Attention-deficit/hyperactivity disorder and lifetime cannabis use: genetic overlap and causality

Attention-deficit/hyperactivity disorder (ADHD) is a severely impairing neurodevelopmental disorder with a prevalence of 5% in children and adolescents and of 2.5% in adults. Comorbid conditions in ADHD play a key role in symptom progression, disorder course and outcome. ADHD is associated with a significantly increased risk for substance use, abuse and dependence. ADHD and cannabis use are partly determined by genetic factors; the heritability of ADHD is estimated at 70-80% and of cannabis use initiation at 40-48%. In this study, we used summary statistics from the largest available meta-analyses of genome-wide association studies (GWAS) of ADHD (n = 53,293) and lifetime cannabis use (n = 32,330) to gain insights into the genetic overlap and causal relationship of these two traits. We estimated their genetic correlation to be r2 = 0.29 (P = 1.63 × 10-5) and identified four new genome-wide significant loci in a cross-trait analysis: two in a single variant association analysis (rs145108385, P = 3.30 × 10-8 and rs4259397, P = 4.52 × 10-8) and two in a gene-based association analysis (WDPCP, P = 9.67 × 10-7 and ZNF251, P = 1.62 × 10-6). Using a two-sample Mendelian randomization approach we found support that ADHD is causal for lifetime cannabis use, with an odds ratio of 7.9 for cannabis use in individuals with ADHD in comparison to individuals without ADHD (95% CI (3.72, 15.51), P = 5.88 × 10-5). These results substantiate the temporal relationship between ADHD and future cannabis use and reinforce the need to consider substance misuse in the context of ADHD in clinical interventions.

Degree of genetic liability for Alzheimer's disease associated with specific proteomic profiles in cerebrospinal fluid

Genetic factors play a major role in Alzheimer's disease (AD) pathology, but biological mechanisms through which these factors contribute to AD remain elusive. Using a cerebrospinal fluid (CSF) proteomic approach, we examined associations between polygenic risk scores for AD (PGRS) and CSF proteomic profiles in 250 individuals with normal cognition, mild cognitive impairment, and AD-type dementia from the Alzheimer's Disease Neuroimaging Initiative. Out of 412 proteins, 201 were associated with PGRS. Hierarchical clustering analysis on proteins associated with PGRS at different single-nucleotide polymorphism p-value inclusion thresholds identified 3 clusters: (1) a protein cluster correlated with highly significant single-nucleotide polymorphisms, associated with amyloid-beta pathology and complement cascades; (2) a protein cluster associated with PGRS additionally including variants contributing to modest risk, involved in neural injury; (3) a protein cluster that also included less strongly associated variants, enriched with cytokine-cytokine interactions and cell adhesion molecules. These findings suggest that CSF protein levels reflect varying degrees of genetic liability for AD and may serve as a tool to investigate biological mechanisms in AD.

Author Correction: Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Author Correction: GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability

Several occurrences of the word 'schizophrenia' have been re-worded as 'liability to schizophrenia' or 'schizophrenia risk', including in the title, which should have been "GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability," as well as in Supplementary Figures 1-10 and Supplementary Tables 7-10, to more accurately reflect the findings of the work.

Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer's disease risk

Alzheimer's disease (AD) is highly heritable and recent studies have identified over 20 disease-associated genomic loci. Yet these only explain a small proportion of the genetic variance, indicating that undiscovered loci remain. Here, we performed a large genome-wide association study of clinically diagnosed AD and AD-by-proxy (71,880 cases, 383,378 controls). AD-by-proxy, based on parental diagnoses, showed strong genetic correlation with AD (r_g = 0.81). Meta-analysis identified 29 risk loci, implicating 215 potential causative genes. Associated genes are strongly expressed in immune-related tissues and cell types (spleen, liver, and microglia). Gene-set analyses indicate biological mechanisms involved in lipid-related processes and degradation of amyloid precursor proteins. We show strong genetic correlations with multiple health-related outcomes, and Mendelian randomization results suggest a protective effect of cognitive ability on AD risk. These results are a step forward in identifying the genetic factors that contribute to AD risk and add novel insights into the neurobiology of AD.

Conditional and interaction gene-set analysis reveals novel functional pathways for blood pressure

Gene-set analysis provides insight into which functional and biological properties of genes are aetiologically relevant for a particular phenotype. But genes have multiple properties, and these properties are often correlated across genes. This can cause confounding in a gene-set analysis, because one property may be statistically associated even if biologically irrelevant to the phenotype, by being correlated with gene properties that are relevant. To address this issue we present a novel conditional and interaction gene-set analysis approach, which attains considerable functional refinement of its conclusions compared to traditional gene-set analysis. We applied our approach to blood pressure phenotypes in the UK Biobank data (N = 360,243), the results of which we report here. We confirm and further refine several associations with multiple processes involved in heart and blood vessel formation but also identify novel interactions, among others with cardiovascular tissues involved in regulatory pathways of blood pressure homoeostasis.

Gene-set analysis (GSA) is widely used to infer functional and biological properties of a gene set. Here, the authors develop a conditional and interaction gene-set analysis approach that can considerably refine results from traditional GSA.

GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia

Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.

Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to variation in intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present a large-scale genetic association study of intelligence (n = 269,867), identifying 205 associated genomic loci (190 new) and 1,016 genes (939 new) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and associations with 146 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain, specifically in striatal medium spiny neurons and hippocampal pyramidal neurons. Gene set analyses implicate pathways related to nervous system development and synaptic structure. We confirm previous strong genetic correlations with multiple health-related outcomes, and Mendelian randomization analysis results suggest protective effects of intelligence for Alzheimer's disease and ADHD and bidirectional causation with pleiotropic effects for schizophrenia. These results are a major step forward in understanding the neurobiology of cognitive function as well as genetically related neurological and psychiatric disorders.

A tutorial on conducting genome-wide association studies: Quality control and statistical analysis

OBJECTIVES

Genome-wide association studies (GWAS) have become increasingly popular to identify associations between single nucleotide polymorphisms (SNPs) and phenotypic traits. The GWAS method is commonly applied within the social sciences. However, statistical analyses will need to be carefully conducted and the use of dedicated genetics software will be required. This tutorial aims to provide a guideline for conducting genetic analyses.

METHODS

We discuss and explain key concepts and illustrate how to conduct GWAS using example scripts provided through GitHub (https://github.com/MareesAT/GWA_tutorial/). In addition to the illustration of standard GWAS, we will also show how to apply polygenic risk score (PRS) analysis. PRS does not aim to identify individual SNPs but aggregates information from SNPs across the genome in order to provide individual-level scores of genetic risk.

RESULTS

The simulated data and scripts that will be illustrated in the current tutorial provide hands-on practice with genetic analyses. The scripts are based on PLINK, PRSice, and R, which are commonly used, freely available software tools that are accessible for novice users.

CONCLUSIONS

By providing theoretical background and hands-on experience, we aim to make GWAS more accessible to researchers without formal training in the field.

MIR137 schizophrenia-associated locus controls synaptic function by regulating synaptogenesis, synapse maturation and synaptic transmission

The MIR137 locus is a replicated genetic risk factor for schizophrenia. The risk-associated allele is reported to increase miR-137 expression and miR-137 overexpression alters synaptic transmission in mouse hippocampus. We investigated the cellular mechanisms underlying these observed effects in mouse hippocampal neurons in culture. First, we correlated the risk allele to expression of the genes in the MIR137 locus in human postmortem brain. Some evidence for increased MIR137HG expression was observed, especially in hippocampus of the disease-associated genotype. Second, in mouse hippocampal neurons, we confirmed previously observed changes in synaptic transmission upon miR-137 overexpression. Evoked synaptic transmission and spontaneous release were 50% reduced. We identified defects in release probability as the underlying cause. In contrast to previous observations, no evidence was obtained for selective synaptic vesicle docking defects. Instead, ultrastructural morphometry revealed multiple effects of miR-137 overexpression on docking, active zone length and total vesicle number. Moreover, proteomic analyses of neuronal protein showed that expression of Syt1 and Cplx1, previously reported as downregulated upon miR-137 overexpression, was unaltered. Immunocytochemistry of synapses overexpressing miR-137 showed normal Synaptotagmin1 and Complexin1 protein levels. Instead, our proteomic analyses revealed altered expression of genes involved in synaptogenesis. Concomitantly, synaptogenesis assays revealed 31% reduction in synapse formation. Taken together, these data show that miR-137 regulates synaptic function by regulating synaptogenesis, synaptic ultrastructure and synapse function. These effects are plausible contributors to the increased schizophrenia risk associated with miR-137 overexpression.

Item-level analyses reveal genetic heterogeneity in neuroticism

Genome-wide association studies (GWAS) of psychological traits are generally conducted on (dichotomized) sums of items or symptoms (e.g., case-control status), and not on the individual items or symptoms themselves. We conduct large-scale GWAS on 12 neuroticism items and observe notable and replicable variation in genetic signal between items. Within samples, genetic correlations among the items range between 0.38 and 0.91 (mean rg = .63), indicating genetic heterogeneity in the full item set. Meta-analyzing the two samples, we identify 255 genome-wide significant independent genomic regions, of which 138 are item-specific. Genetic analyses and genetic correlations with 33 external traits support genetic differences between the items. Hierarchical clustering analysis identifies two genetically homogeneous item clusters denoted depressed affect and worry. We conclude that the items used to measure neuroticism are genetically heterogeneous, and that biological understanding can be gained by studying them in genetically more homogeneous clusters.

Genetically-Informed Patient Selection for iPSC Studies of Complex Diseases May Aid in Reducing Cellular Heterogeneity

Induced pluripotent stem cell (iPSC) technology is more and more used for the study of genetically complex human disease but is challenged by variability, sample size and polygenicity. We discuss studies involving iPSC-derived neurons from patients with Schizophrenia (SCZ), to exemplify that heterogeneity in sampling strategy complicate the detection of disease mechanisms. We offer a solution to controlling variability within and between iPSC studies by using specific patient selection strategies.

Genome-wide association analysis of insomnia complaints identifies risk genes and genetic overlap with psychiatric and metabolic traits

Persistent insomnia is among the most frequent complaints in general practice. To identify genetic factors for insomnia complaints, we performed a genome-wide association study (GWAS) and a genome-wide gene-association study (GWGAS) in 113,006 individuals. We identify three loci and seven genes of which one locus and five genes are supported by joint analysis with an independent sample (n=7,565). Our top association (MEIS1, P<5×10^-8) has previously been implicated in Restless Legs Syndrome (RLS). Additional analyses favor the hypothesis that MEIS1 shows pleiotropy for insomnia and RLS, and that the observed association with insomnia complaints cannot be explained only by the presence of an RLS subgroup. Sex-specific analyses suggested different genetic architectures across sexes in addition to common genetic factors. We show substantial positive genetic overlap with internalizing and metabolic traits and negative overlap with subjective well-being and educational attainment. These findings provide novel insight into the genetic architecture of insomnia.

Genome-wide association study of lifetime cannabis use based on a large meta-analytic sample of 32 330 subjects from the International Cannabis Consortium

Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32 330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10(-8)) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

A guide on gene prioritization in studies of psychiatric disorders

There has been an increasing interest in the identification of genetic variants causing individual differences in human behavior. Psychiatrists have contributed to the genetics field by defining the most important behavioral characteristics and by studying the association between genetic variants and behavioral differences within phenotypically well-characterized samples in which detailed assessments have been collected (e.g. neuroimaging). These samples are typically limited in size and are therefore not suitable for a genome-wide association analysis. Instead, gene association studies conducted in such samples typically focus on a few genes of interest, allowing smaller sample sizes. However, the selection of high-priority genes is not always straightforward and psychiatrists will usually have a limited background in genetics. We aim to fill this gap by (i) providing a basic introduction to genetics; (ii) showing how the selection of genes of interest can be optimized by the use of two web tools: Polysearch and Gene Prospector; (iii) illustrating how statistical power analyses can be performed and discussing the importance of sufficiently powered studies. This guide can help psychiatrists with limited experience in genetics in designing genetic studies that allow identification of specific behavioral, cognitive, or neural correlates of genetic risk variants, while avoiding common pitfalls. Copyright © 2015 John Wiley & Sons, Ltd.

What Cure Models Can Teach us About Genome-Wide Survival Analysis

The aim of logistic regression is to estimate genetic effects on disease risk, while survival analysis aims to determine effects on age of onset. In practice, genetic variants may affect both types of outcomes. A cure survival model analyzes logistic and survival effects simultaneously. The aim of this simulation study is to assess the performance of logistic regression and traditional survival analysis under a cure model and to investigate the benefits of cure survival analysis. We simulated data under a cure model and varied the percentage of subjects at risk for disease (cure fraction), the logistic and survival effect sizes, and the contribution of genetic background risk factors. We then computed the error rates and estimation bias of logistic, Cox proportional hazards (PH), and cure PH analysis, respectively. The power of logistic and Cox PH analysis is sensitive to the cure fraction and background heritability. Our results show that traditional Cox PH analysis may erroneously detect age of onset effects if no such effects are present in the data. In the presence of genetic background risk even the cure model results in biased estimates of both the odds ratio and the hazard ratio. Cure survival analysis takes cure fractions into account and can be used to simultaneously estimate the effect of genetic variants on disease risk and age of onset. Since genome-wide cure survival analysis is not computationally feasible, we recommend this analysis for genetic variants that are significant in a traditional survival analysis.

Genetic liability for schizophrenia predicts risk of immune disorders

BACKGROUND

Schizophrenia patients and their parents have an increased risk of immune disorders compared to population controls and their parents. This may be explained by genetic overlap in the pathogenesis of both types of disorders. The purpose of this study was to investigate the genetic overlap between schizophrenia and three immune disorders and to compare with the overlap between schizophrenia and two disorders not primarily characterized by immune dysregulation: bipolar disorder and type 2 diabetes.

METHODS

We performed a polygenic risk score analysis using results from the schizophrenia Psychiatric GWAS consortium (PGC) (8922 cases and 9528 controls) and five Wellcome Trust Case Control Consortium (WTCCC) case samples as target cases: bipolar disorder (n=1998), type 1 diabetes (n=2000), Crohn's diseases (n=2005), rheumatoid arthritis (n=1999), and type 2 diabetes (n=1999). The WTCCC British Birth Cohort and National Blood Service samples (n=3004) were used as target controls. Additionally, we tested whether schizophrenia polygenic risk scores significantly differed between patients with immune disorder, bipolar disorder, and type 2 diabetes respectively.

RESULTS

Polygenic risk scores for schizophrenia significantly predicted disease status in all three immune disorder samples (Nagelkerke-R(2) 1.1%-1.3%; p<0.05). The polygenic risk of schizophrenia in patients with immune disorders was significantly lower than in patients with bipolar disorder (Nagelkerke-R(2) 6.0%; p<0.05), but higher than in type 2 diabetes patients (Nagelkerke-R(2) 0.5%; p<0.05).

CONCLUSIONS

Our results suggest that genetic factors are shared between schizophrenia and immune disorders. This contributes to an accumulating body of evidence that immune processes may play a role in the etiology of schizophrenia.

A systems medicine research approach for studying alcohol addiction

According to the World Health Organization, about 2 billion people drink alcohol. Excessive alcohol consumption can result in alcohol addiction, which is one of the most prevalent neuropsychiatric diseases afflicting our society today. Prevention and intervention of alcohol binging in adolescents and treatment of alcoholism are major unmet challenges affecting our health-care system and society alike. Our newly formed German SysMedAlcoholism consortium is using a new systems medicine approach and intends (1) to define individual neurobehavioral risk profiles in adolescents that are predictive of alcohol use disorders later in life and (2) to identify new pharmacological targets and molecules for the treatment of alcoholism. To achieve these goals, we will use omics-information from epigenomics, genetics transcriptomics, neurodynamics, global neurochemical connectomes and neuroimaging (IMAGEN; Schumann et al. ) to feed mathematical prediction modules provided by two Bernstein Centers for Computational Neurosciences (Berlin and Heidelberg/Mannheim), the results of which will subsequently be functionally validated in independent clinical samples and appropriate animal models. This approach will lead to new early intervention strategies and identify innovative molecules for relapse prevention that will be tested in experimental human studies. This research program will ultimately help in consolidating addiction research clusters in Germany that can effectively conduct large clinical trials, implement early intervention strategies and impact political and healthcare decision makers.

Assumptions and properties of limiting pathway models for analysis of epistasis in complex traits

For most complex traits, results from genome-wide association studies show that the proportion of the phenotypic variance attributable to the additive effects of individual SNPs, that is, the heritability explained by the SNPs, is substantially less than the estimate of heritability obtained by standard methods using correlations between relatives. This difference has been called the "missing heritability". One explanation is that heritability estimates from family (including twin) studies are biased upwards. Zuk et al. revisited overestimation of narrow sense heritability from twin studies as a result of confounding with non-additive genetic variance. They propose a limiting pathway (LP) model that generates significant epistatic variation and its simple parametrization provides a convenient way to explore implications of epistasis. They conclude that over-estimation of narrow sense heritability from family data ('phantom heritability') may explain an important proportion of missing heritability. We show that for highly heritable quantitative traits large phantom heritability estimates from twin studies are possible only if a large contribution of common environment is assumed. The LP model is underpinned by strong assumptions that are unlikely to hold, including that all contributing pathways have the same mean and variance and are uncorrelated. Here, we relax the assumptions that underlie the LP model to be more biologically plausible. Together with theoretical, empirical, and pragmatic arguments we conclude that in outbred populations the contribution of additive genetic variance is likely to be much more important than the contribution of non-additive variance.

Underestimated effect sizes in GWAS: fundamental limitations of single SNP analysis for dichotomous phenotypes

Complex diseases are often highly heritable. However, for many complex traits only a small proportion of the heritability can be explained by observed genetic variants in traditional genome-wide association (GWA) studies. Moreover, for some of those traits few significant SNPs have been identified. Single SNP association methods test for association at a single SNP, ignoring the effect of other SNPs. We show using a simple multi-locus odds model of complex disease that moderate to large effect sizes of causal variants may be estimated as relatively small effect sizes in single SNP association testing. This underestimation effect is most severe for diseases influenced by numerous risk variants. We relate the underestimation effect to the concept of non-collapsibility found in the statistics literature. As described, continuous phenotypes generated with linear genetic models are not affected by this underestimation effect. Since many GWA studies apply single SNP analysis to dichotomous phenotypes, previously reported results potentially underestimate true effect sizes, thereby impeding identification of true effect SNPs. Therefore, when a multi-locus model of disease risk is assumed, a multi SNP analysis may be more appropriate.

Emotionele arbeid en psychologisch welzijn van docenten

Emotional labour and psychological well-being in teachers

S. Stringer, E. Ouweneel, P. Le Blanc, A. Cheriakova & J. Smulders, Gedrag & Organisatie, volume 22, September 2009, nr. 3, pp. 214-231

Emotional labour could have negative as well as positive effects on the employees' psychological well-being. In this cross-sectional study among 149 high school teachers, the relationship between emotional labour – in this study conceptualized as emotional demands – and emotional exhaustion and work engagement respectively was studied. First of all, it was examined whether emotional dissonance mediates the relationship between emotional demands and both emotional exhaustion and work engagement. Next, the possible moderating effect of two emotion regulation strategies, surface acting and deep acting, on the relationship between emotional dissonance and the two outcome variables was studied. The results showed that emotional dissonance partially mediated the relationship between emotional demands and emotional exhaustion. Furthermore, it was found that deep acting had a buffer effect on the negative relationship between emotional dissonance and work engagement. Finally, the implications of the results are discussed and suggestions for further research are mentioned.

Gender differences in the association of overweight and asthma morbidity among urban adolescents with asthma

Asthma and obesity disproportionately affect US African-American youth. Among youth with asthma, obesity has been associated with poor control. The impact of gender on this association is unclear. We examined these relationships in a sample of urban, African-American adolescents with asthma. Questionnaires were used to identify high school students with asthma, and to examine the association of body mass index (BMI) to asthma morbidity, by gender. Of 5967 students completing questionnaires, 599 (10%) met criteria for asthma and 507 had data sufficient for inclusion in further analyses (46% male, mean age = 15.1 yr). Univariately, BMI > 85th percentile was significantly related only to reported emergency department visits (ED) and school days missed for any reason, Odds Ratio (95%Confidence Interval) = 1.7(1.1-2.7), p = 0.01 and 1.8(1.1-3.0), p = 0.01, respectively. A significant gender-BMI interaction (p < 0.05) was observed in multivariate models for ED visits, hospitalizations and school days missed for asthma. In gender-specific models, adjusted Risk Ratios for BMI > 85th and ED visits, hospitalizations, and school days missed because of asthma were 1.7(0.9-3.2), 6.6(3.1-14.6) and 3.6(1.8-7.2) in males. These associations were not observed in females. Gender modifies the association between BMI and asthma-related morbidity among adolescents with asthma. Results have implications for clinical management as well as future research.

Elevated expression of DNA ligase I in human cancers

PURPOSE

Human DNA ligase I plays an essential role in DNA replication, recombination, and repair by catalyzing the formation of phosphodiester bonds between adjacent 5'-phosphoryl and 3'-hydroxyl termini at single breaks in duplex DNA molecules. DNA ligase I is responsible for the majority of DNA ligase activity present in proliferating cells among four different forms of DNA ligases, designated DNA ligase I, II, III, and IV. In this study, we were interested in comparing DNA ligase I level in human tumors versus normal tissues and in studying whether the inhibition of DNA ligase I could lead to tumor cell death.

EXPERIMENTAL DESIGN

DNA ligase I level was measured by Western immunoblot assay in various human malignant tumor specimens and benign tissues obtained from patients, in peripheral blood lymphocytes obtained from healthy donors, and in human tumors grown in nude mice. We also have designed antisense oligonucleotides (ODNs) targeting the mRNA of DNA ligase I and tested whether DNA ligase I antisense ODNs could control tumor cell growth.

RESULTS

The amount of DNA ligase I enzyme in malignant tumors was considerably higher than that in benign normal tissues and peripheral blood lymphocytes. The level of DNA ligase I in human tumors grown in nude mice was also very high, and the expression of DNA ligase I appears to be constitutive during in vivo tumor development. We have observed that DNA ligase I antisense ODN inhibited tumor cell growth in a dose-response manner, but nonspecific control ODNs had little effect on the growth of the same cell lines.

CONCLUSIONS

The presence of DNA ligase I at higher levels in human tumors than in benign normal tissues and normal peripheral lymphocytes suggests DNA ligase I plays more of a role in proliferating cells than in resting cells. These results, together with our finding that DNA ligase I antisense ODNs can suppress tumor cell proliferation, warrant the design and testing of human DNA ligase I inhibitors as new anticancer agents.

The role of computed tomography scans in evaluating sinus disease in pediatric patients

OBJECTIVES

To determine the incidence and severity of sinus abnormalities in children undergoing computed tomography (CT) of the sinuses for suspected chronic sinusitis. To compare these findings with abnormalities noted on random CT scans.

METHODS

Sixty CT scans, performed for evaluation of sinus disease in symptomatic children aged 2-12, were compared with 50 CT scans of children aged 2-12 of the orbits or sinuses obtained for indications other than sinusitis. A staging system was applied to assess the severity of abnormalities.

RESULTS

Mucoperiosteal thickening was present in 60% of symptomatic and 46%, of random CT scans (logistic regression, P = 0.144). Children aged 2-4 and 9-12 had an increased prevalence of abnormalities in both groups, although these findings were not statistically significant (logistic regression, P = 0.817). Early stage sinus disease was present in the majority of random (96%) and symptomatic (85%) children.

CONCLUSIONS

There is a high incidence of mucoperiosteal thickening in the paranasal sinuses of children. CT scans of the sinuses should be obtained from children who are being considered for sinus surgery after failing the appropriate medical therapy. Decisions regarding the need for sinus surgery should not be solely based on imaging abnormalities.

Managing dysphagia in palliative care

Dysphagia is a common problem in patients with advanced cancer. The nursing management of this condition must pay equal attention to the various physical and psychological signs and symptoms to promote patient well-being and comfort.

Occult primary tumors of the head and neck: detection with 2-[F-18] fluoro-2-deoxy-D-glucose SPECT

PURPOSE

To evaluate 2-[fluorine-18]fluoro-2-deoxy-D-glucose (FDG) single photon emission computed tomography (SPECT) in the detection of clinically occult primary tumors of the upper aerodigestive tract.

MATERIALS AND METHODS

Eighteen patients with histologically proved cervical nodal metastasis from squamous cell carcinoma (SCC) underwent FDG SPECT; 17 also underwent computed tomography (CT) and one underwent magnetic resonance (MR) imaging. All 18 patients underwent direct panendoscopy and biopsy. Biopsy and imaging results were correlated.

RESULTS

Among 11 histologically proved primary tumors, FDG SPECT depicted nine tumors; CT depicted four lesions. Five patients had abnormal FDG uptake with negative biopsy results. Among five patients with normal SPECT findings, biopsy results were positive in two and negative in three. FDG SPECT at the initial reading had sensitivity of 81%, specificity of 38%, positive predictive value of 64%, and negative predictive value of 60% for detection of occult primary tumors.

CONCLUSION

FDG SPECT guidance of endoscopic biopsies in patients with occult primary SCCs of the head and neck has the potential to yield a higher rate of positive biopsy results than that traditionally expected from "blind" endoscopic procedures with "random" or "speculative" biopsy. FDG SPECT and CT are likely to remain complementary studies for the detection of occult primary tumors of the head and neck.

Nonnutritive sucking during tube feedings: effects on preterm neonates in an intensive care unit

Preterm neonates (mean 32 weeks' gestation, 1,300 gm birth weight) were provided a pacifier for nonnutritive sucking during tube feedings in the intensive care nursery. Their clinical course, subsequent bottle feeding behavior, and performance on the Brazelton Neonatal Behavior Assessment scale were compared with those of control group infants. The infants provided with pacifiers averaged 27 fewer tube feedings, started bottle feeding three days earlier, averaged a greater weight gain per day, and were discharged eight days earlier for an average hospital cost savings of approximately $3,500. Formula intake was similar for the two groups, although nurses appeared to provide more feeding stimulation for the control infants. On the Brazelton scale, the infants provided with pacifiers showed weak reflexes more frequently. Increased restfulness and diminished activity level in these infants may have contributed to the appearance of weak reflexes. The consistency between these findings and those of previous investigators suggests that the provision of a pacifier for nonnutritive sucking during tube feedings may be a cost-effective form of intervention.

Teenage, lower-class, black mothers and their preterm infants: an intervention and developmental follow-up

To assess the combined risks of being born preterm and to a teenage mother, and to evaluate the effects of an early intervention, preterm infants born to lower-class, black, teenage mothers were provided a home-based, parent-training intervention, and their development was then compared with that of nonintervention controls, of term infants of teenage mothers, and of term and preterm infants of adult mothers. Despite equivalence on prenatal care, factors which placed the preterm infant of the teenage mother at greater risk at birth were the small-for-date size of the infant and the less realistic developmental milestones and child rearing attitudes expressed by the mother. The preterm infants of teenage mothers who received intervention showed more optimal growth, Denver scores, and face-to-face interactions at 4 months. Their mothers rated their infants' temperaments more optimally, expressed more realistic developmental milestones and child-rearing attitudes, and received higher ratings on face-to-face interactions. At 8 months, the intervention group received superior Bayley mental, Caldwell, and infant temperament scores.