Mikhail Kovtun

Genome-Wide Direct Target Analysis Reveals a Role for SHORT-ROOT in Root Vascular Patterning through Cytokinin Homeostasis

SHORT-ROOT (SHR) is a key regulator of root growth and development in Arabidopsis (Arabidopsis thaliana). Made in the stele, the SHR protein moves into an adjacent cell layer, where it specifies endodermal cell fate; it is also essential for apical meristem maintenance, ground tissue patterning, vascular differentiation, and lateral root formation. Much has been learned about the mechanism by which SHR controls radial patterning, but how it regulates other aspects of root morphogenesis is still unclear. To dissect the SHR developmental pathway, we have determined the genome-wide locations of SHR direct targets using a chromatin immunoprecipitation followed by microarray analysis method. K-means clustering analysis not only identified additional quiescent center-specific SHR targets but also revealed a direct role for SHR in gene regulation in the pericycle and xylem. Using cell type-specific markers, we showed that in shr, the phloem and the phloem-associated pericycle expanded, whereas the xylem and xylem-associated pericycle diminished. Interestingly, we found that cytokinin level was elevated in shr and that exogenous cytokinin conferred a shr-like vascular patterning phenotype in wild-type root. By chromatin immunoprecipitation-polymerase chain reaction and reverse transcription-polymerase chain reaction assays, we showed that SHR regulates cytokinin homeostasis by directly controlling the transcription of cytokinin oxidase 3, a cytokinin catabolism enzyme preferentially expressed in the stele. Finally, overexpression of a cytokinin oxidase in shr alleviated its vascular patterning defect. On the basis of these results, we suggest that one mechanism by which SHR controls vascular patterning is the regulation of cytokinin homeostasis.

Fuzzy set analyses of genetic determinants of health and disability status

Analyses of complex genotype-phenotype relations require new statistical procedures because of the potentially high dimensionability of those relations which are expressed with both measurement error and stochasticity in the correlation function. We propose modifying a multivariate procedure called grade of membership (GoM) analysis to deal with the special problems of such analyses. In doing so, we make clear some special features of the GoM model for multivariate analysis of high dimensional, discrete data. This is illustrated for apolipoprotein E (APOE) assessments made on 1805 people in the 1999 National Long Term Care Survey. A number of interesting relations with APOE polymorphism were found where disability profiles were more predictive than specific diagnoses because they implicitly contained information on chronicity and severity of disease processes.

How the effects of aging and stresses of life are integrated in mortality rates: insights for genetic studies of human health and longevity

Increasing proportions of elderly individuals in developed countries combined with substantial increases in related medical expenditures make the improvement of the health of the elderly a high priority today. If the process of aging by individuals is a major cause of age related health declines then postponing aging could be an efficient strategy for improving the health of the elderly. Implementing this strategy requires a better understanding of genetic and non-genetic connections among aging, health, and longevity. We review progress and problems in research areas whose development may contribute to analyses of such connections. These include genetic studies of human aging and longevity, the heterogeneity of populations with respect to their susceptibility to disease and death, forces that shape age patterns of human mortality, secular trends in mortality decline, and integrative mortality modeling using longitudinal data. The dynamic involvement of genetic factors in (i) morbidity/mortality risks, (ii) responses to stresses of life, (iii) multi-morbidities of many elderly individuals, (iv) trade-offs for diseases, (v) genetic heterogeneity, and (vi) other relevant aging-related health declines, underscores the need for a comprehensive, integrated approach to analyze the genetic connections for all of the above aspects of aging-related changes. The dynamic relationships among aging, health, and longevity traits would be better understood if one linked several research fields within one conceptual framework that allowed for efficient analyses of available longitudinal data using the wealth of available knowledge about aging, health, and longevity already accumulated in the research field.

Genetics of aging, health and survival: Dynamic regulation of human longevity related traits

BACKGROUND The roles of genetic factors in human longevity would be better understood if one can use more efficient methods in genetic analyses and investigate pleiotropic effects of genetic variants on aging and health related traits. DATA AND METHODS We used EMMAX software with modified correction for population stratification to perform genome wide association studies (GWAS) of female lifespan from the original FHS cohort. The male data from the original FHS cohort and male and female data combined from the offspring FHS cohort were used to confirm findings. We evaluated pleiotropic effects of selected genetic variants as well as gene-smoking interactions on health and aging related traits. Then we reviewed current knowledge on functional properties of genes related to detected variants. RESULTS The eight SNPs with genome-wide significant variants were negatively associated with lifespan in both males and females. After additional QC, two of these variants were selected for further analyses of their associations with major diseases (cancer and CHD) and physiological aging changes. Gene-smoking interactions contributed to these effects. Genes closest to detected variants appear to be involved in similar biological processes and health disorders, as those found in other studies of aging and longevity e.g., in cancer and neurodegeneration. CONCLUSIONS The impact of genes on longevity may involve trade-off-like effects on different health traits. Genes that influence lifespan represent various molecular functions but may be involved in similar biological processes and health disorders, which could contribute to genetic heterogeneity of longevity and the lack of replication in genetic association studies.

Pleiotropic Meta-Analyses of Longitudinal Studies Discover Novel Genetic Variants Associated with Age-Related Diseases

Age-related diseases may result from shared biological mechanisms in intrinsic processes of aging. Genetic effects on age-related diseases are often modulated by environmental factors due to their little contribution to fitness or are mediated through certain endophenotypes. Identification of genetic variants with pleiotropic effects on both common complex diseases and endophenotypes may reveal potential conflicting evolutionary pressures and deliver new insights into shared genetic contribution to healthspan and lifespan. Here, we performed pleiotropic meta-analyses of genetic variants using five NIH-funded datasets by integrating univariate summary statistics for age-related diseases and endophenotypes. We investigated three groups of traits: (1) endophenotypes such as blood glucose, blood pressure, lipids, hematocrit, and body mass index, (2) time-to-event outcomes such as the age-at-onset of diabetes mellitus (DM), cancer, cardiovascular diseases (CVDs) and neurodegenerative diseases (NDs), and (3) both combined. In addition to replicating previous findings, we identify seven novel genome-wide significant loci (< 5e-08), out of which five are low-frequency variants. Specifically, from Group 2, we find rs7632505 on 3q21.1 in SEMA5B, rs460976 on 21q22.3 (1 kb from TMPRSS2) and rs12420422 on 11q24.1 predominantly associated with a variety of CVDs, rs4905014 in ITPK1 associated with stroke and heart failure, rs7081476 on 10p12.1 in ANKRD26 associated with multiple diseases including DM, CVDs, and NDs. From Group 3, we find rs8082812 on 18p11.22 and rs1869717 on 4q31.3 associated with both endophenotypes and CVDs. Our follow-up analyses show that rs7632505, rs4905014, and rs8082812 have age-dependent effects on coronary heart disease or stroke. Functional annotation suggests that most of these SNPs are within regulatory regions or DNase clusters and in linkage disequilibrium with expression quantitative trait loci, implying their potential regulatory influence on the expression of nearby genes. Our mediation analyses suggest that the effects of some SNPs are mediated by specific endophenotypes. In conclusion, these findings indicate that loci with pleiotropic effects on age-related disorders tend to be enriched in genes involved in underlying mechanisms potentially related to nervous, cardiovascular and immune system functions, stress resistance, inflammation, ion channels and hematopoiesis, supporting the hypothesis of shared pathological role of infection, and inflammation in chronic age-related diseases.

Pleiotropic Associations of Allelic Variants in a 2q22 Region with Risks of Major Human Diseases and Mortality

Gaining insights into genetic predisposition to age-related diseases and lifespan is a challenging task complicated by the elusive role of evolution in these phenotypes. To gain more insights, we combined methods of genome-wide and candidate-gene studies. Genome-wide scan in the Atherosclerosis Risk in Communities (ARIC) Study (N = 9,573) was used to pre-select promising loci. Candidate-gene methods were used to comprehensively analyze associations of novel uncommon variants in Caucasians (minor allele frequency~2.5%) located in band 2q22.3 with risks of coronary heart disease (CHD), heart failure (HF), stroke, diabetes, cancer, neurodegenerative diseases (ND), and mortality in the ARIC study, the Framingham Heart Study (N = 4,434), and the Health and Retirement Study (N = 9,676). We leveraged the analyses of pleiotropy, age-related heterogeneity, and causal inferences. Meta-analysis of the results from these comprehensive analyses shows that the minor allele increases risks of death by about 50% (p = 4.6×10−9), CHD by 35% (p = 8.9×10−6), HF by 55% (p = 9.7×10−5), stroke by 25% (p = 4.0×10−2), and ND by 100% (p = 1.3×10−3). This allele also significantly influences each of two diseases, diabetes and cancer, in antagonistic fashion in different populations. Combined significance of the pleiotropic effects was p = 6.6×10−21. Causal mediation analyses show that endophenotypes explained only small fractions of these effects. This locus harbors an evolutionary conserved gene-desert region with non-coding intergenic sequences likely involved in regulation of protein-coding flanking genes ZEB2 and ACVR2A. This region is intensively studied for mutations causing severe developmental/genetic disorders. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality.

Pure and Confounded Effects of Causal SNPs on Longevity: Insights for Proper Interpretation of Research Findings in GWAS of Populations with Different Genetic Structures

This paper shows that the effects of causal SNPs on lifespan, estimated through GWAS, may be confounded and the genetic structure of the study population may be responsible for this effect. Simulation experiments show that levels of linkage disequilibrium (LD) and other parameters of the population structure describing connections between two causal SNPs may substantially influence separate estimates of the effect of the causal SNPs on lifespan. This study suggests that differences in LD levels between two causal SNP loci within two study populations may contribute to the failure to replicate previous GWAS findings. The results of this paper also show that successful replication of the results of genetic association studies does not necessarily guarantee proper interpretation of the effect of a causal SNP on lifespan.

Linear Latent Structure Analysis and Modelling of Multiple Categorical Variables

Linear latent structure analysis is a new approach for investigation of population heterogeneity using high-dimensional categorical data. In this approach, the population is represented by a distribution of latent vectors, which play the role of heterogeneity variables, and individual characteristics are represented by the expectation of this vector conditional on individual response patterns. Results of the computer experiments demonstrating a good quality of reconstruction of model parameters are described. The heterogeneity distribution estimated from 1999 National Long Term Care Survey (NLTCS) is discussed. A predictive power of the heterogeneity scores on mortality is analysed using vital statistics data linked to NLTCS.

Hidden heterogeneity in Alzheimer's disease: Insights from genetic association studies and other analyses

ABSTRACT Despite evident success in clarifying many important features of Alzheimers disease (AD) the efficient methods of its prevention and treatment are not yet available. The reasons are likely to be the fact that AD is a multifactorial and heterogeneous health disorder with multiple alternative pathways of disease development and progression. The availability of genetic data on individuals participated in longitudinal studies of aging health and longevity, as well as on participants of cross‐sectional case‐control studies allow for investigating genetic and non‐genetic connections with AD and to link the results of these analyses with research findings obtained in clinical, experimental, and molecular biological studies of this health disorder. The objective of this paper is to perform GWAS of AD in several study populations and investigate possible roles of detected genetic factors in developing AD hallmarks and in other health disorders. The data collected in the Framingham Heart Study (FHS), Cardiovascular Health Study (CHS), Health and Retirement Study (HRS) and Late Onset Alzheimers Disease Family Study (LOADFS) were used in these analyses. The logistic regression and Coxs regression were used as statistical models in GWAS. The results of analyses confirmed strong associations of genetic variants from well‐known genes APOE, TOMM40, PVRL2 (NECTIN2), and APOC1 with AD. Possible roles of these genes in pathological mechanisms resulting in development of hallmarks of AD are described. Many genes whose connection with AD was detected in other studies showed nominally significant associations with this health disorder in our study. The evidence on genetic connections between AD and vulnerability to infection, as well as between AD and other health disorders, such as cancer and type 2 diabetes, were investigated. The progress in uncovering hidden heterogeneity in AD would be substantially facilitated if common mechanisms involved in development of AD, its hallmarks, and AD related chronic conditions were investigated in their mutual connection. HIGHLIGHTSThe heterogeneity of Alzheimers disease (AD) is investigated by GWAS in several study populations.The strong associations between AD and the well‐known genes APOE, TOMM40, PVRL2 (NECTIN2) and APOC1 are confirmed.The genetic connections between AD and vulnerability to infections, cancer, T2D and other health disorders are explored.

MXP: Modular eXpandable framework for building bioinformatics Pipelines

Background Pipelines are a natural tool in bioinformatics applications. Virtually any meaningful processing of biological data involves the execution of multiple software tools, and this execution must be arranged in a coherent manner. Many tools for the building of pipelines were developed over time and used to facilitate work with increasing volume of bioinformatics data. Here we present a flexible and expandable framework for building pipelines, MXP, which we hope will find its own niche in bioinformatics applications. Results We developed MXP and tested it on various tasks in our organization, primarily for building pipelines for GWAS (Genome-Wide Association Studies) and post-GWAS analysis. It was proven to be sufficiently flexible and useful. Conclusions MXP implements a number of novel features which, from our point of view, make it to be more suitable and more convenient for building bioinformatics pipelines.