The importance of modelling heterogeneity in complex disease: application to NIMH Schizophrenia Genetics Initiative data

As for other complex diseases, linkage analyses of schizophrenia (SZ) have produced evidence for numerous chromosomal regions, with inconsistent results reported across studies. The presence of locus heterogeneity appears likely and may reduce the power of linkage analyses if homogeneity is assumed. In addition, when multiple heterogeneous datasets are pooled, intersample variation in the proportion of linked families ( a) may diminish the power of the pooled sample to detect susceptibility loci, in spite of the larger sample size obtained. We compare the significance of linkage. findings obtained using allele- sharing LOD scores ( LODexp) - which assume homogeneity - and heterogeneity LOD scores ( HLOD) in European American and African American NIMH SZ families. We also pool these two samples and evaluate the relative power of the LODexp and two different heterogeneity statistics. One of these ( HLOD- P) estimates the heterogeneity parameter a only in aggregate data, while the second ( HLOD- S) determines a separately for each sample. In separate and combined data, we show consistently improved performance of HLOD scores over LODexp. Notably, genome-wide significant evidence for linkage is obtained at chromosome 10p in the European American sample using a recessive HLOD score. When the two samples are combined, linkage at the 10p locus also achieves genome-wide significance under HLOD- S, but not HLOD- P. Using HLOD- S, improved evidence for linkage was also obtained for a previously reported region on chromosome 15q. In linkage analyses of complex disease, power may be maximised by routinely modelling locus heterogeneity within individual datasets, even when multiple datasets are combined to form larger samples.

Evaluation of IDDM8 susceptibility locus in a Russian simplex family data set

Type 1 diabetes (TID) susceptibility locus, IDDM8, has been accurately mapped to 200 kilobases at the terminal end of chromosome 6q27. This is within the region which harbours a cluster of three genes encoding proteasome subunit beta 1 (PMSB1), TATA-box binding protein (TBP) and a homologue of mouse programming cell death activator 2 (PDCD2). In this study, we evaluated whether these genes contribute to TID susceptibility using the transmission disequilibrium test of the data set from 114 affected Russian simplex families. The A allele of the G/A1180 single nucleotide polymorphism (SNP) at the PDCD2 gene, which was significant in its preferential transfer from parents to diabetic children (75 transmissions vs. 47 non-transmissionS, x(2) = 12.85, P corrected = 0.0038), was found to be associated with T1D. G/A1180 dimorphism and two other SNPs, C/T771 TBP and G/T(-271) PDCD2, were shown to share three common haplotypes, two of which (A-T-G and A-T-T) have been associated with higher development risk of TID. The third haplotype (G-T-G) was related to having a lower risk of disease. These findings suggest that the PDCD2 gene is a likely susceptibility gene for TID within IDDM8. However, it was not possible to exclude the TBP gene from being another putative susceptibility gene in this region. (c) 2005 Elsevier Ltd. All rights reserved.

A genome scan for epidermal skin pattern in adolescent twins reveals suggestive linkage on 12p13.31

Deterioration in stratum corneum reticular patterning (skin pattern or skin wrinkling) has been associated with increased rates of solar keratoses and skin cancer. A previous analysis of data from the twin sample used in this investigation has shown that 86% of the variation in skin pattern is genetic at age 12 and 62% in an adult sample (mean age 47.5). Variation due to genetic influences is likely to be influenced by more than one locus. Here, we present results of a genome-wide linkage scan of skin pattern in adolescent twins and siblings from 428 nuclear twin families. Sib-pair linkage analysis was performed on skin pattern data collected from twins at age 12 (378 informative families) and 14 (316 families). Suggestive linkage was found at marker D12S397 (12p13.31, logarithm of the odds (lod) 1.94), when the effect of the trait locus was modelled to influence the skin pattern equally at both ages 12 and 14. In the same analysis, a peak was seen at 4q23 with a lod score of 1.55. A possible candidate for the peak at 12p13.31 is the protease inhibitor, alpha-2-macroglobulin.

Replicated linkage for eye color on 15q using comparative ratings of sibling pairs

The aim of the study was to perform a genetic linkage analysis for eye color, for comparative data. Similarity in eye color of mono- and dizygotic twins was rated by the twins' mother, their father and/or the twins themselves. For 4748 twin pairs the similarity in eye color was available on a three point scale (not at all alike-somewhat alike-completely alike), absolute eye color on individuals was not assessed. The probability that twins were alike for eye color was calculated as a weighted average of the different responses of all respondents on several different time points. The mean probability of being alike for eye color was 0.98 for MZ twins (2167 pairs), whereas the mean probability for DZ twins was 0.46 (2537 pairs), suggesting very high heritability for eye color. For 294 DZ twin pairs genome-wide marker data were available. The probability of being alike for eye color was regressed on the average amount of IBD sharing. We found a peak LOD-score of 2.9 at chromosome 15q, overlapping with the region recently implicated for absolute ratings of eye color in Australian twins [Zhu, G., Evans, D. M., Duffy, D. L., Montgomery, G. W., Medland, S. E., Gillespie, N. A., Ewen, K. R., Jewell, M., Liew, Y. W., Hayward, N. K., Sturm, R. A., Trent, J. M., and Martin, N. G. (2004). Twin Res. 7:197-210] and containing the OCA2 gene, which is the major candidate gene for eye color [Sturm, R. A. Teasdale, R. D, and Box, N. F. (2001). Gene 277:49-62]. Our results demonstrate that comparative measures on relatives can be used in genetic linkage analysis.

Genome-wide scan of IQ finds significant linkage to a quantitative trait locus on 2q

A genome-wide linkage scan of 795 microsatellite markers (761 autosomal, 34 X chromosome) was performed on Multidimensional Aptitude Battery subtests and verbal, performance and full scale scores, the WAIS-R Digit Symbol subtest, and two word-recognition tests (Schonell Graded Word Reading Test, Cambridge Contextual Reading Test) highly predictive of IQ. The sample included 361 families comprising 2-5 siblings who ranged in age from 15.7 to 22.2 years; genotype, but not phenotype, data were available for 81% of parents. A variance components analysis which controlled for age and sex effects showed significant linkage for the Cambridge reading test and performance IQ to the same region on chromosome 2, with respective LOD scores of 4.15 and 3.68. Suggestive linkage (LOD score > 2.2) for various measures was further supported on chromosomes 6, 7, 11, 14, 21 and 22. Where location of linkage peaks converged for IQ subtests within the same scale, the overall scale score provided increased evidence for linkage to that region over any individual subtest. Association studies of candidate genes, particularly those involved in neural transmission and development, will be directed to genes located under the linkage peaks identified in this study.

A linkage study of academic skills defined by the Queensland Core Skills Test

This study used genome-wide linkage analysis to detect Quantitative Trait Loci (QTLs) implicated in variation in general academic achievement as measured by the Queensland Core Skills Test (QCST) (Queensland Studies Authority, 2004). Data from 210 families were analysed. While no empirically derived significant or suggestive peaks for general academic achievement were indicated a peak on chromosome 2 was observed in a region where Posthuma et al. (2005) reported significant linkage for Performance IQ (PIQ) and suggestive linkage for Full Scale IQ (FSIQ), and Luciano et al. (this issue) observed significant linkage for PIQ and word reading. A peak on chromosome 18 was also observed approximately 20 cM removed from a region recently implicated in reading achievement. In addition, on chromosomes 2 and 18 peaks for a number of specific academic skills, two of which were suggestive, coincided with the general academic achievement peaks. The findings suggest that variation in general academic achievement is influenced by genes on chromosome 2 which have broad influence on a variety of cognitive abilities.

Genome-wide linkage scan for loci influencing plasma triglycerides

Background: Plasma triglyceride concentration is known to be a significant risk factor for cardiovascular disease (CVD). Previous studies have found that the level of triglycerides is strongly influenced by genetic factors. Methods: To identify quantitative trait loci influencing triglycerides, we conducted a genome-wide linkage scan on data from 485 Australian adult dizygotic twin pairs. Prior to linkage analysis, triglyceride values were adjusted for the effects of covariates including age, sex, time since last meal, time of blood collection (CT) and time to plasma separation. Results: The heritability estimate for ln(triglyceride) adjusted for all above fixed effects was 0.49. The highest multipoint LOD score observed was 2.94 (genome-wide p=0.049) on chromosome 7 (at 65cM). This 7p region contains several candidate genes. Two other regions with suggestive multipoint LOD scores were also identified on chromosome 4 (LOD score=2.26 at 62cM) and chromosome X (LOD score=2.01 at 81cM). Conclusions: The linkage peaks found represent newly identified regions for more detailed study, in particular the significant linkage observed on chromosome 7p13. \ (c) 2006 Elsevier B.V. All rights reserved.

A simple method to localise pleiotropic susceptibility loci using univariate linkage analyses of correlated traits

Univariate linkage analysis is used routinely to localise genes for human complex traits. Often, many traits are analysed but the significance of linkage for each trait is not corrected for multiple trait testing, which increases the experiment-wise type-I error rate. In addition, univariate analyses do not realise the full power provided by multivariate data sets. Multivariate linkage is the ideal solution but it is computationally intensive, so genome-wide analysis and evaluation of empirical significance are often prohibitive. We describe two simple methods that efficiently alleviate these caveats by combining P-values from multiple univariate linkage analyses. The first method estimates empirical pointwise and genome-wide significance between one trait and one marker when multiple traits have been tested. It is as robust as an appropriate Bonferroni adjustment, with the advantage that no assumptions are required about the number of independent tests performed. The second method estimates the significance of linkage between multiple traits and one marker and, therefore, it can be used to localise regions that harbour pleiotropic quantitative trait loci (QTL). We show that this method has greater power than individual univariate analyses to detect a pleiotropic QTL across different situations. In addition, when traits are moderately correlated and the QTL influences all traits, it can outperform formal multivariate VC analysis. This approach is computationally feasible for any number of traits and was not affected by the residual correlation between traits. We illustrate the utility of our approach with a genome scan of three asthma traits measured in families with a twin proband.