Early life infection and proinflammatory, atherogenic metabolomic and lipidomic profiles in infancy: a population-based cohort study

Metabolomic studies of respiratory infections in early life: A narrative review

Respiratory infections are a leading cause of morbidity and mortality during the early life period, and experiencing recurrent infections may increase the risk of developing chronic respiratory diseases, such as asthma. Over the last several decades, metabolomics methods have been applied to inform upon the underlying biochemistry of pediatric respiratory infection response, to discriminate between respiratory infection types, and to identify biomarkers of severity and susceptibility. While these studies have demonstrated the power of applying metabolomics to the study of pediatric respiratory infection and contributed to an understanding of respiratory infections during the unique period of immune development, key differences in study design, infection type(s) of interest, biosamples, metabolomics measurement methods, and lack of external validation have limited the translation of these findings into the clinic. The purpose of this review is to summarize overlaps across existing studies of commonly reported metabolomics findings and emphasize areas of opportunity for future study. We highlight several metabolomics pathways-such as the citric acid cycle and sphingolipid metabolism-that have been reported consistently in respiratory infection response. We then discuss putatively identified metabolomic markers to discriminate between respiratory infection types and possible markers of infection severity and proneness. Finally, we close with a summary and perspective of future directions of the field.

The associations between prenatal plastic phthalate exposure and lipid acylcarnitine levels in humans and mice

Phthalates are ubiquitous environmental pollutants known for their endocrine-disrupting properties, particularly during critical periods such as pregnancy and early childhood. Phthalates alter lipid metabolism, but the role of prenatal exposure on the offspring lipidome is less understood. In particular, we focused on long chain acylcarnitines - intermediates of fatty acid oxidation that serve as potential biomarkers of mitochondrial function and energy metabolism. This study aimed (i) to investigate the association between prenatal phthalate exposure and the child's blood acylcarnitine concentrations and, (ii) to evaluate the impact of prenatal administration of di-(2-ethylhexyl) phthalate (DEHP) on acylcarnitine levels in mouse offspring blood, brain and liver. We conducted analyses of both a prospective birth cohort study and an experimental study in mice. From the Barwon Infant Study cohort (1074 mother-child pairs), prenatal phthalate exposure was assessed at 36 weeks' gestation and its association with acylcarnitine levels was examined in cord blood, and child's blood at 6 months, 12 months and 4 years. In mice, pregnant C57BL/6 J mouse dams were exposed to 20 μg/kg DEHP for 5 days mid-gestation, and offspring tissues were analyzed at 1 month of age postnatally for acylcarnitine profiles. Our findings demonstrate that prenatal phthalate levels (specifically butyl benzyl phthalate (BBzP) and diisobutyl phthalate (DiBP)) are inversely associated with total long chain acylcarnitine levels in human cord blood at birth. In contrast, BBzP was positively associated with the long chain acylcarnitines at 12 months of age. In mice, prenatal DEHP exposure for only 5 days led to decreased palmitoylcarnitine (AC16:0) levels in the brain and liver, but not in blood. Taken together, our findings highlight that prenatal phthalate exposure can alter acylcarnitine profiles, indicating disruptions in fatty acid metabolism that may have long-term effects on metabolic health.

The plasma metabolome of juvenile idiopathic arthritis varies according to subtype and underlying inflammatory status

BACKGROUND

Juvenile idiopathic arthritis (JIA) is challenging to classify and effectively monitor due to the lack of disease- and subtype-specific biomarkers. A robust molecular signature that tracks with specific JIA features over time is urgently required, and targeted plasma metabolomics may reveal such a signature. The primary aim of this study was to characterise the differences in the plasma metabolome between JIA patients and non-JIA controls and identify specific markers of JIA subtype. We also assessed the extent to which these signatures are due to underlying inflammation as assessed by glycoprotein acetyls (GlycA) and high-sensitivity C-Reactive Protein (hsCRP) levels.

METHODS

Targeted nuclear magnetic resonance (NMR) metabolomic profiles of plasma of 72 children with JIA and 18 controls were assessed cross-sectionally. Associations between 71 metabolomic biomarkers and JIA, JIA subtype, disease activity status, and inflammation markers (GlycA and hsCRP) were assessed using multivariable linear regression models.

RESULTS

JIA was associated with higher GlycA (mean difference = 0.93 standard deviations, 95% confidence interval = [0.370, 1.494], Padj = 0.039) and docosahexaenoic acid (1.06, [0.51, 1.60], Padj = 0.021), and lower acetate (-0.92, [-1.43, -0.41], Padj = 0.024) relative to controls. This variation was largely driven by systemic JIA (sJIA), with 24 of 71 total biomarkers significantly different (Padj <0.05) relative to controls. There were no specific differences identified in oligoarticular (oJIA) or polyarticular (rheumatoid factor positive or negative) JIA relative to controls. Despite being generally highly correlated with hsCRP (r > 0.70), GlycA, but not hsCRP, was positively associated with active disease in sJIA (0.22, [-0.40, -0.04], Padj = 0.018), and 6 of 24 sJIA-associated markers were associated with GlycA levels. Only 1 sJIA-associated biomarker, histidine, was associated with hsCRP levels.

CONCLUSION

Differences in the plasma NMR metabolomic profiles are apparent in children with sJIA, but not other JIA subtypes, relative to non-JIA controls. These findings suggest a potential utility for classifying and monitoring JIA through metabolomic profiling, with chronic inflammation, measured by GlycA, potentially playing a role in at least some of these metabolomic differences.

Impact of Distinct Antiandrogen Exposures on the Plasma Metabolome in Feminizing Gender-affirming Hormone Therapy

CONTEXT

The plasma metabolome is a functional readout of metabolic activity and is associated with phenotypes exhibiting sexual dimorphism, such as cardiovascular disease. Sex hormones are thought to play a key role in driving sexual dimorphism.

OBJECTIVE

Gender-affirming hormone therapy (GAHT) is a cornerstone of transgender care, but longitudinal changes in the plasma metabolome with feminizing GAHT have not been described.

METHODS

Blood samples were collected at baseline and after 3 and 6 months of GAHT from transgender women (n = 53). Participants were randomized to different anti-androgens, cyproterone acetate or spironolactone. Nuclear magnetic resonance-based metabolomics was used to measure 249 metabolic biomarkers in plasma. Additionally, we used metabolic biomarker data from an unrelated cohort of children and their parents (n = 3748) to identify sex- and age-related metabolite patterns.

RESULTS

We identified 43 metabolic biomarkers altered after 6 months in both anti-androgen groups, most belonging to the very low- or low-density lipoprotein subclasses, with all but 1 showing a decrease. We observed a cyproterone acetate-specific decrease in glutamine, glycine, and alanine levels. Notably, of the metabolic biomarkers exhibiting the most abundant "sex- and age-related" pattern (higher in assigned female children and lower in assigned female adults, relative to assigned males), 80% were significantly lowered after GAHT, reflecting a shift toward the adult female profile.

CONCLUSION

Our results suggest an anti-atherogenic signature in the plasma metabolome after the first 6 months of feminizing GAHT, with cyproterone acetate also reducing specific plasma amino acids. This study provides novel insight into the metabolic changes occurring across feminizing GAHT.

Plasma lipidomics analysis reveals altered profile of triglycerides and phospholipids in children with Medium-Chain Acyl-CoA dehydrogenase deficiency

Medium-chain acyl-CoA dehydrogenase deficiency (MCADD) is the most prevalent mitochondrial fatty acid β-oxidation disorder. In this study, we assessed the variability of the lipid profile in MCADD by analysing plasma samples obtained from 25 children with metabolically controlled MCADD (following a normal diet with frequent feeding and under l-carnitine supplementation) and 21 paediatric control subjects (CT). Gas chromatography-mass spectrometry was employed for the analysis of esterified fatty acids, while high-resolution C18-liquid chromatography-mass spectrometry was used to analyse lipid species. We identified a total of 251 lipid species belonging to 15 distinct lipid classes. Principal component analysis revealed a clear distinction between the MCADD and CT groups. Univariate analysis demonstrated that 126 lipid species exhibited significant differences between the two groups. The lipid species that displayed the most pronounced variations included triacylglycerols and phosphatidylcholines containing saturated and monounsaturated fatty acids, specifically C14:0 and C16:0, which were found to be more abundant in MCADD. The observed changes in the plasma lipidome of children with non-decompensated MCADD suggest an underlying alteration in lipid metabolism. Therefore, longitudinal monitoring and further in-depth investigations are warranted to better understand whether such alterations are specific to MCADD children and their potential long-term impacts.

Implementation of Modern Therapeutic Drug Monitoring and Lipidomics Approaches in Clinical Practice: A Case Study with Colistin Treatment

Nowadays, lipidomics plays a crucial role in the investigation of novel biomarkers of various diseases. Its implementation into the field of clinical analysis led to the identification of specific lipids and/or significant changes in their plasma levels in patients suffering from cancer, Alzheimer's disease, sepsis, and many other diseases and pathological conditions. Profiling of lipids and determination of their plasma concentrations could also be helpful in the case of drug therapy management, especially in combination with therapeutic drug monitoring (TDM). Here, for the first time, a combined approach based on the TDM of colistin, a last-resort antibiotic, and lipidomic profiling is presented in a case study of a critically ill male patient suffering from Pseudomonas aeruginosa-induced pneumonia. Implementation of innovative analytical approaches for TDM (online combination of capillary electrophoresis with tandem mass spectrometry, CZE-MS/MS) and lipidomics (liquid chromatography-tandem mass spectrometry, LC-MS/MS) was demonstrated. The CZE-MS/MS strategy confirmed the chosen colistin drug dosing regimen, leading to stable colistin concentrations in plasma samples. The determined colistin concentrations in plasma samples reached the required minimal inhibitory concentration of 1 μg/mL. The complex lipidomics approach led to monitoring 545 lipids in collected patient plasma samples during and after the therapy. Some changes in specific individual lipids were in good agreement with previous lipidomics studies dealing with sepsis. The presented case study represents a good starting point for identifying particular individual lipids that could correlate with antimicrobial and inflammation therapeutic management.

Increased innate immune responses in adolescents with obesity and its relation to subclinical cardiovascular measures: An exploratory study

Cardiometabolic risk accrues across the life course and childhood and adolescence are key periods for effective prevention. Obesity is associated with inflammation in adults, but pediatric data are scarce. In a cross-sectional and longitudinal study, we investigated immune cell composition and activation in 31 adolescents with obesity (41.9% male, BMIz>2.5, 14.4 years) and 22 controls with healthy weight (45.1% male, -1.5 Collapse

Key Words

• Disease
• Health sciences
• Immunology
• Pathophysiology
• Risk factor

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Affiliation(s)

Siroon Bekkering Department of Internal Medicine, Radboud University Medical Centre, Nijmegen 6525 GA, the Netherlands Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia
Christoph Saner Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Division of Pediatric Endocrinology, Diabetology and Metabolism, Department of Pediatrics, University Children`s Hospital Bern, Inselspital, Bern 3010, Switzerland Department of Biomedical Research, University of Bern, 3010 Bern, Switzerland
Boris Novakovic Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Toby Mansell Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Danielle K. Longmore Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Endocrinology, The Royal Children`s Hospital, Parkville, VIC 3052, Australia
Zoe McCallum Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia Department of Neurodevelopment and Disability, Royal Children’s Hospital, Parkville, VIC 3052, Australia
Anne-Louise Ponsonby Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Florey Institute of Neuroscience and Mental Health, University of Melbourne, Parkville, VIC 3052, Australia
Markus Juonala Department of Medicine, University of Turku, 20500 Turku, Finland Division of Medicine, Turku University Hospital, 20500 Turku, Finland
Mihai G. Netea Department of Internal Medicine, Radboud University Medical Centre, Nijmegen 6525 GA, the Netherlands Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
Matthew A. Sabin Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Endocrinology, The Royal Children`s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Richard Saffery Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia
Niels P. Riksen Department of Internal Medicine, Radboud University Medical Centre, Nijmegen 6525 GA, the Netherlands
David P. Burgner Murdoch Children’s Research Institute, The Royal Children’s Hospital, Parkville, VIC 3052, Australia Department of Paediatrics, The University of Melbourne, Parkville, VIC 3052, Australia Department of Pediatrics, Monash University, Clayton, VIC 3168, Australia

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Inflammation proteomics datasets in the ALSPAC cohort

Proteomics is the identification, detection and quantification of proteins within a biological sample. The complete set of proteins expressed by an organism is known as the proteome. The availability of new high-throughput proteomic technologies, such as Olink Proteomic Proximity Extension Assay (PEA) technology has enabled detailed investigation of the circulating proteome in large-scale epidemiological studies. In particular, the Olink® Target 96 inflammatory panel allows the measurement of 92 circulating inflammatory proteins. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1991-1992 and has followed these women, their partners, and their offspring ever since. In this data note, we describe the newly-released proteomic data available in ALSPAC. Ninety-two proteins were analysed in 9000 blood plasma samples using the Olink® Target 96 inflammatory panel. Samples were derived from 2968 fasted mothers (mean age 47.5; Focus on Mothers 1 (FOM1)), 3005 non-fasted offspring at age 9 (Focus@9) and 3027 fasted offspring at age 24 (Focus@24). Post sample filtering, 1834 offspring have data at both timepoints and 1119 of those have data from their mother available. We performed quality control analyses using a standardised data processing workflow ( metaboprep) to produce a filtered dataset of 8983 samples for researchers to use in future analyses. Initial validation analyses indicate that IL-6 measured using the Olink® Target 96 inflammatory panel is highly correlated with IL-6 previously measured by clinical chemistry (Pearson's correlation = 0.77) and we are able to reproduce the reported positive correlation between body mass index (BMI) and IL-6. The pre-processing and validation analyses indicate a rich proteomic dataset to further characterise the role of inflammation in health and disease.

Cord blood lipid correlation network profiles are associated with subsequent attention-deficit/hyperactivity disorder and autism spectrum disorder symptoms at 2 years: a prospective birth cohort study

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are neurodevelopmental conditions with early life origins. Alterations in blood lipids have been linked to ADHD and ASD; however, prospective early life data are limited. This study examined (i) associations between the cord blood lipidome and ADHD/ASD symptoms at 2 years of age, (ii) associations between prenatal and perinatal predictors of ADHD/ASD symptoms and cord blood lipidome, and (iii) mediation by the cord blood lipidome.

METHODS

From the Barwon Infant Study cohort (1074 mother-child pairs, 52.3% male children), child circulating lipid levels at birth were analysed using ultra-high-performance liquid chromatography-tandem mass spectrometry. These were clustered into lipid network modules via Weighted Gene Correlation Network Analysis. Associations between lipid modules and ADHD/ASD symptoms at 2 years, assessed with the Child Behavior Checklist, were explored via linear regression analyses. Mediation analysis identified indirect effects of prenatal and perinatal risk factors on ADHD/ASD symptoms through lipid modules.

FINDINGS

The acylcarnitine lipid module is associated with both ADHD and ASD symptoms at 2 years of age. Risk factors of these outcomes such as low income, Apgar score, and maternal inflammation were partly mediated by higher birth acylcarnitine levels. Other cord blood lipid profiles were also associated with ADHD and ASD symptoms.

INTERPRETATION

This study highlights that elevated cord blood birth acylcarnitine levels, either directly or as a possible marker of disrupted cell energy metabolism, are on the causal pathway of prenatal and perinatal risk factors for ADHD and ASD symptoms in early life.

FUNDING

The foundational work and infrastructure for the BIS was sponsored by the Murdoch Children's Research Institute, Deakin University, and Barwon Health. Subsequent funding was secured from the Minderoo Foundation, the European Union's Horizon 2020 research and innovation programme (ENDpoiNTs: No 825759), National Health and Medical Research Council of Australia (NHMRC) and Agency for Science, Technology and Research Singapore [APP1149047], The William and Vera Ellen Houston Memorial Trust Fund (via HOMER Hack), The Shepherd Foundation, The Jack Brockhoff Foundation, the Scobie & Claire McKinnon Trust, the Shane O'Brien Memorial Asthma Foundation, the Our Women Our Children's Fund Raising Committee Barwon Health, the Rotary Club of Geelong, the Ilhan Food Allergy Foundation, Geelong Medical and Hospital Benefits Association, Vanguard Investments Australia Ltd, the Percy Baxter Charitable Trust, and Perpetual Trustees.

Pre-pregnancy obesity is associated with greater systemic inflammation and increased risk of antenatal depression

BACKGROUND

Pre-pregnancy obesity is an emerging risk factor for perinatal depression. However, the underlying mechanisms remain unclear. We investigated the association between pre-pregnancy body mass index (BMI) and perinatal depressive symptoms in a large population-based pre-birth cohort, the Barwon Infant Study. We also assessed whether the levels of circulating inflammatory markers during pregnancy mediated this relationship.

METHODS

Depressive symptoms were assessed in 883 women using the Edinburgh Postnatal Depression Scale (EPDS) and psychological stress using the Perceived Stress Scale (PSS) at 28 weeks gestation and 4 weeks postpartum. Glycoprotein acetyls (GlycA), high-sensitivity C-reactive protein (hsCRP) and cytokines were assessed at 28 weeks gestation. We performed regression analyses, adjusted for potential confounders, and investigated mediation using nested counterfactual models.

RESULTS

The estimated effect of pre-pregnancy obesity (BMI ≥ 30 kg/m2) on antenatal EPDS scores was 1.05 points per kg/m2 increase in BMI (95% CI: 0.20, 1.90; p = 0.02). GlycA, hsCRP, interleukin (IL) -1ra and IL-6 were higher in women with obesity, compared to healthy weight women, while eotaxin and IL-4 were lower. Higher GlycA was associated with higher EPDS and PSS scores and partially mediated the association between pre-pregnancy obesity and EPDS/PSS scores in unadjusted models, but this association attenuated upon adjustment for socioeconomic adversity. IL-6 and eotaxin were negatively associated with EPDS/PSS scores, however there was no evidence for mediation.

CONCLUSIONS

Pre-pregnancy obesity increases the risk of antenatal depressive symptoms and is also associated with systemic inflammation during pregnancy. While discrete inflammatory markers are associated with antenatal depressive symptoms and perceived stress, their role in mediating the effects of pre-pregnancy obesity on antenatal depression requires further investigation.

Metabolomics identifies disturbances in arginine, phenylalanine, and glycine metabolism as differentiating features of exacerbating atopic asthma in children

Background

Asthma exacerbations are highly prevalent in children, but only a few studies have examined the biologic mechanisms underlying exacerbations in this population.

Objective

High-resolution metabolomics analyses were performed to understand the differences in metabolites in children with exacerbating asthma who were hospitalized in a pediatric intensive care unit for status asthmaticus. We hypothesized that compared with a similar population of stable outpatients with asthma, children with exacerbating asthma would have differing metabolite abundance patterns with distinct clustering profiles.

Methods

A total of 98 children aged 6 through 17 years with exacerbating asthma (n = 69) and stable asthma (n = 29) underwent clinical characterization procedures and submitted plasma samples for metabolomic analyses. High-confidence metabolites were retained and utilized for pathway enrichment analyses to identify the most relevant metabolic pathways that discriminated between groups.

Results

In all, 118 and 131 high-confidence metabolites were identified in positive and negative ionization mode, respectively. A total of 103 unique metabolites differed significantly between children with exacerbating asthma and children with stable asthma. In all, 8 significantly enriched pathways that were largely associated with alterations in arginine, phenylalanine, and glycine metabolism were identified. However, other metabolites and pathways of interest were also identified.

Conclusion

Metabolomic analyses identified multiple perturbed metabolites and pathways that discriminated children with exacerbating asthma who were hospitalized for status asthmaticus. These results highlight the complex biology of inflammation in children with exacerbating asthma and argue for additional studies of the metabolic determinants of asthma exacerbations in children because many of the identified metabolites of interest may be amenable to targeted interventions.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

Lipids are biological molecules that play vital roles in all living organisms. They perform many cellular functions, such as 1) forming cellular and subcellular membranes, 2) storing and using energy, and 3) serving as chemical messengers during intra- and inter-cellular signal transduction. The large-scale study of the pathways and networks of cellular lipids in biological systems is called "lipidomics" and is one of the fastest-growing omics technologies of the last two decades. With state-of-the-art mass spectrometry instrumentation and sophisticated data handling, clinical studies show how human lipid composition changes in health and disease, thereby making it a valuable medium to collect for clinical applications, such as disease diagnostics, therapeutic decision-making, and drug development. This review gives a comprehensive overview of current workflows used in clinical research, from sample collection and preparation to data and clinical interpretations. This is followed by an appraisal of applications in 2022 and a perspective on the exciting future of clinical lipidomics.

Pharmacometabolomics for the Study of Lipid-Lowering Therapies: Opportunities and Challenges

Lipid-lowering therapies are widely used to prevent the development of atherosclerotic cardiovascular disease (ASCVD) and related mortality worldwide. "Omics" technologies have been successfully applied in recent decades to investigate the mechanisms of action of these drugs, their pleiotropic effects, and their side effects, aiming to identify novel targets for future personalized medicine with an improvement of the efficacy and safety associated with the treatment. Pharmacometabolomics is a branch of metabolomics that is focused on the study of drug effects on metabolic pathways that are implicated in the variation of response to the treatment considering also the influences from a specific disease, environment, and concomitant pharmacological therapies. In this review, we summarized the most significant metabolomic studies on the effects of lipid-lowering therapies, including the most commonly used statins and fibrates to novel drugs or nutraceutical approaches. The integration of pharmacometabolomics data with the information obtained from the other "omics" approaches could help in the comprehension of the biological mechanisms underlying the use of lipid-lowering drugs in view of defining a precision medicine to improve the efficacy and reduce the side effects associated with the treatment.

Inflammation proteomics datasets in the ALSPAC cohort

Proteomics is the identification, detection and quantification of proteins within a biological sample. The complete set of proteins expressed by an organism is known as the proteome. The availability of new high-throughput proteomic technologies, such as Olink Proteomic Proximity Extension Assay (PEA) technology has enabled detailed investigation of the circulating proteome in large-scale epidemiological studies. In particular, the Olink® Target 96 inflammatory panel allows the measurement of 92 circulating inflammatory proteins. The Avon Longitudinal Study of Parents and Children (ALSPAC) is a prospective population-based cohort study which recruited pregnant women in 1991-1992 and has followed these women, their partners, and their offspring ever since. In this data note, we describe the proteomic data available in ALSPAC. Ninety-two proteins were analysed in 9000 blood plasma samples using the Olink® Target 96 inflammatory panel. Samples were derived from 2968 fasted mothers (mean age 47.5; Focus on Mothers 1 (FOM1)), 3005 non-fasted offspring at age 9 (Focus@9) and 3027 fasted offspring at age 24 (Focus@24). Post sample filtering, 1834 offspring have data at both timepoints and 1119 of those have data from their mother available. We performed quality control analyses using a standardised data processing workflow (metaboprep) to produce a filtered dataset of 8983 samples for researchers to use in future analyses. Initial validation analyses indicate that IL-6 measured using the Olink® Target 96 inflammatory panel is highly correlated with IL-6 previously measured by clinical chemistry (Pearson’s correlation = 0.77) and we are able to reproduce the reported positive correlation between body mass index (BMI) and IL-6. The pre-processing and validation analyses indicate a rich proteomic dataset to further characterise the role of inflammation in health and disease.