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• Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

  Whole genome sequencing data of 57 single (PTA), clonally expanded and bulk human cells. Cells were obtained from bone marrow samples of patients with Fanconi Anemia (PMCFANCNN) or pediatric AML (PBNNNNN), from a clonal intestinal organoid line (STE0072/D-ORGWTNISL), from human cord blood (PMCCB15) and from a human lymphoblastoid cell line (PMCAHH1). WGS libraries were sequenced to ~15-30x genomic coverage (paired-end) on an Illumina Novaseq.

  Dataset EGAD00001011126

• Single-Cell Transcriptomic Characterisation of Patient-Derived Glioblastoma Cell Lines for Co-culture Modelling (Parse Evercode WT v3)

  Patient-derived glioblastoma (GBM) cell lines provide a tractable system to model tumour biology and enable functional studies. Here, we generate single-cell transcriptomic profiles of patient-derived GBM cell lines using Parse Evercode WT v3, including both standard and GFP-labelled variants. These datasets establish a transcriptional reference for subsequent co-culture experiments with patient-derived GBM organoids, enabling the study of cell–cell interactions and tumour microenvironment dynamics.

  Dataset EGAD00001016126

• Personalized Medicine Based on Genomic Data

  Understanding how an individual's genetics are associated with their susceptibility to complex diseases and phenotypes is fundamental to advancing precision medicine. This study involved a series of integrative analyses of biospecimens and corresponding clinical data. This study aims to comprehensively investigate genotype-phenotype associations.

  Study JGAS000874

• Characterizing the Role of the Immune Microenvironment in Multiple Myeloma Progression at a Single Cell Level

  The plasma cell disease multiple myeloma (MM) is highly dependent on its bone marrow microenvironment (BMME). Early alterations within the bone marrow microenvironment that contribute to the progression of multiple myeloma (MM) from its precursor stages could hold the key to identifying novel therapeutic approaches, yet the intrinsic variability in cellular populations between patients together with differences in sample processing and analysis methods have made it difficult to identify consistent changes between datasets. Here, we used single-cell RNA sequencing of BM cells from precursor stages, monoclonal gammopathy of unknown significance (MGUS), smoldering MM (SMM) and newly diagnosed MM and analyzed our data in combination with a previously published dataset that used a similar patient population and sample processing. Despite vast interpatient heterogeneity, some alterations were seen consistently in both datasets. We identified changes in immune cell populations as disease progressed that were characterized by a substantial decrease in memory and naïve CD4 T cells and an increase in CD8+ effector T cells and T-regulatory cells. These alterations were further accompanied by an enrichment of non-clonal memory B cells and an increase of CD14 and CD16 monocytes in MM compared to its precursor stages. These results provide crucial information of the immune changes associated with the progression to clinical MM and can help to develop immune based strategies for patient stratification and early therapeutic intervention. 

  Study phs002756

• Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002004

• Gut metagenome associations with extensive digital health data in a volunteer-based EstMB cohort second timepoint data

  As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2,509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. Out of the 2,509 Estonian Microbiome Project participants, a sub-cohort of over 300 individuals provided an additional stool sample after a median follow-up period of 4.4 years. All participants of the EstMB cohort gave informed consent for the data and samples to be used for scientific purposes. In the second time point, the participants were instructed to send the samples by post immediately after taking the sample and time their sample collection to avoid shipping on the weekends. In the study, by utilising retrospective medication usage data from the electronic health records and the Estonian microbiome cohort shotgun metagenomics data set (n = 2,509), we systematically evaluate the long-term effects of antibiotics and human-targeted medications on the gut microbiome. We show that past usage of medications is associated with the gut microbiome. For example, the effects of antibiotics, psycholeptics, antidepressants, proton pump inhibitors, and beta-blockers are detectable several years after use. Furthermore, by analysing a subcohort (n >300 individuals) from the second time point, we show that similar changes in the gut microbiome occur after treatment initiation or discontinuation, possibly indicating causal effects.

  Study EGAS50000001181

• Memory-like HCV-specific CD8+ T cells retain a chronic scar after cure of chronic HCV infection

  Chronic hepatitis C virus (HCV) infection is associated with CD8+ T-cell exhaustion characterized by limited effector functions and thus compromised anti-viral activity. Exhausted HCV-specific CD8+ T cells are comprised of memory-like and terminally exhausted CD8+ T-cell subsets. So far, little is not known about the molecular profile and fate of these cells after elimination of chronic antigen stimulation by direct acting antiviral therapy (DAA). Here, we report an antigen-driven molecular core signature underlying exhausted CD8+ T-cell subset heterogeneity in chronic viral infection with a progenitor/progeny relationship of memory-like and terminally exhausted HCV-specific CD8+ T cells via an intermediate stage. Furthermore, transcriptional profiling reveals that the memory-like cells remain after DAA-mediated cure while terminally exhausted HCV-specific CD8+ T-cell subsets are lost. Thus, the memory polarization of the overall HCV-specific CD8+ T-cell response after cure does not result from re-differentiation of exhausted T cells. Consequently, antigen elimination has little impact on the exhausted core signature of memory-like CD8+ T cells that remains clearly different from bona fide T-cell memory. These results identify a molecular signature of T-cell exhaustion that is imprinted like a chronic scar in HCV-specific CD8+ T cells even after HCV cure, highlighting the requirement of re-programming to elicit full effector potential of exhausted T cells.

  Study EGAS00001004538

• Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized controlled trial AGITG-MAX

  Patients and methods: We analyzed tumor samples of 256 patients enrolled in the AGITG-MAX 3-arm randomized controlled trial (RCT) who were randomly assigned to receive either capecitabine, or capecitabine and bevacizumab with- or without mitomycin. Chromosome 18q11.2-q12.1 copy number status was measured and correlated with PFS according to a predefined analysis plan with marker-treatment interaction as the primary end-point.Results: Chromosome 18q11.2-q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the non-randomized study, significant PFS benefit of bevacizumab was observed in chromosome 18q11.2-q12.1 loss patients (P=0.009), and not in 18q no-loss patients (P=0.67). Although significance for marker-treatment interaction was not reached (Pinteraction = 0.28), hazard ratio and 95% confidence interval (HRinteraction 0.72, CI 0.39 - 1.32) show striking overlap with the non-randomized study cohorts (HRinteraction 0.41, CI 0.32 - 0.8) supported by a non-significant Cochrane chi-squared (P=0.11) for heterogeneity. Conclusions: PFS characteristics for marker positive- and negative patients randomized for treatment with- or without bevacizumab were consistent with those of the non-randomized discovery study, though the number of AGITG-MAX samples fell short to reach significance for marker-treatment interaction. Post-hoc analysis of the AGITG-MAX RCT provides supportive evidence for chromosome 18q11.2-q12.1 as a clinically relevant predictive marker for mCRC patients.

  Study EGAS00001005453

• Study of 5'UTR Mutations in Prostate Cancer

  The 5' untranslated region (5' UTR) of mRNA controls the translation of specific transcripts through encoded cis-regulatory elements. Yet exceedingly little is known about the prevalence and function of 5' UTR mutations in cancer. We have uncovered many 5' UTR mutations in our analysis of localized and castration resistant prostate cancer patients, and hypothesize that systematic mutations in critical 5' UTR regulatory regions perturb gene expression to drive prostate cancer progression. To elucidate the functional 5' UTR regulatory landscape of prostate cancer, we have taken a multi-faceted approach including ribosome profiling, in vitro reporter assays and the development of a novel high throughput method to functionally access the impact of recurrent 5' UTR mutations on both transcription and translation.

  Study phs001825

• NHLBI TOPMed: The Genetics and Epidemiology of Asthma in Barbados

  Asthma is a complex disease where the interplay between genetic factors and environmental exposures influences susceptibility and disease prognosis. Asthmatics of African descent tend to have more severe asthma and more severe clinical symptoms than individuals of European ancestry. The baseline prevalence of asthma in Barbados is high (~20%), and from admixture analyses, we have determined that the proportion of African ancestry among Barbadian founders is similar to U.S. African Americans, rendering this a unique population to disentangle the genetic basis for asthma disparities among African ancestry populations in general. We therefore performed whole genome sequencing on 1,100 individuals from the Barbados Genetics of Asthma Study (BAGS), in order to generate additional discovery of rare and structural variants that may control risk to asthma.

  Study phs001143