Extreme discordant sib pairs for mapping quantitative trait loci in humans

Analysis of differences between siblings (sib pair analysis) is a standard method of genetic linkage analysis for mapping quantitative trait loci, such as those contributing to hypertension and obesity, in humans. In traditional designs, pairs are selected at random or with one sib having an extreme trait value. The majority of such pairs provide little power to detect linkage; only pairs that are concordant for high values, low values, or extremely discordant pairs (for example, one in the top 10 percent and the other in the bottom 10 percent of the distribution) provide substantial power. Focus on discordant pairs can reduce the amount of genotyping necessary over conventional designs by 10- to 40-fold.     

Preliminary evidence of linkage of salt sensitivity in black Americans at the beta 2-adrenergic receptor locus

Salt sensitivity is a heritable trait that is a hallmark of hypertension in black Americans. Genes encoding adrenergic receptors are candidate loci for the inheritance of this hypertension-related trait because of the role of these receptors in the regulation of renal sodium excretion and vascular tone. We performed this study to determine whether these loci are responsible for some of the phenotypic variation in salt sensitivity. Hypertensive black American probands were ascertained, followed by sequential ascertainment of adult sib pairs among the first-, second- and third-degree relatives of the proband. Both hypertensive and normotensive siblings were tested for salt sensitivity by an intravenous sodium-loading, lasix volume-depletion protocol. Genotyping was performed with restriction fragment length polymorphisms in genomic DNA probed with clones containing the beta 2- and alpha 2c10-adrenergic receptor genes. A total of 109 sib pairs was evaluated. Salt sensitivity was defined as the change in blood pressure in each individual, comparing the sodium-loaded with the volume-depleted state. Systolic pressure decreased by an average of 9.0 +/- 9%, diastolic pressure by 1.5 +/- 11%, and mean arterial pressure by 5.0 +/- 9%. Neither blood pressure nor salt sensitivity was linked at the alpha 2c10-adrenergic receptor locus. No evidence suggested that systolic salt sensitivity and baseline blood pressure were linked at the beta 2-adrenergic receptor locus. Model-independent sib pair linkage analysis suggested that diastolic blood pressure response to sodium loading/volume depletion is linked at the beta 2-adrenergic receptor locus (P < .006). Evidence for linkage was significant at the .05 level after adjustment for the number of phenotypic traits examined.     

Regression models for multiple outcomes in large epidemiologic studies

In situations in which one cannot specify a single primary outcome, epidemiologic analyses often examine multiple associations between outcomes and explanatory covariates or risk factors. To compare alternative approaches to the analysis of multiple outcomes in regression models, I used generalized estimating equations (GEE) models, a multivariate extension of generalized linear models, to incorporate the dependence among the outcomes from the same subject and to provide robust variance estimates of the regression coefficients. I applied the methods in a hospital-population-based study of complications of surgical anaesthesia, using GEE model fitting and quasi-likelihood score and Wald tests. In one GEE model specification, I allowed the associations between each of the outcomes and a covariate to differ, yielding a regression coefficient for each of the outcome and covariate combinations; I obtained the covariances among the set of outcome-specific regression coefficients for each covariate from the robust 'sandwich' variance estimator. To address the problem of multiple inference, I used simultaneous methods that make adjustments to the test statistic p-values and the confidence interval widths, to control type I error and simultaneous coverage, respectively. In a second model specification, for each of the covariates I assumed a common association between the outcomes and the covariate, which eliminates the problem of multiplicity by use of a global test of association. In an alternative approach to multiplicity, I used empirical Bayes methods to shrink the outcome-specific coefficients toward a pooled mean that is similar to the common effect coefficient. GEE regression models can provide a flexible framework for estimation and testing of multiple outcomes.     

NGF induces transient but not sustained activation of ERK in PC12 mutant cells incapable of differentiating

Calcium urolithiasis is often associated with increased intestinal absorption and urine excretion of calcium, and has been suggested to result from increased vitamin D production. The role of the enzyme 1 alpha-hydroxylase, the rate-limiting step in active vitamin D production, was evaluated in 36 families, including 28 sibships with at least a pair of affected sibs, using qualitative and quantitative trait linkage analyses. Sibs with a verified calcium urolithiasis passage (n = 117) had higher 24-h calciuria (P = 0.03), oxaluria (P = 0.02), fasting and postcalcium loading urine calcium/creatinine (Ca/cr) ratios (P = 0.008 and P = 0.002, respectively), and serum 1,25(OH)2 vitamin D levels (P = 0.02) compared with nonstone-forming sibs (n = 120). Markers from a 9-centiMorgan interval encompassing the VDD1 locus on chromosome 12q13-14 (putative 1 alpha-hydroxylase) were analyzed in 28 sibships (146 sib pairs) of single and recurrent stone formers and in 14 sibships (65 sib pairs) with recurrent-only (> or = 3 episodes) stone-forming sibs. Two-point and multipoint analyses did not reveal excess in alleles shared among affected sibs at the VDD1 locus. Linkage of stone formation to the VDD1 locus could be excluded, respectively, with a lambda d of 2.0 (single and recurrent stone formers) and 3.25 (recurrent stone formers). Quantitative trait analyses revealed no evidence for linkage to 24-h calciuria and oxaluria, serum 1,25(OH)2 vitamin D levels, and Ca/cr ratios. This study shows absence of linkage of the putative 1 alpha-hydroxylase locus to calcium stone formation or to quantitative traits associated with idiopathic hypercalciuria. In addition, there is coaggregation of calciuric and oxaluric phenotypes with stone formation.     

Empirical evaluation of genome scans for linkage of a quantitative trait associated with a complex disorder

Nonparametric sib-pair analysis (Haseman-Elston) was used to search for evidence of linkage between a putative locus for a complex quantitative trait Q1 and genome-wide markers (367 markers from 10 chromosomes) for the first 100 replicates of nuclear family data. The characteristics of the statistically positive linkage results [the magnitude of p-values (p), the number of supporting flanking markers, and the percentage of positive replicates] were compared for true linkage (major and minor genes) and false positive evidence for linkage. Discriminant analysis was used to evaluate which characteristics of these statistically positive linkage results are good indicators to discriminate true linkage from false positive evidence for linkage. Sensitivity and false positive rates of several proposed criteria for linkage, as well as the criteria based on our results were evaluated. The relationship between the map location of the marker with the lowest p-value and the map location of the true underlying gene was also evaluated, which provided useful information for fine mapping and replication studies.     

Association of posterior p-values of S.A.G.E. SIBPAL proportion-IBD and Haseman-Elston statistics for ACTHR112

A common practice among researchers performing linkage studies is the use of equal allele frequencies as input when reporting p-values from computer linkage programs such as S.A.G.E. SIBPAL. Our results, using 5,000 sets from a uniform-prior distribution of allele frequencies, showed that such input may be problematic. Further, we found that the S.A.G.E. SIBPAL test for proportion of alleles shared identical by descent among concordantly affected sib pairs showed a greater percentage of significant p-values with decreasing parental genotype information (Table III), while the S.A.G.E. SIBPAL Haseman-Elston test produced significant p-values comparatively less frequently (Table IV).     

Multiple-trait quantitative trait loci analysis using a large mouse sibship

Quantitative trait loci influencing several phenotypes were assessed using a genetically heterogeneous mouse population. The 145 individuals were produced by a cross between (BALB/cJ x C57BL/6J)F1 females and (C3H/HeJ x DBA/2J)F1 males. The population is genetically equivalent to full siblings derived from heterozygous parents, with known linkage phase. Each individual in the population represents a unique combination of alleles from the inbred grandparents. Quantitative phenotypes for eight T cell measures were obtained at 8 and 18 mo of age. Single-marker locus, repeated measures analysis of variance identified nine marker-phenotype associations with an experimentwise significance level of P < 0.05. Six of the eight quantitative phenotypes could be associated with at least one locus having experiment-wide significance. Composite interval, repeated measures analysis of variance identified 13 chromosomal regions with comparisonwise (nominal) significance associations of P < 0.001. The heterozygous-parent cross provides a reproducible, general method for identification of loci associated with quantitative trait phenotypes or repeated phenotypic measures.     

A comparison of one-sided methods to identify significant individual outcomes in a multiple outcome setting: stepwise tests or global tests with closed testing

We compare two approaches to the identification of individual significant outcomes when a comparison of two groups involves multiple outcome variables. The approaches are all designed to control the familywise error rate (FWE) with any subset of the null hypothesis being true (in the strong sense). The first approach is initially to use a global test of the overall hypothesis that the groups are equivalent for all variables, followed by an application of the closed testing algorithm of Marcus, Peritz and Gabriel. The global tests considered here are ordinary least squares (OLS), generalized least squares (GLS), an approximation to a likelihood ratio test (ALR), and a new test based on an approximation to the most powerful similar test for simple alternatives. The second approach is that of stepwise testing, which tests the univariate hypotheses in a specific order with appropriate adjustment to the univariate p-values for multiplicity. The stepwise tests considered include both step-down and step-up tests of a general type, and likewise permutation tests that incorporate the dependence structure of the data. We illustrate the tests with two examples of birth outcomes: a comparison of cocaine-exposed new-borns to control new-borns on neurobehavioural and physical growth variables, and, in a separate study, a comparison of babies born to diabetic mothers and babies born to non-diabetic mothers on minor malformations. After describing the methods and analysing the birth outcome data, we use simulations on Gaussian data to provide guidelines for the use of these procedures in terms of power and computation.     

Sib-pair collection strategies for complex diseases

When planning an affected sib pair collection for use in a genomewide search for complex trait loci, researchers must ask: (a) Which family structures will yield the most informative pairs? and (b) Should recruitment extend beyond the index sib pair? The optimal collection strategy will depend on the trait's genetic architecture, but this is rarely known for non-Mendelian diseases. In the present report, we study the consequences of collecting only those sib pairs arising from pedigrees with a precisely specified structure as opposed to a strategy that collects all affected sib pairs at random (i.e., blind to the affection status of first-degree relatives). The former approach turns out to be risky because the power of specific pedigree structures can vary dramatically even among models producing identical observable parameters (such as population prevalence and sibling recurrence rate). In contrast, the latter approach typically involves only a modest loss of power as compared with the optimal (but unknowable) design. Further, we compare the strategy of collecting all affected sib pairs at random with the alternative of imposing some modest limitations on family structure (e.g., presence of at least one unaffected sib or parent). The latter approach generally provides some increase in power but entails additional effort to contact and phenotype relatives: the overall merit of imposing such requirements needs to be evaluated in the context of the specific disease to be studied and of the clinical and analytical resources available. In addition, these findings suggest that a further explanation for failure to replicate positive complex trait linkages lies in differences in ascertainment strategy between data sets.     

A simulation study of the effects of assignment of prior identity-by-descent probabilities to unselected sib pairs, in covariance-structure modeling of a quantitative-trait locus

Sib pair-selection strategies, designed to identify the most informative sib pairs in order to detect a quantitative-trait locus (QTL), give rise to a missing-data problem in genetic covariance-structure modeling of QTL effects. After selection, phenotypic data are available for all sibs, but marker data-and, consequently, the identity-by-descent (IBD) probabilities-are available only in selected sib pairs. One possible solution to this missing-data problem is to assign prior IBD probabilities (i.e., expected values) to the unselected sib pairs. The effect of this assignment in genetic covariance-structure modeling is investigated in the present paper. Two maximum-likelihood approaches to estimation are considered, the pi-hat approach and the IBD-mixture approach. In the simulations, sample size, selection criteria, QTL-increaser allele frequency, and gene action are manipulated. The results indicate that the assignment of prior IBD probabilities results in serious estimation bias in the pi-hat approach. Bias is also present in the IBD-mixture approach, although here the bias is generally much smaller. The null distribution of the log-likelihood ratio (i.e., in absence of any QTL effect) does not follow the expected null distribution in the pi-hat approach after selection. In the IBD-mixture approach, the null distribution does agree with expectation.     

Genetics of Hb F/F cell variance in adults and heterocellular hereditary persistence of fetal hemoglobin

Hb F and F cell values in normal adults vary considerably with a continuous distribution that is substantially skewed to the right implicating a polygenic influence. The high values of Hb F and F cells are transmitted in the condition referred to as heterocellular hereditary persistence fetal hemoglobin which should be regarded as a multifactorial quantitative trait, quite distinct from the classical pancellular hereditary persistence of fetal hemoglobins. Several factors have been shown to influence F cell/Hb F levels in normal adults including age, gender, genetic determinants linked and unlinked to the beta-globin locus on chromosome 11p. Two trans-acting quantitative trait loci for F cell variance have been mapped, one on 6q and the other on Xp, with at least one other implicated. As an initial step towards hunting for the other quantitative trait loci we have carried out a preliminary analysis of F cell variance in 182 pairs of monozygotic and 373 pairs of dizygotic twins. The correlation coefficient of F cell variance in monozygotic twins was 0.89, while that in the dizygotic twins was 0.51. Overwhelming evidence for a strong genetic component in the control of Hb F/F cell levels is provided by a heritability of 0.87. However, the role and extent of contribution from the quantitative trait loci on 6q and Xp are still not known.     

Linkage of circulating eosinophils to markers on chromosome 5q

Although peripheral blood eosinophilia is strongly associated with the risk of developing asthma, genetic determinants of eosinophilia have not been extensively studied. We used sib-pair analysis to assess linkage of circulating eosinophils (as a percent of total white blood cells [WBC]) to nine markers located in chromosome 5q31-33. The study was divided into two phases. Of 246 sib pairs available for the first phase, 35 were classified as low concordant (LC) (both sibs had <= 2% circulating eosinophils), 18 were defined as high concordant (HC) (both sibs had 5% or more circulating eosinophils), and 26 were defined as discordant (one sib had <= 2% and the other sib had 5% or more circulating eosinophils). Significant evidence for linkage among low concordant sib pairs was found for several markers in the region under study, with a peak for marker D5S500 (proportion of alleles shared identical by descent [ibd] = 0.68 +/- 0.05 [mean +/- SE], p = 0.0004). A cross-validating study was done in which an additional 19 sib pairs that were low concordant for circulating eosinophils were studied. Evidence for linkage was also observed in this subset. Results were independent of current wheezing, total serum IgE levels, and other potential confounders. A multipoint analysis done for all low-concordant sib pairs available showed that the maximal logarithm of the odds favoring genetic linkage (LOD) score (2.4, p = 0.0004) was observed in correspondence with marker D5S658. We conclude that a locus or loci may be present in chromosome 5q31-33 that controls for circulating eosinophils as a proportion of total WBC.     

Constraints on general slowing: a meta-analysis using hierarchical linear models with random coefficients

General slowing (GS) theories are often tested by meta-analysis that model mean latencies of older adults as a function of mean latencies of younger adults. Ordinary least squares (OLS) regression is inappropriate for this purpose because it fails to account for the nested structure of multitask response time (RT) data. Hierarchical linear models (HLM) are an alternative method for analyzing such data. OLS analysis of data from 21 studies that used iterative cognitive tasks supported GS; however, HLM analysis demonstrated significant variance in slowing across experimental tasks and a process-specific effect by showing less slowing for memory scanning than for visual-search and mental-rotation tasks. The authors conclude that HLM is more suitable than OLS methods for meta-analyses of RT data and for testing GS theories.     

A quantitative-trait locus on chromosome 6p influences different aspects of developmental dyslexia

Recent application of nonparametric-linkage analysis to reading disability has implicated a putative quantitative-trait locus (QTL) on the short arm of chromosome 6. In the present study, we use QTL methods to evaluate linkage to the 6p25-21.3 region in a sample of 181 sib pairs from 82 nuclear families that were selected on the basis of a dyslexic proband. We have assessed linkage directly for several quantitative measures that should correlate with different components of the phenotype, rather than using a single composite measure or employing categorical definitions of subtypes. Our measures include the traditional IQ/reading discrepancy score, as well as tests of word recognition, irregular-word reading, and nonword reading. Pointwise analysis by means of sib-pair trait differences suggests the presence, in 6p21.3, of a QTL influencing multiple components of dyslexia, in particular the reading of irregular words (P=.0016) and nonwords (P=.0024). A complementary statistical approach involving estimation of variance components supports these findings (irregular words, P=.007; nonwords, P=.0004). Multipoint analyses place the QTL within the D6S422-D6S291 interval, with a peak around markers D6S276 and D6S105 consistently identified by approaches based on trait differences (irregular words, P=.00035; nonwords, P=.0035) and variance components (irregular words, P=.007; nonwords, P=.0038). Our findings indicate that the QTL affects both phonological and orthographic skills and is not specific to phoneme awareness, as has been previously suggested. Further studies will be necessary to obtain a more precise localization of this QTL, which may lead to the isolation of one of the genes involved in developmental dyslexia.     

The power of iterated generalized least squares (GLS) method to detect direct relationships in the analysis of correlated quantitative traits

We examined the power of the stepwise iterated generalized least squares (GLS) method by modeling the relationship between quantitative traits and other variables using the simulated data for Problem 2A. The comparison between the generating model provided by the workshop and the results of the stepwise iterated GLS model showed that this method could be used as a first step in identifying the underlying model for genetic data. The estimated covariance matrices also provide useful information about the genetic properties of the traits.     

Evidence for association and genetic linkage of the angiotensin-converting enzyme locus with hypertension and blood pressure in men but not women in the Framingham Heart Study

BACKGROUND: There is controversy regarding the association of the angiotensin-converting enzyme deletion-insertion (ACE D/I) polymorphism with systemic hypertension and with blood pressure. We investigated these relations in a large population-based sample of men and women by using association and linkage analyses. METHODS AND RESULTS: The study sample consisted of 3095 participants in the Framingham Heart Study. Blood pressure measurements were obtained at regular examinations. The ACE D/I polymorphism was identified by using a polymerase chain reaction assay. In logistic regression analysis, the adjusted odds ratios for hypertension among men for the DD and DI genotypes were 1.59 (95% confidence interval [CI], 1.13 to 2.23) and 1.18 (95% CI, 0.87 to 1.62), respectively, versus II (chi2 P=.02). In women, adjusted odds ratios for the DD and DI genotypes were 1.00 (95% CI, 0.70 to 1.44) and 0.78 (95% CI, 0.56 to 1.09), respectively (P=.14). In linear regression analysis, there was an association of the ACE DD genotype with increased diastolic blood pressure in men (age-adjusted P=.03, multivariate-adjusted P=.14) but not women. Quantitative trait linkage analyses in 1044 pairs of siblings, by using both ACE D/I and a nearby microsatellite polymorphism of the human growth hormone gene, supported a role of the ACE locus in influencing blood pressure in men but not in women. CONCLUSIONS: In our large, population-based sample, there is evidence for association and genetic linkage of the ACE locus with hypertension and with diastolic blood pressure in men but not women. Our data support the hypothesis that ACE, or a nearby gene, is a sex-specific candidate gene for hypertension. Confirmatory studies in other large population-based samples are warranted.     

Lac repressor inducible gene expression in human breast cancer cells in vitro and in a xenograft tumor

As part of an ongoing search for susceptibility loci for NIDDM, we tested 19 genes whose products are implicated in insulin secretion or action for linkage with NIDDM. Loci included the G-protein-coupled inwardly rectifying potassium channels expressed in beta-cells (KCNJ3 and KCNJ7), glucagon (GCG), glucokinase regulatory protein (GCKR), glucagon-like peptide I receptor (GLP1R), LIM/homeodomain islet-1 (ISL1), caudal-type homeodomain 3 (CDX3), proprotein convertase 2 (PCSK2), cholecystokinin B receptor (CCKBR), hexokinase 1 (HK1), hexokinase 2 (HK2), mitochondrial FAD-glycerophosphate dehydrogenase (GPD2), liver and muscle forms of pyruvate kinase (PKL, PKM), fatty acid-binding protein 2 (FABP2), hepatic phosphofructokinase (PFKL), protein serine/threonine phosphatase 1 beta (PPP1CB), and low-density lipoprotein receptor (LDLR). Additionally, we tested the histidine-rich calcium locus (HRC) on chromosome 19q. All regions were tested for linkage with microsatellite markers in 751 individuals from 172 families with at least two patients with overt NIDDM (according to World Health Organization criteria) in the sibship, using nonparametric methods. These 172 families comprise 352 possible affected sib pairs with overt NIDDM or 621 possible affected sib pairs defined as having a fasting plasma glucose value of >6.1 mmol/l or a glucose value of >7.8 mmol/l 2 h after oral glucose load. No evidence for linkage was found with any of the 19 candidate genes and NIDDM in our population by nonparametric methods, suggesting that those genes are not major contributors to the pathogenesis of NIDDM. However, some evidence for suggestive linkage was found between a more severe form of NIDDM, defined as overt NIDDM diagnosed before 45 years of age, and the CCKBR locus (11p15.4; P = 0.004). Analyses of six additional markers spanning 27 cM on chromosome 11p confirmed the suggestive linkage in this region. Whether an NIDDM susceptibility gene lies on chromosome 11p in our population must be determined by further analyses.     

Linkage of genetic markers on human chromosomes 20 and 12 to NIDDM in Caucasian sib pairs with a history of diabetic nephropathy

The potential contribution of maturity-onset diabetes of the young (MODY) genes to NIDDM susceptibility in African-American and Caucasian NIDDM-affected sibling pairs with a history of adult-onset diabetic nephropathy has been evaluated. Evidence for linkage to NIDDM was found with polymorphic loci that map to the long arms of human chromosomes 20 and 12 in regions containing the MODY1 and MODY3 genes. Nonparametric analysis of chromosome 20 inheritance data collected with the MODY1-linked marker D20S197 provides evidence for linkage to NIDDM with a P value of 0.005 in Caucasian sib pairs using affected sibpair (ASP) analyses. Non-parametric analysis of chromosome 12 inheritance data collected with the MODY3-linked markers D12S349 and D12S86 provides evidence for linkage to NIDDM with P values of 0.04 and 0.006, respectively, in Caucasian sib pairs using similar analyses. No evidence for linkage of MODY1 and MODY3 markers to NIDDM in African-American sib pairs was observed. In addition, no evidence for linkage to MODY2 (glucokinase-associated MODY) was observed with either study population. Results of multipoint maximum logarithm of odds (LOD) score analysis were consistent with the ASP results. A maximum LOD score of 1.48 was calculated for linkage to MODY1-linked loci and 1.45 to MODY3-linked loci in Caucasian sib pairs. Tabulation of allele sharing in affected sib pairs with D20S197 and D12S349 suggests that affected sibling pairs may inherit susceptibility genes simultaneously from chromosome 20 and chromosome 12. The results suggest that genes contributing to NIDDM in the general Caucasian population are located in the regions containing the MODY1 and MODY3 genes.     

A new cavity classification

The role of common variation in the low density lipoprotein (LDL) receptor gene (LDLR) as a determinant of variation in plasma LDL cholesterol in normolipidemic populations is not well established. To address this question, we used both association and linkage analysis to evaluate the relationship between plasma LDL cholesterol and genetic variation in LDLR and in three other candidate genes for lipoprotein metabolism, namely, APOE, PONI, and LPL. We studied a sample of 719 normolipidemic Alberta Hutterites, who comprised 1217 sib pairs. Variation in each of the four candidate genes was significantly associated with variation in plasma LDL cholesterol, but the average effects of the alleles were small. In contrast, sib pair analysis showed that only the LDLR gene variation was linked with variation in plasma LDL cholesterol (P = 0.026). Thus, the common LDLR gene variation was both associated with and linked to variation in plasma LDL cholesterol, suggesting that there is a functional impact of structural variation in LDLR on plasma LDL cholesterol in this study sample. However, the absence of linkage of variation in LDL cholesterol with the other three candidate genes, in particular APOE, is consistent with a lower sensitivity of linkage analysis compared with association analysis for detecting modest effects on quantitative traits. Attributes such as the genetic structure of the study sample, the amount of variance attributable to the locus, and the information content of the marker appear to affect the ability to detect genotype-phenotype relationships using linkage analysis.     

Analytic strategies to detect linkage to a common disorder with genetically determined age of onset: diabetes mellitus in Pima Indians

Segregation analysis suggests that the high prevalence of non-insulin-dependent diabetes mellitus in Pima Indians may be partially due to a single locus with a major effect on age of onset. A simulation study was conducted to evaluate the power of various age-adjustment strategies in linkage analysis to detect this putative gene in 1,862 sib-pairs from 264 potentially informative nuclear families. Simulations were performed at a recombination fraction (theta) of 0.05 for values of polymorphism information content (PIC) ranging from 0.38 to 1.00. Under the codominant age-of-onset model supported by segregation analysis, power to detect linkage (at P < 0.0001) at PIC = 1.00 was 75% for the Haseman-Elston (HE) sib-pair test and 63% for the affected sib-pair test (ASP) with no age adjustment. Substantial improvements in power were possible for the HE test by defining the trait as a survival analysis "residual" (power = 91%) and for the ASP test by use of an age-of-onset threshold above which individuals are not included in the analysis (power = 90%, for age of onset < 45 yrs). The parametric method of linkage analysis was most powerful, as long as both the analysis model and the simulation model involved a genetic effect on age of onset, regardless of whether dominance at the trait locus was misspecified. Methods of age adjustment based on the probability of eventually becoming affected only improved power when the genetic effect was on susceptibility rather than age of onset. The method of age adjustment in linkage analysis may depend on whether one anticipates a genetic effect primarily on age of onset or on ultimate susceptibility.