Bone morphogenic protein-2 signaling in human disc degeneration and correlation to the Pfirrmann MRI grading system

Hollenberg, Alex M.; Maqsoodi, Noorullah; Phan, Amy; Huber, Aric; Jubril, Ayodeji; Baldwin, Avionna; Yokogawa, Noriaki; Eliseev, Roman A.; Mesfin, Addisu

doi:10.1016/j.spinee.2021.03.002

Cited by 17 publications

(14 citation statements)

References 59 publications

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“…Pfirrmann grading focuses on the morphological assessment of the IVD, whereas the early stages of IVD degeneration may not be reflected in morphological changes. 28 In subjects who develop early IVD degeneration, the Pfirrmann grading system may underestimate the level of IVD degeneration. Moreover, the low sample sizes of patients with grades I and V may have influenced the results.…”

Section: Discussionmentioning

confidence: 99%

“…In this study, although 10% of patients with grade IV disease were categorized into the osteoporosis group and 21% of patients with grade II disease were categorized into the healthy group, sufficient statistical evidence to support an association between BMFF and Pfirrmann grade remains lacking. Pfirrmann grading focuses on the morphological assessment of the IVD, whereas the early stages of IVD degeneration may not be reflected in morphological changes 28 . In subjects who develop early IVD degeneration, the Pfirrmann grading system may underestimate the level of IVD degeneration.…”

Section: Discussionmentioning

confidence: 99%

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Q‐Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration

Xie

Lü

et al. 2021

Magnetic Resonance Imaging

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Background The relationship between osteoporosis and intervertebral disc (IVD) degeneration remains controversial. Novel quantitative Dixon (Q‐Dixon) and GRAPPATINI T2 mapping techniques have shown potential for evaluating the biochemical components of the spine. Purpose To investigate the correlation of osteoporosis with IVD degeneration in postmenopausal women. Study Type Prospective. Subjects A total of 105 postmenopausal females (mean age, 65 years; mean body mass index, 26 kg/m2). Field Strength/Sequence 3 T; sagittal; 6‐echo Q‐Dixon, multiecho spin‐echo GRAPPATINI T2 mapping, turbo spin echo (TSE) T1‐weighted and TSE T2‐weighted sequences. Assessment The subjects were divided into normal (N = 47), osteopenia (N = 28), and osteoporosis (N = 30) groups according to quantitative computed tomography examination. The Pfirrmann grade of each IVD was obtained. Region of interest analysis was performed separately by two radiologists (X.L., with 10 years of experience, and S.C., with 20 years of experience) on a fat fraction map and T2 map to calculate the bone marrow fat fraction (BMFF) from the L1 to L5 vertebrae and the T2 values of each adjacent IVD separately. Statistical Tests One‐way analysis of variance, post‐hoc comparisons, and Kruskal–Wallis H tests were performed to evaluate the differences in the magnetic resonance imaging parameters between the groups. The relationships between BMFF and the IVD features were analyzed using the Spearman correlation analysis and linear regression models. Results There were significant differences in BMFF among the three groups. The osteoporosis group had higher BMFF values (64.5 ± 5.9%). No significant correlation was found between BMFF and Pfirrmann grade (r = 0.251, P = 0.06). BMFF was significantly negatively correlated with the T2 of the adjacent IVD from L1 to L3 (r = −0.731; r = −0.637; r = −0.547), while significant weak correlations were found at the L4 to L5 levels (r = −0.337; r = −0.278). Data Conclusion This study demonstrated that osteoporosis is associated with IVD degeneration. Level of Evidence 2 Technical Efficacy Stage 4

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Q‐Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration

Xie

Lü

et al. 2021

Magnetic Resonance Imaging

View full text Add to dashboard Cite

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“…The Pfirrmann grade system was used to evaluate the degree of disc degeneration on the T2-weighted MRI ( Figure 1 ). Details of the Pfirrmann grading system can be found in Reference [ 16 ]. Pfirrmann grades I and II were taken as nondegenerative discs, whereas grades III, IV, and V were considered degenerative discs [ 16 ].…”

Section: Methodsmentioning

confidence: 99%

“…Details of the Pfirrmann grading system can be found in Reference [ 16 ]. Pfirrmann grades I and II were taken as nondegenerative discs, whereas grades III, IV, and V were considered degenerative discs [ 16 ]. Based on the Pfirrmann grading system, patients were classified into group N (nondegenerative discs in lumbar) and group D (degenerative discs in lumbar).…”

Section: Methodsmentioning

confidence: 99%

Development and Validation of a Novel Nomogram to Predict the Risk of Intervertebral Disc Degeneration

Sun

Wang

et al. 2022

Mediators of Inflammation

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Intervertebral disc degeneration (IVDD) has been a complex disorder resulted from genetic and environmental risk factors. The aim of this study was to identify the risk factors associated with IVDD in orthopaedic patients and develop a prediction model for predicting the risk of IVDD. A total of 309 patients were retrospectively included in the study and randomly divided into the training group and the validation group. The least absolute shrinkage and selection operator regression (LASSO) and the univariate logistic regression analysis were used to optimize factors selection for the IVDD risk model. Multivariable logistic regression analysis was used to establish a predicting nomogram model incorporating the factors. In addition, discrimination, calibration, and clinical usefulness of the nomogram model were evaluated via the C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA). Then, based on the results above, the relationship between IVDD and angiotensin II (AngII) level in peripheral blood was examined prospectively. The predictors of the nomogram include age, sex, hypertension, diabetes, gout, working posture, and exercising hours per week. The C -index values of the training and validation groups were 0.916 (95% CI, 0.876-0.956) and 0.949 (95% CI, 0.909-0.989), respectively, which indicated that the model displayed good discrimination. In addition, the area under the curve (AUC) values of the ROC curve of the training and the validation group were 0.815 (95% CI, 0.759-0.870) and 0.805 (95% CI, 0.718-0.892), respectively, revealing the satisfactory discrimination performance of the model. The prospective investigation showed that the average AngII level in the degenerated group ( 97.62 ± 44.02 pg/mL) was significantly higher than that in the nondegenerated group ( 52.91 ± 9.01 pg/mL) ( p < 0.001 ). This present study explored the risk factors for IVDD and established a prediction model, which would effectively predict the risk of IVDD. In addition, based on the prediction model, AngII was revealed to be a potentially auxiliary clinical diagnostic marker for IVDD.

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“…The causes of cLBP are varied and can be both mechanical and nonmechanical, and can be worsened by risk factors including inactivity, smoking, age, and others. [1][2][3] Biomarkers have been studied extensively in known contributors to cLBP [4][5][6] such as intervertebral disc (IVD) degeneration (IDD), 7 modic changes, [8][9][10] and fibromyalgia. 11 The significant association of disparate biomarkers with the causes of cLBP and the response to treatment supports the need for integrative and harmonized "omics" approach that has been developed and implemented by BACPAC.…”

Section: Chronic Low Back Painmentioning

confidence: 99%

Protocol for Biospecimen Collection and Analysis Within the BACPAC Research Program

et al. 2022

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The Biospecimen Collection and Processing Working Group of the NIH HEAL Initiative BACPAC Research Program was charged with identifying molecular biomarkers of interest to chronic low back pain (cLBP). Having identified biomarkers of interest, the Working Group worked with the New York University Grossman School of Medicine, Center for Biospecimen Research and Development—funded by the Early Phase Pain Investigation Clinical Network Data Coordinating Center—to harmonize consortium-wide and site-specific efforts for biospecimen collection and analysis. Biospecimen collected are saliva, blood (whole, plasma, serum), urine, stool, and spine tissue (paraspinal muscle, ligamentum flavum, vertebral bone, facet cartilage, disc endplate, annulus fibrosus, or nucleus pulposus). The omics data acquisition and analyses derived from the biospecimen include genomics and epigenetics from DNA, proteomics from protein, transcriptomics from RNA, and microbiomics from 16S rRNA. These analyses contribute to the overarching goal of BACPAC to phenotype cLBP and will guide future efforts for precision medicine treatment.

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Bone morphogenic protein-2 signaling in human disc degeneration and correlation to the Pfirrmann MRI grading system

Cited by 17 publications

References 59 publications

Q‐Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration

Q‐Dixon and GRAPPATINI T2 Mapping Parameters: A Whole Spinal Assessment of the Relationship Between Osteoporosis and Intervertebral Disc Degeneration

Development and Validation of a Novel Nomogram to Predict the Risk of Intervertebral Disc Degeneration

Protocol for Biospecimen Collection and Analysis Within the BACPAC Research Program

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