Shufelt, Chrisandra

Importance and Objective: Aging is a complex biological process uniquely shaped in women by hormonal transitions, particularly across the menopause transition. While chronological age alone fails to capture individual health variability, emerging molecular biomarkers offer tools to quantify biological aging and understand mechanisms underlying age-related decline. This review synthesizes the current landscape of aging biomarkers, including senescence-associated secretory phenotype factors, epigenetic clocks, clonal hematopoiesis of indeterminate potential, and telomere length, with a particular emphasis on their relevance to menopause. Methods: This narrative review synthesizes human studies, translational research, and foundational basic science identified through PubMed searches through June 2025, examining aging biomarkers in general populations, among women in the menopause transition, and in relation to vasomotor symptoms and hormone therapy. Discussion and Conclusion: Evidence demonstrates that changes in biological aging biomarkers are observed across multiple molecular systems during midlife, including the menopause transition, reflecting broader age-related biological remodeling. Postmenopausal status, particularly following early or surgical menopause, has been associated with biological aging phenotypes, including elevated senescence-associated secretory phenotype factors, epigenetic age acceleration, clonal hematopoiesis, and shorter leukocyte telomere length, likely reflecting a combination of chronological aging, hormonal changes, and individual biological vulnerability. While severe vasomotor symptoms have been linked to higher epigenetic age, hormone therapy may favorably influence certain senescence markers and biological age discrepancy. Despite these advances, significant limitations constrain clinical translation, as current biomarkers capture overlapping biological processes and lack validated thresholds to define biological aging, especially in women. Future research requires large, longitudinal studies across diverse populations to establish clinically meaningful thresholds and sex-specific calibration. Advancing precision health strategies for women requires a better understanding of how reproductive and hormonal factors modify biomarker trajectories to improve risk prediction and to facilitate the development of targeted interventions for age-related diseases.

Background Hypermobile Ehlers–Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSDs) are heritable connective tissue disorders characterized by widespread fragile soft connective tissue affecting the skin, ligaments, joints, vasculature, and internal organs. Although hEDS and HSD are autosomal-dominant conditions and would be expected to display a 1:1 sex ratio, studies report higher prevalence in women. Objectives The purpose of this exploratory study was to determine whether self-reported sexual problems differed between females and males diagnosed with hEDS or HSD compared with controls with chronic pain but no hypermobility. Methods In this exploratory retrospective study, we examined 1,407 patients diagnosed with hEDS or HSD according to the 2017 diagnostic criteria for eight indicators of sexual problems based on a validated screening tool. Results Patients in each diagnosis primarily self-reported as White, non-Hispanic females (90%). Of the 1,407 patients who attended the EDS Clinic, 976 (69%) were diagnosed with HSD, 240 (17%) with hEDS, and 191 (14%) were chronic pain controls with neither diagnosis. For HSD, 937 (96%) were females vs. 39 (4%) males (24:1 females to males), while for hEDS, 210 (88%) were females vs. 30 (13%) males (7:1 females to males), and controls were 165 (86%) females vs. 26 (14%) males (6:1 females to males). Females with hEDS reported significantly higher rates of sexual issues than chronic pain controls, including sexual problems (69%, p = 0.018), problems with sexual interest (41%, p = 0.023), sexual pain (45%, p = 0.006), and orgasm difficulty (34%, p = 0.022) compared with males with hEDS or males or females with HSD. In contrast, males diagnosed with hEDS did not report any sexual problems over controls, and males and females diagnosed with HSD reported only one issue—more problems with sexual interest—compared with controls (females p = 0.019, males p = 0.018). However, the small number of males in this study limits conclusions that can be drawn for them. Conclusions This study is unique because we examine sex differences in sexual problems in patients with hEDS and HSD. Our findings indicate a higher percentage of sexual problems in females with hEDS than chronic pain controls without hypermobility, but this was not observed for females with HSD.

Background: Functional hypothalamic amenorrhea (FHA) is a common form of secondary amenorrhea caused partly by undernutrition relative to demand. Objective: To compare the dietary nutritional intake between women with FHA and eumenorrheic controls and evaluate micronutrient profiles. Methods: This cross-sectional study included 30 women with FHA and 29 eumenorrheic controls not on hormones. FHA was defined as ≥3 consecutive months of amenorrhea, estradiol of <50 pg/mL, and FSH and LH of <10 mIU/L, excluding other etiologies. A 3-day food diary was collected for dietary analysis, excluding dietary supplements using ESHA Research Food Processor. Results: The mean age of women with FHA and controls was 26.4 years ± 6.2 versus 30.3 years ± 3.7 ( p = 0.002), with no differences in BMI ( p = 0.16) or the waist-to-hip ratio ( p = 0.71). Women with FHA and controls consumed comparable median calorie intake (1784 kcal [1465, 2011] vs. 1732 kcal [1578, 1982], p = 0.62), with no differences in self-reported exercise patterns. Women with FHA consumed more dietary protein (84.2g [74, 112] vs. 74 g [59, 92], p = 0.001) and dietary fiber (30.1 g [22, 43] vs. 17.3 g [15, 23], p = 0.02) versus controls, respectively. When expressed as a percentage of estimated average requirements (% estimated average requirement), women with FHA had higher intakes of vitamin A (105% [45, 219] vs. 43% [21, 86], p = 0.005), vitamin C (201% [139, 351] vs. 107% [75, 190], p = 0.004), and iron (169% [146, 220] vs. 120% [99, 192], p = 0.027) compared with controls. Conclusions: Women with FHA had similar caloric intake to eumenorrheic controls but consumed more dietary protein, fiber, vitamin A, vitamin C, and iron. Future studies should examine the nutritional profiles of women with FHA in relation to long-term health consequences such as bone and vascular health.

PURPOSE This national study was undertaken to determine screening mammography rates among transgender and gender diverse (TGD) individuals. METHODS TGD individuals and cisgender women who qualified to receive screening mammography based on American College of Radiology guidelines were identified in the longitudinal OptumLabs Data Warehouse. The primary end point was the percentage of patients who had high rates of screening (>75% recommended screenings). Multivariable analyses were conducted in a matched population of transgender men to cisgender women to identify and adjust for factors associated with high adherence. Individuals were matched at a 1:4 ratio (transgender men: cisgender women) on age, race/ethnicity, year of enrollment in their health care plan, and duration of follow-up. RESULTS This study focused on 10,478 TGD individuals (3,778 transgender men; 1,294 transgender women; 5,406 with gender dysphoria not meeting other TGD criteria, NMOT) and 6,218,369 cisgender women. For transgender men, transgender women, individuals with gender dysphoria NMOT, and cisgender women, high mammography rates were observed in 41.1% (95% CI, 39.5 to 42.6), 7.4% (95% CI, 6.0 to 8.8), 11.9% (95% CI, 11.0 to 12.7), and 38.3% (95% CI, 38.3 to 38.4), respectively ( P < .0001). When transgender men were compared with 15,112 matched cisgender women, an age-based differential association was observed between sex and high mammography rates (interaction P = .0003); compared with cisgender women, transgender men appeared more likely to manifest high rates of screening at age 40-49 years (odds ratios [ORs], 1.38 [95% CI, 1.28 to 1.50]; P < .0001) and 50-59 years (OR, 1.57 [95% CI, 1.35 to 1.81]; P < .0001) but not in the older age groups. CONCLUSION The relatively high rates of screening mammography in cisgender women and transgender men suggest clinicians are offering mammography to individuals who are at average or high breast cancer risk, as compared with cisgender women, and not to transgender women at low risk.

Abstract Background Artificial intelligence enhanced electrocardiograms (AI-ECG) have matured over the past 10 years. More recently, the AI-ECG estimate of biological sex has shown potential as a novel tool for cardiovascular risk stratification among women. Cardiovascular disease is a leading cause of pregnancy-related mortality; however, there have been limited approaches for estimating the physiological demands of pregnancy and its impact of maternal cardiovascular outcomes. Purpose To estimate pregnancy-related changes on AI-ECG-based sex and age estimation in a prospective cohort of otherwise healthy, complication free pregnant women. Methods This secondary analysis of the SPEC-AI Nigeria Clinical Trial identified pregnant women without any pregnancy-related complications (at baseline or during follow-up) who had at least two 12 lead ECGs recorded during the study. The ECGs were analyzed with previously-developed algorithms to predict age and biological sex. To address bias in the AI-ECG age estimate, a reference cohort of 25,144 healthy patients was analyzed using quantile regression to estimate the 75th percentile of the reference distribution as a function of age. The estimate of biological sex was used to determine a sex discordance score with a discordance of 0.2 considered clinically relevant. To simplify the trends in the data, the ECGs were categorized as during pregnancy (&lt;=28 days prior to birth), peripartum (+/- 28 days of birth), and postpartum (28+ days after birth), and mixed effects models with a random intercept were used for analysis. Results A total of 207 females with a median age of 31 years (IQR 28 to 36 years) and normal blood pressures (systolic: 110 (IQR 10 to 120); diastolic: 70 (IQR 60-77); mmHg) were included from 5 clinical sites in Nigeria. The majority (73%, 150/207) of participants were in their second trimester at time of enrollment and the median number of ECGs per participant was 3 (max 7). The sex discordance score was elevated in 38% of the women at baseline and this percentage fell to 23% postpartum; which resulted in a decrease in the mean discordance score of 0.03 (95% CI: -0.06 to 0.0; p=0.028). Conversely, the percentage of patients with elevated age prediction increased from 35% to 41% over the course of pregnancy. This resulted in an increase in the bias-corrected AI-ECG age of 3.0 years (95% CI: 1.5 to 4.6 years; p&lt;0.001). Conclusion This study demonstrates the preliminary utility of serial AI-ECG based assessment as a marker for the biological effects of pregnancy. The increase in sex discordance score during pregnancy may be related to changes in cardiac structure, such as increased ventricular mass and chamber dilation which often reverses postpartum. However, the impact on age estimation appeared to persist in the early postpartum period. Further study is warranted to associate any changes observed with long term maternal or fetal outcomes.Figure

Abstract Background: Although hypermobile Ehlers-Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSD) are inherited disorders expected to display a 1:1 sex ratio, most studies report a strong female dominance. This study analyzed sex differences in 122 self-reported symptoms and comorbidities in patients diagnosed with hEDS or HSD using the 2017 criteria. Methods: Self-reported data was obtained from November 1, 2019, to April 25, 2025, ( n =2,451) from an Intake Questionnaire of adult (≤18 years old) patients diagnosed with hEDS or HSD at the EDS Clinic at Mayo Clinic Florida and analyzed by sex. Results: We found that 90.6% ( n =575) of hEDS patients were female and 9.4% ( n =60) were male, with a sex ratio of 9.6:1 female-to-male, while 95.2% ( n =1,728) of HSD patients were female and 4.8% ( n =88) were male, with a sex ratio of 19.6:1 female-to-male. Females were older than males: hEDS 35 vs. 28 years of age ( p <0.001), HSD 34 vs. 31 years of age ( p =0.004). Overall, females self-reported more symptoms/comorbidities than males: hEDS 31/122 (25.4%), HSD 59/122 (48.4%). In contrast, only 5/122 (4.1%) symptoms/comorbidities were self-reported more often in males including attention deficit disorder/attention deficit hyperactivity disorder, delay in developmental milestones, snoring, autism spectrum disorder, and obstructive sleep apnea. Females with HSD had more mast cell-related symptoms (i.e., hives p <0.001) which were reflected in higher mast cell scores than males ( p <0.001). Patients with higher mast cell scores also had higher serum levels of total IgE ( p =0.029). More females with HSD were diagnosed with fibromyalgia ( p <0.001) and reported symptoms associated with autonomic dysfunction than males. Aside from abuse, which was higher in females (hEDS p =0.039, HSD p <0.001), few sex differences were reported for psychological symptoms/comorbidities. In support for the idea that elevated mast cell activity in females may lead to extracellular matrix remodeling that promotes hypermobility, females with hEDS/HSD had greater serum collagen-4α1 ( p <0.0001) and fibronectin ( p =0.015) than males by ELISA. Conclusions: Females with hEDS and HSD report a higher burden of symptoms/comorbidities than males, providing a possible explanation for fewer males being reported in demographic data. Sex differences in symptoms/comorbidities may reflect sex differences in pathogenic drivers of disease.

Objective: Perimenopause is the time leading up to a woman’s last menstrual cycle and includes the 12 months afterward. Studies that systematically compare perimenopause symptoms across diverse cultural and geographic settings are lacking. This study, utilizing data from Flo, an international mobile health application, aimed to assess global knowledge and symptom experiences related to perimenopause. Methods: This cross-sectional survey was conducted via the Flo application, offered to users aged 18 years and above. The primary endpoints were knowledge of perimenopause symptoms from all survey participants, and self-reported perimenopause symptoms for survey participants aged 35 years and above. Secondary analyses compared knowledge scores and symptoms across geographic regions. Results: A total of 17,494 women from 158 countries were included. Commonly recognized perimenopause symptoms included hot flashes (71%), sleep problems (68%), and weight gain (65%). Of the participants, 12,681 were aged 35 years or above, with the most common self-reported symptoms being fatigue (83%), physical and mental exhaustion (83%), irritability (80%), depressive mood (77%), sleep problems (76%), digestive issues (76%), and anxiety (75%). This pattern of symptoms was similar among those who self-reported being in perimenopause, though higher than in those not in perimenopause. International variation in perimenopause symptom knowledge and symptoms experienced was noted ( P <0.001). Conclusions: This survey highlights a discordance between perimenopause knowledge and actual symptoms experienced across diverse global populations. While hot flashes were the most widely recognized symptom, respondents aged 35 years or above most commonly reported experiencing fatigue, physical and mental exhaustion, and irritability.

Abstract Objective Perimenopause is an under-recognized life stage that may be accompanied by complex and fluctuating symptoms. We aimed to quantify the prevalence of perimenopause uncertainty and explore the underlying drivers. Methods We conducted a mixed-methods study based on a cross-sectional survey of U.S. women aged 35 years and above (N=7,640). Closed-ended responses were analyzed to estimate the prevalence of perimenopause uncertainty with subgroup differences investigated by age and symptom severity. Content analysis of free-text responses (n=409) was conducted to identify the main uncertainty drivers. Results Overall, 34% of participants reported being unsure of their reproductive stage. Uncertainty peaked among those aged 40-44 (42%) and was highest among those with severe symptom burden (37%). The content analysis revealed three main uncertainty drivers. Symptom confusion and attribution was the most common (56%), reflecting difficulties interpreting bodily changes and distinguishing perimenopause from other causes. Knowledge gaps and information seeking accounted for 28% of responses, highlighting limited health literacy, assumptions about age, and active searches for evidence. Barriers to confirmation and care (16%) described dismissive healthcare encounters and reluctance to acknowledge perimenopause. Younger women (35-39 years) were more likely to cite knowledge gaps, while healthcare barriers peaked in the 40-44 age group. Conclusion Perimenopause uncertainty is a prevalent and clinically meaningful challenge. This uncertainty is conceptually distinct from illness-focused models: it is a universal transition with ambiguity and often lack of validation. Better symptom recognition and targeted communication is a crucial first step toward improving women’s awareness and support during perimenopause.

Objective: Generative artificial intelligence is rapidly evolving and is now being explored in health care to support patient and clinician education. This study evaluated the accuracy, completeness, and readability of four large language models (LLMs): ChatGPT 3.5, Gemini, ChatGPT 4.0, and OpenEvidence in answering questions about menopause and hormone therapy. Methods: A total of 35 questions (20 patient-level, 15 clinician-level) were entered into each LLM. OpenEvidence was only used for clinician-level questions. Four blinded expert reviewers rated responses as accurate and complete, accurate but incomplete, or inaccurate. Readability of patient-level responses was assessed using the Flesch Reading Ease Score (FRES) and word count. Analysis used ANOVA for readability, odds ratios for accuracy comparisons. Results: For patient-level questions, ChatGPT 3.5 achieved the highest accuracy (70%), followed by ChatGPT 4.0 (60%) and Gemini (30%); Gemini had significantly lower odds of accuracy compared with ChatGPT 3.5 (OR=0.18, 95% CI=0.05-0.71; P =0.014). FRES scores differed significantly ( P <0.001): Gemini scored 38.9±7.3 (“difficult”), ChatGPT 3.5 scored 31.0±11.2, and ChatGPT 4.0 scored 26.5±8.6 (both “very difficult”). For clinician-level questions, ChatGPT 4.0 achieved the highest accuracy (67%), followed by ChatGPT 3.5 and OpenEvidence (60% each) and Gemini (47%); no significant differences were observed among models (all P >0.05). Conclusion: LLMs demonstrated limited accuracy and frequent incorrect or incomplete responses to menopause-related queries, highlighting the need to improve model performance to ensure accurate and reliable information for both patients and clinicians.