Advances in Proteomic and Metabolomic Profiling of Neurodegenerative Diseases

Advances in Huntington's Disease Biomarkers: A 10-Year Bibliometric Analysis and a Comprehensive Review

Neurodegenerative disorders (NDs) cause progressive neuronal loss and are a significant public health concern, with NDs projected to become the second leading global cause of death within two decades. Huntington's disease (HD) is a rare, progressive ND caused by an autosomal-dominant mutation in the huntingtin (HTT) gene, leading to severe neuronal loss in the brain and resulting in debilitating motor, cognitive, and psychiatric symptoms. Given the complex pathology of HD, biomarkers are essential for performing early diagnosis, monitoring disease progression, and evaluating treatment efficacy. However, the identification of consistent HD biomarkers is challenging due to the prolonged premanifest HD stage, HD's heterogeneous presentation, and its multiple underlying biological pathways. This study involves a 10-year bibliometric analysis of HD biomarker research, revealing key research trends and gaps. The study also features a comprehensive literature review of emerging HD biomarkers, concluding the need for better stratification of HD patients and well-designed longitudinal studies to validate HD biomarkers. Promising candidate wet HD biomarkers- including neurofilament light chain protein (NfL), microRNAs, the mutant HTT protein, and specific metabolic and inflammatory markers- are discussed, with emphasis on their potential utility in the premanifest HD stage. Additionally, biomarkers reflecting brain structural deficits and motor or behavioral impairments, such as neurophysiological (e.g., motor tapping, speech, EEG, and event-related potentials) and imaging (e.g., MRI, PET, and diffusion tensor imaging) biomarkers, are evaluated. The findings underscore that the discovery and validation of reliable HD biomarkers urgently require improved patient stratification and well-designed longitudinal studies. Reliable biomarkers, particularly in the premanifest HD stage, are crucial for optimizing HD clinical management strategies, enabling personalized treatment approaches, and advancing clinical trials of HD-modifying therapies.

Cerebrospinal Fluid Metabolomics and Proteomics Integration in Neurological Syndromes

The integration of multi-omics data has increasingly been recognized as an effective approach to addressing complex problems and advancing precision medicine. Metabolomics and proteomics are closely related, and their integration provides complementary insights and enables cross-validation of experimental results. The integration of proteomics and metabolomics in cerebrospinal fluid is expected to reconstruct the complex biological networks underlying nervous system diseases, enhance understanding of molecular mechanisms, and aid in disease classification and prognosis prediction. However, integrating multi-omics data still faces numerous challenges, limiting the application of combined proteomic and metabolomic analyses in neurological diseases. Based on the advantages of integrated proteomics and metabolomics, this chapter introduces, for the first time, common strategies for the integrated analyses of omics data. Furthermore, we review advances in cerebrospinal fluid proteomics and metabolomics for neurological syndromes, highlighting current challenges and future directions.

Scrutinizing neurodegenerative diseases: decoding the complex genetic architectures through a multi-omics lens

Neurodegenerative diseases present complex genetic architectures, reflecting a continuum from monogenic to oligogenic and polygenic models. Recent advances in multi-omics data, coupled with systems genetics, have significantly refined our understanding of how these data impact neurodegenerative disease mechanisms. To contextualize these genetic discoveries, we provide a comprehensive critical overview of genetic architecture concepts, from Mendelian inheritance to the latest insights from oligogenic and omnigenic models. We explore the roles of common and rare genetic variants, gene-gene and gene-environment interactions, and epigenetic influences in shaping disease phenotypes. Additionally, we emphasize the importance of multi-omics layers including genomic, transcriptomic, proteomic, epigenetic, and metabolomic data in elucidating the molecular mechanisms underlying neurodegeneration. Special attention is given to missing heritability and the contribution of rare variants, particularly in the context of pleiotropy and network pleiotropy. We examine the application of single-cell omics technologies, transcriptome-wide association studies, and epigenome-wide association studies as key approaches for dissecting disease mechanisms at tissue- and cell-type levels. Our review introduces the OmicPeak Disease Trajectory Model, a conceptual framework for understanding the genetic architecture of neurodegenerative disease progression, which integrates multi-omics data across biological layers and time points. This review highlights the critical importance of adopting a systems genetics approach to unravel the complex genetic architecture of neurodegenerative diseases. Finally, this emerging holistic understanding of multi-omics data and the exploration of the intricate genetic landscape aim to provide a foundation for establishing more refined genetic architectures of these diseases, enhancing diagnostic precision, predicting disease progression, elucidating pathogenic mechanisms, and refining therapeutic strategies for neurodegenerative conditions.

Revolutionizing Personalized Medicine: Synergy with Multi-Omics Data Generation, Main Hurdles, and Future Perspectives

The field of personalized medicine is undergoing a transformative shift through the integration of multi-omics data, which mainly encompasses genomics, transcriptomics, proteomics, and metabolomics. This synergy allows for a comprehensive understanding of individual health by analyzing genetic, molecular, and biochemical profiles. The generation and integration of multi-omics data enable more precise and tailored therapeutic strategies, improving the efficacy of treatments and reducing adverse effects. However, several challenges hinder the full realization of personalized medicine. Key hurdles include the complexity of data integration across different omics layers, the need for advanced computational tools, and the high cost of comprehensive data generation. Additionally, issues related to data privacy, standardization, and the need for robust validation in diverse populations remain significant obstacles. Looking ahead, the future of personalized medicine promises advancements in technology and methodologies that will address these challenges. Emerging innovations in data analytics, machine learning, and high-throughput sequencing are expected to enhance the integration of multi-omics data, making personalized medicine more accessible and effective. Collaborative efforts among researchers, clinicians, and industry stakeholders are crucial to overcoming these hurdles and fully harnessing the potential of multi-omics for individualized healthcare.

Decoding Neurodegeneration: A Review of Molecular Mechanisms and Therapeutic Advances in Alzheimer's, Parkinson's, and ALS

Neurodegenerative diseases, such as Alzheimer's, Parkinson's, ALS, and Huntington's, remain formidable challenges in medicine, with their relentless progression and limited therapeutic options. These diseases arise from a web of molecular disturbances-misfolded proteins, chronic neuroinflammation, mitochondrial dysfunction, and genetic mutations-that slowly dismantle neuronal integrity. Yet, recent scientific breakthroughs are opening new paths to intervene in these once-intractable conditions. This review synthesizes the latest insights into the underlying molecular dynamics of neurodegeneration, revealing how intertwined pathways drive the course of these diseases. With an eye on the most promising advances, we explore innovative therapies emerging from cutting-edge research: nanotechnology-based drug delivery systems capable of navigating the blood-brain barrier, gene-editing tools like CRISPR designed to correct harmful genetic variants, and stem cell strategies that not only replace lost neurons but foster neuroprotective environments. Pharmacogenomics is reshaping treatment personalization, enabling tailored therapies that align with individual genetic profiles, while molecular diagnostics and biomarkers are ushering in an era of early, precise disease detection. Furthermore, novel perspectives on the gut-brain axis are sparking interest as mounting evidence suggests that microbiome modulation may play a role in reducing neuroinflammatory responses linked to neurodegenerative progression. Taken together, these advances signal a shift toward a comprehensive, personalized approach that could transform neurodegenerative care. By integrating molecular insights and innovative therapeutic techniques, this review offers a forward-looking perspective on a future where treatments aim not just to manage symptoms but to fundamentally alter disease progression, presenting renewed hope for improved patient outcomes.

Personalized Medicine Approach to Proteomics and Metabolomics of Cytochrome P450 Enzymes: A Narrative Review

Cytochrome P450 enzymes (CYPs) represent a diverse family of heme-thiolate proteins involved in the metabolism of a wide range of endogenous compounds and xenobiotics. In recent years, proteomics and metabolomics have been used to obtain a comprehensive insight into the role of CYPs in health and disease aspects. The objective of the present work is to better understand the status of proteomics and metabolomics in CYP research in optimizing therapeutics and patient safety from a personalized medicine approach. The literature used in this narrative review was procured by electronic search of PubMed, Medline, Embase, and Google Scholar databases. The following keywords were used in combination to identify related literature: "proteomics," "metabolomics," "cytochrome P450," "drug metabolism," "disease conditions," "proteome," "liquid chromatography-mass spectrometry," "integration," "metabolites," "pathological conditions." We reviewed studies that utilized proteomics and metabolomics approaches to explore the multifaceted roles of CYPs in identifying disease markers and determining the contribution of CYP enzymes in developing treatment strategies. The applications of various cutting-edge analytical techniques, including liquid chromatography-mass spectrometry, nuclear magnetic resonance, and bioinformatics analyses in CYP proteomics and metabolomics studies, have been highlighted. The identification of CYP enzymes through metabolomics and/or proteomics in various disease conditions provides key information in the diagnostic and therapeutic landscape. Leveraging both proteomics and metabolomics presents a powerful approach for an exhaustive exploration of the multifaceted roles played by CYP enzymes in personalized medicine. Proteomics and metabolomics have enabled researchers to unravel the complex connection between CYP enzymes and metabolic markers associated with specific diseases. As technology and methodologies evolve, an integrated approach promises to further elucidate the role of CYPs in human health and disease, potentially ushering in a new era of personalized medicine.

Low-Dose Radiation Induces Alterations in Fatty Acid and Tyrosine Metabolism in the Mouse Hippocampus: Insights from Integrated Multiomics

In recent years, there has been a drastic surge in neurological disorders with sporadic cases contributing more than ever to their cause. Radiation exposure through diagnostic or therapeutic routes often results in neurological injuries that may lead to neurodegenerative pathogenesis. However, the underlying mechanisms regulating the neurological impact of exposure to near-low doses of ionizing radiation are not known. In particular, the neurological changes caused by metabolomic reprogramming have not yet been elucidated. Hence, in the present study, C57BL/6 mice were exposed to a single whole-body X-ray dose of 0.5 Gy, and 14 days post-treatment, the hippocampus was subjected to metabolomic analysis. The hippocampus of the irradiated animals showed significant alterations in 15 metabolites, which aligned with altered tyrosine, phenylalanine, and alpha-linolenic acid metabolism and the biosynthesis of unsaturated fatty acids. Furthermore, a multiomics interaction network comprising metabolomics and RNA sequencing data analysis provided insights into gene-metabolite interactions. Tyrosine metabolism was revealed to be the most altered, which was demonstrated by the interaction of several crucial genes and metabolites. The present study revealed the regulation of low-dose radiation-induced neurotoxicity at the metabolomic level and its implications for the pathogenesis of neurological disorders. The present study also provides novel insights into metabolomic pathways altered following near-low-dose IR exposure and its link with neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease.

Proteomics profiling and machine learning in nusinersen-treated patients with spinal muscular atrophy

AIM

The availability of disease-modifying therapies and newborn screening programs for spinal muscular atrophy (SMA) has generated an urgent need for reliable prognostic biomarkers to classify patients according to disease severity. We aim to identify cerebrospinal fluid (CSF) prognostic protein biomarkers in CSF samples of SMA patients collected at baseline (T0), and to describe proteomic profile changes and biological pathways influenced by nusinersen before the sixth nusinersen infusion (T302).

METHODS

In this multicenter retrospective longitudinal study, we employed an untargeted liquid chromatography mass spectrometry (LC-MS)-based proteomic approach on CSF samples collected from 61 SMA patients treated with nusinersen (SMA1 n=19, SMA2 n=19, SMA3 n=23) at T0 at T302. The Random Forest (RF) machine learning algorithm and pathway enrichment analysis were applied for analysis.

RESULTS

The RF algorithm, applied to the protein expression profile of naïve patients, revealed several proteins that could classify the different types of SMA according to their differential abundance at T0. Analysis of changes in proteomic profiles identified a total of 147 differentially expressed proteins after nusinersen treatment in SMA1, 135 in SMA2, and 289 in SMA3. Overall, nusinersen-induced changes on proteomic profile were consistent with i) common effects observed in allSMA types (i.e. regulation of axonogenesis), and ii) disease severity-specific changes, namely regulation of glucose metabolism in SMA1, of coagulation processes in SMA2, and of complement cascade in SMA3.

CONCLUSIONS

This untargeted LC-MS proteomic profiling in the CSF of SMA patients revealed differences in protein expression in naïve patients and showed nusinersen-related modulation in several biological processes after 10 months of treatment. Further confirmatory studies are needed to validate these results in larger number of patients and over abroader timeframe.

Microstructural Changes in the Corpus Callosum in Neurodegenerative Diseases

The corpus callosum, the largest white matter structure in the brain, plays a crucial role in interhemispheric communication and cognitive function. This review examines the microstructural changes observed in the corpus callosum across various neurodegenerative diseases, including Alzheimer's disease, Parkinson's disease, Huntington's disease, and amyotrophic lateral sclerosis (ALS). New neuroimaging studies, mainly those that use diffusion tensor imaging (DTI) and advanced tractography methods, were put together to show how changes have happened in the organization of white matter and the connections between them. Some of the most common ways the corpus callosum breaks down are discussed, including less fractional anisotropy, higher mean diffusivity, and atrophy in certain regions. The relationship between these microstructural changes and cognitive decline, motor dysfunction, and disease progression is explored. Additionally, we consider the potential of corpus callosum imaging as a biomarker for early disease detection and monitoring. Studies show that people with these disorders have lower fractional anisotropy and higher mean diffusivity in the corpus callosum, often in ways that are specific to the disease. These changes often happen before gray matter atrophy and are linked to symptoms, which suggests that the corpus callosum could be used as an early sign of neurodegeneration. The review also highlights the implications of these findings for understanding disease mechanisms and developing therapeutic strategies. Future directions, including the application of advanced imaging techniques and longitudinal studies, are discussed to elucidate the role of corpus callosum degeneration in neurodegenerative processes. This review underscores the importance of the corpus callosum in understanding the pathophysiology of neurodegenerative diseases and its potential as a target for therapeutic interventions.

Exploring the Hypocholesterolemic Potential of a Fucus vesiculosus Extract: Omic Insights into Molecular Mechanisms at the Intestinal Level

High blood cholesterol levels are a major risk factor for cardiovascular diseases. A purified aqueous extract of Fucus vesiculosus, rich in phlorotannins and peptides, has been described for its potential to inhibit cholesterol biosynthesis and intestinal absorption. In this work, the effect of this extract on intestinal cells' metabolites and proteins was analysed to gain a deeper understanding of its mode of action on lipids' metabolism, particularly concerning the absorption and transport of exogenous cholesterol. Caco-2 cells, differentiated into enterocytes, were exposed to the extract, and analysed by untargeted metabolomics and proteomics. The results of the metabolomic analysis showed statistically significant differences in glutathione content of cells exposed to the extract compared to control cells, along with an increased expression of fatty acid amides in exposed cells. A proteomic analysis showed an increased expression in cells exposed to the extract compared to control cells of FAB1 and NPC1, proteins known to be involved in lipid metabolism and transport. To the extent of our knowledge, this study is the first use of untargeted metabolomics and a proteomic analysis to investigate the effects of F. vesiculosus on differentiated Caco-2 cells, offering insights into the molecular mechanism of the extract's compounds on intestinal cells.

COVID-19 and Comorbidities: What Has Been Unveiled by Metabolomics?

The COVID-19 pandemic has brought about diverse impacts on the global population. Individuals with comorbidities were more susceptible to the severe symptoms caused by the virus. Within the crisis scenario, metabolomics represents a potential area of science capable of providing relevant information for understanding the metabolic pathways associated with the intricate interaction between the viral disease and previous comorbidities. This work aims to provide a comprehensive description of the scientific production pertaining to metabolomics within the specific context of COVID-19 and comorbidities, while highlighting promising areas for exploration by those interested in the subject. In this review, we highlighted the studies of metabolomics that indicated a variety of metabolites associated with comorbidities and COVID-19. Furthermore, we observed that the understanding of the metabolic processes involved between comorbidities and COVID-19 is limited due to the urgent need to report disease outcomes in individuals with comorbidities. The overlap of two or more comorbidities associated with the severity of COVID-19 hinders the comprehension of the significance of each condition. Most identified studies are observational, with a restricted number of patients, due to challenges in sample collection amidst the emergent situation.

Human brains preserve in diverse environments for at least 12 000 years

The brain is thought to be among the first human organs to decompose after death. The discovery of brains preserved in the archaeological record is therefore regarded as unusual. Although mechanisms such as dehydration, freezing, saponification, and tanning are known to allow for the preservation of the brain on short time scales in association with other soft tissues (≲4000 years), discoveries of older brains, especially in the absence of other soft tissues, are rare. Here, we collated an archive of more than 4400 human brains preserved in the archaeological record across approximately 12 000 years, more than 1300 of which constitute the only soft tissue preserved amongst otherwise skeletonized remains. We found that brains of this type persist on time scales exceeding those preserved by other means, which suggests an unknown mechanism may be responsible for preservation particular to the central nervous system. The untapped archive of preserved ancient brains represents an opportunity for bioarchaeological studies of human evolution, health and disease.

A top-down proteomic approach reveals a salivary protein profile able to classify Parkinson's disease with respect to Alzheimer's disease patients and to healthy controls

Parkinson's disease (PD) is a complex neurodegenerative disease with motor and non-motor symptoms. Diagnosis is complicated by lack of reliable biomarkers. To individuate peptides and/or proteins with diagnostic potential for early diagnosis, severity and discrimination from similar pathologies, the salivary proteome in 36 PD patients was investigated in comparison with 36 healthy controls (HC) and 35 Alzheimer's disease (AD) patients. A top-down platform based on HPLC-ESI-IT-MS allowed characterizing and quantifying intact peptides, small proteins and their PTMs (overall 51). The three groups showed significantly different protein profiles, PD showed the highest levels of cystatin SA and antileukoproteinase and the lowest of cystatin SN and some statherin proteoforms. HC exhibited the lowest abundance of thymosin β4, short S100A9, cystatin A, and dimeric cystatin B. AD patients showed the highest abundance of α-defensins and short oxidized S100A9. Moreover, different proteoforms of the same protein, as S-cysteinylated and S-glutathionylated cystatin B, showed opposite trends in the two pathological groups. Statherin, cystatins SA and SN classified accurately PD from HC and AD subjects. α-defensins, histatin 1, oxidized S100A9, and P-B fragments were the best classifying factors between PD and AD patients. Interestingly statherin and thymosin β4 correlated with defective olfactory functions in PD patients. All these outcomes highlighted implications of specific proteoforms involved in the innate-immune response and inflammation regulation at oral and systemic level, suggesting a possible panel of molecular and clinical markers suitable to recognize subjects affected by PD.

Neuroprotective mechanisms of defatted walnut powder against scopolamine-induced Alzheimer's disease in mice revealed through metabolomics and proteomics analyses

ETHNOPHARMACOLOGICAL RELEVANCE

Defatted walnut powder (DWP), the byproduct remaining after extracting oil from the walnut kernel, has the actions of nourishing liver and the kidney, replenishing blood, and calming the nerves, which is believed to be a brain-nourishing in Chinese medicine. DWP is rich in phenolic substances with demonstrated anti-inflammatory, antioxidant, lipid-lowering and neuroprotective effects. Despite these promising properties of DWP, its effectiveness in treating Alzheimer's disease (AD) remains unclear, and further research is needed to understand the mechanism of action.

AIM OF THE STUDY

This study aimed to investigate the potential mechanism of DWP on AD by constructing the overall metabolic profile of mice with an anti-scopolamine AD model and verification of the highly correlated pathway.

MATERIALS AND METHODS

The neuroprotective efficacy of DWP in a mouse model of AD established by scopolamine injection was examined. Spatial memory performance in the Morris water maze (MWM), markers of cholinergic function in hippocampus and cortex, and neuropathological changes were compared among control, model, and DWP-consuming model group mice. In addition, combined metabolomic and proteomic analyses were conducted to investigate changes in metabolite and protein expression profiles in AD model mice induced by DWP consumption. Differentially expressed proteins and metabolites were then analyzed for KEGG pathway enrichment and results confirmed through targeted amino acid metabolomics.

RESULTS

The results showed that consumption of DWP improved spatial learning and memory in the MWM, enhanced cholinergic function, and reduced histopathological damage in the cortex and hippocampus of AD model mice. Based on differentially abundant metabolites and proteins, 43 metabolic pathways modulated by DWP were identified, mainly involving in amino acid metabolic pathways strongly associated with cellular energetics and antioxidant capacity, and targeted amino acid metabolomics confirmed that DWPE significantly elevated the levels of Arginine (Arg), Histidine (His), Proline (Pro), Serine (Ser), and Tyrosine (Tyr), while reducing the levels of Glutamate (Glu). This ultimately resulted in an improvement in the progression of AD.

CONCLUSION

This study identified numerous metabolic networks modulated by DWP that can mitigate scopolamine-induced AD neuropathology and cognitive dysfunction. DWP is a promising resource to identify AD-related pathogenic pathways and therapeutic strategies.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Biomarker Methodologies: A NIMH Perspective

Biomarkers are critically important in the development of drugs, biologics, medical devices, and psychosocial interventions for psychiatric disorders. As the lead federal agency charged with setting and supporting the national agenda for mental health research, the National Institute of Mental Health (NIMH) funds a broad portfolio of basic, translational, and clinical research focused on identifying, developing, and validating biomarkers for serious mental illnesses and neurodevelopmental conditions. In psychiatric research over the past 10 years, there has been an intensive effort to identify biomarkers as potential tools to improve treatment options for individuals with mental health concerns and increase success in the development of novel interventions. This chapter highlights examples of biomarker technologies that have been utilized to advance understanding of the pathophysiology of psychiatric disorders and the development of novel therapeutics.

Integrative proteomic and metabonomic profiling elucidates amino acid and lipid metabolism disorder in CA-MRSA-infected breast abscesses

Objective

Bacterial culture and drug sensitivity testing have been the gold standard for confirming community-acquired methicillin-resistant Staphylococcus aureus (CA-MRSA) infection in breast abscess with a long history. However, these tests may delay treatment and increase the risk of nosocomial infections. To handle and improve this critical situation, this study aimed to explore biomarkers that could facilitate the rapid diagnosis of CA-MRSA infection.

Methods

This study for the first time applied label-free quantitative proteomics and non-targeted metabonomics to identify potential differentially expressed proteins (DEPs) and differentially expressed metabolites (DEMs) in breast abscess infected with CA-MRSA compared to methicillin-susceptible S. aureus (MSSA). The two omics data were integrated and analyzed using bioinformatics, and the results were validated using Parallel Reaction Monitoring (PRM). Receiver operating characteristic (ROC) curves were generated to evaluate the predictive efficiency of the identified biomarkers for diagnosing CA-MRSA infection.

Results

After using the above-mentioned strategies, 109 DEPs were identified, out of which 86 were upregulated and 23 were downregulated. Additionally, a total of 61 and 26 DEMs were initially screened in the positive and negative ion modes, respectively. A conjoint analysis indicated that the amino acid metabolism, glycosphingolipid biosynthesis, and glycerophospholipid metabolism pathways were co-enriched by the upstream DEPs and downstream DEMs, which may be involved in structuring the related network of CA-MRSA infection. Furthermore, three significant DEMs, namely, indole-3-acetic acid, L-(-)-methionine, and D-sedoheptulose 7-phosphate, displayed good discriminative abilities in early identification of CA-MRSA infection in ROC analysis.

Conclusion

As there is limited high-quality evidence and multiple omics research in this field, the explored candidate biomarkers and pathways may provide new insights into the early diagnosis and drug resistance mechanisms of CA-MRSA infection in Chinese women.

A Systematic Review on Metabolomics Analysis in Hearing Impairment: Is It a Possible Tool in Understanding Auditory Pathologies?

With more than 466 million people affected, hearing loss represents the most common sensory pathology worldwide. Despite its widespread occurrence, much remains to be explored, particularly concerning the intricate pathogenic mechanisms underlying its diverse phenotypes. In this context, metabolomics emerges as a promising approach. Indeed, lying downstream from molecular biology's central dogma, the metabolome reflects both genetic traits and environmental influences. Furthermore, its dynamic nature facilitates well-defined changes during disease states, making metabolomic analysis a unique lens into the mechanisms underpinning various hearing impairment forms. Hence, these investigations may pave the way for improved diagnostic strategies, personalized interventions and targeted treatments, ultimately enhancing the clinical management of affected individuals. In this comprehensive review, we discuss findings from 20 original articles, including human and animal studies. Existing literature highlights specific metabolic changes associated with hearing loss and ototoxicity of certain compounds. Nevertheless, numerous critical issues have emerged from the study of the current state of the art, with the lack of standardization of methods, significant heterogeneity in the studies and often small sample sizes being the main limiting factors for the reliability of these findings. Therefore, these results should serve as a stepping stone for future research aimed at addressing the aforementioned challenges.

Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer's Disease

The development of early non-invasive diagnosis methods and identification of novel biomarkers are necessary for managing Alzheimer's disease (AD) and facilitating effective prognosis and treatment. AD has multi-factorial nature and involves complex molecular mechanism, which causes neuronal degeneration. The primary challenges in early AD detection include patient heterogeneity and lack of precise diagnosis at the preclinical stage. Several cerebrospinal fluid (CSF) and blood biomarkers have been proposed to show excellent diagnosis ability by identifying tau pathology and cerebral amyloid beta (Aβ) for AD. Intense research endeavors are being made to develop ultrasensitive detection techniques and find potent biomarkers for early AD diagnosis. To mitigate AD worldwide, understanding various CSF biomarkers, blood biomarkers, and techniques that can be used for early diagnosis is imperative. This review attempts to provide information regarding AD pathophysiology, genetic and non-genetic factors associated with AD, several potential blood and CSF biomarkers, like neurofilament light, neurogranin, Aβ, and tau, along with biomarkers under development for AD detection. Besides, numerous techniques, such as neuroimaging, spectroscopic techniques, biosensors, and neuroproteomics, which are being explored to aid early AD detection, have been discussed. The insights thus gained would help in finding potential biomarkers and suitable techniques for the accurate diagnosis of early AD before cognitive dysfunction.

Dyrk1a Phosphorylation of α-Synuclein Mediating Apoptosis of Dopaminergic Neurons in Parkinson's Disease

Objective

To investigate the role of aberrant Dyrk1a expression in phosphorylation modification at the α-synuclein serine 129 (Ser129) site to analyze its molecular mechanism in mediating apoptosis of PD.

Methods

The protein level of P-α-synuclein (Ser129), α-synuclein, Bcl-2, Bax, active caspase 3, GSK3β, PI3K, AKT, and cyclinD1 were detected. The mRNA transcript levels of Dyrk1a and DAT and protein levels of IL-1β, IL-6, COX-2, and TNF-α were detected.

Results

P-α-synuclein (Ser129), α-synuclein, Bax, active caspase 3, GSK3β, and cyclinD1 expressions were decreased in Dyrk1a-AAV-ShRNA (P < 0.05), and Bcl-2, AKT, and PI3K expressions were increased (P < 0.05). Increased TH protein expression was shown in Dyrk1a-AAV-ShRNA (P < 0.05). Dyrk1a mRNA was decreased in the Dyrk1a-AAV-ShRNA group (P < 0.05), and DAT mRNA was increased (P < 0.05). IL-1β, IL-6, COX-2, and TNF-α protein levels were decreased in Dyrk1al-AAV-Sh-RNA (P < 0.05). Transcriptome sequencing showed that Fam220a, which was expected to activate STAT family protein binding activity and participate in the negative regulation of transcription through RNA polymerase II and protein dephosphorylation showed differentially upregulated expression. The untargeted metabolome showed that the major compounds in the Dyrk1a-AAV-ShRNA group were hormones and transmission mediators and the most metabolism-related pathways. Fam220a showed differentially upregulated expression, and differentially expressed genes were enriched for the neuroactive ligand-receptor interaction, vascular smooth muscle contraction, and melanogenesis-related pathways.

Conclusion

Abnormal Dyrk1a expression can affect α-synuclein phosphorylation modifications, and dyrk1a knockdown activates the PI3K/AKT pathway and reduces dopaminergic neuron apoptosis. It provides a theoretical basis for the group to further investigate the molecular mechanism.

Synthesis of bioactive oligosaccharides and their potential health benefits

Oligosaccharides, a low polymerization degree of carbohydrate, possess various physiological activities, such as anti-diabetes, anti-obesity, anti-aging, anti-viral, and gut microbiota regulation, having a widely used in food and medical fields. However, due to the limited natural oligosaccharides, many un-natural oligosaccharides from complex polysaccharides are being studied for amplifying the available pool of oligosaccharides. More recently, various oligosaccharides were developed by using several artificial strategies, such as chemical degradation, enzyme catalysis, and biosynthesis, then they can be applied in various sectors. Moreover, it has gradually become a trend to use biosynthesis to realize the synthesis of oligosaccharides with clear structure. Emerging research has found that un-natural oligosaccharides exert more comprehensive effects against various human diseases through multiple mechanisms. However, these oligosaccharides from various routes have not been critical reviewed and summarized. Therefore, the purpose of this review is to present the various routes of oligosaccharides preparations and healthy effects, with a focus on diabetes, obesity, aging, virus, and gut microbiota. Additionally, the application of multi-omics for these natural and un-natural oligosaccharides has also been discussed. Especially, the multi-omics are needed to apply in various disease models to find out various biomarkers to respond to the dynamic change process of oligosaccharides.

Endogenous neural stem cells characterization using omics approaches: Current knowledge in health and disease

Neural stem cells (NSCs), an invaluable source of neuronal and glial progeny, have been widely interrogated in the last twenty years, mainly to understand their therapeutic potential. Most of the studies were performed with cells derived from pluripotent stem cells of either rodents or humans, and have mainly focused on their potential in regenerative medicine. High-throughput omics technologies, such as transcriptomics, epigenetics, proteomics, and metabolomics, which exploded in the past decade, represent a powerful tool to investigate the molecular mechanisms characterizing the heterogeneity of endogenous NSCs. The transition from bulk studies to single cell approaches brought significant insights by revealing complex system phenotypes, from the molecular to the organism level. Here, we will discuss the current literature that has been greatly enriched in the “omics era”, successfully exploring the nature and function of endogenous NSCs and the process of neurogenesis. Overall, the information obtained from omics studies of endogenous NSCs provides a sharper picture of NSCs function during neurodevelopment in healthy and in perturbed environments.

Neurodegenerative disorders: From clinicopathology convergence to systems biology divergence

Neurodegenerative diseases are multifactorial. This means that several genetic, epigenetic, and environmental factors contribute to their emergence. Therefore, for the future management of these highly prevalent diseases, it is necessary to change perspective. If a holistic viewpoint is assumed, the phenotype (the clinicopathological convergence) emerges from the perturbation of a complex system of functional interactions among proteins (systems biology divergence). The systems biology top-down approach starts with the unbiased collection of sets of data generated through one or more -omics techniques and has the aim to identify the networks and the components that participate in the generation of a phenotype (disease), often without any available a priori knowledge. The principle behind the top-down method is that the molecular components that respond similarly to experimental perturbations are somehow functionally related. This allows the study of complex and relatively poorly characterized diseases without requiring extensive knowledge of the processes under investigation. In this chapter, the use of a global approach will be applied to the comprehension of neurodegeneration, with a particular focus on the two most prevalent ones, Alzheimer's and Parkinson's diseases. The final purpose is to distinguish disease subtypes (even with similar clinical manifestations) to launch a future of precision medicine for patients with these disorders.

Bioenhancing effects of piperine and curcumin on triterpenoid pharmacokinetics and neurodegenerative metabolomes from Centella asiatica extract in beagle dogs

Centell-S is a water-soluble extract of Centella asiatica containing more than 80% w/w triterpenoid glycosides. Madecassoside and asiaticoside are two major components of the extract and can be converted into active metabolites, triterpenic acids in large mammal species. In this study, the pharmacokinetic profiles and metabolomic changes generated by the bioactive triterpenoids of Centell-S alone, and in combination with the bioenhancers piperine and curcumin, were investigated in beagle dogs. The test substances were orally administered over multiple doses for 7 consecutive days. At day 1 and 7 after receiving the test compounds, the level of major bioactive triterpenoids and related metabolites were measured using triple quadrupole and high-resolution accurate mass orbitrap models of LCMS to determine pharmacokinetic and metabolomic profiles, respectively. Centell-S was well tolerated, alone and in all combination groups. The combination of Centell-S and piperine significantly increased (p < 0.05) the systemic exposure of madecassoside on day 1 and asiatic acid on day 7, by approximately 1.5 to 3.0-fold of C_max and AUC values as compared to the Centell-S alone, while the addition of curcumin did not provide a significant improvement. Several metabolomic changes were observed from pre-dose to 4 h post-dose, with some biomarkers of neurodegenerative diseases including L-glutamine, lysophosphatidylcholine (17:0), taurochenodeoxycholic acid, uric acid, stearic acid, palmitic acid, and lactic acid showing good correlation with the systemic exposure of the bioactive triterpenoids (asiatic acid). Thus, the combining of piperine to Centell-S exhibits the improvement of bioactive triterpenoids which are related to the biomarkers of neurodegenerative diseases. These promising results might be useful for the development of this standardised extract to become a more effective phytomedicine for neurodegenerative diseases.

Interrogating the Metabolomic Profile of Amyotrophic Lateral Sclerosis in the Post-Mortem Human Brain by Infrared Matrix-Assisted Laser Desorption Electrospray Ionization (IR-MALDESI) Mass Spectrometry Imaging (MSI)

Amyotrophic lateral sclerosis (ALS) is an idiopathic, fatal neurodegenerative disease characterized by progressive loss of motor function with an average survival time of 2-5 years after diagnosis. Due to the lack of signature biomarkers and heterogenous disease phenotypes, a definitive diagnosis of ALS can be challenging. Comprehensive investigation of this disease is imperative to discovering unique features to expedite the diagnostic process and improve diagnostic accuracy. Here, we present untargeted metabolomics by mass spectrometry imaging (MSI) for comparing sporadic ALS (sALS) and C9orf72 positive (C9Pos) post-mortem frontal cortex human brain tissues against a control cohort. The spatial distribution and relative abundance of metabolites were measured by infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) MSI for association to biological pathways. Proteomic studies on the same patients were completed via LC-MS/MS in a previous study, and results were integrated with imaging metabolomics results to enhance the breadth of molecular coverage. Utilizing METASPACE annotation platform and MSiPeakfinder, nearly 300 metabolites were identified across the sixteen samples, where 25 were identified as dysregulated between disease cohorts. The dysregulated metabolites were further examined for their relevance to alanine, aspartate, and glutamate metabolism, glutathione metabolism, and arginine and proline metabolism. The dysregulated pathways discussed are consistent with reports from other ALS studies. To our knowledge, this work is the first of its kind, reporting on the investigation of ALS post-mortem human brain tissue analyzed by multiomic MSI.

Clinical relevance of biomarkers, new therapeutic approaches, and role of post-translational modifications in the pathogenesis of Alzheimer's disease

Alzheimer's disease (AD) is a neurodegenerative disorder that causes progressive loss of cognitive functions like thinking, memory, reasoning, behavioral abilities, and social skills thus affecting the ability of a person to perform normal daily functions independently. There is no definitive cure for this disease, and treatment options available for the management of the disease are not very effective as well. Based on histopathology, AD is characterized by the accumulation of insoluble deposits of amyloid beta (Aβ) plaques and neurofibrillary tangles (NFTs). Although several molecular events contribute to the formation of these insoluble deposits, the aberrant post-translational modifications (PTMs) of AD-related proteins (like APP, Aβ, tau, and BACE1) are also known to be involved in the onset and progression of this disease. However, early diagnosis of the disease as well as the development of effective therapeutic approaches is impeded by lack of proper clinical biomarkers. In this review, we summarized the current status and clinical relevance of biomarkers from cerebrospinal fluid (CSF), blood and extracellular vesicles involved in onset and progression of AD. Moreover, we highlight the effects of several PTMs on the AD-related proteins, and provide an insight how these modifications impact the structure and function of proteins leading to AD pathology. Finally, for disease-modifying therapeutics, novel approaches, and targets are discussed for the successful treatment and management of AD.

Neurospecific Molecules Measured in Periphery in Humans: How Do They Correlate with the Brain Levels? A Systematic Review

Human brain state is usually estimated by brain-specific substances in peripheral tissues, but, for most analytes, a concordance between their content in the brain and periphery is unclear. In this systematic review, we summarized the investigated correlations in humans. PubMed was searched up to June 2022. We included studies measuring the same endogenous neurospecific analytes in the central nervous system and periphery in the same subjects. Not eligible were studies of cerebrospinal fluid, with significant blood–brain barrier disruption, of molecules with well-established blood-periphery concordance or measured in brain tumors. Seventeen studies were eligible. Four studies did not report on correlation and four revealed no significant correlation. Four molecules were examined twice. For BDNF, there was no correlation in both studies. For phenylalanine, glutamine, and glutamate, results were contradictory. Strong correlations were found for free tryptophan (r = 0.97) and translocator protein (r = 0.90). Thus, only for three molecules was there some certainty. BDNF in plasma or serum does not reflect brain content, whereas free tryptophan (in plasma) and translocator protein (in blood cells) can serve as peripheral biomarkers. We expect a breakthrough in the field with advanced in vivo metabolomic analyses, neuroimaging techniques, and blood assays for exosomes of brain origin.

Multi-Omics Techniques for Soybean Molecular Breeding

Soybean is a major crop that provides essential protein and oil for food and feed. Since its origin in China over 5000 years ago, soybean has spread throughout the world, becoming the second most important vegetable oil crop and the primary source of plant protein for global consumption. From early domestication and artificial selection through hybridization and ultimately molecular breeding, the history of soybean breeding parallels major advances in plant science throughout the centuries. Now, rapid progress in plant omics is ushering in a new era of precision design breeding, exemplified by the engineering of elite soybean varieties with specific oil compositions to meet various end-use targets. The assembly of soybean reference genomes, made possible by the development of genome sequencing technology and bioinformatics over the past 20 years, was a great step forward in soybean research. It facilitated advances in soybean transcriptomics, proteomics, metabolomics, and phenomics, all of which paved the way for an integrated approach to molecular breeding in soybean. In this review, we summarize the latest progress in omics research, highlight novel findings made possible by omics techniques, note current drawbacks and areas for further research, and suggest that an efficient multi-omics approach may accelerate soybean breeding in the future. This review will be of interest not only to soybean breeders but also to researchers interested in the use of cutting-edge omics technologies for crop research and improvement.