Identifying rare, medically-relevant genetic variation in a diverse population: opportunities and pitfalls

Purpose To evaluate the effectiveness and specificity of population-based genomic screening in Alabama. Methods The Alabama Genomic Health Initiative (AGHI) has enrolled and evaluated 5,369 participants for the presence of pathogenic/likely pathogenic (P/LP) variants using the Illumina Global Screening Array (GSA), with validation of all P/LP variants via Sanger sequencing in a CLIA-certified laboratory before return of results. Results Among 131 variants identified by the GSA that were evaluated by Sanger sequencing, 67 (51%) were false positives (FP). For 39 of the 67 FP variants, a benign/likely benign variant was present at or near the targeted P/LP variant. Importantly, African-Americans were significantly enriched for FP variants, likely due to a higher rate of non-targeted alternative alleles close to array-targeted P/LP variants. Conclusion In AGHI, we have implemented an array-based process to screen for highly penetrant genetic variants in actionable disease genes. We demonstrate the need for clinical validation of array-identified variants in direct-to-consumer or population testing, especially for diverse populations.

[1]  E. Clayton Be Ready to Talk With Parents About Direct-to-Consumer Genetic Testing. , 2019, JAMA pediatrics.

[2]  Nikki M. Carroll,et al.  Physician Experience with Direct-To-Consumer Genetic Testing in Kaiser Permanente , 2019, Journal of personalized medicine.

[3]  Stephanie A. Bien,et al.  The Future of Genomic Studies Must Be Globally Representative: Perspectives from PAGE. , 2019, Annual review of genomics and human genetics.

[4]  A. Philippakis,et al.  The "All of Us" Research Program. , 2019, The New England journal of medicine.

[5]  Caroline F Wright,et al.  Assessing the analytical validity of SNP-chips for detecting very rare pathogenic variants: implications for direct-to-consumer genetic testing , 2019, bioRxiv.

[6]  Caroline F. Wright,et al.  Very rare pathogenic genetic variants detected by SNP-chips are usually false positives: implications for direct-to-consumer genetic testing , 2019 .

[7]  michel More than 26 million people have taken an at-home ancestry test - e-traces , 2019 .

[8]  C. Reuter,et al.  Direct-to-consumer raw genetic data and third-party interpretation services: more burden than bargain? , 2018, Genetics in medicine : official journal of the American College of Medical Genetics.

[9]  H. LaDuca,et al.  False-positive results released by direct-to-consumer genetic tests highlight the importance of clinical confirmation testing for appropriate patient care , 2018, Genetics in Medicine.

[10]  Chunlei Liu,et al.  ClinVar: improving access to variant interpretations and supporting evidence , 2017, Nucleic Acids Res..

[11]  James J. Cummings,et al.  Consumer use and response to online third‐party raw DNA interpretation services , 2017, Molecular genetics & genomic medicine.

[12]  R. Myers,et al.  Genomic sequencing identifies secondary findings in a cohort of parent study participants , 2017, bioRxiv.

[13]  W. Chung,et al.  Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics , 2016, Genetics in Medicine.

[14]  Peter Szolovits,et al.  Genetic Misdiagnoses and the Potential for Health Disparities. , 2016, The New England journal of medicine.

[15]  Ricardo Villamarín-Salomón,et al.  ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..

[16]  James Y. Zou Analysis of protein-coding genetic variation in 60,706 humans , 2015, Nature.

[17]  Gabor T. Marth,et al.  A global reference for human genetic variation , 2015, Nature.

[18]  Bale,et al.  Standards and Guidelines for the Interpretation of Sequence Variants: A Joint Consensus Recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology , 2015, Genetics in Medicine.

[19]  Avni Santani,et al.  Actionable exomic incidental findings in 6503 participants: challenges of variant classification , 2015, Genome research.

[20]  J. Shendure,et al.  A general framework for estimating the relative pathogenicity of human genetic variants , 2014, Nature Genetics.

[21]  Marc S. Williams,et al.  ACMG recommendations for reporting of incidental findings in clinical exome and genome sequencing , 2013, Genetics in Medicine.

[22]  Kenny Q. Ye,et al.  An integrated map of genetic variation from 1,092 human genomes , 2012, Nature.

[23]  Jacob A. Tennessen,et al.  Evolution and Functional Impact of Rare Coding Variation from Deep Sequencing of Human Exomes , 2012, Science.

[24]  G Lippi,et al.  Direct‐to‐consumer testing: more risks than opportunities , 2011, International journal of clinical practice.

[25]  Simon Cawley,et al.  Next generation genome-wide association tool: design and coverage of a high-throughput European-optimized SNP array. , 2011, Genomics.

[26]  Josyf Mychaleckyj,et al.  Robust relationship inference in genome-wide association studies , 2010, Bioinform..

[27]  K. Manly,et al.  Genomics, prior probability, and statistical tests of multiple hypotheses. , 2004, Genome research.

[28]  Weihua Chang,et al.  Whole-genome genotyping with the single-base extension assay , 2005, Nature Methods.