38 results found
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, 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.
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.
Norris T, Razieh C, Zaccardi F, et al., 2021, Impact of cardiometabolic multimorbidity and ethnicity on cardiovascular/renal complications in patients with COVID-19, Heart, 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.
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.
Takis P, Lewis M, 2021, PROCESSING 1H-NMR SPECTRAL DATA
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
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.
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.
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
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, Tenori L, Giusti B, et al., 2019, NMR-based metabolomics identifies patients at high risk of death within two years after acute myocardial infarction in the AMI-Florence II cohort, BMC MEDICINE, Vol: 17, ISSN: 1741-7015
© 2018 Elsevier B.V. NMR measures a relatively small portion of the human metabolome, which roughly corresponds to all free small molecules present in concentrations ≥1 μM. However, the method is intrinsically quantitative and highly reproducible and, whenever standardized pre-analytical and analytical procedures are used, it allows for fast fingerprinting and profiling of a variety of biosamples. While developing methods for accurate and automated identification and quantitation of detectable metabolites, we have proposed a Urine Shift Predictor that also provides the concentration of NMR-invisible inorganic ions. For biomedical applications, two peculiar features are associated to the fast, untargeted NMR-metabolomic fingerprinting of biofluids, i.e. the ability to: i) identify the individual phenotype that constitutes the metabolic signature of a person and monitor its behavior over time; ii) identify the signature of different diseases. The combination of the two in longitudinal cohort studies could become a tool for fast and untargeted screening of populations.
Takis PG, Taddei A, Pini R, et al., 2018, Fingerprinting Acute Digestive Diseases by Untargeted NMR Based Metabolomics, INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, Vol: 19, ISSN: 1422-0067
Cortese N, Castino G, Capretti G, et al., 2018, Metabolomics analysis of pancreatic juice indicates an alteration in glucose metabolism in pancreatic ductal adenocarcinoma patients, Pancreatology, Vol: 18, Pages: S150-S150, ISSN: 1424-3903
Takis P, Luchinat C, 2017, Urine Shift Predictor
1H-NMR assignment of urine metabolites
Takis PG, Schaefer H, Spraul M, et al., 2017, Deconvoluting interrelationships between concentrations and chemical shifts in urine provides a powerful analysis tool, NATURE COMMUNICATIONS, Vol: 8, ISSN: 2041-1723
Grifoni E, Vignoli A, Tenori L, et al., 2017, Metabolomics by nuclear magnetic resonance identifies patients at high risk of death within two years after acute coronary syndrome, Publisher: OXFORD UNIV PRESS, Pages: 786-786, ISSN: 0195-668X
Takis PG, Papavasileiou KD, Peristeras LD, et al., 2017, Unscrambling micro-solvation of -COOH and -NH groups in neat dimethyl sulfoxide: insights from H-1-NMR spectroscopy and computational studies, PHYSICAL CHEMISTRY CHEMICAL PHYSICS, Vol: 19, Pages: 13710-13722, ISSN: 1463-9076
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