Evidence map›Paper›PMID 26629547›Full record

ArticleEBioMedicine2015

Circulating Unsaturated Fatty Acids Delineate the Metabolic Status of Obese Individuals.

Yan Ni, Linjing Zhao, Haoyong Yu, Xiaojing Ma, Yuqian Bao, Cynthia Rajani, Lenora W M Loo, Yurii B Shvetsov, Herbert Yu, Tianlu Chen and 8 more

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in EBioMedicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
73citing papers in PubMed, 1 pooled it
6.2field-weighted citation impact, top 3% 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

73 citing papers in PubMed, 1 synthesis or guideline pooled it, 147 citations in OpenAlex.

  1. Pooled it
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  8. Role of fatty acid metabolism-related genes in periodontitis based on machine learning and bioinformatics analysis.Hua xi kou qiang yi xue za zhi = Huaxi kouqiang yixue zazhi = West China journal of stomatology · 2024
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  11. The Potential of Bile Acids as Biomarkers for Metabolic Disorders.International journal of molecular sciences · 2023
    Review
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  13. Lipid droplets are intracellular mechanical stressors that impair hepatocyte function.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  14. Article
  15. Review
  16. Dihomo-International journal of molecular sciences · 2023
    Review
  17. Article
  18. Review
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  20. Article

13 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

18 authors at 6 institutions in 2 countries.

Yan NiShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; University of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Linjing ZhaoShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; University of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Haoyong YuDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
Xiaojing MaDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
Yuqian BaoShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
Cynthia RajaniUniversity of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Lenora W M LooUniversity of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Yurii B ShvetsovUniversity of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Herbert YuUniversity of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Tianlu ChenShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Yinan ZhangShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Congrong WangShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
Cheng HuShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
Mingming SuUniversity of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Guoxiang XieUniversity of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Aihua ZhaoShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.
Wei JiaShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; University of Hawaii Cancer Center, Honolulu, HI 96813, USA.
Weiping JiaShanghai Key Laboratory of Diabetes Mellitus and Center for Translational Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China ; Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Diabetes Institute, Shanghai 200233, China.
Shanghai Jiao Tong University · CNCancer Center of Hawaii · USShanghai Sixth People's Hospital · CNUniversity of Hawaii System · USUniversity of Hawaiʻi at Mānoa · USUniversity of Hawaii Cancer Center

Funding

University of Hawaii Cancer Center CCSGP30CA071789 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI Xin Chen · 1996 to 2026
$56.2M
NCI NIH HHS P30 CA071789
6 · The paper itself

Abstract

backgroundObesity is not a homogeneous condition across individuals since about 25-40% of obese individuals can maintain healthy status with no apparent signs of metabolic complications. The simple anthropometric measure of body mass index does not always reflect the biological effects of excessive body fat on health, thus additional molecular characterizations of obese phenotypes are needed to assess the risk of developing subsequent metabolic conditions at an individual level.

methodsTo better understand the associations of free fatty acids (FFAs) with metabolic phenotypes of obesity, we applied a targeted metabolomics approach to measure 40 serum FFAs from 452 individuals who participated in four independent studies, using an ultra-performance liquid chromatograph coupled to a Xevo G2 quadruple time-of-flight mass spectrometer.

findingsFFA levels were significantly elevated in overweight/obese subjects with diabetes compared to their healthy counterparts. We identified a group of unsaturated fatty acids (UFAs) that are closely correlated with metabolic status in two groups of obese individuals who underwent weight loss intervention and can predict the recurrence of diabetes at two years after metabolic surgery. Two UFAs, dihomo-gamma-linolenic acid and palmitoleic acid, were also able to predict the future development of metabolic syndrome (MS) in a group of obese subjects.

interpretationThese findings underscore the potential role of UFAs in the MS pathogenesis and also as important markers in predicting the risk of developing diabetes in obese individuals or diabetes remission after a metabolic surgery.

Indexed as

AdultBiomarkersChromatography, High Pressure LiquidCluster AnalysisDiabetes Mellitus, Type 2Fatty Acids, UnsaturatedFemaleHumansMaleMetabolic SyndromeMetabolomeMetabolomicsMiddle AgedObesityOdds RatioOverweightBiomarkersFatty Acids, UnsaturatedAA, arachidonic acidBMI, body mass indexCVD, cardiovascular diseaseDAG, diacylglycerolDBP, diastolic blood pressureDGLA, dihomo-gamma-linolenic acidDNL, de novo lipogenesisFATPs, fatty acid transport proteinsFFA, free fatty acidsFree fatty acidsGLA, γ-linolenic acidHA, heptadecanoic acidHbA1c, glycated hemoglobinHDL, high-density lipoproteinHO, metabolically healthy obeseInsulin resistanceLA, linoleic acidLDL, low-density lipoproteinMetabolic syndromeMS, metabolic syndromeMUFA, monounsaturated acidNAFLD, nonalcoholic fatty liver diseaseNW, normal weightObesityOGTT, oral glucose tolerance testOPLS-DA, orthogonal partial least square discriminant analysisPA, palmitoleic acidPUFA, polyunsaturated fatty acidRSD, relative standard deviationSBP, systolic blood pressureSCD, stearoyl-CoA desaturaseSFA, saturated fatty acidSHDS, the Shanghai Diabetes StudySHOS, the Shanghai Obesity StudyT2D, type 2 diabetesTC, total cholesterolTG, triglyceridesType 2 diabetesUFA, unsaturated fatty acidUnsaturated fatty acidsUO, metabolically unhealthy obeseVLCD, very low carbohydrate diet

Identifiers

PMID26629547
PMCPMC4634820
OpenAlexW2137890713

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.