Children and adolescents with all forms of shoulder instability demonstrate differences in their movement and muscle activity patterns when compared to age- and sex-matched controls.

BACKGROUND: Shoulder instability is a complex impairment and identifying biomarkers which differentiate subgroups is challenging. There is limited fundamental movement and muscle activity data for identifying different mechanisms for shoulder instability in children and adolescents which may inform subgrouping and treatment allocation. HYPOTHESIS: Children and adolescents with shoulder instability (irrespective of etiology) have differences in their movement and muscle activity profiles compared to age- and sex-matched controls (two-tailed). METHODS: Young people between eight to 18 years were recruited into two groups of shoulder instability (SI) or and age- and sex-matched controls (CG). All forms of SI were included and young people with co-existing neurological pathologies or deficits were excluded. Participants attended a single session and carried out four unweighted and three weighted tasks in which their movements and muscle activity was measured using 3D-movement analysis and surface electromyography. Statistical parametric mapping was used to identify between group differences. RESULTS: Data was collected for 30 young people (15 SI (6M:9F) and 15 CG (8M:7F)). The mean (SD) age for all participants was 13.6 years (3.0). The SI group demonstrated consistently more protracted and elevated sternoclavicular joint positions during all movements. Normalized muscle activity in Latissimus dorsi was lower in the SI group and had the most statistically significant differences across all movements. Where differences were identified, the SI group also had increased normalized activity of their middle trapezius, posterior deltoid and biceps muscles whilst activity of their latissimus dorsi, triceps and anterior deltoid were decreased compared to the CG group. No statistically significant differences were found for pectoralis major across any movements. Weighted tasks produced fewer differences in muscle activity patterns compared to unweighted tasks. DISCUSSION: Young people with SI may adapt their movements to minimize glenohumeral joint instability. This was demonstrated by reduced variability in acromioclavicular and sternoclavicular joint angles, adoption of different movement strategies across the same joints and increased activity of the scapular stabilizing muscles, despite achieving similar arm positions to the CG. CONCLUSION: Young people with shoulder instability demonstrated consistent differences in their muscle activity and movement patterns. Consistently observed differences at the shoulder girdle included increased sternoclavicular protraction and elevation accompanied by increased normalized activity of the posterior scapula stabilizing muscles. Existing methods of measurement may be used to inform clinical decision making, however, further work is needed evaluate the prognostic and clinical utility of derived 3D and sEMG data for informing decision making within shoulder instability

Transcriptional, epigenetic and metabolic signatures in cardiometabolic syndrome defined by extreme phenotypes

This is the final version. Available on open access from BMC via the DOI in this recordAvailability of data and materials: The datasets generated during this study are available at EGA under study ID EGAS00001003780. The codes generated during this study and all supplementary tables are available at GitLab https://gitlab.com/dseyres/extremephenotype.Background: This work is aimed at improving the understanding of cardiometabolic syndrome pathophysiology and its relationship with thrombosis by generating a multi-omic disease signature. Methods/Results: We combined classic plasma biochemistry and plasma biomarkers with the transcriptional and epigenetic characterisation of cell types involved in thrombosis, obtained from two extreme phenotype groups (morbidly obese and lipodystrophy) and lean individuals to identify the molecular mechanisms at play, highlighting patterns of abnormal activation in innate immune phagocytic cells. Our analyses showed that extreme phenotype groups could be distinguished from lean individuals, and from each other, across all data layers. The characterisation of the same obese group, six months after bariatric surgery revealed the loss of the abnormal activation of innate immune cells previously observed. However, rather than reverting to the gene expression landscape of lean individuals, this occurred via the establishment of novel gene expression landscapes. Netosis and its control mechanisms emerge amongst the pathways that show an improvement after surgical intervention. Conclusions: We showed that the morbidly obese and lipodystrophy groups, despite some differences, shared a common cardiometabolic syndrome signature. We also showed that this could be used to discriminate, amongst the normal population, those individuals with a higher likelihood of presenting with the disease, even when not displaying the classic features.British Heart FoundationMedical Research Council (MRC)Wellcome TrustNational Institute for Health Research (NIHR)Isaac Newton fellowshipJohn and Lucille Van Geest Foundatio

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology

This is the final version. Available on open access from Nature Research via the DOI in this recordData availability; For ethical and legal reasons access to INTERVAL data are subject to controls. Bona fide scientists can seek access to relevant de-identified individual participant data—including genetic, haematology analyser and proteomic data—and a copy of the trial’s data dictionary by applying to the INTERVAL Data Access Committee using the email address [email protected]. The INTERVAL Data Access Committee (supplemented, when required, by expertise from additional external scientists) meets several times a year to review applications according to the usual academic criteria of scientific validity and feasibility. Following approval by the INTERVAL Data Access Committee, a material transfer or research collaboration agreement will be agreed and signed with the applicants. Applicants might be requested to provide reimbursement of data management or preparation costs, as the INTERVAL trial is no longer in receipt of funding. Applicants will be required to provide updates to the INTERVAL Data Access Committee on their use of the INTERVAL trial data, including provision of copies of any publications. Applicants will be required to adhere in publications with the INTERVAL trial’s policy for acknowledgment of the trial’s funders, stakeholders, and scientific or technical contributors. The GRCh37 genome reference build is available for download from https://grch37.ensembl.org/info/data/ftp/index.html. Genomewide summary statistics may be downloaded by anonymous ftp from ftp://ftp.sanger.ac.uk/pub/project/humgen/summary_statistics/sysmex_blood_cell_genetics. The data from Ulirsch et al.29 are available from https://github.com/caleblareau/singlecell_bloodtraits/, from the Gene Expression Omnibus (GEO) under accession GSE119453 and from the Sequence Read Archive (SRA) under accession PRJNA491478. Other MK epigenetic data were generated by the BLUEPRINT project and are available in the EGA dataset EGAD00001001871.Code availability: The R code used for the association analysis is available in the git repository: https://github.com/ParsaAkbari/UKBB500K-Conditional-Analysis.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

Platelet function is modified by common sequence variation in megakaryocyte super enhancers

Linking non-coding genetic variants associated with the risk of diseases or disease-relevant traits to target genes is a crucial step to realize GWAS potential in the introduction of precision medicine. Here we set out to determine the mechanisms underpinning variant association with platelet quantitative traits using cell type-matched epigenomic data and promoter long-range interactions. We identify potential regulatory functions for 423 of 565 (75%) non-coding variants associated with platelet traits and we demonstrate, through ex vivo and proof of principle genome editing validation, that variants in super enhancers play an important role in controlling archetypical platelet functions

Genetic determinants of risk in pulmonary arterial hypertension: international genome-wide association studies and meta-analysis

Background Rare genetic variants cause pulmonary arterial hypertension, but the contribution of common genetic variation to disease risk and natural history is poorly characterised. We tested for genome-wide association for pulmonary arterial hypertension in large international cohorts and assessed the contribution of associated regions to outcomes. Methods We did two separate genome-wide association studies (GWAS) and a meta-analysis of pulmonary arterial hypertension. These GWAS used data from four international case-control studies across 11744 individuals with European ancestry (including 2085 patients). One GWAS used genotypes from 5895 whole-genome sequences and the other GWAS used genotyping array data from an additional 5849 individuals. Cross-validation of loci reaching genome-wide significance was sought by meta-analysis. Conditional analysis corrected for the most significant variants at each locus was used to resolve signals for multiple associations. We functionally annotated associated variants and tested associations with duration of survival. All-cause mortality was the primary endpoint in survival analyses. Findings A locus near SOX17 (rs10103692, odds ratio 1·80 [95% CI 1·55–2·08], p=5·13×10– ¹⁵) and a second locus in HLA-DPA1 and HLA-DPB1 (collectively referred to as HLA-DPA1/DPB1 here; rs2856830, 1·56 [1·42–1·71], p=7·65×10– ²⁰) within the class II MHC region were associated with pulmonary arterial hypertension. The SOX17 locus had two independent signals associated with pulmonary arterial hypertension (rs13266183, 1·36 [1·25–1·48], p=1·69×10– ¹²; and rs10103692). Functional and epigenomic data indicate that the risk variants near SOX17 alter gene regulation via an enhancer active in endothelial cells. Pulmonary arterial hypertension risk variants determined haplotype-specific enhancer activity, and CRISPR-mediated inhibition of the enhancer reduced SOX17 expression. The HLA-DPA1/DPB1 rs2856830 genotype was strongly associated with survival. Median survival from diagnosis in patients with pulmonary arterial hypertension with the C/C homozygous genotype was double (13·50 years [95% CI 12·07 to >13·50]) that of those with the T/T genotype (6·97 years [6·02–8·05]), despite similar baseline disease severity. Interpretation This is the first study to report that common genetic variation at loci in an enhancer near SOX17 and in HLA-DPA1/DPB1 is associated with pulmonary arterial hypertension. Impairment of SOX17 function might be more common in pulmonary arterial hypertension than suggested by rare mutations in SOX17. Further studies are needed to confirm the association between HLA typing or rs2856830 genotyping and survival, and to determine whether HLA typing or rs2856830 genotyping improves risk stratification in clinical practice or trials. Funding UK NIHR, BHF, UK MRC, Dinosaur Trust, NIH/NHLBI, ERS, EMBO, Wellcome Trust, EU, AHA, ACClinPharm, Netherlands CVRI, Dutch Heart Foundation, Dutch Federation of UMC, Netherlands OHRD and RNAS, German DFG, German BMBF, APH Paris, INSERM, Université Paris-Sud, and French ANR

GWAS meta-analysis of intrahepatic cholestasis of pregnancy implicates multiple hepatic genes and regulatory elements

Intrahepatic cholestasis of pregnancy (ICP) is a pregnancy-specific liver disorder affecting 0.5–2% of pregnancies. The majority of cases present in the third trimester with pruritus, elevated serum bile acids and abnormal serum liver tests. ICP is associated with an increased risk of adverse outcomes, including spontaneous preterm birth and stillbirth. Whilst rare mutations affecting hepatobiliary transporters contribute to the aetiology of ICP, the role of common genetic variation in ICP has not been systematically characterised to date. Here, we perform genome-wide association studies (GWAS) and meta-analyses for ICP across three studies including 1138 cases and 153,642 controls. Eleven loci achieve genome-wide significance and have been further investigated and fine-mapped using functional genomics approaches. Our results pinpoint common sequence variation in liver-enriched genes and liver-specific cis-regulatory elements as contributing mechanisms to ICP susceptibility

Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.The authors would like to acknowledge the participation of National Institute of Health Research (NIHR) Cambridge BioResource volunteers and thank the NIHR Cambridge BioResource staff for their support. The work was funded by a grant from the European Commission 7th Framework Program (FP7/2007–2013, grant 282510, BLUEPRINT) to XE, PF, JHAM, MY, HGS and WHO. WHO is an NIHR senior investigator and receives funding from Bristol-Myers Squibb, the British Heart Foundation, the Medical Research Council and the NIHR. OGI, FJM, AF, JMM, LC and PF are funded by the Wellcome Trust (WT108749/Z/15/Z) with additional funding for specific project components such as GENCODE from the National Human Genome Research Institute of the National Institutes of Health (2U41HG007234), accordingly the content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. KD is a HSST trainee supported by NHS Health Education England. NF is funded by the NIHR Cambridge Biomedical Research Centre. FP is supported by the Fundação Carlos Chagas Filho de Amparo à Pesquisado Estado do Rio de Janeiro (FAPERJ; E-26/203.229/2016). NANJ is a recipient of a scholarship from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES; Finance Code 001). DS work has been supported in part by an Isaac Newton fellowship to MF. MF is supported by the British Heart Foundation (FS/18/53/33863)

Cell type-specific novel long non-coding RNA and circular RNA in the BLUEPRINT hematopoietic transcriptomes atlas.

Transcriptional profiling of hematopoietic cell subpopulations has helped to characterize the developmental stages of the hematopoietic system and the molecular bases of malignant and non-malignant blood diseases. Previously, only the genes targeted by expression microarrays could be profiled genome-wide. High-throughput RNA sequencing, however, encompasses a broader repertoire of RNA molecules, without restriction to previously annotated genes. We analyzed the BLUEPRINT consortium RNA-sequencing data for mature hematopoietic cell types. The data comprised 90 total RNA-sequencing samples, each composed of one of 27 cell types, and 32 small RNA-sequencing samples, each composed of one of 11 cell types. We estimated gene and isoform expression levels for each cell type using existing annotations from Ensembl. We then used guided transcriptome assembly to discover unannotated transcripts. We identified hundreds of novel non-coding RNA genes and showed that the majority have cell type-dependent expression. We also characterized the expression of circular RNA and found that these are also cell type-specific. These analyses refine the active transcriptional landscape of mature hematopoietic cells, highlight abundant genes and transcriptional isoforms for each blood cell type, and provide a valuable resource for researchers of hematologic development and diseases. Finally, we made the data accessible via a web-based interface: https://blueprint.haem.cam.ac.uk/bloodatlas/.The authors would like to acknowledge the participation of National Institute of Health Research (NIHR) Cambridge BioResource volunteers and thank the NIHR Cambridge BioResource staff for their support. The work was funded by a grant from the European Commission 7th Framework Program (FP7/2007–2013, grant 282510, BLUEPRINT) to XE, PF, JHAM, MY, HGS and WHO. WHO is an NIHR senior investigator and receives funding from Bristol-Myers Squibb, the British Heart Foundation, the Medical Research Council and the NIHR. OGI, FJM, AF, JMM, LC and PF are funded by the Wellcome Trust (WT108749/Z/15/Z) with additional funding for specific project components such as GENCODE from the National Human Genome Research Institute of the National Institutes of Health (2U41HG007234), accordingly the content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. KD is a HSST trainee supported by NHS Health Education England. NF is funded by the NIHR Cambridge Biomedical Research Centre. FP is supported by the Fundação Carlos Chagas Filho de Amparo à Pesquisado Estado do Rio de Janeiro (FAPERJ; E-26/203.229/2016). NANJ is a recipient of a scholarship from the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brasil (CAPES; Finance Code 001). DS work has been supported in part by an Isaac Newton fellowship to MF. MF is supported by the British Heart Foundation (FS/18/53/33863)

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.

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

A genome-wide association study of blood cell morphology identifies cellular proteins implicated in disease aetiology.

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