Association between polygenic liability for schizophrenia and substance involvement: A nationwide population‐based study in Taiwan

Schizophrenia and substance involvement frequently co‐occur in individuals, and a bidirectional relationship between the two has been proposed; shared underlying genetic factors could be an alternative explanation. This study investigated the genetic overlap between schizophrenia and substance involvement, including tobacco, alcohol and betel nut use. The study subjects were recruited from the Taiwan Biobank, and genome‐wide genotyping data was available for 18 327 participants without schizophrenia. We calculated the Psychiatric Genomics Consortium‐derived polygenic risk score (PRS) for schizophrenia in each participant. The significance of the schizophrenia PRS associated with substance involvement was evaluated using a regression model with adjustments for gender, age and population stratification components. The modified effect of gender or birth decade was also explored. The schizophrenia PRS was positively associated with lifetime tobacco smoking in women (OR in per SD increase in PRS = 1.12 with 95% CI 1.04‐1.20, P = .002), but not in men (OR = 0.99 with 95% CI 0.95‐1.04, P = .74), and the gender‐PRS interaction reached significance (P = .006). The OR between PRS and lifetime tobacco smoking increased with the birth decade (P of birth decade‐PRS interaction = .0002). In women, OR increased from 0.97 (P = .85) for subjects with a birth decade before 1950 to 1.21 (P = .04) for subjects with a birth decade after 1980; in men, the corresponding OR increased from 0.88 (P = .04) to 1.13 (P = .11). There was no association between schizophrenia PRS and alcohol/betel nut use phenotypes. This study provides evidence for the genetic overlap between schizophrenia and tobacco use in women, and this overlap was stronger in the younger population.     

Albuminuria,Disease Duration,and Glycated Hemoglobin Are Related With Bone Mineral Density in Type 1 Diabetes: A Cross-sectional Study

ObjectiveStudies have found a significant decrease in bone mineral density (BMD) in individuals with type 1 diabetes (T1D) compared to healthy controls. Factors associated with this phenomenon have yet to be defined; therefore, this study aimed to explore the association of glycated hemoglobin (HbA1c), disease duration, albuminuria, and glomerular filtration rate with BMD in adults with T1D.MethodsA cross-sectional study was carried out in tertiary care center. BMD analysis was performed by dual x-ray absorptiometry. Linear models were constructed considering variables associated with BMD. Approval from the ethics committees and informed consent were obtained.ResultsWe included 128 participants, of whom 59% were women, and 16% had menopause. The median age was 33 (26-42) years. The average age of diabetes diagnosis was 15.3 ± 6.3 years, and the median disease duration was 19.5 (12-27) years. In the adjusted analysis, higher albuminuria (P < .01) and disease duration (P < .05) were associated with a lower BMD in the femoral neck and total hip, independently of age, sex, and body mass index (BMI). Higher HbA1c (P < .01) was associated with a lower spine BMD after adjustment for age, sex, and BMI.ConclusionStudied factors specific to T1D, including albuminuria, disease duration, and HbA1c have an association with BMD regardless of BMI, age, and sex.     

Influence of an active stable system on the behavior and body condition of Icelandic horses

Horses are often stabled in individual boxes, a method that does not meet their natural needs and may cause psychical and musculoskeletal diseases. This problem is particularly evident in Iceland, where horses often spend the long winter periods in cramped boxes. The aim of this study was to analyze the suitability of a group housing system in Iceland, but the results are also applicable to horses of other regions. Eight Icelandic horses were observed in an active stable system, and their behavior and time budget were recorded. Movement and lying behavior were studied with ALT (Activity, Lying, Temperature detection) pedometers. The effect of an automatic concentrate feeding station (CFS) on the horses’ behavior was examined. In the first period of investigation, the horses were fed concentrates manually, and in the second period, they were fed with the CFS. Additional behavioral observations and a determination of social hierarchy occurred directly or by video surveillance. The physical condition of the horses was recorded by body weight (BW) measurement and body condition scoring (BCS). The results showed a significant increase between the first and second trial periods in both the activity (P < 0.001) and the lying time (P = 0.003) of the horses with use of the CFS. However, there was no significant change in BW during the first period without the CFS (P = 0.884) or during the second period with the CFS (P = 0.540). The BCS of the horses was constant at a very good level during both trial periods, and the horses showed a low level of aggression, a firm social hierarchy and behavioral synchronization. This study concludes that group housing according to the active stable principle is a welfare-friendly option for keeping horses and is a suitable alternative to conventional individual boxes.     

Testing the heritability and parent-of-origin hypotheses for ages at onset of psoriatic arthritis under biased sampling

The heritability and parent-of-origin effect hypotheses for chronic diseases can be evaluated by estimating and conducting inference about the parameters that measure the within-family dependences in disease onset times. We model the within-family associations in these times using a Gaussian copula whose correlation matrix accommodates the different pairwise family relationships. We derive score-type statistics to test the heritability and parent-of-origin effect hypotheses when the families selection protocol induces a sampling bias. We illustrate the use of the developed methods through an application to a motivating family study in Psoriatic arthritis and provide strong evidence of excessive paternal transmission of risk.     

Bone Mineral Density of the 1/3 Radius Refines Osteoporosis Diagnosis,Correlates With Prevalent Fractures,and Enhances Fracture Risk Estimates

ObjectiveTo investigate the added value of 1/3 radius (1/3R) for the diagnosis of osteoporosis by spine and hip sites and its correlation with prevalent fractures and predicted fracture risk.MethodsFracture Risk Assessment Tool (FRAX) scores for hip and major osteoporotic fractures (MOF) with/without trabecular bone score were considered proxy for fracture risk. The contribution of 1/3R to risk prediction was depicted via linear regression models with FRAX score as the dependent variable—first only with central and then with radius T-score as an additional covariate. Significance of change in the explained variance was compared by F-test.ResultsThe study included 1453 patients, 86% women, aged 66 ± 10 years. A total of 32% (n = 471) were osteoporotic by spine/hip and 8% (n = 115) by radius only, constituting a 24.4% increase in the number of subjects defined as osteoporotic (n = 586, 40%). Prior fracture prevalence was similar among patients with osteoporosis by spine/hip (17.4%) and radius only (19.1%) (P = .77).FRAX prediction by a regression model using spine/hip T-score yielded explained variance of 51.8% and 49.9% for MOF and 39.8% and 36.4% for hip (with/without trabecular bone score adjustment, respectively). The contribution of 1/3R was statistically significant (P < .001) and slightly increased the explained variance to 52.3% and 50.4% for MOF and 40.9% and 37.4% for hip, respectively.ConclusionReclassification of BMD results according to radius measurements results in higher diagnostic output. Prior fractures were equally prevalent among patients with radius-only and classic-site osteoporosis. FRAX tool performance slightly improved by incorporating radius BMD. Whether this approach may lead to a better fracture prediction warrants further prospective evaluation.     

Score test for missing at random or not under logistic missingness models

Missing data are frequently encountered in various disciplines and can be divided into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). Valid statistical approaches to missing data depend crucially on correct identification of the underlying missingness mechanism. Although the problem of testing whether this mechanism is MCAR or MAR has been extensively studied, there has been very little research on testing MAR versus MNAR. A critical challenge that is faced when dealing with this problem is the issue of model identification under MNAR. In this paper, under a logistic model for the missing probability, we develop two score tests for the problem of whether the missingness mechanism is MAR or MNAR under a parametric model and a semiparametric location model on the regression function. The implementation of the score tests circumvents the identification issue as it requires only parameter estimation under the null MAR assumption. Our simulations and analysis of human immunodeficiency virus data show that the score tests have well-controlled type I errors and desirable powers.     

Deep generative models for 3D molecular structure

Deep generative models have gained recent popularity for chemical design. Many of these models have historically operated in 2D space; however, more recently explicit 3D molecular generative models have become of interest, which are the topic of this article. Dozens of published models have been developed in the last few years to generate molecules directly in 3D, outputting both the atom types and coordinates, either in one-shot or adding atoms or fragments step-by-step. These 3D generative models can also be guided by structural information such as a binding pocket representation to successfully generate molecules with docking score ranges similar to known actives, but still showing lower computational efficiency and generation throughput than 1D/2D generative models and sometimes producing unrealistic conformations. We advocate for a unified benchmark of metrics to evaluate generation and propose perspectives to be addressed in next implementations.