Biology subjects

Escott-Price, V.

Publications and source records attributed to Escott-Price, V..

At least 19 recordsLinked to original sources

bioRxiv2026

drugMR: A multi-omics pipeline for genetically anchored drug-target discovery

Motivation: Genetically supported drug targets are an estimated 2.6 times more likely to succeed clinically, yet a disease association alone does not show which protein to target, in which direction, or what other effects may follow. This currently requires chaining separate tools. Results: drugMR is a Nextflow pipeline that, from GWAS and pQTL summary statistics, runs cis-Mendelian randomisation, colocalisation, SMR-HEIDI with bulk and/or single-cell QTLs, three-trait colocalisation and a phenome-wide screen for adverse effects and repurposing. Datasets are added through a manifest, every step runs in containers on a laptop, cluster or cloud, and results are explored in a dashboard. Applied to schizophrenia with brain pQTLs, drugMR tested 2,019 proteins in 4 h 19 min and prioritised 58 proteogenomic targets, 22 with multi-omic support; 4 had potential adverse effects. Availability and implementation: drugMR: https://github.com/guillermocomesanacimadevila/drugMR; documentation: https://guillermocomesanacimadevila.github.io/drugMR/. Demo data: https://doi.org/10.5281/zenodo.22917384.

bioinformatics↗

bioRxiv2026

Proteomic Signatures of Neuropathological Alterations in Alzheimer's Disease: Insights from the Bio-Hermes Study

Large-scale plasma proteomics can capture molecular changes across the Alzheimers disease (AD) continuum and provide insight into biological mechanisms associated with AD pathology. We analysed the Bio-Hermes cohort (n = 961), with participants enrolled across 17 sites in the United States from April 2021 to November 2022. Participants were stratified by clinical status and amyloid PET scan-based Core1 biomarker status (CN Core1-, CN Core1+, MCI Core1+, and AD dementia Core1+). We performed differential abundance analyses across biologically defined contrasts, clustered proteins into co-expression networks, and evaluated protein panels to distinguish participants with biologically defined AD from amyloid-negative cognitively normal controls. We also used Mendelian randomization (MR) to assess genetic evidence for potential causal relationships with AD risk. The biologically defined contrast, Core1+ vs. CN Core1-, identified 69 differentially abundant proteins. Across AD stages, eight core proteins were consistently dysregulated from preclinical through prodromal and dementia phases, and three additional proteins emerged at MCI Core1+ and remained altered in AD dementia Core1+. We identified 29 co-expression modules, six of which varied significantly across the AD continuum. Among differential abundance proteins, ACHE ranked highest for distinguishing biologically defined AD from CN Core1-. Stage-specific protein panels improved the discriminatory performance for MCI Core1+ (AUC = 0.850) and AD dementia Core1+ (AUC = 0.856). MR provided genetic evidence consistent with an association between plasma ACHE abundance and AD risk. Plasma proteomics delineated a stage-spanning core signature across the AD continuum. These findings nominate co-expression modules and candidate proteins for further validation in early detection and AD screening.

neuroscience↗

bioRxiv2026

New Human IPSC Models of Late-onset Alzheimer's Disease Polygenic Risk Identify Multiple Impairments of Microglial Function

Genetic discoveries implicate microglia in late-onset Alzheimers disease (AD). We modelled AD in a powerful study of 51 human induced pluripotent stem cell (iPSC) microglia derived from high-polygenic risk AD or low-risk cognitively well individuals, sampled from a large cohort. We explored mitochondrial function, cytokine secretion, endocytosis, phagocytosis, lipid accumulation, calcium store release, and chemotaxis under basal conditions and immune challenge. High polygenic risk was independently associated with significant functional deficits in iPSC microglia under immune challenge, in mitochondrial ATP production (p=0.005, -13%), and inflammatory cytokine release (IL-6: p=0.018, -42%; TNF p=0.026, -38.5%). Furthermore, a selective deficit in amyloid-{beta} uptake was identified (p=0.00477, -5.9%). Deficits in inflammatory cytokine release were driven by APOE {varepsilon}4. These findings reflect primary changes in AD pathogenesis predating plaque formation and validate a human in vitro platform for late-onset AD to further understand disease mechanisms and screen drug or genetic therapies.

neuroscience↗

bioRxiv2026

Co-expression-based models improve eQTL predictions and highlightnovel transcriptome-wide genes associated with schizophrenia

Non-coding genetic variants statistically associated with complex heritability phenotypes are thought to act primarily through transcriptome regulatory mechanisms. Predictions of gene expression in tissue like the human brain traditionally rely primarily on cis-eQTLs. Here, we introduce INGENE and MODULE, trans-eQTLs models designed to enhance the prediction of gene expression by capturing the collective impact of candidate trans-eQTLs acting within co-expression networks. Exploiting RNA-seq data in six post-mortem brain regions (amygdala, caudate nucleus, dorsal/subgenual anterior cingulate cortex, dorsolateral prefrontal cortex, and hippocampus), we validate our models on two testing datasets, demonstrating increased gene predictability compared to both an original cis-based model and to EpiXcan, the leading benchmark in cis-model performance. Integration of cis- and trans-predictions significantly improves gene-level expression imputation (MLE = 0.05) for 18,744 genes across the six brain regions considered. Applying cis and trans models to PGC wave 3 genotypes identifies 766 SCZ-associated genes across brain regions (pFDR < .01), emphasizing the complementary nature of cis and trans predictions in trait association discovery. Of these genes, 641 represent novel transcriptome-wide associations with schizophrenia, highlighting the role of trans-heritability and genetic interactions underlying risk for this disorder, in addition to further supporting 125 previous candidates.

genomics↗

bioRxiv2025

Contrasting patterns of interleukin signalling in LRRK2 and idiopathic Parkinson's

Sporadic PD and LRRK2-associated Parkinsons Disease (PD) present with similar features although the familial form of disease is classically associated with less cognitive impairment, better REM sleep behaviour, and reduced incidence of hyposmia but more freezing gait and postural instability. Although being classified as the same disease from a clinical perspective there is an ongoing debate on whether these 2 conditions are linked to different causative molecular mechanisms. In this work we analysed the transcriptomics and proteomics profile of sporadic and LRRK2 PD patients to contrast and compare inflammatory markers in blood and CSF. Analyses showed molecular differences in the burden of inflammatory signals clearly differentiating the sporadic and the familial forms of disease. Finally, a cluster of closely connected proteins whose expression levels were changed in the familial forms of disease was highlighted. The levels of these inflammatory markers were associated with tau pathology suggesting this protein cluster might be a system model to evaluate the control of tau metabolism in the presence of LRRK2 mutations.

neuroscience↗

bioRxiv2025

Complementary MR measures of white matter and their relation to cardiovascular health and cognition

Magnetic Resonance Imaging (MRI) offers many ways to non-invasively estimate the properties of white matter (WM) in the brain. In addition to the various metrics derived from diffusion-weighted MRI, one can estimate total WM volume from T1-weighted MRI, WM hyper-intensities from T2-weighted MRI, myelination from the T1:T2 ratio, or from the magnetisation-transfer ratio (MTR). Here we utilise the presence of all of these MR contrasts in a population based life-span cohort of 650 healthy adults [CamCAN cohort] to identify the latent factors underlying the covariance of 11 commonly-used WM metrics. Four factors were needed to explain 89% of the variance, which we interpreted in terms of 1) fibre density / myelination, 2) free-water / tissue damage, 3) fibre-crossing complexity and 4) microstructural complexity. These factors showed distinct effects of age and sex. To test the validity of these factors, we related them to measures of cardiovascular health and cognitive performance. Specifically, we ran path analyses 1) linking cardio-vascular measures to the WM factors, given the idea that WM health is related to cardiovascular health, and 2) linking the WM factors to cognitive measure, given the idea that WM health is important for cognition. Even after adjusting for age, we found that a vascular factor related to pulse pressure predicted the WM factor capturing free-water / tissue damage, and that several WM factors made unique predictions for fluid intelligence and processing speed. Our results show that there is both complementary and redundant information across common MR measures of WM, and their underlying latent factors may be useful for pinpointing the differential causes and contributions of white matter health in healthy aging.

neuroscience↗

bioRxiv2023

Transcriptomics analyses of the LRRK2 protein interactome reveal distinct molecular signatures for sporadic and LRRK2 Parkinson's Disease

Mutations in the LRRK2 gene are the most common genetic cause for familial Parkinsons Disease (LRRK2-PD) and an important risk factor for sporadic PD (sPD). Multiple clinical trials are ongoing to evaluate the benefits associated with the therapeutical reduction of LRRK2 kinase activity. In this study, we described the changes on transcriptomic profiles (whole blood mRNA levels) of LRRK2 protein interactors in the sPD and LRRK2-PD cases as compared to healthy controls with the aim of comparing the two PD conditions. We went on to model the protein-protein interaction (PPI) network around LRRK2, which was weighted to reflect the transcriptomic changes in the network based on the expression and co-expression levels. Our results showed that LRRK2 interactors present both similar but also different alterations in expression levels and co-expression behaviours in the sPD and LRRK2-PD cases. The similar changes result in decreased connectivity within a topological cluster of the LRRK2 PPI network associated with ribosomal functions and DNA/RNA metabolism in both the sPD and LRRK2-PD scenario; while the connectivity within the autophagy/mitophagy/neurotransmitter-transport related cluster was increased exclusively in the LRRK2-PD condition as compared to the healthy controls. These results suggest that, albeit being classified as the same disease based on clinical features, LRRK2-PD and sPD show some significant differences from a molecular perspective.

neuroscience↗

bioRxiv2022

What does heritability of Alzheimer's disease represent?

INTRODUCTIONBoth Alzheimers disease (AD) and ageing have a strong genetic component. In each case, many associated variants have been discovered, but how much missing heritability remains to be discovered is debated. Variability in the estimation of SNP-based heritability could explain the differences in reported heritability. METHODSWe compute heritability in five large independent cohorts (N=7,396, 1,566, 803, 12,528 and 3,963) to determine whether a consensus for the AD heritability estimate can be reached. These cohorts vary by sample size, age of cases and controls and phenotype definition. We compute heritability a) for all SNPs, b) excluding APOE region, c) excluding both APOE and genome-wide association study hit regions, and d) SNPs overlapping a microglia gene-set. RESULTSSNP-based heritability of Alzheimers disease is between 38 and 66% when age and genetic disease architecture are correctly accounted for. The heritability estimates decrease by 12% [SD=8%] on average when the APOE region is excluded and an additional 1% [SD=3%] when genome-wide significant regions were removed. A microglia gene-set explains 69-84% of our estimates of SNP-based heritability using only 3% of total SNPs in all cohorts. CONCLUSIONThe heritability of neurodegenerative disorders cannot be represented as a single number, because it is dependent on the ages of cases and controls. Genome-wide association studies pick up a large proportion of total AD heritability when age and genetic architecture are correctly accounted for. Around 13% of SNP-based heritability can be explained by known genetic loci and the remaining heritability likely resides around microglial related genes. Author SummaryEstimates of heritability in Alzheimers disease, the proportion of phenotypic variance explained by genetics, are very varied across different studies, therefore, the amount of missing heritability not yet captured by current genome-wide association studies is debated. We investigate this in five independent cohorts, provide estimates based on these cohorts and detail necessary suggestions to accurately calculate heritability in age-related disorders. We also confirm the importance of microglia relevant genetic markers in Alzheimers disease. This manuscript provides suggestions for other researchers computing heritability in late-onset disorders and the microglia gene-set used in this study will be published alongside this manuscript and made available to other researchers. The correct assessment of disease heritability will aid in better understanding the amount of missing heritability in Alzheimers disease.

genetics↗

bioRxiv2022

Tissue specific LRRK2 interactomes reveal a distinct functional unit within the striatum

Mutations in LRRK2 are the most common genetic cause of Parkinsons disease. Despite substantial research efforts, the physiological and pathological role of this multidomain protein remains poorly defined. In this study, we used a systematic approach to construct the general protein-protein interactome around LRRK2, which was then differentiated into 15 tissue-specific interactomes taking into consideration the differential expression patterns and the co-expression behaviours of the LRRK2 interactors in different healthy tissues. The LRRK2 interactors exhibited distinct expression features in the brain as compared to the peripheral tissues analysed. Moreover, a high degree of similarity was found for the LRRK2 interactors in putamen, caudate and nucleus accumbens, thus defining a potential LRRK2 functional cluster within the striatum. We also explored the functions highlighted by the "core LRRK2 interactors" within each tissue and illustrated how the LRRK2 interactomes can be used as a tool to trace the relationship between LRRK2 and specific interactors of interest, here exemplified with a study focused on the LRRK2 interactors belonging to the Rab protein family.

neuroscience↗

bioRxiv2022

Restoring synapse integrity and memory in Alzheimer's disease by downregulation of the Wnt antagonist Dickkopf-3

Increasing evidence supports a role for deficient Wnt signaling in Alzheimers disease (AD). Studies reveal that the secreted Wnt antagonist Dickkopf-3 (DKK3) colocalizes to amyloid plaques in AD patients. Here, we investigate the contribution of DKK3 to synapse integrity in healthy and AD brains. Our findings show that DKK3 expression is upregulated in the brains of AD subjects and that DKK3 protein levels increase at early stages in the disease. In hAPP-J20 and hAPPNL-G-F/NL-G-F AD models, extracellular DKK3 levels are increased and DKK3 accumulates at dystrophic neuronal processes around plaques. Functionally, DKK3 triggers the loss of excitatory synapses through blockade of the Wnt/GSK3{beta} signaling with a concomitant increase in inhibitory synapses signaling via activation of the Wnt/JNK pathway. In contrast, DKK3 knockdown restores synapse number and memory in hAPP-J20 mice. Collectively, our findings identify DKK3 as a novel driver of synaptic defects and memory impairment in AD.

neuroscience↗

bioRxiv2021

The impact of genetic risk for Alzheimers disease on the structural brain networks of young adults

We investigated the structural brain networks of 562 young adults in relation to polygenic risk for Alzheimers disease, using magnetic resonance imaging (MRI) and genotype data from the Avon Longitudinal Study of Parents and Children. Diffusion MRI data were used to perform whole-brain tractography and to generate structural brain networks for the whole-brain connectome, and for the default mode, limbic and visual subnetworks. The mean clustering coefficient, mean betweenness centrality, characteristic path length, global efficiency and mean nodal strength were calculated for these networks, for each participant. The connectivity of the rich-club, feeder and local connections was also calculated. Polygenic risk scores (PRS), estimating each participants genetic risk, were calculated at genome-wide level and for nine specific disease pathways. Correlations were calculated between the PRS and a) the graph theoretical metrics of the structural networks and b) the rich-club, feeder and local connectivity of the whole-brain networks. In the visual subnetwork, the mean nodal strength was negatively correlated with the genomewide PRS (r=-0.19, p=1.3x10-5), the mean betweenness centrality was positively correlated with the plasma lipoprotein particle assembly PRS (r=0.16, p=9.2x10-4), and the mean clustering coefficient was negatively correlated with the tau protein binding PRS (r=-0.16, p=9.2x10-4). In the default mode network, the mean nodal strength was negatively correlated with the genomewide PRS (r=-0.14, p=1.5x10-3). The rich-club and feeder connectivities were negatively correlated with the genome-wide PRS (r=-0.16, p=3.7x10-4; r=-0.15, p=8.8x10-4). Our results indicate small reductions in brain connectivity in young adults at risk of developing Alzheimers disease in later life.

neuroscience↗

bioRxiv2021

Abi3 regulates microglial ramification and dynamic tissue surveillance in vivo.

A rare coding variant of Abelson-interactor gene family member 3 (Abi3) is associated with increased risk of late-onset Alzheimers Disease (AD). Although Abi3 is recognised as a core microglial gene, its role in microglia is largely unknown. Here we demonstrate that Abi3 is crucial for normal microglial morphology, distribution, and homeostatic tissue surveillance activity in vivo.

neuroscience↗

bioRxiv2021

Genetic variability associated with OAS1 expression in myeloid cells increases the risk of Alzheimer's disease and severe COVID-19 outcomes

Genome-wide association studies of late-onset Alzheimers disease (AD) have highlighted the importance of variants associated with genes expressed by the innate immune system in determining risk for AD. Recently, we and others have shown that genes associated with variants that confer risk for AD are significantly enriched in transcriptional networks expressed by amyloid-responsive microglia. This allowed us to predict new risk genes for AD, including the interferon-responsive oligoadenylate synthetase 1 (OAS1). However, the function of OAS1 within microglia and its genetic pathway are not known. Using genotyping from 1,313 individuals with sporadic AD and 1,234 control individuals, we confirm that the OAS1 variant, rs1131454, is associated with increased risk for AD and decreased OAS1 expression. Moreover, we note that the same locus was recently associated with critical illness in response to COVID-19, linking variants that are associated with AD and a severe response to COVID-19. By analysing single-cell RNA-sequencing (scRNA-seq) data of isolated microglia from APPNL-G-F knock-in and wild-type C57BL/6J mice, we identify a transcriptional network that is significantly upregulated with age and amyloid deposition, and contains the mouse orthologue Oas1a, providing evidence that Oas1a plays an age-dependent function in the innate immune system. We identify a similar interferon-related transcriptional network containing OAS1 by analysing scRNA-seq data from human microglia isolated from individuals with AD. Finally, using human iPSC-derived microglial cells (h-iPSC-Mg), we see that OAS1 is required to limit the pro-inflammatory response of microglia. When stimulated with interferon-gamma (IFN-{gamma}), we note that cells with lower OAS1 expression show an exaggerated pro-inflammatory response, with increased expression and secretion of TNF-. Collectively, our data support a link between genetic risk for AD and susceptibility to critical illness with COVID-19 centred on OAS1 and interferon signalling, a finding with potential implications for future treatments of both AD and COVID-19, and the development of biomarkers to track disease progression.

genetics↗

bioRxiv2020

Identifying genetic variants associated with cerebellar volume in 33,265 individuals from the UK-Biobank

There is expanding interest in researching the cerebellum given accumulating evidence of its important contributions to cognitive and emotional functions, in addition to more established sensorimotor roles. While large genome-wide association studies (GWAS) have shed light on the common allele architecture of cortical and subcortical brain structures, the cerebellum remains under investigated. We conducted a meta-GWAS of cerebellar volume in 33,265 UK-Biobank European participants. Results show cerebellar volume to be moderately heritable (h2SNP=50.6%). We identified 33 independent genome-wide associated SNPs with total cerebellar volume, with 6 of these SNPs mapped to protein-coding genes and 5 more shown to alter cerebellar gene expression. We highlight 21 unique candidate genes for follow-up analysis. Cerebellar volume showed significant genetic correlation with brainstem, pallidum and thalamus volumes, but no significant correlations with neuropsychiatric phenotypes. Our results provide important new knowledge of the genetic architecture of cerebellar volume and its relationship with other brain phenotypes.

neuroscience↗

bioRxiv2020

Monocyte-specific changes in gene expression implicate LACTB2 and PLIN2 in Alzheimer's disease.

More than 50 genetic loci have been identified as being associated with Alzheimers disease (AD) from genome-wide association studies (GWAS) and many of these are involved in immune pathways and lipid metabolism. Therefore, we performed a transcriptome-wide association study (TWAS) of immune-relevant cells, to study the mis-regulation of genes implicated in AD. We used expression and genetic data from naive and induced CD14+ monocytes and two GWAS of AD to study genetically controlled gene expression in monocytes at different stages of differentiation and compared the results with those from TWAS of brain and blood. We identified nine genes with statistically independent TWAS signals, seven are known AD risk genes from GWAS: BIN1, PTK2B, SPI1, MS4A4A, MS4A6E, APOE and PVR and two, LACTB2 and PLIN2/ADRP, are novel candidate genes for AD. Three genes, SPI1, PLIN2 and LACTB2, are TWAS significant specifically in monocytes. LACTB2 is a mitochondrial endoribonuclease and PLIN2/ADRP associates with intracellular neutral lipid storage droplets (LSDs) which have been shown to play a role in the regulation of the immune response. Notably, LACTB2 and PLIN2 were not detected from GWAS alone.

neuroscience↗

bioRxiv2019

Positioning Personal Polygenic Risk score against the population background.

The polygenic risk scores (PRS) approach has been widely used across different traits for estimating polygenic risk, pleiotropy and disease prediction, but mostly in European populations. The predictive ability of the PRS in non-European populations is currently limited due to the lack of genetic research performed in populations of non-European ancestry. One of the main challenges of the practical use of PRS is to place an individuals personal score in the context of the PRS distribution in the underlying population. In this paper we present an approach for estimating the parameters of the PRS distribution in a population using summary information from public data.\n\nUnstandardized PRS are usually not directly comparable even between European studies. Our approach can be used for standardisation whilst accounting for genotyping platforms, data quality and ancestry. It can be applied to assessing polygenic disease risk for individuals from a European population for any complex genetic disorder and, assuming that most of the disease risk loci are likely to be shared between populations, to estimating the disease risk for individuals from other populations. We demonstrate the precision of our method with simulations. We show the utility of our estimates in application to Alzheimers disease in the Alzheimers Disease Neuroimaging Initiative (ADNI) study. We present population specific PRSs for different populations using 1000 Genomes data.

bioinformatics↗

bioRxiv2019

Analyses of rare and common alleles in parent-proband trios implicate rare missense variants in SLC6A1 in schizophrenia and confirm the involvement of loss of function intolerant and neurodevelopmental disorder genes.

Schizophrenia is a highly polygenic disorder with important contributions coming from both common and rare risk alleles, the latter including CNVs and rare coding variants (RCVs), sometimes occurring as de novo variants (DNVs). We performed DNV analysis in whole exome-sequencing data obtained from a new sample of 613 schizophrenia trios, and combined this with published data for a total of 3,444 trios. Loss-of-function (LoF) DNVs were significantly enriched among 3,488 LoF intolerant genes in our new trio data (rate ratio (RR) (95% CI) = 2.23 (1.31, 3.79); p = 2.2 x 10-3), supporting previous findings. In the full dataset, genes associated with neurodevelopmental disorders (NDD; n=160) were significantly enriched for LoF DNVs (RR (95% CI) = 3.32 (2.0, 5.21); p = 7.4 x 10-6). Within this set of NDD genes, SLC6A1, encoding a gamma-aminobutyric acid transporter, was associated with missense-damaging DNVs (p = 5.2 x 10-5). Using data from a subset of 1,122 trios for which we had genome-wide common variant data, schizophrenia polygenic risk was significantly over-transmitted to probands (p = 2.6 x 10-60), as was bipolar disorder common variant polygenic risk (p = 5.7 x 10-17). We defined carriers of candidate schizophrenia-related DNVs as those with LoF or deletion DNVs in LoF intolerant or NDD genes. These individuals had significantly less over-transmission of common risk alleles than non-carriers (p = 3.5 x 10-4), providing robust support for the hypothesis that this set of DNVs is enriched for those related to schizophrenia.

genetics↗

bioRxiv2019

Genetic association study of psychotic experiences in UK Biobank

Psychotic experiences, such as hallucinations and delusions, are reported by approximately 5%-10% of the general population, though only a small proportion of individuals develop psychotic disorders such as schizophrenia or bipolar disorder. Studying the genetic aetiology of psychotic experiences in the general population, and its relationship with the genetic aetiology of other disorders, may increase our understanding of their pathological significance. Using the population-based UK Biobank sample, we performed the largest genetic association study of psychotic experiences in individuals without a psychotic disorder. We conducted three genome-wide association studies (GWAS) for (i) any psychotic experience (6123 cases vs. 121,843 controls), (ii) distressing psychotic experiences (2143 cases vs. 121,843 controls), and (iii) multiple occurrence psychotic experiences (3337 cases vs. 121,843 controls). Analyses of polygenic risk scores (PRS), genetic correlation, and copy number variation (CNV) were conducted to assess whether genetic liability to psychotic experiences is shared with schizophrenia and/or other neuropsychiatric disorders and traits. GWAS analyses identified four loci associated with psychotic experiences including a locus in Ankyrin-3 (ANK3, OR=1.16, p=3.06 x 10-8) with any psychotic experience and a locus in cannabinoid receptor 2 gene (CNR2, OR=0.66, p=3.78x10-8) with distressing psychotic experiences. PRS analyses identified associations between psychotic experiences and genetic liability for schizophrenia, major depressive disorder, and bipolar disorder, and these associations were stronger for distressing psychotic experiences. Genetic correlation analysis identified significant genetic correlations between psychotic experiences and major depressive disorder, schizophrenia, autism spectrum disorder and a cross-disorder GWAS. Individuals reporting psychotic experiences had an increased burden of CNVs previously associated with schizophrenia (OR=2.04, p=2.49x10-4) and of those associated with neurodevelopmental disorders more widely (OR=1.75, p=1.41x10-3). In conclusion, we identified four genome-wide significant loci in the largest GWAS of psychotic experiences from the population-based UK Biobank sample and found support for a shared genetic aetiology between psychotic experiences and schizophrenia, but also major depressive disorder, bipolar disorder and neurodevelopmental disorders.

genetics↗