Evaluating Face2Gene as a Tool to Identify Cornelia de Lange Syndrome by Facial Phenotypes

Characteristic or classic phenotype of Cornelia de Lange syndrome (CdLS) is associated with a recognisable facial pattern. However, the heterogeneity in causal genes and the presence of overlapping syndromes have made it increasingly difficult to diagnose only by clinical features. DeepGestalt technology, and its app Face2Gene, is having a growing impact on the diagnosis and management of genetic diseases by analysing the features of affected individuals. Here, we performed a phenotypic study on a cohort of 49 individuals harbouring causative variants in known CdLS genes in order to evaluate Face2Gene utility and sensitivity in the clinical diagnosis of CdLS. Based on the profile images of patients, a diagnosis of CdLS was within the top five predicted syndromes for 97.9% of our cases and even listed as first prediction for 83.7%. The age of patients did not seem to affect the prediction accuracy, whereas our results indicate a correlation between the clinical score and affected genes. Furthermore, each gene presents a different pattern recognition that may be used to develop new neural networks with the goal of separating different genetic subtypes in CdLS. Overall, we conclude that computer-assisted image analysis based on deep learning could support the clinical diagnosis of CdL

Digging into the admixture strata of current-day Canary Islanders based on mitogenomes

Summary: The conquest of the Canary Islands by Europeans began at the beginning of the 15th century and culminated in 1496 with the surrender of the aborigines. The collapse of the aboriginal population during the conquest and the arrival of settlers caused a drastic change in the demographic composition of the archipelago. To shed light on this historical process, we analyzed 896 mitogenomes of current inhabitants from the seven main islands. Our findings confirm the continuity of aboriginal maternal contributions and the persistence of their genetic footprints in the current population, even at higher levels (>60% on average) than previously evidenced. Moreover, the age estimates for most autochthonous founder lineages support a first aboriginal arrival to the islands at the beginning of the first millennium. We also revealed for the first time that the main recognizable genetic influences from Europe are from Portuguese and Galicians

Benchmarking of human Y-chromosomal haplogroup classifiers with whole-genome and whole-exome sequence data

In anthropological, medical, and forensic studies, the nonrecombinant region of the human Y chromosome (NRY) enables accurate reconstruction of pedigree relationships and retrieval of ancestral information. Using high-throughput sequencing (HTS) data, we present a benchmarking analysis of command-line tools for NRY haplogroup classification. The evaluation was performed using paired Illumina data from whole-genome sequencing (WGS) and whole-exome sequencing (WES) experiments from 50 unrelated donors. Additionally, as a validation, we also used paired WGS/WES datasets of 54 individuals from the 1000 Genomes Project. Finally, we evaluated the tools on data from third-generation HTS obtained from a subset of donors and one reference sample. Our results show that WES, despite typically offering less genealogical resolution than WGS, is an effective method for determining the NRY haplogroup. Y-LineageTracker and Yleaf showed the highest accuracy for WGS data, classifying precisely 98% and 96% of the samples, respectively. Yleaf outperforms all benchmarked tools in the WES data, classifying approximately 90% of the samples. Yleaf, Y-LineageTracker, and pathPhynder can correctly classify most samples (88%) sequenced with third-generation HTS. As a result, Yleaf provides the best performance for applications that use WGS and WES. Overall, our study offers researchers with a guide that allows them to select the most appropriate tool to analyze the NRY region using both second- and third-generation HTS data

Table_1_A catalog of the genetic causes of hereditary angioedema in the Canary Islands (Spain).docx

Hereditary angioedema (HAE) is a rare disease where known causes involve C1 inhibitor dysfunction or dysregulation of the kinin cascade. The updated HAE management guidelines recommend performing genetic tests to reach a precise diagnosis. Unfortunately, genetic tests are still uncommon in the diagnosis routine. Here, we characterized for the first time the genetic causes of HAE in affected families from the Canary Islands (Spain). Whole-exome sequencing data was obtained from 41 affected patients and unaffected relatives from 29 unrelated families identified in the archipelago. The Hereditary Angioedema Database Annotation (HADA) tool was used for pathogenicity classification and causal variant prioritization among the genes known to cause HAE. Manual reclassification of prioritized variants was used in those families lacking known causal variants. We detected a total of eight different variants causing HAE in this patient series, affecting essentially SERPING1 and F12 genes, one of them being a novel SERPING1 variant (c.686-12A>G) with a predicted splicing effect which was reclassified as likely pathogenic in one family. Altogether, the diagnostic yield by assessing previously reported causal genes and considering variant reclassifications according to the American College of Medical Genetics guidelines reached 66.7% (95% Confidence Interval [CI]: 30.1-91.0) in families with more than one affected member and 10.0% (95% CI: 1.8-33.1) among cases without family information for the disease. Despite the genetic causes of many patients remain to be identified, our results reinforce the need of genetic tests as first-tier diagnostic tool in this disease, as recommended by the international WAO/EAACI guidelines for the management of HAE.</p

Switching TNF antagonists in patients with chronic arthritis: An observational study of 488 patients over a four-year period

The objective of this work is to analyze the survival of infliximab, etanercept and adalimumab in patients who have switched among tumor necrosis factor (TNF) antagonists for the treatment of chronic arthritis. BIOBADASER is a national registry of patients with different forms of chronic arthritis who are treated with biologics. Using this registry, we have analyzed patient switching of TNF antagonists. The cumulative discontinuation rate was calculated using the actuarial method. The log-rank test was used to compare survival curves, and Cox regression models were used to assess independent factors associated with discontinuing medication. Between February 2000 and September 2004, 4,706 patients were registered in BIOBADASER, of whom 68% had rheumatoid arthritis, 11% ankylosing spondylitis, 10% psoriatic arthritis, and 11% other forms of chronic arthritis. One- and two-year drug survival rates of the TNF antagonist were 0.83 and 0.75, respectively. There were 488 patients treated with more than one TNF antagonist. In this situation, survival of the second TNF antagonist decreased to 0.68 and 0.60 at 1 and 2 years, respectively. Survival was better in patients replacing the first TNF antagonist because of adverse events (hazard ratio (HR) for discontinuation 0.55 (95% confidence interval (CI), 0.34-0.84)), and worse in patients older than 60 years (HR 1.10 (95% CI 0.97-2.49)) or who were treated with infliximab (HR 3.22 (95% CI 2.13-4.87)). In summary, in patients who require continuous therapy and have failed to respond to a TNF antagonist, replacement with a different TNF antagonist may be of use under certain situations. This issue will deserve continuous reassessment with the arrival of new medications. © 2006 Gomez-Reino and Loreto Carmona; licensee BioMed Central Ltd