Sudden Infant Death Syndrome: Beyond Risk Factors

Prenatal and postnatal factors associated with sudden infant death syndrome: an umbrella review of meta-analyses

BACKGROUND

Comprehensive quantitative evidence on the risk and protective factors for sudden infant death syndrome (SIDS) effects is lacking. We investigated the risk and protective factors related to SIDS.

METHODS

We conducted an umbrella review of meta-analyses of observational and interventional studies assessing SIDS-related factors. PubMed/MEDLINE, Embase, EBSCO, and Google Scholar were searched from inception until January 18, 2023. Data extraction, quality assessment, and certainty of evidence were assessed by using A Measurement Tool Assessment Systematic Reviews 2 following PRISMA guidelines. According to observational evidence, credibility was graded and classified by class and quality of evidence (CE; convincing, highly suggestive, suggestive, weak, or not significant). Our study protocol was registered with PROSPERO (CRD42023458696). The risk and protective factors related to SIDS are presented as equivalent odds ratios (eORs).

RESULTS

We identified eight original meta-analyses, including 152 original articles, covering 12 unique risk and protective factors for SIDS across 21 countries/regions and five continents. Several risk factors, including prenatal drug exposure [eOR = 7.84 (95% CI = 4.81-12.79), CE = highly suggestive], prenatal opioid exposure [9.55 (95% CI = 4.87-18.72), CE = suggestive], prenatal methadone exposure [9.52 (95% CI = 3.34-27.10), CE = weak], prenatal cocaine exposure [4.38 (95% CI = 1.95-9.86), CE = weak], prenatal maternal smoking [2.25 (95% CI = 1.95-2.60), CE = highly suggestive], postnatal maternal smoking [1.97 (95% CI = 1.75-2.22), CE = weak], bed sharing [2.89 (95% CI = 1.81-4.60), CE = weak], and infants found with heads covered by bedclothes after last sleep [11.01 (95% CI = 5.40-22.45), CE = suggestive], were identified. On the other hand, three protective factors, namely, breastfeeding [0.57 (95% CI = 0.39-0.83), CE = non-significant], supine sleeping position [0.48 (95% CI = 0.37-0.63), CE = suggestive], and pacifier use [0.44 (95% CI = 0.30-0.65), CE = weak], were also identified.

CONCLUSIONS

Based on the evidence, we propose several risk and protective factors for SIDS. This study suggests the need for further studies on SIDS-related factors supported by weak credibility, no association, or a lack of adequate research.

The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young

BACKGROUND

Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing.

METHODS

The SDY Case Registry is a National Institutes of Health/Centers for Disease Control and Prevention surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases < 20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015 to 2019. The cohort included 211 children (median age 0.33 year; range 0-20 years), determined to have died suddenly and unexpectedly and from whom DNA biospecimens for DNA extractions and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex- and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy, and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, pathogenic and likely pathogenic genetic variation was identified using a Bayesian-based artificial intelligence (AI) tool.

RESULTS

The SDY cohort was 43% European, 29% African, 3% Asian, 16% Hispanic, and 9% with mixed ancestries and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy, or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, potentially damaging variants in epilepsy, cardiomyopathy, and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death.

CONCLUSIONS

While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.

Altered 5-HT2A/C receptor binding in the medulla oblongata in the sudden infant death syndrome (SIDS): Part I. Tissue-based evidence for serotonin receptor signaling abnormalities in cardiorespiratory- and arousal-related circuits

The sudden infant death syndrome (SIDS), the leading cause of postneonatal infant mortality in the United States, is typically associated with a sleep period. Previously, we showed evidence of serotonergic abnormalities in the medulla (e.g. altered serotonin (5-HT)1A receptor binding), in SIDS cases. In rodents, 5-HT2A/C receptor signaling contributes to arousal and autoresuscitation, protecting brain oxygen status during sleep. Nonetheless, the role of 5-HT2A/C receptors in the pathophysiology of SIDS is unclear. We hypothesize that in SIDS, 5-HT2A/C receptor binding is altered in medullary nuclei that are key for arousal and autoresuscitation. Here, we report altered 5-HT2A/C binding in several key medullary nuclei in SIDS cases (n = 58) compared to controls (n = 12). In some nuclei the reduced 5-HT2A/C and 5-HT1A binding overlapped, suggesting abnormal 5-HT receptor interactions. The data presented here (Part 1) suggest that a subset of SIDS is due in part to abnormal 5-HT2A/C and 5-HT1A signaling across multiple medullary nuclei vital for arousal and autoresuscitation. In Part II to follow, we highlight 8 medullary subnetworks with altered 5-HT receptor binding in SIDS. We propose the existence of an integrative brainstem network that fails to facilitate arousal and/or autoresuscitation in SIDS cases.

The impact of damaging epilepsy and cardiac genetic variant burden in sudden death in the young

Background

Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing.

Methods

The SDY Case Registry is a National Institutes of Health/Centers for Disease Control surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases <20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015-2019. The cohort included 211 children (mean age 1 year; range 0-20 years), determined to have died suddenly and unexpectedly and in whom DNA biospecimens and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex-and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, genetic variation predicted to be damaging was identified using a Bayesian-based artificial intelligence (AI) tool.

Results

The SDY cohort was 42% European, 30% African, 17% Hispanic, and 11% with mixed ancestries, and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, damaging variants in epilepsy, cardiomyopathy and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death.

Conclusions

While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort, and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.

Development of a Risk Score to Predict Sudden Infant Death Syndrome

Sudden Infant Death Syndrome (SIDS) is the third leading cause of death among infants younger than one year of age. Effective SIDS prediction models have yet to be developed. Hence, we developed a risk score for SIDS, testing contemporary factors including infant exposure to passive smoke, circumcision, and sleep position along with known risk factors based on 291 SIDS and 242 healthy control infants. The data were retrieved from death certificates, parent interviews, and medical records collected between 1989−1992, prior to the Back to Sleep Campaign. Multivariable logistic regression models were performed to develop a risk score model. Our finalized risk score model included: (i) breastfeeding duration (OR = 13.85, p < 0.001); (ii) family history of SIDS (OR = 4.31, p < 0.001); (iii) low birth weight (OR = 2.74, p = 0.003); (iv) exposure to passive smoking (OR = 2.64, p < 0.001); (v) maternal anemia during pregnancy (OR = 2.07, p = 0.03); and (vi) maternal age <25 years (OR = 1.77, p = 0.01). The area under the curve for the overall model was 0.79, and the sensitivity and specificity were 79% and 63%, respectively. Once this risk score is further validated it could ultimately help physicians identify the high risk infants and counsel parents about modifiable risk factors that are most predictive of SIDS.

Machine Learning Model Based on Lipidomic Profile Information to Predict Sudden Infant Death Syndrome

Sudden infant death syndrome (SIDS) represents the leading cause of death in under one year of age in developing countries. Even in our century, its etiology is not clear, and there is no biomarker that is discriminative enough to predict the risk of suffering from it. Therefore, in this work, taking a public dataset on the lipidomic profile of babies who died from this syndrome compared to a control group, a univariate analysis was performed using the Mann–Whitney U test, with the aim of identifying the characteristics that enable discriminating between both groups. Those characteristics with a p-value less than or equal to 0.05 were taken; once these characteristics were obtained, classification models were implemented (random forests (RF), logistic regression (LR), support vector machine (SVM) and naive Bayes (NB)). We used seventy percent of the data for model training, subjecting it to a cross-validation (k = 5) and later submitting to validation in a blind test with 30% of the remaining data, which allows simulating the scenario in real life—that is, with an unknown population for the model. The model with the best performance was RF, since in the blind test, it obtained an AUC of 0.9, specificity of 1, and sensitivity of 0.8. The proposed model provides the basis for the construction of a SIDS risk prediction computer tool, which will contribute to prevention, and proposes lines of research to deal with this pathology.

Indeterminacy of the Diagnosis of Sudden Infant Death Syndrome Leading to Problems with the Validity of Data

The validity of infant mortality data is essential in assessing health care quality and in the setting of preventive measures. This study explores different diagnostic procedures used to determine the cause of death across forensic settings and thus the issue of the reduced validity of data. All records from three forensic medical departments that conducted autopsies on children aged 12 months or younger (n = 204) who died during the years 2007–2016 in Moravia were included. Differences in diagnostic procedures were found to be statistically significant. Each department works with a different set of risk factors and places different emphasis on different types of examination. The most significant differences could be observed in sudden infant death syndrome and suffocation diagnosis frequency. The validity of statistical data on the causes of infant mortality is thus significantly reduced. Therefore, the possibilities of public health and social policy interventions toward preventing sudden and unexpected infant death are extraordinarily complicated by this lack of data validity.

Epidemiology of sudden infant death syndrome in Mexico, 2005-2020

BACKGROUND

Sudden Infant Death Syndrome (SIDS) constitutes one of the main causes of mortality in children under one year of age in developed countries; it's frequency to varies geographically. In Mexico the real incidence of SIDS is not known.

METHODS

National databases of deaths in children under one year of age, from 2005 to 2020, were analyzed, due to Sudden Unexpected Infant Death (SUID) [SIDS (R95), accidental suffocation in a sleeping environment (W75), and other ill-defined and unspecified causes of mortality (R99), according to the International Classification of Diseases, tenth revision (ICD 10)]. Mortality rates per year of occurrence due to SUID and their subcategories were calculated. Simple frequencies of SIDS were obtained per year and month of occurrence, state of residence, age, place of death, and access to social security services.

RESULTS

In the study period 473,545 infant deaths occurred; 7,714 (1.62%) deaths were due to SUID; of these, 6,489 (84%) were due to SIDS, which is among the 10 leading causes of infant death in Mexico. The average mortality rate for SUID was 22.4/100,000 live births, for SIDS was 18.8/100,000 live births. Mortality rates within the states were variable, ranging from 2.4/100,000 to 105.1/100,000 live births. In 81% of SIDS records there was no autopsy; 38% of deaths due to SIDS occurred in infants under one month of age, up to 87% of deaths occurred in families without social security services or it was unknown, and 76.2% of deaths occurred at home. Deaths were more frequent during the last months of autumn and during winter.

CONCLUSION

In Mexico there is an underregistry of SIDS as cause of death, along with other SUID categories. Health workers need to be trained to improve diagnosis and data registration, including the practice of autopsies; additionally, it is necessary to implement a public health campaign.

Multi-Omics for the Understanding of Brain Diseases

Brain diseases, including both neurodegenerative diseases and mental disorders, represent the third largest healthcare problem in developed countries, after cardiovascular disorders and cancer [...].