Periodontitis and risk of alopecia areata: A nationwide population-based cohort study in Korea

Identifying immuno-related diagnostic genes and immune infiltration signatures for periodontitis and alopecia areata

BACKGROUND

Although there have been indications that periodontitis (PD) may be susceptible to alopecia areata (AA), the underlying mechanism of its pathogenesis remains poorly understood. The objective of our study is to conduct further research into the occurrence of this complication.

METHODS

The gene expression omnibus (GEO) database was the source of acquisition for both PD and AA datasets. Various methods, including the differentially expressed genes (DEGs) analysis, functional enrichment analysis, protein-protein interaction (PPI) network construction, Cytohubba algorithms, and RandomForest algorithms, were utilized to identify candidate hub immuno-related genes (IRGs) for diagnosing AA with PD. The diagnostic efficacy was assessed by constructing receiver operating characteristic (ROC) curves. To further deepen our understanding, immune cell infiltration, flow cytometry assay, and immunofluorescence techniques were employed to uncover immune cell dysregulation in PD and AA.

RESULTS

899 and 803 DEGs were detected in AA and PD, respectively, with an intersection of 150 common DEGs enriched in immune regulation. Further analysis of the junction of shared DEGs and IRGs was analyzed using the PPI network, Mcode, and Cytohubba algorithms. Three hub genes (CTSS, IL2RG, and ITGAL) were subsequently selected by Cytohubba and RandomForest algorithms and were found to be promising candidate hub genes with high diagnostic values (AUC ranging from 0.776 to 0.909) for diagnosing AA with PD. Additionally, various dysregulated immune cells were observed, with mast cells potentially serving as markers for AA and plasma for PD.

CONCLUSION

Three candidate hub IRGs (CTSS, IL2RG, and ITGAL) were identified with considerable diagnostic values. Besides, mast cells could serve as markers for AA, while plasma may indicate PD. Our research has the potential to identify shared diagnostic candidate genes and immune cells for AA and PD patients.

Association between androgenetic alopecia and periodontitis

AIM

Androgenic alopecia (AGA) is men's most common form of hair loss. It is affected by changes in the expression and activity of 5αR and the metabolism of testosterone and DHT. There is an association between AGA and systemic inflammatory diseases. We hypothesized that there is an association between AGA and periodontal disease, as inflamed gingiva and periodontal fibroblasts have been shown to express more 5αR. Thus, this study aimed to evaluate the relationship between periodontal disease and AGA and the potential effect of aging on this association.

MATERIALS AND METHODS

Out of a cohort of 1088 individuals, 385 white males aged 25-65 with similar socioeconomic levels and without systemic disease were included. Periodontitis was defined using NHANES data. AGA was evaluated using the Norwood-Hamilton scale. The relationship between AGA, periodontal disease severity, and age was assessed.

RESULTS

There was a correlation between age and baldness (r = .421, p < .001). There was a significant correlation between AGA and periodontal disease in younger patients aged 25-34 and 35-44. (p < .042 and p < .036, respectively). There was no significant correlation between AGA and periodontal disease in the 45-54 and 55-65 age groups (p > .05).

CONCLUSION

There may be a relationship between periodontal disease and AGA in the 25-44 age range, suggesting that this association starts at an early age in adulthood.

Bidirectional association between Parkinson's disease and obstructive sleep apnea: a cohort study

STUDY OBJECTIVES

Chronic intermittent hypoxia due to obstructive sleep apnea (OSA) causes oxidative stress, which may contribute to the pathophysiology of Parkinson's disease (PD). However, the bidirectional relationship between PD and OSA has not been satisfactorily established. The objective of this study was to try to estimate whether there is a bidirectional relationship between PD and OSA through a retrospective cohort study in the South Korean population.

METHODS

This study used data from the Korean National Health Information Database of the National Health Insurance Service, which contains data from 3.5 million individuals evenly distributed. In study 1, patients with OSA were matched in a 1:2 ratio with non-OSA controls. In study 2, patients with PD were matched in a 1:2 ratio with non-PD controls. A stratified Cox proportional hazards model was used to calculate hazard ratios.

RESULTS

In study 1, which included 6,396 patients with OSA and 12,792 non-OSA controls, the incidence of PD per 10,000 person-years was 11.59 in the OSA group and 8.46 in the non-OSA group. The OSA group demonstrated a 1.54-fold higher incidence of PD than the non-OSA group (95% confidence interval, 1.14-2.07; P < .05). In study 2, which included 3,427 patients with PD and 6,854 non-PD controls, the incidence of OSA per 10,000 person-years was 14.97 in the PD group and 7.72 in the non-PD group. The PD group demonstrated a 1.92-fold higher incidence of OSA than the non-PD group (95% confidence interval, 1.32-2.78; P < .05).

CONCLUSIONS

This study supports a possible bidirectional relationship between PD and OSA.

CITATION

Jeon S-H, Hwang YS, Oh S-Y, et al. Bidirectional association between Parkinson's disease and obstructive sleep apnea: a cohort study. J Clin Sleep Med. 2023;19(9):1615-1623.

Analysis of Cause-of-Death Mortality in Children and Young Adults with Diabetes: A Nationwide 10-Year Follow-Up Cohort Study

We examined the associations of clinical characteristics and cause-of-death patterns with mortality in children and young adults (<30 years) with diabetes. We analyzed a nationwide cohort sample from the KNHIS database using propensity score matching from a sample of 1 million people from 2002 to 2013. There were 10,006 individuals in the diabetes mellitus (DM) group and 10,006 in the control (no DM) group. The numbers of deaths were 77 in the DM group and 20 in the control group. The deaths of patients in the DM Group were 3.74 (95% confidence interval (CI) = 2.25-6.21) times higher than in the control group. Type 1 DM, type 2 DM and unspecified DM were 4.52 (95% CI = 1.89-10.82) times, 3.25 (95% CI = 1.95-5.43) times and 10.20 (95% CI = 5.24-20.18) times higher, respectively. Mental disorders were 2.08 times higher in the risk of death (95% CI = 1.27-3.40). Mortality rates have increased in children and young adults with diabetes alone. Therefore, in the future, it is necessary to identify the cause of the increased mortality rate among young diabetic people and select vulnerable groups among them so that early prevention can be achieved.

Long-term bidirectional association between asthma and attention deficit hyperactivity disorder: A big data cohort study

BACKGROUND

Previous studies have argued that attention deficit hyperactivity disorder (ADHD) is associated with asthma. However, reliable evidence to verify this association has not yet been reported.

OBJECTIVES

To investigate the bidirectional association between asthma and ADHD through a 12-year big data cohort study.

METHODS

The independent variable group was extracted from 3.5 million individuals randomly sampled by the National Health Insurance Service (NHIS). In Study 1, the incidence of ADHD according to asthma was evaluated, while in Study 2, the incidence of asthma according to ADHD was analyzed. Propensity score (PS) matching with several variables was used to obtain a control group.

MEASUREMENTS AND MAIN RESULTS

In Study 1, the asthma group included 131,937 individuals and the non-asthma group included 131,937 individuals. The adjusted hazard ratio (aHR) for ADHD in the asthma group was 1.17 [95% confidence interval (CI): 1.11-1.23]. In subgroup analysis, the aHRs for ADHD of individuals in the subgroups male sex, 0-5 years old, 6-10 years old, atopic dermatitis, allergic rhinitis, Charlson comorbidity index (CCI) 1, and CCI > 2 were significant (aHR: 2.83, 1.70, 1.79, 1.09, 1.15, 1.06, and 1.49, respectively). In Study 2, ADHD was found to significantly affect asthma in all age groups (aHRs of the subgroups 0∼60 and 0∼17 years old were 1.10 and 1.09, respectively). In the 0∼17 years old subgroup, the association of ADHD with asthma was greater with younger age (aHRs of the subgroups 0∼5 and 6∼10 years old were 2.53 and 1.54, respectively).

CONCLUSION

From long-term follow-up, the incidence of ADHD was 1.17 times higher in the asthma group than in the control group. The incidence of asthma was 1.10 times higher in the ADHD group than in the control group. Asthma and ADHD have a bidirectional relationship, and childhood asthma and ADHD should be rigorously managed.