Multi-Polygenic Risk Score Prediction Model for Bipolar Disorder

Bipolar disorder (BP), a severe mental disorder characterized by recurring manic and depressive episodes, has been shown to have a strong genetic underpinning. Current theory suggests that it is the summation of risk alleles, spread across the entirety of the genome, which contributes to the development of BP, as well as other polygenic traits. The comorbid nature of these polygenic traits are often problematic for diagnosticians as the symptomology of the disorders may vary substantially between individuals and can create diagnostic confusion. To alleviate issues such as these, a more objective measure, to be used alongside current diagnostic procedures, is needed. To accomplish this, researchers have begun to turn their attention towards an ever increasing body of publicly available genetic data. Recently, polygenic risk scores have been implemented in genetic risk prediction. Genome-wide association study (GWAS) summary statistics, derived on a plethora of psychiatric disorders, are readily accessible and provide a cost efficient strategy for generating risk scores. In this study, we attempted to not only predict the diagnosis of bipolar disorder utilizing publicly available genotype information, but to also improve upon current methodology by showing that the inclusion of risk scores calculated on comorbid traits can benefit the accuracy and generalizability of the classification model. While the results reported herein are mixed, this study provides strong support for the feasibility of genetic prediction of psychiatric disorders. This approach was, to our knowledge, entirely novel and the first time it had been implemented in practice

Unraveling the Influence of Heritable Genetic Variation on Nicotine Use and Complex Human Traits

Smoking, a leading cause of preventable deaths worldwide and with both genetic and environmental influences, has been associated with numerous health risks, prompting the need for a deeper understanding of its genetic liability. Developing a deeper comprehension of the genetic factors influencing smoking behaviors may enhance our understanding of molecular pathways, networks, and their associations with other traits, aiming to identify potential treatment targets. Furthermore, the multifaceted nature and diverse genetic and environmental influences of smoking traits makes them exemplary phenotypes for understanding the genetics of complex traits. This dissertation encompasses three novel studies aimed at investigating the genetic influences on nicotine use and other complex traits. Chapter 2 used genome-wide association study summary statistics to examine whether human orthologs of genes identified in mice exposed to nicotine during development influence smoking behaviors in humans. This approach provided insight into the potential shared genetic architecture across species. Chapter 3 explored the use of expression-based gene-single nucleotide polymorphism (SNP) annotations to enhance the identification of relevant tissues associated with complex traits, including smoking behaviors. By leveraging estimated expression effects, this study aimed to uncover tissue-specific mechanisms underlying these traits. In Chapter 4, a transcriptome-wide association study was conducted to identify and characterize relevant SNPs, genes, and tissues associated with nicotine use and other complex traits. This study included diverse cohorts of varying ancestries and proposed methods to leverage multiple unrelated samples for enhanced statistical power. Collectively, the presented findings emphasize the polygenic nature of complex traits, highlight the need for larger and more ancestrally diverse sample sizes, and expand our toolkit for investigating genetic architecture, offering new avenues for exploring the genetics of human complex traits.</p

Validation of Induced Microglia-Like Cells (iMG Cells) for Future Studies of Brain Diseases

Microglia are the primary resident immune cells of the central nervous system that maintain physiological homeostasis in the brain and contribute to the pathogenesis of many psychiatric disorders and neurodegenerative diseases. Due to the lack of appropriate human cellular models, it is difficult to study the basic pathophysiological processes linking microglia to brain diseases. In this study, we adopted a microglia-like cellular model derived from peripheral blood monocytes with granulocyte-macrophage colony-stimulating factor (GM-CSF) and interleukin-34 (IL-34). We characterized and validated this in vitro cellular model by morphology, immunocytochemistry, gene expression profiles, and functional study. Our results indicated that the iMG cells developed typical microglial ramified morphology, expressed microglial specific surface markers (P2RY12 and TMEM119), and possessed phagocytic activity. Principal component analyses and multidimensional scaling analyses of RNA-seq data showed that iMG cells were distinct from monocytes and induced macrophages (iMacs) but clustered closer to human microglia and hiPSC-induced microglia. Heatmap analyses also found that iMG cells, but not monocytes, were closely clustered with human primary microglia. Further pathway and relative expression analysis indicated that unique genes from iMG cells were involved in the regulation of the complement system, especially in the synapse and ion transport. Overall, our data demonstrated that the iMG model mimicked many features of the brain resident microglia, highlighting its utility in the study of microglial function in many brain diseases, such as schizophrenia and Alzheimer\u27s disease (AD)

Polygenic Risk Scores for Subtyping of Schizophrenia

Schizophrenia is a complex disorder with many comorbid conditions. In this study, we used polygenic risk scores (PRSs) from schizophrenia and comorbid traits to explore consistent cluster structure in schizophrenia patients. With 10 comorbid traits, we found a stable 4-cluster structure in two datasets (MGS and SSCCS). When the same traits and parameters were applied for the patients in a clinical trial of antipsychotics, the CATIE study, a 5-cluster structure was observed. One of the 4 clusters found in the MGS and SSCCS was further split into two clusters in CATIE, while the other 3 clusters remained unchanged. For the 5 CATIE clusters, we evaluated their association with the changes of clinical symptoms, neurocognitive functions, and laboratory tests between the enrollment baseline and the end of Phase I trial. Class I was found responsive to treatment, with significant reduction for the total, positive, and negative symptoms (p=0.0001, 0.0099, and 0.0028, respectively), and improvement for cognitive functions (VIGILANCE, p=0.0099; PROCESSING SPEED, p=0.0006; WORKING MEMORY, p=0.0023; and REASONING, p=0.0015). Class II had modest reduction of positive symptoms (p=0.0492) and better PROCESSING SPEED (p=0.0071). Class IV had a specific reduction of negative symptoms (p=0.0111) and modest cognitive improvement for all tested domains. Interestingly, Class IV was also associated with decreased lymphocyte counts and increased neutrophil counts, an indication of ongoing inflammation or immune dysfunction. In contrast, Classes III and V showed no symptom reduction but a higher level of phosphorus. Overall, our results suggest that PRSs from schizophrenia and comorbid traits can be utilized to classify patients into subtypes with distinctive clinical features. This genetic susceptibility based subtyping may be useful to facilitate more effective treatment and outcome prediction

A Frameshift Variant in the CHST9 Gene Identified by Family-Based Whole Genome Sequencing Is Associated with Schizophrenia in Chinese Population

Recent studies imply that rare variants contribute to the risk of schizophrenia, however, the exact variants or genes responsible for this condition are largely unknown. In this study, we conducted whole genome sequencing (WGS) of 20 Chinese families. Each family consisted of at least two affected siblings diagnosed with schizophrenia and at least one unaffected sibling. We examined functional variants that were found in affected sibling(s) but not in unaffected sibling(s) within a family. Matching this criterion, a frameshift heterozygous deletion of CA (–/CA) at chromosome 18:24722722, also referred to as rs752084147, in the Carbohydrate Sulfotransferase 9 (CHST9) gene, was detected in two families. This deletion was confirmed by PCR-based Sanger sequencing. With the observed frequency of 0.00076 in Han Chinese population, we performed both case-control and family-based analyses to evaluate its association with schizophrenia. In the case-control analyses, Chi-square test P-value was 6.80e-12 and the P-value was 0.0008 after one million simulations. In family-based segregation analyses, segregation P-value was 7.72e-7 and simulated P-value was 5.70e-6. For both the case-control and family-based analyses, the CA deletion was significantly associated with schizophrenia in the Chinese population. Further investigation of this gene is warranted in the development of schizophrenia by utilizing larger and more ethnically diverse samples

Retraction Note: Identification of de Novo Mutations in Prenatal Neurodevelopment-Associated Genes in Schizophrenia in Two Han Chinese Patient-Sibling Family-Based Cohorts (Translational Psychiatry, (2020), 10, 1, (307), 10.1038/s41398-020-00987-Z)

© 2020, The Author(s). This article1 has been retracted at the request of Authors Xingwang Li and Lin He. After publication, it was realized that approval to use data from the NSFC-NIH Sino-US cooperation project (Project No. 81361120389) was not obtained from the data owners. Authors Dongmei Cao, Xiangning Chen, Lin He, Kenneth Kendler, Xingwang Li, Travis Mize, Chunling Wan and Jain-Shing Wu agree to this retraction. Authors Shan Jiang, Jingchun Chen and Zongming Zhao do not agree to this retraction. Authors Guang He, Peilin Jia, Xiaoqian Jiang, Yimei Lu, Ming Tsuang, Yin-Ying Wang and Daizhan Zhou did not respond to correspondence from the Publisher about this retraction

Identification of CHST9 as A Candidate Gene for Schizophrenia from Whole Genome Sequencing

Recent results imply that rare variants contribute to the risk of schizophrenia. We conducted whole genome sequencing for 99 subjects from 20 Chinese families (parents and at least two siblings with a schizophrenia diagnosis and one unaffected sibling). Of the 9 frameshift mutations identified in more than 2 families, one was at chromosome 10:125780762 on the Carbohydrate Sulfotransferase 15 (CHST15) gene and another at chromosome 18:24722723 on the Carbohydrate Sulfotransferase 9 (CHST9) gene. We observed these deletions in 4 affected persons of two families from whole. At least two types of mutations (one or three bases insertion) have been identified in 6 families. Given the frequencies of these mutations observed in the general population (data from ExAC database:http://exac.broadinstitute.org/) are between 0.002 to 0.00001, the largest p-value that CHST15 is associated with schizophrenia is less than 0.002^6, or 6.4E-17. This finding was replicated in an independent Chinese sample of 85 subjects from 17 families, where 7 families were found with similar mutations at the same location. We are in the process to validate these mutations by PCR- and cloning-based Sanger Sequencing. CHST15 and CHST9 has been reported to be associated with cancers but never with schizophrenia. Further study of the biological functions of CHST15 and CHST9 genes are warranted to understand their contribution to schizophrenia

Transcriptome-wide gene-gene interaction associations elucidate pathways and functional enrichment of complex traits.

It remains unknown to what extent gene-gene interactions contribute to complex traits. Here, we introduce a new approach using predicted gene expression to perform exhaustive transcriptome-wide interaction studies (TWISs) for multiple traits across all pairs of genes expressed in several tissue types. Using imputed transcriptomes, we simultaneously reduce the computational challenge and improve interpretability and statistical power. We discover (in the UK Biobank) and replicate (in independent cohorts) several interaction associations, and find several hub genes with numerous interactions. We also demonstrate that TWIS can identify novel associated genes because genes with many or strong interactions have smaller single-locus model effect sizes. Finally, we develop a method to test gene set enrichment of TWIS associations (E-TWIS), finding numerous pathways and networks enriched in interaction associations. Epistasis is may be widespread, and our procedure represents a tractable framework for beginning to explore gene interactions and identify novel genomic targets

A Frameshift Variant in the CHST9 Gene Identified by Family-Based Whole Genome Sequencing Is Associated with Schizophrenia in Chinese Population.

Recent studies imply that rare variants contribute to the risk of schizophrenia, however, the exact variants or genes responsible for this condition are largely unknown. In this study, we conducted whole genome sequencing (WGS) of 20 Chinese families. Each family consisted of at least two affected siblings diagnosed with schizophrenia and at least one unaffected sibling. We examined functional variants that were found in affected sibling(s) but not in unaffected sibling(s) within a family. Matching this criterion, a frameshift heterozygous deletion of CA (-/CA) at chromosome 18:24722722, also referred to as rs752084147, in the Carbohydrate Sulfotransferase 9 (CHST9) gene, was detected in two families. This deletion was confirmed by PCR-based Sanger sequencing. With the observed frequency of 0.00076 in Han Chinese population, we performed both case-control and family-based analyses to evaluate its association with schizophrenia. In the case-control analyses, Chi-square test P-value was 6.80e-12 and the P-value was 0.0008 after one million simulations. In family-based segregation analyses, segregation P-value was 7.72e-7 and simulated P-value was 5.70e-6. For both the case-control and family-based analyses, the CA deletion was significantly associated with schizophrenia in the Chinese population. Further investigation of this gene &nbsp;is warranted&nbsp;in the development of schizophrenia by&nbsp;utilizing larger and more ethnically diverse samples