Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

Identifying the Critical Gaps in Research on Sex Differences in Metabolism Across the Life Span

Identifying the Critical Gaps in Research on Sex Differences in Metabolism Across the Life Span Abstract The National Institutes of Health (NIH) Office of Research in Women’s Health now functions under a mandate calling for the systematic inclusion of both female and male cells, animals, and human subjects in all types of research, so that sex as a biological variable is understood in health and disease. Sex-specific data can improve disease prevention, diagnosis, and treatment as well as reduce inequities. Inclusion of women in research studies has modestly improved over the last 20 years, yet preclinical research is still primarily done using male animal models and male-derived cells, with the result that many conclusions are made based on incomplete and sex-biased data. There are important, yet poorly studied, sex differences in cardiometabolic disease. To begin to address these sex differences, the Center for Women’s Health Research at the University of Colorado held its inaugural National Conference, “Sex Differences Across the Lifespan: A Focus on Metabolism,” in September 2016 (cwhr@ucdenver.edu). Research to address the important goal of understanding key sex differences in cardiometabolic disease across the life span is lacking. The goal of this article is to discuss the current state of research addressing sex differences in cardiometabolic health across the life span, to outline critical research gaps that must be addressed in response to NIH mandates, and, importantly, to develop strategies to address sex as a biological variable to understand disease mechanisms as well as develop diagnostic and therapeutic modalities. Although inclusion of women in research studies has improved over the last 20 years, preclinical research is still primarily done using male animal models and male-derived cells, with the result that many conclusions are made based on incomplete and sex-biased data. The National Institutes of Health (NIH) Office of Research in Women’s Health now functions under a mandate calling for the systematic inclusion of both female and male cells, animals, and human subjects in all types of research, so that sex as a biological variable is considered in health and disease. Sex-specific data can improve disease prevention, diagnosis, and treatment as well as reduce inequities. Research to address the important goal of understanding key sex differences in cardiometabolic disease across the life span is lacking (Table 1). Table 1. Proportion of NIH Budget Allocated to Research in Areas of Interest to Women’s Health Institute  Percentage of NIH Total Budget  NICHD  4.1  NIMH  4.8  NHLBI  9.6  NCI  16.1  Women’s healtha  14  Institute  Percentage of NIH Total Budget  NICHD  4.1  NIMH  4.8  NHLBI  9.6  NCI  16.1  Women’s healtha  14  Of the total $32.3 billion NIH budget, a small proportion is allocated to the areas of maternal, fetal, and women’s health specifically, despite the potential to pay huge dividends in life span. It is not currently possible to discern specific funding lines. Abbreviations: NCI, National Cancer Institute; NHLBI, National Heart, Lung, and Blood Institute; NICHD, Eunice Kennedy Shriver National institute of Child Health and Human Development; NIMH, National Institute of Mental Health. a Reporting for this category does not follow the standard NIH Research, Condition, and Disease Categorization process. This category assigns project funding according to populations tracked by sex or ethnicity. The databases used to track sex or ethnicity are complex and are not currently compatible with the NIH Research, Condition, and Disease Categorization system (https://report.nih.gov/categorical_spending.aspx#legend11). View Large There are important, yet poorly studied, sex differences in cardiometabolic disease. To begin to address these sex differences, the Center for Women’s Health Research at the University of Colorado held its inaugural National Conference, “Sex Differences Across the Lifespan: A Focus on Metabolism,” in September 2016 (cwhr@ucdenver.edu). Based on the research presentations and discussions from that conference, the goal of this article is to discuss the current state of research addressing sex differences in cardiometabolic health across the life span, to outline critical research gaps that must be addressed in response to NIH mandates and, importantly, to develop strategies to address sex as a biological variable to understand disease mechanisms as well as develop diagnostic and therapeutic modalities. The Urgency of the Burden of Cardiometabolic Disease in Women Although cardiovascular disease (CVD) is the most prevalent cause of death in both men and women, much less is known about its effects in women than in men, and there are important differences being identified. In women, CVD is the leading cause of mortality and morbidity for US women; one in four US women die of CVD, which is twice as many as from all forms of cancer combined (1, 2). In 2008, there were 9,127,416 CVD deaths in women worldwide, representing one-third of all deaths. The INTERHEART report indicates that 94% of the population-adjusted cardiovascular (CV) mortality in women is due to modifiable risk factors. In the United States, two of three women have at least one major coronary risk factor (3). Overall mortality from CVD decreased from 1997 to 2013, but in women ages 35 to 54 years, mortality is increasing by 1% annually, an increase attributed to rising rates of obesity, diabetes, and sedentary lifestyle (4, 5). Furthermore, CVD is becoming a major problem in other low- and middle-income countries, with a projected 120% increase in CV mortality in women living in the poorer countries between 1990 and 2020, compared with 29% in women living in wealthier countries. Globally, women are especially vulnerable as 60% of the world’s poor and two-thirds of illiterate adults are women (www.who.int/pmnch/topics/maternal/2011_women_ncd_report.pdf). This document is not intended to be comprehensive with regard to all cardiometabolic issues affecting women’s health and sex differences; rather, it will highlight key issues, discuss research gaps, and comment on research priorities. Research is urgently needed to identify the mechanisms responsible for the above sex-specific increases in CVD risk and to develop therapies that are safe and effective in women. This research must take into account biological and behavioral factors that differ between women and men, including unique exposures in women across the life span from conception through aging. In the following sections, we elaborate upon the unique biological issues faced by women across the life span, as well as the sex differences in each phase of life. Priorities in the Fundamental Research on Sex as a Biological Variable for Cardiometabolism Energy balance Evidence suggests estrogens regulate fat distribution (6). Rodent studies specifically demonstrate that estrogen loss [ovariectomized (OVX), estrogen receptor α (ESR1 or ERα) Esr1−/− and GnRH agonist-treated mice] leads to decreased physical activity, increased adiposity, and decreased muscle mass, whereas estrogen replacement reverses these changes. In addition, in a high-fat diet model, estradiol had a beneficial impact to decrease visceral adipose tissue and increase brown adipose tissue (7). Manipulation of ERα demonstrates that the impact of estradiol in diet-induced obesity is both central and peripheral (8). Similarly, studies in humans during female-specific age-related transitions demonstrate increased adiposity, with redistribution of fat to abdominal depots and increased incidence of metabolic dysfunction. The specific role of estrogen vs age in these transitions is being studied. Sex hormones regulate fat distribution in part by controlling lipid uptake and lipolysis in a sex- and depot-specific manner. Sex chromosomes and adiposity Employing a recently developed four-core genotype mouse modeling system, insights have been generated as to the contributions of genetic and hormonal mechanisms underlying sex differences in obesity (8, 9). Regardless of XX or XY status, gonad-intact male mice have greater body weight than female mice; in addition, XX status is associated with an increased weight regardless of gonadal sex. In this same model, manipulation of sex hormones with gonadectomy indicates that XX status is associated with greater fat mass gain than XY status (9). The molecular contribution of the X chromosome to adiposity requires further study. Sex hormone regulation of adipocyte precursors The recent identification of distinct adipocyte subpopulations—specifically, their progenitor cells and developmental origins—opens the door to understanding the impact of sex hormones on regional adipocyte production. Gavin et al. (10) exploited fate-mapping strategies to show that a subpopulation of adipocytes is produced from bone marrow stem cells in mice. These marrow-derived adipocytes preferentially accumulate in adipose tissue of females rather than males and in abdominal rather than peripheral fat depots. Importantly, these cells exhibit a highly proinflammatory adipokine profile and, therefore, a potentially harmful phenotype. Marrow-derived adipocytes have been detected in humans, highlighting their clinical relevance. Klemm, Kohrt, and Gavin subsequently tested whether loss of ovarian hormone production in OVX mice would influence the production and distribution of marrow-derived adipocytes (D. J. Klemm, W. Kohrt, and K. Gavin, unpublished data, November 2017). The percentage of marrow-derived adipocytes was more than twofold higher in the abdominal fat of OVX mice compared with controls, but percentages in peripheral fat were only minimally increased. Replacement of estradiol, but not progesterone, reduced marrow-derived adipocyte production to levels below those measured in surgery-naive mice. Estradiol appeared to act through estrogen receptor α (ESR1 or ERα) as marrow-derived adipocyte production was stimulated in abdominal fat of female Esr2 knockout mice. The results demonstrate that loss of ovarian hormone signaling elicits preferential accumulation of marrow-derived adipocytes in abdominal adipose tissue. This process may explain in part the redistribution of fat and changes in adipose tissue function that contribute to chronic metabolic dysfunction at menopause. Aging Sex differences in human aging have been defined in a wide range of demographic and experimental studies, yet the molecular mechanisms underlying these differences remain poorly understood. In mouse strains, females do not always live longer than males; however, there are distinct differences in how females and males respond to interventions that extend life span (11). For instance, reduced insulin–insulinlike growth factor signaling leads to greater life span extension in females than males (12), whereas aspirin and other interventions thought to reduce inflammation have more pronounced effects in males (13). Rapamycin, an inhibitor of the mTOR pathway, causes the most pronounced extension of mouse life span of any drug and mediates this effect in both sexes, although the extension is greater in females (14). The mTOR protein kinase (in the TORC1 complex) phosphorylates substrates involved in control of cell growth, proliferation, and stress response pathways. With aging, two downstream substrates behave differently in males and females, and these differences may underlie the differential effects of other longevity drugs in females and males. To achieve the ultimate goal of preventing age-associated chronic disease states and maintain human function later in life, it is necessary to understand sex differences with respect to aging and longevity interventions. Critical gaps and research priorities What are the mechanisms whereby sex hormones regulate body mass and how do they interact with diet and age? What is the relative contribution of estrogen signaling in the brain vs the periphery on body weight regulation? What are the molecular mechanisms whereby XX status contributes to increased fat mass? What is the metabolic consequence of sex hormone regulation of bone marrow–derived adipocytes? How can we extrapolate lessons learned regarding sex differences in aging in cell and animal models to human aging and disease? Research Priorities for Cardiometabolic Risk with Pregnancy: Mother and Offspring Fetal origins of adult disease comprise a compelling area of study that provides a rationale for addressing cardiometabolic disease across the life span, including pregestation. Pregnancy conditions also affect lifetime CV risk in the mother. Additional acquired sex differences in cardiometabolic function present across the life span (childhood, puberty, adulthood, menopause, and aging) and interact with environmental factors, disease, and metabolic stress (exercise, obesity, diabetes). Preconception Maternal and paternal fitness prior to conception affects offspring metabolic health. For example, Stanford et al. (15) have tested the impact of exercise (maternal, paternal, or both) upon offspring health outcomes in rats. Of particular note, maternal exercise before and during pregnancy significantly improved glucose tolerance and decreased insulin concentrations in offspring. There was an additive metabolic benefit for offspring if both parents underwent exercise training. Exercise specifically affected hepatic metabolism. Raipuria et al. (16) reported that maternal exercise appeared to decrease the metabolic risk induced by maternal obesity in rats, improving insulin/glucose metabolism, with greater effects in male than female offspring [(15) (heart), (16) (skeletal muscle and fat)]. In humans, Tomić et al. (17) reported that maternal physical activity reduced gestational diabetes. This was in contrast to older reports that provided a cautionary or neutral message about maternal exercise in humans [(18), (19) review]. Pregnancy Pregnancy has a unique and substantial impact on the future health of both mother and baby across a wide range of conditions and risk factors. Common pregnancy complications such as gestational diabetes, hypertensive disorders of pregnancy, behavioral health challenges, and preterm birth all increase future risk for cardiometabolic and other disease in both mother and child. Placental biology The placenta controls gas and nutrient exchange, waste transfer from the fetus to the mother, and immune and endocrine support to the developing fetus. The molecular mechanisms underlying many of these functions are only beginning to be elucidated yet are central to our understanding of fetal development and pregnancy health and disease. One example of a critical placental function is defense against microbial infection, where the trophoblast, which is directly bathed in maternal blood, restricts the spread of pathogens into the fetal compartment. Sheridan et al. (20) recently found that cultured primary human trophoblast from term, healthy placentas are resistant to infection by diverse types of DNA and RNA viruses. Moreover, resistance to infection can be conferred to nonplacental cells by transferring trophoblast-conditioned medium to recipient cells [specifically microRNAs from the chromosome 19 microRNA cluster (C19MC)] (21). These findings suggest that trophoblast communicates protective molecular signals, which are packaged within exosomes that are released into the maternal circulation and, possibly, transmitted to the fetal compartment. Because dysfunctional or diseased placenta may adversely affect the health of the fetus and offspring after birth, this line of emerging research illuminating the role of the placenta beyond nutrient and waste transfer is important in understanding the long-term consequences of placental function on metabolic health. Critical gaps and research priorities What is the impact of parental health behaviors on offspring metabolic health and is there a differential impact on female and male offspring? What are the mechanisms whereby maternal and paternal fitness and metabolic health prior to conception contribute to the metabolic phenotype of the offspring? What are the mechanisms of pregnancy and early life critical periods for programming cardiometabolic disease susceptibility in women and their offspring? How does the fetal sex influence maternal adaptation to pregnancy and placental function? Are there sex differences in fetal response to placental dysfunction? What are the mechanisms underlying the long-term effect of feto-placental injury? What are the molecular mechanisms underlying placental cell defense? Research Priorities Related to Cardiometabolic Disease in Pregnancy Obesity in pregnancy Nearly two-thirds of American women of childbearing age are overweight or obese, and almost half these women, once pregnant, have excess gestational weight gain that contributes to their cardiometabolic risk, as well as that of the next generation (22). For example, infants born to obese mothers have increased liver fat and are at higher risk of obesity, diabetes, nonalcoholic hepatic steatosis, and increased mortality due to CVD (23). Research has not vigorously tested the impact of the sex of the offspring on these outcomes. Preeclampsia and hypertensive diseases of pregnancy Preeclampsia (PE) increases a twofold to fourfold risk for ischemic heart disease in women. Data regarding the impact of PE on offspring suggest an increased incidence of hypertension and QRISK (global lifetime risk for CVD) (24). To date, PE is not included in CVD risk engines or routinely assessed in young adults at excess risk for hypertension. The mechanism whereby PE contributes to excess risk in mothers and offspring is unknown, Gestational diabetes Gestational diabetes confers a 7- to 12-fold increased risk for developing type 2 diabetes (T2D) in 5 to 10 years after delivery, whereas preeclampsia, preterm delivery, delivery of a small-for-gestational age neonate, and gestational diabetes are independently associated with a 50% to 300% increased risk for CVD (25, 26). Postpartum weight retention exacerbates this risk; pregnancy weight retained beyond 6 to 12 months postpartum tends to be retained long term and is independently linked to future obesity, CVD, and T2D. Intrauterine growth restriction Intrauterine growth restriction in a sheep model system results in decreases in amino acid uptake rate, muscle myofiber area, and muscle mass (27). However, the impact of this on future dysmetabolism is unclear. In this same model, there is hepatic insulin resistance and decreased β-cell mass (28). This constellation of changes in organ development likely contributes to increased risk of diabetes in intrauterine growth restriction offspring. Of great interest, supplementation of amino acids in utero can reverse some of these effects (29). Reproductive immunology Sex hormones have failed to fully explain the female predominance of autoimmunity. However, immunological changes that occur during and after pregnancy have durability across the life span and may play an important role in evolution of autoimmunity (30). There is also growing awareness of accelerated CVD in women with some autoimmune diseases, an association that has also not been explained by sex hormones. Microchimerism is a phenomenon of pregnancy in which there is bidirectional transport between mother and fetus, including immune regulatory (Treg) cells (31). The maternal and fetal microchimerism is widespread, and the cells lodge themselves throughout the body. The importance of microchimerism on autoimmune disease and the attendant CV risk is an emerging area of sex differences research. Technology-driven interventions Women of childbearing age are among the fastest growing users of technology, across race and socioeconomic class. The use of eHealth has advantages over traditional face-to-face lifestyle interventions, especially for the difficult-to-reach postpartum population, including allowing for real-time self-monitoring of diet and exercise, instant feedback, and wireless uploading of data. The flexibility of mHealth (mobile health technology), coupled with the pace of technological advancement, potentially allows for rapid refinement and optimization of interventions and the opportunity to scale interventions to reach a broad audience (32). Critical gaps and research priorities How does pregnancy affect maternal health and the health of offspring? What is the impact of maternal obesity, gestational weight gain, and diet exposure on the development of the maternal and infant microbiome? What are the CVD outcomes for women with a remote history of preeclampsia or hypertensive disorders of pregnancy? How does the fetus adapt to abnormal nutrient delivery (insufficient or excess), stress, blood flow, and environmental toxins and how do these adaptations affect later life metabolic processes and development of disease? What are the immunological consequences of gravidity and parity for women’s health? What are the most efficacious technological advances that will help women of childbearing age to have healthy transitions after childbirth? Emerging Research Gaps on Sex Differences in Cardiometabolic Health in Youth Biology of sex differences in CV risk development in youth The rapidly increasing burden of noncommunicable chronic diseases in youth represents a global public health challenge. Particularly worrisome is the rapid increase in obesity and youth onset of T2D. Early obesity and metabolic syndrome point toward fetal origins and early life environmental exposures. A life span approach to health and disease incorporates the concept that there are critical periods of development during which environmental exposures, such as developmental overnutrition, undernutrition, or inadequate physical activity, have lasting effects on health. Childhood development Emerging evidence in stem cells derived from fetal samples (e.g., umbilical cord tissue, amniotic fluid) has documented fetal programming by maternal obesity that is remarkably consistent with observations in reported animal models of maternal obesity, including an inherent capacity for excess adipogenesis that is correlated with neonatal adiposity (33–35). These studies with stem cells provide the opportunity to examine the cellular function contributing to risk for development of metabolic disease later in life. The cells can be obtained noninvasively and probed to determine aspects of metabolism attributable to fetal exposures and, furthermore, to understand whether infant sex affects the metabolic response to intrauterine stress or the predictive value of the mesenchymal stem cells for childhood metabolic health. Adolescence and T2D In the course of the SEARCH for Diabetes in Youth study, Dabelea et al. (36) examined prevalence of T2D for 2001 and 2009 among youth aged 10 to 19 years. Although rates of T2D in adult men and women were found to be similar, adolescent girls, for reasons that remain unclear, had a 60% higher prevalence rate than boys. The causes for this sex difference are not understood. Critical gaps and research priorities What are the mechanisms responsible for the associations of maternal phenotype and behavior and childhood environment on risk for CVD in offspring? Are there effective interventions directed at preventing the transgenerational cycle of obesity and diabetes? Why are the rates for adolescent girls developing T2D higher than for adolescent boys? Are there differences in the determinants of dysregulated metabolism and response to the environment in girls and boys? Determinants of Sex Differences in Cardiometabolic Health in Adults Sex and ethnicity In contrast to sex difference findings in adolescents with T2D, the prevalence of T2D in adults in the United States does not differ by sex, yet there is a sex difference in CVD outcomes among those with diabetes. Compared with men with diabetes, women with diabetes have a threefold greater coronary heart disease mortality risk (37, 38). Women with diabetes also have poor survival after myocardial infarction compared with men (39), and women with diabetes have a significantly greater risk of stroke than men with or without diabetes (40). Although the prevalence of peripheral arterial disease in men vs women with diabetes is not firmly established, diabetes is a more significant risk factor for claudication in women compared with men, and women have increased postoperative mortality following revascularization (41, 42). Furthermore, there is an understudied interplay between race/ethnicity and sex on differences in the prevalence of diabetes and its complications. The prevalence of diabetes is greater in race/ethnic minorities in the United States—non-Hispanic blacks (NHBs); Latinos of Puerto Rican, Mexican, and Central American descent; South Asians; and Alaska Natives/Pacific Islanders—compared with non-Hispanic whites (NHWs) (43). Minority women, especially NHBs and Mexican American women, have a higher prevalence of obesity than their male counterparts or NHW women, and there are race/ethnic differences in body fat distribution (43, 44). Overall, the risk of CVD is lower in most minority populations (except Native Americans) compared with NHWs; however, CVD and poststroke mortality rates are higher in NHBs and Latinos, respectively, compared with NHWs (43). Minority populations with diabetes are less physically active, have a higher risk factor burden, and have poorer access to health care compared with NHWs, which may explain their disproportionately adverse outcomes following a CVD event (43). There is a critical need to identify where to focus prevention and intervention strategies to reduce these disparities (39). Sexual dimorphism in lipid metabolism Studies with 3H- and 14C-labeled fatty acids indicated sex differences in adipose tissue and fatty acid metabolism in human subjects (45). Specifically, (1) at any given body mass index, women have more adipose tissue than men; (2) differences in regional adipose tissue exist; (3) net fat gain is sexually dimorphic; (4) sex-specific differences exist in upper vs lower body fat distribution between women and men; and (5) women recycle free fatty acids better than men. Diabetes Women with both type 1 diabetes and T2D face an increased risk for CVD that is at least twofold to fourfold higher than the increase in CVD risk seen in men with diabetes (39). Premenopausal women without diabetes are at a lower risk for CVD than men without diabetes of the same age, and much of this protection from CVD is thought to be due to the effects of estrogen, including receptor-mediated effects on lipid and glucose metabolism, endothelial function, and fat deposition. In contrast, premenopausal women, normally considered to be protected from CVD, appear to lack the cardioprotection if they have diabetes. Women generally have less ectopic fat deposition, more favorable lipid levels, and less insulin resistance than men. In type 1 diabetes, which is primarily diagnosed during the premenopausal years, women seem to lose the benefits of estrogen, as evidenced by a more androgenic pattern of fat deposition and reduced insulin sensitivity that does not differ from that in men with type 1 diabetes. The evidence that estrogen is involved in the sex difference in CVD risk with diabetes is further supported by the fact that other estrogen-related diseases, such as osteoporosis, are also disproportionately increased in women when they have diabetes. Diabetes and exercise Exercise is a cornerstone of treatment of T2D, yet most people with T2D are sedentary. Among other barriers, people with T2D have a reduced maximal and submaximal exercise capacity compared with individuals without diabetes, even in the absence of complications associated with T2D (46). This results in greater effort during low- to moderate-intensity exercise and greater perception of difficulty among people with diabetes than for nondiabetic people. Exercise effort is important because higher effort levels during exercise predict lower adherence to regular physical activity (47). The decrease in cardiorespiratory fitness in people with diabetes compared with individuals without diabetes is greater in women than men. Cardiac abnormalities, particularly an abnormally increased pulmonary capillary wedge pressure with exercise, play a role but cannot account for all of the exercise impairment (48). Abnormalities in mitochondrial function and metabolism and oxygen delivery also likely play a role, and these questions are being investigated currently. Animal models of diabetes suggest that there is limited physiological adaptation to exercise training, that endothelial nitric oxide is unresponsive under diabetic conditions, and that this pathway can be targeted pharmacologically to restore the adaptive response to exercise training (49, 50). Exercise training appears to benefit most people with diabetes, in terms of improved cardiorespiratory fitness, although this is not consistently reported, and sex differences in physiological adaptation to exercise training have not been determined. It is also unclear whether the influences of T2D on exercise effort are more or less pronounced at low, moderate, or vigorous intensities, respectively. Transgender The transgender community represents one of the most underserved and marginalized populations in health care. Because the chromosomal configuration [46 XY in males transitioning to females (transwomen) and 46 XX females transitioning to males (transmen)], remains unchanged (51), these individuals also provide a unique opportunity to determine which metabolic functions are determined by the prevailing milieu of sex steroids. Relevant to CVD risk, both transmales and transfemales exhibit a higher incidence of T2D than the general population (52). Furthermore, data from a large gender identity study suggest that hormone therapy taken by transgender individuals is associated with a higher CV mortality rate among transwomen but not among transmen (52). Despite receiving similar estrogen therapy, transwomen who elected orchiectomy had improved metabolic health compared with transwomen who retained their testes. Furthermore, data suggest that suppression of endogenous testosterone in transwomen appears to improve insulin sensitivity and reduce hepatic steatosis (53). Menopause Estrogen appears to be cardioprotective until the time of menopause unless diabetes is present, after which protective effects are lost as estrogen deficiency develops. Premenopausal women store fat primarily in gluteofemoral depots, which are considered benign or metabolically beneficial, whereas men tend to store fat in abdominal depots that are linked to chronic disease. Critical gaps and research priorities How are sex differences and race/ethnicity interrelated with CVD in diabetes and nonalcoholic fatty liver disease? How do sex and race/ethnicity effects on CVD in individuals with diabetes interact with social and cultural factors known to contribute to CVD? Are there strategies to reduce sex disparities in the use of known CVD preventive interventions? What are the mechanisms underlying the apparent paradox of estrogen having beneficial effects in the premenopausal period and detrimental effects after menopause? What are the mechanisms responsible for sex differences in fuel partitioning, particularly in the context of calorie excess, diabetes, loss of sex hormones, and aging? What are the underlying mechanisms of sex differences in functional exercise capacity and the adaptive exercise training response, and how are these differences altered by age and diabetes? What are the sex difference in therapeutic treatments and effects of diabetes drugs on CVD outcomes and the role of sex hormones? What are the metabolic impacts of cross-hormone therapy (transgender and anabolic steroid use) or androgen and estrogen use in the context of biologically different sex? What Are the Sex Differences That Affect Cardiac Function and Outcomes? Cardiovascular metabolism The heart is a metabolic omnivore that metabolizes a wide variety of substrates to generate the ∼5 kg of adenosine triphosphate/d (or 2 metric tons/y) required for contraction, relaxation, and other processes. Myocardial metabolism is intimately related to cardiac energetics and function. The predominant fuels for the postnatal mammalian heart are fatty acids, although glucose, ketones, lactate, amino acids, and local glycogen and triglycerides may also be used. Different substrates have different advantages/disadvantages. For example, fatty acids generate more adenosine triphosphate/mole than glucose, but glucose is more oxygen efficient. Recent studies using positron emission tomography have shown that sex has a major, quantifiable impact on myocardial metabolism, especially in those with obesity or T2D. In a cross-sectional study of obese and nonobese subjects, female sex predicted higher oxygen consumption, fatty acid utilization and oxidation, and myocardial perfusion but lower glucose utilization, glucose utilization/plasma insulin, and metabolic efficiency (54). Sex also had an effect on myocardial metabolism in a study of obese subjects with and without T2D (55). Female sex again was associated with higher myocardial oxygen consumption and blood flow. Interestingly, sex and T2D interacted in the prediction of plasma fatty acid concentrations, which necessarily influence myocardial metabolism. The women had higher myocardial fatty acid utilization and esterification rates and lower percent oxidation rates than men (55). Last, sex affects the myocardial metabolic response to medications for T2D (56). Cardiovascular outcomes Although there are substantial areas of overlap in CV outcomes between men and women, up to one-third of CVD presentations are sufficiently different between women and men so as to contribute to health disparities‎, because male-pattern CVD is the standard for recognition and treatment (57). Examples of CVD patterns that are more prevalent in women include myocardial infarction with no obstructive coronary artery disease, coronary microvascular dysfunction, and heart failure with preserved ejection fraction, all of which have been understudied (58). Important steps include policy regarding study and trial design to include female-pattern CVD, as well as female-only studies as well as other trials to address the leading health care threat for 52% of the population. Pregnancy-related cardiomyopathy About 1 in 1000 pregnancies worldwide are complicated by the development of dilated cardiomyopathy around the peripartum period, known as peripartum cardiomyopathy (PPCM) (59). The disease strikes otherwise healthy young women and often leads to persistent heart failure, cardiac transplantation, or death. PPCM is thus a serious cardiac disease that is unique to women. Patten and his colleagues (60) have now uncovered two key insights. First, mechanistic work in mouse models and clinical epidemiological and echocardiographic studies have revealed that PPCM is, in large part, a vascular disease triggered by late-gestational vasculo-toxic hormones secreted by the placenta and pituitary during late gestation and the postpartum period. Second, human genetic studies have revealed that a large proportion of women with PPCM carry mutations in the gene TTN, which encodes for titin, a protein critical for sarcomeric function. PPCM is thus a vasculo/hormonal disease, caused in at least a subset of women by underlying genetic predisposition (61). Critical gaps and research priorities What are the fundamental mechanisms underlying differences in heart failure in men and women with diabetes? What is the cause of female preponderance of heart failure with preserved ejection fraction in women? What are the short- and long-term impacts of pregnancy on women’s cardiac health? What is the mechanistic relationship between mutations in titin and the hormonal/vascular insult of pregnancy? How do sex differences in cardiac fuel metabolism influence cardiac function and inform sex-specific interventions for heart failure? Conclusions The NIH Office of Research in Women’s Health has issued a mandate to close the knowledge gap in women’s health and sex/gender research in the basic research as well as in the clinical research arena. In the area of cardiometabolic disease, there is much to be learned to close this gap. Our collective statement described in this article highlights selected ongoing research and, most important, outlines critical research gaps that must be addressed to improve the health of women and the next generation across the life span. Abbreviations: CV cardiovascular CVD cardiovascular disease NHB non-Hispanic black NHW non-Hispanic white NIH National Institutes of Health OVX ovariectomized PE preeclampsia PPCM peripartum cardiomyopathy T2D type 2 diabetes. Conference Speakers in Alphabetical Order Arany, Zoltan, University of Pennsylvania Bairey Merz, C. Noel, Cedars-Sinai Medical Center Barrett-Connor, Elizabeth, University of California, San Diego–School of Medicine Boyle, Kristen, University of Colorado Anschutz Medical Campus Brown, Laura, University of Colorado Anschutz Medical Campus Clegg, Deborah, Cedars-Sinai Medical Center Cree-Green, Melanie, University of Colorado Anschutz Medical Campus Dabelea, Dana, University of Colorado Anschutz Medical Campus Friedman, Jacob, University of Colorado Anschutz Medical Campus Goodyear, Laurie, Joslin Diabetes Center/Harvard Medical School Graham, Ginger Hill-Golden, Sherita, Johns Hopkins University, Department of Medicine Huebschmann, Amy, University of Colorado Anschutz Medical Campus Jenkins, Marjorie, US Food and Drug Administration Jensen, Michael, Mayo Clinic Julian, Colleen, University of Colorado Anschutz Medical Campus Kelsey, Megan, University of Colorado School of Medicine/Children’s Hospital Colorado Kennedy, Brian, Buck Institute for Research on Aging Klemm, Dwight, University of Colorado Anschutz Medical Campus Kohrt, Wendy, University of Colorado Anschutz Medical Campus Lindenfeld, JoAnn, Vanderbilt University Medical Center Moreau, Kerrie, University of Colorado Anschutz Medical Campus Nadeau, Kristen, University of Colorado Anschutz Medical Campus Nelson, J. Lee, Fred Hutchinson Cancer Research Center and University of Washington Nicklas, Jacinda, University of Colorado Anschutz Medical Campus Peterson, Linda, Washington University School of Medicine Regensteiner, Judith, University of Colorado Anschutz Medical Campus Reusch, Jane, University of Colorado and Denver VAMC Roberts, Jim, Magee-Women’s Research Institute Rudolph, Michael, University of Colorado Denver Anschutz Medical Campus Sadovsky, Yoel, Magee-Women’s Research Institute Santoro, Nanette, University of Colorado Anschutz Medical Campus Snell-Bergeon, Janet, University of Colorado Anschutz Medical Campus Wenger, Nanette, Emory University School of Medicine Zeitler, Phil, University of Colorado Anschutz Medical Campus Acknowledgments We thank the staff from the CUSOM Center for Women’s Health Research (Nancy Oudet, MSW, Anne Kercsmar, MA, Elizabeth Hepworth, and David Samson), all conference participants, and the sponsors of the meeting. Financial Support: This work was supported by the University of Colorado School of Medicine; AstraZeneca Independent Medical Education Grant 72236); the Society for Women’s Health Research; Mary & George Sissel; the Boettcher Foundation; the Specialized Center of Research on Sex Differences, NIH Grant P50 HD073063; UCHealth; Gilead Sciences; the Colorado BioScience Association; and Sanofi. Disclosure Summary: The authors have nothing to disclose. References 1. Yusuf S, Reddy S, Ounpuu S, Anand S. Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation . 2001; 104( 22): 2746– 2753. Google Scholar CrossRef Search ADS PubMed  2. Gupta D, Wenger NK. Guidelines for the prevention of cardiovascular disease in women: international challenges and opportunities. Expert Rev Cardiovasc Ther . 2014; 10( 3): 379– 385. Google Scholar CrossRef Search ADS   3. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet . 2004; 364( 9438): 937– 952. Google Scholar CrossRef Search ADS PubMed  4. Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S. Explaining the decrease in U.S. deaths from coronary disease, 1980–2000. N Engl J Med . 2007; 356( 23): 2388– 2398. Google Scholar CrossRef Search ADS PubMed  5. Towfighi A, Zheng L, Ovbiagele B. Sex-specific trends in midlife coronary heart disease risk and prevalence. Arch Intern Med . 2009; 169( 19): 1762– 1766. Google Scholar CrossRef Search ADS PubMed  6. Jones WS, Duscha BD, Robbins JL, Duggan NN, Regensteiner JG, Kraus WE, Hiatt WR, Dokun AO, Annex BH. Alteration in angiogenic and anti-angiogenic forms of vascular endothelial growth factor-A in skeletal muscle of patients with intermittent claudication following exercise training. Vasc Med . 2012; 17: 94– 100. Google Scholar CrossRef Search ADS PubMed  7. Al-Qahtani SM, Bryzgalova G, Valladolid-Acebes I, Korach-André M, Dahlman-Wright K, Efendić S, Berggren PO, Portwood N. 17β-Estradiol suppresses visceral adipogenesis and activates brown adipose tissue-specific gene expression. Horm Mol Biol Clin Investig . 2017; 29( 1): 13– 26. Google Scholar PubMed  8. Yasrebi A, Rivera JA, Krumm EA, Yang JA, Roepke TA. Activation of estrogen response element-independent ERα signaling protects female mice from diet-induced obesity. Endocrinology . 2017; 158( 2): 319– 334. Google Scholar PubMed  9. Chen X, McClusky R, Chen J, Beaven SW, Tontonoz P, Arnold AP, Reue K. The number of x chromosomes causes sex differences in adiposity in mice. PLoS Genet . 2012; 8( 5): e1002709. Google Scholar CrossRef Search ADS PubMed  10. Gavin KM, Gutman JA, Kohrt WM, Wei Q, Shea KL, Miller HL, Sullivan TM, Erickson PF, Helm KM, Acosta AS, Childs CR, Musselwhite E, Varella-Garcia M, Kelly K, Majka SM, Klemm DJ. De novo generation of adipocytes from circulating progenitor cells in mouse and human adipose tissue. FASEB J . 2015; 30( 3): 1096– 1108. Google Scholar CrossRef Search ADS PubMed  11. Mitchell SJ, Madrigal-Matute J, Scheibye-Knudsen M, Fang E, Aon M, González-Reyes JA, Cortassa S, Kaushik S, Gonzalez-Freire M, Patel B, Wahl D, Ali A, Calvo-Rubio M, Burón MI, Guiterrez V, Ward TM, Palacios HH, Cai H, Frederick DW, Hine C, Broeskamp F, Habering L, Dawson J, Beasley TM, Wan J, Ikeno Y, Hubbard G, Becker KG, Zhang Y, Bohr VA, Longo DL, Navas P, Ferrucci L, Sinclair DA, Cohen P, Egan JM, Mitchell JR, Baur JA, Allison DB, Anson RM, Villalba JM, Madeo F, Cuervo AM, Pearson KJ, Ingram DK, Bernier M, de Cabo R. Effects of sex, strain, and energy intake on hallmarks of aging in mice. Cell Metab . 2016; 23( 6): 1093– 1112. Google Scholar CrossRef Search ADS PubMed  12. Ashpole NM, Logan S, Yabluchanskiy A, Mitschelen MC, Yan H, Farley JA, Hodges EL, Ungvari Z, Csiszar A, Chen S, Georgescu C, Hubbard GB, Ikeno Y, Sonntag WE. IGF-1 has sexually dimorphic, pleiotropic, and time-dependent effects on healthspan, pathology, and lifespan. Geroscience  2017; 39( 2): 129– 145. Google Scholar CrossRef Search ADS PubMed  13. Miller RA, Harrison DE, Astle CM, Floyd RA, Flurkey K, Hensley KL, Javors MA, Leeuwenburgh C, Nelson JF, Ongini E, Nadon NL, Warner HR, Strong R. An Aging Interventions Testing Program: study design and interim report. Aging Cell . 2007; 6( 4): 565– 575. Google Scholar CrossRef Search ADS PubMed  14. Kennedy BK, Lamming DW. The mechanistic target of rapamycin: the grand conducTOR of metabolism and aging. Cell Metab . 2016; 23( 6): 990– 1003. Google Scholar CrossRef Search ADS PubMed  15. Stanford KI, Lee MY, Getchell KM, So K, Hirshman MF, Goodyear LJ. Exercise before and during pregnancy prevents the deleterious effects of maternal high-fat feeding on metabolic health of male offspring. Diabetes . 2014; 64( 2): 427– 433. Google Scholar CrossRef Search ADS PubMed  16. Raipuria M, Bahari H, Morris MJ. Effects of maternal diet and exercise during pregnancy on glucose metabolism in skeletal muscle and fat of weanling rats. PLoS One . 2015; 10( 4): e0120980. Google Scholar CrossRef Search ADS PubMed  17. Tomić V, Sporiš G, Tomić J, Milanović Z, Zigmundovac-Klaić D, Pantelić S. The effect of maternal exercise during pregnancy on abnormal fetal growth. Croat Med J . 2013; 54( 4): 362– 368. Google Scholar CrossRef Search ADS PubMed  18. Manders MA, Sonder GJ, Mulder EJ, Visser GH. The effects of maternal exercise on fetal heart rate and movement patterns. Early Hum Dev . 1997; 48( 3): 237– 247. Google Scholar CrossRef Search ADS PubMed  19. O’Connor PJ, Poudevigne MS, Cress ME, Motl RW, Clapp JF III. Safety and efficacy of supervised strength training adopted in pregnancy. J Phys Act Health . 2011; 8( 3): 309– 320. Google Scholar CrossRef Search ADS PubMed  20. Sheridan MA, Yunusov D, Balaraman V, Alexenko AP, Yabe S, Verjovski-Almeida S, Schust DJ, Franz AW, Sadovsky Y, Ezashi T, Roberts RM. Vulnerability of primitive human placental trophoblast to Zika virus. Proc Natl Acad Sci USA . 2017; 114( 9): E1587– E1596. Google Scholar CrossRef Search ADS PubMed  21. Chang G, Mouillet JF, Mishima T, Chu T, Sadovsky E, Coyne CB, Parks WT, Surti U, Sadovsky Y. Expression and trafficking of placental microRNAs at the feto-maternal interface. FASEB J . 2017; 31( 7): 2760– 2770. Google Scholar CrossRef Search ADS PubMed  22. Barbour LA. Changing perspectives in pre-existing diabetes and obesity in pregnancy: maternal and infant short- and long-term outcomes. Curr Opin Endocrinol Diabetes Obes . 2014; 21( 4): 257– 263. Google Scholar CrossRef Search ADS PubMed  23. Voortman T, Tielemans MJ, Stroobant W, Schoufour JD, Kiefte-de Jong JC, Steenweg-de Graaff J, van den Hooven EH, Tiemeier H, Jaddoe VWV, Franco OH. Plasma fatty acid patterns during pregnancy and child’s growth, body composition, and cardiometabolic health: The Generation R Study [published online ahead of print April 13, 2017]. Clin Nutr . doi: 10.1016/j.clnu.2017.04.006. 24. Zhou X, Niu JM, Ji WJ, Zhang Z, Wang PP, Ling XF, Li YM. Precision test for precision medicine: opportunities, challenges and perspectives regarding pre-eclampsia as an intervention window for future cardiovascular disease. Am J Transl Res . 2016; 8( 5): 1920– 1934. Google Scholar PubMed  25. Choi DJ, Yoon CH, Lee H, Ahn SY, Oh KJ, Park HY, Lee HY, Cho MC, Chung IM, Shin MS, Park SJ, Shim CY, Han SW, Chae IH. The association of family history of premature cardiovascular disease or diabetes mellitus on the occurrence of gestational hypertensive disease and diabetes. PLoS One . 2016; 11( 12): e0167528. Google Scholar CrossRef Search ADS PubMed  26. Retnakaran R, Shah BR. Role of type 2 diabetes in determining retinal, renal, and cardiovascular outcomes in women with previous gestational diabetes mellitus. Diabetes Care . 2016; 40( 1): 101– 108. Google Scholar CrossRef Search ADS PubMed  27. Brown LD, Hay WW Jr. Impact of placental insufficiency on fetal skeletal muscle growth. Mol Cell Endocrinol . 2016; 435: 69– 77. Google Scholar CrossRef Search ADS PubMed  28. Brown LD, Davis M, Wai S, Wesolowski SR, Hay WW Jr, Limesand SW, Rozance PJ. Chronically increased amino acids improve insulin secretion, pancreatic vascularity, and islet size in growth-restricted fetal sheep. Endocrinology . 2016; 157( 10): 3788– 3799. Google Scholar CrossRef Search ADS PubMed  29. Brown LD, Kohn JR, Rozance PJ, Hay WW Jr, Wesolowski SR. Exogenous amino acids suppress glucose oxidation and potentiate hepatic glucose production in late gestation fetal sheep. Am J Physiol Regul Integr Comp Physiol . 2017; 312( 5): R654– R663. Google Scholar CrossRef Search ADS PubMed  30. Mittal A, Pachter L, Nelson JL, Kjærgaard H, Smed MK, Gildengorin VL, Zoffmann V, Hetland ML, Jewell NP, Olsen J, Jawaheer D. Pregnancy-induced changes in systemic gene expression among healthy women and women with rheumatoid arthritis. PLoS One . 2015; 10( 12): e0145204. Google Scholar CrossRef Search ADS PubMed  31. Gammill HS, Stephenson MD, Aydelotte TM, Nelson JL. Microchimerism in recurrent miscarriage. Cell Mol Immunol . 2014; 11( 6): 589– 594. Google Scholar CrossRef Search ADS PubMed  32. McLean A, Osgood N, Newstead-Angel J, Stanley K, Knowles D, van der Kamp W, Qian W, Dyck R. Building research capacity: results of a feasibility study using a novel mHealth epidemiological data collection system within a gestational diabetes population. Stud Health Technol Inform . 2017; 234: 228– 232. Google Scholar PubMed  33. Iaffaldano L, Nardelli C, Raia M, Mariotti E, Ferrigno M, Quaglia F, Labruna G, Capobianco V, Capone A, Maruotti GM, Pastore L, Di Noto R, Martinelli P, Sacchetti L, Del Vecchio L. High aminopeptidase N/CD13 levels characterize human amniotic mesenchymal stem cells and drive their increased adipogenic potential in obese women. Stem Cells Dev . 2013; 22( 16): 2287– 2297. Google Scholar CrossRef Search ADS PubMed  34. Boyle KE, Patinkin ZW, Shapiro AL, Baker PR II, Dabelea D, Friedman JE. Mesenchymal stem cells from infants born to obese mothers exhibit greater potential for adipogenesis: the Healthy Start BabyBUMP Project. Diabetes . 2015; 65( 3): 647– 659. Google Scholar CrossRef Search ADS PubMed  35. Chen JR, Lazarenko OP, Blackburn ML, Rose S, Frye RE, Badger TM, Andres A, Shankar K. Maternal obesity programs senescence signaling and glucose metabolism in osteo-progenitors from rat and human. Endocrinology . 2016; 157( 11): 4172– 4183. Google Scholar CrossRef Search ADS PubMed  36. Dabelea D, Mayer-Davis EJ, Saydah S, Imperatore G, Linder B, Divers J, Bell R, Badaru A, Talton JW, Crume T, Liese AD, Merchant AT, Lawrence JM, Reynolds K, Dolan L, Liu LL, Hamman RF; SEARCH for Diabetes in Youth Study. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA . 2014; 311( 17): 1778– 1786. Google Scholar CrossRef Search ADS PubMed  37. Manson JE, Colditz GA, Stampfer MJ, Willett WC, Krolewski AS, Rosner B, Arky RA, Speizer FE, Hennekens CH. A prospective study of maturity-onset diabetes mellitus and risk of coronary heart disease and stroke in women. Arch Intern Med . 1991; 151( 6): 1141– 1147. Google Scholar CrossRef Search ADS PubMed  38. Preis SR, Hwang SJ, Coady S, Pencina MJ, D’Agostino RB Sr, Savage PJ, Levy D, Fox CS. Trends in all-cause and cardiovascular disease mortality among women and men with and without diabetes mellitus in the Framingham Heart Study, 1950 to 2005. Circulation . 2009; 119( 13): 1728– 1735. Google Scholar CrossRef Search ADS PubMed  39. Regensteiner JG, Golden S, Huebschmann AG, Barrett-Connor E, Chang AY, Chyun D, Fox CS, Kim C, Mehta N, Reckelhoff JF, Reusch JE, Rexrode KM, Sumner AE, Welty FK, Wenger NK, Anton B; American Heart Association Diabetes Committee of the Council on Lifestyle and Cardiometabolic Health, Council on Epidemiology and Prevention, Council on Functional Genomics and Translational Biology, and Council on Hypertension. Sex differences in the cardiovascular consequences of diabetes mellitus: a scientific statement from the American Heart Association. Circulation . 2015; 132( 25): 2424– 2447. Google Scholar CrossRef Search ADS PubMed  40. Peters SA, Huxley RR, Woodward M. Diabetes as a risk factor for stroke in women compared with men: a systematic review and meta-analysis of 64 cohorts, including 775,385 individuals and 12,539 strokes. Lancet . 2014; 383( 9933): 1973– 1980. Google Scholar CrossRef Search ADS PubMed  41. Gardner AW, Parker DE, Montgomery PS, Blevins SM. Diabetic women are poor responders to exercise rehabilitation in the treatment of claudication. J Vasc Surg . 2014; 59( 4): 1036– 1043. Google Scholar CrossRef Search ADS PubMed  42. Magnant JG, Cronenwett JL, Walsh DB, Schneider JR, Besso SR, Zwolak RM. Surgical treatment of infrainguinal arterial occlusive disease in women. J Vasc Surg . 1993; 17: 67– 76; discussion 76–78. Google Scholar CrossRef Search ADS PubMed  43. Golden SH, Brown A, Cauley JA, Chin MH, Gary-Webb TL, Kim C, Sosa JA, Sumner AE, Anton B. Health disparities in endocrine disorders: biological, clinical, and nonclinical factors—an Endocrine Society scientific statement. J Clin Endocrinol Metab . 2012; 97( 9): E1579– E1639. Google Scholar CrossRef Search ADS PubMed  44. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA . 2012; 307( 5): 491– 497. Google Scholar CrossRef Search ADS PubMed  45. Santosa S, Jensen MD. The sexual dimorphism of lipid kinetics in humans. Front Endocrinol (Lausanne) . 2015; 6: 103. Google Scholar PubMed  46. Regensteiner JG, Sippel J, McFarling ET, Wolfel EE, Hiatt WR. Effects of non-insulin-dependent diabetes on oxygen consumption during treadmill exercise. Med Sci Sports Exerc . 1995; 27( 5): 661– 667. Google Scholar CrossRef Search ADS PubMed  47. Huebschmann AG, Reis EN, Emsermann C, Dickinson LM, Reusch JE, Bauer TA, Regensteiner JG. Women with type 2 diabetes perceive harder effort during exercise than nondiabetic women. Appl Physiol Nutr Metab . 2009; 34: 851– 857. Google Scholar CrossRef Search ADS PubMed  48. Regensteiner JG, Bauer TA, Reusch JE, Quaife RA, Chen MY, Smith SC, Miller TM, Groves BM, Wolfel EE. Cardiac dysfunction during exercise in uncomplicated type 2 diabetes. Med Sci Sports Exerc . 2009; 41( 5): 977– 984. Google Scholar CrossRef Search ADS PubMed  49. Keller AC, Knaub LA, Miller MW, Birdsey N, Klemm DJ, Reusch JE. Saxagliptin restores vascular mitochondrial exercise response in the Goto-Kakizaki rat. J Cardiovasc Pharmacol . 2015; 65( 2): 137– 147. Google Scholar PubMed  50. Miller MW, Knaub LA, Olivera-Fragoso LF, Keller AC, Balasubramaniam V, Watson PA, Reusch JE. Nitric oxide regulates vascular adaptive mitochondrial dynamics. Am J Physiol Heart Circ Physiol . 2013; 304( 12): H1624– H1633. Google Scholar CrossRef Search ADS PubMed  51. Gooren LJ, Kreukels B, Lapauw B, Giltay EJ. (Patho)physiology of cross-sex hormone administration to transsexual people: the potential impact of male-female genetic differences. Andrologia . 2014; 47( 1): 5– 19. Google Scholar CrossRef Search ADS PubMed  52. Wierckx K, Elaut E, Declercq E, Heylens G, De Cuypere G, Taes Y, Kaufman JM, T’Sjoen G. Prevalence of cardiovascular disease and cancer during cross-sex hormone therapy in a large cohort of trans persons: a case-control study. Eur J Endocrinol . 2013; 169( 4): 471– 478. Google Scholar CrossRef Search ADS PubMed  53. Morselli E, Santos RS, Criollo A, Nelson MD, Palmer BF, Clegg DJ. The effects of oestrogens and their receptors on cardiometabolic health. Nat Rev Endocrinol . 2017; 13( 6): 352– 364. Google Scholar CrossRef Search ADS PubMed  54. Peterson LR, Soto PF, Herrero P, Mohammed BS, Avidan MS, Schechtman KB, Dence C, Gropler RJ. Impact of gender on the myocardial metabolic response to obesity. JACC Cardiovasc Imaging . 2008; 1( 4): 424– 433. Google Scholar CrossRef Search ADS PubMed  55. Peterson LR, Saeed IM, McGill JB, Herrero P, Schechtman KB, Gunawardena R, Recklein CL, Coggan AR, DeMoss AJ, Dence CS, Gropler RJ. Sex and type 2 diabetes: obesity-independent effects on left ventricular substrate metabolism and relaxation in humans. Obesity (Silver Spring) . 2011; 20( 4): 802– 810. Google Scholar CrossRef Search ADS PubMed  56. Lyons MR, Peterson LR, McGill JB, Herrero P, Coggan AR, Saeed IM, Recklein C, Schechtman KB, Gropler RJ. Impact of sex on the heart’s metabolic and functional responses to diabetic therapies. Am J Physiol Heart Circ Physiol . 2013; 305( 11): H1584– H1591. Google Scholar CrossRef Search ADS PubMed  57. Humphries KH, Izadnegahdar M, Sedlak T, Saw J, Johnston N, Schenck-Gustafsson K, Shah RU, Regitz-Zagrosek V, Grewal J, Vaccarino V, Wei J, Bairey Merz CN. Sex differences in cardiovascular disease—impact on care and outcomes. Front Neuroendocrinol . 2017; 46: 46– 70. Google Scholar CrossRef Search ADS PubMed  58. Bairey Merz CN, Pepine CJ, Walsh MN, Fleg JL. Ischemia and no obstructive coronary artery disease (INOCA): developing evidence-based therapies and research agenda for the next decade. Circulation . 2017; 135( 11): 1075– 1092. Google Scholar CrossRef Search ADS PubMed  59. Arany Z, Elkayam U. Peripartum cardiomyopathy. Circulation . 2016; 133( 14): 1397– 1409. Google Scholar CrossRef Search ADS PubMed  60. Patten IS, Rana S, Shahul S, Rowe GC, Jang C, Liu L, Hacker MR, Rhee JS, Mitchell J, Mahmood F, Hess P, Farrell C, Koulisis N, Khankin EV, Burke SD, Tudorache I, Bauersachs J, del Monte F, Hilfiker-Kleiner D, Karumanchi SA, Arany Z. Cardiac angiogenic imbalance leads to peripartum cardiomyopathy. Nature . 2012; 485( 7398): 333– 338. Google Scholar CrossRef Search ADS PubMed  61. Ware JS, Li J, Mazaika E, Yasso CM, DeSouza T, Cappola TP, Tsai EJ, Hilfiker-Kleiner D, Kamiya CA, Mazzarotto F, Cook SA, Halder I, Prasad SK, Pisarcik J, Hanley-Yanez K, Alharethi R, Damp J, Hsich E, Elkayam U, Sheppard R, Kealey A, Alexis J, Ramani G, Safirstein J, Boehmer J, Pauly DF, Wittstein IS, Thohan V, Zucker MJ, Liu P, Gorcsan J III, McNamara DM, Seidman CE, Seidman JG, Arany Z; IMAC-2 and IPAC Investigators. Shared genetic predisposition in peripartum and dilated cardiomyopathies. N Engl J Med . 2016; 374( 3): 233– 241. Google Scholar CrossRef Search ADS PubMed  Copyright © 2018 Endocrine Society http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Endocrinology Oxford University Press

Identifying the Critical Gaps in Research on Sex Differences in Metabolism Across the Life Span

Loading next page...
1
 
/lp/ou_press/identifying-the-critical-gaps-in-research-on-sex-differences-in-W4vb9olHNr

References (65)

Publisher
Oxford University Press
Copyright
Copyright © 2018 Endocrine Society
ISSN
0013-7227
eISSN
1945-7170
DOI
10.1210/en.2017-03019
pmid
29300998
Publisher site
See Article on Publisher Site

Abstract

Abstract The National Institutes of Health (NIH) Office of Research in Women’s Health now functions under a mandate calling for the systematic inclusion of both female and male cells, animals, and human subjects in all types of research, so that sex as a biological variable is understood in health and disease. Sex-specific data can improve disease prevention, diagnosis, and treatment as well as reduce inequities. Inclusion of women in research studies has modestly improved over the last 20 years, yet preclinical research is still primarily done using male animal models and male-derived cells, with the result that many conclusions are made based on incomplete and sex-biased data. There are important, yet poorly studied, sex differences in cardiometabolic disease. To begin to address these sex differences, the Center for Women’s Health Research at the University of Colorado held its inaugural National Conference, “Sex Differences Across the Lifespan: A Focus on Metabolism,” in September 2016 (cwhr@ucdenver.edu). Research to address the important goal of understanding key sex differences in cardiometabolic disease across the life span is lacking. The goal of this article is to discuss the current state of research addressing sex differences in cardiometabolic health across the life span, to outline critical research gaps that must be addressed in response to NIH mandates, and, importantly, to develop strategies to address sex as a biological variable to understand disease mechanisms as well as develop diagnostic and therapeutic modalities. Although inclusion of women in research studies has improved over the last 20 years, preclinical research is still primarily done using male animal models and male-derived cells, with the result that many conclusions are made based on incomplete and sex-biased data. The National Institutes of Health (NIH) Office of Research in Women’s Health now functions under a mandate calling for the systematic inclusion of both female and male cells, animals, and human subjects in all types of research, so that sex as a biological variable is considered in health and disease. Sex-specific data can improve disease prevention, diagnosis, and treatment as well as reduce inequities. Research to address the important goal of understanding key sex differences in cardiometabolic disease across the life span is lacking (Table 1). Table 1. Proportion of NIH Budget Allocated to Research in Areas of Interest to Women’s Health Institute  Percentage of NIH Total Budget  NICHD  4.1  NIMH  4.8  NHLBI  9.6  NCI  16.1  Women’s healtha  14  Institute  Percentage of NIH Total Budget  NICHD  4.1  NIMH  4.8  NHLBI  9.6  NCI  16.1  Women’s healtha  14  Of the total $32.3 billion NIH budget, a small proportion is allocated to the areas of maternal, fetal, and women’s health specifically, despite the potential to pay huge dividends in life span. It is not currently possible to discern specific funding lines. Abbreviations: NCI, National Cancer Institute; NHLBI, National Heart, Lung, and Blood Institute; NICHD, Eunice Kennedy Shriver National institute of Child Health and Human Development; NIMH, National Institute of Mental Health. a Reporting for this category does not follow the standard NIH Research, Condition, and Disease Categorization process. This category assigns project funding according to populations tracked by sex or ethnicity. The databases used to track sex or ethnicity are complex and are not currently compatible with the NIH Research, Condition, and Disease Categorization system (https://report.nih.gov/categorical_spending.aspx#legend11). View Large There are important, yet poorly studied, sex differences in cardiometabolic disease. To begin to address these sex differences, the Center for Women’s Health Research at the University of Colorado held its inaugural National Conference, “Sex Differences Across the Lifespan: A Focus on Metabolism,” in September 2016 (cwhr@ucdenver.edu). Based on the research presentations and discussions from that conference, the goal of this article is to discuss the current state of research addressing sex differences in cardiometabolic health across the life span, to outline critical research gaps that must be addressed in response to NIH mandates and, importantly, to develop strategies to address sex as a biological variable to understand disease mechanisms as well as develop diagnostic and therapeutic modalities. The Urgency of the Burden of Cardiometabolic Disease in Women Although cardiovascular disease (CVD) is the most prevalent cause of death in both men and women, much less is known about its effects in women than in men, and there are important differences being identified. In women, CVD is the leading cause of mortality and morbidity for US women; one in four US women die of CVD, which is twice as many as from all forms of cancer combined (1, 2). In 2008, there were 9,127,416 CVD deaths in women worldwide, representing one-third of all deaths. The INTERHEART report indicates that 94% of the population-adjusted cardiovascular (CV) mortality in women is due to modifiable risk factors. In the United States, two of three women have at least one major coronary risk factor (3). Overall mortality from CVD decreased from 1997 to 2013, but in women ages 35 to 54 years, mortality is increasing by 1% annually, an increase attributed to rising rates of obesity, diabetes, and sedentary lifestyle (4, 5). Furthermore, CVD is becoming a major problem in other low- and middle-income countries, with a projected 120% increase in CV mortality in women living in the poorer countries between 1990 and 2020, compared with 29% in women living in wealthier countries. Globally, women are especially vulnerable as 60% of the world’s poor and two-thirds of illiterate adults are women (www.who.int/pmnch/topics/maternal/2011_women_ncd_report.pdf). This document is not intended to be comprehensive with regard to all cardiometabolic issues affecting women’s health and sex differences; rather, it will highlight key issues, discuss research gaps, and comment on research priorities. Research is urgently needed to identify the mechanisms responsible for the above sex-specific increases in CVD risk and to develop therapies that are safe and effective in women. This research must take into account biological and behavioral factors that differ between women and men, including unique exposures in women across the life span from conception through aging. In the following sections, we elaborate upon the unique biological issues faced by women across the life span, as well as the sex differences in each phase of life. Priorities in the Fundamental Research on Sex as a Biological Variable for Cardiometabolism Energy balance Evidence suggests estrogens regulate fat distribution (6). Rodent studies specifically demonstrate that estrogen loss [ovariectomized (OVX), estrogen receptor α (ESR1 or ERα) Esr1−/− and GnRH agonist-treated mice] leads to decreased physical activity, increased adiposity, and decreased muscle mass, whereas estrogen replacement reverses these changes. In addition, in a high-fat diet model, estradiol had a beneficial impact to decrease visceral adipose tissue and increase brown adipose tissue (7). Manipulation of ERα demonstrates that the impact of estradiol in diet-induced obesity is both central and peripheral (8). Similarly, studies in humans during female-specific age-related transitions demonstrate increased adiposity, with redistribution of fat to abdominal depots and increased incidence of metabolic dysfunction. The specific role of estrogen vs age in these transitions is being studied. Sex hormones regulate fat distribution in part by controlling lipid uptake and lipolysis in a sex- and depot-specific manner. Sex chromosomes and adiposity Employing a recently developed four-core genotype mouse modeling system, insights have been generated as to the contributions of genetic and hormonal mechanisms underlying sex differences in obesity (8, 9). Regardless of XX or XY status, gonad-intact male mice have greater body weight than female mice; in addition, XX status is associated with an increased weight regardless of gonadal sex. In this same model, manipulation of sex hormones with gonadectomy indicates that XX status is associated with greater fat mass gain than XY status (9). The molecular contribution of the X chromosome to adiposity requires further study. Sex hormone regulation of adipocyte precursors The recent identification of distinct adipocyte subpopulations—specifically, their progenitor cells and developmental origins—opens the door to understanding the impact of sex hormones on regional adipocyte production. Gavin et al. (10) exploited fate-mapping strategies to show that a subpopulation of adipocytes is produced from bone marrow stem cells in mice. These marrow-derived adipocytes preferentially accumulate in adipose tissue of females rather than males and in abdominal rather than peripheral fat depots. Importantly, these cells exhibit a highly proinflammatory adipokine profile and, therefore, a potentially harmful phenotype. Marrow-derived adipocytes have been detected in humans, highlighting their clinical relevance. Klemm, Kohrt, and Gavin subsequently tested whether loss of ovarian hormone production in OVX mice would influence the production and distribution of marrow-derived adipocytes (D. J. Klemm, W. Kohrt, and K. Gavin, unpublished data, November 2017). The percentage of marrow-derived adipocytes was more than twofold higher in the abdominal fat of OVX mice compared with controls, but percentages in peripheral fat were only minimally increased. Replacement of estradiol, but not progesterone, reduced marrow-derived adipocyte production to levels below those measured in surgery-naive mice. Estradiol appeared to act through estrogen receptor α (ESR1 or ERα) as marrow-derived adipocyte production was stimulated in abdominal fat of female Esr2 knockout mice. The results demonstrate that loss of ovarian hormone signaling elicits preferential accumulation of marrow-derived adipocytes in abdominal adipose tissue. This process may explain in part the redistribution of fat and changes in adipose tissue function that contribute to chronic metabolic dysfunction at menopause. Aging Sex differences in human aging have been defined in a wide range of demographic and experimental studies, yet the molecular mechanisms underlying these differences remain poorly understood. In mouse strains, females do not always live longer than males; however, there are distinct differences in how females and males respond to interventions that extend life span (11). For instance, reduced insulin–insulinlike growth factor signaling leads to greater life span extension in females than males (12), whereas aspirin and other interventions thought to reduce inflammation have more pronounced effects in males (13). Rapamycin, an inhibitor of the mTOR pathway, causes the most pronounced extension of mouse life span of any drug and mediates this effect in both sexes, although the extension is greater in females (14). The mTOR protein kinase (in the TORC1 complex) phosphorylates substrates involved in control of cell growth, proliferation, and stress response pathways. With aging, two downstream substrates behave differently in males and females, and these differences may underlie the differential effects of other longevity drugs in females and males. To achieve the ultimate goal of preventing age-associated chronic disease states and maintain human function later in life, it is necessary to understand sex differences with respect to aging and longevity interventions. Critical gaps and research priorities What are the mechanisms whereby sex hormones regulate body mass and how do they interact with diet and age? What is the relative contribution of estrogen signaling in the brain vs the periphery on body weight regulation? What are the molecular mechanisms whereby XX status contributes to increased fat mass? What is the metabolic consequence of sex hormone regulation of bone marrow–derived adipocytes? How can we extrapolate lessons learned regarding sex differences in aging in cell and animal models to human aging and disease? Research Priorities for Cardiometabolic Risk with Pregnancy: Mother and Offspring Fetal origins of adult disease comprise a compelling area of study that provides a rationale for addressing cardiometabolic disease across the life span, including pregestation. Pregnancy conditions also affect lifetime CV risk in the mother. Additional acquired sex differences in cardiometabolic function present across the life span (childhood, puberty, adulthood, menopause, and aging) and interact with environmental factors, disease, and metabolic stress (exercise, obesity, diabetes). Preconception Maternal and paternal fitness prior to conception affects offspring metabolic health. For example, Stanford et al. (15) have tested the impact of exercise (maternal, paternal, or both) upon offspring health outcomes in rats. Of particular note, maternal exercise before and during pregnancy significantly improved glucose tolerance and decreased insulin concentrations in offspring. There was an additive metabolic benefit for offspring if both parents underwent exercise training. Exercise specifically affected hepatic metabolism. Raipuria et al. (16) reported that maternal exercise appeared to decrease the metabolic risk induced by maternal obesity in rats, improving insulin/glucose metabolism, with greater effects in male than female offspring [(15) (heart), (16) (skeletal muscle and fat)]. In humans, Tomić et al. (17) reported that maternal physical activity reduced gestational diabetes. This was in contrast to older reports that provided a cautionary or neutral message about maternal exercise in humans [(18), (19) review]. Pregnancy Pregnancy has a unique and substantial impact on the future health of both mother and baby across a wide range of conditions and risk factors. Common pregnancy complications such as gestational diabetes, hypertensive disorders of pregnancy, behavioral health challenges, and preterm birth all increase future risk for cardiometabolic and other disease in both mother and child. Placental biology The placenta controls gas and nutrient exchange, waste transfer from the fetus to the mother, and immune and endocrine support to the developing fetus. The molecular mechanisms underlying many of these functions are only beginning to be elucidated yet are central to our understanding of fetal development and pregnancy health and disease. One example of a critical placental function is defense against microbial infection, where the trophoblast, which is directly bathed in maternal blood, restricts the spread of pathogens into the fetal compartment. Sheridan et al. (20) recently found that cultured primary human trophoblast from term, healthy placentas are resistant to infection by diverse types of DNA and RNA viruses. Moreover, resistance to infection can be conferred to nonplacental cells by transferring trophoblast-conditioned medium to recipient cells [specifically microRNAs from the chromosome 19 microRNA cluster (C19MC)] (21). These findings suggest that trophoblast communicates protective molecular signals, which are packaged within exosomes that are released into the maternal circulation and, possibly, transmitted to the fetal compartment. Because dysfunctional or diseased placenta may adversely affect the health of the fetus and offspring after birth, this line of emerging research illuminating the role of the placenta beyond nutrient and waste transfer is important in understanding the long-term consequences of placental function on metabolic health. Critical gaps and research priorities What is the impact of parental health behaviors on offspring metabolic health and is there a differential impact on female and male offspring? What are the mechanisms whereby maternal and paternal fitness and metabolic health prior to conception contribute to the metabolic phenotype of the offspring? What are the mechanisms of pregnancy and early life critical periods for programming cardiometabolic disease susceptibility in women and their offspring? How does the fetal sex influence maternal adaptation to pregnancy and placental function? Are there sex differences in fetal response to placental dysfunction? What are the mechanisms underlying the long-term effect of feto-placental injury? What are the molecular mechanisms underlying placental cell defense? Research Priorities Related to Cardiometabolic Disease in Pregnancy Obesity in pregnancy Nearly two-thirds of American women of childbearing age are overweight or obese, and almost half these women, once pregnant, have excess gestational weight gain that contributes to their cardiometabolic risk, as well as that of the next generation (22). For example, infants born to obese mothers have increased liver fat and are at higher risk of obesity, diabetes, nonalcoholic hepatic steatosis, and increased mortality due to CVD (23). Research has not vigorously tested the impact of the sex of the offspring on these outcomes. Preeclampsia and hypertensive diseases of pregnancy Preeclampsia (PE) increases a twofold to fourfold risk for ischemic heart disease in women. Data regarding the impact of PE on offspring suggest an increased incidence of hypertension and QRISK (global lifetime risk for CVD) (24). To date, PE is not included in CVD risk engines or routinely assessed in young adults at excess risk for hypertension. The mechanism whereby PE contributes to excess risk in mothers and offspring is unknown, Gestational diabetes Gestational diabetes confers a 7- to 12-fold increased risk for developing type 2 diabetes (T2D) in 5 to 10 years after delivery, whereas preeclampsia, preterm delivery, delivery of a small-for-gestational age neonate, and gestational diabetes are independently associated with a 50% to 300% increased risk for CVD (25, 26). Postpartum weight retention exacerbates this risk; pregnancy weight retained beyond 6 to 12 months postpartum tends to be retained long term and is independently linked to future obesity, CVD, and T2D. Intrauterine growth restriction Intrauterine growth restriction in a sheep model system results in decreases in amino acid uptake rate, muscle myofiber area, and muscle mass (27). However, the impact of this on future dysmetabolism is unclear. In this same model, there is hepatic insulin resistance and decreased β-cell mass (28). This constellation of changes in organ development likely contributes to increased risk of diabetes in intrauterine growth restriction offspring. Of great interest, supplementation of amino acids in utero can reverse some of these effects (29). Reproductive immunology Sex hormones have failed to fully explain the female predominance of autoimmunity. However, immunological changes that occur during and after pregnancy have durability across the life span and may play an important role in evolution of autoimmunity (30). There is also growing awareness of accelerated CVD in women with some autoimmune diseases, an association that has also not been explained by sex hormones. Microchimerism is a phenomenon of pregnancy in which there is bidirectional transport between mother and fetus, including immune regulatory (Treg) cells (31). The maternal and fetal microchimerism is widespread, and the cells lodge themselves throughout the body. The importance of microchimerism on autoimmune disease and the attendant CV risk is an emerging area of sex differences research. Technology-driven interventions Women of childbearing age are among the fastest growing users of technology, across race and socioeconomic class. The use of eHealth has advantages over traditional face-to-face lifestyle interventions, especially for the difficult-to-reach postpartum population, including allowing for real-time self-monitoring of diet and exercise, instant feedback, and wireless uploading of data. The flexibility of mHealth (mobile health technology), coupled with the pace of technological advancement, potentially allows for rapid refinement and optimization of interventions and the opportunity to scale interventions to reach a broad audience (32). Critical gaps and research priorities How does pregnancy affect maternal health and the health of offspring? What is the impact of maternal obesity, gestational weight gain, and diet exposure on the development of the maternal and infant microbiome? What are the CVD outcomes for women with a remote history of preeclampsia or hypertensive disorders of pregnancy? How does the fetus adapt to abnormal nutrient delivery (insufficient or excess), stress, blood flow, and environmental toxins and how do these adaptations affect later life metabolic processes and development of disease? What are the immunological consequences of gravidity and parity for women’s health? What are the most efficacious technological advances that will help women of childbearing age to have healthy transitions after childbirth? Emerging Research Gaps on Sex Differences in Cardiometabolic Health in Youth Biology of sex differences in CV risk development in youth The rapidly increasing burden of noncommunicable chronic diseases in youth represents a global public health challenge. Particularly worrisome is the rapid increase in obesity and youth onset of T2D. Early obesity and metabolic syndrome point toward fetal origins and early life environmental exposures. A life span approach to health and disease incorporates the concept that there are critical periods of development during which environmental exposures, such as developmental overnutrition, undernutrition, or inadequate physical activity, have lasting effects on health. Childhood development Emerging evidence in stem cells derived from fetal samples (e.g., umbilical cord tissue, amniotic fluid) has documented fetal programming by maternal obesity that is remarkably consistent with observations in reported animal models of maternal obesity, including an inherent capacity for excess adipogenesis that is correlated with neonatal adiposity (33–35). These studies with stem cells provide the opportunity to examine the cellular function contributing to risk for development of metabolic disease later in life. The cells can be obtained noninvasively and probed to determine aspects of metabolism attributable to fetal exposures and, furthermore, to understand whether infant sex affects the metabolic response to intrauterine stress or the predictive value of the mesenchymal stem cells for childhood metabolic health. Adolescence and T2D In the course of the SEARCH for Diabetes in Youth study, Dabelea et al. (36) examined prevalence of T2D for 2001 and 2009 among youth aged 10 to 19 years. Although rates of T2D in adult men and women were found to be similar, adolescent girls, for reasons that remain unclear, had a 60% higher prevalence rate than boys. The causes for this sex difference are not understood. Critical gaps and research priorities What are the mechanisms responsible for the associations of maternal phenotype and behavior and childhood environment on risk for CVD in offspring? Are there effective interventions directed at preventing the transgenerational cycle of obesity and diabetes? Why are the rates for adolescent girls developing T2D higher than for adolescent boys? Are there differences in the determinants of dysregulated metabolism and response to the environment in girls and boys? Determinants of Sex Differences in Cardiometabolic Health in Adults Sex and ethnicity In contrast to sex difference findings in adolescents with T2D, the prevalence of T2D in adults in the United States does not differ by sex, yet there is a sex difference in CVD outcomes among those with diabetes. Compared with men with diabetes, women with diabetes have a threefold greater coronary heart disease mortality risk (37, 38). Women with diabetes also have poor survival after myocardial infarction compared with men (39), and women with diabetes have a significantly greater risk of stroke than men with or without diabetes (40). Although the prevalence of peripheral arterial disease in men vs women with diabetes is not firmly established, diabetes is a more significant risk factor for claudication in women compared with men, and women have increased postoperative mortality following revascularization (41, 42). Furthermore, there is an understudied interplay between race/ethnicity and sex on differences in the prevalence of diabetes and its complications. The prevalence of diabetes is greater in race/ethnic minorities in the United States—non-Hispanic blacks (NHBs); Latinos of Puerto Rican, Mexican, and Central American descent; South Asians; and Alaska Natives/Pacific Islanders—compared with non-Hispanic whites (NHWs) (43). Minority women, especially NHBs and Mexican American women, have a higher prevalence of obesity than their male counterparts or NHW women, and there are race/ethnic differences in body fat distribution (43, 44). Overall, the risk of CVD is lower in most minority populations (except Native Americans) compared with NHWs; however, CVD and poststroke mortality rates are higher in NHBs and Latinos, respectively, compared with NHWs (43). Minority populations with diabetes are less physically active, have a higher risk factor burden, and have poorer access to health care compared with NHWs, which may explain their disproportionately adverse outcomes following a CVD event (43). There is a critical need to identify where to focus prevention and intervention strategies to reduce these disparities (39). Sexual dimorphism in lipid metabolism Studies with 3H- and 14C-labeled fatty acids indicated sex differences in adipose tissue and fatty acid metabolism in human subjects (45). Specifically, (1) at any given body mass index, women have more adipose tissue than men; (2) differences in regional adipose tissue exist; (3) net fat gain is sexually dimorphic; (4) sex-specific differences exist in upper vs lower body fat distribution between women and men; and (5) women recycle free fatty acids better than men. Diabetes Women with both type 1 diabetes and T2D face an increased risk for CVD that is at least twofold to fourfold higher than the increase in CVD risk seen in men with diabetes (39). Premenopausal women without diabetes are at a lower risk for CVD than men without diabetes of the same age, and much of this protection from CVD is thought to be due to the effects of estrogen, including receptor-mediated effects on lipid and glucose metabolism, endothelial function, and fat deposition. In contrast, premenopausal women, normally considered to be protected from CVD, appear to lack the cardioprotection if they have diabetes. Women generally have less ectopic fat deposition, more favorable lipid levels, and less insulin resistance than men. In type 1 diabetes, which is primarily diagnosed during the premenopausal years, women seem to lose the benefits of estrogen, as evidenced by a more androgenic pattern of fat deposition and reduced insulin sensitivity that does not differ from that in men with type 1 diabetes. The evidence that estrogen is involved in the sex difference in CVD risk with diabetes is further supported by the fact that other estrogen-related diseases, such as osteoporosis, are also disproportionately increased in women when they have diabetes. Diabetes and exercise Exercise is a cornerstone of treatment of T2D, yet most people with T2D are sedentary. Among other barriers, people with T2D have a reduced maximal and submaximal exercise capacity compared with individuals without diabetes, even in the absence of complications associated with T2D (46). This results in greater effort during low- to moderate-intensity exercise and greater perception of difficulty among people with diabetes than for nondiabetic people. Exercise effort is important because higher effort levels during exercise predict lower adherence to regular physical activity (47). The decrease in cardiorespiratory fitness in people with diabetes compared with individuals without diabetes is greater in women than men. Cardiac abnormalities, particularly an abnormally increased pulmonary capillary wedge pressure with exercise, play a role but cannot account for all of the exercise impairment (48). Abnormalities in mitochondrial function and metabolism and oxygen delivery also likely play a role, and these questions are being investigated currently. Animal models of diabetes suggest that there is limited physiological adaptation to exercise training, that endothelial nitric oxide is unresponsive under diabetic conditions, and that this pathway can be targeted pharmacologically to restore the adaptive response to exercise training (49, 50). Exercise training appears to benefit most people with diabetes, in terms of improved cardiorespiratory fitness, although this is not consistently reported, and sex differences in physiological adaptation to exercise training have not been determined. It is also unclear whether the influences of T2D on exercise effort are more or less pronounced at low, moderate, or vigorous intensities, respectively. Transgender The transgender community represents one of the most underserved and marginalized populations in health care. Because the chromosomal configuration [46 XY in males transitioning to females (transwomen) and 46 XX females transitioning to males (transmen)], remains unchanged (51), these individuals also provide a unique opportunity to determine which metabolic functions are determined by the prevailing milieu of sex steroids. Relevant to CVD risk, both transmales and transfemales exhibit a higher incidence of T2D than the general population (52). Furthermore, data from a large gender identity study suggest that hormone therapy taken by transgender individuals is associated with a higher CV mortality rate among transwomen but not among transmen (52). Despite receiving similar estrogen therapy, transwomen who elected orchiectomy had improved metabolic health compared with transwomen who retained their testes. Furthermore, data suggest that suppression of endogenous testosterone in transwomen appears to improve insulin sensitivity and reduce hepatic steatosis (53). Menopause Estrogen appears to be cardioprotective until the time of menopause unless diabetes is present, after which protective effects are lost as estrogen deficiency develops. Premenopausal women store fat primarily in gluteofemoral depots, which are considered benign or metabolically beneficial, whereas men tend to store fat in abdominal depots that are linked to chronic disease. Critical gaps and research priorities How are sex differences and race/ethnicity interrelated with CVD in diabetes and nonalcoholic fatty liver disease? How do sex and race/ethnicity effects on CVD in individuals with diabetes interact with social and cultural factors known to contribute to CVD? Are there strategies to reduce sex disparities in the use of known CVD preventive interventions? What are the mechanisms underlying the apparent paradox of estrogen having beneficial effects in the premenopausal period and detrimental effects after menopause? What are the mechanisms responsible for sex differences in fuel partitioning, particularly in the context of calorie excess, diabetes, loss of sex hormones, and aging? What are the underlying mechanisms of sex differences in functional exercise capacity and the adaptive exercise training response, and how are these differences altered by age and diabetes? What are the sex difference in therapeutic treatments and effects of diabetes drugs on CVD outcomes and the role of sex hormones? What are the metabolic impacts of cross-hormone therapy (transgender and anabolic steroid use) or androgen and estrogen use in the context of biologically different sex? What Are the Sex Differences That Affect Cardiac Function and Outcomes? Cardiovascular metabolism The heart is a metabolic omnivore that metabolizes a wide variety of substrates to generate the ∼5 kg of adenosine triphosphate/d (or 2 metric tons/y) required for contraction, relaxation, and other processes. Myocardial metabolism is intimately related to cardiac energetics and function. The predominant fuels for the postnatal mammalian heart are fatty acids, although glucose, ketones, lactate, amino acids, and local glycogen and triglycerides may also be used. Different substrates have different advantages/disadvantages. For example, fatty acids generate more adenosine triphosphate/mole than glucose, but glucose is more oxygen efficient. Recent studies using positron emission tomography have shown that sex has a major, quantifiable impact on myocardial metabolism, especially in those with obesity or T2D. In a cross-sectional study of obese and nonobese subjects, female sex predicted higher oxygen consumption, fatty acid utilization and oxidation, and myocardial perfusion but lower glucose utilization, glucose utilization/plasma insulin, and metabolic efficiency (54). Sex also had an effect on myocardial metabolism in a study of obese subjects with and without T2D (55). Female sex again was associated with higher myocardial oxygen consumption and blood flow. Interestingly, sex and T2D interacted in the prediction of plasma fatty acid concentrations, which necessarily influence myocardial metabolism. The women had higher myocardial fatty acid utilization and esterification rates and lower percent oxidation rates than men (55). Last, sex affects the myocardial metabolic response to medications for T2D (56). Cardiovascular outcomes Although there are substantial areas of overlap in CV outcomes between men and women, up to one-third of CVD presentations are sufficiently different between women and men so as to contribute to health disparities‎, because male-pattern CVD is the standard for recognition and treatment (57). Examples of CVD patterns that are more prevalent in women include myocardial infarction with no obstructive coronary artery disease, coronary microvascular dysfunction, and heart failure with preserved ejection fraction, all of which have been understudied (58). Important steps include policy regarding study and trial design to include female-pattern CVD, as well as female-only studies as well as other trials to address the leading health care threat for 52% of the population. Pregnancy-related cardiomyopathy About 1 in 1000 pregnancies worldwide are complicated by the development of dilated cardiomyopathy around the peripartum period, known as peripartum cardiomyopathy (PPCM) (59). The disease strikes otherwise healthy young women and often leads to persistent heart failure, cardiac transplantation, or death. PPCM is thus a serious cardiac disease that is unique to women. Patten and his colleagues (60) have now uncovered two key insights. First, mechanistic work in mouse models and clinical epidemiological and echocardiographic studies have revealed that PPCM is, in large part, a vascular disease triggered by late-gestational vasculo-toxic hormones secreted by the placenta and pituitary during late gestation and the postpartum period. Second, human genetic studies have revealed that a large proportion of women with PPCM carry mutations in the gene TTN, which encodes for titin, a protein critical for sarcomeric function. PPCM is thus a vasculo/hormonal disease, caused in at least a subset of women by underlying genetic predisposition (61). Critical gaps and research priorities What are the fundamental mechanisms underlying differences in heart failure in men and women with diabetes? What is the cause of female preponderance of heart failure with preserved ejection fraction in women? What are the short- and long-term impacts of pregnancy on women’s cardiac health? What is the mechanistic relationship between mutations in titin and the hormonal/vascular insult of pregnancy? How do sex differences in cardiac fuel metabolism influence cardiac function and inform sex-specific interventions for heart failure? Conclusions The NIH Office of Research in Women’s Health has issued a mandate to close the knowledge gap in women’s health and sex/gender research in the basic research as well as in the clinical research arena. In the area of cardiometabolic disease, there is much to be learned to close this gap. Our collective statement described in this article highlights selected ongoing research and, most important, outlines critical research gaps that must be addressed to improve the health of women and the next generation across the life span. Abbreviations: CV cardiovascular CVD cardiovascular disease NHB non-Hispanic black NHW non-Hispanic white NIH National Institutes of Health OVX ovariectomized PE preeclampsia PPCM peripartum cardiomyopathy T2D type 2 diabetes. Conference Speakers in Alphabetical Order Arany, Zoltan, University of Pennsylvania Bairey Merz, C. Noel, Cedars-Sinai Medical Center Barrett-Connor, Elizabeth, University of California, San Diego–School of Medicine Boyle, Kristen, University of Colorado Anschutz Medical Campus Brown, Laura, University of Colorado Anschutz Medical Campus Clegg, Deborah, Cedars-Sinai Medical Center Cree-Green, Melanie, University of Colorado Anschutz Medical Campus Dabelea, Dana, University of Colorado Anschutz Medical Campus Friedman, Jacob, University of Colorado Anschutz Medical Campus Goodyear, Laurie, Joslin Diabetes Center/Harvard Medical School Graham, Ginger Hill-Golden, Sherita, Johns Hopkins University, Department of Medicine Huebschmann, Amy, University of Colorado Anschutz Medical Campus Jenkins, Marjorie, US Food and Drug Administration Jensen, Michael, Mayo Clinic Julian, Colleen, University of Colorado Anschutz Medical Campus Kelsey, Megan, University of Colorado School of Medicine/Children’s Hospital Colorado Kennedy, Brian, Buck Institute for Research on Aging Klemm, Dwight, University of Colorado Anschutz Medical Campus Kohrt, Wendy, University of Colorado Anschutz Medical Campus Lindenfeld, JoAnn, Vanderbilt University Medical Center Moreau, Kerrie, University of Colorado Anschutz Medical Campus Nadeau, Kristen, University of Colorado Anschutz Medical Campus Nelson, J. Lee, Fred Hutchinson Cancer Research Center and University of Washington Nicklas, Jacinda, University of Colorado Anschutz Medical Campus Peterson, Linda, Washington University School of Medicine Regensteiner, Judith, University of Colorado Anschutz Medical Campus Reusch, Jane, University of Colorado and Denver VAMC Roberts, Jim, Magee-Women’s Research Institute Rudolph, Michael, University of Colorado Denver Anschutz Medical Campus Sadovsky, Yoel, Magee-Women’s Research Institute Santoro, Nanette, University of Colorado Anschutz Medical Campus Snell-Bergeon, Janet, University of Colorado Anschutz Medical Campus Wenger, Nanette, Emory University School of Medicine Zeitler, Phil, University of Colorado Anschutz Medical Campus Acknowledgments We thank the staff from the CUSOM Center for Women’s Health Research (Nancy Oudet, MSW, Anne Kercsmar, MA, Elizabeth Hepworth, and David Samson), all conference participants, and the sponsors of the meeting. Financial Support: This work was supported by the University of Colorado School of Medicine; AstraZeneca Independent Medical Education Grant 72236); the Society for Women’s Health Research; Mary & George Sissel; the Boettcher Foundation; the Specialized Center of Research on Sex Differences, NIH Grant P50 HD073063; UCHealth; Gilead Sciences; the Colorado BioScience Association; and Sanofi. Disclosure Summary: The authors have nothing to disclose. References 1. Yusuf S, Reddy S, Ounpuu S, Anand S. Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanization. Circulation . 2001; 104( 22): 2746– 2753. Google Scholar CrossRef Search ADS PubMed  2. Gupta D, Wenger NK. Guidelines for the prevention of cardiovascular disease in women: international challenges and opportunities. Expert Rev Cardiovasc Ther . 2014; 10( 3): 379– 385. Google Scholar CrossRef Search ADS   3. Yusuf S, Hawken S, Ounpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budaj A, Pais P, Varigos J, Lisheng L; INTERHEART Study Investigators. Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet . 2004; 364( 9438): 937– 952. Google Scholar CrossRef Search ADS PubMed  4. Ford ES, Ajani UA, Croft JB, Critchley JA, Labarthe DR, Kottke TE, Giles WH, Capewell S. Explaining the decrease in U.S. deaths from coronary disease, 1980–2000. N Engl J Med . 2007; 356( 23): 2388– 2398. Google Scholar CrossRef Search ADS PubMed  5. Towfighi A, Zheng L, Ovbiagele B. Sex-specific trends in midlife coronary heart disease risk and prevalence. Arch Intern Med . 2009; 169( 19): 1762– 1766. Google Scholar CrossRef Search ADS PubMed  6. Jones WS, Duscha BD, Robbins JL, Duggan NN, Regensteiner JG, Kraus WE, Hiatt WR, Dokun AO, Annex BH. Alteration in angiogenic and anti-angiogenic forms of vascular endothelial growth factor-A in skeletal muscle of patients with intermittent claudication following exercise training. Vasc Med . 2012; 17: 94– 100. Google Scholar CrossRef Search ADS PubMed  7. Al-Qahtani SM, Bryzgalova G, Valladolid-Acebes I, Korach-André M, Dahlman-Wright K, Efendić S, Berggren PO, Portwood N. 17β-Estradiol suppresses visceral adipogenesis and activates brown adipose tissue-specific gene expression. Horm Mol Biol Clin Investig . 2017; 29( 1): 13– 26. Google Scholar PubMed  8. Yasrebi A, Rivera JA, Krumm EA, Yang JA, Roepke TA. Activation of estrogen response element-independent ERα signaling protects female mice from diet-induced obesity. Endocrinology . 2017; 158( 2): 319– 334. Google Scholar PubMed  9. Chen X, McClusky R, Chen J, Beaven SW, Tontonoz P, Arnold AP, Reue K. The number of x chromosomes causes sex differences in adiposity in mice. PLoS Genet . 2012; 8( 5): e1002709. Google Scholar CrossRef Search ADS PubMed  10. Gavin KM, Gutman JA, Kohrt WM, Wei Q, Shea KL, Miller HL, Sullivan TM, Erickson PF, Helm KM, Acosta AS, Childs CR, Musselwhite E, Varella-Garcia M, Kelly K, Majka SM, Klemm DJ. De novo generation of adipocytes from circulating progenitor cells in mouse and human adipose tissue. FASEB J . 2015; 30( 3): 1096– 1108. Google Scholar CrossRef Search ADS PubMed  11. Mitchell SJ, Madrigal-Matute J, Scheibye-Knudsen M, Fang E, Aon M, González-Reyes JA, Cortassa S, Kaushik S, Gonzalez-Freire M, Patel B, Wahl D, Ali A, Calvo-Rubio M, Burón MI, Guiterrez V, Ward TM, Palacios HH, Cai H, Frederick DW, Hine C, Broeskamp F, Habering L, Dawson J, Beasley TM, Wan J, Ikeno Y, Hubbard G, Becker KG, Zhang Y, Bohr VA, Longo DL, Navas P, Ferrucci L, Sinclair DA, Cohen P, Egan JM, Mitchell JR, Baur JA, Allison DB, Anson RM, Villalba JM, Madeo F, Cuervo AM, Pearson KJ, Ingram DK, Bernier M, de Cabo R. Effects of sex, strain, and energy intake on hallmarks of aging in mice. Cell Metab . 2016; 23( 6): 1093– 1112. Google Scholar CrossRef Search ADS PubMed  12. Ashpole NM, Logan S, Yabluchanskiy A, Mitschelen MC, Yan H, Farley JA, Hodges EL, Ungvari Z, Csiszar A, Chen S, Georgescu C, Hubbard GB, Ikeno Y, Sonntag WE. IGF-1 has sexually dimorphic, pleiotropic, and time-dependent effects on healthspan, pathology, and lifespan. Geroscience  2017; 39( 2): 129– 145. Google Scholar CrossRef Search ADS PubMed  13. Miller RA, Harrison DE, Astle CM, Floyd RA, Flurkey K, Hensley KL, Javors MA, Leeuwenburgh C, Nelson JF, Ongini E, Nadon NL, Warner HR, Strong R. An Aging Interventions Testing Program: study design and interim report. Aging Cell . 2007; 6( 4): 565– 575. Google Scholar CrossRef Search ADS PubMed  14. Kennedy BK, Lamming DW. The mechanistic target of rapamycin: the grand conducTOR of metabolism and aging. Cell Metab . 2016; 23( 6): 990– 1003. Google Scholar CrossRef Search ADS PubMed  15. Stanford KI, Lee MY, Getchell KM, So K, Hirshman MF, Goodyear LJ. Exercise before and during pregnancy prevents the deleterious effects of maternal high-fat feeding on metabolic health of male offspring. Diabetes . 2014; 64( 2): 427– 433. Google Scholar CrossRef Search ADS PubMed  16. Raipuria M, Bahari H, Morris MJ. Effects of maternal diet and exercise during pregnancy on glucose metabolism in skeletal muscle and fat of weanling rats. PLoS One . 2015; 10( 4): e0120980. Google Scholar CrossRef Search ADS PubMed  17. Tomić V, Sporiš G, Tomić J, Milanović Z, Zigmundovac-Klaić D, Pantelić S. The effect of maternal exercise during pregnancy on abnormal fetal growth. Croat Med J . 2013; 54( 4): 362– 368. Google Scholar CrossRef Search ADS PubMed  18. Manders MA, Sonder GJ, Mulder EJ, Visser GH. The effects of maternal exercise on fetal heart rate and movement patterns. Early Hum Dev . 1997; 48( 3): 237– 247. Google Scholar CrossRef Search ADS PubMed  19. O’Connor PJ, Poudevigne MS, Cress ME, Motl RW, Clapp JF III. Safety and efficacy of supervised strength training adopted in pregnancy. J Phys Act Health . 2011; 8( 3): 309– 320. Google Scholar CrossRef Search ADS PubMed  20. Sheridan MA, Yunusov D, Balaraman V, Alexenko AP, Yabe S, Verjovski-Almeida S, Schust DJ, Franz AW, Sadovsky Y, Ezashi T, Roberts RM. Vulnerability of primitive human placental trophoblast to Zika virus. Proc Natl Acad Sci USA . 2017; 114( 9): E1587– E1596. Google Scholar CrossRef Search ADS PubMed  21. Chang G, Mouillet JF, Mishima T, Chu T, Sadovsky E, Coyne CB, Parks WT, Surti U, Sadovsky Y. Expression and trafficking of placental microRNAs at the feto-maternal interface. FASEB J . 2017; 31( 7): 2760– 2770. Google Scholar CrossRef Search ADS PubMed  22. Barbour LA. Changing perspectives in pre-existing diabetes and obesity in pregnancy: maternal and infant short- and long-term outcomes. Curr Opin Endocrinol Diabetes Obes . 2014; 21( 4): 257– 263. Google Scholar CrossRef Search ADS PubMed  23. Voortman T, Tielemans MJ, Stroobant W, Schoufour JD, Kiefte-de Jong JC, Steenweg-de Graaff J, van den Hooven EH, Tiemeier H, Jaddoe VWV, Franco OH. Plasma fatty acid patterns during pregnancy and child’s growth, body composition, and cardiometabolic health: The Generation R Study [published online ahead of print April 13, 2017]. Clin Nutr . doi: 10.1016/j.clnu.2017.04.006. 24. Zhou X, Niu JM, Ji WJ, Zhang Z, Wang PP, Ling XF, Li YM. Precision test for precision medicine: opportunities, challenges and perspectives regarding pre-eclampsia as an intervention window for future cardiovascular disease. Am J Transl Res . 2016; 8( 5): 1920– 1934. Google Scholar PubMed  25. Choi DJ, Yoon CH, Lee H, Ahn SY, Oh KJ, Park HY, Lee HY, Cho MC, Chung IM, Shin MS, Park SJ, Shim CY, Han SW, Chae IH. The association of family history of premature cardiovascular disease or diabetes mellitus on the occurrence of gestational hypertensive disease and diabetes. PLoS One . 2016; 11( 12): e0167528. Google Scholar CrossRef Search ADS PubMed  26. Retnakaran R, Shah BR. Role of type 2 diabetes in determining retinal, renal, and cardiovascular outcomes in women with previous gestational diabetes mellitus. Diabetes Care . 2016; 40( 1): 101– 108. Google Scholar CrossRef Search ADS PubMed  27. Brown LD, Hay WW Jr. Impact of placental insufficiency on fetal skeletal muscle growth. Mol Cell Endocrinol . 2016; 435: 69– 77. Google Scholar CrossRef Search ADS PubMed  28. Brown LD, Davis M, Wai S, Wesolowski SR, Hay WW Jr, Limesand SW, Rozance PJ. Chronically increased amino acids improve insulin secretion, pancreatic vascularity, and islet size in growth-restricted fetal sheep. Endocrinology . 2016; 157( 10): 3788– 3799. Google Scholar CrossRef Search ADS PubMed  29. Brown LD, Kohn JR, Rozance PJ, Hay WW Jr, Wesolowski SR. Exogenous amino acids suppress glucose oxidation and potentiate hepatic glucose production in late gestation fetal sheep. Am J Physiol Regul Integr Comp Physiol . 2017; 312( 5): R654– R663. Google Scholar CrossRef Search ADS PubMed  30. Mittal A, Pachter L, Nelson JL, Kjærgaard H, Smed MK, Gildengorin VL, Zoffmann V, Hetland ML, Jewell NP, Olsen J, Jawaheer D. Pregnancy-induced changes in systemic gene expression among healthy women and women with rheumatoid arthritis. PLoS One . 2015; 10( 12): e0145204. Google Scholar CrossRef Search ADS PubMed  31. Gammill HS, Stephenson MD, Aydelotte TM, Nelson JL. Microchimerism in recurrent miscarriage. Cell Mol Immunol . 2014; 11( 6): 589– 594. Google Scholar CrossRef Search ADS PubMed  32. McLean A, Osgood N, Newstead-Angel J, Stanley K, Knowles D, van der Kamp W, Qian W, Dyck R. Building research capacity: results of a feasibility study using a novel mHealth epidemiological data collection system within a gestational diabetes population. Stud Health Technol Inform . 2017; 234: 228– 232. Google Scholar PubMed  33. Iaffaldano L, Nardelli C, Raia M, Mariotti E, Ferrigno M, Quaglia F, Labruna G, Capobianco V, Capone A, Maruotti GM, Pastore L, Di Noto R, Martinelli P, Sacchetti L, Del Vecchio L. High aminopeptidase N/CD13 levels characterize human amniotic mesenchymal stem cells and drive their increased adipogenic potential in obese women. Stem Cells Dev . 2013; 22( 16): 2287– 2297. Google Scholar CrossRef Search ADS PubMed  34. Boyle KE, Patinkin ZW, Shapiro AL, Baker PR II, Dabelea D, Friedman JE. Mesenchymal stem cells from infants born to obese mothers exhibit greater potential for adipogenesis: the Healthy Start BabyBUMP Project. Diabetes . 2015; 65( 3): 647– 659. Google Scholar CrossRef Search ADS PubMed  35. Chen JR, Lazarenko OP, Blackburn ML, Rose S, Frye RE, Badger TM, Andres A, Shankar K. Maternal obesity programs senescence signaling and glucose metabolism in osteo-progenitors from rat and human. Endocrinology . 2016; 157( 11): 4172– 4183. Google Scholar CrossRef Search ADS PubMed  36. Dabelea D, Mayer-Davis EJ, Saydah S, Imperatore G, Linder B, Divers J, Bell R, Badaru A, Talton JW, Crume T, Liese AD, Merchant AT, Lawrence JM, Reynolds K, Dolan L, Liu LL, Hamman RF; SEARCH for Diabetes in Youth Study. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA . 2014; 311( 17): 1778– 1786. Google Scholar CrossRef Search ADS PubMed  37. Manson JE, Colditz GA, Stampfer MJ, Willett WC, Krolewski AS, Rosner B, Arky RA, Speizer FE, Hennekens CH. A prospective study of maturity-onset diabetes mellitus and risk of coronary heart disease and stroke in women. Arch Intern Med . 1991; 151( 6): 1141– 1147. Google Scholar CrossRef Search ADS PubMed  38. Preis SR, Hwang SJ, Coady S, Pencina MJ, D’Agostino RB Sr, Savage PJ, Levy D, Fox CS. Trends in all-cause and cardiovascular disease mortality among women and men with and without diabetes mellitus in the Framingham Heart Study, 1950 to 2005. Circulation . 2009; 119( 13): 1728– 1735. Google Scholar CrossRef Search ADS PubMed  39. Regensteiner JG, Golden S, Huebschmann AG, Barrett-Connor E, Chang AY, Chyun D, Fox CS, Kim C, Mehta N, Reckelhoff JF, Reusch JE, Rexrode KM, Sumner AE, Welty FK, Wenger NK, Anton B; American Heart Association Diabetes Committee of the Council on Lifestyle and Cardiometabolic Health, Council on Epidemiology and Prevention, Council on Functional Genomics and Translational Biology, and Council on Hypertension. Sex differences in the cardiovascular consequences of diabetes mellitus: a scientific statement from the American Heart Association. Circulation . 2015; 132( 25): 2424– 2447. Google Scholar CrossRef Search ADS PubMed  40. Peters SA, Huxley RR, Woodward M. Diabetes as a risk factor for stroke in women compared with men: a systematic review and meta-analysis of 64 cohorts, including 775,385 individuals and 12,539 strokes. Lancet . 2014; 383( 9933): 1973– 1980. Google Scholar CrossRef Search ADS PubMed  41. Gardner AW, Parker DE, Montgomery PS, Blevins SM. Diabetic women are poor responders to exercise rehabilitation in the treatment of claudication. J Vasc Surg . 2014; 59( 4): 1036– 1043. Google Scholar CrossRef Search ADS PubMed  42. Magnant JG, Cronenwett JL, Walsh DB, Schneider JR, Besso SR, Zwolak RM. Surgical treatment of infrainguinal arterial occlusive disease in women. J Vasc Surg . 1993; 17: 67– 76; discussion 76–78. Google Scholar CrossRef Search ADS PubMed  43. Golden SH, Brown A, Cauley JA, Chin MH, Gary-Webb TL, Kim C, Sosa JA, Sumner AE, Anton B. Health disparities in endocrine disorders: biological, clinical, and nonclinical factors—an Endocrine Society scientific statement. J Clin Endocrinol Metab . 2012; 97( 9): E1579– E1639. Google Scholar CrossRef Search ADS PubMed  44. Flegal KM, Carroll MD, Kit BK, Ogden CL. Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999-2010. JAMA . 2012; 307( 5): 491– 497. Google Scholar CrossRef Search ADS PubMed  45. Santosa S, Jensen MD. The sexual dimorphism of lipid kinetics in humans. Front Endocrinol (Lausanne) . 2015; 6: 103. Google Scholar PubMed  46. Regensteiner JG, Sippel J, McFarling ET, Wolfel EE, Hiatt WR. Effects of non-insulin-dependent diabetes on oxygen consumption during treadmill exercise. Med Sci Sports Exerc . 1995; 27( 5): 661– 667. Google Scholar CrossRef Search ADS PubMed  47. Huebschmann AG, Reis EN, Emsermann C, Dickinson LM, Reusch JE, Bauer TA, Regensteiner JG. Women with type 2 diabetes perceive harder effort during exercise than nondiabetic women. Appl Physiol Nutr Metab . 2009; 34: 851– 857. Google Scholar CrossRef Search ADS PubMed  48. Regensteiner JG, Bauer TA, Reusch JE, Quaife RA, Chen MY, Smith SC, Miller TM, Groves BM, Wolfel EE. Cardiac dysfunction during exercise in uncomplicated type 2 diabetes. Med Sci Sports Exerc . 2009; 41( 5): 977– 984. Google Scholar CrossRef Search ADS PubMed  49. Keller AC, Knaub LA, Miller MW, Birdsey N, Klemm DJ, Reusch JE. Saxagliptin restores vascular mitochondrial exercise response in the Goto-Kakizaki rat. J Cardiovasc Pharmacol . 2015; 65( 2): 137– 147. Google Scholar PubMed  50. Miller MW, Knaub LA, Olivera-Fragoso LF, Keller AC, Balasubramaniam V, Watson PA, Reusch JE. Nitric oxide regulates vascular adaptive mitochondrial dynamics. Am J Physiol Heart Circ Physiol . 2013; 304( 12): H1624– H1633. Google Scholar CrossRef Search ADS PubMed  51. Gooren LJ, Kreukels B, Lapauw B, Giltay EJ. (Patho)physiology of cross-sex hormone administration to transsexual people: the potential impact of male-female genetic differences. Andrologia . 2014; 47( 1): 5– 19. Google Scholar CrossRef Search ADS PubMed  52. Wierckx K, Elaut E, Declercq E, Heylens G, De Cuypere G, Taes Y, Kaufman JM, T’Sjoen G. Prevalence of cardiovascular disease and cancer during cross-sex hormone therapy in a large cohort of trans persons: a case-control study. Eur J Endocrinol . 2013; 169( 4): 471– 478. Google Scholar CrossRef Search ADS PubMed  53. Morselli E, Santos RS, Criollo A, Nelson MD, Palmer BF, Clegg DJ. The effects of oestrogens and their receptors on cardiometabolic health. Nat Rev Endocrinol . 2017; 13( 6): 352– 364. Google Scholar CrossRef Search ADS PubMed  54. Peterson LR, Soto PF, Herrero P, Mohammed BS, Avidan MS, Schechtman KB, Dence C, Gropler RJ. Impact of gender on the myocardial metabolic response to obesity. JACC Cardiovasc Imaging . 2008; 1( 4): 424– 433. Google Scholar CrossRef Search ADS PubMed  55. Peterson LR, Saeed IM, McGill JB, Herrero P, Schechtman KB, Gunawardena R, Recklein CL, Coggan AR, DeMoss AJ, Dence CS, Gropler RJ. Sex and type 2 diabetes: obesity-independent effects on left ventricular substrate metabolism and relaxation in humans. Obesity (Silver Spring) . 2011; 20( 4): 802– 810. Google Scholar CrossRef Search ADS PubMed  56. Lyons MR, Peterson LR, McGill JB, Herrero P, Coggan AR, Saeed IM, Recklein C, Schechtman KB, Gropler RJ. Impact of sex on the heart’s metabolic and functional responses to diabetic therapies. Am J Physiol Heart Circ Physiol . 2013; 305( 11): H1584– H1591. Google Scholar CrossRef Search ADS PubMed  57. Humphries KH, Izadnegahdar M, Sedlak T, Saw J, Johnston N, Schenck-Gustafsson K, Shah RU, Regitz-Zagrosek V, Grewal J, Vaccarino V, Wei J, Bairey Merz CN. Sex differences in cardiovascular disease—impact on care and outcomes. Front Neuroendocrinol . 2017; 46: 46– 70. Google Scholar CrossRef Search ADS PubMed  58. Bairey Merz CN, Pepine CJ, Walsh MN, Fleg JL. Ischemia and no obstructive coronary artery disease (INOCA): developing evidence-based therapies and research agenda for the next decade. Circulation . 2017; 135( 11): 1075– 1092. Google Scholar CrossRef Search ADS PubMed  59. Arany Z, Elkayam U. Peripartum cardiomyopathy. Circulation . 2016; 133( 14): 1397– 1409. Google Scholar CrossRef Search ADS PubMed  60. Patten IS, Rana S, Shahul S, Rowe GC, Jang C, Liu L, Hacker MR, Rhee JS, Mitchell J, Mahmood F, Hess P, Farrell C, Koulisis N, Khankin EV, Burke SD, Tudorache I, Bauersachs J, del Monte F, Hilfiker-Kleiner D, Karumanchi SA, Arany Z. Cardiac angiogenic imbalance leads to peripartum cardiomyopathy. Nature . 2012; 485( 7398): 333– 338. Google Scholar CrossRef Search ADS PubMed  61. Ware JS, Li J, Mazaika E, Yasso CM, DeSouza T, Cappola TP, Tsai EJ, Hilfiker-Kleiner D, Kamiya CA, Mazzarotto F, Cook SA, Halder I, Prasad SK, Pisarcik J, Hanley-Yanez K, Alharethi R, Damp J, Hsich E, Elkayam U, Sheppard R, Kealey A, Alexis J, Ramani G, Safirstein J, Boehmer J, Pauly DF, Wittstein IS, Thohan V, Zucker MJ, Liu P, Gorcsan J III, McNamara DM, Seidman CE, Seidman JG, Arany Z; IMAC-2 and IPAC Investigators. Shared genetic predisposition in peripartum and dilated cardiomyopathies. N Engl J Med . 2016; 374( 3): 233– 241. Google Scholar CrossRef Search ADS PubMed  Copyright © 2018 Endocrine Society

Journal

EndocrinologyOxford University Press

Published: Jan 1, 2018

There are no references for this article.