1
|
Pontes JGDM, Jadranin M, Assalin MR, Quintero Escobar M, Stanisic D, Costa TBBC, van Helvoort Lengert A, Boldrini É, Morini da Silva SR, Vidal DO, Liu LHB, Maschietto M, Tasic L. Lipidomics by Nuclear Magnetic Resonance Spectroscopy and Liquid Chromatography-High-Resolution Mass Spectrometry in Osteosarcoma: A Pilot Study. Metabolites 2024; 14:416. [PMID: 39195512 DOI: 10.3390/metabo14080416] [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: 06/04/2024] [Revised: 07/22/2024] [Accepted: 07/24/2024] [Indexed: 08/29/2024] Open
Abstract
Cancer is a complex disease that can also affect the younger population; however, it is responsible for a relatively high mortality rate of children and youth, especially in low- and middle-income countries (LMICs). Besides that, lipidomic studies in this age range are scarce. Therefore, we analyzed blood serum samples from young patients (12 to 35 years) with bone sarcoma (osteosarcoma) and compared their lipidomics to the ones from the control group of samples, named healthy control (HC group), using NMR and LC-MS techniques. Furthermore, differences in the lipidomic profiles between OS patients with and without metastasis indicate higher glycerophosphocholine (GPC) and glycerophospholipid (GPL) levels in osteosarcoma and increased cholesterol, choline, polyunsaturated fatty acids (PUFAs), and glycerols during the metastasis. These differences, detected in the peripheral blood, could be used as biomarkers for liquid biopsy.
Collapse
Affiliation(s)
| | - Milka Jadranin
- Laboratory of Biological Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-970, Brazil
- Department of Chemistry, Institute of Chemistry, Technology and Metallurgy, University of Belgrade, Njegoševa 12, 11000 Belgrade, Serbia
| | - Márcia Regina Assalin
- Laboratory of Biological Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-970, Brazil
- Embrapa Environment, Jaguariúna 13820-000, Brazil
| | - Melissa Quintero Escobar
- Laboratory of Biological Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-970, Brazil
| | - Danijela Stanisic
- Laboratory of Biological Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-970, Brazil
| | | | | | - Érica Boldrini
- Barretos Children's Cancer Hospital, Barretos 14784-400, Brazil
| | | | - Daniel Onofre Vidal
- Molecular Oncology Research Center (CPOM), Barretos Cancer Hospital, Barretos 14784-400, Brazil
| | - Leticia Huan Bacellar Liu
- Laboratory of Biological Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-970, Brazil
| | - Mariana Maschietto
- Brazilian Biosciences National Laboratory (LNBio), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas 13083-100, Brazil
| | - Ljubica Tasic
- Laboratory of Biological Chemistry, Institute of Chemistry, Universidade Estadual de Campinas, Campinas 13083-970, Brazil
| |
Collapse
|
2
|
Mondal K, Del Mar NA, Gary AA, Grambergs RC, Yousuf M, Tahia F, Stephenson B, Stephenson DJ, Chalfant CE, Reiner A, Mandal N. Sphingolipid changes in mouse brain and plasma after mild traumatic brain injury at the acute phases. Lipids Health Dis 2024; 23:200. [PMID: 38937745 PMCID: PMC11209960 DOI: 10.1186/s12944-024-02186-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Accepted: 06/14/2024] [Indexed: 06/29/2024] Open
Abstract
BACKGROUND Traumatic brain injury (TBI) causes neuroinflammation and can lead to long-term neurological dysfunction, even in cases of mild TBI (mTBI). Despite the substantial burden of this disease, the management of TBI is precluded by an incomplete understanding of its cellular mechanisms. Sphingolipids (SPL) and their metabolites have emerged as key orchestrators of biological processes related to tissue injury, neuroinflammation, and inflammation resolution. No study so far has investigated comprehensive sphingolipid profile changes immediately following TBI in animal models or human cases. In this study, sphingolipid metabolite composition was examined during the acute phases in brain tissue and plasma of mice following mTBI. METHODS Wildtype mice were exposed to air-blast-mediated mTBI, with blast exposure set at 50-psi on the left cranium and 0-psi designated as Sham. Sphingolipid profile was analyzed in brain tissue and plasma during the acute phases of 1, 3, and 7 days post-TBI via liquid-chromatography-mass spectrometry. Simultaneously, gene expression of sphingolipid metabolic markers within brain tissue was analyzed using quantitative reverse transcription-polymerase chain reaction. Significance (P-values) was determined by non-parametric t-test (Mann-Whitney test) and by Tukey's correction for multiple comparisons. RESULTS In post-TBI brain tissue, there was a significant elevation of 1) acid sphingomyelinase (aSMase) at 1- and 3-days, 2) neutral sphingomyelinase (nSMase) at 7-days, 3) ceramide-1-phosphate levels at 1 day, and 4) monohexosylceramide (MHC) and sphingosine at 7-days. Among individual species, the study found an increase in C18:0 and a decrease in C24:1 ceramides (Cer) at 1 day; an increase in C20:0 MHC at 3 days; decrease in MHC C18:0 and increase in MHC C24:1, sphingomyelins (SM) C18:0, and C24:0 at 7 days. Moreover, many sphingolipid metabolic genes were elevated at 1 day, followed by a reduction at 3 days and an absence at 7-days post-TBI. In post-TBI plasma, there was 1) a significant reduction in Cer and MHC C22:0, and an increase in MHC C16:0 at 1 day; 2) a very significant increase in long-chain Cer C24:1 accompanied by significant decreases in Cer C24:0 and C22:0 in MHC and SM at 3 days; and 3) a significant increase of C22:0 in all classes of SPL (Cer, MHC and SM) as well as a decrease in Cer C24:1, MHC C24:1 and MHC C24:0 at 7 days. CONCLUSIONS Alterations in sphingolipid metabolite composition, particularly sphingomyelinases and short-chain ceramides, may contribute to the induction and regulation of neuroinflammatory events in the early stages of TBI, suggesting potential targets for novel diagnostic, prognostic, and therapeutic strategies in the future.
Collapse
Affiliation(s)
- Koushik Mondal
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
- Molecular Diagnostics Laboratory, Department of Basic & Translational Research, Saroj Gupta Cancer Centre & Research Institute, Kolkata, WB, 700 063, India
| | - Nobel A Del Mar
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
| | - Ashlyn A Gary
- Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Richard C Grambergs
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
| | - Mohd Yousuf
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
| | - Faiza Tahia
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
| | - Benjamin Stephenson
- Departments of Medicine and Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
| | - Daniel J Stephenson
- Departments of Medicine and Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
| | - Charles E Chalfant
- Departments of Medicine and Cell Biology, University of Virginia School of Medicine, Charlottesville, VA, 22903, USA
- Research Service, Richmond VA Medical Center, Richmond, VA, 23298, USA
| | - Anton Reiner
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
- Department of Anatomy and Neurobiology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA
| | - Nawajes Mandal
- Department of Ophthalmology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA.
- Department of Anatomy and Neurobiology, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA.
- Department of Pharmaceutical Sciences, College of Pharmacy, The University of Tennessee Health Science Centre, Memphis, TN, 38163, USA.
- Memphis VA Medical Center, Memphis, TN, 38104, USA.
| |
Collapse
|
3
|
Lin WJ, Chiang AWT, Zhou EH, Liang C, Liu CH, Ma WL, Cheng WC, Lewis NE. iLipidome: enhancing statistical power and interpretability using hidden biosynthetic interdependencies in the lipidome. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.16.594607. [PMID: 38826229 PMCID: PMC11142111 DOI: 10.1101/2024.05.16.594607] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Numerous biological processes and diseases are influenced by lipid composition. Advances in lipidomics are elucidating their roles, but analyzing and interpreting lipidomics data at the systems level remain challenging. To address this, we present iLipidome, a method for analyzing lipidomics data in the context of the lipid biosynthetic network, thus accounting for the interdependence of measured lipids. iLipidome enhances statistical power, enables reliable clustering and lipid enrichment analysis, and links lipidomic changes to their genetic origins. We applied iLipidome to investigate mechanisms driving changes in cellular lipidomes following supplementation of docosahexaenoic acid (DHA) and successfully identified the genetic causes of alterations. We further demonstrated how iLipidome can disclose enzyme-substrate specificity and pinpoint prospective glioblastoma therapeutic targets. Finally, iLipidome enabled us to explore underlying mechanisms of cardiovascular disease and could guide the discovery of early lipid biomarkers. Thus, iLipidome can assist researchers studying the essence of lipidomic data and advance the field of lipid biology.
Collapse
|
4
|
He M, Hou G, Liu M, Peng Z, Guo H, Wang Y, Sui J, Liu H, Yin X, Zhang M, Chen Z, Rensen PCN, Lin L, Wang Y, Shi B. Lipidomic studies revealing serological markers associated with the occurrence of retinopathy in type 2 diabetes. J Transl Med 2024; 22:448. [PMID: 38741137 DOI: 10.1186/s12967-024-05274-9] [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: 08/21/2023] [Accepted: 05/04/2024] [Indexed: 05/16/2024] Open
Abstract
PURPOSE The duration of type 2 diabetes mellitus (T2DM) and blood glucose levels have a significant impact on the development of T2DM complications. However, currently known risk factors are not good predictors of the onset or progression of diabetic retinopathy (DR). Therefore, we aimed to investigate the differences in the serum lipid composition in patients with T2DM, without and with DR, and search for potential serological indicators associated with the development of DR. METHODS A total of 622 patients with T2DM hospitalized in the Department of Endocrinology of the First Affiliated Hospital of Xi'an JiaoTong University were selected as the discovery set. One-to-one case-control matching was performed according to the traditional risk factors for DR (i.e., age, duration of diabetes, HbA1c level, and hypertension). All cases with comorbid chronic kidney disease were excluded to eliminate confounding factors. A total of 42 pairs were successfully matched. T2DM patients with DR (DR group) were the case group, and T2DM patients without DR (NDR group) served as control subjects. Ultra-performance liquid chromatography-mass spectrometry (LC-MS/MS) was used for untargeted lipidomics analysis on serum, and a partial least squares discriminant analysis (PLS-DA) model was established to screen differential lipid molecules based on variable importance in the projection (VIP) > 1. An additional 531 T2DM patients were selected as the validation set. Next, 1:1 propensity score matching (PSM) was performed for the traditional risk factors for DR, and a combined 95 pairings in the NDR and DR groups were successfully matched. The screened differential lipid molecules were validated by multiple reaction monitoring (MRM) quantification based on mass spectrometry. RESULTS The discovery set showed no differences in traditional risk factors associated with the development of DR (i.e., age, disease duration, HbA1c, blood pressure, and glomerular filtration rate). In the DR group compared with the NDR group, the levels of three ceramides (Cer) and seven sphingomyelins (SM) were significantly lower, and one phosphatidylcholine (PC), two lysophosphatidylcholines (LPC), and two SMs were significantly higher. Furthermore, evaluation of these 15 differential lipid molecules in the validation sample set showed that three Cer and SM(d18:1/24:1) molecules were substantially lower in the DR group. After excluding other confounding factors (e.g., sex, BMI, lipid-lowering drug therapy, and lipid levels), multifactorial logistic regression analysis revealed that a lower abundance of two ceramides, i.e., Cer(d18:0/22:0) and Cer(d18:0/24:0), was an independent risk factor for the occurrence of DR in T2DM patients. CONCLUSION Disturbances in lipid metabolism are closely associated with the occurrence of DR in patients with T2DM, especially in ceramides. Our study revealed for the first time that Cer(d18:0/22:0) and Cer(d18:0/24:0) might be potential serological markers for the diagnosis of DR occurrence in T2DM patients, providing new ideas for the early diagnosis of DR.
Collapse
Affiliation(s)
- Mingqian He
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Guixue Hou
- BGI-SHENZHEN, No. 21 Hongan 3rd Street, Yantian District, Shenzhen, Guangdong, 518083, P.R. China
| | - Mengmeng Liu
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Zhaoyi Peng
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Hui Guo
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Yue Wang
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Jing Sui
- Department of Endocrinology and International Medical Center, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Hui Liu
- Biobank, The First Affiliated Hospital of Xi'an JiaoTong University, Xi'an, Shaanxi, 710061, China
| | - Xiaoming Yin
- Chengdu HuiXin Life Technology, Chengdu, Sichuan, 610091, P.R. China
| | - Meng Zhang
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Ziyi Chen
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
| | - Patrick C N Rensen
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China
- Department of Medicine, Division of Endocrinology, Leiden University Medical Center, P.O. Box 9600, Leiden, 2300 RA, The Netherlands
| | - Liang Lin
- BGI-SHENZHEN, No. 21 Hongan 3rd Street, Yantian District, Shenzhen, Guangdong, 518083, P.R. China.
- , Building NO.7, BGI Park, No. 21 Hongan 3rd Street, Yantian District, Shenzhen, Guangdong, 518083, P.R. China.
| | - Yanan Wang
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China.
- Med-X institute, Center for Immunological and Metabolic Diseases, the First Affiliated Hospital of Xi'an JiaoTong University, Xi'an JiaoTong university, Xi'an, Shaanxi, 710061, P.R. China.
| | - Bingyin Shi
- Department of Endocrinology, the First Affiliated Hospital of Xi'an JiaoTong University, No.277, West Yanta Road, Xi'an, Shaanxi, 710061, P.R. China.
| |
Collapse
|
5
|
Mandal N, Stentz F, Asuzu PC, Nyenwe E, Wan J, Dagogo-Jack S. Plasma Sphingolipid Profile of Healthy Black and White Adults Differs Based on Their Parental History of Type 2 Diabetes. J Clin Endocrinol Metab 2024; 109:740-749. [PMID: 37804534 PMCID: PMC10876402 DOI: 10.1210/clinem/dgad595] [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: 07/16/2023] [Revised: 09/18/2023] [Accepted: 10/05/2023] [Indexed: 10/09/2023]
Abstract
CONTEXT Ceramides and sphingolipids have been linked to type 2 diabetes (T2D). The Ceramides and Sphingolipids as Predictors of Incident Dysglycemia (CASPID) study is designed to determine the association of plasma sphingolipids with the pathophysiology of human T2D. OBJECTIVE A comparison of plasma sphingolipids profiles in Black and White adults with (FH+) and without (FH-) family history of T2D. DESIGN We recruited 100 Black and White FH- (54 Black, 46 White) and 140 FH+ (75 Black, 65 White) adults. Fasting plasma levels of 58 sphingolipid species, including 18 each from 3 major classes (ceramides, monohexosylceramides, and sphingomyelins, all with 18:1 sphingoid base) and 4 long-chain sphingoid base-containing species, were measured by liquid chromatography/mass spectrometry. RESULTS Sphingomyelin was the most abundant sphingolipid in plasma (89% in FH-), and was significantly elevated in FH+ subjects (93%). Ceramides and monohexosylceramides comprised 5% and 6% of total sphingolipids in the plasma of FH- subjects, and were reduced significantly in FH+ subjects (3% and 4%, respectively). In FH+ subjects, most ceramide and monohexosylceramide species were decreased but sphingomyelin species were increased. The level of C18:1 species of all 3 classes was elevated in FH+ subjects. CONCLUSION Elevated levels of sphingomyelin, the major sphingolipids of plasma, and oleic acid-containing sphingolipids in healthy FH+ subjects compared with healthy FH- subjects may reflect heritable elements linking sphingolipids and the development of T2D.
Collapse
Affiliation(s)
- Nawajes Mandal
- Departments of Ophthalmology, Anatomy and Neurobiology, University of Tennessee Health Science Center, Memphis, TN 38163, USA
- Research, Memphis VA Medical Center, Memphis, TN 38104, USA
| | - Frankie Stentz
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Peace Chiamaka Asuzu
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Ebenezer Nyenwe
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Jim Wan
- Department of Preventive Medicine, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| | - Sam Dagogo-Jack
- Department of Medicine, Division of Endocrinology, Diabetes and Metabolism, University of Tennessee Health Science Center, Memphis, TN 38163, USA
- General Clinical Research Center, University of Tennessee Health Science Center, Memphis, TN 38163, USA
| |
Collapse
|
6
|
Carrard J, Angst T, Weber N, Bienvenue J, Infanger D, Streese L, Hinrichs T, Croci I, Schmied C, Gallart-Ayala H, Höchsmann C, Koehler K, Hanssen H, Ivanisevic J, Schmidt-Trucksäss A. Investigating the circulating sphingolipidome response to a single high-intensity interval training session within healthy females and males in their twenties (SphingoHIIT): Protocol for a randomised controlled trial. F1000Res 2023; 11:1565. [PMID: 37533665 PMCID: PMC10390797 DOI: 10.12688/f1000research.128978.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/15/2023] [Indexed: 08/04/2023] Open
Abstract
Introduction: Growing scientific evidence indicates that sphingolipids predict cardiometabolic risk, independently of and beyond traditional biomarkers such as low-density lipoprotein cholesterol. To date, it remains largely unknown if and how exercise, a simple, low-cost, and patient-empowering modality to optimise cardiometabolic health, influences sphingolipid levels. The SphingoHIIT study aims to assess the response of circulating sphingolipid species to a single session of high-intensity interval training (HIIT). Methods: This single-centre randomised controlled trial (RCT) will last 11 days per participant and aim to include 32 young and healthy individuals aged 20-29 (50% females). Participants will be randomly allocated to the HIIT (n= 16) or control groups (physical rest, n= 16). Participants will self-sample fasted dried blood spots for three consecutive days before the intervention (HIIT versus rest) to determine baseline sphingolipid levels. Dried blood spots will also be collected at five time points (2, 15, 30, 60min, and 24h) following the intervention (HIIT versus rest). To minimise the dietary influence, participants will receive a standardised diet for four days, starting 24 hours before the first dried blood sampling. For females, interventions will be timed to fall within the early follicular phase to minimise the menstrual cycle's influence on sphingolipid levels. Finally, physical activity will be monitored for the whole study duration using a wrist accelerometer. Ethics and dissemination: The Ethics Committee of Northwest and Central Switzerland approved this protocol (ID 2022-00513). Findings will be disseminated in scientific journals and meetings. Trial Registration The trial was registered on www.clinicaltrials.gov (NCT05390866, https://clinicaltrials.gov/ct2/show/NCT05390866) on May 25, 2022.
Collapse
Affiliation(s)
- Justin Carrard
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Thomas Angst
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Nadia Weber
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Joëlle Bienvenue
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Denis Infanger
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Lukas Streese
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Timo Hinrichs
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Ilaria Croci
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
- Cardiac Exercise Research Group, Department of Circulation and Medical Imaging, Norwegian University of Science and Technology, Trondheim, Norway
| | - Christian Schmied
- Sports Cardiology Section, Department of Cardiology, University Heart Center Zurich,, University Hospital Zurich, Zurich, 8091, Switzerland
| | - Hector Gallart-Ayala
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Lausanne, 1005, Switzerland
| | - Christoph Höchsmann
- Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Karsten Koehler
- Department of Sport and Health Sciences, Technical University of Munich, Munich, Germany
| | - Henner Hanssen
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| | - Julijana Ivanisevic
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Lausanne, 1005, Switzerland
| | - Arno Schmidt-Trucksäss
- Division of Sport and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Basel, 4052, Switzerland
| |
Collapse
|
7
|
Safari F, Kehelpannala C, Safarchi A, Batarseh AM, Vafaee F. Biomarker Reproducibility Challenge: A Review of Non-Nucleotide Biomarker Discovery Protocols from Body Fluids in Breast Cancer Diagnosis. Cancers (Basel) 2023; 15:2780. [PMID: 37345117 DOI: 10.3390/cancers15102780] [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: 02/24/2023] [Revised: 05/02/2023] [Accepted: 05/10/2023] [Indexed: 06/23/2023] Open
Abstract
Breast cancer has now become the most commonly diagnosed cancer, accounting for one in eight cancer diagnoses worldwide. Non-invasive diagnostic biomarkers and associated tests are superlative candidates to complement or improve current approaches for screening, early diagnosis, or prognosis of breast cancer. Biomarkers detected from body fluids such as blood (serum/plasma), urine, saliva, nipple aspiration fluid, and tears can detect breast cancer at its early stages in a minimally invasive way. The advancements in high-throughput molecular profiling (omics) technologies have opened an unprecedented opportunity for unbiased biomarker detection. However, the irreproducibility of biomarkers and discrepancies of reported markers have remained a major roadblock to clinical implementation, demanding the investigation of contributing factors and the development of standardised biomarker discovery pipelines. A typical biomarker discovery workflow includes pre-analytical, analytical, and post-analytical phases, from sample collection to model development. Variations introduced during these steps impact the data quality and the reproducibility of the findings. Here, we present a comprehensive review of methodological variations in biomarker discovery studies in breast cancer, with a focus on non-nucleotide biomarkers (i.e., proteins, lipids, and metabolites), highlighting the pre-analytical to post-analytical variables, which may affect the accurate identification of biomarkers from body fluids.
Collapse
Affiliation(s)
- Fatemeh Safari
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
| | - Cheka Kehelpannala
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Azadeh Safarchi
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- Microbiomes for One Systems Health, Health and Biosecurity, CSIRO, Westmead, NSW 2145, Australia
| | - Amani M Batarseh
- BCAL Diagnostics Ltd., Suite 506, 50 Clarence St, Sydney, NSW 2000, Australia
- BCAL Dx, The University of Sydney, Sydney Knowledge Hub, Merewether Building, Sydney, NSW 2006, Australia
| | - Fatemeh Vafaee
- School of Biotechnology and Biomolecular Sciences, University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- UNSW Data Science Hub (uDASH), University of New South Wales (UNSW Sydney), Sydney, NSW 2052, Australia
- OmniOmics.ai Pty Ltd., Sydney, NSW 2035, Australia
| |
Collapse
|
8
|
Shi C, Zi Y, Huang S, Chen J, Wang X, Zhong J. Development and application of lipidomics for food research. ADVANCES IN FOOD AND NUTRITION RESEARCH 2023; 104:1-42. [PMID: 37236729 DOI: 10.1016/bs.afnr.2022.10.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/28/2023]
Abstract
Lipidomics is an emerging and promising omics derived from metabolomics to comprehensively analyze all of lipid molecules in biological matrices. The purpose of this chapter is to introduce the development and application of lipidomics for food research. First, three aspects of sample preparation are introduced: food sampling, lipid extraction, and transportation and storage. Second, five types of instruments for data acquisition are summarized: direct infusion-mass spectrometry (MS), chromatographic separation-MS, ion mobility-MS, MS imaging, and nuclear magnetic resonance spectroscopy. Third, data acquisition and analysis software are described for the lipidomics software development. Fourth, the application of lipidomics for food research is discussed such as food origin and adulteration analysis, food processing research, food preservation research, and food nutrition and health research. All the contents suggest that lipidomics is a powerful tool for food research based on its ability of lipid component profile analysis.
Collapse
Affiliation(s)
- Cuiping Shi
- Xinhua Hospital, Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ye Zi
- Xinhua Hospital, Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai Jiao Tong University School of Medicine, Shanghai, China; National R&D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Integrated Scientific Research Base on Comprehensive Utilization Technology for By-Products of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, College of Food Science & Technology, Shanghai Ocean University, Shanghai, China
| | - Shudan Huang
- Xinhua Hospital, Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai Jiao Tong University School of Medicine, Shanghai, China; National R&D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Integrated Scientific Research Base on Comprehensive Utilization Technology for By-Products of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, College of Food Science & Technology, Shanghai Ocean University, Shanghai, China
| | - Jiahui Chen
- Xinhua Hospital, Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai Jiao Tong University School of Medicine, Shanghai, China; National R&D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Integrated Scientific Research Base on Comprehensive Utilization Technology for By-Products of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, College of Food Science & Technology, Shanghai Ocean University, Shanghai, China
| | - Xichang Wang
- National R&D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Integrated Scientific Research Base on Comprehensive Utilization Technology for By-Products of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, College of Food Science & Technology, Shanghai Ocean University, Shanghai, China
| | - Jian Zhong
- Xinhua Hospital, Shanghai Institute for Pediatric Research, Shanghai Key Laboratory of Pediatric Gastroenterology and Nutrition, Shanghai Jiao Tong University School of Medicine, Shanghai, China; National R&D Branch Center for Freshwater Aquatic Products Processing Technology (Shanghai), Integrated Scientific Research Base on Comprehensive Utilization Technology for By-Products of Aquatic Product Processing, Ministry of Agriculture and Rural Affairs of the People's Republic of China, Shanghai Engineering Research Center of Aquatic-Product Processing and Preservation, College of Food Science & Technology, Shanghai Ocean University, Shanghai, China.
| |
Collapse
|
9
|
Pistritu DV, Vasiliniuc AC, Vasiliu A, Visinescu EF, Visoiu IE, Vizdei S, Martínez Anghel P, Tanca A, Bucur O, Liehn EA. Phospholipids, the Masters in the Shadows during Healing after Acute Myocardial Infarction. Int J Mol Sci 2023; 24:ijms24098360. [PMID: 37176067 PMCID: PMC10178977 DOI: 10.3390/ijms24098360] [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: 04/03/2023] [Revised: 05/02/2023] [Accepted: 05/03/2023] [Indexed: 05/15/2023] Open
Abstract
Phospholipids are major components of cell membranes with complex structures, high heterogeneity and critical biological functions and have been used since ancient times to treat cardiovascular disease. Their importance and role were shadowed by the difficulty or incomplete available research methodology to study their biological presence and functionality. This review focuses on the current knowledge about the roles of phospholipids in the pathophysiology and therapy of cardiovascular diseases, which have been increasingly recognized. Used in singular formulation or in inclusive combinations with current drugs, phospholipids proved their positive and valuable effects not only in the protection of myocardial tissue, inflammation and fibrosis but also in angiogenesis, coagulation or cardiac regeneration more frequently in animal models as well as in human pathology. Thus, while mainly neglected by the scientific community, phospholipids present negligible side effects and could represent an ideal target for future therapeutic strategies in healing myocardial infarction. Acknowledging and understanding their mechanisms of action could offer a new perspective into novel therapeutic strategies for patients suffering an acute myocardial infarction, reducing the burden and improving the general social and economic outcome.
Collapse
Affiliation(s)
- Dan-Valentin Pistritu
- Victor Babes' National Institute of Pathology, 99-101 Splaiul Independentei, 050096 Bucharest, Romania
| | | | - Anda Vasiliu
- Victor Babes' National Institute of Pathology, 99-101 Splaiul Independentei, 050096 Bucharest, Romania
| | - Elena-Florentina Visinescu
- Faculty of Human Medicine, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
| | - Ioana-Elena Visoiu
- Faculty of Human Medicine, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
| | - Smaranda Vizdei
- Faculty of Human Medicine, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
| | - Paula Martínez Anghel
- Victor Babes' National Institute of Pathology, 99-101 Splaiul Independentei, 050096 Bucharest, Romania
- Business Academy Aarhus, 30 Sønderhøj, 8260 Viby J, Denmark
| | - Antoanela Tanca
- Victor Babes' National Institute of Pathology, 99-101 Splaiul Independentei, 050096 Bucharest, Romania
- Faculty of Human Medicine, Carol Davila University of Medicine and Pharmacy, 37 Dionisie Lupu Street, 020021 Bucharest, Romania
| | - Octavian Bucur
- Victor Babes' National Institute of Pathology, 99-101 Splaiul Independentei, 050096 Bucharest, Romania
- Viron Molecular Medicine Institute, 201 Washington Street, Boston, MA 02108, USA
| | - Elisa Anamaria Liehn
- Victor Babes' National Institute of Pathology, 99-101 Splaiul Independentei, 050096 Bucharest, Romania
- Institute for Molecular Medicine, University of Southern Denmark, 25 J.B Winsløws Vej, 5230 Odense, Denmark
- National Heart Center Singapore, 5 Hospital Dr., Singapore 169609, Singapore
| |
Collapse
|
10
|
Julve J, Genua I, Quifer-Rada P, Yanes Ó, Barranco-Altirriba M, Hernández M, Junza A, Capellades J, Granado-Casas M, Alonso N, Castelblanco E, Mauricio D. Circulating metabolomic and lipidomic changes in subjects with new-onset type 1 diabetes after optimization of glycemic control. Diabetes Res Clin Pract 2023; 197:110578. [PMID: 36804334 DOI: 10.1016/j.diabres.2023.110578] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2022] [Revised: 02/08/2023] [Accepted: 02/10/2023] [Indexed: 02/18/2023]
Abstract
AIMS To uncover novel candidate metabolomic and lipidomic biomarkers in newly-diagnosed type 1 diabetes (T1DM) after achieving optimal glucose control. METHODS Comprehensive lipidomic and metabolomic analysis was performed in serum of 12 adults with T1DM at onset and after achieving optimal glycemic control (HbA1c < 7 %) (after 2-6 months). RESULTS After intensive therapy, subjects (mean age 25.2 years, 58.3 % men) showed decreases in blood glucose (p < 0.001), HbA1c [11.5 % (9.2-13.4) to 6.2 % (5.2 - 6.7); p < 0.001] and changes in 51 identified lipids. Among these changes, we found that triglycerides (TG) containing medium chain fatty acids (TG45:0, TG47:1), sphingomyelins (SM) (SM(d18:2/20:0), SM42:4)), and phosphatidylcholines (PC) (PC(O-26:2), PC(O-30:0), PC(O-32:0), PC(O-42:6), PC(O-44:5), PC(O-38:3), PC(O-33:0), PC(O-46:8), PC(O-44:6), PC(O-40:3), PC(O-42:4), PC(O-46:7), PC(O-46:6), PC(O-44:5), PC(O-42:3), PC(O-44:4)) decreased; whereas PC(35:1), PC(37:1) and TG containing longer chain fatty acids (TG(52:1), TG(55:7), TG(51:2), TG(53:3), TG52:2), TG(53:2), TG(57:3), TG(61:3), TG(61:2) increased. Further, dihydro O-acylceramide (18:1/18:0/16:0), diacylglycerophosphoethanolamine (PE(34:1)), diacylglycerophosphoinositol (PI(38:6), and dihydrosphingomyelins (dihydroSM(36:0), dihydroSM(40:0), dihydroSM(41:0), dihydroSM(42:0)) increased. Uric acid, mannitol, and mannitol-1-acetate levels also increased. CONCLUSIONS Our data uncovered potential favorable changes in the metabolism of glycerophospholipids, glycerolipids, and sphingolipids in new-onset T1DM after achieving optimal glycemic control. Further research on their potential role in developing diabetes-related complications is needed.
Collapse
Affiliation(s)
- Josep Julve
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), 08041 Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain
| | - Idoia Genua
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), 08041 Barcelona, Spain; Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain
| | - Paola Quifer-Rada
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain; LactApp Women's Health, Barcelona, Spain
| | - Óscar Yanes
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain; Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain
| | - Maria Barranco-Altirriba
- Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; B2SLab, Departament d'Enginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Barcelona, Spain; Networking Biomedical Research Centre in the Subject Area of Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain; Institut de Recerca Sant Joan de Déu, Esplugues de Llobregat, Barcelona, Spain
| | - Marta Hernández
- Department of Endocrinology & Nutrition, University Hospital Arnau de Vilanova, Lleida, Spain; Lleida Institute for Biomedical Research Dr. Pifarré Foundation (IRBLleida), University of Lleida, 25198 Lleida, Spain
| | - Alexandra Junza
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain; Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain
| | - Jordi Capellades
- Universitat Rovira i Virgili, Department of Electronic Engineering & IISPV, Tarragona, Spain
| | - Minerva Granado-Casas
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain; Lleida Institute for Biomedical Research Dr. Pifarré Foundation (IRBLleida), University of Lleida, 25198 Lleida, Spain
| | - Núria Alonso
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain; Department of Medicine, Autonomous University of Barcelona, Barcelona, Spain; Department of Endocrinology & Nutrition, University Hospital Germans Trias i Pujol, 08916 Badalona, Spain
| | - Esmeralda Castelblanco
- Endocrinology, Metabolism and Lipid Research Division, Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO 63110, USA; Unitat de Suport a la Recerca Barcelona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol i Gurina (IDIAP Jordi Gol), 08007 Barcelona, Spain.
| | - Didac Mauricio
- Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), 08041 Barcelona, Spain; CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Barcelona, Spain; Department of Endocrinology & Nutrition, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Unitat de Suport a la Recerca Barcelona, Institut Universitari d'Investigació en Atenció Primària Jordi Gol i Gurina (IDIAP Jordi Gol), 08007 Barcelona, Spain; Department of Medicine, University of Vic - Central University of Catalonia, Vic, Spain.
| |
Collapse
|
11
|
Nutritional lipidomics for the characterization of lipids in food. ADVANCES IN FOOD AND NUTRITION RESEARCH 2023. [PMID: 37516469 DOI: 10.1016/bs.afnr.2022.12.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Lipids represent one out of three major macronutrient classes in the human diet. It is estimated to account for about 15-20% of the total dietary intake. Triacylglycerides comprise the majority of them, estimated 90-95%. Other lipid classes include free fatty acids, phospholipids, cholesterol, and plant sterols as minor components. Various methods are used for the characterization of nutritional lipids, however, lipidomics approaches become increasingly attractive for this purpose due to their wide coverage, comprehensiveness and holistic view on composition. In this chapter, analytical methodologies and workflows utilized for lipidomics profiling of food samples are outlined with focus on mass spectrometry-based assays. The chapter describes common lipid extraction protocols, the distinct instrumental mass-spectrometry based analytical platforms for data acquisition, chromatographic and ion-mobility spectrometry methods for lipid separation, briefly mentions alternative methods such as gas chromatography for fatty acid profiling and mass spectrometry imaging. Critical issues of important steps of lipidomics workflows such as structural annotation and identification, quantification and quality assurance are discussed as well. Applications reported over the period of the last 5years are summarized covering the discovery of new lipids in foodstuff, differential profiling approaches for comparing samples from different origin, species, varieties, cultivars and breeds, and for food processing quality control. Lipidomics as a powerful tool for personalized nutrition and nutritional intervention studies is briefly discussed as well. It is expected that this field is significantly growing in the near future and this chapter gives a short insight into the power of nutritional lipidomics approaches.
Collapse
|
12
|
Segrado F, Cavalleri A, Cantalupi A, Mariani L, Dagnino S, Krogh V, Venturelli E, Agnoli C. A software-assisted untargeted liquid chromatography-mass spectrometry method for lipidomic profiling of human plasma samples. Int J Biol Markers 2022; 37:368-376. [PMID: 36310449 DOI: 10.1177/03936155221132291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
INTRODUCTION In this paper, an analytical pipeline designed for untargeted lipidomic profiling in human plasma is proposed. The analytical pipeline was developed for case-control studies nested in prospective cohorts. METHODS The procedure consisted of isopropanol protein precipitation followed by reverse phase liquid chromatography coupled to high resolution mass spectrometry and software-assisted data processing. The compounds are putatively annotated by matching experimental mass spectrometry data with spectral library data using LipidSearch software. The lipid profile of a pool of plasma samples from 10 healthy volunteers was detected in both positive and negative polarity modes. The impact of the chosen polarity on the number and quality of the lipid identification has been evaluated. RESULTS More than 1000 lipids from 12 different classes were detected, 1150 in positive mode and 273 in negative mode. Nearly half of them were unambiguously identified by the software in positive mode, and about one-third in negative mode. The method repeatability was assessed on the plasma pool samples by means of variance components analysis. The intra- and inter-assay precision was measured for 10 lipids chosen among the most abundant found within the different lipid classes. The intra-assay coefficients of variation ranged from 2.56% to 4.56% while intra- and inter-day coefficients of variance never exceeded the 15% benchmark adopted. The lipidomic profiles of the 10 healthy volunteers were also investigated. DISCUSSION This method detects a wide range of lipids and reports their degree of identification. It is particularly fit and well-designed for large case-control epidemiologic studies.
Collapse
Affiliation(s)
- Francesco Segrado
- Epidemiology and Prevention Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Adalberto Cavalleri
- Epidemiology and Prevention Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Alice Cantalupi
- Epidemiology and Prevention Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy.,Laboratorio Chimica, Mercelogia e Biologia Molecolare, Centro Ricerche sul Riso, Ente Nazionale Risi, Castello d'Agogna, Italy
| | - Luigi Mariani
- Clinical Epidemiology and Trial Organization Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Sonia Dagnino
- MRC Centre for Environment and Health, School of Public Health, 4615Imperial College London, London, UK
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Elisabetta Venturelli
- Epidemiology and Prevention Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Claudia Agnoli
- Epidemiology and Prevention Unit, 9329Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| |
Collapse
|
13
|
Sun J, Wang Z, Yang C. Ion Mobility Mass Spectrometry Development and Applications. Crit Rev Anal Chem 2022:1-8. [PMID: 36325979 DOI: 10.1080/10408347.2022.2139589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Although as an analytical method with high specificity and high sensitivity, mass spectrometry (MS) has a wide range of applications in many fields, it still needs other technologies as the assist and supplement to enhance the scope and capability of analysis. Coupling with ion mobility (IM) can make an enhancement effect in the field of pharmaceutical analysis as a supplementary method. The two-dimensional mass technology improves the confidence of compounds annotations while increasing peak capacity, with the gradual deepening of theoretical research on IM-MS, it has shown unique advantages in the complex analysis conditions. IM-MS owns great potential for improving the depth, range, dimension of in-depth drug research. In this review, the principle, instruments and methods, applications, advantages and limitations of IM-MS are described. Here, we also elaborate on the prospects in structural evaluation, separation, and identification of complex compounds for the drug discovery and development phase and the great advantages of macromolecules and omics.
Collapse
Affiliation(s)
- Jiahui Sun
- Department of Pharmaceutical Analysis and Analytical Chemistry, College of Pharmacy, Harbin Medical University, Harbin, China
| | - Zhibin Wang
- Key Laboratory of Chinese Materia Medica (Ministry of Education), Heilongjiang University of Chinese Medicine, Harbin, China
| | - Chunjuan Yang
- Department of Pharmaceutical Analysis and Analytical Chemistry, College of Pharmacy, Harbin Medical University, Harbin, China
| |
Collapse
|
14
|
Lipidomics in Understanding Pathophysiology and Pharmacologic Effects in Inflammatory Diseases: Considerations for Drug Development. Metabolites 2022; 12:metabo12040333. [PMID: 35448520 PMCID: PMC9030008 DOI: 10.3390/metabo12040333] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2022] [Revised: 03/29/2022] [Accepted: 04/04/2022] [Indexed: 01/26/2023] Open
Abstract
The lipidome has a broad range of biological and signaling functions, including serving as a structural scaffold for membranes and initiating and resolving inflammation. To investigate the biological activity of phospholipids and their bioactive metabolites, precise analytical techniques are necessary to identify specific lipids and quantify their levels. Simultaneous quantification of a set of lipids can be achieved using high sensitivity mass spectrometry (MS) techniques, whose technological advancements have significantly improved over the last decade. This has unlocked the power of metabolomics/lipidomics allowing the dynamic characterization of metabolic systems. Lipidomics is a subset of metabolomics for multianalyte identification and quantification of endogenous lipids and their metabolites. Lipidomics-based technology has the potential to drive novel biomarker discovery and therapeutic development programs; however, appropriate standards have not been established for the field. Standardization would improve lipidomic analyses and accelerate the development of innovative therapies. This review aims to summarize considerations for lipidomic study designs including instrumentation, sample stabilization, data validation, and data analysis. In addition, this review highlights how lipidomics can be applied to biomarker discovery and drug mechanism dissection in various inflammatory diseases including cardiovascular disease, neurodegeneration, lung disease, and autoimmune disease.
Collapse
|
15
|
Berkowitz L, Cabrera-Reyes F, Salazar C, Ryff CD, Coe C, Rigotti A. Sphingolipid Profiling: A Promising Tool for Stratifying the Metabolic Syndrome-Associated Risk. Front Cardiovasc Med 2022; 8:785124. [PMID: 35097004 PMCID: PMC8795367 DOI: 10.3389/fcvm.2021.785124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 12/21/2021] [Indexed: 11/24/2022] Open
Abstract
Metabolic syndrome (MetS) is a multicomponent risk condition that reflects the clustering of individual cardiometabolic risk factors related to abdominal obesity and insulin resistance. MetS increases the risk for cardiovascular diseases (CVD) and type 2 diabetes mellitus (T2DM). However, there still is not total clinical consensus about the definition of MetS, and its pathophysiology seems to be heterogeneous. Moreover, it remains unclear whether MetS is a single syndrome or a set of diverse clinical conditions conferring different metabolic and cardiovascular risks. Indeed, traditional biomarkers alone do not explain well such heterogeneity or the risk of associated diseases. There is thus a need to identify additional biomarkers that may contribute to a better understanding of MetS, along with more accurate prognosis of its various chronic disease risks. To fulfill this need, omics technologies may offer new insights into associations between sphingolipids and cardiometabolic diseases. Particularly, ceramides –the most widely studied sphingolipid class– have been shown to play a causative role in both T2DM and CVD. However, the involvement of simple glycosphingolipids remains controversial. This review focuses on the current understanding of MetS heterogeneity and discuss recent findings to address how sphingolipid profiling can be applied to better characterize MetS-associated risks.
Collapse
Affiliation(s)
- Loni Berkowitz
- Department of Nutrition, Diabetes and Metabolism & Center of Molecular Nutrition and Chronic Diseases, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- *Correspondence: Loni Berkowitz
| | - Fernanda Cabrera-Reyes
- Department of Gastroenterology, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Cristian Salazar
- Department of Nutrition, Diabetes and Metabolism & Center of Molecular Nutrition and Chronic Diseases, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Carol D. Ryff
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Christopher Coe
- Institute on Aging, University of Wisconsin-Madison, Madison, WI, United States
| | - Attilio Rigotti
- Department of Nutrition, Diabetes and Metabolism & Center of Molecular Nutrition and Chronic Diseases, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| |
Collapse
|
16
|
Gao Y, Li J, Fan S, Chen P, Huang M, Bi H. Lipid Analysis of Follicular Fluids by UHPLC-ESI-HRMS Discovers Potential Biomarkers for Ovarian Hyperstimulation Syndrome. Front Endocrinol (Lausanne) 2022; 13:895116. [PMID: 35846297 PMCID: PMC9276923 DOI: 10.3389/fendo.2022.895116] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Accepted: 05/12/2022] [Indexed: 11/29/2022] Open
Abstract
Ovarian hyperstimulation syndrome (OHSS) is a serious iatrogenic complication during ovarian stimulation. Even though the incidence of OHSS was relatively low in clinical practice, the consequence can be potentially devastating and life-threatening. Abnormal lipid metabolism may relate to the pathological development of OHSS, but there is still a research gap in the lipidomic research. So here in our study, an ultra-high-performance liquid chromatography coupled with electrospray ionization high-resolution mass spectrometry (UHPLC-ESI-HRMS) based lipidomic analysis was performed using follicular fluid samples obtained from 17 patients undergoing OHSS. The lipid profiles of OHSS patients were characterized by increased cholesterol ester (ChE) and decreased lysophosphatidylcholine (LPC), phosphatidylinositol (PI), sphingomyelin (SM), dimethylphosphatidylethanolamine (dMePE) and lysodimethylphosphatidylethanolamine (LdMePE). Totally 10 lipids including LPC(18:0), SM(d18:1/16:0), PC(18:0/18:1), PC(20:2/20:5), PC(16:0/18:1), TG(16:0/18:1/18:1), TG(16:0/18:2/18:2), TG(16:0/16:1/18:1), ChE(20:4) and TG(8:0/8:0/10:0) were selected as differential lipids. In conclusion, this study demonstrated the alteration of various lipids in OHSS patients, which suggested the key role of lipids during the development of OHSS and shed light on the further pathophysiological research of OHSS.
Collapse
Affiliation(s)
- Yue Gao
- Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Jingjie Li
- Center of Reproductive Medicine, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Shicheng Fan
- Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Pan Chen
- Pharmacy Department, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Min Huang
- Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
| | - Huichang Bi
- Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou, China
- School of Pharmaceutical Sciences, Southern Medical University, Guangzhou, China
- *Correspondence: Huichang Bi, ;
| |
Collapse
|
17
|
Meikle TG, Huynh K, Giles C, Meikle PJ. Clinical lipidomics: realizing the potential of lipid profiling. J Lipid Res 2021; 62:100127. [PMID: 34582882 PMCID: PMC8528718 DOI: 10.1016/j.jlr.2021.100127] [Citation(s) in RCA: 53] [Impact Index Per Article: 17.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 09/18/2021] [Accepted: 09/21/2021] [Indexed: 11/17/2022] Open
Abstract
Dysregulation of lipid metabolism plays a major role in the etiology and sequelae of inflammatory disorders, cardiometabolic and neurological diseases, and several forms of cancer. Recent advances in lipidomic methodology allow comprehensive lipidomic profiling of clinically relevant biological samples, enabling researchers to associate lipid species and metabolic pathways with disease onset and progression. The resulting data serve not only to advance our fundamental knowledge of the underlying disease process but also to develop risk assessment models to assist in the diagnosis and management of disease. Currently, clinical applications of in-depth lipidomic profiling are largely limited to the use of research-based protocols in the analysis of population or clinical sample sets. However, we foresee the development of purpose-built clinical platforms designed for continuous operation and clinical integration-assisting health care providers with disease risk assessment, diagnosis, and monitoring. Herein, we review the current state of clinical lipidomics, including the use of research-based techniques and platforms in the analysis of clinical samples as well as assays already available to clinicians. With a primary focus on MS-based strategies, we examine instrumentation, analysis techniques, statistical models, prospective design of clinical platforms, and the possible pathways toward implementation of clinical lipidomics.
Collapse
Affiliation(s)
- Thomas G Meikle
- Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Kevin Huynh
- Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, Victoria, Australia
| | - Corey Giles
- Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, Victoria, Australia
| | - Peter J Meikle
- Metabolomics Laboratory, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia; Baker Department of Cardiometabolic Health, University of Melbourne, Parkville, Victoria, Australia; Faculty of Medicine, Nursing and Health Sciences, Central Clinical School, Monash University, Melbourne, Victoria, Australia.
| |
Collapse
|
18
|
Cebo M, Calderón Castro C, Schlotterbeck J, Gawaz M, Chatterjee M, Lämmerhofer M. Untargeted UHPLC-ESI-QTOF-MS/MS analysis with targeted feature extraction at precursor and fragment level for profiling of the platelet lipidome with ex vivo thrombin-activation. J Pharm Biomed Anal 2021; 205:114301. [PMID: 34391135 DOI: 10.1016/j.jpba.2021.114301] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Revised: 07/28/2021] [Accepted: 07/30/2021] [Indexed: 01/17/2023]
Abstract
Lipids play a major role in platelet signaling and activation. In this study, we analyzed the platelet lipidome in an untargeted manner by reversed-phase UHPLC for lipid species separation coupled to high-resolution QTOF-MS/MS in data-independent acquisition (DIA) mode with sequential window acquisition of all theoretical fragment ion mass spectra (SWATH) for compound detection. Lipid identification and peak picking was supported by the characteristic regular elution pattern of lipids differing in carbon and double bond numbers. It was primarily based on post-acquisition targeted feature extraction from the SWATH data. Multiple extracted ion chromatograms (EICs) from SWATH data of diagnostic ions on MS1 and MS2 level from both positive and negative ion mode allowed to distinguish between poorly resolved isomeric lipids based on their distinct fragment ions, which were used for relative quantification at a molecular lipid species level. It supports assay specificity for relative lipid quantitation via multiple quantifiably ions unlike to data-dependent acquisition methods which rely on precursor ions only. This approach was used to analyze human platelet samples. 457 lipids were annotated. Concentrations of lipids were estimated by stable isotope-labelled lipid class-specific internal standards as surrogate calibrants. Heatmaps of lipid concentrations in dependence on carbon and double bond numbers for the distinct lipid classes revealed a snapshot of the platelet lipidome in the resting state with lipid species distributions within classes supporting some functional interpretations. As expected, activation of the platelets by thrombin has led to significant alterations in the platelet lipidome as proven by univariate (volcano plot) and multivariate (PLS-DA) statistics. Several lipids were significantly up-regulated (lysophosphatidylinositols, oxylipins such as thromboxane B2 (TXB2), hydroxyheptadecatrienoic acid (HHT), hydroxyeicosatetraenoic acid (HETE), hydroxyoctadecadienoic acid (HODE), sphingoid-bases, (very) long chain saturated fatty acids) or down-regulated (lysophosphatidylethanolamines, polyunsaturated fatty acids, phosphatidylinositols). Several of them are well known as biomarkers of platelet activation while others may provide some further insights into pathways of platelet activation and platelet metabolism.
Collapse
Affiliation(s)
- Malgorzata Cebo
- University of Tübingen, Institute of Pharmaceutical Sciences, Pharmaceutical (Bio)Analysis, Auf der Morgenstelle 8, 72076, Tübingen, Germany
| | | | - Jörg Schlotterbeck
- University of Tübingen, Institute of Pharmaceutical Sciences, Pharmaceutical (Bio)Analysis, Auf der Morgenstelle 8, 72076, Tübingen, Germany
| | - Meinrad Gawaz
- Department of Cardiology and Angiology, University Hospital Tübingen, Otfried-Müller-Strasse 10, 72076, Tübingen, Germany
| | - Madhumita Chatterjee
- Department of Cardiology and Angiology, University Hospital Tübingen, Otfried-Müller-Strasse 10, 72076, Tübingen, Germany
| | - Michael Lämmerhofer
- University of Tübingen, Institute of Pharmaceutical Sciences, Pharmaceutical (Bio)Analysis, Auf der Morgenstelle 8, 72076, Tübingen, Germany.
| |
Collapse
|
19
|
Carrard J, Gallart-Ayala H, Infanger D, Teav T, Wagner J, Knaier R, Colledge F, Streese L, Königstein K, Hinrichs T, Hanssen H, Ivanisevic J, Schmidt-Trucksäss A. Metabolic View on Human Healthspan: A Lipidome-Wide Association Study. Metabolites 2021; 11:metabo11050287. [PMID: 33946321 PMCID: PMC8146132 DOI: 10.3390/metabo11050287] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Revised: 04/23/2021] [Accepted: 04/28/2021] [Indexed: 12/22/2022] Open
Abstract
As ageing is a major risk factor for the development of non-communicable diseases, extending healthspan has become a medical and societal necessity. Precise lipid phenotyping that captures metabolic individuality could support healthspan extension strategies. This study applied ‘omic-scale lipid profiling to characterise sex-specific age-related differences in the serum lipidome composition of healthy humans. A subset of the COmPLETE-Health study, composed of 73 young (25.2 ± 2.6 years, 43% female) and 77 aged (73.5 ± 2.3 years, 48% female) clinically healthy individuals, was investigated, using an untargeted liquid chromatography high-resolution mass spectrometry approach. Compared to their younger counterparts, aged females and males exhibited significant higher levels in 138 and 107 lipid species representing 15 and 13 distinct subclasses, respectively. Percentage of difference ranged from 5.8% to 61.7% (females) and from 5.3% to 46.0% (males), with sphingolipid and glycerophophospholipid species displaying the greatest amplitudes. Remarkably, specific sphingolipid and glycerophospholipid species, previously described as cardiometabolically favourable, were found elevated in aged individuals. Furthermore, specific ether-glycerophospholipid and lyso-glycerophosphocholine species displayed higher levels in aged females only, revealing a more favourable lipidome evolution in females. Altogether, age determined the circulating lipidome composition, while lipid species analysis revealed additional findings that were not observed at the subclass level.
Collapse
Affiliation(s)
- Justin Carrard
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Hector Gallart-Ayala
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, CH-1005 Lausanne, Switzerland; (H.G.-A.); (T.T.)
| | - Denis Infanger
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Tony Teav
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, CH-1005 Lausanne, Switzerland; (H.G.-A.); (T.T.)
| | - Jonathan Wagner
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Raphael Knaier
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Flora Colledge
- Division of Sports Science, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland;
| | - Lukas Streese
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Karsten Königstein
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Timo Hinrichs
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Henner Hanssen
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
| | - Julijana Ivanisevic
- Metabolomics Platform, Faculty of Biology and Medicine, University of Lausanne, Quartier UNIL-CHUV, Rue du Bugnon 19, CH-1005 Lausanne, Switzerland; (H.G.-A.); (T.T.)
- Correspondence: (J.I.); (A.S.-T.)
| | - Arno Schmidt-Trucksäss
- Division of Sports and Exercise Medicine, Department of Sport, Exercise and Health, University of Basel, Birsstrasse 320B, CH-4052 Basel, Switzerland; (J.C.); (D.I.); (J.W.); (R.K.); (L.S.); (K.K.); (T.H.); (H.H.)
- Correspondence: (J.I.); (A.S.-T.)
| |
Collapse
|
20
|
Coupling Machine Learning and Lipidomics as a Tool to Investigate Metabolic Dysfunction-Associated Fatty Liver Disease. A General Overview. Biomolecules 2021; 11:biom11030473. [PMID: 33810079 PMCID: PMC8004861 DOI: 10.3390/biom11030473] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/08/2021] [Accepted: 03/18/2021] [Indexed: 12/15/2022] Open
Abstract
Hepatic biopsy is the gold standard for staging nonalcoholic fatty liver disease (NAFLD). Unfortunately, accessing the liver is invasive, requires a multidisciplinary team and is too expensive to be conducted on large segments of the population. NAFLD starts quietly and can progress until liver damage is irreversible. Given this complex situation, the search for noninvasive alternatives is clinically important. A hallmark of NAFLD progression is the dysregulation in lipid metabolism. In this context, recent advances in the area of machine learning have increased the interest in evaluating whether multi-omics data analysis performed on peripheral blood can enhance human interpretation. In the present review, we show how the use of machine learning can identify sets of lipids as predictive biomarkers of NAFLD progression. This approach could potentially help clinicians to improve the diagnosis accuracy and predict the future risk of the disease. While NAFLD has no effective treatment yet, the key to slowing the progression of the disease may lie in predictive robust biomarkers. Hence, to detect this disease as soon as possible, the use of computational science can help us to make a more accurate and reliable diagnosis. We aimed to provide a general overview for all readers interested in implementing these methods.
Collapse
|
21
|
Hyötyläinen T. Analytical challenges in human exposome analysis with focus on environmental analysis combined with metabolomics. J Sep Sci 2021; 44:1769-1787. [PMID: 33650238 DOI: 10.1002/jssc.202001263] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 02/23/2021] [Accepted: 02/23/2021] [Indexed: 12/19/2022]
Abstract
Environmental factors, such as chemical exposures, are likely to play a crucial role in the development of several human chronic diseases. However, how the specific exposures contribute to the onset and progress of various diseases is still poorly understood. In part, this is because comprehensive characterization of the chemical exposome is a highly challenging task, both due to its complex dynamic nature as well as due to the analytical challenges. Herein, the analytical challenges in the field of exposome research are reviewed, with specific emphasis on the sampling, sample preparation, and analysis, as well as challenges in the compound identification. The primary focus is on the human chemical exposome, that is, exposures to mixtures of environmental chemicals and its impact on human metabolome. In order to highlight the recent progress in the exposome research in relation to human health and disease, selected examples of human exposome studies are presented.
Collapse
Affiliation(s)
- Tuulia Hyötyläinen
- MTM Research Centre, School of Science and Technology, Örebro University, Örebro, Sweden
| |
Collapse
|
22
|
Zardini Buzatto A, Kwon BK, Li L. Development of a NanoLC-MS workflow for high-sensitivity global lipidomic analysis. Anal Chim Acta 2020; 1139:88-99. [DOI: 10.1016/j.aca.2020.09.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2020] [Revised: 08/29/2020] [Accepted: 09/01/2020] [Indexed: 12/17/2022]
|
23
|
Orešič M, McGlinchey A, Wheelock CE, Hyötyläinen T. Metabolic Signatures of the Exposome-Quantifying the Impact of Exposure to Environmental Chemicals on Human Health. Metabolites 2020; 10:metabo10110454. [PMID: 33182712 PMCID: PMC7698239 DOI: 10.3390/metabo10110454] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 11/08/2020] [Accepted: 11/09/2020] [Indexed: 02/06/2023] Open
Abstract
Human health and well-being are intricately linked to environmental quality. Environmental exposures can have lifelong consequences. In particular, exposures during the vulnerable fetal or early development period can affect structure, physiology and metabolism, causing potential adverse, often permanent, health effects at any point in life. External exposures, such as the “chemical exposome” (exposures to environmental chemicals), affect the host’s metabolism and immune system, which, in turn, mediate the risk of various diseases. Linking such exposures to adverse outcomes, via intermediate phenotypes such as the metabolome, is one of the central themes of exposome research. Much progress has been made in this line of research, including addressing some key challenges such as analytical coverage of the exposome and metabolome, as well as the integration of heterogeneous, multi-omics data. There is strong evidence that chemical exposures have a marked impact on the metabolome, associating with specific disease risks. Herein, we review recent progress in the field of exposome research as related to human health as well as selected metabolic and autoimmune diseases, with specific emphasis on the impacts of chemical exposures on the host metabolome.
Collapse
Affiliation(s)
- Matej Orešič
- School of Medical Sciences, Örebro University, SE-701 82 Örebro, Sweden; (M.O.); (A.M.)
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, FI-20520 Turku, Finland
| | - Aidan McGlinchey
- School of Medical Sciences, Örebro University, SE-701 82 Örebro, Sweden; (M.O.); (A.M.)
| | - Craig E. Wheelock
- Division of Physiological Chemistry II, Department of Medical Biochemistry and Biophysics, Karolinska Institute, SE-171 77 Stockholm, Sweden;
| | - Tuulia Hyötyläinen
- MTM Research Centre, School of Science and Technology, Örebro University, SE-701 82 Örebro, Sweden
- Correspondence:
| |
Collapse
|
24
|
Zhu Y, Wancewicz B, Schaid M, Tiambeng TN, Wenger K, Jin Y, Heyman H, Thompson CJ, Barsch A, Cox ED, Davis DB, Brasier AR, Kimple ME, Ge Y. Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research. J Proteome Res 2020; 20:463-473. [PMID: 33054244 DOI: 10.1021/acs.jproteome.0c00510] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.
Collapse
Affiliation(s)
- Yanlong Zhu
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Benjamin Wancewicz
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Michael Schaid
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Research Service, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 53705, United States
| | - Timothy N Tiambeng
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Kent Wenger
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Yutong Jin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Heino Heyman
- Bruker Daltonics Inc., Billerica, Massachusetts 01821, United States
| | | | | | - Elizabeth D Cox
- Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin 53792, United States
| | - Dawn B Davis
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Research Service, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 53705, United States
| | - Allan R Brasier
- Institute for Clinical and Translational Research, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Michelle E Kimple
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Research Service, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 53705, United States
| | - Ying Ge
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| |
Collapse
|
25
|
Sen P, Lamichhane S, Mathema VB, McGlinchey A, Dickens AM, Khoomrung S, Orešič M. Deep learning meets metabolomics: a methodological perspective. Brief Bioinform 2020; 22:1531-1542. [PMID: 32940335 DOI: 10.1093/bib/bbaa204] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 08/08/2020] [Accepted: 08/10/2020] [Indexed: 12/15/2022] Open
Abstract
Deep learning (DL), an emerging area of investigation in the fields of machine learning and artificial intelligence, has markedly advanced over the past years. DL techniques are being applied to assist medical professionals and researchers in improving clinical diagnosis, disease prediction and drug discovery. It is expected that DL will help to provide actionable knowledge from a variety of 'big data', including metabolomics data. In this review, we discuss the applicability of DL to metabolomics, while presenting and discussing several examples from recent research. We emphasize the use of DL in tackling bottlenecks in metabolomics data acquisition, processing, metabolite identification, as well as in metabolic phenotyping and biomarker discovery. Finally, we discuss how DL is used in genome-scale metabolic modelling and in interpretation of metabolomics data. The DL-based approaches discussed here may assist computational biologists with the integration, prediction and drawing of statistical inference about biological outcomes, based on metabolomics data.
Collapse
Affiliation(s)
- Partho Sen
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520 Turku, Finland.,School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
| | - Santosh Lamichhane
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520 Turku, Finland
| | - Vivek B Mathema
- Metabolomics and Systems Biology, Department of Biochemistry, and Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand
| | - Aidan McGlinchey
- School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
| | - Alex M Dickens
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520 Turku, Finland
| | - Sakda Khoomrung
- Metabolomics and Systems Biology, Department of Biochemistry, and Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand.,Center for Innovation in Chemistry (PERCH), Faculty of Science, Mahidol University, Rama 6 Road, Bangkok 10400, Thailand
| | - Matej Orešič
- Turku Bioscience Centre, University of Turku and Åbo Akademi University, 20520 Turku, Finland.,School of Medical Sciences, Örebro University, 702 81 Örebro, Sweden
| |
Collapse
|
26
|
Advances in lipidomics. Clin Chim Acta 2020; 510:123-141. [PMID: 32622966 DOI: 10.1016/j.cca.2020.06.049] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 06/29/2020] [Accepted: 06/30/2020] [Indexed: 01/24/2023]
Abstract
The present article examines recently published literature on lipids, mainly focusing on research involving glycero-, glycerophospho- and sphingo-lipids. The primary aim is identification of distinct profiles in biologic lipidomic systems by ultra-high-performance liquid chromatography (UHPLC) coupled with mass spectrometry (MS, tandem MS) with multivariate data analysis. This review specifically targets lipid biomarkers and disease pathway mechanisms in humans and artificial targets. Different specimen matrices such as primary blood derivatives (plasma, serum, erythrocytes, and blood platelets), faecal matter, urine, as well as biologic tissues (liver, lung and kidney) are highlighted.
Collapse
|
27
|
Torkhovskaya TI, Zakharova TS, Korotkevich EI, Kasum-zade NK, Shalina RI, Markin SS. Blood Plasma Lipidome: Opportunities in the Early Diagnostics of Preeclampsia. RUSSIAN JOURNAL OF BIOORGANIC CHEMISTRY 2020. [DOI: 10.1134/s1068162020030206] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
28
|
Liu Y, Chan DK, Thalamuthu A, Wen W, Jiang J, Paradise M, Lee T, Crawford J, Wai Kin Wong M, Hua Xu Y, Poljak A, Pickford R, Sachdev PS, Braidy N. Plasma lipidomic biomarker analysis reveals distinct lipid changes in vascular dementia. Comput Struct Biotechnol J 2020; 18:1613-1624. [PMID: 32670502 PMCID: PMC7334482 DOI: 10.1016/j.csbj.2020.06.001] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2020] [Revised: 05/31/2020] [Accepted: 06/01/2020] [Indexed: 11/17/2022] Open
Abstract
Vascular dementia (VaD) is a complex neurocognitive disorder secondary to a variety of cerebrovascular lesions. Numerous studies have shown that lipid metabolism is involved in the pathobiology of the disease. We examined the plasma lipid profiles in VaD, with the expectation of identifying reliable lipid biomarkers for VaD. 49 VaD patients and 48 healthy controls were recruited from Bankstown-Lidcombe Hospital in Sydney, Australia. Lipids were extracted by single phase 1-butanol/methanol, and untargeted analysis was performed by liquid chromatography coupled-mass spectrometry (LC–MS/MS). Univariate analysis of variance was used to examine the differences in lipid classes and individual lipids between VaD and control groups. In an independent sample of 161 subjects from the Older Australian Twins Study (OATS), elastic net penalization for the generalized linear model (Glmnet) and Random Forest were applied to the lipid levels to subcategorise the sample into vascular cognitive impairment and controls. Most lipids belonging to the classes of ceramides (Cer), cholesterol esters (ChE) and phospholipids were significantly lower in VaD plasma, while glycerides were elevated compared to controls. Levels of ChE, Cer and the two lipid classes together achieved the best accuracy in discriminating VaD from controls, with more than 80% accuracy. The probable VaD group in the OATS sample predicted by the lipid levels showed greater impairment in most cognitive domains, especially attention and processing speed and executive function from controls but did not differ in white matter hyperintensities and DTI measures. As a conclusion, plasma lipids levels, in particular Cer and ChE, are abnormal in VaD and may help discriminate them from healthy controls. Understanding the basis of these differences may provide insights into the pathobiology of VaD.
Collapse
Affiliation(s)
- Yue Liu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Daniel K.Y. Chan
- Department of Aged Care and Rehabilitation, Bankstown Hospital, Bankstown, NSW, Australia
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
- Neuroscience Research Australia, Randwick, Australia
| | - Wei Wen
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Jiyang Jiang
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Matthew Paradise
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Teresa Lee
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - John Crawford
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Matthew Wai Kin Wong
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
| | - Ying Hua Xu
- Department of Aged Care and Rehabilitation, Bankstown Hospital, Bankstown, NSW, Australia
| | - Anne Poljak
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, Australia
- School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Russell Pickford
- Mark Wainwright Analytical Centre, University of New South Wales, Sydney, Australia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
- Neuropsychiatric Institute, Euroa Centre, Prince of Wales Hospital, Sydney, Australia
| | - Nady Braidy
- Centre for Healthy Brain Ageing (CHeBA), School of Psychiatry, University of New South Wales, Sydney, Australia
- Corresponding author: School of Medicine, Huzhou University, Wuxing district, Zhejiang, China
| |
Collapse
|
29
|
Cebo M, Schlotterbeck J, Gawaz M, Chatterjee M, Lämmerhofer M. Simultaneous targeted and untargeted UHPLC-ESI-MS/MS method with data-independent acquisition for quantification and profiling of (oxidized) fatty acids released upon platelet activation by thrombin. Anal Chim Acta 2020; 1094:57-69. [DOI: 10.1016/j.aca.2019.10.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2019] [Accepted: 10/06/2019] [Indexed: 12/19/2022]
|
30
|
Abstract
Lipidomics data generated using untargeted mass spectrometry techniques can offer great biological insight to metabolic status and disease diagnoses. As the community's ability to conduct large-scale studies with deep coverage of the lipidome expands, approaches to analyzing untargeted data and extracting biological insight are needed. Currently, the function of most individual lipids are not known; however, meaningful biological information can be extracted. Here, I will describe a step-by-step approach to identify patterns and trends in untargeted mass spectrometry lipidomics data to assist users in extracting information leading to a greater understanding of biological systems.
Collapse
|
31
|
Li L, Zhong S, Shen X, Li Q, Xu W, Tao Y, Yin H. Recent development on liquid chromatography-mass spectrometry analysis of oxidized lipids. Free Radic Biol Med 2019; 144:16-34. [PMID: 31202785 DOI: 10.1016/j.freeradbiomed.2019.06.006] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 05/21/2019] [Accepted: 06/05/2019] [Indexed: 12/13/2022]
Abstract
Polyunsaturated fatty acids (PUFAs) in the cellular membrane can be oxidized by various enzymes or reactive oxygen species (ROS) to form many oxidized lipids. These metabolites are highly bioactive, participating in a variety of physiological and pathophysiological processes. Mass spectrometry (MS), coupled with Liquid Chromatography, has been increasingly recognized as an indispensable tool for the analysis of oxidized lipids due to its excellent sensitivity and selectivity. We will give an update on the understanding of the molecular mechanisms related to generation of various oxidized lipids and recent progress on the development of LC-MS in the detection of these bioactive lipids derived from fatty acids, cholesterol esters, and phospholipids. The purpose of this review is to provide an overview of the formation mechanisms and technological advances in LC-MS for the study of oxidized lipids in human diseases, and to shed new light on the potential of using oxidized lipids as biomarkers and mechanistic clues of pathogenesis related to lipid metabolism. The key technical problems associated with analysis of oxidized lipids and challenges in the field will also discussed.
Collapse
Affiliation(s)
- Luxiao Li
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, 200031, China; University of Chinese Academy of Sciences, CAS, Beijing, 100049, China
| | - Shanshan Zhong
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, 200031, China; University of Chinese Academy of Sciences, CAS, Beijing, 100049, China
| | - Xia Shen
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, 200031, China; University of Chinese Academy of Sciences, CAS, Beijing, 100049, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, 200031, China
| | - Qiujing Li
- Department of Pharmacy, Zhangzhou Health Vocational College, Zhangzhou, 363000, China
| | - Wenxin Xu
- Department of Medical Technology, Zhangzhou Health Vocational College, Zhangzhou, 363000, China
| | - Yongzhen Tao
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, 200031, China
| | - Huiyong Yin
- CAS Key Laboratory of Nutrition, Metabolism and Food Safety, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences (SIBS), Chinese Academy of Sciences (CAS), Shanghai, 200031, China; University of Chinese Academy of Sciences, CAS, Beijing, 100049, China; School of Life Science and Technology, ShanghaiTech University, Shanghai, 200031, China; Key Laboratory of Food Safety Risk Assessment, Ministry of Health, Beijing, 100000, China.
| |
Collapse
|
32
|
Lipidomic analysis reveals sphingomyelin and phosphatidylcholine species associated with renal impairment and all-cause mortality in type 1 diabetes. Sci Rep 2019; 9:16398. [PMID: 31705008 PMCID: PMC6841673 DOI: 10.1038/s41598-019-52916-w] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2019] [Accepted: 10/24/2019] [Indexed: 12/11/2022] Open
Abstract
There is an urgent need for a better molecular understanding of the pathophysiology underlying development and progression of diabetic nephropathy. The aim of the current study was to identify novel associations between serum lipidomics and diabetic nephropathy. Non-targeted serum lipidomic analyses were performed with mass spectrometry in 669 individuals with type 1 diabetes. Cross-sectional associations of lipid species with estimated glomerular filtration rate (eGFR) and urinary albumin excretion were assessed. Moreover, associations with register-based longitudinal follow-up for progression to a combined renal endpoint including ≥30% decline in eGFR, ESRD and all-cause mortality were evaluated. Median follow-up time was 5.0–6.4 years. Adjustments included traditional risk factors and multiple testing correction. In total, 106 lipid species were identified. Primarily, alkyl-acyl phosphatidylcholines, triglycerides and sphingomyelins demonstrated cross-sectional associations with eGFR and macroalbuminuria. In longitudinal analyses, thirteen lipid species were associated with the slope of eGFR or albuminuria. Of these lipids, phosphatidylcholine and sphingomyelin species, PC(O-34:2), PC(O-34:3), SM(d18:1/24:0), SM(d40:1) and SM(d41:1), were associated with lower risk of the combined renal endpoint. PC(O-34:3), SM(d40:1) and SM(d41:1) were associated with lower risk of all-cause mortality while an SM(d18:1/24:0) was associated with lower risk of albuminuria group progression. We report distinct associations between lipid species and risk of renal outcomes in type 1 diabetes, independent of traditional markers of kidney function.
Collapse
|
33
|
Torkhovskaya TI, Zakharova TS, Korotkevich EI, Ipatova OM, Markin SS. Human Blood Plasma Lipidome: Opportunities and Prospects of Its Analysis in Medical Chemistry. RUSSIAN JOURNAL OF BIOORGANIC CHEMISTRY 2019. [DOI: 10.1134/s106816201905011x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
|
34
|
Calderón C, Rubarth L, Cebo M, Merfort I, Lämmerhofer M. Lipid Atlas of Keratinocytes and Betulin Effects on its Lipidome Profiled by Comprehensive UHPLC–MS/MS with Data Independent Acquisition Using Targeted Data Processing. Proteomics 2019; 20:e1900113. [DOI: 10.1002/pmic.201900113] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Revised: 07/24/2019] [Indexed: 01/11/2023]
Affiliation(s)
- Carlos Calderón
- Institute of Pharmaceutical Sciences Pharmaceutical (Bio‐)Analysis University of Tübingen Auf der Morgenstelle 8 72076 Tübingen Germany
| | - Lara Rubarth
- Institute of Pharmaceutical Sciences Department of Pharmaceutical Biology and Biotechnology University of Freiburg 79104 Freiburg Germany
| | - Malgorzata Cebo
- Institute of Pharmaceutical Sciences Pharmaceutical (Bio‐)Analysis University of Tübingen Auf der Morgenstelle 8 72076 Tübingen Germany
| | - Irmgard Merfort
- Institute of Pharmaceutical Sciences Department of Pharmaceutical Biology and Biotechnology University of Freiburg 79104 Freiburg Germany
| | - Michael Lämmerhofer
- Institute of Pharmaceutical Sciences Pharmaceutical (Bio‐)Analysis University of Tübingen Auf der Morgenstelle 8 72076 Tübingen Germany
| |
Collapse
|
35
|
Plasma lipidome variation during the second half of the human lifespan is associated with age and sex but minimally with BMI. PLoS One 2019; 14:e0214141. [PMID: 30893377 PMCID: PMC6426235 DOI: 10.1371/journal.pone.0214141] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Accepted: 03/07/2019] [Indexed: 12/21/2022] Open
Abstract
Recent advances in mass spectrometry-based techniques have inspired research into lipidomics, a subfield of ‘–omics’, which aims to identify and quantify large numbers of lipids in biological extracts. Although lipidomics is becoming increasingly popular as a screening tool for understanding disease mechanisms, it is largely unknown how the lipidome naturally varies by age and sex in healthy individuals. We aimed to identify cross-sectional associations of the human lipidome with ‘physiological’ ageing, using plasma from 100 subjects with an apolipoprotein E (APOE) E3/E3 genotype, and aged between 56 to 100 years. Untargeted analysis was performed by liquid chromatography coupled-mass spectrometry (LC-MS/MS) and data processing using LipidSearch software. Regression analyses confirmed a strong negative association of age with the levels of various lipid, which was stronger in males than females. Sex-related differences include higher LDL-C, HDL-C, total cholesterol, particular sphingomyelins (SM), and docosahexaenoic acid (DHA)-containing phospholipid levels in females. Surprisingly, we found a minimal relationship between lipid levels and body mass index (BMI). In conclusion, our results suggest substantial age and sex-related variation in the plasma lipidome of healthy individuals during the second half of the human lifespan. In particular, globally low levels of blood lipids in the ‘oldest old’ subjects over 95 years could signify a unique lipidome associated with extreme longevity.
Collapse
|
36
|
Zandkarimi F, Brown LM. Application of Ion Mobility Mass Spectrometry in Lipidomics. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1140:317-326. [DOI: 10.1007/978-3-030-15950-4_18] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
|
37
|
Overgaard AJ, Weir JM, Jayawardana K, Mortensen HB, Pociot F, Meikle PJ. Plasma lipid species at type 1 diabetes onset predict residual beta-cell function after 6 months. Metabolomics 2018; 14:158. [PMID: 30830451 PMCID: PMC6280838 DOI: 10.1007/s11306-018-1456-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/30/2018] [Indexed: 01/10/2023]
Abstract
INTRODUCTION The identification of metabolomic dysregulation appears promising for the prediction of type 1 diabetes and may also reveal metabolic pathways leading to beta-cell destruction. Recent studies indicate that regulation of multiple phospholipids precede the presence of autoantigens in the development of type 1 diabetes. OBJECTIVES We hypothesize that lipid biomarkers in plasma from children with recent onset type 1 diabetes will reflect their remaining beta-cell function and predict future changes in beta-cell function. METHODS We performed targeted lipidomic profiling by electrospray ionization tandem mass spectrometry to acquire comparative measures of 354 lipid species covering 25 lipid classes and subclasses in plasma samples from 123 patients < 17 years of age followed prospectively at 1, 3, 6 and 12 months after diagnosis. Lipidomic profiles were analysed using liner regression to investigate the relationship between plasma lipids and meal stimulated C-peptide levels at each time point. P-values were corrected for multiple comparisons by the method of Benjamini and Hochberg. RESULTS Linear regression analysis showed that the relative levels of cholesteryl ester, diacylglycerol and triacylglycerol at 1 month were associated to the change in c-peptide levels from 1 to 6 months (corrected p-values of 4.06E-03, 1.72E-02 and 1.72E02, respectively). Medium chain saturated and monounsaturated fatty acids were the major constituents of the di- and triacylglycerol species suggesting a link with increased lipogenesis. CONCLUSION These observations support the hypothesis of lipid disturbances as explanatory factors for residual beta-cell function in children with new onset type 1 diabetes.
Collapse
Affiliation(s)
- Anne Julie Overgaard
- Steno Diabetes Center Copenhagen, Niels Steensensvej 2, 2820, Gentofte, Denmark.
- Baker IDI Heart and Diabetes Research Institute, 75 Commercial Road, Melbourne, Australia.
| | - Jacquelyn M Weir
- Baker IDI Heart and Diabetes Research Institute, 75 Commercial Road, Melbourne, Australia
| | - Kaushala Jayawardana
- Baker IDI Heart and Diabetes Research Institute, 75 Commercial Road, Melbourne, Australia
| | | | - Flemming Pociot
- Steno Diabetes Center Copenhagen, Niels Steensensvej 2, 2820, Gentofte, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Peter J Meikle
- Baker IDI Heart and Diabetes Research Institute, 75 Commercial Road, Melbourne, Australia
- Department of Biochemistry and Molecular Biology, University of Melbourne, Melbourne, Australia
| |
Collapse
|
38
|
Grip T, Dyrlund TS, Ahonen L, Domellöf M, Hernell O, Hyötyläinen T, Knip M, Lönnerdal B, Orešič M, Timby N. Serum, plasma and erythrocyte membrane lipidomes in infants fed formula supplemented with bovine milk fat globule membranes. Pediatr Res 2018; 84:726-732. [PMID: 30120403 DOI: 10.1038/s41390-018-0130-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Revised: 07/05/2018] [Accepted: 07/11/2018] [Indexed: 01/28/2023]
Abstract
BACKGROUND Supplementation of formula with bovine milk fat globule membranes has been shown to narrow the gap in immunological and cognitive development between breast-fed and formula-fed infants. METHOD In a double-blinded randomized controlled trial 160 formula-fed infants received an experimental formula (EF), supplemented with bovine milk fat globule membranes, or standard formula until 6 months of age. A breast-fed reference group was recruited. Lipidomic analyses were performed on plasma and erythrocyte membranes at 6 months and on serum at 4 and 12 months of age. RESULTS At 6 months of age, we observed a significant separation in the plasma lipidome between the two formula groups, mostly due to differences in concentrations of sphingomyelins (SM), phosphatidylcholines (PC), and ceramides, and in the erythrocyte membrane lipidome, mostly due to SMs, PEs and PCs. Already at 4 months, a separation in the serum lipidome was evident where SMs and PCs contributed. The separation was not detected at 12 months. CONCLUSIONS The effect of MFGM supplementation on the lipidome is likely part of the mechanisms behind the positive cognitive and immunological effects of feeding the EF previously reported in the same study population.
Collapse
Affiliation(s)
- Tove Grip
- Clinical Sciences/Pediatrics, Umeå University, Umeå, Sweden
| | | | - Linda Ahonen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | | | - Olle Hernell
- Clinical Sciences/Pediatrics, Umeå University, Umeå, Sweden
| | | | - Mikael Knip
- Children´s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.,Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.,Folkhälsan Research Institute, Helsinki, Finland
| | - Bo Lönnerdal
- Department of Nutrition, University of California, Davis, United States
| | - Matej Orešič
- Turku Centre for Biotechnology, University of Turku and Åbo Academy University, Turku, Finland.,School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Niklas Timby
- Clinical Sciences/Pediatrics, Umeå University, Umeå, Sweden.
| |
Collapse
|
39
|
Pedersen HK, Forslund SK, Gudmundsdottir V, Petersen AØ, Hildebrand F, Hyötyläinen T, Nielsen T, Hansen T, Bork P, Ehrlich SD, Brunak S, Oresic M, Pedersen O, Nielsen HB. A computational framework to integrate high-throughput ‘-omics’ datasets for the identification of potential mechanistic links. Nat Protoc 2018; 13:2781-2800. [DOI: 10.1038/s41596-018-0064-z] [Citation(s) in RCA: 59] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
|
40
|
Brandsma J, Goss VM, Yang X, Bakke PS, Caruso M, Chanez P, Dahlén SE, Fowler SJ, Horvath I, Krug N, Montuschi P, Sanak M, Sandström T, Shaw DE, Chung KF, Singer F, Fleming LJ, Sousa AR, Pandis I, Bansal AT, Sterk PJ, Djukanović R, Postle AD. Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers. Metabolomics 2018; 14:123. [PMID: 30830396 PMCID: PMC6153688 DOI: 10.1007/s11306-018-1412-2] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 08/12/2018] [Indexed: 01/20/2023]
Abstract
BACKGROUND Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood. OBJECTIVES To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort. METHODS Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes. RESULTS The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender. CONCLUSIONS We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.
Collapse
Affiliation(s)
- Joost Brandsma
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
| | - Victoria M Goss
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Xian Yang
- Data Science Institute, Imperial College, London, UK
| | - Per S Bakke
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Massimo Caruso
- Department of Clinical and Experimental Medicine, University of Catania, Catania, Italy
| | - Pascal Chanez
- Department of Respiratory Diseases, Aix-Marseille University, Marseille, France
| | - Sven-Erik Dahlén
- Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden
| | - Stephen J Fowler
- Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK
- Manchester Academic Health Science Centre, University Hospital of South Manchester, Manchester, UK
| | - Ildiko Horvath
- Department of Pulmonology, Semmelweis University, Budapest, Hungary
| | - Norbert Krug
- Fraunhofer Institute for Toxicology and Experimental Medicine, Hannover, Germany
| | - Paolo Montuschi
- Department of Pharmacology, Faculty of Medicine, Catholic University of the Sacred Heart, Rome, Italy
| | - Marek Sanak
- Department of Medicine, Jagiellonian University, Krakow, Poland
| | - Thomas Sandström
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Dominick E Shaw
- Respiratory Research Unit, University of Nottingham, Nottingham, UK
| | - Kian Fan Chung
- National Heart and Lung Institute, Imperial College, London, UK
| | | | | | - Ana R Sousa
- Respiratory Therapy Unit, GlaxoSmithKline, London, UK
| | | | - Aruna T Bansal
- Acclarogen Ltd, St John's Innovation Centre, Cambridge, UK
| | - Peter J Sterk
- Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Ratko Djukanović
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- National Institute for Health Research Southampton Biomedical Research Centre, Southampton, UK
| | - Anthony D Postle
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | | |
Collapse
|
41
|
Schlotterbeck J, Chatterjee M, Gawaz M, Lämmerhofer M. Comprehensive MS/MS profiling by UHPLC-ESI-QTOF-MS/MS using SWATH data-independent acquisition for the study of platelet lipidomes in coronary artery disease. Anal Chim Acta 2018; 1046:1-15. [PMID: 30482286 DOI: 10.1016/j.aca.2018.08.060] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2018] [Revised: 08/29/2018] [Accepted: 08/30/2018] [Indexed: 01/13/2023]
Abstract
A non-targeted lipidomics workflow based on C8 core-shell particle ultra high-performance liquid chromatography (UHPLC) hyphenated to ESI-QTOF-MS in data-independent acquisition (DIA) mode with sequential window acquisition of all theoretical fragment ion spectra (SWATH) was developed and applied to differential platelet lipidomics profiling of cardiovascular disease patients (stable angina pectoris (n = 10), ST-elevated myocardial infarction (n = 13)) against healthy controls (n = 10). DIA with SWATH generates comprehensive MS and MS/MS data throughout the entire chromatograms and all study samples. Hence, chromatograms can be extracted based on precursors or fragments which provided some benefits in terms of assay specificity in some cases. SWATH acquisition offers flexible experimental design with variable Q1 isolation windows. Liquid chromatography as well as SWATH settings were optimized to cover the lipidome of human platelets. The flexibility of the SWATH experiment design was utilized to implement target SWATH windows with narrow 5 Da Q1 precursor ion selection width (multiple reaction monitoring (MRM)-like SWATH windows) for the detection of low abundant oxidized phospholipids. Data processing was performed with MS-DIAL, and its feasibilities and caveats are discussed by illustrative examples. Thereby, identification of lipids is still a bottleneck in non-targeted lipidomics workflow. MS-DIAL, however, offers automatic identification via spectral matching using an in silico library. In total 1971 molecular features were detected cross the samples of which 611 were identified (total score >70%). The quality of the acquired data was validated with embedded quality control samples (n = 11). 80.3% of all features detected in the QC samples showed a coefficient of variation of below 30%. Multivariate statistics were used to visualize differences in the lipidome of distinct sample groups at a false discovery rate of 5%.
Collapse
Affiliation(s)
- Jörg Schlotterbeck
- University of Tübingen, Institute of Pharmaceutical Sciences, Pharmaceutical (Bio-)Analysis, Auf der Morgenstelle 8, 72076, Tübingen, Germany
| | - Madhumita Chatterjee
- Department of Cardiology and Cardiovascular Medicine, University Hospital Tübingen, Otfried-Müller-Strasse 10, 72076, Tübingen, Germany
| | - Meinrad Gawaz
- Department of Cardiology and Cardiovascular Medicine, University Hospital Tübingen, Otfried-Müller-Strasse 10, 72076, Tübingen, Germany
| | - Michael Lämmerhofer
- University of Tübingen, Institute of Pharmaceutical Sciences, Pharmaceutical (Bio-)Analysis, Auf der Morgenstelle 8, 72076, Tübingen, Germany.
| |
Collapse
|
42
|
Dynamics of Plasma Lipidome in Progression to Islet Autoimmunity and Type 1 Diabetes - Type 1 Diabetes Prediction and Prevention Study (DIPP). Sci Rep 2018; 8:10635. [PMID: 30006587 PMCID: PMC6045612 DOI: 10.1038/s41598-018-28907-8] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2018] [Accepted: 07/02/2018] [Indexed: 12/16/2022] Open
Abstract
Type 1 diabetes (T1D) is one of the most prevalent autoimmune diseases among children in Western countries. Earlier metabolomics studies suggest that T1D is preceded by dysregulation of lipid metabolism. Here we used a lipidomics approach to analyze molecular lipids in a prospective series of 428 plasma samples from 40 children who progressed to T1D (PT1D), 40 children who developed at least a single islet autoantibody but did not progress to T1D during the follow-up (P1Ab) and 40 matched controls (CTR). Sphingomyelins were found to be persistently downregulated in PT1D when compared to the P1Ab and CTR groups. Triacylglycerols and phosphatidylcholines were mainly downregulated in PT1D as compared to P1Ab at the age of 3 months. Our study suggests that distinct lipidomic signatures characterize children who progressed to islet autoimmunity or overt T1D, which may be helpful in the identification of at-risk children before the initiation of autoimmunity.
Collapse
|
43
|
Vuckovic D. Improving metabolome coverage and data quality: advancing metabolomics and lipidomics for biomarker discovery. Chem Commun (Camb) 2018; 54:6728-6749. [PMID: 29888773 DOI: 10.1039/c8cc02592d] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
This Feature Article highlights some of the key challenges within the field of metabolomics and examines what role separation and analytical sciences can play to improve the use of metabolomics in biomarker discovery and personalized medicine. Recent progress in four key areas is highlighted: (i) improving metabolite coverage, (ii) developing accurate methods for unstable metabolites including in vivo global metabolomics methods, (iii) advancing inter-laboratory studies and reference materials and (iv) improving data quality, standardization and quality control of metabolomics studies.
Collapse
Affiliation(s)
- Dajana Vuckovic
- Department of Chemistry and Biochemistry, Concordia University, 7141 Sherbrooke Street West, Montréal, Québec H4B 1R6, Canada.
| |
Collapse
|
44
|
Donato P, Micalizzi G, Oteri M, Rigano F, Sciarrone D, Dugo P, Mondello L. Comprehensive lipid profiling in the Mediterranean mussel (Mytilus galloprovincialis) using hyphenated and multidimensional chromatography techniques coupled to mass spectrometry detection. Anal Bioanal Chem 2018; 410:3297-3313. [DOI: 10.1007/s00216-018-1045-3] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Revised: 03/20/2018] [Accepted: 03/23/2018] [Indexed: 01/09/2023]
|
45
|
Huynh K, Martins RN, Meikle PJ. Lipidomic Profiles in Diabetes and Dementia. J Alzheimers Dis 2018; 59:433-444. [PMID: 28582856 DOI: 10.3233/jad-161215] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Lipids are a diverse class of hydrophobic and amphiphilic molecules which make up the bulk of most biological systems and are essential for human life. The role of lipids in health and disease has been recognized for many decades, as evidenced by the early identification of cholesterol as an important risk factor of heart disease and the development and introduction of statins as a one of the most successful therapeutic interventions to date. While several studies have demonstrated an increased risk of dementia, including Alzheimer's disease (AD), in those with diabetes mellitus, the nature of this risk is not well understood. Recent developments in the field of lipidomics, driven primarily by technological advances in high pressure liquid chromatography and particularly mass spectrometry, have enabled the detailed characterization of the many hundreds of individual lipid species in mammalian systems and their association with disease states. Diabetes mellitus and AD have received particular attention due to their prominence in Western societies as a result of the ongoing obesity epidemic and the aging populations. In this review, we examine how these lipidomic studies are informing on the relationship between lipid metabolism with diabetes and AD and how this may inform on the common pathological pathways that link diabetes risk with dementia.
Collapse
Affiliation(s)
- Kevin Huynh
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.,Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| | - Ralph N Martins
- School of Biomedical and Health Sciences, Edith Cowan University, Perth Western Australia, WA, Australia.,Department of Biomedical Sciences, Macquarie University, Sydney, NSW, Australia
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.,Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, VIC, Australia
| |
Collapse
|
46
|
Gender-related metabolomics and lipidomics: From experimental animal models to clinical evidence. J Proteomics 2018; 178:82-91. [DOI: 10.1016/j.jprot.2017.11.001] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 10/16/2017] [Accepted: 11/01/2017] [Indexed: 02/06/2023]
|
47
|
Bowden JA, Heckert A, Ulmer CZ, Jones CM, Koelmel JP, Abdullah L, Ahonen L, Alnouti Y, Armando AM, Asara JM, Bamba T, Barr JR, Bergquist J, Borchers CH, Brandsma J, Breitkopf SB, Cajka T, Cazenave-Gassiot A, Checa A, Cinel MA, Colas RA, Cremers S, Dennis EA, Evans JE, Fauland A, Fiehn O, Gardner MS, Garrett TJ, Gotlinger KH, Han J, Huang Y, Neo AH, Hyötyläinen T, Izumi Y, Jiang H, Jiang H, Jiang J, Kachman M, Kiyonami R, Klavins K, Klose C, Köfeler HC, Kolmert J, Koal T, Koster G, Kuklenyik Z, Kurland IJ, Leadley M, Lin K, Maddipati KR, McDougall D, Meikle PJ, Mellett NA, Monnin C, Moseley MA, Nandakumar R, Oresic M, Patterson R, Peake D, Pierce JS, Post M, Postle AD, Pugh R, Qiu Y, Quehenberger O, Ramrup P, Rees J, Rembiesa B, Reynaud D, Roth MR, Sales S, Schuhmann K, Schwartzman ML, Serhan CN, Shevchenko A, Somerville SE, St John-Williams L, Surma MA, Takeda H, Thakare R, Thompson JW, Torta F, Triebl A, Trötzmüller M, Ubhayasekera SJK, Vuckovic D, Weir JM, Welti R, Wenk MR, Wheelock CE, Yao L, Yuan M, Zhao XH, Zhou S. Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma. J Lipid Res 2017; 58:2275-2288. [PMID: 28986437 PMCID: PMC5711491 DOI: 10.1194/jlr.m079012] [Citation(s) in RCA: 270] [Impact Index Per Article: 38.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2017] [Revised: 10/02/2017] [Indexed: 12/22/2022] Open
Abstract
As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.
Collapse
Affiliation(s)
- John A Bowden
- Marine Biochemical Sciences Group, Chemical Sciences Division, Hollings Marine Laboratory, National Institute of Standards and Technology, Charleston, SC
| | - Alan Heckert
- Statistical Engineering Division, National Institute of Standards and Technology, Gaithersburg, MD
| | - Candice Z Ulmer
- Marine Biochemical Sciences Group, Chemical Sciences Division, Hollings Marine Laboratory, National Institute of Standards and Technology, Charleston, SC
| | - Christina M Jones
- Marine Biochemical Sciences Group, Chemical Sciences Division, Hollings Marine Laboratory, National Institute of Standards and Technology, Charleston, SC
| | - Jeremy P Koelmel
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | | | - Linda Ahonen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Yazen Alnouti
- Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, NE
| | - Aaron M Armando
- Departments of Chemistry and Biochemistry and Pharmacology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - John M Asara
- Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Takeshi Bamba
- Division of Metabolomics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Japan
| | - John R Barr
- Division of Laboratory Sciences, Centers for Disease Control and Prevention, National Center for Environmental Health, Atlanta, GA
| | - Jonas Bergquist
- Department of Chemistry-BMC, Analytical Chemistry, Uppsala University, Uppsala, Sweden
| | - Christoph H Borchers
- University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria, Victoria, British Columbia, Canada
- Department of Biochemistry and Microbiology, University of Victoria, Victoria, British Columbia, Canada
- Gerald Bronfman Department of Oncology McGill University, Montreal, Quebec, Canada
- Proteomics Centre, Segal Cancer Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, Canada
| | - Joost Brandsma
- Faculty of Medicine, Academic Unit of Clinical and Experimental Sciences, Southampton General Hospital, University of Southampton, Southampton, United Kingdom
| | - Susanne B Breitkopf
- Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, MA
| | - Tomas Cajka
- National Institutes of Health West Coast Metabolomics Center, University of California Davis Genome Center, Davis, CA
| | - Amaury Cazenave-Gassiot
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore and Singapore Lipidomic Incubator (SLING), Life Sciences Institute, Singapore
| | - Antonio Checa
- Division of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Michelle A Cinel
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Romain A Colas
- Department of Anesthesiology, Perioperative and Pain Medicine, Center for Experimental Therapeutics and Reperfusion Injury, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Serge Cremers
- Biomarker Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY
| | - Edward A Dennis
- Departments of Chemistry and Biochemistry and Pharmacology, School of Medicine, University of California, San Diego, La Jolla, CA
| | | | - Alexander Fauland
- Division of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Oliver Fiehn
- National Institutes of Health West Coast Metabolomics Center, University of California Davis Genome Center, Davis, CA
- Biochemistry Department, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Michael S Gardner
- Division of Laboratory Sciences, Centers for Disease Control and Prevention, National Center for Environmental Health, Atlanta, GA
| | - Timothy J Garrett
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | - Katherine H Gotlinger
- Department of Pharmacology, New York Medical College School of Medicine, Valhalla, NY
| | - Jun Han
- University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria, Victoria, British Columbia, Canada
| | | | - Aveline Huipeng Neo
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore and Singapore Lipidomic Incubator (SLING), Life Sciences Institute, Singapore
| | | | - Yoshihiro Izumi
- Division of Metabolomics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Japan
| | - Hongfeng Jiang
- Biomarker Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY
| | - Houli Jiang
- Department of Pharmacology, New York Medical College School of Medicine, Valhalla, NY
| | - Jiang Jiang
- Departments of Chemistry and Biochemistry and Pharmacology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Maureen Kachman
- Metabolomics Core, BRCF, University of Michigan, Ann Arbor, MI
| | | | | | | | - Harald C Köfeler
- Core Facility for Mass Spectrometry, Medical University of Graz, Graz, Austria
| | - Johan Kolmert
- Division of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | | | - Grielof Koster
- Faculty of Medicine, Academic Unit of Clinical and Experimental Sciences, Southampton General Hospital, University of Southampton, Southampton, United Kingdom
| | - Zsuzsanna Kuklenyik
- Division of Laboratory Sciences, Centers for Disease Control and Prevention, National Center for Environmental Health, Atlanta, GA
| | - Irwin J Kurland
- Stable Isotope and Metabolomics Core Facility, Diabetes Research Center, Albert Einstein College of Medicine, Bronx, NY
| | - Michael Leadley
- Analytical Facility of Bioactive Molecules, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Karen Lin
- University of Victoria-Genome British Columbia Proteomics Centre, University of Victoria, Victoria, British Columbia, Canada
| | - Krishna Rao Maddipati
- Lipidomics Core Facility and Department of Pathology, Wayne State University, Detroit, MI
| | - Danielle McDougall
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | - Peter J Meikle
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | | | - Cian Monnin
- Department of Chemistry and Biochemistry, Concordia University, Montréal, Québec, Canada
| | - M Arthur Moseley
- Proteomics and Metabolomics Shared Resource, Levine Science Research Center, Duke University School of Medicine, Durham, NC
| | - Renu Nandakumar
- Biomarker Core Laboratory, Irving Institute for Clinical and Translational Research, Columbia University Medical Center, New York, NY
| | - Matej Oresic
- Turku Centre for Biotechnology, University of Turku and Åbo Akademi University, Turku, Finland
| | - Rainey Patterson
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL
| | | | - Jason S Pierce
- Department of Biochemistry and Molecular Biology Medical University of South Carolina, Charleston, SC
| | - Martin Post
- Analytical Facility of Bioactive Molecules, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Anthony D Postle
- Faculty of Medicine, Academic Unit of Clinical and Experimental Sciences, Southampton General Hospital, University of Southampton, Southampton, United Kingdom
| | - Rebecca Pugh
- Chemical Sciences Division, Environmental Specimen Bank Group, Hollings Marine Laboratory, National Institute of Standards and Technology, Charleston, SC
| | - Yunping Qiu
- Stable Isotope and Metabolomics Core Facility, Diabetes Research Center, Albert Einstein College of Medicine, Bronx, NY
| | - Oswald Quehenberger
- Departments of Medicine and Pharmacology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Parsram Ramrup
- Department of Chemistry and Biochemistry, Concordia University, Montréal, Québec, Canada
| | - Jon Rees
- Division of Laboratory Sciences, Centers for Disease Control and Prevention, National Center for Environmental Health, Atlanta, GA
| | - Barbara Rembiesa
- Department of Biochemistry and Molecular Biology Medical University of South Carolina, Charleston, SC
| | - Denis Reynaud
- Analytical Facility of Bioactive Molecules, The Hospital for Sick Children Research Institute, Toronto, ON, Canada
| | - Mary R Roth
- Division of Biology, Kansas Lipidomics Research Center, Kansas State University, Manhattan, KS
| | - Susanne Sales
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Kai Schuhmann
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | | | - Charles N Serhan
- Department of Anesthesiology, Perioperative and Pain Medicine, Center for Experimental Therapeutics and Reperfusion Injury, Brigham and Women's Hospital and Harvard Medical School, Boston, MA
| | - Andrej Shevchenko
- Max Planck Institute of Molecular Cell Biology and Genetics, Dresden, Germany
| | - Stephen E Somerville
- Hollings Marine Laboratory, Medical University of South Carolina, Charleston, SC
| | - Lisa St John-Williams
- Proteomics and Metabolomics Shared Resource, Levine Science Research Center, Duke University School of Medicine, Durham, NC
| | | | - Hiroaki Takeda
- Division of Metabolomics, Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, Higashi-ku, Fukuoka, Japan
| | - Rhishikesh Thakare
- Department of Pharmaceutical Sciences, University of Nebraska Medical Center, Omaha, NE
| | - J Will Thompson
- Proteomics and Metabolomics Shared Resource, Levine Science Research Center, Duke University School of Medicine, Durham, NC
| | - Federico Torta
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore and Singapore Lipidomic Incubator (SLING), Life Sciences Institute, Singapore
| | - Alexander Triebl
- Core Facility for Mass Spectrometry, Medical University of Graz, Graz, Austria
| | - Martin Trötzmüller
- Core Facility for Mass Spectrometry, Medical University of Graz, Graz, Austria
| | | | - Dajana Vuckovic
- Department of Chemistry and Biochemistry, Concordia University, Montréal, Québec, Canada
| | - Jacquelyn M Weir
- Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia
| | - Ruth Welti
- Division of Biology, Kansas Lipidomics Research Center, Kansas State University, Manhattan, KS
| | - Markus R Wenk
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore and Singapore Lipidomic Incubator (SLING), Life Sciences Institute, Singapore
| | - Craig E Wheelock
- Division of Physiological Chemistry 2, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Libin Yao
- Division of Biology, Kansas Lipidomics Research Center, Kansas State University, Manhattan, KS
| | - Min Yuan
- Division of Signal Transduction, Beth Israel Deaconess Medical Center, Boston, MA
| | - Xueqing Heather Zhao
- Stable Isotope and Metabolomics Core Facility, Diabetes Research Center, Albert Einstein College of Medicine, Bronx, NY
| | - Senlin Zhou
- Lipidomics Core Facility and Department of Pathology, Wayne State University, Detroit, MI
| |
Collapse
|
48
|
Cajka T, Smilowitz JT, Fiehn O. Validating Quantitative Untargeted Lipidomics Across Nine Liquid Chromatography-High-Resolution Mass Spectrometry Platforms. Anal Chem 2017; 89:12360-12368. [PMID: 29064229 DOI: 10.1021/acs.analchem.7b03404] [Citation(s) in RCA: 162] [Impact Index Per Article: 23.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Liquid chromatography-mass spectrometry (LC-MS) methods are most often used for untargeted metabolomics and lipidomics. However, methods have not been standardized as accepted "best practice" documents, and reports lack harmonization with respect to quantitative data that enable interstudy comparisons. Researchers use a wide variety of high-resolution mass spectrometers under different operating conditions, and it is unclear if results would yield different biological conclusions depending on the instrument performance. To this end, we used 126 identical human plasma samples and 29 quality control samples from a nutritional intervention study. We investigated lipidomic data acquisitions across nine different MS instruments (1 single TOF, 1 Q/orbital ion trap, and 7 QTOF instruments). Sample preparations, chromatography conditions, and data processing methods were kept identical. Single-point internal standard calibrations were used to estimate absolute concentrations for 307 unique lipids identified by accurate mass, MS/MS spectral match, and retention times. Quantitative results were highly comparable between the LC-MS platforms tested. Using partial least-squares discriminant analysis (PLS-DA) to compare results between platforms, a 92% overlap for the most discriminating lipids based on variable importance in projection (VIP) scores was achieved for all lipids that were detected by at least two instrument platforms. Importantly, even the relative positions of individual samples on the PLS-DA projections were identical. The key for success in harmonizing results was to avoid ion saturation by carefully evaluating linear dynamic ranges using serial dilutions and adjusting the resuspension volume and/or injection volume before running actual study samples.
Collapse
Affiliation(s)
- Tomas Cajka
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis , Davis, California 95616, United States
| | - Jennifer T Smilowitz
- Department of Food Science and Technology, University of California, Davis , Davis, California 95616, United States.,Foods for Health Institute, University of California Davis , Davis, California 95616, United States
| | - Oliver Fiehn
- West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis , Davis, California 95616, United States.,Biochemistry Department, Faculty of Science, King Abdulaziz University , Jeddah 21589, Saudi Arabia
| |
Collapse
|
49
|
Lipidomic analysis of plasma in patients with lacunar infarction using normal-phase/reversed-phase two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry. Anal Bioanal Chem 2017; 409:3211-3222. [PMID: 28251292 DOI: 10.1007/s00216-017-0261-6] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2016] [Revised: 01/23/2017] [Accepted: 02/14/2017] [Indexed: 12/28/2022]
Abstract
Stroke is a major cause of mortality and long-term disability worldwide. The study of biomarkers and pathogenesis is vital for early diagnosis and treatment of stroke. In the present study, a continuous-flow normal-phase/reversed-phase two-dimensional liquid chromatography-quadrupole time-of-flight mass spectrometry (NP/RP 2D LC-QToF/MS) method was employed to measure lipid species in human plasma, including healthy controls and lacunar infarction (LI) patients. As a result, 13 lipid species were demonstrated with significant difference between the two groups, and a "plasma biomarker model" including glucosylceramide (38:2), phosphatidylethanolamine (35:2), free fatty acid (16:1), and triacylglycerol (56:5) was finally established. This model was evaluated as an effective tool in that area under the receiver operating characteristic curve reached 1.000 in the discovery set and 0.947 in the validation set for diagnosing LI patients from healthy controls. Besides, the sensitivity and specificity of disease diagnosis in validation set were 93.3% and 96.6% at the best cutoff value, respectively. This study demonstrates the promising potential of NP/RP 2D LC-QToF/MS-based lipidomics approach in finding bio-markers for disease diagnosis and providing special insights into the metabolism of stroke induced by small vessel disease. Graphical abstract Flow-chart of the plasma biomarker model establishment through biomarker screening and validation.
Collapse
|
50
|
Abstract
PURPOSE OF REVIEW Alzheimer's disease is the most common cause of dementia. There are still no disease modifying treatments that can cure or slow disease progression. Recently, Alzheimer's disease researchers have attempted to improve early detection and diagnostic criteria for Alzheimer's disease, with the rationale that treatment of disease, or even prevention, may be more successful during the early preclinical stages of Alzheimer's disease when neurodegenerative damage is not as widespread. As the brain has a high lipid content, lipidomics may offer novel insights into the underlying pathogenesis of Alzheimer's disease. This review reports on recent developments in the relatively unexplored field of lipidomics in Alzheimer's disease, including novel biomarkers and pathomechanisms of Alzheimer's disease. RECENT FINDINGS Numerous biomarker panels involving phospholipids and sphingolipids have been proposed, indicating perturbed lipid metabolism in early stages of Alzheimer's disease. Future strategies targeting these metabolic changes through dietary supplementation could have therapeutic benefits in at-risk individuals. SUMMARY Dysregulated lipid metabolism could reflect pathological changes in synaptic function and neuronal membranes, leading to cognitive decline. However, extensive validation in large independent cohorts is required before lipid biomarkers can be used clinically to assess Alzheimer's disease risk and progression.
Collapse
|