Human Splicing Finder: an online bioinformatics tool to predict splicing signals

Thousands of mutations are identified yearly. Although many directly affect protein expression, an increasing proportion of mutations is now believed to influence mRNA splicing. They mostly affect existing splice sites, but synonymous, non-synonymous or nonsense mutations can also create or disrupt splice sites or auxiliary cis-splicing sequences. To facilitate the analysis of the different mutations, we designed Human Splicing Finder (HSF), a tool to predict the effects of mutations on splicing signals or to identify splicing motifs in any human sequence. It contains all available matrices for auxiliary sequence prediction as well as new ones for binding sites of the 9G8 and Tra2-β Serine-Arginine proteins and the hnRNP A1 ribonucleoprotein. We also developed new Position Weight Matrices to assess the strength of 5′ and 3′ splice sites and branch points. We evaluated HSF efficiency using a set of 83 intronic and 35 exonic mutations known to result in splicing defects. We showed that the mutation effect was correctly predicted in almost all cases. HSF could thus represent a valuable resource for research, diagnostic and therapeutic (e.g. therapeutic exon skipping) purposes as well as for global studies, such as the GEN2PHEN European Project or the Human Variome Project

Thoracic aortic aneurysms and dissections: genetic analysis of Mendelian and complex cases

The present doctoral thesis deals with the still partially unraveled genetic component of thoracic aortic aneurysms and dissections, a frequently asymptomatic but potentially lethal condition and major cause of sudden death. Our main objective was to contribute to further elucidate the genetics behind it, from both Mendelian and complex perspectives. We analyzed single and familial, forensic and clinical mendelian cases applying either a candidate-gene or whole exome massive parallel sequencing approach, respectively. We were able to solve approximately 23% of the forensic single cases and identified two strong candidate mutations in TGFB2 and PRKG1 genes in the two non-syndromic familial cases analyzed. For the analysis of complex cases we chose a population-based approach. We selected bicuspid aortic valve patients with and without concomitant thoracic aortic dilation and faced them against general population controls. We were not able to identify any consistently significant association, though a promising one arose involving HMCN2 and calcium metabolism that should be considered in future studies. The direct clinical consequences some of these results had supported molecular diagnosis, reliable genotype-phenotype correlations, and risk stratification as important tools for clinical management of these patients and family members at risk, as well as the need of research to continue

The genetic associations of rhegmatogenous retinal detachment and ectopia lentis

A genetic predisposition to Rhegmatogenous Retinal Detachment (RD) has been suggested for over 40 years. Ectopia Lentis (EL) is known to have a genetic aetiology as part of Marfan Syndrome, other ocular syndromes and when occurring in isolation. This work investigates the genetic aetiology to these conditions in Mendelian and non Mendelian inheritance. The work in this thesis establishes a clear genotype-phenotype correlation between isolated EL and its most important causative gene: ADAMTSL4. This suggests that mutations in this gene result in a more severe phenotype than other genes causing EL. In doing so, a novel clinical grading system for this condition has also been developed. The expression of ADAMTSL4 and distribution of its protein within ocular tissue has also been investigated and suggests further roles for this protein in ocular development. Modelling of the protein was undertaken and provides insights for future investigations. Traditional and novel next generation investigative tools have also been employed to examine families with Mendelian inherited phenotypes including RD and EL. The role of a deleted exon in ADAMTS17 has been identified as playing a role in Weill-Marchesani Like syndrome. A novel ocular phenotype has also been defined in three families demonstrated to be caused by mutations in ADAMTS1 8. This gene has previously been described in few probands with ophthalmic phenotypes, and this work has further delineated the role of this gene. It is becoming clear that members of the ADAMTS family of proteins play a significant role in ocular development. Finally, over 1300 probands with non-Mendelian RD were recruited and closely phenotyped as part of this work. It has demonstrated novel racial differences in the phenotypes of those affected. This cohort contributed significantly towards the first genome wide association study (GWAS) into RD; and established for the first time the genetic contribution to this condition. Further funding has now been acquired to investigate this cohort further using a novel exome array. Preliminary quality control analysis has been performed; allowing a platform for further detailed analysis to identify putative functional variants associated with RD

Molecular Genetics and Pathogenesis of Ehlers–Danlos Syndrome and Related Connective Tissue Disorders

Ehlers–Danlos syndromes (EDS) are a group of heritable connective tissue disorders (HCTDs) characterized by a variable degree of skin hyperextensibility, joint hypermobility and tissue fragility. The current EDS classification distinguishes 13 subtypes and 19 different causal genes mainly involved in collagen and extracellular matrix synthesis and maintenance. EDS need to be differentiated from other HCTDs with a variable clinical overlap, including Marfan syndrome and related disorders, some types of skeletal dysplasia and cutis laxa. The clinical recognition of EDS is not always straightforward, and, for a definite diagnosis, molecular testing can be of great assistance, especially in patients with an uncertain phenotype. Currently, the major challenging task in EDS is to unravel the molecular basis of the hypermobile EDS that is the most frequent form, and for which the diagnosis is only clinical in the absence of any definite laboratory test. This EDS subtype, as well as other EDS-reminiscent phenotypes, are currently investigated worldwide to unravel the primary genetic defect and related pathomechanisms. The research articles, case report, and reviews published in the Special Issue entitled “Molecular Genetics and Pathogenesis of Ehlers–Danlos Syndrome and Related Connective Tissue Disorders” focus on different clinical, genetic and molecular aspects of several EDS subtypes and some related disorders, offering novel findings and future research and nosological perspectives

Bicuspid aortic valve and associated aortopathy: a combined biomechanics, histological and genetic analysis

Bicuspid aortic valve (BAV) is the most common inborn heart defect and a continuum of a disease process affecting the aortic valve and the thoracic aorta with an increased risk of thoracic aortic aneurysm (TAA) formation and dissection. Aortic dilatation may be related to haemodynamic perturbations or intrinsic wall abnormalities. The aim of this thesis was to investigate the relative contribution of these parameters to BAV aortopathy via integrated analyses. Distribution of circumferential stress in the aorta of BAV patients planned to undergo surgery was analysed using computed tomography imaging and computational modelling. During surgery, aortic biopsies were taken from discrete areas and examined for histological abnormalities. Maximal mechanical stress occurred in the medial ascending aorta in the majority of cases with integrated analyses exhibiting a positive correlation between aortic fibrosis and mechanical stress, both in the root and the ascending aorta. The degree of histological abnormalities and transforming growth factor beta (TGFβ) activation was also assessed in collected tissue biopsies. Patients with either root dilatation and/or predominant regurgitant valve disease had greater levels of medial wall degeneration in their ascending aorta whereas enhanced TGFβ signalling was present in aneurysmal but also, non-dilated BAV aortic segments, pointing to a genetic trigger. Copy number variation (CNV) analyses in a larger BAV cohort revealed a large heterozygous deletion in the angiotensin converting enzyme (ACE) gene and targeted next-generation sequencing revealed previously reported variants in NOTCH1, COL3A1, and APOE genes with additional discovery of a large number of likely pathogenic variants in genes related to BAV formation and aortopathy. In conclusion, different BAV aortic phenotypes were recognised and further analysed. The presence of multiple likely pathogenic variants in sequenced patients suggests a polygenic nature of BAV disease which, in conjuction with local haemodynamic perturbations, supports a mutlifactorial origin of BAV aortopathy.Open Acces

Evidence for Hitchhiking of Deleterious Mutations within the Human Genome

Deleterious mutations present a significant obstacle to adaptive evolution. Deleterious mutations can inhibit the spread of linked adaptive mutations through a population; conversely, adaptive substitutions can increase the frequency of linked deleterious mutations and even result in their fixation. To assess the impact of adaptive mutations on linked deleterious mutations, we examined the distribution of deleterious and neutral amino acid polymorphism in the human genome. Within genomic regions that show evidence of recent hitchhiking, we find fewer neutral but a similar number of deleterious SNPs compared to other genomic regions. The higher ratio of deleterious to neutral SNPs is consistent with simulated hitchhiking events and implies that positive selection eliminates some deleterious alleles and increases the frequency of others. The distribution of disease-associated alleles is also altered in hitchhiking regions. Disease alleles within hitchhiking regions have been associated with auto-immune disorders, metabolic diseases, cancers, and mental disorders. Our results suggest that positive selection has had a significant impact on deleterious polymorphism and may be partly responsible for the high frequency of certain human disease alleles

Genetics and genomics of aortic form and function

The thoracic aorta is a dynamic organ which adapts and remodels throughout life. Thoracic aortic size, shape and function are important contributors to both cardiovascular health and disease and risk of aortic disease. A complex interaction of environmental, genetic and haemodynamic factors is mediated by cells of the aortic wall. This thesis presents aortic phenotyping, genotyping and genome-wide associations of aortic traits in a large healthy cohort of 1218 volunteers. This is the largest study to report normal parameters for healthy thoracic aortic size, shape and function derived from cardiovascular magnetic resonance imaging. Anthropometric and cardiovascular risk factors such as age, gender, body fat mass and lipid profile are identified as significant determinants of aortic phenotype. The work suggests that cardiovascular risk factors could impair normal adaptive aortic remodelling with age. Genome-wide association studies of aortic dimensions and function identify new common variants, genes and pathways which could be important in aortic biology and cardiovascular risk. These include genes involved in cardiovascular development (eg PCDH7 and SON associated with aortic root diameter), autonomic cardiovascular responses (eg GABA receptor genes associated with aortic root diameter), fibrosis (eg ACTC1, AGTR1 associated with ascending aortic distensibility, BAMBI and MYOD associated with descending aortic distensibility) and obesity (eg ARID5B and IRX3 associated with aortic pulse wave velocity and ascending aortic area respectively). Multiple regulatory pathways including TGF-ß and IGF signalling (IGF1R, IGF2R), are identified which are associated with aortic dimensions and function. Joint trait analysis of aortic root dimensions identifies a new genome-wide significant association with TENM4, a key driver of early mesodermal development, and suggestive association with PTN, which is functionally related and plays a key role in angiogenesis. The primary analyses are complemented by exploratory assessment of rare genetic variation in bicuspid aortic valve (BAV) using panel sequencing in 177 patients. Rare variants might cause, or modify phenotype in BAV, but the clinical utility of panel sequencing remains poor. A further complementary study investigates the interaction of haemodynamics with aortic cellular phenotype, using microarray assessment of aortic endothelial cell transcriptomic response to shear stress pattern. Several genes of interest in atherosclerosis and aortic disease are differentially expressed with shear stress pattern, such as FABP4, ANGPT2, FILIP1, KIT, DCHS1, TGFBR3 and LOX. This work yields new insights into aortic phenotype, identifies key loci which might determine aortic traits and explores the complex interdependence of genetics, haemodynamics and environmental variables in aortic biology.Open Acces

Lessons from the CAGI-4 Hopkins clinical panel challenge

The CAGI-4 Hopkins clinical panel challenge was an attempt to assess state of the art methods for clinical phenotype prediction from DNA sequence. Participants were provided with exonic sequences of 83 genes for 106 patients from the Johns Hopkins DNA Diagnostic Laboratory. Five groups participated in the challenge, predicting both the probability that each patient had each of fourteen possible classes of disease, as well as one or more causal variants. In cases where the Hopkins laboratory reported a variant, at least one predictor correctly identified the disease class in 36 of 43 patients (84%). Even in cases where the Hopkins laboratory did not find a variant, at least one predictor correctly identified the class in 39 of 63 patients (62%). Each prediction group correctly diagnosed at least one patient that was not successfully diagnosed by any other groups. We discuss the causal variant predictions by the different groups and their implications for further development of methods to assess variants of unknown significance. Our results suggest that clinically relevant variants may be missed when physicians order small panels targeted on a specific phenotype. We also quantify the false positive rate of DNA-guided analysis in the absence of prior phenotypic indication. This article is protected by copyright. All rights reserved

An integrated clinical program and crowdsourcing strategy for genomic sequencing and Mendelian disease gene discovery.

Despite major progress in defining the genetic basis of Mendelian disorders, the molecular etiology of many cases remains unknown. Patients with these undiagnosed disorders often have complex presentations and require treatment by multiple health care specialists. Here, we describe an integrated clinical diagnostic and research program using whole-exome and whole-genome sequencing (WES/WGS) for Mendelian disease gene discovery. This program employs specific case ascertainment parameters, a WES/WGS computational analysis pipeline that is optimized for Mendelian disease gene discovery with variant callers tuned to specific inheritance modes, an interdisciplinary crowdsourcing strategy for genomic sequence analysis, matchmaking for additional cases, and integration of the findings regarding gene causality with the clinical management plan. The interdisciplinary gene discovery team includes clinical, computational, and experimental biomedical specialists who interact to identify the genetic etiology of the disease, and when so warranted, to devise improved or novel treatments for affected patients. This program effectively integrates the clinical and research missions of an academic medical center and affords both diagnostic and therapeutic options for patients suffering from genetic disease. It may therefore be germane to other academic medical institutions engaged in implementing genomic medicine programs

Evaluation of blood-based microRNAs toward clinical use as biomarkers in common and rare diseases

According to the GLOBOCAN project of the International Agency for Research on Cancer, the top three common cancer diseases worldwide in the year 2020 were breast, lung and colorectal cancer. These are usually diagnosed via imaging methods (e.g. computer tomography) or invasive methods (e.g. biopsy). However, these techniques are potentially risky and expensive and thus not accessible to all patients, resulting in most cancers being detected in an advanced stage. Since the discovery of small non-coding RNAs and specifically microRNAs and their role as gene regulators, many researchers investigate their association with disease development. In particular, researchers examine body fluid based microRNAs which could present potential cost-effective and minimally- or non-invasive alternatives to the previously described established diagnosis methods. This dissertation focuses on microRNAs and investigates their suitability as minimally-invasive blood-borne biomarkers for potential diagnostic purposes. More specifically, the goals of this work are (1) to implement a new method to predict novel microRNAs, (2) to understand stability and characteristics of these small non-coding RNAs, possibly relevant for the last goal, (3) to discover potential diagnostic biomarkers in common and rare diseases. The first goal was addressed by developing miRMaster, a web service to predict new microRNAs. The tool uses machine learning and high-throughput sequencing data to find microRNA candidates that follow the known biogenesis pathways. The second goal was pursued in four publications. First, we performed a large scale evaluation of miRMaster by generating a high-resolution map of the human small non-coding RNA transcriptome for which we analyzed and validated potential microRNA candidates. Next, we examined the influence of seasonal effects on microRNA expression profiles and observed the largest difference between spring and the other seasons. Additionally, we evaluated the evolutionary conservation of small non-coding RNAs in zoo animals and showed that the distribution of sncRNA classes varies across species, while common microRNA families are present in more diverse organisms than assumed so far. Furthermore, we analyzed if microRNAs are technically stable, and whether biological variation is preserved when using capillary dried blood spots as an alternative sample collection device to venous blood specimens. Finally, we investigated the suitability of microRNAs as biomarkers for two diseases: lung cancer and Marfan disease. We identified blood-borne biomarker candidates for lung cancer detection in a large-scale multi-center study via machine learning. For the rare Marfan disease we analyzed the paired messenger RNA and microRNA expression levels in whole-blood samples. This highlighted several significantly deregulated microRNAs and messenger RNAs, which we subsequently validated in an independent cohort. In summary, this thesis provides valuable results toward potential clinical use of microRNAs, and the herein described projects represent comprehensive analyses of them from different perspectives: starting with microRNA discovery, addressing various technical and biological questions and ending with the potential use as biomarkers.Nach Angaben des GLOBOCAN-Projekts der International Agency for Research on Cancer sind die drei häufigsten Krebserkrankungen weltweit im Jahr 2020 Brust-, Lungen- und Darmkrebs. Diese werden in der Regel durch bildgebende Verfahren (z.B. Computertomographie) oder invasive Methoden (z.B. Biopsie) diagnostiziert. Diese Verfahren sind jedoch potenziell risikoreich und teuer und daher nicht für alle Patienten zugänglich. Dies führt dazu, dass die meisten Krebsarten erst in einem fortgeschrittenen Stadium entdeckt werden. Seit der Entdeckung der kurzen nichtkodierenden RNAs und insbesondere der microRNAs und ihrer Rolle als Genregulatoren untersuchen viele Forscher ihren Zusammenhang mit der Krankheitsentwicklung. Insbesondere untersuchen die Forscher die in Körperflüssigkeiten vorkommenden microRNAs, die potenziell kosteneffiziente und minimal- oder nicht-invasive Alternativen zu den bisher beschriebenen etablierten Diagnosemethoden darstellen könnten. Diese Dissertation konzentriert sich auf microRNAs und untersucht deren Eignung als minimal-invasive blutbasierte Biomarker für potenzielle diagnostische Zwecke. Genauer gesagt sind die Ziele dieser Arbeit (1) die Implementierung einer neuen Methode zur Vorhersage neuartiger microRNAs, (2) das Verständnis über die Stabilität und Charakteristika dieser kurzen nicht-kodierenden RNAs, die möglicherweise für das nächste Ziel relevant sind, (3) die Entdeckung potenzieller diagnostischer Biomarker für verschiedene Anwendungen. Das erste Ziel wurde durch die Entwicklung von miRMaster verfolgt, einem Webdienst zur Vorhersage neuer microRNAs. Das Tool nutzt maschinelles Lernen und Hochdurchsatz-Sequenzierungsdaten, um microRNA-Kandidaten zu finden, die den bekannten Wege der Biogenese folgen. Das zweite Ziel wurde in vier Veröffentlichungen verfolgt. Zunächst führten wir eine groß angelegte Evaluierung von miRMaster durch, indem wir eine High-Resolution Map des menschlichen Transkriptoms kurzer nichtkodierender RNAs erstellten, für die wir potenzielle microRNA-Kandidaten analysierten und validierten. Anschließend untersuchten wir den Einfluss saisonaler Effekte auf die microRNA-Expressionsprofile und beobachteten den größten Unterschied zwischen dem Frühling und den anderen Jahreszeiten. Darüber hinaus untersuchten wir die evolutionäre Erhaltung kurzer nichtkodierender RNAs in Zoo-Tieren und zeigten, dass die Verteilung der kurzer nichtkodierenden RNA-Klassen zwischen den Arten variiert, während gemeinsame microRNA-Familien in verschiedeneren Organismen vorkommen als bisher angenommen. Darüber hinaus analysierten wir, ob microRNAs technisch stabil sind und ob die biologische Variation erhalten bleibt, wenn kapillares Trockenblut als alternatives Probenentnahmeverfahren zu venösen Blutproben verwendet werden. Schließlich untersuchten wir die Eignung von microRNAs als Biomarker für zwei Krankheiten: Lungenkrebs und Marfan-Krankheit. In einer groß angelegten multizentrischen Studie identifizierten wir mit Hilfe von maschinellem Lernen Biomarker-Kandidaten aus dem Blut für die Erkennung von Lungenkrebs. Für die seltene Marfan-Krankheit analysierten wir die gepaarten Expressionsniveaus von messengerRNA und microRNA in Vollblutproben. Dabei wurden mehrere signifikant deregulierte microRNAs und messengerRNAs festgestellt, die wir anschließend in einer unabhängigen Kohorte validierten. Zusammenfassend lässt sich sagen, dass diese Arbeit wertvolle Ergebnisse im Hinblick auf die potenzielle klinische Verwendung von microRNAs liefert. Die hier beschriebenen Projekte stellen umfassende Analysen aus verschiedenen Blickwinkeln dar: angefangen bei der Entdeckung von microRNAs, über verschiedene technische und biologische Fragen bis hin zur potenziellen Verwendung als Biomarker