Biology subjects

Enroth, S.

Publications and source records attributed to Enroth, S..

4 recordsLinked to original sources

bioRxiv2020

Genomic evaluation of circulating proteins for drug target characterisation and precision medicine

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. By mapping and replicating protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, we identified 467 pQTLs for 85 proteins. The pQTLs were used in combination with other sources of information to evaluate known drug targets, and suggest new target candidates or repositioning opportunities, underpinned by a) causality assessment using Mendelian randomization, b) pathway mapping using trans-pQTL gene assignments, and c) protein-centric polygenic risk scores enabling matching of plausible target mechanisms to sub-groups of individuals enabling precision medicine.

genetics↗

bioRxiv2019

Loss of Y in leukocytes, dysregulation of autosomal immune genes and disease risks

Mosaic loss of chromosome Y (LOY) in leukocytes has been associated with many diseases, yet it remains unclear whether this form of clonal mosaicism exerts a direct physiological effect. Here we perform single-cell and bulk RNA sequencing in leukocytes, observing considerable variation in the rate of LOY across individuals, cell types and disease state. Cells with LOY demonstrated a profound degree of transcriptional dysregulation impacting [~]500 autosomal genes. These genes are preferentially involved in immune functions but also encode proteins with roles in other diverse biological processes. Our findings highlight a surprisingly broad role for chromosome Y challenging the view of it as a "genetic wasteland". Furthermore, they support the hypothesis that altered immune function in leukocytes is a mechanism directly linking LOY to disease.

immunology↗

bioRxiv2018

High throughput proteomics identifies 484 high-accuracy plasma protein biomarker signatures for ovarian cancer

Ovarian cancer is usually detected at a late stage with the 5-year survival at only 30-40%. Additional means for early detection and improved diagnosis are acutely needed. To search for novel biomarkers, we compared circulating plasma levels of 981 proteins in patients with ovarian cancer and benign tumours, using the proximity extension assay. A novel combinatorial strategy was developed for identification of multivariate biomarker signatures, resulting in 484 mutually exclusive models out of which 448 did not contain the present biomarker MUCIN-16. The top-ranking model consisted of 14 proteins and had a AUC=0.95, PPV=1.0, sensitivity=0.99 and specificity=1.0 for detection of stage III-IV ovarian cancer in the discovery data, and an AUC=0.89, PPV=0.93, sensitivity=0.89 and specificity=0.95 in the replication data. The novel plasma protein signature could be used to improve the diagnosis of women with adnexal ovarian mass or in screening to identify women that should be referred to specialized examination.

cancer biology↗

bioRxiv2018

New genetic signals for lung function highlight pathways and pleiotropy, and chronic obstructive pulmonary disease associations across multiple ancestries

Reduced lung function predicts mortality and is key to the diagnosis of COPD. In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, one-half of which are new. In combination these variants strongly predict COPD in deeply-phenotyped patient populations. Furthermore, the combined effect of these variants showed generalisability across smokers and never-smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD.

genomics↗