The role of diet in the prevention and management of menopausal symptoms is poorly understood1,2. Digital health platforms have the potential to optimise collection of population-level menopause symptom data particularly in a rapidly changing environment2,3. This study explored the prevalence of menopause symptoms utilising data collection capabilities of a mobile app in a large population of peri- and postmenopausal women and to investigate novel associations between diet quality and symptoms.

Baseline data on diet, 20 menopause symptoms (i.e. 3 vasomotor, 3 sexual, 4 psychological and 10 somatic) and other characteristics of 70,412 participants of the ZOE PREDICT 3 app-based study in UK (n = 27,932 peri- and n = 42,480 postmenopausal) were analysed (NCT04735835). Dietary assessment was performed through an app-based food frequency questionnaire (PREDICTFFQ)4 and diet quality assessed using the Healthy Eating Index-2020 (HEI, score 0-100)5.

The burden of menopausal symptomatology was high; with 99.8% and 92.7% of peri- and postmenopausal participants reporting 1 or more symptoms respectively and 66.0% and 41.2% of peri- and postmenopausal participants experiencing >12 symptoms, respectively (P<0.001). Mean ( ±SD) symptom number was greater in the peri- versus postmenopausal group; 13.5±3.8, vs. 10.5±5.5 (P<0.001). HEI (mean±SD) was slightly lower in the peri- versus postmenopausal group; 73.9±9.7 vs. 76.6±8.9 respectively (P<0.001). Logistic regression analyses showed that a 20 unit increase in HEI was associated with reduction of 6%-37% and 12%-43% in likelihood of symptom presence (dependent on the symptom) in peri- and postmenopausal participants, respectively (P<0.05). ORs remained significant in adjusted models (for age, BMI, use of hormone replacement therapy, total energy intake and home environment (urban, rural) showing reductions of 7%-19% and 6-21%, respectively (P<0.05). Logistic regression analyses revealed that a similar increase in HEI (20 units) was associated with 17% and 19% reductions in the number of symptoms reported by peri- and postmenopausal women after multiple adjustments (P<0.05).

This large observational study confirms the high prevalence of menopausal symptoms among peri- and postmenopausal women and provides new evidence between adherence to healthy eating and reduced likelihood of menopausal symptoms, increasing the potential for symptom reduction by specific dietary approaches. Further studies should examine this relationship in longitudinal and dietary intervention settings.

Obesity is a complex condition which is significantly impacted by an individual’s biology, environment and behavioural factors. Excess energy dense (ED)(kJ/g) food intake (1), higher eating rate (2), increased eating frequency (3) and eating later in the day (4) have all been linked with obesity, but findings are mixed and require clarification using robust and objective measures of food intake behaviour. The aim of this research was to investigate associations between these eating behaviours and energy intake (EI) within a controlled residential setting in 65 participants (BMI 36.4 ±11.0 (range 17.6-65.2); 9 optimal weight, 15 overweight and 41 with obesity/severe obesity; age 44.3±12.7 years (range 18.6-67.6 years), 44F,21M).

As part of baseline measurements for a larger study (5) participants were assessed for 36hrs (twonights) within the Human Intervention Studies Unit at Ulster University, UK, and had ad lib access to a personalised menu (n 54 foods) representing a range of low/high fat macronutrient mix food groups with varying carbohydrate and protein content (6). Food intake and eating behaviour were measured covertly and validated by CCTV. Study outcomes were 24-hour EI (MJ), ED (kJ/g), % nutrient contribution to total EI, as well as parameters of eating including: size (g, kJ) speed (g/min; kJ/min;), number (n) and duration (mins) of eating occasions (defined as consumption of at least 210kJ separated by ≥5 minutes) and the timing of eating (epochs: 7-11am, 11:01-3pm, 3:01-7pm, 7:01-11pm). On the final morning, blood samples were collected before and 90mins after a standardised breakfast for the analysis of glicentin, a proglucagon-derived peptide. Associations between total EI and measures of eating behaviour were assessed using Spearman’s Rank

Correlation analysis showed weak positive associations between total EI and fasting glicentin (r = 0.296, p = 0.024), ED (r = 0.364, p = 0.004), and moderate associations with number (r = 0.419, p = 0.001) and size of eating occasions (r = 0.415, p = 0.005) as well as total weight of food consumed (r= 0.634, p<0.001). Of note, there was also a positive association between EI/eating occasion and a faster eating rate as expressed by [kJ/min (r = 0.519; p<0.001)] but not g/min (r = 0.276, p = 0.07). There was also a stronger relationship between EI and lean mass (r = 0.450, p<0.001) than bodyweight (r = 0.291, p = 0.023).

These findings suggest that food portion size and increased eating frequency may be a more important drivers of EI than dietary ED, and that the rate of eating higher ED foods may be linked to consuming a higher energy meal. These findings are skewed towards individuals with obesity but if confirmed highlight a need for weight management programmes to strengthen strategies to improve portion control and to limit grazing behaviours. There is also a need for robust randomised controlled trials to determine if eating slower reduces overall EI.

Digital health technologies delivering dietary and lifestyle advice1,2 may offer a contemporary approach to menopause symptom mitigation in a large population base3. This study aimed to evaluate alterations in both diet quality and menopause symptom burden following the implementation of an app-based, personalised dietary intervention in peri- and postmenopausal participants.

Baseline and follow-up data (mean follow-up time, 207 ± 72 days) on diet, menopause symptom number (from 20 vasomotor, sexual, psychological and somatic symptoms), symptom severity (0-not at all, 1-a little, 3-quite a bit and 5-extremely) and other characteristics of 4,287 UK based participants of the ZOE PREDICT 3 study (1,000 perimenopausal and 3,287 postmenopausal) were analysed (NCT04735835). Dietary assessment was performed through an app-based food frequency questionnaire (PREDICT-FFQ)2 and diet quality assessed using the Healthy Eating Index-2020 (HEI, score 0-100)4. A novel Menopause Symptom Tracker Score (MSTS 0-100, Copyright © 2024 Zoe Limited) was used to capture symptom number and severity.

There was a modest increase in diet quality after the intervention in both peri- and postmenopausal participants; mean HEI from 76.4 ± 8.4 to 79.7 ± 6.8 (P<0.001) and from 78.7 ± 7.8 to 81.1 ± 6.4 (P<0.001), respectively. Baseline MSTS was higher in peri- versus postmenopausal participants 28.9 ± 15.1 vs. 18.1 ± 15.0 (P<0.001). However, both groups showed a significant decrease in mean MSTS after the intervention compared to baseline; mean change (95%CI) in perimenopausal was -8.7 (-9.5, -7.9; 30.1% reduction) and in postmenopausal was -6.6 (-6.9, -6.2; 36.5% reduction) (P for both <0.001).

The reduction in the overall MSTS was greater in perimenopausal compared to postmenopausal (P<0.001). Reductions in domain-specific MSTS for peri- and postmenopausal groups respectively, were as follows: vasomotor −0.56 (−0.71, −0.40; 24.9% reduction) and −0.47 (−0.54, −0.41; 31.8% reduction), sexual −0.72 (−0.87, −0.57; 18.6%) and -1.08 (-1.16, −0.99; 28.7%), psychological -2.3 (-2.5, 2.0; 35.0%) and -1.2 (-1.3, -1.1; 44.2%), somatic -5.1 (-5.6, -4.7; 31.5%) and -3.8 (-4.0, -3.6; 37.5%) (P for all <0.001). The reduction in the psychological and somatic domain-specific MSTS was greater in peri-compared to postmenopausal group (P for both <0.001).

This study supports the potential of personalised app-based dietary interventions in the mitigation of menopausal symptoms during menopause transition and its potential to affect the health and quality of life of millions. Further studies should investigate their efficacy in a randomised, controlled dietary intervention setting.

Diet is an important modifiable lifestyle factor for human health, and plant-rich dietary patterns are associated with lower risk of non-communicable diseases in numerous studies. However, objective assessment of plant-rich dietary exposure in nutritional epidemiology studies remains challenging. This study aimed to develop and evaluate metabolic signatures of the most widely used plant-rich dietary patterns using a targeted metabolomics method comprising of 108 plant food metabolites.

A total of 218 healthy participants from the POLYNTAKE cohort were included, aged 51.5 ± 17.7 years, with 24h urine samples measured using ultra-high-performance liquid chromatography–mass spectrometry. The validation dataset employed three sample types to test the robustness of the signature, including 24h urine (ABP cohort, n = 88), plasma (POLYNTAKE cohort, n = 195), and spot urine (TwinsUK cohort, n = 198). Adherence to the plant-rich diet was assessed using a priori plant- rich dietary patterns. A combination of metabolites that evaluates the adherence and metabolic response to a specific diet was identified as metabolic signature. We applied linear regression analysis to select the metabolites significantly associated with dietary patterns (adjusting energy intake), and ridge regression to estimate penalized weights of each candidate metabolite. The correlation between metabolic signature and the dietary pattern was assessed by Spearman analysis (FDR < 0.05).

The metabolic signatures consisting of 42, 22, 35, 15, 33, and 33 predictive metabolites across different subclasses were found to be associated with adherence to Amended Mediterranean Score (A-MED), Original MED (O-MED), Dietary Approaches to Stop Hypertension (DASH), Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND), healthy Plant-based Diet Index (hPDI) and unhealthy PDI (uDPI), respectively. The overlapping and distinct predictive metabolites across six dietary patterns predominantly consisted of phenolic acids (n = 38), including 14 cinnamic acids, 14 hydroxybenzoic acids, seven phenylacetic acids, and three hippuric acids. Six metabolites were included in all signatures, including two lignans: enterolactone-glucuronide, enterolactone-sulfate, and four phenolic acids: cinnamic acid, cinnamic acid-4'-sulfate, 2'- hydroxycinnamic acid, and 4-methoxybenzoic acid-3-sulfate. The established signatures were robustly correlated with dietary patterns in validation dataset (r = 0.13 - 0.40, FDR < 0.05).

We developed and evaluated a set of metabolic signatures that robustly reflected the adherence and metabolic response to plant-rich dietary patterns, suggesting the potential of these signatures to serve as an objective assessment of free-living eating habits.

TwinsUK is the largest cohort of community-dwelling adult twins in the UK. The registry comprises over 14,000 volunteer twins (14,838 including mixed, single and triplets); it is predominantly female (82%) and middle-aged (mean age 59). In addition, over 1800 parents and siblings of twins are registered volunteers. During the last 27 years, TwinsUK has collected numerous questionnaire responses, physical/cognitive measures and biological measures on over 8500 subjects. Data were collected alongside four comprehensive phenotyping clinical visits to the Department of Twin Research and Genetic Epidemiology, King’s College London. Such collection methods have resulted in very detailed longitudinal clinical, biochemical, behavioral, dietary and socioeconomic cohort characterization; it provides a multidisciplinary platform for the study of complex disease during the adult life course, including the process of healthy aging. The major strength of TwinsUK is the availability of several ‘omic’ technologies for a range of sample types from participants, which includes genomewide scans of single-nucleotide variants, next-generation sequencing, metabolomic profiles, microbiomics, exome sequencing, epigenetic markers, gene expression arrays, RNA sequencing and telomere length measures. TwinsUK facilitates and actively encourages sharing the ‘TwinsUK’ resource with the scientific community — interested researchers may request data via the TwinsUK website (http://twinsuk.ac.uk/resources-for-researchers/access-our-data/) for their own use or future collaboration with the study team. In addition, further cohort data collection is planned via the Wellcome Open Research gateway (https://wellcomeopenresearch.org/gateways). The current article presents an up-to-date report on the application of technological advances, new study procedures in the cohort and future direction of TwinsUK.

The COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) project is a large international collaborative effort to analyze individual-level phenotype data from twins in multiple cohorts from different environments. The main objective is to study factors that modify genetic and environmental variation of height, body mass index (BMI, kg/m2) and size at birth, and additionally to address other research questions such as long-term consequences of birth size. The project started in 2013 and is open to all twin projects in the world having height and weight measures on twins with information on zygosity. Thus far, 54 twin projects from 24 countries have provided individual-level data. The CODATwins database includes 489,981 twin individuals (228,635 complete twin pairs). Since many twin cohorts have collected longitudinal data, there is a total of 1,049,785 height and weight observations. For many cohorts, we also have information on birth weight and length, own smoking behavior and own or parental education. We found that the heritability estimates of height and BMI systematically changed from infancy to old age. Remarkably, only minor differences in the heritability estimates were found across cultural–geographic regions, measurement time and birth cohort for height and BMI. In addition to genetic epidemiological studies, we looked at associations of height and BMI with education, birth weight and smoking status. Within-family analyses examined differences within same-sex and opposite-sex dizygotic twins in birth size and later development. The CODATwins project demonstrates the feasibility and value of international collaboration to address gene-by-exposure interactions that require large sample sizes and address the effects of different exposures across time, geographical regions and socioeconomic status.

Low birth weight (LBW) can have an impact on health outcomes in later life, especially in relation to pre-disposition to metabolic disease. Several studies suggest that LBW resulting from restricted intrauterine growth leaves a footprint on DNA methylation in utero, and this influence likely persists into adulthood. To investigate this further, we performed epigenome-wide association analyses of blood DNA methylation using Infinium HumanMethylation450 BeadChip profiles in 71 adult monozygotic (MZ) twin pairs who were extremely discordant for birth weight. A signal mapping to the IGF1R gene (cg12562232, p = 2.62 × 10−8), was significantly associated with birth weight discordance at a genome-wide false-discovery rate (FDR) of 0.05. We pursued replication in three additional independent datasets of birth weight discordant MZ pairs and observed the same direction of association, but the results were not significant. However, a meta-analysis across the four independent samples, in total 216 birth-weight discordant MZ twin pairs, showed a significant positive association between birth weight and DNA methylation differences at IGF1R (random-effects meta-analysis p = .04), and the effect was particularly pronounced in older twins (random-effects meta-analysis p = .008, 98 older birth-weight discordant MZ twin pairs). The results suggest that severe intra-uterine growth differences (birth weight discordance >20%) are associated with methylation changes in the IGF1R gene in adulthood, independent of genetic effects.

In humans, in contrast to animals, the genetic influences on infidelity are unclear. We report here a large study of over 1600 unselected United Kingdom female twin pairs who confidentially reported previous episodes of infidelity and total lifetime number of sexual partners, as well as attitudes towards infidelity. Our findings demonstrate that infidelity and number of sexual partners are both under moderate genetic influence (41% and 38% heritable, respectively) and the genetic correlation between these two traits is strong (47%). Conversely, attitudes towards infidelity are driven by shared and unique environmental, but not genetic, influences. A genome-wide linkage scan identified three suggestive but nonsignificant linkage areas associated with infidelity and number of sexual partners on chromosomes 3, 7 and 20 with a maximum LOD score of 2.46. We were unsuccessful in associating infidelity or number of sexual partners with a locus implicated in other mammals' sexual behavior, the vasopressin receptor gene. Nonetheless, our findings on the heritabil-ity of sexual infidelity and number of sexual partners provide support for certain evolutionary theories of human sexual behavior, as well as justifying further genetic and molecular research in this domain.