Database screening as a strategy to identify endogenous candidate metabolites to probe and assess mitochondrial drug toxicity

Adverse drug reactions (ADRs) are considered an inherent risk of medication use, and some ADRs have been associated with off-target drug interactions with mitochondria. Metabolites that reflect mitochondrial function may help identify patients at risk of mitochondrial toxicity. We employed a database strategy to identify candidate mitochondrial metabolites that could be clinically useful to identify individuals at increased risk of mitochondrial-related ADRs. This led to L-carnitine being identified as the candidate mitochondrial metabolite. L-carnitine, its acetylated metabolite, acetylcarnitine and other acylcarnitines are mitochondrial biomarkers used to detect inborn errors of metabolism. We hypothesized that changes in L-carnitine disposition, induced by a "challenge test" of intravenous L-carnitine, could identify mitochondrial-related ADRs by provoking variation in L-carnitine and/or acetylcarnitine blood levels. To test this hypothesis, we induced mitochondrial drug toxicity with clofazimine (CFZ) in a mouse model. Following CFZ treatment, mice received an L-carnitine "challenge test". CFZ-induced changes in weight were consistent with previous work and reflect CFZ-induced catabolism. L-carnitine induced differences in whole blood acetylcarnitine concentrations in a manner that was dependent on CFZ treatment. This supports the usefulness of a database strategy for the discovery of candidate metabolite biomarkers of drug toxicity and substantiates the potential of the L-carnitine "challenge test" as a "probe" to identify drug-related toxicological manifestations.

Kidney function as a key driver of the pharmacokinetic response to high-dose L-carnitine in septic shock

STUDY OBJECTIVE

Levocarnitine (L-carnitine) has shown promise as a metabolic-therapeutic for septic shock, where mortality approaches 40%. However, high-dose (≥ 6 grams) intravenous supplementation results in a broad range of serum concentrations. We sought to describe the population pharmacokinetics (PK) of high-dose L-carnitine, test various estimates of kidney function, and assess the correlation of PK parameters with pre-treatment metabolites in describing drug response for patients with septic shock.

DESIGN

Population PK analysis was done with baseline normalized concentrations using nonlinear mixed effect models in the modeling platform Monolix. Various estimates of kidney function, patient demographics, dose received, and organ dysfunction were tested as population covariates.

DATA SOURCE

We leveraged serum samples and metabolomics data from a phase II trial of L-carnitine in vasopressor-dependent septic shock. Serum was collected at baseline (T0); end-of-infusion (T12); and 24, 48, and 72 h after treatment initiation.

PATIENTS AND INTERVENTION

Patients were adaptively randomized to receive intravenous L-carnitine (6 grams, 12 grams, or 18 grams) or placebo.

MEASUREMENTS AND MAIN RESULTS

The final dataset included 542 serum samples from 130 patients randomized to L-carnitine. A two-compartment model with linear elimination and a fixed volume of distribution (17.1 liters) best described the data and served as a base structural model. Kidney function estimates as a covariate on the elimination rate constant (k) reliably improved model fit. Estimated glomerular filtration rate (eGFR), based on the 2021 Chronic Kidney Disease Epidemiology collaboration (CKD-EPI) equation with creatinine and cystatin C, outperformed creatinine clearance (Cockcroft-Gault) and older CKD-EPI equations that use an adjustment for self-identified race.

CONCLUSIONS

High-dose L-carnitine supplementation is well-described by a two-compartment population PK model in patients with septic shock. Kidney function estimates that leverage cystatin C provided superior model fit. Future investigations into high-dose L-carnitine supplementation should consider baseline metabolic status and dose adjustments based on renal function over a fixed or weight-based dosing paradigm.

Plasma metabolomics and quantitative interstitial abnormalities in ever-smokers

BACKGROUND

Quantitative interstitial abnormalities (QIA) are an automated computed tomography (CT) finding of early parenchymal lung disease, associated with worse lung function, reduced exercise capacity, increased respiratory symptoms, and death. The metabolomic perturbations associated with QIA are not well known. We sought to identify plasma metabolites associated with QIA in smokers. We also sought to identify shared and differentiating metabolomics features between QIA and emphysema, another smoking-related advanced radiographic abnormality.

METHODS

In 928 former and current smokers in the Genetic Epidemiology of COPD cohort, we measured QIA and emphysema using an automated local density histogram method and generated metabolite profiles from plasma samples using liquid chromatography-mass spectrometry (Metabolon). We assessed the associations between metabolite levels and QIA using multivariable linear regression models adjusted for age, sex, body mass index, smoking status, pack-years, and inhaled corticosteroid use, at a Benjamini-Hochberg False Discovery Rate p-value of ≤ 0.05. Using multinomial regression models adjusted for these covariates, we assessed the associations between metabolite levels and the following CT phenotypes: QIA-predominant, emphysema-predominant, combined-predominant, and neither- predominant. Pathway enrichment analyses were performed using MetaboAnalyst.

RESULTS

We found 85 metabolites significantly associated with QIA, with overrepresentation of the nicotinate and nicotinamide, histidine, starch and sucrose, pyrimidine, phosphatidylcholine, lysophospholipid, and sphingomyelin pathways. These included metabolites involved in inflammation and immune response, extracellular matrix remodeling, surfactant, and muscle cachexia. There were 75 metabolites significantly different between QIA-predominant and emphysema-predominant phenotypes, with overrepresentation of the phosphatidylethanolamine, nicotinate and nicotinamide, aminoacyl-tRNA, arginine, proline, alanine, aspartate, and glutamate pathways.

CONCLUSIONS

Metabolomic correlates may lend insight to the biologic perturbations and pathways that underlie clinically meaningful quantitative CT measurements like QIA in smokers.

Vitamin D Insufficiency as a Risk Factor for Paclitaxel-Induced Peripheral Neuropathy in SWOG S0221

BACKGROUND

Prior work suggests that patients with vitamin D insufficiency may have a higher risk of chemotherapy-induced peripheral neuropathy (CIPN) from paclitaxel. The objective of this study was to validate vitamin D insufficiency as a CIPN risk factor.

METHODS

We used data and samples from the prospective phase III SWOG S0221 (ClinicalTrials.gov identifier: NCT00070564) trial that compared paclitaxel-containing chemotherapy regimens for early-stage breast cancer. We quantified pretreatment 25-hydroxy-vitamin D in banked serum samples using a liquid chromatography-tandem mass spectrometry targeted assay. We tested the association between vitamin D insufficiency (≤20 ng/mL) and grade ≥3 sensory CIPN via multiple logistic regression and then adjusted for self-reported race, age, body mass index, and paclitaxel schedule (randomization to weekly or every-2-week dosing). We also tested the direct effect of vitamin D deficiency on mechanical hypersensitivity in mice randomized to a regular or vitamin D-deficient diet.

RESULTS

Of the 1,191 female patients in the analysis, 397 (33.3%) had pretreatment vitamin D insufficiency, and 195 (16.4%) developed grade ≥3 CIPN. Patients with vitamin D insufficiency had a higher incidence of grade ≥3 CIPN than those who had sufficient vitamin D (20.7% vs 14.2%; odds ratio [OR], 1.57; 95% CI, 1.14-2.15; P=.005). The association retained significance after adjusting for age and paclitaxel schedule (adjusted OR, 1.65; 95% CI, 1.18-2.30; P=.003) but not race (adjusted OR, 1.39; 95% CI, 0.98-1.97; P=.066). In the mouse experiments, the vitamin D-deficient diet caused mechanical hypersensitivity and sensitized mice to paclitaxel (both P<.05).

CONCLUSIONS

Pretreatment vitamin D insufficiency is the first validated potentially modifiable predictive biomarker of CIPN from paclitaxel. Prospective trials are needed to determine whether vitamin D supplementation prevents CIPN and improves treatment outcomes in patients with breast and other cancer types.

Distinguishing the Concentration- vs. Bioaccumulation-Dependent Immunological and Metabolic Effects of Clofazimine

The antimycobacterial drug clofazimine (CFZ) is used as a single agent at high doses, to suppress the exaggerated inflammation associated with leprosy. Paradoxically, increasing doses of CFZ leads to bioaccumulation of CFZ in the spleen and other organs under physiologically relevant dosing regimens, without accompanying dose-dependent elevation in the concentrations of the circulating drug in the blood. In long-term oral dosing regimens, CFZ induces immunological and metabolic changes resulting in splenomegaly, while the mass of other organs decreases or remains unchanged. As an organ that extensively sequesters CFZ as insoluble drug precipitates, the spleen likely influences drug-induced inflammatory signaling. To probe the role of systemic drug concentrations vs. drug bioaccumulation in the spleen, healthy mice were treated with six different dosing regimens. A subgroup of these mice underwent surgical splenectomies prior to drug treatment to assess the bioaccumulation-dependent changes in immune system signaling and immune-system-mediated drug distribution. Under increasing drug loading, the spleen was observed to grow up to six times in size, sequestering over 10% of the total drug load. Interestingly, when the spleen was removed prior to CFZ administration, drug distribution in the rest of the organism was unaffected. However, there were profound cytokine elevations in the serum of asplenic CFZ-treated mice, indicating that the spleen is primarily involved in suppressing the inflammatory signaling mechanisms that are upregulated during CFZ bioaccumulation. Thus, beyond its role in drug sequestration, the spleen actively modulates the systemic effect of CFZ on the immune system, without impacting its blood concentrations or distribution to the rest of the organism.

Nebulized Recombinant Tissue Plasminogen Activator (rt-PA) for Acute COVID-19-Induced Respiratory Failure: An Exploratory Proof-of-Concept Trial

Acute lung injury in COVID-19 results in diffuse alveolar damage with disruption of the alveolar-capillary barrier, coagulation activation, alveolar fibrin deposition and pulmonary capillary thrombi. Nebulized recombinant tissue plasminogen activator (rt-PA) has the potential to facilitate localized thrombolysis in the alveolar compartment and improve oxygenation. In this proof-of-concept safety study, adults with COVID-19-induced respiratory failure and a <300 mmHg PaO2/FiO2 (P/F) ratio requiring invasive mechanical ventilation (IMV) or non-invasive respiratory support (NIRS) received nebulized rt-PA in two cohorts (C1 and C2), alongside standard of care, between 23 April-30 July 2020 and 21 January-19 February 2021, respectively. Matched historical controls (MHC; n = 18) were used in C1 to explore efficacy. Safety co-primary endpoints were treatment-related bleeds and <1.0-1.5 g/L fibrinogen reduction. A variable dosing strategy with clinical efficacy endpoint and minimal safety concerns was determined in C1 for use in C2; patients were stratified by ventilation type to receive 40-60 mg rt-PA daily for ≤14 days. Nine patients in C1 (IMV, 6/9; NIRS, 3/9) and 26 in C2 (IMV, 12/26; NIRS, 14/26) received nebulized rt-PA for a mean (SD) of 6.7 (4.6) and 9.1(4.6) days, respectively. Four bleeds (one severe, three mild) in three patients were considered treatment related. There were no significant fibrinogen reductions. Greater improvements in mean P/F ratio from baseline to study end were observed in C1 compared with MHC (C1; 154 to 299 vs. MHC; 154 to 212). In C2, there was no difference in the baseline P/F ratio of NIRS and IMV patients. However, a larger improvement in the P/F ratio occurred in NIRS patients (NIRS; 126 to 240 vs. IMV; 120 to 188) and fewer treatment days were required (NIRS; 7.86 vs. IMV; 10.5). Nebulized rt-PA appears to be well-tolerated, with a trend towards improved oxygenation, particularly in the NIRS group. Randomized clinical trials are required to demonstrate the clinical effect significance and magnitude.

Pre-treatment Amino Acids and Risk of Paclitaxel-induced Peripheral Neuropathy in SWOG S0221

Background

Chemotherapy-induced peripheral neuropathy (CIPN) is a treatment-limiting and debilitating neurotoxicity of many commonly used anti-cancer agents, including paclitaxel. The objective of this study was to confirm the previously found inverse association between pre-treatment blood concentrations of histidine and CIPN occurrence and examine relationships of other amino acids with CIPN severity.

Methods

Pre-treatment levels of 20 amino acid concentrations were measured via a targeted mass spectrometry assay in banked serum from the SWOG S0221 (NCT00070564) trial of patients with early-stage breast cancer receiving paclitaxel. The associations between amino acid levels and CIPN occurrence or severity were tested in regression analysis adjusted for paclitaxel schedule, age, self-reported race, and body mass index with Bonferroni correction for multiple comparisons. The network of metabolic pathways of amino acids was analyzed using over-representation analysis in MetaboAnalyst. The partial correlation network of amino acids was evaluated using a debiased sparse partial correlation algorithm and Cytoscape.

Results

In the primary analysis, histidine concentration was not associated with CIPN occurrence (odds ratio (OR) = 0.97 [0.83, 1.13], p = 0.72). In a secondary analysis, no amino acid was associated with CIPN occurrence (all p > 0.0025). Higher concentrations of four amino acids, glutamate (β = 0.58 [0.23, 0.93], p = 0.001), phenylalanine (β = 0.54 [0.19, 0.89], p = 0.002), tyrosine (β = 0.57 [0.23, 0.91], p = 0.001), and valine (β = 0.58 [0.24, 0.92], p = 0.001) were associated with more severe CIPN, but none of these associations retained significance after adjustment. In the over-representation analysis, no amino acid metabolic pathways were significantly enriched (all FDR > 0.05). In the network of enriched pathways, glutamate metabolism had the highest centrality.

Conclusions

This analysis showed that pre-treatment serum amino acid concentrations are not strongly predictive of CIPN severity. Future prospectively designed studies that assess non-amino acid metabolomics predictors are encouraged.

Clofazimine-Mediated, Age-Related Changes in Skeletal Muscle Mitochondrial Metabolites

Mitochondrial health declines with age, and older patients can demonstrate dysfunction in mitochondrial-rich tissues, such as cardiac and skeletal muscle. Aged mitochondria may make older adults more susceptible to adverse drug reactions (ADRs). We assessed mitochondrial metabolic function by measuring two metabolites, l-carnitine and acetylcarnitine, to determine their effectiveness as candidate clinical biomarkers for age-related, drug-induced alterations in mitochondrial metabolism. To study age- and medication-related changes in mitochondrial metabolism, we administered the FDA-approved mitochondriotropic drug, clofazimine (CFZ), or vehicle for 8 weeks to young (4-week-old) and old (61-week-old) male C57BL/6J mice. At the end of treatment, whole blood and cardiac and skeletal muscle were analyzed for l-carnitine, acetylcarnitine, and CFZ levels; muscle function was measured via a treadmill test. No differences were found in blood or cardiac carnitine levels of CFZ-treated mice, but CFZ-treated mice displayed lost body mass and alterations in endurance and levels of skeletal muscle mitochondrial metabolites. These findings demonstrate the age-related susceptibility of the skeletal muscle to mitochondria drug toxicity. Since drug-induced alterations in mitochondrial metabolism in skeletal muscle were not reflected in the blood by l-carnitine or acetylcarnitine levels, drug-induced catabolism and changes in muscle function appear more relevant to stratifying individuals at increased risk for ADRs.

The Gut Microbiome Modulates Body Temperature Both in Sepsis and Health

Rationale: Among patients with sepsis, variation in temperature trajectories predicts clinical outcomes. In healthy individuals, normal body temperature is variable and has decreased consistently since the 1860s. The biologic underpinnings of this temperature variation in disease and health are unknown. Objectives: To establish and interrogate the role of the gut microbiome in calibrating body temperature. Methods: We performed a series of translational analyses and experiments to determine whether and how variation in gut microbiota explains variation in body temperature in sepsis and in health. We studied patient temperature trajectories using electronic medical record data. We characterized gut microbiota in hospitalized patients using 16S ribosomal RNA gene sequencing. We modeled sepsis using intraperitoneal LPS in mice and modulated the microbiome using antibiotics, germ-free, and gnotobiotic animals. Measurements and Main Results: Consistent with prior work, we identified four temperature trajectories in patients hospitalized with sepsis that predicted clinical outcomes. In a separate cohort of 116 hospitalized patients, we found that the composition of patients' gut microbiota at admission predicted their temperature trajectories. Compared with conventional mice, germ-free mice had reduced temperature loss during experimental sepsis. Among conventional mice, heterogeneity of temperature response in sepsis was strongly explained by variation in gut microbiota. Healthy germ-free and antibiotic-treated mice both had lower basal body temperatures compared with control animals. The Lachnospiraceae family was consistently associated with temperature trajectories in hospitalized patients, experimental sepsis, and antibiotic-treated mice. Conclusions: The gut microbiome is a key modulator of body temperature variation in both health and critical illness and is thus a major, understudied target for modulating physiologic heterogeneity in sepsis.

Sustained Perturbation of Metabolism and Metabolic Subphenotypes Are Associated With Mortality and Protein Markers of the Host Response

Perturbed host metabolism is increasingly recognized as a pillar of sepsis pathogenesis, yet the dynamic alterations in metabolism and its relationship to other components of the host response remain incompletely understood. We sought to identify the early host-metabolic response in patients with septic shock and to explore biophysiological phenotyping and differences in clinical outcomes among metabolic subgroups.

DESIGN

We measured serum metabolites and proteins reflective of the host-immune and endothelial response in patients with septic shock.

SETTING

We considered patients from the placebo arm of a completed phase II, randomized controlled trial conducted at 16 U.S. medical centers. Serum was collected at baseline (within 24 hr of the identification of septic shock), 24-hour, and 48-hour postenrollment. Linear mixed models were built to assess the early trajectory of protein analytes and metabolites stratified by 28-day mortality status. Unsupervised clustering of baseline metabolomics data was conducted to identify subgroups of patients.

PATIENTS

Patients with vasopressor-dependent septic shock and moderate organ dysfunction that were enrolled in the placebo arm of a clinical trial.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

Fifty-one metabolites and 10 protein analytes were measured longitudinally in 72 patients with septic shock. In the 30 patients (41.7%) who died prior to 28 days, systemic concentrations of acylcarnitines and interleukin (IL)-8 were elevated at baseline and persisted at T24 and T48 throughout early resuscitation. Concentrations of pyruvate, IL-6, tumor necrosis factor-α, and angiopoietin-2 decreased at a slower rate in patients who died. Two groups emerged from clustering of baseline metabolites. Group 1 was characterized by higher levels of acylcarnitines, greater organ dysfunction at baseline and postresuscitation (p < 0.05), and greater mortality over 1 year (p < 0.001).

CONCLUSIONS

Among patients with septic shock, nonsurvivors exhibited a more profound and persistent dysregulation in protein analytes attributable to neutrophil activation and disruption of mitochondrial-related metabolism than survivors.

Metabolomic signatures associated with weight gain and psychosis spectrum diagnoses: A pilot study

Psychosis spectrum disorders (PSDs), as well as other severe mental illnesses where psychotic features may be present, like bipolar disorder, are associated with intrinsic metabolic abnormalities. Antipsychotics (APs), the cornerstone of treatment for PSDs, incur additional metabolic adversities including weight gain. Currently, major gaps exist in understanding psychosis illness biomarkers, as well as risk factors and mechanisms for AP-induced weight gain. Metabolomic profiles may identify biomarkers and provide insight into the mechanistic underpinnings of PSDs and antipsychotic-induced weight gain. In this 12-week prospective naturalistic study, we compared serum metabolomic profiles of 25 cases within approximately 1 week of starting an AP to 6 healthy controls at baseline to examine biomarkers of intrinsic metabolic dysfunction in PSDs. In 17 of the case participants with baseline and week 12 samples, we then examined changes in metabolomic profiles over 12 weeks of AP treatment to identify metabolites that may associate with AP-induced weight gain. In the cohort with pre-post data (n = 17), we also compared baseline metabolomes of participants who gained ≥5% baseline body weight to those who gained <5% to identify potential biomarkers of antipsychotic-induced weight gain. Minimally AP-exposed cases were distinguished from controls by six fatty acids when compared at baseline, namely reduced levels of palmitoleic acid, lauric acid, and heneicosylic acid, as well as elevated levels of behenic acid, arachidonic acid, and myristoleic acid (FDR < 0.05). Baseline levels of the fatty acid adrenic acid was increased in 11 individuals who experienced a clinically significant body weight gain (≥5%) following 12 weeks of AP exposure as compared to those who did not (FDR = 0.0408). Fatty acids may represent illness biomarkers of PSDs and early predictors of AP-induced weight gain. The findings may hold important clinical implications for early identification of individuals who could benefit from prevention strategies to reduce future cardiometabolic risk, and may lead to novel, targeted treatments to counteract metabolic dysfunction in PSDs.

Lung Microbiota and Metabolites Collectively Associate with Clinical Outcomes in Milder Stage Chronic Obstructive Pulmonary Disease

Rationale: Chronic obstructive pulmonary disease (COPD) is variable in its development. Lung microbiota and metabolites collectively may impact COPD pathophysiology, but relationships to clinical outcomes in milder disease are unclear. Objectives: Identify components of the lung microbiome and metabolome collectively associated with clinical markers in milder stage COPD. Methods: We analyzed paired microbiome and metabolomic data previously characterized from bronchoalveolar lavage fluid in 137 participants in the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), or (GOLD [Global Initiative for Chronic Obstructive Lung Disease Stage 0-2). Datasets used included 1) bacterial 16S rRNA gene sequencing; 2) untargeted metabolomics of the hydrophobic fraction, largely comprising lipids; and 3) targeted metabolomics for a panel of hydrophilic compounds previously implicated in mucoinflammation. We applied an integrative approach to select features and model 14 individual clinical variables representative of known associations with COPD trajectory (lung function, symptoms, and exacerbations). Measurements and Main Results: The majority of clinical measures associated with the lung microbiome and metabolome collectively in overall models (classification accuracies, >50%, P < 0.05 vs. chance). Lower lung function, COPD diagnosis, and greater symptoms associated positively with Streptococcus, Neisseria, and Veillonella, together with compounds from several classes (glycosphingolipids, glycerophospholipids, polyamines and xanthine, an adenosine metabolite). In contrast, several Prevotella members, together with adenosine, 5'-methylthioadenosine, sialic acid, tyrosine, and glutathione, associated with better lung function, absence of COPD, or less symptoms. Significant correlations were observed between specific metabolites and bacteria (Padj < 0.05). Conclusions: Components of the lung microbiome and metabolome in combination relate to outcome measures in milder COPD, highlighting their potential collaborative roles in disease pathogenesis.

Co-occurrence and metabolic biomarkers of sensory and motor subtypes of peripheral neuropathy from paclitaxel

PURPOSE

Chemotherapy-induced peripheral neuropathy (CIPN) is the major treatment-limiting toxicity of paclitaxel, which predominantly presents as sensory symptoms, with motor symptoms in some patients. Differentiating CIPN into subtypes has been recommended to direct CIPN research. The objective of this study was to investigate whether sensory and motor CIPN are distinct subtypes with different predictive biomarkers in patients with breast cancer receiving paclitaxel.

METHODS

Data were from a prospective cohort of 60 patients with breast cancer receiving up to 12 weekly infusions of 80 mg/m² paclitaxel (NCT02338115). European Organisation for Research and Treatment of Cancer Quality of Life questionnaire CIPN20 was used to evaluate CIPN. Clusters of the time course of sensory (CIPN_S), motor (CIPN_M), and the difference between sensory and motor (CIPN_S-CIPN_M) were identified using k-means clustering on principal component scores. Predictive metabolomic biomarkers of maximum CIPN_S and CIPN_M were investigated using linear regressions adjusted for baseline CIPN, paclitaxel pharmacokinetics, and body mass index.

RESULTS

More sensory than motor CIPN was found (CIPN_S change: mean = 10.8, ranged [-3.3, 52.1]; CIPN_M change: mean = 3.5, range: [-7.5, 35.0]). Three groups were identified with No CIPN, Mixed CIPN, and Sensory-dominant CIPN (maximum CIPN_S: mean = 12.7 vs. 40.9 vs. 74.3, p < 0.001; maximum CIPN_M: mean = 5.4 vs. 25.5 vs. 36.1, p < 0.001; average CIPN_S-CIPN_M: mean = 2.8 vs. 5.8 vs. 24.9, p < 0.001). Biomarkers of motor CIPN were similar to previously identified biomarkers of sensory CIPN, including lower serum histidine (p = 0.029).

CONCLUSION

Our findings suggest that sensory and motor CIPN co-occur and may not have differentiating metabolic biomarkers. These findings need to be validated in larger cohorts of patients treated with paclitaxel and other neurotoxic agents to determine the optimal approach to predict, prevent, and treat CIPN and improve patients' outcomes.

Redox Potential Correlates with Changes in Metabolite Concentrations Attributable to Pathways Active in Oxidative Stress Response in Swine Traumatic Shock

INTRODUCTION

Oxidation-reduction (redox) reactions, and the redox potential (RP) that must be maintained for proper cell function, lie at the heart of physiologic processes in critical illness. Imbalance in RP reflects systemic oxidative stress, and whole blood RP measures have been shown to correlate with oxygen debt level over time in swine traumatic shock. We hypothesize that RP measures reflect changing concentrations of metabolites involved in oxidative stress. To test this hypothesis, we compared blood and urine RP with concentrations of multiple metabolites in a swine traumatic shock model to identify meaningful RP-metabolite relationships.

METHODS

Seven swine were subjected to traumatic shock. Mixed venous (MV) RP, urine RP, and concurrent MV and urine metabolite concentrations were assessed at baseline, max O 2 Debt (80 mL/kg), end resuscitation, and 2 h post-resuscitation. RP was measured at collection via open circuit potential using nanoporous gold electrodes with Ag/AgCl reference and a ParstatMC potentiostat. Metabolite concentrations were measured by quantitative 1 H-NMR spectroscopy. MV and urine RP were compared with time-matched metabolites across all swine. LASSO regression with leave-one-out cross validation was used to determine meaningful RP/metabolite relationships. Metabolites had to maintain magnitude and direction of coefficients across 6 or more swine to be considered as having a meaningful relationship. KEGG IDs of these metabolites were uploaded into Metscape for pathway identification and evaluation for physiologic function.

RESULTS

Meaningful metabolite relationships (and mean coefficients across cross-validation folds) with MV RP included: choline (-6.27), ATP (-4.39), glycine (5.93), ADP (1.84), glucose (15.96), formate (-13.09), pyruvate (6.18), and taurine (-7.18). Relationships with urine RP were: betaine (4.81), urea (4.14), glycine (-2.97), taurine (10.32), 3-hydroxyisobutyrate (-7.67), N-phenylacetylglycine, PAG (-14.52), hippurate (12.89), and formate (-5.89). These meaningful metabolites were found to scavenge extracellular peroxide (pyruvate), inhibit ROS and activate cellular antioxidant defense (taurine), act as indicators of antioxidant mobilization against oxidative stress (glycine + PAG), and reflect renal hydroxyl radical trapping (hippurate), among other activities.

CONCLUSIONS

Real-time RP measures demonstrate significant relationships with metabolites attributable to metabolic pathways involved in systemic responses to oxidative stress, as well as those involved in these processes. These data support RP measures as a feasible, biologically relevant marker of oxidative stress. As a direct measure of redox state, RP may be a useful biomarker and clinical tool in guiding diagnosis and therapy in states of increased oxidative stress and may offer value as a marker for organ injury in these states as well.

Vitamin D insufficiency as a peripheral neuropathy risk factor in white and black patients in SWOG 0221

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Background: Peripheral neuropathy (PN) is a treatment-limiting toxicity of paclitaxel. Black patients have higher rates of PN and vitamin D insufficiency, and our prior work suggests vitamin D insufficiency increases risk of paclitaxel-induced PN. The objective of this study was to validate that patients with vitamin D insufficiency have higher risk of paclitaxel-induced PN and investigate whether this explains racial disparities in PN risk. Methods: This retrospective validation study was conducted in the phase III SWOG 0221 (NCT00070564) trial comparing paclitaxel-containing chemotherapy regimens for early-stage breast cancer. Pre-treatment 25-hydroxy-vitamin D was quantified in cryopreserved serum. Males and patients who received less than a third of the paclitaxel treatment were excluded. The association between vitamin D insufficiency (≤20 ng/mL) and grade 3+ sensory PN was tested via logistic regression and then adjusted for self-reported race, age, paclitaxel schedule (QW vs Q2W), and body mass index. Results: Of the 1,116 female patients in the analysis, 169 (15.1%) experienced PN and 376 (33.7%) had vitamin D insufficiency. Vitamin D insufficiency was associated with higher PN risk (19.4% vs 13.0%, OR = 1.62, p = 0.005, Data Table). The association was borderline significant (OR = 1.44, p = 0.056) after adjustment for black race (OR = 2.41, p = 0.001), paclitaxel schedule (OR = 2.22, p < 0.001), and age (OR = 1.03, p = 0.005). Compared with white patients (n = 943), black patients (n = 99) had more prevalent vitamin D insufficiency (77.8% vs 28.6%, OR = 8.72, p < 0.001) and increased PN risk (29.3% vs 13.5%, OR = 2.66, p < 0.001); adjusting for vitamin D insufficiency decreased but did not eliminate the higher PN risk in black patients (OR = 2.23, p = 0.002). Conclusions: Vitamin D insufficiency increases risk of paclitaxel-induced PN and partially explains the higher risk of PN in black patients. Prospective trials are needed to test whether vitamin D supplementation lessens PN and reduces disparities in treatment outcomes. [Table: see text]

A Metabolomic Severity Score for Airflow Obstruction and Emphysema

Chronic obstructive pulmonary disease (COPD) is a disease with marked metabolic disturbance. Previous studies have shown the association between single metabolites and lung function for COPD, but whether a combination of metabolites could predict phenotype is unknown. We developed metabolomic severity scores using plasma metabolomics from the Metabolon platform from two US cohorts of ever-smokers: the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) (n = 648; training/testing cohort; 72% non-Hispanic, white; average age 63 years) and the COPDGene Study (n = 1120; validation cohort; 92% non-Hispanic, white; average age 67 years). Separate adaptive LASSO (adaLASSO) models were used to model forced expiratory volume at one second (FEV₁) and MESA-adjusted lung density using 762 metabolites common between studies. Metabolite coefficients selected by the adaLASSO procedure were used to create a metabolomic severity score (metSS) for each outcome. A total of 132 metabolites were selected to create a metSS for FEV₁. The metSS-only models explained 64.8% and 31.7% of the variability in FEV₁ in the training and validation cohorts, respectively. For MESA-adjusted lung density, 129 metabolites were selected, and metSS-only models explained 59.0% of the variability in the training cohort and 17.4% in the validation cohort. Regression models including both clinical covariates and the metSS explained more variability than either the clinical covariate or metSS-only models (53.4% vs. 46.4% and 31.6%) in the validation dataset. The metabolomic pathways for arginine biosynthesis; aminoacyl-tRNA biosynthesis; and glycine, serine, and threonine pathway were enriched by adaLASSO metabolites for FEV₁. This is the first demonstration of a respiratory metabolomic severity score, which shows how a metSS can add explanation of variance to clinical predictors of FEV₁ and MESA-adjusted lung density. The advantage of a comprehensive metSS is that it explains more disease than individual metabolites and can account for substantial collinearity among classes of metabolites. Future studies should be performed to determine whether metSSs are similar in younger, and more racially and ethnically diverse populations as well as whether a metabolomic severity score can predict disease development in individuals who do not yet have COPD.

Serum Levels of Acylcarnitines and Amino Acids Are Associated with Liberation from Organ Support in Patients with Septic Shock

Sepsis-induced metabolic dysfunction is associated with mortality, but the signatures that differentiate variable clinical outcomes among survivors are unknown. Our aim was to determine the relationship between host metabolism and chronic critical illness (CCI) in patients with septic shock. We analyzed metabolomics data from mechanically ventilated patients with vasopressor-dependent septic shock from the placebo arm of a recently completed clinical trial. Baseline serum metabolites were measured by liquid chromatography-mass spectrometry and ¹H-nuclear magnetic resonance. We conducted a time-to-event analysis censored at 28 days. Specifically, we determined the relationship between metabolites and time to extubation and freedom from vasopressors using a competing risk survival model, with death as a competing risk. We also compared metabolite concentrations between CCI patients, defined as intensive care unit level of care ≥ 14 days, and those with rapid recovery. Elevations in two acylcarnitines and four amino acids were related to the freedom from organ support (subdistributional hazard ratio < 1 and false discovery rate < 0.05). Proline, glycine, glutamine, and methionine were also elevated in patients who developed CCI. Our work highlights the need for further testing of metabolomics to identify patients at risk of CCI and to elucidate potential mechanisms that contribute to its etiology.

Quantitative Analysis of the Phase Transition Mechanism Underpinning the Systemic Self-Assembly of a Mechanopharmaceutical Device

Clofazimine (CFZ) is a poorly soluble, weakly basic, small molecule antibiotic clinically used to treat leprosy and is now in clinical trials as a treatment for multidrug resistant tuberculosis and COVID-19. CFZ exhibits complex, context-dependent pharmacokinetics that are characterized by an increasing half-life in long term treatment regimens. The systemic pharmacokinetics of CFZ have been previously represented by a nonlinear, 2-compartment model incorporating an expanding volume of distribution. This expansion reflects the soluble-to-insoluble phase transition that the drug undergoes as it precipitates out and accumulates within macrophages disseminated throughout the organism. Using mice as a model organism, we studied the mechanistic underpinnings of this increasing half-life and how the systemic pharmacokinetics of CFZ are altered with continued dosing. To this end, M. tuberculosis infection status and multiple dosing schemes were studied alongside a parameter sensitivity analysis (PSA) to further understanding of systemic drug distribution. Parameter values governing the sigmoidal expansion function that captures the phase transition were methodically varied, and in turn, the systemic concentrations of the drug were calculated and compared to the experimentally measured concentrations of drug in serum and spleen. The resulting amounts of drug sequestered were dependent on the total mass of CFZ administered and the duration of drug loading. This phenomenon can be captured by altering three different parameters of an expansion function corresponding to key biological determinants responsible for the precipitation and the accumulation of the insoluble drug mass in macrophages. Through this analysis of the context dependent pharmacokinetics of CFZ, a predictive framework for projecting the systemic distribution and self-assembly of precipitated drug complexes as intracellular mechanopharmaceutical devices of this and other drugs exhibiting similarly complex pharmacokinetics can be constructed.

Citrullinated Histone H3 Mediates Sepsis-Induced Lung Injury Through Activating Caspase-1 Dependent Inflammasome Pathway

Sepsis is a life-threatening organ dysfunction caused by dysregulated host response to infection that often results in acute lung injury (ALI)/acute respiratory distress syndrome (ARDS). An emerging mechanism of sepsis-induced ARDS involves neutrophils/macrophages undergoing cell death, releasing nuclear histones to cause tissue damage that exacerbates pulmonary injury. While published studies focus on unmodified histones, little is known about the role of citrullinated histone H3 (CitH3) in the pathogenesis of sepsis and ALI. In this study, we found that levels of CitH3 were elevated in the patients with sepsis-induced ARDS and correlated to PaO2/FiO2 in septic patients. Systematic administration of CitH3 peptide in mice provoked Caspase-1 activation in the lung tissue and caused ALI. Neutralization of CitH3 with monoclonal antibody improved survival and attenuated ALI in a mouse sepsis model. Furthermore, we demonstrated that CitH3 induces ALI through activating Caspase-1 dependent inflammasome in bone marrow derived macrophages and bone marrow derived dendritic cells. Our study suggests that CitH3 is an important mediator of inflammation and mortality during sepsis-induced ALI.

Breath analysis for detection and trajectory monitoring of acute respiratory distress syndrome in swine

Despite the enormous impact on human health, acute respiratory distress syndrome (ARDS) is poorly defined, and its timely diagnosis is difficult, as is tracking the course of the syndrome. The objective of this pilot study was to explore the utility of breath collection and analysis methodologies to detect ARDS through changes in the volatile organic compound (VOC) profiles present in breath. Five male Yorkshire mix swine were studied and ARDS was induced using both direct and indirect lung injury. An automated portable gas chromatography device developed in-house was used for point of care breath analysis and to monitor swine breath hourly, starting from initiation of the experiment until the development of ARDS, which was adjudicated based on the Berlin criteria at the breath sampling points and confirmed by lung biopsy at the end of the experiment. A total of 67 breath samples (chromatograms) were collected and analysed. Through machine learning, principal component analysis and linear discrimination analysis, seven VOC biomarkers were identified that distinguished ARDS. These represent seven of the nine biomarkers found in our breath analysis study of human ARDS, corroborating our findings. We also demonstrated that breath analysis detects changes 1–6 h earlier than the clinical adjudication based on the Berlin criteria. The findings provide proof of concept that breath analysis can be used to identify early changes associated with ARDS pathogenesis in swine. Its clinical application could provide intensive care clinicians with a noninvasive diagnostic tool for early detection and continuous monitoring of ARDS.

ARDS, confirmed by lung biopsy, was induced in swine, with breath monitored hourly. Seven VOC markers distinguish ARDS, which are the same as those in human ARDS and can predict ARDS onset ∼3 h earlier than clinical adjudication.https://bit.ly/3zIIIMQ

Cyst fluid metabolites distinguish malignant from benign pancreatic cysts

OBJECTIVES

Current standard of care imaging, cytology, or cystic fluid analysis cannot reliably differentiate malignant from benign pancreatic cystic neoplasms. This study sought to determine if the metabolic profile of cystic fluid could distinguish benign and malignant lesions, as well as mucinous and non-mucinous lesions.

Methods

Metabolic profiling by untargeted mass spectrometry and quantitative nuclear magnetic resonance was performed in 24 pancreatic cyst fluid from surgically resected samples with pathological diagnoses and clinicopathological correlation.

Results

(Iso)-butyrylcarnitine distinguished malignant from benign pancreatic cysts, with a diagnostic accuracy of 89%. (Iso)-butyrylcarnitine was 28-fold more abundant in malignant cyst fluid compared with benign cyst fluid (P=.048). Furthermore, 5-oxoproline (P=.01) differentiated mucinous from non-mucinous cysts with a diagnostic accuracy of 90%, better than glucose (82% accuracy), a previously described metabolite that distinguishes mucinous from non-mucinous cysts. Combined analysis of glucose and 5-oxoproline did not improve the diagnostic accuracy. In comparison, standard of care cyst fluid carcinoembryonic antigen (CEA) and cytology had a diagnostic accuracy of 40% and 60% respectively for mucinous cysts. (Iso)-butyrylcarnitine and 5-oxoproline correlated with cyst fluid CEA levels (P<.0001 and P<.05 respectively). For diagnosing malignant pancreatic cysts, the diagnostic accuracies of cyst size > 3 cm, ≥ 1 high-risk features, cyst fluid CEA, and cytology are 38%, 75%, 80%, and 75%, respectively.

Conclusions

(Iso)-butyrylcarnitine has potential clinical application for accurately distinguishing malignant from benign pancreatic cysts, and 5-oxoproline for distinguishing mucinous from non-mucinous cysts.

Functional lower airways genomic profiling of the microbiome to capture active microbial metabolism

BACKGROUND

Microbiome studies of the lower airways based on bacterial 16S rRNA gene sequencing assess microbial community structure but can only infer functional characteristics. Microbial products, such as short-chain fatty acids (SCFAs), in the lower airways have significant impact on the host's immune tone. Thus, functional approaches to the analyses of the microbiome are necessary.

METHODS

Here we used upper and lower airway samples from a research bronchoscopy smoker cohort. In addition, we validated our results in an experimental mouse model. We extended our microbiota characterisation beyond 16S rRNA gene sequencing with the use of whole-genome shotgun (WGS) and RNA metatranscriptome sequencing. SCFAs were also measured in lower airway samples and correlated with each of the sequencing datasets. In the mouse model, 16S rRNA gene and RNA metatranscriptome sequencing were performed.

RESULTS

Functional evaluations of the lower airway microbiota using inferred metagenome, WGS and metatranscriptome data were dissimilar. Comparison with measured levels of SCFAs shows that the inferred metagenome from the 16S rRNA gene sequencing data was poorly correlated, while better correlations were noted when SCFA levels were compared with WGS and metatranscriptome data. Modelling lower airway aspiration with oral commensals in a mouse model showed that the metatranscriptome most efficiently captures transient active microbial metabolism, which was overestimated by 16S rRNA gene sequencing.

CONCLUSIONS

Functional characterisation of the lower airway microbiota through metatranscriptome data identifies metabolically active organisms capable of producing metabolites with immunomodulatory capacity, such as SCFAs.

Pharmacometabolomics identifies candidate predictor metabolites of an L-carnitine treatment mortality benefit in septic shock

Sepsis‐induced metabolic dysfunction contributes to organ failure and death. L‐carnitine has shown promise for septic shock, but a recent phase II study of patients with vasopressor‐dependent septic shock demonstrated a non‐significant reduction in mortality. We undertook a pharmacometabolomics study of these patients (n = 250) to identify metabolic profiles predictive of a 90‐day mortality benefit from L‐carnitine. The independent predictive value of each pretreatment metabolite concentration, adjusted for L‐carnitine dose, on 90‐day mortality was determined by logistic regression. A grid‐search analysis maximizing the Z‐statistic from a binomial proportion test identified specific metabolite threshold levels that discriminated L‐carnitine responsive patients. Threshold concentrations were further assessed by hazard ratio and Kaplan‐Meier estimate. Accounting for L‐carnitine treatment and dose, 11 ¹H‐NMR metabolites and 12 acylcarnitines were independent predictors of 90‐day mortality. Based on the grid‐search analysis numerous acylcarnitines and valine were identified as candidate metabolites of drug response. Acetylcarnitine emerged as highly viable for the prediction of an L‐carnitine mortality benefit due to its abundance and biological relevance. Using its most statistically significant threshold concentration, patients with pretreatment acetylcarnitine greater than or equal to 35 µM were less likely to die at 90 days if treated with L‐carnitine (18 g) versus placebo (p = 0.01 by log rank test). Metabolomics also identified independent predictors of 90‐day sepsis mortality. Our proof‐of‐concept approach shows how pharmacometabolomics could be useful for tackling the heterogeneity of sepsis and informing clinical trial design. In addition, metabolomics can help understand mechanisms of sepsis heterogeneity and variable drug response, because sepsis induces alterations in numerous metabolite concentrations.

Serum Levels of Branched Chain Amino Acids Predict Duration of Cardiovascular Organ Failure in Septic Shock

BACKGROUND

Sepsis shifts cardiac metabolic fuel preference and this disruption may have implications for cardiovascular function. A greater understanding of the role of metabolism in the development and persistence of cardiovascular failure in sepsis could serve to identify novel pharmacotherapeutic approaches.

METHODS

Secondary analysis of prospective quantitative proton nuclear magnetic resonance (1H-NMR) metabolomic data from patients enrolled in a phase II randomized control trial of L-carnitine in septic shock. Participants with a sequential organ failure assessment (SOFA) score of > = 5, lactate > = 2, and requiring vasopressor support for at least 4 h were eligible for enrollment. The independent prognostic value of metabolites to predict survival with shock resolution within 48 h and vasopressor free days were assessed. Concentrations of predictive metabolites were compared between participants with and without shock resolution at 48 h.

RESULTS

Serum 1H-NMR metabolomics data from 228 patients were analyzed. Eighty-one (36%) patients met the primary outcome; 33 (14%) died prior to 48 h. The branched chain amino acids (BCAA), valine, leucine, and isoleucine were univariate predictors of the primary outcome after adjusting for multiple hypothesis testing, while valine remained significant after controlling for SOFA score. Similar results were observed when analyzed based on vasopressor free days, and persisted after controlling for confounding variables and excluding non-survivors. BCAA concentrations at 48 h significantly discriminated between those with shock resolution versus persistent shock.

CONCLUSIONS

Among patients with septic shock, BCAA concentrations independently predict time to shock resolution. This study provides hypothesis generating data into the potential contribution of BCAAs to the pathophysiology of cardiovascular failure in sepsis, opening areas for future investigations.

A novel swine model of the acute respiratory distress syndrome using clinically relevant injury exposures

To date, existing animal models of the acute respiratory distress syndrome (ARDS) have failed to translate preclinical discoveries into effective pharmacotherapy or diagnostic biomarkers. To address this translational gap, we developed a high-fidelity swine model of ARDS utilizing clinically relevant lung injury exposures. Fourteen male swine were anesthetized, mechanically ventilated, and surgically instrumented for hemodynamic monitoring, blood, and tissue sampling. Animals were allocated to one of three groups: (1) Indirect lung injury only: animals were inoculated by direct injection of Escherichia coli into the kidney parenchyma, provoking systemic inflammation and distributive shock physiology; (2) Direct lung injury only: animals received volutrauma, hyperoxia, and bronchoscope-delivered gastric particles; (3) Combined indirect and direct lung injury: animals were administered both above-described indirect and direct lung injury exposures. Animals were monitored for up to 12 h, with serial collection of physiologic data, blood samples, and radiographic imaging. Lung tissue was acquired postmortem for pathological examination. In contrast to indirect lung injury only and direct lung injury only groups, animals in the combined indirect and direct lung injury group exhibited all of the physiological, radiographic, and histopathologic hallmarks of human ARDS: impaired gas exchange (mean PaO₂ /FiO₂ ratio 124.8 ± 63.8), diffuse bilateral opacities on chest radiographs, and extensive pathologic evidence of diffuse alveolar damage. Our novel porcine model of ARDS, built on clinically relevant lung injury exposures, faithfully recapitulates the physiologic, radiographic, and histopathologic features of human ARDS and fills a crucial gap in the translational study of human lung injury.

Genetic and Metabolite Variability in One-Carbon Metabolism Applied to an Insulin Resistance Model in Patients With Schizophrenia Receiving Atypical Antipsychotics

Background: Patients with schizophrenia are at high risk of pre-mature mortality due to cardiovascular disease (CVD). Our group has completed studies in pharmacogenomics and metabolomics that have independently identified perturbations in one-carbon metabolism as associated with risk factors for CVD in this patient population. Therefore, this study aimed to use genetic and metabolomic data to determine the relationship between folate pharmacogenomics, one-carbon metabolites, and insulin resistance as measured using the homeostatic model assessment for insulin resistance (HOMA-IR) as a marker of CVD. Methods: Participants in this pilot analysis were on a stable atypical antipsychotic regimen for at least 6 months, with no diabetes diagnosis or use of antidiabetic medications. Participant samples were genotyped for MTHFR variants rs1801131 (MTHFR A1298C) and rs1801133 (MTHFR C677T). Serum metabolite concentrations were obtained with NMR. A least squares regression model was used to predict log(HOMA-IR) values based on the following independent variables: serum glutamate, glycine, betaine, serine, and threonine concentrations, and carrier status of the variant alleles for the selected genotypes. Results: A total of 67 participants were included, with a median age of 47 years old (IQR 42-52), 39% were female, and the median BMI was 30.3 (IQR 26.3-37.1). Overall, the model demonstrated an ability to predict log(HOMA-IR) values with an adjusted R ² of 0.44 and a p-value of < 0.001. Glutamate, threonine, and carrier status of the MTHFR 1298 C or MTHFR 677 T allele were positively correlated with log(HOMA-IR), whereas glycine, serine, and betaine concentrations trended inversely with log(HOMA-IR). All factors included in this final model were considered as having a possible effect on predicting log(HOMA-IR) as measured with a p-value < 0.1. Conclusions: Presence of pharmacogenomic variants that decrease the functional capacity of the MTHFR enzyme are associated with increased risk for cardiovascular disease, as measured in this instance by log(HOMA-IR). Furthermore, serine, glycine, and betaine concentrations trended inversely with HOMA-IR, suggesting that increased presence of methyl-donating groups is associated with lower measures of insulin resistance. Ultimately, these results will need to be replicated in a significantly larger population.

A comprehensive assessment of multi-system responses to a renal inoculation of uropathogenic E. coli in swine

BACKGROUND

The systemic responses to infection and its progression to sepsis remains poorly understood. Progress in the field has been stifled by the shortcomings of experimental models which include poor replication of the human condition. To address these challenges, we developed and piloted a novel large animal model of severe infection that is capable of generating multi-system clinically relevant data.

METHODS

Male swine (n = 5) were anesthetized, mechanically ventilated, and surgically instrumented for continuous hemodynamic monitoring and serial blood sampling. Animals were inoculated with uropathogenic E. coli by direct injection into the renal parenchyma and were maintained until a priori endpoints were met. The natural history of the infection was studied. Animals were not resuscitated. Multi-system data were collected hourly to 6 hours; all animals were euthanized at predetermined physiologic endpoints.

RESULTS

Core body temperature progressively increased from mean (SD) 37.9(0.8)°C at baseline to 43.0(1.2)°C at experiment termination (p = 0.006). Mean arterial pressure did not begin to decline until 6h post inoculation, dropping from 86(9) mmHg at baseline to 28(5) mmHg (p = 0.005) at termination. Blood glucose progressively declined but lactate levels did not elevate until the last hours of the experiment. There were also temporal changes in whole blood concentrations of a number of metabolites including increases in the catecholamine precursors, tyrosine (p = 0.005) and phenylalanine (p = 0.005). Lung, liver, and kidney function parameters worsened as infection progressed and at study termination there was histopathological evidence of injury in these end-organs.

CONCLUSION

We demonstrate a versatile, multi-system, longitudinal, swine model of infection that could be used to further our understanding of the mechanisms that underlie infection-induced multi-organ dysfunction and failure, optimize resuscitation protocols and test therapeutic interventions. Such a model could improve translation of findings from the bench to the bedside, circumventing a significant obstacle in sepsis research.

Peptidylarginine deiminase 2 has potential as both a biomarker and therapeutic target of sepsis

Peptidylarginine deiminases (PADs) are a family of calcium-dependent enzymes that are involved in a variety of human disorders, including cancer and autoimmune diseases. Although targeting PAD4 has shown no benefit in sepsis, the role of PAD2 remains unknown. Here, we report that PAD2 is engaged in sepsis and sepsis-induced acute lung injury in both human patients and mice. Pad2^–/– or selective inhibition of PAD2 by a small molecule inhibitor increased survival and improved overall outcomes in mouse models of sepsis. Pad2 deficiency decreased neutrophil extracellular trap (NET) formation. Importantly, Pad2 deficiency inhibited Caspase-11–dependent pyroptosis in vivo and in vitro. Suppression of PAD2 expression reduced inflammation and increased macrophage bactericidal activity. In contrast to Pad2^–/–, Pad4 deficiency enhanced activation of Caspase-11–dependent pyroptosis in BM-derived macrophages and displayed no survival improvement in a mouse sepsis model. Collectively, our findings highlight the potential of PAD2 as an indicative marker and therapeutic target for sepsis.

Peptidylarginine deiminases 2 (PAD2) regulates neutrophil extracellular trap (NET) formation in sepsis and sepsis-induced acute lung injury.

Serum citrullinated histone H3 concentrations differentiate patients with septic verses non-septic shock and correlate with disease severity

Purpose

Microbial infection stimulates neutrophil/macrophage/monocyte extracellular trap formation, which leads to the release of citrullinated histone H3 (CitH3) catalyzed by peptidylarginine deiminase (PAD) 2 and 4. Understanding these molecular mechanisms in the pathogenesis of septic shock will be an important next step for developing novel diagnostic and treatment modalities. We sought to determine the expression of CitH3 in patients with septic shock, and to correlate CitH3 levels with PAD2/PAD4 and clinically relevant outcomes.

Methods

Levels of CitH3 were measured in serum samples of 160 critically ill patients with septic and non-septic shock, and healthy volunteers. Analyses of clinical and laboratory characteristics of patients were conducted.

Results

Levels of circulating CitH3 at enrollment were significantly increased in septic shock patients (n = 102) compared to patients hospitalized with non-infectious shock (NIC) (n = 32, p < 0.0001). The area under the curve (95% CI) for distinguishing septic shock from NIC using CitH3 was 0.76 (0.65–0.86). CitH3 was positively correlated with PAD2 and PAD4 concentrations and Sequential Organ Failure Assessment Scores [total score (r = 0.36, p < 0.0001)]. The serum levels of CitH3 at 24 h (p < 0.01) and 48 h (p < 0.05) were significantly higher in the septic patients that did not survive.

Conclusion

CitH3 is increased in patients with septic shock. Its serum concentrations correlate with disease severity and prognosis, which may yield vital insights into the pathophysiology of sepsis.

Electronic supplementary material

The online version of this article (10.1007/s15010-020-01528-y) contains supplementary material, which is available to authorized users.

Using l-Carnitine as a Pharmacologic Probe of the Interpatient and Metabolic Variability of Sepsis

OBJECTIVE

The objective of this review is to discuss the therapeutic use and differential treatment response to Levo-carnitine (l-carnitine) treatment in septic shock, and to demonstrate common lessons learned that are important to the advancement of precision medicine approaches to sepsis. We propose that significant interpatient variability in the metabolic response to l-carnitine and clinical outcomes can be used to elucidate the mechanistic underpinnings that contribute to sepsis heterogeneity.

METHODS

A narrative review was conducted that focused on explaining interpatient variability in l-carnitine treatment response. Relevant biological and patient-level characteristics considered include genetic, metabolic, and morphomic phenotypes; potential drug interactions; and pharmacokinetics (PKs).

MAIN RESULTS

Despite promising results in a phase I study, a recent phase II clinical trial of l-carnitine treatment in septic shock showed a nonsignificant reduction in mortality. However, l-carnitine treatment induces significant interpatient variability in l-carnitine and acylcarnitine concentrations over time. In particular, administration of l-carnitine induces a broad, dynamic range of serum concentrations and measured peak concentrations are associated with mortality. Applied systems pharmacology may explain variability in drug responsiveness by using patient characteristics to identify pretreatment phenotypes most likely to derive benefit from l-carnitine. Moreover, provocation of sepsis metabolism with l-carnitine offers a unique opportunity to identify metabolic response signatures associated with patient outcomes. These approaches can unmask latent metabolic pathways deranged in the sepsis syndrome and offer insight into the pathophysiology, progression, and heterogeneity of the disease.

CONCLUSIONS

The compiled evidence suggests there are several potential explanations for the variability in carnitine concentrations and clinical response to l-carnitine in septic shock. These serve as important confounders that should be considered in interpretation of l-carnitine clinical studies and broadly holds lessons for future clinical trial design in sepsis. Consideration of these factors is needed if precision medicine in sepsis is to be achieved.

A Multilevel Bayesian Approach to Improve Effect Size Estimation in Regression Modeling of Metabolomics Data Utilizing Imputation with Uncertainty

To ensure scientific reproducibility of metabolomics data, alternative statistical methods are needed. A paradigm shift away from the p-value toward an embracement of uncertainty and interval estimation of a metabolite's true effect size may lead to improved study design and greater reproducibility. Multilevel Bayesian models are one approach that offer the added opportunity of incorporating imputed value uncertainty when missing data are present. We designed simulations of metabolomics data to compare multilevel Bayesian models to standard logistic regression with corrections for multiple hypothesis testing. Our simulations altered the sample size and the fraction of significant metabolites truly different between two outcome groups. We then introduced missingness to further assess model performance. Across simulations, the multilevel Bayesian approach more accurately estimated the effect size of metabolites that were significantly different between groups. Bayesian models also had greater power and mitigated the false discovery rate. In the presence of increased missing data, Bayesian models were able to accurately impute the true concentration and incorporating the uncertainty of these estimates improved overall prediction. In summary, our simulations demonstrate that a multilevel Bayesian approach accurately quantifies the estimated effect size of metabolite predictors in regression modeling, particularly in the presence of missing data.

Impact of the pre-illness lipid profile on sepsis mortality

PURPOSE

To determine if baseline lipid levels contribute to the relationship between lipid levels during sepsis and outcomes.

MATERIALS AND METHODS

We conducted a retrospective cohort study at a tertiary-care academic medical center. Multivariable logistic regression models were used to adjust for confounders. Both Systemic Inflammatory Response Syndrome (SIRS) and Sequential Organ Failure Assessment (SOFA) score-based definitions of sepsis were analyzed.

MEASUREMENTS AND MAIN RESULTS

After adjusting for patient characteristics and severity of illness, baseline values for both low density lipoprotein (LDL) cholesterol and triglycerides were associated with mortality (LDL cholesterol odds ratio [OR] 0.44, 95% confidence interval [CI] 0.23-0.84, p = .013; triglyceride OR 0.54, 95% CI 0.37-0.78, p = .001) using a SIRS based definition of sepsis. An interaction existed between these two variables, which resulted in increased mortality with higher baseline low density lipoprotein (LDL) cholesterol values for individuals with triglycerides below 208 mg/dL and the opposite direction of association above this level (interaction OR 1.48, 95% CI 1.02-2.16, p = .039). When using a SOFA score-based definition, only triglycerides remained associated with the mortality (OR 0.55, 95% CI 0.35-0.86, p = .008).

CONCLUSIONS

Baseline lipid values, particularly triglyceride concentrations, are associated with hospital mortality in septic patients.

Disruption of histidine and energy homeostasis in chronic obstructive pulmonary disease

Background

Chronic obstructive pulmonary disease (COPD) is a systemic condition that is too complex to be assessed by lung function alone. Metabolomics has the potential to help understand the mechanistic underpinnings that contribute to COPD pathogenesis. Since blood metabolomics may be affected by sex and body mass index (BMI), the aim of this study was to determine the metabolomic variability in male smokers with and without COPD who have a narrow BMI range.

Methods

We compared the quantitative proton nuclear magnetic resonance acquired serum metabolomics of a male Chinese Han population of non-smokers without COPD, and smokers with and without COPD. We also assessed the impact of smoking status on metabolite concentrations and the associations between metabolite concentrations and inflammatory markers such as serum interleukin-6 and histamine, and blood cell differential (%). Metabolomics data were log-transformed and auto-scaled for parametric statistical analysis. Mean normalized metabolite concentration values and continuous demographic variables were compared by Student’s t-test with Welch correction or ANOVA with post-hoc Tukey’s test, as applicable; t-test p-values for metabolomics data were corrected for false discovery rate (FDR). A Pearson association matrix was built to evaluate the relationship between metabolite concentrations, clinical parameters and markers of inflammation.

Results

Twenty-eight metabolites were identified and quantified. Creatine, glycine, histidine, and threonine concentrations were reduced in COPD patients compared to non-COPD smokers (FDR ≤15%). Concentrations of these metabolites were inversely correlated with interleukin-6 levels. COPD patients had overall dampening of metabolite concentrations including energy-related metabolic pathways such as creatine metabolism. They also had higher histamine levels and percent basophils compared to smokers without COPD.

Conclusion

COPD is associated with alterations in the serum metabolome, including a disruption in the histidine-histamine and creatine metabolic pathways. These findings support the use of metabolomics to understand the pathogenic mechanisms involved in COPD.

Trial registrationwww.clinicaltrials.gov, NCT03310177.

Bronchoalveolar Lavage Fluid from COPD Patients Reveals More Compounds Associated with Disease than Matched Plasma

Smoking causes chronic obstructive pulmonary disease (COPD). Though recent studies identified a COPD metabolomic signature in blood, no large studies examine the metabolome in bronchoalveolar lavage (BAL) fluid, a more direct representation of lung cell metabolism. We performed untargeted liquid chromatography-mass spectrometry (LC-MS) on BAL and matched plasma from 115 subjects from the SPIROMICS cohort. Regression was performed with COPD phenotypes as the outcome and metabolites as the predictor, adjusted for clinical covariates and false discovery rate. Weighted gene co-expression network analysis (WGCNA) grouped metabolites into modules which were then associated with phenotypes. K-means clustering grouped similar subjects. We detected 7939 and 10,561 compounds in BAL and paired plasma samples, respectively. FEV₁/FVC (Forced Expiratory Volume in One Second/Forced Vital Capacity) ratio, emphysema, FEV₁ % predicted, and COPD exacerbations associated with 1230, 792, eight, and one BAL compounds, respectively. Only two plasma compounds associated with a COPD phenotype (emphysema). Three BAL co-expression modules associated with FEV₁/FVC and emphysema. K-means BAL metabolomic signature clustering identified two groups, one with more airway obstruction (34% of subjects, median FEV₁/FVC 0.67), one with less (66% of subjects, median FEV₁/FVC 0.77; p < 2 × 10^-4). Associations between metabolites and COPD phenotypes are more robustly represented in BAL compared to plasma.

Inkjet-printed micro-calibration standards for ultraquantitative Raman spectral cytometry

Herein we report the development of a cytometric analysis platform for measuring the contents of individual cells in absolute (picogram) scales; this study represents the first report of Raman-based quantitation of the absolute mass - or the total amount - of multiple endogenous biomolecules within single-cells. To enable ultraquantitative calibration, we engineered single-cell-sized micro-calibration standards of known composition by inkjet-printer deposition of biomolecular components in microarrays across the surface of silicon chips. We demonstrate clinical feasibility by characterizing the compositional phenotype of human skin fibroblast and porcine alveolar macrophage cell populations in the respective contexts of Niemann-Pick disease and drug-induced phospholipidosis: two types of lipid storage disorders. We envision this microanalytical platform as the foundation for many future biomedical applications, ranging from diagnostic assays to pathological analysis to advanced pharmaco/toxicokinetic research studies.

Untargeted Metabolomics Differentiates l-Carnitine Treated Septic Shock 1-Year Survivors and Nonsurvivors

l-Carnitine is a candidate therapeutic for the treatment of septic shock, a condition that carries a ≥40% mortality. Responsiveness to l-carnitine may hinge on unique metabolic profiles that are not evident from the clinical phenotype. To define these profiles, we performed an untargeted metabolomic analysis of serum from 21 male sepsis patients enrolled in a placebo-controlled l-carnitine clinical trial. Although treatment with l-carnitine is known to induce changes in the sepsis metabolome, we found a distinct set of metabolites that differentiated 1-year survivors from nonsurvivors. Following feature alignment, we employed a new and innovative data reduction strategy followed by false discovery correction, and identified 63 metabolites that differentiated carnitine-treated 1-year survivors versus nonsurvivors. Following identification by MS/MS and database search, several metabolite markers of vascular inflammation were determined to be prominently elevated in the carnitine-treated nonsurvivor cohort, including fibrinopeptide A, allysine, and histamine. While preliminary, these results corroborate that metabolic profiles may be useful to differentiate l-carnitine treatment responsiveness. Furthermore, these data show that the metabolic signature of l-carnitine-treated nonsurvivors is associated with a severity of illness (e.g., vascular inflammation) that is not routinely clinically detected.

Rapid, Reproducible, Quantifiable NMR Metabolomics: Methanol and Methanol: Chloroform Precipitation for Removal of Macromolecules in Serum and Whole Blood

Background: Though blood is an excellent biofluid for metabolomics, proteins and lipids present in blood can interfere with 1d-¹H NMR spectra and disrupt quantification of metabolites. Here, we present effective macromolecule removal strategies for serum and whole blood (WB) samples. Methods: A variety of macromolecule removal strategies were compared in both WB and serum, along with tests of ultrafiltration alone and in combination with precipitation methods. Results: In healthy human serum, methanol:chloroform:water extraction with ultrafiltration was compared to methanol precipitation with and without ultrafiltration. Methods were tested in healthy pooled human serum, and in serum from patients with sepsis. Effects of long-term storage at −80 °C were tested to explore the impact of macromolecule removal strategy on serum from different conditions. In WB a variety of extraction strategies were tested in two types of WB (from pigs and baboons) to examine the impact of macromolecule removal strategies on different samples. Conclusions: In healthy human serum methanol precipitation of serum with ultrafiltration was superior, but was similar in recovery and variance to methanol:chloroform:water extraction with ultrafiltration in pooled serum from patients with sepsis. In WB, high quality, quantifiable spectra were obtained with the use of a methanol: chloroform precipitation.

An Expandable Mechanopharmaceutical Device (1): Measuring the Cargo Capacity of Macrophages in a Living Organism

PURPOSE

Clofazimine (CFZ) is an FDA-approved, poorly soluble small molecule drug that precipitates as crystal-like drug inclusions (CLDIs) which accumulate in acidic cytoplasmic organelles of macrophages. In this study, we considered CLDIs as an expandable mechanopharmaceutical device, to study how macrophages respond to an increasingly massive load of endophagolysosomal cargo.

METHODS

First, we experimentally tested how the accumulation of CFZ in CLDIs impacted different immune cell subpopulations of different organs. Second, to further investigate the mechanism of CLDI formation, we asked whether specific accumulation of CFZ hydrochloride crystals in lysosomes could be explained as a passive, thermodynamic equilibrium phenomenon. A cellular pharmacokinetic model was constructed, simulating CFZ accumulation driven by pH-dependent ion trapping of the protonated drug in the acidic lysosomes, followed by the precipitation of CFZ hydrochloride salt via a common ion effect caused by high chloride concentrations.

RESULTS

While lower loads of CFZ were mostly accommodated in lung macrophages, increased CFZ loading was accompanied by organ-specific changes in macrophage numbers, size and intracellular membrane architecture, maximizing the cargo storage capabilities. With increasing loads, the total cargo mass and concentrations of CFZ in different organs diverged, while that of individual macrophages converged. The simulation results support the notion that the proton and chloride ion concentrations of macrophage lysosomes are sufficient to drive the massive, cell type-selective accumulation and growth of CFZ hydrochloride biocrystals.

CONCLUSION

CLDIs effectively function as an expandable mechanopharmaceutical device, revealing the coordinated response of the macrophage population to an increasingly massive, whole-organism endophagolysosomal cargo load.

An Expandable Mechanopharmaceutical Device (2): Drug Induced Granulomas Maximize the Cargo Sequestering Capacity of Macrophages in the Liver

PURPOSE

Drug-induced liver injuries (DILI) comprise a significant proportion of adverse drug reactions leading to hospitalizations and death. One frequent DILI is granulomatous inflammation from exposure to harmful metabolites that activate inflammatory pathways of immune cells of the liver, which may act as a barrier to isolate the irritating stimulus and limit tissue damage.

METHODS

Paralleling the accumulation of CFZ precipitates in the liver, granulomatous inflammation was studied to gain insight into its effect on liver structure and function. A structural analog that does not precipitate within macrophages was also studied using micro-analytical approaches. Depleting macrophages was used to inhibit granuloma formation and assess its effect on drug bioaccumulation and toxicity.

RESULTS

Granuloma-associated macrophages showed a distinct phenotype, differentiating them from non-granuloma macrophages. Granulomas were induced by insoluble CFZ cargo, but not by the more soluble analog, pointing to precipitation being a factor driving granulomatous inflammation. Granuloma-associated macrophages showed increased activation of lysosomal master-regulator transcription factor EB (TFEB). Inhibiting granuloma formation increased hepatic necrosis and systemic toxicity in CFZ-treated animals.

CONCLUSIONS

Granuloma-associated macrophages are a specialized cell population equipped to actively sequester and stabilize cytotoxic chemotherapeutic agents. Thus, drug-induced granulomas may function as drug sequestering "organoids" -an induced, specialized sub-compartment- to limit tissue damage.

Atypical Antipsychotic Exposure May Not Differentiate Metabolic Phenotypes of Patients with Schizophrenia

STUDY OBJECTIVE

Patients with schizophrenia are known to have higher rates of metabolic disease than the general population. Contributing factors likely include lifestyle and atypical antipsychotic (AAP) use, but the underlying mechanisms are unknown. The objective of this study was to identify metabolomic variability in adult patients with schizophrenia who were taking AAPs and grouped by fasting insulin concentration, our surrogate marker for metabolic risk.

DESIGN

Metabolomics analysis PARTICIPANTS: Ninety-four adult patients with schizophrenia who were taking an AAP for at least 6 months, with no changes in their antipsychotic regimen for the previous 8 weeks, and who did not require treatment with insulin, participated in the study. Twenty age- and sex-matched nonobese (10 subjects) and obese (10 subjects) controls without cardiovascular disease or mental health diagnoses were used to match the body mass index (BMI) range of the patients with schizophrenia to account for metabolite concentration differences attributable to BMI.

MEASUREMENTS AND MAIN RESULTS

Existing serum samples were used to identify aqueous metabolites (to differentiate fasting insulin concentration quartiles) and fatty acids with quantitative nuclear magnetic resonance and gas chromatography methods, respectively. To exclude metabolites from our pathway mapping analysis that were due to variability in weight, we also subjected serum samples from the nonobese and obese controls to the same analyses. Patients with schizophrenia had a median age of 47.0 years (interquartile range 41.0-52.0 years). Using a false discovery rate threshold of less than 25%, 10 metabolites, not attributable to weight, differentiated insulin concentration quartiles in patients with schizophrenia and identified variability in one-carbon metabolism between groups. Patients with higher fasting insulin concentrations (quartiles 3 and 4) also trended toward higher levels of saturated fatty acids compared with patients with lower fasting insulin concentrations (quartiles 1 and 2).

CONCLUSION

Our results illustrate the utility of metabolomics to identify pathways underlying variable fasting insulin concentration in patients with schizophrenia. Importantly, no significant difference in AAP exposure was observed among groups, suggesting that current antipsychotic use may not be a primary factor that differentiates middle-aged adult patients with schizophrenia by fasting insulin concentration.

Associations of the plasma lipidome with mortality in the acute respiratory distress syndrome: a longitudinal cohort study

Background

It is unknown if the plasma lipidome is a useful tool for improving our understanding of the acute respiratory distress syndrome (ARDS). Therefore, we measured the plasma lipidome of individuals with ARDS at two time-points to determine if changes in the plasma lipidome distinguished survivors from non-survivors. We hypothesized that both the absolute concentration and change in concentration over time of plasma lipids are associated with 28-day mortality in this population.

Methods

Samples for this longitudinal observational cohort study were collected at multiple tertiary-care academic medical centers as part of a previous multicenter clinical trial. A mass spectrometry shot-gun lipidomic assay was used to quantify the lipidome in plasma samples from 30 individuals. Samples from two different days were analyzed for each subject. After removing lipids with a coefficient of variation > 30%, differences between cohorts were identified using repeated measures analysis of variance. The false discovery rate was used to adjust for multiple comparisons. Relationships between significant compounds were explored using hierarchical clustering of the Pearson correlation coefficients and the magnitude of these relationships was described using receiver operating characteristic curves.

Results

The mass spectrometry assay reliably measured 359 lipids. After adjusting for multiple comparisons, 90 compounds differed between survivors and non-survivors. Survivors had higher levels for each of these lipids except for five membrane lipids. Glycerolipids, particularly those containing polyunsaturated fatty acid side-chains, represented many of the lipids with higher concentrations in survivors. The change in lipid concentration over time did not differ between survivors and non-survivors.

Conclusions

The concentration of multiple plasma lipids is associated with mortality in this group of critically ill patients with ARDS. Absolute lipid levels provided more information than the change in concentration over time. These findings support future research aimed at integrating lipidomics into critical care medicine.

Electronic supplementary material

The online version of this article (10.1186/s12931-018-0758-3) contains supplementary material, which is available to authorized users.

Reverse Engineering the Intracellular Self-Assembly of a Functional Mechanopharmaceutical Device

Weakly basic, poorly soluble chemical agents could be exploited as building blocks for constructing sophisticated molecular devices inside the cells of living organisms. Here, using experimental and computational approaches, we probed the relationship between the biological mechanisms mediating lysosomal ion homeostasis and the self-assembly of a weakly basic small molecule building block (clofazimine) into a functional, mechanopharmaceutical device (intracellular Crystal-Like Drug Inclusions – “CLDIs”) in macrophage lysosomes. Physicochemical considerations indicate that the intralysosomal stabilization of the self-assembled mechanopharmaceutical device depends on the pH_max of the weakly basic building block and its affinity for chloride, both of which are consistent with the pH and chloride content of a physiological lysosomal microenvironment. Most importantly, in vitro and in silico studies revealed that high expression levels of the vacuolar ATPase (V-ATPase), irrespective of the expression levels of chloride channels, are necessary and sufficient to explain the cell-type dependent formation, stabilization, and biocompatibility of the self-assembled mechanopharmaceutical device within macrophages.

New Strategies and Challenges in Lung Proteomics and Metabolomics. An Official American Thoracic Society Workshop Report

This document presents the proceedings from the workshop entitled, "New Strategies and Challenges in Lung Proteomics and Metabolomics" held February 4th-5th, 2016, in Denver, Colorado. It was sponsored by the National Heart Lung Blood Institute, the American Thoracic Society, the Colorado Biological Mass Spectrometry Society, and National Jewish Health. The goal of this workshop was to convene, for the first time, relevant experts in lung proteomics and metabolomics to discuss and overcome specific challenges in these fields that are unique to the lung. The main objectives of this workshop were to identify, review, and/or understand: (1) emerging technologies in metabolomics and proteomics as applied to the study of the lung; (2) the unique composition and challenges of lung-specific biological specimens for metabolomic and proteomic analysis; (3) the diverse informatics approaches and databases unique to metabolomics and proteomics, with special emphasis on the lung; (4) integrative platforms across genetic and genomic databases that can be applied to lung-related metabolomic and proteomic studies; and (5) the clinical applications of proteomics and metabolomics. The major findings and conclusions of this workshop are summarized at the end of the report, and outline the progress and challenges that face these rapidly advancing fields.

The Physicochemical Basis of Clofazimine-Induced Skin Pigmentation

Clofazimine is a weakly basic, Food and Drug Administration-approved antibiotic recommended by the World Health Organization to treat leprosy and multi-drug-resistant tuberculosis. Upon prolonged treatment, clofazimine extensively bioaccumulates and precipitates throughout the organism, forming crystal-like drug inclusions (CLDIs). Due to the drug's red color, it is widely believed that clofazimine bioaccumulation results in skin pigmentation, its most common side effect. To test whether clofazimine-induced skin pigmentation is due to CLDI formation, we synthesized a closely related clofazimine analog that does not precipitate under physiological pH and chloride conditions that are required for CLDI formation. Despite the absence of detectable CLDIs in mice, administration of this analog still led to significant skin pigmentation. In clofazimine-treated mice, skin cryosections revealed no evidence of CLDIs when analyzed with a microscopic imaging system specifically designed for detecting clofazimine aggregates. Rather, the reflectance spectra of the skin revealed a signal corresponding to the soluble, free base form of the drug. Consistent with the low concentrations of clofazimine in the skin, these results suggest that clofazimine-induced skin pigmentation is not due to clofazimine precipitation and CLDI formation, but rather to the partitioning of the circulating, free base form of the drug into subcutaneous fat.

Metabolomics as a Driver in Advancing Precision Medicine in Sepsis

The objective of this review is to explain the science of metabolomics-a science of systems biology that measures and studies endogenous small molecules (metabolites) that are present in a single biological sample-and its application to the diagnosis and treatment of sepsis. In addition, we discuss how discovery through metabolomics can contribute to the development of precision medicine targets for this complex disease state and the potential avenues for those new discoveries to be applied in the clinical environment. A nonsystematic literature review was performed focusing on metabolomics, pharmacometabolomics, and sepsis. Human (adult and pediatric) and animal studies were included. Metabolomics has been investigated in the diagnosis, prognosis, and risk stratification of sepsis, as well as for the identification of drug target opportunities. Metabolomics elucidates a new level of detail when compared with other systems biology sciences, with regard to the metabolites that are most relevant in the pathophysiology of sepsis, as well as highlighting specific biochemical pathways at work in sepsis. Metabolomics also highlights biochemical differences between sepsis survivors and nonsurvivors at a level of detail greater than that demonstrated by genomics, transcriptomics, or proteomics, potentially leading to actionable targets for new therapies. The application of pharmacometabolomics and its integration with other systems pharmacology to sepsis therapeutics could be particularly helpful in differentiating drug responders and nonresponders and furthering knowledge of mechanisms of drug action and response. The accumulated literature on metabolomics suggests it is a viable tool for continued discovery around the pathophysiology, diagnosis and prognosis, and treatment of sepsis in both adults and children, and it provides a greater level of biochemical detail and insight than other systems biology approaches. However, the clinical application of metabolomics in sepsis has not yet been fully realized. Prospective validation studies are needed to translate metabolites from the discovery phase into the clinical utility phase.

Emerging Biomarkers of Illness Severity: Urinary Metabolites Associated with Sepsis and Necrotizing Methicillin-Resistant Staphylococcus aureus Pneumonia

Our objective was to illustrate the potential of metabolomics to identify novel biomarkers of illness severity in a child with fatal necrotizing pneumonia caused by methicillin-resistant Staphylococcus aureus (MRSA). We present a case report with two control groups and a metabolomics analysis: an infant with fatal MRSA pneumonia, four children with influenza pneumonia (pneumonia control group), and seven healthy children with no known infections (healthy control group). Urine samples were collected from all children. Metabolites were identified and quantified using ¹ H-nuclear magnetic resonance spectrometry. Normalized metabolite concentration data from children with influenza pneumonia and healthy controls were compared by using an unpaired Student t test. To identify differentiating metabolites of MRSA pneumonia, the fold change of each metabolite was calculated by dividing each urine metabolite concentration of the patient with fatal MRSA pneumonia by the median urine concentration values of the same metabolite of the patients with influenza pneumonia and healthy controls, respectively. MetScape (http://metscape.ncibi.org/), a bioinformatics tool, was used for data visualization and interpretation. Urine metabolite concentrations previously identified as associated with sepsis in children (e.g., 3-hydroxybutyrate, carnitine, and creatinine) were higher in the patient with fatal MRSA pneumonia compared with those of patients with influenza pneumonia and healthy controls. The concentrations of additional metabolites-acetone, acetoacetate, choline, fumarate, glucose, and 3-aminoisobutyrate-were more than 25-fold higher in the patient with MRSA pneumonia than those of patients with influenza pneumonia and healthy controls. These metabolic changes in the urine preceded the clinical severe sepsis phenotype, suggesting that detection of the extent of metabolic disruption can aid in the early identification of a sepsis phenotype in advance of the clinical diagnosis. These data also support the utility of metabolomics for the development of clinical assays to identify patients with pediatric pneumonia at high risk for deterioration.

Detecting ordered small molecule drug aggregates in live macrophages: a multi-parameter microscope image data acquisition and analysis strategy

Following prolonged administration, certain orally bioavailable but poorly soluble small molecule drugs are prone to precipitate out and form crystal-like drug inclusions (CLDIs) within the cells of living organisms. In this research, we present a quantitative multi-parameter imaging platform for measuring the fluorescence and polarization diattenuation signals of cells harboring intracellular CLDIs. To validate the imaging system, the FDA-approved drug clofazimine (CFZ) was used as a model compound. Our results demonstrated that a quantitative multi-parameter microscopy image analysis platform can be used to study drug sequestering macrophages, and to detect the formation of ordered molecular aggregates formed by poorly soluble small molecule drugs in animals.