Scott P Oltman, Elizabeth E Rogers, Rebecca J Baer, Ribka Amsalu, Gretchen Bandoli, Christina D Chambers, Hyunkeun Cho, John M Dagle, Kayla L Karvonen, Stephen F Kingsmore, Safyer McKenzie-Sampson, Allison Momany, Eric Ontiveros, Liana D Protopsaltis, Larry Rand, Erica Sanford Kobayashi, Martina A Steurer, Kelli K Ryckman, Laura L Jelliffe-Pawlowski
{"title":"Early Newborn Metabolic Patterning and Sudden Infant Death Syndrome.","authors":"Scott P Oltman, Elizabeth E Rogers, Rebecca J Baer, Ribka Amsalu, Gretchen Bandoli, Christina D Chambers, Hyunkeun Cho, John M Dagle, Kayla L Karvonen, Stephen F Kingsmore, Safyer McKenzie-Sampson, Allison Momany, Eric Ontiveros, Liana D Protopsaltis, Larry Rand, Erica Sanford Kobayashi, Martina A Steurer, Kelli K Ryckman, Laura L Jelliffe-Pawlowski","doi":"10.1001/jamapediatrics.2024.3033","DOIUrl":null,"url":null,"abstract":"<p><strong>Importance: </strong>Sudden infant death syndrome (SIDS) is a major cause of infant death in the US. Previous research suggests that inborn errors of metabolism may contribute to SIDS, yet the relationship between SIDS and biomarkers of metabolism remains unclear.</p><p><strong>Objective: </strong>To evaluate and model the association between routinely measured newborn metabolic markers and SIDS in combination with established risk factors for SIDS.</p><p><strong>Design, setting, and participants: </strong>This was a case-control study nested within a retrospective cohort using data from the California Office of Statewide Health Planning and Development and the California Department of Public Health. The study population included infants born in California between 2005 and 2011 with full metabolic data collected as part of routine newborn screening (NBS). SIDS cases were matched to controls at a ratio of 1:4 by gestational age and birth weight z score. Matched data were split into training (2/3) and testing (1/3) subsets. Data were analyzed from January 2005 to December 2011.</p><p><strong>Exposures: </strong>Metabolites measured by NBS and established risk factors for SIDS.</p><p><strong>Main outcomes and measures: </strong>The primary outcome was SIDS. Logistic regression was used to evaluate the association between metabolic markers combined with known risk factors and SIDS.</p><p><strong>Results: </strong>Of 2 276 578 eligible infants, 354 SIDS (0.016%) cases (mean [SD] gestational age, 38.3 [2.3] weeks; 220 male [62.1%]) and 1416 controls (mean [SD] gestational age, 38.3 [2.3] weeks; 723 male [51.1%]) were identified. In multivariable analysis, 14 NBS metabolites were significantly associated with SIDS in a univariate analysis: 17-hydroxyprogesterone, alanine, methionine, proline, tyrosine, valine, free carnitine, acetyl-L-carnitine, malonyl carnitine, glutarylcarnitine, lauroyl-L-carnitine, dodecenoylcarnitine, 3-hydroxytetradecanoylcarnitine, and linoleoylcarnitine. The area under the receiver operating characteristic curve for a 14-marker SIDS model, which included 8 metabolites, was 0.75 (95% CI, 0.72-0.79) in the training set and was 0.70 (95% CI, 0.65-0.76) in the test set. Of 32 infants in the test set with model-predicted probability greater than 0.5, a total of 20 (62.5%) had SIDS. These infants had 14.4 times the odds (95% CI, 6.0-34.5) of having SIDS compared with those with a model-predicted probability less than 0.1.</p><p><strong>Conclusions and relevance: </strong>Results from this case-control study showed an association between aberrant metabolic analytes at birth and SIDS. These findings suggest that we may be able to identify infants at increased risk for SIDS soon after birth, which could inform further mechanistic research and clinical efforts focused on monitoring and prevention.</p>","PeriodicalId":14683,"journal":{"name":"JAMA Pediatrics","volume":null,"pages":null},"PeriodicalIF":24.7000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11385317/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JAMA Pediatrics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1001/jamapediatrics.2024.3033","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PEDIATRICS","Score":null,"Total":0}
引用次数: 0
Abstract
Importance: Sudden infant death syndrome (SIDS) is a major cause of infant death in the US. Previous research suggests that inborn errors of metabolism may contribute to SIDS, yet the relationship between SIDS and biomarkers of metabolism remains unclear.
Objective: To evaluate and model the association between routinely measured newborn metabolic markers and SIDS in combination with established risk factors for SIDS.
Design, setting, and participants: This was a case-control study nested within a retrospective cohort using data from the California Office of Statewide Health Planning and Development and the California Department of Public Health. The study population included infants born in California between 2005 and 2011 with full metabolic data collected as part of routine newborn screening (NBS). SIDS cases were matched to controls at a ratio of 1:4 by gestational age and birth weight z score. Matched data were split into training (2/3) and testing (1/3) subsets. Data were analyzed from January 2005 to December 2011.
Exposures: Metabolites measured by NBS and established risk factors for SIDS.
Main outcomes and measures: The primary outcome was SIDS. Logistic regression was used to evaluate the association between metabolic markers combined with known risk factors and SIDS.
Results: Of 2 276 578 eligible infants, 354 SIDS (0.016%) cases (mean [SD] gestational age, 38.3 [2.3] weeks; 220 male [62.1%]) and 1416 controls (mean [SD] gestational age, 38.3 [2.3] weeks; 723 male [51.1%]) were identified. In multivariable analysis, 14 NBS metabolites were significantly associated with SIDS in a univariate analysis: 17-hydroxyprogesterone, alanine, methionine, proline, tyrosine, valine, free carnitine, acetyl-L-carnitine, malonyl carnitine, glutarylcarnitine, lauroyl-L-carnitine, dodecenoylcarnitine, 3-hydroxytetradecanoylcarnitine, and linoleoylcarnitine. The area under the receiver operating characteristic curve for a 14-marker SIDS model, which included 8 metabolites, was 0.75 (95% CI, 0.72-0.79) in the training set and was 0.70 (95% CI, 0.65-0.76) in the test set. Of 32 infants in the test set with model-predicted probability greater than 0.5, a total of 20 (62.5%) had SIDS. These infants had 14.4 times the odds (95% CI, 6.0-34.5) of having SIDS compared with those with a model-predicted probability less than 0.1.
Conclusions and relevance: Results from this case-control study showed an association between aberrant metabolic analytes at birth and SIDS. These findings suggest that we may be able to identify infants at increased risk for SIDS soon after birth, which could inform further mechanistic research and clinical efforts focused on monitoring and prevention.
期刊介绍:
JAMA Pediatrics, the oldest continuously published pediatric journal in the US since 1911, is an international peer-reviewed publication and a part of the JAMA Network. Published weekly online and in 12 issues annually, it garners over 8.4 million article views and downloads yearly. All research articles become freely accessible online after 12 months without any author fees, and through the WHO's HINARI program, the online version is accessible to institutions in developing countries.
With a focus on advancing the health of infants, children, and adolescents, JAMA Pediatrics serves as a platform for discussing crucial issues and policies in child and adolescent health care. Leveraging the latest technology, it ensures timely access to information for its readers worldwide.