Genome-wide association study in a Chinese population identifies a susceptibility locus for type 2 diabetes at 7q32 near PAX4

AIMS/HYPOTHESIS

Most genetic variants identified for type 2 diabetes have been discovered in European populations. We performed genome-wide association studies (GWAS) in a Chinese population with the aim of identifying novel variants for type 2 diabetes in Asians.

METHODS

We performed a meta-analysis of three GWAS comprising 684 patients with type 2 diabetes and 955 controls of Southern Han Chinese descent. We followed up the top signals in two independent Southern Han Chinese cohorts (totalling 10,383 cases and 6,974 controls), and performed in silico replication in multiple populations.

RESULTS

We identified CDKN2A/B and four novel type 2 diabetes association signals with p < 1 × 10(-5) from the meta-analysis. Thirteen variants within these four loci were followed up in two independent Chinese cohorts, and rs10229583 at 7q32 was found to be associated with type 2 diabetes in a combined analysis of 11,067 cases and 7,929 controls (p meta = 2.6 × 10(-8); OR [95% CI] 1.18 [1.11, 1.25]). In silico replication revealed consistent associations across multiethnic groups, including five East Asian populations (p meta = 2.3 × 10(-10)) and a population of European descent (p = 8.6 × 10(-3)). The rs10229583 risk variant was associated with elevated fasting plasma glucose, impaired beta cell function in controls, and an earlier age at diagnosis for the cases. The novel variant lies within an islet-selective cluster of open regulatory elements. There was significant heterogeneity of effect between Han Chinese and individuals of European descent, Malaysians and Indians.

CONCLUSIONS/INTERPRETATION

Our study identifies rs10229583 near PAX4 as a novel locus for type 2 diabetes in Chinese and other populations and provides new insights into the pathogenesis of type 2 diabetes.

Association of CD247 with systemic lupus erythematosus in Asian populations

OBJECTIVE

Systemic lupus erythematosus (SLE) is a prototypic autoimmune disease with complex genetic inheritance. CD247 (CD3Z, TCRZ) plays a vital role in antigen recognition and signal transduction in antigen-specific immune responses, and is known to be involved in SLE pathogenesis. Weak disease association was reported for genetic variants in this gene in Caucasian studies for SLE, Crohn's disease and systemic sclerosis, but its role as a genetic risk factor was never firmly established.

METHODS

In this study, using a collection of 612 SLE patients and 2193 controls of Chinese ethnicity living in Hong Kong in a genome-wide study, single nucleotide polymorphisms (SNPs) in and around CD247 were identified as being associated with SLE. The two most significant SNPs in this locus were selected for further replication using TaqMan genotyping assay in 3339 Asian patients from Hong Kong, Mainland China, and Thailand, as well as 4737 ethnically and geographically matched controls.

RESULTS

The association of CD247 with SLE in Asian populations was confirmed (rs704853: odds ratio [OR] = 0. 81, p = 2.47 × 10(-7); rs858543: OR = 1.10, p = 0.0048). Patient-only analysis suggested that rs704853 is also linked to oral ulcers, hematologic disorders and anti-double-stranded DNA (dsDNA) antibody production.

CONCLUSION

A significant association between variants in CD247 and SLE was demonstrated in Asian populations. Understanding the involvement of CD247 in SLE may shed new light on disease mechanisms and development of new treatment paradigms.

Replication study of SNP associations for colorectal cancer in Hong Kong Chinese

BACKGROUND

Recent genome-wide association studies of colorectal cancer (CRC) have identified common single-nucleotide polymorphisms (SNPs) mapping to 10 independent loci that confer modest increased risk. These studies have been conducted in European populations and it is unclear whether these observations generalise to populations with different ethnicities and rates of CRC.

METHODS

An association study was performed on 892 CRC cases and 890 controls recruited from the Hong Kong Chinese population, genotyping 32 SNPs, which were either associated with CRC in previous studies or are in close proximity to previously reported risk SNPs.

RESULTS

Twelve of the SNPs showed evidence of an association. The strongest associations were provided by rs10795668 on 10p14, rs4779584 on 15q14 and rs12953717 on 18q21.2. There was significant linear association between CRC risk and the number of independent risk variants possessed by an individual (P=2.29 × 10(-5)).

CONCLUSION

These results indicate that some previously reported SNP associations also impact on CRC risk in the Chinese population. Possible reasons for failure of replication for some loci include inadequate study power, differences in allele frequency, linkage disequilibrium structure or effect size between populations. Our results suggest that many associations for CRC are likely to generalise across populations.

Fine mapping of the 9q31 Hirschsprung's disease locus

Hirschsprung’s disease (HSCR) is a congenital disorder characterised by the absence of ganglia along variable lengths of the intestine. The RET gene is the major HSCR gene. Reduced penetrance of RET mutations and phenotypic variability suggest the involvement of additional modifying genes in the disease. A RET-dependent modifier locus was mapped to 9q31 in families bearing no coding sequence (CDS) RET mutations. Yet, the 9q31 causative locus is to be identified. To fine-map the 9q31 region, we genotyped 301 tag-SNPs spanning 7 Mb on 137 HSCR Dutch trios. This revealed two HSCR-associated regions that were further investigated in 173 Chinese HSCR patients and 436 controls using the genotype data obtained from a genome-wide association study recently conducted. Within one of the two identified regions SVEP1 SNPs were found associated with Dutch HSCR patients in the absence of RET mutations. This ratifies the reported linkage to the 9q31 region in HSCR families with no RET CDS mutations. However, this finding could not be replicated. In Chinese, HSCR was found associated with IKBKAP. In contrast, this association was stronger in patients carrying RET CDS mutations with p = 5.10 × 10⁻⁶ [OR = 3.32 (1.99, 5.59)] after replication. The HSCR-association found for IKBKAP in Chinese suggests population specificity and implies that RET mutation carriers may have an additional risk. Our finding is supported by the role of IKBKAP in the development of the nervous system.

Application of genome-wide SNP data for uncovering pairwise relationships and quantitative trait loci

The genetic analysis of quantitative traits in humans is changing as a result of the availability of whole-genome SNP data. Heritability analysis can make use of actual genetic sharing between pairs of individuals estimated from the genotype data, rather than the expected genetic sharing implied by their family relationship. This could provide more accurate heritability estimates and help to overcome the equal environment assumption. Quantitative trait locus (QTL) linkage mapping can make use of local genetic sharing inferred from very dense local genotype data from pedigree members or individuals not previously known to be related. This approach may be particularly suited for detecting loci that contain rare variants with major effect on the phenotype. Finally, whole-genome SNP data can be used to measure the genetic similarity between individuals to provide matched sets for association studies, in order to avoid spurious association from population stratification.

OpenADAM: an open source genome-wide association data management system for Affymetrix SNP arrays

Background

Large scale genome-wide association studies have become popular since the introduction of high throughput genotyping platforms. Efficient management of the vast array of data generated poses many challenges.

Description

We have developed an open source web-based data management system for the large amount of genotype data generated from the Affymetrix GeneChip^® Mapping Array and Affymetrix Genome-Wide Human SNP Array platforms. The database supports genotype calling using DM, BRLMM, BRLMM-P or Birdseed algorithms provided by the Affymetrix Power Tools. The genotype and corresponding pedigree data are stored in a relational database for efficient downstream data manipulation and analysis, such as calculation of allele and genotype frequencies, sample identity checking, and export of genotype data in various file formats for analysis using commonly-available software. A novel method for genotyping error estimation is implemented using linkage disequilibrium information from the HapMap project. All functionalities are accessible via a web-based user interface.

Conclusion

OpenADAM provides an open source database system for management of Affymetrix genome-wide association SNP data.

Genetic influences on the difference in variability of height, weight and body mass index between Caucasian and East Asian adolescent twins

OBJECTIVE

Twin studies are useful for investigating the causes of trait variation between as well as within a population. The goals of the present study were two-fold: First, we aimed to compare the total phenotypic, genetic and environmental variances of height, weight and BMI between Caucasians and East Asians using twins. Secondly, we intended to estimate the extent to which genetic and environmental factors contribute to differences in variability of height, weight and BMI between Caucasians and East Asians.

DESIGN

Height and weight data from 3735 Caucasian and 1584 East Asian twin pairs (age: 13-15 years) from Australia, China, Finland, Japan, the Netherlands, South Korea, Taiwan and the United States were used for analyses. Maximum likelihood twin correlations and variance components model-fitting analyses were conducted to fulfill the goals of the present study.

RESULTS

The absolute genetic variances for height, weight and BMI were consistently greater in Caucasians than in East Asians with corresponding differences in total variances for all three body measures. In all 80 to 100% of the differences in total variances of height, weight and BMI between the two population groups were associated with genetic differences.

CONCLUSION

Height, weight and BMI were more variable in Caucasian than in East Asian adolescents. Genetic variances for these three body measures were also larger in Caucasians than in East Asians. Variance components model-fitting analyses indicated that genetic factors contributed to the difference in variability of height, weight and BMI between the two population groups. Association studies for these body measures should take account of our findings of differences in genetic variances between the two population groups.

Association of F11 receptor gene polymorphisms with central obesity and blood pressure

OBJECTIVES

F11 receptor, also known as junctional adhesion molecule-1, in the autonomic nervous system is implicated in the development of hypertension in spontaneous hypertensive rats. We investigated the association of single nucleotide polymorphisms (SNPs) in the F11 receptor gene (F11R) with hypertension and central obesity in Hong Kong Chinese.

METHODS

Seven tagging SNPs were identified in the HapMap database. Genotyping was performed using Sequenom MassArray in 263 hypertensive subjects and 393 normotensive controls, of whom 263 matched the cases in age and sex.

RESULTS

When subjects on anti-hypertensive medication were excluded, rs790056 and rs2774276 were associated with lower systolic blood pressure (TT:124.8 +/- 18.3 mmHg vs. TC + CC: 120.2 +/- 15.5 mmHg, P = 0.004 and CC: 124.7 +/- 18.5 mmHg vs. CG+GG: 120.5 +/- 15.1 mmHg, P = 0.007 respectively). Comparing 213 subjects with central obesity with 213 controls matched for sex and age, rs2481084 and rs3737787 were associated with lower odds of central obesity (odds ratio = 0.516, P = 0.002 and odds ratio = 0.540, P = 0.005 respectively). All these associations remained significant after correction for multiple testing. Analysis of statistically similar SNPs suggested that the causative variants for systolic blood pressure were located in F11R, whilst those for central obesity could be due to causative variants in the transcription factor 1 gene immediately upstream.

CONCLUSIONS

F11 receptor plays a role in blood pressure regulation, not only in rats but also in man. The link between F11 receptor and central obesity merits further investigation.

Replication of twelve association studies for Huntington's disease residual age of onset in large Venezuelan kindreds

BACKGROUND

The major determinant of age of onset in Huntington's disease is the length of the causative triplet CAG repeat. Significant variance remains, however, in residual age of onset even after repeat length is factored out. Many genetic polymorphisms have previously shown evidence of association with age of onset of Huntington's disease in several different populations.

OBJECTIVE

To replicate these genetic association tests in 443 affected people from a large set of kindreds from Venezuela.

METHODS

Previously tested polymorphisms were analysed in the HD gene itself (HD), the GluR6 kainate glutamate receptor (GRIK2), apolipoprotein E (APOE), the transcriptional coactivator CA150 (TCERG1), the ubiquitin carboxy-terminal hydrolase L1 (UCHL1), p53 (TP53), caspase-activated DNase (DFFB), and the NR2A and NR2B glutamate receptor subunits (GRIN2A, GRIN2B).

RESULTS

The GRIN2A single-nucleotide polymorphism explains a small but considerable amount of additional variance in residual age of onset in our sample. The TCERG1 microsatellite shows a trend towards association but does not reach statistical significance, perhaps because of the uninformative nature of the polymorphism caused by extreme allele frequencies. We did not replicate the genetic association of any of the other genes.

CONCLUSIONS

GRIN2A and TCERG1 may show true association with residual age of onset for Huntington's disease. The most surprising negative result is for the GRIK2 (TAA)(n) polymorphism, which has previously shown association with age of onset in four independent populations with Huntington's disease. The lack of association in the Venezuelan kindreds may be due to the extremely low frequency of the key (TAA)(16) allele in this population.

Introduction to the special issue: human linkage studies for behavioral traits

In the post Genome era, the aim of behavior genetics has shifted from estimating the relative contributions of genes and environmental factors to (co-)variation in human complex traits, to localization of genes and identification of functional genetic variants. This special issue reflects this transition and presents fifteen papers that report on genome-wide linkage scans for complex traits in humans and on methodological tools and innovations. Six papers focus on cognition and report overlapping linkage peaks on chromosomes 6p and 14p. Papers on addictive behavior, i.e. smoking and alcohol dependence and its endophenotypes, find moderate LOD scores on chromosomes 6p, 5q, 4p and 7q, respectively. Three papers concentrate on emotionality, depression and loneliness and examine chromosomes 2q and 12q. The papers in this issue represent a summary of the first large scale linkage enterprises of human behavioral traits.

Genetic Power Calculator: design of linkage and association genetic mapping studies of complex traits

SUMMARY

A website for performing power calculations for the design of linkage and association genetic mapping studies of complex traits.

AVAILABILITY

The package is made available athttp://statgen.iop.kcl.ac.uk/gpc/.

The effect of genotype and pedigree error on linkage analysis: analysis of three asthma genome scans

The effects of genotype and relationship errors on linkage results are evaluated in three of the Genetic Analysis Workshop 12 asthma genome scans. A number of errors are detected in the samples. While the evidence for linkage is not striking in any data set with or without error, in some cases the difference in test statistic could support different conclusions. The results provide empirical evidence for the predicted effects of genotype and relationship error and highlight the need for rigorous detection and elimination of data error in complex trait studies.

Association analysis in a variance components framework

Association analyses conducted in a variance components framework can include information from all available individuals but remain unbiased in the presence of familiality or linkage. Models that include both linkage and association parameters provide different estimates of the effect of a single locus and can be used to distinguish causal polymorphisms from other types of variation. We examine some of these models and their properties in a blind analysis of the simulated Genetic Analysis Workshop 12 data sets.

GRR: graphical representation of relationship errors

SUMMARY

A graphical tool for verifying assumed relationships between individuals in genetic studies is described. GRR can detect many common errors using genotypes from many markers.

AVAILABILITY

GRR is available at http://bioinformatics.well.ox.ac.uk/GRR.

Optimal sibship selection for genotyping in quantitative trait locus linkage analysis

In this paper we present a novel method for selecting optimally informative sibships of any size for quantitative trait locus (QTL) linkage analysis. The method allocates a quantitative index of potential informativeness to each sibship on the basis of observed trait scores and an assumed true QTL model. Any sample of phenotypically screened sibships can therefore be easily rank-ordered for selective genotyping. The quantitative index is the sibship's expected contribution to the non-centrality parameter. This expectation represents the weighted sum of chi(2) test statistics that would be obtained given the observed trait values over all possible sibship genotypic configurations; each configuration is weighted by the likelihood of it occurring given the assumed true genetic model. The properties of this procedure are explored in relation to the accuracy of the assumed true genetic model and sibship size. In comparison to previous methods of selecting phenotypically extreme sibships for genotyping, the proposed method is considerably more efficient and is robust with regard to the specification of the genetic model.

A powerful and rapid approach to human genome scanning using small quantities of genomic DNA

Dense maps of short-tandem-repeat polymorphisms (STRPs) have allowed genome-wide searches for genes involved in a great variety of diseases with genetic influences, including common complex diseases. Generally for this purpose, marker sets with a 10 cM spacing are genotyped in hundreds of individuals. We have performed power simulations to estimate the maximum possible inter-marker distance that still allows for sufficient power. In this paper we further report on modifications of previously published protocols, resulting in a powerful screening set containing 229 STRPs with an average spacing of 18·3 cM. A complete genome scan using our protocol requires only 80 multiplex PCR reactions which are all carried out using one set of conditions and which do not contain overlapping marker allele sizes. The multiplex PCR reactions are grouped by sets of chromosomes, which enables on-line statistical analysis of a set of chromosomes, as sets of chromosomes are being genotyped. A genome scan following this modified protocol can be performed using a maximum amount of 2·5 μg of genomic DNA per individual, isolated from either blood or from mouth swabs.

DeFries-Fulker multiple regression analysis of sibship QTL data: a SAS macro

A SAS macro package for performing multipoint QTL mapping using the DeFries-Fulker multiple regression method is presented.

Life events and depression in a community sample of siblings

BACKGROUND

The overall aim of the GENESiS project is to identify quantitative trait loci (QTLs) for anxiety/depression, and to examine the interaction between these loci and psychosocial adversity. Here we present life-events data with the aim of clarifying: (i) the aetiology of life events as inferred from sibling correlations; (ii) the relationship between life events and measures of anxiety and depression, as well as neuroticism; and (iii) the interaction between life events and neuroticism on anxiety/depression indices.

METHODS

We assessed the occurrence of one network and three personal life-event categories and multiple indices of anxiety/depression including General Health Questionnaire, Anhedonic Depression, Anxious Arousal and Neuroticism in a large community-based sample of2150 sib pairs, 410 trios and 81 quads. Liability threshold models and raw ordinal maximum likelihood were used to estimate within-individual and between-sibling correlations of life events. The relationship between life events and indices of emotional states and personality were assessed by multiple linear regression and canonical correlations.

RESULTS

Life events showed sibling correlations of 0-37 for network events and between 0-10 and 0.19 for personal events. Adverse life events were related to anxiety and depression and, to a less extent, neuroticism. Trait-vulnerability (as indexed by co-sib's neuroticism, anxiety and depression) accounted for 11% and life events for 3% of the variance in emotional states. There were no interaction effects.

CONCLUSIONS

Life events show moderate familiality and are significantly related to symptoms of anxiety and depression in the community. Appropriate modelling of life events in linkage and association analyses should help to identify QTLs for depression and anxiety.

Variance-Components QTL linkage analysis of selected and non-normal samples: conditioning on trait values

Standard variance-components quantitative trait loci (QTL) linkage analysis can produce an elevated rate of type 1 errors when applied to selected samples and non-normal data. Here we describe an adjustment of the log-likelihood function based on conditioning on trait values. This leads to a likelihood ratio test that is valid in selected samples and non-normal data, and equal in power to alternative methods for analyzing selected samples that require knowledge of the ascertainment procedure or the trait values of non-selected individuals.

The impact of genotyping error on family-based analysis of quantitative traits

Errors in genotyping can substantially influence the power to detect linkage using affected sib-pairs, but it is not clear what effect such errors have on quantitative trait analyses. Here we use Monte Carlo simulation to examine the influence of genotyping error on multipoint vs two-point analysis, variable map density, locus effect size and allele frequency in quantitative trait linkage and association studies of sib-pairs. The analyses are conducted using variance components methods. We contrast the effects of error on quantitative trait analyses with those on the affected sib-pair design. The results indicate that genotyping error influences linkage studies of affected sib pairs more severely than studies of quantitative traits in unselected sibs. In situations of modest effect size, 5% genotyping error eliminates all supporting evidence for linkage to a true susceptibility locus in affected pairs, but may only result in a loss of 15% of linkage information in random pairs. Multipoint analysis does not suffer substantially more than two-point analysis; for moderate error rates (< 5%), multipoint analysis with error is more powerful than two-point with no error. Map density does not appear to be an important factor for linkage analysis. QTL association analyses of common alleles are reasonably robust to genotyping error but power can be affected dramatically with rare alleles.

Parent ratings of temperament in twins: explaining the 'too low' DZ correlations

Twin studies of child temperament using objective measures consistently suggest moderate heritability for most dimensions. However, parent rating measures produce unusual patterns of results. Intraclass correlations for identical (MZ) twins are typically high, whereas fraternal (DZ) twin intraclass correlations are much lower than would be predicted from an additive genetic model. The 'too low' DZ correlations can be explained by parent-rating biases that either exaggerate the differences between DZ twins (contrast effects) or that inflate the similarity of MZ twins (assimilation effects), or by the presence of non-additive genetic variance. To evaluate the three possible explanations, we used model-fitting procedures applied to parent-rating data averaged across 14, 20, 24, and 36 months of age in a sample of 196 twin pairs participating in the MacArthur Longitudinal Twin Study. The data were best described by a model that included contrast effects. Implications for non-twin research are discussed.

Power of linkage versus association analysis of quantitative traits, by use of variance-components models, for sibship data

Optimal design of quantitative-trait loci (QTL) mapping studies requires a precise understanding of the power of QTL linkage versus QTL association analysis, under a range of different conditions. In this article, we investigate the power of QTL linkage and association analyses for simple random sibship samples, under the variance-components model proposed by Fulker et al. After a brief description of an extension of this variance-components model, we show that the powers of both linkage and association analyses are crucially dependent on the proportion of phenotypic variance attributable to the QTL. The main difference between the two tests is that, whereas the power of association is directly related to the QTL heritability, the power of linkage is related more closely to the square of the QTL heritability. We also describe both how the power of linkage is attenuated by incomplete linkage and incomplete marker information and how the power of association is attenuated by incomplete linkage disequilibrium.

High-resolution mapping of quantitative trait loci in outbred mice

Screening the whole genome of a cross between two inbred animal strains has proved to be a powerful method for detecting genetic loci underlying quantitative behavioural traits, but the level of resolution offered by quantitative trait loci (QTL) mapping is still too coarse to permit molecular cloning of the genetic determinants. To achieve high-resolution mapping, we used an outbred stock of mice for which the entire genealogy is known. The heterogeneous stock (HS) was established 30 years ago from an eight-way cross of C57BL/6, BALB/c, RIII, AKR, DBA/2, I, A/J and C3H inbred mouse strains. At the time of the experiment reported here, the HS mice were at generation 58, theoretically offering at least a 30-fold increase in resolution for QTL mapping compared with a backcross or an F2 intercross. Using the HS mice we have mapped a QTL influencing a psychological trait in mice to a 0.8-cM interval on chromosome 1. This method allows simultaneous fine mapping of multiple QTLs, as shown by our report of a second QTL on chromosome 12. The high resolution possible with this approach makes QTLs accessible to positional cloning.

Quantitative-trait locus for specific language and reading deficits on chromosome 6p

Reading disability (RD), or dyslexia, is a complex cognitive disorder manifested by difficulties in learning to read, in otherwise normal individuals. Individuals with RD manifest deficits in several reading and language skills. Previous research has suggested the existence of a quantitative-trait locus (QTL) for RD on the short arm of chromosome 6. In the present study, RD subjects' performance in several measures of word recognition and component skills of orthographic coding, phonological decoding, and phoneme awareness were individually subjected to QTL analysis, with a new sample of 126 sib pairs, by means of a multipoint mapping method and eight informative DNA markers on chromosome 6 (D6S461, D6S276, D6S105, D6S306, D6S258, D6S439, D6S291, and D6S1019). The results indicate significant linkage across a distance of at least 5 cM for deficits in orthographic (LOD = 3.10) and phonological (LOD = 2.42) skills, confirming previous findings.

Combined linkage and association sib-pair analysis for quantitative traits

An extension to current maximum-likelihood variance-components procedures for mapping quantitative-trait loci in sib pairs that allows a simultaneous test of allelic association is proposed. The method involves modeling of the allelic means for a test of association, with simultaneous modeling of the sib-pair covariance structure for a test of linkage. By partitioning of the mean effect of a locus into between- and within-sibship components, the method controls for spurious associations due to population stratification and admixture. The power and efficacy of the method are illustrated through simulation of various models of both real and spurious association.

Increase in power through multivariate analyses

Power to detect genetic and environmental influences increases not only with sample size but also with the number of measurements through longitudinal and/or multivariate designs, if those measurements correlate with each other. Power simulations are presented for uni- through quadrivariate cases, with differing genetic and environmental parameters. Even though subject attrition is a problem for most longitudinal studies, the gain in power available may more than make up for this shortcoming in many situations. In terms of planning studies to examine genetic and environmental influences, power calculations should not only consider sample size but number of measurements on particular phenotypes and their intercorrelations.

Exploring the genetic and environmental etiology of high general cognitive ability in fourteen- to thirty-six-month-old twins

Although numerous theories have attempted to explain the origins of high general cognitive ability (g), the genetic and environmental etiology of high g during infancy and early childhood has not previously been investigated. We report results of a twin study of high cognitive ability at 14, 20, 24, and 36 months using twins from the more than 600 children participating in the MacArthur Longitudinal Twin Study. High g groups were formed from the ninetieth percentile and above at each age, with IQ equivalent means at or above 126 across the ages. Results suggest increasing genetic influence and increasing genetic stability from 14 to 36 months using DeFries-Fulker multiple regression analyses. However, genetic influences are substantial when examining individuals who possess high g scores averaged across all 4 ages. These results suggest that, although high cognitive ability may be genetically influenced in early childhood, these influences differ in magnitude from 14 to 36 months.

Exploring the genetic etiology of low general cognitive ability from 14 to 36 months

The genetic and environmental etiology of low general cognitive ability (g) during infancy and early childhood has not previously been investigated. The current study examined the genetic etiology of low cognitive ability at 14, 20, 24, and 36 months with twins from the MacArthur Longitudinal Twin Study. Low g groups were formed from the lowest 10th percentile at each age. Univariate probandwise concordance rates and DeFries-Fulker (J. C. DeFries & D. W. Fulker, 1985, 1988) multiple regression techniques suggest genetic etiology in low general cognitive ability groups. The stability of low general cognitive ability over time also appears to be primarily due to genetic factors. Although replication is necessary, these results suggest that the genetic etiology of low g during infancy and early childhood is at least as great as the heritability of g in the unselected population.

Exploring the genetic etiology of low general cognitive ability from 14 to 36 months

The genetic and environmental etiology of low general cognitive ability (g) during infancy and early childhood has not previously been investigated. The current study examined the genetic etiology of low cognitive ability at 14, 20, 24, and 36 months with twins from the MacArthur Longitudinal Twin Study. Low g groups were formed from the lowest 10th percentile at each age. Univariate probandwise concordance rates and DeFries-Fulker (J. C. DeFries & D. W. Fulker, 1985, 1988) multiple regression techniques suggest genetic etiology in low general cognitive ability groups. The stability of low general cognitive ability over time also appears to be primarily due to genetic factors. Although replication is necessary, these results suggest that the genetic etiology of low g during infancy and early childhood is at least as great as the heritability of g in the unselected population.

The familial aggregation of depressive symptoms, antisocial behavior, and alcohol abuse

This study describes results from an ongoing family study of adolescent boys and their families designed to investigate potential risk factors for substance abuse. The adolescent treatment probands have severe drug and alcohol related problems and were recruited through a residential rehabilitation program. To date, the sample includes 251 individuals: 39 male probands and their families and 34 control families matched for age and geographic location (zip code). Probands and participating family members are given a structured interview which assesses alcohol and drug problems, and various psychiatric symptoms. The purpose of the present study was to examine the coaggregation of depressive symptoms, antisocial behavior, and alcohol misuse. Multivariate pedigree analyses were performed using a model that allowed for the estimation of vertical familial transmission, residual sibling resemblance, and assortative mating. Spouse correlations were estimated at .57, .21, and .31 for antisocial behavior, depressive symptoms, and alcohol abuse, respectively. Residual sibling environment (i.e., sibling resemblance unaccounted for by parent-offspring transmission) was not found for alcohol problem symptoms, but did contribute to resemblance for antisocial behavior and depressive symptoms. The proportion of variance accounted for by vertical familial transmission was estimated at approximately 30 to 40%. More important, correlations among the transmissible family factors for these psychiatric syndromes ranged from .58 to .73, suggesting substantial overlap among the underlying familial antecedents for these disorders.

An improved multipoint sib-pair analysis of quantitative traits

Kruglyak and Lander (1995) recently published a multipoint sib-pair procedure based on the expected distribution of zero, one and two marker alleles shared identical by descent (ibd) and the method of maximum-likelihood (ML). Their approach uses phenotypic sib-pair differences, which ignores the bivariate structure of sib-pair data. Their simulations suggested that their method was more powerful than the regression method of Haseman and Elston (1972). We show through computation and simulation that their approach can be made more powerful still if the bivariate nature of sib-pair data is acknowledged. In addition, methods based on the average number of shared alleles that also employ bivariate ML procedures (Nance and Neale, 1989; Xu and Atchley, 1995) are more powerful than the approach they recommend and very similar to true ML using the distribution of ibd. The simple ML approach using the average number of shared alleles that we recommend seems to offer both optimal power and flexibility.

Linkage between sexual orientation and chromosome Xq28 in males but not in females

We have extended our analysis of the role of the long arm of the X chromosome (Xq28) in sexual orientation by DNA linkage analyses of two newly ascertained series of families that contained either two gay brothers or two lesbian sisters as well as heterosexual siblings. Linkage between the Xq28 markers and sexual orientation was detected for the gay male families but not for the lesbian families or for families that failed to meet defined inclusion criteria for the study of sex-linked sexual orientation. Our results corroborate the previously reported linkage between Xq28 and male homosexuality in selected kinships and suggest that this region contains a locus that influences individual variations in sexual orientation in men but not in women.

Multipoint interval mapping of quantitative trait loci, using sib pairs

The sib-pair interval-mapping procedure of Fulker and Cardon is extended to take account of all available marker information on a chromosome simultaneously. The method provides a computationally fast multipoint analysis of sib-pair data, using a modified Haseman-Elston approach. It gives results very similar to those of the earlier interval-mapping procedure when marker information is relatively uniform and a coarse map is used. However, there is a substantial improvement over the original method when markers differ in information content and/or when a dense map is employed. The method is illustrated by using simulated sib-pair data.

Linkage analysis of a common oligogenic disease using selected sib pairs

Sib pairs drawn from the simulated common oligogenic disease families were selected for extreme quantitative trait scores and analyzed using interval mapping and multipoint methods. Linkage analyses of 112 selected sib pairs, in which one or more members had trait values exceeding the disease threshold, were compared with analyses of the total unselected sib-pair sample (771 pairs). Selected sample regression models yielded comparable significance levels to those obtained from the unselected sample at most loci on the six simulated chromosomes, demonstrating the efficiency of selected sib-pair analysis for quantitative characters. Two of the three disease QTLs were detected in both selected and unselected samples. Interval mapping and multipoint analyses yielded location estimates close to the simulated positions of the QTLs. The combined strategy of using interval mapping and multipoint methods with selected sib pairs appears to provide improved accuracy and sensitivity over more traditional sib-pair methods for detecting quantitative trait loci.

Gender-controlled measures of socially desirable responding

Items in various scales that measure socially desirable responding (SDR) appear to vary in significance in male and female respondents. Recent findings suggest that females are more sensitive to the contents of more than two-thirds of such items. As a result, scales that measure SDR cannot be considered gender balanced, not to mention gender free. We examined three levels at which SDR items can be construed as gender controlled and arrived at a formula for item selection in the development of gender-controlled scales. Application of the formula resulted in the 10-item Gender-Free Inventory of Desirable Responding (GFIDR), with an inter-item reliability of .68, and the 12-item Gender Balanced Inventory of Desirable Responding (GBIDR), with an inter-item reliability of .71. The distribution characteristics of the two scales suggested that gender differences in the higher moments should be considered in the interpretation of results based on otherwise gender-controlled scales.

Continuity and change in infant shyness from 14 to 20 months

Objective measures of shyness in the MacArthur Longitudinal Twin Study were obtained in two testing situations: the laboratory and the home. A longitudinal hierarchical model was fitted to the data, allowing estimation of the extent to which genetic, shared environmental, and unique environmental influences contributed to continuity and change of the shyness phenotype from 14 to 20 months of age. The sample consisted of 163 monozygotic and 138 same-sex dizygotic twin pairs. Models were fitted to raw data using a maximum-likelihood pedigree approach. Genetic, shared environmental, and unique environmental first-order factors, with specific variances, were modeled on each of four shyness ratings assessed in the laboratory and home at 14 and 20 months. Four second-order genetic, shared environmental, and unique environmental factors were also modeled. Results indicated that developmental change from 14 to 20 months and situational specificity between the laboratory and the home are mediated largely by shared and unique environmental influences. Genetic variation is largely responsible for both the stability in shyness from 14 to 20 months and the phenotypic correlations observed between the laboratory and the home settings.

Genetic and environmental influences on early childhood behavior

The Child Behavior Checklist for Ages 2-3 (Adelbach et al., J. Abnorm. Child Psychol. 15;629-650; 1987) was completed by mothers of 229 pairs of twins (mean age = 33 months). Using the two broad-band groupings of Internalizing and Externalizing described by Achenbach et al. (1987), various models to estimate genetic and environmental parameters were fitted using LISREL 7. Model-fitting results showed that the genetic components to the observed phenotypical variation were small and not necessary in the model. Influences from the shared environment, however, could not be dropped from the model without a deterioration in fit. Parameter estimates were not significantly different in boys and girls.

A maximum-likelihood model-fitting approach to conducting a Hayman analysis of diallel tables with complete or missing data

A method is presented for conducting a Hayman analysis of non-replicated diallel tables using a maximum-likelihood (ML) model-fitting approach, rather than a traditional analysis of variance (ANOVA) approach. Hayman's linear model for a diallel analysis is used to generate a table of expected cell means. This table of expected cell means is fit to a table of observed cell means, and the fit is assessed using a chi-square value. Often data collected from diallel crosses fail to meet the underlying assumptions of ANOVA. The ML method makes no assumptions about equal cell sizes or homogeneity of variance. Thus, the ML method for diallel analysis provides some statistical advantages over ANOVA methods. The ML method also offers the advantage of having the ability to analyze diallels with missing cells. Using the ML method, incomplete diallel tables can be analyzed, and the partitioning of all the sources of variation in a diallel table is still accomplished from the remaining crosses. These advantages make the ML method an attractive approach for extracting the maximum amount of information from a diallel table.

Multiple regression analysis of twin data: a model-fitting approach

The multiple regression methodology proposed by DeFries and Fulker (DF; 1985, 1988) for the analysis of twin data is compared with maximum-likelihood estimation of genetic and environmental parameters from covariance structure. Expectations for the regression coefficients from submodels omitting the h2 and c2 terms are derived. Model comparisons similar to those conducted using maximum-likelihood estimation procedures are illustrated using multiple regression. Submodels of the augmented DF model are shown to yield parameter estimates highly similar to those obtained from the traditional latent variable model. While maximum-likelihood estimation of covariance structure may be the optimal statistical method of estimating genetic and environmental parameters, the model-fitting approach we propose is a useful extension to the highly flexible and conceptually simple DF methodology.

Differential heritability across levels of cognitive ability

Differences in heritability and shared environmentality across levels of cognitive ability were assessed in a sample of 264 twin pairs tested at 1 year of age and in subsets tested at 2 and 3 years. Using an extension of the DF multiple regression methodology for analyzing twin data, no evidence was found for a linear or quadratic effect of level of cognitive ability on estimates of heritability or shared environmentality.