bims-ciryme 2022-06-05 papers

Nucleic Acids Res. 2022 Jun 03. pii: gkac419. [Epub ahead of print]

CircadiOmics: circadian omic web portal.

Muntaha Samad, Forest Agostinelli, Tomoki Sato, Kohei Shimaji, Pierre Baldi.

Circadian rhythms are a foundational aspect of biology. These rhythms are found at the molecular level in every cell of every living organism and they play a fundamental role in homeostasis and a variety of physiological processes. As a result, biomedical research of circadian rhythms continues to expand at a rapid pace. To support this research, CircadiOmics (http://circadiomics.igb.uci.edu/) is the largest annotated repository and analytic web server for high-throughput omic (e.g. transcriptomic, metabolomic, proteomic) circadian time series experimental data. CircadiOmics contains over 290 experiments and over 100 million individual measurements, across >20 unique tissues/organs, and 11 different species. Users are able to visualize and mine these datasets by deriving and comparing periodicity statistics for oscillating molecular species including: period, amplitude, phase, P-value and q-value. These statistics are obtained from BIO_CYCLE and JTK_CYCLE and are intuitively aggregated and displayed for comparison. CircadiOmics is the most up-to-date and cutting-edge web portal for searching and analyzing circadian omic data and is used by researchers around the world.

DOI: https://doi.org/10.1093/nar/gkac419

PLoS Genet. 2022 Jun;18(6): e1010162

Using genetic variation to disentangle the complex relationship between food intake and health outcomes.

Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

DOI: https://doi.org/10.1371/journal.pgen.1010162

Diabetes. 2022 Jun 03. pii: dbi220004. [Epub ahead of print]

The Liver-Alpha Cell Axis in Health and in Disease.

Michael M Richter, Katrine D Galsgaard, Emilie Elmelund, Filip K Knop, Malte P Suppli, Jens J Holst, Marie Winther-Sørensen, Sasha A S Kjeldsen, Nicolai J Wewer Albrechtsen.

Glucagon and insulin are the main regulators of blood glucose. While the actions of insulin are extensively mapped, less is known about glucagon. Besides glucagon's role in glucose homeostasis, there are additional links between the pancreatic alpha cells and the hepatocytes, often collectively referred to as the liver-alpha cell axis, which may be of importance for health and disease. Thus, glucagon receptor antagonism (pharmacological or genetic), which disrupts the liver-alpha cell axis, not only results in lower fasting glucose, but also in reduced amino acid turnover, and dyslipidemia. Here, we review the actions of glucagon on glucose homeostasis, amino acid catabolism, and lipid metabolism in the context of the liver-alpha cell axis. The concept of glucagon resistance is also discussed, and we argue that the various elements of the liver-alpha cell axis may be differentially affected in metabolic diseases such as diabetes, obesity, and non-alcoholic fatty liver disease (NAFLD). This conceptual rethinking of glucagon biology may explain why patients with type 2 diabetes have hyperglucagonemia and how NAFLD disrupts the liver-alpha cell axis, compromising the normal glucagon-mediated enhancement of substrate-induced amino acid turnover and possibly fatty acid beta-oxidation. Glucagon-induced glucose production may, in contrast to amino acid catabolism, however not be affected by NAFLD explaining the diabetogenic effect of NAFLD-associated hyperglucagonemia. Consideration of the liver-alpha cell axis is essential to understand the complex pathophysiology underlying diabetes and other metabolic diseases.

DOI: https://doi.org/10.2337/dbi22-0004