Development Of Molecular Biomarkers Research Articles

Genetic characterization of tetracycline-resistant Staphylococcus aureus with reduced vancomycin susceptibility using whole-genome sequencing.

This study aimed to analyze the genetic characteristics of Staphylococcus aureus with reduced vancomycin susceptibility (RVS-SA). Whole-genome sequencing was performed on 27 RVS-SA clinical isolates, and comparative genomic analysis was performed using S. aureus reference strains. Pan-genome orthologous groups (POGs) were identified that were present in RVS-SA but absent in the reference strains, but further analysis showed that the presence of these POGs was influenced by tetracycline resistance rather than vancomycin resistance. Therefore, we restricted our analysis to tetracycline-resistant (tetR) RVS-SA and tetR vancomycin-susceptible S. aureus (VSSA). Phylogenomic analysis showed them to be closely related, and further analysis revealed the presence of an uncharacterized protein SAB0394 and the absence of lytA in tetR RVS-SA, which are involved in cell wall thickening. In summary, using whole-genome sequencing we identified gain or loss of genes in tetR RVS-SA strains. These findings provide insights into the investigation of mechanisms associated with reduced vancomycin susceptibility and have the potential to contribute to the development of molecular biomarkers for the rapid and efficient detection of RVS-SA.

Variability in the Clinical Effects of the Omega-3 Polyunsaturated Fatty Acids DHA and EPA in Cardiovascular Disease-Possible Causes and Future Considerations.

Cardiovascular disease (CVD) that includes myocardial infarction and stroke, is the leading cause of mortality worldwide. Atherosclerosis, the primary underlying cause of CVD, can be controlled by pharmacological and dietary interventions, including n-3 polyunsaturated fatty acid (PUFA) supplementation. n-3 PUFA supplementation, primarily consisting of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), has shown promise in reducing atherosclerosis by modulating risk factors, including triglyceride levels and vascular inflammation. n-3 PUFAs act by replacing pro-inflammatory fatty acid types in cell membranes and plasma lipids, by regulating transcription factor activity, and by inducing epigenetic changes. EPA and DHA regulate cellular function through shared and differential molecular mechanisms. Large clinical studies on n-3 PUFAs have reported conflicting findings, causing confusion among the public and health professionals. In this review, we discuss important factors leading to these inconsistencies, in the context of atherosclerosis, including clinical study design and the differential effects of EPA and DHA on cell function. We propose steps to improve clinical and basic experimental study design in order to improve supplement composition optimization. Finally, we propose that understanding the factors underlying the poor response to n-3 PUFAs, and the development of molecular biomarkers for predicting response may help towards a more personalized treatment.

Microbial biomarkers of tree water status for next-generation biomonitoring of forest ecosystems.

Next-generation biomonitoring proposes to combine machine-learning algorithms with environmental DNA data to automate the monitoring of the Earth's major ecosystems. In the present study, we searched for molecular biomarkers of tree water status to develop next-generation biomonitoring of forest ecosystems. Because phyllosphere microbial communities respond to both tree physiology and climate change, we investigated whether environmental DNA data from tree phyllosphere could be used as molecular biomarkers of tree water status in forest ecosystems. Using an amplicon sequencing approach, we analysed phyllosphere microbial communities of four tree species (Quercus ilex, Quercus robur, Pinus pinaster and Betula pendula) in a forest experiment composed of irrigated and non-irrigated plots. We used these microbial community data to train a machine-learning algorithm (Random Forest) to classify irrigated and non-irrigated trees. The Random Forest algorithm detected tree water status from phyllosphere microbial community composition with more than 90% accuracy for oak species, and more than 75% for pine and birch. Phyllosphere fungal communities were more informative than phyllosphere bacterial communities in all tree species. Seven fungal amplicon sequence variants were identified as candidates for the development of molecular biomarkers of water status in oak trees. Altogether, our results show that microbial community data from tree phyllosphere provides information on tree water status in forest ecosystems and could be included in next-generation biomonitoring programmes that would use in situ, real-time sequencing of environmental DNA to help monitor the health of European temperate forest ecosystems.

Current and emerging tissue‐based molecular biomarkers for prostate cancer management: A narrative review

AbstractProstate cancer is a heterogeneous disease process with a wide spectrum of clinicopathologic variables that impact diagnosis, risk stratification, and management. To improve diagnostic accuracy and to better inform clinical decision making, the development of molecular biomarkers has undergone considerable discovery and clinical validation in the past decade. Prostate cancer is no longer seen as a single disease entity but one with considerable heterogeneity existing between tumors and between patients. Biomarkers now allow for more personalized and precision‐based approaches to management that otherwise would have depended on applying clinical algorithms alone. The aim of this review is to discuss and evaluate prostate cancer tissue‐based biomarkers that have been developed to aid diagnosis, improve risk stratification, and management.

Integration of small RNAs from plasma and cerebrospinal fluid for classification of multiple sclerosis.

Multiple Sclerosis (MS) is an autoimmune, neurological disease, commonly presenting with a relapsing-remitting form, that later converts to a secondary progressive stage, referred to as RRMS and SPMS, respectively. Early treatment slows disease progression, hence, accurate and early diagnosis is crucial. Recent advances in large-scale data processing and analysis have progressed molecular biomarker development. Here, we focus on small RNA data derived from cell-free cerebrospinal fluid (CSF), cerebrospinal fluid cells, plasma and peripheral blood mononuclear cells as well as CSF cell methylome data, from people with RRMS (n = 20), clinically/radiologically isolated syndrome (CIS/RIS, n = 2) and neurological disease controls (n = 14). We applied multiple co-inertia analysis (MCIA), an unsupervised and thereby unbiased, multivariate method for simultaneous data integration and found that the top latent variable classifies RRMS status with an Area Under the Receiver Operating Characteristics (AUROC) score of 0.82. Variable selection based on Lasso regression reduced features to 44, derived from the small RNAs from plasma (20), CSF cells (8) and cell-free CSF (16), with a marginal reduction in AUROC to 0.79. Samples from SPMS patients (n = 6) were subsequently projected on the latent space and differed significantly from RRMS and controls. On contrary, we found no differences between relapse and remission or between inflammatory and non-inflammatory disease controls, suggesting that the latent variable is not prone to inflammatory signals alone, but could be MS-specific. Hence, we here showcase that integration of small RNAs from plasma and CSF can be utilized to distinguish RRMS from SPMS and neurological disease controls.

Development of Advanced Imaging and Molecular Imaging for Barrett's Neoplasia.

Barrett esophagus (BE) is a precursor to a life-threatening esophageal adenocarcinoma (EAC). Surveillance endoscopy with random biopsies is recommended for early intervention against EAC, but its adherence in the clinical setting is poor. Dysplastic lesions with flat architecture and patchy distribution in BE are hardly detected by high-resolution endoscopy, and the surveillance protocol entails issues of time and labor and suboptimal interobserver agreement for diagnosing dysplasia. Therefore, the development of advanced imaging technologies is necessary for Barrett’s surveillance. Recently, non-endoscopic or endoscopic technologies, such as cytosponge, endocytoscopy, confocal laser endomicroscopy, autofluorescence imaging, and optical coherence tomography/volumetric laser endomicroscopy, were developed, but most of them are not clinically available due to the limited view field, expense of the equipment, and significant time for the learning curve. Another strategy is focused on the development of molecular biomarkers, which are also not ready to use. However, a combination of advanced imaging techniques together with specific biomarkers is expected to identify morphological abnormalities and biological disorders at an early stage in the surveillance. Here, we review recent developments in advanced imaging and molecular imaging for Barrett’s neoplasia. Further developments in multiple biomarker panels specific for Barrett’s HGD/EAC include wide-field imaging systems for targeting ‘red flags’, a high-resolution imaging system for optical biopsy, and a computer-aided diagnosis system with artificial intelligence, all of which enable a real-time and accurate diagnosis of dysplastic BE in Barrett’s surveillance and provide information for precision medicine.

Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder

BackgroundAutism spectrum disorder (ASD) is a neurodevelopmental condition with hallmark behavioral manifestations including impaired social communication and restricted repetitive behavior. In addition, many affected individuals display metabolic imbalances, immune dysregulation, gastrointestinal dysfunction, and altered gut microbiome compositions. MethodsWe sought to better understand nonbehavioral features of ASD by determining molecular signatures in peripheral tissues through mass spectrometry methods (ultrahigh performance liquid chromatography–tandem mass spectrometry) with broad panels of identified metabolites. Herein, we compared the global metabolome of 231 plasma and 97 fecal samples from a large cohort of children with ASD and typically developing control children. ResultsDifferences in amino acid, lipid, and xenobiotic metabolism distinguished ASD and typically developing samples. Our results implicated oxidative stress and mitochondrial dysfunction, hormone level elevations, lipid profile changes, and altered levels of phenolic microbial metabolites. We also revealed correlations between specific metabolite profiles and clinical behavior scores. Furthermore, a summary of metabolites modestly associated with gastrointestinal dysfunction in ASD is provided, and a pilot study of metabolites that can be transferred via fecal microbial transplant into mice is identified. ConclusionsThese findings support a connection between metabolism, gastrointestinal physiology, and complex behavioral traits and may advance discovery and development of molecular biomarkers for ASD.

Renal Cell and Urothelial Carcinoma: Biomarkers for New Treatments.

Therapies for genitourinary malignancies have evolved considerably in the past five years. Combination treatment targeting biologically relevant immune and angiogenic pathways is improving patient survival in metastatic renal cell carcinoma (RCC), whereas immune checkpoint blockade (ICB), novel targeted therapy, and antibody drug conjugates have changed the landscape of urothelial cancer (UC) treatment. A daily challenge for clinicians is identifying patients who derive a preferential benefit from the available therapeutic options. The completion of large-scale genomics projects has yielded comprehensive descriptions of the molecular heterogeneity present in RCC and UC, although clinical applications of these data continue to evolve. Major molecular subtypes of RCC align well with histology subtype, and although some molecular characteristics appear to carry prognostic information, biomarkers predicting benefit from tyrosine kinase inhibitor (TKI) or immunotherapy are generally lacking. Unexpectedly, similar work has demonstrated that UC can be grouped into "molecular subtypes" that share properties with those found in breast cancer and other solid tumors. Furthermore, this molecular subtype classification is prognostic and potentially predictive of differential benefit from conventional and targeted therapies. This article provides an update on the current state of molecular biomarker development and potential clinical utility in RCC and UC.

НОВЫЙ ВЗГЛЯД НА МОЛЕКУЛЯРНО-ГЕНЕТИЧЕСКИЕ АСПЕКТЫ ПРОКСИМАЛЬНЫХ СПИНАЛЬНЫХ МЫШЕЧНЫХ АТРОФИЙ У ДЕТЕЙ (ОБЗОР И СОБСТВЕННЫЕ НАБЛЮДЕНИЯ)

Спинальная мышечная атрофия – это прогрессирующее генетическое нейромышечное заболевание, приводящее к инвалидизации. Значительные достижения в области молекулярно-генетических исследований при этой патологии позволили расширить понимание патогенетических механизмов, включая определение модифицирующих факторов, оказывающих влияние на тяжесть течения и диверсификацию заболевания. Разработка молекулярных биомаркеров является многообещающим для СМА в контексте поиска эффективной патогенетической терапии. Однако впереди еще долгий путь. Учитывая сложность и многогранность заболевания, путь вперед будет достаточно сложной задачей. Тем не менее, учитывая определенные достижения в области генной терапии в целом, есть основания для осторожного оптимизма.

A meta-analysis of the accuracy of a neuroendocrine tumor mRNA biomarker (NETest) in the blood.

606 Background: There is no accurate blood biomarker of neuroendocrine tumor (NET) disease. The inability to effectively assess disease in real-time has hindered management. The advance of genomic medicine and the development of molecular biomarkers has provided a strategy – liquid biopsy – to facilitate management. We reviewed the role of a blood mRNA-based NET biomarker, the NETest, as an in vitro diagnostic (IVD) to assess clinical utility. Methods: A systematic review of the literature using PRISMA guidelines was undertaken. The methodological quality was evaluated using the QUADAS-2 tool. We identified 10 original scientific papers, which met inclusion criteria. These were assessed by qualitative analysis, and thereafter meta-analysis. Data were pooled and median (95% CI) diagnostic odds ratio (DOR), positive likelihood ratio (+LR) and negative likelihood ratio (–LR) calculated. For the meta-analysis, a generic inverse variance method was undertaken using the accuracy and AUC data. Results: The ten studies exhibited moderate to high methodological quality. They evaluated NETest usage both as a diagnostic and as a monitoring tool. Meta-analysis identified the diagnostic accuracy of the NETest to be 94.9-96% with a median DOR of 400, +LR of 164 and–LR of 0.05. The NETest was 85.5-86% accurate in differentiating stable from progressive disease. As a marker of natural history, the accuracy was 90-94%. As an interventional/ response biomarker, the accuracy was 94-97%. The pooled AUC for the NETest was 0.954±0.005, with a z-statistic of 175.06 ( p< 0.001). Conclusions: The NETest is an accurate biomarker suitable for clinical use in NET disease management. The meta-analysis supports the utility of the NETest as an IVD to establish a diagnosis and monitor therapeutic efficacy. The use of a multianalyte genomic test as a biomarker provides information relevant to NET management consistent with observations regarding the utility of liquid biopsy in other oncological disciplines.

Novel biomarkers for the diagnosis and prognosis of colorectal cancer.

Colorectal cancer (CRC) is among the most common malignancies and remains a major cause of cancer-related death worldwide. Despite recent advances in surgical and multimodal therapies, the overall survival of advanced CRC patients remains very low. Cancer progression, including invasion and metastasis, is a major cause of death among CRC patients. The underlying mechanisms of action resulting in cancer progression are beginning to unravel. The reported molecular and biochemical mechanisms that might contribute to the phenotypic changes in favor of carcinogenesis include apoptosis inhibition, enhanced tumor cell proliferation, increased invasiveness, cell adhesion perturbations, angiogenesis promotion, and immune surveillance inhibition. These events may contribute to the development and progression of cancer. A biomarker is a molecule that can be detected in tissue, blood, or stool samples to allow the identification of pathological conditions such as cancer. Thus, it would be beneficial to identify reliable and practical molecular biomarkers that aid in the diagnostic and therapeutic processes of CRC. Recent research has targeted the development of biomarkers that aid in the early diagnosis and prognostic stratification of CRC. Despite that, the identification of diagnostic, prognostic, and/or predictive biomarkers remains challenging, and previously identified biomarkers might be insufficient to be clinically applicable or offer high patient acceptability. Here, we discuss recent advances in the development of molecular biomarkers for their potential usefulness in early and less-invasive diagnosis, treatment, and follow-up of CRC.

Molecular tools for coral reef restoration: Beyond biomarker discovery

AbstractAs coral reefs continue to decline due to climate change and other stressors, scientists have proposed adopting genomic tools, such as biomarkers, to aid in the conservation and restoration of these threatened ecosystems. Biomarkers are easily measured indicators of biological processes that can be used to predict or diagnose health, resilience, and other key performance metrics. The ultimate goal of developing biomarkers is to determine the conservation value and utility of a given coral colony, including the host animal, its algal symbionts, and their microbial partners. However, this goal remains distant because most efforts have not yet moved beyond the initial discovery phase. We review recent progress in the development of coral molecular biomarkers from a practical standpoint and consider the many challenges that remain as roadblocks to large‐scale implementation. We caution practitioners that, while biomarkers are a promising technology, they are unlikely to be available for field application in the near future barring a rapid shift in research focus from discovery to subsequent validation and field trials. To facilitate such a shift, we propose a stepwise framework to guide additional study in this area, with the aim of accelerating practical molecular biomarker development to enhance coral restoration practice.

The construction and analysis of gene co-expression network of differentially expressed genes identifies potential biomarkers in thyroid cancer

Background: The incidence and mortality of thyroid cancer has been increasing steadily in the United States. However, the molecular pathogenesis of thyroid cancer is not fully characterized. Methods: The R package of DESeq2 was applied to detect differentially expressed genes (DEGs) between 57 paired thyroid cancer and noncancerous tissues using RNA sequencing data from The Cancer Genome Atlas database. Weighted gene co-expression network analysis was used to construct co-expression modules and study the relationship between co-expression modules and clinical traits. Gene ontology (GO) enrichment analysis was performed on these genes from interested co-expression modules. Results: A cohort of 750 up-regulated and 296 down-regulated genes were identified in thyroid cancer. The weighted gene co-expression network analysis identified 5 gene co-expression modules. Two modules were significantly associated with patients’ age, cancer stage and multifocality. SERPINA1 and MRO were their hub genes respectively. Conclusions: The bioinformatics study for those co-expression modules and hub genes paves the way for the development of molecular biomarkers in thyroid cancer.

Differential protein expression of hippocampal cells associated with heavy metals (Pb, As, and MeHg) neurotoxicity: Deepening into the molecular mechanism of neurodegenerative diseases

Chronic exposure to heavy metals such as Pb, As, and MeHg can be associated with an increased risk of developing neurodegenerative diseases. Our in vitro bioassays results showed the potency of heavy metals in the order of Pb < As < MeHg on hippocampal cells. The main objective of this study was combining in vitro label free proteomics and systems biology approach for elucidating patterns of biological response, discovering underlying mechanisms of Pb, As, and MeHg toxicity in hippocampal cells. The omics data was refined by using different filters and normalization and multilevel analysis tools were employed to explore the data visualization. The functional and pathway visualization was performed by using Gene ontology and PathVisio tools. Using these all integrated approaches, we identified significant proteins across treatments within the mitochondrial dysfunction, oxidative stress, ubiquitin proteome dysfunction, and mRNA splicing related to neurodegenerative diseases. The systems biology analysis revealed significant alterations in proteins implicated in Parkinson's disease (PD) and Alzheimer's disease (AD). The current proteomics analysis of three metals support the insight into the proteins involved in neurodegeneration and the altered proteins can be useful for metal-specific biomarkers of exposure and its adverse effects. SignificanceThe proteomics techniques have been claimed to be more sensitive than the conventional toxicological assays, facilitating the measurement of responses to heavy metals (Pb, As, and MeHg) exposure before obvious harm has occurred demonstrating their predictive value. Also, proteomics allows for the comparison of responses between Pb, As, and MeHg metals, permitting the evaluation of potency differences hippocampal cells of the brain. Hereby, the molecular information provided by pathway and gene functional analysis can be used to develop a more thorough understanding of each metal mechanism at the protein level for different neurological adverse outcomes (e.g. Parkinson's disease, Alzheimer's diseases). Efforts are put into developing proteomics based toxicity testing methods using in vitro models for improving human risk assessment. Some of the key proteins identified can also potentially be used as biomarkers in epidemiologic studies. These heavy metal response patterns shed new light on the mechanisms of mRNA splicing, ubiquitin pathway role in neurodegeneration, and can be useful for the development of molecular biomarkers of heavy metals exposure.

Protein Biomarkers for Early Detection of Pancreatic Ductal Adenocarcinoma: Progress and Challenges.

Approximately 75% of patients with pancreatic ductal adenocarcinoma are diagnosed with advanced cancer, which cannot be safely resected. The most commonly used biomarker CA19-9 has inadequate sensitivity and specificity for early detection, which we define as Stage I/II cancers. Therefore, progress in next-generation biomarkers is greatly needed. Recent reports have validated a number of biomarkers, including combination assays of proteins and DNA mutations; however, the history of translating promising biomarkers to clinical utility suggests that several major hurdles require careful consideration by the medical community. The first set of challenges involves nominating and verifying biomarkers. Candidate biomarkers need to discriminate disease from benign controls with high sensitivity and specificity for an intended use, which we describe as a two-tiered strategy of identifying and screening high-risk patients. Community-wide efforts to share samples, data, and analysis methods have been beneficial and progress meeting this challenge has been achieved. The second set of challenges is assay optimization and validating biomarkers. After initial candidate validation, assays need to be refined into accurate, cost-effective, highly reproducible, and multiplexed targeted panels and then validated in large cohorts. To move the most promising candidates forward, ideally, biomarker panels, head-to-head comparisons, meta-analysis, and assessment in independent data sets might mitigate risk of failure. Much more investment is needed to overcome these challenges. The third challenge is achieving clinical translation. To moonshot an early detection test to the clinic requires a large clinical trial and organizational, regulatory, and entrepreneurial know-how. Additional factors, such as imaging technologies, will likely need to improve concomitant with molecular biomarker development. The magnitude of the clinical translational challenge is uncertain, but interdisciplinary cooperation within the PDAC community is poised to confront it.

Molecular Testing for the Treatment of Advanced Colorectal Cancer: An Overview.

Concurrent with an expansion in the number of agents available for the treatment of advanced CRC, there has been an increase in our understanding of selection biomarkers to optimize the management of patients with this disease. For CRC patients being considered for anti-EGFR therapy, expanded RAS testing is the standard of care to determine the subset of patients who can benefit from cetuximab or panitumumab in conjunction with chemotherapy. A small fraction of patients have HER2 amplification where emerging data suggest treatment with drugs targeting this alteration. Although advanced CRC patients who harbor the BRAF V600E mutation have a poorer prognosis, they are eligible for combinatorial therapy targeting EGFR/BRAF or BRAF/MEK within the MAP kinase signaling pathway. Once primarily thought to be a negative prognostic marker, BRAF V600E mutation is now considered as a positive predictive factor with an opportunity for clinical intervention. A growing body of evidence also supports MSI testing as clinical benefits with immune checkpoint blockade by cancer immunotherapy have been demonstrated in MSI-high patients whose tumors exhibit high mutational burden. It has been established that UGT1A1*28 polymorphism is associated with irinotecan toxicity, but this test is rarely performed as the management strategy has not been identified. No established predictive biomarker for anti-VEGF therapy has yet to be discovered.It is becoming increasingly apparent that our growing understanding of biomarkers is revolutionizing and improving our strategies in the treatment of advanced CRC. Traditional nonselective cytotoxic chemotherapy is gradually being augmented and even in some cases supplanted by selective targeted agents based on our increasing understanding of tumor signaling and mechanism at the molecular level. The prospect of personalized medicine in directing treatment approaches that are optimally beneficial for patients brings tremendous excitement to the growing field of cancer therapeutics. As discussed in this chapter, the concurrent development of molecular biomarkers with new treatment strategies holds great promise of precision medicine in improving outcomes for patients with advanced CRC.

Evaluating Molecular Biomarkers for the Early Detection of Lung Cancer: When Is a Biomarker Ready for Clinical Use? An Official American Thoracic Society Policy Statement.

Molecular biomarkers have the potential to improve the current state of early lung cancer detection. The goal of this project was to develop a policy statement that provides guidance about the level of evidence required to determine that a molecular biomarker, used to support early lung cancer detection, is appropriate for clinical use. An ad hoc project steering committee was formed, to include individuals with expertise in the early detection of lung cancer and molecular biomarker development, from inside and outside of the Assembly on Thoracic Oncology. Key questions, generated from the results of a survey of the project steering committee, were discussed at an in-person meeting. Results of the discussion were summarized in a policy statement that was circulated to the steering committee and revised multiple times to achieve consensus. With a focus on the clinical applications of lung cancer screening and lung nodule evaluation, the policy statement outlines categories of results that should be reported in the early phases of molecular biomarker development, discusses the level of evidence that would support study of the clinical utility, describes the outcomes that should be proven to consider a molecular biomarker clinically useful, and suggests study designs capable of assessing these outcomes. The application of molecular biomarkers to assist with the early detection of lung cancer has the potential to substantially improve our ability to select patients for lung cancer screening, and to assist with the characterization of indeterminate lung nodules. We have described relevant considerations and have suggested standards to apply when determining whether a molecular biomarker for the early detection of lung cancer is ready for clinical use.

Whole-Genome Sequence of the 1,4-Dioxane-Degrading Bacterium Mycobacterium dioxanotrophicus PH-06.

ABSTRACTWe report here the complete genome sequence of Mycobacterium dioxanotrophicus PH-06, which is capable of using 1,4-dioxane as a sole source of carbon and energy. The reported sequence will enable the elucidation of this novel metabolic pathway and the development of molecular biomarkers to assess bioremediation potential at contaminated sites.

The Epigenetics of Epilepsy and Its Progression

Epilepsy is a common and devastating neurological disorder characterized by recurrent and unprovoked spontaneous seizures. One leading hypothesis for the development and progression of epilepsy is that large-scale changes in gene transcription and protein expression contribute to aberrant network restructuring and hyperexcitability, resulting in the genesis of repeated seizures. Current research shows that epigenetic mechanisms, including posttranslational alterations to the proteins around which DNA is coiled, chemical modifications to DNA, and the activity of various noncoding RNA molecules exert important influences on these gene networks in experimental epilepsy. Key findings from animal models have been replicated in humans using brain tissue obtained from living patients at the time of neurosurgical resection for pharmacoresistant epilepsy. These findings have spurred efforts to target epigenetic processes to disrupt or modify epilepsy in experimental models with varying degrees of success. In this review, we will (1) summarize the epigenetic mechanisms implicated in epileptogenesis and epilepsy, (2) explore the influence of metabolic factors on epigenetic mechanisms, and (3) assess the potential of using epigenetic markers to support diagnosis and prognosis. Translation of these findings may guide the development of molecular biomarkers and novel therapeutics for prevention or modification of epileptic disorders.

Epigenetic Biomarkers for Parkinson's Disease: From Diagnostics to Therapeutics.

Parkinson’s disease (PD) is a prevalent neurodegenerative illness that is often diagnosed after significant pathology and neuronal cell loss has occurred. Biomarkers of PD are greatly needed for early diagnosis, as well as for the prediction of disease progression and treatment outcome. In this regard, the epigenome, which is partially dynamic, holds considerable promise for the development of molecular biomarkers for PD. Epigenetic marks are modified by both DNA sequence and environmental factors associated with PD, and such marks could serve as a unifying predictor of at-risk individuals. Epigenetic abnormalities have been detected in PD and other age-dependent neurodegenerative diseases, some of which were reported to occur early on and were reversible by PD medications. Emerging reports indicate that certain epigenetic differences observed in the PD brain are detectable in more easily accessible tissues. In this review, we examine epigenetic-based strategies for the development of PD biomarkers. Despite the complexities and challenges faced, the epigenome offers a new source of biomarkers with potential etiological relevance to PD, and may expand opportunities for personalized therapies.