Imputation Server PGS: an automated approach to calculate polygenic risk scores on imputation servers.

Polygenic scores (PGS) enable the prediction of genetic predisposition for a wide range of traits and diseases by calculating the weighted sum of allele dosages for genetic variants associated with the trait or disease in question. Present approaches for calculating PGS from genotypes are often inefficient and labor-intensive, limiting transferability into clinical applications. Here, we present 'Imputation Server PGS', an extension of the Michigan Imputation Server designed to automate a standardized calculation of polygenic scores based on imputed genotypes. This extends the widely used Michigan Imputation Server with new functionality, bringing the simplicity and efficiency of modern imputation to the PGS field. The service currently supports over 4489 published polygenic scores from publicly available repositories and provides extensive quality control, including ancestry estimation to report population stratification. An interactive report empowers users to screen and compare thousands of scores in a fast and intuitive way. Imputation Server PGS provides a user-friendly web service, facilitating the application of polygenic scores to a wide range of genetic studies and is freely available at https://imputationserver.sph.umich.edu.

Identification of regulatory networks and crosstalk factors in brown adipose tissue and liver of a cold-exposed cardiometabolic mouse model.

BACKGROUND: Activation of brown adipose tissue (BAT) has gained attention due to its ability to dissipate energy and counteract cardiometabolic diseases (CMDs). METHODS: This study investigated the consequences of cold exposure on the BAT and liver proteomes of an established CMD mouse model based on LDL receptor-deficient (LdlrKO) mice fed a high-fat, high-sucrose, high-cholesterol diet for 16 weeks. We analyzed energy metabolism in vivo and performed untargeted proteomics on BAT and liver of LdlrKO mice maintained at 22 °C or 5 °C for 7 days. RESULTS: We identified several dysregulated pathways, miRNAs, and transcription factors in BAT and liver of cold-exposed Ldlrko mice that have not been previously described in this context. Networks of regulatory interactions based on shared downstream targets and analysis of ligand-receptor pairs identified fibrinogen alpha chain (FGA) and fibronectin 1 (FN1) as potential crosstalk factors between BAT and liver in response to cold exposure. Importantly, genetic variations in the genes encoding FGA and FN1 have been associated with cardiometabolic-related phenotypes and traits in humans. DISCUSSION: This study describes the key factors, pathways, and regulatory networks involved in the crosstalk between BAT and the liver in a cold-exposed CMD mouse model. These findings may provide a basis for future studies aimed at testing whether molecular mediators, as well as regulatory and signaling mechanisms involved in tissue adaption upon cold exposure, could represent a target in cardiometabolic disorders.

Penetrance, cancer incidence and survival in HFE haemochromatosis-A population-based cohort study.

BACKGROUND AND AIMS: Haemochromatosis is characterized by progressive iron overload affecting the liver and can cause cirrhosis and hepatocellular carcinoma. Most haemochromatosis patients are homozygous for p.C282Y in HFE, but only a minority of individuals with this genotype will develop the disease. The aim was to assess the penetrance of iron overload, fibrosis, hepatocellular carcinoma and life expectancy. METHODS: A total of 8839 individuals from the Austrian region of Tyrol were genotyped for the p.C282Y variant between 1997 and 2021. Demographic, laboratory parameters and causes of death were assessed from health records. Penetrance, survival, and cancer incidence were ascertained from diagnosed cases, insurance- and cancer registry data. Outcomes were compared with a propensity score-matched control population. RESULTS: Median age at diagnosis in 542 p.C282Y homozygous individuals was 47.8 years (64% male). At genotyping, the prevalence of iron overload was 55%. The cumulative penetrance of haemochromatosis defined as the presence of provisional iron overload was 24.2% in males and 10.5% in females aged 60 years or younger. Among p.C282Y homozygotes of the same ages, the cumulative proportion of individuals without fibrosis (FIB-4 score < 1.3) was 92.8% in males and 96.7% in females. Median life expectancy was reduced by 6.8 years in individuals homozygous for p.C282Y when compared with population-matched controls (p = .001). Hepatocellular carcinoma incidence was not significantly higher in p.C282Y homozygotes than in controls matched for age and sex. CONCLUSION: Reduced survival and the observed age-dependent increase in penetrance among p.C282Y homozygotes call for earlier diagnosis of haemochromatosis to prevent complications.

Performing highly parallelized and reproducible GWAS analysis on biobank-scale data.

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.

Nuclear and mitochondrial genetic variants associated with mitochondrial DNA copy number.

Mitochondrial DNA copy number (mtDNA-CN) is a biomarker for mitochondrial dysfunction associated with several diseases. Previous genome-wide association studies (GWAS) have been performed to unravel underlying mechanisms of mtDNA-CN regulation. However, the identified gene regions explain only a small fraction of mtDNA-CN variability. Most of this data has been estimated from microarrays based on various pipelines. In the present study we aimed to (1) identify genetic loci for qPCR-measured mtDNA-CN from three studies (16,130 participants) using GWAS, (2) identify potential systematic differences between our qPCR derived mtDNA-CN measurements compared to the published microarray intensity-based estimates, and (3) disentangle the nuclear from mitochondrial regulation of the mtDNA-CN phenotype. We identified two genome-wide significant autosomal loci associated with qPCR-measured mtDNA-CN: at HBS1L (rs4895440, p = 3.39 × 10-13) and GSDMA (rs56030650, p = 4.85 × 10-08) genes. Moreover, 113/115 of the previously published SNPs identified by microarray-based analyses were significantly equivalent with our findings. In our study, the mitochondrial genome itself contributed only marginally to mtDNA-CN regulation as we only detected a single rare mitochondrial variant associated with mtDNA-CN. Furthermore, we incorporated mitochondrial haplogroups into our analyses to explore their potential impact on mtDNA-CN. However, our findings indicate that they do not exert any significant influence on our results.