Projects

  • Glaucoma prediction

    Our research pilots a genomics-guided approach to glaucoma screening by leveraging polygenic risk scores (PRS) to identify individuals at high risk before symptoms emerge. Glaucoma, a leading cause of irreversible blindness, is often diagnosed too late due to being asymptomatic in early stages. By integrating genetic risk with clinical data, we aim to improve early detection, personalize risk assessment, and prevent vision loss more effectively. Using Finnish biobank and registry data, we are among the first to test whether PRS-based screening can deliver real-world clinical benefits. This work lays the groundwork for implementing population-level genetic screening strategies in glaucoma care.

  • Germline influences in cancer

    We investigate how inherited genetic variation influences cancer risk, prognosis, and treatment response by combining germline genomics with clinical, epidemiological, and multi-omic data. We study both common and rare genetic factors across solid tumors, focusing on outcomes such as survival, therapy effectiveness, and the risk of multiple primary cancers. Using large biobank-linked datasets, we investigate how genetic profiles interact with lifestyle, tumor features, and treatments to better understand cancer biology and patient outcomes. A key aim is to improve risk stratification and personalize cancer care through genetics-informed prediction tools.

  • Inflammatory rheumatic diseases

    We explore how genetic and real-world clinical data together impact the risk, severity, and comorbidities of inflammatory diseases, especially inflammatory rheumatic conditions like rheumatoid arthritis. We use nationwide biobank data linked with longitudinal lab measurements, clinical outcomes, and medication data to study long-term inflammation patterns and their genetic underpinnings.

  • Toward genomics-guided breast cancer screening

    We advance personalized breast cancer screening by integrating comprehensive inherited risk estimation, including polygenic risk scores and rare pathogenic variants, into clinical practice. We are actively involved in the Intervene breast cancer study (https://www.intervene.fi/), a clinical pilot study testing genomics-guided breast cancer screening in a real-world healthcare setting. By combining genetic data with family history and clinical factors, we aim to improve individual risk prediction and move toward more tailored, risk-based screening strategies. These efforts support the development of more targeted breast cancer screening programs.

  • Laboratory biomarker and medication trajectories

    We explore how genetic and biomarker data influence medication response by analyzing lab and drug use trajectories across large-scale biobank data. We link prescription records, clinical laboratory measurements, and multi-omics to uncover factors affecting drug efficacy, side effects, and adherence. This approach enables the discovery of predictive markers for treatment outcomes across diseases with major public health burden, such as cardiometabolic diseases, cancer, and mental health conditions.

Selected publications

Find more of the group’s publications at University of Helsinki Research portal

  • Mars N, Koskela J, Ripatti P, Kiiskinen TJ, Havulinna AS, Lindbohm JV, Ahola-Olli A, Kurki M, Karjalainen J, Palta P, FinnGen, Neale BM, Daly M, Salomaa V, Palotie A, Widén E, Ripatti S. Polygenic and clinical risk scores and their impact on age at onset and prediction of cardiometabolic diseases and common cancers. Nat Med. 2020;26:549–557.

  • Mars N, Kerminen S, Tamlander M, Pirinen M, Jakkula E, Aaltonen K, Meretoja T, Heinävaara S, Widén E, Ripatti S. Comprehensive inherited risk estimation for risk-based breast cancer screening in women. J Clin Oncol. 2024;42(13):1477–1487.

  • Tamlander M, Jermy B, Seppälä TT, Färkkilä M, Widén E, Ripatti S, Mars N. Genome-wide polygenic risk scores for colorectal cancer have implications for risk-based screening. Br J Cancer. 2024;130(4):651-659.

  • Mars N, Widén E, Kerminen S, Meretoja T, Pirinen M, Palta P, Della Briotta Parolo P, FinnGen, Palotie A, Kaprio J, Joensuu H, Daly M, Ripatti S. Polygenic risk, susceptibility genes, and breast cancer over the life course. Nat Commun. 2020;11(1):6383.

  • Mars N, Lindbohm JV, della Briotta Parolo P, Widén E, Kaprio J, Palotie A, FinnGen, Ripatti S. Systematic comparison of family history and polygenic risk across 24 common diseases. AJHG. 2022;109(12):2152–2162.

  • Kerola AM, Palomäki A, Laivuori H, Laitinen T, Färkkilä M, Eklund KK, Ripatti S, Perola M, Ganna A, Lindbohm JV, Mars N. Patterns of reproductive health in inflammatory rheumatic diseases and other immune-mediated diseases: a nationwide registry study. Rheumatology. 2024;63(10):2701–2710.

  • Palomäki A, FinnGen Rheumatology Clinical Expert Group, Palotie A, Koskela J, FinnGen, Ripatti S, Laitinen T, Mars N. Lifetime risk of rheumatoid arthritis-associated interstitial lung disease in MUC5B mutation carriers. Annals of the Rheumatic Diseases. 2021;80(12):1530-1536.

  • Lindbohm JV, Mars N, Sipilä PN, Singh-Manoux A, Runz H, FinnGen, Livingston G, Seshadri S, Xavier R. Hingorani AD, Ripatti S, Kivimäki M. Immune system-wide Mendelian randomization and triangulation analyses support autoimmunity as a modifiable component in dementia-causing diseases. Nature Aging. 2022;2(10):956-972.

  • Mars N, Kerminen S, Yen-Chen AF, Kanai M, Läll K, Thomas LF, Skogholt AH, della Briotta Parolo P, The Biobank Japan Project, FinnGen, Neale BM, Smoller JW, Gabrielsen ME, Hveem K, Mägi R, Matsuda K, Okada Y, Pirinen M, Palotie A, Ganna A, Martin AR, Ripatti S. Genome-wide risk prediction of common diseases across ancestries in one million people. Cell Genomics. 2022;2:100118.

  • Tamlander M, Mars N, Pirinen M, FinnGen, Widén E, Ripatti S. Integration of questionnaire-based risk factors improves polygenic risk scores for coronary heart disease and type 2 diabetes. Commun Biol. 2022;5:158.

  • Lindbohm, JV, Sipilä PN*, Mars N*, Knüppel A, Pentti J, Nyberg ST, Frank P, Ahmadi-Abhari S, Brunner EJ, Shipley MJ, Singh-Manoux A, Tabak AG, Batty GD, Kivimäki M. Association between change in cardiovascular risk scores and future cardiovascular disease: analyses of data from the Whitehall II longitudinal, prospective cohort study. Lancet Digital Health. 2021;3(7):434-444.

  • Krishna C*, Tervi A*, Saffern M*, Wilson EA*, Yoo S-K, Mars N, Roudko V, Cho BA, Jones SE, Vaninov N, Selvan ME, Gumus ZH, FinnGen, Lenz TL, Merad M, Boffetta P, Martinez-Jimenez F, Ollila HM, Samstein RM, Chowell D. An immunogenetic basis for lung cancer risk. Science. 2024;383(6685):eadi3808.

  • Jermy B*, Läll K*, Wolford BN*, Wang Y, Zguro K, Cheng Y, Kanai M, Kanoni S, Yang Z, Hartonen T, Monti R, Wanner J, Youssef O, Lipper C, van Heel D, Okada Y, McCartney DL, Hayward C, Marioni RE, Furini S, Renieri A, Martin AR, Neale BM, Hveem K, Mägi R, Palotie A, Heyne H, Mars N, Ganna A, Ripatti S. A unified framework for estimating country-specific cumulative incidence for 18 diseases stratified by polygenic risk. Nat Commun. 2024;15(1):5007.