Dataset for "Blood integrin and cytokine producing T cells are associated with stage and genetic risk score in age-related macular degeneration"

DOI

This dataset contains flow cytometry data from 5 panels of flow cytometry measurements on peripheral blood mononuclear cells from AMD patients and controls. The FlowJo gating analysis generated frequency tables of cell populations for each panel. Additionally, the dataset includes genetic risk scores (GRS-52) for all samples, along with the allele scores for each of the 52 single nucleotide polymorphisms (SNPs) associated with AMD.

Information about the data:

The dataset contains flow cytometry data from five different panels:

Conventional dendritic cells (cDC) panel Mononuclear myeloid (DCm) panel T cell general (T) panel - includes extracellular marker staining T cell skewing (Tskew) panel - includes both extracellular and intracellular marker staining B cell (B) panel

The dataset contains 111 samples measured across two batches:

Batch 1 (March 2021): Discovery cohort Batch 2 (November 2021): Replication cohort

Each batch was divided into 14 experimental days, with 5-10 samples measured per experiment. As a quality control measure, PBMC aliquots from internal controls were included in each experiment to monitor inter-experiment variability.

Sample Breakdown:

Controls (noAMD): 39 samples, labeled noAMD01 to noAMD39. Early / Intermediate AMD (eAMD): 21 samples, labeled eAMD01 to eAMD21. Late AMD (lAMD): 38 samples, labeled lAMD01 to lAMD39 (lAMD13 was omitted, because something went wrong during FCM measurements) Internal Control Batch 1 (ICd): 6 samples, aliquots from control patient noAMD12, with sample IDs noAMD12_ICd01 to noAMD12_ICd06. Internal Control Batch 2 (ICr): 8 samples, aliquots from a buffy coat, with sample IDs ICr01 to ICr08.

Information about the uploaded dataset files: A complete overview of all data files are described in README. Below some of the important files are highlighted.

Go the Files tab and click on Change view to Tree, which will reveal that the uploaded dataset consists of two parts:

The FlowJo folder which contains all original files for the FlowJo analysis The R_project folder which contains the whole R project for data analysis.

The FlowJo folder:

Data_fcs folder containing 14 zip files with raw FCS files measured on 14 different experiment days. WSP.zip in the Gating folder containing the Workspace (wsp) files for FlowJo analysis. GatingStrategy.zip in the Gating folder containing the gating tree strategy used in the wsp files for each panel.

The R_project folder:

FlowJoTables folder in the data folder containing frequency tables of cell populations for each panel (B, cDC, DCm, Tskew, T) extracted from FlowJo gating GRS table in the data folder containing GRS-52 for all samples, along with the allele scores for each of the 52 SNPs associated with AMD clinical data table in the metadata folder containing clinical information for all samples, including both patients and controls facs111_md table in the metadata folder containing clinical data for all samples measured in FCM, including patients, controls, and internal controls facs534_md table in the metadata folder containing file directories for all FCM-measured samples, along with some clinical information, including data for patients, controls, and internal controls paper_analysis.html is the data analysis script using the data and metadata resulting in all figures and tables for the paper (or see paper_analysis.Rmd)
prep_stat table in the analysis folder containing combined clinical data, GRS data, and frequency tables of live cell populations for each panel (B, cDC, DCm, Tskew, T) extracted from FlowJo gating

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R, 4.3.2

FlowJo Software, v10.8.1

Age-related macular degeneration (AMD) remains a leading cause of vision loss in the geriatric population. There are age-related changes in peripheral blood leukocyte composition, but their significance for AMD remains unclear. We aimed to determine changes in immune cell populations in blood of AMD patients. A standardized 31 parameter flow cytometry analysis was conducted on peripheral blood mononuclear cells from 59 patients with early and advanced AMD and 39 controls without AMD older than 65 years. Fundus photography and optical coherence tomography were used to classify disease stages and a custom genotype array was used to compute an AMD genetic risk score based on 52 AMD disease risk variants (GRS-52). A generalized linear regression model corrected for age, sex, and smoking status revealed that AMD patients showed decreased frequencies of CD4-positive T helper cell population expressing Integrin Alpha E (CD103) (Padj = 0.019). We further noted that early AMD was characterized by increased interleukin-4 (IL-4)-producing CD4+ T helper cells (Padj = 0.013; <0.001), as well as IL-4-producing cytotoxic CD8+ T cells (Padj = 0.016; <0.001). Reclassification of samples based on the GRS-52 revealed that IL-17-producing T cells decreased incrementally across GRS-52 categories. In AMD, alterations in peripheral blood leukocyte populations are associated with genetic risk score and disease stage and include specifically IL-4 and IL-17A cytokine-producing and CD103 integrin expressing T cell populations.

Identifier
DOI https://doi.org/10.34894/JRCGZD
Related Identifier IsCitedBy https://doi.org/10.2139/ssrn.4821992
Metadata Access https://dataverse.nl/oai?verb=GetRecord&metadataPrefix=oai_datacite&identifier=doi:10.34894/JRCGZD
Provenance
Creator Rijken, Rianne ORCID logo; Pameijer, Els M.; Gerritsen, Bram; Hiddingh, Sanne; Stehouwer, Marilette; de Boer, Joke H.; van Leeuwen, Redmer; Kuiper, Jonas
Publisher DataverseNL
Contributor Rijken, Rianne; DHS Datamanagement; Kuiper, Jonas
Publication Year 2024
Rights CC0 1.0; info:eu-repo/semantics/openAccess; http://creativecommons.org/publicdomain/zero/1.0
OpenAccess true
Contact Rijken, Rianne (UMC Utrecht); DHS Datamanagement (UMC Utrecht); Kuiper, Jonas (UMC Utrecht)
Representation
Resource Type Dataset
Format application/zip; text/csv; application/gzip; text/html; text/x-r-notebook
Size 980080468; 917635436; 1640753228; 1022346160; 892370578; 1353618315; 888226373; 893361893; 944311416; 664817380; 598964463; 1296757177; 1035088711; 1335420518; 53437; 87298; 76914; 8880; 33438; 11826; 1984; 131754; 7021; 2437981; 173819; 19419; 6778; 15246939; 34273; 10679156; 68380; 30176; 3569; 4836; 73481; 128354; 8539970
Version 1.0
Discipline Life Sciences; Medicine