INTERACTION BETWEEN HERPESVIRUSES AND GENETIC VARIATION IN SCHIZOPHRENIA PATHOGENESIS: A CANDIDATE GENE APPROACH

Schizophrenia is a debilitating disorder characterized by disturbances in thought with lifetime prevalence of one percent. The public health burden of schizophrenia due to medical care, social disability, and co-morbid conditions is substantial. Genetic variation, viral infection, or interaction of the two could influence schizophrenia risk. An understanding of these disease pathways could lead to strategies for prevention and treatment of schizophrenia. We used a positional approach to identify schizophrenia candidate genes that could interact with cytomegalovirus and herpes simplex viruses (HSV). We focused on three groups of genes: TNF and MICB near D6S2672, which was associated with schizophrenia and CMV in our previous studies; IL1â, IL1RN, and IL10, immune related genes associated with schizophrenia in published articles; and IL-18, IL18BP, IL18RAP, IL12A, and IL12B, positional candidate genes in the IL-18 pathway. We used multiple case-control and family-based samples to test these hypotheses. We comprehensively sequenced TNF, and genotyped eight SNPs in a case-control sample. We detected no significant associations. We used a dual-luciferase expression assay to quantify TNF expression driven by common promoter haplotypes. Differences in TNF expression did not correlate with schizophrenia. To localize the D6S2672 association, we genotyped 26 SNPs spanning 100kb in a case-control sample. Based on suggestive associations, we selected five SNPs to assay among additional samples. A SNP in MICB was associated with schizophrenia in these samples. The opposite allele was associated with HSV1 in two non-schizophrenia groups. We used comprehensive sequencing data to select tag SNPs at IL1â, IL1RN, IL10, and IL-18 pathway genes. Tag SNPs were evaluated in a case-control sample. In IL1â, IL1RN, and IL10 significant associations were not detected. However, meta-analysis of rs16944 (IL1â -511) studies suggests modest, but significant, risk for schizophrenia in Caucasian samples. In IL-18 pathway genes, a IL18RAP SNP was associated with schizophrenia, the opposite allele was associated with HSV1. Identified associations with schizophrenia may be due to host gene-virus interaction. These genetic variants could clarify which patients are vulnerable to viral infection. Treatment or prevention may be feasible, if our results are confirmed. Further replicate studies are warranted, as are functional studies of associated polymorphisms

Rare loss of function variants in candidate genes and risk of colorectal cancer

Although ~ 25% of colorectal cancer or polyp (CRC/P) cases show familial aggregation, current germline genetic testing identifies a causal genotype in the 16 major genes associated with high penetrance CRC/P in only 20% of these cases. As there are likely other genes underlying heritable CRC/P, we evaluated the association of variation at novel loci with CRC/P. We evaluated 158 a priori selected candidate genes by comparing the number of rare potentially disruptive variants (PDVs) found in 84 CRC/P cases without an identified CRC/P risk-associated variant and 2440 controls. We repeated this analysis using an additional 73 CRC/P cases. We also compared the frequency of PDVs in select genes among CRC/P cases with two publicly available data sets. We found a significant enrichment of PDVs in cases vs. controls: 20% of cases vs. 11.5% of controls with ≥ 1 PDV (OR = 1.9, p = 0.01) in the original set of cases. Among the second cohort of CRC/P cases, 18% had a PDV, significantly different from 11.5% (p = 0.02). Logistic regression, adjusting for ancestry and multiple testing, indicated association between CRC/P and PDVs in NTHL1 (p = 0.0001), BRCA2 (p = 0.01) and BRIP1 (p = 0.04). However, there was no significant difference in the frequency of PDVs at each of these genes between all 157 CRC/P cases and two publicly available data sets. These results suggest an increased presence of PDVs in CRC/P cases and support further investigation of the association of NTHL1, BRCA2 and BRIP1 variation with CRC/P

Actionable, Pathogenic Incidental Findings in 1,000 Participants’ Exomes

The incorporation of genomics into medicine is stimulating interest on the return of incidental findings (IFs) from exome and genome sequencing. However, no large-scale study has yet estimated the number of expected actionable findings per individual; therefore, we classified actionable pathogenic single-nucleotide variants in 500 European- and 500 African-descent participants randomly selected from the National Heart, Lung, and Blood Institute Exome Sequencing Project. The 1,000 individuals were screened for variants in 114 genes selected by an expert panel for their association with medically actionable genetic conditions possibly undiagnosed in adults. Among the 1,000 participants, 585 instances of 239 unique variants were identified as disease causing in the Human Gene Mutation Database (HGMD). The primary literature supporting the variants’ pathogenicity was reviewed. Of the identified IFs, only 16 unique autosomal-dominant variants in 17 individuals were assessed to be pathogenic or likely pathogenic, and one participant had two pathogenic variants for an autosomal-recessive disease. Furthermore, one pathogenic and four likely pathogenic variants not listed as disease causing in HGMD were identified. These data can provide an estimate of the frequency (∼3.4% for European descent and ∼1.2% for African descent) of the high-penetrance actionable pathogenic or likely pathogenic variants in adults. The 23 participants with pathogenic or likely pathogenic variants were disproportionately of European (17) versus African (6) descent. The process of classifying these variants underscores the need for a more comprehensive and diverse centralized resource to provide curated information on pathogenicity for clinical use to minimize health disparities in genomic medicine

Landscape of somatic single nucleotide variants and indels in colorectal cancer and impact on survival

Colorectal cancer (CRC) is a biologically heterogeneous disease. To characterize its mutational profile, we conduct targeted sequencing of 205 genes for 2,105 CRC cases with survival data. Our data shows several findings in addition to enhancing the existing knowledge of CRC. We identify PRKCI, SPZ1, MUTYH, MAP2K4, FETUB, and TGFBR2 as additional genes significantly mutated in CRC. We find that among hypermutated tumors, an increased mutation burden is associated with improved CRC-specific survival (HR=0.42, 95% CI: 0.21-0.82). Mutations in TP53 are associated with poorer CRC-specific survival, which is most pronounced in cases carrying TP53 mutations with predicted 0% transcriptional activity (HR=1.53, 95% CI: 1.21-1.94). Furthermore, we observe differences in mutational frequency of several genes and pathways by tumor location, stage, and sex. Overall, this large study provides deep insights into somatic mutations in CRC, and their potential relationships with survival and tumor features. Large scale sequencing study is of paramount importance to unravel the heterogeneity of colorectal cancer. Here, the authors sequenced 205 cancer genes in more than 2000 tumours and identified additional mutated driver genes, determined that mutational burden and specific mutations in TP53 are associated with survival odds

CSER and eMERGE: current and potential state of the display of genetic information in the electronic health record

Objective Clinicians’ ability to use and interpret genetic information depends upon how those data are displayed in electronic health records (EHRs). There is a critical need to develop systems to effectively display genetic information in EHRs and augment clinical decision support (CDS)

Clinical Sequencing Exploratory Research Consortium: Accelerating Evidence-Based Practice of Genomic Medicine

Despite rapid technical progress and demonstrable effectiveness for some types of diagnosis and therapy, much remains to be learned about clinical genome and exome sequencing (CGES) and its role within the practice of medicine. The Clinical Sequencing Exploratory Research (CSER) consortium includes 18 extramural research projects, one National Human Genome Research Institute (NHGRI) intramural project, and a coordinating center funded by the NHGRI and National Cancer Institute. The consortium is exploring analytic and clinical validity and utility, as well as the ethical, legal, and social implications of sequencing via multidisciplinary approaches; it has thus far recruited 5,577 participants across a spectrum of symptomatic and healthy children and adults by utilizing both germline and cancer sequencing. The CSER consortium is analyzing data and creating publically available procedures and tools related to participant preferences and consent, variant classification, disclosure and management of primary and secondary findings, health outcomes, and integration with electronic health records. Future research directions will refine measures of clinical utility of CGES in both germline and somatic testing, evaluate the use of CGES for screening in healthy individuals, explore the penetrance of pathogenic variants through extensive phenotyping, reduce discordances in public databases of genes and variants, examine social and ethnic disparities in the provision of genomics services, explore regulatory issues, and estimate the value and downstream costs of sequencing. The CSER consortium has established a shared community of research sites by using diverse approaches to pursue the evidence-based development of best practices in genomic medicine

Actionable exomic incidental findings in 6503 participants: challenges of variant classification

Recommendations for laboratories to report incidental findings from genomic tests have stimulated interest in such results. In order to investigate the criteria and processes for assigning the pathogenicity of specific variants and to estimate the frequency of such incidental findings in patients of European and African ancestry, we classified potentially actionable pathogenic single-nucleotide variants (SNVs) in all 4300 European- and 2203 African-ancestry participants sequenced by the NHLBI Exome Sequencing Project (ESP). We considered 112 gene-disease pairs selected by an expert panel as associated with medically actionable genetic disorders that may be undiagnosed in adults. The resulting classifications were compared to classifications from other clinical and research genetic testing laboratories, as well as with in silico pathogenicity scores. Among European-ancestry participants, 30 of 4300 (0.7%) had a pathogenic SNV and six (0.1%) had a disruptive variant that was expected to be pathogenic, whereas 52 (1.2%) had likely pathogenic SNVs. For African-ancestry participants, six of 2203 (0.3%) had a pathogenic SNV and six (0.3%) had an expected pathogenic disruptive variant, whereas 13 (0.6%) had likely pathogenic SNVs. Genomic Evolutionary Rate Profiling mammalian conservation score and the Combined Annotation Dependent Depletion summary score of conservation, substitution, regulation, and other evidence were compared across pathogenicity assignments and appear to have utility in variant classification. This work provides a refined estimate of the burden of adult onset, medically actionable incidental findings expected from exome sequencing, highlights challenges in variant classification, and demonstrates the need for a better curated variant interpretation knowledge base

Utilization and utility of clinical laboratory reports with graphical elements

Background: Graphical reports that contain charts, images, and tables have potential to convey information more effectively than text-based reports; however, studies have not measured how much clinicians value such features. We sought to identify factors that might influence the utilization of reports with graphical elements postulating that this is a surrogate for relative clinical utility of these graphical elements. Materials and Methods: We implemented a pilot project at ARUP laboratories to develop online enhanced laboratory test reports that contained graphical elements. We monitored on-demand clinician access to reports generated for 48 reportable tests over 22 months. We evaluated utilization of reports with graphical elements by clinicians at all institutions that use ARUP as a reference laboratory using descriptive statistics, regression, and meta-analysis tools to evaluate groups of similar test reports. Results: Median download rate by test was 8.6% with high heterogeneity in download rates between tests. Test reports with additional graphical elements were not necessarily downloaded more often than reports without these elements. Recently implemented tests and tests reporting abnormal results were associated with higher download rates (P < 0.01). Higher volume tests were associated with lower download rates (P = 0.03). Conclusions: In select cases graphical information may be clinically useful, particularly for less frequently ordered tests and in on reports of abnormal results. The utilization data presented could be used as a reference point for other laboratories planning on implementing graphical reporting. However, between-test heterogeneity was high and in many cases graphical elements may add little clinical utility, particularly if these merely reinforce information already contained in text based reports

Modeling the impact of data sharing on variant classification

ObjectiveMany genetic variants are classified, but many more are variants of uncertain significance (VUS). Clinical observations of patients and their families may provide sufficient evidence to classify VUS. Understanding how long it takes to accumulate sufficient patient data to classify VUS can inform decisions in data sharing, disease management, and functional assay development.Materials and methodsOur software models the accumulation of clinical evidence (and excludes all other types of evidence) to measure their unique impact on variant interpretation. We illustrate the time and probability for VUS classification when laboratories share evidence, when they silo evidence, and when they share only variant interpretations.ResultsUsing conservative assumptions for frequencies of observed clinical evidence, our models show the probability of classifying rare pathogenic variants with an allele frequency of 1/100&nbsp;000 increases from less than 25% with no data sharing to nearly 80% after one year when labs share data, with nearly 100% classification after 5 years. Conversely, our models found that extremely rare (1/1&nbsp;000&nbsp;000) variants have a low probability of classification using only clinical data.DiscussionThese results quantify the utility of data sharing and demonstrate the importance of alternative lines of evidence for interpreting rare variants. Understanding variant classification circumstances and timelines provides valuable insight for data owners, patients, and service providers. While our modeling parameters are based on our own assumptions of the rate of accumulation of clinical observations, users may download the software and run simulations with updated parameters.ConclusionsThe modeling software is available at https://github.com/BRCAChallenge/classification-timelines

A bayesian approach to laboratory utilization management

Background: Laboratory utilization management describes a process designed to increase healthcare value by altering requests for laboratory services. A typical approach to monitor and prioritize interventions involves audits of laboratory orders against specific criteria, defined as rule-based laboratory utilization management. This approach has inherent limitations. First, rules are inflexible. They adapt poorly to the ambiguity of medical decision-making. Second, rules judge the context of a decision instead of the patient outcome allowing an order to simultaneously save a life and break a rule. Third, rules can threaten physician autonomy when used in a performance evaluation. Methods: We developed an alternative to rule-based laboratory utilization. The core idea comes from a formula used in epidemiology to estimate disease prevalence. The equation relates four terms: the prevalence of disease, the proportion of positive tests, test sensitivity and test specificity. When applied to a laboratory utilization audit, the formula estimates the prevalence of disease (pretest probability [PTP]) in the patients tested. The comparison of PTPs among different providers, provider groups, or patient cohorts produces an objective evaluation of laboratory requests. We demonstrate the model in a review of tests for enterovirus (EV) meningitis. Results: The model identified subpopulations within the cohort with a low prevalence of disease. These low prevalence groups shared demographic and seasonal factors known to protect against EV meningitis. This suggests too many orders occurred from patients at low risk for EV. Conclusion: We introduce a new method for laboratory utilization management programs to audit laboratory services