Gabapentin Drug Misuse Signals: A Pharmacovigilance Assessment Using the FDA Adverse Event Reporting System

Background: Although there have been increasing reports of intentional gabapentin misuse, epidemiological evidence for the phenomenon is limited. The purpose of this study was to determine whether there are pharmacovigilance abuse signals for gabapentin.Methods: Using FDA Adverse Events Reporting System reports from January 1, 2005 to December 31, 2015, we calculated pharmacovigilance signal measures (i.e., reporting odds ratio, proportional reporting ratio, information component, and empirical Bayes geometric mean) for abuse-related adverse event (AR-AE)-gabapentin pairs. Loglinear modeling assessed the frequency of concurrent reporting of abuse-related and abusespecific AEs (AS-AEs) associated with gabapentin. Findings were compared to a positive (pregabalin) and negative (duloxetine) control.Results: From 2005-2015 there were 5,951,229 unique AE reports submitted to the FDA including 99,977 for gabapentin, 73,977 for duloxetine, and 97,813 for pregabalin. Significant drug-AR-AE pair signals involving gabapentin included: drug abuser, multiple drug overdose, and substance-induced psychotic disorder. Significant drug AR-AE signals involving gabapentin and pregabalin, but not duloxetine, were: ataxia, dependence, drug abuse, increased drug tolerance, and overdose. Compared to duloxetine, gabapentin had significantly greater odds of a coreport for an AS-AE with drug withdrawal syndrome (OR: 6.55), auditory hallucinations (OR: 4.57), delusions (OR: 2.36), euphoric mood (OR: 5.45), ataxia (OR: 2.85), drug abuser (OR: 3.01), aggression (OR: L98), psychotic disorder (OR: 1.96), and feeling abnormal (OR: 1.31).Conclusions: We identified abuse-related signals for gabapentin and highlighted several CNS effects that may be associated with its abuse. Gabapentin prescribers should be aware of the drug\u27s abuse liability and effects that may accompany its use

Impact of Individual Acute Phase Serum Amyloid A Isoforms on HDL Metabolism in Mice

The acute phase (AP) reactant serum amyloid A (SAA), an HDL apolipoprotein, exhibits pro-inflammatory activities, but its physiological function(s) are poorly understood. Functional differences between SAA1.1 and SAA2.1, the two major SAA isoforms, are unclear. Mice deficient in either isoform were used to investigate plasma isoform effects on HDL structure, composition, and apolipoprotein catabolism. Lack of either isoform did not affect the size of HDL, normally enlarged in the AP, and did not significantly change HDL composition. Plasma clearance rates of HDL apolipoproteins were determined using native HDL particles. The fractional clearance rates (FCRs) of apoA-I, apoA-II, and SAA were distinct, indicating that HDL is not cleared as intact particles. The FCRs of SAA1.1 and SAA2.1 in AP mice were similar, suggesting that the selective deposition of SAA1.1 in amyloid plaques is not associated with a difference in the rates of plasma clearance of the isoforms. Although the clearance rate of SAA was reduced in the absence of the HDL receptor, scavenger receptor class B type I (SR-BI), it remained significantly faster compared with that of apoA-I and apoA-II, indicating a relatively minor role of SR-BI in SAA’s rapid clearance. These studies enhance our understanding of SAA metabolism and SAA’s effects on AP-HDL composition and catabolism

Increasing Adipocyte Lipoprotein Lipase Improves Glucose Metabolism in High Fat Diet-Induced Obesity

Lipid accumulation in liver and skeletal muscle contributes to co-morbidities associated with diabetes and obesity. We made a transgenic mouse in which the adiponectin (Adipoq) promoter drives expression of lipoprotein lipase (LPL) in adipocytes to potentially increase adipose tissue lipid storage. These mice (Adipoq-LPL) have improved glucose and insulin tolerance as well as increased energy expenditure when challenged with a high fat diet (HFD). To identify the mechanism(s) involved, we determined whether the Adipoq-LPL mice diverted dietary lipid to adipose tissue to reduce peripheral lipotoxicity, but we found no evidence for this. Instead, characterization of the adipose tissue of the male mice after HFD challenge revealed that the mRNA levels of peroxisome proliferator-activated receptor-γ (PPARγ) and a number of PPARγ-regulated genes were higher in the epididymal fat pads of Adipoq-LPL mice than control mice. This included adiponectin, whose mRNA levels were increased, leading to increased adiponectin serum levels in the Adipoq-LPL mice. In many respects, the adipose phenotype of these animals resembles thiazolidinedione treatment except for one important difference, the Adipoq-LPL mice did not gain more fat mass on HFD than control mice and did not have increased expression of genes in adipose such as glycerol kinase, which are induced by high affinity PPAR agonists. Rather, there was selective induction of PPARγ-regulated genes such as adiponectin in the adipose of the Adipoq-LPL mice, suggesting that increasing adipose tissue LPL improves glucose metabolism in diet-induced obesity by improving the adipose tissue phenotype. Adipoq-LPL mice also have increased energy expenditure

Thinking outside the curve, part I: modeling birthweight distribution

<p>Abstract</p> <p>Background</p> <p>Greater epidemiologic understanding of the relationships among fetal-infant mortality and its prognostic factors, including birthweight, could have vast public health implications. A key step toward that understanding is a realistic and tractable framework for analyzing birthweight distributions and fetal-infant mortality. The present paper is the first of a two-part series that introduces such a framework.</p> <p>Methods</p> <p>We propose describing a birthweight distribution via a normal mixture model in which the number of components is determined from the data using a model selection criterion rather than fixed <it>a priori</it>.</p> <p>Results</p> <p>We address a number of methodological issues, including how the number of components selected depends on the sample size, how the choice of model selection criterion influences the results, and how estimates of mixture model parameters based on multiple samples from the same population can be combined to produce confidence intervals. As an illustration, we find that a 4-component normal mixture model reasonably describes the birthweight distribution for a population of white singleton infants born to heavily smoking mothers. We also compare this 4-component normal mixture model to two competitors from the existing literature: a contaminated normal model and a 2-component normal mixture model. In a second illustration, we discover that a 6-component normal mixture model may be more appropriate than a 4-component normal mixture model for a general population of black singletons.</p> <p>Conclusions</p> <p>The framework developed in this paper avoids assuming the existence of an interval of birthweights over which there are no compromised pregnancies and does not constrain birthweights within compromised pregnancies to be normally distributed. Thus, the present framework can reveal heterogeneity in birthweight that is undetectable via a contaminated normal model or a 2-component normal mixture model.</p

Determinants of Work Hours Among a Cohort of Male and Female Farmers 50 Years and Older in Kentucky and South Carolina (2002-2005)

The average age of United States farmers has been increasing for 20 years. The objective is to examine the factors associated with hours worked among farmers age 50 and older. A cohort of Kentucky and South Carolina farmers (n = 1394) over age 50 were surveyed annually during 2002-2005. Of those that reported any farm work, males worked 24 mean hours/week and females worked 14 mean hours/week. Greater satisfaction and more experience farming, increased acreage, and presence of animals significantly increased estimated hours farmed, whereas chronic health problems, although prevalent, had a minor role in determining work hours

A comparison of recent procedures in weibull mixture testing

Abstract. The paper considers recent approaches to testing homogeneity in a finite mixture model, the modified likelihood ratio test (MLRT) of Chen et al. (2001) and the D-tests of Charnigo and Sun (2004). They are adapted to Weibull mixtures with and without a Weibull-to-exponential transformation of the data. Critical quantiles are calculated by simulation. To cope with the dependency of quantiles on the unknown shape parameter, corrected D-statistics are introduced. The power of these tests is compared with that of the ADDS test by Mosler and Scheicher (2007)