Interactive effects of in utero nutrition and genetic inheritance on cognition: New evidence using sibling comparisons

A large literature links early environments and later outcomes, such as cognition; however, little is known about the mechanisms. One potential mechanism is sensitivity to early environments that is moderated or amplified by the genotype. With this mechanism in mind, a complementary literature outside economics examines the interaction between genes and environments, but often problems of endogeneity and bias in estimation are uncorrected. A key issue in the literature is exploring environmental variation that is not exogenous, which is potentially problematic if there are gene–environment correlation or gene–gene interactions. Using sibling pairs with genetic data in the Wisconsin Longitudinal Study we extend a previous, and widely cited, gene–environment study that explores an interaction between the FADS2 gene, which is associated with the processing of essential fatty acids related to cognitive development, and early life nutrition in explaining later-life IQ. Our base OLS findings suggest that individuals with specific FADS2 variants gain roughly 0.15 standard deviations in IQ for each standard deviation increase in birth weight, our measure of the early nutrition environment; while, individuals with other variants of FADS2 do not have a statistically significant association with early nutrition, implying the genotype is influencing the effects of environmental exposure. When including family-level fixed effects, however, the magnitude of the gene–environment interaction is reduced by half and statistical significance dissipates, implying the interaction between FADS2 and early nutrition in explaining later life IQ may in part be due to unobserved, family-level factors. The example has wider implications for the practice of investigating gene–environment interactions when the environmental exposure is not exogenous and robustness to unobserved variation in the genome is not controlled for in the analysis.     

Genetic risk for Alzheimer disease in children: Evidence from early‐life IQ and brain white‐matter microstructure

It remains unclear whether the genetic risk for late‐onset Alzheimer disease (AD) is linked to premorbid individual differences in general cognitive ability and brain structure. The objective of the present study was to determine whether the genetic risk of late‐onset AD is related to premorbid individual differences in intelligence quotient (IQ) and characteristics of the cerebral white‐matter in children. The study sample included children of the Generation R Study from Rotterdam, The Netherlands. IQ was measured using a well‐validated Dutch nonverbal IQ test (n = 1908) at ages 5 to 9 years. White‐matter microstructure was assessed by measuring fractional anisotropy (FA) of white‐matter tracts using diffusion tensor imaging (DTI) (n = 919) at ages 9 to 12 years. Genetic risk was quantified using three biologically defined genetic risk scores (GRSs) hypothesized to be related to the pathophysiology of late‐onset AD: immune response, cholesterol/lipid metabolism and endocytosis. Higher genetic risk for late‐onset AD that included genes associated with immune responsivity had a negative influence on cognition and cerebral white‐matter microstructure. For each unit increase in the immune response GRS, IQ decreased by 0.259 SD (95% CI [?0.500, ?0.017]). For each unit increase in the immune response GRS, global FA decreased by 0.373 SD (95% CI [?0.721, ?0.026]). Neither cholesterol/lipid metabolism nor endocytosis GRSs were associated with IQ or cerebral white‐matter microstructure. Our findings suggest that elevated genetic risk for late‐onset AD may in part be manifest during childhood neurodevelopment through alterations in immune responsivity.     

Identifying Gene Interaction Enrichment for Gene Expression Data

Gene set analysis allows the inclusion of knowledge from established gene sets, such as gene pathways, and potentially improves the power of detecting differentially expressed genes. However, conventional methods of gene set analysis focus on gene marginal effects in a gene set, and ignore gene interactions which may contribute to complex human diseases. In this study, we propose a method of gene interaction enrichment analysis, which incorporates knowledge of predefined gene sets (e.g. gene pathways) to identify enriched gene interaction effects on a phenotype of interest. In our proposed method, we also discuss the reduction of irrelevant genes and the extraction of a core set of gene interactions for an identified gene set, which contribute to the statistical variation of a phenotype of interest. The utility of our method is demonstrated through analyses on two publicly available microarray datasets. The results show that our method can identify gene sets that show strong gene interaction enrichments. The enriched gene interactions identified by our method may provide clues to new gene regulation mechanisms related to the studied phenotypes. In summary, our method offers a powerful tool for researchers to exhaustively examine the large numbers of gene interactions associated with complex human diseases, and can be a useful complement to classical gene set analyses which only considers single genes in a gene set.     

Combined analysis of RNA‐sequence and microarray data reveals effective metabolism‐based prognostic signature for neuroblastoma

The relationship between metabolism reprogramming and neuroblastoma (NB) is largely unknown. In this study, one RNA‐sequence data set (n = 153) was used as discovery cohort and two microarray data sets (n = 498 and n = 223) were used as validation cohorts. Differentially expressed metabolic genes were identified by comparing stage 4s and stage 4 NBs. Twelve metabolic genes were selected by LASSO regression analysis and integrated into the prognostic signature. The metabolic gene signature successfully stratifies NB patients into two risk groups and performs well in predicting survival of NB patients. The prognostic value of the metabolic gene signature is also independent with other clinical risk factors. Nine metabolism‐related long non‐coding RNAs (lncRNAs) were also identified and integrated into the metabolism‐related lncRNA signature. The lncRNA signature also performs well in predicting survival of NB patients. These results suggest that the metabolic signatures have the potential to be used for risk stratification of NB. Gene set enrichment analysis (GSEA) reveals that multiple metabolic processes (including oxidative phosphorylation and tricarboxylic acid cycle, both of which are emerging targets for cancer therapy) are enriched in the high‐risk NB group, and no metabolic process is enriched in the low‐risk NB group. This result indicates that metabolism reprogramming is associated with the progression of NB and targeting certain metabolic pathways might be a promising therapy for NB.     

Family‐based genome scan for age at onset of late‐onset Alzheimer's disease in whole exome sequencing data

Alzheimer's disease (AD) is a common and complex neurodegenerative disease. Age at onset (AAO) of AD is an important component phenotype with a genetic basis, and identification of genes in which variation affects AAO would contribute to identification of factors that affect timing of onset. Increase in AAO through prevention or therapeutic measures would have enormous benefits by delaying AD and its associated morbidities. In this paper, we performed a family‐based genome‐wide association study for AAO of late‐onset AD in whole exome sequence data generated in multigenerational families with multiple AD cases. We conducted single marker and gene‐based burden tests for common and rare variants, respectively. We combined association analyses with variance component linkage analysis, and with reference to prior studies, in order to enhance evidence of the identified genes. For variants and genes implicated by the association study, we performed a gene‐set enrichment analysis to identify potential novel pathways associated with AAO of AD. We found statistically significant association with AAO for three genes (WRN, NTN4 and LAMC3) with common associated variants, and for four genes (SLC8A3, SLC19A3, MADD and LRRK2) with multiple rare‐associated variants that have a plausible biological function related to AD. The genes we have identified are in pathways that are strong candidates for involvement in the development of AD pathology and may lead to a better understanding of AD pathogenesis.     

Genetically determined partial complement C4 deficiency states are not independent risk factors for SLE in UK and Spanish populations

Systemic lupus erythematosus (SLE) is a chronic, multisystem autoimmune disease. Complete deficiency of complement component C4 confers strong genetic risk for SLE. Partial C4 deficiency states have also shown association with SLE, but despite much effort over the last 30 years, it has not been established whether this association is primarily causal or secondary to long-range linkage disequilibrium. The complement C4 locus, located in the major histocompatibility complex (MHC) class III region, exhibits copy-number variation (CNV) and C4 itself exists as two paralogs, C4A and C4B. In order to determine whether partial C4 deficiency is an independent genetic risk factor for SLE, we investigated C4 CNV in the context of HLA-DRB1 and MHC region SNP polymorphism in the largest and most comprehensive complement C4 study to date. Specifically, we genotyped 2,207 subjects of northern and southern European ancestry (1,028 SLE cases and 1,179 controls) for total C4, C4A, and C4B gene copy numbers, and the loss-of-function C4 exon 29 CT indel. We used multiple logistic regression to determine the independence of C4 CNV from known SNP and HLA-DRB1 associations. We clearly demonstrate that genetically determined partial C4 deficiency states are not independent risk factors for SLE in UK and Spanish populations. These results are further corroborated by the lack of association shown by the C4A exon 29 CT insertion in either cohort. Thus, although complete homozygous deficiency of complement C4 is one of the strongest genetic risk factors for SLE, partial C4 deficiency states do not independently predispose to the disease.     

Analysis of case-parent trios at a locus with a deletion allele: association of GSTM1 with autism

Background

The fourth component of human complement (C4), an essential factor of the innate immunity, is represented as two isoforms (C4A and C4B) in the genome. Although these genes differ only in 5 nucleotides, the encoded C4A and C4B proteins are functionally different. Based on phenotypic determination, unbalanced production of C4A and C4B is associated with several diseases, such as systemic lupus erythematosus, type 1 diabetes, several autoimmune diseases, moreover with higher morbidity and mortality of myocardial infarction and increased susceptibility for bacterial infections. Despite of this major clinical relevance, only low throughput, time and labor intensive methods have been used so far for the quantification of C4A and C4B genes.

Results

A novel quantitative real-time PCR (qPCR) technique was developed for rapid and accurate quantification of the C4A and C4B genes applying a duplex, TaqMan based methodology. The reliable, single-step analysis provides the determination of the copy number of the C4A and C4B genes applying a wide range of DNA template concentration (0.3–300 ng genomic DNA). The developed qPCR was applied to determine C4A and C4B gene dosages in a healthy Hungarian population (N = 118). The obtained data were compared to the results of an earlier study of the same population. Moreover a set of 33 samples were analyzed by two independent methods. No significant difference was observed between the gene dosages determined by the employed techniques demonstrating the reliability of the novel qPCR methodology. A Microsoft Excel worksheet and a DOS executable are also provided for simple and automated evaluation of the measured data.

Conclusion

This report describes a novel real-time PCR method for single-step quantification of C4A and C4B genes. The developed technique could facilitate studies investigating disease association of different C4 isotypes.     

Association between the oxytocin receptor (OXTR) gene and children's social cognition at 18 months

At 18 months, children engage in a variety of social behaviors that reflect their nascent ability to understand the intentions of other people (e.g. joint attention, empathy, cooperation and self‐recognition). Although numerous contextual factors have been shown to predict social cognition in young children, the genetic underpinnings of social‐cognitive traits has been understudied in this age group. Owing to the known effects of oxytocin on adult social cognition and psychopathology, this study hypothesized that variability in the oxytocin receptor gene (OXTR) would be associated with social cognition in children at 18 months. Participants consisted of 350 children (182 males; 168 females) who were part of an ongoing longitudinal study that aimed to assess environmental and genetic contributions to children's cognitive and socio‐emotional functioning. At 18 months, social cognition was measured using previously validated and developmentally sensitive tasks assessing children's joint attention, empathy, cooperation and self‐recognition. Five potentially functional OXTR variants were genotyped: rs1042778, rs2254298, rs11131149, rs237897 and rs237899. A family‐based association design was used to control for population admixture and stratification, and additional non‐genomic covariates were controlled. Results showed that variability in rs11131149 was significantly associated with social cognition (P = 0.009), with more copies of the major allele related to higher social cognition, and more copies of the minor (risk) allele associated with lower social cognition. A haplotype consisting of rs11131149–rs2254298 was also associated with social cognition (P = 0.020). Implications for normative and pathological development are discussed, and key areas for future research are proposed.     

Gene copy-number variation and associated polymorphisms of complement component C4 in human systemic lupus erythematosus (SLE): low copy number is a risk factor for and high copy number is a protective factor against SLE susceptibility in European Americans

Interindividual gene copy-number variation (CNV) of complement component C4 and its associated polymorphisms in gene size (long and short) and protein isotypes (C4A and C4B) probably lead to different susceptibilities to autoimmune disease. We investigated the C4 gene CNV in 1,241 European Americans, including patients with systemic lupus erythematosus (SLE), their first-degree relatives, and unrelated healthy subjects, by definitive genotyping and phenotyping techniques. The gene copy number (GCN) varied from 2 to 6 for total C4, from 0 to 5 for C4A, and from 0 to 4 for C4B. Four copies of total C4, two copies of C4A, and two copies of C4B were the most common GCN counts, but each constituted only between one-half and three-quarters of the study populations. Long C4 genes were strongly correlated with C4A (R=0.695; P<.0001). Short C4 genes were correlated with C4B (R=0.437; P<.0001). In comparison with healthy subjects, patients with SLE clearly had the GCN of total C4 and C4A shifting to the lower side. The risk of SLE disease susceptibility significantly increased among subjects with only two copies of total C4 (patients 9.3%; unrelated controls 1.5%; odds ratio [OR] = 6.514; P=.00002) but decreased in those with > or =5 copies of C4 (patients 5.79%; controls 12%; OR=0.466; P=.016). Both zero copies (OR=5.267; P=.001) and one copy (OR=1.613; P=.022) of C4A were risk factors for SLE, whereas > or =3 copies of C4A appeared to be protective (OR=0.574; P=.012). Family-based association tests suggested that a specific haplotype with a single short C4B in tight linkage disequilibrium with the -308A allele of TNFA was more likely to be transmitted to patients with SLE. This work demonstrates how gene CNV and its related polymorphisms are associated with the susceptibility to a human complex disease.     

The Dyslexia Candidate Locus on 2p12 Is Associated with General Cognitive Ability and White Matter Structure

Independent studies have shown that candidate genes for dyslexia and specific language impairment (SLI) impact upon reading/language-specific traits in the general population. To further explore the effect of disorder-associated genes on cognitive functions, we investigated whether they play a role in broader cognitive traits. We tested a panel of dyslexia and SLI genetic risk factors for association with two measures of general cognitive abilities, or IQ, (verbal and non-verbal) in the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort (N>5,000). Only the MRPL19/C2ORF3 locus showed statistically significant association (minimum P = 0.00009) which was further supported by independent replications following analysis in four other cohorts. In addition, a fifth independent sample showed association between the MRPL19/C2ORF3 locus and white matter structure in the posterior part of the corpus callosum and cingulum, connecting large parts of the cortex in the parietal, occipital and temporal lobes. These findings suggest that this locus, originally identified as being associated with dyslexia, is likely to harbour genetic variants associated with general cognitive abilities by influencing white matter structure in localised neuronal regions.     

Association of the variants and haplotypes in the DOCK7, PCSK9 and GALNT2 genes and the risk of hyperlipidaemia

Little is known about the association between the single nucleotide polymorphisms (SNPs) and haplotypes of the dedicator of cytokinesis 7 (DOCK7), pro‐protein convertase subtilisin/kexin type 9 (PCSK9) and polypeptide N‐acetylgalactosaminyltransferase 2 (GALNT2) and serum lipid traits in the Chinese populations. This study was to determine the association between nine SNPs in the three genes and their haplotypes and hypercholesterolaemia (HCH)/hypertriglyceridaemia (HTG), and to identify the possible gene–gene interactions among these SNPs. Genotyping was performed in 733 HCH and 540 HTG participants. The haplotype of C‐C‐G‐C‐T‐G‐C‐C‐G [in the order of DOCK7 rs1168013 (G>C), rs10889332 (C>T); PCSK9 rs615563 (G>A), rs7552841 (C>T), rs11206517 (T>G); and GALNT2 rs1997947 (G>A), rs2760537 (C>T), rs4846913 (C>A) and rs11122316 (G>A) SNPs] was associated with increased risk of HCH and HTG. The haplotypes of C‐C‐G‐C‐T‐G‐C‐C‐A and G‐C‐G‐T‐T‐G‐T‐C‐G were associated with a reduced risk of HCH and HTG. The haplotypes of G‐C‐G‐C‐T‐G‐C‐C‐A and G‐C‐G‐C‐T‐G‐T‐C‐G were associated with increased risk of HCH. The haplotypes of C‐T‐G‐C‐T‐G‐C‐C‐G, G‐C‐A‐C‐T‐G‐C‐C‐G and G‐C‐G‐C‐T‐G‐C‐C‐A were associated with an increased risk of HTG. The haplotypes of G‐C‐G‐C‐T‐G‐T‐C‐A and G‐C‐G‐T‐T‐G‐T‐C‐G were associated with a reduced risk of HTG. In addition, possible inter‐locus interactions among the DOCK7, PCSK9 and GALNT2 SNPs were also noted. However, further functional studies of these genes are still required to clarify which SNPs are functional and how these genes actually affect the serum lipid levels.     

Neuropsychological effects of the CSMD1 genome‐wide associated schizophrenia risk variant rs10503253

The single‐nucleotide polymorphism (SNP) rs10503253, located within the CUB and Sushi multiple domains‐1 (CSMD1) gene on 8p23.2, was recently identified as genome‐wide significant for schizophrenia (SZ), but is of unknown function. We investigated the neurocognitive effects of this CSMD1 variant in vivo in patients and healthy participants using behavioral and imaging measures of brain structure and function. We compared carriers and non‐carriers of the risk ‘A’ allele on measures of neuropsychological performance typically impaired in SZ (general cognitive ability, episodic and working memory and attentional control) in independent samples of Irish patients (n = 387) and controls (n = 171) and German patients (205) and controls (n = 533). Across these groups, the risk ‘A’ allele at CSMD1 was associated with deleterious effects across a number of neurocognitive phenotypes. Specifically, the risk allele was associated with poorer performance on neuropsychological measures of general cognitive ability and memory function but not attentional control. These effects, while significant, were subtle, and varied between samples. Consistent with previous evidence suggesting that CSMD1 may be involved in brain mechanisms related to memory and learning, these data appear to reflect the deleterious effects of the identified ‘A’ risk allele on neurocognitive function, possibly as part of the mechanism by which CSMD1 is associated with SZ risk.     

Dissection of the genetic architecture of three seed‐quality traits and consequences for breeding in Brassica napus

Genome‐wide association studies (GWASs) combining high‐throughput genome resequencing and phenotyping can accelerate the dissection of genetic architecture and identification of genes for plant complex traits. In this study, we developed a rapeseed genomic variation map consisting of 4 542 011 SNPs and 628 666 INDELs. GWAS was performed for three seed‐quality traits, including erucic acid content (EAC), glucosinolate content (GSC) and seed oil content (SOC) using 3.82 million polymorphisms in an association panel. Six, 49 and 17 loci were detected to be associated with EAC, GSC and SOC in multiple environments, respectively. The mean total contribution of these loci in each environment was 94.1% for EAC and 87.9% for GSC, notably higher than that for SOC (40.1%). A high correlation was observed between phenotypic variance and number of favourable alleles for associated loci, which will contribute to breeding improvement by pyramiding these loci. Furthermore, candidate genes were detected underlying associated loci, based on functional polymorphisms in gene regions where sequence variation was found to correlate with phenotypic variation. Our approach was validated by detection of well‐characterized FAE1 genes at each of two major loci for EAC on chromosomes A8 and C3, along with MYB28 genes at each of three major loci for GSC on chromosomes A9, C2 and C9. Four novel candidate genes were detected by correlation between GSC and SOC and observed sequence variation, respectively. This study provides insights into the genetic architecture of three seed‐quality traits, which would be useful for genetic improvement of B. napus.     

Association of ATM and BMI‐1 genetic variation with breast cancer risk in Han Chinese

We tested the hypothesis that genetic variation in ATM and BMI‐1 genes can alter the risk of breast cancer through genotyping 6 variants among 524 breast cancer cases and 518 cancer‐free controls of Han nationality. This was an observational, hospital‐based, case–control association study. Analyses of single variant, linkage, haplotype, interaction and nomogram were performed. Risk was expressed as odds ratio (OR) and 95% confidence interval (CI). All studied variants were in the Hardy‐Weinberg equilibrium and were not linked. The mutant allele frequencies of rs1890637, rs3092856 and rs1801516 in ATM gene were significantly higher in cases than in controls (P = .005, <.001 and .001, respectively). Two variants, rs1042059 and rs201024480, in BMI‐1 gene were low penetrant, with no detectable significance. After adjustment, rs189037 and rs1801516 were significantly associated with breast cancer under the additive model (OR: 1.37 and 1.52, 95% CI: 1.10‐1.71 and 1.14‐2.04, P: .005 and .005, respectively). In haplotype analysis, haplotypes A‐C‐G‐G (in order of rs189037, rs3092856, rs1801516 and rs373759) and A‐C‐A‐A in ATM gene were significantly associated with 1.98‐fold and 6.04‐fold increased risk of breast cancer (95% CI: 1.36‐2.90 and 1.65‐22.08, respectively). Nomogram analysis estimated that the cumulative proportion of 3 significant variants in ATM gene was about 12.5%. Our findings collectively indicated that ATM gene was a candidate gene in susceptibility to breast cancer in Han Chinese.     

The impact of CACNA1C gene,and its epistasis with ZNF804A,on white matter microstructure in health,schizophrenia and bipolar disorder1

Genome‐wide studies have identified allele A (adenine) of single nucleotide polymorphism (SNP) rs1006737 of the calcium‐channel CACNA1C gene as a risk factor for both schizophrenia (SZ) and bipolar disorder (BD) as well as allele A for rs1344706 in the ZNF804A gene. These illnesses have also been associated with white matter abnormalities, reflected by reductions in fractional anisotropy (FA), measured using diffusion tensor imaging (DTI). We assessed the impact of the CACNA1C psychosis risk variant on FA in SZ, BD and health. 230 individuals (with existing ZNF804A rs1344706 genotype data) were genotyped for CACNA1C rs1006737 and underwent DTI. FA data was analysed with tract‐based spatial statistics and threshold‐free cluster enhancement significance correction (P < 0.05) to detect effects of CACNA1C genotype on FA, and its potential interaction with ZNF804A genotype and with diagnosis, on FA. There was no significant main effect of the CACNA1C genotype on FA, nor diagnosis by genotype(s) interactions. Nevertheless, when inspecting SZ in particular, risk allele carriers had significantly lower FA than the protective genotype individuals, in portions of the left middle occipital and parahippocampal gyri, right cerebellum, left optic radiation and left inferior and superior temporal gyri. Our data suggests a minor involvement of CACNA1C rs1006737 in psychosis via conferring susceptibility to white matter microstructural abnormalities in SZ. Put in perspective, ZNF804A rs1344706, not only had a significant main effect, but its SZ‐specific effects were two orders of magnitude more widespread than that of CACNA1C rs1006737.     

Genetic Basis of a Cognitive Complexity Metric

Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ), reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787). Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG), followed by meta-analysis (N>6500) at the single marker level. Twin modelling showed RC is highly heritable (67%), has considerable genetic overlap with IQ (59%), and is a major component of genetic covariation between reasoning and working memory (72%). At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB), and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.