The Role of Neighborhoods in the Receipt of Transcranial Doppler Screening among Children with Sickle Cell Disease

Summary: Although transcranial Doppler (TCD) screening assesses the need for stroke prevention efforts among children with sickle cell disease (SCD), screening rates remain low across many parts of the United States. We sought to identify neighborhoods with low TCD screening rates and neighborhood-level factors related to screening to inform the utility of community-level interventions to improve TCD screening. Children ages 2 to 16 years with SCD (HbSS/HbS/b-thalassemia) living in Wayne County, MI, were identified in Michigan Medicaid (2007 to 2011) through newborn screening records. Children were enrolled for Z1 year and could contribute multiple years. We determined receipt of Z1 TCD screening and neighborhood (census tract) each year. The proportion of children receiving TCD in the tract was calculated and investigated for spatial patterns across tracts (Moran's I). Median household income, % unemployment, % black residents, and % less than high school education within each tract were ascertained from the American Community Survey. Logistic regression with generalized estimating equations was used to model associations between TCD screening and neighborhood-level factors. Overall, 329 children contributed 532 person-years and screening rates increased from 7% to 36% from 2007 to 2011. Median screening rate in tracts was 0% (interquartile range=29%) and there was no spatial pattern of TCD screening across tracts (Moran's I Z-score= 0.94, P-value=0.35). No associations were found between neighborhood characteristics and receipt of TCD screening in this disadvantaged Michigan county. Additional research is needed to inform interventions to increase TCD screening in this high stroke-risk population

Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons

The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions

Extremely strong coupling superconductivity in artificial two-dimensional Kondo lattices

When interacting electrons are confined to low-dimensions, the electron-electron correlation effect is enhanced dramatically, which often drives the system into exhibiting behaviors that are otherwise highly improbable. Superconductivity with the strongest electron correlations is achieved in heavy-fermion compounds, which contain a dense lattice of localized magnetic moments interacting with a sea of conduction electrons to form a 3D Kondo lattice. It had remained an unanswered question whether superconductivity would persist upon effectively reducing the dimensionality of these materials from three to two. Here we report on the observation of superconductivity in such an ultimately strongly-correlated system of heavy electrons confined within a 2D square-lattice of Ce-atoms (2D Kondo lattice), which was realized by fabricating epitaxial superlattices built of alternating layers of heavy-fermion CeCoIn5 and conventional metal YbCoIn5. The field-temperature phase diagram of the superlattices exhibits highly unusual behaviors, including a striking enhancement of the upper critical field relative to the transition temperature. This implies that the force holding together the superconducting electron-pairs takes on an extremely strong coupled nature as a result of two-dimensionalization.Comment: A revised version has been accepted for publication in Nature Physic

Genome-wide association of major depression: description of samples for the GAIN Major Depressive Disorder Study: NTR and NESDA biobank projects.

To identify the genomic regions that confer risk and protection for major depressive disorder (MDD) in humans, large-scale studies are needed. Such studies should collect multiple phenotypes, DNA, and ideally, biological material that allows gene expression analysis, transcriptomic, proteomic, and metabolomic studies. In this paper, we briefly review linkage studies of MDD and then describe the large-scale nationwide biological sample collection in Dutch twin families from the Netherlands Twin Register (NTR) and in participants in the Netherlands Study of Depression and Anxiety (NESDA). Within these studies, 1862 participants with a diagnosis of MDD and 1857 controls at low liability for MDD have been selected for genome-wide genotyping by the US Foundation for the National Institutes of Health Genetic Association Information Network. Stage 1 genome-wide association results are scheduled to be accessible before the end of 2007. Genome-wide association results are open-access and can be viewed at the dbGAP web portal (http://www.ncbi.nlm.nih.gov). Approved users can download the genotype and phenotype data, which have been made available as of 9 October 2007

Shifting patterns of natural variation in the nuclear genome of caenorhabditis elegans

<p>Abstract</p> <p>Background</p> <p>Genome wide analysis of variation within a species can reveal the evolution of fundamental biological processes such as mutation, recombination, and natural selection. We compare genome wide sequence differences between two independent isolates of the nematode <it>Caenorhabditis elegans </it>(CB4856 and CB4858) and the reference genome (N2).</p> <p>Results</p> <p>The base substitution pattern when comparing N2 against CB4858 reveals a transition over transversion bias (1.32:1) that is not present in CB4856. In CB4856, there is a significant bias in the direction of base substitution. The frequency of A or T bases in N2 that are G or C bases in CB4856 outnumber the opposite frequencies for transitions as well as transversions. These differences were not observed in the N2/CB4858 comparison. Similarly, we observed a strong bias for deletions over insertions in CB4856 (1.44: 1) that is not present in CB4858. In both CB4856 and CB4858, there is a significant correlation between SNP rate and recombination rate on the autosomes but not on the X chromosome. Furthermore, we identified numerous significant hotspots of variation in the CB4856-N2 comparison.</p> <p>In both CB4856 and CB4858, based on a measure of the strength of selection (k_a/k_s), all the chromosomes are under negative selection and in CB4856, there is no difference in the strength of natural selection in either the autosomes versus X or between any of the chromosomes. By contrast, in CB4858, k_a/k_svalues are smaller in the autosomes than in the X chromosome. In addition, in CB4858, k_a/k_svalues differ between chromosomes.</p> <p>Conclusions</p> <p>The clear bias of deletions over insertions in CB4856 suggests that either the CB4856 genome is becoming smaller or the N2 genome is getting larger. We hypothesize the hotspots found represent alleles that are shared between CB4856 and CB4858 but not N2. Because the k_a/k_sratio in the X chromosome is higher than the autosomes on average in CB4858, purifying selection is reduced on the X chromosome.</p

Worldwide population differentiation at disease-associated SNPs

<p>Abstract</p> <p>Background</p> <p>Recent genome-wide association (GWA) studies have provided compelling evidence of association between genetic variants and common complex diseases. These studies have made use of cases and controls almost exclusively from populations of European ancestry and little is known about the frequency of risk alleles in other populations. The present study addresses the transferability of disease associations across human populations by examining levels of population differentiation at disease-associated single nucleotide polymorphisms (SNPs).</p> <p>Methods</p> <p>We genotyped ~1000 individuals from 53 populations worldwide at 25 SNPs which show robust association with 6 complex human diseases (Crohn's disease, type 1 diabetes, type 2 diabetes, rheumatoid arthritis, coronary artery disease and obesity). Allele frequency differences between populations for these SNPs were measured using Fst. The Fst values for the disease-associated SNPs were compared to Fst values from 2750 random SNPs typed in the same set of individuals.</p> <p>Results</p> <p>On average, disease SNPs are not significantly more differentiated between populations than random SNPs in the genome. Risk allele frequencies, however, do show substantial variation across human populations and may contribute to differences in disease prevalence between populations. We demonstrate that, in some cases, risk allele frequency differences are unusually high compared to random SNPs and may be due to the action of local (i.e. geographically-restricted) positive natural selection. Moreover, some risk alleles were absent or fixed in a population, which implies that risk alleles identified in one population do not necessarily account for disease prevalence in all human populations.</p> <p>Conclusion</p> <p>Although differences in risk allele frequencies between human populations are not unusually large and are thus likely not due to positive local selection, there is substantial variation in risk allele frequencies between populations which may account for differences in disease prevalence between human populations.</p

Characterisation of age and polarity at onset in bipolar disorder

Background Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools. Aims To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics. Method Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts. Results Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO. Conclusions AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses

Genome-wide Association Study of Borderline Personality Disorder Reveals Genetic Overlap with Bipolar Disorder, Major Depression and Schizophrenia

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case–control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P=4.42 × 10−7) and PKP4 (P=8.67 × 10−7); and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, PFDR=0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [P=2.99 × 10−3]), SCZ (rg=0.34 [P=4.37 × 10−5]) and MDD (rg=0.57 [P=1.04 × 10−3]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies

Development and validation of the ISARIC 4C Deterioration model for adults hospitalised with COVID-19: a prospective cohort study.

BACKGROUND: Prognostic models to predict the risk of clinical deterioration in acute COVID-19 cases are urgently required to inform clinical management decisions. METHODS: We developed and validated a multivariable logistic regression model for in-hospital clinical deterioration (defined as any requirement of ventilatory support or critical care, or death) among consecutively hospitalised adults with highly suspected or confirmed COVID-19 who were prospectively recruited to the International Severe Acute Respiratory and Emerging Infections Consortium Coronavirus Clinical Characterisation Consortium (ISARIC4C) study across 260 hospitals in England, Scotland, and Wales. Candidate predictors that were specified a priori were considered for inclusion in the model on the basis of previous prognostic scores and emerging literature describing routinely measured biomarkers associated with COVID-19 prognosis. We used internal-external cross-validation to evaluate discrimination, calibration, and clinical utility across eight National Health Service (NHS) regions in the development cohort. We further validated the final model in held-out data from an additional NHS region (London). FINDINGS: 74 944 participants (recruited between Feb 6 and Aug 26, 2020) were included, of whom 31 924 (43·2%) of 73 948 with available outcomes met the composite clinical deterioration outcome. In internal-external cross-validation in the development cohort of 66 705 participants, the selected model (comprising 11 predictors routinely measured at the point of hospital admission) showed consistent discrimination, calibration, and clinical utility across all eight NHS regions. In held-out data from London (n=8239), the model showed a similarly consistent performance (C-statistic 0·77 [95% CI 0·76 to 0·78]; calibration-in-the-large 0·00 [-0·05 to 0·05]); calibration slope 0·96 [0·91 to 1·01]), and greater net benefit than any other reproducible prognostic model. INTERPRETATION: The 4C Deterioration model has strong potential for clinical utility and generalisability to predict clinical deterioration and inform decision making among adults hospitalised with COVID-19. FUNDING: National Institute for Health Research (NIHR), UK Medical Research Council, Wellcome Trust, Department for International Development, Bill & Melinda Gates Foundation, EU Platform for European Preparedness Against (Re-)emerging Epidemics, NIHR Health Protection Research Unit (HPRU) in Emerging and Zoonotic Infections at University of Liverpool, NIHR HPRU in Respiratory Infections at Imperial College London

Who approves fraudulence? Configurational causes of consumers' unethical judgments

Corrupt behavior presents major challenges for organizations in a wide range of settings. This article embraces a complexity theoretical perspective to elucidate the causal patterns of factors underlying consumers’ unethical judgments. This study examines how causal conditions of four distinct domains combine into configurational causes of unethical judgments of two frequent forms of corrupt consumer behavior: shoplifting and fare dodging. The findings of fuzzy-set Qualitative Comparative Analyses indicate alternative, consistently sufficient ‘‘recipes’’ for the outcomes of interest. This study extends prior work on the topic by offering new insights into the interplay and the interconnected structures of multiple causal factors and by describing configurational causes of consumers’ ethical evaluations of corrupt behaviors. This knowledge may support practitioners and policy makers to develop education and control approaches to thwart corrupt consumer behaviors