Biomedical subjects

Cathy Shyr

Publications and source records attributed to Cathy Shyr.

4 recordsLinked to original sources

PubMed2026

An EHR-based framework for modeling growth curves and constructing growth centile charts for genetic disorders.

Growth modeling is central to human genetics, as deviations from typical growth can signal an underlying disorder. In this cohort study, we developed a generalizable framework for generating growth charts across genetic conditions using electronic health records (EHR). Leveraging 22 years of longitudinal EHR data from 452,470 patients across 15 genetic conditions and unaffected individuals, we generated sex- and condition-specific growth charts using Generalized Additive Models for Location, Scale, and Shape, and quantified differences in size, timing, and intensity using SuperImposition by Translation and Rotation (SITAR). SITAR-derived growth parameters showed strong concordance with established annotations in OMIM and Orphanet, and identified previously unreported growth patterns. We stratified cystic fibrosis by CFTR functional class and observed greater growth impairment in individuals with homozygous minimal-function variants compared to those with residual function. This framework provides a generalizable approach for leveraging EHR data to refine genotype-phenotype relationships and enable continuous updating of growth charts across genetic conditions.

Journal Article↗

PubMed2026

Sex-Based Disparities in Fabry Disease Cause Challenges in Newborn Screening.

INTRODUCTION: Fabry disease (FD) is a multi-systemic, X-linked lysosomal storage disorder caused by decreased α-galactosidase activity. Early diagnosis enables timely treatment, but enzyme-based newborn screening (NBS) may not detect affected females. We hypothesized that enzyme-based NBS limitations contribute to sex-based diagnostic disparities in FD and investigated these differences. METHODS: Retrospective cohort analyses used data from the Fabry Registry (FR: 2001-2023) and Tennessee NBS (2017-2024). Sex differences in diagnosis via NBS, biochemical phenotype, symptom onset, and treatment initiation were analyzed using Wilcoxon and chi-square tests. RESULTS: Among 8,657 FR individuals, 73 (67 males, 6 females) were identified via NBS. FR data show that affected females had significantly higher residual α-galactosidase activity than affected males (leukocyte median: 45.9% vs. 3.9%, plasma median: 32.5% vs. 3.9%; p < 0.0001 for both). FR females had delayed symptom onset (18.1 vs. 11.1 years), later diagnosis (35.5 vs. 30.8 years), and lower treatment rates (51.1% vs. 80.8%) compared to males (all %, p < 0.0001). Tennessee NBS detected 25 males but no females. CONCLUSION: Females with FD have delays in symptom onset, diagnosis, and treatment compared to males. Furthermore, higher residual enzyme activity causes current enzyme-based NBS to miss most females. Incorporating sex-specific cutoffs and/or molecular sequencing into NBS could improve early detection and reduce sex-based disparities.

Humans↗

PubMed2026

Sex-Specific Diagnostic Inequality in Fabry Disease: Lessons Learned from Analysis of Newborn Screening and Cascade Testing in Tennessee from 2017 to 2024.

INTRODUCTION: Fabry disease (FD) is an X-linked lysosomal storage disease caused by alpha-galactosidase A (aGAL) deficiency. Newborn screening (NBS) programs for FD have been implemented in several US states; however, its effectiveness in identifying affected females remains uncertain. We hypothesized that sex-specific inequality of NBS-based detection of FD results in different diagnostic pathways for males and females with FD. METHODS: We compared diagnostic approaches for males and females with FD using Tennessee NBS results and Vanderbilt Lysosomal Storage Disorders Database (VLSDD). Sex-specific detection differences were assessed using Fisher's exact test (α = 0.05). RESULTS: Tennessee NBS identified 25 males but no females with FD from 2017 to 2024. In VLSDD, among 81 individuals with FD, sex distribution was nearly equal (42 males, 39 females). Among males, 26/42 (62%) were diagnosed via NBS, 7/42 (17%) through known family history, and 9/42 (21%) based on clinical symptoms. All 16 males diagnosed through non-NBS were born before its implementation. In contrast, none of the 39 females were diagnosed through NBS (p value <0.05). Of these, 13/39 (33%) were diagnosed through cascade testing following their sons' detection by NBS, with a median age at diagnosis of 28 years (25th-75th percentile: 24.5-34.0). Of the remaining 26 females, 12/26 (46%) were diagnosed after a family member was diagnosed through clinical symptoms and 14/26 (54%) were diagnosed through clinical symptoms. CONCLUSIONS: NBS effectively identifies affected males but fails to detect females with FD, though it can indirectly facilitate diagnosis of older female relatives.

Humans↗

PubMed2026

Evaluating pregnancy and neonatal outcomes in mothers with genetic disease using electronic health care records.

PURPOSE: The effect of Mendelian disorders on pregnancy and neonatal outcomes is poorly understood because of their rarity and the challenge of compiling complete prenatal and postnatal records. METHODS: Using electronic health records from a single academic center, we developed a retrospective cohort of maternal-infant dyads. Cases were mothers with molecularly confirmed Mendelian disorders paired with live-born infants; controls had no documented genetic disease. Outcomes were evaluated overall, by organ system, and by individual disorder. RESULTS: The cohort included 58,912 dyads, 241 with genetic diagnoses and 58,671 controls. Although overall outcomes were generally favorable, mothers with genetic disorders had higher rates of cesarean delivery and neonatal intensive care unit admission, earlier gestational age, and lower Apgar scores. Neonatal risks were greatest among neurological and cardiovascular disorders. Known associations were replicated, including increased neonatal intensive care unit admission in 22q11.2 deletion syndrome, cesarean delivery in Turner syndrome, and gestational diabetes in cystic fibrosis. We also provided descriptive electronic-health-record-based case reports and case series for 35 disorders previously lacking published pregnancy outcome data. CONCLUSION: This study identifies elevated perinatal risks in specific Mendelian disease groups and demonstrates how electronic-health-record-linked data can support prenatal counseling, risk stratification, and individualized care for individuals with genetic disorders.

Humans↗