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Sex differences in the genetic architecture of optimism and health and their interrelation: a study of Australian and Swedish twins

Mosing, MA (författare)
Pedersen, NL (författare)
Karolinska Institutet
Martin, NG (författare)
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Wright, MJ (författare)
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 (creator_code:org_t)
2012-02-21
2010
Engelska.
Ingår i: Twin research and human genetics : the official journal of the International Society for Twin Studies. - : Cambridge University Press (CUP). - 1832-4274. ; 13:4, s. 322-329
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
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  • Optimism has a positive influence on mental and somatic health throughout lifetime and into old age. This association is mainly due to shared genetic influences, with some indication of sex differences in the heritability of these and related traits (e.g., depression and subjective wellbeing). Here we extend our initial study of Australian twins by combining with data available from Swedish twins, in order to increase the power to explore potential sex differences in the genetic architecture of optimism, mental and self-rated health and their covariation. Optimism, mental, and self-rated health were measured in 3053 Australian (501 identical female (MZf), 153 identical male (MZm), 274 non-identical female (DZf), 77 non-identical male (DZm), and 242 non-identical opposite-sex twin pairs, and 561 single twins; mean age 60.97 ± 8.76), and 812 Swedish (71 MZf, 53 MZm, 93 DZf and 67 DZm twin pairs, and 244 single twins; mean age 60 ± 14.3) twin individuals using the Life Orientation Test (LOT), the General Health Questionnaire (GHQ) and a single-item self-rating of overall health, respectively. In females all three traits were moderately heritable (.27–.47), whereas in males heritability was substantially lower (.08–.19), but genetic modeling showed that sex differences were not significant. The absence of significant sex differences, despite the consistent trend across the two cohorts, is likely due to a lack of power, raising the importance for future studies, on the same or similar traits, to utilize large samples and to keep the possibility of sex differences in mind when conducting their analyses.

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