Challenging dogma: is hepatic lipid accumulation in type 2 diabetes due to mitochondrial dysfunction?
Bibliographic record
Abstract
A major prevailing hypothesis is that hepatic lipid accumulation contributes to hyperglycaemia in type 2 diabetics by blunting the ability of insulin to suppress hepatic glucose production (Lowell & Shulman, 2005). While the cause of this excess hepatic lipid content is widely debated, evidence from multiple experimental models suggests that lipid accumulation is related to impaired mitochondrial oxidative capacity (Szendroedi et al. 2009; Rector et al. 2010, 2011; Schmid et al. 2011; Franko et al. 2014; Linden et al. 2014). This evidence is based, in part, on in vivo assessments of hepatic ATP production using indirect 31-P magnetic resonance spectroscopy (MRS) (Szendroedi et al. 2009; Schmid et al. 2011). In this issue of The Journal of Physiology, Lund et al. (2016) argue that more direct assessments of human liver mitochondria are warranted in order to eliminate the potential influence of cytosolic ATP inherent in the 31-P MRS approach, and to determine whether dysregulation exists within specific sites of the mitochondrial oxidative phosphorylation cascade. Using biopsies of human liver – an innovation for the field of mitochondrial bioenergetics in diabetes – the authors report similar respiratory capacities assessed in vitro despite increases in liver lipid content in type 2 diabetics vs. control subjects. Respiratory capacities were assessed for the specific reason of addressing the hypothesis that a reduction in mitochondrial oxidative capacity itself, particularly with regard to fat oxidation, is causal for hepatic fat accumulation. These findings directly challenge the growing dogmatic view that mitochondrial dysfunction contributes to ectopic lipid accumulation and hepatic pathology in type 2 diabetes. As the authors note, reconciling these findings with previous work requires careful consideration of the methodologies employed. In vitro assessments of mitochondrial oxidative phosphorylation are based on oximetry whereby the rate of oxygen utilization (‘respiration’) is interpreted as an index of ATP synthesis. This procedure effectively retains mitochondrial morphology by avoiding tissue homogenization. Furthermore, a preliminary washing step removes the cytosolic compartment which permits the isolation of specific enzymatic components of oxidative phosphorylation by strategic introduction of exogenous substrates. The measurement of ‘capacities’ offers the specific advantage of testing the dogmatic hypothesis that a ‘reduced capacity’ for oxidative phosphorylation – specifically fat oxidation – exists in type 2 diabetic liver. Indeed, this study demonstrated that mitochondrial capacity for fat oxidation in vitro was not different between diabetics and control participants, which does not support the long-held view of reduced mitochondrial capacity being causally linked to increases in liver lipid content. The authors note that comparing their data to the previous MRS literature might suggest that the evidence for reduced ATP synthesis rates in vivo could be influenced by cytosolic ATP. This comparative approach is essential for reconciling the literature but is also important for questioning how we can advance our in vitro methodologies to model critical regulatory factors present in vivo. Indeed, a strength of the previous studies with 31-P MRS (Szendroedi et al. 2009; Schmid et al. 2011) would seem to be the calculation of ATP synthesis rates in the presence of physiological regulatory parameters within the cytosol, cell membrane and extracellular compartments in vivo. As Lund et al. discuss, considering the advantages and disadvantages of both approaches, one advance might be to re-examine human liver mitochondrial function in vitro with physiological concentrations of substrates found in vivo (‘sub-capacity’). Careful consideration of additional regulatory factors of hepatic fat oxidation (e.g. lipid droplet catabolism, endocrine/humoral regulators, fatty acid uptake, etc.) might raise further intriguing approaches for modelling respiratory control in vivo that might be lost in vitro. Furthermore, comparing respirometric responses to other in vitro approaches, as used previously in rodents (Rector et al. 2010, 2011; Franko et al. 2014; Linden et al. 2014), might be a useful comparative approach to isolate potential dysfunctions in fat oxidation. The present investigation is significant in that it challenges a prevailing model that mitochondrial dysfunction contributes to hepatic fat accumulation in type 2 diabetes in humans. Indeed, the similarities between control and diabetics in the Lund study are consistent with an alternative model whereby lipid accumulation is due to an excess delivery of lipids to the liver or de novo lipogenesis from glucose that surpasses metabolic demand (i.e. excess dietary intake combined with sedentarism) rather than reductions in fat oxidation within mitochondria themselves. As such, the present investigation should stimulate conversation regarding the prevailing conceptual models of mitochondrial dysfunction as a causal event in hepatic lipid accumulation in type 2 diabetes. Furthermore, this investigation forms a foundation for future conciliatory investigations that draw on the advantages of major in vitro and in vivo methodologies for assessing hepatic mitochondrial function in humans. None declared.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.004 | 0.013 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.011 | 0.020 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".