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INVESTIGATING THE IMPACT OF TEA CONSUMPTION ON COGNITIVE FUNCTION AND EXPLORING TEA-GENETIC INTERACTIONS IN OLDER ADULTS AGED 65-105 YEARS: FINDINGS FROM THE 2002−2018 CLHLS DATA

 

L. Yu1, M. Yang2, K.X. Ye3,4,5, C. Li1, M. Zou1, J. Wang1, X. Yuan1, D. Zheng1, C. Sun1, Y. Zhang1, Q. Feng6,
A.B. Maier3,4,7, L. Sun1, L. Feng3,4,5, Y. Wang1, H. Chen8,9, Y. Zeng9,10

 

1. Weifang Medical University, Weifang, China; 2. School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan, China; 3. Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 4. Centre for Healthy Longevity, National University Health System, Singapore; 5. Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; 6. Department of Sociology, National University of Singapore, Singapore; 7. Faculty of Behavioral and Movement Sciences, Department of Human Movement Sciences, Vrije University, Amsterdam Movement Sciences, Amsterdam, the Netherlands; 8. Department of Management, Business School of Xiangtan University, Xiangtan, China; 9. Center for Study of Aging and Human Development and Geriatrics Division, School of Medicine, Duke University, Durham, North Carolina; 10. Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China.

Corresponding Author: Yanyu Wang, Weifang Medical University, Weifang, China, wangyanyu@wfmc.edu.cn; Huashuai Chen, Yi Zeng, Center for Study of Aging and Human Development and Geriatrics Division, School of Medicine, Duke University, Durham, North Carolina, huashuai.chen@gmail.com; zengyi68@gmail.com

J Prev Alz Dis 2024;
Published online January 24, 2024, http://dx.doi.org/10.14283/jpad.2024.22

 


Abstract

BACKGROUND: As the global population ages, cognitive impairment (CI) becomes more prevalent. Tea has been one of the most popular drinks in the world. Several studies have demonstrated that tea consumption has an impact on cognitive function.
OBJECTIVE: This study aims to examine the association between tea consumption and cognitive function and explore the potential effect of genetics on the relationship between tea consumption and CI risk in older adults.
DESIGN: This is a prospective longitudinal study using data from the Chinese Longitudinal Healthy Longevity Survey (CLHLS).
SETTING: Six waves of data from CLHLS containing 76,270 subjects were analyzed. Generalized estimation equations (GEE) with a logit link function were adopted to estimate the effect of tea consumption on CI risk from a cross-sectional and longitudinal perspective.
PARTICIPANTS: A population-based cohort of adults aged 65-105 years.
MEASUREMENTS: The frequency and type of tea consumption were obtained by questionnaires. CI was measured based on MMSE. Polygenic risk was measured using the polygenic score approach described by the International Schizophrenia.
RESULTS: The results showed that drinking green tea had a better protective effect on cognitive function than other types of tea, the incidence of CI gradually decreased with the increase of tea consumption frequency, and men were more likely to benefit from tea consumption. Additionally, we also found a significant interaction between tea consumption and genetic risk, measured by polygenic risk score (PRS).
CONCLUSIONS: Based on current research evidence, tea consumption, may be a simple and important measure for CI prevention.

Key words: Cognitive impairment, tea consumption, polygenic risk, tea-gene interaction, older adults.


 

Introduction

Population aging is one of the major challenges faced by most countries in the world, including China (1). Cognitive impairment (CI) is a common central nervous system disease among older adults. It limits the individual’s ability to work, live, and socialize, is a major obstacle to active and functional aging, and causes a heavy medical burden on families and society (2, 3). Therefore, the academic community has directed its attention towards strategies aimed at decelerating cognitive decline and mitigating the onset of cognitive diseases, such as Alzheimer’s disease.
According to the Chinese Longitudinal Healthy Longevity Survey (CLHLS), tea consumption is associated with better cognitive function in the oldest-old Chinese (4). The Singapore Longitudinal Aging Study (SLAS) has found that drinking tea may slow the cognitive decline of older adults (5). A sizeable body of biological research evidence suggests that various phytochemicals in tea, including catechins, L-theanine, and caffeine, play important roles in the underlying biological mechanisms of the protective effects of tea consumption on cognitive function (4).
There are comparatively fewer studies on the relationship between the type of tea consumed and the improvement of cognitive function, and the majority of cross-sectional studies have drawn inconsistent results, although a growing number of studies indicate that tea consumption may have a possible protective effect on cognitive function. Several studies have examined the effects of one type of tea, such as green tea (6-8), black tea (9-11), or scented tea (9), on cognitive function. Most studies have found that green tea has a significant protective effect on cognitive function in older adults (12). While some studies have found that black tea and oolong tea have a significant effect on reducing CI (9), other studies have found no effect of black tea on cognitive decline in older American men (10) and neither black tea nor oolong tea has a protective effect on cognitive function (13). In a study that compared different teas, green tea consumption was found to be significantly associated with a reduced risk of cognitive decline, and no association was found between black tea and the incidence of dementia or mild cognitive impairment (MCI) (11).
Numerous investigations have suggested that the protective mechanism of tea consumption on cognitive function is influenced by the interaction between behavior and genotype, and the effect of tea consumption on disease varies by genotype (14-18). Previous studies using the CLHLS cohort found that the interaction between the FOXA genotype and tea consumption had a significant effect on cognitive function in people over 92 years of age (19), and the interaction between FOXO1A-209 genotype and tea consumption was significantly associated with reduced mortality in old age (20, 21). The findings of these two studies indicate an interaction between tea consumption and genotype. However, these studies focused on the relationship between single nucleotide polymorphisms (SNPs) and disease, ignoring the influence of polygenes on disease. The polygenic risk score (PRS) is a method that weights the genotypic effects of a set of SNPS and associates them with a phenotype to calculate an individual’s predisposition to that phenotype (polygenic phenotype). By integrating the effects of multiple susceptibility sites, PRS has been shown to quantify the genetic risk of various complex diseases. PRS serves as a genetic indicator, representing genetic strength or risk, and holds potential application value in population risk stratification, disease risk prediction, treatment selection, and disease prognosis estimation (22, 23). Therefore, investigating the interaction between tea consumption and PRS on cognitive function is more meaningful than studying the interaction between a single gene and tea consumption on cognitive function.
This study aimed to investigate the effects of different amounts and types of tea consumption on cognitive function, utilizing cross-sectional and longitudinal data from CLHLS. Additionally, the study sought to explore the potential interaction between tea consumption and genetic type on CI risk in older adults.

 

Materials and Methods

Study Participants

We used data from the 2002, 2005, 2008, 2011, 2014, and 2018 waves of the CLHLS. The baseline survey was conducted in 1998. During follow-ups, participants were randomly selected from about half of the counties and city districts in 23 out of 31 Chinese provinces. The survey areas covered 985 million people in the baseline year 1998 and 1,156 million people in the most recent census year 2010, approximately 84-85 percent of the total population of China (1, 24). A remaining 76,270 participants aged 65-105 were included after removing those without information on cognitive function or tea consumption. Extensive data were collected using internationally standardized questionnaires adapted to the Chinese cultural and social context. The data quality of CLHLS has been reported as satisfactory by previous studies (25). All participants were informed of the study’s purpose, confidentiality issues, and their rights as research participants.

Variables Definition

Frequencies of Tea Consumption (both “at present” and “around age 60”) were defined as the following 3 dummies: (1) Almost every day; (2) Not every day, but occasionally (weekly/ monthly/ sometimes); (3) Rarely/never.
The choice of «at present» and «around age 60» as the two time points for assessing tea consumption and its impact on cognitive function was made to ensure a comprehensive exploration of the dynamic relationship over time. «At present» was selected to capture the current tea consumption habits, allowing for a cross-sectional analysis of the participants’ current lifestyles. Simultaneously, «around age 60» was chosen to investigate potential long-term effects during a critical period when cognitive changes often begin to manifest (26, 27). This dual-time point approach allows us to examine both contemporary and historical aspects of tea consumption, providing a nuanced perspective on its association with cognitive function.
Type of Tea Consumption, which was defined as the following three dummies: (1) green tea; (2) not-green tea, including oolong/white/yellow tea, red/dark/compressed tea, and scented tea; (3) not a tea drinker. Information on types of tea consumption was reported only in the 2014 and 2018 waves of CLHLS. Frequencies of tea consumption were reported in all the waves of CLHLS from 2002-2018.
Cognitive Impairment was assessed by the MMSE; the total score ranged from 0 to 30, with a lower score representing poorer cognitive function. In the primary analysis, we used education-specific cut-offs to define CI based on the latest normative and validation study of MMSE in the Chinese population (28). The MMSE cut-offs for defining CI were less than or equal to 16 for those without schooling, less than or equal to 19 for those with 1-6 years of education, and less than or equal to 23 for those with more than six years of education.
Cognitive Decline was defined as when cognitive function is active in the first wave but impaired in the follow-up wave. The reference group is those who are cognitively active in both waves. Those samples were dropped if the cognitive function in the first wave was already impaired.

Assessment of Polygenic Risk

The DNA samples of the CLHLS genotyping datasets analyzed in the present study were genotyped by Beijing Genomics Institute (BGI) using the Affymetrix Axiom™ myDesign™ (384-format) Bead Chips, which were created by selecting 27,000 candidate single nucleotide polymorphisms (SNPs) from each of the 13,226 samples among 2008, 2011, and 2014 waves of CLHLS datasets. These 27,000 SNPs of the healthy aging genes include (a) SNPs associated with longevity and/or health status (measured by activities of daily living and cognitive function) at old ages identified by us using the CLHLS genomewide association study (GWAS) and the US. Health and Retirement Survey (HRS) GWAS datasets; (b) SNPs associated with various chronic diseases including Alzheimer’s disease, dementia, cognitive and mental problems, and other diseases reported in the literature. These SNPs passed the quality-control test with a genotyping rate >= 0.90 and the average genotype imputation accuracy equals 0.99. We obtained 287,898 imputed SNPs for each of the 13,226 samples based on the 27,000 initially genotyped SNPs using IMPUTE software version 215 and the 1,000 Genomes Project integrated phase 1 release as a reference panel.
We pooled the CLHLS samples from the 2008, 2011, and 2014 waves when analyzing the interaction effects between genes and tea consumption behaviors on CI. Only the information collected in the first survey was considered for follow-up samples that were surveyed two or three times between 2008 and 2014. Finally, we got 9,698 samples aged 65-105 with DNA and cognitive function information among the 13,226 CLHLS genotyping samples.
The polygenic risk was measured using the polygenic score approach described by the International Schizophrenia Consortium et al. (2009). This approach requires discovery and a target dataset. The discovery dataset is used to identify individual SNPs associated with the outcome at a chosen p-value threshold (PT). Results from the discovery dataset are then used to derive polygenic scores in the target dataset. In this approach, the polygenic score is the weighted sum of all the alleles that either confer risk for or are protective against the outcome of interest and are significant at the pT. PRS was calculated by PLINK1 using the –score option, which computes a linear function of the additively coded number of reference alleles weighted by the log odds ratios (betas) from discovery samples.

Statistical Analyses

We used the logit link function and reported the odds ratios (OR) and 95% confidence intervals (CIs) obtained from the model’s estimated robust standard errors. An exchangeable correlation structure was used to account for subject-level repeated measures. All statistical analyses were performed using the statistical software Stata 14.1.
For this study, we used the results of the South China samples of CLHLS as our discovery dataset and the North China samples of CLHLS as our target dataset. Table S1 lists the characteristics of subsamples living in the south and north regions of China. PRS was calculated by PLINK1 using the –score option, which computes a linear function of the additively coded number of reference alleles weighted by the log odds ratios (betas) from discovery samples.
We standardized the PRS for each of the exclusive groups of the identified loci associated with CI at different significance levels through the z-scores transformation. After rescaling the z-scores transformation, the standardized PRS had a mean of 0 and a standard deviation of 1.0. We abbreviated “standardized PRS” as “PRS” hereafter and in the main text to simplify the presentations.
We evaluated the associations between tea consumption behaviors (at present or around age 60), PRS, and CI using the logistic regression model. Table 5 shows the results of a logistic regression analyzing the interaction effects of PRS and tea consumption on the CI of older adults.
Results

The Characteristics of The Study Samples

The characteristics of the study samples in all six waves during 2002-2018 are shown in Table 1. The proportion of people who do not drink tea has had an upward trend from 2002 to 2018. Overall, in six waves of data, the proportion of those who rarely/never drink tea ranges from 51.6% to 74.9% at present and 52.0% to 71.6% around age 60. The number of people who consume green tea was more than those who consume other types of tea.

Table 1. Characteristics of the study samples, CLHLS 2002-2018

 

Cross-Sectional Association of Tea Consumption Frequencies with CI

Table 2 shows the cross-sectional associations of tea consumption frequencies with CI during 2002-2018.
As can be seen from Table 2, the incidence of CI in the older adults who rarely/never drank tea, occasionally drank tea, and daily drank tea decreased successively. In other words, as the frequency of tea consumption increased, the incidence of CI gradually decreased. Model 1, which referred to the results without controlling for any covariates, showed that occasional and daily tea consumption was protective for cognitive function compared to non-tea drinkers, whether they were tea drinkers around age 60 or at present (OR = 0.84, 95%CI, 0.80–0.88, p < 0.001; OR = 0.61, 95%CI, 0.58–0.63, p < 0.001; OR = 0.74, 95%CI, 0.71–0.77, p < 0.001; OR = 0.52, 95%CI, 0.50–0.54, p < 0.001, respectively). After adjusting for covariates, the risk of CI decreased in older adults drinking tea occasionally and daily at present (OR = 0.87, 95%CI, 0.82–0.92, p < 0.001; OR = 0.69, 95%CI, 0.65–0.73, p < 0.001, respectively), and only those aged around 60 who drank tea daily had a reduced risk of CI (OR = 0.84, 95%CI, 0.80–0.89, p < 0.001).
Gender-stratified analysis showed that among older adults who drank tea around age 60 or at present, daily drinking tea had a protective effect on cognition in both men and women (OR = 0.80, 95%CI, 0.74–0.87, p < 0.001; OR = 0.86, 95%CI, 0.80–0.93, p < 0.001; OR = 0.63, 95%CI, 0.59–0.69, p < 0.001; OR = 0.73, 95%CI, 0.68–0.79, p < 0.001, respectively), and occasional tea consumption only had a protective effect on the cognition of current tea drinkers in both men and women(OR = 0.86, 95%CI, 0.78–0.94, p = 0.001; OR = 0.87, 95%CI, 0.81–0.94, p < 0.001, respectively).

Table 2. Cross-sectional associations of frequencies of tea consumption with cognitive impairment

Notes: (1) Dependent variable: Cognitive impairment (active=0). (2) Generalized estimation equation (GEE) were used. Samples in all the 6 waves from 2002-2018 were included. (3) Model 1: base model; model 2: adjusted for age, sex, region, rural/urban residence, education, marital status, co-residence with children, and family income; and model 3: model 2 plus smoking, alcohol consumption, physical exercise, and dummies of waves. (4) P value: * <0.05, **<0.01.

 

Cross-Sectional Association of Tea Types with CI

Table 3 reports the cross-sectional associations of types of tea consumption with CI during 2014-2018.
As shown in Table 3, the green tea consumption group has the lowest incidence of CI, followed by non-green tea drinkers and those who do not consume any tea. Model 1, which did not control for any covariates, showed that drinking tea (green tea or non-green tea) had a protective effect on cognitive function (OR = 0.44, 95%CI, 0.39–0.51, p < 0.001; OR = 0.53, 95%CI, 0.47–0.61, p < 0.001; OR = 0.38, 95%CI, 0.34–0.44, p < 0.001; OR = 0.45, 95%CI, 0.39–0.52, p < 0.001, respectively), compared to non-tea drinkers, whether they were around age 60 or current tea drinkers. Even after further controlling for demographic variables and variables such as smoking, alcohol consumption, and physical exercise, the association remained statistically significant among older adults who currently drink tea (OR = 0.61, 95%CI, 0.52–0.71, p < 0.001; OR = 0.80, 95%CI, 0.67–0.95, p < 0.001, respectively). In older people who drank tea around age 60, only green tea consumption was shown to have a protective effect on cognitive function (OR = 0.70, 95%CI, 0.59–0.83, p < 0.001).
Gender-stratified analysis showed that drinking green tea had a protective effect on cognitive function in both men and women (OR = 0.69, 95%CI, 0.54–0.87, p = 0.002; OR = 0.72, 95%CI, 0.57–0.92, p = 0.010; OR = 0.56, 95%CI, 0.45–0.70, p < 0.001; OR = 0.66, 95%CI, 0.52–0.83, p < 0.001, respectively), while drinking non-green tea only had a protective effect on cognitive function in older men who drank tea at present(OR = 0.78, 95% CI, 0.62–0.99, p = 0.038).

Table 3. Cross-sectional associations of types of tea consumption with cognitive impairment

Notes: (1) Dependent variable: Cognitive impairment (active=0). (2) Generalized estimation equation (GEE) were used. Samples in all the 6 waves from 2002-2018 were included. (3) Model 1: base model; model 2: adjusted for age, sex, region, rural/urban residence, education, marital status, co-residence with children, and family income; and model 3: model 2 plus smoking, alcohol consumption, physical exercise, and dummies of waves. (4) P value: * <0.05, **<0.01.

 

Longitudinal Association of Tea Consumption Frequencies with CI

The longitudinal associations of frequencies of tea consumption with CI during 2002–2018 are presented in Table 4. The dependent variable is the cognitive decline from this period to the next two periods with an interval of six years.
Table 4 indicated that the incidence of CI in the group who drink tea at present or around age 60 was successively reduced among those who drink tea rarely/never, occasionally, and every day. The results of model 1 showed that daily tea consumption was protective for cognitive function compared to non-tea drinkers in the older adults drinking tea both around age 60 and at present (OR = 0.75, 95%CI, 0.67–0.83, p< 0.01; OR = 0.74, 95%CI, 0.67–0.82, p < 0.01, respectively). After controlling for covariates, among older adults who drink tea at present, drinking tea daily still has a protective effect on cognitive function (OR=0.87, 95%CI, 0.77–0.98, p < 0.01; OR=0.86, 95%CI, 0.76–097, p < 0.05, respectively). According to gender-stratified analysis, there was no statistically significant difference between drinking tea and cognitive function in men and women, possibly due to the small sample size after grouping.

Table 4. Longitudinal associations of frequencies of tea consumption with cognitive decline

Notes: (1) OR = Odds Ratio; CI = confidence interval. Dependent variable: Cognitive decline (both active=0). (2) Generalized estimation equation (GEE) were used. Samples in all the 6 waves from 2002-2018 were included. (3) Model 1: base model; model 2: adjusted for age, sex, region, rural/urban residence, education, marital status, co-residence with children, and family income; and model 3: model 2 plus smoking, alcohol consumption, physical exercise, and dummies of waves. (4) P value: * <0.05, **<0.01.

 

Interaction Effects between Genetics and Tea Consumption on CI

To identify independent loci for constructing PRS that exhibit significant interaction effects with tea-consumption behaviors on CI, we removed those SNPs that currently lack significant interaction effects (p > 0.05) with tea-consumption behavior on CI from the discovery dataset. We obtained 12,574 SNPs which have interaction effects with tea consumption at P < 0.05 among the total of 287,898 imputed SNPs.
Association analyses were conducted using the PLINK software on the discovery dataset and selected SNPs/loci at the following two different p-value thresholds: (1) pT<0.01: 196 SNPs and 36 independent loci were obtained; (2) pT<0.05: 927 SNPs and 134 independent loci were obtained. The above two sets of p-value thresholds represent a low and middle degree of polygenicity, respectively. The list of independent loci selected at pT<0.01 and pT<0.05 from the discovery dataset is shown in Supplemental Table S2.
The results of Logistic regression are shown in Table 5. The combination effects in Table 5, i.e., log (odds ratio), of tea consumption and PRS on CI are shown in Figure 1.

Figure 1. Comparison of log(Odds Ratios) of PRS constructed by 36 loci at pT<0.01 on Cognitive impairment between Tea drinkers and Non-drinkers, based on Model 1 in Table 5

Table 5 and Figure 1 showed that tea-consumption behavior had significant interaction effects with PRS on CI.

Table 5. Interaction effects between Standardized PRS and tea drinking frequencies associated with Cognitive Impairment (Logistic models)

Note: (1) Using South sample as discovery and North sample as replication. (2) PRSes were standardized with mean=0 and SD=1. (3) Covariates include: age, east/middle/west regions, rural/urban residence, education, marital status, number of family members, smoking, alcohol drinking, and physical exercise. Coefficients of covariates are not listed.

 

Discussion

Using the six waves of CLHLS data from 2002 to 2018, both cross-sectional and longitudinal analyses found that tea consumption had a significant protective effect on the occurrence of cognitive function, and the incidence of CI in the older adults who rarely/never drank tea, occasionally drank tea, and daily drank tea gradually decreased. The incidence of CI was lower in the group that consumed green tea than in the non-green tea consumption group. In addition, gender and genetic basis are also factors that affect the effect of tea consumption, and this study found that men who drink tea have a greater protective effect on cognitive function than women. The interaction between tea consumption and PRS had an impact on CI.
Overall, tea consumption was found to have a protective effect on cognitive function in the current study. which is consistent with previous findings (4, 29). Numerous meta-analytic investigations have demonstrated that the tea consumption has a neuroprotective effect. A systematic review of 26 observational studies (including 52,503 participants) showed that daily tea consumption significantly reduced the risk of cognitive decline, CI, and MCI in older adults (30). Studies of Chinese Singaporeans have shown that regular tea consumption, especially black, oolong, or green tea, is beneficial for attention, balance, gait, and the basic activities of daily living (31, 32). Moreover, studies have found that a high frequency of green tea consumption is associated with low levels of formation of the microtubule-associated protein tau (tau), and hence they may reverse or delay the occurrence and development of AD by reducing the level of cerebrospinal fluid tau and improving CI (33).
Cognitive decline in this study refers to active cognitive function in the first wave and impaired cognitive function in subsequent waves. The reference group is those who are cognitively active in both waves. As the process of drinking tea slows cognitive decline is long and slow, the interval between the two tests in this study was three years, which is relatively short and may not accurately reflect the effects of drinking tea on cognitive function. Therefore, to better understand the longitudinal effects of tea consumption on cognitive function, we defined cognitive decline as the change of cognition function from this period to the next two periods with an interval of six years. The sample periods were 2002-2008, 2005-2011, 2008-2014, and 2011-2018, with a total of four periods of data.
In the longitudinal study of the association between frequency of tea consumption and CI, we found that in model 1 without controlling for any covariates, daily tea consumption had a protective effect on cognitive function. This effect was observed regardless of whether tea consumption occurred around age 60 or at present. Even after controlling for various covariates, in older adults who drink tea at present, drinking tea daily still had a protective effect on cognitive function. This is also consistent with previous research results. In a longitudinal study of 65-year-old community-living Chinese adults, the cognitive function of 1,438 participants was reassessed by the MMSE 1–2 years after the initial assessment. After adjusting for confounding variables, it was found that the greater the tea consumption, the lower the prevalence of cognitive decline (9). The Singapore Longitudinal Ageing Study (SLAS) found that the association between tea consumption and reduced risk of CI was independent of known risk factors and appeared to be dose and duration-dependent (5), which may also explain why daily tea drinkers have a lower risk of CI in older adults.
In this study, a greater proportion of tea drinkers consume green tea, which is consistent with the proportion of green tea produced in China and the country’s tea culture. As one of the most commonly consumed beverages in China, drinking green tea has a health effect on the body (5, 34-36). Tea contains various bioactive compounds, such as tea catechins, L-theanine, and caffeine. These compounds exert neuroprotective effects through different mechanisms (37-39). L-theanine and catechins both have antioxidant and anti-inflammatory effects (40, 41). Theanine is a naturally occurring free amino acid in tea with neuroprotective effects (42, 43). Catechins, especially epigallocatechin 3-gallate (EGCG), are powerful antioxidants and iron chelators involved in regulating a variety of biological mechanisms, such as regulating signal transduction pathways and stress hormone secretion, and catecholamines production, Inhibition of acetylcholinesterase activity (29, 44). Due to the different degrees of fermentation in the production process, as well as the origin, plant varieties, and other factors, the tea polyphenol content of various types of tea is different. Therefore, information on lifetime tea consumption and blood concentrations of catechins and L-theanine could be collected for further investigation in future studies. Overall, the results of this study align with previous findings, indicating that drinking green tea has a protective effect on cognitive function.

The present study found that gender had different protective effects on cognitive function among tea drinkers. It was found that men benefited more from drinking tea, aligning with the findings published in a meta-analysis conducted in Japan. This report found that green tea consumption reduced all-cause mortality in middle-aged and older adults, but there were differences between males and females (45). A community-based epidemiological study found that green tea consumption was protective against CI in males, particularly in males aged 70 years, but not in females. Additional evidence comes from the APOEε4 allele, which is known to increase the risk of dementia and may be mediated by estrogen in women (46, 47). Research evidence has also shown that brain structure and function in men and women differ throughout the aging process (48). The findings of the current study suggest that gender differences exert an influence on the protective effects of green tea, revealing that such effects are detectable only in males. Although the cause of the only protective effect in males remains elusive, it nonetheless highlights the need to consider protective and risk factors in men and women independently. The results of Zeng’s analysis of the health characteristics of centenarians (21) also seem to explain the gender difference in CI. He argued that gender differences in CI fit the gender health-survival paradox, in which women tend to live longer but experience poor health compared to men (49). The same findings were found in previous studies (50-52). Gender paradoxes are often linked to gender differences in socioeconomic status, genetic and acquired risks, and disease patterns and prevention.
While some studies have shown that drinking tea has potential cognitive benefits for men, it is essential to acknowledge that existing literature also highlights positive effects in females. SLAS found a greater protective effect of tea consumption on cognitive function in women but not men. The data suggest an effect modification role for gender. However, firm conclusions cannot be drawn due to the lack of statistical significance in the interaction throughout the whole study sample (5). Another longitudinal study also found that tea intake slowed the rate of cognitive decline in females, but it did not find an effect of tea consumption on cognitive performance in males (53). The intricacies of gender-specific responses to tea consumption warrant further investigation. Future research endeavors should delve deeper into understanding whether tea may exert varying cognitive benefits based on gender, shedding light on the nuanced aspects of this relationship.
Because aging is related to CI (24, 54), we explored the effects of age grouping on the association between tea consumption and CI in our initial attempt to unravel the intricate relationship between age and cognitive function. However, our analysis faces challenges that reveal contradictory outcomes. To ensure the robustness and interpretability of our results, we deliberately decided to discontinue age grouping in our analysis. This choice was driven by the need to maintain clarity and consistency in our findings. Ultimately, we simply add age as a continuous variable to the covariate. Looking ahead, future investigations may delve into more nuanced age-specific effects or consider alternative strategies for a comprehensive understanding of the interplay between age and the potential cognitive benefits of tea consumption.
To the best of our understanding, the present study is the first to look at the interaction effects between PRS-evaluated genetic risk and tea consumption on CI in older adults, and the analysis was performed on a much larger sample, with longer follow-up periods and a larger number of follow-up assessments. In previous reviews, GWAS has been introduced in various aspects (55), among which an important understanding of the genetic loci identified by GWAS is that a single genetic locus has a weak effect on complex phenotypes/disease occurrence, that is, it reflects polygenic genetic characteristics. Therefore, integrating the effects of multiple genetic loci into a PRS can better represent the genetic background of the phenotype/disease.
We have tried to include interactive PRS * gender in the regression model. However, the results showed that there was no statistically significant difference in PRS between the gender (Table S3). Due to the above facts, we did not analyze the three-way interaction effect of «PRS * tea drinking * gender», but rather the interaction effect of PRS and tea drinking, thus ensuring a streamlined presentation of our key findings in the main text.
This study found that tea interacts with genetic risk, regardless of whether tea was consumed at present or around age 60. Table 5 and Figure 1 show that a higher PRS value correlates with a higher odds ratio, which indicates a higher prevalence of CI in older adults. However, the tea-consumption behavior has significant interaction effects with PRS on CI. Specifically, the association between PRS and CI will be stronger for those who drink tea at least sometimes compared with those who rarely/never drink tea. That is to say, frequently drinking tea may significantly reduce CI risk in older adults who have relatively low PRS values, but in those with high values of PRS, tea consumption may not have an effect.
The present study has several limitations. First, the classification of tea is simply divided into green tea and non-green tea, and further studies on the correlation between other types of tea and cognitive function are needed. Second, when analyzing the interaction between tea consumption and PRS on cognitive function, we classified tea consumption as a binary variable (yes or no), without considering the frequency or type. Therefore, we must interpret our results cautiously, treat them as exploratory findings, and look forward to further replication studies.

Directions for Future Research

As reviewed, in this large-scale longitudinal study spanning nearly 20 years, our research supports the finding that tea consumption can be recommended as an important and simple measure to prevent CI.
In future research, we can conduct more long-term follow-up studies to delve deeper into the dynamic relationships between tea consumption, genetics, and cognitive function, particularly among older adults. Biomarkers can be determined to explore potential biological mechanisms between tea consumption and genes and cognitive function. Further study of other lifestyle factors that interact with tea consumption, such as diet, physical exercise, etc., to fully understand the impact of these factors on cognitive health. Additionally, we recognize the potential value of neuroimaging in understanding cognitive changes, our work based on data from Singapore did reveal differences in brain imaging between regular tea drinkers and non-drinkers(56), and future investigations will explore its application in elucidating the neural underpinnings of the observed effects. These future research directions aim to expand our understanding of the relationships between tea consumption, genetics, and cognitive function, paving the way for more informed strategies in cognitive health management.

 

Funding: This work is supported by the Natural Science Foundation of Shandong Province, grant number ZR2021MC103, and the Humanities and Social Science Research Project, Ministry of Education, China, grant number 19YJA190006. Collections of the Chinese Longitudinal Healthy Longevity Surveys (CLHLS) datasets analyzed in this paper were jointly supported by the National Key R&D Program of China, grant number 2018YFC2000400, National Natural Sciences Foundation of China, grant number 72061137004, and the US. National Institute of Aging/National Institute of Health, grant number P01AG031719.

Author contributions: Conceptualization, LY, YW, YZ; methodology, YW, HC, LF, and LS; formal analysis, HC, KXY, QF, and JW; investigation, HC; data curation, LY, MX, JW, XY, and QF; writing—original draft preparation, L.Y., Y.W. and M.Y., M.X.; writing—review and editing, K.X.Y., J.W., X.Y., C.L., LY, DZ, QF, ABM, CS, LS, and LF; Supervision, LF and YW; project administration, HC, YZ and YW; funding acquisition, HC, YZ and YW. All authors have read and agreed to the published version of the manuscript.

Informed Consent Statement: Informed consent was obtained from all subjects involved in the study.

Conflicts of interest: The authors have no relevant financial or non-financial competing interests to declare with this manuscript.

Ethics, consent, and permission: The Peking University Institutional Review Board (IRB00001052-13074) has approved the study protocol of the current study.

 

SUPPLEMENTARY MATERIAL

 

References

 

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