Clinical trial NCT05297058: Associations of Age Measures With Serum Anti-Müllerian Hormone
Official title: Association of Chronological Age, Subjective Age, Epigenetic Age and Bio-functional Age With Serum Anti-müllerian Hormone
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Aging
Keywords: Aging
Anti-müllerian hormone
Bio-functional age
Epigenetic age
Lead sponsor: Insel Gruppe AG, University Hospital Bern
Sponsor class: OTHER
First posted: 2022-03-25
Enrollment: 50
Sex: FEMALE
Minimum age (years): 35
Maximum age (years): 45
Standard ages: ADULT
Accepts healthy volunteers: yes
Observational model: CASE_ONLY
Time perspective: CROSS_SECTIONAL
Sampling method: PROBABILITY_SAMPLE
Study population: Patients of the Dep. of Obstetrics and Gynecology, Bern University Hospital, Switzerland as well as women contacted by advertisement are eligible for the study.

Brief summary: This study aims to assess the association between aging and serum anti-müllerian hormone.

Detailed description: As life expectancy is increasing and has significant effects on health, economy and other aspects, the need for an Active and Healthy ageing (AHA) strategy becomes more important. Although ageing is often defined by chronological age (CA), it is significantly influenced by other factors such as psychological, social and mental-emotional factors. To evaluate these influences, the bio-functional status (BFS) was created which consists of 45 non-invasive assessments of different categories and reflects a normal middle-European population. By means of BFS the bio-functional age (BFA) can be calculated, revealing individual strengths and resources for healthy ageing as well as potential health risks.

In women ageing leads to a depletion of the ovarian reserves and change of sex hormone levels introducing menopause. Age at menopause is associated with several health issues. Women with premature (age ≤40) or early menopause (age ≤45) are not only considered to have higher risk for osteoporosis but also cardiovascular diseases and cognitive disorders such as dementia. Late menopause (age ≥55) increases the risk of breast and ovarian cancer. Timely preventative measures might limit these risks. For example, hormone replacement therapy has shown to reduce later development of issues associated with premature or early menopause.

The difficulty lies in the variability of age at menopause between 40 and 60 years. In order to take appropriate preventative measures, the age of menopause has to be predicted individually for every woman. This requires a reliable predictive marker for menopause. In studies serum anti-müllerian hormone (AMH) was described as a potential predictor.

AMH is synthetized in granulosa cells of the follicles and reduces the effects of the follicle-stimulating hormone (FSH) on said cells preventing further recruitment of follicles. Hence, AMH is associated with the functional ovarian reserve and declines with age. It is mainly used for detection of reproductive age in women and might be a reliable predictive marker for menopause.

Using the epiAge-test the epigenetic age, also called the biological age, can be calculated. The epiAge-Test was created by Prof. Dr. Moshe Szyf based on the research of Steve Horvath's epigenetic clock. Horvath discovered that DNA methylation can be directly associated with ageing. The methylation occurs on cytosine nucleotides followed by guanine nucleotides creating so called CpG-islands. Taking mathematical and statistical analyses into account, Horvath identified 353 CpG-islands which were consistently altered with age. Szyf further developed Horvath's calculator and created the epiAge-test using 13 CpG-islands that show the highest correlation with ageing to calculate the epigenetic age.

Accordingly, age(ing) can be operationalized in different ways: chronological age (CA) based on birth certificate, subjective age (SA) based on the individual's self-perceived age, externally estimated age (EA) based on the age estimation of two unrelated people, bio-functional age (BFA) based on a 4-dimension validated test-battery, epigenetic age (epiAge) based on DNA methylation increasingly modified with ageing, and serum AMH reflecting a woman's reproductive age.

Eligibility criteria: Inclusion Criteria:

* Informed consent as documented by signature
* Female
* Age between 35 and 45 years
* German as native language
* Regular menstrual cycle with a mean length of 21-35 days
* Next menstrual period is predictable within a 7-day time frame
* Willing to attend bio-functional status analysis and to give blood and saliva samples

Exclusion Criteria:

* Pregnancy or breastfeeding
* Hormonal contraception
* Chronic diseases
* Mental illness
* Smoking \>10 cigarettes per day or over 10 packyears
* Consumption of \>30g alcohol per day (\>1 liter of beer or \>0.3 liter of wine)
* Inability to give consent

Primary outcomes:
measure: Assessing the chronological age
timeFrame: At baseline, once per participant
Secondary outcomes:
measure: Serum anti-müllerian hormone (AMH)
timeFrame: At baseline, once per participant
measure: Serum follicle-stimulating hormone (FSH)
timeFrame: At baseline, once per participant
measure: Serum estradiol (E2)
timeFrame: At baseline, once per participant
measure: Subjective age
timeFrame: At baseline, once per participant
measure: Externally estimated age
timeFrame: At baseline, once per participant
measure: Bio-functional age (BFA)
timeFrame: At baseline, once per participant
measure: Epigenetic age
timeFrame: At baseline, once per participant
Other outcomes:
Locations:
city: Bern
country: Switzerland
facility: Dep. of Obstetrics and Gynecology, Bern University Hospital
Study officials:
affiliation: Dep. of Obstetrics and Gynecology, Bern University Hospital, Switzerland
name: Petra Stute, Prof. Dr. med.
role: STUDY_CHAIR
References:
citation: Stute P, Bitterlich N, Bousquet J, Meissner F, von Wolff M, Poethig D. Measuring Active and Healthy Ageing: Applying a GENERIC Interdisciplinary Assessment Model Incorporating ICF. J Nutr Health Aging. 2017;21(9):1002-1009. doi: 10.1007/s12603-017-0908-1.
citation: Stute P, Anker M, Hollenstein L, von Wolff M, Bitterlich N, Meissner F, Poethig D. Measuring chronic stress exposure incorporating the active and healthy ageing (AHA) concept within the cross-sectional Bern cohort study 2014 (BeCS-14). Biopsychosoc Med. 2019 Feb 12;13:2. doi: 10.1186/s13030-019-0143-6. eCollection 2019.
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citation: van Rooij IA, Broekmans FJ, Scheffer GJ, Looman CW, Habbema JD, de Jong FH, Fauser BJ, Themmen AP, te Velde ER. Serum antimullerian hormone levels best reflect the reproductive decline with age in normal women with proven fertility: a longitudinal study. Fertil Steril. 2005 Apr;83(4):979-87. doi: 10.1016/j.fertnstert.2004.11.029.
citation: Broer SL, Eijkemans MJ, Scheffer GJ, van Rooij IA, de Vet A, Themmen AP, Laven JS, de Jong FH, Te Velde ER, Fauser BC, Broekmans FJ. Anti-mullerian hormone predicts menopause: a long-term follow-up study in normoovulatory women. J Clin Endocrinol Metab. 2011 Aug;96(8):2532-9. doi: 10.1210/jc.2010-2776. Epub 2011 May 25.
citation: Pellatt L, Rice S, Dilaver N, Heshri A, Galea R, Brincat M, Brown K, Simpson ER, Mason HD. Anti-Mullerian hormone reduces follicle sensitivity to follicle-stimulating hormone in human granulosa cells. Fertil Steril. 2011 Nov;96(5):1246-51.e1. doi: 10.1016/j.fertnstert.2011.08.015. Epub 2011 Sep 13.
citation: Moolhuijsen LME, Visser JA. Anti-Mullerian Hormone and Ovarian Reserve: Update on Assessing Ovarian Function. J Clin Endocrinol Metab. 2020 Nov 1;105(11):3361-73. doi: 10.1210/clinem/dgaa513.
citation: Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14(10):R115. doi: 10.1186/gb-2013-14-10-r115.
citation: Poloni C, Szyf M, Cheishvili D, Tsoukas CM. Are the Healthy Vulnerable? Cytomegalovirus Seropositivity in Healthy Adults Is Associated With Accelerated Epigenetic Age and Immune Dysregulation. J Infect Dis. 2022 Feb 1;225(3):443-452. doi: 10.1093/infdis/jiab365.