Genotype-Phenotype Association Analysis Reveals New Pathogenic Factors for Osteogenesis Imperfecta Disease

Deciphering potential causative factors for undiagnosed Waardenburg syndrome through multi-data integration

BACKGROUND

Waardenburg syndrome (WS) is a rare genetic disorder mainly characterized by hearing loss and pigmentary abnormalities. Currently, seven causative genes have been identified for WS, but clinical genetic testing results show that 38.9% of WS patients remain molecularly unexplained. In this study, we performed multi-data integration analysis through protein-protein interaction and phenotype-similarity to comprehensively decipher the potential causative factors of undiagnosed WS. In addition, we explored the association between genotypes and phenotypes in WS with the manually collected 443 cases from published literature.

RESULTS

We predicted two possible WS pathogenic genes (KIT, CHD7) through multi-data integration analysis, which were further supported by gene expression profiles in single cells and phenotypes in gene knockout mouse. We also predicted twenty, seven, and five potential WS pathogenic variations in gene PAX3, MITF, and SOX10, respectively. Genotype-phenotype association analysis showed that white forelock and telecanthus were dominantly present in patients with PAX3 variants; skin freckles and premature graying of hair were more frequently observed in cases with MITF variants; while aganglionic megacolon and constipation occurred more often in those with SOX10 variants. Patients with variations of PAX3 and MITF were more likely to have synophrys and broad nasal root. Iris pigmentary abnormality was more common in patients with variations of PAX3 and SOX10. Moreover, we found that patients with variants of SOX10 had a higher risk of suffering from auditory system diseases and nervous system diseases, which were closely associated with the high expression abundance of SOX10 in ear tissues and brain tissues.

CONCLUSIONS

Our study provides new insights into the potential causative factors of WS and an alternative way to explore clinically undiagnosed cases, which will promote clinical diagnosis and genetic counseling. However, the two potential disease-causing genes (KIT, CHD7) and 32 potential pathogenic variants (PAX3: 20, MITF: 7, SOX10: 5) predicted by multi-data integration in this study are all computational predictions and need to be further verified through experiments in follow-up research.

Integrative analyses of genetic characteristics associated with skeletal endothelial cells

The osseous vascular endothelium encompasses a vast intricate framework that regulates bone remodeling. Osteoporosis, an age-associated systemic bone disease, is characterized by the degeneration of the vascular architecture. Nevertheless, the precise mechanisms underpinning the metamorphosis of endothelial cells (ECs) with advancing age remain predominantly enigmatic. In this study, we conducted a systematic analysis of differentially expressed genes (DEGs) and the associated pathways in juvenile and mature femoral ECs, utilizing data sourced from the Gene Expression Omnibus (GEO) repositories (GSE148804) and employing bioinformatics tools. Through this approach, we successfully discerned six pivotal genes, namely Adamts1, Adamts2, Adamts4, Adamts14, Col5a1, and Col5a2. Subsequently, we constructed a miRNA-mRNA network based on miRNAs displaying differential expression between CD31hiEMCNhi and CD31lowEMCNlow ECs, utilizing online repositories for prediction. The expression of miR-466i-3p and miR-466i-5p in bone marrow ECs exhibited an inverse correlation with age. Our in vivo experiments additionally unveiled miR-466i-5p as a pivotal regulator in osseous ECs and a promising therapeutic target for age-related osteoporosis.

Osteogenesis imperfecta: a cross-sectional study of skeletal and extraskeletal features in a large cohort of Italian patients

Introduction

The present study aims to describe a large cohort of Italian patients affected by osteogenesis imperfecta, providing a picture of the clinical bony and non-bony features and the molecular background to improve knowledge of the disease to inform appropriate management in clinical practice.

Methods

A total of 568 subjects (from 446 unrelated Italian families) affected by osteogenesis imperfecta who received outpatient care at Istituto Ortopedico Rizzoli from 2006 to 2021 were considered in the present study.

Results

Skeletal and extraskeletal features were analyzed showing a lower height (mean z-scores equal to -1.54 for male patients and -1.47 for female patients) compared with the general Italian population. Half of the patient population showed one or more deformities, and most of the patients had suffered a relatively low number of fractures (<10). An alteration in the sclera color was identified in 447 patients. Similarly, several extraskeletal features, like deafness, dental abnormalities, and cardiac problems, were investigated. Additionally, inheritance and genetic background were evaluated, showing that most of the patients have a positive family history and the majority of pathogenic variants detected were on collagen genes, as per literature.

Conclusion

This study supports the definition of a clear picture of the heterogeneous clinical manifestations leading to variable severity in terms of skeletal and extra-skeletal traits and of the genetic background of an Italian population of osteogenesis imperfecta patients. In this perspective, this clearly highlights the crucial role of standardized and structured collection of high-quality data in disease registries particularly in rare disease scenarios, helping clinicians in disease monitoring and follow-up to improve clinical practice.

Prediction of disease comorbidity using explainable artificial intelligence and machine learning techniques: A systematic review

OBJECTIVE

Disease comorbidity is a major challenge in healthcare affecting the patient's quality of life and costs. AI-based prediction of comorbidities can overcome this issue by improving precision medicine and providing holistic care. The objective of this systematic literature review was to identify and summarise existing machine learning (ML) methods for comorbidity prediction and evaluate the interpretability and explainability of the models.

MATERIALS AND METHODS

The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework was used to identify articles in three databases: Ovid Medline, Web of Science and PubMed. The literature search covered a broad range of terms for the prediction of disease comorbidity and ML, including traditional predictive modelling.

RESULTS

Of 829 unique articles, 58 full-text papers were assessed for eligibility. A final set of 22 articles with 61 ML models was included in this review. Of the identified ML models, 33 models achieved relatively high accuracy (80-95%) and AUC (0.80-0.89). Overall, 72% of studies had high or unclear concerns regarding the risk of bias.

DISCUSSION

This systematic review is the first to examine the use of ML and explainable artificial intelligence (XAI) methods for comorbidity prediction. The chosen studies focused on a limited scope of comorbidities ranging from 1 to 34 (mean = 6), and no novel comorbidities were found due to limited phenotypic and genetic data. The lack of standard evaluation for XAI hinders fair comparisons.

CONCLUSION

A broad range of ML methods has been used to predict the comorbidities of various disorders. With further development of explainable ML capacity in the field of comorbidity prediction, there is a significant possibility of identifying unmet health needs by highlighting comorbidities in patient groups that were not previously recognised to be at risk for particular comorbidities.

Systematic review of health related-quality of life in adults with osteogenesis imperfecta

BACKGROUND

Osteogenesis imperfecta (OI) is a rare, connective tissue disorder characterised by bone fragility, resulting in recurrent fractures and skeletal deformities. Extra-skeletal manifestations include dentinogenesis imperfecta, hearing abnormalities and lung disease. These co-morbidities combined with recurrent fractures can exert a significant impact on health-related quality of life (HR-QOL). It is important to assess HR-QOL throughout adulthood because the prevalence of some OI-specific complications increases with age.

METHODS

PubMed, EMBASE and CENTRAL databases were searched on 2nd February 2022 to identify studies reporting quantitative assessments of HR-QOL in adults with OI. The primary endpoint was to determine the impact of an OI diagnosis on adult's HR-QOL. Secondary endpoints were to (i) examine how frequently various HR-QOL assessment tools were used (ii) identify differences in HR-QOL between OI types and (iii) investigate the determinants of HR-QOL in adults with OI. Search results were exported to Endnote where two reviewers independently conducted title/abstract and full-text reviews. Data from accepted studies were extracted into Microsoft Excel. A narrative synthesis was then undertaken.

RESULTS

The review identified 17 studies with a total of 1,648 adults. The Short Form-36 (SF-36) was the most frequently reported HR-QOL assessment tool and was used in nine studies. Physical HR-QOL was reduced in adults with OI. Physical component scores (PCS) or individual physical domains of the SF-36 were lower in eight of nine studies. Mental component scores (MCS) were preserved in all six studies, however individual mental health domains of the SF-36 were reduced in some studies. The prevalence of anxiety/depression was relatively low in adults with OI. Those with type III OI had lower physical and respiratory HR-QOL but preserved mental HR-QOL compared with type I. The prevalence of fatigue and pain was higher in adults with OI compared with reference populations. Age and cardio-pulmonary co-morbidities were associated with lower HR-QOL.

CONCLUSION

OI in adulthood has a wide-ranging negative impact on HR-QOL. Physical and respiratory HR-QOL were lower, while the prevalence of pain and fatigue were higher than in reference populations. Mental HR-QOL was relatively preserved, although some deficits were identified. Age and cardio-pulmonary co-morbidities were associated with lower HR-QOL.

Improving the accuracy and internal consistency of regression-based clustering of high-dimensional datasets

Component-wise Sparse Mixture Regression (CSMR) is a recently proposed regression-based clustering method that shows promise in detecting heterogeneous relationships between molecular markers and a continuous phenotype of interest. However, CSMR can yield inconsistent results when applied to high-dimensional molecular data, which we hypothesize is in part due to inherent limitations associated with the feature selection method used in the CSMR algorithm. To assess this hypothesis, we explored whether substituting different regularized regression methods (i.e. Lasso, Elastic Net, Smoothly Clipped Absolute Deviation (SCAD), Minmax Convex Penalty (MCP), and Adaptive-Lasso) within the CSMR framework can improve the clustering accuracy and internal consistency (IC) of CSMR in high-dimensional settings. We calculated the true positive rate (TPR), true negative rate (TNR), IC and clustering accuracy of our proposed modifications, benchmarked against the existing CSMR algorithm, using an extensive set of simulation studies and real biological datasets. Our results demonstrated that substituting Adaptive-Lasso within the existing feature selection method used in CSMR led to significantly improved IC and clustering accuracy, with strong performance even in high-dimensional scenarios. In conclusion, our modifications of the CSMR method resulted in improved clustering performance and may thus serve as viable alternatives for the regression-based clustering of high-dimensional datasets.

Morphological Study of Dental Structure in Dentinogenesis Imperfecta Type I with Scanning Electron Microscopy

Background: Dentinogenesis imperfecta type I (DGI-I) is a hereditary alteration of dentin associated with osteogenesis imperfecta (OI). Aim: To describe and study the morphological characteristics of DGI-I with scanning electron microscopy (SEM). Material and methods: Twenty-five teeth from 17 individuals diagnosed with OI and 30 control samples were studied with SEM at the level of the enamel, dentin–enamel junction (DEJ) and four levels of the dentin, studying its relationship with clinical–radiographic alterations. The variables were analysed using Fisher’s exact test, with a confidence level of 95% and asymptotic significance. Results: OI teeth showed alterations in the prismatic structure in 56%, interruption of the union in the enamel and dentin in 64% and alterations in the tubular structure in all of the cases. There is a relationship between the severity of OI and the morphological alteration of the dentin in the superficial (p = 0.019) and pulpar dentin (p 0.004) regions. Conclusions: Morphological alterations of the tooth structure are found in OI samples in the enamel, DEJ and dentin in all teeth regardless of the presence of clinical–radiographic alterations. Dentin structural anomalies and clinical dental alterations were observed more frequently in samples from subjects with a more severe phenotype of OI.

Patient-reported outcomes in a Chinese cohort of osteogenesis imperfecta unveil psycho-physical stratifications associated with clinical manifestations

Background

Osteogenesis imperfecta (OI) is a rare congenital disorder of the skeletal system, inflicting debilitating physical and psychological distress on patients and caregivers. Over the decades, much effort has been channeled towards understanding molecular mechanisms and developing new treatments. It has recently become more apparent that patient-reported outcome measurements (PROM) during treatment, healing and rehabilitation are helpful in facilitating smoother communication, refining intervention strategies and achieving higher quality of life. To date, systematic analyses of PROM in OI patients remain scarce.

Results

Here, utilizing a PROM Information System, we report a cross-sectional and longitudinal study in a southern Chinese cohort of 90 OI patients, covering both the child and adult age-groups. In the child group where both self and parental surveys were obtained, we identified two clusters of comparable sizes showing different outlooks in physical mobility and emotional experiences. One cluster (Cluster 1) is more negative about themselves than the other (Cluster 2). A concordance of 84.7% between self and parental assessments was recorded, suggesting the stability and validity of PROM-based stratification. Clinical subtyping, deformity, leg length discrepancy, and limited joint mobility were significantly associated with this stratification, with Cluster 1 showing higher percentages of severe phenotypes than Cluster 2. Since OI is a genetic disorder, we performed genetic testing on 72 of the 90 patients, but found no obvious association between genotypes and the PROM stratification. Analyses of longitudinal data suggested that patients tended to stay in the same psychological state, in both clusters. Adult patients also showed a continuous spectrum of self-evaluation that matches their clinical manifestations.

Conclusion

By systematically analyzing patient-reported outcomes, our study demonstrated the link between the sociopsychological wellbeing of OI patients, and their clinical manifestations, which may serve as the basis for evaluating clinical interventions and help achieve better patient-centric medical practices. The lack of genotype-PROM association may be due to the diverse mutational spectrum in OI, which warrants further investigation when a larger sample size is available.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-022-02394-7.

Prenatal trio-based whole exome sequencing in fetuses with abnormalities of the skeletal system

Whole exome sequencing (WES) could yield diagnostic significance in the prenatal diagnosis of skeletal abnormalities. But the phenotypes of fetuses with skeletal abnormalities are heterogenous, and the clinical information we could obtain from an ongoing pregnancy is limited, making the prenatal diagnosis complicated. Therefore, the following interpretation and genetic counseling remain a challenge for clinicians. The aim of this study is to present and investigate the utility of trio-based WES in five fetuses with skeletal anomalies. Five trios with fetal ultrasonic skeletal anomalies were recruited in our study. Fetal specimens and parental peripheral blood were subjected to WES. The fetal skeletal abnormalities were presented through ultrasound scanning images. Fetal WES results showed variants in the PPIB, CHST3, COL1A1, and FGFR3 genes in the five trios. Inherited variants were found in two of the trios, while de novo variants were observed in three of them. Two novel compound heterozygous variants (c.437C > A and c.1044C > G) in CHST3 were identified. We presented five trios with fetal skeletal anomalies, found two novel variants and broadened the spectrum of variants associated with skeletal abnormalities, which would help the establishment of genotype-phenotype relationship in the prenatal setting. Trio-based WES could assist the prenatal diagnosis and genetic counseling of fetuses with skeletal abnormalities.

Epidemiology of rare diseases in Brazil: protocol of the Brazilian Rare Diseases Network (RARAS-BRDN)

The Brazilian Policy of Comprehensive Care for People with Rare Diseases (BPCCPRD) was established by the Ministry of Health to reduce morbidity and mortality and improve the quality of life of people with rare diseases (RD). Several laboratory tests, most using molecular genetic technologies, have been incorporated by the Brazilian Public Health System, and 18 specialised centres have so far been established at university hospitals (UH) in the capitals of the Southern, Southeastern and Northeastern regions. However, whether the available human and technological resources in these services are appropriate and sufficient to achieve the goals of care established by the BPCCPRD is unknown. Despite great advances in diagnosis, especially due to new technologies and the recent structuring of clinical assessment of RD in Brazil, epidemiological data are lacking and when available, restricted to specific disorders. This position paper summarises the performance of a nationally representative survey on epidemiology, clinical status, and diagnostic and therapeutic resources employed for individuals with genetic and non-genetic RD in Brazil. The Brazilian Rare Disease Network (BRDN) is under development, comprising 40 institutions, including 18 UH, 17 Rare Diseases Reference Services and five Newborn Screening Reference Services. A retrospective study will be initially conducted, followed by a prospective study. The data collection instrument will use a standard protocol with sociodemographic data and clinical and diagnostic aspects according to international ontology. This great collaborative network is the first initiative of a large epidemiological data collection of RD in Latin America, and the results will increase the knowledge of RD in Brazil and help health managers to improve national public policy on RD in Brazil.

Current Insights into Collagen Type I

Collagen type I (Col-I) is unique due to its high biocompatibility in human tissue. Despite its availability from various sources, Col-I naturally mimics the extracellular matrix (ECM) and generally makes up the larger protein component (90%) in vasculature, skin, tendon bone, and other tissue. The acceptable physicochemical properties of native Col-I further enhance the incorporation of Col-I in various fields, including pharmaceutical, cosmeceutical, regenerative medicine, and clinical. This review aims to discuss Col-I, covering the structure, various sources of availability, native collagen synthesis, current extraction methods, physicochemical characteristics, applications in various fields, and biomarkers. The review is intended to provide specific information on Col-I currently available, going back five years. This is expected to provide a helping hand for researchers who are concerned about any development on collagen-based products particularly for therapeutic fields.

Case Report: A Novel COL1A1 Missense Mutation Associated With Dentineogenesis Imperfecta Type I

Background: Osteogenesis imperfecta (OI) is a clinical and genetic disorder that results in bone fragility, blue sclerae and dentineogenesis imperfecta (DGI), which is mainly caused by a mutation in the COL1A1 or COL1A2 genes, which encode type I procollagen. Case Report: A missense mutation (c.1463G > C) in exon 22 of the COL1A1 gene was found using whole-exome sequencing. However, the cases reported herein only exhibited a clinical DGI-I phenotype. There were no cases of bone disease or any other common abnormal symptom caused by a COL1A1 mutation. In addition, the ultrastructural analysis of the tooth affected with non-syndromic DGI-I showed that the abnormal dentine was accompanied by the disruption of odontoblast polarization, a reduced number of odontoblasts, a reduction in hardness and elasticity, and the loss of dentinal tubules, suggesting a severe developmental disorder. We also investigated the odontoblast differentiation ability using dental pulp stem cells (DPSCs) that were isolated from a patient with DGI-I and cultured. Stem cells isolated from patients with DGI-I are important to elucidate their pathogenesis and underlying mechanisms to develop regenerative therapies. Conclusion: This study can provide new insights into the phenotype-genotype association in collagen-associated diseases and improve the clinical diagnosis of OI/DGI-I.

Two novel mutations of COL1A1 in fetal genetic skeletal dysplasia of Chinese

Background

Skeletal disorders, which have great genotypic and phenotypic varieties, are a considerable challenge to differentiate these diseases and provide a definitive prenatal diagnosis or pre‐implantation. The present study aims to identify the causative mutation in two unrelated outbred Han–Chinese families.

Method

Two short‐limb fetuses were referred to our hospital. Genomic DNA was extracted from the amniotic fluid of the short‐limb fetuses and from peripheral blood of their parents. To identify the causative gene, next‐generation‐based target capture sequencing was performed on these two fetuses, followed by Sanger Sequencing in unrelated healthy controls. Segregation analysis of the candidate variant was performed in parents by using Sanger sequencing. The mutations were analyzed by SIFT, PolyPhen and Provean.

Results

We found that fetal genetic skeletal dysplasia was confirmed according to the correlations between genetic mutations and phenotypes in two Chinese families. Targeted next generation sequencing was performed to screen causative mutations in patients. Two novel heterozygous mutations COL1A1 c.1706 G > C (p. G569A) and c.3307 G > A (p. G1103S) were respectively identified. The results suggested that COL1A1 novel mutations were in highly conserved glycine residues present in the Gly‐X‐Y sequence repeats of the triple helical region of the collagen type I α chain, which was responsible for Osteogenesis Imperfecta. The presence of the missense mutation was also confirmed with the Sanger sequence. These two mutations were predicted to be pathogenic by SIFT, PolyPhen and Provean.

Conclusion

Our findings showed that the mutations of COL1A1 may play important roles in fetal genetic skeletal dysplasia in Chinese patients. Exome sequencing enhances the accurate diagnosis in utero then provides appropriate genetic counseling.