Research

Statistical genetics & bioinformatics

I am interested in statistical methods for genetic epidemiology. Some methodological work done with colleagues, students and postdocs, include:

Causal inference

As far as possible, we adopt the triangulation of evidence principle, including observational analysis, Mendelian randomization (MR), mediation analysis, and other techniques to assess causal pathways in molecular epidemiology.

  • In the field of atrial fibrillation research, following a strong observational association, supported by independent replication, we implemented a complex MR analysis plan that uncovered a case of perfect confounder (Circ Genom Precis Med 2019), where BMI was entirely explaining a spurious association between a phospholipid and atrial conduction.

  • We used MR analysis for laboratory experiment prioritization, uncovering for the first time and confirming the causal role of an antisense RNA on the regulation of the desmoplakin gene, which is now a potential therapeutic target for desmoplakin-related diseases (Hum Genet 2025).

  • Additional work on causal inference concerned kidney function, with applications (NDT 2017), reviews (JASN 2016) and commentaries (Cardiovasc Res 2022).

Kidney function genetic epidemiology

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 (Freiburg University) and me. The CKDGen includes >120 studies from all continents, totaling >1 million participants.

Our work is summarized in a perspective commentary (Kidney Int 2020).

Among others, GWAS were conducted on eGFR (Nat Genet 2019, Nat Commun 2016, PLoS Genet 2012, Nat Genet 2010) and albuminuria (Nat Commun 2019, Diabetes 2016), including cross-trait investigations of the X chromosome (Nat Commun 2024).

GWAS summary statistics can be found here.

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 N=13,393). For more information, see the CHRIS cohort profile (Int J Epidemiol 2025), the protocol paper (J Transl Med 2015) and biochemistry methods (Hum Genet 2017).

Our epidemiological research on specific study aspects has included pain sensitivity (J Pain 2018), smoking and heart rate variability (PLoS ONE 2019), nutrition (J Nephrol 2023), and kidney diseases (J Nephrol 2025), among others.

On the genomics side, a recent study on the genetic basis of complement activation was particularly fascinating (Cell Rep 2024).

COVID-19

During the pandemic, my group has been involved in population-based studies on COVID-19. We designed and planned the CHRIS COVID-19 study (Pathog Glob Health 2021), constituted by a population-representative sample and a one-year follow-up. We observed that contextual determinants reflecting the course of the pandemic were predominant compared to individual sociodemographic characteristics in explaining SARS-CoV-2 testing probability (Pathog Glob Health 2023). Further modeling of COVID-19 symptom distribution over time demonstrated that regular symptom tracking even in small, population-representative samples is an effective screening tool for monitoring a pandemic during its course (BMJ Open 2023). We also estimated prevalence and determinant of SARS-CoV-2 infections in the Gardena valley (Epidemiol Infect 2021).