Evidence map›Paper›PMID 23806069›Full record

ReviewGenome medicine2013

Obesity genomics: assessing the transferability of susceptibility loci across diverse populations.

Yingchang Lu, Ruth Jf Loos

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Genome medicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
59citing papers in PubMed, 4 pooled it
–field-weighted citation impact
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

59 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Review
  6. Article
  7. Review
  8. Article
  9. Article
  10. Technologies, strategies, and cautions when deconvoluting genome-wide association signals: FTO in focus.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2023
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Association of theMedicina (Kaunas, Lithuania) · 2020
    Article
  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

2 authors.

Yingchang LuThe Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
Ruth Jf LoosThe Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Charles Bronfman Institute of Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA ; The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The prevalence of obesity has nearly doubled worldwide over the past three decades, but substantial differences exist between nations. Although these differences are partly due to the degree of westernization, genetic factors also contribute. To date, little is known about whether the same genes contribute to obesity-susceptibility in populations of different ancestry. We review the transferability of obesity-susceptibility loci (identified by genome-wide association studies) using both single nucleotide polymorphism (SNP) and locus-wide comparisons. SNPs in FTO and near MC4R, obesity-susceptibility loci first identified in Europeans, replicate widely across other ancestries. SNP-to-SNP comparisons suggest that more than half of the 36 body mass index-associated loci are shared across European and East Asian ancestry populations, whereas locus-wide analyses suggest that the transferability might be even more extensive. Furthermore, by taking advantage of differences in haplotype structure, populations of different ancestries can help to narrow down loci, thereby pinpointing causal genes for functional follow-up. Larger-scale genetic association studies in ancestrally diverse populations will be needed for in-depth and locus-wide analyses aimed at determining, with greater confidence, the transferability of loci and allowing fine-mapping. Understanding similarities and differences in genetic susceptibility across populations of diverse ancestries might eventually contribute to a more targeted prevention and customized treatment of obesity.

Identifiers

PMID23806069
PMCPMC3706771

What Socratic 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 Socratic graph.