A candidate prostate cancer susceptibility gene at chromosome 17p.

It is difficult to identify genes that predispose to prostate cancer due to late age at diagnosis, presence of phenocopies within high-risk pedigrees and genetic complexity. A genome-wide scan of large, high-risk pedigrees from Utah has provided evidence for linkage to a locus on chromosome 17p. We carried out positional cloning and mutation screening within the refined interval, identifying a gene, ELAC2, harboring mutations (including a frameshift and a nonconservative missense change) that segregate with prostate cancer in two pedigrees. In addition, two common missense variants in the gene are associated with the occurrence of prostate cancer. ELAC2 is a member of an uncharacterized gene family predicted to encode a metal-dependent hydrolase domain that is conserved among eukaryotes, archaebacteria and eubacteria. The gene product bears amino acid sequence similarity to two better understood protein families, namely the PSO2 (SNM1) DNA interstrand crosslink repair proteins and the 73-kD subunit of mRNA 3' end cleavage and polyadenylation specificity factor (CPSF73).

The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity.

We present the "sumLINK" statistic--the sum of multipoint LOD scores for the subset of pedigrees with nominally significant linkage evidence at a given locus--as an alternative to common methods to identify susceptibility loci in the presence of heterogeneity. We also suggest the "sumLOD" statistic (the sum of positive multipoint LOD scores) as a companion to the sumLINK. sumLINK analysis identifies genetic regions of extreme consistency across pedigrees without regard to negative evidence from unlinked or uninformative pedigrees. Significance is determined by an innovative permutation procedure based on genome shuffling that randomizes linkage information across pedigrees. This procedure for generating the empirical null distribution may be useful for other linkage-based statistics as well. Using 500 genome-wide analyses of simulated null data, we show that the genome shuffling procedure results in the correct type 1 error rates for both the sumLINK and sumLOD. The power of the statistics was tested using 100 sets of simulated genome-wide data from the alternative hypothesis from GAW13. Finally, we illustrate the statistics in an analysis of 190 aggressive prostate cancer pedigrees from the International Consortium for Prostate Cancer Genetics, where we identified a new susceptibility locus. We propose that the sumLINK and sumLOD are ideal for collaborative projects and meta-analyses, as they do not require any sharing of identifiable data between contributing institutions. Further, loci identified with the sumLINK have good potential for gene localization via statistical recombinant mapping, as, by definition, several linked pedigrees contribute to each peak.

Identifying rarer genetic variants for common complex diseases: diseased versus neutral discovery panels.

The power of genetic association studies to identify disease susceptibility alleles fundamentally relies on the variants studied. The standard approach is to determine a set of tagging-SNPs (tSNPs) that capture the majority of genomic variation in regions of interest by exploiting local correlation structures. Typically, tSNPs are selected from neutral discovery panels - collections of individuals comprehensively genotyped across a region. We investigated the implications of discovery panel design on tSNP performance in association studies using realistically-simulated sequence data. We found that discovery panels of 24 sequenced 'neutral' individuals (similar to NIEHS or HapMap ENCODE data) were sufficient to select well-powered tSNPs to identify common susceptibility alleles. For less common alleles (0.01-0.05 frequency) we found neutral panels of this size inadequate, particularly if low-frequency variants were removed prior to tSNP selection; superior tSNPs were found using panels of diseased individuals. Only large neutral panels (200 individuals) matched diseased panel performance in selecting well-powered tSNPs to detect both common and rarer alleles. The 1000 Genomes Project initiative may provide larger neutral panels necessary to identify rarer susceptibility alleles in association studies. In the interim, our results suggest investigators can boost power to detect such alleles by sequencing diseased individuals for tSNP selection.

Identifying rare variants for genetic risk through a combined pedigree and phenotype approach: application to suicide and asthma.

Suicidal behavior is a complex disorder, with evidence for genetic risk independent of other genetic risk factors including psychiatric disorders. Since 1996, over 3000 DNA samples from Utah suicide decedents have been collected and banked for research use through the Utah Medical Examiner. In addition, over 12,000 Utah suicides were identified through examination of death certificates back to 1904. By linking this data with the Utah Population Database, we have identified multiple extended pedigrees with increased risk for suicide completion. A number of medical conditions co-occur with suicide, including asthma, and this study was undertaken to identify genetic risk common to asthma and suicide. This study tests the hypothesis that a particular comorbid condition may identify a more homogeneous genetic subgroup, facilitating the identification of specific genetic risk factors in that group. From pedigrees at increased risk for suicide, we identified three pedigrees also at significantly increased familial risk for asthma. Five suicide decedents from each of these pedigrees, plus an additional three decedents not from these pedigrees with diagnosed asthma, and 10 decedents with close relatives with asthma were genotyped. Results were compared with 183 publicly available unaffected control exomes from 1000 Genomes and CEPH (Centre d'etude du polymorphisme humain) samples genotyped on the same platform. A further 432 suicide decedents were also genotyped as non-asthma suicide controls. Genotyping was done using the Infinium HumanExome BeadChip. For analysis, we used the pedigree extension of Variant Annotation, Analysis and Search Tool (pVAAST) to calculate the disease burden of each gene. The Phenotype Driven Variant Ontological Re-ranking tool (Phevor) then re-ranked our pVAAST results in context of the phenotype. Using asthma as a seed phenotype, Phevor traversed biomedical ontologies and identified genes with similar biological properties to those known to result in asthma. Our top associated genes included those related to neurodevelopment or neural signaling (brain-derived neurotrophic factor (BDNF), neutral sphingomyelinase 2 (SMPD2), homeobox b2 (HOXB2), neural cell adhesion molecule (NCAM2), heterogeneous nuclear ribonucleoprotein A0 (HNRNPA0)), inflammation (free fatty acid receptor 2 (FFAR2)) and inflammation with additional evidence of neuronal involvement (oxidized low density lipoprotein receptor 1 (OLR1), toll-like receptor 3 (TLR3)). Of particular interest, BDNF has been previously implicated in both psychiatric disorders and asthma. Our results demonstrate the utility of combining pedigree and co-occurring phenotypes to identify rare variants associated with suicide risk in conjunction with specific co-occurring conditions.

Genetic risk factors in two Utah pedigrees at high risk for suicide.

We have used unique population-based data resources to identify 22 high-risk extended pedigrees that show clustering of suicide over twice that expected from demographically adjusted incidence rates. In this initial study of genetic risk factors, we focused on two high-risk pedigrees. In the first of these (pedigree 12), 10/19 (53%) of the related suicides were female, and the average age at death was 30.95. In the second (pedigree 5), 7/51 (14%) of the suicides were female and the average age at death was 36.90. Six decedents in pedigree 12 and nine in pedigree 5 were genotyped with the Illumina HumanExome BeadChip. Genotypes were analyzed using the Variant Annotation, Analysis, and Search program package that computes likelihoods of risk variants using the functional impact of the DNA variation, aggregative scoring of multiple variants across each gene and pedigree structure. We prioritized variants that were: (1) shared across pedigree members, (2) rare in other Utah suicides not related to these pedigrees, (3) < or = 5% in genotyping data from 398 other Utah population controls and (4) < or = 5% frequency in publicly available sequence data from 1358 controls and/or in dbSNP. Results included several membrane protein genes (ANO5, and TMEM141 for pedigree 12 and FAM38A and HRCT1 for pedigree 5). Other genes with known neuronal involvement and/or previous associations with psychiatric conditions were also identified, including NFKB1, CASP9, PLXNB1 and PDE11A in pedigree 12, and THOC1, and AUTS2 in pedigree 5. Although the study is limited to variants included on the HumanExome BeadChip, these findings warrant further exploration, and demonstrate the utility of this high-risk pedigree resource to identify potential genes or gene pathways for future development of targeted interventions.

Immunophenotypic and gene expression analysis of monoclonal B-cell lymphocytosis shows biologic characteristics associated with good prognosis CLL.

Monoclonal B-cell lymphocytosis (MBL) is a hematologic condition wherein small B-cell clones can be detected in the blood of asymptomatic individuals. Most MBL have an immunophenotype similar to chronic lymphocytic leukemia (CLL), and 'CLL-like' MBL is a precursor to CLL. We used flow cytometry to identify MBL from unaffected members of CLL kindreds. We identified 101 MBL cases from 622 study subjects; of these, 82 individuals with MBL were further characterized. In all, 91 unique MBL clones were detected: 73 CLL-like MBL (CD5(+)CD20(dim)sIg(dim)), 11 atypical MBL (CD5(+)CD20(+)sIg(+)) and 7 CD5(neg) MBL (CD5(neg)CD20(+)sIg(neg)). Extended immunophenotypic characterization of these MBL subtypes was performed, and significant differences in cell surface expression of CD23, CD49d, CD79b and FMC-7 were observed among the groups. Markers of risk in CLL such as CD38, ZAP70 and CD49d were infrequently expressed in CLL-like MBL, but were expressed in the majority of atypical MBL. Interphase cytogenetics was performed in 35 MBL cases, and del 13q14 was most common (22/30 CLL-like MBL cases). Gene expression analysis using oligonucleotide arrays was performed on seven CLL-like MBL, and showed activation of B-cell receptor associated pathways. Our findings underscore the diversity of MBL subtypes and further clarify the relationship between MBL and other lymphoproliferative disorders.

Shared genomic segment analysis. Mapping disease predisposition genes in extended pedigrees using SNP genotype assays.

We examine the utility of high density genotype assays for predisposition gene localization using extended pedigrees. Results for the distribution of the number and length of genomic segments shared identical by descent among relatives previously derived in the context of genomic mismatch scanning are reviewed in the context of dense single nucleotide polymorphism maps. We use long runs of loci at which cases share a common allele identically by state to localize hypothesized predisposition genes. The distribution of such runs under the hypothesis of no genetic effect is evaluated by simulation. Methods are illustrated by analysis of an extended prostate cancer pedigree previously reported to show significant linkage to chromosome 1p23. Our analysis establishes that runs of simple single locus statistics can be powerful, tractable and robust for finding DNA shared between relatives, and that extended pedigrees offer powerful designs for gene detection based on these statistics.

Genome-wide linkage analysis for aggressive prostate cancer in Utah high-risk pedigrees.

BACKGROUND: It has been proposed that studying alternative phenotypes, such as tumor aggressiveness, may be a solution for overcoming the apparent heterogeneity that has hindered the identification of prostate cancer (PC) genes. We present the results of a genome-scan for predisposition to aggressive PC using the Utah high-risk pedigree resource. METHODS: We identified 259 subjects with aggressive PC in 57 extended and nuclear families. Parametric and non-parametric multipoint linkage statistics were calculated for a genome-wide set of 401 microsatellite markers using the MCLINK software package. Stratification analyses by the number of affected subjects per pedigree (<5, >or=5) and the average age at diagnosis of affected subjects (<70 years, >or=70 years) were also performed. RESULTS: No significant results were observed at the genome-wide level, but suggestive evidence for linkage was observed on chromosomes 9q (HLOD = 2.04) and 14q (HLOD = 2.08); several pedigrees showed individual evidence for linkage at each locus (LOD > 0.58). The subset of pedigrees with earlier age at onset demonstrated nominal linkage evidence on chromosomes 3q (HLOD = 1.79), 8q (HLOD = 1.67), and 20q (HLOD=1.82). The late-onset subset showed suggestive linkage on chromosome 6p (HLOD = 2.37) and the subset of pedigrees with fewer than five affected subjects showed suggestive linkage on chromosome 10p (HLOD = 1.99). CONCLUSIONS: Linkage evidence observed on chromosomes 6p, 8q, and 20q support previously reported PC aggressiveness loci. While these results are encouraging, further research is necessary to identify the gene or genes responsible for PC aggressiveness and surmount the overarching problem of PC heterogeneity.

Identification and study of Utah pseudo-isolate populations-prospects for gene identification.

Isolate populations of varied types have proven powerful for gene identification for rare Mendelian disorders, and continue to show such promise for more complex phenotypes. Existing isolate populations are limited in the phenotypes available for study, and new population isolates are unlikely to arise. We utilize genealogical data available for the state of Utah, dating back to its European founders, to retrospectively define and examine pseudo-isolate subpopulations. These pseudo-isolate populations are defined by selection of a set of "founders" from the genealogical data, and then limitation of "immigration" by censoring of matings and offspring that do not match the isolate population design. A wide variety of pseudo isolate and other study designs are possible by varying the number and type of founders and the extent of immigration allowed. We present several different example Birth-Country pseudo-isolate populations defined within the Utah Population Database (UPDB). We utilize linked cancer phenotype data available for the Utah population to show the utility of this pseudo-isolate approach for identification of more genetically homogeneous prostate cancer pedigrees for predisposition gene identification. In conclusion, we present a unique approach to retrospective "creation" of isolate populations using existing genealogical data. We use the UPDB to exhibit the utility of this approach for the highly heterogeneous Utah population, and suggest the approach is feasible for any population for which high quality genealogy and phenotype data are available.

Evidence of a pharmacogenomic response to interleukin-l receptor antagonist in rheumatoid arthritis.

Biological activity of the IL-1 system depends on the balance between two proinflammatory proteins (IL-1alpha and IL-1beta) and the related anti-inflammatory protein, the IL-1 receptor antagonist (IL-1Ra). The genes for these proteins lie within 430 kb on human chromosome 2. Based on a clinical trial of human recombinant IL-1ra in rheumatoid arthritis, we tested whether IL-1 genotype might be related to the likelihood of response to anti-IL-1 therapy. A positive response was defined as a reduction of at least 50% in the number of swollen joints by week 24, following treatment with either 150 mg/day IL-1ra or placebo. The response rate to treatment, independent of genotype, was 48% (44/91). A highly significant association was found between carriage of the rarer allele at IL1A(+4845) and response to treatment (P=0.0009; OR=4.85 (1.85,12.70)). The response rate in patients carrying this allele was 63.4% compared with 26.3% in noncarriers. A weaker association was found for IL1B(+3954) (P=0.02). There was a highly significant interaction between treatment (150 mg/day or placebo) and the composite genotype across IL1A(+4845) and IL1B(+3954) (P=7.6 x 10(-5)). No associations with IL-1 genotypes were found in patients receiving placebo. Thus, a significant pharmacogenomic effect was found in the treatment of RA patients with recombinant IL-1ra.

Generating genetic risk scores from intermediate phenotypes for use in association studies of clinically significant endpoints.

While previous results of genetic association studies for common, complex diseases (eg., coronary artery disease, CAD) have been disappointing, examination of multiple related genes within a physiologic pathway may provide improved resolution. This paper describes a method of calculating a genetic risk score (GRS) for a clinical endpoint by integrating data from many candidate genes and multiple intermediate phenotypes (IPs). First, the association of all single nucleotide polymorphisms (SNPs) to an IP is determined and regression beta-coefficients are used to calculate an IP-specific GRS for each individual, repeating this analysis for every IP. Next, the IPs are assessed by a second regression as predictors of the clinical endpoint. Each IP's individual GRS is then weighted by the regression beta-coefficients from the second step, creating a single, composite GRS. As an example, 3,172 patients undergoing coronary angiography were evaluated for 3 SNPs from the cholesterol metabolism pathway. Although these data provide only a preliminary example, the GRS method detected significant differences in CAD by GRS group, whereas separate genotypes did not. These results illustrate the potential of the GRS methodology for multigenic risk evaluation and suggest that such approaches deserve further examination in common, complex diseases such as CAD.

Genomewide transmission/disequilibrium testing--consideration of the genotypic relative risks at disease loci.

Genomewide association studies are set to become the tool of the future for detection of small-effect genes in complex diseases. It will therefore be necessary to calculate sufficient sample sizes with which to perform them. In this paper I illustrate how to calculate the required number of families for general genotypic relative risks (GRRs). I show the superior sensitivity of the genomewide association study over the standard genomewide affected-sib-pair linkage analysis, for a range of different underlying GRR patterns. I also illustrate the extent of change in the sample sizes that is necessary for a genomewide association analysis depending on the pattern of the GRRs at the disease locus. In many cases, the comparative numbers of families required under different genetic mechanisms vary by several orders of magnitude. These sometimes dramatic differences have important implications for the determination of the size of the collection of samples prior to analysis and for the types of effects that are likely--and unlikely--to be detected by such an analysis.

A low density genome-wide search for loci involved in alcohol dependence using the transmission/disequilibrium test, sib-TDT, and two combined tests.

The transmission/disequilibrium test (TDT), sib-TDT and two combined tests have been implemented in an attempt to identify loci across the genome that may be involved in alcohol dependence. Since these tests are based on the existence of association between marker and disease loci, the low-density map used (13 cM) will have missed any disease loci situated between markers. Nevertheless, genome-wide suggestive linkage results were found at three markers--D6S474, D8S1715, and D12S372--two of which also gave nominally significant evidence by two-point linkage analysis. These are regions that deserve further investigation with respect to their involvement in alcohol dependence, and in order to evaluate the relative efficacy of the different methods used.

The effect of selective sampling on mapping quantitative trait loci.

Sib pairs were selectively sampled for extreme concordance or discordance for the quantitative trait Q1, a simulated phenotype (GAW10). Two selective sampling criteria were used (SC1 and SC2), and results for these were compared to linkage analyses using all pairs (ALL). In total 773 sib pairs were available, which reduced to an average of 59.7 pairs under SC1, and 134.1 pairs under SC2. Whole genome screens were performed on 10 different data replicates for each selection criterion (ALL, SC1, and SC2). Fine screens were then performed over regions which indicated at least suggestive linkage, and these regions were also fine screened in an independent data replicate in an attempt to repeat any areas found. The results for the coarse genome screens were similar under each of the criteria, although in general lower maxima and slightly more erratic lods were found under the stricter selection methods. The correct region on chromosome 5 (responsible for approximately 22% of the variance of Q1) was detected (p < 0.0001) in 6/10 of the data replicates using ALL, and 4/10 using SC1 and SC2. The second quantitative trait locus (QTL) on chromosome 8 (only 0.5% of the variance of Q1) was detected in only a single data replicate using SC1. False positive rates were similar for each criterion, whereas power decreased using selective sampling compared to ALL, although this was probably due to an insufficient initial sample size.

Correcting for multiple analyses in genomewide linkage studies.

The dissection of complex traits frequently calls for multiple analyses to be performed, including the use of both multiple phenotypes and genetic models. These multiple phenotypes and models are often not independent, and hence the necessary correction for the multiple testing is not straightforward. In this paper we offer a new approach to address the problem of how to correct for non-independent multiple analyses in genomewide linkage studies. We describe one method of how to determine the number of 'effectively independent' tests performed in a linkage study using simple linear regression techniques. Further we describe how to use such information to establish genomewide significance thresholds for infinitely dense genomewide maps.

Primary biliary cirrhosis shows association with genetic polymorphism of tumour necrosis factor alpha promoter region.

BACKGROUND/AIMS: Primary biliary cirrhosis is an autoimmune disease in which increased prevalence in first-degree relatives and an association with HLA DR8 suggest a genetic background. TNFalpha is a mediator of inflammation and immunity, and is implicated in the pathogenesis of primary biliary cirrhosis, ex vivo studies having shown reduced production of TNFalpha by lymphocytes from patients. Our group has previously described a biallelic promoter-region polymorphism of the TNFA gene at position -308, and demonstrated that the rare allele, TNF*2, has increased promoter function compared with the common allele, TNF*1. A further biallelic base change has been described in the TNFA gene at -238. We conducted a case-control study to assess association of these gene polymorphisms with primary biliary cirrhosis. METHODS: Ninety-one patients and 213 controls were genotyped for both TNFA loci using restriction fragment length polymorphism analysis of PCR products. RESULTS: The high production TNFA-308*2 allele was significantly under-represented among subjects with primary biliary cirrhosis (27.5% PBC, 41.6% controls, p=0.02, pc=0.04, OR for carriage of TNF*1/*1 genotype=1.89, CI=1.10-3.32). No association was shown with the TNFA -238 polymorphism. CONCLUSION: Primary biliary cirrhosis is associated with reduced carriage of TNF*2. This is in keeping with a protective role of TNFalpha against the disease.

An analysis of linkage disequilibrium in the interleukin-1 gene cluster, using a novel grouping method for multiallelic markers.

In population- and family-based association studies, it is useful to have some knowledge of the patterns of linkage disequilibrium that exist between markers in candidate regions. When such studies are carried out with multiallelic markers, it is often convenient to group the alleles into a biallelic system, for analysis. In this study, we specifically examined the interleukin-1 (IL-1) gene cluster on chromosome 2, a region containing candidates for many inflammatory and autoimmune disorders. Data were collected on eight markers, four of which were multiallelic. Using these data, we investigated the effect of three allele-grouping strategies, including a novel method, on the detection of linkage disequilibrium. The novel approach, termed the "delta method," measures the deviation from the expected haplotype frequencies under linkage equilibrium, for each allelic combination. This information is then used to group the alleles, in an attempt to avoid the grouping together of alleles at one locus that are in opposite disequilibrium with the same allele at the second locus. The estimate haplotype frequencies (EH) program was used to estimate haplotype frequencies and the disequilibrium measure. In our data it was found that the delta method compared well with the other two strategies. Using this method, we found that there was a reasonable correlation between disequilibrium and physical distance in the region (r=-.540, P=.001, one-tailed). We also identified a common, eight-locus haplotype of the IL-1 gene cluster.

Genomewide multipoint linkage analysis of seven extended Palauan pedigrees with schizophrenia, by a Markov-chain Monte Carlo method.

Palauans are an isolated population in Micronesia with lifetime prevalence of schizophrenia (SCZD) of 2%, compared to the world rate of approximately 1%. The possible enrichment for SCZD genes, in conjunction with the potential for reduced etiological heterogeneity and the opportunity to ascertain statistically powerful extended pedigrees, makes Palauans a population of choice for the mapping of SCZD genes. We have used a Markov-chain Monte Carlo method to perform a genomewide multipoint analysis in seven extended pedigrees from Palau. Robust multipoint parametric and nonparametric linkage (NPL) analyses were performed under three nested diagnostic classifications-core, spectrum, and broad. We observed four regions of interest across the genome. Two of these regions-on chromosomes 2p13-14 (for which, under core diagnostic classification, NPL=6.5 and parametric LOD=4.8) and 13q12-22 (for which, under broad diagnostic classification, parametric LOD=3.6, and, under spectrum diagnostic classification, parametric LOD=3.5)-had evidence for linkage with genomewide significance, after correction for multiple testing; with the current pedigree resource and genotyping, these regions are estimated to be 4.3 cM and 19.75 cM in size, respectively. A third region, with intermediate evidence for linkage, was identified on chromosome 5q22-qter (for which, under broad diagnostic classification, parametric LOD=2.5). The fourth region of interest had only borderline suggestive evidence for linkage (on 3q24-28; for this region, under broad diagnostic classification, parametric LOD=2.0). All regions exhibited evidence for genetic heterogeneity. Our findings provide significant evidence for susceptibility loci on chromosomes 2p13-14 and 13q12-22 and support both a model of genetic heterogeneity and the utility of a broader set of diagnostic classifications in the population from Palau.

A new nonparametric linkage statistic for mapping both qualitative and quantitative trait loci.

We describe an alternative nonparametric linkage (NPL) statistic to that of Kruglyak et al. [Am. J. Hum. Genet. 58:1347-63, 1996] that can be used with qualitative phenotypes, and is easily extended for use with quantitative phenotypes. We analyzed the Genetic Analysis Workshop 12 simulated isolated population data, replicate 1, using two phenotypes; affected status (AFF) a dichotomous phenotype and quantitative trait Q5, which was chosen since it was the most strongly associated with AFF. One false positive significant NPL score was observed for the AFF phenotype. For Q5 a single region on chromosome 1 reached genome-wide significance. The peak of this signal was for marker D01G137 at 135.1 cM with a quantitative trait locus (QTL)-NPL score of 4.19. The nearest marker to the true location of the major gene (MG5 at 137.1 cM) was D01G139 at position 135.8 cM, where the QTL-NPL score was still high at 4.08.

A robust multipoint linkage statistic (tlod) for mapping complex trait loci.

Classical parametric two-point linkage analysis is a powerful analysis tool, however there are clear disadvantages too, including the sensitivity to allele frequency mis-specification. Conversely, multipoint linkage analysis is not sensitive to allele frequency mis-specification, but it is sensitive to genetic model mis-specification. Göring and Terwilliger [Am J Hum Genet 66:1095-106, 2000] proposed a new robust multipoint statistic that increased the robustness of multipoint analyses. In this paper we have referred to this new statistic as the tlod. We applied this new statistic to the Genetic Analysis Workshop (GAW) 12 data using affected status (AFF) as the phenotype of interest. The heterogeneity tlod and two-point hlod scores correlated highly across the genome (p < 0.0001), as expected, but the het-tlod had a lower number false positives. In addition, the tlod analysis handled missing data better, as would be expected for a multipoint method. When one-third of the genotype data was removed (dead people) the tlod analysis was less affected than the two-point analysis. When tlod scores were compared with multipoint lod scores in true gene locations, the robustness of the tlod to model mis-specification was clearly evident. When the "best" replicate from the general population was analyzed, a borderline genome-wide significant two-point hlod result (3.6) was found 4 cM from MG6 and MG7 on chromosome 6. The heterogeneity tlod score was lower than the two-point hlod score (1.8), but greater than the heterogeneity multipoint lod score (0.4). However, when replicate 1 of the isolated population was analyzed none of the true gene locations were identified with either statistic.