Search Results - EGA European Genome-Phenome Archive

DNA hypermethylation and differential gene expression associated with Klinefelter syndrome

The molecular basis for the phenotypic traits and morbidity in Klinefelter syndrome (KS) are not clarified. As DNA methylation affect gene expression and thereby play a role in disease susceptibility, we performed genome-wide DNA methylation profiling of leucocytes from peripheral blood samples from 67 KS patients, 67 male controls and 33 female controls, in addition to genome-wide RNA-sequencing profiling in a subset of 9 KS patients, 9 control males and 13 female controls. Characterization of the methylome as well as the transcriptome of both coding and non-coding genes identified a unique epigenetic and genetic landscape of both autosomal chromosomes as well as the X chromosome in KS. A subset of genes show significant correlation between methylation values and expression values. Gene set enrichment analysis of differentially methylated positions yielded terms associated with well-known comorbidities seen in KS. In addition, differentially expressed genes revealed enrichment for genes involved in the immune system, wnt-signaling pathway and neuron development. Based on our data we point towards many new candidate genes (AKAP17A, AMOT, APOB, DACT1, DDX58, DOCK7, EIF2S3, FIGNL1, G3BP1, HENMT1, HERC5, IFI44, IFI44L, IFIT1, IFIT3, ISG15, KANK1, LGALS1, NSD1, PEX10, PLSCR1, RSAD2, SHROOM2, SLC25A6, SPEG, SPON2, TXLNG), which may be implicated in the phenotype and further point towards non-coding genes (RP13-216E22.4, RP13-36G14.4, G087825, G088512), which may be involved in X chromosome inactivation in KS and in the regulation of escape genes.

Study EGAS00001002797

A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

Radiation-induced glioma (RIG) is a highly aggressive brain cancer arising as a consequence of radiation therapy. We report a case of RIG that arose in the brain stem following treatment for paediatric medulloblastoma, and the development and characterisation of a matched orthotopic patient-derived xenograft (PDX) model (TK-RIG915). Patient and PDX tumours were analysed using DNA methylation profiling, whole genome sequencing (WGS) and RNA sequencing. While initially thought to be a diffuse intrinsic pontine glioma (DIPG) based on disease location, results from methylation profiling and WGS were not consistent with this diagnosis. Furthermore, clustering analyses based on RNA expression suggested the tumours were distinct from primary DIPG. Additional gene expression analysis demonstrated concordance with a published RIG expression profile. Multiple genetic alterations that enhance PI3K/AKT and Ras/Raf/MEK/ERK signalling were discovered in TK-RIG915 including an activating mutation in PIK3CA, upregulation of PDGFRA and AKT2, inactivating mutations in NF1, and a gain-of-function mutation in PTPN11. Additionally, deletion of CDKN2A/B, increased IDH1 expression, and decreased ARID1A expression were observed. Detection of phospho-S6, -4EBP1 and -ERK via immunohistochemistry confirmed PI3K pathway and ERK activation. Here, we report one of the first PDX models for RIG, which recapitulates the patient disease and is molecularly distinct from primary brain stem glioma. Genetic interrogation of this model has enabled the identification of potential therapeutic vulnerabilities in this currently incurable disease.

Study EGAS00001004709

Whole-genome sequencing of normal Singaporean volunteers

Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST. Among others, male gender (β = -15.539, 95% confidence interval [CI] = -26.245 - -4.832, p = 0.005), older age (β = -0.493, CI = -0.941 - -0.044, p = 0.032) and manual labor (β = -26.856, CI = -49.715 - -3.997, p = 0.022) were associated with reduced TST, whereas alcohol consumption (β = 19.247, CI = 8.008 - 30.486, p = 8.54x10-04) was associated with increased TST. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with various cardiovascular disease risk markers such as body mass index (β = -0.006, CI = -0.00 - -0.000, p = 0.040) and waist circumference (β = 0.001, CI = -0.015-0.017, p = 0.893), whereas self-reported measures were not. We then showed that insufficient sleep was associated with premature telomere attrition, using telomere length estimated using whole-genome sequencing (β = 1.275, CI = 0.187 - 2.363, p = 0.023) and quantitative PCR (β = 0.001, CI = 8.318x10-05 - 0.001, p = 0.028). Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies.

Study EGAS00001004007

Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

Constitutional LZTR1 or SMARCB1 pathogenic variants have been found in ~86% of familial and ~40% of sporadic schwannomatosis cases. Hence, we performed massively parallel sequencing of the entire LZTR1, SMARCB1 and NF2 genomic loci in 35 individuals with schwannomas negative for constitutional first-hit pathogenic variants in the LZTR1/SMARCB1/NF2 coding sequences, however with 22q deletion and/or a different NF2 pathogenic variant in each tumor, including six cases with only one tumor available. Furthermore, we verified whether any other LZTR1/SMARCB1/NF2 (likely) pathogenic variant(s) could be found in 16 cases carrying a SMARCB1 constitutional variant in the 3’ untranslated region (3’-UTR) c.*17C>T, c.*70C>T or c.*82C>T. As no additional variants were found, functional studies were performed to clarify the effect of these 3’-UTR variants on the transcript. The 3’-UTR variants c.*17C>T and c.*82C>T showed pathogenicity by negatively affecting SMARCB1 transcript level. Two novel deep intronic SMARCB1 variants, c.500+883T>G and c.500+887G>A, resulting in out-of-frame missplicing of intron 4, were identified in two unrelated individuals. Further resequencing of the entire repeat - masked genomics sequences of chromosome 22q in individuals negative for pathogenic variants in the SMARCB1/LZTR1/NF2 coding- and non-coding regions revealed five potential schwannomatosis-predisposing candidate genes, i.e. MYO18B, NEFH, SGSM1, SGSM3 and SBF1, pending further verification.

Study EGAS00001005680

Epigenetic age deceleration reflects fitness improvements following a six-month endurance exercise intervention

Epigenetic clocks are emerging as promising biomarkers of biological aging, yet their sensitivity to short-term interventions remains unclear. This pilot study investigates whether the GrimAge clock can capture the effects of a six-month cycling-based endurance exercise training intervention, with cardiorespiratory fitness (VO₂ max) and body composition as primary outcomes. We enrolled 42 adults aged 35-65, of whom 38 completed the study and 33 adhered to the protocol (>66% adherence). Participants demonstrated significant improvements in VO₂ max (+20%, P < 0.001) and body composition (P < 0.001). High-quality epigenetic data preprocessing yielded highly reproducible GrimAge estimates (< 2 months measurement error), which strongly correlated with chronological age (R² = 0.86, P < 0.001). On average, GrimAge decreased by 7.44 months relative to the expected trajectory (P = 0.012), reflecting improvements in VO₂ max (R² = 0.27, P = 0.002) but not body composition changes. Notably, GrimAge changes strongly correlated with fluctuations in leukocyte composition, particularly neutrophil fraction (R² = 0.74, P < 0.001). Adjusting for leukocyte composition improved consistency in GrimAge changes, aligning them with additional intervention outcomes and explaining up to 81% of variance. These findings demonstrate that GrimAge is responsive to short-term endurance training, serving as a meaningful biomarker of improved cardiorespiratory fitness, while also capturing immune system variability. This study supports the use of GrimAge in evaluating longevity interventions and highlights the importance of accounting for leukocyte composition in epigenetic aging research.

Study EGAS00001008221

Conserved features of TERT promoter duplications reveal an activation mechanism that mimics hotspot mutations in cancer

Mutations in the TERT promoter are the single most common non-coding mutation in cancer and represent the genetic underpinnings of tumor cell immortality. Beyond the two most common point mutations, G228A and G250A, which selectively recruit the ETS factor GABP to activate TERT, the significance of other variants in the TERT promoter are unknown. We identified duplications of wildtype sequence within the core promoter region of TERT in 7 different cancer types that have strikingly similar features including size, insertion position, and inclusion of one of the native ETS motifs. Each duplication activates the TERT promoter to a similar level as G228A and G250A and is critically dependent on the insertion site. The GABP tetramer binds to the TERT duplicated promoter sequence by virtue of the native ETS motif and its duplicated version with precise spacing, and it is necessary for the transcriptional activation by all duplications tested. Spatiotemporal analysis in a multifocal glioblastoma shows the duplication is clonal and its activation of TERT is readily detectable at the single cell level and in bulk tumor tissue. We conclude that recurrent TERT promoter duplications of the native ETS sequence are functionally and mechanistically equivalent to the hotspot mutations that confer tumor cell immortality. The shared mechanism of these divergent somatic genetic alterations suggests a strong selective pressure for recruitment of the GABP tetramer to activate TERT.

Study EGAS00001006118

Epigenome Wide DNA Methylation Study for Osteoporosis Risk

Osteoporosis is characterized by low bone mineral density (BMD). The advancement of high-throughput technologies and integrative approaches provided an opportunity for deciphering the mechanisms underlying osteoporosis. In this study, we generated genomic (from whole blood DNA), transcriptomic and methylomic (from peripheral blood monocytes, PBMs), and serum metabolomic datasets from 143 premenopausal Caucasian females aged 25-40 years, including 74 with relatively high hip BMD (Z scores ≥ 0.8) and 69 with relatively low hip BMD (Z scores ≤ -0.8). The BMD Z score was defined as the number of standard deviations a subject's BMD differed from the mean BMD of their age-, gender-, and ethnicity-matched population. We identified differentially methylated CpG sites (DMCs) in peripheral blood monocytes (PBMs) at the whole methylome level between premenopausal women with high BMD and those with low BMD and deciphered how the DMCs influence the BMD variation through affecting the expression of the relevant genes. We also performed differential gene expression and metabolic analysis to assess their biological interaction and causal mechanisms. Our study provided novel insights into the pathogenesis of osteoporosis.

Study phs001960

Advancing fast in the analysis of circulating tumour DNA

In cancer patients, solid tumours also release DNA fragments into the blood, and they are called Circulating Tumours DNA (ctDNA). Nowadays, the standard procedure for cancer monitoring is analysis of surgically obtained biopsies. They generate a big amount of material, but the operation is highly invasive and provide medical doctors with a single-time snapshot of the tumours, which are often highly changeable. Analysis of ctDNA, on the other hand, can provide continuous information regarding the tumour itself without the need of invasive procedures. This is why interest in this method is growing, and with it, the need for its technological optimization. Guanhua Zhu and colleagues, at the Genome Institute of Singapore, developed a methodology to quantify ctDNA burden, which means to estimate the amount of tumours derived circulating DNA among all cell-free DNA in the blood of individuals. Their work, published in Nature Communications in april 2021 and summarized in a sketch below, uses state-of-the art methods to analyse cfDNA degradation patterns at promoters and exon regions, to discern it from the DNA coming from the tumours. The bright point of their approach is that simultaneously enable for profiling of actionable cancer mutations and quantitative estimation of ctDNA burden. Their sequencing data of ctDNA has been deposited in the EGA under the accession number EGAS00001004657. This study sums up to a total of 37 of cfDNA and 36 about ctDNA present up to date in the EGA archive. The existence of cfDNA was firstly described back in 2002, while the use of ctDNA analysis in the oncological field exploded only after 2016. The approach is rapidly evolving, moving in parallel with the ever-improving sequencing technologies. Especially, the possibility to obtain high quality sequences from minimal amount of material is a crucial factor. Being able to alleviate cancer patients of disturbing and often slow-recovery procedures, while at the same time improving the quality of diagnosis and disease monitoring seems like a lot to ask. Thankfully, we are blessed with brilliant and dedicated scientists from all around the world who collaborate to make this a reality, sharing their results, knowledge and data.

Blog advancing-fast-in-the-analysis-of-circulating-tumour-dna

Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

Study EGAS50000001554

The dataset of Southeast Borneo individuals (Banjar and Ngaju ethnic groups) was used as comparative data to determine the Asian parental population of the Malagasy. Our study found strong support for an origin of the Asian ancestry of Malagasy among the Banjar.

Malagasy genetic diversity results from an exceptional proto-globalisation process that took place over a thousand years ago across the Indian Ocean. Previous efforts to locate the Asian origin of Malagasy have highlighted Borneo broadly as a potential source, but so far no firm source populations have been identified. Here, we have generated genome-wide data from two Southeast Borneo populations, the Banjar and the Ngaju, together with published data compiled from populations across the Indian Ocean region. We find strong support for an origin of the Asian ancestry of Malagasy among the Banjar. This group emerged from the long-standing presence of a Malay Empire trading post in Southeast Borneo, which favoured admixture between the Malay and an autochthonous Borneo group, the Ma’anyan. Reconciling genetic, historical and linguistic data, we show that the Banjar, in Malay-led voyages, were the most probable Asian source among the analysed groups in the founding of the Malagasy gene pool.

Study EGAS00001001841

An instructive role for IL7RA in the development of human B-cell precursor leukemia

Kinase signaling fuels growth of B-cell precursor acute lymphoblastic leukemia (BCP-ALL). Yet its role in leukemia initiation is unclear and has not been shown in primary human hematopoietic cells. We previously described activating mutations in interleukin-7 receptor alpha (IL7RA) in poor-prognosis “ph-like” BCP-ALL. Here we show that expression of activated mutant IL7RA in human CD34+ hematopoietic cells creates a preleukemic state in transplanted NOD/LtSz-scid IL2Rγnull mice, characterized by persistence of self-renewing Pro-B cells with non-productive V(D)J gene rearrangements. Preleukemic CD34+CD10highCD19+ cells evolved to a BCP-ALL with spontaneously acquired CDKN2A deletions as commonly observed in primary human BCP-ALL. CRISPR mediated silencing of CDKN2A in primary human CD34+ cells transduced with activated IL7RA resulted in robust development of BCP-ALLs in-vivo. Thus, we demonstrate for the first time that constitutive activation of IL7RA can initiate preleukemia in primary human hematopoietic progenitors and cooperates with CDKN2A silencing in progression into BCP-ALL.

Study EGAS00001005347

TenK10K Phase 1: Single Cell

Understanding the genetic basis of gene expression can shed light on the regulatory mechanisms underlying complex traits and diseases. Single-cell resolved measures of RNA levels and single-cell expression quantitative trait loci (sc-eQTLs) have revealed genetic regulation that drives sub-tissue cell states and types across diverse human tissues. Here, we describe the first phase of TenK10K, the largest- to-date dataset of matched whole-genome sequencing (WGS) and single-cell RNA-sequencing (scRNA-seq). We leverage scRNA-seq data from over 5 million cells across 28 immune cell types and matched WGS from 1,925 individuals. This provides power to detect associations between rare and low-frequency genetic variants that have largely been uncharacterised in their impact on cell-specific gene expression. We map the effects of both common and rare variants in a cell type specific manner using SAIGE-QTL.

Study EGAS50000001653

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DNA hypermethylation and differential gene expression associated with Klinefelter syndrome

A novel orthotopic patient-derived xenograft model of radiation-induced glioma following medulloblastoma

Whole-genome sequencing of normal Singaporean volunteers

Targeted sequencing of candidate regions on chromosome 22q predisposing to multiple schwannomas

Epigenetic age deceleration reflects fitness improvements following a six-month endurance exercise intervention

Conserved features of TERT promoter duplications reveal an activation mechanism that mimics hotspot mutations in cancer

Epigenome Wide DNA Methylation Study for Osteoporosis Risk

Advancing fast in the analysis of circulating tumour DNA

Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

The dataset of Southeast Borneo individuals (Banjar and Ngaju ethnic groups) was used as comparative data to determine the Asian parental population of the Malagasy. Our study found strong support for an origin of the Asian ancestry of Malagasy among the Banjar.

An instructive role for IL7RA in the development of human B-cell precursor leukemia

TenK10K Phase 1: Single Cell

Non Tumour Renal Cell Line Sequencing

Splenic Marginal Zone Lymphoma with villous lymphocytes exome sequencing

Genome and transcriptome sequence data from a metastatic large cell neuroendocrine tumour of the lung patient

Genome and transcriptome sequence data from a metastatic colorectal cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a serous carcinoma of fallopian tube patient

Genome and transcriptome sequence data from a metastatic adult granulosa cell tumour patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic adenocarcinoma of the lung patient

Genome and transcriptome sequence data from a metastatic medullary thyroid cancer patient

Genome and transcriptome sequence data from a metastatic colorectal cancer patient

Genome and transcriptome sequence data from a metastatic adenocarcinoma presumably of ovarian origin patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic uterine leiomyosarcoma patient

Genome and transcriptome sequence data from a squamous cell carcinoma of the lung patient

Genome and transcriptome sequence data from a metastatic adenocarcinoma of the rectum patient

Genome and transcriptome sequence data from a metastatic gastric cancer patient

Genome and transcriptome sequence data from a metastatic colon cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic ductal carcinoma of the breast patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic colon cancer patient

Genome and transcriptome sequence data from a metastatic clear cell sarcoma patient

Genome and transcriptome sequence data from a metastatic uveal melanoma patient

Genome and transcriptome sequence data from a low grade serous ovarian cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic colorectal cancer patient

Genome and transcriptome sequence data from a metastatic renal cell carcinoma patient

Genome and transcriptome sequence data from an anaplastic myxopapillary ependymoma patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic breast cancer patient

Genome and transcriptome sequence data from a metastatic collecting duct kidney cancer patient

Genome and transcriptome sequence data from a metastatic gastric adenocarcinoma patient

Genome and transcriptome sequence data from a metastatic breast cancer patient