Evidence map›Paper›PMID 29846621›Full record

ArticleThe Journal of clinical endocrinology and metabolism2018

Subcutaneous Fat Fibrosis Links Obesity to Insulin Resistance in Chinese Americans.

Diana L Alba, Jeffrey A Farooq, Matthew Y C Lin, Anne L Schafer, John Shepherd, Suneil K Koliwad

Open access · bronzeAbstract readMulticenter Study
In one paragraph

Article in The Journal of clinical endocrinology and metabolism, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
3.9field-weighted citation impact, top 6% 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

22 citing papers in PubMed, 38 citations in OpenAlex.

  1. Trial
  2. Observational
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  15. Review
  16. Article
  17. Review
  18. Adipose Tissue Fibrosis: Mechanisms, Models, and Importance.International journal of molecular sciences · 2020
    Review
  19. Article
  20. Article
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

6 authors at 2 institutions in 1 country.

Diana L AlbaDivision of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of California, San Francisco, San Francisco, California.
Jeffrey A FarooqDiabetes Center, University of California, San Francisco, San Francisco, California.
Matthew Y C LinDepartment of Surgery, University of California, San Francisco, San Francisco, California.
Anne L SchaferDivision of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of California, San Francisco, San Francisco, California.
John ShepherdDepartment of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California.
Suneil K KoliwadDivision of Endocrinology, Diabetes, and Metabolism, Department of Medicine, University of California, San Francisco, San Francisco, California.
University of California, San Francisco · USSan Francisco VA Medical Center · US

Funding

Clinical and Translational Science InstituteUL1TR001872 · NCATS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI COLLARD, HAROLD R, JACOBY, VANESSA · 2016 to 2025
$112.1M
Research BaseP30DK063720 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KRUMMEL, MATTHEW F · 2003 to 2019
$21.8M
UCSF Nutrition Obesity Research CenterP30DK098722 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CHRISTIAN VAISSE · 2015 to 2026
$14.6M
DIABETES, ENDOCRINOLOGY &METABOLISM TRAINING PROGRAMT32DK007418 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI EDWARD C HSIAO · 1986 to 2026
$14.3M
Microglia: dietary fat-sensitive mediators of inflammation and metabolic diseaseR01DK103175 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KOLIWAD, SUNEIL KRISHNA · 2015 to 2019
$1.8M
NCATS NIH HHS UL1 TR001872NIDDK NIH HHS P30 DK063720NIDDK NIH HHS P30 DK098722NIDDK NIH HHS R01 DK103175NIDDK NIH HHS T32 DK007418
6 · The paper itself

Abstract

Objective: Type 2 diabetes presents at a lower body mass index (BMI) in Chinese individuals than in white individuals. We sought to determine the role of subcutaneous adipose tissue (SCAT)-intrinsic factors, vs BMI or adiposity per se, in the vulnerability of Chinese individuals to obesity-associated impairment of insulin sensitivity. Research Design and Methods: Thirty-two Chinese and 30 white men and women from a cohort in the San Francisco Bay Area underwent anthropometric measurements, body composition (dual-energy X-ray absorptiometry) analyses, and measurement of fasting plasma glucose and insulin. Forty-eight also provided abdominal SCAT samples for transcriptional and biochemical analyses of tissue fibrosis. Results: BMI correlated with total body fat in white (r = 0.74, P < 0.001) but not Chinese individuals, whereas BMI correlated with visceral adipose tissue (VAT) accrual in both ethnicities (r = 0.88 and 0.81, respectively; P < 0.01). Insulin resistance (homeostatic model assessment of insulin resistance) worsened with VAT mass, but not total body fat, in Chinese subjects (r = 0.63, P < 0.01), whereas it worsened with both in white individuals. By contrast, SCAT mRNA levels of genes encoding profibrotic proteins rose remarkably along with both BMI and VAT mass in Chinese but not white subjects. Similarly, SCAT levels of hydroxyproline, an indicator of tissue collagen content that correlated with increasing VAT mass, were higher in Chinese vs white subjects, particularly in the setting of relative insulin resistance. Conclusions: Our findings dissociate BMI from adiposity in Chinese individuals and instead highlight SCAT fibrosis as a process linked to visceral adiposity and insulin resistance in this group.

Indexed as

AdiposityAdultAgedAnthropometryAsianBlood GlucoseBody CompositionBody Mass IndexFemaleFibrosisHumansHydroxyprolineInsulin ResistanceMaleMiddle AgedObesityBlood GlucoseHydroxyproline

Identifiers

PMID29846621
PMCPMC6126891
OpenAlexW2807525281

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.