Substance dependence low-density whole genome association study in two distinct American populations

Cocaine and opioid dependence are common, complex disorders with high heritability that commonly co-occur with other substance dependence disorders. Improved insight into the genetic basis of substance dependence would help elucidate its etiology and could inform its prevention and treatment. To generate new hypotheses about the genetics of substance dependence, we genotyped 5633 tagging single nucleotide polymorphism (SNP) markers in 1699 subjects from 339 African American (AA) families and 334 European American (EA) families ascertained through a sib pair meeting DSM-IV criteria for either cocaine or opioid dependence. The associations between genetic markers and five substance dependence traits (cocaine dependence, opioid dependence, cocaine-induced paranoia, alcohol dependence, and nicotine dependence) were assessed by family based association tests (FBAT). Results were ranked according to several criteria including statistical significance, concordance of results across population samples, and potential biological relevance of the implicated gene. The top-ranked result was an association of SNP rs1133503 in the MANEA gene with cocaine-induced paranoia (CIP). Our study provides an initial substance dependence trait-specific blueprint of associated regions for future candidate gene studies.     

Gene-Environment Dependence Creates Spurious Gene-Environment Interaction

Gene-environment interactions have the potential to shed light on biological processes leading to disease and to improve the accuracy of epidemiological risk models. However, relatively few such interactions have yet been confirmed. In part this is because genetic markers such as tag SNPs are usually studied, rather than the causal variants themselves. Previous work has shown that this leads to substantial loss of power and increased sample size when gene and environment are independent. However, dependence between gene and environment can arise in several ways including mediation, pleiotropy, and confounding, and several examples of gene-environment interaction under gene-environment dependence have recently been published. Here we show that under gene-environment dependence, a statistical interaction can be present between a marker and environment even if there is no interaction between the causal variant and the environment. We give simple conditions under which there is no marker-environment interaction and note that they do not hold in general when there is gene-environment dependence. Furthermore, the gene-environment dependence applies to the causal variant and cannot be assessed from marker data. Gene-gene interactions are susceptible to the same problem if two causal variants are in linkage disequilibrium. In addition to existing concerns about mechanistic interpretations, we suggest further caution in reporting interactions for genetic markers.     

A Time-Series DDP for Functional Proteomics Profiles

Summary Using a new type of array technology, the reverse phase protein array (RPPA), we measure time-course protein expression for a set of selected markers that are known to coregulate biological functions in a pathway structure. To accommodate the complex dependent nature of the data, including temporal correlation and pathway dependence for the protein markers, we propose a mixed effects model with temporal and protein-specific components. We develop a sequence of random probability measures (RPM) to account for the dependence in time of the protein expression measurements. Marginally, for each RPM we assume a Dirichlet process model. The dependence is introduced by defining multivariate beta distributions for the unnormalized weights of the stick-breaking representation. We also acknowledge the pathway dependence among proteins via a conditionally autoregressive model. Applying our model to the RPPA data, we reveal a pathway-dependent functional profile for the set of proteins as well as marginal expression profiles over time for individual markers.     

A joint modeling approach for analyzing marker data in the presence of a terminal event

In many medical studies, markers are contingent on recurrent events and the cumulative markers are usually of interest. However, the recurrent event process is often interrupted by a dependent terminal event, such as death. In this article, we propose a joint modeling approach for analyzing marker data with informative recurrent and terminal events. This approach introduces a shared frailty to specify the explicit dependence structure among the markers, the recurrent, and terminal events. Estimation procedures are developed for the model parameters and the degree of dependence, and a prediction of the covariate‐specific cumulative markers is provided. The finite sample performance of the proposed estimators is examined through simulation studies. An application to a medical cost study of chronic heart failure patients from the University of Virginia Health System is illustrated.     

Interleukin 6, soluble tumor necrosis factor receptor I and red blood cell distribution width as biological markers of functional dependence in an elderly population: a translational approach

In the present investigation we have analyzed the association between functional dependence and inflammatory biomarkers using the Barthel Index (BI) and the Katz Index (KI). This analysis may contribute to translational medicine by incorporating the clinical and laboratory data to better understand the relationship between chronic inflammation and functional dependence in the elderly population. The ultimate goal of this study was to identify possible useful biomarkers of functional dependence in the elderly. Participants in this study consisted of 120 older subjects (90 women and 30 men; range 68-105 years) who were selected from the Santa Teresa nursing home (Oviedo, Spain). We studied functional status using the following tools to diagnose the functional dependence by clinicians: BI and KI for activities of daily living. We analyzed morbidity, sociodemographic characteristics and a panel of inflammatory and inflammatory-related markers. In linear regression models adjusted by age, sex, anti-inflammatory drug use and morbid conditions high levels of interleukin 6 (IL-6) and soluble TNF receptor-I (sTNF-RI) were associated with functional dependence as measured using BI and KI. Elevated levels of red blood cell distribution width (RDW) were also associated with functional dependence measured using the KI after adjusting for the same potential confounders. The current results suggest that high IL-6, sTNF-RI and RDW levels are associated with the functional dependence in the elderly population. The results are consistent with the presumed underlying biological mechanism, in which the up-regulation of inflammatory mediators is associated with functional dependence in elderly subjects.     

Polymorphisms in the glutamate decarboxylase 1 gene associated with heroin dependence

The GAD1 gene encodes the 67-kDa glutamic acid decarboxylase isoform (GAD67), the rate-limiting enzyme responsible for γ-aminobutyric acid (GABA) biosynthesis from glutamic acid, and may be involved in the development of drug dependence. To identify markers contributing to the genetic susceptibility to heroin dependence, this study examined the potential association between heroin dependence and 15 single nucleotide polymorphisms (SNPs, rs1978340, rs3762556, rs3791878, rs3749034, rs11542313, rs2241165, rs2241164, rs769407, rs3749033, rs16858977, rs701492, rs16858988, rs4668331, rs7578661, rs769395) of GAD1 gene using the MassARRAY system. Participants included 370 heroin-dependent subjects and 389 healthy controls. The allelic or genotypic frequencies of the rs1978340 (promoter region), rs3791878 (promoter region), and rs11542313 (exon 3) polymorphisms in heroin addicts were significantly different from those in healthy controls. Strong linkage disequilibrium was observed in two blocks (D'>0.9). Significantly more C-C-C-C-A haplotypes (p=0.0053 after Bonferroni correction) and significantly fewer T-C-A-C-A haplotypes (p=0.0003 after Bonferroni correction) were found in heroin dependent subjects. These findings point to a role for GAD1 polymorphism in heroin dependence among Han Chinese, and may be informative for future genetic or neurobiological studies on heroin dependence.     

Hypoxia modulates stem cell properties and induces EMT through N-glycosylation of EpCAM in breast cancer cells

Epithelial cell adhesion molecule (EpCAM), which is a transmembrane glycoprotein, is related to tumor progression. We demonstrated that EpCAM plays important roles in proliferation, apoptosis, and metastasis during breast cancer (BC) progression. But the role of N-glycosylation in EpCAM in tumor aggressiveness is not clear. Here, we evaluated the role of N-glycosylation of EpCAM in stemness and epithelial–mesenchymal transition (EMT) characteristics. EpCAM overexpression increases the expression of stemness markers (NANOG,SOX2, and OCT4) and EMT markers (N-cadherin and vimentin) under the condition of hypoxia in BC. Knockdown of EpCAM and mutation of N-glycosylation of EpCAM maintained in severe hypoxia lead to a significant reduction of stemness/EMT markers. In addition, we found that N-glycosylation of EpCAM is a crucial factor during this process. This demonstrates that EpCAM has a novel regulatory role in stemness/EMT dependence of hypoxia-inducible factor 1-alpha via regulating nuclear factor kappa B in BC cells. Hence, our study reveals EpCAM glycosylation modification as a new regulator of stemness/EMT under hypoxic in BC and points out EpCAM as a potential therapeutic target.     

Mapping a locus for alcohol physical dependence and associated withdrawal to a 1.1 Mb interval of mouse chromosome 1 syntenic with human chromosome 1q23.2-23.3

Physiological dependence and associated withdrawal episodes are thought to constitute a motivational force perpetuating continued alcohol use/abuse. Although no animal model duplicates alcoholism, models for specific factors, like the withdrawal syndrome, are useful to identify potential determinants of liability in humans. We previously detected quantitative trait loci (QTLs) with large effects on predisposition to physical dependence and associated withdrawal following chronic or acute alcohol exposure to a large region of chromosome 1 in mice ( Alcdp1 and Alcw1 , respectively). Here, we provide the first confirmation of Alcw1 in a congenic strain, and, using interval-specific congenic strains, narrow its position to a minimal 1.1   Mb (maximal 1.7   Mb) interval syntenic with human chromosome 1q23.2-23.3. We also report the development of a small donor segment congenic that confirms capture of a gene(s) affecting physical dependence after chronic alcohol exposure within this small interval. This congenic will be invaluable for determining whether this interval harbors a gene(s) involved in additional alcohol responses for which QTLs have been detected on distal chromosome 1, including alcohol consumption, alcohol-conditioned aversion and -induced ataxia. The possibility that this QTL plays an important role in such diverse responses to alcohol makes it an important target. Moreover, human studies have identified markers on chromosome 1q associated with alcoholism, although this association is still suggestive and mapped to a large region. Thus, the fine mapping of this QTL and analyses of the genes within the QTL interval can inform developing models for genetic determinants of alcohol dependence in humans.     

Resting potential-dependent regulation of the voltage sensitivity of sodium channel gating in rat skeletal muscle in vivo

Normal muscle has a resting potential of -85 mV, but in a number of situations there is depolarization of the resting potential that alters excitability. To better understand the effect of resting potential on muscle excitability we attempted to accurately simulate excitability at both normal and depolarized resting potentials. To accurately simulate excitability we found that it was necessary to include a resting potential-dependent shift in the voltage dependence of sodium channel activation and fast inactivation. We recorded sodium currents from muscle fibers in vivo and found that prolonged changes in holding potential cause shifts in the voltage dependence of both activation and fast inactivation of sodium currents. We also found that altering the amplitude of the prepulse or test pulse produced differences in the voltage dependence of activation and inactivation respectively. Since only the Nav1.4 sodium channel isoform is present in significant quantity in adult skeletal muscle, this suggests that either there are multiple states of Nav1.4 that differ in their voltage dependence of gating or there is a distribution in the voltage dependence of gating of Nav1.4. Taken together, our data suggest that changes in resting potential toward more positive potentials favor states of Nav1.4 with depolarized voltage dependence of gating and thus shift voltage dependence of the sodium current. We propose that resting potential-induced shifts in the voltage dependence of sodium channel gating are essential to properly regulate muscle excitability in vivo.     

Membrane Potential Dependent Duration of Action Potentials in Cultured Rat Hippocampal Neurons

(1) Fluctuations of the membrane potential states are essential for the brain functions from the response of individual neurons to the cognitive function of the brain. It has been reported in slice preparations that the action potential duration is dependent on the membrane potential states. (2) In order to examine whether dependence of action potential duration on the membrane potential could happen in isolated individual neurons that have no network connections, we studied the membrane potential dependence of the action potential duration by artificially setting the membrane potentials to different states in individual cultured rat hippocampal neurons using patch-clamp technique. (3) We showed that the action potential of individual neurons generated from depolarized membrane potentials had broader durations than those generated from hyperpolarized membrane potentials. (4) Furthermore, the membrane potential dependence of the action potential duration was significantly reduced in the presence of voltage-gated K⁺ channel blockers, TEA, and 4-AP, suggesting involvement of both delayed rectifier I _K and transient I _A current in the membrane potential dependence of the action potential duration. (5) These results indicated that the dependence of action potential duration on the membrane potential states could be an intrinsic property of individual neurons. Bo Gong and Mingna Liu contributed equally to this work.     

Mouse DRG Cell Line with Properties of Nociceptors

In vitro cell lines from DRG neurons aid drug discovery because they can be used for early stage, high-throughput screens for drugs targeting pain pathways, with minimal dependence on animals. We have established a conditionally immortal DRG cell line from the Immortomouse. Using immunocytochemistry, RT-PCR and calcium microfluorimetry, we demonstrate that the cell line MED17.11 expresses markers of cells committed to the sensory neuron lineage. Within a few hours under differentiating conditions, MED17.11 cells extend processes and following seven days of differentiation, express markers of more mature DRG neurons, such as NaV1.7 and Piezo2. However, at least at this time-point, the nociceptive marker NaV1.8 is not expressed, but the cells respond to compounds known to excite nociceptors, including the TRPV1 agonist capsaicin, the purinergic receptor agonist ATP and the voltage gated sodium channel agonist, veratridine. Robust calcium transients are observed in the presence of the inflammatory mediators bradykinin, histamine and norepinephrine. MED17.11 cells have the potential to replace or reduce the use of primary DRG culture in sensory, pain and developmental research by providing a simple model to study acute nociception, neurite outgrowth and the developmental specification of DRG neurons.     

Ultrastructural changes in the skin in fatal electrical trauma

The study was performed on 20 guinea-pigs. The animals were injured by alternating current at 380 and 220 V. The developing destructive alterations were characterized by histological, histochemical and electron-microscopic techniques, and a complex of electric markers was established. A dependence of morphological changes on the voltage values was demonstrated. The complex of alterations found may be employed for the differentiation of electric markers from mechanical or thermal injuries.     

Bayesian analysis of population structure based on linked molecular information

The Bayesian model-based approach to inferring hidden genetic population structures using multilocus molecular markers has become a popular tool within certain branches of biology. In particular, it has been shown that heterogeneous data arising from genetically dissimilar latent groups of individuals can be effectively modelled using an unsupervised classification formulation. However, most currently employed models ignore potential linkage within the employed molecular information, and can therefore lead to biased inferences under certain circumstances. Utilizing the general theory of graphical models, we develop a framework that accounts for dependences both within linked molecular marker loci and DNA sequence data. Due to a high level of sequence conservation among eukaryotic species, the latter aspect is particularly relevant for analyzing rapidly evolving microbial species. The advantages of incorporating the dependence due to linkage in the classification models are illustrated by analyses of both simulated data and real samples of Bacillus cereus.     

Markov chain Monte Carlo for mapping a quantitative trait locus in outbred populations

A Bayesian approach is presented for mapping a quantitative trait locus (QTL) using the 'Fernando and Grossman' multivariate Normal approximation to QTL inheritance. For this model, a Bayesian implementation that includes QTL position is problematic because standard Markov chain Monte Carlo (MCMC) algorithms do not mix, i.e. the QTL position gets stuck in one marker interval. This is because of the dependence of the covariance structure for the QTL effects on the adjacent markers and may be typical of the 'Fernando and Grossman' model. A relatively new MCMC technique, simulated tempering, allows mixing and so makes possible inferences about QTL position based on marginal posterior probabilities. The model was implemented for estimating variance ratios and QTL position using a continuous grid of allowed positions and was applied to simulated data of a standard granddaughter design. The results showed a smooth mixing of QTL position after implementation of the simulated tempering sampler. In this implementation, map distance between QTL and its flanking markers was artificially stretched to reduce the dependence of markers and covariance. The method generalizes easily to more complicated applications and can ultimately contribute to QTL mapping in complex, heterogeneous, human, animal or plant populations.     

QTLs associated with growth traits and abdominal fat weight and their interactions with gender and hatch in commercial meat-type chickens

Associations between microsatellite markers and traits related to growth and fatness were investigated using resource broiler population. A sire-line x dam-line F1 male was backcrossed to 12 dam-line females to produce 24 sires and 47 dams of the backcross 1 (BC1) generation. These 71 parents were genotyped with 76 microsatellite markers. Following full-sib mating among the parents, 234 BC1-F2 progeny were phenotyped for five growth traits (body weight at 49 days from hatch, wog weight, front half weight, breast weight and tender weight) and abdominal fat weight. Maximum likelihood analysis was used to estimate the marker effects and to evaluate their statistical significance. Individual marker-trait analysis revealed 44 significant associations out of the 456 marker-trait combinations. Correction for multiple comparisons by controlling the false discovery rate (FDR) resulted in 12 significant associations at FDR = 10% with markers on chromosomes 1, 2, 5 and 13. Seventy-five percent of the 44 significant associations displayed no dependence on either hatch or gender; half of the remaining associations displayed dependence of the quantitative trait loci (QTL) effect on hatch x gender interaction. Thus, the analysed traits in this study may be dependent on external factors.     

Homozygosity and linkage disequilibrium

We illustrate how homozygosity of haplotypes can be used to measure the level of disequilibrium between two or more markers. An excess of either homozygosity or heterozygosity signals a departure from the gametic phase equilibrium: We describe the specific form of dependence that is associated with high (low) homozygosity and derive various linkage disequilibrium measures. They feature a clear biological interpretation, can be used to construct tests, and are standardized to allow comparison across loci and populations. They are particularly advantageous to measure linkage disequilibrium between highly polymorphic markers.     

Genomewide linkage scan for opioid dependence and related traits

Risk of opioid dependence is genetically influenced. We recruited a sample of 393 small nuclear families (including 250 full-sib and 46 half-sib pairs), each with at least one individual with opioid dependence. Subjects underwent a detailed evaluation of substance dependence-related traits. As planned a priori to reduce heterogeneity, we used cluster analytic methods to identify opioid dependence-related symptom clusters, which were shown to be heritable. We then completed a genomewide linkage scan (with 409 markers) for the opioid-dependence diagnosis and for the two cluster-defined phenotypes represented by >250 families: the heavy-opioid-use cluster and the non-opioid-use cluster. Further exploratory analyses were completed for the other cluster-defined phenotypes. The statistically strongest results were seen with the cluster-defined traits. For the heavy-opioid-use cluster, we observed a LOD score of 3.06 on chromosome 17 (empirical pointwise P = .0002) for European American (EA) and African American (AA) subjects combined, and, for the non-opioid-use cluster, we observed a LOD score of 3.46 elsewhere on chromosome 17 (empirical pointwise P = .00002, uncorrected for multiple traits studied) for EA subjects only. We also identified a possible linkage (LOD score 2.43) of opioid dependence with chromosome 2 markers for the AA subjects. These results are an initial step in identifying genes for opioid dependence on the basis of a genomewide investigation (i.e., a study not conditioned on prior physiological candidate-gene hypotheses).     

A genome-wide scanning and fine mapping study of COGA data

A thorough genetic mapping study was performed to identify predisposing genes for alcoholism dependence using the Collaborative Study on the Genetics of Alcoholism (COGA) data. The procedure comprised whole-genome linkage and confirmation analyses, single locus and haplotype fine mapping analyses, and gene x environment haplotype regression. Stratified analysis was considered to reduce the ethnic heterogeneity and simultaneously family-based and case-control study designs were applied to detect potential genetic signals. By using different methods and markers, we found high linkage signals at D1S225 (253.7 cM), D1S547 (279.2 cM), D2S1356 (64.6 cM), and D7S2846 (56.8 cM) with nonparametric linkage scores of 3.92, 4.10, 4.44, and 3.55, respectively. We also conducted haplotype and odds ratio analyses, where the response was the dichotomous status of alcohol dependence, explanatory variables were the inferred individual haplotypes and the three statistically significant covariates were age, gender, and max drink (the maximum number of drinks consumed in a 24-hr period). The final model identified important AD-related haplotypes within a candidate region of NRXN1 at 2p21 and a few others in the inter-gene regions. The relative magnitude of risks to the identified risky/protective haplotypes was elucidated.