Exploring the overlap between alopecia areata and major depressive disorder: Epidemiological and genetic perspectives.

BACKGROUND: Research suggests that Alopecia areata (AA) and Major Depressive Disorder (MDD) show substantial comorbidity. To date, no study has investigated the hypothesis that this is attributable to shared genetic aetiology. OBJECTIVES: To investigate AA-MDD comorbidity on the epidemiological and molecular genetic levels. METHODS: First, epidemiological analyses were performed using data from a cohort of adult German health insurance beneficiaries (n = 1.855 million) to determine the population-based prevalence of AA-MDD comorbidity. Second, analyses were performed to determine the prevalence of MDD in a clinical AA case-control sample with data on psychiatric phenotypes, stratifying for demographic factors to identify possible contributing factors to AA-MDD comorbidity. Third, the genetic overlap between AA and MDD was investigated using a polygenic risk score (PRS) approach and linkage disequilibrium score (LDSC) regression. For PRS, summary statistics from a large MDD GWAS meta-analysis (PGC-MD2) were used as the training sample, while a Central European AA cohort, including the above-mentioned AA patients, and an independent replication US-AA cohort were used as target samples. LDSC was performed using summary statistics of PGC-MD2 and the largest AA meta-analysis to date. RESULTS: High levels of AA-MDD comorbidity were reported in the population-based (MDD in 24% of AA patients), and clinical samples (MDD in 44% of AA patients). MDD-PRS explained a modest proportion of variance in AA case-control status (R2  = 1%). This signal was limited to the major histocompatibility complex (MHC) region on chromosome 6. LDSC regression (excluding MHC) revealed no significant genetic correlation between AA and MDD. CONCLUSIONS: As in previous research, AA patients showed an increased prevalence of MDD. The present analyses suggest that genetic overlap may be confined to the MHC region, which is implicated in immune function. More detailed investigation is required to refine understanding of how the MHC is involved in the development of AA and MDD comorbidity.

Genome-wide association analyses of symptom severity among clozapine-treated patients with schizophrenia spectrum disorders.

Clozapine is the most effective antipsychotic for patients with treatment-resistant schizophrenia. However, response is highly variable and possible genetic underpinnings of this variability remain unknown. Here, we performed polygenic risk score (PRS) analyses to estimate the amount of variance in symptom severity among clozapine-treated patients explained by PRSs (R2) and examined the association between symptom severity and genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activity. Genome-wide association (GWA) analyses were performed to explore loci associated with symptom severity. A multicenter cohort of 804 patients (after quality control N = 684) with schizophrenia spectrum disorder treated with clozapine were cross-sectionally assessed using the Positive and Negative Syndrome Scale and/or the Clinical Global Impression-Severity (CGI-S) scale. GWA and PRS regression analyses were conducted. Genotype-predicted CYP1A2, CYP2D6, and CYP2C19 enzyme activities were calculated. Schizophrenia-PRS was most significantly and positively associated with low symptom severity (p = 1.03 × 10-3; R2 = 1.85). Cross-disorder-PRS was also positively associated with lower CGI-S score (p = 0.01; R2 = 0.81). Compared to the lowest tertile, patients in the highest schizophrenia-PRS tertile had 1.94 times (p = 6.84×10-4) increased probability of low symptom severity. Higher genotype-predicted CYP2C19 enzyme activity was independently associated with lower symptom severity (p = 8.44×10-3). While no locus surpassed the genome-wide significance threshold, rs1923778 within NFIB showed a suggestive association (p = 3.78×10-7) with symptom severity. We show that high schizophrenia-PRS and genotype-predicted CYP2C19 enzyme activity are independently associated with lower symptom severity among individuals treated with clozapine. Our findings open avenues for future pharmacogenomic projects investigating the potential of PRS and genotype-predicted CYP-activity in schizophrenia.

Increasing sample diversity in psychiatric genetics - Introducing a new cohort of patients with schizophrenia and controls from Vietnam - Results from a pilot study.

OBJECTIVES: Genome-Wide Association Studies (GWAS) of Schizophrenia (SCZ) have provided new biological insights; however, most cohorts are of European ancestry. As a result, derived polygenic risk scores (PRS) show decreased predictive power when applied to populations of different ancestries. We aimed to assess the feasibility of a large-scale data collection in Hanoi, Vietnam, contribute to international efforts to diversify ancestry in SCZ genetic research and examine the transferability of SCZ-PRS to individuals of Vietnamese Kinh ancestry. METHODS: In a pilot study, 368 individuals (including 190 SCZ cases) were recruited at the Hanoi Medical University's associated psychiatric hospitals and outpatient facilities. Data collection included sociodemographic data, baseline clinical data, clinical interviews assessing symptom severity and genome-wide SNP genotyping. SCZ-PRS were generated using different training data sets: (i) European, (ii) East-Asian and (iii) trans-ancestry GWAS summary statistics from the latest SCZ GWAS meta-analysis. RESULTS: SCZ-PRS significantly predicted case status in Vietnamese individuals using mixed-ancestry (R2 liability = 4.9%, p = 6.83 × 10-8), East-Asian (R2 liability = 4.5%, p = 2.73 × 10-7) and European (R2 liability = 3.8%, p = 1.79 × 10-6) discovery samples. DISCUSSION: Our results corroborate previous findings of reduced PRS predictive power across populations, highlighting the importance of ancestral diversity in GWA studies.

Genome-wide association study results for educational attainment aid in identifying genetic heterogeneity of schizophrenia.

Higher educational attainment (EA) is negatively associated with schizophrenia (SZ). However, recent studies found a positive genetic correlation between EA and SZ. We investigate possible causes of this counterintuitive finding using genome-wide association study results for EA and SZ (N = 443,581) and a replication cohort (1169 controls; 1067 cases) with deeply phenotyped SZ patients. We find strong genetic dependence between EA and SZ that cannot be explained by chance, linkage disequilibrium, or assortative mating. Instead, several genes seem to have pleiotropic effects on EA and SZ, but without a clear pattern of sign concordance. Using EA as a proxy phenotype, we isolate FOXO6 and SLITRK1 as novel candidate genes for SZ. Our results reveal that current SZ diagnoses aggregate over at least two disease subtypes: one part resembles high intelligence and bipolar disorder (BIP), while the other part is a cognitive disorder that is independent of BIP.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

This corrects the article DOI: 10.1038/mp.2016.97.

A direct test of the diathesis-stress model for depression.

The diathesis-stress theory for depression states that the effects of stress on the depression risk are dependent on the diathesis or vulnerability, implying multiplicative interactive effects on the liability scale. We used polygenic risk scores for major depressive disorder (MDD) calculated from the results of the most recent analysis from the Psychiatric Genomics Consortium as a direct measure of the vulnerability for depression in a sample of 5221 individuals from 3083 families. In the same we also had measures of stressful life events and social support and a depression symptom score, as well as DSM-IV MDD diagnoses for most individuals. In order to estimate the variance in depression explained by the genetic vulnerability, the stressors and their interactions, we fitted linear mixed models controlling for relatedness for the whole sample as well as stratified by sex. We show a significant interaction of the polygenic risk scores with personal life events (0.12% of variance explained, P-value=0.0076) contributing positively to the risk of depression. Additionally, our results suggest possible differences in the aetiology of depression between women and men. In conclusion, our findings point to an extra risk for individuals with combined vulnerability and high number of reported personal life events beyond what would be expected from the additive contributions of these factors to the liability for depression, supporting the multiplicative diathesis-stress model for this disease.

Largest GWAS of PTSD (N=20 070) yields genetic overlap with schizophrenia and sex differences in heritability.

The Psychiatric Genomics Consortium-Posttraumatic Stress Disorder group (PGC-PTSD) combined genome-wide case-control molecular genetic data across 11 multiethnic studies to quantify PTSD heritability, to examine potential shared genetic risk with schizophrenia, bipolar disorder, and major depressive disorder and to identify risk loci for PTSD. Examining 20 730 individuals, we report a molecular genetics-based heritability estimate (h2SNP) for European-American females of 29% that is similar to h2SNP for schizophrenia and is substantially higher than h2SNP in European-American males (estimate not distinguishable from zero). We found strong evidence of overlapping genetic risk between PTSD and schizophrenia along with more modest evidence of overlap with bipolar and major depressive disorder. No single-nucleotide polymorphisms (SNPs) exceeded genome-wide significance in the transethnic (overall) meta-analysis and we do not replicate previously reported associations. Still, SNP-level summary statistics made available here afford the best-available molecular genetic index of PTSD-for both European- and African-American individuals-and can be used in polygenic risk prediction and genetic correlation studies of diverse phenotypes. Publication of summary statistics for ∼10 000 African Americans contributes to the broader goal of increased ancestral diversity in genomic data resources. In sum, the results demonstrate genetic influences on the development of PTSD, identify shared genetic risk between PTSD and other psychiatric disorders and highlight the importance of multiethnic/racial samples. As has been the case with schizophrenia and other complex genetic disorders, larger sample sizes are needed to identify specific risk loci.

ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties.

Difficulties in social communication are part of the phenotypic overlap between autism spectrum disorders (ASD) and schizophrenia. Both conditions follow, however, distinct developmental patterns. Symptoms of ASD typically occur during early childhood, whereas most symptoms characteristic of schizophrenia do not appear before early adulthood. We investigated whether overlap in common genetic influences between these clinical conditions and impairments in social communication depends on the developmental stage of the assessed trait. Social communication difficulties were measured in typically-developing youth (Avon Longitudinal Study of Parents and Children, N⩽5553, longitudinal assessments at 8, 11, 14 and 17 years) using the Social Communication Disorder Checklist. Data on clinical ASD (PGC-ASD: 5305 cases, 5305 pseudo-controls; iPSYCH-ASD: 7783 cases, 11 359 controls) and schizophrenia (PGC-SCZ2: 34 241 cases, 45 604 controls, 1235 trios) were either obtained through the Psychiatric Genomics Consortium (PGC) or the Danish iPSYCH project. Overlap in genetic influences between ASD and social communication difficulties during development decreased with age, both in the PGC-ASD and the iPSYCH-ASD sample. Genetic overlap between schizophrenia and social communication difficulties, by contrast, persisted across age, as observed within two independent PGC-SCZ2 subsamples, and showed an increase in magnitude for traits assessed during later adolescence. ASD- and schizophrenia-related polygenic effects were unrelated to each other and changes in trait-disorder links reflect the heterogeneity of genetic factors influencing social communication difficulties during childhood versus later adolescence. Thus, both clinical ASD and schizophrenia share some genetic influences with impairments in social communication, but reveal distinct developmental profiles in their genetic links, consistent with the onset of clinical symptoms.

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.

Functional neuroimaging effects of recently discovered genetic risk loci for schizophrenia and polygenic risk profile in five RDoC subdomains.

Recently, 125 loci with genome-wide support for association with schizophrenia were identified. We investigated the impact of these variants and their accumulated genetic risk on brain activation in five neurocognitive domains of the Research Domain Criteria (working memory, reward processing, episodic memory, social cognition and emotion processing). In 578 healthy subjects we tested for association (i) of a polygenic risk profile score (RPS) including all single-nucleotide polymorphisms (SNPs) reaching genome-wide significance in the recent genome-wide association studies (GWAS) meta-analysis and (ii) of all independent genome-wide significant loci separately that showed sufficient distribution of all allelic groups in our sample (105 SNPs). The RPS was nominally associated with perigenual anterior cingulate and posterior cingulate/precuneus activation during episodic memory (PFWE(ROI)=0.047) and social cognition (PFWE(ROI)=0.025), respectively. Single SNP analyses revealed that rs9607782, located near EP300, was significantly associated with amygdala recruitment during emotion processing (PFWE(ROI)=1.63 × 10-4, surpassing Bonferroni correction for the number of SNPs). Importantly, this association was replicable in an independent sample (N=150; PFWE(ROI)<0.025). Other SNP effects previously associated with imaging phenotypes were nominally significant, but did not withstand correction for the number of SNPs tested. To assess whether there was true signal within our data, we repeated single SNP analyses with 105 randomly chosen non-schizophrenia-associated variants, observing fewer significant results and lower association probabilities. Applying stringent methodological procedures, we found preliminary evidence for the notion that genetic risk for schizophrenia conferred by rs9607782 may be mediated by amygdala function. We critically evaluate the potential caveats of the methodological approaches employed and offer suggestions for future studies.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

The antipsychotic clozapine is uniquely effective in the management of schizophrenia; however, its use is limited by its potential to induce agranulocytosis. The causes of this, and of its precursor neutropenia, are largely unknown, although genetic factors have an important role. We sought risk alleles for clozapine-associated neutropenia in a sample of 66 cases and 5583 clozapine-treated controls, through a genome-wide association study (GWAS), imputed human leukocyte antigen (HLA) alleles, exome array and copy-number variation (CNV) analyses. We then combined associated variants in a meta-analysis with data from the Clozapine-Induced Agranulocytosis Consortium (up to 163 cases and 7970 controls). In the largest combined sample to date, we identified a novel association with rs149104283 (odds ratio (OR)=4.32, P=1.79 × 10-8), intronic to transcripts of SLCO1B3 and SLCO1B7, members of a family of hepatic transporter genes previously implicated in adverse drug reactions including simvastatin-induced myopathy and docetaxel-induced neutropenia. Exome array analysis identified gene-wide associations of uncommon non-synonymous variants within UBAP2 and STARD9. We additionally provide independent replication of a previously identified variant in HLA-DQB1 (OR=15.6, P=0.015, positive predictive value=35.1%). These results implicate biological pathways through which clozapine may act to cause this serious adverse effect.

Genome-wide common and rare variant analysis provides novel insights into clozapine-associated neutropenia.

This corrects the article DOI: 10.1038/mp.2016.97.

Copy number variation in bipolar disorder.

Large (>100 kb), rare (<1% in the population) copy number variants (CNVs) have been shown to confer risk for schizophrenia (SZ), but the findings for bipolar disorder (BD) are less clear. In a new BD sample from the United Kingdom (n=2591), we have examined the occurrence of CNVs and compared this with previously reported samples of 6882 SZ and 8842 control subjects. When combined with previous data, we find evidence for a contribution to BD for three SZ-associated CNV loci: duplications at 1q21.1 (P=0.022), deletions at 3q29 (P=0.03) and duplications at 16p11.2 (P=2.3 × 10(-4)). The latter survives multiple-testing correction for the number of recurrent large CNV loci in the genome. Genes in 20 regions (total of 55 genes) were enriched for rare exonic CNVs among BD cases, but none of these survives correction for multiple testing. Finally, our data provide strong support for the hypothesis of a lesser contribution of very large (>500 kb) CNVs in BD compared with SZ, most notably for deletions >1 Mb (P=9 × 10(-4)).

High loading of polygenic risk in cases with chronic schizophrenia.

Genomic risk profile scores (GRPSs) have been shown to predict case-control status of schizophrenia (SCZ), albeit with varying sensitivity and specificity. The extent to which this variability in prediction accuracy is related to differences in sampling strategies is unknown. Danish population-based registers and Neonatal Biobanks were used to identify two independent incident data sets (denoted target and replication) comprising together 1861 cases with SCZ and 1706 controls. A third data set was a German prevalent sample with diagnoses assigned to 1773 SCZ cases and 2161 controls based on clinical interviews. GRPSs were calculated based on the genome-wide association results from the largest SCZ meta-analysis yet conducted. As measures of genetic risk prediction, Nagelkerke pseudo-R(2) and variance explained on the liability scale were calculated. GRPS for SCZ showed positive correlations with the number of psychiatric admissions across all P-value thresholds in both the incident and prevalent samples. In permutation-based test, Nagelkerke pseudo-R(2) values derived from samples enriched for frequently admitted cases were found to be significantly higher than for the full data sets (Ptarget=0.017, Preplication=0.04). Oversampling of frequently admitted cases further resulted in a higher proportion of variance explained on the liability scale (improvementtarget= 50%; improvementreplication= 162%). GRPSs are significantly correlated with chronicity of SCZ. Oversampling of cases with a high number of admissions significantly increased the amount of variance in liability explained by GRPS. This suggests that at least part of the effect of common single-nucleotide polymorphisms is on the deteriorative course of illness.

Common alleles contribute to schizophrenia in CNV carriers.

The genetic architecture of schizophrenia is complex, involving risk alleles ranging from common alleles of weak effect to rare alleles of large effect, the best exemplar of the latter being large copy number variants (CNVs). It is currently unknown whether pathophysiology in those with defined rare mutations overlaps with that in other individuals with the disorder who do not share the same rare mutation. Under an extreme heterogeneity model, carriers of specific high-penetrance mutations form distinct subgroups. In contrast, under a polygenic threshold model, high-penetrance rare allele carriers possess many risk factors, of which the rare allele is the only one, albeit an important, factor. Under the latter model, cases with rare mutations can be expected to share some common risk alleles, and therefore pathophysiological mechanisms, with cases without the same mutation. Here we show that, compared with controls, individuals with schizophrenia who have known pathogenic CNVs carry an excess burden of common risk alleles (P=2.25 × 10(-17)) defined from a genome-wide association study largely based on individuals without known CNVs. Our finding is not consistent with an extreme heterogeneity model for CNV carriers, but does offer support for the polygenic threshold model of schizophrenia. That this is so provides support for the notion that studies aiming to model the effects of rare variation may uncover pathophysiological mechanisms of relevance to those with the disorder more widely.

Expression analysis in a rat psychosis model identifies novel candidate genes validated in a large case-control sample of schizophrenia.

Antagonists of the N-methyl-D-aspartate (NMDA)-type glutamate receptor induce psychosis in healthy individuals and exacerbate schizophrenia symptoms in patients. In this study we have produced an animal model of NMDA receptor hypofunction by chronically treating rats with low doses of the NMDA receptor antagonist MK-801. Subsequently, we performed an expression study and identified 20 genes showing altered expression in the brain of these rats compared with untreated animals. We then explored whether the human orthologs of these genes are associated with schizophrenia in the largest schizophrenia genome-wide association study published to date, and found evidence for association for 4 out of the 20 genes: SF3B1, FOXP1, DLG2 and VGLL4. Interestingly, three of these genes, FOXP1, SF3B1 and DLG2, have previously been implicated in neurodevelopmental disorders.

The association between lower educational attainment and depression owing to shared genetic effects? Results in ~25,000 subjects.

An association between lower educational attainment (EA) and an increased risk for depression has been confirmed in various western countries. This study examines whether pleiotropic genetic effects contribute to this association. Therefore, data were analyzed from a total of 9662 major depressive disorder (MDD) cases and 14,949 controls (with no lifetime MDD diagnosis) from the Psychiatric Genomics Consortium with additional Dutch and Estonian data. The association of EA and MDD was assessed with logistic regression in 15,138 individuals indicating a significantly negative association in our sample with an odds ratio for MDD 0.78 (0.75-0.82) per standard deviation increase in EA. With data of 884,105 autosomal common single-nucleotide polymorphisms (SNPs), three methods were applied to test for pleiotropy between MDD and EA: (i) genetic profile risk scores (GPRS) derived from training data for EA (independent meta-analysis on ~120,000 subjects) and MDD (using a 10-fold leave-one-out procedure in the current sample), (ii) bivariate genomic-relationship-matrix restricted maximum likelihood (GREML) and (iii) SNP effect concordance analysis (SECA). With these methods, we found (i) that the EA-GPRS did not predict MDD status, and MDD-GPRS did not predict EA, (ii) a weak negative genetic correlation with bivariate GREML analyses, but this correlation was not consistently significant, (iii) no evidence for concordance of MDD and EA SNP effects with SECA analysis. To conclude, our study confirms an association of lower EA and MDD risk, but this association was not because of measurable pleiotropic genetic effects, which suggests that environmental factors could be involved, for example, socioeconomic status.

Temporal delay discounting in acutely ill and weight-recovered patients with anorexia nervosa.

BACKGROUND: Patients with anorexia nervosa (AN) are characterized by a very low body weight but readily give up immediate rewards (food) for long-term goals (slim figure), which might indicate an unusual level of self-control. This everyday clinical observation may be quantifiable in the framework of the anticipation-discounting dilemma. METHOD: Using a cross-sectional design, this study compared the capacity to delay reward in 34 patients suffering from acute AN (acAN), 33 weight-recovered AN patients (recAN) and 54 healthy controls. We also used a longitudinal study to reassess 21 acAN patients after short-term weight restoration. A validated intertemporal choice task and a hyperbolic model were used to estimate temporal discounting rates. RESULTS: Confirming the validity of the task used, decreased delay discounting was associated with age and low self-reported impulsivity. However, no group differences in key measures of temporal discounting of monetary rewards were found. CONCLUSIONS: Increased cognitive control, which has been suggested as a key characteristic of AN, does not seem to extend the capacity to wait for delayed monetary rewards. Differences between our study and the only previous study reporting decreased delay discounting in adult AN patients may be explained by the different age range and chronicity of acute patients, but the fact that weight recovery was not associated with changes in discount rates suggests that discounting behavior is not a trait marker in AN. Future studies using paradigms with disorder-specific stimuli may help to clarify the role of delay discounting in AN.