Top

European Journal of Medical Research

Published in:

Open Access 01-12-2023 | Septicemia | Research

A hypoxia- and lactate metabolism-related gene signature to predict prognosis of sepsis: discovery and validation in independent cohorts

Authors: Yaojun Peng, Qiyan Wu, Xinhuan Ding, Lingxiong Wang, Hanpu Gong, Cong Feng, Tianyi Liu, Haiyan Zhu

Published in: European Journal of Medical Research | Issue 1/2023

Abstract

Background

High throughput gene expression profiling is a valuable tool in providing insight into the molecular mechanism of human diseases. Hypoxia- and lactate metabolism-related genes (HLMRGs) are fundamentally dysregulated in sepsis and have great predictive potential. Therefore, we attempted to build an HLMRG signature to predict the prognosis of patients with sepsis.

Methods

Three publicly available transcriptomic profiles of peripheral blood mononuclear cells from patients with sepsis (GSE65682, E-MTAB-4421 and E-MTAB-4451, total n = 850) were included in this study. An HLMRG signature was created by employing Cox regression and least absolute shrinkage and selection operator estimation. The CIBERSORT method was used to analyze the abundances of 22 immune cell subtypes based on transcriptomic data. Metascape was used to investigate pathways related to the HLMRG signature.

Results

We developed a prognostic signature based on five HLMRGs (ERO1L, SIAH2, TGFA, TGFBI, and THBS1). This classifier successfully discriminated patients with disparate 28-day mortality in the discovery cohort (GSE65682, n = 479), and consistent results were observed in the validation cohort (E-MTAB-4421 plus E-MTAB-4451, n = 371). Estimation of immune infiltration revealed significant associations between the risk score and a subset of immune cells. Enrichment analysis revealed that pathways related to antimicrobial immune responses, leukocyte activation, and cell adhesion and migration were significantly associated with the HLMRG signature.

Conclusions

Identification of a prognostic signature suggests the critical role of hypoxia and lactate metabolism in the pathophysiology of sepsis. The HLMRG signature can be used as an efficient tool for the risk stratification of patients with sepsis.

Available only for authorised users

Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, Bellomo R, Bernard GR, Chiche JD, Coopersmith CM, et al. The third international consensus definitions for sepsis and septic shock (Sepsis-3). JAMA. 2016;315(8):801–10.CrossRefPubMedPubMedCentral

Hotchkiss RS, Moldawer LL, Opal SM, Reinhart K, Turnbull IR, Vincent JL. Sepsis and septic shock. Nat Rev Dis Primers. 2016;2:16045.PubMedPubMedCentral

Preau S, Vodovar D, Jung B, Lancel S, Zafrani L, Flatres A, Oualha M, Voiriot G, Jouan Y, Joffre J, et al. Energetic dysfunction in sepsis: a narrative review. Ann Intensive Care. 2021;11(1):104.PubMedPubMedCentral

Brooks GA. Cell-cell and intracellular lactate shuttles. J Physiol. 2009;587(Pt 23):5591–600.PubMedPubMedCentral

Nguyen HB, Rivers EP, Knoblich BP, Jacobsen G, Muzzin A, Ressler JA, Tomlanovich MC. Early lactate clearance is associated with improved outcome in severe sepsis and septic shock. Crit Care Med. 2004;32(8):1637–42.PubMed

Rishu AH, Khan R, Al-Dorzi HM, Tamim HM, Al-Qahtani S, Al-Ghamdi G, Arabi YM. Even mild hyperlactatemia is associated with increased mortality in critically ill patients. Crit Care (London, England). 2013;17(5):R197.

Nolt B, Tu F, Wang X, Ha T, Winter R, Williams DL, Li C. Lactate and immunosuppression in sepsis. Shock (Augusta, Ga). 2018;49(2):120–5.PubMed

Bakker J, Postelnicu R, Mukherjee V. Lactate: where are we now? Crit Care Clin. 2020;36(1):115–24.PubMed

Wardi G, Brice J, Correia M, Liu D, Self M, Tainter C. Demystifying lactate in the emergency department. Ann Emerg Med. 2020;75(2):287–98.PubMed

10.

Marik PE, Bellomo R. Stress hyperglycemia: an essential survival response. Crit Care (London, England). 2013;17(2):305.

11.

Gibot S. On the origins of lactate during sepsis. Crit Care (London, England). 2012;16(5):151.

12.

Gore DC, Jahoor F, Hibbert JM, DeMaria EJ. Lactic acidosis during sepsis is related to increased pyruvate production, not deficits in tissue oxygen availability. Ann Surg. 1996;224(1):97–102.PubMedPubMedCentral

13.

Adrie C, Bachelet M, Vayssier-Taussat M, Russo-Marie F, Bouchaert I, Adib-Conquy M, Cavaillon JM, Pinsky MR, Dhainaut JF, Polla BS. Mitochondrial membrane potential and apoptosis peripheral blood monocytes in severe human sepsis. Am J Respir Crit Care Med. 2001;164(3):389–95.PubMed

14.

Skibsted S, Bhasin MK, Aird WC, Shapiro NI. Bench-to-bedside review: future novel diagnostics for sepsis - a systems biology approach. Crit care (London, England). 2013;17(5):231.

15.

van Engelen TSR, Wiersinga WJ, Scicluna BP, van der Poll T. Biomarkers in sepsis. Crit Care Clin. 2018;34(1):139–52.PubMed

16.

Liu AC, Patel K, Vunikili RD, Johnson KW, Abdu F, Belman SK, Glicksberg BS, Tandale P, Fontanez R, Mathew OK, et al. Sepsis in the era of data-driven medicine: personalizing risks, diagnoses, treatments and prognoses. Brief Bioinform. 2020;21(4):1182–95.PubMed

17.

Stanski NL, Wong HR. Prognostic and predictive enrichment in sepsis. Nat Rev Nephrol. 2020;16(1):20–31.PubMed

18.

Sweeney TE, Perumal TM, Henao R, Nichols M, Howrylak JA, Choi AM, Bermejo-Martin JF, Almansa R, Tamayo E, Davenport EE, et al. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun. 2018;9(1):694.PubMedPubMedCentral

19.

Galtung N, Diehl-Wiesenecker E, Lehmann D, Markmann N, Bergström WH, Wacker J, Liesenfeld O, Mayhew M, Buturovic L, Luethy R, et al. Prospective validation of a transcriptomic severity classifier among patients with suspected acute infection and sepsis in the emergency department. Eur J Emerg Med. 2022;29(5):357–65.PubMedPubMedCentral

20.

Ferreira BL, Leite GGF, Brunialti MKC, Assuncao M, Azevedo LCP, Freitas F, Salomao R. HIF-1α and hypoxia responsive genes are differentially expressed in leukocytes from survivors and non-survivors patients during clinical sepsis. Shock (Augusta, Ga). 2021;56(1):80–91.PubMed

21.

Cheng SC, Quintin J, Cramer RA, Shepardson KM, Saeed S, Kumar V, Giamarellos-Bourboulis EJ, Martens JH, Rao NA, Aghajanirefah A, et al. mTOR- and HIF-1α-mediated aerobic glycolysis as metabolic basis for trained immunity. Science (New York, NY). 2014;345(6204):1250684.

22.

Scicluna BP, van Vught LA, Zwinderman AH, Wiewel MA, Davenport EE, Burnham KL, Nürnberg P, Schultz MJ, Horn J, Cremer OL, et al. Classification of patients with sepsis according to blood genomic endotype: a prospective cohort study. Lancet Respir Med. 2017;5(10):816–26.PubMed

23.

Davenport EE, Burnham KL, Radhakrishnan J, Humburg P, Hutton P, Mills TC, Rautanen A, Gordon AC, Garrard C, Hill AV, et al. Genomic landscape of the individual host response and outcomes in sepsis: a prospective cohort study. Lancet Respir Med. 2016;4(4):259–71.PubMedPubMedCentral

24.

Johnson WE, Li C, Rabinovic A. Adjusting batch effects in microarray expression data using empirical Bayes methods. Biostatistics (Oxford, England). 2007;8(1):118–27.PubMed

25.

Li J, Qiao H, Wu F, Sun S, Feng C, Li C, Yan W, Lv W, Wu H, Liu M, et al. A novel hypoxia- and lactate metabolism-related signature to predict prognosis and immunotherapy responses for breast cancer by integrating machine learning and bioinformatic analyses. Front Immunol. 2022;13:998140.PubMedPubMedCentral

26.

Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015;1(6):417–25.PubMedPubMedCentral

27.

Peng Y, Wu Q, Liu H, Zhang J, Han Q, Yin F, Wang L, Chen Q, Zhang F, Feng C, et al. An immune-related gene signature predicts the 28-day mortality in patients with sepsis. Front Immunol. 2023;14:1152117.PubMedPubMedCentral

28.

Peng Y, Zhao J, Yin F, Sharen G, Wu Q, Chen Q, Sun X, Yang J, Wang H, Zhang D. A methylation-driven gene panel predicts survival in patients with colon cancer. FEBS Open Bio. 2021;11(9):2490–506.PubMedPubMedCentral

29.

Engebretsen S, Bohlin J. Statistical predictions with glmnet. Clin Epigenet. 2019;11(1):123.

30.

Goeman JJ. L1 penalized estimation in the Cox proportional hazards model. Biometr J Biometrische Zeitschrift. 2010;52(1):70–84.

31.

Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh AA. Robust enumeration of cell subsets from tissue expression profiles. Nat Methods. 2015;12(5):453–7.PubMedPubMedCentral

32.

Zeng D, Ye Z, Shen R, Yu G, Wu J, Xiong Y, Zhou R, Qiu W, Huang N, Sun L, et al. IOBR: multi-omics immuno-oncology biological research to decode tumor microenvironment and signatures. Front Immunol. 2021;12:687975.PubMedPubMedCentral

33.

Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, Benner C, Chanda SK. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun. 2019;10(1):1523.PubMedPubMedCentral

34.

Ye L, Jiang Y, Zhang M. Crosstalk between glucose metabolism, lactate production and immune response modulation. Cytokine Growth Factor Rev. 2022;68:81–92.PubMed

35.

Liang S, Xing M, Chen X, Peng J, Song Z, Zou W. Predicting the prognosis in patients with sepsis by a pyroptosis-related gene signature. Front Immunol. 2022;13:1110602.PubMedPubMedCentral

36.

Zhu S, Huang Y, Ye C. Identification of a ferroptosis-related prognostic signature in sepsis via bioinformatics analyses and experiment validation. Biomed Res Int. 2022;2022:8178782.PubMedPubMedCentral

37.

Jiang S, Zhang W, Lu Y. Development and validation of novel inflammatory response-related gene signature for sepsis prognosis. J Zhejiang Univ Sci B. 2022;23(12):1028–41.PubMedPubMedCentral

38.

Luo Y, Li L, Chen X, Gou H, Yan K, Xu Y. Effects of lactate in immunosuppression and inflammation: progress and prospects. Int Rev Immunol. 2022;41(1):19–29.PubMed

39.

Dietl K, Renner K, Dettmer K, Timischl B, Eberhart K, Dorn C, Hellerbrand C, Kastenberger M, Kunz-Schughart LA, Oefner PJ, et al. Lactic acid and acidification inhibit TNF secretion and glycolysis of human monocytes. J Immunol (Baltimore, Md: 1950). 2010;184(3):1200–9.

40.

Peter K, Rehli M, Singer K, Renner-Sattler K, Kreutz M. Lactic acid delays the inflammatory response of human monocytes. Biochem Biophys Res Commun. 2015;457(3):412–8.PubMed

41.

Errea A, Cayet D, Marchetti P, Tang C, Kluza J, Offermanns S, Sirard JC, Rumbo M. Lactate inhibits the pro-inflammatory response and metabolic reprogramming in murine macrophages in a GPR81-Independent manner. PLoS ONE. 2016;11(11):e0163694.PubMedPubMedCentral

42.

Goetze K, Walenta S, Ksiazkiewicz M, Kunz-Schughart LA, Mueller-Klieser W. Lactate enhances motility of tumor cells and inhibits monocyte migration and cytokine release. Int J Oncol. 2011;39(2):453–63.PubMed

43.

Hoque R, Farooq A, Ghani A, Gorelick F, Mehal WZ. Lactate reduces liver and pancreatic injury in Toll-like receptor- and inflammasome-mediated inflammation via GPR81-mediated suppression of innate immunity. Gastroenterology. 2014;146(7):1763–74.PubMed

44.

Ratter JM, Rooijackers HMM, Hooiveld GJ, Hijmans AGM, de Galan BE, Tack CJ, Stienstra R. In vitro and in vivo effects of lactate on metabolism and cytokine production of human primary PBMCs and monocytes. Front Immunol. 2018;9:2564.PubMedPubMedCentral

Title: A hypoxia- and lactate metabolism-related gene signature to predict prognosis of sepsis: discovery and validation in independent cohorts
Authors: Yaojun Peng
Qiyan Wu
Xinhuan Ding
Lingxiong Wang
Hanpu Gong
Cong Feng
Tianyi Liu
Haiyan Zhu
Publication date: 01-12-2023
Publisher: BioMed Central
Keywords: Septicemia
Septicemia
Published in: European Journal of Medical Research / Issue 1/2023
Electronic ISSN: 2047-783X
DOI: https://doi.org/10.1186/s40001-023-01307-z

Keynote webinar | Spotlight on medication adherence

Springer Medicine

A hypoxia- and lactate metabolism-related gene signature to predict prognosis of sepsis: discovery and validation in independent cohorts

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2023

Identification of HOXB9 to predict prognosis of endometrial cancer based on comprehensive bioinformatics analysis

The influence of vitamin D on handgrip strength in elderly trauma patients

Activating transcription factor (ATF) 6 upregulates cystathionine β synthetase (CBS) expression and hydrogen sulfide (H2S) synthesis to ameliorate liver metabolic damage

Pan-cancer analysis from multi-omics data reveals AAMP as an unfavourable prognostic marker

Investigating and comparing the dimensions of worry of Iranian primiparous women in each trimester of pregnancy

Metastasis of breast cancer to bones alters the tumor immune microenvironment