Erin Rooney Riggs, Erica F Andersen, Athena M Cherry, Sibel Kantarci, Hutton Kearney, Ankita Patel, Gordana Raca, Deborah I Ritter, Sarah T South, Erik C Thorland, Daniel Pineda-Alvarez, Swaroop Aradhya, Christa Lese Martin <<<

PURPOSE: Copy-number analysis to detect disease-causing losses and gains across the genome is recommended for the evaluation of individuals with neurodevelopmental disorders and/or multiple congenital anomalies, as well as for fetuses with ultrasound abnormalities. In the decade that this analysis has been in widespread clinical use, tremendous strides have been made in understanding the effects of copy-number variants (CNVs) in both affected individuals and the general population. However, continued broad implementation of array and next-generation sequencing-based technologies will expand the types of CNVs encountered in the clinical setting, as well as our understanding of their impact on human health.METHODS: To assist clinical laboratories in the classification and reporting of CNVs, irrespective of the technology used to identify them, the American College of Medical Genetics and Genomics has developed the following professional standards in collaboration with the National Institutes of Health (NIH)-funded Clinical Genome Resource (ClinGen) project.RESULTS: This update introduces a quantitative, evidence-based scoring framework; encourages the implementation of the five-tier classification system widely used in sequence variant classification; and recommends "uncoupling" the evidence-based classification of a variant from its potential implications for a particular individual.CONCLUSION: These professional standards will guide the evaluation of constitutional CNVs and encourage consistency and transparency across clinical laboratories. <<<

Yajie Zhao, Eugene J Gardner, Marcus A Tuke, Huairen Zhang, Maik Pietzner, Mine Koprulu, Raina Y Jia, Katherine S Ruth, Andrew R Wood, Robin N Beaumont, Jessica Tyrrell, Samuel E Jones, Hana Lango Allen, Felix R Day, Claudia Langenberg, Timothy M Frayling, Michael N Weedon, John R B Perry, Ken K Ong, Anna Murray <<<

PURPOSE: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes.METHODS: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data.RESULTS: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 × 10-8), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P < 7 × 10-6).CONCLUSION: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking. <<<

PURPOSE: The study aimed to determine the diagnostic yield, optimal timing, and methodology of next generation sequencing data reanalysis in suspected Mendelian disorders.METHODS: We conducted a systematic review and meta-analysis of studies that conducted data reanalysis in patients with suspected Mendelian disorders. Random effects model was used to pool the estimated outcome with subgroup analysis stratified by timing, sequencing methodology, sample size, segregation, use of research validation, and artificial intelligence (AI) variant curation tools.RESULTS: A search of PubMed, Embase, Scopus, and Web of Science between 2007 and 2021 yielded 9327 articles, of which 29 were selected. Significant heterogeneity was noted between studies. Reanalysis had an overall diagnostic yield of 0.10 (95% CI = 0.06-0.13). Literature updates accounted for most new diagnoses. Diagnostic yield was higher after 24 months, although this was not statistically significant. Increased diagnoses were obtained with research validation and data sharing. AI-based tools did not adversely affect reanalysis diagnostic rate.CONCLUSION: Next generation sequencing data reanalysis can improve diagnostic yield. Owing to the heterogeneity of the studies, the optimal time to reanalysis and the impact of AI-based tools could not be determined with confidence. We propose standardized guidelines for future studies to reduce heterogeneity and improve the quality of the conclusions. <<<

O Y Olivia Tse, Peiyong Jiang, Suk Hang Cheng, Wenlei Peng, Huimin Shang, John Wong, Stephen L Chan, Liona C Y Poon, Tak Y Leung, K C Allen Chan, Rossa W K Chiu, Y M Dennis Lo <<<

5-Methylcytosine (5mC) is an important type of epigenetic modification. Bisulfite sequencing (BS-seq) has limitations, such as severe DNA degradation. Using single molecule real-time sequencing, we developed a methodology to directly examine 5mC. This approach holistically examined kinetic signals of a DNA polymerase (including interpulse duration and pulse width) and sequence context for every nucleotide within a measurement window, termed the holistic kinetic (HK) model. The measurement window of each analyzed double-stranded DNA molecule comprised 21 nucleotides with a cytosine in a CpG site in the center. We used amplified DNA (unmethylated) and M.SssI-treated DNA (methylated) (M.SssI being a CpG methyltransferase) to train a convolutional neural network. The area under the curve for differentiating methylation states using such samples was up to 0.97. The sensitivity and specificity for genome-wide 5mC detection at single-base resolution reached 90% and 94%, respectively. The HK model was then tested on human-mouse hybrid fragments in which each member of the hybrid had a different methylation status. The model was also tested on human genomic DNA molecules extracted from various biological samples, such as buffy coat, placental, and tumoral tissues. The overall methylation levels deduced by the HK model were well correlated with those by BS-seq ( = 0.99; < 0.0001) and allowed the measurement of allele-specific methylation patterns in imprinted genes. Taken together, this methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses. <<<