Clinical and polysomnographic predictors of the Natural History of poor sleep in the general population

Study Objectives: Approximately 8-10% of the general population suffers from chronic insomnia, whereas another 20-30% of the population has insomnia symptoms at any given time (i.e., poor sleep). However, few longitudinal studies have examined risk factors of the natural history of poor sleep, and none have examined the role of polysomnographic (PSG) variables. Design: Representative longitudinal study. Setting: Sleep laboratory. Participants: From a random, general population sample of 1,741 individuals of the adult Penn State Cohort, 1,395 were followed up after 7.5 yr. Measurements: Full medical evaluation and 1-night PSG at baseline and telephone interview at follow-up. Results: The rate of incident poor sleep was 18.4%. Physical (e.g., obesity, sleep apnea, and ulcer) and mental (e.g., depression) health conditions and behavioral factors (e.g., smoking and alcohol consumption) increased the odds of incident poor sleep as compared to normal sleep. The rates of persistent, remitted, and poor sleepers who developed chronic insomnia were 39%, 44%, and 17%, respectively. Risk factors for persistent poor sleep were physical health conditions combined with psychologic distress. Shorter objective sleep duration and a family history of sleep problems were risk factors for poor sleep evolving into chronic insomnia. Conclusions: Poor sleep appears to be primarily a symptom of physical and mental health conditions, whereas the persistence of poor sleep is associated with psychologic distress. Importantly, sleep apnea appears to be associated with incident poor sleep but not with chronic insomnia. Finally, this study suggests that objective short sleep duration in poor sleepers is a biologic marker of genetic predisposition to chronic insomniaThis research was funded in part by the National Institutes of Health grants RO1 51931, RO1 40916 (to Dr. Bixler), and RO1 64415 (to Dr. Vgontzas)

In-Home Training for Fathers of Children with Autism: A Follow up Study and Evaluation of Four Individual Training Components

Literature regarding fathers of children with autism remains sparse, and because mothers are the more common intervening parent, few training methods have focused on fathers. Thus, we sought to evaluate effects of in-home training directed at fathers and their ability to train mothers in the same manner in which they were trained. Fathers were taught four skills commonly associated with in-home training interventions for parents of children with autism: following the child’s lead, imitation with animation, commenting on the child, and expectant waiting. Father skills were evaluated twice a week for 12 weeks during videotaped in-home father–child play sessions. Analyses included visual inspection of graphed data and statistical analyses of father skill acquisition, mother skill acquisition, and child behaviors with both parents. A multivariate repeated measures analysis of 18 dyads revealed significant increases in frequencies of fathers’ imitation with animation, expectant waiting, and commenting on the child. Child initiating rates increased significantly as did frequencies of child non-speech vocalizations. Analysis of mothers revealed significant increases in frequencies of imitation with animation, expectant waiting, and following the child’s lead. Child behaviors had similar results for father and mother sessions. Findings are consistent with those from our first study indicating that fathers can effectively implement skills that promote father–child social interactions and that children respond positively to this approach

Patient-reported outcome measures of the impact of cancer on patient’s everyday lives: a systematic review

Purpose: Patients with advanced disease are living longer and commonly used patient-reported outcome measures (PROMs) may miss relevant elements of the quality of extended survival. This systematic review examines the measures used to capture aspects of the quality of survival including impact on patients’ everyday lives such as finances, work and family roles. Methods: Searches were conducted in MEDLINE, EMBASE, CINAHL and PsycINFO restricted to English language articles. Information on study characteristics, instruments and outcomes was systematically extracted and synthesised. A predefined set of criteria was used to rate the quality of studies. Results: From 2761 potentially relevant articles, 22 met all inclusion criteria, including 10 concerning financial distress, 3 on roles and responsibilities and 9 on multiple aspects of social well-being. Generally, studies were not of high quality; many lacked bias free participant selection, had confounding factors and had not accounted for all participants. High levels of financial distress were reported and were associated with multiple demographic factors such as age and income. There were few reports concerned with impacts on patients’ roles/responsibilities in everyday life although practical and emotional struggles with parenting were identified. Social difficulties were common and associated with multiple factors including being a caregiver. Many studies were single time-point surveys and used non-validated measures. Exceptions were employment of the COST and Social Difficulties Inventory (SDI), validated measures of financial and social distress respectively. Conclusions: Impact on some important parts of patients’ everyday lives is insufficiently and inconsistently captured. Further PROM development focussing on roles and responsibilities, including work and caring for dependents, is warranted. Implications for Cancer Survivors: Factors such as finances, employment and responsibility for caring for dependents (e.g. children and elderly relatives) can affect the well-being of cancer survivors. There is a need to ensure that any instruments used to assess patients’ social well-being are broad enough to include these areas so that any difficulties arising can be better understood and appropriately supported

Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors

Novel genetic loci underlying human intracranial volume identified through genome-wide association

Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438 adults, we discovered five novel loci for intracranial volume and confirmed two known signals. Four of the loci are also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height. We found a high genetic correlation with child head circumference (ρgenetic=0.748), which indicated a similar genetic background and allowed for the identification of four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial volume were also related to childhood and adult cognitive function, Parkinson’s disease, and enriched near genes involved in growth pathways including PI3K–AKT signaling. These findings identify biological underpinnings of intracranial volume and provide genetic support for theories on brain reserve and brain overgrowth

Novel genetic loci associated with hippocampal volume

The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg =-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Narcissistic Features in Young Adolescents: Relations to Aggression and Internalizing Symptoms

Recent research and theory suggest narcissistic features contribute to aggression in adults. The present study examined the association of narcissistic features with aggression and internalizing symptoms in 233 students of 5th–8th grade at three inner-city schools. A factor analysis of the Narcissistic Personality Inventory in this sample revealed three factors: Adaptive Narcissism, Exploitativeness, and Exhibitionism. Regression analyses were used to predict the association of these three narcissistic features with self-, teacher-, and peer-reported aggression and self-reported internalizing symptoms. Results indicate narcissistic exploitativeness positively predicted self-reported proactive aggression, and narcissistic exhibitionism positively predicted internalizing symptoms. Narcissism and self-esteem interacted to predict teacher-reported aggression and self-reported internalizing symptoms. Results are discussed in the context of existing theories of narcissism, threatened egotism, and self-perception bias.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45298/1/10964_2004_Article_485227.pd