Roseann E. Peterson

Binge Eating Disorder Mediates Links between Symptoms of Depression, Anxiety, and Caloric Intake in Overweight and Obese Women

Despite considerable comorbidity between mood disorders, binge eating disorder (BED), and obesity, the underlying mechanisms remain unresolved. Therefore, the purpose of this study was to examine models by which internalizing behaviors of depression and anxiety influence food intake in overweight/obese women. Thirty-two women (15 BED, 17 controls) participated in a laboratory eating-episode and completed questionnaires assessing symptoms of anxiety and depression. Path analysis was used to test mediation and moderation models to determine the mechanisms by which internalizing symptoms influenced kilocalorie (kcal) intake. The BED group endorsed significantly more symptoms of depression (10.1 versus 4.8, P = 0.005 ) and anxiety (8.5 versus 2.7, P = 0.003). Linear regression indicated that BED diagnosis and internalizing symptoms accounted for 30% of the variance in kcal intake. Results from path analysis suggested that BED mediates the influence of internalizing symptoms on total kcal intake (empirical P < 0.001 ). The associations between internalizing symptoms and food intake are best described as operating indirectly through a BED diagnosis. This suggests that symptoms of depression and anxiety influence whether one engages in binge eating, which influences kcal intake. Greater understanding of the mechanisms underlying the associations between mood, binge eating, and food intake will facilitate the development of more effective prevention and treatment strategies for both BED and obesity.

Genome-Wide Meta-Analysis of Cotinine Levels in Cigarette Smokers Identifies Locus at 4q13.2.

Genome-wide association studies (GWAS) of complex behavioural phenotypes such as cigarette smoking typically employ self-report phenotypes. However, precise biomarker phenotypes may afford greater statistical power and identify novel variants. Here we report the results of a GWAS meta-analysis of levels of cotinine, the primary metabolite of nicotine, in 4,548 daily smokers of European ancestry. We identified a locus close to UGT2B10 at 4q13.2 (minimum p = 5.89 × 10−10 for rs114612145), which was consequently replicated. This variant is in high linkage disequilibrium with a known functional variant in the UGT2B10 gene which is associated with reduced nicotine and cotinine glucuronidation activity, but intriguingly is not associated with nicotine intake. Additionally, we observed association between multiple variants within the 15q25.1 region and cotinine levels, all located within the CHRNA5-A3-B4 gene cluster or adjacent genes, consistent with previous much larger GWAS using self-report measures of smoking quantity. These results clearly illustrate the increase in power afforded by using precise biomarker measures in GWAS. Perhaps more importantly however, they also highlight that biomarkers do not always mark the phenotype of interest. The use of metabolite data as a proxy for environmental exposures should be carefully considered in the context of individual differences in metabolic pathways.

Comparisons of Energy Intake and Energy Expenditure in Overweight and Obese Women With and Without Binge Eating Disorder

The purpose of this study was to determine whether there are differences in energy intake or energy expenditure that distinguish overweight/obese women with and without binge eating disorder (BED). Seventeen overweight/obese women with BED and 17 overweight/obese controls completed random 24‐h dietary recall interviews, and had total daily energy expenditure (TDEE) assessed by the doubly labeled water (DLW) technique with concurrent food log data collection. Participants received two baseline dual‐energy X‐ray absorptiometry (DXA) scans and had basal metabolic rate (BMR) and thermic effect of food (TEF) measured using indirect calorimetry. Results indicated no between group differences in TDEE, BMR, and TEF. As in our previous work, according to dietary recall data, the BED group had significantly higher caloric intake on days when they had binge eating episodes than on days when they did not (3,255 vs. 2,343 kcal). There was no difference between BED nonbinge day intake and control group intake (2,233 vs. 2,140 kcal). Similar results were found for food log data. Dietary recall data indicated a trend toward higher average daily intake in the BED group (2,587 vs. 2,140 kcal). Furthermore, when comparing TDEE to dietary recall and food log data, both groups displayed significant under‐reporting of caloric intake of similar magnitudes ranging from 20 to 33%. Predicted energy requirements estimated via the Harris—Benedict equation (HBE) underestimated measured TDEE by 23–24%. Our data suggest that increased energy intake reported by BED individuals is due to increased food consumption and not metabolic or under‐reporting differences.

On the association of common and rare genetic variation influencing body mass index: a combined SNP and CNV analysis

BackgroundAs the architecture of complex traits incorporates a widening spectrum of genetic variation, analyses integrating common and rare variation are needed. Body mass index (BMI) represents a model trait, since common variation shows robust association but accounts for a fraction of the heritability. A combined analysis of single nucleotide polymorphisms (SNP) and copy number variation (CNV) was performed using 1850 European and 498 African-Americans from the Study of Addiction: Genetics and Environment. Genetic risk sum scores (GRSS) were constructed using 32 BMI-validated SNPs and aggregate-risk methods were compared: count versus weighted and proxy versus imputation.ResultsThe weighted SNP-GRSS constructed from imputed probabilities of risk alleles performed best and was highly associated with BMI (p = 4.3×10−16) accounting for 3% of the phenotypic variance. In addition to BMI-validated SNPs, common and rare BMI/obesity-associated CNVs were identified from the literature. Of the 84 CNVs previously reported, only 21-kilobase deletions on 16p12.3 showed evidence for association with BMI (p = 0.003, frequency = 16.9%), with two CNVs nominally associated with class II obesity, 1p36.1 duplications (OR = 3.1, p = 0.009, frequency 1.2%) and 5q13.2 deletions (OR = 1.5, p = 0.048, frequency 7.7%). All other CNVs, individually and in aggregate, were not associated with BMI or obesity. The combined model, including covariates, SNP-GRSS, and 16p12.3 deletion accounted for 11.5% of phenotypic variance in BMI (3.2% from genetic effects). Models significantly predicted obesity classification with maximum discriminative ability for morbid-obesity (p = 3.15×10−18).ConclusionResults show that incorporating validated effect sizes and allelic probabilities improve prediction algorithms. Although rare-CNVs did not account for significant phenotypic variation, results provide a framework for integrated analyses.

The Genetic Architecture of Major Depressive Disorder in Han Chinese Women

Importance Despite the moderate, well-demonstrated heritability of major depressive disorder (MDD), there has been limited success in identifying replicable genetic risk loci, suggesting a complex genetic architecture. Research is needed to quantify the relative contribution of classes of genetic variation across the genome to inform future genetic studies of MDD. Objectives To apply aggregate genetic risk methods to clarify the genetic architecture of MDD by estimating and partitioning heritability by chromosome, minor allele frequency, and functional annotations and to test for enrichment of rare deleterious variants. Design, Setting, and Participants The CONVERGE (China, Oxford, and Virginia Commonwealth University Experimental Research on Genetic Epidemiology) study collected data on 5278 patients with recurrent MDD from 58 provincial mental health centers and psychiatric departments of general medical hospitals in 45 cities and 23 provinces of China. Screened controls (n = 5196) were recruited from a range of locations, including general hospitals and local community centers. Data were collected from August 1, 2008, to October 31, 2012. Main Outcomes and Measures Genetic risk for liability to recurrent MDD was partitioned using sparse whole-genome sequencing. Results In aggregate, common single-nucleotide polymorphisms (SNPs) explained between 20% and 29% of the variance in MDD risk, and the heritability in MDD explained by each chromosome was proportional to its length (r = 0.680; P = .0003), supporting a common polygenic etiology. Partitioning heritability by minor allele frequency indicated that the variance explained was distributed across the allelic frequency spectrum, although relatively common SNPs accounted for a disproportionate fraction of risk. Partitioning by genic annotation indicated a greater contribution of SNPs in protein-coding regions and within 3′-UTR regions of genes. Enrichment of SNPs associated with DNase I-hypersensitive sites was also found in many tissue types, including brain tissue. Examining burden scores from singleton exonic SNPs predicted to be deleterious indicated that cases had significantly more mutations than controls (odds ratio, 1.009; 95% CI, 1.003-1.014; P = .003), including those occurring in genes expressed in the brain (odds ratio, 1.011; 95% CI, 1.003-1.018; P = .004) and within nuclear-encoded genes with mitochondrial gene products (odds ratio, 1.075; 95% CI, 1.018-1.135; P = .009). Conclusions and Relevance Results support a complex etiology for MDD and highlight the value of analyzing components of heritability to clarify genetic architecture.

Genetic effects influencing risk for major depressive disorder in China and Europe

Major depressive disorder (MDD) is a common, complex psychiatric disorder and a leading cause of disability worldwide. Despite twin studies indicating its modest heritability (~30–40%), extensive heterogeneity and a complex genetic architecture have complicated efforts to detect associated genetic risk variants. We combined single-nucleotide polymorphism (SNP) summary statistics from the CONVERGE and PGC studies of MDD, representing 10 502 Chinese (5282 cases and 5220 controls) and 18 663 European (9447 cases and 9215 controls) subjects. We determined the fraction of SNPs displaying consistent directions of effect, assessed the significance of polygenic risk scores and estimated the genetic correlation of MDD across ancestries. Subsequent trans-ancestry meta-analyses combined SNP-level evidence of association. Sign tests and polygenic score profiling weakly support an overlap of SNP effects between East Asian and European populations. We estimated the trans-ancestry genetic correlation of lifetime MDD as 0.33; female-only and recurrent MDD yielded estimates of 0.40 and 0.41, respectively. Common variants downstream of GPHN achieved genome-wide significance by Bayesian trans-ancestry meta-analysis (rs9323497; log10 Bayes Factor=8.08) but failed to replicate in an independent European sample (P=0.911). Gene-set enrichment analyses indicate enrichment of genes involved in neuronal development and axonal trafficking. We successfully demonstrate a partially shared polygenic basis of MDD in East Asian and European populations. Taken together, these findings support a complex etiology for MDD and possible population differences in predisposing genetic factors, with important implications for future genetic studies.

SNP-based heritability estimates of the personality dimensions and polygenic prediction of both neuroticism and major depression: findings from CONVERGE.

Biometrical genetic studies suggest that the personality dimensions, including neuroticism, are moderately heritable (~0.4 to 0.6). Quantitative analyses that aggregate the effects of many common variants have recently further informed genetic research on European samples. However, there has been limited research to date on non-European populations. This study examined the personality dimensions in a large sample of Han Chinese descent (N=10 064) from the China, Oxford, and VCU Experimental Research on Genetic Epidemiology study, aimed at identifying genetic risk factors for recurrent major depression among a rigorously ascertained cohort. Heritability of neuroticism as measured by the Eysenck Personality Questionnaire (EPQ) was estimated to be low but statistically significant at 10% (s.e.=0.03, P=0.0001). In addition to EPQ, neuroticism based on a three-factor model, data for the Big Five (BF) personality dimensions (neuroticism, openness, conscientiousness, extraversion and agreeableness) measured by the Big Five Inventory were available for controls (n=5596). Heritability estimates of the BF were not statistically significant despite high power (>0.85) to detect heritabilities of 0.10. Polygenic risk scores constructed by best linear unbiased prediction weights applied to split-half samples failed to significantly predict any of the personality traits, but polygenic risk for neuroticism, calculated with LDpred and based on predictive variants previously identified from European populations (N=171 911), significantly predicted major depressive disorder case–control status (P=0.0004) after false discovery rate correction. The scores also significantly predicted EPQ neuroticism (P=6.3 × 10−6). Factor analytic results of the measures indicated that any differences in heritabilities across samples may be due to genetic variation or variation in haplotype structure between samples, rather than measurement non-invariance. Findings demonstrate that neuroticism can be significantly predicted across ancestry, and highlight the importance of studying polygenic contributions to personality in non-European populations.

11,670 whole-genome sequences representative of the Han Chinese population from the CONVERGE project

The China, Oxford and Virginia Commonwealth University Experimental Research on Genetic Epidemiology (CONVERGE) project on Major Depressive Disorder (MDD) sequenced 11,670 female Han Chinese at low-coverage (1.7X), providing the first large-scale whole genome sequencing resource representative of the largest ethnic group in the world. Samples are collected from 58 hospitals from 23 provinces around China. We are able to call 22 million high quality single nucleotide polymorphisms (SNP) from the nuclear genome, representing the largest SNP call set from an East Asian population to date. We use these variants for imputation of genotypes across all samples, and this has allowed us to perform a successful genome wide association study (GWAS) on MDD. The utility of these data can be extended to studies of genetic ancestry in the Han Chinese and evolutionary genetics when integrated with data from other populations. Molecular phenotypes, such as copy number variations and structural variations can be detected, quantified and analysed in similar ways. Design Type(s) individual genetic characteristics comparison design • clinical history design Measurement Type(s) whole genome sequencing • genetic sequence variation analysis Technology Type(s) DNA sequencing • Whole Genome Association Study Factor Type(s) diagnosis Sample Characteristic(s) Homo sapiens • saliva • Liaoning Province • Hebei Province • Heilongjiang Province • Municipality of Beijing • Jilin Province • Hunan Province • Sichuan Province • Municipality of Chongqing • Fujian Province • Guangdong Province • Hainan Province • Zhejiang Province • Anhui Province • Jiangsu Province • Shandong Province • Gansu Province • Guangxi Zhuang Autonomous Region • Jiangxi Province • Municipality of Shanghai • Shaanxi Province • Municipality of Tianjin • Hubei Province • Henan Province Design Type(s) individual genetic characteristics comparison design • clinical history design Measurement Type(s) whole genome sequencing • genetic sequence variation analysis Technology Type(s) DNA sequencing • Whole Genome Association Study Factor Type(s) diagnosis Sample Characteristic(s) Homo sapiens • saliva • Liaoning Province • Hebei Province • Heilongjiang Province • Municipality of Beijing • Jilin Province • Hunan Province • Sichuan Province • Municipality of Chongqing • Fujian Province • Guangdong Province • Hainan Province • Zhejiang Province • Anhui Province • Jiangsu Province • Shandong Province • Gansu Province • Guangxi Zhuang Autonomous Region • Jiangxi Province • Municipality of Shanghai • Shaanxi Province • Municipality of Tianjin • Hubei Province • Henan Province Machine-accessible metadata file describing the reported data (ISA-Tab format)

Deep Sequencing of Three Loci Implicated in Large-Scale Genome-Wide Association Study Smoking Meta-Analyses.

INTRODUCTION Genome-wide association study meta-analyses have robustly implicated three loci that affect susceptibility for smoking: CHRNA5\CHRNA3\CHRNB4, CHRNB3\CHRNA6 and EGLN2\CYP2A6. Functional follow-up studies of these loci are needed to provide insight into biological mechanisms. However, these efforts have been hampered by a lack of knowledge about the specific causal variant(s) involved. In this study, we prioritized variants in terms of the likelihood they account for the reported associations. METHODS We employed targeted capture of the CHRNA5\CHRNA3\CHRNB4, CHRNB3\CHRNA6, and EGLN2\CYP2A6 loci and flanking regions followed by next-generation deep sequencing (mean coverage 78×) to capture genomic variation in 363 individuals. We performed single locus tests to determine if any single variant accounts for the association, and examined if sets of (rare) variants that overlapped with biologically meaningful annotations account for the associations. RESULTS In total, we investigated 963 variants, of which 71.1% were rare (minor allele frequency < 0.01), 6.02% were insertion/deletions, and 51.7% were catalogued in dbSNP141. The single variant results showed that no variant fully accounts for the association in any region. In the variant set results, CHRNB4 accounts for most of the signal with significant sets consisting of directly damaging variants. CHRNA6 explains most of the signal in the CHRNB3\CHRNA6 locus with significant sets indicating a regulatory role for CHRNA6. Significant sets in CYP2A6 involved directly damaging variants while the significant variant sets suggested a regulatory role for EGLN2. CONCLUSIONS We found that multiple variants implicating multiple processes explain the signal. Some variants can be prioritized for functional follow-up.

Rapporteur summaries of plenary, symposia, and oral sessions from the XXIIIrd World Congress of Psychiatric Genetics Meeting in Toronto, Canada, 16-20 October 2015

The XXIIIrd World Congress of Psychiatric Genetics meeting, sponsored by the International Society of Psychiatric Genetics, was held in Toronto, ON, Canada, on 16–20 October 2015. Approximately 700 participants attended to discuss the latest state-of-the-art findings in this rapidly advancing and evolving field. The following report was written by trainee travel awardees. Each was assigned one session as a rapporteur. This manuscript represents the highlights and topics that were covered in the plenary sessions, symposia, and oral sessions during the conference, and contains major notable and new findings.