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Lteif C, Huang Y, Guerra LA, Gawronski BE, Duarte JD. Using Omics to Identify Novel Therapeutic Targets in Heart Failure. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004398. [PMID: 38766848 DOI: 10.1161/circgen.123.004398] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Omics refers to the measurement and analysis of the totality of molecules or biological processes involved within an organism. Examples of omics data include genomics, transcriptomics, epigenomics, proteomics, metabolomics, and more. In this review, we present the available literature reporting omics data on heart failure that can inform the development of novel treatments or innovative treatment strategies for this disease. This includes polygenic risk scores to improve prediction of genomic data and the potential of multiomics to more efficiently identify potential treatment targets for further study. We also discuss the limitations of omic analyses and the barriers that must be overcome to maximize the utility of these types of studies. Finally, we address the current state of the field and future opportunities for using multiomics to better personalize heart failure treatment strategies.
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Affiliation(s)
- Christelle Lteif
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL
| | - Yimei Huang
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL
| | - Leonardo A Guerra
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL
| | - Brian E Gawronski
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL
| | - Julio D Duarte
- Center for Pharmacogenomics and Precision Medicine, Department of Pharmacotherapy and Translational Research, University of Florida College of Pharmacy, Gainesville, FL
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Parmar R, Pickering H, Ahn R, Rossetti M, Gjertson DW, Ruffin F, Chan LC, Fowler VG, Yeaman MR, Reed EF. Integrated transcriptomic analysis reveals immune signatures distinguishing persistent versus resolving outcomes in MRSA bacteremia. Front Immunol 2024; 15:1373553. [PMID: 38846955 PMCID: PMC11153731 DOI: 10.3389/fimmu.2024.1373553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 05/02/2024] [Indexed: 06/09/2024] Open
Abstract
Introduction Staphylococcus aureus bacteremia (SAB) is a life-threatening infection particularly involving methicillin-resistant S. aureus (MRSA). In contrast to resolving MRSA bacteremia (RB), persistent MRSA bacteremia (PB) blood cultures remain positive despite appropriate antibiotic treatment. Host immune responses distinguishing PB vs. RB outcomes are poorly understood. Here, integrated transcriptomic, IL-10 cytokine levels, and genomic analyses sought to identify signatures differentiating PB vs. RB outcomes. Methods Whole-blood transcriptomes of propensity-matched PB (n=28) versus RB (n=30) patients treated with vancomycin were compared in one independent training patient cohort. Gene expression (GE) modules were analyzed and prioritized relative to host IL-10 cytokine levels and DNA methyltransferase-3A (DNMT3A) genotype. Results Differential expression of T and B lymphocyte gene expression early in MRSA bacteremia discriminated RB from PB outcomes. Significant increases in effector T and B cell signaling pathways correlated with RB, lower IL-10 cytokine levels and DNMT3A heterozygous A/C genotype. Importantly, a second PB and RB patient cohort analyzed in a masked manner demonstrated high predictive accuracy of differential signatures. Discussion Collectively, the present findings indicate that human PB involves dysregulated immunity characterized by impaired T and B cell responses associated with excessive IL-10 expression in context of the DNMT3A A/A genotype. These findings reveal distinct immunologic programs in PB vs. RB outcomes, enable future studies to define mechanisms by which host and/or pathogen drive differential signatures and may accelerate prediction of PB outcomes. Such prognostic assessment of host risk could significantly enhance early anti-infective interventions to avert PB and improve patient outcomes.
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Affiliation(s)
- Rajesh Parmar
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Harry Pickering
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Richard Ahn
- Department of Microbiology, Immunology, & Molecular Genetics, University of California Los Angeles, Los Angeles, CA, United States
| | - Maura Rossetti
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - David W. Gjertson
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Felicia Ruffin
- Division of Infectious Diseases, Duke University, Durham, NC, United States
| | - Liana C. Chan
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
- Divisions of Molecular Medicine and Infectious Diseases, Los Angeles County Harbor-UCLA Medical Center, Torrance, CA, United States
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Vance G. Fowler
- Division of Infectious Diseases, Duke University, Durham, NC, United States
| | - Michael R. Yeaman
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
- Divisions of Molecular Medicine and Infectious Diseases, Los Angeles County Harbor-UCLA Medical Center, Torrance, CA, United States
- Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, United States
| | - Elaine F. Reed
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
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Xie X, Zhou R, Fang Z, Zhang Y, Wang Q, Liu X. Seeing beyond words: Visualizing autism spectrum disorder biomarker insights. Heliyon 2024; 10:e30420. [PMID: 38694128 PMCID: PMC11061761 DOI: 10.1016/j.heliyon.2024.e30420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 04/24/2024] [Accepted: 04/25/2024] [Indexed: 05/04/2024] Open
Abstract
Objective This study employs bibliometric and visual analysis to elucidate global research trends in Autism Spectrum Disorder (ASD) biomarkers, identify critical research focal points, and discuss the potential integration of diverse biomarker modalities for precise ASD assessment. Methods A comprehensive bibliometric analysis was conducted using data from the Web of Science Core Collection database until December 31, 2022. Visualization tools, including R, VOSviewer, CiteSpace, and gCLUTO, were utilized to examine collaborative networks, co-citation patterns, and keyword associations among countries, institutions, authors, journals, documents, and keywords. Results ASD biomarker research emerged in 2004, accumulating a corpus of 4348 documents by December 31, 2022. The United States, with 1574 publications and an H-index of 213, emerged as the most prolific and influential country. The University of California, Davis, contributed significantly with 346 publications and an H-index of 69, making it the leading institution. Concerning journals, the Journal of Autism and Developmental Disorders, Autism Research, and PLOS ONE were the top three publishers of ASD biomarker-related articles among a total of 1140 academic journals. Co-citation and keyword analyses revealed research hotspots in genetics, imaging, oxidative stress, neuroinflammation, gut microbiota, and eye tracking. Emerging topics included "DNA methylation," "eye tracking," "metabolomics," and "resting-state fMRI." Conclusion The field of ASD biomarker research is dynamically evolving. Future endeavors should prioritize individual stratification, methodological standardization, the harmonious integration of biomarker modalities, and longitudinal studies to advance the precision of ASD diagnosis and treatment.
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Affiliation(s)
- Xinyue Xie
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Rongyi Zhou
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Zihan Fang
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Yongting Zhang
- The First Affiliated Hospital of Henan University of Chinese Medicine, Pediatrics Hospital, Zhengzhou, Henan, 450000, China
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Qirong Wang
- Henan University of Chinese Medicine, School of Pediatrics, Zhengzhou, Henan, 450046, China
| | - Xiaomian Liu
- Henan University of Chinese Medicine, School of Medicine, Zhengzhou, Henan, 450046, China
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Tóth G, Golubova A, Falk A, Lind SB, Nicholas M, Lanekoff I. Interleukin-13 Treatment of Living Lung Tissue Model Alters the Metabolome and Proteome-A Nano-DESI MS Metabolomics and Shotgun Proteomics Study. Int J Mol Sci 2024; 25:5034. [PMID: 38732251 PMCID: PMC11084154 DOI: 10.3390/ijms25095034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Revised: 04/04/2024] [Accepted: 04/30/2024] [Indexed: 05/13/2024] Open
Abstract
Asthma is a chronic respiratory disease with one of the largest numbers of cases in the world; thus, constant investigation and technical development are needed to unravel the underlying biochemical mechanisms. In this study, we aimed to develop a nano-DESI MS method for the in vivo characterization of the cellular metabolome. Using air-liquid interface (ALI) cell layers, we studied the role of Interleukin-13 (IL-13) on differentiated lung epithelial cells acting as a lung tissue model. We demonstrate the feasibility of nano-DESI MS for the in vivo monitoring of basal-apical molecular transport, and the subsequent endogenous metabolic response, for the first time. Conserving the integrity of the ALI lung-cell layer enabled us to perform temporally resolved metabolomic characterization followed by "bottom-up" proteomics on the same population of cells. Metabolic remodeling was observed upon histamine and corticosteroid treatment of the IL-13-exposed lung cell monolayers, in correlation with alterations in the proteomic profile. This proof of principle study demonstrates the utility of in vivo nano-DESI MS for characterizing ALI tissue layers, and the new markers identified in our study provide a good starting point for future, larger-scale studies.
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Affiliation(s)
- Gábor Tóth
- Department of Chemistry—BMC, Uppsala University, 75237 Uppsala, Sweden
| | | | - Alexander Falk
- Department of Chemistry—BMC, Uppsala University, 75237 Uppsala, Sweden
| | | | | | - Ingela Lanekoff
- Department of Chemistry—BMC, Uppsala University, 75237 Uppsala, Sweden
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Ewald JD, Zhou G, Lu Y, Kolic J, Ellis C, Johnson JD, Macdonald PE, Xia J. Web-based multi-omics integration using the Analyst software suite. Nat Protoc 2024; 19:1467-1497. [PMID: 38355833 DOI: 10.1038/s41596-023-00950-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 11/21/2023] [Indexed: 02/16/2024]
Abstract
The growing number of multi-omics studies demands clear conceptual workflows coupled with easy-to-use software tools to facilitate data analysis and interpretation. This protocol covers three key components involved in multi-omics analysis, including single-omics data analysis, knowledge-driven integration using biological networks and data-driven integration through joint dimensionality reduction. Using the dataset from a recent multi-omics study of human pancreatic islet tissue and plasma samples, the first section introduces how to perform transcriptomics/proteomics data analysis using ExpressAnalyst and lipidomics data analysis using MetaboAnalyst. On the basis of significant features detected in these workflows, the second section demonstrates how to perform knowledge-driven integration using OmicsNet. The last section illustrates how to perform data-driven integration from the normalized omics data and metadata using OmicsAnalyst. The complete protocol can be executed in ~2 h. Compared with other available options for multi-omics integration, the Analyst software suite described in this protocol enables researchers to perform a wide range of omics data analysis tasks via a user-friendly web interface.
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Affiliation(s)
- Jessica D Ewald
- Institute of Parasitology, McGill University, Montreal, Quebec, Canada
| | - Guangyan Zhou
- Institute of Parasitology, McGill University, Montreal, Quebec, Canada
| | - Yao Lu
- Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada
| | - Jelena Kolic
- Life Sciences Institute, Department of Cellular and Physiological Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cara Ellis
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - James D Johnson
- Life Sciences Institute, Department of Cellular and Physiological Sciences, University of British Columbia, Vancouver, British Columbia, Canada
| | - Patrick E Macdonald
- Department of Pharmacology, University of Alberta, Edmonton, Alberta, Canada
| | - Jianguo Xia
- Institute of Parasitology, McGill University, Montreal, Quebec, Canada.
- Department of Microbiology and Immunology, McGill University, Montreal, Quebec, Canada.
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Chrétienneau C, Spindola LM, Vorspan F, Lagerberg TV, Marie‐Claire C, Bellivier F, Mouly S, Laplanche J, Bloch V, Le Hellard S, Icick R. An epigenetic candidate-gene association study of parental styles in suicide attempters with substance use disorders. Addict Biol 2024; 29:e13392. [PMID: 38564607 PMCID: PMC10986931 DOI: 10.1111/adb.13392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Revised: 02/07/2024] [Accepted: 02/27/2024] [Indexed: 04/04/2024]
Abstract
Suicide attempts (SA) are prevalent in substance use disorders (SUD). Epigenetic mechanisms may play a pivotal role in the molecular mechanisms of environmental effects eliciting suicidal behaviour in this population. Hypothalamic-pituitary-adrenal axis (HPA), oxytocin and neurotrophin pathways have been consistently involved in SA, yet , their interplay with childhood adversity remains unclear, particularly in SUD. In 24 outpatients with SUDs, we examined the relation between three parental dysfunctional styles and history of SA with methylation of 32 genes from these pathways, eventually analysing 823 methylation sites. Extensive phenotypic characterization was obtained using a semi-structured interview. Parental style was patient-reported using the Measure of Parental Style (MOPS) questionnaire, analysed with and without imputation of missing items. Linear regressions were performed to adjust for possible confounders, followed by multiple testing correction. We describe both differentially methylated probes (DMPs) and regions (DMRs) for each set of analyses (with and without imputation of MOPS items). Without imputation, five DMRs in OXTR, CRH and NTF3 significantly interacted with MOPS father abuse to increase the risk for lifetime SA, thus covering the three pathways. After imputation of missing MOPS items, two other DMPs from FKBP5 and SOCS3 significantly interacted with each of the three father styles to increase the risk for SA. Although our findings must be interpreted with caution due to small sample size, they suggest implications of stress reactivity genes in the suicidal risk of SUD patients and highlight the significance of father dysfunction as a potential marker of childhood adversity in SUD patients.
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Affiliation(s)
- Clara Chrétienneau
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Leticia M. Spindola
- NORMENT, Department of Clinical ScienceUniversity of BergenBergenNorway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical GeneticsHaukeland University HospitalBergenNorway
| | - Florence Vorspan
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Trine Vik Lagerberg
- Division of Mental Health and Addiction Department of Psychology, Faculty of Social SciencesOslo University Hospital | University of Oslo, Oslo, NorwayOsloNorway
| | - Cynthia Marie‐Claire
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Frank Bellivier
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Stéphane Mouly
- Department of Internal MedicineLariboisière Hospital, Assistance Publique‐Hôpitaux de ParisParisFrance
- Université Paris CitéParisFrance
| | - Jean‐Louis Laplanche
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
| | - Vanessa Bloch
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
- Pharmacie HospitalièreAssistance Publique – Hôpitaux de Paris, GHU APHP. NordParisFrance
| | - Stéphanie Le Hellard
- NORMENT, Department of Clinical ScienceUniversity of BergenBergenNorway
- Dr. Einar Martens Research Group for Biological Psychiatry, Department of Medical GeneticsHaukeland University HospitalBergenNorway
| | - Romain Icick
- Département Universitaire de Psychiatrie et de Médecine Addictologique, GHU APHP. NordAssistance Publique – Hôpitaux de ParisParisFrance
- INSERM UMR‐S 1144, Optimisation Thérapeutique en Neurospsychopharmacologie, OTeNUniversité Paris CitéParisFrance
- FHU NOR‐SUD Network of Research in Substance Use DisordersParisFrance
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Liu Y, Zeng X, Zhang H. An Emerging Approach of Age-Related Hearing Loss Research: Application of Integrated Multi-Omics Analysis. Adv Biol (Weinh) 2024; 8:e2300613. [PMID: 38279573 DOI: 10.1002/adbi.202300613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/03/2024] [Indexed: 01/28/2024]
Abstract
As one of the most common otologic diseases in the elderly, age-related hearing loss (ARHL) usually characterized by hearing loss and cognitive disorders, which have a significant impact on the elderly's physical and mental health and quality of life. However, as a typical disease of aging, it is unclear why aging causes widespread hearing impairment in the elderly. As molecular biological experiments have been conducted for research recently, ARHL is gradually established at various levels with the application and development of integrated multi-omics analysis in the studies of ARHL. Here, the recent progress in the application of multi-omics analysis in the molecular mechanisms of ARHL development and therapeutic regimens, including the combined analysis of different omics, such as transcriptome, proteome, and metabolome, to screen for risk sites, risk genes, and differences in lipid metabolism, etc., is outlined and the integrated histological data further promote the profound understanding of the disease process as well as physiological mechanisms of ARHL. The advantages and disadvantages of multi-omics analysis in disease research are also discussed and the authors speculate on the future prospects and applications of this part-to-whole approach, which may provide more comprehensive guidance for ARHL and aging disease prevention and treatment.
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Affiliation(s)
- Yue Liu
- Department of Otolaryngology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Department of Otolaryngology, Longgang E.N.T. Hospital and Shenzhen Key Laboratory of E.N.T, Institute of E.N.T., Shenzhen, 518172, China
- Department of Graduate and Scientific Research, Zunyi Medical University Zhuhai Campus, Zhuhai, 519041, China
| | - Xianhai Zeng
- Department of Otolaryngology, Longgang E.N.T. Hospital and Shenzhen Key Laboratory of E.N.T, Institute of E.N.T., Shenzhen, 518172, China
- Department of Graduate and Scientific Research, Zunyi Medical University Zhuhai Campus, Zhuhai, 519041, China
| | - Huasong Zhang
- Department of Otolaryngology, Guangdong Provincial Key Laboratory of Major Obstetric Diseases, Guangdong Provincial Clinical Research Center for Obstetrics and Gynecology, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China
- Department of Otolaryngology, Longgang E.N.T. Hospital and Shenzhen Key Laboratory of E.N.T, Institute of E.N.T., Shenzhen, 518172, China
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Xu Z, Liao H, Huang L, Chen Q, Lan W, Li S. IBPGNET: lung adenocarcinoma recurrence prediction based on neural network interpretability. Brief Bioinform 2024; 25:bbae080. [PMID: 38557672 PMCID: PMC10982951 DOI: 10.1093/bib/bbae080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 01/31/2024] [Accepted: 02/07/2024] [Indexed: 04/04/2024] Open
Abstract
Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer. Early-stage patients have a 30-50% probability of metastatic recurrence after surgical treatment. Here, we propose a new computational framework, Interpretable Biological Pathway Graph Neural Networks (IBPGNET), based on pathway hierarchy relationships to predict LUAD recurrence and explore the internal regulatory mechanisms of LUAD. IBPGNET can integrate different omics data efficiently and provide global interpretability. In addition, our experimental results show that IBPGNET outperforms other classification methods in 5-fold cross-validation. IBPGNET identified PSMC1 and PSMD11 as genes associated with LUAD recurrence, and their expression levels were significantly higher in LUAD cells than in normal cells. The knockdown of PSMC1 and PSMD11 in LUAD cells increased their sensitivity to afatinib and decreased cell migration, invasion and proliferation. In addition, the cells showed significantly lower EGFR expression, indicating that PSMC1 and PSMD11 may mediate therapeutic sensitivity through EGFR expression.
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Affiliation(s)
- Zhanyu Xu
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Haibo Liao
- School of computer, Electronic and Information, Guangxi University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Liuliu Huang
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Qingfeng Chen
- School of computer, Electronic and Information, Guangxi University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Wei Lan
- School of computer, Electronic and Information, Guangxi University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
| | - Shikang Li
- Department of Thoracic and Cardiovascular Surgery, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi Zhuang Autonomous Region 530021, China
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Kimura S, Harashima H. Nano-Bio Interactions: Exploring the Biological Behavior and the Fate of Lipid-Based Gene Delivery Systems. BioDrugs 2024; 38:259-273. [PMID: 38345754 DOI: 10.1007/s40259-024-00647-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2024] [Indexed: 03/06/2024]
Abstract
Gene therapy for many diseases is rapidly becoming a reality, as demonstrated by the recent approval of various nucleic acid-based therapeutics. Non-viral systems such as lipid-based carriers, lipid nanoparticles (LNPs), for delivering different payloads including small interfering RNA, plasmid DNA, and messenger RNA have been particularly extensively explored and developed for clinical uses. One of the most important issues in LNP development is delivery to extrahepatic tissues. To achieve this, various lipids and lipid-like materials are being examined and screened. Several LNP formulations that target extrahepatic tissues, such as the spleen and the lungs have been developed by adjusting the lipid compositions of LNPs. However, mechanistic details of how the characteristics of LNPs affect delivery efficiency remains unclear. The purpose of this review is to provide an overview of LNP-based nucleic acid delivery focusing on LNP components and their structures, as well as discussing biological factors, such as biomolecular corona and cellular responses related to the delivery efficiency.
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Affiliation(s)
- Seigo Kimura
- Integrated Research Consortium on Chemical Sciences, Graduate School of Science, Nagoya University, Nagoya, 464-8602, Japan.
| | - Hideyoshi Harashima
- Laboratory for Innovative Nanomedicine, Faculty of Pharmaceutical Sciences, Hokkaido University, Sapporo, 060-0812, Japan.
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Morin L, Lecureur V, Lescoat A. Results from omic approaches in rat or mouse models exposed to inhaled crystalline silica: a systematic review. Part Fibre Toxicol 2024; 21:10. [PMID: 38429797 PMCID: PMC10905840 DOI: 10.1186/s12989-024-00573-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 02/26/2024] [Indexed: 03/03/2024] Open
Abstract
BACKGROUND Crystalline silica (cSiO2) is a mineral found in rocks; workers from the construction or denim industries are particularly exposed to cSiO2 through inhalation. cSiO2 inhalation increases the risk of silicosis and systemic autoimmune diseases. Inhaled cSiO2 microparticles can reach the alveoli where they induce inflammation, cell death, auto-immunity and fibrosis but the specific molecular pathways involved in these cSiO2 effects remain unclear. This systematic review aims to provide a comprehensive state of the art on omic approaches and exposure models used to study the effects of inhaled cSiO2 in mice and rats and to highlight key results from omic data in rodents also validated in human. METHODS The protocol of systematic review follows PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Eligible articles were identified in PubMed, Embase and Web of Science. The search strategy included original articles published after 1990 and written in English which included mouse or rat models exposed to cSiO2 and utilized omic approaches to identify pathways modulated by cSiO2. Data were extracted and quality assessment was based on the SYRCLE's Risk of Bias tool for animal studies. RESULTS Rats and male rodents were the more used models while female rodents and autoimmune prone models were less studied. Exposure of animals were both acute and chronic and the timing of outcome measurement through omics approaches were homogeneously distributed. Transcriptomic techniques were more commonly performed while proteomic, metabolomic and single-cell omic methods were less utilized. Immunity and inflammation were the main domains modified by cSiO2 exposure in lungs of mice and rats. Less than 20% of the results obtained in rodents were finally verified in humans. CONCLUSION Omic technics offer new insights on the effects of cSiO2 exposure in mice and rats although the majority of data still need to be validated in humans. Autoimmune prone model should be better characterised and systemic effects of cSiO2 need to be further studied to better understand cSiO2-induced autoimmunity. Single-cell omics should be performed to inform on pathological processes induced by cSiO2 exposure.
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Affiliation(s)
- Laura Morin
- Univ Rennes, CHU Rennes, INSERM, EHESP, IRSET (Institut de recherche en sante, environnement et travail), UMR_S 1085, 35000, Rennes, France
| | - Valérie Lecureur
- Univ Rennes, CHU Rennes, INSERM, EHESP, IRSET (Institut de recherche en sante, environnement et travail), UMR_S 1085, 35000, Rennes, France.
| | - Alain Lescoat
- Univ Rennes, CHU Rennes, INSERM, EHESP, IRSET (Institut de recherche en sante, environnement et travail), UMR_S 1085, 35000, Rennes, France
- Department of Internal Medicine, Rennes University Hospital, 35000, Rennes, France
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Li J, Wu YJ, Liu MF, Li N, Dang LH, An GS, Lu XJ, Wang LL, Du QX, Cao J, Sun JH. Multi-omics integration strategy in the post-mortem interval of forensic science. Talanta 2024; 268:125249. [PMID: 37839320 DOI: 10.1016/j.talanta.2023.125249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/13/2023] [Accepted: 09/25/2023] [Indexed: 10/17/2023]
Abstract
Estimates of post-mortem interval (PMI), which often serve as pivotal evidence in forensic contexts, are fundamentally based on assessments of variability among diverse molecular markers (including proteins and metabolites), their correlations, and their temporal changes in post-mortem organisms. Nevertheless, the present approach to estimating the PMI is not comprehensive and exhibits poor performance. We developed an innovative approach that integrates multi-omics and artificial intelligence, using multimolecular, multimarker, and multidimensional information to accurately describe the intricate biological processes that occur after death, ultimately enabling inference of the PMI. Called the multi-omics stacking model (MOSM), it combines metabolomics, protein microarray electrophoresis, and fourier transform-infrared spectroscopy data. It shows improved prediction accuracy of the PMI, which is urgently needed in the forensic field. It achieved an accuracy of 0.93, generalized area under the receiver operating characteristic curve of 0.98, and minimum mean absolute error of 0.07. The MOSM integration framework not only considers multiple markers but also incorporates machine-learning models with distinct algorithmic principles. The diversity of biological mechanisms and algorithmic models further ensures the generalizability and robustness of PMI estimation.
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Affiliation(s)
- Jian Li
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Yan-Juan Wu
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Ming-Feng Liu
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Na Li
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Li-Hong Dang
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Guo-Shuai An
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Xiao-Jun Lu
- Criminal Investigation Detachment, Baotou City Public Security Bureau, No. 191, Jianshe Road, Qingshan District, Baotou City, Inner Mongolia Autonomous Region, 014030, PR China
| | - Liang-Liang Wang
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Qiu-Xiang Du
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China
| | - Jie Cao
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China.
| | - Jun-Hong Sun
- School of Forensic Medicine, Shanxi Medical University, No. 98, University Street, Wujinshan Town, Yuci District, Jinzhong City, Shanxi Province, 030604, PR China; Shanxi Key Laboratory of Forensic Medicine, Jinzhong, 030600, Shanxi, China.
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12
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Tan Y, Nie DR, Cao Y, Ke C, Pan J, Shi WY, Zhang W. Trends in the application of "omics" to Alzheimer's disease: a bibliometric and visualized study. Neurol Sci 2024; 45:401-416. [PMID: 37749399 DOI: 10.1007/s10072-023-07079-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Accepted: 09/15/2023] [Indexed: 09/27/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is a progressive neurodegenerative disease with an insidious onset. The widespread application of omics techniques in AD has attracted considerable attention. We aimed to make a comprehensive analysis of published omics articles on AD in order to determine the research profile and application trends of omics techniques in AD. METHODS This study utilizes bibliometric and visual methods including a map collaboration map, co-citations, and keywords to identify knowledge structures, hot topics, and research trends based on 6,828 publications from the Web of Science Core Collection (WoSCC) database. RESULTS The results of this study showed that 5654 institutions from 91 countries published articles in this field. The USA, China, and the UK played a leading role in publishing numerous articles in relevant journals as well as prolific institutions and authors, respectively. This paper collects a large number of literatures on the application of AD omics technology from the WoSCC database and found the omics technology applied to AD is mainly based on genomics technology. The application of transcriptomics technology has shown an increasing trend in recent years, and the application of multi-omics technology will be the general trend in the future. CONCLUSION The development status, frontier hotspots, and general trends of omics application technologies are reviewed. This article will provide intelligence support to researchers and institutions in the field of Alzheimer's omics research and applications from a practical perspective.
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Affiliation(s)
- Yan Tan
- Department of Acupuncture-Moxibustion and Tuina, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Duo Rui Nie
- Graduate School, Hunan University of Chinese Medicine, Changsha, China
| | - Yang Cao
- Department of Acupuncture-Moxibustion and Tuina, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Chao Ke
- Department of Acupuncture-Moxibustion and Tuina, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Jiang Pan
- Department of Acupuncture-Moxibustion and Tuina, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Wen Ying Shi
- Department of Acupuncture-Moxibustion and Tuina, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China
| | - Wei Zhang
- Department of Acupuncture-Moxibustion and Tuina, The First Affiliated Hospital of Hunan University of Chinese Medicine, Changsha, China.
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13
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Chen P, Wang Y, Chen F, Zhou B. Epigenetics in obesity: Mechanisms and advances in therapies based on natural products. Pharmacol Res Perspect 2024; 12:e1171. [PMID: 38293783 PMCID: PMC10828914 DOI: 10.1002/prp2.1171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 10/19/2023] [Accepted: 12/28/2023] [Indexed: 02/01/2024] Open
Abstract
Obesity is a major risk factor for morbidity and mortality because it has a close relationship to metabolic illnesses, such as diabetes, cardiovascular diseases, and some types of cancer. With no drugs available, the mainstay of obesity management remains lifestyle changes with exercise and dietary modifications. In light of the tremendous disease burden and unmet therapeutics, fresh perspectives on pathophysiology and drug discovery are needed. The development of epigenetics provides a compelling justification for how environmental, lifestyle, and other risk factors contribute to the pathogenesis of obesity. Furthermore, epigenetic dysregulations can be restored, and it has been reported that certain natural products obtained from plants, such as tea polyphenols, ellagic acid, urolithins, curcumin, genistein, isothiocyanates, and citrus isoflavonoids, were shown to inhibit weight gain. These substances have great antioxidant potential and are of great interest because they can also modify epigenetic mechanisms. Therefore, understanding epigenetic modifications to target the primary cause of obesity and the epigenetic mechanisms of anti-obesity effects with certain phytochemicals can prove rational strategies to prevent the disease and develop novel therapeutic interventions. Thus, the current review aimed to summarize the epigenetic mechanisms and advances in therapies for obesity based on natural products to provide evidence for the development of several potential anti-obesity drug targets.
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Affiliation(s)
- Peng Chen
- Department of PharmacyRenmin Hospital of Wuhan UniversityWuhanHubeiP.R. China
| | - Yulai Wang
- Department of Pharmacy, Huangshi Central HospitalAffiliated Hospital of Hubei Polytechnic UniversityHuangshiHubeiP.R. China
| | - Fuchao Chen
- Sinopharm Dongfeng General HospitalHubei University of MedicineShiyanHubeiP.R. China
| | - Benhong Zhou
- Department of PharmacyRenmin Hospital of Wuhan UniversityWuhanHubeiP.R. China
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14
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Wang L, Sun T, Liu X, Wang Y, Qiao X, Chen N, Liu F, Zhou X, Wang H, Shen H. Myocarditis: A multi-omics approach. Clin Chim Acta 2024; 554:117752. [PMID: 38184138 DOI: 10.1016/j.cca.2023.117752] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Revised: 12/29/2023] [Accepted: 12/29/2023] [Indexed: 01/08/2024]
Abstract
Myocarditis, an inflammatory condition of weakened heart muscles often triggered by a variety of causes, that can result in heart failure and sudden death. Novel ways to enhance our understanding of myocarditis pathogenesis is available through newer modalities (omics). In this review, we examine the roles of various biomolecules and associated functional pathways across genomics, transcriptomics, proteomics, and metabolomics in the pathogenesis of myocarditis. Our analysis further explores the reproducibility and variability intrinsic to omics studies, underscoring the necessity and significance of employing a multi-omics approach to gain profound insights into myocarditis pathogenesis. This integrated strategy not only enhances our understanding of the disease, but also confirms the critical importance of a holistic multi-omics approach in disease analysis.
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Affiliation(s)
- Lulu Wang
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Tao Sun
- Department of Cardiology, Affiliated Hospital of Jiangsu University, Zhenjiang 212000, Jiangsu, China
| | - Xiaolan Liu
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Yan Wang
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Xiaorong Qiao
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Nuo Chen
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Fangqian Liu
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Xiaoxiang Zhou
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Hua Wang
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China
| | - Hongxing Shen
- School of Medicine, Jiangsu University, Zhenjiang 212013, Jiangsu, China.
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15
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Lucena-Padros H, Bravo-Gil N, Tous C, Rojano E, Seoane-Zonjic P, Fernández RM, Ranea JAG, Antiñolo G, Borrego S. Bioinformatics Prediction for Network-Based Integrative Multi-Omics Expression Data Analysis in Hirschsprung Disease. Biomolecules 2024; 14:164. [PMID: 38397401 PMCID: PMC10886964 DOI: 10.3390/biom14020164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 01/15/2024] [Accepted: 01/27/2024] [Indexed: 02/25/2024] Open
Abstract
Hirschsprung's disease (HSCR) is a rare developmental disorder in which enteric ganglia are missing along a portion of the intestine. HSCR has a complex inheritance, with RET as the major disease-causing gene. However, the pathogenesis of HSCR is still not completely understood. Therefore, we applied a computational approach based on multi-omics network characterization and clustering analysis for HSCR-related gene/miRNA identification and biomarker discovery. Protein-protein interaction (PPI) and miRNA-target interaction (MTI) networks were analyzed by DPClusO and BiClusO, respectively, and finally, the biomarker potential of miRNAs was computationally screened by miRNA-BD. In this study, a total of 55 significant gene-disease modules were identified, allowing us to propose 178 new HSCR candidate genes and two biological pathways. Moreover, we identified 12 key miRNAs with biomarker potential among 137 predicted HSCR-associated miRNAs. Functional analysis of new candidates showed that enrichment terms related to gene ontology (GO) and pathways were associated with HSCR. In conclusion, this approach has allowed us to decipher new clues of the etiopathogenesis of HSCR, although molecular experiments are further needed for clinical validations.
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Affiliation(s)
- Helena Lucena-Padros
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
| | - Nereida Bravo-Gil
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Cristina Tous
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Elena Rojano
- Department of Molecular Biology and Biochemistry, University of Malaga, 29010 Malaga, Spain
- Biomedical Research Institute of Malaga, IBIMA, 29010 Malaga, Spain
| | - Pedro Seoane-Zonjic
- Department of Molecular Biology and Biochemistry, University of Malaga, 29010 Malaga, Spain
- Biomedical Research Institute of Malaga, IBIMA, 29010 Malaga, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 29071 Malaga, Spain
| | - Raquel María Fernández
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Juan A. G. Ranea
- Department of Molecular Biology and Biochemistry, University of Malaga, 29010 Malaga, Spain
- Biomedical Research Institute of Malaga, IBIMA, 29010 Malaga, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 29071 Malaga, Spain
- Spanish National Bioinformatics Institute (INB/ELIXIR-ES), Instituto de Salud Carlos III (ISCIII), 28029 Madrid, Spain
| | - Guillermo Antiñolo
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
| | - Salud Borrego
- Department of Maternofetal Medicine, Genetics and Reproduction, Institute of Biomedicine of Seville, University Hospital Virgen del Rocío/CSIC/University of Seville, 41013 Seville, Spain
- Center for Biomedical Network Research on Rare Diseases (CIBERER), 41013 Seville, Spain
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16
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Lv Y, Wen L, Hu WJ, Deng C, Ren HW, Bao YN, Su BW, Gao P, Man ZY, Luo YY, Li CJ, Xiang ZX, Wang B, Luan ZL. Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes. Metab Brain Dis 2024; 39:147-171. [PMID: 37542622 DOI: 10.1007/s11011-023-01271-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/27/2023] [Indexed: 08/07/2023]
Abstract
Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.
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Affiliation(s)
- Ye Lv
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Lin Wen
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Wen-Juan Hu
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Chong Deng
- Department of Neurosurgery, The Second Affiliated Hospital of Dalian Medical University, Dalian, 116027, China
| | - Hui-Wen Ren
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Ya-Nan Bao
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Bo-Wei Su
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Ping Gao
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Zi-Yue Man
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Yi-Yang Luo
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Cheng-Jie Li
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Zhi-Xin Xiang
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China
| | - Bing Wang
- Department of Endocrinology and Metabolism, The Central hospital of Dalian University of Technology, Dalian, 116000, China.
| | - Zhi-Lin Luan
- Advanced Institute for Medical Sciences, Dalian Medical University, Dalian, 116044, China.
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17
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Amente LD, Mills NT, Le TD, Hyppönen E, Lee SH. Unraveling phenotypic variance in metabolic syndrome through multi-omics. Hum Genet 2024; 143:35-47. [PMID: 38095720 DOI: 10.1007/s00439-023-02619-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Accepted: 11/18/2023] [Indexed: 01/19/2024]
Abstract
Complex multi-omics effects drive the clustering of cardiometabolic risk factors, underscoring the imperative to comprehend how individual and combined omics shape phenotypic variation. Our study partitions phenotypic variance in metabolic syndrome (MetS), blood glucose (GLU), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and blood pressure through genome, transcriptome, metabolome, and exposome (i.e., lifestyle exposome) analyses. Our analysis included a cohort of 62,822 unrelated individuals with white British ancestry, sourced from the UK biobank. We employed linear mixed models to partition phenotypic variance using the restricted maximum likelihood (REML) method, implemented in MTG2 (v2.22). We initiated the analysis by individually modeling omics, followed by subsequent integration of pairwise omics in a joint model that also accounted for the covariance and interaction between omics layers. Finally, we estimated the correlations of various omics effects between the phenotypes using bivariate REML. Significant proportions of the MetS variance were attributed to distinct data sources: genome (9.47%), transcriptome (4.24%), metabolome (14.34%), and exposome (3.77%). The phenotypic variances explained by the genome, transcriptome, metabolome, and exposome ranged from 3.28% for GLU to 25.35% for HDL-C, 0% for GLU to 19.34% for HDL-C, 4.29% for systolic blood pressure (SBP) to 35.75% for TG, and 0.89% for GLU to 10.17% for HDL-C, respectively. Significant correlations were found between genomic and transcriptomic effects for TG and HDL-C. Furthermore, significant interaction effects between omics data were detected for both MetS and its components. Interestingly, significant correlation of omics effect between the phenotypes was found. This study underscores omics' roles, interaction effects, and random-effects covariance in unveiling phenotypic variation in multi-omics domains.
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Affiliation(s)
- Lamessa Dube Amente
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute, Adelaide, SA, 5000, Australia.
| | - Natalie T Mills
- Discipline of Psychiatry, University of Adelaide, Adelaide, SA, 5000, Australia
| | - Thuc Duy Le
- UniSA STEM, University of South Australia, Mawson Lakes, SA, 5095, Australia
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA, 5000, Australia
- UniSA Clinical and Health Sciences, University of South Australia, Adelaide, SA, 5000, Australia
| | - S Hong Lee
- Australian Centre for Precision Health, University of South Australia, Adelaide, SA, 5000, Australia.
- UniSA Allied Health and Human Performance, University of South Australia, Adelaide, SA, 5000, Australia.
- South Australian Health and Medical Research Institute, Adelaide, SA, 5000, Australia.
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18
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Shin TH, Lee G. Reduced lysosomal activity and increased amyloid beta accumulation in silica-coated magnetic nanoparticles-treated microglia. Arch Toxicol 2024; 98:121-134. [PMID: 37798515 DOI: 10.1007/s00204-023-03612-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 09/20/2023] [Indexed: 10/07/2023]
Abstract
Nanoparticles have been used in neurological research in recent years because of their blood-brain barrier penetration activity. However, their potential neuronanotoxicity remains a concern. In particular, microglia, which are resident phagocytic cells, are mainly exposed to nanoparticles in the brain. We investigated the changes in lysosomal function in silica-coated magnetic nanoparticles containing rhodamine B isothiocyanate dye [MNPs@SiO2(RITC)]-treated BV2 murine microglial cells. In addition, we analyzed amyloid beta (Aβ) accumulation and molecular changes through the integration of transcriptomics, proteomics, and metabolomics (triple-omics) analyses. Aβ accumulation significantly increased in the 0.1 μg/μl MNPs@SiO2(RITC)-treated BV2 cells compared to the untreated control and 0.01 μg/μl MNPs@SiO2(RITC)-treated BV2 cells. Moreover, the MNPs@SiO2(RITC)-treated BV2 cells showed lysosomal swelling, a dose-dependent reduction in proteolytic activity, and an increase in lysosomal swelling- and autophagy-related protein levels. Moreover, proteasome activity decreased in the MNPs@SiO2(RITC)-treated BV2 cells, followed by a concomitant reduction in intracellular adenosine triphosphate (ATP). By employing triple-omics and a machine learning algorithm, we generated an integrated single molecular network including reactive oxygen species (ROS), autophagy, lysosomal storage disease, and amyloidosis. In silico analysis of the single triple omics network predicted an increase in ROS, suppression of autophagy, and aggravation of lysosomal storage disease and amyloidosis in the MNPs@SiO2(RITC)-treated BV2 cells. Aβ accumulation and lysosomal swelling in the cells were alleviated by co-treatment with glutathione (GSH) and citrate. These findings suggest that MNPs@SiO2(RITC)-induced reduction in lysosomal activity and proteasomes can be recovered by GSH and citrate treatment. These results also highlight the relationship between nanotoxicity and Aβ accumulation.
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Affiliation(s)
- Tae Hwan Shin
- Department of Biomedical Sciences, Dong-A University, Busan, 49315, Republic of Korea.
| | - Gwang Lee
- Department of Physiology, Ajou University School of Medicine, Suwon, 16499, Republic of Korea.
- Department of Molecular Science and Technology, Ajou University, Suwon, 16499, Republic of Korea.
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19
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Tan Y, Yao B, Kang Y, Shi S, Shi Z, Su J. Emerging role of the crosstalk between gut microbiota and liver metabolome of subterranean herbivores in response to toxic plants. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 269:115902. [PMID: 38171231 DOI: 10.1016/j.ecoenv.2023.115902] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 12/22/2023] [Accepted: 12/26/2023] [Indexed: 01/05/2024]
Abstract
Plant secondary metabolites (PSMs) are a defense mechanism against herbivores, which in turn use detoxification metabolism to process ingested and absorbed PSMs. The feeding environment can cause changes in liver metabolism patterns and the gut microbiota. Here, we compared gut microbiota and liver metabolome to investigate the response mechanism of plateau zokors (Eospalax baileyi) to toxic plant Stellera chamaejasme (SC) in non-SC and SC grassland (-SCG and +SCG). Our results indicated that exposure to SC in the -SCG population increased liver inflammatory markers including prostaglandin (PG) in the Arachidonic acid pathway, while exposure to SC in the +SCG population exhibited a significant downregulation of PGs. Secondary bile acids were significantly downregulated in +SCG plateau zokors after SC treatment. Of note, the microbial taxa Veillonella in the -SCG group was significantly correlated with liver inflammation markers, while Clostridium innocum in the +SCG group had a significant positive correlation with secondary bile acids. The increase in bile acids and PGs can lead to liver inflammatory reactions, suggesting that +SCG plateau zokors may mitigate the toxicity of SC plants by reducing liver inflammatory markers including PGs and secondary bile acids, thereby avoiding liver damage. This provides new insight into mechanisms of toxicity by PSMs and counter-mechanisms for toxin tolerance by herbivores.
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Affiliation(s)
- Yuchen Tan
- College of Grassland Science, Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Baohui Yao
- College of Grassland Science, Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Yukun Kang
- College of Grassland Science, Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Shangli Shi
- College of Grassland Science, Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China
| | - Zunji Shi
- State Key Laboratory of Herbage Improvement and Grassland Agro-ecosystems, Center for Grassland Microbiome, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730000, China.
| | - Junhu Su
- College of Grassland Science, Key Laboratory of Grassland Ecosystem (Ministry of Education), Gansu Agricultural University-Massey University Research Centre for Grassland Biodiversity, Gansu Agricultural University, Lanzhou 730070, China.
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20
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Saima, Latha S, Sharma R, Kumar A. Role of Network Pharmacology in Prediction of Mechanism of Neuroprotective Compounds. Methods Mol Biol 2024; 2761:159-179. [PMID: 38427237 DOI: 10.1007/978-1-0716-3662-6_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/02/2024]
Abstract
Network pharmacology is an emerging pioneering approach in the drug discovery process, which is used to predict the therapeutic mechanism of compounds using various bioinformatic tools and databases. Emerging studies have indicated the use of network pharmacological approaches in various research fields, particularly in the identification of possible mechanisms of herbal compounds/ayurvedic formulations in the management of various diseases. These techniques could also play an important role in the prediction of the possible mechanisms of neuroprotective compounds. The first part of the chapter includes an introduction on neuroprotective compounds based on literature. Further, network pharmacological approaches are briefly discussed. The use of network pharmacology in the prediction of the neuroprotective mechanism of compounds is discussed in detail with suitable examples. Finally, the chapter concludes with the current challenges and future prospectives.
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Affiliation(s)
- Saima
- Department of Pharmacology, Delhi Pharmaceutical Science and Research University (DPSRU), New Delhi, India
| | - S Latha
- Department of Pharmacology, Delhi Pharmaceutical Science and Research University (DPSRU), New Delhi, India
| | - Ruchika Sharma
- Centre for Precision Medicine and Pharmacy, Delhi Pharmaceutical Sciences and Research University (DPSRU), New Delhi, India
| | - Anoop Kumar
- Department of Pharmacology, Delhi Pharmaceutical Science and Research University (DPSRU), New Delhi, India
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21
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Peña N, Amézaga J, Marrugat G, Landaluce A, Viar T, Arce J, Larruskain J, Lekue J, Ferreri C, Ordovás JM, Tueros I. Competitive season effects on polyunsaturated fatty acid content in erythrocyte membranes of female football players. J Int Soc Sports Nutr 2023; 20:2245386. [PMID: 37605439 PMCID: PMC10446798 DOI: 10.1080/15502783.2023.2245386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Accepted: 08/01/2023] [Indexed: 08/23/2023] Open
Abstract
BACKGROUND An optimal and correctly balanced metabolic status is essential to improve sports performance in athletes. Recent advances in omic tools, such as the lipid profile of the mature erythrocyte membranes (LPMEM), allow to have a comprehensive vision of the nutritional and metabolic status of these individuals to provide personalized recommendations for nutrients, specifically, the essential omega-3 and omega-6 fatty acids, individuating deficiencies/unbalances that can arise from both habitual diet and sportive activity. This work aimed to study the LPMEM in professional female football players during the football season for the first time and compare it with those defined as optimal values for the general population and a control group. METHODS An observational study was carried out on female football players from the Athletic Club (Bilbao) playing in the first division of the Spanish league. Blood samples were collected at three points: at the beginning, mid-season, and end of the season for three consecutive seasons (2019-2020, 2020-2021, and 2021-2022), providing a total of 160 samples from 40 women. The LPMEM analysis was obtained by GC-FID by published method and correlated to other individual data, such as blood biochemical parameters, body composition, and age. RESULTS We observed a significant increase in docosahexaenoic acid (DHA) (p 0.048) and total polyunsaturated fatty acid (PUFA) (p 0.021) in the first season. In the second season, we observed a buildup in the membrane arachidonic acid (AA) (p < .001) and PUFA (p < .001) contents when high training accumulated. In comparison with the benchmark of average population values, 69% of the football players showed lower levels of omega-6 dihomo-γ-linolenic acid (DGLA), whereas 88%, 44%, and 81% of the participants showed increased values of AA, eicosapentaenoic acid (EPA), and the ratio of saturated and monounsaturated fatty acids (SFA/MUFA), respectively. Regarding relationships between blood biochemical parameters, body composition, and age with LPMEM, we observed some mild negative correlations, such as AA and SFA/MUFA ratio with vitamin D levels (coefficient = -0.34 p = .0019 and coefficient = -.25 p = .042); DGLA with urea and cortisol (coefficient = -0.27 p < .006 and coefficient = .28 p < .0028) and AA with age (coefficient = -0.33 p < .001). CONCLUSION In conclusion, relevant variations in several fatty acids of the membrane fatty acid profile of elite female football players were observed during the competitive season and, in comparison with the general population, increased PUFA contents were confirmed, as reported in other sportive activities, together with the new aspect of DGLA diminution, an omega-6 involved in immune and anti-inflammatory responses. Our results highlight membrane lipidomics as a tool to ascertain the molecular profile of elite female football players with a potential application for future personalized nutritional strategies (diet and supplementation) to address unbalances created during the competitive season.
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Affiliation(s)
- Nere Peña
- Basque Research and Technology Alliance (BRTA). Parque Tecnológico de Bizkaia, AZTI, Food Research, Derio, Spain
| | - Javier Amézaga
- Basque Research and Technology Alliance (BRTA). Parque Tecnológico de Bizkaia, AZTI, Food Research, Derio, Spain
| | - Gerard Marrugat
- Basque Research and Technology Alliance (BRTA). Parque Tecnológico de Bizkaia, AZTI, Food Research, Derio, Spain
| | | | | | - Julen Arce
- Athletic Club, Medical Services, Lezama, Spain
| | | | | | - Carla Ferreri
- Consiglio Nazionale Delle Ricerche, Istituto per la Sintesi Organica E la Fotoreattività, Bologna, Italy
| | - José María Ordovás
- Nutrition and Genomics Laboratory, JM-USDA-HNRCA at Tufts University, Boston, MA, USA
- Instituto de Salud Carlos III (ISCIII), Consortium CIBERObn, Madrid, Spain
- IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
| | - Itziar Tueros
- Basque Research and Technology Alliance (BRTA). Parque Tecnológico de Bizkaia, AZTI, Food Research, Derio, Spain
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22
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Santorelli L, Caterino M, Costanzo M. Proteomics and Metabolomics in Biomedicine. Int J Mol Sci 2023; 24:16913. [PMID: 38069240 PMCID: PMC10706996 DOI: 10.3390/ijms242316913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
The technological advances of recent years have significantly enhanced medical discoveries [...].
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Affiliation(s)
- Lucia Santorelli
- Department of Oncology and Hematology-Oncology, University of Milano, 20122 Milan, Italy;
| | - Marianna Caterino
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 80131 Naples, Italy;
- CEINGE–Biotecnologie Avanzate Franco Salvatore, 80145 Naples, Italy
| | - Michele Costanzo
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, 80131 Naples, Italy;
- CEINGE–Biotecnologie Avanzate Franco Salvatore, 80145 Naples, Italy
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23
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Su ZW, Yan TY, Feng J, Zhang MY, Han L, Zhang HF, Xiao Y. Protective Effects and Mechanism of Polysaccharides from Edible Medicinal Plants in Alcoholic Liver Injury: A Review. Int J Mol Sci 2023; 24:16530. [PMID: 38003718 PMCID: PMC10671977 DOI: 10.3390/ijms242216530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2023] [Revised: 10/25/2023] [Accepted: 10/26/2023] [Indexed: 11/26/2023] Open
Abstract
Alcohol use accounts for a large variety of diseases, among which alcoholic liver injury (ALI) poses a serious threat to human health. In order to overcome the limitations of chemotherapeutic agents, some natural constituents, especially polysaccharides from edible medicinal plants (PEMPs), have been applied for the prevention and treatment of ALI. In this review, the protective effects of PEMPs on acute, subacute, subchronic, and chronic ALI are summarized. The pathogenesis of alcoholic liver injury is analyzed. The structure-activity relationship (SAR) and safety of PEMPs are discussed. In addition, the mechanism underlying the hepatoprotective activity of polysaccharides from edible medicinal plants is explored. PEMPs with hepatoprotective activities mainly belong to the families Orchidaceae, Solanaceae, and Liliaceae. The possible mechanisms of PEMPs include activating enzymes related to alcohol metabolism, attenuating damage from oxidative stress, regulating cytokines, inhibiting the apoptosis of hepatocytes, improving mitochondrial function, and regulating the gut microbiota. Strategies for further research into the practical application of PEMPs for ALI are proposed. Future studies on the mechanism of action of PEMPs will need to focus more on the utilization of multi-omics approaches, such as proteomics, epigenomics, and lipidomics.
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Affiliation(s)
- Zhuo-Wen Su
- National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Food Engineering and Nutritional Science, International Joint Research Center of Shaanxi Province for Food and Health Sciences, Shaanxi Normal University, Xi’an 710119, China; (Z.-W.S.)
- Academician and Expert Workstations in Puer City of Yunnan Province, Puer 665600, China
| | - Ting-Yu Yan
- National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Food Engineering and Nutritional Science, International Joint Research Center of Shaanxi Province for Food and Health Sciences, Shaanxi Normal University, Xi’an 710119, China; (Z.-W.S.)
| | - Jing Feng
- National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Food Engineering and Nutritional Science, International Joint Research Center of Shaanxi Province for Food and Health Sciences, Shaanxi Normal University, Xi’an 710119, China; (Z.-W.S.)
| | - Meng-Yuan Zhang
- National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Food Engineering and Nutritional Science, International Joint Research Center of Shaanxi Province for Food and Health Sciences, Shaanxi Normal University, Xi’an 710119, China; (Z.-W.S.)
| | - Lei Han
- National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Food Engineering and Nutritional Science, International Joint Research Center of Shaanxi Province for Food and Health Sciences, Shaanxi Normal University, Xi’an 710119, China; (Z.-W.S.)
| | - Hua-Feng Zhang
- National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest China, College of Food Engineering and Nutritional Science, International Joint Research Center of Shaanxi Province for Food and Health Sciences, Shaanxi Normal University, Xi’an 710119, China; (Z.-W.S.)
- Academician and Expert Workstations in Puer City of Yunnan Province, Puer 665600, China
| | - Ying Xiao
- Faculty of Medicine, Macau University of Science and Technology, Macau SAR, China
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24
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Zhu Z, Chen X, Zhang S, Yu R, Qi C, Cheng L, Zhang X. Leveraging molecular quantitative trait loci to comprehend complex diseases/traits from the omics perspective. Hum Genet 2023; 142:1543-1560. [PMID: 37755483 DOI: 10.1007/s00439-023-02602-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 09/14/2023] [Indexed: 09/28/2023]
Abstract
Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.
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Affiliation(s)
- Zijun Zhu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Xinyu Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Sainan Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Rui Yu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Changlu Qi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China
| | - Liang Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, 150081, Heilongjiang, China.
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China.
| | - Xue Zhang
- NHC Key Laboratory of Molecular Probe and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150028, Heilongjiang, China
- McKusick-Zhang Center for Genetic Medicine, State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China
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Di Pietrantonio N, Cappellacci I, Mandatori D, Baldassarre MPA, Pandolfi A, Pipino C. Role of Epigenetics and Metabolomics in Predicting Endothelial Dysfunction in Type 2 Diabetes. Adv Biol (Weinh) 2023; 7:e2300172. [PMID: 37616517 DOI: 10.1002/adbi.202300172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 06/15/2023] [Indexed: 08/26/2023]
Abstract
Type 2 diabetes (T2D) is a worldwide health problem and cardiovascular disease (CVD) is a leading cause of morbidity and mortality in T2D patients, making the prevention of CVD onset a major priority. It is therefore crucial to optimize diagnosis and treatment to reduce this burden. Endothelial dysfunction is one of the most important prognostic factors for CVD progression, thus novel approaches to identify the early phase of endothelial dysfunction may lead to specific preventive measures to reduce the occurrence of CVD. Nowadays, multiomics approaches have provided unprecedented opportunities to stratify T2D patients into endotypes, improve therapeutic treatment and outcome and amend the survival prediction. Among omics strategies, epigenetics and metabolomics are gaining increasing interest. Recently, a dynamic correlation between metabolic pathways and gene expression through chromatin remodeling, such as DNA methylation, has emerged, indicating new perspectives on the regulatory networks impacting cellular processes. Thus, a better understanding of epigenetic-metabolite relationships can provide insight into the physiological processes altered early in the endothelium that ultimately head to disease development. Here, recent studies on epigenetics and metabolomics related to CVD prevention potentially useful to identify disease biomarkers, as well as new therapies hopefully targeting the early phase of endothelial dysfunction are highlighted.
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Affiliation(s)
- Nadia Di Pietrantonio
- Department of Medical, Oral and Biotechnological Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
- Center for Advanced Studies and Technology-CAST, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
| | - Ilaria Cappellacci
- Department of Medical, Oral and Biotechnological Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
- Center for Advanced Studies and Technology-CAST, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
| | - Domitilla Mandatori
- Department of Medical, Oral and Biotechnological Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
- Center for Advanced Studies and Technology-CAST, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
| | - Maria Pompea Antonia Baldassarre
- Center for Advanced Studies and Technology-CAST, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
- Department of Medicine and Aging Sciences, "G. d'Annunzio" University Chieti-Pescara, Chieti, 66100, Italy
| | - Assunta Pandolfi
- Department of Medical, Oral and Biotechnological Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
- Center for Advanced Studies and Technology-CAST, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
| | - Caterina Pipino
- Department of Medical, Oral and Biotechnological Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
- Center for Advanced Studies and Technology-CAST, "G. d'Annunzio" University of Chieti-Pescara, Chieti, 66100, Italy
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Zhou Q, Lu M, Li GS, Peng GL, Song YF. Identification of potential molecular mechanisms and therapeutic targets for recurrent pelvic organ prolapse. Heliyon 2023; 9:e19440. [PMID: 37681155 PMCID: PMC10481308 DOI: 10.1016/j.heliyon.2023.e19440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Revised: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/09/2023] Open
Abstract
Background The pathogenesis of recurrent pelvic organ prolapse (POP) is currently unclear. Therefore, developing targeted preventive measures is difficult. This study identified potential key pathways, crucial genes, comorbidities, and therapeutic targets associated with the occurrence and development of recurrent POP. Methods The original microarray data GSE28660, GSE53868, and GSE12852 were downloaded from the GEO database. Identification and validation of differentially expressed genes (DEGs) and hub genes associated with recurrent POP were performed using R software and cytoHubba of Cytoscape. Protein-protein interaction (PPI) networks were constructed using the STRING tool and visualized using Cytoscape. Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) enrichment analyses were effectively performed using DAVID platforms. In addition, the NetworkAnalyst platform was used to explore and visualize the miRNA-hub gene network, TF-hub gene network, hub gene-disease network, and hub gene-drug/chemical network. Results A total of 110 DEGs and 6 hub genes (ADIPOQ, IL6, PPARG, CEBPA, LPL, and LIPE) were identified in this study. These genes were primarily enriched in the PPAR, AMPK, and adipocytokine, non-alcoholic fatty liver disease, and signaling pathways related to glycerol metabolism. Moreover, 96 miRNAs and 97 TFs were identified to as being associated with recurrent POP. These genes were closely linked to adipocyte metabolism and distribution, energy metabolism, and the longevity regulatory pathway. In addition, 192 diseases or chronic complications were potentially related to the recurrence of POP, including diabetes, hypertension, obesity, inflammatory diseases, and chronic obstructive pulmonary disease. Furthermore, 954 drugs or compounds were shown to have therapeutic potential for recurrent POP, and the most critical target drugs were dexamethasone, bisphenol A, efavirenz, 1-methyl-3-isobutylxanthine, and estradiol. Conclusions The results of this study revealed that ADIPOQ, IL6, PPARG, CEBPA, LPL, and LIPE as potential hub genes associated with recurrent POP, and these hub genes may aid in the understanding of the mechanism underlying POP recurrence and the development of potential molecular drugs.
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Affiliation(s)
- Quan Zhou
- Department of Gynecology and Obstetrics, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, PR China
- Department of Gynecology and Obstetrics, The First College of Clinical Medical Science, China Three Gorges University/Yichang Central People's Hospital, Yichang, 443000, PR China
| | - Man Lu
- Department of Gynecology and Obstetrics, The First College of Clinical Medical Science, China Three Gorges University/Yichang Central People's Hospital, Yichang, 443000, PR China
| | - Guo-Sheng Li
- Department of Gynecology and Obstetrics, The First College of Clinical Medical Science, China Three Gorges University/Yichang Central People's Hospital, Yichang, 443000, PR China
| | - Gan-Lu Peng
- Department of Gynecology and Obstetrics, The First College of Clinical Medical Science, China Three Gorges University/Yichang Central People's Hospital, Yichang, 443000, PR China
| | - Yan-Feng Song
- Department of Gynecology and Obstetrics, The 900th Hospital of Joint Logistic Support Force, PLA, Fuzhou, Fujian, PR China
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27
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Ko YJ, Kim SY, Lee S, Yoon JG, Kim MJ, Jun H, Kim H, Chae JH, Kim KJ, Kim K, Lim BC. Epilepsy phenotype and gene ontology analysis of the 129 genes in a large neurodevelopmental disorders cohort. Front Neurol 2023; 14:1218706. [PMID: 37645600 PMCID: PMC10461058 DOI: 10.3389/fneur.2023.1218706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 07/19/2023] [Indexed: 08/31/2023] Open
Abstract
Objective Although pediatric epilepsy is an independent disease entity, it is often observed in pediatric neurodevelopmental disorders (NDDs) as a major or minor clinical feature, which might provide diagnostic clues. This study aimed to identify the clinical and genetic characteristics of patients with epilepsy in an NDD cohort and demonstrate the importance of genetic testing. Methods We retrospectively analyzed the detailed clinical differences of pediatric NDD patients with epilepsy according to their genetic etiology. Among 1,213 patients with NDDs, 477 were genetically diagnosed by exome sequencing, and 168 had epilepsy and causative variants in 129 genes. Causative genes were classified into two groups: (i) the "epilepsy-genes" group resulting in epilepsy as the main phenotype listed in OMIM, Epi25, and ClinGen (67 patients) and (ii) the "NDD-genes" group not included in the "epilepsy-genes" group (101 patients). Results Patients in the "epilepsy-genes" group started having seizures, often characterized by epilepsy syndrome, at a younger age. However, overall clinical features, including treatment responses and all neurologic manifestations, showed no significant differences between the two groups. Gene ontology analysis revealed the close interactions of epilepsy genes associated with ion channels and neurotransmitters. Conclusion We demonstrated a similar clinical presentation of different gene groups regarding biological/molecular processes in a large NDDs cohort with epilepsy. Phenotype-driven genetic analysis should cover a broad scope, and further studies are required to elucidate integrated pathomechanisms.
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Affiliation(s)
- Young Jun Ko
- Department of Pediatrics, Chung-Ang University Gwangmyeong Hospital, Gwangmyeong, Republic of Korea
| | - Soo Yeon Kim
- Department of Pediatrics, Pediatric Neuroscience Center, Seoul National University Children's Hospital, Seoul, Republic of Korea
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Seungbok Lee
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Jihoon G. Yoon
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Man Jin Kim
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hyeji Jun
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Hunmin Kim
- Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Jong-Hee Chae
- Department of Pediatrics, Pediatric Neuroscience Center, Seoul National University Children's Hospital, Seoul, Republic of Korea
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Ki Joong Kim
- Department of Pediatrics, Pediatric Neuroscience Center, Seoul National University Children's Hospital, Seoul, Republic of Korea
| | - Kwangsoo Kim
- Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Byung Chan Lim
- Department of Pediatrics, Pediatric Neuroscience Center, Seoul National University Children's Hospital, Seoul, Republic of Korea
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28
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Lin KZ, Zhang NR. Quantifying common and distinct information in single-cell multimodal data with Tilted Canonical Correlation Analysis. Proc Natl Acad Sci U S A 2023; 120:e2303647120. [PMID: 37523521 PMCID: PMC10410705 DOI: 10.1073/pnas.2303647120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Accepted: 06/24/2023] [Indexed: 08/02/2023] Open
Abstract
Multimodal single-cell technologies profile multiple modalities for each cell simultaneously, enabling a more thorough characterization of cell populations. Existing dimension-reduction methods for multimodal data capture the "union of information," producing a lower-dimensional embedding that combines the information across modalities. While these tools are useful, we focus on a fundamentally different task of separating and quantifying the information among cells that is shared between the two modalities as well as unique to only one modality. Hence, we develop Tilted Canonical Correlation Analysis (Tilted-CCA), a method that decomposes a paired multimodal dataset into three lower-dimensional embeddings-one embedding captures the "intersection of information," representing the geometric relations among the cells that is common to both modalities, while the remaining two embeddings capture the "distinct information for a modality," representing the modality-specific geometric relations. We analyze single-cell multimodal datasets sequencing RNA along surface antibodies (i.e., CITE-seq) as well as RNA alongside chromatin accessibility (i.e., 10x) for blood cells and developing neurons via Tilted-CCA. These analyses show that Tilted-CCA enables meaningful visualization and quantification of the cross-modal information. Finally, Tilted-CCA's framework allows us to perform two specific downstream analyses. First, for single-cell datasets that simultaneously profile transcriptome and surface antibody markers, we show that Tilted-CCA helps design the target antibody panel to complement the transcriptome best. Second, for developmental single-cell datasets that simultaneously profile transcriptome and chromatin accessibility, we show that Tilted-CCA helps identify development-informative genes and distinguish between transient versus terminal cell types.
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Affiliation(s)
- Kevin Z. Lin
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA19104
| | - Nancy R. Zhang
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA19104
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Nam SL, Tarazona Carrillo K, de la Mata AP, Harynuk JJ. Untargeted Metabolomic Profiling of Aqueous and Lyophilized Pooled Human Feces from Two Diet Cohorts Using Two-Dimensional Gas Chromatography Coupled with Time-of-Flight Mass Spectrometry. Metabolites 2023; 13:828. [PMID: 37512535 PMCID: PMC10383202 DOI: 10.3390/metabo13070828] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Revised: 06/28/2023] [Accepted: 06/30/2023] [Indexed: 07/30/2023] Open
Abstract
The metabolic profiles of human feces are influenced by various genetic and environmental factors, which makes feces an attractive biosample for numerous applications, including the early detection of gut diseases. However, feces is complex, heterogeneous, and dynamic with a significant live bacterial biomass. With such challenges, stool metabolomics has been understudied compared to other biospecimens, and there is a current lack of consensus on methods to collect, prepare, and analyze feces. One of the critical steps required to accelerate the field is having a metabolomics stool reference material available. Fecal samples are generally presented in two major forms: fecal water and lyophilized feces. In this study, two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS) was used as an analytical platform to characterize pooled human feces, provided by the National Institute of Standards and Technology (NIST) as Research-Grade Test Materials. The collected fecal samples were derived from eight healthy individuals with two different diets: vegans and omnivores, matched by age, sex, and body mass index (BMI), and stored as fecal water and lyophilized feces. Various data analysis strategies were presented to determine the differences in the fecal metabolomic profiles. The results indicate that the sample storage condition has a major influence on the metabolic profiles of feces such that the impact from storage surpasses the metabolic differences from the diet types. The findings of the current study would contribute towards the development of a stool reference material.
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Affiliation(s)
- Seo Lin Nam
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2G2, Canada
| | | | | | - James J Harynuk
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2G2, Canada
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Nimer RM, Abdel Rahman AM. Recent advances in proteomic-based diagnostics of cystic fibrosis. Expert Rev Proteomics 2023; 20:151-169. [PMID: 37766616 DOI: 10.1080/14789450.2023.2258282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Accepted: 07/06/2023] [Indexed: 09/29/2023]
Abstract
INTRODUCTION Cystic fibrosis (CF) is a genetic disease characterized by thick and sticky mucus accumulation, which may harm numerous internal organs. Various variables such as gene modifiers, environmental factors, age of diagnosis, and CF transmembrane conductance regulator (CFTR) gene mutations influence phenotypic disease diversity. Biomarkers that are based on genomic information may not accurately represent the underlying mechanism of the disease as well as its lethal complications. Therefore, recent advancements in mass spectrometry (MS)-based proteomics may provide deep insights into CF mechanisms and cellular functions by examining alterations in the protein expression patterns from various samples of individuals with CF. AREAS COVERED We present current developments in MS-based proteomics, its application, and findings in CF. In addition, the future roles of proteomics in finding diagnostic and prognostic novel biomarkers. EXPERT OPINION Despite significant advances in MS-based proteomics, extensive research in a large cohort for identifying and validating diagnostic, prognostic, predictive, and therapeutic biomarkers for CF disease is highly needed.
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Affiliation(s)
- Refat M Nimer
- Department of Medical Laboratory Sciences, Jordan University of Science and Technology, Irbid, Jordan
| | - Anas M Abdel Rahman
- Metabolomics Section, Department of Clinical Genomics, Center for Genome Medicine, King Faisal Specialist Hospital and Research Centre (KFSHRC), Riyadh, Saudi Arabia
- Department of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
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31
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Chaithanya P, Meshram RJ. Chemo Markers as Biomarkers in Septic Shock: A Comprehensive Review of Their Utility and Clinical Applications. Cureus 2023; 15:e42558. [PMID: 37637638 PMCID: PMC10460194 DOI: 10.7759/cureus.42558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 07/27/2023] [Indexed: 08/29/2023] Open
Abstract
Sepsis is a life-threatening condition characterized by a dysregulated host response to infection, often leading to septic shock. Early diagnosis and prompt intervention are crucial for improving patient outcomes. Chemo markers, which are measurable biological substances associated with the pathophysiology of septic shock, have emerged as potential biomarkers for the identification, risk stratification, and management of this condition. This comprehensive review aims to thoroughly evaluate the utility and clinical applications of chemo markers in septic shock. The review begins by discussing the criteria for ideal chemo markers, including specificity, sensitivity, dynamic range, stability, non-invasiveness, and prognostic value. These characteristics ensure accurate diagnosis, early detection, effective monitoring, and prediction of clinical outcomes. Furthermore, the review explores the role of chemo markers in monitoring treatment response and disease progression, highlighting their ability to serve as objective indicators for assessing the effectiveness of interventions and making timely adjustments in management strategies. Moreover, the prognostic value of chemo markers in predicting outcomes is discussed, emphasizing their association with mortality, hospital stays, and the development of complications. Integration of chemo markers into prognostic models or scoring systems enhances risk stratification and informs therapeutic decisions. The review also delves into recent advances in chemo marker research and technology, emphasizing the potential for discovering novel chemo markers with enhanced diagnostic and prognostic capabilities. It highlights the use of high-throughput proteomics, genomics, and transcriptomics in identifying specific molecular signatures associated with septic shock. This contributes to a deeper understanding of the complex immune and inflammatory responses involved. In conclusion, chemo markers have emerged as valuable biomarkers in septic shock, offering potential utility in diagnosis, risk stratification, treatment monitoring, and prediction of outcomes. Continued research, validation, and integration into clinical practice are necessary to fully realize their potential in improving patient care and outcomes in septic shock.
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Affiliation(s)
- Pulivarthi Chaithanya
- Pediatrics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Higher Education and Research, Wardha, IND
| | - Revat J Meshram
- Pediatrics, Jawaharlal Nehru Medical College, Datta Meghe Institute of Medical Sciences, Wardha, IND
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Siavrienė E, Petraitytė G, Mikštienė V, Maldžienė Ž, Sasnauskienė A, Žitkutė V, Ambrozaitytė L, Rančelis T, Utkus A, Kučinskas V, Preikšaitienė E. Molecular and Functional Characterisation of a Novel Intragenic 12q24.21 Deletion Resulting in MED13L Haploinsufficiency Syndrome. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:1225. [PMID: 37512036 PMCID: PMC10385642 DOI: 10.3390/medicina59071225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 06/17/2023] [Accepted: 06/26/2023] [Indexed: 07/30/2023]
Abstract
Background and Objectives: Heterozygous pathogenic variants in the MED13L gene cause impaired intellectual development and distinctive facial features with or without cardiac defects (MIM #616789). This complex neurodevelopmental disorder is characterised by various phenotypic features, including plagiocephaly, strabismus, clubfoot, poor speech, and developmental delay. The aim of this study was to evaluate the clinical significance and consequences of a novel heterozygous intragenic MED13L deletion in a proband with clinical features of a MED13L-related disorder through extensive clinical, molecular, and functional characterisation. Materials and Methods: Combined comparative genomic hybridisation and single-nucleotide polymorphism array (SNP-CGH) was used to identify the changes in the proband's gDNA sequence (DECIPHER #430183). Intragenic MED13L deletion was specified via quantitative polymerase chain reaction (qPCR) and Sanger sequencing of the proband's cDNA sample. Western blot and bioinformatics analyses were used to investigate the consequences of this copy number variant (CNV) at the protein level. CRISPR-Cas9 technology was used for a MED13L-gene-silencing experiment in a culture of the control individual's skin fibroblasts. After the MED13L-gene-editing experiment, subsequent functional fibroblast culture analyses were performed. Results: The analysis of the proband's cDNA sample allowed for specifying the regions of the breakpoints and identifying the heterozygous deletion that spanned exons 3 to 10 of MED13L, which has not been reported previously. In silico, the deletion was predicted to result in a truncated protein NP_056150.1:p.(Val104Glyfs*5), partly altering the Med13_N domain and losing the MedPIWI and Med13_C domains. After MED13L gene editing was performed, reduced cell viability; an accelerated aging process; and inhibition of the RB1, E2F1, and CCNC gene expression were found to exist. Conclusions: Based on these findings, heterozygous intragenic 12q24.21 deletion in the affected individual resulted in MED13L haploinsufficiency due to the premature termination of protein translation, therefore leading to MED13L haploinsufficiency syndrome.
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Affiliation(s)
- Evelina Siavrienė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Gunda Petraitytė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Violeta Mikštienė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Živilė Maldžienė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Aušra Sasnauskienė
- Department of Biochemistry and Molecular Biology, Institute of Biosciences, Life Sciences Centre, Vilnius University, 10257 Vilnius, Lithuania
| | - Vilmantė Žitkutė
- Department of Biochemistry and Molecular Biology, Institute of Biosciences, Life Sciences Centre, Vilnius University, 10257 Vilnius, Lithuania
| | - Laima Ambrozaitytė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Tautvydas Rančelis
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Algirdas Utkus
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Vaidutis Kučinskas
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
| | - Eglė Preikšaitienė
- Department of Human and Medical Genetics, Institute of Biomedical Sciences, Faculty of Medicine, Vilnius University, 08410 Vilnius, Lithuania
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Liu X, Jiang L, Zhang W, Zhang J, Luan X, Zhan Y, Wang T, Da J, Liu L, Zhang S, Guo Y, Zhang K, Wang Z, Miao N, Xie X, Liu P, Li Y, Jin H, Zhang B. Fam20c regulates the calpain proteolysis system through phosphorylating Calpasatatin to maintain cell homeostasis. J Transl Med 2023; 21:417. [PMID: 37370126 DOI: 10.1186/s12967-023-04275-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 06/14/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND The family with sequence similarity 20-member C (FAM20C) kinase, a Golgi casein kinase, which is responsible for phosphorylating the majority of the extracellular phosphoproteins within S-x-E/pS motifs, and is fundamentally associated with multiple biological processes to maintain cell proliferation, biomineralization, migration, adhesion, and phosphate homeostasis. In dissecting how FAM20C regulates downstream molecules and potential mechanisms, however, there are multiple target molecules of FAM20C, particularly many phenomena remain elusive, such as changes in cell-autonomous behaviors, incompatibility in genotypes and phenotypes, and others. METHODS Here, assay for transposase-accessible chromatin using sequencing (ATAC-seq), RNA sequencing (RNA-seq), proteomics, and phosphoproteomics were performed in Fam20c-dificient osteoblasts and to facilitate an integrated analysis and determine the impact of chromatin accessibility, genomic expression, protein alterations, signaling pathway, and post translational modifcations. RESULTS By combining ATAC-seq and RNA-seq, we identified TCF4 and Wnt signaling pathway as the key regulators in Fam20c-dificient cells. Further, we showed Calpastatin/Calpain proteolysis system as a novel target axis for FAM20C to regulate cell migration and F-actin cytoskeleton by integrated analysis of proteomics and phosphoproteomics. Furthermore, Calpastatin/Calpain proteolysis system could negatively regulate the Wnt signaling pathway. CONCLUSION These observations implied that Fam20c knockout osteoblasts would cause cell homeostatic imbalance, involving changes in multiple signaling pathways in the conduction system.
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Affiliation(s)
- Xinpeng Liu
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, 510280, China
| | - Lili Jiang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Pediatric Dentistry, School of Stomatology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Wenxuan Zhang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Jiahui Zhang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Stomatology and Dental Hygiene, The Fourth Affiliated Hospital, Harbin Medical University, Harbin, China
| | - Xinrui Luan
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yuanbo Zhan
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Tuo Wang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Junlong Da
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Lixue Liu
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shujian Zhang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yuyao Guo
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Kai Zhang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Implantology, School and Hospital of Stomatology, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, 250012, People's Republic of China
| | - Zhiping Wang
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, 510280, China
| | - Nan Miao
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Periodontology and Oral Mucosa, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Xiaohua Xie
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
- Department of Stomatology, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Peihong Liu
- Department of Stomatology, The First Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Ying Li
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Han Jin
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
| | - Bin Zhang
- Heilongjiang Provincial Key Laboratory of Hard Tissue Development and Regeneration, The Second Affiliated Hospital of Harbin Medical University, Harbin, China.
- Heilongjiang Academy of Medical Sciences, Harbin, China.
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Lee M. Deep Learning Techniques with Genomic Data in Cancer Prognosis: A Comprehensive Review of the 2021-2023 Literature. BIOLOGY 2023; 12:893. [PMID: 37508326 PMCID: PMC10376033 DOI: 10.3390/biology12070893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/16/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023]
Abstract
Deep learning has brought about a significant transformation in machine learning, leading to an array of novel methodologies and consequently broadening its influence. The application of deep learning in various sectors, especially biomedical data analysis, has initiated a period filled with noteworthy scientific developments. This trend has majorly influenced cancer prognosis, where the interpretation of genomic data for survival analysis has become a central research focus. The capacity of deep learning to decode intricate patterns embedded within high-dimensional genomic data has provoked a paradigm shift in our understanding of cancer survival. Given the swift progression in this field, there is an urgent need for a comprehensive review that focuses on the most influential studies from 2021 to 2023. This review, through its careful selection and thorough exploration of dominant trends and methodologies, strives to fulfill this need. The paper aims to enhance our existing understanding of applications of deep learning in cancer survival analysis, while also highlighting promising directions for future research. This paper undertakes aims to enrich our existing grasp of the application of deep learning in cancer survival analysis, while concurrently shedding light on promising directions for future research in this vibrant and rapidly proliferating field.
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Affiliation(s)
- Minhyeok Lee
- School of Electrical and Electronics Engineering, Chung-Ang University, Seoul 06974, Republic of Korea
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35
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Zhuang Y, Xing F, Ghosh D, Hobbs BD, Hersh CP, Banaei-Kashani F, Bowler RP, Kechris K. Deep learning on graphs for multi-omics classification of COPD. PLoS One 2023; 18:e0284563. [PMID: 37083575 PMCID: PMC10121008 DOI: 10.1371/journal.pone.0284563] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2022] [Accepted: 04/03/2023] [Indexed: 04/22/2023] Open
Abstract
Network approaches have successfully been used to help reveal complex mechanisms of diseases including Chronic Obstructive Pulmonary Disease (COPD). However despite recent advances, we remain limited in our ability to incorporate protein-protein interaction (PPI) network information with omics data for disease prediction. New deep learning methods including convolution Graph Neural Network (ConvGNN) has shown great potential for disease classification using transcriptomics data and known PPI networks from existing databases. In this study, we first reconstructed the COPD-associated PPI network through the AhGlasso (Augmented High-Dimensional Graphical Lasso Method) algorithm based on one independent transcriptomics dataset including COPD cases and controls. Then we extended the existing ConvGNN methods to successfully integrate COPD-associated PPI, proteomics, and transcriptomics data and developed a prediction model for COPD classification. This approach improves accuracy over several conventional classification methods and neural networks that do not incorporate network information. We also demonstrated that the updated COPD-associated network developed using AhGlasso further improves prediction accuracy. Although deep neural networks often achieve superior statistical power in classification compared to other methods, it can be very difficult to explain how the model, especially graph neural network(s), makes decisions on the given features and identifies the features that contribute the most to prediction generally and individually. To better explain how the spectral-based Graph Neural Network model(s) works, we applied one unified explainable machine learning method, SHapley Additive exPlanations (SHAP), and identified CXCL11, IL-2, CD48, KIR3DL2, TLR2, BMP10 and several other relevant COPD genes in subnetworks of the ConvGNN model for COPD prediction. Finally, Gene Ontology (GO) enrichment analysis identified glycosaminoglycan, heparin signaling, and carbohydrate derivative signaling pathways significantly enriched in the top important gene/proteins for COPD classifications.
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Affiliation(s)
- Yonghua Zhuang
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
- Biostatistics Shared Resource, University of Colorado Cancer Center, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Fuyong Xing
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Debashis Ghosh
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
| | - Brian D. Hobbs
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, United States of America
- Harvard Medical School, Boston, MA, United States of America
| | - Farnoush Banaei-Kashani
- Department of Computer Science and Engineering, University of Colorado Denver, Denver, CO, United States of America
| | | | - Katerina Kechris
- Department of Biostatistics and Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, United States of America
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Strauss JC, Haskey N, Ramay HR, Ghosh TS, Taylor LM, Yousuf M, Ohland C, McCoy KD, Ingram RJM, Ghosh S, Panaccione R, Raman M. Weighted Gene Co-Expression Network Analysis Identifies a Functional Guild and Metabolite Cluster Mediating the Relationship between Mucosal Inflammation and Adherence to the Mediterranean Diet in Ulcerative Colitis. Int J Mol Sci 2023; 24:ijms24087323. [PMID: 37108484 PMCID: PMC10138710 DOI: 10.3390/ijms24087323] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Revised: 04/09/2023] [Accepted: 04/13/2023] [Indexed: 04/29/2023] Open
Abstract
Diet influences the pathogenesis and clinical course of inflammatory bowel disease (IBD). The Mediterranean diet (MD) is linked to reductions in inflammatory biomarkers and alterations in microbial taxa and metabolites associated with health. We aimed to identify features of the gut microbiome that mediate the relationship between the MD and fecal calprotectin (FCP) in ulcerative colitis (UC). Weighted gene co-expression network analysis (WGCNA) was used to identify modules of co-abundant microbial taxa and metabolites correlated with the MD and FCP. The features considered were gut microbial taxa, serum metabolites, dietary components, short-chain fatty acid and bile acid profiles in participants that experienced an increase (n = 13) or decrease in FCP (n = 16) over eight weeks. WGCNA revealed ten modules containing sixteen key features that acted as key mediators between the MD and FCP. Three taxa (Faecalibacterium prausnitzii, Dorea longicatena, Roseburia inulinivorans) and a cluster of four metabolites (benzyl alcohol, 3-hydroxyphenylacetate, 3-4-hydroxyphenylacetate and phenylacetate) demonstrated a strong mediating effect (ACME: -1.23, p = 0.004). This study identified a novel association between diet, inflammation and the gut microbiome, providing new insights into the underlying mechanisms of how a MD may influence IBD. See clinicaltrials.gov (NCT04474561).
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Affiliation(s)
- Jaclyn C Strauss
- Department of Medicine, Cumming School of Medicine, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Natasha Haskey
- Department of Biology, Irving K Barber Faculty of Science, University of British Columbia-Okanagan, 3137 University Way, Kelowna, BC V1V 1V7, Canada
| | - Hena R Ramay
- International Microbiome Centre, HRIC 4AA08 Foothills Campus, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Tarini Shankar Ghosh
- APC Microbiome Ireland, College of Medicine and Health, University College Cork, College Road, National University of Ireland, T12 K8AF Cork, Ireland
| | - Lorian M Taylor
- Department of Medicine, Cumming School of Medicine, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Munazza Yousuf
- Department of Medicine, Cumming School of Medicine, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Christina Ohland
- International Microbiome Centre, HRIC 4AA08 Foothills Campus, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Kathy D McCoy
- International Microbiome Centre, HRIC 4AA08 Foothills Campus, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Richard J M Ingram
- Department of Medicine, Cumming School of Medicine, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Subrata Ghosh
- APC Microbiome Ireland, College of Medicine and Health, University College Cork, College Road, National University of Ireland, T12 K8AF Cork, Ireland
| | - Remo Panaccione
- Department of Medicine, Cumming School of Medicine, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
| | - Maitreyi Raman
- Department of Medicine, Cumming School of Medicine, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada
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Sameni M, Mirmotalebisohi SA, Dehghan Z, Abooshahab R, Khazaei-Poul Y, Mozafar M, Zali H. Deciphering molecular mechanisms of SARS-CoV-2 pathogenesis and drug repurposing through GRN motifs: a comprehensive systems biology study. 3 Biotech 2023; 13:117. [PMID: 37070032 PMCID: PMC10090260 DOI: 10.1007/s13205-023-03518-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/13/2023] [Indexed: 03/28/2023] Open
Abstract
The world has recently been plagued by a new coronavirus infection called SARS-CoV-2. This virus may lead to severe acute respiratory syndrome followed by multiple organ failure. SARS-CoV-2 has approximately 80-90% genetic similarity to SARS-CoV. Given the limited omics data available for host response to the viruses (more limited data for SARS-CoV-2), we attempted to unveil the crucial molecular mechanisms underlying the SARS-CoV-2 pathogenesis by comparing its regulatory network motifs with SARS-CoV. We also attempted to identify the non-shared crucial molecules and their functions to predict the specific mechanisms for each infection and the processes responsible for their different manifestations. Deciphering the crucial shared and non-shared mechanisms at the molecular level and signaling pathways underlying both diseases may help shed light on their pathogenesis and pave the way for other new drug repurposing against COVID-19. We constructed the GRNs for host response to SARS-CoV and SARS-CoV-2 pathogens (in vitro) and identified the significant 3-node regulatory motifs by analyzing them topologically and functionally. We attempted to identify the shared and non-shared regulatory elements and signaling pathways between their host responses. Interestingly, our findings indicated that NFKB1, JUN, STAT1, FOS, KLF4, and EGR1 were the critical shared TFs between motif-related subnetworks in both SARS and COVID-1, which are considered genes with specific functions in the immune response. Enrichment analysis revealed that the NOD-like receptor signaling, TNF signaling, and influenza A pathway were among the first significant pathways shared between SARS and COVID-19 up-regulated DEGs networks, and the term "metabolic pathways" (hsa01100) among the down-regulated DEGs networks. WEE1, PMAIP1, and TSC22D2 were identified as the top three hubs specific to SARS. However, MYPN, SPRY4, and APOL6 were the tops specific to COVID-19 in vitro. The term "Complement and coagulation cascades" pathway was identified as the first top non-shared pathway for COVID-19 and the MAPK signaling pathway for SARS. We used the identified crucial DEGs to construct a drug-gene interaction network to propose some drug candidates. Zinc chloride, Fostamatinib, Copper, Tirofiban, Tretinoin, and Levocarnitine were the six drugs with higher scores in our drug-gene network analysis. Supplementary Information The online version contains supplementary material available at 10.1007/s13205-023-03518-x.
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Affiliation(s)
- Marzieh Sameni
- Student Research Committee, Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Seyed Amir Mirmotalebisohi
- Student Research Committee, Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Zeinab Dehghan
- Department of Comparative Biomedical Sciences, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran
| | | | - Yalda Khazaei-Poul
- Student Research Committee, Department of Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Cellular and Molecular Biology Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam Mozafar
- Department of Pharmaceutical Biotechnology, Faculty of Pharmacy, Tehran University of Medical Science, Tehran, Iran
| | - Hakimeh Zali
- Proteomics Research Center, Shahid Beheshti University of Medical Science, Tehran, Iran
- Department of Tissue Engineering and Applied Cell Sciences, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Danzi F, Pacchiana R, Mafficini A, Scupoli MT, Scarpa A, Donadelli M, Fiore A. To metabolomics and beyond: a technological portfolio to investigate cancer metabolism. Signal Transduct Target Ther 2023; 8:137. [PMID: 36949046 PMCID: PMC10033890 DOI: 10.1038/s41392-023-01380-0] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/08/2023] [Accepted: 02/15/2023] [Indexed: 03/24/2023] Open
Abstract
Tumour cells have exquisite flexibility in reprogramming their metabolism in order to support tumour initiation, progression, metastasis and resistance to therapies. These reprogrammed activities include a complete rewiring of the bioenergetic, biosynthetic and redox status to sustain the increased energetic demand of the cells. Over the last decades, the cancer metabolism field has seen an explosion of new biochemical technologies giving more tools than ever before to navigate this complexity. Within a cell or a tissue, the metabolites constitute the direct signature of the molecular phenotype and thus their profiling has concrete clinical applications in oncology. Metabolomics and fluxomics, are key technological approaches that mainly revolutionized the field enabling researchers to have both a qualitative and mechanistic model of the biochemical activities in cancer. Furthermore, the upgrade from bulk to single-cell analysis technologies provided unprecedented opportunity to investigate cancer biology at cellular resolution allowing an in depth quantitative analysis of complex and heterogenous diseases. More recently, the advent of functional genomic screening allowed the identification of molecular pathways, cellular processes, biomarkers and novel therapeutic targets that in concert with other technologies allow patient stratification and identification of new treatment regimens. This review is intended to be a guide for researchers to cancer metabolism, highlighting current and emerging technologies, emphasizing advantages, disadvantages and applications with the potential of leading the development of innovative anti-cancer therapies.
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Affiliation(s)
- Federica Danzi
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
| | - Raffaella Pacchiana
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
| | - Andrea Mafficini
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
| | - Maria T Scupoli
- Department of Neurosciences, Biomedicine and Movement Sciences, Biology and Genetics Section, University of Verona, Verona, Italy
| | - Aldo Scarpa
- Department of Diagnostics and Public Health, University of Verona, Verona, Italy
- ARC-NET Research Centre, University and Hospital Trust of Verona, Verona, Italy
| | - Massimo Donadelli
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy.
| | - Alessandra Fiore
- Department of Neurosciences, Biomedicine and Movement Sciences, Section of Biochemistry, University of Verona, Verona, Italy
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Ouyang Y, Lu W, Wang Y, Wang B, Li F, Li X, Bai Y, Wang Y. Integrated analysis of mRNA and extrachromosomal circular DNA profiles to identify the potential mRNA biomarkers in breast cancer. Gene 2023; 857:147174. [PMID: 36627094 DOI: 10.1016/j.gene.2023.147174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 12/13/2022] [Accepted: 01/04/2023] [Indexed: 01/08/2023]
Abstract
Extrachromosomal circular DNAs (eccDNAs) have been proved an inseparable relationship with cancer, based on the biological mechanisms of its biogenesis and impact on tumorigenesis, but still lacked of methods to analyze its function on the pathogenesis and progression of breast cancer (BC). The mRNA and eccDNA from BC cell samples (MDA-MB-453 and MCF-12A) were extracted with the removal of rRNA and linear DNA, respectively. High-throughput sequencing and bioinformatics analysis were performed to explore their expression level and molecular characterization of eccDNA. A total number of 161,062 eccDNA ranging from 33 bp to 54229 bp were detected with a median size of 1143 bp, distributed on all chromosomes and enriched on chromosome 20 the most. EccDNAs located in exons, upstream and downstream 2 kb regions were significantly increased compared with background. Analysis of eccDNA-related differentially expressed genes (eccDEGs) showed that FAT2 properly separated the two cells. CTNNB1, CACNA2D2 and CACNA1D were the hub genes with higher degrees in critical modules. All these four genes were significantly differentially expressed between breast invasive carcinoma (BRCA) tissues and normal ones. FAT2 and CTNNB1 correlated with significantly different overall survival (OS) when differentially expressed. The four genes showed a strong correlation with each other significantly and changed between tumor and normal samples. The results showed the potential of FAT2, CTNNB1, CACNA2D2 and CACNA1D as biomarkers with analysis of both DEGs and eccDEGs, which might assist in clinical medical treatment.
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Affiliation(s)
- Yunfei Ouyang
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Wenxiang Lu
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Ying Wang
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Bangting Wang
- First Affiliated Hospital of Nanjing Medical University, Nanjing 210096, PR China
| | - Fuyu Li
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Xiaohan Li
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China
| | - Yunfei Bai
- State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210096, PR China.
| | - Yan Wang
- First Affiliated Hospital of Nanjing Medical University, Nanjing 210096, PR China.
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Zhu H, Li Y, Guo J, Feng S, Ge H, Gu C, Wang M, Nie R, Li N, Wang Y, Wang H, Zhong J, Qian X, He G. Integrated proteomic and phosphoproteomic analysis for characterization of colorectal cancer. J Proteomics 2023; 274:104808. [PMID: 36596410 DOI: 10.1016/j.jprot.2022.104808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 12/19/2022] [Accepted: 12/26/2022] [Indexed: 01/02/2023]
Abstract
Proteins and translationally modified proteins like phosphoproteins have essential regulatory roles in tumorigenesis. This study attempts to elucidate the dysregulated proteins driving colorectal cancer (CRC). To explore the differential proteins, we performed iTRAQ labeling proteomics and TMT labeling phosphoproteomics analysis of CRC tissues and adjacent non-cancerous tissues. The functions of quantified proteins were analyzed using Gene Ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Subcellular localization analysis. Depending on the results, we identified 330 differential proteins and 82 phosphoproteins in CRC. GO and KEGG analyses demonstrated that protein changes were primarily associated with regulating biological and metabolic processes through binding to other molecules. Co-expression relationships between proteomic and phosphoproteomic analysis revealed that TMC5, SMC4, SLBP, VSIG2, and NDRG2 were significantly dysregulated differential proteins. Additionally, based on the predicted co-expression proteins, we identified that the stem-loop binding protein (SLBP) was up-regulated in CRC cells and promoted the proliferation and migration of CRC. This study reports an integrated proteomic and phosphoproteomic analysis of CRC to discern the functional impact of protein alterations and provides a candidate diagnostic biomarker or therapeutic target for CRC. SIGNIFICANCE: Combining one or more high-throughput omics technologies with bioinformatics to analyze biological samples and explore the links between biomolecules and their functions can provide more comprehensive and multi-level insights for disease mechanism research. Proteomics, phosphoproteomics, metabolomics and their combined analysis play an important role in the auxiliary diagnosis, the discovery of biomarkers and novel therapeutic targets for colorectal cancer. In this integrated proteomic and phosphoproteomic analysis, we identified proteins and phosphoproteins in colorectal cancer tissue and analyzed potential mechanisms contributing to progression in colorectal cancer. The results of this study provide a foundation to focus future experiments on the contribution of altered protein and phosphorylation patterns to prevention and treatment of colorectal cancer.
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Affiliation(s)
- Huifang Zhu
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Yongzhen Li
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Jingyu Guo
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Shuang Feng
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Hong Ge
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Chuansha Gu
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Mengyao Wang
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Ruicong Nie
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Na Li
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Yongxia Wang
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Haijun Wang
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Jiateng Zhong
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China
| | - Xinlai Qian
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China.
| | - Guoyang He
- Department of Pathology, Xinxiang Medical University, 601 Jinsui Road, Xinxiang City, Henan Province, China.
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Srinath A, Xie B, Li Y, Sone JY, Romanos S, Chen C, Sharma A, Polster S, Dorrestein PC, Weldon KC, DeBiasse D, Moore T, Lightle R, Koskimäki J, Zhang D, Stadnik A, Piedad K, Hagan M, Shkoukani A, Carrión-Penagos J, Bi D, Shen L, Shenkar R, Ji Y, Sidebottom A, Pamer E, Gilbert JA, Kahn ML, D'Souza M, Sulakhe D, Awad IA, Girard R. Plasma metabolites with mechanistic and clinical links to the neurovascular disease cavernous angioma. COMMUNICATIONS MEDICINE 2023; 3:35. [PMID: 36869161 PMCID: PMC9984539 DOI: 10.1038/s43856-023-00265-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 02/20/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND Cavernous angiomas (CAs) affect 0.5% of the population, predisposing to serious neurologic sequelae from brain bleeding. A leaky gut epithelium associated with a permissive gut microbiome, was identified in patients who develop CAs, favoring lipid polysaccharide producing bacterial species. Micro-ribonucleic acids along with plasma levels of proteins reflecting angiogenesis and inflammation were also previously correlated with CA and CA with symptomatic hemorrhage. METHODS The plasma metabolome of CA patients and CA patients with symptomatic hemorrhage was assessed using liquid-chromatography mass spectrometry. Differential metabolites were identified using partial least squares-discriminant analysis (p < 0.05, FDR corrected). Interactions between these metabolites and the previously established CA transcriptome, microbiome, and differential proteins were queried for mechanistic relevance. Differential metabolites in CA patients with symptomatic hemorrhage were then validated in an independent, propensity matched cohort. A machine learning-implemented, Bayesian approach was used to integrate proteins, micro-RNAs and metabolites to develop a diagnostic model for CA patients with symptomatic hemorrhage. RESULTS Here we identify plasma metabolites, including cholic acid and hypoxanthine distinguishing CA patients, while arachidonic and linoleic acids distinguish those with symptomatic hemorrhage. Plasma metabolites are linked to the permissive microbiome genes, and to previously implicated disease mechanisms. The metabolites distinguishing CA with symptomatic hemorrhage are validated in an independent propensity-matched cohort, and their integration, along with levels of circulating miRNAs, enhance the performance of plasma protein biomarkers (up to 85% sensitivity and 80% specificity). CONCLUSIONS Plasma metabolites reflect CAs and their hemorrhagic activity. A model of their multiomic integration is applicable to other pathologies.
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Affiliation(s)
- Abhinav Srinath
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Bingqing Xie
- Department of Medicine, University of Chicago, Chicago, IL, 60637, USA
| | - Ying Li
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
- Department of Neurosurgery, First Affiliated Hospital of Harbin Medical University, 150001, Harbin, Heilongjiang, China
| | - Je Yeong Sone
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Sharbel Romanos
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Chang Chen
- Bioinformatics Core, Center for Research Informatics, The University of Chicago, Chicago, IL, 60637, USA
| | - Anukriti Sharma
- Department of Surgery, The University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA
- Department of Pediatrics, The University of California San Diego and Scripps Institution of Oceanography, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Sean Polster
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Pieter C Dorrestein
- Department of Pediatrics, The University of California San Diego and Scripps Institution of Oceanography, 9500 Gilman Drive, La Jolla, CA, 92093, USA
- Department of Pharmacology, The University of California San Diego, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Kelly C Weldon
- Department of Pediatrics, The University of California San Diego and Scripps Institution of Oceanography, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Dorothy DeBiasse
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Thomas Moore
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Rhonda Lightle
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Janne Koskimäki
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Dongdong Zhang
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Agnieszka Stadnik
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Kristina Piedad
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Matthew Hagan
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Abdallah Shkoukani
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Julián Carrión-Penagos
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Dehua Bi
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Le Shen
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
- Department of Surgery, The University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Robert Shenkar
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
| | - Yuan Ji
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Ashley Sidebottom
- Host-Microbe Metabolomics Facility, Duchossois Family Institute, University of Chicago, Chicago, IL, USA
| | - Eric Pamer
- Host-Microbe Metabolomics Facility, Duchossois Family Institute, University of Chicago, Chicago, IL, USA
| | - Jack A Gilbert
- Department of Surgery, The University of Chicago, 5841 S. Maryland Avenue, Chicago, IL, 60637, USA
- Department of Pediatrics, The University of California San Diego and Scripps Institution of Oceanography, 9500 Gilman Drive, La Jolla, CA, 92093, USA
| | - Mark L Kahn
- Department of Medicine and Cardiovascular Institute, University of Pennsylvania, 3400 Civic Center Boulevard, Philadelphia, PA, 19104, USA
| | - Mark D'Souza
- Host-Microbe Metabolomics Facility, Duchossois Family Institute, University of Chicago, Chicago, IL, USA
| | - Dinanath Sulakhe
- Host-Microbe Metabolomics Facility, Duchossois Family Institute, University of Chicago, Chicago, IL, USA
| | - Issam A Awad
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA.
| | - Romuald Girard
- Neurovascular Surgery Program, Department of Neurological Surgery, The University of Chicago, 5841S. Maryland Avenue, Chicago, IL, 60637, USA
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Metabolomics in Corneal Diseases: A Narrative Review from Clinical Aspects. Metabolites 2023; 13:metabo13030380. [PMID: 36984820 PMCID: PMC10055016 DOI: 10.3390/metabo13030380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Revised: 02/25/2023] [Accepted: 03/01/2023] [Indexed: 03/08/2023] Open
Abstract
Corneal pathologies may have subtle manifestations in the initial stages, delaying diagnosis and timely treatment. This can lead to irreversible visual loss. Metabolomics is a rapidly developing field that allows the study of metabolites in a system, providing a complementary tool in the early diagnosis and management of corneal diseases. Early identification of biomarkers is key to prevent disease progression. The advancement of nuclear magnetic resonance and mass spectrometry allows the identification of new biomarkers in the analysis of tear, cornea, and aqueous humor. Novel perspectives on disease mechanisms are identified, which provide vital information for potential targeted therapies in the future. Current treatments are analyzed at a molecular level to offer further information regarding their efficacy. In this article, we provide a comprehensive review of the metabolomic studies undertaken in the cornea and various pathologies such as dry eye disease, Sjogren’s syndrome, keratoconus, post-refractive surgery, contact lens wearers, and diabetic corneas. Lastly, we discuss the exciting future that metabolomics plays in cornea research.
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43
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Tang J, Xu Q, Tang K, Ye X, Cao Z, Zou M, Zeng J, Guan X, Han J, Wang Y, Yang L, Lin Y, Jiang K, Chen X, Zhao Y, Tian D, Li C, Shen W, Du X. Susceptibility identification for seasonal influenza A/H3N2 based on baseline blood transcriptome. Front Immunol 2023; 13:1048774. [PMID: 36713410 PMCID: PMC9878565 DOI: 10.3389/fimmu.2022.1048774] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 12/23/2022] [Indexed: 01/13/2023] Open
Abstract
Introduction Influenza susceptibility difference is a widely existing trait that has great practical significance for the accurate prevention and control of influenza. Methods Here, we focused on the human susceptibility to the seasonal influenza A/H3N2 of healthy adults at baseline level. Whole blood expression data for influenza A/H3N2 susceptibility from GEO were collected firstly (30 symptomatic and 19 asymptomatic). Then to explore the differences at baseline, a suite of systems biology approaches - the differential expression analysis, co-expression network analysis, and immune cell frequencies analysis were utilized. Results We found the baseline condition, especially immune condition between symptomatic and asymptomatic, was different. Co-expression module that is positively related to asymptomatic is also related to immune cell type of naïve B cell. Function enrichment analysis showed significantly correlation with "B cell receptor signaling pathway", "immune response-activating cell surface receptor signaling pathway" and so on. Also, modules that are positively related to symptomatic are also correlated to immune cell type of neutrophils, with function enrichment analysis showing significantly correlations with "response to bacterium", "inflammatory response", "cAMP-dependent protein kinase complex" and so on. Responses of symptomatic and asymptomatic hosts after virus exposure show differences on resisting the virus, with more effective frontline defense for asymptomatic hosts. A prediction model was also built based on only baseline transcription information to differentiate symptomatic and asymptomatic population with accuracy of 0.79. Discussion The results not only improve our understanding of the immune system and influenza susceptibility, but also provide a new direction for precise and targeted prevention and therapy of influenza.
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Affiliation(s)
- Jing Tang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Qiumei Xu
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China,Guangzhou Eighth People’s Hospital, Guangzhou Medical University, Guangzhou, China
| | - Kang Tang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Xiaoyan Ye
- Department of Otolaryngology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Zicheng Cao
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China,School of Public Health, Shantou University, Shantou, China
| | - Min Zou
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Jinfeng Zeng
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Xinyan Guan
- Department of Chronic Disease Control and Prevention, Shenzhen Guangming District Center for Disease Control and Prevention, Shenzhen, China
| | - Jinglin Han
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Yihan Wang
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Lan Yang
- School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China,School of Public Health, The University of Hong Kong, Pokfulam, Hong Kong SAR, China
| | - Yishan Lin
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Kaiao Jiang
- Palos Verdes Peninsula High School, Rancho Palos Verdes, CA, United States
| | - Xiaoliang Chen
- Department of Chronic Disease Control and Prevention, Shenzhen Guangming District Center for Disease Control and Prevention, Shenzhen, China
| | - Yang Zhao
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Dechao Tian
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China
| | - Chunwei Li
- Department of Otolaryngology, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China
| | - Wei Shen
- Department of Rheumatology and Immunology, Nanjing Drum Tower Hospital Clinical College of Nanjing Medical University, Nanjing, China,*Correspondence: Xiangjun Du, ; Wei Shen,
| | - Xiangjun Du
- School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, China,School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, China,Key Laboratory of Tropical Disease Control, Ministry of Education, Sun Yat-sen University, Guangzhou, China,*Correspondence: Xiangjun Du, ; Wei Shen,
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Punetha A, Kotiya D. Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice. Proteomes 2023; 11:2. [PMID: 36648960 PMCID: PMC9844371 DOI: 10.3390/proteomes11010002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/03/2023] [Accepted: 01/04/2023] [Indexed: 01/12/2023] Open
Abstract
Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.
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Affiliation(s)
- Ankita Punetha
- Department of Microbiology, Biochemistry and Molecular Genetics, Rutgers New Jersey Medical School, Rutgers University, 225 Warren St., Newark, NJ 07103, USA
| | - Deepak Kotiya
- Department of Pharmacology and Nutritional Sciences, University of Kentucky, 900 South Limestone St., Lexington, KY 40536, USA
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Liu C, Duan Y, Zhou Q, Wang Y, Gao Y, Kan H, Hu J. A classification method of gastric cancer subtype based on residual graph convolution network. Front Genet 2023; 13:1090394. [PMID: 36685956 PMCID: PMC9845413 DOI: 10.3389/fgene.2022.1090394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2022] [Accepted: 12/09/2022] [Indexed: 01/06/2023] Open
Abstract
Background: Clinical diagnosis and treatment of tumors are greatly complicated by their heterogeneity, and the subtype classification of cancer frequently plays a significant role in the subsequent treatment of tumors. Presently, the majority of studies rely far too heavily on gene expression data, omitting the enormous power of multi-omics fusion data and the potential for patient similarities. Method: In this study, we created a gastric cancer subtype classification model called RRGCN based on residual graph convolutional network (GCN) using multi-omics fusion data and patient similarity network. Given the multi-omics data's high dimensionality, we built an artificial neural network Autoencoder (AE) to reduce the dimensionality of the data and extract hidden layer features. The model is then built using the feature data. In addition, we computed the correlation between patients using the Pearson correlation coefficient, and this relationship between patients forms the edge of the graph structure. Four graph convolutional network layers and two residual networks with skip connections make up RRGCN, which reduces the amount of information lost during transmission between layers and prevents model degradation. Results: The results show that RRGCN significantly outperforms other classification methods with an accuracy as high as 0.87 when compared to four other traditional machine learning methods and deep learning models. Conclusion: In terms of subtype classification, RRGCN excels in all areas and has the potential to offer fresh perspectives on disease mechanisms and disease progression. It has the potential to be used for a broader range of disorders and to aid in clinical diagnosis.
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Affiliation(s)
- Can Liu
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China,Anhui Computer Application Research Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Hefei, Anhui, China
| | - Yuchen Duan
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Qingqing Zhou
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China
| | - Yongkang Wang
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China,Anhui Computer Application Research Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Hefei, Anhui, China
| | - Yong Gao
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China,Anhui Computer Application Research Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Hefei, Anhui, China
| | - Hongxing Kan
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China,Anhui Computer Application Research Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Hefei, Anhui, China
| | - Jili Hu
- School of Medical Informatics Engineering, Anhui University of Chinese Medicine, Hefei, Anhui, China,Anhui Computer Application Research Institute of Chinese Medicine, China Academy of Chinese Medical Sciences, Hefei, Anhui, China,*Correspondence: Jili Hu,
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Chalikiopoulou C, Gómez-Tamayo JC, Katsila T. Untargeted Metabolomics for Disease-Specific Signatures. Methods Mol Biol 2023; 2571:71-81. [PMID: 36152151 DOI: 10.1007/978-1-0716-2699-3_7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Human diseases account for complex traits that usually exhibit markedly diverse clinical manifestations coming from a series of pathogenic processes that shape heterogeneous phenotypes. Considering that correlation does not imply causation as well as population differences and/or inter-individual variability, disease-specific signatures are becoming critical for biomarker discovery. Untargeted metabolomics is deemed to be a powerful approach to delineate molecular pathways of prime interest. Metabotypes capture the interplay of genomics and environmental influences per se. Untargeted metabolomics share the charm of being not only hypothesis-driven but also hypothesis-generating. Notwithstanding, the applicability of untargeted metabolomics toward clinically relevant outcomes depend on wet- and dry-lab procedures in the context of elegant study designs with clear rationale. As ideal may be far from feasible, herein we provide recommendations to combat sample mishandling that adversely affect data outcomes and if so, deal with imbalanced datasets toward data integrity.
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Affiliation(s)
| | | | - Theodora Katsila
- Institute of Chemical Biology, National Hellenic Research Foundation, Athens, Greece.
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Hassan T, Firdous P, Nissar K, Ahmad MB, Imtiyaz Z. Role of proteomics in surgical oncology. Proteomics 2023. [DOI: 10.1016/b978-0-323-95072-5.00012-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/01/2023]
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48
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Qu X, Ma J, Gao H, Zhang Y, Zhai J, Gong J, Song Y, Hu T. Integration of metabolomics and proteomics analysis to explore the mechanism of neurotoxicity induced by receipt of isoniazid and rifampicin in mice. Neurotoxicology 2023; 94:24-34. [PMID: 36347327 DOI: 10.1016/j.neuro.2022.11.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/06/2022]
Abstract
Isoniazid (INH) and rifampicin (RIF) are co-administered in tuberculosis treatment but can cause neurotoxicity, and the mechanism is not known. To explore this mechanism, we employed an integrated approach using metabolomics analysis (MA) and proteomics analysis (PA). Male mice were divided into three groups and administered vehicle (control group), or co-administered INH (120 mg/kg) and RIF (240 mg/kg), for 7 or 14 days. Mice brains were collected for mass spectrometry-based PA and MA plus lipidomics analysis. Measurement of brain levels of malondialdehyde and superoxide dismutase revealed time-dependent brain injury after exposure to INH+RIF for 7 and 14 days. Also, 422 proteins, 35 metabolites, and 21 lipids were dysregulated and identified. MA demonstrated "purine metabolism," "phenylalanine, tyrosine and tryptophan biosynthesis," "biosynthesis of unsaturated fatty acids," "phenylalanine metabolism," and "arginine biosynthesis" to be disturbed significantly. PA demonstrated pathways such as "lipids," "amino acids," and "energy metabolism" to be disrupted. Peroxisome proliferator-activated receptor (PPAR) pathways were changed in energy metabolism, which led to the neurotoxicity induced by INH+RIF. Immunohistochemical analyses of PPARs in mice brains verified that PPAR-α and -γ expression was downregulated. PPAR-α and -γ activation might be a key target for alleviating INH+RIF-induced neurotoxicity.
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Affiliation(s)
- Xiaoyu Qu
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China
| | - Jie Ma
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China
| | - Huan Gao
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China
| | - Yueming Zhang
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China
| | - Jinghui Zhai
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China
| | - Jiawei Gong
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China
| | - Yanqing Song
- Department of Pharmacy, The First Hospital of Jilin University, 130021 Changchun, China.
| | - Tingting Hu
- State Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, 130021 Changchun, China.
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He DN, Wang N, Wen XL, Li XH, Guo Y, Fu SH, Xiong FF, Wu ZY, Zhu X, Gao XL, Wang ZZ, Wang HJ. Multi-omics analysis reveals a molecular landscape of the early recurrence and early metastasis in pan-cancer. Front Genet 2023; 14:1061364. [PMID: 37152984 PMCID: PMC10157260 DOI: 10.3389/fgene.2023.1061364] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 04/03/2023] [Indexed: 05/09/2023] Open
Abstract
Cancer remains a formidable challenge in medicine due to its propensity for recurrence and metastasis, which can result in unfavorable treatment outcomes. This challenge is particularly acute for early-stage patients, who may experience recurrence and metastasis without timely detection. Here, we first analyzed the differences in clinical characteristics among the primary tumor, recurrent tumor, and metastatic tumor in different stages of cancer, which may be caused by the molecular level. Moreover, the importance of predicting early cancer recurrence and metastasis is emphasized by survival analyses. Next, we used a multi-omics approach to identify key molecular changes associated with early cancer recurrence and metastasis and discovered that early metastasis in cancer demonstrated a high degree of genomic and cellular heterogeneity. We performed statistical comparisons for each level of omics data including gene expression, mutation, copy number variation, immune cell infiltration, and cell status. Then, various analytical techniques, such as proportional hazard model and Fisher's exact test, were used to identify specific genes or immune characteristics associated with early cancer recurrence and metastasis. For example, we observed that the overexpression of BPIFB1 and high initial B-cell infiltration levels are linked to early cancer recurrence, while the overexpression or amplification of ANKRD22 and LIPM, mutation of IGHA1 and MUC16, high fibroblast infiltration level, M1 polarization of macrophages, cellular status of DNA repair are all linked to early cancer metastasis. These findings have led us to construct classifiers, and the average area under the curve (AUC) of these classifiers was greater than 0.75 in The Cancer Genome Atlas (TCGA) cancer patients, confirming that the features we identified could be biomarkers for predicting recurrence and metastasis of early cancer. Finally, we identified specific early sensitive targets for targeted therapy and immune checkpoint inhibitor therapy. Once the biomarkers we identified changed, treatment-sensitive targets can be treated accordingly. Our study has comprehensively characterized the multi-omics characteristics and identified a panel of biomarkers of early cancer recurrence and metastasis. Overall, it provides a valuable resource for cancer recurrence and metastasis research and improves our understanding of the underlying mechanisms driving early cancer recurrence and metastasis.
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Affiliation(s)
- Dan-ni He
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Na Wang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Xiao-Ling Wen
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Xu-Hua Li
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Yu Guo
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Shu-heng Fu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Fei-fan Xiong
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Zhe-yu Wu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xu Zhu
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
| | - Xiao-ling Gao
- The Medical Laboratory Center, Hainan General Hospital, Haikou, China
- *Correspondence: Hong-jiu Wang, ; Zhen-zhen Wang, ; Xiao-ling Gao,
| | - Zhen-zhen Wang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- *Correspondence: Hong-jiu Wang, ; Zhen-zhen Wang, ; Xiao-ling Gao,
| | - Hong-jiu Wang
- Key Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- College of Biomedical Information and Engineering, Hainan Medical University, Haikou, China
- *Correspondence: Hong-jiu Wang, ; Zhen-zhen Wang, ; Xiao-ling Gao,
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Virzì GM, Mattiotti M, de Cal M, Ronco C, Zanella M, De Rosa S. Endotoxin in Sepsis: Methods for LPS Detection and the Use of Omics Techniques. Diagnostics (Basel) 2022; 13:diagnostics13010079. [PMID: 36611371 PMCID: PMC9818564 DOI: 10.3390/diagnostics13010079] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 12/19/2022] [Accepted: 12/23/2022] [Indexed: 12/29/2022] Open
Abstract
Lipopolysaccharide (LPS) or endotoxin, the major cell wall component of Gram-negative bacteria, plays a pivotal role in the pathogenesis of sepsis. It is able to activate the host defense system through interaction with Toll-like receptor 4, thus triggering pro-inflammatory mechanisms. A large amount of LPS induces inappropriate activation of the immune system, triggering an exaggerated inflammatory response and consequent extensive organ injury, providing the basis of sepsis damage. In this review, we will briefly describe endotoxin's molecular structure and its main pathogenetic action during sepsis. In addition, we will summarize the main different available methods for endotoxin detection with a special focus on the wider spectrum offered by omics technologies (genomics, transcriptomics, proteomics, and metabolomics) and promising applications of these in the identification of specific biomarkers for sepsis.
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Affiliation(s)
- Grazia Maria Virzì
- Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, 36100 Vicenza, Italy
- IRRIV—International Renal Research Institute Vicenza, 36100 Vicenza, Italy
- Correspondence: ; Tel.: +39-0444753650; Fax: +39-0444753949
| | - Maria Mattiotti
- Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, 36100 Vicenza, Italy
- IRRIV—International Renal Research Institute Vicenza, 36100 Vicenza, Italy
- Nephrology, Dialysis and Renal Transplant Unit, IRCCS—Azienda Ospedaliero-Universitaria di Bologna, Department of Experimental Diagnostic and Specialty Medicine (DIMES), Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy
| | - Massimo de Cal
- Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, 36100 Vicenza, Italy
- IRRIV—International Renal Research Institute Vicenza, 36100 Vicenza, Italy
| | - Claudio Ronco
- Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, 36100 Vicenza, Italy
- IRRIV—International Renal Research Institute Vicenza, 36100 Vicenza, Italy
| | - Monica Zanella
- Department of Nephrology, Dialysis and Transplant, San Bortolo Hospital, 36100 Vicenza, Italy
- IRRIV—International Renal Research Institute Vicenza, 36100 Vicenza, Italy
| | - Silvia De Rosa
- IRRIV—International Renal Research Institute Vicenza, 36100 Vicenza, Italy
- Centre for Medical Sciences—CISMed, University of Trento, Via S. Maria Maddalena 1, 38122 Trento, Italy
- Anesthesia and Intensive Care, Santa Chiara Regional Hospital, APSS Trento, 38122 Trento, Italy
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