AgingNCT05297058
Associations of Age Measures With Serum Anti-Müllerian Hormone
An observational study of Aging, run by Insel Gruppe AG, University Hospital Bern at 1 site in Switzerland.
Trial summary
This study aims to assess the association between aging and serum anti-müllerian hormone. Read more about this study
- Who is it for?
- Ages 35 to 45 years, women onlyHealthy volunteers can take part
- Conditions the study is for
- Aging
- How many people
- 50 participants
- Where
- 1 siteSwitzerland
- Study dates
- 1 Jul 2022to 20 Mar 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 35 to 45 years
- Women only
- Healthy volunteers accepted
- Adult
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.
Who may be able to join
- 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
Who cannot join
- 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
Trial locations and contacts
1 site in 1 country.
Switzerland1 site
Dep. of Obstetrics and Gynecology, Bern University Hospital
Bern
About this study
Official title: Association of Chronological Age, Subjective Age, Epigenetic Age and Bio-functional Age With Serum Anti-müllerian Hormone
This study aims to assess the association between aging and serum anti-müllerian hormone.
Read the 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.
- Conditions
- Aging
- Keywords
- Aging, Anti-müllerian hormone, Bio-functional age, Epigenetic age
What is being measured
The primary outcome is the main question the study is designed to answer.
Assessing the chronological age
Evaluated by birthdate of participant
Measured: At baseline, once per participant
Secondary outcomes (7)
Serum anti-müllerian hormone (AMH)
A venous blood sample is taken to evaluate the serum AMH level.
Measured: At baseline, once per participant
Serum follicle-stimulating hormone (FSH)
A venous blood sample is taken to evaluate the serum FSH level.
Measured: At baseline, once per participant
Serum estradiol (E2)
A venous blood sample is taken to evaluate the serum E2 level.
Measured: At baseline, once per participant
Subjective age
Participants will be asked how old they actually feel.
Measured: 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.
Measured: 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.
Measured: 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.
Measured: At baseline, once per participant
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted25 Mar 2022
- Study start1 Jul 2022
- Primary completion20 Mar 2024
- Study completion20 Mar 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (12)Papers the sponsor has linked to this study.
- Other trials for AgingStudies of the same condition, open and under way.
- More trials run by Insel Gruppe AG, University Hospital BernThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Cross-sectional
- Enrolment
- 50 participants (actual)
Sponsor and investigators
- Lead sponsor
- Insel Gruppe AG, University Hospital Bern
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Petra Stute, Prof. Dr. med., Study chair, Dep. of Obstetrics and Gynecology, Bern University Hospital, Switzerland
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05297058
- Sponsor's protocol ID
- 2021-02246
- Status last verified
- Oct 2024
- First submitted
- 16 Mar 2022
- Last updated
- 28 Oct 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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.
PubMed 29083441Stute 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.
PubMed 30805024Stute 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.
PubMed 31133213Shuster 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.
PubMed 19733988Hartge P. Genetics of reproductive lifespan. Nat Genet. 2009 Jun;41(6):637-8. doi: 10.1038/ng0609-637. No abstract available.
PubMed 19471299te 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.
PubMed 12099629van 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.
PubMed 15820810Broer 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.
PubMed 21613357Pellatt 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.
PubMed 21917251Moolhuijsen 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.
PubMed 32770239Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14(10):R115. doi: 10.1186/gb-2013-14-10-r115.
PubMed 24138928Poloni 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.
PubMed 34255838
Study at a glance
From the registry record, last updated by the sponsor on 28 Oct 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Association of Chronological Age, Subjective Age, Epigenetic Age and Bio-functional Age With Serum Anti-müllerian Hormone
- ClinicalTrials.gov ID
- NCT05297058
- Acronym / sponsor ID
- 2021-02246
- Conditions
- Aging
- Keywords
- Aging, Anti-müllerian hormone, Bio-functional age, Epigenetic age
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 50 participants (actual)
- Lead sponsor
- Insel Gruppe AG, University Hospital BernUniversity, hospital or other
- Study start
- 1 Jul 2022 (actual)
- Primary completion
- 20 Mar 2024 (actual)
- Study completion
- 20 Mar 2024 (actual)
- First posted
- 25 Mar 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Case only
- Time perspective
- Cross-sectional
Who may qualify
- Ages
- 35 to 45 years
- Sex
- Female only
- Healthy volunteers
- Accepted
- Age groups
- Adult
- 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.
Key inclusion criteria (7 listed)
- 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
Key exclusion criteria (7 listed)
- Pregnancy or breastfeeding
- Hormonal contraception
- Chronic diseases
- Mental illness
- Smoking >10 cigarettes per day or over 10 packyears
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Assessing the chronological age
Time frame: At baseline, once per participant
Evaluated by birthdate of participant
7 secondary outcomes
Serum anti-müllerian hormone (AMH)
Time frame: At baseline, once per participant
Serum follicle-stimulating hormone (FSH)
Time frame: At baseline, once per participant
Serum estradiol (E2)
Time frame: At baseline, once per participant
Subjective age
Time frame: At baseline, once per participant
Externally estimated age
Time frame: At baseline, once per participant
Bio-functional age (BFA)
Time frame: At baseline, once per participant
Epigenetic age
Time frame: At baseline, once per participant
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Oct 2024.
- Background: PubMed 29083441Stute 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.
- Background: PubMed 30805024Stute 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.
- Background: PubMed 31133213Stute 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.
- Background: PubMed 19733988Shuster 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.
- Background: PubMed 19471299Hartge P. Genetics of reproductive lifespan. Nat Genet. 2009 Jun;41(6):637-8. doi: 10.1038/ng0609-637. No abstract available.
- Background: PubMed 12099629te 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.
- Background: PubMed 15820810van 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.
- Background: PubMed 21613357Broer 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.
- Background: PubMed 21917251Pellatt 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.
- Background: PubMed 32770239Moolhuijsen 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.
- Background: PubMed 24138928Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14(10):R115. doi: 10.1186/gb-2013-14-10-r115.
- Background: PubMed 34255838Poloni 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.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Petra Stute, Prof. Dr. med. study chair
Dep. of Obstetrics and Gynecology, Bern University Hospital, Switzerland
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Aging, run by Insel Gruppe AG, University Hospital Bern at 1 site in Switzerland.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 7 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 28 Oct 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Switzerland. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Assessing the chronological age (time frame: At baseline, once per participant). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05297058, which also lists 12 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 28 Oct 2024.