Johan LM Björkegren

Johan Björkegren

Researcher

Focusing on cardiovascular diseases, the goal of my research is to use multi-modal big data analysis to create reliable network models of human biology and disease.

About me

2013-           

  • PROFESSOR | Genetics and Genomic Sciences
  • PROFESSOR | Medicine, Cardiology

Department of Genetics and Genomic Sciences, Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY

2003- Associate Professor of Molecular Medicine, Karolinska Institutet, Stockholm, Sweden

2015- Visiting Professor, University of Tartu, Tartu, Estonia

Focusing on cardiovascular diseases, the goal of my research is to use multi-modal big data analysis to create reliable network models of human biology and disease. Network models have enormous potential to improve our ability to predict disease risk, identify new therapeutic targets, and to monitor molecular effects of treatments. To achieve this goal, I have designed and generated a range of clinical datasets of cardiovascular disease that combine detailed clinical characteristics with imaging, genomics, proteomics, and other types of data.

My research has long focused on cardiovascular disease. My early work explored the role of triglyceride-rich lipoproteins in coronary artery disease (CAD), and my postdoctoral studies in mouse models established the hepatic gene microsomal triglyceride transfer protein as a key target to lower plasma cholesterol levels and reduce atherosclerosis. Since then, my primary focus has been systems analyses to generate network models from large genomic datasets—both from CAD patients in the clinic and from cellular and mouse models of atherosclerosis progression and regression in the laboratory.

Throughout the last decade, I have designed and led a range of clinical and mouse model studies to elucidate the inherit complexity of CAD. As one of the first clinical scientists to apply the emerging technologies of molecular profiling to large patient cohorts, I have revealed the role of functionally associated genes in several molecular networks that drive CAD. A common complex disease such as CAD cannot be understood nor cured by targeting isolated genes. Rather, the focus needs to be on molecular disease processes mirrored by regulatory-gene networks that capture the combined effects of many genetic and environmental risk factors.

To this end, at Karolinska Institutet and Tartu University Hospital, much of my time has gone into gathering a truly unique biobank from CAD patients undergoing different forms of heart surgery. The Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) is a joint study initiative between the cardiovascular chief surgeon at the Tartu University Hospital in Estonia, Dr. Arno Ruusalepp, and myself. Using the STARNET bio-bank, I have since 2013 been mainly active at the Department of Genetics and Genomic Sciences at Mount Sinai where we have generated RNA sequence data from up to nine CAD-relevant tissues isolated from over 800 hundred clinically well–characterized patients. This unprecedented dataset is the main resource for our current efforts to generate network models that predict the risk for and clinical outcomes of CAD.

My entrepreneurial ambitions have focused on translating the results of our systems genetic research into new therapies and diagnostics for patients at risk for or suffering CAD. I have launched several entrepreneurial projects. Of particular importance is Clinical Gene Networks AB—the first Bio-IT company in Sweden, founded in 2003 with the goal of exploring “clinical” networks to generate the next generation of diagnostics and therapies based on network models of complex diseases. Since 2019, I am reestablishing myself at the Karolinska Institutet at the Department of Medicine at Huddinge University Hospital.

Research description

I use multi-modal big data analysis to create new and reliable network models of human molecular biology in health and disease that can lead to better disease prediction, monitoring and therapies. To this effort I have created clinical datasets of mainly cardiovascular disease patients in Sweden, Estonia and now in the US that are enriched for many of these data modalities including genetics, -omics (epigenetics, RNA, proteins, metabolites and lipids) combined with detailed clinical characteristics including imaging.

I have a broad background in the design and analysis of clinical studies apprehending and applying the new screening and bioinformatics analysis tools to elucidate the true complexity of common diseases. The focus of these studies has been the role of functionally associated genes in molecular networks driving disease. Vital to this approach of a more granular understanding of complex disease biology is to originate these studies in humans suffering the disease whereas animal and cell disease model systems have chiefly been used for the purpose of validating key disease drivers and processes first identified in humans (i.e. top-down vs. a bottom-up approach).

STARNET bio-bank

This effort has now resulted in one of the world’s most unique cardiometabolic disease (CMD)-related dataset, STARNET, published in Science and Nature journals. Currently, we are expanding STARNET (v2) (with 1316 coronary artery disease (CAD)-affected subjects and 372 subjects verified to be CAD-free (nonCAD)) now processing  samples allowing transomic analyses (epigenomics, transcriptomics and proteomics) including single nuclei RNAseq and with the additions of portal vein and the gut microbiome. Moving forward, I am highly driven, motivated and focused to expand the central theme of my research strategies; a global understanding of the molecular regulatory-gene landscape enabling diagnostics and therapies of molecularly-defined subcategories of CMD patients (i.e. precision medicine).

Complete List of Published Work in MyBibliography: https://www.ncbi.nlm.nih.gov/myncbi/johan.bjorkegren.1/bibliography/public/

  1. Franzén et al. Cardiometabolic Risk Loci Share Downstream Cis and Trans Genes Across Tissues and Diseases” Science 19 Aug 2016:Vol. 353, Issue 6301, pp. 827-830.
  2. Zeng et al.. “Contribution of Gene Regulatory Networks to Heritability of Coronary Artery Disease”. J Am Coll Cardiol. 2019 Jun 18;73(23):2946-2957. doi: 10.1016/j.jacc.2019.03.520.
  3. Cohain el al. “An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease” Nat Commun. 2021 Jan 22;12(1):547.
  4. Hartman et al. “Sex-stratified gene regulatory networks reveal differentially activated key drivers of human coronary artery disease” Circulation. 2021 Feb 16;143(7):713-726.
  5. Koplev et al. “A mechanistic framework for cardiometabolic and coronary artery diseases” Nature Cardiovascular Research, in press (available online January 12th, 2022)

Historical contributions to Science:

1. In my PhD work I studied the role of apolipoprotein (apo) and lipid composition of triglyceride-rich lipoproteins (TRLs) for CAD. I found that the TRL content of apoCI was particularly relevant for risk of developing early CAD. This work involved both sampling and characterization of patients and a wide range of molecular laboratory methods.

    1. Bjorkegren, J. (2006). "Dual roles of apolipoprotein CI in the formation of atherogenic remnants." Curr Atheroscler Rep 8(1): 1-2.
    2. Hamsten, A., A. Silveira, S. Boquist, R. Tang, M. G. Bond, U. de Faire and J. Bjorkegren (2005). "The apolipoprotein CI content of triglyceride-rich lipoproteins independently predicts early atherosclerosis in healthy middle-aged men." J Am Coll Cardiol 45(7): 1013-1017
    3. Bjorkegren, J., S. Boquist, A. Samnegard, P. Lundman, P. Tornvall, C. G. Ericsson and A. Hamsten (2000). "Accumulation of apolipoprotein C-I-rich and cholesterol-rich VLDL remnants during exaggerated postprandial triglyceridemia in normolipidemic patients with coronary artery disease." Circulation 101(3):227-230.
    4. Bjorkegren, J., F. Karpe, R. W. Milne and A. Hamsten (1998). "Differences in apolipoprotein and lipid composition between human chylomicron remnants and very low-density lipoproteins isolated from fasting and postprandial plasma." J Lipid Res 39(7): 1412-1420.  
  1. During my post-doc years at UCSF, CA, I generated genetically modified mouse models relevant for CAD and atherosclerosis. I carefully investigated the hepatic gene microsomal triglyceride transfer protein (Mttp) conditional gene knockout in the liver and heart examining the effects of Mttp deletion on plasma cholesterol levels, liver steatosis and fat accumulation and secretion of lipoproteins from the heart.
    1. Larsson, S. L., J. Skogsberg and J. Bjorkegren (2004). "The low-density lipoprotein receptor prevents secretion of dense apoB100-containing lipoproteins from the liver." J Biol Chem 279(2): 831-836.
    2. Bjorkegren, J., A. Beigneux, M. O. Bergo, J. J. Maher and S. G. Young (2002). "Blocking the secretion of hepatic very low-density lipoproteins renders the liver more susceptible to toxin-induced injury." J Biol Chem 277(7): 5476-5483.
    3. Bjorkegren et al. (2001). "Lipoprotein secretion and triglyceride stores in the heart." J Biol Chem 276(42): 38511-38517
    4. Raabe et al. (1999). "Analysis of the role of microsomal triglyceride transfer protein in the liver of tissue-specific knockout mice." J Clin Invest 103(9): 1287-1298.  
  2.  I have extensively used these mouse models also after my post-doc for key CAD target validation and in combination with holistic functional transcriptomic studies of gene expression during atherosclerosis progression and regression. From these studies, I have defined regulatory gene networks driving atherosclerosis progression and regression that are highly relevant for my current studies of patients of CAD to establish networks active both in early and late phases of coronary atherosclerosis.  
    1. Bjorkegren, J. et al. (2014). "Plasma cholesterol-induced lesion networks activated before regression of early, mature, and advanced atherosclerosis." PLoS Genet. 10(2): e1004201.
    2. Shang et al. (2014). "Lim domain binding 2: a key driver of transendothelial migration of leukocytes and atherosclerosis." Arterioscler Thromb Vasc Biol 34(9): 2068-2077.
    3. Skogsberg et al. (2008). "Transcriptional profiling uncovers a network of cholesterol-responsive atherosclerosis target genes." PLoS. Genet. 4(3): e1000036.
    4. Kovacs et al. (2007). "Human C-reactive protein slows atherosclerosis development in a mouse model with human-like hypercholesterolemia." Proc. Natl. Acad. Sci. U S A 104(34): 13768-13773.  
  3. I have uniquely designed clinical studies to sample multiple vascular and metabolic tissues enabling systems genetics approaches to study CAD by generating genomics datasets from the STAGE and STARNET cohorts. For these types of functional genomics studies, I have evolved as a leader in the field of network CAD biology.
    1. Foroughi et al. (2015). "Expression quantitative trait Loci acting across multiple tissues are enriched in inherited risk for coronary artery disease." Circ Cardiovasc Genet 8(2): 305-315.
    2. Schadt, E. E. and J. L. Bjorkegren (2012). "NEW: network-enabled wisdom in biology, medicine, and health care." Science Transl. Med. 4(115): 115rv111
    3. Hägg et al. (2009). "Multi-organ expression profiling uncovers a gene module in coronary artery disease involving transendothelial migration of leukocytes and LIM domain binding 2: the Stockholm Atherosclerosis Gene Expression (STAGE) study." PLoS genetics 5: e1000754.
    4. Tegner, J. and J. Bjorkegren (2007). "Perturbations to uncover gene networks." Trends Genet 23(1): 34-41.  
  4. Founder of one of Sweden’s leading biotech companies in the Bio-IT sectors (Clinical Gene Networks AB). www.clinicalgenenetworks.com

Teaching portfolio

TEACHING/LECTURING AT THE KAROLINSKA INSTITUTET, 2002–2013

Lecturer in the PhD program, “Systems biology- from model organism to complex diseases” (# 2085) at the School of Medical Bioinformatics (FMB), Strategy and Development Office, Karolinska Institutet: Cardiovascular systems medicine”, 2 scheduled hours per semester, 2006-2012

Lecturer in the PhD program, “Bioinformatics in Medicine” The School of Medical Bioinformatics, Center for Medical Innovation: 1 scheduled hour per semester, 2002-2005.

Lecturer at the PhD program, “An overview of the process of atherosclerosis” (# 1551) at the Karolinska University Hospital, Solna 1 scheduled hour per year. “Systems biological approach to atherosclerosis”, 2005–2009.

Lecturer in the PhD program of Clinical Sciences at the Karolinska University Hospital, Huddinge: “From gene to disease”. Atherosclerosis: Gen-protein function. 1 scheduled hour per semester, 2003–2005.

Lecturer in the Biomedical School, semester 6, “Molecular Medicine”, the Karolinska University Hospital, Solna: 1 scheduled hour per semester, 2002–2004.

“Your food intake is a matter of your heart”, Health care at Karolinska Institutet, 2004, 2005, 2008.

Education

Stockholm Business School, SU, Sweden

BA

06/1988

Business

Karolinska Institutet, Stockholm, Sweden

BMSc

01/1995

Medical School

Karolinska University Hospital, Stockholm

MD

06/1998

Fully qualified physician

Karolinska Institutet, Sweden

PhD

05/1998

Lipoproteins/ Atherosclerosis

Gladstone Institute of Cardiovascular Disease, University of California, San Francisco, CA, USA

Postdoctorial

12/2001

CAD mouse models

Academic honours, awards and prizes

2016 - NIH-director Francis Collins, blog on Science 2016 article*

2010-2013 - Senior investigator position, Swedish Heart-Lung foundation

2008-2009 - Senior investigator award, Karolinska Institutet

2008 - Invited speaker to the Rudbeck Seminar series, Uppsala University, Sweden

2004-2007 - Research Assistant position for the Swedish research council                                                    

2003 - Finalist in the Young Investigator Award, International Society of Atherosclerosis, Kyoto

1999-2002 - Fogarty fellowship (VR), University of San Francisco, University of California

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