Evidence map›Paper›PMID 32544198›Full record

ArticlePloS one2020

Lipidomics of human adipose tissue reveals diversity between body areas.

Naba Al-Sari, Tommi Suvitaival, Ismo Mattila, Ashfaq Ali, Linda Ahonen, Kajetan Trost, Trine Foged Henriksen, Flemming Pociot, Lars Ove Dragsted, Cristina Legido-Quigley

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.3field-weighted citation impact, top 21% 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

16 citing papers in PubMed, 23 citations in OpenAlex.

  1. Article
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  7. White adipose tissue remodeling in Little Brown Myotis (Myotis lucifugus) with white-nose syndrome.Metabolomics : Official journal of the Metabolomic Society · 2024
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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

10 authors at 3 institutions in 2 countries.

Naba Al-SariSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Tommi SuvitaivalSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Ismo MattilaSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Ashfaq AliSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Linda AhonenSteno Diabetes Center Copenhagen, Gentofte, Denmark.ORCID 0000-0001-7704-3912
Kajetan TrostSteno Diabetes Center Copenhagen, Gentofte, Denmark.
Trine Foged HenriksenCapio CFR, Kgs, Lyngby, Denmark.
Flemming PociotSteno Diabetes Center Copenhagen, Gentofte, Denmark.ORCID 0000-0003-3274-5448
Lars Ove DragstedDept. Nutrition, Exercise and Sports, University of Copenhagen, Gentofte, Denmark.ORCID 0000-0003-0609-6317
Cristina Legido-QuigleySteno Diabetes Center Copenhagen, Gentofte, Denmark.
Steno Diabetes Centers · DKUniversity of Copenhagen · DKDanish Defence Acquisition and Logistics Organization · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

aimsAdipose tissue plays a pivotal role in storing excess fat and its composition reflects the history of person's lifestyle and metabolic health. Broad profiling of lipids with mass spectrometry has potential for uncovering new knowledge on the pathology of obesity, metabolic syndrome, diabetes and other related conditions. Here, we developed a lipidomic method for analyzing human subcutaneous adipose biopsies. We applied the method to four body areas to understand the differences in lipid composition between these areas. MATERIALS AND

methodsAdipose tissue biopsies from 10 participants were analyzed using ultra-high-performance liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. The sample preparation optimization included the optimization of the lipid extraction, the sample amount and the sample dilution factor to detect lipids in an appropriate concentration range. Lipidomic analyses were performed for adipose tissue collected from the abdomen, breast, thigh and lower back. Differences in lipid levels between tissues were visualized with heatmaps.

resultsLipidomic analysis on human adipose biopsies lead to the identification of 186lipids in 2 mg of sample. Technical variation of the lipid-class specific internal standards were below 5%, thus indicating acceptable repeatability. Triacylglycerols were highly represented in the adipose tissue samples, and lipids from 13 lipid classes were identified. Long polyunsaturated triacylglycerols in higher levels in thigh (q<0.05), when compared with the abdomen, breast and lower back, indicating that the lipidome was area-specific.

conclusionThe method presented here is suitable for the analysis of lipid profiles in 2 mg of adipose tissue. The amount of fat across the body is important for health but we argue that also the distribution and the particular profile of the lipidome may be relevant for metabolic outcomes. We suggest that the method presented in this paper could be useful for detecting such aberrations.

Indexed as

LipidomicsAdipose TissueBiopsyHumansOrgan Specificity

Identifiers

PMID32544198
PMCPMC7297320
OpenAlexW3034552053

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.