Investigating the Transition of Pre-Symptomatic to Symptomatic Huntington's Disease Status Based on Omics Data

Knocking down GRAMD1C expression reduces 6-OHDA-induced apoptosis in PC12 cells

Aim

To explore the differential genes in Parkinson's disease (PD) through a preliminary GEO database, and to investigate the possible mechanisms.

Materials and Methods

The PD differentially expressed genes (DEGs) were analyzed by the microarray method. Then, these DEGs were applied to KEGG and GO analyses to predict the related signaling pathways and molecular functions. Comparison of GRAMD1C expression levels in the putamen of normal and Parkinson's patients by bioinformatic analysis. PC12 cells were cultured to construct a 6-hydroxydopamine (6-OHDA)-induced Parkinson's cell model. RT-qPCR was performed to detect the efficiency of GRAMD1C siRNA. MTT assay was conducted to examine the proliferation of cells. Then, the apoptosis of each group of cells was measured by flow cytometry. Western blot was carried out to determine the expression of apoptosis-related proteins.

Results

Through bioinformatics, GRAMD1C was confirmed to be one of the most significantly upregulated genes in PD. Furthermore, GRAMD1C was notably enhanced in the PD patients and 6-OHDA-induced PC12 cells. Besides, 6-OHDA stimulation significantly reduced PC12 cell proliferation, and it reverted with the GRAMD1C siRNA. Moreover, the flow cytometry results showed that knockdown of GRAMD1C could effectively reduce the high apoptosis rate of PC12 cells induced by 6-OHDA treatment. Similarly, western blot results found that 6-OHDA stimulation markedly increased the expression levels of Bax and Caspase 3Caspase 3 and decreased the Bcl-2 expression in PC12 cells, and GRAMD1C knockdown reversed these changes.

Conclusion

GRAMD1C is upregulated in PD, and may affect the PD process through the apoptotic pathway.

A metabolomics study on carcinogenesis of ground-glass nodules

Objective

This study aimed to identify differential metabolites and key metabolic pathways between lung adenocarcinoma (LUAD) tissues and normal lung (NL) tissues using metabolomics techniques, to discover potential biomarkers for the early diagnosis of lung cancer.

Material and Methods

Forty-five patients with primary ground-glass nodules (GGN) identified on computed tomography imaging and who were willing to undergo surgery at Shanghai General Hospital from December 2021 to December 2022 were recruited to the study. All participants underwent video thoracoscopy surgery with segmental or wedge resection of the lung. Tissue samples for pathological examination were collected from the site of ground-glass nodules (GGN) lesion and 3 cm away from the lesion (NL). The pathology results were 35 lung adenocarcinoma (LUAD) cases (13 invasive adenocarcinoma, 14 minimally invasive adenocarcinoma, and eight adenocarcinoma in situ), 10 benign samples, and 45 NL tissues. For the untargeted metabolomics technique, 25 LUAD samples were assigned as the case group and 30 NL tissues as the control group. For the targeted metabolomics technique, ten LUAD samples were assigned as the case group and 15 NL tissues as the control group. Samples were analyzed by untargeted and targeted metabolomics, with liquid chromatography-tandem mass spectrometry detection used as part of the experimental procedure.

Results

Untargeted metabolomics revealed 164 differential metabolites between the case and control groups, comprising 110 up regulations and 54 down regulations. The main metabolic differences found by the untargeted method were organic acids and their derivatives. Targeted metabolomics revealed 77 differential metabolites between the case and control groups, comprising 69 up regulations and eight down regulations. The main metabolic changes found by the targeted method were fatty acids, amino acids, and organic acids. The levels of organic acids such as lactic acid, fumaric acid, and malic acid were significantly increased in LUAD tissue compared to NL. Specifically, an increased level of L-lactic acid was found by both untargeted (variable importance in projection [VIP] = 1.332, fold-change [FC] = 1.678, q = 0.000) and targeted metabolomics (VIP = 1.240, FC = 1.451, q = 0.043). Targeted metabolomics also revealed increased levels of fumaric acid (VIP = 1.481, FC = 1.764, q = 0.106) and L-malic acid (VIP = 1.376, FC = 1.562, q = 0.012). Most of the 20 differential fatty acids identified were downregulated, including dodecanoic acid (VIP = 1.416, FC = 0.378, q = 0.043) and tridecane acid (VIP = 0.880, FC = 0.780, q = 0.106). Furthermore, increased levels of differential amino acids were found in LUAD samples.

Conclusion

Lung cancer is a complex and heterogeneous disease with diverse genetic alterations. The study of metabolic profiles is a promising research field in this cancer type. Targeted and untargeted metabolomics revealed significant differences in metabolites between LUAD and NL tissues, including elevated levels of organic acids, decreased levels of fatty acids, and increased levels of amino acids. These metabolic features provide valuable insights into LUAD pathogenesis and can potentially serve as biomarkers for prognosis and therapy response.

Deregulated Transcriptome as a Platform for Adrenal Huntington's Disease-Related Pathology

Huntington's disease (HD) is a neurodegenerative disorder that affects mainly the central nervous system (CNS) by inducing progressive deterioration in both its structure and function. In recent years, there has been growing interest in the impact of HD on peripheral tissue function. Herein, we used the R6/2 mouse model of HD to investigate the influence of the disease on adrenal gland functioning. A transcriptomic analysis conducted using a well-established quantitative method, an Affymetrix array, revealed changes in gene expression in the R6/2 model compared to genetic background controls. For the first time, we identified disruptions in cholesterol and sterol metabolism, blood coagulation, and xenobiotic metabolism in HD adrenal glands. This study showed that the disrupted expression of these genes may contribute to the underlying mechanisms of Huntington's disease. Our findings may contribute to developing a better understanding of Huntington's disease progression and aid in the development of novel diagnostic or therapeutic approaches.

Metabolism-related biomarkers, molecular classification, and immune infiltration in diabetic ulcers with validation

Diabetes mellitus (DM) can lead to diabetic ulcers (DUs), which are the most severe complications. Due to the need for more accurate patient classifications and diagnostic models, treatment and management strategies for DU patients still need improvement. The difficulty of diabetic wound healing is caused closely related to biological metabolism and immune chemotaxis reaction dysfunction. Therefore, the purpose of our study is to identify metabolic biomarkers in patients with DU and construct a molecular subtype-specific prognostic model that is highly accurate and robust. RNA-sequencing data for DU samples were obtained from the Gene Expression Omnibus (GEO) database. DU patients and normal individuals were compared regarding the expression of metabolism-related genes (MRGs). Then, a novel diagnostic model based on MRGs was constructed with the random forest algorithm, and classification performance was evaluated utilizing receiver operating characteristic (ROC) analysis. The biological functions of MRGs-based subtypes were investigated using consensus clustering analysis. A principal component analysis (PCA) was conducted to determine whether MRGs could distinguish between subtypes. We also examined the correlation between MRGs and immune infiltration. Lastly, qRT-PCR was utilized to validate the expression of the hub MRGs with clinical validations and animal experimentations. Firstly, 8 metabolism-related hub genes were obtained by random forest algorithm, which could distinguish the DUs from normal samples validated by the ROC curves. Secondly, DU samples could be consensus clustered into three molecular classifications by MRGs, verified by PCA analysis. Thirdly, associations between MRGs and immune infiltration were confirmed, with LYN and Type 1 helper cell significantly positively correlated; RHOH and TGF-β family remarkably negatively correlated. Finally, clinical validations and animal experiments of DU skin tissue samples showed that the expressions of metabolic hub genes in the DU groups were considerably upregulated, including GLDC, GALNT6, RHOH, XDH, MMP12, KLK6, LYN, and CFB. The current study proposed an auxiliary MRGs-based DUs model while proposing MRGs-based molecular clustering and confirmed the association with immune infiltration, facilitating the diagnosis and management of DU patients and designing individualized treatment plans.

Axonal energy metabolism, and the effects in aging and neurodegenerative diseases

Human studies consistently identify bioenergetic maladaptations in brains upon aging and neurodegenerative disorders of aging (NDAs), such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and Amyotrophic lateral sclerosis. Glucose is the major brain fuel and glucose hypometabolism has been observed in brain regions vulnerable to aging and NDAs. Many neurodegenerative susceptible regions are in the topological central hub of the brain connectome, linked by densely interconnected long-range axons. Axons, key components of the connectome, have high metabolic needs to support neurotransmission and other essential activities. Long-range axons are particularly vulnerable to injury, neurotoxin exposure, protein stress, lysosomal dysfunction, etc. Axonopathy is often an early sign of neurodegeneration. Recent studies ascribe axonal maintenance failures to local bioenergetic dysregulation. With this review, we aim to stimulate research in exploring metabolically oriented neuroprotection strategies to enhance or normalize bioenergetics in NDA models. Here we start by summarizing evidence from human patients and animal models to reveal the correlation between glucose hypometabolism and connectomic disintegration upon aging/NDAs. To encourage mechanistic investigations on how axonal bioenergetic dysregulation occurs during aging/NDAs, we first review the current literature on axonal bioenergetics in distinct axonal subdomains: axon initial segments, myelinated axonal segments, and axonal arbors harboring pre-synaptic boutons. In each subdomain, we focus on the organization, activity-dependent regulation of the bioenergetic system, and external glial support. Second, we review the mechanisms regulating axonal nicotinamide adenine dinucleotide (NAD+) homeostasis, an essential molecule for energy metabolism processes, including NAD+ biosynthetic, recycling, and consuming pathways. Third, we highlight the innate metabolic vulnerability of the brain connectome and discuss its perturbation during aging and NDAs. As axonal bioenergetic deficits are developing into NDAs, especially in asymptomatic phase, they are likely exaggerated further by impaired NAD+ homeostasis, the high energetic cost of neural network hyperactivity, and glial pathology. Future research in interrogating the causal relationship between metabolic vulnerability, axonopathy, amyloid/tau pathology, and cognitive decline will provide fundamental knowledge for developing therapeutic interventions.

Mitochondrial dysfunction in chromaffin cells from the R6/1 mouse model of Huntington's disease: Impact on exocytosis and calcium current regulation

From a pathogenic perspective, Huntington's disease (HD) is being considered as a synaptopathy. As such, alterations in brain neurotransmitter release occur. As the activity of the sympathoadrenal axis is centrally controlled, deficits in the exocytotic release of catecholamine release may also occur. In fact, in chromaffin cells (CCs) of the adrenal medulla of the R6/1 model of HD, decrease of secretion and altered kinetics of the exocytotic fusion pore have been reported. Those alterations could be linked to mitochondrial deficits occurring in peripheral CCs, similar to those described in brain mitochondria. Here we have inquired about alterations in mitochondrial structure and function and their impact on exocytosis and calcium channel currents (I_Ca). We have monitored various parameters linked to those events, in wild type (WT) and the R6/1 mouse model of HD at a pre-disease stage (2 months age, 2 m), and when motor deficits are present (7 months age, 7 m). In isolated CCs from 7 m and in the adrenal medulla of R6/1 mice, we found the following alterations (with respect 7 m WT mice): (i) augmented fragmented mitochondria and oxidative stress with increased oxidized glutathione; (ii) decreased basal and maximal respiration; (iii) diminution of ATP cell levels; (iv) mitochondrial depolarization; (v) drastic decrease of catecholamine release with poorer potentiation by protonophore FCCP; (vi) decreased I_Ca inhibition by FCCP; and (vii) lesser potentiation by BayK8644 of I_Ca and smaller prolongation of current deactivation. Of note was the fact several of these alterations were already manifested in CCs from 2 m R6/1 mice at pre-disease stages. Based on those results, a plausible hypothesis can be raised in the sense that altered mitochondrial function seems to be an early primary event in HD pathogenesis. This is in line with an increasing number of mitochondrial, metabolic, and inflammatory alterations being recently reported in various HD peripheral tissues.

Integrated Bioinformatics Analysis of Shared Genes, miRNA, Biological Pathways and Their Potential Role as Therapeutic Targets in Huntington's Disease Stages

Huntington's Disease (HD) is a progressive neurodegenerative disease caused by CAG repeat expansion in the huntingtin gene (HTT). The HTT gene was the first disease-associated gene mapped to a chromosome, but the pathophysiological mechanisms, genes, proteins or miRNAs involved in HD remain poorly understood. Systems bioinformatics approaches can divulge the synergistic relationships of multiple omics data and their integration, and thus provide a holistic approach to understanding diseases. The purpose of this study was to identify the differentially expressed genes (DEGs), HD-related gene targets, pathways and miRNAs in HD and, more specifically, between the pre-symptomatic and symptomatic HD stages. Three publicly available HD datasets were analysed to obtain DEGs for each HD stage from each dataset. In addition, three databases were used to obtain HD-related gene targets. The shared gene targets between the three public databases were compared, and clustering analysis was performed on the common shared genes. Enrichment analysis was performed on (i) DEGs identified for each HD stage in each dataset, (ii) gene targets from the public databases and (iii) the clustering analysis results. Furthermore, the hub genes shared between the public databases and the HD DEGs were identified, and topological network parameters were applied. Identification of HD-related miRNAs and their gene targets was obtained, and a miRNA-gene network was constructed. Enriched pathways identified for the 128 common genes revealed pathways linked to multiple neurodegeneration diseases (HD, Parkinson's disease, Spinocerebellar ataxia), MAPK and HIF-1 signalling pathways. Eighteen HD-related hub genes were identified based on network topological analysis of MCC, degree and closeness. The highest-ranked genes were FoxO3 and CASP3, CASP3 and MAP2 were found for betweenness and eccentricity and CREBBP and PPARGC1A were identified for the clustering coefficient. The miRNA-gene network identified eleven miRNAs (mir-19a-3p, mir-34b-3p, mir-128-5p, mir-196a-5p, mir-34a-5p, mir-338-3p, mir-23a-3p and mir-214-3p) and eight genes (ITPR1, CASP3, GRIN2A, FoxO3, TGM2, CREBBP, MTHFR and PPARGC1A). Our work revealed that various biological pathways seem to be involved in HD either during the pre-symptomatic or symptomatic stages of HD. This may offer some clues for the molecular mechanisms, pathways and cellular components underlying HD and how these may act as potential therapeutic targets for HD.

Metabolomic Footprint of Disrupted Energetics and Amino Acid Metabolism in Neurodegenerative Diseases: Perspectives for Early Diagnosis and Monitoring of Therapy

The prevalence of neurodegenerative diseases (NDs) is increasing due to the aging population and improved longevity. They are characterized by a range of pathological hallmarks, including protein aggregation, mitochondrial dysfunction, and oxidative stress. The aim of this review is to summarize the alterations in brain energy and amino acid metabolism in Alzheimer’s disease (AD), Parkinson’s disease (PD), and Huntington’s disease (HD). Based on our findings, we proposed a group of selected metabolites related to disturbed energy or mitochondrial metabolism as potential indicators or predictors of disease. We also discussed the hidden challenges of metabolomics studies in NDs and proposed future directions in this field. We concluded that biochemical parameters of brain energy metabolism disruption (obtained with metabolomics) may have potential application as a diagnostic tool for the diagnosis, prediction, and monitoring of the effectiveness of therapies for NDs. However, more studies are needed to determine the sensitivity of the proposed candidates. We suggested that the most valuable biomarkers for NDs studies could be groups of metabolites combined with other neuroimaging or molecular techniques. To attain clinically applicable results, the integration of metabolomics with other “omic” techniques might be required.

Is bRaQCing bad? New roles for ribosome associated quality control factors in stress granule regulation

Maintenance of proteostasis is of utmost importance to cellular viability and relies on the coordination of many post-transcriptional processes to respond to stressful stimuli. Stress granules (SGs) are RNA–protein condensates that form after translation initiation is inhibited, such as during the integrated stress response (ISR), and may facilitate cellular adaptation to stress. The ribosome-associated quality control (RQC) pathway is a critical translation monitoring system that recognizes aberrant mRNAs encoding potentially toxic nascent peptides to target them for degradation. Both SG regulation and the RQC pathway are directly associated with translation regulation, thus it is of no surprise recent developments have demonstrated a connection between them. VCP's function in the stress activated RQC pathway, ribosome collisions activating the ISR, and the regulation of the 40S ribosomal subunit by canonical SG proteins during the RQC all connect SGs to the RQC pathway. Because mutations in genes that are involved in both SG and RQC regulation are associated with degenerative and neurological diseases, understanding the coordination and interregulation of SGs and RQC may shed light on disease mechanisms. This minireview will highlight recent advances in understanding how SGs and the RQC pathway interact in health and disease contexts.

A Novel Huntington's Disease Assessment Platform to Support Future Drug Discovery and Development

Huntington's disease (HD) is a lethal neurodegenerative disorder without efficient therapeutic options. The inefficient translation from preclinical and clinical research into clinical use is mainly attributed to the lack of (i) understanding of disease initiation, progression, and involved molecular mechanisms; (ii) knowledge of the possible HD target space and general data awareness; (iii) detailed characterizations of available disease models; (iv) better suitable models; and (v) reliable and sensitive biomarkers. To generate robust HD-like symptoms in a mouse model, the neomycin resistance cassette was excised from zQ175 mice, generating a new line: zQ175^Δneo. We entirely describe the dynamics of behavioral, neuropathological, and immunohistological changes from 15-57 weeks of age. Specifically, zQ175^Δneo mice showed early astrogliosis from 15 weeks; growth retardation, body weight loss, and anxiety-like behaviors from 29 weeks; motor deficits and reduced muscular strength from 36 weeks; and finally slight microgliosis at 57 weeks of age. Additionally, we collected the entire bioactivity network of small-molecule HD modulators in a multitarget dataset (HD_MDS). Hereby, we uncovered 358 unique compounds addressing over 80 different pharmacological targets and pathways. Our data will support future drug discovery approaches and may serve as useful assessment platform for drug discovery and development against HD.

Novel molecular mechanisms in Alzheimer’s disease: The potential role of DEK in disease pathogenesis

Alzheimer’s disease and age-related dementias (AD/ADRD) are debilitating diseases that exact a significant physical, emotional, cognitive, and financial toll on the individual and their social network. While genetic risk factors for early-onset AD have been identified, the molecular and genetic drivers of late-onset AD, the most common subtype, remain a mystery. Current treatment options are limited for the 35 million people in the United States with AD/ADRD. Thus, it is critically important to identify novel molecular mechanisms of dementia-related pathology that may be targets for the development of new interventions. Here, we summarize the overarching concepts regarding AD/ADRD pathogenesis. Then, we highlight one potential molecular driver of AD/ADRD, the chromatin remodeling protein DEK. We discuss in vitro, in vivo, and ex vivo findings, from our group and others, that link DEK loss with the cellular, molecular, and behavioral signatures of AD/ADRD. These include associations between DEK loss and cellular and molecular hallmarks of AD/ADRD, including apoptosis, Tau expression, and Tau hyperphosphorylation. We also briefly discuss work that suggests sex-specific differences in the role of DEK in AD/ADRD pathogenesis. Finally, we discuss future directions for exploiting the DEK protein as a novel player and potential therapeutic target for the treatment of AD/ADRD.

In silico gene expression and pathway analysis of DEK in the human brain across the lifespan

DEK, a chromatin-remodelling phosphoprotein, is associated with various functions and biological pathways in the periphery, including inflammation, oncogenesis, DNA repair, and transcriptional regulation. We recently identified an association between DEK loss and central nervous system diseases, such as Alzheimer's. To understand DEK's potential role in disease, it is critical to characterize DEK in healthy human brain to distinguish between neural DEK expression and function in healthy versus diseased states like dementia. We utilized two public databases, BrainCloud and Human Brain Transcriptome, and analysed DEK mRNA expression across the lifespan in learning and memory relevant brain regions. Since DEK loss induces phenotypes associated with brain ageing (e.g., DNA damage and apoptosis), we hypothesized that neural DEK expression may be highest during foetal development and lower in elderly individuals. In agreement with this hypothesis, DEK was most prominently expressed during foetal development in all queried forebrain areas, relative to other ages. Consistent with its roles in the periphery, pathways related to DEK in the brain were associated with cellular proliferation, DNA replication and repair, apoptosis, and inflammation. We also found novel neural development-relevant pathways (e.g., synaptic transmission, neurite outgrowth, and myelination) to be enriched from genes correlated with DEK expression. These findings suggest that DEK is important for human brain development. Overall, we highlight age-related changes in neural DEK expression across the human lifespan and illuminate novel biological pathways associated with DEK that are distinct from normal brain ageing. These findings may further our understanding of how DEK impacts brain function and disease susceptibility.

Brain Epitranscriptomic Analysis Revealed Altered A-to-I RNA Editing in Septic Patients

Recent studies suggest that RNA editing is associated with impaired brain function and neurological and psychiatric disorders. However, the role of A-to-I RNA editing during sepsis-associated encephalopathy (SAE) remains unclear. In this study, we analyzed adenosine-to-inosine (A-to-I) RNA editing in postmortem brain tissues from septic patients and controls. A total of 3024 high-confidence A-to-I RNA editing sites were identified. In sepsis, there were fewer A-to-I RNA editing genes and editing sites than in controls. Among all A-to-I RNA editing sites, 42 genes showed significantly differential RNA editing, with 23 downregulated and 19 upregulated in sepsis compared to controls. Notably, more than 50% of these genes were highly expressed in the brain and potentially related to neurological diseases. Notably, cis-regulatory analysis showed that the level of RNA editing in six differentially edited genes was significantly correlated with the gene expression, including HAUS augmin-like complex subunit 2 (HAUS2), protein phosphatase 3 catalytic subunit beta (PPP3CB), hook microtubule tethering protein 3 (HOOK3), CUB and Sushi multiple domains 1 (CSMD1), methyltransferase-like 7A (METTL7A), and kinesin light chain 2 (KLC2). Furthermore, enrichment analysis showed that fewer gene functions and KEGG pathways were enriched by edited genes in sepsis compared to controls. These results revealed alteration of A-to-I RNA editing in the human brain associated with sepsis, thus providing an important basis for understanding its role in neuropathology in SAE.

Integrated Transcriptomics and Metabolomics Analyses of Stress-Induced Murine Hair Follicle Growth Inhibition

Psychological stress plays an important role in hair loss, but the underlying mechanisms are not well-understood, and the effective therapies available to regrow hair are rare. In this study, we established a chronic restraint stress (CRS)-induced hair growth inhibition mouse model and performed a comprehensive analysis of metabolomics and transcriptomics. Metabolomics data analysis showed that the primary and secondary metabolic pathways, such as carbohydrate metabolism, amino acid metabolism, and lipid metabolism were significantly altered in skin tissue of CRS group. Transcriptomics analysis also showed significant changes of genes expression profiles involved in regulation of metabolic processes including arachidonic acid metabolism, glutathione metabolism, glycolysis gluconeogenesis, nicotinate and nicotinamide metabolism, purine metabolism, retinol metabolism and cholesterol metabolism. Furthermore, RNA-Seq analyses also found that numerous genes associated with metabolism were significantly changed, such as Hk-1, in CRS-induced hair growth inhibition. Overall, our study supplied new insights into the hair growth inhibition induced by CRS from the perspective of integrated metabolomics and transcriptomics analyses.

Nuclear and cytoplasmic huntingtin inclusions exhibit distinct biochemical composition, interactome and ultrastructural properties

Despite the strong evidence linking the aggregation of the Huntingtin protein (Htt) to the pathogenesis of Huntington's disease (HD), the mechanisms underlying Htt aggregation and neurodegeneration remain poorly understood. Herein, we investigated the ultrastructural properties and protein composition of Htt cytoplasmic and nuclear inclusions in mammalian cells and primary neurons overexpressing mutant exon1 of the Htt protein. Our findings provide unique insight into the ultrastructural properties of cytoplasmic and nuclear Htt inclusions and their mechanisms of formation. We show that Htt inclusion formation and maturation are complex processes that, although initially driven by polyQ-dependent Htt aggregation, also involve the polyQ and PRD domain-dependent sequestration of lipids and cytoplasmic and cytoskeletal proteins related to HD dysregulated pathways; the recruitment and accumulation of remodeled or dysfunctional membranous organelles, and the impairment of the protein quality control and degradation machinery. We also show that nuclear and cytoplasmic Htt inclusions exhibit distinct biochemical compositions and ultrastructural properties, suggesting different mechanisms of aggregation and toxicity.

Current State of Metabolomics Research in Meat Quality Analysis and Authentication

In the past decades, as an emerging omic, metabolomics has been widely used in meat science research, showing promise in meat quality analysis and meat authentication. This review first provides a brief overview of the concept, analytical techniques, and analysis workflow of metabolomics. Additionally, the metabolomics research in quality analysis and authentication of meat is comprehensively described. Finally, the limitations, challenges, and future trends of metabolomics application in meat quality analysis and meat authentication are critically discussed. We hope to provide valuable insights for further research in meat quality.

Identification of Novel Serum Metabolic Biomarkers as Indicators in the Progression of Intravenous Leiomyomatosis: A High Performance Liquid Chromatography-Tandem Mass Spectrometry-Based Study

Background

Intravenous leiomyomatosis (IVL) is a rare estrogen-dependent neoplasm. However, identifiable and reliable biomarkers are still not available for clinical application, especially for the diagnosis and prognosis of the disease.

Methods

In the present study, 30 patients with IVL and 30 healthy controls were recruited. Serum samples were isolated from these participants for further high performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) analysis to study metabolomics alterations and identify differentially expressed metabolites based on orthogonal partial least-squares discriminant analysis (OPLS-DA). Subsequently, lasso regression analysis and a generalized linear regression model were applied to screen out hub metabolites associated with the progression of IVL.

Results

First, 16 metabolites in the positive ion mode were determined from the 240 identifiable metabolites at the superclass level, with ten metabolites upregulated in the IVL group and the remaining six metabolites downregulated. Our data further proved that four metabolites [hypoxanthine, acetylcarnitine, glycerophosphocholine, and hydrocortisone (cortisol)] were closely related to the oncogenesis of IVL. Hypoxanthine and glycerophosphocholine might function as protective factors in the development of IVL (OR = 0.19 or 0.02, respectively). Nevertheless, acetylcarnitine and hydrocortisone (cortisol), especially the former, might serve as risk indicators for the disease to promote the development or recurrence of IVL (OR = 18.16 or 2.10, respectively). The predictive accuracy of these hub metabolites was further validated by the multi-class receiver operator characteristic curve analysis (ROC) with the Scikit-learn algorithms.

Conclusion

Four hub metabolites were finally determined via comprehensive bioinformatics analysis, and these substances could potentially serve as novel biomarkers in predicting the prognosis or progression of IVL.

Functional multigenic variations associated with hodgkin lymphoma

INTRODUCTION

The current study aimed to describe genotypes associated with Hodgkin lymphoma (HL) in a cohort of Saudi and non-Saudi patients and discuss their possible susceptibility to HL.

METHODS

We studied clinical, histopathological, and laboratory findings of HL patients admitted over 12 years duration, at King Fahd University Hospital, KSA. The genomic DNAs of HL patients (n = 61) and normal control subjects (n = 36) were extracted, and genotyping was performed using the Illumina human exome bead chip. Set of HL patients and set of normal controls were included in this study.

RESULTS

A total of 35 DNA variants were found to be highly significant with the P-value <9.90 × 10^-11 among 243 345 exonic biomarkers and obeying the Hardy-Weinberg equilibrium. Nine, MEGF11-rs150945752 (P-value 1.20 × 10^-12 ), CACNA1I- s58055559 (P-value 1.93 × 10^-12 ), DECR2-rs146760080 (P-value 2.19 × 10^-12 ), STAB1-rs143894786 (P-value 2.45 × 10^-12 ), ZNF526-rs144433879 (P-value 2.76 × 10^-12 ), CPLANE1-rs200612080 (P-value 3.77 × 10^-12 ), DLK1-rs1058009 (P-value 5.95 × 10^-12 ), RTN4RL2-rs61745214 (P-value 7.71 × 10^-12 ), and PGRMC1-rs145582672 (P-value 8.56 × 10^-12 ), exonic variants on chromosomes 15, 22, and 16 were highly associated with HL cases. THE HIGHLY SIGNIFICANT HAPLOTYPES AT CHROMOSOME 3: rs143894786G; rs149982219G with P-value = 3.43 × 10^-14 was found to be the risk haplotype for the HL patients. The opposite alleles at chromosome 3: rs143894786A; rs149982219G is protective with P-value = 2.46 × 10^-12 . Maximum number of SNPs at the chromosome 19: rs144433879C; rs181265966G; rs201144421C; rs145591797G; rs200560875G; rs77270337G (risk P-value = 2.24 × 10^-12 ) and its opposite allele rs144433879A; rs181265966A; rs201144421T; rs145591797A; rs200560875A; rs77270337A (protective P-value = 2.60 × 10^-9 ) were found to be associated haplotype with the HL and controls, respectively, in Saudi population.

CONCLUSION

Our study concludes that the HL is genetically heterogeneous with multigene causation.