Keith Humphreys

Gains in fluid intelligence after training non-verbal reasoning in 4-year-old children: a controlled, randomized study.

Fluid intelligence (Gf) predicts performance on a wide range of cognitive activities, and children with impaired Gf often experience academic difficulties. Previous attempts to improve Gf have been hampered by poor control conditions and single outcome measures. It is thus still an open question whether Gf can be improved by training. This study included 4-year-old children (N = 101) who performed computerized training (15 min/day for 25 days) of either non-verbal reasoning, working memory, a combination of both, or a placebo version of the combined training. Compared to the placebo group, the non-verbal reasoning training group improved significantly on Gf when analysed as a latent variable of several reasoning tasks. Smaller gains on problem solving tests were seen in the combination training group. The group training working memory improved on measures of working memory, but not on problem solving tests. This study shows that it is possible to improve Gf with training, which could have implications for early interventions in children.

Genome-wide association study of follicular lymphoma identifies a risk locus at 6p21.32

To identify susceptibility loci for non-Hodgkin lymphoma subtypes, we conducted a three-stage genome-wide association study. We identified two variants associated with follicular lymphoma at 6p21.32 (rs10484561, combined P = 1.12 × 10−29 and rs7755224, combined P = 2.00 × 10−19; r2 = 1.0), supporting the idea that major histocompatibility complex genetic variation influences follicular lymphoma susceptibility. We also found confirmatory evidence of a previously reported association between chronic lymphocytic leukemia/small lymphocytic lymphoma and rs735665 (combined P = 4.24 × 10−9).

Oestrogen receptor alpha gene haplotype and postmenopausal breast cancer risk: a case control study.

IntroductionOestrogen receptor α, which mediates the effect of oestrogen in target tissues, is genetically polymorphic. Because breast cancer development is dependent on oestrogenic influence, we have investigated whether polymorphisms in the oestrogen receptor α gene (ESR1) are associated with breast cancer risk.MethodsWe genotyped breast cancer cases and age-matched population controls for one microsatellite marker and four single-nucleotide polymorphisms (SNPs) in ESR1. The numbers of genotyped cases and controls for each marker were as follows: TAn, 1514 cases and 1514 controls; c.454-397C → T, 1557 cases and 1512 controls; c.454-351A → G, 1556 cases and 1512 controls; c.729C → T, 1562 cases and 1513 controls; c.975C → G, 1562 cases and 1513 controls. Using logistic regression models, we calculated odds ratios (ORs) and 95% confidence intervals (CIs). Haplotype effects were estimated in an exploratory analysis, using expectation-maximisation algorithms for case-control study data.ResultsThere were no compelling associations between single polymorphic loci and breast cancer risk. In haplotype analyses, a common haplotype of the c.454-351A → G or c.454-397C → T and c.975C → G SNPs appeared to be associated with an increased risk for ductal breast cancer: one copy of the c.454-351A → G and c.975C → G haplotype entailed an OR of 1.19 (95% CI 1.06–1.33) and two copies with an OR of 1.42 (95% CI 1.15–1.77), compared with no copies, under a model of multiplicative penetrance. The association with the c.454-397C → T and c.975C → G haplotypes was similar. Our data indicated that these haplotypes were more influential in women with a high body mass index. Adjustment for multiple comparisons rendered the associations statistically non-significant.ConclusionWe found suggestions of an association between common haplotypes in ESR1 and the risk for ductal breast cancer that is stronger in heavy women.

Mammographic Density Reduction Is a Prognostic Marker of Response to Adjuvant Tamoxifen Therapy in Postmenopausal Patients With Breast Cancer

PURPOSE Tamoxifen treatment is associated with a reduction in mammographic density and an improved survival. However, the extent to which change in mammographic density during adjuvant tamoxifen therapy can be used to measure response to treatment is unknown. PATIENTS AND METHODS Overall, 974 postmenopausal patients with breast cancer who had both a baseline and a follow-up mammogram were eligible for analysis. On the basis of treatment information abstracted from medical records, 474 patients received tamoxifen treatment and 500 did not. Mammographic density was measured by using an automated thresholding method and expressed as absolute dense area. Change in mammographic density was calculated as percentage change from baseline. Survival analysis was performed by using delayed-entry Cox proportional hazards regression models, with death as a result of breast cancer as the end point. Analyses were adjusted for a range of patient and tumor characteristics. RESULTS During a 15-year follow-up, 121 patients (12.4%) died from breast cancer. Women treated with tamoxifen who experienced a relative density reduction of more than 20% between baseline and first follow-up mammogram had a reduced risk of death as a result of breast cancer of 50% (hazard ratio, 0.50; 95% CI, 0.27 to 0.93) compared with women with stable mammographic density. In the no-tamoxifen group, there was no statistically significant association between mammographic density change and survival. The survival advantage was not observed when absolute dense areas at baseline or follow-up were evaluated separately. CONCLUSION A decrease in mammographic density after breast cancer diagnosis appears to serve as a prognostic marker for improved long-term survival in patients receiving adjuvant tamoxifen, and these data should be externally validated.

GWAS of follicular lymphoma reveals allelic heterogeneity at 6p21.32 and suggests shared genetic susceptibility with diffuse large B-cell lymphoma.

Non-Hodgkin lymphoma (NHL) represents a diverse group of hematological malignancies, of which follicular lymphoma (FL) is a prevalent subtype. A previous genome-wide association study has established a marker, rs10484561 in the human leukocyte antigen (HLA) class II region on 6p21.32 associated with increased FL risk. Here, in a three-stage genome-wide association study, starting with a genome-wide scan of 379 FL cases and 791 controls followed by validation in 1,049 cases and 5,790 controls, we identified a second independent FL–associated locus on 6p21.32, rs2647012 (ORcombined = 0.64, Pcombined = 2×10−21) located 962 bp away from rs10484561 (r2<0.1 in controls). After mutual adjustment, the associations at the two SNPs remained genome-wide significant (rs2647012:ORadjusted = 0.70, Padjusted = 4×10−12; rs10484561:ORadjusted = 1.64, Padjusted = 5×10−15). Haplotype and coalescence analyses indicated that rs2647012 arose on an evolutionarily distinct haplotype from that of rs10484561 and tags a novel allele with an opposite (protective) effect on FL risk. Moreover, in a follow-up analysis of the top 6 FL–associated SNPs in 4,449 cases of other NHL subtypes, rs10484561 was associated with risk of diffuse large B-cell lymphoma (ORcombined = 1.36, Pcombined = 1.4×10−7). Our results reveal the presence of allelic heterogeneity within the HLA class II region influencing FL susceptibility and indicate a possible shared genetic etiology with diffuse large B-cell lymphoma. These findings suggest that the HLA class II region plays a complex yet important role in NHL.

High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer

IntroductionMammographic density (MD) is a strong, independent risk factor for breast cancer, but measuring MD is time consuming and reader dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image-processing software for the fully automated analysis of MD and penalized regression to construct a measure that mimics a well-established semiautomated measure (Cumulus). We also describe measures that incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk.MethodsWe randomly partitioned our dataset into a training set for model building (733 cases, 748 controls) and a test set for model assessment (765 cases, 747 controls). The Pearson product-moment correlation coefficient (r) was used to compare the MD measurements by Cumulus and our automated measure, which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images.ResultsWe observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (r = 0.884; 95% CI, 0.872 to 0.894) in an external test set. Adding a variable, which includes extra information to percentage density, significantly improved the fit of the logistic regression model of breast cancer risk (P = 0.0002).ConclusionsOur results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice.

Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement

IntroductionOver the last decade several breast cancer risk alleles have been identified which has led to an increased interest in individualised risk prediction for clinical purposes.MethodsWe investigate the performance of an up-to-date 18 breast cancer risk single-nucleotide polymorphisms (SNPs), together with mammographic percentage density (PD), body mass index (BMI) and clinical risk factors in predicting absolute risk of breast cancer, empirically, in a well characterised Swedish case-control study of postmenopausal women. We examined the efficiency of various prediction models at a population level for individualised screening by extending a recently proposed analytical approach for estimating number of cases captured.ResultsThe performance of a risk prediction model based on an initial set of seven breast cancer risk SNPs is improved by additionally including eleven more recently established breast cancer risk SNPs (P = 4.69 × 10-4). Adding mammographic PD, BMI and all 18 SNPs to a Swedish Gail model improved the discriminatory accuracy (the AUC statistic) from 55% to 62%. The net reclassification improvement was used to assess improvement in classification of women into low, intermediate, and high categories of 5-year risk (P = 8.93 × 10-9). For scenarios we considered, we estimated that an individualised screening strategy based on risk models incorporating clinical risk factors, mammographic density and SNPs, captures 10% more cases than a screening strategy using the same resources, based on age alone. Estimates of numbers of cases captured by screening stratified by age provide insight into how individualised screening programs might appear in practice.ConclusionsTaken together, genetic risk factors and mammographic density offer moderate improvements to clinical risk factor models for predicting breast cancer.

Variation in DNA repair genes ERCC2, XRCC1, and XRCC3 and risk of follicular lymphoma

The reasons for the positive association between skin cancer and non-Hodgkins lymphoma are not known but may be due to common susceptibility involving suboptimal DNA repair. Therefore, we investigated selected polymorphisms and haplotypes in three DNA repair genes, previously associated with skin cancer and DNA repair capacity, in risk of follicular lymphoma, including possible gene interaction with cigarette smoking and sun exposure. We genotyped 19 single nucleotide polymorphisms (SNP) in the ERCC2, XRCC1, and XRCC3 genes in 430 follicular lymphoma patients and 605 controls within a population-based case-control study in Denmark and Sweden. Odds ratios (OR) and 95% confidence intervals (95% CI) were calculated using unconditional logistic regression and haplotype associations were assessed with a global score test. We observed no associations between variation in the ERCC2 and XRCC1 genes and follicular lymphoma risk. In XRCC3, increased risk of follicular lymphoma was suggested for rare homozygotes of three SNPs [Rs3212024: OR, 1.8 (95% CI, 1.1-2.8); Rs3212038: OR, 1.5 (95% CI, 1.0-2.4); Rs3212090: OR, 1.5 (95% CI, 1.0-2.5)]. These results were strengthened in current cigarette smokers. However, evidence of differences in XRCC3 haplotype distributions between follicular lymphoma cases and controls was weak, both overall and in current smokers. We conclude that polymorphic variation in the XRCC3 gene, but not in ERCC2 or XRCC1, may be of importance for susceptibility to follicular lymphoma, perhaps primarily in current smokers. The link between skin cancer and follicular lymphoma is unlikely to be mediated through common variation in the studied DNA repair gene polymorphisms. (Cancer Epidemiol Biomarkers Prev 2006;15(2)–65)

The Genetic Structure of the Swedish Population

Patterns of genetic diversity have previously been shown to mirror geography on a global scale and within continents and individual countries. Using genome-wide SNP data on 5174 Swedes with extensive geographical coverage, we analyzed the genetic structure of the Swedish population. We observed strong differences between the far northern counties and the remaining counties. The population of Dalarna county, in north middle Sweden, which borders southern Norway, also appears to differ markedly from other counties, possibly due to this county having more individuals with remote Finnish or Norwegian ancestry than other counties. An analysis of genetic differentiation (based on pairwise Fst) indicated that the population of Swedens southernmost counties are genetically closer to the HapMap CEU samples of Northern European ancestry than to the populations of Swedens northernmost counties. In a comparison of extended homozygous segments, we detected a clear divide between southern and northern Sweden with small differences between the southern counties and considerably more segments in northern Sweden. Both the increased degree of homozygosity in the north and the large genetic differences between the south and the north may have arisen due to a small population in the north and the vast geographical distances between towns and villages in the north, in contrast to the more densely settled southern parts of Sweden. Our findings have implications for future genome-wide association studies (GWAS) with respect to the matching of cases and controls and the need for within-county matching. We have shown that genetic differences within a single country may be substantial, even when viewed on a European scale. Thus, population stratification needs to be accounted for, even within a country like Sweden, which is often perceived to be relatively homogenous and a favourable resource for genetic mapping, otherwise inferences based on genetic data may lead to false conclusions.

The SNAP25 Gene Is Linked to Working Memory Capacity and Maturation of the Posterior Cingulate Cortex During Childhood

BACKGROUND Working memory (WM) is the ability to retain task relevant information. This ability is important for a wide range of cognitive tasks, and WM deficits are a central cognitive impairment in neurodevelopment disorders such as attention-deficit/hyperactivity disorder (ADHD). Although WM capacity is known to be highly heritable, most genes involved remain unidentified. METHODS Single nucleotide polymorphisms in genes previously associated with cognitive functions or ADHD were selected for genotyping. Associations of these with WM tasks were investigated in a community sample of 330 children and young adults. One single nucleotide polymorphisms was also investigated in an independent sample of 88 4-year-old children. Furthermore, association between brain structure and activity, as measured by magnetic resonance imaging techniques, and single nucleotide polymorphisms alleles were estimated in 88 participants. RESULTS Genotype at rs363039, located in the gene coding for synaptosomal-associated protein, 25 kDa (SNAP25) was associated to WM capacity in both samples. Associations in the community sample were also found with measures of other cognitive functions. In addition, this polymorphism affected the gray matter and brain activity in the posterior cingulate cortex, an area included in the so-called default mode network previously correlated to regulation of attention and hypothesized to be implicated in ADHD. CONCLUSIONS A novel gene-brain-behavior network was identified in which a genotype located in SNAP25 affects WM and has age-dependent effects on both brain structure and brain activity. Identifying such networks could be a key to better understanding cognitive development as well as some of its disorders.