175 research outputs found

    The impact of education, country, race and ethnicity on the self-report of postpartum depression using the Edinburgh Postnatal Depression Scale

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    Universal screening for postpartum depression is recommended in many countries. Knowledge of whether the disclosure of depressive symptoms in the postpartum period differs across cultures could improve detection and provide new insights into the pathogenesis. Moreover, it is a necessary step to evaluate the universal use of screening instruments in research and clinical practice. In the current study we sought to assess whether the Edinburgh Postnatal Depression Scale (EPDS), the most widely used screening tool for postpartum depression, measures the same underlying construct across cultural groups in a large international dataset. Ordinal regression and measurement invariance were used to explore the association between culture, operationalized as education, ethnicity/race and continent, and endorsement of depressive symptoms using the EPDS on 8209 new mothers from Europe and the USA. Education, but not ethnicity/race, influenced the reporting of postpartum depression [difference between robust comparative fit indexes (∆*CFI) 0.01), but not between European countries (∆*CFI < 0.01). Investigators and clinicians should be aware of the potential differences in expression of phenotype of postpartum depression that women of different educational backgrounds may manifest. The increasing cultural heterogeneity of societies together with the tendency towards globalization requires a culturally sensitive approach to patients, research and policies, that takes into account, beyond rhetoric, the context of a person's experiences and the context in which the research is conducted

    Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

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    OBJECTIVE-Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels.RESEARCH DESIGN AND METHODS-We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.RESULTS-Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 x 10(-26)), HFE (rs1800562/P = 2.6 x 10(-20)), TMPRSS6 (rs855791/P = 2.7 x 10(-14)), ANK1 (rs4737009/P = 6.1 x 10(-12)), SPTA1 (rs2779116/P = 2.8 x 10(-9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 x 10(-9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 x 10(-54)), MTNR1B (rs1387153/P = 4.0 X 10(-11)), GCK (rs1799884/P = 1.5 x 10(-20)) and G6PC2/ABCB11 (rs552976/P = 8.2 x 10(-18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (%HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify similar to 2% of a general white population screened for diabetes with HbA(1c).CONCLUSIONS-GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c) Diabetes 59: 3229-3239, 201

    Long-term air pollution exposure and Parkinson's disease mortality in a large pooled European cohort: An ELAPSE study

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    BACKGROUND: The link between exposure to ambient air pollution and mortality from cardiorespiratory diseases is well established, while evidence on neurodegenerative disorders including Parkinson's Disease (PD) remains limited. OBJECTIVE: We examined the association between long-term exposure to ambient air pollution and PD mortality in seven European cohorts. METHODS: Within the project 'Effects of Low-Level Air Pollution: A Study in Europe' (ELAPSE), we pooled data from seven cohorts among six European countries. Annual mean residential concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2), black carbon (BC), and ozone (O3), as well as 8 PM2.5 components (copper, iron, potassium, nickel, sulphur, silicon, vanadium, zinc), for 2010 were estimated using Europe-wide hybrid land use regression models. PD mortality was defined as underlying cause of death being either PD, secondary Parkinsonism, or dementia in PD. We applied Cox proportional hazard models to investigate the associations between air pollution and PD mortality, adjusting for potential confounders. RESULTS: Of 271,720 cohort participants, 381 died from PD during 19.7 years of follow-up. In single-pollutant analyses, we observed positive associations between PD mortality and PM2.5 (hazard ratio per 5 µg/m3: 1.25; 95% confidence interval: 1.01-1.55), NO2 (1.13; 0.95-1.34 per 10 µg/m3), and BC (1.12; 0.94-1.34 per 0.5 × 10-5m-1), and a negative association with O3 (0.74; 0.58-0.94 per 10 µg/m3). Associations of PM2.5, NO2, and BC with PD mortality were linear without apparent lower thresholds. In two-pollutant models, associations with PM2.5 remained robust when adjusted for NO2 (1.24; 0.95-1.62) or BC (1.28; 0.96-1.71), whereas associations with NO2 or BC attenuated to null. O3 associations remained negative, but no longer statistically significant in models with PM2.5. We detected suggestive positive associations with the potassium component of PM2.5. CONCLUSION: Long-term exposure to PM2.5, at levels well below current EU air pollution limit values, may contribute to PD mortality

    Resource profile and user guide of the Polygenic Index Repository

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    Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is growing rapidly. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs’ prediction accuracies, we constructed them using genome-wide association studies — some not previously published — from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the ‘additive SNP factor’. Regressions in which the true regressor is this factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available

    Associations between birth size and later height from infancy through adulthood: An individual based pooled analysis of 28 twin cohorts participating in the CODATwins project.

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    BACKGROUND: There is evidence that birth size is positively associated with height in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. AIM: To analyze the associations of birth weight, length and ponderal index with height from infancy through adulthood within mono- and dizygotic twin pairs, which provides insights into the role of genetic and environmental individual-specific factors. METHODS: This study is based on the data from 28 twin cohorts in 17 countries. The pooled data included 41,852 complete twin pairs (55% monozygotic and 45% same-sex dizygotic) with information on birth weight and a total of 112,409 paired height measurements at ages ranging from 1 to 69 years. Birth length was available for 19,881 complete twin pairs, with a total of 72,692 paired height measurements. The association between birth size and later height was analyzed at both the individual and within-pair level by linear regression analyses. RESULTS: Within twin pairs, regression coefficients showed that a 1-kg increase in birth weight and a 1-cm increase in birth length were associated with 1.14-4.25 cm and 0.18-0.90 cm taller height, respectively. The magnitude of the associations was generally greater within dizygotic than within monozygotic twin pairs, and this difference between zygosities was more pronounced for birth length. CONCLUSION: Both genetic and individual-specific environmental factors play a role in the association between birth size and later height from infancy to adulthood, with a larger role for genetics in the association with birth length than with birth weight

    Genetic and environmental variation in educational attainment: an individual-based analysis of 28 twin cohorts

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    We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural-geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a2 = 0.43; 0.41-0.44), but also environmental variation shared by co-twins was substantial (c2 = 0.31; 0.30-0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900-1949 (a2 = 0.44; 0.41-0.46) than in the later cohorts born in 1950-1989 (a2 = 0.38; 0.36-0.40), with a corresponding lower influence of common environmental factors (c2 = 0.31; 0.29-0.33 and c2 = 0.34; 0.32-0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s

    Education in Twins and Their Parents Across Birth Cohorts Over 100 years: An Individual-Level Pooled Analysis of 42-Twin Cohorts.

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    Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990-1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected
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