Researchers identified 35 significant potential metabolite predictors of sudden infant death syndrome, including ornithine, shedding light on potential diagnostic biomarkers associated with the disease.

A comprehensive metabolomic analysis of sudden infant death syndrome (SIDS) cases was conducted by researchers. Using serum samples from the Chicago Infant Mortality Study and National Institutes of Health NeuroBioBank, 828 metabolites were analyzed to identify potential biomarkers and gain insights into SIDS pathophysiology.

The study—results of which were published in eBioMedicine—included 300 infants, 195 diagnosed with SIDS and 105 non-SIDS controls, with a racially diverse cohort comprised of 70% Black, 13% White, and 16% Hispanic participants. Metabolomic profiling was performed using liquid chromatography-mass spectrometry via the Metabolon DiscoveryHD4 platform. Statistical analyses included Welch’s t-tests, linear and logistic regression, and weighted gene co-expression network analysis (WGCNA).

Thirty-five metabolites were identified as significantly associated with SIDS after adjustment for age, sex, race, ethnicity, and postmortem interval, noted first author Chad M. Aldridge, PT, DPT, of the Department of Neurology at the University of Virginia School of Medicine, and colleagues. Identified metabolites included ornithine (odds ratio [OR] = 21.98; P = 6.44e-7), 5-hydroxylysine (OR = 19.48; P = 6.78e-7), and ribitol (OR = 8.19; P = 4.2e-8). WGCNA identified 10 metabolite clusters, 4 of which were strongly associated with SIDS. Two clusters were enriched for tyrosine metabolism and lipid (sphingomyelins) pathways, which play roles in neurotransmitter function, oxidative stress, and cellular signaling.

SIDS cases demonstrated a mean age difference of −37.4 days compared to controls (95% confidence interval = −54.6 to −20.2 days; P < .001), with a higher prevalence of bedsharing noted in SIDS cases versus controls (48% vs 32%). Key biological pathways implicated included nitrogen metabolism, with ornithine linked to urea cycle disruption, and lipid metabolism, highlighting the potential role of sphingomyelins in neuronal myelination and pulmonary surfactant composition.

There were several limitations in the study, including the use of postmortem biospecimens, though recent research supports the reliability of such material when collected within 48 hours of death. Additionally, combining two cohorts with differing racial and ethnic compositions, sample sizes, and available clinical data—particularly regarding SIDS risk factors like maternal smoking and bedsharing—constrained the ability to adjust for confounding variables in the analysis.

This exploratory study contributes to the understanding of SIDS by identifying metabolite biomarkers and associated biological pathways, with potential implications for diagnostic research, emphasizing the need for validation in independent cohorts to confirm these findings and refine their clinical relevance.

Full disclosures can be found in the published study.