Change-point detection methods are proposed for the case of temporary failures, or transient changes, when an unexpected disorder is ultimately followed by a re-adjustment and return to the initial state. A base distribution of the ‘in-control’ state changes to an ‘out-of-control’ distribution for unknown periods of time. Likelihood based sequential and retrospective tools are proposed for the detection and estimation of each pair of change-points. The accuracy of the obtained change-point estimates is assessed. Proposed methods offer simultaneous control of the familywise false alarm and false re-adjustment rates at the pre-chosen levels.

At least 50% of factors predisposing to alcohol dependence (AD) are genetic and women affected with this disorder present with more psychiatric comorbidities, probably indicating different genetic factors involved. We aimed to run a genome-wide association study (GWAS) followed by a bioinformatic functional annotation of associated genomic regions in patients with AD and eight related clinical measures. A genome-wide significant association of rs220677 with AD (p-value = 1.33 × 10−8 calculated with the Yates-corrected χ2 test under the assumption of dominant inheritance) was discovered in female patients. Associations of AD and related clinical measures with seven other single nucleotide polymorphisms listed in previous GWASs of psychiatric and addiction traits were differently replicated in male and female patients. The bioinformatic analysis showed that regulatory elements in the eight associated linkage disequilibrium blocks define the expression of 80 protein-coding genes. Nearly 68% of these and of 120 previously published coding genes associated with alcohol phenotypes directly interact in a single network, where BDNF is the most significant hub gene. This study indicates that several genes behind the pathogenesis of AD are different in male and female patients, but implicated molecular mechanisms are functionally connected. The study also reveals a central role of BDNF in the pathogenesis of AD.

We study the uniform convergence rate of the nonparametric maximum likelihood estimator (MLE) for the sub-distribution functions in the current status data with competing risks model. It is known that the MLE have $L^2$-norm convergence rate $O_P(n^{-1/3})$ in the absolutely continuous case, but there is no arguments for the same rate of uniform convergence. We specify conditions for the uniform convergence rate $O_P(n^{-1/3}\log^{1/3} n)$ of the MLE for the sub-distribution functions of competing risks on finite intervals. The obtained result refines known uniform convergence rate in the particular case of current status data. The main result is applied in order to get the uniform convergence rate of the MLE for the survival function of failure time in the current status right-censored data model.

Although there have been many studies of gene variant association with different stages of HIV/AIDS progression in United States and European cohorts, few gene-association studies have assessed genic determinants in sub-Saharan African populations, which have the highest density of HIV infections worldwide. We carried out genome-wide association studies on 766 study participants at risk for HIV-1 subtype C (HIV-1C) infection in Botswana. Three gene associations (AP3B1, PTPRA, and NEO1) were shown to have significant association with HIV-1C acquisition. Each gene association was replicated within Botswana or in the United States-African American or United States-European American AIDS cohorts or in both. Each associated gene has a prior reported influence on HIV/ AIDS pathogenesis. Thirteen previously discovered AIDS restriction genes were further replicated in the Botswana cohorts, extending our confidence in these prior AIDS restriction gene reports. This work presents an early step toward the identification of genetic variants associated with and affecting HIV acquisition or AIDS progression in the understudied HIV-1C afflicted Botswana population.

We consider an advanced framework for genome wide association study (GWAS) based on the signal localization.Instead of looking for single genetic markers associated with the phenotype we attempt to discover regions of genetic markers, which are associated with phenotype.We focus on the localization by moving sums of negative logarithms of p-values, which is efficient for discovery of wide regions of genetic markers associated with phenotype.Particularly, we expect the method should be efficient for searching genes containing a number of genetic markers, if any reconstruction in a gene related to a phenotype.The method is implemented in GWATCH software for visualization and interpretation results of multiple statistical tests for genome associations.We discuss some features of the GWATCH software and apply them for HIV/AIDS cohort study from Botswana.

The Russian Federation is the largest and one of the most ethnically diverse countries in the world, however no centralized reference database of genetic variation exists to date. Such data are crucial for medical genetics and essential for studying population history. The Genome Russia Project aims at filling this gap by performing whole genome sequencing and analysis of peoples of the Russian Federation. Here we report the characterization of genome-wide variation of 264 healthy adults, including 60 newly sequenced samples. People of Russia carry known and novel genetic variants of adaptive, clinical and functional consequence that in many cases show allele frequency divergence from neighboring populations. Population genetics analyses revealed six phylogeographic partitions among indigenous ethnicities corresponding to their geographic locales. This study presents a characterization of population-specific genomic variation in Russia with results important for medical genetics and for understanding the dynamic population history of the world's largest country.

We consider the Case 1 interval censoring approach for right‐censored survival data. An important feature of the model is that right‐censored event times are not observed exactly, but at some inspection times. The model covers as particular cases right‐censored data, current status data, and life table survival data with a single inspection time. We discuss the nonparametric estimation approach and consider three nonparametric estimators for the survival function of failure time: maximum likelihood, pseudolikelihood, and the naïve estimator. We establish strong consistency of the estimators with the L1 rate of convergence. Simulation results confirm consistency of the estimators.

We explore the standard life table (actuarial) estimator for grouped right-censored survival data and its extensions in order to consider its relationship with the Kaplan-Meier estimator, and to investigate the critical properties of the extended life table estimators (ELTEs). We discuss certain conditions for the ELTE to be consistent and develop a characterization of the standard life table estimator using the consistency property under any choice of at least two observation times of a finite interval. We also perform a comparative analysis of the ELTEs with the corresponding maximum likelihood estimators for grouped right-censored survival data.

Clinical and experimental data suggest that carcinoembryonic antigen (CEA, CD66e, CEACAM-5) plays a key role in the formation of hepatic metastasis from colorectal and other types of epithelial cancers. The molecular events involved in CEA-induced metastasis have yet to be defined. Our group first cloned the gene (CEAR) for CEA-binding protein from the surface of fixed liver macrophages, (Kupffer cells). In this study to further elucidate the role of CEAR in colorectal cancer progression, its expression in colorectal cancer cells was suppressed by short hairpin RNAs (shRNAs) in CEA-overexpressing and CEA - negative MIP-101 colorectal cancer cell lines. The data show that targeted suppression of endogenous CEAR in tumor cells resulted in changes in cell invasiveness. RT-PCR data indicated reduced levels of E-cadherin, Snail, MMP-2, and Oct-4 in the clones with suppressed CEAR suggesting a role in the epithelial mesenchymal transition. The comparative analysis of tumorigenic activity to the liver of the cell lines with suppressed CEAR has also been conducted using an intrasplenic injection model in immuno-deficient mice. This data shows a decrease in tumor progression associated with CEAR suppression. In summary the results of this study revealed a novel role for CEAR gene in the regulation of colorectal cancer cell invasiveness and progression.

Sub-Saharan Africans infected with HIV-1C make up the largest AIDS patient population in the world and exhibit large heterogeneity in disease progression before initiating antiretroviral therapy. To identify host variants associated with HIV disease progression, we performed genome-wide association studies on a total of 556 treatment-naive HIV-infected individuals in Botswana. We characterized the pattern of HIV disease progression using a novel functional principal component analysis, which can better capture longitudinal CD4 and viral load (VL) trajectories. Two single-nucleotide polymorphisms (SNPs) near HCG22 (chr6, peak variant rs2535307, combined p = 3.72 × 10-7, minor allele as risky allele) and CCNG1 (chr5, peak variant kgp22385164, combined p = 1.88 × 10-6, minor allele as risky allele) were significantly associated with CD4 and VL dynamics. Inspection of SNPs in these gene regions in a third Botswana cohort (using GWATCH) also revealed a strong association of HCG22 with HIV-1C acquisition, suggesting that this region is associated with infection as well as disease progression. Our study uncovered two genetic regions that are significant and have specific effects on HIV-1C acquisition or progression in sub-Saharan Africans, and the result suggested new potential targets for AIDS prevention and treatment. In addition, our results also indicate the possibility of using genetic markers as HIV disease progression indicators in sub-Saharan Africans to prioritize fast progressors for antiretroviral treatment.

A new approach for statistical association signal identification is developed in this paper. We consider a strategy for nonprecise signal identification by extending the well-known signal detection and signal identification methods applicable to the multiple testing problem. Collection of statistical instruments under the presented approach is much broader than under the traditional signal identification methods, allowing more efficient signal discovery. Further assessments of maximal value and average statistics in signal discovery are improved. While our method does not attempt to detect individual predictors, it instead detects sets of predictors that are jointly associated with the outcome. Therefore, an important application would be in genome wide association study (GWAS), where it can be used to detect genes which influence the phenotype but do not contain any individually significant single nucleotide polymorphism (SNP). We compare power of the signal identification method based on extremes of single p-values with the signal localization method based on average statistics for logarithms of p-values. A simulation analysis informs the application of signal localization using the average statistics for wide signals discovery in Gaussian white noise process. We apply average statistics and the localization method to GWAS to discover better gene influences of regulating loci in a Chinese cohort developed for risk of nasopharyngeal carcinoma (NPC).

The aim of the project was to study human immunodeficiency virus (HIV) incidence, sociodemographic and behavioral correlates of HIV acquisition among injection drug users (IDUs).A total of 717 IDUs were recruited, tested, and counseled for HIV-1; 466 HIV-negative participants were enrolled and followed-up at 6 and 12 months. Sociodemographic and behavioral data were collected during each study visit. The association of sociodemographic and behavioral factors to HIV-1 incidence was assessed.During the 9-month recruitment period, 717 IDUs were screened and 466 participants were enrolled. HIV-1 prevalence at baseline was 35%. Most enrolled subjects were young (median age 30), male (75%), injected heroin in the previous 3 months (86%), about 50% had shared syringes and other paraphernalia, and 44% had unprotected sex in the last month. The retention rate at the 12-month follow-up was 72% and the adjusted retention rate was 88%. The HIV incidence rate was 7.2/100 person-years. HIV incidence was significantly associated with specific drug risk behaviors, including injecting the mixture of heroin and psychostimulants, the frequency of injecting in groups with other people, and having more drug dealers.The St Petersburg IDUs cohort demonstrates one of the highest HIV incidence rates in the world. In 2004 to 2006, the HIV incidence was 4.5, in 2005 to 2007-19.6, and in 2008 to 2009-7.2/100 person-years. The peak of HIV epidemic among IDUs in St Petersburg, as determined by 3 independent cohort studies, was in 2006 to 2007. Interventions targeting IDUs with long experience of heroin injection and high levels of injection risk behaviors are urgently needed.

As genome wide association studies plus whole genome sequence analyses for complex human disease determinants are expanding, it seems useful to develop strategies to facilitate large data sharing, rapid replication and validation of provocative statistical associations that straddle the threshold for genome wide significance. At this conference, we shall announce GWATCH, (Genome Wide Association Tracks Chromosome Highway) a web based data release platform that can freely display and inspect unabridged genome tracked association data without compromising privacy or Informed Consent constrictions, allowing for rapid discovery and replication opportunities. We illustrate the utility with HIV-AIDS resistance genes screened in combined large multicenter cohort studies GWAS (MACS, HGDS, MHGS, ALLIVE, LSOCA HOMER) developed and studied over the last decades.

BACKGROUND:As genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations.FINDINGS:Here we present a dynamic web-based platform - GWATCH - that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis.CONCLUSIONS:GWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH.

In order to be inherited in progeny generations, novel genes should originate in germ cells. Here, we suggest that the testes may play a special "catalyst" role in the birth and evolution of new genes. Cancer/testis antigen encoding genes (CT genes) are predominantly expressed both in testes and in a variety of tumors. By the criteria of evolutionary novelty, the CT genes are, indeed, novel genes. We performed homology searches for sequences similar to human CT in various animals and established that most of the CT genes are either found in humans only or are relatively recent in their origin. A majority of all human CT genes originated during or after the origin of Eutheria. These results suggest relatively recent origin of human CT genes and align with the hypothesis of the special role of the testes in the evolution of the gene families.

We evaluated the efficacy of a peer-educator network intervention as a strategy to reduce HIV acquisition among injection drug users (IDUs) and their drug and/or sexual networks. A randomized controlled trial was conducted in St. Petersburg, Russia among IDU index participants and their risk network participants. Network units were randomized to the control or experimental intervention. Only the experimental index participants received training sessions to communicate risk reduction techniques to their network members. Analysis includes 76 index and 84 network participants who were HIV uninfected. The main outcome measure was HIV sero-conversion. The incidence rates in the control and experimental groups were 19.57 (95 % CI 10.74–35.65) and 7.76 (95 % CI 3.51–17.19) cases per 100 p/y, respectively. The IRR was 0.41 (95 % CI 0.15–1.08) without a statistically significant difference between the two groups (log rank test statistic X 2 = 2.73, permutation p value = 0.16). Retention rate was 67 % with a third of the loss due to incarceration or death. The results show a promising trend that this strategy would be successful in reducing the acquisition of HIV among IDUs.