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Uncovering the Prevalence of Cystinosis through Genetic Analysis

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Abstract Background Cystinosis is a metabolic disease characterized by the accumulation of cystine most often presenting in an infantile nephropathic form caused by pathogenic variants in the CTNS gene. It is characterized by progressive loss of glomerular function leading to renal failure by the first decade of life, making early diagnosis crucial to improving outcomes. This study seeks to estimate the prevalence of cystinosis using a population genetics approach. Methods The Human Genome Mutation Database (HGMD) was used to identify known pathogenic variants in CTNS , and the 1000 Genomes (1KG) database was used to identify CTNS variants in a cohort representing a healthy population. These two databases were intersected to identify disease-causing variants and their carriers in the general population. The Hardy-Weinberg equilibrium was used to calculate expected carrier and affected rates for cystinosis. Results The allele frequency for all disease-causing alleles was calculated to be 0.016. The predicted affected rate was calculated to be 0.00027 (approximately 1:3680), and the predicted carrier rate was 0.032 (approximately 1:30). Conclusion Compared to the reported clinical prevalence of between 1 in 100,000 to 1 in 200,000, the prevalence of cystinosis in this study was calculated to be 1 in 3,680. This significantly higher result may be due to the underdiagnosis of cystinosis or variable expressivity of variants presenting with a broad range of disease severity. These results support the proposal of newborn screening for early diagnosis and improved outcomes in infantile nephropathic cystinosis.
Title: Uncovering the Prevalence of Cystinosis through Genetic Analysis
Description:
Abstract Background Cystinosis is a metabolic disease characterized by the accumulation of cystine most often presenting in an infantile nephropathic form caused by pathogenic variants in the CTNS gene.
It is characterized by progressive loss of glomerular function leading to renal failure by the first decade of life, making early diagnosis crucial to improving outcomes.
This study seeks to estimate the prevalence of cystinosis using a population genetics approach.
Methods The Human Genome Mutation Database (HGMD) was used to identify known pathogenic variants in CTNS , and the 1000 Genomes (1KG) database was used to identify CTNS variants in a cohort representing a healthy population.
These two databases were intersected to identify disease-causing variants and their carriers in the general population.
The Hardy-Weinberg equilibrium was used to calculate expected carrier and affected rates for cystinosis.
Results The allele frequency for all disease-causing alleles was calculated to be 0.
016.
The predicted affected rate was calculated to be 0.
00027 (approximately 1:3680), and the predicted carrier rate was 0.
032 (approximately 1:30).
Conclusion Compared to the reported clinical prevalence of between 1 in 100,000 to 1 in 200,000, the prevalence of cystinosis in this study was calculated to be 1 in 3,680.
This significantly higher result may be due to the underdiagnosis of cystinosis or variable expressivity of variants presenting with a broad range of disease severity.
These results support the proposal of newborn screening for early diagnosis and improved outcomes in infantile nephropathic cystinosis.

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