{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T15:54:14Z","timestamp":1791388454056,"version":"4.3.3"},"reference-count":12,"publisher":"Oxford University Press (OUP)","license":[{"start":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T00:00:00Z","timestamp":1791331200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000062","name":"NIDDK","doi-asserted-by":"publisher","award":["R01DK133177"],"award-info":[{"award-number":["R01DK133177"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000865","name":"Bill and Melinda Gates Foundation","doi-asserted-by":"publisher","award":["INV-016823"],"award-info":[{"award-number":["INV-016823"]}],"id":[{"id":"10.13039\/100000865","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000050","name":"NHLBI","doi-asserted-by":"publisher","award":["RO1HL169265"],"award-info":[{"award-number":["RO1HL169265"]}],"id":[{"id":"10.13039\/100000050","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Centers for Disease Control Foundation","award":["1085.1"],"award-info":[{"award-number":["1085.1"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Blood-based proteomics are employed in cohorts of patients with critical illness to provide biologic insights and improve diagnosis and risk stratification. Somalogic developed a multiplex aptamer-based platform (Somascan) with thousands of proteins assayed in a single plasma sample. Results are reported in 2 forms: (a) adaptive normalization by maximum likelihood (ANML), which normalizes measurements to a healthy US population and (b) a non-ANML-normalized form. It is unknown how ANML-normalization influences measurements and associations with outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We correlated ANML and non-ANML protein quantification with 9 immunoassay biomarkers measured in the same patients\u2019 blood samples from the COVID-19 Host Response and Clinical Outcomes (CHROME) cohort. We compared the association of log2 relative fluorescent units (RFUs) with hospital mortality with and without ANML-normalization using adjusted (age, sex, body mass index [BMI]) logistic regression. Results report the odds ratio per doubling of each protein\u2019s RFU and declared significance at a false discovery rate (FDR) &amp;lt;0.05.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 197 patients the average age was 54 years (\u00b116), 51% had COVID-19, 65% were male and hospital mortality was 26%. All biomarkers had equal or higher Pearson correlation between non-ANML-normalization and immunoassay data compared to ANML-normalization. Thousands of proteins changed directionality and significance for risk of mortality based on whether data was ANML-normalized, with 108 of the associations being significant in both, but opposite directionality. The paired Cohen D agreement between beta estimates was moderate (D = 0.61; 95% CI, 0.58\u20130.64).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>In this cohort of critically ill patients, ANML-normalization attenuated correlations with immunoassays and largely changed the distribution and direction of significant mortality-associated proteins compared with non-ANML-normalization.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/jalm\/jfag159","type":"journal-article","created":{"date-parts":[[2026,9,15]],"date-time":"2026-09-15T12:04:36Z","timestamp":1789473876000},"source":"Crossref","is-referenced-by-count":0,"title":["Multiplexed Aptamer-Based Proteomic Data Normalization (Adaptive Normalization by Maximum Likelihood) Significantly Influences Results in Critically Ill Patients"],"prefix":"10.1093","author":[{"given":"Ian B","family":"Stanaway","sequence":"first","affiliation":[{"name":"Division of Nephrology, Kidney Research Institute, University of Washington , Seattle, WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Neha A","family":"Sathe","sequence":"additional","affiliation":[{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington , Seattle WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"F Linzee","family":"Mabrey","sequence":"additional","affiliation":[{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington , Seattle WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth","family":"Kiernan","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Kidney Research Institute, University of Washington , Seattle, WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mark M","family":"Wurfel","sequence":"additional","affiliation":[{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington , Seattle WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laura E","family":"Evans","sequence":"additional","affiliation":[{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington , Seattle WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Eric D","family":"Morrell","sequence":"additional","affiliation":[{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington , Seattle WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pavan K","family":"Bhatraju","sequence":"additional","affiliation":[{"name":"Division of Nephrology, Kidney Research Institute, University of Washington , Seattle, WA ,","place":["United States"]},{"name":"Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington , Seattle WA ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2026,10,7]]},"reference":[{"key":"2026100711234723500_jfag159-B1","article-title":"Longitudinal proteomic analysis of severe COVID-19 reveals survival-associated signatures, tissue-specific cell death, and cell-cell interactions","volume":"2","author":"Filbin","year":"2021","journal-title":"Cell Rep Med"},{"key":"2026100711234723500_jfag159-B2","doi-asserted-by":"crossref","first-page":"744","DOI":"10.1038\/s41467-024-44986-w","article-title":"Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients","volume":"15","author":"Duijvelaar","year":"2024","journal-title":"Nat 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study","volume":"25","author":"Bhatraju","year":"2021","journal-title":"Crit Care"},{"key":"2026100711234723500_jfag159-B9","doi-asserted-by":"crossref","first-page":"L14","DOI":"10.1152\/ajplung.00049.2022","article-title":"Chemokines, soluble PD-L1, and immune cell hyporesponsiveness are distinct features of SARS-CoV-2 critical illness","volume":"323","author":"Morrell","year":"2022","journal-title":"Am J Physiol Lung Cell Mol Physiol"},{"key":"2026100711234723500_jfag159-B10","doi-asserted-by":"crossref","first-page":"4771","DOI":"10.1021\/acs.jproteome.4c00411","article-title":"Crossing the halfway point: aptamer-based, highly multiplexed assay for the assessment of the proteome","volume":"23","author":"Kraemer","year":"2024","journal-title":"J Proteome Res"},{"key":"2026100711234723500_jfag159-B11","doi-asserted-by":"crossref","first-page":"1851","DOI":"10.1038\/s41591-019-0665-2","article-title":"Plasma protein patterns as comprehensive indicators of 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