Allgulander et al. (Allgulander C, Nowak J, Rice JP (1991) Acta Psychiatr Scand 83, 12) published twin pair analyses of psychiatric hospitalization for like-sex pairs from the Swedish Twin Registry born 1926–1958. As noted in a subsequent letter (Allgulander C, Nowak J, Rice JP (1992) Acta Psychiatr Scand 86, 421), several features of the original study resulted in under-ascertainment of cases and underestimated heritability, particularly for alcoholism. The present report updates the prior results by using 17 additional years of follow-up, including members of opposite-sex twin pairs, and addressing biases arising from cohort effects and from excluding pairs with unknown zygosity.
Registry records for 29,602 twin pairs born 1926–1958 were matched against national databases of psychiatric and medical hospitalizations from 1972–2000 to obtain ICD diagnostic codes. Zygosity was known for 10,903 opposite-sex pairs and 15,401 like-sex pairs who participated previously in research. Twin-pair resemblance and genetic and environmental variance proportions were estimated for hospitalization for alcoholism, affective disorders, psychosis, and (in females) anxiety disorders.
Hospitalization rates during the ascertainment window were: alcoholism: males = 3.67%, females = 0.94%; affective disorders: males = 1.99%, females = 2.75%; anxiety disorders: males = 0.46%, females = 0.74%; and psychotic disorders: males = 1.70%, females = 1.96%. Twins from like-sex pairs with unknown zygosity had significantly higher prevalences than those with known zygosity. Tetrachoric correlations and heritability estimates were affected by the method used to model unknown zygosity and cohort effects.
Inclusion of additional follow-up information, opposite-sex twin pairs, age-adjustment, and use of current ICD definitions yielded higher heritability estimates for alcoholism, anxiety disorders, and psychosis than previously published for this nationally-representative sample of twins from Sweden. The results show that relatively small selection biases can alter twin study results and underscore the importance of addressing under-ascertainment of cases in genetic research based on volunteers.
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The disorders and ICD codes corresponding to each diagnostic category were as follows: Alcoholism: alcohol dependence, alcohol abuse, alcohol-induced psychosis (ICD-7: 307,322; ICD-8: 291,303; ICD-9: 291,303,305.0); Anxiety Disorders: anxiety reaction, anxiety neurosis, phobic reaction, phobic neurosis, obsessive-compulsive reaction, obsessive-compulsive neurosis (ICD-7: 310,312,313; ICD-8 & ICD-9: 300.0, 300.2, 300.3); Affective Disorders: depressive neurosis, affective personality disorder, depressive disorder, affective psychosis (ICD-7: 301302314; ICD-8: 296,300.4,301.1; ICD-9: 296,300.4,301.1,311); Psychosis: schizophrenia, affective psychosis, acute psychosis, unspecified psychosis, paranoia (ICD-7: 300-303,309; ICD-8 & 9: 295-299); Substance Abuse: drug dependence, drug abuse, drug-induced psychosis (ICD-7: 323; ICD-8: 294.3, 304; ICD-9: 292, 304, 305.2-305.9).
In preliminary analyses, the bootstrapping was also done under an assumption of a 50:50 MZ:DZ ratio among unknown pairs. The results were essentially identical to those obtained using sample-based proportions, which is not surprising given the very low prevalences being studied. Based on the correlations from each bootstrapped data set, we calculated genetic and environmental parameters based on algebraic expectations. That is, within each sex, h2 = 2*(rMZ−rDZ), c2 = rMZ−h2, e2 = 1−(h2 + c2), with the additional restrictions of h2 ≥ 0 and c2 ≥ 0 (i.e., if rDZ > rMZ for a sample, h2 was set to 0 and c2 was fixed to the weighted average of rMZ and rDZ). These calculations are based on the same expectations as a structural model analysis, and yield the same results under the conditions of a saturated model and approximately equal group sizes. We used this method for convenience as all the calculations could be done using a SAS macro rather than transferring the 1,000 data sets into another program. Based on the bootstrapping analyses, we obtained 1,000 sets of the four like-sex pair correlations and six parameter estimates (a2, c2, and e2 for males and females). The datasets for males and females were independent. Doing all possible combinations of each male dataset with each female dataset would have meant 1,000,000 runs and was unnecessary, because the male and female bootstraps were independent and we were using a saturated model (i.e., there was no dependence between the male and female parameter estimates). Within each sex, there is nearly complete dependence between the MZ and DZ correlations (e.g., across the 1,000 runs, the correlation of the rMZ and rDZ estimates is r = −0.98). Thus, the upper and lower bounds of the confidence intervals for the parameters considered individually are virtually identical (±0.01) to the upper and lower bounds for the joint distribution of h2 and c2.
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The Swedish Twin Registry is supported by grants from the Swedish Scientific Council, the Swedish Ministry of Higher Education, and Astra Zeneca. The authors are grateful to Lisa Halberstadt for helpful comments and J. J. McArdle for statistical advice. Preparation of this manuscript was supported by grants R01-AA-11408 and K01-AA-00236 from the U.S. National Institutes of Health and an Independent Investigator award from the National Alliance for Research on Schizophrenia and Affective Disorders (to CAP). Rebecca Ortiz assisted with manuscript preparation.
Edited by Peter McGuffin
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Prescott, C.A., Kuhn, J.W. & Pedersen, N.L. Twin Pair Resemblance for Psychiatric Hospitalization in the Swedish Twin Registry: A 32-year Follow-up Study of 29,602 Twin Pairs. Behav Genet 37, 547–558 (2007). https://doi.org/10.1007/s10519-007-9143-6