Endophenotypes for Psychosis: Genetic Basis and Mechanistic Insights

Despite breakthroughs made by genome-wide association studies (GWAS) in our understanding of psychosis, further research is still needed to characterise the effects of the genetic variants identified and clarify the neurobiological mechanisms underlying these associations. In this thesis, I aim to bridge these knowledge gaps by studying endophenotypes for psychosis, which are intermediate phenotypes associated with the genetics of psychosis that pinpoint abnormalities in a specific neurobiological domain. In Chapter 1, I conducted a meta-analysis on the N100 event-related potential, combining the results of a local family study and previous literature. I found reduced N100 amplitudes and prolonged N100 latencies in both patients with psychosis and their unaffected relatives compared to controls, suggesting that the N100 is a promising endophenotype. Further analysis of the local family study revealed that the N100 was associated with the CHRNA4 gene, indicating the potential involvement of nicotinic acetylcholine receptors in the N100. In Chapter 2, I computed gene-set specific polygenic risk scores for psychosis by stratifying polygenic risk scores into specific biological domains and tested their associations with established endophenotypes. I found that reduced P300 amplitudes were associated with abnormalities in early brain development in psychosis, supporting the neurodevelopmental hypothesis of schizophrenia. Finally, Chapter 3 involves a mixed-model GWAS on adolescent verbal memory as a psychosis endophenotype in a sample of diverse genetic ancestry. I found new evidence of a significant genetic correlation between schizophrenia and verbal memory in adolescents, consistent with previous observations in family studies. Furthermore, I discovered two genome-wide significant loci that influence verbal memory performance. In particular, the NSF gene identified by my GWAS is involved in synaptic neurotransmission and membrane fusion, and thus my data suggest it plays a role in verbal memory deficits in psychosis. This thesis integrates multiple research methods covering neurophysiology, cognition, and genomics to show how endophenotypes for psychosis can inform our understanding of its aetiology

Neurophysiology in psychosis: The quest for disease biomarkers

Psychotic disorders affect 3% of the population at some stage in life, are a leading cause of disability, and impose a great economic burden on society. Major breakthroughs in the genetics of psychosis have not yet been matched by an understanding of its neurobiology. Biomarkers of perception and cognition obtained through non-invasive neurophysiological tools, especially EEG, offer a unique opportunity to gain mechanistic insights. Techniques for measuring neurophysiological markers are inexpensive and ubiquitous, thus having the potential as an accessible tool for patient stratification towards early treatments leading to better outcomes. In this paper, we review the literature on neurophysiological markers for psychosis and their relevant disease mechanisms, mainly covering event-related potentials including P50/N100 sensory gating, mismatch negativity, and the N100 and P300 waveforms. While several neurophysiological deficits are well established in patients with psychosis, more research is needed to study neurophysiological markers in their unaffected relatives and individuals at clinical high risk. We need to harness EEG to investigate markers of disease risk as key steps to elucidate the aetiology of psychosis and facilitate earlier detection and treatment

CYP2D6 Genetic Variation and Antipsychotic-Induced Weight Gain:A Systematic Review and Meta-Analysis

BACKGROUND: Antipsychotic-induced weight gain is a contributing factor in the reduced life expectancy reported amongst people with psychotic disorders. CYP2D6 is a liver enzyme involved in the metabolism of many commonly used antipsychotic medications. We investigated if CYP2D6 genetic variation influenced weight or BMI among people taking antipsychotic treatment. METHODS: We conducted a systematic review and a random effects meta-analysis of publications in Pubmed, Embase, PsychInfo, and CENTRAAL that had BMI and/or weight measurements of patients on long-term antipsychotics by their CYP2D6-defined metabolic groups (poor, intermediate, normal/extensive, and ultra-rapid metabolizers, UMs). RESULTS: Twelve studies were included in the systematic review. All cohort studies suggested that the presence of reduced-function or non-functional alleles for CYP2D6 was associated with greater antipsychotic-induced weight gain, whereas most cross-sectional studies did not find any significant associations. Seventeen studies were included in the meta-analysis with clinical data of 2,041 patients, including 93 poor metabolizers (PMs), 633 intermediate metabolizers (IMs), 1,272 normal metabolizers (NMs), and 30 UMs. Overall, we did not find associations in any of the comparisons made. The estimated pooled standardized differences for the following comparisons were (i) PM versus NM; weight = –0.07 (95%CI: –0.49 to 0.35, p = 0.74), BMI = 0.40 (95%CI: –0.19 to 0.99, p = 0.19). (ii) IM versus NM; weight = 0.09 (95% CI: –0.04 to 0.22, p = 0.16) and BMI = 0.09 (95% CI: –0.24 to 0.41, p = 0.60). (iii) UM versus EM; weight = 0.01 (95% CI: –0.37 to 0.40, p = 0.94) and BMI = –0.08 (95%CI: –0.57 to 0.42, p = 0.77). CONCLUSION: Our systematic review of cohort studies suggested that CYP2D6 poor metabolizers have higher BMI than normal metabolizers, but the data of cross-sectional studies and the meta-analysis did not show this association. Although our review and meta-analysis constitutes one of the largest studies with comprehensively genotyped samples, the literature is still limited by small numbers of participants with genetic variants resulting in poor or UMs status. We need further studies with larger numbers of extreme metabolizers to establish its clinical utility in antipsychotic treatment. CYP2D6 is a key gene for personalized prescribing in mental health

Schizophrenia and cardiometabolic abnormalities: A Mendelian randomization study

Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect.Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis.Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10−8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods.Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001–0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002–0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis.Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis

Psychosis Endophenotypes:A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models

Psychosis Endophenotypes:A Gene-Set-Specific Polygenic Risk Score Analysis

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes.STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score.STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores.CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.</p

Adolescent Verbal Memory as a Psychosis Endophenotype: A Genome-Wide Association Study in an Ancestrally Diverse Sample

Verbal memory impairment is one of the most prominent cognitive deficits in psychosis. However, few studies have investigated the genetic basis of verbal memory in a neurodevelopmental context, and most genome-wide association studies (GWASs) have been conducted in European-ancestry populations. We conducted a GWAS on verbal memory in a maximum of 11,017 participants aged 8.9 to 11.1 years in the Adolescent Brain Cognitive Development Study&reg;, recruited from a diverse population in the United States. Verbal memory was assessed by the Rey Auditory Verbal Learning Test, which included three measures of verbal memory: immediate recall, short-delay recall, and long-delay recall. We adopted a mixed-model approach to perform a joint GWAS of all participants, adjusting for ancestral background and familial relatedness. The inclusion of participants from all ancestries increased the power of the GWAS. Two novel genome-wide significant associations were found for short-delay and long-delay recall verbal memory. In particular, one locus (rs9896243) associated with long-delay recall was mapped to the NSF (N-Ethylmaleimide Sensitive Factor, Vesicle Fusing ATPase) gene, indicating the role of membrane fusion in adolescent verbal memory. Based on the GWAS in the European subset, we estimated the SNP-heritability to be 15% to 29% for the three verbal memory traits. We found that verbal memory was genetically correlated with schizophrenia, providing further evidence supporting verbal memory as an endophenotype for psychosis

Atmospheric-pressure non-equilibrium plasmas for effective abatement of pathogenic biological aerosols

The COVID-19, viral influenza, tuberculosis, and other widespread infectious diseases evidence that pathogenic biological aerosols (PBAs) are a serious threat to public health. Different from traditional inactivation methods, such as ultraviolet (UV) light which are only safe to use when people are not present, and high-efficiency particulate filters (HEPA) which merely filter microbes without killing them, atmospheric pressure nonequilibrium plasma (APNP) has shown its tremendous potential in drastically diminishing the aerosol transmission route of the infectious agents through the abatement of PBAs. The key issues to develop high performance APNP based air purification system are critically reviewed. Systematic studies on the hazards of different PBAs and the spread of PBAs in indoor environments guide the development of APNP sources to control communicable diseases. The key six sampling and seven detection methods on PBAs are introduced to analyze the PBA abatement efficiency by APNP. Seven common APNP sources which can remove viruses and bacteria aerosols efficiently developed during the past 8 years are introduced. For the APNP sources with small plasma volume, the electric field and diffusion driven charging are the dominant mechanisms to charge PBAs, while the common methods of dusty plasma research can be adapted to atmospheric-pressure conditions to describe the charging effects of APNP sources with large plasma volume. Plentiful long- and short-lifetime reactive oxygen and nitrogen species (RONS) generated by APNP effectively contribute to inactivation of bacterial aerosols. Current studies suggest that viral aerosols are mainly inactivated by short-lifetime RONS including 1O2, ONOO- and ONOOH. The study on the dissolution and reaction of gaseous RONS in microdroplets and accurate measurements on the evolution of charged PBAs are envisaged to be the focus of future research. Opportunities for multidisciplinary collaborative research to advance the development of next-generation high-performance plasma-based air purifiers are highlighted. </p

3-D mesh-based optical network-on-chip for multiprocessor system-on-chip

Optical networks-on-chip (ONoCs) are emerging communication architectures that can potentially offer ultrahigh communication bandwidth and low latency to multiprocessor systems-on-chip (MPSoCs). In addition to ONoC architectures, 3-D integrated technologies offer an opportunity to continue performance improvements with higher integration densities. In this paper, we present a 3-D mesh-based ONoC for MPSoCs, and new low-cost nonblocking 4 × 4, 5 × 5, 6 × 6, and 7 × 7 optical routers for dimension-order routing in the 3-D mesh-based ONoC. Besides, we propose an optimized floorplan for the 3-D mesh-based ONoC. The floorplan follows the regular 3-D mesh topology but implements all optical routers in a single optical layer. The floorplan is optimized to minimize the number of extra waveguide crossings caused when merging the 3-D ONoC to one optical layer. Based on a set of real applications and uniform traffic pattern, we develop a SystemC-based cycle-accurate NoC simulator and compare the 3-D mesh-based ONoC with the matched 2-D mesh-based ONoC and 2-D electronic NoC for performance and energy efficiency. Additionally, we quantitatively analyze thermal effects on the 3-D 8 × 8 × 2 mesh-based ONoC