Loading…
Age and gender leucocytes variances and references values generated using the standardized ONE‐Study protocol
Flow cytometry is now accepted as an ideal technology to reveal changes in immune cell composition and function. However, it is also an error‐prone and variable technology, which makes it difficult to reproduce findings across laboratories. We have recently developed a strategy to standardize whole...
Saved in:
Published in: | Cytometry. Part A 2016-06, Vol.89 (6), p.543-564 |
---|---|
Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3 |
---|---|
cites | cdi_FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3 |
container_end_page | 564 |
container_issue | 6 |
container_start_page | 543 |
container_title | Cytometry. Part A |
container_volume | 89 |
creator | Kverneland, Anders H. Streitz, Mathias Geissler, Edward Hutchinson, James Vogt, Katrin Boës, David Niemann, Nadja Pedersen, Anders Elm Schlickeiser, Stephan Sawitzki, Birgit |
description | Flow cytometry is now accepted as an ideal technology to reveal changes in immune cell composition and function. However, it is also an error‐prone and variable technology, which makes it difficult to reproduce findings across laboratories. We have recently developed a strategy to standardize whole blood flow cytometry. The performance of our protocols was challenged here by profiling samples from healthy volunteers to reveal age‐ and gender‐dependent differences and to establish a standardized reference cohort for use in clinical trials. Whole blood samples from two different cohorts were analyzed (first cohort: n = 52, second cohort: n = 46, both 20–84 years with equal gender distribution). The second cohort was run as a validation cohort by a different operator. The “ONE Study” panels were applied to analyze expression of >30 different surface markers to enumerate proportional and absolute numbers of >50 leucocyte subsets. Indeed, analysis of the first cohort revealed significant age‐dependent changes in subsets e.g. increased activated and differentiated CD4+ and CD8+ T cell subsets, acquisition of a memory phenotype for Tregs as well as decreased MDC2 and Marginal Zone B cells. Males and females showed different dynamics in age‐dependent T cell activation and differentiation, indicating faster immunosenescence in males. Importantly, although both cohorts consisted of a small sample size, our standardized approach enabled validation of age‐dependent changes with the second cohort. Thus, we have proven the utility of our strategy and generated reproducible reference ranges accounting for age‐ and gender‐dependent differences, which are crucial for a better patient monitoring and individualized therapy. © 2016 International Society for Advancement of Cytometry |
doi_str_mv | 10.1002/cyto.a.22855 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1808734927</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1808734927</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3</originalsourceid><addsrcrecordid>eNqFkb9OwzAQxi0EglLYmFFGBlocJ1fHY1WVP1JFB8rAZF2cSwlKk2InRWXiEXhGngSXAiNMd_b9_Pn0fYydhLwfci4uzLqp-9gXIgHYYZ0QQPRiFfHd316IA3bo3BPnEfBI7LMDIcM4jkF1WD2cU4BVFsypysgGJbWm9pLkghXaAivju83cUk6Wvo4rLFtf_Auy2FAWtK6o5kHzSIFrPIs2K1799fR2_PH2fte02TpY2rqpTV0esb0cS0fH37XL7i_Hs9F1bzK9uhkNJz0Tywh6hJAapVKep2mcY2QkykhwKeQgg1yJJDUCBpzyBCUlA1CQ8gQJQgUyRaKoy862uv7jZ79toxeFM1SWWFHdOh0mPJGR90b-j0qlABKQyqPnW9TY2jlviV7aYoF2rUOuN2noTRoa9VcaHj_9Vm7TBWW_8I_9Hoi3wEtR0vpPMT16mE2HW91P6nGZZw</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1799558579</pqid></control><display><type>article</type><title>Age and gender leucocytes variances and references values generated using the standardized ONE‐Study protocol</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Kverneland, Anders H. ; Streitz, Mathias ; Geissler, Edward ; Hutchinson, James ; Vogt, Katrin ; Boës, David ; Niemann, Nadja ; Pedersen, Anders Elm ; Schlickeiser, Stephan ; Sawitzki, Birgit</creator><creatorcontrib>Kverneland, Anders H. ; Streitz, Mathias ; Geissler, Edward ; Hutchinson, James ; Vogt, Katrin ; Boës, David ; Niemann, Nadja ; Pedersen, Anders Elm ; Schlickeiser, Stephan ; Sawitzki, Birgit</creatorcontrib><description>Flow cytometry is now accepted as an ideal technology to reveal changes in immune cell composition and function. However, it is also an error‐prone and variable technology, which makes it difficult to reproduce findings across laboratories. We have recently developed a strategy to standardize whole blood flow cytometry. The performance of our protocols was challenged here by profiling samples from healthy volunteers to reveal age‐ and gender‐dependent differences and to establish a standardized reference cohort for use in clinical trials. Whole blood samples from two different cohorts were analyzed (first cohort: n = 52, second cohort: n = 46, both 20–84 years with equal gender distribution). The second cohort was run as a validation cohort by a different operator. The “ONE Study” panels were applied to analyze expression of >30 different surface markers to enumerate proportional and absolute numbers of >50 leucocyte subsets. Indeed, analysis of the first cohort revealed significant age‐dependent changes in subsets e.g. increased activated and differentiated CD4+ and CD8+ T cell subsets, acquisition of a memory phenotype for Tregs as well as decreased MDC2 and Marginal Zone B cells. Males and females showed different dynamics in age‐dependent T cell activation and differentiation, indicating faster immunosenescence in males. Importantly, although both cohorts consisted of a small sample size, our standardized approach enabled validation of age‐dependent changes with the second cohort. Thus, we have proven the utility of our strategy and generated reproducible reference ranges accounting for age‐ and gender‐dependent differences, which are crucial for a better patient monitoring and individualized therapy. © 2016 International Society for Advancement of Cytometry</description><identifier>ISSN: 1552-4922</identifier><identifier>EISSN: 1552-4930</identifier><identifier>DOI: 10.1002/cyto.a.22855</identifier><identifier>PMID: 27144459</identifier><language>eng</language><publisher>United States</publisher><subject>adaptive immunity ; Adult ; Age Factors ; Aged ; Aged, 80 and over ; aging ; Antigens, CD - genetics ; Antigens, CD - immunology ; Cohort Studies ; Female ; Flow Cytometry - standards ; Healthy Volunteers ; Humans ; Immunologic Memory ; Immunophenotyping - standards ; immunosenescence ; innate immunity ; Lymphocyte Subsets - classification ; Lymphocyte Subsets - cytology ; Lymphocyte Subsets - immunology ; Male ; Middle Aged ; Reference Values ; Sex Factors ; standardization</subject><ispartof>Cytometry. Part A, 2016-06, Vol.89 (6), p.543-564</ispartof><rights>2016 International Society for Advancement of Cytometry</rights><rights>2016 International Society for Advancement of Cytometry.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3</citedby><cites>FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27144459$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kverneland, Anders H.</creatorcontrib><creatorcontrib>Streitz, Mathias</creatorcontrib><creatorcontrib>Geissler, Edward</creatorcontrib><creatorcontrib>Hutchinson, James</creatorcontrib><creatorcontrib>Vogt, Katrin</creatorcontrib><creatorcontrib>Boës, David</creatorcontrib><creatorcontrib>Niemann, Nadja</creatorcontrib><creatorcontrib>Pedersen, Anders Elm</creatorcontrib><creatorcontrib>Schlickeiser, Stephan</creatorcontrib><creatorcontrib>Sawitzki, Birgit</creatorcontrib><title>Age and gender leucocytes variances and references values generated using the standardized ONE‐Study protocol</title><title>Cytometry. Part A</title><addtitle>Cytometry A</addtitle><description>Flow cytometry is now accepted as an ideal technology to reveal changes in immune cell composition and function. However, it is also an error‐prone and variable technology, which makes it difficult to reproduce findings across laboratories. We have recently developed a strategy to standardize whole blood flow cytometry. The performance of our protocols was challenged here by profiling samples from healthy volunteers to reveal age‐ and gender‐dependent differences and to establish a standardized reference cohort for use in clinical trials. Whole blood samples from two different cohorts were analyzed (first cohort: n = 52, second cohort: n = 46, both 20–84 years with equal gender distribution). The second cohort was run as a validation cohort by a different operator. The “ONE Study” panels were applied to analyze expression of >30 different surface markers to enumerate proportional and absolute numbers of >50 leucocyte subsets. Indeed, analysis of the first cohort revealed significant age‐dependent changes in subsets e.g. increased activated and differentiated CD4+ and CD8+ T cell subsets, acquisition of a memory phenotype for Tregs as well as decreased MDC2 and Marginal Zone B cells. Males and females showed different dynamics in age‐dependent T cell activation and differentiation, indicating faster immunosenescence in males. Importantly, although both cohorts consisted of a small sample size, our standardized approach enabled validation of age‐dependent changes with the second cohort. Thus, we have proven the utility of our strategy and generated reproducible reference ranges accounting for age‐ and gender‐dependent differences, which are crucial for a better patient monitoring and individualized therapy. © 2016 International Society for Advancement of Cytometry</description><subject>adaptive immunity</subject><subject>Adult</subject><subject>Age Factors</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>aging</subject><subject>Antigens, CD - genetics</subject><subject>Antigens, CD - immunology</subject><subject>Cohort Studies</subject><subject>Female</subject><subject>Flow Cytometry - standards</subject><subject>Healthy Volunteers</subject><subject>Humans</subject><subject>Immunologic Memory</subject><subject>Immunophenotyping - standards</subject><subject>immunosenescence</subject><subject>innate immunity</subject><subject>Lymphocyte Subsets - classification</subject><subject>Lymphocyte Subsets - cytology</subject><subject>Lymphocyte Subsets - immunology</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Reference Values</subject><subject>Sex Factors</subject><subject>standardization</subject><issn>1552-4922</issn><issn>1552-4930</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><recordid>eNqFkb9OwzAQxi0EglLYmFFGBlocJ1fHY1WVP1JFB8rAZF2cSwlKk2InRWXiEXhGngSXAiNMd_b9_Pn0fYydhLwfci4uzLqp-9gXIgHYYZ0QQPRiFfHd316IA3bo3BPnEfBI7LMDIcM4jkF1WD2cU4BVFsypysgGJbWm9pLkghXaAivju83cUk6Wvo4rLFtf_Auy2FAWtK6o5kHzSIFrPIs2K1799fR2_PH2fte02TpY2rqpTV0esb0cS0fH37XL7i_Hs9F1bzK9uhkNJz0Tywh6hJAapVKep2mcY2QkykhwKeQgg1yJJDUCBpzyBCUlA1CQ8gQJQgUyRaKoy862uv7jZ79toxeFM1SWWFHdOh0mPJGR90b-j0qlABKQyqPnW9TY2jlviV7aYoF2rUOuN2noTRoa9VcaHj_9Vm7TBWW_8I_9Hoi3wEtR0vpPMT16mE2HW91P6nGZZw</recordid><startdate>201606</startdate><enddate>201606</enddate><creator>Kverneland, Anders H.</creator><creator>Streitz, Mathias</creator><creator>Geissler, Edward</creator><creator>Hutchinson, James</creator><creator>Vogt, Katrin</creator><creator>Boës, David</creator><creator>Niemann, Nadja</creator><creator>Pedersen, Anders Elm</creator><creator>Schlickeiser, Stephan</creator><creator>Sawitzki, Birgit</creator><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>P64</scope></search><sort><creationdate>201606</creationdate><title>Age and gender leucocytes variances and references values generated using the standardized ONE‐Study protocol</title><author>Kverneland, Anders H. ; Streitz, Mathias ; Geissler, Edward ; Hutchinson, James ; Vogt, Katrin ; Boës, David ; Niemann, Nadja ; Pedersen, Anders Elm ; Schlickeiser, Stephan ; Sawitzki, Birgit</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>adaptive immunity</topic><topic>Adult</topic><topic>Age Factors</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>aging</topic><topic>Antigens, CD - genetics</topic><topic>Antigens, CD - immunology</topic><topic>Cohort Studies</topic><topic>Female</topic><topic>Flow Cytometry - standards</topic><topic>Healthy Volunteers</topic><topic>Humans</topic><topic>Immunologic Memory</topic><topic>Immunophenotyping - standards</topic><topic>immunosenescence</topic><topic>innate immunity</topic><topic>Lymphocyte Subsets - classification</topic><topic>Lymphocyte Subsets - cytology</topic><topic>Lymphocyte Subsets - immunology</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Reference Values</topic><topic>Sex Factors</topic><topic>standardization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kverneland, Anders H.</creatorcontrib><creatorcontrib>Streitz, Mathias</creatorcontrib><creatorcontrib>Geissler, Edward</creatorcontrib><creatorcontrib>Hutchinson, James</creatorcontrib><creatorcontrib>Vogt, Katrin</creatorcontrib><creatorcontrib>Boës, David</creatorcontrib><creatorcontrib>Niemann, Nadja</creatorcontrib><creatorcontrib>Pedersen, Anders Elm</creatorcontrib><creatorcontrib>Schlickeiser, Stephan</creatorcontrib><creatorcontrib>Sawitzki, Birgit</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Cytometry. Part A</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kverneland, Anders H.</au><au>Streitz, Mathias</au><au>Geissler, Edward</au><au>Hutchinson, James</au><au>Vogt, Katrin</au><au>Boës, David</au><au>Niemann, Nadja</au><au>Pedersen, Anders Elm</au><au>Schlickeiser, Stephan</au><au>Sawitzki, Birgit</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Age and gender leucocytes variances and references values generated using the standardized ONE‐Study protocol</atitle><jtitle>Cytometry. Part A</jtitle><addtitle>Cytometry A</addtitle><date>2016-06</date><risdate>2016</risdate><volume>89</volume><issue>6</issue><spage>543</spage><epage>564</epage><pages>543-564</pages><issn>1552-4922</issn><eissn>1552-4930</eissn><abstract>Flow cytometry is now accepted as an ideal technology to reveal changes in immune cell composition and function. However, it is also an error‐prone and variable technology, which makes it difficult to reproduce findings across laboratories. We have recently developed a strategy to standardize whole blood flow cytometry. The performance of our protocols was challenged here by profiling samples from healthy volunteers to reveal age‐ and gender‐dependent differences and to establish a standardized reference cohort for use in clinical trials. Whole blood samples from two different cohorts were analyzed (first cohort: n = 52, second cohort: n = 46, both 20–84 years with equal gender distribution). The second cohort was run as a validation cohort by a different operator. The “ONE Study” panels were applied to analyze expression of >30 different surface markers to enumerate proportional and absolute numbers of >50 leucocyte subsets. Indeed, analysis of the first cohort revealed significant age‐dependent changes in subsets e.g. increased activated and differentiated CD4+ and CD8+ T cell subsets, acquisition of a memory phenotype for Tregs as well as decreased MDC2 and Marginal Zone B cells. Males and females showed different dynamics in age‐dependent T cell activation and differentiation, indicating faster immunosenescence in males. Importantly, although both cohorts consisted of a small sample size, our standardized approach enabled validation of age‐dependent changes with the second cohort. Thus, we have proven the utility of our strategy and generated reproducible reference ranges accounting for age‐ and gender‐dependent differences, which are crucial for a better patient monitoring and individualized therapy. © 2016 International Society for Advancement of Cytometry</abstract><cop>United States</cop><pmid>27144459</pmid><doi>10.1002/cyto.a.22855</doi><tpages>22</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1552-4922 |
ispartof | Cytometry. Part A, 2016-06, Vol.89 (6), p.543-564 |
issn | 1552-4922 1552-4930 |
language | eng |
recordid | cdi_proquest_miscellaneous_1808734927 |
source | Wiley-Blackwell Read & Publish Collection |
subjects | adaptive immunity Adult Age Factors Aged Aged, 80 and over aging Antigens, CD - genetics Antigens, CD - immunology Cohort Studies Female Flow Cytometry - standards Healthy Volunteers Humans Immunologic Memory Immunophenotyping - standards immunosenescence innate immunity Lymphocyte Subsets - classification Lymphocyte Subsets - cytology Lymphocyte Subsets - immunology Male Middle Aged Reference Values Sex Factors standardization |
title | Age and gender leucocytes variances and references values generated using the standardized ONE‐Study protocol |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-19T08%3A06%3A40IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Age%20and%20gender%20leucocytes%20variances%20and%20references%20values%20generated%20using%20the%20standardized%20ONE%E2%80%90Study%20protocol&rft.jtitle=Cytometry.%20Part%20A&rft.au=Kverneland,%20Anders%20H.&rft.date=2016-06&rft.volume=89&rft.issue=6&rft.spage=543&rft.epage=564&rft.pages=543-564&rft.issn=1552-4922&rft.eissn=1552-4930&rft_id=info:doi/10.1002/cyto.a.22855&rft_dat=%3Cproquest_cross%3E1808734927%3C/proquest_cross%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c4735-ea5bc99b0fbb4fa3c7a73207276d5f928bc2560ef8a7e86595b08ae51957baee3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=1799558579&rft_id=info:pmid/27144459&rfr_iscdi=true |