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Liu X, Wang H, Zhu L. Profound perturbations are found in the proteome and metabolome in children with obesity after weight loss intervention. Heliyon 2024; 10:e31917. [PMID: 38867950 PMCID: PMC11167357 DOI: 10.1016/j.heliyon.2024.e31917] [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: 01/25/2024] [Revised: 05/23/2024] [Accepted: 05/23/2024] [Indexed: 06/14/2024] Open
Abstract
Background and aims The mechanisms occur in children with obesity after lifestyle intervention remain poorly explained. Here, we investigated the serum proteomes and metabolomes of children with obesity who had undergone 30 days of weight loss intervention. Methods and results Serum samples and clinical parameters were collected before and after lifestyle alteration interventions. Proteomic and metabolomic profiling was used to identify the differentially expressed proteins and differentially abundant metabolites in response to weight loss intervention. Lifestyle alteration interventions significantly decreased BMI, waist circumference, hip circumference and body fat, total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL) and high non-HDL cholesterol, but not TG and high-density lipoprotein cholesterol (HDL), in children with obesity. By comparing the multiomics data, we identified 43 proteins and 165 metabolites that were significantly differentially expressed in children with obesity before and after lifestyle alteration interventions. Using integrated -omics analysis, we obtained 7 KEGG pathways that were organically integrated based on the correlations between differentially expressed proteins (DEPs) and metabolites (DMs). Further interaction analysis identified 7 proteins as candidate DEPs and 9 metabolites as candidate DMs. Interestingly, we found that some of these candidate DEPs and candidate DMs were significantly correlated with clinical parameters. Conclusion Our results provide valuable proteome and metabolome data resources for better understanding weight loss-associated responses in children with obesity. In addition, we analyzed the number of significantly differentially expressed proteins and metabolites, shed new light on weight loss pathogenesis in children with obesity, and added potential therapeutic agents for obese children.
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Affiliation(s)
- Xiaoguang Liu
- School of Sport and Health, Guangzhou Sport University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Physical Activity and Health Promotion, Guangzhou Sport University, Guangzhou, China
| | - Huiguo Wang
- School of Sport and Health, Guangzhou Sport University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Physical Activity and Health Promotion, Guangzhou Sport University, Guangzhou, China
| | - Lin Zhu
- School of Sport and Health, Guangzhou Sport University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Physical Activity and Health Promotion, Guangzhou Sport University, Guangzhou, China
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2
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Chen Z, Dodig-Crnković T, Schwenk JM, Tao SC. Current applications of antibody microarrays. Clin Proteomics 2018; 15:7. [PMID: 29507545 PMCID: PMC5830343 DOI: 10.1186/s12014-018-9184-2] [Citation(s) in RCA: 56] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2017] [Accepted: 02/19/2018] [Indexed: 12/14/2022] Open
Abstract
The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis.
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Affiliation(s)
- Ziqing Chen
- Key Laboratory of Systems Biomedicine, (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240 China
| | - Tea Dodig-Crnković
- Affinity Proteomics, SciLifeLab, KTH - Royal Institute of Technology, 171 65 Solna, Sweden
| | - Jochen M. Schwenk
- Affinity Proteomics, SciLifeLab, KTH - Royal Institute of Technology, 171 65 Solna, Sweden
| | - Sheng-ce Tao
- Key Laboratory of Systems Biomedicine, (Ministry of Education), Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai, 200240 China
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
- State Key Laboratory of Oncogenes and Related Genes, Shanghai Jiao Tong University, Shanghai, 200240 China
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3
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Digital gene expression analysis of Takifugu rubripes brain after acute hypoxia exposure using next-generation sequencing. COMPARATIVE BIOCHEMISTRY AND PHYSIOLOGY D-GENOMICS & PROTEOMICS 2017; 24:12-18. [DOI: 10.1016/j.cbd.2017.05.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Revised: 03/07/2017] [Accepted: 05/27/2017] [Indexed: 01/21/2023]
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Ayoglu B, Birgersson E, Mezger A, Nilsson M, Uhlén M, Nilsson P, Schwenk JM. Multiplexed protein profiling by sequential affinity capture. Proteomics 2016; 16:1251-6. [PMID: 26935855 PMCID: PMC5071697 DOI: 10.1002/pmic.201500398] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2015] [Revised: 01/18/2016] [Accepted: 02/29/2016] [Indexed: 01/07/2023]
Abstract
Antibody microarrays enable parallelized and miniaturized analysis of clinical samples, and have proven to provide novel insights for the analysis of different proteomes. However, there are concerns that the performance of such direct labeling and single antibody assays are prone to off‐target binding due to the sample context. To improve selectivity and sensitivity while maintaining the possibility to conduct multiplexed protein profiling, we developed a multiplexed and semi‐automated sequential capture assay. This novel bead‐based procedure encompasses a first antigen capture, labeling of captured protein targets on magnetic particles, combinatorial target elution and a read‐out by a secondary capture bead array. We demonstrate in a proof‐of‐concept setting that target detection via two sequential affinity interactions reduced off‐target contribution, while lowered background and noise levels, improved correlation to clinical values compared to single binder assays. We also compared sensitivity levels with single binder and classical sandwich assays, explored the possibility for DNA‐based signal amplification, and demonstrate the applicability of the dual capture bead‐based antibody microarray for biomarker analysis. Hence, the described concept enhances the possibilities for antibody array assays to be utilized for protein profiling in body fluids and beyond.
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Affiliation(s)
- Burcu Ayoglu
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Elin Birgersson
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Anja Mezger
- Department of Biochemistry and Biophysics, SciLifeLab, Stockholm University, Solna, Sweden
| | - Mats Nilsson
- Department of Biochemistry and Biophysics, SciLifeLab, Stockholm University, Solna, Sweden
| | - Mathias Uhlén
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Peter Nilsson
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
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5
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Fredolini C, Byström S, Pin E, Edfors F, Tamburro D, Iglesias MJ, Häggmark A, Hong MG, Uhlen M, Nilsson P, Schwenk JM. Immunocapture strategies in translational proteomics. Expert Rev Proteomics 2015; 13:83-98. [PMID: 26558424 PMCID: PMC4732419 DOI: 10.1586/14789450.2016.1111141] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Aiming at clinical studies of human diseases, antibody-assisted assays have been applied to biomarker discovery and toward a streamlined translation from patient profiling to assays supporting personalized treatments. In recent years, integrated strategies to couple and combine antibodies with mass spectrometry-based proteomic efforts have emerged, allowing for novel possibilities in basic and clinical research. Described in this review are some of the field's current and emerging immunocapture approaches from an affinity proteomics perspective. Discussed are some of their advantages, pitfalls and opportunities for the next phase in clinical and translational proteomics.
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Affiliation(s)
- Claudia Fredolini
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Sanna Byström
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Elisa Pin
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Fredrik Edfors
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Davide Tamburro
- Department of Oncology-Pathology, Clinical Proteomics Mass Spectrometry, SciLifeLab, Karolinska Institutet, Solna, Sweden
| | - Maria Jesus Iglesias
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Anna Häggmark
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Mun-Gwan Hong
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Mathias Uhlen
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Peter Nilsson
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH - Royal Institute of Technology, Solna, Sweden
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6
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Boström T, Takanen JO, Hober S. Antibodies as means for selective mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2015; 1021:3-13. [PMID: 26565067 DOI: 10.1016/j.jchromb.2015.10.042] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2015] [Revised: 10/15/2015] [Accepted: 10/23/2015] [Indexed: 01/21/2023]
Abstract
For protein analysis of biological samples, two major strategies are used today; mass spectrometry (MS) and antibody-based methods. Each strategy offers advantages and drawbacks. However, combining the two using an immunoenrichment step with MS analysis brings together the benefits of each method resulting in increased sensitivity, faster analysis and possibility of higher degrees of multiplexing. The immunoenrichment can be performed either on protein or peptide level and quantification standards can be added in order to enable determination of the absolute protein concentration in the sample. The combination of immunoenrichment and MS holds great promise for the future in both proteomics and clinical diagnostics. This review describes different setups of immunoenrichment coupled to mass spectrometry and how these can be utilized in various applications.
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Affiliation(s)
- Tove Boström
- School of Biotechnology, Division of Protein Technology, KTH-Royal Institute of Technology, AlbaNova University Center, SE-106 91 Stockholm, Sweden
| | - Jenny Ottosson Takanen
- School of Biotechnology, Division of Proteomics and Nanobiotechnology, KTH-Royal Institute ofTechnology, AlbaNova University Center, SE-106 91 Stockholm, Sweden
| | - Sophia Hober
- School of Biotechnology, Division of Protein Technology, KTH-Royal Institute of Technology, AlbaNova University Center, SE-106 91 Stockholm, Sweden.
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7
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Arner P, Henjes F, Schwenk JM, Darmanis S, Dahlman I, Iresjö BM, Naredi P, Agustsson T, Lundholm K, Nilsson P, Rydén M. Circulating carnosine dipeptidase 1 associates with weight loss and poor prognosis in gastrointestinal cancer. PLoS One 2015; 10:e0123566. [PMID: 25898255 PMCID: PMC4405487 DOI: 10.1371/journal.pone.0123566] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2014] [Accepted: 02/19/2015] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Cancer cachexia (CC) is linked to poor prognosis. Although the mechanisms promoting this condition are not known, several circulating proteins have been proposed to contribute. We analyzed the plasma proteome in cancer subjects in order to identify factors associated with cachexia. DESIGN/SUBJECTS Plasma was obtained from a screening cohort of 59 patients, newly diagnosed with suspected gastrointestinal cancer, with (n = 32) or without (n = 27) cachexia. Samples were subjected to proteomic profiling using 760 antibodies (targeting 698 individual proteins) from the Human Protein Atlas project. The main findings were validated in a cohort of 93 patients with verified and advanced pancreas cancer. RESULTS Only six proteins displayed differential plasma levels in the screening cohort. Among these, Carnosine Dipeptidase 1 (CNDP1) was confirmed by sandwich immunoassay to be lower in CC (p = 0.008). In both cohorts, low CNDP1 levels were associated with markers of poor prognosis including weight loss, malnutrition, lipid breakdown, low circulating albumin/IGF1 levels and poor quality of life. Eleven of the subjects in the discovery cohort were finally diagnosed with non-malignant disease but omitting these subjects from the analyses did not have any major influence on the results. CONCLUSIONS In gastrointestinal cancer, reduced plasma levels of CNDP1 associate with signs of catabolism and poor outcome. These results, together with recently published data demonstrating lower circulating CNDP1 in subjects with glioblastoma and metastatic prostate cancer, suggest that CNDP1 may constitute a marker of aggressive cancer and CC.
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Affiliation(s)
- Peter Arner
- Department of Medicine (H7), Karolinska Institutet, Karolinska University Hospital, Huddinge, 141 86, Stockholm, Sweden
| | - Frauke Henjes
- Affinity Proteomics, Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Jochen M. Schwenk
- Affinity Proteomics, Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Spyros Darmanis
- Affinity Proteomics, Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Ingrid Dahlman
- Department of Medicine (H7), Karolinska Institutet, Karolinska University Hospital, Huddinge, 141 86, Stockholm, Sweden
| | - Britt-Marie Iresjö
- Department of Surgery, Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Peter Naredi
- Department of Surgery, Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Thorhallur Agustsson
- Division of Surgery, Department for Clinical Science, Intervention and Technology (CLINTEC), Södersjukhuset, 118 83, Stockholm, Sweden
| | - Kent Lundholm
- Department of Surgery, Sahlgrenska Academy, University of Gothenburg, 413 45, Gothenburg, Sweden
| | - Peter Nilsson
- Affinity Proteomics, Science for Life Laboratory, School of Biotechnology, Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Mikael Rydén
- Department of Medicine (H7), Karolinska Institutet, Karolinska University Hospital, Huddinge, 141 86, Stockholm, Sweden
- * E-mail:
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8
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Ayoglu B, Chaouch A, Lochmüller H, Politano L, Bertini E, Spitali P, Hiller M, Niks EH, Gualandi F, Pontén F, Bushby K, Aartsma-Rus A, Schwartz E, Le Priol Y, Straub V, Uhlén M, Cirak S, 't Hoen PAC, Muntoni F, Ferlini A, Schwenk JM, Nilsson P, Al-Khalili Szigyarto C. Affinity proteomics within rare diseases: a BIO-NMD study for blood biomarkers of muscular dystrophies. EMBO Mol Med 2015; 6:918-36. [PMID: 24920607 PMCID: PMC4119355 DOI: 10.15252/emmm.201303724] [Citation(s) in RCA: 87] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Despite the recent progress in the broad-scaled analysis of proteins in body fluids, there is still a lack in protein profiling approaches for biomarkers of rare diseases. Scarcity of samples is the main obstacle hindering attempts to apply discovery driven protein profiling in rare diseases. We addressed this challenge by combining samples collected within the BIO-NMD consortium from four geographically dispersed clinical sites to identify protein markers associated with muscular dystrophy using an antibody bead array platform with 384 antibodies. Based on concordance in statistical significance and confirmatory results obtained from analysis of both serum and plasma, we identified eleven proteins associated with muscular dystrophy, among which four proteins were elevated in blood from muscular dystrophy patients: carbonic anhydrase III (CA3) and myosin light chain 3 (MYL3), both specifically expressed in slow-twitch muscle fibers and mitochondrial malate dehydrogenase 2 (MDH2) and electron transfer flavoprotein A (ETFA). Using age-matched sub-cohorts, 9 protein profiles correlating with disease progression and severity were identified, which hold promise for the development of new clinical tools for management of dystrophinopathies.
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Affiliation(s)
- Burcu Ayoglu
- Affinity Proteomics, SciLifeLab, School of Biotechnology KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Amina Chaouch
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Hanns Lochmüller
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Luisa Politano
- Cardiomiology and Medical Genetics, Department of Experimental Medicine, Second University of Naples, Naples, Italy
| | - Enrico Bertini
- Unit of Neuromuscular and Neurodegenerative Disorders, Department of Neurosciences, Bambino Gesú Children's Hospital, Rome, Italy
| | - Pietro Spitali
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Monika Hiller
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Eric H Niks
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Francesca Gualandi
- Unit of Medical Genetics, Department of Medical Sciences, University of Ferrara, Ferrara, Italy
| | - Fredrik Pontén
- SciLifeLab, Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, Sweden
| | - Kate Bushby
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Annemieke Aartsma-Rus
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | | | | | - Volker Straub
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Mathias Uhlén
- Affinity Proteomics, SciLifeLab, School of Biotechnology KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Sebahattin Cirak
- Research Center for Genetic Medicine, Childrens National Medical Center, Washington, DC, USA
| | - Peter A C 't Hoen
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Francesco Muntoni
- The Dubowitz Neuromuscular Centre, UCL Institute of Child Health, London, UK
| | - Alessandra Ferlini
- Unit of Medical Genetics, Department of Medical Sciences, University of Ferrara, Ferrara, Italy
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab, School of Biotechnology KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Peter Nilsson
- Affinity Proteomics, SciLifeLab, School of Biotechnology KTH-Royal Institute of Technology, Stockholm, Sweden
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