Prenatally diagnosed developmental abnormalities of the central nervous system and genetic syndromes: A practical review

Pathogenic variants associated with speech/cognitive delay and seizures affect genes with expression biases in excitatory neurons and microglia in developing human cortex

Background & Objective

Congenital brain malformations and neurodevelopmental disorders (NDDs) are common pediatric neurological disorders and result in chronic disability. With the expansion of genetic testing, new etiologies for NDDs are continually uncovered, with as many as one third attributable to single-gene pathogenic variants. While our ability to identify pathogenic variants has continually improved, we have little understanding of the underlying cellular pathophysiology in the nervous system that results from these variants. We therefore integrated phenotypic information from subjects with monogenic diagnoses with two large, single-nucleus RNA-sequencing (snRNAseq) datasets from human cortex across developmental stages in order to investigate cell-specific biases in gene expression associated with distinct neurodevelopmental phenotypes.

Methods

Phenotypic data was gathered from 1) a single-institution cohort of 84 neonates with pathogenic single-gene variants referred to Duke Pediatric Genetics, and 2) a cohort of 4,238 patients with neurodevelopmental disorders and pathogenic single-gene variants enrolled in the Deciphering Developmental Disorders (DDD) study. Pathogenic variants were grouped into genesets by neurodevelopmental phenotype and geneset expression across cortical cell subtypes was compared within snRNAseq datasets from 86 human cortex samples spanning the 2nd trimester of gestation to adulthood.

Results

We find that pathogenic variants associated with speech/cognitive delay or seizures involve genes that are more highly expressed in cortical excitatory neurons than variants in genes not associated with these phenotypes (Speech/cognitive: p=2.25×10 -7 ; Seizures: p=7.97×10 -12 ). A separate set of primarily rare variants associated with speech/cognitive delay or seizures, distinct from those with excitatory neuron expression biases, demonstrated expression biases in microglia. We also found that variants associated with speech/cognitive delay and an excitatory neuron expression bias could be further parsed by the presence or absence of comorbid seizures. Variants associated with speech/cognitive delay without seizures tended to involve calcium regulatory pathways and showed greater expression in extratelencephalic neurons, while those associated with speech/cognitive delay with seizures tended to involve synaptic regulatory machinery and an intratelencephalic neuron expression bias (ANOVA by geneset p<2×10 -16 ).

Conclusions

By combining extensive phenotype datasets from subjects with neurodevelopmental disorders with massive human cortical snRNAseq datasets across developmental stages, we identified cell-specific expression biases for genes in which pathogenic variants are associated with speech/cognitive delay and seizures. The involvement of genes with enriched expression in excitatory neurons or microglia highlights the unique role both cell types play in proper sculpting of the developing brain. Moreover, this information begins to shed light on distinct cortical cell types that are more likely to be impacted by pathogenic variants and that may mediate the symptomatology of resulting neurodevelopmental disorders.

Advancing fetal diagnosis and prognostication using comprehensive prenatal phenotyping and genetic testing

Prenatal diagnoses of congenital malformations have increased significantly in recent years with use of high-resolution prenatal imaging. Despite more precise radiological diagnoses, discussions with expectant parents remain challenging because congenital malformations are associated with a wide spectrum of outcomes. Comprehensive prenatal genetic testing has become an essential tool that improves the accuracy of prognostication. Testing strategies include chromosomal microarray, exome sequencing, and genome sequencing. The diagnostic yield varies depending on the specific malformations, severity of the abnormalities, and multi-organ involvement. The utility of prenatal genetic diagnosis includes increased diagnostic clarity for clinicians and families, informed pregnancy decision-making, neonatal care planning, and reproductive planning. Turnaround time for results of comprehensive genetic testing remains a barrier, especially for parents that are decision-making, although this has improved over time. Uncertainty inherent to many genetic testing results is a challenge. Appropriate genetic counseling is essential for parents to understand the diagnosis and prognosis and to make informed decisions. Recent research has investigated the yield of exome or genome sequencing in structurally normal fetuses, both with non-invasive screening methods and invasive diagnostic testing; the prenatal diagnostic community must evaluate and analyze the significant ethical considerations associated with this practice prior to generalizing its use. IMPACT: Reviews available genetic testing options during the prenatal period in detail. Discusses the impact of prenatal genetic testing on care using case-based examples. Consolidates the current literature on the yield of genetic testing for prenatal diagnosis of congenital malformations.

Pathogenic/likely pathogenic copy number variations and regions of homozygosity in fetal central nervous system malformations

OBJECTIVE

To explore pathogenic/likely pathogenic copy number variations (P/LP CNVs) and regions of homozygosity (ROHs) in fetal central nervous system (CNS) malformations.

METHODS

A cohort of 539 fetuses with CNS malformations diagnosed by ultrasound/MRI was retrospectively analyzed between January 2016 and December 2019. All fetuses were analyzed by chromosomal microarray analysis (CMA). Three cases with ROHs detected by CMA were subjected to whole-exome sequencing (WES). The fetuses were divided into two groups according to whether they had other structural abnormalities. The CNS phenotypes of the two groups were further classified as simple (one type) or complicated (≥ 2 types).

RESULTS

(1) A total of 35 cases with P/LP CNVs were found. The incidence of P/LP CNVs was higher in the extra-CNS group [18.00% (9/50)] than in the isolated group [5.32% (26/489)] (P < 0.01), while there was no significant difference between the simpletype and complicated-type groups. (2) In the simple-type group, the three most common P/LP CNV phenotypes were holoprosencephaly, Dandy-Walker syndrome, and exencephaly. There were no P/LP CNVs associated with anencephaly, microcephaly, arachnoid cysts, ependymal cysts, or intracranial hemorrhage. (3) Only four cases with ROHs were found, and there were no cases of uniparental disomy or autosomal diseases.

CONCLUSION

The P/LP CNV detection rates varied significantly among the different phenotypes of CNS malformations, although simple CNS abnormalities may also be associated with genetic abnormalities.

Modeling fetal cortical development by quantile regression for gestational age and head circumference: a prospective cross sectional study

OBJECTIVES

To develop charts for fetal brain cortical structures following a proposed standardized methodology and using quantile regression.

METHODS

Prospective cross-sectional study including 344 low-risk singleton pregnancies between 19 and 34 weeks of gestation. The depth of Sylvian (SF), Parieto-occipital (POF) and Calcarine fissures (CF) were measured on ultrasound images using a standardized technique and their changes were evaluated by quantile regression as a function of gestational age (GA) interval or head circumference (HC).

RESULTS

The measurements of SF, POF and CF depth significantly increased with gestation. Linear models better described the changes of cortical variables with GA and HC. When the fit of sulci depth with GA and HC were compared, a close relationship was highlighted for the latter variable.

CONCLUSIONS

We provided prospective charts of fetal cortical development using quantile regression and following a strict standardized methodology These new charts may help in better identifying cases at higher risk of abnormal cortical neurodevelopment.

Deep learning system improved detection efficacy of fetal intracranial malformations in a randomized controlled trial

Congenital malformations of the central nervous system are among the most common major congenital malformations. Deep learning systems have come to the fore in prenatal diagnosis of congenital malformation, but the impact of deep learning-assisted detection of congenital intracranial malformations from fetal neurosonographic images has not been evaluated. Here we report a three-way crossover, randomized control trial (Trial Registration: ChiCTR2100048233) that assesses the efficacy of a deep learning system, the Prenatal Ultrasound Diagnosis Artificial Intelligence Conduct System (PAICS), in assisting fetal intracranial malformation detection. A total of 709 fetal neurosonographic images/videos are read interactively by 36 sonologists of different expertise levels in three reading modes: unassisted mode (without PAICS assistance), concurrent mode (using PAICS at the beginning of the assessment) and second mode (using PAICS after a fully unaided interpretation). Aided by PAICS, the average accuracy of the unassisted mode (73%) is increased by the concurrent mode (80%; P < 0.001) and the second mode (82%; P < 0.001). Correspondingly, the AUC is increased from 0.85 to 0.89 and to 0.90, respectively (P < 0.001 for all). The median read time per data is slightly increased in concurrent mode but substantially prolonged in the second mode, from 6 s to 7 s and to 11 s (P < 0.001 for all). In conclusion, PAICS in both concurrent and second modes has the potential to improve sonologists' performance in detecting fetal intracranial malformations from neurosonographic data. PAICS is more efficient when used concurrently for all readers.

A Clinical Approach to Semiautomated Three-Dimensional Fetal Brain Biometry-Comparing the Strengths and Weaknesses of Two Diagnostic Tools: 5DCNS+TM and SonoCNSTM

(1) Objective: We aimed to evaluate the accuracy and efficacy of AI-assisted biometric measurements of the fetal central nervous system (CNS) by comparing two semiautomatic postprocessing tools. We further aimed to discuss the additional value of semiautomatically generated sagittal and coronal planes of the CNS. (2) Methods: Three-dimensional (3D) volumes were analyzed with two semiautomatic software tools, 5DCNS+™ and SonoCNS™. The application of 5DCNS+™ results in nine planes (axial, coronal and sagittal) displayed in a single template; SonoCNS™ depicts three axial cutting sections. The tools were compared regarding automatic biometric measurement accuracy. (3) Results: A total of 129 fetuses were included for final analysis. Our data indicate that, in terms of the biometric quantification of head circumference (HC), biparietal diameter (BPD), transcerebellar diameter (TCD) and cisterna magna (CM), the accuracy of SonoCNS™ was higher with respect to the manual measurement of an experienced examiner compared to 5DCNS+™, whereas it was the other way around regarding the diameter of the posterior horn of the lateral ventricle (Vp). The inclusion of four orthogonal coronal views in 5DCNS+™ gives valuable information regarding spatial arrangements, particularly of midline structures. (4) Conclusions: Both tools were able to ease assessment of the intracranial anatomy, highlighting the additional value of automated algorithms in clinical use. SonoCNS™ showed a superior accuracy of plane reconstruction and biometry, but volume reconstruction using 5DCNS+™ provided more detailed information, which is needed for an entire neurosonogram as suggested by international guidelines.

Application and Progress of Artificial Intelligence in Fetal Ultrasound

Prenatal ultrasonography is the most crucial imaging modality during pregnancy. However, problems such as high fetal mobility, excessive maternal abdominal wall thickness, and inter-observer variability limit the development of traditional ultrasound in clinical applications. The combination of artificial intelligence (AI) and obstetric ultrasound may help optimize fetal ultrasound examination by shortening the examination time, reducing the physician's workload, and improving diagnostic accuracy. AI has been successfully applied to automatic fetal ultrasound standard plane detection, biometric parameter measurement, and disease diagnosis to facilitate conventional imaging approaches. In this review, we attempt to thoroughly review the applications and advantages of AI in prenatal fetal ultrasound and discuss the challenges and promises of this new field.

Advantages of current fetal neuroimaging and genomic technologies in prenatal diagnosis: A clinical case

The diagnosis of prenatal microcephaly, as well as the possibility of underlining a genetic cause, is becoming more frequent thanks to advances in prenatal imaging and parallel massive sequencing. One case of primary microcephaly in three sibs demonstrates how complementary diagnostic exams can help to diagnose and establish the etiology.

Applicability of a semiautomated volumetric approach (5D CNS+™) for detailed antenatal reconstruction of abnormal fetal CNS anatomy

BACKGROUND

The aim of this study was to evaluate the accuracy and reliability of a semiautomated volumetric approach (5D CNS+™) when examining fetuses with an apparent abnormal anatomy of the central nervous system (CNS).

METHODS

Stored 3D volumes extracted from a cohort of > 1.400 consecutive 2nd and 3rd trimester pregnancies (range 15-36 gestational weeks) were analyzed using the semiautomatic software tool 5D CNS+™, enabling detailed reconstruction of nine diagnostic planes of the fetal brain. All 3D data sets were examined and judged for plane accuracy, the need for manual adjustment, and fetal CNS anomalies affecting successful plane reconstruction.

RESULTS

Based on our data of 91 fetuses with structural cerebral anomalies, we were able to reveal details of a wide range of CNS anomalies with application of the 5D CNS+™ technique. The corresponding anatomical features and consecutive changes of neighboring structures could be clearly demonstrated. Thus, a profound assessment of the entire altered CNS anatomy could be achieved in nearly all cases. The comparison with matched controls showed a significant difference in volume acquisition (p < 0.001) and in need for manual adjustment (p < 0.001) but not in the drop-out rates (p = 0.677) of both groups.

CONCLUSION

5D CNS+™ is applicable in the majority of cases with brain lesions and constitutes a reliable tool even if the integrity of the fetal CNS is compromised by structural anomalies. Using volume data that were acquired in identical cutting sections needed for conventional biometry allows for detailed anatomic surveys grossly independent of the examiner's experience.

Genomic architecture of fetal central nervous system anomalies using whole-genome sequencing

Structural anomalies of the central nervous system (CNS) are one of the most common fetal anomalies found during prenatal imaging. However, the genomic architecture of prenatal imaging phenotypes has not yet been systematically studied in a large cohort. Patients diagnosed with fetal CNS anomalies were identified from medical records and images. Fetal samples were subjected to low-pass and deep whole-genome sequencing (WGS) for aneuploid, copy number variation (CNV), single-nucleotide variant (SNV, including insertions/deletions (indels)), and small CNV identification. The clinical significance of variants was interpreted based on a candidate gene list constructed from ultrasound phenotypes. In total, 162 fetuses with 11 common CNS anomalies were enrolled in this study. Primary diagnosis was achieved in 62 cases, with an overall diagnostic rate of 38.3%. Causative variants included 18 aneuploids, 17 CNVs, three small CNVs, and 24 SNVs. Among the 24 SNVs, 15 were novel mutations not reported previously. Furthermore, 29 key genes of diagnostic variants and critical genes of pathogenic CNVs were identified, including five recurrent genes: i.e., TUBA1A, KAT6B, CC2D2A, PDHA1, and NF1. Diagnostic variants were present in 34 (70.8%) out of 48 fetuses with both CNS and non-CNS malformations, and in 28 (24.6%) out of 114 fetuses with CNS anomalies only. Hypoplasia of the cerebellum (including the cerebellar vermis) and holoprosencephaly had the highest primary diagnosis yields (>70%), while only four (11.8%) out of 34 neural tube defects achieved genetic diagnosis. Compared with the control group, rare singleton loss-of-function variants (SLoFVs) were significantly accumulated in the patient cohort.

Fetal central nervous system anomalies: When should we offer exome sequencing?

OBJECTIVE

To investigate the detection of pathogenic variants using exome sequencing in an international cohort of fetuses with central nervous system (CNS) anomalies.

METHODS

We reviewed trio exome sequencing (ES) results for two previously reported unselected cohorts (Prenatal Assessment of Genomes and Exomes (PAGE) and CUIMC) to identify fetuses with CNS anomalies with unremarkable karyotypes and chromosomal microarrays. Variants were classified according to ACMG guidelines and association of pathogenic variants with specific types of CNS anomalies explored.

RESULTS

ES was performed in 268 pregnancies with a CNS anomaly identified using prenatal ultrasound . Of those with an isolated, single, CNS anomaly, 7/97 (7.2%) had a likely pathogenic/pathogenic (LP/P) variant. This includes 3/23 (13%) fetuses with isolated mild ventriculomegaly and 3/10 (30%) fetuses with isolated agenesis of the corpus callosum. Where there were multiple anomalies within the CNS, 12/63 (19%) had LP/P variants. Of the 108 cases with CNS and other organ system anomalies, 18 (16.7%) had LP/P findings.

CONCLUSION

ES is an important tool in the prenatal evaluation of fetuses with any CNS anomaly. The rate of LP/P variants tends to be highest in fetuses with multiple CNS anomalies and multisystem anomalies, however, ES may also be of benefit for isolated CNS anomalies.

Evaluation of prenatal central nervous system anomalies: obstetric management, fetal outcomes and chromosome abnormalities

Objective

To study the outcomes of fetuses who were diagnosed with central nervous system (CNS) anomalies during prenatal period and to describe the obstetric management of those pregnancies.

Methods

In this retrospective study, fetuses who were detected to have central nervous system anomalies by prenatal ultrasound from January 2010 to December 2019 were recruited. Data regarding prenatal diagnosis and obstetric outcomes were retrieved from maternal and paediatric records. The prognosis of fetuses who were born alive was classified based on their neurodevelopmental outcome within two years of life.

Results

There were a total of 365 fetuses with CNS anomalies within the 10-year study period, with a mean gestational age of 24.65±7.37 weeks at diagnosis. Ventriculomegaly (23.36%) was the commonest CNS anomalies seen. 198 (54.20%) of these fetuses had associated extra-CNS anomalies, with cardiovascular being the most common system involved. Fetal karyotyping was performed in 111 pregnancies, with chromosomal aberrations detected in 53 (49.07%) cases and culture failure in 3 cases. Majority of the chromosomal abnormalities were Edward syndrome (trisomy 18) and Patau syndrome (trisomy 13). Fetuses with congenital CNS anomalies and abnormal chromosomal karyotyping were more likely to be diagnosed earlier by prenatal ultrasound and tend to have poorer obstetric and neurocognitive prognosis. Prenatally, 86 (23.56%) of the cases were lost to follow up and likely to deliver elsewhere. Among the 279 cases whom their pregnancy outcomes were available, 139 (49.82%) pregnancies resulted in live births, 105 (37.63%) pregnancies were electively terminated, while the remaining 35 (12.54%) pregnancies ended in spontaneous loss. The decision of termination of pregnancy largely depends on mean diagnostic gestational age, presence of chromosomal aberrations and abnormal amniotic fluid volume in those fetuses. Two years after delivery, only 75 (53.96%) children out of 139 live births were still alive, 43 (30.93%) died and 21 (15.11%) cases were lost to follow-up. 32 (23.02%) children with prenatally diagnosed CNS anomalies had normal neurodevelopmental outcome. The presence of multiple CNS anomalies and involvement of extra-CNS anomalies indicated a poorer neurodevelopmental prognosis.

Conclusion

Less than 50% of fetuses with prenatally diagnosed CNS anomalies resulted in live births. Even if they survive till delivery, 36.45% of them passed away within 2 years and 62.79% of children who survived till 2 years old had neurodevelopmental disability.

Use of real-time artificial intelligence in detection of abnormal image patterns in standard sonographic reference planes in screening for fetal intracranial malformations

OBJECTIVES

To develop and validate an artificial intelligence system, the Prenatal ultrasound diagnosis Artificial Intelligence Conduct System (PAICS), to detect different patterns of fetal intracranial abnormality in standard sonographic reference planes for screening for congenital central nervous system (CNS) malformations.

METHODS

Neurosonographic images from normal fetuses and fetuses with CNS malformations at 18-40 gestational weeks were retrieved from the databases of two tertiary hospitals in China and assigned randomly (ratio, 8:1:1) to training, fine-tuning and internal validation datasets to develop and evaluate the PAICS. The system was built based on a real-time convolutional neural network (CNN) algorithm, You Only Look Once, version 3 (YOLOv3). An image dataset from a third tertiary hospital was used to further validate, externally, the performance of the PAICS and to compare its performance with that of sonologists with different levels of expertise. Furthermore, a prospective video dataset was employed to evaluate the performance of the PAICS in a real-time scan scenario. The diagnostic accuracy, sensitivity, specificity and area under the receiver-operating-characteristics curve (AUC) were calculated to assess the performance of the PAICS and to compare this with the performance of sonologists with different levels of experience.

RESULTS

In total, 43 890 images from 16 297 pregnancies and 169 videos from 166 pregnancies were used to develop and validate the PAICS. The system achieved excellent performance in identifying 10 types of intracranial image pattern, with macro- and microaverage AUCs, respectively, of 0.933 (95% CI, 0.798-1.000) and 0.977 (95% CI, 0.970-0.985) for the internal validation image dataset, 0.902 (95% CI, 0.816-0.989) and 0.898 (95% CI, 0.885-0.911) for the external validation image dataset and 0.969 (95% CI, 0.886-1.000) and 0.981 (95% CI, 0.974-0.988) in the real-time scan setting. The performance of the PAICS was comparable to that of expert sonologists in terms of macro- and microaverage accuracy (P = 0.863 and P = 0.775, respectively), sensitivity (P = 0.883, P = 0.846) and AUC (P = 0.891, P = 0.788), but required significantly less time (0.025 s per image for PAICS vs 4.4 s for experts, P < 0.001).

CONCLUSIONS

Both in the image dataset and in the real-time scan setting, the PAICS achieved excellent diagnostic performance for various fetal CNS abnormalities. Its performance was comparable to that of experts, but it required less time. A CNN algorithm can be trained to detect fetal CNS abnormalities. The PAICS has the potential to be an effective and efficient tool in screening for fetal CNS malformations in clinical practice. © 2021 International Society of Ultrasound in Obstetrics and Gynecology.

CNS Malformations in the Newborn

Structural brain anomalies are relatively common and may be detected either prenatally or postnatally. Brain malformations can be characterized based on the developmental processes that have been perturbed, either by environmental, infectious, disruptive or genetic causes. Fetuses and neonates with brain malformations should be thoroughly surveilled for potential other anomalies, and depending on the nature of the brain malformation, may require additional investigations such as genetic testing, ophthalmological examinations, cardiorespiratory monitoring, and screening laboratory studies.

Prenatal neurosurgical counseling for conditions affecting the fetal nervous system

OBJECTIVE

The aim of this study was to share a single center's experience of prenatal neurosurgical counseling and explore pregnant women's experiences with counseling.

MATERIAL AND METHODS

This retrospective study analyzed data for 81 women who received prenatal counseling in a single institution (same senior pediatric neurosurgeon) over a 6-year period. Additionally, a retrospective questionnaire study was conducted with 33 women who chose to continue their pregnancy, to assess the strengths and weaknesses of counseling and analyze the reasons for their decision.

RESULTS

Spinal dysraphism was the most frequent condition leading to prenatal counseling, followed by conditions affecting the cerebrospinal fluid. 57.6% of the women did not follow the French national recommendations on folic acid supplementation in the periconceptional period, and 38.3% underwent termination of pregnancy (TOP). One-third of the 33 women who answered our questionnaire changed their mind about TOP after counseling, and 50% reported that the information provided influenced their decision.

CONCLUSION

Prenatal neurosurgical counseling is nowadays an important part of a pediatric neurosurgeon's practice. It provides specific information to the woman to decide whether to continue the pregnancy. Urological concerns are frequent among the malformations encountered. Hence, we conclude that these women should be offered the possibility of seeing a urologist. Areas for improvement include greater awareness regarding folic acid supplementation and improved psychological care. The advantage for a woman of consulting a neurosurgeon consists in receiving information that is as accurate as possible about the level of disability of the future child and about surgery and follow-up.

Prenatal exome sequencing: A useful tool for the fetal neurologist

Prenatal exome sequencing (pES) is a promising tool for diagnosing genetic disorders when structural anomalies are detected on prenatal ultrasound. The aim of this study was to investigate the diagnostic yield and clinical impact of pES as an additional modality for fetal neurologists who counsel parents in case of congenital anomalies of the central nervous system (CNS). We assessed 20 pregnancies of 19 couples who were consecutively referred to the fetal neurologist for CNS anomalies. pES had a diagnostic yield of 53% (10/19) with most diagnosed pregnancies having agenesis or hypoplasia of the corpus callosum (7/10). Overall clinical impact was 63% (12/19), of which the pES result aided parental decision making in 55% of cases (6/11), guided perinatal management in 75% of cases (3/4), and was helpful in approving a late termination of pregnancy request in 75% of cases (3/4). Our data suggest that pES had a high diagnostic yield when CNS anomalies are present, although this study is limited by its small sample size. Moreover, pES had substantial clinical impact, which warrants implementation of pES in the routine care of the fetal neurologist in close collaboration with gynecologists and clinical geneticists.

Application of Single Nucleotide Polymorphism Microarray in Prenatal Diagnosis of Fetuses with Central Nervous System Abnormalities

Background

The current gold standard of karyotype analysis for prenatal diagnosis of fetuses with central nervous system (CNS) abnormalities has some limitations. Here, we assessed the value of single nucleotide polymorphism (SNP) arrays as a diagnostic tool.

Methods

The results of prenatal diagnosis of 344 fetuses with CNS abnormalities as determined by ultrasonographic screening were retrospectively analyzed. All fetuses underwent chromosomal karyotype analysis and genome-wide SNP array analysis simultaneously. The resultant rates and frequencies of genomic abnormalities were compared.

Results

Karyotype analysis found 45 (13.2%) abnormal CNS cases, while SNP array found 60 (17.4%) cases. SNP array detected 23 (6.7%) cases of submicroscopic abnormalities that karyotype analysis did not find. The detection rate of karyotype analysis was 8.1% in the group with isolated CNS anomalies, but 16.5% in the group with CNS abnormalities plus extra ultrasound anomalies. Detection rates of SNP array were 12.4% and 20.8% in these two groups, respectively. Statistical analysis showed that the detection rates of both methods were significantly higher in the group with CNS malformations and other ultrasound anomalies than in the group with isolated CNS anomalies. Abnormal chromosomes were detected most frequently in fetuses with holoprosencephaly.

Conclusion

Genome-wide SNP array technology can significantly improve the positive detection rate of fetuses with CNS abnormalities. Combining karyotype analysis and SNP array technology is recommended for detecting the development of fetuses with abnormal CNS.

Non-classic splicing mutation in the CPLANE1 (C5orf42) gene cause Joubert syndrome in a fetus with severe craniocerebral dysplasia

BACKGROUD

Joubert syndrome is a rare neurodevelopmental disorder characterized by clinical and genetic heterogeneity. The characteristic molar tooth sign, which resulted from cerebellar vermis hypoplasia and midbrain anomalies, is expected to be the key diagnostic feature for this disease. However, it is not easy to make a definite diagnosis in prenatal only based on the imageology due to its clinical heterogeneity.

CASE REPORT

We report on a fetus who was detected cerebellum dysplasia and encephalocele by ultrasound at 19 and 23 gestational weeks and confirmed by MRI examination. The pregnancy was terminated at 23 weeks of gestation. Postaxial polydactyly and deficiency in occipital bone and skin were identified in the induced fetus.

RESULTS

The whole exome sequencing identified a novel compound heterozygous variation in the CPLANE1 gene related with Joubert syndrome, including a 2-bp insertion, NM_023073.3:c.1383_1384dup; p.(Gly462Glufs*3) and a non-classic splicing variation, NC_000005.10(NM_023073.3):c.7691-5_7691-4del. The pathogenicity of the non-classic splicing variation was further confirmed by cDNA level sequencing, which showed a exon 39 skipping that would introduce a premature termination. The novel compound heterozygous variation caused a complete function loss of the CPLANE1 gene.

CONCLUSION

The cerebellum dysplasia fetus without obvious molar tooth sign was finally diagnosed as Joubert syndrome, combined with genetic detecting and the postnatal clinical symptoms. We also highlight the clinical heterogeneity of encephalodysplasia in Joubert syndrome, which increases the clinical diagnosis difficulty, especially for prenatal diagnosis. Our findings provided a new perspective for the prenatal diagnosis of Joubert syndrome with severe craniocerebral dysplasia and expanded the variation spectrum of the CPLANE1 gene.

Geographic distribution of live births and infant mortality from congenital anomalies in Brazil, 2012-2017

In the 2010-2014 period, the mean prevalence of congenital anomalies (CA) in the world was estimated at 398/10,000 births. CA are an important cause of mortality, disability, and comorbidity. Thus, the present study aims to describe the geographical and temporal distributions of live births and infant mortality (IM) due CA (IM-CA) in Brazil, from 2012 to 2017. The data used in this study is available at the Department of Informatics of the Unified Health System (DATASUS). The prevalence of CA at birth was 81.67/10,000 (95% CI 80.46-82.88), and the IM-CA rate was 27.97/10,000 (95% CI 27.95-28.00) in the studied period. The five CA with the highest rates were polydactyly (9.66/10,000, 95% CI 6.10-9.82), Down syndrome (3.40/10,000, 95% CI 3.41-5.99), microcephaly (2.92/10,000, 95% CI 2.91-3.12), hydrocephalus (2.72/10,000, 95% CI 2.65-2.90), and spina bifida (2.44/10,000, 95% CI 2.43-2.64). São Paulo was the Brazilian state with the highest CA birth rate (119.3/10,000), and Amazonas was the state with the highest IM-CA rate (33.8/10,000). The description and data analyses such as those performed in this work are relevant for healthcare systems and can be very useful in the formulation of public health campaigns and policies, as well as informing and educating professionals and the population. The management of clinical actions should consider all social, economic, geographic, and epidemiological factors.

Cross-sectional quantitative analysis of the natural history of TUBA1A and TUBB2B tubulinopathies

Purpose

TUBA1A and TUBB2B tubulinopathies are rare neurodevelopmental disorders characterized by cortical and extracortical malformations and heterogenic phenotypes. There is a need for quantitative clinical endpoints that will be beneficial for future diagnostic and therapeutic trials.

Methods

Quantitative natural history modeling of individuals with TUBA1A and TUBB2B tubulinopathies from clinical reports and database entries of DECIPHER and ClinVar. Main outcome measures were age at disease onset, survival, and diagnostic delay. Phenotypical, neuroradiological, and histopathological features were descriptively illustrated.

Results

Mean age at disease onset was 4 (TUBA1A) and 6 months (TUBB2B), respectively. Mortality was equally estimated with 7% at 3.2 (TUBA1A) and 8.0 years (TUBB2B). Diagnostic delay was significantly higher in TUBB2B (12.3 years) compared with TUBA1A tubulinopathy (4.2 years). We delineated the isotype-dependent clinical, neuroradiological, and histopathological phenotype of affected individuals and present brain malformations associated with epilepsy and an unfavorable course of disease.

Conclusion

The natural history of tubulinopathies is defined by the genotype and associated brain malformations. Defined data on estimated survival, diagnostic delay, and disease characteristics of TUBA1A and TUBB2B tubulinopathy will help to raise disease awareness and encourage future clinical trials to optimize genetic testing, family counseling, and supportive care.

Prenatal genetic considerations in congenital ventriculomegaly and hydrocephalus

BACKGROUND

Fetal ventriculomegaly (VM) is a frequent finding in prenatal ultrasound. Rather than a proper diagnosis, VM is a sonographic sign, making prenatal counseling a complex and challenging undertaking. VM can range from severe pathologic processes leading to severe neurodevelopmental delay to normal variants.

DISCUSSION

A growing number of genetic conditions with different pathophysiological mechanisms, inheritance patterns, and long-term prognosis have been associated both to isolated and complex fetal VM. These include chromosomal abnormalities, copy number variants, and several single gene diseases. In this review, we describe some of the most common genetic conditions associated with fetal VM and provide a simplified diagnostic workflow for the clinician.

Detection of submicroscopic chromosomal aberrations by chromosomal microarray analysis for the prenatal diagnosis of central nervous system abnormalities

Background

Central nervous system (CNS) abnormalities are a group of serious birth defects associated with high rates of stillbirths, infant death, or abnormal development, and various disease‐causing copy number variations play a much more important role in the etiology of CNS abnormalities. This study intends to present a retrospective study of the prenatal diagnosis and the pregnancy outcome of fetuses diagnosed with CNS abnormalities, and evaluate the clinical value of chromosomal microarray analysis (CMA) in prenatal diagnosis of CNS abnormalities.

Methods

A total of 356 fetuses with CNS abnormalities with or without other ultrasound abnormalities subjected to invasive prenatal diagnosis at the first affiliated hospital of Air Force Medical University from January 2015 to August 2018. All cases have performed both karyotyping and CMA concurrently, but 20 fetuses with chromosome aneuploidy were excluded in the current study.

Results

The CMA identified pathogenic copy number variants (pCNVs) in 27/336 (8.03%) fetuses, likely pCNVs in 8/336 (2.38%) fetuses, and variants of unknown significance (VOUS) in 11/336 (3.27%) fetuses. A total of 222 cases had single CNS abnormalities and the pCNVs detection rate was 5.86% (13/222), the remaining 114 cases including CNS abnormalities plus other structural abnormalities, ultrasonographic soft markers and two or more CNS abnormalities, the pCNVs detection rate was 12.3% (14/114).

Conclusions

Fetuses with CNS abnormalities have a higher risk of chromosomal abnormalities, our study showed that CNVs play an important role in the etiology of CNS abnormalities. The application of CMA could increase the detection rate of pCNVs causing CNS abnormalities.

Prenatal ultrasound findings of holoprosencephaly spectrum: Unusual associations

OBJECTIVE

The objective of this study is to evaluate the prenatal diagnosis, postnatal characteristics, and the spectrum of associated findings in fetuses with holoprosencephaly (HPE).

METHODS

Fetal neurosonograms, postnatal assessment, and chromosomal analysis were performed in a cohort of 25 fetuses with HPE.

RESULTS

The prevalence of HPE in high-risk pregnancies was 4.4:10 000. The alobar subtype was the most frequently encountered, with 17 cases (68%). Interestingly, among them, four cases (16%) presented with the rare agnathia-otocephaly complex. Chromosomal abnormalities were detected in 11 cases (44%), the most frequent being trisomy 13 in seven cases (five alobar, one semilobar, and one lobar HPE), followed by trisomy 18 in two cases with semilobar HPE. One case of alobar HPE had 45, XX, t(18;22) (q10;q10), -18p karyotyping, and one case of semilobar HPE was associated with triploidy. Facial malformations in HPE spectrum ranged from cyclopia, proboscis, and arrhinia that were associated with the alobar subtype to hypotelorism and median cleft that were frequent among the semilobar and lobar subtypes. Associated neural tube defects were identified in 12% of cases.

CONCLUSION

Our study illustrates the clinical and genetic heterogeneity of HPE and describes different chromosomal abnormalities associated with HPE.

Dual Myelomeningoceles in Twins: Case Report, Review, and Insights for Etiology

INTRODUCTION

Despite folate supplementation, neural tube defects (NTDs) still occur in 0.5-1.0/1,000 pregnancies, with 30-50% not preventable with folate. Twinning has increased due to artificial fertilization and in itself predisposes to NTDs at a rate of 1.6/1,000. The contributions of genetic and environmental factors to myelomeningocele development remain poorly understood. Expression patterns of congenital pathologies in twins can sometimes provide etiological insight. Concordance of NTDs in twins is 0.03/1,000, with dual myelomeningocele reported in only 23 pairs, only one of which survived. We present the 24th pair, the 1st to maintain lower extremity motor function. We review all prior cases and discuss implications of twin concordance on the interplay of genetic and environmental influences. Case Report and Review: A new case of female monozygotic twins born to a well-nourished 24-year-old female is reported with details of perioperative care. Prenatal ultrasound showed L3-S4 and L5-S4 myelomeningoceles, Chiari II malformations, and ventriculomegaly. Copy number microarray was unrevealing. Each underwent uncomplicated repair on day of life 1, and ventriculoperitoneal shunt placement on days of life 10 and 16. Both had movement in the legs upon 6-week follow-up. All prior reported cases of concordant twin myelomeningoceles were abstracted and analyzed, revealing persistence of occurrence despite folate supplementation and a majority occurring in dizygotic pairs. The literature is also reviewed to summarize current knowledge of myelomeningocele pathophysiology as it relates to genetic and environmental influences.

DISCUSSION

Meticulous surgical and perioperative care allowed for early positive outcomes in each twin. However, etiopathogenesis remains elusive. In general, only of a minority of cases have underlying genetic lesions or clear environmental triggers. Concordance in monozygotic twins argues for a strong genetic influence; yet, literature review reveals a higher rate of concordant dizygotic twins. This, along with the observation of differing resultant phenotypes in monozygotic twins as seen in this case, prompts further investigation into nonfolate environmental influences. While efforts in genetic investigation should continue, the role of teratogens and exposures should not be minimized in research efforts, public health, and family counseling. Clinical genetic testing remains of limited utility in the majority of patients until more is known.