Untargeted Hair Lipidomics: Comprehensive evaluation of the hair-specific lipid signature and considerations for retrospective analysis
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ABSTRACT:
INSTRUMENT(S): 6560 Q-TOF LC/MS
ORGANISM(S): Homo Sapiens (ncbitaxon:9606)
SUBMITTER: 
Maria van de Lavoir
PROVIDER: MSV000091771 | MassIVE | Fri Apr 21 12:51:00 BST 2023
REPOSITORIES: MassIVE
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Project description:Maria van de Lavoir, Katyeny Manuela da Silva, Elias Iturrospe, Rani Robeyns, Alexander L.N. van Nuijs and Adrian Covaci.
2023-04-21 | MSV000091771 | GNPS
Project description:Sarcopenia, a multifactorial systemic disorder, has attracted extensive attention, yet its pathogenesis is not fully understood, partly due to limited research on the relationship between lipid metabolism abnormalities and sarcopenia. Lipidomics offers the possibility to explore this relationship. Our research utilized LC/MS-based nontargeted lipidomics to investigate the lipid profile changes as-sociated with sarcopenia, aiming to enhance understanding of its underlying mechanisms. The study included 40 sarcopenia patients and 40 control subjects matched 1:1 by sex and age. Plasma lipids were detected and quantified, with differential lipids identified through univariate and mul-tivariate statistical analyses. A weighted correlation network analysis (WGCNA) and MetaboAna-lyst were used to identify lipid modules related to the clinical traits of sarcopenia patients and to conduct pathway analysis, respectively. A total of 34 lipid subclasses and 1446 lipid molecules were detected. Orthogonal partial least squares discriminant analysis (OPLS-DA) identified 80 differen-tial lipid molecules, including 38 phospholipids. Network analysis revealed that the brown module (encompassing phosphatidylglycerol (PG) lipids) and the yellow module (containing phosphati-dylcholine (PC), phosphatidylserine (PS), and sphingomyelin (SM) lipids) were closely associated with the clinical traits such as maximum grip strength and skeletal muscle mass (SMI). Pathway analysis highlighted the potential role of the glycerophospholipid metabolic pathway in lipid me-tabolism within the context of sarcopenia. These findings suggest a correlation between sarcopenia and lipid metabolism disturbances, providing valuable insights into the disease's underlying mechanisms and indicating potential avenues for further investigation.
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Project description:BackgroundNonpuerperal mastitis (NPM) is a disease that presents with redness, swelling, heat, and pain during nonlactation and can often be confused with breast cancer. The etiology of NPM remains elusive; however, emerging clinical evidence suggests a potential involvement of lipid metabolism.MethodLiquid chromatography‒mass spectrometry (LC/MS)-based untargeted lipidomics analysis combined with multivariate statistics was performed to investigate the NPM lipid change in breast tissue. Twenty patients with NPM and 10 controls were enrolled in this study.ResultsThe results revealed significant differences in lipidomics profiles, and a total of 16 subclasses with 14,012 different lipids were identified in positive and negative ion modes. Among these lipids, triglycerides (TGs), phosphatidylethanolamines (PEs) and cardiolipins (CLs) were the top three lipid components between the NPM and control groups. Subsequently, a total of 35 lipids were subjected to screening as potential biomarkers, and the chosen lipid biomarkers exhibited enhanced discriminatory capability between the two groups. Furthermore, pathway analysis elucidated that the aforementioned alterations in lipids were primarily associated with the arachidonic acid metabolic pathway. The correlation between distinct lipid populations and clinical phenotypes was assessed through weighted gene coexpression network analysis (WGCNA).ConclusionsThis study demonstrates that untargeted lipidomics assays conducted on breast tissue samples from patients with NPM exhibit noteworthy alterations in lipidomes. The findings of this study highlight the substantial involvement of arachidonic acid metabolism in lipid metabolism within the context of NPM. Consequently, this study offers valuable insights that can contribute to a more comprehensive comprehension of NPM in subsequent investigations.Trial registrationShuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine (Number: 2019-702-57; Date: July 2019).
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Project description:Background and Aims: The diagnosis of Wilson's disease (WD) is challenging by clinical or genetic criteria. A typical early pathological change of WD is the increased liver lipid deposition and lowered serum triglyceride (TG). Therefore, the contents of serum lipids may provide evidence for screening of biomarkers for WD. Methods: 34 WD patients, 31 WD relatives, and 65 normal controls were enrolled in this study. Serum lipidomics data was acquired by an ultra-high-performance liquid chromatography high-resolution mass spectrometry system, and the data were analyzed by multivariate statistical methods. Results: Of all 510 identified lipids, there are 297 differential lipids between the WD and controls, 378 differential lipids between the relatives and controls, and 119 differential lipids between the patients and relatives. In WD, the abundances of most saturated TG were increased, whereas other unsaturated lipids decreased, including phosphatidylcholine (PC), sphingomyelin (SM), lysophosphatidylcholine (LPC), ceramide (Cer), and phosphatidylserine (PS). We also found many serum lipid species may be used as biomarkers for WD. The areas under the receiver operating characteristic curve (AUC) of PS (35:0), PS (38:5), and PS (34:0) were 0.919, 0.843, and 0.907. The AUCs of TG (38:0) and CerG1 (d42:2) were 0.948 and 0.915 and the AUCs of LPC (17:0) and LPC (15:0) were 0.980 and 0.960, respectively. The lipid biomarker panel exhibits good diagnostic performance for WD. The correlation networks were built among the different groups and the potential mechanisms of differential lipids were discussed. Interestingly, similar lipid profile of WD is also found in their relatives, which indicated the changes may also related to the mutation of the ATP7B gene. Conclusions: Lipid deregulation is another important hallmark of WD besides the deposition of copper. Our lipidomic results provide new insights into the diagnostic and therapeutic targets of WD.
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Project description:Objective Central precocious puberty (CPP) is a rare condition that causes early sexual development in children. Although the cure is effective, the etiology of central precocious puberty is unclear. Methods In total, 10 girls with central precocious puberty and same number of age-matched female controls were enrolled. Plasma samples were collected from each participant and subjected to untargeted metabolomics and lipidomics. Student's t-tests were employed to compare the mean of each metabolite and lipid. Furthermore, orthogonal partial least-squares discriminant analysis was conducted and the variable importance in the projection was calculated to identify differentially expressed metabolites or lipids. Subsequent bioinformatics was conducted to investigate the potential function of differentially expressed metabolites and lipids. Results Fifty-nine differentially expressed metabolites were identified based on the criteria used (variable importance in the projection >1 and a P value < 0.05). Kyoto Encyclopedia Genes and Genome (KEGG) enrichment analysis showed that differentially expressed metabolites were enriched in four pathways: beta-alanine metabolism, histidine metabolism, bile secretion, and steroid hormone biosynthesis. As for the lipidomics, 41 differentially expressed lipids were observed and chain length analysis and lipid saturation analysis yielded similar results. Significant differences between the two groups were only observed in (O-acyl) ω-hydroxy fatty acids (OAHFA). Conclusion The present study showed that antibiotic overuse, increased meat consumption, and obesity may have potential roles in the development of central precocious puberty in girls. Several metabolites have diagnostic value but further research is required.
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Project description:Illuminating the comprehensive lipid profiles after dietary supplementation of polyunsaturated fatty acids (PUFAs) is crucial to revealing the tissue distribution of PUFAs in living organisms, as well as to providing novel insights into lipid metabolism. Here, we performed lipidomic analyses on mouse plasma and nine tissues, including the liver, kidney, brain, white adipose, heart, lung, small intestine, skeletal muscle, and spleen, with the dietary intake conditions of arachidonic acid (ARA), eicosapentaenoic acid (EPA), and docosahexaenoic acid (DHA) as the ethyl ester form. We incorporated targeted and untargeted approaches for profiling oxylipins and complex lipids such as glycerol (phospho) lipids, sphingolipids, and sterols, respectively, which led to the characterization of 1026 lipid molecules from the mouse tissues. The lipidomic analysis indicated that the intake of PUFAs strongly impacted the lipid profiles of metabolic organs such as the liver and kidney, while causing less impact on the brain. Moreover, we revealed a unique lipid modulation in most tissues, where phospholipids containing linoleic acid were significantly decreased in mice on the ARA-supplemented diet, and bis(monoacylglycero)phosphate (BMP) selectively incorporated DHA over ARA and EPA. We comprehensively studied the lipid profiles after dietary intake of PUFAs, which gives insight into lipid metabolism and nutrition research on PUFA supplementation.
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Project description:COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease's severity and patient's outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639-0.904) and outcome (AUC= 0.789, CI: 0.658-0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.
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