Evidence map›Paper›PMID 39884281›Full record

ReviewAmerican journal of human genetics2025

Experience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories.

Kathryn E Hatchell, Sarah R Poll, Emily M Russell, Trevor J Williams, Rachel E Ellsworth, Flavia M Facio, Sienna Aguilar, Edward D Esplin, Alice B Popejoy, Robert L Nussbaum and 1 more

Abstract readReview
In one paragraph

Review in American journal of human genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
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

11 authors.

Kathryn E HatchellLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA. Electronic address: khatchell@illumina.com.
Sarah R PollLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Emily M RussellLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Trevor J WilliamsLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Rachel E EllsworthLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Flavia M FacioLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Sienna AguilarLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Edward D EsplinLabcorp Genetics, Inc. (formerly Invitae Corp.), San Francisco, CA, USA.
Alice B PopejoyDepartment of Public Health Sciences (Epidemiology Division), University of California Davis School of Medicine, Davis, CA, USA; UCDavis Health Comprehensive Cancer Center, University of California Davis Medical Center, Sacramento, CA, USA.
Robert L NussbaumDepartment of Pediatrics, University of California, San Francisco, San Francisco, CA, USA.
Swaroop AradhyaDepartment of Pathology, Stanford University School of Medicine, Stanford, CA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings. This perspective piece is based on a decade of experience in a clinical genomics laboratory and provides insight into the relevance of conventional and ancestry-based population descriptors for clinical genetic testing, reporting, and clinical research on aggregated data. As clinicians, laboratory geneticists, genetic counselors, and researchers, we describe real-world experiences collecting conventional population descriptors in the course of clinical genetic testing and expose challenges in ensuring clarity and consistency in the use of population descriptors. Current practices in clinical genomics laboratories that are influenced by population descriptors are identified and discussed through case examples. In relation to this, we describe specific types of clinical research projects in which population descriptors were used and helped derive useful insights related to practicing and improving genomic medicine.

Indexed as

Genetic TestingGenomicsLaboratories, ClinicalRacial GroupsEthnicityHumansancestryclinical laboratorygenetic testingpopulation descriptorsrace/ethnicity

Identifiers

PMID39884281
PMCPMC11947177

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.