The Application of a Random Effects Model to Censored Twin Data

Three measures of explained variation for correlated survival data under the proportional hazards mixed-effects model

Measures of explained variation are useful in scientific research, as they quantify the amount of variation in an outcome variable of interest that is explained by one or more other variables. We develop such measures for correlated survival data, under the proportional hazards mixed-effects model. Because different approaches have been studied in the literature outside the classical linear regression model, we investigate three measures R(2) , Rres2, and ρ(2) that quantify three different population coefficients. We show that although the three population measures are not the same, they reflect similar amounts of variation explained by the predictors. Among the three measures, we show that R(2) , which is the simplest to compute, is also consistent for the first population measure under the usual asymptotic scenario when the number of clusters tends to infinity. The other two measures, on the other hand, all require that in addition the cluster sizes be large. We study the properties of the measures both analytically and through simulation studies. We illustrate their different usage on a multi-center clinical trial and a recurrent events data set. Copyright © 2016 John Wiley & Sons, Ltd.

Phenotype evaluation and genomewide linkage study of clinical variables in schizophrenia

Genetic factors are likely to influence clinical variation in schizophrenia, but it is unclear which variables are most suitable as phenotypes and which molecular genetic loci are involved. We evaluated clinical variable phenotypes and applied suitable phenotypes in genome-wide covariate linkage analysis. We ascertained 170 affected relative pairs (168 sibling-pairs and two avuncular pairs) with DSM-IV schizophrenia or schizoaffective disorder from the United Kingdom. We defined psychotic symptom dimensions, age at onset (AAO), and illness course using the OPCRIT checklist. We evaluated phenotypes using within sibling-pair correlations and applied suitable phenotypes in multipoint covariate linkage analysis based on 372 microsatellite markers at ∼10 cM intervals. The statistical significance of linkage results was assessed by simulation. The positive and disorganized symptom dimensions, AAO, and illness course qualified as suitable phenotypes. There were no genome-wide significant linkage results. There was suggestive evidence of linkage for the positive dimension on chromosomes 2q32, 10q26, and 20q12; the disorganized dimension on 8p21 and 17q21; and illness course on 2q33 and 22q11. The linkage peak for disorganization on 17q21 remained suggestive after correction for multiple testing. To our knowledge, this is the first study to integrate phenotype evaluation and genome-wide covariate linkage analysis for symptom dimensions and illness history variables in sibling-pairs with schizophrenia. The significant within-pair correlations strengthen the evidence that some clinical variables within schizophrenia are suitable phenotypes for molecular genetic investigations. At present there are no genome-wide significant linkage results for these phenotypes, but a number of suggestive findings warrant further investigation.

Now you see him, now you don't: experience, not age, is related to reproduction in kittiwakes

In long-lived species, individuals can skip reproduction. The proportion of breeders affects population growth rate and viability, there is a need to investigate the factors influencing intermittent breeding. The theory predicts that if lack of experience is an important constraint, breeding probabilities should increase with experience for individuals of the same age, whereas under the so-called restraint hypothesis, breeding probabilities should increase with age regardless of experience. However, because the probability of detecting individuals in the wild is generally less than 1, it is difficult to know exactly the number of previous breeding episodes (breeding experience). To cope with this issue, we developed a hidden process model to incorporate experience as a latent state possibly influencing the probability of breeding. Using a 22-year mark-recapture dataset involving 9970 individuals, we analysed simultaneously experience and age effects on breeding probabilities in the kittiwake (Rissa tridactyla). We did not detect an influence of age on adult breeding probabilities. We found that inexperienced birds breed less frequently than experienced birds. Our approach enables us to highlight the key role of experience on adults breeding probabilities and can be used for a wide range of organisms for which detection is less than 1.

Mood-incongruent psychosis in bipolar disorder: conditional linkage analysis shows genome-wide suggestive linkage at 1q32.3, 7p13 and 20q13.31

OBJECTIVE

The majority of research into functional psychosis has proceeded under the assumption that schizophrenia and bipolar disorder are distinct entities with separate underlying disease processes and treatments. This view has been increasingly challenged in both clinical and genetic studies. Findings in recent association studies at two specific genes suggest that the occurrence of mood-incongruent psychotic features may indicate a relatively homogeneous subset of the bipolar phenotype. We examined this hypothesis.

METHODS

Caucasian affected individuals were ascertained from Europe (the United Kingdom, the Republic of Ireland, Germany, Italy and Andalusia). Consensus best-estimate diagnoses were assigned by two independent raters according to all available information. There was no cross-site evaluation of inter-rater reliability. Families multiply affected by bipolar spectrum mood disorder were selected, comprising 383 affected relative pairs. Individuals were considered to be affected if they were diagnosed with DSM-IV bipolar I disorder or schizoaffective disorder, bipolar type. Multipoint, affected relative pair covariate linkage analysis was performed.

RESULTS

Significant familiality of incongruent psychosis was observed [intra-class correlation coefficient (ICC) = 0.309; p = 0.001, one-tail]. Covariate linkage analysis provided three regions with genome-wide suggestive evidence for linkage on chromosomes 1q32.3 (LOD = 4.15, expected 0.12 times per genome scan), 7p13 (LOD = 3.32) and 20q13.31 (LOD = 2.98). No region in our analysis met criteria for genome-wide significance.

CONCLUSION

Our results provide molecular support for the hypothesis that genes may exist for specific forms of bipolar illness, dependent on the presence or absence of incongruent psychosis. Our findings suggest that researchers should take account of mood-congruence/incongruence of psychotic features in studies of bipolar disorder.

On proportional hazards assumption under the random effects models

The proportional hazards mixed-effects model (PHMM) was proposed to handle dependent survival data. Motivated by its application in genetic epidemiology, we study the interpretation of its parameter estimates under violations of the proportional hazards assumption. The estimated fixed effect turns out to be an averaged regression effect over time, while the estimated variance component could be unaffected, inflated or attenuated depending on whether the random effect is on the baseline hazard, and whether the non-proportional regression effect decreases or increases over time. Using the conditional distribution of the covariates we define the standardized covariate residuals, which can be used to check the proportional hazards assumption. The model checking technique is illustrated on a multi-center lung cancer trial.