How ultra-rare is danon disease? an estimate of prevalence based on multiple data sources

Background

Danon disease (DD) is an ultra-rare, sex-linked genetic cardiomyopathy caused by LAMP2 deficiency which affects multiple organs but predominantly manifests as hypertrophic cardiomyopathy (HCM) often leading to severe heart failure. LAMP2 deficiency is a leading target for gene therapy, but lack of prevalence data makes determining potential clinical impact difficult.

Purpose

We evaluated multiple existing data sources to estimate the prevalence of clinical DD and underlying LAMP2 variants.

Methods

DD prevalence estimates were derived based on several approaches: 1) published estimates of DD prevalence in HCM populations were used to estimate a composite prevalence in the overall HCM population, 2) loss-of-function (LoF) LAMP2 variants in genomic databases (gnomAd, AllOfUs, UK Biobank) were used to estimate overall DD prevalence, and 3) the TriNetX EHR database was employed to estimate the number of diagnosed US DD patients, identified with at least 1 instance of ICD10 code E74.05.

Results

See Table 1.

Estimates based on the published literature considered only DD with HCM phenotype. As LAMP2 LoF variants conferring DD risk are also expected to be present in dilated cardiomyopathy and pre-symptomatic cases, estimations beyond the medical literature were appropriate. Differences in the estimates based on the genomic data sources gnomAd, AllOfUs, and the UK Biobank could be explained by recruitment ascertainment, age-distribution, or other factors. In particular, the UK Biobank enrolled persons over 40 years of age, which is beyond the life expectancy of most male DD patients. Application of the 374.05 LAMP2 deficiency ICD10 code (approved in 2024) yielded only 240 EHR-identified DD cases, highlighting the likely profound under-diagnosis of this ultra-rare condition.

Conclusion

Using different approaches to calculating the prevalence of DD resulted in an estimated prevalence range of 240 (estimated diagnosed) to 11,807 (population-based genomic testing) patients. This analysis highlights the need in rare and ultra-rare conditions to look at multiple data sources, taking into consideration their strengths and weaknesses (over versus under diagnosis), to inform prevalence calculations. Continued efforts to improve the DD diagnosis rate and accurately estimate DD prevalence are needed as DD-targeted therapies are developed.For image description, please refer to the figure legend and surrounding text.