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S E Hodge

Publications and source records attributed to S E Hodge.

At least 37 records · Page 2Linked to original sources
PubMed1999

Simulated data for a complex genetic trait (problem 2 for GAW11): how the model was developed, and why.

This paper describes a simulated data set created as Problem 2 for GAW11. The generating model for Problem 2 involved two different genetic diseases, or "types," in three separate populations. The two-locus (2L) type results from the epistatic interaction of two genetic loci, and the three-allele type, from a single locus with two disease-causing alleles and one normal allele. Each type has two phenotypic forms: Mild and Severe. Both forms are subject to both genetic and environmental influences. The disease occurs in three different hypothetical populations, each with different disease allele frequencies and penetrances. In two populations there is also a fourth locus with an allele that is associated with the 2L type. Misdiagnosis can occur, but only after a family has already been ascertained through > or = 2 "genetically" affected offspring. Finally, the three different populations are studied by four different hypothetical research groups. These groups each have their own ideas about how the disease is inherited and have therefore devised different ascertainment schemes based on those beliefs. Each research group collected 100-family data sets, including data on 300 markers on six chromosomes and measurements on disease status and on the proposed two environmental factors. GAW participants were supplied with 25 random replicates of each data set.

Alleles↗
PubMed1999

Direct power comparisons between simple LOD scores and NPL scores for linkage analysis in complex diseases.

Several methods have been proposed for linkage analysis of complex traits with unknown mode of inheritance. These methods include the LOD score maximized over disease models (MMLS) and the "nonparametric" linkage (NPL) statistic. In previous work, we evaluated the increase of type I error when maximizing over two or more genetic models, and we compared the power of MMLS to detect linkage, in a number of complex modes of inheritance, with analysis assuming the true model. In the present study, we compare MMLS and NPL directly. We simulated 100 data sets with 20 families each, using 26 generating models: (1) 4 intermediate models (penetrance of heterozygote between that of the two homozygotes); (2) 6 two-locus additive models; and (3) 16 two-locus heterogeneity models (admixture alpha = 1.0,.7,.5, and.3; alpha = 1.0 replicates simple Mendelian models). For LOD scores, we assumed dominant and recessive inheritance with 50% penetrance. We took the higher of the two maximum LOD scores and subtracted 0.3 to correct for multiple tests (MMLS-C). We compared expected maximum LOD scores and power, using MMLS-C and NPL as well as the true model. Since NPL uses only the affected family members, we also performed an affecteds-only analysis using MMLS-C. The MMLS-C was both uniformly more powerful than NPL for most cases we examined, except when linkage information was low, and close to the results for the true model under locus heterogeneity. We still found better power for the MMLS-C compared with NPL in affecteds-only analysis. The results show that use of two simple modes of inheritance at a fixed penetrance can have more power than NPL when the trait mode of inheritance is complex and when there is heterogeneity in the data set.

Gene Frequency↗
PubMed1999

Lack of genetic linkage or association between a functional serotonin transporter polymorphism and panic disorder.

Given the efficacy of medications that interact with the serotonin transporter (5-HTT) in the treatment of panic disorder, we have used a family-based design to test for genetic association and linkage between panic disorder and a functional polymorphism in the promoter of the gene for 5-HTT. In this study, 340 individuals in 45 families, as well as 74 haplotype relative risk 'trios' were genotyped at the polymorphic locus, which consists of a 44 base pair deletion/insertion. There were no significant differences in allele frequencies or occurrence of genotypes within the triads. No linkage between the 5-HTT polymorphism and panic disorder was observed in the multiplex families, using a variety of simulations for dominant and recessive models of inheritance. Recent reports suggest an association between the 5-HTT polymorphism and anxiety-related traits, as measured with personality assessment. The results reported here provide evidence that the genetic basis of panic disorder may be distinct from anxiety-related traits assessed by personality inventories in normal populations.

Alleles↗
PubMed1998

Association studies in the presence of comorbidity: design and analysis.

Methods for the design and analysis of allelic association studies in the presence of two comorbid disorders are discussed. These methods are applicable to population-based (i.e., case-control) designs. We first develop probability models that represent pathways to the comorbidity of two disorders when it is hypothesized that at least one of the two disorders is associated with a specific allele. These potential pathways are illustrated with the specific example of the association of the human leptin (OB) gene with obesity and major depressive disorders in humans. We then discuss methods of design and analysis using the well-known methods of log-linear analysis [Bishop et al., 1975: "Discrete Multivariate Analysis." M.I.T. Press, Cambridge, MA] to differentiate between these pathways. With the increasing focus in psychiatric genetics on both association studies and pathways to comorbidity we anticipate that these methods will have wide applications.

Alleles↗
PubMed1998

Results of a genome-wide genetic screen for panic disorder.

Panic disorder is characterized by spontaneous and recurrent panic attacks, often accompanied by agoraphobia. The results of family, twin, and segregation studies suggest a genetic role in the etiology of the illness. We have genotyped up to 23 families that have a high density of panic disorder with 540 microsatellite DNA markers in a first-pass genomic screen. The thirteen best families (ELOD > 6.0 under the dominant genetic model) have been genotyped with an ordered set of markers encompassing all the autosomes, at an average marker density of 11 cM. Over 110,000 genotypes have been generated on the whole set of families, and the data have been analyzed under both a dominant and a recessive model, and with the program SIBPAIR. No lod scores exceed 2.0 for either parametric model. Two markers give lod scores over 1.0 under the dominant model (chromosomes 1p and 20p), and four do under the recessive model (7p, 17p, 20q, and X/Y). One of these (20p) may be particularly promising. Analysis with SIBPAIR yielded P values equivalent to a lod score of 1.0 or greater (i.e., P < .016, one-sided, uncorrected for multiple tests) for 11 marker loci (2, 7p, 8p, 8q, 9p, 11q, 12q, 16p, 20p and 20q).

Adolescent↗
PubMed1998

Exact elods and exact power for affected sib pairs analyzed for linkage under simple right and wrong models.

In the struggle to understand the inheritance of complex psychiatric diseases, investigators frequently turn to affected sib pair (ASP) methods of linkage analysis. This paper examines the quantity of "information" (as indicated by the expected maximum lod score [ELOD] and/or power), when ASP data originating from simple dominant or recessive inheritance are analyzed for linkage, both as simple dominant and as simple recessive. That is, these data are analyzed under both right and wrong models. Results are exact (i.e., not based on asymptotic approximations) and thus hold for small sample sizes (e.g., n = 20 sib pairs), as well as for large samples. It is shown that analyzing dominant ASPs (that is, sib pairs suffering from a dominantly inherited disease) as recessive (i.e., under the wrong model) can reduce the ELOD by 20-24% when recombination fraction (theta) is small. In situations where theta is large or gene frequency high, the information loss is less, because in those situations dominant ASPs contain very little information to begin with. For recessive ASPs, the information loss when analyzed under the wrong model is even more pronounced. The fact that a decision to sample ASP data discards more potential linkage information for dominant diseases than for recessive ones is also discussed, as are implications for more complex models. These findings are also of interest because it has been shown that the nonparametric Mean Test of ASPs is statistically identical to recessive lod score analysis [Knapp et al., Hum Hered 44:44-51, 1994]. Hence, the power results for the recessive analyses are also valid for the Mean Test, and thus are valuable for comparing how dominant and recessive ASP data fare in this particular nonparametric analysis.

Gene Frequency↗
PubMed1998

Ironic contrast.

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Genetic Counseling↗
PubMed1998

Logistic regression model for analyzing extended haplotype data.

Recently, there has been increased interest in evaluating extended haplotypes in p53 as risk factors for cancer. An allele-specific polymerase chain reaction (PCR) method, confirmed by restriction analysis, has been used to determine absolute extended haplotypes in diploid genomes. We describe statistical analyses for comparing cases and controls, or comparing different ethnic groups with respect to haplotypes composed of several biallelic loci, especially in the presence of other covariates. Tests based on cross-tabulating all possible genotypes by disease state can have limited power due to the large number of possible genotypes. Tests based simply on cross-tabulating all possible haplotypes by disease state cannot be extended to account for other variables measured on the individual. We propose imposing an assumption of additivity upon the haplotype-based analysis. This yields a logistic regression in which the outcome is case or control, and the predictor variables include the number of copies (0, 1, or 2) of each haplotype, as well as other explanatory variables. In a case-control study, the model can be constructed so that each coefficient gives the log odds ratio for disease for an individual with a single copy of the suspect haplotype and another copy of the most common haplotype, relative to an individual with two copies of the most common haplotype. We illustrate the method with published data on p53 and breast cancer. The method can also be applied to any polymorphic system, whether multiple alleles at a single locus or multiple haplotypes over several loci.

Alleles↗
PubMed1998

The power to detect linkage in complex disease by means of simple LOD-score analyses.

Maximum-likelihood analysis (via LOD score) provides the most powerful method for finding linkage when the mode of inheritance (MOI) is known. However, because one must assume an MOI, the application of LOD-score analysis to complex disease has been questioned. Although it is known that one can legitimately maximize the maximum LOD score with respect to genetic parameters, this approach raises three concerns: (1) multiple testing, (2) effect on power to detect linkage, and (3) adequacy of the approximate MOI for the true MOI. We evaluated the power of LOD scores to detect linkage when the true MOI was complex but a LOD score analysis assumed simple models. We simulated data from 14 different genetic models, including dominant and recessive at high (80%) and low (20%) penetrances, intermediate models, and several additive two-locus models. We calculated LOD scores by assuming two simple models, dominant and recessive, each with 50% penetrance, then took the higher of the two LOD scores as the raw test statistic and corrected for multiple tests. We call this test statistic "MMLS-C." We found that the ELODs for MMLS-C are >=80% of the ELOD under the true model when the ELOD for the true model is >=3. Similarly, the power to reach a given LOD score was usually >=80% that of the true model, when the power under the true model was >=60%. These results underscore that a critical factor in LOD-score analysis is the MOI at the linked locus, not that of the disease or trait per se. Thus, a limited set of simple genetic models in LOD-score analysis can work well in testing for linkage.

Chromosome Mapping↗
PubMed1997

Mapping of familial primary pulmonary hypertension locus (PPH1) to chromosome 2q31-q32.

BACKGROUND: The pathogenesis of primary pulmonary hypertension (PPH) is unknown, although in some instances families with multiple affected members suggest a genetic etiology. METHODS AND RESULTS: We used microsatellite markers and linkage analysis in a large family with PPH to determine the chromosomal location of their disease gene. We tested a second, ethnically distinct, family for cosegregation of disease with markers from the linked region. We mapped the disease locus PPH1; GDB/HUGO designation (GDB:1381541; July 1996), approved when this work was accepted for publication in abstract form (Circulation. 1996;94[suppl I]:1-49.), in these families to a 27-cM region on chromosome 2q31-q32, with a maximum lod score of 3.87 associated with markers D2S350 and D2S364. CONCLUSIONS: Cosegregation of this region with disease in different ethnic groups suggests that we mapped an important locus in familial PPH. Careful study of additional families and sporadic cases will be required to confirm this localization of PPH1 and characterize its overall role.

Adolescent↗
PubMed1997

Genetic anticipation and imprinting in bipolar I illness.

BACKGROUND: The study focused on: (1) the existence of genetic anticipation in a randomly selected sample of bipolar I patients using broad and narrow definitions of the affection status in the parental generation; (2) the relationship between anticipation and the age at investigation in probands and in their relatives; (3) the relationship between anticipation and imprinting. METHOD: One hundred and fifteen bipolar I patients and their first- to third-degree relatives were diagnosed according to DSM-III-R criteria using the Diagnostic Interview for Genetic Studies and the Family Interview for Genetic Studies. RESULTS: Age at onset was found to be 6-10 years younger in probands with affected parents or uncles/aunts. Two-thirds of these families showed positive anticipation under both the broad and the narrow definitions of affection status in the parents' generation. The age at investigation was younger in probands showing positive anticipation. Anticipation was found only in probands inheriting the disorder from the paternal side. CONCLUSIONS: In spite of the inevitable association between young current age and young age at onset, which could result in spurious anticipation effects, our findings suggest that this phenomenon is not the sole cause of observed anticipation.

Adolescent↗
PubMed1997

Magnitude of type I error when single-locus linkage analysis is maximized over models: a simulation study.

It is well known that maximizing the maximum LOD score over multiple parameter values or models (i.e., the method of mod scores, or MMLS), will inflate type I error, compared with assuming only one parameter value/model in the linkage analysis. On the other hand, a mod score often has greater power to detect linkage than does a LOD score (Z) calculated under a wrong genetic model. Therefore, it is of interest to determine the actual magnitude of type I error in realistic genetic situations. Simulated data sets with no linkage were generated under three dominant and three recessive single-locus models, with reduced penetrance (f = .8, .5, and .2). Data sets were analyzed for linkage by (1) maximizing over penetrance only, (2) maximizing over "dominance model" (i.e., dominant versus recessive), and (3) maximizing over both penetrance and dominance model simultaneously. In (1), the resultant significance levels were approximately doubled, compared with baseline values if one had not maximized over penetrances (i.e., compared with a one-sided chi2(1)). In (2), significance levels were increased somewhat less, and, in (3), they were increased by approximately two to three times (but not more than four times) over those of the one-sided chi2(1). This means that, for a given size of test alpha, an investigator would need to increase the Z used as a test criterion, by approximately 0.30 LOD units for analyses as in (1) or (2) and by 0.60 Z units for analyses as in (3). These guidelines, which are valid up to approximately Z = 3.0, are conservative for (1) and are very conservative for (2) and (3). By quantifying the increase in significance level (or, correspondingly, the increase in Z), our findings will enable users to rationally assess the advantages versus the disadvantages of mod scores.

Computer Simulation↗
PubMed1996

The essence of single ascertainment.

We propose a fundamental new definition of single ascertainment, namely, that single ascertainment is any ascertainment scheme in which P[pedigree is ascertained/true structure of pedigree] alpha p(theta), where p(theta) is some function of genetic parameters theta but is not a function of pedigree structure. Stated in words: Under single ascertainment, all pedigrees have equal (or proportional with respect to genetic parameters) probabilities of being ascertained, independent of pedigree size or structure. This new definition of single ascertainment allows us to show several results: (1) The correct likelihood consists of the probability of the data conditioned on the observed pedigree, divided by the function p(theta), whether sampling is "proband-independent" or "proband-dependent." (2) More-familiar definitions of single ascertainment all represent special cases of our definition. (3) When p(theta) represents the prevalence of the trait being studied, our definition corresponds to "classical" single ascertainment, i.e., ascertainment through a single "proband." However, the concept of p(theta) can also be generalized to represent the population frequency of configurations of affected relatives (such as affected sib pairs); we call this "generalized single ascertainment."

Mathematical Computing↗
PubMed1996

Age-at-interview bias in anticipation studies: computer simulations and an example with panic disorder.

The phenomenon of anticipation has received considerable interest recently, especially among researchers investigating the genetics of psychiatric disorders. Anticipation can involve an earlier age at onset, greater severity, and/or a higher number of affected individuals in successive generations within a family. There is some controversy concerning detection of age-at-onset anticipation, due to problems of sampling bias, which may account for the phenomenon by preferentially sampling either lateronset parents or earlier-onset children. One source of bias that has not been explicitly investigated is differential age at interview between parent and child, such that parents have passed through more of the risk period than their offspring. We conducted a computer simulation study of affected parent-child pairs to determine whether, for realistic age-at-onset and age-at-interview distributions, this source of bias is a serious one. Our results show that the timing of diagnostic assessment can strongly affect the ascertainment of parent-child pairs, to produce a severely biased sample exhibiting apparent anticipation. Under realistic assumptions, an investigator may face a greatly increased risk of false positives (i.e. detecting anticipation when none exists). For example, a nominal 5% significance level may correspond to true p values as high as 50% or even approaching 100%. We conclude with an application to existing data on panic disorder.

Adult↗