Hospital Mental Health Admissions in Women after Unsuccessful Infertility Treatment and In Vitro Fertilization: An Australian Population-Based Cohort Study

Objective - To examine the association between in vitro fertilization (IVF) and later admission to hospital with a mental health diagnosis in women who remained childless after infertility treatment. Methods - This was a population-based cohort study using linked administrative hospital and registry data. The study population included all women commencing hospital treatment for infertility in Western Australia between the years 1982 and 2002 aged 20–44 years at treatment commencement who did not have a recorded birth by the end of follow-up (15 August 2010) and did not have a hospital mental health admission prior to the first infertility admission (n=6,567). Of these, 2,623 women had IVF and 3,944 did not. We used multivariate Cox regression modeling of mental health admissions and compared women undergoing IVF treatment with women having infertility treatment but not IVF. Results - Over an average of 17 years of follow-up, 411 women in the cohort were admitted to hospital with a mental health diagnosis; 93 who had IVF and 318 who did not. The unadjusted hazard ratio (HR) for a hospital mental health admission comparing women who had IVF with those receiving other infertility treatment was 0.50 (95% confidence interval [CI] 0.40–0.63). After adjustment for age, calendar year and socio-economic status the HR was 0.56 (95% CI 0.44–0.71). Conclusions - IVF treatment is associated with a reduced risk of hospital mental health admissions in women after unsuccessful infertility treatment. This may be explained by the healthy cohort effect

Reconsidering the Heritability of Intelligence in Adulthood: Taking Assortative Mating and Cultural Transmission into Account

Heritability estimates of general intelligence in adulthood generally range from 75 to 85%, with all heritability due to additive genetic influences, while genetic dominance and shared environmental factors are absent, or too small to be detected. These estimates are derived from studies based on the classical twin design and are based on the assumption of random mating. Yet, considerable positive assortative mating has been reported for general intelligence. Unmodeled assortative mating may lead to biased estimates of the relative magnitude of genetic and environmental factors. To investigate the effects of assortative mating on the estimates of the variance components of intelligence, we employed an extended twin-family design. Psychometric IQ data were available for adult monozygotic and dizygotic twins, their siblings, the partners of the twins and siblings, and either the parents or the adult offspring of the twins and siblings (N = 1314). Two underlying processes of assortment were considered: phenotypic assortment and social homogamy. The phenotypic assortment model was slightly preferred over the social homogamy model, suggesting that assortment for intelligence is mostly due to a selection of mates on similarity in intelligence. Under the preferred phenotypic assortment model, the variance of intelligence in adulthood was not only due to non-shared environmental (18%) and additive genetic factors (44%) but also to non-additive genetic factors (27%) and phenotypic assortment (11%).This non-additive nature of genetic influences on intelligence needs to be accommodated in future GWAS studies for intelligence

A Three-Stage Genome-Wide Association Study of General Cognitive Ability: Hunting the Small Effects

Childhood general cognitive ability (g) is important for a wide range of outcomes in later life, from school achievement to occupational success and life expectancy. Large-scale association studies will be essential in the quest to identify variants that make up the substantial genetic component implicated by quantitative genetic studies. We conducted a three-stage genome-wide association study for general cognitive ability using over 350,000 single nucleotide polymorphisms (SNPs) in the quantitative extremes of a population sample of 7,900 7-year-old children from the UK Twins Early Development Study. Using two DNA pooling stages to enrich true positives, each of around 1,000 children selected from the extremes of the distribution, and a third individual genotyping stage of over 3,000 children to test for quantitative associations across the normal range, we aimed to home in on genes of small effect. Genome-wide results suggested that our approach was successful in enriching true associations and 28 SNPs were taken forward to individual genotyping in an unselected population sample. However, although we found an enrichment of low P values and identified nine SNPs nominally associated with g (P < 0.05) that show interesting characteristics for follow-up, further replication will be necessary to meet rigorous standards of association. These replications may take advantage of SNP sets to overcome limitations of statistical power. Despite our large sample size and three-stage design, the genes associated with childhood g remain tantalizingly beyond our current reach, providing further evidence for the small effect sizes of individual loci. Larger samples, denser arrays and multiple replications will be necessary in the hunt for the genetic variants that influence human cognitive ability

Understanding the Adaptive Growth Strategy of Lactobacillus plantarum by In Silico Optimisation

In the study of metabolic networks, optimization techniques are often used to predict flux distributions, and hence, metabolic phenotype. Flux balance analysis in particular has been successful in predicting metabolic phenotypes. However, an inherent limitation of a stoichiometric approach such as flux balance analysis is that it can predict only flux distributions that result in maximal yields. Hence, previous attempts to use FBA to predict metabolic fluxes in Lactobacillus plantarum failed, as this lactic acid bacterium produces lactate, even under glucose-limited chemostat conditions, where FBA predicted mixed acid fermentation as an alternative pathway leading to a higher yield. In this study we tested, however, whether long-term adaptation on an unusual and poor carbon source (for this bacterium) would select for mutants with optimal biomass yields. We have therefore adapted Lactobacillus plantarum to grow well on glycerol as its main growth substrate. After prolonged serial dilutions, the growth yield and corresponding fluxes were compared to in silico predictions. Surprisingly, the organism still produced mainly lactate, which was corroborated by FBA to indeed be optimal. To understand these results, constraint-based elementary flux mode analysis was developed that predicted 3 out of 2669 possible flux modes to be optimal under the experimental conditions. These optimal pathways corresponded very closely to the experimentally observed fluxes and explained lactate formation as the result of competition for oxygen by the other flux modes. Hence, these results provide thorough understanding of adaptive evolution, allowing in silico predictions of the resulting flux states, provided that the selective growth conditions favor yield optimization as the winning strategy

On the sources of the height–intelligence correlation: New insights from a bivariate ACE model with assortative mating

A robust positive correlation between height and intelligence, as measured by IQ tests, has been established in the literature. This paper makes several contributions toward establishing the causes of this association. First, we extend the standard bivariate ACE model to account for assortative mating. The more general theoretical framework provides several key insights, including formulas to decompose a cross-trait genetic correlation into components attributable to assortative mating and pleiotropy and to decompose a cross-trait within-family correlation. Second, we use a large dataset of male twins drawn from Swedish conscription records and examine how well genetic and environmental factors explain the association between (i) height and intelligence and (ii) height and military aptitude, a professional psychogologist’s assessment of a conscript’s ability to deal with wartime stress. For both traits, we find suggestive evidence of a shared genetic architecture with height, but we demonstrate that point estimates are very sensitive to assumed degrees of assortative mating. Third, we report a significant within-family correlation between height and intelligence \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(\hat{\rho}=0.10),$$\end{document} suggesting that pleiotropy might be at play

Global similarity with local differences in linkage disequilibrium between the Dutch and HapMap–CEU populations

The HapMap project has facilitated the selection of tagging single nucleotide polymorphisms (tagSNPs) for genome-wide association studies (GWAS) under the assumption that linkage disequilibrium (LD) in the HapMap populations is similar to the populations under investigation. Earlier reports support this assumption, although in most of these studies only a few loci were evaluated. We compared pair-wise LD and LD block structure across autosomes between the Dutch population and the CEU-HapMap reference panel. The impact of sampling distribution on the estimation of LD blocks was studied by bootstrapping. A high Pearson correlation (genome-wide; 0.93) between pair-wise

A genome-wide association study with 1,126,563 individuals identifies new risk loci for Alzheimer's disease

Late-onset Alzheimer’s disease is a prevalent age-related polygenic disease that accounts for 50–70% of dementia cases. Currently, only a fraction of the genetic variants underlying Alzheimer’s disease have been identified. Here we show that increased sample sizes allowed identification of seven previously unidentified genetic loci contributing to Alzheimer’s disease. This study highlights microglia, immune cells and protein catabolism as relevant to late-onset Alzheimer’s disease, while identifying and prioritizing previously unidentified genes of potential interest. We anticipate that these results can be included in larger meta-analyses of Alzheimer’s disease to identify further genetic variants that contribute to Alzheimer’s pathology

The Derived Allele of ASPM Is Associated with Lexical Tone Perception

The ASPM and MCPH1 genes have been implicated in the adaptive evolution of the human brain [Mekel-Bobrov N. et al., 2005. Ongoing adaptive evolution of ASPM, a brain size determinant in homo sapiens. Science 309; Evans P.D. et al., 2005. Microcephalin, a gene regulating brain size, continues to evolve adaptively in humans. Science 309]. Curiously, experimental attempts have failed to connect the implicated SNPs in these genes with higher-level brain functions. These results stand in contrast with a population-level study linking the population frequency of their alleles with the tendency to use lexical tones in a language [Dediu D., Ladd D.R., 2007. Linguistic tone is related to the population frequency of the adaptive haplogroups of two brain size genes, ASPM and microcephalin. Proc. Natl. Acad. Sci. U.S.A. 104]. In the present study, we found a significant correlation between the load of the derived alleles of ASPM and tone perception in a group of European Americans who did not speak a tone language. Moreover, preliminary results showed a significant correlation between ASPM load and hemodynamic responses to lexical tones in the auditory cortex, and such correlation remained after phonemic awareness, auditory working memory, and non-verbal IQ were controlled. As in previous studies, no significant correlation between ASPM and cognitive measures were found. MCPH1 did not correlate with any measures. These results suggest that the association between the recently derived allele of ASPM is likely to be specific and is tied to higher level brain functions in the temporal cortex related to human communication

The Interleukin 3 Gene (IL3) Contributes to Human Brain Volume Variation by Regulating Proliferation and Survival of Neural Progenitors

One of the most significant evolutionary changes underlying the highly developed cognitive abilities of humans is the greatly enlarged brain volume. In addition to being far greater than in most other species, the volume of the human brain exhibits extensive variation and distinct sexual dimorphism in the general population. However, little is known about the genetic mechanisms underlying normal variation as well as the observed sex difference in human brain volume. Here we show that interleukin-3 (IL3) is strongly associated with brain volume variation in four genetically divergent populations. We identified a sequence polymorphism (rs31480) in the IL3 promoter which alters the expression of IL3 by affecting the binding affinity of transcription factor SP1. Further analysis indicated that IL3 and its receptors are continuously expressed in the developing mouse brain, reaching highest levels at postnatal day 1–4. Furthermore, we found IL3 receptor alpha (IL3RA) was mainly expressed in neural progenitors and neurons, and IL3 could promote proliferation and survival of the neural progenitors. The expression level of IL3 thus played pivotal roles in the expansion and maintenance of the neural progenitor pool and the number of surviving neurons. Moreover, we found that IL3 activated both estrogen receptors, but estrogen didn’t directly regulate the expression of IL3. Our results demonstrate that genetic variation in the IL3 promoter regulates human brain volume and reveals novel roles of IL3 in regulating brain development

Gene-Based Analysis of Regionally Enriched Cortical Genes in GWAS Data Sets of Cognitive Traits and Psychiatric Disorders

Background: Despite its estimated high heritability, the genetic architecture leading to differences in cognitive performance remains poorly understood. Different cortical regions play important roles in normal cognitive functioning and impairment. Recently, we reported on sets of regionally enriched genes in three different cortical areas (frontomedial, temporal and occipital cortices) of the adult rat brain. It has been suggested that genes preferentially, or specifically, expressed in one region or organ reflect functional specialisation. Employing a gene-based approach to the analysis, we used the regionally enriched cortical genes to mine a genome-wide association study (GWAS) of the Norwegian Cognitive NeuroGenetics (NCNG) sample of healthy adults for association to nine psychometric tests measures. In addition, we explored GWAS data sets for the serious psychiatric disorders schizophrenia (SCZ) (n = 3 samples) and bipolar affective disorder (BP) (n = 3 samples), to which cognitive impairment is linked. Principal Findings: At the single gene level, the temporal cortex enriched gene RAR-related orphan receptor B (RORB) showed the strongest overall association, namely to a test of verbal intelligence (Vocabulary, P = 7.7E-04). We also applied gene set enrichment analysis (GSEA) to test the candidate genes, as gene sets, for enrichment of association signal in the NCNG GWAS and in GWASs of BP and of SCZ. We found that genes differentially expressed in the temporal cortex showed a significant enrichment of association signal in a test measure of non-verbal intelligence (Reasoning) in the NCNG sample. Conclusion: Our gene-based approach suggests that RORB could be involved in verbal intelligence differences, while the genes enriched in the temporal cortex might be important to intellectual functions as measured by a test of reasoning in the healthy population. These findings warrant further replication in independent samples on cognitive traits