Our Research

BACKGROUND: Congenital heart disease (CHD) is the most common major congenital anomaly and a leading cause of infant morbidity and mortality. The rapid expansion of genomic technologies has accelerated the discovery of rare genetic variants implicated in CHD pathogenesis. However, most individuals with CHD still lack an identifiable molecular etiology. The purpose of this scoping review is to systematically characterize genes reported in the recent literature as candidate CHD-associated genes and contextualize these findings within the stages of cardiac morphogenesis.

METHODS: PubMed was searched using predefined terms related to CHD and genetic variants, supplemented by a prospectively maintained internal database. We included human studies published between January 2023 and December 2025 that identified pathogenic, likely pathogenic, or uncertain monogenic variants in at least one patient with CHD. Animal-only studies, chromosomal abnormalities, copy number variants, multigenic associations, transcriptomic/proteomic analyses, reviews, and maternal-only genetic studies were excluded. Gene-disease validity classifications were assigned using the Clinical Genome Resource (ClinGen) CHD Gene Curation Expert Panel framework.

RESULTS: Of 2,834 screened articles, 391 studies met inclusion criteria, identifying 912 unique genes reported as candidate CHD-associated genes. Frequently reported genes included PTPN11, NOTCH1, GATA4, JAG1, MYH6, GATA6, and LZTR1. Identified genes spanned all major stages of cardiogenesis, including developmental priming, cardiac progenitor specification, left-right axis formation, neural crest migration, outflow tract development, septation, and postnatal structural remodeling. Studies increasingly implicated ciliary dysfunction, transcriptional regulation, ribosomal biology, and multigenic inheritance in CHD pathogenesis. Emerging methodologies included stem cell-derived cardiac models, machine learning-based gene prioritization, and epigenetic analyses.

CONCLUSIONS: Recent literature substantially expands the catalog of candidate genes that may be associated with CHD and highlights the biologic complexity underlying cardiac morphogenesis. Integration of genomic, developmental, and functional approaches will be essential to improve mechanistic understanding, refine genetic counseling, and support future precision medicine strategies for CHD.

Neurodevelopmental disorders encompass a large group of conditions, many of which can be explained by genetic variants. KIRREL3 has previously been associated with neurodevelopmental disorders and is expressed in the developing human basal ganglia and amygdala. Through GeneMatcher, which allows clinicians, families, and researchers to share information about novel gene variants, and the Simons Foundation Powering Autism Research (SPARK) project, we identified 26 individuals with different rare missense variants in KIRREL3, which were predicted to be damaging based on their REVEL score. All probands had neurodevelopmental diagnoses including autism spectrum disorder, global developmental delay, intellectual disability, or a learning disability. A full review of previous publications identified 10 rare KIRREL3 missense variants in 13 individuals who had at least one diagnosis of an autism spectrum disorder or intellectual disability. These findings highlight the potential role of KIRREL3 missense variants in neurodevelopmental disorders, which warrants further study.

INTRODUCTION: Neonatal mortality remains disproportionately high in sub-Saharan Africa, where an estimated 27 neonatal deaths per 1,000 live births occur annually. Infections, including sepsis and meningitis, account for a substantial proportion of these deaths, while neural tube defects (NTDs) contribute significantly to both neonatal mortality and long-term disability. Existing surveillance systems in the region are predominantly facility-based, missing the substantial proportion of births and deaths that occur in the community. Population-based surveillance platforms that capture community-level data are urgently needed to generate accurate incidence estimates, identify modifiable risk factors, and guide evidence-based interventions.

COHORT DESCRIPTION: The Consortium to Reduce Infant Mortality (CONRIM) is a multi-institutional partnership among Ugandan physicians and scientists, Yale University, Penn State University, Boston Children's Hospital/Harvard Medical School, and Uganda's National Planning Authority. CONRIM conducts prospective, community-based neonatal surveillance within the Busoga Kingdom in eastern Uganda. A network of 813 trained Village Health Team members conducts household-level visits using a structured Open Data Kit (ODK)-based mobile questionnaire to capture every birth, assess for danger signs of possible serious bacterial infection (pSBI), screen for NTDs, and record maternal nutrition and folic acid use, water, sanitation and hygiene (WASH) conditions, and health care utilization.

FINDINGS TO DATE: Since surveillance began in June 2025, the platform has registered approximately 22,200 household submissions and over 5,700 newborn encounters across the Jinja District (population 660,000). Early data have identified higher than expected rates of infants with NTDs including encephalocele and spina bifida; documented folic acid non-use in before and during most pregnancies; characterized WASH conditions in birthplaces; and mapped geospatial hotspots of neonatal infection risk in northeastern rural subcounties. Prospective 28-day follow-up of all live births has demonstrated a neonatal mortality rate of 21.5 per 1000 live births. A real-time data quality monitoring system with 21 automated quality control flags maintains a 99% clean-record rate.

FUTURE PLANS: Ongoing and planned activities include laboratory-based confirmation of neonatal sepsis via blood culture and cerebrospinal fluid analysis with polymerase chain reaction capacity, portable neuroimaging for NTDs, environmental sampling, genomic studies of folate metabolism pathway genes, linkage with facility-based records at Jinja Regional Referral Hospital and Mulago National Referral Hospital, and community-level interventions informed by surveillance findings.

KEY MESSAGES: What is already known on this topic: Neonatal mortality remains disproportionately high in sub-Saharan Africa, with sepsis and neural tube defects (NTDs) among the leading preventable causes. Existing surveillance systems are predominantly facility-based and fail to capture births, deaths, and environmental exposures occurring at the community level. Emerging approaches in digital health, geospatial analytics, and pathogen genomics have demonstrated potential to enhance infectious disease surveillance, but these have rarely been integrated into population-based neonatal monitoring systems in low-resource settings.What this study adds: The Consortium to Reduce Infant Mortality (CONRIM) is a multidisciplinary initiative designed to develop scalable, population-based systems for understanding and reducing neonatal mortality through integrated epidemiologic, environmental, and biologic data. This paper describes one implementation of the CONRIM framework in the Busoga Kingdom of eastern Uganda, where a network of 813 trained Village Health Team members conducts longitudinal, community-based surveillance of births, neonatal outcomes, NTDs, maternal nutrition (including folic acid use), water, sanitation and hygiene (WASH) conditions, and care-seeking behaviour. This implementation integrates: real-time digital data capture with automated quality control,geospatial information systems (GIS) and remote sensing to characterize environmental risk factors,population-level genomic and metagenomic sampling to investigate host and pathogen factors, anda One Health framework linking human, animal, and environmental exposures. Early findings highlight high data completeness, geospatial clustering of neonatal infection risk, low preconception folic acid use, and identification of NTD cases not captured by facility-based systems.How this study might affect research, practice, or policy: This study demonstrates the feasibility of implementing a community-based, real-time neonatal surveillance system within an existing community health worker network in a low-resource setting. By integrating geospatial, genomic, and environmental data within a unified platform, the CONRIM framework enables more precise identification of drivers of neonatal morbidity and mortality.The approach supports targeted public health interventions, including geographically informed infection control strategies, improved referral pathways, and evidence generation for folic acid fortification policies. More broadly, CONRIM provides a scalable infrastructure for future interventional studies and precision public health strategies aimed at reducing neonatal mortality.

Congenital heart disease (CHD) affects  1% of live births, yet the genetic basis of many cases remains unresolved. Uniparental disomy (UPD), the inheritance of both homologous chromosomes from one parent, is often overlooked. We developed TrioMix-UPD, an integrated short- and long-read sequencing framework for UPD detection and classification. Applying it to 3,740 CHD trios, we identified 12 UPD events, representing a 6.57-fold enrichment relative to the general population. Both advanced maternal age and enrichment of rare inherited variants in synaptonemal complex genes implicated meiotic chromosome segregation defects in UPD risk. Within UPD regions, we identified pathogenic homozygous variants in PIEZO1 and GLYR1 and nominate MESD as a novel CHD candidate gene. Functional studies in zebrafish and human cells recapitulated patient-specific cardiac phenotypes. Differential methylation analyses implicated imprinting dysregulation, including at the Prader-Willi critical region. Collectively, these findings establish UPD as an underrecognized contributor to CHD.