Prevalence estimation of ATTRv in China based on genetic databases
Amyloid transthyretin (ATTR) is divided into either hereditary (ATTRv) or sporadic (ATTRwt) and ATTRv is a rare hereditary disease transmitted as an autosomal dominant manner. Its global prevalence is traditionally estimated as 5,000 to 10,000 persons. However, it may be underestimated and the exact...
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Published in | Frontiers in genetics Vol. 14; p. 1126836 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Switzerland
Frontiers Media S.A
13.04.2023
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Subjects | |
Online Access | Get full text |
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Summary: | Amyloid transthyretin (ATTR) is divided into either hereditary (ATTRv) or sporadic (ATTRwt) and ATTRv is a rare hereditary disease transmitted as an autosomal dominant manner. Its global prevalence is traditionally estimated as 5,000 to 10,000 persons. However, it may be underestimated and the exact prevalence of ATTRv in China mainland remains unknown.
The Genome Aggregation database (gnomAD) database (containing 125,748 exomes) and two genomic sequencing databases--China Metabolic Analytics Project (ChinaMAP) (containing 10588 individuals) and Amcarelab gene database (containing 45392 exomes), were integrated to estimate the prevalence of ATTRv in the world and mainland Chinese populations. Pathogenic variants allele frequency and the prevalence of ATTRv was calculated.
Six variants, counting 470 alleles, were defined as pathogenic variants in gnomAD. The prevalence of ATTRv in the world population was 57.4/100,000. Two variants (2 allele counts) and 15 variants (34 individuals) were defined as pathogenic variants in the ChinaMAP database and the Amcarelab exome database, respectively. Thus, the estimated prevalence interval of ATTRv in mainland China was 18.9/100,000-74,9/100,000.
The present study demonstrated that the previous prevalence was greatly underestimated using traditional methods. Therefore, raising awareness of the disease is essential for recognizing ATTRv in its early stage. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Michel Satya Naslavsky, University of São Paulo, Brazil Edited by: Sarah H. Elsea, Baylor College of Medicine, United States Reviewed by: Dario Ronchi, University of Milan, Italy |
ISSN: | 1664-8021 1664-8021 |
DOI: | 10.3389/fgene.2023.1126836 |