Improved Diagnosis of Rare Disease Patients through Systematic Detection of Runs of Homozygosity.

Autozygosity is associated with an increased risk of genetic rare disease, thus being a relevant factor for clinical genetic studies. More than 2400 exome sequencing data sets were analyzed and screened for autozygosity on the basis of detection of >1 Mbp runs of homozygosity (ROHs). A model was built to predict if an individual is likely to be a consanguineous offspring (accuracy, 98%), and probability of consanguinity ranges were established according to the total ROH size. Application of the model resulted in the reclassification of the consanguinity status of 12% of the patients. The analysis of a subset of 79 consanguineous cases with the Rare Disease (RD)-Connect Genome-Phenome Analysis Platform, combining variant filtering and homozygosity mapping, enabled a 50% reduction in the number of candidate variants and the identification of homozygous pathogenic variants in 41 patients, with an overall diagnostic yield of 52%. The newly defined consanguinity ranges provide, for the first time, specific ROH thresholds to estimate inbreeding within a pedigree on disparate exome sequencing data, enabling confirmation or (re)classification of consanguineous status, hence increasing the efficiency of molecular diagnosis and reporting on secondary consanguinity findings, as recommended by American College of Medical Genetics and Genomics guidelines.

Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics.

Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance-based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall-Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

Role of Academic Biobanks in Public-Private Partnerships in the European Biobanking and BioMolecular Resources Research Infrastructure Community.

Public-private partnerships (PPP) are an efficient means to advance scientific discoveries and boost the medical innovations needed to improve precision medicine. The increasing number and novel nature of such collaborations is keeping the biomedical field in constant flux. Here we provide an update on PPP development involving academic biobanks in the BBMRI community (the European Biobanking and BioMolecular Resources Research Infrastructure) and report the views on PPP of 20 key players from this field. The interviewed academic representants broadly show interest for their institution to establish PPP and initiate or partner with BBMRI expert centers. The results indicate that PPP has gained foothold in this area of biomedical research, with great promise to facilitate access to samples and data and to improve data interoperability and reproducibility.

Transnational access to large prospective cohorts in Europe: Current trends and unmet needs.

Biobank samples and data from studies of large prospective cohorts (LPC) represent an invaluable resource for health research. Efficient sharing and pooling of samples and data is a central pre-requisite for new advances in biomedical science. This requirement, however, is not compatible with the present scattered and traditional access governance structures, where legal and ethical frameworks often form an obstacle for effective sharing. Moreover, the EU General Data Protection Regulation (GDPR) is demanding increasingly rigorous administration from all those organisations processing personal data. The BBMRI-LPC project (Biobanking and Biomolecular Research Infrastructure - Large Prospective Cohorts) assembled 21 LPCs from 10 countries and two EU-wide multinational cohort networks with a key objective to promote collaborative innovative transnational research proposed by external researchers on the broad field of common chronic diseases, and analyze the gaps and needs involved. BBMRI-LPC organized three scientific calls to offer European investigators an opportunity to gain free of charge transnational access to research material available in the participating cohorts. A total of 11 high-quality research proposals involving multiple prospective cohorts were granted, and the access process in the individual projects carefully monitored. Divergent access governance structures, complex legal and ethical frameworks and heterogeneous procedures were identified as currently constituting substantial obstacles for sample and data transfer in Europe. To optimize the scientific value and use of these research resources, practical solutions for more streamlined access governance in collaborative projects are urgently needed. A number of infrastructure developments could be made to improve time-efficiency in access provision.

Effect of post-mortem delay on N-terminal huntingtin protein fragments in human control and Huntington disease brain lysates.

Huntington disease is associated with elongation of a CAG repeat in the HTT gene that results in a mutant huntingtin protein. Several studies have implicated N-terminal huntingtin protein fragments in Huntington disease pathogenesis. Ideally, these fragments are studied in human brain tissue. However, the use of human brain tissue comes with certain unavoidable variables such as post mortem delay, artefacts from freeze-thaw cycles and subject-to-subject variation. Knowledge on how these variables might affect N-terminal huntingtin protein fragments in post mortem human brain is important for a proper interpretation of study results. The effect of post mortem delay on protein in human brain is known to vary depending on the protein of interest. In the present study, we have assessed the effect of post mortem delay on N-terminal huntingtin protein fragments using western blot. We mimicked post mortem delay in one individual control case and one individual Huntington disease case with low initial post mortem delay. The influence of subject-to-subject variation on N-terminal huntingtin fragments was assessed in human cortex and human striatum using two cohorts of control and Huntington disease subjects. Our results show that effects of post mortem delay on N-terminal huntingtin protein fragments are minor in our individual subjects. Additionally, one freeze-thaw cycle decreases the huntingtin western blot signal intensity in the cortex control subject, but does not introduce additional N-terminal huntingtin fragments. Our results suggest that subject-to-subject variation contributes more to variability in N-terminal huntingtin fragments than post mortem delay.

Huntington's disease blood and brain show a common gene expression pattern and share an immune signature with Alzheimer's disease.

There is widespread transcriptional dysregulation in Huntington's disease (HD) brain, but analysis is inevitably limited by advanced disease and postmortem changes. However, mutant HTT is ubiquitously expressed and acts systemically, meaning blood, which is readily available and contains cells that are dysfunctional in HD, could act as a surrogate for brain tissue. We conducted an RNA-Seq transcriptomic analysis using whole blood from two HD cohorts, and performed gene set enrichment analysis using public databases and weighted correlation network analysis modules from HD and control brain datasets. We identified dysregulated gene sets in blood that replicated in the independent cohorts, correlated with disease severity, corresponded to the most significantly dysregulated modules in the HD caudate, the most prominently affected brain region, and significantly overlapped with the transcriptional signature of HD myeloid cells. High-throughput sequencing technologies and use of gene sets likely surmounted the limitations of previously inconsistent HD blood expression studies. Our results suggest transcription is disrupted in peripheral cells in HD through mechanisms that parallel those in brain. Immune upregulation in HD overlapped with Alzheimer's disease, suggesting a common pathogenic mechanism involving macrophage phagocytosis and microglial synaptic pruning, and raises the potential for shared therapeutic approaches.

A high-quality human reference panel reveals the complexity and distribution of genomic structural variants.

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals.

Therapeutic NOTCH3 cysteine correction in CADASIL using exon skipping: in vitro proof of concept.

Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, or CADASIL, is a hereditary cerebral small vessel disease caused by characteristic cysteine altering missense mutations in the NOTCH3 gene. NOTCH3 mutations in CADASIL result in an uneven number of cysteine residues in one of the 34 epidermal growth factor like-repeat (EGFr) domains of the NOTCH3 protein. The consequence of an unpaired cysteine residue in an EGFr domain is an increased multimerization tendency of mutant NOTCH3, leading to toxic accumulation of the protein in the (cerebro)vasculature, and ultimately reduced cerebral blood flow, recurrent stroke and vascular dementia. There is no therapy to delay or alleviate symptoms in CADASIL. We hypothesized that exclusion of the mutant EGFr domain from NOTCH3 would abolish the detrimental effect of the unpaired cysteine and thus prevent toxic NOTCH3 accumulation and the negative cascade of events leading to CADASIL. To accomplish this NOTCH3 cysteine correction by EGFr domain exclusion, we used pre-mRNA antisense-mediated skipping of specific NOTCH3 exons. Selection of these exons was achieved using in silico studies and based on the criterion that skipping of a particular exon or exon pair would modulate the protein in such a way that the mutant EGFr domain is eliminated, without otherwise corrupting NOTCH3 structure and function. Remarkably, we found that this strategy closely mimics evolutionary events, where the elimination and fusion of NOTCH EGFr domains led to the generation of four functional NOTCH homologues. We modelled a selection of exon skip strategies using cDNA constructs and show that the skip proteins retain normal protein processing, can bind ligand and be activated by ligand. We then determined the technical feasibility of targeted NOTCH3 exon skipping, by designing antisense oligonucleotides targeting exons 2-3, 4-5 and 6, which together harbour the majority of distinct CADASIL-causing mutations. Transfection of these antisense oligonucleotides into CADASIL patient-derived cerebral vascular smooth muscle cells resulted in successful exon skipping, without abrogating NOTCH3 signalling. Combined, these data provide proof of concept for this novel application of exon skipping, and are a first step towards the development of a rational therapeutic approach applicable to up to 94% of CADASIL-causing mutations.

The Implicitome: A Resource for Rationalizing Gene-Disease Associations.

High-throughput experimental methods such as medical sequencing and genome-wide association studies (GWAS) identify increasingly large numbers of potential relations between genetic variants and diseases. Both biological complexity (millions of potential gene-disease associations) and the accelerating rate of data production necessitate computational approaches to prioritize and rationalize potential gene-disease relations. Here, we use concept profile technology to expose from the biomedical literature both explicitly stated gene-disease relations (the explicitome) and a much larger set of implied gene-disease associations (the implicitome). Implicit relations are largely unknown to, or are even unintended by the original authors, but they vastly extend the reach of existing biomedical knowledge for identification and interpretation of gene-disease associations. The implicitome can be used in conjunction with experimental data resources to rationalize both known and novel associations. We demonstrate the usefulness of the implicitome by rationalizing known and novel gene-disease associations, including those from GWAS. To facilitate the re-use of implicit gene-disease associations, we publish our data in compliance with FAIR Data Publishing recommendations [https://www.force11.org/group/fairgroup] using nanopublications. An online tool (http://knowledge.bio) is available to explore established and potential gene-disease associations in the context of other biomedical relations.

Transmission of human mtDNA heteroplasmy in the Genome of the Netherlands families: support for a variable-size bottleneck.

Although previous studies have documented a bottleneck in the transmission of mtDNA genomes from mothers to offspring, several aspects remain unclear, including the size and nature of the bottleneck. Here, we analyze the dynamics of mtDNA heteroplasmy transmission in the Genomes of the Netherlands (GoNL) data, which consists of complete mtDNA genome sequences from 228 trios, eight dizygotic (DZ) twin quartets, and 10 monozygotic (MZ) twin quartets. Using a minor allele frequency (MAF) threshold of 2%, we identified 189 heteroplasmies in the trio mothers, of which 59% were transmitted to offspring, and 159 heteroplasmies in the trio offspring, of which 70% were inherited from the mothers. MZ twin pairs exhibited greater similarity in MAF at heteroplasmic sites than DZ twin pairs, suggesting that the heteroplasmy MAF in the oocyte is the major determinant of the heteroplasmy MAF in the offspring. We used a likelihood method to estimate the effective number of mtDNA genomes transmitted to offspring under different bottleneck models; a variable bottleneck size model provided the best fit to the data, with an estimated mean of nine individual mtDNA genomes transmitted. We also found evidence for negative selection during transmission against novel heteroplasmies (in which the minor allele has never been observed in polymorphism data). These novel heteroplasmies are enhanced for tRNA and rRNA genes, and mutations associated with mtDNA diseases frequently occur in these genes. Our results thus suggest that the female germ line is able to recognize and select against deleterious heteroplasmies.

IL7R gene expression network associates with human healthy ageing.

BACKGROUND: The level of expression of the interleukin 7 receptor (IL7R) gene in blood has recently been found to be associated with familial longevity and healthy ageing. IL7R is crucial for T cell development and important for immune competence. To further investigate the IL7R pathway in ageing, we identified the closest interacting genes to construct an IL7R gene network that consisted of IL7R and six interacting genes: IL2RG, IL7, TSLP, CRLF2, JAK1 and JAK3. This network was explored for association with chronological age, familial longevity and immune-related diseases (type 2 diabetes, chronic obstructive pulmonary disease and rheumatoid arthritis) in 87 nonagenarians, 337 of their middle-aged offspring and 321 middle-aged controls from the Leiden Longevity Study (LLS). RESULTS: We observed that expression levels within the IL7R gene network were significantly different between the nonagenarians and middle-aged controls (P = 4.6 × 10(-4)), being driven by significantly lower levels of expression in the elderly of IL7, IL2RG and IL7R. After adjustment for multiple testing and white blood cell composition and in comparison with similarly aged controls, middle-aged offspring of nonagenarian siblings exhibit a lower expression level of IL7R only (P = 0.006). Higher IL7R gene expression in the combined group of middle-aged offspring and controls is associated with a higher prevalence of immune-related disease (P = 0.001). On the one hand, our results indicate that lower IL7R expression levels, as exhibited by the members of long-lived families that can be considered as 'healthy agers', are beneficial in middle age. This is augmented by the observation that higher IL7R gene expression associates with immune-related disease. On the other hand, IL7R gene expression in blood is lower in older individuals, indicating that low IL7R gene expression might associate with reduced health. Interestingly, this contradictory result is supported by the observation that a higher IL7R gene expression level is associated with better prospective survival, both in the nonagenarians (Hazard ratio (HR) = 0.63, P = 0.037) and the middle-aged individuals (HR = 0.33, P = 1.9 × 10(-4)). CONCLUSIONS: Overall, we conclude that the IL7R network reflected by gene expression levels in blood may be involved in the rate of ageing and health status of elderly individuals.

Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels.

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P < 1.09 × 10(-9)) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N = 1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.

The Pathogenesis and Therapy of Muscular Dystrophies.

Current molecular genomic approaches to human genetic disorders have led to an explosion in the identification of the genes and their encoded proteins responsible for these disorders. The identification of the gene altered by mutations in Duchenne and Becker muscular dystrophy was one of the earliest examples of this paradigm. The nearly 30 years of research partly outlined here exemplifies the road that similar current gene discovery protocols will be expected to travel, albeit much more rapidly owing to improved diagnosis of genetic disorders and an understanding of the spectrum of mutations thought to cause them. The identification of the protein dystrophin has led to a new understanding of the muscle cell membrane and the proteins involved in membrane stability, as well as new candidate genes for additional forms of muscular dystrophy. Animal models identified with naturally occurring mutations and developed by genetic manipulation have furthered the understanding of disease progression and underlying pathology. The biochemistry and molecular analysis of patient samples have led to the different dystrophin-dependent and -independent therapies that are currently close to or in human clinical trials. The lessons learned from decades of research on dystrophin have benefited the field of human genetics.

Selection and characterization of llama single domain antibodies against N-terminal huntingtin.

Huntington disease is caused by expansion of a CAG repeat in the huntingtin gene that is translated into an elongated polyglutamine stretch within the N-terminal domain of the huntingtin protein. The mutation is thought to introduce a gain-of-toxic function in the mutant huntingtin protein, and blocking this toxicity by antibody binding could alleviate Huntington disease pathology. Llama single domain antibodies (VHH) directed against mutant huntingtin are interesting candidates as therapeutic agents or research tools in Huntington disease because of their small size, high thermostability, low cost of production, possibility of intracellular expression, and potency of blood-brain barrier passage. We have selected VHH from llama phage display libraries that specifically target the N-terminal domain of the huntingtin protein. Our VHH are capable of binding wild-type and mutant human huntingtin under native and denatured conditions and can be used in Huntington disease studies as a novel antibody that is easy to produce and manipulate.

BBMRI-ERIC as a resource for pharmaceutical and life science industries: the development of biobank-based Expert Centres.

Biological resources (cells, tissues, bodily fluids or biomolecules) are considered essential raw material for the advancement of health-related biotechnology, for research and development in life sciences, and for ultimately improving human health. Stored in local biobanks, access to the human biological samples and related medical data for transnational research is often limited, in particular for the international life science industry. The recently established pan-European Biobanking and BioMolecular resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to improve accessibility and interoperability between academic and industrial parties to benefit personalized medicine, disease prevention to promote development of new diagnostics, devices and medicines. BBMRI-ERIC is developing the concept of Expert Centre as public-private partnerships in the precompetitive, not-for-profit field to provide a new structure to perform research projects that would face difficulties under currently established models of academic-industry collaboration. By definition, Expert Centres are key intermediaries between public and private sectors performing the analysis of biological samples under internationally standardized conditions. This paper presents the rationale behind the Expert Centres and illustrates the novel concept with model examples.

The Complete Genome Sequence of the Murine Pathobiont Helicobacter typhlonius.

BACKGROUND: Immuno-compromised mice infected with Helicobacter typhlonius are used to model microbially inducted inflammatory bowel disease (IBD). The specific mechanism through which H. typhlonius induces and promotes IBD is not fully understood. Access to the genome sequence is essential to examine emergent properties of this organism, such as its pathogenicity. To this end, we present the complete genome sequence of H. typhlonius MIT 97-6810, obtained through single-molecule real-time sequencing. RESULTS: The genome was assembled into a single circularized contig measuring 1.92 Mbp with an average GC content of 38.8%. In total 2,117 protein-encoding genes and 43 RNA genes were identified. Numerous pathogenic features were found, including a putative pathogenicity island (PAIs) containing components of type IV secretion system, virulence-associated proteins and cag PAI protein. We compared the genome of H. typhlonius to those of the murine pathobiont H. hepaticus and human pathobiont H. pylori. H. typhlonius resembles H. hepaticus most with 1,594 (75.3%) of its genes being orthologous to genes in H. hepaticus. Determination of the global methylation state revealed eight distinct recognition motifs for adenine and cytosine methylation. H. typhlonius shares four of its recognition motifs with H. pylori. CONCLUSION: The complete genome sequence of H. typhlonius MIT 97-6810 enabled us to identify many pathogenic features suggesting that H. typhlonius can act as a pathogen. Follow-up studies are necessary to evaluate the true nature of its pathogenic capabilities. We found many methylated sites and a plethora of restriction-modification systems. The genome, together with the methylome, will provide an essential resource for future studies investigating gene regulation, host interaction and pathogenicity of H. typhlonius. In turn, this work can contribute to unraveling the role of Helicobacter in enteric disease.