Evidence map›Paper›PMID 35413480›Full record

ArticleMolecular metabolism2022

Angiopoietin-like 4 governs diurnal lipoprotein lipase activity in brown adipose tissue.

Robin van Eenige, Wietse In Het Panhuis, Milena Schönke, Céline Jouffe, Thomas H Devilee, Ricky Siebeler, Trea C M Streefland, Hetty C M Sips, Amanda C M Pronk, Ruben H P Vorderman and 7 more

Open access · goldAbstract read
In one paragraph

Article in Molecular metabolism, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 13 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors at 3 institutions in 2 countries.

Robin van EenigeDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Wietse In Het PanhuisDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Milena SchönkeDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Céline JouffeInstitute for Diabetes and Endocrinology (IDE), Helmholtz Diabetes Center (HMGU) and German Center for Diabetes Research (DZD), Munich, Germany.
Thomas H DevileeDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Ricky SiebelerDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Trea C M StreeflandDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Hetty C M SipsDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Amanda C M PronkDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Ruben H P VordermanSequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
Hailiang MeiSequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands.
Jan Bert van KlinkenLaboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands; Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Leiden, the Netherlands.
Michel van WeeghelLaboratory Genetic Metabolic Diseases, Amsterdam UMC, University of Amsterdam, Amsterdam Gastroenterology and Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam, the Netherlands; Core Facility Metabolomics, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
Nina H UhlenhautSequencing Analysis Support Core, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands; Metabolic Programming, Technical University of Munich School of Life Sciences, Freising, Germany.
Sander KerstenNutrition, Metabolism and Genomics Group, Division of Human Nutrition, Wageningen, the Netherlands.
Patrick C N RensenDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands.
Sander KooijmanDivision of Endocrinology, Department of Medicine, Leiden University Medical Center, Leiden, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden University Medical Center, Leiden, the Netherlands. Electronic address: s.kooijman@lumc.nl.
Leiden University Medical Center · NLAmsterdam Neuroscience · NLDeutsches Diabetes-Zentrum e.V. · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveBrown adipose tissue (BAT) burns fatty acids (FAs) to produce heat, and shows diurnal oscillation in glucose and triglyceride (TG)-derived FA-uptake, peaking around wakening. Here we aimed to gain insight in the diurnal regulation of metabolic BAT activity.

methodsRNA-sequencing, chromatin immunoprecipitation (ChIP)-sequencing, and lipidomics analyses were performed on BAT samples of wild type C57BL/6J mice collected at 3-hour intervals throughout the day. Knockout and overexpression models were used to study causal relationships in diurnal lipid handling by BAT.

resultsWe identified pronounced enrichment of oscillating genes involved in extracellular lipolysis in BAT, accompanied by oscillations of FA and monoacylglycerol content. This coincided with peak lipoprotein lipase (Lpl) expression, and was predicted to be driven by peroxisome proliferator-activated receptor gamma (PPARγ) activity. ChIP-sequencing for PPARγ confirmed oscillation in binding of PPARγ to Lpl. Of the known LPL-modulators, angiopoietin-like 4 (Angptl4) showed the largest diurnal amplitude opposite to Lpl, and both Angptl4 knockout and overexpression attenuated oscillations of LPL activity and TG-derived FA-uptake by BAT.

conclusionsOur findings highlight involvement of PPARγ and a crucial role of ANGPTL4 in mediating the diurnal oscillation of TG-derived FA-uptake by BAT, and imply that time of day is essential when targeting LPL activity in BAT to improve metabolic health.

Indexed as

Adipose Tissue, BrownLipoprotein LipaseAngiopoietin-Like Protein 4AngiopoietinsAnimalsMiceMice, Inbred C57BLMice, KnockoutPPAR gammaTriglyceridesAngiopoietin-Like Protein 4AngiopoietinsAngptl4 protein, mouseLipoprotein LipasePPAR gammaTriglyceridesAngiopoietin-like 4Brown adipose tissueCircadian/diurnal rhythmsLipoprotein lipasePeroxisome proliferator-activated receptor gammaTranscriptomics

Identifiers

PMID35413480
PMCPMC9048098
OpenAlexW4223499332

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.