| 1. |
- Sliz, E., et al.
(författare)
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Evidence of a causal effect of genetic tendency to gain muscle mass on uterine leiomyomata
- 2023
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Uterine leiomyomata (UL) are the most common tumours of the female genital tract and the primary cause of surgical removal of the uterus. Genetic factors contribute to UL susceptibility. To add understanding to the heritable genetic risk factors, we conduct a genome-wide association study (GWAS) of UL in up to 426,558 European women from FinnGen and a previous UL meta-GWAS. In addition to the 50 known UL loci, we identify 22 loci that have not been associated with UL in prior studies. UL-associated loci harbour genes enriched for development, growth, and cellular senescence. Of particular interest are the smooth muscle cell differentiation and proliferation-regulating genes functioning on the myocardin-cyclin dependent kinase inhibitor 1A pathway. Our results further suggest that genetic predisposition to increased fat-free mass may be causally related to higher UL risk, underscoring the involvement of altered muscle tissue biology in UL pathophysiology. Overall, our findings add to the understanding of the genetic pathways underlying UL, which may aid in developing novel therapeutics.
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| 2. |
- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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| 3. |
- Ruuth, M., et al.
(författare)
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Susceptibility of low-density lipoprotein particles to aggregate depends on particle lipidome, ismodifiable, and associates with future cardiovascular deaths
- 2018
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 39:27, s. 2562-
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Tidskriftsartikel (refereegranskat)abstract
- Aims Low-density lipoprotein (LDL) particles cause atherosclerotic cardiovascular disease (ASCVD) through their retention, modification, and accumulation within the arterial intima. High plasma concentrations of LDL drive this disease, but LDL quality may also contribute. Here, we focused on the intrinsic propensity of LDL to aggregate upon modification. We examined whether inter-individual differences in this quality are linked with LDL lipid composition and coronary artery disease (CAD) death, and basic mechanisms for plaque growth and destabilization. Methods and results We developed a novel, reproducible method to assess the susceptibility of LDL particles to aggregate during lipolysis induced ex vivo by human recombinant secretory sphingomyelinase. Among patients with an established CAD, we found that the presence of aggregation-prone LDL was predictive of future cardiovascular deaths, independently of conventional risk factors. Aggregation-prone LDL contained more sphingolipids and less phosphatidylcholines than did aggregation-resistant LDL. Three interventions in animal models to rationally alter LDL composition lowered its susceptibility to aggregate and slowed atherosclerosis. Similar compositional changes induced in humans by PCSK9 inhibition or healthy diet also lowered LDL aggregation susceptibility. Aggregated LDL in vitro activated macrophages and T cells, two key cell types involved in plaque progression and rupture. Conclusion Our results identify the susceptibility of LDL to aggregate as a novel measurable and modifiable factor in the progression of human ASCVD.
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| 4. |
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| 5. |
- Gabriel, M., et al.
(författare)
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A relational database to identify differentially expressed genes in the endometrium and endometriosis lesions
- 2020
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Endometriosis is a common inflammatory estrogen-dependent gynecological disorder, associated with pelvic pain and reduced fertility in women. Several aspects of this disorder and its cellular and molecular etiology remain unresolved. We have analyzed the global gene expression patterns in the endometrium, peritoneum and in endometriosis lesions of endometriosis patients and in the endometrium and peritoneum of healthy women. In this report, we present the EndometDB, an interactive web-based user interface for browsing the gene expression database of collected samples without the need for computational skills. The EndometDB incorporates the expression data from 115 patients and 53 controls, with over 24000 genes and clinical features, such as their age, disease stages, hormonal medication, menstrual cycle phase, and the different endometriosis lesion types. Using the web-tool, the end-user can easily generate various plot outputs and projections, including boxplots, and heatmaps and the generated outputs can be downloaded in pdf-format.
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| 6. |
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| 7. |
- Heinosalo, T., et al.
(författare)
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Secreted frizzled-related protein 2 (SFRP2) expression promotes lesion proliferation via canonical WNT signaling and indicates lesion borders in extraovarian endometriosis
- 2018
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Ingår i: Human Reproduction. - : Oxford University Press (OUP). - 0268-1161 .- 1460-2350. ; 33:5, s. 817-831
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Tidskriftsartikel (refereegranskat)abstract
- STUDY QUESTION: What is the role of SFRP2 in endometriosis? SUMMARY ANSWER: SFRP2 acts as a canonical WNT/CTNNBI signaling agonist in endometriosis, regulating endometriosis lesion growth and indicating endometriosis lesion borders together with CTNNBI (also known as beta catenin). WHAT IS KNOWN ALREADY: Endometriosis is a common, chronic disease that affects women of reproductive age, causing pain and infertility, and has significant economic impact on national health systems. Despite extensive research, the pathogenesis of endometriosis is poorly understood, and targeted medical treatments are lacking. WNT signaling is dysregulated in various human diseases, but its role in extraovarian endometriosis has not been fully elucidated. STUDY DESIGN, SIZE, DURATION: We evaluated the significance of WNT signaling, and especially secreted frizzled-related protein 2 (SFRP2), in extraovarian endometriosis, including peritoneal and deep lesions. The study design was based on a cohort of clinical samples collected by laparoscopy or curettage and questionnaire data from healthy controls and endometriosis patients. PARTICIPANTS/MATERIALS, SETTING, METHODS: Global gene expression analysis in human endometrium ( n = 104) and endometriosis (n = 177) specimens from 47 healthy controls and 103 endometriosis patients was followed by bioinformatics and supportive qPCR analyses. Immunohistochemistry, Western blotting, primary cell culture and siRNA knockdown approaches were used to validate the findings. MAIN RESULTS AND THE ROLE OF CHANCE: Among the 220 WNT signaling and CTNNBI target genes analysed, 184 genes showed differential expression in extraovarian endometriosis (P < 0.05) compared with endometrium tissue, including SFRP2 and CTNNI. Menstrual cycle-dependent regulation of WNT genes observed in the endometrium was lost in endometriosis lesions, as shown by hierarchical clustering. Immunohistochemical analysis indicated that SFRP2 and CTNNBI are novel endometriosis lesion border markers, complementing immunostaining for the known marker CD10 (also known as MME). SFRP2 and CTNNBI localized similarly in both the epithelium and stroma of extraovarian endometriosis tissue, and interestingly, both also indicated an additional distant lesion border, suggesting that WNT signaling is altered in the endometriosis stroma beyond the primary border indicated by the known marker CD10. SFRP2 expression was positively associated with pain symptoms experienced by patients (P < 0.05), and functional loss of SFRP2 in extraovarian endometriosis primary cell cultures resulted in decreased cell proliferation (P < 0.05) associated with reduced CTNNBI protein expression (P = 0.05). LIMITATIONS REASONS FOR CAUTION: SFRP2 and CTNNBI improved extraovarian endometriosis lesion border detection in a relatively small cohort (n = 20), although larger studies with different endometriosis subtypes in variable cycle phases and under hormonal medication are required. WIDER IMPLICATIONS OF THE FINDINGS: The highly expressed SFRP2 and CTNNBI improve endometriosis lesion border detection, which can have clinical implications for better visualization of endometriosis lesions over CD10. Furthermore, SFRP2 acts as a canonical WNT/CTNNBI signaling agonist in endometriosis and positively regulates endometriosis lesion growth, suggesting that the WNT pathway may be an important therapeutic target for endometriosis.
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| 8. |
- Sieberts, SK, et al.
(författare)
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Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis
- 2016
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7, s. 12460-
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Tidskriftsartikel (refereegranskat)abstract
- Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.
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| 9. |
- Vehmas, A. P., et al.
(författare)
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Ovarian Endometriosis Signatures Established through Discovery and Directed Mass Spectrometry Analysis
- 2014
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Ingår i: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 13:11, s. 4983-4994
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Tidskriftsartikel (refereegranskat)abstract
- New molecular information on potential therapeutic targets or tools for noninvasive diagnosis for endometriosis are important for patient care and treatment. However, surprisingly few efforts have described endometriosis at the protein level. In this work we enumerate the proteins in patient endometrium and ovarian endometrioma by extensive and comprehensive analysis of minute amounts of cryosectioned tissues in a three-tiered mass spectrometric approach. Quantitative comparison of the tissues revealed 214 differentially expressed proteins in ovarian endometrioma and endometrium. These proteins are reported here as a resource of SRM (selected reaction monitoring) assays that are unique, standardized, and openly available. Pathway analysis of the proteome measurements revealed a potential role for Transforming growth factor beta-1 in ovarian endometriosis development. Subsequent mRNA microarray analysis further revealed clear ovarian endometrioma specificity for a subset of these proteins, which was also supported by further in silico studies. In this process two important proteins emerged, Calponin-1 and EMILIN-1, that were additionally confirmed in ovarian endometrioma tissues by immunohistochemistry and Western blotting. This study provides the most comprehensive molecular description of ovarian endometriosis to date and researchers with new molecular methods and tools for high throughput patient screening using the SRM assays.
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