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Divya Narayanan,1 Garrick Wallstrom,2 John Rodriguez,1 Donna Welch,1 Matthew Chapin,1 Paul Arrigg,3,4 Rajkumar Patil,1 Mark Abelson1,4,5 1Ora, Inc, Andover, MA, USA; 2Statistics and Data Corporation, Tempe, AZ, USA; 3Joslin Diabetes Center, Boston, MA, USA; 4Ophthalmology, Harvard Medical School, Boston, MA, USA; 5Ophthalmology, Massachusetts Eye and Ear, Boston, MA, USACorrespondence: Divya NarayananOra, Inc., 300 Brickstone Square, Andover, MA 01810, USATel +1 978-685-8900Fax +1 978-689-0020Email dnarayanan@oraclinical.comPurpose: Early detection and treatment of age-related macular degeneration require a clear understanding of the early progress of the disease. The purpose of this study was to investigate whether minimal macular ophthalmoscopic changes corresponded to changes in visual function.Methods: Color macular photos from a group of older subjects who were classified as grade 0 on AREDS simplified grading were further evaluated by a retinal specialist using 5x magnification for possible minimal macular anomalies. Group 0-A (N = 15) were defined as subjects with no visible macular anomalies while Group 0-B (N = 19) comprised subjects for whom minimal macular mottling, pigment changes or very small drusen (< 63 μm) were observed in the study eye. All subjects had best VA of 20/25 or better and had no evidence of other retinal diseases in the study eye. All subjects underwent a series of visual function tests such as standard ETDRS VA, low luminance ETDRS VA, Pelli-Robson contrast sensitivity, variable contrast flicker (VCF) sensitivity, and reading speed (words per minute, wpm) using both MNRead and low luminance reading on a tablet.Results: There was no significant difference between the mean age between the two groups (74.8 ± 5.2 years for 0-A vs 74.5 ± 4.4 for 0-B, p = 0.82). None of the visual function tests identified any significant difference between the two groups. Mean ETDRS VA was 0.0 ± 0.11 for 0-A subjects and 0.08 ± 0.12 for 0-B (p = 0.063). Mean Pelli-Robson log contrast sensitivity was 1.75 ± 0.29 for 0-A and 1.78 ± 0.17 for the 0-B group (p = 0.73). VCF threshold was 0.47 ± 0.25 for 0-A and 0.43 ± 0.22 for 0-B (p = 0.64). Reading speed using MNRead was 214 ± 47.4 wpm for 0-A and 210 ± 64.7 for 0-B (p = 0.85). Low luminance tablet reading speed was 137 ± 71.8 wpm for 0-A and 151 ± 39.4 (0-B) (p = 0.49).Conclusion: A panel of psychophysical tests did not demonstrate significant differences between subjects with and without minimal macular changes.Keywords: macula, visual function, AMD

John D Rodriguez,1 Keith Lane,1 David A Hollander,1,2 Aron Shapiro,1 Sunita Saigal,1 Andrew J Hertsenberg,1 Garrick Wallstrom,3 Divya Narayanan,1 Endri Angjeli,1 Mark B Abelson1,4 1Ora, Inc., Andover, MA, USA; 2Jules Stein Eye Institute, University of California, Los Angeles, CA, USA; 3Statistics and Data Corporation, Tempe, AZ, USA; 4Department of Ophthalmology, Harvard Medical School, Boston, MA, USA Purpose: To identify parameters from cone function and recovery after photostress that detect functional deficits in early non-exudative age-related macular degeneration (AMD) and to determine the repeatability of these parameters. Methods: Cone-mediated visual function recovery after photostress was examined in three groups of subjects: young normal subjects (ages 20–29; N=8), older normal subjects (ages 50–90; N=9), and early non-exudative AMD subjects (ages 50–90; N=12). Eight AMD and four normal subjects were retested 1 year after the initial evaluation. Early Treatment Diabetic Retinopathy Study (ETDRS) visual acuity (VA) and parameters of cone function (baseline cone sensitivity and cone recovery half-life following photobleach) were measured and compared between AMD and normal subjects. Short-term repeatability was assessed for each subject’s initial evaluation. Long-term repeatability was assessed by comparing outcomes from the initial evaluation and 1-year follow-up. Results: The mean baseline cone threshold was significantly worse in subjects with early AMD compared to older normal subjects (-1.80±0.04 vs -1.57±0.06 log cd/m2 p=0.0027). Moreover, the baseline cone threshold parameter exhibited good short-term (intraclass correlation coefficient [ICC]=0.88) and long-term (ICC=0.85) repeatability in all subjects. The cone intercept parameter and ETDRS VA were not significantly different between AMD and older normal subject groups. Cone recovery half-life was significantly different between older normal and AMD subject groups (p=0.041). Neither ETDRS VA nor cone function parameters were significantly different for any group at the 1-year follow-up. Conclusion: The baseline cone threshold shows potential as a novel parameter to assess visual dysfunction in early AMD. This outcome consistently detected deficits in AMD subjects, and differentiated them from age-matched controls with high test–retest repeatability. Keywords: AMD, photobleach, photoreceptor, cone recovery, Ora LUX

Abstract In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their relationship to disease status. It is still debatable which of these approaches is more favourable, and under what conditions. The former has the advantage of simplicity but suffers severely when alleles at the tested loci are not in linkage disequilibrium (LD) with liability alleles; the latter should capture more of the signal encoded in LD, but is far from simple. The complexity of haplotype analysis could be especially troublesome for association scans over large genomic regions, which, in fact, is becoming the standard design. For these reasons, the authors have been evaluating statistical methods that bridge the gap between single-locus and haplotype-based tests. In this article, they present one such method, which uses non-parametric regression techniques embodied by Bayesian adaptive regression splines (BARS). For a set of markers falling within a common genomic region and a corresponding set of single-locus association statistics, the BARS procedure integrates these results into a single test by examining the class of smooth curves consistent with the data. The non-parametric BARS procedure generally finds no signal when no liability allele exists in the tested region (ie it achieves the specified size of the test) and it is sensitive enough to pick up signals when a liability allele is present. The BARS procedure provides a robust and potentially powerful alternative to classical tests of association, diminishes the multiple testing problem inherent in those tests and can be applied to a wide range of data types, including genotype frequencies estimated from pooled samples.

Background: Treatment of recurrent glioblastoma (GBM) remains problematic with survival after additional therapy typically less than 12 months. We prospectively evaluated whether outcomes might be improved with resection plus permanent implantation of a novel radiation device utilizing the gamma-emitting isotope Cs-131 embedded within bioresorbable collagen tiles., Methods: Recurrent histologic GBM were treated in a single-arm trial. Following radiation, the surgical bed was lined with the tiles. Subsequent treatments were at the treating physician's discretion., Results: 28 patients were treated (20 at first recurrence, range 1-3). Median age was 58 years, KPS was 80, female:male ratio was 10:18. Methylguanine methyltransferase (MGMT) was methylated in 11%, unmethylated in 18%, and unknown in 71%. Post implant, 17 patients (61%) received ≥1 course of systemic therapy. For all patients, Kaplan-Meier estimates of median time to local failure were 12.1 months, post-implant survival was 10.7 months for all patients and 15.1 months for patients who received systemic therapy; for all patients, median overall survival from diagnosis was 25.0 months (range 9.1-143.1). Sex, age, and number of prior progressions were not statistically significant. Local control was continuously maintained in 46% of patients. Two deaths within 30 days occurred, one from intracranial hemorrhage and one after persistent coma. Three symptomatic adverse events occurred: one wound infection requiring surgery and two late radiation brain injury, resolved non-surgically., Conclusion: This pre-commercial trial demonstrated acceptable safety and favorable post-treatment local control and survival. The device has received FDA clearance for use in newly diagnosed malignant and all recurrent intracranial neoplasms., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Introduction Achieving durable local control (LC) for larger (e.g., >2-3 cm) brain metastasis whether newly diagnosed or recurrent remains problematic. Resection (R) alone is typically insufficient and adding radiation therapy (RT) still results in a 12-month recurrence rate of 20% or more in many series. Hypothesizing that R plus immediate radiation utilizing brachytherapy may improve outcomes for this cohort of patients, we designed and prospectively evaluated a permanently implanted surgically targeted radiation therapy (STaRT) device consisting of cesium-131 (Cs-131) seeds positioned within a collagen carrier (GammaTile, GT Medical Technologies, Tempe, AZ). The device was designed to prevent direct source-to-brain contact and maintain inter-source spacing after closure. Methods This was a subgroup analysis of a cohort of patients with either recurrent or previously untreated brain metastases enrolled in a prospective, multi-histology single-arm trial (ClinicalTrials.gov, NCT#03088579), conducted between February 2013 and February 2018, of resection and tumor bed brachytherapy with Cs-131 containing permanently implanted collagen tiles to deliver 60 Gray (Gy) at .5 cm depth. No additional local therapy was given without progression. Results A total of 16 metastases in 11 patients were treated; 12 tumors were recurrent and four were previously untreated. The median preoperative maximum diameter was 3.2 cm (range: 1.9-5.1 cm). Histology was seven breasts, six lungs, and three sarcomas. The median age was 60 years (range: 41-80 years); the Karnofsky Performance Status (KPS) was 70 (range: 70-90). The cohort consisted of seven females and four males. The mean time for implantation completion was five minutes. The median overall survival (OS) was 9.3 months. At a median radiographic follow-up of 9.5 months' treatment, site progression was found in 1/16 (6%) at 10.9 months, and the median treatment site time-to-progression (TTP) has not been reached [95% confidence interval (CI): >10.9 months]. At 12 months, the Kaplan-Meier (K-M) estimates for LC after R+STaRT for all tumors was 83%; for previously untreated tumors, LC at 12 months was 100% and for recurrent tumors, it was 80%. Two tumor beds (12.5%) experienced radiation brain changes: one had grade two and the other grade three. No surgical adverse events occurred. Conclusion In this single-arm precommercial study, R+STaRT demonstrated excellent safety and LC in this cohort. The device has recently received FDA clearance for use in newly diagnosed and recurrent brain metastasis, and randomized clinical trials vs. standard of care treatments in both settings are scheduled to open in 2020., Competing Interests: The authors have declared financial relationships, which are detailed in the next section., (Copyright © 2020, Nakaji et al.)

Background: To prevent irreversible vision loss in age-related macular degeneration (AMD), it is critical to detect retinal dysfunction before permanent structural loss occurs. In the current study we evaluated a series of visual function tests to identify potential endpoints to detect visual dysfunction in non-advanced AMD., Methods: A series of visual function tests were performed on 23 non-advanced AMD subjects (AREDS grade 1-4 on simplified scale) and 34 age-matched normals (AREDS grade 0). Tests included some commonly used endpoints such as ETDRS visual acuity (VA), low luminance (LL) 2.0ND ETDRS VA, MNREAD as well as newly developed tests such as the Ora-VCF™ test, Ora-tablet reading test, color sensitivity etc. Differences between the two groups were compared for each test. Test-retest repeatability and reproducibility was assessed on a subset of subjects and percent agreement was calculated., Results: There was no difference in standard ETDRS VA between non-advanced AMD (0.06 ± 0.02 logMAR) and normal groups (0.04 ± 0.02 logMAR) (p = 0.57). LL 2.0 ETDRS VA and MNREAD showed no difference between the groups (p > 0.05). Ora-VCF™ test was significantly worse in the non-advanced AMD group compared to normals (0.67 ± 0.07 in AMD; 0.45 ± 0.04 in normals, p = 0.005). Non-advanced AMD subjects also had significantly worse reading performance using the Ora-tablet with LL 2.0ND (114.55 ± 11.22 wpm in AMD; 145.17 ± 9.55 wpm in normals p = 0.049). No significant difference between the groups was noted using other tests. Repeatability was 82% for Ora-VCF™ test and 92% for Ora-tablet LL 2.0ND reading. Reproducibility was 89% for both Ora-VCF™ test and Ora-tablet LL 2.0ND reading., Conclusion: While there was no significant difference between non-advanced AMD and normal groups using some current common endpoints such as ETDRS VA, LL 2.0 ETDRS VA or MNREAD, Ora-VCF™ test and Ora-tablet LL 2.0ND reading tests were able to identify significant visual dysfunction in non-advanced AMD subjects. These tests show promise as endpoints for AMD studies.

Purpose: Impaired adaptation to changes in lighting levels as well as mesopic visual function is a common complaint in those over the age of 65. The use of photostress is a well-established method to test the adaption rate and the response of the visual cycle. In this study, we test visual function recovery to mesopic luminance stimuli following a long duration photostress in young and elderly subjects. If successful in strongly differentiating aging macular function, these methods may also be useful in the study of pathologies such as age-related macular degeneration., Methods: A group of 12 older normal subjects (mean age 75.1 ± 4.79) and a control group of 5 younger normal subjects (mean age 26.2 ± 4.19) were subjected to macular photostress using the OraLux photostress system. The OraLux system provides a diffuse light source bleaching 84% of cone photopigment while maintaining an exposure safety factor of 200 times less than the maximum safe exposure. After each photostressing session, macular recovery was tracked using a foveal, variable contrast, flickering stimulus of mean luminance in the high mesopic range. Recovery was tracked for 300 seconds. The endpoint was time to recovery to each individual's baseline sensitivity as determined by two static sensitivity trials prior to photostress., Results: Proportional hazards analysis of recovery time yielded a statistically significant difference between the older group and the young group (HR = 0.181; p =0.0289). The estimated hazard ratio of 0.181 indicates that older subjects return to baseline at less than one-fifth the rate of younger subjects. The hazards ratio remained statistically significant after adjusting for visual acuity (HR = 0.093; p =0.0424)., Conclusion: Photostress recovery of flicker sensitivity under mesopic conditions is a strong differentiator of aging macular function. This agrees with subject-reported complaints in reduced luminance conditions after exposure to bright lights such as night driving. The qualitative similarity between the aging retina and changes in early AMD suggests that flicker recovery following photostress may be useful as a surrogate endpoint in AMD clinical trials., Competing Interests: JR, DW, DN, and MA are employees of Ora, Inc. GW is an employee of Statistics and Data Corp and has no conflicts of interest regarding the publication of this paper., (Copyright © 2019 John D. Rodriguez et al.)

Objective: To characterize the time course of ventricular volume expansion in genetic frontotemporal dementia (FTD) and identify the onset time and rates of ventricular expansion in presymptomatic FTD mutation carriers., Methods: Participants included patients with a mutation in MAPT , PGRN , or C9orf72 , or first-degree relatives of mutation carriers from the GENFI study with MRI scans at study baseline and at 1 year follow-up. Ventricular volumes were obtained from MRI scans using FreeSurfer, with manual editing of segmentation and comparison to fully automated segmentation to establish reliability. Linear mixed models were used to identify differences in ventricular volume and in expansion rates as a function of time to expected disease onset between presymptomatic carriers and noncarriers., Results: A total of 123 participants met the inclusion criteria and were included in the analysis (18 symptomatic carriers, 46 presymptomatic mutation carriers, and 56 noncarriers). Ventricular volume differences were observed 4 years prior to symptom disease onset for presymptomatic carriers compared to noncarriers. Annualized rates of ventricular volume expansion were greater in presymptomatic carriers relative to noncarriers. Importantly, time-intensive manually edited and fully automated ventricular volume resulted in similar findings., Conclusions: Ventricular volume differences are detectable in presymptomatic genetic FTD. Concordance of results from time-intensive manual editing and fully automatic segmentation approaches support its value as a measure of disease onset and progression in future studies in both presymptomatic and symptomatic genetic FTD., (Copyright © 2019 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Objective: The aim of this study was to determine the association of HPV16 antibodies (Abs) and oropharyngeal cancer (OPC) risk in sera obtained prior to clinical diagnosis., Methods: We identified 92 participants with incident OPC and 460 matched controls from the Janus Serum Bank Cohort in Norway. Archived tumor specimens were requested for a subset of the cases. Serum samples were collected from cases, on average, 9.3years before diagnosis (range, 0.1-14.9years). Ten cases had serum samples from multiple time points. IgG seropositivity to 8 HPV16 antigens was determined, and a logistic regression classifier of a panel of all early-antigen (EA) Abs for the predictive diagnosis of OPC was applied., Results: HPV16 EA seropositivity was present in 25.0% of patients with OPC and 7.6% of controls (odds ratio (OR), 4.1; 95% CI, 2.3-7.2, p<0.0001). Abs to E2 were strongly associated with cases 0-2years pre- diagnosis (OR, 150.1; 95% CI, 27.4-1040.0, p<0.0001), and the probability of seropositivity was inversely associated with time to diagnosis (OR, 0.7 per additional year; 95% CI, 0.6-0.9, p=0.0002). Abs to E2 were also strongly associated with tumor HPV status (OR, 35.6; 95% CI, 8.7-200.0, p<0.0001). A positive score on the binary classifier was associated with an overall OR of 15.8 (95% CI, 5.6-53.4) compared with controls (p<0.05), and was strongly associated with tumor HPV status (OR, 27.4; 95% CI, 8.6-99.6, p<0.001)., Conclusions: HPV16 Abs are detectable years prior to diagnosis of OPC, and the probability of seropositivity increases closer to diagnosis., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Objective The purpose of this study was to identify a panel of novel serum tumor antigen-associated autoantibody (TAAb) biomarkers for the diagnosis of high-grade serous ovarian cancer., Methods: To detect TAAb we probed high-density programmable protein microarrays (NAPPA) containing 10,247 antigens with sera from patients with serous ovarian cancer (n=30 cases/30 healthy controls) and measured bound IgG. We identified 735 promising tumor antigens and evaluated these with an independent set of serous ovarian cancer sera (n=30 cases/30 benign disease controls/30 healthy controls). Thirty-nine potential tumor autoantigens were identified and evaluated using an orthogonal programmable ELISA platform against a total of 153 sera samples (n=63 cases/30 benign disease controls/60 healthy controls). Sensitivities at 95% specificity were calculated and a classifier for the detection of high-grade serous ovarian cancer was constructed., Results: We identified 11-TAAbs (ICAM3, CTAG2, p53, STYXL1, PVR, POMC, NUDT11, TRIM39, UHMK1, KSR1, and NXF3) that distinguished high-grade serous ovarian cancer cases from healthy controls with a combined 45% sensitivity at 98% specificity., Conclusion: These are potential circulating biomarkers for the detection of serous ovarian cancer, and warrant confirmation in larger clinical cohorts., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Background: Current non-invasive biomarkers for Crohn's disease are limited in their utility. Progress in identifying individual autoantigens and autoantibodies in Crohn's disease has been challenging due to limitations of available immunoassays., Aims: Our aim was to identify autoantibodies associated with Crohn's disease that may be useful in diagnosis and management using an innovative protein array technology, namely nucleic acid programmable protein arrays [NAPPA]., Methods: Serum samples of 96 patients with established Crohn's disease and 96 healthy controls were included and evenly split into discovery and validation sets randomly. Autoantibodies of both IgG and IgA classes were profiled against ~1900 human proteins in the discovery set on NAPPA. Autoantibodies discovered to be Crohn's disease-specific were further validated in the independent validation set by enzyme-linked immunosorbent assay., Results: Overall, reactivity of IgG autoantibodies was stronger than that of IgA autoantibodies; however, IgA autoantibodies showed greater differential reactivity between cases and controls. Four IgA autoantibodies against SNRPB, PRPH, PTTG1 and SNAI1 were newly identified with sensitivities above 15% at 95% specificity, among which anti-SNRPB-IgA had the highest sensitivity of 24.0%. Autoantibodies associated with specific disease subtypes were also found., Conclusions: As one of the first studies to use immunoproteomics for the identification of autoantibodies in Crohn's disease, our results support the utility of NAPPA in implementing future expanded studies with better coverage of the human proteome and microbial proteomes relevant to Crohn's disease and identifying antibody markers that may have clinical impact in diagnosis and management., (Copyright © 2017 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com)

In the event of a large-scale radiation exposure, accurate and quick assessment of radiation dose received would be critical for triage and medical treatment of large numbers of potentially exposed individuals. Current methods of biodosimetry, such as the dicentric chromosome assay, are time consuming and require sophisticated equipment and highly trained personnel. Therefore, scalable biodosimetry approaches, including gene expression profiles in peripheral blood cells, are being investigated. Due to the limited availability of appropriate human samples, biodosimetry development has relied heavily on mouse models, which are not directly applicable to human response. Therefore, to explore the feasibility of using non-human primate (NHP) models to build and test a biodosimetry algorithm for use in humans, we irradiated ex vivo peripheral blood samples from both humans and rhesus macaques with doses of 0, 2, 5, 6 and 7 Gy, and compared the gene expression profiles 24 h later using Agilent human microarrays. Among the dose-responsive genes in human and using non-human primate, 52 genes showed highly correlated expression patterns between the species, and were enriched in p53/DNA damage response, apoptosis and cell cycle-related genes. When these interspecies-correlated genes were used to build biodosimetry models with using NHP data, the mean prediction accuracy on non-human primate samples was about 90% within 1 Gy of delivered dose in leave-one-out cross-validation. However, tests on human samples suggested that human gene expression values may need to be adjusted prior to application of the NHP model. A "multi-gene" approach utilizing all gene values for cross-species conversion and applying the converted values on the NHP biodosimetry models, gave a leave-one-out cross-validation prediction accuracy for human samples highly comparable (up to 94%) to that for non-human primates. Overall, this study demonstrates that a robust NHP biodosimetry model can be built using interspecies-correlated genes, and that, by using multiple regression-based cross-species conversion of expression values, absorbed dose in human samples can be accurately predicted by the NHP model.

Better and more diverse biomarkers for the development of simple point-of-care tests for active tuberculosis (TB), a clinically heterogeneous disease, are urgently needed. We generated a proteomic Mycobacterium tuberculosis ( Mtb ) High-Density Nucleic Acid Programmable Protein Array (HD-NAPPA) that used a novel multiplexed strategy for expedited high-throughput screening for antibody responses to the Mtb proteome. We screened sera from HIV uninfected and coinfected TB patients and controls ( n = 120) from the US and South Africa (SA) using the multiplex HD-NAPPA for discovery, followed by deconvolution and validation through single protein HD-NAPPA with biologically independent samples ( n = 124). We verified the top proteins with enzyme-linked immunosorbent assays (ELISA) using the original screening and validation samples ( n = 244) and heretofore untested samples ( n = 41). We identified 8 proteins with TB biomarker value; four (Rv0054, Rv0831c, Rv2031c and Rv0222) of these were previously identified in serology studies, and four (Rv0948c, Rv2853, Rv3405c, Rv3544c) were not known to elicit antibody responses. Using ELISA data, we created classifiers that could discriminate patients' TB status according to geography (US or SA) and HIV (HIV- or HIV+) status. With ROC curve analysis under cross validation, the classifiers performed with an AUC for US/HIV- at 0.807; US/HIV+ at 0.782; SA/HIV- at 0.868; and SA/HIV+ at 0.723. With this study we demonstrate a new platform for biomarker/antibody screening and delineate its utility to identify previously unknown immunoreactive proteins., (© 2017 by The American Society for Biochemistry and Molecular Biology, Inc.)

We performed an unbiased proteome-scale profiling of humoral autoimmunity in recent-onset type 1 diabetes (T1D) patients and nondiabetic controls against ∼10 000 human proteins using a Nucleic Acid Programmable Protein Array (NAPPA) platform, complemented by a knowledge-based selection of proteins from genes enriched in human pancreas. Although the global response was similar between cases and controls, we identified and then validated six specific novel T1D-associated autoantibodies (AAbs) with sensitivities that ranged from 16 to 27% at 95% specificity. These included AAbs against PTPRN2, MLH1, MTIF3, PPIL2, NUP50 (from NAPPA screening), and QRFPR (by targeted ELISA). Immunohistochemistry demonstrated that NUP50 protein behaved differently in islet cells, where it stained both nucleus and cytoplasm, compared with only nuclear staining in exocrine pancreas. Conversely, PPIL2 staining was absent in islet cells, despite its presence in exocrine cells. The combination of anti-PTPRN2, -MLH1, -PPIL2, and -QRFPR had an AUC of 0.74 and 37.5% sensitivity at 95% specificity. These data indicate that these markers behave independently and support the use of unbiased screening to find biomarkers because the majority was not predicted based on predicted abundance. Our study enriches the knowledge of the "autoantibody-ome" in unprecedented breadth and width.

Objective: The metadata reflecting the location of the infected host (LOIH) of virus sequences in GenBank often lacks specificity. This work seeks to enhance this metadata by extracting more specific geographic information from related full-text articles and mapping them to their latitude/longitudes using knowledge derived from external geographical databases., Materials and Methods: We developed a rule-based information extraction framework for linking GenBank records to the latitude/longitudes of the LOIH. Our system first extracts existing geospatial metadata from GenBank records and attempts to improve it by seeking additional, relevant geographic information from text and tables in related full-text PubMed Central articles. The final extracted locations of the records, based on data assimilated from these sources, are then disambiguated and mapped to their respective geo-coordinates. We evaluated our approach on a manually annotated dataset comprising of 5728 GenBank records for the influenza A virus., Results: We found the precision, recall, and f-measure of our system for linking GenBank records to the latitude/longitudes of their LOIH to be 0.832, 0.967, and 0.894, respectively., Discussion: Our system had a high level of accuracy for linking GenBank records to the geo-coordinates of the LOIH. However, it can be further improved by expanding our database of geospatial data, incorporating spell correction, and enhancing the rules used for extraction., Conclusion: Our system performs reasonably well for linking GenBank records for the influenza A virus to the geo-coordinates of their LOIH based on record metadata and information extracted from related full-text articles., (© The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Purpose: Mutations in TP53 induce autoantibody immune responses in a subset of cancer patients, which have been proposed as biomarkers for early detection. Here, we investigate the association of p53-specific autoantibodies with multiple tumor subtypes and determine the association with p53 mutation status and epitope specificity., Experimental Design: IgG p53 autoantibodies (p53-AAb), were quantified in 412 serum samples using a programmable ELISA assay from patients with serous ovarian, pancreatic adenocarcinoma, and breast cancer. To determine if patients generated mutation-specific autoantibodies we designed a panel of the most relevant 51 p53 point mutant proteins, to be displayed on custom programmable protein microarrays. To determine the epitope specificity we displayed 12 overlapping tiling fragments and 38 N- and C-terminal deletions spanning the length of the wild-type p53 protein., Results: We detected p53-AAb with sensitivities of 58.8% (ovarian), 22% (pancreatic), 32% (triple negative breast cancer), and 10.2% (HER2+ breast cancer) at 94% specificity. Sera with p53-AAb contained broadly reactive autoantibodies to 51 displayed p53 mutant proteins, demonstrating a polyclonal response to common epitopes. All p53-AAb displayed broad polyclonal immune response to both continuous and discontinuous epitopes at the N- and C-terminus as well as the DNA-binding domain., Conclusion and Clinical Relevance: In this comprehensive analysis, mutations in tumor p53 induce strong, polyclonal autoantibodies with broadly reactive epitope specificity., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Introduction: The reduction in lung cancer mortality associated with computed tomography (CT) screening has led to its increased use and a concomitant increase in the detection of benign pulmonary nodules. Many individuals found to have benign nodules undergo unnecessary, costly, and invasive procedures. Therefore, there is a need for companion diagnostics that stratify individuals with pulmonary nodules into high-risk or low-risk groups. Lung cancers can trigger host immune responses and elicit antibodies against tumor antigens. The identification of these autoantibodies (AAbs) and their corresponding antigens may expand our knowledge of cancer immunity, leading to early diagnosis or even benefiting immunotherapy. Previous studies were performed mostly in the context of comparing cancers and healthy (smoker) controls. We have performed one of the first studies to understand humoral immune response in patients with cancer, patients with benign nodules, and healthy smokers., Methods: We first profiled seroreactivity to 10,000 full-length human proteins in 40 patients with early-stage lung cancer and 40 smoker controls by using nucleic acid programmable protein arrays to identify candidate cancer-specific AAbs. Enzyme-linked immunosorbent assays of promising candidates were performed on 137 patients with lung cancer and 127 smoker controls, as well as on 170 subjects with benign pulmonary nodules., Results: From protein microarray screening experiments using a discovery set of 40 patients and 40 smoker controls, 17 antigens showing higher reactivity in lung cancer cases relative to the controls were subsequently selected for evaluation in a large sample set (n = 264) by using enzyme-linked immunosorbent assay. A five-AAb classifier (tetratricopeptide repeat domain 14 [TTC14], B-Raf proto-oncogene, serine/threonine kinase [BRAF], actin like 6B [ACTL6B], MORC family CW-type zinc finger 2 [MORC2], and cancer/testis antigen 1B [CTAG1B]) that can differentiate lung cancers from smoker controls with a sensitivity of 30% at 89% specificity was developed. We further tested AAb responses in subjects with CT-positive benign nodules (n = 170), and developed a five-AAb panel (keratin 8, type II, TTC14, Kruppel-like factor 8, BRAF, and tousled like kinase 1) with a sensitivity of 30% at 88% specificity. Interestingly, messenger RNA levels of six AAb targets (TTC14, BRAF, MORC family CW-type zinc finger 2, cancer/testis antigen 1B, keratin 8, type II, and tousled like kinase 1) were also found to increase in lung adenocarcinoma tissues based on The Cancer Genome Atlas data set., Conclusion: We discovered AAbs associated with lung adenocaricnoma that have the potential to differentiate cancer from CT-positive benign diseases. We believe that these antibodies warrant future validation using a larger sample set and/or longitudinal samples individually or as a panel. They could potentially be part of companion molecular diagnostic modalities that will benefit subjects undergoing CT screening for lung cancer., (Copyright © 2015 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.)

The rapid rise in the incidence of type 1 diabetes (T1D) suggests the involvement of environmental factors including viral infections. We evaluated the association between viral infections and T1D by profiling antiviral antibodies using a high-throughput immunoproteomics approach in patients with new-onset T1D. We constructed a viral protein array comprising the complete proteomes of seven viruses associated with T1D and open reading frames from other common viruses. Antibody responses to 646 viral antigens were assessed in 42 patients with T1D and 42 age- and sex-matched healthy control subjects (mean age 12.7 years, 50% males). Prevalence of antiviral antibodies agreed with known infection rates for the corresponding virus based on epidemiological studies. Antibody responses to Epstein-Barr virus (EBV) were significantly higher in case than control subjects (odds ratio 6.6; 95% CI 2.0-25.7), whereas the other viruses showed no differences. The EBV and T1D association was significant in both sex and age subgroups (≤12 and >12 years), and there was a trend toward early EBV infections among the case subjects. These results suggest a potential role for EBV in T1D development. We believe our innovative immunoproteomics platform is useful for understanding the role of viral infections in T1D and other disorders where associations between viral infection and disease are unclear., (© 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Background: Basal-like breast cancer (BLBC) is a rare aggressive subtype that is less likely to be detected through mammographic screening. Identification of circulating markers associated with BLBC could have promise in detecting and managing this deadly disease., Methods: Using samples from the Polish Breast Cancer study, a high-quality population-based case-control study of breast cancer, we screened 10,000 antigens on protein arrays using 45 BLBC patients and 45 controls, and identified 748 promising plasma autoantibodies (AAbs) associated with BLBC. ELISA assays of promising markers were performed on a total of 145 BLBC cases and 145 age-matched controls. Sensitivities at 98% specificity were calculated and a BLBC classifier was constructed., Results: We identified 13 AAbs (CTAG1B, CTAG2, TP53, RNF216, PPHLN1, PIP4K2C, ZBTB16, TAS2R8, WBP2NL, DOK2, PSRC1, MN1, TRIM21) that distinguished BLBC from controls with 33% sensitivity and 98% specificity. We also discovered a strong association of TP53 AAb with its protein expression (P = 0.009) in BLBC patients. In addition, MN1 and TP53 AAbs were associated with worse survival [MN1 AAb marker HR = 2.25, 95% confidence interval (CI), 1.03-4.91; P = 0.04; TP53, HR = 2.02, 95% CI, 1.06-3.85; P = 0.03]. We found limited evidence that AAb levels differed by demographic characteristics., Conclusions: These AAbs warrant further investigation in clinical studies to determine their value for further understanding the biology of BLBC and possible detection., Impact: Our study identifies 13 AAb markers associated specifically with BLBC and may improve detection or management of this deadly disease., (©2015 American Association for Cancer Research.)

Sera from patients with ovarian cancer contain autoantibodies (AAb) to tumor-derived proteins that are potential biomarkers for early detection. To detect AAb, we probed high-density programmable protein microarrays (NAPPA) expressing 5177 candidate tumor antigens with sera from patients with serous ovarian cancer (n = 34 cases/30 controls) and measured bound IgG. Of these, 741 antigens were selected and probed with an independent set of ovarian cancer sera (n = 60 cases/60 controls). Twelve potential autoantigens were identified with sensitivities ranging from 13 to 22% at >93% specificity. These were retested using a Luminex bead array using 60 cases and 60 controls, with sensitivities ranging from 0 to 31.7% at 95% specificity. Three AAb (p53, PTPRA, and PTGFR) had area under the curve (AUC) levels >60% (p < 0.01), with the partial AUC (SPAUC) over 5 times greater than for a nondiscriminating test (p < 0.01). Using a panel of the top three AAb (p53, PTPRA, and PTGFR), if at least two AAb were positive, then the sensitivity was 23.3% at 98.3% specificity. AAb to at least one of these top three antigens were also detected in 7/20 sera (35%) of patients with low CA 125 levels and 0/15 controls. AAb to p53, PTPRA, and PTGFR are potential biomarkers for the early detection of ovarian cancer.

Unlabelled: Pathogenic and nonpathogenic species of bacteria and fungi release membrane vesicles (MV), containing proteins, polysaccharides, and lipids, into the extracellular milieu. Previously, we demonstrated that several mycobacterial species, including bacillus Calmette-Guerin (BCG) and Mycobacterium tuberculosis, release MV containing lipids and proteins that subvert host immune response in a Toll-like receptor 2 (TLR2)-dependent manner (R. Prados-Rosales et al., J. Clin. Invest. 121:1471-1483, 2011, doi:10.1172/JCI44261). In this work, we analyzed the vaccine potential of MV in a mouse model and compared the effects of immunization with MV to those of standard BCG vaccination. Immunization with MV from BCG or M. tuberculosis elicited a mixed humoral and cellular response directed to both membrane and cell wall components, such as lipoproteins. However, only vaccination with M. tuberculosis MV was able to protect as well as live BCG immunization. M. tuberculosis MV boosted BCG vaccine efficacy. In summary, MV are highly immunogenic without adjuvants and elicit immune responses comparable to those achieved with BCG in protection against M. tuberculosis., Importance: This work offers a new vaccine approach against tuberculosis using mycobacterial MV. Mycobacterium MV are a naturally released product combining immunogenic antigens in the context of a lipid structure. The fact that MV do not need adjuvants and elicit protection comparable to that elicited by the BCG vaccine encourages vaccine approaches that combine protein antigens and lipids. Consequently, mycobacterium MV establish a new type of vaccine formulation., (Copyright © 2014 Prados-Rosales et al.)

Zoonotic viruses represent emerging or re-emerging pathogens that pose significant public health threats throughout the world. It is therefore crucial to advance current surveillance mechanisms for these viruses through outlets such as phylogeography. Despite the abundance of zoonotic viral sequence data in publicly available databases such as GenBank, phylogeographic analysis of these viruses is often limited by the lack of adequate geographic metadata. However, many GenBank records include references to articles with more detailed information and automated systems may help extract this information efficiently and effectively. In this paper, we describe our efforts to determine the proportion of GenBank records with "insufficient" geographic metadata for seven well-studied viruses. We also evaluate the performance of four different Named Entity Recognition (NER) systems for automatically extracting related entities using a manually created gold-standard.

The brain is a common site of metastatic disease in patients with breast cancer, which has few therapeutic options and dismal outcomes. The purpose of our study was to identify common and rare events that underlie breast cancer brain metastasis. We performed deep genomic profiling, which integrated gene copy number, gene expression and DNA methylation datasets on a collection of breast brain metastases. We identified frequent large chromosomal gains in 1q, 5p, 8q, 11q, and 20q and frequent broad-level deletions involving 8p, 17p, 21p and Xq. Frequently amplified and overexpressed genes included ATAD2, BRAF, DERL1, DNMTRB and NEK2A. The ATM, CRYAB and HSPB2 genes were commonly deleted and underexpressed. Knowledge mining revealed enrichment in cell cycle and G2/M transition pathways, which contained AURKA, AURKB and FOXM1. Using the PAM50 breast cancer intrinsic classifier, Luminal B, Her2+/ER negative, and basal-like tumors were identified as the most commonly represented breast cancer subtypes in our brain metastasis cohort. While overall methylation levels were increased in breast cancer brain metastasis, basal-like brain metastases were associated with significantly lower levels of methylation. Integrating DNA methylation data with gene expression revealed defects in cell migration and adhesion due to hypermethylation and downregulation of PENK, EDN3, and ITGAM. Hypomethylation and upregulation of KRT8 likely affects adhesion and permeability. Genomic and epigenomic profiling of breast brain metastasis has provided insight into the somatic events underlying this disease, which have potential in forming the basis of future therapeutic strategies.

The need for biomarkers that illuminate the pathophysiology of type 1 diabetes (T1D), enhance early diagnosis and provide additional avenues for therapeutic intervention is well recognized in the scientific community. We conducted a proteome-scale, two-stage serological AAb screening followed by an independent validation study. In the first stage, the immunoreactivity was compared between T1D cases and healthy controls against ~6000 human proteins using the nucleic acid programmable protein array (NAPPA). Genes identified with higher signal intensities in patients were challenged with a larger sample set during the second stage. Statistical analysis revealed 26 novel autoantigens and a known T1D-associated autoantigen. During validation, we verified the presence of AAbs to dual specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) using the Luciferase ImmunoPrecipitation System (LIPS) assay (36% sensitivity, 98% specificity). The AUC for a combination of DYRK2A and the classical T1D AAb IA-2A was 0.90 compared to 0.72 for DYRK2A and 0.64 for IA-2A alone. This is the first systematic screening for seroreactivity against a large number of human proteins in T1D patients. We demonstrated the application of protein microarrays to identify novel autoantigens in T1D, expanded the current T1D "autoantigenome" and help fulfill the goal of searching for novel biomarker candidates for T1D., Biological Significance: Protein microarrays provide a high-throughput platform that enables the profiling of serum antibodies to a large number of protein antigens. The value of AAb biomarkers in diagnosis, prognosis and treatment is well recognized in autoimmune diseases including T1D. We performed a systematic screening for new T1D-associated autoantigens by adapting the innovative protein array platform NAPPA. We believe that the discovery in this study will add information on candidate autoantigens that could potentially improve the diagnosis and help uncover the pathophysiology of T1D. The successful use of NAPPA for T1D AAb profiling will open the window for larger studies including more human antigen genes and other autoimmune diseases., (© 2013.)

High proportions of autistic children suffer from gastrointestinal (GI) disorders, implying a link between autism and abnormalities in gut microbial functions. Increasing evidence from recent high-throughput sequencing analyses indicates that disturbances in composition and diversity of gut microbiome are associated with various disease conditions. However, microbiome-level studies on autism are limited and mostly focused on pathogenic bacteria. Therefore, here we aimed to define systemic changes in gut microbiome associated with autism and autism-related GI problems. We recruited 20 neurotypical and 20 autistic children accompanied by a survey of both autistic severity and GI symptoms. By pyrosequencing the V2/V3 regions in bacterial 16S rDNA from fecal DNA samples, we compared gut microbiomes of GI symptom-free neurotypical children with those of autistic children mostly presenting GI symptoms. Unexpectedly, the presence of autistic symptoms, rather than the severity of GI symptoms, was associated with less diverse gut microbiomes. Further, rigorous statistical tests with multiple testing corrections showed significantly lower abundances of the genera Prevotella, Coprococcus, and unclassified Veillonellaceae in autistic samples. These are intriguingly versatile carbohydrate-degrading and/or fermenting bacteria, suggesting a potential influence of unusual diet patterns observed in autistic children. However, multivariate analyses showed that autism-related changes in both overall diversity and individual genus abundances were correlated with the presence of autistic symptoms but not with their diet patterns. Taken together, autism and accompanying GI symptoms were characterized by distinct and less diverse gut microbial compositions with lower levels of Prevotella, Coprococcus, and unclassified Veillonellaceae.

Purpose: We aim to develop a protein microarray platform capable of presenting both natural and denatured forms of proteins for antibody biomarker discovery. We will further optimize plasma screening protocols to improve detection., Experimental Design: We developed a new covalent capture protein microarray chemistry using HaloTag fusion proteins and ligand. To enhance protein yield, we used HeLa cell lysate as an in vitro transcription translation (IVTT) system. Escherichia coli lysates were added to the plasma blocking buffer to reduce nonspecific background. These protein microarrays were probed with plasma samples and autoantibody responses were quantified and compared with or without denaturing buffer treatment., Results: We demonstrated that protein microarrays using the covalent attachment chemistry endured denaturing conditions. Blocking with E. coli lysates greatly reduced the background signals and expression with IVTT based on HeLa cell lysates significantly improved the antibody signals on protein microarrays probed with plasma samples. Plasma samples probed on denatured protein arrays produced autoantibody profiles distinct from those probed on natively displayed proteins., Conclusions and Clinical Relevance: This versatile protein microarray platform allows the display of both natural and denatured proteins, offers a new dimension to search for disease-specific antibodies, broadens the repertoire of potential biomarkers, and will potentially yield clinical diagnostics with greater performance., (© 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

We present a microarray nonlinear calibration (MiNC) method for quantifying antibody binding to the surface of protein microarrays that significantly increases the linear dynamic range and reduces assay variation compared with traditional approaches. A serological analysis of guinea pig Mycobacterium tuberculosis models showed that a larger number of putative antigen targets were identified with MiNC, which is consistent with the improved assay performance of protein microarrays. MiNC has the potential to be employed in biomedical research using multiplex antibody assays that need quantitation, including the discovery of antibody biomarkers, clinical diagnostics with multi-antibody signatures, and construction of immune mathematical models.

Background: Modern genomic and proteomic studies reveal that many diseases are heterogeneous, comprising multiple different subtypes. The common notion that one biomarker can be predictive for all patients may need to be replaced by an understanding that each subtype has its own set of unique biomarkers, affecting how discovery studies are designed and analyzed., Methods: We used Monte Carlo simulation to measure and compare the performance of eight selection methods with homogeneous and heterogeneous diseases using both single-stage and two-stage designs. We also applied the selection methods in an actual proteomic biomarker screening study of heterogeneous breast cancer cases., Results: Different selection methods were optimal, and more than two-fold larger sample sizes were needed for heterogeneous diseases compared with homogeneous diseases. We also found that for larger studies, two-stage designs can achieve nearly the same statistical power as single-stage designs at significantly reduced cost., Conclusions: We found that disease heterogeneity profoundly affected biomarker performance. We report sample size requirements and provide guidance on the design and analysis of biomarker discovery studies for both homogeneous and heterogeneous diseases., Impact: We have shown that studies to identify biomarkers for the early detection of heterogeneous disease require different statistical selection methods and larger sample sizes than if the disease were homogeneous. These findings provide a methodologic platform for biomarker discovery of heterogeneous diseases.

Peptide and protein identification via tandem mass spectrometry (MS/MS) lies at the heart of proteomic characterization of biological samples. Several algorithms are able to search, score, and assign peptides to large MS/MS datasets. Most popular methods, however, underutilize the intensity information available in the tandem mass spectrum due to the complex nature of the peptide fragmentation process, thus contributing to loss of potential identifications. We present a novel probabilistic scoring algorithm called Context-Sensitive Peptide Identification (CSPI) based on highly flexible Input-Output Hidden Markov Models (IO-HMM) that capture the influence of peptide physicochemical properties on their observed MS/MS spectra. We use several local and global properties of peptides and their fragment ions from literature. Comparison with two popular algorithms, Crux (re-implementation of SEQUEST) and X!Tandem, on multiple datasets of varying complexity, shows that peptide identification scores from our models are able to achieve greater discrimination between true and false peptides, identifying up to ∼25% more peptides at a False Discovery Rate (FDR) of 1%. We evaluated two alternative normalization schemes for fragment ion-intensities, a global rank-based and a local window-based. Our results indicate the importance of appropriate normalization methods for learning superior models. Further, combining our scores with Crux using a state-of-the-art procedure, Percolator, we demonstrate the utility of using scoring features from intensity-based models, identifying ∼4-8 % additional identifications over Percolator at 1% FDR. IO-HMMs offer a scalable and flexible framework with several modeling choices to learn complex patterns embedded in MS/MS data.

Cancer patients spontaneously generate autoantibodies (AAb) to tumor-derived proteins. To detect AAb, we have probed novel high-density custom protein microarrays (NAPPA) expressing 4988 candidate tumor antigens with sera from patients with early stage breast cancer (IBC), and bound IgG was measured. We used a three-phase serial screening approach. First, a prescreen was performed to eliminate uninformative antigens. Sera from stage I-III IBC (n = 53) and healthy women (n = 53) were screened for AAb to all 4988 protein antigens. Antigens were selected if the 95th percentile of signal of cases and controls were significantly different (p < 0.05) and if the number of cases with signals above the 95th percentile of controls was significant (p < 0.05). These 761 antigens were screened using an independent set of IBC sera (n = 51) and sera from women with benign breast disease (BBD) (n = 39). From these, 119 antigens had a partial area under the ROC curve (p < 0.05), with sensitivities ranging from 9-40% at >91% specificity. Twenty-eight of these antigens were confirmed using an independent serum cohort (n = 51 cases/38 controls, p < 0.05). Using all 28 AAb, a classifier was identified with a sensitivity of 80.8% and a specificity of 61.6% (AUC = 0.756). These are potential biomarkers for the early detection of breast cancer.

An epidemic curve is a graph in which the number of new cases of an outbreak disease is plotted against time. Epidemic curves are ordinarily constructed after the disease outbreak is over. However, a good estimate of the epidemic curve early in an outbreak would be invaluable to health care officials. Currently, techniques for predicting the severity of an outbreak are very limited. As far as predicting the number of future cases, ordinarily epidemiologists simply make an educated guess as to how many people might become affected. We develop a model for estimating an epidemic curve early in an outbreak, and we show results of experiments testing its accuracy.

BARS (DiMatteo, Genovese, and Kass 2001) uses the powerful reversible-jump MCMC engine to perform spline-based generalized nonparametric regression. It has been shown to work well in terms of having small mean-squared error in many examples (smaller than known competitors), as well as producing visually-appealing fits that are smooth (filtering out high-frequency noise) while adapting to sudden changes (retaining high-frequency signal). However, BARS is computationally intensive. The original implementation in S was too slow to be practical in certain situations, and was found to handle some data sets incorrectly. We have implemented BARS in C for the normal and Poisson cases, the latter being important in neurophysiological and other point-process applications. The C implementation includes all needed subroutines for fitting Poisson regression, manipulating B-splines (using code created by Bates and Venables), and finding starting values for Poisson regression (using code for density estimation created by Kooperberg). The code utilizes only freely-available external libraries (LAPACK and BLAS) and is otherwise self-contained. We have also provided wrappers so that BARS can be used easily within S or R.