Transcriptional level of inflammation markers associates with short-term brain structural changes in first-episode schizophrenia.

BACKGROUND: Inflammation has been implicated in the pathology of schizophrenia and may cause neuronal cell death and dendrite loss. Neuroimaging studies have highlighted longitudinal brain structural changes in patients with schizophrenia, yet it is unclear whether this is related to inflammation. We aim to address this question, by relating brain structural changes with the transcriptional profile of inflammation markers in the early stage of schizophrenia. METHODS: Thirty-eight patients with first-episode schizophrenia and 51 healthy controls were included. High-resolution T1-weighted magnetic resonance imaging (MRI) and clinical assessments were performed at baseline and 2 ~ 6 months follow-up for all subjects. Changes in the brain structure were analyzed using surface-based morphological analysis and correlated with the expression of immune cells-related gene sets of interest reported by previous reviews. Transcriptional data were retrieved from the Allen Human Brain Atlas. Furthermore, we examined the brain structural changes and peripheral inflammation markers in association with behavioral symptoms and cognitive functioning in patients. RESULTS: Patients exhibited accelerated cortical thickness decrease in the left frontal cortices, less decrease or an increase in the superior parietal lobule and right lateral occipital lobe, and increased volume in the bilateral pallidum, compared with controls. Changes in cortical thickness correlated with the transcriptional level of monocyte across cortical regions in patients (r = 0.54, p < 0.01), but not in controls (r = - 0.05, p = 0.76). In addition, cortical thickness change in the left superior parietal lobule positively correlated with changes in digital span-backward test scores in patients. CONCLUSIONS: Patients with schizophrenia exhibit regional-specific cortical thickness changes in the prefrontal and parietooccipital cortices, which is related to their cognitive impairment. Inflammation may be an important factor contributing to cortical thinning in first-episode schizophrenia. Our findings suggest that the immunity-brain-behavior association may play a crucial role in the pathogenesis of schizophrenia.

Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank.

The current study was conducted to provide a general guidance for model specifications in polygenic risk score (PRS) analyses of the UK Biobank, such as adjusting for covariates (i.e. age, sex, recruitment centers, and genetic batch) and the number of principal components (PCs) that need to be included. To cover behavioral, physical and mental health outcomes, we evaluated three continuous outcomes (BMI, smoking, drinking) and two binary outcomes (Major Depressive Disorder and educational attainment). We applied 3280 (656 per phenotype) different models including different sets of covariates. We evaluated these different model specifications by comparing regression parameters such as R2, coefficients, and P values, as well as ANOVA tests. Findings suggest that only up to three PCs appears to be sufficient for controlling population stratification for most outcomes, whereas including other covariates (particularly age and sex) appears to be more essential for model performance.

Associations between genetic liabilities to smoking behavior and schizophrenia symptoms in patients with a psychotic disorder, their siblings and healthy controls.

It is unknown how smoking behavior polygenic scores (PRS) relate to psychosis and psychotic symptoms. To elucidate this, genotype and phenotype data were collected from patients with schizophrenia, their unaffected siblings, and healthy controls in a six-year follow-up prospective cohort study. Associations between smoking behaviors, PRS and schizophrenia symptoms were explored using linear mixed-effect models. The mean number of cigarettes smoked per day were 18 for patients, 13 for siblings and 12 for controls. In the overall sample, PRSs-smoking initiation (i.e., ever smoking as a binary phenotype, PRS-SI) were positively associated with positive symptoms, negative symptoms, and depressive symptoms, whereas PRSs-AI (age at regular smoking initiation) were negatively associated with all symptom dimensions, with similar effect sizes. When considering groups separately, PRS were only associated with psychotic symptoms in siblings and controls. In conclusion, unaffected siblings show smoking behaviors at an intermediate level between patients and healthy controls. Additionally, PRS-SI and PRS-AI are associated with all symptom dimensions only in unaffected siblings and healthy controls, possibly owing to the dominant role of other (genetic) risk factors in patients. Future studies may examine mechanisms via which genetic risk for smoking affects mental health symptoms.

Nongenetic Factors Associated With Psychotic Experiences Among UK Biobank Participants: Exposome-Wide Analysis and Mendelian Randomization Analysis.

Importance: Although hypothesis-driven research has identified several factors associated with psychosis, this one-exposure-to-one-outcome approach fails to embrace the multiplicity of exposures. Systematic approaches, similar to agnostic genome-wide analyses, are needed to identify genuine signals. Objective: To systematically investigate nongenetic correlates of psychotic experiences through data-driven agnostic analyses and genetically informed approaches to evaluate associations. Design, Setting, Participants: This cohort study analyzed data from the UK Biobank Mental Health Survey from January 1 to June 1, 2021. An exposome-wide association study was performed in 2 equal-sized split discovery and replication data sets. Variables associated with psychotic experiences in the exposome-wide analysis were tested in a multivariable model. For the variables associated with psychotic experiences in the final multivariable model, the single-nucleotide variant-based heritability and genetic overlap with psychotic experiences using linkage disequilibrium score regression were estimated, and mendelian randomization (MR) approaches were applied to test potential causality. The significant associations observed in 1-sample MR analyses were further tested in multiple sensitivity tests, including collider-correction MR, 2-sample MR, and multivariable MR analyses. Exposures: After quality control based on a priori criteria, 247 environmental, lifestyle, behavioral, and economic variables. Main Outcomes and Measures: Psychotic experiences. Results: The study included 155 247 participants (87 896 [57%] female; mean [SD] age, 55.94 [7.74] years). In the discovery data set, 162 variables (66%) were associated with psychotic experiences. Of these, 148 (91%) were replicated. The multivariable analysis identified 36 variables that were associated with psychotic experiences. Of these, 28 had significant genetic overlap with psychotic experiences. One-sample MR analyses revealed forward associations with 3 variables and reverse associations with 3. Forward associations with ever having experienced sexual assault and pleiotropy of risk-taking behavior and reverse associations without pleiotropy of experiencing a physically violent crime as well as cannabis use and the reverse association with pleiotropy of worrying too long after embarrassment were confirmed in sensitivity tests. Thus, associations with psychotic experiences were found with both well-studied and unexplored multiple correlated variables. For several variables, the direction of the association was reversed in the final multivariable and MR analyses. Conclusions and Relevance: The findings of this study underscore the need for systematic approaches and triangulation of evidence to build a knowledge base from ever-growing observational data to guide population-level prevention strategies for psychosis.

Phenome-wide and genome-wide analyses of quality of life in schizophrenia.

BACKGROUND: Schizophrenia negatively affects quality of life (QoL). A handful of variables from small studies have been reported to influence QoL in patients with schizophrenia, but a study comprehensively dissecting the genetic and non-genetic contributing factors to QoL in these patients is currently lacking. AIMS: We adopted a hypothesis-generating approach to assess the phenotypic and genotypic determinants of QoL in schizophrenia. METHOD: The study population comprised 1119 patients with a psychotic disorder, 1979 relatives and 586 healthy controls. Using linear regression, we tested >100 independent demographic, cognitive and clinical phenotypes for their association with QoL in patients. We then performed genome-wide association analyses of QoL and examined the association between polygenic risk scores for schizophrenia, major depressive disorder and subjective well-being and QoL. RESULTS: We found nine phenotypes to be significantly and independently associated with QoL in patients, the most significant ones being negative (ß = -1.17; s.e. 0.05; P = 1 × 10-83; r2 = 38%), depressive (ß = -1.07; s.e. 0.05; P = 2 × 10-79; r2 = 36%) and emotional distress (ß = -0.09; s.e. 0.01; P = 4 × 10-59, r2 = 25%) symptoms. Schizophrenia and subjective well-being polygenic risk scores, using various P-value thresholds, were significantly and consistently associated with QoL (lowest association P-value = 6.8 × 10-6). Several sensitivity analyses confirmed the results. CONCLUSIONS: Various clinical phenotypes of schizophrenia, as well as schizophrenia and subjective well-being polygenic risk scores, are associated with QoL in patients with schizophrenia and their relatives. These may be targeted by clinicians to more easily identify vulnerable patients with schizophrenia for further social and clinical interventions to improve their QoL.

The role of rare compound heterozygous events in autism spectrum disorder.

The identification of genetic variants underlying autism spectrum disorders (ASDs) may contribute to a better understanding of their underlying biology. To examine the possible role of a specific type of compound heterozygosity in ASD, namely, the occurrence of a deletion together with a functional nucleotide variant on the remaining allele, we sequenced 550 genes in 149 individuals with ASD and their deletion-transmitting parents. This approach allowed us to identify additional sequence variants occurring in the remaining allele of the deletion. Our main goal was to compare the rate of sequence variants in remaining alleles of deleted regions between probands and the deletion-transmitting parents. We also examined the predicted functional effect of the identified variants using Combined Annotation-Dependent Depletion (CADD) scores. The single nucleotide variant-deletion co-occurrence was observed in 13.4% of probands, compared with 8.1% of parents. The cumulative burden of sequence variants (n = 68) in pooled proband sequences was higher than the burden in pooled sequences from the deletion-transmitting parents (n = 41, X2 = 6.69, p = 0.0097). After filtering for those variants predicted to be most deleterious, we observed 21 of such variants in probands versus 8 in their deletion-transmitting parents (X2 = 5.82, p = 0.016). Finally, cumulative CADD scores conferred by these variants were significantly higher in probands than in deletion-transmitting parents (burden test, ß = 0.13; p = 1.0 × 10-5). Our findings suggest that the compound heterozygosity described in the current study may be one of several mechanisms explaining variable penetrance of CNVs with known pathogenicity for ASD.

2SNP heritability and effects of genetic variants for neutrophil-to-lymphocyte and platelet-to-lymphocyte ratio.

Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) are important biomarkers for disease development and progression. To gain insight into the genetic causes of variance in NLR and PLR in the general population, we conducted genome-wide association (GWA) analyses and estimated SNP heritability in a sample of 5901 related healthy Dutch individuals. GWA analyses identified a new genome-wide significant locus on the HBS1L-MYB intergenic region for PLR, which replicated in a sample of 2538 British twins. For platelet count, we replicated three known genome-wide significant loci in our cohort (at CCDC71L-PIK3CG, BAK1 and ARHGEF3). For neutrophil count, we replicated the PSMD3 locus. For the identified top SNPs, we found significant cis and trans expression quantitative trait loci effects for several loci involved in hematological and immunological pathways. Linkage Disequilibrium score (LD) regression analyses for PLR and NLR confirmed that both traits are heritable, with a polygenetic SNP heritability for PLR of 14.1%, and for NLR of 2.4%. Genetic correlations were present between ratios and the constituent counts, with the genetic correlation (r=0.45) of PLR with platelet count reaching statistical significance. In conclusion, we established that two important biomarkers have a significant heritable SNP component, and identified the first genome-wide locus for PLR.

Heritability and Genome-Wide Association Studies for Hair Color in a Dutch Twin Family Based Sample.

Hair color is one of the most visible and heritable traits in humans. Here, we estimated heritability by structural equation modeling (N = 20,142), and performed a genome wide association (GWA) analysis (N = 7091) and a GCTA study (N = 3340) on hair color within a large cohort of twins, their parents and siblings from the Netherlands Twin Register (NTR). Self-reported hair color was analyzed as five binary phenotypes, namely "blond versus non-blond", "red versus non-red", "brown versus non-brown", "black versus non-black", and "light versus dark". The broad-sense heritability of hair color was estimated between 73% and 99% and the genetic component included non-additive genetic variance. Assortative mating for hair color was significant, except for red and black hair color. From GCTA analyses, at most 24.6% of the additive genetic variance in hair color was explained by 1000G well-imputed SNPs. Genome-wide association analysis for each hair color showed that SNPs in the MC1R region were significantly associated with red, brown and black hair, and also with light versus dark hair color. Five other known genes (HERC2, TPCN2, SLC24A4, IRF4, and KITLG) gave genome-wide significant hits for blond, brown and light versus dark hair color. We did not find and replicate any new loci for hair color.