Targeting de novo loss-of-function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project.
Targeting de novo loss-of-function variants in constrained disease genes improves diagnostic rates in the 100,000 Genomes Project.
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DOI:
10.1007/s00439-022-02509-x
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发表时间:
2023-03
期刊:
影响因子:
5.3
通讯作者:
中科院分区:
文献类型:
--
作者:
Genome sequencing was first offered clinically in the UK through the 100,000 Genomes Project (100KGP). Analysis was restricted to predefined gene panels associated with the patient’s phenotype. However, panels rely on clearly characterised phenotypes and risk missing diagnoses outside of the panel(s) applied. We propose a complementary method to rapidly identify pathogenic variants, including those missed by 100KGP methods. The Loss-of-function Observed/Expected Upper-bound Fraction (LOEUF) score quantifies gene constraint, with low scores correlated with haploinsufficiency. We applied DeNovoLOEUF, a filtering strategy to sequencing data from 13,949 rare disease trios in the 100KGP, by filtering for rare, de novo, loss-of-function variants in disease genes with a LOEUF score < 0.2. We compared our findings with the corresponding patient’s diagnostic reports. 324/332 (98%) of the variants identified using DeNovoLOEUF were diagnostic or partially diagnostic (whereby the variant was responsible for some of the phenotype). We identified 39 diagnoses that were “missed” by 100KGP standard analyses, which are now being returned to patients. We have demonstrated a highly specific and rapid method with a 98% positive predictive value that has good concordance with standard analysis, low false-positive rate, and can identify additional diagnoses. Globally, as more patients are being offered genome sequencing, we anticipate that DeNovoLOEUF will rapidly identify new diagnoses and facilitate iterative analyses when new disease genes are discovered. The online version contains supplementary material available at 10.1007/s00439-022-02509-x.
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DOI:
10.1126/science.1215040
发表时间:
2012-02-17
期刊:
Science (New York, N.Y.)
影响因子:
--
作者:
MacArthur DG;Balasubramanian S;Frankish A;Huang N;Morris J;Walter K;Jostins L;Habegger L;Pickrell JK;Montgomery SB;Albers CA;Zhang ZD;Conrad DF;Lunter G;Zheng H;Ayub Q;DePristo MA;Banks E;Hu M;Handsaker RE;Rosenfeld JA;Fromer M;Jin M;Mu XJ;Khurana E;Ye K;Kay M;Saunders GI;Suner MM;Hunt T;Barnes IH;Amid C;Carvalho-Silva DR;Bignell AH;Snow C;Yngvadottir B;Bumpstead S;Cooper DN;Xue Y;Romero IG;1000 Genomes Project Consortium;Wang J;Li Y;Gibbs RA;McCarroll SA;Dermitzakis ET;Pritchard JK;Barrett JC;Harrow J;Hurles ME;Gerstein MB;Tyler-Smith C
通讯作者:
Tyler-Smith C
影响因子:
5.3
作者:
Austin-Tse CA;Jobanputra V;Perry DL;Bick D;Taft RJ;Venner E;Gibbs RA;Young T;Barnett S;Belmont JW;Boczek N;Chowdhury S;Ellsworth KA;Guha S;Kulkarni S;Marcou C;Meng L;Murdock DR;Rehman AU;Spiteri E;Thomas-Wilson A;Kearney HM;Rehm HL;Medical Genome Initiative*
通讯作者:
Medical Genome Initiative*
影响因子:
64.8
作者:
Karczewski, Konrad J;Francioli, Laurent C;MacArthur, Daniel G
通讯作者:
MacArthur, Daniel G
影响因子:
82.9
作者:
Rehm HL
通讯作者:
Rehm HL
影响因子:
3.7
作者:
Seaby EG;Rehm HL;O'Donnell-Luria A
通讯作者:
O'Donnell-Luria A