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BackgroundClarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.MethodsThe study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].ResultsTotal depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).ConclusionsA history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.

Because longitudinal studies of aging typically lack cognitive data from earlier ages, it is unclear how general cognitive ability (GCA) changes throughout the life course. In 1173 Vietnam Era Twin Study of Aging (VETSA) participants, we assessed young adult GCA at average age 20 and current GCA at 3 VETSA assessments beginning at average age 56. The same GCA index was used throughout. Higher young adult GCA and better GCA maintenance were associated with stronger specific cognitive abilities from age 51 to 73. Given equivalent GCA at age 56, individuals who had higher age 20 GCA outperformed those whose GCA remained stable in terms of memory, executive function, and working memory abilities from age 51 to 73. Thus, paradoxically, despite poorer maintenance of GCA, high young adult GCA still conferred benefits. Advanced predicted brain age and the combination of elevated vascular burden and APOE-ε4 status were associated with poorer maintenance of GCA. These findings highlight the importance of distinguishing between peak and current GCA for greater understanding of cognitive aging.

We examined the influence of lifestyle on brain aging after nearly 30 years, and tested the hypothesis that young adult general cognitive ability (GCA) would moderate these effects. In the community-dwelling Vietnam Era Twin Study of Aging (VETSA), 431 largely non-Hispanic white men completed a test of GCA at mean age 20. We created a modifiable lifestyle behavior composite from data collected at mean age 40. During VETSA, MRI-based measures at mean age 68 included predicted brain age difference (PBAD), Alzheimer's disease (AD) brain signature, and abnormal white matter scores. There were significant main effects of young adult GCA and lifestyle on PBAD and the AD signature (ps ≤ 0.012), and a GCA-by-lifestyle interaction on both (ps ≤ 0.006). Regardless of GCA level, having more favorable lifestyle behaviors predicted less advanced brain age and less AD-like brain aging. Unfavorable lifestyles predicted advanced brain aging in those with lower age 20 GCA, but did not affect brain aging in those with higher age 20 GCA. Targeting early lifestyle modification may promote dementia risk reduction, especially among lower reserve individuals.

Background and aims Smoking is associated with increased risk for brain aging/atrophy and dementia. Few studies have examined early associations with brain aging. This study aimed to measure whether adult men with a history of heavier smoking in early mid-life would have older than predicted brain age 16-28 years later. Design Prospective cohort observational study, utilizing smoking pack years data from average age 40 (early mid-life) predicting predicted brain age difference scores (PBAD) at average ages 56, 62 (later mid-life) and 68 years (early old age). Early mid-life alcohol use was also evaluated. Setting Population-based United States sample. Participants/cases Participants were male twins of predominantly European ancestry who served in the United States military between 1965 and 1975. Structural magnetic resonance imaging (MRI) began at average age 56. Subsequent study waves included most baseline participants; attrition replacement subjects were added at later waves. Measurements Self-reported smoking information was used to calculate pack years smoked at ages 40, 56, 62, and 68. MRIs were processed with the Brain-Age Regression Analysis and Computation Utility software (BARACUS) program to create PBAD scores (chronological age-predicted brain age) acquired at average ages 56 (n = 493; 2002-08), 62 (n = 408; 2009-14) and 68 (n = 499; 2016-19). Findings In structural equation modeling, age 40 pack years predicted more advanced age 56 PBAD [β = -0.144, P = 0.012, 95% confidence interval (CI) = -0.257, -0.032]. Age 40 pack years did not additionally predict PBAD at later ages. Age 40 alcohol consumption, but not a smoking × alcohol interaction, predicted more advanced PBAD at age 56 (β = -0.166, P = 0.001, 95% CI = -0.261, -0.070) with additional influences at age 62 (β = -0.115, P = 0.005, 95% CI = -0.195, -0.036). Age 40 alcohol did not predict age 68 PBAD. Within-twin-pair analyses suggested some genetic mechanism partially underlying effects of alcohol, but not smoking, on PBAD. Conclusions Heavier smoking and alcohol consumption by age 40 appears to predict advanced brain aging by age 56 in men.

The diversity and dominant bacterial taxa in the vagina are reported to be influenced by multiple intrinsic and extrinsic factors, including but not limited to pregnancy, contraceptive use, pathogenic states, socioeconomic status, and ancestry. However, the extent to which host genetic factors influence variation in the vaginal microbiota is unclear. We used a biometrical genetic approach to determine whether host genetic factors contribute to inter-individual differences in taxa from a sample of 332 twins who self-identified as being of African (44 pairs) or European ancestry (122 pairs). Lactobacillus crispatus, a major determinant of vaginal health, was identified as heritable among European American women (narrow-sense heritability = 34.7%, P-value = 0.018). Heritability of L. crispatus is consistent with the reduced prevalence of adverse reproductive disorders, including bacterial vaginosis and preterm birth, among women of European ancestry., Wright et al. apply biometric genetic approach to identify the extent to which host genetic factors influence species-level variation in the vaginal microbiota. Their study suggests that Lactobacillus crispatus, a major determinant of vaginal health, is heritable among European American women, consistent with the reduced prevalence of adverse reproductive disorders in them.

Introduction Using Swedish nationwide registry data, we investigated the contribution of genetic and environmental risk factors to the etiology of smoking status across stages of pregnancy with increasing degrees of social and psychological pressure to reduce or quit smoking, by twin and sibling modeling. Aims and Methods Smoking status was available before, and during early and late pregnancy from the Medical Birth Register. Twin, full-, and half-sibling pairs, both reared together and apart, born between 1960 and 1990 were obtained from national twin and genealogical registers. Genetic structural equation modeling in OpenMx was applied to the population-based data to estimate shared genetic and/or environmental covariance across stages of pregnancy, accounting for maternal birth cohort and age at pregnancy. Results Analyses of paired data on 258 749 individuals suggested that risk factors for smoking status changed across stages of pregnancy. Results predicted substantial heritability (60–70%) and moderate contributions of shared environmental factors (10–15%) for smoking status. Whilst the same shared environmental factors were amplified from before pregnancy to late pregnancy, new primarily unique environmental factors explained ~10% of the variance during early pregnancy which was carried forward to late pregnancy. Conclusions Using registry data on women across pregnancy, we replicated that smoking status is highly heritable. Furthermore, we found support for increased impact of shared environmental factors during pregnancy of factors already present prior to pregnancy, and an independent set of mostly new unique environmental factors that may be triggered by increased social pressure to reduce or quit smoking during pregnancy. Implications As new factors partially explain smoking status during pregnancy and the effects of familial factors increase across pregnancy, efforts to prevent or reduce smoking during pregnancy should receive continued attention, with a focus on both the individual and the family unit.

Magnetic resonance imaging data are being used in statistical models to predicted brain ageing (PBA) and as biomarkers for neurodegenerative diseases such as Alzheimers Disease. Despite their increasing application, the genetic and environmental etiology of global PBA indices is unknown. Likewise, the degree to which genetic influences in PBA are longitudinally stable and how PBA changes over time are also unknown. We analyzed data from 734 men from the Vietnam Era Twin Study of Aging with repeated MRI assessments between the ages 52 to 72 years. Biometrical genetic analyses twin models revealed significant and highly correlated estimates of additive genetic heritability ranging from 59% to 75%. Multivariate longitudinal modelling revealed that covariation between PBA at different timepoints could be explained by a single latent factor with 73% heritability. Our results suggest that genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and are largely explained by common genetic influences. HighlightsWe explored the genetic and environmental etiology of MRI-based predicted brain age (PBA) in a longitudinal sample of males starting in midlife. Genetic influences on PBA are detectable in midlife or earlier, are longitudinally very stable, and largely explained by common genetic influences.

Neuroimaging signatures based on composite scores of cortical thickness and hippocampal volume predict progression from mild cognitive impairment to Alzheimer’s disease. However, little is known about the ability of these signatures among cognitively normal adults to predict progression to mild cognitive impairment. Towards that end, a signature sensitive to microstructural changes that may predate macrostructural atrophy should be useful. We hypothesized that: (i) a validated MRI-derived Alzheimer’s disease signature based on cortical thickness and hippocampal volume in cognitively normal middle-aged adults would predict progression to mild cognitive impairment; and (ii) a novel grey matter mean diffusivity signature would be a better predictor than the thickness/volume signature. This cohort study was part of the Vietnam Era Twin Study of Aging. Concurrent analyses compared cognitively normal and mild cognitive impairment groups at each of three study waves (ns = 246–367). Predictive analyses included 169 cognitively normal men at baseline (age = 56.1, range = 51–60). Our previously published thickness/volume signature derived from independent data, a novel mean diffusivity signature using the same regions and weights as the thickness/volume signature, age, and an Alzheimer’s disease polygenic risk score were used to predict incident mild cognitive impairment an average of 12 years after baseline (follow-up age = 67.2, range = 61–71). Additional analyses adjusted for predicted brain age difference scores (chronological age minus predicted brain age) to determine if signatures were Alzheimer-related and not simply ageing-related. In concurrent analyses, individuals with mild cognitive impairment had higher (worse) mean diffusivity signature scores than cognitively normal participants, but thickness/volume signature scores did not differ between groups. In predictive analyses, age and polygenic risk score yielded an area under the curve of 0.74 (sensitivity = 80.00%; specificity = 65.10%). Prediction was significantly improved with addition of the mean diffusivity signature (area under the curve = 0.83; sensitivity = 85.00%; specificity = 77.85%; P = 0.007), but not with addition of the thickness/volume signature. A model including both signatures did not improve prediction over a model with only the mean diffusivity signature. Results held up after adjusting for predicted brain age difference scores. The novel mean diffusivity signature was limited by being yoked to the thickness/volume signature weightings. An independently derived mean diffusivity signature may thus provide even stronger prediction. The young age of the sample at baseline is particularly notable. Given that the brain signatures were examined when participants were only in their 50 s, our results suggest a promising step towards improving very early identification of Alzheimer’s disease risk and the potential value of mean diffusivity and/or multimodal brain signatures., Among cognitively normal adults in their 50 s, an Alzheimer’s brain signature based on grey matter mean diffusivity—but not cortical thickness—significantly improved prediction of progression to mild cognitive impairment 12 years later. Grey matter mean diffusivity signatures may be sensitive to Alzheimer-related changes as early as middle age., Graphical Abstract Graphical Abstract

ImportanceBoth cognitive reserve and modifiable lifestyle behaviors are associated with dementia risk. The effect of early lifestyle behaviors and cognitive reserve on late midlife brain aging could inform early identification and risk reduction of future dementia.ObjectiveDetermine associations of young adult cognitive reserve, early midlife lifestyle behaviors, and the reserve-by-lifestyle interaction on late midlife brain age. Examine the relationship between mild cognitive impairment (MCI) and brain age.DesignParticipants were from the nationally representative Vietnam Era Twin Study of Aging (VETSA). Cognitive reserve was assessed at median age 20 years (IQR=1.38) with the Armed Forces Qualification Test (AFQT). Lifestyle behaviors (smoking, alcohol consumption, and social engagement) were assessed at median age 41 (IQR=5.00). Structural brain imaging conducted at median age 69 (IQR=4.74) was used to construct predicted brain age difference scores (PBAD=chronological age minus predicted brain age) and MCI was ascertained.SettingIn-person cognitive testing (ages 20 and 69); mailed survey (age 41); structural MRI, MCI diagnosis at University of California, San Diego (age 69).Participants431 community-dwelling men.ExposuresAFQT; self-reported health and lifestyle behaviors.Main outcomes and measuresPBAD scores; MCI.ResultsIn fully adjusted mixed linear models, age 20 cognitive reserve and the age 41 lifestyle composite were associated with age 69 PBAD [t (104)=2.62, p=0.01, 95%CI 0.874, 6.285; t (104)=3.37, p=0.001, 95%CI 0.583, 2.249 respectively] as was the reserve-by-lifestyle interaction [t (104) = −2.29, p=0.02, 95%CI −2.330, −0.167]. Unfavorable lifestyle predicted more advanced brain age, but only for those with lower young adult cognitive reserve. The MCI group had more advanced brain age (F (2,130) = 3.13; p=0.05).Conclusions and relevanceFavorable lifestyle behaviors promoted resistance to accelerated brain aging 3 decades later for those with lower young adult cognitive reserve. High reserve appeared to be protective regardless of lifestyle. The association with MCI suggests that advanced PBAD scores reflect poorer brain integrity, although it is unclear if PBAD is related to Alzheimer’s dementia specifically. Lower cognitive reserve increases risk for dementia, but early lifestyle modification may promote healthier brain aging and dementia risk reduction, particularly in those with lower reserve.Study TypeCohort StudyKey PointsQuestionDo modifiable lifestyle behaviors in early midlife predict later accelerated brain aging and is that association moderated by cognitive reserve?FindingsA lifestyle composite of smoking, alcohol consumption and social engagement at age 41 was associated with estimated brain age in late midlife. There was a significant moderation effect whereby more unfavorable lifestyle behaviors predicted more advanced brain aging, but only in those with low-to-moderate cognitive reserve.MeaningFavorable lifestyle behaviors appear to be protective for brain integrity especially among those with lower cognitive reserve. Early midlife efforts at prevention could be prioritized among those with lower cognitive reserve.

Supplemental Digital Content is available in the text., Blood pressure (BP) and obesity phenotypes may covary due to shared genetic or environmental factors or both. Furthermore, it is possible that the heritability of BP differs according to obesity status—a form of G×E interaction. This hypothesis has never been tested in White twins. The present study included 15 924 White male twin pairs aged between 15 and 33 years from the National Academy of Sciences–National Research Council World War II Veteran Twin Registry. Systolic and diastolic BPs, as well as height and weight, were measured at the induction physical examination. Body mass index (BMI) was used as the index of general obesity. Quantitative genetic modeling was performed using Mx software. Univariate analysis showed that narrow sense heritabilities (95% CI) for systolic BP, diastolic BP, height, and BMI were 0.401 (0.381–0.420), 0.297 (0.280–0.320), 0.866 (0.836–0.897), and 0.639 (0.614–0.664), respectively. Positive phenotypic correlations of BMI with systolic BP (r=0.13) and diastolic BP (r=0.08) were largely due to genetic factors (70% and 86%, respectively). The gene-BMI interaction analysis did not show any support for a modifying effect of BMI on genetic and environmental influences of systolic BP and diastolic BP. Our results suggest that correlations between BP and BMI are mainly explained by common genes influencing both. Higher BMI levels have no influence on the penetrance of genetic vulnerability to elevated BP. These conclusions may prove valuable for gene-finding studies.

Nicotine dependence and smoking quantity are both robustly associated with the CHRNA5-A3-B4 gene cluster in the 15q25 region, and SNP rs16969968 in particular. The purpose of this paper is to use structural equation modeling techniques (SEM) to disentangle the complex pattern of relationships between rs16969968, nicotine quantity (as measured by the number of cigarettes an individual smokes per day; CPD) and nicotine dependence (as measured by the Fagerstrom Test for Nicotine Dependence; FTND). CPD is an indicator, but also a potential cause, of FTND, complicating the interpretation of associations between these constructs and requires a more detailed investigation than standard GWAS or general linear regression models can provide. FTND items and genotypes were collected in four samples, with a combined sample size of 5,373 respondents. A mega-analysis was conducted using a multiple group SEM approach to test competing hypotheses regarding the relationships between the SNP rs16969968, FTND and CPD. In the best fitting model, the FTND items loaded onto two correlated factors. The first, labeled "maintenance," assesses the motivation to maintain constant levels of nicotine through out the day. The second was labeled "urgency" as its items concern the urgency to restore nicotine levels after abstinence. We focus our attention on the "maintenance" factor, of which CPD was an indicator. The best fitting model included a negative feedback loop between the Maintenance factor and CPD. Accordingly, the motivation to maintain higher levels of nicotine increased the quantity of nicotine consumed, which subsequently decreases the maintenance motivation. The fact that the Maintenance-CPD feedback model fits the data best implies that there are at least two biological pathways that lead from rs16969968 to smoking behaviors. The model is consistent with a supply and demand system, which allows individuals to achieve a homeostatic equilibrium for their nicotine concentration.

Background Individuals with eating disorders (EDs) have increased rates of major depressive disorder (MDD) and anxiety disorders. Yet, few studies have investigated rates of EDs and their symptoms in individuals presenting with MDD/anxiety disorders. Identifying potential disordered eating in people with MDD/anxiety disorders is important because even subclinical disordered eating is associated with reduced quality of life, and undiagnosed eating pathology may hinder treatment progress for both MDD/anxiety disorders and comorbid EDs. Method We compared rates of EDs (anorexia nervosa, bulimia nervosa, binge-eating disorder, and other specified feeding and eating disorders) and their symptoms in 130 women with, and 405 women without, lifetime MDD or an anxiety disorder (generalized anxiety disorder, obsessive-compulsive disorder, social phobia, specific phobia, panic disorder, agoraphobia, or post-traumatic stress disorder) recruited from the population-based Michigan State University Twin Registry. Lifetime ED and MDD/anxiety diagnoses, and lifetime clinically significant disordered eating behaviors (e.g., binge eating, excessive exercise) were assessed using the Structured Clinical Interview for DSM-IV (SCID). Results Among participants with lifetime MDD or any anxiety disorder, 13% met criteria for a lifetime ED and 39% reported engaging in at least one lifetime clinically significant disordered eating behavior (e.g., binge eating) on the SCID. In contrast, only 3% of participants without a history of MDD/an anxiety disorder met criteria for a lifetime ED, and only 11% reported lifetime clinically significant disordered eating behavior. Discussion Our findings suggest that women with MDD and anxiety disorders have elevated rates of EDs, and it is therefore imperative to screen for disordered eating in these populations.

Background and aims Individual differences in DSM-IV personality disorders (PDs) are associated with increased prevalence of substance use disorders. Our aims were to determine which combination of PDs trait scores best predict cannabis use (CU) and cannabis use disorder (CUD), and to estimate the size and significance of genetic and environmental risks in PD traits shared with CU and CUD. Design Linear mixed-effects models were used to identify PD traits for inclusion in twin analyses to explore the genetic and environmental associations between the traits and cannabis use. Setting Cross-sectional data were obtained from Norwegian adult twins in a face-to-face interview in 1999-2004 as part of a population-based study of mental health. Participants Subjects were 1419 twins (μage = 28.2 years, range = 19-36) from the Norwegian Institute of Public Health Twin Panel with complete PD and cannabis data. Measurements PD traits were assessed using DSM-IV criteria. Life-time CU and CUD were based on DSM-IV abuse and dependence criteria, including withdrawal and craving. Findings After adjusting for age and sex, antisocial [β = 0.23, 95% confidence interval (CI) = 0.19-0.28] and borderline PDs (β = 0.20, 95% CI = 0.14-0.26) were associated strongly with CU. Antisocial (β = 0.26, 95% CI = 0.21-0.31) and borderline PDs (β = 0.12, 95% CI = 0.06-0.18) were also linked strongly to CUD. Genetic risks in antisocial and borderline PD traits explained 32-60% of the total variance in CU and CUD. Dependent and avoidant PDs explained 11 and 16% of the total variance in CU and CUD, respectively. Conclusions Individual differences in the liability to cannabis use and cannabis use disorder appear to be linked to genetic risks correlated with antisocial and borderline personality disorder traits.

Early identification of younger, non-demented adults at elevated risk for Alzheimer's disease (AD) is crucial because the pathological process begins decades before dementia onset. Toward that end, we showed that an AD polygenic risk score (PRS) could identify mild cognitive impairment (MCI) in adults who were only in their 50s. Participants were 1176 white, non-Hispanic community-dwelling men of European ancestry in the Vietnam Era Twin Study of Aging (VETSA): 7% with amnestic MCI (aMCI); 4% with non-amnestic MCI (naMCI). Mean age was 56 years, with 89%

Background A clearer understanding of the etiological overlap between DSM-IV personality disorders (PDs) and alcohol use (AU) and alcohol use disorder (AUD) is needed. To our knowledge, no study has modeled the association between all 10 DSM-IV PDs and lifetime AU and AUD. The aim of the present study is to identify which PDs are most strongly associated with the phenotypic, genetic, and environmental risks of lifetime AU and AUD, and to determine if these associations are stable across time. Methods Participants were Norwegian twins assessed at two waves. At Wave 1, 2801 twins were assessed for all 10 DSM-IV PD criteria, lifetime AU, and DSM-IV AUD criteria. At Wave 2, six of the 10 PDs were again assessed along with AU and AUD among 2393 twins. Univariate and multiple logistic regressions were run. Significant predictors were further analyzed using bivariate twin Cholesky decompositions. Results Borderline and antisocial PD criteria were the strongest predictors of AU and AUD across the two waves. Despite moderate phenotypic and genetic correlations, genetic variation in these PD criteria explained only 4% and 3% of the risks in AU, and 5% to 10% of the risks in AUD criteria, respectively. At Wave 2, these estimates increased to 8% and 23% for AU, and 17% and 33% for AUD. Conclusions Among a large Norwegian twin sample, borderline and antisocial PD criteria were the strongest predictors of the phenotypic and genotypic liability to AU and AUD. This effect remained consistent across time.

Cigarette smoking is the leading cause of preventable morbidity and mortality. Knowledge is evolving on genetics underlying initiation, regular smoking, nicotine dependence (ND), and cessation. We performed a genome-wide association study using the Fagerström Test for ND (FTND) in 58,000 smokers of European or African ancestry. Five genome-wide significant loci, including two novel loci MAGI2/GNAI1 (rs2714700) and TENM2 (rs1862416) were identified, and loci reported for other smoking traits were extended to ND. Using the heaviness of smoking index (HSI) in the UK Biobank (N=33,791), rs2714700 was consistently associated, but rs1862416 was not associated, likely reflecting ND features not captured by the HSI. Both variants were cis-eQTLs (rs2714700 for MAGI2-AS3 in hippocampus, rs1862416 for TENM2 in lung), and expression of genes spanning ND-associated variants was enriched in cerebellum. SNP-based heritability of ND was 8.6%, and ND was genetically correlated with 17 other smoking traits (rg=0.40–0.95) and co-morbidities. Our results emphasize the FTND as a composite phenotype that expands genetic knowledge of smoking, including loci specific to ND.

Pathological changes in Alzheimer’s disease (AD) begin decades before dementia onset. Because locus coeruleus tau pathology is the earliest occurring AD pathology, targeting indicators of locus coeruleus (dys)function may improve midlife screening for earlier identification of AD risk. Pupillary responses during cognitive tasks are driven by the locus coeruleus and index cognitive effort. Several findings suggest task-associated pupillary response as an early marker of AD risk. Requiring greater effort suggests being closer to one’s compensatory capacity, and adults with mild cognitive impairment (MCI) have greater pupil dilation during digit span tasks than cognitively normal individuals, despite equivalent task performance. Higher AD polygenic risk scores (AD-PRSs) are associated with increased odds of MCI and tau positivity. We hypothesized that AD-PRSs would be associated with pupillary responses in cognitively normal middle-aged adults. We demonstrated that pupillary responses during digit span tasks were heritable (h2=.30-.36) in 1119 men ages 56-66. We then examined associations between AD-PRSs and pupillary responses in a cognitively normal subset who all had comparable span capacities (n=539). Higher AD-PRSs were associated with greater pupil dilation/effort in a high (9-digit recall) cognitive load condition; Cohen’s d=.36 for the upper versus lower quartile of the AD-PRS distribution. Results held up after controlling for APOE genotype. The results support pupillary response—and by inference, locus coeruleus dysfunction—as a genetically-mediated biomarker of early MCI/AD risk. In some studies, cognition predicted disease progression earlier than biomarkers. Pupillary responses might improve screening and early identification of genetically at-risk individuals even before cognitive performance declines.

BackgroundThe aggregation of neurocognitive deficits among the non-psychotic first-degree relatives of adult- and childhood-onset schizophrenia patients suggests that there may be a common etiology for these deficits in childhood- and adult-onset illness. However, there is considerable heterogeneity in the presentation of neurobiological abnormalities, and whether there are differences in the extent of familial transmission for specific domains of cognitive function has not been systematically addressed.MethodsWe employed variance components analysis, as implemented in SOLAR-Eclipse, to evaluate the evidence of familial transmission for empirically derived composite scores representing attention, working memory, verbal learning, verbal retention, and memory for faces. We contrast estimates for adult- and childhood-onset schizophrenia families and matched community control pedigrees, and compare our findings to previous reports based on analogous neurocognitive assessments.ResultsWe observed varying degrees of familial transmission; attention and working memory yielded comparable, significant estimates for adult-onset and community control pedigrees; verbal learning was significant for childhood-onset and community control pedigrees; and facial memory demonstrated significant familial transmission only for childhood-onset schizophrenia. Model-fitting analyses indicated significant differences in familiality between adult- and childhood-onset schizophrenia for attention, working memory, and verbal learning.ConclusionsBy comprehensively assessing a wide range of neurocognitive domains in adult- and childhood-onset schizophrenia families, we provide additional support for specific neurocognitive domains as schizophrenia endophenotypes. Whereas comparable estimates of familial transmission for certain dimensions of cognitive functioning support a shared etiology of adult- and childhood-onset neurocognitive function, observed differences may be taken as preliminary evidence of partially divergent multifactorial architectures.

Understanding genetic influences on Alzheimer’s disease (AD) may improve early identification. AD polygenic risk scores (AD-PRSs) are associated with increased odds of AD and mild cognitive impairment (MCI). Additional sources of genetic risk may also contribute to disease outcomes. Coronary artery disease (CAD) is a risk factor for AD, interacts with AD pathology, and is also heritable. We showed that incidence-based and prevalence-based CAD-PRSs moderate the association between the AD-PRS and MCI, but in opposing directions. Higher incidence-based CAD-PRSs interacted with the AD-PRS to further increase MCI risk. Conversely, the AD-PRS was predictive of MCI when prevalence-based CAD-PRSs were low. The latter finding is likely due to prevalent CAD cases being biased toward longer post-event survival times, perhaps selecting for protective loci that offset AD risk. These results demonstrate: i) the importance of examining multiple PRSs and their interactions; ii) how genetic risk for one disease can modify the impact of genetic risk for another; and iii) the importance of considering ascertainment procedures of GWAS used for genetic risk prediction.

Objective Prior twin studies provide support for a single “common factor” that contributes genetic and environmental risk to a range of disordered eating symptoms. However, the common factor may be indexed less well by binge eating (BE) than other symptoms of eating disorders [i.e., body dissatisfaction (BD) and weight preoccupation (WP)]. We sought to explore the presence of a common factor and test whether loadings differed across three key symptoms (i.e., BE, BD, WP). Method Disordered eating was assessed via self-report in 631 female twin pairs from the Michigan State University Twin Registry. Results We detected a common disordered eating factor that was influenced primarily by additive genetic and nonshared environmental influences. However, we observed different loadings on this common factor by symptom type, as factor loadings for BD and WP were stronger than that for BE. Moreover, the residual environmental and/or genetic variances (i.e., those that are independent of the common factor) were larger in BE than those of BD or WP. Discussion Although all three symptoms share a common set of genetic and environmental influences, risk for BE may involve additional genetic, biological, and environmental factors that are not shared with other symptoms of eating pathology. © 2016 Wiley Periodicals, Inc.(Int J Eat Disord 2017; 50:157–161)

Using Swedish nationwide registry data, the authors investigated the correlation of genetic and environmental risk factors in the etiology of drug abuse as ascertained from medical and criminal registries by modeling twin and sibling data. Medical drug abuse was defined using public inpatient and outpatient records, while criminal drug abuse was ascertained through legal records. Twin, full and half sibling pairs were obtained from the national twin and genealogical registers. Information about sibling pair residence within the same household was obtained from Statistics Sweden. Standard bivariate genetic structural equation modeling was applied to the population-based data on drug abuse ascertained through medical and crime registries, using OpenMx. Analyses of all possible pairs of twins (MZ: N = 4482; DZ: N = 9838 pairs), full- (N = 1,278,086) and half-siblings (paternal: N = 7767; maternal N = 70,553) who grew up together suggested that factors explaining familial resemblance for drug abuse as defined through medical or criminal registries were mostly the same. Results showed substantial heritability and moderate contributions of shared environmental factors to drug abuse; both were higher in males versus females, and higher for drug abuse ascertained through criminal than medical records. Because of the low prevalence of both assessments of drug abuse, having access to population data was crucial to obtain stable estimates. Using objective registry data, the authors found that drug abuse-whether ascertained through medical versus criminal records-was highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of drug abuse. Genetic and shared environmental risk factors for these two forms of drug abuse were highly correlated.

Aims This study explored the factor structure of DSM III-R/IV symptoms for substance abuse and dependence across six illicit substance categories in a population-based sample of males. Method DSM III-R/IV drug abuse and dependence symptoms for cannabis, sedatives, stimulants, cocaine, opioids and hallucinogens from 4179 males born 1940–1970 from the population-based Virginia Adult Twin Study of Psychiatric and Substance Use Disorders were analyzed. Confirmatory factor analyses tested specific hypotheses regarding the latent structure of substance misuse for a comprehensive battery of 13 misuse symptoms measured across six illicit substance categories (78 items). Results Among the models fit, the latent structure of substance misuse was best represented by a combination of substance-specific factors and misuse symptom-specific factors. We found no support for a general liability factor to illicit substance misuse. Conclusions Results indicate that liability to misuse illicit substances is drug class specific, with little evidence for a general liability factor. Additionally, unique dimensions capturing propensity toward specific misuse symptoms (e.g., tolerance, withdrawal) across substances were identified. While this finding requires independent replication, the possibility of symptom-specific misuse factors, present in multiple substances, raises the prospect of genetic, neurobiological and behavioral predispositions toward distinct, narrowly defined features of drug abuse and dependence.

SummaryGenetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed a meta-analysis of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders identifying three groups of inter-related disorders. We detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning in the second trimester prenatally, and play prominent roles in a suite of neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.

BACKGROUNDAlzheimer’s disease (AD) is under considerable genetic influence. However, known susceptibility loci only explain a modest proportion of variance in disease outcomes. This small proportion could occur if the etiology of AD is heterogeneous. We previously found that an AD polygenic risk score (PRS) was significantly associated with mild cognitive impairment (MCI), an early stage of AD. Poor cardiovascular health is also associated with increased risk for AD and has been found to interact with AD pathology. Conditions such as coronary artery disease (CAD) are also heritable, and may contribute to heterogeneity if there are interactions of genetic risk for these conditions as there is phenotypically. However, case-control designs based on prevalent cases of a disease with relatively high case-fatality rate such as CAD may be biased toward individuals who have long post-event survival times and may therefore also identify loci with protective effects.METHODSWe compared interactions between an AD-PRS and two CAD-PRSs, one based on a GWAS of incident cases and one on prevalent cases, on MCI status in 1,209 individuals.RESULTSAs expected, the incidence-based CAD-PRS interacts with the AD-PRS to further increase MCI risk. Conversely, higher prevalence-based CAD-PRSs reduced the effect of AD genetic risk on MCI status.CONCLUSIONSThese results demonstrate: i) the utility of including multiple PRSs and their interaction effects; ii) how genetic risk for one disease may modify the impact of genetic risk for another; and iii) the importance of considering ascertainment procedures of GWAS being used for genetic risk prediction.

Both normative personality and DSM-IV personality disorders have been found to be heritable. However, there is limited knowledge about the extent to which the genetic and environmental influences underlying DSM personality disorders are shared with those of normative personality. The aims of this study were to assess the phenotypic similarity between normative and pathological personality and to investigate the extent to which genetic and environmental influences underlying individual differences in normative personality account for symptom variance across DSM-IV personality disorders.A large population-based sample of adult twins was assessed for DSM-IV personality disorder criteria with structured interviews at two waves spanning a 10-year interval. At the second assessment, participants also completed the Big Five Inventory, a self-report instrument assessing the five-factor normative personality model. The proportion of genetic and environmental liabilities unique to the individual personality disorder measures, and hence not shared with the five Big Five Inventory domains, were estimated by means of multivariate Cholesky twin decompositions.The median percentage of genetic liability to the 10 DSM-IV personality disorders assessed at wave 1 that was not shared with the Big Five domains was 64%, whereas for the six personality disorders that were assessed concurrently at wave 2, the median was 39%. Conversely, the median proportions of unique environmental liability in the personality disorders for wave 1 and wave 2 were 97% and 96%, respectively.The results indicate that a moderate-to-sizable proportion of the genetic influence underlying DSM-IV personality disorders is not shared with the domain constructs of the Big Five model of normative personality. Caution should be exercised in assuming that normative personality measures can serve as proxies for DSM personality disorders when investigating the etiology of these disorders.

Background There is substantial comorbidity between personality disorders (PDs) and anxiety disorders (ADs). Sharing of familial risk factors possibly explains the co-occurrence, but direct causal relationships between the disorders may also exist. Methods 2801 persons from 1391 twin pairs from the Norwegian Institute of Public Health Twin Panel were assessed for all DSM-IV PDs and ADs. Bivariate Poisson-regression analyses were performed to assess whether PDs predicted ADs at three different levels: All PDs combined, PDs combined within DSM-IV-clusters and each individual PD separately. Next, bivariate co-twin control analyses were executed within monozygotic (MZ) and dizygotic (DZ) twin pairs. A similar analytic strategy was employed in multivariate models including PDs as independent variables. Results PDs predicted ADs at all levels of analysis in bivariate regression models. Bivariate co-twin control analyses demonstrated an increased risk of ADs in all PDs combined, all PD-clusters and in schizotypal, paranoid, borderline, antisocial, avoidant and dependent PD. In the multivariate regression model, all PD-clusters and schizotypal, borderline, avoidant and obsessive-compulsive PD predicted ADs. Only borderline and avoidant PD predicted ADs in the multivariate co-twin control analysis. Limitations Over-adjustment may explain the results from the multivariate analyses. The cross-sectional study design hampers causal inference. Conclusions Comorbidity between ADs and PDs can be largely accounted for by shared familial risk factors. However, the results are also consistent with a direct causal relationship partly explaining the co-occurrence. Our results indicate specific environmental factors for comorbidity of ADs and borderline and avoidant PDs that are not shared with other PDs.

Objective We examined the association between the genetic and environmental factors contributing to the liability to having ever engaged in self-induced vomiting (SIV initiation) and the genetic and environmental factors contributing to regular SIV behaviors (weekly or daily) for weight control. Method SIV was assessed in 3,942 women from monozygotic twin pairs and 2,790 women from same-sex dizygotic twin pairs, aged 20–47, from the Swedish Twin study of Adults: Genes and Environment. A causal-contingent-common pathway model assessed the extent to which genetic and environmental factors that influence initiation of SIV also influence regular SIV behaviors. Results In the best-fit model, genetic and individual-specific environmental factors influenced liability to SIV initiation. The genetic factors influencing regular SIV behaviors were the same as the genetic factors influencing SIV initiation. Additional individual-specific environmental factors that were unrelated to SIV initiation influenced regular SIV behaviors. Discussion Our findings provide evidence that the underlying liabilities for SIV initiation and regular SIV lie on the same continuum given the degree of overlap in risk between SIV initiation and regular SIV behaviors. Further, the lack of specific genetic factors and the importance of individual-specific environmental factors for regular SIV behaviors highlight the significance of environmental factors in the etiology of eating disorder symptomatology and the non-deterministic nature of genetic factors. Finally, our results suggest that when it comes to preventing individuals from developing regular SIV behavior, intervening at an environmental level is warranted. © 2015 Wiley Periodicals, Inc. (Int J Eat Disord 2016; 49:421–427)

BACKGROUND:Obsessive-compulsive disorder (OCD) is characterized by five major dimensions, including contamination/washing, harm/checking, symmetry/ordering, hoarding, and forbidden thoughts. How these dimensions may relate etiologically to the symptoms of other obsessive-compulsive related disorders (OCRDs) and anxiety disorders (ADs) is not well known. The aim of this study was to examine the genetic and environmental overlap between each major obsessive-compulsive dimension with the symptoms of other OCRDs and ADs. METHODS:Two thousand four hundred ninety-five twins of both sexes, aged between 18 and 45 years, were recruited from the Australian Twin Registry. Measures used scores on four dimensions (obsessing (forbidden thoughts), washing, checking, and ordering) of the Obsessive-Compulsive Inventory-Revised, Dysmorphic Concerns Questionnaire, Hoarding Rating Scale, Anxiety Sensitivity Index, Social Phobia Inventory, and Stress subscale of the Depression, Anxiety, and Stress Scale. Multivariate twin modeling methods using continuous and categorized variables were performed, also controlling for age and gender. RESULTS:Our findings suggested that forbidden thoughts and washing demonstrated the strongest genetic overlap with other AD symptoms, while ordering was genetically related to OCRD symptoms. Common genetic influences on checking symptoms were best estimated when modeling OCRDs together with AD symptoms. Common environmental factors of ordering and checking were shared with AD symptoms. CONCLUSIONS:Important shared genetic and environmental risk factors exist between OCD, OCRDs, and ADs, but which vary alongside the expression of its major dimensions.

Background.Mixed anxiety–depression (MAD) has been under scrutiny to determine its potential place in psychiatric nosology. The current study sought to investigate its prevalence, clinical characteristics, course and potential validators.Method.Restricted latent-class analyses were fit to 12-month self-reports of depression and anxiety symptom criteria in a large population-based sample of twins. Classes were examined across an array of relevant indicators (demographics, co-morbidity, adverse life events, clinical significance and twin concordance). Longitudinal analyses investigated the stability of, and transitions between, these classes for two time periods approximately 1.5 years apart.Results.In all analyses, a class exhibiting levels of MAD symptomatology distinctly above the unaffected subjects yet having low prevalence of either major depression (MD) or generalized anxiety disorder (GAD) was identified. A restricted four-class model, constraining two classes to have no prior disorder history to distinguish residual or recurrent symptoms from new onsets in the last year, provided an interpretable classification: two groups with no prior history that were unaffected or had MAD and two with prior history having relatively low or high symptom levels. Prevalence of MAD was substantial (9–11%), and subjects with MAD differed quantitatively but not qualitatively from those with lifetime MD or GAD across the clinical validators examined.Conclusions.Our findings suggest that MAD is a commonly occurring, identifiable syndromal subtype that warrants further study and consideration for inclusion in future nosologic systems.

Empirically derived phenotypic measurements have the potential to enhance gene-finding efforts in schizophrenia. Previous research based on factor analyses of symptoms has typically included schizoaffective cases. Deriving factor loadings from analysis of only narrowly defined schizophrenia cases could yield more sensitive factor scores for gene pathway and gene ontology analyses. Using an Irish family sample, this study 1) factor analyzed clinician-rated Operational Criteria Checklist items in cases with schizophrenia only, 2) scored the full sample based on these factor loadings, and 3) implemented genome-wide association, gene-based, and gene-pathway analysis of these SCZ-based symptom factors (final N = 507). Three factors emerged from the analysis of the schizophrenia cases: a manic, a depressive, and a positive symptom factor. In gene-based analyses of these factors, multiple genes had q

Objective In an effort to address earliest detection of mild cognitive impairment (MCI), we examined hippocampal volumes and atrophy in middle-aged men to explore neuroanatomical support for different neuropsychological definitions of MCI. Methods 460 men aged 51–60 years underwent neuropsychological testing and MRI. MCI was defined according to five criteria sets. MRI-derived hippocampal volume and hippocampal occupancy (HOC) were obtained via FreeSurfer. Statistical analyses were performed using linear mixed models. Results Differences in HOC between normal cognitive functioning, amnestic, and non-amnestic MCI were observed using MCI criteria that required one impaired (>1.5 SD) cognitive measure in a given cognitive domain or a cognitive composite score method with a cut-point 2 SD below the mean. Differences in standard hippocampal volume were only found between normal and amnestic presentations and only when using the composite score method. Conclusion Results provide empirical support for detection of pre-MCI in younger cohorts. Convergence of neuropsychological and neuroanatomical data, particularly HOC (as opposed to standard cross-sectional volume), supports early identification of MCI as defined by some neuropsychological criteria.

Until now, data have not been available to elucidate the genetic and environmental sources of comorbidity between all 10 DSM-IV personality disorders (PDs) and cocaine use. Our aim was to determine which PD traits are linked phenotypically and genetically to cocaine use. Cross-sectional data were obtained in a face-to-face interview between 1999 and 2004. Subjects were 1,419 twins (µage = 28.2 years, range = 19–36) from the Norwegian Institute of Public Health Twin Panel, with complete lifetime cocaine use and criteria for all 10 DSM-IV PDs. Stepwise multiple and Least Absolute Shrinkage and Selection Operator (LASSO) regressions were used to identify PDs related to cocaine use. Twin models were fitted to estimate genetic and environmental associations between the PD traits and cocaine use. In the multiple regression, antisocial (OR = 4.24, 95% CI [2.66, 6.86]) and borderline (OR = 2.19, 95% CI [1.35, 3.57]) PD traits were significant predictors of cocaine use. In the LASSO regression, antisocial, borderline, and histrionic were significant predictors of cocaine use. Antisocial and borderline PD traits each explained 72% and 25% of the total genetic risks in cocaine use, respectively. Genetic risks in histrionic PD were not significantly related to cocaine use. Importantly, after removing criteria referencing substance use, antisocial PD explained 65% of the total genetic variance in cocaine use, whereas borderline explained only 4%. Among PD traits, antisocial is the strongest correlate of cocaine use, for which the association is driven largely by common genetic risks.

Background: Most twin studies of multiple sclerosis (MS) are inconclusive regarding the impact of genes and environment on disease susceptibility. In particular, high uncertainty exists about whether shared environmental factors are aetiologically relevant. Objective: To disentangle, with a reasonable degree of confidence, the relative contributions of heritability and of shared and unique environmental components of MS susceptibility. Methods: We performed a meta-analysis of previous twin studies. After a MEDLINE search, we selected eight twin studies in France, UK, Canada, Denmark, North America, Italy, Finland and Sweden. We conducted a biometric multi-group analysis under the liability-threshold model, by taking account of the study-specific ascertainment strategies and the population-specific prevalence rates of MS. Results: The meta-analytic estimates of tetrachoric correlations were 0.71 (95% confidence interval (CI): 0.67–0.74) in monozygotic pairs and 0.46 (95% CI: 0.41–0.50) in dizygotic pairs. The biometric multi-group model provided meta-analytic estimates of 0.50 (95% CI: 0.39–0.61) for heritability, 0.21 (95% CI: 0.11–0.30) for shared environmental component and 0.29 (95% CI: 0.26–0.33) for unique environmental component. Conclusion: Our results support the continuing efforts to identify unknown genetic factors that fill the gap of ‘missing heritability’; moreover, a ‘missing environmentality’ deserves future investigations into the role of non-heritable components that act as both shared and individual-specific exposures.

Theoretical models of binge eating and eating disorders include both transdiagnostic and eating disorder-specific risk factors. Negative urgency (i.e., the tendency to act impulsively when distressed) is a critical transdiagnostic risk factor for binge eating, but limited research has examined interactions between negative urgency and disorder-specific variables. Investigating these interactions can help identify the circumstances under which negative urgency is most strongly associated with binge eating. We examined whether prominent risk factors (i.e., appearance pressures, thin-ideal internalization, body dissatisfaction, dietary restraint) specified in well-established etiologic models of eating disorders moderate negative urgency-binge eating associations. Further, we investigated whether phenotypic moderation effects were due to genetic and/or environmental associations between negative urgency and binge eating. Participants were 988 female twins aged 11-25 years from the Michigan State University Twin Registry. Appearance pressures, thin-ideal internalization, and body dissatisfaction, but not dietary restraint, significantly moderated negative urgency-binge eating associations, with high levels of these risk factors and high negative urgency associated with the greatest binge eating. Twin moderation models revealed that genetic, but not environmental, sharing between negative urgency and binge eating was enhanced at higher levels of these eating disorder-specific variables. Future longitudinal research should investigate whether eating disorder risk factors shape genetic influences on negative urgency into manifesting as binge eating. (PsycINFO Database Record

BackgroundDSM-5 includes two conceptualizations of personality disorders (PDs). The classification in Section II is identical to the one found in DSM-IV, and includes 10 categorical PDs. The Alternative Model (Section III) includes criteria for dimensional measures of maladaptive personality traits organized into five domains. The degree to which the two conceptualizations reflect the same etiological factors is not known.MethodsWe use data from a large population-based sample of adult twins from the Norwegian Institute of Public Health Twin Panel on interview-based DSM-IV PDs and a short self-report inventory that indexes the five domains of the DSM-5 Alternative Model plus a domain explicitly targeting compulsivity. Schizotypal, Paranoid, Antisocial, Borderline, Avoidant, and Obsessive-compulsive PDs were assessed at the same time as the maladaptive personality traits and 10 years previously. Schizoid, Histrionic, Narcissistic, and Dependent PDs were only assessed at the first interview. Biometric models were used to estimate overlap in genetic and environmental risk factors.ResultsWhen measured concurrently, there was 100% genetic overlap between the maladaptive trait domains and Paranoid, Schizotypal, Antisocial, Borderline, and Avoidant PDs. For OCPD, 43% of the genetic variance was shared with the domains. Genetic correlations between the individual domains and PDs ranged from +0.21 to +0.91.ConclusionThe pathological personality trait domains, which are part of the Alternative Model for classification of PDs in DSM-5 Section III, appears to tap, at an aggregate level, the same genetic risk factors as the DSM-5 Section II classification for most of the PDs.

Ovarian hormones (i.e., estradiol and progesterone) have recently been implicated in the etiology of eating disorders in women (1–4). Most research to date has focused on the role of ovarian hormones in risk for binge eating. This is not surprising given findings from animal studies demonstrating that ovarian hormones have direct, causal effects on food intake (5, 6). Specifically, removal of the source of ovarian hormones through bilateral ovariectomy in rats causes increased food intake, and adminstration of estradiol reverses this effect. In contrast, progesterone causes increased food intake, in part, by antagonizing the inhibitory effects of estradiol (6–8). In humans, food intake, binge eating, and emotional eating (i.e., the tendency to eat when experiencing negative emotions, 9) have been found to be significantly higher during the mid-luteal and pre-menstrual phases of the menstrual cycle as compared to the follicular/ovulatory phases (1, 3, 10–13). Studies that have directly examined estradiol and progesterone levels confirm that within-person changes in ovarian hormones account for these menstrual-cycle fluctuations (1, 3, 13). Specifically, while initial pilot data suggested that lower estradiol and higher progesterone levels were associated with increases in binge eating and emotional eating (1, 3), a recent study indicated that interactions between estradiol and progesterone (i.e., high levels of both) contribute to mid-luteal increases in emotional eating as well (14). Moreover, ovarian hormone/dysregulated eating associations have been shown to be stronger in women with clinically significant levels of binge eating compared to women without binge episodes (13). Importantly, in all previous studies, hormone effects on binge eating and emotional eating were independent of important covariates that also change across the menstrual cycle, including negative affect and body mass index (BMI) (1, 3, 13, 14). Far fewer studies, however, have examined menstrual cycle changes in other disordered eating variables. Broadening the phenotypes examined is important for developing more complete models of the role of ovarian hormones in the full spectrum of eating pathology. One particularly important set of variables to investigate are those related to weight concerns/preoccupation (i.e., intense preoccupation with weight, dieting, and the pursuit of thinness; 15). Weight concerns have been identified as one of the most robust prospective risk factors for the development of clinically significant eating disorders (16), and weight concerns are directly related to core symptoms (e.g., undue influence of body weight/shape on self-evaluation) of anorexia nervosa and bulimia nervosa (17). In the only previous report of its kind, Racine et al., (2012) examined the association between menstrual-cycle fluctuations in ovarian hormone and changes in weight concerns in two independent samples of women. In the first sample, robust fluctuations in weight preoccupation were observed across the menstrual cycle, where weight preoccupation levels were highest in the mid-luteal phase (4). Menstrual-cycle changes in weight preoccupation were primarily accounted for by within-person increases in progesterone and, to a lesser extent, decreases in estradiol. However, in a second sample, more modest, non-significant changes in weight preoccupation were observed across the menstrual cycle, and weight preoccupation was highest during the pre-menstrual phase. Reasons for the discrepant results across samples are unclear, although the very small sample sizes of these studies (N = 8 and N = 10, respectively) may have contributed to instability in effects. Clearly, additional research using larger samples of women is needed to clarify the presence/absence of within-person menstrual cycle fluctuations in weight preoccupation. Moreover, it will be important for these studies to determine whether menstrual cycle changes in weight preoccupation are due to changes in ovarian hormones, changes in psychological factors (e.g., increased negative affect), and/or changes in emotional eating that have been shown to fluctuate across the menstrual cycle in past research (1, 3, 13, 14, 18, 19). For example, emotional eating has previously been linked to ovarian hormones (1, 3, 13, 14), and we might expect weight concerns to increase during certain menstrual cycle phases as a result of emotional eating. Specifically, increased emotional eating during the mid-luteal phase could cause women to be more concerned and/or conscious about their body shape/weight; in this case, weight concerns may be due to eating in the presence of negative emotions rather than to changes in ovarian hormones. Thus, it is important to determine what factors might account for menstrual cycle changes in weight preoccupation: emotional eating, psychological factors (e.g., negative affect) and/or ovarian hormones. Given the above, the aim of the current study was to investigate within-person changes in weight preoccupation across the menstrual cycle utilizing a large, community-based sample of women. First, we were interested in examining whether levels of weight preoccupation significantly vary across the menstrual cycle. Second, we wanted to investigate whether within-person fluctuations in weight preoccupation across the menstrual cycle are best accounted for by within-person changes in ovarian hormones, negative affect, emotional eating, or a combination of these factors.

Thin-ideal internalization (i.e., the acceptance of and adherence to sociocultural beauty ideals for women that focus on thinness) is an important risk factor in the development of body dissatisfaction, disordered eating, and eating disorders (see 1; 2 for reviews of this literature .). Cross-sectional and prospective studies have supported the role of thin-ideal internalization in the development of eating problems (e.g., body dissatisfaction, dieting; 1.), and eating disorder prevention programs that target thin-ideal internalization have been effective in decreasing disordered eating (3.). However, as noted by others (4.), prevention programs could, and should, be improved further, particularly given their potential to decrease the development of eating disorders. Increasing knowledge on the etiology of thin-ideal internalization may be key to developing additional intervention techniques. Unfortunately, risk factors for thin-ideal internalization have been studied less frequently than risk factors for eating pathology (5–8.). Existing research has focused on the role of environmental risk factors that are thought to teach and reinforce beauty ideals of thinness, such as media images, parental and peer influences (5; 6.) Although research has demonstrated that hypothesized media, peer, and parental risk factors are indeed associated with thin-ideal internalization (5; 6.), further research is needed to confirm the direction of these effects, as current studies are limited by cross-sectional designs. In addition to environmental risk factors, twin research has demonstrated that genetic influences explain approximately 40% of the variance in thin-ideal internalization in a sample of post-pubertal adolescent and young adult twins (9.). Thus, genetic influences may explain why, despite almost ubiquitous exposure to the thin-ideal in Western countries, only some women ultimately internalize this ideal and go on to develop disordered eating behaviors (9.). More specifically, in the context of environmental risk factors (e.g., thin-ideal focused media) that nearly all women within Western culture experience, it may be level of genetic risk for thin-ideal internalization that differentiates those women who go on to internalize these ideals, and those who do not. Given that only one twin study of thin-ideal internalization has been conducted, further research is needed to extend knowledge of genetic and environmental effects. In particular, it is necessary to examine etiologic effects across adolescence, a key period for the development of thin-ideal internalization. Indeed, mean levels of thin-ideal internalization have been shown to increase across adolescence (9; 10.). The pubertal period appears to be particularly important in this regard, as girls in pre-to-early puberty report significantly lower levels of thin-ideal internalization than girls in mid-puberty and beyond (11.). These increases in mean levels of thin-ideal internalization may indicate key etiological shifts that should be examined as well. Indeed, related phenotypes, such as disordered eating, show significant etiological changes across this period, such that the heritability of disordered eating is negligible in pre-adolescence and pre-pubertal twins, but is significant (i.e., approximately 50% of variance) in pubertal twins and in twins who are in middle adolescence (i.e., about age 14) or older (i.e., ages 16–40 years; 12; 13; 14.). The effects of the shared environment are opposite of those observed for genetic influences: shared environmental influences account for 40% of the variance in disordered eating in pre-adolescence/pre-puberty, and 10% or less from middle adolescence into middle adulthood and in pubertal twins. These findings have been useful because they have led researchers to develop specific hypotheses regarding mechanisms that may account for differences in heritability across puberty, such as changes in ovarian hormones during puberty (15.). Given that adolescence also seems to be a key developmental period for thin-ideal internalization (11.), developmental twin studies of thin-ideal internalization may help elucidate etiological mechanisms that contribute to risk for thin-ideal internalization across development. The aim of the present study was to investigate the extent to which genetic and environmental influences on thin-ideal internalization differ across age and pubertal development in a large (N=1,064) sample of same-sex female twins (ages 8–25 years). To ensure that effects are specific to thin-ideal internalization, we examined developmental differences in genetic and environmental effects while controlling for disordered eating. Specificity of effects are important to establish given phenotypic and genetic overlap in thin-ideal internalization and disordered eating (16–18.) and the need to identify etiological risk factors that contribute uniquely to thin-ideal internalization.

Background and Aims A strong correlation exists between smoking and the use of alcohol and cannabis.This paper uses polygenic risk scores to explore the possibility of overlapping genetic factors.Those scores reflect a combined effect of selected risk alleles for smoking. Methods Summary-level P-values were available for smoking initiation, age at onset of smoking, cigarettes per day and smoking cessation from the Tobacco and Genetics Consortium (n between 22 000and70 000subjects).UsingdifferentP-valuethresholds(0.1,0.2and0.5)fromthemeta-analysis,setsof 'risk alleles' were defined and used to generate a polygenic risk score (weighted sum of the alleles) for each subject in an independent target sample from the Netherlands Twin Register (n = 1583). The association between polygenic smoking scores and alcohol/cannabis use was investigated with regression analysis. Results The polygenic scores for 'cigarettes per day' were associated significantly with the number of glasses alcohol per week (P = 0.005, R 2 = 0.4- 0.5%) and cannabis initiation (P = 0.004, R 2 = 0.6-0.9%). The polygenic scores for 'age at onset of smoking' were associated significantly with 'age at regular drinking' (P = 0.001, R 2 = 1.1-1.5%), while the scores for 'smoking initiation' and 'smoking cessation' did not significantly predict alcohol or cannabis use. Conclusions Smoking, alcohol and cannabis use are influenced by aggregated genetic risk factors shared between these substances.The many common genetic variants each have a very small individual effect size.

Studies suggest that within-person changes in estrogen and progesterone predict changes in binge eating across the menstrual cycle. However, samples have been extremely small (maximum N = 9), and analyses have not examined the interactive effects of hormones that are critical for changes in food intake in animals. The aims of the current study were to examine ovarian hormone interactions in the prediction of within-subject changes in emotional eating in the largest sample of women to date (N = 196). Participants provided daily ratings of emotional eating and saliva samples for hormone measurement for 45 consecutive days. Results confirmed that changes in ovarian hormones predict changes in emotional eating across the menstrual cycle, with a significant estradiol x progesterone interaction. Emotional eating scores were highest during the mid-luteal phase, when progesterone peaks and estradiol demonstrates a secondary peak. Findings extend previous work by highlighting significant interactions between estrogen and progesterone that explain mid-luteal increases in emotional eating. Future work should explore mechanisms (e.g., gene-hormone interactions) that contribute to both within- and between-subject differences in emotional eating.

Quantitative relationship between the magnitude of variation in minor histocompatibility antigens (mHA) and graft versus host disease (GVHD) pathophysiology in stem cell transplant (SCT) donor-recipient pairs (DRP) is not established. In order to elucidate this relationship, whole exome sequencing (WES) was performed on 27 HLA matched related (MRD), & 50 unrelated donors (URD), to identify nonsynonymous single nucleotide polymorphisms (SNPs). An average 2,463 SNPs were identified in MRD, and 4,287 in URD DRP (p

The association between human cytomegalovirus (hCMV) reactivation and the development of graft-versus-host-disease (GVHD) has been observed in stem cell transplantation (SCT). Seventy seven SCT donor-recipient pairs (DRP) (HLA matched unrelated donor (MUD), n=50; matched related donor (MRD), n=27) underwent whole exome sequencing to identify single nucleotide polymorphisms (SNPs) generating alloreactive peptide libraries for each DRP (9-mer peptide-HLA complexes); Human CMV CROSS (Cross-Reactive Open Source Sequence) Database was compiled from NCBI; HLA class I binding affinity for each DRPs HLA was calculated by NetMHCpan 2.8 and hCMV- derived 9-mers algorithmically compared to the alloreactive peptide-HLA complex libraries. Short consecutive (6 or greater) amino acid (AA) sequence homology matching hCMV to recipient peptides was considered for HLA-bound-peptide (IC50, Pre-submission manuscript, 4 tables, 5 figures, 2 supplements & 2 Appendices-available upon request from first author

Depression is a highly heterogeneous condition, and identifying how symptoms present in various groups may greatly increase our understanding of its etiology. Importantly, Major Depressive Disorder is strongly linked with Substance Use Disorders, which may ameliorate or exacerbate specific depression symptoms. It is therefore quite plausible that depression may present with different symptom profiles depending on an individual's substance use status. Given these observations, it is important to examine the underlying construct of depression in groups of substance users compared to non-users. In this study we use a non-clinical sample to examine the measurement structure of the Beck Depression Inventory (BDI-II) in non-users and frequent-users of various substances. Specifically, measurement invariance was examined across those who do vs. do not use alcohol, nicotine, and cannabis. Results indicate strict factorial invariance across non-users and frequent-users of alcohol and cannabis, and metric invariance across non-users and frequent-users of nicotine. This implies that the factor structure of the BDI-II is similar across all substance use groups.

Rabbit anti-thymocyte globulin (ATG) is used as prophylaxis against GVHD following allogeneic hematopoietic cell transplantation (HCT). At our institution, ATG is exclusively used in the conditioning of matched unrelated donor (URD) transplant recipients. A total of 50 URD HCT recipients who received ATG (ATG group) were retrospectively compared with 48 matched related donor (MRD) HCT recipients who did not receive ATG (no ATG group). There were no significant differences between the groups in rates of day 100 mortality, acute GVHD or relapse. Chronic GVHD incidence was significantly lower in the ATG group (P = 0.007). At a median follow-up of 36 months in the entire cohort, 50% patients are alive in the ATG group and 63% of the patients are alive in the no ATG group (P = 0.13). We conclude that the administration of ATG to patients undergoing URD HCT preserves the anti-leukemia benefit of the transplant, while reducing the risk of developing GVHD, resulting in OS rates that are comparable to MRD HCT recipients.

This study examined the relative influence of genetic versus environmental factors on specific aspects of eating behavior. Adult monozygotic twins (22 pairs and 3 singleton reared apart, 38 pairs and 9 singleton reared together, age 18-76 years, BMI 17-43 kg/m 2 ) completed the Three Factor Eating Questionnaire. Genetic and environmental variance components were determined for the three eating behavior constructs and their subscales using model-fitting univariate and multivariate analyses. Unique environmental factors had a substantial influence on all eating behavior variables (ex- plaining 45-71% of variance), and most strongly influenced external locus for hunger and strategic dieting behavior of re- straint (explaining 71% and 69% of variance, respectively). Genetic factors had a statistically significant influence on only 4 variables: restraint, emotional susceptibility to disinhibition, situational susceptibility to disinhibition, and internal locus for hunger (heritabilities were 52%, 55%, 38% and 50%, respectively). Common environmental factors did not statisti- cally significantly influence any variable assessed in this study. In addition, multivariate analyses showed that disinhibi- tion and hunger share a common influence, while restraint appears to be a distinct construct. These findings suggest that the majority of variation in eating behavior variables is associated with unique environmental factors, and highlights the importance of the environment in facilitating specific eating behaviors that may promote excess weight gain.

Background Generalized anxiety disorder (GAD) is a common, chronic condition that is relatively understudied compared to other psychiatric syndromes. Neuroimaging studies have begun to implicate particular neural structures and circuitry in its pathophysiology; however, no genetically-informative research has examined the potential sources of reported brain differences.

The Diagnostic and Statistical Manual (4th ed. [DSM-IV]; American Psychiatric Association, 1994) distinction between clinical disorders on Axis I and personality disorders on Axis II has become increasingly controversial. Although substantial comorbidity between axes has been demonstrated, the structure of the liability factors underlying these two groups of disorders is poorly understood. The aim of this study was to determine the latent factor structure of a broad set of common Axis I disorders and all Axis II personality disorders and thereby to identify clusters of disorders and account for comorbidity within and between axes. Data were collected in Norway, through a population-based interview study (N = 2,794 young adult twins). Axis I and Axis II disorders were assessed with the Composite International Diagnostic Interview (CIDI) and the Structured Interview for DSM-IV Personality (SIDP-IV), respectively. Exploratory and confirmatory factor analyses were used to investigate the underlying structure of 25 disorders. A four-factor model fit the data well, suggesting a distinction between clinical and personality disorders as well as a distinction between broad groups of internalizing and externalizing disorders. The location of some disorders was not consistent with the DSM-IV classification; antisocial personality disorder belonged primarily to the Axis I externalizing spectrum, dysthymia appeared as a personality disorder, and borderline personality disorder appeared in an interspectral position. The findings have implications for a meta-structure for the DSM.

Weight suppression (WS), defined as the discrepancy between one’s highest adult and current weight, is a relatively understudied concept in the area of eating disorders. It was first highlighted in Lowe’s [1] three-factor model of dieting behavior, which included frequency of dieting and overeating, current dieting, and WS. To date, this construct has been investigated primarily among clinical samples, and evidence suggests that WS negatively impacts the course and treatment of eating disorders [e.g., 2]. However, given the rapid increases in rates of overweight and obesity in the U.S. [3–4], it is possible that the ability to maintain weight loss could be advantageous among subsamples of the general population. The following sections briefly review studies of WS and eating-and weight-related constructs among eating disordered and non-eating disordered samples. Restraint theory posits that dietary restraint leads to subsequent overeating [5–6]. However, some have argued that restraint theory does not distinguish between chronic and acute dieting [1]. That is, while acute dieting may increase risk for overeating (including binge eating), chronic dieting may be advantageous for sustaining healthy weight loss. Data suggest that individuals who successfully maintain weight loss in the long term are able to consciously control their dietary intake. For example, participants in the National Weight Control Registry, who have lost an average of 33 kg and maintained this weight loss for more than five years, report fairly high levels of cognitive restraint [7]. Notably, these levels are lower than those of eating disorder patients [7]. Experimental studies suggest that individuals who have lost weight successfully and maintained that loss (i.e., weight suppressors) have adapted their appetitive reactions in a way that facilitates their ability to control weight (e.g., reduced preference for sweets [8]). Thus, the construct of WS may behave differently among individuals with and without eating disorders. Most investigations have demonstrated the negative effects of WS on eating disorders and related constructs. In addition, it has been hypothesized that WS might be particularly relevant to bulimia nervosa (BN), as individuals with this disorder often enter treatment at weights substantially below their highest adult weights. Specifically, in two samples of BN patients in a low-normal weight range, Garner and Fairburn [9] found that one-third and one-half, respectively, had previously been at least 15% overweight. Further, WS was found to be a significant predictor of weight gain among individuals receiving inpatient treatment for BN [10]. WS was also positively associated with binge eating frequency in a sample of women with BN [11]. Evidence further suggests that WS can impact the course of this disorder [2, 11]. For example, Butryn et al. [2] found that WS predicted attrition from BN treatment as well as poor outcomes (i.e., inability to achieve abstinence from bingeing and purging) among treatment completers. Taken together, these results suggest that WS may contribute to the development and maintenance of eating disorders, particularly BN. In addition to these investigations of WS in samples of patients with eating disorders [2, 10, 11], one recent study included non-treatment seeking college freshmen [12]. Lowe, Annunziato et al. [12] found that WS and a history of dieting for weight loss predicted weight gain. However, restraint, disinhibition, and emotional eating were not associated with weight gain in this sample. The authors noted that these results provided further support for WS and restraint as distinct constructs; further, they argued that WS appears to be a robust predictor of future weight gain. These studies provide important information regarding the WS construct; however results from treatment-seeking and college samples may not be applicable to the general population of adults. Although WS has been associated with eating disorder-related traits and weight gain among these groups, eating disordered and college samples might be particularly vulnerable to both more severe eating disorder symptomatology as well as greater weight gain than the general population [12]. Thus, the current study investigated associations among WS and eating disorder-related variables in a population-based sample of female twins, to determine whether these relationships differ for individuals reporting binge eating and loss of control (BE+LOC) vs. those reporting no binge eating (NBE). We chose to examine this form of disordered eating in our population-based sample, as evidence suggests that individuals manifesting subthreshold levels of binge eating report levels of distress comparable to those with binge eating disorder (e.g., [13]). The current study also estimated genetic and environmental influences on WS. Twin samples are useful for such analyses, as including both monozygotic (MZ) and dizygotic (DZ) twins in a structural equation model allows the variance of a given trait to be partitioned into additive genetic (A), common environmental (i.e., that which is shared among twin pairs; C), and unique environmental (i.e., that which is not shared among twin pairs; E) influences [14]. There are several reasons why twin research could provide insight into WS and related constructs. First, body mass index (BMI) is strongly influenced by genetic factors (e.g., approximately 50–90% of variance in BMI is attributable to additive genetic effects [15]). Second, twin studies of eating disorders have found that AN, BN, and related behaviors (e.g., binge eating and vomiting) are moderately heritable (for a review, see Bulik, et al. [16]). However, twin studies have also indicated that specific disordered eating related behaviors and attitudes are differentially influenced by genetic and environmental factors. For example, Neale et al. [17] found that disinhibited eating was most strongly influenced by additive genetic factors. However, restraint was more strongly influenced by common environmental factors. Similarly, the undue influence of weight on self-evaluation has been found to be more strongly influenced by environmental, rather than genetic, factors [18]. Thus, it is unclear to what degree genetic and environmental factors might influence liability to the specific construct of WS. In sum, the current study investigated WS among NBE and BE+LOC women in two ways. Regression models investigating relations between WS and eating disorder-related constructs (body dissatisfaction, drive for thinness, Restraint, Disinhibition, Hunger, and time spent dieting before and after age 18) were conducted separately in these two subsamples. We hypothesized that the associations among these variables and WS might differ for women reporting BE+LOC, relative to NBE participants, such that WS would be associated with more pathological behaviors among the BE+LOC group. Second, the genetic and environmental sources of variance were estimated in each subsample. We hypothesized that genetic influences on WS would be stronger in the BE+LOC group, relative to the NBE group, based on results of prior twin studies in the area of eating disorders.