Infant Mortality

Infant mortality is one of the leading indicators of a nation’s health. We seek to better understand which infant deaths are linked to genetic diseases. That information can then be used to focus resources to improve diagnosis and treatment for those conditions.

In 2020, RCIGM and UC San Diego were jointly awarded a $3.6M, 5-year grant to study infant mortality from the NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development.

2018 INFANT CAUSES OF DEATH

Researchers plan to decode genomes associated with 1,000 infant deaths from dried blood spots. By combining data about the genetic makeup of these infants with data about their environment, birth, and demographic risk factors they will examine the roles these different factors play in infant mortality. The goal is to detect the causes of previously unexplained deaths and use that to inform prevention and intervention strategies.

The study will also probe the ethical implications of returning results to bereaved families.

Research Study

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Christina Chambers, PhD, MPH

UC San Diego

San Diego, CA, Aug. 21, 2017-- Dr. Stephen Kingsmore.  Photo by Earnie Grafton.

Stephen Kingsmore, MD, DSc

Rady Children's Institute for Genomic Medicine

Publications

J Matern Fetal Neonatal Med. 2021 Dec 1:1-8. doi: 10.1080/14767058.2021.2008899. Online ahead of print.

ABSTRACT

OBJECTIVES: Many studies of sudden unexpected infant death (SUID) have focused on individual domains of risk factors (maternal, infant, and environmental), resulting in limited capture of this multifactorial outcome. The objective of this study was to examine the geographic distribution of SUID in San Diego County, and assess maternal, infant, and environmental risk factors from a large, administrative research platform.

STUDY DESIGN: Births in California between 2005 and 2017 were linked to hospital discharge summaries and death files. From this retrospective birth cohort, cases of SUID were identified from infant death files in San Diego County. We estimated adjusted hazard ratios (aHRs) for infant, maternal, and environmental factors and SUID in multivariable Cox regression analysis. Models were adjusted for maternal sociodemographic characteristics and prenatal nicotine exposure.

RESULTS: There were 211 (44/100,000 live births; absolute risk 0.04%) infants with a SUID among 484,905 live births. There was heterogeneity in geographic distribution of cases. Multiparity (0.05%; aHR 1.4, 95% confidence interval (CI) 1.1, 1.9), maternal depression (0.11%; aHR 1.8, 95% CI 1.0, 3.4), substance-related diagnoses (0.27%; aHR 2.3, 95% CI 1.3, 3.8), cannabis-related diagnosis (0.35%; aHR 2.7, 95% CI 1.5, 5.0), prenatal nicotine use (0.23%; aHR 2.5, 95% CI 1.5, 4.2), preexisting hypertension (0.11%; aHR 2.3, 95% CI 1.2, 4.3), preterm delivery (0.09%; aHR 2.1, 95% CI 1.5, 3.0), infant with a major malformation (0.09%; aHR 2.0, 95% CI 1.1, 3.6), respiratory distress syndrome (0.12%; aHR 2.6, 95% CI 1.5, 4.6), and select environmental factors were all associated with SUID.

CONCLUSIONS: Multiple risk factors were confirmed and expanded upon, and the geographic distribution for SUID in San Diego County was identified. Through this approach, prevention efforts can be targeted to geographies that would benefit the most.

PMID:34852708 | DOI:10.1080/14767058.2021.2008899

Cell. 2021 Aug 7:S0092-8674(21)00883-7. doi: 10.1016/j.cell.2021.07.024. Online ahead of print.

ABSTRACT

Throughout development and aging, human cells accumulate mutations resulting in genomic mosaicism and genetic diversity at the cellular level. Mosaic mutations present in the gonads can affect both the individual and the offspring and subsequent generations. Here, we explore patterns and temporal stability of clonal mosaic mutations in male gonads by sequencing ejaculated sperm. Through 300× whole-genome sequencing of blood and sperm from healthy men, we find each ejaculate carries on average 33.3 ± 12.1 (mean ± SD) clonal mosaic variants, nearly all of which are detected in serial sampling, with the majority absent from sampled somal tissues. Their temporal stability and mutational signature suggest origins during embryonic development from a largely immutable stem cell niche. Clonal mosaicism likely contributes a transmissible, predicted pathogenic exonic variant for 1 in 15 men, representing a life-long threat of transmission for these individuals and a significant burden on human population health.

PMID:34388390 | DOI:10.1016/j.cell.2021.07.024

Pediatrics. 2021 Jun 30:e2020019000. doi: 10.1542/peds.2020-019000. Online ahead of print.

ABSTRACT

Congenital anomalies affect 3% to 5% of births and remain the leading cause of infant death in the United States. As whole exome and genome sequencing are increasingly used to diagnose underlying genetic disease, the patient’s clinical presentation remains the most important context for interpreting sequencing results, including frequently reported variants of uncertain significance (VUS). Classification of a variant as VUS acknowledges limits on evidence to establish whether a variant can be classified as pathogenic or benign according to the American College of Medical Genetics guidelines. Importantly, the VUS designation reflects limits on the breadth of evidence linking the genetic variant to a disease. However, available evidence, although limited, may be surprisingly relevant in an individual patient’s case. Accordingly, a VUS result should be approached neither as nondiagnostic genetic result nor as automatically “uncertain” in its potential to guide clinical decision-making. In this article, we discuss a case of an infant born at 29 weeks 4 days without a corpus callosum, whose whole genome sequencing yielded compound heterozygous variants both classified as VUS in ROBO1, a gene encoding for a receptor involved in a canonical signaling mechanism that guides axons across midline. Approaching the VUS result as potentially pathogenic, we found the infant ultimately had pituitary dysfunction and renal anomalies consistent with other reported ROBO1 variants and basic science literature. Accordingly, we highlight resources for variant interpretation available to clinicians to evaluate VUS results, particularly as they inform the diagnosis of individually rare but collectively common rare diseases.

PMID:34193621 | DOI:10.1542/peds.2020-019000

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