A putative causal relationship between genetically determined female body shape and posttraumatic stress disorder.
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ABSTRACT:
SUBMITTER: Polimanti R
PROVIDER: S-EPMC5702961 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundTelomere maintenance is increasingly recognized as being fundamental to glioma oncogenesis with longer leukocyte telomere length (LTL) reported to increase risk of glioma. To gain further insight into the relationship between telomere genetics and risk of glioma, we conducted several complementary analyses, using genome-wide association studies data on LTL (78 592 individuals) and glioma (12 488 cases and 18 169 controls).MethodsWe performed both classical and summary Mendelian randomization (SMR), coupled with heterogeneity in dependent instruments tests, at genome-wide significant LTL loci to examine if an association was mediated by the same causal variant in glioma. To prioritize genes underscoring glioma-LTL associations, we analyzed gene expression and DNA methylation data.ResultsGenetically increased LTL was significantly associated with increased glioma risk, random-effects inverse variance weighted ORs per 1 SD unit increase in the putative risk factor (odds ratio [OR]SD) 4.79 (95% confidence interval: 2.11-10.85; P = 1.76 × 10-4). SMR confirmed the previously reported LTL associations at 3q26.2 (TERC; PSMR = 1.33 × 10-5), 5p15.33 (TERT; PSMR = 9.80 × 10-27), 10q24.33 (STN1 alias OBFC1; PSMR = 4.31 × 10-5), and 20q13.3 (STMN3/RTEL1; PSMR = 2.47 × 10-4) glioma risk loci. Our analysis implicates variation at 1q42.12 (PSMR = 1.55 × 10-2), 6p21.3 (PSMR = 9.76 × 10-3), 6p22.2 (PSMR = 5.45 × 10-3), 7q31.33 (PSMR = 6.52 × 10-3), and 11q22.3 (PSMR = 8.89 × 10-4) as risk factors for glioma risk. While complicated by patterns of linkage disequilibrium, genetic variation involving PARP1, PRRC2A, CARMIL1, POT1, and ATM-NPAT1 was implicated in the etiology of glioma.ConclusionsThese observations extend the role of telomere-related genes in the development of glioma.
| S-EPMC8804896 | biostudies-literature
Project description:The association between physical appearance and income has been of central interest in social science. However, most previous studies often measured physical appearance using classical proxies from subjective opinions based on surveys. In this study, we use novel data, called CAESAR, which contains three-dimensional (3D) whole-body scans to mitigate possible reporting and measurement errors. We demonstrate the existence of significant nonclassical reporting errors in the reported heights and weights by comparing them with measured counterparts, and show that these discrete measurements are too sparse to provide a complete description of the body shape. Instead, we use a graphical autoencoder to obtain intrinsic features, consisting of human body shapes directly from 3D scans and estimate the relationship between body shapes and family income. We also take into account a possible issue of endogenous body shapes using proxy variables and control functions. The estimation results reveal a statistically significant relationship between physical appearance and family income and that these associations differ across genders. This supports the hypothesis on the physical attractiveness premium in labor market outcomes and its heterogeneity across genders.
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Project description:ObjectiveTo analyze the interactions between maternal gestational diabetes mellitus (GDM) and genetically determined maternal body mass index (BMI) during pregnancy on offspring childhood obesity.Research design and methodsA total of 1114 Chinese mother-child pairs (560 GDM and 554 non-GDM) were included between August 2009 and July 2011. Maternal genetic risk score (GRS) of BMI during pregnancy was derived on the basis of 12 single nucleotide polymorphisms identified from a genome-wide association study. Offspring's BMI, BMI-for-age z score, weight, weight-for-age z score, waist circumference, sum of skinfolds, and body fat percentage during childhood were measured or calculated.ResultsMaternal GRS of BMI during pregnancy significantly interacted with maternal GDM status on childhood risks of overweight and obesity (all P for interaction <.05). After multivariable adjustment, per unit of GRS was associated with a 24% (P<.001) and a 28% (P<.001) increased risk of overweight and obesity among children of GDM mothers, whereas no significant associations were observed among children of mothers without GDM. In addition, per unit GRS of BMI during pregnancy was significantly associated with 0.16 kg/m2 higher BMI (P=.002), 0.09 higher BMI-for-age z score (P=.002), 0.24 kg higher weight (P=.04), 0.06 higher weight-for-age z score (P=.02), 0.28 cm higher waist circumference (P=.03), 0.94 mm higher sum of skinfolds (P=.004), and 0.37% higher body fat percentage (P=.03) among children of GDM mothers. There were no significant associations between maternal GRS of BMI during pregnancy and offspring's obesity-related outcomes among children of mothers without GDM.ConclusionOur findings for the first time indicate that maternal GDM status may modify the relation between genetically determined maternal BMI during pregnancy and offspring's obesity risk during childhood.
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Project description:Intelligence predicts important life and health outcomes, but the biological mechanisms underlying differences in intelligence are not yet understood. The use of genetically determined metabotypes (GDMs) to understand the role of genetic and environmental factors, and their interactions, in human complex traits has been recently proposed. However, this strategy has not been applied to human intelligence. Here we implemented a two-sample Mendelian randomization (MR) analysis using GDMs to assess the causal relationships between genetically determined metabolites and human intelligence. The standard inverse-variance weighted (IVW) method was used for the primary MR analysis and three additional MR methods (MR-Egger, weighted median, and MR-PRESSO) were used for sensitivity analyses. Using 25 genetic variants as instrumental variables (IVs), our study found that 5-oxoproline was associated with better performance in human intelligence tests (PIVW?=?9.25?×?10-5). The causal relationship was robust when sensitivity analyses were applied (PMR-Egger?=?0.0001, PWeighted median?=?6.29?×?10-6, PMR-PRESSO?=?0.0007), and repeated analysis yielded consistent result (PIVW?=?0.0087). Similarly, also dihomo-linoleate (20:2n6) and p-acetamidophenylglucuronide showed robust association with intelligence. Our study provides novel insight by integrating genomics and metabolomics to estimate causal effects of genetically determined metabolites on human intelligence, which help to understanding of the biological mechanisms related to human intelligence.
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Project description:BackgroundThe amygdala is a subcortical structure involved in socioemotional and associative fear learning processes relevant for understanding the mechanisms of posttraumatic stress disorder (PTSD). Research in animals indicates that the amygdala is a heterogeneous structure in which the basolateral and centromedial divisions are susceptible to stress. While the amygdala complex is implicated in the pathophysiology of PTSD, little is known about the specific contributions of the individual nuclei that constitute the amygdala complex.MethodsMilitary veterans (n = 355), including military veterans with PTSD (n = 149) and trauma-exposed control subjects without PTSD (n = 206), underwent high-resolution T1-weighted anatomical scans. Automated FreeSurfer segmentation of the amygdala yielded 9 structures: basal, lateral, accessory basal, anterior amygdaloid, and central, medial, cortical, and paralaminar nuclei, along with the corticoamygdaloid transition zone. Subregional volumes were compared between groups using ordinary-least-squares regression with relevant demographic and clinical regressors followed by 3-dimensional shape analysis of whole amygdala.ResultsPTSD was associated with smaller left and right lateral and paralaminar nuclei, but with larger left and right central, medial, and cortical nuclei (p < .05, false discovery rate corrected). Shape analyses revealed lower radial distance in anterior bilateral amygdala and lower Jacobian determinant in posterior bilateral amygdala in PTSD compared with control subjects.ConclusionsAlterations in select amygdala subnuclear volumes and regional shape distortions are associated with PTSD in military veterans. Volume differences of the lateral nucleus and the centromedial complex associated with PTSD demonstrate a subregion-specific pattern that is consistent with their functional roles in fear learning and fear expression behaviors.
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Project description:OBJECTIVE:HDL (high-density lipoprotein) cholesterol (HDL-C) and LDL (low-density lipoprotein) cholesterol (LDL-C) are inversely associated with infectious hospitalizations. Whether these represent causal relationships is unknown. Approach and Results: Adults of 40 to 69 years of age were recruited from across the United Kingdom between 2006 and 2010 and followed until March 31, 2016, as part of the UK Biobank. We determined HDL-C, LDL-C, and triglyceride polygenic scores for UK Biobank participants of British white ancestry (n=407?558). We examined the association of lipid levels and polygenic scores with infectious hospitalizations, antibiotic usage, and 28-day sepsis survival using Cox proportional hazards or logistic regression models. Measured levels of HDL-C and LDL-C were inversely associated with risk of infectious hospitalizations, while triglycerides displayed a positive association. A 1-mmol/L increase in genetically determined levels of HDL-C associated with a hazard ratio for infectious disease of 0.84 ([95% CI, 0.75-0.95]; P=0.004). Mendelian randomization using genetic variants associated with HDL-C as an instrumental variable was consistent with a causal relationship between elevated HDL-C and reduced risk of infectious hospitalizations (inverse weighted variance method, P=0.001). Furthermore, of 3222 participants who experienced an index episode of sepsis, there was a significant inverse association between continuous HDL-C polygenic score and 28-day mortality (adjusted hazard ratio, 0.37 [95% CI, 0.14-0.96] per 1 mmol/L increase; P=0.04). LDL-C and triglyceride polygenic scores were not significantly associated with hospitalization for infection, antibiotic use, or sepsis mortality. CONCLUSIONS:Our results provide causal inference for an inverse relationship between HDL-C, but not LDL-C or triglycerides, and risk of an infectious hospitalization.
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Project description:Background: Polycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder that is influenced by both genetic and environmental factors. However, the etiology of PCOS remains unclear. Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effects of genetically determined metabolites (GDMs) on the risk of PCOS. We used summary level data of a genome-wide association study (GWAS) on 486 metabolites (n = 7,824) as exposure and a PCOS GWAS consisting of 4,138 cases and 20,129 controls as the outcome. Both datasets were obtained from publicly published databases. For each metabolite, a genetic instrumental variable was generated to assess the relationship between the metabolite and PCOS. For MR analysis, we primarily used the standard inverse variance weighted (IVW) method, while three additional methods-the MR-Egger, weighted median, and MR-PRESSO (pleiotropy residual sum and outlier) methods-were performed as sensitivity analyses. Results: Using genetic variants as predictors, we observed a robust relationship between epiandrosterone sulfate (EPIA-S) and PCOS (P IVW = 0.0186, P MR-Egger = 0.0111; P Weighted-median = 0.0154, and P MR-PRESSO = 0.0290). Similarly, 3-dehydrocarnitine, 4-hydroxyhippurate, hexadecanedioate, and β-hydroxyisovalerate may also have causal effects on PCOS development. Conclusions: We identified metabolites that might have causal effects on PCOS development. Our study emphasizes the role of genetic factors underlying the causal relationships between metabolites and PCOS and provides novel insights through the integration of metabolomics and genomics to better understand the mechanisms involved in human disease pathogenesis.
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Project description:Posttraumatic stress disorder (PTSD) is associated with both aggressive and suicidal behavior. Recent research suggests that the diagnosis of intermittent explosive disorder (IED), an impulse-control disorder characterized by repeated impulsive aggressive behavior, may help to identify individuals at risk for attempting suicide. Given the relationship between anger and PTSD, there is likely to be an increased prevalence of IED among individuals with PTSD; however, little is known about the overlap in these two disorders, including how individuals with comorbid IED and PTSD may differ from those with either disorder alone. The purpose of this study is to examine the clinical correlates of comorbid IED and PTSD and the contribution of these two disorders (among others) to lifetime suicide attempt and characteristics of suicidal behavior.In a large sample of community research volunteers (N=1460), we compared individuals with PTSD, IED, and comorbid PTSD and IED on measures of current mood, trait aggression, and trait impulsivity. We also examined the contributions of PTSD, IED, and other syndromal and personality disorders to the prediction of lifetime aggression and lifetime suicide attempt, and their relationship to characteristics of suicide attempts, including level of intent, use of violent versus non-violent means, and the medical seriousness of the attempt.Comorbid PTSD and IED was associated with significantly elevated levels of depression, anxiety, anger, aggression, and impulsivity, as well as with high rates of comorbidity with other psychiatric disorders. IED (?=.56, p<.001), but not PTSD, significantly and uniquely predicted lifetime aggressive behavior. Both IED and PTSD were associated with lifetime suicide attempt in multivariate analysis (ORs: 1.6 and 1.6, ps<.05). The results show that IED, when comorbid with PTSD, identifies a subgroup of individuals with particularly high levels of aggressive behavior and a high rate of suicide attempt (41.4% in this sample).These findings add support to the notion that the diagnosis of IED may aid in identifying individuals at risk for aggressive and suicidal behavior.
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Project description:Cognitive models of post-traumatic stress disorder (PTSD) suggest maladaptive appraisals play a central role in the aetiology of this disorder. The current meta-analysis sought to provide a comprehensive, quantitative examination of the relationship between maladaptive appraisals and PTSD. One-hundred and 35 studies met study inclusion criteria and were subject to random effects meta-analysis. A large effect size was found for the relationship between appraisals and PTSD (r = 0.53, 95% CI = 0.51-0.56, k = 147), albeit with significant heterogeneity. In studies using only the Posttraumatic Cognitions Inventory or Child Post-traumatic Cognitions Inventory, the effect size remained large (r = 0.56; k = 104). In adults, appraisals about the self had a large effect size (r = 0.61), appraisals about the world had a medium effect size (r = 0.46) and self-blame appraisals had a small effect size (r = 0.28). In child/adolescent studies, large effect sizes were found for both 'fragile person in a scary world' and 'permanent and disturbing change' appraisals (r = 0.54 and r = 0.60, respectively). The effect size remained large in prospective longitudinal studies up to one year after trauma. There was no moderation effect for civilian vs military populations, questionnaire vs interview measures of PTSD, single vs multiple trauma exposure, or intentional vs unintentional trauma. The main effect size estimate was robust to sensitivity analyses concerning statistics used, study quality and outliers. These findings are consistent with the strong role for maladaptive appraisals in the aetiology of PTSD proposed by cognitive models. In particular, the role of self-appraisals in adults was highlighted. Avenues for future research include more studies in child, multiple trauma and military populations and longer-term follow up studies.
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Project description:Aspects of the female body may be attractive because they signal evolutionary fitness. Greater body fatness might reflect greater potential to survive famines, but individuals carrying larger fat stores may have poor health and lower fertility in non-famine conditions. A mathematical statistical model using epidemiological data linking fatness to fitness traits, predicted a peaked relationship between fatness and attractiveness (maximum at body mass index (BMI) = 22.8 to 24.8 depending on ethnicity and assumptions). Participants from three Caucasian populations (Austria, Lithuania and the UK), three Asian populations (China, Iran and Mauritius) and four African populations (Kenya, Morocco, Nigeria and Senegal) rated attractiveness of a series of female images varying in fatness (BMI) and waist to hip ratio (WHR). There was an inverse linear relationship between physical attractiveness and body fatness or BMI in all populations. Lower body fat was more attractive, down to at least BMI = 19. There was no peak in the relationship over the range we studied in any population. WHR was a significant independent but less important factor, which was more important (greater r (2)) in African populations. Predictions based on the fitness model were not supported. Raters appeared to use body fat percentage (BF%) and BMI as markers of age. The covariance of BF% and BMI with age indicates that the role of body fatness alone, as a marker of attractiveness, has been overestimated.
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