Claudia Lamina

Genome-wide association studies (GWAS) are transforming genetic research and enable the detection of novel genotype-phenotype relationships. In the last two decades, over 60 000 genetic associations across thousands of traits have been discovered using a GWAS approach. Due to increasing sample sizes, researchers are increasingly faced with computational challenges. A reproducible, modular and extensible pipeline with a focus on parallelization is essential to simplify data analysis and to allow researchers to devote their time to other essential tasks. Here we present nf-gwas, a Nextflow pipeline to run biobank-scale GWAS analysis. The pipeline automatically performs numerous pre- and post-processing steps, integrates regression modeling from the REGENIE package and supports single-variant, gene-based and interaction testing. It includes an extensive reporting functionality that allows to inspect thousands of phenotypes and navigate interactive Manhattan plots directly in the web browser. The pipeline is tested using the unit-style testing framework nf-test, a crucial requirement in clinical and pharmaceutical settings. Furthermore, we validated the pipeline against published GWAS datasets and benchmarked the pipeline on high-performance computing and cloud infrastructures to provide cost estimations to end users. nf-gwas is a highly parallelized, scalable and well-tested Nextflow pipeline to perform GWAS analysis in a reproducible manner.

Mitochondrial dysfunction is a common occurrence in the aging process and is observed in diseases such as age-related macular degeneration (AMD). Increased levels of reactive oxygen species lead to damaged mitochondrial DNA (mtDNA), resulting in dysfunctional mitochondria, and, consequently, mtDNA causes further harm in the retinal tissue. However, it is unclear whether the effects are locally restricted to the high-energy-demanding retinal pigment epithelium or are also systematically present. Therefore, we measured mtDNA copy number (mtDNA-CN) in peripheral blood using a qPCR approach with plasmid normalization in elderly participants with and without AMD from the AugUR study (n = 2262). We found significantly lower mtDNA-CN in the blood of participants with early (n = 453) and late (n = 170) AMD compared to AMD-free participants (n = 1630). In regression analyses, we found lower mtDNA-CN to be associated with late AMD when compared with AMD-free participants. Each reduction of mtDNA-CN by one standard deviation increased the risk for late AMD by 24%. This association was most pronounced in geographic atrophy (OR = 1.76, 95% CI 1.19–2.60, p = 0.004), which has limited treatment options. These findings provide new insights into the relationship between mtDNA-CN in blood and AMD, suggesting that it may serve as a more accessible biomarker than mtDNA-CN in the retina.