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Artyomov, M. N.

Publications and source records attributed to Artyomov, M. N..

2 recordsLinked to original sources

Dietary intake regulates the circulating inflammatory monocyte pool

Caloric restriction is known to improve inflammatory and autoimmune diseases. However, the mechanisms by which reduced caloric intake modulates inflammation are poorly understood. Here we show that short-term fasting reduced monocyte metabolic and inflammatory activity and drastically reduced the number of circulating monocytes. Regulation of peripheral monocyte numbers was dependent on dietary glucose and protein levels. Specifically, we found that activation of the low-energy sensor 5-AMP-activated protein kinase (AMPK) in hepatocytes and suppression of systemic CCL2 production by peroxisome proliferator-activator receptor alpha (PPAR) reduced monocyte mobilization from the bone marrow. Importantly, while caloric restriction improves chronic inflammatory diseases, fasting did not compromise monocyte emergency mobilization during acute infectious inflammation and tissue repair. These results reveal that caloric intake and liver energy sensors dictate the blood and tissue immune tone and link dietary habits to inflammatory disease outcome.\n\nHighlightsO_LIFasting reduces the numbers of peripheral pro-inflammatory monocytes in healthy humans and mice.\nC_LIO_LIA hepatic AMPK-PPAR energy-sensing axis controls homeostatic monocyte numbers via regulation of steady-state CCL2 production.\nC_LIO_LIFasting reduces monocyte metabolic and inflammatory activity.\nC_LIO_LIFasting improves chronic inflammatory diseases but does not compromise monocyte emergency mobilization during acute infectious inflammation and tissue repair.\nC_LI

immunology

A platform for case-control matching enables association studies without genotype sharing

Acquiring a sufficiently powered cohort of control samples can be time consuming or, sometimes, impossible. Accordingly, an ability to leverage control samples that were already collected and sequenced elsewhere could dramatically improve power in all genetic association studies. However, since majority of the genotyped and sequenced human DNA samples to date are subject to strict data sharing regulations, large-scale sharing of, in particular, control samples is extremely challenging. Using insights from image recognition, we developed a method allowing selection of the best-matching controls in an external pool of samples that is compliant with personal genotype data protection restrictions. Our approach uses singular value decomposition of the matrix of case genotypes to rank controls in another study by similarity to cases. We demonstrate that this recovers an accurate case-control association analysis for both ultra-rare and common variants and implement and provide online access to a library of ~17,000 controls that enables association studies for case cohorts lacking control subjects.

genetics