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Kaag Rasmussen M, Møllgård K, Bork PAR, Weikop P, Esmail T, Drici L, Wewer Albrechtsen NJ, Carlsen JF, Huynh NPT, Ghitani N, Mann M, Goldman SA, Mori Y, Chesler AT, Nedergaard M. Trigeminal ganglion neurons are directly activated by influx of CSF solutes in a migraine model. Science 2024; 385:80-86. [PMID: 38963846 DOI: 10.1126/science.adl0544] [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: 09/27/2023] [Accepted: 05/01/2024] [Indexed: 07/06/2024]
Abstract
Classical migraine patients experience aura, which is transient neurological deficits associated with cortical spreading depression (CSD), preceding headache attacks. It is not currently understood how a pathological event in cortex can affect peripheral sensory neurons. In this study, we show that cerebrospinal fluid (CSF) flows into the trigeminal ganglion, establishing nonsynaptic signaling between brain and trigeminal cells. After CSD, ~11% of the CSF proteome is altered, with up-regulation of proteins that directly activate receptors in the trigeminal ganglion. CSF collected from animals exposed to CSD activates trigeminal neurons in naïve mice in part by CSF-borne calcitonin gene-related peptide (CGRP). We identify a communication pathway between the central and peripheral nervous system that might explain the relationship between migrainous aura and headache.
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Affiliation(s)
- Martin Kaag Rasmussen
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Kjeld Møllgård
- Department of Cellular and Molecular Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Peter A R Bork
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Pia Weikop
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Tina Esmail
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Lylia Drici
- NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Nicolai J Wewer Albrechtsen
- NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Department for Clinical Biochemistry, University Hospital Copenhagen - Bispebjerg, Copenhagen, 2400 Copenhagen, Denmark
| | - Jonathan Frederik Carlsen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Department of Radiology, Copenhagen University Hospital-Rigshospitalet, 2100 Copenhagen, Denmark
| | - Nguyen P T Huynh
- Center for Translational Neuromedicine, Division of Glial Disease and Therapeutics, University of Rochester Medical Center, Rochester, NY 14642, USA
- Sana Biotechnology, Cambridge, MA 02139, USA
| | - Nima Ghitani
- National Center for Complementary and Integrative Health (NCCIH), Bethesda, MD 20892, USA
| | - Matthias Mann
- NNF Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Department of Proteomics and Signal Transduction, Max-Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Steven A Goldman
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
- Center for Translational Neuromedicine, Division of Glial Disease and Therapeutics, University of Rochester Medical Center, Rochester, NY 14642, USA
- Sana Biotechnology, Cambridge, MA 02139, USA
| | - Yuki Mori
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
| | - Alexander T Chesler
- National Center for Complementary and Integrative Health (NCCIH), Bethesda, MD 20892, USA
- National Institute of Neurological Disorders and Stroke, Bethesda, MD 20892, USA
| | - Maiken Nedergaard
- Center for Translational Neuromedicine, University of Copenhagen, 2200 Copenhagen, Denmark
- Center for Translational Neuromedicine, Division of Glial Disease and Therapeutics, University of Rochester Medical Center, Rochester, NY 14642, USA
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Kreft IC, van Duijl TT, van Kwawegen C, Atiq F, Phan W, Schuller MBP, Boon-Spijker M, van der Zwaan C, Meijer AB, Hoogendijk AJ, Bierings R, Eikenboom JCJ, Leebeek FWG, van den Biggelaar M. Variant mapping using mass spectrometry-based proteotyping as a diagnostic tool in von Willebrand disease. J Thromb Haemost 2024; 22:1894-1908. [PMID: 38679335 DOI: 10.1016/j.jtha.2024.04.011] [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: 01/17/2024] [Revised: 03/20/2024] [Accepted: 04/15/2024] [Indexed: 05/01/2024]
Abstract
BACKGROUND von Willebrand disease (VWD) is the most common inherited bleeding disorder, characterized by either partial or complete von Willebrand factor (VWF) deficiency or by the occurrence of VWF proteoforms of altered functionality. The gene encoding VWF is highly polymorphic, giving rise to a variety of proteoforms with varying plasma concentrations and clinical significance. OBJECTIVES To address this complexity, we translated genomic variation in VWF to corresponding VWF proteoforms circulating in blood. METHODS VWF was characterized in VWD patients (n = 64) participating in the Willebrand in the Netherlands study by conventional laboratory testing, DNA sequencing and complementary discovery, and targeted mass spectrometry-based plasma proteomic strategies. RESULTS Unbiased plasma profiling combined with immune enrichment of VWF verified VWF and its binding partner factor VIII as key determinants of VWD and revealed a remarkable heterogeneity in VWF amino acid sequence coverage among patients. Subsequent VWF proteotyping enabled identification of both polymorphisms (eg, p.Thr789Ala, p.Gln852Arg, and p.Thr1381Ala), as well as pathogenic variants (n = 16) along with their corresponding canonical sequences. Targeted proteomics using stable isotope-labeled peptides confirmed unbiased proteotyping for 5 selected variants and suggested differential proteoform quantities in plasma. The variant-to-wild-type peptide ratio was determined in 6 type 2B patients heterozygous for p.Arg1306Trp, confirming the relatively low proteoform concentration of the pathogenic variant. The elevated VWF propeptide/VWF ratio indicated increased clearance of specific VWF proteoforms. CONCLUSION This study highlights how VWF proteotyping from plasma could be the first step to bridge the gap between genotyping and functional testing in VWD.
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Affiliation(s)
- Iris C Kreft
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands.
| | - Tirsa T van Duijl
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands
| | - Calvin van Kwawegen
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Ferdows Atiq
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Winny Phan
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands
| | - Margo B P Schuller
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands
| | - Mariëtte Boon-Spijker
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands
| | - Carmen van der Zwaan
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands
| | - Alexander B Meijer
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands; Department of Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, the Netherlands
| | - Arie J Hoogendijk
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands
| | - Ruben Bierings
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jeroen C J Eikenboom
- Department of Internal Medicine, Division of Thrombosis and Hemostasis, Leiden University Medical Center, Leiden, the Netherlands
| | - Frank W G Leebeek
- Department of Hematology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Maartje van den Biggelaar
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, the Netherlands.
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Zelicha H, Kaplan A, Yaskolka Meir A, Rinott E, Tsaban G, Blüher M, Klöting N, Ceglarek U, Isermann B, Stumvoll M, Chassidim Y, Shelef I, Hu FB, Shai I. Altered proteome profiles related to visceral adiposity may mediate the favorable effect of green Mediterranean diet: the DIRECT-PLUS trial. Obesity (Silver Spring) 2024; 32:1245-1256. [PMID: 38757229 DOI: 10.1002/oby.24036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 03/08/2024] [Accepted: 03/19/2024] [Indexed: 05/18/2024]
Abstract
OBJECTIVE The objective of this study was to explore the effects of a green Mediterranean (green-MED) diet, which is high in dietary polyphenols and green plant-based protein and low in red/processed meat, on cardiovascular disease and inflammation-related circulating proteins and their associations with cardiometabolic risk parameters. METHODS In the 18-month weight loss trial Dietary Intervention Randomized Controlled Trial Polyphenols Unprocessed Study (DIRECT-PLUS), 294 participants with abdominal obesity were randomized to basic healthy dietary guidelines, Mediterranean (MED), or green-MED diets. Both isocaloric MED diet groups consumed walnuts (28 g/day), and the green-MED diet group also consumed green tea (3-4 cups/day) and green shakes (Mankai plant shake, 500 mL/day) and avoided red/processed meat. Proteome panels were measured at three time points using Olink CVDII. RESULTS At baseline, a dominant protein cluster was significantly related to higher phenotypic cardiometabolic risk parameters, with the strongest associations attributed to magnetic resonance imaging-assessed visceral adiposity (false discovery rate of 5%). Overall, after 6 months of intervention, both the MED and green-MED diets induced improvements in cardiovascular disease and proinflammatory risk proteins (p < 0.05, vs. healthy dietary guidelines), with the green-MED diet leading to more pronounced beneficial changes, largely driven by dominant proinflammatory proteins (IL-1 receptor antagonist protein, IL-16, IL-18, thrombospondin-2, leptin, prostasin, galectin-9, and fibroblast growth factor 21; adjusted for age, sex, and weight loss; p < 0.05). After 18 months, proteomics cluster changes presented the strongest correlations with visceral adiposity reduction. CONCLUSIONS Proteomics clusters may enhance our understanding of the favorable effect of a green-MED diet that is enriched with polyphenols and low in red/processed meat on visceral adiposity and cardiometabolic risk.
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Affiliation(s)
- Hila Zelicha
- The Health and Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Alon Kaplan
- The Health and Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Anat Yaskolka Meir
- The Health and Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Ehud Rinott
- The Health and Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Gal Tsaban
- The Health and Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
| | - Matthias Blüher
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Nora Klöting
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Zentrum München at the University of Leipzig and University Hospital Leipzig, Leipzig, Germany
| | - Uta Ceglarek
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Berend Isermann
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | | | - Yoash Chassidim
- Department of Engineering, Sapir Academic College, Sapir, Israel
| | - Ilan Shelef
- Soroka University Medical Center, Be'er Sheva, Israel
| | - Frank B Hu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
- Harvard Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Iris Shai
- The Health and Nutrition Innovative International Research Center, Faculty of Health Sciences, Ben-Gurion University of the Negev, Be'er Sheva, Israel
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
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London A, Richter MM, Sjøberg KA, Wewer Albrechtsen NJ, Považan M, Drici L, Schaufuss A, Madsen L, Øyen J, Madsbad S, Holst JJ, van Hall G, Siebner HR, Richter EA, Kiens B, Lundsgaard A, Bojsen-Møller KN. The Impact of Short-term Eucaloric Low-Carbohydrate and High-Carbohydrate Diet on Liver Triacylglycerol Content in Males with Overweight and Obesity; a Randomized Cross-Over Study. Am J Clin Nutr 2024:S0002-9165(24)00540-9. [PMID: 38914224 DOI: 10.1016/j.ajcnut.2024.06.006] [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: 01/25/2024] [Revised: 06/12/2024] [Accepted: 06/17/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Intrahepatic triacylglycerol (liver TG) content is associated with hepatic insulin resistance and dyslipidemia. Liver TG content can be modulated within days under hypocaloric conditions. OBJECTIVE We hypothesized that four days of eucaloric low-carbohydrate/high-fat (LC) intake would decrease liver TG content while a high-carbohydrate/low-fat (HC) intake would increase liver TG content, and further that alterations in liver TG would be linked to dynamic changes in hepatic glucose and lipid metabolism. METHODS A randomized cross-over trial in males with 4 days + 4 days of LC and HC, respectively, with at least 2 weeks of wash-out. 1H-Magnetic Resonance Spectroscopy (1H-MRS) was used to measure liver TG content, with metabolic testing before and after intake of LC diet (11E% carbohydrate corresponding to 102±12 (mean±SD) g/day, 70E% fat) and a HC diet (65E% carbohydrate corresponding to 537±56 g/day, 16E% fat). Stable [6,6-2H2]-glucose and [1,1,2,3,3-D5]-glycerol tracer infusions combined with hyperinsulinemic-euglycemic clamps and indirect calorimetry were used to measure rates of hepatic glucose production (HGP) and lipolysis, whole body insulin sensitivity and substrate oxidation. RESULTS Eleven normoglycemic males with overweight or obesity (BMI 31.6±3.7 kg/m2) completed both diets. The LC diet reduced liver TG content by 35.3% (95%CI: -46.6;-24.1) from 4.9 % [2.4-11.0] (median [IQR]) to 2.9% [1.4-6.9], while there was no change after the HC diet. After the LC diet, fasting whole-body fat oxidation and plasma beta-hydroxybutyrate concentration increased, while markers of de novo lipogenesis diminished. Fasting plasma TG and insulin concentrations were lowered and the hepatic insulin sensitivity index (HISI) increased after LC. Peripheral glucose disposal was unchanged. CONCLUSION Reduced carbohydrate and increased fat intake for four days induced a marked reduction in liver TG content and increased hepatic insulin sensitivity. Increased rates of fat oxidation and ketogenesis combined with lower rates of de novo lipogenesis are suggested to be responsible for lowering of liver TG. CLINICAL TRIAL REGISTRY NUMBER AND WEBSITE WHERE IT WAS OBTAINED: clinicaltrials.gov (NCT04581421).
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Affiliation(s)
- Amalie London
- Department of Endocrinology, Copenhagen University Hospital Hvidovre, Denmark; The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Michael M Richter
- Department of Endocrinology, Copenhagen University Hospital Hvidovre, Denmark; The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark; Department of Clinical Biochemistry, Copenhagen University Hospital Bispebjerg and Frederiksberg, Denmark
| | - Kim Anker Sjøberg
- The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Nicolai J Wewer Albrechtsen
- Department of Clinical Biochemistry, Copenhagen University Hospital Bispebjerg and Frederiksberg, Denmark; NNF Center for Protein Research, University of Copenhagen, Denmark
| | - Michal Považan
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Denmark
| | - Lylia Drici
- Department of Clinical Biochemistry, Copenhagen University Hospital Bispebjerg and Frederiksberg, Denmark; NNF Center for Protein Research, University of Copenhagen, Denmark
| | - Amanda Schaufuss
- The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Lise Madsen
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Denmark; Institute of Marine Research, Bergen, Norway
| | | | - Sten Madsbad
- Department of Endocrinology, Copenhagen University Hospital Hvidovre, Denmark
| | - Jens Juul Holst
- Department of Biomedical Sciences and the NNF Center for Basic Metabolic Research, University of Copenhagen, Denmark
| | - Gerrit van Hall
- Department of Clinical Metabolomics, Rigshospitalet, Denmark
| | - Hartwig Roman Siebner
- Danish Research Centre for Magnetic Resonance (DRCMR), Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Amager and Hvidovre, Denmark; Department of Neurology, Copenhagen University Hospital Bispebjerg and Frederiksberg, Denmark
| | - Erik A Richter
- The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Bente Kiens
- The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Annemarie Lundsgaard
- The August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Denmark
| | - Kirstine Nyvold Bojsen-Møller
- Department of Endocrinology, Copenhagen University Hospital Hvidovre, Denmark; Department of Clinical Medicine, University of Copenhagen, Denmark.
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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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Kurgan N, Kjærgaard Larsen J, Deshmukh AS. Harnessing the power of proteomics in precision diabetes medicine. Diabetologia 2024; 67:783-797. [PMID: 38345659 DOI: 10.1007/s00125-024-06097-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 12/20/2023] [Indexed: 03/21/2024]
Abstract
Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.
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Affiliation(s)
- Nigel Kurgan
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Jeppe Kjærgaard Larsen
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Atul S Deshmukh
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark.
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Wang C, Feng G, Zhao J, Xu Y, Li Y, Wang L, Wang M, Liu M, Wang Y, Mu H, Zhou C. Screening of novel biomarkers for acute kidney transplant rejection using DIA-MS based proteomics. Proteomics Clin Appl 2024; 18:e2300047. [PMID: 38215274 DOI: 10.1002/prca.202300047] [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: 04/27/2023] [Revised: 11/03/2023] [Accepted: 11/22/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND Kidney transplantation is the preferred treatment for patients with end-stage renal disease. However, acute rejection poses a threat to the graft long-term survival. The aim of this study was to identify novel biomarkers to detect acute kidney transplant rejection. METHODS The serum proteomic profiling of kidney transplant patients with T cell-mediated acute rejection (TCMR) and stable allograft function (STA) was analyzed using data-independent acquisition mass spectrometry (DIA-MS). The differentially expressed proteins (DEPs) of interest were further verified by enzyme-linked immunosorbent assay (ELISA). RESULTS A total of 131 DEPs were identified between STA and TCMR patients, 114 DEPs were identified between mild and severe TCMR patients. The verification results showed that remarkable higher concentrations of serum amyloid A protein 1 (SAA1) and insulin like growth factor binding protein 2 (IGFBP2), and lower fetuin-A (AHSG) concentration were found in TCMR patients when compared with STA patients. We also found higher SAA1 concentration in severe TCMR group when compared with mild TCMR group. The receiver operating characteristics (ROC) analysis further confirmed that combination of SAA1, AHSG, and IGFBP2 had excellent performance in the acute rejection diagnosis. CONCLUSIONS Our data demonstrated that serum SAA1, AHSG, and IGFBP2 could be effective biomarkers for diagnosing acute rejection after kidney transplantation. DIA-MS has great potential in biomarker screening of kidney transplantation.
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Affiliation(s)
- Ce Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Gang Feng
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Jie Zhao
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yang Xu
- Department of Kidney Transplant, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Yang Li
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Lin Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Meng Wang
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Miao Liu
- The First Central Clinical School, Tianjin Medical University, Tianjin, China
| | - Yilin Wang
- The First Central Clinical School, Tianjin Medical University, Tianjin, China
| | - Hong Mu
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
| | - Chunlei Zhou
- Department of Clinical Laboratory, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China
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Kiseleva OI, Pyatnitskiy MA, Arzumanian VA, Kurbatov IY, Ilinsky VV, Ilgisonis EV, Plotnikova OA, Sharafetdinov KK, Tutelyan VA, Nikityuk DB, Ponomarenko EA, Poverennaya EV. Multiomics Picture of Obesity in Young Adults. BIOLOGY 2024; 13:272. [PMID: 38666884 PMCID: PMC11048234 DOI: 10.3390/biology13040272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 04/02/2024] [Accepted: 04/12/2024] [Indexed: 04/28/2024]
Abstract
Obesity is a socially significant disease that is characterized by a disproportionate accumulation of fat. It is also associated with chronic inflammation, cancer, diabetes, and other comorbidities. Investigating biomarkers and pathological processes linked to obesity is especially vital for young individuals, given their increased potential for lifestyle modifications. By comparing the genetic, proteomic, and metabolomic profiles of individuals categorized as underweight, normal, overweight, and obese, we aimed to determine which omics layer most accurately reflects the phenotypic changes in an organism that result from obesity. We profiled blood plasma samples by employing three omics methodologies. The untargeted GC×GC-MS metabolomics approach identified 313 metabolites. To augment the metabolomic dataset, we integrated a label-free HPLC-MS/MS proteomics method, leading to the identification of 708 proteins. The genomic layer encompassed the genotyping of 647,250 SNPs. Utilizing omics data, we trained sparse Partial Least Squares models to predict body mass index. Molecular features exhibiting frequently non-zero coefficients were selected as potential biomarkers, and we further explored enriched biological pathways. Proteomics was the most effective in single-omics analyses, with a median absolute error (MAE) of 5.44 ± 0.31 kg/m2, incorporating an average of 24 proteins per model. Metabolomics showed slightly lower performance (MAE = 6.06 ± 0.33 kg/m2), followed by genomics (MAE = 6.20 ± 0.34 kg/m2). As expected, multiomic models demonstrated better accuracy, particularly the combination of proteomics and metabolomics (MAE = 4.77 ± 0.33 kg/m2), while including genomics data did not enhance the results. This manuscript is the first multiomics study of obesity in a gender-balanced cohort of young adults profiled by genomic, proteomic, and metabolomic methods. The comprehensive approach provides novel insights into the molecular mechanisms of obesity, opening avenues for more targeted interventions.
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Affiliation(s)
- Olga I. Kiseleva
- Institute of Biomedical Chemistry, Moscow 119121, Russia; (O.I.K.)
| | - Mikhail A. Pyatnitskiy
- Institute of Biomedical Chemistry, Moscow 119121, Russia; (O.I.K.)
- Faculty of Computer Science, National Research University Higher School of Economics, Moscow 101000, Russia
| | | | - Ilya Y. Kurbatov
- Institute of Biomedical Chemistry, Moscow 119121, Russia; (O.I.K.)
| | | | | | - Oksana A. Plotnikova
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
| | - Khaider K. Sharafetdinov
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
- Russian Medical Academy of Continuing Professional Education, Ministry of Health of the Russian Federation, Moscow 125993, Russia
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, Moscow 119991, Russia
| | - Victor A. Tutelyan
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, Moscow 119991, Russia
| | - Dmitry B. Nikityuk
- Federal Research Centre of Nutrition, Biotechnology and Food Safety, Russian Academy of Sciences, Moscow 109240, Russia
- I.M. Sechenov First Moscow State Medical University (Sechenov University), Ministry of Health of the Russian Federation, Moscow 119991, Russia
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9
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Pietzner M, Uluvar B, Kolnes KJ, Jeppesen PB, Frivold SV, Skattebo Ø, Johansen EI, Skålhegg BS, Wojtaszewski JFP, Kolnes AJ, Yeo GSH, O'Rahilly S, Jensen J, Langenberg C. Systemic proteome adaptions to 7-day complete caloric restriction in humans. Nat Metab 2024; 6:764-777. [PMID: 38429390 DOI: 10.1038/s42255-024-01008-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Accepted: 02/01/2024] [Indexed: 03/03/2024]
Abstract
Surviving long periods without food has shaped human evolution. In ancient and modern societies, prolonged fasting was/is practiced by billions of people globally for religious purposes, used to treat diseases such as epilepsy, and recently gained popularity as weight loss intervention, but we still have a very limited understanding of the systemic adaptions in humans to extreme caloric restriction of different durations. Here we show that a 7-day water-only fast leads to an average weight loss of 5.7 kg (±0.8 kg) among 12 volunteers (5 women, 7 men). We demonstrate nine distinct proteomic response profiles, with systemic changes evident only after 3 days of complete calorie restriction based on in-depth characterization of the temporal trajectories of ~3,000 plasma proteins measured before, daily during, and after fasting. The multi-organ response to complete caloric restriction shows distinct effects of fasting duration and weight loss and is remarkably conserved across volunteers with >1,000 significantly responding proteins. The fasting signature is strongly enriched for extracellular matrix proteins from various body sites, demonstrating profound non-metabolic adaptions, including extreme changes in the brain-specific extracellular matrix protein tenascin-R. Using proteogenomic approaches, we estimate the health consequences for 212 proteins that change during fasting across ~500 outcomes and identified putative beneficial (SWAP70 and rheumatoid arthritis or HYOU1 and heart disease), as well as adverse effects. Our results advance our understanding of prolonged fasting in humans beyond a merely energy-centric adaptions towards a systemic response that can inform targeted therapeutic modulation.
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Affiliation(s)
- Maik Pietzner
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK.
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
| | - Burulça Uluvar
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Kristoffer J Kolnes
- Department of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway
- Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark
| | - Per B Jeppesen
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - S Victoria Frivold
- Institute of Health and Society, Faculty of Medicine, University of Oslo, Oslo, Norway
| | - Øyvind Skattebo
- Department of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway
| | - Egil I Johansen
- Department of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway
| | - Bjørn S Skålhegg
- Department of Nutrition, Division for Molecular Nutrition, University of Oslo, Oslo, Norway
| | - Jørgen F P Wojtaszewski
- August Krogh Section for Molecular Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark
| | - Anders J Kolnes
- Section of Specialized Endocrinology, Department of Endocrinology, Oslo University Hospital, Oslo, Norway
| | - Giles S H Yeo
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Stephen O'Rahilly
- Metabolic Research Laboratory, Wellcome-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jørgen Jensen
- Department of Physical Performance, Norwegian School of Sport Sciences, Oslo, Norway
| | - Claudia Langenberg
- Computational Medicine, Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany.
- Precision Healthcare University Research Institute, Queen Mary University of London, London, UK.
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK.
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10
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Shome M, MacKenzie TMG, Subbareddy SR, Snyder MP. The Importance, Challenges, and Possible Solutions for Sharing Proteomics Data While Safeguarding Individuals' Privacy. Mol Cell Proteomics 2024; 23:100731. [PMID: 38331191 PMCID: PMC10915627 DOI: 10.1016/j.mcpro.2024.100731] [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: 08/14/2023] [Revised: 01/28/2024] [Accepted: 02/05/2024] [Indexed: 02/10/2024] Open
Abstract
Proteomics data sharing has profound benefits at the individual level as well as at the community level. While data sharing has increased over the years, mostly due to journal and funding agency requirements, the reluctance of researchers with regard to data sharing is evident as many shares only the bare minimum dataset required to publish an article. In many cases, proper metadata is missing, essentially making the dataset useless. This behavior can be explained by a lack of incentives, insufficient awareness, or a lack of clarity surrounding ethical issues. Through adequate training at research institutes, researchers can realize the benefits associated with data sharing and can accelerate the norm of data sharing for the field of proteomics, as has been the standard in genomics for decades. In this article, we have put together various repository options available for proteomics data. We have also added pros and cons of those repositories to facilitate researchers in selecting the repository most suitable for their data submission. It is also important to note that a few types of proteomics data have the potential to re-identify an individual in certain scenarios. In such cases, extra caution should be taken to remove any personal identifiers before sharing on public repositories. Data sets that will be useless without personal identifiers need to be shared in a controlled access repository so that only authorized researchers can access the data and personal identifiers are kept safe.
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Affiliation(s)
- Mahasish Shome
- Department of Genetics, Stanford University, Palo Alto, California, USA
| | - Tim M G MacKenzie
- Department of Genetics, Stanford University, Palo Alto, California, USA
| | | | - Michael P Snyder
- Department of Genetics, Stanford University, Palo Alto, California, USA.
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11
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Steigerwald S, Sinha A, Fort KL, Zeng WF, Niu L, Wichmann C, Kreutzmann A, Mourad D, Aizikov K, Grinfeld D, Makarov A, Mann M, Meier F. Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis. Mol Cell Proteomics 2024; 23:100713. [PMID: 38184013 PMCID: PMC10851225 DOI: 10.1016/j.mcpro.2024.100713] [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: 08/30/2023] [Revised: 12/21/2023] [Accepted: 01/03/2024] [Indexed: 01/08/2024] Open
Abstract
Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.
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Affiliation(s)
- Sophia Steigerwald
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Ankit Sinha
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Kyle L Fort
- Thermo Fisher Scientific (GmbH), Bremen, Germany
| | - Wen-Feng Zeng
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany
| | - Lili Niu
- Department Clinical Proteomics, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Christoph Wichmann
- Department Computational Systems Biochemistry, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | | | | | | | | | - Matthias Mann
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Department Clinical Proteomics, NNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
| | - Florian Meier
- Department Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, Martinsried, Germany; Functional Proteomics, Jena University Hospital, Jena, Germany.
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12
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Li Y, Wang B, Yang W, Ma F, Zou J, Li K, Tan S, Feng J, Wang Y, Qin Z, Chen Z, Ding C. Longitudinal plasma proteome profiling reveals the diversity of biomarkers for diagnosis and cetuximab therapy response of colorectal cancer. Nat Commun 2024; 15:980. [PMID: 38302471 PMCID: PMC10834432 DOI: 10.1038/s41467-024-44911-1] [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: 02/27/2023] [Accepted: 01/03/2024] [Indexed: 02/03/2024] Open
Abstract
Cetuximab therapy is the major treatment for colorectal cancer (CRC), but drug resistance limits its effectiveness. Here, we perform longitudinal and deep proteomic profiling of 641 plasma samples originated from 147 CRC patients (CRCs) undergoing cetuximab therapy with multi-course treatment, and 90 healthy controls (HCs). COL12A1, THBS2, S100A8, and S100A9 are screened as potential proteins to distinguish CRCs from HCs both in plasma and tissue validation cohorts. We identify the potential biomarkers (RRAS2, MMP8, FBLN1, RPTOR, and IMPDH2) for the initial response prediction. In a longitudinal setting, we identify two clusters with distinct fluctuations and construct the model with high accuracy to predict the longitudinal response, further validated in the independent cohort. This study reveals the heterogeneity of different biomarkers for tumor diagnosis, the initial and longitudinal response prediction respectively in the first course and multi-course cetuximab treatment, may ultimately be useful in monitoring and intervention strategies for CRC.
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Affiliation(s)
- Yan Li
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Bing Wang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Wentao Yang
- Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Fahan Ma
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jianling Zou
- Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China
| | - Kai Li
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Subei Tan
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jinwen Feng
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yunzhi Wang
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhaoyu Qin
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Zhiyu Chen
- Department of Gastrointestinal Medical Oncology, Fudan University Shanghai Cancer Center, Shanghai, China.
- Department of Oncology, Shanghai Medical College, Fudan University, Shanghai, China.
| | - Chen Ding
- State Key Laboratory of Genetic Engineering and Collaborative Innovation Center for Genetics and Development, School of Life Sciences, Institutes of Biomedical Sciences, Human Phenome Institute, Zhongshan Hospital, Fudan University, Shanghai, China.
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13
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Gharibi H, Ashkarran AA, Jafari M, Voke E, Landry MP, Saei AA, Mahmoudi M. A uniform data processing pipeline enables harmonized nanoparticle protein corona analysis across proteomics core facilities. Nat Commun 2024; 15:342. [PMID: 38184668 PMCID: PMC10771434 DOI: 10.1038/s41467-023-44678-x] [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: 09/06/2023] [Accepted: 12/20/2023] [Indexed: 01/08/2024] Open
Abstract
Protein corona, a layer of biomolecules primarily comprising proteins, forms dynamically on nanoparticles in biological fluids and is crucial for predicting nanomedicine safety and efficacy. The protein composition of the corona layer is typically analyzed using liquid chromatography-mass spectrometry (LC-MS/MS). Our recent study, involving identical samples analyzed by 17 proteomics facilities, highlighted significant data variability, with only 1.8% of proteins consistently identified across these centers. Here, we implement an aggregated database search unifying parameters such as variable modifications, enzyme specificity, number of allowed missed cleavages and a stringent 1% false discovery rate at the protein and peptide levels. Such uniform search dramatically harmonizes the proteomics data, increasing the reproducibility and the percentage of consistency-identified unique proteins across distinct cores. Specifically, out of the 717 quantified proteins, 253 (35.3%) are shared among the top 5 facilities (and 16.2% among top 11 facilities). Furthermore, we note that reduction and alkylation are important steps in protein corona sample processing and as expected, omitting these steps reduces the number of total quantified peptides by around 20%. These findings underscore the need for standardized procedures in protein corona analysis, which is vital for advancing clinical applications of nanoscale biotechnologies.
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Affiliation(s)
- Hassan Gharibi
- Division of Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Ali Akbar Ashkarran
- Department of Radiology and Precision Health Program, Michigan State University, East Lansing, MI, USA
| | - Maryam Jafari
- Division of ENT Diseases, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden
| | - Elizabeth Voke
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, USA
| | - Markita P Landry
- Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA, USA
- Innovative Genomics Institute, Berkeley, CA, USA
- California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA, USA
- Chan Zuckerberg Biohub, San Francisco, CA, USA
| | - Amir Ata Saei
- Centre for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, 17165, Sweden.
- Biozentrum, University of Basel, 4056, Basel, Switzerland.
| | - Morteza Mahmoudi
- Department of Radiology and Precision Health Program, Michigan State University, East Lansing, MI, USA.
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14
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Ivanov MV, Garibova LA, Postoenko VI, Levitsky LI, Gorshkov MV. On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics. Proteomics 2024; 24:e2300090. [PMID: 37496303 DOI: 10.1002/pmic.202300090] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 05/05/2023] [Accepted: 07/18/2023] [Indexed: 07/28/2023]
Abstract
The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E. coli dataset demonstrating in a number of cases that erroneous data processing methods may lead to a low CV which has nothing to do with these methods' performances in quantitation.
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Affiliation(s)
- Mark V Ivanov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Leyla A Garibova
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Valeriy I Postoenko
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Lev I Levitsky
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
| | - Mikhail V Gorshkov
- V. L. Talrose Institute for Energy Problems of Chemical Physics, N. N. Semenov Federal Research Center of Chemical Physics, Russian Academy of Sciences, Moscow, Russia
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15
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Drouard G, Hagenbeek FA, Whipp AM, Pool R, Hottenga JJ, Jansen R, Hubers N, Afonin A, Willemsen G, de Geus EJC, Ripatti S, Pirinen M, Kanninen KM, Boomsma DI, van Dongen J, Kaprio J. Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins. BMC Med 2023; 21:508. [PMID: 38129841 PMCID: PMC10740308 DOI: 10.1186/s12916-023-03198-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 11/27/2023] [Indexed: 12/23/2023] Open
Abstract
BACKGROUND The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remains underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers. METHODS Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N = 651) and the Netherlands Twin Register (NTR) (N = 665). Follow-up comprised 4 BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated in latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. In FinnTwin12, the sources of genetic and environmental variation underlying the protein abundances were quantified by twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) applying mixed-effects models and correlation networks. RESULTS We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 7 and 3 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. CONCLUSIONS Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
| | - Fiona A Hagenbeek
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Alyce M Whipp
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | - Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Aleksei Afonin
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Katja M Kanninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
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16
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Rostgaard N, Olsen MH, Lolansen SD, Nørager NH, Plomgaard P, MacAulay N, Juhler M. Ventricular CSF proteomic profiles and predictors of surgical treatment outcome in chronic hydrocephalus. Acta Neurochir (Wien) 2023; 165:4059-4070. [PMID: 37857909 PMCID: PMC10739511 DOI: 10.1007/s00701-023-05832-y] [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: 07/07/2023] [Accepted: 09/22/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND By applying an unbiased proteomic approach, we aimed to search for cerebrospinal fluid (CSF) protein biomarkers distinguishing between obstructive and communicating hydrocephalus in order to improve appropriate surgical selection for endoscopic third ventriculostomy vs. shunt implants. Our second study purpose was to look for potential CSF biomarkers distinguishing between patients with adult chronic hydrocephalus benefitting from surgery (responders) vs. those who did not (non-responders). METHODS Ventricular CSF samples were collected from 62 patients with communicating hydrocephalus and 28 patients with obstructive hydrocephalus. CSF was collected in relation to the patients' surgical treatment. As a control group, CSF was collected from ten patients with unruptured aneurysm undergoing preventive surgery (vascular clipping). RESULTS Mass spectrometry-based proteomic analysis of the samples identified 1251 unique proteins. No proteins differed significantly between the communicating hydrocephalus group and the obstructive hydrocephalus group. Four proteins were found to be significantly less abundant in CSF from communicating hydrocephalus patients compared to control subjects. A PCA plot revealed similar proteomic CSF profiles of obstructive and communicating hydrocephalus and control samples. For obstructive hydrocephalus, ten proteins were found to predict responders from non-responders. CONCLUSION Here, we show that the proteomic profile of ventricular CSF from patients with hydrocephalus differs slightly from control subjects. Furthermore, we find ten predictors of response to surgical outcome (endoscopic third ventriculostomy or ventriculo-peritoneal shunt) in patients with obstructive hydrocephalus.
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Affiliation(s)
- Nina Rostgaard
- Department of Neurosurgery, The Neuroscience Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Markus Harboe Olsen
- Department of Neuroanaesthesiology, The Neuroscience Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Sara Diana Lolansen
- Department of Neurosurgery, The Neuroscience Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicolas Hernandez Nørager
- Department of Neurosurgery, The Neuroscience Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Peter Plomgaard
- Department of Clinical Biochemistry, Centre of Diagnostic Investigations, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Nanna MacAulay
- Department of Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marianne Juhler
- Department of Neurosurgery, The Neuroscience Centre, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark.
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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17
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Cheung HW, Wong KS, To NS, Wan TSM, Ho ENM. An enhanced label-free proteomics approach for deep-diving into equine plasma proteome, including the discovery of protein biomarkers for strenuous exercise. Drug Test Anal 2023. [PMID: 37986675 DOI: 10.1002/dta.3606] [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: 02/10/2023] [Revised: 08/15/2023] [Accepted: 10/30/2023] [Indexed: 11/22/2023]
Abstract
Plasma proteins have been a valuable source of biomarkers for clinical uses and for monitoring of the illicit use of prohibited substances or practices in equine sports. We have previously reported the first use of label-free proteomics in profiling equine plasma proteome. This study aimed to refine the method by systematically evaluating various plasma fractionation methods and the use of narrower precursor mass ranges in data-independent acquisition (DIA) mass spectrometry (MS). Tandem fractionations of equine plasma with octanoic acid precipitation followed by solid-phase extraction (SPE) with C4 cartridges provided the largest increase in the number of new proteins identified. The use of two narrow precursor mass ranges of m/z 400-600 and 600-800 in DIA not only identified most proteins detectable by using a single mass range of m/z 350-1500 but also identified ~27% more proteins. The improved method was applied to analyse the plasma proteome of 'postrace' samples which, unlike other samples, had been collected from racehorses soon after racing. Multivariate data analysis has identified upregulation of 14 proteins and downregulation of six proteins in postrace plasma compared with the non-postrace plasma samples. Literature review of these proteins has provided evidence of exercise-induced haemolysis and changes in antioxidant enzyme activities, kinin system, insulin signalling and energy metabolism after strenuous exercise. The improved method has enabled a deeper profiling of the equine plasma proteome and identified the proteins associated with normal physiological changes after racing which are potential confounding factors in the development of a biomarker approach for doping control.
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Affiliation(s)
- Hiu Wing Cheung
- Racing Laboratory, The Hong Kong Jockey Club, Sha Tin Racecourse, Sha Tin, Hong Kong, China
| | - Kin-Sing Wong
- Racing Laboratory, The Hong Kong Jockey Club, Sha Tin Racecourse, Sha Tin, Hong Kong, China
| | - Ning Sum To
- Racing Laboratory, The Hong Kong Jockey Club, Sha Tin Racecourse, Sha Tin, Hong Kong, China
| | - Terence S M Wan
- Racing Laboratory, The Hong Kong Jockey Club, Sha Tin Racecourse, Sha Tin, Hong Kong, China
| | - Emmie N M Ho
- Racing Laboratory, The Hong Kong Jockey Club, Sha Tin Racecourse, Sha Tin, Hong Kong, China
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18
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Mundt F, Albrechtsen NJW, Mann SP, Treit P, Ghodgaonkar-Steger M, O’Flaherty M, Raijmakers R, Vizcaíno JA, Heck AJ, Mann M. Foresight in clinical proteomics: current status, ethical considerations, and future perspectives. OPEN RESEARCH EUROPE 2023; 3:59. [PMID: 37645494 PMCID: PMC10446044 DOI: 10.12688/openreseurope.15810.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 10/26/2023] [Indexed: 08/31/2023]
Abstract
With the advent of robust and high-throughput mass spectrometric technologies and bioinformatics tools to analyze large data sets, proteomics has penetrated broadly into basic and translational life sciences research. More than 95% of FDA-approved drugs currently target proteins, and most diagnostic tests are protein-based. The introduction of proteomics to the clinic, for instance to guide patient stratification and treatment, is already ongoing. Importantly, ethical challenges come with this success, which must also be adequately addressed by the proteomics and medical communities. Consortium members of the H2020 European Union-funded proteomics initiative: European Proteomics Infrastructure Consortium-providing access (EPIC-XS) met at the Core Technologies for Life Sciences (CTLS) conference to discuss the emerging role and implementation of proteomics in the clinic. The discussion, involving leaders in the field, focused on the current status, related challenges, and future efforts required to make proteomics a more mainstream technology for translational and clinical research. Here we report on that discussion and provide an expert update concerning the feasibility of clinical proteomics, the ethical implications of generating and analyzing large-scale proteomics clinical data, and recommendations to ensure both ethical and effective implementation in real-world applications.
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Affiliation(s)
- Filip Mundt
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nicolai J. Wewer Albrechtsen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, University Hospital, Bispebjerg Hospital, Bispebjerg, Denmark
| | | | - Peter Treit
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
| | | | - Martina O’Flaherty
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Reinout Raijmakers
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Albert J.R. Heck
- Biomolecular Mass Spectrometry and Proteomics, Bijvoet Centre for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, Utrecht University, Padualaan 8, Utrecht 3584 CH, The Netherlands
| | - Matthias Mann
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Max Planck Institute of Biochemistry, Proteomics and Signal Transduction, Martinsried, Germany
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19
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Bennike TB. Advances in proteomics: characterization of the innate immune system after birth and during inflammation. Front Immunol 2023; 14:1254948. [PMID: 37868984 PMCID: PMC10587584 DOI: 10.3389/fimmu.2023.1254948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Accepted: 09/26/2023] [Indexed: 10/24/2023] Open
Abstract
Proteomics is the characterization of the protein composition, the proteome, of a biological sample. It involves the large-scale identification and quantification of proteins, peptides, and post-translational modifications. This review focuses on recent developments in mass spectrometry-based proteomics and provides an overview of available methods for sample preparation to study the innate immune system. Recent advancements in the proteomics workflows, including sample preparation, have significantly improved the sensitivity and proteome coverage of biological samples including the technically difficult blood plasma. Proteomics is often applied in immunology and has been used to characterize the levels of innate immune system components after perturbations such as birth or during chronic inflammatory diseases like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). In cancers, the tumor microenvironment may generate chronic inflammation and release cytokines to the circulation. In these situations, the innate immune system undergoes profound and long-lasting changes, the large-scale characterization of which may increase our biological understanding and help identify components with translational potential for guiding diagnosis and treatment decisions. With the ongoing technical development, proteomics will likely continue to provide increasing insights into complex biological processes and their implications for health and disease. Integrating proteomics with other omics data and utilizing multi-omics approaches have been demonstrated to give additional valuable insights into biological systems.
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Affiliation(s)
- Tue Bjerg Bennike
- Medical Microbiology and Immunology, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
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20
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Nieman DC, Sakaguchi CA, Pelleigrini M, Thompson MJ, Sumner S, Zhang Q. Healthy lifestyle linked to innate immunity and lipoprotein metabolism: a cross-sectional comparison using untargeted proteomics. Sci Rep 2023; 13:16728. [PMID: 37794065 PMCID: PMC10550951 DOI: 10.1038/s41598-023-44068-9] [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: 06/22/2023] [Accepted: 10/03/2023] [Indexed: 10/06/2023] Open
Abstract
This study used untargeted proteomics to compare blood proteomic profiles in two groups of adults that differed widely in lifestyle habits. A total of 52 subjects in the lifestyle group (LIFE) (28 males, 24 females) and 52 in the control group (CON) (27 males, 25 females) participated in this cross-sectional study. Age, education level, marital status, and height did not differ significantly between LIFE and CON groups. The LIFE and CON groups differed markedly in body composition, physical activity patterns, dietary intake patterns, disease risk factor prevalence, blood measures of inflammation, triglycerides, HDL-cholesterol, glucose, and insulin, weight-adjusted leg/back and handgrip strength, and mood states. The proteomics analysis showed strong group differences for 39 of 725 proteins identified in dried blood spot samples. Of these, 18 were downregulated in the LIFE group and collectively indicated a lower innate immune activation signature. A total of 21 proteins were upregulated in the LIFE group and supported greater lipoprotein metabolism and HDL remodeling. Lifestyle-related habits and biomarkers were probed and the variance (> 50%) in proteomic profiles was best explained by group contrasts in indicators of adiposity. This cross-sectional study established that a relatively small number of proteins are associated with good lifestyle habits.
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Affiliation(s)
- David C Nieman
- Human Performance Laboratory, Biology Department, Appalachian State University, North Carolina Research Campus, Kannapolis, NC, USA.
| | - Camila A Sakaguchi
- Human Performance Laboratory, Biology Department, Appalachian State University, North Carolina Research Campus, Kannapolis, NC, USA
| | - Matteo Pelleigrini
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Michael J Thompson
- Department of Molecular, Cell, and Developmental Biology, University of California Los Angeles, Los Angeles, CA, USA
| | - Susan Sumner
- Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, 28081, USA
| | - Qibin Zhang
- UNCG Center for Translational Biomedical Research, University of North Carolina at Greensboro, North Carolina Research Campus, Kannapolis, NC, USA
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21
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Yao P, Iona A, Kartsonaki C, Said S, Wright N, Lin K, Pozarickij A, Millwood I, Fry H, Mazidi M, Chen Y, Du H, Bennett D, Avery D, Schmidt D, Pei P, Lv J, Yu C, Hill M, Chen J, Peto R, Walters R, Collins R, Li L, Clarke R, Chen Z. Conventional and genetic associations of adiposity with 1463 proteins in relatively lean Chinese adults. Eur J Epidemiol 2023; 38:1089-1103. [PMID: 37676424 PMCID: PMC10570181 DOI: 10.1007/s10654-023-01038-9] [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: 05/22/2023] [Accepted: 07/28/2023] [Indexed: 09/08/2023]
Abstract
Adiposity is associated with multiple diseases and traits, but little is known about the causal relevance and mechanisms underlying these associations. Large-scale proteomic profiling, especially when integrated with genetic data, can clarify mechanisms linking adiposity with disease outcomes. We examined the associations of adiposity with plasma levels of 1463 proteins in 3977 Chinese adults, using measured and genetically-instrumented BMI. We further used two-sample bi-directional MR analyses to assess if certain proteins influenced adiposity, along with other (e.g. enrichment) analyses to clarify possible mechanisms underlying the observed associations. Overall, the mean (SD) baseline BMI was 23.9 (3.3) kg/m2, with only 6% being obese (i.e. BMI ≥ 30 kg/m2). Measured and genetically-instrumented BMI was significantly associated at FDR < 0.05 with levels of 1096 (positive/inverse: 826/270) and 307 (positive/inverse: 270/37) proteins, respectively, with FABP4, LEP, IL1RN, LSP1, GOLM2, TNFRSF6B, and ADAMTS15 showing the strongest positive and PON3, NCAN, LEPR, IGFBP2 and MOG showing the strongest inverse genetic associations. These associations were largely linear, in adiposity-to-protein direction, and replicated (> 90%) in Europeans of UKB (mean BMI 27.4 kg/m2). Enrichment analyses of the top > 50 BMI-associated proteins demonstrated their involvement in atherosclerosis, lipid metabolism, tumour progression and inflammation. Two-sample bi-directional MR analyses using cis-pQTLs identified in CKB GWAS found eight proteins (ITIH3, LRP11, SCAMP3, NUDT5, OGN, EFEMP1, TXNDC15, PRDX6) significantly affect levels of BMI, with NUDT5 also showing bi-directional association. The findings among relatively lean Chinese adults identified novel pathways by which adiposity may increase disease risks and novel potential targets for treatment of obesity and obesity-related diseases.
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Affiliation(s)
- Pang Yao
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Andri Iona
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Christiana Kartsonaki
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Saredo Said
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Neil Wright
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Kuang Lin
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Alfred Pozarickij
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Iona Millwood
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Hannah Fry
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Mohsen Mazidi
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Yiping Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Derrick Bennett
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Daniel Avery
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Dan Schmidt
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Jun Lv
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Michael Hill
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Richard Peto
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Robin Walters
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Rory Collins
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK
| | - Liming Li
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Robert Clarke
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK.
| | - Zhengming Chen
- Clinical Trial Service Unit, Nuffield Department of Population Health, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7LF, UK.
- Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK.
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22
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Alshahrani A, Aljada A, Masood A, Mujammami M, Alfadda AA, Musambil M, Alanazi IO, Al Dubayee M, Abdel Rahman AM, Benabdelkamel H. Proteomic Profiling Identifies Distinct Regulation of Proteins in Obese Diabetic Patients Treated with Metformin. Pharmaceuticals (Basel) 2023; 16:1345. [PMID: 37895816 PMCID: PMC10609691 DOI: 10.3390/ph16101345] [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: 07/20/2023] [Revised: 09/12/2023] [Accepted: 09/20/2023] [Indexed: 10/29/2023] Open
Abstract
Background: Obesity and type 2 diabetes mellitus (T2DM) are characterized by underlying low-grade chronic inflammation. Metformin has been used as the first line of therapy in T2DM as it decreases hepatic glucose production and glucose intestinal absorption, enhances insulin sensitivity and weight loss, and is known to ameliorate inflammation. The mechanisms through which metformin exerts its effect remain unclear. Proteomics has emerged as a unique approach to explore the biological changes associated with diseases, including T2DM. It provides insight into the circulating biomarkers/mediators which could be utilized for disease screening, diagnosis, and prognosis. Methods: This study evaluated the proteomic changes in obese (Ob), obese diabetics (OD), and obese diabetic patients on metformin (ODM) using a 2D DIGE MALDI-TOF mass spectrometric approach. Results: Significant changes in sixteen plasma proteins (15 up and 1 down, ANOVA, p ≤ 0.05; fold change ≥ 1.5) were observed in the ODM group when compared to the Ob and OD groups. Bioinformatic network pathway analysis revealed that the majority of these altered plasma proteins are involved in distinct pathways involving acute-phase response, inflammation, and oxidative response and were centered around HNF4A, ERK, JNK, and insulin signaling pathways. Conclusions: Our study provides important information about the possible biomarkers altered by metformin treatment in obese patients with and without T2DM. These altered plasma proteins are involved in distinct pathways involving acute-phase response, inflammation, and oxidative response and were centered around HNF4A, ERK, JNK, and insulin signaling pathways. The presented proteomic profiling approach may help in identifying potential biomarkers/mediators affected by metformin treatment in T2DM and inform the understanding of metformin's mechanisms of action.
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Affiliation(s)
- Awad Alshahrani
- Department of Medicine, Ministry of National Guard Health Affairs, Riyadh 11426, Saudi Arabia; (A.A.); (M.A.D.)
- King Abdullah International Medical Research Center, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11481, Saudi Arabia
| | - Ahmad Aljada
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh 11533, Saudi Arabia;
| | - Afshan Masood
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, P.O. Box 2925 (98), Riyadh 11461, Saudi Arabia; (A.M.); (A.A.A.); (M.M.)
| | - Muhammad Mujammami
- Endocrinology and Diabetes Unit, Department of Medicine, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia;
- University Diabetes Center, King Saud University Medical City, King Saud University, Riyadh 11461, Saudi Arabia
| | - Assim A. Alfadda
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, P.O. Box 2925 (98), Riyadh 11461, Saudi Arabia; (A.M.); (A.A.A.); (M.M.)
- Department of Medicine, College of Medicine and King Saud Medical City, King Saud University, P.O. Box 2925 (98), Riyadh 11461, Saudi Arabia
| | - Mohthash Musambil
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, P.O. Box 2925 (98), Riyadh 11461, Saudi Arabia; (A.M.); (A.A.A.); (M.M.)
| | - Ibrahim O. Alanazi
- Healthy Aging Research Institute, Health Sector, King Abdulaziz City for Science and Technology (KACST), P.O. Box 6086, Riyadh 11442, Saudi Arabia;
| | - Mohammed Al Dubayee
- Department of Medicine, Ministry of National Guard Health Affairs, Riyadh 11426, Saudi Arabia; (A.A.); (M.A.D.)
- King Abdullah International Medical Research Center, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, Riyadh 11481, Saudi Arabia
| | - Anas M. Abdel Rahman
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh 11533, Saudi Arabia;
- Metabolomics Section, Department of Clinical Genomics, Center for Genomics Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh 11564, Saudi Arabia
| | - Hicham Benabdelkamel
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, P.O. Box 2925 (98), Riyadh 11461, Saudi Arabia; (A.M.); (A.A.A.); (M.M.)
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23
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Zhang X, Hu LG, Lei Y, Stolina M, Homann O, Wang S, Véniant MM, Hsu YH. A transcriptomic and proteomic atlas of obesity and type 2 diabetes in cynomolgus monkeys. Cell Rep 2023; 42:112952. [PMID: 37556324 DOI: 10.1016/j.celrep.2023.112952] [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: 04/01/2022] [Revised: 05/16/2023] [Accepted: 07/23/2023] [Indexed: 08/11/2023] Open
Abstract
Obesity and type 2 diabetes (T2D) remain major global healthcare challenges, and developing therapeutics necessitates using nonhuman primate models. Here, we present a transcriptomic and proteomic atlas of all the major organs of cynomolgus monkeys with spontaneous obesity or T2D in comparison to healthy controls. Molecular changes occur predominantly in the adipose tissues of individuals with obesity, while extensive expression perturbations among T2D individuals are observed in many tissues such as the liver and kidney. Immune-response-related pathways are upregulated in obesity and T2D, whereas metabolism and mitochondrial pathways are downregulated. Moreover, we highlight some potential therapeutic targets, including SLC2A1 and PCSK1 in obesity as well as SLC30A8 and SLC2A2 in T2D. Our study provides a resource for exploring the complex molecular mechanism of obesity and T2D and developing therapies for these diseases, with limitations including lack of hypothalamus, isolated islets of Langerhans, longitudinal data, and body fat percentage.
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Affiliation(s)
- Xianglong Zhang
- Center for Research Acceleration by Digital Innovation (CRADI), Amgen Research, South San Francisco, CA 94080, USA
| | | | - Ying Lei
- Research China, Amgen Research, Shanghai 200020, China
| | - Marina Stolina
- Department of Cardiometabolic Disorders, Amgen Research, Thousand Oaks, CA 91320, USA
| | - Oliver Homann
- Center for Research Acceleration by Digital Innovation (CRADI), Amgen Research, South San Francisco, CA 94080, USA
| | - Songli Wang
- Research Biomics, Amgen Research, South San Francisco, CA 94080, USA
| | - Murielle M Véniant
- Department of Cardiometabolic Disorders, Amgen Research, Thousand Oaks, CA 91320, USA.
| | - Yi-Hsiang Hsu
- Marcus Institute for Aging Research and Harvard Medical School, Boston, MA 02131, USA.
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24
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Zapata RC, Nasamran CA, Chilin-Fuentes DR, Dulawa SC, Osborn O. Identification of adipose tissue transcriptomic memory of anorexia nervosa. Mol Med 2023; 29:109. [PMID: 37582711 PMCID: PMC10428576 DOI: 10.1186/s10020-023-00705-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/24/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Anorexia nervosa (AN) is a complex debilitating disease characterized by intense fear of weight gain and excessive exercise. It is the deadliest of any psychiatric disorder with a high rate of recidivism, yet its pathophysiology is unclear. The Activity-Based Anorexia (ABA) paradigm is a widely accepted mouse model of AN that recapitulates hypophagia and hyperactivity despite reduced body weight, however, not the chronicity. METHODS Here, we modified the prototypical ABA paradigm to increase the time to lose 25% of baseline body weight from less than 7 days to more than 2 weeks. We used this paradigm to identify persistently altered genes after weight restoration that represent a transcriptomic memory of under-nutrition and may contribute to AN relapse using RNA sequencing. We focused on adipose tissue as it was identified as a major location of transcriptomic memory of over-nutririon. RESULTS We identified 300 dysregulated genes that were refractory to weight restroration after ABA, including Calm2 and Vps13d, which could be potential global regulators of transcriptomic memory in both chronic over- and under-nutrition. CONCLUSION We demonstrated the presence of peristent changes in the adipose tissue transcriptome in the ABA mice after weight restoration. Despite being on the opposite spectrum of weight perturbations, majority of the transcriptomic memory genes of under- and over-nutrition did not overlap, suggestive of the different mechanisms involved in these extreme nutritional statuses.
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Affiliation(s)
- Rizaldy C Zapata
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, San Diego, USA.
| | - Chanond A Nasamran
- Center for Computational Biology & Bioinformatics, School of Medicine, University of California San Diego, San Diego, USA
| | - Daisy R Chilin-Fuentes
- Center for Computational Biology & Bioinformatics, School of Medicine, University of California San Diego, San Diego, USA
| | - Stephanie C Dulawa
- Department of Psychiatry, School of Medicine, University of California San Diego, La Jolla, 92093, San Diego, CA, USA
| | - Olivia Osborn
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, San Diego, USA
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25
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Frasca D, Romero M, Diaz A, Blomberg BB. Obesity accelerates age defects in B cells, and weight loss improves B cell function. Immun Ageing 2023; 20:35. [PMID: 37460937 PMCID: PMC10351107 DOI: 10.1186/s12979-023-00361-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 07/11/2023] [Indexed: 07/21/2023]
Abstract
BACKGROUND We have previously shown that obesity accelerates age-associated defects in B cell function and antibody production leading to decreased secretion of protective antibodies and increased autoimmunity. We wanted to evaluate if obese adults enrolled in a voluntary weight reduction program had higher protective and lower autoimmune antibody responses similar to those observed in lean adults. METHODS Experiments were performed using blood isolated from an established cohort of female lean adult and elderly individuals, as well as from the blood of female adults with obesity, before and after a voluntary weight reduction program in which their Body Mass Index (BMI) was reduced 10-34% in 12 months. All participants were vaccinated with the Trivalent Inactivated Influenza vaccine. Serum samples were evaluated for the presence of pro-inflammatory cytokines and adipokines, vaccine-specific antibodies and autoimmune antibodies. We evaluated the composition of the B cell pool by flow cytometry, the expression of RNA for class switch transcription factors and pro-inflammatory markers by qPCR, the in vitro secretion of pro- and anti-inflammatory cytokines and their capacity to induce pro-inflammatory T cells. RESULTS Obesity, similar to aging, induced increased serum levels of pro-inflammatory cytokines and autoimmune antibodies, while vaccine-specific antibodies were reduced. In agreement with the serum results, the B cell pool of obese adults and elderly individuals was enriched in pro-inflammatory B cell subsets and was characterized by higher expression of markers associated with cell senescence, higher levels of T-bet, the transcription factor for autoimmune antibodies and lower levels of E47, the transcription factor associated with protective responses to the influenza vaccine. B cells from obese adults and elderly individuals were also able to secrete inflammatory cytokines and support the generation of inflammatory T cells. All these pro-inflammatory characteristics of B cells from obese individuals were significantly attenuated, but not completely reversed, by weight loss. CONCLUSIONS Although the results from our small observational study show that obesity-induced dysfunctional B cell responses, similar to those occurring during aging, are ameliorated in some but not all obese individuals after weight loss, the effects of body weight loss on mechanistic pathways are largely missing and deserve further investigation.
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Affiliation(s)
- Daniela Frasca
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, RMSB 3153, 1600 NW 10thAve, Miami, FL, 33136, USA.
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA.
| | - Maria Romero
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, RMSB 3153, 1600 NW 10thAve, Miami, FL, 33136, USA
| | - Alain Diaz
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, RMSB 3153, 1600 NW 10thAve, Miami, FL, 33136, USA
| | - Bonnie B Blomberg
- Department of Microbiology and Immunology, University of Miami Miller School of Medicine, RMSB 3153, 1600 NW 10thAve, Miami, FL, 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, USA
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26
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Vernardis SI, Demichev V, Lemke O, Grüning NM, Messner C, White M, Pietzner M, Peluso A, Collet TH, Henning E, Gille C, Campbell A, Hayward C, Porteous DJ, Marioni RE, Mülleder M, Zelezniak A, Wareham NJ, Langenberg C, Farooqi IS, Ralser M. The Impact of Acute Nutritional Interventions on the Plasma Proteome. J Clin Endocrinol Metab 2023; 108:2087-2098. [PMID: 36658456 PMCID: PMC10348471 DOI: 10.1210/clinem/dgad031] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 01/14/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
CONTEXT Humans respond profoundly to changes in diet, while nutrition and environment have a great impact on population health. It is therefore important to deeply characterize the human nutritional responses. OBJECTIVE Endocrine parameters and the metabolome of human plasma are rapidly responding to acute nutritional interventions such as caloric restriction or a glucose challenge. It is less well understood whether the plasma proteome would be equally dynamic, and whether it could be a source of corresponding biomarkers. METHODS We used high-throughput mass spectrometry to determine changes in the plasma proteome of i) 10 healthy, young, male individuals in response to 2 days of acute caloric restriction followed by refeeding; ii) 200 individuals of the Ely epidemiological study before and after a glucose tolerance test at 4 time points (0, 30, 60, 120 minutes); and iii) 200 random individuals from the Generation Scotland study. We compared the proteomic changes detected with metabolome data and endocrine parameters. RESULTS Both caloric restriction and the glucose challenge substantially impacted the plasma proteome. Proteins responded across individuals or in an individual-specific manner. We identified nutrient-responsive plasma proteins that correlate with changes in the metabolome, as well as with endocrine parameters. In particular, our study highlights the role of apolipoprotein C1 (APOC1), a small, understudied apolipoprotein that was affected by caloric restriction and dominated the response to glucose consumption and differed in abundance between individuals with and without type 2 diabetes. CONCLUSION Our study identifies APOC1 as a dominant nutritional responder in humans and highlights the interdependency of acute nutritional response proteins and the endocrine system.
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Affiliation(s)
- Spyros I Vernardis
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Vadim Demichev
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Oliver Lemke
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Nana-Maria Grüning
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Christoph Messner
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Matt White
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Maik Pietzner
- MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0SL, UK
- Computational Medicine, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Alina Peluso
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
| | - Tinh-Hai Collet
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
- Service of Endocrinology, Diabetology, Nutrition and Therapeutic Education, Department of Medicine, Geneva University Hospitals, 1211 Geneva, Switzerland
| | - Elana Henning
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Christoph Gille
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
| | - Aleksej Zelezniak
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE-412 96, Gothenburg, Sweden
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius SE-412 96, Lithuania
- Randall Centre for Cell & Molecular Biophysics, King's College London, New Hunt's House, Guy's Campus, SE1 1UL London, UK
| | | | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, CB2 0SL, UK
- Computational Medicine, Berlin Institute of Health at Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
- Precision Healthcare University Research Institute, Queen Mary University of London, London, E1 1HH, UK
| | - I Sadaf Farooqi
- Metabolic Research Laboratories and National Institute for Health Research Cambridge Biomedical Research Centre, Wellcome-Medical Research Council Institute of Metabolic Science, Addenbrooke's Hospital, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Markus Ralser
- Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, NW1 1HT, UK
- Department of Biochemistry, Charité—Universitätsmedizin Berlin, 10117 Berlin, Germany
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Midha MK, Kapil C, Maes M, Baxter DH, Morrone SR, Prokop TJ, Moritz RL. Vacuum Insulated Probe Heated Electrospray Ionization Source Enhances Microflow Rate Chromatography Signals in the Bruker timsTOF Mass Spectrometer. J Proteome Res 2023; 22:2525-2537. [PMID: 37294184 PMCID: PMC11060334 DOI: 10.1021/acs.jproteome.3c00305] [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] [Indexed: 06/10/2023]
Abstract
By far the largest contribution to ion detectability in liquid chromatography-driven mass spectrometry-based proteomics is the efficient generation of peptide molecular ions by the electrospray source. To maximize the transfer of peptides from the liquid to gaseous phase and allow molecular ions to enter the mass spectrometer at microspray flow rates, an efficient electrospray process is required. Here we describe the superior performance of newly design vacuum insulated probe heated electrospray ionization (VIP-HESI) source coupled to a Bruker timsTOF PRO mass spectrometer operated in microspray mode. VIP-HESI significantly improves chromatography signals in comparison to electrospray ionization (ESI) and nanospray ionization using the captivespray (CS) source and provides increased protein detection with higher quantitative precision, enhancing reproducibility of sample injection amounts. Protein quantitation of human K562 lymphoblast samples displayed excellent chromatographic retention time reproducibility (<10% coefficient of variation (CV)) with no signal degradation over extended periods of time, and a mouse plasma proteome analysis identified 12% more plasma protein groups allowing large-scale analysis to proceed with confidence (1,267 proteins at 0.4% CV). We show that the Slice-PASEF VIP-HESI mode is sensitive in identifying low amounts of peptide without losing quantitative precision. We demonstrate that VIP-HESI coupled with microflow rate chromatography achieves a higher depth of coverage and run-to-run reproducibility for a broad range of proteomic applications. Data and spectral libraries are available via ProteomeXchange (PXD040497).
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Affiliation(s)
- Mukul K Midha
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Charu Kapil
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Michal Maes
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - David H Baxter
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Seamus R Morrone
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Timothy J Prokop
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
| | - Robert L Moritz
- Institute for Systems Biology, 401 Terry Avenue N, Seattle, Washington 98109, United States
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Lange PF, Schilling O, Huesgen PF. Positional proteomics: is the technology ready to study clinical cohorts? Expert Rev Proteomics 2023; 20:309-318. [PMID: 37869791 DOI: 10.1080/14789450.2023.2272046] [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: 05/15/2023] [Accepted: 08/22/2023] [Indexed: 10/24/2023]
Abstract
INTRODUCTION Positional proteomics provides proteome-wide information on protein termini and their modifications, uniquely enabling unambiguous identification of site-specific, limited proteolysis. Such proteolytic cleavage irreversibly modifies protein sequences resulting in new proteoforms with distinct protease-generated neo-N and C-termini and altered localization and activity. Misregulated proteolysis is implicated in a wide variety of human diseases. Protein termini, therefore, constitute a huge, largely unexplored source of specific analytes that provides a deep view into the functional proteome and a treasure trove for biomarkers. AREAS COVERED We briefly review principal approaches to define protein termini and discuss recent advances in method development. We further highlight the potential of positional proteomics to identify and trace specific proteoforms, with a focus on proteolytic processes altered in disease. Lastly, we discuss current challenges and potential for applying positional proteomics in biomarker and pre-clinical research. EXPERT OPINION Recent developments in positional proteomics have provided significant advances in sensitivity and throughput. In-depth analysis of proteolytic processes in clinical cohorts thus appears feasible in the near future. We argue that this will provide insights into the functional state of the proteome and offer new opportunities to utilize proteolytic processes altered or targeted in disease as specific diagnostic, prognostic and companion biomarkers.
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Affiliation(s)
- Philipp F Lange
- Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, Canada
- Michael Cuccione Childhood Cancer Research Program, BC Children's Hospital Research Institute, Vancouver, BC, Canada
- Department of Molecular Oncology, BC Cancer Research Centre, Vancouver, BC, Canada
| | - Oliver Schilling
- Institute of Surgical Pathology, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Pitter F Huesgen
- Central Institute for Engineering, Electronics and Analytics, ZEA-3, Forschungszentrum Jülich, Jülich, Germany
- Cologne Excellence Cluster on Stress Responses in Ageing-Associated Diseases, CECAD, Medical Faculty and University Hospital, University of Cologne, Cologne, Germany
- Institute of Biochemistry, Department for Chemistry, University of Cologne, Cologne, Germany
- Faculty of Biology, University of Freiburg, Freiburg, Germany
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29
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Drouard G, Hagenbeek FA, Whipp A, Pool R, Hottenga JJ, Jansen R, Hubers N, Afonin A, Willemsen G, de Geus EJC, Ripatti S, Pirinen M, Kanninen KM, Boomsma DI, van Dongen J, Kaprio J. Longitudinal multi-omics study reveals common etiology underlying association between plasma proteome and BMI trajectories in adolescent and young adult twins. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.28.23291995. [PMID: 37425750 PMCID: PMC10327285 DOI: 10.1101/2023.06.28.23291995] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Background The influence of genetics and environment on the association of the plasma proteome with body mass index (BMI) and changes in BMI remain underexplored, and the links to other omics in these associations remain to be investigated. We characterized protein-BMI trajectory associations in adolescents and adults and how these connect to other omics layers. Methods Our study included two cohorts of longitudinally followed twins: FinnTwin12 (N=651) and the Netherlands Twin Register (NTR) (N=665). Follow-up comprised four BMI measurements over approximately 6 (NTR: 23-27 years old) to 10 years (FinnTwin12: 12-22 years old), with omics data collected at the last BMI measurement. BMI changes were calculated using latent growth curve models. Mixed-effects models were used to quantify the associations between the abundance of 439 plasma proteins with BMI at blood sampling and changes in BMI. The sources of genetic and environmental variation underlying the protein abundances were quantified using twin models, as were the associations of proteins with BMI and BMI changes. In NTR, we investigated the association of gene expression of genes encoding proteins identified in FinnTwin12 with BMI and changes in BMI. We linked identified proteins and their coding genes to plasma metabolites and polygenic risk scores (PRS) using mixed-effect models and correlation networks. Results We identified 66 and 14 proteins associated with BMI at blood sampling and changes in BMI, respectively. The average heritability of these proteins was 35%. Of the 66 BMI-protein associations, 43 and 12 showed genetic and environmental correlations, respectively, including 8 proteins showing both. Similarly, we observed 6 and 4 genetic and environmental correlations between changes in BMI and protein abundance, respectively. S100A8 gene expression was associated with BMI at blood sampling, and the PRG4 and CFI genes were associated with BMI changes. Proteins showed strong connections with many metabolites and PRSs, but we observed no multi-omics connections among gene expression and other omics layers. Conclusions Associations between the proteome and BMI trajectories are characterized by shared genetic, environmental, and metabolic etiologies. We observed few gene-protein pairs associated with BMI or changes in BMI at the proteome and transcriptome levels.
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Affiliation(s)
- Gabin Drouard
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Fiona A. Hagenbeek
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Alyce Whipp
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - René Pool
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jouke Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Rick Jansen
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Psychiatry, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Mood, Anxiety, Psychosis, Sleep & Stress Program, Amsterdam, The Netherlands
| | - Nikki Hubers
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Aleksei Afonin
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - BIOS Consortium
- Biobank-based Integrative Omics Study Consortium. Lists of authors and their affiliations appear in the supplementary material (see Additional file 1)
| | | | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Matti Pirinen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Department of Public Health, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Department of Mathematics and Statistics, University of Helsinki, Helsinki, Finland
| | - Katja M. Kanninen
- A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
- Amsterdam Reproduction & Development (AR&D) Research Institute, Amsterdam, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
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30
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Matzinger M, Mayer RL, Mechtler K. Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing. Proteomics 2023; 23:e2200162. [PMID: 36806919 PMCID: PMC10909491 DOI: 10.1002/pmic.202200162] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 02/09/2023] [Accepted: 02/10/2023] [Indexed: 02/21/2023]
Abstract
The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.
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Affiliation(s)
- Manuel Matzinger
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
| | - Rupert L. Mayer
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
| | - Karl Mechtler
- Research Institute of Molecular Pathology (IMP)Vienna BioCenterViennaAustria
- Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of SciencesVienna BioCenter (VBC)ViennaAustria
- Institute of Molecular Biotechnology (IMBA), Austrian Academy of SciencesVienna BioCenter (VBC)ViennaAustria
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31
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Bader JM, Albrecht V, Mann M. MS-based proteomics of body fluids: The end of the beginning. Mol Cell Proteomics 2023:100577. [PMID: 37209816 PMCID: PMC10388585 DOI: 10.1016/j.mcpro.2023.100577] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/07/2023] [Accepted: 05/11/2023] [Indexed: 05/22/2023] Open
Abstract
Accurate biomarkers are a crucial and necessary precondition for precision medicine, yet existing ones are often unspecific and new ones have been very slow to enter the clinic. Mass spectrometry (MS)-based proteomics excels by its untargeted nature, specificity of identification and quantification making it an ideal technology for biomarker discovery and routine measurement. It has unique attributes compared to affinity binder technologies, such as OLINK Proximity Extension Assay and SOMAscan. In a previous review we described technological and conceptual limitations that had held back success (Geyer et al., 2017). We proposed a 'rectangular strategy' to better separate true biomarkers by minimizing cohort-specific effects. Today, this has converged with advances in MS-based proteomics technology, such as increased sample throughput, depth of identification and quantification. As a result, biomarker discovery studies have become more successful, producing biomarker candidates that withstand independent verification and, in some cases, already outperform state-of-the-art clinical assays. We summarize developments over the last years, including the benefits of large and independent cohorts, which are necessary for clinical acceptance. They are also required for machine learning or deep learning. Shorter gradients, new scan modes and multiplexing are about to drastically increase throughput, cross-study integration, and quantification, including proxies for absolute levels. We have found that multi-protein panels are inherently more robust than current single analyte tests and better capture the complexity of human phenotypes. Routine MS measurement in the clinic is fast becoming a viable option. The full set of proteins in a body fluid (global proteome) is the most important reference and the best process control. Additionally, it increasingly has all the information that could be obtained from targeted analysis although the latter may be the most straightforward way to enter into regular use. Many challenges remain, not least of a regulatory and ethical nature, but the outlook for MS-based clinical applications has never been brighter.
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Affiliation(s)
- Jakob M Bader
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Vincent Albrecht
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany
| | - Matthias Mann
- Department of Proteomics and Signal Transduction, Max Planck Institute of Biochemistry, 82152 Martinsried, Germany; Novo Nordisk Foundation Center for Protein Research, Faculty of Health Sciences, University of Copenhagen, 2200 Copenhagen, Denmark.
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32
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Zhao Q, Han B, Xu Q, Wang T, Fang C, Li R, Zhang L, Pei Y. Proteome and genome integration analysis of obesity. Chin Med J (Engl) 2023; 136:910-921. [PMID: 37000968 PMCID: PMC10278747 DOI: 10.1097/cm9.0000000000002644] [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: 11/07/2022] [Indexed: 04/03/2023] Open
Abstract
ABSTRACT The prevalence of obesity has increased worldwide in recent decades. Genetic factors are now known to play a substantial role in the predisposition to obesity and may contribute up to 70% of the risk for obesity. Technological advancements during the last decades have allowed the identification of many hundreds of genetic markers associated with obesity. However, the transformation of current genetic variant-obesity associations into biological knowledge has been proven challenging. Genomics and proteomics are complementary fields, as proteomics extends functional analyses. Integrating genomic and proteomic data can help to bridge a gap in knowledge regarding genetic variant-obesity associations and to identify new drug targets for the treatment of obesity. We provide an overview of the published papers on the integrated analysis of proteomic and genomic data in obesity and summarize four mainstream strategies: overlap, colocalization, Mendelian randomization, and proteome-wide association studies. The integrated analyses identified many obesity-associated proteins, such as leptin, follistatin, and adenylate cyclase 3. Despite great progress, integrative studies focusing on obesity are still limited. There is an increased demand for large prospective cohort studies to identify and validate findings, and further apply these findings to the prevention, intervention, and treatment of obesity. In addition, we also discuss several other potential integration methods.
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Affiliation(s)
- Qigang Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
| | - Baixue Han
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
| | - Qian Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
| | - Tao Wang
- Department of Endocrinology, The Second Affiliated Hospital, Soochow University, Suzhou, Jiangsu 215004, China
| | - Chen Fang
- Department of Endocrinology, The Second Affiliated Hospital, Soochow University, Suzhou, Jiangsu 215004, China
| | - Rui Li
- Department of Gastroenterology, The First Affiliated Hospital, Soochow University, Suzhou, Jiangsu 215006, China
| | - Lei Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
- Center for Genetic Epidemiology and Genomics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
| | - Yufang Pei
- Department of Epidemiology and Biostatistics, School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215123, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215213, China
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Messner CB, Demichev V, Wang Z, Hartl J, Kustatscher G, Mülleder M, Ralser M. Mass spectrometry-based high-throughput proteomics and its role in biomedical studies and systems biology. Proteomics 2023; 23:e2200013. [PMID: 36349817 DOI: 10.1002/pmic.202200013] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/13/2022] [Accepted: 10/13/2022] [Indexed: 11/11/2022]
Abstract
There are multiple reasons why the next generation of biological and medical studies require increasing numbers of samples. Biological systems are dynamic, and the effect of a perturbation depends on the genetic background and environment. As a consequence, many conditions need to be considered to reach generalizable conclusions. Moreover, human population and clinical studies only reach sufficient statistical power if conducted at scale and with precise measurement methods. Finally, many proteins remain without sufficient functional annotations, because they have not been systematically studied under a broad range of conditions. In this review, we discuss the latest technical developments in mass spectrometry (MS)-based proteomics that facilitate large-scale studies by fast and efficient chromatography, fast scanning mass spectrometers, data-independent acquisition (DIA), and new software. We further highlight recent studies which demonstrate how high-throughput (HT) proteomics can be applied to capture biological diversity, to annotate gene functions or to generate predictive and prognostic models for human diseases.
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Affiliation(s)
- Christoph B Messner
- Precision Proteomics Center, Swiss Institute of Allergy and Asthma Research (SIAF), University of Zurich, Davos, Switzerland
| | - Vadim Demichev
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Ziyue Wang
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Johannes Hartl
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Georg Kustatscher
- Wellcome Centre for Cell Biology, University of Edinburgh, Max Born Crescent, Edinburgh, Scotland, UK
| | - Michael Mülleder
- Core Facility High Throughput Mass Spectrometry, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Markus Ralser
- Institute of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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Woldemariam S, Dorner TE, Wiesinger T, Stein KV. Multi-omics approaches for precision obesity management : Potentials and limitations of omics in precision prevention, treatment and risk reduction of obesity. Wien Klin Wochenschr 2023; 135:113-124. [PMID: 36717394 PMCID: PMC10020295 DOI: 10.1007/s00508-022-02146-4] [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: 04/29/2022] [Accepted: 12/12/2022] [Indexed: 02/01/2023]
Abstract
INTRODUCTION Obesity is a multifactorial chronic disease that cannot be addressed by simply promoting better diets and more physical activity. To date, not a single country has successfully been able to curb the accumulating burden of obesity. One explanation for the lack of progress is that lifestyle intervention programs are traditionally implemented without a comprehensive evaluation of an individual's diagnostic biomarkers. Evidence from genome-wide association studies highlight the importance of genetic and epigenetic factors in the development of obesity and how they in turn affect the transcriptome, metabolites, microbiomes, and proteomes. OBJECTIVE The purpose of this review is to provide an overview of the different types of omics data: genomics, epigenomics, transcriptomics, proteomics, metabolomics and illustrate how a multi-omics approach can be fundamental for the implementation of precision obesity management. RESULTS The different types of omics designs are grouped into two categories, the genotype approach and the phenotype approach. When applied to obesity prevention and management, each omics type could potentially help to detect specific biomarkers in people with risk profiles and guide healthcare professionals and decision makers in developing individualized treatment plans according to the needs of the individual before the onset of obesity. CONCLUSION Integrating multi-omics approaches will enable a paradigm shift from the one size fits all approach towards precision obesity management, i.e. (1) precision prevention of the onset of obesity, (2) precision medicine and tailored treatment of obesity, and (3) precision risk reduction and prevention of secondary diseases related to obesity.
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Affiliation(s)
- Selam Woldemariam
- Karl Landsteiner Institute for Health Promotion Research, 3062, Kirchstetten, Austria
| | - Thomas E Dorner
- Karl Landsteiner Institute for Health Promotion Research, 3062, Kirchstetten, Austria
- Academy for Ageing Research, House of Mercy, 1160, Vienna, Austria
| | - Thomas Wiesinger
- Karl Landsteiner Institute for Health Promotion Research, 3062, Kirchstetten, Austria
| | - Katharina Viktoria Stein
- Karl Landsteiner Institute for Health Promotion Research, 3062, Kirchstetten, Austria.
- Department of Public Health and Primary Care, Leiden University Medical Centre, 2511 DP, The Hague, The Netherlands.
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Kreft IC, Hoogendijk AJ, van der Zwaan C, van Alphen FPJ, Boon-Spijker M, Prinsze F, Meijer AB, de Korte D, van den Hurk K, van den Biggelaar M. Mass spectrometry-based analysis on the impact of whole blood donation on the global plasma proteome. Transfusion 2023; 63:564-573. [PMID: 36722460 DOI: 10.1111/trf.17254] [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: 10/07/2022] [Revised: 12/27/2022] [Accepted: 12/27/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND Biomonitoring may provide important insights into the impact of a whole blood donation for individual blood donors. STUDY DESIGN AND METHODS Here, we used unbiased mass spectrometry (MS)-based proteomics to assess longitudinal changes in the global plasma proteome, after a single blood donation for new and regular donors. Subsequently, we compared plasma proteomes of 76 male and female whole blood donors, that were grouped based on their ferritin and hemoglobin (Hb) levels. RESULTS The longitudinal analysis showed limited changes in the plasma proteomes of new and regular donors after a whole blood donation during a 180-day follow-up period, apart from a significant short-term decrease in fibronectin. No differences were observed in the plasma proteomes of donors with high versus low Hb and/or ferritin levels. Plasma proteins with the highest variation between and within donors included pregnancy zone protein, which was associated with sex, Alfa 1-antitrypsin which was associated with the allelic variation, and Immunoglobulin D. Coexpression analysis revealed clustering of proteins that are associated with platelet, red cell, and neutrophil signatures as well as with the complement system and immune responses, including a prominent correlating cluster of immunoglobulin M (IgM), immunoglobulin J chain (JCHAIN), and CD5 antigen-like (CD5L). DISCUSSION Overall, our proteomic approach shows that whole blood donation has a limited impact on the plasma proteins measured. Our findings suggest that plasma profiling can be successfully employed to consistently detect proteins and protein complexes that reflect the functionality and integrity of platelets, red blood cells, and immune cells in blood donors and thus highlights its potential use for donor health monitoring.
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Affiliation(s)
- Iris C Kreft
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Arie J Hoogendijk
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Carmen van der Zwaan
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Floris P J van Alphen
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Mariette Boon-Spijker
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
| | - Femmeke Prinsze
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Alexander B Meijer
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
- Department of Biomolecular Mass Spectrometry and Proteomics, Utrecht Institute for Pharmaceutical Sciences (UIPS), Utrecht University, Utrecht, The Netherlands
| | - Dirk de Korte
- Department of Blood Cell Research, Sanquin Research, Amsterdam, The Netherlands
- Department of Product and Process Development, Sanquin Blood Bank, Amsterdam, The Netherlands
| | - Katja van den Hurk
- Donor Studies, Department of Donor Medicine Research, Sanquin Research, Amsterdam, The Netherlands
| | - Maartje van den Biggelaar
- Laboratory of Proteomics, Department of Molecular Hematology, Sanquin Research, Amsterdam, The Netherlands
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Midha MK, Kapil C, Maes M, Baxter DH, Morrone SR, Prokop TJ, Moritz RL. Vacuum Insulated Probe Heated ElectroSpray Ionization source (VIP-HESI) enhances micro flow rate chromatography signals in the Bruker timsTOF mass spectrometer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528699. [PMID: 36824828 PMCID: PMC9949110 DOI: 10.1101/2023.02.15.528699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/17/2023]
Abstract
By far the largest contribution to ion detectability in liquid chromatography-driven mass spectrometry-based proteomics is the efficient generation of peptide ions by the electrospray source. To maximize the transfer of peptides from liquid to a gaseous phase to allow molecular ions to enter the mass spectrometer at micro-spray flow rates, an efficient electrospray process is required. Here we describe superior performance of new Vacuum-Insulated-Probe-Heated-ElectroSpray-Ionization source (VIP-HESI) coupled with micro-spray flow rate chromatography and Bruker timsTOF PRO mass spectrometer. VIP-HESI significantly improves chromatography signals in comparison to nano-spray ionization using the CaptiveSpray source and provides increased protein detection with higher quantitative precision, enhancing reproducibility of sample injection amounts. Protein quantitation of human K562 lymphoblast samples displayed excellent chromatographic retention time reproducibility (<10% coefficient-of-variation (CV)) with no signal degradation over extended periods of time, and a mouse plasma proteome analysis identified 12% more plasma protein groups allowing large-scale analysis to proceed with confidence (1,267 proteins at 0.4% CV). We show that Slice-PASEF mode with VIP-HESI setup is sensitive in identifying low amounts of peptide without losing quantitative precision. We demonstrate that VIP-HESI coupled with micro-flow-rate chromatography achieves higher depth of coverage and run-to-run reproducibility for a broad range of proteomic applications.
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Validation of disease-specific biomarkers for the early detection of bronchopulmonary dysplasia. Pediatr Res 2023; 93:625-632. [PMID: 35595912 PMCID: PMC9988689 DOI: 10.1038/s41390-022-02093-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 03/23/2022] [Accepted: 04/25/2022] [Indexed: 11/08/2022]
Abstract
OBJECTIVE To demonstrate and validate the improvement of current risk stratification for bronchopulmonary dysplasia (BPD) early after birth by plasma protein markers (sialic acid-binding Ig-like lectin 14 (SIGLEC-14), basal cell adhesion molecule (BCAM), angiopoietin-like 3 protein (ANGPTL-3)) in extremely premature infants. METHODS AND RESULTS Proteome screening in first-week-of-life plasma samples of n = 52 preterm infants <32 weeks gestational age (GA) on two proteomic platforms (SomaLogic®, Olink-Proteomics®) confirmed three biomarkers with significant predictive power: BCAM, SIGLEC-14, and ANGPTL-3. We demonstrate high sensitivity (0.92) and specificity (0.86) under consideration of GA, show the proteins' critical contribution to the predictive power of known clinical risk factors, e.g., birth weight and GA, and predicted the duration of mechanical ventilation, oxygen supplementation, as well as neonatal intensive care stay. We confirmed significant predictive power for BPD cases when switching to a clinically applicable method (enzyme-linked immunosorbent assay) in an independent sample set (n = 25, p < 0.001) and demonstrated disease specificity in different cohorts of neonatal and adult lung disease. CONCLUSION While successfully addressing typical challenges of clinical biomarker studies, we demonstrated the potential of BCAM, SIGLEC-14, and ANGPTL-3 to inform future clinical decision making in the preterm infant at risk for BPD. TRIAL REGISTRATION Deutsches Register Klinische Studien (DRKS) No. 00004600; https://www.drks.de . IMPACT The urgent need for biomarkers that enable early decision making and personalized monitoring strategies in preterm infants with BPD is challenged by targeted marker analyses, cohort size, and disease heterogeneity. We demonstrate the potential of the plasma proteins BCAM, SIGLEC-14, and ANGPTL-3 to identify infants with BPD early after birth while improving the predictive power of clinical variables, confirming the robustness toward proteome assays and proving disease specificity. Our comprehensive analysis enables a phase-III clinical trial that allows full implementation of the biomarkers into clinical routine to enable early risk stratification in preterms with BPD.
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Rostgaard N, Olsen MH, Ottenheijm M, Drici L, Simonsen AH, Plomgaard P, Gredal H, Poulsen HH, Zetterberg H, Blennow K, Hasselbalch SG, MacAulay N, Juhler M. Differential proteomic profile of lumbar and ventricular cerebrospinal fluid. Fluids Barriers CNS 2023; 20:6. [PMID: 36670437 PMCID: PMC9863210 DOI: 10.1186/s12987-022-00405-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 12/29/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Pathological cerebral conditions may manifest in altered composition of the cerebrospinal fluid (CSF). Although diagnostic CSF analysis seeks to establish pathological disturbances in the brain proper, CSF is generally sampled from the lumbar compartment for reasons of technical ease and ethical considerations. We here aimed to compare the molecular composition of CSF obtained from the ventricular versus the lumbar CSF compartments to establish a relevance for employing lumbar CSF as a proxy for the CSF bathing the brain tissue. METHODS CSF was collected from 46 patients with idiopathic normal pressure hydrocephalus (iNPH) patients during their diagnostic workup (lumbar samples) and in connection with their subsequent CSF diversion shunt surgery (ventricular samples). The mass-spectrometry-based proteomic profile was determined in these samples and in addition, selected biomarkers were quantified with ELISA (S100B, neurofilament light (NfL), amyloid-β (Aβ40, Aβ42), and total tau (T-tau) and phosphorylated tau (P-tau) forms). The latter analysis was extended to include paired porcine samples obtained from the lumbar compartment and the cerebromedullary cistern closely related to the ventricles. RESULTS In total 1231 proteins were detected in the human CSF. Of these, 216 distributed equally in the two CSF compartments, whereas 22 were preferentially (or solely) present in the ventricular CSF and four in the lumbar CSF. The selected biomarkers of neurodegeneration and Alzheimer's disease displayed differential distribution, some with higher (S100B, T-tau, and P-tau) and some with lower (NfL, Aβ40, Aβ42) levels in the ventricular compartment. In the porcine samples, all biomarkers were most abundant in the lumbar CSF. CONCLUSIONS The overall proteomic profile differs between the ventricular and the lumbar CSF compartments, and so does the distribution of clinically employed biomarkers. However, for a range of CSF proteins and biomarkers, one can reliably employ lumbar CSF as a proxy for ventricular CSF if or a lumbar/cranial index for the particular molecule has been established. It is therefore important to verify the compartmental preference of the proteins or biomarkers of interest prior to extrapolating from lumbar CSF to that of the ventricular fluid bordering the brain.
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Affiliation(s)
- Nina Rostgaard
- grid.475435.4Department of Neurosurgery, The Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Markus Harboe Olsen
- grid.475435.4Department of Neuroanaesthesiology, The Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Maud Ottenheijm
- grid.5254.60000 0001 0674 042XNNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark ,grid.475435.4Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Lylia Drici
- grid.5254.60000 0001 0674 042XNNF Center for Protein Research, University of Copenhagen, Copenhagen, Denmark ,grid.475435.4Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Anja Hviid Simonsen
- grid.475435.4Danish Dementia Research Centre, Department of Neurology, Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Peter Plomgaard
- grid.475435.4Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Hanne Gredal
- grid.5254.60000 0001 0674 042XDepartment of Veterinary Clinical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Helle Harding Poulsen
- grid.5254.60000 0001 0674 042XDepartment of Veterinary Clinical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Henrik Zetterberg
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Gothenburg, Sweden ,grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Gothenburg, Sweden ,grid.83440.3b0000000121901201Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK ,grid.83440.3b0000000121901201UK Dementia Research Institute at UCL, London, UK ,grid.24515.370000 0004 1937 1450Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Kaj Blennow
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Gothenburg, Sweden ,grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Gothenburg, Sweden
| | - Steen Gregers Hasselbalch
- grid.475435.4Danish Dementia Research Centre, Department of Neurology, Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark ,grid.5254.60000 0001 0674 042XDepartment of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Nanna MacAulay
- grid.5254.60000 0001 0674 042XDepartment of Neuroscience, University of Copenhagen, Copenhagen, Denmark
| | - Marianne Juhler
- grid.475435.4Department of Neurosurgery, The Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark ,grid.5254.60000 0001 0674 042XDepartment of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Hu A, Zhang L, Wang Z, Yuan C, Lin L, Zhang J, Gao X, Chen X, Guo W, Yang P, Shen H. Cancer Serum Atlas-Supported Precise Pan-Targeted Proteomics Enable Multicancer Detection. Anal Chem 2023; 95:862-871. [PMID: 36584310 DOI: 10.1021/acs.analchem.2c03299] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
The wide dynamic range of serum proteome restrained discovery of clinically interested proteins in large cohort studies. Herein, we presented a high-sensitivity, high-throughput, and precise pan-targeted serum proteomic strategy for highly efficient cancer serum proteomic research and biomarker discovery. We constructed a resource of over 2000 cancer-secreted proteins, and the standard MS assays and spectra of at least one synthetic unique peptide per protein were acquired and documented (Cancer Serum Atlas, www.cancerserumatlas.com). Then, the standard peptide-anchored parallel reaction monitoring (SPA-PRM) method was developed with support of the Cancer Serum Atlas, achieving precise quantification of cancer-secreted proteins with high throughput and sensitivity. We directly quantified 325 cancer-related serum proteins in 288 serums of four cancer types (liver, stomach, lung, breast) and controls with the pan-targeted strategy and discovered considerable potential biomarker benefits for early detection of cancer. Finally, a proteomic-based multicancer detection model was built, demonstrating high sensitivity (87.2%) and specificity (100%), with 73.8% localization accuracy for an independent test set. In conclusion, the Cancer Serum Atlas provides a wide range of potential biomarkers that serve as targets and standard assays for systematic and highly efficient serological studies of cancer. The Cancer Serum Atlas-supported pan-targeted proteomic strategy enables highly efficient biomarker discovery and multicancer detection and thus can be a powerful tool for liquid biopsy.
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Affiliation(s)
- Anqi Hu
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
| | - Lei Zhang
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
| | - Zhenxin Wang
- Department of Laboratory Medicine of Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Chunyan Yuan
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
| | - Ling Lin
- Department of Cardiology, Shanghai Institute of Cardiovascular Diseases, Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Jiayi Zhang
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
| | - Xia Gao
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
| | - Xuguang Chen
- Informatization Office, Fudan University, Shanghai 200032, China
| | - Wei Guo
- Department of Laboratory Medicine of Zhongshan Hospital, Fudan University, Shanghai 200032, China
| | - Pengyuan Yang
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
| | - Huali Shen
- Institutes of Biomedical Sciences and Minhang Hospital, Fudan University, Shanghai 200032, China
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Perry AS, Tanriverdi K, Risitano A, Hwang SJ, Murthy VL, Nayor M, Zhao S, Levy D, Shah RV, Freedman JE. The inflammatory proteome, obesity, and medical weight loss and regain in humans. Obesity (Silver Spring) 2023; 31:150-158. [PMID: 36334095 PMCID: PMC9923277 DOI: 10.1002/oby.23587] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2022] [Revised: 08/12/2022] [Accepted: 08/16/2022] [Indexed: 11/06/2022]
Abstract
OBJECTIVE Weight regain occurs after medical weight loss via mechanisms of post-weight-loss "metabolic adaptation." The relationship of inflammatory proteins with weight loss/regain was studied to determine a role for inflammation in metabolic adaptation. METHODS Seventy-four proteins central to inflammation and immune regulation (Olink) were analyzed in plasma from up to 490 participants in a trial of medical weight-loss maintenance. Cross-sectional and longitudinal associations of proteins with weight were measured using linear and mixed effects regression models and t testing, with replication in the Framingham Heart Study. RESULTS Broad changes in the inflammatory proteome were observed among the study cohort (60% women, 35% African American) with initial weight loss of ≈8 kg from a median 94 kg at study entry (33/74 proteins; 7 increased; 26 decreased), many of which tracked with weight regain of median ≈2 kg over the next 30 months. Ten proteins were associated with different rates of weight regain, some specifying pathways of chemotaxis and innate immune responses. Several of the observed protein associations were also linked to prevalent obesity in the Framingham Heart Study. CONCLUSIONS Broad changes in the inflammatory proteome track with changes in weight and may identify specific pathways that modify patterns of weight regain.
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Affiliation(s)
- Andrew S Perry
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Kahraman Tanriverdi
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Antonina Risitano
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Shih-Jen Hwang
- Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Venkatesh L Murthy
- Department of Medicine and Radiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew Nayor
- Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USA
| | - Shilin Zhao
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Daniel Levy
- Framingham Heart Study, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Ravi V Shah
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Jane E Freedman
- Vanderbilt Translational and Clinical Cardiovascular Research Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
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Torun F, Virreira Winter S, Doll S, Riese FM, Vorobyev A, Mueller-Reif JB, Geyer PE, Strauss MT. Transparent Exploration of Machine Learning for Biomarker Discovery from Proteomics and Omics Data. J Proteome Res 2022; 22:359-367. [PMID: 36426751 PMCID: PMC9903317 DOI: 10.1021/acs.jproteome.2c00473] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
Biomarkers are of central importance for assessing the health state and to guide medical interventions and their efficacy; still, they are lacking for most diseases. Mass spectrometry (MS)-based proteomics is a powerful technology for biomarker discovery but requires sophisticated bioinformatics to identify robust patterns. Machine learning (ML) has become a promising tool for this purpose. However, it is sometimes applied in an opaque manner and generally requires specialized knowledge. To enable easy access to ML for biomarker discovery without any programming or bioinformatics skills, we developed "OmicLearn" (http://OmicLearn.org), an open-source browser-based ML tool using the latest advances in the Python ML ecosystem. Data matrices from omics experiments are easily uploaded to an online or a locally installed web server. OmicLearn enables rapid exploration of the suitability of various ML algorithms for the experimental data sets. It fosters open science via transparent assessment of state-of-the-art algorithms in a standardized format for proteomics and other omics sciences.
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Affiliation(s)
| | | | - Sophia Doll
- OmicEra
Diagnostics GmbH, 82152 Planegg, Germany
| | | | | | | | | | - Maximilian T. Strauss
- Novo
Nordisk Foundation Center for Protein Research, University of Copenhagen, 2200 Copenhagen, Denmark,
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Mohaupt P, Roucou X, Delaby C, Vialaret J, Lehmann S, Hirtz C. The alternative proteome in neurobiology. Front Cell Neurosci 2022; 16:1019680. [PMID: 36467612 PMCID: PMC9712206 DOI: 10.3389/fncel.2022.1019680] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 11/02/2022] [Indexed: 10/13/2023] Open
Abstract
Translation involves the biosynthesis of a protein sequence following the decoding of the genetic information embedded in a messenger RNA (mRNA). Typically, the eukaryotic mRNA was considered to be inherently monocistronic, but this paradigm is not in agreement with the translational landscape of cells, tissues, and organs. Recent ribosome sequencing (Ribo-seq) and proteomics studies show that, in addition to currently annotated reference proteins (RefProt), other proteins termed alternative proteins (AltProts), and microproteins are encoded in regions of mRNAs thought to be untranslated or in transcripts annotated as non-coding. This experimental evidence expands the repertoire of functional proteins within a cell and potentially provides important information on biological processes. This review explores the hitherto overlooked alternative proteome in neurobiology and considers the role of AltProts in pathological and healthy neuromolecular processes.
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Affiliation(s)
- Pablo Mohaupt
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Xavier Roucou
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Constance Delaby
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Jérôme Vialaret
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Sylvain Lehmann
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
| | - Christophe Hirtz
- LBPC-PPC, Université de Montpellier, IRMB CHU de Montpellier, INM INSERM, Montpellier, France
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Ashkarran AA, Gharibi H, Voke E, Landry MP, Saei AA, Mahmoudi M. Measurements of heterogeneity in proteomics analysis of the nanoparticle protein corona across core facilities. Nat Commun 2022; 13:6610. [PMID: 36329043 PMCID: PMC9633814 DOI: 10.1038/s41467-022-34438-8] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 10/25/2022] [Indexed: 11/06/2022] Open
Abstract
Robust characterization of the protein corona-the layer of proteins that spontaneously forms on the surface of nanoparticles immersed in biological fluids-is vital for prediction of the safety, biodistribution, and diagnostic/therapeutic efficacy of nanomedicines. Protein corona identity and abundance characterization is entirely dependent on liquid chromatography coupled to mass spectroscopy (LC-MS/MS), though the variability of this technique for the purpose of protein corona characterization remains poorly understood. Here we investigate the variability of LC-MS/MS workflows in analysis of identical aliquots of protein coronas by sending them to different proteomics core-facilities and analyzing the retrieved datasets. While the shared data between the cores correlate well, there is considerable heterogeneity in the data retrieved from different cores. Specifically, out of 4022 identified unique proteins, only 73 (1.8%) are shared across the core facilities providing semiquantitative analysis. These findings suggest that protein corona datasets cannot be easily compared across independent studies and more broadly compromise the interpretation of protein corona research, with implications in biomarker discovery as well as the safety and efficacy of our nanoscale biotechnologies.
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Affiliation(s)
- Ali Akbar Ashkarran
- grid.17088.360000 0001 2150 1785Department of Radiology and Precision Health Program, Michigan State University, East Lansing, MI USA
| | - Hassan Gharibi
- grid.4714.60000 0004 1937 0626Division of Physiological Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Elizabeth Voke
- grid.47840.3f0000 0001 2181 7878Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA USA
| | - Markita P. Landry
- grid.47840.3f0000 0001 2181 7878Department of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA USA ,grid.510960.b0000 0004 7798 3869Innovative Genomics Institute, Berkeley, CA USA ,grid.47840.3f0000 0001 2181 7878California Institute for Quantitative Biosciences, University of California, Berkeley, Berkeley, CA USA ,grid.499295.a0000 0004 9234 0175Chan Zuckerberg Biohub, San Francisco, CA USA
| | - Amir Ata Saei
- grid.4714.60000 0004 1937 0626Division of Physiological Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden ,grid.38142.3c000000041936754XDepartment of Cell Biology, Harvard Medical School, Boston, MA USA ,grid.6612.30000 0004 1937 0642Present Address: Biozentrum, University of Basel, 4056 Basel, Switzerland
| | - Morteza Mahmoudi
- grid.17088.360000 0001 2150 1785Department of Radiology and Precision Health Program, Michigan State University, East Lansing, MI USA
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Hill EB, Siebert JC, Yazza DN, Ostendorf DM, Bing K, Wayland L, Scorsone JJ, Bessesen DH, MacLean PS, Melanson EL, Catenacci VA, Borengasser SJ. Proteomics, dietary intake, and changes in cardiometabolic health within a behavioral weight-loss intervention: A pilot study. Obesity (Silver Spring) 2022; 30:2134-2145. [PMID: 36321274 PMCID: PMC9634672 DOI: 10.1002/oby.23574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2022] [Revised: 08/15/2022] [Accepted: 08/24/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Identifying associations among circulating proteins, dietary intakes, and clinically relevant indicators of cardiometabolic health during weight loss may elucidate biologically relevant pathways affected by diet, allowing for an incorporation of precision nutrition approaches when designing future interventions. This study hypothesized that plasma proteins would be associated with diet and cardiometabolic health indicators within a behavioral weight-loss intervention. METHODS This secondary data analysis included participants (n = 20, mean [SD], age: 40.1 [9.5] years, BMI: 34.2 [4.0] kg/m2 ) who completed a 1-year behavioral weight-loss intervention. Cardiovascular disease-related plasma proteins, diet, and cardiometabolic health indicators were evaluated at baseline and 3 months. Associations were determined via linear regression and integrated networks created using Visualization Of LineAr Regression Elements (VOLARE). RESULTS A total of 16 plasma proteins were associated with ≥1 diet or health indicator at baseline (p < 0.001); changes in 42 proteins were associated with changes in diet or health indicators from baseline to 3 months (p < 0.005). Baseline tumor necrosis factor receptor superfamily member 10C (TNFRSF10C) was associated with intakes of dark green vegetables (r = -0.712), and fatty acid-binding protein 4 (FABP4) was associated with intakes of unsweetened coffee (r = -0.689). Changes in refined-grain intakes were associated with changes in scavenger receptor cysteine-rich type 1 protein M130 (CD163; r = 0.725), interleukin-1 receptor type 1 (IL1R-T1; r = 0.624), insulin (r = 0.656), and triglycerides (r = 0.648). CONCLUSIONS Circulating cardiovascular disease-related proteins were associated with diet and cardiometabolic health indicators prior to and in response to weight loss.
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Affiliation(s)
- Emily B. Hill
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Deaunabah N. Yazza
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Danielle M. Ostendorf
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kristen Bing
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Liza Wayland
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Jared J. Scorsone
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Daniel H. Bessesen
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Paul S. MacLean
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Edward L. Melanson
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Division of Geriatric Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Eastern Colorado Veterans Affairs Geriatric Research, Education, and Clinical Center, Denver, CO, USA
| | - Victoria A. Catenacci
- Department of Medicine, Division of Endocrinology, Metabolism, and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Medicine, Anschutz Health and Wellness Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Sarah J. Borengasser
- Department of Pediatrics, Section of Nutrition, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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45
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King CD, Kapp KL, Arul AB, Choi MJ, Robinson RAS. Advancements in automation for plasma proteomics sample preparation. Mol Omics 2022; 18:828-839. [PMID: 36048090 PMCID: PMC9879274 DOI: 10.1039/d2mo00122e] [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] [Indexed: 01/28/2023]
Abstract
Automation is necessary to increase sample processing throughput for large-scale clinical analyses. Replacement of manual pipettes with robotic liquid handler systems is especially helpful in processing blood-based samples, such as plasma and serum. These samples are very heterogenous, and protein expression can vary greatly from sample-to-sample, even for healthy controls. Detection of true biological changes requires that variation from sample preparation steps and downstream analytical detection methods, such as mass spectrometry, remains low. In this mini-review, we discuss plasma proteomics protocols and the benefits of automation towards enabling detection of low abundant proteins and providing low sample error and increased sample throughput. This discussion includes considerations for automation of major sample depletion and/or enrichment strategies for plasma toward mass spectrometry detection.
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Affiliation(s)
- Christina D King
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - Kathryn L Kapp
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37232, USA
| | - Albert B Arul
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - Min Ji Choi
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
| | - Renã A S Robinson
- Department of Chemistry, Vanderbilt University, Nashville, Tennessee 37235, USA
- Vanderbilt Institute of Chemical Biology, Vanderbilt University, Nashville, Tennessee 37232, USA
- Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee 37232, USA
- Vanderbilt Memory & Alzheimer's Center, Vanderbilt University Medical Center, Nashville, Tennessee 37212, USA
- Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee 37232, USA
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46
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Cominetti O, Núñez Galindo A, Corthésy J, Carayol J, Germain N, Galusca B, Estour B, Hager J, Gheldof N, Dayon L. Proteomics reveals unique plasma signatures in constitutional thinness. Proteomics Clin Appl 2022; 16:e2100114. [PMID: 35579096 PMCID: PMC9787820 DOI: 10.1002/prca.202100114] [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: 11/11/2021] [Revised: 04/14/2022] [Accepted: 05/13/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE Studying the plasma proteome of control versus constitutionally thin (CT) individuals, exposed to overfeeding, may give insights into weight-gain management, providing relevant information to the clinical entity of weight-gain resistant CT, and discovering new markers for the condition. EXPERIMENTAL DESIGN Untargeted protein relative quantification of 63 CT and normal-weight individuals was obtained in blood plasma at baseline, during and after an overfeeding challenge using mass spectrometry-based proteomics. RESULTS The plasma proteome of CT subjects presented limited specificity with respect to controls at baseline. Yet, CT showed lower levels of inflammatory C-reactive protein and larger levels of protective insulin-like growth factor-binding protein 2. Differences were more marked during and after overfeeding. CT plasma proteome showed larger magnitude and significance in response, suggesting enhanced "resilience" and more rapid adaptation to changes. Four proteins behaved similarly between CT and controls, while five were regulated in opposite fashion. Ten proteins were differential during overfeeding in CT only (including increased fatty acid-binding protein and glyceraldehyde-3-phosphate dehydrogenase, and decreased apolipoprotein C-II and transferrin receptor protein 1). CONCLUSIONS AND CLINICAL RELEVANCE This first proteomic profiling of a CT cohort reveals different plasma proteomes between CT subjects and controls in a longitudinal clinical trial. Our molecular observations further support that the resistance to weight gain in CT subjects appears predominantly biological. CLINICALTRIALS gov Identifier: NCT02004821.
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Affiliation(s)
- Ornella Cominetti
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland
| | - Antonio Núñez Galindo
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland
| | - John Corthésy
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland
| | - Jérôme Carayol
- Nestlé Institute of Health SciencesNestlé ResearchLausanneSwitzerland,Present address:
Playtika Switzerland SARue du Port‐Franc 2ALausanne1003Switzerland
| | - Natacha Germain
- Division of EndocrinologyDiabetes, Metabolism and Eating Disorders, CHU St‐EtienneFrance
| | - Bogdan Galusca
- Division of EndocrinologyDiabetes, Metabolism and Eating Disorders, CHU St‐EtienneFrance
| | - Bruno Estour
- Division of EndocrinologyDiabetes, Metabolism and Eating Disorders, CHU St‐EtienneFrance
| | - Jörg Hager
- Nestlé Institute of Health SciencesNestlé ResearchLausanneSwitzerland
| | - Nele Gheldof
- Nestlé Institute of Health SciencesNestlé ResearchLausanneSwitzerland,Present address:
VPA ‐ AVP‐R‐Administration, EPFLBI A2 483, Station 7Lausanne1015Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety & Analytical SciencesNestlé ResearchLausanneSwitzerland,Institut des Sciences et Ingénierie ChimiquesÉcole Polytechnique Fédérale de Lausanne (EPFL)LausanneSwitzerland
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47
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Zapata RC, Carretero M, Reis FCG, Chaudry BS, Ofrecio J, Zhang D, Sasik R, Ciaraldi T, Petrascheck M, Osborn O. Adipocytes control food intake and weight regain via Vacuolar-type H + ATPase. Nat Commun 2022; 13:5092. [PMID: 36042358 PMCID: PMC9427743 DOI: 10.1038/s41467-022-32764-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Accepted: 08/12/2022] [Indexed: 11/10/2022] Open
Abstract
Energy metabolism becomes dysregulated in individuals with obesity and many of these changes persist after weight loss and likely play a role in weight regain. In these studies, we use a mouse model of diet-induced obesity and weight loss to study the transcriptional memory of obesity. We found that the 'metabolic memory' of obesity is predominantly localized in adipocytes. Utilizing a C. elegans-based food intake assay, we identify 'metabolic memory' genes that play a role in food intake regulation. We show that expression of ATP6v0a1, a subunit of V-ATPase, is significantly induced in both obese mouse and human adipocytes that persists after weight loss. C. elegans mutants deficient in Atp6v0A1/unc32 eat less than WT controls. Adipocyte-specific Atp6v0a1 knockout mice have reduced food intake and gain less weight in response to HFD. Pharmacological disruption of V-ATPase assembly leads to decreased food intake and less weight re-gain. In summary, using a series of genetic tools from invertebrates to vertebrates, we identify ATP6v0a1 as a regulator of peripheral metabolic memory, providing a potential target for regulation of food intake, weight loss maintenance and the treatment of obesity.
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Affiliation(s)
- Rizaldy C Zapata
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Maria Carretero
- Department of Molecular Medicine and Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Felipe Castellani Gomes Reis
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Besma S Chaudry
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Jachelle Ofrecio
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Dinghong Zhang
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Roman Sasik
- Center for Computational Biology & Bioinformatics, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - Theodore Ciaraldi
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA
- VA San Diego Healthcare System, La Jolla, CA, 92037, USA
| | - Michael Petrascheck
- Department of Molecular Medicine and Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Olivia Osborn
- Division of Endocrinology and Metabolism, School of Medicine, University of California San Diego, La Jolla, CA, 92093, USA.
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48
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Dayon L, Cominetti O, Affolter M. Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications. Expert Rev Proteomics 2022; 19:131-151. [PMID: 35466824 DOI: 10.1080/14789450.2022.2070477] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids. AREAS COVERED We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics. EXPERT OPINION While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.
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Affiliation(s)
- Loïc Dayon
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland.,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne, Switzerland
| | - Ornella Cominetti
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland
| | - Michael Affolter
- Proteomics, Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, CH-1015 Lausanne, Switzerland
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49
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Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions. Proc Natl Acad Sci U S A 2022; 119:e2106053119. [PMID: 35275789 PMCID: PMC8931255 DOI: 10.1073/pnas.2106053119] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
SignificanceDeep profiling of the plasma proteome at scale has been a challenge for traditional approaches. We achieve superior performance across the dimensions of precision, depth, and throughput using a panel of surface-functionalized superparamagnetic nanoparticles in comparison to conventional workflows for deep proteomics interrogation. Our automated workflow leverages competitive nanoparticle-protein binding equilibria that quantitatively compress the large dynamic range of proteomes to an accessible scale. Using machine learning, we dissect the contribution of individual physicochemical properties of nanoparticles to the composition of protein coronas. Our results suggest that nanoparticle functionalization can be tailored to protein sets. This work demonstrates the feasibility of deep, precise, unbiased plasma proteomics at a scale compatible with large-scale genomics enabling multiomic studies.
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50
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Dubois E, Galindo AN, Dayon L, Cominetti O. Assessing normalization methods in mass spectrometry-based proteome profiling of clinical samples. Biosystems 2022; 215-216:104661. [PMID: 35247480 DOI: 10.1016/j.biosystems.2022.104661] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 02/21/2022] [Accepted: 02/28/2022] [Indexed: 12/31/2022]
Abstract
BACKGROUND Large-scale proteomic studies have to deal with unwanted variability, especially when samples originate from different centers and multiple analytical batches are needed. Such variability is typically added throughout all the steps of a clinical research study, from human biological sample collection and storage, sample preparation, spectral data acquisition, to peptide and protein quantification. In order to remove such diverse and unwanted variability, normalization of the protein data is performed. There have been already several published reviews comparing normalization methods in the -omics field, but reports focusing on proteomic data generated with mass spectrometry (MS) are much fewer. Additionally, most of these reports have only dealt with small datasets. RESULTS As a case study, here we focused on the normalization of a large MS-based proteomic dataset obtained from an overweight and obese pan-European cohort, where different normalization methods were evaluated, namely: center standardize, quantile protein, quantile sample, global standardization, ComBat, median centering, mean centering, single standard and removal of unwanted variation (RUV); some of these are generic normalization methods while others have been specifically created to deal with genomic or metabolomic data. We checked how relationships between proteins and clinical variables (e.g., gender, levels of triglycerides or cholesterol) were improved after normalizing the data with the different methods. CONCLUSIONS Some normalization methods were better adapted for this particular large-scale shotgun proteomic dataset of human plasma samples labeled with isobaric tags and analyzed with liquid chromatography-tandem MS. In particular, quantile sample normalization, RUV, mean and median centering showed very good performance, while quantile protein normalization provided worse results than those obtained with unnormalized data.
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Affiliation(s)
- Etienne Dubois
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland
| | - Antonio Núñez Galindo
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland; Chemistry and Chemical Engineering Section, School of Basic Sciences, Ecole Polytechnique Fédérale de Lausanne, 1015, Lausanne, Switzerland
| | - Ornella Cominetti
- Nestlé Institute of Food Safety & Analytical Sciences, Nestlé Research, EPFL Innovation Park, 1015, Lausanne, Switzerland.
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