DNA pooling identifies QTLs on chromosome 4 for general cognitive ability in children

Using pooled data for genomic prediction in a bivariate framework with missing data

Pooling samples to derive group genotypes can enable the economically efficient use of commercial animals within genetic evaluations. To test a multivariate framework for genetic evaluations using pooled data, simulation was used to mimic a beef cattle population including two moderately heritable traits with varying genetic correlations, genotypes and pedigree data. There were 15 generations (n = 32,000; random selection and mating), and the last generation was subjected to genotyping through pooling. Missing records were induced in two ways: (a) sequential culling and (b) random missing records. Gaps in genotyping were also explored whereby genotyping occurred through generation 13 or 14. Pools of 1, 20, 50 and 100 animals were constructed randomly or by minimizing phenotypic variation. The EBV was estimated using a bivariate single-step genomic best linear unbiased prediction model. Pools of 20 animals constructed by minimizing phenotypic variation generally led to accuracies that were not different than using individual progeny data. Gaps in genotyping led to significantly different EBV accuracies (p < .05) for sires and dams born in the generation nearest the pools. Pooling of any size generally led to larger accuracies than no information from generation 15 regardless of the way missing records arose, the percentage of records available or the genetic correlation. Pooling to aid in the use of commercial data in genetic evaluations can be utilized in multivariate cases with varying relationships between the traits and in the presence of systematic and randomly missing phenotypes.

Genomic prediction using pooled data in a single-step genomic best linear unbiased prediction framework

Economically relevant traits are routinely collected within the commercial segments of the beef industry but are rarely included in genetic evaluations because of unknown pedigrees. Individual relationships could be resurrected with genomics, but this would be costly; therefore, pooling DNA and phenotypic data provide a cost-effective solution. Pedigree, phenotypic, and genomic data were simulated for a beef cattle population consisting of 15 generations. Genotypes mimicked a 50k marker panel (841 quantitative trait loci were located across the genome, approximately once per 3 Mb) and the phenotype was moderately heritable. Individuals from generation 15 were included in pools (observed genotype and phenotype were mean values of a group). Estimated breeding values (EBV) were generated from a single-step genomic best linear unbiased prediction model. The effects of pooling strategy (random and minimizing or uniformly maximizing phenotypic variation within pools), pool size (1, 2, 10, 20, 50, 100, or no data from generation 15), and generational gaps of genotyping on EBV accuracy (correlation of EBV with true breeding values) were quantified. Greatest EBV accuracies of sires and dams were observed when there was no gap between genotyped parents and pooled offspring. The EBV accuracies resulting from pools were usually greater than no data from generation 15 regardless of sire or dam genotyping. Minimizing phenotypic variation increased EBV accuracy by 8% and 9% over random pooling and uniformly maximizing phenotypic variation, respectively. A pool size of 2 was the only scenario that did not significantly decrease EBV accuracy compared with individual data when pools were formed randomly or by uniformly maximizing phenotypic variation (P > 0.05). Pool sizes of 2, 10, 20, or 50 did not generally lead to statistical differences in EBV accuracy than individual data when pools were constructed to minimize phenotypic variation (P > 0.05). Largest numerical increases in EBV accuracy resulting from pooling compared with no data from generation 15 were seen with sires with prior low EBV accuracy (those born in generation 14). Pooling of any size led to larger EBV accuracies of the pools than individual data when minimizing phenotypic variation. Resulting EBV for the pools could be used to inform management decisions of those pools. Pooled genotyping to garner commercial-level phenotypes for genetic evaluations seems plausible although differences exist depending on pool size and pool formation strategy.

Cognitive genomics: Searching for the genetic roots of neuropsychological functioning

OBJECTIVE

Human cognition has long been known to be under substantial genetic control. With the complete mapping of the human genome, genome-wide association studies for many complex traits have proliferated; however, the highly polygenic nature of intelligence has made the identification of the precise genes that influence both global and specific cognitive abilities more difficult than anticipated.

METHOD

Here, we review the latest developments in the genomics of cognition, including a discussion of methodological advances in the genetic analysis of complex traits, and shared genetic contributions to cognitive abilities and neuropsychiatric disorders.

RESULTS

A wealth of twin and family studies have provided compelling evidence for a strong heritable component of both global and specific cognitive abilities, and for the existence of "generalist genes" responsible for a large portion of the variance in diverse cognitive abilities. Increasingly sophisticated analytic tools and ever-larger sample sizes are now facilitating the identification of specific genetic and molecular underpinnings of cognitive abilities, leading to optimism regarding possibilities for novel treatments for illnesses related to cognitive function.

CONCLUSIONS

We conclude with a set of future directions for the field, which will further accelerate discoveries regarding the biological pathways relevant to cognitive abilities. These, in turn, may be further interrogated in order to link biological mechanisms to behavior. (PsycINFO Database Record

Behavioural genetics in the 21st century

Behavioural genetics will continue to flow into the mainstream of behavioural research as more behavioural scientists incorporate this approach in their research. Future research will go beyond simply asking whether and how much genetic factors influence behaviour to ask questions about development, about relations among traits, and about the interplay between nature and nurture. The identification of specific genes associated with behaviour will make it possible for behavioural scientists to ask more precise questions about how genotypes become phenotypes.

Altered GPM6A/M6 dosage impairs cognition and causes phenotypes responsive to cholesterol in human and Drosophila

Glycoprotein M6A (GPM6A) is a neuronal transmembrane protein of the PLP/DM20 (proteolipid protein) family that associates with cholesterol-rich lipid rafts and promotes filopodia formation. We identified a de novo duplication of the GPM6A gene in a patient with learning disability and behavioral anomalies. Expression analysis in blood lymphocytes showed increased GPM6A levels. An increase of patient-derived lymphoblastoid cells carrying membrane protrusions supports a functional effect of this duplication. To study the consequences of GPM6A dosage alterations in an intact nervous system, we employed Drosophila melanogaster as a model organism. We found that knockdown of Drosophila M6, the sole member of the PLP family in flies, in the wing, and whole organism causes malformation and lethality, respectively. These phenotypes as well as the protrusions of patient-derived lymphoblastoid cells with increased GPM6A levels can be alleviated by cholesterol supplementation. Notably, overexpression as well as loss of M6 in neurons specifically compromises long-term memory in the courtship conditioning paradigm. Our findings thus indicate a critical role of correct GPM6A/M6 levels for cognitive function and support a role of the GPM6A duplication for the patient's phenotype. Together with other recent findings, this study highlights compromised cholesterol homeostasis as a recurrent feature in cognitive phenotypes.

Sex-specific effects on spatial learning and memory, and sex-independent effects on blood pressure of a <3.3 Mbp rat chromosome 2 QTL region in Dahl salt-sensitive rats

Epidemiological studies have consistently found that hypertension is associated with poor cognitive performance. We hypothesize that a putative causal mechanism underlying this association is due to genetic loci affecting both blood pressure and cognition. Consistent with this notion, we reported several blood pressure (BP) quantitative trait loci (QTLs) that co-localized with navigational performance (Nav)-QTLs influencing spatial learning and memory in Dahl rats. The present study investigates a chromosome 2 region harboring BP-f4 and Nav-8 QTLs. We developed two congenic strains, S.R2A and S.R2B introgressing Dahl R-chromosome 2 segments into Dahl S chromosome 2 region spanning BP-f4 and Nav-8 QTLs. Radiotelemetric blood pressure analysis identified only S.R2A congenic rats with lower systolic blood pressure (females: -26.0 mmHg, P = 0.003; males: -30.9 mmHg, P<1×10(-5)), diastolic blood pressure (females: -21.2 mmHg, P = 0.01; males: -25.7 mmHg, P<1×10(-5)), and mean arterial pressure (females: -23.9 mmHg, P = 0.004; males: -28.0 mmHg, P<1×10(-5)) compared with corresponding Dahl S controls, confirming the presence of BP-f4 QTL on rat chromosome 2. The S.R2B congenic segment did not affect blood pressure. Testing of S.R2A, S.R2B, and Dahl S male rats in the Morris water maze (MWM) task revealed significantly decreased spatial navigation performance in S.R2A male congenic rats when compared with Dahl S male controls (P<0.05). The S.R2B congenic segment did not affect performance of the MWM task in males. The S.R2A female rats did not differ in spatial navigation when compared with Dahl S female controls, indicating that the Nav-8 effect on spatial navigation is male-specific. Our results suggest the existence of a single QTL on chromosome 2 176.6-179.9 Mbp region which affects blood pressure in both males and females and cognition solely in males.

Genetic overlap among intelligence and other candidate endophenotypes for schizophrenia

BACKGROUND

A strategy to improve genetic studies of schizophrenia involves the use of endophenotypes. Information on overlapping genetic contributions among endophenotypes may provide additional power, reveal biological pathways, and have practical implications for genetic research. Several cognitive endophenotypes, including intelligence, are likely to be modulated by overlapping genetic influences.

METHODS

We quantified potential genetic and environmental correlations among endophenotypes for schizophrenia, including sensorimotor gating, openness, verbal fluency, early visual perception, spatial working memory, and intelligence, using variance component models in 35 patients and 145 relatives from 25 multigenerational Dutch families multiply affected with schizophrenia.

RESULTS

Significant correlations were found between spatial working memory and intelligence (.45), verbal fluency and intelligence (.36), verbal fluency and spatial working memory (.20), and early visual perception and spatial working memory (.19). A strong genetic correlation (.75) accounted for 76% of the variance shared between spatial working memory and intelligence. Significant environmental correlations were found between verbal fluency and openness (.50) and between verbal fluency and spatial working memory (.58). Sensorimotor gating and openness showed few genetic or environmental correlations with other endophenotypes.

CONCLUSIONS

Our results suggest that intelligence strongly overlaps genetically with a known cognitive endophenotype for schizophrenia. Intelligence may thus be a promising endophenotype for genetic research in schizophrenia, even though the underlying genetic mechanism may still be complex. In contrast, sensorimotor gating and openness appear to represent separate genetic entities with simpler inheritance patterns and may therefore augment the detection of separate genetic pathways contributing to schizophrenia.

Detection of QTL for growth rate in the blacklip abalone (Haliotis rubra Leach) using selective DNA pooling

The objective of this study was to identify QTL for growth rate in the blacklip abalone Haliotis rubra using selective DNA pooling. Three full-sibling families of H. rubra derived from crosses of wild broodstock were used. DNA was extracted from the largest and smallest 10% of progeny and combined into two pools for each phenotypic tail. The DNA pools were typed with 139 microsatellites, and markers showing significant differences between the peak height ratios of alleles inherited from the parents were individually genotyped and analysed by interval mapping. A strong correlation (r = 0.94, P < 0.001) was found between the t-values from the analysis of pools and the t-values from the analysis of individual genotypes. Based on the interval mapping analysis, QTL were detected on nine linkage groups at a chromosome-wide P < 0.01 and one linkage group at a chromosome-wide P < 0.05. The study demonstrated that selective DNA pooling is efficient and effective as a first-pass screen for the discovery of QTL in an aquaculture species.

Addiction science and its genetics

AIM

To assess the progress and impact of genetic studies in the addictions arena and to present this information in a form accessible to the general readership of Addiction.

METHODS

Review of the evidence that genes are involved in addiction, approaches to their identification, current findings and the potential implications.

RESULTS

Family, twin and adoption studies provide strong evidence that addiction runs in families and that this is determined in part by genetic factors. Two main molecular genetic approaches, namely linkage and association, have been adopted to identify the specific genes involved. Both methods are fraught with problems. Linkage is limited by issues of sensitivity, and association by false positives. Perhaps the strongest finding in psychiatric genetics to date is the impressive effect that a single genetic variant, in the aldehyde dehydrogenase 2 gene, has on drinking behaviour and reducing the risk of developing alcohol dependence. Other findings are currently less robust; however, the implications of elucidating the genetic underpinning of addiction will be profound.

CONCLUSIONS

Addiction genetics is a developing science that has yet to prove its worth in the clinical setting.

Genetic regulation of plasma von Willebrand factor levels: quantitative trait loci analysis in a mouse model

BACKGROUND

The genetic factors responsible for the wide variation in plasma von Willebrand factor (VWF) levels observed among individuals are largely unknown, although these genes are also likely to contribute to variability in the severity of von Willebrand disease (VWD) and other bleeding and thrombotic disorders. We have previously mapped two genes contributing to the regulation of plasma VWF levels in mice (Mvwf1 on chromosome 11 and Mvwf2 on chromosome 6).

OBJECTIVE

To identify additional quantitative trait loci (QTL) contributing to the genetic regulation of murine plasma VWF levels.

METHODS

To map genetic loci contributing to the > 7-fold difference in plasma VWF levels between two mouse strains (A/J and CASA/RkJ), high-density individual genotyping and R/qtl analyses were applied to a previously generated set of approximately 200 F2 mice obtained from an intercross of these two inbred lines.

RESULTS

Genomic loci for two additional candidate VWF modifier genes were identified: Mvwf3 on chromosome 4 and Mvwf4 on chromosome 13. These loci demonstrate primarily epistatic effects when co-inherited with two CASA/RkJ Vwf alleles, although Mvwf4 may also exert a small, independent, additive effect.

CONCLUSIONS

Mvwf3 and Mvwf4, combined with the effect of Mvwf2, explain approximately 45% of the genetic variation in plasma VWF level among the A/J and CASA/RkJ strains. Mvwf3 and Mvwf4 exhibit homology of synteny to three human chromosomal segments (on chromosomes 1, 5 and 6) previously reported by the Genetic Analysis of Idiopathic Thrombophilia (GAIT) study, suggesting that orthologs of Mvwf3 and Mvwf4 may also encode important VWF modifier genes in humans.

Genomic DNA pooling for whole-genome association scans in complex disease: empirical demonstration of efficacy in rheumatoid arthritis

A pragmatic approach that balances the benefit of a whole-genome association (WGA) experiment against the cost of individual genotyping is to use pooled genomic DNA samples. We aimed to determine the feasibility of this approach in a WGA scan in rheumatoid arthritis (RA) using the validated human leucocyte antigen (HLA) and PTPN22 associations as test loci. A total of 203 269 single-nucleotide polymorphisms (SNPs) on the Affymetrix 100K GeneChip and Illumina Infinium microarrays were examined. A new approach to the estimation of allele frequencies from Affymetrix hybridization intensities was developed involving weighting for quality signals from the probe quartets. SNPs were ranked by z-scores, combined from United Kingdom and New Zealand case-control cohorts. Within a 1.7 Mb HLA region, 33 of the 257 SNPs and at PTPN22, 21 of the 45 SNPs, were ranked within the top 100 associated SNPs genome wide. Within PTPN22, individual genotyping of SNP rs1343125 within MAGI3 confirmed association and provided some evidence for association independent of the PTPN22 620W variant (P=0.03). Our results emphasize the feasibility of using genomic DNA pooling for the detection of association with complex disease susceptibility alleles. The results also underscore the importance of the HLA and PTPN22 loci in RA aetiology.

Computerized lifelong mentoring support using robot for autistic individuals

Developmental diversity in childhood is transformed into personality variation in adulthood. This view is now revalued through an ongoing paradigm shift in the field of developmental conditions, the transition from the qualitative dichotomy perspective to the quantitative concept. In the quantitative concept, autism is not a disease nor a developmental qualitative disorder, but a behavioral extreme in individual variation. Although the traditional qualitative view cannot interpret the recent worldwide prevalence of autism, the increase in the reported number of cases with autism and border cases can be easily explained by a dimensional exploration in which the primary autistic phenotype is regarded as an evolutional superiority. Therefore, the only suitable intervention is mentoring which provides a powerful lifelong support for higher social achievement in individuals with autism. Here, we hypothesize the coming mentoring circumstances for autistic individuals in the near future. Ongoing progress in robot and computer technology might allow the guardians to leave the major part of mentoring support to an individualized robot, and the 'folk physics' tendency in individuals with autism could facilitate the spread of the mentoring support system. The development of the robot mentor software may be simple because of the uniformity and stereotypy of the behavior patterns in individuals with autism. With the help of the robot mentor and under its guidance, autistic people might enjoy their social life and contribute to the prosperity of the human society to the maximum degree. Because the future population ratio of autistics/non-autistics might be reversed according to the current trend of the prevalence, mentoring robot programs for autistic individuals should be developed without delay as a novel preliminary activity in the Jiminy Cricket movement, which is a campaign to reverse the estrangement of the present majority from autism and to increase the number of mentors for autistic individuals. In this article, prerequisites for the mentoring program of the robot mentor are expected and discussed.

“Scientific roots” of dualism in neuroscience

Although the dualistic concept is unpopular among neuroscientists involved in experimental studies of the brain, neurophysiological literature is full of covert dualistic statements on the possibility of understanding neural mechanisms of human consciousness. Particularly, the covert dualistic attitude is exhibited in the unwillingness to discuss neural mechanisms of consciousness, leaving the problem of consciousness to psychologists and philosophers. This covert dualism seems to be rooted in the main paradigm of neuroscience that suggests that cognitive functions, such as language production and comprehension, face recognition, declarative memory, emotions, etc., are performed by neural networks consisting of simple elements. I argue that neural networks of any complexity consisting of neurons whose function is limited to the generation of electrical potentials and the transmission of signals to other neurons are hardly capable of producing human mental activity, including consciousness. Based on results obtained in physiological, morphological, clinical, and genetic studies of cognitive functions (mainly linguistic ones), I advocate the hypothesis that the performance of cognitive functions is based on complex cooperative activity of "complex" neurons that are carriers of "elementary cognition." The uniqueness of human cognitive functions, which has a genetic basis, is determined by the specificity of genes expressed by these "complex" neurons. The main goal of the review is to show that the identification of the genes implicated in cognitive functions and the understanding of a functional role of their products is a possible way to overcome covert dualism in neuroscience.

Investigating cognitive genetics and its implications for the treatment of cognitive deficit

Cognitive impairment in the elderly, caused by either normal ageing process or dementia, is an increasing problem in developed countries that has enormous social and economic considerations. Research investigating the genetic basis of cognition is a new and rapidly developing field that may aid in the development of new treatments for age-related cognitive deficit. Over the past 6 years, a number of quantitative trait loci (QTLs) have been associated with cognitive functioning in humans including loci within the genes catechol-o-methyltransferase, brain-derived neurotrophic factor, muscle segment homeobox 1, serotonin transporter 2A (HTR2A), cholinergic muscarinic receptor 2, cathepsin D, metabotrophic glutamate receptor and most recently the class II human leukocyte antigens. Unfortunately, inconsistency within the literature, which is a hallmark of almost all association studies investigating complex diseases and traits, is casting doubt as to which genes are truly associated with cognition and which are a result of Type 2 error. This review will highlight implicated intelligence QTLs, examine the probable reasons for the current discrepancies between reports and discuss the potential advantages that may be procured from the study of cognitive genetics.

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.

Interspecies synteny mapping identifies a quantitative trait locus for bone mineral density on human chromosome Xp22

Bone mineral density (BMD) is a complex trait with a strong genetic component and an important predictor of osteoporotic fracture risk. Here we report the use of a cross-species strategy to identify genes that regulate BMD, proceeding from quantitative trait mapping in mice to association mapping of the syntenic region in the human genome. We identified a quantitative trait locus (QTL) on the mouse X-chromosome for post-maturity change in spine BMD in a cross of SAMP6 and AKR/J mice and conducted association mapping of the syntenic region on human chromosome Xp22. We studied 76 single nucleotide polymorphisms (SNP) from the human region in two sets of DNA pools prepared from individuals with lumbar spine-BMD (LS-BMD) values falling into the top and bottom 13th percentiles of a population-based study of 3100 post-menopausal women. This procedure identified a region of significant association for two adjacent SNP (rs234494 and rs234495) within the Xp22 locus (P<0.001). Individual genotyping for rs234494 in the BMD pools confirmed the presence of an association for alleles (P=0.018) and genotypes (P=0.008). Analysis of rs234494 and rs234495 in 1053 women derived from the same population who were not selected for BMD values showed an association with LS-BMD for rs234495 (P=0.01) and for haplotypes defined by both SNP (P=0.002). Our study illustrates that interspecies synteny can be used to identify and refine QTL for complex traits and represents the first example where a human QTL for BMD regulation has been mapped using this approach.

A genomewide scan for intelligence identifies quantitative trait loci on 2q and 6p

Between 40% and 80% of the variation in human intelligence (IQ) is attributable to genetic factors. Except for many rare mutations resulting in severe cognitive dysfunction, attempts to identify these factors have not been successful. We report a genomewide linkage scan involving 634 sibling pairs designed to identify chromosomal regions that explain variation in IQ. Model-free multipoint linkage analysis revealed evidence of a significant quantitative-trait locus for performance IQ at 2q24.1-31.1 (LOD score 4.42), which overlaps the 2q21-33 region that has repeatedly shown linkage to autism. A second region revealed suggestive linkage for both full-scale and verbal IQs on 6p25.3-22.3 (LOD score 3.20 for full-scale IQ and 2.33 for verbal IQ), overlapping marginally with the 6p22.3-21.31 region implicated in reading disability and dyslexia.

Accurate determination of microsatellite allele frequencies in pooled DNA samples

Pooling of DNA samples instead of individual genotyping can speed up genetic association studies. However, for microsatellite markers, the electrophoretic pattern of DNA pools can be complex, and procedures for deriving allele frequencies are often confounded by PCR-induced stutter artefacts. We have developed a mathematical procedure to remove stutter noise and accurately determine allele frequencies in pools. A stutter correction model can be reliably derived from one standard 'training set' of the same 10 individual DNA samples for each marker, which can also include heterozygous patterns with partially overlapping peaks. Compared with earlier methods, this reduces the number of genotypes needed in the training set considerably, and allows standardization of analyses for different markers. Moreover, the use of a procedure that fits all data simultaneously makes the method less sensitive to aberrant data. The model was tested with 34 markers, 18 of which were newly defined from human sequence data. Allele frequencies derived from stutter-corrected DNA pool patterns were compared with the summed individual genotyping results of all the individuals in the pools (n = 109 and n = 64). We show that the model is robust and accurately extracts allele frequencies from pooled DNA samples for 32 of the 34 microsatellite markers tested. Finally, we performed a case-control study in celiac disease and found that weakly associated disease alleles, identified by individual genotyping, were only detectable in pools after stutter correction. This efficient method for correcting stutter artefacts in microsatellite markers enables large-scale genetic association studies using DNA pools to be performed.

MaGIC: a program to generate targeted marker sets for genome-wide association studies

High-throughput genotyping technologies such as DNA pooling and DNA microarrays mean that whole-genome screens are now practical for complex disease gene discovery using association studies. Because it is currently impractical to use all available markers, a subset is typically selected on the basis of required saturation density. Restricting markers to those within annotated genomic features of interest (e.g., genes or exons) or within feature-rich regions, reduces workload and cost while retaining much information. We have designed a program (MaGIC) that exploits genome assembly data to create lists of markers correlated with other genomic features. Marker lists are generated at a user-defined spacing and can target features with a user-defined density. Maps are in base pairs or linkage disequilibrium units (LDUs) as derived from the International HapMap data, which is useful for association studies and fine-mapping. Markers may be selected on the basis of heterozygosity and source database, and single nucleotide polymorphism (SNP) markers may additionally be selected on the basis of validation status. The import function means the method can be used for any genomic features such as housekeeping genes, long interspersed elements (LINES), or Alu repeats in humans, and is also functional for other species with equivalent data. The program and source code is freely available at http://cogent.iop.kcl.ac.uk/MaGIC.cogx.

Intelligence: genetics, genes, and genomics

More is known about the genetics of intelligence than about any other trait, behavioral or biological, which is selectively reviewed in this article. Two of the most interesting genetic findings are that heritability of intelligence increases throughout the life span and that the same genes affect diverse cognitive abilities. The most exciting direction for genetic research on intelligence is to harness the power of the Human Genome Project to identify some of the specific genes responsible for the heritability of intelligence. The next research direction will be functional genomics--for example, understanding the brain pathways between genes and intelligence. Deoxyribonucleic acid (DNA) will integrate life sciences research on intelligence; bottom-up molecular biological research will meet top-down psychological research in the brain.

A whole genome screen for association in Polish multiple sclerosis patients

We have performed the first systematic search for MS susceptibility genes completed in the Polish population. This screen was performed using 6000 microsatellite markers typed in pooled DNA from cases (n=200), controls (n=200) and trio families (n=129). Five associated markers are identified, one (D6S2444) from the HLA region and four are from novel regions not previously associated with MS, 2p16 (D2S2153), 3p13 (D3S3568), 7p22 (D7S2521) and 15q26 (D15S649).

Two genome-wide linkage disequilibrium screens in Scandinavian multiple sclerosis patients

We report the first two genome-wide screens for linkage disequilibrium between putative multiple sclerosis (MS) susceptibility genes and genetic markers performed in the genetically homogenous Scandinavian population, using 6000 microsatellite markers and DNA pools of approximately 200 MS cases and 200 controls in each screen. Usable data were achieved from the same 3331 markers in both screens. Nine markers from eight genomic regions (1p33, 3q13, 6p21, 6q14, 7p22, 9p21, 9q21 and Xq22) were identified as potentially associated with MS in both screens.

CHIP: Defining a dimension of the vulnerability to attention deficit hyperactivity disorder (ADHD) using sibling and individual data of children in a community-based sample

We are taking a quantitative trait approach to the molecular genetic study of attention deficit hyperactivity disorder (ADHD) using a truncated case-control association design. An epidemiological sample of children aged 5 to 15 years was evaluated for symptoms of ADHD using a parent rating scale. Individuals scoring high or low on this scale were selected for further investigation with additional questionnaires and DNA analysis. Data in studies like this are typically complicated. In the study reported on here, individuals have from 1 to 4 questionnaires completed on them and the sample is composed of a mixture of singletons and siblings. In this paper, we describe how we used a genetic hierarchical model to fit our data, together with a twin dataset, in order to estimate genetic factor loadings. Correlation matrices were estimated for our data using a maximum likelihood approach to account for missing data. We describe how we used these results to create a composite score, the heritability of which was estimated to be acceptably high using the twin dataset. This score measures a quantitative dimension onto which molecular genetic data will be mapped.

Linkage and associated studies of schizophrenia

Genetic epidemiology has provided consistent evidence over many years that schizophrenia has a genetic component, and that this genetic component is complex, polygenic, and involves epistatic interaction between loci. Molecular genetics studies have, however, so far failed to identify any DNA variant that can be demonstrated to contribute to either liability to schizophrenia or to any identifiable part of the underlying pathology. Replication studies of positive findings have been difficult to interpret for a variety of reasons. First, few have reproduced the initial findings, which may be due either to random variation between two samples in the genetic inputs involved, or to a lack of power to replicate an effect at a given alpha level. Where positive data have been found in replication studies, the positioning of the locus has been unreliable, leading no closer to positional cloning of genes involved. However, an assessment of all the linkage studies performed over the past ten years does suggest a number of regions where positive results are found numerous times. These include regions on chromosomes 1, 2, 4, 5, 6, 7, 8, 9, 10, 13, 15, 18, 22 and the X. All of these data are critically reviewed and their locations compared. Reasons for the difficulty in obtaining consistent results and possible strategies for overcoming them are discussed. Am. J. Med. Genet. (Semin. Med. Genet.) 97:23-44, 2000.

Identification of a single QTL, Mptp1, for susceptibility to MPTP-induced substantia nigra pars compacta neuron loss in mice

The loss of substantia nigra pars compacta (SNpc) neurons seen in idiopathic Parkinson's disease is hypothesized to result from a genetic susceptibility to an unknown environmental toxin. MPTP has been used as a prototypical toxin, since exposure to this drug results in variable SNpc cell death in several vertebrate species, including man and mouse. Previously, we have shown that C57BL/6J mice are sensitive to this compound, while Swiss-Webster mice are resistant. In this study, we intercrossed these mouse strains to map quantitative trait loci (QTL) for MPTP sensitivity. Using genome wide PCR analysis, we found that a single major QTLs, Mptp1, located near the distal end of chromosome 1 between D1Mit113 and D1Mit293, accounts for the majority of the strain sensitivity to MPTP.

High-throughput analysis of informative CYP2D6 compound haplotypes

We describe a high-throughput protocol for detecting key polymorphisms in the drug-metabolizing enzyme gene CYP2D6 and a number of linked microsatellites that is both fast and relatively inexpensive to perform. This approach employs GeneScan technology to enable a researcher to determine rapidly the status of seven simple nucleotide polymorphisms in CYP2D6 and also to assay repeat number variation at five closely linked dinucleotide microsatellite loci. The method requires only three PCRs and two GeneScan runs per sample. We anticipate that this will be of value to researchers in three different ways: (1) rapid discrimination of common CYP2D6 alleles, (2) high-resolution haplotyping for association studies involving chromosome 22q13.1 using microsatellite variation, and (3) generation of compound haplotypes for investigating the evolution of CYP2D6 variation. We also report compound haplotype frequencies for an Ashkenazi Jewish and a British sample.

Cathepsin D exon 2 polymorphism associated with general intelligence in a healthy older population

General intelligence is a heritable trait that is a risk factor for both the onset of dementia and the rate of cognitive decline in community-dwelling older persons. Previous studies screening for quantitative trait loci (QTLs) that influence general intelligence in healthy individuals have identified four loci, two of which are located within the genes insulin-like growth factor 2 receptor (IGF2R) and the Msx1 homeobox. Here, we report the finding of another QTL associated with general intelligence that is located within exon 2 of the cathepsin D (CTSD) gene. A group of 767 healthy adults with a follow-up period of over 15 years have been analyzed for cross-sectional and longitudinal trends in cognitive change using the Heim intelligence test score (AH4-1). We observed a significant association (P = 0.01) between a functional C > T (Ala > Val) transition within exon 2 of the CTSD gene that increases the secretion of pro-CTSD from the cell, and the AH4-1 score at initial testing on entry to the longitudinal study. Interestingly, CTSD is transported by IGF2R from the trans Golgi network to the lysosome.

Family-based association tests for quantitative traits using pooled DNA

Interest in whole-genome QTL mapping has spurred efforts to reduce the cost of studies now based primarily on individual genotyping. Pooled DNA tests are a possible solution, and understanding how measurement error affects test power could assist in study design. Here we describe pooled tests explicitly optimised for measurement error, including family-based tests robust to population stratification. Our results suggest that pooled DNA whole-genome screens may be feasible with current instruments.

Quantitative technologies for allele frequency estimation of SNPs in DNA pools

We have compared several genotyping methods to assess their applicability to single nucleotide polymorphism (SNP) allele frequency estimation in DNA pools. The accuracy of these methods (restriction fragment length polymorphism, real-time pyrophosphate DNA sequencing, single base extension with fluorescently labeled ddNTPs, homogeneous 5'-nuclease assay, and MALDI-TOF mass spectrometry) was tested by calculating the standard deviation among heterozygous individuals (which are natural DNA pools with 50% representation of each allele) and by estimating allele frequency in artificial pools. We show that although the methods differ in their accuracy, they can all serve for quantification of allele frequency in DNA pools with reasonable accuracy. We found that the influence of the error variance attributed to pool construction on quantification accuracy is insignificant and is SNP dependent.

Validation of single nucleotide polymorphism quantification in pooled DNA samples with SNaPIT. A glycosylase-mediated methods for polymorphism detection method

Association studies using genome scans to identify quantitative trait loci for multifactorial disorders, with anything approaching reasonable power, have been compromised by the need for a very dense array of genetic markers and large numbers of affected individuals. These requirements impose enormous burdens on the genotyping capacity for most laboratories. DNA pooling has been proposed as a possible approach to reduce genotyping costs and effort. We report on the application of the SNaPIT technology to evaluate allele frequencies in pooled DNA samples and conclude that it offers a cost effective, efficient and accurate estimator and provides several advantages over competing technologies in this regard.

The genetic basis for psychiatric illness in man

Following the influential genetic studies of Heston and Kety, there has been growing acceptance of the role of genes in determining behaviour. It is now recognized that most types of behaviour, from normal variations in traits such as personality to complex psychiatric disorders, are influenced not only by environmental factors but also by multiple genes. While twin and adoption studies have been vital in demonstrating the heritability of behaviour, the focus is now on the identification of the genes involved using the molecular genetic strategies linkage analysis and allelic association. This article will discuss techniques that have been used in psychiatric genetics, and how they have advanced our understanding of complex behaviour.

A whole genome screen for linkage disequilibrium in multiple sclerosis confirms disease associations with regions previously linked to susceptibility

Linkage analysis in multiplex families has provisionally identified several genomic regions where genes influencing susceptibility to multiple sclerosis are likely to be located. It is anticipated that association mapping will provide a higher degree of resolution, but this more powerful approach is limited by the substantial genotyping effort required. Here, we describe the first use of DNA pooling to screen the whole genome for association in multiple sclerosis based on a 0.5 cM map of microsatellite markers and using four DNA pools derived from cases (n = 216), controls (n = 219) and trio families (n = 745 affected individuals and their 1490 parents). The 10 markers showing the greatest evidence for association with multiple sclerosis that emerge from this analysis include three from the HLA region on chromosome 6p (D6S1615, D6S2444 and TNFa), providing a positive control for the method, four from regions previously identified by linkage analysis in UK multiplex families (two mapping to chromosome 17q GCT6E11 and D17S1535; one to chromosome 1p GGAA30B06; and one to 19q D19S585), and three from novel sites with respect to linkage analysis (D1S1590 at 1q; D2S2739 at 2p; and D4S416 at 4q). Our results thus provide further supporting evidence for the candidature of 6p, 17q, 19q and 1p as regions encoding susceptibililty genes for multiple sclerosis. The protocol used in this UK-based study is now being extended to 18 additional sites in Europe in order to search for susceptibility genes shared between populations of common ancestry, as well as those that exert ethnically more restricted effects.

High-throughput single-nucleotide polymorphism genotyping by fluorescent competitive allele-specific polymerase chain reaction (SNiPTag)

Single nucleotide polymorphisms (SNPs) are becoming widely recognized as the new currency for gene mapping as increasing numbers are discovered. Here we outline a method for their rapid analysis based on an allele-specific polymerase chain reaction (PCR) which employs a competitive approach, whereby both allele-specific primers are present in the same reaction and carry different fluorescent labels. This procedure is simple and amenable to high-throughput genotyping using conventional automated sequencing equipment, and no post-PCR modifications are required. Verification of the procedure was carried out by comparison of results derived by this method with those from restriction enzyme digestion of the ALDH2 exon 12 functional polymorphism (Glu-487-Lys) in 109 individuals. Additionally, we have examined all combinations of nucleotide substitutions and shown them to be differentiated by this method. As proof of concept, several assays were combined and loaded on a single gel lane/capillary to substantially improve throughput. This was made possible by designing the PCR products to be of different lengths and no interference was observed between products differing in size by only six nucleotides. We outline a number of test assays for well-characterized SNPs in human candidate genes for behavioral disorders.

Optimal selection strategies for QTL mapping using pooled DNA samples

The cost of large-scale association studies may be reduced substantially by analysis of pooled DNA from multiple individuals. Here we examine the optimal symmetric and asymmetric designs for pooling experiments for quantitative traits under a range of assumptions about the underlying genetic model and the sources of experimental errors in allele frequency estimation. The results indicate that, in the absence of experimental errors and for common alleles with additive effects, a symmetric pooling scheme comparing the top 27% with the bottom 27% of the trait distribution is optimal, extracting 80% the total information available. A symmetric design is not optimal for rare or recessive alleles, which require asymmetric (or other) pooling strategies. Allele frequency measurement errors reduce the optimal pooling fraction as well as the overall efficiency of the pooling design. In contrast, random variation in the amount of DNA contributed by individuals to a pool reduces only the overall efficiency of the pooling design. Our results emphasize the importance of minimising experimental errors and suggest a pooling fraction of around 20%.

Role of individual neurons and neural networks in cognitive functioning of the brain: a new insight

The prevailing concept in modern neuroscience is that neuron networks play a dominant role in the functioning of the nervous system, whereas the role of individual neurons is rather insignificant. This concept suggests that "individuality" of single neurons is primarily determined by their place in a network rather than their intrinsic properties. Here I argue that individual neurons may play an important, if not decisive, role in performing cognitive functions of the brain. This tentative viewpoint is supported by experimental and clinical insights into disorders of cognitive functions and by genetic studies of cognitive abilities and disabilities. The results obtained in these studies indicate that many specific cognitive functions are carried out by groups of highly specialized neurons whose roles in performing these functions are genetically predetermined and their activity could not be substituted by the activity of other neurons. In this context, the main role of neural networks and intercellular interactions is to form dynamic ensembles of neurons involved in performing a given cognitive function.

QTL association analysis of the DRD4 exon 3 VNTR polymorphism in a population sample of children screened with a parent rating scale for ADHD symptoms

Current developments in molecular genetics have led to a rapid increase in research aimed at the identification of genetic variation that influences complex human phenotypes. One phenotype that has aroused a great deal of interest is the behavioral trait hyperactivity and the related clinical disorder attention-deficit hyperactivity disorder (ADHD). The driving force behind the molecular genetic research in this area is the overwhelming evidence from quantitative genetic studies that show high heritablility (h(2) = 0.7-0.9) for the behaviors characterizing the diagnosis of ADHD, whether the disorder is viewed as a categorical entity or a continuous trait. To date, molecular studies have aimed at identifying susceptibility genes for ADHD, defined using operational diagnostic criteria, and have focused on variation within genes that regulate dopamine neurotransmission. Several studies report ADHD to be associated with the 7-repeat allele of a 48 bp repeat polymorphism (DRD4-7) in exon 3 of the dopamine D4 receptor gene (DRD4). In this study, we take a dimensional perspective of ADHD and examine the relationship of this DRD4 polymorphism in a sample of children selected from the general population on the basis of high and low scores on the five ADHD items of the Strengths and Difficulties Questionnaire (SDQ) as rated by their parents. We found a significant relationship between DRD4-7 and high-scoring individuals [chi-square = 8.63; P = 0.003; OR = 2.09 (95% CI 1.24 < OR < 3.54), F-statistic = 7.245; P = 0.008].

Genetics, environment and cognitive abilities: review and work in progress towards a genome scan for quantitative trait locus associations using DNA pooling

BACKGROUND

Multivariate genetic research indicates that genetic effects on diverse cognitive abilities are general rather than specific or modular. General cognitive ability (g), a key factor in learning and memory, is among the most heritable behavioural traits.

AIMS

To give a brief overview of quantitative genetic research on g and to describe initial results from a programme of research that aims to identify genes responsible for the substantial heritability of general cognitive ability.

METHOD

The research uses a new technique called DNA pooling, which combines DNA from individuals within a group and makes it feasible to screen thousands of DNA markers for a systematic scan of the genome for associations between DNA markers and g. Two independent samples of children with very high g scores and two control samples of children with average g scores were compared in a systematic scan of 147 markers on chromosome 4 and 66 markers on chromosome 22.

RESULTS

Three replicated associations on chromosome 4 were identified using DNA pooling and confirmed using individual genotyping.

CONCLUSIONS

These first results of the application of DNA pooling in systematic analysis of allelic association are encouraging.

No association between apolipoprotein E polymorphisms and general cognitive ability in children

In this work we explored the hypothesis that variation in the gene encoding apolipoprotein E (ApoE) is a factor modifying general cognitive ability (g). A case control sample of 101 high g and 101 average g children was scored for ApoE genotypes and two variants in the transcriptional regulatory region of the gene (Th1/E47cs and -491 AT). No evidence of association between these polymorphisms and g was found. We conclude that variation at these loci is not a factor with a measurable impact on general cognitive ability in the healthy population.

The genetics of g in human and mouse

The g factor refers to the substantial overlap that exists between individual differences in diverse cognitive processes in humans. In this article, I argue that a mouse model of g could provide a powerful analytic tool for exploring cognitive processes that are linked functionally by genes.

Determination of SNP allele frequencies in pooled DNAs by primer extension genotyping and denaturing high-performance liquid chromatography

By testing DNA pools rather than single samples the number of tests for a case-control association study can be decreased to only two for each marker: one on the patient and one on the control pool. A fundamental requirement is that each pool represents the frequency of the markers in the corresponding population beyond the influence of experimental errors. Consequently the latter must be carefully determined. To this aim, we prepared pools of different size (49-402 individuals) with accurately quantified DNAs, estimated the allelic frequencies in the pools of two SNPs by primer extension genotyping followed by DHPLC analysis and compared them with the real frequencies determined in the single samples. Our data show that (1) the method is highly reproducible: the standard deviation of repeated determinations was +/-0.014; (2) the experimental error (i.e., the discrepancy between the estimated and real frequencies) was +/-0.013 (95% C.I.: 0.0098-0.0165). The magnitude of this error was not correlated to the pool size or to the type of SNP. The effect of the observed experimental error on the power of the association test was evaluated. We conclude that this method constitutes an efficient tool for high-throughput association screenings provided that the experimental error is low. We therefore recommend that before a pool is used for extensive association studies, its quality, i.e., the experimental error, is verified by determining the difference between estimated and real frequencies for at least one marker.

DNA

The authors predict that in a few years, many areas of psychology will be awash in specific genes responsible for the widespread influence of genetics on behavior. As the focus shifts from finding genes (genomics) to understanding how genes affect behavior (behavioral genomics), it is important for the future of psychology as a science that pathways between genes and behavior be examined not only at the molecular biological level of cells or the neuroscience level of the brain but also at the psychological level of analysis. After a brief overview of quantitative genetic research, the authors describe how genes that influence complex traits like behavioral dimensions and disorders in human and nonhuman animals are being found. Finally, the authors discuss behavioral genomics and predict that DNA will revolutionize psychological research and treatment early in the 21st century.

Chasing behaviour genes into the next millennium

Both linkage and association strategies are appropriate for the characterization of genes implicated in human behavioural dimensions and disorders. For the foreseeable future, association studies involving whole-genome scanning will combine strategies using both single-nucleotide and simple-sequence-repeat polymorphisms.

Psychiatric genetics: back to the future

For the last decade or more geneticists have been predicting that advances in molecular genetics are going to revolutionize our understanding of psychiatric disorders and human behavior. However, with a few exceptions, these expectations have yet to be fulfilled. As the century draws to a close and we contemplate the prospect of the complete sequence of the human genome it seems timely to consider the state of the field and to consider carefully how it might advance, the problems to be faced and the resources required. Molecular Psychiatry (2000) 5, 22-31.