Our research is focussed on the molecular epidemiology of common non-communicable diseases that often develop over many years and can partly be prevented or delayed by early preventive measures and optimised identification of persons at greatest risk. The diseases we are working with often overlap and are summarised as “cardiometabolic diseases” – they include type 2 diabetes, cardiovascular disease (such as heart attack and stroke), chronic kidney disease, and heart failure.
I also have a strong research interest in Type 1 diabetes (T1D), especially regarding clinical and genetic heterogeneity and the role of C-peptide as a potential surrogate endpoint in clinical trials.
We use data from large, clinic- and population-based cohorts of tens of thousands of persons who have been assessed with state-of-the-art methods, and employ advanced statistical modelling including traditional regression-type approaches and machine learning applications (such as gradient boosting and random forest) to analyse these data. We also use a method called “Mendelian randomization” where we use genetic data in order to assess causal effects in observational data and try to distinguish “correlation versus causation”, which is a prerequisite for identifying potential novel drug targets.
We usually start off with three types of data:
- Molecular biomarker data in blood, urine or faeces, e.g. genomics (DNA), proteomics (proteins), metabolomics (small molecules), and gut microbiomics
- Assessment data, e.g. clinical questionnaires, blood biochemistry, renal function, weight, height
- Outcome data, e.g., who developed diabetes during the 10-year period after baseline assessment
We analyse these data with three overarching aims:
- Improve risk prediction and the identification of persons who will benefit most from early intervention and targeted prevention
- Discover new potential drug targets and modifiable risk factors for the treatment and prevention of cardiometabolic diseases
- Broaden our understanding of the pathophysiology of cardiometabolic diseases and shed light on the many remaining unknowns in their development
Our current research priority is to explore the role of the gut microbiome and the urine microbiome in kidney disease - a project in the SCAPIS cohort study that we are lucky to collaborate on with colleagues from Uppsala and Lund.
- Co-supervisor for Ph.D. student Malin Anna Enarsson, Karolinska Institutet/Region Dalarna
- Co-supervisor for Ph.D. student: Jonas Wuopio, Karolinska Institutet/Region Dalarna
- Co-supervisor for Ph.D. student: Ann-Sofie Rönnegård, Karolinska Institutet/Region Dalarna
- Main supervisor for Master students at Karolinska Institutet: Jennifer Vidovic (Spring Semester 2019), Emmi Salinas (Spring Semester 2019), Karin Sundqvist (Autumn Semester 2018), Simon Marschall (Autumn Semester 2018)
- Ph.D. (2017) in molecular epidemiology, Department of Medical Sciences, Uppsala University (main supervisor Prof. Tove Fall, co-supervisors Profs. Erik Ingelsson and Johan Sundström)
- M.D. (2013): B.M. B.Ch., University of Oxford, U.K. (preclinical years at Oriel College, clinical years at Balliol College)
- B.Sc.-M.Sc. (equivalent) in psychology (2008): Dipl.-Psych, University of Braunschweig, Germany
- Languages (fluent): Swedish, English, German, French, plus: a tiny bit Russian
Akademiska priser och utmärkelser
- June 2019: Loo and Hans Osterman Foundation, Karolinska Institutet: SEK 70,000 kr (PI)
- September 2018: Foundation for Age-related Diseases, Karolinska Institutet: SEK 85,000 kr (PI)
- June 2018: Young Investigator Research Grant, European Foundation for the Study of Diabetes, EFSD: EUR 50,000 € (PI)
- June 2018: Engagement Grant, Karolinska Institutet: SEK 200,000 kr (PI)
- May 2017: Research grant prize for best PhD thesis, Department of Medical Sciences, Uppsala University: SEK 100,000 kr (PI)
COI: I am also working with a company that develops treatments for T1D.
Selected recent publications:
- Ärnlöv J, Nowak C. Association between albuminuria, incident cardiovascular events, and mortality in persons without hypertension, diabetes, and cardiovascular disease. Eur J Prev Cardiol. 2020 Nov 23:zwaa095. doi: 10.1093/eurjpc/zwaa095. Epub ahead of print. PMID: 33624107.
- Wuopio J, Orho-Melander M, Ärnlöv J, Nowak C. Estimated salt intake and risk of atrial fibrillation in a prospective community-based cohort. J Intern Med. 2020 Nov 19;. doi: 10.1111/joim.13194. PubMed PMID: 33210391.
- Salihovic S, Broeckling CD, Ganna A, Prenni JE, Sundström J, Berne C, Lind L, Ingelsson E, Fall T, Ärnlöv J, Nowak C. Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes. Sci Rep. 2020 Oct 5;10(1):16474. doi: 10.1038/s41598-020-72456-y. PMID: 33020500.
- Nowak C, Ärnlöv J. Kidney Disease Biomarkers Improve Heart Failure Risk Prediction in the General Population. Circ Heart Fail. 2020 Aug 6;:CIRCHEARTFAILURE120006904. doi: 10.1161/CIRCHEARTFAILURE.120.006904. PMID: 32757644.
- Ärnlöv J, Dluzen DF, Nowak C. Atherosclerotic Aortic Calcification-Associated Polymorphism in HDAC9 and Associations with Mortality, Cardiovascular Disease, and Kidney Disease. iScience. 2020 Jul 24;23(7):101253. doi: 10.1016/j.isci.2020.101253. PMID: 32585591.
- Beijer K*, Nowak C*, Sundström J, Ärnlöv J, Fall T, Lind L. In search of causal pathways in diabetes: a study using proteomics and genotyping data from a cross-sectional study. Diabetologia. 2019 Nov;62(11):1998-2006. doi: 10.1007/s00125-019-4960-8. PMID: 31446444. *shared first
- Nowak C, Ärnlöv J. A Mendelian randomization study of the effects of blood lipids on breast cancer risk. Nat Commun. 2018 Sep 27;9(1):3957. doi: 10.1038/s41467-018-06467-9. PMID: 30262900.
- Nowak C, Carlsson AC, Östgren CJ, Nyström FH, Alam M, Feldreich T, Sundström J, Carrero JJ, Leppert J, Hedberg P, Henriksen E, Cordeiro AC, Giedraitis V, Lind L, Ingelsson E, Fall T, Ärnlöv J. Multiplex proteomics for prediction of major cardiovascular events in type 2 diabetes. Diabetologia. 2018 Aug;61(8):1748-1757. doi: 10.1007/s00125-018-4641-z. PMID: 29796748.