DOI: 10.5061/dryad.931zcrjxd
title: Proteomic profiling of serum extracellular vesicles from uranium-exposed miners

description: This dataset contains quantitative proteomic data from serum-derived
 extracellular vesicles (EVs) isolated from 29 former uranium miners. Small
 and large EVs were separated by differential ultracentrifugation and
 analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS).
 The dataset includes raw and normalized protein intensities for each EV
 subtype, as well as metadata on mining tenure and age. These data were
 used to examine associations between mining tenure and the molecular
 profiles of serum-derived EVs. EV proteomics may serve as a sensitive tool
 for assessing the long-term health effects of uranium exposure.
description: # Proteomic profiling of serum extracellular vesicles from uranium-exposed
 miners Dataset DOI:
 [10.5061/dryad.931zcrjxd](https://doi.org/10.5061/dryad.931zcrjxd) ##
 Description of the data and file structure # Serum-derived EVs Proteomics
 Analysis in Uranium Miners This repository contains data and documentation
 for the proteomic analysis of serum-derived extracellular vesicles (EVs)
 from uranium miners, focusing on the relationship between mining tenure
 and EVs-derived protein expression profiles. ## 1. Project Overview This
 study investigates how uranium mining exposure affects the protein content
 of serum-derived small and large EVs. Miners were classified into **short
 tenure (ST)** and **long tenure (LT)** groups based on their mining
 history, and proteomic differences were assessed accordingly. ## 2. Source
 Files This dataset consists of 5 individual CSV files. * **File 1:**
 `Miner_Info.csv` (Participant metadata) * **File 2:**
 `small_EVs_COMPLETE.csv` (Raw protein intensities for small EVs) * **File
 3:** `small_EVs_normalized.csv` (Normalized protein intensities for small
 EVs) * **File 4:** `large_EVs_COMPLETE.csv` (Raw protein intensities for
 large EVs) * **File 5:** `large_EVs_normalized.csv` (Normalized protein
 intensities for large EVs) ## 3. Sample Metadata (File: `Miner Info.csv`)
 Contains miner-level metadata and phenotype classification used in
 downstream analysis. | Column Name | Description | | ---------------------
 | ------------------------------------------------------------- | | Sample
 ID | Unique identifier for each participant (e.g., OLC\_10002) | | Mining
 Tenure | Total years of uranium mining experience | | Tenure
 Classification | Group label based on tenure: ST (1–9 years), LT (10–40
 years) | | Age | Age in years at time of sample collection | ## 4.
 Proteomics Data Files Each file below contains quantified protein
 intensities per sample for either **small** or **large** EVs, in both raw
 and normalized formats. ### 4.1 File: `small EVs_COMPLETE.csv` * **Type:**
 Raw protein intensity * **Rows:** Each sample (by Sample ID) *
 **Columns:** Proteins (e.g., Alpha-2-macroglobulin [OS=Homo sapiens],
 etc.) ### 4.2 File: `small EVs_normalized.csv` * **Type:** Normalized
 intensities of small EV proteins * **Normalization method:** Total peptide
 amount ### 4.3 File: `large EVs_COMPLETE.csv` * **Type:** Raw protein
 intensity from large EVs ### 4.4 File: `large EVs_normalized.csv` *
 **Type:** Normalized large EV protein intensities &gt; Note: Protein names
 are annotated in UniProt format (e.g., "[OS=Homo sapiens]"). ##
 5. Data Processing Workflow ### Software and Database * **Search
 Software:** Thermo Proteome Discoverer v2.5 * **Database:** UniProt *Homo
 sapiens* (reviewed; downloaded Oct 26, 2023) ### Search Parameters *
 **Enzyme:** Trypsin (allowing 2 missed cleavages) * **Static
 Modifications:** Carbamidomethyl (C) * **Variable Modifications:**
 Oxidation (M), Acetyl (N-term) * **Precursor Tolerance:** 10 ppm *
 **Fragment Tolerance:** 0.02 Da * **FDR Threshold:** 1% ## 6.
 Quantification and Normalization * **Quantification Method:**
 Intensity-based precursor abundance * **Normalization:** Total peptide
 amount normalization for intra-sample correction ## 7. Output Summary |
 File Name | Description | | -------------------------- |
 ------------------------------------------------- | | `Miner Info.csv` |
 Sample ID and phenotype annotations (age, tenure) | | `small
 EVs_COMPLETE.csv` | Raw intensities of small EV proteins | | `small
 EVs_normalized.csv` | Normalized small EV protein data | | `large
 EVs_COMPLETE.csv` | Raw intensities of large EV proteins | | `large
 EVs_normalized.csv` | Normalized large EV protein data | ## 8. Contact For
 questions, please contact: * **Name:** Dr. Katherine Zychowski *
 **Affiliation:** University of New Mexico * **Email:**
 [kzychowski@salud.unm.edu](mailto:kzychowski@salud.unm.edu) ## 9. Human
 Subjects Data All human subjects' data included in this dataset have
 been de-identified in compliance with applicable legal and ethical
 standards. Explicit informed consent was obtained from all study
 participants for the public sharing of their de-identified data.
 Participant metadata includes only non-identifiable variables such as age
 (in years) and mining tenure (in years). The 'Race/Ethnicity'
 and 'Smoking History' columns were removed from the dataset to
 comply with Dryad's data anonymization policy. ## 10. Files and
 Variables ### File 1: `Miner_Info.csv` * **Description:** Participant
 metadata including anonymized demographic information (age, mining tenure)
 and tenure classification. * **Variables:** Sample ID, Mining Tenure,
 Tenure Classification, Age. ### File 2: `small_EVs_COMPLETE.csv` *
 **Description:** Raw, un-normalized protein intensities from small
 extracellular vesicles (S-EVs) for each participant. * **Variables:**
 Sample ID, Protein abundances by UniProt accession. ### File 3:
 `small_EVs_normalized.csv` * **Description:** Normalized protein
 intensities from small extracellular vesicles (S-EVs) for each
 participant. * **Variables:** Sample ID, Normalized protein abundances by
 UniProt accession. ### File 4: `large_EVs_COMPLETE.csv` * **Description:**
 Raw, un-normalized protein intensities from large extracellular vesicles
 (L-EVs) for each participant. * **Variables:** Sample ID, Protein
 abundances by UniProt accession. ### File 5: `large_EVs_normalized.csv` *
 **Description:** Normalized protein intensities from large extracellular
 vesicles (L-EVs) for each participant. * **Variables:** Sample ID,
 Normalized protein abundances by UniProt accession. ## Human subjects data
 All human subjects data included in this dataset have been fully
 de-identified in compliance with applicable legal and ethical standards.
 Explicit informed consent was obtained from all study participants for the
 collection, analysis, and public sharing of their de-identified data. No
 personally identifiable information (PII), including names, contact
 information, or identifiable health data, is included in the dataset.
 De-identification procedures involved removing all direct identifiers. To
 comply with Dryad's data anonymization policy and minimize the risk
 of re-identification, the 'Race/Ethnicity' and 'Smoking
 History' variables were removed from the public dataset. The
 remaining participant metadata includes only non-identifiable variables
 such as age (in years) and mining tenure (in years). All samples were
 assigned anonymized study ID codes with no link to personal identifiers.
 The dataset is compliant with Dryad’s human subjects data policy and is
 appropriate for open-access publication under the CC0 license.