Analyses stratified by maternal age and recombination further characterize genes associated with maternal nondisjunction of chromosome 21

Metabolomics of mothers of children with autism, idiopathic developmental delay, and Down syndrome

Developmental delays have been associated with metabolic disturbances in children. Previous research in the childhood autism risk from genetics and the environment (CHARGE) case-control study identified neurodevelopment-related plasma metabolites in children, suggesting disturbances in the energy-related tricarboxylic acid (TCA) cycle and 1-carbon metabolism (1CM). Here, we investigated associations between children's neurodevelopmental outcomes and their mothers' plasma metabolite profiles in a subset of mother-child dyads from CHARGE, including those with autism spectrum disorder (ASD, n = 209), Down syndrome (DS, n = 76), idiopathic developmental delay (iDD, n = 64), and typically developed (TD, n = 185) controls. Multiple linear regression revealed associations between child neurodevelopmental outcomes and maternal plasma metabolites related to the TCA cycle, 1CM, and lipid metabolism. Despite profound metabolic disturbances in children with DS reported previously, few of these differences were observed in the mothers, which might reflect differences in gene dosage between children with DS and their euploid mothers. Notably differences in maternal metabolism related to ASD and iDD followed similar patterns of disturbance in previously reported metabolic signatures in children but were generally smaller in magnitude. Similar patterns of metabolic disturbances observed in mothers and their children with ASD or iDD could reflect shared genetic, mitochondrial, and/or environmental risk factors.

Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos

Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes rely either on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or on direct detection of crossovers in gametes or multigeneration pedigrees, which limits data set scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, and the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations show our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ∼150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared with disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.

Aberrant landscapes of maternal meiotic crossovers contribute to aneuploidies in human embryos

Meiotic recombination is crucial for human genetic diversity and chromosome segregation accuracy. Understanding its variation across individuals and the processes by which it goes awry are long-standing goals in human genetics. Current approaches for inferring recombination landscapes either rely on population genetic patterns of linkage disequilibrium (LD)-capturing a time-averaged view-or direct detection of crossovers in gametes or multi-generation pedigrees, which limits dataset scale and availability. Here, we introduce an approach for inferring sex-specific recombination landscapes using data from preimplantation genetic testing for aneuploidy (PGT-A). This method relies on low-coverage (<0.05×) whole-genome sequencing of in vitro fertilized (IVF) embryo biopsies. To overcome the data sparsity, our method exploits its inherent relatedness structure, knowledge of haplotypes from external population reference panels, as well as the frequent occurrence of monosomies in embryos, whereby the remaining chromosome is phased by default. Extensive simulations demonstrate our method's high accuracy, even at coverages as low as 0.02×. Applying this method to PGT-A data from 18,967 embryos, we mapped 70,660 recombination events with ~150 kbp resolution, replicating established sex-specific recombination patterns. We observed a reduced total length of the female genetic map in trisomies compared to disomies, as well as chromosome-specific alterations in crossover distributions. Based on haplotype configurations in pericentromeric regions, our data indicate chromosome-specific propensities for different mechanisms of meiotic error. Our results provide a comprehensive view of the role of aberrant meiotic recombination in the origins of human aneuploidies and offer a versatile tool for mapping crossovers in low-coverage sequencing data from multiple siblings.

Mothers of children with Down syndrome: a clinical and epidemiological study

Down syndrome is the main genetic cause of intellectual disability. Many studies describe the clinical characteristics of DS patients; however, few have investigated the clinical profile of mothers who have children with DS. Advanced maternal age (≥ 35 years old) is a risk factor for DS. Although there is an overall increase in pregnancies among women with advanced maternal age, there is still a lack of awareness of the increased risk of aneuploidy. Here, we reported the clinical and epidemiological profile of DS children and their mothers in a public reference hospital in the State of Rio de Janeiro, Brazil. For data collection, we performed a face-to-face interview guided by a structured questionnaire with closed-ended questions. A total of 344 individuals, 172 mothers and their DS children, were included in this study. Our results show that 56% of the mothers sampled were ≥ 35 years of age at childbirth. Although 98% of them received prenatal care, only 4% obtained a prenatal diagnosis of DS. Most mothers reported not drinking alcohol or smoking cigarettes during pregnancy. Furthermore, 91% of women took prenatal vitamins and supplements; however, 47% were not aware of their benefits for a healthy pregnancy. Given the strict correlation between advanced maternal age and DS, prenatal care should include genetic counseling for women over 35 years of age. This study highlights the importance of prenatal care and the urgent need for better DS screening allowing for immediate postnatal care, positively impacting the life expectancy of these patients.

Aurora kinase genetic polymorphisms: an association study in Down syndrome and spontaneous abortion

Aneuploidies, such as Down syndrome (DS), are the leading cause of pregnancy loss. Abnormalities in aurora kinase proteins result in genomic instability and aneuploidy, mainly in tumors. Thus, polymorphisms in Aurora kinase genes could influence the occurrence of DS and spontaneous abortion. A case-control study was conducted including 124 mothers of DS children (DSM) and 219 control mothers (CM) to investigate DS risk according to AURKA and AURKC polymorphisms. Genotyping was performed using TaqMan real-time PCR. The minor allele frequency (MAF) observed in AURKA rs2273535 was, respectively, 0.23 in DSM and 0.20 in CM, whereas the frequency of the AURKC rs758099 T allele was 0.32 in case and 0.33 in control mothers. Statistical analysis showed no significant difference in the distribution of genotypes and allele frequencies between DSM and CM. According to previous history of spontaneous abortion, the AURKA rs2273535 genotypes (TT + AT vs. AA: OR 2.54, 95% CI 1.13-5.71, p = 0.02; AT vs. AA: OR 2.39, 95% CI 1.03-5.51, p = 0.04; T vs. A: OR 2.08, 95% CI 1.12-3.90, p = 0.02) and AURKC rs758099 (TT vs. CC: OR 4.34, 95% CI 1.03-18.02, p = 0.04; TT + CT vs. CC: OR 2.52, 95% CI 1.02-6.23, p = 0.04; T vs. C: OR 2.03, 95% CI 1.09-3.80, p = 0.02) were observed as risk factors for spontaneous abortion in case mothers. Our study suggests a possible relationship between AURKA/AURKC variants and increased risk of spontaneous abortion within Down syndrome mothers.