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Clinical proteomics data contains uniquely identifiable, personally sensitive and incidental findings

ABSTRACT: The goal of clinical proteomics is to identify, quantify, and characterize proteins in body fluids or tissue to assist diagnosis, prognosis, and treatment of patients. In this way, it is similar to more mature omics technologies, such as genomics, that are increasingly applied in biomedicine. We argue that, similar to those fields, proteomics also faces ethical issues related to the kinds of information that is inherently obtained through sample measurement, although their acquisition was not the primary purpose. Specifically, we show that individuals can be identified both by their characteristic, individual-specific protein levels and by variant peptides reporting on coding single nucleotide polymorphisms. Furthermore, it is in the nature of blood plasma proteomics profiling that it broadly reports on the health status of an individual – beyond the disease under investigation. Finally, we show that private and potentially sensitive information, such as ethnicity and pregnancy status, can increasingly be derived from proteomics data. Although this is potentially valuable not only to the individual, but also for biomedical research, it raises ethical questions similar to the incidental findings obtained through other omics technologies. We here introduce the necessity of - and argue for the desirability for - ethical and human rights-related issues to be discussed within the proteomics community. Those thoughts are more fully developed in our accompanying manuscript. Appreciation and discussion of ethical aspects of proteomic research will allow for deeper, better-informed, more diverse, and, most importantly, wiser guidelines for clinical proteomics.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma

SUBMITTER: Philipp Geyer

LAB HEAD: Philipp E. Geyer

PROVIDER: PXD021677 | Pride | 2020-12-21

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20150618_QEp1_LC7_PhGe_SA_Plate1B_1_1.raw	Raw
	Variant_OxidationMSites.txt	Txt
	Variant_evidence.txt	Txt
	Variant_parameters.txt	Txt
	Variant_peptides.txt	Txt

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Project description:This dataset results from the discovery, characterization and validation of 74 genetically variant peptides from fingermark protein. These peptides contain single amino acid polymorphisms, the result of non-synonymous SNPs. Detection of these peptide markers in fingermark proteomic datasets allows inferences to be made about the genotype status of corresponding SNP alleles. These inferences provide an individual genetic profile that may be used to calculate random match probabilities and provide information about potential genetic background. Epidermal corneocytes from five European and four South Asian subjects were isolated, processed, proteolytically digested with trypsin and 0.75 µg applied to a Q ExactiveTM hybrid quadrupole-Orbitrap mass spectrometer. The resulting datasets were used for discovery of genetically variant peptides by a “bottom-up” analysis of potential variants identified in X!Tandem datasets (thegpm.org) or by a “top-down” proteomic confirmation of non-synonymous SNP variants shown to be present in corresponding subject exome datasets. The later method resulted in discovery of a rare allele that was not observed in the 1000 Genome Project. The cumulative profiles of detected genetically variant peptides were obtained for each subject. Candidate genetically variant peptides were then validated by comparing proteomically inferred SNP alleles with matching genotypes in exome datasets. An average of 28.8 ± 4.4 genetically variant peptides were detected from each subject. Across the 9 subjects a total of 264 SNP allele inferences were made resulting in 260 true positives and 4 false positives, a false positive rate of 1.5%. Random match probabilities were calculated using the genotype frequencies of common genetically variant peptides from the matching major populations in the 1000 genome project. Estimates ranged up to a value of 1 in 1.7 x 108, with a median probability of 1 in 2.4 x 106. When probabilities were recalculated using values from other major genetic population groups African values were considerably less conservative, with resulting likelihood ratios (AFR/other populations) ranging up to 6 orders of magnitude. Conversely there was no resolution among estimates obtained from all non-African population groups, where resulting random match probabilities were within an order of magnitude. These genetically variant peptides are a starting point for the development of targeted mass spectrometry-based proteomic analyses that will increase the sensitivity of peptide detection. This project represents a novel mode of genetic information that can be obtained from fingermarks and has the potential to complement or confirm other methods of human identification including analysis of ridge patterns or touch DNA.

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Clinical proteomics data contains uniquely identifiable, personally sensitive and incidental findings

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