Parenteral and enteral nutrition in surgical critical care: Plasma metabolomics demonstrates divergent effects on nitrogen, fatty-acid, ribonucleotide, and oxidative metabolism

Parent, Brodie A. MD, MS; Seaton, Max MD; Djukovic, Danijel PhD; Gu, Haiwei PhD; Wheelock, Brittany; Navarro, Sandi L. PhD; Raftery, Daniel PhD; O’Keefe, Grant E. MD, MPH

Journal of Trauma and Acute Care Surgery: April 2017 - Volume 82 - Issue 4 - p 704–713
doi: 10.1097/TA.0000000000001381
AAST Plenary Papers
Editor's Choice

BACKGROUND: Artificial nutrition support is central to the care of critically ill patients and is primarily provided enterally (EN). There are circumstances when parenteral nutrition (PN) is considered necessary. We are uncertain how each of these approaches confer clinical benefits beyond simply providing calories. We sought to better understand how each of these techniques influence metabolism in critically ill patients using a broad-based metabolomics approach. Metabolic responses to EN and PN may differ in ways that could help us understand how to optimize use of these therapies.

METHODS: We prospectively enrolled subjects over 7 months in 2015 at an urban, Level I trauma center. Subjects were included before starting either EN or PN during their inpatient admission. Plasma samples were obtained between 1 and 12 hours before initiation of artificial nutrition, and 3 and 7 days later. All samples were analyzed with liquid chromatography/mass spectrometry-based metabolomics. Differences in metabolite concentrations were assessed via principal component analyses and multiple linear regression.

RESULTS: We enrolled 30 subjects. Among the critically ill subjects, 10 received EN and 10 received PN. In subjects receiving EN, amino acid and urea cycle metabolites (citrulline, p = 0.04; ornithine, p = 0.05) increased, as did ribonucleic acid metabolites (uridine, p = 0.04; cysteine, 0 = 0.05; oxypurinol, p = 0.04). Oxidative stress decreased over time (increased betaine, p = 0.05; decreased 4-pyridoxic acid, p = 0.04). In subjects receiving PN, amino acid concentrations increased over time (taurine, p = 0.04; phenylalanine, p = 0.05); omega 6 and omega 3 fatty acid concentrations decreased over time (p = 0.05 and 0.03, respectively).

CONCLUSION: EN was associated with amino acid repletion, urea cycle upregulation, restoration of antioxidants, and increasing ribonucleic acid synthesis. Parenteral nutrition was associated with increased amino acid concentrations, but did not influence protein metabolism or antioxidant repletion. This suggests that parenteral amino acids are used less effectively than those given enterally. The biomarkers reported in this study may be useful in guiding nutrition therapy for critically ill patients.

LEVEL OF EVIDENCE: Therapeutic study, level III; prognostic study, level II.

From the Department of Surgery (B.A.P., M.S., D.D., B.W., G.E.O.) University of Washington Medical Center Harborview, Seattle Washington; Department of Surgery (M.S.), University of Maryland, Baltimore, Maryland; Mitochondria and Metabolism Center (H.G., D.R.), University of Washington, Seattle, Washington; Department of Epidemiology and Nutrition (S.L.N.), University of Washington, Seattle, Washington.

Submitted: August 31, 2016, Revised: October 24, 2016, Accepted: December 22, 2016, Published online: January 26, 2017.

This study was presented at the 75th annual meeting of the American Association for the Surgery of Trauma, September 13–16, 2016, in Waikoloa, Hawaii.

Supplemental digital content is available for this article. Direct URL citations appear in the printed text, and links to the digital files are provided in the HTML text of this article on the journal’s Web site (

Address for reprints: Brodie A. Parent, MD, MS, Department of Surgery, University of Washington Medical Center, Harborview 325 9th Ave, Seattle, WA 98104; email:

Article Outline

Nutrition therapy is important in the care of critically ill surgical patients. Early enteral nutrition has a favorable impact on clinical outcomes, such as nosocomial infections, duration of mechanical ventilation, length-of-stay, and mortality.1–3 However, published studies have led to varying recommendations for the optimal amount, type, route and timing of nutritional support.1,3–9 In particular, there is continuing controversy regarding the ideal clinical context for use of parenteral nutrition (PN).1 Enteral nutrition (EN) is generally the preferred form of artificial nutritional therapy in surgical critically ill patients, but PN may be of some benefit in certain circumstances.9 Biologic mechanisms for differences in patient response to PN and EN remain largely unclear.

Ongoing debates in surgical nutrition science may stem, in part, from our inability to reliably characterize metabolism and to precisely measure responses to nutrition therapy in critically ill patients.10,11 Although calorimetry and nitrogen-balance studies can provide some guidance, these methods are resource- and time-intensive, making them impractical for daily clinical use.10

Metabolomics, the study of small molecules involved in metabolism, may provide a rapid and comprehensive “snapshot” of physiology in critically ill patients.12 In this study, we aimed to understand how EN and PN influence metabolic pathways in critically ill patients using a broad-based metabolomics approach. We hypothesized that metabolism of amino acids after initiation of EN and PN would be quantifiably different. Insights into these metabolic differences may help us understand how to optimize use of these therapies, thereby minimizing complications and improving outcomes.

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Study Design, Subjects, and Setting

Critically ill trauma and surgical patients admitted to Harborview Medical Center from May 2015 to November 2015 were consented and enrolled in this prospective cohort study. Inclusion criteria were: (a) admission to the surgical or trauma intensive care unit; (b) impending initiation of nutrition support, with ability to donate a blood sample 1 to 12 hours before initiation; and c) age between 18 and 65 years. Ten healthy volunteers were also enrolled from among the hospital staff. These volunteers fasted for 12 hours, but were not hospitalized and were not on artificial nutrition. This group was included to help determine whether a given metabolite in a hospitalized patient had a higher or lower concentration than a “normal” non-hospitalized subject. However, no direct statistical comparisons were made using these nonhospitalized volunteers. Any subject was excluded if she/he had a history of cancer, endocrine disorders, or chronic organ dysfunction, or if they were pregnant, obese (body mass index, ≥ 35 m/kg2), had an active infection requiring antibiotic treatment, or had undergone an abdominal/orthopedic operation within 24 hours of sampling. These exclusion criteria were specified to reduce confounding factors, consistent with established procedures in other metabolomics studies.12,13 Patients who undergo exploratory laparotomy, pelvic fixation, or open long-bone fixation develop a postoperative inflammation response which is expected to be much more pronounced compared to other surgical procedures.13 Therefore, postoperative patients from these groups were specifically excluded. All study procedures were approved by the University of Washington Institutional Review Board.

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Sample Collection and Processing

Venous blood samples from critically ill subjects were obtained between 1 and 12 hours before nutrition initiation in 5 mL K2 EDTA Vacutainer tubes (Franklin Lakes, NJ), and on day three and day seven after starting nutrition. Blood samples from healthy volunteers were obtained the morning after at least 12 hours of fasting. Samples were placed on ice and centrifuged at 2,500g for 10 minutes. The plasma supernatants were then frozen at −80°C.

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Metabolite Measurements

Mass spectrometry–based analysis occurred for all plasma samples after thawing. Our detailed protocol for sample processing and metabolomics analysis has been previously reported.11 Briefly, after metabolite extraction, samples underwent targeted liquid chromatography and quadrupole mass spectrometry (Sciex 5500 Qtrap), and metabolites were identified by comparison with known standards to obtain relative concentrations. Quality control samples derived from the pooled plasma sample were included in all processing. We measured 214 previously identified metabolites from over 25 different metabolic pathways (see Table, Supplemental Digital Content 1,

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Treatment and Outcomes

The primary exposures of interest were EN or PN. Main outcomes were concentrations of plasma metabolites. The majority of metabolites were quantified via relative concentrations. Absolute quantification (μM) was possible for some amino acids because isotope-labeled internal standards for these compounds have been developed.14,15 Of note, we did not compare metabolic differences between EN and PN directly; rather, our focus in this study was to compare before and after the initiation of each therapy.

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Statistical Analysis and Data Presentation

Continuous data are represented as medians and interquartile ranges (IQRs). Categorical data are represented as counts and percentages.

Subjects were divided into groups based on receipt of EN versus PN for purposes of analysis. Broad metabolic comparisons before (day 0) and after (days 3 and 7) nutrition support initiation were made using principal component analysis (PCA),12 with oblique rotation to allow for clustering of repeated measures within individuals over time. We focused primarily on these before and after comparisons because the two groups of study subjects were doubtlessly quite different from a metabolic standpoint.

We also compared the three groups (critically ill subjects before initiation of nutritional support) to understand how they differed metabolically. Trends over time were assessed using linear regression with robust standard errors, allowing for clustering of repeated measures within individuals. One model was constructed for subjects on EN and one model was constructed for subjects on PN. The exposure variable corresponded to the time of nutrition initiation (a categorical variable for day 0, day 3, and day 7 of nutrition). Outcome variables were changes in metabolite concentrations over time. The Benjamini-Hochberg false-discovery rate correction16 was applied to all p values to account for multiple testing, and statistical significance was set at alpha ≤0.05. All statistical analyses were performed using Stata 12.1 (StataCorp., College Station, TX) and the R software environment, version Heat maps for metabolite concentrations were generated using “GENE-E” software 3.0.2,18 with scaling of relative concentrations by row.

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We enrolled 20 critically ill subjects and 10 healthy volunteers. Demographic and clinical characteristics are shown in Table 1 and summarized here. All 10 subjects on EN were trauma patients, with a median Injury Severity Score (ISS) of 29 (IQR, 27–34), and 90% (n = 9) were injured by a blunt mechanism. Among subjects on PN, 50% (n = 5) were admitted for trauma with a median ISS of 34 (IQR, 33–41), and 50% (n = 5) were admitted for a non–trauma-related operations. The majority of subjects in the EN group started nutrition due to tracheal intubation, while the majority of those in the PN group started nutrition due to ileus/enteral intolerance (Table 1). Subjects in the EN group started nutrition earlier in the hospital course (median hospital day, 2.5; IQR, 5–9) compared with subjects in the PN group (median hospital day, 7; IQR, 5–9).

We collected and analyzed 70 plasma samples using mass spectrometry. Of 214 total metabolites assayed, 102 were reliably identified and quantified. The measurement of the plasma metabolites had high technical reproducibility; the average coefficient of variance for relative concentrations was 6.3% and for isotope-labeled internal standards, the coefficient of variance was 3.4%.

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Metabolic Profile Changes After Initiation of Enteral or Parenteral Nutrition

PCA is a method used to recognize statistical patterns in data, and selects metabolites which best explain the overall variation in the data.12 In both EN and PN, PCA demonstrated that plasma metabolic profiles at day 0 (before nutrition) were different from days 3 and 7 (after nutrition) (Fig. 1A and B).

For subjects receiving enteral nutrition, the first principal component accounted for 28% of the total variance among days 0, 3, and 7 samples. Changes in N2-N2-dimethylguanosine, 1-methyladenosine, L-kyneurenine, N-acetylneuraminate, and deoxycarnitine contributed to the differences between timepoints.

The second principal component accounted for an additional 17% of the variance and included leucine, isoleucine, asparagine, methionine, and arginine. The metabolites from these two components are involved in nucleotide, amino acid, and sugar metabolism.

For subjects receiving parenteral nutrition, changes in 1-methylguanosine, N2-N2-dimethylguanosine, glucoronate, inositol, and cystamine constituted the first principal component, which accounted for 25% of the total variance between days 0, 3, and 7. The second principal component accounted for 22% of the variance and included proline, alanine, glycine, threonine, and pipecolate. The metabolites from these two components are all involved in amino acid, nucleotide, and lipid metabolism.

Metabolites which did not vary significantly among subjects over time included those involved with gut microflora metabolism and the pentose phosphate pathway.

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Enteral Nutrition Is Associated With Increased Amino Acids, Urea Cycle Products, Antioxidants and Ribonucleic Acid Products

Next, we determined metabolite pathways which differed over time among subjects who started EN. After false-discovery-rate correction, 9 of 102 identified metabolites showed statistically significant variation over the first week after starting enteral nutrition (Table 2). The initiation of enteral nutrition was associated with a gradual rise in plasma amino acids, urea cycle products and ribonucleic acid (RNA) synthetic products over the first week of nutrition (Fig. 2A and B).

Relative to day 0, samples from days 3 and 7 showed gradually increasing levels of both essential and nonessential amino acids (Fig. 3A) and urea cycle metabolites (Fig. 3B). Specifically, from day 0 to day 7, plasma concentrations for both citrulline and ornithine increased (p = 0.04 and 0.05, respectively).

We also observed increased metabolites related to RNA synthesis (Fig. 3C) and attenuation of oxidative stress (Fig. 3D). Specific changes in RNA synthetic plasma metabolites included increases in uridine, cysteine and oxypurinol (p = 0.04, 0.05 and 0.05, respectively). Specific changes in oxidation metabolites included increases in betaine and biotin, and a decrease in 4-pyridoxic acid (p = 0.05, 0.06, and 0.04, respectively).

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Parenteral Nutrition Is Associated With Increased Amino Acids, Decreased Urea Cycle Products and Decreased Essential Fatty Acids

We then determined metabolite pathways which differed over time among subjects who started PN. Overall, after false discovery rate correction, 5 of 102 identified metabolites showed statistically significant variation over the first week after exposure to PN (Table 2).

Generally, the initiation of PN was also associated with increased concentrations of plasma amino acids. However, subjects also showed decreased concentrations of urea cycle metabolites and essential fatty acids over time (Fig. 2C and D).

Relative to day 0, samples from days three and seven showed a gradual rise in both essential and non-essential amino acids (Fig. 4A), decreased urea cycle metabolites (Fig. 4B), and decreasing essential fatty acids (Fig. 4C). Specifically, from day 0 to day 7, subjects who started PN demonstrated rising plasma concentrations for taurine and phenylalanine (p = 0.04 and 0.05, respectively), decreasing levels of urate (p = 0.03), and decreasing omega-6 and omega-3 fatty acids (p = 0.05 and 0.03, respectively).

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In this study of critically ill surgical patients, we applied broad-based metabolomics in a novel way to determine the metabolic response to artificial nutritional support. The institution of EN was associated with a number of metabolic changes including amino-acid repletion, urea cycle upregulation, antioxidant restoration, and increased RNA synthesis, which, taken together, reflect anabolism. Subjects receiving parenteral nutrition had fewer changes in metabolic pathways. Although there was evidence of amino acid repletion, this could simply be measurement of the amino acids that were infused as part of the parenteral formula. The reductions in circulating fatty acids perhaps reflect intermittent administration of lipids; of note, omega-6 fatty acids are absent in parenteral lipids. These observations suggest that parenteral nutrients do not promote urea cycling, antioxidant metabolism, or RNA transcription to a similar degree that enteral nutritional support does. This supports the notion that parenteral nutrients are not used as effectively as enteral nutrients.2

Initiation of EN was associated with restoration of antioxidant equilibrium over time. This was seen as progressively increasing levels of vitamin and antioxidant substrates (betaine and biotin), and diminishing levels of antioxidant catabolites (4-pyridoxic acid). Biotin is known as vitamin B7 and is a cofactor in carboxylase-based reactions in protein lysis.19 Betaine is an antioxidant and methyl donor which is thought to protect against osmotic stress, modulate inflammation, and regulate lipid metabolism.20 Finally, 4-pyridoxic acid is a catabolite of vitamin B6 involved in nicotinamide metabolism.19 Restoration of these antioxidants with EN may be particularly relevant for trauma patients, who generally have ongoing depletion of antioxidant stores over the first week of injury.11

Of note, prior studies have found similar associations with EN and antioxidant repletion. For example, Windsor and colleagues21 studied 34 patients with acute pancreatitis who started on EN or PN, and found that the group on EN had lower markers of acute inflammation and an increased total antioxidant capacity. Other systemic reviews have also confirmed that EN appears to restore antioxidant balance more effectively than parenteral nutrition.22

Plasma amino acid concentrations and urea cycle products increased after starting enteral nutrition and approached levels measured in healthy volunteers. This suggests that EN is associated with restoration of circulating amino acids, coupled with processing of excess amino acids to their end-products in the urea cycle.19 This interpretation is consistent with prior literature showing that gut absorption of amino acids is tightly regulated to maintain a steady-state in the plasma, and any excess enteral amino acids are catabolized directly to urea cycle end-products in the liver.23,24 The increases in urea cycle products likely indicate that enteral amino acids are effectively used as a source for energy.

In contrast, subjects on PN showed plasma amino acid concentrations which were often higher than those in healthy volunteers, and urea cycle products that were not clearly increased. These data are consistent with the fact that PN is not subject to the same hepatic “first-pass” effect as EN,23 and therefore subjects on PN do not have tightly regulated plasma amino acid concentrations, or shunting of excess amino-acids directly to the urea cycle. Therefore, it appears that parenteral infusion can increase amino acid concentrations, but these amino acids are not efficiently metabolized. Our data are corroborated by a prior study of 49 trauma patients and 43 healthy volunteers, where PN initiation was associated with higher plasma levels of amino acids.25

As expected, subjects on PN showed downtrending levels of essential omega fatty acids, which are not supplemented in our PN formulas. In addition, PN subjects showed increasing levels of carnitine, which is an amino acid involved in fatty acid transport from plasma to both skeletal and smooth muscle.19,26 A gradual increase in carnitine can be expected in subjects who receive regular intravenous lipid infusions, where continuous transport of lipid out of the intravascular space must occur.

As previously described,10,11,27 the evaluation of metabolic response to nutrition therapy in critically ill patients is limited by time- and resource-intensive tools like calorimetry and nitrogen balance studies. With recent innovations in mass spectrometry–based metabolomics, the biomarkers reported in this study can now be obtained in approximately 3 hours.28 This makes bedside application of this tool a real possibility. In the near future, metabolomics could be used to identify nutritionally “high-risk” patients, to quantify metabolic response to therapy, and to help guide titration of calories, protein, and micronutrients based on individual patient profiles.

Several limitations are relevant to the interpretation of this study and are related to the current capabilities of mass spectrometry–based metabolomics. First, all metabolite changes in this study should be interpreted with caution. Metabolites are often involved in multiple pathways, and change in a metabolite's concentration could represent a change in utilization, or a change in production, or both. Therefore, individual metabolite changes should be interpreted in concert with other metabolites in the pathways of interest.29 Second, given the large quantity of data and multiple analyses in this study, there are more opportunities for random highly biased results (false positives). We have partly accounted for this fact using a false discovery rate correction in all our analyses, but our findings still need to be replicated in independent larger studies before any definitive conclusions are drawn. Third, observed effects may be due differences between the subjects in the two cohorts. For example, patients receiving parenteral nutrition were more likely to have an ileus, gastrointestinal tract dysfunction, and perhaps an altered microbiome; these may have influenced the metabolic response to nutrients, irrespective of the route of administration. However, we accounted for most other major confounding factors by excluding those subjects with cancer, chronic organ dysfunction, pregnancy, obesity, active infection, or a recent major operation. Fourth, it is possible that observed effects are due to differences in timing of nutrition initiation, which could lead to bias. However, we attempted to account for such individual variation by adjusting our analyses for clustering of serial observations within subjects,30 thereby accounting for potential bias due to individual factors like nutrition timing.

The metabolic response to enteral nutrition includes a cascade of events related to amino acid metabolism, urea cycling, RNA synthesis, and antioxidant repletion. Parenteral nutrition appears to increase plasma amino acid concentrations, without concomitant increase in their metabolism. Also, fatty acid concentrations dropped markedly. This suggests that parenteral nutrients are used less effectively than enteral nutrients. Biomarkers reported in this study may eventually become clinically useful in guiding nutrition therapy for critically ill patients.

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B.A.P., M.S., D.D., H.G., S.L.N., D.R., and G.E.O. designed this study. B.A.P., B.W., and G.E.O. conducted the literature search. All authors contributed to data collection. B.A.P., M.S., D.D., H.G., S.L.N., D.R., and G.E.O. performed data analysis and interpretation. B.A.P. and G.E.O. wrote the article, which all authors critically revised.

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This article was prepared with financial support from the National Institute of Health grant 2T32 GM007037 (GEO and BP). We wish to thank Lauren Jacobson, MS, Peter Louras, MS and Laura Hennessey, RN for their contributions to sample collection for this study.

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The authors declare no conflicts of interest.

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1. Singer P, Pichard C. Reconciling divergent results of the latest parenteral nutrition studies in the ICU. Curr Opin Clin Nutr Metab Care. 2013;16(2):187–193.
2. Huynh D, Chapman MJ, Nguyen NQ. Nutrition support in the critically ill. Curr Opin Gastroenterol. 2013;29(2):208–215.
3. Rice TW, Wheeler AP, Thompson BT, Steingrub J, Hite RD, Moss M, Morris A, Dong N, Rock P. Initial trophic vs full enteral feeding in patients with acute lung injury: the EDEN randomized trial. JAMA. 2012;307(8):795–803.
4. Singer P, Anbar R, Cohen J, Sharpio H, Shalita-Chesner M, Lev S, Grozovski E, Theilla M, Frishman S, Madar Z. The tight calorie control study (TICACOS): a prospective, randomized, controlled pilot study of nutritional support in critically ill patients. Intensive Care Med. 2011;37(4):601–609.
5. Andrews PJ, Avenell A, Noble DW, Campbell MK, Croal BL, Simpson WG, Vale LD, Battison CG, Jenkinson DJ, Cook JA. Randomised trial of glutamine, selenium, or both, to supplement parenteral nutrition for critically ill patients. BMJ. 2011;342:d1542.
6. Doig GS, Simpson F, Sweetman EA, Finfer SR, Cooper DJ, Heighes PT, Davies AR, O'Leary M, Solano T, Peake S. Early parenteral nutrition in critically ill patients with short-term relative contraindications to early enteral nutrition: a randomized controlled trial. JAMA. 2013;309(20):2130–2138.
7. Choi EY, Park DA, Park J. Calorie intake of enteral nutrition and clinical outcomes in acutely critically ill patients: a meta-analysis of randomized controlled trials. JPEN J Parenter Enteral Nutr. 2015;39:291–300.
8. Chung CK, Whitney R, Thompson CM, Pham TN, Maier RV, O'Keefe GE. Experience with an enteral-based nutritional support regimen in critically ill trauma patients. J Am Coll Surg. 2013;217(6):1108–1117.
9. Heidegger CP, Berger MM, Graf S, Zingg W, Darmon P, Constanza MC, Thibault R, Pichard C. Optimisation of energy provision with supplemental parenteral nutrition in critically ill patients: a randomised controlled clinical trial. Lancet. 2013;381(9864):385–393.
10. Ferrie S, Allman-Farinelli M. Commonly used “nutrition” indicators do not predict outcome in the critically ill: a systematic review. Nutr Clin Pract. 2013;28(4):463–484.
11. Parent BA, Seaton M, Sood RF, Gu H, Djukovic D, Raftery D, O'Keefe GE. Use of metabolomics to trend recovery and therapy after injury in critically ill trauma patients. JAMA Surg. 2016;151:e160853.
12. Gowda GA, Zhang S, Gu H, Asiago V, Shanaiah N, Raftery D. Metabolomics-based methods for early disease diagnostics. Expert Rev Mol Diagn. 2008;8(5):617–633.
13. Mao H, Wang H, Wang B, Liu X, Gao H, Xu M, Zhao H, Deng X, Lin D. Systemic metabolic changes of traumatic critically ill patients revealed by an NMR-based metabonomic approach. J Proteome Res. 2009;8(12):5423–5430.
14. Bueschl C, Krska R, Kluger B, Schuhmacher R. Isotopic labeling-assisted metabolomics using LC-MS. Anal Bioanal Chem. 2013;405(1):27–33.
15. Gu H, Du J, Carnevale NF, Carroll PA, Turner SJ, Chiorean EG, Eisenman RN, Raftery D. Metabolomics method to comprehensively analyze amino acids in different domains. Analyst. 2015;140(8):2726–2734.
16. Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J R Stat Soc B Met. 1995;57(1):289–300.
17. Team. RC. R: A language and environment for statistical computing. R Foundation for Statistical Computing. 2014; Vienna, Austria. URL
18. Harvard TBIoMa. GENE-E. URL: 2015;Version 3.0.204.
19. Wishart DS, Jewison T, Guo AC, Wilson M, Knox C, Liu Y, Djoumbou Y, Mandal R, Aziat F, Dong E, et al. HMDB 3.0—the human metabolome database in 2013. Nucleic Acids Res. 2013;41(Database issue):D801–D807.
20. Lever M, Slow S. The clinical significance of betaine, an osmolyte with a key role in methyl group metabolism. Clin Biochem. 2010;43(9):732–744.
21. Windsor AC, Kanwar S, Li AG, Barnes E, Guthrie JA, Spark JI, Welsh F, Guilou PJ, Reynolds JV. Compared with parenteral nutrition, enteral feeding attenuates the acute phase response and improves disease severity in acute pancreatitis. Gut. 1998;42(3):431–435.
22. Marik PE, Zaloga GP. Early enteral nutrition in acutely ill patients: a systematic review. Crit Care Med. 2001;29(12):2264–2270.
23. Abumrad NN, Miller B. The physiologic and nutritional significance of plasma-free amino acid levels. JPEN J Parenter Enteral Nutr. 1983;7(2):163–170.
24. Wu G. Intestinal mucosal amino acid catabolism. J Nutr. 1998;128(8):1249–1252.
25. Shaw JH, Wolfe RR. An integrated analysis of glucose, fat, and protein metabolism in severely traumatized patients. Studies in the basal state and the response to total parenteral nutrition. Ann Surg. 1989;209(1):63–72.
26. Wachter S, Vogt M, Kreis R, Boesch C, Bigler P, Hoppeler H, Krahenbuhl S. Long-term administration of L-carnitine to humans: effect on skeletal muscle carnitine content and physical performance. Clin Chim Acta. 2002;318(1–2):51–61.
27. Schlein KM, Coulter SP. Best practices for determining resting energy expenditure in critically ill adults. Nutr Clin Pract. 2014;29(1):44–55.
28. Rinehart D, Johnson CH, Nguyen T, Ivanisevic J, Benton HP, Lloyd J, Arkin AP, Deutschbauer AM, Patti GJ, Siuzdak G. Metabolomic data streaming for biology-dependent data acquisition. Nat Biotechnol. 2014;32(6):524–527.
29. Alonso A, Marsal S, Julià A. Analytical methods in untargeted metabolomics: state of the art in 2015. Front Bioeng Biotechnol. 2015;3:23.
30. Williams RL. A note on robust variance estimation for cluster-correlated data. Biometrics. 2000;56(2):645–646.
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Dr. Panna A. Codner (Milwaukee, Wisconsin): The manuscript is extremely well-written and actually a fascinating read with just a huge amount of data. And I’m sure the authors had a hard time to compress it into such a short presentation.

Indeed, there are innumerable questions that can come from this preliminary study and it really fits very well within the precision medicine model that is of interest to so many people.

The gist of the manuscript, although not necessarily the gist of the presentation, really was around the molecular evidence that the body metabolizes nutrients given parenterally very different than it does with nutrients given enterally.

This is something we have known intrinsically but maybe this is the beginning of figuring out why, how, and if it can be modified.

I really tried to keep my questions simple as points of clarification because the authors, I’m sure, are working on many of the potential follow-up questions for the future. But I really have five questions.

First, most of your exclusion criteria which, in the manuscript, include a history of cancer, endocrine disorders, pregnancy, chronic organ dysfunction, obesity and active infection, make sense in this preliminary type of study.

You also included only immediate postoperative patients, but according to the manuscript only abdominal orthopedic ones. Is there something intrinsically in these groups that would make them different from, say, a thoracic or a neurosurgical procedure?

Second, your study had three groups: healthy volunteers—all, presumably, on enteral nutrition—critically-ill patients on enteral nutrition, and those on parenteral nutrition.

You constructed two models: one for those on enteral and one for those on parenteral and really focused on each group’s before and after comparisons rather than comparing between groups.

It’s unclear from the manuscript where the healthy controls fit in here. Were they included in the enteral nutrition group? And would that skew the results?

Third, there was a difference in time between the insult and initiation of nutrition and, presumably, study enrollment in the two groups. Do you think that played a role in the differences between the subjects’ response to initiation of nutrition? That difference, I believe, was close to a week.

Fourth, along those same lines, all ten of the enteral patients were victims of trauma; whereas, only half were trauma victims in the parenteral group. Why add in the potential confounder of a more varied study group?

Finally, ileus, itself, I think, is an organ dysfunction. The parenteral group consisted almost exclusively of patients with intolerance of enteral feeds. Do you think that some of the lack of anabolic response seen with the parenteral nutrition was not necessarily the fault of the route but related to something within the GI tract which wasn’t happening in patients with GI tract dysfunction?

Again, I think this is a phenomenal piece of work and the manuscript clearly reflects the authors’ enthusiasm and expertise on the subject. This type of individual metabolic information may be invaluable to future clinicians in mitigating some of the catabolic consequences and I look forward to the authors’ continued work.

Thank you.

Dr. Carrie Sims (Philadelphia, Pennsylvania): A quick question, actually two. Was there any crossover in your design? Where all the patients who were initially in the enteral group kept on enteral nutrition for seven days or did some people in the parenteral group crossover to enteral?

And when I looked at your data for Day 0, those numbers actually looked different, whether you were assigned to the parenteral or enteral of nutrition group so maybe those people are inherently different, aside from the fact they were given different sources of nutrition.

The second thing is did you look at fatty acid metabolism? There is some interest in whether or not when you switch from glucose metabolism to predominantly fatty acid metabolism it’s a marker for a change in acute inflammation to chronic inflammation so I would be interested in knowing if you found any differences. Thank you so much.

Dr. Grant E. O’Keefe (Seattle, Washington): Thank you. I did have a lot of trouble getting everything down into this talk, as you could probably tell.

We enrolled non-trauma patients primarily out of necessity. We could have waited longer but I think that in the interest of getting the study done we wanted to get some more patients who were treated with parenteral nutrition.

In regard to the question of the healthy controls, they weren’t part of the two artificial nutrition groups and I hope we’ve clarified that now. They were just used as a reference for the metabolomic measurements.

And you are correct. The time of starting either enteral or parenteral nutrition probably addresses some of the other questions as well but these are quite different patients.

I think that it’s probably not fair to compare the patients in the enteral nutrition group directly to the patients in the parenteral nutrition group. There are probably many factors that are related to when we started their nutritional support that determine their metabolomic status.

On average, enteral nutrition started on about Day 3 whereas the median start day was Day 8 for the parenteral group.

I think an ileus is probably one of the most underappreciated components of organ failure and perhaps that is, at least in part, related to some of the differences in the metabolic responses is that the parenteral nutrition patients see and not just their inability or differences in handling the nutrients.

You asked whether any patients crossed over from one group to the other. No, none of the patients crossed over. They were all independent. That was deliberate.

The fatty acid metabolism is fascinating. There are so much data here I had to cut some of it out but I think the notion that there is more fatty acid metabolism later on in a critically-ill patient’s course was borne out in our data.

What we see is that some of the fatty acids are much lower in the parenteral nutrition patients. And that’s probably not simply due to the mode of nutritional support. We observed not just the omega-3s and the omega-6s, but all the fatty acids are lower in the parenteral nutrition patients.

Thank you.


Enteral nutrition; parenteral nutrition; metabolomics; metabolism; critical-illness

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