| 1. |
- Altmae, Signe, et al.
(författare)
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Interactome of Human Embryo Implantation : Identification of Gene Expression Pathways, Regulation, and Integrated Regulatory Networks
- 2012
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Ingår i: Molecular Endocrinology. - : The Endocrine Society. - 0888-8809 .- 1944-9917. ; 26:1, s. 203-217
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Tidskriftsartikel (refereegranskat)abstract
- A prerequisite for successful embryo implantation is adequate preparation of receptive endometrium and the establishment and maintenance of a viable embryo. The success of implantation further relies upon a two-way dialogue between the embryo and uterus. However, molecular bases of these preimplantation and implantation processes in humans are not well known. We performed genome expression analyses of humanembryos (n = 128) andhumanendometria (n = 8). We integrated these data with protein-protein interactions in order to identify molecular networks within the endometrium and the embryo, and potential embryo-endometrium interactions at the time of implantation. For that, we applied a novel network profiling algorithm HyperModules, which combines topological module identification and functional enrichment analysis. We found a major wave of transcriptional down-regulation in preimplantation embryos. In receptive-stage endometrium, several genes and signaling pathways were identified, including JAK-STAT signaling and inflammatory pathways. The main curated embryo-endometrium interaction network highlighted the importance of cell adhesion molecules in the implantation process. We also identified cytokine-cytokine receptor interactions involved in implantation, where osteopontin (SPP1), leukemia inhibitory factor (LIF) and leptin (LEP) pathways were intertwining. Further, we identified a number of novel players in human embryo-endometrium interactions, such as apolipoprotein D (APOD), endothelin 1 (END1), fibroblast growth factor 7 (FGF7), gastrin (GAST), kringle containing trnasmembrane protein 1 (KREMEN1), neuropilin 1 (NRP1), serpin peptidase inhibitor clade A member 3 (SERPINA3), versican (VCAN), and others. Our findings provide a fundamental resource for better understanding of the genetic network that leads to successful embryo implantation. We demonstrate the first systems biology approach into the complex molecular network of the implantation process in humans.
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| 2. |
- Lokk, Kaie, et al.
(författare)
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DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns
- 2014
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Ingår i: Genome Biology. - : BioMed Central. - 1465-6906 .- 1474-760X. ; 15:4, s. r54-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: DNA epigenetic modifications, such as methylation, are important regulators of tissue differentiation, contributing to processes of both development and cancer. Profiling the tissue-specific DNA methylome patterns will provide novel insights into normal and pathogenic mechanisms, as well as help in future epigenetic therapies. In this study, 17 somatic tissues from four autopsied humans were subjected to functional genome analysis using the Illumina Infinium HumanMethylation450 BeadChip, covering 486 428 CpG sites. RESULTS: Only 2% of the CpGs analyzed are hypermethylated in all 17 tissue specimens; these permanently methylated CpG sites are located predominantly in gene-body regions. In contrast, 15% of the CpGs are hypomethylated in all specimens and are primarily located in regions proximal to transcription start sites. A vast number of tissue-specific differentially methylated regions are identified and considered likely mediators of tissue-specific gene regulatory mechanisms since the hypomethylated regions are closely related to known functions of the corresponding tissue. Finally, a clear inverse correlation is observed between promoter methylation within CpG islands and gene expression data obtained from publicly available databases. CONCLUSIONS: This genome-wide methylation profiling study identified tissue-specific differentially methylated regions in 17 human somatic tissues. Many of the genes corresponding to these differentially methylated regions contribute to tissue-specific functions. Future studies may use these data as a reference to identify markers of perturbed differentiation and disease-related pathogenic mechanisms.
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| 3. |
- Möller, Steffen, et al.
(författare)
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Healthspan pathway maps in C. elegans and humans highlight transcription, proliferation/biosynthesis and lipids
- 2020
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Ingår i: Aging. - : Impact Journals LLC. - 1945-4589 .- 1945-4589. ; 12:13, s. 12534-12581
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Forskningsöversikt (refereegranskat)abstract
- The molecular basis of aging and of aging-associated diseases is being unraveled at an increasing pace. An extended healthspan, and not merely an extension of lifespan, has become the aim of medical practice. Here, we define health based on the absence of diseases and dysfunctions. Based on an extensive review of the literature, in particular for humans and C. elegans, we compile a list of features of health and of the genes associated with them. These genes may or may not be associated with survival/lifespan. In turn, survival/lifespan genes that are not known to be directly associated with health are not considered. Clusters of these genes based on molecular interaction data give rise to maps of healthspan pathways for humans and for C. elegans. Overlaying healthspan-related gene expression data onto the healthspan pathway maps, we observe the downregulation of (pro-inflammatory) Notch signaling in humans and of proliferation in C. elegans. We identify transcription, proliferation/biosynthesis and lipids as a common theme on the annotation level, and proliferation-related kinases on the gene/protein level. Our literature-based data corpus, including visualization, should be seen as a pilot investigation of the molecular underpinnings of health in two different species.
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| 4. |
- Reisberg, Sulev, et al.
(författare)
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Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations : challenges and solutions
- 2019
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Ingår i: Genetics in Medicine. - : NATURE PUBLISHING GROUP. - 1098-3600 .- 1530-0366. ; 21:6, s. 1345-1354
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. Methods: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. Results: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. Conclusion: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.
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| 5. |
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| 6. |
- Segal, Eran, et al.
(författare)
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Building an international consortium for tracking coronavirus health status
- 2020
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Ingår i: Nature Medicine. - : Springer Science and Business Media LLC. - 1078-8956 .- 1546-170X. ; 26:8, s. 1161-1165
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- We call upon the research community to standardize efforts to use daily self-reported data about COVID-19 symptoms in the response to the pandemic and to form a collaborative consortium to maximize global gain while protecting participant privacy.
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| 7. |
- Tasa, Tonis, et al.
(författare)
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Genetic variation in the Estonian population : pharmacogenomics study of adverse drug effects using electronic health records
- 2019
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Ingår i: European Journal of Human Genetics. - : NATURE PUBLISHING GROUP. - 1018-4813 .- 1476-5438. ; 27:3, s. 442-454
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Tidskriftsartikel (refereegranskat)abstract
- Pharmacogenomics aims to tailor pharmacological treatment to each individual by considering associations between genetic polymorphisms and adverse drug effects (ADEs). With technological advances, pharmacogenomic research has evolved from candidate gene analyses to genome-wide association studies. Here, we integrate deep whole-genome sequencing (WGS) information with drug prescription and ADE data from Estonian electronic health record (EHR) databases to evaluate genome- and pharmacome-wide associations on an unprecedented scale. We leveraged WGS data of 2240 Estonian Biobank participants and imputed all single-nucleotide variants (SNVs) with allele counts over 2 for 13,986 genotyped participants. Overall, we identified 41 (10 novel) loss-of-function and 567 (134 novel) missense variants in 64 very important pharmacogenes. The majority of the detected variants were very rare with frequencies below 0.05%, and 6 of the novel lossof-function and 99 of the missense variants were only detected as single alleles (allele count = 1). We also validated documented pharmacogenetic associations and detected new independent variants in known gene-drug pairs. Specifically, we found that CTNNA3 was associated with myositis and myopathies among individuals taking nonsteroidal anti-inflammatory oxicams and replicated this finding in an extended cohort of 706 individuals. These findings illustrate that population-based WGS-coupled EHRs are a useful tool for biomarker discovery.
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| 8. |
- Torabi Moghadam, Behrooz
(författare)
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Computational discovery of DNA methylation patterns as biomarkers of ageing, cancer, and mental disorders : Algorithms and Tools
- 2017
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Epigenetics refers to the mitotically heritable modifications in gene expression without a change in the genetic code. A combination of molecular, chemical and environmental factors constituting the epigenome is involved, together with the genome, in setting up the unique functionality of each cell type.DNA methylation is the most studied epigenetic mark in mammals, where a methyl group is added to the cytosine in a cytosine-phosphate-guanine dinucleotides or a CpG site. It has been shown to have a major role in various biological phenomena such as chromosome X inactivation, regulation of gene expression, cell differentiation, genomic imprinting. Furthermore, aberrant patterns of DNA methylation have been observed in various diseases including cancer.In this thesis, we have utilized machine learning methods and developed new methods and tools to analyze DNA methylation patterns as a biomarker of ageing, cancer subtyping and mental disorders.In Paper I, we introduced a pipeline of Monte Carlo Feature Selection and rule-base modeling using ROSETTA in order to identify combinations of CpG sites that classify samples in different age intervals based on the DNA methylation levels. The combination of genes that showed up to be acting together, motivated us to develop an interactive pathway browser, named PiiL, to check the methylation status of multiple genes in a pathway. The tool enhances detecting differential patterns of DNA methylation and/or gene expression by quickly assessing large data sets.In Paper III, we developed a novel unsupervised clustering method, methylSaguaro, for analyzing various types of cancers, to detect cancer subtypes based on their DNA methylation patterns. Using this method we confirmed the previously reported findings that challenge the histological grouping of the patients, and proposed new subtypes based on DNA methylation patterns. In Paper IV, we investigated the DNA methylation patterns in a cohort of schizophrenic and healthy samples, using all the methods that were introduced and developed in the first three papers.
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