Jenny van Dongen

The continuing value of twin studies in the omics era

The classical twin study has been a powerful heuristic in biomedical, psychiatric and behavioural research for decades. Twin registries worldwide have collected biological material and longitudinal phenotypic data on tens of thousands of twins, providing a valuable resource for studying complex phenotypes and their underlying biology. In this Review, we consider the continuing value of twin studies in the current era of molecular genetic studies. We conclude that classical twin methods combined with novel technologies represent a powerful approach towards identifying and understanding the molecular pathways that underlie complex traits.

The Adult Netherlands Twin Register: twenty-five years of survey and biological data collection.

Over the past 25 years, the Adult Netherlands Twin Register (ANTR) has collected a wealth of information on physical and mental health, lifestyle, and personality in adolescents and adults. This article provides an overview of the sources of information available, the main research findings, and an outlook for the future. Between 1991 and 2012, longitudinal surveys were completed by twins, their parents, siblings, spouses, and offspring. Data are available for 33,957 participants, with most individuals having completed two or more surveys. Smaller projects provided in-depth phenotyping, including measurements of the autonomic nervous system, neurocognitive function, and brain imaging. For 46% of the ANTR participants, DNA samples are available and whole genome scans have been obtained in more than 11,000 individuals. These data have resulted in numerous studies on heritability, gene x environment interactions, and causality, as well as gene finding studies. In the future, these studies will continue with collection of additional phenotypes, such as metabolomic and telomere length data, and detailed genetic information provided by DNA and RNA sequencing. Record linkage to national registers will allow the study of morbidity and mortality, thus providing insight into the development of health, lifestyle, and behavior across the lifespan.

Disease variants alter transcription factor levels and methylation of their binding sites

Most disease-associated genetic variants are noncoding, making it challenging to design experiments to understand their functional consequences. Identification of expression quantitative trait loci (eQTLs) has been a powerful approach to infer the downstream effects of disease-associated variants, but most of these variants remain unexplained. The analysis of DNA methylation, a key component of the epigenome, offers highly complementary data on the regulatory potential of genomic regions. Here we show that disease-associated variants have widespread effects on DNA methylation in trans that likely reflect differential occupancy of trans binding sites by cis-regulated transcription factors. Using multiple omics data sets from 3,841 Dutch individuals, we identified 1,907 established trait-associated SNPs that affect the methylation levels of 10,141 different CpG sites in trans (false discovery rate (FDR) < 0.05). These included SNPs that affect both the expression of a nearby transcription factor (such as NFKB1, CTCF and NKX2-3) and methylation of its respective binding site across the genome. Trans methylation QTLs effectively expose the downstream effects of disease-associated variants.

Genetic and environmental influences interact with age and sex in shaping the human methylome

The methylome is subject to genetic and environmental effects. Their impact may depend on sex and age, resulting in sex- and age-related physiological variation and disease susceptibility. Here we estimate the total heritability of DNA methylation levels in whole blood and estimate the variance explained by common single nucleotide polymorphisms at 411,169 sites in 2,603 individuals from twin families, to establish a catalogue of between-individual variation in DNA methylation. Heritability estimates vary across the genome (mean=19%) and interaction analyses reveal thousands of sites with sex-specific heritability as well as sites where the environmental variance increases with age. Integration with previously published data illustrates the impact of genome and environment across the lifespan at methylation sites associated with metabolic traits, smoking and ageing. These findings demonstrate that our catalogue holds valuable information on locations in the genome where methylation variation between people may reflect disease-relevant environmental exposures or genetic variation.

Identification of context-dependent expression quantitative trait loci in whole blood

Genetic risk factors often localize to noncoding regions of the genome with unknown effects on disease etiology. Expression quantitative trait loci (eQTLs) help to explain the regulatory mechanisms underlying these genetic associations. Knowledge of the context that determines the nature and strength of eQTLs may help identify cell types relevant to pathophysiology and the regulatory networks underlying disease. Here we generated peripheral blood RNA–seq data from 2,116 unrelated individuals and systematically identified context-dependent eQTLs using a hypothesis-free strategy that does not require previous knowledge of the identity of the modifiers. Of the 23,060 significant cis-regulated genes (false discovery rate (FDR) ≤ 0.05), 2,743 (12%) showed context-dependent eQTL effects. The majority of these effects were influenced by cell type composition. A set of 145 cis-eQTLs depended on type I interferon signaling. Others were modulated by specific transcription factors binding to the eQTL SNPs.

Blood lipids influence DNA methylation in circulating cells

BackgroundCells can be primed by external stimuli to obtain a long-term epigenetic memory. We hypothesize that long-term exposure to elevated blood lipids can prime circulating immune cells through changes in DNA methylation, a process that may contribute to the development of atherosclerosis. To interrogate the causal relationship between triglyceride, low-density lipoprotein (LDL) cholesterol, and high-density lipoprotein (HDL) cholesterol levels and genome-wide DNA methylation while excluding confounding and pleiotropy, we perform a stepwise Mendelian randomization analysis in whole blood of 3296 individuals.ResultsThis analysis shows that differential methylation is the consequence of inter-individual variation in blood lipid levels and not vice versa. Specifically, we observe an effect of triglycerides on DNA methylation at three CpGs, of LDL cholesterol at one CpG, and of HDL cholesterol at two CpGs using multivariable Mendelian randomization. Using RNA-seq data available for a large subset of individuals (N = 2044), DNA methylation of these six CpGs is associated with the expression of CPT1A and SREBF1 (for triglycerides), DHCR24 (for LDL cholesterol) and ABCG1 (for HDL cholesterol), which are all key regulators of lipid metabolism.ConclusionsOur analysis suggests a role for epigenetic priming in end-product feedback control of lipid metabolism and highlights Mendelian randomization as an effective tool to infer causal relationships in integrative genomics data.

The Evolutionary Paradox and the Missing Heritability of Schizophrenia

Schizophrenia is one of the most detrimental common psychiatric disorders, occurring at a prevalence of approximately 1%, and characterized by increased mortality and reduced reproduction, especially in men. The heritability has been estimated around 70% and the genome‐wide association meta‐analyses conducted by the Psychiatric Genomics Consortium have been successful at identifying an increasing number of risk loci. Various theories have been proposed to explain why genetic variants that predispose to schizophrenia persist in the population, despite the fitness reduction in affected individuals, a question known as the evolutionary paradox. In this review, we consider evolutionary perspectives of schizophrenia and of the empirical evidence that may support these perspectives. Proposed evolutionary explanations include balancing selection, fitness trade‐offs, fluctuating environments, sexual selection, mutation‐selection balance and genomic conflicts. We address the expectations about the genetic architecture of schizophrenia that are predicted by different evolutionary scenarios and discuss the implications for genetic studies. Several potential sources of “missing” heritability, including gene–environment interactions, epigenetic variation, and rare genetic variation are examined from an evolutionary perspective. A better understanding of evolutionary history may provide valuable clues to the genetic architecture of schizophrenia and other psychiatric disorders, which is highly relevant to genetic studies that aim to detect genetic risk variants.

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.

Heritability of metabolic syndrome traits in a large population-based sample.

Heritability estimates of metabolic syndrome traits vary widely across studies. Some studies have suggested that the contribution of genes may vary with age or sex. We estimated the heritability of 11 metabolic syndrome-related traits and height as a function of age and sex in a large population-based sample of twin families (N = 2,792–27,021, for different traits). A moderate-to-high heritability was found for all traits [from H2 = 0.47 (insulin) to H2 = 0.78 (BMI)]. The broad-sense heritability (H2) showed little variation between age groups in women; it differed somewhat more in men (e.g., for glucose, H2 = 0.61 in young females, H2 = 0.56 in older females, H2 = 0.64 in young males, and H2= 0.27 in older males). While nonadditive genetic effects explained little variation in the younger subjects, nonadditive genetic effects became more important at a greater age. Our findings show that in an unselected sample (age range, ∼18–98 years), the genetic contribution to individual differences in metabolic syndrome traits is moderate to large in both sexes and across age. Although the prevalence of the metabolic syndrome has greatly increased in the past decades due to lifestyle changes, our study indicates that most of the variation in metabolic syndrome traits between individuals is due to genetic differences.

Age-related accrual of methylomic variability is linked to fundamental ageing mechanisms

BackgroundEpigenetic change is a hallmark of ageing but its link to ageing mechanisms in humans remains poorly understood. While DNA methylation at many CpG sites closely tracks chronological age, DNA methylation changes relevant to biological age are expected to gradually dissociate from chronological age, mirroring the increased heterogeneity in health status at older ages.ResultsHere, we report on the large-scale identification of 6366 age-related variably methylated positions (aVMPs) identified in 3295 whole blood DNA methylation profiles, 2044 of which have a matching RNA-seq gene expression profile. aVMPs are enriched at polycomb repressed regions and, accordingly, methylation at those positions is associated with the expression of genes encoding components of polycomb repressive complex 2 (PRC2) in trans. Further analysis revealed trans-associations for 1816 aVMPs with an additional 854 genes. These trans-associated aVMPs are characterized by either an age-related gain of methylation at CpG islands marked by PRC2 or a loss of methylation at enhancers. This distinct pattern extends to other tissues and multiple cancer types. Finally, genes associated with aVMPs in trans whose expression is variably upregulated with age (733 genes) play a key role in DNA repair and apoptosis, whereas downregulated aVMP-associated genes (121 genes) are mapped to defined pathways in cellular metabolism.ConclusionsOur results link age-related changes in DNA methylation to fundamental mechanisms that are thought to drive human ageing.