Combinatorial batching of DNA for ultralow-cost detection of pathogenic variants.

BACKGROUND: Next-generation sequencing (NGS) based population screening holds great promise for disease prevention and earlier diagnosis, but the costs associated with screening millions of humans remain prohibitive. New methods for population genetic testing that lower the costs of NGS without compromising diagnostic power are needed. METHODS: We developed double batched sequencing where DNA samples are batch-sequenced twice - directly pinpointing individuals with rare variants. We sequenced batches of at-birth blood spot DNA using a commercial 113-gene panel in an explorative (n = 100) and a validation (n = 100) cohort of children who went on to develop pediatric cancers. All results were benchmarked against individual whole genome sequencing data. RESULTS: We demonstrated fully replicable detection of cancer-causing germline variants, with positive and negative predictive values of 100% (95% CI, 0.91-1.00 and 95% CI, 0.98-1.00, respectively). Pathogenic and clinically actionable variants were detected in RB1, TP53, BRCA2, APC, and 19 other genes. Analyses of larger batches indicated that our approach is highly scalable, yielding more than 95% cost reduction or less than 3 cents per gene screened for rare disease-causing mutations. We also show that double batched sequencing could cost-effectively prevent childhood cancer deaths through broad genomic testing. CONCLUSIONS: Our ultracheap genetic diagnostic method, which uses existing sequencing hardware and standard newborn blood spots, should readily open up opportunities for population-wide risk stratification using genetic screening across many fields of clinical genetics and genomics.

Risk of Early-Onset Depression Associated With Polygenic Liability, Parental Psychiatric History, and Socioeconomic Status.

Importance: Combining information on polygenic risk scores (PRSs) with other known risk factors could potentially improve the identification of risk of depression in the general population. However, to our knowledge, no study has estimated the association of PRS with the absolute risk of depression, and few have examined combinations of the PRS and other important risk factors, including parental history of psychiatric disorders and socioeconomic status (SES), in the identification of depression risk. Objective: To assess the individual and joint associations of PRS, parental history, and SES with relative and absolute risk of early-onset depression. Design, Setting, and Participants: This case-cohort study included participants from the iPSYCH2012 sample, a case-cohort sample of all singletons born in Denmark between May 1, 1981, and December 31, 2005. Hazard ratios (HRs) and absolute risks were estimated using Cox proportional hazards regression for case-cohort designs. Exposures: The PRS for depression; SES measured using maternal educational level, maternal marital status, and paternal employment; and parental history of psychiatric disorders (major depression, bipolar disorder, other mood or psychotic disorders, and other psychiatric diagnoses). Main Outcomes and Measures: Hospital-based diagnosis of depression from inpatient, outpatient, or emergency settings. Results: Participants included 17 098 patients with depression (11 748 [68.7%] female) and 18 582 (9429 [50.7%] male) individuals randomly selected from the base population. The PRS, parental history, and lower SES were all significantly associated with increased risk of depression, with HRs ranging from 1.32 (95% CI, 1.29-1.35) per 1-SD increase in PRS to 2.23 (95% CI, 1.81-2.64) for maternal history of mood or psychotic disorders. Fully adjusted models had similar effect sizes, suggesting that these risk factors do not confound one another. Absolute risk of depression by the age of 30 years differed substantially, depending on an individual's combination of risk factors, ranging from 1.0% (95% CI, 0.1%-2.0%) among men with high SES in the bottom 2% of the PRS distribution to 23.7% (95% CI, 16.6%-30.2%) among women in the top 2% of PRS distribution with a parental history of psychiatric disorders. Conclusions and Relevance: This study suggests that current PRSs for depression are not more likely to be associated with major depressive disorder than are other known risk factors; however, they may be useful for the identification of risk in conjunction with other risk factors.

Evaluation of whole genome amplified DNA to decrease material expenditure and increase quality.

AIM: The overall aim of this study is to evaluate whole genome amplification of DNA extracted from dried blood spot samples. We wish to explore ways of optimizing the amplification process, while decreasing the amount of input material and inherently the cost. Our primary focus of optimization is on the amount of input material, the amplification reaction volume, the number of replicates and amplification time and temperature. Increasing the quality of the amplified DNA and the subsequent results of array genotyping is a secondary aim of this project. METHODS: This study is based on DNA extracted from dried blood spot samples. The extracted DNA was subsequently whole genome amplified using the REPLIg kit and genotyped on the PsychArray BeadChip (assessing > 570,000 SNPs genome wide). We used Genome Studio to evaluate the quality of the genotype data by call rates and log R ratios. RESULTS: The whole genome amplification process is robust and does not vary between replicates. Altering amplification time, temperature or number of replicates did not affect our results. We found that spot size i.e. amount of input material could be reduced without compromising the quality of the array genotyping data. We also showed that whole genome amplification reaction volumes can be reduced by a factor of 4, without compromising the DNA quality. DISCUSSION: Whole genome amplified DNA samples from dried blood spots is well suited for array genotyping and produces robust and reliable genotype data. However, the amplification process introduces additional noise to the data, making detection of structural variants such as copy number variants difficult. With this study, we explore ways of optimizing the amplification protocol in order to reduce noise and increase data quality. We found, that the amplification process was very robust, and that changes in amplification time or temperature did not alter the genotyping calls or quality of the array data. Adding additional replicates of each sample also lead to insignificant changes in the array data. Thus, the amount of noise introduced by the amplification process was consistent regardless of changes made to the amplification protocol. We also explored ways of decreasing material expenditure by reducing the spot size or the amplification reaction volume. The reduction did not affect the quality of the genotyping data.