Aging
Conditions
Keywords
Aging, Anti-müllerian hormone, Bio-functional age, Epigenetic age
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.
Interventions
None listed
Sponsors
Insel Gruppe AG, University Hospital Bern
Study design
Observational model
CASE_ONLY
Time perspective
CROSS_SECTIONAL
Eligibility
Sex/Gender
FEMALE
Age
35 Years to 45 Years
Healthy volunteers
Yes
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
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Assessing the chronological age | At baseline, once per participant | Evaluated by birthdate of participant |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Serum follicle-stimulating hormone (FSH) | At baseline, once per participant | A venous blood sample is taken to evaluate the serum FSH level. |
| Serum estradiol (E2) | At baseline, once per participant | A venous blood sample is taken to evaluate the serum E2 level. |
| Subjective age | At baseline, once per participant | Participants will be asked how old they actually feel. |
| Serum anti-müllerian hormone (AMH) | At baseline, once per participant | A venous blood sample is taken to evaluate the serum AMH level. |
| Bio-functional age (BFA) | At baseline, once per participant | 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. |
| Epigenetic age | At baseline, once per participant | 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. |
| Externally estimated age | At baseline, once per participant | 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. |
Countries
Switzerland
Outcome results
None listed