Abundant pleiotropy across neuroimaging modalities identified through a multivariate genome-wide association study.

Genetic pleiotropy is abundant across spatially distributed brain characteristics derived from one neuroimaging modality (e.g. structural, functional or diffusion magnetic resonance imaging [MRI]). A better understanding of pleiotropy across modalities could inform us on the integration of brain function, micro- and macrostructure. Here we show extensive genetic overlap across neuroimaging modalities at a locus and gene level in the UK Biobank (N = 34,029) and ABCD Study (N = 8607). When jointly analysing phenotypes derived from structural, functional and diffusion MRI in a genome-wide association study (GWAS) with the Multivariate Omnibus Statistical Test (MOSTest), we boost the discovery of loci and genes beyond previously identified effects for each modality individually. Cross-modality genes are involved in fundamental biological processes and predominantly expressed during prenatal brain development. We additionally boost prediction of psychiatric disorders by conditioning independent GWAS on our multimodal multivariate GWAS. These findings shed light on the shared genetic mechanisms underlying variation in brain morphology, functional connectivity, and tissue composition.

An association between YKL-40 and type 2 diabetes in psychotic disorders.

OBJECTIVE: This study examines if YKL-40 is increased in individuals with psychotic disorders and if elevated YKL-40 levels at baseline is associated with subsequent development of type 2 diabetes. METHOD: A total of 1383 patients with a diagnosis of schizophrenia or affective psychosis and 799 healthy controls were recruited in the period 2002-2015. Plasma YKL-40 and metabolic risk factors were measured and medication was recorded. Using national registry data, association between baseline risk factors and later development of type 2 diabetes was assessed using Cox proportional hazards models. RESULTS: Plasma YKL-40 was higher in patients vs. healthy controls also after adjusting for metabolic risk factors, with no difference between the schizophrenia and affective psychosis groups. Patients were diagnosed with type 2 diabetes at a significantly younger age. Multivariate Cox regression analyses showed that elevated YKL-40 (hazard ratio (HR) = 5.6, P = 0.001), elevated glucose (HR = 3.6, P = 0.001), and schizophrenia diagnosis (HR = 3.0, P = 0.014) at baseline were associated with subsequent development of type 2 diabetes. CONCLUSIONS: Patients with psychotic disorders have at baseline increased levels of YKL-40 beyond the effect of comorbid type 2 diabetes and metabolic risk factors. Elevated YKL-40 level at baseline is associated with later development of type 2 diabetes.

Associations between persistent organic pollutants and metabolic syndrome in morbidly obese individuals.

BACKGROUND AND AIMS: Persons with "metabolically healthy" obesity may develop cardiometabolic complications at a lower rate than equally obese persons with evident metabolic syndrome. Even morbidly obese individuals vary in risk profile. Persistent organic pollutants (POPs) are widespread environmental chemicals that impair metabolic homeostasis. We explored whether prevalence of metabolic syndrome in morbidly obese individuals is associated with serum concentrations of POPs. METHODS AND RESULTS: A cross-sectional study among 161 men and 270 women with BMI >35 kg/m2 and comorbidity, or >40 kg/m2. Circulating concentrations of 15 POPs were stratified by number of metabolic syndrome components. In multiple logistic regression analysis odds ratios between top quartile POPs and metabolic risk factors versus POPs below the top quartile were calculated adjusting for age, gender, body mass index, smoking status, alcohol consumption and cholesterol concentrations. Age-adjusted concentrations of trans-nonachlor and dioxin-like and non-dioxin-like polychlorinated biphenyls (PCBs) increased with number of metabolic syndrome components in both genders (p < 0.001), while the organochlorine pesticides HCB, ß-HCH and p,p'DDE increased only in women (p < 0.008). Organochlorine pesticides in the top quartile were associated with metabolic syndrome as were dioxin-like and non-dioxin-like PCBs (OR 2.3 [95% CI 1.3-4.0]; OR 2.5 [95% CI 1.3-4.8] and 2.0 [95% CI 1.1-3.8], respectively). Organochlorine pesticides were associated with HDL cholesterol and glucose (OR = 2.0 [95% CI = 1.1-3.4]; 2.4 [95% CI = 1.4-4.0], respectively). Dioxin-like PCBs were associated with diastolic blood pressure, glucose and homeostatic model assessment-insulin resistance index (OR = 2.0 [95% CI = 1.1-3.6], 2.1 [95% CI = 1.2-3.6] and 2.1 [95% CI = 1.0-4.3], respectively). CONCLUSION: In subjects with morbid obesity, metabolic syndrome was related to circulating levels of organochlorine pesticides and PCBs suggesting that these compounds aggravate clinically relevant complications of obesity.

Genetic risk scores and family history as predictors of schizophrenia in Nordic registers.

BACKGROUND: Family history is a long-standing and readily obtainable risk factor for schizophrenia (SCZ). Low-cost genotyping technologies have enabled large genetic studies of SCZ, and the results suggest the utility of genetic risk scores (GRS, direct assessments of inherited common variant risk). Few studies have evaluated family history and GRS simultaneously to ask whether one can explain away the other. METHODS: We studied 5959 SCZ cases and 8717 controls from four Nordic countries. All subjects had family history data from national registers and genome-wide genotypes that were processed through the quality control procedures used by the Psychiatric Genomics Consortium. Using external training data, GRS were estimated for SCZ, bipolar disorder (BIP), major depression, autism, educational attainment, and body mass index. Multivariable modeling was used to estimate effect sizes. RESULTS: Using harmonized genomic and national register data from Denmark, Estonia, Norway, and Sweden, we confirmed that family history of SCZ and GRS for SCZ and BIP were risk factors for SCZ. In a joint model, the effects of GRS for SCZ and BIP were essentially unchanged, and the effect of family history was attenuated but remained significant. The predictive capacity of a model including GRS and family history neared the minimum for clinical utility. CONCLUSIONS: Combining national register data with measured genetic risk factors represents an important investigative approach for psychotic disorders. Our findings suggest the potential clinical utility of combining GRS and family history for early prediction and diagnostic improvements.

Psychotic patients who used cannabis frequently before illness onset have higher genetic predisposition to schizophrenia than those who did not.

BACKGROUND: Schizophrenia (SZ) and bipolar disorder (BD) are heritable, polygenic disorders with shared clinical and genetic components, suggesting a psychosis continuum. Cannabis use is a well-documented environmental risk factor in psychotic disorders. In the current study, we investigated the relationship between SZ genetic load and cannabis use before illness onset in SZ and BD spectrums. Since frequent early cannabis use (age <18 years) is believed to increase the risk of developing psychosis more than later use, follow-up analyses were conducted comparing early use to later use and no use. METHODS: We assigned a SZ-polygenic risk score (PGRS) to each individual in our independent sample (N = 381 SZ spectrum cases, 220 BD spectrum cases and 415 healthy controls), calculated from the results of the Psychiatric Genomics Consortium (PGC) SZ case-control study (N = 81 535). SZ-PGRS in patients who used cannabis weekly to daily in the period before first illness episode was compared with that of those who never or infrequently used cannabis. RESULTS: Patients with weekly to daily cannabis use before illness onset had the highest SZ-PGRS (p = 0.02, Cohen's d = 0.33). The largest difference was found between patients with daily or weekly cannabis use before illness onset <18 years of age and patients with no or infrequent use of cannabis (p = 0.003, Cohen's d = 0.42). CONCLUSIONS: Our study supports an association between high SZ-PGRS and frequent cannabis use before illness onset in psychosis continuum disorders.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

This corrects the article DOI: 10.1038/mp.2016.244.

Persistent increase in TNF and IL-1 markers in severe mental disorders suggests trait-related inflammation: a one year follow-up study.

OBJECTIVE: We evaluated if plasma levels of inflammatory markers are persistently altered in severe mental disorders with psychotic symptoms or associated with state characteristics in a longitudinal study. METHODS: Soluble tumor necrosis factor receptor 1 (sTNF-R1), interleukin-1 receptor antagonist (IL-1Ra), von Willebrand factor (VWF), and osteoprotegerin (OPG) were measured in schizophrenia (n = 69) and affective (n = 55) spectrum patients at baseline and at one-year follow-up, and compared to healthy controls (HC) (n = 92) with analysis of covariance. Association between change in symptoms and inflammatory markers was analyzed with mixed-effects models. RESULTS: sTNF-R1 was higher in the schizophrenia (P < 0.0001) and affective disorders (P = 0.02) compared to HC, while IL-1Ra was higher in schizophrenia (P = 0.01) compared to HC at one year follow-up. There were no significant differences between schizophrenia and affective groups; however, levels in the affective group were in between schizophrenia and HC for sTNF-R1 and IL-1Ra. There were no significant associations between change in symptoms and inflammatory markers. CONCLUSION: Persistently increased sTNF-R1 and IL-1Ra after one year in patients with severe mental disorders primarily reflecting data from the schizophrenia group may suggest that inflammation is a trait phenomenon, and not only the result of stress-related mechanisms associated with acute episodes.

Genome-wide association study of borderline personality disorder reveals genetic overlap with bipolar disorder, major depression and schizophrenia.

Borderline personality disorder (BOR) is determined by environmental and genetic factors, and characterized by affective instability and impulsivity, diagnostic symptoms also observed in manic phases of bipolar disorder (BIP). Up to 20% of BIP patients show comorbidity with BOR. This report describes the first case-control genome-wide association study (GWAS) of BOR, performed in one of the largest BOR patient samples worldwide. The focus of our analysis was (i) to detect genes and gene sets involved in BOR and (ii) to investigate the genetic overlap with BIP. As there is considerable genetic overlap between BIP, major depression (MDD) and schizophrenia (SCZ) and a high comorbidity of BOR and MDD, we also analyzed the genetic overlap of BOR with SCZ and MDD. GWAS, gene-based tests and gene-set analyses were performed in 998 BOR patients and 1545 controls. Linkage disequilibrium score regression was used to detect the genetic overlap between BOR and these disorders. Single marker analysis revealed no significant association after correction for multiple testing. Gene-based analysis yielded two significant genes: DPYD (P=4.42 × 10-7) and PKP4 (P=8.67 × 10-7); and gene-set analysis yielded a significant finding for exocytosis (GO:0006887, PFDR=0.019; FDR, false discovery rate). Prior studies have implicated DPYD, PKP4 and exocytosis in BIP and SCZ. The most notable finding of the present study was the genetic overlap of BOR with BIP (rg=0.28 [P=2.99 × 10-3]), SCZ (rg=0.34 [P=4.37 × 10-5]) and MDD (rg=0.57 [P=1.04 × 10-3]). We believe our study is the first to demonstrate that BOR overlaps with BIP, MDD and SCZ on the genetic level. Whether this is confined to transdiagnostic clinical symptoms should be examined in future studies.

Genetic evidence for role of integration of fast and slow neurotransmission in schizophrenia.

The most recent genome-wide association studies (GWAS) of schizophrenia (SCZ) identified hundreds of risk variants potentially implicated in the disease. Further, novel statistical methodology designed for polygenic architecture revealed more potential risk variants. This can provide a link between individual genetic factors and the mechanistic underpinnings of SCZ. Intriguingly, a large number of genes coding for ionotropic and metabotropic receptors for various neurotransmitters-glutamate, γ-aminobutyric acid (GABA), dopamine, serotonin, acetylcholine and opioids-and numerous ion channels were associated with SCZ. Here, we review these findings from the standpoint of classical neurobiological knowledge of neuronal synaptic transmission and regulation of electrical excitability. We show that a substantial proportion of the identified genes are involved in intracellular cascades known to integrate 'slow' (G-protein-coupled receptors) and 'fast' (ionotropic receptors) neurotransmission converging on the protein DARPP-32. Inspection of the Human Brain Transcriptome Project database confirms that that these genes are indeed expressed in the brain, with the expression profile following specific developmental trajectories, underscoring their relevance to brain organization and function. These findings extend the existing pathophysiology hypothesis by suggesting a unifying role of dysregulation in neuronal excitability and synaptic integration in SCZ. This emergent model supports the concept of SCZ as an 'associative' disorder-a breakdown in the communication across different slow and fast neurotransmitter systems through intracellular signaling pathways-and may unify a number of currently competing hypotheses of SCZ pathophysiology.

GWAS meta-analysis reveals novel loci and genetic correlates for general cognitive function: a report from the COGENT consortium.

The complex nature of human cognition has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. In an attempt to overcome these barriers, the current study utilized GWAS meta-analysis to examine the association of common genetic variation (~8M single-nucleotide polymorphisms (SNP) with minor allele frequency ⩾1%) to general cognitive function in a sample of 35 298 healthy individuals of European ancestry across 24 cohorts in the Cognitive Genomics Consortium (COGENT). In addition, we utilized individual SNP lookups and polygenic score analyses to identify genetic overlap with other relevant neurobehavioral phenotypes. Our primary GWAS meta-analysis identified two novel SNP loci (top SNPs: rs76114856 in the CENPO gene on chromosome 2 and rs6669072 near LOC105378853 on chromosome 1) associated with cognitive performance at the genome-wide significance level (P<5 × 10-8). Gene-based analysis identified an additional three Bonferroni-corrected significant loci at chromosomes 17q21.31, 17p13.1 and 1p13.3. Altogether, common variation across the genome resulted in a conservatively estimated SNP heritability of 21.5% (s.e.=0.01%) for general cognitive function. Integration with prior GWAS of cognitive performance and educational attainment yielded several additional significant loci. Finally, we found robust polygenic correlations between cognitive performance and educational attainment, several psychiatric disorders, birth length/weight and smoking behavior, as well as a novel genetic association to the personality trait of openness. These data provide new insight into the genetics of neurocognitive function with relevance to understanding the pathophysiology of neuropsychiatric illness.

Modeling psychiatric disorders: from genomic findings to cellular phenotypes.

Major programs in psychiatric genetics have identified >150 risk loci for psychiatric disorders. These loci converge on a small number of functional pathways, which span conventional diagnostic criteria, suggesting a partly common biology underlying schizophrenia, autism and other psychiatric disorders. Nevertheless, the cellular phenotypes that capture the fundamental features of psychiatric disorders have not yet been determined. Recent advances in genetics and stem cell biology offer new prospects for cell-based modeling of psychiatric disorders. The advent of cell reprogramming and induced pluripotent stem cells (iPSC) provides an opportunity to translate genetic findings into patient-specific in vitro models. iPSC technology is less than a decade old but holds great promise for bridging the gaps between patients, genetics and biology. Despite many obvious advantages, iPSC studies still present multiple challenges. In this expert review, we critically review the challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes.

Genome-wide autozygosity is associated with lower general cognitive ability.

Inbreeding depression refers to lower fitness among offspring of genetic relatives. This reduced fitness is caused by the inheritance of two identical chromosomal segments (autozygosity) across the genome, which may expose the effects of (partially) recessive deleterious mutations. Even among outbred populations, autozygosity can occur to varying degrees due to cryptic relatedness between parents. Using dense genome-wide single-nucleotide polymorphism (SNP) data, we examined the degree to which autozygosity associated with measured cognitive ability in an unselected sample of 4854 participants of European ancestry. We used runs of homozygosity-multiple homozygous SNPs in a row-to estimate autozygous tracts across the genome. We found that increased levels of autozygosity predicted lower general cognitive ability, and estimate a drop of 0.6 s.d. among the offspring of first cousins (P=0.003-0.02 depending on the model). This effect came predominantly from long and rare autozygous tracts, which theory predicts as more likely to be deleterious than short and common tracts. Association mapping of autozygous tracts did not reveal any specific regions that were predictive beyond chance after correcting for multiple testing genome wide. The observed effect size is consistent with studies of cognitive decline among offspring of known consanguineous relationships. These findings suggest a role for multiple recessive or partially recessive alleles in general cognitive ability, and that alleles decreasing general cognitive ability have been selected against over evolutionary time.

Genetic overlap between Alzheimer's disease and Parkinson's disease at the MAPT locus.

We investigated the genetic overlap between Alzheimer's disease (AD) and Parkinson's disease (PD). Using summary statistics (P-values) from large recent genome-wide association studies (GWAS) (total n=89 904 individuals), we sought to identify single nucleotide polymorphisms (SNPs) associating with both AD and PD. We found and replicated association of both AD and PD with the A allele of rs393152 within the extended MAPT region on chromosome 17 (meta analysis P-value across five independent AD cohorts=1.65 × 10(-7)). In independent datasets, we found a dose-dependent effect of the A allele of rs393152 on intra-cerebral MAPT transcript levels and volume loss within the entorhinal cortex and hippocampus. Our findings identify the tau-associated MAPT locus as a site of genetic overlap between AD and PD, and extending prior work, we show that the MAPT region increases risk of Alzheimer's neurodegeneration.

Genetic pleiotropy between multiple sclerosis and schizophrenia but not bipolar disorder: differential involvement of immune-related gene loci.

Converging evidence implicates immune abnormalities in schizophrenia (SCZ), and recent genome-wide association studies (GWAS) have identified immune-related single-nucleotide polymorphisms (SNPs) associated with SCZ. Using the conditional false discovery rate (FDR) approach, we evaluated pleiotropy in SNPs associated with SCZ (n=21,856) and multiple sclerosis (MS) (n=43,879), an inflammatory, demyelinating disease of the central nervous system. Because SCZ and bipolar disorder (BD) show substantial clinical and genetic overlap, we also investigated pleiotropy between BD (n=16,731) and MS. We found significant genetic overlap between SCZ and MS and identified 21 independent loci associated with SCZ, conditioned on association with MS. This enrichment was driven by the major histocompatibility complex (MHC). Importantly, we detected the involvement of the same human leukocyte antigen (HLA) alleles in both SCZ and MS, but with an opposite directionality of effect of associated HLA alleles (that is, MS risk alleles were associated with decreased SCZ risk). In contrast, we found no genetic overlap between BD and MS. Considered together, our findings demonstrate genetic pleiotropy between SCZ and MS and suggest that the MHC signals may differentiate SCZ from BD susceptibility.

GWAS-based pathway analysis differentiates between fluid and crystallized intelligence.

Cognitive abilities vary among people. About 40-50% of this variability is due to general intelligence (g), which reflects the positive correlation among individuals' scores on diverse cognitive ability tests. g is positively correlated with many life outcomes, such as education, occupational status and health, motivating the investigation of its underlying biology. In psychometric research, a distinction is made between general fluid intelligence (gF) - the ability to reason in novel situations - and general crystallized intelligence (gC) - the ability to apply acquired knowledge. This distinction is supported by developmental and cognitive neuroscience studies. Classical epidemiological studies and recent genome-wide association studies (GWASs) have established that these cognitive traits have a large genetic component. However, no robust genetic associations have been published thus far due largely to the known polygenic nature of these traits and insufficient sample sizes. Here, using two GWAS datasets, in which the polygenicity of gF and gC traits was previously confirmed, a gene- and pathway-based approach was undertaken with the aim of characterizing and differentiating their genetic architecture. Pathway analysis, using genes selected on the basis of relaxed criteria, revealed notable differences between these two traits. gF appeared to be characterized by genes affecting the quantity and quality of neurons and therefore neuronal efficiency, whereas long-term depression (LTD) seemed to underlie gC. Thus, this study supports the gF-gC distinction at the genetic level and identifies functional annotations and pathways worthy of further investigation.

Polygenic risk score and the psychosis continuum model.

OBJECTIVE: Schizophrenia (SZ) and bipolar disorder (BD) are heritable, polygenic disorders with shared clinical characteristics and genetic risk indicating a psychosis continuum. This is the first study using polygenic risk score (PGRS) to investigate the localization of diagnostic subcategories along the entire psychosis spectrum. METHOD: Based on results from the Psychiatric Genomics Consortium (PGC), we assigned a SZ and BD PGRS to each individual in our independent sample [N=570 BD spectrum cases, 452 SZ spectrum cases and 415 healthy controls (CTR)]. Potential differences in mean SZ and BD PGRS across diagnostic spectrums and subcategories were explored. RESULTS: SZ and BD PGRSs were significantly associated with both SZ and BD spectrums compared with CTR. For the subcategories, SZ PGRS was significantly associated with SZ, schizoaffective disorder, psychosis not otherwise specified, and BD1, while BD PGRS was significantly associated with BD1 and BD2. There were no significant differences between any of the diagnostic spectrums or subgroups for neither the SZ nor BD PGRS. Lifetime psychosis was significantly associated with SZ PGRS but not with BD PGRS. CONCLUSION: These findings further support the psychosis continuum model and provide molecular polygenetic validation of the localization of diagnostic subcategories within this continuum.

Common variant at 16p11.2 conferring risk of psychosis.

Epidemiological and genetic data support the notion that schizophrenia and bipolar disorder share genetic risk factors. In our previous genome-wide association study, meta-analysis and follow-up (totaling as many as 18 206 cases and 42 536 controls), we identified four loci showing genome-wide significant association with schizophrenia. Here we consider a mixed schizophrenia and bipolar disorder (psychosis) phenotype (addition of 7469 bipolar disorder cases, 1535 schizophrenia cases, 333 other psychosis cases, 808 unaffected family members and 46 160 controls). Combined analysis reveals a novel variant at 16p11.2 showing genome-wide significant association (rs4583255[T]; odds ratio=1.08; P=6.6 × 10(-11)). The new variant is located within a 593-kb region that substantially increases risk of psychosis when duplicated. In line with the association of the duplication with reduced body mass index (BMI), rs4583255[T] is also associated with lower BMI (P=0.0039 in the public GIANT consortium data set; P=0.00047 in 22 651 additional Icelanders).

Molecular genetic evidence for overlap between general cognitive ability and risk for schizophrenia: a report from the Cognitive Genomics consorTium (COGENT).

It has long been recognized that generalized deficits in cognitive ability represent a core component of schizophrenia (SCZ), evident before full illness onset and independent of medication. The possibility of genetic overlap between risk for SCZ and cognitive phenotypes has been suggested by the presence of cognitive deficits in first-degree relatives of patients with SCZ; however, until recently, molecular genetic approaches to test this overlap have been lacking. Within the last few years, large-scale genome-wide association studies (GWAS) of SCZ have demonstrated that a substantial proportion of the heritability of the disorder is explained by a polygenic component consisting of many common single-nucleotide polymorphisms (SNPs) of extremely small effect. Similar results have been reported in GWAS of general cognitive ability. The primary aim of the present study is to provide the first molecular genetic test of the classic endophenotype hypothesis, which states that alleles associated with reduced cognitive ability should also serve to increase risk for SCZ. We tested the endophenotype hypothesis by applying polygenic SNP scores derived from a large-scale cognitive GWAS meta-analysis (~5000 individuals from nine nonclinical cohorts comprising the Cognitive Genomics consorTium (COGENT)) to four SCZ case-control cohorts. As predicted, cases had significantly lower cognitive polygenic scores compared to controls. In parallel, polygenic risk scores for SCZ were associated with lower general cognitive ability. In addition, using our large cognitive meta-analytic data set, we identified nominally significant cognitive associations for several SNPs that have previously been robustly associated with SCZ susceptibility. Results provide molecular confirmation of the genetic overlap between SCZ and general cognitive ability, and may provide additional insight into pathophysiology of the disorder.

Genetic variants affecting the neural processing of human facial expressions: evidence using a genome-wide functional imaging approach.

Human faces present crucial visual information for social interaction. Specialized brain regions are involved in the perception of faces, with the fusiform face area (FFA) a key neuronal substrate. Face processing is genetically controlled, but by which specific genes is unknown. A genome-wide approach identified common single nucleotide polymorphisms (SNPs) associated with areas of increased brain activity in response to affective facial expressions, measured with functional magnetic resonance imaging. SNPs in 20 genetic regions were linked with neural responses to negative facial expressions in a Norwegian sample (n=246), which included patients with mental illness. Three genetic regions were linked with FFA activation in a further discovery experiment using positive facial expressions and involving many of the same individuals (n=284). Two of these three regions showed significant association with right FFA activation to negative facial expressions in an independent North American replication sample of healthy Caucasians (n=85, 3q26.31, P=0.004; 20p12.3, P=0.045). The activation patterns were particularly striking for the SNP in 3q26.31, which lies in a gene TMEM212; only the FFA was activated. The specialized function of this brain region suggests that TMEM212 could contribute to the innate architecture of face processing.