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

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

Detailed Description
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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.

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

Conditions
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Aging

Participation Criteria
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Eligibility Criteria
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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

Ages Eligible for Study
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Minimum Age: 35 Years
Maximum Age: 45 Years

Sexes Eligible for Study
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Female

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Assessing the chronological age | Evaluated by birthdate of participant | At baseline, once per participant | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Serum anti-müllerian hormone (AMH) | A venous blood sample is taken to evaluate the serum AMH level. | At baseline, once per participant | 
| Serum follicle-stimulating hormone (FSH) | A venous blood sample is taken to evaluate the serum FSH level. | At baseline, once per participant | 
| Serum estradiol (E2) | A venous blood sample is taken to evaluate the serum E2 level. | At baseline, once per participant | 
| Subjective age | Participants will be asked how old they actually feel. | At baseline, once per participant | 
| 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 | 
| 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 | 
| 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 | 
| Assessing the correlation between subjective and externally estimated age |  | At baseline, once per participant | 
| Assessing the correlation between BFA and serum AMH |  | At baseline, once per participant | 
| Assessing the correlation between subjective age and BFA |  | At baseline, once per participant | 
| Assessing the correlation between subjective age and serum AMH |  | At baseline, once per participant | 
| Assessing the correlation between externally estimated age and serum AMH |  | At baseline, once per participant | 
| Assessing the correlation between externally estimated age and chronological age |  | At baseline, once per participant | 
| Assessing the correlation between subjective age and chronological age |  | At baseline, once per participant | 
| Assessing the correlation between externally estimated age and BFA |  | At baseline, once per participant | 
| Assessing the correlation between chronological age and serum AMH |  | At baseline, once per participant | 
| Assessing the correlation between epigenetic age and serum AMH |  | At baseline, once per participant | 
| Assessing the correlation between epigenetic age and chronological age |  | At baseline, once per participant | 
| Assessing the correlation between epigenetic age and subjective age |  | At baseline, once per participant | 
| Assessing the correlation between epigenetic age and BFA |  | At baseline, once per participant | 
| Assessing the correlation between epigenetic age and externally estimated age |  | At baseline, once per participant | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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Aging, Anti-müllerian hormone, Bio-functional age, Epigenetic age