Type 2 diabetes: Evidence for linkage on chromosome 20 in 716 Finnish affected sib pairs

We are conducting a genome scan at an average resolution of 10 centimorgans (cM) for type 2 diabetes susceptibility genes in 716 affected sib pairs from 477 Finnish families. To date, our best evidence for linkage is on chromosome 20 with potentially separable peaks located on both the long and short arms. The unweighted multipoint maximum logarithm of odds score (MLS) was 3.08 on 20p (location, x̂ = 19.5 cM) under an additive model, whereas the weighted MLS was 2.06 on 20q (x̂ = 57 cM, recurrence risk, λ̂s = 1.25, P = 0.009). Weighted logarithm of odds scores of 2.00 (x̂ = 69.5 cM, P = 0.010) and 1.92 (x̂ = 18.5 cM, P = 0.013) were also observed. Ordered subset analyses based on sibships with extreme mean values of diabetes-related quantitative traits yielded sets of families who contributed disproportionately to the peaks. Two-hour glucose levels in offspring of diabetic individuals gave a MLS of 2.12 (P = 0.0018) at 9.5 cM. Evidence from this and other studies suggests at least two diabetes-susceptibility genes on chromosome 20. We have also screened the gene for maturity-onset diabetes of the young 1, hepatic nuclear factor 4-a (HNF-4α) in 64 affected sibships with evidence for high chromosomal sharing at its location on chromosome 20q. We found no evidence that sequence changes in this gene accounted for the linkage results we observed.

Localization of atherosclerosis susceptibility loci to chromosomes 4 and 6 using the Ldlr knockout mouse model

Atherosclerosis is a complex disease resulting from the interaction of multiple genes. We have used the Ldlr knockout mouse model in an interspecific genetic cross to map atherosclerosis susceptibility loci. A total of 174 (MOLF/Ei × B6.129S7-Ldlrtm1Her) × C57BL/6J-Ldlrtm1Her backcross mice, homozygous for the Ldlr null allele, were fed a Western-type diet for 3 months and then killed for quantification of aortic lesions. A genome scan was carried out by using DNA pools and microsatellite markers spaced at ≈18-centimorgan intervals. Quantitative trait locus analysis of individual backcross mice confirmed linkages to chromosomes 4 (Athsq1, logarithm of odds = 6.2) and 6 (Athsq2, logarithm of odds = 6.7). Athsq1 affected lesions in females only whereas Athsq2 affected both sexes. Among females, the loci accounted for ≈50% of the total variance of lesion area. The susceptible allele at Athsq1 was derived from the MOLF/Ei genome whereas the susceptible allele at Athsq2 was derived from C57BL/6J. Inheritance of susceptible alleles at both loci conferred a 2-fold difference in lesion area, suggesting an additive effect of Athsq1 and Athsq2. No associations were observed between the quantitative trait loci and levels of plasma total cholesterol, high density lipoprotein cholesterol, non-high density lipoprotein cholesterol, insulin, or body weight. We provide strong evidence for complex inheritance of atherosclerosis in mice with elevated plasma low density lipoprotein cholesterol and show a major influence of nonlipoprotein-related factors on disease susceptibility. Athsq1 and Athsq2 represent candidate susceptibility loci for human atherosclerosis, most likely residing on chromosomes 1p36–32 and 12p13–12, respectively.

Copulas in QTL mapping

The standard variance components method for mapping quantitative trait loci is derived on the assumption of normality. Unsurprisingly, statistical tests based on this method do not perform so well if this assumption is not satisfied. We use the statistical concept of copulas to relax the assumption of normality and derive a test that can perform well under any distribution of the continuous trait. In particular, we discuss bivariate normal copulas in the context of sib-pair studies. Our approach is illustrated by a linkage analysis of lipoprotein(a) levels, whose distribution is highly skewed. We demonstrate that the asymptotic critical levels of the test can still be calculated using the interval mapping approach. The new method can be extended to more general pedigrees and multivariate phenotypes in a similar way as the original variance components method.

Polymorphisms in the trace amine receptor 4 (TRAR4) gene on chromosome 6q23.2 are associated with susceptibility to schizophrenia

Several linkage studies across multiple population groups provide convergent support for a susceptibility locus for schizophrenia - and, more recently, for bipolar disorder - on chromosome 6q13-q26. We genotyped 192 European-ancestry and African American (AA) pedigrees with schizophrenia from samples that previously showed linkage evidence to 6q13-q26, focusing on the MOXD1-STX7-TRARs gene cluster at 6q23.2, which contains a number of prime candidate genes for schizophrenia. Thirty-one screening single-nucleotide polymorphisms (SNPs) were selected, providing a minimum coverage of at least 1 SNP/20 kb. The association observed with rs4305745 (P = .0014) within the TRAR4 (trace amine receptor 4) gene remained significant after correction for multiple testing. Evidence for association was proportionally stronger in the smaller AA sample. We performed database searches and sequenced genomic DNA in a 30-proband subsample to obtain a high-density map of 23 SNPs spanning 21.6 kb of this gene. Single-SNP analyses and also haplotype analyses revealed that rs4305745 and/or two other polymorphisms in perfect linkage disequilibrium (LD) with rs4305745 appear to be the most likely variants underlying the association of the TRAR4 region with schizophrenia. Comparative genomic analyses further revealed that rs4305745 and/or the associated polymorphisms in complete LD with rs4305745 could potentially affect gene expression. Moreover, RT-PCR studies of various human tissues, including brain, confirm that TRAR4 is preferentially expressed in those brain regions that have been implicated in the pathophysiology of schizophrenia. These data provide strong preliminary evidence that TRAR4 is a candidate gene for schizophrenia; replication is currently being attempted in additional clinical samples.

Multicenter linkage study of schizophrenia loci on chromosome 22q

The hypothesis of the existence of one or more schizophrenia susceptibility loci on chromosome 22q is supported by reports of genetic linkage and association, meta-analyses of linkage, and the observation of elevated risk for psychosis in people with velocardiofacial syndrome, caused by 22q11 microdeletions. We tested this hypothesis by evaluating 10 microsatellite markers spanning 22q in a multicenter sample of 779 pedigrees. We also incorporated age at onset and sex into the analysis as covariates. No significant evidence for linkage to schizophrenia or for linkage associated with earlier age at onset, gender, or heterogeneity across sites was observed. We interpret these findings to mean that the population-wide effects of putative 22q schizophrenia susceptibility loci are too weak to detect with linkage analysis even in large samples.

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.

Bias, precision and heritability of self-reported and clinically measured height in Australian twins

Many studies of quantitative and disease traits in human genetics rely upon self-reported measures. Such measures are based on questionnaires or interviews and are often cheaper and more readily available than alternatives. However, the precision and potential bias cannot usually be assessed. Here we report a detailed quantitative genetic analysis of stature. We characterise the degree of measurement error by utilising a large sample of Australian twin pairs (857 MZ, 815 DZ) with both clinical and self-reported measures of height. Self-report height measurements are shown to be more variable than clinical measures. This has led to lowered estimates of heritability in many previous studies of stature. In our twin sample the heritability estimate for clinical height exceeded 90%. Repeated measures analysis shows that 2-3 times as many self-report measures are required to recover heritability estimates similar to those obtained from clinical measures. Bivariate genetic repeated measures analysis of self-report and clinical height measures showed an additive genetic correlation > 0.98. We show that the accuracy of self-report height is upwardly biased in older individuals and in individuals of short stature. By comparing clinical and self-report measures we also showed that there was a genetic component to females systematically reporting their height incorrectly; this phenomenon appeared to not be present in males. The results from the measurement error analysis were subsequently used to assess the effects of error on the power to detect linkage in a genome scan. Moderate reduction in error (through the use of accurate clinical or multiple self-report measures) increased the effective sample size by 22%; elimination of measurement error led to increases in effective sample size of 41%.

Identification of the semaphorin receptor PLXNA2 as a candidate for susceptibility to schizophrenia

The discovery of genetic factors that contribute to schizophrenia susceptibility is a key challenge in understanding the etiology of this disease. Here, we report the identification of a novel schizophrenia candidate gene on chromosome 1q32, plexin A2 (PLXNA2), in a genome-wide association study using 320 patients with schizophrenia of European descent and 325 matched controls. Over 25 000 single-nucleotide polymorphisms (SNPs) located within approximately 14 000 genes were tested. Out of 62 markers found to be associated with disease status, the most consistent finding was observed for a candidate locus on chromosome 1q32. The marker SNP rs752016 showed suggestive association with schizophrenia (odds ratio (OR) = 1.49, P = 0.006). This result was confirmed in an independent case control sample of European Americans (combined OR = 1.38, P = 0.035) and similar genetic effects were observed in smaller subsets of Latin Americans (OR = 1.26) and Asian Americans (OR = 1.37). Supporting evidence was also obtained from two family-based collections, one of which reached statistical significance (OR = 2.2, P = 0.02). High-density SNP mapping showed that the region of association spans approximately 60 kb of the PLXNA2 gene. Eight out of 14 SNPs genotyped showed statistically significant differences between cases and controls. These results are in accordance with previous genetic findings that identified chromosome 1q32 as a candidate region for schizophrenia. PLXNA2 is a member of the transmembrane semaphorin receptor family that is involved in axonal guidance during development and may modulate neuronal plasticity and regeneration. The PLXNA2 ligand semaphorin 3A has been shown to be upregulated in the cerebellum of individuals with schizophrenia. These observations, together with the genetic results, make PLXNA2 a likely candidate for the 1q32 schizophrenia susceptibility locus.

Identification des gènes modifiant l’âge d’apparition du glaucome primaire à angle-ouvert dans une famille canadienne-française fondatrice.

Le glaucome est un groupe hétérogène de maladies qui sont caractérisées par l’apoptose des cellules ganglionnaires de la rétine et la dégénérescence progressive du nerf optique. Il s’agit de la première cause de cécité irréversible, qui touche environ 60 millions de personnes dans le monde. Sa forme la plus commune est le glaucome à angle ouvert (GAO), un trouble polygénique causé principalement par une prédisposition génétique, en interaction avec d’autres facteurs de risque tels que l’âge et la pression intraoculaire élevée (PIO). Le GAO est une maladie génétique complexe, bien que certaines formes sévères sont autosomiques dominantes. Dix-sept loci ont été liés à la maladie et acceptés par la « Human Genome Organisation » (HUGO) et cinq gènes ont été identifiés à ces loci (MYOC, OPTN, WDR36, NTF4, ASB10). Récemment, des études d’association sur l’ensemble du génome ont identifié plus de 20 facteurs de risque fréquents, avec des effets relativement faibles. Depuis plus de 50 ans, notre équipe étudie 749 membres de la grande famille canadienne-française CA où la mutation MYOCK423E cause une forme autosomale dominante de GAO dont l’âge de début est fortement variable. Premièrement, il a été montré que cette variabilité de l’âge de début de l’hypertension intraoculaire possède une importante composante génétique causée par au moins un gène modificateur. Ce modificateur interagit avec la mutation primaire et altère la sévérité du glaucome chez les porteurs de MYOCK423E. Un gène modificateur candidat WDR36 a été génotypé dans 2 grandes familles CA et BV. Les porteurs de variations non-synonymes de WDR36 ainsi que de MYOCK423E de la famille CA ont montré une tendance à développer la maladie plus jeune. Un outil de forage de données a été développé pour représenter des informations connues relatives à la maladie et faciliter la priorisation des gènes candidats. Cet outil a été appliqué avec succès à la dépression bipolaire et au glaucome. La suite du projet consiste à finaliser un balayage de génome sur la famille CA et à séquencer les loci afin d’identifier les variations modificatrices du glaucome. Éventuellement, ces variations permettront d’identifier les individus dont le glaucome risque d’être plus agressif.

Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity.

Detecting Loci under Recent Positive Selection in Dairy and Beef Cattle by Combining Different Genome-Wide Scan Methods

As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP) data generated from dairy and beef cattle (taurine and indicine). The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10-7) population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3) in Brown Swiss (P = 3.82×10-12), and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.

A genome-wide scan for selection signatures in Nellore cattle

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Genome-wide scan for visceral leishmaniasis in mixed-breed dogs identifies candidate genes involved in T helper cells and macrophage signaling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)