Efficient multipoint linkage analysis through reduction of inheritance space

Drawing human pedigree charts with DrawPed

Creating pedigree charts is a recurring task in biomedical research, but there are few online tools for drawing complex human pedigrees available and even fewer are free. With DrawPed we aim to close this gap. DrawPed automatically draws pedigree charts from standard PED format pedigree files. Users can also create pedigrees from scratch and interactively edit existing pedigrees. The application can display conditions not captured in a PED file such as deceased persons or suspected consanguinity of parents. Pedigree charts are displayed as SVGs, which are scalable and hence publication-ready. Pedigrees can be exported as PED files for storage, exchange, or use in other applications. DrawPed is open source and freely available at https://www.genecascade.org/DrawPed/.

Privacy-preserving genotype imputation in a trusted execution environment

Genotype imputation is an essential tool in genomics research, whereby missing genotypes are inferred using reference genomes to enhance downstream analyses. Recently, public imputation servers have allowed researchers to leverage large-scale genomic data resources for imputation. However, privacy concerns about uploading one's genetic data to a server limit the utility of these services. We introduce a secure hardware-based solution for privacy-preserving genotype imputation, which keeps the input genomes private by processing them within Intel SGX's trusted execution environment. Our solution features SMac, an efficient and secure imputation algorithm designed for Intel SGX, which employs a state-of-the-art imputation strategy also utilized by existing imputation servers. SMac achieves imputation accuracy equivalent to existing tools and provides protection against known side-channel attacks on SGX while maintaining scalability. We also show the necessity of our enhanced security by identifying vulnerabilities in existing imputation software. Our work represents a step toward privacy-preserving genomic analysis services.

Artificially intelligent scoring and classification engine for forensic identification

Despite advances in genotyping technologies, traditional kinship analysis tools utilized in forensic identification have seen limited evolution and lack measures of accuracy. Here, we leverage artificial intelligence (AI) and extend the Elston-Stewart algorithm to deliver a method that provides an unprecedented level of flexibility to matching individuals with pedigrees by likelihood ratio. We designed an AI that utilizes a prediction cascade based on gradient descent logistic regression which allows for iterative solution of multi missing person scenarios. Furthermore, the AI can quantify the confidence underlying likelihood ratios across the spectrum of pedigrees, regardless of the amount of genetic information available and the number of missing persons. The algorithm accommodates an arbitrary number of generations and ancestral relationships, including multiple marriages, mutations, and consanguinity. We demonstrate that a properly trained AI significantly and reproducibly outperforms a human interpreter. We discuss published limitations of existing tools and demonstrate that they are not amenable to the size and complexity of this study. This novel method significantly improves the trade-off between sensitivity and specificity beyond the limits of traditional kinship analysis tools and introduces opportunities beyond the field of forensic genetics.

Mutations in mitochondrial DNA causing tubulointerstitial kidney disease

Tubulointerstitial kidney disease is an important cause of progressive renal failure whose aetiology is incompletely understood. We analysed a large pedigree with maternally inherited tubulointerstitial kidney disease and identified a homoplasmic substitution in the control region of the mitochondrial genome (m.547A>T). While mutations in mtDNA coding sequence are a well recognised cause of disease affecting multiple organs, mutations in the control region have never been shown to cause disease. Strikingly, our patients did not have classical features of mitochondrial disease. Patient fibroblasts showed reduced levels of mitochondrial tRNAPhe, tRNALeu1 and reduced mitochondrial protein translation and respiration. Mitochondrial transfer demonstrated mitochondrial transmission of the defect and in vitro assays showed reduced activity of the heavy strand promoter. We also identified further kindreds with the same phenotype carrying a homoplasmic mutation in mitochondrial tRNAPhe (m.616T>C). Thus mutations in mitochondrial DNA can cause maternally inherited renal disease, likely mediated through reduced function of mitochondrial tRNAPhe.

Model-Free Linkage Analysis of a Binary Trait

Genetic linkage analysis aims to detect chromosomal regions containing genetic variants that influence risk of specific inherited diseases. The presence of linkage is indicated when a disease or trait cosegregates through the families with genetic markers at a particular region of the genome. Two main types of genetic linkage analysis are in common use, namely model-based linkage analysis and model-free linkage analysis. In this chapter, we focus solely on the latter type and specifically on binary traits or phenotypes, such as the presence or absence of a specific disease. Model-free linkage analysis is based on allele-sharing, where patterns of genetic similarity among affected relatives are compared to chance expectations. Because the model-free methods do not require the specification of the inheritance parameters of a genetic model, they are preferred by many researchers at early stages in the study of a complex disease. We introduce the history of model-free linkage analysis in Subheading 1. Table 1 describes a standard model-free linkage analysis workflow. We describe three popular model-free linkage analysis methods, the nonparametric linkage (NPL) statistic, the affected sib-pair (ASP) likelihood ratio test, and a likelihood approach for pedigrees. The theory behind each linkage test is described in this section together with a simple example of the relevant calculations. Table 4 provides a summary of popular genetic analysis software packages that implement model-free linkage models. In Subheading 2, we work through the methods on a rich example providing sample software code and output. Subheading 3 contains notes with additional details on various topics that may need further consideration during analysis.

Next-generation genotype imputation service and methods

Genotype imputation is a key component of genetic association studies, where it increases power, facilitates meta-analysis, and aids interpretation of signals. Genotype imputation is computationally demanding and, with current tools, typically requires access to a high-performance computing cluster and to a reference panel of sequenced genomes. Here we describe improvements to imputation machinery that reduce computational requirements by more than an order of magnitude with no loss of accuracy in comparison to standard imputation tools. We also describe a new web-based service for imputation that facilitates access to new reference panels and greatly improves user experience and productivity.

A novel COL4A1 frameshift mutation in familial kidney disease: the importance of the C-terminal NC1 domain of type IV collagen

BACKGROUND

Hereditary microscopic haematuria often segregates with mutations of COL4A3, COL4A4 or COL4A5 but in half of families a gene is not identified. We investigated a Cypriot family with autosomal dominant microscopic haematuria with renal failure and kidney cysts.

METHODS

We used genome-wide linkage analysis, whole exome sequencing and cosegregation analyses.

RESULTS

We identified a novel frameshift mutation, c.4611_4612insG:p.T1537fs, in exon 49 of COL4A1. This mutation predicts truncation of the protein with disruption of the C-terminal part of the NC1 domain. We confirmed its presence in 20 family members, 17 with confirmed haematuria, 5 of whom also had stage 4 or 5 chronic kidney disease. Eleven family members exhibited kidney cysts (55% of those with the mutation), but muscle cramps or cerebral aneurysms were not observed and serum creatine kinase was normal in all individuals tested.

CONCLUSIONS

Missense mutations of COL4A1 that encode the CB3 [IV] segment of the triple helical domain (exons 24 and 25) are associated with HANAC syndrome (hereditary angiopathy, nephropathy, aneurysms and cramps). Missense mutations of COL4A1 that disrupt the NC1 domain are associated with antenatal cerebral haemorrhage and porencephaly, but not kidney disease. Our findings extend the spectrum of COL4A1 mutations linked with renal disease and demonstrate that the highly conserved C-terminal part of the NC1 domain of the α1 chain of type IV collagen is important in the integrity of glomerular basement membrane in humans.

Dosage transmission disequilibrium test (dTDT) for linkage and association detection

Both linkage and association studies have been successfully applied to identify disease susceptibility genes with genetic markers such as microsatellites and Single Nucleotide Polymorphisms (SNPs). As one of the traditional family-based studies, the Transmission/Disequilibrium Test (TDT) measures the over-transmission of an allele in a trio from its heterozygous parents to the affected offspring and can be potentially useful to identify genetic determinants for complex disorders. However, there is reduced information when complete trio information is unavailable. In this study, we developed a novel approach to "infer" the transmission of SNPs by combining both the linkage and association data, which uses microsatellite markers from families informative for linkage together with SNP markers from the offspring who are genotyped for both linkage and a Genome-Wide Association Study (GWAS). We generalized the traditional TDT to process these inferred dosage probabilities, which we name as the dosage-TDT (dTDT). For evaluation purpose, we developed a simulation procedure to assess its operating characteristics. We applied the dTDT to the simulated data and documented the power of the dTDT under a number of different realistic scenarios. Finally, we applied our methods to a family study of alcohol dependence (COGA) and performed individual genotyping on complete families for the top signals. One SNP (rs4903712 on chromosome 14) remained significant after correcting for multiple testing Methods developed in this study can be adapted to other platforms and will have widespread applicability in genomic research when case-control GWAS data are collected in families with existing linkage data.

Comparison of requirements and capabilities of major multipurpose software packages

The aim of this chapter is to introduce the reader to commonly used software packages and illustrate their input requirements, analysis options, strengths, and limitations. We focus on packages that perform more than one function and include a program for quality control, linkage, and association analyses. Additional inclusion criteria were (1) programs that are free to academic users and (2) currently supported, maintained, and developed. Using those criteria, we chose to review three programs: Statistical Analysis for Genetic Epidemiology (S.A.G.E.), PLINK, and Merlin. We will describe the required input format and analysis options. We will not go into detail about every possible program in the packages, but we will give an overview of the packages requirements and capabilities.

Model-free linkage analysis of a binary trait

Genetic linkage analysis aims to detect chromosomal regions containing genes that influence risk of specific inherited diseases. The presence of linkage is indicated when a disease or trait cosegregates through the families with genetic markers at a particular region of the genome. Two main types of genetic linkage analysis are in common use, namely model-based linkage analysis and model-free linkage analysis. In this chapter, we focus solely on the latter type and specifically on binary traits or phenotypes, such as the presence or absence of a specific disease. Model-free linkage analysis is based on allele-sharing, where patterns of genetic similarity among affected relatives are compared to chance expectations. Because the model-free methods do not require the specification of the inheritance parameters of a genetic model, they are preferred by many researchers at early stages in the study of a complex disease. We introduce the history of model-free linkage analysis in Subheading 1. Table 1 describes a standard model-free linkage analysis workflow. We describe three popular model-free linkage analysis methods, the nonparametric linkage (NPL) statistic, the affected sib-pair (ASP) likelihood ratio test, and a likelihood approach for pedigrees. The theory behind each linkage test is described in this section, together with a simple example of the relevant calculations. Table 4 provides a summary of popular genetic analysis software packages that implement model-free linkage models. In Subheading 2, we work through the methods on a rich example providing sample software code and output. Subheading 3 contains notes with additional details on various topics that may need further consideration during analysis.

Interplay between BRCA1 and RHAMM regulates epithelial apicobasal polarization and may influence risk of breast cancer

Differentiated mammary epithelium shows apicobasal polarity, and loss of tissue organization is an early hallmark of breast carcinogenesis. In BRCA1 mutation carriers, accumulation of stem and progenitor cells in normal breast tissue and increased risk of developing tumors of basal-like type suggest that BRCA1 regulates stem/progenitor cell proliferation and differentiation. However, the function of BRCA1 in this process and its link to carcinogenesis remain unknown. Here we depict a molecular mechanism involving BRCA1 and RHAMM that regulates apicobasal polarity and, when perturbed, may increase risk of breast cancer. Starting from complementary genetic analyses across families and populations, we identified common genetic variation at the low-penetrance susceptibility HMMR locus (encoding for RHAMM) that modifies breast cancer risk among BRCA1, but probably not BRCA2, mutation carriers: n = 7,584, weighted hazard ratio ((w)HR) = 1.09 (95% CI 1.02-1.16), p(trend) = 0.017; and n = 3,965, (w)HR = 1.04 (95% CI 0.94-1.16), p(trend) = 0.43; respectively. Subsequently, studies of MCF10A apicobasal polarization revealed a central role for BRCA1 and RHAMM, together with AURKA and TPX2, in essential reorganization of microtubules. Mechanistically, reorganization is facilitated by BRCA1 and impaired by AURKA, which is regulated by negative feedback involving RHAMM and TPX2. Taken together, our data provide fundamental insight into apicobasal polarization through BRCA1 function, which may explain the expanded cell subsets and characteristic tumor type accompanying BRCA1 mutation, while also linking this process to sporadic breast cancer through perturbation of HMMR/RHAMM.

Approaches to genetic linkage analysis

Genetic linkage analysis concerns the estimation of genetic distance between two or more genetic loci. In genetic epidemiology, it is predominantly used to identify, or map, a genetic locus that is associated with quantitative trait variation or, in the case of binary or discrete traits, modification of the risk of being affected with a disease or phenotype. Linkage analysis uses a panel of reference genetic markers to track the segregation of genomic segments within families or sets of relatives. Individuals within the families must be measured for the trait, and often the families have been selected because they segregate the phenotype of interest.

MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes

Genome-wide association studies (GWAS) can identify common alleles that contribute to complex disease susceptibility. Despite the large number of SNPs assessed in each study, the effects of most common SNPs must be evaluated indirectly using either genotyped markers or haplotypes thereof as proxies. We have previously implemented a computationally efficient Markov Chain framework for genotype imputation and haplotyping in the freely available MaCH software package. The approach describes sampled chromosomes as mosaics of each other and uses available genotype and shotgun sequence data to estimate unobserved genotypes and haplotypes, together with useful measures of the quality of these estimates. Our approach is already widely used to facilitate comparison of results across studies as well as meta-analyses of GWAS. Here, we use simulations and experimental genotypes to evaluate its accuracy and utility, considering choices of genotyping panels, reference panel configurations, and designs where genotyping is replaced with shotgun sequencing. Importantly, we show that genotype imputation not only facilitates cross study analyses but also increases power of genetic association studies. We show that genotype imputation of common variants using HapMap haplotypes as a reference is very accurate using either genome-wide SNP data or smaller amounts of data typical in fine-mapping studies. Furthermore, we show the approach is applicable in a variety of populations. Finally, we illustrate how association analyses of unobserved variants will benefit from ongoing advances such as larger HapMap reference panels and whole genome shotgun sequencing technologies.

Rapid haplotype inference for nuclear families

Hapi is a new dynamic programming algorithm that ignores uninformative states and state transitions in order to efficiently compute minimum-recombinant and maximum likelihood haplotypes. When applied to a dataset containing 103 families, Hapi performs 3.8 and 320 times faster than state-of-the-art algorithms. Because Hapi infers both minimum-recombinant and maximum likelihood haplotypes and applies to related individuals, the haplotypes it infers are highly accurate over extended genomic distances.

Identification of a mutation in complement factor H-related protein 5 in patients of Cypriot origin with glomerulonephritis

BACKGROUND

Complement is a key component of the innate immune system, and variation in genes that regulate its activation is associated with renal and other disease. We aimed to establish the genetic basis for a familial disorder of complement regulation associated with persistent microscopic haematuria, recurrent macroscopic haematuria, glomerulonephritis, and progressive renal failure.

METHODS

We sought patients from the West London Renal and Transplant Centre (London, UK) with unusual renal disease and affected family members as a method of identification of new genetic causes of kidney disease. Two families of Cypriot origin were identified in which renal disease was consistent with autosomal dominant transmission and renal biopsy of at least one individual showed C3 glomerulonephritis. A mutation was identified via a genome-wide linkage study and candidate gene analysis. A PCR-based diagnostic test was then developed and used to screen for the mutation in population-based samples and in individuals and families with renal disease.

FINDINGS

Occurrence of familial renal disease cosegregated with the same mutation in the complement factor H-related protein 5 gene (CFHR5). In a cohort of 84 Cypriots with unexplained renal disease, four had mutation in CFHR5. Overall, we identified 26 individuals with the mutation and evidence of renal disease from 11 ostensibly unrelated kindreds, including the original two families. A mutant CFHR5 protein present in patient serum had reduced affinity for surface-bound complement. We term this renal disease CFHR5 nephropathy.

INTERPRETATION

CFHR5 nephropathy accounts for a substantial burden of renal disease in patients of Cypriot origin and can be diagnosed with a specific molecular test. The high risk of progressive renal disease in carriers of the CFHR5 mutation implies that isolated microscopic haematuria or recurrent macroscopic haematuria should not be regarded as a benign finding in individuals of Cypriot descent.

FUNDING

UK Medical Research Council and Wellcome Trust.

Estimating genome-wide IBD sharing from SNP data via an efficient hidden Markov model of LD with application to gene mapping

MOTIVATION

Association analysis is the method of choice for studying complex multifactorial diseases. The premise of this method is that affected persons contain some common genomic regions with similar SNP alleles and such areas will be found in this analysis. An important disadvantage of GWA studies is that it does not distinguish between genomic areas that are inherited from a common ancestor [identical by descent (IBD)] and areas that are identical merely by state [identical by state (IBS)]. Clearly, areas that can be marked with higher probability as IBD and have the same correlation with the disease status of identical areas that are more probably only IBS, are better candidates to be causative, and yet this distinction is not encoded in standard association analysis.

RESULTS

We develop a factorial hidden Markov model-based algorithm for computing genome-wide IBD sharing. The algorithm accepts as input SNP data of measured individuals and estimates the probability of IBD at each locus for every pair of individuals. For two g-degree relatives, when g > or = 8, the computation yields a precision of IBD tagging of over 50% higher than previous methods for 95% recall. Our algorithm uses a first-order Markovian model for the linkage disequilibrium process and employs a reduction of the state space of the inheritance vector from being exponential in g to quadratic. The higher accuracy along with the reduced time complexity marks our method as a feasible means for IBD mapping in practical scenarios.

AVAILABILITY

A software implementation, called IBDMAP, is freely available at http://bioinfo.cs.technion.ac.il/IBDmap.

Supervised machine learning and logistic regression identifies novel epistatic risk factors with PTPN22 for rheumatoid arthritis

Investigating genetic interactions (epistasis) has proven difficult despite the recent advances of both laboratory methods and statistical developments. With no 'best' statistical approach available, combining several analytical methods may be optimal for detecting epistatic interactions. Using a multi-stage analysis that incorporated supervised machine learning and methods of association testing, we investigated epistatic interactions with a well-established genetic factor (PTPN22 1858T) in a complex autoimmune disease (rheumatoid arthritis (RA)). Our analysis consisted of four principal stages: Stage I (data reduction)-identifying candidate chromosomal regions in 292 affected sibling pairs, by predicting PTPN22 concordance using multipoint identity-by-descent probabilities and a supervised machine learning algorithm (Random Forests); Stage II (extension analysis)-testing detailed genetic data within candidate chromosomal regions for epistasis with PTPN22 1858T in 677 cases and 750 controls using logistic regression; Stage III (replication analysis)-confirmation of epistatic interactions in 947 cases and 1756 controls; Stage IV (combined analysis)-a pooled analysis including all 1624 RA cases and 2506 control subjects for final estimates of effect size. A total of seven replicating epistatic interactions were identified. SNP variants within CDH13, MYO3A, CEP72 and near WFDC1 showed significant evidence for interaction with PTPN22, affecting susceptibility to RA.

Mutations in the formin gene INF2 cause focal segmental glomerulosclerosis

Focal segmental glomerulosclerosis (FSGS) is a pattern of kidney injury observed either as an idiopathic finding or as a consequence of underlying systemic conditions. Several genes have been identified which, when mutated, lead to inherited FSGS and/or the nephrotic syndrome. These findings have accelerated the understanding of glomerular podocyte function and disease, motivating our search for additional FSGS genes. Using linkage analysis, we identified a locus for autosomal dominant FSGS on a region of chromosome 14q. By sequencing multiple genes in this region, we detected nine independent non-conservative missense mutations in INF2, which encodes a member of the formin family of actin regulating proteins. These mutations, all within the diaphanous inhibitory domain, segregate with disease in 11 unrelated families and alter highly conserved amino acid residues. The observation that mutations in this podocyte-expressed formin cause FSGS highlights the importance of fine regulation of actin polymerization in podocyte function.

Exclusion of known corneal dystrophy genes in an autosomal dominant pedigree of a unique anterior membrane corneal dystrophy

PURPOSE

With advances in phenotyping tools and availability of molecular characterization, an increasing number of phenotypically and genotypically diverse inherited corneal dystrophies are described. We aimed to determine the underlying causative genetic mechanism in a three-generation pedigree affected with a unique anterior membrane corneal dystrophy characterized by early onset recurrent corneal erosions, small discrete focal opacities at the level of Bowman layer and anterior stroma, anterior stromal flecks, and prominent corneal nerves.

METHODS

Twenty affected and unaffected members of a three-generation family were examined and extensively clinically characterized including corneal topography and in vivo confocal microscopy, and biological specimens were collected for DNA extraction. Mutational analysis of two corneal genes (TGFBI [Transforming Growth factor-beta induced] and ZEB1 [zinc finger E box-binding homeobox 1]) was undertaken, in addition to testing with the Asper Corneal Dystrophy gene chip (Asper Ophthalmics, Tartu, Estonia). Subsequent Genotyping To 11 Known Corneal Gene Loci (COL8A2 [Collagen, Type VIII, Alpha-2], TACSTD2 [Tumor-Associated Calcium Signal Transducer 2], PIP5K3 [Phosphatidylinositol-3-Phosphate 5-Kinase, Type III], GSN [Gelsolin], KERA [Keratocan], VSX1 [Visual System Homeobox Gene 1], COL6A1 [Collagen, Type VI, Alpha-1], MMP9 [Matrix Metalloproteinase 9], KRT3 [Keratin 3]), and two putative loci, 3p14-q13 and 15q22.33-24) was undertaken using polymorphic markers, and haplotypes constructed. Multipoint linkage analysis was performed to generate LOD scores and produce LOD plots across the candidate intervals.

RESULTS

No pathogenic sequence variations were detected in TGFBI or ZEB1 of the proband nor on the Asper Corneal Dystrophy gene chip (302 mutations in 12 genes). Multipoint linkage analysis of 11 known corneal genes and loci generated negative LOD plots and was able to exclude all genes tested including PIP5K3.

CONCLUSIONS

Exclusion of linkage to candidate corneal loci combined with an absence of pathogenic mutations in known corneal genes in this pedigree suggest a different genetic causative mechanism in this dystrophy than the previously documented corneal genes. This unique phenotype of an anterior membrane dystrophy may therefore provide an opportunity to identify a new gene responsible for corneal disease.

Speeding up HMM algorithms for genetic linkage analysis via chain reductions of the state space

We develop an hidden Markov model (HMM)-based algorithm for computing exact parametric and non-parametric linkage scores in larger pedigrees than was possible before. The algorithm is applicable whenever there are chains of persons in the pedigree with no genetic measurements and with unknown affection status. The algorithm is based on shrinking the state space of the HMM considerably using such chains. In a two g-degree cousins pedigree the reduction drops the state space from being exponential in g to being linear in g. For a Finnish family in which two affected children suffer from a rare cold-inducing sweating syndrome, we were able to reduce the state space by more than five orders of magnitude from 2(50) to 2(32). In another pedigree of state-space size of 2(27), used for a study of pituitary adenoma, the state space reduced by a factor of 8.5 and consequently exact linkage scores can now be computed, rather than approximated.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Investigation of parent-of-origin effect in comitant strabismus using MOD score analysis

PURPOSE

Comitant strabismus is a common pediatric ophthalmic disorder with both genetic and non-genetic factors contributing to its etiology. The aim of the current study is to investigate the phenomenon of a parent-of-origin effect, genomic imprinting, as a possible mode of inheritance in comitant strabismus.

METHODS

We performed parametric genome-wide MOD score (model-maximized LOD score) linkage analysis, incorporating imprinting effects, for 382 microsatellite markers in a sample of 258 individuals (117 males and 141 females) from 55 Japanese families with comitant strabismus. We included individuals as affected patients if they presented with comitant esotropia or exotropia based on ophthalmic examination, history taking, or analysis of medical records.

RESULTS

Significant or suggestive linkage to comitant strabismus with evidence of maternal or paternal imprinting was detected at D4S1575 (4q28.3), D7S486 (7q31.2), D11S1320 (11q24.2), D12S324 (12q24.32), and D19S420 (19q13.11). Using the MOD score approach, we found new evidence of linkage to comitant strabismus at three loci on chromosomes 6q26 (MOD(imp)=MOD(reg)=3.75), 12q24.32 (MOD(imp)=3.36), and 19q13.11 (MOD(imp)=3.79).

CONCLUSIONS

The results suggest that the parent-of-origin effect may play a role in the etiology of comitant strabismus.

Genotype imputation

Genotype imputation is now an essential tool in the analysis of genome-wide association scans. This technique allows geneticists to accurately evaluate the evidence for association at genetic markers that are not directly genotyped. Genotype imputation is particularly useful for combining results across studies that rely on different genotyping platforms but also increases the power of individual scans. Here, we review the history and theoretical underpinnings of the technique. To illustrate performance of the approach, we summarize results from several gene mapping studies. Finally, we preview the role of genotype imputation in an era when whole genome resequencing is becoming increasingly common.

Analysis of a large multi-generational family provides insight into the genetics of chronic lymphocytic leukemia

We report the genetic analysis of a large multi-generational family composed of 144 individuals in which 11 members have been diagnosed with chronic lymphocytic leukaemia (CLL). The observation of a significant over-representation of monoclonal B-cell lymphocytosis (MBL) in unaffected family members strongly supports MBL being a surrogate marker of carrier status. A genome-wide linkage scan of the family using high-density 10K single nucleotide polymorphisms provided no significant evidence for a single gene model of disease susceptibility, inviting speculation that susceptibility to CLL has a more complex basis. The absence of a correlation in IGHV usage between affected family members does however argue strongly against exposure to a single super-antigen in disease development.

Searching for epistasis and linkage heterogeneity by correlations of pedigree-specific linkage scores

Recognizing that multiple genes are likely responsible for common complex traits, statistical methods are needed to rapidly screen for either interacting genes or locus heterogeneity in genetic linkage data. To achieve this, some investigators have proposed examining the correlation of pedigree linkage scores between pairs of chromosomal regions, because large positive correlations suggest interacting loci and large negative correlations suggest locus heterogeneity (Cox et al. [1999]; Maclean et al. [1993]). However, the statistical significance of these extreme correlations has been difficult to determine due to the autocorrelation of linkage scores along chromosomes. In this study, we provide novel solutions to this problem by using results from random field theory, combined with simulations to determine the null correlation for syntenic loci. Simulations illustrate that our new methods control the Type-I error rates, so that one can avoid the extremely conservative Bonferroni correction, as well as the extremely time-consuming permutational method to compute P-values for non-syntenic loci. Application of these methods to prostate cancer linkage studies illustrates interpretation of results and provides insights into the impact of marker information content on the resulting statistical correlations, and ultimately the asymptotic P-values.

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.

Fine mapping of familial prostate cancer families narrows the interval for a susceptibility locus on chromosome 22q12.3 to 1.36 Mb

Genetic studies suggest that hereditary prostate cancer is a genetically heterogeneous disease with multiple contributing loci. Studies of high-risk prostate cancer families selected for aggressive disease, analysis of large multigenerational families, and a meta-analysis from the International Consortium for Prostate Cancer Genetics (ICPCG), all highlight chromosome 22q12.3 as a susceptibility locus with strong statistical significance. Recently, two publications have narrowed the 22q12.3 locus to a 2.18 Mb interval using 54 high-risk families from the ICPCG collaboration, as defined by three recombination events on either side of the locus. In this paper, we present the results from fine mapping studies at 22q12.3 using both haplotype and recombination data from 42 high-risk families contributed from the Mayo Clinic and the Prostate Cancer Genetic Research Study (PROGRESS) mapping studies. No clear consensus interval is present when all families are used. However, in the subset of 14 families with >/=5 affected men per family, a 2.53-Mb shared consensus segment that overlaps with the previously published interval is identified. Combining these results with data from the earlier ICPCG study reduces the three-recombination interval at 22q12.3 to approximately 1.36 Mb.

Identification of a chromosome 8p locus for early-onset coronary heart disease in a French Canadian population

Susceptibility to coronary heart disease (CHD) has long been known to exhibit familial aggregation, with heritability estimated to be greater than 50%. The French Canadian population of the Saguenay-Lac Saint-Jean region of Quebec, Canada is descended from a founder population that settled this region 300-400 years ago and this may provide increased power to detect genes contributing to complex traits such as CHD. Probands with early-onset CHD, defined by angiographically determined coronary stenosis, and their relatives were recruited from this population (average sibship size of 6.4). Linkage analysis was performed following a genome-wide microsatellite marker scan on 42 families with 284 individuals. Nonparametric linkage (NPL) analysis provided suggestive evidence for a CHD susceptibility locus on chromosome 8 with an NPL score of 3.14 (P=0.001) at D8S1106. Linkage to this locus was verified by fine mapping in an enlarged sample of 50 families with 320 individuals. This analysis provided evidence of linkage at D8S552 (NPL score=3.53, P=0.0003), a marker that maps to the same location as D8S1106. Candidate genes in this region, including macrophage scavenger receptor 1, farnesyl-diphosphate farnesyltransferase 1, fibrinogen-like 1, and GATA-binding protein 4, were resequenced in all coding exons in both affected and unaffected individuals. Association studies with variants in these and five other genes did not identify a disease-associated mutation. In conclusion, a genome-wide scan and additional fine mapping provide evidence for a locus on chromosome 8 that contributes to CHD in a French Canadian population.

Genome-wide scan of bipolar II disorder

OBJECTIVE

Bipolar disorder (BD) II is characterized by recurrent hypomanic and depressive episodes and has been somewhat of a controversial diagnosis since its description in the 1970s. Clinical opinions notwithstanding, the biological validity of BD II was supported in a genetic study of 58 multiplex bipolar families wherein the statistical evidence for linkage derived from BD II sibling-pairs sharing marker alleles on chromosome 18q. The BD II phenotype alone has never been studied in a genome-wide scan analysis in the current or other bipolar family samples. We have performed genome-wide non-parametric analysis on 74 bipolar pedigrees using only the BD II phenotype as affection model.

METHODS

This sample consists of the 65 pedigrees previously reported and 9 additional novel pedigrees that had BD II exclusively, as the affected phenotype. In the entire sample, there were 146 all possible relative-pairs. Analysis was performed using the non-parametric method in GENEHUNTER, with the 'ALL' option that computes linkage scores in all individuals in a pedigree simultaneously.

RESULTS

The current analyses supported the previous finding on chromosome 18q21. In addition a peak with a non-parametric LOD (NPL) of 2.07 occurred between D9S915 and D9S2157, located on 9q34. Analysis of the nine BD II families alone identified peaks on 9p13 and 9q33, with NPL scores of 3.20 and 2.09, respectively. There was no evidence at 18q21 in these nine families.

CONCLUSIONS

This suggests that there may be substantial differences in the etiology of BD in families that have BD II exclusively as the diagnosis.

A comprehensive screen for SNP associations on chromosome region 5q31–33 in Swedish/Norwegian celiac disease families

Celiac disease (CD) is a gluten-induced enteropathy, which results from the interplay between environmental and genetic factors. There is a strong human leukocyte antigen (HLA) association with the disease, and HLA-DQ alleles represent a major genetic risk factor. In addition to HLA-DQ, non-HLA genes appear to be crucial for CD development. Chromosomal region 5q31-33 has demonstrated linkage with CD in several genome-wide studies, including in our Swedish/Norwegian cohort. In a European meta-analysis 5q31-33 was the only region that reached a genome-wide level of significance except for the HLA region. To identify the genetic variant(s) responsible for this linkage signal, we performed a comprehensive single nucleotide polymorphism (SNP) association screen in 97 Swedish/Norwegian multiplex families who demonstrate linkage to the region. We selected tag SNPs from a 16 Mb region representing the 95% confidence interval of the linkage peak. A total of 1,404 SNPs were used for the association analysis. We identified several regions with SNPs demonstrating moderate single- or multipoint associations. However, the isolated association signals appeared insufficient to account for the linkage signal seen in our cohort. Collective effects of multiple risk genes within the region, incomplete genetic coverage or effects related to copy number variation are possible explanations for our findings.

Suggestive genetic linkage to chromosome 11p11.2-q12.2 in hereditary prostate cancer families with primary kidney cancer

BACKGROUND

The Seattle-based PROGRESS study was started in 1995 to ascertain hereditary prostate cancer (HPC) families for studies of genetic susceptibility. Subsequent studies by several research groups, including our own, suggest that HPC is a genetically heterogeneous disease. To be successful in mapping loci for such a complex disease, one must consider ways of grouping families into subsets that likely share the same genetic origin. Towards that end, we analyzed a genome-wide scan of HPC families with primary kidney cancer.

METHODS

An 8.1 cM genome-wide scan including 441 microsatellite markers was analyzed by both parametric and non-parametric linkage approaches in fifteen HPC families with the co-occurrence of kidney cancer.

RESULTS

There was no evidence for significant linkage in the initial findings. However, two regions of suggestive linkage were observed at 11q12 and 4q21, with HLOD scores of 2.59 and 2.10, respectively. The primary result on chromosome 11 was strengthened after excluding two families with members who had rare transitional cell carcinoma (TCC). Specifically, we observed a non-parametric Kong and Cox P-value of 0.004 for marker D11S1290 at 11p11.2. The 8 cM region between 11p11.2 and 11q12.2 was refined by the addition of 16 new markers. The subset of HPC families with a median age of diagnosis >65 years demonstrated the strongest evidence for linkage, with an HLOD = 2.50. The P-values associated with non-parametric analysis ranged from 0.004 to 0.05 across five contiguous markers.

CONCLUSIONS

Analysis of HPC families with members diagnosed with primary renal cell carcinoma demonstrates suggestive linkage to chromosome 11p11.2-q12.2.

MCMC-based linkage analysis for complex traits on general pedigrees: multipoint analysis with a two-locus model and a polygenic component

We describe a new program lm_twoqtl, part of the MORGAN package, for parametric linkage analysis with a quantitative trait locus (QTL) model having one or two QTLs and a polygenic component, which models additional familial correlation from other unlinked QTLs. The program has no restriction on number of markers or complexity of pedigrees, facilitating use of more complex models with general pedigrees. This is the first available program that can handle a model with both two QTLs and a polygenic component. Competing programs use only simpler models: one QTL, one QTL plus a polygenic component, or variance components (VC). Use of simple models when they are incorrect, as for complex traits that are influenced by multiple genes, can bias estimates of QTL location or reduce power to detect linkage. We compute the likelihood with Markov Chain Monte Carlo (MCMC) realization of segregation indicators at the hypothesized QTL locations conditional on marker data, summation over phased multilocus genotypes of founders, and peeling of the polygenic component. Simulated examples, with various sized pedigrees, show that two-QTL analysis correctly identifies the location of both QTLs, even when they are closely linked, whereas other analyses, including the VC approach, fail to identify the location of QTLs with modest contribution. Our examples illustrate the advantage of parametric linkage analysis with two QTLs, which provides higher power for linkage detection and better localization than use of simpler models.

Forward-time simulations of human populations with complex diseases

Due to the increasing power of personal computers, as well as the availability of flexible forward-time simulation programs like simuPOP, it is now possible to simulate the evolution of complex human diseases using a forward-time approach. This approach is potentially more powerful than the coalescent approach since it allows simulations of more than one disease susceptibility locus using almost arbitrary genetic and demographic models. However, the application of such simulations has been deterred by the lack of a suitable simulation framework. For example, it is not clear when and how to introduce disease mutants—especially those under purifying selection—to an evolving population, and how to control the disease allele frequencies at the last generation. In this paper, we introduce a forward-time simulation framework that allows us to generate large multi-generation populations with complex diseases caused by unlinked disease susceptibility loci, according to specified demographic and evolutionary properties. Unrelated individuals, small or large pedigrees can be drawn from the resulting population and provide samples for a wide range of study designs and ascertainment methods. We demonstrate our simulation framework using three examples that map genes associated with affection status, a quantitative trait, and the age of onset of a hypothetical cancer, respectively. Nonadditive fitness models, population structure, and gene–gene interactions are simulated. Case-control, sibpair, and large pedigree samples are drawn from the simulated populations and are examined by a variety of gene-mapping methods.

Complex diseases such as hypertension and diabetes are usually caused by multiple disease-susceptibility genes, environment factors, and interactions between them. Simulating populations or samples with complex diseases is an effective approach to study the likely genetic architecture of these diseases and to develop more effective gene-mapping methods. Compared to traditional backward-time (coalescent) methods, population-based, forward-time simulations are more suitable for this task because they can simulate almost arbitrary demographic and genetic features. Forward-time simulations also allow the researcher to perform head-to-head comparisons among gene-mapping methods based on different study designs and ascertainment methods. Unfortunately, evolving a population generation by generation is a random process, so the fates of disease alleles are unpredictable and there is no effective way to control the disease allele frequency at the present generation. In this paper, the authors propose a simulation method that avoids these problems and makes forward-time population simulation a practical solution for the simulation of complex diseases.

Functional P2X7Receptor Polymorphisms (His155Tyr, Arg307Gln, Glu496Ala) in Patients with Crohn's Disease

Genetic factors contribute to inflammatory bowel diseases. Recently, the P2X(7) receptor was found to be a key player in caspase-1-mediated processing of the proinflammatory cytokines, interleukin-1beta and interleukin-18. We therefore aimed to determine whether the gain-of-function single nucleotide polymorphism (SNP) His155Tyr and the loss-of-function SNP Arg307Gln and Glu496Ala were associated with susceptibility to Crohn's disease (CD). For association analysis, 681 unrelated CD patients and 736 healthy controls were enrolled. Furthermore, 490 CD trios were included for segregation analysis. Genotyping was performed by the application of the TaqMan(R) MGB biallelic discrimination system. The Arg307Gln polymorphism revealed a borderline significant difference in genotype frequencies between CD patients and controls (P = 0.06) without implying any pathological significance because of low case numbers. Case-control statistics for the variants His155Tyr and Glu496Ala showed no association with CD phenotype (P = 0.19 and 0.99). Subsequent family-based transmission disequilibrium test did not prove an association of the investigated single-nucleotide polymorphisms with CD. In conclusion, the analysed intragenetic variants of the P2X(7) receptor may not be a susceptibility factor for CD.

Finding cardiovascular disease genes in the dog

Recent advances in canine genomics are changing the landscape of veterinary biology, and by default, veterinary medicine. No longer are clinicians locked into traditional methods of diagnoses and therapy. Rather, major advances in canine genetics and genomics from the past five years are now changing the way the veterinarian of the 21st century practices medicine. First, the availability of a dense genome map gives canine genetics a much-needed foothold in comparative medicine, allowing advances made in human and mouse genetics to be applied to companion animals. Second, the recently released 7.5x whole genome sequence of the dog is facilitating the identification of hereditary disease genes. Finally, development of genetic tools for rapid screening of families and populations at risk for inherited disease means that the cost of identifying and testing for disease loci will significantly decrease in coming years. Out of these advances will come major changes in companion animal diagnostics and therapy. Clinicians will be able to offer their clients genetic testing and counseling for a myriad of disorders. In this review we summarize recent findings in canine genomics and discuss their application to the study of canine cardiac health.

Linkage analysis using sex-specific recombination fractions with GENEHUNTER-MODSCORE

MOTIVATION

Sex-specific marker maps have become increasingly available. We have implemented the usage of sex-specific recombination frequencies in the GENEHUNTER-MODSCORE program that performs multipoint linkage analysis. Furthermore, we have devised a consistent method to choose the combinations of male and female genetic positions at which linkage scores should be calculated. Marker coordinates can be read automatically from publicly available genetic maps.

RESULTS

In a MOD-score analysis of the COGA dataset provided for Genetic Analysis Workshop 14, the highest linkage peak on chromosome 1 further increases when using sex-specific maps, while some smaller peaks are decreased. Simulations confirm that the MOD score can be biased when a sex-averaged instead of the correct sex-specific map is employed. This shows that an adequate modeling of the female:male ratio of genetic distances is important, especially for complex traits.

AVAILABILITY

The new version of GENEHUNTER-MODSCORE can be downloaded from the following website: http://www.staff.uni-marburg.de/~strauchk/software.html

Linkage analysis of rheumatoid arthritis in US and UK families reveals interactions between HLA-DRB1 and loci on chromosomes 6q and 16p

OBJECTIVE

HLA is the most strongly associated locus in rheumatoid arthritis (RA), accounting for up to one-third of the genetic contribution. Conditioning on the effect of true disease loci such as HLA can lead to increased power to detect effects at other loci and, in addition, allows investigation of the underlying disease models, including interactions. The aim of this study was to detect susceptibility loci for RA by conditioning on HLA in a large sample of affected sibling pairs (ASPs) and to test for evidence of interaction between novel loci and HLA.

METHODS

Genotype data from 3 whole-genome linkage scans for RA in a US population and a UK population were pooled, resulting in a combined data set of 886 ASPs. This pooling of data increased the power to detect loci showing low levels of heterogeneity. Nonparametric linkage analysis was performed to identify regions of interest. Joint 2-locus analysis was then performed for HLA and each of the loci that demonstrated evidence of linkage in the 886 ASPs.

RESULTS

Evidence for linkage was most significant at HLA (P = 4 x 10(-16)), with 7 non-HLA loci showing some evidence for linkage (P = 0.05-0.003). Joint modeling of these loci with HLA provided evidence for linkage at a genome-wide significance level for loci on 6q (P = 2.7 x 10(-6)) and 16p (P = 2 x 10(-4)).

CONCLUSION

These data provide the most convincing evidence to date that 6q and 16p harbor susceptibility genes. In addition, these loci may interact with HLA, facilitating the search for candidate genes within this region.

Online system for faster multipoint linkage analysis via parallel execution on thousands of personal computers

Computation of LOD scores is a valuable tool for mapping disease-susceptibility genes in the study of Mendelian and complex diseases. However, computation of exact multipoint likelihoods of large inbred pedigrees with extensive missing data is often beyond the capabilities of a single computer. We present a distributed system called "SUPERLINK-ONLINE," for the computation of multipoint LOD scores of large inbred pedigrees. It achieves high performance via the efficient parallelization of the algorithms in SUPERLINK, a state-of-the-art serial program for these tasks, and through the use of the idle cycles of thousands of personal computers. The main algorithmic challenge has been to efficiently split a large task for distributed execution in a highly dynamic, nondedicated running environment. Notably, the system is available online, which allows computationally intensive analyses to be performed with no need for either the installation of software or the maintenance of a complicated distributed environment. As the system was being developed, it was extensively tested by collaborating medical centers worldwide on a variety of real data sets, some of which are presented in this article.

Identification of genetic loci for basal cell nevus syndrome and inflammatory bowel disease in a single large pedigree

Basal Cell Nevus Syndrome (BCNS) is an autosomal dominant disease. PTCH1 gene mutations have been found responsible in many but not all pedigrees. Inflammatory Bowel Disease (IBD) is a complex genetic disorder, disproportionate in Ashkenazim, and characterized by chronic intestinal inflammation. We revisited a large Ashkenazim pedigree, first reported in 1968, with multiple diagnoses of BCNS and IBD, and with a common genetic cause for both disorders proposed. We expanded the pedigree to four generations and performed a genome-wide linkage study for BCNS and IBD traits. Twelve members with BCNS, seven with IBD, five with both diagnoses and eight unaffected were genotyped. Both non-parametric (GENEHUNTER 2.1) and parametric (FASTLINK) linkage analyses were performed and a validation through simulation was performed. BCNS linked to chromosome 9q22 (D9S1120) just proximal to the PTCH1 gene (NPL=3.26, P=0.003; parametric two-point LOD=2.4, parametric multipoint LOD=3.7). Novel IBD linkage evidence was observed at chromosome 1p13 (D1S420, NPL 3.92, P=0.0047; parametric two-point LOD=1.9). Linkage evidence was also observed to previously reported IBD loci on 4q, (D4S2623, NPL 3.02, P=0.012; parametric two-point LOD=2.15), 10q23 (D10S1225 near DLG5, NPL 3.33, P=0.0085; parametric two-point LOD=1.3), 12 overlapping the IBD2 locus (D12S313, NPL 2.6, P=0.018; parametric two-point LOD=1.52), and 7q (D7S510 and D7S3046, NPL 4.06, P=0.0035; parametric two-point LOD=2.18). In this pedigree affected by both BCNS and IBD, the two traits and their respective candidate genetic loci segregate independently; BCNS maps to the PTCH1 gene and IBD maps to several candidate regions, mostly overlapping previously observed IBD loci.

Genome-wide meta-analysis for rheumatoid arthritis

Meta-analysis is being increasingly used as a tool for integrating data from different studies of complex phenotypes, because the power of any one study to identify causal loci is limited. We applied a novel meta-analytical approach (Loesgen et al. in Genet Epidemiol 21(Suppl 1):S142-S147, 2001) in compiling results from four studies of rheumatoid arthritis in Caucasians including two studies from NARAC (Jawaheer et al. in Am J Hum Genet 68:927-936, 2001; Jawaheer et al. in Arthritis Rheum 48:906-916, 2003), one study from the UK (MacKay et al. in Arthritis Rheum 46:632-639, 2001) and one from France (Cornelis et al. in Proc Natl Acad Sci USA 95:10746-10750, 1998). For each study, we obtained NPL scores by performing interval mapping (2 cM intervals) using GeneHunter2 (Kruglyak et al. in Am J Hum Genet 58:1347-1363, 1996; Markianos et al. in Am J Hum Genet 68:963-977, 2001). The marker maps differed among the three consortium groups, therefore, the marker maps were aligned after the interval mapping was completed and the NPL scores that were within 1 cM of each other were combined using the method of Loesgen et al. (Genet Epidemiol 21(Suppl 1):S142-S147, 2001) by calculating the weighted average of the NPL score. This approach avoids some problems in analysis encountered by using GeneHunter2 when some markers in the sample are not genotyped. This procedure provided marginal evidence (P<0.05) of linkage on chromosome 1, 2, 5 and 18, strong evidence (P<0.01) on chromosomes 8 and 16, and overwhelming evidence in the HLA region of chromosome 6.

Quantitative trait loci controlling refractoriness to Plasmodium falciparum in natural Anopheles gambiae mosquitoes from a malaria-endemic region in western Kenya

Natural anopheline populations exhibit much variation in ability to support malaria parasite development, but the genetic mechanisms underlying this variation are not clear. Previous studies in Mali, West Africa, identified two quantitative trait loci (QTL) in Anopheles gambiae mosquitoes that confer refractoriness (failure of oocyst development in mosquito midguts) to natural Plasmodium falciparum parasites. We hypothesize that new QTL may be involved in mosquito refractoriness to malaria parasites and that the frequency of natural refractoriness genotypes may be higher in the basin region of Lake Victoria, East Africa, where malaria transmission intensity and parasite genetic diversity are among the highest in the world. Using field-derived F2 isofemale families and microsatellite marker genotyping, two loci significantly affecting oocyst density were identified: one on chromosome 2 between markers AG2H135 and AG2H603 and the second on chromosome 3 near marker AG3H93. The first locus was detected in three of the five isofemale families studied and colocalized to the same region as Pen3 and pfin1 described in other studies. The second locus was detected in two of the five isofemale families, and it appears to be a new QTL. QTL on chromosome 2 showed significant additive effects while those on chromosome 3 exhibited significant dominant effects. Identification of P. falciparum-refractoriness QTL in natural An. gambiae mosquitoes is critical to the identification of the genes involved in malaria parasite transmission in nature and for understanding the coevolution between malaria parasites and mosquito vectors.

The most common mutation in FKRP causing limb girdle muscular dystrophy type 2I (LGMD2I) may have occurred only once and is present in Hutterites and other populations

Limb girdle muscular dystrophy (LGMD) is common in the Hutterite population of North America. We previously identified a mutation in the TRIM32 gene in chromosome region 9q32, causing LGMD2H in approximately two-thirds of the 60 Hutterite LGMD patients studied to date. A genomewide scan was undertaken in five families who did not show linkage to the LGMD2H locus on chromosome 9. A second LGMD locus, LGMD2I, was identified in chromosome region 19q13.3, and the causative mutation was identified as c.826C>A (L276I), a missense mutation in the FKRP gene. A comparison of the clinical characteristics of the two LGMD patient groups in this population reveals some differences. LGMD2I patients generally have an earlier age at diagnosis, a more severe course, and higher serum creatine kinase (CK) levels. In addition, some of these patients show calf hypertrophy, cardiac symptoms, and severe reactions to general anesthesia. None of these features are present among LGMD2H patients. A single common haplotype surrounding the FKRP gene was identified in the Hutterite LGMD2I patients. An identical core haplotype was also identified in 19 other non-Hutterite LGMD2I patients from Europe, Canada, and Brazil. The occurrence of this mutation on a common core haplotype suggests that L276I is a founder mutation that is dispersed among populations of European origin.

Prostate cancer and genetic susceptibility: a genome scan incorporating disease aggressiveness

BACKGROUND

Prostate cancer is a heterogeneous disease, both genetically and phenotypically. Linkage studies attempting to map genes for hereditary prostate cancer (HPC) have proved challenging, and one potential problem contributing to this challenge is the variability in disease phenotypes.

METHODS

We collected clinical data on 784 affected men with prostate cancer from 248 HPC families for whom a genomic screen was performed. Disease characteristics (i.e., Gleason score, stage, prostate-specific antigen (PSA)) were used to classify affected men into categories of clinically insignificant, moderate, or aggressive prostate cancer. To potentially enrich for a genetic etiology, we restricted linkage analyses to only men with aggressive disease, although we used genotype information from all family members; linkage analyses used both dominant and recessive models. In addition, subset analyses considered age at diagnosis, number of affected men per family and other stratifications to try to increase genetic homogeneity.

RESULTS

Several regions of interest (heterogeneity LOD score, HLOD>1.0) were identified in families (n=123) with >or=2 affecteds with aggressive prostate cancer. "Suggestive" linkage was observed at chromosome 22q11.1 (Dominant model HLOD=2.18) and the result was stronger (Dominant HLOD=2.75) in families with evidence of male-to-male transmission. A second region at 22q12.3-q13.1 was also highlighted (Recessive model HLOD=1.90) among men with aggressive disease, as was a region on chromosome 18.

CONCLUSIONS

These analyses suggest that using clinically defined phenotypes may be a useful approach for simplifying the locus heterogeneity problems that confound the search for prostate cancer susceptibility genes.

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.

An updated meta-analysis approach for genetic linkage

We present a meta-analysis procedure for genome-wide linkage studies (MAGS). The MAGS procedure combines genome-wide linkage results across studies with possibly distinct marker maps. We applied the MAGS procedure to the simulated data from the Genetic Analysis Workshop 14 in order to investigate power to detect linkage to disease genes and power to detect linkage to disease modifier genes while controlling for type I error. We analyzed all 100 replicates of the four simulated studies for chromosomes 1 (disease gene), 2 (modifier gene), 3 (disease gene), 4 (no disease gene), 5 (disease gene), and 10 (modifier gene) with knowledge of the simulated disease gene locations. We found that the procedure correctly identified the disease loci on chromosomes 1, 3, and 5 and did not erroneously identify a linkage signal on chromosome 4. The MAGS procedure provided little to no evidence of linkage to the disease modifier genes on chromosomes 2 and 10.