EPA and DHA inhibit LDL-induced upregulation of human adipose tissue NLRP3 inflammasome/IL-1β pathway and its association with diabetes risk factors

Abstract

Elevated numbers of atherogenic lipoproteins (apoB) predict the incidence of type 2 diabetes (T2D). We reported that this may be mediated via the activation of the NLRP3 inflammasome, as low-density lipoproteins (LDL) induce interleukin-1 beta (IL-1β) secretion from human white adipose tissue (WAT) and macrophages. However, mitigating nutritional approaches remained unknown. We tested whether omega-3 eicosapentaenoic and docosahexaenoic acids (EPA and DHA) treat LDL-induced upregulation of WAT IL-1β-secretion and its relation to T2D risk factors. Twelve-week intervention with EPA and DHA (2.7 g/day, Webber Naturals) abolished baseline group-differences in WAT IL-1β-secretion between subjects with high-apoB (N = 17) and low-apoB (N = 16) separated around median plasma apoB. Post-intervention LDL failed to trigger IL-1β-secretion and inhibited it in lipopolysaccharide-stimulated WAT. Omega-3 supplementation also improved β-cell function and postprandial fat metabolism in association with higher blood EPA and mostly DHA. It also blunted the association of WAT NLRP3 and IL1B expression and IL-1β-secretion with multiple cardiometabolic risk factors including adiposity. Ex vivo, EPA and DHA inhibited WAT IL-1β-secretion in a dose-dependent manner. In conclusion, EPA and DHA treat LDL-induced upregulation of WAT NLRP3 inflammasome/IL-1β pathway and related T2D risk factors. This may aid in the prevention of T2D and related morbidities in subjects with high-apoB.Clinical Trail Registration ClinicalTrials.gov (NCT04496154): Omega-3 to Reduce Diabetes Risk in Subjects with High Number of Particles That Carry "Bad Cholesterol" in the Blood - Full Text View - ClinicalTrials.gov.

Keywords: Human adipose tissue; Marine-source omega-3 fatty acids; NLRP3 inflammasome and interleukin-1 beta; Plasma apoB; Type 2 diabetes.

Fig. 1

Percent FA in plasma and RBC PL at baseline and post-intervention: Baseline and post-intervention % FA in plasma PL (A) and RBC PL (B) in all subjects (N = 33) who completed the 12-week supplementation with 2.7 g/d EPA and DHA. N.B. Mead acid was excluded from analysis as only N = 2 had measurable post-intervention data in RBC. * for p < 0.05, ** for p < 0.01 and *** for p < 0.001 versus baseline.

Fig. 2

WAT IL-1β-secretion at baseline and post-intervention: WAT IL-1β-secretion induced by the 7-incubation conditions with LDL, LPS and/or ATP at baseline (A) and post-intervention (B), and % change in WAT IL-1β-secretion induced by LDL/LDL versus medium/medium (negative control) at baseline (C) and post-intervention (D), by LDL/ATP versus medium/ATP at baseline (E) and post-intervention (F), and by LPS/LDL versus LPS/medium at baseline (G) and post-intervention (H) in subjects with low-apoB (N = 13) and high-apoB (baseline N = 15, post-intervention N = 13) who completed the intervention.

Fig. 3

Risk factors for T2D at baseline and post-intervention: Group-differences at baseline and post-intervention in 1st phase C-peptide secretion (A), 2nd phase C-peptide secretion (B), insulin sensitivity (C), total disposition index (D), AUC_6hrs postprandial plasma apoB48 (E), and AUC_6hrs postprandial plasma TG (F) in subjects with low-apoB (N = 16) and high-apoB (N = 17) who completed the intervention, except for panels E and F where N = 15 for low-apoB and N = 16 for high-apoB for missing data.

Fig. 4

Association of post-intervention % shift in RBC PL omega-3 FA with % change in T2D risk factors: Pearson correlation of % shift in EPA, DPA, DHA or EPA + DHA with % change in total C-peptide secretion (A–D), insulin sensitivity (E–H), total disposition index (I–L), AUC_6hrs postprandial plasma apoB48 (M–P), AUC_6hrs postprandial plasma TG (Q–T), fasting plasma LDL-C (U-X) and estimated LDL size (Y-AB) in subjects with low-apoB (N = 16, open circles, dotted regression lines) and high-apoB (N = 17, closed circles, dashed regression lines) who completed the 12-week supplementation with EPA and DHA, except for panels M-AB where N = 15 for low-apoB and N = 16 for high-apoB for missing data. Solid regression line represents pooled data for all subjects.

Fig. 5

Association of LDL/LDL-induced WAT IL-1β-secretion with T2D risk factors at baseline and post-intervention: Pearson correlation of LDL/LDL-induced WAT IL-1β-secretion with 1st phase disposition index (A), WAT mRNA expression of PPARG (B), CASP1 (C) and SREBP2 (D) normalized for HPRT at baseline in subjects with low-apoB (N = 9, open circles, dotted regression lines) and high-apoB (N = 15, closed circles, dashed regression lines) who completed the intervention, and with the same parameters post-intervention (E–H) in subjects with low-apoB (N = 12) and high-apoB (N = 13). Solid regression line represents pooled data for all subjects.

Fig. 6

Association of LDL/ATP-induced WAT IL-1β-secretion with T2D risk factors at baseline and post-intervention: Pearson correlation of baseline LDL/ATP-induced WAT IL-1β-secretion with 1st phase disposition index (A), total disposition index (B),  insulin sensitivity (C), WAT mRNA expression of ADGRE1 (D), MCP1 (E), PPARG (F), and SREBP2 (G) normalized for HPRT, BMI (H), android fat (I), and total body fat (J) at baseline in subjects with low-apoB (N = 13, open circles, dotted regression lines) and high-apoB (N = 14, closed circles, dashed regression lines) who completed the intervention, and with the same parameters post-intervention (K–T) in subjects with low-apoB (N = 12) and high-apoB (N = 13). Solid regression line represents pooled data for all subjects.

Fig. 7

Association of LPS/LDL-induced WAT IL-1β-secretion with T2D risk factors at baseline and post-intervention: Pearson correlation of baseline LPS/LDL-induced WAT IL-1β-secretion with total GIIS_IVGTT (A),  insulin sensitivity (B), AUC_6hrs postprandial plasma apoB48 (C), AUC_6hrs postprandial plasma TG (D), fasting WAT mRNA expression of ADIPOQ (E) and CD36 (F) normalized for HPRT, fasting plasma apoB (G), estimated LDL size (H) BMI (I), and android fat (J) in subjects with low-apoB (N = 13, open circles, dotted regression lines) and high-apoB (N = 14, closed circles, dashed regression lines) who completed the intervention, and with the same parameters post-intervention (K–T) in subjects with low-apoB (N = 11) and high-apoB (N = 13). Solid regression line represents pooled data for all subjects.

Fig. 8

Effects of EPA and DHA on WAT IL-1β-secretion ex vivo: Effects of 50, 100 or 200 µmol/L EPA:DHA (2:1) versus equal concentrations of oleate and palmitate on IL-1β-secretion in unstimulated WAT (A) and LPS/ATP-stimulated WAT (B), and effects of 200 µmol/L EPA:DHA (2:1) versus oleate and palmitate on IL-1β-secretion at baseline and post-intervention in unstimulated WAT (C), LDL/ATP-stimulated WAT (D), LPS/LDL-stimulated WAT (E) and LPS/ATP-stimulated WAT (F) in subjects who completed the intervention. Panels A, B included 5 subjects at baseline (N = 1 low-apoB and N = 4 high-apoB) and panels C–F included 18 subjects at baseline (N = 9 low-apoB and N = 9 high-apoB) and 14 subjects post-intervention (N = 6 low-apoB and N = 8 high-apoB). * for p < 0.05, ** for p < 0.01 and *** for p < 0.001 versus control (0.105 µmol/L albumin in 5% fetal bovine serum medium) or similar concentrations of oleate or palmitate, and ^$ for p < 0.05, ^$$ for p < 0.01 versus control.

Fig. 9

Pleiotropic effects of EPA and DHA: Supplementation with 2.7 g/d EPA and DHA over 12-weeks inhibited LDL-induced WAT-IL-1β-secretion ex vivo, ameliorated GIIS secretion and postprandial plasma clearance of chylomicrons and TG, and inhibited the association of WAT-IL-1β-secretion with multiple systemic risk factors for T2D and measures of WAT inflammation and dysfunction