Embryonic Statistical Analyses Reveal 2 Growth Phenotypes in Mouse Models of Down Syndrome

Overview

Journal Am J Obstet Gynecol

Publisher Elsevier

Specialty Gynecology & Obstetrics

Date 2023 Aug 6

PMID 37544351

Authors

April D Adams

Jielu Lin

Diana W Bianchi

Lauren Bishop

Taisuke Sato

Laura L Baxter

Victoria Hoffmann

Laura Koehly

Faycal Guedj

Affiliations

Soon will be listed here.

Abstract

Background: Down syndrome is associated with several comorbidities, including intellectual disability, growth restriction, and congenital heart defects. The prevalence of Down syndrome-associated comorbidities is highly variable, and intellectual disability, although fully penetrant, ranges from mild to severe. Understanding the basis of this interindividual variability might identify predictive biomarkers of in utero and postnatal outcomes that could be used as endpoints to test the efficacy of future therapeutic interventions.

Objective: The main objective of this study was to examine if antenatal interindividual variability exists in mouse models of Down syndrome and whether applying statistical approaches to clinically relevant measurements (ie, the weights of the embryo, placenta, and brain) could define cutoffs that discriminate between subgroups of trisomic embryos.

Study Design: Three commonly used mouse models of Down syndrome (Dp(16)1/Yey, Ts65Dn, and Ts1Cje) and a new model (Ts66Yah) were used in this study. Trisomic and euploid littermate embryos were used from each model with total numbers of 102 for Ts66Yah, 118 for Dp(16)1/Yey, 92 for Ts65Dn, and 126 for Ts1Cje. Placental, embryonic, and brain weights and volumes at embryonic day 18.5 were compared between genotypes in each model. K-mean clustering analysis was applied to embryonic and brain weights to identify severity classes in trisomic embryos, and brain and placental volumetric measurements were compared between genotypes and classes for each strain. In addition, Ts66Yah embryos were examined for malformations because embryonic phenotypes have never been examined in this model.

Results: Reduced body and brain weights were present in Ts66Yah, Dp(16)1/Yey, and Ts65Dn embyos. Cluster analysis identified 2 severity classes in trisomic embryos-mild and severe-in all 4 models that were distinguishable using a putative embryonic weight cutoff of <0.5 standard deviation below the mean. Ts66Yah trisomic embryos develop congenital anomalies that are also found in humans with Down syndrome, including congenital heart defects and renal pelvis dilation.

Conclusion: Statistical approaches applied to clinically relevant measurements revealed 2 classes of phenotypic severity in trisomic mouse models of Down syndrome. Analysis of severely affected trisomic animals may facilitate the identification of biomarkers and endpoints that can be used to prenatally predict outcomes and the efficacy of treatments.

References

Steffensen E, Pedersen L, Lou S, Vogel I . Is the first-trimester combined screening result associated with the phenotype of Down syndrome? A population-based cohort study. Prenat Diagn. 2022; 43(1):51-61. PMC: 10108102. DOI: 10.1002/pd.6284. View

Massin N, Frendo J, Guibourdenche J, Luton D, Giovangrandi Y, Muller F . Defect of syncytiotrophoblast formation and human chorionic gonadotropin expression in Down's syndrome. Placenta. 2001; 22 Suppl A:S93-7. DOI: 10.1053/plac.2001.0658. View

Guedj F, Lopes Pereira P, Najas S, Barallobre M, Chabert C, Souchet B . DYRK1A: a master regulatory protein controlling brain growth. Neurobiol Dis. 2012; 46(1):190-203. DOI: 10.1016/j.nbd.2012.01.007. View

Guihard-Costa A, Khung S, Delbecque K, Menez F, Delezoide A . Biometry of face and brain in fetuses with trisomy 21. Pediatr Res. 2005; 59(1):33-8. DOI: 10.1203/01.pdr.0000190580.88391.9a. View

Wessels M, Los F, Frohn-Mulder I, Niermeijer M, Willems P, Wladimiroff J . Poor outcome in Down syndrome fetuses with cardiac anomalies or growth retardation. Am J Med Genet A. 2002; 116A(2):147-51. DOI: 10.1002/ajmg.a.10823. View

Adams A, Hoffmann V, Koehly L, Guedj F, Bianchi D . Novel insights from fetal and placental phenotyping in 3 mouse models of Down syndrome. Am J Obstet Gynecol. 2021; 225(3):296.e1-296.e13. PMC: 8429205. DOI: 10.1016/j.ajog.2021.03.019. View

Patkee P, Baburamani A, Kyriakopoulou V, Davidson A, Avini E, Dimitrova R . Early alterations in cortical and cerebellar regional brain growth in Down Syndrome: An in vivo fetal and neonatal MRI assessment. Neuroimage Clin. 2019; 25:102139. PMC: 6938981. DOI: 10.1016/j.nicl.2019.102139. View

Hook E, Mutton D, Ide R, Alberman E, Bobrow M . The natural history of Down syndrome conceptuses diagnosed prenatally that are not electively terminated. Am J Hum Genet. 1995; 57(4):875-81. PMC: 1801486. View

Ekinci N, Acer N, Akkaya A, Sankur S, Kabadayi T, Sahin B . Volumetric evaluation of the relations among the cerebrum, cerebellum and brain stem in young subjects: a combination of stereology and magnetic resonance imaging. Surg Radiol Anat. 2008; 30(6):489-94. DOI: 10.1007/s00276-008-0356-z. View

10.

Adams A, Guedj F, Bianchi D . Placental development and function in trisomy 21 and mouse models of Down syndrome: Clues for studying mechanisms underlying atypical development. Placenta. 2019; 89:58-66. PMC: 10040210. DOI: 10.1016/j.placenta.2019.10.002. View

11.

Guedj F, Kane E, Bishop L, Pennings J, Herault Y, Bianchi D . The Impact of Mmu17 Non-Hsa21 Orthologous Genes in the Ts65Dn Mouse Model of Down Syndrome: The Gold Standard Refuted. Biol Psychiatry. 2023; 94(1):84-97. PMC: 10330375. DOI: 10.1016/j.biopsych.2023.02.012. View

12.

Wright A, Zhou Y, Weier J, Caceres E, Kapidzic M, Tabata T . Trisomy 21 is associated with variable defects in cytotrophoblast differentiation along the invasive pathway. Am J Med Genet A. 2004; 130A(4):354-64. DOI: 10.1002/ajmg.a.30254. View

13.

Mircher C, Toulas J, Cieuta-Walti C, Marey I, Conte M, Briceno L . Anthropometric charts and congenital anomalies in newborns with Down syndrome. Am J Med Genet A. 2017; 173(8):2166-2175. DOI: 10.1002/ajmg.a.38305. View

14.

Pidoux G, Guibourdenche J, Frendo J, Gerbaud P, Conti M, Luton D . Impact of trisomy 21 on human trophoblast behaviour and hormonal function. Placenta. 2004; 25 Suppl A:S79-84. DOI: 10.1016/j.placenta.2004.01.007. View

15.

Corry E, Mone F, Segurado R, Downey P, McParland P, McAuliffe F . Placental disease and abnormal umbilical artery Doppler waveforms in trisomy 21 pregnancy: A case-control study. Placenta. 2016; 47:24-28. DOI: 10.1016/j.placenta.2016.09.001. View

16.

Vis J, de Bruin-Bon R, Bouma B, Huisman S, Imschoot L, van den Brink K . Congenital heart defects are under-recognised in adult patients with Down's syndrome. Heart. 2010; 96(18):1480-4. DOI: 10.1136/hrt.2010.197509. View

17.

Guseh S, Little S, Bennett K, Silva V, Wilkins-Haug L . Antepartum management and obstetric outcomes among pregnancies with Down syndrome from diagnosis to delivery. Prenat Diagn. 2017; 37(7):640-646. DOI: 10.1002/pd.5054. View

18.

Klosowska A, Kuchta A, Cwiklinska A, Salaga-Zaleska K, Jankowski M, Klosowski P . Relationship between growth and intelligence quotient in children with Down syndrome. Transl Pediatr. 2022; 11(4):505-513. PMC: 9085946. DOI: 10.21037/tp-21-424. View

19.

Tarui T, Im K, Madan N, Madankumar R, Skotko B, Schwartz A . Quantitative MRI Analyses of Regional Brain Growth in Living Fetuses with Down Syndrome. Cereb Cortex. 2019; 30(1):382-390. PMC: 7029684. DOI: 10.1093/cercor/bhz094. View

20.

Ramos B, Gaudilliere B, Bonni A, Gill G . Transcription factor Sp4 regulates dendritic patterning during cerebellar maturation. Proc Natl Acad Sci U S A. 2007; 104(23):9882-7. PMC: 1887555. DOI: 10.1073/pnas.0701946104. View