Evidence map›Paper›PMID 25563503›Full record

ReviewHuman genomics2015

Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities.

Tesfaye B Mersha, Tilahun Abebe

Erratum issuedOpen access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Human genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 238 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
238citing papers in PubMed, 7 pooled it
24.7field-weighted citation impact, top 1% 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

238 citing papers in PubMed, 7 syntheses or guidelines pooled it, 457 citations in OpenAlex.

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  11. The Landscape of Genomic and Socioeconomic Variables in Patients with Colorectal Cancer Based on Genetic Ancestry.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026
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178 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 2 institutions in 1 country.

Tesfaye B MershaDivision of Asthma Research, Department of Pediatrics, Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA. tesfaye.mersha@cchmc.org.
Tilahun AbebeDepartment of Biology, University of Northern Iowa, Cedar Falls, IA, USA. tilahun.abebe@uni.edu.
University of Cincinnati · USUniversity of Northern Iowa · US

Funding

Admixture mapping in African American Asthmatic ChildrenK01HL103165 · NHLBI · CINCINNATI CHILDRENS HOSP MED CTR · PI MERSHA, TESFAYE B. · 2010 to 2014
$648k
NHLBI NIH HHS K01 HL103165NHLBI NIH HHS K01HL103165
6 · The paper itself

Abstract

This review explores the limitations of self-reported race, ethnicity, and genetic ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and ancestry. Although race and ethnicity are related, race refers to a person's physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic ancestry inferred using ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European ancestry. Genetic analysis of individual ancestry shows that some self-identified African Americans have up to 99% of European ancestry, whereas some self-identified European Americans have substantial admixture from African ancestry. Similarly, African ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using "ancestry" (or biogeographical ancestry) to describe actual genetic variation, "race" to describe health disparity in societies characterized by racial categories, and "ethnicity" to describe traditions, lifestyle, diet, and values. We also suggest using ancestry informative markers for precise characterization of individuals' biological ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals.

Indexed as

Biomedical ResearchGenomicsEthnicityGenetic MarkersHumansPhenotypeRacial GroupsSelf ReportGenetic Markers

Identifiers

PMID25563503
PMCPMC4307746
OpenAlexW2113129492

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.