Incidence of community-acquired lower respiratory tract infections and pneumonia among older adults in the United Kingdom: a population-based study.

Community-acquired lower respiratory tract infections (LRTI) and pneumonia (CAP) are common causes of morbidity and mortality among those aged ≥65 years; a growing population in many countries. Detailed incidence estimates for these infections among older adults in the United Kingdom (UK) are lacking. We used electronic general practice records from the Clinical Practice Research Data link, linked to Hospital Episode Statistics inpatient data, to estimate incidence of community-acquired LRTI and CAP among UK older adults between April 1997-March 2011, by age, sex, region and deprivation quintile. Levels of antibiotic prescribing were also assessed. LRTI incidence increased with fluctuations over time, was higher in men than women aged ≥70 and increased with age from 92.21 episodes/1000 person-years (65-69 years) to 187.91/1000 (85-89 years). CAP incidence increased more markedly with age, from 2.81 to 21.81 episodes/1000 person-years respectively, and was higher among men. For both infection groups, increases over time were attenuated after age-standardisation, indicating that these rises were largely due to population aging. Rates among those in the most deprived quintile were around 70% higher than the least deprived and were generally higher in the North of England. GP antibiotic prescribing rates were high for LRTI but lower for CAP (mostly due to immediate hospitalisation). This is the first study to provide long-term detailed incidence estimates of community-acquired LRTI and CAP in UK older individuals, taking person-time at risk into account. The summary incidence commonly presented for the ≥65 age group considerably underestimates LRTI/CAP rates, particularly among older individuals within this group. Our methodology and findings are likely to be highly relevant to health planners and researchers in other countries with aging populations

Comparison of CATs, CURB-65 and PMEWS as Triage Tools in Pandemic Influenza Admissions to UK Hospitals: Case Control Analysis Using Retrospective Data

Triage tools have an important role in pandemics to identify those most likely to benefit from higher levels of care. We compared Community Assessment Tools (CATs), the CURB-65 score, and the Pandemic Medical Early Warning Score (PMEWS); to predict higher levels of care (high dependency - Level 2 or intensive care - Level 3) and/or death in patients at or shortly after admission to hospital with A/H1N1 2009 pandemic influenza. This was a case-control analysis using retrospectively collected data from the FLU-CIN cohort (1040 adults, 480 children) with PCR-confirmed A/H1N1 2009 influenza. Area under receiver operator curves (AUROC), sensitivity, specificity, positive predictive values and negative predictive values were calculated. CATs best predicted Level 2/3 admissions in both adults [AUROC (95% CI): CATs 0.77 (0.73, 0.80); CURB-65 0.68 (0.64, 0.72); PMEWS 0.68 (0.64, 0.73), p<0.001] and children [AUROC: CATs 0.74 (0.68, 0.80); CURB-65 0.52 (0.46, 0.59); PMEWS 0.69 (0.62, 0.75), p<0.001]. CURB-65 and CATs were similar in predicting death in adults with both performing better than PMEWS; and CATs best predicted death in children. CATs were the best predictor of Level 2/3 care and/or death for both adults and children. CATs are potentially useful triage tools for predicting need for higher levels of care and/or mortality in patients of all ages

Fine-scale detection of population-specific linkage disequilibrium using haplotype entropy in the human genome

<p>Abstract</p> <p>Background</p> <p>The creation of a coherent genomic map of recent selection is one of the greatest challenges towards a better understanding of human evolution and the identification of functional genetic variants. Several methods have been proposed to detect linkage disequilibrium (LD), which is indicative of natural selection, from genome-wide profiles of common genetic variations but are designed for large regions.</p> <p>Results</p> <p>To find population-specific LD within small regions, we have devised an entropy-based method that utilizes differences in haplotype frequency between populations. The method has the advantages of incorporating multilocus association, conciliation with low allele frequencies, and independence from allele polarity, which are ideal for short haplotype analysis. The comparison of HapMap SNPs data from African and Caucasian populations with a median resolution size of ~23 kb gave us novel candidates as well as known selection targets. Enrichment analysis for the yielded genes showed associations with diverse diseases such as cardiovascular, immunological, neurological, and skeletal and muscular diseases. A possible scenario for a selective force is discussed. In addition, we have developed a web interface (ENIGMA, available at <url>http://gibk21.bse.kyutech.ac.jp/ENIGMA/index.html</url>), which allows researchers to query their regions of interest for population-specific LD.</p> <p>Conclusion</p> <p>The haplotype entropy method is powerful for detecting population-specific LD embedded in short regions and should contribute to further studies aiming to decipher the evolutionary histories of modern humans.</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

Schizophrenia and psychotic symptoms in families of two American Indian tribes

Abstract Background The risk of schizophrenia is thought to be higher in population isolates that have recently been exposed to major and accelerated cultural change, accompanied by ensuing socio-environmental stressors/triggers, than in dominant, mainstream societies. We investigated the prevalence and phenomenology of schizophrenia in 329 females and 253 males of a Southwestern American Indian tribe, and in 194 females and 137 males of a Plains American Indian tribe. These tribal groups were evaluated as part of a broader program of gene-environment investigations of alcoholism and other psychiatric disorders. Methods Semi-structured psychiatric interviews were conducted to allow diagnoses utilizing standardized psychiatric diagnostic criteria, and to limit cultural biases. Study participants were recruited from the community on the basis of membership in pedigrees, and not by convenience. After independent raters evaluated the interviews blindly, DSM-III-R diagnoses were assigned by a consensus of experts well-versed in the local cultures. Results Five of the 582 Southwestern American Indian respondents (prevalence = 8.6 per 1000), and one of the 331 interviewed Plains American Indians (prevalence = 3.02 per 1000) had a lifetime diagnosis of schizophrenia. The lifetime prevalence rates of schizophrenia within these two distinct American Indian tribal groups is consistent with lifetime expectancy rates reported for the general United States population and most isolate and homogeneous populations for which prevalence rates of schizophrenia are available. While we were unable to factor in the potential modifying effect that mortality rates of schizophrenia-suffering tribal members may have had on the overall tribal rates, the incidence of schizophrenia among the living was well within the normative range. Conclusion The occurrence of schizophrenia among members of these two tribal population groups is consistent with prevalence rates reported for population isolates and in the general population. Vulnerabilities to early onset alcohol and drug use disorders do not lend convincing support to a diathesis-stressor model with these stressors, commonly reported with these tribes. Nearly one-fifth of the respondents reported experiencing psychotic-like symptoms, reaffirming the need to examine sociocultural factors actively before making positive diagnoses of psychosis or schizophrenia.</p

Extreme Evolutionary Disparities Seen in Positive Selection across Seven Complex Diseases

Positive selection is known to occur when the environment that an organism inhabits is suddenly altered, as is the case across recent human history. Genome-wide association studies (GWASs) have successfully illuminated disease-associated variation. However, whether human evolution is heading towards or away from disease susceptibility in general remains an open question. The genetic-basis of common complex disease may partially be caused by positive selection events, which simultaneously increased fitness and susceptibility to disease. We analyze seven diseases studied by the Wellcome Trust Case Control Consortium to compare evidence for selection at every locus associated with disease. We take a large set of the most strongly associated SNPs in each GWA study in order to capture more hidden associations at the cost of introducing false positives into our analysis. We then search for signs of positive selection in this inclusive set of SNPs. There are striking differences between the seven studied diseases. We find alleles increasing susceptibility to Type 1 Diabetes (T1D), Rheumatoid Arthritis (RA), and Crohn's Disease (CD) underwent recent positive selection. There is more selection in alleles increasing, rather than decreasing, susceptibility to T1D. In the 80 SNPs most associated with T1D (p-value <7.01×10−5) showing strong signs of positive selection, 58 alleles associated with disease susceptibility show signs of positive selection, while only 22 associated with disease protection show signs of positive selection. Alleles increasing susceptibility to RA are under selection as well. In contrast, selection in SNPs associated with CD favors protective alleles. These results inform the current understanding of disease etiology, shed light on potential benefits associated with the genetic-basis of disease, and aid in the efforts to identify causal genetic factors underlying complex disease

Socioeconomic status and prostate cancer incidence and mortality rates among the diverse population of California

The racial/ethnic disparities in prostate cancer rates are well documented, with the highest incidence and mortality rates observed among African-Americans followed by non-Hispanic Whites, Hispanics, and Asian/Pacific Islanders. Whether socioeconomic status (SES) can account for these differences in risk has been investigated in previous studies, but with conflicting results. Furthermore, previous studies have focused primarily on the differences between African-Americans and non-Hispanic Whites, and little is known for Hispanics and Asian/Pacific Islanders. To further investigate the relationship between SES and prostate cancer among African-Americans, non-Hispanic Whites, Hispanics, and Asian/Pacific Islanders, we conducted a large population-based cross-sectional study of 98,484 incident prostate cancer cases and 8,997 prostate cancer deaths from California. Data were abstracted from the California Cancer Registry, a population-based surveillance, epidemiology, and end results (SEER) registry. Each prostate cancer case and death was assigned a multidimensional neighborhood-SES index using the 2000 US Census data. SES quintile-specific prostate cancer incidence and mortality rates and rate ratios were estimated using SEER*Stat for each race/ethnicity categorized into 10-year age groups. For prostate cancer incidence, we observed higher levels of SES to be significantly associated with increased risk of disease [SES Q1 vs. Q5: relative risk (RR) = 1.28; 95% confidence interval (CI): 1.25–1.30]. Among younger men (45–64 years), African-Americans had the highest incidence rates followed by non-Hispanic Whites, Hispanics, and Asian/Pacific Islanders for all SES levels. Yet, among older men (75–84 years) Hispanics, following African-Americans, displayed the second highest incidence rates of prostate cancer. For prostate cancer deaths, higher levels of SES were associated with lower mortality rates of prostate cancer deaths (SES Q1 vs. Q5: RR = 0.88; 95% CI: 0.92–0.94). African-Americans had a twofold to fivefold increased risk of prostate cancer deaths in comparison to non-Hispanic Whites across all levels of SES. Our findings suggest that SES alone cannot account for the greater burden of prostate cancer among African-American men. In addition, incidence and mortality rates of prostate cancer display different age and racial/ethnic patterns across gradients of SES

The differential effects of core stabilization exercise regime and conventional physiotherapy regime on postural control parameters during perturbation in patients with movement and control impairment chronic low back pain

<p>Abstract</p> <p>Background</p> <p>The purpose of the present study was to examine the differential effect of core stability exercise training and conventional physiotherapy regime on altered postural control parameters in patients with chronic low back pain (CLBP). As heterogeneity in CLBP population moderates the effect of intervention on outcomes, in this study, interventions approaches were used based on sub-groups of CLBP.</p> <p>Methods</p> <p>This was an allocation concealed, blinded, sequential and pragmatic control trial. Three groups of participants were investigated during postural perturbations: 1) CLBP patients with movement impairment (n = 15, MI group) randomized to conventional physiotherapy regime 2) fifteen CLBP patients with control impairment randomized to core stability group (CI group) and 3) fifteen healthy controls (HC).</p> <p>Results</p> <p>The MI group did not show any significant changes in postural control parameters after the intervention period however they improved significantly in disability scores and fear avoidance belief questionnaire work score (P < 0.05). The CI group showed significant improvements in Fx, Fz, and My variables (p < 0.013, p < 0.006, and p < 0.002 respectively with larger effect sizes: Hedges's g > 0.8) after 8 weeks of core stability exercises for the adjusted p values. Postural control parameters of HC group were analyzed independently with pre and post postural control parameters of CI and MI group. This revealed the significant improvements in postural control parameters in CI group compared to MI group indicating the specific adaptation to the core stability exercises in CI group. Though the disability scores were reduced significantly in CI and MI groups (p < 0.001), the post intervention scores between groups were not found significant (p < 0.288). Twenty percentage absolute risk reduction in flare-up rates during intervention was found in CI group (95% CI: 0.69-0.98).</p> <p>Conclusions</p> <p>In this study core stability exercise group demonstrated significant improvements after intervention in ground reaction forces (Fz, Mz; g > 0.8) indicating changes in load transfer patterns during perturbation similar to HC group.</p> <p>Trial registration</p> <p>UTRN095032158-06012009423714</p

Granger Causality Analysis of Steady-State Electroencephalographic Signals during Propofol-Induced Anaesthesia

Changes in conscious level have been associated with changes in dynamical integration and segregation among distributed brain regions. Recent theoretical developments emphasize changes in directed functional (i.e., causal) connectivity as reflected in quantities such as ‘integrated information’ and ‘causal density’. Here we develop and illustrate a rigorous methodology for assessing causal connectivity from electroencephalographic (EEG) signals using Granger causality (GC). Our method addresses the challenges of non-stationarity and bias by dividing data into short segments and applying permutation analysis. We apply the method to EEG data obtained from subjects undergoing propofol-induced anaesthesia, with signals source-localized to the anterior and posterior cingulate cortices. We found significant increases in bidirectional GC in most subjects during loss-of-consciousness, especially in the beta and gamma frequency ranges. Corroborating a previous analysis we also found increases in synchrony in these ranges; importantly, the Granger causality analysis showed higher inter-subject consistency than the synchrony analysis. Finally, we validate our method using simulated data generated from a model for which GC values can be analytically derived. In summary, our findings advance the methodology of Granger causality analysis of EEG data and carry implications for integrated information and causal density theories of consciousness

A high-density transcript linkage map with 1,845 expressed genes positioned by microarray-based Single Feature Polymorphisms (SFP) in Eucalyptus

<p>Abstract</p> <p>Background</p> <p>Technological advances are progressively increasing the application of genomics to a wider array of economically and ecologically important species. High-density maps enriched for transcribed genes facilitate the discovery of connections between genes and phenotypes. We report the construction of a high-density linkage map of expressed genes for the heterozygous genome of <it>Eucalyptus </it>using Single Feature Polymorphism (SFP) markers.</p> <p>Results</p> <p>SFP discovery and mapping was achieved using pseudo-testcross screening and selective mapping to simultaneously optimize linkage mapping and microarray costs. SFP genotyping was carried out by hybridizing complementary RNA prepared from 4.5 year-old trees xylem to an SFP array containing 103,000 25-mer oligonucleotide probes representing 20,726 unigenes derived from a modest size expressed sequence tags collection. An SFP-mapping microarray with 43,777 selected candidate SFP probes representing 15,698 genes was subsequently designed and used to genotype SFPs in a larger subset of the segregating population drawn by selective mapping. A total of 1,845 genes were mapped, with 884 of them ordered with high likelihood support on a framework map anchored to 180 microsatellites with average density of 1.2 cM. Using more probes per unigene increased by two-fold the likelihood of detecting segregating SFPs eventually resulting in more genes mapped. <it>In silico </it>validation showed that 87% of the SFPs map to the expected location on the 4.5X draft sequence of the <it>Eucalyptus grandis </it>genome.</p> <p>Conclusions</p> <p>The <it>Eucalyptus </it>1,845 gene map is the most highly enriched map for transcriptional information for any forest tree species to date. It represents a major improvement on the number of genes previously positioned on <it>Eucalyptus </it>maps and provides an initial glimpse at the gene space for this global tree genome. A general protocol is proposed to build high-density transcript linkage maps in less characterized plant species by SFP genotyping with a concurrent objective of reducing microarray costs. HIgh-density gene-rich maps represent a powerful resource to assist gene discovery endeavors when used in combination with QTL and association mapping and should be especially valuable to assist the assembly of reference genome sequences soon to come for several plant and animal species.</p