Schizophrenia genetics: Building the foundations of the future

In recent years, our understanding of the genetic architecture of schizophrenia, a phrase which denotes the numbers of risk variants, their frequencies and effect sizes, has been transformed. This has come about through advances in technology that have allowed almost the entire human genome to be simultaneously interrogated for the presence of disease-associated genetic variation and allows this to be performed in sample sizes powered for a realistic possibility of success. Another development has been the emergence of international consortia willing to share raw data and their coalescence into super-consortia to achieve sample sizes and bodies of clinical and analytic expertise that was unimaginable a decade ago. These innovations have driven the emergence of statistically robust and replicable genetic findings in schizophrenia, and a rapid escalation in the number of those findings over the last 5 years. The latest example comes from the Schizophrenia Working Group of the Psychiatric Genomics Consortium (PGC-SCZ) which, at the time of publication, included contributions from around 37 000 individuals with schizophrenia, 302 investigators, 35 countries, and 4 continents.1 In their recent paper, published in Nature in July 2014, the PGC-SCZ group report 128 statistically independent genetic associations, implicating a minimum of 108 conservatively defined schizophrenia-associated genetic loci.1 Of the identified loci, 83 have not been previously robustly supported as playing a role in schizophrenia, but it is also important to note the findings are consistent with previous literature; 25 loci that had previously been reported as associated with schizophrenia in large samples were again supported in this much larger analysis, confirming that the use of large samples and stringent statistical cut-offs results in reproducible findings. The availability of so many robustly supported findings offers immense opportunities for investigating and advancing our understanding of etiology

Capturing health and eating status through a nutritional perception screening questionnaire (NPSQ9) in a randomised internet-based personalised nutrition intervention : the Food4Me study

BACKGROUND: National guidelines emphasize healthy eating to promote wellbeing and prevention of non-communicable diseases. The perceived healthiness of food is determined by many factors affecting food intake. A positive perception of healthy eating has been shown to be associated with greater diet quality. Internet-based methodologies allow contact with large populations. Our present study aims to design and evaluate a short nutritional perception questionnaire, to be used as a screening tool for assessing nutritional status, and to predict an optimal level of personalisation in nutritional advice delivered via the Internet. METHODS: Data from all participants who were screened and then enrolled into the Food4Me proof-of-principle study (n = 2369) were used to determine the optimal items for inclusion in a novel screening tool, the Nutritional Perception Screening Questionnaire-9 (NPSQ9). Exploratory and confirmatory factor analyses were performed on anthropometric and biochemical data and on dietary indices acquired from participants who had completed the Food4Me dietary intervention (n = 1153). Baseline and intervention data were analysed using linear regression and linear mixed regression, respectively. RESULTS: A final model with 9 NPSQ items was validated against the dietary intervention data. NPSQ9 scores were inversely associated with BMI (β = -0.181, p < 0.001) and waist circumference (Β = -0.155, p < 0.001), and positively associated with total carotenoids (β = 0.198, p < 0.001), omega-3 fatty acid index (β = 0.155, p < 0.001), Healthy Eating Index (HEI) (β = 0.299, p < 0.001) and Mediterranean Diet Score (MDS) (β = 0. 279, p < 0.001). Findings from the longitudinal intervention study showed a greater reduction in BMI and improved dietary indices among participants with lower NPSQ9 scores. CONCLUSIONS: Healthy eating perceptions and dietary habits captured by the NPSQ9 score, based on nine questionnaire items, were associated with reduced body weight and improved diet quality. Likewise, participants with a lower score achieved greater health improvements than those with higher scores, in response to personalised advice, suggesting that NPSQ9 may be used for early evaluation of nutritional status and to tailor nutritional advice. TRIAL REGISTRATION: NCT01530139 .Peer reviewedFinal Published versio

Association Between Schizophrenia-Related Polygenic Liability and the Occurrence and Level of Mood-Incongruent Psychotic Symptoms in Bipolar Disorder

Importance Bipolar disorder (BD) overlaps schizophrenia in its clinical presentation and genetic liability. Alternative approaches to patient stratification beyond current diagnostic categories are needed to understand the underlying disease processes/mechanisms. Objectives To investigate the relationship between common-variant liability for schizophrenia, indexed by polygenic risk scores (PRS) and psychotic presentations of BD, using clinical descriptions which consider both occurrence and level of mood-incongruent psychotic features. Design Case-control design: using multinomial logistic regression, to estimate differential associations of PRS across categories of cases and controls. Settings & Participants 4399 BD cases, 2966 (67%) female, mean age-at-interview 46 [sd 12] years, from the BD Research Network (BDRN) were included in the final analyses. For comparison genotypic data for 4976 schizophrenia cases and 9012 controls from the Type-1 diabetes genetics consortium and Generation Scotland were included. Exposure Standardised PRS, calculated using alleles with an association p-value threshold < 0.05 in the second Psychiatric Genomics Consortium genome-wide association study of schizophrenia, adjusted for the first 10 population principal components and genotyping-platform. Main outcome measure Multinomial logit models estimated PRS associations with BD stratified by (1) Research Diagnostic Criteria (RDC) BD subtypes (2) Lifetime occurrence of psychosis.(3) Lifetime mood-incongruent psychotic features and (4) ordinal logistic regression examined PRS associations across levels of mood-incongruence. Ratings were derived from the Schedule for Clinical Assessment in Neuropsychiatry interview (SCAN) and the Bipolar Affective Disorder Dimension Scale (BADDS). Results Across clinical phenotypes, there was an exposure-response gradient with the strongest PRS association for schizophrenia (RR=1.94, (95% C.I. 1.86, 2.01)), then schizoaffective BD (RR=1.37, (95% C.I. 1.22, 1.54)), BD I (RR= 1.30, (95% C.I. 1.24, 1.36)) and BD II (RR=1.04, (95% C.I. 0.97, 1.11)). Within BD cases, there was an effect gradient, indexed by the nature of psychosis, with prominent mood-incongruent psychotic features having the strongest association (RR=1.46, (95% C.I. 1.36, 1.57)), followed by mood-congruent psychosis (RR= 1.24, (95% C.I. 1.17, 1.33)) and lastly, BD cases with no history of psychosis (RR=1.09, (95% C.I. 1.04, 1.15)). Conclusion We show for the first time a polygenic-risk gradient, across schizophrenia and bipolar disorder, indexed by the occurrence and level of mood-incongruent psychotic symptoms

The impacts of social determinants of health and cardiometabolic factors on cognitive and functional aging in Colombian underserved populations

Global initiatives call for further understanding of the impact of inequity on aging across underserved populations. Previous research in low- and middle-income countries (LMICs) presents limitations in assessing combined sources of inequity and outcomes (i.e., cognition and functionality). In this study, we assessed how social determinants of health (SDH), cardiometabolic factors (CMFs), and other medical/social factors predict cognition and functionality in an aging Colombian population. We ran a cross-sectional study that combined theory- (structural equation models) and data-driven (machine learning) approaches in a population-based study (N = 23,694; M = 69.8 years) to assess the best predictors of cognition and functionality. We found that a combination of SDH and CMF accurately predicted cognition and functionality, although SDH was the stronger predictor. Cognition was predicted with the highest accuracy by SDH, followed by demographics, CMF, and other factors. A combination of SDH, age, CMF, and additional physical/psychological factors were the best predictors of functional status. Results highlight the role of inequity in predicting brain health and advancing solutions to reduce the cognitive and functional decline in LMICs.Fil: Santamaria Garcia, Hernando. Pontificia Universidad Javeriana; Colombia. Hospital Universitario San Ignacio; Colombia. University of California; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Moguilner, Sebastian Gabriel. Universidad de San Andrés; Argentina. Massachusetts General Hospital; Estados Unidos. Universidad Adolfo Ibañez; ChileFil: Rodriguez Villagra, Odir Antonio. Universidad de Costa Rica; Costa RicaFil: Botero Rodriguez, Felipe. Pontificia Universidad Javeriana; ColombiaFil: Pina Escudero, Stefanie Danielle. University of California; Estados UnidosFil: O’Donovan, Gary. Universidad Adolfo Ibañez; Chile. Universidad de los Andes; ColombiaFil: Albala, Cecilia. Universidad de Chile; ChileFil: Matallana, Diana. Fundacion Santa Fe de Bogota; Colombia. Hospital Universitario San Ignacio; Colombia. Pontificia Universidad Javeriana; ColombiaFil: Schulte, Michael. Universidad Adolfo Ibañez; ChileFil: Slachevsky, Andrea. Universidad del Desarrollo; Chile. Universidad de Chile; ChileFil: Yokoyama, Jennifer S.. University of California; Estados UnidosFil: Possin, Katherine. University of California; Estados UnidosFil: Ndhlovu, Lishomwa C.. Weill Cornell Medicine; Estados UnidosFil: Al-Rousan, Tala. University of California at San Diego; Estados UnidosFil: Corley, Michael J.. Weill Cornell Medicine; Estados UnidosFil: Kosik, Kenneth. University of California; Estados UnidosFil: Muniz Terrera, Graciela. University of Edinburgh; Reino Unido. Ohio University; Estados UnidosFil: Miranda, J. Jaime. George Institute For Global Health; Australia. Cronicas Centro de Excelencia En Enfermedades Crónicas; Perú. Universidad Peruana Cayetano Heredia; PerúFil: Ibañez, Agustin Mariano. Universidad de San Andrés; Argentina. Trinity College Dublin; Irlanda. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. University of California; Estados Unidos. Universidad Adolfo Ibañez; Chil

Post-partum psychosis and its association with bipolar disorder in the UK: a case-control study using polygenic risk scores

Background For more than 150 years, controversy over the status of post-partum psychosis has hindered research and caused considerable confusion for clinicians and women, with potentially negative consequences. We aimed to explore the hypothesis that genetic vulnerability differs between women with first-onset post-partum psychosis and those with bipolar disorder more generally. Methods In this case-control study on first-onset post-partum psychosis and bipolar disorder in the UK, we included 203 women with first-onset post-partum psychosis (defined as a manic, mixed, or psychotic depression episode within 6 weeks of delivery without a psychiatric history) and 1225 parous women with a history of bipolar disorder. Information on women with bipolar disorder was obtained from the Bipolar Disorder Research Network database, and participants were recruited through screening community mental health teams across the UK and via the media and patient support organisations. All were assessed using a semistructured face-to-face psychiatric interview and psychiatric case note review. 2809 women from the general population were recruited via the national UK Blood Services and the 1958 Birth Cohort (UK National Child Development Study) as controls and matched to cases according to genetic ancestry. All self-reported their ethnicity as White and were recruited from across the UK. Polygenic risk scores (PRSs) were generated from discovery genome-wide association studies of schizophrenia, bipolar disorder, and major depression. Logistic regression was used to model the effect of each PRS on diagnosis, and the RRs and ORs presented were adjusted for ten principal components of genetic variation to account for population stratification. Findings 203 women with first-onset post-partum psychosis (median age at interview: 46 years [IQR 37–55]) and 1225 women with bipolar disorder (49 years [41–58]) were recruited between September, 1991, and May, 2013, as well as 2809 controls. Women with first-onset post-partum psychosis had similar bipolar disorder and schizophrenia PRSs to women with bipolar disorder, which were significantly higher than those of controls. When compared with controls, women with first-onset post-partum psychosis had an adjusted relative risk ratio (RR) for bipolar disorder PRSs of 1·71 (95% CI 1·56–1·86, p<0·0001) and for schizophrenia PRSs of 1·82 (1·66–1·97, p<0·0001). The effect sizes were similar when comparing women with bipolar disorder to controls (adjusted RR 1·77 [1·69–1·84], p<0·0001 for bipolar disorder PRSs; 2·00 (1·92–2·08), p<0·0001 for schizophrenia PRSs). Although women with bipolar disorder also had higher major depression PRSs than did controls (1·24 [1·17–1·31], p<0·0001), women with first-onset post-partum psychosis did not differ from controls in their polygenic liability to major depression (0·97 (0·82–1·11), p=0·63)

Effect of an internet-based, personalized nutrition randomized trial on dietary changes associated with the Mediterranean diet: the Food4Me Study

Background: Little is known about the efficacy of personalized nutrition (PN) interventions for improving consumption of a Mediterranean diet (MedDiet). Objective: The objective was to evaluate the effect of a PN intervention on dietary changes associated with the MedDiet. Design: Participants (n = 1607) were recruited into a 6-mo, Internet-based, PN randomized controlled trial (Food4Me) designed to evaluate the effect of PN on dietary change. Participants were randomly assigned to receive conventional dietary advice [control; level 0 (L0)] or PN advice on the basis of current diet [level 1 (L1)], diet and phenotype [level 2 (L2)], or diet, phenotype, and genotype [level 3 (L3)]. Dietary intakes from food-frequency questionnaires at baseline and at 6 mo were converted to a MedDiet score. Linear regression compared participant characteristics between high (>5) and low (≤5) MedDiet scores. Differences in MedDiet scores between treatment arms at month 6 were evaluated by using contrast analyses. Results: At baseline, high MedDiet scorers had a 0.5 lower body mass index (in kg/m2; P = 0.007) and a 0.03 higher physical activity level (P = 0.003) than did low scorers. MedDiet scores at month 6 were greater in individuals randomly assigned to receive PN (L1, L2, and L3) than in controls (PN compared with controls: 5.20 ± 0.05 and 5.48 ± 0.07, respectively; P = 0.002). There was no significant difference in MedDiet scores at month 6 between PN advice on the basis of L1 compared with L2 and L3. However, differences in MedDiet scores at month 6 were greater in L3 than in L2 (L3 compared with L2: 5.63 ± 0.10 and 5.38 ± 0.10, respectively; P = 0.029). Conclusions: Higher MedDiet scores at baseline were associated with healthier lifestyles and lower adiposity. After the intervention, MedDiet scores were greater in individuals randomly assigned to receive PN than in controls, with the addition of DNA-based dietary advice resulting in the largest differences in MedDiet scores. Although differences were significant, their clinical relevance is modest. This trial was registered at clinicaltrials.gov as NCT01530139

Convergent evidence that ZNF804A is a regulator of pre-messenger RNA processing and gene expression

Genome-wide association studies have linked common variation in ZNF804A with an increased risk of schizophrenia. However, little is known about the biology of ZNF804A and its role in schizophrenia. Here, we investigate the function of ZNF804A using a variety of complementary molecular techniques. We show that ZNF804A is a nuclear protein that interacts with neuronal RNA splicing factors and RNA-binding proteins including RBFOX1, which is also associated with schizophrenia, CELF3/4, components of the ubiquitin-proteasome system and the ZNF804A paralog, GPATCH8. GPATCH8 also interacts with splicing factors and is localized to nuclear speckles indicative of a role in pre-messenger RNA (mRNA) processing. Sequence analysis showed that GPATCH8 contains ultraconserved, alternatively spliced poison exons that are also regulated by RBFOX proteins. ZNF804A knockdown in SH-SY5Y cells resulted in robust changes in gene expression and pre-mRNA splicing converging on pathways associated with nervous system development, synaptic contact, and cell adhesion. We observed enrichment (P = 1.66 × 10–9) for differentially spliced genes in ZNF804A-depleted cells among genes that contain RBFOX-dependent alternatively spliced exons. Differentially spliced genes in ZNF804A-depleted cells were also enriched for genes harboring de novo loss of function mutations in autism spectrum disorder (P = 6.25 × 10–7, enrichment 2.16) and common variant alleles associated with schizophrenia (P = .014), bipolar disorder and schizophrenia (P = .003), and autism spectrum disorder (P = .005). These data suggest that ZNF804A and its paralogs may interact with neuronal-splicing factors and RNA-binding proteins to regulate the expression of a subset of synaptic and neurodevelopmental genes

Changes in physical activity following a genetic-based internet-delivered personalized intervention: randomized controlled trial (Food4Me)

Background: There is evidence that physical activity (PA) can attenuate the influence of the fat mass- and obesity-associated (FTO) genotype on the risk to develop obesity. However, whether providing personalized information on FTO genotype leads to changes in PA is unknown. Objective: The purpose of this study was to determine if disclosing FTO risk had an impact on change in PA following a 6-month intervention. Methods: The single nucleotide polymorphism (SNP) rs9939609 in the FTO gene was genotyped in 1279 participants of the Food4Me study, a four-arm, Web-based randomized controlled trial (RCT) in 7 European countries on the effects of personalized advice on nutrition and PA. PA was measured objectively using a TracmorD accelerometer and was self-reported using the Baecke questionnaire at baseline and 6 months. Differences in baseline PA variables between risk (AA and AT genotypes) and nonrisk (TT genotype) carriers were tested using multiple linear regression. Impact of FTO risk disclosure on PA change at 6 months was assessed among participants with inadequate PA, by including an interaction term in the model: disclosure (yes/no) × FTO risk (yes/no). Results: At baseline, data on PA were available for 874 and 405 participants with the risk and nonrisk FTO genotypes, respectively. There were no significant differences in objectively measured or self-reported baseline PA between risk and nonrisk carriers. A total of 807 (72.05%) of the participants out of 1120 in the personalized groups were encouraged to increase PA at baseline. Knowledge of FTO risk had no impact on PA in either risk or nonrisk carriers after the 6-month intervention. Attrition was higher in nonrisk participants for whom genotype was disclosed (P=.01) compared with their at-risk counterparts. Conclusions: No association between baseline PA and FTO risk genotype was observed. There was no added benefit of disclosing FTO risk on changes in PA in this personalized intervention. Further RCT studies are warranted to confirm whether disclosure of nonrisk genetic test results has adverse effects on engagement in behavior change