Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies,American Journal of Human Genetics

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Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies
American Journal of Human Genetics ( IF 9.8 ) Pub Date : 2023-08-17 , DOI: 10.1016/j.ajhg.2023.07.010
Chelsea Lowther ₁ , Elise Valkanas ₂ , Jessica L Giordano ₃ , Harold Z Wang ₄ , Benjamin B Currall ₁ , Kathryn O'Keefe ₄ , Emma Pierce-Hoffman ₅ , Nehir E Kurtas ₁ , Christopher W Whelan ₅ , Stephanie P Hao ₄ , Ben Weisburd ₄ , Vahid Jalili ₅ , Jack Fu ₁ , Isaac Wong ₄ , Ryan L Collins ₆ , Xuefang Zhao ₁ , Christina A Austin-Tse ₇ , Emily Evangelista ₅ , Gabrielle Lemire ₅ , Vimla S Aggarwal ₈ , Diane Lucente ₉ , Laura D Gauthier ₁₀ , Charlotte Tolonen ₁₀ , Nareh Sahakian ₁₀ , Christine Stevens ₅ , Joon-Yong An ₁₁ , Shan Dong ₁₂ , Mary E Norton ₁₃ , Tippi C MacKenzie ₁₄ , Bernie Devlin ₁₅ , Kelly Gilmore ₁₆ , Bradford C Powell ₁₇ , Alicia Brandt ₁₇ , Francesco Vetrini ₁₈ , Michelle DiVito ₃ , Stephan J Sanders ₁₂ , Daniel G MacArthur ₁₉ , Jennelle C Hodge ₁₈ , Anne O'Donnell-Luria ₂₀ , Heidi L Rehm ₄ , Neeta L Vora ₁₆ , Brynn Levy ₈ , Harrison Brand ₁ , Ronald J Wapner ₃ , Michael E Talkowski ₂₁

Affiliation

Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA.
Department of Obstetrics & Gynecology, Columbia University Medical Center, New York, NY, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Department of Pathology, Harvard Medical School, Boston, MA, USA.
Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Data Science Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
School of Biosystem and Biomedical Science, Korea University, Seoul, South Korea.
Department of Psychiatry, UCSF Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
Center for Maternal-Fetal Precision Medicine, University of California, San Francisco, San Francisco, CA, USA; Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California, San Francisco, San Francisco, California, USA.
Center for Maternal-Fetal Precision Medicine, University of California, San Francisco, San Francisco, CA, USA.
Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.
Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Centre for Population Genomics, Garvan Institute of Medical Research, and University of New South Wales Sydney, Sydney, NSW, Australia; Centre for Population Genomics, Murdoch Children's Research Institute, Melbourne, VIC, Australia.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA.
Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, The Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Neurology, Harvard Medical School, Boston, MA, USA; Program in Biological and Biomedical Sciences, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA; Program in Bioinformatics and Integrative Genomics, Division of Medical Sciences, Harvard Medical School, Boston, MA, USA.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

中文翻译：

基因组测序对自闭症谱系障碍和胎儿结构异常诊断评估的系统评价

短读长基因组测序 (GS) 有望成为评估自闭症谱系障碍 (ASD) 和胎儿结构异常 (FSA) 的主要诊断方法。然而，很少有研究根据当前标准护理诊断测试（核型、染色体微阵列（CMA）和外显子组测序（ES））全面评估其性能。为了评估 GS 的临床效用，我们在 1,612 个四重家庭（包括患有 ASD 的个体）和 295 个产前家庭中将其诊断率与这三种测试进行了比较。我们的 GS 分析框架在 7.8% 的 ASD 先证者中发现了诊断变异，几乎是 CMA (4.3%) 的 2 倍，是 ES (2.7%) 的 3 倍。然而，当我们从外显子组数据中系统地捕获拷贝数变异 (CNV) 时，ES 的诊断率 (7.4%) 更接近但没有超过 GS。同样，我们估计 GS 在未选择的 FSA 中可以实现 46.1% 的总体诊断率，这意味着比核型诊断率提高了 17.2%，比 CMA 提高了 14.1%，比带有 CNV 识别的 ES 提高了 4.1%，或者在没有 CNV 发现的情况下提高了 36.1%。总体而言，与 ASD 和 FSA 中所有三种标准护理测试的组合相比，GS 的诊断率分别增加了 0.4% 和 0.8%。这对应于九个 GS 独特的诊断变异，包括 ES 未捕获的外显子中的序列变异、现有标准护理测试无法访问的结构变异 (SV) 以及 GS 分辨率改变变异分类的 SV。总体而言，这项大规模评估表明，GS 显着优于每个单独的护理标准测试，同时也优于所有三种测试的组合，因此值得考虑作为评估 ASD 和 FSA 的一级诊断方法。

更新日期：2023-08-17

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