ABSTRACT
Blood cells contain functionally important intracellular structures, such as granules, critical to immunity and thrombosis. Quantitative variation in these structures has not been subjected previously to large-scale genetic analysis. We perform genome-wide association studies of 63 flow-cytometry derived cellular phenotypes-including cell-type specific measures of granularity, nucleic acid content and reactivity-in 41,515 participants in the INTERVAL study. We identify 2172 distinct variant-trait associations, including associations near genes coding for proteins in organelles implicated in inflammatory and thrombotic diseases. By integrating with epigenetic data we show that many intracellular structures are likely to be determined in immature precursor cells. By integrating with proteomic data we identify the transcription factor FOG2 as an early regulator of platelet formation and α-granularity. Finally, we show that colocalisation of our associations with disease risk signals can suggest aetiological cell-types-variants in IL2RA and ITGA4 respectively mirror the known effects of daclizumab in multiple sclerosis and vedolizumab in inflammatory bowel disease.
Subject(s)
Genome-Wide Association Study , Proteomics , Microscopy , Transcription Factors , CausalityABSTRACT
Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.
ABSTRACT
Since the description of the first case with gray platelet syndrome (GPS) in 1971, this rare inherited platelet disorder has been the focus of extensive clinical and basic research. These studies have not only increased our knowledge about the clinical manifestations of GPS but also deepened our understanding of the biogenesis of platelet α-granules and their pathophysiology in hemostasis and thrombosis. The discovery of the causal gene, neurobeachin-like 2, in 2011 was a milestone in hematology. Following this was the rapid diagnosis and phenotyping of many new patients and the further development of experimental models to characterize the pathophysiological relevance of neurobeachin-like 2 in hemostasis and immunity. The impact of altered protein function on cells other than platelets became apparent, including defects in the granules of neutrophils and monocytes and changes in the transcriptomic and proteomic profiles of other immune cells such as T lymphocytes. Besides the previously recognized clinical manifestations of macrothrombocytopenia, splenomegaly, and early-onset bone marrow fibrosis, we now recognize that immunologic abnormalities, including autoimmune diseases and recurrent infections, affect a proportion of patients with GPS. There is a proinflammatory signature of the plasma in GPS, with quantitative alterations of multiple proteins, including many produced by the liver. This review will cover the classical features of GPS and then focus on additional clinical manifestations of immune dysregulation and cellular defects beyond platelets in patients with this rare disorder.
Subject(s)
Autoimmune Diseases , Gray Platelet Syndrome , Humans , Megakaryocytes/metabolism , Gray Platelet Syndrome/diagnosis , Gray Platelet Syndrome/genetics , Autoimmunity , Proteomics , Blood Platelets/metabolism , Autoimmune Diseases/genetics , Autoimmune Diseases/metabolism , Cytoplasmic Granules/metabolismABSTRACT
Gray platelet syndrome (GPS) is a rare recessive disorder caused by biallelic variants in NBEAL2 and characterized by bleeding symptoms, the absence of platelet α-granules, splenomegaly, and bone marrow (BM) fibrosis. Due to the rarity of GPS, it has been difficult to fully understand the pathogenic processes that lead to these clinical sequelae. To discern the spectrum of pathologic features, we performed a detailed clinical genotypic and phenotypic study of 47 patients with GPS and identified 32 new etiologic variants in NBEAL2. The GPS patient cohort exhibited known phenotypes, including macrothrombocytopenia, BM fibrosis, megakaryocyte emperipolesis of neutrophils, splenomegaly, and elevated serum vitamin B12 levels. Novel clinical phenotypes were also observed, including reduced leukocyte counts and increased presence of autoimmune disease and positive autoantibodies. There were widespread differences in the transcriptome and proteome of GPS platelets, neutrophils, monocytes, and CD4 lymphocytes. Proteins less abundant in these cells were enriched for constituents of granules, supporting a role for Nbeal2 in the function of these organelles across a wide range of blood cells. Proteomic analysis of GPS plasma showed increased levels of proteins associated with inflammation and immune response. One-quarter of plasma proteins increased in GPS are known to be synthesized outside of hematopoietic cells, predominantly in the liver. In summary, our data show that, in addition to the well-described platelet defects in GPS, there are immune defects. The abnormal immune cells may be the drivers of systemic abnormalities such as autoimmune disease.