Doctoral Defense in Statistics - Garðar Sveinbjörnsson

Doctoral candidate:
Garðar Sveinbjörnsson

Title of thesis:
Utilizing sequence annotations in genome-wide association studies

Opponents:
Dr. Samuli Ripatti, Director of Institute for Molecular Medicine Finland (FIMM), University of Helsinki
Dr. Jóhanna Jakobsdóttir Assistant Professor at the Centre of Public Health Sciences, University of Iceland, 

Advisor:
Dr. Daníel F. Guðbjartsson, Vice President of applied Statistics, deCODE genetics.

Also in the doctoral committee:
Dr. Sigrún Helga Lund, Professor at the Faculty of Physical Sciences, University of Iceland
Dr. Patrick Sulem, Head of Clinical sequencing, deCODE genetics.

Chair of Ceremony:
Dr. Einar Örn Sveinbjörnsson, Professor and Head of the Faculty of Physical Sciences, University of Iceland.

Abstract:
In genome-wide associations studies (GWAS) sequence variants are tested for association with diseases or traits. The multiple testing burden in these studies is substantial and needs to be accounted for. The consensus approach has been to assign equal prior probability of association to all sequence variants tested and control the Family wise error rate (FWER) with a Bonferroni correction. However, sequence variants with certain annotations, such as protein coding variants, are more likely to associate than others. In article I we estimated the enrichment of association signals by sequence annotations. We proposed the use of a weighted Bonferroni adjustment that controls for the FWER, using as weights the enrichment of sequence annotations among association signals. We showed that this weighted adjustment increases the power to detect association over the standard Bonferroni correction. Articles II and III are GWASs of non-alcoholic fatty liver (NAFL) and dilated cardiomyopathy (DCM) that apply the proposed weighting scheme and explore sequence annotations of identified disease associations to understand the underlying biological mechanism. In article II we performed a GWAS of NAFL and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction (PDFF) extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and found rare, protective, predicted loss-of-function variants (pLOF) in MTARC1 and GPAM, underscoring them as potential drug targets. We leveraged messenger RNA expression, plasma proteomics and sequence annotation to identify putative causal genes. We analyzed levels plasma proteins in 35,559 and show that proteomics can potentially discriminate between NAFL and cirrhosis and outperform other biomarkers. Article III is a GWAS of DCM, an important cause of heart failure. Sequence variants causing DCM in Iceland were not known before the study. We performed a GWAS on DCM and identified two DCM variants in established cardiomyopathy genes, a missense variant p.Phe145Leu in NKX2-5 carried by 1 in 7100 Icelanders and a frameshift variant p.Phe1626Serfs*40 in FLNC carried by 1 in 3600 Icelanders. Both variants associated with heart failure and sudden cardiac death. In summary, we propose the use of a valuable method that increases power in GWAS by prioritizing variants in coding regions. In applications we provide important insights into NAFL pathogenesis and new therapeutic options. Finally, we identify rare coding variants that cause DCM and sudden death.

About the candidate:
Garðar Sveinbjörnsson was born in Reykjavik 1987. He earned a BSc in mathematics from the University of Iceland in 2007 and an MSc in statistics from ETH Zurich in 2012. Since 2013, he has been conducting research at deCODE Genetics, where he worked on the PhD thesis.