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Jennings, L. L.

Publications and source records attributed to Jennings, L. L..

2 recordsLinked to original sources

Human serum proteome profoundly overlaps with genetic signatures of disease

Circulating proteins are prognostic for human outcomes including cancer, heart failure, brain trauma and brain amyloid plaque burden. A deep serum proteome survey recently revealed close associations of serum protein networks and common diseases. The present study reveals unprecedented number of individual serum proteins that overlap genetic signatures of diseases emanating from different tissues of the body. Here, 54,469 low-frequency and common exome-array variants were compared with 4782 protein measurements in the serum of 5343 individuals of the deeply annotated AGES Reykjavik cohort. Using a study-wide significant threshold, 2019 independent exome array variants affecting levels of 2135 serum proteins were identified. These variants overlapped genetic loci for hundreds of complex disease traits, emphasizing the emerging role for serum proteins as biomarkers of and potential causative agents of multiple diseases.

genetics

Deep serum proteomics reveal biomarkers and causal candidates for type 2 diabetes

The prevalence of type 2 diabetes mellitus (T2DM) is expected to increase rapidly in the next decades, posing a major challenge to societies worldwide. The emerging era of precision medicine calls for the discovery of biomarkers of clinical value for prediction of disease onset, where causal biomarkers can furthermore provide actionable targets. Blood-based factors like serum proteins are in contact with every organ in the body to mediate global homeostasis and may thus directly regulate complex processes such as aging and the development of common chronic diseases. We applied a data-driven proteomics approach measuring serum levels of 4,137 proteins in 5,438 Icelanders to discover novel biomarkers for incident T2DM and describe the serum protein profile of prevalent T2DM. We identified 536 proteins associated with incident or prevalent T2DM. Through LASSO penalized logistic regression analysis combined with bootstrap resampling, a panel of 20 protein biomarkers that accurately predicted incident T2DM was identified with a significant incremental improvement over traditional risk factors. Finally, a Mendelian randomization analysis provided support for a causal role of 48 proteins in the development of T2DM, which could be of particular interest as novel therapeutic targets.

genetics