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| Name | Class |
|---|---|
| Nestlé Health Science | INDUSTRY |
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This observational cross-sectional study aims to better understand how the menopausal transition affects brain energy metabolism and cognition. Menopause, a natural stage in a woman's life, is typically divided into three phases: premenopause, perimenopause, and postmenopause. This transition involves hormonal fluctuations and a decline in estrogen levels, which can impact physical, emotional, and cognitive well-being. Common symptoms include hot flashes, sleep disturbances, mood changes, and difficulties with memory and concentration.
Emerging evidence suggests that the decline in estrogen may impair how the brain uses glucose, its primary energy source. This reduction in glucose metabolism is thought to contribute to cognitive difficulties reported during midlife. In contrast, the brain's capacity to use ketones-alternative energy substrates produced during fasting or low-carbohydrate intake-appears preserved during aging and hormonal changes. Increasing circulating ketones may offer a promising strategy to support brain energy and cognitive function.
To explore these relationships, the study will employ advanced brain imaging (PET scans) to assess glucose and ketone uptake in the brain. Additional measures will include hormone levels, cognitive testing, continuous glucose monitoring, and MRI. PET tracers will also be used to evaluate estrogen receptor distribution, providing insight into how the brain responds to hormonal changes.
A total of 45 women aged 35-60 will be enrolled and categorized into three groups (15 per group): premenopause, perimenopause, and postmenopause. Each participant will attend four study visits that include questionnaires, blood tests, cognitive assessments, metabolic measurements, and imaging procedures.
The results may help identify early neurobiological and metabolic markers associated with the menopausal transition. These findings could inform new approaches to preserve brain health and prevent cognitive decline in aging women. Improving understanding of how the female brain adapts to hormonal shifts may ultimately support more targeted strategies for promoting healthy aging.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| premenopause | Women between 35 and 55 years old who still have regular menstrual cycles, with no noticeable changes in the past 10 months. | ||
| perimenopause | Women between 40 and 60 years old who have experienced changes in their menstrual cycles, such as irregular timing (varying by more than 7 days) for at least 10 cycles, or no period for 3 to 11 months. | ||
| postmenopause | Women between 45 and 65 years old who have not had a menstrual period for 12 months or more. |
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| Measure | Description | Time Frame |
|---|---|---|
| cerebral metabolic rates (μmol/100 g/min) measured by PET (11C-AcAc +18F-FDG) | Brain energy metabolism will be quantified using two PET tracers: 11C-acetoacetate (for ketone use) and 18F-fluorodeoxyglucose (for glucose use). This will allow comparison of brain fuel usage between three menopausal groups (PRE, PERI, POST).Total Cerebral metabolic rates (μmol/100 g/min) (CMR tot= CMR acac + CMRglu) | 1 day at baseline |
| Tracer influx rates (k) measured by PET (11C-AcAc +18F-FDG) | Brain energy metabolism will be quantified using two PET tracers: 11C-acetoacetate (for ketone use) and 18F-fluorodeoxyglucose (for glucose use). This will allow comparison of brain fuel usage between three menopausal groups (PRE, PERI, POST). tracer influx rates (K values). | 1 day at baseline |
| Measure | Description | Time Frame |
|---|---|---|
| Time-activity curves of the estrogen receptor in the brain (by 18F-4FMFES PET) | Time-activity curves of the estrogen recept will be measured using 18F-4FMFES PET express as SUV (Standardized Uptake Value) | 1 day at baseline |
| distribution volume ratio of the estrogen receptor in the brain (by 18F-4FMFES PET) |
| Measure | Description | Time Frame |
|---|---|---|
| Brain volume | Will be measured by MRI - T1-weighted images and express in cm³ | 1 day at baseline |
| Rey Auditory Verbal Learning Test (RAVLT) | Assesses verbal memory. Total score (range: 0-75); higher scores indicate better performance |
Inclusion Criteria:
Perimenopause: Women aged 40 to 60; Menstrual cycles varying by more than 7 days per cycle for at least 10 cycles, or no period for 3 to 11 months
postmenopause: Women aged 45 to 65; No menstrual period for ≥ 12 months
Exclusion Criteria:
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Healthy individuals from the general population
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Melanie Fortier, M.Sc. | Contact | 1-819-821-5206 | recherche.cerveau@usherbrooke.ca |
| Name | Affiliation | Role |
|---|---|---|
| Stephen Cunnane, Ph.D | Université de Sherbrooke | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Centre de recherche sur le Vieillissement | Sherbrooke | Quebec | J1H 4C4 | Canada |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38501109 | Background | Andy C, Nerattini M, Jett S, Carlton C, Zarate C, Boneu C, Fauci F, Ajila T, Battista M, Pahlajani S, Christos P, Fink ME, Williams S, Brinton RD, Mosconi L. Systematic review and meta-analysis of the effects of menopause hormone therapy on cognition. Front Endocrinol (Lausanne). 2024 Mar 4;15:1350318. doi: 10.3389/fendo.2024.1350318. eCollection 2024. | |
| 26650926 |
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There is no current plan to share individual participant data (IPD) with external researchers. While data reuse within the study team is permitted, external data sharing is subject to sponsor agreement and may be considered on a case-by-case basis in the future.
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| ID | Term |
|---|---|
| D007662 | Ketosis |
| ID | Term |
|---|---|
| D000138 | Acidosis |
| D000137 | Acid-Base Imbalance |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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Whole blood and plasma will be retained
distribution volume ratio of the estrogen receptor will be measured by kinetic modelisation using 18F-4FMFES PET. |
| 1 day at baseline |
| Glucose variability (SD of glucose measured by continuous glucose monitoring) | Continuous glucose monitoring (CGM) will track glucose levels over several days. Glycemic variability will be assessed by the standard deviation of glucose values over the 5 days monitoring period. (mmol/L) | Over 5 days following sensor placement et stabilisation |
| Glucose average (mean of glucose measured by continuous glucose monitoring) | Continuous glucose monitoring (CGM) will track glucose levels over several days. Average glucose concentration over the monitoring period.(mmol/L) | Over 5 days following sensor placement et stabilisation |
| Time in range | Total minutes with glucose values within the standard glycemic range (3.9-10.0 mmol/L) over the 5 days monitoring period. (min) | Over 5 days following sensor placement et stabilisation |
| 1 day at baseline |
| Stroop Color and Word test (Stroop Test) (secondes) | Measures processing speed and executive function; outcome is time to completion. Unit of Measure: Seconds; lower scores indicate better performance | 1 day at baseline |
| Trail making test (secondes) | Assesses cognitive flexibility, visual attention, and processing speed. Unit of Measure: Seconds; lower scores indicate better performance | 1 day at baseline |
| Montreal Cognitive Assessment (MoCA) score | Global cognitive screening tool. Unit of Measure: Score (range: 0-30); higher scores indicate better cognition. | 1 day at baseline |
| Boston naming tests (total answer) | Measures language and word retrieval ability.Total correct responses (range: 0-60); higher scores are better | 1 day at baseline |
| Symbol coding (score) | Assesses processing speed.Score (higher = better) | 1 day at baseline |
| Logical Memory Subtest of the Wechsler Memory Scale-IV | Assesses elayed story recall. Score (0-25); higher scores indicate better memory | 1 day at baseline |
| Fasting plasma glucose (mM) | Blood samples will be used to assess the systemic metabolis plasma markers and will be compared across 3 groups | 1 day at baseline |
| Fasting plasma insulin (mM) | Blood samples will be used to assess the systemic metabolis plasma markers and will be compared across 3 groups | 1 day at baseline |
| Fasting plasma HbA1c (%) | Blood samples will be used to assess the systemic metabolis plasma markers and will be compared across 3 groups | 1 day at baseline |
| Fasting plasma total ketone (uM) | Blood samples will be used to assess the systemic metabolis plasma markers and will be compared across 3 groups. Total ketone = acetoacetate + beta-hydroxybutyrate | 1 day at baseline |
| Estrogene levels (pmol/L) | Blood samples will be used to assess sex hormone and will be compared across 3 group | 1 day at baseline |
| follicule stimulating hormone levels (mIU/mL) | Blood samples will be used to assess sex hormone and will be compared across 3 group | 1 day at baseline |
| Progesterone (nmol/L) | Blood samples will be used to assess sex hormone and will be compared across 3 group | 1 day at baseline |
| hormone lutéinisante (mUI/mL) | Blood samples will be used to assess sex hormone and will be compared across 3 group | 1 day at baseline |
| Menopause-Specific Quality of Life Questionnaire | Self-reported questionnaires. Self-reported symptom burden. Unit of Measure: Score (range: 0-44); higher = more severe symptoms | 1 day at baseline |
| Menopause Rating Scale | Self-reported symptom burden. Unit of Measure: Score (range: 0-44); higher = more severe symptoms | 1 day at baseline |
| Pittsburgh Sleep Quality Index | Self-reported questionnaire. Assesses sleep quality over the past month. Unit of Measure: Score (range: 0-21); higher = poorer sleep | 1 day at baseline |
| Patient Health Questionnaire (PHQ-9) | Depressive symptoms. Score (range: 0-27); higher = more severe depression | 1 day at baseline |
| Subjective memory complain | Self-reported memory or concentration issues. Unit of Measure: Score (range 62-372) ; higher scores indicate more complaints | 1 day at baseline |
| International Physical Activity Questionnaire | Physical activity over the past week. (MET-minutes/week) | 1 day at baseline |
| Castellano CA, Baillargeon JP, Nugent S, Tremblay S, Fortier M, Imbeault H, Duval J, Cunnane SC. Regional Brain Glucose Hypometabolism in Young Women with Polycystic Ovary Syndrome: Possible Link to Mild Insulin Resistance. PLoS One. 2015 Dec 9;10(12):e0144116. doi: 10.1371/journal.pone.0144116. eCollection 2015. |
| 38902275 | Background | Mosconi L, Nerattini M, Matthews DC, Jett S, Andy C, Williams S, Yepez CB, Zarate C, Carlton C, Fauci F, Ajila T, Pahlajani S, Andrews R, Pupi A, Ballon D, Kelly J, Osborne JR, Nehmeh S, Fink M, Berti V, Dyke JP, Brinton RD. In vivo brain estrogen receptor density by neuroendocrine aging and relationships with cognition and symptomatology. Sci Rep. 2024 Jun 20;14(1):12680. doi: 10.1038/s41598-024-62820-7. |
| 32699974 | Background | Paquette M, Phoenix S, Lavallee E, Rousseau JA, Guerin B, Turcotte EE, Lecomte R. Cross-Species Physiological Assessment of Brain Estrogen Receptor Expression Using 18F-FES and 18F-4FMFES PET Imaging. Mol Imaging Biol. 2020 Oct;22(5):1403-1413. doi: 10.1007/s11307-020-01520-w. Epub 2020 Jul 22. |
| 37759805 | Background | Arjmand S, Bender D, Jakobsen S, Wegener G, Landau AM. Peering into the Brain's Estrogen Receptors: PET Tracers for Visualization of Nuclear and Extranuclear Estrogen Receptors in Brain Disorders. Biomolecules. 2023 Sep 18;13(9):1405. doi: 10.3390/biom13091405. |
| 33103819 | Background | Fortier M, Castellano CA, St-Pierre V, Myette-Cote E, Langlois F, Roy M, Morin MC, Bocti C, Fulop T, Godin JP, Delannoy C, Cuenoud B, Cunnane SC. A ketogenic drink improves cognition in mild cognitive impairment: Results of a 6-month RCT. Alzheimers Dement. 2021 Mar;17(3):543-552. doi: 10.1002/alz.12206. Epub 2020 Oct 26. |
| 31027873 | Background | Fortier M, Castellano CA, Croteau E, Langlois F, Bocti C, St-Pierre V, Vandenberghe C, Bernier M, Roy M, Descoteaux M, Whittingstall K, Lepage M, Turcotte EE, Fulop T, Cunnane SC. A ketogenic drink improves brain energy and some measures of cognition in mild cognitive impairment. Alzheimers Dement. 2019 May;15(5):625-634. doi: 10.1016/j.jalz.2018.12.017. Epub 2019 Apr 23. |
| 29914035 | Background | Croteau E, Castellano CA, Richard MA, Fortier M, Nugent S, Lepage M, Duchesne S, Whittingstall K, Turcotte EE, Bocti C, Fulop T, Cunnane SC. Ketogenic Medium Chain Triglycerides Increase Brain Energy Metabolism in Alzheimer's Disease. J Alzheimers Dis. 2018;64(2):551-561. doi: 10.3233/JAD-180202. |
| 32709961 | Background | Cunnane SC, Trushina E, Morland C, Prigione A, Casadesus G, Andrews ZB, Beal MF, Bergersen LH, Brinton RD, de la Monte S, Eckert A, Harvey J, Jeggo R, Jhamandas JH, Kann O, la Cour CM, Martin WF, Mithieux G, Moreira PI, Murphy MP, Nave KA, Nuriel T, Oliet SHR, Saudou F, Mattson MP, Swerdlow RH, Millan MJ. Brain energy rescue: an emerging therapeutic concept for neurodegenerative disorders of ageing. Nat Rev Drug Discov. 2020 Sep;19(9):609-633. doi: 10.1038/s41573-020-0072-x. Epub 2020 Jul 24. |
| 30091648 | Background | Mosconi L, Brinton RD. How would we combat menopause as an Alzheimer's risk factor? Expert Rev Neurother. 2018 Sep;18(9):689-691. doi: 10.1080/14737175.2018.1510320. Epub 2018 Aug 13. No abstract available. |
| 29016679 | Background | Mosconi L, Berti V, Quinn C, McHugh P, Petrongolo G, Osorio RS, Connaughty C, Pupi A, Vallabhajosula S, Isaacson RS, de Leon MJ, Swerdlow RH, Brinton RD. Perimenopause and emergence of an Alzheimer's bioenergetic phenotype in brain and periphery. PLoS One. 2017 Oct 10;12(10):e0185926. doi: 10.1371/journal.pone.0185926. eCollection 2017. |
| 28855400 | Background | Mosconi L, Berti V, Quinn C, McHugh P, Petrongolo G, Varsavsky I, Osorio RS, Pupi A, Vallabhajosula S, Isaacson RS, de Leon MJ, Brinton RD. Sex differences in Alzheimer risk: Brain imaging of endocrine vs chronologic aging. Neurology. 2017 Sep 26;89(13):1382-1390. doi: 10.1212/WNL.0000000000004425. Epub 2017 Aug 30. |
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| 10981461 | Background | Gold EB, Sternfeld B, Kelsey JL, Brown C, Mouton C, Reame N, Salamone L, Stellato R. Relation of demographic and lifestyle factors to symptoms in a multi-racial/ethnic population of women 40-55 years of age. Am J Epidemiol. 2000 Sep 1;152(5):463-73. doi: 10.1093/aje/152.5.463. |
| 39708829 | Background | Delanerolle G, Phiri P, Elneil S, Talaulikar V, Eleje GU, Kareem R, Shetty A, Saraswath L, Kurmi O, Benetti-Pinto CL, Muhammad I, Rathnayake N, Toh TH, Aggarwal IM, Shi JQ, Taylor J, Riach K, Potocnik K, Litchfield I, Kemp HF, Briggs P; MARIE collaborative. Menopause: a global health and wellbeing issue that needs urgent attention. Lancet Glob Health. 2025 Feb;13(2):e196-e198. doi: 10.1016/S2214-109X(24)00528-X. Epub 2024 Dec 18. No abstract available. |
| 22344196 | Background | Harlow SD, Gass M, Hall JE, Lobo R, Maki P, Rebar RW, Sherman S, Sluss PM, de Villiers TJ; STRAW + 10 Collaborative Group. Executive summary of the Stages of Reproductive Aging Workshop + 10: addressing the unfinished agenda of staging reproductive aging. J Clin Endocrinol Metab. 2012 Apr;97(4):1159-68. doi: 10.1210/jc.2011-3362. Epub 2012 Feb 16. |
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