Dr. Jon Krohn
Tel: 01865 287680
Broadly, I'm interested in the many factors that interact together to explain our characteristic traits. These factors could be genetic factors that one is born with ("nature") or they may be environmental factors related to an individual's unique life experience ("nurture"). The characteristic traits ("phenotypes") that I investigate range from relatively simple biochemical traits (e.g., cholesterol levels) to highly complex traits like behaviour (e.g., reactions to new experiences) and disease (e.g., Multiple Sclerosis).
To carry out my research, I develop and apply a variety of statistical techniques (both frequentist and Bayesian) to large data sets (such as those derived from heterogeneous stock mice) in attempts to find reliable relationships between phenotypes (e.g., disease-related traits) and their many potential predicting factors (e.g., genetic markers, gene expression data, brain imaging results, and environmental variables). Once these relationships are established, I employ algorithms intended to identify the causal pathways by which these factors are related. For example, a particular genetic sequence may affect the extent to which a gene is expressed in the central nervous system, which in turn may influence an individual's experience-specific susceptibility to anxiety and depression. Once potential causal pathways are determined in this way, other researchers can subsequently perform experiments (e.g., gene knockout, conditional transgenic) to verify the validity of the candidate causal mechanism.
Ultimately, understanding the biological pathways underlying disease could lead to the identification of therapeutic drug targets, while recognition of the aspects of an individual's environment that contribute to the disease can inform preventative measures. In the case of anxiety and depression, this translates to improved quality of life for those who are afflicted.
An outline of my ongoing interests and activities is available on my personal website, jonkrohn.com.
Factors influencing success of clinical genome sequencing across a broad spectrum of disorders. Taylor J, Martin H, Lise S, Broxholme J, Cazier J-P, Rimmer A, et al. Nature Genetics
- Genetic interactions with sex make a relatively small contribution to the heritability of complex traits in mice. Krohn J, Speed D, Palme R, Touma C, Mott R, Flint J. PLoS ONE 9: e96450
- Sex-stratified genome-wide association studies in 270,000 individuals show evidence for sexual dimorphism in genetic loci for anthropometric traits. Randall JC, Winkler TW, Kutalik Z, Berndt SI, Jackson AU, et al. PLoS Genetics 9: e1003500
- Sparse Instrumental Variables: an integrative approach to biomarker validation. Agakov F, Krohn J, Colombo M, McKeigue P. Journal of Epidemiology and Community Health 65: A10
- A comparison of exogenous promoter activity at the ROSA26 locus using a PhiC31 integrase mediated cassette exchange approach in mouse ES cells. Chen C-M, Krohn J, Bhattacharya S, Davies B. PLoS ONE 6: e23376
- Inference of causal relationships between biomarkers and outcomes in high dimensions. Agakov F, McKeigue P, Krohn J, Flint J. Journal of Systemics, Cybernetics and Informatics 9: 1-8
- Association of UV radiation with multiple sclerosis prevalence and sex ratio in France. Orton S, Wald L, Confavreux C, Vukusic S, Krohn J, Ramagopalan S, Herrera B, Sadovnick A, Ebers G. Neurology 76: 425-31
- Inference of causal relationships between biomarkers and outcomes in high dimensions. Agakov F, McKeigue P, Krohn J, Flint J. Proceedings of the Fourth International Symposium on Bio- and Medical Informatics and Cybernetics (selected as top paper from amongst seven in its category)
- Sparse Instrumental Variables (SPIV) for genome-wide studies. Agakov F, McKeigue P, Krohn J, Storkey A. Advances in Neural Information Processing Systems 23 (Edited by: J Lafferty, C Williams, J Shawe-Taylor, R Zemel & A Culotta)
- Exposure to a context previously associated with nausea elicits conditioned gaping in rats: A model of anticipatory nausea. Limebeer CL, Krohn JP, Cross-Mellor S, Litt DE, Ossenkopp K-P, Parker LA. Behav Brain Res 187: 33-40
In preparation in 2014:
- Networks of gene expression data in heterogeneous stock mice. Krohn J, Mott R, Flint J.
- Fine-Mapping QTL and Inferring Causal Pathways that Underlie Sixty Murine Phenotypes. Mouse Genetics conference in Washington, D.C. (selected as "Outstanding Student Presentation" from a field of sixteen students)
- Gene-by-Environment Interactions Underlying Anxiety Across Six Murine Experiments. Complex Trait Community conference at Northwestern University in Chicago
- Sex-by-Gene Interactions in 100 Murine Phenotypes Investigated by Resample Model Averaging. European Mathematical Genetics Meeting at the University of Oxford
- Early-onset mood and anxiety problems: the role of early life adversities, epigenetic mechanisms and continuing brain development. Magdalen College, University of Oxford
Statistics, neuroscience, genetics
Statistics, Bayesian, frequentist, R, Matlab, Perl, Unix, SQL, LaTeX, neuroscience, genetics, anxiety, depression, fear-related behaviour, gene expression, DNA, RNA, causal pathway.