Glycolysis is a ubiquitous pathway thought to be essential for the production of oil in developing seeds of Arabidopsis thaliana and oil crops. Compartmentation of primary metabolism in developing embryos poses a significant challenge for testing this hypothesis and for the engineering of seed biomass production. It also raises the question whether there is a preferred route of carbon from imported photosynthate to seed oil in the embryo. Plastidic pyruvate kinase catalyzes a highly regulated, ATP-producing reaction of glycolysis. The Arabidopsis genome encodes 14 putative isoforms of pyruvate kinases. Three genes encode subunits α, β1, and β2 of plastidic pyruvate kinase. The plastid enzyme prevalent in developing seeds likely has a subunit composition of 4α4β1, is most active at pH 8.0, and is inhibited by Glu. Disruption of the gene encoding the β1 subunit causes a reduction in plastidic pyruvate kinase activity and 60% reduction in seed oil content. The seed oil phenotype is fully restored by expression of the β1 subunit–encoding cDNA and partially by the β2 subunit–encoding cDNA. Therefore, the identified pyruvate kinase catalyzes a crucial step in the conversion of photosynthate into oil, suggesting a preferred plastid route from its substrate phosphoenolpyruvate to fatty acids.
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Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury1–4. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries5. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction.
Chronic obstructive pulmonary disease (COPD) is associated with age and smoking, but other determinants of the disease are incompletely understood. Clonal hematopoiesis of indeterminate potential (CHIP) is a common, age-related state in which somatic mutations in clonal blood populations induce aberrant inflammatory responses. Patients with CHIP have an elevated risk for cardiovascular disease, but the association with COPD remains unclear. We analyzed whole-genome and exome sequencing data to detect CHIP in 48,835 subjects, of whom 8,444 had moderate-to-very-severe COPD, from four separate cohorts with COPD phenotyping and smoking history. We measured emphysema in murine models in which Tet2 was deleted in hematopoietic cells. In COPDGene, individuals with CHIP had a risk of moderate-to-severe and severe or very severe COPD 1.6 and 2.2 times greater than non-carriers, respectively (adjusted 95% confidence intervals [CI], 1.1 to 2.2 and 1.5 to 3.2). These findings were consistent observed in three additional cohorts and meta-analyses of all subjects. CHIP was also associated with decreased FEV1% predicted in COPDGene (mean between group difference -5.7%; adjusted 95% CI, -8.8 to -2.6), a finding replicated in additional cohorts. Smoke exposure was associated with a small but significant increased risk of having CHIP (OR 1.03 per ten pack-years, 95% CI 1.01-1.05) in the meta-analysis of all subjects. Inactivation of Tet2 in mouse hematopoietic cells exacerbated emphysema development and inflammation in cigarette smoke exposure models. Somatic mutations in blood cells are associated with the development and severity of COPD, independent of age and cumulative smoke exposure.
Background Prognostic tools are required to guide clinical decision-making in COVID-19. Methods We studied the relationship between the ratio of interleukin (IL)-6 to IL-10 and clinical outcome in 80 patients hospitalized for COVID-19, and created a simple 5-point linear score predictor of clinical outcome, the Dublin-Boston score. Clinical outcome was analysed as a three-level ordinal variable (“Improved”, “Unchanged”, or “Declined”). For both IL-6:IL-10 ratio and IL-6 alone, we associated clinical outcome with a) baseline biomarker levels, b) change in biomarker level from day 0 to day 2, c) change in biomarker from day 0 to day 4, and d) slope of biomarker change throughout the study. The associations between ordinal clinical outcome and each of the different predictors were performed with proportional odds logistic regression. Associations were run both “unadjusted” and adjusted for age and sex. Nested cross-validation was used to identify the model for incorporation into the Dublin-Boston score. Findings The 4-day change in IL-6:IL-10 ratio was chosen to derive the Dublin-Boston score. Each 1 point increase in the score was associated with a 5.6 times increased odds for a more severe outcome (OR 5.62, 95% CI -3.22–9.81, P = 1.2 × 10 −9 ). Both the Dublin-Boston score and the 4-day change in IL-6:IL-10 significantly outperformed IL-6 alone in predicting clinical outcome at day 7. Interpretation The Dublin-Boston score is easily calculated and can be applied to a spectrum of hospitalized COVID-19 patients. More informed prognosis could help determine when to escalate care, institute or remove mechanical ventilation, or drive considerations for therapies. Funding Funding was received from the Elaine Galwey Research Fellowship, American Thoracic Society, National Institutes of Health and the Parker B Francis Research Opportunity Award.
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