A novel variant in IFT122 associated with a severe phenotype of cranioectodermal dysplasia.

A 27-year-old multiparous woman conceived her fetus naturally. Early second-trimester ultrasound showed short extremities with systemic subcutaneous edema. The pregnancy was artificially terminated at 19 weeks of gestation because of the abnormalities based on the parents' wishes. The parents desired whole-exome sequencing to detect a causative gene using the umbilical cord and the parents' saliva. Compound heterozygous variants (NC_000003.11(NM_052989.3):c.230 T > G/NC_000003.11(NM_052985.4):c.1178A > T) were identified. We described a fetus with a novel compound heterozygous variant in IFT122. The phenotype of this case was severer than of other types of cranioectodermal dysplasia.

Clinical features of fetal hydrothorax associated with mucopolysaccharidosis-VII.

Mucopolysaccharidosis (MPS)-VII, called Sly disease, is a lysosomal storage disorder that can cause fetal hydrops, including fetal hydrothorax (FHT). We describe two fetal cases that received thoracoamniotic shunting for FHT, which was later found to be associated with MPS-VII by exome sequencing. Bilateral FHT accompanied by skin edema and ascites was found before 20 weeks of gestation in both cases. One fetus died in utero at 35 weeks of gestation, and the other survived with preterm delivery at 30 weeks of gestation. Both cases inherited compound pathogenic variants of GUSB from parents. Comparison with previously reported primary FHT cases revealed distinct clinical features in MPS-VII-associated FHT: early gestational age at diagnosis (<26 weeks), bilateral effusion, skin edema with ascites, and poor survival. A genetic analysis would be considered for FHT cases, with consideration of shunting when they show early-onset bilateral effusions with skin edema and ascites.

A novel FLNA variant in a fetus with skeletal dysplasia.

Otopalatodigital spectrum disorder (OPDSD) is characterized by variable phenotypes, including skeletal dysplasia, and is caused by pathogenic variants in filamin A-encoding FLNA. FLNA variants associated with lethal OPDSD primarily alter the CH2 subdomain of the ABD of FLNA. Herein, we report a novel FLNA mutation in a fetus with severe skeletal dysplasia in a pregnant multigravida female with a history of repeated miscarriages and terminations.

Automated urinary sediment detection for Fabry disease using deep-learning algorithms.

Fabry disease is a congenital lysosomal storage disease, and most of these cases develop organ damage in middle age. There are some promising therapeutic options for this disorder, which can stabilize the progression of the disease. However, a long delay in diagnosis prevents early intervention, resulting in treatment failure. Because Fabry disease is a rare disease, it is not well recognized and disease specific screening tests are rarely performed. Hence, a novel approach to for detecting patients with a widely practiced clinical test is crucial for the early detection of the disease. Recently, decision support systems based on artificial intelligence (AI) have been developed in many clinical fields. However, the construction of these models requires datasets from a large number of samples; this aspect is one of the main obstacles in AI-based approaches for rare diseases. In this study, with a novel image amplification method to construct the dataset for AI-model training, we built the deep neural-network model to detect Fabry cases from their urine samples. Sensitivity, specificity, and the AUC of the models on validation dataset were 0.902 (95% CI, 0.900-0.903), 0.977 (0.950-0.980), and 0.968 (0.964-0.972), respectively. This model could also extract disease-specific findings that are interpretable with human recognition. These results indicate that we can apply novel AI models for rare diseases based on this image amplification method we developed. We expect this approach could contribute to the diagnosis of Fabry disease. Synopsis: This is the first reported AI-based decision support system to detect undiagnosed Fabry cases, and our new image amplification method will contribute to the AI models for other rare disorders.

Multisite assessment of the impact of a prenatal testing educational App on patient knowledge and preparedness for prenatal testing decision making.

In this study, we wanted to assess the impact of the use of a patient educational app on patient knowledge about noninvasive prenatal testing (NIPT) and preparedness for prenatal screening decision-making. A randomized control study was carried out at three international sites between January 2019 and October 2020. Study participants completed a pre-consultation survey and post-consultation survey to assess knowledge, satisfaction, and preparedness for prenatal screening consultation. Providers completed a post-consultation survey. In the control arm, the pre-consultation survey was completed prior to consultation with their prenatal care provider. In the intervention arm, the pre-consultation survey was completed after using the app but prior to consultation with their prenatal care provider. Mean knowledge scores in the 203 participants using the app were significantly higher pre-consultation (p < 0.001) and post-consultation (p < 0.005) than those not using the app. Higher pre-consultation knowledge scores in the intervention group were observed at all sites. Most (86%) app users stated they were "Satisfied" or "Very Satisfied" with it as a tool. Providers rated the intervention group as more prepared than controls (p = 0.027); provider assessment of knowledge was not significantly different (p = 0.073). This study shows that clinical implementation of a patient educational app in a real-world setting was feasible, acceptable to pregnant people, and positively impacted patient knowledge.

Collection of 2429 constrained headshots of 277 volunteers for deep learning.

Deep learning has rapidly been filtrating many aspects of human lives. In particular, image recognition by convolutional neural networks has inspired numerous studies in this area. Hardware and software technologies as well as large quantities of data have contributed to the drastic development of the field. However, the application of deep learning is often hindered by the need for big data and the laborious manual annotation thereof. To experience deep learning using the data compiled by us, we collected 2429 constrained headshot images of 277 volunteers. The collection of face photographs is challenging in terms of protecting personal information; we therefore established an online procedure in which both the informed consent and image data could be obtained. We did not collect personal information, but issued agreement numbers to deal with withdrawal requests. Gender and smile labels were manually and subjectively annotated only from the appearances, and final labels were determined by majority among our team members. Rotated, trimmed, resolution-reduced, decolorized, and matrix-formed data were allowed to be publicly released. Moreover, simplified feature vectors for data sciences were released. We performed gender and smile recognition by building convolutional neural networks based on the Inception V3 model with pre-trained ImageNet data to demonstrate the usefulness of our dataset.

Confined placental mosaicism of trisomy 6 detected through genome-wide NIPT was associated with placental abruption.

Confined placental mosaicism (CPM) leads to discordant noninvasive prenatal testing (NIPT) results. We describe a very rare case of CPM of trisomy 6 detected through genome-wide NIPT. This case was associated with placental abruption, which might suggest an association between certain types of CPM detected by NIPT and pregnancy complications.

Awareness of paternal age effect disorders among Japanese pregnant women: implications for prenatal genetic counseling for advanced paternal age.

The increasing prevalence of advanced paternal age (APA) has mirrored the rise in maternal age. APA is associated with an increased risk of de novo pathogenic single-nucleotide variants, but this topic has been much less frequently discussed than advanced maternal age (AMA). To explore the awareness of pregnant women regarding paternal age effect (PAE) disorders, a self-administered questionnaire survey was conducted for pregnant women at their first prenatal visit before 17 weeks of gestation. A total of 120 valid respondents (95.2%) were included in the analyses. Of these, 63.3% of pregnant women were aware of PAE disorders. This was markedly lower than the 90.8% recognition of maternal age effect (MAE) disorders. One-third of women with awareness of MAE disorders were not aware of PAE disorders. Pregnant women who were parous, older than their male partners, with knowledge of prenatal testing prior to this pregnancy, and with experience of prenatal testing in a prior pregnancy were significantly more aware of PAE disorders than others. Awareness of PAE disorders was not associated with undergoing prenatal testing during the present pregnancy. Our results show that the prevalence of pregnant women's awareness of PAE disorders was lower than that of MAE disorders. The current study served as a preliminary baseline of information about pregnant women's awareness of PAE disorders. With the introduction of non-invasive prenatal testing, which has the potential to identify PAE disorders, these findings will help the development of a framework for comprehensive prenatal genetic counseling for APA pregnancies.

Pregnant women's opinions toward prenatal pretest genetic counseling in Japan.

In-person models of genetic counseling (GC) have been the common method in Japan for pregnant women to receive GC. However, recent increases in the number of pregnant women considering undergoing prenatal testing have made it challenging to retain individualized in-person care. To explore pregnant women's opinions toward pretest GC models and the ideal time duration, a self-administered questionnaire survey was conducted for women at their first prenatal visit. A total of 114 valid respondents (93.4%) were included in the analyses. Of these, 80.7% of women preferred in-person GC, followed by classroom (9.6%), group (3.5%), and telegenetic-based GC (2.6%). Women with experience in undergoing prenatal testing significantly did not prefer in-person GC (p = 0.05). Sixty-two women (54.4%) preferred a duration of 15-29 min for pretest GC sessions, followed by 30-59 min (28.9%) and <15 min (14.9%). Women's preference of ≥30 min in length was significantly associated with anhedonia, singleton pregnancies, acquaintance with people with trisomy 21, and awareness of prenatal testing. Women who were unaware of the need for agreement with the partner for prenatal testing and who did not know the average life expectancy of a trisomy 21 patient significantly preferred <15 min in length over other durations. While the majority of women preferred in-person GC for <30 min, their preferences varied by their background characteristics, experiences, attitudes, and knowledge. These findings will help establish a prenatal GC system offering a choice of GC models in Japan; however, further large-scale studies are needed to confirm these findings.