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• Oxidative phosphorylation is a key ontogenetic feature of monocyte immunometabolism promoting myeloid differentiation after birth

  Neonates primarily rely on innate immunity, yet their inflammatory responses to microbes, particularly those of monocytes, are usually restricted compared to adults. This is controversially interpreted as immaturity increasing the risk of sepsis or essential programming allowing immune adaptation after birth. Which changes the cellular immunometabolism undergoes after birth and its role in these concepts are poorly defined. Here, we applied transcriptomic, metabolic, and immunological approaches and found that monocytes exhibit an inverse ontogenetic balance of immunometabolism. Our data show that glycolysis in monocytes increases within the first year of life and fuels their inflammatory responsiveness. In contrast, oxidative phosphorylation (OXPHOS) is high in neonatal monocytes supporting myeloid differentiation but declines only gradually during the first five years of life. Treatment of neonatal monocytes with lipopolysaccharide induces an adult-like immunometabolic phenotype. Ketogenic diet restricts glycolysis in adult monocytes, but cannot reactivate OXPHOS and revive a neonatal-like immunometabolic phenotype, suggesting that neonatal metabolism is hardwired and cannot be restored by simple dietary changes. Transcriptional network and population-wide human variation analyses identified E2F1, MYB, STAT1 and FLI1 as important regulators of age-dependent cell functions and related energy demands in human monocytes. Collectively, our findings show that restricted glycolysis and increased OXPHOS are a physiological programming in neonatal monocytes. Premature switching to an adult-like metabolism could untimely enhance inflammatory responses and disrupt important myeloid differentiation, whereas microbial challenges accumulating during childhood seem to induce an essential gradual metabolic switch.

  Study EGAS00001007555

• H3Africa - Stroke Investigative Research and Education Networks

  Although stroke is a discrete phenotype, it is the clinical culmination of several complex and interacting biological processes, precipitated by various genetic and environmental factors, thereby making ready analyses of its underlying mechanisms a challenge. However, the formulation of successful tailor-made prevention strategies for limiting the immense personal and societal burden of stroke in Sub-Saharan Africa (SSA) is contingent on a better understanding of the predisposing risk factors for stroke in the region, which may not necessarily match the nature of stroke risk factors described among other people on other continents. Indeed, the underlying risk factors for stroke in SSA have hitherto not been comprehensively characterized, and currently there is a paucity of expertise, experience, and infrastructure in genomics and environmental research in SSA, to initiate and sustain such investigation. We seek to establish the Stroke Investigative Research and Education Network (SIREN) as a multidisciplinary collaborative research network of investigators in SSA and the United States collectively focused on exploring ways to promote a better understanding of the genetic and environmental risk factors for stroke among people of African ancestry. SIREN will evaluate unique contributors to stroke in SSA and compare these findings with those in a cohort of African American stroke survivors, all while simultaneously building sustainable capacities in phenomics, biobanking, genomics, biostatistics and bioinformatics for future high-level investigation of stroke and other vascular disease entities in SSA.

  Study EGAS00001007331

• Genome-wide association study identifies common variants associated with breast cancer in South African Black women

  Genome-wide association studies (GWAS) have characterized the contribution of common variants to the development of breast cancer (BC) in populations of European descent, however no GWAS have been reported in resident African populations. This GWAS included 2,485 resident African BC cases and 1,101 population matched controls. Two risk loci were identified, one on chromosome 15, located between UNC13C and RAB27A (rs7181788, p = 1.01x10-08) and a second in an intron of USP22 on chromosome 17 (rs899342, p = 4.62x10-08). RAB27A is a member of the RAS oncogene family associated with invasive growth and metastasis, and UNC13C is involved in tumor progression. The rs899342 SNP is an eQTL for expression of USP22 in a wide range of tissues. Several genome-wide significant signals were detected in a hormone receptor subtype analysis. Comparison of a meta-analysis of other African ancestry BC GWAS datasets predominantly of West African ancestry with our South African data showed limited evidence of shared risk loci, suggesting potential heterogeneity in genetic risk factors for breast cancer in different African populations. A European ancestry derived polygenic risk model for BC was applied to our data, explaining only 0.79% of variance, with an area under the curve of 0.56. This study identified genetic risk factors for BC in a resident African population, but larger studies in this and other African populations are needed to further define the contribution of common variants to BC risk.

  Study EGAS00001008032

• deep-learning-powered tissue deconvolution for cfDNA

  Plasma cell-free DNA (cfDNA) is a noninvasive biomarker for cell death of all organs. Deciphering the tissue origin of cfDNA can reveal abnormal cell death because of diseases, which has great clinical potential in disease detection and monitoring. Despite the great promise, the sensitive and accurate quantification of tissue-derived cfDNA remains challenging to existing methods due to the limited characterization of tissue methylation and the reliance on unsupervised methods. To fully exploit the clinical potential of tissue-derived cfDNA, here we present one of the largest comprehensive and high-resolution methylation atlas based on 521 noncancer tissue samples spanning 29 major types of human tissues. We systematically identified fragment-level tissue-specific methylation patterns and extensively validated them in orthogonal datasets. Based on the rich tissue methylation atlas, we develop the first supervised tissue deconvolution approach, a deep-learning-powered model, cfSort, for sensitive and accurate tissue deconvolution in cfDNA. On the benchmarking data, cfSort showed superior sensitivity and accuracy compared to the existing methods. We further demonstrated the clinical utilities of cfSort with two potential applications: aiding disease diagnosis and monitoring treatment side effects. The tissue-derived cfDNA fraction estimated from cfSort reflected the clinical outcomes of the patients. In summary, the tissue methylation atlas and cfSort enhanced the performance of tissue deconvolution in cfDNA, thus facilitating cfDNA-based disease detection and longitudinal treatment monitoring.

  Study EGAS00001007213

• Using human iPSC-derived oligodendrocytes to explore t(1;11) translocation DAC

  Dac EGAC00001001694

• Whole genome sequencing to identify structural variants in early-stage breast cancer

  Dac EGAC50000000461

• Relationship between low LDL cholesterol concentrations not due to statin therapy and risk of type 2 diabetes: a US-based cross-sectional observational study using electronic medical records

  Lipid lowering therapy using HMG-CoA reductase inhibitors (statins) is associated with an approximately 9-12% increase in the risk of new-onset type 2 diabetes (T2DM). The risk of diabetes could be increased by statins directly; however, genetic approaches have also implicated low LDL cholesterol (LDL-C) concentrations as a risk factor for T2DM. Mendelian randomization studies using functional variants in both HMGCR (GeneID:3156) and PCSK9 (GeneID:255738) genes found a higher risk of T2DM in individuals with variants associated with lower LDL-C concentrations. Since PCSK9 and HMGCR are involved in lipid metabolism through distinct molecular pathways, the altered glycemic effect associated with variants in both genes is likely to be the result of their common effect on LDL-C concentrations. Despite the findings from statin clinical trials and genetic studies, there is little direct evidence implicating low LDL-C concentrations with increased risk of T2DM. Individuals who have very low LDL-C concentrations not due to lipid lowering therapy can provide insights into the relationship between low LDL-C concentrations and T2DM. Here, we used de-identified electronic health records (EHRs) to test the hypothesis that low LDL-C concentrations are associated with T2DM.

  Study phs001588

• Stereotyped B-cell responses are linked to IgG constant region polymorphisms in multiple sclerosis

  Clonally related B cells infiltrate the brain, meninges, and cerebrospinal fluid of multiple sclerosis (MS) patients, but the mechanisms driving the B-cell response and shaping the immunoglobulin repertoires remain unclear. Here, we used single-cell full-length RNA-seq and B-cell receptor reconstruction to simultaneously assess the phenotypes, isotypes, constant region polymorphisms, and the paired heavy- and light-chain repertoires in intrathecal B cells. We detected extensive clonal connections between the memory B cell and antibody-secreting cell compartments and observed clonally related cells of different isotypes, including IgM/IgG1, IgG1/IgA1, IgG1/IgG2, and IgM/IgA1. There was a strong dominance of the G1m1 allotype constant region polymorphisms in antibody-secreting cells, but not in memory B cells. Tightly linked to the G1m1 allotype, we found a preferential pairing of the immunoglobulin heavy-chain variable (IGHV)4 gene family with the κ variable (IGKV)1 gene family. The IGHV4-39 gene was most used and showed the highest frequency of pairing with IGKV1-5 and IGKV1(D)-33. These results link IgG constant region polymorphisms to stereotyped B-cell responses in MS and indicate that the intrathecal B-cell response in these patients could be directed against structurally similar epitopes.

  Study EGAS00001005745

• Sex chromosome aneuploidies give rise to changes in the circular RNA profile

  Purpose The landscape of circular RNAs (circRNAs), an important class of non-coding RNAs that regulate gene expression, has never been described in human disorders of sex chromosome aneuploidies. We profiled circRNAs in Turner syndrome females (45,X;TS) and Klinefelter syndrome males (47,XXY; KS) to investigate how circRNAs respond to a missing or an extra X chromosome. Methods Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. CircRNAs were identified using a combination of circRNA identification pipelines (CIRI2, CIRCexplorer2 and circRNA_finder). Results Differential expression of circRNAs was observed throughout the genome in TS and KS, in all tissues. The host-genes from which several of these circRNAs were derived, were associated with known phenotypic traits. Furthermore, several differentially expressed circRNAs had the potential to capture micro RNAs that targeted protein-coding genes with altered expression in TS and KS. Conclusion Sex chromosome aneuploidies introduce pervasive changes in the circRNA transcriptome, demonstrating that the genomic changes in these syndromes are more complex than hitherto thought. CircRNAs may help explain some of the genomic and phenotypic traits observed in these syndromes.

  Study EGAS00001006404

• PSCP_bisulphite analysis in hESCs (2018-08-13)

  Many studies over the past 10 years, culminating in the recent report of the International Stem Cell Initiative (ISCI, 2011) have shown that hPSC acquire genetic and epigenetic changes during their time in culture. Many of the genetic changes are non-random and recurrent, probably because they provide a selective growth advantage to the undifferentiated cells. Some are shared by embryonal carcinoma cells, the malignant counterparts of ES cells. The origins of these growth advantages are poorly understood, but may come from altered cell cycle dynamics, resistance to apoptosis or altered patterns of differentiation. Less is known about the nature and consequences of epigenetic changes, but it is likely that these similarly affect hPSC behaviour; e.g., enhanced expression of DLK1, an imprinted gene, is associated with altered hPSC growth (Enver et al 2005). Inevitably, these genetic and epigenetic changes will impact on our ability to use hPSC for regenerative medicine, either because malignant transformation of the undifferentiated cells or their differentiated derivatives to be used for transplantation compromises safety, or because they impede the function of those differentiated derivatives, or because they affect the efficiency with which the undifferentiated cells can be expanded and differentiated into desired cell types. Focusing initially upon the existing clinical grade hESC lines, later moving to iPSC, we will Consolidate and extend knowledge of the rate, type and functional impact of the genetic variations that occur during hPSC culture. We will use whole genome and exome sequencing as well as SNP arrays, together with clonal analysis and other cytogenetics techniques. Common changes will be compared with those found in the normal human population, at low frequency in the original cell population or observed during iPSC generation in the HIPSCI project currently based at the WTSI. These studies will provide a better understanding of the range of genetic changes that occur in hPSC beyond the CNVs already identified. In conjunction with cancer genome resources and expertise at WTSI, bioinformatic analyses of these hPSC data will allow us to assess potential impact on hPSC behaviour pertinent to applications in regenerative medicine, notably the likelihood that specific changes arising in undifferentiated PSC cultures may be associated with potential malignant transformation of differentiated progeny. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2018-08-13.

  Dataset EGAD00001004295