Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight
Human tear fluid contains numerous compounds, which are present in highly variable amounts owing to the dynamic and multipurpose functions of tears. A better understanding of the level and sources of variance is essential for determining the functions of the different tear components and the limitat...
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MDPI AG
2024-01-01
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Online Access: | https://www.mdpi.com/1422-0067/25/3/1559 |
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author | Bella Bruszel Edit Tóth-Molnár Tamás Janáky Zoltán Szabó |
author_facet | Bella Bruszel Edit Tóth-Molnár Tamás Janáky Zoltán Szabó |
author_sort | Bella Bruszel |
collection | DOAJ |
description | Human tear fluid contains numerous compounds, which are present in highly variable amounts owing to the dynamic and multipurpose functions of tears. A better understanding of the level and sources of variance is essential for determining the functions of the different tear components and the limitations of tear samples as a potential biomarker source. In this study, a quantitative proteomic method was used to analyze variations in the tear protein profiles of healthy volunteers. High day-to-day and inter-eye personal variances were observed in the tear volumes, protein content, and composition of the tear samples. Several normalization and outlier exclusion approaches were evaluated to decrease variances. Despite the intrapersonal variances, statistically significant differences and cluster analysis revealed that proteome profile and immunoglobulin composition of tear fluid present personal characteristics. Using correlation analysis, we could identify several correlating protein clusters, mainly related to the source of the proteins. Our study is the first attempt to achieve more insight into the biochemical background of human tears by statistical evaluation of the experimentally observed dynamic behavior of the tear proteome. As a pilot study for determination of personal protein profiles of the tear fluids of individual patients, it contributes to the application of this noninvasively collectible body fluid in personal medicine. |
first_indexed | 2024-03-08T03:56:03Z |
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issn | 1661-6596 1422-0067 |
language | English |
last_indexed | 2024-03-08T03:56:03Z |
publishDate | 2024-01-01 |
publisher | MDPI AG |
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series | International Journal of Molecular Sciences |
spelling | doaj.art-da8ea27009e349dab810bc0b636cf4472024-02-09T15:13:43ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672024-01-01253155910.3390/ijms25031559Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological InsightBella Bruszel0Edit Tóth-Molnár1Tamás Janáky2Zoltán Szabó3Department of Medical Chemistry, Albert Szent-Györgyi Medical School, University of Szeged, Dóm tér 8, H-6720 Szeged, HungaryDepartment of Ophtalmology, Albert Szent-Györgyi Health Centre, University of Szeged, Korányi Fasor 10-11, H-6720 Szeged, HungaryDepartment of Medical Chemistry, Albert Szent-Györgyi Medical School, University of Szeged, Dóm tér 8, H-6720 Szeged, HungaryDepartment of Medical Chemistry, Albert Szent-Györgyi Medical School, University of Szeged, Dóm tér 8, H-6720 Szeged, HungaryHuman tear fluid contains numerous compounds, which are present in highly variable amounts owing to the dynamic and multipurpose functions of tears. A better understanding of the level and sources of variance is essential for determining the functions of the different tear components and the limitations of tear samples as a potential biomarker source. In this study, a quantitative proteomic method was used to analyze variations in the tear protein profiles of healthy volunteers. High day-to-day and inter-eye personal variances were observed in the tear volumes, protein content, and composition of the tear samples. Several normalization and outlier exclusion approaches were evaluated to decrease variances. Despite the intrapersonal variances, statistically significant differences and cluster analysis revealed that proteome profile and immunoglobulin composition of tear fluid present personal characteristics. Using correlation analysis, we could identify several correlating protein clusters, mainly related to the source of the proteins. Our study is the first attempt to achieve more insight into the biochemical background of human tears by statistical evaluation of the experimentally observed dynamic behavior of the tear proteome. As a pilot study for determination of personal protein profiles of the tear fluids of individual patients, it contributes to the application of this noninvasively collectible body fluid in personal medicine.https://www.mdpi.com/1422-0067/25/3/1559human tearsdata independent analysisquantitative analysiscorrelation analysisnormalizationoutlier detection |
spellingShingle | Bella Bruszel Edit Tóth-Molnár Tamás Janáky Zoltán Szabó Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight International Journal of Molecular Sciences human tears data independent analysis quantitative analysis correlation analysis normalization outlier detection |
title | Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight |
title_full | Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight |
title_fullStr | Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight |
title_full_unstemmed | Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight |
title_short | Sources of Variance in Human Tear Proteomic Samples: Statistical Evaluation, Quality Control, Normalization, and Biological Insight |
title_sort | sources of variance in human tear proteomic samples statistical evaluation quality control normalization and biological insight |
topic | human tears data independent analysis quantitative analysis correlation analysis normalization outlier detection |
url | https://www.mdpi.com/1422-0067/25/3/1559 |
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