degree of hsCRP change, body mass index and the num ber of implanted stents.Conclusion. The work demonstrated the significance of cellular indices of systemic inflammation (NLR, SII and SIRI) in assessing the prognosis of in-hospital mortality in patients with MI combined with T2D.

Epigenetic profiling of prostate cancer reveals potential prognostic signatures

PurposeWhile epigenetic profiling discovered biomarkers in several tumor entities, its application in prostate cancer is still limited. We explored DNA methylation-based deconvolution of benign and malignant prostate tissue for biomarker discovery and the potential of radiomics as a non-invasive surrogate.MethodsWe retrospectively included 30 patients (63 [58–79] years) with prostate cancer (PCa) who had a multiparametric MRI of the prostate before radical prostatectomy between 2014 and 2019. The control group comprised four patients with benign prostate tissue adjacent to the PCa lesions and four patients with benign prostatic hyperplasia. Tissue punches of all lesions were obtained. DNA methylation analysis and reference-free in silico deconvolution were conducted to retrieve Latent Methylation Components (LCMs). LCM-based clustering was analyzed for cellular composition and correlated with clinical disease parameters. Additionally, PCa and adjacent benign lesions were analyzed using radiomics to predict the epigenetic signatures non-invasively.ResultsLCMs identified two clusters with potential prognostic impact. Cluster one was associated with malignant prostate tissue (p < 0.001) and reduced immune-cell-related signatures (p = 0.004) of CD19 and CD4 cells. Cluster one comprised exclusively malignant prostate tissue enriched for significant prostate cancer and advanced tumor stages (p < 0.03 for both). No radiomics model could non-invasively predict the epigenetic clusters.ConclusionEpigenetic clusters were associated with prognostically and clinically relevant metrics in prostate cancer. Further, immune cell-related signatures differed significantly between prognostically favorable and unfavorable clusters. Further research is necessary to explore potential diagnostic and therapeutic implications.

Single-cell analysis reveals the implication of vascular endothelial cell-intrinsic ANGPT2 in human intracranial aneurysm.

While previous single-cell RNA sequencing (scRNA-seq) studies have attempted to dissect intracranial aneurysm (IA), the primary molecular mechanism for IA pathogenesis remains unknown. Here, we uncovered the alterations of cellular compositions, especially the transcriptome changes of vascular endothelial cells (ECs), in human IA. We performed scRNA-seq to compare the cell atlas of sporadic IA and the control artery. The transcriptomes of 43,462 cells were profiled for further analysis. In general, IA had increased immune cells (T/NK cells, B cells, myeloid cells, mast cells, neutrophils) and fewer vascular cells (ECs, vascular smooth muscle cells and fibroblasts). Based on the obtained high-quantity and high-quality EC data, we found genes associated with angiogenesis in ECs from IA patients. By EC-specific expression of candidate genes in vivo, we observed the involvement of angpt2a in causing cerebral vascular abnormality. Furthermore, an IA zebrafish model mimicking the main features of human IA was generated through targeting pdgfrb gene, and knockdown of angpt2a alleviated the vascular dilation in the IA zebrafish model. By performing a landscape view of the single-cell transcriptomes of IA and the control artery, we contribute to a deeper understanding of the cellular composition and the molecular changes of ECs in IA. The implication of angiogenic regulator ANGPT2 in IA formation and progression, provides a novel potential therapeutical target for IA interventions.

Brain Proteome Profiling Reveals Common and Divergent Signatures in Parkinson's Disease, Multiple System Atrophy, and Progressive Supranuclear Palsy.

The molecular pathogenesis of degenerative parkinsonisms, including Parkinson's disease (PD), progressive supranuclear palsy (PSP), and Multiple system atrophy (MSA), remains largely unknown. To gain novel insight into molecular processes associated with these diseases, we conducted a proteome-wide expression study in prefrontal cortex tissue from a cohort of 181 individuals, comprising PD (N = 73), PSP (N = 18), MSA (N = 17) and healthy control (N = 73). Using marker gene profiles, we first assess the cellular composition of the samples and, subsequently, identify distinct protein signatures for each disease, while correcting for cell composition. Our findings indicate that all three diseases are characterized by a structural and/or functional loss of deep cortical neurons, while PD exhibits an additional decrease in somatostatin-expressing interneurons, as well as in endothelial cells. Differential protein expression analysis identified multiple proteins and pathways with disease-specific expression, some of which have previously been associated with parkinsonism or neurodegeneration in general. Notably, we observed a strong mitochondrial signature which was present in both PD and PSP, albeit of a different composition and most pronounced in PSP, but not in MSA where immunological/inflammation-related pathways dominated. Additionally, we identified protein signatures associated with the severity of α-synuclein pathology in PD and showed that these are highly enriched in an upregulation of mitochondrial processes, specifically related to oxidative phosphorylation and in particular respiratory complexes I and IV. We identify multiple novel signatures of protein expression, associated with PD, PSP, and MSA, as well as with the severity of α-synuclein pathology in the PD brain.