Religion as a Cross-cultural Determinant of Depression in Elderly Europeans: Results from the EURODEP Collaboration

Background. The protective effects of religion against late life depression may depend on the broader sociocultural environment. This paper examines whether the prevailing religious climate is related to cross-cultural differences of depression in elderly Europeans. Methods. Two approaches were employed, using data from the EURODEP collaboration. First, associations were studied between church-attendance, religious denomination and depression at the syndrome level for six EURODEP study centres (five countries, N = 8398). Secondly, ecological associations were computed by multi-level analysis between national estimates of religious climate, derived from the European Value Survey and depressive symptoms, for the pooled dataset of 13 EURODEP study centres (11 countries, N = 17739). Results. In the first study, depression rates were lower among regular church-attenders, most prominently among Roman Catholics. In the second study, fewer depressive symptoms were found among the female elderly in countries, generally Roman Catholic, with high rates of regular church-attendance. Higher levels of depressive symptoms were found among the male elderly in Protestant countries. Conclusions. Religious practice is associated with less depression in elderly Europeans, both on the individual and the national level. Religious practice, especially when it is embedded within a traditional value-orientation, may facilitate coping with adversity in later life

An analysis of the growth of leaf area of oil palms in Indonesia

In two cultivar × density trials for oil palms (Elaeis guineensis) planted in Indonesia, single leaf area, number of green leaves per tree, leaf opening rate per year and rachis length of leaves were followed over fourteen years. The data were analysed to determine the time course of canopy leaf area and to predict the moment of canopy closure. Growth functions were fitted to the observed data. Estimates of leaf area index (L) were based on single leaf area, number of green leaves, leaf opening and planting density. The time course of L was modelled on the basis of the fitted functions to the components. The moment of canopy closure was calculated from the planting density and the functions fitted for rachis length. The modelled time course of L was considerably different from the function fitted to the single leaf area data. The expansion of L was not as rapid as expected from the area growth of single leaves and, after maximum L was reached, a steady decline was observed. The continuously declining number of green leaves was the main cause of these two observations. The time course of L differed considerably between the two experiments. Not only were there large differences in the number of green leaves maintained per tree in the experiments but also the final area of single leaves differed between both experiments. The first factor was a result of the management of the experiments, whereas the second factor was most likely influenced by a difference in soil-related factors at the two locations. Leaf areas and numbers of leaves per tree were different for each cultivar, as was L. This was also the parameter most sensitive to planting density. Individual leaf area and leaf number per tree were not affected by planting density, but rachis length was affected by the planting density treatment. The moment of canopy closure was similar in both experiments. Planting density was the main factor that determined the onset of canopy closure

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Long-term exposure to low-level air pollution and incidence of chronic obstructive pulmonary disease: The ELAPSE project.

BACKGROUND: Air pollution has been suggested as a risk factor for chronic obstructive pulmonary disease (COPD), but evidence is sparse and inconsistent. OBJECTIVES: We examined the association between long-term exposure to low-level air pollution and COPD incidence. METHODS: Within the 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE) study, we pooled data from three cohorts, from Denmark and Sweden, with information on COPD hospital discharge diagnoses. Hybrid land use regression models were used to estimate annual mean concentrations of particulate matter with a diameter < 2.5 µm (PM2.5), nitrogen dioxide (NO2), and black carbon (BC) in 2010 at participants' baseline residential addresses, which were analysed in relation to COPD incidence using Cox proportional hazards models. RESULTS: Of 98,058 participants, 4,928 developed COPD during 16.6 years mean follow-up. The adjusted hazard ratios (HRs) and 95% confidence intervals for associations with COPD incidence were 1.17 (1.06, 1.29) per 5 µg/m3 for PM2.5, 1.11 (1.06, 1.16) per 10 µg/m3 for NO2, and 1.11 (1.06, 1.15) per 0.5 10-5m-1 for BC. Associations persisted in subset participants with PM2.5 or NO2 levels below current EU and US limit values and WHO guidelines, with no evidence for a threshold. HRs for NO2 and BC remained unchanged in two-pollutant models with PM2.5, whereas the HR for PM2.5 was attenuated to unity with NO2 or BC. CONCLUSIONS: Long-term exposure to low-level air pollution is associated with the development of COPD, even below current EU and US limit values and possibly WHO guidelines. Traffic-related pollutants NO2 and BC may be the most relevant

Shared genetic risk between eating disorder- and substance-use-related phenotypes:Evidence from genome-wide association studies

First published: 16 February 202

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles

Genome-wide association analyses identify 123 susceptibility loci for migraine and implicate neurovascular mechanisms in its pathophysiology. Subtype analyses highlight risk loci specific for migraine with or without aura in addition to shared risk variants.Migraine affects over a billion individuals worldwide but its genetic underpinning remains largely unknown. Here, we performed a genome-wide association study of 102,084 migraine cases and 771,257 controls and identified 123 loci, of which 86 are previously unknown. These loci provide an opportunity to evaluate shared and distinct genetic components in the two main migraine subtypes: migraine with aura and migraine without aura. Stratification of the risk loci using 29,679 cases with subtype information indicated three risk variants that seem specific for migraine with aura (in HMOX2, CACNA1A and MPPED2), two that seem specific for migraine without aura (near SPINK2 and near FECH) and nine that increase susceptibility for migraine regardless of subtype. The new risk loci include genes encoding recent migraine-specific drug targets, namely calcitonin gene-related peptide (CALCA/CALCB) and serotonin 1F receptor (HTR1F). Overall, genomic annotations among migraine-associated variants were enriched in both vascular and central nervous system tissue/cell types, supporting unequivocally that neurovascular mechanisms underlie migraine pathophysiology.Clinical epidemiolog

Rare variants with large effects provide functional insights into the pathology of migraine subtypes, with and without aura

Publisher Copyright: © 2023, The Author(s).Migraine is a complex neurovascular disease with a range of severity and symptoms, yet mostly studied as one phenotype in genome-wide association studies (GWAS). Here we combine large GWAS datasets from six European populations to study the main migraine subtypes, migraine with aura (MA) and migraine without aura (MO). We identified four new MA-associated variants (in PRRT2, PALMD, ABO and LRRK2) and classified 13 MO-associated variants. Rare variants with large effects highlight three genes. A rare frameshift variant in brain-expressed PRRT2 confers large risk of MA and epilepsy, but not MO. A burden test of rare loss-of-function variants in SCN11A, encoding a neuron-expressed sodium channel with a key role in pain sensation, shows strong protection against migraine. Finally, a rare variant with cis-regulatory effects on KCNK5 confers large protection against migraine and brain aneurysms. Our findings offer new insights with therapeutic potential into the complex biology of migraine and its subtypes.Peer reviewe