| 1. |
- Lu, Yingchang, et al.
(author)
-
New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk
- 2016
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
-
Journal article (peer-reviewed)abstract
- To increase our understanding of the genetic basis of adiposity and its links to cardiometabolic disease risk, we conducted a genome-wide association meta-analysis of body fat percentage (BF%) in up to 100,716 individuals. Twelve loci reached genome-wide significance (P<5 × 10(-8)), of which eight were previously associated with increased overall adiposity (BMI, BF%) and four (in or near COBLL1/GRB14, IGF2BP1, PLA2G6, CRTC1) were novel associations with BF%. Seven loci showed a larger effect on BF% than on BMI, suggestive of a primary association with adiposity, while five loci showed larger effects on BMI than on BF%, suggesting association with both fat and lean mass. In particular, the loci more strongly associated with BF% showed distinct cross-phenotype association signatures with a range of cardiometabolic traits revealing new insights in the link between adiposity and disease risk.
|
|
| 2. |
- Carlström, Karl E., et al.
(author)
-
Therapeutic efficacy of dimethyl fumarate in relapsing-remitting multiple sclerosis associates with ROS pathway in monocytes
- 2019
-
In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 10:1, s. 1-13
-
Journal article (peer-reviewed)abstract
- Dimethyl fumarate (DMF) is a first-line-treatment for relapsing-remitting multiple sclerosis (RRMS). The redox master regulator Nrf2, essential for redox balance, is a target of DMF, but its precise therapeutic mechanisms of action remain elusive. Here we show impact of DMF on circulating monocytes and T cells in a prospective longitudinal RRMS patient cohort. DMF increases the level of oxidized isoprostanes in peripheral blood. Other observed changes, including methylome and transcriptome profiles, occur in monocytes prior to T cells. Importantly, monocyte counts and monocytic ROS increase following DMF and distinguish patients with beneficial treatment-response from non-responders. A single nucleotide polymorphism in the ROS-generating NOX3 gene is associated with beneficial DMF treatment-response. Our data implicate monocyte-derived oxidative processes in autoimmune diseases and their treatment, and identify NOX3 genetic variant, monocyte counts and redox state as parameters potentially useful to inform clinical decisions on DMF therapy of RRMS.
|
|
| 3. |
- Das, Jyotirmoy, et al.
(author)
-
Identification of DNA methylation patterns predisposing for an efficient response to BCG vaccination in healthy BCG-naive subjects
- 2019
-
In: Epigenetics. - : TAYLOR & FRANCIS INC. - 1559-2294 .- 1559-2308. ; 14:6, s. 589-601
-
Journal article (peer-reviewed)abstract
- The protection against tuberculosis induced by the Bacille Calmette Guerin (BCG) vaccine is unpredictable. In our previous study, altered DNA methylation pattern in peripheral blood mononuclear cells (PBMCs) in response to BCG was observed in a subgroup of individuals, whose macrophages killed mycobacteria effectively (responders). These macrophages also showed production of Interleukin-1 beta (IL-1 beta) in response to mycobacterial stimuli before vaccination. Here, we hypothesized that the propensity to respond to the BCG vaccine is reflected in the DNA methylome. We mapped the differentially methylated genes (DMGs) in PBMCs isolated from responders/non-responders at the time point before vaccination aiming to identify possible predictors of BCG responsiveness. We identified 43 DMGs and subsequent bioinformatic analyses showed that these were enriched for actin-modulating pathways, predicting differences in phagocytosis. This could be validated by experiments showing that phagocytosis of mycobacteria, which is an event preceding mycobacteria-induced IL-1 beta production, was strongly correlated with the DMG pattern.
|
|
| 4. |
|
|
| 5. |
- Gawel, Danuta, et al.
(author)
-
A validated single-cell-based strategy to identify diagnostic and therapeutic targets in complex diseases
- 2019
-
In: Genome Medicine. - : Springer Science and Business Media LLC. - 1756-994X. ; 11
-
Journal article (peer-reviewed)abstract
- Background: Genomic medicine has paved the way for identifying biomarkers and therapeutically actionable targets for complex diseases, but is complicated by the involvement of thousands of variably expressed genes across multiple cell types. Single-cell RNA-sequencing study (scRNA-seq) allows the characterization of such complex changes in whole organs. Methods: The study is based on applying network tools to organize and analyze scRNA-seq data from a mouse model of arthritis and human rheumatoid arthritis, in order to find diagnostic biomarkers and therapeutic targets. Diagnostic validation studies were performed using expression profiling data and potential protein biomarkers from prospective clinical studies of 13 diseases. A candidate drug was examined by a treatment study of a mouse model of arthritis, using phenotypic, immunohistochemical, and cellular analyses as read-outs. Results: We performed the first systematic analysis of pathways, potential biomarkers, and drug targets in scRNA-seq data from a complex disease, starting with inflamed joints and lymph nodes from a mouse model of arthritis. We found the involvement of hundreds of pathways, biomarkers, and drug targets that differed greatly between cell types. Analyses of scRNA-seq and GWAS data from human rheumatoid arthritis (RA) supported a similar dispersion of pathogenic mechanisms in different cell types. Thus, systems-level approaches to prioritize biomarkers and drugs are needed. Here, we present a prioritization strategy that is based on constructing network models of disease-associated cell types and interactions using scRNA-seq data from our mouse model of arthritis, as well as human RA, which we term multicellular disease models (MCDMs). We find that the network centrality of MCDM cell types correlates with the enrichment of genes harboring genetic variants associated with RA and thus could potentially be used to prioritize cell types and genes for diagnostics and therapeutics. We validated this hypothesis in a large-scale study of patients with 13 different autoimmune, allergic, infectious, malignant, endocrine, metabolic, and cardiovascular diseases, as well as a therapeutic study of the mouse arthritis model. Conclusions: Overall, our results support that our strategy has the potential to help prioritize diagnostic and therapeutic targets in human disease.
|
|
| 6. |
- Gawel, Danuta R., 1988-
(author)
-
Identification of genes and regulators that are shared across T cell associated diseases
- 2018
-
Doctoral thesis (other academic/artistic)abstract
- Genome-wide association studies (GWASs) of hundreds of diseases and millions of patients have led to the identification of genes that are associated with more than one disease. The aims of this PhD thesis were to a) identify a group of genes important in multiple diseases (shared disease genes), b) identify shared up-stream disease regulators, and c) determine how the same genes can be involved in the pathogenesis of different diseases. These aims have been tested on CD4+ T cells because they express the T helper cell differentiation pathway, which was the most enriched pathway in analyses of all disease associated genes identified with GWASs.Combining information about known gene-gene interactions from the protein-protein interaction (PPI) network with gene expression changes in multiple T cell associated diseases led to the identification of a group of highly interconnected genes that were miss-expressed in many of those diseases – hereafter called ‘shared disease genes’. Those genes were further enriched for inflammatory, metabolic and proliferative pathways, genetic variants identified by all GWASs, as well as mutations in cancer studies and known diagnostic and therapeutic targets. Taken together, these findings supported the relevance of the shared disease genes.Identification of the shared upstream disease regulators was addressed in the second project of this PhD thesis. The underlying hypothesis assumed that the determination of the shared upstream disease regulators is possible through a network model showing in which order genes activate each other. For that reason a transcription factor–gene regulatory network (TF-GRN) was created. The TF-GRN was based on the time-series gene expression profiling of the T helper cell type 1 (Th1), and T helper cell type 2 (Th2) differentiation from Native T-cells. Transcription factors (TFs) whose expression changed early during polarization and had many downstream predicted targets (hubs) that were enriched for disease associated single nucleotide polymorphisms (SNPs) were prioritised as the putative early disease regulators. These analyses identified three transcription factors: GATA3, MAF and MYB. Their predicted targets were validated by ChIP-Seq and siRNA mediated knockdown in primary human T-cells. CD4+ T cells isolated from seasonal allergic rhinitis (SAR) and multiple sclerosis (MS) patients in their non-symptomatic stages were analysed in order to demonstrate predictive potential of those three TFs. We found that those three TFs were differentially expressed in symptom-free stages of the two diseases, while their TF-GRN{predicted targets were differentially expressed during symptomatic disease stages. Moreover, using RNA-Seq data we identified a disease associated SNP that correlated with differential splicing of GATA3.A limitation of the above study is that it concentrated on TFs as main regulators in cells, excluding other potential regulators such as microRNAs. To this end, a microRNA{gene regulatory network (mGRN) of human CD4+ T cell differentiation was constructed. Within this network, we defined regulatory clusters (groups of microRNAs that are regulating groups of mRNAs). One regulatory cluster was differentially expressed in all of the tested diseases, and was highly enriched for GWAS SNPs. Although the microRNA processing machinery was dynamically upregulated during early T-cell activation, the majority of microRNA modules showed specialisation in later time-points.In summary this PhD thesis shows the relevance of shared genes and up-stream disease regulators. Putative mechanisms of why shared genes can be involved in pathogenesis of different diseases have also been demonstrated: a) differential gene expression in different diseases; b) alternative transcription factor splicing variants may affect different downstream gene target group; and c) SNPs might cause alternative splicing.
|
|
| 7. |
- Gustafsson, Mika, et al.
(author)
-
A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases
- 2015
-
In: Science Translational Medicine. - : AMER ASSOC ADVANCEMENT SCIENCE. - 1946-6234 .- 1946-6242. ; 7:313
-
Journal article (peer-reviewed)abstract
- Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development.
|
|
| 8. |
- Hellberg, Sandra, et al.
(author)
-
Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis
- 2016
-
In: Cell Reports. - : Cell Press. - 2211-1247. ; 16:11, s. 2928-2939
-
Journal article (peer-reviewed)abstract
- Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS and has a varying disease course as well as variable response to treatment. Biomarkers may therefore aid personalized treatment. We tested whether in vitro activation of MS patient-derived CD4+ T cells could reveal potential biomarkers. The dynamic gene expression response to activation was dysregulated in patient-derived CD4+ T cells. By integrating our findings with genome-wide association studies, we constructed a highly connected MS gene module, disclosing cell activation and chemotaxis as central components. Changes in several module genes were associated with differences in protein levels, which were measurable in cerebrospinal fluid and were used to classify patients from control individuals. In addition, these measurements could predict disease activity after 2 years and distinguish low and high responders to treatment in two additional, independent cohorts. While further validation is needed in larger cohorts prior to clinical implementation, we have uncovered a set of potentially promising biomarkers.
|
|
| 9. |
- Kilpeläinen, Tuomas O, et al.
(author)
-
Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels
- 2016
-
In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 7
-
Journal article (peer-reviewed)abstract
- Leptin is an adipocyte-secreted hormone, the circulating levels of which correlate closely with overall adiposity. Although rare mutations in the leptin (LEP) gene are well known to cause leptin deficiency and severe obesity, no common loci regulating circulating leptin levels have been uncovered. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching P<10(-6) in 19,979 additional individuals. We identify five loci robustly associated (P<5 × 10(-8)) with leptin levels in/near LEP, SLC32A1, GCKR, CCNL1 and FTO. Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown experiments in mouse adipose tissue explants show convincing evidence for adipogenin, a regulator of adipocyte differentiation, as the novel causal gene in the SLC32A1 locus influencing leptin levels. Our findings provide novel insights into the regulation of leptin production by adipose tissue and open new avenues for examining the influence of variation in leptin levels on adiposity and metabolic health.
|
|
| 10. |
- Koivula, Lauri, et al.
(author)
-
Intensity-based dual model method for generation of synthetic CT images from standard T2-weighted MR images - Generalized technique for four different MR scanners
- 2017
-
In: Radiotherapy and Oncology. - : Elsevier BV. - 0167-8140. ; 125:3, s. 411-419
-
Journal article (peer-reviewed)abstract
- Background and purpose: Recent studies have shown that it is possible to conduct entire radiotherapy treatment planning (RTP) workflow using only MR images. This study aims to develop a generalized intensity-based method to generate synthetic CT (sCT) images from standard T2-weighted (T2w) MR images of the pelvis. Materials and methods: This study developed a generalized dual model HU conversion method to convert standard T2w MR image intensity values to synthetic HU values, separately inside and outside of atlas-segmented bone volume contour. The method was developed and evaluated with 20 and 35 prostate cancer patients, respectively. MR images with scanning sequences in clinical use were acquired with four different MR scanners of three vendors. Results: For the generated synthetic CT (sCT) images of the 35 prostate patients, the mean (and maximal) HU differences in soft and bony tissue volumes were 16±6HUs (34HUs) and -46±56HUs (181HUs), respectively, against the true CT images. The average of the PTV mean dose difference in sCTs compared to those in true CTs was -0.6±0.4% (-1.3%). Conclusions: The study provides a generalized method for sCT creation from standard T2w images of the pelvis. The method produced clinically acceptable dose calculation results for all the included scanners and MR sequences.
|
|
