Cited by 215Adipokines, Inflammation, and Metabolic DiseasesAdipose Tissue and MetabolismLipid metabolism and disorders

Lipodystrophy: metabolic insights from a rare disorder

Huang-Doran, Isabel, Sleigh, Alison, Rochford, Justin J, O'Rahilly, Stephen, Savage, David B·2010·Journal of Endocrinology

Abstract

Obesity, insulin resistance and their attendant complications are among the leading causes of morbidity and premature mortality today, yet we are only in the early stages of understanding the molecular pathogenesis of these aberrant phenotypes. A powerful approach has been the study of rare patients with monogenic syndromes that manifest as extreme phenotypes. For example, there are striking similarities between the biochemical and clinical profiles of individuals with excess fat (obesity) and those with an abnormal paucity of fat (lipodystrophy), including severe insulin resistance, dyslipidaemia, hepatic steatosis and features of hyperandrogenism. Rare lipodystrophy patients therefore provide a tractable genetically defined model for the study of a prevalent human disease phenotype. Indeed, as we review herein, detailed study of these syndromes is beginning to yield valuable insights into the molecular genetics underlying different forms of lipodystrophy, the essential components of normal adipose tissue development and the mechanisms by which disturbances in adipose tissue function can lead to almost all the features of the metabolic syndrome.

Integrity signals

Registry

Crossref · 10.1677/joe-10-0272

Cites

94 of 94 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Patients with acquired generalized lipodystrophy lose fat from large areas of the body during childhood and adolescence and often have hepatic steatosis.

    “Patients with acquired generalized lipodystrophy lose fat from large areas of the body during childhood and adolescence and often have hepatic steatosis (100).”

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Huang-Doran, I., Sleigh, A., Rochford, J. J., O'Rahilly, S., & Savage, D. B.
Affiliations
  • University of Cambridge (GB)
  • Wellcome/MRC Institute of Metabolic Science (GB)
Venue
Journal of Endocrinology
Published
2010-09-24
Volume
207
Issue
3
Pages
245-255
ISSN
  • 0022-0795 (ISSN-L)
  • 1479-6805
OpenAlex
W2166938485
Cited by
215
References
94
Citations by year
2026: 2 · 2025: 9 · 2024: 9 · 2023: 11 · 2022: 13 · 2021: 8 · 2020: 14 · 2019: 13 · 2018: 22 · 2017: 19 · 2016: 14 · 2015: 13 · 2014: 15 · 2013: 20 · 2012: 17
FWCI
12.33
Type
journal article
Language
en
Open access
closed
Locations
  • Journal of Endocrinology (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • GlaxoSmithKline
  • Wellcome Trust (091551, 078986/Z/06/Z)
  • National Institute for Health and Care Research
  • Medical Research Council
  • NIHR Cambridge Biomedical Research Centre
Topics
  • Health Sciences › Medicine › Epidemiology › Adipokines, Inflammation, and Metabolic Diseases
  • Health Sciences › Medicine › Physiology › Adipose Tissue and Metabolism
  • Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Lipid metabolism and disorders
Keywords
lipodystrophy, obesity, insulin resistance, metabolic syndrome, monogenic disorders, adipose tissue development, dyslipidemia, hepatic steatosis, hyperandrogenism, molecular genetics, rare genetic disorders
MeSH terms
Adipose Tissue, Animals, Fatty Liver, Female, Humans, Insulin Resistance, Lipodystrophy, Male, Obesity, Gene Expression, Hyperandrogenism, Metabolic Syndrome, Dyslipidemias, Mice

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review