Patterns of multiple congenital anomalies in the National Birth Defect Prevention Study: Challenges and insights

Meredith M Howley1, Eva Williford1, A J Agopian2

  • 1Birth Defects Registry, New York State Department of Health, Albany, New York, USA.

Birth Defects Research
|March 12, 2022
PubMed

Insights

Multiple congenital anomalies (MCAs) in children can indicate underlying causes. Analyzing MCA patterns in the National Birth Defects Prevention Study (NBDPS) helps identify syndromic associations and guide future genetic research.

Area of Science:

  • Pediatric genetics and developmental biology
  • Birth defect surveillance and epidemiology
  • Syndromology and genetic associations

Background:

  • Multiple congenital anomalies (MCAs) affect 20%-30% of children with birth defects, involving multiple organ systems.
  • Studying MCA patterns offers insights into causes, mechanisms, and developmental pathways.
  • The National Birth Defects Prevention Study (NBDPS) investigated MCAs, excluding known genetic abnormalities.

Purpose of the Study:

  • To explore patterns of multiple congenital anomalies (MCAs) within the NBDPS.
  • To identify significant co-occurring birth defects and their associations.
  • To inform genetic studies and improve birth defect surveillance.

Main Methods:

  • Defined MCAs as two or more NBDPS-eligible birth defects.
  • Calculated adjusted observed-to-expected ratios for MCA patterns using co-occurring defect analysis.
  • Analyzed 50,186 case infants, identifying numerous combinations of birth defects.

Main Results:

  • 3.7% of infants had at least two eligible birth defects, with 209 two-way to 69 five-way combinations observed.
  • Sacral agenesis (70%) and gastroschisis (3%) showed the highest and lowest proportions of MCAs, respectively.
  • Heart defects (63%), oral clefts (23%), and anorectal atresia/stenosis (21%) were common in MCAs; top patterns aligned with known syndromes like VATER/VACTERL and CHARGE.

Conclusions:

  • Highest observed-to-expected ratios often corresponded to known syndromes or associations.
  • Emphasizes recognizing syndromic patterns even without a formal diagnosis.
  • Suggests improved surveillance methods for identifying associations like VATER/VACTERL and aids genetic research by defining high-yield case groups.
Abstract

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