PubMed HealthSearch

Biomedical subjects

Mahdi Akbarzadeh

Publications and source records attributed to Mahdi Akbarzadeh.

3 recordsLinked to original sources

Systemic Comorbidities of Keloid and Hypertrophic Scars: A Phenome-Wide Association Study in a Multiethnic U.S. Pediatric Cohort.

BACKGROUND: Excessive scarring (ES), including keloids and hypertrophic scars, impairs function, appearance, and quality of life in children. Its pediatric comorbidity spectrum is not well defined, limiting anticipatory guidance and multidisciplinary care. This research aims to investigate comorbidities of ES in a diverse pediatric cohort using a phenome-wide association study (PheWAS). METHODS: This population-based study leveraged longitudinal electronic health record (EHR) data from participants enrolled in the Children's Hospital of Philadelphia (CHOP) from 2006. Diagnosis codes (International Classification of Diseases, Ninth Revision, Clinical Modification [ICD-9-CM] and Tenth Revision [ICD-10-CM]) were mapped to 3109 phenotype codes (PheCodes). PheWAS analyses were conducted using logistic regression, with Bonferroni correction applied to account for multiple testing. RESULTS: Among 86,092 pediatric participants, 662 (0.77%) were identified with ES; the remaining served as controls. Multivariable PheWAS screening identified 154 significant associations across 16 disease categories, of which 105 were not reported previously to our knowledge. Dermatologic phenotypes (n = 28; 18%) were most enriched, including acne and other follicular disorders, eczema, pigmentary changes, papulosquamous and granulomatous disorders, and cutaneous infections. Respiratory phenotypes (n = 21; 14%) included respiratory failure, pneumonia, asthma, allergic rhinitis, pharyngitis, and tonsillar hypertrophy. Sense organ disorders (n = 19; 12%) comprised conjunctivitis, refractive errors, otitis, and hearing impairment. Infection-related phenotypes (n = 14; 9%) highlighted susceptibility to viral (influenza, human papillomavirus [HPV], molluscum contagiosum), fungal (candidiasis, dermatophytosis), and bacterial infections. CONCLUSIONS: These findings suggest that ES in children indicates not only localized wound-healing impairment, but also systemic immune, developmental, and proliferative dysregulations, emphasizing the need for genetic and mechanistic studies to clarify causal pathways and multidisciplinary surveillance beyond dermatologic care.

Humans

Computational strategies for copy number variation detection, disease association, and beyond.

Copy number variations (CNVs) are key structural variations that contribute to human genetic diversity, evolution, and disease susceptibility. Advances in sequencing technologies and computational methods have improved CNV detection, yet association studies remain challenged by methodological limitations and a lack of standardisation. This review provides an overview of computational strategies for germline CNV detection and disease association. We highlight the value of CNV analysis for uncovering genetic contributions to complex traits and disease risk and outline an analysis workflow including key benchmarking methods. We also discuss current challenges and future directions for advancing CNV detection and association analysis.

Humans

DNA methylation and machine learning: challenges and perspective toward enhanced clinical diagnostics.

DNA methylation is an epigenetic modification that regulates gene expression by adding methyl groups to DNA, affecting cellular function and disease development. Machine learning, a subset of artificial intelligence, analyzes large datasets to identify patterns and make predictions. Over the past two decades, advances in bioinformatics technologies for arrays and sequencing have generated vast amounts of data, leading to the widespread adoption of machine learning methods for analyzing complex biological information for medical problems. This review explores recent advancements in DNA methylation studies that leverage emerging machine learning techniques for more precise, comprehensive, and rapid patient diagnostics based on DNA methylation markers. We present a general workflow for researchers, from clinical research questions to result interpretation and monitoring. Additionally, we showcase successful examples in diagnosing cancer, neurodevelopmental disorders, and multifactorial diseases. Some of these studies have led to the development of diagnostic platforms that have entered the global healthcare market, highlighting the promising future of this field.

Humans