Study Links Early Metabolic Anomalies to Increased Risk of Sudden Infant Death Syndrome

"In the case-control study involving 2,276,578 infants born in California, a predictive model that integrated 14 metabolic markers from newborn screenings along with established SIDS risk factors demonstrated robust performance," the researchers reported in JAMA Pediatrics.

The model achieved an area under the receiver operating characteristic curve of 0.75 in the training set and 0.70 in the test set. Infants with a probability of SIDS greater than 0.5, according to the model, had 14.4 times higher odds of experiencing SIDS compared to those with a probability of less than 0.1.

The results indicate that combining newborn metabolic profiles with clinical risk factors could enhance the identification of infants at higher risk for SIDS.

Sudden Infant Death Syndrome is a leading cause of infant mortality in the US. While previous research has suggested that inborn errors of metabolism might play a role in SIDS, the connection between SIDS and metabolic biomarkers remains ambiguous. Therefore, Scott P. Oltman, California Preterm Birth Initiative, University of California San Francisco, San Francisco, and colleagues aimed to evaluate and model the association between routinely measured newborn metabolic markers and SIDS combined with established risk factors for SIDS.

For this purpose, the researchers conducted 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 focused on infants born in California between 2005 and 2011 with complete metabolic data from routine newborn screenings. SIDS cases were matched with controls in a 1:4 ratio based on gestational age and birth weight z score. The matched data were divided into training (two-thirds) and testing (one-third) subsets. Analysis was performed on data collected from January 2005 to December 2011.

The study investigated metabolites measured by newborn screening alongside established SIDS risk factors. To evaluate the association between these metabolic markers and SIDS, logistic regression was used, incorporating both metabolic data and known risk factors.

The following were the key takeaways from the study:

• Of 2 276 578 eligible infants, 354 SIDS cases (mean gestational age, 38.3 weeks; 62.1% males) and 1416 controls (mean gestational age, 38.3 weeks; 51.1% males) were identified.
• In multivariable analysis, 14 NBS metabolites were significantly associated with SIDS in 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 eight metabolites, was 0.75 in the training set and 0.70 in the test set.
• Of 32 infants in the test set with model-predicted probability greater than 0.5, 62.5% had SIDS. These infants had 14.4 times the odds of having SIDS compared with those with a model-predicted probability of less than 0.1.

"The case-control study results indicated a link between abnormal metabolic analytes at birth and an increased risk of SIDS. These findings suggest that it may be possible to identify infants at higher risk for SIDS shortly after birth. Such early identification could lead to further research into underlying mechanisms and enhance clinical strategies for monitoring and prevention," the researchers concluded.

Reference:

Oltman SP, Rogers EE, Baer RJ, et al. Early Newborn Metabolic Patterning and Sudden Infant Death Syndrome. JAMA Pediatr. Published online September 09, 2024. doi:10.1001/jamapediatrics.2024.3033