Lupus Low Disease Activity State and organ damage in relation to quality of life in systemic lupus erythematosus: a cohort study with up to 11 years of follow-up.

OBJECTIVES: Beyond prevention of organ damage, treatment goals in systemic lupus erythematosus (SLE) include optimisation of health-related quality of life (HRQoL). The Lupus Low Disease Activity State (LLDAS) has received increasing attention as a goal whenever remission cannot be achieved. How SLE disease activity, organ damage, and LLDAS attainment relate to patient-reported outcomes (PROs) is not fully explored, which formed the scope of this investigation. METHODS: We included 327 patients with SLE from a tertiary referral centre. Longitudinal registrations of disease activity using SLEDAI-2K and physician global assessment (PhGA), organ damage using the SLICC/ACR damage index (SDI), pharmacotherapies, EQ-5D-3L data, as well as visual analogue scale (VAS) scores for fatigue, pain, and overall SLE-related health state over a median follow-up time of 8.5 years were analysed. RESULTS: In the overall population, as well as subgroups of patients with recent-onset SLE and those with clinically active, autoantibody-positive disease, LLDAS attainment, lower PhGA, and lower clinical SLEDAI-2K scores were associated with favourable HRQoL by EQ-5D-3L and VAS assessments, while increasing SDI scores were associated with poor PROs yet not fatigue in the overall population. PROs were further enhanced by being in LLDAS sustainedly. In fully adjusted models of the entire study population, LLDAS attainment and lower disease activity were associated with favourable PROs, irrespective of SDI. CONCLUSION: In one of the longest to date observational studies, we demonstrated that low disease activity and being sustainedly in LLDAS were coupled with favourable HRQoL, pain, fatigue, and overall health experience, irrespective of organ damage.

Hydroxychloroquine in lupus or rheumatoid arthritis pregnancy and risk of major congenital malformations: a population-based cohort study.

OBJECTIVES: To assess the infant risk of major congenital malformations (MCM) associated with first-trimester exposure to hydroxychloroquine (HCQ) among mothers with systemic lupus erythematosus (SLE) or rheumatoid arthritis (RA). METHODS: This population-based cohort study utilised Swedish nationwide registers and included all singleton births (2006-2021) among individuals with prevalent SLE or RA in Sweden. The exposure was filling ≥1 HCQ prescription during the first trimester. The outcome was infant MCM within one year of birth. Inverse probability of treatment weighting was applied to adjust for potential confounders (e.g. maternal smoking, body mass index, pregestational diabetes, and corticosteroids). Modified Poisson regression models with robust variance estimated risk ratios and 95% confidence intervals (RR 95%CI). RESULTS: We included 1,007 births (453 exposed) and 2,500 births (144 exposed) in the SLE and RA cohorts, respectively. The MCM risks in the SLE overall cohort, exposed, and unexposed groups were 3.6%, 3.7%, and 3.4%, respectively. The corresponding figures in the RA cohort were 4.4%, 5.6%, and 4.3%, respectively. The adjusted RRs (95%CI) were 1.29 (0.65-2.56) in the SLE cohort, 1.32 (0.56-3.13) in the RA cohort, and 1.30 (0.76-2.23) in the pooled analysis. The adjusted risk difference (exposed vs unexposed) was small (0.9% in SLE and 1.3% in RA). Sensitivity analyses examining different exposure and outcome windows yielded similar findings. CONCLUSIONS: First-trimester exposure to HCQ was not associated with a significantly increased risk of MCM. HCQ's benefits may outweigh the risks in managing SLE or RA during pregnancy.

Interaction between smoking and genetic factors in the development of chronic bronchitis.

RATIONALE: Smoking is a primary risk factor for chronic bronchitis, emphysema, and chronic obstructive pulmonary disease, but since not all smokers develop disease, it has been suggested that some individuals may be more susceptible to exogenous factors, such as smoking, and that this susceptibility could be genetically determined. OBJECTIVES: The aim of the present study was to assess, in a population-based sample of twins, the following: (1) to what extent genetic factors contribute to the development of chronic bronchitis, including emphysema, taking sex into consideration, and (2) whether the genetic influences on chronic bronchitis, including emphysema, are separate from those for smoking behavior. METHODS: Disease cases and smoking habits were identified in 44,919 twins older than 40 years from the Swedish Twin Registry. Disease was defined as self-reported chronic bronchitis or emphysema, or recurrent cough with phlegm. Individuals who had smoked 10 pack-years or more were defined as smokers. Univariate and bivariate structural equation models were used to estimate the heritability specific for chronic bronchitis and that in common with smoking. MEASUREMENTS AND MAIN RESULTS: The heritability estimate for chronic bronchitis was a moderate 40% and only 14% of the genetic influences were shared with smoking. CONCLUSIONS: Genetic factors independent of those related to smoking habits play a role in the development of chronic bronchitis.

Bias in variance components due to nonresponse in twin studies.

Incomplete data on trait values may bias estimates of genetic and environmental variance components obtained from twin analyses. If the nonresponse mechanism is 'ignorable' then methods such as full information maximum likelihood estimation will produce consistent variance component estimates. If, however, nonresponse is 'nonignorable', then the situation is more complicated. We demonstrate that a within-pair correlation of nonresponse, possibly different for monozygotic (MZ) and dizygotic (DZ) twins, may well be compatible with 'ignorability'. By means of Monte Carlo simulation, we assess the potential bias in variance component estimates for different types of nonresponse mechanisms. The simulation results guide the interpretation of analyses of data on perceptual speed from the Swedish Adoption/Twin Study of Aging. The results suggest that the dramatic decrease in genetic influences on perceptual speed observed after 13 years of follow-up is not attributable solely to dropout from the study, and thus support the hypothesis that genetic influences on some cognitive abilities decrease with age in late life.

GENESTAT: an information portal for design and analysis of genetic association studies.

We present the rationale, the background and the structure for version 2.0 of the GENESTAT information portal (www.genestat.org) for statistical genetics. The fast methodological advances, coupled with a range of standalone software, makes it difficult for expert as well as non-expert users to orientate when designing and analysing their genetic studies. The ultimate ambition of GENESTAT is to guide on statistical methodology related to the broad spectrum of research in genetic epidemiology. GENESTAT 2.0 focuses on genetic association studies. Each entry provides a summary of a topic and gives links to key papers, websites and software. The flexibility of the internet is utilised for cross-referencing and for open editing. This paper gives an overview of GENESTAT and gives short introductions to the current main topics in GENESTAT, with additional entries on the website. Methods and software developers are invited to contribute to the portal, which is powered by a Wikipedia-type engine and allows easy additions and editing.

A random change point model for assessing variability in repeated measures of cognitive function.

Some cognitive functions undergo transitions in old age, which motivates the use of a change point model for the individual trajectory. The age when the change occurs varies between individuals and is treated as random. We illustrate the properties of a random change point model and use it for data from a Swedish study of change in cognitive function in old age. Variance estimates are obtained from Markov chain Monte Carlo simulation using Gibbs sampling. The random change point model is compared with models within the family of linear random effects models. The focus is on the ability to capture variability in measures of cognitive function. The models make different assumptions about the variance over the age span, and we demonstrate that the random change point model has the most reasonable structure.

Likelihood ratio tests in behavioral genetics: problems and solutions.

The likelihood ratio test of nested models for family data plays an important role in the assessment of genetic and environmental influences on the variation in traits. The test is routinely based on the assumption that the test statistic follows a chi-square distribution under the null, with the number of restricted parameters as degrees of freedom. However, tests of variance components constrained to be non-negative correspond to tests of parameters on the boundary of the parameter space. In this situation the standard test procedure provides too large p-values and the use of the Akaike Information Criterion (AIC) or the Bayesian Information Criterion (BIC) for model selection is problematic. Focusing on the classical ACE twin model for univariate traits, we adapt existing theory to show that the asymptotic distribution for the likelihood ratio statistic is a mixture of chi-square distributions, and we derive the mixing probabilities. We conclude that when testing the AE or the CE model against the ACE model, the p-values obtained from using the chi(2)(1 df) as the reference distribution should be halved. When the E model is tested against the ACE model, a mixture of chi(2)(0 df), chi(2)(1 df) and chi(2)(2 df) should be used as the reference distribution, and we provide a simple formula to compute the mixing probabilities. Similar results for tests of the AE, DE and E models against the ADE model are also derived. Failing to use the appropriate reference distribution can lead to invalid conclusions.