Molecular variation of the human elastin (ELN) gene in a normal human population

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

Copy number losses (deletions) are a major contributor to the etiology of severe genetic disorders. Although haploinsufficient genes play a critical role in deletion pathogenicity, current methods for deletion pathogenicity prediction fail to integrate multiple lines of evidence for haploinsufficiency at the gene level, limiting their power to pinpoint deleterious deletions associated with genetic disorders. Here we introduce DosaCNV, a deep multiple-instance learning framework that, for the first time, models deletion pathogenicity jointly with gene haploinsufficiency. By integrating over 30 gene-level features potentially predictive of haploinsufficiency, DosaCNV shows unmatched performance in prioritizing pathogenic deletions associated with a broad spectrum of genetic disorders. Furthermore, DosaCNV outperforms existing methods in predicting gene haploinsufficiency even though it is not trained on known haploinsufficient genes. Finally, DosaCNV leverages a state-of-the-art technique to quantify the contributions of individual gene-level features to haploinsufficiency, allowing for human-understandable explanations of model predictions. Altogether, DosaCNV is a powerful computational tool for both fundamental and translational research.

Measuring intolerance to mutation in human genetics

In numerous applications, from working with animal models to mapping the genetic basis of human disease susceptibility, knowing whether a single disrupting mutation in a gene is likely to be deleterious is useful. With this goal in mind, a number of measures have been developed to identify genes in which protein-truncating variants (PTVs), or other types of mutations, are absent or kept at very low frequency in large population samples-genes that appear 'intolerant' to mutation. One measure in particular, the probability of being loss-of-function intolerant (pLI), has been widely adopted. This measure was designed to classify genes into three categories, null, recessive and haploinsufficient, on the basis of the contrast between observed and expected numbers of PTVs. Such population-genetic approaches can be useful in many applications. As we clarify, however, they reflect the strength of selection acting on heterozygotes and not dominance or haploinsufficiency.

Aging, carotid artery distensibility, and the Ser422Gly elastin gene polymorphism in humans

Elastin is a protein of the extracellular matrix that forms the major component of elastic fibers from the arterial wall thickness and plays an important role in elastic properties of large blood vessels. To study the relationships between the Ser422Gly polymorphism in exon 16 of the gene-encoding elastin and the distensibility of 2 different arteries, the radial artery (a muscular artery) and the common carotid artery (an elastic artery), we studied a cohort of 320 subjects (49+/-12 years of age) without evidence of cardiovascular disease and who had never been treated with cardiovascular drugs. Distensibility and elastic modulus were evaluated for the common carotid and the radial arteries with high-resolution echo-tracking devices (NIUS-02 and Wall Track System). The A-to-G nucleotide change corresponding to the Ser422Gly amino acid change was studied by digestion of polymerase chain reaction products with BstNI. Results indicate that genotype frequencies (AA=10%, AG=51%, GG=39%) were in agreement with the Hardy-Weinberg equilibrium. For the carotid artery, a significant decrease in distensibility was observed in subjects carrying the A allele (with AA+AG genotypes) compared with subjects with the GG genotype (13.8+/-6.4 kPa(-1). 10(-3) versus 15.9+/-6.2 kPa(-1). 10(-3), P<0.01), assuming a dominant effect of the A allele. Moreover, the presence of the A allele was associated with a significant increase in elastic modulus (0.98+/-0.40 kPa. 10(3) in subjects with AA+AG genotypes versus 0.83+/-0.41 kPa. 10(3) in subjects with GG genotypes, P<0.01). Multivariate analysis indicated that these results were observed after adjustment for age, gender, and mean arterial blood pressure (P<0.01). In contrast, no association was found between arterial parameters and genotypes for the radial artery. The 2-way analysis of covariance adjusted for mean arterial blood pressure indicated that the association between the A allele and distensibility of the carotid artery was observed only in subjects >50 years of age, assuming for carotid distensibility a significant age effect (P<0.01), genotype effect (P=0.01), and age-genotype interaction (P=0.04). The present results indicate a relationship between the Ser422Gly polymorphism and the distensibility of elastic arteries but not of muscular arteries and suggest that there is an age-genotype interaction for carotid artery distensibility.