Evidence map›Paper›PMID 28149326›Full record

ArticleEpigenetics & chromatin2017

Genome-wide methylation data mirror ancestry information.

Elior Rahmani, Liat Shenhav, Regev Schweiger, Paul Yousefi, Karen Huen, Brenda Eskenazi, Celeste Eng, Scott Huntsman, Donglei Hu, Joshua Galanter and 10 more

Abstract read
In one paragraph

Article in Epigenetics & chromatin, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 75 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
75citing papers in PubMed, 2 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

75 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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  14. Estimating population structure using epigenome-wide methylation data.medRxiv : the preprint server for health sciences · 2025
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15 more citing papers are in PubMed but not listed here.

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

20 authors.

Elior RahmaniBlavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.ORCID 0000-0002-9017-2070
Liat ShenhavDepartment of Statistics, Tel Aviv University, Tel Aviv, Israel.
Regev SchweigerBlavatnik School of Computer Science, Tel Aviv University, Tel Aviv, Israel.
Paul YousefiCenter for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA.
Karen HuenCenter for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA.
Brenda EskenaziCenter for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA.
Celeste EngDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Scott HuntsmanDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Donglei HuDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Joshua GalanterDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Sam S OhDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Melanie WaldenbergerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.
Konstantin StrauchInstitute of Genetic Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.
Harald GrallertResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.
Thomas MeitingerInstitute of Human Genetics, Helmholtz Zentrum München, Munich, Germany.
Christian GiegerResearch Unit of Molecular Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, Neuherberg, Germany.
Nina HollandCenter for Environmental Research and Children's Health (CERCH), School of Public Health, University of California Berkeley, Berkeley, CA USA.
Esteban G BurchardDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Noah ZaitlenDepartment of Medicine, University of California San Francisco, San Francisco, CA USA.
Eran HalperinDepartment of Computer Science, University of California Los Angeles, Los Angeles, CA USA.

Funding

Molecular Mechanisms of Obesity in Children Exposed to Phthalates in UteroR01ES021369 · NIEHS · UNIVERSITY OF CALIFORNIA BERKELEY · PI HOLLAND, NINA T · 2013 to 2017
$3.1M
PON Epigenetics and Neurodevelopment in ChildrenR01ES023067 · NIEHS · UNIVERSITY OF CALIFORNIA BERKELEY · PI HOLLAND, NINA T · 2014 to 2017
$1.3M
Wood Smoke and Genetic Susceptibility to Asthma in An Honduran PopulationK23HL111636 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GALANTER, JOSHUA MARK · 2012 to 2016
$832k
Richer Models of Asthma Risk: Bridging the Environment-Genetics DivideK25HL121295 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI ZAITLEN, NOAH A · 2014 to 2018
$784k
NHLBI NIH HHS K23 HL111636NHLBI NIH HHS K25 HL121295NIEHS NIH HHS R01 ES021369NIEHS NIH HHS R01 ES023067
6 · The paper itself

Abstract

backgroundGenetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data.

resultsWe demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with

conclusionsEPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.

Indexed as

User-Computer InterfaceAlgorithmsCpG IslandsDatabases, GeneticDNA MethylationEpigenomicsGenome, HumanGenome-Wide Association StudyGenotypeHumansInternetPolymorphism, Single NucleotidePrincipal Component AnalysisAncestryDNA methylationEpigeneticsEpigenome-wide association study (EWAS)Illumina 450KPopulation structure

Identifiers

PMID28149326
PMCPMC5267476

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Registered trials

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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.