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Arnaout, Ramy

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Arnaout

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Ramy

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Arnaout, Ramy
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    Autism gene Ube3a and seizures impair sociability by repressing VTA Cbln1
    (2017) Krishnan, Vaishnav; Stoppel, David C.; Nong, Yi; Johnson, Mark; Nadler, Monica; Ozkaynak, Ekim; Teng, Brian L.; Nagakura, Ikue; Mohammad, Fahim; Silva, Michael; Peterson, Sally; Cruz, Tristan J.; Kasper, Ekkehard; Arnaout, Ramy; Anderson, Matthew
    Summary Maternally inherited 15q11-13 chromosomal triplications cause a frequent and highly penetrant autism linked to increased gene dosages of UBE3A, which both possesses ubiquitin-ligase and transcriptional co-regulatory functions. Here, using in vivo mouse genetics, we show that increasing UBE3A in the nucleus down-regulates glutamatergic synapse organizer cerebellin-1 (Cbln1) that is needed for sociability in mice. Epileptic seizures also repress Cbln1 and are found to expose sociability impairments in mice with asymptomatic increases of UBE3A. This Ube3a-seizure synergy maps to glutamate neurons of the midbrain ventral tegmental area (VTA) where Cbln1 deletions impair sociability and weaken glutamatergic transmission. We provide preclinical evidence that viral-vector-based chemogenetic activations of, or Cbln1 restorations in VTA glutamatergic neurons rescues sociability deficits induced by Ube3a and/or seizures. Our results suggest a gene × seizure interaction in VTA glutamatergic neurons that impairs sociability by downregulating Cbln1, a key node in the expanding protein interaction network of autism genes.
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    The Landscape of Inappropriate Laboratory Testing: A 15-Year Meta-Analysis
    (Public Library of Science, 2013) Zhi, Ming; Ding, Eric L.; Theisen-Toupal, Jesse C.; Whelan, Julia S; Arnaout, Ramy
    Background: Laboratory testing is the single highest-volume medical activity and drives clinical decision-making across medicine. However, the overall landscape of inappropriate testing, which is thought to be dominated by repeat testing, is unclear. Systematic differences in initial vs. repeat testing, measurement criteria, and other factors would suggest new priorities for improving laboratory testing. Methods: A multi-database systematic review was performed on published studies from 1997–2012 using strict inclusion and exclusion criteria. Over- vs. underutilization, initial vs. repeat testing, low- vs. high-volume testing, subjective vs. objective appropriateness criteria, and restrictive vs. permissive appropriateness criteria, among other factors, were assessed. Results: Overall mean rates of over- and underutilization were 20.6% (95% CI 16.2–24.9%) and 44.8% (95% CI 33.8–55.8%). Overutilization during initial testing (43.9%; 95% CI 35.4–52.5%) was six times higher than during repeat testing (7.4%; 95% CI 2.5–12.3%; P for stratum difference <0.001). Overutilization of low-volume tests (32.2%; 95% CI 25.0–39.4%) was three times that of high-volume tests (10.2%; 95% CI 2.6–17.7%; P<0.001). Overutilization measured according to restrictive criteria (44.2%; 95% CI 36.8–51.6%) was three times higher than for permissive criteria (12.0%; 95% CI 8.0–16.0%; P<0.001). Overutilization measured using subjective criteria (29.0%; 95% CI 21.9–36.1%) was nearly twice as high as for objective criteria (16.1%; 95% CI 11.0–21.2%; P = 0.004). Together, these factors explained over half (54%) of the overall variability in overutilization. There were no statistically significant differences between studies from the United States vs. elsewhere (P = 0.38) or among chemistry, hematology, microbiology, and molecular tests (P = 0.05–0.65) and no robust statistically significant trends over time. Conclusions: The landscape of overutilization varies systematically by clinical setting (initial vs. repeat), test volume, and measurement criteria. Underutilization is also widespread, but understudied. Expanding the current focus on reducing repeat testing to include ordering the right test during initial evaluation may lead to fewer errors and better care.
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    Advantages and Limitations of Anticipating Laboratory Test Results from Regression- and Tree-Based Rules Derived from Electronic Health-Record Data
    (Public Library of Science, 2014) Mohammad, Fahim; Theisen-Toupal, Jesse C.; Arnaout, Ramy
    Laboratory testing is the single highest-volume medical activity, making it useful to ask how well one can anticipate whether a given test result will be high, low, or within the reference interval (“normal”). We analyzed 10 years of electronic health records—a total of 69.4 million blood tests—to see how well standard rule-mining techniques can anticipate test results based on patient age and gender, recent diagnoses, and recent laboratory test results. We evaluated rules according to their positive and negative predictive value (PPV and NPV) and area under the receiver-operator characteristic curve (ROC AUCs). Using a stringent cutoff of PPV and/or NPV≥0.95, standard techniques yield few rules for sendout tests but several for in-house tests, mostly for repeat laboratory tests that are part of the complete blood count and basic metabolic panel. Most rules were clinically and pathophysiologically plausible, and several seemed clinically useful for informing pre-test probability of a given result. But overall, rules were unlikely to be able to function as a general substitute for actually ordering a test. Improving laboratory utilization will likely require different input data and/or alternative methods.
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    Robust estimates of overall immune-repertoire diversity from high-throughput measurements on samples
    (Nature Publishing Group, 2016) Kaplinsky, Joseph; Arnaout, Ramy
    The diversity of an organism's B- and T-cell repertoires is both clinically important and a key measure of immunological complexity. However, diversity is hard to estimate by current methods, because of inherent uncertainty in the number of B- and T-cell clones that will be missing from a blood or tissue sample by chance (the missing-species problem), inevitable sampling bias, and experimental noise. To solve this problem, we developed Recon, a modified maximum-likelihood method that outputs the overall diversity of a repertoire from measurements on a sample. Recon outputs accurate, robust estimates by any of a vast set of complementary diversity measures, including species richness and entropy, at fractional repertoire coverage. It also outputs error bars and power tables, allowing robust comparisons of diversity between individuals and over time. We apply Recon to in silico and experimental immune-repertoire sequencing data sets as proof of principle for measuring diversity in large, complex systems.
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    Customized Care 2020: How Medical Sequencing and Network Biology Will Enable Personalized Medicine
    (Biology Reports Ltd, 2009) Boguski, Mark S.; Arnaout, Ramy; Hill, Colin
    Applications of next-generation nucleic acid sequencing technologies will lead to the development of precision diagnostics that will, in turn, be a major technology enabler of precision medicine. Terabyte-scale, multidimensional data sets derived using these technologies will be used to reverse engineer the specific disease networks that underlie individual patients’ conditions. Modeling and simulation of these networks in the presence of virtual drugs, and combinations of drugs, will identify the most efficacious therapy for precision medicine and customized care. In coming years the practice of medicine will routinely employ network biology analytics supported by high-performance supercomputing.
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    Quantitative deep sequencing reveals dynamic HIV-1 escape and large population shifts during CCR5 antagonist therapy in vivo
    (Public Library of Science, 2009) Korber, Bette; Russ, Carsten; Lo, Chien-Chi; Leitner, Thomas; Gaschen, Brian; Theiler, James; Paredes, Roger; Su, Zhaohui; Gulick, Roy M.; Greaves, Wayne; Coakley, Eoin; Flexner, Charles; Nusbaum, Chad; Tsibris, Athe; Arnaout, Ramy; Hughes, Michael; Kuritzkes, Daniel
    High-throughput sequencing platforms provide an approach for detecting rare HIV-1 variants and documenting more fully quasispecies diversity. We applied this technology to the V3 loop-coding region of env in samples collected from 4 chronically HIV-infected subjects in whom CCR5 antagonist (vicriviroc [VVC]) therapy failed. Between 25,000–140,000 amplified sequences were obtained per sample. Profound baseline V3 loop sequence heterogeneity existed; predicted CXCR4-using populations were identified in a largely CCR5-using population. The V3 loop forms associated with subsequent virologic failure, either through CXCR4 use or the emergence of high-level VVC resistance, were present as minor variants at 0.8–2.8% of baseline samples. Extreme, rapid shifts in population frequencies toward these forms occurred, and deep sequencing provided a detailed view of the rapid evolutionary impact of VVC selection. Greater V3 diversity was observed post-selection. This previously unreported degree of V3 loop sequence diversity has implications for viral pathogenesis, vaccine design, and the optimal use of HIV-1 CCR5 antagonists.
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    Specificity and Overlap in Gene Segment-defined Antibody Repertoires
    (BioMed Central, 2005) Arnaout, Ramy
    Background: To date several studies have sought to catalog the full suite of antibodies that humans naturally produce against single antigens or other specificities (repertoire). Here we analyze the properties of all sequenced repertoires in order to better understand the specificity of antibody responses. Specifically, we ask whether the large-scale sequencing of antibody repertoires might provide a diagnostic tool for detecting antigen exposure. We do this by examining the overlap in V\(_{H-}\), D\(_-\), and J\(_{H-}\) segment usage among sequenced repertoires. Results: We find that repertoire overlap in V\(_{H-}\), D\(_-\), and J\(_{H-}\) segment use is least for V\(_H\) segments and greatest for J\(_H\) segments, consistent with there being more V\(_H\) than J\(_H\) segments in the human genome. We find that for any two antigens chosen at random, chances are 90 percent that their repertoires' V\(_H\) segments will overlap by less than half, and 98 percent that their VDJ\(_H\) combinations will overlap by ≤10 percent. We ran computer simulations to test whether enrichment for specific VDJ\(_H\) combinations could be detected in "antigen-exposed" populations, and found that enrichment is detectable with moderate-to-high sensitivity and high specificity, even when some VDJ\(_H\) combinations are not represented at all in some test sets. Conclusion: Thus, as large-scale sequencing becomes cost-effective for clinical testing, we suggest that sequencing an individual's expressed antibody repertoire has the potential to become a useful diagnostic modality.