DHCR7 Expression Predicts Poor Outcomes and Mortality From Sepsis

Faheem W Guirgis; Vinitha Jacob; Dongyuan Wu; Morgan Henson; Kimberly Daly-Crews; Charlotte Hopson; Lauren Page Black; Elizabeth L DeVos; Dawoud Sulaiman; Guillaume Labilloy; Todd M Brusko; Jordan A Shavit; Andrew Bertrand; Matthew Feldhammer; Brett Baskovich; Kiley Graim; Susmita Datta; Srinivasa T Reddy

doi:10.1097/CCE.0000000000000929

DHCR7 Expression Predicts Poor Outcomes and Mortality From Sepsis

Crit Care Explor. 2023 Jun 14;5(6):e0929. doi: 10.1097/CCE.0000000000000929. eCollection 2023 Jun.

Authors

Faheem W Guirgis¹, Vinitha Jacob², Dongyuan Wu³, Morgan Henson¹, Kimberly Daly-Crews¹, Charlotte Hopson¹, Lauren Page Black¹, Elizabeth L DeVos¹, Dawoud Sulaiman⁴, Guillaume Labilloy⁵, Todd M Brusko^{6

7}, Jordan A Shavit^{8

9}, Andrew Bertrand¹, Matthew Feldhammer¹⁰, Brett Baskovich¹¹, Kiley Graim¹², Susmita Datta³, Srinivasa T Reddy⁴

Affiliations

¹ Department of Emergency Medicine, University of Florida College of Medicine, Jacksonville, FL.
² Department of Emergency Medicine, University of Michigan College of Medicine, Ann Arbor, MI.
³ Department of Biostatistics, University of Florida, Gainesville, FL.
⁴ Division of Cardiology, Department of Medicine, David Geffen School of Medicine, UCLA, Los Angeles, CA.
⁵ UF Health Jacksonville Center for Data Solutions, Jacksonville, FL.
⁶ Department of Pathology, Immunology, and Laboratory Medicine, University of Florida Diabetes Institute, College of Medicine, Gainesville, FL.
⁷ Department of Pediatrics, University of Florida Diabetes Institute, College of Medicine, Gainesville, FL.
⁸ Department of Pediatrics, University of Michigan School of Medicine, Ann Arbor, MI.
⁹ Department of Human Genetics, University of Michigan School of Medicine, Ann Arbor, MI.
¹⁰ Department of Pathology, University of Florida College of Medicine, Jacksonville, FL.
¹¹ Department of Pathology, Mt. Sinai School of Medicine, New York, NY.
¹² Computer and Information Science Engineering, University of Florida, Gainesville, FL.

Abstract

This is a study of lipid metabolic gene expression patterns to discover precision medicine for sepsis.

Objectives: Sepsis patients experience poor outcomes including chronic critical illness (CCI) or early death (within 14 d). We investigated lipid metabolic gene expression differences by outcome to discover therapeutic targets.

Design setting and particitpants: Secondary analysis of samples from prospectively enrolled sepsis patients (first 24 hr) and a zebrafish endotoxemia model for drug discovery. Patients were enrolled from the emergency department or ICU at an urban teaching hospital. Enrollment samples from sepsis patients were analyzed. Clinical data and cholesterol levels were recorded. Leukocytes were processed for RNA sequencing and reverse transcriptase polymerase chain reaction. A lipopolysaccharide zebrafish endotoxemia model was used for confirmation of human transcriptomic findings and drug discovery.

Main outcomes and measures: The derivation cohort included 96 patients and controls (12 early death, 13 CCI, 51 rapid recovery, and 20 controls) and the validation cohort had 52 patients (6 early death, 8 CCI, and 38 rapid recovery).

Results: The cholesterol metabolism gene 7-dehydrocholesterol reductase (DHCR7) was significantly up-regulated in both derivation and validation cohorts in poor outcome sepsis compared with rapid recovery patients and in 90-day nonsurvivors (validation only) and validated using RT-qPCR analysis. Our zebrafish sepsis model showed up-regulation of dhcr7 and several of the same lipid genes up-regulated in poor outcome human sepsis (dhcr24, sqlea, cyp51, msmo1, and ldlra) compared with controls. We then tested six lipid-based drugs in the zebrafish endotoxemia model. Of these, only the Dhcr7 inhibitor AY9944 completely rescued zebrafish from lipopolysaccharide death in a model with 100% lethality.

Conclusions: DHCR7, an important cholesterol metabolism gene, was up-regulated in poor outcome sepsis patients warranting external validation. This pathway may serve as a potential therapeutic target to improve sepsis outcomes.

Keywords: genetics; lipids; sepsis; transcriptomics; zebrafish.

Abstract

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