NIH Disease Funding Levels and Burden of Disease

BACKGROUND: An analysis of NIH funding in 1996 found that the strongest predictor of funding, disability-adjusted life-years (DALYs), explained only 39% of the variance in funding. In 1998, Congress requested that the Institute of Medicine (IOM) evaluate priority-setting criteria for NIH funding; the IOM recommended greater consideration of disease burden. We examined whether the association between current burden and funding has changed since that time. METHODS: We analyzed public data on 2006 NIH funding for 29 common conditions. Measures of US disease burden in 2004 were obtained from the World Health Organization's Global Burden of Disease study and national databases. We assessed the relationship between disease burden and NIH funding dollars in univariate and multivariable log-linear models that evaluated all measures of disease burden. Sensitivity analyses examined associations with future US burden, current and future measures of world disease burden, and a newly standardized NIH accounting method. RESULTS: In univariate and multivariable analyses, disease-specific NIH funding levels increased with burden of disease measured in DALYs (p = 0.001), which accounted for 33% of funding level variation. No other factor predicted funding in multivariable models. Conditions receiving the most funding greater than expected based on disease burden were AIDS ($2474 M), diabetes mellitus ($390 M), and perinatal conditions ($297 M). Depression ($719 M), injuries ($691 M), and chronic obstructive pulmonary disease ($613 M) were the most underfunded. Results were similar using estimates of future US burden, current and future world disease burden, and alternate NIH accounting methods. CONCLUSIONS: Current levels of NIH disease-specific research funding correlate modestly with US disease burden, and correlation has not improved in the last decade

A Retrospective Cohort Study of the Potency of lipid-lowering therapy and Race-gender Differences in LDL cholesterol control

<p>Abstract</p> <p>Background</p> <p>Reasons for race and gender differences in controlling elevated low density lipoprotein (LDL) cholesterol may be related to variations in prescribed lipid-lowering therapy. We examined the effect of lipid-lowering drug treatment and potency on time until LDL control for black and white women and men with a baseline elevated LDL.</p> <p>Methods</p> <p>We studied 3,484 older hypertensive patients with dyslipidemia in 6 primary care practices over a 4-year timeframe. Potency of lipid-lowering drugs calculated for each treated day and summed to assess total potency for at least 6 and up to 24 months. Cox models of time to LDL control within two years and logistic regression models of control within 6 months by race-gender adjust for: demographics, clinical, health care delivery, primary/specialty care, LDL measurement, and drug potency.</p> <p>Results</p> <p>Time to LDL control decreased as lipid-lowering drug potency increased (P < 0.001). Black women (N = 1,440) received the highest potency therapy (P < 0.001) yet were less likely to achieve LDL control than white men (N = 717) (fully adjusted hazard ratio [HR] 0.66 [95% CI 0.56-0.78]). Black men (N = 666) and white women (N = 661) also had lower adjusted HRs of LDL control (0.82 [95% CI 0.69, 0.98] and 0.75 [95% CI 0.64-0.88], respectively) than white men. Logistic regression models of LDL control by 6 months and other sensitivity models affirmed these results.</p> <p>Conclusions</p> <p>Black women and, to a lesser extent, black men and white women were less likely to achieve LDL control than white men after accounting for lipid-lowering drug potency as well as diverse patient and provider factors. Future work should focus on the contributions of medication adherence and response to treatment to these clinically important differences.</p

Appropriate model use for predicting elevations and inundation extent for extreme flood events

Flood risk assessment is generally studied using flood simulation models; however, flood risk managers often simplify the computational process; this is called a “simplification strategy”. This study investigates the appropriateness of the “simplification strategy” when used as a flood risk assessment tool for areas prone to flash flooding. The 2004 Boscastle, UK, flash flood was selected as a case study. Three different model structures were considered in this study, including: (1) a shock-capturing model, (2) a regular ADI-type flood model and (3) a diffusion wave model, i.e. a zero-inertia approach. The key findings from this paper strongly suggest that applying the “simplification strategy” is only appropriate for flood simulations with a mild slope and over relatively smooth terrains, whereas in areas susceptible to flash flooding (i.e. steep catchments), following this strategy can lead to significantly erroneous predictions of the main parameters—particularly the peak water levels and the inundation extent. For flood risk assessment of urban areas, where the emergence of flash flooding is possible, it is shown to be necessary to incorporate shock-capturing algorithms in the solution procedure, since these algorithms prevent the formation of spurious oscillations and provide a more realistic simulation of the flood levels

Evaluating genetic markers and neurobiochemical analytes for fluoxetine response using a panel of mouse inbred strains

RationaleIdentification of biomarkers that establish diagnosis or treatment response is critical to the advancement of research and management of patients with depression.ObjectiveOur goal was to identify biomarkers that can potentially assess fluoxetine response and risk to poor treatment outcome.MethodsWe measured behavior, gene expression, and the levels of 36 neurobiochemical analytes across a panel of genetically diverse mouse inbred lines after chronic treatment with water or fluoxetine.ResultsGlyoxylase 1 (GLO1) and guanine nucleotide-binding protein 1 (GNB1) mostly account for baseline anxiety-like and depressive-like behavior, indicating a common biological link between depression and anxiety. Fluoxetine-induced biochemical alterations discriminated positive responders, while baseline neurobiochemical differences differentiated negative responders (p < 0.006). Results show that glial fibrillary acidic protein, S100 beta protein, GLO1, and histone deacetylase 5 contributed most to fluoxetine response. These proteins are linked within a cellular growth/proliferation pathway, suggesting the involvement of cellular genesis in fluoxetine response. Furthermore, a candidate genetic locus that associates with baseline depressive-like behavior contains a gene that encodes for cellular proliferation/adhesion molecule (Cadm1), supporting a genetic basis for the role of neuro/gliogenesis in depression.ConclusionWe provided a comprehensive analysis of behavioral, neurobiochemical, and transcriptome data across 30 mouse inbred strains that has not been accomplished before. We identified biomarkers that influence fluoxetine response, which, altogether, implicate the importance of cellular genesis in fluoxetine treatment. More broadly, this approach can be used to assess a wide range of drug response phenotypes that are challenging to address in human samples.Electronic supplementary materialThe online version of this article (doi:10.1007/s00213-011-2574-z) contains supplementary material, which is available to authorized users

Gene Expression in a Drosophila Model of Mitochondrial Disease

Background A point mutation in the Drosophila gene technical knockout (tko), encoding mitoribosomal protein S12, was previously shown to cause a phenotype of respiratory chain deficiency, developmental delay, and neurological abnormalities similar to those presented in many human mitochondrial disorders, as well as defective courtship behavior. Methodology/Principal Findings Here, we describe a transcriptome-wide analysis of gene expression in tko25t mutant flies that revealed systematic and compensatory changes in the expression of genes connected with metabolism, including up-regulation of lactate dehydrogenase and of many genes involved in the catabolism of fats and proteins, and various anaplerotic pathways. Gut-specific enzymes involved in the primary mobilization of dietary fats and proteins, as well as a number of transport functions, were also strongly up-regulated, consistent with the idea that oxidative phosphorylation OXPHOS dysfunction is perceived physiologically as a starvation for particular biomolecules. In addition, many stress-response genes were induced. Other changes may reflect a signature of developmental delay, notably a down-regulation of genes connected with reproduction, including gametogenesis, as well as courtship behavior in males; logically this represents a programmed response to a mitochondrially generated starvation signal. The underlying signalling pathway, if conserved, could influence many physiological processes in response to nutritional stress, although any such pathway involved remains unidentified. Conclusions/Significance These studies indicate that general and organ-specific metabolism is transformed in response to mitochondrial dysfunction, including digestive and absorptive functions, and give important clues as to how novel therapeutic strategies for mitochondrial disorders might be developed.Public Library of Scienc