Between-subject Variance Research Articles

Short-term markers of DNA damage among roofers who work with hot asphalt.

BackgroundRoofers are at increased risk for various malignancies and their occupational exposures to polycyclic aromatic hydrocarbons (PAHs) have been considered as important risk factors. The overall goal of this project was to investigate the usefulness of phosphorylated histone H2AX (γH2AX) as a short-term biomarker of DNA damage among roofers.MethodsBlood, urine, and dermal wipe samples were collected from 20 roofers who work with hot asphalt before and after 6 h of work on Monday and Thursday of the same week (4 sampling periods). Particle-bound and gas-phase PAHs were collected using personal monitors during work hours. γH2AX was quantified in peripheral lymphocytes using flow cytometry and 8-hydroxy-2-deoxyguanosine (8-OHdG) was assessed in urine using ELISA. General linear mixed models were used to evaluate associations between DNA damage and possible predictors (such as sampling period, exposure levels, work- and life-style factors). Differences in mean biomarker and DNA damage levels were tested via ANOVA contrasts.ResultsExposure measurements did not show an association with any of the urinary biomarkers or the measures of DNA damage. Naphthalene was the most abundant PAH in gas-phase, while benzo(e)pyrene was the most abundant particle-bound PAH. Post-shift levels of γH2AX and 8-OHdG were higher on both study days, when compared to pre-shift levels. Cigarette smoking was a predictor of γH2AX and urinary creatinine was a predictor of urinary 8-OHdG. Between-subject variance to total variance ratio was 35.3 % for γH2ax and 4.8 % for 8-OHdG.ConclusionγH2AX is a promising biomarker of DNA damage in occupational epidemiology studies. It has a lower within-subject variation than urinary 8-OHdG and can easily be detected in large scale groups. Future studies that explore the kinetics of H2AX phosphorylation in relation to chemical exposures may reveal the transient and persistent nature of this sensitive biomarker of early DNA damage.Electronic supplementary materialThe online version of this article (doi:10.1186/s12940-016-0182-4) contains supplementary material, which is available to authorized users.

A unique method for estimating the reliability learning curve of optic nerve sheath diameter ultrasound measurement.

BackgroundOptic nerve sheath diameter (ONSD) measurement using ultrasound has been proposed as a rapid, non-invasive, point of care technique to estimate intra-cranial pressure (ICP). Ultrasonic measurement of the optic nerve sheath can be quite challenging and there is limited literature surrounding learning curves for this technique. We attempted to develop a method to estimate the reliability learning curve for ONSD measurement utilizing a unique definition of reliability: a plateau in within-subject variability with unchanged between-subject variability.MethodsAs part of a previously published study, a single operator measured the ONSD in 120 healthy volunteers over a 6-month period. Utilizing the assumption that the four measurements made on each subject during this study should be equal, the relationship of within-subject variance was described using a quadratic-plateau model as assessed by segmental polynomial (knot) regression.ResultsSegmental polynomial (knot) regression revealed a plateau in within-subject variance after the 21st subject. However, there was no difference in overall mean values [3.69 vs 3.68 mm (p = 0.884)] or between-subject variance [14.49 vs 11.92 (p = 0.54)] above or below this cutoff.ConclusionsThis study suggests a significant finite learning curve associated with ONSD measurements. It also offers a unique method of calculating the learning curve associated with ONSD measurement.

Pros and Cons of Using the Informed Basis Set to Account for Hemodynamic Response Variability with Developmental Data.

Conventional analysis of functional magnetic resonance imaging (fMRI) data using the general linear model (GLM) employs a neural model convolved with a canonical hemodynamic response function (HRF) peaking 5 s after stimulation. Incorporation of a further basis function, namely the canonical HRF temporal derivative, accounts for delays in the hemodynamic response to neural activity. A population that may benefit from this flexible approach is children whose hemodynamic response is not yet mature. Here, we examined the effects of using the set based on the canonical HRF plus its temporal derivative on both first- and second-level GLM analyses, through simulations and using developmental data (an fMRI dataset on proprioceptive mapping in children and adults). Simulations of delayed fMRI first-level data emphasized the benefit of carrying forward to the second-level a derivative boost that combines derivative and nonderivative beta estimates. In the experimental data, second-level analysis using a paired t-test showed increased mean amplitude estimate (i.e., increased group contrast mean) in several brain regions related to proprioceptive processing when using the derivative boost compared to using only the nonderivative term. This was true especially in children. However, carrying forward to the second-level the individual derivative boosts had adverse consequences on random-effects analysis that implemented one-sample t-test, yielding increased between-subject variance, thus affecting group-level statistic. Boosted data also presented a lower level of smoothness that had implication for the detection of group average activation. Imposing soft constraints on the derivative boost by limiting the time-to-peak range of the modeled response within a specified range (i.e., 4–6 s) mitigated these issues. These findings support the notion that there are pros and cons to using the informed basis set with developmental data.

Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing

Functional magnetic resonance imaging (fMRI) research is routinely criticized for being statistically underpowered due to characteristically small sample sizes and much larger sample sizes are being increasingly recommended. Additionally, various sources of artifact inherent in fMRI data can have detrimental impact on effect size estimates and statistical power. Here we show how specific removal of non-BOLD artifacts can improve effect size estimation and statistical power in task-fMRI contexts, with particular application to the social-cognitive domain of mentalizing/theory of mind. Non-BOLD variability identification and removal is achieved in a biophysical and statistically principled manner by combining multi-echo fMRI acquisition and independent components analysis (ME-ICA). Without smoothing, group-level effect size estimates on two different mentalizing tasks were enhanced by ME-ICA at a median rate of 24% in regions canonically associated with mentalizing, while much more substantial boosts (40–149%) were observed in non-canonical cerebellar areas. Effect size boosting occurs via reduction of non-BOLD noise at the subject-level and consequent reductions in between-subject variance at the group-level. Smoothing can attenuate ME-ICA-related effect size improvements in certain circumstances. Power simulations demonstrate that ME-ICA-related effect size enhancements enable much higher-powered studies at traditional sample sizes. Cerebellar effects observed after applying ME-ICA may be unobservable with conventional imaging at traditional sample sizes. Thus, ME-ICA allows for principled design-agnostic non-BOLD artifact removal that can substantially improve effect size estimates and statistical power in task-fMRI contexts. ME-ICA could mitigate some issues regarding statistical power in fMRI studies and enable novel discovery of aspects of brain organization that are currently under-appreciated and not well understood.

Directional Optical Coherence Tomography Reveals Reliable Outer Nuclear Layer Measurements.

Directional Optical Coherence Tomography (D-OCT) is a method used to optically segment and identify the outer nuclear layer (ONL) in vivo. The purpose of this study was to determine the repeatability and reproducibility of D-OCT ONL thickness measurements in healthy eyes. Sixteen healthy eyes of sixteen subjects were imaged using the Cirrus SD-OCT. The OCT beam entry position was varied horizontally and vertically through the pupil, and cross-sectional images were obtained at baseline and 1-month follow-up by two observers. Detailed segmentation was performed to quantify the thickness of ONL without the inclusion of overlying Henle Fiber Layer. Inter-observer, intra-observer, and inter-visit variability was evaluated using Bland-Altman and coefficient of variation analysis for each category. All 16 eyes were successfully imaged, registered, and segmented. The maximum mean (SD) inter-operator difference was 2.6 (4.8) μm. The maximum mean (SD) intra-operator difference was 2.4 (5.3) μm. There was no statistically significant difference in ONL measurements detected between baseline and follow-up (p > 0.05). The mean (SD) differences measured across visits by one operator varied from -1.6 (3.1) to 1.1 (6.1) μm. The mean (SD) coefficient of variance (CV%) for all sectors with horizontal orientation was 9.1% (2.3%), 10.1% (2.5%), and 8.6% (2.3%) for inter-observer, intra-observer, and inter-visit, respectively. The mean (SD) coefficient of variance (CV%) for all sectors with vertical orientation was 8.3% (1.8%), 6.9% (1.4%), and 8.3% (2.1%) for inter-observer, intra-observer, and inter-visit, respectively. The majority of the variation of paired repeated measurements originated from between-subject variance. The within-subject variance accounted for less than 1% of the total variability. ONL thickness measurements can be quantified with good repeatability and reproducibility using D-OCT. Identifying the magnitude of D-OCT variability among normal subjects will allow for improved development of future clinical studies that quantitatively track the progression of macular pathology.

Individual Differences in Sleep Timing Relate to Melanopsin-Based Phototransduction in Healthy Adolescents and Young Adults.

Individual differences in sleep timing have been widely recognized and are of particular relevance in adolescents and young adults who often show mild to severely delayed sleep. The biological mechanisms underlying the between-subject variance remain to be determined. Recent human genetics studies showed an association between sleep timing and melanopsin gene variation, but support for functional effects on downstream pathways and behavior was not demonstrated before. We therefore investigated the association between the autonomic (i.e., pupil diameter) and behavioral (i.e., sleep timing) readouts of two different downstream brain areas, both affected by the same melanopsin-dependent retinal phototransduction: the olivary pretectal nucleus (OPN) and the suprachiasmatic nucleus (SCN). Our study population included 71 healthy individuals within an age range with known vulnerability to a delayed sleep phase (16.8-35.7 y, 37 males, 34 females). Pupillometry was performed to estimate functionality of the intrinsic melanopsin-signaling circuitry based on the OPN-mediated post-illumination pupil response (PIPR) to blue light. Sleep timing was quantified by estimating the SCN-mediated mid-sleep timing in three different ways in parallel: using a chronotype questionnaire, a sleep diary, and actigraphy. All three measures consistently showed that those individuals with a later mid-sleep timing had a more pronounced PIPR (0.03 < P < 0.05), indicating a stronger blue-light responsiveness of the intrinsic melanopsin-based phototransduction circuitry. Trait-like individual differences in the melanopsin phototransduction circuitry contribute to individual differences in sleep timing. Blue light-sensitive young individuals are more prone to delayed sleep.

Quantitative and Qualitative Responses to Topical Cold in Healthy Caucasians Show Variance between Individuals but High Test-Retest Reliability.

Increased sensitivity to cold may be a predictor of persistent pain, but cold pain threshold is often viewed as unreliable. This study aimed to determine the within-subject reliability and between-subject variance of cold response, measured comprehensively as cold pain threshold plus pain intensity and sensation quality at threshold. A test-retest design was used over three sessions, one day apart. Response to cold was assessed at four sites (thenar eminence, volar forearm, tibialis anterior, plantar foot). Cold pain threshold was measured using a Medoc thermode and standard method of limits. Intensity of pain at threshold was rated using a 10cm visual analogue scale. Quality of sensation at threshold was quantified with indices calculated from subjects' selection of descriptors from a standard McGill Pain Questionnaire. Within-subject reliability for each measure was calculated with intra-class correlation coefficients and between-subject variance was evaluated as group coefficient of variation percentage (CV%). Gender and site comparisons were also made. Forty-five healthy adults participated: 20 male, 25 female; mean age 29 (range 18–56) years. All measures at all four test sites showed high within-subject reliability: cold pain thresholds r = 0.92–0.95; pain rating r = 0.93–0.97; McGill pain quality indices r = 0.87–0.85. In contrast, all measures showed wide between-subject variance (CV% between 51.4% and 92.5%). Upper limb sites were consistently more sensitive than lower limb sites, but equally reliable. Females showed elevated cold pain thresholds, although similar pain intensity and quality to males. Females were also more reliable and showed lower variance for all measures. Thus, although there was clear population variation, response to cold for healthy individuals was found to be highly reliable, whether measured as pain threshold, pain intensity or sensation quality. A comprehensive approach to cold response testing therefore may add validity and improve acceptance of this potentially important pain measure.

Discovering and validating between-subject variations in plasma lipids in healthy subjects.

Lipid levels are commonly used in clinical settings as disease biomarkers, and the advent of mass spectrometry-based (MS) lipidomics heralds the possibility of identifying additional lipids that can inform disease predispositions. However, the degree of natural variation for many lipids remains poorly understood, thus confounding downstream investigations on whether a specific intervention is driving observed lipid fluctuations. Here, we performed targeted mass spectrometry with multiple reaction monitoring across a comprehensive spectrum of 192 plasma lipids on eight subjects across three time-points separated by six hours and two standardized meals. A validation study to confirm the initial discoveries was performed in a further set of nine subjects, subject to the identical study design. Technical variation of the MS was assessed using duplicate measurements in the validation study, while biological variation was measured for lipid species with coefficients of variation <20%. We observed that eight lipid species from the phosphatidylethanolamine and phosphatidylcholine lipid classes were discovered and validated to vary consistently across the three time-points, where the within-subject variance can be up to 1.3-fold higher than between-subject variance. These findings highlight the importance of understanding the range of biological variation in plasma lipids as a precursor to their use in clinical biochemistry.

A Winding Road: Alzheimer's Disease Increases Circuitous Functional Connectivity Pathways.

Neuroimaging has been successful in characterizing the pattern of cerebral atrophy that accompanies the progression of Alzheimer’s disease (AD). Examination of functional connectivity, the strength of signal synchronicity between brain regions, has gathered pace as another way of understanding changes to the brain that are associated with AD. It appears to have good sensitivity and detect effects that precede cognitive decline, and thus offers the possibility to understand the neurobiology of the disease in its earliest phases. However, functional connectivity analyzes to date generally consider only the strongest connections, with weaker links ignored. This proof-of-concept study compared patients with mild-to-moderate AD (N = 11) and matched control individuals (N = 12) based on functional connectivities derived from blood-oxygenation level dependent (BOLD) sensitive functional MRI acquired during resting wakefulness. All positive connectivities irrespective of their strength were included. Transitive closures of the resulting connectome were calculated that classified connections as either direct or indirect. Between-group differences in the proportion of indirect paths were observed. In AD, there was broadly increased indirect connectivity across greater spatial distances. Furthermore, the indirect pathways in AD had greater between-subject topological variance than controls. The prevailing characterization of AD as being a disconnection syndrome is refined by the observation that direct links between regions that are impaired are perhaps replaced by an increase in indirect functional pathways that is only detectable through inclusion of connections across the entire range of connection strengths.

Assessing Assay Variability of Pesticide Metabolites in the Presence of Heavy Left-Censoring.

Assessing assay variability for field samples in environmental research is challenging, since a quantitative assay is typically constrained by a lower limit of detection. The purpose of this paper is to compare three parametric models for assessing assay variability using duplicate data subject to heavy left-censoring. Efron information criterion (EIC) and Bayesian information criterion (BIC) are used to aid in model selections. Distributional parameter estimates are obtained using maximum likelihood estimation for bivariate lognormal, bivariate zero-inflated lognormal, and bivariate 3-component mixture models. We illustrate a practical application using duplicate pesticide data from the Community Participatory Approach to Measuring Farmworker Pesticide Exposure (PACE3) study. Furthermore, a simulation study is conducted to empirically evaluate the performance of the three models. The results from PACE3 indicate that the bivariate zero-inflated lognormal model is fairly competitive based on EIC or BIC. Further, total variability for the lognormal component can be decomposed into between-subject and within-subject variance based on this model. Assay variability estimates such as within-subject coefficient variation, minimum detectable change, and probability of k-fold difference can be easily derived under the bivariate zero-inflated lognormal model. Additionally, the assay variability is rather large for the PACE3 data. Therefore, apparent longitudinal change in pesticide exposure should be examined cautiously in the context of substantial assay variability.

Evaluation of method performance for oxidative stress biomarkers in urine and biological variations in urine of patients with type 2 diabetes mellitus and diabetic nephropathy.

BackgroundOxidative stress biomarkers such as superoxide dismutase (CuZnSOD), catalase (CAT) and malondialdehyde (MDA) play an important role in the pathogenesis or progression of numerous diseases. Data regarding the biological variation and analytical quality specifications (imprecision, bias and total error) for judging the acceptability of method performance for oxidative stress biomarkers in urine are conspicuously lacking in the literature. Such data are important in setting analytical quality specifications, assessing the utility of population reference intervals (index of individuality) and assessing the significance of changes in serial results from an individual (reference change value; RCV).Materials and methods20 patients with type 2 diabetes mellitus (T2DM), 20 patients with diabetic nephropathy (DN) and 14 healthy individuals as control were involved in this study. Timed first morning urine samples were taken from patients and healthy groups on the zero, 1st, 3rd, 5th, 7th, 15th and 30th days. Index of individuality and reference change value were calculated from within-subject and between-subject variations. Methods of oxidative stress biomarkers in human blood were adopted in human urine and markers were measured as spectrophotometrically. Also, analytical quality specifications for evaluation of the method performance were established for oxidative stress biomarkers in urine.ResultsWithin-subject variations of oxidative stress biomarkers were significantly higher in patients with DN and T2DM compared to healthy subjects. MDA showed low individuality, and within-subject variances of MDA were larger than between-subject variances in all groups. However, CAT and CuZnSOD showed strong individuality, but within-subject variances of them were smaller than between-subject variances in all groups. RCVs of all analytes in diabetic patients were relatively higher, because of high within-subject variation, resulting in a higher RCV. Also, the described methodology achieves these goals, with analytical CVs of < 3.5% for all analytes. Goals for bias and total error were 6.0-7.9% and 12.5-23.3%, respectively.ConclusionsRCVs concept for predicting the clinical status in diabetic patients represents an optimization of laboratory reporting and could be a valuable tool for clinical decision. Furthermore, for oxidative stress biomarkers’ measurements in urine, the desirable imprecision goals based on biological variation are obtainable by current methodologies.

TNFα G308A polymorphism is associated with resilience to sleep deprivation-induced psychomotor vigilance performance impairment in healthy young adults.

Cytokines such as TNFα play an integral role in sleep/wake regulation and have recently been hypothesized to be involved in cognitive impairment due to sleep deprivation. We examined the effect of a guanine to adenine substitution at position 308 in the TNFα gene (TNFα G308A) on psychomotor vigilance performance impairment during total sleep deprivation. A total of 88 healthy women and men (ages 22-40) participated in one of five laboratory total sleep deprivation experiments. Performance on a psychomotor vigilance test (PVT) was measured every 2-3h. The TNFα 308A allele, which is less common than the 308G allele, was associated with greater resilience to psychomotor vigilance performance impairment during total sleep deprivation (regardless of time of day), and also provided a small performance benefit at baseline. The effect of genotype on resilience persisted when controlling for between-subjects differences in age, gender, race/ethnicity, and baseline sleep duration. The TNFα G308A polymorphism predicted less than 10% of the overall between-subjects variance in performance impairment during sleep deprivation. Nonetheless, the differential effect of the polymorphism at the peak of performance impairment was more than 50% of median performance impairment at that time, which is sizeable compared to the effects of other genotypes reported in the literature. Our findings provided evidence for a role of TNFα in the effects of sleep deprivation on psychomotor vigilance performance. Furthermore, the TNFα G308A polymorphism may have predictive potential in a biomarker panel for the assessment of resilience to psychomotor vigilance performance impairment due to sleep deprivation.

A Bivariate Mixed-Effects Location-Scale Model with application to Ecological Momentary Assessment (EMA) data.

A bivariate mixed-effects location-scale model is proposed for estimation of means, variances, and covariances of two continuous outcomes measured concurrently in time and repeatedly over subjects. Modeling the two outcomes jointly allows examination of BS and WS association between the outcomes and whether the associations are related to covariates. The variance-covariance matrices of the BS and WS effects are modeled in terms of covariates, explaining BS and WS heterogeneity. The proposed model relaxes assumptions on the homogeneity of the within-subject (WS) and between-subject (BS) variances. Furthermore, the WS variance models are extended by including random scale effects. Data from a natural history study on adolescent smoking are used for illustration. 461 students, from 9th and 10th grades, reported on their mood at random prompts during seven consecutive days. This resulted in 14,105 prompts with an average of 30 responses per student. The two outcomes considered were a subject's positive affect and a measure of how tired and bored they were feeling. Results showed that the WS association of the outcomes was negative and significantly associated with several covariates. The BS and WS variances were heterogeneous for both outcomes, and the variance of the random scale effects were significantly different from zero.

Variance components of short-term biomarkers of manganese exposure in an inception cohort of welding trainees

Various biomarkers of exposure have been explored as a way to quantitatively estimate an internal dose of manganese (Mn) exposure, but given the tight regulation of Mn in the body, inter-individual variability in baseline Mn levels, and variability in timing between exposure and uptake into various biological tissues, identification of a valuable and useful biomarker for Mn exposure has been elusive. Thus, a mixed model estimating variance components using restricted maximum likelihood was used to assess the within- and between-subject variance components in whole blood, plasma, and urine (MnB, MnP, and MnU, respectively) in a group of nine newly-exposed apprentice welders, on whom baseline and subsequent longitudinal samples were taken over a three month period. In MnB, the majority of variance was found to be between subjects (94%), while in MnP and MnU the majority of variance was found to be within subjects (79% and 99%, respectively), even when controlling for timing of sample. While blood seemed to exhibit a homeostatic control of Mn, plasma and urine, with the majority of the variance within subjects, did not. Results presented here demonstrate the importance of repeat measure or longitudinal study designs when assessing biomarkers of Mn, and the spurious associations that could result from cross-sectional analyses.

Determinants of Variance in the Habitual Physical Activity of Overweight Adults.

The number of days of data and number of subjects necessary to estimate total physical activity (TPA) and moderate-to-vigorous physical activity (MVPA) requires an understanding of within- and between-subject variances, and the influence of sex, body composition, and age. Seventy-one adults wore accelerometers for 7-day intervals over 6 consecutive months. Body fat and sex influenced TPA and MVPA. The sources of subject-related variation for TPA and MVPA were within-subject (48.4% and 54.3%), between-subject (34.3% and 31.8%), and calendar effects (17.3% and 13.9%). Based on within-subject variances, the error associated with estimating TPA and MVPA by collecting 1 to 7 days of data ranged from 28.2% to 13.3% for TPA and 62.0% to 28.6% for MVPA. Based on between-subject variances, detecting a 10% difference between 2 groups at a power of 90% requires approximately 200 and 725 subjects per group for TPA and MVPA, respectively. Estimates of MVPA are more variable than TPA in overweight adults, therefore more days of data are required to estimate MVPA and larger sample sizes to detect treatment differences for MVPA. Log-transforming data reduces the need for additional days of data collection, thereby improving chances of detecting treatment effects.

Assessment of Depression in a Rodent Model of Spinal Cord Injury

Despite an increased incidence of depression in patients after spinal cord injury (SCI), there is no animal model of depression after SCI. To address this, we used a battery of established tests to assess depression after a rodent contusion injury. Subjects were acclimated to the tasks, and baseline scores were collected before SCI. Testing was conducted on days 9-10 (acute) and 19-20 (chronic) postinjury. To categorize depression, subjects' scores on each behavioral measure were averaged across the acute and chronic stages of injury and subjected to a principal component analysis. This analysis revealed a two-component structure, which explained 72.2% of between-subjects variance. The data were then analyzed with a hierarchical cluster analysis, identifying two clusters that differed significantly on the sucrose preference, open field, social exploration, and burrowing tasks. One cluster (9 of 26 subjects) displayed characteristics of depression. Using these data, a discriminant function analysis was conducted to derive an equation that could classify subjects as "depressed" on days 9-10. The discriminant function was used in a second experiment examining whether the depression-like symptoms could be reversed with the antidepressant, fluoxetine. Fluoxetine significantly decreased immobility in the forced swim test (FST) in depressed subjects identified with the equation. Subjects that were depressed and treated with saline displayed significantly increased immobility on the FST, relative to not depressed, saline-treated controls. These initial experiments validate our tests of depression, generating a powerful model system for further understanding the relationships between molecular changes induced by SCI and the development of depression.

Pharmacodynamic modelling of placebo and buprenorphine effects on event-related potentials in experimental pain.

The purpose of the study was to investigate placebo and buprenorphine effects on event-related potentials (ERPs) in experimental pain and the potential benefit of population pharmacodynamic modelling in data analysis. Nineteen healthy volunteers received transdermal placebo and buprenorphine in a cross-over study. Drug plasma concentrations and ERPs after electrical stimulation at the median nerve with intensity adjusted to pain detection threshold were recorded until 144 hrs after administration. Placebo and concentration-effect models were fitted to data using non-linear mixed-effects modelling implemented in NONMEM (V7.2.0.). Pharmacodynamic models were developed to adequately describe both placebo and buprenorphine ERP data. Models predicted significant placebo effects, but did not predict significant effects related to buprenorphine concentration. Models revealed that ERPs varied both between subjects and between study occasions. ERPs were found to be reproducible within subjects and occasions as population variance was found to be eight times higher than the unexplained variances. Between-subject variance accounted for more than 75% of the population variance. In conclusion, pharmacodynamic modelling was successfully implemented to allow for placebo and variability correction in ERP of experimental pain. Improved outcome of ERP studies can be expected if variation between subjects and study occasions can be identified and described.

Runmixregls: A Program to Run theMIXREGLSMixed-Effects Location Scale Software from withinStata

Hedeker and Nordgren (2013) present the stand-alone MIXREGLS program for fitting the mixed-effects location scale model to continuous longitudinal and other clustered data. This model can be used when interest lies in joint modeling the mean and dispersion of subjects' responses over time. The model extends the standard two-level randomintercept mixed model by allowing both the within- and between-subject variances to be influenced by the covariates and for the within-subject variance to additionally depend on a subject random-scale effect. In this article we present the runmixregls command to run MIXREGLS seamlessly from within Stata. We illustrate the notable advantages of using runmixregls by replicating and extending the two example analyses presented in Hedeker and Nordgren (2013). We then use runmixregls to demonstrate a new and important research finding. Namely, that ignoring the random-scale effect in the withinsubject variance function will lead to the regression coefficients in this function to be estimated with spurious precision, especially the regression coefficients of subject-level covariates.

Determinants of personal exposure to some carcinogenic substances and nitrogen dioxide among the general population in five Swedish cities

Environmental levels of airborne carcinogenic and related substances are comparatively better known than individual exposure and its determinants. We report on a personal monitoring program involving five Swedish urban populations. The aim of the program was to investigate personal exposure to benzene, 1,3-butadiene, formaldehyde, and nitrogen dioxide (NO2). The measurements were performed among 40 inhabitants during seven consecutive days, in one urban area each year, during 2000-2008. The estimated population exposure levels were 1.95 μg/m(3) for benzene, 0.56 μg/m(3) for 1,3-butadiene, 19.4 μg/m(3) for formaldehyde, and 14.1 μg/m(3) for NO2. Statistical analysis using a mixed-effects model revealed that time spent in traffic and time outdoors contributed to benzene and 1,3- butadiene exposure. For benzene, refueling a car was an additional determinant influencing the exposure level. Smoking or environmental tobacco smoke were significant determinants of exposure to NO2, benzene, and 1,3-butadiene. Those with a gas stove had higher NO2 exposure. Living in a single-family house increased the exposure to formaldehyde significantly. In a variance component model, the between-subject variance dominated for 1,3-butadiene and formaldehyde, whereas the between-city variance dominated for NO2. For benzene, the between-subject and between-cities variances were similar.

Sulcal depth-position profile is a genetically mediated neuroscientific trait: description and characterization in the central sulcus.

Genetic and environmental influences on brain morphology were assessed in an extended-pedigree design by extracting depth-position profiles (DPP) of the central sulcus (CS). T1-weighted magnetic resonance images were used to measure CS length and depth in 467 human subjects from 35 extended families. Three primary forms of DPPs were observed. The most prevalent form, present in 70% of subjects, was bimodal, with peaks near hand and mouth regions. Trimodal and unimodal configurations accounted for 15 and 8%, respectively. Genetic control accounted for 56 and 66% of between-subject variance in average CS depth and length, respectively, and was not significantly influenced by environmental factors. Genetic control over CS depth ranged from 1 to 50% across the DPP. Areas of peak heritability occurred at locations corresponding to hand and mouth areas. Left and right analogous CS depth measurements were strongly pleiotropic. Shared genetic influence lessened as the distance between depth measurements was increased. We argue that DPPs are powerful phenotypes that should inform genetic influence of more complex brain regions and contribute to gene discovery efforts.