The role of ageing in the wish to be dead: disentangling age, period and cohort effects in suicide ideation in European population.

AIMS: To investigate potential age, period and birth cohort effects in the prevalence of suicide ideation in European ageing population. METHODS: A total of 50 782 community-dwelling adults (aged + 50) from 20 different European countries were collected in the Survey Health Ageing and Retirement study. A multilevel logistic regression model of repeated measures was modelled to assess the effects of age and other variables, including the variability of observations over three levels: birth cohort groups, time period assessment and individual differences. RESULTS: The larger effect of variability was attributed to individual-level factors (57.8%). Youngest-old people (65-79 years) showed lower suicide ideation than middle-aged people (50-64 years). No significative differences were found for suicide ideation between middle-aged people and oldest-old (80 + years). Only 0.85% and 0.13% of the total variability of suicide ideation accounted for birth cohort and period effects, respectively. Cohorts born between 1941 and 1944 possessed the lowest estimates of suicide ideation. Conversely, suicide ideation started to rise with post-War generations and reached a significant level for people born from 1953-1957 to 1961-1964. Regarding the time period, participants assessed in 2006-2007 showed a lower likelihood of suicide ideation. The rest of the cohorts and period groups did not show any significant effect on the prevalence of suicide ideation. CONCLUSIONS: Our results suggest that age and suicide ideation relationship is not linear in middle and older age. The European Baby boomers born from 50s to mid-60s might report higher suicide ideation than their ancestors. This scenario would imply a greater need for mental healthcare services for older people in the future.

Pharmacometabolomics applied to zonisamide pharmacokinetic parameter prediction.

INTRODUCTION: Zonisamide is a new-generation anticonvulsant antiepileptic drug metabolized primarily in the liver, with subsequent elimination via the renal route. OBJECTIVES: Our objective was to evaluate the utility of pharmacometabolomics in the detection of zonisamide metabolites that could be related to its disposition and therefore, to its efficacy and toxicity. METHODS: This study was nested to a bioequivalence clinical trial with 28 healthy volunteers. Each participant received a single dose of zonisamide on two separate occasions (period 1 and period 2), with a washout period between them. Blood samples of zonisamide were obtained from all patients at baseline for each period, before volunteers were administered any medication, for metabolomics analysis. RESULTS: After a Lasso regression was applied, age, height, branched-chain amino acids, steroids, triacylglycerols, diacyl glycerophosphoethanolamine, glycerophospholipids susceptible to methylation, phosphatidylcholines with 20:4 FA (arachidonic acid) and cholesterol ester and lysophosphatidylcholine were obtained in both periods. CONCLUSION: To our knowledge, this is the only research study to date that has attempted to link basal metabolomic status with pharmacokinetic parameters of zonisamide.

Correction to: Pharmacometabolomics applied to zonisamide pharmacokinetic parameter prediction.

The original version of this article contains a mistake.

Partition of the genetic trend to validate multiple selection decisions.

In this note, a procedure to partition the genetic trend of a selected population is presented. Each part of the genetic gain accounts for the Mendelian sampling terms of different groups of animals, which can be sometimes assigned to different selection policies. The method is based on a simple transformation of the predicted breeding values. The procedure was illustrated with two simulated examples. In the first example, the genetic trend is partitioned into two pieces, one coming from the selection on sires and the other coming from the selection on dams. The second example shows how the impact of an artificial insemination center in the genetic gain of the whole population can be evaluated.