Genetics of schizophrenia (Review)

Circulating inflammatory cytokines influencing schizophrenia: a Mendelian randomization study

Introduction

Schizophrenia (SCZ) is a severe psychiatric disorder whose pathophysiology remains elusive. Recent investigations have underscored the significance of systemic inflammation, particularly the impact of circulating inflammatory proteins, in SCZ.

Methods

This study explores the potential causal association between certain inflammatory proteins and SCZ. Bidirectional Mendelian randomization (MR) analyses were conducted utilizing data from expansive genome-wide association studies (GWAS). Data regarding circulating inflammatory proteins were sourced from the GWAS Catalog database, encompassing 91 inflammatory cytokines. SCZ-related data were derived from the Finngen database, incorporating 47,696 cases and 359,290 controls. Analytical methods such as inverse variance weighted, MR-Egger, weighted median, simple mode, and weighted mode were employed to evaluate the association between inflammatory cytokines and SCZ. Sensitivity analyses were also performed to affirm the robustness of the results.

Results

Following FDR adjustment, significant associations were observed between levels of inflammatory cytokines, including Fibroblast Growth Factor 5 (OR = 1.140, 95%CI = 1.045, 1.243, p = 0.003, FDR=0.015), C-C Motif Chemokine 4 (OR = 0.888, 95%CI = 0.816, 0.967, p = 0.006, FDR = 0.015), C-X-C Motif Chemokine 1 (OR = 0.833, 95%CI = 0.721, 0.962, p = 0.013, FDR = 0.064), and C-X-C Motif Chemokine 5 (OR = 0.870, 95%CI = 0.778, 0.973, p = 0.015, FDR = 0.074), and the risk of SCZ.

Conclusion

Our results from MR analysis suggest a potential causal link between circulating inflammatory cytokines and SCZ, thereby enriching our understanding of the interactions between inflammation and SCZ. Furthermore, these insights provide a valuable foundation for devising therapeutic strategies targeting inflammation.

The Finnish Adoptive Family Study of Schizophrenia: differences in somatic diseases and conditions between adoptees with high or low genetic risk for schizophrenia spectrum disorders

BACKGROUND AND AIMS

There is some evidence that offspring of patients with schizophrenia have higher somatic morbidity, which is thought to be partially due to genetic links between somatic disorders and schizophrenia. This study explored differences in somatic diseases and conditions of adoptees with high genetic risk (HR) or low genetic risk (LR) for schizophrenia spectrum disorders.

MATERIAL AND METHODS

The study is part of the Finnish Adoptive Family Study of Schizophrenia. The adoptive research design used made it possible to examine how the somatic health of adoptees raised in similar adoptive families, is affected by their genetic susceptibility to schizophrenia. The study sample consisted of 373 adoptees, of whom 190 had HR and 183 had LR for schizophrenia spectrum disorders. Data on somatic morbidity were gathered from the hospital records and from the national registers of the Care Register of Health Care and the Social Insurance Institution.

RESULTS

The only statistically significant difference found was in genitourinary diseases, the likelihood being twofold higher in HR adoptees compared to LR adoptees (16.8% vs. 8.2%; adj. OR = 2.13, 95% CI 1.06-4.25, p = .033). Adoptees who were female and aged over 40 had a higher prevalence of genitourinary illnesses than non-adoptees.

CONCLUSION

The significant prevalence of genitourinary diseases in adoptees at risk for schizophrenia spectrum disorders suggests that some specific somatic diseases and schizophrenia may have a shared hereditary etiology. More research is required for specific somatic diseases in study populations that can differentiate between the effects of genetic and environmental factors.

A multi-threaded approach to genotype pattern mining for detecting digenic disease genes

To locate disease-causing DNA variants on the human gene map, the customary approach has been to carry out a genome-wide association study for one variant after another by testing for genotype frequency differences between individuals affected and unaffected with disease. So-called digenic traits are due to the combined effects of two variants, often on different chromosomes, while individual variants may have little or no effect on disease. Machine learning approaches have been developed to find variant pairs underlying digenic traits. However, many of these methods have large memory requirements so that only small datasets can be analyzed. The increasing availability of desktop computers with large numbers of processors and suitable programming to distribute the workload evenly over all processors in a machine make a new and relatively straightforward approach possible, that is, to evaluate all existing variant and genotype pairs for disease association. We present a prototype of such a method with two components, Vpairs and Gpairs, and demonstrate its advantages over existing implementations of such well-known algorithms as Apriori and FP-growth. We apply these methods to published case-control datasets on age-related macular degeneration and Parkinson disease and construct an ROC curve for a large set of genotype patterns.

The Structure of Temperament in Caregivers of Patients with Schizophrenia

The onset of schizophrenia symptoms usually occurs in early youth. As a result, the parents of these patients usually become their caregivers. The role of a caregiver for a person with schizophrenia is a considerable mental and physical burden. Therefore, an interesting issue is what motivates these people to take up this challenge. It is probable that, apart from the moral imperative or kinship, the factor determining this decision is the personality structure of the caregiver. The aim of our study was to compare the structure of temperament (according to the model of temperament as formal characteristics of behavior developed by Jan Strelau) in caregivers of young adults (age 18-25 years) with schizophrenia with the structure of temperament of parents of healthy young adults still living in the family home under their care. The study group consisted of 64 people (51 women), who were taking care of young adults (aged 18-25 years) with schizophrenia, while the control group (53 people, 42 women) consisted of parents of healthy adults still living in the family home. Both groups were asked to complete a questionnaire of the authors' own design on their demographic data as well as The Formal Characteristics of Behavior-Temperament Inventory to assess the temperament traits. The results were given in the number of points obtained on average in each dimension. Both groups did not differ in terms of size and age, with women predominating. Caregivers of young adults with schizophrenia had higher values of briskness (43.22 ± 4.45 vs. 42.90 ± 3.98, p = 0.032), emotional reactivity (46.02 ± 4.39 vs. 41.01 ± 3.12, p = 0.012) and activity level (44.01.89 ± 4.15 vs. 37.59 ± 4.77, p = 0.022) compared to the control group. The remaining dimensions of temperament: perseverance, sensory sensitivity, rhythmicity, and endurance did not differentiate between the two groups. The temperament structure of caregivers of young people with schizophrenia differs from the temperament structure of caregivers of healthy adults. Caregivers of sick people have higher values of briskness, emotional reactivity, and activity level compared to the control group.

Translational Study of Copy Number Variations in Schizophrenia

Rare copy number variations (CNVs) are part of the genetics of schizophrenia; they are highly heterogeneous and personalized. The CNV Analysis Group of the Psychiatric Genomic Consortium (PGC) conducted a large-scale analysis and discovered that recurrent CNVs at eight genetic loci were pathogenic to schizophrenia, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.23, 15q13.3, distal 16p11.2, proximal 16p11.2, and 22q11.2. We adopted a two-stage strategy to translate this knowledge into clinical psychiatric practice. As a screening test, we first developed a real-time quantitative PCR (RT-qPCR) panel that simultaneously detected these pathogenic CNVs. Then, we tested the utility of this screening panel by investigating a sample of 557 patients with schizophrenia. Chromosomal microarray analysis (CMA) was used to confirm positive cases from the screening test. We detected and confirmed thirteen patients who carried CNVs at these hot loci, including two patients at 1q21.1, one patient at 7q11.2, three patients at 15q13.3, two patients at 16p11.2, and five patients at 22q11.2. The detection rate in this sample was 2.3%, and the concordance rate between the RT-qPCR test panel and CMA was 100%. Our results suggest that a two-stage approach is cost-effective and reliable in achieving etiological diagnosis for some patients with schizophrenia and improving the understanding of schizophrenia genetics.

Identification of a Rare Novel KMT2C Mutation That Presents with Schizophrenia in a Multiplex Family

Schizophrenia is a complex genetic disorder involving many common variants with modest effects and rare mutations with high penetrance. Rare mutations associated with schizophrenia are highly heterogeneous and private for affected individuals and families. Identifying such mutations can help establish the molecular diagnosis, elucidate the pathogenesis, and provide helpful genetic counseling for affected patients and families. We performed a whole-exome sequencing analysis to search for rare pathogenic mutations co-segregating with schizophrenia transmitted in a dominant inheritance in a two-generation multiplex family. We identified a rare missense mutation H1574R (Histidine1574Arginine, rs199796552) of KMT2C (lysine methyltransferase 2C) co-segregating with affected members in this family. The mutation is a novel deleterious mutation of KMT2C, not reported before in the literature. The KMT2C encodes a histone 3 lysine 4 (H3K4)-specific methyltransferase and involves epigenetic regulation of brain gene expression. Mutations of KMT2C have been found in neurodevelopmental disorders, such as Kleefstra syndrome, intellectual disability, and autism spectrum disorders. Our finding suggests that schizophrenia might be one of the clinical phenotype spectra of KMT2C mutations, and KMT2C might be a novel risk gene for schizophrenia. Nevertheless, the co-segregation of this mutation with schizophrenia in this family might also be due to chance; functional assays of this mutation are needed to address this issue.

Identification of Rare Mutations of Two Presynaptic Cytomatrix Genes BSN and PCLO in Schizophrenia and Bipolar Disorder

Schizophrenia and bipolar disorder are severe mental disorders with a major component of genetic factors in their etiology. Rare mutations play a significant role in these two disorders, and they are highly heterogeneous and personalized. Identification of personalized mutations is essential for the establishment of molecular diagnosis, providing insight into pathogenesis and guiding the personalized treatment for each affected patient. We conducted whole-genome sequencing analysis of families with schizophrenia and bipolar disorder to search for their genetic underpinnings. This report identified a rare missense mutation Arg1087Gln of BSN (bassoon presynaptic cytomatrix protein) co-segregating with schizophrenia in a family with multiple affected members. Furthermore, we identified the rare missense mutation Ser1535Leu of PCLO (piccolo presynaptic cytomatrix protein) in two sisters with bipolar disorder and another rare missense mutation, His5142Arg in PCLO, in a patient with schizophrenia. These three missense mutations were very rare and were predicted to be pathogenic. The BSN and PCLO genes encode two structurally related proteins of the presynaptic cytomatrix at the active zone that regulates neurotransmission at the presynaptic neuronal terminal. Our findings suggest the involvement of the presynaptic matrix in the pathogenesis of schizophrenia and bipolar disorder, and BSN and PCLO are the risk genes for schizophrenia and bipolar disorder.

Evaluation of Genotype-Based Gene Expression Model Performance: A Cross-Framework and Cross-Dataset Study

Predicting gene expression from genotyped data is valuable for studying inaccessible tissues such as the brain. Herein we present eGenScore, a polygenic/poly-variation method, and compare it with PrediXcan, a method based on regularized linear regression using elastic nets. While both methods have the same purpose of predicting gene expression based on genotype, they carry important methodological differences. We compared the performance of expression quantitative trait loci (eQTL) models to predict gene expression in the frontal cortex, comparing across these frameworks (eGenScore vs. PrediXcan) and training datasets (BrainEAC, which is brain-specific, vs. GTEx, which has data across multiple tissues). In addition to internal five-fold cross-validation, we externally validated the gene expression models using the CommonMind Consortium database. Our results showed that (1) PrediXcan outperforms eGenScore regardless of the training database used; and (2) when using PrediXcan, the performance of the eQTL models in frontal cortex is higher when trained with GTEx than with BrainEAC.

Shedding light on the role of CX3CR1 in the pathogenesis of schizophrenia

Schizophrenia has a complex and heterogeneous molecular and clinical picture. Over the years of research on this disease, many factors have been suggested to contribute to its pathogenesis. Recently, the inflammatory processes have gained particular interest in the context of schizophrenia due to the increasing evidence from epidemiological, clinical and experimental studies. Within the immunological component, special attention has been brought to chemokines and their receptors. Among them, CX3C chemokine receptor 1 (CX3CR1), which belongs to the family of seven-transmembrane G protein-coupled receptors, and its cognate ligand (CX3CL1) constitute a unique system in the central nervous system. In the view of regulation of the brain homeostasis through immune response, as well as control of microglia reactivity, the CX3CL1–CX3CR1 system may represent an attractive target for further research and schizophrenia treatment. In the review, we described the general characteristics of the CX3CL1–CX3CR1 axis and the involvement of this signaling pathway in the physiological processes whose disruptions are reported to participate in mechanisms underlying schizophrenia. Furthermore, based on the available clinical and experimental data, we presented a guide to understanding the implication of the CX3CL1–CX3CR1 dysfunctions in the course of schizophrenia.