Association between Congestive Heart Failure and Ossification of the Posterior Longitudinal Ligament in Korea: A Nationwide Longitudinal Cohort Study

Article information

Nerve. 2024;10(1):19-24
Publication date (electronic) : 2024 April 9
doi : https://doi.org/10.21129/nerve.2023.00493
1Department of Neurosurgery, CHA Bundang Medical Center, CHA University College of Medicine, Seongnam, Republic of Korea
2Genome & Health Big Data Branch, Department of Public Health, Graduate School of Public Health, Seoul National University, Seoul, Republic of Korea
3Department of Neurosurgery, Sungkyunkwan University, Kangbuk Samsung Hospital, Seoul, Republic of Korea
4Department of Neurosurgery, Chungbuk National University College of Medicine, Chungbuk National University Hospital, Cheongju, Republic of Korea
Corresponding author: Seil Sohn Department of Neurosurgery, CHA Bundang Medical Center, CHA University College of Medicine, 59, Yatap-ro, Bundang-gu, Seongnam 13496, Republic of Korea Tel: +82-31-881-7966 Fax: +82-2-780-5269 E-mail: sisohn@cha.ac.kr
Received 2023 November 14; Revised 2023 November 27; Accepted 2023 December 4.

Abstract

Objective

The objective of this nationwide, long-term follow-up study was to explore the connection between congestive heart failure (CHF) and ossification of the posterior longitudinal ligament (OPLL) in Korea.

Methods

Patient information was collected from the Health Screening cohort of the National Health Insurance Service. Individuals diagnosed with OPLL were identified using specific International Classification of Diseases, 10th revision codes (M48.8, M48.81, M48.82, and M48.83). A total of 1,289 OPLL patients and 6,445 controls were included in the study, selected through 1:5 age and sex matching. The data spanned from January 1, 2004 to July 31, 2015. To compute the incidence rate of CHF in each group, the Kaplan-Meier method was employed. Additionally, Cox proportional-hazards regression analysis was utilized to estimate the hazard ratio of CHF.

Results

CHF was present in 19 patients (1.47%) in the OPLL group and 71 patients (1.10%) in the control group. After accounting for age and sex, the hazard ratio for CHF in the OPLL group was 3.164 (95% confidence interval [CI], 1.867-5.360). When additionally considering income and underlying diseases, the hazard ratio for CHF within the OPLL group was 3.355 (95% CI, 1.977-5.694). All subgroups of OPLL patients exhibited an increased risk ratio for CHF across parameters such as sex, age, diabetes, hypertension, and dyslipidemia.

Conclusion

According to this nationwide longitudinal study, an elevated incidence rate of CHF was associated with OPLL.

INTRODUCTION

Ossification of the posterior longitudinal ligament (OPLL) is a multifactorial condition characterized by abnormal bone formation, which results in the replacement of spinal ligamentous tissue13,15,16,18,20). The precise cause and mechanism of OPLL remain unestablished. The posterior longitudinal ligament (PLL) extends along the dorsal surface of the vertebral canal, spanning from the axis to the sacrum, where it functions to resist excessive spinal hyperflexion. Typically composed of well-aligned fibroblasts and lacking cartilage components, the PLL can undergo pathological ossification known as OPLL. In cases of OPLL, fibroblast-like cells transform into chondrocytes and osteoblasts, accompanied by an augmented vascularity attributed to the overexpression of bone morphogenetic protein (BMP). Consequently, this process leads to the replacement of the native ligament's fibrous structure with cartilaginous tissue, as well as the emergence of regions characterized by degeneration and ossification7,17,21). As OPLL develops, it leads to a narrowing of the spinal canal, thereby causing harm to the spinal cord6,19). Consequently, patients exhibit clinical manifestations of myelopathy, which significantly compromises their quality of life7,8).

To date, there has been a dearth of investigations exploring the direct link between congestive heart failure (CHF) and OPLL. Nevertheless, CHF has established associations with factors such as infection and atherosclerosis. In pursuit of advancing our understanding, our nationwide longitudinal study endeavors to illuminate the potential relationship between CHF and OPLL.

MATERIALS AND METHODS

1. Data Source

Within South Korea, there exists a form of universal health insurance encompassing vital medical expenses for all residents under a unified public framework known as the National Health Insurance Service (NHIS). The NHIS administers comprehensive health assessments annually or biennially for individuals above the age of 40 who are either full-time or temporary workers. Additionally, the NHIS compiles individual data, incorporating demographic attributes and medical examinations, within the National Health Information Database (NHID). For our study, we have duly secured the authorization to access NHID health examination data spanning from 2004 to 2015 through the assistance of the Institutional Review Board (approval no. 2020-01-011) at the Bundang Medical Center, CHA University11).

2. Establishment of the Study Cohort

A comprehensive national health examination was undergone by a total of 514,557 individuals, with their progress being closely monitored over a 12-year span until December 31, 2015. Individuals identified by the International Classification of Diseases, 10th Revision codes 'M48.8, M48.80, M48.81, M48.82, M48.83' were categorized as patients with OPLL (n=3,405). Among this group, 1,977 subjects were excluded due to the absence of computed tomography data. Within the remaining 1,428 subjects, individuals newly diagnosed with OPLL after January 1, 2003 were selected as the primary cohorts for our investigation, resulting in a total of 1,289 participants. Utilizing the 'Match IT' R package algorithm, a control group consisting of 6,445 subjects was meticulously chosen through a 1:5 age- and sex-stratified matching methodology (Fig. 1).

Fig. 1.

Flow diagram of the cohort formation process. The National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) was used in this 12-year longitudinal cohort study. NIHSS: the National Institutes of Health Strock Scale; OPLL: ossification of the posterior longitudinal ligament; ICD-10: International Classification of Diseases, Tenth Revision; CT: computed tomography.

Throughout the duration of the study, the participants were under continuous observation commencing from the date of their initial CHF diagnosis. This surveillance persisted until either their mortality or the culmination of the designated observation period. The occurrence of CHF was meticulously analyzed, with meticulous consideration given to variables encompassing age, sex, income, and underlying medical conditions.

3. Statistical Analysis

Both the χ2 test and Student’s t-test were employed to compare the demographic variables between the OPLL group and the control group. To estimate the probability of CHF-free survival in each group, the Kaplan-Meier method was employed. The impact of OPLL on the occurrence of CHF was explored using multivariate analysis within the framework of the Cox proportional-hazards regression model (Table 1).

Characteristics of the OPLL and control groups

In detail, two refined models were developed. Model 1 was adjusted for age and sex, while Model 2 was adjusted for age, sex, income, and pertinent medical factors, including hypertension, diabetes, and dyslipidemia (Table 2). For subgroup analyses aimed at adjusting covariates, the Cox proportional-hazards regression model was employed, utilizing R software version 3.3.3 (The R Foundation for Statistical Computing, Vienna, Austria). This approach was chosen to ensure the meticulous examination of covariate effects within the context of the study.

Adjusted hazard ratio for CHF in the OPLL and control groups

RESULTS

1. Characteristics of the OPLL and Control Groups

For both the newly diagnosed OPLL group and the control group, a larger proportion of the subjects were female (51.67%) and the average age was 57.4 ± 9.65 years.

2. CHF in the OPLL and Control Groups

Regarding CHF, the experimental group exhibited a higher incidence rate (2.153) compared to the control group (0.874) per 1000 person-years. Moreover, we identified that the hazard ratio of the control group was 3.164 (95% confidence interval [CI], 1.867-5.360) in Model 1, while in Model 2, it was 3.355 (95% CI, 1.977-5.694) (Table 2). In Fig. 2, during the 12-year follow-up period for CHF, the cumulative incidence in the experimental group was observed to be higher compared to that in the control group.

Fig. 2.

The cumulative incidence rates of congestive heart failure (CHF) in the ossification of the posterior longitudinal ligament (OPLL) and control groups were compared. Kaplan-Meier curves with increasing CHF risks were contrasted between the OPLL and control groups.

3. Subgroup Analysis of the OPLL Incidence Rate

There are ten subgroups categorized by sex, age, diabetes mellitus, hypertension, and dyslipidemia (Table 3). Across all subgroup factors, the incidence rate of CHF exhibited a difference between the OPLL group and the control group. About the incidence of CHF, notable differences were evident among both males (95% CI, 2.948-6.174) and females (95% CI, 3.724-7.891). Moreover, significant differences were observed in the age <65 group (95% CI, 4.219-9.111), age ≥65 group (95% CI, 2.538-5.227), individuals without diabetes mellitus (95% CI, 3.722-6.627), individuals with diabetes mellitus (95% CI, 2.376-8.409), those without hypertension (95% CI, 3.591-7.888), and those with hypertension (95% CI, 3.298-6.694). Lastly, a notably distinct incidence of CHF was evident both in individuals without dyslipidemia (95% CI, 3.682-6.643) and those with dyslipidemia (95% CI, 2.425-7.769).

The incidence rate of CHF in subgroup analyses between the OPLL and control groups

DISCUSSION

Our countrywide longitudinal research found that the OPLL group had a 3.164-fold greater incidence of CHF after controlling sex and age. The OPLL group also had a 3.355-fold greater incidence of CHF after controlling sex, age, wealth, hypertension, dyslipidemia, and diabetes mellitus. In addition, our study showed that the incidence of CHF was greater in the OPLL group than in the control group in sex, age, non-diabetes, diabetes, non-hypertension, hypertension, non-dyslipidemia, and dyslipidemia subgroups.

Until now, no studies have examined the direct connection between OPLL and CHF. Instead, several papers have shown that cytokines, signaling, and inflammation are associated with CHF. Yousefi et al.22) reported the transforming growth factor (TGF)-β and Wnt signaling pathways have been documented as pivotal regulators of myofibroblast biology within cardiac fibrosis, a process that contributes to the development of CHF. In previous studies related to cardiovascular disease and OPLL, there was a paper that studied the relationship between acute myocardial infarction (AMI) and OPLL. Kim et al.10) reported nationwide longitudinal cohort analysis between AMI and OPLL shows that patients with OPLL have an elevated risk of AMI, and the correlation is related to dysregulation of TGF-β.

Firstly, several members of the superfamily, including TGF-β1, TGF-β2, and TGF-β3 are associated with cardiac fibrosis following AMI and cardiac fibrosis is also closely related to CHF. For example, elevated expression levels of TGF-β1 due to mutation of TGF-β superfamily10), a prototypical fibrogenic cytokine, have been observed in cases of cardiac fibrosis, both in human subjects and experimental models22). Bai et al.1) reported rats were subjected to induced AMI through RNA manipulation by inhibiting the TGF-β1 gene. During the progression of OPLL, multiple genes, including TGF-β and BMP, play significant roles. The TGF-β/BMP signaling pathway orchestrates the intricate processes required for osteoblastogenesis, thereby facilitating the advancement of OPLL14,20). Consequently, this cytokine, TGF-β, could potentially elucidate a link between OPLL and CHF.

Secondly, the activation of the Wnt/β-catenin pathway by TGF-β has been extensively documented. TGF-β triggers an elevation in Akt phosphorylation via PI3K activation, leading to the inhibition of GSK3β (an enzyme crucial in β-catenin degradation). This sequence of events contributes to the augmentation of cardiac fibrosis22). Activation of Wnt/β-catenin signaling within osteocytes leads to enhanced bone formation and bone resorption, ultimately resulting in a positive balance that yields bone gain2). These mechanisms have the potential to contribute to the development of OPLL. Therefore, Wnt/β-catenin signaling is reasonable to explain the association between OPLL and CHF.

Thirdly, it has been noted that C-reactive protein (CRP) can serve as a robust indicator concerning vascular disease3,4,12). Habibi et al.5) reported the outcomes from intracranial vessel wall magnetic resonance imaging (MRI) revealed a robust connection between CRP and CHF (p<0.001). An MRI study provided compelling evidence linking CRP to the risk of CHF. Human genetic information indicates that CRP contributes causally to the development of CHF. Therefore, evaluating CRP levels could provide supplementary prognostic insights, enhancing overall risk assessment for patients with CHF. This genetic support underscores a potential causal connection between CRP and the onset of CHF.

Kawaguchi et al.9) reported a significant statistical disparity in CRP levels between patients with OPLL and those without OPLL was observed. The average serum CRP concentration was found to be 0.122 ± 0.141 mg/dL in the OPLL cohort, whereas it measured 0.086 ± 0.114 mg/dL in the comparison group (p=0.047). Therefore, CRP is reasonable to explain the association between OPLL and CHF.

Our longitudinal cohort study has several limitations. First of all, while our analysis accounted for variables such as sex, age, income, hypertension, diabetes, and dyslipidemia among participants, the study did not incorporate the influence of patients' lifestyle factors, such as smoking intensity, alcohol consumption, physical activity levels, and obesity status. These lifestyle elements could potentially exert a significant influence on the development of CHF.

At last, since no clear mechanism for OPLL has been elucidated, further studies will be needed to determine whether the signaling pathways discussed above are directly related to the incidence of OPLL. As a result, it is difficult to understand the exact relationship between OPLL and CHF through TGF-β, Wnt signaling, and CRP. Nevertheless, this is the first study attempting to find the connection between CHF and OPLL in Korean patients. Also, it is the largest nationwide longitudinal study indicating an increased risk of CHF in OPLL patients.

CONCLUSION

Our longitudinal cohort study conducted in Korea reveals a higher incidence of CHF among patients with OPLL.

Notes

FUNDING

This study received support from the Basic Science Research Program through the National Research Foundation of Korea, which is funded by the Ministry of Science and ICT (RS-2023-00209591).

No potential conflict of interest relevant to this article was reported.

References

1. Bai M, Pan CL, Jiang GX, Zhang YM. CircRNA 010567 improves myocardial infarction rats through inhibiting TGF-β1. Eur Rev Med Pharmacol Sci 24:369–375. 2020;
2. Delgado-Calle J, Bellido T. Osteocytes and skeletal pathophysiology. Curr Mol Biol Rep 1:157–167. 2015;
3. Di Napoli M, Papa F, Bocola V. Prognostic influence of increased C-reactive protein and fibrinogen levels in ischemic stroke. Stroke 32:133–138. 2001;
4. Erren M, Reinecke H, Junker R, Fobker M, Schulte H, Schurek JO, et al. Systemic inflammatory parameters in patients with atherosclerosis of the coronary and peripheral arteries. Arterioscler Thromb Vasc Biol 19:2355–2363. 1999;
5. Habibi D, Daneshpour MS, Asgarian S, Kohansal K, Hadaegh F, Mansourian M, et al. Effect of C-reactive protein on the risk of Heart failure: a mendelian randomization study. BMC Cardiovasc Disord 23:112. 2023;
6. He Z, Tung NTC, Makino H, Yasuda T, Seki S, Suzuki K, et al. Assessment of cervical myelopathy risk in ossification of the posterior longitudinal ligament patients with spinal cord compression based on segmental dynamic versus static factors. Neurospine 20:651–661. 2023;
7. Head J, Rymarczuk G, Stricsek G, Velagapudi L, Maulucci C, Hoelscher C, et al. Ossification of the posterior longitudinal ligament: surgical approaches and associated complications. Neurospine 16:517–529. 2019;
8. Hou X, Sun C, Liu X, Liu Z, Qi Q, Guo Z, et al. Clinical features of thoracic spinal stenosis-associated myelopathy: a retrospective analysis of 427 cases. Clin Spine Surg 29:86–89. 2016;
9. Kawaguchi Y, Nakano M, Yasuda T, Seki S, Suzuki K, Yahara Y, et al. Serum biomarkers in patients with ossification of the posterior longitudinal ligament (OPLL): Inflammation in OPLL. PLoS One 12:e0174881. 2017;
10. Kim J, Kim CY, Kim JG, Kim H, Sheen SH, Han I, et al. Association of acute myocardial infarction with ossification of the posterior longitudinal ligament in Korea: a nationwide longitudinal cohort study. Nerve 9:27–33. 2023;
11. Lee DH, Sheen SH, Lee DG, Jang JW, Lee DC, Shin SH, et al. Association between ischemic stroke and seropositive rheumatoid arthritis in Korea: A nationwide longitudinal cohort study. PLoS One 16:e0251851. 2021;
12. Lee SH, Kim H, Han IB, Sheen SH, Hong JB, Sohn S. Association between ischemic stroke and pyogenic spondylitis in Korea: Nationwide longitudinal cohort study. J Cerebrovasc Endovasc Neurosurg 25:143–149. 2023;
13. Oshima Y, Doi T, Kato S, Taniguchi Y, Matsubayashi Y, Nakajima K, et al. Association between ossification of the longitudinal ligament of the cervical spine and arteriosclerosis in the carotid artery. Sci Rep 10:3369. 2020;
14. Park J, Cho YE, Kim KH, Shin S, Kim S, Lim CH, et al. Correlation between the severity of multifidus fatty degeneration and the size of ossification of posterior longitudinal ligament at each spinal level. Neurospine 20:921–930. 2023;
15. Saito H, Yayama T, Mori K, Kumagai K, Fujikawa H, Chosei Y, et al. Increased cellular expression of interleukin-6 in patients with ossification of the posterior longitudinal ligament. Spine (Phila Pa 1976) 48:E78–E86. 2023;
16. Sakou T, Matsunaga S, Koga H. Recent progress in the study of pathogenesis of ossification of the posterior longitudinal ligament. J Orthop Sci 5:310–315. 2000;
17. Song J, Mizuno J, Hashizume Y, Nakagawa H. Immunohistochemistry of symptomatic hypertrophy of the posterior longitudinal ligament with special reference to ligamentous ossification. Spinal Cord 44:576–581. 2006;
18. Tung NTC, He Z, Makino H, Yasuda T, Seki S, Suzuki K, et al. Association of inflammation, ectopic bone formation, and sacroiliac joint variation in ossification of the posterior longitudinal ligament. J Clin Med 12:349. 2023;
19. Won YI, Lee CH, Yuh WT, Kwon SW, Kim CH, Chung CK. Genetic odyssey to ossification of the posterior longitudinal ligament in the cervical spine: a systematic review. Neurospine 19:299–306. 2022;
20. Yan L, Gao R, Liu Y, He B, Lv S, Hao D. The pathogenesis of ossification of the posterior longitudinal ligament. Aging Dis 8:570–582. 2017;
21. Yonemori K, Imamura T, Ishidou Y, Okano T, Matsunaga S, Yoshida H, et al. Bone morphogenetic protein receptors and activin receptors are highly expressed in ossified ligament tissues of patients with ossification of the posterior longitudinal ligament. Am J Pathol 150:1335–1347. 1997;
22. Yousefi F, Shabaninejad Z, Vakili S, Derakhshan M, Movahedpour A, Dabiri H, et al. TGF-β and WNT signaling pathways in cardiac fibrosis: non-coding RNAs come into focus. Cell Commun Signal 18:87. 2020;

Article information Continued

Fig. 1.

Flow diagram of the cohort formation process. The National Health Insurance Service-Health Screening Cohort (NHIS-HEALS) was used in this 12-year longitudinal cohort study. NIHSS: the National Institutes of Health Strock Scale; OPLL: ossification of the posterior longitudinal ligament; ICD-10: International Classification of Diseases, Tenth Revision; CT: computed tomography.

Fig. 2.

The cumulative incidence rates of congestive heart failure (CHF) in the ossification of the posterior longitudinal ligament (OPLL) and control groups were compared. Kaplan-Meier curves with increasing CHF risks were contrasted between the OPLL and control groups.

Table 1.

Characteristics of the OPLL and control groups

Variables OPLL (n = 1,289) Control (n = 6,445) p-value
Male 623 (48.33) 3,115 (48.33) 1
Age (years) 57.4 ± 9.65 57.4 ± 9.65 1
Age ≥ 65 339 (26.30) 1,695 (26.30) 1

The data is presented as number (%) or mean ± standard deviation.

OPLL: ossification of the posterior longitudinal ligament.

Table 2.

Adjusted hazard ratio for CHF in the OPLL and control groups

Group n Event Duration (days) IR* (%) HR (95% CI)
Model 1 Model 2
CHR
 OPLL 1,289 19 3,220,967 2.153 3.164 (1.867, 5.360) 3.355 (1.977, 5.694)
 Control 6,445 71 29,657,516 0.874 1 (Ref) 1 (Ref)

CHF: congestive heart failure; OPLL: ossification of the posterior longitudinal ligament; IR: incidence rate; HR: hazard ratio; CI: confidence interval; Ref: reference.

*IR: The incident rate per 1000 person-years.

Model 1: Adjusted for age and sex.

Model 2: Adjusted for age, sex, low income, diabetes mellitus, hypertension, and dyslipidemia.

Table 3.

The incidence rate of CHF in subgroup analyses between the OPLL and control groups

Variables OPLL
Control
HR (95% CI)
Event IR (%) Event IR (%)
Sex
 Male 7 1.781 31 0.819 4.266 (2.948, 6.174)
 Female 12 2.452 40 0.922 5.421 (3.724, 7.891)
Age
 <65 5 0.781 24 0.392 6.200 (4.219, 9.111)
 ≥65 14 5.773 47 2.350 3.642 (2.538, 5.227)
Diabetes
 No 19 2.385 57 0.804 4.974 (3.722, 6.627)
 Yes 0 0.000 17 1.639 4.470 (2.376, 8.409)
Hypertension
 No 8 1.424 29 0.605 5.322 (3.591, 7.888)
 Yes 11 3.429 42 1.261 4.699 (3.298, 6.694)
Dyslipidemia
 No 14 1.854 59 0.882 4.946 (3.682, 6.643)
 Yes 5 3.923 12 0.838 4.341 (2.425, 7.769)

CHF: congestive heart failure; OPLL: ossification of the posterior longitudinal ligament; IR: incidence rate; HR: hazard ratio; CI: confidence interval.