Sleep and Insulin Resistance: The Impact of Gender Affirming Hormone Therapy in the Adolescent Transgender Population (ATP)

  • STATUS
    Recruiting
  • End date
    Dec 24, 2023
  • participants needed
    30
  • sponsor
    Duke University
Updated on 24 October 2022
insulin
Accepts healthy volunteers

Summary

Disordered sleep is a health issue with significant impacts on physical and psychological well-being that has increased in prevalence, but its impact on transgender adolescents has not been fully quantified. While there is found to be an impact of sex steroids on sleep, and sex-dependent differences in the impact of sleep duration and quality on insulin resistance (IR), there is limited available information regarding the impact of Gender Affirming Hormone Therapy (GAHT) for transgender individuals on sleep and IR. Our study aims to quantify the impacts of GAHT on sleep and IR in the pediatric transgender population as well as determine the degree of correlation of sleep to IR in this population.

Description

Disordered sleep is a health issue with significant impacts on physical and psychological well-being that has been increasing in prevalence over the past several decades, but its impact on one of our more vulnerable populations, transgender adolescents, has not yet been quantified. In the pediatric population, it is known that sleep disorders are common, with rates of insomnia up to 20-30% and the presence of sleep deprivation in >/= 50% of adolescents. In transgender adolescents data regarding the prevalence of sleep disorders is limited, but suggests higher rates of insomnia and short sleep than seen in their cisgender counterparts. No studies to date have evaluated the impact of Gender Affirming Hormone Therapy (GAHT) on sleep duration, quality, or efficiency in the pediatric transgender population, and in the adult, population data remains limited and contradictory.

Sex differences in sleep have been robustly evaluated, with evidence of worse subjective sleep in women despite improved objective sleep quality on actigraphy/polysomnography, greater impact from sleep deprivation upon women, and a relative delay in the chronotype of men compared to women. There is evidence that sex differences in sleep have origins in the prenatal/early postnatal period with differences in receptor expression on sleep-wake brain nuclei based upon early sex hormone exposure in rodent models. Following the onset of puberty exposure to sex, steroids activate these differentiated structures, with evidence of increased sensitivity of the brains of female rodents to sex steroids in multiple studies. Numerous studies have evaluated the impact of this sex steroid activation. Administration of feminizing hormones appears to have mixed and balanced results, with the increase in sleep efficiency/quality and strengthening of the circadian rhythm but sleep reduction from estrogen that is balanced by a decrease in efficiency/quality and increase in sedation and sleep duration from progesterone. Testosterone has been demonstrated to be reduced by sleep deprivation, with a demonstrated association between lower testosterone levels and disordered sleep, however, the impact of testosterone administration on sleep quality has been inconsistent.

Short and disrupted sleep has been shown to be linked to insulin resistance (IR) via various physiologic mechanisms. Clinically, increased risk for IR has been shown in children and adults to be associated with short sleep duration, delay in sleep chronotype, experimental sleep restriction, worsening OSA severity, sleep fragmentation, and subjective poor sleep quality. Additionally, there have been shown to be sex-dependent differences in IR pathophysiology, with an increase in insulin resistance in obese female vs male adolescents and different metabolomic signatures associated with IR across sexes in cisgender adolescents and in transgender adults following treatment with GAHT. Data regarding the development of insulin resistance following GAHT is limited but shows increased IR with the administration of estradiol and inconsistent impact of testosterone administration with some studies showing a decrease in IR and some showing no effect. It is therefore our hypothesis that administration of GAHT including testosterone will lead to improvement in IR through the direct effect of testosterone and indirect effect of improved sleep duration and quality. With the administration of GAHT including estradiol, investigators hypothesize that IR will worsen in a sleep-independent manner.

Subjective assessment of sleep will occur with the completion of the patient and parent sleep questionnaires (PROMIS Pediatric Sleep Disturbances-Patient and Parent Proxy, PROMIS Pediatric Sleep Practices-Patient and Parent Proxy, STOP-bang) at baseline and 12 months following GAHT. Actigraphy data will be collected for 7 days at baseline and 12 months following GAHT to assay a number of facets of sleep quality/efficiency including total sleep duration, sleep onset latency, mid-sleep time, and number of nighttime awakenings, wake after sleep onset, and sleep efficiency. Fasting serum and spot urine samples will be collected at baseline and following 12 months of GAHT. investigators will utilize a comprehensive suite of targeted and non-targeted assays. Estradiol, testosterone, LH, FSH, fasting glucose, insulin, HbA1C, liver function tests, kidney function tests, CRP, complete blood cell count with differential, and lipid panel will be extracted from their medical charts. HOMA-IR will be calculated using the fasting glucose and insulin levels, and insulin sensitivity will also be assessed via surrogate markers of serum adiponectin and triglyceride: HDL ratio. Metabolomic profile testing for 60 metabolites (45 acylcarnitines and 15 amino acids) will be performed by liquid chromatography/tandem mass spectrometry of serum samples, and first AM fasting spot urine non-targeted metabolomic profiling will be performed by gas chromatography/mass spectrometry at baseline and following 12 months of GAHT. Will obtain spot urine sample for evaluation of proteinuria or glucosuria in order to screen for eligibility for study. Anthropometric data (BMI, TANITA) and vital signs will be extracted from medical charts. Data regarding health risk behaviors (drug/alcohol use, screen time, physical activities) will be obtained from the Behavioral Risk Assessment questionnaire, and data regarding medical history and current medications will be obtained from both Intake Questionnaire and EMR. Both the Intake Questionnaire and the Behavioral Risk Assessment questionnaire are part of the standard of care for the Duke Child and Adolescent Gender Care Clinic. Data regarding psychiatric comorbidities and gender dysphoria will be obtained from questionnaires (PROMIS Depression and Anxiety, Eating Pathologies Symptoms Inventory for assessment of psychiatric comorbidities, and Body Image Scale and Utrecht Gender Dysphoria for assessment of dysphoria) at baseline and following GAHT.

Surveys completed exclusively for research purposes out of the above include: PROMIS Pediatric Sleep Disturbances-Patient and Parent Proxy, PROMIS Pediatric Sleep Practices-Patient and Parent Proxy, STOP-bang

Laboratory assays completed exclusively for research purposes includes: CRP, adiponectin, Urine, and serum metabolomics assays, spot urine protein and glucose, and obtaining fasting insulin and glucose after 12 months of GAHT

Additional testing completed exclusively for research purposes includes: Actigraphy monitoring

Details
Condition Sleep Disorder, Insulin Resistance, Gender Dysphoria
Clinical Study IdentifierNCT05489159
SponsorDuke University
Last Modified on24 October 2022

Eligibility

Yes No Not Sure

Inclusion Criteria

12 to 18 (inclusive) years of age
Identify as transgender or non-binary and plan to undergo treatment with GAHT

Exclusion Criteria

Prior treatment with GAHT or puberty-blockers (GnRH agonists)
Known Diabetes Mellitus
Current or recent (within the past month) use of systemic corticosteroids, medications for weight loss or topiramate
Proteinuria or chronic kidney disease, which could affect the metabolomic profiling
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