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Glycoproteins play important roles in numerous physiological processes and are often implicated in disease. Analysis of site-specific protein glycobiology through glycoproteomics has evolved rapidly in recent years thanks to hardware and software innovations. Particularly, the introduction of parallel accumulation serial fragmentation (PASEF) on hybrid trapped ion mobility time-of-flight mass spectrometry instruments combined deep proteome sequencing with separation of (near-)isobaric precursor ions or converging isotope envelopes through ion mobility separation. However, the reported use of PASEF in integrated glycoproteomics workflows to comprehensively capture the glycoproteome is still limited. To this end, we developed an integrated methodology using timsTOF Pro 2 to enhance N-glycopeptide identifications in complex mixtures. We systematically optimized the ion optics tuning, collision energies, mobility isolation width, and the use of dopant-enriched nitrogen gas (DEN). Thus, we obtained a marked increase in unique glycopeptide identification rates compared to standard proteomics settings, showcasing our results on a large set of glycopeptides. With short liquid chromatography gradients of 30 min, we increased the number of unique N-glycopeptide identifications in human plasma samples from around 100 identifications under standard proteomics conditions to up to 1500 with our optimized glycoproteomics approach, highlighting the need for tailored optimizations to obtain comprehensive data.
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Glicopeptídeos , Proteômica , Proteômica/métodos , Humanos , Glicopeptídeos/análise , Glicopeptídeos/química , Glicopeptídeos/sangue , Fluxo de Trabalho , Glicoproteínas/análise , Glicoproteínas/química , Glicoproteínas/sangue , Cromatografia Líquida , Espectrometria de Massas em TandemRESUMO
Research data is accumulating rapidly and with it the challenge of fully reproducible science. As a consequence, implementation of high-quality management of scientific data has become a global priority. The FAIR (Findable, Accesible, Interoperable and Reusable) principles provide practical guidelines for maximizing the value of research data; however, processing data using workflows-systematic executions of a series of computational tools-is equally important for good data management. The FAIR principles have recently been adapted to Research Software (FAIR4RS Principles) to promote the reproducibility and reusability of any type of research software. Here, we propose a set of 10 quick tips, drafted by experienced workflow developers that will help researchers to apply FAIR4RS principles to workflows. The tips have been arranged according to the FAIR acronym, clarifying the purpose of each tip with respect to the FAIR4RS principles. Altogether, these tips can be seen as practical guidelines for workflow developers who aim to contribute to more reproducible and sustainable computational science, aiming to positively impact the open science and FAIR community.
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OBJECTIVES: Minimal residual disease status in multiple myeloma is an important prognostic biomarker. Recently, personalized blood-based targeted mass spectrometry (MS-MRD) was shown to provide a sensitive and minimally invasive alternative to measure minimal residual disease. However, quantification of MS-MRD requires a unique calibrator for each patient. The use of patient-specific stable isotope labelled (SIL) peptides is relatively costly and time-consuming, thus hindering clinical implementation. Here, we introduce a simplification of MS-MRD by using an off-the-shelf calibrator. METHODS: SILuMAB-based MS-MRD was performed by spiking a monoclonal stable isotope labeled IgG, SILuMAB-K1, in the patient serum. The abundance of both M-protein-specific peptides and SILuMAB-specific peptides were monitored by mass spectrometry. The relative ratio between M-protein peptides and SILuMAB peptides allowed for M-protein quantification. We assessed linearity, sensitivity and reproducibility of SILuMAB-based MS-MRD in longitudinally collected sera from the IFM-2009 clinical trial. RESULTS: A linear dynamic range was achieved of over 5 log scales, allowing for M-protein quantification down to 0.001â¯g/L. The inter-assay CV of SILuMAB-based MS-MRD was on average 11â¯%. Excellent concordance between SIL- and SILuMAB-based MS-MRD was shown (R2>0.985). Additionally, signal intensity of spiked SILuMAB can be used for quality control purpose to assess system performance and incomplete SILuMAB digestion can be used as quality control for sample preparation. CONCLUSIONS: Compared to SIL peptides, SILuMAB-based MS-MRD improves the reproducibility, turn-around-times and cost-efficacy of MS-MRD without diminishing its sensitivity and specificity. Furthermore, SILuMAB can be used as a MS-MRD quality control tool to monitor sample preparation efficacy and assay performance.
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Mieloma Múltiplo , Humanos , Mieloma Múltiplo/diagnóstico , Neoplasia Residual , Reprodutibilidade dos Testes , Espectrometria de Massas/métodos , Peptídeos , IsótoposRESUMO
OBJECTIVES: Minimal residual disease (MRD) status in multiple myeloma (MM) is an important prognostic biomarker. Personalized blood-based targeted mass spectrometry detecting M-proteins (MS-MRD) was shown to provide a sensitive and minimally invasive alternative to MRD-assessment in bone marrow. However, MS-MRD still comprises of manual steps that hamper upscaling of MS-MRD testing. Here, we introduce a proof-of-concept for a novel workflow using data independent acquisition-parallel accumulation and serial fragmentation (dia-PASEF) and automated data processing. METHODS: Using automated data processing of dia-PASEF measurements, we developed a workflow that identified unique targets from MM patient sera and personalized protein sequence databases. We generated patient-specific libraries linked to dia-PASEF methods and subsequently quantitated and reported M-protein concentrations in MM patient follow-up samples. Assay performance of parallel reaction monitoring (prm)-PASEF and dia-PASEF workflows were compared and we tested mixing patient intake sera for multiplexed target selection. RESULTS: No significant differences were observed in lowest detectable concentration, linearity, and slope coefficient when comparing prm-PASEF and dia-PASEF measurements of serial dilutions of patient sera. To improve assay development times, we tested multiplexing patient intake sera for target selection which resulted in the selection of identical clonotypic peptides for both simplex and multiplex dia-PASEF. Furthermore, assay development times improved up to 25× when measuring multiplexed samples for peptide selection compared to simplex. CONCLUSIONS: Dia-PASEF technology combined with automated data processing and multiplexed target selection facilitated the development of a faster MS-MRD workflow which benefits upscaling and is an important step towards the clinical implementation of MS-MRD.
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Mieloma Múltiplo , Neoplasia Residual , Fluxo de Trabalho , Humanos , Mieloma Múltiplo/diagnóstico , Mieloma Múltiplo/sangue , Neoplasia Residual/diagnóstico , Ensaios de Triagem em Larga Escala/métodos , Medicina de Precisão/métodos , AutomaçãoRESUMO
OBJECTIVES: Multiple myeloma (MM) is a plasma cell malignancy characterized by a monoclonal expansion of plasma cells that secrete a characteristic M-protein. This M-protein is crucial for diagnosis and monitoring of MM in the blood of patients. Recent evidence has emerged suggesting that N-glycosylation of the M-protein variable (Fab) region contributes to M-protein pathogenicity, and that it is a risk factor for disease progression of plasma cell disorders. Current methodologies lack the specificity to provide a site-specific glycoprofile of the Fab regions of M-proteins. Here, we introduce a novel glycoproteogenomics method that allows detailed M-protein glycoprofiling by integrating patient specific Fab region sequences (genomics) with glycoprofiling by glycoproteomics. METHODS: Glycoproteogenomics was used for the detailed analysis of de novo N-glycosylation sites of M-proteins. First, Genomic analysis of the M-protein variable region was used to identify de novo N-glycosylation sites. Subsequently glycopeptide analysis with LC-MS/MS was used for detailed analysis of the M-protein glycan sites. RESULTS: Genomic analysis uncovered a more than two-fold increase in the Fab Light Chain N-glycosylation of M-proteins of patients with Multiple Myeloma compared to Fab Light Chain N-glycosylation of polyclonal antibodies from healthy individuals. Subsequent glycoproteogenomics analysis of 41 patients enrolled in the IFM 2009 clinical trial revealed that the majority of the Fab N-glycosylation sites were fully occupied with complex type glycans, distinguishable from Fc region glycans due to high levels of sialylation, fucosylation and bisecting structures. CONCLUSIONS: Together, glycoproteogenomics is a powerful tool to study de novo Fab N-glycosylation in plasma cell dyscrasias.
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Mieloma Múltiplo , Humanos , Mieloma Múltiplo/metabolismo , Mieloma Múltiplo/genética , Mieloma Múltiplo/diagnóstico , Glicosilação , Proteômica/métodos , Espectrometria de Massas em Tandem , Glicoproteínas/metabolismo , Cromatografia Líquida , Proteínas do Mieloma/metabolismo , Proteínas do Mieloma/análiseRESUMO
Real-time database searching allows for simpler and automated proteomics workflows as it eliminates technical bottlenecks in high-throughput experiments. Most importantly, it enables results-dependent acquisition (RDA), where search results can be used to guide data acquisition during acquisition. This is especially beneficial for glycoproteomics since the wide range of physicochemical properties of glycopeptides lead to a wide range of optimal acquisition parameters. We established here the GlycoPaSER prototype by extending the Parallel Search Engine in Real-time (PaSER) functionality for real-time glycopeptide identification from fragmentation spectra. Glycopeptide fragmentation spectra were decomposed into peptide and glycan moiety spectra using common N-glycan fragments. Each moiety was subsequently identified by a specialized algorithm running in real-time. GlycoPaSER can keep up with the rate of data acquisition for real-time analysis with similar performance to other glycoproteomics software and produces results that are in line with the literature reference data. The GlycoPaSER prototype presented here provides the first proof-of-concept for real-time glycopeptide identification that unlocks the future development of RDA technology to transcend data acquisition.
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Glicopeptídeos , Ferramenta de Busca , Sequência de Aminoácidos , Glicopeptídeos/química , Glicosilação , Software , Polissacarídeos/químicaRESUMO
Population-scale expression profiling studies can provide valuable insights into biological and disease-underlying mechanisms. The availability of phenotypic traits is essential for studying clinical effects. Therefore, missing, incomplete, or inaccurate phenotypic information can make analyses challenging and prevent RNA-seq or other omics data to be reused. A possible solution are predictors that infer clinical or behavioral phenotypic traits from molecular data. While such predictors have been developed based on different omics data types and are being applied in various studies, metabolomics-based surrogates are less commonly used than predictors based on DNA methylation profiles.In this study, we inferred 17 traits, including diabetes status and exposure to lipid medication, using previously trained metabolomic predictors. We evaluated whether these metabolomic surrogates can be used as an alternative to reported information for studying the respective phenotypes using expression profiling data of four population cohorts. For the majority of the 17 traits, the metabolomic surrogates performed similarly to the reported phenotypes in terms of effect sizes, number of significant associations, replication rates, and significantly enriched pathways.The application of metabolomics-derived surrogate outcomes opens new possibilities for reuse of multi-omics data sets. In studies where availability of clinical metadata is limited, missing or incomplete information can be complemented by these surrogates, thereby increasing the size of available data sets. Additionally, the availability of such surrogates could be used to correct for potential biological confounding. In the future, it would be interesting to further investigate the use of molecular predictors across different omics types and cohorts.
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Metabolômica , FenótipoRESUMO
Because positron emission tomography (PET) and optical imaging are very complementary, the combination of these two imaging modalities is very enticing in the oncology field. Such bimodal imaging generally relies on imaging agents bearing two different imaging reporters. In the bioconjugation field, this is mainly performed by successive random conjugations of the two reporters on the protein vector, but these random conjugations can alter the vector properties. In this study, we aimed at abrogating the heterogeneity of the bimodal imaging immunoconjugate and mitigating the impact of multiple random conjugations. A trivalent platform bearing a DFO chelator for 89Zr labeling, a NIR fluorophore, IRDye800CW, and a bioconjugation handle was synthesized. This bimodal probe was site-specifically grafted to trastuzumab via glycan engineering. This new bimodal immunoconjugate was then investigated in terms of radiochemistry, in vitro and in vivo, and compared to the clinically relevant random equivalent. In vitro and in vivo, our strategy provides several improvements over the current clinical standard. The combination of site-specific conjugation with the monomolecular platform reduced the heterogeneity of the final immunoconjugate, improved the resistance of the fluorophore toward radiobleaching, and reduced the nonspecific uptake in the spleen and liver compared to the standard random immunoconjugate. To conclude, the strategy developed is very promising for the synthesis of better defined dual-labeled immunoconjugates, although there is still room for improvement. Importantly, this conjugation strategy is highly modular and could be used for the synthesis of a wide range of dual-labeled immunoconjugates.
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Imunoconjugados , Neoplasias , Linhagem Celular Tumoral , Corantes Fluorescentes/química , Humanos , Imunoconjugados/química , Tomografia por Emissão de Pósitrons/métodos , Radioisótopos/química , Distribuição Tecidual , Zircônio/químicaRESUMO
Many patients with primary focal segmental glomerulosclerosis (FSGS) develop recurrence of proteinuria after kidney transplantation. Several circulating permeability factors (CPFs) responsible for recurrence have been suggested, but were never validated. We aimed to find proteins involved in the mechanism of action of CPF(s) and/or potential biomarkers for the presence of CPF(s). Cultured human podocytes were exposed to plasma from patients with FSGS with presumed CPF(s) or healthy and disease controls. Podocyte proteomes were analyzed by LC-MS. Results were validated using flow cytometry, RT-PCR, and immunofluorescence. Podocyte granularity was examined using flow cytometry, electron microscopy imaging, and BODIPY staining. Perilipin-2 protein expression was increased in podocytes exposed to presumed CPF-containing plasmas, and correlated with the capacity of plasma to induce podocyte granularity, identified as lipid droplet accumulation. Elevated podocyte perilipin-2 was confirmed at protein and mRNA level and was also detected in glomeruli of FSGS patients whose active disease plasmas induced podocyte perilipin-2 and lipid droplets. Our study demonstrates that presumably, CPF-containing plasmas from FSGS patients induce podocyte lipid droplet accumulation and perilipin-2 expression, identifying perilipin-2 as a potential biomarker. Future research should address the mechanism underlying CPF-induced alterations in podocyte lipid metabolism, which ultimately may result in novel leads for treatment.
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Glomerulosclerose Segmentar e Focal , Podócitos , Humanos , Podócitos/metabolismo , Glomerulosclerose Segmentar e Focal/metabolismo , Perilipina-2/genética , Perilipina-2/metabolismo , Gotículas Lipídicas/metabolismo , Glomérulos Renais/metabolismo , Biomarcadores/metabolismoRESUMO
An effective response to the coronavirus disease 2019 (COVID-19) pandemic requires a better understanding of the biology of the infection and the identification of validated biomarker profiles that would increase the availability, accuracy, and speed of COVID-19 testing. Here, we describe the strategic objectives and action lines of the European Alliance of Medical Research Infrastructures (AMRI), established to improve the research process and tackle challenges related to diagnostic tests and biomarker development. Recommendations include: the creation of a European taskforce for validation of novel diagnostic products, the definition and promotion of criteria for COVID-19 samples biobanking, the identification and validation of biomarkers as clinical endpoints for clinical trials, and the definition of immune biomarker signatures at different stages of the disease. An effective management of the COVID-19 pandemic is possible only if there is a high level of knowledge and coordination between the public and private sectors within a robust quality framework.
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Pesquisa Biomédica , COVID-19 , Bancos de Espécimes Biológicos , Biomarcadores , Teste para COVID-19 , Humanos , Pandemias , SARS-CoV-2RESUMO
BACKGROUND: Due to improved treatment, more patients with multiple myeloma (MM) reach a state of minimal residual disease (MRD). Different strategies for MM MRD monitoring include flow cytometry, allele-specific oligonucleotide-quantitative PCR, next-generation sequencing, and mass spectrometry (MS). The last 3 methods rely on the presence and the stability of a unique immunoglobulin fingerprint derived from the clonal plasma cell population. For MS-MRD monitoring it is imperative that MS-compatible clonotypic M-protein peptides are identified. To support implementation of molecular MRD techniques, we studied the presence and stability of these clonotypic features in the CoMMpass database. METHODS: An analysis pipeline based on MiXCR and HIGH-VQUEST was constructed to identify clonal molecular fingerprints and their clonotypic peptides based on transcriptomic datasets. To determine the stability of the clonal fingerprints, we compared the clonal fingerprints during disease progression for each patient. RESULTS: The analysis pipeline to establish the clonal fingerprint and MS-suitable clonotypic peptides was successfully validated in MM cell lines. In a cohort of 609 patients with MM, we demonstrated that the most abundant clone harbored a unique clonal molecular fingerprint and that multiple unique clonotypic peptides compatible with MS measurements could be identified for all patients. Furthermore, the clonal immunoglobulin gene fingerprints of both the light and heavy chain remained stable during MM disease progression. CONCLUSIONS: Our data support the use of the clonal immunoglobulin gene fingerprints in patients with MM as a suitable MRD target for MS-MRD analyses.
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Genes de Imunoglobulinas/fisiologia , Mieloma Múltiplo , Peptídeos/química , Biomarcadores , Progressão da Doença , Humanos , Mieloma Múltiplo/diagnóstico , Mieloma Múltiplo/genética , Neoplasia Residual/genética , Peptídeos/genéticaRESUMO
BACKGROUND: Minimal residual disease (MRD) status assessed on bone marrow aspirates is a major prognostic biomarker in multiple myeloma (MM). In this study we evaluated blood-based targeted mass spectrometry (MS-MRD) as a sensitive, minimally invasive alternative to measure MM disease activity. METHODS: Therapy response of 41 MM patients in the IFM-2009 clinical trial (NCT01191060) was assessed with MS-MRD on frozen sera and compared to routine state-of-the-art monoclonal protein (M-protein) diagnostics and next-generation sequencing (NGS-MRD) at 2 time points. RESULTS: In all 41 patients we were able to identify clonotypic M-protein-specific peptides and perform serum-based MS-MRD measurements. MS-MRD is significantly more sensitive to detect M-protein compared to either electrophoretic M-protein diagnostics or serum free light chain analysis. The concordance between NGS-MRD and MS-MRD status in 81 paired bone marrow/sera samples was 79%. The 50% progression-free survival (PFS) was identical (49 months) for patients who were either NGS-positive or MS-positive directly after maintenance treatment. The 50% PFS was 69 and 89 months for NGS-negative and MS-negative patients, respectively. The longest 50% PFS (96 months) was observed in patients who were MRD-negative for both methods. MS-MRD relapse during maintenance treatment was significantly correlated to poor PFS (P < 0.0001). CONCLUSIONS: Our data indicate proof-of-principle that MS-MRD evaluation in blood is a feasible, patient friendly alternative to NGS-MRD assessed on bone marrow. Clinical validation of the prognostic value of MS-MRD and its complementary value in MRD-evaluation of patients with MM is warranted in an independent larger cohort.
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Mieloma Múltiplo , Medula Óssea/metabolismo , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Humanos , Espectrometria de Massas , Mieloma Múltiplo/diagnóstico , Mieloma Múltiplo/tratamento farmacológico , Mieloma Múltiplo/genética , Neoplasia Residual/diagnósticoRESUMO
INTRODUCTION: The importance of biomarkers for pharmaceutical drug development and clinical diagnostics is more significant than ever in the current shift toward personalized medicine. Biomarkers have taken a central position either as companion markers to support drug development and patient selection, or as indicators aiming to detect the earliest perturbations indicative of disease, minimizing therapeutic intervention or even enabling disease reversal. Protein biomarkers are of particular interest given their central role in biochemical pathways. Hence, capabilities to analyze multiple protein biomarkers in one assay are highly interesting for biomedical research. AREAS COVERED: We here review multiple methods that are suitable for robust, high throughput, standardized, and affordable analysis of protein biomarkers in a multiplex format. We describe innovative developments in immunoassays, the vanguard of methods in clinical laboratories, and mass spectrometry, increasingly implemented for protein biomarker analysis. Moreover, emerging techniques are discussed with potentially improved protein capture, separation, and detection that will further boost multiplex analyses. EXPERT COMMENTARY: The development of clinically applied multiplex protein biomarker assays is essential as multi-protein signatures provide more comprehensive information about biological systems than single biomarkers, leading to improved insights in mechanisms of disease, diagnostics, and the effect of personalized medicine.
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Biomarcadores/química , Proteômica/métodos , Animais , Biomarcadores/análise , Humanos , Imunoensaio/métodos , Espectrometria de Massas/métodosRESUMO
INTRODUCTION: Assessing the specificity of protein binders is an essential first step in protein biomarker assay development. Affimers are novel protein binders and can potentially replace antibodies in multiple protein capture-based assays. Affimers are selected for their high specificity against the target protein and have benefits over antibodies like batch-to-batch reproducibility and are stable across a wide range of chemical conditions. Here we mimicked a typical initial screening of affimers and commercially available monoclonal antibodies against two non-related proteins, IL-37b and proinsulin, to assess the potential of affimers as alternative to antibodies. METHODS: Binding specificity of anti-IL-37b and anti-proinsulin affimers and antibodies was investigated via magnetic bead-based capture of their recombinant protein targets in human plasma. Captured proteins were analyzed using SDS-PAGE, Coomassie blue staining, Western blotting and LC-MS/MS-based proteomics. RESULTS: All affimers and antibodies were able to bind their target protein in human plasma. Gel and LC-MS/MS analysis showed that both affimer and antibody-based captures resulted in co-purified background proteins. However, affimer-based captures showed the highest relative enrichment of IL-37b and proinsulin. CONCLUSIONS: For both proteins tested, affimers show higher specificity in purifying their target proteins from human plasma compared to monoclonal antibodies. These results indicate that affimers are promising antibody-replacement tools for protein biomarker assay development.
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Materiais Biomiméticos/química , Interleucina-1 , Proinsulina , Biomarcadores , Humanos , Interleucina-1/antagonistas & inibidores , Interleucina-1/química , Proinsulina/antagonistas & inibidores , Proinsulina/química , Proteínas Recombinantes/biossíntese , Proteínas Recombinantes/química , Proteínas Recombinantes/isolamento & purificaçãoRESUMO
AIM: To investigate whether a history of severe hypoglycaemia (SH) or the associated presence of impaired awareness of hypoglycaemia (IAH) is characterized by a pro-inflammatory profile in people with type 1 diabetes. RESEARCH DESIGN AND METHODS: We measured circulating inflammatory markers and pro- and anti-inflammatory cytokine production after ex vivo stimulation of peripheral blood mononuclear cells (PBMCs) in a well-characterized cohort of individuals with type 1 diabetes (n = 239) and in people without diabetes (n = 56). Data were corrected for confounders by using multivariate linear regression models. RESULTS: People with type 1 diabetes had higher circulating concentrations of high-sensitivity C-reactive protein (hs-CRP; 0.91 [0.36-2.25] vs. 0.52 [0.20-0.98] pg/mL, P < 0.001 and interleukin-18-binding protein (IL-18BP; 1746 [1304-2112] vs. 1381 [1191-1807] pg/mL; P = 0.001) than those without diabetes. In multivariate analysis, only higher hs-CRP concentrations persisted. Neither circulating immune cells nor ex vivo cytokine levels produced by PBMCs in response to an extensive panel of stimuli differed in groups defined by awareness state or a history of SH, apart from elevated IL-18BP in people with, versus those without, history of SH (1524 [1227-1903] vs. 1913 [1459-2408] pg/mL; P < 0.001). CONCLUSIONS: IAH or history of SH in people with type 1 diabetes was not associated with altered inflammatory profiles, arguing against chronically elevated inflammatory activity mediating the increased cardiovascular risk associated with hypoglycaemia. The finding of higher circulating concentrations of IL-18BP in individuals with a history of SH requires further investigation.
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Diabetes Mellitus Tipo 1 , Hipoglicemia , Conscientização , Estudos de Coortes , Diabetes Mellitus Tipo 1/complicações , Humanos , Hipoglicemia/induzido quimicamente , Leucócitos MononuclearesRESUMO
BACKGROUND: Parkinson's disease (PD) and atypical parkinsonisms (APD) have overlapping symptoms challenging an early diagnosis. Diagnostic accuracy is important because PD and APD have different prognosis and response to treatment. We aimed to identify diagnostic inflammatory biomarkers of PD and APD in cerebrospinal fluid (CSF) using the multiplex proximity extension assay (PEA) technology and to study possible correlations of biomarkers with disease progression. METHODS: CSF from a longitudinal cohort study consisting of PD and APD patients (PD, n = 44; multiple system atrophy (MSA), n = 14; vascular parkinsonism (VaP), n = 9; and PD with VaP, n = 7) and controls (n = 25) were analyzed. RESULTS: Concentrations of CCL28 were elevated in PD compared to controls (p = 0.0001). Five other biomarkers differentiated both MSA and PD from controls (p < 0.05) and 10 biomarkers differentiated MSA from controls, of which two proteins, i.e. beta nerve growth factor (ß-NGF) and Delta and Notch like epidermal growth factor-related receptor (DNER), were also present at lower levels in MSA compared to PD (both p = 0.032). Two biomarkers (MCP-1 and MMP-10) positively correlated with PD progression (rho > 0.650; p < 0.01). CONCLUSIONS: PEA technique identified potential new CSF biomarkers to help to predict the prognosis of PD. Also, we identified new candidate biomarkers to distinguish MSA from PD.
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Biomarcadores/líquido cefalorraquidiano , Transtornos Parkinsonianos/líquido cefalorraquidiano , Idoso , Estudos de Coortes , Feminino , Humanos , Estudos Longitudinais , Masculino , Pessoa de Meia-Idade , Atrofia de Múltiplos Sistemas/líquido cefalorraquidiano , Atrofia de Múltiplos Sistemas/diagnóstico , Doença de Parkinson/líquido cefalorraquidiano , Doença de Parkinson/diagnóstico , Transtornos Parkinsonianos/diagnósticoRESUMO
BACKGROUND: Overweight and obesity can lead to adipose tissue inflammation, which causes insulin resistance and on the long-term type 2 diabetes mellitus (T2D). The inflammatory changes of obese-adipose tissue are characterized by macrophage infiltration and activation, but validated circulating biomarkers for adipose tissue inflammation for clinical use are still lacking. One of the most secreted enzymes by activated macrophages is chitotriosidase (CHIT1). OBJECTIVE: To test whether circulating CHIT1 enzymatic activity levels reflect adipose tissue inflammation. METHODS: Plasma and adipose tissue samples of 105 subjects (35 lean, 37 overweight, and 33 T2D patients) were investigated. CHIT1 mRNA levels were determined in adipose tissue-resident innate immune cells. CHIT1 mRNA levels, protein abundance, and plasma enzymatic activity were subsequently measured in adipose tissue biopsies and plasma of control subjects with varying levels of obesity and adipose tissue inflammation as well as in T2D patients. RESULTS: In adipose tissue, CHIT1 mRNA levels were higher in stromal vascular cells compared to adipocytes, and higher in adipose tissue-residing macrophages compared to circulating monocytes (p < 0.001). CHIT1 mRNA levels in adipose tissue were enhanced in overweightcompared to lean subjects and even more in T2D patients (p < 0.05). In contrast, plasma CHIT1 enzymatic activity did not differ between lean, overweight subjects and T2D patients. A mutation of the CHIT1 gene decreases plasma CHIT1 activity. CONCLUSIONS: CHIT1 is expressed by adipose tissue macrophages and expression is higher in overweight subjects and T2D patients, indicating its potential as tissue biomarker for adipose tissue inflammation. However, these differences do not translate into different plasma CHIT1 activity levels. Moreover, a common CHIT1 gene mutation causing loss of plasma CHIT1 activity interferes with its use as a biomarker of adipose tissue inflammation. These results indicate that plasma CHIT1 activity is of limited value as a circulating biomarker for adipose tissue inflammation in human subjects.
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Tecido Adiposo/química , Diabetes Mellitus Tipo 2/complicações , Hexosaminidases , Inflamação , Sobrepeso/complicações , Idoso , Biomarcadores/sangue , Feminino , Hexosaminidases/análise , Hexosaminidases/genética , Hexosaminidases/metabolismo , Humanos , Inflamação/sangue , Inflamação/complicações , Inflamação/diagnóstico , Masculino , Pessoa de Meia-Idade , RNA Mensageiro/análiseRESUMO
INTRODUCTION: The onset of type 2 diabetes mellitus (T2DM) is strongly associated with obesity and subsequent perturbations in immuno-metabolic responses. To understand the complexity of these systemic changes and better monitor the health status of people at risk, validated clinical biomarkers are needed. Omics technologies are increasingly applied to measure the interplay of genes, proteins and metabolites in biological systems, which is imperative in understanding molecular mechanisms of disease and selecting the best possible molecular biomarkers for clinical use. Areas covered: This review describes the complex onset of T2DM, the contribution of obesity and adipose tissue inflammation to the T2DM disease mechanism, and the output of current biomarker strategies. A new biomarker approach is described that combines published and new self-generated data to merge multiple -omes (i.e. genome, proteome, metabolome etc.) toward understanding of mechanism of disease on the individual level and design multiparameter biomarker panels that drive significant impacts on personalized healthcare. Expert commentary: We here propose an approach to use cross-omics analyses to contextualize published biomarker data and better understand molecular mechanisms of health and disease. This will improve the current and future innovation gaps in translation of discovered putative biomarkers to clinically applicable biomarker tests.
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Biomarcadores/metabolismo , Diabetes Mellitus Tipo 2/metabolismo , Biomarcadores/sangue , Diabetes Mellitus Tipo 2/genética , Diabetes Mellitus Tipo 2/patologia , Humanos , Pesquisa Translacional Biomédica/métodosRESUMO
Background Choosing which biomarker tests to select for further research and development is not only a matter of diagnostic accuracy, but also of the clinical and monetary benefits downstream. Early health economic modeling provides tools to assess the potential effects of biomarker innovation and support decision-making. Methods We applied early health economic modeling to the case of diagnosing primary aldosteronism in patients with resistant hypertension. We simulated a cohort of patients using a Markov cohort state-transition model. Using the headroom method, we compared the currently used aldosterone-to-renin ratio to a hypothetical new test with perfect diagnostic properties to determine the headroom based on quality-adjusted life-years (QALYs) and costs, followed by threshold analyses to determine the minimal diagnostic accuracy for a cost-effective product. Results Our model indicated that a perfect diagnostic test would yield 0.027 QALYs and increase costs by 43 per patient. At a cost-effectiveness threshold of 20,000 per QALY, the maximum price for this perfect test to be cost-effective is 498 (95% confidence interval [CI]: 275-808). The value of the perfect test was most strongly influenced by the sensitivity of the current biomarker test. Threshold analysis showed the novel test needs a sensitivity of at least 0.9 and a specificity of at least 0.7 to be cost-effective. Conclusions Our model-based approach evaluated the added value of a clinical biomarker innovation, prior to extensive investment in development, clinical studies and implementation. We conclude that early health economic modeling can be a valuable tool when prioritizing biomarker innovations in the laboratory.
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Biomarcadores/química , Adulto , Feminino , Humanos , MasculinoRESUMO
BACKGROUND: Applying good data management and FAIR (Findable, Accessible, Interoperable, and Reusable) data principles in research projects can help disentangle knowledge discovery, study result reproducibility, and data reuse in future studies. Based on the concepts of the original FAIR principles for research data, FAIR principles for research software were recently proposed. FAIR Digital Objects enable discovery and reuse of Research Objects, including computational workflows for both humans and machines. Practical examples can help promote the adoption of FAIR practices for computational workflows in the research community. We developed a multi-omics data analysis workflow implementing FAIR practices to share it as a FAIR Digital Object. FINDINGS: We conducted a case study investigating shared patterns between multi-omics data and childhood externalizing behavior. The analysis workflow was implemented as a modular pipeline in the workflow manager Nextflow, including containers with software dependencies. We adhered to software development practices like version control, documentation, and licensing. Finally, the workflow was described with rich semantic metadata, packaged as a Research Object Crate, and shared via WorkflowHub. CONCLUSIONS: Along with the packaged multi-omics data analysis workflow, we share our experiences adopting various FAIR practices and creating a FAIR Digital Object. We hope our experiences can help other researchers who develop omics data analysis workflows to turn FAIR principles into practice.