Browsing by Subject "Genetic risk"

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Open Access
Insights into autism spectrum disorder genomic architecture and biology from 71 risk loci
(Cell Press, 2015) Sanders, S. J.; He, X.; Willsey, A. J.; Ercan-Sencicek, A. G.; Samocha, K. E.; Cicek, A. E.; Murtha, M. T.; Bal, V. H.; Bishop, S. L.; Dong, S.; Goldberg, A. P.; Jinlu, C.; Keaney, J. F.; Keaney III, J. F.; Mandell, J. D.; Moreno-De-Luca, D.; Poultney, C. S.; Robinson, E. B.; Smith L.; Solli-Nowlan, T.; Su, M. Y.; Teran, N. A.; Walker, M. F.; Werling, D. M.; Beaudet, A. L.; Cantor, R. M.; Fombonne, E.; Geschwind, D. H.; Grice, D. E.; Lord, C.; Lowe, J. K.; Mane, S. M.; Martin, D.M.; Morrow, E. M.; Talkowski, M. E.; Sutcliffe, J. S.; Walsh, C. A.; Yu, T. W.; Ledbetter, D. H.; Martin, C. L.; Cook, E. H.; Buxbaum, J. D.; Daly, M. J.; Devlin, B.; Roeder, K.; State, M. W.
Analysis of de novo CNVs (dnCNVs) from the full Simons Simplex Collection (SSC) (N = 2,591 families) replicates prior findings of strong association with autism spectrum disorders (ASDs) and confirms six risk loci (1q21.1, 3q29, 7q11.23, 16p11.2, 15q11.2-13, and 22q11.2). The addition of published CNV data from the Autism Genome Project (AGP) and exome sequencing data from the SSC and the Autism Sequencing Consortium (ASC) shows that genes within small de novo deletions, but not within large dnCNVs, significantly overlap the high-effect risk genes identified by sequencing. Alternatively, large dnCNVs are found likely to contain multiple modest-effect risk genes. Overall, we find strong evidence that de novo mutations are associated with ASD apart from the risk for intellectual disability. Extending the transmission and de novo association test (TADA) to include small de novo deletions reveals 71 ASD risk loci, including 6 CNV regions (noted above) and 65 risk genes (FDR ≤ 0.1). Through analysis of de novo mutations in autism spectrum disorder (ASD), Sanders et al. find that small deletions, but not large deletions/duplications, contain one critical gene. Combining CNV and sequencing data, they identify 6 loci and 65 genes associated with ASD.
Open Access
Privacy-preserving genomic testing in the clinic: a model using HIV treatment
(Nature Publishing Group, 2016) Mclaren, P. J.; Raisaro, J. L.; Aouri, M.; Rotger, M.; Ayday, E.; Bartha, I.; Delgado, M. B.; Vallet, Y.; Günthard, H. F.; Cavassini, M.; Furrer, H.; Doco-Lecompte, T.; Marzolini, C.; Schmid, P.; Di Benedetto, C.; Decosterd, L. A.; Fellay, J.; Hubaux, Jean-Pierre; Telenti A.
Purpose:The implementation of genomic-based medicine is hindered by unresolved questions regarding data privacy and delivery of interpreted results to health-care practitioners. We used DNA-based prediction of HIV-related outcomes as a model to explore critical issues in clinical genomics.Methods:We genotyped 4,149 markers in HIV-positive individuals. Variants allowed for prediction of 17 traits relevant to HIV medical care, inference of patient ancestry, and imputation of human leukocyte antigen (HLA) types. Genetic data were processed under a privacy-preserving framework using homomorphic encryption, and clinical reports describing potentially actionable results were delivered to health-care providers.Results:A total of 230 patients were included in the study. We demonstrated the feasibility of encrypting a large number of genetic markers, inferring patient ancestry, computing monogenic and polygenic trait risks, and reporting results under privacy-preserving conditions. The average execution time of a multimarker test on encrypted data was 865 ms on a standard computer. The proportion of tests returning potentially actionable genetic results ranged from 0 to 54%.Conclusions:The model of implementation presented herein informs on strategies to deliver genomic test results for clinical care. Data encryption to ensure privacy helps to build patient trust, a key requirement on the road to genomic-based medicine.