ArticleAMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science2016
On the privacy risks of sharing clinical proteomics data.
Article in AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ethical Principles, Constraints and Opportunities in Clinical Proteomics.Molecular & cellular proteomics : MCP · 2021Pooled it
- Review
- Assessing Privacy Vulnerabilities in Genetic Data Sets: Scoping Review.JMIR bioinformatics and biotechnology · 2024Article
- Large scale proteomic studies create novel privacy considerations.Scientific reports · 2023Article
- Identifying individuals using proteomics: are we there yet?Frontiers in molecular biosciences · 2022Review
- Data Management of Sensitive Human Proteomics Data: Current Practices, Recommendations, and Perspectives for the Future.Molecular & cellular proteomics : MCP · 2021Article
- Beyond Genes: Re-Identifiability of Proteomic Data and Its Implications for Personalized Medicine.Genes · 2019Review
- A Golden Age for Working with Public Proteomics Data.Trends in biochemical sciences · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Although the privacy issues in human genomic studies are well known, the privacy risks in clinical proteomic data have not been thoroughly studied. As a proof of concept, we reported a comprehensive analysis of the privacy risks in clinical proteomic data. It showed that a small number of peptides carrying the minor alleles (referred to as the minor allelic peptides) at non-synonymous single nucleotide polymorphism (nsSNP) sites can be identified in typical clinical proteomic datasets acquired from the blood/serum samples of individual patient, from which the patient can be identified with high confidence. Our results suggested the presence of significant privacy risks in raw clinical proteomic data. However, these risks can be mitigated by a straightforward pre-processing step of the raw data that removing a very small fraction (0.1%, 7.14 out of 7,504 spectra on average) of MS/MS spectra identified as the minor allelic peptides, which has little or no impact on the subsequent analysis (and re-use) of these datasets.
Identifiers
27595046PMC5009298What OpenQuestion holds
Registered trials
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.