Genomic medicine for kidney disease

被引:99
|
作者
Groopman, Emily E. [1 ]
Rasouly, Hila Milo [1 ]
Gharavi, Ali G. [1 ]
机构
[1] Columbia Univ, Coll Phys & Surg, Div Nephrol, 1150 St Nicholas Ave,Russ Berrie Pavil 412C, New York, NY 10032 USA
基金
美国国家卫生研究院;
关键词
DOMINANT POLYCYSTIC KIDNEY; CONGENITAL NEPHROTIC SYNDROME; COPY-NUMBER; CLINICAL EXOME; INCIDENTAL FINDINGS; ALPORT SYNDROME; SECONDARY FINDINGS; GITELMAN-SYNDROME; AMERICAN-COLLEGE; GENETIC-VARIANTS;
D O I
10.1038/nrneph.2017.167
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
Technologies such as next-generation sequencing and chromosomal microarray have advanced the understanding of the molecular pathogenesis of a variety of renal disorders. Genetic findings are increasingly used to inform the clinical management of many nephropathies, enabling targeted disease surveillance, choice of therapy, and family counselling. Genetic analysis has excellent diagnostic utility in paediatric nephrology, as illustrated by sequencing studies of patients with congenital anomalies of the kidney and urinary tract and steroid-resistant nephrotic syndrome. Although additional investigation is needed, pilot studies suggest that genetic testing can also provide similar diagnostic insight among adult patients. Reaching a genetic diagnosis first involves choosing the appropriate testing modality, as guided by the clinical presentation of the patient and the number of potential genes associated with the suspected nephropathy. Genome-wide sequencing increases diagnostic sensitivity relative to targeted panels, but holds the challenges of identifying causal variants in the vast amount of data generated and interpreting secondary findings. In order to realize the promise of genomic medicine for kidney disease, many technical, logistical, and ethical questions that accompany the implementation of genetic testing in nephrology must be addressed. The creation of evidence-based guidelines for the utilization and implementation of genetic testing in nephrology will help to translate genetic knowledge into improved clinical outcomes for patients with kidney disease.
引用
收藏
页码:83 / 104
页数:22
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