Metabolic biomarker profiling for identification of susceptibility to severe pneumonia and COVID-19 in the general population

Abstract

Biomarkers of low-grade inflammation have been associated with susceptibility to a severe infectious disease course, even when measured prior to disease onset. We investigated whether metabolic biomarkers measured by nuclear magnetic resonance (NMR) spectroscopy could be associated with susceptibility to severe pneumonia (2507 hospitalised or fatal cases) and severe COVID-19 (652 hospitalised cases) in 105,146 generally healthy individuals from UK Biobank, with blood samples collected 2007–2010. The overall signature of metabolic biomarker associations was similar for the risk of severe pneumonia and severe COVID-19. A multi-biomarker score, comprised of 25 proteins, fatty acids, amino acids and lipids, was associated equally strongly with enhanced susceptibility to severe COVID-19 (odds ratio 2.9 [95%CI 2.1–3.8] for highest vs lowest quintile) and severe pneumonia events occurring 7–11 years after blood sampling (2.6 [1.7–3.9]). However, the risk for severe pneumonia occurring during the first 2 years after blood sampling for people with elevated levels of the multi-biomarker score was over four times higher than for long-term risk (8.0 [4.1–15.6]). If these hypothesis generating findings on increased susceptibility to severe pneumonia during the first few years after blood sampling extend to severe COVID-19, metabolic biomarker profiling could potentially complement existing tools for identifying individuals at high risk. These results provide novel molecular understanding on how metabolic biomarkers reflect the susceptibility to severe COVID-19 and other infections in the general population.

1H-NMR metabolomics-based surrogates to impute common clinical risk factors and endpoints

“…Besides anthropometric measures and other physiological characteristics, the blood 1 H-NMR metabolome was previously also shown to capture aspects directly pertaining to health outcomes. In particular, we and others have previously reported 1 H-NMR metabolomics-based risk estimators of cardiometabolic disease [59], [60], pneumonia and COVID infection [61], and all-cause mortality [17]. While this clearly illustrates the vast potential of the blood 1 H-NMR metabolome as a universal readout for health outcomes, it also raises the question what factors give rise to metabolomic profiles associated with adverse outcomes.…”

Quality control and removal of technical variation of NMR metabolic biomarker data in ∼120,000 UK Biobank participants

“…UK Biobank is a deeply phenotyped cohort of approximately 500,000 thousand adults (Bycroft et al, 2018;Sudlow et al, 2015). Presently, NMR metabolic biomarkers have been quantified in approximately one third of randomly selected participants (Methods) (Julkunen et al, 2021). After sample QC (Methods), NMR metabolic biomarker data were available for 121,657 UK Biobank participants: 117,994 at baseline assessment (2006)(2007)(2008)(2009)(2010) and 5,139 at first repeat assessment (2012)(2013).…”

“…Further details on UK Biobank sample handling can be found in UK Biobank Resource 3000 (https://biobank.ndph.ox.ac.uk/showcase/showcase/docs/nmrm_companion_doc.pdf). Further details on the Nightingale Health NMR spectroscopy quantification pipeline are detailed in (Würtz et al, 2017) and details pertaining to UK Biobank detailed in (Julkunen et al, 2021).…”

“…Absolute concentrations of 168 biomarkers and 81 biomarker ratios were quantified by NMR spectroscopy (Nightingale Health Plc.) from non-fasting plasma samples (UK Biobank aliquot 3) of 121,695 randomly selected UK Biobank participants as previously described (Julkunen et al, 2021). These included 117,981 participants at baseline assessment and 5,141 participants at repeat assessment, among which there were 1,427 participants with measurements at both time points.…”

“…The emergence and increasing scale of biobanks containing hundreds of thousands to millions of samples promises to enable discovery of new insights into human health and disease. To date, biomarker quantification has been completed in 121,695 participants (Julkunen et al, 2021), which have recently been made available for download by UK Biobank. Molecular phenotype data in large sample sizes are typically subject to the effects of unwanted technical variation (e.g.…”