A novel compound heterozygous mutation of the CLCN7 gene is associated with autosomal recessive osteopetrosis

Wang, Xia; Wang, Yingcan; Xu, Ting; Fan, Yanjie; Ding, Yifeng; Qian, Jihong

doi:10.3389/fped.2023.978879

Cited by 2 publications

(2 citation statements)

References 39 publications

(57 reference statements)

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“…It causes osteopetrosis owing to defective osteoclast functioning, illustrating that the gene can intersect with sarcopenia-related pathways. 35 36 37 cg00647232 (SEC16B) is associated with cellular trafficking and has been linked to body weight regulation and metabolic disease. It may also influence the development of sarcopenia, particularly through pathways involving muscle protein synthesis or degradation.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning-Based Identification of Diagnostic Biomarkers for Korean Male Sarcopenia Through Integrative DNA Methylation and Methylation Risk Score: From the Korean Genomic Epidemiology Study (KoGES)

Ahn,

Sung,

Song

2024

J Korean Med Sci

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Background Sarcopenia, characterized by a progressive decline in muscle mass, strength, and function, is primarily attributable to aging. DNA methylation, influenced by both genetic predispositions and environmental exposures, plays a significant role in sarcopenia occurrence. This study employed machine learning (ML) methods to identify differentially methylated probes (DMPs) capable of diagnosing sarcopenia in middle-aged individuals. We also investigated the relationship between muscle strength, muscle mass, age, and sarcopenia risk as reflected in methylation profiles. Methods Data from 509 male participants in the urban cohort of the Korean Genome Epidemiology Study_Health Examinee study were categorized into quartile groups based on the sarcopenia criteria for appendicular skeletal muscle index (ASMI) and handgrip strength (HG). To identify diagnostic biomarkers for sarcopenia, we used recursive feature elimination with cross validation (RFECV), to pinpoint DMPs significantly associated with sarcopenia. An ensemble model, leveraging majority voting, was utilized for evaluation. Furthermore, a methylation risk score (MRS) was calculated, and its correlation with muscle strength, function, and age was assessed using likelihood ratio analysis and multinomial logistic regression. Results Participants were classified into two groups based on quartile thresholds: sarcopenia (n = 37) with ASMI and HG in the lowest quartile, and normal ranges (n = 48) in the highest. In total, 238 DMPs were identified and eight probes were selected using RFECV. These DMPs were used to build an ensemble model with robust diagnostic capabilities for sarcopenia, as evidenced by an area under the receiver operating characteristic curve of 0.94. Based on eight probes, the MRS was calculated and then validated by analyzing age, HG, and ASMI among the control group (n = 424). Age was positively correlated with high MRS (coefficient, 1.2494; odds ratio [OR], 3.4882), whereas ASMI and HG were negatively correlated with high MRS (ASMI coefficient, −0.4275; OR, 0.6521; HG coefficient, −0.3116; OR, 0.7323). Conclusion Overall, this study identified key epigenetic markers of sarcopenia in Korean males and developed a ML model with high diagnostic accuracy for sarcopenia. The MRS also revealed significant correlations between these markers and age, HG, and ASMI. These findings suggest that both diagnostic models and the MRS can play an important role in managing sarcopenia in middle-aged populations.

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Section: Discussionmentioning

confidence: 99%

Machine Learning-Based Identification of Diagnostic Biomarkers for Korean Male Sarcopenia Through Integrative DNA Methylation and Methylation Risk Score: From the Korean Genomic Epidemiology Study (KoGES)

Ahn,

Sung,

Song

2024

J Korean Med Sci

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“…In conclusion, we have reviewed the clinical features, types, and related pathogenic genes of osteopetrosis, and emphasized the craniofacial and dental abnormalities, and presented a molecular explanation of the craniofacial and dental anomalies present in osteopetrotic patients. The limitations of our study include not paying special attention to other phenotypes, such as neurodegeneration [ 97 ], leukocytosis [ 98 ], and hematological abnormality [ 98 ], which may be associated with the structural functional correlations of different mutations. New advances in the treatment of osteopetrosis were also introduced in detail, such as toxic doses of zoledronate lead and the radiographic signs of OPT mentioned by Whyte et al [ 99 ].…”

Section: Discussionmentioning

confidence: 99%

Molecular Mechanisms of Craniofacial and Dental Abnormalities in Osteopetrosis

Duan

2023

IJMS

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Osteopetrosis is a group of genetic bone disorders characterized by increased bone density and defective bone resorption. Osteopetrosis presents a series of clinical manifestations, including craniofacial deformities and dental problems. However, few previous reports have focused on the features of craniofacial and dental problems in osteopetrosis. In this review, we go through the clinical features, types, and related pathogenic genes of osteopetrosis. Then we summarize and describe the characteristics of craniofacial and dental abnormalities in osteopetrosis that have been published in PubMed from 1965 to the present. We found that all 13 types of osteopetrosis have craniomaxillofacial and dental phenotypes. The main pathogenic genes, such as chloride channel 7 gene (CLCN7), T cell immune regulator 1 (TCIRG1), osteopetrosis-associated transmembrane protein 1 (OSTM1), pleckstrin homology domain-containing protein family member 1 (PLEKHM1), and carbonic anhydrase II (CA2), and their molecular mechanisms involved in craniofacial and dental phenotypes, are discussed. We conclude that the telltale craniofacial and dental abnormalities are important for dentists and other clinicians in the diagnosis of osteopetrosis and other genetic bone diseases.

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A novel compound heterozygous mutation of the CLCN7 gene is associated with autosomal recessive osteopetrosis

Cited by 2 publications

References 39 publications

Machine Learning-Based Identification of Diagnostic Biomarkers for Korean Male Sarcopenia Through Integrative DNA Methylation and Methylation Risk Score: From the Korean Genomic Epidemiology Study (KoGES)

Machine Learning-Based Identification of Diagnostic Biomarkers for Korean Male Sarcopenia Through Integrative DNA Methylation and Methylation Risk Score: From the Korean Genomic Epidemiology Study (KoGES)

Molecular Mechanisms of Craniofacial and Dental Abnormalities in Osteopetrosis

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