Prevention of violence against women and girls: A cost-effectiveness study across 6 low- and middle-income countries

BackgroundViolence against women and girls (VAWG) is a human rights violation with social, economic, and health consequences for survivors, perpetrators, and society. Robust evidence on economic, social, and health impact, plus the cost of delivery of VAWG prevention, is critical to making the case for investment, particularly in low- and middle-income countries (LMICs) where health sector resources are highly constrained. We report on the costs and health impact of VAWG prevention in 6 countries.Methods and findingsWe conducted a trial-based cost-effectiveness analysis of VAWG prevention interventions using primary data from 5 randomised controlled trials (RCTs) in sub-Saharan Africa and 1 in South Asia. We evaluated 2 school-based interventions aimed at adolescents (11 to 14 years old) and 2 workshop-based (small group or one to one) interventions, 1 community-based intervention, and 1 combined small group and community-based programme all aimed at adult men and women (18+ years old). All interventions were delivered between 2015 and 2018 and were compared to a do-nothing scenario, except for one of the school-based interventions (government-mandated programme) and for the combined intervention (access to financial services in small groups). We computed the health burden from VAWG with disability-adjusted life year (DALY). We estimated per capita DALYs averted using statistical models that reflect each trial’s design and any baseline imbalances. We report cost-effectiveness as cost per DALY averted and characterise uncertainty in the estimates with probabilistic sensitivity analysis (PSA) and cost-effectiveness acceptability curves (CEACs), which show the probability of cost-effectiveness at different thresholds. We report a subgroup analysis of the small group component of the combined intervention and no other subgroup analysis. We also report an impact inventory to illustrate interventions’ socioeconomic impact beyond health. We use a 3% discount rate for investment costs and a 1-year time horizon, assuming no effects post the intervention period. From a health sector perspective, the cost per DALY averted varies between US$222 (2018), for an established gender attitudes and harmful social norms change community-based intervention in Ghana, to US$17,548 (2018) for a livelihoods intervention in South Africa. Taking a societal perspective and including wider economic impact improves the cost-effectiveness of some interventions but reduces others. For example, interventions with positive economic impacts, often those with explicit economic goals, offset implementation costs and achieve more favourable cost-effectiveness ratios. Results are robust to sensitivity analyses. Our DALYs include a subset of the health consequences of VAWG exposure; we assume no mortality impact from any of the health consequences included in the DALYs calculations. In both cases, we may be underestimating overall health impact. We also do not report on participants’ health costs.ConclusionsWe demonstrate that investment in established community-based VAWG prevention interventions can improve population health in LMICs, even within highly constrained health budgets. However, several VAWG prevention interventions require further modification to achieve affordability and cost-effectiveness at scale. Broadening the range of social, health, and economic outcomes captured in future cost-effectiveness assessments remains critical to justifying the investment urgently required to prevent VAWG globally.

In a cost-effectiveness study, Dr. Giulia Ferrari and colleagues examine the costs and health impact of prevention of violence against women and girls in six low- and middle-income countries.     

Deglutarylation of glutaryl-CoA dehydrogenase by deacylating enzyme SIRT5 promotes lysine oxidation in mice

A wide range of protein acyl modifications has been identified on enzymes across various metabolic processes; however, the impact of these modifications remains poorly understood. Protein glutarylation is a recently identified modification that can be nonenzymatically driven by glutaryl-CoA. In mammalian systems, this unique metabolite is only produced in the lysine and tryptophan oxidative pathways. To better understand the biology of protein glutarylation, we studied the relationship between enzymes within the lysine/tryptophan catabolic pathways, protein glutarylation, and regulation by the deglutarylating enzyme sirtuin 5 (SIRT5). Here, we identify glutarylation on the lysine oxidation pathway enzyme glutaryl-CoA dehydrogenase (GCDH) and show increased GCDH glutarylation when glutaryl-CoA production is stimulated by lysine catabolism. Our data reveal that glutarylation of GCDH impacts its function, ultimately decreasing lysine oxidation. We also demonstrate the ability of SIRT5 to deglutarylate GCDH, restoring its enzymatic activity. Finally, metabolomic and bioinformatic analyses indicate an expanded role for SIRT5 in regulating amino acid metabolism. Together, these data support a feedback loop model within the lysine/tryptophan oxidation pathway in which glutaryl-CoA is produced, in turn inhibiting GCDH function via glutaryl modification of GCDH lysine residues and can be relieved by SIRT5 deacylation activity.     

Sex‐specific aging in animals: Perspective and future directions

Sex differences in aging occur in many animal species, and they include sex differences in lifespan, in the onset and progression of age‐associated decline, and in physiological and molecular markers of aging. Sex differences in aging vary greatly across the animal kingdom. For example, there are species with longer‐lived females, species where males live longer, and species lacking sex differences in lifespan. The underlying causes of sex differences in aging remain mostly unknown. Currently, we do not understand the molecular drivers of sex differences in aging, or whether they are related to the accepted hallmarks or pillars of aging or linked to other well‐characterized processes. In particular, understanding the role of sex‐determination mechanisms and sex differences in aging is relatively understudied. Here, we take a comparative, interdisciplinary approach to explore various hypotheses about how sex differences in aging arise. We discuss genomic, morphological, and environmental differences between the sexes and how these relate to sex differences in aging. Finally, we present some suggestions for future research in this area and provide recommendations for promising experimental designs.     

Modeling the CRL4A ligase complex to predict target protein ubiquitination induced by cereblon-recruiting PROTACs

PROteolysis TArgeting Chimeras (PROTACs) are hetero-bifunctional small molecules that can simultaneously recruit target proteins and E3 ligases to form a ternary complex, promoting target protein ubiquitination and degradation via the Ubiquitin-Proteasome System (UPS). PROTACs have gained increasing attention in recent years due to certain advantages over traditional therapeutic modalities and enabling targeting of previously “undruggable” proteins. To better understand the mechanism of PROTAC-induced Target Protein Degradation (TPD), several computational approaches have recently been developed to study and predict ternary complex formation. However, mounting evidence suggests that ubiquitination can also be a rate-limiting step in PROTAC-induced TPD. Here, we propose a structure-based computational approach to predict target protein ubiquitination induced by cereblon (CRBN)-based PROTACs by leveraging available structural information of the CRL4A ligase complex (CRBN/DDB1/CUL4A/Rbx1/NEDD8/E2/Ub). We generated ternary complex ensembles with Rosetta, modeled multiple CRL4A ligase complex conformations, and predicted ubiquitination efficiency by separating the ternary ensemble into productive and unproductive complexes based on the proximity of the ubiquitin to accessible lysines on the target protein. We validated our CRL4A ligase complex models with published ternary complex structures and additionally employed our modeling workflow to predict ubiquitination efficiencies and sites of a series of cyclin-dependent kinases (CDKs) after treatment with TL12–186, a pan-kinase PROTAC. Our predictions are consistent with CDK ubiquitination and site-directed mutagenesis of specific CDK lysine residues as measured using a NanoBRET ubiquitination assay in HEK293 cells. This work structurally links PROTAC-induced ternary formation and ubiquitination, representing an important step toward prediction of target “degradability.”     

Genetic background influences survival of infections with Salmonella enterica serovar Typhimurium in the Collaborative Cross

Salmonella infections typically cause self-limiting gastroenteritis, but in some individuals these bacteria can spread systemically and cause disseminated disease. Salmonella Typhimurium (STm), which causes severe systemic disease in most inbred mice, has been used as a model for disseminated disease. To screen for new infection phenotypes across a range of host genetics, we orally infected 32 Collaborative Cross (CC) mouse strains with STm and monitored their disease progression for seven days by telemetry. Our data revealed a broad range of phenotypes across CC strains in many parameters including survival, bacterial colonization, tissue damage, complete blood counts (CBC), and serum cytokines. Eighteen CC strains survived to day 7, while fourteen susceptible strains succumbed to infection before day 7. Several CC strains had sex differences in survival and colonization. Surviving strains had lower pre-infection baseline temperatures and were less active during their daily active period. Core body temperature disruptions were detected earlier after STm infection than activity disruptions, making temperature a better detector of illness. All CC strains had STm in spleen and liver, but susceptible strains were more highly colonized. Tissue damage was weakly negatively correlated to survival. We identified loci associated with survival on Chromosomes (Chr) 1, 2, 4, 7. Polymorphisms in Ncf2 and Slc11a1, known to reduce survival in mice after STm infections, are located in the Chr 1 interval, and the Chr 7 association overlaps with a previously identified QTL peak called Ses2. We identified two new genetic regions on Chr 2 and 4 associated with susceptibility to STm infection. Our data reveal the diversity of responses to STm infection across a range of host genetics and identified new candidate regions for survival of STm infection.     

The Discovery of Single-Nucleotide Polymorphisms—and Inferences about Human Demographic History

A method of historical inference that accounts for ascertainment bias is developed and applied to single-nucleotide polymorphism (SNP) data in humans. The data consist of 84 short fragments of the genome that were selected, from three recent SNP surveys, to contain at least two polymorphisms in their respective ascertainment samples and that were then fully resequenced in 47 globally distributed individuals. Ascertainment bias is the deviation, from what would be observed in a random sample, caused either by discovery of polymorphisms in small samples or by locus selection based on levels or patterns of polymorphism. The three SNP surveys from which the present data were derived differ both in their protocols for ascertainment and in the size of the samples used for discovery. We implemented a Monte Carlo maximum-likelihood method to fit a subdivided-population model that includes a possible change in effective size at some time in the past. Incorrectly assuming that ascertainment bias does not exist causes errors in inference, affecting both estimates of migration rates and historical changes in size. Migration rates are overestimated when ascertainment bias is ignored. However, the direction of error in inferences about changes in effective population size (whether the population is inferred to be shrinking or growing) depends on whether either the numbers of SNPs per fragment or the SNP-allele frequencies are analyzed. We use the abbreviation "SDL," for "SNP-discovered locus," in recognition of the genomic-discovery context of SNPs. When ascertainment bias is modeled fully, both the number of SNPs per SDL and their allele frequencies support a scenario of growth in effective size in the context of a subdivided population. If subdivision is ignored, however, the hypothesis of constant effective population size cannot be rejected. An important conclusion of this work is that, in demographic or other studies, SNP data are useful only to the extent that their ascertainment can be modeled.