Inference of the Genetic Architecture Underlying BMI and Height with the Use of 20,240 Sibling Pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 × 10⁻⁷) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 × 10⁻¹⁰) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.     

Resequencing Three Candidate Genes for Major Depressive Disorder in a Dutch Cohort

Major depressive disorder (MDD) is a psychiatric disorder, characterized by periods of low mood of more than two weeks, loss of interest in normally enjoyable activities and behavioral changes. MDD is a complex disorder and does not have a single genetic cause. In 2009 a genome wide association study (GWAS) was performed on the Dutch GAIN-MDD cohort. Many of the top signals of this GWAS mapped to a region spanning the gene PCLO, and the non-synonymous coding single nucleotide polymorphism (SNP) rs2522833 in the PCLO gene became genome wide significant after post-hoc analysis. We performed resequencing of PCLO, GRM7, and SLC6A4 in 50 control samples from the GAIN-MDD cohort, to detect new genomic variants. Subsequently, we genotyped these variants in the entire GAIN-MDD cohort and performed association analysis to investigate if rs2522833 is the causal variant or simply in linkage disequilibrium with a more associated variant. GRM7 and SLC6A4 are both candidate genes for MDD from literature. We aimed to gather more evidence that rs2522833 is indeed the causal variant in the GAIN-MDD cohort or to find a previously undetected common variant in either PCLO, GRM7, or SLC6A4 with a higher association in this cohort. After next generation sequencing and association analysis we excluded the possibility of an undetected common variant to be more associated. For neither PCLO nor GRM7 we found a more associated variant. For SLC6A4, we found a new SNP that showed a lower P-value (P = 0.07) than in the GAIN-MDD GWAS (P = 0.09). However, no evidence for genome-wide significance was found. Although we did not take into account rare variants, we conclude that our results provide further support for the hypothesis that the non-synonymous coding SNP rs2522833 in the PCLO gene is indeed likely to be the causal variant in the GAIN-MDD cohort.     

Sex Differences in Genetic Architecture of Complex Phenotypes?

We examined sex differences in familial resemblance for a broad range of behavioral, psychiatric and health related phenotypes (122 complex traits) in children and adults. There is a renewed interest in the importance of genotype by sex interaction in, for example, genome-wide association (GWA) studies of complex phenotypes. If different genes play a role across sex, GWA studies should consider the effect of genetic variants separately in men and women, which affects statistical power. Twin and family studies offer an opportunity to compare resemblance between opposite-sex family members to the resemblance between same-sex relatives, thereby presenting a test of quantitative and qualitative sex differences in the genetic architecture of complex traits. We analyzed data on lifestyle, personality, psychiatric disorder, health, growth, development and metabolic traits in dizygotic (DZ) same-sex and opposite-sex twins, as these siblings are perfectly matched for age and prenatal exposures. Sample size varied from slightly over 300 subjects for measures of brain function such as EEG power to over 30,000 subjects for childhood psychopathology and birth weight. For most phenotypes, sample sizes were large, with an average sample size of 9027 individuals. By testing whether the resemblance in DZ opposite-sex pairs is the same as in DZ same-sex pairs, we obtain evidence for genetic qualitative sex-differences in the genetic architecture of complex traits for 4% of phenotypes. We conclude that for most traits that were examined, the current evidence is that same the genes are operating in men and women.     

The brain matures with stronger functional connectivity and decreased randomness of its network

We investigated the development of the brain's functional connectivity throughout the life span (ages 5 through 71 years) by measuring EEG activity in a large population-based sample. Connectivity was established with Synchronization Likelihood. Relative randomness of the connectivity patterns was established with Watts and Strogatz' (1998) graph parameters C (local clustering) and L (global path length) for alpha (~10 Hz), beta (~20 Hz), and theta (~4 Hz) oscillation networks. From childhood to adolescence large increases in connectivity in alpha, theta and beta frequency bands were found that continued at a slower pace into adulthood (peaking at ~50 yrs). Connectivity changes were accompanied by increases in L and C reflecting decreases in network randomness or increased order (peak levels reached at ~18 yrs). Older age (55+) was associated with weakened connectivity. Semi-automatically segmented T1 weighted MRI images of 104 young adults revealed that connectivity was significantly correlated to cerebral white matter volume (alpha oscillations: r = 33, p<01; theta: r = 22, p<05), while path length was related to both white matter (alpha: max. r = 38, p<001) and gray matter (alpha: max. r = 36, p<001; theta: max. r = 36, p<001) volumes. In conclusion, EEG connectivity and graph theoretical network analysis may be used to trace structural and functional development of the brain.     

Common variants in the type 2 diabetes KCNQ1 gene are associated with impairments in insulin secretion during hyperglycaemic glucose clamp

Background

Genome-wide association studies in Japanese populations recently identified common variants in the KCNQ1 gene to be associated with type 2 diabetes. We examined the association of these variants within KCNQ1 with type 2 diabetes in a Dutch population, investigated their effects on insulin secretion and metabolic traits and on the risk of developing complications in type 2 diabetes patients.

Methodology

The KCNQ1 variants rs151290, rs2237892, and rs2237895 were genotyped in a total of 4620 type 2 diabetes patients and 5285 healthy controls from the Netherlands. Data on macrovascular complications, nephropathy and retinopathy were available in a subset of diabetic patients. Association between genotype and insulin secretion/action was assessed in the additional sample of 335 individuals who underwent a hyperglycaemic clamp.

Principal Findings

We found that all the genotyped KCNQ1 variants were significantly associated with type 2 diabetes in our Dutch population, and the association of rs151290 was the strongest (OR 1.20, 95% CI 1.07–1.35, p = 0.002). The risk C-allele of rs151290 was nominally associated with reduced first-phase glucose-stimulated insulin secretion, while the non-risk T-allele of rs2237892 was significantly correlated with increased second-phase glucose-stimulated insulin secretion (p = 0.025 and 0.0016, respectively). In addition, the risk C-allele of rs2237892 was associated with higher LDL and total cholesterol levels (p = 0.015 and 0.003, respectively). We found no evidence for an association of KCNQ1 with diabetic complications.

Conclusions

Common variants in the KCNQ1 gene are associated with type 2 diabetes in a Dutch population, which can be explained at least in part by an effect on insulin secretion. Furthermore, our data suggest that KCNQ1 is also associated with lipid metabolism.     

The genetics of coronary heart disease: the contribution of twin studies.

Despite the decline in coronary heart disease in many European countries, the disease remains an enormous public health problem. Although we know a great deal about environmental risk factors for coronary heart disease, a heritable component was recognized a long time ago. The earliest and best known examples of how our genetic constitution may determine cardiovascular risk relate to lipoprotein(a), familial hypercholesterolaemia and apolipoprotein E. In the past 20 years a fair number of polymorphisms assessed singly have shown strong associations with the disease but most are subject to poor repeatability. Twins constitute a compelling natural experiment to establish the genetic contribution to coronary heart disease and its risk factors. GenomEUtwin, a recently funded Framework 5 Programme of the European Community, affords the opportunity of comparing the heritability of risk factors in different European Twin Registries. As an illustration we present the heritabilities of systolic and diastolic blood pressure, based on data from over 4000 twin pairs from six different European countries and Australia. Heritabilities for systolic blood pressure are between 52 and 66% and for diastolic blood pressure between 44 and 66%. There is no evidence of sex differences in heritability estimates and very little to no evidence for a significant contribution of shared family environment. A non-twin based prospective case/cohort study of coronary heart disease and stroke (MORGAM) will allow hypotheses relating to cardiovascular disease, generated in the twin cohorts, to be tested prospectively in adult populations. Twin studies have also contributed to our understanding of the life course hypothesis, and GenomEUtwin has the potential to add to this.     

A fine-mapping study of 7 top scoring genes from a GWAS for major depressive disorder

Major depressive disorder (MDD) is a psychiatric disorder that is characterized--amongst others--by persistent depressed mood, loss of interest and pleasure and psychomotor retardation. Environmental circumstances have proven to influence the aetiology of the disease, but MDD also has an estimated 40% heritability, probably with a polygenic background. In 2009, a genome wide association study (GWAS) was performed on the Dutch GAIN-MDD cohort. A non-synonymous coding single nucleotide polymorphism (SNP) rs2522833 in the PCLO gene became only nominally significant after post-hoc analysis with an Australian cohort which used similar ascertainment. The absence of genome-wide significance may be caused by low SNP coverage of genes. To increase SNP coverage to 100% for common variants (m.a.f.>0.1, r(2)>0.8), we selected seven genes from the GAIN-MDD GWAS: PCLO, GZMK, ANPEP, AFAP1L1, ST3GAL6, FGF14 and PTK2B. We genotyped 349 SNPs and obtained the lowest P-value for rs2715147 in PCLO at P?=?6.8E-7. We imputed, filling in missing genotypes, after which rs2715147 and rs2715148 showed the lowest P-value at P?=?1.2E-6. When we created a haplotype of these SNPs together with the non-synonymous coding SNP rs2522833, the P-value decreased to P?=?9.9E-7 but was not genome wide significant. Although our study did not identify a more strongly associated variant, the results for PCLO suggest that the causal variant is in high LD with rs2715147, rs2715148 and rs2522833.