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...

Full description

Saved in:
Bibliographic Details
Published in:Cytometry. Part A 2016-06, Vol.89 (6), p.543-564
Main Authors: Kverneland, Anders H., Streitz, Mathias, Geissler, Edward, Hutchinson, James, Vogt, Katrin, Boës, David, Niemann, Nadja, Pedersen, Anders Elm, Schlickeiser, Stephan, Sawitzki, Birgit
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 &amp; 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 &gt;30 different surface markers to enumerate proportional and absolute numbers of &gt;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 &gt;30 different surface markers to enumerate proportional and absolute numbers of &gt;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 &gt;30 different surface markers to enumerate proportional and absolute numbers of &gt;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