Statistical genetics & bioinformatics
I am interested in developing methods for genetic epidemiology. Here is some methodological work done with the help of colleagues, PhD students, and PostDocs, to address issues we identified in applied projects:
- How recruitment-related issues may affect genetic heritability estimation in epidemiological studies (Hum Genet 2017) with Damia Noce
- Analysis of censored outcomes in the presence of family structure (Biom J 2016) with Fabiola Del Greco, John Thompson & Cosetta Minelli
- Relationship between pedigree completeness and power and type I error of linkage analysis (Hum Hered 2014) with Aude Saint-Pierre
- Algorithms for quality control of genome-wide association study (GWAS) results (Bioinformatics 2012) with Christian Fuchsberger & Daniel Taliun
- Statistical modeling of linkage disequilibrium (BMC Genomics 2008); Daniel Taliun extended the pattern recognition to the whole genome (BMC Bioinformatics 2014; IEEE/ACM Trans Comput Biol Bioinform 2016)
The CHRIS Study
Together with colleagues at Eurac Research, I am conducting the Cooperative Health Research In South Tyrol (CHRIS) study, a longitudinal population-based study aimed at assessing the molecular basis of human health and disease (baseline sample size 13,393). For more information, see the protocol paper J Transl Med 2015 and related publications:
Hum Genet 2017 (biochemical parameters),
J Pain 2018 (pain sensitivity questionnaire),
PLoS ONE 2019 (heart rate variability and smoking).
Genetic epidemiology of kidney function
I study the genetics of kidney function. Studies were and are being conducted mainly within the CKDGen Consortium, a large worldwide initiative aimed at characterizing the genetic background of kidney function and chronic kidney disease. The project is currently coordinated by Anna Köttgen (University of Freiburg) and myself. The CKDGen includes >120 studies from all continents, totaling nearly 1 million participants.
Some publications:
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