Grimur Hjörleifsson

Nonalcoholic fatty liver (NAFL) and its sequelae are growing health problems. We performed a genome-wide association study of NAFL, cirrhosis and hepatocellular carcinoma, and integrated the findings with expression and proteomic data. For NAFL, we utilized 9,491 clinical cases and proton density fat fraction extracted from 36,116 liver magnetic resonance images. We identified 18 sequence variants associated with NAFL and 4 with cirrhosis, and found rare, protective, predicted loss-of-function variants in MTARC1 and GPAM, underscoring them as potential drug targets. We leveraged messenger RNA expression, splicing and predicted coding effects to identify 16 putative causal genes, of which many are implicated in lipid metabolism. We analyzed levels of 4,907 plasma proteins in 35,559 Icelanders and 1,459 proteins in 47,151 UK Biobank participants, identifying multiple proteins involved in disease pathogenesis. We show that proteomics can discriminate between NAFL and cirrhosis. The present study provides insights into the development of noninvasive evaluation of NAFL and new therapeutic options.

Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.

The genus Streptomyces has proven to be a rich reservoir of specialized metabolites, accounting for 80% of all microbially produced antibiotics including chloramphenicol and nystatin from S. venezuelae and S. noursei respectively. However, the discovery of novel microbial chemistry is still greatly needed to combat antimicrobial resistance. Comparative metabolomics, using platforms such as Global Natural Products Social Molecular Networking (GNPS), as well as tools such as antiSMASH and BiGSCAPE have aided the mining of biosynthetic gene clusters (BGC’s) across datasets but comparing the chemistry to the encoding biosynthetic gene clusters is a significant bottleneck. In this study, ten Streptomyces strains were selected, based on phylogeny and availability of genome sequence. The strains were cultured on 6 types of Actinomycete-specific media to maximise metabolite diversity. Liquid Chromatography tandem Mass Spectrometry (LC-MS/MS) was used to obtain spectral data from crude metabolite extracts enabling comparative metabolomics analysis via the GNPS platform. As the genome sequences were publicly available, genome mining of BGC’s was achieved using antiSMASH resulting in 260 BGC’s across the ten strains. This revealed 53 gene cluster families when analysed using BiGSCAPE, the largest encoding for 8 metabolites. In future, both biosynthetic (BGC’s) and chemistry (parent ions) datasets will be computationally linked based on strain presence/absence. The development of standardised datasets that enable cross-‘omics comparison will aid prioritisation of novel antibiotics, especially when combined with bioactivity data.