Publications
49 results found
Alexander J, Powell N, Marchesi J, et al., 2023, Considerations for peripheral blood transport and storage during large-scale multicentre metabolome research, Gut, Pages: 1-4, ISSN: 0017-5749
Harvey N, Takis PG, Lindon JC, et al., 2023, Optimization of diffusion-ordered NMR spectroscopy experiments for high-throughput automation in human metabolic phenotyping, Analytical Chemistry, Vol: 95, Pages: 3147-3152, ISSN: 0003-2700
The diffusion-ordered nuclear magnetic resonance spectroscopy (DOSY) experiment allows the calculation of diffusion coefficient values of metabolites in complex mixtures. However, this experiment has not yet been broadly used for metabolic profiling due to lack of a standardized protocol. Here we propose a pipeline for the DOSY experimental setup and data processing in metabolic phenotyping studies. Due to the complexity of biological samples, three experiments (a standard DOSY, a relaxation-edited DOSY, and a diffusion-edited DOSY) have been optimized to provide DOSY metabolic profiles with peak-picked diffusion coefficients for over 90% of signals visible in the one-dimensional 1H general biofluid profile in as little as 3 min 36 s. The developed parameter sets and tools are straightforward to implement and can facilitate the use of DOSY for metabolic profiling of human blood plasma and urine samples.
Stebbing J, Takis PG, Sands CJ, et al., 2023, Comparison of phenomics and cfDNA in a large breast screening population: the Breast Screening and Monitoring Study (BSMS), Oncogene, Pages: 1-8, ISSN: 0950-9232
To assess their roles in breast cancer diagnostics, we aimed to compare plasma cell-free DNA (cfDNA) levels with the circulating metabolome in a large breast screening cohort of women recalled for mammography, including healthy women and women with mammographically detected breast diseases, ductal carcinoma in situ and invasive breast cancer: the Breast Screening and Monitoring Study (BSMS). In 999 women, plasma was analyzed by nuclear magnetic resonance (NMR) and Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and then processed to isolate and quantify total cfDNA. NMR and UPLC-MS results were compared with data for 186 healthy women derived from the AIRWAVE cohort. Results showed no significant differences between groups for all metabolites, whereas invasive cancers had significantly higher plasma cfDNA levels than all other groups. When stratified the supervised OPLS-DA analysis and total cfDNA concentration showed high discrimination accuracy between invasive cancers and the disease/medication-free subjects. Furthermore, comparison of OPLS-DA data for invasive breast cancers with the AIRWAVE cohort showed similar discrimination between breast cancers and healthy controls. This is the first report of agreement between metabolomics and plasma cfDNA levels for discriminating breast cancer from healthy subjects in a true screening population. It also emphasizes the importance of sample standardization. Follow on studies will involve analysis of candidate features in a larger validation series as well as comparing results with serial plasma samples taken at the next routine screening mammography appointment. The findings here help establish the role of plasma analysis in the diagnosis of breast cancer in a large real-world cohort.
Augustin A, Le Guennec A, Umamahesan C, et al., 2023, Faecal metabolite deficit, gut inflammation and diet in Parkinson’s disease: integrative analysis indicates inflammatory response syndrome, Clinical and Translational Medicine, Vol: 13, ISSN: 2001-1326
Background:Gut-brain axis is widely implicated in the pathophysiology of Parkinson's disease (PD). We take an integrated approach to considering the gut as a target for disease-modifying intervention, using continuous measurements of disease facets irrespective of diagnostic divide.Methods:We characterised 77 participants with diagnosed-PD, 113 without, by dietary/exogenous substance intake, faecal metabolome, intestinal inflammation, serum cytokines/chemokines, clinical phenotype including colonic transit time. Complete-linkage hierarchical cluster analysis of metabolites discriminant for PD-status was performed.Results:Longer colonic transit was linked to deficits in faecal short-chain-fatty acids outside PD, to a ‘tryptophan-containing metabolite cluster’ overall. Phenotypic cluster analysis aggregated colonic transit with brady/hypokinesia, tremor, sleep disorder and dysosmia, each individually associated with tryptophan-cluster deficit. Overall, a faster pulse was associated with deficits in a metabolite cluster including benzoic acid and an imidazole-ring compound (anti-fungals) and vitamin B3 (anti-inflammatory) and with higher serum CCL20 (chemotactic for lymphocytes/dendritic cells towards mucosal epithelium). The faster pulse in PD was irrespective of postural hypotension. The benzoic acid-cluster deficit was linked to (well-recognised) lower caffeine and alcohol intakes, tryptophan-cluster deficit to higher maltose intake. Free-sugar intake was increased in PD, maltose intake being 63% higher (p = .001). Faecal calprotectin was 44% (95% CI 5%, 98%) greater in PD [p = .001, adjusted for proton-pump inhibitors (p = .001)], with 16% of PD-probands exceeding a cut-point for clinically significant inflammation compatible with inflammatory bowel disease. Higher maltose intake was associated with exceeding this calprotectin cut-point.Conclusions:Emerging picture is of (i) clinical phenotype being described by deficits in microbial metabolites essenti
Liew F, Talwar S, Cross A, et al., 2023, SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination, EBioMedicine, Vol: 87, Pages: 1-14, ISSN: 2352-3964
Background:Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced.Methods:In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data.Findings:Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination.Interpretation:The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity.Funding:This
Mullish BH, 2022, 614 Microbiome modification with fecal microbiota transplant from healthy donors before anti-PD1 therapy reduces primary resistance to immunotherapy in advanced and metastatic melanoma patients, Publisher: BioMed Central, ISSN: 2051-1426
Vink E, Davis C, MacLean A, et al., 2022, Viral coinfections in hospitalized Coronavirus disease 2019 patients recruited to the international severe acute respiratory and emerging infections consortium WHO clinical characterisation protocol UK study, Open Forum Infectious Diseases, Vol: 9, Pages: 1-10, ISSN: 2328-8957
BackgroundWe conducted this study to assess the prevalence of viral coinfection in a well characterized cohort of hospitalized coronavirus disease 2019 (COVID-19) patients and to investigate the impact of coinfection on disease severity.MethodsMultiplex real-time polymerase chain reaction testing for endemic respiratory viruses was performed on upper respiratory tract samples from 1002 patients with COVID-19, aged <1 year to 102 years old, recruited to the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK study. Comprehensive demographic, clinical, and outcome data were collected prospectively up to 28 days post discharge.ResultsA coinfecting virus was detected in 20 (2.0%) participants. Multivariable analysis revealed no significant risk factors for coinfection, although this may be due to rarity of coinfection. Likewise, ordinal logistic regression analysis did not demonstrate a significant association between coinfection and increased disease severity.ConclusionsViral coinfection was rare among hospitalized COVID-19 patients in the United Kingdom during the first 18 months of the pandemic. With unbiased prospective sampling, we found no evidence of an association between viral coinfection and disease severity. Public health interventions disrupted normal seasonal transmission of respiratory viruses; relaxation of these measures mean it will be important to monitor the prevalence and impact of respiratory viral coinfections going forward.
Takis PG, Vuckovic I, Tan T, et al., 2022, NMRpQuant: an automated software for large scale urinary total protein quantification by one-dimensional 1H NMR profiles, Bioinformatics, Vol: 38, Pages: 4437-4439, ISSN: 1367-4803
Summary1H nuclear magnetic resonance (NMR) spectroscopy is an established bioanalytical technology for metabolic profiling of biofluids in both clinical and large-scale population screening applications. Recently, urinary protein quantification has been demonstrated using the same 1D 1H NMR experimental data captured for metabolic profiling. Here, we introduce NMRpQuant, a freely available platform that builds on these findings with both novel and further optimized computational NMR approaches for rigorous, automated protein urine quantification. The results are validated by interlaboratory comparisons, demonstrating agreement with clinical/biochemical methodologies, pointing at a ready-to-use tool for routine protein urinalyses.Availability and implementationNMRpQuant was developed on MATLAB programming environment. Source code and Windows/macOS compiled applications are available at https://github.com/pantakis/NMRpQuant, and working examples are available at https://doi.org/10.6084/m9.figshare.18737189.v1.
Norris T, Razieh C, Zaccardi F, et al., 2022, Impact of cardiometabolic multimorbidity and ethnicity on cardiovascular/renal complications in patients with COVID-19, Heart, Vol: 108, Pages: 1200-1208, ISSN: 1355-6037
Objective Using a large national database of people hospitalised with COVID-19, we investigated the contribution of cardio-metabolic conditions, multi-morbidity and ethnicity on the risk of in-hospital cardiovascular complications and death.Methods A multicentre, prospective cohort study in 302 UK healthcare facilities of adults hospitalised with COVID-19 between 6 February 2020 and 16 March 2021. Logistic models were used to explore associations between baseline patient ethnicity, cardiometabolic conditions and multimorbidity (0, 1, 2, >2 conditions), and in-hospital cardiovascular complications (heart failure, arrhythmia, cardiac ischaemia, cardiac arrest, coagulation complications, stroke), renal injury and death.Results Of 65 624 patients hospitalised with COVID-19, 44 598 (68.0%) reported at least one cardiometabolic condition on admission. Cardiovascular/renal complications or death occurred in 24 609 (38.0%) patients. Baseline cardiometabolic conditions were independently associated with increased odds of in-hospital complications and this risk increased in the presence of cardiometabolic multimorbidity. For example, compared with having no cardiometabolic conditions, 1, 2 or ≥3 conditions was associated with 1.46 (95% CI 1.39 to 1.54), 2.04 (95% CI 1.93 to 2.15) and 3.10 (95% CI 2.92 to 3.29) times higher odds of any cardiovascular/renal complication, respectively. A similar pattern was observed for all-cause death. Compared with the white group, the South Asian (OR 1.19, 95% CI 1.10 to 1.29) and black (OR 1.53 to 95% CI 1.37 to 1.72) ethnic groups had higher risk of any cardiovascular/renal complication.Conclusions In hospitalised patients with COVID-19, cardiovascular complications or death impacts just under half of all patients, with the highest risk in those of South Asian or Black ethnicity and in patients with cardiometabolic multimorbidity.
Chasapi SA, Karagkouni E, Kalavrizioti D, et al., 2022, NMR-based metabolomics in differential diagnosis of Chronic Kidney Disease (CKD) subtypes, Metabolites, Vol: 12, Pages: 1-14, ISSN: 2218-1989
Chronic Kidney Disease (CKD) is considered as a major public health problem as it can lead to end-stage kidney failure, which requires replacement therapy. A prompt and accurate diagnosis, along with the appropriate treatment, can delay CKD’s progression, significantly. Herein, we sought to determine whether CKD etiology can be reflected in urine metabolomics during its early stage. This is achieved through the analysis of the urine metabolic fingerprint from 108 CKD patients by means of Nuclear Magnetic Resonance (NMR) spectroscopy metabolomic analysis. We report the first NMR—metabolomics data regarding the three most common etiologies of CKD: Chronic Glomerulonephritis (IgA and Membranous Nephropathy), Diabetic Nephropathy (DN) and Hypertensive Nephrosclerosis (HN). Analysis aided a moderate glomerulonephritis clustering, providing characterization of the metabolic fluctuations between the CKD subtypes and control disease. The urine metabolome of IgA Nephropathy reveals a specific metabolism, reflecting its different etiology or origin and is useful for determining the origin of the disease. In contrast, urine metabolomes from DN and HN patients did not reveal any indicative metabolic pattern, which is consistent with their fused clinical phenotype. These findings may contribute to improving diagnostics and prognostic approaches for CKD, as well as improving our understanding of its pathology.
Correia GDS, Takis PG, Sands CJ, et al., 2022, 1H NMR Signals from urine excreted protein are a source of bias in probabilistic quotient normalization, Analytical Chemistry, Vol: 94, Pages: 6919-6923, ISSN: 0003-2700
Normalization to account for variation in urinary dilution is crucial for interpretation of urine metabolic profiles. Probabilistic quotient normalization (PQN) is used routinely in metabolomics but is sensitive to systematic variation shared across a large proportion of the spectral profile (>50%). Where 1H nuclear magnetic resonance (NMR) spectroscopy is employed, the presence of urinary protein can elevate the spectral baseline and substantially impact the resulting profile. Using 1H NMR profile measurements of spot urine samples collected from hospitalized COVID-19 patients in the ISARIC 4C study, we determined that PQN coefficients are significantly correlated with observed protein levels (r2 = 0.423, p < 2.2 × 10–16). This correlation was significantly reduced (r2 = 0.163, p < 2.2 × 10–16) when using a computational method for suppression of macromolecular signals known as small molecule enhancement spectroscopy (SMolESY) for proteinic baseline removal prior to PQN. These results highlight proteinuria as a common yet overlooked source of bias in 1H NMR metabolic profiling studies which can be effectively mitigated using SMolESY or other macromolecular signal suppression methods before estimation of normalization coefficients.
Takis P, Vuckovic I, Macura S, 2022, NMRpQuant
NMRpQuant is a freely available software for the automated total urinary protein via 1D 1H NMR urine profiles.(check the associated paper: https://doi.org/10.1093/bioinformatics/btac502)
Närhi F, Moonesinghe SR, Shenkin SD, et al., 2022, Implementation of corticosteroids in treatment of COVID-19 in the ISARIC WHO Clinical Characterisation Protocol UK: prospective, cohort study., The Lancet Digital Health, Vol: 4, Pages: e220-e234, ISSN: 2589-7500
BACKGROUND: Dexamethasone was the first intervention proven to reduce mortality in patients with COVID-19 being treated in hospital. We aimed to evaluate the adoption of corticosteroids in the treatment of COVID-19 in the UK after the RECOVERY trial publication on June 16, 2020, and to identify discrepancies in care. METHODS: We did an audit of clinical implementation of corticosteroids in a prospective, observational, cohort study in 237 UK acute care hospitals between March 16, 2020, and April 14, 2021, restricted to patients aged 18 years or older with proven or high likelihood of COVID-19, who received supplementary oxygen. The primary outcome was administration of dexamethasone, prednisolone, hydrocortisone, or methylprednisolone. This study is registered with ISRCTN, ISRCTN66726260. FINDINGS: Between June 17, 2020, and April 14, 2021, 47 795 (75·2%) of 63 525 of patients on supplementary oxygen received corticosteroids, higher among patients requiring critical care than in those who received ward care (11 185 [86·6%] of 12 909 vs 36 415 [72·4%] of 50 278). Patients 50 years or older were significantly less likely to receive corticosteroids than those younger than 50 years (adjusted odds ratio 0·79 [95% CI 0·70-0·89], p=0·0001, for 70-79 years; 0·52 [0·46-0·58], p<0·0001, for >80 years), independent of patient demographics and illness severity. 84 (54·2%) of 155 pregnant women received corticosteroids. Rates of corticosteroid administration increased from 27·5% in the week before June 16, 2020, to 75-80% in January, 2021. INTERPRETATION: Implementation of corticosteroids into clinical practice in the UK for patients with COVID-19 has been successful, but not universal. Patients older than 70 years, independent of illness severity, chronic neurological disease, and dementia, were less likely to receive corticosteroids than those who were younger, as were pregnant wom
Dejnirattisai W, Huo J, Zhou D, et al., 2022, SARS-CoV-2 Omicron-B.1.1.529 leads to widespread escape from neutralizing antibody responses, Cell, Vol: 185, Pages: 467-484.e15, ISSN: 0092-8674
On 24th November 2021, the sequence of a new SARS-CoV-2 viral isolate Omicron-B.1.1.529 was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titers of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic Alpha, Beta, Gamma, or Delta are substantially reduced, or the sera failed to neutralize. Titers against Omicron are boosted by third vaccine doses and are high in both vaccinated individuals and those infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of the large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses and uses mutations that confer tight binding to ACE2 to unleash evolution driven by immune escape. This leads to a large number of mutations in the ACE2 binding site and rebalances receptor affinity to that of earlier pandemic viruses.
de Silva TI, Liu G, Lindsey BB, et al., 2021, The impact of viral mutations on recognition by SARS-CoV-2 specific T cells., iScience, Vol: 24, Pages: 103353-103353, ISSN: 2589-0042
We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.
Wickenhagen A, Sugrue E, Lytras S, et al., 2021, A prenylated dsRNA sensor protects against severe COVID-19, Science, Vol: 374, Pages: 1-18, ISSN: 0036-8075
Drake TM, Riad AM, Fairfield CJ, et al., 2021, Characterisation of in-hospital complications associated with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, multicentre cohort study, The Lancet, Vol: 398, Pages: 223-237, ISSN: 0140-6736
BACKGROUND: COVID-19 is a multisystem disease and patients who survive might have in-hospital complications. These complications are likely to have important short-term and long-term consequences for patients, health-care utilisation, health-care system preparedness, and society amidst the ongoing COVID-19 pandemic. Our aim was to characterise the extent and effect of COVID-19 complications, particularly in those who survive, using the International Severe Acute Respiratory and Emerging Infections Consortium WHO Clinical Characterisation Protocol UK. METHODS: We did a prospective, multicentre cohort study in 302 UK health-care facilities. Adult patients aged 19 years or older, with confirmed or highly suspected SARS-CoV-2 infection leading to COVID-19 were included in the study. The primary outcome of this study was the incidence of in-hospital complications, defined as organ-specific diagnoses occurring alone or in addition to any hallmarks of COVID-19 illness. We used multilevel logistic regression and survival models to explore associations between these outcomes and in-hospital complications, age, and pre-existing comorbidities. FINDINGS: Between Jan 17 and Aug 4, 2020, 80 388 patients were included in the study. Of the patients admitted to hospital for management of COVID-19, 49·7% (36 367 of 73 197) had at least one complication. The mean age of our cohort was 71·1 years (SD 18·7), with 56·0% (41 025 of 73 197) being male and 81·0% (59 289 of 73 197) having at least one comorbidity. Males and those aged older than 60 years were most likely to have a complication (aged ≥60 years: 54·5% [16 579 of 30 416] in males and 48·2% [11 707 of 24 288] in females; aged <60 years: 48·8% [5179 of 10 609] in males and 36·6% [2814 of 7689] in females). Renal (24·3%, 17 752 of 73 197), complex respiratory (18·4%, 13 486 of 73 197), and systemic (16·3%, 11 895 of 73 197) complications were
COVID-19 Host Genetics Initiative, 2021, Mapping the human genetic architecture of COVID-19, Nature, Vol: 600, Pages: 472-477, ISSN: 0028-0836
The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3-7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Lima Cunha D, Richardson R, Tracey-White D, et al., 2021, REP1-deficiency causes systemic dysfunction of lipid metabolism and oxidative stress in choroideremia, JCI Insight, Vol: 6, ISSN: 2379-3708
Choroideremia (CHM) is a X-linked recessive chorioretinal dystrophy caused by mutations in CHM, encoding for Rab escort protein 1 (REP1). Loss of functional REP1 leads to the accumulation of unprenylated Rab proteins and defective intracellular protein trafficking, the putative cause for photoreceptor, retinal pigment epithelium (RPE) and choroidal degeneration. CHM is ubiquitously expressed, but adequate prenylation is considered to be achieved, outside the retina, through the isoform REP2. Recently, the possibility of systemic features in CHM has been debated, hence, in this study whole metabolomic analysis of plasma samples from 25 CHM patients versus age and gender matched controls was performed. Results showed plasma alterations in oxidative stress-related metabolites, coupled with alterations in tryptophan metabolism leading to significantly raised serotonin levels. Lipid metabolism was disrupted with decreased branched fatty acids and acylcarnitines, suggestive of dysfunctional lipid oxidation, and imbalances of several sphingolipids and glycerophospholipids. Targeted lipidomics of the chmru848 zebrafish provided further evidence for dysfunction, with the use of Fenofibrates over Simvastatin circumventing the prenylation pathway to improve the lipid profile and increase survival. This study provides strong evidence for systemic manifestations of CHM and proposes novel pathomechanisms and targets for therapeutic consideration.
Takis PG, Jiménez B, Al-Saffar NMS, et al., 2021, A computationally lightweight algorithm for deriving reliable metabolite panel measurements from 1D 1H NMR., Analytical Chemistry, Vol: 93, Pages: 4995-5000, ISSN: 0003-2700
Small Molecule Enhancement SpectroscopY (SMolESY) was employed to develop a unique and fully automated computational solution for the assignment and integration of 1H nuclear magnetic resonance (NMR) signals from metabolites in challenging matrices containing macromolecules (herein blood products). Sensitive and reliable quantitation is provided by instant signal deconvolution and straightforward integration bolstered by spectral resolution enhancement and macromolecular signal suppression. The approach is highly efficient, requiring only standard one-dimensional 1H NMR spectra and avoiding the need for sample preprocessing, complex deconvolution, and spectral baseline fitting. The performance of the algorithm, developed using >4000 NMR serum and plasma spectra, was evaluated using an additional >8800 spectra, yielding an assignment accuracy greater than 99.5% for all 22 metabolites targeted. Further validation of its quantitation capabilities illustrated a reliable performance among challenging phenotypes. The simplicity and complete automation of the approach support the application of NMR-based metabolite panel measurements in clinical and population screening applications.
Takis P, 2020, SMolESY-select
SMolESY-select (v1.0) is a freely available software for the auto-assignment/relative quantification of 22 serum/plasma metabolites, requiring only the standard 1H-NMR 1D spectrum, acquired at 600 MHz & prepared according to specific SOPs
Donisi G, Barbagallo M, Capretti G, et al., 2020, Isolation of proximal fluids to investigate the tumor microenvironment of pancreatic adenocarcinoma, Journal of Visualized Experiments, Vol: 165, Pages: 1-15, ISSN: 1940-087X
Pancreatic adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death, and soon to become the second. There is an urgent need of variables associated to specific pancreatic pathologies to help preoperative differential diagnosis and patient profiling. Pancreatic juice is a relatively unexplored body fluid, which, due to its close proximity to the tumor site, reflects changes in the surrounding tissue. Here we describe in detail the intraoperative collection procedure. Unfortunately, translating pancreatic juice collection to murine models of PDAC, to perform mechanistic studies, is technically very challenging. Tumor interstitial fluid (TIF) is the extracellular fluid, outside blood and plasma, which bathes tumor and stromal cells. Similarly to pancreatic juice, for its property to collect and concentrate molecules that are found diluted in plasma, TIF can be exploited as an indicator of microenvironmental alterations and as a valuable source of disease-associated biomarkers. Since TIF is not readily accessible, various techniques have been proposed for its isolation. We describe here two simple and technically undemanding methods for its isolation: tissue centrifugation and tissue elution.
Musio B, Ragone R, Todisco S, et al., 2020, A community-built calibration system: The case study of quantification of metabolites in grape juice by qNMR spectroscopy, TALANTA, Vol: 214, ISSN: 0039-9140
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Takis P, Jimenez B, Sands C, et al., 2020, SMolESY: An efficient and quantitative alternative to on-instrument macromolecular ¹H-NMR signal suppression, Chemical Science, Vol: 11, Pages: 6000-6011, ISSN: 2041-6520
One-dimensional (1D) proton-nuclear magnetic resonance (1H-NMR) spectroscopy is an established technique for measuring small molecules in a wide variety of complex biological sample types. It is demonstrably reproducible, easily automatable and consequently ideal for routine and large-scale application. However, samples containing proteins, lipids, polysaccharides and other macromolecules produce broad signals which overlap and convolute those from small molecules. NMR experiment types designed to suppress macromolecular signals during acquisition may be additionally performed, however these approaches add to the overall sample analysis time and cost, especially for large cohort studies, and fail to produce reliably quantitative data. Here, we propose an alternative way of computationally eliminating macromolecular signals, employing the mathematical differentiation of standard 1H-NMR spectra, producing small molecule-enhanced spectra with preserved quantitative capability and increased resolution. Our approach, presented in its simplest form, was implemented in a cheminformatic toolbox and successfully applied to more than 3000 samples of various biological matrices rich or potentially rich with macromolecules, offering an efficient alternative to on-instrument experimentation, facilitating NMR use in routine and large-scale applications.
Takis P, 2020, SMolESY_platform
A tool for transforming 1H-NMR spectra into "SMolESY" - Aligning, Integrating, bucketing for a full implementation of SMolESY into NMR-based metabolomics pipeline and analytical studies.
Cortese N, Capretti G, Barbagallo M, et al., 2020, Metabolome of Pancreatic Juice Delineates Distinct Clinical Profiles of Pancreatic Cancer and Reveals a Link between Glucose Metabolism and PD-1(+) Cells, CANCER IMMUNOLOGY RESEARCH, Vol: 8, Pages: 493-505, ISSN: 2326-6066
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- Citations: 16
Gallo V, Ragone R, Musio B, et al., 2019, A Contribution to the Harmonization of Non-targeted NMR Methods for Data-Driven Food Authenticity Assessment, Food Analytical Methods, ISSN: 1936-9751
Takis P, Luchinat C, 2019, Method for predicting chemical shift values of NMR spin systems in a sample of a fluid class, in particular in a sample of a biofluid, US10401312B2
Correlation information between captured characteristics and chemical shift values of captured NMR spin systems is provided by a model appliance for a fluid class. An NMR spectrum of a sample of the fluid class is recorded. Peaks in the recorded NMR spectrum which belong to defined reference NMR spin systems are identified, and experimental chemical shift values of the peaks from the recorded NMR spectrum are determined. A chemical shift value of at least one of the captured NMR spin systems not belonging to the reference NMR spin systems is predicted by applying the model appliance onto the experimental chemical shift values of the reference NMR spin systems. Peaks in an NMR spectrum of a sample of a fluid class are attributed more quickly and reliably to NMR spins systems of compounds contained in the sample.
Vignoli A, Ghini V, Meoni G, et al., 2019, Hochdurchsatz‐Metabolomik mit 1D‐NMR, Angewandte Chemie, Vol: 131, Pages: 980-1007, ISSN: 0044-8249
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