Evidence map›Paper›PMID 35178663›Full record

ArticleHepatology international2022

Distinctive clinical and genetic features of lean vs overweight fatty liver disease using the UK Biobank.

Daljeet Chahal, Divya Sharma, Sareh Keshavarzi, Fakhar Ali Qazi Arisar, Keyur Patel, Wei Xu, Mamatha Bhat

Abstract read
PubMed Publisher
In one paragraph

Article in Hepatology international, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
3.6field-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

23 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Impact of genotyping (Frontiers in endocrinology · 2025
    Article
  11. Review
  12. Disparities among ethnic groups in mortality and outcomes among adults with MASLD: A multicenter study.Liver international : official journal of the International Association for the Study of the Liver · 2024
    Article
  13. Article
  14. Article
  15. Prospective study design and data analysis in UK Biobank.Science translational medicine · 2024
    Review
  16. Review
  17. Review
  18. Article
  19. Review
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Daljeet ChahalDivision of Gastroenterology, University of British Columbia, Vancouver, Canada.ORCID http://orcid.org/0000-0003-2486-1449
Divya SharmaDivision of Gastroenterology, University of British Columbia, Vancouver, Canada.
Sareh KeshavarziDivision of Gastroenterology, University of British Columbia, Vancouver, Canada.
Fakhar Ali Qazi ArisarDivision of Gastroenterology, University of British Columbia, Vancouver, Canada.
Keyur PatelDivision of Gastroenterology, University of British Columbia, Vancouver, Canada.
Wei XuDivision of Gastroenterology, University of British Columbia, Vancouver, Canada.
Mamatha BhatDivision of Gastroenterology, University of British Columbia, Vancouver, Canada. mamatha.bhat@uhn.ca.
University of British Columbia · CAUniversity Health Network · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLean NAFLD may differ from NAFLD found in overweight or obese patients. We used the UK biobank to conduct a cross-sectional study that examined features that distinguish lean NAFLD from overweight or obese NAFLD.

methodsMRI-PDFF data were used to identify patients with NAFLD, with NAFLD defined as PDFF ≥ 5%. BMI patient cohorts were identified, with lean defined as a BMI < 25, and overweight or obese defined as a BMI ≥ 25. Variables of interest to fatty liver disease, including single nucleotide polymorphisms, were chosen from the UK biobank data portal. Logistic regression was used to generate models predictive of NAFLD in each cohort.

results1007 patients had NAFLD, and of these, 871 had BMI ≥ 25, and 136 BMI < 25. Factors associated with NAFLD in patients with BMI < 25 included male sex, white blood cell count, red blood cell count, triglycerides, ALT, creatinine, visceral adipose tissue, rs58542926 T, and rs738409 G. In contrast, factors associated with NAFLD in patients with BMI ≥ 25 included male sex, waist circumference, HDL cholesterol, triglycerides, serum glucose, ALT, creatinine, urate, visceral adipose tissue, rs1260326 T, rs1044498 C, rs58542926 T, and rs738409 G. For lean patients, our generated prediction score had an AUC of 0.92, sensitivity of 0.90 and specificity of 0.81. For overweight or obese patients, the prediction score had an AUC of 0.86, sensitivity of 0.87 and specificity of 0.70.

conclusionsOur analysis suggests that lean and overweight or obese NAFLD are distinct entities. We have developed a risk score incorporating both clinical and genetic factors that accurately classify lean patients with NAFLD, with the potential to serve as a tool for screening purposes.

Indexed as

Non-alcoholic Fatty Liver DiseaseOverweightBiological Specimen BanksBody Mass IndexCreatinineCross-Sectional StudiesHumansMaleObesityTriglyceridesUnited KingdomCreatinineTriglyceridesCirrhosisDiabetesFatty liverLean NASHLiverNAFLDNASHObesitySteatohepatitisTransplant

Identifiers

PMID35178663
OpenAlexW4212879278

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.