Model misspecification and multipoint linkage analysis

Obelisc: an identical-by-descent mapping tool based on SNP streak

Motivation

Genetic linkage analysis has made a huge contribution to the genetic mapping of Mendelian diseases. However, most previously available linkage analysis methods have limited applicability. Since parametric linkage analysis requires predefined model of inheritance with a fixed set of parameters, it is inapplicable without fully structured pedigree information. Furthermore, the analytical results are dependent on the specification of model parameters. While non-parametric linkage analysis can avoid these problems, the runs of homozygosity (ROH) mapping, a widely used non-parametric linkage analysis method, can only deal with recessive inheritance. The implementation of non-parametric linkage analyses capable of dealing with both dominant and recessive inheritance has been required.

Results

We have developed the Obelisc (Observational linkage scan), a flexibly applicable user-friendly non-parametric linkage analysis tool, which also provides an intuitive visualization of the analytical results. Obelisc is based on the SNP streak approach, which does not require any predefined inheritance model with parameters. In contrast to the ROH mapping, the SNP streak approach is applicable to both dominant and recessive traits. To illustrate the performance of Obelisc, we generated a pseudo-pedigree from the publicly available BioBank Japan Project genome-wide genotype dataset (n > 180 000). By applying Obelisc to this pseudo-pedigree, we successfully identified the regions with inherited identical-by-descent haplotypes shared among the members of the pseudo-pedigree, which was validated by the population-based haplotype phasing approach.

Availability and implementation

Obelisc is feely available at https://github.com/qsonehara/Obelisc as a python package with example datasets.

Supplementary information

Supplementary data are available at Bioinformatics online.

Model-Based Linkage Analysis of a Quantitative Trait

Linkage Analysis is a family-based method of analysis to examine whether any typed genetic markers cosegregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single-marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it also includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single-marker analysis, and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

Exome sequencing identifies a novel frameshift mutation of MYO6 as the cause of autosomal dominant nonsyndromic hearing loss in a Chinese family

Autosomal dominant types of nonsyndromic hearing loss (ADNSHL) are typically postlingual in onset and progressive. High genetic heterogeneity, late onset age, and possible confounding due to nongenetic factors hinder the timely molecular diagnoses for most patients. In this study, exome sequencing was applied to investigate a large Chinese family segregating ADNSHL in which we initially failed to find strong evidence of linkage to any locus by whole-genome linkage analysis. Two affected family members were selected for sequencing. We identified two novel mutations disrupting known ADNSHL genes and shared by the sequenced samples: c.328C>A in COCH (DFNA9) resulting in a p.Q110K substitution and a deletion c. 2814_2815delAA in MYO6 (DFNA22) causing a frameshift alteration p.R939Tfs*2. The pathogenicity of novel coding variants in ADNSHL genes was carefully evaluated by analysis of co-segregation with phenotype in the pedigree and in light of established genotype-phenotype correlations. The frameshift deletion in MYO6 was confirmed as the causative variant for this pedigree, whereas the missense mutation in COCH had no clinical significance. The results allowed us to retrospectively identify the phenocopy in one patient that contributed to the negative finding in the linkage scan. Our clinical data also supported the emerging genotype-phenotype correlation for DFNA22.

False-positive rates in two-point parametric linkage analysis

Two-point linkage analyses of whole genome sequence data are a promising approach to identify rare variants that segregate with complex diseases in large pedigrees because, in theory, the causal variants have been genotyped. We used whole genome sequence data and simulated traits provided by Genetic Analysis Workshop 18 to evaluate the proportion of false-positive findings in a binary trait using classic two-point parametric linkage analysis. False-positive genome-wide significant log of odds (LOD) scores were identified in more than 80% of 50 replicates for a binary phenotype generated by dichotomizing a quantitative trait that was simulated with a polygenic component (that was not based on any of the provided whole genome sequence genotypes). In contrast, when the trait was truly nongenetic (created by randomly assigning affected-unaffected status), the number of false-positive results was well controlled. These results suggest that when using two-point linkage analyses on whole genome sequence data, one should carefully examine regions yielding significant two-point LOD scores with multipoint analysis and that a more stringent significance threshold may be needed.

Genome-wide linkage analysis of congenital heart defects using MOD score analysis identifies two novel loci

Background

Congenital heart defects (CHD) is the most common cause of death from a congenital structure abnormality in newborns and is often associated with fetal loss. There are many types of CHD. Human genetic studies have identified genes that are responsible for the inheritance of a particular type of CHD and for some types of CHD previously thought to be sporadic. However, occasionally different members of the same family might have anatomically distinct defects — for instance, one member with atrial septal defect, one with tetralogy of Fallot, and one with ventricular septal defect. Our objective is to identify susceptibility loci for CHD in families affected by distinct defects. The occurrence of these apparently discordant clinical phenotypes within one family might hint at a genetic framework common to most types of CHD.

Results

We performed a genome-wide linkage analysis using MOD score analysis in families with diverse CHD. Significant linkage was obtained in two regions, at chromosome 15 (15q26.3, P_empirical = 0.0004) and at chromosome 18 (18q21.2, P_empirical = 0.0005).

Conclusions

In these two novel regions four candidate genes are located: SELS, SNRPA1, and PCSK6 on 15q26.3, and TCF4 on 18q21.2. The new loci reported here have not previously been described in connection with CHD. Although further studies in other cohorts are needed to confirm these findings, the results presented here together with recent insight into how the heart normally develops will improve the understanding of CHD.

A comparison of different linkage statistics in small to moderate sized pedigrees with complex diseases

Background

In the last years GWA studies have successfully identified common SNPs associated with complex diseases. However, most of the variants found this way account for only a small portion of the trait variance. This fact leads researchers to focus on rare-variant mapping with large scale sequencing, which can be facilitated by using linkage information. The question arises why linkage analysis often fails to identify genes when analyzing complex diseases. Using simulations we have investigated the power of parametric and nonparametric linkage statistics (KC-LOD, NPL, LOD and MOD scores), to detect the effect of genes responsible for complex diseases using different pedigree structures.

Results

As expected, a small number of pedigrees with less than three affected individuals has low power to map disease genes with modest effect. Interestingly, the power decreases when unaffected individuals are included in the analysis, irrespective of the true mode of inheritance. Furthermore, we found that the best performing statistic depends not only on the type of pedigrees but also on the true mode of inheritance.

Conclusions

When applied in a sensible way linkage is an appropriate and robust technique to map genes for complex disease. Unlike association analysis, linkage analysis is not hampered by allelic heterogeneity. So, why does linkage analysis often fail with complex diseases? Evidently, when using an insufficient number of small pedigrees, one might miss a true genetic linkage when actually a real effect exists. Furthermore, we show that the test statistic has an important effect on the power to detect linkage as well. Therefore, a linkage analysis might fail if an inadequate test statistic is employed. We provide recommendations regarding the most favorable test statistics, in terms of power, for a given mode of inheritance and type of pedigrees under study, in order to reduce the probability to miss a true linkage.

Model-based linkage analysis of a quantitative trait

Linkage analysis is a family-based method of analysis to examine whether any typed genetic markers co-segregate with a given trait, in this case a quantitative trait. If linkage exists, this is taken as evidence in support of a genetic basis for the trait. Historically, linkage analysis was performed using a binary disease trait, but has been extended to include quantitative disease measures. Quantitative traits are desirable as they provide more information than binary traits. Linkage analysis can be performed using single marker methods (one marker at a time) or multipoint (using multiple markers simultaneously). In model-based linkage analysis, the genetic model for the trait of interest is specified. There are many software options for performing linkage analysis. Here, we use the program package Statistical Analysis for Genetic Epidemiology (S.A.G.E.). S.A.G.E. was chosen because it includes programs to perform data cleaning procedures and to generate and test genetic models for a quantitative trait, in addition to performing linkage analysis. We demonstrate in detail the process of running the program LODLINK to perform single marker analysis and MLOD to perform multipoint analysis using output from SEGREG, where SEGREG was used to determine the best fitting statistical model for the trait.

Estimation and visualization of identity-by-descent within pedigrees simplifies interpretation of complex trait analysis

Linkage analysis identifies markers that appear to be co-inherited with a trait within pedigrees. The inheritance of a chromosomal segment may be probabilistically reconstructed, with missing data complicating inference. Inheritance patterns are further obscured in the analysis of complex traits, where variants in one or more genes may contribute to phenotypic variation within a pedigree. In this case, determining which relatives share a trait variant is not simple. We describe how to represent these patterns of inheritance for marker loci. We summarize how to sample patterns of inheritance consistent with genotypic and pedigree data using gl_auto, available in MORGAN v3.0. We describe identification of classes of equivalent inheritance patterns with the program IBDgraph. We finally provide an example of how these programs may be used to simplify interpretation of linkage analysis of complex traits in general pedigrees. We borrow information across loci in a parametric linkage analysis of a large pedigree. We explore the contribution of each equivalence class to a linkage signal, illustrate estimated patterns of identity-by-descent sharing, and identify a haplotype tagging the chromosomal segment driving the linkage signal. Haplotype carriers are more likely to share the linked trait variant, and can be prioritized for subsequent DNA sequencing.

Family-based designs for genome-wide association studies

Association mapping has successfully identified common SNPs associated with many diseases. However, the inability of this class of variation to account for most of the supposed heritability has led to a renewed interest in methods - primarily linkage analysis - to detect rare variants. Family designs allow for control of population stratification, investigations of questions such as parent-of-origin effects and other applications that are imperfectly or not readily addressed in case-control association studies. This article guides readers through the interface between linkage and association analysis, reviews the new methodologies and provides useful guidelines for applications. Just as effective SNP-genotyping tools helped to realize the potential of association studies, next-generation sequencing tools will benefit genetic studies by improving the power of family-based approaches.

Fast, exact linkage analysis for categorical traits on arbitrary pedigree designs

Multi-symptom diseases without a consistent continuous measurement of severity may be best understood with a categorical interpretation. In this paper, we present LOCate v.2, a fast, exact algorithm for linkage analysis of all types of categorical traits, both ordinal and nominal. Our method is able to incorporate missing data and analyze complex genealogical structure, including inbreeding loops. LOCate v.2 computes exact likelihoods efficiently through an elimination algorithm, similar to that used by Superlink for binary traits. We compare LOCate v.2 to LOT and QTLlink, two existing methods of linkage analysis for ordinal traits. We find that LOCate v.2 outperforms both methods when used to analyze simulated nominal traits. In addition, LOCate v.2 performs as well as QTLlink on simulated ordinal traits, and better than LOT due to the necessity of cutting large pedigrees for analysis in LOT. To demonstrate the versatility of LOCate v.2, we conduct an ordinal and nominal linkage analysis of ventricular arrhythmias in a large, inbred pedigree of German Shepherd dogs. We find that a trichotomous ordinal or nominal interpretation strengthens the evidence in favor of linkage to a region on chromosome 6, and provides new evidence of linkage to a region on chromosome 11. LOCate v.2 is a unified, fast, and robust method for linkage analysis of ordinal and nominal traits which will be valuable to researchers interested in investigating any type of categorical trait.

Linkage to 20p13 including the ANGPT4 gene in families with mixed Alzheimer's disease and vascular dementia

This study aimed at identifying novel susceptibility genes for a mixed phenotype of Alzheimer's disease and vascular dementia. Results from a genome scan showed strongest linkage to 20p13 in 18 families, and subsequent fine mapping was performed with both microsatellites and single-nucleotide polymorphisms in 18 selected candidate transcripts in an extended sample set of 30 families. The multipoint linkage peak was located at marker rs2144151 in the ANGPT4 gene, which is a strong candidate gene for vascular disease because of its involvement in angiogenesis. Although the significance of the linkage decreased, we find this result intriguing, considering that we included additional families, and thus the reduced linkage signal may be caused by genetic heterogeneity.

Genome-wide linkage analysis of multiple metabolic factors: evidence of genetic heterogeneity

The metabolic syndrome is a highly complex disease and has become one of the major public-health challenges worldwide. We sought to identify genetic loci with potential influence on multiple metabolic factors in a white population in Beaver Dam, Wisconsin, and to explore the possibility of genetic heterogeneity by family history of diabetes (FHD). Three metabolic factors were generated using principal-component factor analysis, and they represented: (i) glycemia, (ii) blood pressure, and (iii) combined (BMI, high-density lipoprotein (HDL) cholesterol, and serum uric acid) factors. Multipoint model-free linkage analysis of these factors with 385 microsatellite markers was performed on 1,055 sib-pairs, using Haseman-Elston regression. Genome-wide suggestive evidence of linkage was found at 30 cM on chromosome 22q (empirical P (P(e)) = 0.0002) for the glycemia factor, at 188-191 cM on chromosome 1q (P(e) = 0.0007) for the blood pressure factor, and at 82 cM on chromosome 17q (P(e) = 0.0007) for the combined factor. Subset analyses of the families by FHD showed evidence of genetic heterogeneity, with divergent linkage signals in the subsets on at least four chromosomes. We found evidence of genetic heterogeneity by FHD for the three metabolic factors. The results also confirmed findings of previous studies that mapped components of the metabolic syndrome to a chromosome 1q region.

Identification of novel susceptibility loci for Guam neurodegenerative disease: challenges of genome scans in genetic isolates

Amyotrophic lateral sclerosis/parkinsonism-dementia complex (ALS/PDC) is a fatal neurodegenerative disease found in the Chamorro people of Guam and other Pacific Island populations. The etiology is unknown, although both genetic and environmental factors appear important. To identify loci for ALS/PDC, we conducted both genome-wide linkage and association analyses, using approximately 400 microsatellite markers, in the largest sample assembled to date, comprising a nearly complete sample of all living and previously sampled deceased cases. A single, large, complex pedigree was ascertained from a village on Guam, with smaller families and a case-control sample ascertained from the rest of Guam by population-based neurological screening and archival review. We found significant evidence for two regions with novel ALS/PDC loci on chromosome 12 and supportive evidence for the involvement of the MAPT region on chromosome 17. D12S1617 on 12p gave the strongest evidence of linkage (maximum LOD score, Z(max) = 4.03) in our initial scan, with additional support in the complete case-control sample in the form of evidence of allelic association at this marker and another nearby marker. D12S79 on 12q also provided significant evidence of linkage (Z(max) = 3.14) with support from flanking markers. Our results suggest that ALS/PDC may be influenced by as many as three loci, while illustrating challenges that are intrinsic in genetic analyses of isolated populations, as well as analytical strategies that are useful in this context. Elucidation of the genetic basis of ALS/PDC should improve our understanding of related neurodegenerative disorders including Alzheimer disease, Parkinson disease, frontotemporal dementia and ALS.

Hypoplastic left heart syndrome links to chromosomes 10q and 6q and is genetically related to bicuspid aortic valve

OBJECTIVES

This study was designed to identify disease loci for hypoplastic left heart syndrome (HLHS) and evaluate the genetic relationship between HLHS and bicuspid aortic valve (BAV).

BACKGROUND

Previously, we identified that HLHS and BAV exhibit complex inheritance, and both HLHS and BAV kindreds are enriched for BAV. However, the genetic basis of HLHS and its relationship to BAV remains unclear.

METHODS

Family-based nonparametric genome-wide linkage analysis was performed in kindreds ascertained by either an HLHS or BAV proband. Echocardiograms were performed on 1,013 participants using a sequential sampling strategy (33 HLHS kindreds, 102 BAV kindreds).

RESULTS

The recurrence risk ratio of BAV in HLHS families (8.05) was nearly identical to that in BAV families (8.77). Linkage to chromosomal regions 10q22 and 6q23 with maximum logarithm of odds scores of 3.2 and 3.1, respectively, was identified in HLHS kindreds. In addition, 5 suggestive loci were identified (7q31, 11q22, 12q13, 14q23, and 20q11). We previously identified loci at chromosomes 18q22, 13q34, and 5q21 in BAV kindreds. The relationship between these loci was examined in the combined HLHS and BAV cohort and associations between loci were demonstrated (5q21, 13q34, and 14q23; 6q23 and 10q22; 7q31 and 20q11). Subsequent subsets linkage analysis showed a significant improvement in the logarithm of odds score at 14q23 only (4.1, p < 0.0001).

CONCLUSIONS

These studies demonstrate linkage to multiple loci identifying HLHS as genetically heterogeneous. Subsets linkage analyses and recurrence risk ratios in a combined cohort provide evidence that some HLHS and BAV are genetically related.

Multipoint lods provide reliable linkage evidence despite unknown limiting distribution: type I error probabilities decrease with sample size for multipoint lods and mods

We investigate the behavior of type I error rates in model-based multipoint (MP) linkage analysis, as a function of sample size (N). We consider both MP lods (i.e., MP linkage analysis that uses the correct genetic model) and MP mods (maximizing MP lods over 18 dominant and recessive models). Following Xing and Elston (2006 Genet. Epidemiol, 30: 447-458), we first consider MP linkage analysis limited to a single position; then we enlarge the scope and maximize the lods and mods over a span of positions. In all situations we examined, type I error rates decrease with increasing sample size, apparently approaching zero. We show: (a) For MP lods analyzed only at a single position, well-known statistical theory predicts that type I error rates approach zero. (b) For MP lods and mods maximized over position, this result has a different explanation, related to the fact that one maximizes the scores over only a finite portion of the parameter range. The implications of these findings may be far-reaching: Although it is widely accepted that fixed nominal critical values for MP lods and mods are not known, this study shows that whatever the nominal error rates are, the actual error rates appear to decrease with increasing sample size. Moreover, the actual (observed) type I error rate may be quite small for any given study. We conclude that MP lod and mod scores provide reliable linkage evidence for complex diseases, despite the unknown limiting distributions of these MP scores.

Genome-wide parametric linkage analyses of 644 bipolar pedigrees suggest susceptibility loci at chromosomes 16 and 20

OBJECTIVE

Our aim is to map chromosomal regions that harbor loci that increase susceptibility to bipolar disorder.

METHODS

We analyzed 644 bipolar families ascertained by the National Institute of Mental Health Human Genetics Initiative for bipolar disorder. The families have been genotyped with microsatellite loci spaced every approximately 10 cM or less across the genome. Earlier analyses of these pedigrees have been limited to nonparametric (model-free) methods and thus, information from unaffected subjects with genotypes was not considered. In this study, we used parametric analyses assuming dominant and recessive transmission and specifying a maximum penetrance of 70%, so that information from unaffecteds could be weighed in the linkage analyses. As in previous linkage analyses of these pedigrees, we analyzed three diagnostic categories: model 1 included only bipolar I and schizoaffective, bipolar cases (1565 patients of whom approximately 4% were schizoaffective, bipolar); model 2 included all individuals in model 1 plus bipolar II patients (1764 total individuals); and model 3 included all individuals in model 2 with the addition of patients with recurrent major depressive disorder (2046 total persons).

RESULTS

Assuming dominant inheritance the highest genome-wide pair-wise logarithm of the odds (LOD) score was 3.2 with D16S749 using model 2 patients. Multipoint analyses of this region yielded a maximum LOD score of 4.91. Under recessive transmission a number of chromosome 20 markers were positive and multipoint analyses of the area gave a maximum LOD of 3.0 with model 2 cases.

CONCLUSION

The chromosome 16p and 20 regions have been implicated by some studies and the data reported herein provide additional suggestive evidence of bipolar susceptibility genes in these regions.

Inferential testing for linkage with GENEHUNTER-MODSCORE: The impact of the pedigree structure on the null distribution of multipoint MOD scores

The asymptotic distribution of [MOD] scores under the null hypothesis of no linkage is only known for affected sib pairs and other types of affected relative pairs. We have extended the GENEHUNTER-MODSCORE program to allow for simulations under the null hypothesis of no linkage to determine the empirical significance of MOD-score results in general situations. We performed simulations with families of different size (one million replicates of 500 families per simulation setting) to thoroughly investigate the impact of the pedigree size on the null distribution of multipoint MOD scores. It is shown that the distribution is dependent on the size and structure of the pedigrees under study. By performing simulations in the context of MOD-score analysis, our new tool efficiently explores the linkage data in a comprehensive way and also provides a valid method to inferentially test for linkage.

Contemporary model-free methods for linkage analysis

Model-free linkage methods are based on identifying regions of the genome in which patterns of allele sharing among family members correspond to patterns of phenotype correlation among family members. Two general classes of model-free linkage methods are discussed in this chapter, relative pair methods designed primarily for analysis of discrete traits and variance component methods designed primarily for analysis of quantitative traits. These methods have been used to identify numerous genes influencing complex human phenotypes and remain viable approaches to gene localization in the twenty-first century.

A novel approach to detect parent-of-origin effects from pedigree data with application to Beckwith-Wiedemann syndrome

The parent-of-origin phenomenon in humans is now well recognized, and the deregulation of imprinted genes has been implicated in a number of human diseases. Recently, several linkage analysis methods have been developed to allow for parent-of-origin effects in the analysis of pedigree data. However, in general, one does not know a priori if disease-causing loci are imprinted or not. Linkage methods that allow for imprinting can lose power if there is no imprinting. Conversely, linkage methods that do not allow for imprinting will lose power if there is imprinting, because of penetrance values not being correctly specified. Therefore, it is important to know whether imprinting is a possible mode of disease inheritance before performing linkage analyses. In this paper we describe a simple covariate-coding scheme to test for the presence of parent-of-origin effects, and provide a formula for calculating parent-specific penetrance values prior to any linkage analysis. In simulation studies our coding scheme successfully detected parent-of-origin effects and, when pedigrees were ascertained sequentially or through a single proband, inclusion of this covariate more accurately estimated penetrance values than when such a covariate was not included. The use of accurate penetrance values in a linkage analysis that allows for imprinting can provide higher power when the disease locus is imprinted. Finally, we applied our approach to 27 pedigrees affected with Beckwith-Wiedemann syndrome (BWS), an overgrowth syndrome, and found that a maternally expressed parent-of-origin model based on the likelihood ratio test was the most parsimonious, suggesting a role for paternally imprinted genes in BWS.

MOD-Score Analysis with Simple Pedigrees: An Overview of Likelihood-Based Linkage Methods

A MOD-score analysis, in which the parametric LOD score is maximized with respect to the trait-model parameters, can be a powerful method for the mapping of complex traits. With affected sib pairs, it has been shown before that MOD scores asymptotically follow a mixture of chi(2) distributions with 2, 1 and 0 degrees of freedom under the null hypothesis of no linkage. In that context, a MOD-score analysis yields some (albeit limited) information regarding the trait-model parameters, and there is a chance for an increased power compared to a simple LOD-score analysis. Here, it is shown that with unilineal affected relative pairs, MOD scores asymptotically follow a mixture of chi(2) distributions with 1 and 0 degrees of freedom under the null hypothesis, that is, the same distribution as followed by simple LOD scores. No information regarding the trait model can be obtained in this setting, and no power is gained when compared to a LOD-score analysis. An outlook to larger pedigrees is given. The number of degrees of freedom underlying the null distribution of MOD scores, that depends on the type of pedigrees studied, corresponds to the number of explored dimensions related to power and to the number of parameters that can jointly be estimated.

Y chromosome lineage- and village-specific genes on chromosomes 1p22 and 6q27 control visceral leishmaniasis in Sudan

Familial clustering and ethnic differences suggest that visceral leishmaniasis caused by Leishmania donovani is under genetic control. A recent genome scan provided evidence for a major susceptibility gene on Chromosome 22q12 in the Aringa ethnic group in Sudan. We now report a genome-wide scan using 69 families with 173 affected relatives from two villages occupied by the related Masalit ethnic group. A primary ten-centimorgan scan followed by refined mapping provided evidence for major loci at 1p22 (LOD score 5.65; nominal p = 1.72 × 10⁻⁷; empirical p < 1 × 10⁻⁵; λ_S = 5.1) and 6q27 (LOD score 3.74; nominal p = 1.68 × 10⁻⁵; empirical p < 1 × 10⁻⁴; λ_S = 2.3) that were Y chromosome–lineage and village-specific. Neither village supported a visceral leishmaniasis susceptibility gene on 22q12. The results suggest strong lineage-specific genes due to founder effect and consanguinity in these recently immigrant populations. These chance events in ethnically uniform African populations provide a powerful resource in the search for genes and mechanisms that regulate this complex disease.

The parasitic disease kala-azar, or visceral leishmaniasis, is associated with liver, spleen, and lymph gland enlargement, as well as fever, weight loss, and anaemia. It is fatal unless treated. Three major foci of disease occur in India, Sudan, and Brazil. Importantly, 80%–90% of infections are asymptomatic. Understanding why two people with the same exposure to infection differ in susceptibility could provide important leads for improved therapies. We studied families with multiple cases of clinical disease from two villages in Sudan. After typing 300–400 genetic markers across the human genome, we determined which chromosomes carry susceptibility genes. We were surprised that our results differed from those published earlier for a village 100 kilometers from our site. All of these villages are occupied by people of the same ethnic group who migrated from western Sudan late last century following a major drought. We stratified our analysis by village, and used male Y chromosome markers to tag extended pedigrees. Our results suggest that recent immigration, in combination with consanguineal marriage in a strongly patriarchal society, has amplified founder effects resulting in different lineages within each village carrying different susceptibility loci. This demonstrates the importance of understanding population genetic substructure in studying genes that regulate complex disease.

Distribution and magnitude of type I error of model-based multipoint lod scores: implications for multipoint mod scores

The multipoint lod score and mod score methods have been advocated for their superior power in detecting linkage. However, little has been done to determine the distribution of multipoint lod scores or to examine the properties of mod scores. In this paper we study the distribution of multipoint lod scores both analytically and by simulation. We also study by simulation the distribution of maximum multipoint lod scores when maximized over different penetrance models. The multipoint lod score is approximately normally distributed with mean and variance that depend on marker informativity, marker density, specified genetic model, number of pedigrees, pedigree structure, and pattern of affection status. When the multipoint lod scores are maximized over a set of assumed penetrances models, an excess of false positive indications of linkage appear under dominant analysis models with low penetrances and under recessive analysis models with high penetrances. Therefore, caution should be taken in interpreting results when employing multipoint lod score and mod score approaches, in particular when inferring the level of linkage significance and the mode of inheritance of a trait.

Localization and replication of the systemic lupus erythematosus linkage signal at 4p16: interaction with 2p11, 12q24 and 19q13 in European Americans

Systemic lupus erythematosus (SLE) is a systemic autoimmune disease characterized by both population and phenotypic heterogeneity. Our group previously identified linkage to SLE at 4p16 in European Americans (EA). In the present study we replicate this linkage effect in a new cohort of 76 EA families multiplex for SLE by model-free linkage analysis. Using densely spaced microsatellite markers in the linkage region, we have localized the potential SLE susceptibility gene(s) to be telomeric to the marker D4S2928 by haplotype construction. In addition, marker D4S394 showed marginal evidence of linkage disequilibrium with the putative disease locus by the transmission disequilibrium test and significant evidence of association using a family-based association approach as implemented in the program ASSOC. We also performed both two-point and multipoint model-based analyses to characterize the genetic model of the potential SLE susceptibility gene(s), and the lod scores both maximized under a recessive model with penetrances of 0.8. Finally, we performed a genome-wide scan of the total 153 EA pedigrees and evaluated the possibility of interaction between linkage signals at 4p16 and other regions in the genome. Fourteen regions on 11 chromosomes (1q24, 1q42, 2p11, 2q32, 3p14.2, 4p16, 5p15, 7p21, 8p22, 10q22, 12p11, 12q24, 14q12, 19q13) showed evidence of linkage, among which, signals at 2p11, 12q24 and 19q13 also showed evidence of interaction with that at 4p16. These results provide important additional information about the SLE linkage effect at 4p16 and offer a unique approach to uncovering susceptibility loci involved in complex human diseases.

Genome scan for loci predisposing to anxiety disorders using a novel multivariate approach: strong evidence for a chromosome 4 risk locus

We conducted a 10-centimorgan linkage autosomal genome scan in a set of 19 extended American pedigrees (219 subjects) ascertained through probands with panic disorder. Several anxiety disorders--including social phobia, agoraphobia, and simple phobia--in addition to panic disorder segregate in these families. In previous studies of this sample, linkage analyses were based separately on each of the individual categorical affection diagnoses. Given the substantial comorbidity between anxiety disorders and their probable shared genetic liability, it is clear that this method discards a considerable amount of information. In this article, we propose a new approach that considers panic disorder, simple phobia, social phobia, and agoraphobia as expressions of the same multivariate, putatively genetically influenced trait. We applied the most powerful multipoint Haseman-Elston method, using the grade of membership score generated from a fuzzy clustering of these phenotypes as the dependent variable in Haseman-Elston regression. One region on chromosome 4q31-q34, at marker D4S413 (with multipoint and single-point nominal P values < .00001), showed strong evidence of linkage (genomewide significance at P<.05). The same region is known to be the site of a neuropeptide Y receptor gene, NPY1R (4q31-q32), that was recently connected to anxiolytic-like effects in rats. Several other regions on four chromosomes (4q21.21-22.3, 5q14.2-14.3, 8p23.1, and 14q22.3-23.3) met criteria for suggestive linkage (multipoint nominal P values < .01). Family-by-family analysis did not show any strong evidence of heterogeneity. Our findings support the notion that the major anxiety disorders, including phobias and panic disorder, are complex traits that share at least one susceptibility locus. This method could be applied to other complex traits for which shared genetic-liability factors are thought to be important, such as substance dependencies.

Genome-wide linkage scan in a large bipolar disorder sample from the National Institute of Mental Health genetics initiative suggests putative loci for bipolar disorder, psychosis, suicide, and panic disorder

We conducted a 9-cM genome scan in a large bipolar pedigree sample from the National Institute of Mental Health genetics initiative (1060 individuals from 154 multiplex families). We performed parametric and nonparametric analyses using both standard diagnostic models and comorbid conditions thought to identify phenotypic subtypes: psychosis, suicidal behavior, and panic disorder. Our strongest linkage signals (genome-wide significance) were observed on chromosomes 10q25, 10p12, 16q24, 16p13, and 16p12 using standard diagnostic models, and on 6q25 (suicidal behavior), 7q21 (panic disorder) and 16p12 (psychosis) using phenotypic subtypes. Several other regions were suggestive of linkage, including 1p13 (psychosis), 1p21 (psychosis), 1q44, 2q24 (suicidal behavior), 2p25 (psychosis), 4p16 (psychosis, suicidal behavior), 5p15, 6p25 (psychosis), 8p22 (psychosis), 8q24, 10q21, 10q25 (suicidal behavior), 10p11 (psychosis), 13q32 and 19p13 (psychosis). Over half the implicated regions were identified using phenotypic subtypes. Several regions - 1p, 1q, 6q, 8p, 13q and 16p - have been previously reported to be linked to bipolar disorder. Our results suggest that dissection of the disease phenotype can enrich the harvest of linkage signals and expedite the search for susceptibility genes. This is the first large-scale linkage scan of bipolar disorder to analyze simultaneously bipolar disorder, psychosis, suicidal behavior, and panic disorder.

Genomewide scan for real-word reading subphenotypes of dyslexia: novel chromosome 13 locus and genetic complexity

Dyslexia is a common learning disability exhibited as a delay in acquiring reading skills despite adequate intelligence and instruction. Reading single real words (real-word reading, RWR) is especially impaired in many dyslexics. We performed a genome scan, using variance components (VC) linkage analysis and Bayesian Markov chain Monte Carlo (MCMC) joint segregation and linkage analysis, for three quantitative measures of RWR in 108 multigenerational families, with follow up of the strongest signals with parametric LOD score analyses. We used single-word reading efficiency (SWE) to assess speed and accuracy of RWR, and word identification (WID) to assess accuracy alone. Adjusting SWE for WID provided a third measure of RWR efficiency. All three methods of analysis identified a strong linkage signal for SWE on chromosome 13q. Based on multipoint analysis with 13 markers we obtained a MCMC intensity ratio (IR) of 53.2 (chromosome-wide P < 0.004), a VC LOD score of 2.29, and a parametric LOD score of 2.94, based on a quantitative-trait model from MCMC segregation analysis (SA). A weaker signal for SWE on chromosome 2q occurred in the same location as a significant linkage peak seen previously in a scan for phonological decoding. MCMC oligogenic SA identified three models of transmission for WID, which could be assigned to two distinct linkage peaks on chromosomes 12 and 15. Taken together, these results indicate a locus for efficiency and accuracy of RWR on chromosome 13, and a complex model for inheritance of RWR accuracy with loci on chromosomes 12 and 15.

Advances in statistical human genetics over the last 25 years

The past 25 years has seen an explosion in the number of genetic markers that can be measured on DNA samples at an ever decreasing cost. Although basic statistical methods for analysing such data gathered on samples of either independent individuals or family members, one or two markers at a time, were already well developed before this explosion occurred, there has been a corresponding burst in activity to develop multiple marker models to find disease-causing gene variants, capitalizing on the data that have become available, to increase the power of such methods. This has required the concomitant development of faster algorithms to speed up the computation of various likelihoods. For linkage analysis, to obtain the approximate locations for genes of interest, Mendelian segregation models have been extended to be more realistic and statistical models that do not assume specific modes of inheritance have been extended to allow for the analysis of larger pedigree structures. For association analysis, to obtain more precise locations for genes of interest, the recent completion of the first stage of the HapMap project has spurred the development, still underway, of novel experimental designs and analytical methods to combat the curse of dimensionality and the resulting multiple testing problem. Perhaps the greatest current challenge concerns how best to gather and synthesize the many lines of evidence possible in order to discover the genetic determinants underlying complex diseases.

Linkage analysis of alcohol dependence using MOD scores

Alcohol dependence is a typical example of a complex trait that is governed by several genes and for which the mode of inheritance is unknown. We analyzed the microsatellite markers and the Affymetrix single-nucleotide polymorphisms (SNPs) for a subset of the Collaborative Study on the Genetics of Alcoholism family sample, 93 pedigrees of Caucasian ancestry comprising 919 persons, 390 of whom are affected according to DSM III-R and Feighner criteria. In particular, we performed parametric single-marker linkage analysis using MLINK of the LINKAGE package (for the microsatellite data), as well as multipoint MOD-score analysis with GENEHUNTER-MODSCORE (for the microsatellite and SNP data). By use of two liability classes, different penetrances were assigned to males and females. In order to investigate parent-of-origin effects, we calculated MOD scores under trait models with and without imprinting. In addition, for the microsatellite data, the MOD-score analysis was performed with sex-averaged as well as sex-specific maps. The highest linkage peaks were obtained on chromosomes 1, 2, 7, 10, 12, 13, 15, and 21. There was evidence for paternal imprinting at the loci on chromosomes 2, 10, 12, 13, 15, and 21. A tendency to maternal imprinting was observed at two loci on chromosome 7. Our findings underscore the fact that an adequate modeling of the genotype-phenotype relation is crucial for the genetic mapping of a complex trait.

Analysis of genes for alcoholism using two-disease-locus models

Using model-based two-locus methods for mapping genes, we analyzed the family data from the Collaborative Study on the Genetics of Alcoholism. Microsatellite data from 143 families ascertained through having three or more individuals affected with alcohol dependence were used for this investigation. Four regions showing evidence for linkage were identified using single-locus models from previous investigations. We investigated the genetic linkage, pattern of disease inheritance, and pair-wise genetic epistasis of these loci using the TLINKAGE program for two-disease-locus analysis.

Linkage disequilibrium inflates type I error rates in multipoint linkage analysis when parental genotypes are missing

OBJECTIVES

Describe the inflation in nonparametric multipoint LOD scores due to inter-marker linkage disequilibrium (LD) across many markers with varied allele frequencies.

METHOD

Using simulated two-generation families with and without parents, we conducted nonparametric multipoint linkage analysis with 2 to 10 markers with minor allele frequencies (MAF) of 0.5 and 0.1.

RESULTS

Misspecification of population haplotype frequencies by assuming linkage equilibrium caused inflated multipoint LOD scores due to inter-marker LD when parental genotypes were not included. Inflation increased as more markers in LD were included and decreased as markers in equilibrium were added. When marker allele frequencies were unequal, the r2 measure of LD was a better predictor of inflation than D'.

CONCLUSION

This observation strongly supports the evaluation of LD in multipoint linkage analyses, and further suggests that unaccounted for LD may be suspected when two-point and multipoint linkage analyses show a marked disparity in regions with elevated r2 measures of LD. Given the increasing popularity of high-density genome-wide SNP screens, inter-marker LD should be a concern in future linkage studies.

A genome scan in multigenerational families with dyslexia: Identification of a novel locus on chromosome 2q that contributes to phonological decoding efficiency

Dyslexia is a common and complex developmental disorder manifested by unexpected difficulty in learning to read. Multiple different measures are used for diagnosis, and may reflect different biological pathways related to the disorder. Impaired phonological decoding (translation of written words without meaning cues into spoken words) is thought to be a core deficit. We present a genome scan of two continuous measures of phonological decoding ability: phonemic decoding efficiency (PDE) and word attack (WA). PDE measures both accuracy and speed of phonological decoding, whereas WA measures accuracy alone. Multipoint variance component linkage analyses (VC) and Markov chain Monte-Carlo (MCMC) multipoint joint linkage and segregation analyses were performed on 108 families. A strong signal was observed on chromosome 2 for PDE using both VC (LOD=2.65) and MCMC methods (intensity ratio (IR)=32.1). The IR is an estimate of the ratio of the posterior to prior probability of linkage in MCMC analysis. The chromosome 2 signal was not seen for WA. More detailed mapping with additional markers provided statistically significant evidence for linkage of PDE to chromosome 2, with VC-LOD=3.0 and IR=59.6 at D2S1399. Parametric analyses of PDE, using a model obtained by complex segregation analysis, provided a multipoint maximum LOD=2.89. The consistency of results from three analytic approaches provides strong evidence for a locus on chromosome 2 that influences speed but not accuracy of phonological decoding.

Effect of genotyping error on type-I error rate of affected sib pair studies with genotyped parents

OBJECTIVE

In affected sib pair studies without genotyped parents the effect of genotyping error is generally to reduce the type I error rate and power of tests for linkage. The effect of genotyping error when parents have been genotyped is unknown. We investigated the type I error rate of the single-point Mean test for studies in which genotypes of both parents are available.

METHODS

Datasets were simulated assuming no linkage and one of five models for genotyping error. In each dataset, Mendelian-inconsistent families were either excluded or regenotyped, and then the Mean test applied.

RESULTS

We found that genotyping errors lead to an inflated type I error rate when inconsistent families are excluded. Depending on the genotyping-error model assumed, regenotyping inconsistent families has one of several effects. It may produce the same type I error rate as if inconsistent families are excluded; it may reduce the type I error, but still leave an anti-conservative test; or it may give a conservative test. Departures of the type I error rate from its nominal level increase with both the genotyping error rate and sample size.

CONCLUSION

We recommend that markers with high error rates either be excluded from the analysis or be regenotyped in all families.

Linkage analysis of a completely ascertained sample of familial schizophrenics and bipolars from Palau, Micronesia

We report on linkage analysis of a completely ascertained population of familial psychosis derived from the oceanic nation of Palau. Palau, an archipelago of islands in the Southern Pacific, currently has a population of approximately 23,000 individuals. The peoples of Palau populated these islands recently in human history, approximately 2,000 years ago. As both historical and genetic evidence suggest, the population is far more homogeneous than most other populations undergoing genetic studies, and should therefore prove quite useful for mapping genetic variants having a meaningful impact on susceptibility to psychotic disorders. Moreover, for our study, essentially all on-island schizophrenics (150) and individuals with other psychotic disorders (25) participated. By analysis of narrow (only schizophrenia) and broad (all psychosis) diagnostic schemes, two-point linkage analyses suggest that two regions of the genome harbor genetic variants affecting liability in most families, 3q28 (LOD = 3.03) and 17q32.2 (LOD = 2.80). Results from individual pedigrees also support 2q37.2, 2p14, and 17p13 as potentially harboring important genetic variants. Most of these regions have been implicated in other genetic studies of psychosis in populations physically quite distant from this Oceanic population, although some (e.g., 3q28) appear to be novel results for schizophrenia linkage analyses.

Joint oligogenic segregation and linkage analysis using bayesian Markov chain Monte Carlo methods

One of the most challenging areas in human genetics is the dissection of quantitative traits. In this context, the efficient use of available data is important, including, when possible, use of large pedigrees and many markers for gene mapping. In addition, methods that jointly perform linkage analysis and estimation of the trait model are appealing because they combine the advantages of a model-based analysis with the advantages of methods that do not require prespecification of model parameters for linkage analysis. Here we review a Markov chain Monte Carlo approach for such joint linkage and segregation analysis, which allows analysis of oligogenic traits in the context of multipoint linkage analysis of large pedigrees. We provide an outline for practitioners of the salient features of the method, interpretation of the results, effect of violation of assumptions, and an example analysis of a two-locus trait to illustrate the method.

Issues in Association Analysis: Error Control in Case-Control Association Studies for Disease Gene Discovery

Several sources of errors are discussed. While genotyping errors have little effect on power in case-control association studies, they tend to strongly increase false positive results in TDT type tests unless occurrence of errors is allowed for in the analysis (e.g., TDTae test). Disregarding non-genetic risk factors is shown to lead to a form of hidden heterogeneity, which can strongly reduce power. Stratification of data into more homogeneous subgroups is advocated as a simple solution to allowing for non-genetic risk factors such as socio-economic status and food preferences.

A genome-wide screen on the genetics of atopy in a multiethnic European population reveals a major atopy locus on chromosome 3q21.3

BACKGROUND

Dissecting complex diseases in underlying distinct traits and studying these for their genetic basis might enhance the power as well as the specificity, of detection of disease genes. These phenotypes are known as intermediate phenotypes.

OBJECTIVE

We were interested in the atopic basis of asthma, and used the sensitization to mite (Dermatophagoides pteronyssinus) allergens as a pathophysiologically important intermediate phenotype.

METHODS

This time we performed a genome-wide scan based on the same already used multiethnic European population consisting of 82 nuclear families with at least two affected siblings. We carried out nonparametric as well as parametric MOD-score analyses based on the genotypes of 603 microsatellite markers.

RESULTS

In comparison with our first genome-wide candidate region search three novel regions additionally appeared to be significant. We obtained significant results for the region 2p12 with a MOD score of 3.35 and for the region 16q21 with a MOD score of 4.18. The most significant result was found for the region 3q21.3 with the same microsatellite marker, which showed significant linkage to atopic dermatitis (AD) in another study with a MOD score of 4.51 and an nonparametric linkage analysis (NPL) of 4.00.

CONCLUSION

Our findings indicate that atopy, allergic asthma, allergic rhinitis and AD on the one hand are distinct traits on both the clinical and genetic basis, but on the other hand, our results also underline that these traits are closely related diseases concerning the atopic basis of the traits.

High factor VIII levels in venous thromboembolism show linkage to imprinted loci on chromosomes 5 and 11

High factor VIII (FVIII) levels are known to be a risk factor for deep venous thrombosis, but the mechanisms responsible for high FVIII levels remain unclear. Here, a new phenotype “FVIII level residuum” (FVIII-R) was defined in order to eliminate the impact of common determinants on FVIII levels. We studied 13 families of patients with thrombosis and reproducibly high FVIII levels of unknown origin. Since familial clustering was evident, we looked for a possible genetic basis. A genome scan was performed with 402 evenly spaced microsatellite markers. A quantitative linkage analysis using variance component methods showed suggestive evidence for linkage of FVIII-R with a locus on chromosome 8 (logarithm of odds [LOD] = 2.1). In addition, we performed parametric exploratory linkage analysis of dichotomized FVIII-R, taking a parent-of-origin effect into account. Single-trait-locus MOD-score analysis showed suggestive evidence for linkage under an imprinting model at chromosomes 5 and 11. Furthermore, a 2-trait-locus analysis under a multiplicative model for the loci of chromosomes 5 and 11 yielded a remarkable LOD of 4.44. It confirmed the finding of paternal imprinting, obtained by single-trait-locus analysis, at both loci. Our results suggest that high FVIII levels in venous thromboembolism represent a complex trait caused by several genetic factors.

Mapping genes of complex psychiatric diseases in Daghestan genetic isolates

Genetic isolates, which provide outstanding opportunities for identification of susceptibility genes for complex diseases, can be classified as primary (having an ancient demographic history in a stable environment) or secondary (having a younger demographic history) Neel [1992: Minority populations: Genetics, demography, and health, pp. 1-13]. Daghestan contains 26 out of 50 indigenous Caucasus ethnicities that have been in existence for hundreds of generations in the same highland region. The ethnic groups are subdivided into numerous primary isolates. The founder effect and gene drift in these primary isolates may have caused aggregation of specific haplotypes with limited numbers of pathogenic alleles and loci in some isolates relative to others. These are expressed as inter-population differences in lifetime prevalence and features of certain complex clinical phenotypes and in patterns of genetic linkage and linkage disequilibrium (LD). Stable highland and ethnic-cultural environments have led to increased penetrance and a reduced number of phenocopies, which typically hamper the identification of any susceptibility genes for complex diseases. Owing to these characteristics of the primary isolates, a comparative linkage study in the primary isolates allows us to define the number of susceptibility genes for any complex disease and to identify the source of variability and non-replication of linkage analysis results. As part of an ongoing study, seven extended schizophrenia and one nonspecific mental retardation kindreds have been ascertained from Daghestan isolates. Lifetime morbid risk for schizophrenia in the isolates varied from 0 to 5%. A genome scan with markers spaced 10 cM apart was carried out on these pedigrees and linkage analysis was performed using descent graph methods, as implemented in Simwalk2. To identify regions containing susceptibility genes within these kindreds, we followed up those regions with non-parametric and parametric linkage analyses, with the choice of genetic model guided by the results obtained in the NPL. While the analyses are ongoing, the most positive findings were made in different isolated pedigrees on chromosomes 17p11, 3q24, and 22q for schizophrenia and on chromosome 12q for nonspecific mental retardation.

Comparison of microsatellites versus single-nucleotide polymorphisms in a genome linkage screen for prostate cancer-susceptibility Loci

Prostate cancer is one of the most common cancers among men and has long been recognized to occur in familial clusters. Brothers and sons of affected men have a 2-3-fold increased risk of developing prostate cancer. However, identification of genetic susceptibility loci for prostate cancer has been extremely difficult. Although the suggestion of linkage has been reported for many chromosomes, the most promising regions have been difficult to replicate. In this study, we compare genome linkage scans using microsatellites with those using single-nucleotide polymorphisms (SNPs), performed in 467 men with prostate cancer from 167 families. For the microsatellites, the ABI Prism Linkage Mapping Set version 2, with 402 microsatellite markers, was used, and, for the SNPs, the Early Access Affymetrix Mapping 10K array was used. Our results show that the presence of linkage disequilibrium (LD) among SNPs can lead to inflated LOD scores, and this seems to be an artifact due to the assumption of linkage equilibrium that is required by the current genetic-linkage software. After excluding SNPs with high LD, we found a number of new LOD-score peaks with values of at least 2.0 that were not found by the microsatellite markers: chromosome 8, with a maximum model-free LOD score of 2.2; chromosome 2, with a LOD score of 2.1; chromosome 6, with a LOD score of 4.2; and chromosome 12, with a LOD score of 3.9. The LOD scores for chromosomes 6 and 12 are difficult to interpret, because they occurred only at the extreme ends of the chromosomes. The greatest gain provided by the SNP markers was a large increase in the linkage information content, with an average information content of 61% for the SNPs, versus an average of 41% for the microsatellite markers. The strengths and weaknesses of microsatellite versus SNP markers are illustrated by the results of our genome linkage scans.

Linkage analysis of psychosis in bipolar pedigrees suggests novel putative loci for bipolar disorder and shared susceptibility with schizophrenia

The low-to-moderate resolution of linkage analysis in complex traits has underscored the need to identify disease phenotypes with presumed genetic homogeneity. Bipolar disorder (BP) accompanied by psychosis (psychotic BP) may be one such phenotype. We previously reported a genome-wide screen in a large bipolar pedigree sample. In this follow-up study, we reclassified the disease phenotype based on the presence or absence of psychotic features and subgrouped pedigrees according to familial load of psychosis. Evidence for significant linkage to psychotic BP (genome-wide P<0.05) was obtained on chromosomes 9q31 (lod=3.55) and 8p21 (lod=3.46). Several other sites were supportive of linkage, including 5q33 (lod=1.78), 6q21 (lod=1.81), 8p12 (lod=2.06), 8q24 (lod=2.01), 13q32 (lod=1.96), 15q26 (lod=1.96), 17p12 (lod=2.42), 18q21 (lod=2.4), and 20q13 (lod=1.98). For most loci, the highest lod scores, including those with genome-wide significance (at 9q31 and 8p21), occurred in the subgroup of families with the largest concentration of psychotic individuals (> or =3 in a family). Interestingly, all regions but six--5q33, 6q21, 8p21, 8q24, 13q32 and 18q21--appear to be novel; namely, they did not show notable linkage to BP in other genome scans, which did not employ psychosis for disease classification. Also of interest is possible overlap with schizophrenia, another major psychotic disorder: seven of the regions presumed linked in this study--5q, 6q, 8p, 13q, 15q, 17p, and 18q--are also implicated in schizophrenia, as are 2p13 and 10q26, which showed more modest support for linkage. Our results suggest that BP in conjunction with psychosis is a potentially useful phenotype that may: (1) expedite the detection of susceptibility loci for BP and (2) cast light on the genetic relationship between BP and schizophrenia.

Low-Density Lipoprotein Particle Size Loci in Familial Combined Hyperlipidemia

Objective— Low-density lipoprotein (LDL) size is associated with vascular disease and with familial combined hyperlipidemia (FCHL).

Methods and Results— We used logarithm of odds (lod) score and Bayesian Markov chain Monte Carlo (MCMC) linkage analysis methods to perform a 10-cM genome scan of LDL size, measured as peak particle diameter (PPD) and adjusted for age, sex, body mass index, and triglycerides in 4 large families with FCHL (n=185). We identified significant evidence of linkage to a chromosome 9p locus (multipoint lod max =3.70; MCMC intensity ratio [IR]=21) in a single family, and across all 4 families to chromosomes 16q23 (lod max =3.00; IR=43) near cholesteryl ester transfer protein ( CETP ) and to 11q22 (lod max =3.71; IR=120). Chromosome 14q24-31, a region with previous suggestive LDL PPD linkage evidence, yielded an IR of 71 but an lod max =1.79 in the combined families.

Conclusions— These results of significant evidence of linkage to 3 regions (9p, 16q, and 11q) and confirmatory support of previous reported linkage to 14q in large FCHL pedigrees demonstrate that LDL size is a trait influenced by multiple loci and illustrate the complementary use of lod score and MCMC methods in analysis of a complex trait.

A major lung cancer susceptibility locus maps to chromosome 6q23-25

Lung cancer is a major cause of death in the United States and other countries. The risk of lung cancer is greatly increased by cigarette smoking and by certain occupational exposures, but familial factors also clearly play a major role. To identify susceptibility genes for familial lung cancer, we conducted a genomewide linkage analysis of 52 extended pedigrees ascertained through probands with lung cancer who had several first-degree relatives with the same disease. Multipoint linkage analysis, under a simple autosomal dominant model, of all 52 families with three or more individuals affected by lung, throat, or laryngeal cancer, yielded a maximum heterogeneity LOD score (HLOD) of 2.79 at 155 cM on chromosome 6q (marker D6S2436). A subset of 38 pedigrees with four or more affected individuals yielded a multipoint HLOD of 3.47 at 155 cM. Analysis of a further subset of 23 multigenerational pedigrees with five or more affected individuals yielded a multipoint HLOD score of 4.26 at the same position. The 14 families with only three affected relatives yielded negative LOD scores in this region. A predivided samples test for heterogeneity comparing the LOD scores from the 23 multigenerational families with those from the remaining families was significant (P=.007). The 1-HLOD multipoint support interval from the multigenerational families extends from C6S1848 at 146 cM to 164 cM near D6S1035, overlapping a genomic region that is deleted in sporadic lung cancers as well as numerous other cancer types. Parametric linkage and variance-components analysis that incorporated effects of age and personal smoking also supported linkage in this region, but with somewhat diminished support. These results localize a major susceptibility locus influencing lung cancer risk to 6q23-25.

Linkage of bipolar affective disorder on chromosome 8q24: follow-up and parametric analysis

Our group first reported a linkage finding for bipolar (BP) disorder on chromosome 8q24 in a study of 50 multiplex pedigrees, with an HLOD score reaching 2.39. Recently, Cichon et al reported an LOD score of 3.62 in the same region using two-point parametric analysis. Subsequently, we published the results of a genome scan for linkage to BP disorder using a sample extended to 65 pedigrees in which chromosome 8q24 provided the best finding, an NPL score of 3.13, approaching the accepted score for suggestive linkage. We have now fine mapped this region of chromosome 8 in our 65 pedigrees by the addition of 19 microsatellite markers reaching a marker density of 0.8 cM and an information content of 0.84. After the addition of the new data, the original NPL score slightly increased to 3.25. Two-point parametric analysis using the model employed by Cichon et al obtained an LOD score of 3.32 for marker D8S256 at theta=0.14 exceeding the proposed threshold for genomewide significance. After adjusting the parameters in accordance with the 'common disease-common variant' hypothesis, multipoint parametric analysis resulted in an HLOD of 2.49 (alpha=0.78) between D8S529 and D8S256, and defined a 1-LOD interval corresponding to a 2.3 Mb region. No allelic association with the disease was observed for our set of microsatellite markers. Biologically, plausible candidate genes in this region include thyroglobulin, KCNQ3 coding for a voltage-gated potassium channel and the gene for brain adenyl-cyclase (ADCY8).

Where are the prostate cancer genes?--A summary of eight genome wide searches

BACKGROUND

There is strong evidence for genetic susceptibility to prostate cancer, but most of the genes underlying this susceptibility remain to be identified.

METHODS

We reviewed the results of eight genome-wide linkage searches based on 1,293 families with multiple cases of prostate cancer.

RESULTS

Across these studies, 11 linkage peaks with LOD scores in excess of 2 were identified. However, no chromosomal region was reported as significant at this level by more than one study and only one corresponded to a peak previously suggested by another group.

CONCLUSIONS

These results indicate that prostate cancer is genetically complex, and that combined analyses of large family sets will be required to evaluate reliably the linkage evidence.

Confirmation of chromosome 7q11 locus for predisposition to intracranial aneurysm

A significant linkage of intracranial aneurysm (IA) has recently been reported to chromosomal region 7q11 (MLS=3.22) in a genomic search of 85 Japanese nuclear families with at least two affected siblings (104 sib pairs). This region contains the elastin gene (ELN, OMIM 130160), which is a functional candidate gene for IA. We have replicated this finding through linkage analyses in 13 extended pedigrees from Utah, comprising 39 IA cases. We genotyped three markers flanking ELN and performed two-point and multipoint parametric analyses, employing simple dominant and recessive models. Analyses utilizing a recessive affecteds-only model yielded significant confirmation of linkage to the region (best evidence, multipoint TLOD=2.34, at D7S2421, corrected P=0.001). This study is the first to confirm the linkage of the 7q11 locus for IA.

Parametric and nonparametric genome scan analyses for human handedness

We have performed a genome scan using 25 nuclear families consisting of right-handed parents with at least two left-handed children. Handedness was assessed as a qualitative trait using a laterality quotient. Laterality quotients indicate the direction of handedness, which is hand preference for performing unimanual tasks. Both parametric and nonparametric linkage analyses were applied. The parametric analysis using the single-locus genetic model of Klar resulted in four different regions with LOD scores higher than 1. The region on chromosome 10q26 gave a suggestive LOD score of 2.02 at a recombination fraction of 0.05. Nonparametric analysis gave an NPL score for this region of 2.16. However, further fine mapping of the region on chromosome 10q26 failed to obtain a higher LOD score. These results suggest that handedness is a human quantitative trait locus and that the proposed non-Mendelian monogenic models are incorrect.

Genome-wide multipoint parametric linkage analysis of pulse pressure in large, extended utah pedigrees

High pulse pressure, a measure of arterial aging, is an important predictor of cardiovascular and general mortality. It has been suggested that the genetic etiology of pulse pressure is the same as systolic blood pressure. We performed a genome-wide, multipoint, parametric linkage analysis in 26 large, extended Utah pedigrees to locate genes affecting pulse pressure. Four parametric models were considered, including dominant and recessive modes of inheritance involving genes for high and low pulse pressure. Linkage analysis revealed 11 regions with a logarithm of the odds (LOD) >1.5, including 2 regions attaining genome-wide suggestive evidence for linkage after accounting for multiple tests. Inspecting pedigree-specific multipoint linkage evidence suggested that these 2 regions localized to 15.7 cM on chromosome 8p (LOD=2.89), between markers D8S136 and D8S1477, and 20.0 cM on chromosome 12q (LOD=2.59), between D12S1300 and D12S2070. Both regions were identified better by pulse pressure compared with equivalent analyses with systolic or diastolic blood pressure. Results for pulse pressure overlapped favorably with those of others for related blood pressure phenotypes and support the hypothesis that genes with pleiotropic effects on blood pressure phenotypes do exist, but that the genetic etiologies are not identical. In conclusion, our results suggest that pulse pressure might be of use for identifying genes involved in blood pressure phenotypes and arterial aging.

Multipoint and single point non-parametric linkage analysis with imperfect data

We used simulation to explore the impact of common data imperfections (i.e., missing parents, genotyping error, map error, and missing genotypes) upon the performance of multipoint and single point linkage analysis in the analyses of linkage data from pairs of siblings affected with an idealized complex trait. The performance of single point and multipoint linkage was similar under an unrealistic best case scenario; however, when four data imperfections were combined, the performance of single point linkage analysis appeared to be superior to multipoint. The absence of parental genotypes in the presence of 1% genotype error led to marked degradation of linkage signal, particularly for multipoint analyses.