Susan A. Treloar

Genetic influences on endometriosis in an Australian twin sample

OBJECTIVE To investigate the prevalence of and twin pair concordance for endometriosis. DESIGN A questionnaire survey incorporating validation. SETTING An Australia-wide volunteer sample of female monozygotic (MZ) and dizygotic (DZ) twin pairs from the Australian National Health and Medical Research Council Twin Register. PATIENT(S) Twins were selected only on the basis of previous participation in twin research. INTERVENTION(S) Questionnaires were sent to 3,298 individuals. Information was requested from physicians named by consenting twins. MAIN OUTCOME MEASURE(S) Reported endometriosis, validated where possible by pathology or surgical report. RESULT(S) Three thousand ninety-six (94%) of the twins and 145 (82%) of the physicians responded to the survey. Two hundred fifteen twins reported endometriosis, for a prevalence rate of .07 among question respondents. Tetrachoric twin pair correlations for self-reported endometriosis (MZ: n = 854 and DZ: n = 493) were rMz = .46+/-.09 and rDz = .28 +/-.13. When available medical and pathology reports were included, they changed to rMz =.52 +/-.08 and rDZ = .19+/-.16, suggesting that 51% of the variance of the latent liability to endometriosis may be attributable to additive genetic influences. CONCLUSION(S) These findings support the hypothesis that genes influence liability to endometriosis.

Identification and Analysis of Error Types in High-Throughput Genotyping

Although it is clear that errors in genotyping data can lead to severe errors in linkage analysis, there is as yet no consensus strategy for identification of genotyping errors. Strategies include comparison of duplicate samples, independent calling of alleles, and Mendelian-inheritance-error checking. This study aimed to develop a better understanding of error types associated with microsatellite genotyping, as a first step toward development of a rational error-detection strategy. Two microsatellite marker sets (a commercial genomewide set and a custom-designed fine-resolution mapping set) were used to generate 118,420 and 22,500 initial genotypes and 10,088 and 8,328 duplicates, respectively. Mendelian-inheritance errors were identified by PedManager software, and concordance was determined for the duplicate samples. Concordance checking identifies only human errors, whereas Mendelian-inheritance-error checking is capable of detection of additional errors, such as mutations and null alleles. Neither strategy is able to detect all errors. Inheritance checking of the commercial marker data identified that the results contained 0.13% human errors and 0.12% other errors (0.25% total error), whereas concordance checking found 0.16% human errors. Similarly, Mendelian-inheritance-error checking of the custom-set data identified 1.37% errors, compared with 2.38% human errors identified by concordance checking. A greater variety of error types were detected by Mendelian-inheritance-error checking than by duplication of samples or by independent reanalysis of gels. These data suggest that Mendelian-inheritance-error checking is a worthwhile strategy for both types of genotyping data, whereas fine-mapping studies benefit more from concordance checking than do studies using commercial marker data. Maximization of error identification increases the likelihood of linkage when complex diseases are analyzed.

Genomewide Linkage Study in 1,176 Affected Sister Pair Families Identifies a Significant Susceptibility Locus for Endometriosis on Chromosome 10q26

Endometriosis is a common gynecological disease that affects up to 10% of women in their reproductive years. It causes pelvic pain, severe dysmenorrhea, and subfertility. The disease is defined as the presence of tissue resembling endometrium in sites outside the uterus. Its cause remains uncertain despite >50 years of hypothesis-driven research, and thus the therapeutic options are limited. Disease predisposition is inherited as a complex genetic trait, which provides an alternative route to understanding the disease. We seek to identify susceptibility loci, using a positional-cloning approach that starts with linkage analysis to identify genomic regions likely to harbor these genes. We conducted a linkage study of 1,176 families (931 from an Australian group and 245 from a U.K. group), each with at least two members--mainly affected sister pairs--with surgically diagnosed disease. We have identified a region of significant linkage on chromosome 10q26 (maximum LOD score [MLS] of 3.09; genomewide P = .047) and another region of suggestive linkage on chromosome 20p13 (MLS = 2.09). Minor peaks (with MLS > 1.0) were found on chromosomes 2, 6, 7, 8, 12, 14, 15, and 17. This is the first report of linkage to a major locus for endometriosis. The findings will facilitate discovery of novel positional genetic variants that influence the risk of developing this debilitating disease. Greater understanding of the aberrant cellular and molecular mechanisms involved in the etiology and pathophysiology of endometriosis should lead to better diagnostic methods and targeted treatments.

Genetic influences on handedness: Data from 25,732 Australian and Dutch twin families

Handedness refers to a consistent asymmetry in skill or preferential use between the hands and is related to lateralization within the brain of other functions such as language. Previous twin studies of handedness have yielded inconsistent results resulting from a general lack of statistical power to find significant effects. Here we present analyses from a large international collaborative study of handedness (assessed by writing/drawing or self report) in Australian and Dutch twins and their siblings (54,270 individuals from 25,732 families). Maximum likelihood analyses incorporating the effects of known covariates (sex, year of birth and birth weight) revealed no evidence of hormonal transfer, mirror imaging or twin specific effects. There were also no differences in prevalence between zygosity groups or between twins and their singleton siblings. Consistent with previous meta-analyses, additive genetic effects accounted for about a quarter (23.64%) of the variance (95%CI 20.17, 27.09%) with the remainder accounted for by non-shared environmental influences. The implications of these findings for handedness both as a primary phenotype and as a covariate in linkage and association analyses are discussed.

Genetics of Educational Attainment in Australian Twins: Sex Differences and Secular Changes

The relative effects of genetic and environmental factors in producing individual differences in educational achievement are compared across women and men and over birth cohorts. In a large sample of Australian twin pairs, the heritability of self-reported educational attainment did not vary among women and men born before and after 1950. In a “psychometric” model of twin resemblance, based on separate self-reports in 1981 and 1989, genetic factors explained 57% of the stable variance in educational achievement, while environmental factors shared by twins accounted for 24% of the variance. Corrections for phenotypic assortative mating for educational level, however, suggested that estimated common-environmental effects could be entirely explained by the correlation between additive genetic values for mates. Taking this into account, heritability of “true” educational attainment in Australia may be as high as 82% with the remaining variation being due to individual environments or experiences. Unlike previous studies in Scandinavian countries, results in Australia suggest that factors influencing educational success are comparable between women and men and for individuals born at different points during this century.

Genetic influences on post-natal depressive symptoms: findings from an Australian twin sample

BACKGROUND Conflicting evidence exists on causes of vulnerability to post-natal depression. We investigated genetic and environmental influences on variation in post-natal depressive symptoms (PNDS) following first live birth, and sources of covariation with the personality trait Neuroticism and lifetime major depression occurring post-natally (DEP-PN) and at other times (DEP-XPN) to test for shared genetic influences. METHOD Retrospective interview and questionnaire data from 838 parous female twin pairs (539 monozygotic, 299 dizygotic) from the Australian National Health and Medical Research Council volunteer adult twin register were used for multivariate genetic model-fitting. Data on PNDS were evaluated for consistency with diagnostic interview assessment. RESULTS Genetic factors explained 38% of variance in PNDS (95% confidence interval 26-49%) and 25% of the variance in interview-assessed DEP-PN. The genetic correlation between PNDS and lifetime major depression (DEP-PN and DEP-XPN) was low (r(g) = 0.17, 95% confidence interval = 0.09-0.28), suggesting that the questionnaire was measuring a construct other than postnatally occurring major depression, possibly post-natal dysphoria. Associations between PNDS and obstetric factors were very modest. CONCLUSIONS Findings suggest modest genetic influences on major depression occurring postnatally. Independent and stronger genetic influences identified for post-natal symptomatology or dysphoria (PNDS) justify further investigation.

The international endogene study: a collection of families for genetic research in endometriosis

OBJECTIVE The aim of the International Endogene Study is to discover genes that influence susceptibility to endometriosis. DESIGN The study brings together two research groups based in Australia and the United Kingdom that independently have been collecting families for linkage analysis and candidate gene studies. Both groups used similar methods to recruit families, obtain clinical notes, assign disease status based on the operative records and available histology, and collect common clinical data including age at onset of symptoms, age at diagnosis, and symptoms experienced. SETTING Recruitment has been mainly from Australia, the United Kingdom, and the United States. PATIENT(S) All affected participants have surgically confirmed disease. INTERVENTION(S) None. MAIN OUTCOME MEASURE(S) Clinical and epidemiological data. RESULT(S) To date, >1,100 families with affected sisters have been recruited, and >1,200 triads (affected women and both parents), for case-control studies. CONCLUSION(S) We have created the largest resource yet assembled of clinical data and DNA for linkage and association studies in endometriosis. The increase in power to detect susceptibility genes vindicates the decision to merge the two studies and demonstrates the value of large-scale international collaboration.

Investigating genetic discrimination in Australia: a large‐scale survey of clinical genetics clients

We report first results from the Australian Genetic Discrimination Project of clinical genetics services clients’ perceptions and experiences regarding alleged differential treatment associated with having genetic information. Adults (n = 2667) who had presented from 1998 to 2003 regarding predictive or presymptomatic testing for designated mature‐onset conditions were surveyed; 951/1185 respondents met inclusion criteria for current asymptomatic status. Neurological conditions and familial cancers were primary relevant conditions for 87% of asymptomatic respondents. Specific incidents of alleged negative treatment, reported by 10% (n = 93) of respondents, occurred in life insurance (42%), employment (5%), family (22%), social (11%) and health (20%) domains. Respondents where neuro‐degenerative conditions were relevant were more likely overall to report incidents and significantly more likely to report incidents in the social domain. Most incidents in the post‐test period occurred in the first year after testing. Only 15% of respondents knew where to complain officially if treated negatively because of genetics issues. Recommendations include the need for increased community and clinical education regarding genetic discrimination, for extended clinical genetics sector engagement and for co‐ordinated monitoring, research and policy development at national levels in order for the full benefits of genetic testing technology to be realised.

A deletion mutation in GDF9 in sisters with spontaneous DZ twins

A loss of function mutation in growth differentiation factor 9 (GDF9) in sheep causes increased ovulation rate and infertility in a dosage-sensitive manner. Spontaneous dizygotic (DZ) twinning in the human is under genetic control and women with a history of DZ twinning have an increased incidence of multiple follicle growth and multiple ovulation. We sequenced the GDF9 coding region in DNA samples from 20 women with DZ twins and identified a four-base pair deletion in GDF9 in two sisters with twins from one family. We screened a further 429 families and did not find the loss of function mutation in any other families. We genotyped eight single nucleotide polymorphisms across the GDF9 locus in 379 families with two sisters who have both given birth to spontaneous DZ twins (1527 individuals) and 226 triad families with mothers of twins and their parents (723 individuals). Using case control analysis and the transmission disequilibrium test we found no evidence for association between common variants in GDF9 and twinning in the families. We conclude that rare mutations in GDF9 may influence twinning, but twinning frequency is not associated with common variation in GDF9.

Genetic analysis of the age at menopause by using estimating equations and Bayesian random effects models

Multi-wave self-report data on age at menopause in 2182 female twin pairs (1355 monozygotic and 827 dizygotic pairs), were analysed to estimate the genetic, common and unique environmental contribution to variation in age at menopause. Two complementary approaches for analysing correlated time-to-onset twin data are considered: the generalized estimating equations (GEE) method in which one can estimate zygosity-specific dependence simultaneously with regression coefficients that describe the average population response to changing covariates; and a subject-specific Bayesian mixed model in which heterogeneity in regression parameters is explicitly modelled and the different components of variation may be estimated directly. The proportional hazards and Weibull models were utilized, as both produce natural frameworks for estimating relative risks while adjusting for simultaneous effects of other covariates. A simple Markov chain Monte Carlo method for covariate imputation of missing data was used and the actual implementation of the Bayesian model was based on Gibbs sampling using the freeware package BUGS.