The impact of anorexia nervosa and BMI polygenic risk on childhood growth: A 20-year longitudinal population-based study.

Growth deviating from the norm during childhood has been associated with anorexia nervosa (AN) and obesity later in life. In this study, we examined whether polygenic scores (PGSs) for AN and BMI are associated with growth trajectories spanning the first two decades of life. AN PGSs and BMI PGSs were calculated for participants of the Avon Longitudinal Study of Parents and Children (ALSPAC; n = 8,654). Using generalized (mixed) linear models, we associated PGSs with trajectories of weight, height, body mass index (BMI), fat mass index (FMI), lean mass index (LMI), and bone mineral density (BMD). Female participants with AN PGSs one standard deviation (SD) higher had, on average, 0.004% slower growth in BMI between the ages 6.5 and 24 years and a 0.4% slower gain in BMD between the ages 10 and 24 years. Higher BMI PGSs were associated with faster growth for BMI, FMI, LMI, BMD, and weight trajectories in both sexes throughout childhood. Female participants with both a high AN PGS and a low BMI PGS showed slower growth compared to those with both a low AN PGS and a low BMI PGS. We conclude that AN PGSs and BMI PGSs have detectable sex-specific effects on growth trajectories. Female participants with a high AN PGS and low BMI PGS likely constitute a high-risk group for AN, as their growth was slower compared to their peers with high PGSs on both traits. Further research is needed to better understand how the AN PGS and the BMI PGS co-influence growth during childhood and whether a high BMI PGS can mitigate the effects of a high AN PGS.

Proteome-wide Mendelian randomization identifies causal links between blood proteins and severe COVID-19.

In November 2021, the COVID-19 pandemic death toll surpassed five million individuals. We applied Mendelian randomization including >3,000 blood proteins as exposures to identify potential biomarkers that may indicate risk for hospitalization or need for respiratory support or death due to COVID-19, respectively. After multiple testing correction, using genetic instruments and under the assumptions of Mendelian Randomization, our results were consistent with higher blood levels of five proteins GCNT4, CD207, RAB14, C1GALT1C1, and ABO being causally associated with an increased risk of hospitalization or respiratory support/death due to COVID-19 (ORs = 1.12-1.35). Higher levels of FAAH2 were solely associated with an increased risk of hospitalization (OR = 1.19). On the contrary, higher levels of SELL, SELE, and PECAM-1 decrease risk of hospitalization or need for respiratory support/death (ORs = 0.80-0.91). Higher levels of LCTL, SFTPD, KEL, and ATP2A3 were solely associated with a decreased risk of hospitalization (ORs = 0.86-0.93), whilst higher levels of ICAM-1 were solely associated with a decreased risk of respiratory support/death of COVID-19 (OR = 0.84). Our findings implicate blood group markers and binding proteins in both hospitalization and need for respiratory support/death. They, additionally, suggest that higher levels of endocannabinoid enzymes may increase the risk of hospitalization. Our research replicates findings of blood markers previously associated with COVID-19 and prioritises additional blood markers for risk prediction of severe forms of COVID-19. Furthermore, we pinpoint druggable targets potentially implicated in disease pathology.

The network structure of mania symptoms differs between people with and without binge eating.

OBJECTIVES: People with bipolar disorder who also report binge eating have increased psychopathology and greater impairment than those without binge eating. Whether this co-occurrence is related to binge eating as a symptom or presents differently across full-syndrome eating disorders with binge eating is unclear. METHODS: We first compared networks of 13 lifetime mania symptoms in 34,226 participants from the United Kingdom's National Institute for Health and Care Research BioResource with (n = 12,104) and without (n = 22,122) lifetime binge eating. Second, in the subsample with binge eating, we compared networks of mania symptoms in participants with lifetime anorexia nervosa binge-eating/purging (n = 825), bulimia nervosa (n = 3737), and binge-eating disorder (n = 3648). RESULTS: People with binge eating endorsed every mania symptom significantly more often than those without binge eating. Within the subsample, people with bulimia nervosa most often had the highest endorsement rate of each mania symptom. We found significant differences in network parameter statistics, including network structure (M = 0.25, p = 0.001) and global strength (S = 1.84, p = 0.002) when comparing the binge eating with no binge-eating participants. However, network structure differences were sensitive to reductions in sample size and the greater density of the latter network was explained by the large proportion of participants (34%) without mania symptoms. The structure of the anorexia nervosa binge-eating/purging network differed from the bulimia nervosa network (M = 0.66, p = 0.001), but the result was unstable. CONCLUSIONS: Our results suggest that the presence and structure of mania symptoms may be more associated with binge eating as a symptom rather than any specific binge-type eating disorder. Further research with larger sample sizes is required to confirm our findings.

Risk and protective factors for new-onset binge eating, low weight, and self-harm symptoms in >35,000 individuals in the UK during the COVID-19 pandemic.

OBJECTIVE: The disruption caused by the COVID-19 pandemic has been associated with poor mental health, including increases in eating disorders and self-harm symptoms. We investigated risk and protective factors for the new onset of these symptoms during the pandemic. METHOD: Data were from the COVID-19 Psychiatry and Neurological Genetics study and the Repeated Assessment of Mental health in Pandemics Study (n = 36,715). Exposures were socio-demographic characteristics, lifetime psychiatric disorder, and COVID-related variables, including SARS-CoV-2 infection/illness with COVID-19. We identified four subsamples of participants without pre-pandemic experience of our outcomes: binge eating (n = 24,211), low weight (n = 24,364), suicidal and/or self-harm ideation (n = 18,040), and self-harm (n = 29,948). Participants reported on our outcomes at frequent intervals (fortnightly to monthly). We fitted multiple logistic regression models to identify factors associated with the new onset of our outcomes. RESULTS: Within each subsample, new onset was reported by: 21% for binge eating, 10.8% for low weight, 23.5% for suicidal and/or self-harm ideation, and 3.5% for self-harm. Shared risk factors included having a lifetime psychiatric disorder, not being in paid employment, higher pandemic worry scores, and being racially minoritized. Conversely, infection with SARS-CoV-2/illness with COVID-19 was linked to lower odds of binge eating, low weight, and suicidal and/or self-harm ideation. DISCUSSION: Overall, we detected shared risk factors that may drive the comorbidity between eating disorders and self-harm. Subgroups of individuals with these risk factors may require more frequent monitoring during future pandemics. PUBLIC SIGNIFICANCE: In a sample of 35,000 UK residents, people who had a psychiatric disorder, identified as being part of a racially minoritized group, were not in paid employment, or were more worried about the pandemic were more likely to experience binge eating, low weight, suicidal and/or self-harm ideation, and self-harm for the first time during the pandemic. People with these risk factors may need particular attention during future pandemics to enable early identification of new psychiatric symptoms.

The United Kingdom Eating Disorders Genetics Initiative.

OBJECTIVE: The United Kingdom Eating Disorders Genetics Initiative (EDGI UK), part of the National Institute for Health and Care Research (NIHR) Mental Health BioResource, aims to deepen our understanding of the environmental and genetic etiology of eating disorders. EDGI UK launched in February 2020 and is partnered with the UK eating disorders charity, Beat. Multiple EDGI branches exist worldwide. This article serves the dual function of providing an in-depth description of our study protocol and of describing our initial sample including demographics, diagnoses, and physical and psychiatric comorbidities. METHOD: EDGI UK recruits via media and clinical services. Anyone living in England, at least 16 years old, with a lifetime probable or clinical eating disorder is eligible to sign up online: edgiuk.org. Participants complete online questionnaires, donate a saliva sample for genetic analysis, and consent to medical record linkage and recontact for future studies. RESULTS: As of September 2022, EDGI UK recruited 7435 survey participants: 98% female, 93.1% white, 97.8% cisgender, 65.9% heterosexual, and 52.1% have a university degree. Over half (57.8%) of these participants have returned their saliva DNA kit. The most common diagnoses are anorexia nervosa (48.3%), purging disorder (37.8%), bulimia nervosa (37.5%), binge-eating disorder (15.8%), and atypical anorexia nervosa (7.8%). CONCLUSION: EDGI UK is the largest UK eating disorders study and efforts to increase its diversity are underway. It offers a unique opportunity to accelerate eating disorder research. Researchers and participants with lived experience can collaborate on projects with unparalleled sample size. PUBLIC SIGNIFICANCE STATEMENT: Eating disorders are debilitating and costly for society but are under-researched due to underfunding. EDGI UK is one of the largest eating disorder studies worldwide with ongoing recruitment. The collected data constitute a resource for secondary analysis. We will combine data from all international EDGI branches and the NIHR BioResource to facilitate research that improves our understanding of eating disorders and their comorbidities.

Sociodemographic, mental health, and physical health factors associated with participation within re-contactable mental health cohorts: an investigation of the GLAD Study.

BACKGROUND: The Genetic Links to Anxiety and Depression (GLAD) Study is a large cohort of individuals with lifetime anxiety and/or depression, designed to facilitate re-contact of participants for mental health research. At the start of the pandemic, participants from three cohorts, including the GLAD Study, were invited to join the COVID-19 Psychiatry and Neurological Genetics (COPING) study to monitor mental and neurological health. However, previous research suggests that participation in longitudinal studies follows a systematic, rather than random, process, which can ultimately bias results. Therefore, this study assessed participation biases following the re-contact of GLAD Study participants. METHODS: In April 2020, all current GLAD Study participants (N = 36,770) were invited to the COPING study. Using logistic regression, we investigated whether sociodemographic, mental, and physical health characteristics were associated with participation in the COPING baseline survey (aim one). Subsequently, we used a zero-inflated negative binomial regression to examine whether these factors were also related to participation in the COPING follow-up surveys (aim two). RESULTS: For aim one, older age, female gender identity, non-binary or self-defined gender identities, having one or more physical health disorders, and providing a saliva kit for the GLAD Study were associated with an increased odds of completing the COPING baseline survey. In contrast, lower educational attainment, Asian or Asian British ethnic identity, Black or Black British ethnic identity, higher alcohol consumption at the GLAD sign-up survey, and current or ex-smoking were associated with a reduced odds. For aim two, older age, female gender, and saliva kit provision were associated with greater COPING follow-up survey completion. Lower educational attainment, higher alcohol consumption at the GLAD Study sign-up, ex-smoking, and self-reported attention deficit hyperactivity disorder had negative relationships. CONCLUSIONS: Participation biases surrounding sociodemographic and physical health characteristics were particularly evident when re-contacting the GLAD Study volunteers. Factors associated with participation may vary depending on study design. Researchers should examine the barriers and mechanisms underlying participation bias in order to combat these issues and address recruitment biases in future studies.

Genetic examination of the Mood Disorder Questionnaire and its relationship with bipolar disorder.

The Mood Disorder Questionnaire (MDQ) is a common screening tool for bipolar disorder that assesses manic symptoms. Its utility for genetic studies of mania or bipolar traits has not been fully examined. We psychometrically compared the MDQ to self-reported bipolar disorder in participants from the United Kingdom National Institute of Health and Care Research Mental Health BioResource. We conducted genome-wide association studies of manic symptom quantitative traits and symptom subgroups, derived from the MDQ items (N = 11,568-19,859). We calculated genetic correlations with bipolar disorder and other psychiatric and behavioral traits. The MDQ screener showed low positive predictive value (0.29) for self-reported bipolar disorder. Neither concurrent nor lifetime manic symptoms were genetically correlated with bipolar disorder. Lifetime manic symptoms had a highest genetic correlation (rg = 1.0) with posttraumatic stress disorder although this was not confirmed by within-cohort phenotypic correlations (rp = 0.41). Other significant genetic correlations included attention deficit hyperactivity disorder (rg = 0.69), insomnia (rg = 0.55), and major depressive disorder (rg = 0.42). Our study adds to existing literature questioning the MDQ's validity and suggests it may capture symptoms of general distress or psychopathology, rather than hypomania/mania specifically, in at-risk populations.

Patient characteristics associated with retrospectively self-reported treatment outcomes following psychological therapy for anxiety or depressive disorders - a cohort of GLAD study participants.

BACKGROUND: Progress towards stratified care for anxiety and depression will require the identification of new predictors. We collected data on retrospectively self-reported therapeutic outcomes in adults who received psychological therapy in the UK in the past ten years. We aimed to replicate factors associated with traditional treatment outcome measures from the literature. METHODS: Participants were from the Genetic Links to Anxiety and Depression (GLAD) Study, a UK-based volunteer cohort study. We investigated associations between retrospectively self-reported outcomes following therapy, on a five-point scale (global rating of change; GRC) and a range of sociodemographic, clinical and therapy-related factors, using ordinal logistic regression models (n = 2890). RESULTS: Four factors were associated with therapy outcomes (adjusted odds ratios, OR). One sociodemographic factor, having university-level education, was associated with favourable outcomes (OR = 1.37, 95%CI: 1.18, 1.59). Two clinical factors, greater number of reported episodes of illness (OR = 0.95, 95%CI: 0.92, 0.97) and higher levels of personality disorder symptoms (OR = 0.89, 95%CI: 0.87, 0.91), were associated with less favourable outcomes. Finally, reported regular use of additional therapeutic activities was associated with favourable outcomes (OR = 1.39, 95%CI: 1.19, 1.63). There were no statistically significant differences between fully adjusted multivariable and unadjusted univariable odds ratios. CONCLUSION: Therapy outcome data can be collected quickly and inexpensively using retrospectively self-reported measures in large observational cohorts. Retrospectively self-reported therapy outcomes were associated with four factors previously reported in the literature. Similar data collected in larger observational cohorts may enable detection of novel associations with therapy outcomes, to generate new hypotheses, which can be followed up in prospective studies.

Eating disorder symptoms and their associations with anthropometric and psychiatric polygenic scores.

BACKGROUND: Eating disorder (ED) symptoms are prevalent in the general population, but their shared genetic underpinnings with psychiatric, metabolic, and anthropometric traits are not known. Here, we examined if polygenic scores (PGSs) of traits associated with anorexia nervosa are also associated with adolescent ED symptoms in the Avon Longitudinal Study of Parents and Children (ALSPAC). METHODS: A total of 8654 participants with genotype data and at least one phenotypic measure were included from the ALSPAC study. We associated PGS from 25 traits (16 psychiatric, 4 metabolic, and 5 anthropometric) with eight ED symptoms, including behaviours such as fasting for weight loss and cognitions such as body dissatisfaction. RESULTS: Higher attention deficit hyperactivity disorder PGS and lower educational attainment PGS were associated with fasting for weight loss. Higher insomnia PGS was associated with increased body dissatisfaction. We found no evidence of an association between metabolic trait PGS and any ED symptom. Fat-free mass, fat mass, and body fat percentage PGSs, were positively associated with binge eating, excessive exercise, fasting for weight loss, body dissatisfaction, and weight and shape concern. CONCLUSIONS: ED symptoms are genetically associated with psychiatric and anthropometric, but not with metabolic traits. Our findings provide insights for future genetic research investigating on why some individuals with ED symptoms progress to develop threshold EDs while others do not.

Psychological trauma and the genetic overlap between posttraumatic stress disorder and major depressive disorder.

BACKGROUND: Posttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD. METHODS: Genetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals. RESULTS: Genetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01-1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001). CONCLUSIONS: Our findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.

No Evidence for Passive Gene-Environment Correlation or the Influence of Genetic Risk for Psychiatric Disorders on Adult Body Composition via the Adoption Design.

The relationship between genetic and environmental risk is complex and for many traits, estimates of genetic effects may be inflated by passive gene-environment correlation. This arises because biological offspring inherit both their genotypes and rearing environment from their parents. We tested for passive gene-environment correlation in adult body composition traits using the 'natural experiment' of childhood adoption, which removes passive gene-environment correlation within families. Specifically, we compared 6165 adoptees with propensity score matched non-adoptees in the UK Biobank. We also tested whether passive gene-environment correlation inflates the association between psychiatric genetic risk and body composition. We found no evidence for inflation of heritability or polygenic scores in non-adoptees compared to adoptees for a range of body composition traits. Furthermore, polygenic risk scores for anorexia nervosa, attention-deficit/hyperactivity disorder and schizophrenia did not differ in their influence on body composition traits in adoptees and non-adoptees. These findings suggest that passive gene-environment correlation does not inflate genetic effects for body composition, or the influence of psychiatric disorder genetic risk on body composition. Our design does not look at passive gene-environment correlation in childhood, and does not test for 'pure' environmental effects or the effects of active and evocative gene-environment correlations, where child genetics directly influences home environment. However, these findings suggest that genetic influences identified for body composition in this adult sample are direct, and not confounded by the family environment provided by biological relatives.

Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank.

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

A major role for common genetic variation in anxiety disorders.

Anxiety disorders are common, complex psychiatric disorders with twin heritabilities of 30-60%. We conducted a genome-wide association study of Lifetime Anxiety Disorder (ncase = 25 453, ncontrol = 58 113) and an additional analysis of Current Anxiety Symptoms (ncase = 19 012, ncontrol = 58 113). The liability scale common variant heritability estimate for Lifetime Anxiety Disorder was 26%, and for Current Anxiety Symptoms was 31%. Five novel genome-wide significant loci were identified including an intergenic region on chromosome 9 that has previously been associated with neuroticism, and a locus overlapping the BDNF receptor gene, NTRK2. Anxiety showed significant positive genetic correlations with depression and insomnia as well as coronary artery disease, mirroring findings from epidemiological studies. We conclude that common genetic variation accounts for a substantive proportion of the genetic architecture underlying anxiety.

Age and sex-related variability in the presentation of generalized anxiety and depression symptoms.

BACKGROUND: Generalized anxiety and depression are extremely prevalent and debilitating. There is evidence for age and sex variability in symptoms of depression, but despite comorbidity it is unclear whether this extends to anxiety symptomatology. Studies using questionnaire sum scores typically fail to address this phenotypic complexity. METHOD: We conducted exploratory and confirmatory factor analyses on Generalized Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9) items to identify latent factors of anxiety and depression in participants from the Genetic Links to Anxiety and Depression Study (N = 35,637; 16-93 years). We assessed age- and sex-related variability in latent factors and individual symptoms using multiple logistic regression. RESULTS: Four factors of mood, worry, motor, and somatic symptoms were identified (comparative fit index [CFI] = 0.99, Tucker-Lewis Index [TLI] = 0.99, root mean square error of approximation [RMSEA] = 0.07, standardized root mean square residuals [SRMR] = 0.04). Symptoms of irritability (odds ratio [OR] = 0.81) were most strongly associated with younger age, and sleep change (OR = 1.14) with older age. Males were more likely to report mood and motor symptoms (p < .001) and females to report somatic symptoms (p < .001). CONCLUSION: Significant age and sex variability suggest that classic diagnostic criteria reflect the presentation most commonly seen in younger males. This study provides avenues for diagnostic adaptation and factor-specific interventions.

One size does not fit all. Genomics differentiates among anorexia nervosa, bulimia nervosa, and binge-eating disorder.

OBJECTIVE: Genome-wide association studies have identified multiple genomic regions associated with anorexia nervosa. No genome-wide studies of other eating disorders, such as bulimia nervosa and binge-eating disorder, have been performed, despite their substantial heritability. Exploratively, we aimed to identify traits that are genetically associated with binge-type eating disorders. METHOD: We calculated genome-wide polygenic scores for 269 trait and disease outcomes using PRSice v2.2 and their association with anorexia nervosa, bulimia nervosa, and binge-eating disorder in up to 640 cases and 17,050 controls from the UK Biobank. Significant associations were tested for replication in the Avon Longitudinal Study of Parents and Children (up to 217 cases and 3,018 controls). RESULTS: Individuals with binge-type eating disorders had higher polygenic scores than controls for other psychiatric disorders, including depression, schizophrenia, and attention deficit hyperactivity disorder, and higher polygenic scores for body mass index. DISCUSSION: Our findings replicate some of the known comorbidities of eating disorders on a genomic level and motivate a deeper investigation of shared and unique genomic factors across the three primary eating disorders.

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

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Self-reported medication use as an alternate phenotyping method for anxiety and depression in the UK Biobank.

The requirement for large sample sizes for psychiatric genetic analyses necessitates novel approaches to derive cases. Anxiety and depression show substantial genetic overlap and share pharmacological treatments. Data on prescribed medication could be effective for inferring case status when other indicators of mental health are unavailable. We investigated self-reported current medication use in UK Biobank participants of European ancestry. Medication Status cases reported using antidepressant or anxiolytic medication (n = 22,218), controls did not report psychotropic medication use (n = 168,959). A subset, "Medication Only," additionally did not meet criteria for any other mental health indicator (case n = 2,643, control n = 107,029). We assessed genetic overlap between these phenotypes and two published genetic association studies of anxiety and depression, and an internalizing disorder trait derived from symptom-based questionnaires in UK Biobank. Genetic correlations between Medication Status and the three anxiety and depression phenotypes were significant (rg  = 0.60-0.73). In the Medication Only subset, the genetic correlation with depression was significant (rg  = 0.51). The three polygenic scores explained 0.33% - 0.80% of the variance in Medication Status and 0.07% - 0.19% of the variance in Medication Only. This study provides evidence that self-reported current medication use offers an alternate or supplementary anxiety or depression phenotype in genetic studies where diagnostic information is sparse or unavailable.

Eating behavior trajectories in the first 10 years of life and their relationship with BMI.

BACKGROUND: Child eating behaviors are highly heterogeneous and their longitudinal impact on childhood weight is unclear. The objective of this study was to characterize eating behaviors during the first 10 years of life and evaluate associations with BMI at age 11 years. METHOD: Data were parental reports of eating behaviors from 15 months to age 10 years (n = 12,048) and standardized body mass index (zBMI) at age 11 years (n = 4884) from the Avon Longitudinal Study of Parents and Children. Latent class growth analysis was used to derive latent classes of over-, under-, and fussy-eating. Linear regression models for zBMI at 11 years on each set of classes were fitted to assess associations with eating behavior trajectories. RESULTS: We identified four classes of overeating; "low stable" (70%), "low transient" (15%), "late increasing" (11%), and "early increasing" (6%). The "early increasing" class was associated with higher zBMI (boys: ß = 0.83, 95% CI: 0.65, 1.02; girls: ß = 1.1; 0.92, 1.28) compared with "low stable." Six classes were found for undereating; "low stable" (25%), "low transient" (37%), "low decreasing" (21%), "high transient" (11%), "high decreasing" (4%), and "high stable" (2%). The latter was associated with lower zBMI (boys: ß = -0.79; -1.15, -0.42; girls: ß = -0.76; -1.06, -0.45). Six classes were found for fussy eating; "low stable" (23%), "low transient" (15%), "low increasing" (28%), "high decreasing" (14%), "low increasing" (13%), and "high stable" (8%). The "high stable" class was associated with lower zBMI (boys: ß = -0.49; -0.68-0.30; girls: ß = -0.35; -0.52, -0.18). CONCLUSIONS: Early increasing overeating during childhood is associated with higher zBMI at age 11. High persistent levels of undereating and fussy eating are associated with lower zBMI. Longitudinal trajectories of eating behaviors may help identify children potentially at risk of adverse weight outcomes.

Drug Targetor: a web interface to investigate the human druggome for over 500 phenotypes.

SUMMARY: Results from hundreds of genome-wide association studies (GWAS) are now freely available and offer a catalogue of the association between phenotypes across medicine with variants in the genome. With the aim of using this data to better understand therapeutic mechanisms, we have developed Drug Targetor, a web interface that allows the generation and exploration of drug-target networks of hundreds of phenotypes using GWAS data. Drug Targetor networks consist of drug and target nodes ordered by genetic association and connected by drug-target or drug-gene relationship. We show that Drug Targetor can help prioritize drugs, targets and drug-target interactions for a specific phenotype based on genetic evidence. AVAILABILITY AND IMPLEMENTATION: Drug Targetor v1.21 is a web application freely available online at drugtargetor.com and under MIT licence. The source code can be found at https://github.com/hagax8/drugtargetor. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A longitudinal study of eating behaviours in childhood and later eating disorder behaviours and diagnoses.

BACKGROUND: Eating behaviours in childhood are considered as risk factors for eating disorder behaviours and diagnoses in adolescence. However, few longitudinal studies have examined this association. AIMS: We investigated associations between childhood eating behaviours during the first ten years of life and eating disorder behaviours (binge eating, purging, fasting and excessive exercise) and diagnoses (anorexia nervosa, binge eating disorder, purging disorder and bulimia nervosa) at 16 years. METHOD: Data on 4760 participants from the Avon Longitudinal Study of Parents and Children were included. Longitudinal trajectories of parent-rated childhood eating behaviours (8 time points, 1.3-9 years) were derived by latent class growth analyses. Eating disorder diagnoses were derived from self-reported, parent-reported and objectively measured anthropometric data at age 16 years. We estimated associations between childhood eating behaviours and eating disorder behaviours and diagnoses, using multivariable logistic regression models. RESULTS: Childhood overeating was associated with increased risk of adolescent binge eating (risk difference, 7%; 95% CI 2 to 12) and binge eating disorder (risk difference, 1%; 95% CI 0.2 to 3). Persistent undereating was associated with higher anorexia nervosa risk in adolescent girls only (risk difference, 6%; 95% CI, 0 to 12). Persistent fussy eating was associated with greater anorexia nervosa risk (risk difference, 2%; 95% CI 0 to 4). CONCLUSIONS: Our results suggest continuities of eating behaviours into eating disorders from early life to adolescence. It remains to be determined whether childhood eating behaviours are an early manifestation of a specific phenotype or whether the mechanisms underlying this continuity are more complex. Findings have the potential to inform preventative strategies for eating disorders.