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- Brownstein, Catherine A., et al.
(författare)
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An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge
- 2014
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Ingår i: Genome Biology. - : Springer Science and Business Media LLC. - 1465-6906 .- 1474-760X. ; 15:3, s. R53-
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Tidskriftsartikel (refereegranskat)abstract
- Background: There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. Results: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. Conclusions: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups.
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- Bennet, Anna M, et al.
(författare)
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Genetic association of sequence variants near AGER/NOTCH4 and dementia.
- 2011
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Ingår i: Journal of Alzheimer's disease : JAD. - 1875-8908. ; 24:3, s. 475-84
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Tidskriftsartikel (refereegranskat)abstract
- We performed a survey of sequence variation in a series of 20 genes involved in inflammation-related pathways for association with dementia risk in twin and unrelated case-control samples consisting in total of 1462 Swedish dementia casesand 1929 controls. For a total of 218 tested genetic markers, strong evidence was obtained implicating a region near AGER and NOTCH4 on chromosome 6p with replication across both samples and maximum combined significance at marker rs1800625 (OR = 1.37, 95% CI 1.19–1.56, p = 1.36×10(–6)). Imputation of the associated genomic interval provided an improved signal atrs8365, near the 3UTR of AGER (p = 7.34×10(–7)). The associated region extends 120 kb encompassing 11 candidate genes.While AGER encodes a key receptor for amyloid-β protein, an analysis of network context based upon genes now confirmed to contribute to dementia risk (AβPP, PSEN1, PSEN2, CR1, CLU, PICALM, and APOE) suggested strong functional coupling to NOTCH4, with no significant coupling to the remaining candidates. The implicated region occurs in the broad HLA locus on chromosome 6p, but associated markers were not in strong LD with known variants that regulate HLA gene function, suggesting that this may represent a signal distinct from immune-system pathways.
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- Franco, M, et al.
(författare)
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Prediction of response to anti-cancer drugs becomes robust via network integration of molecular data
- 2019
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Ingår i: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9:1, s. 2379-
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Tidskriftsartikel (refereegranskat)abstract
- Despite the widening range of high-throughput platforms and exponential growth of generated data volume, the validation of biomarkers discovered from large-scale data remains a challenging field. In order to tackle cancer heterogeneity and comply with the data dimensionality, a number of network and pathway approaches were invented but rarely systematically applied to this task. We propose a new method, called NEAmarker, for finding sensitive and robust biomarkers at the pathway level. scores from network enrichment analysis transform the original space of altered genes into a lower-dimensional space of pathways. These dimensions are then correlated with phenotype variables. The method was first tested using in vitro data from three anti-cancer drug screens and then on clinical data of The Cancer Genome Atlas. It proved superior to the single-gene and alternative enrichment analyses in terms of (1) universal applicability to different data types with a possibility of cross-platform integration, (2) consistency of the discovered correlates between independent drug screens, and (3) ability to explain differential survival of treated patients. Our new screen of anti-cancer compounds validated the performance of multivariate models of drug sensitivity. The previously proposed methods of enrichment analysis could achieve comparable levels of performance in certain tests. However, only our method could discover predictors of both in vitro response and patient survival given administration of the same drug.
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