| 51. |
- Diamanti, Klev, 1987-, et al.
(author)
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Integration of whole-body PET/MRI with non-targeted metabolomics provides new insights into insulin sensitivity of various tissues
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Other publication (other academic/artistic)abstract
- Background: Alteration of various metabolites has been linked to type 2 diabetes (T2D) and insulin resistance. However, identifying significant associations between metabolites and tissue-specific alterations is challenging and requires a multi-omics approach. In this study, we aimed at discovering associations of metabolites from subcutaneous adipose tissue (SAT) and plasma with the volume, the fat fraction (FF) and the insulin sensitivity (Ki) of specific tissues using [18F]FDG PET/MRI.Materials and Methods: In a cohort of 42 subjects with different levels of glucose tolerance (normal, prediabetes and T2D) matched for age and body-mass-index (BMI) we calculated associations between parameters of whole-body FDG PET/MRI during clamp and non-targeted metabolomics profiling for SAT and blood plasma. We also used a rule-based classifier to identify a large collection of prevalent patterns of co-dependent metabolites that characterize non-diabetes (ND) and T2D.Results: The plasma metabolomics profiling revealed that hepatic fat content was positively associated with tyrosine, and negatively associated with lysoPC(P-16:0). Ki in visceral adipose tissue (VAT) and SAT, was positively associated with several species of lysophospholipids while the opposite applied to branched-chain amino acids (BCAA) and their intermediates. The adipose tissue metabolomics revealed a positive association between non-esterified fatty acids and, VAT and liver Ki. On the contrary, bile acids and carnitines in adipose tissue were inversely associated with VAT Ki. Finally, we presented a transparent machine-learning model that predicted ND or T2D in “unseen” data with an accuracy of 78%.Conclusions: Novel associations of several metabolites from SAT and plasma with the FF, volume and insulin senstivity of various tissues throughout the body were discovered using PET/MRI and a new integrative multi-omics approach. A promising computational model that predicted ND and T2D with high certainty, suggested novel non-linear interdependencies of metabolites.
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| 52. |
- Diamanti, Klev, et al.
(author)
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Intra- and inter-individual metabolic profiling highlights carnitine and lysophosphatidylcholine pathways as key molecular defects in type 2 diabetes
- 2019
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 9653-
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Journal article (peer-reviewed)abstract
- Type 2 diabetes (T2D) mellitus is a complex metabolic disease commonly caused by insulin resistance in several tissues. We performed a matched two-dimensional metabolic screening in tissue samples from 43 multi-organ donors. The intra-individual analysis was assessed across five key metabolic tissues (serum, visceral adipose tissue, liver, pancreatic islets and skeletal muscle), and the inter-individual across three different groups reflecting T2D progression. We identified 92 metabolites differing significantly between non-diabetes and T2D subjects. In diabetes cases, carnitines were significantly higher in liver, while lysophosphatidylcholines were significantly lower in muscle and serum. We tracked the primary tissue of origin for multiple metabolites whose alterations were reflected in serum. An investigation of three major stages spanning from controls, to pre-diabetes and to overt T2D indicated that a subset of lysophosphatidylcholines was significantly lower in the muscle of pre-diabetes subjects. Moreover, glycodeoxycholic acid was significantly higher in liver of pre-diabetes subjects while additional increase in T2D was insignificant. We confirmed many previously reported findings and substantially expanded on them with altered markers for early and overt T2D. Overall, the analysis of this unique dataset can increase the understanding of the metabolic interplay between organs in the development of T2D.
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| 53. |
- Diamanti, Klev, et al.
(author)
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Maps of context-dependent putative regulatory regions and genomic signal interactions
- 2016
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In: Nucleic Acids Research. - : Oxford University Press (OUP). - 0305-1048 .- 1362-4962. ; 44:19, s. 9110-9120
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Journal article (peer-reviewed)abstract
- Gene transcription is regulated mainly by transcription factors (TFs). ENCODE and Roadmap Epigenomics provide global binding profiles of TFs, which can be used to identify regulatory regions. To this end we implemented a method to systematically construct cell-type and species-specific maps of regulatory regions and TF-TF interactions. We illustrated the approach by developing maps for five human cell-lines and two other species. We detected similar to 144k putative regulatory regions among the human cell-lines, with the majority of them being similar to 300 bp. We found similar to 20k putative regulatory elements in the ENCODE heterochromatic domains suggesting a large regulatory potential in the regions presumed transcriptionally silent. Among the most significant TF interactions identified in the heterochromatic regions were CTCF and the cohesin complex, which is in agreement with previous reports. Finally, we investigated the enrichment of the obtained putative regulatory regions in the 3D chromatin domains. More than 90% of the regions were discovered in the 3D contacting domains. We found a significant enrichment of GWAS SNPs in the putative regulatory regions. These significant enrichments provide evidence that the regulatory regions play a crucial role in the genomic structural stability. Additionally, we generated maps of putative regulatory regions for prostate and colorectal cancer human cell-lines.
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| 54. |
- Diamanti, Klev, 1987-, et al.
(author)
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Organ-specific metabolic pathways distinguish prediabetes, type 2 diabetes, and normal tissues
- 2022
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In: Cell Reports Medicine. - : Elsevier BV. - 2666-3791. ; 3:10
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Journal article (peer-reviewed)abstract
- Environmental and genetic factors cause defects in pancreatic islets driving type 2 diabetes (T2D) together with the progression of multi-tissue insulin resistance. Mass spectrometry proteomics on samples from five key metabolic tissues of a cross-sectional cohort of 43 multi-organ donors provides deep coverage of their proteomes. Enrichment analysis of Gene Ontology terms provides a tissue-specific map of altered biological processes across healthy, prediabetes (PD), and T2D subjects. We find widespread alterations in several relevant biological pathways, including increase in hemostasis in pancreatic islets of PD, increase in the complement cascade in liver and pancreatic islets of PD, and elevation in cholesterol biosynthesis in liver of T2D. Our findings point to inflammatory, immune, and vascular alterations in pancreatic islets in PD that are hypotheses to be tested for potential contributions to hormonal perturbations such as impaired insulin and increased glucagon production. This multi-tissue proteomic map suggests tissue-specific metabolic dysregulations in T2D. © 2022 The Author(s)
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| 55. |
- Diamanti, Klev, 1987-, et al.
(author)
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Single nucleus transcriptomics data integration recapitulates the major cell types in human liver
- 2021
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In: Hepatology Research. - : Wiley. - 1386-6346 .- 1872-034X. ; 51:2, s. 233-238
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Journal article (peer-reviewed)abstract
- Hepatology Research published by John Wiley & Sons Australia, Ltd on behalf of Japan Society of Hepatology Aim: The aim of this study was to explore the benefits of data integration from different platforms for single nucleus transcriptomics profiling to characterize cell populations in human liver. Methods: We generated single-nucleus RNA sequencing data from Chromium 10X Genomics and Drop-seq for a human liver sample. We utilized state of the art bioinformatics tools to undertake a rigorous quality control and to integrate the data into a common space summarizing the gene expression variation from the respective platforms, while accounting for known and unknown confounding factors. Results: Analysis of single nuclei transcriptomes from both 10X and Drop-seq allowed identification of the major liver cell types, while the integrated set obtained enough statistical power to separate a small population of inactive hepatic stellate cells that was not characterized in either of the platforms. Conclusions: Integration of droplet-based single nucleus transcriptomics data enabled identification of a small cluster of inactive hepatic stellate cells that highlights the potential of our approach. We suggest single-nucleus RNA sequencing integrative approaches could be utilized to design larger and cost-effective studies.
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| 56. |
- Draminski, Michal, et al.
(author)
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Monte Carlo feature selection for supervised classification
- 2008
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In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 24:1, s. 110-117
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Journal article (peer-reviewed)abstract
- MOTIVATION: Pre-selection of informative features for supervised classification is a crucial, albeit delicate, task. It is desirable that feature selection provides the features that contribute most to the classification task per se and which should therefore be used by any classifier later used to produce classification rules. In this article, a conceptually simple but computer-intensive approach to this task is proposed. The reliability of the approach rests on multiple construction of a tree classifier for many training sets randomly chosen from the original sample set, where samples in each training set consist of only a fraction of all of the observed features. RESULTS: The resulting ranking of features may then be used to advantage for classification via a classifier of any type. The approach was validated using Golub et al. leukemia data and the Alizadeh et al. lymphoma data. Not surprisingly, we obtained a significantly different list of genes. Biological interpretation of the genes selected by our method showed that several of them are involved in precursors to different types of leukemia and lymphoma rather than being genes that are common to several forms of cancers, which is the case for the other methods.
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| 57. |
- Edman Ahlbom, Bodil, et al.
(author)
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Molecular analysis of chromosome 21 in a patient with a phenotype of down syndrome and apparently normal karyotype
- 1996
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In: American Journal of Medical Genetics. Part A. - 1552-4825 .- 1552-4833. ; 63:4, s. 566-572
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Journal article (peer-reviewed)abstract
- Down syndrome (DS) is caused in most cases by the presence of an extra chromosome 21. It has been shown that the DS phenotype is produced by duplication of only a small part of the long arm of chromosome 21, the 21q22 region, including and distal to locus D21S55. We present molecular investigations on a woman with clinically typical DS but apparently normal chromosomes. Her parents were consanguineous and she had a sister with a DS phenotype, who died at the age of 15 days. Repeated cytogenetic investigations (G-banding and high resolution banding) on the patient and her parents showed apparently normal chromosomes. Autoradiographs of quantitative Southern blots of DNAs from the patient, her parents, trisomy 21 patients, and normal controls were analyzed after hybridization with unique DNA sequences regionally mapped on chromosome 21. Sequences D21S59, D21S1, D21S11, D21S8, D21S17, D21S55, ERG, D21S15, D21S112, and COL6A1 were all found in two copies. Fluorescent in situ hybridization with a chromosome 21-specific genomic library showed no abnormalities and only two copies of chromosome 21 were detected. Nineteen markers from the critical region studied with polymerase chain reaction amplification of di- and tetranucleotide repeats did not indicate any partial trisomy 21. From this study we conclude that the patient does not have any partial submicroscopic trisomy for any segment of chromosome 21. It seems reasonable to assume that she suffers from an autosomal recessive disorder which is phenotypically indistinguishable from DS.
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| 58. |
- Enroth, Stefan, et al.
(author)
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Cancer associated epigenetic transitions identified by genome-wide histone methylation binding profiles in human colorectal cancer samples and paired normal mucosa
- 2011
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In: BMC Cancer. - : BioMed Central. - 1471-2407 .- 1471-2407. ; 11
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Journal article (peer-reviewed)abstract
- BACKGROUND: Despite their well-established functional roles, histone modifications have received less attention than DNA methylation in the cancer field. In order to evaluate their importance in colorectal cancer (CRC), we generated the first genome-wide histone modification profiles in paired normal colon mucosa and tumor samples.METHODS: Chromatin immunoprecipitation and microarray hybridization (ChIP-chip) was used to identify promoters enriched for histone H3 trimethylated on lysine 4 (H3K4me3) and lysine 27 (H3K27me3) in paired normal colon mucosa and tumor samples from two CRC patients and for the CRC cell line HT29.RESULTS: By comparing histone modification patterns in normal mucosa and tumors, we found that alterations predicted to have major functional consequences were quite rare. Furthermore, when normal or tumor tissue samples were compared to HT29, high similarities were observed for H3K4me3. However, the differences found for H3K27me3, which is important in determining cellular identity, indicates that cell lines do not represent optimal tissue models. Finally, using public expression data, we uncovered previously unknown changes in CRC expression patterns. Genes positive for H3K4me3 in normal and/or tumor samples, which are typically already active in normal mucosa, became hyperactivated in tumors, while genes with H3K27me3 in normal and/or tumor samples and which are expressed at low levels in normal mucosa, became hypersilenced in tumors.CONCLUSIONS: Genome wide histone modification profiles can be used to find epigenetic aberrations in genes associated with cancer. This strategy gives further insights into the epigenetic contribution to the oncogenic process and may identify new biomarkers.
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