Testing replication of a 5-SNP set for general cognitive ability in six population samples

Implication of the APP Gene in Intellectual Abilities

Background:

Cognitive functions are highly heritable and polygenic, though the source of this genetic influence is unclear. On the neurobiological level, these functions rely on effective neuroplasticity, in which the activity-regulated cytoskeleton associated protein (ARC) plays an essential role.

Objectives:

To examine whether the ARC gene complex may contribute to the genetic components of intellectual function given the crucial role of ARC in brain plasticity and memory formation.

Methods:

The ARC complex was tested for association with intelligence (IQ) in children from the Avon Longitudinal Study of Parents and Children (ALSPAC, N = 5,165). As Alzheimer’s disease (AD) shares genetics with cognitive functioning, the association was followed up in an AD sample (17,008 cases, 37,154 controls).

Results:

The ARC complex revealed association with verbal and total IQ (empirical p = 0.027 and 0.041, respectively) in the ALSPAC. The strongest single variant signal (rs2830077; empirical p = 0.018), within the APP gene, was confirmed in the AD sample (p = 2.76E-03). Functional analyses of this variant showed its preferential binding to the transcription factor CP2.

Discussion:

This study implicates APP in childhood IQ. While follow-up studies are needed, this observation could help elucidate the etiology of disorders associated with cognitive dysfunction, such as AD.

SNP sets and reading ability: testing confirmation of a 10-SNP set in a population sample

A set of 10 SNPs associated with reading ability in 7-year-olds was reported based on initial pooled analyses of 100K SNP chip data, with follow-up testing stages using pooling and individual testing. Here we examine this association in an adolescent population sample of Australian twins and siblings (N = 1177) aged 12 to 25 years. One (rs1842129) of the 10 SNPs approached significance (P = .05) but no support was found for the remaining 9 SNPs or the SNP set itself. Results indicate that these SNPs are not associated with reading ability in an Australian population. The results are interpreted as supporting use of much larger SNP sets in common disorders where effects are small.

Genome-wide association study for femoral neck bone geometry

Poor femoral neck bone geometry at the femur is an important risk factor for hip fracture. We conducted a genome-wide association study (GWAS) of femoral neck bone geometry, examining approximately 379,000 eligible single-nucleotide polymorphisms (SNPs) in 1000 Caucasians. A common genetic variant, rs7430431 in the receptor transporting protein 3 (RTP3) gene, was identified in strong association with the buckling ratio (BR, P = 1.6 x 10(-7)), an index of bone structural instability, and with femoral cortical thickness (CT, P = 1.9 x 10(-6)). The RTP3 gene is located in 3p21.31, a region that we found to be linked with CT (LOD = 2.19, P = 6.0 x 10(-4)) in 3998 individuals from 434 pedigrees. The replication analyses in 1488 independent Caucasians and 2118 Chinese confirmed the association of rs7430431 to BR and CT (combined P = 7.0 x 10(-3) for BR and P = 1.4 x 10(-2) for CT). In addition, 350 hip fracture patients and 350 healthy control individuals were genotyped to assess the association of the RTP3 gene with the risk of hip fracture. Significant association between a nearby common SNP, rs10514713 of the RTP3 gene, and hip fracture (P = 1.0 x 10(-3)) was found. Our observations suggest that RTP3 may be a novel candidate gene for femoral neck bone geometry.

Challenges in phenotype definition in the whole-genome era: multivariate models of memory and intelligence

Refining phenotypes for the study of neuropsychiatric disorders is of paramount importance in neuroscience. Poor phenotype definition provides the greatest obstacle for making progress in disorders like schizophrenia, bipolar disorder, Attention Deficit/Hyperactivity Disorder (ADHD), and autism. Using freely available informatics tools developed by the Consortium for Neuropsychiatric Phenomics (CNP), we provide a framework for defining and refining latent constructs used in neuroscience research and then apply this strategy to review known genetic contributions to memory and intelligence in healthy individuals. This approach can help us begin to build multi-level phenotype models that express the interactions between constructs necessary to understand complex neuropsychiatric diseases. These results are available online through the http://www.phenowiki.org database. Further work needs to be done in order to provide consensus-building applications for the broadly defined constructs used in neuroscience research.

Meeting the Challenges of Neuroimaging Genetics

As research encompassing neuroimaging and genetics gains momentum, extraordinary information will be uncovered on the genetic architecture of the human brain. However, there are significant challenges to be addressed first. Not the least of these challenges is to accomplish the sample size necessary to detect subtle genetic influences on the morphometry and function of the healthy brain. Aside from sample size, image acquisition and analysis methods need to be refined in order to ensure optimum sensitivity to genetic and complementary environmental influences. Then there is the vexing issue of interpreting the resulting data. We describe how researchers from the east coast of Australia and the west coast of America have embarked upon a collaboration to meet these challenges using data currently being collected from a large-scale twin study, and offer some opinions about future directions in the field.