Diagnosis Of Genetic Syndromes Research Articles

Computer-aided facial analysis as a tool to identify patients with Silver–Russell syndrome and Prader–Willi syndrome

Genetic syndromes often show facial features that provide clues for the diagnosis. However, memorizing these features is a challenging task for clinicians. In the last years, the app Face2Gene proved to be a helpful support for the diagnosis of genetic diseases by analyzing features detected in one or more facial images of affected individuals. Our aim was to evaluate the performance of the app in patients with Silver–Russell syndrome (SRS) and Prader–Willi syndrome (PWS). We enrolled 23 pediatric patients with clinically or genetically diagnosed SRS and 29 pediatric patients with genetically confirmed PWS. One frontal photo of each patient was acquired. Top 1, top 5, and top 10 sensitivities were analyzed. Correlation with the specific genetic diagnosis was investigated. When available, photos of the same patient at different ages were compared. In the SRS group, Face2Gene showed top 1, top 5, and top 10 sensitivities of 39%, 65%, and 91%, respectively. In 41% of patients with genetically confirmed SRS, SRS was the first syndrome suggested, while in clinically diagnosed patients, SRS was suggested as top 1 in 33% of cases (p = 0.74). Face2Gene performed better in younger patients with SRS: in all patients in whom a photo taken at a younger age than the age of enrollment was available, SRS was suggested as top 1, albeit with variable degree of probability. In the PWS group, the top 1, top 5, and top 10 sensitivities were 76%, 97%, and 100%, respectively. PWS was suggested as top 1 in 83% of patients genetically diagnosed with paternal deletion of chromosome 15q11-13 and in 60% of patients presenting with maternal uniparental disomy of chromosome 15 (p = 0.17). The performance was uniform throughout the investigated age range (1–15 years).Conclusion: In addition to a thorough medical history and detailed clinical examination, the Face2Gene app can be a useful tool to support clinicians in identifying children with a potential diagnosis of SRS or PWS.What is Known:• Several genetic syndromes present typical facial features that may provide clues for the diagnosis.• Memorizing all syndromic facial characteristics is a challenging task for clinicians.What is New:• Face2Gene may represent a useful support for pediatricians for the diagnosis of genetic syndromes.• Face2Gene app can be a useful tool to integrate in the diagnostic path of patients with SRS and PWS.

Comparing 2D and 3D representations for face-based genetic syndrome diagnosis.

Human genetic syndromes are often challenging to diagnose clinically. Facial phenotype is a key diagnostic indicator for hundreds of genetic syndromes and computer-assisted facial phenotyping is a promising approach to assist diagnosis. Most previous approaches to automated face-based syndrome diagnosis have analyzed different datasets of either 2D images or surface mesh-based 3D facial representations, making direct comparisons of performance challenging. In this work, we developed a set of subject-matched 2D and 3D facial representations, which we then analyzed with the aim of comparing the performance of 2D and 3D image-based approaches to computer-assisted syndrome diagnosis. This work represents the most comprehensive subject-matched analyses to date on this topic. In our analyses of 1907 subject faces representing 43 different genetic syndromes, 3D surface-based syndrome classification models significantly outperformed 2D image-based models trained and evaluated on the same subject faces. These results suggest that the clinical adoption of 3D facial scanning technology and continued collection of syndromic 3D facial scan data may substantially improve face-based syndrome diagnosis.

Functional correlation of genome-wide DNA methylation profiles in genetic neurodevelopmental disorders.

An expanding range of genetic syndromes are characterized by genome-wide disruptions in DNA methylation profiles referred to as episignatures. Episignatures are distinct, highly sensitive, and specific biomarkers that have recently been applied in clinical diagnosis of genetic syndromes. Episignatures are contained within the broader disorder-specific genome-wide DNA methylation changes, which can share significant overlap amongdifferent conditions. In this study, we performed functional genomic assessment and comparison of disorder-specific and overlapping genome-wide DNA methylation changes related to 65 genetic syndromes with previously described episignatures. We demonstrate evidence of disorder-specific and recurring genome-wide differentially methylated probes (DMPs) and regions (DMRs). The overall distribution of DMPs and DMRs across the majority of the neurodevelopmental genetic syndromes analyzed showed substantial enrichment in gene promoters and CpG islands, and under-representation of the more variable intergenic regions. Analysis showed significant enrichment of the DMPs and DMRs in gene pathways and processes related to neurodevelopment, including neurogenesis, synaptic signaling and synaptic transmission. This study expands beyond the diagnostic utility of DNA methylation episignatures by demonstrating correlation between the function of the mutated genes and the consequent genomic DNA methylation profiles as a key functional element in the molecular etiology of genetic neurodevelopmental disorders.

Multi-Scale Part-Based Syndrome Classification of 3D Facial Images

Identification and delineation of craniofacial characteristics support the clinical and molecular diagnosis of genetic syndromes. Deep learning (DL) frameworks for syndrome identification from 2D facial images are trained on large clinical datasets using standard convolutional neural networks for classification. In contrast, despite the increased availability of 3D scanners in clinical setups, similar frameworks remain absent for 3D facial photographs. The main challenges involve working with smaller datasets and the need for DL operations applicable to 3D geometric data. Therefore, to date, most 3D methods refrain from working across multiple syndromic groups and/or are solely based on traditional machine learning. The first contribution of this work is the use of geometric deep learning with spiral convolutions in a triplet-loss architecture. This geometric encoding (GE) learns a lower dimensional metric space from 3D facial data that is used as input to linear discriminant analysis (LDA) performing multiclass classification. Benchmarking is done against principal component analysis (PCA), a common technique in 3D facial shape analysis, and related work based on 65 distinct 3D facial landmarks as input to LDA. The second contribution of this work involves a part-based implementation to 3D facial shape analysis and multi-class syndrome classification, and this is applied to both GE and PCA. Based on 1,786 3D facial photographs of controls and individuals from 13 different syndrome classes, a five-fold cross-validation was used to investigate both contributions. Results indicate that GE performs better than PCA as input to LDA, and this especially so for more compact (lower dimensional) spaces. In addition, a part-based approach increases performance significantly for both GE and PCA, with a more significant improvement for the latter. I.e., this contribution enhances the power of the dataset. Finally, and interestingly, according to ablation studies within the part-based approach, the upper lip is the most distinguishing facial segment for classifying genetic syndromes in our dataset, which follows clinical expectation. This work stimulates an enhanced use of advanced part-based geometric deep learning methods for 3D facial imaging in clinical genetics.

Development and evaluation of a machine learning-based point-of-care screening tool for genetic syndromes in children: a multinational retrospective study

Delays in the diagnosis of genetic syndromes are common, particularly in low and middle-income countries with limited access to genetic screening services. We, therefore, aimed to develop and evaluate a machine learning-based screening technology using facial photographs to evaluate a child's risk of presenting with a genetic syndrome for use at the point of care. In this retrospective study, we developed a facial deep phenotyping technology based on deep neural networks and facial statistical shape models to screen children for genetic syndromes. We trained the machine learning models on facial photographs from children (aged <21 years) with a clinical or molecular diagnosis of a genetic syndrome and controls without a genetic syndrome matched for age, sex, and race or ethnicity. Images were obtained from three publicly available databases (the Atlas of Human Malformations in Diverse Populations of the National Human Genome Research Institute, Face2Gene, and the dataset available from Ferry and colleagues) and the archives of the Children's National Hospital (Washington, DC, USA), in addition to photographs taken on a standard smartphone at the Children's National Hospital. We designed a deep learning architecture structured into three neural networks, which performed image standardisation (Network A), facial morphology detection (Network B), and genetic syndrome risk estimation, accounting for phenotypic variations due to age, sex, and race or ethnicity (Network C). Data were divided randomly into 40 groups for cross validation, and the performance of the model was evaluated in terms of accuracy, sensitivity, and specificity in both the total population and stratified by race or ethnicity, age, and sex. Our dataset included 2800 facial photographs of children (1318 [47%] female and 1482 [53%] male; 1576 [56%] White, 432 [15%] African, 430 [15%] Hispanic, and 362 [13%] Asian). 1400 children with 128 genetic conditions were included (the most prevalent being Williams-Beuren syndrome [19%], Cornelia de Lange syndrome [17%], Down syndrome [16%], 22q11.2 deletion [13%], and Noonan syndrome [12%] syndrome) in addition to 1400 photographs of matched controls. In the total population, our deep learning-based model had an accuracy of 88% (95% CI 87-89) for the detection of a genetic syndrome, with 90% sensitivity (95% CI 88-92) and 86% specificity (95% CI 84-88). Accuracy was greater in White (90%, 89-91) and Hispanic populations (91%, 88-94) than in African (84%, 81-87) and Asian populations (82%, 78-86). Accuracy was also similar in male (89%, 87-91) and female children (87%, 85-89), and similar in children younger than 2 years (86%, 84-88) and children aged 2 years or older (eg, 89% [87-91] for those aged 2 years to <5 years). This genetic screening technology could support early risk stratification at the point of care in global populations, which has the potential accelerate diagnosis and reduce mortality and morbidity through preventive care. Children's National Hospital and Government of Abu Dhabi.

Fetal micrognathia in the first trimester: An ominous finding even after a normal array

ObjectiveTo evaluate the prognosis of fetuses with a prenatal diagnosis of micrognathia in the first trimester. Study designOver a 3-year period, patients with fetal micrognathia were detected at the time of nuchal translucency screening. The medical records of these pregnancies were reviewed, including maternal demographics, sonographic findings, genetic testing results and pregnancy outcomes. ResultsForty-three cases of first-trimester micrognathia were included in this study. Chromosomal abnormalities were detected in seven cases. Of the fetuses with a normal array, further investigation of monogenic disorders with whole-exome sequencing was undertaken in 13 cases. Monogenic syndromes were identified in eight cases, including six with de-novo dominant alleles and two with recessive conditions. Whole-exome sequencing was refused in 23 cases; among these, other additional anomalies were found on anatomic ultrasound in 10 cases. ConclusionThis study demonstrated that caution should be adopted when finding an apparently isolated micrognathia in early gestation, even with a normal array. A diagnosis of genetic syndrome or multiple anomalies on subsequent scans is most likely, and will affect the final prognosis.

Dysmorphology : an approach for diagnosis of genetic syndromes

Dysmorphology : an approach for diagnosis of genetic syndromes

Computer-aided Facial Analysis in Diagnosing Dysmorphic Syndromes in Indian Children

To assess the utility of computer-aided facial analysis in identifying dysmorphic syndromes in Indian children. Fifty-one patients with a definite molecular or cytogenetic diagnosis and recognizable facial dysmorphism were enrolled in the study and their facial photographs were uploaded in the Face2Gene software. The results provided by the software were compared with the molecular diagnosis. Of the 51 patients, the software predicted the correct diagnosis in 37 patients (72.5%); predicted as the first in the top ten suggestions in 26 (70.2%). In 14 patients, the software did not suggest a correct diagnosis. Computer-aided facial analysis is a method that can aid in diagnosis of genetic syndromes in Indian children. As more clinicians start to use this software, its accuracy is expected to improve.

EPID-11. OCCURRENCE OF SYSTEMIC CANCER IN PATIENTS WITH GLIOBLASTOMA: POPULATION CHARACTERIZATION AND COMPLICATIONS

Abstract It is unclear how the diagnosis of a second cancer influences the treatment and complications of patients with glioblastoma (GBM). A chart review of adults with primary or secondary GBM and another systemic cancer seen in the last five years was performed. Demographic data, thromboembolic events, cytopenia and deviations from the standardized GBM treatment protocol (EBRT with 60 Gy plus concurrent temozolomide followed by adjuvant temozolomide) were analyzed. Exclusion criteria was the diagnosis of genetic syndromes that predispose to tumorigenesis. A total of 56 GBM patients with 61 systemic cancers were identified. The most common systemic cancers were breast and prostate each representing 27 %. Men were 55% of patients (p=0.3) but older (69+11 years, p=0.003) than when compared to CBTRUS data. Systemic cancer was diagnosed before GBM in 82% of the cases. Age at the diagnosis of systemic cancer was 64 +11 years. Patients with systemic cancer diagnosed prior to GBM, had shorter survival (1.15+1.08 years versus 4.4+ 3.4 years, p &lt; 0.001), but survival was not shorter than expected when compared to historical survival of GBM. Thromboembolism was seen in 27% of patients, only once it was seen before the diagnosis of GBM. Although all patients with hematological malignancies had low platelets, thrombocytopenia was not associated to prior chemotherapy. Deviation of GBM treatment was seen in 15% of the cases, a delay in the systemic cancer once. This is the largest documented series of patients with GBM and systemic cancer. We conclude that although this population is older than expected, thromboembolism rates and survival are similar to the literature for patients with GBM. In the light of all those considerations, patients with GBM and the diagnosis of a systemic cancer should be treated according to guideline.

EPID-14. OCCURRENCE OF SYSTEMIC CANCER IN PATIENTS WITH OLIGODENDROGLIOMAS: POPULATION CHARACTERIZATION AND COMPLICATIONS

Abstract Following clinic observations of patients with the diagnosis of oligodendroglioma and a systemic cancer, a chart review was done to understand the possible complications that a systemic cancer might bring to the treatment of the patient. Inclusion criteria was histological diagnosis of diffuse or anaplastic oligodendroglioma and another non-skin systemic cancer. Exclusion criteria was the diagnosis of genetic syndrome that predispose tumorigenesis. A total of 12 patients and 13 cancers were identified. 1p19q co-delection information was available for all patients except for 2. The most common systemic cancers were breast (46%) and gynecological cancers (16%). Different from CBTRUS data, men were underrepresented, being 31% of the patients, but difference did not reach statistical significance (p =0.08). Regarding age, patients were older than expected (53 + 12 years old, p&lt; 0.0001). Systemic cancer was diagnosed after the oligodendroglioma diagnosis in 54% of the cases. Age at the diagnosis of systemic cancer was 54 + 10 years old. All patients are alive, except for two. Thromboembolism was seen in 25% of the patients (p=0.2 when comparing with literature for oligodendroglioma), and occurred always after the oligodendroglioma diagnosis. Thrombocytopenia was not associated to prior chemotherapy. No deviation of glioma treatment was seen. This chart review of patients with Oligodendroglioma and a systemic cancer identifies that this population is older than expected and thromboembolism rates are similar to the literature. The overrepresentation of women in this cohort represents the profile of systemic cancer that accompanied oligodendrogliomas. It is unclear why breast and other gynecological cancers were the most common. Further studies, likely multicentric due to the rarity of this diagnosis, as further research in large repository data should be performed to confirm this finding.

Fetal megacystis: a lot more than LUTO.

ABSTRACTObjectiveFetal megacystis presents a challenge in terms of counseling and management because of its varied etiology and evolution. The aim of this study was to present a comprehensive overview of the underlying etiologies and structural anomalies associated with fetal megacystis.MethodsThis was a retrospective multicenter study of cases referred to the fetal medicine unit of one of the eight academic hospitals in The Netherlands with a diagnosis of fetal megacystis. For each case, data on and measurements of fetal urinary tract and associated structural anomalies were collected. All available postmortem examinations and postnatal investigations were reviewed in order to establish the final diagnosis. In the first trimester, fetal megacystis was defined as longitudinal bladder diameter (LBD) ≥ 7 mm, and in the second and third trimesters as an enlarged bladder failing to empty during an extended ultrasound examination lasting at least 40 min.ResultsOf the 541 pregnancies with fetal megacystis, it was isolated (or solely accompanied by other signs of lower urinary tract obstruction (LUTO)) in 360 (67%) cases and associated with other abnormal ultrasound findings in 181 (33%) cases. The most common associated ultrasound anomaly was an increased nuchal translucency thickness (22%), followed by single umbilical artery (10%) and cardiac defect (10%). A final diagnosis was established in 418 cases, including 222 (53%) cases with isolated LUTO and 60 (14%) infants with normal micturition or minor isolated urological anomalies. In the remaining 136 (33%) cases, concomitant developmental or chromosomal abnormality or genetic syndrome was diagnosed. Overall, 40 chromosomal abnormalities were diagnosed, including trisomy 18 (n = 24), trisomy 21 (n = 5), Turner syndrome (n = 5), trisomy 13 (n = 3) and 22q11 deletion (n = 3). Thirty‐two cases presented with anorectal malformations involving the anus, rectum and urogenital tract. In cases with confirmed urethral and anal atresia, megacystis occurred early in pregnancy and the bladder appeared severely distended (the LBD (in mm) was equal to or greater than twice the gestational age (in weeks)). Fetal macrosomia was detected in six cases and an overgrowth syndrome was detected in four cases, comprising two infants with Beckwith–Wiedemann syndrome and two with Sotos syndrome. Megacystis‐microcolon‐intestinal hypoperistalsis syndrome was diagnosed in five (1%) cases and prenatally suspected only in one case.ConclusionsAlthough the main cause of fetal megacystis is LUTO, an enlarged fetal bladder can also be present as a concomitant finding of miscellaneous genetic syndromes, developmental disturbances and chromosomal abnormalities. We provide an overview of the structural anomalies and congenital disorders associated with fetal megacystis and propose a practical guide for the differential diagnosis of genetic syndromes and chromosomal and developmental abnormalities in pregnancies presenting with fetal megacystis, focusing on the morphological examination of the fetus. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Application of human face recognition technology in genetic syndrome diagnosis

Genetic syndromes often involve craniofacial malformations, and certain syndromes are associated with a specific facial pattern such as Down syndrome.With the development of artificial intelligence in the medical field, face recognition technology has been successfully applied in the diagnosis of genetic syndrome, such as Down syndrome, Cornelia de Lange syndrome, 22q11.2 deletion syndrome and Noonan syndrome.Some reports suggested that the detection rates of face recognition technology are higher than clinical specialists.In the future, face recognition technology is expected to be applied in the screening of and genetic syndromes, to help the diagnosis and to be applied in scientific research. Key words: Human face recognition technology; Genetic syndrome; Medical diagnosis

P40 Analysis of Family Clustering in Lung Cancer (LC): Genetic Cancer Risk Assessment (GRCA) into the Thoracic Oncology Unit

Inherited susceptibility for lung cancer (LC) has been described, a recent paper showed that 2.5% of LC patients (pts) carried a pathogenic germline variation in genes such ATM, TP53, BRCA2, EGFR, and PARK2. Some of those genes cause well recognized syndromes. Thus, GRCA for LC could help to identify a genetic predisposition syndrome, guide genetic testing, offering specific treatments and genetic counseling. This is a retrospective and descriptive study. We performed a review of 66 medical records of LC pts diagnosed between 2011 and 2016. We collected age at diagnosis, smoking, previous cancer diagnosis, and family history (FH) for cancer: number of affected family members and sort of cancer. Genetic evaluation and testing was not available at time of first evaluation, but we tried to identify genetic syndromes according to the clustering pattern and NCCN criteria. Mean age was 62.5 years (range 26-88y); 30 pts (45.5%) had FH with 46 affected relatives: 21 pts had at least one first degree affected member, only 2 pts had more than 3 affected members. Among the tumors, Breast cancer (BrCa) was found in 12 family members; one pt had a previous BrCa diagnosis at 33y; LC was found in 1 relative; 4 cases of colon cancer were described; 1 case was found for prostate and melanoma respectively. Other tumors were described, but they are not frequently associated to other genetic syndromes. We found no statistical differences on smoking between pts with or without FH. Pts with FH tended to be younger (p=0.026). Based on the family assessment, 8 (10.6%) cases met NCCN criteria for genetic counseling and testing for BRCA and Homologous Recombination (HR) pathway genes. Unfortunately, age of diagnosis for family members was available in 8 out 46 cases, data available were taken from the first clinical assessment which limits this analysis. Even if the expected number of pts with inherited susceptibility to LC is low, a proper GRCA could improve the diagnosis of genetic syndromes. This could bring advantages, such as offering PARP inhibitors for Pts carrying mutations in HR pathway genes, cascade screening and set up prevention measures adapted for each gene risks. Finally, more extended genetic analysis could be offered based on clinical features of index cases. At our knowledge, GRCA clinics for LC is not frequent in Mexico, these results underline the importance of setting up this clinic at our center.

An Update on the Histology of Pheochromocytomas: How Does it Relate to Genetics?

Pheochromocytomas are rare neuroendocrine tumors of the adrenal gland, whereas any extra-adrenal tumor with similar histology is designated as paraganglioma. These tumors have a very high rate of germline mutations in a large number of genes, up to 35% to 40%, frequently predisposing for other tumors as well. Therefore, they represent a phenomenal challenge for treating physicians. This review focuses on pheochromocytomas only, with special attention to gross and microscopic clues to the diagnosis of genetic syndromes, including the role of succinate dehydrogenase subunit A and subunit B immunohistochemistry as surrogate markers for genetic analysis in the field of succinate dehydrogenase subunit gene mutations.

Findings of postoperative clinical assessment of swallowing in infants with congenital heart defect.

Describe the findings of postoperative clinical evaluation of swallowing in infants with congenital heart disease (CHD) in a reference hospital in southern Brazil. This is a cross-sectional study conducted postoperatively with infants with medical diagnosis of CHD aged 0-6 months in a Pediatric Intensive Care Unit. Exclusion criteria comprised infants with neurological and respiratory impairments, craniofacial malformation, structural alteration in the upper airways, and suspicion or diagnosis of genetic syndromes. Clinical evaluation was performed through partial application of the Assessment of Pediatric Dysphagia protocol. Regarding statistical analysis, the quantitative variables were described by median and interquartile range and the qualitative variables were described by absolute and relative frequencies. Non-parametric tests were used to evaluate the associations. Of the 31 infants in the sample, 23 (74.2%) were classified with some degree of dysphagia. Significant difference was observed in the clinical evaluation performed with bottle-feeding compared with breast-feeding; a larger number of swallowing disorders was also found in bottle-feeding. Statistically significant correlation was observed between duration of orotracheal intubation (OTI) >24 h and presence of dysphagia. Postoperative clinical evaluation enabled description of swallowing impairments in infants with CHD regardless of the type of feeding offered, as well as identification of presence of dysphagia in a large number of individuals in the sample and its association with duration of OTI >24 h.

Abnormal maternal biomarkers of homocysteine and methionine metabolism and the risk of congenital heart defects

BackgroundRecent advances in genetic technology have had a significant impact on the practice of clinical genetics and the diagnosis of genetic syndromes associated with cardiac malformations. AimThe present study was aimed to determine whether biomarkers of the folic acid pathway, including homocysteine and methionine metabolism are altered among non pregnant women who have had a previous pregnancy affected by congenital heart defects. Subjects and methodsThe study was conducted on 50 women attending the Medical Genetics center and the Pediatric Cardiology Clinic, Faculty of Medicine, Ain Shams University for follow up. Mothers were subdivided into: Group 1 (Cases): 25 mothers with a history of congenital heart defects in previous children. Group 2 (Controls): 25 mothers and their children didn’t have any birth defects including congenital heart defects. In both groups women will be excluded: If they were pregnant or taking folate antagonist medications (antiepileptic drugs) or vitamin supplementations at the time of the study. Measurement of plasma concentration of: Vitamin B-12, folic acid, Homocysteine, Methionine, S-adenosylmethionine (SAM) and S-adenosylhomocysteine (SAH), by using Radio immunoassay kit was done. ResultsThere is a significant difference between cases and controls as regards history of early neonatal deaths (28%) in cases versus (4%) in controls (P<0.05). The study also revealed that the most frequent congenital cardiovascular malformation is VSD (32%) followed by ASD (20%).As regards biomarker concentrations all, were significantly different between case and control subjects except for methionine. ConclusionAn elevated levels of maternal homocysteine is an independent risk factor for congenital heart defects. Finally: There is an increasing need for professionals to apply and interpret genetic testing in a clinically meaningful way for prevention of congenital heart defects.

PCA and LDA Method with Neural Network for Primary Diagnosis of Genetic Syndrome

PCA and LDA Method with Neural Network for Primary Diagnosis of Genetic Syndrome

Non‐invasive diagnosis of sweat gland dysplasia using optical coherence tomography and reflectance confocal microscopy in a family with anhidrotic ectodermal dysplasia (Christ–Siemens–Touraine syndrome)

Anhidrotic ectodermal dysplasia (AED) is an inherited syndrome, which originates mainly from genetic alteration of the ectodysplasin A (EDA) gene. It regularly affects the adnexa of the skin which results in a characteristic phenotype of the patients including hypo- or anhidrosis leading to severe disturbances in the regulation of body temperature. To prevent the development of the symptoms in early childhood promising therapeutic approaches are currently under clinical investigation. In this context, timely diagnosis of this genetic syndrome is crucial. The purpose of our study was the investigation of modern non-invasive imaging methods such as optical coherence tomography (OCT) and reflectance confocal microscopy (RCM) in the immediate diagnosis of AED. We examined a 3-year-old boy with the suspicion for an AED syndrome and his family members with RCM and OCT to document presence and characteristic features of sweat glands in comparison to non-affected individuals. The patient and the affected brother showed significantly reduced sweat glands in the imaging compared to the controls. The genetic analysis revealed a mutation of the EDA gene for hemizygosity previously associated with AED and the mother was revealed as the conductor of the genetic alteration. With the help of non-invasive imaging, we were able to detect sweat gland dysplasia in the affected family members without performing a biopsy which led us to the diagnosis of an AED. The application of modern dermatological imaging techniques might serve as valuable supplementary tools in the immediate, non-invasive diagnosis of genetic syndromes especially in newborns when early therapeutic approaches are planned.

Impact of NGS in the medical sciences: genetic syndromes with an increased risk of developing cancer as an example of the use of new technologies

The increased speed and decreasing cost of sequencing, along with an understanding of the clinical relevance of emerging information for patient management, has led to an explosion of potential applications in healthcare. Currently, SNP arrays and Next-Generation Sequencing (NGS) technologies are relatively new techniques used to scan genomes for gains and losses, losses of heterozygosity (LOH), SNPs, and indel variants as well as to perform complete sequencing of a panel of candidate genes, the entire exome (whole exome sequencing) or even the whole genome. As a result, these new high-throughput technologies have facilitated progress in the understanding and diagnosis of genetic syndromes and cancers, two disorders traditionally considered to be separate diseases but that can share causal genetic alterations in a group of developmental disorders associated with congenital malformations and cancer risk. The purpose of this work is to review these syndromes as an example of a group of disorders that has been included in a panel of genes for NGS analysis. We also highlight the relationship between development and cancer and underline the connections between these syndromes.

Congenital cataracts in two siblings with Wolfram Syndrome

Background: Wolfram syndrome is characterized by optic atrophy, insulin dependent diabetes mellitus, diabetes insipidus and deafness. There are several other associated conditions reported in the literature, but congenital or early childhood cataracts are not among them.Materials and methods: Observational case series with confirmatory genetic analysis.Results: A pair of siblings, followed over 17 years, who manifest congenital or early childhood cataracts, diabetes insipidus, diabetes mellitus, optic atrophy, and deafness. They are both compound heterozygotes for mutations (V415 deletion and A684V substitution) in the WFS1 gene. Their father has congenital sensorineural hearing loss and developed optic atrophy. He is heterozygous for A684V in WFS1.Conclusions: Wolfram syndrome should be in the differential diagnosis of genetic syndromes associated with congenital and early childhood cataracts. Here, we report on a mother who is a phenotypically normal carrier of an autosomal recessive Wolfram syndrome gene, and a father who has some of the findings of the syndrome and carries a single mutation that appears to be responsible for his hearing loss and optic atrophy. Their 2 children are compound heterozygotes and manifest the full Wolfram syndrome, in addition to cataracts.