scholarly journals Ending diagnostic odyssey using clinical whole-exome sequencing (CWES)

2021 ◽  
Vol 45 (6) ◽  
pp. 259-266
Author(s):  
Ching-Wan Lam

Abstract Objectives Most rare diseases are genetic diseases. Due to the diversity of rare diseases and the high likelihood of patients with rare diseases to be undiagnosed or misdiagnosed, it is not unusual that these patients undergo a long diagnostic odyssey before they receive a definitive diagnosis. This situation presents a clear need to set up a dedicated clinical service to end the diagnostic odyssey of patients with rare diseases. Methods Therefore, in 2014, we started an Undiagnosed Diseases Program in Hong Kong with the aim of ending the diagnostic odyssey of patients and families with rare diseases by clinical whole-exome sequencing (CWES), who have not received a definitive diagnosis after extensive investigation. Results In this program, we have shown that genetic diseases diagnosed by CWES were different from that using traditional approaches indicating that CWES is an essential tool to diagnose rare diseases and ending diagnostic odysseys. In addition, we identified several novel genes responsible for monogenic diseases. These include the TOP2B gene for autism spectrum disorder, the DTYMK gene for severe cerebral atrophy, the KIF13A gene for a new mosaic ectodermal syndrome associated with hypomelanosis of Ito, and the CDC25B gene for a new syndrome of cardiomyopathy and endocrinopathy. Conclusions With the incorporation of CWES in an Undiagnosed Diseases Program, we have ended diagnostic odysseys of patients with rare diseases in Hong Kong in the past 7 years. In this program, we have shown that CWES is an essential tool to end diagnostic odysseys. With the declining cost of next-generation sequencers and reagents, CWES set-ups are now affordable for clinical laboratories. Indeed, owing to the increasing availability of CWES and treatment modalities for rare diseases, precedence can be given to both common and rare medical conditions.

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alana R. Rodney ◽  
Reuben M. Buckley ◽  
Robert S. Fulton ◽  
Catrina Fronick ◽  
Todd Richmond ◽  
...  

AbstractOver 94 million domestic cats are susceptible to cancers and other common and rare diseases. Whole exome sequencing (WES) is a proven strategy to study these disease-causing variants. Presented is a 35.7 Mb exome capture design based on the annotated Felis_catus_9.0 genome assembly, covering 201,683 regions of the cat genome. Whole exome sequencing was conducted on 41 cats with known and unknown genetic diseases and traits, of which ten cats had matching whole genome sequence (WGS) data available, used to validate WES performance. At 80 × mean exome depth of coverage, 96.4% of on-target base coverage had a sequencing depth > 20-fold, while over 98% of single nucleotide variants (SNVs) identified by WGS were also identified by WES. Platform-specific SNVs were restricted to sex chromosomes and a small number of olfactory receptor genes. Within the 41 cats, we identified 31 previously known causal variants and discovered new gene candidate variants, including novel missense variance for polycystic kidney disease and atrichia in the Peterbald cat. These results show the utility of WES to identify novel gene candidate alleles for diseases and traits for the first time in a feline model.


2019 ◽  
Author(s):  
Go Hun Seo ◽  
Taeho Kim ◽  
Jung-young Park ◽  
Jungsul Lee ◽  
Sehwan Kim ◽  
...  

AbstractPurposeEVIDENCE, an automated interpretation system, has been developed to facilitate the entire process of whole exome sequencing (WES) analyses. This study investigated the diagnostic yield of EVIDENCE in patients suspected genetic disorders.MethodsDNA from 330 probands (age range, 0–68 years) with suspected genetic disorders were subjected to WES. Candidate variants were identified by EVIDENCE and confirmed by testing family members and/or clinical reassessments.ResultsThe average number of overlapping organ categories per patient was 4.5 ± 5.0. EVIDENCE reported a total 244 variants in 215 (65.1%) of the 330 probands. After clinical reassessment and/or family member testing, 196 variants were identified in 171 probands (51.8%), including 115 novel variants. These variants were confirmed as being responsible for 146 genetic disorders. One hundred-seven (54.6%) of the 196 variants were categorized as pathogenic or likely pathogenic before, and 146 (74.6%) after, clinical assessment and/or family member testing. Factors associated with a variant being confirmed as causative include rules, such as PVS1, PS1, PM1, PM5, and PP5, and similar symptom scores between that variant and a patient’s phenotype.ConclusionThis new, automated variant interpretation system facilitated the diagnosis of various genetic diseases with a 51% improvement in diagnostic yield.


2017 ◽  
Vol 92 (3) ◽  
pp. 281-289 ◽  
Author(s):  
T.B. Balci ◽  
T. Hartley ◽  
Y. Xi ◽  
D.A. Dyment ◽  
C.L. Beaulieu ◽  
...  

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Hosneara Akter ◽  
Mohammad Shahnoor Hossain ◽  
Nushrat Jahan Dity ◽  
Md. Atikur Rahaman ◽  
K. M. Furkan Uddin ◽  
...  

AbstractCollectively, rare genetic diseases affect a significant number of individuals worldwide. In this study, we have conducted whole-exome sequencing (WES) and identified underlying pathogenic or likely pathogenic variants in five children with rare genetic diseases. We present evidence for disease-causing autosomal recessive variants in a range of disease-associated genes such as DHH-associated 46,XY gonadal dysgenesis (GD) or 46,XY sex reversal 7, GNPTAB-associated mucolipidosis II alpha/beta (ML II), BBS1-associated Bardet–Biedl Syndrome (BBS), SURF1-associated Leigh Syndrome (LS) and AP4B1-associated spastic paraplegia-47 (SPG47) in unrelated affected members from Bangladesh. Our analysis pipeline detected three homozygous mutations, including a novel c. 863 G > C (p.Pro288Arg) variant in DHH, and two compound heterozygous variants, including two novel variants: c.2972dupT (p.Met991Ilefs*) in GNPTAB and c.229 G > C (p.Gly77Arg) in SURF1. All mutations were validated by Sanger sequencing. Collectively, this study adds to the genetic heterogeneity of rare genetic diseases and is the first report elucidating the genetic profile of (consanguineous and nonconsanguineous) rare genetic diseases in the Bangladesh population.


2015 ◽  
Vol 89 (3) ◽  
pp. 275-284 ◽  
Author(s):  
S.L. Sawyer ◽  
T. Hartley ◽  
D.A. Dyment ◽  
C.L. Beaulieu ◽  
J. Schwartzentruber ◽  
...  

2020 ◽  
Author(s):  
Alana R. Rodney ◽  
Reuben M. Buckley ◽  
Robert S. Fulton ◽  
Catrina Fronick ◽  
Todd Richmond ◽  
...  

AbstractOver 94 million domestic cats are considered pets, who, as our companions, are also susceptible to cancers, common and rare diseases. Whole exome sequencing (WES) is a cost-effective strategy to study their putative disease-causing variants. Presented is ~35.8 Mb exome capture design based on the annotated Felis_catus_9.0 genome assembly, covering 201,683 regions of the cat genome. WES was conducted on 41 cats from various breeds with known and unknown diseases and traits, including 10 cats with prior whole genome sequence (WGS) data available, to test WES capture probe performance. A WES and WGS comparison was completed to understand variant discovery capability of each platform. At ~80x exome coverage, the percent of on-target base coverage >20x was 96.4% with an average of 10.4% off-target. For variant discovery, greater than 98% of WGS SNPs were also discovered by WES. Platform specific variants were mainly restricted to a small number of sex chromosome and olfactory receptor genes. Within the 41 cats with ~31 diseases and normal traits, 45 previously known disease or trait causal variants were observed, such as Persian progressive retinal degeneration and hydrocephalus. Novel candidate variants for polycystic kidney disease and atrichia in the Peterbald breed were also identified as well as a new cat patient with a known variant for cystinuria. These results show the discovery potential of deep exome sequencing to validate existing disease gene models and identify novel gene candidate alleles for many common and rare diseases in cats.


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