Rewiring of catecholamine‐induced calcium signalling is an early event in non‐alcoholic fatty liver disease
Bibliographic record
Abstract
Non-alcoholic fatty liver disease (NAFLD) is a global health problem without approved pharmacological treatment (Riazi et al., 2022). Mechanistically, excessive accumulation of triglycerides in hepatocytes due to increased de novo lipogenesis and decreased β-oxidation constitutes an early defining feature in the pathogenesis of NAFLD. Emerging evidence of the last 20 years assigned a central role in the regulation of hepatic energy homeostasis to calcium signalling (Oliva-Vilarnau et al., 2018). However, information about molecular events preceding the onset of hepatic steatosis are limited. The study by Brumer et al. (2023) convincingly demonstrates changes in catecholamine-induced inositol 1,4,5-trisphosphate (IP3) production and calcium signalling in mouse liver after short-term exposure to high fat diet (HFD) before the apparition of histological changes. Lying at the root of these early changes are liver-resident alpha-1B adrenergic receptors (α1BARs) that play a role in glycaemic control, as well as carbohydrate and lipid homeostasis. α1BARs are G protein-coupled receptors (GPCRs) that activate Gαq/11 following the binding of catecholamines such as norepinephrine. Once active, Gαq/11 kicks off a signalling cascade involving phospholipase C (PLC) that is directly involved in the production of IP3 and diacylglycerol (DAG) from phosphatidylinositol 4,5-bisphosphate. Then, IP3 diffuses to the endoplasmic reticulum where it binds the IP3 receptor resulting in the mobilization of calcium, an important second messenger in human physiology. The reduction in calcium mobilization upon HFD did not result from an inhibition of the sarco/endoplasmic reticulum calcium ATPase (SERCA) or store-operated Ca2⁺ channel (SOC) activity. Nor was any difference observed in the expression or distribution of the key signalling components α1BAR, Gαq, PLCβ3, IP3R, SERCA. Instead, Brumer et al. (2023) showed that short-term exposure to HFD affected the amount of IP3 that is generated by PLC, which results in lower IP3R activity and limited release of calcium from intracellular stores. Taken together, these findings shed new light on the early events that lead to NAFLD and may facilitate the development of therapeutics that rescue this hormone-induced calcium signalling axis. However, further work is needed to address the molecular basis for the decrease in IP3 production. One possibility could be a reduced ability of α1BARs to efficiently activate Gαq/11. Although the expression and distribution of α1BARs and Gαq/11 remained unchanged after short-term HFD, differences in membrane fatty acid composition can allosterically affect the ability of GPCRs to effectively exchange the GDP in the Gα subunit with GTP (Dawaliby et al., 2016). This would result in fewer active GTPGαq/11 available to bind PLC. Similarly, membrane lipid composition can affect the localization of PLC and the availability of calcium can affect its catalytic activity. Yet another explanation could come from the generation of DAG through hepatic lipogenesis that activates novel protein kinase C (PKC) isoforms in the absence of calcium mobilization, resulting in PKC-dependent desensitization of GPCR-dependent calcium signalling. Moving forward, it will be important to show that the observed phenomena also occur in human hepatocytes in order to narrow the translational gap. Of relevance in this context could be the wealth of organotypic hepatocyte culture methods that have emerged in recent years, which allow the accurate emulation of hepatic steatosis and its progression to inflammation and fibrosis (Ramos et al., 2022). Although not specifically evaluated yet, their overall phenotypic and molecular resemblance to steatotic liver fuels hopes that also hormonally controlled Ca2⁺ oscillations are preserved in these systems. Combined, the finding that high-fat diet rapidly curbs GPCR-dependent PLC activation, resulting in perturbed Ca2⁺ transients and suppressed propagation of trans-lobular Ca2⁺ waves, opens new avenues for the pharmacological exploration of new mechanisms that target NAFLD onset. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. VML is co-founder, CEO and a shareholder of HepaPredict AB, as well as chairman of the board and shareholder of PersoMedix AB. SCW declares no competing interests. S.W. and V.L. were responsible for the conception or design of the work, drafting the work or revising it critically for important intellectual content, and final approval of the version to be published. Both authors agree to be accountable for all aspects of the work. S.C.W. is supported by a fellowship from the Swedish Society for Medical Research (P18-0098; PD20-0153). V.M.L. is supported by the Swedish Research Council (grant agreement numbers 2019-01837 and 2021-02801), by the EU/EFPIA/OICR/McGill/KTH/Diamond Innovative Medicines Initiative 2 Joint Undertaking (EUbOPEN grant number 875510), by the Swedish Strategic Research Programme in Diabetes (SFO Diabetes) and Stem Cells and Regenerative Medicine (SFO StratRegen), and by the Robert Bosch Foundation, Stuttgart, Germany.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".