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Systems-level perspective of sudden infant death syndrome.

ABSTRACT: Sudden infant death syndrome (SIDS) remains one of the primary causes of infant mortality in developed countries. Although the causes of SIDS remain largely inconclusive, some of the most informative associations implicate molecular, genetic, anatomical, physiological, and environmental (i.e., infant sleep) factors. Thus, a comprehensive and evolving systems-level model is required to understand SIDS susceptibility. Such models, by being powerful enough to uncover indirect associations, could be used to expand our list of candidate targets for in-depth analysis. We present an integrated WikiPathways model for SIDS susceptibility that includes associated cell systems, signaling pathways, genetics, and animal phenotypes. Experimental and literature-based gene-regulatory data have been integrated into this model to identify intersecting upstream control elements and associated interactions. To expand this pathway model, we performed a comprehensive analysis of existing proteomics data from brainstem samples of infants with SIDS. From this analysis, we discovered changes in the expression of several proteins linked to known SIDS pathologies, including factors involved in glial cell production, hypoxia regulation, and synaptic vesicle release, in addition to interactions with annotated SIDS markers. Our results highlight new targets for further consideration that further enrich this pathway model, which, over time, can improve as a wiki-based, community curation project.

SUBMITTER: Salomonis N

PROVIDER: S-EPMC4193964 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

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Systems-level perspective of sudden infant death syndrome.

Salomonis Nathan N

Pediatric research 20140625 3

Sudden infant death syndrome (SIDS) remains one of the primary causes of infant mortality in developed countries. Although the causes of SIDS remain largely inconclusive, some of the most informative associations implicate molecular, genetic, anatomical, physiological, and environmental (i.e., infant sleep) factors. Thus, a comprehensive and evolving systems-level model is required to understand SIDS susceptibility. Such models, by being powerful enough to uncover indirect associations, could be ...[more]

PMID: 24964230

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Project description:Background: Sudden infant death syndrome (SIDS) is one of the leading causes of infant mortality in the United States (US). The extent to which SIDS manifests with an underlying neuropathological mechanism is highly controversial. SIDS correlates with markers of poor prenatal and postnatal care, generally rooted in the lack of access and quality of healthcare endemic to select racial and ethnic groups, and thus can be viewed in the context of health disparities. However, some evidence suggests that at least a subset of SIDS cases may result from a neuropathological mechanism. To explain these issues, a triple-risk hypothesis has been proposed, whereby an underlying biological abnormality in an infant facing an extrinsic risk during a critical developmental period SIDS is hypothesized to occur. Each SIDS decedent is thus thought to have a unique combination of these risk factors leading to their death. This article reviews the neuropathological literature of SIDS and uses machine learning tools to identify distinct subtypes of SIDS decedents based on epidemiological data. Methods: We analyzed US Period Linked Birth/Infant Mortality Files from 1990 to 2017 (excluding 1992–1994). Using t-SNE, an unsupervised machine learning dimensionality reduction algorithm, we identified clusters of SIDS decedents. Following identification of these groups, we identified changes in the rates of SIDS at the state level and across three countries. Results: Through t-SNE and distance based statistical analysis, we identified three groups of SIDS decedents, each with a unique peak age of death. Within the US, SIDS is geographically heterogeneous. Following this, we found low birth weight and normal birth weight SIDS rates have not been equally impacted by implementation of clinical guidelines. We show that across countries with different levels of cultural heterogeneity, reduction in SIDS rates has also been distinct between decedents with low vs. normal birth weight. Conclusions: Different epidemiological and extrinsic risk factors exist based on the three unique SIDS groups we identified with t-SNE and distance based statistical measurements. Clinical guidelines have not equally impacted the groups, and normal birth weight infants comprise more of the cases of SIDS even though low birth weight infants have a higher SIDS rate.

Dataset Information

Systems-level perspective of sudden infant death syndrome.

Publications

Systems-level perspective of sudden infant death syndrome.

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