Purpose of Twin Studies

Twin studies typically have three main aims: to obtain relevant information of twins, by twins, and for twins. Studies of twins are designed to collect information about factors differentiating twins from singletons, such as the development of linguistic abilities and sibling relationships. Studies by twins are typically behavioral genetic studies in which genetically and environmentally systematic information of twins are utilized as a biometrical method. This second type of research is the focus of the KoTReC. Studies for twins are focused on providing evidence-based support for nursing and educating twins, mainly in infancy and childhood, by producing relevant information about the causes of parenting stress and environmental effects on infant growth and development.

The age ranges of the two cohorts in the KTS and ToTCoP are different, and the aims of the projects also differ. In the KTS, which includes participants between 15 and 40 years of age, almost all the research is conducted with a behavioral genetic focus (i.e., a by-twins study), including psychological, psychiatric, sociological, socio-economic, neurological, and molecular genetic characteristics. On the other hand, the ToTCoP, which examines twin participants from birth to 6 years of age, includes all three of the main aims of twin studies. For studies of twins, a set of singleton data that is comparable to twin data were obtained for several important variables.

Recruitment of Twin Participants

The strategy to recruit twins and their families in both the KTS and ToTCoP is to send letters to twin families identified by the Basic Resident Register (BRR; nation-wide census). The BRR is a quasi-complete (i.e., complete at a specific time in a specific area) residential record of each municipal area, which contains each resident's name, gender, residential address, and date of birth. This information gathering is authorized by each municipal area's regulations, and data are available at city halls. Twins or higher multiples can be identified as individuals who share the same date of birth and address. With this method, it is difficult to recruit newborn and adult twins because it takes several months for newborns to be registered on the BRR and because most adult twins live apart. Because these data are not obtained electronically, but rather by printed documents with a substantial cost, well-trained staff are required to identify multiple births and transfer the information manually. This strategy has a number of methodological shortcomings (see Ando et al., Reference Ando, Nonaka, Ozaki, Sato, Fujisawa, Ozaki and Ooki2006), but it is the only way to obtain ‘population-based’, rather than hospital-based or twin support group-based, twin data in Japan.

These research projects included three residential twin data collection periods from the BRR (1998–2002, 2003–2004, 2009), and cover the Tokyo metropolis and the neighboring prefectures (Kanagawa, Chiba, and Saitama). The 1998–2002 data contain approximately 10,000 pairs, which substantially overlap with the 2003–2004 data set, which contains 46,000 pairs. In addition, data from around 1,000 pairs of twins under 3 years of age were added in 2009. Currently, approximately 48,000 sets of multiple birth families are registered at our center.

Additional recruitment of twin child cohorts was conducted by voluntary participation through a poster campaign in public healthcare centers in the target areas and magazine advertisements in publications distributed nation-wide.

Zygosity Diagnosis and DNA Data

In order to identify twins’ zygosity, the KTS project mainly used a three-item questionnaire administered to twins themselves (Ooki et al., Reference Ooki, Yamada, Asaka and Hayakawa1990), whereas the ToTCoP administered the questionnaire to parents (Ooki & Asaka, Reference Ooki and Asaka2004). These questionnaires asked for judgments about the twins’ physical similarities, and experiences of being mistaken for each other. The items in the ToTCoP questionnaire (and the KTS questionnaire) were as follows: ‘Were your twin children (you and your co-twin) as alike as two peas in a pod?’ ‘Were your twin children (you and your co-twin) mixed up (as children)?’ and ‘If so, by whom were your twin children (you) mixed up?’ This questionnaire has been found to have almost 95% accuracy by comparison with genetic markers (Ooki & Asaka, Reference Ooki and Asaka2004).

DNA samples were collected from approximately 600 pairs of adult twins (KTS) by analyzing blood (approximately 240 pairs in 1998, partially replicated in 1999), buccal smear (approximately 200 pairs in 2005), nail or hair roots (approximately 100 pairs in 2010), and saliva (approximately 60 pairs in 2011; Table 1). These DNA data were also used to identify zygosity. Agreement rate between the DNA-based diagnoses and the questionnaire-based diagnoses was 93.0% (94.3% for monozygotic (MZ) and 87.5% for dizygotic (DZ); a preliminary result was reported by Shikishima et al., Reference Shikishima, Ozaki, Ando, Toda and Yoshimura2007).

TABLE 1

Data Collection History of the KTS (KTP)

Note: ^aBl = blood; S = saliva; Bc = buccal smear; N = nail; H = hair root.

^bPG = public game; D = dictator game; U = ultimatum game.

Abbreviation of instruments not introduced in the text.

SPSRQ (The Sensitivity to Punishment and Sensitivity to Reward Questionnaire; Torrubia et al., Reference Torrubia, Avila, Molto and Caseras2001); EC (Japanese version of Effortful Control Scale; Yamagata et al., Reference Yamagata, Takahashi, Ozaki, Fujisawa, Nonaka and Ando2005b); Klein Grid (Klein et al., Reference Klein, Sepekoff and Wolf1985); RSES (Rosenberg Self-Esteem Scale; Rosenberg, Reference Rosenberg1965); PSAI (Pre-School Activities Inventory; Golombok & Rust, Reference Golombok and Rust1993); BSRI (Bem Sex Role Inventory; Bem, Reference Bem1974); EAT (Eating Attitude Test; Garner et al.,1982); TFEQ-R21 (Three Factor Eating Questionnaire; Stunkard & Messick, Reference Stunkard and Messick1985); SIDE (The Sibling Inventory of Differential Experience; Daniels & Plomin, Reference Daniels and Plomin1985); PBI (Parental Bonding Instrument; Parker et al., Reference Parker, Tupling and Brown1979); FACESIII (Family Adaptability and Cohesion Scale; Olson, Reference Olson1985).

In the following sections, the research design and major findings of each of the sub-projects at the KoTReC are introduced.

The KTS

The KTS, originally named the Keio Twin Project (Shikishima et al., Reference Shikishima, Ando, Ono, Toda and Yoshimura2006), was established in 1998 to conduct behavioral genetic studies in adolescence and early adulthood. Twins entering the study in 1998 were aged between 15 and 30 years of age, and new participants within the same age range were added subsequently. Table 1 shows the major variables and survey administration year by year. As shown in the table, there were six entry time points in 1998, 1999, 2001, 2002, 2007, and 2011, totaling more than 2,000 twin pair data sets, some of which include their parents’ data.

The variables investigated include cognition (general and specific cognitive abilities), decision-making tasks, personality traits (two-, five-, and seven-factor models), mental health, attitude and gender, eating, physical traits, and family and school environment.

Cognition and Decision Making

Cognition has been an important phenotype of interest in the history of behavioral genetics. At the KoTReC, the Kyodai Nx15- (Lynn et al., Reference Lynn, Hampson and Bingham1987; Osaka & Umemoto, Reference Osaka and Umemoto1973, Shikishima et al., Reference Shikishima, Hiraishi, Yamagata, Sugimoto, Takemura, Ozaki and Ando2009) is used as a full-scale intelligence test to measure individual difference of general cognitive ability in adolescence and adulthood. The Kyodai Nx15- is the most systematic group intelligence test available for this age range in Japan, and consists of 12 sub-scales covering verbal and spatial aspects of reasoning, memory, and processing speed. In situations where the full-scale version is too long to be administered (i.e., in an experimental session with many variables), a four-subscale version with two verbal and two spatial sub-tests is used.

Overall, our results indicate that the cognitive domain is a unitary feature of its genetic structure. Ando et al. (Reference Ando, Ono and Wright2001) reported that different aspects of working memory, storage, and executive functions of verbal and spatial modalities are mediated by a single latent genetic factor that also explains general cognitive ability, measured by the sub-scale version of the Kyodai Nx-15. Shikishima and colleagues developed a syllogistic reasoning test called BAROCO (Shikishima et al., Reference Shikishima, Hiraishi, Yamagata, Sugimoto, Takemura, Ozaki and Ando2009), named from a mnemonic word to memorize a syllogism form in classical logic, with 100 items, and reported that its genetic component completely overlapped with those of the Kyodai Nx-15. Based on these findings, a shortened five-item version, the BAROCO Short, was developed and validated (Shikishima et al., Reference Shikishima, Hiraishi, Yamagata and Ando2011a).

Researchers in our project recently began investigating the possibility of a ‘general intelligence gene’ by comparing epigenetic differences of discordant identical twin siblings (Yu et al., Reference Yu, Furukawa, Kobayashi, Shikishima, Cha and Toda2012).

Gender differences in spatial ability were independently investigated using a mental rotation task (Suzuki et al., Reference Suzuki, Shikishima and Ando2011; Vandenberg & Kuse, Reference Vandenberg and Kuse1978). A sex limitation analysis revealed that there were no gender-specific genetic factors affecting this trait, but that the additive genetic influence was greater in males.

Endophenotypes of cognitive abilities, event-related potential (ERP) indices in a working memory task and electroencephalography under resting conditions with eyes open and closed were measured individually for approximately 150 pairs of twins, together with the full-scale Wechsler Adult Intelligence Scale and specific cognitive abilities, simple reaction time and inspection time, in an international collaborative study (Wright et al., Reference Wright, De Geus, Ando, Luciano, Psothuma, Ono and Boomsma2001). These data, and data from another endophenotype (structural brain imaging examined using magnetic resonance imaging), will be analyzed and published in the near future.

We recently began to conduct behavioral genetic studies of ‘decision-making’ tasks, such as economic games (a public goods task, and the dictator and ultimatum games), time preferences, and Allais and Ellsberg paradoxes, which are commonly used tasks in behavioral economics. Collaborative studies with economists are also underway at the center.

Personality and Mental Health

Personality traits have been another important research focus in behavioral genetics, and studies in our project have investigated the genetic structure of personality and related phenotypes. Ono and colleagues reported the results of a univariate genetic analysis of the five-factor model of personality using the NEO Personality Inventory Revised Test (NEO-PI-R, Costa & McCrae, Reference Costa and McCrae1992; Yoshimura et al., Reference Yoshimura, Nakamura, Ono, Sakurai, Saito, Mitani and Asai1998). The results clearly replicated a very robust finding of this field that there are substantial genetic and non-shared environmental influences on personality traits (Ono et al., Reference Ono, Ando, Onoda, Yoshimura, Kanba, Hirano and Asai2000). Yamagata conducted an international comparative study of the five-factor model by conducting genetic factor analysis based upon 30 sub-scales of the NEO-PI-R, revealing that the genetic structure is strikingly congruent among Japan, Germany, and Canada (Yamagata et al., Reference Yamagata, Suzuki, Ando, Ono, Kijima, Yoshimura and Jang2006). Using the same data set, Jang reported genetic comorbidity between Neuroticism and Agreeableness, and their molecular bases (Jang et al., Reference Jang, Hu, Livesley, Angleitner, Riemann, Ando and Hamer2001), and proposed a two-higher-order-genetic-factor structure of the Big Five factors (Jang et al., Reference Jang, Livesley, Ando, Yamagata, Suzuki, Angleitner and Spinath2006). Furthermore, McCrae, who originally developed the NEO-PI-R, reported that these higher-order genetic factors contained artifacts as well as substance effects (McCrae et al., Reference McCrae, Yamagata, Jang, Riemann, Ando, Ono and Spinath2008). Conversely, Rushton proposed a single general personality factor model and reported its genetic validity using our NEO-PI-R and the Temperament and Character Inventory (TCI) data (Rushton et al., Reference Rushton, Bons, Ando, Hur, Irwing, Vernon and Barbaranelli2009).

The TCI was developed by Cloninger, based upon his theory of personality development (Cloninger et al., Reference Cloninger, Svrakic and Przybeck1993), which proposes that four temperamental traits (Novelty Seeking, Harm Avoidance, Reward Dependence, and Persistence) are driven by genetic neurotransmission-related factors, whereas three character traits (Self-Directedness, Cooperativeness, and Self-Transcendence) are determined by post-natal experience. A study in our project attempted to verify this theory, revealing that Novelty Seeking, Harm Avoidance, and Reward Dependence are genetically independent, as Cloninger et al.'s (Reference Cloninger, Svrakic and Przybeck1993) theory predicts, but persistence and the three character traits exhibited genetic overlap with the three temperamental traits (Ando et al., Reference Ando, Ono, Yoshimura, Onoda, Shinohara, Kanba and Asai2002). In addition, we found that one facet of Novelty Seeking (Exploratory Excitement) is strongly genetically correlated with Harm Avoidance, so should be rearranged by changing combination of facets to make scales genetically consistent (Ando et al., Reference Ando, Suzuki, Yamagata, Kijima, Maekawa, Ono and Jang2004). Yamagata and colleagues (Reference Yamagata, Takahashi, Kijima, Maekawa, Ono and Ando2005) applied the same methodology to examine the genetic structure of Effortful Control (Rothbart et al., Reference Rothbart, Ahadi and Evans2000) and confirmed its genetic coherence, supporting the validity of the theory.

Ono and colleagues investigated the genetic and environmental overlap between temperamental TCI traits and depressive symptoms measured by the Hospital Anxiety Depression Scale (Kitamura, Reference Kitamura1993; Zigmond & Snaith, Reference Zigmond and Snaith1983), suggesting that there are no independent ‘depression-specific genes’, but that depressive symptoms are dependent on genetic factors involved in normal temperamental dimensions under specific unique environments (Ono et al., Reference Ono, Ando, Onoda, Yoshimura, Momose, Hirano and Kanba2002). The twin studies at KoTReC are not hospital-based studies, and no medically diagnosed participants have been identified. However, the data from several scales related to mental health and psychiatry, including the Subjective Well-Being Inventory (SUBI; Sell & Nagpal, Reference Sell and Nagpal1992), the Autism-Spectrum Questionnaire (AQ; Baron-Cohen et al., Reference Baron-Cohen, Hoekstra, Knickmeyer and Wheelwright2006), the State and Trait Anxiety Inventory (STAI; Spielberger et al., Reference Spielberger, Gorsuch and Lushene1970), the Zung Self-Rating Depression Scale (SDS), the Quick Inventory of Depressive Symptomatology (QID-SR), and the Quality of Life Scale (QLS; Rush et al., Reference Rush, Trivedi, Ibrahim, Carmody, Arnow, Klein and Keller2003), are available for our normal twin samples. In addition, a univariate genetic analysis of Eating Disorder Inventory (EDI) data in this sample revealed substantial shared environmental influences on four of five sub-scales of the EDI (Kamakura et al., Reference Kamakura, Ando and Ono2003).

Because the KTS is designed in a longitudinal fashion as shown in Table 1, several cognitive and personality phenotypes were measured at different time points for the same individuals. Developmental changes and the stability of the Behavioral Inhibition System (BIS) and Behavioral Activation System (BAS; Carver & White, Reference Carver and White1994) — two measures of temperament based on Gray's reinforcement sensitivity theory — have been investigated (Takahashi et al., Reference Takahashi, Yamagata, Kijima, Shigemasu, Ono and Ando2007). The results indicated that genetic influences contribute only to continuity, whereas environmental influences contribute to both continuity and change in the two traits, and that the degree of genetic influences does not differ across time.

Attitudes

Results similar to those reported by Takahashi et al.'s (Reference Takahashi, Yamagata, Kijima, Shigemasu, Ono and Ando2007) BIS/BAS longitudinal study were reported for the self-esteem scale (Kamakura et al., Reference Kamakura, Ando and Ono2007). Developmental stability was affected by genetic and non-shared environmental factors, whereas developmental changes were affected by non-shared environmental factors. However, the degree of genetic influence increased during adolescence and young adulthood.

Self-esteem is a personality trait, and can be considered as a type of attitude. Our twin studies have involved a number of measures of attitudes other than self-esteem, such as general trust, voting behavior, empathy, and authoritarianism (Table 1). Shikishima reported a series of behavioral genetic studies on attitude variables traditionally thought to be transmitted through the family environment. The results revealed a substantial genetic influence on authoritarianism (Shikishima et al., Reference Shikishima, Ando, Yamagata, Ozaki, Takahashi and Nonaka2008) and trust (Shikishima et al., Reference Shikishima, Ando, Ono, Toda and Yoshimura2006), with no significant effect of shared environmental factors. However, significant environment × environment interactions were found, indicating that shared family environmental factors significantly affected empathy for individuals exhibiting high or very low parental warmth (Shikishima et al., Reference Shikishima, Yamagata, Hiraishi, Sugimoto, Murayama and Ando2011b). A study using direction of causation (DOC) analysis (Heath et al., Reference Heath, Kessler, Neale, Hewitt, Eaves and Kendler1993), an application of behavioral genetic methodology, revealed that the level of general trust can be predicted by personality factors (Extraversion and Agreeableness; Hiraishi et al., Reference Hiraishi, Yamagata, Shikishima and Ando2008a), indicating that humans adaptively control the activation of domain-specific mental mechanisms in accord with domain-general genetic traits like personality.

Other Variables

As shown in Table 1, a large number of variables have been investigated in previous studies, some of which have been published. These variables include eating disorder symptoms (EDI; Kamakura et al., Reference Kamakura, Ando and Ono2003), gender role personality factors (Sasaki et al., Reference Sasaki, Yamagata, Shikishima, Ozaki and Ando2009), testosterone (Uchida et al., Reference Uchida, Bribiescas, Ellison, Kanamori, Ando, Hirose and Ono2006), the relationship between second to fourth finger ratio (2D4D) and sexual orientation (Hiraishi et al., Reference Hiraishi, Sasaki, Shikishima and Ando2012), and parenting (Shikishima et al., in press).

In 2002, 2010, and 2011, parents of the twin participants in our studies provided information about several additional variables. Since 2009, the Web interface of our project (http://www.futago-labo.net/ in Japanese only) has been available to supplement some experimental and questionnaire data.

The ToTCoP

ToTCoP was established to conduct a longitudinal cohort twin study starting from 2003 (Ando et al., Reference Ando, Nonaka, Ozaki, Sato, Fujisawa, Ozaki and Ooki2006) and continues to conduct studies of, by, and for twins from infancy. This project consists of four data sources; (1) questionnaires (Table 2), (2) cognitive and social investigations in the home (Table 3), (3) cognitive, linguistic, and social investigations in university-based laboratories (Table 4), and (4) brain activity and motor skill experiments in university-based laboratories.

TABLE 2

Timeline of Investigation Tools in Questionnaire-Based Research

ADHD-RS-IV = ADHD Rating Scale — IV, (DuPaul et al., Reference DuPaul, Power, Anastopoulos and Reid1998); BISQ = Brief Infant Sleep Questionnaire, (Sadeh, Reference Sadeh2004); BIS/BAS = Behavioral Inhibition and Activation Systems Scales (Carver & White, Reference Carver and White1994); CBQ = Children's Behavior Questionnaire (Ahadi et al., Reference Ahadi, Rothbart and Ye1993); CFQ = Child Feeding Questionnaire (Birch, Reference Birch, Fisher, Grimm-Thomas, Markey, Sawyer and Johnson2001), Denver II (Frankenburg et al., Reference Frankenburg, Dodds, Archer, Shapiro and Bresnick1992); ECBQ = Early Childhood Behavior Questionnaire (Putman et al., Reference Putman, Jones and Rothbart2002); EES = Evaluation of Environmental Stimulation (Anme, Reference Anme1997); MAI = Maternal Attachment Inventory (Müller, Reference Müller1994); IBQ-R = Infant Behavior Questionnaire-Revised (Gartstein & Rothbart, Reference Gartstein and Rothbart2003; Nakagawa & Sukigawa, Reference Nakagawa and Sukigawa2005); MEQ = Morningness-Eveningness Questionnaire (Horne & Östberg, Reference Horne and Östberg1976); M-CHAT = Modified Checklist for Autism in Toddlers (Baron-Cohen et al., Reference Baron-Cohen, Allen and Gillberg1992; Robins et al., Reference Robins, Fein, Barton and Green2001); ODBI = Oppositional Defiant Behavior Inventory (Harada et al., Reference Harada, Saitoh, Iida, Sakuma, Iwasaka, Imai and Amano2004); PTCI = Preschool Temperament & Character Inventory (Constantino et al., Reference Constantino, Cloninger, Clarke and Hashemi2002); KINDL = Questionnaire for Measuring Health-Related Quality of Life in Children and Adolescents (Bullinger et al., Reference Bullinger, Mackensen and Kirchberger1994); RAM = Relationship Attribution Measure (Fincham & Bradbury, Reference Fincham and Bradbury1992); SDQ = Strength and Difficulty Questionnaire (Goodman, Reference Goodman1999); SDS = Self-rated Depression Scale (Zung, Reference Zung1965); SIB = The Sibling Inventory of Behavior (Volling & Blandon, Reference Volling, Blandon, Anderson Moore and Lippman2005); Short Marital-Adjustment Scale (Locke & Wallace, Reference Locke and Wallace1959).

TABLE 3

Timeline of Home Assessment

Bayley = Bayley Scales of Infant Development (Bayley, Reference Bayley1993); ESCS = Early Social Communication Scales (Mundy et al., Reference Mundy, Delgado, Block, Venezia, Hogan and Seibert2003); K-ABC = Kaufman Assessment Battery for Children (Kaufman & Kaufman, Reference Kaufman and Kaufman1983); CDI = MacArthur Communicative Developmental Inventories (Fenson et al., Reference Fenson, Dale, Reznick, Thal, Bates, Hartung and Reilly1993); PSI = Parenting Stress Inventory (Abidin et al., Reference Abidin1995) ; Marital love (Locke & Wallace, Reference Locke and Wallace1959).

TABLE 4

Timeline of Laboratory Assessment

PFQ = Parental Feelings Questionnaire (Deater-Deckard, Reference Deater-Deckard1996; Deater-Deckard, Reference Deater-Deckard2000); PDI = Parental Discipline Interview, (Deater-Deckard, Reference Deater-Deckard2000); SIB = Sibling Inventory of Behavior (Volling & Blandon, Reference Volling, Blandon, Anderson Moore and Lippman2005); MISR = Maternal Interview of Sibling Relationships (Stoclker et al., 1989).

Questionnaire-Based Research

Table 2 shows the timeline of the questionnaire investigation tools used for each specific time point from infancy to childhood when twins enter elementary school. The variables in these questionnaires are related to children's characteristics and parents’ characteristics, and both types of questions are given to both mothers and fathers until participants are 36 months old. The versions for fathers are partially shortened or different from the versions for mothers, which contain additional items regarding parenting stress. When participants are aged 42 months or older, the questionnaires are administered only to twins’ mothers, because asking twins’ fathers to answer questionnaires tended to lower the total response rate, and the reliability of fathers’ evaluations of twins’ behavior was low.

As Table 2 indicates, the number of participating twin families (over 1,600) was relatively large at the first session, constituting approximately 55% of the total twin births in the target area. Although we observed a high degree of data attrition, we retained substantial numbers of twin pairs that could be investigated longitudinally. For example, Fujisawa and colleagues investigated the relationship between head circumference growth from birth to 10 months of age, and socio-cognitive ability at 19 months. Although no significant phenotypic correlation was found between them, significant genetic and shared environmental correlations in opposite directions (i.e., genetically negative and environmentally positive) were reported (Fujisawa et al., Reference Fujisawa, Ozaki, Ozaki, Yamagata, Kawahashi and Ando2012a). In addition, Yamagata examined the longitudinal association between authoritative parenting and children's peer problems at 42 and 48 months using a longitudinal MZ twin difference design. They reported that when genetic and family environmental covariates were controlled, authoritative parenting and children's peer problems concurrently influenced each other, peer problems increased authoritative parenting, and authoritative parenting decreased peer problems, canceling each other out (Yamagata et al., in press).

For preschool and first grade elementary school children, additional twin families were recruited. The main research target of these two age groups is social adaptation to changes in educational environmental conditions from preschool to elementary school. To tap these time-specific features of environmental change, we conducted preliminary but relatively large-scale studies with approximately 1,000 non-twin individuals to develop appropriate items.

Performance-Based Research at Home and in the University Lab

Two independent performance-based studies (with some overlapping twin pairs) are currently underway, as shown in Table 3 (assessment and observation at home) and Table 4 (assessment in the university laboratory). Both studies involve individual cognitive ability tests (Bayley II for younger and Kaufman Assessment Battery for Children (K-ABC) for older twin children), theory of mind and executive function tasks, questionnaires, and observation of dyadic and triadic interactions between twin siblings and among twin siblings and parents.

One of the main purposes of our studies is to investigate the development of pre-reading skills and the relationship with cognitive abilities during early childhood. The Japanese kana writing system is different from alphabetic systems such as English. Our experiments are designed to be comparable with English language experiments, such as Byrne et al.'s (Reference Byrne, Deleland, Fieldling-Barnsley, Quain, Samuelson, Hoien and Olson2002) study. We developed a Japanese version of a test battery to measure pre-reading skills such as phonological awareness, non-word repetition, receptive vocabulary, and visual perceptual skills (Kakihana et al., Reference Kakihana, Ando, Koyama, Iitaka and Sugawara2009). Preliminary results revealed a significant influence of shared environmental factors on kana pre-reading skills, and no significant effect of genetic influence (Fujisawa et al., Reference Fujisawa, Wadsworth, Kakihana, Olson, DeFries, Byrne and Ando2012b). However, we found that genetic factors had significant and stable effects on cognitive abilities (Fujisawa & Ando, Reference Fujisawa and Ando2010, Reference Fujisawa and Ando2011).

As mentioned above, studies of twins typically have another important aim. As such, we compared twin siblings with non-twin siblings to investigate the relationship between sibling relationships and social adjustment among children. We found that the effects of sibling relationships on pro-social behaviors and conduct problems were stronger for twin siblings than for non-twin siblings, and positive relationships between siblings increased peer problems only among MZ twins; this is the opposite effect compared with that reported among DZ twins and non-twin siblings (Nozaki et al., in press).

Three Independent Anonymous Twin Studies

Longitudinal studies place a heavy burden on participants, sometimes resulting in severe data attrition. To obtain large samples to verify specific research questions, the KoTReC conducted three independent ‘anonymous’ twin studies (i.e., twins who received questionnaire mails do not have to inform their names to the KoTReC, which lets them know that they are not followed longitudinally and reduces their burdens to collaborate in our research), a large-scale cross-sectional twin study (CROSS) and two high school twin studies.

The CROSS was conducted in 2007 with over 4,000 pairs of twins and their parents, with an age range of 3 to 26 years old. There were five age categories: early childhood from 3 to 5 years old, middle childhood from 6 to 9 years, late childhood from 10 to 12 years, adolescence from 12 to 18 years, and adulthood from 19 to 26 years.

The design and sample size of this study is shown in Table 5. As shown in the table, the item questions in the CROSS were not based upon standardized, well-organized, or internationally used psychological scales like those in our cohort studies. Rather, the CROSS used independent measures focusing on specific questions, even though some were related and can be grouped in categories such as academic performance and parental stress. For example, Strengths and Difficulties Questionnaire (SDQ; Goodman, Reference Goodman1999) data were used to examine genetic and environmental influences on the relationship between negative parenting and conduct problems of children in terms of attention deficit hyperactivity disorder status (Fujisawa et al., Reference Fujisawa, Yamagata, Ozaki and Ando2012c).

TABLE 5

The Variables List of the CROSS Study

Two high school twin studies (Table 6) were conducted to investigate the genetic and environmental relationships between educational attainment, cognitive ability, and family social environment. Murayama and colleagues (Reference Murayama, Elliot and Yamagata2011) applied academic motivation data to verify the performance-approach and performance-avoidance achievement goal theories (Murayama et al., Reference Murayama, Elliot and Yamagata2011).

TABLE 6

Items of Two Anonymous High School Twin Studies

Ozaki (Reference Ozaki2008) challenged methodological limitations using paired comparison analysis applied to biometric modeling (Ozaki, Reference Ozaki2008), non-normal structural equation modeling with higher order moments applied to DOC (Ozaki & Ando, Reference Ozaki and Ando2009), and estimation of four parameters (additive genetic, non-additive genetic, shared, and non-shared environmental factors) at the same time (Ozaki et al., Reference Ozaki, Toyoda, Iwama, Kubo and Ando2011).