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  • 1.
    Berglund, Sofia
    et al.
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden.;Karolinska Inst, Dept Clin Neurosci, Therapeut Immune Design, Stockholm, Sweden.;Karolinska Univ Hosp, Cell Therapy & Allogene Stem Cell Transplantat CA, Stockholm, Sweden..
    Watz, Emma
    Karolinska Univ Hosp, Dept Clin Immunol & Transfus Med, Stockholm, Sweden.;Karolinska Inst, Dept Clin Sci Intervent & Technol CLINTEC, Stockholm, Sweden..
    Remberger, Mats
    Uppsala Univ, Uppsala Univ Hosp, Dept Med Sci, Uppsala, Sweden.;KFUE, Uppsala, Sweden..
    Legert, Karin Garming
    Karolinska Inst, Dept Dent Med, Stockholm, Sweden..
    Axdorph-Nygell, Ulla
    Karolinska Univ Hosp, Dept Clin Immunol & Transfus Med, Stockholm, Sweden.;Karolinska Inst, Dept Clin Sci Intervent & Technol CLINTEC, Stockholm, Sweden..
    Sundin, Mikael
    Karolinska Inst, Dept Clin Sci Intervent & Technol CLINTEC, Stockholm, Sweden.;Karolinska Univ Hosp, Astrid Lindgren Childrens Hosp, Pediat Hematol Immunol & Hematopoiet Cell Transpl, Stockholm, Sweden..
    Uhlin, Michael
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. Karolinska Univ Hosp, Dept Clin Immunol & Transfus Med, Stockholm, Sweden.;Karolinska Inst, Dept Clin Sci Intervent & Technol CLINTEC, Stockholm, Sweden.
    Mattsson, Jonas
    Karolinska Inst, Dept Oncol Pathol, Stockholm, Sweden.;Princess Margaret Canc Ctr, Div Med Oncol & Hematol, Toronto, ON, Canada.;Univ Toronto, Dept Med, Toronto, ON, Canada..
    Granulocyte transfusions could benefit patients with severe oral mucositis after allogeneic hematopoietic stem cell transplantation2019In: Vox Sanguinis, ISSN 0042-9007, E-ISSN 1423-0410, Vol. 114, no 7, p. 769-777Article in journal (Refereed)
    Abstract [en]

    Background and objectives Mucositis is a common complication after allogeneic hematopoietic stem cell transplantation (HSCT), and is caused by a combination of conditioning-induced mucosal damage and severe neutropenia. The symptoms include oral and abdominal pain, inability to swallow food and fluids, and severe diarrhoea. Severe mucositis is associated with increased risk of Graft-versus-Host disease and infection. Granulocyte transfusions (GCX) could be a treatment option, and our objective was to study its feasibility and potential benefits. Material and methods This retrospective, single-centre study included 30 patients receiving GCX because of severe oral mucositis after HSCT during 2005-2017. Clinical outcome, response to GCX, change in opiate administration and adverse events were studied. Results Twenty-seven patients received GCX from donors pre-treated with steroids and G-CSF, and three from donors pre-treated with steroids only. Overall response was 83% (24/29 evaluable patients). Fifteen patients reached a complete response. In 14 of 24 responders, a reduction of the administration of opiate pain relief was seen. In eight patients this reduction was >= 50% of the dose. Adverse events (AEs) were reported in 14 cases, and were mild to moderate, and well manageable with symptomatic treatment. No life-threatening or fatal AEs were recorded. Conclusions These results indicate that GCX could be a safe and effective treatment for oral mucositis after HSCT with the potential to reduce the necessity of opiate analgesic treatment in this disorder. No severe AEs were seen in this study, but the risk for severe pulmonary AEs after GCX needs to be considered.

  • 2.
    Drobin, Kimi
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Assadi, Ghazaleh
    Karolinska Inst, Dept Biosci & Nutr, Stockholm, Sweden..
    Hong, Mun-Gwan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Anggraeni Andersson, Margaretha
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Fredolini, Claudia
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab. Royal Inst Technol, KTH, Sch Biotechnol, Affin Prote,SciLifeLab, Stockholm, Sweden..
    Forsström, Björn
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Reznichenko, Anna
    Karolinska Inst, Dept Biosci & Nutr, Stockholm, Sweden..
    Akhter, Tahmina
    Karolinska Inst, Dept Biosci & Nutr, Stockholm, Sweden..
    Ek, Weronica E.
    Karolinska Inst, Dept Biosci & Nutr, Stockholm, Sweden.;Uppsala Univ, Sci Life Lab, Dept Immunol Genet & Pathol, Uppsala, Sweden..
    Bonfiglio, Ferdinando
    Karolinska Inst, Dept Biosci & Nutr, Stockholm, Sweden.;Biodonostia Hlth Res Inst, Dept Gastrointestinal & Liver Dis, San Sebastian, Spain..
    Hansen, Mark Berner
    AstraZeneca R&D, Innovat & Global Med, Molndal, Sweden.;Univ Copenhagen, Bispebjerg Hosp, Ctr Digest Dis, Copenhagen, Denmark..
    Sandberg, Kristian
    Uppsala Univ, Sci Life Lab, Drug Discovery & Dev Platform, Uppsala, Sweden.;Uppsala Univ, Uppsala Biomed Ctr, Dept Med Chem, Organ Pharmaceut Chem, Uppsala, Sweden.;Karolinska Inst, Dept Physiol & Pharmacol, Stockholm, Sweden..
    Greco, Dario
    Univ Helsinki, Inst Biotechnol, Helsinki, Finland..
    Repsilber, Dirk
    Orebro Univ, Sch Med Sci, Orebro, Sweden..
    Schwenk, Jochen M.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    D'Amato, Mauro
    Karolinska Inst, Dept Biosci & Nutr, Stockholm, Sweden.;BioDonostia Hlth Res Inst, San Sebastian, Spain.;Ikerbasque, Basque Fdn Sci, Bilbao, Spain..
    Halfvarson, Jonas
    Orebro Univ, Fac Med & Hlth, Dept Gastroenterol, SE-70182 Orebro, Sweden..
    Targeted Analysis of Serum Proteins Encoded at Known Inflammatory Bowel Disease Risk Loci2019In: Inflammatory Bowel Diseases, ISSN 1078-0998, E-ISSN 1536-4844, Vol. 25, no 2, p. 306-316Article in journal (Refereed)
    Abstract [en]

    Few studies have investigated the blood proteome of inflammatory bowel disease (IBD). We characterized the serum abundance of proteins encoded at 163 known IBD risk loci and tested these proteins for their biomarker discovery potential. Based on the Human Protein Atlas (HPA) antibody availability, 218 proteins from genes mapping at 163 IBD risk loci were selected. Targeted serum protein profiles from 49 Crohns disease (CD) patients, 51 ulcerative colitis (UC) patients, and 50 sex- and age-matched healthy individuals were obtained using multiplexed antibody suspension bead array assays. Differences in relative serum abundance levels between disease groups and controls were examined. Replication was attempted for CD-UC comparisons (including disease subtypes) by including 64 additional patients (33 CD and 31 UC). Antibodies targeting a potentially novel risk protein were validated by paired antibodies, Western blot, immuno-capture mass spectrometry, and epitope mapping. By univariate analysis, 13 proteins mostly related to neutrophil, T-cell, and B-cell activation and function were differentially expressed in IBD patients vs healthy controls, 3 in CD patients vs healthy controls and 2 in UC patients vs healthy controls (q < 0.01). Multivariate analyses further differentiated disease groups from healthy controls and CD subtypes from UC (P < 0.05). Extended characterization of an antibody targeting a novel, discriminative serum marker, the laccase (multicopper oxidoreductase) domain containing 1 (LACC1) protein, provided evidence for antibody on-target specificity. Using affinity proteomics, we identified a set of IBD-associated serum proteins encoded at IBD risk loci. These candidate proteins hold the potential to be exploited as diagnostic biomarkers of IBD.

  • 3. Gremel, Gabriela
    et al.
    Wanders, Alkwin
    Cedernaes, Jonathan
    Fagerberg, Linn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hallström, Björn
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Edlund, Karolina
    Sjostedt, Evelina
    Uhlén, Mathias
    KTH, School of Biotechnology (BIO), Proteomics and Nanobiotechnology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ponten, Fredrik
    The human gastrointestinal tract-specific transcriptome and proteome as defined by RNA sequencing and antibody-based profiling2015In: Journal of gastroenterology, ISSN 0944-1174, E-ISSN 1435-5922, Vol. 50, no 1, p. 46-57Article in journal (Refereed)
    Abstract [en]

    The gastrointestinal tract (GIT) is subdivided into different anatomical organs with many shared functions and characteristics, but also distinct differences. We have combined a genome-wide transcriptomics analysis with immunohistochemistry-based protein profiling to describe the gene and protein expression patterns that define the human GIT. RNA sequencing data derived from stomach, duodenum, jejunum/ileum and colon specimens were compared to gene expression levels in 23 other normal human tissues analysed with the same method. Protein profiling based on immunohistochemistry and tissue microarrays was used to sub-localize the corresponding proteins with GIT-specific expression into sub-cellular compartments and cell types. Approximately 75 % of all human protein-coding genes were expressed in at least one of the GIT tissues. Only 51 genes showed enriched expression in either one of the GIT tissues and an additional 83 genes were enriched in two or more GIT tissues. The list of GIT-enriched genes with validated protein expression patterns included various well-known but also previously uncharacterised or poorly studied genes. For instance, the colon-enriched expression of NXPE family member 1 (NXPE1) was established, while NLR family, pyrin domain-containing 6 (NLRP6) expression was primarily found in the human small intestine. We have applied a genome-wide analysis based on transcriptomics and antibody-based protein profiling to identify genes that are expressed in a specific manner within the human GIT. These genes and proteins constitute important starting points for an improved understanding of the normal function and the different states of disease associated with the GIT.

  • 4. Jakobsson, Hedvig E.
    et al.
    Abrahamsson, Thomas R.
    Jenmalm, Maria C.
    Harris, Keith
    Quince, Christopher
    Jernberg, Cecilia
    Björkstén, Bengt
    Engstrand, Lars
    Andersson, Anders F.
    KTH, School of Biotechnology (BIO), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Decreased gut microbiota diversity, delayed Bacteroidetes colonisation and reduced Th1 responses in infants delivered by Caesarean section2014In: Gut, ISSN 0017-5749, E-ISSN 1468-3288, Vol. 63, no 4, p. 559-566Article in journal (Refereed)
    Abstract [en]

    important stimuli for immune development, and a reduced microbial exposure as well as caesarean section (CS) has been associated with the development of allergic disease. Here we address how microbiota development in infants is affected by mode of delivery, and relate differences in colonisation patterns to the maturation of a balanced Th1/Th2 immune response. Design The postnatal intestinal colonisation pattern was investigated in 24 infants, born vaginally (15) or by CS (nine). The intestinal microbiota were characterised using pyrosequencing of 16S rRNA genes at 1 week and 1, 3, 6, 12 and 24 months after birth. Venous blood levels of Th1- and Th2-associated chemokines were measured at 6, 12 and 24 months. Results Infants born through CS had lower total microbiota diversity during the first 2 years of life. CS delivered infants also had a lower abundance and diversity of the Bacteroidetes phylum and were less often colonised with the Bacteroidetes phylum. Infants born through CS had significantly lower levels of the Th1-associated chemokines CXCL10 and CXCL11 in blood. Conclusions CS was associated with a lower total microbial diversity, delayed colonisation of the Bacteroidetes phylum and reduced Th1 responses during the first 2 years of life.

  • 5. Liu, Zhengtao
    et al.
    Que, Shuping
    Zhou, Lin
    Zheng, Shusen
    Romeo, Stefano
    Mardinoglu, Adil
    Valenti, Luca
    The effect of the TM6SF2 E167K variant on liver steatosis and fibrosis in patients with chronic hepatitis C: a meta-analysis2017In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 9273Article in journal (Refereed)
    Abstract [en]

    The impact of Transmembrane 6 superfamily member 2 (TM6SF2) E167K variant, which causes hepatocellular fat retention by altering lipoprotein secretion, on liver damage and metabolic traits in chronic hepatitis C patients is still debated. We performed a systematic review and meta-analysis to clarify this relationship. Four studies with a total of 4325 patients were included. The risk of histologically-determined advanced steatosis, fibrosis, and cirrhosis (but not of severe inflammation) were increased in carriers of the TM6SF2 variant (P < 0.05). Unlike the inconsistent association with steatosis severity, due to the confounding effect of infection by the genotype-3 hepatitis C virus, the TM6SF2 variant was robustly associated with advanced fibrosis (OR = 1.07; 95% confidence interval [CI] = 1.01-1.14) and in particular with cirrhosis (OR = 2.05; 95% CI = 1.39-3.02). Regarding metabolic features, individuals positive for the TM6SF2 variant exhibited 5.8-12.0% lower levels of circulating triglycerides and non-HDL cholesterol (P < 0.05). Carriers of the variant were leaner, but there was high heterogeneity across studies (I-2 = 97.2%). No significant association was observed between the TM6SF2 variant and insulin resistance or hepatitis C viral load (both P > 0.05). In conclusion, the TM6SF2 E167K variant promotes the development of steatosis, fibrosis and cirrhosis in patients with chronic hepatitis C. Conversely, this variant reduces circulating atherogenic lipid fractions.

  • 6.
    Lundmark, Anna
    et al.
    Karolinska Inst, Dept Dent Med, Div Periodontol, Huddinge, Sweden..
    Hu, Yue O. O.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab. Karolinska Inst, CTMR, Dept Microbiol Tumor & Cell Biol, Stockholm, Sweden..
    Huss, Mikael
    Stockholm Univ, Natl Bioinformat Infrastruct Sweden, Dept Biochem & Biophys, Sci Life Lab, Solna, Sweden..
    Johannsen, Gunnar
    Karolinska Inst, Dept Dent Med, Div Periodontol, Huddinge, Sweden..
    Andersson, Anders F.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Gene Technology. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Yucel-Lindberg, Tulay
    Karolinska Inst, Dept Dent Med, Div Periodontol, Huddinge, Sweden..
    Identification of Salivary Microbiota and Its Association With Host Inflammatory Mediators in Periodontitis2019In: Frontiers in Cellular and Infection Microbiology, E-ISSN 2235-2988, Vol. 9, article id 216Article in journal (Refereed)
    Abstract [en]

    Periodontitis is a microbial-induced chronic inflammatory disease, which may not only result in tooth loss, but can also contribute to the development of various systemic diseases. The transition from healthy to diseased periodontium depends on microbial dysbiosis and impaired host immune response. Although periodontitis is a common disease as well as associated with various systemic inflammatory conditions, the taxonomic profiling of the salivary microbiota in periodontitis and its association with host immune and inflammatory mediators has not been reported. Therefore, the aim of this study was to identify key pathogens and their potential interaction with the host's inflammatory mediators in saliva samples for periodontitis risk assessment. The microbial 16S rRNA gene sequencing and the levels of inflammatory mediators were performed in saliva samples from patients with chronic periodontitis and periodontally healthy control subjects. The salivary microbial community composition differed significantly between patients with chronic periodontitis and healthy controls. Our analyses identified a number of microbes, including bacteria assigned to Eubacterium saphenum, Tannerella forsythia, Filifactor alocis, Streptococcus mitis/parasanguinis, Parvimonas micra, Prevotella sp., Phocaeicola sp., and Fretibacterium sp. as more abundant in periodontitis, compared to healthy controls. In samples from healthy individuals, we identified Campylobacter concisus, and Veillonella sp. as more abundant. Integrative analysis of the microbiota and inflammatory mediators/cytokines revealed associations that included positive correlations between the pathogens Treponema sp. and Selenomas sp. and the cytokines chitinase 3-like 1, sIL-6R alpha, sTNF-R1, and gp 130/sIL-6R beta. In addition, a negative correlation was identified between IL-10 and Filifactor alocis. Our results reveal distinct and disease-specific patterns of salivary microbial composition between patients with periodontitis and healthy controls, as well as significant correlations between microbiota and host-mediated inflammatory cytokines. The positive correlations between the pathogens Treponema sp. and Selenomas sp. and the cytokines chitinase 3-like 1, sIL-6R alpha, sTNF-R1, and gp 130/sIL-6R beta might have the future potential to serve as a combined bacteria-host salivary biomarker panel for diagnosis of the chronic infectious disease periodontitis. However, further studies are required to determine the capacity of these microbes and inflammatory mediators as a salivary biomarker panel for periodontitis.

  • 7.
    Mardinoglu, Adil
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Boren, Jan
    Univ Gothenburg, Dept Mol & Clin Med, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Gothenburg, Sweden..
    Smith, Ulf
    Univ Gothenburg, Dept Mol & Clin Med, Gothenburg, Sweden.;Sahlgrens Univ Hosp, Gothenburg, Sweden..
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nielsen, Jens
    KTH, Centres, Science for Life Laboratory, SciLifeLab. Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden..
    Systems biology in hepatology: approaches and applications2018In: Nature Reviews. Gastroenterology & Hepatology, ISSN 1759-5045, E-ISSN 1759-5053, Vol. 15, no 6, p. 365-377Article, review/survey (Refereed)
    Abstract [en]

    Detailed insights into the biological functions of the liver and an understanding of its crosstalk with other human tissues and the gut microbiota can be used to develop novel strategies for the prevention and treatment of liver-associated diseases, including fatty liver disease, cirrhosis, hepatocellular carcinoma and type 2 diabetes mellitus. Biological network models, including metabolic, transcriptional regulatory, protein-protein interaction, signalling and co-expression networks, can provide a scaffold for studying the biological pathways operating in the liver in connection with disease development in a systematic manner. Here, we review studies in which biological network models were used to integrate multiomics data to advance our understanding of the pathophysiological responses of complex liver diseases. We also discuss how this mechanistic approach can contribute to the discovery of potential biomarkers and novel drug targets, which might lead to the design of targeted and improved treatment strategies. Finally, we present a roadmap for the successful integration of models of the liver and other human tissues with the gut microbiota to simulate whole-body metabolic functions in health and disease.

  • 8.
    Mardinoglu, Adil
    et al.
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Ural, Dilek
    Koc Univ, Sch Med, TR-34450 Istanbul, Turkey..
    Zeybel, Mujdat
    Koc Univ, Sch Med, Dept Gastroenterol & Hepatol, TR-34450 Istanbul, Turkey..
    Yuksel, Hatice Hilal
    KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, Centres, Science for Life Laboratory, SciLifeLab. KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova. KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science.
    Boren, Jan
    Univ Gothenburg, Dept Mol & Clin Med, S-41345 Gothenburg, Sweden.;Sahlgrenska Univ Hosp Gothenburg, S-41345 Gothenburg, Sweden..
    The Potential Use of Metabolic Cofactors in Treatment of NAFLD2019In: Nutrients, ISSN 2072-6643, E-ISSN 2072-6643, Vol. 11, no 7, article id 1578Article, review/survey (Refereed)
    Abstract [en]

    Non-alcoholic fatty liver disease (NAFLD) is caused by the imbalance between lipid deposition and lipid removal from the liver, and its global prevalence continues to increase dramatically. NAFLD encompasses a spectrum of pathological conditions including simple steatosis and non-alcoholic steatohepatitis (NASH), which can progress to cirrhosis and liver cancer. Even though there is a multi-disciplinary effort for development of a treatment strategy for NAFLD, there is not an approved effective medication available. Single or combined metabolic cofactors can be supplemented to boost the metabolic processes altered in NAFLD. Here, we review the dosage and usage of metabolic cofactors including l-carnitine, Nicotinamide riboside (NR), l-serine, and N-acetyl-l-cysteine (NAC) in human clinical studies to improve the altered biological functions associated with different human diseases. We also discuss the potential use of these substances in treatment of NAFLD and other metabolic diseases including neurodegenerative and cardiovascular diseases of which pathogenesis is linked to mitochondrial dysfunction.

  • 9. Wilman, H. R.
    et al.
    Parisinos, C. A.
    Atabaki-Pasdar, N.
    Kelly, M.
    Thomas, E. L.
    Neubauer, S.
    Jennison, C.
    Ehrhardt, B.
    Baum, P.
    Schoelsch, C.
    Freijer, J.
    Grempler, R.
    Graefe-Mody, U.
    Hennige, A.
    Dings, C.
    Lehr, T.
    Scherer, N.
    Sihinecich, I.
    Pattou, F.
    Raverdi, V.
    Caiazzo, R.
    Torres, F.
    Verkindt, H.
    Mari, A.
    Tura, A.
    Giorgino, T.
    Bizzotto,
    Froguel, P.
    Bonneford, A.
    Canouil, M.
    Dhennin, V.
    Brorsson, C.
    Brunak, S.
    De Masi, F.
    Gudmundsdóttir, V.
    Pedersen, H.
    Banasik, K.
    Thomas, C.
    Sackett, P.
    Staerfeldt, H. -H
    Lundgaard, A.
    Nilsson, B.
    Nielsen, A.
    Mazzoni, G.
    Karaderi, T.
    Rasmussen, S.
    Johansen, J.
    Allesøe, R.
    Fritsche, A.
    Thorand, B.
    Adamski, J.
    Grallert, H.
    Haid, M.
    Sharma, S.
    Troll, M.
    Adam, J.
    Ferrer, J.
    Eriksen, H.
    Frost, G.
    Häussler, Ragna S.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Hong, Mun-Gwan
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Schwenk, Jochen M.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Uhlén, Mathias
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Protein Science, Affinity Proteomics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
    Nicolay, C.
    Pavo, I.
    Steckel-Hamann, B.
    Thomas, M.
    Adragni, K.
    Wu, H.
    Hart, L.
    Roderick, S.
    van Leeuwen, N.
    Dekkers, K.
    Frau, F.
    Gassenhuber, J.
    Jablonka, B.
    Musholt, P.
    Ruetten, H.
    Tillner, J.
    Baltauss, T.
    Bernard Poenaru, O.
    de Preville, N.
    Rodriquez, M.
    Arumugam, M.
    Allin, K.
    Engelbrechtsen, L.
    Hansen, T.
    Forman, A.
    Jonsson, A.
    Pedersen, O.
    Dutta, A.
    Vogt, J.
    Vestergaard, H.
    Laakso, M.
    Kokkola, T.
    Kuulasmaa, T.
    Franks, P.
    Giordano, N.
    Pomares-Millan, H.
    Fitipaldi, H.
    Mutie, P.
    Klintenberg, M.
    Bergstrom, M.
    Groop, L.
    Ridderstrale, M.
    Atabaki Pasdar, N.
    Deshmukh, H.
    Heggie, A.
    Wake, D.
    McEvoy, D.
    McVittie, I.
    Walker, M.
    Hattersley, A.
    Hill, A.
    Jones, A.
    McDonald, T.
    Perry, M.
    Nice, R.
    Hudson, M.
    Thorne, C.
    Dermitzakis, E.
    Viñuela, A.
    Cabrelli, L.
    Loftus, H.
    Dawed, A.
    Donnelly, L.
    Forgie, I.
    Pearson, E.
    Palmer, C.
    Brown, A.
    Koivula, R.
    Wesolowska-Andersen, A.
    Abdalla, M.
    McRobert, N.
    Fernandez, J.
    Jiao, Y.
    Robertson, N.
    Gough, S.
    Kaye, J.
    Mourby, M.
    Mahajan, A.
    McCarthy, M.
    Shah, N.
    Teare, H.
    Holl, R.
    Koopman, A.
    Rutters, F.
    Beulens, J.
    Groeneveld, L.
    Bell, J.
    Thomas, L.
    Whitcher, B.
    Hingorani, A. D.
    Patel, R. S.
    Hemingway, H.
    Franks, P. W.
    Bell, J. D.
    Banerjee, R.
    Yaghootkar, H.
    Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration2019In: Journal of Hepatology, ISSN 0168-8278, E-ISSN 1600-0641, Vol. 71, no 3, p. 594-602Article in journal (Refereed)
    Abstract [en]

    Background &amp; Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p &lt;5 × 10−8). The 2 HFE variants account for ∼85% of all cases of hereditary haemochromatosis. Mendelian randomisation analysis provided evidence that higher central obesity plays a causal role in increased liver iron content. Phenome-wide association analysis demonstrated shared aetiopathogenic mechanisms for elevated liver iron, high blood pressure, cirrhosis, malignancies, neuropsychiatric and rheumatological conditions, while also highlighting inverse associations with anaemias, lipidaemias and ischaemic heart disease. Conclusion: Our study provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific, that higher central obesity is causally associated with higher liver iron, and that liver iron shares common aetiology with multiple metabolic and non-metabolic diseases. Lay summary: Excess liver iron content is common and is associated with liver diseases and metabolic diseases including diabetes, high blood pressure, and heart disease. We identified 3 genetic variants that are linked to an increased risk of developing higher liver iron content. We show that the same genetic variants are linked to higher risk of many diseases, but they may also be associated with some health advantages. Finally, we use genetic variants associated with waist-to-hip ratio as a tool to show that central obesity is causally associated with increased liver iron content.

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