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At least 19 recordsLinked to original sources
PubMed2006

Association genetics in Pinus taeda L. I. Wood property traits.

Genetic association is a powerful method for dissecting complex adaptive traits due to (i) fine-scale mapping resulting from historical recombination, (ii) wide coverage of phenotypic and genotypic variation within a single experiment, and (iii) the simultaneous discovery of loci and alleles. In this article, genetic association among single nucleotide polymorphisms (58 SNPs) from 20 wood- and drought-related candidate genes and an array of wood property traits with evolutionary and commercial importance, namely, earlywood and latewood specific gravity, percentage of latewood, earlywood microfibril angle, and wood chemistry (lignin and cellulose content), was tested using mixed linear models (MLMs) that account for relatedness among individuals by using a pairwise kinship matrix. Population structure, a common systematic bias in association studies, was assessed using 22 nuclear microsatellites. Different phenotype:genotype associations were found, some of them confirming previous evidence from collocation of QTL and genes in linkage maps (for example, 4cl and percentage of latewood) and two that involve nonsynonymous polymorphisms (cad SNP M28 with earlywood specific gravity and 4cl SNP M7 with percentage of latewood). The strongest genetic association found in this study was between allelic variation in alpha-tubulin, a gene involved in the formation of cortical microtubules, and earlywood microfibril angle. Intragenic LD decays rapidly in conifers; thus SNPs showing genetic association are likely to be located in close proximity to the causative polymorphisms. This first multigene association genetic study in forest trees has shown the feasibility of candidate gene strategies for dissecting complex adaptive traits, provided that genes belonging to key pathways and appropriate statistical tools are used. This approach is of particular utility in species such as conifers, where genomewide strategies are limited by their large genomes.

Chromosome Mapping↗
PubMed2005

SNP discovery in associating genetic variation with human disease phenotypes.

With the completion of the human genome project, attention is now rapidly shifting towards the study of individual genetic variation. The most abundant source of genetic variation in the human genome is represented by single nucleotide polymorphisms (SNPs), which can account for heritable inter-individual differences in complex phenotypes. Identification of SNPs that contribute to susceptibility to common diseases will provide highly accurate diagnostic information that will facilitate early diagnosis, prevention, and treatment of human diseases. Over the past several years, the advancement of increasingly high-throughput and cost-effective methods to discover and measure SNPs has begun to open the door towards this endeavor. Genetic association studies are considered to be an effective approach towards the detection of SNPs with moderate effects, as in most common diseases with complex phenotypes. This requires careful study design, analysis and interpretation. In this review, we discuss genetic association studies and address the prospect for candidate gene association studies, comparing the strengths and weaknesses of indirect and direct study designs. Our focus is on the continuous need for SNP discovery methods and the use of currently available prescreening methods for large-scale genetic epidemiological research until more advanced sequencing methods currently under development will become available.

Base Sequence↗
PubMed1997

The medical utility of genomics data in neuropsychiatry: mutational genetics versus association genetics.

The long anticipated 'genetic revolution' in neuropsychiatry has yet to have an impact on the practice of clinical medicine. Excitement in the 1980s over major genetic breakthroughs in schizophrenia and manic depression, for example, has been replaced in the late 1990s by the sobering realization that most common neuropsychiatric disorders are multifactorial. Despite considerable effort and resources, no 'causative' genetic variation has been identified that plays a definitive major role in any common neuropsychiatric disorder.

Biological Psychiatry↗
PubMed2005

Obstacles and opportunities in meta-analysis of genetic association studies.

Genetic association studies have the potential to advance our understanding of genotype-phenotype relationships, especially for common, complex diseases where other approaches, such as linkage, are less powerful. Unfortunately, many reported studies are not replicated or corroborated. This lack of reproducibility has many potential causes, relating to study design, sample size, and power issues, and from sources of true variability among populations. Genetic association studies can be considered as more similar to randomized trials than other types of observational epidemiological studies because of "Mendelian randomization" (Mendel's second law). The rationale and methodology for synthesizing randomized trials is highly relevant to the meta-analysis of genetic association studies. Nevertheless, there are a number of obstacles to overcome when performing such meta-analyses. In this review, the impacts of Type I error, lack of power, and publication and reporting biases are explored, and the role of multiple testing is discussed. A number of special features of association studies are especially pertinent, because they may lead to true variability among study results. These include population dynamics and structure, linkage disequilibrium, conformity to Hardy-Weinberg Equilibrium, bias, population stratification, statistical heterogeneity, epistatic and environmental interactions, and the choice of statistical models used in the analysis. Approaches to dealing with these issues are outlined. The supreme importance of complete and consistent study reporting and of making data readily available is also highlighted as a prerequisite for sound meta-analysis. We believe that systematic review and meta-analysis has an important role to play in understanding genetic association studies and should help us to separate the wheat from the chaff.

Epistasis, Genetic↗
PubMed2002

Ethnic-specific genetic associations with pulmonary tuberculosis.

Several susceptibility-associated genetic polymorphisms have been proposed to explain differential susceptibility to tuberculosis (TB) disease progression in different populations. Here, polymorphisms in the natural resistance-associated macrophage protein 1 (NRAMP1), vitamin D receptor, tumor necrosis factor-alpha, interleukin (IL)-1, and IL-10 genes were evaluated in 358 Cambodian patients with pulmonary TB and 106 tuberculin-positive control subjects. Heterozygosity for the -1082 polymorphism of the IL-10 promoter and heterozygosity for 2 linked polymorphic NRAMP1 variants, D543N and 3' untranslated region, were associated with TB susceptibility and resistance, respectively. Other polymorphisms associated with differential susceptibility to TB were not associated with susceptibility or resistance to TB in Cambodians. The novel pattern of genetic associations with susceptibility and resistance to TB detected in Cambodia is consistent with the conclusion that unique environmental and natural selective factors have resulted in the development of ethnic-specific host genetic factors associated with TB susceptibility and resistance worldwide.

Adult↗
PubMedDate not supplied

The genetic associate: a career option in genetic counseling.

Eleven training programs designed to prepare genetic associates (genetic counselors) at the master's degree level are compared and contrasted. Sarah Lawrence College developed the first such program in 1969; currently, most genetic associate programs are housed in medical schools in major universities across the nation. The newest program (at the University of South Carolina) accepted its first class in the fall of 1985. Data provided herein will enable college and university faculty to advise interested students about this viable career option.

Allied Health Personnel↗
PubMed2005

What makes a good genetic association study?

Genetic association studies are central to efforts to identify and characterise genomic variants underlying susceptibility to multifactorial disease. However, obtaining robust replication of initial association findings has proved difficult. Much of this inconsistency can be attributed to inadequacies in study design, implementation, and interpretation--inadequately powered sample groups are a major concern. Several additional factors affect the quality of any given association study, with appropriate sample-recruitment strategy, logical variant selection, minimum genotyping error, relevant data analysis, and valid interpretation all essential to generation of robust findings. Replication has a vital role in showing that associations that are identified reflect interesting biological processes rather than methodological quirks. For an unbiased view of the evidence for and against any particular association, study quality, rather than significance value, needs to play the dominant part.

Gene Frequency↗
PubMed1999

Benefits and pitfalls encountered in psychiatric genetic association studies.

The genetic association strategy is currently being applied to a number of psychiatric phenotypes including disease vulnerability, personality variation and clinical response to psychotropic drugs. Association studies offer the prospect of identification of the specific alleles that confer significant effects on clinical phenotype. However, it should be noted that this strategy has additional advantages as well as unique drawbacks. In this paper, we review the basic methodology utilized in each step of a typical psychiatric genetic association study and discuss their potential benefits and pitfalls with particular emphasis on the selection of clinical phenotype, the identification of a candidate gene, the selection of a candidate variant, clinical data set design, and the statistical analysis of association data. With appropriate design and execution, it is hoped that the association strategy will prove to be as successful in psychiatry as it has proven to be in other branches of medicine.

Alleles↗
PubMed2005

Bayesian implementation of a genetic model-free approach to the meta-analysis of genetic association studies.

A genetic model-free method for the meta-analysis of genetic association studies is described that estimates the mode of inheritance from the data rather than assuming that it is known. For a bi-allelic polymorphism, with G as risk allele and g as wild-type, the genetic model depends on the ratio of the two log odds ratios, lambda = log OR(Gg)/log OR(GG), where OR(GG) compares GG with gg and OR(Gg) compares Gg with gg. Modelling log OR(GG) as a random effect creates a hierarchical model that can be implemented within a Bayesian framework. In Bayesian modelling, vague prior distributions have to be specified for all unknown parameters when no external information is available. When the data are sparse even supposedly vague prior distributions may have an influence on the posterior estimates. We investigate the impact of different vague prior distributions for the between-study standard deviation of log OR(GG) and for lambda, by considering three published meta-analyses and associated simulations. Our results show that depending on the characteristics of the meta-analysis the results may indeed be sensitive to the choice of vague prior distribution for either parameter. Genetic association studies usually use a case-control design that should be analysed by the corresponding retrospective likelihood. However, under some circumstances the prospective likelihood has been shown to produce identical results and it is usually preferred for its simplicity. In our meta-analyses the two likelihoods give very similar results.

Bayes Theorem↗
PubMed2024

Genetic association between epilepsy and gliomas: Insights from Mendelian randomization and single-cell transcriptomic analyses.

BACKGROUND: Seizures are prevalent in glioma patients, especially in those with low-grade gliomas. The interaction between gliomas and epilepsy involves complex biological mechanisms that are not fully understood. METHODS: We collected Genome-Wide Association Study data for epilepsy and gliomas, performed differential expression analysis, and conducted Gene Ontology (GO) enrichment analysis on the identified genes. Single-cell RNA sequencing data (scRNA-seq) from GSE221534 dataset in Gene Expression Omnibus (GEO) were used to analyze cell-cell interactions within glioma samples from patients with and without epilepsy. RESULTS: Mendelian Randomization (MR) analysis revealed significant associations between genetic variants related to epilepsy and glioma risk, suggesting a potential causal relationship, especially in astrocytomas. Differential expression analysis identified epilepsy-related genes that were significantly upregulated in astrocytoma tissues compared to normal brain tissues. GO enrichment analysis indicated that these genes are involved in critical biological processes such as neurogenesis and cellular signaling. The scRNA-seq analysis showed, compared to non-epileptic samples, glioma stem cells, microglia, and NK cells are increased in the core regions of astrocytomas in epileptic patients. Additionally, intercellular communication between tumor cells and other non-tumor cells is markedly enhanced in astrocytoma samples from epileptic patients. CONCLUSION: This study provides evidence of a genetic association between epilepsy and gliomas and elucidates the biological mechanisms through which epilepsy may influence glioma progression.

Humans↗
PubMed2005

Statistical tools for linkage analysis and genetic association studies.

Genetic mapping by linkage analysis has been an invaluable tool in the positional strategy to identify the molecular basis of many rare Mendelian disorders. With the attention of the scientific and medical community shifting towards the analysis of more common, complex traits, it has become necessary to develop new approaches that take into account the complexity of the genetic basis of these disorders and their possible interaction with other, nongenetic factors. Linkage disequilibrium studies are now becoming increasingly popular thanks to the advent of genotyping platforms that allow genome-wide searching for association between hundreds of thousands of random polymorphisms and disease phenotypes in large samples of unrelated individuals. Moreover, the definition of the disease phenotype itself is being reconsidered to include quantitative traits that may better define the underlying biologic mechanisms for many pathologic conditions. This article will review classic and new approaches to genetic mapping by linkage and association analysis and discuss the directions this field is likely to take in the near future.

Alleles↗
PubMed2003

Genetic associations: false or true?

Genetic association studies for multigenetic diseases are like fishing for the truth in a sea of trillions of candidate analyses. Red herrings are unavoidably common, and bias might cause serious misconceptions. However, a sizeable proportion of identified genetic associations are probably true. Meta-analysis, a rigorous, comprehensive, quantitative synthesis of all the available data, might help us to separate the true from the false.

Genetic Predisposition to Disease↗
PubMed2006

Clinical review: Type 1 diabetes-associated autoimmunity: natural history, genetic associations, and screening.

CONTEXT: Type 1 diabetes (T1D) is associated with autoimmune thyroid disease (AIT), celiac disease (CD), Addison's disease (AD), and other autoimmune diseases. These diseases can occur together in defined syndromes with distinct pathophysiology and characteristics: autoimmune polyendocrine syndrome I, autoimmune polyendocrine syndrome II, and the immunodysregulation polyendocrinopathy enteropathy X-linked syndrome. EVIDENCE ACQUISITION: Review of the medical literature was performed with particular attention to the natural history, genetic factors, and syndromes associated with T1D, AIT, CD, and AD. EVIDENCE SYNTHESIS: Genetic risk for these diseases overlaps and includes genes within the major histocompatibility complex (MHC) such as the human leukocyte antigens (HLA) DR and DQ alleles and the MHC I-related gene A (MIC-A). Other genes outside of the MHC have been associated with these autoimmune diseases, including the gene encoding the lymphoid tyrosine phosphatase (PTPN22) and the cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) gene. CONCLUSION: Genetic risk for T1D overlaps with AIT, CD, and AD. Disease risk is associated with organ-specific autoantibodies, which can be used to screen subjects with T1D.

Adrenal Gland Diseases↗
PubMed1976

The genetic associate: a new health professional.

Sarah Lawrence College has pioneered a masters program to train Genetic Associates. The Genetic Associate is a new category of allied health professional in clinical genetics. Trained to offer coordinative and supportive care to the patient with potential or actual genetic disease, Genetic Associates are potential providers of unmet health needs in the developing field of human genetics. There are 56 graduates of this program employed in 12 states and one foreign country. This paper describes the curriculum, the students, and a preliminary evaluation of Genetic Associates' performance as members of the health care team.

Adult↗
PubMed2002

The design, execution, and interpretation of genetic association studies to decipher complex diseases.

Genetic association studies are becoming increasingly frequent in the obstetric and gynecologic literature and they are considered central to the deciphering of the genetic basis of complex disease. The purpose, design, execution, analysis, and interpretation of genetic association studies in reproduction are discussed. Frequently used terms are defined (eg, genotype, haplotype, polymorphism, single nucleotide polymorphism, linkage disequilibrium). Guidelines are proposed for the evaluation of reports of genetic association studies (including selection of polymorphisms for study, study design, assay characteristics, sample size, multiple testing, and multivariable analysis). The potential value of this type of investigation in elucidating the mechanisms of disease in reproduction is illustrated.

Genetic Diseases, Inborn↗
PubMed2005

Admixture-matched case-control study: a practical approach for genetic association studies in admixed populations.

Case-control genetic association studies in admixed populations are known to be susceptible to genetic confounding due to population stratification. The transmission/disequilibrium test (TDT) approach can avoid this problem. However, the TDT is expensive and impractical for late-onset diseases. Case-control study designs, in which, cases and controls are matched by admixture, can be an appealing and a suitable alternative for genetic association studies in admixed populations. In this study, we applied this matching strategy when recruiting our African American participants in the Study of African American, Asthma, Genes and Environments. Group admixture in this cohort consists of 83% African ancestry and 17% European ancestry, which was consistent with reports from other studies. By carrying out several complementary analyses, our results show that there is a substructure in the cohort, but that the admixture distributions are almost identical in cases and controls, and also in cases only. We performed association tests for asthma-related traits with ancestry, and only found that FEV(1), a measure for baseline pulmonary function, was associated with ancestry after adjusting for socio-economic and environmental risk factors (P=0.01). We did not observe an excess of type I error rate in our association tests for ancestry informative markers and asthma-related phenotypes when ancestry was not adjusted in the analyses. Furthermore, using the association tests between genetic variants in a known asthma candidate gene, beta(2) adrenergic receptor (beta(2)AR) and DeltaFEF(25-75), an asthma-related phenotype, as an example, we demonstrated population stratification was not a confounder in our genetic association. Our present work demonstrates that admixture-matched case-control strategies can efficiently control population stratification confounding in admixed populations.

Adolescent↗