An Update of Twin Research in Spain: The Murcia Twin Registry

Calculating Within-Pair Difference Scores in the Co-twin Control Design. Effects of Alternative Strategies

Co-twin studies are an elegant and powerful design that allows controlling for the effect of confounding variables, including genetic and a range of environmental factors. There are several approaches to carry out this design. One of the methods commonly used, when contrasting continuous variables, is to calculate difference scores between members of a twin pair on two associated variables, in order to analyse the covariation of such differences. However, information regarding whether and how the different ways of estimating within-pair difference scores may impact the results is scant. This study aimed to compare the results obtained by different methods of data transformation when performing a co-twin study and test how the magnitude of the association changes using each of those approaches. Data was simulated using a direction of causation model and by fixing the effect size of causal path to low, medium, and high values. Within-pair difference scores were calculated as relative scores for diverse within-pair ordering conditions or absolute scores. Pearson's correlations using relative difference scores vary across the established scenarios (how twins were ordered within pairs) and these discrepancies become larger as the within-twin correlation increases. Absolute difference scores tended to produce the lowest correlation in every condition. Our results show that both using absolute difference scores or ordering twins within pairs, may produce an artificial decrease in the magnitude of the studied association, obscuring the ability to detect patterns compatible with causation, which could lead to discrepancies across studies and erroneous conclusions.

Sex differences in lifetime prevalence of low back pain: A multinational study of opposite-sex twin pairs

BACKGROUND

Low back pain (LBP) is more likely to occur in people with a family history of this condition, highlighting the importance of accounting for familial factors when studying the individual risk of LBP. We conducted a study of opposite-sex twin pairs investigating sex differences in LBP while accounting for (genetic and shared environmental) familial factors.

METHODS

We applied a matched co-twin control design to study 795 adult opposite-sex pairs from Australia, Spain, and the United States (US). We used mixed-effects logistic regression to assess the within-pair association between female sex and lifetime prevalence of LBP in unadjusted and adjusted models for body-mass-index, and depression, as well as interactions between female sex and age (

RESULTS

The mean age of the sample was 47.4 years (Standard Deviation = 16.5). The adjusted odds ratio (aOR) of the association between sex and LBP in the merged sample was 1.11 (95% Confidence Interval = 0.88-1.40), with 87.4% of the variance in the studied association explained by between-site heterogeneity (Q test; p = 0.001). Females had 2.37 (95% CI: 1.48-3.78) higher odds of LBP compared to their male co-twins in the Spanish sample (adjusted), but a sex association was not found in the Australian nor US samples.

CONCLUSIONS

We found no evidence of the association between sex and LBP in our merged sample. Between-population differences (i.e. cultural background or health system characteristics) are likely to be major factors leading to variation in the sex association with LBP when familial factors are accounted for.

SIGNIFICANCE

Our study of adult opposite-sex twin pairs found no evidence of an association between female sex and lifetime prevalence of low back pain after controlling for familial factors in the merged sample from Australia, Spain and USA, contrary to findings from previous studies of unrelated individuals. Our findings indicate potentially relevant between-country genetic, cultural and environmental differences which may need to be considered for optimal and individualized strategies for the prevention and management of low back pain across the lifespan.

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Affiliation(s)

Lucas Calais-Ferreira Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia Centre for Adolescent Health, Murdoch Children's Research Institute, Melbourne, Victoria, Australia
Daniel Pozzobon Biomechanics Laboratory, Sports and Physical Education Center, Federal University of Santa Maria, Santa Maria, Brazil
Marina B Pinheiro Institute for Musculoskeletal Health, The University of Sydney and Sydney Local Health District, Sydney, New South Wales, Australia Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
Fiona M Blyth Sydney School of Public Health, Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
Juan R Ordoñana Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain Murcia Institute of Biomedical Research, IMIB-Arrixaca, Murcia, Spain
Glen E Duncan Department of Nutrition and Exercise Physiology, Elson S. Floyd College of Medicine, Washington State University Health Sciences Spokane, Washington, USA
John L Hopper Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
Paulo H Ferreira Musculoskeletal Research Hub, Charles Perkins Centre, School of Health Sciences, University of Sydney, Sydney, New South Wales, Australia
Manuela L Ferreira School of Health Sciences, Faculty of Medicine and Health, The University of Sydney, Sydney Musculoskeletal Health, The Kolling Institute, Sydney, New South Wales, Australia

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Sex differences in sleep quality and psychological distress: Insights from a middle-aged twin sample from Spain

There is a moderate association between poor sleep and psychological distress. There are marked sex differences in the prevalence of both variables, with females outnumbering males. However, the origin of these sex differences remains unclear. The objectives of this study were to: (1) study genetic and environmental influences on the relationship between poor sleep quality and psychological distress; and (2) test possible sex differences in this relationship. The sample comprised 3544 participants from the Murcia Twin Registry. Univariate and multivariate twin models were fitted to estimate the magnitude of genetic and environmental influences on both individual variance and covariance between poor sleep quality and psychological distress. Sleep quality and psychological distress were measured using the Pittsburgh Sleep Quality Index and the EuroQol five-dimensions questionnaire, respectively. The results reveal a strong genetic association between poor sleep quality and psychological distress, which accounts for 44% (95%CI: 27%-61%) of the association between these two variables. Substantial genetic (rA = 0.50; 95%CI: 0.32, 0.67) and non-shared environmental (rE = 0.41; 95%CI: 0.30, 0.52) correlations were also found, indicating a moderate overlap between genetic (and non-shared environmental) factors influencing both phenotypes. Equating sexes in sex-limitation models did not result in significant decreases in model fit. Despite the remarkable sex differences in the prevalence of both poor sleep quality and psychological distress, there were no sex differences in the genetic and environmental influences on these variables. This suggests that genetic factors play a similar role for men and women in explaining individual differences in both phenotypes and their relationship.

Phenotypic, Genetic and Environmental Architecture of the Components of Sleep Quality

The genetic and environmental underpinnings of sleep quality have been widely investigated. However, less is known about the etiology of the different sleep quality components and their associations. Subjective sleep quality has been studied most commonly using the Pittsburgh Sleep Quality Index (PSQI). Therefore, this work aimed to study the structure of sleep quality dimensions in a population-based twin sample by examining the etiology of the associations among the PSQI components themselves and between them. The sample comprised 2129 participants from the Murcia Twin Registry. In order to study the phenotypic, genetic and environmental structure of the PSQI we used three alternative multivariate twin models including all seven sub-scales of the PSQI (subjective sleep quality, latency, duration, efficiency, disturbances, use of sleeping medication and daytime dysfunction): a multivariate model (with seven separate correlated factors), a common pathway model and an independent pathway model. The multivariate correlated factors model showed the best fit to the data. All twin models indicated significant genetic overlap among most of the PSQI components, except daytime dysfunction and use of sleep medication. Bivariate heritability explained between 25 and 50% of the covariance for most associations between dimensions. Furthermore, the common pathway model showed that around one third of the variance (0.32; CI 95% 0.18.0.43) of a latent factor common to all questionnaire dimensions is explained by genetic factors. Genetic influences on a latent factor common to all questionnaire dimensions produced the same heritability estimates as the PSQI global score. However, sleep quality dimensions showed considerable specificity regarding its genetic-environmental structure.

Nature and nurture. Genetic and environmental factors on the relationship between back pain and sleep quality

BACKGROUND

Chronic low back pain (LBP), neck pain (NP), and sleep quality (SQ) are genetically influenced. All three conditions frequently co-occur and shared genetic etiology on a pairwise base has been reported. However, to our knowledge no study has yet investigated if these three conditions are influenced by the same genetic and environmental factors and the extent and pattern of genetic overlap between them, hence the current research.

METHODS

The sample included 2134 participants. Lifetime prevalence of NP and LBP were assessed through a dichotomous self-reported question derived from the Spanish National Health Survey. SQ was measured using the Pittsburgh Sleep Quality Index Questionnaire. A common pathway model with sleep quality and back pain as latent factors was fitted.

RESULTS

Our results highlight that a latent back pain factor, including both NP and LBP, is explained by both genetic (41%) and environmental (59%) factors. There are also significant unique environmental factors for NP (33%) and LBP (37%) respectively. Yet, specific genetic factors were scant (9%) for NP and negligible for LBP (0%). Genetic and environmental factors affecting SQ only contribute with 3% and 5% of the variance, respectively, to the common latent back pain variable.

CONCLUSIONS

NP and LBP share most of their genetic variance, while environmental effects show greater specificity for each of the back pain locations. Associations with SQ were of a limited magnitude.

[Twin research in Germany]

Nach dem Zweiten Weltkrieg wurden weltweit Zwillingskohorten aufgebaut, die inzwischen ca. 1,5 Mio. Zwillinge umfassen und zwischen 1950 und 2012 über 2748 Zwillingsstudien hervorgebracht haben. Diese Zahl steigt jedes Jahr um weitere 500 bis 1000. Die Unterrepräsentanz deutscher Zwillingsstudien in diesen Datenbanken lässt sich nicht allein durch den Missbrauch medizinischer Forschung im Nationalsozialismus erklären. Entwicklung und Ausbau großer Zwillingskohorten sind ethisch und datenschutzrechtlich eine Herausforderung. Zwillingskohorten ermöglichen jedoch die Langzeit- und Echtzeiterforschung vieler medizinischer Fragestellungen; und die Zwillingsstudien tragen auch nach der Entschlüsselung des Humangenoms erheblich zur Beantwortung der Frage nach Anlage oder Umwelt als mögliche Erkrankungsauslöser bei.

Derzeit gibt es 2 deutsche Zwillingskohorten: die biomedizinische Kohorte HealthTwiSt mit ca. 1500 Zwillingspaaren und TwinLife, eine soziologisch-psychologische Kohorte mit ca. 4000 Zwillingspaaren. Daneben gibt es krankheitsspezifische Kohorten. 2016 startete das TwinHealth-Konsortium der Medizinischen Fakultät der Universität Tübingen mit dem Ziel, eine forschungsoffene und nachhaltige Zwillingsforschung am Standort Tübingen zur Bearbeitung unterschiedlicher Fragestellungen zu etablieren.

Der Artikel bietet mithilfe einer systematischen Literaturrecherche und einer medizinhistorischen Betrachtung einen Überblick über die weltweite und nationale Entwicklung von Zwillingsstudien und -datenbanken der letzten 100 Jahre. Anhand der Tübinger TwinHealth-Initiative beleuchtet er den Aufbau eines Zwillingskollektivs und dessen juristische, ethische und Datenschutzaspekte.

An information-based framework for development national twin registry: Scoping review and focus group discussion

BACKGROUND

Registries in various clinical domains have been established in the last decades. The specific genetic structure of twins has enabled researchers to find answers to the role of genetics and the environment in medical sciences. Thus, twin registries were developed across the world to support twin studies. Our main objective was to devise a conceptual model for developing the national twin registry to ensure the success of this registry.

METHODS

In this descriptive and qualitative study, the combination of literature review and focus group discussions was applied to achieve suitable models for developing a national twin registry based on lessons learned from founded registries. The qualitative synthesis and reporting results were conducted based on the COREQ checklist.

RESULTS

According to a systematic literature review, the characteristics and employed strategies employed by established twin registries were recognized. Moreover, based on our objectives, suitable models for registry development were defined. The source of information, the different levels of data, and the information flow were determined based on this model.

CONCLUSION

Suggesting a conceptual framework for twin registry development at the national level based on the experiences of other countries could contribute to a greater understanding of twin registry implementation efficiently.

Disparity between central and peripheral refraction inheritance in twins

The last decades have witnessed a sudden increase in myopia incidence among youngsters that have been related to modern lifestyle along with the use of emerging technologies affecting visual exposure. Increasing exposures to known risk factors for myopia, such as time spent indoors, close-distance work, or low-light conditions are thought to be responsible for this public health issue. In most cases, development of myopia is secondary to a vitreous chamber enlargement, although the related mechanisms and the potential interaction between central and peripheral retinal area remain unclear. For a better understanding, we performed a classical twin study where objective refractive error along 70° of horizontal retinal arc was measured in 100 twin pairs of university students, 78% of which showed manifest myopia. We found the variance of shared environmental origin (range 0.34 to 0.67) explained most of the objective refractive error variance within central 42° of the retina (22° temporal to 19° nasal), whereas additive genetic variance (range 0.34 to 0.76) was predominant in the peripheral retinal areas measured. In this sample of millennial university students, with a large prevalence of myopia, environmental exposures were mostly responsible for inter-individual variation in the retinal horizontal area surrounding the macula, while their relative weight on phenotypic variance was gradually descending, and replaced by the variance of genetic origin, towards the retinal periphery.

The Role of the Environment in Overweight and Eating Behavior Variability: Insights from a Multivariate Twin Study

Research has emphasized the genetic basis of individual differences in body mass index (BMI); however, genetic factors cannot explain the rapid rise of obesity. Eating behaviors have been stipulated to be the behavioral expression of genetic risk in an obesogenic environment. In this study, we decompose variation and covariation between three key eating behaviors and BMI in a sample of 698 participants, consisting of 167 monozygotic, 150 dizygotic complete same-sex female twins and 64 incomplete pairs from a population-based twin registry in the southeast of Spain, The Murcia Twin Registry. Phenotypes were emotional eating, uncontrolled eating and cognitive restraint, measured by the Three Factor Eating Questionnaire and objectively measured BMI. Variation in eating behaviors was driven by nonshared environmental factors (range: 56%-65%), whereas shared environmental and genetic factors were secondary. All three eating behaviors were correlated with BMI (r = .19-.25). Nonshared environmental factors explained the covariations (Emotional eating-Uncontrolled eating: rE = .54, 95% CI [.43, .64]; BMI-Cognitive restraint: rE = .15, 95% CI [.01, .28]). In contrast to BMI, individual differences in eating behaviors are mostly explained by nonshared environmental factors, which also accounted for the phenotypic correlation between eating behaviors and BMI. Due to the sample size, analyses were underpowered to detect contributions of additive genetic or shared environmental factors to variation and covariation of the phenotypes. Although more research is granted, these results support that eating behaviors could be viable intervention targets to help individuals maintain a healthy weight.

Sleep quality and chronic neck pain: a cotwin study

STUDY OBJECTIVES

Sleep quality and chronic neck pain (NP) are associated. However, the genetic influences on this association have not been explored. This study investigated the genetic and environmental influences on the association between sleep quality and chronic NP.

METHODS

The sample comprised 2,328 individual twins from the Murcia Twin Registry (Spain). A bidirectional cotwin logistic regression analysis was performed (sleep quality assessed as the exposure and chronic NP as the outcome and vice versa). Analysis included 2 sequential stages: total sample analysis and within-pair twin case-control analysis.

RESULTS

Sleep quality was significantly associated with chronic NP in the total sample analysis (adjusted odds ratio [OR]: 1.09; 95% confidence interval [CI]: 1.06, 1.12; P < .001); in the cotwin case-control analysis, including both monozygotic and dizygotic twin pairs (adjusted OR: 1.10; 95% CI: 1.04, 1.17; P = .001); in dizygotic pairs (Adjusted OR: 1.11; 95% CI: 1.03, 1.19; P = .005); but not in monozygotic pairs (adjusted OR: 1.08; 95% CI: 0.98, 1.19; P = .118). Chronic NP was significantly associated with poor sleep quality in the total sample analysis (adjusted OR: 1.80; 95% CI: 1.43, 2.26; P < .001); in the cotwin case-control analysis, including both monozygotic and dizygotic twin pairs (Adjusted OR: 1.63; 95% CI: 1.07, 2.47; P = .023); in dizygotic pairs (Adjusted OR: 1.80; 95% CI: 1.05, 3.09; P = .031), but not in monozygotic pairs (adjusted OR: 1.67; 95% CI: 0.80, 3.48; P = .170).

CONCLUSIONS

The association between sleep quality and chronic NP is partially confounded by genetic factors.