Association of Chronological Age, Subjective Age and Bio-functional Age With Serum Anti-müllerian Hormone

Aging Clinical Trial

Official title:

Association of Chronological Age, Subjective Age and Bio-functional Age With Serum Anti-müllerian Hormone

Clinical Trial Details — Status: Active, not recruiting

Administrative data

• NCT number: NCT05297058
• Other study ID #: 2021-02246
• Status: Active, not recruiting
• Start date: July 1, 2022
• Est. completion date: December 31, 2024

Study information

• Verified date: November 2023
• Source: Insel Gruppe AG, University Hospital Bern
• Contact: n/a
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

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

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.

Recruitment information / eligibility

• Status: Active, not recruiting
• Enrollment: 50
• Est. completion date: December 31, 2024
• Est. primary completion date: April 30, 2024
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: Female
• Age group: 35 Years to 45 Years

Eligibility

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

Related Conditions & MeSH terms

• Aging

Locations

Country	Name	City	State
Switzerland	Dep. of Obstetrics and Gynecology, Bern University Hospital	Bern

Sponsors (1)

Lead Sponsor	Collaborator
Insel Gruppe AG, University Hospital Bern

Country where clinical trial is conducted

Switzerland, 

References & Publications (12)

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. — View Citation

Hartge P. Genetics of reproductive lifespan. Nat Genet. 2009 Jun;41(6):637-8. doi: 10.1038/ng0609-637. No abstract available. — View 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. Erratum In: Genome Biol. 2015;16:96. — View 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. — View 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. — View 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. — View Citation

Shuster LT, Rhodes DJ, Gostout BS, Grossardt BR, Rocca WA. Premature menopause or early menopause: long-term health consequences. Maturitas. 2010 Feb;65(2):161-6. doi: 10.1016/j.maturitas.2009.08.003. Epub 2009 Sep 5. — View 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. — View 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. — View Citation

Stute P, von Bergen M, Bitterlich N, Meissner F, von Wolff M, Poethig D. Measuring cognitive performance in way that incorporates the concept of active and healthy ageing (AHA). Maturitas. 2019 Jul;125:27-32. doi: 10.1016/j.maturitas.2019.03.018. Epub 2019 Mar 25. — View Citation

te Velde ER, Pearson PL. The variability of female reproductive ageing. Hum Reprod Update. 2002 Mar-Apr;8(2):141-54. doi: 10.1093/humupd/8.2.141. — View 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. — View Citation

* Note: There are 12 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Assessing the chronological age	Evaluated by birthdate of participant	At baseline, once per participant
Secondary	Serum anti-müllerian hormone (AMH)	A venous blood sample is taken to evaluate the serum AMH level.	At baseline, once per participant
Secondary	Serum follicle-stimulating hormone (FSH)	A venous blood sample is taken to evaluate the serum FSH level.	At baseline, once per participant
Secondary	Serum estradiol (E2)	A venous blood sample is taken to evaluate the serum E2 level.	At baseline, once per participant
Secondary	Subjective age	Participants will be asked how old they actually feel.	At baseline, once per participant
Secondary	Externally estimated age	Two nurses who don't know the participant or their chronological age will be asked to externally estimate the participant's age. For data analysis, the average of these two estimates will be used.	At baseline, once per participant
Secondary	Bio-functional age (BFA)	To evaluate the bio-functional age, a bio-functional status (BFS) is taken. The BFS consists of 45 separate tests and evaluates physical, physiological, psychomotor, cognitive, mental, and social-emotional factors.	At baseline, once per participant
Secondary	Epigenetic age	A saliva sample will be taken to evaluate the epigenetic age. The epigenetic age is evaluated by examining DNA methylation. No genetic data is collected.	At baseline, once per participant
Secondary	Assessing the correlation between subjective and externally estimated age		At baseline, once per participant
Secondary	Assessing the correlation between BFA and serum AMH		At baseline, once per participant
Secondary	Assessing the correlation between subjective age and BFA		At baseline, once per participant
Secondary	Assessing the correlation between subjective age and serum AMH		At baseline, once per participant
Secondary	Assessing the correlation between externally estimated age and serum AMH		At baseline, once per participant
Secondary	Assessing the correlation between externally estimated age and chronological age		At baseline, once per participant
Secondary	Assessing the correlation between subjective age and chronological age		At baseline, once per participant
Secondary	Assessing the correlation between externally estimated age and BFA		At baseline, once per participant
Secondary	Assessing the correlation between chronological age and serum AMH		At baseline, once per participant
Secondary	Assessing the correlation between epigenetic age and serum AMH		At baseline, once per participant
Secondary	Assessing the correlation between epigenetic age and chronological age		At baseline, once per participant
Secondary	Assessing the correlation between epigenetic age and subjective age		At baseline, once per participant
Secondary	Assessing the correlation between epigenetic age and BFA		At baseline, once per participant
Secondary	Assessing the correlation between epigenetic age and externally estimated age		At baseline, once per participant