A robust mean and variance test with application to high-dimensional phenotypes

Most studies of continuous health-related outcomes examine differences in mean levels (location) of the outcome by exposure. However, identifying effects on the variability (scale) of an outcome, and combining tests of mean and variability (location-and-scale), could provide additional insights into biological mechanisms. A joint test could improve power for studies of high-dimensional phenotypes, such as epigenome-wide association studies of DNA methylation at CpG sites. One possible cause of heterogeneity of variance is a variable interacting with exposure in its effect on outcome, so a joint test of mean and variability could help in the identification of effect modifiers. Here, we review a scale test, based on the Brown-Forsythe test, for analysing variability of a continuous outcome with respect to both categorical and continuous exposures, and develop a novel joint location-and-scale score (JLSsc) test. These tests were compared to alternatives in simulations and used to test associations of mean and variability of DNA methylation with gender and gestational age using data from the Accessible Resource for Integrated Epigenomics Studies (ARIES). In simulations, the Brown-Forsythe and JLSsc tests retained correct type I error rates when the outcome was not normally distributed in contrast to the other approaches tested which all had inflated type I error rates. These tests also identified > 7500 CpG sites for which either mean or variability in cord blood methylation differed according to gender or gestational age. The Brown-Forsythe test and JLSsc are robust tests that can be used to detect associations not solely driven by a mean effect

The Roles and Acting Mechanism of Caenorhabditis elegans DNase II Genes in Apoptotic DNA Degradation and Development

DNase II enzymes are acidic endonucleases that have been implicated in mediating apoptotic DNA degradation, a critical cell death execution event. C. elegans genome contains three DNase II homologues, NUC-1, CRN-6, and CRN-7, but their expression patterns, acting sites, and roles in apoptotic DNA degradation and development are unclear. We have conducted a comprehensive analysis of three C. elegans DNase II genes and found that nuc-1 plays a major role, crn-6 plays an auxiliary role, and crn-7 plays a negligible role in resolving 3′ OH DNA breaks generated in apoptotic cells. Promoter swapping experiments suggest that crn-6 but not crn-7 can partially substitute for nuc-1 in mediating apoptotic DNA degradation and both fail to replace nuc-1 in degrading bacterial DNA in intestine. Despite of their restricted and largely non-overlapping expression patterns, both CRN-6 and NUC-1 can mediate apoptotic DNA degradation in many cells, suggesting that they are likely secreted nucleases that are retaken up by other cells to exert DNA degradation functions. Removal or disruption of NUC-1 secretion signal eliminates NUC-1's ability to mediate DNA degradation across its expression border. Furthermore, blocking cell corpse engulfment does not affect apoptotic DNA degradation mediated by nuc-1, suggesting that NUC-1 acts in apoptotic cells rather than in phagocytes to resolve 3′ OH DNA breaks. Our study illustrates how multiple DNase II nucleases play differential roles in apoptotic DNA degradation and development and reveals an unexpected mode of DNase II action in mediating DNA degradation

U.S. Billion-ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry

The Report, Biomass as Feedstock for a Bioenergy and Bioproducts Industry: The Technical Feasibility of a Billion-Ton Annual Supply (generally referred to as the Billion-Ton Study or 2005 BTS), was an estimate of “potential” biomass within the contiguous United States based on numerous assumptions about current and future inventory and production capacity, availability, and technology. In the 2005 BTS, a strategic analysis was undertaken to determine if U.S. agriculture and forest resources have the capability to potentially produce at least one billion dry tons of biomass annually, in a sustainable manner—enough to displace approximately 30% of the country’s present petroleum consumption. To ensure reasonable confidence in the study results, an effort was made to use relatively conservative assumptions. However, for both agriculture and forestry, the resource potential was not restricted by price. That is, all identified biomass was potentially available, even though some potential feedstock would more than likely be too expensive to actually be economically available. In addition to updating the 2005 study, this report attempts to address a number of its shortcoming

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Tumour brain: pre‐treatment cognitive and affective disorders caused by peripheral cancers

People that develop extracranial cancers often display co-morbid neurological disorders, such as anxiety, depression and cognitive impairment, even before commencement of chemotherapy. This suggests bidirectional crosstalk between non-CNS tumours and the brain, which can regulate peripheral tumour growth. However, the reciprocal neurological effects of tumour progression on brain homeostasis are not well understood. Here, we review brain regions involved in regulating peripheral tumour development and how they, in turn, are adversely affected by advancing tumour burden. Tumour-induced activation of the immune system, blood–brain barrier breakdown and chronic neuroinflammation can lead to circadian rhythm dysfunction, sleep disturbances, aberrant glucocorticoid production, decreased hippocampal neurogenesis and dysregulation of neural network activity, resulting in depression and memory impairments. Given that cancer-related cognitive impairment diminishes patient quality of life, reduces adherence to chemotherapy and worsens cancer prognosis, it is essential that more research is focused at understanding how peripheral tumours affect brain homeostasis

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease