{"entity": "journal", "iuid": "a31f445f31764e128bdff346ac4ebcf2", "timestamp": "2026-08-15T13:00:32.756Z", "links": {"self": {"href": "https://publications.scilifelab.se/journal/Genome%20Med.json"}, "display": {"href": "https://publications.scilifelab.se/journal/Genome%20Med"}}, "title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "publications_count": 19, "publications": [{"entity": "publication", "iuid": "43f86786cbb24b618ae7f2e4aff2b849", "links": {"self": {"href": "https://publications.scilifelab.se/publication/43f86786cbb24b618ae7f2e4aff2b849.json"}, "display": {"href": "https://publications.scilifelab.se/publication/43f86786cbb24b618ae7f2e4aff2b849"}}, "title": "Multiomics assessment of lung adenocarcinoma subtypes defined through tumor purity-adjusted DNA methylation.", "authors": [{"family": "Nacer", "given": "Deborah F", "initials": "DF"}, {"family": "Arbajian", "given": "Elsa", "initials": "E"}, {"family": "Veerla", "given": "Srinivas", "initials": "S"}, {"family": "Aine", "given": "Mattias", "initials": "M"}, {"family": "J\u00f6nsson", "given": "Mats", "initials": "M"}, {"family": "Rosengren", "given": "Frida", "initials": "F"}, {"family": "Karlsson", "given": "Anna", "initials": "A"}, {"family": "Salomonsson", "given": "Annette", "initials": "A"}, {"family": "Isaksson", "given": "Sofi", "initials": "S"}, {"family": "Planck", "given": "Maria", "initials": "M"}, {"family": "Staaf", "given": "Johan", "initials": "J"}], "type": "journal article", "published": "2026-02-14", "journal": {"title": "Genome Med", "issn": "1756-994X", "volume": "18", "issue": "1", "issn-l": "1756-994X"}, "abstract": "Molecular subtypes of lung adenocarcinoma (LUAD) with varying prognosis and characteristics have been proposed based on one or two-dimensional studies but are not yet implemented into clinical routine. Epigenetic modifications in cancer cells are independent of sequence variants, directly linked to gene and genome regulation, and thus provide important information to guide subclassification efforts.\n\nWe performed in-depth epigenomic profiling of 95 primary LUAD samples from a Swedish discovery cohort with comprehensive clinicopathological, epigenomic, genomic, transcriptomic, proteomic, and metabolomic data. Additionally, we estimated pure tumor cell methylomes using a computational approach. We subdivided the discovery cohort into four epigenetic subtypes, the epitypes, reflecting distinct tumor cell methylation states. Resulting epitypes were contrasted based on clinicopathological and molecular features, and our main findings were validated in two additional primary tumor cohorts totaling over 700 samples.\n\nOf the four DNA methylation epitypes, M1-M4, M1 and M4 were associated with the previously proposed mRNA subtypes Terminal Respiratory Unit and Proximal Proliferative, respectively. Epitypes M2 and M3 showed similar mRNA/protein subtype composition but differed with respect to e.g., higher expression of the LUAD histology-associated NAPSA/surfactant metabolism expression metagene in M3. Genes included in this metagene showed lower DNA methylation in M3, counter to a global tendency towards promoter hypermethylation in this epitype. To further delineate tumor intrinsic links between the epigenomic and expression phenotypes, 62 LUAD cell lines classified into the four epitypes were investigated and recapitulated several characteristics from the tumor epitypes, such as methylation and expression pattens of NAPSA/surfactant genes, highlighting epigenetic states as likely drivers or maintainers of broad tumor phenotypes and differentiation states.\n\nDissecting LUAD based on combined biological characteristics using multiomics data has deepened our understanding of the heterogeneity in this complex disease and the mechanisms underlying phenotype formation and maintenance. There remains a critical need for large, publicly accessible, well-annotated multiomic LUAD cohorts to support rigorous subtype discovery and validation, particularly those linked to targeted therapy trial outcomes.\n\nThe online version contains supplementary material available at 10.1186/s13073-026-01609-x.", "doi": "10.1186/s13073-026-01609-x", "pmid": "41691315", "labels": {"NGI SNP genotyping": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "National Genomics Infrastructure": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12927254"}, {"db": "pii", "key": "10.1186/s13073-026-01609-x"}], "notes": [], "created": "2026-06-01T11:12:56.465Z", "modified": "2026-06-01T11:12:56.469Z"}, {"entity": "publication", "iuid": "43121743f286455382be9baac0b2e1c9", "links": {"self": {"href": "https://publications.scilifelab.se/publication/43121743f286455382be9baac0b2e1c9.json"}, "display": {"href": "https://publications.scilifelab.se/publication/43121743f286455382be9baac0b2e1c9"}}, "title": "Multi-omics data integration from patients with carotid stenosis illuminates key molecular signatures of atherosclerotic instability.", "authors": [{"family": "Das", "given": "Vivek", "initials": "V"}, {"family": "Narayanan", "given": "Sampath", "initials": "S"}, {"family": "Zhang", "given": "Xiang", "initials": "X"}, {"family": "Bergman", "given": "Otto", "initials": "O"}, {"family": "Djordjevic", "given": "Djordje", "initials": "D"}, {"family": "Kronqvist", "given": "Malin", "initials": "M"}, {"family": "Chemaly", "given": "Melody", "initials": "M"}, {"family": "Karadimou", "given": "Glykeria", "initials": "G"}, {"family": "Sundman", "given": "Sofija", "initials": "S"}, {"family": "Prasad", "given": "Inika", "initials": "I"}, {"family": "Buckler", "given": "Andrew J", "initials": "AJ"}, {"family": "Knape", "given": "Karin Conde", "initials": "KC"}, {"family": "Michaelsen", "given": "Natasha Barascuk", "initials": "NB"}, {"family": "Hedin", "given": "Ulf", "initials": "U"}, {"family": "Matic", "given": "Ljubica", "initials": "L"}], "type": "journal article", "published": "2026-02-06", "journal": {"title": "Genome Med", "issn": "1756-994X", "volume": "18", "issue": "1", "issn-l": "1756-994X"}, "abstract": "Understanding the pathophysiology of unstable atherosclerosis is imperative to prevent myocardial infarction and stroke. Here, we used multi-omics integration to identify key molecular targets with diagnostic and therapeutic potential.\n\nBiobank of Karolinska Endarterectomies encompassing patients with symptomatic (S) and asymptomatic (AS) carotid atherosclerosis was the main resource. Plaques, peripheral blood monocytes and plasma sampled locally from around plaque or periphery of n > 700 individuals, were profiled by transcriptomics, proteomics and metabolomics. A supervised machine learning method DIABLO was used for patient data integration. Multi-omics layers were integrated separately across local and peripheral disease sites, and their intersection, with stratification for symptomatology. Identified analytes were investigated using scRNAseq, clinical and outcome data.\n\nIn peripheral circulation, FABP4, IL6, Bilirubin and Sphingomyelin were the most prominent analytes. F11, ANGPTL3, ICOSLG, ITGB1 and Sphingomyelin were enriched in the local disease site, while FABP4, C1R, IL6, Bilirubin and Sphingomyelin appeared at the intersection. Coagulation, necroptosis, inflammation and cholesterol metabolism were confirmed as key pathways determining symptomatology. Clinical analyses showed an impact of lipid-lowering therapy on ICOSLG expression, anti-hypertensives on plasma FABP4 and BLVRB levels, anti-diabetics on plasma Sphingomyelins, while no medications affected ANGPTL3. Association with future adverse events was shown for plasma Bilirubin, Sphingomyelin, ANGPTL3 and ICOSLG plaque levels. Open-source target analyses suggested genetic involvement of F11, C1S, EGFR, IL6, ANGPTL3 in the disease.\n\nUsing an innovative, multi-modal data integration machine learning framework, this study provides confirmatory and novel information on mechanisms behind atherosclerotic instability. The findings raise possibilities for translational prioritizations to aid personalized medicine.\n\nThe online version contains supplementary material available at 10.1186/s13073-026-01601-5.", "doi": "10.1186/s13073-026-01601-5", "pmid": "41652626", "labels": {"National Genomics Infrastructure": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "NGI Short read": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12927228"}, {"db": "pii", "key": "10.1186/s13073-026-01601-5"}], "notes": [], "created": "2026-05-27T11:37:57.073Z", "modified": "2026-05-27T11:37:57.076Z"}, {"entity": "publication", "iuid": "e3a0b036f1a64129a355aafe11a904e8", "links": {"self": {"href": "https://publications.scilifelab.se/publication/e3a0b036f1a64129a355aafe11a904e8.json"}, "display": {"href": "https://publications.scilifelab.se/publication/e3a0b036f1a64129a355aafe11a904e8"}}, "title": "Disease-specific epigenetic deregulation of enhancers, transposons, and polycomb targets in acute promyelocytic leukemia.", "authors": [{"family": "Zhong", "given": "Xiangfu", "initials": "X"}, {"family": "Cordeddu", "given": "Lina", "initials": "L"}, {"family": "Gamboa-Cedeno", "given": "Angelica", "initials": "A"}, {"family": "Bengtz\u00e9n", "given": "Sofia", "initials": "S"}, {"family": "Ekwall", "given": "Karl", "initials": "K"}, {"family": "Lennartsson", "given": "Andreas", "initials": "A"}, {"family": "Lehmann", "given": "S\u00f6ren", "initials": "S"}], "type": "journal article", "published": "2025-10-30", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "17", "issue": "1", "pages": "135"}, "abstract": "Acute promyelocytic leukemia (APL) is a subtype of acute myeloid leukemia (AML), characterized by a fusion between the PML and RARA genes and by a block in the myeloid maturation at the promyelocytic stage.\r\n\r\nThis study investigates the epigenetic landscape of APL by integrating ChIP-seq data on eight histone modifications and RNA-seq in APL as well as non-APL AML. APL showed a distinct chromatin profile that differed from non-APL AML.\r\n\r\nWe describe APL-specific changes in H3K27ac, H3K9me3, and H3K27me3 with impact on enhancer activity, repression of transposable elements, and Polycomb regulated gene repression. The APL-specific H3K27ac pattern identifies APL-specific enhancer and super-enhancer regions, including a subset of enhancers that are bound by the PML-RARA fusion protein. While chromatin bound specifically by PML-RARA were dominantly active, APL was also characterized by gain of APL-specific heterochromatin states with significant gains of H3K9me3 enriched lamina-associated domains and the transposable elements LINE, LTR, and SINE.\r\n\r\nThese findings suggest a unique enhancer and heterochromatin profile in APL, with implications for transcription regulation and treatment response. These findings offer novel insights into the pathogenesis of APL.", "doi": "10.1186/s13073-025-01565-y", "pmid": "41168841", "labels": {"Bioinformatics Support for Computational Resources": "Service", "NGI Stockholm (Genomics Production)": "Service", "NGI Short read": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Other": "Service", "National Genomics Infrastructure": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12573822"}, {"db": "pii", "key": "10.1186/s13073-025-01565-y"}], "notes": [], "created": "2025-11-28T10:53:15.320Z", "modified": "2026-07-15T07:14:00.504Z"}, {"entity": "publication", "iuid": "261b0843fccf4712a18fb2b1182b7e69", "links": {"self": {"href": "https://publications.scilifelab.se/publication/261b0843fccf4712a18fb2b1182b7e69.json"}, "display": {"href": "https://publications.scilifelab.se/publication/261b0843fccf4712a18fb2b1182b7e69"}}, "title": "Recommendations for bioinformatics in clinical practice.", "authors": [{"family": "Lavrichenko", "given": "Ksenia", "initials": "K"}, {"family": "Engdal", "given": "Emilie Sofie", "initials": "ES"}, {"family": "Marvig", "given": "Rasmus L", "initials": "RL"}, {"family": "Jemt", "given": "Anders", "initials": "A"}, {"family": "Vignes", "given": "Jone Marius", "initials": "JM"}, {"family": "Almusa", "given": "Henrikki", "initials": "H"}, {"family": "Saether", "given": "Kristine Bilgrav", "initials": "KB"}, {"family": "Briem", "given": "Eir\u00edkur", "initials": "E"}, {"family": "Caceres", "given": "Eva", "initials": "E"}, {"family": "Elvarsd\u00f3ttir", "given": "Edda Mar\u00eda", "initials": "EM"}, {"family": "G\u00edslason", "given": "Magn\u00fas Halld\u00f3r", "initials": "MH"}, {"family": "Haanp\u00e4\u00e4", "given": "Maria K", "initials": "MK"}, {"family": "Henmyr", "given": "Viktor", "initials": "V"}, {"family": "Hotakainen", "given": "Ronja", "initials": "R"}, {"family": "Kaasinen", "given": "Eevi", "initials": "E"}, {"family": "Kanninga", "given": "Roan", "initials": "R"}, {"family": "Khan", "given": "Sofia", "initials": "S"}, {"family": "Lie-Nielsen", "given": "Mary Gertrude", "initials": "MG"}, {"family": "Madsen", "given": "Majbritt Busk", "initials": "MB"}, {"family": "M\u00e4hler", "given": "Niklas", "initials": "N"}, {"family": "Maqbool", "given": "Khurram", "initials": "K"}, {"family": "Neethiraj", "given": "Ramprasad", "initials": "R"}, {"family": "Nyr\u00e9n", "given": "Karl", "initials": "K"}, {"family": "Paavola", "given": "Minna", "initials": "M"}, {"family": "Pruisscher", "given": "Peter", "initials": "P"}, {"family": "Sheng", "given": "Ying", "initials": "Y"}, {"family": "Singh", "given": "Ashish Kumar", "initials": "AK"}, {"family": "Srivastava", "given": "Aashish", "initials": "A"}, {"family": "Stautland", "given": "Thomas K", "initials": "TK"}, {"family": "Andreasen", "given": "Daniel T", "initials": "DT"}, {"family": "de Boer", "given": "Esmee Ten Berk", "initials": "ETB"}, {"family": "Vang", "given": "S\u00f8ren", "initials": "S"}, {"family": "Wirta", "given": "Valtteri", "initials": "V"}, {"family": "Bagger", "given": "Frederik Otzen", "initials": "FO"}], "type": "journal article", "published": "2025-10-17", "journal": {"title": "Genome Med", "issn": "1756-994X", "volume": "17", "issue": "1", "pages": "124", "issn-l": "1756-994X"}, "abstract": "Next-generation sequencing (NGS) is well established in clinical diagnostics, and whole-genome sequencing (WGS) is increasingly becoming the method of choice, as a result of lower prices and robust comprehensive data. While guidelines exist for variant interpretation and laboratory quality considerations, there remains a need for standardised bioinformatics practices to ensure clinical consensus, accuracy, reproducibility and comparability.\n\nThis article presents consensus recommendations developed by 13 clinical bioinformatics units participating in the Nordic Alliance for Clinical Genomics (NACG) by expert bioinformaticians working in clinical production. The recommendations are based on clinical practice and focus on analysis types, test and validation, standardisation and accreditation, as well as core competencies and technical management required for clinical bioinformatics operations.\n\nKey recommendations include adopting the hg38 genome build as reference, and a standard set of recommended analyses, including the use of multiple tools for structural variant (SV) calling and in-house data sets for filtering recurrent calls. Clinical bioinformatics in production should operate at standards similar to ISO 15189, utilising off-grid clinical-grade high-performance computing systems, standardised file formats and strict version control. Reproducibility should be ensured through containerised software environments. Pipelines must be documented and tested for accuracy and reproducibility, minimally covering unit, integration and end-to-end testing. Standard truth sets such as GIAB and SEQC2 for germline and somatic variant calling, respectively, should be supplemented by recall testing of real human samples that have been previously tested using a validated method. Data integrity must be verified using file hashing, while sample identity must be confirmed through fingerprinting and genetically inferred identification markers such as sex and relatedness. Finally, clinical bioinformatics should encompass diverse skills, including software development, data management, quality assurance and domain expertise in human genetics.\n\nThese recommendations provide a consensus framework for standardising bioinformatics practices across clinical WGS applications and can serve as a practical guide to facilities that are new to large-scale sequencing-based diagnostics, or as a reference for those who already run high-volume clinical production using NGS.", "doi": "10.1186/s13073-025-01543-4", "pmid": "41107899", "labels": {"Clinical Genomics": "Collaborative", "Clinical Genomics Ume\u00e5": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC12535132"}, {"db": "pii", "key": "10.1186/s13073-025-01543-4"}], "notes": [], "created": "2025-11-26T09:16:18.557Z", "modified": "2025-11-26T09:16:18.579Z"}, {"entity": "publication", "iuid": "7e76ffce8f844e768925d3f1ccdc1ad3", "links": {"self": {"href": "https://publications.scilifelab.se/publication/7e76ffce8f844e768925d3f1ccdc1ad3.json"}, "display": {"href": "https://publications.scilifelab.se/publication/7e76ffce8f844e768925d3f1ccdc1ad3"}}, "title": "Prematurity and genetic liability for autism spectrum disorder.", "authors": [{"family": "Zhang", "given": "Yali", "initials": "Y"}, {"family": "Yahia", "given": "Ashraf", "initials": "A"}, {"family": "Sandin", "given": "Sven", "initials": "S"}, {"family": "\u00c5den", "given": "Ulrika", "initials": "U"}, {"family": "Tammimies", "given": "Kristiina", "initials": "K"}], "type": "journal article", "published": "2025-10-02", "journal": {"title": "Genome Med", "issn": "1756-994X", "volume": "17", "issue": "1", "pages": "108", "issn-l": "1756-994X"}, "abstract": "Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by diverse presentations and a strong genetic component. Environmental factors, such as prematurity, have also been linked to increased liability for ASD, though the interaction between genetic predisposition and prematurity remains unclear. This study aims to investigate the impact of genetic liability and preterm birth on ASD conditions.\n\nWe analyzed phenotype and genetic data from two large ASD cohorts, the Simons Foundation Powering Autism Research for Knowledge (SPARK) and Simons Simplex Collection (SSC), encompassing 78,559 individuals for phenotype analysis, 12,519 individuals with genome sequencing data, and 8104 individuals with exome sequencing data. Statistical significance of differences in clinical measures was evaluated between individuals with different ASD and preterm status. We assessed the rare variants burden using generalized estimating equations (GEE) models and polygenic load using the ASD-associated polygenic risk score (PRS). Furthermore, we developed a machine learning model to predict ASD in preterm children using phenotype and genetic features available at birth.\n\nIndividuals with both preterm birth and ASD exhibit more severe phenotypic outcomes despite similar levels of genetic liability for ASD across the term and preterm groups. Notably, preterm-ASD individuals showed an elevated rate of de novo variants identified in exome sequencing (GEE model, p = 0.005) in comparison to non-ASD-preterm group. Additionally, a GEE model showed that a higher ASD PRS, preterm birth, and male sex were positively associated with a higher predicted probability for ASD in SPARK, reaching a probability close to 90%. Lastly, we developed a machine learning model using phenotype and genetic features available at birth with limited predictive power (AUROC = 0.65).\n\nPreterm birth may exacerbate multimorbidity present in ASD, which was not due to ASD-associated genetic variants. However, increased ASD-associated rare variants may elevate the likelihood of a preterm child being diagnosed with ASD. Additionally, a polygenic load of ASD-associated variants had an additive role with preterm birth in the predicted probability for ASD, especially for boys. Future integration of genetic and phenotypic data in larger preterm or population-based cohorts will be crucial for advancing early ASD identification in preterm subgroup.", "doi": "10.1186/s13073-025-01552-3", "pmid": "41039503", "labels": {"Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12490119"}, {"db": "pii", "key": "10.1186/s13073-025-01552-3"}], "notes": [], "created": "2025-11-28T10:53:10.261Z", "modified": "2025-11-28T10:53:10.272Z"}, {"entity": "publication", "iuid": "0e7f05d70eab4cae84503ca82067d860", "links": {"self": {"href": "https://publications.scilifelab.se/publication/0e7f05d70eab4cae84503ca82067d860.json"}, "display": {"href": "https://publications.scilifelab.se/publication/0e7f05d70eab4cae84503ca82067d860"}}, "title": "Structural variant allelic heterogeneity in MECP2 duplication syndrome provides insight into clinical severity and variability of disease expression.", "authors": [{"family": "Pehlivan", "given": "Davut", "initials": "D", "orcid": "0000-0001-5788-0270", "researcher": {"href": "https://publications.scilifelab.se/researcher/161dfab97b5b4438a16506714d94e751.json"}}, {"family": "Bengtsson", "given": "Jesse D", "initials": "JD"}, {"family": "Bajikar", "given": "Sameer S", "initials": "SS", "orcid": "0000-0002-8868-881X", "researcher": {"href": "https://publications.scilifelab.se/researcher/9a5e570d3c134f8b89e99f8bef1a4859.json"}}, {"family": "Grochowski", "given": "Christopher M", "initials": "CM"}, {"family": "Lun", "given": "Ming Yin", "initials": "MY"}, {"family": "Gandhi", "given": "Mira", "initials": "M"}, {"family": "Jolly", "given": "Angad", "initials": "A"}, {"family": "Trostle", "given": "Alexander J", "initials": "AJ"}, {"family": "Harris", "given": "Holly K", "initials": "HK"}, {"family": "Suter", "given": "Bernhard", "initials": "B"}, {"family": "Aras", "given": "Sukru", "initials": "S"}, {"family": "Ramocki", "given": "Melissa B", "initials": "MB"}, {"family": "Du", "given": "Haowei", "initials": "H"}, {"family": "Mehaffey", "given": "Michele G", "initials": "MG"}, {"family": "Park", "given": "KyungHee", "initials": "K"}, {"family": "Wilkey", "given": "Ellen", "initials": "E"}, {"family": "Karakas", "given": "Cemal", "initials": "C"}, {"family": "Eisfeldt", "given": "Jesper J", "initials": "JJ"}, {"family": "Pettersson", "given": "Maria", "initials": "M"}, {"family": "Liu", "given": "Lynn", "initials": "L"}, {"family": "Shinawi", "given": "Marwan S", "initials": "MS"}, {"family": "Kimonis", "given": "Virginia E", "initials": "VE"}, {"family": "Wiszniewski", "given": "Wojciech", "initials": "W"}, {"family": "Mckenzie", "given": "Kyle", "initials": "K"}, {"family": "Roser", "given": "Timo", "initials": "T"}, {"family": "Vianna-Morgante", "given": "Angela M", "initials": "AM"}, {"family": "Cornier", "given": "Alberto S", "initials": "AS"}, {"family": "Abdelmoity", "given": "Ahmed", "initials": "A"}, {"family": "Hwang", "given": "James P", "initials": "JP"}, {"family": "Jhangiani", "given": "Shalini N", "initials": "SN"}, {"family": "Muzny", "given": "Donna M", "initials": "DM"}, {"family": "Mitani", "given": "Tadahiro", "initials": "T"}, {"family": "Muramatsu", "given": "Kazuhiro", "initials": "K"}, {"family": "Nabatame", "given": "Shin", "initials": "S"}, {"family": "Glaze", "given": "Daniel G", "initials": "DG"}, {"family": "Fatih", "given": "Jawid M", "initials": "JM"}, {"family": "Gibbs", "given": "Richard A", "initials": "RA"}, {"family": "Liu", "given": "Zhandong", "initials": "Z"}, {"family": "Lindstrand", "given": "Anna", "initials": "A"}, {"family": "Sedlazeck", "given": "Fritz J", "initials": "FJ"}, {"family": "Lupski", "given": "James R", "initials": "JR", "orcid": "0000-0001-9907-9246", "researcher": {"href": "https://publications.scilifelab.se/researcher/88dd1dee9767489aaf25865670feb7b7.json"}}, {"family": "Zoghbi", "given": "Huda Y", "initials": "HY", "orcid": "0000-0002-0700-3349", "researcher": {"href": "https://publications.scilifelab.se/researcher/d3c7c189c611492e91113a5ae59fa66d.json"}}, {"family": "Carvalho", "given": "Claudia M B", "initials": "CMB", "orcid": "0000-0002-2090-298X", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a1a6b6936aa442384c5aef0eff0715a.json"}}], "type": "journal article", "published": "2024-12-18", "journal": {"title": "Genome Med", "issn": "1756-994X", "volume": "16", "issue": "1", "pages": "146", "issn-l": "1756-994X"}, "abstract": "MECP2 Duplication Syndrome, also known as X-linked intellectual developmental disorder Lubs type (MRXSL; MIM: 300260), is a neurodevelopmental disorder caused by copy number gains spanning MECP2. Despite varying genomic rearrangement structures, including duplications and triplications, and a wide range of duplication sizes, no clear correlation exists between DNA rearrangement and clinical features. We had previously demonstrated that up to 38% of MRXSL families are characterized by complex genomic rearrangements (CGRs) of intermediate complexity (2 \u2264 copy number variant breakpoints < 5), yet the impact of these genomic structures on regulation of gene expression and phenotypic manifestations have not been investigated.\n\nTo study the role of the genomic rearrangement structures on an individual's clinical phenotypic variability, we employed a comprehensive genomics, transcriptomics, and deep phenotyping analysis approach on 137 individuals affected by MRXSL. Genomic structural information was correlated with transcriptomic and quantitative phenotypic analysis using Human Phenotype Ontology (HPO) semantic similarity scores.\n\nDuplication sizes in the cohort ranging from 64.6 kb to 16.5 Mb were classified into four categories comprising of tandem duplications (48%), terminal duplications (22%), inverted triplications (20%), and other CGRs (10%). Most of the terminal duplication structures consist of translocations (65%) followed by recombinant chromosomes (23%). Notably, 65% of de novo events occurred in the Terminal duplication group in contrast with 17% observed in Tandem duplications. RNA-seq data from lymphoblastoid cell lines indicated that the MECP2 transcript quantity in MECP2 triplications is statistically different from all duplications, but not between other classes of genomic structures. We also observed a significant (p < 0.05) correlation (Pearson R = 0.6, Spearman p = 0.63) between the log-transformed MECP2 RNA levels and MECP2 protein levels, demonstrating that genomic aberrations spanning MECP2 lead to altered MECP2 RNA and MECP2 protein levels. Genotype-phenotype analyses indicated a gradual worsening of phenotypic features, including overall survival, developmental levels, microcephaly, epilepsy, and genitourinary/eye abnormalities in the following order: Tandem duplications, Other complex duplications, Terminal duplications/Translocations, and Triplications encompassing MECP2.\n\nIn aggregate, this combined analysis uncovers an interplay between MECP2 dosage, genomic rearrangement structure and phenotypic traits. Whereas the level of MECP2 is a key determinant of the phenotype, the DNA rearrangement structure can contribute to clinical severity and disease expression variability. Employing this type of analytical approach will advance our understanding of the impact of genomic rearrangements on genomic disorders and may help guide more targeted therapeutic approaches.", "doi": "10.1186/s13073-024-01411-7", "pmid": "39696717", "labels": {"Clinical Genomics Stockholm": "Service", "Clinical Genomics": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC11658439"}, {"db": "pii", "key": "10.1186/s13073-024-01411-7"}], "notes": [], "created": "2025-11-18T20:49:24.050Z", "modified": "2025-11-18T20:49:24.239Z"}, {"entity": "publication", "iuid": "daf828c0cd6f4236a8d690d701364184", "links": {"self": {"href": "https://publications.scilifelab.se/publication/daf828c0cd6f4236a8d690d701364184.json"}, "display": {"href": "https://publications.scilifelab.se/publication/daf828c0cd6f4236a8d690d701364184"}}, "title": "Rare predicted loss-of-function variants of type I IFN immunity genes are associated with life-threatening COVID-19", "authors": [{"family": "Matuozzo", "given": 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"initials": "MA"}, {"family": "Smeele", "given": "Patrick", "initials": "P"}, {"family": "Smit", "given": "Marry", "initials": "M"}, {"family": "Stijnis", "given": "Cornelis S", "initials": "CS"}, {"family": "Stilma", "given": "Willemke", "initials": "W"}, {"family": "Teunissen", "given": "Charlotte", "initials": "C"}, {"family": "Thoral", "given": "Patrick", "initials": "P"}, {"family": "Tsonas", "given": "Anissa M", "initials": "AM"}, {"family": "Tuinman", "given": "Pieter R", "initials": "PR"}, {"family": "van der Valk", "given": "Marc", "initials": "M"}, {"family": "Veelo", "given": "Denise", "initials": "D"}, {"family": "Volleman", "given": "Carolien", "initials": "C"}, {"family": "de Vries", "given": "Heder", "initials": "H"}, {"family": "Vught", "given": "Lonneke A", "initials": "LA"}, {"family": "van Vugt", "given": "Mich\u00e8le", "initials": "M"}, {"family": "Wouters", "given": "Dorien", "initials": "D"}, {"family": "Zwinderman", "given": "A H", "initials": "AH"}, {"family": "Brouwer", "given": "Matthijs C", "initials": "MC"}, {"family": "Wiersinga", "given": "W Joost", "initials": "WJ"}, {"family": "Vlaar", "given": "Alexander P J", "initials": "APJ"}, {"family": "van de Beek", "given": "Diederik", "initials": "D", "orcid": "0000-0002-4571-044X", "researcher": {"href": "https://publications.scilifelab.se/researcher/16a11a5216564abe9d6b7f230a4a13c2.json"}}, {"family": "Tompkins", "given": "Miranda F", "initials": "MF"}, {"family": "Alba", "given": "Camille", "initials": "C"}, {"family": "Snow", "given": "Andrew L", "initials": "AL"}, {"family": "Hupalo", "given": "Daniel N", "initials": "DN"}, {"family": "Rosenberger", "given": "John", "initials": "J"}, {"family": "Sukumar", "given": "Gauthaman", "initials": "G"}, {"family": "Wilkerson", "given": "Matthew D", "initials": "MD"}, {"family": "Zhang", "given": "Xijun", "initials": "X"}, {"family": "Lack", "given": "Justin", "initials": "J"}, {"family": "Oler", "given": "Andrew J", "initials": "AJ"}, {"family": "Dobbs", "given": "Kerry", "initials": "K"}, {"family": "Danielson", "given": "Jeffrey J", "initials": "JJ"}, {"family": "Biondi", "given": "Andrea", "initials": "A"}, {"family": "Bettini", "given": "Laura Rachele", "initials": "LR"}, {"family": "D\u2019Angio\u2019", "given": "Mariella", "initials": "M"}, {"family": "Beretta", "given": "Ilaria", "initials": "I"}, {"family": "Imberti", "given": "Luisa", "initials": "L"}, {"family": "Sottini", "given": "Alessandra", "initials": "A"}, {"family": "Quaresima", "given": "Virginia", "initials": "V"}, {"family": "Quiros-Roldan", "given": "Eugenia", "initials": "E"}, {"family": "Rossi", "given": "Camillo", "initials": "C"}, {"family": "Meyts", "given": "Isabelle", "initials": "I", "orcid": "0000-0003-1214-0302", "researcher": {"href": "https://publications.scilifelab.se/researcher/dfde01a48b334b2a896597ac69be80c8.json"}}, {"family": "Zhang", "given": "Shen Ying", "initials": "SY"}, {"family": "Puel", "given": "Anne", "initials": "A", "orcid": "0000-0003-2603-0323", "researcher": {"href": "https://publications.scilifelab.se/researcher/3bcef4c205904e5db9e36f3aadaa13bb.json"}}, {"family": "Notarangelo", "given": "Luigi D", "initials": "LD", "orcid": "0000-0002-8335-0262", "researcher": {"href": "https://publications.scilifelab.se/researcher/d8d346e44c2d443ba3da3fcf2725b96c.json"}}, {"family": "Boisson-Dupuis", "given": "Stephanie", "initials": "S", "orcid": "0000-0002-7115-116X", "researcher": {"href": "https://publications.scilifelab.se/researcher/5584eef132004c55a120c70d9a9f9eee.json"}}, {"family": "Su", "given": "Helen C", "initials": "HC", "orcid": "0000-0002-5582-9110", "researcher": {"href": "https://publications.scilifelab.se/researcher/5f3b00f2707541b39b2205d70fd2d6f7.json"}}, {"family": "Boisson", "given": "Bertrand", "initials": "B", "orcid": "0000-0001-5240-3555", "researcher": {"href": "https://publications.scilifelab.se/researcher/e7c47acbcc3346bcb65102b534b25cc8.json"}}, {"family": "Jouanguy", "given": "Emmanuelle", "initials": "E", "orcid": "0000-0002-7358-9157", "researcher": {"href": "https://publications.scilifelab.se/researcher/2667361dc2e7417bb94bfc89bf425cc6.json"}}, {"family": "Casanova", "given": "Jean Laurent", "initials": "JL"}, {"family": "Zhang", "given": "Qian", "initials": "Q"}, {"family": "Abel", "given": "Laurent", "initials": "L", "orcid": "0000-0001-7016-6493", "researcher": {"href": "https://publications.scilifelab.se/researcher/24ef4ca1eb3a4b1bbee73f07cd64fe92.json"}}, {"family": "Cobat", "given": "Aur\u00e9lie", "initials": "A", "orcid": "0000-0001-7209-6257", "researcher": {"href": "https://publications.scilifelab.se/researcher/eaba2f9452294eec89161b589d96ff29.json"}}], "type": "journal-article", "published": "2023-04-05", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "15", "issue": "1", "pages": null}, "abstract": "We previously reported inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity in 1-5% of unvaccinated patients with life-threatening COVID-19, and auto-antibodies against type I IFN in another 15-20% of cases.\r\n\r\nWe report here a genome-wide rare variant burden association analysis in 3,269 unvaccinated patients with life-threatening COVID-19 (1,301 previously reported and 1,968 new patients), and 1,373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. A quarter of the patients tested had antibodies against type I IFN (234 of 928) and were excluded from the analysis.\r\n\r\nNo gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7 , with an OR of 27.68 (95%CI:1.5-528.7, P= 1.1\u00d710 -4 ), in analyses restricted to biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70 [95%CI:1.3-8.2], P= 2.1\u00d710 -4 ). Adding the recently reported TYK2 COVID-19 locus strengthened this enrichment, particularly under a recessive model (OR=19.65 [95%CI:2.1-2635.4]; P= 3.4\u00d710 -3 ). When these 14 loci and TLR7 were considered, all individuals hemizygous ( n =20) or homozygous ( n =5) for pLOF or bLOF variants were patients (OR=39.19 [95%CI:5.2-5037.0], P =4.7\u00d710 -7 ), who also showed an enrichment in heterozygous variants (OR=2.36 [95%CI:1.0-5.9], P =0.02). Finally, the patients with pLOF or bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P= 1.68\u00d710 -5 ).\r\n\r\nRare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie life-threatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.", "doi": "10.1186/s13073-023-01173-8", "pmid": "36324795", "labels": {"Clinical Genomics Stockholm": "Service", "Clinical Genomics": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC9628204"}, {"db": "pii", "key": "2022.10.22.22281221"}], "notes": [], "created": "2022-11-30T05:59:39.705Z", "modified": "2024-01-19T11:56:54.797Z"}, {"entity": "publication", "iuid": "be695a433fa7423e9418d12e55b4d672", "links": {"self": {"href": "https://publications.scilifelab.se/publication/be695a433fa7423e9418d12e55b4d672.json"}, "display": {"href": "https://publications.scilifelab.se/publication/be695a433fa7423e9418d12e55b4d672"}}, "title": "Loss of Y in leukocytes as a risk factor for critical COVID-19 in men", "authors": [{"family": "Bruhn-Olszewska", "given": "Bo\u017cena", "initials": "B", "orcid": "0000-0003-2141-0247", "researcher": {"href": "https://publications.scilifelab.se/researcher/0fa96509bbe94834858aee3c16d41b97.json"}}, {"family": "Davies", "given": "Hanna", "initials": "H", "orcid": "0000-0002-6289-3815", "researcher": {"href": "https://publications.scilifelab.se/researcher/1d800ab99360483d8bd12ba4b386a4a4.json"}}, {"family": "Sarkisyan", "given": "Daniil", "initials": "D", "orcid": "0000-0002-2451-4386", "researcher": {"href": "https://publications.scilifelab.se/researcher/44fdd52fbf5d420396c87a31addea920.json"}}, {"family": "Juhas", "given": "Ulana", "initials": "U", "orcid": "0000-0001-8393-5845", "researcher": {"href": "https://publications.scilifelab.se/researcher/851c9b9c7ba943d6836633f8bd5003bd.json"}}, {"family": "Rychlicka-Buniowska", "given": "Edyta", "initials": "E", "orcid": "0000-0001-8050-2489", "researcher": {"href": "https://publications.scilifelab.se/researcher/9b253253073749839c443de3003ecb89.json"}}, {"family": "W\u00f3jcik", "given": "Magdalena", "initials": "M", "orcid": "0000-0001-5475-8448", "researcher": {"href": "https://publications.scilifelab.se/researcher/cbf367a185b347c6a9bf6b6f2adfe6e5.json"}}, {"family": "Horbacz", "given": "Monika", "initials": "M", "orcid": "0000-0003-1644-2957", "researcher": {"href": "https://publications.scilifelab.se/researcher/76c7f6d571214ca9a6940293c3dbc6c1.json"}}, {"family": "J\u0105kalski", "given": "Marcin", "initials": "M", "orcid": "0000-0002-5481-9148", "researcher": {"href": "https://publications.scilifelab.se/researcher/e4411ec776b94c89b0444bd8d49672ca.json"}}, {"family": "Olszewski", "given": "Pawe\u0142", "initials": "P", "orcid": "0000-0002-2788-5254", "researcher": {"href": "https://publications.scilifelab.se/researcher/214b8864edb24164a1c9af68396603b9.json"}}, {"family": "Westholm", "given": "Jakub O", "initials": "JO", "orcid": "0000-0002-6849-6220", "researcher": {"href": "https://publications.scilifelab.se/researcher/161d8b5fb6734b33ad5f5590edbc0cff.json"}}, {"family": "Smialowska", "given": "Agata", "initials": "A"}, {"family": "Wierzba", "given": "Karol", "initials": "K", "orcid": "0000-0003-1257-4047", "researcher": {"href": "https://publications.scilifelab.se/researcher/ddedb819ee5d4e33b0382e87e7369dec.json"}}, {"family": "Torinsson Naluai", "given": "\u00c5sa", "initials": "\u00c5", "orcid": "0000-0002-0504-6492", "researcher": {"href": "https://publications.scilifelab.se/researcher/bcf3474dc7054c598cbe3a195deb8a1b.json"}}, {"family": "Jern", "given": "Niklas", "initials": "N"}, {"family": "Andersson", "given": "Lars Magnus", "initials": "LM", "orcid": "0000-0002-9203-5969", "researcher": {"href": "https://publications.scilifelab.se/researcher/da6e24cc65a14537ad30353de972cd5f.json"}}, {"family": "J\u00e4rhult", "given": "Josef D", "initials": "JD", "orcid": "0000-0002-7075-1059", "researcher": {"href": "https://publications.scilifelab.se/researcher/2598129f86ee47ebafc696148f9da01f.json"}}, {"family": "Filipowicz", "given": "Natalia", "initials": "N", "orcid": "0000-0002-9673-2649", "researcher": {"href": "https://publications.scilifelab.se/researcher/153a4d73f8cb4ec68cedfd85556e383e.json"}}, {"family": "Tiensuu Janson", "given": "Eva", "initials": "E", "orcid": "0000-0002-1649-4880", "researcher": {"href": "https://publications.scilifelab.se/researcher/3838152188ee4e2580d139757ecd8df8.json"}}, {"family": "Rubertsson", "given": "Sten", "initials": "S"}, {"family": "Lipcsey", "given": "Mikl\u00f3s", "initials": "M", "orcid": "0000-0002-1976-4129", "researcher": {"href": "https://publications.scilifelab.se/researcher/81805f2324634628abefcf0ab6ce6a15.json"}}, {"family": "Gissl\u00e9n", "given": "Magnus", "initials": "M", "orcid": "0000-0002-2357-1020", "researcher": {"href": "https://publications.scilifelab.se/researcher/8b50df8c8ecc45b89574dc76e244b07e.json"}}, {"family": "Hultstr\u00f6m", "given": "Michael", "initials": "M", "orcid": "0000-0003-4675-1099", "researcher": {"href": "https://publications.scilifelab.se/researcher/c9a74d3380a24c31930e6e671e685b5b.json"}}, {"family": "Frithiof", "given": "Robert", "initials": "R", "orcid": "0000-0003-2278-7951", "researcher": {"href": "https://publications.scilifelab.se/researcher/8fec11dd18f941b7842610ad14237a35.json"}}, {"family": "Dumanski", "given": "Jan P", "initials": "JP", "orcid": "0000-0002-1489-1452", "researcher": {"href": "https://publications.scilifelab.se/researcher/15b14282209342cfa9c82cdbf02999f6.json"}}], "type": "journal-article", "published": "2022-12-14", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "14", "issue": "1", "pages": "139"}, "abstract": "The COVID-19 pandemic, which has a prominent social and economic impact worldwide, shows a largely unexplained male bias for the severity and mortality of the disease. Loss of chromosome Y (LOY) is a risk factor candidate in COVID-19 due to its prior association with many chronic age-related diseases, and its impact on immune gene transcription.\n\nPublicly available scRNA-seq data of PBMC samples derived from male patients critically ill with COVID-19 were reanalyzed, and LOY status was added to the annotated cells. We further studied LOY in whole blood for 211 COVID-19 patients treated at intensive care units (ICU) from the first and second waves of the pandemic. Of these, 139 patients were subject to cell sorting for LOY analysis in granulocytes, low-density neutrophils (LDNs), monocytes, and PBMCs.\n\nReanalysis of available scRNA-seq data revealed LDNs and monocytes as the cell types most affected by LOY. Subsequently, DNA analysis indicated that 46%, 32%, and 29% of critically ill patients showed LOY above 5% cut-off in LDNs, granulocytes, and monocytes, respectively. Hence, the myeloid lineage that is crucial for the development of severe COVID-19 phenotype is affected by LOY. Moreover, LOY correlated with increasing WHO score (median difference 1.59%, 95% HDI 0.46% to 2.71%, p=0.025), death during ICU treatment (median difference 1.46%, 95% HDI 0.47% to 2.43%, p=0.0036), and history of vessel disease (median difference 2.16%, 95% HDI 0.74% to 3.7%, p=0.004), among other variables. In 16 recovered patients, sampled during ICU stay and 93-143 days later, LOY decreased significantly in whole blood and PBMCs. Furthermore, the number of LDNs at the recovery stage decreased dramatically (median difference 76.4 per 10,000 cell sorting events, 95% HDI 55.5 to 104, p=6e-11).\n\nWe present a link between LOY and an acute, life-threatening infectious disease. Furthermore, this study highlights LOY as the most prominent clonal mutation affecting the myeloid cell lineage during emergency myelopoiesis. The correlation between LOY level and COVID-19 severity might suggest that this mutation affects the functions of monocytes and neutrophils, which could have consequences for male innate immunity.", "doi": "10.1186/s13073-022-01144-5", "pmid": "36514076", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Long-term Support WABI": "Collaborative", "Bioinformatics Support and Infrastructure": "Collaborative", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC9747543"}, {"db": "pii", "key": "10.1186/s13073-022-01144-5"}], "notes": [], "created": "2022-12-20T08:30:45.356Z", "modified": "2023-06-19T09:07:39.861Z"}, {"entity": "publication", "iuid": "1a0289c420df4fc983dce95076ff7b8c", "links": {"self": {"href": "https://publications.scilifelab.se/publication/1a0289c420df4fc983dce95076ff7b8c.json"}, "display": {"href": "https://publications.scilifelab.se/publication/1a0289c420df4fc983dce95076ff7b8c"}}, "title": "A community-driven resource for genomic epidemiology and antimicrobial resistance prediction of Neisseria gonorrhoeae at Pathogenwatch.", "authors": [{"family": "S\u00e1nchez-Bus\u00f3", "given": "Leonor", "initials": "L", "orcid": "0000-0002-4162-0228", "researcher": {"href": "https://publications.scilifelab.se/researcher/a13add576f1f464caa7ac0ceabadcbff.json"}}, {"family": "Yeats", "given": "Corin A", "initials": "CA"}, {"family": "Taylor", "given": "Benjamin", "initials": "B"}, {"family": "Goater", "given": "Richard J", "initials": "RJ"}, {"family": "Underwood", "given": "Anthony", "initials": "A"}, {"family": "Abudahab", "given": "Khalil", "initials": "K"}, {"family": "Argim\u00f3n", "given": "Silvia", "initials": "S"}, {"family": "Ma", "given": "Kevin C", "initials": "KC"}, {"family": "Mortimer", "given": "Tatum D", "initials": "TD"}, {"family": "Golparian", "given": "Daniel", "initials": "D"}, {"family": "Cole", "given": "Michelle J", "initials": "MJ"}, {"family": "Grad", "given": "Yonatan H", "initials": "YH"}, {"family": "Martin", "given": "Irene", "initials": "I"}, {"family": "Raphael", "given": "Brian H", "initials": "BH"}, {"family": "Shafer", "given": "William M", "initials": "WM"}, {"family": "Town", "given": "Katy", "initials": "K"}, {"family": "Wi", "given": "Teodora", "initials": "T"}, {"family": "Harris", "given": "Simon R", "initials": "SR"}, {"family": "Unemo", "given": "Magnus", "initials": "M"}, {"family": "Aanensen", "given": "David M", "initials": "DM"}], "type": "journal article", "published": "2021-04-19", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "13", "issue": "1", "pages": "61"}, "abstract": "Antimicrobial-resistant (AMR) Neisseria gonorrhoeae is an urgent threat to public health, as strains resistant to at least one of the two last-line antibiotics used in empiric therapy of gonorrhoea, ceftriaxone and azithromycin, have spread internationally. Whole genome sequencing (WGS) data can be used to identify new AMR clones and transmission networks and inform the development of point-of-care tests for antimicrobial susceptibility, novel antimicrobials and vaccines. Community-driven tools that provide an easy access to and analysis of genomic and epidemiological data is the way forward for public health surveillance.\r\n\r\nHere we present a public health-focussed scheme for genomic epidemiology of N. gonorrhoeae at Pathogenwatch ( https://pathogen.watch/ngonorrhoeae ). An international advisory group of experts in epidemiology, public health, genetics and genomics of N. gonorrhoeae was convened to inform on the utility of current and future analytics in the platform. We implement backwards compatibility with MLST, NG-MAST and NG-STAR typing schemes as well as an exhaustive library of genetic AMR determinants linked to a genotypic prediction of resistance to eight antibiotics. A collection of over 12,000 N. gonorrhoeae genome sequences from public archives has been quality-checked, assembled and made public together with available metadata for contextualization.\r\n\r\nAMR prediction from genome data revealed specificity values over 99% for azithromycin, ciprofloxacin and ceftriaxone and sensitivity values around 99% for benzylpenicillin and tetracycline. A case study using the Pathogenwatch collection of N. gonorrhoeae public genomes showed the global expansion of an azithromycin-resistant lineage carrying a mosaic mtr over at least the last 10 years, emphasising the power of Pathogenwatch to explore and evaluate genomic epidemiology questions of public health concern.\r\n\r\nThe N. gonorrhoeae scheme in Pathogenwatch provides customised bioinformatic pipelines guided by expert opinion that can be adapted to public health agencies and departments with little expertise in bioinformatics and lower-resourced settings with internet connection but limited computational infrastructure. The advisory group will assess and identify ongoing public health needs in the field of gonorrhoea, particularly regarding gonococcal AMR, in order to further enhance utility with modified or new analytic methods.", "doi": "10.1186/s13073-021-00858-2", "pmid": "33875000", "labels": {"Clinical Genomics \u00d6rebro": "Collaborative", "Clinical Genomics": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-021-00858-2"}, {"db": "pmc", "key": "PMC8054416"}], "notes": [], "created": "2021-12-08T10:01:03.147Z", "modified": "2021-12-08T12:29:21.543Z"}, {"entity": "publication", "iuid": "44584992ffd84031895bb087891f144e", "links": {"self": {"href": "https://publications.scilifelab.se/publication/44584992ffd84031895bb087891f144e.json"}, "display": {"href": "https://publications.scilifelab.se/publication/44584992ffd84031895bb087891f144e"}}, "title": "Rare deleterious mutations of HNRNP genes result in shared neurodevelopmental disorders.", "authors": [{"family": "Gillentine", "given": "Madelyn A", "initials": "MA"}, {"family": "Wang", "given": "Tianyun", "initials": "T"}, {"family": "Hoekzema", "given": "Kendra", "initials": "K"}, {"family": "Rosenfeld", "given": "Jill", "initials": "J"}, {"family": "Liu", "given": "Pengfei", "initials": "P"}, {"family": "Guo", "given": "Hui", "initials": "H"}, {"family": "Kim", "given": "Chang N", "initials": "CN"}, {"family": "De Vries", "given": "Bert B A", "initials": "BBA"}, {"family": "Vissers", "given": "Lisenka E L M", "initials": "LELM"}, {"family": "Nordenskjold", "given": "Magnus", "initials": "M"}, {"family": "Kvarnung", "given": "Malin", "initials": "M"}, {"family": "Lindstrand", "given": "Anna", "initials": "A"}, {"family": "Nordgren", "given": "Ann", "initials": "A"}, {"family": "Gecz", "given": "Jozef", "initials": "J"}, {"family": "Iascone", "given": "Maria", "initials": "M"}, {"family": "Cereda", "given": "Anna", "initials": "A"}, {"family": "Scatigno", "given": "Agnese", "initials": "A"}, {"family": "Maitz", "given": "Silvia", "initials": "S"}, {"family": "Zanni", "given": "Ginevra", "initials": "G"}, {"family": "Bertini", "given": "Enrico", "initials": "E"}, {"family": "Zweier", "given": "Christiane", "initials": "C"}, {"family": "Schuhmann", "given": "Sarah", "initials": "S"}, {"family": "Wiesener", "given": "Antje", "initials": "A"}, {"family": "Pepper", "given": "Micah", "initials": "M"}, {"family": "Panjwani", "given": "Heena", "initials": "H"}, {"family": "Torti", "given": "Erin", "initials": "E"}, {"family": "Abid", "given": "Farida", "initials": "F"}, {"family": "Anselm", "given": "Irina", "initials": "I"}, {"family": "Srivastava", "given": "Siddharth", "initials": "S"}, {"family": "Atwal", "given": "Paldeep", "initials": "P"}, {"family": "Bacino", "given": "Carlos A", "initials": "CA"}, {"family": "Bhat", "given": "Gifty", "initials": "G"}, {"family": "Cobian", "given": "Katherine", "initials": "K"}, {"family": "Bird", "given": "Lynne M", "initials": "LM"}, {"family": "Friedman", "given": "Jennifer", "initials": "J"}, {"family": "Wright", "given": "Meredith S", "initials": "MS"}, {"family": "Callewaert", "given": "Bert", "initials": "B"}, {"family": "Petit", "given": "Florence", "initials": "F"}, {"family": "Mathieu", "given": "Sophie", "initials": "S"}, {"family": "Afenjar", "given": "Alexandra", "initials": "A"}, {"family": "Christensen", "given": "Celenie K", "initials": "CK"}, {"family": "White", "given": "Kerry M", "initials": "KM"}, {"family": "Elpeleg", "given": "Orly", "initials": "O"}, {"family": "Berger", "given": "Itai", "initials": "I"}, {"family": "Espineli", "given": "Edward J", "initials": "EJ"}, {"family": "Fagerberg", "given": "Christina", "initials": "C"}, {"family": "Brasch-Andersen", "given": "Charlotte", "initials": "C"}, {"family": "Hansen", "given": "Lars Kj\u00e6rsgaard", "initials": "LK"}, {"family": "Feyma", "given": "Timothy", "initials": "T"}, {"family": "Hughes", "given": "Susan", "initials": "S"}, {"family": "Thiffault", "given": "Isabelle", "initials": "I"}, {"family": "Sullivan", "given": "Bonnie", "initials": "B"}, {"family": "Yan", "given": "Shuang", "initials": "S"}, {"family": "Keller", "given": "Kory", "initials": "K"}, {"family": "Keren", "given": "Boris", "initials": "B"}, {"family": "Mignot", "given": "Cyril", "initials": "C"}, {"family": "Kooy", "given": "Frank", "initials": "F"}, {"family": "Meuwissen", "given": "Marije", "initials": "M"}, {"family": "Basinger", "given": "Alice", "initials": "A"}, {"family": "Kukolich", "given": "Mary", "initials": "M"}, {"family": "Philips", "given": "Meredith", "initials": "M"}, {"family": "Ortega", "given": "Lucia", "initials": "L"}, {"family": "Drummond-Borg", "given": "Margaret", "initials": "M"}, {"family": "Lauridsen", "given": "Mathilde", "initials": "M"}, {"family": "Sorensen", "given": "Kristina", "initials": "K"}, {"family": "Lehman", "given": "Anna", "initials": "A"}, {"family": "CAUSES Study", "given": "", "initials": ""}, {"family": "Lopez-Rangel", "given": "Elena", "initials": "E"}, {"family": "Levy", "given": "Paul", "initials": "P"}, {"family": "Lessel", "given": "Davor", "initials": "D"}, {"family": "Lotze", "given": "Timothy", "initials": "T"}, {"family": "Madan-Khetarpal", "given": "Suneeta", "initials": "S"}, {"family": "Sebastian", "given": "Jessica", "initials": "J"}, {"family": "Vento", "given": "Jodie", "initials": "J"}, {"family": "Vats", "given": "Divya", "initials": "D"}, {"family": "Benman", "given": "L Manace", "initials": "LM"}, {"family": "Mckee", "given": "Shane", "initials": "S"}, {"family": "Mirzaa", "given": "Ghayda M", "initials": "GM"}, {"family": "Muss", "given": "Candace", "initials": "C"}, {"family": "Pappas", "given": "John", "initials": "J"}, {"family": "Peeters", "given": "Hilde", "initials": "H"}, {"family": "Romano", "given": "Corrado", "initials": "C"}, {"family": "Elia", "given": "Maurizio", "initials": "M"}, {"family": "Galesi", "given": "Ornella", "initials": "O"}, {"family": "Simon", "given": "Marleen E H", "initials": "MEH"}, {"family": "van Gassen", "given": "Koen L I", "initials": "KLI"}, {"family": "Simpson", "given": "Kara", "initials": "K"}, {"family": "Stratton", "given": "Robert", "initials": "R"}, {"family": "Syed", "given": "Sabeen", "initials": "S"}, {"family": "Thevenon", "given": "Julien", "initials": "J"}, {"family": "Palafoll", "given": "Irene Valenzuela", "initials": "IV"}, {"family": "Vitobello", "given": "Antonio", "initials": "A"}, {"family": "Bournez", "given": "Marie", "initials": "M"}, {"family": "Faivre", "given": "Laurence", "initials": "L"}, {"family": "Xia", "given": "Kun", "initials": "K"}, {"family": "SPARK Consortium", "given": "", "initials": ""}, {"family": "Earl", "given": "Rachel K", "initials": "RK"}, {"family": "Nowakowski", "given": "Tomasz", "initials": "T"}, {"family": "Bernier", "given": "Raphael A", "initials": "RA"}, {"family": "Eichler", "given": "Evan E", "initials": "EE", "orcid": "0000-0002-8246-4014", "researcher": {"href": "https://publications.scilifelab.se/researcher/43901cc9fc3b4f5c9a18260e36558eb9.json"}}], "type": "journal article", "published": "2021-04-19", "journal": {"title": "Genome Med", "issn": "1756-994X", "volume": "13", "issue": "1", "pages": "63", "issn-l": "1756-994X"}, "abstract": "With the increasing number of genomic sequencing studies, hundreds of genes have been implicated in neurodevelopmental disorders (NDDs). The rate of gene discovery far outpaces our understanding of genotype-phenotype correlations, with clinical characterization remaining a bottleneck for understanding NDDs. Most disease-associated Mendelian genes are members of gene families, and we hypothesize that those with related molecular function share clinical presentations.\n\nWe tested our hypothesis by considering gene families that have multiple members with an enrichment of de novo variants among NDDs, as determined by previous meta-analyses. One of these gene families is the heterogeneous nuclear ribonucleoproteins (hnRNPs), which has 33 members, five of which have been recently identified as NDD genes (HNRNPK, HNRNPU, HNRNPH1, HNRNPH2, and HNRNPR) and two of which have significant enrichment in our previous meta-analysis of probands with NDDs (HNRNPU and SYNCRIP). Utilizing protein homology, mutation analyses, gene expression analyses, and phenotypic characterization, we provide evidence for variation in 12 HNRNP genes as candidates for NDDs. Seven are potentially novel while the remaining genes in the family likely do not significantly contribute to NDD risk.\n\nWe report 119 new NDD cases (64 de novo variants) through sequencing and international collaborations and combined with published clinical case reports. We consider 235 cases with gene-disruptive single-nucleotide variants or indels and 15 cases with small copy number variants. Three hnRNP-encoding genes reach nominal or exome-wide significance for de novo variant enrichment, while nine are candidates for pathogenic mutations. Comparison of HNRNP gene expression shows a pattern consistent with a role in cerebral cortical development with enriched expression among radial glial progenitors. Clinical assessment of probands (n = 188-221) expands the phenotypes associated with HNRNP rare variants, and phenotypes associated with variation in the HNRNP genes distinguishes them as a subgroup of NDDs.\n\nOverall, our novel approach of exploiting gene families in NDDs identifies new HNRNP-related disorders, expands the phenotypes of known HNRNP-related disorders, strongly implicates disruption of the hnRNPs as a whole in NDDs, and supports that NDD subtypes likely have shared molecular pathogenesis. To date, this is the first study to identify novel genetic disorders based on the presence of disorders in related genes. We also perform the first phenotypic analyses focusing on related genes. Finally, we show that radial glial expression of these genes is likely critical during neurodevelopment. This is important for diagnostics, as well as developing strategies to best study these genes for the development of therapeutics.", "doi": "10.1186/s13073-021-00870-6", "pmid": "33874999", "labels": {"Clinical Genomics Stockholm": "Service", "Clinical Genomics": "Service"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-021-00870-6"}, {"db": "pmc", "key": "PMC8056596"}], "notes": [], "created": "2021-11-20T12:20:16.589Z", "modified": "2021-11-20T12:20:16.626Z"}, {"entity": "publication", "iuid": "e1ffd455972d46ac91b2d42c7121ac87", "links": {"self": {"href": "https://publications.scilifelab.se/publication/e1ffd455972d46ac91b2d42c7121ac87.json"}, "display": {"href": "https://publications.scilifelab.se/publication/e1ffd455972d46ac91b2d42c7121ac87"}}, "title": "Integration of whole genome sequencing into a healthcare setting: high diagnostic rates across multiple clinical entities in 3219 rare disease patients.", "authors": [{"family": "Stranneheim", "given": "Henrik", "initials": "H"}, {"family": "Lagerstedt-Robinson", "given": "Kristina", "initials": "K"}, {"family": "Magnusson", "given": "M\u00e5ns", "initials": "M"}, {"family": "Kvarnung", "given": "Malin", "initials": "M"}, {"family": "Nilsson", "given": "Daniel", "initials": "D"}, {"family": "Lesko", "given": "Nicole", "initials": "N"}, {"family": "Engvall", "given": "Martin", "initials": "M"}, {"family": "Anderlid", "given": "Britt-Marie", "initials": "BM"}, {"family": "Arnell", "given": "Henrik", "initials": "H"}, {"family": "Johansson", "given": "Carolina Backman", "initials": "CB"}, {"family": "Barbaro", "given": "Michela", "initials": "M"}, {"family": "Bj\u00f6rck", "given": "Erik", "initials": "E"}, {"family": "Bruhn", "given": "Helene", "initials": "H"}, {"family": "Eisfeldt", "given": "Jesper", "initials": "J"}, {"family": "Freyer", "given": "Christoph", "initials": "C"}, {"family": "Grigelioniene", "given": "Giedre", "initials": "G"}, {"family": "Gustavsson", "given": "Peter", "initials": "P"}, {"family": "Hammarsj\u00f6", "given": "Anna", "initials": "A"}, {"family": "Hellstr\u00f6m-Pigg", "given": "Maritta", "initials": "M"}, {"family": "Iwarsson", "given": "Erik", "initials": "E"}, {"family": "Jemt", "given": "Anders", "initials": "A"}, {"family": "Laaksonen", "given": "Mikael", "initials": "M"}, {"family": "Enoksson", "given": "Sara Lind", "initials": "SL"}, {"family": "Malmgren", "given": "Helena", "initials": "H"}, {"family": "Naess", "given": "Karin", "initials": "K"}, {"family": "Nordenskj\u00f6ld", "given": "Magnus", "initials": "M"}, {"family": "Oscarson", "given": "Mikael", "initials": "M"}, {"family": "Pettersson", "given": "Maria", "initials": "M"}, {"family": "Rasi", "given": "Chiara", "initials": "C"}, {"family": "Rosenbaum", "given": "Adam", "initials": "A"}, {"family": "Sahlin", "given": "Ellika", "initials": "E"}, {"family": "Sardh", "given": "Eliane", "initials": "E"}, {"family": "St\u00f6dberg", "given": "Tommy", "initials": "T"}, {"family": "Tesi", "given": "Bianca", "initials": "B"}, {"family": "Tham", "given": "Emma", "initials": "E"}, {"family": "Thonberg", "given": "H\u00e5kan", "initials": "H"}, {"family": "T\u00f6h\u00f6nen", "given": "Virpi", "initials": "V"}, {"family": "von D\u00f6beln", "given": "Ulrika", "initials": "U"}, {"family": "Vassiliou", "given": "Daphne", "initials": "D"}, {"family": "Vonlanthen", "given": "Sofie", "initials": "S"}, {"family": "Wikstr\u00f6m", "given": "Ann-Charlotte", "initials": "AC"}, {"family": "Wincent", "given": "Josephine", "initials": "J"}, {"family": "Winqvist", "given": "Ola", "initials": "O"}, {"family": "Wredenberg", "given": "Anna", "initials": "A"}, {"family": "Ygberg", "given": "Sofia", "initials": "S"}, {"family": "Zetterstr\u00f6m", "given": "Rolf H", "initials": "RH"}, {"family": "Marits", "given": "Per", "initials": "P"}, {"family": "Soller", "given": "Maria Johansson", "initials": "MJ"}, {"family": "Nordgren", "given": "Ann", "initials": "A"}, {"family": "Wirta", "given": "Valtteri", "initials": "V", "orcid": "0000-0003-3811-5439", "researcher": {"href": "https://publications.scilifelab.se/researcher/cba024b2e3c347f6b981922d984ad2d6.json"}}, {"family": "Lindstrand", "given": "Anna", "initials": "A"}, {"family": "Wedell", "given": "Anna", "initials": "A", "orcid": "0000-0003-0806-5602", "researcher": {"href": "https://publications.scilifelab.se/researcher/07f3e6152da043d38c7a81974fcf8c23.json"}}], "type": "journal article", "published": "2021-03-17", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "13", "issue": "1", "pages": "40"}, "abstract": "We report the findings from 4437 individuals (3219 patients and 1218 relatives) who have been analyzed by whole genome sequencing (WGS) at the Genomic Medicine Center Karolinska-Rare Diseases (GMCK-RD) since mid-2015. GMCK-RD represents a long-term collaborative initiative between Karolinska University Hospital and Science for Life Laboratory to establish advanced, genomics-based diagnostics in the Stockholm healthcare setting.\n\nOur analysis covers detection and interpretation of SNVs, INDELs, uniparental disomy, CNVs, balanced structural variants, and short tandem repeat expansions. Visualization of results for clinical interpretation is carried out in Scout-a custom-developed decision support system. Results from both singleton (84%) and trio/family (16%) analyses are reported. Variant interpretation is done by 15 expert teams at the hospital involving staff from three clinics. For patients with complex phenotypes, data is shared between the teams.\n\nOverall, 40% of the patients received a molecular diagnosis ranging from 19 to 54% for specific disease groups. There was heterogeneity regarding causative genes (n = 754) with some of the most common ones being COL2A1 (n = 12; skeletal dysplasia), SCN1A (n = 8; epilepsy), and TNFRSF13B (n = 4; inborn errors of immunity). Some causative variants were recurrent, including previously known founder mutations, some novel mutations, and recurrent de novo mutations. Overall, GMCK-RD has resulted in a large number of patients receiving specific molecular diagnoses. Furthermore, negative cases have been included in research studies that have resulted in the discovery of 17 published, novel disease-causing genes. To facilitate the discovery of new disease genes, GMCK-RD has joined international data sharing initiatives, including ClinVar, UDNI, Beacon, and MatchMaker Exchange.\n\nClinical WGS at GMCK-RD has provided molecular diagnoses to over 1200 individuals with a broad range of rare diseases. Consolidation and spread of this clinical-academic partnership will enable large-scale national collaboration.", "doi": "10.1186/s13073-021-00855-5", "pmid": "33726816", "labels": {"Clinical Genomics Stockholm": "Collaborative", "Clinical Genomics": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-021-00855-5"}, {"db": "pmc", "key": "PMC7968334"}], "notes": [], "created": "2021-03-17T22:59:29.113Z", "modified": "2023-06-19T07:51:37.812Z"}, {"entity": "publication", "iuid": "4508bd9d4cb6483f9bb4e4f390fdd0ef", "links": {"self": {"href": "https://publications.scilifelab.se/publication/4508bd9d4cb6483f9bb4e4f390fdd0ef.json"}, "display": {"href": "https://publications.scilifelab.se/publication/4508bd9d4cb6483f9bb4e4f390fdd0ef"}}, "title": "Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.", "authors": [{"family": "Gudmundsdottir", "given": "Valborg", "initials": "V"}, {"family": "Pedersen", "given": "Helle Krogh", "initials": "HK"}, {"family": "Mazzoni", "given": "Gianluca", "initials": "G"}, {"family": "Allin", "given": "Kristine H", "initials": "KH"}, {"family": "Artati", "given": "Anna", "initials": "A"}, {"family": "Beulens", "given": "Joline W", "initials": "JW"}, {"family": "Banasik", "given": "Karina", "initials": "K"}, {"family": "Brorsson", "given": "Caroline", "initials": "C"}, {"family": "Cederberg", "given": "Henna", "initials": "H"}, {"family": "Chabanova", "given": "Elizaveta", "initials": "E"}, {"family": "De Masi", "given": "Federico", "initials": "F"}, {"family": "Elders", "given": "Petra J", "initials": "PJ"}, {"family": "Forgie", "given": "Ian", "initials": "I"}, {"family": "Giordano", "given": "Giuseppe N", "initials": "GN"}, {"family": "Grallert", "given": "Harald", "initials": "H"}, {"family": "Gupta", "given": "Ramneek", "initials": "R"}, {"family": "Haid", "given": "Mark", "initials": "M"}, {"family": "Hansen", "given": "Torben", "initials": "T"}, {"family": "Hansen", "given": "Tue H", "initials": "TH"}, {"family": "Hattersley", "given": "Andrew T", "initials": "AT"}, {"family": "Heggie", "given": "Alison", "initials": "A"}, {"family": "Hong", "given": "Mun-Gwan", "initials": "MG"}, {"family": "Jones", "given": "Angus G", "initials": "AG"}, {"family": "Koivula", "given": "Robert", "initials": "R"}, {"family": "Kokkola", "given": "Tarja", "initials": "T"}, {"family": "Laakso", "given": "Markku", "initials": "M"}, {"family": "L\u00f8ngreen", "given": "Peter", "initials": "P"}, {"family": "Mahajan", "given": "Anubha", "initials": "A"}, {"family": "Mari", "given": "Andrea", "initials": "A"}, {"family": "McDonald", "given": "Timothy J", "initials": "TJ"}, {"family": "McEvoy", "given": "Donna", "initials": "D"}, {"family": "Musholt", "given": "Petra B", "initials": "PB"}, {"family": "Pavo", "given": "Imre", "initials": "I"}, {"family": "Prehn", "given": "Cornelia", "initials": "C"}, {"family": "Ruetten", "given": "Hartmut", "initials": "H"}, {"family": "Ridderstr\u00e5le", "given": "Martin", "initials": "M"}, {"family": "Rutters", "given": "Femke", "initials": "F"}, {"family": "Sharma", "given": "Sapna", "initials": "S"}, {"family": "Slieker", "given": "Roderick C", "initials": "RC"}, {"family": "Syed", "given": "Ali", "initials": "A"}, {"family": "Tajes", "given": "Juan Fernandez", "initials": "JF"}, {"family": "Thomas", "given": "Cecilia Engel", "initials": "CE"}, {"family": "Thomsen", "given": "Henrik S", "initials": "HS"}, {"family": "Vangipurapu", "given": "Jagadish", "initials": "J"}, {"family": "Vestergaard", "given": "Henrik", "initials": "H"}, {"family": "Vi\u00f1uela", "given": "Ana", "initials": "A"}, {"family": "Wesolowska-Andersen", "given": "Agata", "initials": "A"}, {"family": "Walker", "given": "Mark", "initials": "M"}, {"family": "Adamski", "given": "Jerzy", "initials": "J"}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}, {"family": "McCarthy", "given": "Mark I", "initials": "MI"}, {"family": "Pearson", "given": "Ewan", "initials": "E"}, {"family": "Dermitzakis", "given": "Emmanouil", "initials": "E"}, {"family": "Franks", "given": "Paul W", "initials": "PW"}, {"family": "Pedersen", "given": "Oluf", "initials": "O"}, {"family": "Brunak", "given": "S\u00f8ren", "initials": "S", "orcid": "0000-0003-0316-5866", "researcher": {"href": "https://publications.scilifelab.se/researcher/76fd1f30268c450092b654e25a5db4ee.json"}}], "type": "journal article", "published": "2020-12-01", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "12", "issue": "1", "pages": "109"}, "abstract": "The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.\n\nClusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.\n\nWe identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.\n\nOur results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.", "doi": "10.1186/s13073-020-00806-6", "pmid": "33261667", "labels": {"Affinity Proteomics Stockholm": "Collaborative"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-020-00806-6"}, {"db": "pmc", "key": "PMC7708171"}], "notes": [], "created": "2020-12-10T19:03:50.791Z", "modified": "2021-11-10T12:44:28.124Z"}, {"entity": "publication", "iuid": "870f001b1e924bc3b362c4ae5d683273", "links": {"self": {"href": "https://publications.scilifelab.se/publication/870f001b1e924bc3b362c4ae5d683273.json"}, "display": {"href": "https://publications.scilifelab.se/publication/870f001b1e924bc3b362c4ae5d683273"}}, "title": "Whole-genome sequence association analysis of blood proteins in a longitudinal wellness cohort.", "authors": [{"family": "Zhong", "given": "Wen", "initials": "W"}, {"family": "Gummesson", "given": "Anders", "initials": "A"}, {"family": "Tebani", "given": "Abdellah", "initials": "A"}, {"family": "Karlsson", "given": "Max J", "initials": "MJ"}, {"family": "Hong", "given": "Mun-Gwan", "initials": "MG"}, {"family": "Schwenk", "given": "Jochen M", "initials": "JM", "orcid": "0000-0001-8141-8449", "researcher": {"href": "https://publications.scilifelab.se/researcher/aba5822711b246b397fffacb7ae403b3.json"}}, {"family": "Edfors", "given": "Fredrik", "initials": "F"}, {"family": "Bergstr\u00f6m", "given": "G\u00f6ran", "initials": "G"}, {"family": "Fagerberg", "given": "Linn", "initials": "L"}, {"family": "Uhl\u00e9n", "given": "Mathias", "initials": "M", "orcid": "0000-0002-4858-8056", "researcher": {"href": "https://publications.scilifelab.se/researcher/ff81da3cb0cf4262873b993a1b06798c.json"}}], "type": "journal article", "published": "2020-06-23", "journal": {"title": "Genome Med", "issn": "1756-994X", "issn-l": "1756-994X", "volume": "12", "issue": "1", "pages": "53"}, "abstract": "The human plasma proteome is important for many biological processes and targets for diagnostics and therapy. It is therefore of great interest to understand the interplay of genetic and environmental factors to determine the specific protein levels in individuals and to gain a deeper insight of the importance of genetic architecture related to the individual variability of plasma levels of proteins during adult life.\n\nWe have combined whole-genome sequencing, multiplex plasma protein profiling, and extensive clinical phenotyping in a longitudinal 2-year wellness study of 101 healthy individuals with repeated sampling. Analyses of genetic and non-genetic associations related to the variability of blood levels of proteins in these individuals were performed.\n\nThe analyses showed that each individual has a unique protein profile, and we report on the intra-individual as well as inter-individual variation for 794 plasma proteins. A genome-wide association study (GWAS) using 7.3 million genetic variants identified by whole-genome sequencing revealed 144 independent variants across 107 proteins that showed strong association (P < 6 \u00d7 10-11) between genetics and the inter-individual variability on protein levels. Many proteins not reported before were identified (67 out of 107) with individual plasma level affected by genetics. Our longitudinal analysis further demonstrates that these levels are stable during the 2-year study period. The variability of protein profiles as a consequence of environmental factors was also analyzed with focus on the effects of weight loss and infections.\n\nWe show that the adult blood levels of many proteins are determined at birth by genetics, which is important for efforts aimed to understand the relationship between plasma proteome profiles and human biology and disease.", "doi": "10.1186/s13073-020-00755-0", "pmid": "32576278", "labels": {"Affinity Proteomics Stockholm": "Collaborative", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-020-00755-0"}, {"db": "pmc", "key": "PMC7310558"}], "notes": [], "created": "2020-12-10T19:03:45.805Z", "modified": "2024-01-16T13:48:42.348Z"}, {"entity": "publication", "iuid": "fe4601405ded493f93c9a5be716c5c06", "links": {"self": {"href": "https://publications.scilifelab.se/publication/fe4601405ded493f93c9a5be716c5c06.json"}, "display": {"href": "https://publications.scilifelab.se/publication/fe4601405ded493f93c9a5be716c5c06"}}, "title": "From cytogenetics to cytogenomics: whole-genome sequencing as a first-line test comprehensively captures the diverse spectrum of disease-causing genetic variation underlying intellectual disability.", "authors": [{"family": "Lindstrand", "given": "Anna", "initials": "A", "orcid": "0000-0003-0806-5602", "researcher": {"href": "https://publications.scilifelab.se/researcher/07f3e6152da043d38c7a81974fcf8c23.json"}}, {"family": "Eisfeldt", "given": "Jesper", "initials": "J"}, {"family": "Pettersson", "given": "Maria", "initials": "M"}, {"family": "Carvalho", "given": "Claudia M B", "initials": "CMB"}, {"family": "Kvarnung", "given": "Malin", "initials": "M"}, {"family": "Grigelioniene", "given": "Giedre", "initials": "G"}, {"family": "Anderlid", "given": "Britt-Marie", "initials": "BM"}, {"family": "Bjerin", "given": "Olof", "initials": "O"}, {"family": "Gustavsson", "given": "Peter", "initials": "P"}, {"family": "Hammarsj\u00f6", "given": "Anna", "initials": "A"}, {"family": "Georgii-Hemming", "given": "Patrik", "initials": "P"}, {"family": "Iwarsson", "given": "Erik", "initials": "E"}, {"family": "Johansson-Soller", "given": "Maria", "initials": "M"}, {"family": "Lagerstedt-Robinson", "given": "Kristina", "initials": "K"}, {"family": "Lieden", "given": "Agne", "initials": "A"}, {"family": "Magnusson", "given": "M\u00e5ns", "initials": "M"}, {"family": "Martin", "given": "Marcel", "initials": "M"}, {"family": "Malmgren", "given": "Helena", "initials": "H"}, {"family": "Nordenskj\u00f6ld", "given": "Magnus", "initials": "M"}, {"family": "Norling", "given": "Ameli", "initials": "A"}, {"family": "Sahlin", "given": "Ellika", "initials": "E"}, {"family": "Stranneheim", "given": "Henrik", "initials": "H"}, {"family": "Tham", "given": "Emma", "initials": "E"}, {"family": "Wincent", "given": "Josephine", "initials": "J"}, {"family": "Ygberg", "given": "Sofia", "initials": "S"}, {"family": "Wedell", "given": "Anna", "initials": "A"}, {"family": "Wirta", "given": "Valtteri", "initials": "V", "orcid": "0000-0003-3811-5439", "researcher": {"href": "https://publications.scilifelab.se/researcher/cba024b2e3c347f6b981922d984ad2d6.json"}}, {"family": "Nordgren", "given": "Ann", "initials": "A"}, {"family": "Lundin", "given": "Johanna", "initials": "J"}, {"family": "Nilsson", "given": "Daniel", "initials": "D"}], "type": "journal article", "published": "2019-11-07", "journal": {"volume": "11", "issn": "1756-994X", "issue": "1", "pages": "68", "title": "Genome Med", "issn-l": "1756-994X"}, "abstract": "Since different types of genetic variants, from single nucleotide variants (SNVs) to large chromosomal rearrangements, underlie intellectual disability, we evaluated the use of whole-genome sequencing (WGS) rather than chromosomal microarray analysis (CMA) as a first-line genetic diagnostic test.\n\nWe analyzed three cohorts with short-read WGS: (i) a retrospective cohort with validated copy number variants (CNVs) (cohort 1, n = 68), (ii) individuals referred for monogenic multi-gene panels (cohort 2, n = 156), and (iii) 100 prospective, consecutive cases referred to our center for CMA (cohort 3). Bioinformatic tools developed include FindSV, SVDB, Rhocall, Rhoviz, and vcf2cytosure.\n\nFirst, we validated our structural variant (SV)-calling pipeline on cohort 1, consisting of three trisomies and 79 deletions and duplications with a median size of 850 kb (min 500 bp, max 155 Mb). All variants were detected. Second, we utilized the same pipeline in cohort 2 and analyzed with monogenic WGS panels, increasing the diagnostic yield to 8%. Next, cohort 3 was analyzed by both CMA and WGS. The WGS data was processed for large (> 10 kb) SVs genome-wide and for exonic SVs and SNVs in a panel of 887 genes linked to intellectual disability as well as genes matched to patient-specific Human Phenotype Ontology (HPO) phenotypes. This yielded a total of 25 pathogenic variants (SNVs or SVs), of which 12 were detected by CMA as well. We also applied short tandem repeat (STR) expansion detection and discovered one pathologic expansion in ATXN7. Finally, a case of Prader-Willi syndrome with uniparental disomy (UPD) was validated in the WGS data. Important positional information was obtained in all cohorts. Remarkably, 7% of the analyzed cases harbored complex structural variants, as exemplified by a ring chromosome and two duplications found to be an insertional translocation and part of a cryptic unbalanced translocation, respectively.\n\nThe overall diagnostic rate of 27% was more than doubled compared to clinical microarray (12%). Using WGS, we detected a wide range of SVs with high accuracy. Since the WGS data also allowed for analysis of SNVs, UPD, and STRs, it represents a powerful comprehensive genetic test in a clinical diagnostic laboratory setting.", "doi": "10.1186/s13073-019-0675-1", "pmid": "31694722", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Long-term Support WABI": "Collaborative", "National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Stockholm (Genomics Production)": "Service", "Clinical Genomics Stockholm": "Technology development", "Bioinformatics Support for Computational Resources": "Service", "Bioinformatics (NBIS)": "Collaborative", "Clinical Genomics": "Technology development"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-019-0675-1"}, {"db": "pmc", "key": "PMC6836550"}], "notes": [], "created": "2019-11-21T13:21:06.171Z", "modified": "2024-01-16T13:48:43.561Z"}, {"entity": "publication", "iuid": "e9dcc8c6cfb543bd9d2439e6e883fbb3", "links": {"self": {"href": "https://publications.scilifelab.se/publication/e9dcc8c6cfb543bd9d2439e6e883fbb3.json"}, "display": {"href": "https://publications.scilifelab.se/publication/e9dcc8c6cfb543bd9d2439e6e883fbb3"}}, "title": "Linking FOXO3, NCOA3, and TCF7L2 to Ras pathway phenotypes through a genome-wide forward genetic screen in human colorectal cancer cells", "authors": [{"family": "Kundu", "given": "Snehangshu", "initials": "S"}, {"family": "Ali", "given": "Muhammad Akhtar", "initials": "MA"}, {"family": "Handin", "given": "Niklas", "initials": "N"}, {"family": "Padhan", "given": "Narendra", "initials": "N"}, {"family": "Larsson", "given": "Jimmy", "initials": "J"}, {"family": "Karoutsou", "given": "Maria", "initials": "M"}, {"family": "Ban", "given": "Kenneth", "initials": "K"}, {"family": "Wi\u015bniewski", "given": "Jacek R", "initials": "JR"}, {"family": "Artursson", "given": "Per", "initials": "P"}, {"family": "He", "given": "Liqun", "initials": "L"}, {"family": "Hellstr\u00f6m", "given": "Mats", "initials": "M"}, {"family": "Sj\u00f6blom", "given": "Tobias", "initials": "T"}], "type": "journal-article", "published": "2018-12-00", "journal": {"volume": "10", "issn": "1756-994X", "issue": "1", "pages": null, "title": "Genome Med", "issn-l": "1756-994X"}, "abstract": null, "doi": "10.1186/s13073-017-0511-4", "pmid": "29301589", "labels": {"National Genomics Infrastructure": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "BioProject", "description": "A genome-wide forward genetic screen in transposon mutagenized human colorectal carcinomas cells", "key": "PRJNA419878"}, {"db": "https://www.ebi.ac.uk/pride/archive/", "description": "https://www.ebi.ac.uk/pride/archive/projects/PXD008382", "key": "PXD008382"}], "notes": [], "created": "2018-01-09T20:57:49.046Z", "modified": "2024-01-16T13:48:45.035Z"}, {"entity": "publication", "iuid": "d0a79cde90174e5c9f0b7441e521b554", "links": {"self": {"href": "https://publications.scilifelab.se/publication/d0a79cde90174e5c9f0b7441e521b554.json"}, "display": {"href": "https://publications.scilifelab.se/publication/d0a79cde90174e5c9f0b7441e521b554"}}, "title": "Cell-free DNA profiling of metastatic prostate cancer reveals microsatellite instability, structural rearrangements and clonal hematopoiesis.", "authors": [{"family": "Mayrhofer", "given": "Markus", "initials": "M"}, {"family": "De Laere", "given": "Bram", "initials": "B"}, {"family": "Whitington", "given": "Tom", "initials": "T"}, {"family": "Van Oyen", "given": "Peter", "initials": "P"}, {"family": "Ghysel", "given": "Christophe", "initials": "C"}, {"family": "Ampe", "given": "Jozef", "initials": "J"}, {"family": "Ost", "given": "Piet", "initials": "P"}, {"family": "Demey", "given": "Wim", "initials": "W"}, {"family": "Hoekx", "given": "Lucien", "initials": "L"}, {"family": "Schrijvers", "given": "Dirk", "initials": "D"}, {"family": "Brouwers", "given": "Barbara", "initials": "B"}, {"family": "Lybaert", "given": "Willem", "initials": "W"}, {"family": "Everaert", "given": "Els", "initials": "E"}, {"family": "De Maeseneer", "given": "Daan", "initials": "D"}, {"family": "Strijbos", "given": "Michiel", "initials": "M"}, {"family": "Bols", "given": "Alain", "initials": "A"}, {"family": "Fransis", "given": "Karen", "initials": "K"}, {"family": "Oeyen", "given": "Steffi", "initials": "S"}, {"family": "van Dam", "given": "Pieter-Jan", "initials": "P"}, {"family": "Van den Eynden", "given": "Gert", "initials": "G"}, {"family": "Rutten", "given": "Annemie", "initials": "A"}, {"family": "Aly", "given": "Markus", "initials": "M"}, {"family": "Nordstr\u00f6m", "given": "Tobias", "initials": "T"}, {"family": "Van Laere", "given": "Steven", "initials": "S"}, {"family": "Rantalainen", "given": "Mattias", "initials": "M"}, {"family": "Rajan", "given": "Prabhakar", "initials": "P"}, {"family": "Egevad", "given": "Lars", "initials": "L"}, {"family": "Ull\u00e9n", "given": "Anders", "initials": "A"}, {"family": "Yachnin", "given": "Jeffrey", "initials": "J"}, {"family": "Dirix", "given": "Luc", "initials": "L"}, {"family": "Gr\u00f6nberg", "given": "Henrik", "initials": "H"}, {"family": "Lindberg", "given": "Johan", "initials": "J"}], "type": "journal article", "published": "2018-11-21", "journal": {"volume": "10", "issn": "1756-994X", "issue": "1", "pages": "85", "title": "Genome Med", "issn-l": "1756-994X"}, "abstract": "There are multiple existing and emerging therapeutic avenues for metastatic prostate cancer, with a common denominator, which is the need for predictive biomarkers. Circulating tumor DNA (ctDNA) has the potential to cost-efficiently accelerate precision medicine trials to improve clinical efficacy and diminish costs and toxicity. However, comprehensive ctDNA profiling in metastatic prostate cancer to date has been limited.\r\n\r\nA combination of targeted and low-pass whole genome sequencing was performed on plasma cell-free DNA and matched white blood cell germline DNA in 364 blood samples from 217 metastatic prostate cancer patients.\r\n\r\nctDNA was detected in 85.9% of baseline samples, correlated to line of therapy and was mirrored by circulating tumor cell enumeration of synchronous blood samples. Comprehensive profiling of the androgen receptor (AR) revealed a continuous increase in the fraction of patients with intra-AR structural variation, from 15.4% during first-line metastatic castration-resistant prostate cancer therapy to 45.2% in fourth line, indicating a continuous evolution of AR during the course of the disease. Patients displayed frequent alterations in DNA repair deficiency genes (18.0%). Additionally, the microsatellite instability phenotype was identified in 3.81% of eligible samples (\u2265\u20090.1 ctDNA fraction). Sequencing of non-repetitive intronic and exonic regions of PTEN, RB1, and TP53 detected biallelic inactivation in 47.5%, 20.3%, and 44.1% of samples with \u2265\u20090.2 ctDNA fraction, respectively. Only one patient carried a clonal high-impact variant without a detectable second hit. Intronic high-impact structural variation was twice as common as exonic mutations in PTEN and RB1. Finally, 14.6% of patients presented false positive variants due to clonal hematopoiesis, commonly ignored in commercially available assays.\r\n\r\nctDNA profiles appear to mirror the genomic landscape of metastatic prostate cancer tissue and may cost-efficiently provide somatic information in clinical trials designed to identify predictive biomarkers. However, intronic sequencing of the interrogated tumor suppressors challenges the ubiquitous focus on coding regions and is vital, together with profiling of synchronous white blood cells, to minimize erroneous assignments which in turn may confound results and impede true associations in clinical trials.", "doi": "10.1186/s13073-018-0595-5", "pmid": "30458854", "labels": {"Clinical Genomics Stockholm": "Service", "Bioinformatics Support for Computational Resources": "Service", "Clinical Genomics": "Service"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-018-0595-5"}, {"db": "pmc", "key": "PMC6247769"}], "notes": [], "created": "2018-12-06T15:00:23.816Z", "modified": "2024-01-16T13:48:45.170Z"}, {"entity": "publication", "iuid": "914e667e695641e7827adaf9b0dcf69b", "links": {"self": {"href": "https://publications.scilifelab.se/publication/914e667e695641e7827adaf9b0dcf69b.json"}, "display": {"href": "https://publications.scilifelab.se/publication/914e667e695641e7827adaf9b0dcf69b"}}, "title": "Type 2 diabetes and obesity induce similar transcriptional reprogramming in human myocytes.", "authors": [{"family": "V\u00e4remo", "given": "Leif", "initials": "L"}, {"family": "Henriksen", "given": "Tora Ida", "initials": "TI"}, {"family": "Scheele", "given": "Camilla", "initials": "C"}, {"family": "Broholm", "given": "Christa", "initials": "C"}, {"family": "Pedersen", "given": "Maria", "initials": "M"}, {"family": "Uhl\u00e9n", "given": "Mathias", "initials": "M", "orcid": "0000-0002-4858-8056", "researcher": {"href": "https://publications.scilifelab.se/researcher/ff81da3cb0cf4262873b993a1b06798c.json"}}, {"family": "Pedersen", "given": "Bente Klarlund", "initials": "BK"}, {"family": "Nielsen", "given": "Jens", "initials": "J", "orcid": "0000-0002-9955-6003", "researcher": {"href": "https://publications.scilifelab.se/researcher/7a596e289be4438a8a2653b1f25fea8b.json"}}], "type": "journal article", "published": "2017-05-25", "journal": {"volume": "9", "issn": "1756-994X", "issue": "1", "pages": "47", "title": "Genome Med", "issn-l": "1756-994X"}, "abstract": "Skeletal muscle is one of the primary tissues involved in the development of type 2 diabetes (T2D). The close association between obesity and T2D makes it difficult to isolate specific effects attributed to the disease alone. Therefore, here we set out to identify and characterize intrinsic properties of myocytes, associated independently with T2D or obesity.\n\nWe generated and analyzed RNA-seq data from primary differentiated myotubes from 24 human subjects, using a factorial design (healthy/T2D and non-obese/obese), to determine the influence of each specific factor on genome-wide transcription. This setup enabled us to identify intrinsic properties, originating from muscle precursor cells and retained in the corresponding myocytes. Bioinformatic and statistical methods, including differential expression analysis, gene-set analysis, and metabolic network analysis, were used to characterize the different myocytes.\n\nWe found that the transcriptional program associated with obesity alone was strikingly similar to that induced specifically by T2D. We identified a candidate epigenetic mechanism, H3K27me3 histone methylation, mediating these transcriptional signatures. T2D and obesity were independently associated with dysregulated myogenesis, down-regulated muscle function, and up-regulation of inflammation and extracellular matrix components. Metabolic network analysis identified that in T2D but not obesity a specific metabolite subnetwork involved in sphingolipid metabolism was transcriptionally regulated.\n\nOur findings identify inherent characteristics in myocytes, as a memory of the in vivo phenotype, without the influence from a diabetic or obese extracellular environment, highlighting their importance in the development of T2D.", "doi": "10.1186/s13073-017-0432-2", "pmid": "28545587", "labels": {"National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Stockholm (Genomics Production)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-017-0432-2"}, {"db": "pmc", "key": "PMC5444103"}], "notes": [], "created": "2017-11-03T15:53:40.517Z", "modified": "2024-01-16T13:48:47.954Z"}, {"entity": "publication", "iuid": "f3d7e33e0bef4063bfd1f2c3849265da", "links": {"self": {"href": "https://publications.scilifelab.se/publication/f3d7e33e0bef4063bfd1f2c3849265da.json"}, "display": {"href": "https://publications.scilifelab.se/publication/f3d7e33e0bef4063bfd1f2c3849265da"}}, "title": "Many obesity-associated SNPs strongly associate with DNA methylation changes at proximal promoters and enhancers.", "authors": [{"family": "Voisin", "given": "Sarah", "initials": "S"}, {"family": "Alm\u00e9n", "given": "Markus S\u00e4llman", "initials": "MS"}, {"family": "Zheleznyakova", "given": "Galina Y", "initials": "GY"}, {"family": "Lundberg", "given": "Lina", "initials": "L"}, {"family": "Zarei", "given": "Sanaz", "initials": "S"}, {"family": "Castillo", "given": "Sandra", "initials": "S"}, {"family": "Eriksson", "given": "Fia Ence", "initials": "FE"}, {"family": "Nilsson", "given": "Emil K", "initials": "EK"}, {"family": "Bl\u00fcher", "given": "Matthias", "initials": "M"}, {"family": "B\u00f6ttcher", "given": "Yvonne", "initials": "Y"}, {"family": "Kovacs", "given": "Peter", "initials": "P"}, {"family": "Klovins", "given": "Janis", "initials": "J"}, {"family": "Rask-Andersen", "given": "Mathias", "initials": "M"}, {"family": "Schi\u00f6th", "given": "Helgi B", "initials": "HB"}], "type": "journal article", "published": "2015-10-08", "journal": {"volume": "7", "issn": "1756-994X", "issue": null, "pages": "103", "title": "Genome Med", "issn-l": "1756-994X"}, "abstract": "The mechanisms by which genetic variants, such as single nucleotide polymorphisms (SNPs), identified in genome-wide association studies act to influence body mass remain unknown for most of these SNPs, which continue to puzzle the scientific community. Recent evidence points to the epigenetic and chromatin states of the genome as having important roles.\n\nWe genotyped 355 healthy young individuals for 52 known obesity-associated SNPs and obtained DNA methylation levels in their blood using the Illumina 450 K BeadChip. Associations between alleles and methylation at proximal cytosine residues were tested using a linear model adjusted for age, sex, weight category, and a proxy for blood cell type counts. For replication in other tissues, we used two open-access datasets (skin fibroblasts, n\u2009=\u200962; four brain regions, n\u2009=\u2009121-133) and an additional dataset in subcutaneous and visceral fat (n\u2009=\u2009149).\n\nWe found that alleles at 28 of these obesity-associated SNPs associate with methylation levels at 107 proximal CpG sites. Out of 107 CpG sites, 38 are located in gene promoters, including genes strongly implicated in obesity (MIR148A, BDNF, PTPMT1, NR1H3, MGAT1, SCGB3A1, HOXC12, PMAIP1, PSIP1, RPS10-NUDT3, RPS10, SKOR1, MAP2K5, SIX5, AGRN, IMMP1L, ELP4, ITIH4, SEMA3G, POMC, ADCY3, SSPN, LGR4, TUFM, MIR4721, SULT1A1, SULT1A2, APOBR, CLN3, SPNS1, SH2B1, ATXN2L, and IL27). Interestingly, the associated SNPs are in known eQTLs for some of these genes. We also found that the 107 CpGs are enriched in enhancers in peripheral blood mononuclear cells. Finally, our results indicate that some of these associations are not blood-specific as we successfully replicated four associations in skin fibroblasts.\n\nOur results strongly suggest that many obesity-associated SNPs are associated with proximal gene regulation, which was reflected by association of obesity risk allele genotypes with differential DNA methylation. This study highlights the importance of DNA methylation and other chromatin marks as a way to understand the molecular basis of genetic variants associated with human diseases and traits.", "doi": "10.1186/s13073-015-0225-4", "pmid": "26449484", "labels": {"National Genomics Infrastructure": null, "NGI Uppsala (SNP&SEQ Technology Platform)": null}, "xrefs": [{"db": "pii", "key": "10.1186/s13073-015-0225-4"}, {"db": "pmc", "key": "PMC4599317"}], "notes": [], "created": "2017-05-02T12:58:52.365Z", "modified": "2020-01-21T13:56:06.308Z"}, {"entity": "publication", "iuid": "18a47010d25b47b2bb656d6e7d31ffa9", "links": {"self": {"href": "https://publications.scilifelab.se/publication/18a47010d25b47b2bb656d6e7d31ffa9.json"}, "display": {"href": "https://publications.scilifelab.se/publication/18a47010d25b47b2bb656d6e7d31ffa9"}}, "title": "Comprehensive analysis of the genome transcriptome and proteome landscapes of three tumor cell lines.", "authors": [{"family": "Akan", "given": "Pelin", "initials": "P"}, {"family": "Alexeyenko", "given": "Andrey", "initials": "A"}, {"family": "Costea", "given": "Paul Igor", "initials": "PI"}, {"family": "Hedberg", "given": "Lilia", "initials": "L"}, {"family": "Solnestam", "given": "Beata Werne", "initials": "BW"}, {"family": "Lundin", "given": "Sverker", "initials": "S"}, {"family": "H\u00e4llman", "given": "Jimmie", "initials": "J"}, {"family": "Lundberg", "given": "Emma", "initials": "E", "orcid": "0000-0001-7034-0850", "researcher": {"href": "https://publications.scilifelab.se/researcher/1ffe6259ceb540f385861b5ae52b3055.json"}}, {"family": "Uhl\u00e9n", "given": "Mathias", "initials": "M", "orcid": "0000-0002-4858-8056", "researcher": {"href": "https://publications.scilifelab.se/researcher/ff81da3cb0cf4262873b993a1b06798c.json"}}, {"family": "Lundeberg", "given": "Joakim", "initials": "J", "orcid": "0000-0003-4313-1601", "researcher": {"href": "https://publications.scilifelab.se/researcher/4a4e6ca0f29b4ead8569e2729481c3e0.json"}}], "type": "journal article", "published": "2012-11-18", "journal": {"volume": "4", "issn": "1756-994X", "issue": "11", "pages": "86", "title": "Genome Med", "issn-l": "1756-994X"}, "abstract": "We here present a comparative genome, transcriptome and functional network analysis of three human cancer cell lines (A431, U251MG and U2OS), and investigate their relation to protein expression. Gene copy numbers significantly influenced corresponding transcript levels; their effect on protein levels was less pronounced. We focused on genes with altered mRNA and/or protein levels to identify those active in tumor maintenance. We provide comprehensive information for the three genomes and demonstrate the advantage of integrative analysis for identifying tumor-related genes amidst numerous background mutations by relating genomic variation to expression/protein abundance data and use gene networks to reveal implicated pathways.", "doi": "10.1186/gm387", "pmid": "23158748", "labels": {"National Genomics Infrastructure": null, "NGI Stockholm (Genomics Applications)": null, "NGI Stockholm (Genomics Production)": null, "Spatial Proteomics": null}, "xrefs": [{"db": "pii", "key": "gm387"}, {"db": "pmc", "key": "PMC3580420"}], "notes": [], "created": "2017-05-04T14:55:10.176Z", "modified": "2021-07-08T13:44:33.049Z"}], "created": "2017-05-09T09:12:27.685Z", "modified": "2020-11-27T13:14:06.939Z"}