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Susan E Hodge

Publications and source records attributed to Susan E Hodge.

At least 19 recordsLinked to original sources
PubMed2006

A third-pass genome scan in panic disorder: evidence for multiple susceptibility loci.

BACKGROUND: Panic disorder (PD) is a common illness with a definite but "complex" genetic contribution and estimated heritability of 30-46%. METHODS: We report a genome scan in 120 multiplex PD pedigrees consisting of 1591 individuals of whom 992 were genotyped with 371 markers at an average spacing of 9cM. Parametric two-point, multipoint, and nonparametric analyses were performed using three PD models (Broad, Intermediate, Narrow) and allowing for homogeneity or heterogeneity. The two-point analyses were also performed allowing for independent male and female recombination fractions (theta). Genome-wide significance was empirically evaluated using simulations of this dataset. RESULTS: Evidence for linkage reached genome-wide significance in one region on chromosome 15q (near GABA-A receptor subunit genes) and was suggestive at loci on 2p, 2q and 9p using an averaged theta. Analyses allowing for sex-specific theta's were consistent except that support at one locus on 2q increased to genome-wide significance and an additional region of suggestive linkage on 12q was identified. However, differences in male and female recombination fractions predicted by the sex-specific approach were not consistent with current physical maps. CONCLUSIONS: These data provide evidence for chromosomal regions on 15q and 2q that may be important in genetic susceptibility to panic disorder. Although we are encouraged by the findings of analyses using sex-specific recombination fractions, we also note that further understanding of this analytic strategy will be important.

Chromosomes, Human, Pair 15↗
PubMed2006

An alternative foundation for the planning and evaluation of linkage analysis. II. Implications for multiple test adjustments.

The 'multiple testing problem' currently bedevils the field of genetic epidemiology. Briefly stated, this problem arises with the performance of more than one statistical test and results in an increased probability of committing at least one Type I error. The accepted/conventional way of dealing with this problem is based on the classical Neyman-Pearson statistical paradigm and involves adjusting one's error probabilities. This adjustment is, however, problematic because in the process of doing that, one is also adjusting one's measure of evidence. Investigators have actually become wary of looking at their data, for fear of having to adjust the strength of the evidence they observed at a given locus on the genome every time they conduct an additional test. In a companion paper in this issue (Strug & Hodge I), we presented an alternative statistical paradigm, the 'evidential paradigm', to be used when planning and evaluating linkage studies. The evidential paradigm uses the lod score as the measure of evidence (as opposed to a p value), and provides new, alternatively defined error probabilities (alternative to Type I and Type II error rates). We showed how this paradigm separates or decouples the two concepts of error probabilities and strength of the evidence. In the current paper we apply the evidential paradigm to the multiple testing problem - specifically, multiple testing in the context of linkage analysis. We advocate using the lod score as the sole measure of the strength of evidence; we then derive the corresponding probabilities of being misled by the data under different multiple testing scenarios. We distinguish two situations: performing multiple tests of a single hypothesis, vs. performing a single test of multiple hypotheses. For the first situation the probability of being misled remains small regardless of the number of times one tests the single hypothesis, as we show. For the second situation, we provide a rigorous argument outlining how replication samples themselves (analyzed in conjunction with the original sample) constitute appropriate adjustments for conducting multiple hypothesis tests on a data set.

Chromosome Mapping↗
PubMed2006

An alternative foundation for the planning and evaluation of linkage analysis. I. Decoupling "error probabilities" from "measures of evidence".

The lod score, which is based on the likelihood ratio (LR), is central to linkage analysis. Users interpret lods by translating them into standard statistical concepts such as p values, alpha levels and power. An alternative statistical paradigm, the Evidential Framework, in contrast, works directly with the LR. A key feature of this paradigm is that it decouples error probabilities from measures of evidence. We describe the philosophy behind and the operating characteristics of this paradigm--based on new, alternatively-defined error probabilities. We then apply this approach to linkage studies of a genetic trait for: I. fully informative gametes, II. double backcross sibling pairs, and III. nuclear families. We consider complete and incomplete penetrance for the disease model, as well as using an incorrect penetrance. We calculate the error probabilities (exactly for situations I and II, via simulation for III), over a range of recombination fractions, sample sizes, and linkage criteria. We show how to choose linkage criteria and plan linkage studies, such that the probabilities of being misled by the data (i.e. concluding either that there is strong evidence favouring linkage when there is no linkage, or that there is strong evidence against linkage when there is linkage) are low, and the probability of observing strong evidence in favour of the truth is high. We lay the groundwork for applying this paradigm in genetic studies and for understanding its implications for multiple tests.

Computer Simulation↗
PubMed2006

Centralizing the non-central chi-square: A new method to correct for population stratification in genetic case-control association studies.

We present a new method, the delta-centralization (DC) method, to correct for population stratification (PS) in case-control association studies. DC works well even when there is a lot of confounding due to PS. The latter causes overdispersion in the usual chi-square statistics which then have non-central chi-square distributions. Other methods approach the noncentrality indirectly, but we deal with it directly, by estimating the non-centrality parameter tau itself. Specifically: (1) We define a quantity delta, a function of the relevant subpopulation parameters. We show that, for relatively large samples, delta exactly predicts the elevation of the false positive rate due to PS, when there is no true association between marker genotype and disease. (This quantity delta is quite different from Wright's F(ST) and can be large even when F(ST) is small.) (2) We show how to estimate delta, using a panel of unlinked "neutral" loci. (3) We then show that delta2 corresponds to tau the noncentrality parameter of the chi-square distribution. Thus, we can centralize the chi-square using our estimate of 6; this is the DC method. (4) We demonstrate, via computer simulations, that DC works well with as few as 25-30 unlinked markers, where the markers are chosen to have allele frequencies reasonably close (within +/- .1) to those at the test locus. (5) We compare DC with genomic control and show that where as the latter becomes overconservative when there is considerable confounding due to PS (i.e. when delta is large), DC performs well for all values of delta.

Bayes Theorem↗
PubMed2006

Possible interaction between HLA-DRbeta1 and thyroglobulin variants in Graves' disease.

Graves' disease (GD) is influenced by two major susceptibility loci, HLA-DR3 and thyroglobulin (Tg). Recently we have shown that specific HLA-DR and Tg gene sequences predispose to Graves' disease. Individuals carrying at least one arginine at position 74 of the DRbeta1 chain (denoted the R- genotype) have a significantly increased risk of GD, as do individuals homozygous for the single nucleotide protein (SNP) in exon 33 of the Tg gene (denoted the CC genotype). Therefore, for the current study we hypothesized that these two genes may interact to influence the etiology of GD. To test this hypothesis, we analyzed the genotypes of 185 Caucasian patients with GD and 143 Caucasian controls for both genes. We tested for an interaction effect, that is, is one gene's effect on GD greater when the other gene is also present than when the other gene is absent? A logistic regression analysis yielded an estimate of 4.31 for the interaction term (p = 0.053). Our results may suggest an interaction between the R- and CC variants in conferring susceptibility to GD. These results, if confirmed, may imply that these two variants interact biologically to increase the odds of GD.

Adult↗
PubMed2005

New simple tests for age-at-onset anticipation: application to panic disorder.

Recently, testing for anticipation has received renewed interest. It is well known that standard statistical methods are inappropriate for this purpose due to problems of sampling bias. Few statistical tests have been proposed for comparing mean age of onset in affected parents with mean age of onset in affected children. All of them are difficult to compute and lack software to perform the tests. In this report, we formulate the problem in terms of symmetry tests. We propose a simple generalized paired t-test and a Wilcoxon signed rank test to adjust for the bias caused by the right truncation of both the parent's and child's ages at onset. We also extend the generalized paired t-test to a random effects model that enables analysis of correlated data from nuclear families, and could be further extended to larger family structures. We illustrate the approaches with an example of panic disorder.

Age of Onset↗
PubMed2004

Investigation of polymorphisms in the CREM gene in panic disorder.

Clinical and animal studies suggest a role for pathways regulated by cyclic-AMP in anxiety. Mouse gene deletion studies, our own linkage findings on chromosome 10, and a recently published genetic association study by Domschke et al. [2003: Am J Med Genet 117B:70-78] suggest that the cAMP responsive element modulator (CREM) may be involved in panic disorder. We have employed a family-based design to investigate the role of DNA sequence variations in the gene for CREM in panic disorder. We have genotyped 613 individuals in 70 panic disorder pedigrees, as well as 42 parent/offspring triads. Subjects were genotyped at two informative single nucleotide polymorphisms (SNPs) and three polymorphic microsatellites in the CREM genomic region; and the data were analyzed for genetic association and linkage. Linkage analysis employing several diagnostic/genetic models produced a maximum lod score of 0.63 for SNP-1, located in the 5' UTR of CREM, under a dominant model with a broad diagnostic definition of panic disorder. Non-parametric analysis, using the NPL statistic or FBAT, also did not support any linkage or association between the markers and panic disorder. All five markers (spanning 77 kb) used in the study showed modest, but significant linkage disequilibrium. Analysis of 2-, 3-, 4-, or 5-marker haplotypes using TRANSMIT failed to find any globally significant results; however, individual haplotypes containing a single allele of MS-3 were nominally associated with panic disorder. These findings provide little additional evidence for a susceptibility locus for panic disorder either within the CREM gene or in a nearby region of chromosome 10p11 in our sample.

5' Untranslated Regions↗
PubMed2004

Interstitial cystitis and panic disorder: a potential genetic syndrome.

BACKGROUND: Evidence from a genetic linkage study had suggested a possible syndrome in some families with panic disorder (PD). This syndrome includes bladder problems (possibly urinary interstitial cystitis [IC]), thyroid disorders, chronic headaches/migraine, and/or mitral valve prolapse. In 19 multiplex families with PD, one marker (D13S779) on chromosome 13 gave a logarithm of odds score of more than 4 when individuals with any of the syndrome conditions were analyzed as affected. Families with the bladder problems yielded the highest logarithm of odds scores. These findings were replicated in an extended sample of 60 families. Whereas PD had been well characterized by direct interview, the urologic problems had been found only via medical history checklists and records. A case review by a board-certified urologist suggested they could be IC. OBJECTIVE: To determine whether patients diagnosed as having IC by urodynamics and/or cystoscopy and their first-degree relatives (FDRs) have increased rates of the syndrome conditions, thus validating that the bladder problems observed in the linkage study could be IC and providing further support for the panic syndrome. DESIGN: Case-control and family history study. SETTING: Two metropolitan urology clinics. PARTICIPANTS: One hundred forty-six probands (67 with IC and 79 with other urologic disorders) and 815 FDRs. MAIN OUTCOME MEASURES: Lifetime rates of syndrome conditions in probands and FDRs who were blind to urologic or psychiatric diagnoses in the proband. RESULTS: Compared with patients without IC, patients with IC had a significantly higher lifetime prevalence of PD (controlling for age and sex) (odds ratio, 4.05; 95% confidence interval, 1.22-13.40; P =.02) and a higher lifetime prevalence of any of the syndrome disorders (controlling for age and sex) (odds ratio, 2.22; 95% confidence interval, 0.89-5.54; P =.09). First-degree relatives of probands with (vs without) IC were significantly more likely to have PD, thyroid disorder, urologic problems, and any of the syndrome disorders (controlling for age and sex of the relative and sex of the proband) (adjusted odds ratio, 1.95; 95% confidence interval, 1.13-3.38; P =.02). These results in relatives were not influenced by PD in probands, and did not change substantially when controlling for the proband-relative relationship, modeling age as a categorical (vs continuous) variable, or excluding FDRs with PD. There were no interactions between proband IC status and sex of the relative. CONCLUSIONS: The increased frequency of seemingly disparate disorders in patients with IC and their FDRs is consistent with the genetic linkage findings in families with PD. These findings suggest that the bladder problems observed in the linkage study may be IC. The hypothesis that there is a familial, possibly pleiotropic, syndrome that may include IC, PD, thyroid disorders, and other disorders of possible autonomic or neuromuscular control deserves further investigation.

Adult↗
PubMed2004

Evidence for genetic linkage between a polymorphism in the adenosine 2A receptor and panic disorder.

Data from clinical and behavioral pharmacological studies have implicated adenosine in anxiety behaviors, while genetic studies have suggested that adenosine receptors may be associated with panic disorder. We have undertaken an analysis of several DNA sequence variations in the adenosine 2A receptor (ADORA2A) in a large sample of panic disorder pedigrees. Individuals from 70 panic disorder pedigrees, and 83 child-parent 'trios', were genotyped at five single-nucleotide polymorphisms (SNPs) in and near the ADORA2A gene and were analyzed for genetic linkage and association. Linkage analysis revealed elevated LOD scores for a silent substitution (1083C/T, SNP-4) in the second coding exon. This SNP has been previously reported to be associated with panic disorder. We observed a maximal heterogeneity LOD score of 2.98 (theta=0) under a recessive genetic model and narrow diagnostic model. Other SNPs showed no evidence for linkage. Association tests were not significant for any of the five ADORA2A SNPs. When SNP haplotypes were assessed in the triads with TRANSMIT, one 3-marker haplotype (SNPs 1, 4, 5) was nominally significantly associated with panic disorder (p=0.029). Pairwise estimations of linkage disequilibrium between the SNPs showed strong patterns of linkage disequilibrium across the ADORA2A locus. Analyses carried out by broadening the panic disorder phenotype to include agoraphobia continued to support linkage to ADORA2A. Our findings provide evidence for a susceptibility locus for panic disorder, and possibly including agoraphobia, either within the ADORA2A gene or in a nearby region of chromosome 22, and serves as the first successful candidate gene replication study in panic disorder.

Female↗
PubMed2004

The reliability of haplotyping inference in nuclear families: misassignment rates for SNPs and microsatellites.

Single nucleotide polymorphisms (SNPs) are widely used when investigators try to map complex disease genes. Although biallelic SNP markers are less informative than microsatellite markers, one can increase their information content by using haplotypes. However, assigning haplotypes (i.e., assigning phase) correctly can be problematic in the presence of SNP heterozygosity. For example, a doubly heterozygous individual, with genotype 12, 12, could have haplotypes 1-1/2-2 or 1-2/2-1 with equal probability; in the absence of additional information, there is no way to determine which haplotype is correct. Thus an algorithm that assigns haplotypes to such an individual will assign the wrong one 50% of the time. We have studied the frequency of haplotype misassignments, i.e., haplotypes that are misassigned solely because of inherent marker ambiguity (not because of errors in genotyping or calculation). We examined both SNPs and microsatellite markers. We used the computer programs GENEHUNTER and SIMWALK to assign the haplotypes. We simulated (a) families with 1-5 children, (b) haplotypes involving different numbers of marker loci (3, 5, 7 and 10 loci, all in linkage equilibrium), and (c) different allele frequencies. Misassignment rates are highest (a) in small families, (b) with many SNP loci, and (c) for loci with the greatest heterozygosity (i.e., where both alleles have frequency 0.5). For example, for triads (i.e., one-child families with both parents genotyped), misassignment rates for SNPs can reach almost 50%. Family sizes of 4-5 children are required in order to ensure a misassignment frequency of < or = 5% for ten-SNP haplotypes with allele frequencies of 0.25-0.5. For microsatellites, a family size of at least 2-3 children is necessary to keep haplotyping misassignments < or = 5%. Finally, we point out that it is misleading for a computer program to yield haplotype assignments without indicating that they may have been misassigned, and we discuss the implications of these misassignments for association and linkage analysis.

Chromosome Mapping↗
PubMed2004

Effect of population stratification on case-control association studies. I. Elevation in false positive rates and comparison to confounding risk ratios (a simulation study).

OBJECTIVES: This is the first of two articles discussing the effect of population stratification on the type I error rate (i.e., false positive rate). This paper focuses on the confounding risk ratio (CRR). It is accepted that population stratification (PS) can produce false positive results in case-control genetic association. However, which values of population parameters lead to an increase in type I error rate is unknown. Some believe PS does not represent a serious concern, whereas others believe that PS may contribute to contradictory findings in genetic association. We used computer simulations to estimate the effect of PS on type I error rate over a wide range of disease frequencies and marker allele frequencies, and we compared the observed type I error rate to the magnitude of the confounding risk ratio. METHODS: We simulated two populations and mixed them to produce a combined population, specifying 160 different combinations of input parameters (disease prevalences and marker allele frequencies in the two populations). From the combined populations, we selected 5000 case-control datasets, each with either 50, 100, or 300 cases and controls, and determined the type I error rate. In all simulations, the marker allele and disease were independent (i.e., no association). RESULTS: The type I error rate is not substantially affected by changes in the disease prevalence per se. We found that the CRR provides a relatively poor indicator of the magnitude of the increase in type I error rate. We also derived a simple mathematical quantity, Delta, that is highly correlated with the type I error rate. In the companion article (part II, in this issue), we extend this work to multiple subpopulations and unequal sampling proportions. CONCLUSION: Based on these results, realistic combinations of disease prevalences and marker allele frequencies can substantially increase the probability of finding false evidence of marker disease associations. Furthermore, the CRR does not indicate when this will occur.

Bias↗
PubMed2004

Effect of population stratification on case-control association studies. II. False-positive rates and their limiting behavior as number of subpopulations increases.

There has been considerable debate in the literature concerning bias in case-control association mapping studies due to population stratification. In this paper, we perform a theoretical analysis of the effects of population stratification by measuring the inflation in the test's type I error (or false-positive rate). Using a model of stratified sampling, we derive an exact expression for the type I error as a function of population parameters and sample size. We give necessary and sufficient conditions for the bias to vanish when there is no statistical association between disease and marker genotype in each of the subpopulations making up the total population. We also investigate the variation of bias with increasing subpopulations and show, both theoretically and by using simulations, that the bias can sometimes be quite substantial even with a very large number of subpopulations. In a companion simulation-based paper (Heiman et al., Part I, this issue), we have focused on the CRR (confounding risk ratio) and its relationship to the type I error in the case of two subpopulations, and have also quantified the magnitude of the type I error that can occur with relatively low CRR values.

Bias↗
PubMed2004

Comparative informativeness for linkage of multiple SNPs and single microsatellites.

Single nucleotide polymorphisms (SNPs), or biallelic markers, are popular in genetic linkage studies due to their abundance in the genome, stability, and ease of scoring. We determined the 'information ratio' (IR) of closely spaced SNPs in simulated nuclear families and affected sib pairs (ASPs). (The IR is the ratio of actual average maximum lod score to the maximum lod score attainable if the marker were fully informative.) The nuclear families included parental information, whereas the ASPs did not. We analyzed these SNPs in two ways: (1) using multipoint analysis, and (2) treating the SNPs as 'composite markers' (i.e., haplotypes, as assigned by GENEHUNTER). (3) We also calculated the IR of a single microsatellite marker with multiple alleles and compared with the IR from the SNPs. For each set of input conditions, we simulated 1000 nuclear families, of 2, 3, 4, or 5 children each, as well as 1000 ASPs. We generated SNP marker data for strings of k = 1, 2, 3, 5, 7, and 10 SNP loci, with no recombination (theta = 0) and no linkage disequilibrium among the SNPs. The MAF (minor allele frequency) was either 0.5 or 0.25, and allele frequencies were the same for all k loci in any analysis. We also generated marker data for one single-locus microsatellite marker, with m = 3, 4, 5, 6, 7, and 9 equally frequent alleles. In all simulations, the disease was fully penetrant dominant, and there was no recombination or linkage disequilibrium among markers or between marker and disease. When multipoint analysis was used, we found that 5-7 closely spaced SNPs were usually enough to yield an IR of approximately 100%, for nuclear families of any size. However, for the ASPs, even 7-10 SNPs yielded an IR of only 70-80%. A microsatellite with 9 equally frequent alleles yielded about the same IR (86-88%) as a string of 4-5 SNPs, in nuclear families. SNPs analyzed as 'composite markers' analyses performed worse, due to the inherent ambiguity of SNP haplotyping.

Alleles↗
PubMed2003

Comparison of the linkage results of two phenotypic constructs from longitudinal data in the Framingham Heart Study: analyses on data measured at three time points and on the average of three measurements.

BACKGROUND: Family studies are often conducted in a cross-sectional manner without long-term follow-up data. The relative contribution of a gene to a specific trait could change over the lifetime. The Framingham Heart Study offers a unique opportunity to investigate potential gene x time interaction. We performed linkage analysis on the body mass index (BMI) measured in 1970, 1978, and 1986 for this project. RESULTS: We analyzed the data in two different ways: three genome-wide linkage analyses on each exam, and one genome-wide linkage analysis on the mean of the three measurements. Variance-component linkage analyses were performed by the SOLAR program. Genome-wide scans show consistent evidence of linkage of quantitative trait loci (QTLs) on chromosomes 3, 6, 9, and 16 in three measurements with a maximum multipoint LOD score > 2.2. However, only chromosome 9 has a LOD score = 2.14 when the mean values were analyzed. More interestingly, we found potential gene x environment interactions: increasing LOD scores with age on chromosomes 3, 9, and 16 and decreasing LOD scores on chromosome 6 in the three exams. CONCLUSION: The results indicate two points: 1) it is possible that a gene (or genes) influencing BMI is (are) up- or down-regulated as people aged due to aging process or changes in lifestyle, environments, or genetic epistasis; 2) using mean values from longitudinal data may reduce the power to detect linkage and may have no power to detect gene x time, and/or gene x gene interactions.

Adult Children↗