In vivo insulin sensitivity can be assessed using “open loop” clamp or “closed loop” methods. Open loop clamp methods are static, and fix plasma glucose independently from plasma insulin. Closed loop methods are dynamic, and assess glucose disposal in response to a stable isotope labeled glucose tolerance test. Using PPARα−/− mice, open and closed loop assessments of insulin sensitivity/glucose disposal were compared. Indirect calorimetry done for the assessment of diurnal substrate utilization/metabolic flexibility showed that chow fed PPARα−/− mice had increased glucose utilization during the light (starved) cycle. Euglycemic clamps showed no differences in insulin stimulated glucose disposal, whether for chow or high fat diets, but did show differences in basal glucose clearance for chow fed PPARα−/− versus SV129J-wt mice. In contrast, the dynamic stable isotope labeled glucose tolerance tests reveal enhanced glucose disposal for PPARα−/− versus SV129J-wt, for chow and high fat diets. Area under the curve for plasma labeled and unlabeled glucose for PPARα−/− was ≈1.7-fold lower, P < 0.01 during the stable isotope labeled glucose tolerance test for both diets. Area under the curve for plasma insulin was 5-fold less for the chow fed SV129J-wt (P < 0.01) but showed no difference on a high fat diet (0.30 ± 0.1 for SV129J-wt vs. 0.13 ± 0.10 for PPARα−/−, P = 0.28). This study demonstrates that dynamic stable isotope labeled glucose tolerance test can assess “silent” metabolic phenotypes, not detectable by the static, “open loop”, euglycemic or hyperglycemic clamps. Both open loop and closed loop methods may describe different aspects of metabolic inflexibility and insulin sensitivity.

Background

A better understanding of the pathophysiology involving coronary artery calcification (CAC) in patients on hemodialysis (HD) will help to develop new therapies. We sought to identify the differences in metabolomics profiles between patients on HD with and without CAC.

Methods

In this case-control study, nested within a cohort of 568 incident patients on HD, the cases were patients without diabetes with a CAC score >100 (n=51), and controls were patients without diabetes with a CAC score of zero (n=48). We measured 452 serum metabolites in each participant. Metabolites and pathway scores were compared using Mann-Whitney U tests, partial least squares-discriminant analyses, and pathway enrichment analyses.

Results

Compared with controls, cases were older (64±13 versus 42±12 years) and were less likely to be Black (51% versus 94%). We identified three metabolites in bile-acid synthesis (chenodeoxycholic, deoxycholic, and glycolithocholic acids) and one pathway (arginine/proline metabolism). After adjusting for demographics, higher levels of chenodeoxycholic, deoxycholic, and glycolithocholic acids were associated with higher odds of having CAC; comparing the third with the first tertile of each bile acid, the OR was 6.34 (95% CI, 1.12 to 36.06), 6.73 (95% CI, 1.20 to 37.82), and 8.53 (95% CI, 1.50 to 48.49), respectively. These associations were no longer significant after further adjustment for coronary artery disease and medication use. Per 1 unit higher in the first principal component score, arginine/proline metabolism was associated with CAC after adjusting for demographics (OR, 1.83; 95% CI, 1.06 to 3.15), and the association remained significant with additional adjustments for statin use (OR, 1.84; 95% CI, 1.04 to 3.27).

Conclusions

Among patients on HD without diabetes mellitus, chenodeoxycholic, deoxycholic, and glycolithocholic acids may be potential biomarkers for CAC, and arginine/proline metabolism is a plausible mechanism to study for CAC. These findings need to be confirmed in future studies.

Background

Alterations in gut microbiota (GMB) and host metabolites have been noted in individuals with HIV. However, it remains unclear whether alterations in GMB and related functional groups contribute to disrupted host metabolite profiles in these individuals.

Methods

This study included 185 women (128 with longstanding HIV infection, 88% under antiretroviral therapy; and 57 women without HIV from the same geographic location with comparable characteristics). Stool samples were analyzed by 16S rRNA V4 region sequencing, and GMB function was inferred by PICRUSt. Plasma metabolomic profiling was performed using liquid chromatography-tandem mass spectrometry, and 133 metabolites (amino acids, biogenic amines, acylcarnitines, and lipids) were analyzed.

Results

Four predominant bacterial genera were identified as associated with HIV infection, with higher abundances of Ruminococcus and Oscillospira and lower abundances of Bifidobacterium and Collinsella in women with HIV than in those without. Women with HIV showed a distinct plasma metabolite profile, which featured elevated glycerophospholipid levels compared with those without HIV. Functional analyses also indicated that GMB lipid metabolism was enriched in women with HIV. Ruminococcus and Oscillospira were among the top bacterial genera contributing to the GMB glycerophospholipid metabolism pathway and showed positive correlations with host plasma glycerophospholipid levels. One bacterial functional capacity in the acetate and propionate biosynthesis pathway was identified to be mainly contributed by Bifidobacterium; this functional capacity was lower in women with HIV than in women without HIV.

Conclusions

Our integrative analyses identified altered GMB with related functional capacities that might be associated with disrupted plasma metabolite profiles in women with HIV.

[Image: see text]