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• International consensus definition of DNA methylation subgroups in juvenile myelomonocytic leukemia

  Known clinical and genetic markers have limitations in predicting disease course and outcome in juvenile myelomonocytic leukemia (JMML). DNA methylation (DNAme) patterns in JMML have correlated with outcome across multiple studies, suggesting it as a biomarker to improve patient stratification. However, standardized approaches to classify JMML based on DNAme patterns are lacking. We therefore sought to define an international consensus for DNAme subgroups in JMML and develop classification methods for clinical implementation.

  Study EGAS00001004682

• An isogenic human iPSC model unravels neurodevelopmental abnormalities in SMA

  Whether neurodevelopmental defects underlie the selective neuronal death that characterizes neurodegenerative diseases is becoming an intriguing question. To address it, we focused on the motor neuron (MN) disease Spinal Muscular Atrophy (SMA), caused by reduced levels of the ubiquitous protein SMN. Taking advantage of the first isogenic human induced pluripotent stem cell-derived SMA model that we have generated and a spinal cord organoid system, here we report that the relative and temporal expression of early neural progenitor and MN markers is altered in SMA. Furthermore, the corrected isogenic controls only partially reverse these abnormalities. These findings raise the relevant clinical implication that SMN-increasing treatments might not fully amend SMA pathological phenotypes. The approach we have taken demonstrates that the discovery of new disease mechanisms is greatly improved by using human isogenic models. Moreover, our study implies that SMA has a developmental component that might trigger the MN degeneration.

  Study EGAS00001007259

• Exploring the role of mtDNA variation in Multiple Sclerosis in a large cohort of discordant monozygotic twins

  Several lines of evidence indicate that mitochondrial DNA (mtDNA) variants might predispose to multiple sclerosis (MS). We examined this in 49 monozygotic (MZ) twin pairs clinically discordant for MS at study entry. Since the nuclear DNA of MZ twins is identical, our study provides a unique setting to functionally associate unique mtDNA variants and skewed heteroplasmy with MS development. In order to identify mtDNA variants in the twin cohort, we deeply sequenced the mitochondrial genome in blood of all 49 MZ twin pairs using next generation sequencing (Illumina, HiSeq or MiSeq) with an average coverage depth of ~25,000 sequences per base. Heteroplasmic variants were validated using targeted deep sequencing (TDS) (Illumina, MiSeq) in DNA isolated from blood and buccal swabs. In addition, whole blood was also available of 5 additional MS-affected or healthy siblings and 1 dizygotic twin pair discordant for MS, comprising in total 6 non-identical sib pairs. Moreover, all cases were screened for pathogenic mtDNA polymerase gamma (POLG) mutations. The data provides valuable insights in the possible involvement of mtDNA variants in the pathogenesis of MS, and gives information on the segregation of heteroplasmic variants within MZ twins and non-identical siblings and across different tissues.

  Study EGAS00001001240

• BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples (DLBCL-panel)

  This dataset contains BAM files from capture-based targeted sequencing of 4 agressive B-cell lymphoma tumour samples for cases 2, 3, 4 and 13. The sequencing panel used is a DLBCL-oriented panel containing 136 genes, described in Mozas P. et al., Hematol Oncol 2023.

  Dataset EGAD50000000802

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• bulk RNA-Seq samples of CRC patients

  The dataset contains samples of 30 CRC patients (3 samples for each patient, tumor and 2 normal adjacent tissue sites, 90 samples in total). Dataset is composed by fastq file (paired end) type from bulk RNA-Seq.

  Dataset EGAD00001009635

• scRNAseq data from ALI cultures of healthy donors and patients with asthma, infected with RSV

  This dataset contains the count matrices and corresponding metadata for our study on bronchial epithelial cells response to RSV in healthy and in asthma. This scRNAseq data is from primary cells, that have been differentiated in ALI cultures and infected with RSV.

  Dataset EGAD00001011264

• Genomic determinants of response and resistance to inotuzumab in B-ALL

  Inotuzumab Ozogamicin (InO) is an antibody-drug conjugate which delivers calicheamicin to CD22-expressing cells. In a retrospective cohort of InO treated B-cell acute lymphoblastic leukemia (B-ALL) patients, we sought to understand the genomic determinants of response to InO. Acquired CD22 mutations were observed in 11% (3/27) of post-InO relapsed samples. CD22 mutation types were diverse (frameshift, nonsense, missense and stoploss) and we identified multiple mechanisms of mutation induced CD22 escape, including protein truncation, protein destabilization, and epitope alteration. Accelerated acquisition of mutations by error-prone DNA damage repair could drive CD22 mutation and escape. Acquired loss-of-function mutations in TP53, ATM and CDKN2A were observed, suggesting compromise of the G1/S DNA damage checkpoint as a mechanism of evading InO-induced apoptosis. In conclusion, genetic alterations modulating CD22 expression and DNA damage response influence InO efficacy. The diverse mechanisms of CD22 escape advocates for a refined approach for monitoring CD22-targeted therapy.

  Study EGAS50000000067

• Human islet 3D chromatin maps provide insights into type 2 diabetes

  The transcriptional output of each cell type is controlled by thousands of enhancers, many of which contain genetic risk variants for common diseases such as type 2 diabetes (T2D). To gain insight into how enhancer variation influences diabetes risk, we created promoter capture Hi-C maps in human pancreatic islets. This linked diabetes-associated islet enhancers with their target genes, often located hundreds of kilobases away. We identified hubs that show spatial and functional connections between enhancersand target genes related to islet function and diabetes. We demonstrate that genetic variants distributed across hub enhancers have a major impact on T2D heritability, and use this knowledge to identify individuals in whom islet regulatory variation has a prominent role in T2D risk. Our results demonstrate the importance of 3D chromatin architecture for molecular interpretation of T2D genetic association signals, and define genomic spaces that harbor a distinct component of the T2D polygenic burden.

  Study EGAS00001002917

• Genome-wide Rare Variant Score Associates With Morphological Subtypes of Autism Spectrum Disorder

  Defining different genetic subtypes of Autism Spectrum Disorder (ASD) can help predict developmental outcomes. Based on minor physical and major congenital anomalies, we categorized 325 Canadian children with ASD into dysmorphic and non-dysmorphic subgroupings. We developed a method to calculate a genome-wide rare variant score (GRVS) from whole-genome sequencing (WGS) data for each ASD proband. GRVS is a sum of the number of variants in morphology-associated coding and non-coding regions, weighted by their effect sizes. Probands with dysmorphic ASD had a significantly higher GRVS compared to those with non-dysmorphic ASD (P= 0.027). Using the polygenic transmission disequilibrium test, we observed an over-transmission of ASD-associated common variants in non-dysmorphic ASD probands (P= 2.9×10-3). We replicated our findings using 442 ASD probands that had accompanying morphology data in the Simons Simplex Collection. Our findings provide support for an alternative genomic classification of ASD subgroups using morphology data, which may inform intervention protocols.

  Study EGAS00001005753