The importance of having two X chromosomes

Historically, it was thought that the number of X chromosomes plays little role in causing sex differences in traits. Recently, selected mouse models have been used increasingly to compare mice with the same type of gonad but with one versus two copies of the X chromosome. Study of these models demonstrates that mice with one X chromosome can be strikingly different from those with two X chromosomes, when the differences are not attributable to confounding group differences in gonadal hormones. The number of X chromosomes affects adiposity and metabolic disease, cardiovascular ischaemia/reperfusion injury and behaviour. The effects of X chromosome number are likely the result of inherent differences in expression of X genes that escape inactivation, and are therefore expressed from both X chromosomes in XX mice, resulting in a higher level of expression when two X chromosomes are present. The effects of X chromosome number contribute to sex differences in disease phenotypes, and may explain some features of X chromosome aneuploidies such as in Turner and Klinefelter syndromes

The Effects of Perinatal Testosterone Exposure on the DNA Methylome of the Mouse Brain Are Late-Emerging

Background The biological basis for sex differences in brain function and disease susceptibility is poorly understood. Examining the role of gonadal hormones in brain sexual differentiation may provide important information about sex differences in neural health and development. Permanent masculinization of brain structure, function, and disease is induced by testosterone prenatally in males, but the possible mediation of these effects by long-term changes in the epigenome is poorly understood. Methods We investigated the organizational effects of testosterone on the DNA methylome and transcriptome in two sexually dimorphic forebrain regions—the bed nucleus of the stria terminalis/preoptic area and the striatum. To study the contribution of testosterone to both the establishment and persistence of sex differences in DNA methylation, we performed genome-wide surveys in male, female, and female mice given testosterone on the day of birth. Methylation was assessed during the perinatal window for testosterone\u27s organizational effects and in adulthood. Results The short-term effect of testosterone exposure was relatively modest. However, in adult animals the number of genes whose methylation was altered had increased by 20-fold. Furthermore, we found that in adulthood, methylation at a substantial number of sexually dimorphic CpG sites was masculinized in response to neonatal testosterone exposure. Consistent with this, testosterone\u27s effect on gene expression in the striatum was more apparent in adulthood. Conclusion Taken together, our data imply that the organizational effects of testosterone on the brain methylome and transcriptome are dramatic and late-emerging. Our findings offer important insights into the long-term molecular effects of early-life hormonal exposure

The Sex Chromosome Trisomy mouse model of XXY and XYY: metabolism and motor performance

BACKGROUND: Klinefelter syndrome (KS), caused by XXY karyotype, is characterized by low testosterone, infertility, cognitive deficits, and increased prevalence of health problems including obesity and diabetes. It has been difficult to separate direct genetic effects from hormonal effects in human studies or in mouse models of KS because low testosterone levels are confounded with sex chromosome complement. METHODS: In this study, we present the Sex Chromosome Trisomy (SCT) mouse model that produces XXY, XYY, XY, and XX mice in the same litters, each genotype with either testes or ovaries. The independence of sex chromosome complement and gonadal type allows for improved recognition of sex chromosome effects that are not dependent on levels of gonadal hormones. All mice were gonadectomized and treated with testosterone for 3 weeks. Body weight, body composition, and motor function were measured. RESULTS: Before hormonal manipulation, XXY mice of both sexes had significantly greater body weight and relative fat mass compared to XY mice. After gonadectomy and testosterone replacement, XXY mice (both sexes) still had significantly greater body weight and relative fat mass, but less relative lean mass compared to XY mice. Liver, gonadal fat pad, and inguinal fat pad weights were also higher in XXY mice, independent of gonadal sex. In several of these measures, XX mice also differed from XY mice, and gonadal males and females differed significantly on almost every metabolic measure. The sex chromosome effects (except for testis size) were also seen in gonadally female mice before and after ovariectomy and testosterone treatment, indicating that they do not reflect group differences in levels of testicular secretions. XYY mice were similar to XY mice on body weight and metabolic variables but performed worse on motor tasks compared to other groups. CONCLUSIONS: We find that the new SCT mouse model for XXY and XYY recapitulates features found in humans with these aneuploidies. We illustrate that this model has significant promise for unveiling the role of genetic effects compared to hormonal effects in these syndromes, because many phenotypes are different in XXY vs. XY gonadal female mice which have never been exposed to testicular secretions

Modulation of T Cell Function by Combination of Epitope Specific and Low Dose Anticytokine Therapy Controls Autoimmune Arthritis

Innate and adaptive immunity contribute to the pathogenesis of autoimmune arthritis by generating and maintaining inflammation, which leads to tissue damage. Current biological therapies target innate immunity, eminently by interfering with single pro-inflammatory cytokine pathways. This approach has shown excellent efficacy in a good proportion of patients with Rheumatoid Arthritis (RA), but is limited by cost and side effects. Adaptive immunity, particularly T cells with a regulatory function, plays a fundamental role in controlling inflammation in physiologic conditions. A growing body of evidence suggests that modulation of T cell function is impaired in autoimmunity. Restoration of such function could be of significant therapeutic value. We have recently demonstrated that epitope-specific therapy can restore modulation of T cell function in RA patients. Here, we tested the hypothesis that a combination of anti-cytokine and epitope-specific immunotherapy may facilitate the control of autoimmune inflammation by generating active T cell regulation. This novel combination of mucosal tolerization to a pathogenic T cell epitope and single low dose anti-TNFα was as therapeutically effective as full dose anti-TNFα treatment. Analysis of the underlying immunological mechanisms showed induction of T cell immune deviation

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

The Sex Chromosome Trisomy mouse model of XXY and XYY: metabolism and motor performance

Abstract Background Klinefelter syndrome (KS), caused by XXY karyotype, is characterized by low testosterone, infertility, cognitive deficits, and increased prevalence of health problems including obesity and diabetes. It has been difficult to separate direct genetic effects from hormonal effects in human studies or in mouse models of KS because low testosterone levels are confounded with sex chromosome complement. Methods In this study, we present the Sex Chromosome Trisomy (SCT) mouse model that produces XXY, XYY, XY, and XX mice in the same litters, each genotype with either testes or ovaries. The independence of sex chromosome complement and gonadal type allows for improved recognition of sex chromosome effects that are not dependent on levels of gonadal hormones. All mice were gonadectomized and treated with testosterone for 3 weeks. Body weight, body composition, and motor function were measured. Results Before hormonal manipulation, XXY mice of both sexes had significantly greater body weight and relative fat mass compared to XY mice. After gonadectomy and testosterone replacement, XXY mice (both sexes) still had significantly greater body weight and relative fat mass, but less relative lean mass compared to XY mice. Liver, gonadal fat pad, and inguinal fat pad weights were also higher in XXY mice, independent of gonadal sex. In several of these measures, XX mice also differed from XY mice, and gonadal males and females differed significantly on almost every metabolic measure. The sex chromosome effects (except for testis size) were also seen in gonadally female mice before and after ovariectomy and testosterone treatment, indicating that they do not reflect group differences in levels of testicular secretions. XYY mice were similar to XY mice on body weight and metabolic variables but performed worse on motor tasks compared to other groups. Conclusions We find that the new SCT mouse model for XXY and XYY recapitulates features found in humans with these aneuploidies. We illustrate that this model has significant promise for unveiling the role of genetic effects compared to hormonal effects in these syndromes, because many phenotypes are different in XXY vs. XY gonadal female mice which have never been exposed to testicular secretions

Methods for Empirical and Numerical Analysis of Tailings Flow Runout (CanBreach Project)

Tailings dam failures are capable of producing mass flows in the downstream environment. These tailings flows can travel at high velocities, cover long distances, and cause widespread inundation. The ability to understand and predict the mobility and behaviour of tailings flows is a crucial step in ensuring the safety of people, infrastructure, and the environment. In this paper, we summarize the outcomes of collaborative research projects over the past four years that developed improved predictive empirical and numerical models of potential tailings dam breaches and their downstream impacts. This work included: 1) development of a new tailings flow runout classification system; 2) compilation of detailed databases of historical tailings flows; 3) development of new empirical relationships between released volume and inundation area; 4) recalibration of an existing semi-empirical model adapted to tailings flows; 5) benchmarking of several existing numerical runout models; 6) analysis of sensitivities and uncertainties in numerical runout models; and 7) demonstration of a probabilistic approach to numerical runout prediction. The results of this research can help practitioners develop better inundation maps, dam classifications, and emergency preparedness and response plans in tailings management practice.Science, Faculty ofEarth, Ocean and Atmospheric Sciences, Department ofApplied Science, Faculty ofMining Engineering, Keevil Institute ofMedicine, Faculty ofPopulation and Public Health (SPPH), School ofNon UBCUnreviewedGraduateFacultyOthe

Feminized behavior and brain gene expression in a novel mouse model of Klinefelter Syndrome.

Klinefelter Syndrome (KS) is the most common sex chromosome aneuploidy in men and is characterized by the presence of an additional X chromosome (XXY). In some Klinefelter males, certain traits may be feminized or shifted from the male-typical pattern towards a more female-typical one. Among them might be partner choice, one of the most sexually dimorphic traits in the animal kingdom. We investigated the extent of feminization in XXY male mice (XXYM) in partner preference and gene expression in the bed nucleus of the stria terminalis/preoptic area and the striatum in mice from the Sex Chromosome Trisomy model. We tested for partner preference using a three-chambered apparatus in which the test mouse was free to choose between stimulus animals of either sex. We found that partner preference in XXYM was feminized. These differences were likely due to interactions of the additional X chromosome with the Y. We also discovered genes that differed in expression in XXYM versus XYM. Some of these genes are feminized in their expression pattern. Lastly, we also identified genes that differed only between XXYM versus XYM and not XXM versus XYM. Genes that are both feminized and unique to XXYM versus XYM represent strong candidates for dissecting the molecular pathways responsible for phenotypes present in KS/XXYM but not XXM. In sum, our results demonstrated that investigating behavioral and molecular feminization in XXY males can provide crucial information about the pathophysiology of KS and may aid our understanding of sex differences in brain and behavior