Associations Between Gut Microbiota and Menopause Symptoms: Novel Insights from the ZOE PREDICT 3 Cohort
Curie Kim1, Francesco Asnicar2, George Pounis3, Lucy Marples1, Kate Bermingham1, Wendy Hall3, Nicola Segata2, Tim Spector1,4, Sarah Berry1,3
1Zoe Ltd, United Kingdom
2Department CIBIO, University of Trento, Trento, Italy
3Department of Nutritional Sciences, School of Life Sciences and Medicine, King’s College London, United Kingdom
4Department of Twins Research and Genetic Epidemiology, King’s College London, London, UK
Microbiome composition may differ according to menopause status, which may be partially mediated by diet(1). Peri- and post-menopausal symptom burden is associated with diet quality(2), however, knowledge on the association between menopause symptoms and gut microbiome composition is limited(3). This study investigates the associations between gut microbiome composition and menopause symptoms.
Data was analysed from 70,399 peri- (N = 27,926) and post-menopausal women (N = 42,473) from the PREDICT 3 cohort (NCT04735835), examining the gut microbiome composition (using metagenomic sequencing) and diet quality using Healthy Eating Index (HEI) scores derived from the PREDICT Food Frequency Questionnaire. Data was also collected on menopause symptoms, grouped into vasomotor, sexual, psychological and somatic domains. A Menopause Symptom Tracker Score (MSTS) (0-100) was used to capture symptom prevalence (out of 20 symptoms) and impact on quality of life (0-not at all, 1-a little, 3-quite a bit and 5-extremely), with higher score values reflecting greater symptom burden(4).
Using random forest machine learning (ML) models, we found that  microbiome composition was predictive of the MSTS (AUCall = 0.70; AUCperi = 0.66; AUCpost = 0.65), as well as physical (e.g., fatigue, weight gain and slowed metabolism, thinning hair) and psychological (e.g., low mood or depression, anxiety and mood changes) domain scores (AUCall = 0.70; AUCperi = 0.66; AUCpost = 0.68 and AUCall = 0.70; AUCperi = 0.65; AUCpost = 0.66 respectively). Microbiome was also predictive of diet quality (HEI; AUCall  = 0.77; AUCperi = 0.77; AUCpost = 0.75). Subsequently, we compared the top 50 species predictive for the HEI and MSTS respectively, and identified 32 common predictive species. Notably, the top predictive species for both HEI and MSTS was the not-yet-characterised Lachnospiraceae species-level genome bin SGB4964.
To the best of our knowledge, this is the first time associations between menopause symptoms and the gut microbiome have been identified. Further work is needed to unravel diet-microbiome-symptom interrelationships and investigate a potential causal  role of microbiome in menopause symptom burden. This knowledge could ultimately lead to novel, microbiome-based strategies for improving the quality of life for women during and after the menopausal transition.
References
Bermingham KM, Linenberg I, Hall WL et al. (2022) EBioMedicine 85, 104303
Pounis G, Birmingham K, Capdevilla J et al. 2024. Proc Nutr Soc OC112
Yang M, Wen S, Zhang J, et al. (2022) Dis Markers 2022, 3767373
Asnicar F, Berry SE, Valdes AM et al. (2021) Nat Med 27, 321-332

**Associations Between Gut Microbiota and Menopause Symptoms: Novel Insights from the ZOE PREDICT 3 Cohort**
Curie Kim1, Francesco Asnicar2, George Pounis3, Lucy Marples1, Kate Bermingham1, Wendy Hall3, Nicola Segata2, Tim Spector1,4, Sarah Berry1,3
1Zoe Ltd, United Kingdom
2Department CIBIO, University of Trento, Trento, Italy
3Department of Nutritional Sciences, School of Life Sciences and Medicine, King’s College London, United Kingdom
4Department of Twins Research and Genetic Epidemiology, King’s College London, London, UK
Microbiome composition may differ according to menopause status, which may be partially mediated by diet(1). Peri- and post-menopausal symptom burden is associated with diet quality(2), however, knowledge on the association between menopause symptoms and gut microbiome composition is limited(3). This study investigates the associations between gut microbiome composition and menopause symptoms.
Data was analysed from 70,399 peri- (_N_ = 27,926) and post-menopausal women (_N_ = 42,473) from the PREDICT 3 cohort (NCT04735835), examining the gut microbiome composition (using metagenomic sequencing) and diet quality using Healthy Eating Index (HEI) scores derived from the PREDICT Food Frequency Questionnaire. Data was also collected on menopause symptoms, grouped into vasomotor, sexual, psychological and somatic domains. A Menopause Symptom Tracker Score (MSTS) (0-100) was used to capture symptom prevalence (out of 20 symptoms) and impact on quality of life (0-not at all, 1-a little, 3-quite a bit and 5-extremely), with higher score values reflecting greater symptom burden(4).
Using random forest machine learning (ML) models, we found that  microbiome composition was predictive of the MSTS (AUCall = 0.70; AUCperi = 0.66; AUCpost = 0.65), as well as physical (e.g., fatigue, weight gain and slowed metabolism, thinning hair) and psychological (e.g., low mood or depression, anxiety and mood changes) domain scores (AUCall = 0.70; AUCperi = 0.66; AUCpost = 0.68 and AUCall = 0.70; AUCperi = 0.65; AUCpost = 0.66 respectively). Microbiome was also predictive of diet quality (HEI; AUCall  = 0.77; AUCperi = 0.77; AUCpost = 0.75). Subsequently, we compared the top 50 species predictive for the HEI and MSTS respectively, and identified 32 common predictive species. Notably, the top predictive species for both HEI and MSTS was the not-yet-characterised Lachnospiraceae species-level genome bin SGB4964.
To the best of our knowledge, this is the first time associations between menopause symptoms and the gut microbiome have been identified. Further work is needed to unravel diet-microbiome-symptom interrelationships and investigate a potential causal  role of microbiome in menopause symptom burden. This knowledge could ultimately lead to novel, microbiome-based strategies for improving the quality of life for women during and after the menopausal transition.
**References**
1. Bermingham KM, Linenberg I, Hall WL et al. (2022) _EBioMedicine_ 85, 104303
2. Pounis G, Birmingham K, Capdevilla J et al. 2024. _Proc Nutr Soc_ OC112
3. Yang M, Wen S, Zhang J, et al. (2022) _Dis Markers_ 2022, 3767373
4. Asnicar F, Berry SE, Valdes AM et al. (2021) _Nat Med_ 27, 321-332

Associations between gut microbiota and menopause symptoms: novel insights from the ZOE PREDICT 3 cohort