Analyzing the most frequent disease loci in targeted patient categories optimizes disease gene identification and test accuracy worldwide.

Title

Analyzing the most frequent disease loci in targeted patient categories optimizes disease gene identification and test accuracy worldwide.

Creator

Lebo Roger V; Tonk Vijay S

Publisher

Journal of translational medicine

Date

2015
2015-01

Description

BACKGROUND: Our genomewide studies support targeted testing the most frequent genetic diseases by patient category: (1) pregnant patients, (2) at-risk conceptuses, (3) affected children, and (4) abnormal adults. This approach not only identifies most reported disease causing sequences accurately, but also minimizes incorrectly identified additional disease causing loci. METHODS: Diseases were grouped in descending order of occurrence from four data sets: (1) GeneTests 534 listed population prevalences, (2) 4129 high risk prenatal karyotypes, (3) 1265 affected patient microarrays, and (4) reanalysis of 25,452 asymptomatic patient results screened prenatally for 108 genetic diseases. These most frequent diseases are categorized by transmission: (A) autosomal recessive, (B) X-linked, (C) autosomal dominant, (D) microscopic chromosome rearrangements, (E) submicroscopic copy number changes, and (F) frequent ethnic diseases. RESULTS: Among affected and carrier patients worldwide, most reported mutant genes would be identified correctly according to one of four patient categories from at-risk couples with \textless64 tested genes to affected adults with 314 tested loci. Three clinically reported patient series confirmed this approach. First, only 54 targeted chromosomal sites would have detected all 938 microscopically visible unbalanced karyotypes among 4129 karyotyped POC, CVS, and amniocentesis samples. Second, 37 of 48 reported aneuploid regions were found among our 1265 clinical microarrays confirming the locations of 8 schizophrenia loci and 20 aneuploidies altering intellectual ability, while also identifying 9 of the most frequent deletion syndromes. Third, testing 15 frequent genes would have identified 124 couples with a 1 in 4 risk of a fetus with a recessive disease compared to the 127 couples identified by testing all 108 genes, while testing all mutations in 15 genes could have identified more couples. CONCLUSION: Testing the most frequent disease causing abnormalities in 1 of 8 reported disease loci [\textasciitilde1 of 84 total genes] will identify \textasciitilde 7 of 8 reported abnormal Caucasian newborn genotypes. This would eliminate \textasciitilde8 to 10 of \textasciitilde10 Caucasian newborn gene sequences selected as abnormal that are actually normal variants identified when testing all \textasciitilde2500 diseases looking for the remaining 1 of 8 disease causing genes. This approach enables more accurate testing within available laboratory and reimbursement resources.

Subject

*Genetic Loci; *Genetic Predisposition to Disease; Adult; Child; Chromosomes; Disease/*genetics; European Continental Ancestry Group; Female; Genes; Genetic Testing/*methods; Genetics; Heterozygote; Human/genetics; Humans; Infant; Newborn; Population; Pregnancy; Prenatal Diagnosis; Rare Diseases/genetics; Recessive

Rights

Article information provided for research and reference use only. All rights are retained by the journal listed under publisher and/or the creator(s).

Pages

16–16

Volume

13

Citation

Lebo Roger V; Tonk Vijay S, “Analyzing the most frequent disease loci in targeted patient categories optimizes disease gene identification and test accuracy worldwide.,” NEOMED Bibliography Database, accessed December 3, 2021, https://neomed.omeka.net/items/show/4858.

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