| 1. |
- Autio, Reija, et al.
(author)
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A method for finding putative causes of gene expression variation
- 2004
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In: 2nd TICSP Workshop on Computational Systems Biology, WCSB 2004 : Silja Opera, Helsinki-St. Petersburg, June 14 - 16, 2004 - Silja Opera, Helsinki-St. Petersburg, June 14 - 16, 2004. - 1456-2774. - 9521512040 ; 24, s. 29-30
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Conference paper (other academic/artistic)abstract
- The majority of microarray studies evaluate gene ex- pression differences between various specimens or con- ditions. However, the causes of this variability often re- main unknown. Our aim is to identify underlying causes of these patterns, a process that would eventually enable a mechanistic understanding of the deregulation of gene expression in cancer. The procedure consists of three phases: pre-processing, data integration and statistical analysis. We have applied the strategy to identify genes that are overexpressed due to amplification in breast cancer. The data were obtained from 14 breast cancer cell lines, which were subjected to cDNA microarray based copy number and expression experiments. The re- sult of the analysis was a list that consisted of 92 genes. This set includes several genes that are known to be both overexpressed and amplified in breast cancer. The com- plete study was published in Journal of the Franklin In- stitute 2004, and in this paper we focus on the main issues of the study.
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| 2. |
- Elo, Laura L., et al.
(author)
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Genome-wide profiling of interleukin-4 and STAT6 transcription factor regulation of human Th2 cell programming
- 2010
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In: Immunity. - : Cell Press. - 1074-7613 .- 1097-4180. ; 32:6, s. 852-862
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Journal article (peer-reviewed)abstract
- Dissecting the molecular mechanisms by which T helper (Th) cells differentiate to effector Th2 cells is important for understanding the pathogenesis of immune-mediated diseases, such as asthma and allergy. Because the STAT6 transcription factor is an upstream mediator required for interleukin-4 (IL-4)-induced Th2 cell differentiation, its targets include genes important for this process. Using primary human CD4(+) T cells, and by blocking STAT6 with RNAi, we identified a number of direct and indirect targets of STAT6 with ChIP sequencing. The integration of these data sets with detailed kinetics of IL-4-driven transcriptional changes showed that STAT6 was predominantly needed for the activation of transcription leading to the Th2 cell phenotype. This integrated genome-wide data on IL-4- and STAT6-mediated transcription provide a unique resource for studies on Th cell differentiation and, in particular, for designing interventions of human Th2 cell responses.
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| 3. |
- Hirvonen, M Karoliina, et al.
(author)
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Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes
- 2023
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In: Scientific Reports. - : Nature Publishing Group. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.
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| 4. |
- Huuhtanen, Jani, et al.
(author)
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Single-cell analysis of immune recognition in chronic myeloid leukemia patients following tyrosine kinase inhibitor discontinuation
- 2024
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In: Leukemia. - : Springer Nature. - 0887-6924 .- 1476-5551. ; 38, s. 109-125
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Journal article (peer-reviewed)abstract
- Immunological control of residual leukemia cells is thought to occur in patients with chronic myeloid leukemia (CML) that maintain treatment-free remission (TFR) following tyrosine kinase inhibitor (TKI) discontinuation. To study this, we analyzed 55 single-cell RNA and T cell receptor (TCR) sequenced samples (scRNA+TCRαβ-seq) from patients with CML (n = 13, N = 25), other cancers (n = 28), and healthy (n = 7). The high number and active phenotype of natural killer (NK) cells in CML separated them from healthy and other cancers. Most NK cells in CML belonged to the active CD56dim cluster with high expression of GZMA/B, PRF1, CCL3/4, and IFNG, with interactions with leukemic cells via inhibitory LGALS9-TIM3 and PVR-TIGIT interactions. Accordingly, upregulation of LGALS9 was observed in CML target cells and TIM3 in NK cells when co-cultured together. Additionally, we created a classifier to identify TCRs targeting leukemia-associated antigen PR1 and quantified anti-PR1 T cells in 90 CML and 786 healthy TCRβ-sequenced samples. Anti-PR1 T cells were more prevalent in CML, enriched in bone marrow samples, and enriched in the mature, cytotoxic CD8+TEMRA cluster, especially in a patient maintaining TFR. Our results highlight the role of NK cells and anti-PR1 T cells in anti-leukemic immune responses in CML.
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| 5. |
- Kallionpää, Henna, et al.
(author)
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Early Detection of Peripheral Blood Cell Signature in Children Developing beta-Cell Autoimmunity at a Young Age
- 2019
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In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 68:10, s. 2024-2034
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Journal article (peer-reviewed)abstract
- The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding autoantibody positivity or reflect progressive beta-cell destruction. Here we report the mRNA sequencing-based analysis of 306 samples including fractionated samples of CD4(+) and CD8(+) T cells as well as CD4(-)CD8(-) cell fractions and unfractionated peripheral blood mononuclear cell samples longitudinally collected from seven children who developed beta-cell autoimmunity (case subjects) at a young age and matched control subjects. We identified transcripts, including interleukin 32 (IL32), that were upregulated before T1D-associated autoantibodies appeared. Single-cell RNA sequencing studies revealed that high IL32 in case samples was contributed mainly by activated T cells and NK cells. Further, we showed that IL32 expression can be induced by a virus and cytokines in pancreatic islets and beta-cells, respectively. The results provide a basis for early detection of aberrations in the immune system function before T1D and suggest a potential role for IL32 in the pathogenesis of T1D.
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| 6. |
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| 7. |
- Konki, Mikko, et al.
(author)
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Peripheral blood DNA methylation differences in twin pairs discordant for Alzheimer's disease.
- 2019
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In: Clinical Epigenetics. - : BioMed Central. - 1868-7083 .- 1868-7075. ; 11:1
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Journal article (peer-reviewed)abstract
- BACKGROUND: Alzheimer's disease results from a neurodegenerative process that starts well before the diagnosis can be made. New prognostic or diagnostic markers enabling early intervention into the disease process would be highly valuable. Environmental and lifestyle factors largely modulate the disease risk and may influence the pathogenesis through epigenetic mechanisms, such as DNA methylation. As environmental and lifestyle factors may affect multiple tissues of the body, we hypothesized that the disease-associated DNA methylation signatures are detectable in the peripheral blood of discordant twin pairs.RESULTS: Comparison of 23 disease discordant Finnish twin pairs with reduced representation bisulfite sequencing revealed peripheral blood DNA methylation differences in 11 genomic regions with at least 15.0% median methylation difference and FDR adjusted p value ≤ 0.05. Several of the affected genes are primarily associated with neuronal functions and pathologies and do not display disease-associated differences in gene expression in blood. The DNA methylation mark in ADARB2 gene was found to be differentially methylated also in the anterior hippocampus, including entorhinal cortex, of non-twin cases and controls. Targeted bisulfite pyrosequencing of the DNA methylation mark in ADARB2 gene in 62 Finnish and Swedish twin pairs revealed that, in addition to the disease status, DNA methylation of this region is influenced by gender, age, zygosity, APOE genotype, and smoking. Further analysis of 120 Swedish twin pairs indicated that this specific DNA methylation mark is not predictive for Alzheimer's disease and becomes differentially methylated after disease onset.CONCLUSIONS: DNA methylation differences can be detected in the peripheral blood of twin pairs discordant for Alzheimer's disease. These DNA methylation signatures may have value as disease markers and provide insights into the molecular mechanisms of pathogenesis. We found no evidence that the DNA methylation marks would be associated with gene expression in blood. Further studies are needed to elucidate the potential importance of the associated genes in neuronal functions and to validate the prognostic or diagnostic value of the individual marks or marker panels.
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| 8. |
- Kostic, Aleksandar D., et al.
(author)
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The dynamics of the human infant gut microbiome in development and in progression toward type 1 diabetes
- 2015
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In: Cell Host and Microbe. - : Cell Press. - 1931-3128 .- 1934-6069. ; 17:2, s. 260-273
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Journal article (peer-reviewed)abstract
- Colonization of the fetal and infant gut microbiome results in dynamic changes in diversity, which can impact disease susceptibility. To examine the relationship between human gut microbiome dynamics throughout infancy and type 1 diabetes (T1D), we examined a cohort of 33 infants genetically predisposed to T1D. Modeling trajectories of microbial abundances through infancy revealed a subset of microbial relationships shared across most subjects. Although strain composition of a given species was highly variable between individuals, it was stable within individuals throughout infancy. Metabolic composition and metabolic pathway abundance remained constant across time. A marked drop in alpha-diversity was observed in T1D progressors in the time window between seroconversion and T1D diagnosis, accompanied by spikes in inflammation-favoring organisms, gene functions, and serum and stool metabolites. This work identifies trends in the development of the human infant gut microbiome along with specific alterations that precede T1D onset and distinguish T1D progressors from nonprogressors.
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| 9. |
- Laajala, Essi, et al.
(author)
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Permutation-based significance analysis reduces the type 1 error rate in bisulfite sequencing data analysis of human umbilical cord blood samples
- 2022
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In: Epigenetics. - : Taylor & Francis. - 1559-2294 .- 1559-2308. ; 17:12, s. 1608-1627
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Journal article (peer-reviewed)abstract
- DNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2% of human CpG sites. To detect such associations outside these regions, we chose the bisulphite sequencing approach. We collected and curated clinical data on 200 newborn infants; whose umbilical cord blood samples were analysed with the reduced representation bisulphite sequencing (RRBS) method. A generalized linear mixed-effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables, such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis. We discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. The inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models.
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| 10. |
- Laajala, Essi, et al.
(author)
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Umbilical cord blood DNA methylation in children who later develop type 1 diabetes
- 2021
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In: European Journal of Immunology. - : John Wiley & Sons. - 0014-2980 .- 1521-4141. ; 51:Suppl. 1, s. 291-291
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Journal article (other academic/artistic)abstract
- Distinct DNA methylation patterns have recently been observed to precede Type 1 Diabetes in whole blood collected from young children. Our aim was to determine if such methylation patterns are present already at the time of birth. Reduced representation bisulfite sequencing (RRBS) analysis was performed on a unique collection of umbilical cord blood samples collected within the Type 1 Diabetes Prediction and Prevention (DIPP) study. Children later diagnosed with Type 1 Diabetes and/or testing positive for multiple islet autoantibodies (N=43) were compared to control individuals (N=79), who remained autoantibody‐negative throughout the DIPP follow‐up until 15 years of age. Altogether 24 clinical and technical covariates related to the pregnancy and the mother were included in a binomial mixed effects model, which was fit separately for each high‐coverage CpG site, followed by spatial and multiple testing adjustment of P values. We discovered a strong inflation of P values, which was caused by a standard spatial adjustment method. Findings that were based on Benjamini‐Hochberg corrected spatially adjusted P values, could not be validated by Pyrosequencing. We therefore used permutation‐based significance analysis and showed that sex‐associated differentially methylated cytosines could be reproducibly detected with this approach. After empirical type 1 error control, no differences in cord blood methylation patterns were observed between cases and controls. Differences between children who progress to Type 1 Diabetes and those who remain healthy throughout childhood, are not yet present in the perinatal DNA methylome.
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| 11. |
- Laajala, Essi, et al.
(author)
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Umbilical cord blood DNA methylation in children who later develop type 1 diabetes
- 2022
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In: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 65:9, s. 1534-1540
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Journal article (peer-reviewed)abstract
- AIMS/HYPOTHESIS: Distinct DNA methylation patterns have recently been observed to precede type 1 diabetes in whole blood collected from young children. Our aim was to determine whether perinatal DNA methylation is associated with later progression to type 1 diabetes.METHODS: Reduced representation bisulphite sequencing (RRBS) analysis was performed on umbilical cord blood samples collected within the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study. Children later diagnosed with type 1 diabetes and/or who tested positive for multiple islet autoantibodies (n = 43) were compared with control individuals (n = 79) who remained autoantibody-negative throughout the DIPP follow-up until 15 years of age. Potential confounding factors related to the pregnancy and the mother were included in the analysis.RESULTS: No differences in the umbilical cord blood methylation patterns were observed between the cases and controls at a false discovery rate <0.05.CONCLUSIONS/INTERPRETATION: Based on our results, differences between children who progress to type 1 diabetes and those who remain healthy throughout childhood are not yet present in the perinatal DNA methylome. However, we cannot exclude the possibility that such differences would be found in a larger dataset.
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| 12. |
- Liu, Dong, 1989-
(author)
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Perspectives on Probabilistic Graphical Models
- 2020
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Doctoral thesis (other academic/artistic)abstract
- Probabilistic graphical models provide a natural framework for the representation of complex systems and offer straightforward abstraction for the interactions within the systems. Reasoning with help of probabilistic graphical models allows us to answer inference queries with uncertainty following the framework of probability theory. General inference tasks can be to compute marginal probabilities, conditional probabilities of states of a system, or the partition function of the underlining distribution of a Markov random field (undirected graphical model). Critically, the success of graphical models in practice largely relies on efficient approximate inference methods that offer fast and accurate reasoning results. Closely related to the inference tasks in graphical models, another fundamental problem is how to decide the parameters of a candidate graphical model by extracting information from empirical observations, i.e., parameter learning for a graphical model. The two essential topics (inference and learning) interact with and facilitate each other. For instance, the learning of a graphical model usually uses an inference method as a subroutine, while the learned graphical model is then employed for inference tasks in the presence of new evidence.In this dissertation, we develop new algorithms and models for generic inference in Markov random fields. We firstly present an alternative view of belief propagation in terms of a divergence minimization, which is in contrast to the intuition of free energy minimization. The alternative view brings the development of a variant of belief propagation algorithm which turns out to generalize the standard one. Insights on the convergence behavior of the developed algorithm in the binary state space are provided apart from the intuition in development. As a step beyond approximate inference with message passing, we develop a region-based energy network model that performs generic inference via region-based free energy minimization, which turns inference in Markov random fields into an optimization problem. This model incorporates both our essential understanding of inference and modern neural network models with computational efficiency.The further part of the dissertation focuses on parameter learning for probabilistic graphical models. This part starts with the discussion on parameter learning of undirected graphical models and explains the role of an (approximate) inference method in this routine. As for directed graphical models, new finite mixture models incorporating normalizing flows in neural network implementations are presented for more expressive and flexible modeling. The learning of developed generic models is handled within expectation maximization due to the presence of hidden (or latent) variables. The expressive modeling method and learning are further extended to dynamic systems within a reduced dynamic Bayesian network, i.e., a hidden Markov model. The dissertation closes with a chapter on the likelihood-free learning for a class of directed graphical models, where (directed) generative models induce implicit probability distributions and are learned via the optimal transport distance.
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| 13. |
- Vatanen, Tommi, et al.
(author)
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The human gut microbiome in early-onset type 1 diabetes from the TEDDY study
- 2018
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In: Nature. - : Springer Science and Business Media LLC. - 0028-0836 .- 1476-4687. ; 562:7728, s. 589-594
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Journal article (peer-reviewed)abstract
- Type 1 diabetes (T1D) is an autoimmune disease that targets pancreatic islet beta cells and incorporates genetic and environmental factors1, including complex genetic elements2, patient exposures3 and the gut microbiome4. Viral infections5 and broader gut dysbioses6 have been identified as potential causes or contributing factors; however, human studies have not yet identified microbial compositional or functional triggers that are predictive of islet autoimmunity or T1D. Here we analyse 10,913 metagenomes in stool samples from 783 mostly white, non-Hispanic children. The samples were collected monthly from three months of age until the clinical end point (islet autoimmunity or T1D) in the The Environmental Determinants of Diabetes in the Young (TEDDY) study, to characterize the natural history of the early gut microbiome in connection to islet autoimmunity, T1D diagnosis, and other common early life events such as antibiotic treatments and probiotics. The microbiomes of control children contained more genes that were related to fermentation and the biosynthesis of short-chain fatty acids, but these were not consistently associated with particular taxa across geographically diverse clinical centres, suggesting that microbial factors associated with T1D are taxonomically diffuse but functionally more coherent. When we investigated the broader establishment and development of the infant microbiome, both taxonomic and functional profiles were dynamic and highly individualized, and dominated in the first year of life by one of three largely exclusive Bifidobacterium species (B. bifidum, B. breve or B. longum) or by the phylum Proteobacteria. In particular, the strain-specific carriage of genes for the utilization of human milk oligosaccharide within a subset of B. longum was present specifically in breast-fed infants. These analyses of TEDDY gut metagenomes provide, to our knowledge, the largest and most detailed longitudinal functional profile of the developing gut microbiome in relation to islet autoimmunity, T1D and other early childhood events. Together with existing evidence from human cohorts7,8 and a T1D mouse model9, these data support the protective effects of short-chain fatty acids in early-onset human T1D.
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