78 research outputs found

    Radiographic severity of knee osteoarthritis is conditional on interleukin 1 receptor antagonist gene variations

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    BACKGROUND: A lack of biomarkers that identify patients at risk for severe osteoarthritis (OA) complicates development of disease-modifying OA drugs. OBJECTIVE: To determine whether inflammatory genetic markers could stratify patients with knee OA into high and low risk for destructive disease. METHODS: Genotype associations with knee OA severity were assessed in two Caucasian populations. Fifteen single nucleotide polymorphisms (SNPs) in six inflammatory genes were evaluated for association with radiographic severity and with synovial fluid mediators in a subset of the patients. RESULTS: Interleukin 1 receptor antagonist (IL1RN) SNPs (rs419598, rs315952 and rs9005) predicted Kellgren-Lawrence scores independently in each population. One IL1RN haplotype was associated with lower odds of radiographic severity (OR=0.15; 95% CI 0.065 to 0.349; p<0.0001), greater joint space width and lower synovial fluid cytokine levels. Carriage of the IL1RN haplotype influenced the age relationship with severity. CONCLUSION: IL1RN polymorphisms reproducibly contribute to disease severity in knee OA and may be useful biomarkers for patient selection in disease-modifying OA drug trials

    PIK3CA Mutations Frequently Coexist with RAS and BRAF Mutations in Patients with Advanced Cancers

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    Oncogenic mutations of PIK3CA, RAS (KRAS, NRAS), and BRAF have been identified in various malignancies, and activate the PI3K/AKT/mTOR and RAS/RAF/MEK pathways, respectively. Both pathways are critical drivers of tumorigenesis.Tumor tissues from 504 patients with diverse cancers referred to the Clinical Center for Targeted Therapy at MD Anderson Cancer Center starting in October 2008 were analyzed for PIK3CA, RAS (KRAS, NRAS), and BRAF mutations using polymerase chain reaction-based DNA sequencing.PIK3CA mutations were found in 54 (11%) of 504 patients tested; KRAS in 69 (19%) of 367; NRAS in 19 (8%) of 225; and BRAF in 31 (9%) of 361 patients. PIK3CA mutations were most frequent in squamous cervical (5/14, 36%), uterine (7/28, 25%), breast (6/29, 21%), and colorectal cancers (18/105, 17%); KRAS in pancreatic (5/9, 56%), colorectal (49/97, 51%), and uterine cancers (3/20, 15%); NRAS in melanoma (12/40, 30%), and uterine cancer (2/11, 18%); BRAF in melanoma (23/52, 44%), and colorectal cancer (5/88, 6%). Regardless of histology, KRAS mutations were found in 38% of patients with PIK3CA mutations compared to 16% of patients with wild-type (wt)PIK3CA (p = 0.001). In total, RAS (KRAS, NRAS) or BRAF mutations were found in 47% of patients with PIK3CA mutations vs. 24% of patients wtPIK3CA (p = 0.001). PIK3CA mutations were found in 28% of patients with KRAS mutations compared to 10% with wtKRAS (p = 0.001) and in 20% of patients with RAS (KRAS, NRAS) or BRAF mutations compared to 8% with wtRAS (KRAS, NRAS) or wtBRAF (p = 0.001).PIK3CA, RAS (KRAS, NRAS), and BRAF mutations are frequent in diverse tumors. In a wide variety of tumors, PIK3CA mutations coexist with RAS (KRAS, NRAS) and BRAF mutations

    A simplified (modified) Duke Activity Status Index (M-DASI) to characterise functional capacity: A secondary analysis of the Measurement of Exercise Tolerance before Surgery (METS) study

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    Background Accurate assessment of functional capacity, a predictor of postoperative morbidity and mortality, is essential to improving surgical planning and outcomes. We assessed if all 12 items of the Duke Activity Status Index (DASI) were equally important in reflecting exercise capacity. Methods In this secondary cross-sectional analysis of the international, multicentre Measurement of Exercise Tolerance before Surgery (METS) study, we assessed cardiopulmonary exercise testing and DASI data from 1455 participants. Multivariable regression analyses were used to revise the DASI model in predicting an anaerobic threshold (AT) >11 ml kg −1 min −1 and peak oxygen consumption (VO 2 peak) >16 ml kg −1 min −1, cut-points that represent a reduced risk of postoperative complications. Results Five questions were identified to have dominance in predicting AT>11 ml kg −1 min −1 and VO 2 peak>16 ml.kg −1min −1. These items were included in the M-DASI-5Q and retained utility in predicting AT>11 ml.kg −1.min −1 (area under the receiver-operating-characteristic [AUROC]-AT: M-DASI-5Q=0.67 vs original 12-question DASI=0.66) and VO 2 peak (AUROC-VO2 peak: M-DASI-5Q 0.73 vs original 12-question DASI 0.71). Conversely, in a sensitivity analysis we removed one potentially sensitive question related to the ability to have sexual relations, and the ability of the remaining four questions (M-DASI-4Q) to predict an adequate functional threshold remained no worse than the original 12-question DASI model. Adding a dynamic component to the M-DASI-4Q by assessing the chronotropic response to exercise improved its ability to discriminate between those with VO 2 peak>16 ml.kg −1.min −1 and VO 2 peak<16 ml.kg −1.min −1. Conclusions The M-DASI provides a simple screening tool for further preoperative evaluation, including with cardiopulmonary exercise testing, to guide perioperative management

    Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

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    [This corrects the article DOI: 10.1186/s13054-016-1208-6.]

    Integration of the Duke Activity Status Index into preoperative risk evaluation: a multicentre prospective cohort study.

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    BACKGROUND: The Duke Activity Status Index (DASI) questionnaire might help incorporate self-reported functional capacity into preoperative risk assessment. Nonetheless, prognostically important thresholds in DASI scores remain unclear. We conducted a nested cohort analysis of the Measurement of Exercise Tolerance before Surgery (METS) study to characterise the association of preoperative DASI scores with postoperative death or complications. METHODS: The analysis included 1546 participants (≥40 yr of age) at an elevated cardiac risk who had inpatient noncardiac surgery. The primary outcome was 30-day death or myocardial injury. The secondary outcomes were 30-day death or myocardial infarction, in-hospital moderate-to-severe complications, and 1 yr death or new disability. Multivariable logistic regression modelling was used to characterise the adjusted association of preoperative DASI scores with outcomes. RESULTS: The DASI score had non-linear associations with outcomes. Self-reported functional capacity better than a DASI score of 34 was associated with reduced odds of 30-day death or myocardial injury (odds ratio: 0.97 per 1 point increase above 34; 95% confidence interval [CI]: 0.96-0.99) and 1 yr death or new disability (odds ratio: 0.96 per 1 point increase above 34; 95% CI: 0.92-0.99). Self-reported functional capacity worse than a DASI score of 34 was associated with increased odds of 30-day death or myocardial infarction (odds ratio: 1.05 per 1 point decrease below 34; 95% CI: 1.00-1.09), and moderate-to-severe complications (odds ratio: 1.03 per 1 point decrease below 34; 95% CI: 1.01-1.05). CONCLUSIONS: A DASI score of 34 represents a threshold for identifying patients at risk for myocardial injury, myocardial infarction, moderate-to-severe complications, and new disability

    Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

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    Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe

    Analysis of shared heritability in common disorders of the brain

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    ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders

    The genetic architecture of the human cerebral cortex

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    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

    Partitioning the Heritability of Tourette Syndrome and Obsessive Compulsive Disorder Reveals Differences in Genetic Architecture

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