Abstract
Background
The development of osteoporosis is partly explained by interactions between genetic and lifestyle or environmental factors.
Objectives
In the current study, we determined the relationship between coffee consumption and the risk of osteoporosis among individuals with ESR1 rs2982573 in Taiwan.
Design, Participants and Setting
In this population-based cross-sectional study, we used genetic, demographic, and lifestyle data from participants recruited in Taiwan Biobank (TWB) between 2016 and 2019. We used multiple logistic regression analyses to determine the relationship between osteoporosis and variant rs2982573 genotypes (TT, TC, and CC).
Main Outcome
The primary outcome was osteoporosis.
Results
Individuals with osteoporosis (n = 515) were older than those without the disease (mean age ±SE (year); 61.324±0.361 versus 53.068 ±0.130, p<0.001). There was no significant association between rs2982573 and osteoporosis (OR, 0.904; 95% CI, 0.706–1.157; p=0.422 for TC+CC when compared with the TT genotype). Coffee consumption was associated with a lower risk of osteoporosis (OR, 0.737; 95% CI, 0.592–0.918; p=0.006). The p-value for interaction between rs2982573 and coffee consumption was 0.0393. In our subgroup analyses, the adjusted ORs (95% CI) were 0.635 (0.410–0.985) in coffee drinking TC+CC individuals and 1.095 (0.809–1.482) in non-coffee drinking TC+CC individuals, respectively when compared with their TT genotype counterparts.
Conclusion
According to our study, participants in the TWB with the TC+CC genotype of ESR1 rs2982573 who consumed at least three cups of coffee per week were less likely to have osteoporosis.
Key words: Osteoporosis, bone mineral density, coffee drinking, polymorphism, bone
Introduction
Osteoporosis is a systemic skeletal disorder characterized by low bone mass that causes fragile bones, which are susceptible to fracture (1). So far over 200 million people are affected by osteoporosis worldwide (2). According to the National Nutrition and Health Survey in Taiwan (NAHSIT), 23.9% of men and 38.3% of women over 50 were diagnosed with osteoporosis between 2005 and 2008 (3). A number of risk factors for osteoporosis (including, but not limited to, rheumatoid arthritis, diabetes, and smoking) are involved in pathways that lead to bone formation and osteoporotic fractures (4).
According to Pouresmaeili and colleagues (4), genes should be considered as fundamental biomarkers for early diagnosis of osteoporosis even though the genetics of this disorder poses considerable challenges. As far as we know, several genes have shown associations with osteoporosis. The mechanisms contributing to complex and common disorders such as osteoporosis have been explained by interactions between genetic, lifestyle, and environmental factors.
Estrogen plays an important role in the regulation of bone metabolism (5). It exhibits this function through binding to specific receptors, whose signaling mediates the buildup of bone mass (6, 7, 8). It is believed that estrogen deficiency promotes bone loss, especially in postmenopausal women. Coffee, a commonly consumed beverage in the world has also been linked to bone health both positively and negatively. (9, 10) Research findings on the association between coffee and osteoporosis are conflicting and therefore cannot be considered conclusive (11, 12, 13, 14, 15, 16, 17, 18).
Clinical risk factors such as inadequate sun exposure, sedentary lifestyle, and low calcium intake (19) as well as environmental factors such pollutants and heavy metals (20) cannot adequately predict osteoporosis vulnerability (21). Genetic factors contribute substantially to the pathogenesis of the disease (22). However, they have not been considered in the majority of epidemiological studies despite their role in osteoporosis (23, 24, 25, 26). Consequently, most genetic determinants of osteoporosis are unknown (27). ESR1 (ERα), which encodes estrogen receptor 1, is a key receptor that mediates the bone-related function of estrogen (7, 28). It is also a candidate gene associated with osteoporosis risk (6, 28). The UK Biobank data revealed that rs2982573 (located 1 kb upstream of ESR1) is one of the variants that are strongly associated with bone mineral density (BMD), which is a proxy for osteoporosis (29).
Research also indicates that coffee may be a risk factor for osteoporosis among postmenopausal women with low estrogen (30). The bioactive compounds found in it are believed to alter estrogen levels (31, 32). Earlier, we mentioned the link between coffee consumption, estrogen changes, and osteoporosis. Studies targeting these variables, however, have examined only a few genetic variants. More research is needed on the role that clinical, genetic, and environmental factors play in osteoporosis (21, 27). Currently, there is no research examining the association between coffee, ESR1 polymorphism, and osteoporosis. Therefore, we investigated the interactive effect of coffee consumption and the genetic variant, ESR1 rs2982573, on osteoporosis risk.
Methods
Study Population
We obtained data from 12,139 participants enrolled in TWB between 2016 and 2019. These individuals were cancer-free. Biobank individuals who had undergone dual-energy X-ray absorptiometry (DXA) scan and whose T-scores were between -1 to -2.5. Also excluded were those with missing data (n = 3). The final analyses included data from 6676 participants. This study was conducted according to the guidelines laid down in the Declaration of Helsinki and all procedures involving research study participants were approved the institutional review board at Chung Shan Medical University. All the Biobank participants had provided written informed consent during enrollment.
Genotyping
As stated earlier, the ESR1 rs2982573 is an osteoporosis-associated variant. This was the motivating factor behind this replication study. All subjects in TWB had provided blood samples for DNA extraction. Genotyping was performed at Academia Sinica using the custom genotyping arrays developed through the ThermoFisher Axiom platform as previously described (33, 34). Imputations were carried out using IMPUTE2 (v2.3.1) and SHAPEIT (v2.r790). For postimputation quality control, the rs2982573 variant had 1) an information score greater than 0.3, 2) minor allele frequencies (MAF) greater than 0.01%, and 3) a missing rate <5%.
Outcome, exposures, and definitions
BMD was measured at the Mackay Memorial Hospital using the Discovery™ QDR™ Bone Densitometry Systems (HOLOGIC) machine. A BMD T-score of -2.5 or less in the hip defined osteoporosis. We obtained information on coffee drinking from the TWB questionnaires. Participants were asked if they drank coffee and the frequency (number of times) per week. Those who responded “Yes” to drinking coffee and at least three times per week were considered coffee drinkers. Each cup had a capacity of around 130cc to 500cc. Coffee consumers were asked about the type of coffee they drank: Their responses included “plain black coffee,” “coffee with creamer,” and “coffee with milk.” Exposure variables included age, sex, exercise, tea consumption, vegetarian diet, smoking, alcohol consumption, and body mass index (BMI).
Statistical analysis
We used SAS software (version 9.4; SAS Institute, Cary, NC, USA) and Plink 1.9 to analyze data. Descriptive data were presented as mean±SE (for continuous variables) and numbers (n) and percentages (for categorical variables). We used the chi-square test to compare the differences among categorical variables and the t-test for continuous variables. We estimated the ORs and 95% CI for osteoporosis among study participants using multiple logistic regression analyses.
Results
The clinical and demographic characteristics of the study subjects are shown in Table 1. The study population included 515 osteoporosis (women, 458 and men, 57), and 6161 osteoporosis-free individuals. Those with osteoporosis were older than those without the disease (mean age ±SE (year); 61.324+0.361 versus 53.068 ±0.130, p<0.001). The association of osteoporosis with exposure variables is shown in Table 2. There was no association between variant rs2982573 and osteoporosis (OR, 0.904; 95% CI, 0.706–1.157; p=0.422 for TC+CC when compared with the TT genotype). Coffee consumption was associated with lower odds of osteoporosis when compared with the no coffee drinking group (OR, 0.737; 95% CI, 0.592–0.918; p=0.006). The ORs for osteoporosis in women and men who drank coffee were 0.764 (95% CI, 0.603–0.968; p=0.026) and 0.630 (95% CI, 0.333–1.192; p=0.115), respectively. Menopause was linked to an increased risk of osteoporosis (OR, 3.454; 95% CI, 2.151–5.545). When compared with normal weight, the OR (95% CI) was 7.888 (4.959–12.546) for underweight, 0.154 (0.113–0.210) for overweight, and 0.060 (0.037–0.096), respectively (p<0.001). Other factors significantly associated with osteoporosis included male sex (OR, 0.125; 95% CI, 0.086 – 0.180; p<0.001), age (OR, 1.138; 95% CI, 1.122–1.154; p<0.001), exercise (OR, 0.641; 95% CI, 0.513–0.800; p<0.001), and vegetarian diet (OR, 1.575; 95% CI, 1.130–2.194; p = 0.007). The p-value for interaction between rs2982573 and coffee consumption was 0.0393. After sub-group analyses (Table 3), we observed that adjusted ORs (95% CI) were 0.635 (0.410–0.985) for TC+CC and coffee consumption and 1.095 (0.809–1.482) for TC+CC and no coffee consumption, respectively, compared to the TT genotype. In a separate model with TT/no coffee consumption as the reference group (Table 4), the adjusted ORs (95% CI) were 0.837 (0.653–1.073; p=0.160) for TT/coffee consumption, 1.099 (0.811–1.490; p=0.542) for TC+CC/no coffee consumption, and 0.528 (0.348–0.800; p=0.003) for TC+CC/coffee drinking, respectively.
Table 1.
Characteristics of individuals that participated in Taiwan Biobank
| Variables | No osteoporosis (N = 6161) | Osteoporosis (N = 515) | p-value | Women (N = 3878) | Men (N = 2798) | p-value |
|---|---|---|---|---|---|---|
| Osteoporosis | - | <0.001 | ||||
| No | - | - | 3420 (88.19) | 2741 (97.96) | ||
| Yes | - | - | 458 (11.81) | 57 (2.04) | ||
| rs2982573 n, % | 0.192 | 0.574 | ||||
| TT | 4552 (73.88) | 394 (76.50) | 2883 (74.34) | 2063 (73.73) | ||
| TC+CC | 1609 (26.12) | 121 (23.50) | 995 (25.66) | 735 (26.27) | ||
| Coffee drinking n, % | <0.001 | 0.492 | ||||
| No | 3326 (53.98) | 337 (65.44) | 2114 (54.51) | 1549 (55.36) | ||
| Yes | 2835 (46.02) | 178 (34.56) | 1764 (45.49) | 1249 (44.64) | ||
| Sex n, % | <0.001 | - | ||||
| Women | 3420 (55.51) | 458 (88.93) | - | - | ||
| Men | 2741 (44.49) | 57 (11.07) | - | - | ||
| Age (mean±SE), years | 53.068±0.130 | 61.324±0.361 | <0.001 | 53.114 ± 0.157 | 54.523 ± 0.205 | <0.001 |
| Exercise n, % | 0.001 | <0.001 | ||||
| No | 3293 (53.45) | 234 (45.44) | 2163 (55.78) | 1364 (48.75) | ||
| Yes | 2868 (46.55) | 281 (54.56) | 1715 (44.22) | 1434 (51.25) | ||
| Smoking n, % | <0.001 | <0.001 | ||||
| No | 4729 (76.76) | 474 (92.04) | 3714 (95.77) | 1489 (53.22) | ||
| Yes | 1432 (23.24) | 41 (7.96) | 164 (4.23) | 1309 (46.78) | ||
| Alcohol drinking n, % | <0.001 | <0.001 | ||||
| No | 5334 (86.58) | 493 (95.73) | 3745 (96.57) | 2082 (74.41) | ||
| Yes | 827 (13.42) | 22 (4.27) | 133 (3.43) | 716 (25.59) | ||
| BMI categories (kg/m2) n, % | <0.001 | <0.001 | ||||
| Normal-weight (≥18.5 to <24) | 2196 (35.64) | 383 (74.37) | 1850 (47.71) | 729 (26.05) | ||
| Underweight (<18.5) | 60 (0.97) | 60 (11.65) | 98 (2.53) | 22 (0.79) | ||
| Overweight (≥24 to <27) | 2051 (33.29) | 53 (10.29) | 1015 (26.17) | 1089 (38.92) | ||
| Obesity (≥27) | 1854 (30.09) | 19 (3.69) | 915 (23.59) | 958 (34.24) | ||
| Tea intake n, % | <0.001 | <0.001 | ||||
| No | 4576 (74.27) | 440 (85.44) | 3122 (80.51) | 1894 (67.69) | ||
| Yes | 1585 (25.73) | 75 (14.56) | 756 (19.49) | 904 (32.31) | ||
| Vegetarian diet n, % | <0.001 | <0.001 | ||||
| No | 5681 (92.21) | 448 (86.99) | 3520 (90.77) | 2609 (93.25) | ||
| Yes | 480 (7.79) | 67 (13.01) | 358 (9.23) | 189 (6.75) | ||
| Menopause n, % | ||||||
| No | - | - | 1679 (43.30) | - | - | |
| Yes | - | - | 2199 (56.70) | - | - | |
Abbreviations: BMI, body mass index; SE, standard error; Note: TT, TC+CC are the genotypes of rs2982573
Table 2.
Relationship between the variables and osteoporosis among study subjects
| Variables | Model 1 (N = 6676) | Model 2 (N = 3878) | Model 3 (N = 2798) | ||||||
|---|---|---|---|---|---|---|---|---|---|
| OR | 95 % CI | p-value | OR | 95 % CI | p-value | OR | 95 % CI | p-value | |
| rs2982573 | |||||||||
| TT | 1 | 1 | 1 | ||||||
| TC+CC | 0.904 | 0.706–1.157 | 0.422 | 0.821 | 0.625–1.077 | 0.155 | 1.507 | 0.802–2.830 | 0.203 |
| Coffee drinking | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 0.737 | 0.592–0.918 | 0.006 | 0.764 | 0.603–0.968 | 0.026 | 0.630 | 0.333–1.192 | 0.155 |
| Sex | |||||||||
| Women | 1 | 1 | 1 | ||||||
| Men | 0.125 | 0.086–0.180 | <0.001 | - | - | - | - | - | - |
| Age (years) | 1.138 | 1.122–1.154 | <0.001 | 1.149 | 1.131–1.167 | <0.001 | 1.070 | 1.036–1.106 | <0.001 |
| Exercise | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 0.641 | 0.513–0.800 | <0.001 | 0.697 | 0.548–0.886 | 0.003 | 0.405 | 0.216–0.759 | 0.005 |
| Smoking | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 1.444 | 0.932–2.239 | 0.100 | 1.891 | 0.996–3.593 | 0.052 | 1.037 | 0.547–1.965 | 0.911 |
| Alcohol drinking | |||||||||
| No | 1 | 1 | 1 | ||||||
| Yes | 0.807 | 0.483–1.349 | 0.413 | 0.605 | 0.272–1.347 | 0.219 | 1.103 | 0.527–2.308 | 0.795 |
| BMI categories | |||||||||
| Normal-weight | 1 | 1 | 1 | ||||||
| Underweight | 7.888 | 4.959–12.546 | <0.001 | 5.214 | 3.104–8.757 | <0.001 | 37.456 | 13.664–102.679 | <0.001 |
| Overweight | 0.154 | 0.113–0.210 | <0.001 | 0.170 | 0.122–0.235 | <0.001 | 0.057 | 0.017–0.186 | <0.001 |
| Obesity | 0.060 | 0.037–0.096 | <0.001 | 0.049 | 0.02–0.086 | <0.001 | 0.105 | 0.040–0.275 | <0.001 |
| Menopause | |||||||||
| No | - | - | - | 1 | - | - | - | ||
| Yes | - | - | - | 3.454 | 2.151–5.545 | <0.001 | - | - | - |
Adjusted for tea consumption and vegetarian diet; Abbreviations: OR, odds ratio; CI, 95% confidence interval; Model 1: Odds ratios for osteoporosis in study subjects; Model 2: Odds ratios for osteoporosis in women; Model 3: Odds ratios for osteoporosis in men
Table 3.
Association of osteoporosis with variant rs2982573 among coffee and non-coffee drinkers
| Variables | No coffee drinking | Coffee drinking | ||||
|---|---|---|---|---|---|---|
| OR | 95 % CI | p-value | OR | 95 % CI | p-value | |
| rs2982573 | ||||||
| TT | 1 | 1 | ||||
| TC+CC | 1.095 | 0.809–1.482 | 0.556 | 0.635 | 0.410–0.985 | 0.042 |
| Sex | ||||||
| Women | 1 | 1 | ||||
| Men | 0.135 | 0.086–0.211 | <0.001 | 0.105 | 0.055–0.200 | <0.001 |
| Age (years) | 1.132 | 1.113–1.152 | <0.001 | 1.149 | 1.123–1.176 | <0.001 |
Adjusted for exercise, smoking, drinking, BMI, tea consumption, and vegetarian diet; Abbreviations: OR, odds ratio; CI, 95% confidence interval
Table 4.
Logistic regression analysis showing the odds of osteoporosis among rs2982573 coffee and non-coffee drinkers
| Variables | OR | 95 % CI | p-value |
|---|---|---|---|
| TT/no coffee drinking | 1 | ||
| TT/coffee drinking | 0.837 | 0.653–1.073 | 0.160 |
| TC+CC/no coffee drinking | 1.099 | 0.811–1.490 | 0.542 |
| TC+CC/coffee drinking | 0.528 | 0.348–0.800 | 0.003 |
| Sex | |||
| Women | 1 | ||
| Men | 0.124 | 0.086–0.179 | <0.001 |
| Age (years) | 1.138 | 1.123–1.154 | <0.001 |
Adjusted for exercise, smoking, drinking, BMI, tea consumption, and vegetarian diet; Abbreviations: OR, odds ratio; CI, 95% confidence interval
Discussion
In our multivariate analysis, we found that coffee consumption (of at least 3 times a week) was associated with lower odds of developing osteoporosis. Surprisingly, we found that the association between the ESR1 rs2982573 variant and osteoporosis risk lacked statistical significance. On the contrary, this finding does not reflect those previously reported (6, 28, 35). However, we found that rs2982573 and coffee drinking had a significant interaction. Because of this, we further analyzed the data by subgroups. Interestingly, the results showed that coffee consumption and the TT+CC genotype of rs2982573 substantially reduced the odds of osteoporosis. This observation shows that either rs2982573 or coffee drinking would likely modify the association of the other with osteoporosis even though the underlying mechanisms are not clear enough.
Coffee is widely consumed in Taiwan. The prevalence of osteoporosis in the Island was 17.4% in 2001 and 25.0% in 2011 (3, 36). According to disease statistics in TWB, the prevalence of self-reported osteoporosis is 5.45% in female and 2.27% in male participants. Considering that the association between osteoporosis and coffee was substantial, we attempted to examine whether this association could be explained by coffee type (that is, plain black coffee, coffee with creamer, and coffee with milk). We found a significant association (data not shown) with black coffee drinking (OR, 0.379; 95% CI, 0.153–0.941) when compared with no coffee drinking. Polyphenols in coffee might potentially reduce the risk of osteoporosis by inhibiting osteoclastogenesis (37, 38). We also observed that the association of coffee with creamer and coffee with milk did not achieve statistical significance. In contrast, previous research has linked milk and coffee consumption to bone health in postmenopausal women (39). In our previous publication, coffee drinking was associated with osteoporosis in men and premenopausal women in Taiwan (38). Despite that, we could not determine whether the association differed by coffee type. Results from prior studies on the associations between osteoporosis or osteoporotic fractures and coffee consumption have been inconsistent (10, 40). Hence, large-scale studies would clarify these associations.
Other factors found to be significantly associated with lower odds of osteoporosis included male sex and exercise no matter the coffee drinking status or rs2982573 genotypes. In the current study, menopause remains a significant factor associated with osteoporosis in Taiwanese women. Previous studies have reported higher odds of the disease in women than men (41). This is due to menopause and estrogen decrease as mentioned earlier. However, according to De Martinis and colleagues, men are under-screened for osteoporosis (42). As expected, we found in a separate model (data not shown) that osteoporosis risk was higher in menopausal women (OR, 3.463; 95% CI, 2.157–5.560). The results of a systematic review highlighted that physical activity is necessary to improve bone health and prevent osteoporosis (43). When we used normal BMI as a reference group, we found that overweight and obesity were associated with lower odds of osteoporosis, while the disease risk was significantly higher in underweight individuals. These findings reflect those that have been previously reported (44, 45, 46). There is, however, increasing evidence that not only underweight individuals are at risk for osteoporosis, but also obese and sarcopenic individuals (47, 48).
Based on what we know, the rs2982573 polymorphism has not been replicated in Taiwan. Analyses of the UK Biobank data suggested that the variant was significantly correlated with bone mineral density (29). In Korea, this SNP has also been significantly associated with obesity-related traits among men (35). For the first time, we have shown that coffee consumption in combination with the TC/CC genotype of rs2982573 is protective against osteoporosis in Taiwan. The strength of the study is the large sample size. However, the study is not without limitations. First, because the study is cross-sectional, it may not provide conclusive information about cause-effect relationships. Next, the proportion of male participants with osteoporosis was relatively small. Therefore, larger sample sizes would clarify sex-based differences in the association of disease with coffee consumption and rs2982573 or other related polymorphisms. Finally, we lacked information about the preparation and brewing methods of coffee.
Conclusions
In summary, we found that drinking coffee (at least 3 times a week) and having the TC+CC genotype of ESR1 rs2982573 reduced osteoporosis risk among Taiwan Biobank participants. These results provide insight into genetic and lifestyle factors that contribute to osteoporosis in Taiwan and could be used as a reference for studies evaluating the disease and its associated variables.
Data Availability Statement: The data that support the findings of this study are available from Taiwan Biobank but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the correponding author upon reasonable request and with permission of Taiwan Biobank.
Contributions
Conceptualization, Chi-Ling Wu, Oswald Ndi Nfor, Wen-Yu Lu, Disline Manli Tantoh and Yung-Po Liaw; Data curation, Wen-Yu Lu; Formal analysis, Oswald Ndi Nfor, Wen-Yu Lu and Yung-Po Liaw; Methodology, Chi-Ling Wu, Oswald Ndi Nfor, Disline Manli Tantoh and Yung-Po Liaw; Supervision, Yung-Po Liaw; Writing — original draft, Chi-Ling Wu; Writing — review & editing, Oswald Ndi Nfor, Wen-Yu Lu, Disline Manli Tantoh and Yung-Po Liaw.
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