Genetic Analysis of a Large Family with Migraine, Vertigo, and Motion Sickness.

BACKGROUND: Migraine is a common disorder most typically presenting as headache and often associated with vertigo and motion sickness. It is a genetically complex condition with multiple genes ultimately contributing to the predisposition and development of this episodic neurological disorder. We identified a large American family of 29 individuals of which 17 members suffered from at least one of these disorders, migraine, vertigo, or motion sickness. Many of these individuals suffered from several simultaneously. We hypothesized that vertigo and motion sickness may involve genes that are independent to those directly contributing to migraine susceptibility. METHODS: Genome-wide linkage analysis performed using 400 microsatellite repeat markers spaced at 10 cM throughout the genome. The members of this family were phenotyped for each condition, migraine, vertigo, and motion sickness and analyzed separately. Statistical analysis was performed using two-point and multipoint linkage analysis employing a number of models including autosomal recessive or dominant patterns of inheritance with high and low genetic penetrance. RESULTS: We identified a novel locus for migraine, 9q13-q22 (maximum two-point logarithm of odds [LOD] score-2.51). In addition, there are suggestive LOD scores that localize to different chromosomes for each phenotype; vertigo (chromosome 18, LOD score of 1.82) and motion sickness (chromosome 4, LOD score of 2.09). CONCLUSIONS: Our analysis supports our hypothesis that the migraine-associated vertigo and motion sickness may involve distinct susceptibility genes.

Analyse génétique d'une famille étendue dont les membres souffrent de migraines, de vertiges et du mal des transports. Contexte : La migraine est un trouble courant qui entraîne habituellement des maux de tête et qui est souvent associé à des vertiges et au mal des transports. Il s'agit aussi d'une condition génétique complexe en vertu de laquelle de nombreux gènes contribuent à terme à cette prédisposition et au développement de ce trouble neurologique périodique. À cet égard, nous avons identifié une famille étendue américaine comptant 29 membres. De ce nombre, 17 d'entre eux avaient souffert d'au moins un de ces troubles : des migraines, des vertiges ou le mal des transports. À noter que plusieurs d'entre eux avaient souffert de ces troubles en même temps. Nous avons émis l'hypothèse que les vertiges et le mal des transports pourraient impliquer des gènes qui sont indépendants de ceux contribuant directement à la propension aux migraines. Méthodes : Nous avons effectué une analyse de liaison au moyen de 400 marqueurs microsatellites répétés et espacés à tous les 10 cm au sein de l'ensemble du génome des membres de cette famille. Les membres de cette famille ont été « phénotypés ¼ pour chaque type de trouble (les migraines, les vertiges et le mal des transports) et ont été ensuite analysés de façon séparée. Nous avons effectué une analyse statistique au moyen de l'analyse de liaison multipoint et à deux points, utilisant pour ce faire un certain nombre de modèles, par exemple le modèle autosomique récessif ou des patterns dominants de transmission avec une pénétrance génétique élevée ou faible. Résultats : Nous avons été en mesure d'identifier un nouveau locus dans le cas de la migraine : 9q13-q22 (maximum 2-points ; score au logarithme des probabilités ou LOD : - 2,51). De plus, il est des scores révélateurs au logarithme des probabilités qui permettent de localiser divers chromosomes pour chaque phénotype : vertiges (chromosome 18 ; score au logarithme des probabilités ou LOD : 1,82) et mal des transports (chromosome 4 ; score au logarithme des probabilités ou LOD : 2,09). Conclusions : Notre analyse confirme ainsi notre hypothèse initiale, à savoir que les cas de migraine auxquels sont associés des vertiges et le mal des transports pourraient très bien impliquer différents gènes de susceptibilité.

Analysis of the interleukin-1 receptor antagonist gene variable number tandem repeats in ischemic stroke.

BACKGROUND: There is an increasing interest in the role of inflammatory mechanisms contributing to the development of stroke. Recent studies have reported an association between allele 2 of a variable number tandem repeat of the interleukin-1 receptor antagonist (IL1RN) gene in Caucasian patients with ischemic stroke. The purpose of this investigation is to independently confirm these results in our study population. METHODS: We recruited and genotyped 516 Caucasian patients with ischemic stroke and 380 matched controls. Tests of association were performed to estimate odds ratio (OR) for the IL1RN gene variable number tandem repeat polymorphism with case-control status. Genotype frequencies of IL1RN gene were compared by case-control and symptom status using χ2 contingency tables and logistic regression models. RESULTS: No significant association was observed between any of the IL1RN gene genotypes and ischemic stroke. The unadjusted association model a, and the fully saturated model e, adjusted for age, gender, and stroke risk factors demonstrated no significant increase in risk associated with the IL1RN gene 2/2 genotype (a: OR, 1.11; 95% confidence interval [CI], .67-1.89; P=.615; and e: OR, .95; 95% CI, .46-1.94; P=.574). Analyses of genotypic and allelic frequencies of each Trial of Org 10172 in Acute Stroke Treatment subtype with control and pairwise comparison between stroke subtypes did not show any significant differences in their distributions, and all P values were greater than the significance level of .05. CONCLUSION: Our results do not confirm an association between the gene and ischemic stroke in Caucasian patients.

Predicting functionally important SNP classes based on negative selection.

BACKGROUND: With the advent of cost-effective genotyping technologies, genome-wide association studies allow researchers to examine hundreds of thousands of single nucleotide polymorphisms (SNPs) for association with human disease. Recently, many researchers applying this strategy have detected strong associations to disease with SNP markers that are either not in linkage disequilibrium with any nonsynonymous SNP or large distances from any annotated gene. In such cases, no well-established standard practice for effective SNP selection for follow-up studies exists. We aim to identify and prioritize groups of SNPs that are more likely to affect phenotypes in order to facilitate efficient SNP selection for follow-up studies. RESULTS: Based on the annotations available in the Ensembl database, we categorized SNPs in the human genome into classes related to regulatory attributes, such as epigenetic modifications and transcription factor binding sites, in addition to classes related to gene structure and cross-species conservation. Using the distribution of derived allele frequencies (DAF) within each class, we assessed the strength of natural selection for each class relative to the genome as a whole. We applied this DAF analysis to Perlegen resequenced SNPs genome-wide. Regulatory elements annotated by Ensembl such as specific histone methylation sites as well as classes defined by cross-species conservation showed negative selection in comparison to the genome as a whole. CONCLUSIONS: These results highlight which annotated classes are under purifying selection, have putative functional importance, and contain SNPs that are strong candidates for follow-up studies after genome-wide association. Such SNP annotation may also be useful in interpreting results of whole-genome sequencing studies.

An analysis of methylenetetrahydrofolate reductase and glutathione S-transferase omega-1 genes as modifiers of the cerebral response to ischemia.

BACKGROUND: Cerebral ischemia involves a series of reactions which ultimately influence the final volume of a brain infarction. We hypothesize that polymorphisms in genes encoding proteins involved in these reactions could act as modifiers of the cerebral response to ischemia and impact the resultant stroke volume. The final volume of a cerebral infarct is important as it correlates with the morbidity and mortality associated with non-lacunar ischemic strokes. METHODS: The proteins encoded by the methylenetetrahydrofolate reductase (MTHFR) and glutathione S-transferase omega-1 (GSTO-1) genes are, through oxidative mechanisms, key participants in the cerebral response to ischemia. On the basis of these biological activities, they were selected as candidate genes for further investigation. We analyzed the C677T polymorphism in the MTHFR gene and the C419A polymorphism in the GSTO-1 gene in 128 patients with non-lacunar ischemic strokes. RESULTS: We found no significant association of either the MTHFR (p = 0.72) or GSTO-1 (p = 0.58) polymorphisms with cerebral infarct volume. CONCLUSION: Our study shows no major gene effect of either the MTHFR or GSTO-1 genes as a modifier of ischemic stroke volume. However, given the relatively small sample size, a minor gene effect is not excluded by this investigation.

Are molecular haplotypes worth the time and expense? A cost-effective method for applying molecular haplotypes.

Because current molecular haplotyping methods are expensive and not amenable to automation, many researchers rely on statistical methods to infer haplotype pairs from multilocus genotypes, and subsequently treat these inferred haplotype pairs as observations. These procedures are prone to haplotype misclassification. We examine the effect of these misclassification errors on the false-positive rate and power for two association tests. These tests include the standard likelihood ratio test (LRTstd) and a likelihood ratio test that employs a double-sampling approach to allow for the misclassification inherent in the haplotype inference procedure (LRTae). We aim to determine the cost-benefit relationship of increasing the proportion of individuals with molecular haplotype measurements in addition to genotypes to raise the power gain of the LRTae over the LRTstd. This analysis should provide a guideline for determining the minimum number of molecular haplotypes required for desired power. Our simulations under the null hypothesis of equal haplotype frequencies in cases and controls indicate that (1) for each statistic, permutation methods maintain the correct type I error; (2) specific multilocus genotypes that are misclassified as the incorrect haplotype pair are consistently misclassified throughout each entire dataset; and (3) our simulations under the alternative hypothesis showed a significant power gain for the LRTae over the LRTstd for a subset of the parameter settings. Permutation methods should be used exclusively to determine significance for each statistic. For fixed cost, the power gain of the LRTae over the LRTstd varied depending on the relative costs of genotyping, molecular haplotyping, and phenotyping. The LRTae showed the greatest benefit over the LRTstd when the cost of phenotyping was very high relative to the cost of genotyping. This situation is likely to occur in a replication study as opposed to a whole-genome association study.

Association of angiotensinogen gene polymorphisms with essential hypertension in African-Americans and Caucasians.

OBJECTIVE: Molecular variants of angiotensinogen (AGT) have been linked to essential hypertension, and promoter variants have been shown to alter the transcription rate of AGT in vitro. We employed a case-control study to determine whether single nucleotide polymorphisms (SNPs) in the promoter region of AGT were associated with hypertension in African-Americans and Caucasians. METHODS: The frequencies of the variants at base positions -6, -20, -217, -793, and -776, both alone and in combination (haplotypes), were compared between cases and controls in samples stratified based on race and sex. A logistic regression model was applied to test whether AGT genotypes were significant predictors of the disease while adjusting for race, sex, and age. RESULTS: Subjects with the AA or AG genotype at locus -793 were significantly more likely to have the disease (OR = 1.88, 95% CI = 1.12-3.15). Additionally, the differences in haplotype frequency distributions between cases and controls were significant at the 7% level for all four subgroups (stratified by race and sex) after adjusting for multiple testing. Based on the odds ratios for each individual haplotype, the haplotype AAAAT (nucleotide sequences at base positions -6, -20, -217, -793, -776) in African-American males, African-American females, and Caucasian females may confer susceptibility to the disease in these population subsets. CONCLUSION: Overall, the present report provides statistical evidence for the association of AGT with essential hypertension.

Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies.

BACKGROUND: Phenotype error causes reduction in power to detect genetic association. We present a quantification of phenotype error, also known as diagnostic error, on power and sample size calculations for case-control genetic association studies between a marker locus and a disease phenotype. We consider the classic Pearson chi-square test for independence as our test of genetic association. To determine asymptotic power analytically, we compute the distribution's non-centrality parameter, which is a function of the case and control sample sizes, genotype frequencies, disease prevalence, and phenotype misclassification probabilities. We derive the non-centrality parameter in the presence of phenotype errors and equivalent formulas for misclassification cost (the percentage increase in minimum sample size needed to maintain constant asymptotic power at a fixed significance level for each percentage increase in a given misclassification parameter). We use a linear Taylor Series approximation for the cost of phenotype misclassification to determine lower bounds for the relative costs of misclassifying a true affected (respectively, unaffected) as a control (respectively, case). Power is verified by computer simulation. RESULTS: Our major findings are that: (i) the median absolute difference between analytic power with our method and simulation power was 0.001 and the absolute difference was no larger than 0.011; (ii) as the disease prevalence approaches 0, the cost of misclassifying a unaffected as a case becomes infinitely large while the cost of misclassifying an affected as a control approaches 0. CONCLUSION: Our work enables researchers to specifically quantify power loss and minimum sample size requirements in the presence of phenotype errors, thereby allowing for more realistic study design. For most diseases of current interest, verifying that cases are correctly classified is of paramount importance.

Precision and type I error rate in the presence of genotype errors and missing parental data: a comparison between the original transmission disequilibrium test (TDT) and TDTae statistics.

BACKGROUND: Two factors impacting robustness of the original transmission disequilibrium test (TDT) are: i) missing parental genotypes and ii) undetected genotype errors. While it is known that independently these factors can inflate false-positive rates for the original TDT, no study has considered either the joint impact of these factors on false-positive rates or the precision score of TDT statistics regarding these factors. By precision score, we mean the absolute difference between disease gene position and the position of markers whose TDT statistic exceeds some threshold. METHODS: We apply our transmission disequilibrium test allowing for errors (TDTae) and the original TDT to phenotype and modified single-nucleotide polymorphism genotype simulation data from Genetic Analysis Workshop. We modify genotype data by randomly introducing genotype errors and removing a percentage of parental genotype data. We compute empirical distributions of each statistic's precision score for a chromosome harboring a simulated disease locus. We also consider inflation in type I error by studying markers on a chromosome harboring no disease locus. RESULTS: The TDTae shows median precision scores of approximately 13 cM, 2 cM, 0 cM, and 0 cM at the 5%, 1%, 0.1%, and 0.01% significance levels, respectively. By contrast, the original TDT shows median precision scores of approximately 23 cM, 21 cM, 15 cM, and 7 cM at the corresponding significance levels, respectively. For null chromosomes, the original TDT falsely rejects the null hypothesis for 28.8%, 14.8%, 5.4%, and 1.7% at the 5%, 1%, 0.1% and 0.01%, significance levels, respectively, while TDTae maintains the correct false-positive rate. CONCLUSION: Because missing parental genotypes and undetected genotype errors are unknown to the investigator, but are expected to be increasingly prevalent in multilocus datasets, we strongly recommend TDTae methods as a standard procedure, particularly where stricter significance levels are required.

Statistical significance for hierarchical clustering in genetic association and microarray expression studies.

BACKGROUND: With the increasing amount of data generated in molecular genetics laboratories, it is often difficult to make sense of results because of the vast number of different outcomes or variables studied. Examples include expression levels for large numbers of genes and haplotypes at large numbers of loci. It is then natural to group observations into smaller numbers of classes that allow for an easier overview and interpretation of the data. This grouping is often carried out in multiple steps with the aid of hierarchical cluster analysis, each step leading to a smaller number of classes by combining similar observations or classes. At each step, either implicitly or explicitly, researchers tend to interpret results and eventually focus on that set of classes providing the "best" (most significant) result. While this approach makes sense, the overall statistical significance of the experiment must include the clustering process, which modifies the grouping structure of the data and often removes variation. RESULTS: For hierarchically clustered data, we propose considering the strongest result or, equivalently, the smallest p-value as the experiment-wise statistic of interest and evaluating its significance level for a global assessment of statistical significance. We apply our approach to datasets from haplotype association and microarray expression studies where hierarchical clustering has been used. CONCLUSION: In all of the cases we examine, we find that relying on one set of classes in the course of clustering leads to significance levels that are too small when compared with the significance level associated with an overall statistic that incorporates the process of clustering. In other words, relying on one step of clustering may furnish a formally significant result while the overall experiment is not significant.