Exploration of genetic susceptibility to pancreatic cancer: A GWAS approach

Pancreatic cancer is the 4th most common cause for cancer death in the United States, accompanied by less than 5% five-year survival rate based on current treatments, particularly because it is usually detected at a late stage. Identifying a high-risk population to launch an effective preventive strategy and intervention to control this highly lethal disease is desperately needed. The genetic etiology of pancreatic cancer has not been well profiled. We hypothesized that unidentified genetic variants by previous genome-wide association study (GWAS) for pancreatic cancer, due to stringent statistical threshold or missing interaction analysis, may be unveiled using alternative approaches. To achieve this aim, we explored genetic susceptibility to pancreatic cancer in terms of marginal associations of pathway and genes, as well as their interactions with risk factors. We conducted pathway- and gene-based analysis using GWAS data from 3141 pancreatic cancer patients and 3367 controls with European ancestry. Using the gene set ridge regression in association studies (GRASS) method, we analyzed 197 pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Using the logistic kernel machine (LKM) test, we analyzed 17906 genes defined by University of California Santa Cruz (UCSC) database. Using the likelihood ratio test (LRT) in a logistic regression model, we analyzed 177 pathways and 17906 genes for interactions with risk factors in 2028 pancreatic cancer patients and 2109 controls with European ancestry. After adjusting for multiple comparisons, six pathways were marginally associated with risk of pancreatic cancer ( P < 0.00025): Fc epsilon RI signaling, maturity onset diabetes of the young, neuroactive ligand-receptor interaction, long-term depression (Ps < 0.0002), and the olfactory transduction and vascular smooth muscle contraction pathways (P = 0.0002; Nine genes were marginally associated with pancreatic cancer risk (P < 2.62 × 10−5), including five reported genes (ABO, HNF1A, CLPTM1L, SHH and MYC), as well as four novel genes (OR13C4, OR 13C3, KCNA6 and HNF4 G); three pathways significantly interacted with risk factors on modifying the risk of pancreatic cancer (P < 2.82 × 10−4): chemokine signaling pathway with obesity ( P < 1.43 × 10−4), calcium signaling pathway (P < 2.27 × 10−4) and MAPK signaling pathway with diabetes (P < 2.77 × 10−4). However, none of the 17906 genes tested for interactions survived the multiple comparisons corrections. In summary, our current GWAS study unveiled unidentified genetic susceptibility to pancreatic cancer using alternative methods. These novel findings provide new perspectives on genetic susceptibility to and molecular mechanisms of pancreatic cancer, once confirmed, will shed promising light on the prevention and treatment of this disease. ^

Maintenance of pre-mRNA secondary structure by epistatic selection.

Linkage disequilibrium between polymorphisms in a natural population may result from various evolutionary forces, including random genetic drift due to sampling of gametes during reproduction, restricted migration between subpopulations in a subdivided population, or epistatic selection. In this report, we present evidence that the majority of significant linkage disequilibria observed in introns of the alcohol dehydrogenase locus (Adh) of Drosophila pseudoobscura are due to epistatic selection maintaining secondary structure of precursor mRNA (pre-mRNA). Based on phylogenetic-comparative analysis and a likelihood approach, we propose secondary structure models of Adh pre-mRNA for the regions of the adult intron and intron 2 where clustering of linkage disequilibria has been observed. Furthermore, we applied the likelihood ratio test to the phylogenetically predicted secondary structure in intron 1. In contrast to the other two structures, polymorphisms associated with the more conserved stem-loop structure of intron 1 are in low frequency, and linkage disequilibria have not been observed. These findings are qualitatively consistent with a model of compensatory fitness interactions. This model assumes that mutations disrupting pairing in a secondary structural element are individually deleterious if they destabilize a functionally important structure; a second "compensatory" mutation, however, may restabilize the structure and restore fitness.

Statistical Hurdle Models for Single Cell Gene Expression: Differential Expression and Graphical Modeling

Thesis (Ph.D.)--University of Washington, 2016-06

On a resampling approach for tests on the number of clusters with mixture model-based clustering of tissue samples

We consider the problem of assessing the number of clusters in a limited number of tissue samples containing gene expressions for possibly several thousands of genes. It is proposed to use a normal mixture model-based approach to the clustering of the tissue samples. One advantage of this approach is that the question on the number of clusters in the data can be formulated in terms of a test on the smallest number of components in the mixture model compatible with the data. This test can be carried out on the basis of the likelihood ratio test statistic, using resampling to assess its null distribution. The effectiveness of this approach is demonstrated on simulated data and on some microarray datasets, as considered previously in the bioinformatics literature. (C) 2004 Elsevier Inc. All rights reserved.

Selection pressure-driven evolution of the Epstein-Barr virus-encoded oncogene LMP1 in virus isolates from southeast Asia

The geographically constrained distribution of Epstein-Barr virus (EBV)-associated nasopharyngeal carcinoma (NPC) in southeast Asian populations suggests that both viral and host genetics may influence disease risk. Although susceptibility loci have been mapped within the human genome, the role of viral genetics in the focal distribution of NPC remains an enigma. Here we report a molecular phylogenetic analysis of an NPC-associated viral oncogene, LMP1, in a large panel of EBV isolates from southeast Asia and from Papua New Guinea, Africa, and Australia, regions of the world where NPC is and is not endemic, respectively. This analysis revealed that LMP1 sequences show a distinct geographic structure, indicating that the southeast Asian isolates have evolved as a lineage distinct from those of Papua New Guinea, African, and Australian isolates. Furthermore, a likelihood ratio test revealed that the C termini of the LMP1 sequences of the southeast Asian lineage are under significant positive selection pressure, particularly at some sites within the C-terminal activator regions. We also present evidence that although the N terminus and transmembrane region of LMP1 have undergone recombination, the C-terminal region of the gene has evolved without any history of recombination. Based on these observations, we speculate that selection pressure may be driving the LMP1 sequences in virus isolates from southeast Asia towards a more malignant phenotype, thereby influencing the endemic distribution of NPC in this region.

Detecting finite bandwidth periodic signals in stationary noise using the signal coherence spectrum

All signals that appear to be periodic have some sort of variability from period to period regardless of how stable they appear to be in a data plot. A true sinusoidal time series is a deterministic function of time that never changes and thus has zero bandwidth around the sinusoid's frequency. A zero bandwidth is impossible in nature since all signals have some intrinsic variability over time. Deterministic sinusoids are used to model cycles as a mathematical convenience. Hinich [IEEE J. Oceanic Eng. 25 (2) (2000) 256-261] introduced a parametric statistical model, called the randomly modulated periodicity (RMP) that allows one to capture the intrinsic variability of a cycle. As with a deterministic periodic signal the RMP can have a number of harmonics. The likelihood ratio test for this model when the amplitudes and phases are known is given in [M.J. Hinich, Signal Processing 83 (2003) 1349-13521. A method for detecting a RMP whose amplitudes and phases are unknown random process plus a stationary noise process is addressed in this paper. The only assumption on the additive noise is that it has finite dependence and finite moments. Using simulations based on a simple RMP model we show a case where the new method can detect the signal when the signal is not detectable in a standard waterfall spectrograrn display. (c) 2005 Elsevier B.V. All rights reserved.

On Statistical Hypothesis Testing via Simulation Method

A procedure for calculating critical level and power of likelihood ratio test, based on a Monte-Carlo simulation method is proposed. General principles of software building for its realization are given. Some examples of its application are shown.

Fractal Analysis for Cancer Research: Case Study and Simulation of Fractals

2010 Mathematics Subject Classification: 65D18.

Development of safety performance functions for empirical Bayes estimation of crash reduction factors

Crash reduction factors (CRFs) are used to estimate the potential number of traffic crashes expected to be prevented from investment in safety improvement projects. The method used to develop CRFs in Florida has been based on the commonly used before-and-after approach. This approach suffers from a widely recognized problem known as regression-to-the-mean (RTM). The Empirical Bayes (EB) method has been introduced as a means to addressing the RTM problem. This method requires the information from both the treatment and reference sites in order to predict the expected number of crashes had the safety improvement projects at the treatment sites not been implemented. The information from the reference sites is estimated from a safety performance function (SPF), which is a mathematical relationship that links crashes to traffic exposure. The objective of this dissertation was to develop the SPFs for different functional classes of the Florida State Highway System. Crash data from years 2001 through 2003 along with traffic and geometric data were used in the SPF model development. SPFs for both rural and urban roadway categories were developed. The modeling data used were based on one-mile segments that contain homogeneous traffic and geometric conditions within each segment. Segments involving intersections were excluded. The scatter plots of data show that the relationships between crashes and traffic exposure are nonlinear, that crashes increase with traffic exposure in an increasing rate. Four regression models, namely, Poisson (PRM), Negative Binomial (NBRM), zero-inflated Poisson (ZIP), and zero-inflated Negative Binomial (ZINB), were fitted to the one-mile segment records for individual roadway categories. The best model was selected for each category based on a combination of the Likelihood Ratio test, the Vuong statistical test, and the Akaike's Information Criterion (AIC). The NBRM model was found to be appropriate for only one category and the ZINB model was found to be more appropriate for six other categories. The overall results show that the Negative Binomial distribution model generally provides a better fit for the data than the Poisson distribution model. In addition, the ZINB model was found to give the best fit when the count data exhibit excess zeros and over-dispersion for most of the roadway categories. While model validation shows that most data points fall within the 95% prediction intervals of the models developed, the Pearson goodness-of-fit measure does not show statistical significance. This is expected as traffic volume is only one of the many factors contributing to the overall crash experience, and that the SPFs are to be applied in conjunction with Accident Modification Factors (AMFs) to further account for the safety impacts of major geometric features before arriving at the final crash prediction. However, with improved traffic and crash data quality, the crash prediction power of SPF models may be further improved.

Joint Analysis of Multiple Algorithms and Performance Measures

There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.

MAGIC observations of the February 2014 flare of 1ES 1011+496 and ensuing constraint of the EBL density

Context. In February-March 2014, the MAGIC telescopes observed the high-frequency peaked BL Lac 1ES 1011+496 (z=0.212) in flaring state at very-high energy (VHE, E>100GeV). The flux reached a level more than 10 times higher than any previously recorded flaring state of the source. Aims. Description of the characteristics of the flare presenting the light curve and the spectral parameters of the night-wise spectra and the average spectrum of the whole period. From these data we aim at detecting the imprint of the Extragalactic Background Light (EBL) in the VHE spectrum of the source, in order to constrain its intensity in the optical band. Methods. We analyzed the gamma-ray data from the MAGIC telescopes using the standard MAGIC software for the production of the light curve and the spectra. For the constraining of the EBL we implement the method developed by the H.E.S.S. collaboration in which the intrinsic energy spectrum of the source is modeled with a simple function (< 4 parameters), and the EBL-induced optical depth is calculated using a template EBL model. The likelihood of the observed spectrum is then maximized, including a normalization factor for the EBL opacity among the free parameters. Results. The collected data allowed us to describe the flux changes night by night and also to produce di_erential energy spectra for all nights of the observed period. The estimated intrinsic spectra of all the nights could be fitted by power-law functions. Evaluating the changes in the fit parameters we conclude that the spectral shape for most of the nights were compatible, regardless of the flux level, which enabled us to produce an average spectrum from which the EBL imprint could be constrained. The likelihood ratio test shows that the model with an EBL density 1:07 (-0.20,+0.24)stat+sys, relative to the one in the tested EBL template (Domínguez et al. 2011), is preferred at the 4:6 σ level to the no-EBL hypothesis, with the assumption that the intrinsic source spectrum can be modeled as a log-parabola. This would translate into a constraint of the EBL density in the wavelength range [0.24 μm,4.25 μm], with a peak value at 1.4 μm of λF_ = 12:27^(+2:75)_ (-2:29) nW m^(-2) sr^(-1), including systematics.

Association of SNPs in LCP1 and CTIF with hearing in 11 year old children:findings from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort and the G-EAR consortium

BACKGROUND: The genetic basis of hearing loss in humans is relatively poorly understood. In recent years, experimental approaches including laboratory studies of early onset hearing loss in inbred mouse strains, or proteomic analyses of hair cells or hair bundles, have suggested new candidate molecules involved in hearing function. However, the relevance of these genes/gene products to hearing function in humans remains unknown. We investigated whether single nucleotide polymorphisms (SNPs) in the human orthologues of genes of interest arising from the above-mentioned studies correlate with hearing function in children. METHODS: 577 SNPs from 13 genes were each analysed by linear regression against averaged high (3, 4 and 8 kHz) or low frequency (0.5, 1 and 2 kHz) audiometry data from 4970 children in the Avon Longitudinal Study of Parents and Children (ALSPAC) birth-cohort at age eleven years. Genes found to contain SNPs with low p-values were then investigated in 3417 adults in the G-EAR study of hearing. RESULTS: Genotypic data were available in ALSPAC for a total of 577 SNPs from 13 genes of interest. Two SNPs approached sample-wide significance (pre-specified at p = 0.00014): rs12959910 in CBP80/20-dependent translation initiation factor (CTIF) for averaged high frequency hearing (p = 0.00079, β = 0.61 dB per minor allele); and rs10492452 in L-plastin (LCP1) for averaged low frequency hearing (p = 0.00056, β = 0.45 dB). For low frequencies, rs9567638 in LCP1 also enhanced hearing in females (p = 0.0011, β = -1.76 dB; males p = 0.23, β = 0.61 dB, likelihood-ratio test p = 0.006). SNPs in LCP1 and CTIF were then examined against low and high frequency hearing data for adults in G-EAR. Although the ALSPAC results were not replicated, a SNP in LCP1, rs17601960, is in strong LD with rs9967638, and was associated with enhanced low frequency hearing in adult females in G-EAR (p = 0.00084). CONCLUSIONS: There was evidence to suggest that multiple SNPs in CTIF may contribute a small detrimental effect to hearing, and that a sex-specific locus in LCP1 is protective of hearing. No individual SNPs reached sample-wide significance in both ALSPAC and G-EAR. This is the first report of a possible association between LCP1 and hearing function.

Wild carrot differentiation in Europe and positive selection at DcAOX1 gene

By definition, the domestication process leads to an overall reduction of crop genetic diversity. This lead to the current search of genomic regions in wild crop relatives (CWR), an important task for modern carrot breeding. Nowadays massive sequencing possibilities can allow for discovery of novel genetic resources in wild populations, but this quest could be aided by the use of a surrogate gene (to first identify and prioritize novel wild populations for increased sequencing effort). Alternative oxidase (AOX) gene family seems to be linked to all kinds of abiotic and biotic stress reactions in various organisms and thus have the potential to be used in the identification of CWR hotspots of environment-adapted diversity. High variability of DcAOX1 was found in populations of wild carrot sampled across a West-European environmental gradient. Even though no direct relation was found with the analyzed climatic conditions or with physical distance, population differentiation exists and results mainly from the polymorphisms associated with DcAOX1 exon 1 and intron 1. The relatively high number of amino acid changes and the identification of several unusually variable positions (through a likelihood ratio test), suggests that DcAOX1 gene might be under positive selection. However, if positive selection is considered, it only acts on some specific populations (i.e. is in the form of adaptive differences in different population locations) given the observed high genetic diversity. We were able to identify two populations with higher levels of differentiation which are promising as hot spots of specific functional diversity.

Diagnostic accuracy of loop-mediated isothermal amplification as a near-patient test for meningococcal disease in children: An observational cohort study

Background: Diagnosis of meningococcal disease relies on recognition of clinical signs and symptoms that are notoriously non-specific, variable, and often absent in the early stages of the disease. Loop-mediated isothermal amplification (LAMP) has previously been shown to be fast and effective for the molecular detection of meningococcal DNA in clinical specimens. We aimed to assess the diagnostic accuracy of meningococcal LAMP as a near-patient test in the emergency department.

Methods: For this observational cohort study of diagnostic accuracy, children aged 0-13 years presenting to the emergency department of the Royal Belfast Hospital for Sick Children (Belfast, UK) with suspected meningococcal disease were eligible for inclusion. Patients underwent a standard meningococcal pack of investigations testing for meningococcal disease. Respiratory (nasopharyngeal swab) and blood specimens were collected from patients and tested with near-patient meningococcal LAMP and the results were compared with those obtained by reference laboratory tests (culture and PCR of blood and cerebrospinal fluid).

Findings: Between Nov 1, 2009, and Jan 31, 2012, 161 eligible children presenting at the hospital underwent the meningococcal pack of investigations and were tested for meningococcal disease, of whom 148 consented and were enrolled in the study. Combined testing of respiratory and blood specimens with use of LAMP was accurate (sensitivity 89% [95% CI 72-96], specificity 100% [97-100], positive predictive value 100% [85-100]; negative predictive value 98% [93-99]) and diagnostically useful (positive likelihood ratio 213 [95% CI 13-infinity] and negative likelihood ratio 0·11 [0·04-0·32]). The median time required for near-patient testing from sample to result was 1 h 26 min (IQR 1 h 20 min-1 h 32 min).

Interpretation: Meningococcal LAMP is straightforward enough for use in any hospital with basic laboratory facilities, and near-patient testing with this method is both feasible and effective. By contrast with existing UK National Institute of Health and Care Excellence guidelines, we showed that molecular testing of non-invasive respiratory specimens from children is diagnostically accurate and clinically useful.

Validación diagnóstica del test neural 1 para el síndrome de túnel del carpo

El objetivo de este estudio fue realizar una prueba de validez diagnostica del test neural 1 para el diagnóstico del Síndrome de Túnel del Carpo (STC) utilizando como prueba de referencia o de oro el test de conducción nerviosa. En este estudio participaron 115 sujetos, 230 manos con sospecha clínica de STC quienes fueron evaluados con el test de conducción nerviosa y el test neural 1. Se encontró una sensibilidad del 93.0% (IC 95%:88,21-96,79) y una especificidad del 6,67% (IC 95%:0,0-33,59), razón de verosimilitud positiva fue de 1,00 y razón de verosimilitud negativa de 1,05. Valor predictivo positivo de 86,9% y un valor predictivo negativo de 12,5%. Se concluye que el test neural 1 es una prueba clínica de alta sensibilidad y baja especificidad de gran utilidad para el monitoreo e identificación del STC. Es un procedimiento para el diagnóstico clínico de bajo costo que puede incluirse en los exámenes de rutina de los trabajadores como complemento a las pruebas clínicas sugeridas por las Gatiso para dar mayor precisión a la identificación temprana del STC. Se sugiere combinarla con otros test de mayor especificidad para ser aplicada en trabajadores en condiciones de riesgo o que presenten síntomas en miembros superiores y realizar otros estudios en donde participen sujetos sin diagnóstico clínico del STC.