Establishing Episignatures as a Diagnostic Tool for Diabetic Embryopathy
Clinical Genetics and Therapeutics
-
Primary Categories:
- Clinical Genetics
-
Secondary Categories:
- Clinical Genetics
Introduction:
Diabetic embryopathy (DE) encompasses a group of congenital anomalies in infants of diabetic mothers (IDMs) and presents with a wide spectrum of phenotypes across various organ systems. There is no recognized diagnostic tool for DE due to the lack of knowledge about the pathogenesis. Changes in DNA methylation, known as episignatures, have shown promise as diagnostic biomarkers in other congenital conditions. A previous study examining episignatures as a biomarker of DE (Schulze et al., 2019) was able to differentiate between DNA methylation patterns for infants with DE, healthy IDMs, and healthy unexposed infants. However, the small sample size and lack of adequate population diversity prevents clinical application of episignatures as a diagnostic tool for DE from this study alone.
Methods:
We searched several electronic databases to conduct a literature review of case studies, journal articles, reviews, and meta-analyses within the past 15 years (2009-2022) to extract the 57 most common congenital anomalies associated with DE. The requirements of case patients were (1) non-diagnostic genetic testing, (2) high maternal HbA1c during gestation, preferably during the first trimester, and (3) anomalies consistent with DE. Controls for this study were healthy infants of mothers with high gestational HbA1c values and infants with fetal anomalies born to healthy mothers. Most recruitment occurred via chart review at Cincinnati Children’s Hospital Medical Center. Methylation arrays were run in two batches at the University of Western Ontario and analyzed with the machine-learning based algorithm, EpiSign.
Results:
We found the most common categories of anomalies associated with DE involved structural development of the central nervous system and cardiovascular system, as well as craniofacial anomalies. Several conditions were found to have a much greater frequency in IDMs as opposed to the general population, including caudal regression syndrome and femoral hypoplasia. We have recruited 40 participants (28 cases and 12 controls). There was no significant difference between the cases and controls regarding maternal age, birth length, birth head circumference, age at study entry, sex, or race. Both the cases and controls had an elevated pre-pregnancy body mass index (BMI) at 44.0 kg/m2 and 32.3 kg/m2 respectively. A significant difference between gestational age was observed between the cases and controls, with case patients being more premature. For cases, 39% were infants of mothers with gestational diabetes (GDM), 46% infants of Type 2 Diabetic (T2DM) mothers, and 14% infants of mothers with Type 1 Diabetes (T1DM). Methylation array data has been returned from the first 14 samples, with a promising episignature. The methylation pattern was both consistent among patients with DE in this initial cohort and did not exhibit significant overlap with the training controls or any other established condition in the EpiSign database. We are currently awaiting results from the second batch of samples to confirm the findings.
Conclusion:
Our preliminary data is consistent with an episignature for DE. To confirm this episignature, we have recruited an additional patient cohort and are awaiting the results. We anticipate that the data will support an analysis of differentially methylated genes in DE that will potentially be useful for clinical diagnosis and for improving our understanding of the pathogenesis of DE.
Diabetic embryopathy (DE) encompasses a group of congenital anomalies in infants of diabetic mothers (IDMs) and presents with a wide spectrum of phenotypes across various organ systems. There is no recognized diagnostic tool for DE due to the lack of knowledge about the pathogenesis. Changes in DNA methylation, known as episignatures, have shown promise as diagnostic biomarkers in other congenital conditions. A previous study examining episignatures as a biomarker of DE (Schulze et al., 2019) was able to differentiate between DNA methylation patterns for infants with DE, healthy IDMs, and healthy unexposed infants. However, the small sample size and lack of adequate population diversity prevents clinical application of episignatures as a diagnostic tool for DE from this study alone.
Methods:
We searched several electronic databases to conduct a literature review of case studies, journal articles, reviews, and meta-analyses within the past 15 years (2009-2022) to extract the 57 most common congenital anomalies associated with DE. The requirements of case patients were (1) non-diagnostic genetic testing, (2) high maternal HbA1c during gestation, preferably during the first trimester, and (3) anomalies consistent with DE. Controls for this study were healthy infants of mothers with high gestational HbA1c values and infants with fetal anomalies born to healthy mothers. Most recruitment occurred via chart review at Cincinnati Children’s Hospital Medical Center. Methylation arrays were run in two batches at the University of Western Ontario and analyzed with the machine-learning based algorithm, EpiSign.
Results:
We found the most common categories of anomalies associated with DE involved structural development of the central nervous system and cardiovascular system, as well as craniofacial anomalies. Several conditions were found to have a much greater frequency in IDMs as opposed to the general population, including caudal regression syndrome and femoral hypoplasia. We have recruited 40 participants (28 cases and 12 controls). There was no significant difference between the cases and controls regarding maternal age, birth length, birth head circumference, age at study entry, sex, or race. Both the cases and controls had an elevated pre-pregnancy body mass index (BMI) at 44.0 kg/m2 and 32.3 kg/m2 respectively. A significant difference between gestational age was observed between the cases and controls, with case patients being more premature. For cases, 39% were infants of mothers with gestational diabetes (GDM), 46% infants of Type 2 Diabetic (T2DM) mothers, and 14% infants of mothers with Type 1 Diabetes (T1DM). Methylation array data has been returned from the first 14 samples, with a promising episignature. The methylation pattern was both consistent among patients with DE in this initial cohort and did not exhibit significant overlap with the training controls or any other established condition in the EpiSign database. We are currently awaiting results from the second batch of samples to confirm the findings.
Conclusion:
Our preliminary data is consistent with an episignature for DE. To confirm this episignature, we have recruited an additional patient cohort and are awaiting the results. We anticipate that the data will support an analysis of differentially methylated genes in DE that will potentially be useful for clinical diagnosis and for improving our understanding of the pathogenesis of DE.
)
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
){kind=logo}
)
){kind=logo}
)
)
)
)
)
)
){kind=logo}
){kind=logo}
){kind=logo}