Twin registers across the globe: what's out there in 2002?

Twin research offers the greatest power for the genetic analysis of complex multifactorial traits and diseases in humans. Modern twin analyses extend beyond the classical twin study for estimating the heritability of a trait. The human genome project can fulfil its promises only after functional characterisation of single genes in the context of genetic background and environment. Twin research can make a major contribution in that regard. Twin research is greatly facilitated by the willingness, motivation, cooperation, and generosity of the participants and their families. A second important aspect is the availability of twin registries that serve as a resource for genetic epidemiology. Currently, there is no systematic overview of the twin collections worldwide. This special issue will help to overcome the limited accessibility of this resource by providing basic information on most of the existing twin registers. Furthermore, an additional goal is to facilitate collaboration between registers. Some basic principles, potentials, and problems will be exemplified by my personal experience in the Berlin Twin Study.     

Chinese National Twin Registry as a resource for genetic epidemiologic studies of common and complex diseases in China.

Twins, due to their unique genetic and environmental relationships, have provided crucial insight in our understanding of genetic contributions to numerous etiologically complex disorders in developed countries. As the leading cause of death and adult disability, cardio- and cerebrovascular diseases are common in China, followed by cancer. Obesity and psychological disorders are increasing. The overall goal of this program is to develop a resource for genetic epidemiologic studies of these and other common and complex diseases in China. Our initial focus is to delineate the genetic and environmental determinants of vascular diseases in general, coronary artery disease (CAD) and stroke in particular. To date, we have over 4500 twin pairs registered and about 700 twin pairs studied for various metabolic traits (e.g., lipids, glucose, insulin, etc.). The long-term plan of this program is to (1) establish a population-based twin registry from several selected regions in China for future studies of specific common complex diseases; (2) conduct detailed phenotyping for clinical and intermediate traits related to cardiovascular diseases; (3) expand studies of twins to twin families by including their parents, siblings, and offspring for genetic linkage and association studies; and (4) follow up twins in the registry longitudinally. The goals of the program are health education and promotion of healthy behavior, early identification of cases to provide timely medical attention, and the evaluation of long-term effects of identified risk factors. We want to develop collaborations with investigators who have expertise in cancer, psychological disorders, and other disease areas.     

The Danish Twin Registry: 127 birth cohorts of twins.

The Danish Twin Registry is the oldest national twin register in the world, initiated in 1954 by ascertainment of twins born from 1870 to 1910. During a number of studies birth cohorts have been added to the register, and by the recent addition of birth cohorts from 1931 to 1952 the Registry now comprizes 127 birth cohorts of twins from 1870 to 1996, with a total of more than 65,000 twin pairs included. In all cohorts the ascertainment has been population-based and independent of the traits studied, although different procedures of ascertainment have been employed. In the oldest cohorts only twin pairs with both twins surviving to age 6 have been included while from 1931 all ascertained twins are included. The completeness of the ascertainment after adjustment for infant mortality is high, with approximately 90% ascertained up to 1968, and complete ascertainment of all liveborn twin pairs since 1968. The Danish Twin Registry is used as a source for large studies on genetic influence on aging and age-related health problems, normal variation in clinical parameters associated with the metabolic syndrome and cardiovascular diseases, and clinical studies of specific diseases. The combination of survey data with data obtained by linkage to national health related registers enables follow-up studies both of the general twin population and of twins from clinical studies.     

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.     

全基因组关联研究现状

在过去的5年中, 全基因组关联研究(Genome-wide association study, GWAS)方法已被证明是研究复杂疾病和性状遗传易感变异的一种有效手段。目前, 各国科学家在多种复杂疾病和性状中开展了大量的GWAS, 对肿瘤、糖尿病、心脏病、神经精神疾病、自身免疫及免疫相关疾病等复杂疾病以及一些常见性状(如身高、体重、血脂、色素等)的遗传易感基因研究取得了重大成果。截止到2010年9月11日, 运用GWAS开展了对近200种复杂疾病/性状的研究, 发现了3 000多个疾病相关的遗传变异。文章就GWAS的发展及其在复杂疾病/性状中的应用做一综述。     

Selection strategies for linkage studies using twins.

Genetic linkage analysis for complex diseases offers a major challenge to geneticists. In these complex diseases multiple genetic loci are responsible for the disease and they may vary in the size of their contribution; the effect of any single one of them is likely to be small. In many situations, like in extensive twin registries, trait values have been recorded for a large number of individuals, and preliminary studies have revealed summary measures for those traits, like mean, variance and components of variance, including heritability. Given the small effect size, a random sample of twins will require a prohibitively large sample size. It is well known that selective sampling is far more efficient in terms of genotyping effort. In this paper we derive easy expressions for the information contributed by sib pairs for the detection of linkage to a quantitative trait locus (QTL). We consider random samples as well as samples of sib pairs selected on the basis of their trait values. These expressions can be rapidly computed and do not involve simulation. We extend our results for quantitative traits to dichotomous traits using the concept of a liability threshold model. We present tables with required sample sizes for height, insulin levels and migraine, three of the traits studied in the GenomEUtwin project.     

A twin approach to unraveling epigenetics

The regulation of gene expression plays a pivotal role in complex phenotypes, and epigenetic mechanisms such as DNA methylation are essential to this process. The availability of next-generation sequencing technologies allows us to study epigenetic variation at an unprecedented level of resolution. Even so, our understanding of the underlying sources of epigenetic variability remains limited. Twin studies have played an essential role in estimating phenotypic heritability, and these now offer an opportunity to study epigenetic variation as a dynamic quantitative trait. High monozygotic twin discordance rates for common diseases suggest that unexplained environmental or epigenetic factors could be involved. Recent genome-wide epigenetic studies in disease-discordant monozygotic twins emphasize the power of this design to successfully identify epigenetic changes associated with complex traits. We describe how large-scale epigenetic studies of twins can improve our understanding of how genetic, environmental and stochastic factors impact upon epigenetics, and how such studies can provide a comprehensive understanding of how epigenetic variation affects complex traits.     

同卵双胞胎在复杂性状DNA甲基化调控机制研究中的应用

同卵双胞胎来源于同一个受精卵,DNA序列基本一致,但在某些重要表型上如复杂疾病,并不完全一样。利用表型不一致的同卵双胞胎进行研究,能在遗传背景、母体效应、年龄性别效应等一致的基础上,深入研究分析复杂性状的表观调控机制。而DNA甲基化是最为稳定的一类表观遗传修饰。在人类中,利用同卵双胞胎对印记异常疾病、精神类疾病、自身免疫病及癌症等疾病的DNA甲基化调控研究已经揭示了多个致病基因,为研究疾病的表观调控以及表观遗传学药物的应用打下了基础。本文着重对同卵双胞胎DNA甲基化状态、DNA甲基化遗传力计算以及复杂性状DNA甲基化调控的研究应用及其进展展开综述,以期为复杂性状表观调控机制研究提供借鉴和参考。     

Gene-environment interaction and the mapping of complex traits: some statistical models and their implications

The manifestation of many complex diseases or traits is very likely the result of an inextricable interplay of the biological and the environmental. Yet the role of environmental effect has traditionally been played down, for various reasons. In this paper, some simple statistical models that incorporate gene-environment interaction (GEI) have been proposed and their behavior and implications investigated. These implications concern the conditional independence assumption in likelihood calculation of pedigree data, the fine-tuning of the sib pair method for mapping quantitative traits, apportioning of disease or trait variation due to specific causes. In addition, they concern properties of gene mapping methods that do not take GEI into account, and they bring into question the utility of commonly used measures of genetic effects such as recurrence risk ratio for relative pairs, twin concordance rates, and heritability coefficients. In the presence of GEI, all these measures are functions not only of genetic effects and gene frequency, but also of environmental effects, the distribution of environmental factors in the population, and of GEI. Above all, these measures are all measures of familial aggregation, since they can be significant even in the absence of any genetic component of the disease. Thus their use as indicators of the genetic basis of complex diseases is cast into doubt.     

Progress and promise of genome-wide association studies for human complex trait genetics

Enormous progress in mapping complex traits in humans has been made in the last 5 yr. There has been early success for prevalent diseases with complex phenotypes. These studies have demonstrated clearly that, while complex traits differ in their underlying genetic architectures, for many common disorders the predominant pattern is that of many loci, individually with small effects on phenotype. For some traits, loci of large effect have been identified. For almost all complex traits studied in humans, the sum of the identified genetic effects comprises only a portion, generally less than half, of the estimated trait heritability. A variety of hypotheses have been proposed to explain why this might be the case, including untested rare variants, and gene-gene and gene-environment interaction. Effort is currently being directed toward implementation of novel analytic approaches and testing rare variants for association with complex traits using imputed variants from the publicly available 1000 Genomes Project resequencing data and from direct resequencing of clinical samples. Through integration with annotations and functional genomic data as well as by in vitro and in vivo experimentation, mapping studies continue to characterize functional variants associated with complex traits and address fundamental issues such as epistasis and pleiotropy. This review focuses primarily on the ways in which genome-wide association studies (GWASs) have revolutionized the field of human quantitative genetics.     

The genetics of human personality

Personality traits are the relatively enduring patterns of thoughts, feelings and behaviors that reflect the tendency to respond in certain ways under certain circumstances. Twin and family studies have showed that personality traits are moderately heritable, and can predict various lifetime outcomes, including psychopathology. The Research Domain Criteria characterizes psychiatric diseases as extremes of normal tendencies, including specific personality traits. This implies that heritable variation in personality traits, such as neuroticism, would share a common genetic basis with psychiatric diseases, such as major depressive disorder. Despite considerable efforts over the past several decades, the genetic variants that influence personality are only beginning to be identified. We review these recent and increasingly rapid developments, which focus on the assessment of personality via several commonly used personality questionnaires in healthy human subjects. Study designs covered include twin, linkage, candidate gene association studies, genome‐wide association studies and polygenic analyses. Findings from genetic studies of personality have furthered our understanding about the genetic etiology of personality, which, like neuropsychiatric diseases themselves, is highly polygenic. Polygenic analyses have showed genetic correlations between personality and psychopathology, confirming that genetic studies of personality can help to elucidate the etiology of several neuropsychiatric diseases.     

GenomEUtwin: a strategy to identify genetic influences on health and disease.

In this issue of Twin Research, we describe different facets of a European Community funded effort, GenomEUtwin, which capitalises on eight of the world's largest and best characterised twin registers and a multi-national population cohort, MORGAM. This international study, reaching beyond the geographical borders of Europe, is based on linkage and association strategies designed to identify genetic contributors to health and disease using integrated expertise of participating groups in genetics, epidemiology and biostatistics. By merging information from numerous epidemiological and genetic databases, GenomEUtwin will create an intellectual and technical infrastructure for future genetic epidemiological studies aiming to define genetic and life style risks for common human diseases.     

An update on molecular genetic studies of human personality traits

Personality is a complex phenotype and people differ considerably when they are evaluated by self-report questionnaires. There is convincing evidence from twin studies that basic personality dimensions in men and women have a considerable genetic component. However, only recently have common genetic polymorphisms been associated with particular personality traits, especially the dopamine D4 receptor with novelty seeking and the serotonin transporter with anxiety-related traits or neuroticism. The current review examines progress in the past few years in molecular personality genetics and focuses on the reasons for difficulties in replicating first findings as well as the prospects for future studies in this area. The molecular genetic structure of human personality is worth studying both for its intrinsic interest in helping us to understand individual differences in human behaviour and the light it will shed on more complex behavioural disorders that are likely to partially share some common genetic variants.     

复杂疾病全基因组关联研究进展—— 研究设计和遗传标记

实现全基因组关联研究(Genome-wide association study, GWA)在数年前还是遗传学家们的梦想, 如今它已经变成了现实。自2005年Science杂志报道了第一项有关年龄相关性(视网膜)黄斑变性全基因组关联研究研究以来, 有关与复杂疾病的全基因组关联研究如雨后春笋般层出不穷。文中介绍了近两年来全基因组关联研究在复杂疾病研究领域内的主要发现、全基因组关联研究设计原理、遗传标记的选择、比较及相关商品信息。最后介绍了人类基因组拷贝数变异的研究进展, 总结了人类全基因组关联研究所取得成就和存在的问题, 并对全基因组关联研究未来的研究重点和要解决的问题进行了展望。     

Statistical Power to Detect Genetic (Co)Variance of Complex Traits Using SNP Data in Unrelated Samples

We have recently developed analysis methods (GREML) to estimate the genetic variance of a complex trait/disease and the genetic correlation between two complex traits/diseases using genome-wide single nucleotide polymorphism (SNP) data in unrelated individuals. Here we use analytical derivations and simulations to quantify the sampling variance of the estimate of the proportion of phenotypic variance captured by all SNPs for quantitative traits and case-control studies. We also derive the approximate sampling variance of the estimate of a genetic correlation in a bivariate analysis, when two complex traits are either measured on the same or different individuals. We show that the sampling variance is inversely proportional to the number of pairwise contrasts in the analysis and to the variance in SNP-derived genetic relationships. For bivariate analysis, the sampling variance of the genetic correlation additionally depends on the harmonic mean of the proportion of variance explained by the SNPs for the two traits and the genetic correlation between the traits, and depends on the phenotypic correlation when the traits are measured on the same individuals. We provide an online tool for calculating the power of detecting genetic (co)variation using genome-wide SNP data. The new theory and online tool will be helpful to plan experimental designs to estimate the missing heritability that has not yet been fully revealed through genome-wide association studies, and to estimate the genetic overlap between complex traits (diseases) in particular when the traits (diseases) are not measured on the same samples.     

Genetic and environmental factors in complex diseases: the older Finnish Twin Cohort.

In studies on the Finnish Twin Cohort, we investigate genetic and environmental determinants of common, complex diseases, and their behavioral risk factors in Finland, a genetically unique and culturally homogenous population. We have formed the following databases: 1) Like-sexed twin pairs (13,888 pairs of known zygosity) form the older Twin Cohort. They have participated since 1975 in mail surveys, in clinical examinations for subsamples, and have been followed-up for morbidity using national medical registers; 2) The older Twin Cohort was expanded in 1996 to include opposite-sex pairs born 1938-1957 (c. 8000 pairs); 3) Two, new longitudinal studies of adolescent twins and their families, form a complementary, ongoing study base described in more detail in an accompanying article. Genetic and environmental effects vary over the life-span, and only longitudinal studies in genetically informative data sets permits the evaluation of such effects. Finally, the inclusion of DNA-based genetic information in a phenotypically rich family data base will offer a unique resource for research in genetic epidemiology and behavioral medicine.     

SCtool:识别复杂性状和疾病间遗传关联的工具

识别复杂性状和疾病间遗传关联可以提供有用的病因学见解,并有助于确定可能的因果关系的优先级。尽管已有很多工具可以实现复杂性状和疾病间遗传关联,但是某些工具代码可读性差、并且不同工具基于不同的计算机语言、工具间的串联性较差。因此,本研究基于全基因组关联研究(GWAS)数据,提出了SCtool,一个开源、跨平台和用户友好的软件工具。SCtool整合了ldsc, TwosampleMR和MR-BMA三种软件,其主要功能是基于GWAS汇总水平的数据,识别复杂性状和疾病、复杂性状和复杂性状以及疾病与疾病间的遗传相关性并探究其间潜在的因果关联。最后,使用SCtool揭示了全身性铁状态(铁蛋白,血清铁,转铁蛋白,转铁蛋白饱和度)与表观遗传时钟GrimAge之间的遗传关联。     

Density of common complex ocular traits in the aging eye: analysis of secondary traits in genome-wide association studies

Genetic association studies are identifying genetic risks for common complex ocular traits such as age-related macular degeneration (AMD). The subjects used for discovery of these loci have been largely from clinic-based, case-control studies. Typically, only the primary phenotype (e.g., AMD) being studied is systematically documented and other complex traits (e.g., affecting the eye) are largely ignored. The purpose of this study was to characterize these other or secondary complex ocular traits present in the cases and controls of clinic-based studies being used for genetic study of AMD. The records of 100 consecutive new patients (of any diagnosis) age 60 or older for which all traits affecting the eye had been recorded systematically were reviewed. The average patient had 3.5 distinct diagnoses. A subset of 10 complex traits was selected for further study because they were common and could be reliably diagnosed. The density of these 10 complex ocular traits increased by 0.017 log-traits/year (P = 0.03), ranging from a predicted 2.74 at age 60 to 4.45 at age 90. Trait-trait association was observed only between AMD and primary vitreomacular traction (P = 0.0009). Only 1% of subjects age 60 or older had no common complex traits affecting the eye. Extrapolations suggested that a study of 2000 similar subjects would have sufficient power to detect genetic association with an odds ratio of 2.0 or less for 4 of these 10 traits. In conclusion, the high prevalence of complex traits affecting the aging eye and the inherent biases in referral patterns leads to the potential for confounding by undocumented secondary traits within case-control studies. In addition to the primary trait, other common ocular phenotypes should be systematically documented in genetic association studies so that adjustments for potential trait-trait associations and other bias can be made and genetic risk variants identified in secondary analyses.