Quantifying the Role of Adverse Events in the Mortality Difference between First and Second-Generation Antipsychotics in Older Adults: Systematic Review and Meta-Synthesis

Background: Observational studies have reported higher mortality among older adults treated with first-generation antipsychotics (FGAs) versus second-generation antipsychotics (SGAs). A few studies examined risk for medical events, including stroke, ventricular arrhythmia, venous thromboembolism, myocardial infarction, pneumonia, and hip fracture. Objectives: 1) Review robust epidemiologic evidence comparing mortality and medical event risk between FGAs and SGAs in older adults; 2) Quantify how much these medical events explain the observed mortality difference between FGAs and SGAs. Data sources Pubmed and Science Citation Index. Study eligibility criteria, participants, and interventions Studies of antipsychotic users that: 1) evaluated mortality or medical events specified above; 2) restricted to populations with a mean age of 65 years or older 3) compared FGAs to SGAs, or both to a non-user group; (4) employed a “new user” design; (5) adjusted for confounders assessed prior to antipsychotic initiation; (6) and did not require survival after antipsychotic initiation. A separate search was performed for mortality estimates associated with the specified medical events. Study appraisal and synthesis methods For each medical event, we used a non-parametric model to estimate lower and upper bounds for the proportion of the mortality difference—comparing FGAs to SGAs—mediated by their difference in risk for the medical event. Results: We provide a brief, updated summary of the included studies and the biological plausibility of these mechanisms. Of the 1122 unique citations retrieved, we reviewed 20 observational cohort studies that reported 28 associations. We identified hip fracture, stroke, myocardial infarction, and ventricular arrhythmias as potential intermediaries on the causal pathway from antipsychotic type to death. However, these events did not appear to explain the entire mortality difference. Conclusions: The current literature suggests that hip fracture, stroke, myocardial infarction, and ventricular arrhythmias partially explain the mortality difference between SGAs and FGAs

A QTL genome scan of the metabolic syndrome and its component traits

BACKGROUND: Because high blood pressure, altered lipid levels, obesity, and diabetes so frequently occur together, they are sometimes collectively referred to as the metabolic syndrome. While there have been many studies of each metabolic syndrome trait separately, few studies have attempted to analyze them combined, i.e., as one composite variable, in quantitative trait linkage or association analysis. We used genotype and phenotype data from the Framingham Heart Study to perform a full-genome scan for quantitative trait loci underlying the metabolic syndrome. RESULTS: Heritability estimates for all of the covariate-adjusted and age- and gender-standardized individual traits, and the composite metabolic syndrome trait, were all fairly high (0.39–0.62), and the composite trait was among the highest at 0.61. The composite trait yielded no regions with suggestive linkage by Lander and Kruglyak's criteria, although there were several noteworthy regions for individual traits, some of which were also observed for the composite variable. CONCLUSION: Despite its high heritability, the composite metabolic syndrome trait variable did not increase the power to detect or localize linkage peaks in this sample. However, this strategy and related methods of combining correlated individual traits deserve further investigation, particularly in settings with complex causal pathways

Properties of permutation-based gene tests and controlling type 1 error using a summary statistic based gene test

Background: The advent of genome-wide association studies has led to many novel disease-SNP associations, opening the door to focused study on their biological underpinnings. Because of the importance of analyzing these associations, numerous statistical methods have been devoted to them. However, fewer methods have attempted to associate entire genes or genomic regions with outcomes, which is potentially more useful knowledge from a biological perspective and those methods currently implemented are often permutation-based. Results: One property of some permutation-based tests is that their power varies as a function of whether significant markers are in regions of linkage disequilibrium (LD) or not, which we show from a theoretical perspective. We therefore develop two methods for quantifying the degree of association between a genomic region and outcome, both of whose power does not vary as a function of LD structure. One method uses dimension reduction to “filter” redundant information when significant LD exists in the region, while the other, called the summary-statistic test, controls for LD by scaling marker Z-statistics using knowledge of the correlation matrix of markers. An advantage of this latter test is that it does not require the original data, but only their Z-statistics from univariate regressions and an estimate of the correlation structure of markers, and we show how to modify the test to protect the type 1 error rate when the correlation structure of markers is misspecified. We apply these methods to sequence data of oral cleft and compare our results to previously proposed gene tests, in particular permutation-based ones. We evaluate the versatility of the modification of the summary-statistic test since the specification of correlation structure between markers can be inaccurate. Conclusion: We find a significant association in the sequence data between the 8q24 region and oral cleft using our dimension reduction approach and a borderline significant association using the summary-statistic based approach. We also implement the summary-statistic test using Z-statistics from an already-published GWAS of Chronic Obstructive Pulmonary Disorder (COPD) and correlation structure obtained from HapMap. We experiment with the modification of this test because the correlation structure is assumed imperfectly known

The Relation of Patient Dependence to Home Health Aide Use in Alzheimer's Disease

BACKGROUND: Although there has been much research devoted to understanding the predictors of nursing home placement (NHP) in Alzheimer's disease (AD) patients, there is currently a lack of research concerning the predictors of home health care. The objective of this study was to examine whether the Dependence Scale can predict home health aide (HHA) use. METHODS: The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers in the United States. Markov analyses (n=75) were used to calculate annual transition probabilities for the "new onset" of HHA use (instances where an HHA was absent at the previous visit, but present at the next visit) as a function of HHA presence at the preceding year's visit and dependence level at that preceding year's visit. RESULTS: The dependence level at the previous year's visit was a significant predictor of HHA use at the next year's visit. Three specific items of the Dependence Scale (needing household chores done for oneself, needing to be watched or kept company when awake, and needing to be escorted when outside) were significant predictors of the presence of an HHA. CONCLUSION: The Dependence Scale is a valuable tool for predicting HHA use in AD patients. Obtaining a better understanding of home health care in AD patients may help delay NHP and have a positive impact on the health and well-being of both the caregiver and the patient

Change in Body Mass Index before and after Alzheimer's Disease Onset

OBJECTIVES: A high body mass index (BMI) in middle-age or a decrease in BMI at late-age has been considered a predictor for the development of Alzheimer's disease (AD). However, little is known about the BMI change close to or after AD onset. METHODS: BMI of participants from three cohorts, the Washington Heights and Inwood Columbia Aging Project (WHICAP; population-based) and the Predictors Study (clinic-based), and National Alzheimer's Coordinating Center (NACC; clinic-based) were analyzed longitudinally. We used generalized estimating equations to test whether there were significant changes of BMI over time, adjusting for age, sex, education, race, and research center. Stratification analyses were run to determine whether BMI changes depended on baseline BMI status. RESULTS: BMI declined over time up to AD clinical onset, with an annual decrease of 0.21 (p=0.02) in WHICAP and 0.18 (p=0.04) kg/m2 in NACC. After clinical onset of AD, there was no significant decrease of BMI. BMI even increased (b=0.11, p=0.004) among prevalent AD participants in NACC. During the prodromal period, BMI decreased over time in overweight (BMI>/=25 and /=30) NACC participants. After AD onset, BMI tended to increase in underweight/normal weight (BMI<25) patients and decrease in obese patients in all three cohorts, although the results were significant in NACC study only. CONCLUSIONS: Our study suggests that while BMI declines before the clinical AD onset, it levels off after clinical AD onset, and might even increase in prevalent AD. The pattern of BMI change may also depend on the initial BMI

Enkephalinase: Selective inhibitors and partial characterization

There are at least two types of enzymes in brain, endopeptidases and aminopeptidases, which metabolize enkephalins. Evidence is presented to suggest that enkephalinase, an endopeptidase cleaving at the Gly-Phe bond, is specific for the endogenous enkephalinergic system. Selective inhibitors are described for each enzyme. These are parachloromercuriphenylsulfonic acid and puromycin in the case of aminopeptidases and various enkephalin fragments in the case of enkephalinase. Some characteristics of the two types of enzymes are described. Enkephalinase has many properties in common with the well-characterized brain angiotensin-converting enzyme. These two enzymes, however, behaved differently when tested for chloride dependance, for activity in several buffers and for susceptibility to specific inhibitors.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23269/1/0000206.pd

Clinical Characteristics and Longitudinal Changes of Informal Cost of Alzheimer's Disease in the Community

Most estimates of the cost of informal caregiving in patients with Alzheimer's disease (AD) remain cross-sectional. Longitudinal estimates of informal caregiving hours and costs are less frequent and are from assessments covering only short periods of time. The objectives of this study were to estimate long-term trajectories of the use and cost of informal caregiving for patients with AD and the effects of patient characteristics on the use and cost of informal caregiving. The sample is drawn from the Predictors Study, a large, multicenter cohort of patients with probable AD, prospectively followed annually for up to 7 years in three university-based AD centers in the United States (n=170). Generalized linear mixed models were used to estimate the effects of patient characteristics on use and cost of informal caregiving. Patients' clinical characteristics included cognitive status (Mini-Mental State Examination), functional capacity (Blessed Dementia Rating Scale (BDRS)), comorbidities, psychotic symptoms, behavioral problems, depressive symptoms, and extrapyramidal signs. Results show that rates of informal care use and caregiving hours (and costs) increased substantially over time but were related differently to patients' characteristics. Use of informal care was significantly associated with worse cognition, worse function, and higher comorbidities. Conditional on receiving informal care, informal caregiving hours (and costs) were mainly associated with worse function. Each additional point on the BDRS increased informal caregiving costs 5.4%. Average annual informal cost was estimated at $25,381 per patient, increasing from$20,589 at baseline to $43,030 in Year 4