Validation of a clinical-grade assay to measure donor-derived cell-free DNA in solid organ transplant recipients

[Abstract] The use of circulating cell-free DNA (cfDNA) as a biomarker in transplant recipients offers advantages over invasive tissue biopsy as a quantitative measure for detection of transplant rejection and immunosuppression optimization. However, the fraction of donor-derived cfDNA (dd-cfDNA) in transplant recipient plasma is low and challenging to quantify. Previously reported methods to measure dd-cfDNA require donor and recipient genotyping, which is impractical in clinical settings and adds cost. We developed a targeted next-generation sequencing assay that uses 266 single-nucleotide polymorphisms to accurately quantify dd-cfDNA in transplant recipients without separate genotyping. Analytical performance of the assay was characterized and validated using 1117 samples comprising the National Institute for Standards and Technology Genome in a Bottle human reference genome, independently validated reference materials, and clinical samples. The assay quantifies the fraction of dd-cfDNA in both unrelated and related donor-recipient pairs. The dd-cfDNA assay can reliably measure dd-cfDNA (limit of blank, 0.10%; limit of detection, 0.16%; limit of quantification, 0.20%) across the linear quantifiable range (0.2% to 16%) with across-run CVs of 6.8%. Precision was also evaluated for independently processed clinical sample replicates and is similar to across-run precision. Application of the assay to clinical samples from heart transplant recipients demonstrated increased levels of dd-cfDNA in patients with biopsy-confirmed rejection and decreased levels of dd-cfDNA after successful rejection treatment. This noninvasive clinical-grade sequencing assay can be completed within 3 days, providing the practical turnaround time preferred for transplanted organ surveillance

Assessing the Evolutionary Impact of Amino Acid Mutations in the Human Genome

Quantifying the distribution of fitness effects among newly arising mutations in the human genome is key to resolving important debates in medical and evolutionary genetics. Here, we present a method for inferring this distribution using Single Nucleotide Polymorphism (SNP) data from a population with non-stationary demographic history (such as that of modern humans). Application of our method to 47,576 coding SNPs found by direct resequencing of 11,404 protein coding-genes in 35 individuals (20 European Americans and 15 African Americans) allows us to assess the relative contribution of demographic and selective effects to patterning amino acid variation in the human genome. We find evidence of an ancient population expansion in the sample with African ancestry and a relatively recent bottleneck in the sample with European ancestry. After accounting for these demographic effects, we find strong evidence for great variability in the selective effects of new amino acid replacing mutations. In both populations, the patterns of variation are consistent with a leptokurtic distribution of selection coefficients (e.g., gamma or log-normal) peaked near neutrality. Specifically, we predict 27–29% of amino acid changing (nonsynonymous) mutations are neutral or nearly neutral (|s|<0.01%), 30–42% are moderately deleterious (0.01%<|s|<1%), and nearly all the remainder are highly deleterious or lethal (|s|>1%). Our results are consistent with 10–20% of amino acid differences between humans and chimpanzees having been fixed by positive selection with the remainder of differences being neutral or nearly neutral. Our analysis also predicts that many of the alleles identified via whole-genome association mapping may be selectively neutral or (formerly) positively selected, implying that deleterious genetic variation affecting disease phenotype may be missed by this widely used approach for mapping genes underlying complex traits

Cell-Free DNA and Active Rejection in Kidney Allografts

Histologic analysis of the allograft biopsy specimen is the standard method used to differentiate rejection from other injury in kidney transplants. Donor-derived cell-free DNA (dd-cfDNA) is a noninvasive test of allograft injury that may enable more frequent, quantitative, and safer assessment of allograft rejection and injury status. To investigate this possibility, we prospectively collected blood specimens at scheduled intervals and at the time of clinically indicated biopsies. In 102 kidney recipients, we measured plasma levels of dd-cfDNA and correlated the levels with allograft rejection status ascertained by histology in 107 biopsy specimens. The dd-cfDNA level discriminated between biopsy specimens showing any rejection (T cell-mediated rejection or antibody-mediated rejection [ABMR]) and controls (no rejection histologically), P1% indicate a probability of active rejection

An IL28B Genotype-Based Clinical Prediction Model for Treatment of Chronic Hepatitis C

BACKGROUND:Genetic variation in IL28B and other factors are associated with sustained virological response (SVR) after pegylated-interferon/ribavirin treatment for chronic hepatitis C (CHC). Using data from the HALT-C Trial, we developed a model to predict a patient's probability of SVR based on IL28B genotype and clinical variables. METHODS:HALT-C enrolled patients with advanced CHC who had failed previous interferon-based treatment. Subjects were re-treated with pegylated-interferon/ribavirin during trial lead-in. We used step-wise logistic regression to calculate adjusted odds ratios (aOR) and create the predictive model. Leave-one-out cross-validation was used to predict a priori probabilities of SVR and determine area under the receiver operator characteristics curve (AUC). RESULTS:Among 646 HCV genotype 1-infected European American patients, 14.2% achieved SVR. IL28B rs12979860-CC genotype was the strongest predictor of SVR (aOR, 7.56; p<.0001); the model also included HCV RNA (log10 IU/ml), AST:ALT ratio, Ishak fibrosis score and prior ribavirin treatment. For this model AUC was 78.5%, compared to 73.0% for a model restricted to the four clinical predictors and 60.0% for a model restricted to IL28B genotype (p<0.001). Subjects with a predicted probability of SVR <10% had an observed SVR rate of 3.8%; subjects with a predicted probability >10% (43.3% of subjects) had an SVR rate of 27.9% and accounted for 84.8% of subjects actually achieving SVR. To verify that consideration of both IL28B genotype and clinical variables is required for treatment decisions, we calculated AUC values from published data for the IDEAL Study. CONCLUSION:A clinical prediction model based on IL28B genotype and clinical variables can yield useful individualized predictions of the probability of treatment success that could increase SVR rates and decrease the frequency of futile treatment among patients with CHC

Evolutionary Processes Acting on Candidate cis-Regulatory Regions in Humans Inferred from Patterns of Polymorphism and Divergence

Analysis of polymorphism and divergence in the non-coding portion of the human genome yields crucial information about factors driving the evolution of gene regulation. Candidate cis-regulatory regions spanning more than 15,000 genes in 15 African Americans and 20 European Americans were re-sequenced and aligned to the chimpanzee genome in order to identify potentially functional polymorphism and to characterize and quantify departures from neutral evolution. Distortions of the site frequency spectra suggest a general pattern of selective constraint on conserved non-coding sites in the flanking regions of genes (CNCs). Moreover, there is an excess of fixed differences that cannot be explained by a Gamma model of deleterious fitness effects, suggesting the presence of positive selection on CNCs. Extensions of the McDonald-Kreitman test identified candidate cis-regulatory regions with high probabilities of positive and negative selection near many known human genes, the biological characteristics of which exhibit genome-wide trends that differ from patterns observed in protein-coding regions. Notably, there is a higher probability of positive selection in candidate cis-regulatory regions near genes expressed in the fetal brain, suggesting that a larger portion of adaptive regulatory changes has occurred in genes expressed during brain development. Overall we find that natural selection has played an important role in the evolution of candidate cis-regulatory regions throughout hominid evolution

Genetic Testing for Early Detection of Individuals at Risk of Coronary Heart Disease and Monitoring Response to Therapy: Challenges and Promises

Coronary heart disease (CHD) often presents suddenly with little warning. Traditional risk factors are inadequate to identify the asymptomatic high-risk individuals. Early identification of patients with subclinical coronary artery disease using noninvasive imaging modalities would allow the early adoption of aggressive preventative interventions. Currently, it is impractical to screen the entire population with noninvasive coronary imaging tools. The use of relatively simple and inexpensive genetic markers of increased CHD risk can identify a population subgroup in which benefit of atherosclerotic imaging modalities would be increased despite nominal cost and radiation exposure. Additionally, genetic markers are fixed and need only be measured once in a patient’s lifetime, can help guide therapy selection, and may be of utility in family counseling

Cost Effectiveness of Sequencing 34 Cancer-Associated Genes as an Aid for Treatment Selection in Patients with Metastatic Melanoma.

ObjectiveTo determine whether a next-generation sequencing (NGS) panel of 34 cancer-associated genes would cost-effectively aid in the treatment selection for patients with metastatic melanoma, compared with a single-site BRAF V600 mutation test.MethodsA decision model was developed to estimate the costs and health outcomes of the two test strategies. The cost effectiveness of these two strategies was analyzed from a payer perspective over a 2-year time horizon with model parameters taken from the literature.ResultsIn the base case, the gene sequencing panel strategy resulted in a cost of US$120,022 and 0.721 quality-adjusted life years (QALYs) per patient, whereas the single-site mutation test strategy resulted in a cost of US$128,965 and 0.704 QALYs. Thus, the gene sequencing panel strategy cost US$8943 less per patient and increased QALYs by 0.0174 per patient. Sensitivity analyses showed that, compared with the single-site mutation test strategy, the gene sequencing panel strategy had a 90.9$79.6 million and a gain of 155 QALYs

Cost Effectiveness of Sequencing 34 Cancer-Associated Genes as an Aid for Treatment Selection in Patients with Metastatic Melanoma.

ObjectiveTo determine whether a next-generation sequencing (NGS) panel of 34 cancer-associated genes would cost-effectively aid in the treatment selection for patients with metastatic melanoma, compared with a single-site BRAF V600 mutation test.MethodsA decision model was developed to estimate the costs and health outcomes of the two test strategies. The cost effectiveness of these two strategies was analyzed from a payer perspective over a 2-year time horizon with model parameters taken from the literature.ResultsIn the base case, the gene sequencing panel strategy resulted in a cost of US$120,022 and 0.721 quality-adjusted life years (QALYs) per patient, whereas the single-site mutation test strategy resulted in a cost of US$128,965 and 0.704 QALYs. Thus, the gene sequencing panel strategy cost US$8943 less per patient and increased QALYs by 0.0174 per patient. Sensitivity analyses showed that, compared with the single-site mutation test strategy, the gene sequencing panel strategy had a 90.9$79.6 million and a gain of 155 QALYs