Sex differences in viral entry protein expression and host transcript responses to SARS-CoV-2.

Epidemiological studies suggest that men exhibit a higher mortality rate to COVID-19 than women, yet the underlying biology is largely unknown. Here, we seek to delineate sex differences in the gene expression of viral entry proteins ACE2 and TMPRSS2, and host transcriptional responses to SARS-CoV-2 through large-scale analysis of genomic and clinical data. We first compiled 220,000 human gene expression profiles from three databases and completed the meta-information through machine learning and manual annotation. Large scale analysis of these profiles indicated that male samples show higher expression levels of ACE2 and TMPRSS2 than female samples, especially in the older group (>60 years) and in the kidney. Subsequent analysis of 6,031 COVID-19 patients at Mount Sinai Health System revealed that men have significantly higher creatinine levels, an indicator of impaired kidney function. Further analysis of 782 COVID-19 patient gene expression profiles taken from upper airway and blood suggested men and women present distinct expression changes. Computational deconvolution analysis of these profiles revealed male COVID-19 patients have enriched kidney-specific mesangial cells in blood compared to healthy patients. Together, this study suggests biological differences in the kidney between sexes may contribute to sex disparity in COVID-19.

Rationale and Design of Family-Based Approach in a Minority Community Integrating Systems-Biology for Promotion of Health (FAMILIA).

BACKGROUND: The 2020 American Heart Association Impact Goal aims to improve cardiovascular health of all Americans by 20% while reducing deaths from cardiovascular disease and stroke by 20%. A large step toward this goal would be to better understand and take advantage of the significant intersection between behavior and biology across the entire life-span. In the proposed FAMILIA studies, we aim to directly address this major knowledge and clinical health gap by implementing an integrated family-centric health promotion intervention and focusing on the intersection of environment and behavior, while understanding the genetic and biologic basis of cardiovascular disease. METHODS: We plan to recruit 600 preschool children and their 600 parents or caregivers from 12-15 Head Start schools in Harlem, NY, and perform a 2:1 (2 intervention/1 control) cluster randomization of the schools. The preschool children will receive our intensive 37-hour educational program as the intervention for 4 months. For the adults, those in the "intervention" group will be randomly assigned to 1 of 2 intervention programs: an "individual-focused" or "peer-to-peer based." The primary outcome in children will be a composite score of knowledge (K), attitudes (A), habits (H), related to body mass index Z score (B), exercise (E), and alimentation (A) (KAH-BEA), using questionnaires and anthropometric measurements. For adults, the primary outcome will be a composite score for behaviors/outcomes related to blood pressure, exercise, weight, alimentation (diet) and tobacco (smoking; Fuster-BEWAT score). Saliva will be collected from the children for SNP genotyping, and blood will be collected from adults for RNA sequencing to identify network models and predictors of primary prevention outcomes. CONCLUSION: The FAMILIA studies seek to demonstrate that targeting a younger age group (3-5 years) and using a family-based approach may be a critical strategy in promoting cardiovascular health across the life-span.

The Self-Directed Biological Transformation Initiative and Well-Being.

OBJECTIVE: To examine the effects of a comprehensive residential mind-body program on well-being. DESIGN: The Self-Directed Biological Transformation Initiative was a quasi-randomized trial comparing the effects of participation in a 6-day Ayurvedic system of medicine-based comprehensive residential program with a 6-day residential vacation at the same retreat location. SETTING: Retreat setting. PARTICIPANTS: 69 healthy women (n = 58) and men (n = 11) (mean age ± standard deviation, 53.6 ± 12 years). INTERVENTION: The Ayurvedic intervention addressed physical and emotional well-being through group meditation and yoga, massage, diet, adaptogenic herbs, lectures, and journaling. OUTCOME MEASURES: A battery of standardized questionnaires. RESULTS: Participants in the Ayurvedic program showed significant and sustained increases in ratings of spirituality (p < 0.01) and gratitude (p < 0.05) compared with the vacation group, which showed no change. The Ayurvedic participants also showed increased ratings for self-compassion (p < 0.01) as well as less anxiety at the 1-month follow-up (p < 0.05). CONCLUSIONS: Findings suggest that a short-term intensive program providing holistic instruction and experience in mind-body healing practices can lead to significant and sustained increases in perceived well-being and that relaxation alone is not enough to improve certain aspects of well-being.

Causal inference in biology networks with integrated belief propagation.

Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.

NEW: network-enabled wisdom in biology, medicine, and health care.

Complete repertoires of molecular activity in and between tissues provided by new high-dimensional "omics" technologies hold great promise for characterizing human physiology at all levels of biological hierarchies. The combined effects of genetic and environmental perturbations at any level of these hierarchies can lead to vicious cycles of pathology and complex systemic diseases. The challenge lies in extracting all relevant information from the rapidly increasing volumes of omics data and translating this information first into knowledge and ultimately into wisdom that can yield clinically actionable results. Here, we discuss how molecular networks are central to the implementation of this new biology in medicine and translation to preventive and personalized health care.

The arrestin domain-containing 3 protein regulates body mass and energy expenditure.

A human genome-wide linkage scan for obesity identified a linkage peak on chromosome 5q13-15. Positional cloning revealed an association of a rare haplotype to high body-mass index (BMI) in males but not females. The risk locus contains a single gene, "arrestin domain-containing 3" (ARRDC3), an uncharacterized α-arrestin. Inactivating Arrdc3 in mice led to a striking resistance to obesity, with greater impact on male mice. Mice with decreased ARRDC3 levels were protected from obesity due to increased energy expenditure through increased activity levels and increased thermogenesis of both brown and white adipose tissues. ARRDC3 interacted directly with ß-adrenergic receptors, and loss of ARRDC3 increased the response to ß-adrenergic stimulation in isolated adipose tissue. These results demonstrate that ARRDC3 is a gender-sensitive regulator of obesity and energy expenditure and reveal a surprising diversity for arrestin family protein functions.

Statistical power of phylo-HMM for evolutionarily conserved element detection.

BACKGROUND: An important goal of comparative genomics is the identification of functional elements through conservation analysis. Phylo-HMM was recently introduced to detect conserved elements based on multiple genome alignments, but the method has not been rigorously evaluated. RESULTS: We report here a simulation study to investigate the power of phylo-HMM. We show that the power of the phylo-HMM approach depends on many factors, the most important being the number of species-specific genomes used and evolutionary distances between pairs of species. This finding is consistent with results reported by other groups for simpler comparative genomics models. In addition, the conservation ratio of conserved elements and the expected length of the conserved elements are also major factors. In contrast, the influence of the topology and the nucleotide substitution model are relatively minor factors. CONCLUSION: Our results provide for general guidelines on how to select the number of genomes and their evolutionary distance in comparative genomics studies, as well as the level of power we can expect under different parameter settings.