Evidence map›Paper›PMID 28662067›Full record

ArticlePloS one2017

Sharing extended summary data from contemporary genetics studies is unlikely to threaten subject privacy.

Silviu-Alin Bacanu

Abstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. The new genetics of intelligence.Nature reviews. Genetics · 2018
    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

1 author.

Silviu-Alin BacanuDepartment of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, Virginia, United States of America.ORCID http://orcid.org/0000-0002-4364-1583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundStarting from a forensic problem, Homer et al. showed that it was possible to detect if an individual contributes only 0.5% of the DNA in a pool. The finding was extended to prove the possibility of detecting whether a subject participated in a small homogeneous GWAS. We denote this as the detection of a subject belonging to a certain cohort (SBCC). Subsequently, Visscher and Hill showed that the power to detect SBCC signal for an ethnically homogeneous cohort depends roughly on the ratio of the number of independent markers and total sample size. However, it is not clear if the same holds for more ethnically diverse cohorts. Later, Masca et al. propose running as SBCC test a regression of departure from assumed population frequency of i) subject genotype on ii) cohort of interest frequency. They use simulations to show that the approach has better SBCC detection power than the original Homer method but is impeded by population stratification. APPROACH: To investigate the possibility of SBCC detection in multi-ethnic cohorts, we generalize the Masca et al. approach by theoretically deriving the correlation between a subject genotype and the cohort reference allele frequencies (RAFs) for stratified cohorts. Based on the derived formula, we theoretically show that, due to background stratification noise, SBCC detection is unlikely even for mildly stratified cohorts of size greater than around a thousand subjects. Thus, for the vast majority of contemporary cohorts, the fear of compromising privacy via SBCC detection is unfounded.

Indexed as

Information DisseminationPrivacyCohort StudiesGenotypeHumans

Identifiers

PMID28662067
PMCPMC5491025

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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.