Environmental exposures (both organic and inorganic) modulate the immune system. In our research we employ systems biology approaches to investigate the relevance of this phenomena in the development of allergies.
Karelian Allergy Project - KARA

This study focuses on the regions of Finnish and Russian Karelia, which are geographically very similar, but have a dramatic difference in the prevalence of allergies and asthma. The biodiversity hypothesis suggests that reduced exposure to diverse environmental microbes has resulted in the current increase in chronic inflammatory diseases in western societies. We have shown that the living environment, the skin microbiota, and the prevalence of allergies are interrelated, with children living in more rural areas having a richer microbiota on their skin, and suffering less frequently from allergic diseases compared with children living in the cities. Currently we are investigating in depth the association between genome-wide epigenetic markers and gene expression profiles in blood leukocytes, the composition of the skin microbiota, and the living environment of these children.

Microbe-Gene Interactions in Allergy and Autoimmunity Related to the Skin

The MAARS project is an EU-funded, international study exploring the nature and duration of microbial stimuli and associated changes in the epithelial barrier leading to the development of skin-related allergy and autoimmunity. Atopic dermatitis and psoriasis serve as models for investigation of the programming of the immune system towards an allergic or autoimmune inflammation. The aim of the study is to identify microbe-host-interaction networks involved in the initiation, development and persistence of atopic dermatitis and psoriasis. The project will pave the way for progress in prevention, new diagnostic strategies and treatment options for allergy and autoimmunity related skin diseases.

Microbiome Dynamics Upon Exposure to Engineered Nanomaterials

This Academy of Finland funded project seeks to; define the molecular mechanisms that drive changes in the microbiome, identify transcriptional responses that engineered nanomaterials (ENM) cause on the body surfaces including skin and lungs, and study how these two systems are interrelated. Nanosized zinc oxide (ZnO), titanium dioxide (TiO2) and silver (Ag) are used as model particles in this project because they are commonly employed components of antimicrobial coatings on devices and in several products such as cosmetics, (sun) creams and clothes. The effects of ENM exposure to local microbiome are studied by 16S rRNA sequencing, gene expression arrays or RNAseq. Advanced tools for multi-omic data integration are then are used to combine the different data layers to understand the complex biological processes that characterize transitions between microbiome types. Knowledge of the biological effects of ENM exposure and the mechanisms behind them should improve understanding of microbe-host interactions, enhance the design of ENM-based diagnostics and treatments in nanomedicine and provide a framework for risk assessment of nanomaterials.


Safety is a prerequisite to the continued success of nanotechnology and nanomedicine, therefore it is critical to develop methods that give better prediction of the biological effects and risks of engineered nanomaterials (ENM) for human health and the environment. Simple, fast, cost efficient, and yet reliable methods are required to meet the challenge of the ever-decreasing time between the development of new ENM and their marketing. The overarching aim of nanosafety, like our recently completed EU-funded  NANOSOLUTIONS project, is to provide a means to develop a classification of ENM based on an understanding of their potentially adverse interactions with living organisms at the molecular, cellular, and organism levels.

Due to the vast array of ENM that need to be tested, our ongoing objectives are to determine the “biological identity” of ENM, i.e. to assess global expression levels of mRNA, miRNA and proteins from cells and organisms in response to ENM, which can then be used to develop a computational predictive tool for the assessment of ENM safety, i.e. ENM SAFETY CLASSIFIER.

We also work with other groups to develop non-animal based methods that can be used for highthroughput screening and prioritizing of ENM for health hazard assessment.