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Circulating tumor DNA (ctDNA) has shown great promise as a biomarker for early detection of cancer. However, due to the low abundance of ctDNA, especially at early stages, it is hard to detect at high accuracies while keeping sequencing costs low. Here we present a pilot stage study to detect large scale somatic copy numbers variations (CNVs), which contribute more molecules to ctDNA signal compared to point mutations, via cell free DNA sequencing. We show that it is possible to detect somatic CNVs in early stage colorectal cancer (CRC) patients and subsequently discriminate them from normal patients. With 25 normal and 24 CRC samples, we achieve 100% specificity (lower bound confidence interval: 86%) and ~79% sensitivity (95% confidence interval: 63% - 95%,), though the performance should be considered with caution given the limited sample size. We report a lack of concordance between the CNVs detected via cfDNA sequencing and CNVs identified in parent tissue samples. However, recent findings suggest that a lack of concordance is expected for CNVs in CRC because of their sub-clonal nature. Finally, the CNVs we detect very likely contribute to cancer progression as they lie in functionally important regions, and have been shown to be associated with CRC specifically. This study paves the path for a larger scale exploration of the potential of CNV detection for both diagnoses and prognoses of cancer., Competing Interests: The authors declare that this study was funded in part by Sequenom Inc. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Background: Atrial fibrillation (AF) is the most commonly encountered arrhythmia and is associated with an elevated risk of stroke. Improving the identification of patients with the highest risk for AF to enable appropriate surveillance and treatment, if necessary, is critical to reducing AF-associated morbidity and mortality. Multiple common single nucleotide polymorphisms (SNPs) are unequivocally associated with the lifetime risk of AF. In the current study we aimed to prospectively validate an AF genetic risk score (GRS) in previously undiagnosed patients at risk for AF., Methods and Findings: Individuals 40 years of age or older with 1 clinical risk factor for AF, presenting with symptoms of AF, or with a first diagnosis of AF, were enrolled for genetic testing and ambulatory cardiac rhythm monitoring with an adhesive patch monitor or a long-term Holter monitor (mean wear time 10 days 21 hours and 13 days 18 hours, respectively). An AF event was the first diagnosis of AF by ECG, patch monitor, or long-term Holter monitor. The AF GRS was determined for each participant based on the weighted contribution of 12 genetic risk loci. Of 904 participants, 85 manifested AF. Their mean age was 66.2 (SD 11.8) years; 38% of participants were male. Participants in the highest quintile of AF GRS were more likely (odds ratio 3.11; 95% CI 1.27-7.58; p = 0.01) to have had an AF event than participants in the lowest quintile after adjusting for age, sex, smoking status, BMI, hypertension, diabetes mellitus, heart failure, and prior myocardial infarction. Study limitations included an ethnically homogenous population, a restricted rhythm monitoring period, and the evolving discovery of SNPs associated with AF., Conclusions: Prospective assessment of a GRS for AF identified participants with elevated risk of AF beyond established clinical criteria. Accordingly, a GRS for AF could be incorporated into overall risk assessment to better identify patients at the highest risk of developing AF, although further testing in larger populations is needed to confirm these findings., Trial Registration: ClinicalTrials.gov NCT01970969.