Cross-sectional analysis of potential risk factors of the pineal gland calcification

The pineal gland as the main part of the epithalamus, is known to secrete melatonin as the direct regulator of [1] circadian rhythms in humans [2]. In addition, melatonin has been reported to be involved in neuroprotection against oxidative stress, inflammation, amyloid effects, and apoptosis [3, 4] and its dysregulation has been implicated in several neurodegenerative disorders [3, 5, 6], and stroke [7, 8]. The Pineal gland has a high rate of calcification in the human body forming deposits of magnesium and calcium around corpora arenacea [9]. There have been reports which suggested that the level of melatonin secretion is not affected by pineal calcification and consider this phenomenon as a physiologic process and not associated with aging and disease [10, 11]. On the other hand, some studies have suggested that the pineal gland calcification (PGC) is an age-related pathological process, and the level of 6-sulfatoxymelatonin, the main metabolic form of melatonin, is directly dependent on the size of uncalcified pineal tissue [12, 13].

The chemistry of PGC and the factors which predict the level of pineal calcification are poorly understood and require further studies to determine the main contributing demographic and pathologic factors in PGC induction. There are reports that suggest reduced melatonin levels in smoking and opioid using individuals [14‐18]. But studies which investigated smoking and opioid use in relation to the pineal gland calcification are lacking.

Here, we conducted a cross-sectional study on a population of patients referred to Ali Ebne Abi Taleb radiology center in years 2017–2018, assessing the association of PGC and PGC score with the demographic, lifestyle (smoking and opioid use) and history of metabolic and cerebrovascular diseases. To the best of our knowledge this is the first report assessing smoking and opioid use in relation to the pineal gland calcification.

Table 1 depicts the basic characteristics of the population study. 691 patients were assessed by reading brain CT and medical records. 586 patients were entered in to our analyses after exclusion of patients with low quality CT-scan, pineal tumors or pineal trauma and individuals with incomplete medical records. 84.47% of patients were positive for PGC, and the highest percentage of subjects (28.50%) were calculated a PGC-score of 2 in a scale from 0 to 6. The mean age of PGC (58.90 ± 22.27) and non-PGC cases (55.63 ± 23.28) did not differ significantly (p-value = 0.209). The chi² test, displayed a significant association between male sex and PGC (p-value < 0.001). Additionally, cigarette smoking and regular opioid use displayed a significant association with PGC (respective p-value:0.001, 0.023).

According to the logistic and ordered logistic regression analysis, significant factors related to PGC by univariate logistic regression were found to be male sex, cigarette smoking and regular opioid use. Male sex was associated with more than twice higher odds of PGC (OR: 2.35 (95% CI: 1.49–3.70), p-value < 0.001), smoking cigarettes was associated with more than 6 times higher odds ratio of PGC (OR: 6.80 (95% CI: 1.63- 28.40), p-value < 0.01), and opioid use was associated with 121% higher odds ratio of PGC (OR: 2.21 (95% CI: 1.10–4.46), p-value: 0.02). We next performed multivariate logistic analysis adjusting for factors which displayed an association p-value lower than 0.2 in the unadjusted model. Adjusting for sex, cigarette smoking, and opioid use, we found male sex and smoking cigarettes as the significant risk factors for PGC (male sex adjusted OR: 2.30 (95% CI: 1.39–3.82), p-value = 0.001; Cigarette smoking adjusted OR: 4.47 (95% CI: 1.01–19.78), p-value = 0.048). We did not find a significant association between opioid use and PGC in the adjusted logistic model (see Table 2).

We next used sensitivity analysis by sex-stratification to investigate gender-specific associations of PGC with different factors. In men an odds ratio of 7.44 (95% CI: 0.99–55.985), p-value = 0.051) was observed for PGC in association with cigarette smoking. In female subjects age displayed a significant association with PGC (OR: 1.02 (95% CI: 1.00–1.036), p-value = 0.012).

Performing ordered logistic regression analysis on the potential risk factors for the categorized PGC-score (cPGC_score), in the unadjusted model, male sex and cigarette smoking displayed a statistically significant association with cPGC_score (respective p-value: < 0.001, 0.01). In the multivariate ordered logistic test, male sex showed a significant association with cPGC_score (adjusted OR: 1.72 (95% CI: 1.23–2.39), p-value: 0.001). In addition to adjusting for gender, we performed a sensitivity analysis by sex-stratification. In the unadjusted ordered logistic model in men cigarette smoking displayed a significant association with cPGC_score (p-value:0.23). Also, in the multivariate analysis in men only, cigarette smoking was found to be significantly associated with higher cPGC_score (adjusted OR: 1.76 (95% CI: 1.02–3.02), p-value: 0.039). Performing the same analysis in women, we did not find a statistically significant association between cigarette smoking and higher cPGC-score (adjusted OR: 0.88 (95% CI: 0.30–2.53), p-value: 0.814).

Figure 1 indicates the mean categorized PGC_scores for the 10 quantiles of the age. Based on this graph, until the 5^th decile of age (below 63 years old in our population), there was an increasing trend of PGC_score by age. Therefore, we added ordered logistic analysis stratified by age (below age 63 and above 63) for different potential risk factors (Table 2). Our results indicated that in patients aged < 63 years: age (adjusted OR: 1.03 (95% CI: 1.01–1.05), p-value < 0.001) and male sex (adjusted OR: 2.82 (95% CI: 1.72–4.62), p-value < 0.001) were the two main positive associated factors of higher PGC_score, and hyperlipidemia (adjusted OR: 0.33 (95% CI: 0.13–0.87), p-value = 0.025) was the main factor negatively associated with higher PGC_score. A dose–response linear trend was observed for the categorized PGC_score and age deciles below 63 (p-trend < 0.001) (Table 3). On the contrary, in the patients aged 63 and above, the only significant associated factor of PGC_score was found to be cigarette smoking (adjusted OR: 2.31(95% CI: 1.20–4.42), p-value = 0.011). Additionally, when performed separated analysis for men and women, we found that the association of cigarette smoking and PGC_score in patients aged 63 and above, is only significant in male objects (OR: 2.94 (95% CI: 1.40–6.18), p-value: 0.004). The gender differential results may be probably driven from residual confounding from gender or its interaction effects with smoking. Additionally, the reason may be the small number of smoking women compared to men (supplemental Table 1).

We performed a cross-sectional study to investigate the association of demographic and personal habits with the pineal gland calcification. We found that the male sex is one of the factors significantly associated with PGC. Future studies are required to investigate the underlying reason for this gender difference in risk of pineal calcification.

In addition to male sex, our adjusted logistic analysis suggests cigarette smoking as a potent factor associated with increased odds of PGC (OR: 4.47 (95% CI: 1.01–19.78), cPGC_score in men (OR: 1.76 (95% CI: 1.02–3.02)), and cPGC_score in patients >  = 63 years (OR: 2.31(95% CI: 1.20–4.42)). We did not find any association between opioid regular use and PGC in the adjusted regression analyses. To the best of our knowledge, no previous study has assessed the connection of smoking and opioid use with PGC which is a unique character and strength of the present study. There are previously published evidences that support a link between smoking and opioid use with decreased melatonin levels [14‐18]. Our results do not indicate opioid use effect on melatonin to occur through inducing PGC. Previous studies showing the effect of smoking on melatonin levels, have indicated changes in the pharmacokinetic parameters of melatonin such as a lowered C_max (serum maximum concentration) when exogenous melatonin was injected. This study showed a pharmacokinetic effect of smoking for removal of melatonin from the body as the underlying mechanism for this effect, and suggested an impact of smoking independent of the pineal gland activity [20]. Our results showed an association between smoking and the pineal gland calcification. We propose future studies to investigate whether the decreasing effect of smoking on melatonin levels may be mediated at least partially by increasing the pineal gland calcification.

Smoking has been shown by several previous studies to be a risk factor for vascular calcification in different tissues [21‐24]. The suggested underlying mechanisms are the smoking-induced oxidative stress and alterations in the vesicular trafficking in the vascular smooth muscle cells [20]. Future studies are required to ask whether smoking may induce pineal gland calcification via similar mechanisms.

There has been variation in the results of the former reports assessing whether the pineal gland calcification is a function of age or not. Some previous studies support a direct association between aging and PGC in all ages in human and animal studies [25, 26], proposing PGC is an inevitable process of aging; while some other studies found that the increase in PGC by age is observed only by certain age (60 years old), and above this age the correlation disappears or is reversed [27]). Our results conform to the later, showing an age-dependent increase in PGC_score only in patients aged below 63. In younger individuals, previous studies have shown that PGC is not observed before age 5, but shows an age-dependent increase from age older than 5 to 20 years old [28, 29]. Here, we have assessed PGC in patients above 15 years old, and we observed a significant association between PGC and age only in patients younger than 63 years old.

Given that the gold standard method in diagnosing the pineal gland calcifications (PGC) can only be achieved by postmortem investigation of the pineal gland, we propose future anatomo-histological studies on postmortem biopsy samples to assess the association of smoking and PGC. Previous post mortem pineal gland studies found pineal calcification at the highest rate in the age group of 46–65 years old, but no differences between genders were observed [30‐32].

Some previous studies have suggested calcification as a commonly dominant feature of cystic pineal glands [33‐39]. Future studies are required to assess whether there is a relationship between the risk of pineal gland calcification and cysts.

One limitation of our study is the lack of information on some of the potential risk factors of the pineal gland calcification, such as the body mass index, alcohol consumption, diet, physical activity and sunlight exposure. However, a complete medical history record for each of patients was available providing valuable information on the current diseases of the patients including diabetes mellitus, hyperlipidemia, hypertension and cerebrovascular diseases. The other limitation of the present study is the lack of information on the start age of the above-mentioned diseases or duration of smoking and opioid addiction or the dosage of their use.

In conclusion, we found that until age 63, age and male sex are the two potential associated risk factors for pineal gland calcification, and above this age smoking cigarettes may be a risk factor for PGC, which warrants further investigation in the future.