Computational deconvolution of genome wide expression data from Parkinson's and Huntington's disease brain tissues using population-specific expression analysis

Physiology of malate dehydrogenase and how dysregulation leads to disease

Malate dehydrogenase (MDH) is pivotal in mammalian tissue metabolism, participating in various pathways beyond its classical roles and highlighting its adaptability to cellular demands. This enzyme is involved in maintaining redox balance, lipid synthesis, and glutamine metabolism and supports rapidly proliferating cells' energetic and biosynthetic needs. The involvement of MDH in glutamine metabolism underlines its significance in cell physiology. In contrast, its contribution to lipid metabolism highlights its role in essential biosynthetic processes necessary for cell maintenance and proliferation. The enzyme's regulatory mechanisms, such as post-translational modifications, underscore its complexity and importance in metabolic regulation, positioning MDH as a potential target in metabolic dysregulation. Furthermore, the association of MDH with various pathologies, including cancer and neurological disorders, suggests its involvement in disease progression. The overexpression of MDH isoforms MDH1 and MDH2 in cancers like breast, prostate, and pancreatic ductal adenocarcinoma, alongside structural modifications, implies their critical role in the metabolic adaptation of tumor cells. Additionally, mutations in MDH2 linked to pheochromocytomas, paragangliomas, and other metabolic diseases emphasize MDH's role in metabolic homeostasis. This review spotlights MDH's potential as a biomarker and therapeutic target, advocating for further research into its multifunctional roles and regulatory mechanisms in health and disease.

OLA-1, an Obg-like ATPase, integrates hunger with temperature information in sensory neurons in C. elegans

Animals detect changes in both their environment and their internal state and modify their behavior accordingly. Yet, it remains largely to be clarified how information of environment and internal state is integrated and how such integrated information modifies behavior. Well-fed C. elegans migrates to past cultivation temperature on a thermal gradient, which is disrupted when animals are starved. We recently reported that the neuronal activities synchronize between a thermosensory neuron AFD and an interneuron AIY, which is directly downstream of AFD, in well-fed animals, while this synchrony is disrupted in starved animals. However, it remained to be determined whether the disruption of the synchrony is derived from modulation of the transmitter release from AFD or from the modification of reception or signal transduction in AIY. By performing forward genetics on a transition of thermotaxis behavior along starvation, we revealed that OLA-1, an Obg-like ATPase, functions in AFD to promote disruption of AFD-AIY synchrony and behavioral transition. Our results suggest that the information of hunger is delivered to the AFD thermosensory neuron and gates transmitter release from AFD to disrupt thermotaxis, thereby shedding light onto a mechanism for the integration of environmental and internal state to modulate behavior.

MALAT1 lncRNA and Parkinson's Disease: The role in the Pathophysiology and Significance for Diagnostic and Therapeutic Approaches

Parkinson's disease (PD) is the second most common age-related neurodegenerative disorder. PD is characterized by progressive loss of dopamine-producing neurons in the substantia nigra (SN) region of brain tissue followed by the α-synuclein-based Lewy bodies' formation. These conditions are manifested by various motor and non-motor symptoms such as resting tremor, limb rigidity, bradykinesia and posture instability, cognitive impairment, sleep disorders, and emotional and memory dysfunctions. Long non-coding RNAs (lncRNAs) are closely related to protein-coding genes and are involved in various biological processes. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) lncRNA is involved in different pathways, including alternative splicing, transcriptional regulation, and post-transcriptional regulation, and also interacts with RNAs as a miRNA sponge. MALAT1 is highly expressed in brain tissues and several lines of evidence suggested it is probably involved in synapse generation and other neurophysiological pathways. This narrative review discussed all aspects of MALAT1-associated mechanisms involved in the PD pathogenesis, i.e., perturbed α-synuclein homeostasis, apoptosis and autophagy, and neuro-inflammation. Lastly, the possible applications of MALAT1 as a diagnostic biomarker and its importance to developing therapeutic strategies were highlighted. The literature search was conducted using neurodegeneration, neurodegenerative disorders, Parkinson's disease, lncRNA, and MALAT1 as search items in Google Scholar, Web of Knowledge, PubMed, and Scopus up to December 2021.

Revealing the Roles of MOAP1 in Diseases: A Review

Modulator of apoptosis protein1 (MOAP1), also known as MAP1 and PNMA4, belongs to the PNMA gene family consisting of at least 15 genes located on different chromosomes. MOAP1 interacts with the BAX protein, one of the most important apoptosis regulators. Due to its critical role in a few of disease-associated pathways, MOAP1 is associated with many diseases such as cancers and neurological diseases. In this study, we introduced MOAP1 and its biological functions and reviewed the associations between MOAP1 and a few diseases including cancers, neurological diseases, and other diseases such as inflammation and heart diseases. We also explained possible biological mechanisms underlying the associations between MOAP1 and these diseases, and discussed a few future directions regarding MOAP1, especially its potential roles in neurodegenerative disorders. In summary, MOAP1 plays a critical role in the development and progression of cancers and neurological diseases by regulating a few genes related to cellular apoptosis such as BAX and RASSF1A and interacting with disease-associated miRNAs, including miR-25 and miR1228.

Brain Microenvironment Heterogeneity: Potential Value for Brain Tumors

Uncovering the complexity of the microenvironment that emerges in brain disorders is key to identify potential vulnerabilities that might help challenging diseases affecting this organ. Recently, genomic and proteomic analyses, especially at the single cell level, have reported previously unrecognized diversity within brain cell types. The complexity of the brain microenvironment increases during disease partly due to the immune infiltration from the periphery that contributes to redefine the brain connectome by establishing a new crosstalk with resident brain cell types. Within the rewired brain ecosystem, glial cell subpopulations are emerging hubs modulating the dialogue between the Immune System and the Central Nervous System with important consequences in the progression of brain tumors and other disorders. Single cell technologies are crucial not only to define and track the origin of disease-associated cell types, but also to identify their molecular similarities and differences that might be linked to specific brain injuries. These altered molecular patterns derived from reprogramming the healthy brain into an injured organ, might provide a new generation of therapeutic targets to challenge highly prevalent and lethal brain disorders that remain incurable with unprecedented specificity and limited toxicities. In this perspective, we present the most relevant clinical and pre-clinical work regarding the characterization of the heterogeneity within different components of the microenvironment in the healthy and injured brain with a special interest on single cell analysis. Finally, we discuss how understanding the diversity of the brain microenvironment could be exploited for translational purposes, particularly in primary and secondary tumors affecting the brain.

Epigenetic inactivation of the autophagy-lysosomal system in appendix in Parkinson's disease

The gastrointestinal tract may be a site of origin for α-synuclein pathology in idiopathic Parkinson's disease (PD). Disruption of the autophagy-lysosome pathway (ALP) may contribute to α-synuclein aggregation. Here we examined epigenetic alterations in the ALP in the appendix by deep sequencing DNA methylation at 521 ALP genes. We identified aberrant methylation at 928 cytosines affecting 326 ALP genes in the appendix of individuals with PD and widespread hypermethylation that is also seen in the brain of individuals with PD. In mice, we find that DNA methylation changes at ALP genes induced by chronic gut inflammation are greatly exacerbated by α-synuclein pathology. DNA methylation changes at ALP genes induced by synucleinopathy are associated with the ALP abnormalities observed in the appendix of individuals with PD specifically involving lysosomal genes. Our work identifies epigenetic dysregulation of the ALP which may suggest a potential mechanism for accumulation of α-synuclein pathology in idiopathic PD.

Unraveling Targetable Systemic and Cell-Type-Specific Molecular Phenotypes of Alzheimer's and Parkinson's Brains With Digital Cytometry

Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most common neurodegenerative disorders worldwide, with age being their major risk factor. The increasing worldwide life expectancy, together with the scarcity of available treatment choices, makes it thus pressing to find the molecular basis of AD and PD so that the causing mechanisms can be targeted. To study these mechanisms, gene expression profiles have been compared between diseased and control brain tissues. However, this approach is limited by mRNA expression profiles derived for brain tissues highly reflecting their degeneration in cellular composition but not necessarily disease-related molecular states. We therefore propose to account for cell type composition when comparing transcriptomes of healthy and diseased brain samples, so that the loss of neurons can be decoupled from pathology-associated molecular effects. This approach allowed us to identify genes and pathways putatively altered systemically and in a cell-type-dependent manner in AD and PD brains. Moreover, using chemical perturbagen data, we computationally identified candidate small molecules for specifically targeting the profiled AD/PD-associated molecular alterations. Our approach therefore not only brings new insights into the disease-specific and common molecular etiologies of AD and PD but also, in these realms, foster the discovery of more specific targets for functional and therapeutic exploration.

Role of Long Noncoding RNAs in Parkinson's Disease: Putative Biomarkers and Therapeutic Targets

Parkinson's disease (PD) is a neurodegenerative disease characterized by bradykinesia, rigidity, and tremor. Age is the main risk factor. Long noncoding RNAs (lncRNAs) are novel RNA molecules of more than 200 nucleotides in length. They may be involved in the regulation of many pathological processes of PD. PD has a variety of pathophysiological mechanisms, including alpha-synuclein aggregate, mitochondrial dysfunction, oxidative stress, calcium homeostasis, axonal transport, and neuroinflammation. Among these, the impacts of lncRNAs on the pathogenesis and progression of PD need to be highlighted. lncRNAs may serve as putative biomarkers and therapeutic targets for the early diagnosis of PD. This study aimed to investigate the role of lncRNAs in various pathological processes of PD and the specific lncRNAs that might be used as putative diagnostic biomarkers and therapeutic targets of PD.

Common gene expression signatures in Parkinson's disease are driven by changes in cell composition

The etiology of Parkinson’s disease is largely unknown. Genome-wide transcriptomic studies in bulk brain tissue have identified several molecular signatures associated with the disease. While these studies have the potential to shed light into the pathogenesis of Parkinson’s disease, they are also limited by two major confounders: RNA post-mortem degradation and heterogeneous cell type composition of bulk tissue samples. We performed RNA sequencing following ribosomal RNA depletion in the prefrontal cortex of 49 individuals from two independent case-control cohorts. Using cell type specific markers, we estimated the cell type composition for each sample and included this in our analysis models to compensate for the variation in cell type proportions. Ribosomal RNA depletion followed by capture by random primers resulted in substantially more even transcript coverage, compared to poly(A) capture, in post-mortem tissue. Moreover, we show that cell type composition is a major confounder of differential gene expression analysis in the Parkinson’s disease brain. Accounting for cell type proportions attenuated numerous transcriptomic signatures that have been previously associated with Parkinson’s disease, including vesicle trafficking, synaptic transmission, immune and mitochondrial function. Conversely, pathways related to endoplasmic reticulum, lipid oxidation and unfolded protein response were strengthened and surface as the top differential gene expression signatures in the Parkinson’s disease prefrontal cortex. Our results indicate that differential gene expression signatures in Parkinson’s disease bulk brain tissue are significantly confounded by underlying differences in cell type composition. Modeling cell type heterogeneity is crucial in order to unveil transcriptomic signatures that represent regulatory changes in the Parkinson’s disease brain and are, therefore, more likely to be associated with underlying disease mechanisms.

Inference of cell type content from human brain transcriptomic datasets illuminates the effects of age, manner of death, dissection, and psychiatric diagnosis

Psychiatric illness is unlikely to arise from pathology occurring uniformly across all cell types in affected brain regions. Despite this, transcriptomic analyses of the human brain have typically been conducted using macro-dissected tissue due to the difficulty of performing single-cell type analyses with donated post-mortem brains. To address this issue statistically, we compiled a database of several thousand transcripts that were specifically-enriched in one of 10 primary cortical cell types in previous publications. Using this database, we predicted the relative cell type content for 833 human cortical samples using microarray or RNA-Seq data from the Pritzker Consortium (GSE92538) or publicly-available databases (GSE53987, GSE21935, GSE21138, CommonMind Consortium). These predictions were generated by averaging normalized expression levels across transcripts specific to each cell type using our R-package BrainInABlender (validated and publicly-released on github). Using this method, we found that the principal components of variation in the datasets strongly correlated with the predicted neuronal/glial content of the samples. This variability was not simply due to dissection–the relative balance of brain cell types appeared to be influenced by a variety of demographic, pre- and post-mortem variables. Prolonged hypoxia around the time of death predicted increased astrocytic and endothelial gene expression, illustrating vascular upregulation. Aging was associated with decreased neuronal gene expression. Red blood cell gene expression was reduced in individuals who died following systemic blood loss. Subjects with Major Depressive Disorder had decreased astrocytic gene expression, mirroring previous morphometric observations. Subjects with Schizophrenia had reduced red blood cell gene expression, resembling the hypofrontality detected in fMRI experiments. Finally, in datasets containing samples with especially variable cell content, we found that controlling for predicted sample cell content while evaluating differential expression improved the detection of previously-identified psychiatric effects. We conclude that accounting for cell type can greatly improve the interpretability of transcriptomic data.

Deconvolution of expression microarray data reveals 131I-induced responses otherwise undetected in thyroid tissue

High-throughput gene expression analysis is increasingly used in radiation research for discovery of damage-related or absorbed dose-dependent biomarkers. In tissue samples, cell type-specific responses can be masked in expression data due to mixed cell populations which can preclude biomarker discovery. In this study, we deconvolved microarray data from thyroid tissue in order to assess possible bias from mixed cell type data. Transcript expression data [GSE66303] from mouse thyroid that received 5.9 Gy from ¹³¹I over 24 h (or 0 Gy from mock treatment) were deconvolved by cell frequency of follicular cells and C-cells using csSAM and R and processed with Nexus Expression. Literature-based signature genes were used to assess the relative impact from ionizing radiation (IR) or thyroid hormones (TH). Regulation of cellular functions was inferred by enriched biological processes according to Gene Ontology terms. We found that deconvolution increased the detection rate of significantly regulated transcripts including the biomarker candidate family of kallikrein transcripts. Detection of IR-associated and TH-responding signature genes was also increased in deconvolved data, while the dominating trend of TH-responding genes was reproduced. Importantly, responses in biological processes for DNA integrity, gene expression integrity, and cellular stress were not detected in convoluted data–which was in disagreement with expected dose-response relationships–but upon deconvolution in follicular cells and C-cells. In conclusion, previously reported trends of ¹³¹I-induced transcriptional responses in thyroid were reproduced with deconvolved data and usually with a higher detection rate. Deconvolution also resolved an issue with detecting damage and stress responses in enriched data, and may reduce false negatives in other contexts as well. These findings indicate that deconvolution can optimize microarray data analysis of heterogeneous sample material for biomarker screening or other clinical applications.

Evidence for a Pan-Neurodegenerative Disease Response in Huntington's and Parkinson's Disease Expression Profiles

Huntington's and Parkinson's Diseases (HD and PD) are neurodegenerative disorders that share some pathological features but are disparate in others. For example, while both diseases are marked by aberrant protein aggregation in the brain, the specific proteins that aggregate and types of neurons affected differ. A better understanding of the molecular similarities and differences between these two diseases may lead to a more complete mechanistic picture of both the individual diseases and the neurodegenerative process in general. We sought to characterize the common transcriptional signature of HD and PD as well as genes uniquely implicated in each of these diseases using mRNA-Seq data from post mortem human brains in comparison to neuropathologically normal controls. The enriched biological pathways implicated by HD differentially expressed genes show remarkable consistency with those for PD differentially expressed genes and implicate the common biological processes of neuroinflammation, apoptosis, transcriptional dysregulation, and neuron-associated functions. Comparison of the differentially expressed (DE) genes highlights a set of consistently altered genes that span both diseases. In particular, processes involving nuclear factor kappa-light-chain-enhancer of activated B cells (NFkB) and transcription factor cAMP response element-binding protein (CREB) are the most prominent among the genes common to HD and PD. When the combined HD and PD data are compared to controls, relatively few additional biological processes emerge as significantly enriched, suggesting that most pathways are independently seen within each disorder. Despite showing comparable numbers of DE genes, DE genes unique to HD are enriched in far more coherent biological processes than the DE genes unique to PD, suggesting that PD may represent a more heterogeneous disorder. The complexity of the biological processes implicated by this analysis provides impetus for the development of better experimental models to validate the results.

Integrated transcriptional analysis unveils the dynamics of cellular differentiation in the developing mouse hippocampus

The ability to assign expression patterns to the individual cell types that constitute a tissue is a major challenge. This especially applies to brain, given its plethora of different, functionally interconnected cell types. Here, we derived cell type-specific transcriptome signatures from existing single cell RNA data and integrated these signatures with a newly generated dataset of expression (bulk RNA-Seq) of the postnatal developing mouse hippocampus. This integrated analysis allowed us to provide a comprehensive and unbiased prediction of the differentiation drivers for 11 different hippocampal cell types and describe how the different cell types interact to support crucial developmental stages. Our results provide a reliable resource of predicted differentiation drivers and insights into the multifaceted aspects of the cells in hippocampus during development.

An environment-dependent transcriptional network specifies human microglia identity

Microglia play essential roles in central nervous system (CNS) homeostasis and influence diverse aspects of neuronal function. However, the transcriptional mechanisms that specify human microglia phenotypes are largely unknown. We examined the transcriptomes and epigenetic landscapes of human microglia isolated from surgically resected brain tissue ex vivo and after transition to an in vitro environment. Transfer to a tissue culture environment resulted in rapid and extensive down-regulation of microglia-specific genes that were induced in primitive mouse macrophages after migration into the fetal brain. Substantial subsets of these genes exhibited altered expression in neurodegenerative and behavioral diseases and were associated with noncoding risk variants. These findings reveal an environment-dependent transcriptional network specifying microglia-specific programs of gene expression and facilitate efforts to understand the roles of microglia in human brain diseases.

MicroRNAs in Parkinson's disease

Parkinson's disease is the second most common neurodegenerative disease commonly affecting the older population. Loss of dopaminergic neurons in the substantia nigra of brain leads to impairment of motor activities as well as cognitive defects. There are many underlying causes to this disease, both genetic and epigenetic, which are yet to be fully explored. Non-coding RNAs are significant part of our genome and are involved in various cellular processes. MicroRNAs, which are small non-coding RNAs having 20-22 nucleotides, are involved in many underlying mechanisms of pathogenesis of several neurodegenerative diseases including Parkinson's. This review focuses on the role played by microRNAs in regulating various genes responsible for the onset and pathogenesis of Parkinson's disease and various literature evidences pointing at the usefulness of targeting specific microRNAs as a potential alternate therapeutic strategy for successful impairment of the disease progression. This review also discusses about various biofluid-based microRNA markers which may be potentially utilized for diagnostic purposes.

Transcriptomic Profiling of Extracellular RNAs Present in Cerebrospinal Fluid Identifies Differentially Expressed Transcripts in Parkinson's Disease

Background: Parkinson’s disease (PD) is a debilitating neurological disorder for which prognostic and diagnostic biomarkers are lacking. Cerebrospinal fluid (CSF) is an accessible body fluid that comes into direct contact with the central nervous system (CNS) and acts as a nuclease-free repository where RNA transcripts shed by brain tissues can reside for extended periods of time.

Objective: We studied the RNA species present in the CSF of PD patients to identify novel diagnostic biomarkers.

Methods: Small volumes of CSF from 27 PD patients and 30 healthy age- and sex-matched controls were used for RNA extraction followed by next-generation sequencing (RNA-seq) using the Illumina platform. CSF contains a number of fragmented RNA species that were individually sequenced and analyzed. Comparing PD to control subjects, we observed a pool of dysregulated sequencing tags that were further analyzed and validated by quantitative real-time PCR (qRT-PCR).

Results: A total of 201 differentially expressed sequencing tags (DETs), including 92 up-regulated and 109 down-regulated DETs were identified. We validated the following DETs by real time PCR in the patient samples: Dnmt1, Ezh2, CCR3, SSTR5,PTPRC, UBC, NDUFV2, BMP7, SCN9, SCN9 antisense (AC010127.3), and long noncoding RNAs AC079630 and UC001lva.4 (close to the LRRK2 gene locus), as potential PD biomarkers.

Conclusions: The CSF is a unique environment that contains many species of RNA. Our work demonstrates that CSF can potentially be used to identify biomarkers for the detection and tracking of disease progression and evaluation of therapeutic outcomes.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Identification of Vulnerable Cell Types in Major Brain Disorders Using Single Cell Transcriptomes and Expression Weighted Cell Type Enrichment

The cell types that trigger the primary pathology in many brain diseases remain largely unknown. One route to understanding the primary pathological cell type for a particular disease is to identify the cells expressing susceptibility genes. Although this is straightforward for monogenic conditions where the causative mutation may alter expression of a cell type specific marker, methods are required for the common polygenic disorders. We developed the Expression Weighted Cell Type Enrichment (EWCE) method that uses single cell transcriptomes to generate the probability distribution associated with a gene list having an average level of expression within a cell type. Following validation, we applied EWCE to human genetic data from cases of epilepsy, Schizophrenia, Autism, Intellectual Disability, Alzheimer's disease, Multiple Sclerosis and anxiety disorders. Genetic susceptibility primarily affected microglia in Alzheimer's and Multiple Sclerosis; was shared between interneurons and pyramidal neurons in Autism and Schizophrenia; while intellectual disabilities and epilepsy were attributable to a range of cell-types, with the strongest enrichment in interneurons. We hypothesized that the primary cell type pathology could trigger secondary changes in other cell types and these could be detected by applying EWCE to transcriptome data from diseased tissue. In Autism, Schizophrenia and Alzheimer's disease we find evidence of pathological changes in all of the major brain cell types. These findings give novel insight into the cellular origins and progression in common brain disorders. The methods can be applied to any tissue and disorder and have applications in validating mouse models.

Beyond the redox imbalance: Oxidative stress contributes to an impaired GLUT3 modulation in Huntington's disease

Failure in energy metabolism and oxidative damage are associated with Huntington's disease (HD). Ascorbic acid released during synaptic activity inhibits use of neuronal glucose, favouring lactate uptake to sustain brain activity. Here, we observe a decreased expression of GLUT3 in STHdhQ111 cells (HD cells) and R6/2 mice (HD mice). Localisation of GLUT3 is decreased at the plasma membrane in HD cells affecting the modulation of glucose uptake by ascorbic acid. An ascorbic acid analogue without antioxidant activity is able to inhibit glucose uptake in HD cells. The impaired modulation of glucose uptake by ascorbic acid is directly related to ROS levels indicating that oxidative stress sequesters the ability of ascorbic acid to modulate glucose utilisation. Therefore, in HD, a decrease in GLUT3 localisation at the plasma membrane would contribute to an altered neuronal glucose uptake during resting periods while redox imbalance should contribute to metabolic failure during synaptic activity.

Proteotoxicity and cardiac dysfunction

Baseline physiological function of the mammalian heart is under the constant threat of environmental or intrinsic pathological insults. Cardiomyocyte proteins are thus subject to unremitting pressure to function optimally, and this depends on them assuming and maintaining proper conformation. This review explores the multiple defenses a cell may use for its proteins to assume and maintain correct protein folding and conformation. There are multiple quality control mechanisms to ensure that nascent polypeptides are properly folded and mature proteins maintain their functional conformation. When proteins do misfold, either in the face of normal or pathological stimuli or because of intrinsic mutations or post-translational modifications, they must either be refolded correctly or recycled. In the absence of these corrective processes, they may become toxic to the cell. Herein, we explore some of the underlying mechanisms that lead to proteotoxicity. The continued presence and chronic accumulation of misfolded or unfolded proteins can be disastrous in cardiomyocytes because these misfolded proteins can lead to aggregation or the formation of soluble peptides that are proteotoxic. This in turn leads to compromised protein quality control and precipitating a downward spiral of the cell's ability to maintain protein homeostasis. Some underlying mechanisms are discussed and the therapeutic potential of interfering with proteotoxicity in the heart is explored.