Background: Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype... Show moreBackground: Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchical structure. However, to date, the use of HPO has not yet been widely implemented in the field of inborn errors of immunity (IEIs), mainly due to a lack of comprehensive IEI-related terms. Objectives: We sought to systematically review available terms in HPO for the depiction of IEIs, to expand HPO, yielding more comprehensive sets of terms, and to reannotate IEIs with HPO terms to provide accurate, standardized phenotypic descriptions. Methods: We initiated a collaboration involving expert clinicians, geneticists, researchers working on IEIs, and bioinformaticians. Multiple branches of the HPO tree were restructured and extended on the basis of expert review. Our ontology-guided machine learning coupled with a 2-tier expert review was applied to reannotate defined subgroups of IEIs. Results: We revised and expanded 4 main branches of the HPO tree. Here, we reannotated 73 diseases from 4 International Union of Immunological Societies-defined IEI disease subgroups with HPO terms. We achieved a 4.7-fold increase in the number of phenotypic terms per disease. Given the new HPO annotations, we demonstrated improved ability to computationally match selected IEI cases to their known diagnosis, and improved phenotype-driven disease classification. Conclusions: Our targeted expansion and reannotation presents enhanced precision of disease annotation, will enable superior HPO-based IEI characterization, and hence benefit both IEI diagnostic and research activities. Show less
DNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >... Show moreDNA methylation quantitative trait locus (mQTL) analyses on 32,851 participants identify genetic variants associated with DNA methylation at 420,509 sites in blood, resulting in a database of >270,000 independent mQTLs.Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated. Show less
Mierlo, G. van; Dirks, R.A.M.; Clerck, L. de; Brinkman, A.B.; Huth, M.; Kloet, S.L.; ... ; Marks, H. 2019
The pluripotent ground state is defined as a basal state free of epigenetic restrictions, which influence lineage specification. While naive embryonic stem cells (ESCs) can be maintained in a... Show moreThe pluripotent ground state is defined as a basal state free of epigenetic restrictions, which influence lineage specification. While naive embryonic stem cells (ESCs) can be maintained in a hypomethylated state with open chromatin when grown using two small-molecule inhibitors (2i)/leukemia inhibitory factor (LIF), in contrast to serum/LIF-grownESCs that resemble early post-implantation embryos, broader features of the ground-state pluripotent epigenome are not well understood. We identified epigenetic features of mouse ESCs cultured using 2i/LIF or serum/LIF by proteomic profiling of chromatin-associated complexes and histone modifications. Polycomb-repressive complex 2 (PRC2) and its product H3K27me3 are highly abundant in 2i/LIF ESCs, and H3K27me3 is distributed genome-wide in a CpG-dependent fashion. Consistently, PRC2-deficient ESCs showed increased DNA methylation at sites normally occupied by H3K27me3 and increased H4 acetylation. Inhibiting DNA methylation in PRC2-deficient ESCs did not affect their viability or transcriptome. Our findings suggest a unique H3K27me3 configuration protects naive ESCs from lineage priming, and they reveal widespread epigenetic crosstalk in ground-state pluripotency. Show less
Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological... Show moreMedicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health arid healthcare for all Europearis. Show less
