Discovery of new epigenomics-based biomarkers and the early diagnosis of neurodegenerative diseases

Potential application of aptamers combined with DNA nanoflowers in neurodegenerative diseases

The efficacy of neurotherapeutic drugs hinges on their ability to traverse the blood-brain barrier and access the brain, which is crucial for treating or alleviating neurodegenerative diseases (NDs). Given the absence of definitive cures for NDs, early diagnosis and intervention become paramount in impeding disease progression. However, conventional therapeutic drugs and existing diagnostic approaches must meet clinical demands. Consequently, there is a pressing need to advance drug delivery systems and early diagnostic methods tailored for NDs. Certain aptamers endowed with specific functionalities find widespread utility in the targeted therapy and diagnosis of NDs. DNA nanoflowers (DNFs), distinctive flower-shaped DNA nanomaterials, are intricately self-assembled through rolling ring amplification (RCA) of circular DNA templates. Notably, imbuing DNFs with diverse functionalities becomes seamlessly achievable by integrating aptamer sequences with specific functions into RCA templates, resulting in a novel nanomaterial, aptamer-bound DNFs (ADNFs) that amalgamates the advantageous features of both components. This article delves into the characteristics and applications of aptamers and DNFs, exploring the potential or application of ADNFs in drug-targeted delivery, direct treatment, early diagnosis, etc. The objective is to offer prospective ideas for the clinical treatment or diagnosis of NDs, thereby contributing to the ongoing efforts in this critical field.

Electrochemical Biosensor for Point-of-Care Testing of Low-Abundance Biomarkers of Neurological Diseases

The neurofilament protein light chain (NEFL) is a potential biomarker of neurodegenerative diseases, and interleukin-6 (IL-6) is also closely related to neuroinflammation. Especially, NEFL and IL-6 are the two most low-abundance known protein markers of neurological diseases, making their detection very important for the early diagnosis and prognosis prediction of such kinds of diseases. Nevertheless, quantitative detection of low concentrations of NEFL and IL-6 in serum remains quite difficult, especially in the point-of-care test (POCT). Herein, we developed a portable, sensitive electrochemical biosensor combined with smartphones that can be applied to multiple scenarios for the quantitative detection of NEFL and IL-6, meeting the need of the POCT. We used a double-antibody sandwich configuration combined with polyenzyme-catalyzed signal amplification to improve the sensitivity of the biosensor for the detection of NEFL and IL-6 in sera. We could detect NEFL as low as 5.22 pg/mL and IL-6 as low as 3.69 pg/mL of 6 μL of serum within 2 h, demonstrating that this electrochemical biosensor worked well with serum systems. Results also showed its superior detection capabilities over those of high-sensitivity ELISA for serum samples. Importantly, by detecting NEFL and IL-6 in sera, the biosensor showed its potential for the POCT model detection of all known biomarkers of neurological diseases, making it possible for the mass screening of patients with neurodegenerative diseases.

Integrated Analysis of Cortex Single-Cell Transcriptome and Serum Proteome Reveals the Novel Biomarkers in Alzheimer's Disease

Blood-based proteomic analysis is a routine practice for detecting the biomarkers of human disease. The results obtained from blood alone cannot fully reflect the alterations of nerve cells, including neurons and glia cells, in Alzheimer's disease (AD) brains. Therefore, the present study aimed to investigate novel potential AD biomarker candidates, through an integrated multi-omics approach in AD. We propose a comprehensive strategy to identify high-confidence candidate biomarkers by integrating multi-omics data from AD, including single-nuclei RNA sequencing (snRNA-seq) datasets of the prefrontal and entorhinal cortices, as wells as serum proteomic datasets. We first quantified a total of 124,658 nuclei, 8 cell types, and 3701 differentially expressed genes (DEGs) from snRNA-seq dataset of 30 human cortices, as well as 1291 differentially expressed proteins (DEPs) from serum proteomic dataset of 11 individuals. Then, ten DEGs/DEPs (NEBL, CHSY3, STMN2, MARCKS, VIM, FGD4, EPB41L2, PLEKHG1, PTPRZ1, and PPP1R14A) were identified by integration analysis of snRNA-seq and proteomics data. Finally, four novel candidate biomarkers (NEBL, EPB41L2, FGD4, and MARCKS) for AD further stood out, according to bioinformatics analysis, and they were verified by enzyme-linked immunosorbent assay (ELISA) verification. These candidate biomarkers are related to the regulation process of the actin cytoskeleton, which is involved in the regulation of synaptic loss in the AD brain tissue. Collectively, this study identified novel cell type-related biomarkers for AD by integrating multi-omics datasets from brains and serum. Our findings provided new targets for the clinical treatment and prognosis of AD.

Potential diagnostic biomarkers for schizophrenia

Schizophrenia (SCH) is a complex and severe mental disorder with high prevalence, disability, mortality and carries a heavy disease burden, the lifetime prevalence of SCH is around 0.7%-1.0%, which has a profound impact on the individual and society. In the clinical practice of SCH, key problems such as subjective diagnosis, experiential treatment, and poor overall prognosis are still challenging. In recent years, some exciting discoveries have been made in the research on objective biomarkers of SCH, mainly focusing on genetic susceptibility genes, metabolic indicators, immune indices, brain imaging, electrophysiological characteristics. This review aims to summarize the biomarkers that may be used for the prediction and diagnosis of SCH.

The Perspectives of Early Diagnosis of Schizophrenia Through the Detection of Epigenomics-Based Biomarkers in iPSC-Derived Neurons

The lack of early diagnostic biomarkers for schizophrenia greatly limits treatment options that deliver therapeutic agents to affected cells at a timely manner. While previous schizophrenia biomarker research has identified various biological signals that are correlated with certain diseases, their reliability and practicality as an early diagnostic tool remains unclear. In this article, we discuss the use of atypical epigenetic and/or consequent transcriptional alterations (ETAs) as biomarkers of early-stage schizophrenia. Furthermore, we review the viability of discovering and applying these biomarkers through the use of cutting-edge technologies such as human induced pluripotent stem cell (iPSC)-derived neurons, brain models, and single-cell level analyses.

Pharmacometabonomics: data processing and statistical analysis

Individual variations in drug efficacy, side effects and adverse drug reactions are still challenging that cannot be ignored in drug research and development. The aim of pharmacometabonomics is to better understand the pharmacokinetic properties of drugs and monitor the drug effects on specific metabolic pathways. Here, we systematically reviewed the recent technological advances in pharmacometabonomics for better understanding the pathophysiological mechanisms of diseases as well as the metabolic effects of drugs on bodies. First, the advantages and disadvantages of all mainstream analytical techniques were compared. Second, many data processing strategies including filtering, missing value imputation, quality control-based correction, transformation, normalization together with the methods implemented in each step were discussed. Third, various feature selection and feature extraction algorithms commonly applied in pharmacometabonomics were described. Finally, the databases that facilitate current pharmacometabonomics were collected and discussed. All in all, this review provided guidance for researchers engaged in pharmacometabonomics and metabolomics, and it would promote the wide application of metabolomics in drug research and personalized medicine.