Publications by authors named "Valborg Gudmundsdottir"

19 Publications

  • Page 1 of 1

Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes.

Circ Genom Precis Med 2021 08 9;14(4):e003258. Epub 2021 Jul 9.

Department of Epidemiology (N.F., G.H.), University of North Carolina, Chapel Hill.

Background: Coronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis.

Methods: We performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium.

Results: We replicated 2 loci (rs9369640 and rs9349379 near and rs10757278 near ) for CAC and one locus for cIMT (rs7412 and rs445925 near ) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near at 13q13.3) at =2.0×10 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints , encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations (<3.1×10) for 3 previously reported coronary artery disease loci for these subclinical atherosclerotic phenotypes (rs2891168 near and rs11170820 near for CAC, and rs7412 near for cIMT).

Conclusions: Our results provide potential biological mechanisms that could link CAC and cIMT to increased cardiovascular disease risk in individuals with T2D.
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http://dx.doi.org/10.1161/CIRCGEN.120.003258DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8435075PMC
August 2021

Serum levels of ACE2 are higher in patients with obesity and diabetes.

Obes Sci Pract 2021 Apr 16;7(2):239-243. Epub 2020 Dec 16.

Icelandic Heart Association Kopavogur Iceland.

Objective: As severity of outcome in COVID-19 is disproportionately higher among individuals with obesity, smokers, patients with hypertension, kidney disease, chronic pulmonary disease, coronary heart disease (CHD), and/or type 2 diabetes (T2D), serum levels of ACE2, the cellular entry point for the coronavirus SARS-CoV-2, were examined in these high-risk groups.

Methods: Associations of ACE2 levels to smokers and patients with hypertension, T2D, obesity, CHD, or COPD were investigated in a single center population-based study of 5457 Icelanders from the Age, Gene/Environment Susceptibility Reykjavík Study (AGES-RS) of the elderly (mean age 75 ± 6 years), using multiple linear regression analysis.

Results: Serum levels of ACE2 were higher in smokers and individuals with T2D and/or obesity while they were unaffected in the other patient groups.

Conclusion: ACE2 levels are higher in some patient groups with comorbidities linked to COVID-19 including obesity and T2D and as such may have an emerging role as a circulating biomarker for severity of outcome in the disease.
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http://dx.doi.org/10.1002/osp4.472DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8019273PMC
April 2021

Whole blood co-expression modules associate with metabolic traits and type 2 diabetes: an IMI-DIRECT study.

Genome Med 2020 12 1;12(1):109. Epub 2020 Dec 1.

NIHR Exeter Clinical Research Facility, University of Exeter Medical School, Exeter, UK.

Background: The rising prevalence of type 2 diabetes (T2D) poses a major global challenge. It remains unresolved to what extent transcriptomic signatures of metabolic dysregulation and T2D can be observed in easily accessible tissues such as blood. Additionally, large-scale human studies are required to further our understanding of the putative inflammatory component of insulin resistance and T2D. Here we used transcriptomics data from individuals with (n = 789) and without (n = 2127) T2D from the IMI-DIRECT cohorts to describe the co-expression structure of whole blood that mainly reflects processes and cell types of the immune system, and how it relates to metabolically relevant clinical traits and T2D.

Methods: Clusters of co-expressed genes were identified in the non-diabetic IMI-DIRECT cohort and evaluated with regard to stability, as well as preservation and rewiring in the cohort of individuals with T2D. We performed functional and immune cell signature enrichment analyses, and a genome-wide association study to describe the genetic regulation of the modules. Phenotypic and trans-omics associations of the transcriptomic modules were investigated across both IMI-DIRECT cohorts.

Results: We identified 55 whole blood co-expression modules, some of which clustered in larger super-modules. We identified a large number of associations between these transcriptomic modules and measures of insulin action and glucose tolerance. Some of the metabolically linked modules reflect neutrophil-lymphocyte ratio in blood while others are independent of white blood cell estimates, including a module of genes encoding neutrophil granule proteins with antibacterial properties for which the strongest associations with clinical traits and T2D status were observed. Through the integration of genetic and multi-omics data, we provide a holistic view of the regulation and molecular context of whole blood transcriptomic modules. We furthermore identified an overlap between genetic signals for T2D and co-expression modules involved in type II interferon signaling.

Conclusions: Our results offer a large-scale map of whole blood transcriptomic modules in the context of metabolic disease and point to novel biological candidates for future studies related to T2D.
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http://dx.doi.org/10.1186/s13073-020-00806-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7708171PMC
December 2020

It's in Our Blood: A Glimpse of Personalized Medicine.

Trends Mol Med 2021 01 25;27(1):20-30. Epub 2020 Sep 25.

Icelandic Heart Association, IS-201 Kopavogur, Iceland; Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland. Electronic address:

Recent advances in protein profiling technology has facilitated simultaneous measurement of thousands of proteins in large population studies, exposing the depth and complexity of the plasma and serum proteomes. This revealed that proteins in circulation were organized into regulatory modules under genetic control and closely associated with current and future common diseases. Unlike networks in solid tissues, serum protein networks comprise members synthesized across different tissues of the body. Genetic analysis reveals that this cross-tissue regulation of the serum proteome participates in systemic homeostasis and mirrors the global disease state of individuals. Here, we discuss how application of this information in routine clinical evaluations may transform the future practice of medicine.
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http://dx.doi.org/10.1016/j.molmed.2020.09.003DOI Listing
January 2021

ACE2 levels are altered in comorbidities linked to severe outcome in COVID-19.

medRxiv 2020 Jun 5. Epub 2020 Jun 5.

Aims: Severity of outcome in COVID-19 is disproportionately higher among the obese, males, smokers, those suffering from hypertension, kidney disease, coronary heart disease (CHD) and/or type 2 diabetes (T2D). We examined if serum levels of ACE2, the cellular entry point for the coronavirus SARS-CoV-2, were altered in these high-risk groups.

Methods: Associations of serum ACE2 levels to hypertension, T2D, obesity, CHD, smokers and males in a single center population-based study of 5457 Icelanders from the Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS) of the elderly (mean age 75+/-6 years).

Results: Smokers, males, and individuals with T2D or obesity have altered serum levels of ACE2 that may influence productive infection of SARS-CoV-2 in these high-risk groups.

Conclusion: ACE2 levels are upregulated in some patient groups with comorbidities linked to COVID-19 and as such may have an emerging role as a circulating biomarker for severity of outcome in COVID-19.
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http://dx.doi.org/10.1101/2020.06.04.20122044DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7276056PMC
June 2020

Antihypertensive medication uses and serum ACE2 levels: ACEIs/ARBs treatment does not raise serum levels of ACE2.

medRxiv 2020 May 25. Epub 2020 May 25.

Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Iceland.

Importance: Recent reports have shown that hypertension is the most common comorbidity associated with mortality in the current coronavirus disease 2019 (COVID-19). This has been related to the use of angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin II receptor blockers (ARBs) as animal studies indicate that these medications increase levels of ACE2, the cellular entry point for the coronavirus SARS-CoV-2. This has prompted clinicians to recommend discontinuing ACEIs and ARBs.

Objective: To examine the effect of ACEIs or ARBs treatment on serum levels of ACE2 and other key enzymes in the renin-angiotensin system (RAS).

Design Setting And Participants: A single center population-based study of 5457 Icelanders from the Age, Gene/Environment Susceptibility Reykjavik Study (AGES-RS) of the elderly (mean age 75±6 years) stratified by ACEIs (N = 699) or ARBs (N = 753) treatment.

Main Outcomes And Measures: The AGES-RS study population was stratified by ACEIs and ARBs medication use and compared for age, body mass index (BMI) (kg/m), hypertension and type 2 diabetes (T2D) as well as serum levels of renin, ACE and ACE2.

Results: While renin and ACE levels were significantly raised in serum of individuals on ACEIs or ARBs treatments, the ACE2 levels remained unaffected.

Conclusions And Relevance: Treatment with ACEIs or ARBs does not raise ACE2 levels in serum. Therefore, the present study does not support the proposed discontinuation of these medications among patients affected with COVID-19.
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http://dx.doi.org/10.1101/2020.05.21.20108738DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7265694PMC
May 2020

Circulating Protein Signatures and Causal Candidates for Type 2 Diabetes.

Diabetes 2020 08 8;69(8):1843-1853. Epub 2020 May 8.

Faculty of Medicine, University of Iceland, Reykjavik, Iceland

The increasing prevalence of type 2 diabetes poses a major challenge to societies worldwide. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach, measuring serum levels of 4,137 proteins in 5,438 elderly Icelanders, and identified 536 proteins associated with prevalent and/or incident type 2 diabetes. We validated a subset of the observed associations in an independent case-control study of type 2 diabetes. These protein associations provide novel biological insights into the molecular mechanisms that are dysregulated prior to and following the onset of type 2 diabetes and can be detected in serum. A bidirectional two-sample Mendelian randomization analysis indicated that serum changes of at least 23 proteins are downstream of the disease or its genetic liability, while 15 proteins were supported as having a causal role in type 2 diabetes.
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http://dx.doi.org/10.2337/db19-1070DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7372075PMC
August 2020

A computational framework to integrate high-throughput '-omics' datasets for the identification of potential mechanistic links.

Nat Protoc 2018 12;13(12):2781-2800

Clinical Microbiomics A/S, Copenhagen, Denmark.

We recently presented a three-pronged association study that integrated human intestinal microbiome data derived from shotgun-based sequencing with untargeted serum metabolome data and measures of host physiology. Metabolome and microbiome data are high dimensional, posing a major challenge for data integration. Here, we present a step-by-step computational protocol that details and discusses the dimensionality-reduction techniques used and methods for subsequent integration and interpretation of such heterogeneous types of data. Dimensionality reduction was achieved through a combination of data normalization approaches, binning of co-abundant genes and metabolites, and integration of prior biological knowledge. The use of prior knowledge to overcome functional redundancy across microbiome species is one central advance of our method over available alternative approaches. Applying this framework, other investigators can integrate various '-omics' readouts with variables of host physiology or any other phenotype of interest (e.g., connecting host and microbiome readouts to disease severity or treatment outcome in a clinical cohort) in a three-pronged association analysis to identify potential mechanistic links to be tested in experimental settings. Although we originally developed the framework for a human metabolome-microbiome study, it is generalizable to other organisms and environmental metagenomes, as well as to studies including other -omics domains such as transcriptomics and proteomics. The provided R code runs in ~1 h on a standard PC.
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http://dx.doi.org/10.1038/s41596-018-0064-zDOI Listing
December 2018

Co-regulatory networks of human serum proteins link genetics to disease.

Science 2018 08 2;361(6404):769-773. Epub 2018 Aug 2.

Icelandic Heart Association, Holtasmari 1, IS-201 Kopavogur, Iceland.

Proteins circulating in the blood are critical for age-related disease processes; however, the serum proteome has remained largely unexplored. To this end, 4137 proteins covering most predicted extracellular proteins were measured in the serum of 5457 Icelanders over 65 years of age. Pairwise correlation between proteins as they varied across individuals revealed 27 different network modules of serum proteins, many of which were associated with cardiovascular and metabolic disease states, as well as overall survival. The protein modules were controlled by cis- and trans-acting genetic variants, which in many cases were also associated with complex disease. This revealed co-regulated groups of circulating proteins that incorporated regulatory control between tissues and demonstrated close relationships to past, current, and future disease states.
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http://dx.doi.org/10.1126/science.aaq1327DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6190714PMC
August 2018

Integrative network analysis highlights biological processes underlying GLP-1 stimulated insulin secretion: A DIRECT study.

PLoS One 2018 2;13(1):e0189886. Epub 2018 Jan 2.

Department of Molecular Cell Biology, Leiden University Medical Center, Leiden, The Netherlands.

Glucagon-like peptide 1 (GLP-1) stimulated insulin secretion has a considerable heritable component as estimated from twin studies, yet few genetic variants influencing this phenotype have been identified. We performed the first genome-wide association study (GWAS) of GLP-1 stimulated insulin secretion in non-diabetic individuals from the Netherlands Twin register (n = 126). This GWAS was enhanced using a tissue-specific protein-protein interaction network approach. We identified a beta-cell protein-protein interaction module that was significantly enriched for low gene scores based on the GWAS P-values and found support at the network level in an independent cohort from Tübingen, Germany (n = 100). Additionally, a polygenic risk score based on SNPs prioritized from the network was associated (P < 0.05) with glucose-stimulated insulin secretion phenotypes in up to 5,318 individuals in MAGIC cohorts. The network contains both known and novel genes in the context of insulin secretion and is enriched for members of the focal adhesion, extracellular-matrix receptor interaction, actin cytoskeleton regulation, Rap1 and PI3K-Akt signaling pathways. Adipose tissue is, like the beta-cell, one of the target tissues of GLP-1 and we thus hypothesized that similar networks might be functional in both tissues. In order to verify peripheral effects of GLP-1 stimulation, we compared the transcriptome profiling of ob/ob mice treated with liraglutide, a clinically used GLP-1 receptor agonist, versus baseline controls. Some of the upstream regulators of differentially expressed genes in the white adipose tissue of ob/ob mice were also detected in the human beta-cell network of genes associated with GLP-1 stimulated insulin secretion. The findings provide biological insight into the mechanisms through which the effects of GLP-1 may be modulated and highlight a potential role of the beta-cell expressed genes RYR2, GDI2, KIAA0232, COL4A1 and COL4A2 in GLP-1 stimulated insulin secretion.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0189886PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5749727PMC
January 2018

Metabolite ratios as potential biomarkers for type 2 diabetes: a DIRECT study.

Diabetologia 2018 Jan 25;61(1):117-129. Epub 2017 Oct 25.

Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine, Berlin Buch, Germany.

Aims/hypothesis: Circulating metabolites have been shown to reflect metabolic changes during the development of type 2 diabetes. In this study we examined the association of metabolite levels and pairwise metabolite ratios with insulin responses after glucose, glucagon-like peptide-1 (GLP-1) and arginine stimulation. We then investigated if the identified metabolite ratios were associated with measures of OGTT-derived beta cell function and with prevalent and incident type 2 diabetes.

Methods: We measured the levels of 188 metabolites in plasma samples from 130 healthy members of twin families (from the Netherlands Twin Register) at five time points during a modified 3 h hyperglycaemic clamp with glucose, GLP-1 and arginine stimulation. We validated our results in cohorts with OGTT data (n = 340) and epidemiological case-control studies of prevalent (n = 4925) and incident (n = 4277) diabetes. The data were analysed using regression models with adjustment for potential confounders.

Results: There were dynamic changes in metabolite levels in response to the different secretagogues. Furthermore, several fasting pairwise metabolite ratios were associated with one or multiple clamp-derived measures of insulin secretion (all p < 9.2 × 10). These associations were significantly stronger compared with the individual metabolite components. One of the ratios, valine to phosphatidylcholine acyl-alkyl C32:2 (PC ae C32:2), in addition showed a directionally consistent positive association with OGTT-derived measures of insulin secretion and resistance (p ≤ 5.4 × 10) and prevalent type 2 diabetes (OR 2.64 [β 0.97 ± 0.09], p = 1.0 × 10). Furthermore, Val_PC ae C32:2 predicted incident diabetes independent of established risk factors in two epidemiological cohort studies (HR 1.57 [β 0.45 ± 0.06]; p = 1.3 × 10), leading to modest improvements in the receiver operating characteristics when added to a model containing a set of established risk factors in both cohorts (increases from 0.780 to 0.801 and from 0.862 to 0.865 respectively, when added to the model containing traditional risk factors + glucose).

Conclusions/interpretation: In this study we have shown that the Val_PC ae C32:2 metabolite ratio is associated with an increased risk of type 2 diabetes and measures of insulin secretion and resistance. The observed effects were stronger than that of the individual metabolites and independent of known risk factors.
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http://dx.doi.org/10.1007/s00125-017-4436-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6448944PMC
January 2018

Pancreatic Islet Protein Complexes and Their Dysregulation in Type 2 Diabetes.

Front Genet 2017 20;8:43. Epub 2017 Apr 20.

Department of Bio and Health Informatics, Technical University of DenmarkKgs Lyngby, Denmark.

Type 2 diabetes (T2D) is a complex disease that involves multiple genes. Numerous risk loci have already been associated with T2D, although many susceptibility genes remain to be identified given heritability estimates. Systems biology approaches hold potential for discovering novel T2D genes by considering their biological context, such as tissue-specific protein interaction partners. Pancreatic islets are a key T2D tissue and many of the known genetic risk variants lead to impaired islet function, hence a better understanding of the islet-specific dysregulation in the disease-state is essential to unveil the full potential of person-specific profiles. Here we identify 3,692 overlapping pancreatic islet protein complexes (containing 10,805 genes) by integrating islet gene and protein expression data with protein interactions. We found 24 of these complexes to be significantly enriched for genes associated with diabetic phenotypes through heterogeneous evidence sources, including genetic variation, methylation, and gene expression in islets. The analysis specifically revealed ten T2D candidate genes with probable roles in islets (, and ), of which the last six are novel in the context of T2D and the data that went into the analysis. Fifteen of the twenty-four complexes were further enriched for combined genetic associations with glycemic traits, exemplifying how perturbation of protein complexes by multiple small effects can give rise to diabetic phenotypes. The complex nature of T2D ultimately prompts an understanding of the individual patients at the network biology level. We present the foundation for such work by exposing a subset of the global interactome that is dysregulated in T2D and consequently provides a good starting point when evaluating an individual's alterations at the genome, transcriptome, or proteome level in relation to T2D in clinical settings.
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http://dx.doi.org/10.3389/fgene.2017.00043DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5397424PMC
April 2017

Early differences in islets from prediabetic NOD mice: combined microarray and proteomic analysis.

Diabetologia 2017 03 12;60(3):475-489. Epub 2017 Jan 12.

Laboratory for Clinical and Experimental Endocrinology, KU Leuven, Herestraat 49 bus 902, 3000, Leuven, Belgium.

Aims/hypothesis: Type 1 diabetes is an endocrine disease where a long preclinical phase, characterised by immune cell infiltration in the islets of Langerhans, precedes elevated blood glucose levels and disease onset. Although several studies have investigated the role of the immune system in this process of insulitis, the importance of the beta cells themselves in the initiation of type 1 diabetes is less well understood. The aim of this study was to investigate intrinsic differences present in the islets from diabetes-prone NOD mice before the onset of insulitis.

Methods: The islet transcriptome and proteome of 2-3-week-old mice was investigated by microarray and 2-dimensional difference gel electrophoresis (2D-DIGE), respectively. Subsequent analyses using sophisticated pathway analysis and ranking of differentially expressed genes and proteins based on their relevance in type 1 diabetes were performed.

Results: In the preinsulitic period, alterations in general pathways related to metabolism and cell communication were already present. Additionally, our analyses pointed to an important role for post-translational modifications (PTMs), especially citrullination by PAD2 and protein misfolding due to low expression levels of protein disulphide isomerases (PDIA3, 4 and 6), as causative mechanisms that induce beta cell stress and potential auto-antigen generation.

Conclusions/interpretation: We conclude that the pancreatic islets, irrespective of immune differences, may contribute to the initiation of the autoimmune process.

Data Availability: All microarray data are available in the ArrayExpress database ( www.ebi.ac.uk/arrayexpress ) under accession number E-MTAB-5264.
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http://dx.doi.org/10.1007/s00125-016-4191-1DOI Listing
March 2017

Ranking factors involved in diabetes remission after bariatric surgery using machine-learning integrating clinical and genomic biomarkers.

NPJ Genom Med 2016 26;1:16035. Epub 2016 Oct 26.

Department of Bio and Health Informatics, Technical University of Denmark, Kongens Lyngby, Denmark.

As weight-loss surgery is an effective treatment for the glycaemic control of type 2 diabetes in obese patients, yet not all patients benefit, it is valuable to find predictive factors for this diabetic remission. This will help elucidating possible mechanistic insights and form the basis for prioritising obese patients with dysregulated diabetes for surgery where diabetes remission is of interest. In this study, we combine both clinical and genomic factors using heuristic methods, informed by prior biological knowledge in order to rank factors that would have a role in predicting diabetes remission, and indeed in identifying patients who may have low likelihood in responding to bariatric surgery for improved glycaemic control. Genetic variants from the Illumina CardioMetaboChip were prioritised through single-association tests and then seeded a larger selection from protein-protein interaction networks. Artificial neural networks allowing nonlinear correlations were trained to discriminate patients with and without surgery-induced diabetes remission, and the importance of each clinical and genetic parameter was evaluated. The approach highlighted insulin treatment, baseline HbA1c levels, use of insulin-sensitising agents and baseline serum insulin levels, as the most informative variables with a decent internal validation performance (74% accuracy, area under the curve (AUC) 0.81). Adding information for the eight top-ranked single nucleotide polymorphisms (SNPs) significantly boosted classification performance to 84% accuracy (AUC 0.92). The eight SNPs mapped to eight genes - and - three of which are known to have a role in insulin secretion, insulin sensitivity or obesity, but have not been indicated for diabetes remission after bariatric surgery before.
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http://dx.doi.org/10.1038/npjgenmed.2016.35DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5685313PMC
October 2016

Human gut microbes impact host serum metabolome and insulin sensitivity.

Nature 2016 07 13;535(7612):376-81. Epub 2016 Jul 13.

Insulin resistance is a forerunner state of ischaemic cardiovascular disease and type 2 diabetes. Here we show how the human gut microbiome impacts the serum metabolome and associates with insulin resistance in 277 non-diabetic Danish individuals. The serum metabolome of insulin-resistant individuals is characterized by increased levels of branched-chain amino acids (BCAAs), which correlate with a gut microbiome that has an enriched biosynthetic potential for BCAAs and is deprived of genes encoding bacterial inward transporters for these amino acids. Prevotella copri and Bacteroides vulgatus are identified as the main species driving the association between biosynthesis of BCAAs and insulin resistance, and in mice we demonstrate that P. copri can induce insulin resistance, aggravate glucose intolerance and augment circulating levels of BCAAs. Our findings suggest that microbial targets may have the potential to diminish insulin resistance and reduce the incidence of common metabolic and cardiovascular disorders.
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http://dx.doi.org/10.1038/nature18646DOI Listing
July 2016

Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota.

Nature 2015 Dec 2;528(7581):262-266. Epub 2015 Dec 2.

The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.

In recent years, several associations between common chronic human disorders and altered gut microbiome composition and function have been reported. In most of these reports, treatment regimens were not controlled for and conclusions could thus be confounded by the effects of various drugs on the microbiota, which may obscure microbial causes, protective factors or diagnostically relevant signals. Our study addresses disease and drug signatures in the human gut microbiome of type 2 diabetes mellitus (T2D). Two previous quantitative gut metagenomics studies of T2D patients that were unstratified for treatment yielded divergent conclusions regarding its associated gut microbial dysbiosis. Here we show, using 784 available human gut metagenomes, how antidiabetic medication confounds these results, and analyse in detail the effects of the most widely used antidiabetic drug metformin. We provide support for microbial mediation of the therapeutic effects of metformin through short-chain fatty acid production, as well as for potential microbiota-mediated mechanisms behind known intestinal adverse effects in the form of a relative increase in abundance of Escherichia species. Controlling for metformin treatment, we report a unified signature of gut microbiome shifts in T2D with a depletion of butyrate-producing taxa. These in turn cause functional microbiome shifts, in part alleviated by metformin-induced changes. Overall, the present study emphasizes the need to disentangle gut microbiota signatures of specific human diseases from those of medication.
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http://dx.doi.org/10.1038/nature15766DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4681099PMC
December 2015

A proteomic study of the regulatory role for STAT-1 in cytokine-induced beta-cell death.

Proteomics Clin Appl 2015 Oct 11;9(9-10):938-52. Epub 2015 Apr 11.

Division of Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium.

Purpose: Signal transducer and activator of transcription 1 (STAT-1) plays a crucial role in cytokine-induced beta-cell destruction. However, its precise downstream pathways have not been completely clarified. We performed a proteome analysis of cytokine-exposed C57Bl/6 and STAT-1(-/-) mouse islets and prioritized proteins for their potential in relation to type 1 diabetes (T1D).

Experimental Design: Differential proteins were identified using a combination of 2D-DIGE and MALDI-TOF/TOF analysis and were subjected to ingenuity pathway analysis (IPA). Protein-protein interaction networks were created and a phenome-interactome ranking of the differential proteins based on their assignment to T1D was performed.

Results: Numerous STAT-1-regulated proteins were identified and divided in different groups according to their biological function. The largest group of proteins was the one involved in protein synthesis and processing. Network analysis revealed a complex interaction between proteins from different functional groups and IPA analysis confirmed the protective effect of STAT-1 deletion on cytokine-induced beta-cell death. Finally, a central role in this STAT-1-regulated mechanism was assigned to small ubiquitin-related modifier 4 (SUMO4).

Conclusions And Clinical Relevance: These findings confirm a central role for STAT-1 in pancreatic islet inflammation induced destruction and most importantly elucidate the underlying proteomic pathways involved.
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http://dx.doi.org/10.1002/prca.201400124DOI Listing
October 2015

The genome of a Late Pleistocene human from a Clovis burial site in western Montana.

Nature 2014 Feb;506(7487):225-9

Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark, Kemitorvet 208, Kgs. Lyngby DK-2800, Denmark.

Clovis, with its distinctive biface, blade and osseous technologies, is the oldest widespread archaeological complex defined in North America, dating from 11,100 to 10,700 (14)C years before present (bp) (13,000 to 12,600 calendar years bp). Nearly 50 years of archaeological research point to the Clovis complex as having developed south of the North American ice sheets from an ancestral technology. However, both the origins and the genetic legacy of the people who manufactured Clovis tools remain under debate. It is generally believed that these people ultimately derived from Asia and were directly related to contemporary Native Americans. An alternative, Solutrean, hypothesis posits that the Clovis predecessors emigrated from southwestern Europe during the Last Glacial Maximum. Here we report the genome sequence of a male infant (Anzick-1) recovered from the Anzick burial site in western Montana. The human bones date to 10,705 ± 35 (14)C years bp (approximately 12,707-12,556 calendar years bp) and were directly associated with Clovis tools. We sequenced the genome to an average depth of 14.4× and show that the gene flow from the Siberian Upper Palaeolithic Mal'ta population into Native American ancestors is also shared by the Anzick-1 individual and thus happened before 12,600 years bp. We also show that the Anzick-1 individual is more closely related to all indigenous American populations than to any other group. Our data are compatible with the hypothesis that Anzick-1 belonged to a population directly ancestral to many contemporary Native Americans. Finally, we find evidence of a deep divergence in Native American populations that predates the Anzick-1 individual.
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http://dx.doi.org/10.1038/nature13025DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4878442PMC
February 2014
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