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To type or not to type: the use of unaffected siblings in nonparametric linkage analysis.

Unaffected individuals are often disregarded in nonparametric linkage analysis. Because of the presumed high complexity of genetic interactions and the resulting low penetrance of any single genetic effect, the statistical contribution of unaffected sib pairs is thought to be considerably lower than that of the affected. However, in cases where a large number of unaffected family members are available for genotyping--as is the case in the simulated Genetic Analysis Workshop 12 data set--the relatively low value of the unaffected sibs may be offset by their number. In this paper, I demonstrate that unaffected siblings do contain a significant amount of statistical information, and show that the most powerful method of nonparametric analysis utilizes both affected and unaffected individuals. I also show that selecting the unaffected individuals based on their age is the most cost effective and usually the most powerful strategy.

Adult↗

Landscape approaches to historical and contemporary gene flow in plants.

Growing interest in metapopulation dynamics and dispersal at a landscape level is promoting new approaches to the study of contemporary gene flow. These approaches have been fostered by the development of new genetic markers and statistical methods, as well as an awareness that contemporary gene flow cannot be reliably estimated by conventional methods based on genetic structure. Estimation of the spatial and temporal dynamics of pollen and seed movement with respect to extant landscape features can aid evolutionary and conservation biologists in predicting the demographic and genetic responses of species to naturally occurring or human-mediated population subdivision.

Journal Article↗

Linkage analysis: principles and methods for the analysis of human quantitative traits.

Currently, mapping genes for complex human traits relies on two complementary approaches, linkage and association analyses. Both suffer from several methodological and theoretical limitations, which can considerably increase the type-1 error rate and reduce the power to map human quantitative trait loci (QTL). This review focuses on linkage methods for QTL mapping. It summarizes the most common linkage statistics used, namely Haseman-Elston-based methods, variance components, and statistics that condition on trait values. Methods developed more recently that accommodate the X-chromosome, parental imprinting and allelic association in linkage analysis are also summarized. The type-I error rate and power of these methods are discussed. Finally, rough guidelines are provided to help guide the choice of linkage statistics.

Genetic Linkage↗

Multiple regression analysis of twin data: etiology of deviant scores versus individual differences.

The multiple regression analysis of twin data in which a cotwin's score is predicted from a proband's score and the coefficient of relationship (the basic model) provides a statistically powerful test of genetic etiology. When an augmented model that also contains an interaction term is fitted to the same data set, direct estimates of heritability (h2) and the proportion of variance due to shared environmental influences (c2) are obtained. A simple transformation of selected twin data prior to regression analysis facilitates direct estimates of h2g (an index of the extent to which the difference between the mean of probands and that of the unselected population is heritable) and a test of the hypothesis that the etiology of deviant scores differs from that of variation within the normal range.

Data Interpretation, Statistical↗

Genetic control of serum immunoglobulin G levels in the chicken.

Serum IgG (7S) levels differed significantly for chickens from 10 different inbred lines. Within lines differences between B blood groups were statistically significant. The genetic control of serum IgG was further examined using birds from B complex haplotypes marked at the B locus and the Ir-GAT locus. Birds from each of five subgroup haplotypes (B1B1 Ir-GAT-Lo and -Hi, B19B19 Ir-GAT-Lo and -Hi, and B2B2 Ir-GAT intermediate) were tested for levels of serum IgG at 3, 6, 9, and 21 weeks of age. The rate and level of IgG reached in the serum was more than two-fold greater in the GAT-Hi birds than in the GAT-Lo. The Ir region of the B complex exerts some control over the ontogenesis of IgG, though most of the genetic variation seems not to be B complex associated.

Animals↗

Model-based inference of haplotype block variation.

The haplotype block structure of SNP variation in human DNA has been demonstrated by several recent studies. The presence of haplotype blocks can be used to dramatically increase the statistical power of genetic mapping. Several criteria have already been proposed for identifying these blocks, all of which require haplotypes as input. We propose a comprehensive statistical model of haplotype block variation and show how the parameters of this model can be learned from haplotypes and/or unphased genotype data. Using real-world SNP data, we demonstrate that our approach can be used to resolve genotypes into their constituent haplotypes with greater accuracy than previously known methods.

Algorithms↗

Nonrandom association of genetic markers in a sample of South African blacks.

According to classical genetic theory, allelic genes at one locus are expected to segregate and be manifested independently of allelic genes at another locus. At the population level any significant deviation from this general hypothesis resulting from specific biologic and genetic effects can be recognized in the form of nonrandom associations between genetic markers. The present data, consisting of 24 genetic polymorphisms determined from a sample of 998 unselected and unrelated South African blacks, offers an opportunity to test whether or not any such nonrandom associations exist between the genetic markers. After appropriate statistical calculations on the population data, we found that 13 pairs of genetic polymorphisms demonstrate a nonrandom association (statistically significant). Because the results cannot be explained in terms of known biologic mechanisms, we conclude that the associations observed could be due to random statistical effects (repeated application of the chi-square test) and/or to real (as yet unknown) biologic phenomena in the population studied. This tentative conclusion can serve as a guideline for more specific investigations.

Black People↗

Genetic rat models of hypertension: relationship to human hypertension.

Experimental models of human disease are frequently used to investigate the pathophysiology of disease as well as the mechanisms of action of therapeutics. However, as long as models have been used there have been debates about the utility of experimental models and their applicability for human disease on the phenotypic and genomic level. The recent advances in molecular genetics and genomics have provided powerful tools to study the genetics of multifactorial diseases, such as hypertension. However, studies of such diseases in humans remain challenging in part due to lack of statistical power and genetic heterogeneity within patient populations. For hypertension, various rat models have been developed and used for the identification of susceptibility loci for genetic hypertension. With the advent of "comparative genomics," the application of genetic studies to both human and animal model systems allows for a new paradigm, where comparative genomics can be used to bridge between model utility and clinical relevance. This review discusses recent approaches in genetics to facilitate gene discovery for polygenic disorders with specific focus on how comparative mapping can be used to select target regions in the human genome for large-scale association studies and linkage disequilibrium testing in clinical populations.

Animals↗

PAWE-3D: visualizing power for association with error in case-control genetic studies of complex traits.

UNLABELLED: A website that plots power and sample size calculations over a range of up to eight parameters (including diagnostic misclassification error parameters) for two commonly used statistical tests of genetic association, the linear trend test and the genotypic test of association. AVAILABILITY: This method is made available via the website http://linkage.rockefeller.edu/pawe3d/ CONTACT: pawe3d@linkage.rockefeller.edu.

Algorithms↗

Do-it-yourself statistics: A computer-assisted likelihood approach to analysis of data from genetic crosses.

Graduate school programs in genetics have become so full that courses in statistics have often been eliminated. In addition, typical introductory statistics courses for the "statistics user" rather than the nascent statistician are laden with methods for analysis of measured variables while genetic data are most often discrete numbers. These courses are often seen by students and genetics professors alike as largely irrelevant cookbook courses. The powerful methods of likelihood analysis, although commonly employed in human genetics, are much less often used in other areas of genetics, even though current computational tools make this approach readily accessible. This article introduces the MLIKELY.PAS computer program and the logic of do-it-yourself maximum-likelihood statistics. The program itself, course materials, and expanded discussions of some examples that are only summarized here are available at http://www.unisi. it/ricerca/dip/bio_evol/sitomlikely/mlikely.h tml.

Animals↗

Linkage and linkage disequilibrium analysis of the lipoprotein lipase gene with lipid profiles in Chinese hypertensive families.

Elevated TG [triacylglycerol (triglyceride)] is a significant independent risk factor for cardiovascular disease. LPL (lipoprotein lipase) is one of the key enzymes in the metabolism of the TG-rich lipoproteins which hydrolyses TG from the chylomicrons and very-LDL (low-density lipoprotein). To investigate the relationship between the LPL gene and lipid profiles, especially TG, in 148 hypertensive families, we have chosen seven flanking microsatellite markers and four internal markers of the LPL gene and conducted linkage analysis by SOLAR and S.A.G.E. (statistical analysis for genetic epidemiology)/SIBPAL 2 programs, and linkage disequilibrium analysis by QTDT (quantitative transmission/disequilibrium test) and GOLD (graphical overview of linkage disequilibrium). There were statistically significant differences in lipid levels between subjects without and with hypertension within families. A maximum LOD score of 1.3 with TG at the marker D8S261 was observed by SOLAR. Using S.A.G.E./SIBPAL 2, we identified a linkage with TG at the marker 'ATTT' located within intron 6 of the LPL gene (P=0.0095). Two SNPs (single nucleotide polymorphisms), HindIII and HinfI, were found in linkage disequilibrium with LDL-cholesterol levels (P=0.0178 and P=0.0088 respectively). A strong linkage disequilibrium was observed between the HindIII in intron 8 and HinfI in the exon 9 (P<0.00001, D'=0.895). Linkage disequilibrium was also found between the 'ATTT' polymorphism in intron 6 and two SNPs (P=0.0021 and D'=0.611 for HindIII; and P=0.00004, D'=0.459 for HinfI). The present study in the Chinese families with hypertension suggested that the LPL gene might influence lipid levels, especially TG metabolism. Replication studies both in Chinese and other populations are warranted to confirm these results.

Adult↗

Putting the "landscape" in landscape genetics.

Landscape genetics has emerged as a new research area that integrates population genetics, landscape ecology and spatial statistics. Researchers in this field can combine the high resolution of genetic markers with spatial data and a variety of statistical methods to evaluate the role that landscape variables play in shaping genetic diversity and population structure. While interest in this research area is growing rapidly, our ability to fully utilize landscape data, test explicit hypotheses and truly integrate these diverse disciplines has lagged behind. Part of the current challenge in the development of the field of landscape genetics is bridging the communication and knowledge gap between these highly specific and technical disciplines. The goal of this review is to help bridge this gap by exposing geneticists to terminology, sampling methods and analysis techniques widely used in landscape ecology and spatial statistics but rarely addressed in the genetics literature. We offer a definition for the term "landscape genetics", provide an overview of the landscape genetics literature, give guidelines for appropriate sampling design and useful analysis techniques, and discuss future directions in the field. We hope, this review will stimulate increased dialog and enhance interdisciplinary collaborations advancing this exciting new field.

Animals↗

Further refinement of the MYP2 locus for autosomal dominant high myopia by linkage disequilibrium analysis.

INTRODUCTION: High myopia (>-6.00 diopters) is a complex common disorder that predisposes individuals to retinal detachment, glaucoma, macular degeneration, and premature cataracts. A recent linkage analysis of seven families with autosomal dominant high myopia has identified one locus (MYP2) for high myopia on chromosome 18p11.31 (Young et al.: Am J Hum Genet 1998;63:109-119). Haplotype analysis revealed an initial interval of 7.6 centimorgans (cM). METHODS: Transmission disequilibrium tests (TDT) with both the Statistical Analysis for Genetic Epidemiology (SAGE) 3.1 TDTEX and GENEHUNTER 2 (GH2) programs were performed using chromosome 18p marker alleles for this interval. RESULTS: Using SAGE analysis, the following p values were obtained for markers in marker order in this region: D18S1146 (p = 0.227), D18S481 (p = 0.001), D18S63 (p = 0.062), D18S1138 (p = 0.0004), D18S52 (p = 1.79 x 10(-6)), and D18S62 (p = 0.141). GH2 TDT analysis revealed the following p values for the best allele for the markers: D18S1146 (p = 0.083), D18S481 (p = 0.108), D18S63 (p = 0.034), D18S1138 (p = 0.011), D18S52 (p = 0.007), and D18S62 (p = 0.479). CONCLUSION: These data suggest that the gene for 18p11.31-linked high myopia is most proximal to marker D18S52, with a likely interval of 0.8 cM between markers D18S63 and D18S52. Due to the contraction of the interval size by TDT, these results provide a basis for focused positional cloning and candidate gene analysis at the MYP2 locus.

Chromosomes, Human, Pair 18↗

Genetics and epigenetics in major psychiatric disorders: dilemmas, achievements, applications, and future scope.

No specific gene has been identified for any major psychiatric disorder, including schizophrenia, in spite of strong evidence supporting a genetic basis for these complex and devastating disorders. There are several likely reasons for this failure, ranging from poor study design with low statistical power to genetic mechanisms such as polygenic inheritance, epigenetic interactions, and pleiotropy. Most study designs currently in use are inadequate to uncover these mechanisms. However, to date, genetic studies have provided some valuable insight into the causes and potential therapies for psychiatric disorders. There is a growing body of evidence suggesting that the understanding of the genetic etiology of psychiatric illnesses, including schizophrenia, will be more successful with integrative approaches considering both genetic and epigenetic factors. For example, several genes including those encoding dopamine receptors (DRD2, DRD3, and DRD4), serotonin receptor 2A (HTR2A) and catechol-O-methyltransferase (COMT) have been implicated in the etiology of schizophrenia and related disorders through meta-analyses and large, multicenter studies. There is also growing evidence for the role of DRD1, NMDA receptor genes (GRIN1, GRIN2A, GRIN2B), brain-derived neurotrophic factor (BDNF), and dopamine transporter (SLC6A3) in both schizophrenia and bipolar disorder. Recent studies have indicated that epigenetic modification of reelin (RELN), BDNF, and the DRD2 promoters confer susceptibility to clinical psychiatric conditions. Pharmacologic therapy of psychiatric disorders will likely be more effective once the molecular pathogenesis is known. For example, the hypoactive alleles of DRD2 and the hyperactive alleles of COMT, which degrade the dopamine in the synaptic cleft, are associated with schizophrenia. It is likely that insufficient dopaminergic transmission in the frontal lobe plays a role in the development of negative symptoms associated with this disorder. Antipsychotic therapies with a partial dopamine D2 receptor agonist effect may be a plausible alternative to current therapies, and would be effective in symptom reduction in psychotic individuals. It is also possible that therapies employing dopamine D1/D2 receptor agonists or COMT inhibitors will be beneficial for patients with negative symptoms in schizophrenia and bipolar disorder. The complex etiology of schizophrenia, and other psychiatric disorders, warrants the consideration of both genetic and epigenetic systems and the careful design of experiments to illumine the genetic mechanisms conferring liability for these disorders and the benefit of existing and new therapies.

Brain↗

Genetic analysis of NIDDM. The study of quantitative traits.

Many studies are in progress worldwide to elucidate the genetics of NIDDM. Nevertheless, few articles are available that combine the interdisciplinary fields of medicine, genetics, physiology, and statistics in order to provide the scientific rationale for such an endeavor. Here we describe the methodology and background necessary to study the genetics of NIDDM and discuss how to analyze the data. We also provide a detailed bibliography for researchers and a glossary for those who are not experts in the field. In particular, we wish to emphasize the analysis of intermediate quantitative traits as a means to dissect the genetic basis of NIDDM.

Diabetes Mellitus, Type 2↗

Genetic algorithms-based design and optimization of statistical quality-control procedures.

In general, one cannot use algebraic or enumerative methods to optimize a quality-control (QC) procedure for detecting the total allowable analytical error with a stated probability with the minimum probability for false rejection. Genetic algorithms (GAs) offer an alternative, as they do not require knowledge of the objective function to be optimized and can search through large parameter spaces quickly. To explore the application of GAs in statistical QC, I developed two interactive computer programs based on the deterministic crowding genetic algorithm. Given an analytical process, the program "Optimize" optimizes a user-defined QC procedure, whereas the program "Design" designs a novel optimized QC procedure. The programs search through the parameter space and find the optimal or near-optimal solution. The possible solutions of the optimization problem are evaluated with computer simulation.

Algorithms↗

Genetic diversity in black howler monkeys (Alouatta pigra) from Belize.

To assess the level of genetic variation in a threatened black howler monkey (Alouatta pigra) population, we examined 36 allozyme loci and restriction fragment profiles of mitochondrial DNA (mtDNA). Mean heterozygosity at allozyme loci was only 0.021 and 5.6 percent of the loci were polymorphic. Analyses of mtDNA also revealed low genetic diversity compared with other primates. F-statistics revealed no significant genetic heterogeneity among troops within the Bermudian Landing preserve, but did indicate a deficiency of heterozygotes at one of the two loci. We explore several explanations for this result, which is unexpected in a socially structured primate. Low genetic diversity in this population may reflect its history of demographic bottlenecks.

Alleles↗

Use of classification trees for association studies.

We propose the use of classification trees for association studies. This approach is applied to a data set from Genetic Analysis Workshop 9 (GAW9), and our analysis precisely identified two disease alleles. Our purpose is to demonstrate the great potential of tree-based analyses for genetic studies, and discuss some issues that warrant further investigation.

Alleles↗