# Different Associations of Plasma Lipopolysaccharide and Lipopolysaccharide-Binding Protein Concentrations with the Deterioration of Energy Metabolism from Healthy Individuals to Patients with Non-Alcoholic Fatty Liver Disease

**Authors:** Nobuo Fuke, Yosui Tamaki, Kazunobu Aso, Yu Ota, Shin Otake, Shigenori Suzuki

PMC · DOI: 10.3390/metabo16020144 · Metabolites · 2026-02-20

## TL;DR

This study shows that plasma LPS is linked to triglycerides in healthy people but not in those with non-alcoholic fatty liver disease (NAFLD), suggesting LPS may affect metabolism before NAFLD develops.

## Contribution

The study reveals stage-specific associations of LPS and LBP with energy metabolism in healthy individuals versus NAFLD patients.

## Key findings

- Plasma LPS and LBP concentrations were significantly higher in NAFLD patients compared to healthy individuals.
- Plasma LPS correlated with triglycerides in healthy individuals but not in NAFLD patients.
- Plasma LBP was inversely associated with hepatic fat fraction in NAFLD patients, though this was weakened after adjusting for liver enzymes.

## Abstract

Background: Energy metabolism progressively deteriorates from a healthy state to non-alcoholic fatty liver disease (NAFLD), and circulating lipopolysaccharide (LPS) may contribute to this process. However, previous studies have analyzed healthy individuals and NAFLD patients together, leaving stage-specific associations unclear. Whether LPS and its surrogate marker, lipopolysaccharide-binding protein (LBP), show similar relationships during NAFLD development also remains unknown. This study evaluated the associations between plasma LPS and LBP concentrations with clinical parameters in healthy individuals and NAFLD patients. Methods: We conducted a cross-sectional study of 31 healthy individuals (median age [IQR]: 31 (26–43) years) and 31 NAFLD patients (59 (54–70) years). Plasma LPS and LBP concentrations and clinical parameters were measured. Correlations were assessed using Spearman’s rank analysis, followed by multivariate regression adjusting for age, sex, and BMI. Results: Plasma LPS and LBP concentrations were significantly higher in NAFLD patients compared to healthy individuals. Additionally, in the univariate regression analysis for all study participants, plasma LPS concentrations were correlated with obesity, blood pressure, liver function, lipid metabolism, and glucose metabolism. Plasma LBP concentrations were also correlated with age, obesity, blood pressure, liver function, lipid metabolism, glucose metabolism, and inflammatory cytokines. In healthy individuals, LPS correlated positively with triglycerides (TG), remaining significant after adjustment and exclusion of participants with any clinical test values outside the normal range. This association was not observed in NAFLD patients. Plasma LBP did not correlate with TG in either group; however, it was inversely associated with hepatic fat fraction in NAFLD patients, although this association was attenuated after adjusting for alanine aminotransferase. Conclusions: Plasma LPS correlates with TG even in clinically healthy individuals, suggesting LPS may influence lipid metabolism before NAFLD onset.

## Linked entities

- **Proteins:** IRF6 (interferon regulatory factor 6), LBP (lipopolysaccharide binding protein)
- **Diseases:** non-alcoholic fatty liver disease (MONDO:0013209), NAFLD (MONDO:0013209)

## Full-text entities

- **Genes:** ACE (angiotensin I converting enzyme) [NCBI Gene 1636] {aka ACE1, CD143, DCP, DCP1}, GPT (glutamic--pyruvic transaminase) [NCBI Gene 2875] {aka AAT1, ALT, ALT1, GPT1, SGPT}, ACE2 (angiotensin converting enzyme 2) [NCBI Gene 59272] {aka ACEH}, LBP (lipopolysaccharide binding protein) [NCBI Gene 3929] {aka BPIFD2}, MUC2 (mucin 2, oligomeric mucus/gel-forming) [NCBI Gene 4583] {aka MLP, MUC-2, SMUC}, TLR4 (toll like receptor 4) [NCBI Gene 7099] {aka ARMD10, CD284, TLR-4, TOLL}, IL22 (interleukin 22) [NCBI Gene 50616] {aka IL-21, IL-22, IL-D110, IL-TIF, ILTIF, TIFIL-23}, DBP (D-box binding PAR bZIP transcription factor) [NCBI Gene 1628] {aka DABP, taxREB302}, TNF (tumor necrosis factor) [NCBI Gene 7124] {aka DIF, IMD127, TNF-alpha, TNFA, TNFSF2, TNLG1F}, INS (insulin) [NCBI Gene 3630] {aka IDDM, IDDM1, IDDM2, ILPR, IRDN, MODY10}, KRT18 (keratin 18) [NCBI Gene 3875] {aka CK-18, CYK18, K18}, GCG (glucagon) [NCBI Gene 2641] {aka GLP-1, GLP1, GLP2, GRPP}, GLP1R (glucagon like peptide 1 receptor) [NCBI Gene 2740] {aka GLP-1, GLP-1-R, GLP-1R}, UCP1 (uncoupling protein 1) [NCBI Gene 7350] {aka SLC25A7, UCP}, AP2B1 (adaptor related protein complex 2 subunit beta 1) [NCBI Gene 163] {aka ADTB2, AP105B, AP2-BETA, CLAPB1}, MYD88 (MYD88 innate immune signal transduction adaptor) [NCBI Gene 4615] {aka IMD68, MYD88D, WM1}, GGT1 (gamma-glutamyltransferase 1) [NCBI Gene 2678] {aka CD224, D22S672, D22S732, GGT, GGT 1, GGTD}, LIPA (lipase A, lysosomal acid type) [NCBI Gene 3988] {aka CESD, LAL}, IL6 (interleukin 6) [NCBI Gene 3569] {aka BSF-2, BSF2, CDF, HGF, HSF, IFN-beta-2}, CRP (C-reactive protein) [NCBI Gene 1401] {aka PTX1}, PYY (peptide YY) [NCBI Gene 5697] {aka PYY-I, PYY1}, SLC5A2 (solute carrier family 5 member 2) [NCBI Gene 6524] {aka SGLT2}, SLC17A5 (solute carrier family 17 member 5) [NCBI Gene 26503] {aka AST, ISSD, NSD, SD, SIALIN, SIASD}, AGT (angiotensinogen) [NCBI Gene 183] {aka ANHU, SERPINA8, hFLT1}, COG2 (component of oligomeric golgi complex 2) [NCBI Gene 22796] {aka CDG2Q, LDLC}, TGFB1 (transforming growth factor beta 1) [NCBI Gene 7040] {aka CAEND1, CED, DPD1, IBDIMDE, LAP, TGF-beta1}, DPP4 (dipeptidyl peptidase 4) [NCBI Gene 1803] {aka ADABP, ADCP2, CD26, DPPIV, TP103}, LGALS3BP (galectin 3 binding protein) [NCBI Gene 3959] {aka 90K, BTBD17B, CyCAP, M2BP, MAC-2-BP, TANGO10B}
- **Diseases:** weight gain (MESH:D015430), Hepatic steatosis (MESH:D005234), Obesity (MESH:D009765), NASH (MESH:D005235), metabolic abnormalities (MESH:D008659), Wilson's disease (MESH:D006527), hepatocyte damage (MESH:D020263), TG (MESH:C566031), Hemochromatosis (MESH:D006432), headache (MESH:D006261), MASLD (MESH:D008107), inflammation (MESH:D007249), hepatocyte injury (MESH:D014947), hyperglycemia (MESH:D006943), metabolic syndrome (MESH:D024821), iron overload (MESH:D019190), Fibrosis (MESH:D005355), dyslipidemia (MESH:D050171), mitochondrial dysfunction (MESH:D028361), NAFLD (MESH:D065626), Diabetes (MESH:D003920), endothelial dysfunction (MESH:D014652), Liver fibrosis (MESH:D008103), abnormalities in glucose metabolism (MESH:D044882), overnutrition (MESH:D044343), Hepatitis B or C (MESH:D006509), type 2 diabetes (MESH:D003924), carbohydrate (MESH:C562602), Drug-induced liver injury (MESH:D056486), hepatocellular carcinoma (MESH:D006528), Primary biliary cirrhosis (MESH:D008105), deterioration of (MESH:D000075902), Autoimmune hepatitis (MESH:D019693), cognitive impairment (MESH:D003072), endotoxemia (MESH:D019446), hypertension (MESH:D006973), Citrin deficiency (MESH:C538053), infection (MESH:D007239), colitis (MESH:D003092), chills (MESH:D023341), gastrointestinal diseases (MESH:D005767), weight loss (MESH:D015431), hepatic insulin resistance (MESH:D007333)
- **Chemicals:** water (MESH:D014867), eicosapentaenoic acid (MESH:D015118), metformin (MESH:D008687), free fatty acids (MESH:D005230), sulfonylurea (MESH:D013453), cholesterol (MESH:D002784), Ethanol (MESH:D000431), hyaluronic acid (MESH:D006820), blood glucose (MESH:D001786), ezetimibe (MESH:D000069438), polysaccharides (MESH:D011134), TG (MESH:D014280), ATP (MESH:D000255), fructose (MESH:D005632), UDCA (MESH:D014580), lipid (MESH:D008055), fibrate (MESH:D058607), LPS (MESH:D008070), alpha-tocopherol (MESH:D024502), heparin (MESH:D006493), alcohol (MESH:D000438), glucose (MESH:D005947), calcium (MESH:D002118), M2BPGi (-), proton (MESH:D011522), NA (MESH:D012964), glycerol (MESH:D005990), TCA (MESH:D014238), carbohydrate (MESH:D002241), fatty acid (MESH:D005227)
- **Species:** Mus musculus (house mouse, species) [taxon 10090], Homo sapiens (human, species) [taxon 9606]
- **Cell lines:** L- — Mus musculus (Mouse), Spontaneously immortalized cell line (CVCL_0462)

## Full text

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## Figures

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## References

68 references — full list in the complete paper: https://tomesphere.com/paper/PMC12942947/full.md

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Source: https://tomesphere.com/paper/PMC12942947