A comprehensive framework for trans-ancestry pathway analysis using GWAS summary data from diverse populations.

As more multi-ancestry GWAS summary data become available, we have developed a comprehensive trans-ancestry pathway analysis framework that effectively utilizes this diverse genetic information. Within this framework, we evaluated various strategies for integrating genetic data at different levels-SNP, gene, and pathway-from multiple ancestry groups. Through extensive simulation studies, we have identified robust strategies that demonstrate superior performance across diverse scenarios. Applying these methods, we analyzed 6,970 pathways for their association with schizophrenia, incorporating data from African, East Asian, and European populations. Our analysis identified over 200 pathways significantly associated with schizophrenia, even after excluding genes near genome-wide significant loci. This approach substantially enhances detection efficiency compared to traditional single-ancestry pathway analysis and the conventional approach that amalgamates single-ancestry pathway analysis results across different ancestry groups. Our framework provides a flexible and effective tool for leveraging the expanding pool of multi-ancestry GWAS summary data, thereby improving our ability to identify biologically relevant pathways that contribute to disease susceptibility.

Loss of function of OTUD7A in the schizophrenia- associated 15q13.3 deletion impairs synapse development and function in human neurons.

Identifying causative gene(s) within disease-associated large genomic regions of copy-number variants (CNVs) is challenging. Here, by targeted sequencing of genes within schizophrenia (SZ)-associated CNVs in 1,779 SZ cases and 1,418 controls, we identified three rare putative loss-of-function (LoF) mutations in OTU deubiquitinase 7A (OTUD7A) within the 15q13.3 deletion in cases but none in controls. To tie OTUD7A LoF with any SZ-relevant cellular phenotypes, we modeled the OTUD7A LoF mutation, rs757148409, in human induced pluripotent stem cell (hiPSC)-derived induced excitatory neurons (iNs) by CRISPR-Cas9 engineering. The mutant iNs showed a ∼50% decrease in OTUD7A expression without undergoing nonsense-mediated mRNA decay. The mutant iNs also exhibited marked reduction of dendritic complexity, density of synaptic proteins GluA1 and PSD-95, and neuronal network activity. Congruent with the neuronal phenotypes in mutant iNs, our transcriptomic analysis showed that the set of OTUD7A LoF-downregulated genes was enriched for those relating to synapse development and function and was associated with SZ and other neuropsychiatric disorders. These results suggest that OTUD7A LoF impairs synapse development and neuronal function in human neurons, providing mechanistic insight into the possible role of OTUD7A in driving neuropsychiatric phenotypes associated with the 15q13.3 deletion.

Annotating functional effects of non-coding variants in neuropsychiatric cell types by deep transfer learning.

Genomewide association studies (GWAS) have identified a large number of loci associated with neuropsychiatric traits, however, understanding the molecular mechanisms underlying these loci remains difficult. To help prioritize causal variants and interpret their functions, computational methods have been developed to predict regulatory effects of non-coding variants. An emerging approach to variant annotation is deep learning models that predict regulatory functions from DNA sequences alone. While such models have been trained on large publicly available dataset such as ENCODE, neuropsychiatric trait-related cell types are under-represented in these datasets, thus there is an urgent need of better tools and resources to annotate variant functions in such cellular contexts. To fill this gap, we collected a large collection of neurodevelopment-related cell/tissue types, and trained deep Convolutional Neural Networks (ResNet) using such data. Furthermore, our model, called MetaChrom, borrows information from public epigenomic consortium to improve the accuracy via transfer learning. We show that MetaChrom is substantially better in predicting experimentally determined chromatin accessibility variants than popular variant annotation tools such as CADD and delta-SVM. By combining GWAS data with MetaChrom predictions, we prioritized 31 SNPs for Schizophrenia, suggesting potential risk genes and the biological contexts where they act. In summary, MetaChrom provides functional annotations of any DNA variants in the neuro-development context and the general method of MetaChrom can also be extended to other disease-related cell or tissue types.

CCmed: cross-condition mediation analysis for identifying replicable trans-associations mediated by cis-gene expression.

MOTIVATION: Trans-acting expression quantitative trait loci (eQTLs) collectively explain a substantial proportion of expression variation, yet are challenging to detect and replicate since their effects are often individually weak. A large proportion of genetic effects on distal genes are mediated through cis-gene expression. Cis-association (between SNP and cis-gene) and gene-gene correlation conditional on SNP genotype could establish trans-association (between SNP and trans-gene). Both cis-association and gene-gene conditional correlation have effects shared across relevant tissues and conditions, and trans-associations mediated by cis-gene expression also have effects shared across relevant conditions. RESULTS: We proposed a Cross-Condition Mediation analysis method (CCmed) for detecting cis-mediated trans-associations with replicable effects in relevant conditions/studies. CCmed integrates cis-association and gene-gene conditional correlation statistics from multiple tissues/studies. Motivated by the bimodal effect-sharing patterns of eQTLs, we proposed two variations of CCmed, CCmedmost and CCmedspec for detecting cross-tissue and tissue-specific trans-associations, respectively. We analyzed data of 13 brain tissues from the Genotype-Tissue Expression (GTEx) project, and identified trios with cis-mediated trans-associations across brain tissues, many of which showed evidence of trans-association in two replication studies. We also identified trans-genes associated with schizophrenia loci in at least two brain tissues. AVAILABILITY AND IMPLEMENTATION: CCmed software is available at http://github.com/kjgleason/CCmed. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Epigenome-wide analysis of DNA methylation in lung tissue shows concordance with blood studies and identifies tobacco smoke-inducible enhancers.

Smoking-associated DNA hypomethylation has been observed in blood cells and linked to lung cancer risk. However, its cause and mechanistic relationship to lung cancer remain unclear. We studied the association between tobacco smoking and epigenome-wide methylation in non-tumor lung (NTL) tissue from 237 lung cancer cases in the Environment And Genetics in Lung cancer Etiology study, using the Infinium HumanMethylation450 BeadChip. We identified seven smoking-associated hypomethylated CpGs (P < 1.0 × 10-7), which were replicated in NTL data from The Cancer Genome Atlas. Five of these loci were previously reported as hypomethylated in smokers' blood, suggesting that blood-based biomarkers can reflect changes in the target tissue for these loci. Four CpGs border sequences carrying aryl hydrocarbon receptor binding sites and enhancer-specific histone modifications in primary alveolar epithelium and A549 lung adenocarcinoma cells. A549 cell exposure to cigarette smoke condensate increased these enhancer marks significantly and stimulated expression of predicted target xenobiotic response-related genes AHRR (P = 1.13 × 10-62) and CYP1B1 (P < 2.49 × 10-61). Expression of both genes was linked to smoking-related transversion mutations in lung tumors. Thus, smoking-associated hypomethylation may be a consequence of enhancer activation, revealing environmentally-induced regulatory elements implicated in lung carcinogenesis.

Reversal of dendritic phenotypes in 16p11.2 microduplication mouse model neurons by pharmacological targeting of a network hub.

The architecture of dendritic arbors contributes to neuronal connectivity in the brain. Conversely, abnormalities in dendrites have been reported in multiple mental disorders and are thought to contribute to pathogenesis. Rare copy number variations (CNVs) are genetic alterations that are associated with a wide range of mental disorders and are highly penetrant. The 16p11.2 microduplication is one of the CNVs most strongly associated with schizophrenia and autism, spanning multiple genes possibly involved in synaptic neurotransmission. However, disease-relevant cellular phenotypes of 16p11.2 microduplication and the driver gene(s) remain to be identified. We found increased dendritic arborization in isolated cortical pyramidal neurons from a mouse model of 16p11.2 duplication (dp/+). Network analysis identified MAPK3, which encodes ERK1 MAP kinase, as the most topologically important hub in protein-protein interaction networks within the 16p11.2 region and broader gene networks of schizophrenia-associated CNVs. Pharmacological targeting of ERK reversed dendritic alterations associated with dp/+ neurons, outlining a strategy for the analysis and reversal of cellular phenotypes in CNV-related psychiatric disorders.

Parental Origin of Interstitial Duplications at 15q11.2-q13.3 in Schizophrenia and Neurodevelopmental Disorders.

Duplications at 15q11.2-q13.3 overlapping the Prader-Willi/Angelman syndrome (PWS/AS) region have been associated with developmental delay (DD), autism spectrum disorder (ASD) and schizophrenia (SZ). Due to presence of imprinted genes within the region, the parental origin of these duplications may be key to the pathogenicity. Duplications of maternal origin are associated with disease, whereas the pathogenicity of paternal ones is unclear. To clarify the role of maternal and paternal duplications, we conducted the largest and most detailed study to date of parental origin of 15q11.2-q13.3 interstitial duplications in DD, ASD and SZ cohorts. We show, for the first time, that paternal duplications lead to an increased risk of developing DD/ASD/multiple congenital anomalies (MCA), but do not appear to increase risk for SZ. The importance of the epigenetic status of 15q11.2-q13.3 duplications was further underlined by analysis of a number of families, in which the duplication was paternally derived in the mother, who was unaffected, whereas her offspring, who inherited a maternally derived duplication, suffered from psychotic illness. Interestingly, the most consistent clinical characteristics of SZ patients with 15q11.2-q13.3 duplications were learning or developmental problems, found in 76% of carriers. Despite their lower pathogenicity, paternal duplications are less frequent in the general population with a general population prevalence of 0.0033% compared to 0.0069% for maternal duplications. This may be due to lower fecundity of male carriers and differential survival of embryos, something echoed in the findings that both types of duplications are de novo in just over 50% of cases. Isodicentric chromosome 15 (idic15) or interstitial triplications were not observed in SZ patients or in controls. Overall, this study refines the distinct roles of maternal and paternal interstitial duplications at 15q11.2-q13.3, underlining the critical importance of maternally expressed imprinted genes in the contribution of Copy Number Variants (CNVs) at this interval to the incidence of psychotic illness. This work will have tangible benefits for patients with 15q11.2-q13.3 duplications by aiding genetic counseling.

Winner's Curse Correction and Variable Thresholding Improve Performance of Polygenic Risk Modeling Based on Genome-Wide Association Study Summary-Level Data.

Recent heritability analyses have indicated that genome-wide association studies (GWAS) have the potential to improve genetic risk prediction for complex diseases based on polygenic risk score (PRS), a simple modelling technique that can be implemented using summary-level data from the discovery samples. We herein propose modifications to improve the performance of PRS. We introduce threshold-dependent winner's-curse adjustments for marginal association coefficients that are used to weight the single-nucleotide polymorphisms (SNPs) in PRS. Further, as a way to incorporate external functional/annotation knowledge that could identify subsets of SNPs highly enriched for associations, we propose variable thresholds for SNPs selection. We applied our methods to GWAS summary-level data of 14 complex diseases. Across all diseases, a simple winner's curse correction uniformly led to enhancement of performance of the models, whereas incorporation of functional SNPs was beneficial only for selected diseases. Compared to the standard PRS algorithm, the proposed methods in combination led to notable gain in efficiency (25-50% increase in the prediction R2) for 5 of 14 diseases. As an example, for GWAS of type 2 diabetes, winner's curse correction improved prediction R2 from 2.29% based on the standard PRS to 3.10% (P = 0.0017) and incorporating functional annotation data further improved R2 to 3.53% (P = 2×10-5). Our simulation studies illustrate why differential treatment of certain categories of functional SNPs, even when shown to be highly enriched for GWAS-heritability, does not lead to proportionate improvement in genetic risk-prediction because of non-uniform linkage disequilibrium structure.

Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants.

We searched a gene expression dataset comprised of 634 schizophrenia (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of transcript expression values) with SZ cases overrepresented compared with controls. These outlier genes were enriched for brain expression and for genes known to be associated with neurodevelopmental disorders. SZ cases showed higher outlier burden (i.e., total outlier events per subject) than controls for genes within copy number variants (CNVs) associated with SZ or neurodevelopmental disorders. Outlier genes were enriched for CNVs and for rare putative regulatory variants, but this only explained a small proportion of the outlier subjects, highlighting the underlying presence of additional genetic and potentially, epigenetic mechanisms.

A rare functional noncoding variant at the GWAS-implicated MIR137/MIR2682 locus might confer risk to schizophrenia and bipolar disorder.

Schizophrenia (SZ) genome-wide association studies (GWASs) have identified common risk variants in >100 susceptibility loci; however, the contribution of rare variants at these loci remains largely unexplored. One of the strongly associated loci spans MIR137 (miR137) and MIR2682 (miR2682), two microRNA genes important for neuronal function. We sequenced ∼6.9 kb MIR137/MIR2682 and upstream regulatory sequences in 2,610 SZ cases and 2,611 controls of European ancestry. We identified 133 rare variants with minor allele frequency (MAF) <0.5%. The rare variant burden in promoters and enhancers, but not insulators, was associated with SZ (p = 0.021 for MAF < 0.5%, p = 0.003 for MAF < 0.1%). A rare enhancer SNP, 1:g.98515539A>T, presented exclusively in 11 SZ cases (nominal p = 4.8 × 10(-4)). We further identified its risk allele T in 2 of 2,434 additional SZ cases, 11 of 4,339 bipolar (BP) cases, and 3 of 3,572 SZ/BP study controls and 1,688 population controls; yielding combined p values of 0.0007, 0.0013, and 0.0001 for SZ, BP, and SZ/BP, respectively. The risk allele T of 1:g.98515539A>T reduced enhancer activity of its flanking sequence by >50% in human neuroblastoma cells, predicting lower expression of MIR137/MIR2682. Both empirical and computational analyses showed weaker transcription factor (YY1) binding by the risk allele. Chromatin conformation capture (3C) assay further indicated that 1:g.98515539A>T influenced MIR137/MIR2682, but not the nearby DPYD or LOC729987. Our results suggest that rare noncoding risk variants are associated with SZ and BP at MIR137/MIR2682 locus, with risk alleles decreasing MIR137/MIR2682 expression.

Identification of loci associated with schizophrenia by genome-wide association and follow-up.

We carried out a genome-wide association study of schizophrenia (479 cases, 2,937 controls) and tested loci with P < 10(-5) in up to 16,726 additional subjects. Of 12 loci followed up, 3 had strong independent support (P < 5 x 10(-4)), and the overall pattern of replication was unlikely to occur by chance (P = 9 x 10(-8)). Meta-analysis provided strongest evidence for association around ZNF804A (P = 1.61 x 10(-7)) and this strengthened when the affected phenotype included bipolar disorder (P = 9.96 x 10(-9)).

Somatic Genomics and Clinical Features of Lung Adenocarcinoma: A Retrospective Study.

BACKGROUND: Lung adenocarcinoma (LUAD) is the most common histologic subtype of lung cancer and has a high risk of distant metastasis at every disease stage. We aimed to characterize the genomic landscape of LUAD and identify mutation signatures associated with tumor progression. METHODS AND FINDINGS: We performed an integrative genomic analysis, incorporating whole exome sequencing (WES), determination of DNA copy number and DNA methylation, and transcriptome sequencing for 101 LUAD samples from the Environment And Genetics in Lung cancer Etiology (EAGLE) study. We detected driver genes by testing whether the nonsynonymous mutation rate was significantly higher than the background mutation rate and replicated our findings in public datasets with 724 samples. We performed subclonality analysis for mutations based on mutant allele data and copy number alteration data. We also tested the association between mutation signatures and clinical outcomes, including distant metastasis, survival, and tumor grade. We identified and replicated two novel candidate driver genes, POU class 4 homeobox 2 (POU4F2) (mutated in 9 [8.9%] samples) and ZKSCAN1 (mutated in 6 [5.9%] samples), and characterized their major deleterious mutations. ZKSCAN1 was part of a mutually exclusive gene set that included the RTK/RAS/RAF pathway genes BRAF, EGFR, KRAS, MET, and NF1, indicating an important driver role for this gene. Moreover, we observed strong associations between methylation in specific genomic regions and somatic mutation patterns. In the tumor evolution analysis, four driver genes had a significantly lower fraction of subclonal mutations (FSM), including TP53 (p = 0.007), KEAP1 (p = 0.012), STK11 (p = 0.0076), and EGFR (p = 0.0078), suggesting a tumor initiation role for these genes. Subclonal mutations were significantly enriched in APOBEC-related signatures (p < 2.5×10-50). The total number of somatic mutations (p = 0.0039) and the fraction of transitions (p = 5.5×10-4) were associated with increased risk of distant metastasis. Our study's limitations include a small number of LUAD patients for subgroup analyses and a single-sample design for investigation of subclonality. CONCLUSIONS: These data provide a genomic characterization of LUAD pathogenesis and progression. The distinct clonal and subclonal mutation signatures suggest possible diverse carcinogenesis pathways for endogenous and exogenous exposures, and may serve as a foundation for more effective treatments for this lethal disease. LUAD's high heterogeneity emphasizes the need to further study this tumor type and to associate genomic findings with clinical outcomes.

MicroRNA-9 and microRNA-326 regulate human dopamine D2 receptor expression, and the microRNA-mediated expression regulation is altered by a genetic variant.

The human dopamine receptor D2 (DRD2) has been implicated in the pathophysiology of schizophrenia and other neuropsychiatric disorders. Most antipsychotic drugs influence dopaminergic transmission through blocking dopamine receptors, primarily DRD2. We report here the post-transcriptional regulation of DRD2 expression by two brain-expressed microRNAs (miRs), miR-326 and miR-9, in an ex vivo mode, and show the relevance of miR-mediated DRD2 expression regulation in human dopaminergic neurons and in developing human brains. Both miRs targeted the 3'-UTR (untranslated region) of DRD2 in NT2 (neuron-committed teratocarcinoma, which endogenously expresses DRD2) and CHO (Chinese hamster ovary) cell lines, decreasing luciferase activity measured by a luciferase reporter gene assay. miR-326 overexpression reduced DRD2 mRNA and DRD2 receptor synthesis. Both antisense miR-326 and antisense miR-9 increased DRD2 protein abundance, suggesting an endogenous repression of DRD2 expression by both miRs. Furthermore, a genetic variant (rs1130354) within the DRD2 3'-UTR miR-targeting site interferes with miR-326-mediated repression of DRD2 expression. Finally, co-expression analysis identified an inverse correlation of DRD2 expression with both miR-326 and miR-9 in differentiating dopaminergic neurons derived from human induced pluripotent stem cells (iPSCs) and in developing human brain regions implicated in schizophrenia. Our study provides empirical evidence suggesting that miR-326 and miR-9 may regulate dopaminergic signaling, and miR-326 and miR-9 may be considered as potential drug targets for the treatment of disorders involving abnormal DRD2 function, such as schizophrenia.

Transcriptome study of differential expression in schizophrenia.

Schizophrenia genome-wide association studies (GWAS) have identified common SNPs, rare copy number variants (CNVs) and a large polygenic contribution to illness risk, but biological mechanisms remain unclear. Bioinformatic analyses of significantly associated genetic variants point to a large role for regulatory variants. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines (LCLs) from 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate (FDR) of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, microRNA (miRNA) processing and immunity. This functional diversity is consistent with schizophrenia's likely significant pathophysiological heterogeneity. The overall enrichment of immune-related genes among those differentially expressed by affection status is consistent with hypothesized immune contributions to schizophrenia risk. The observed differential expression of extended major histocompatibility complex (xMHC) region histones (HIST1H2BD, HIST1H2BC, HIST1H2BH, HIST1H2BG and HIST1H4K) converges with the genetic evidence from GWAS, which find the xMHC to be the most significant susceptibility locus. Among the differentially expressed immune-related genes, B3GNT2 is implicated in autoimmune disorders previously tied to schizophrenia risk (rheumatoid arthritis and Graves' disease), and DICER1 is pivotal in miRNA processing potentially linking to miRNA alterations in schizophrenia (e.g. MIR137, the second strongest GWAS finding). Our analysis provides novel candidate genes for further study to assess their potential contribution to schizophrenia.

Common variants on chromosome 6p22.1 are associated with schizophrenia.

Schizophrenia, a devastating psychiatric disorder, has a prevalence of 0.5-1%, with high heritability (80-85%) and complex transmission. Recent studies implicate rare, large, high-penetrance copy number variants in some cases, but the genes or biological mechanisms that underlie susceptibility are not known. Here we show that schizophrenia is significantly associated with single nucleotide polymorphisms (SNPs) in the extended major histocompatibility complex region on chromosome 6. We carried out a genome-wide association study of common SNPs in the Molecular Genetics of Schizophrenia (MGS) case-control sample, and then a meta-analysis of data from the MGS, International Schizophrenia Consortium and SGENE data sets. No MGS finding achieved genome-wide statistical significance. In the meta-analysis of European-ancestry subjects (8,008 cases, 19,077 controls), significant association with schizophrenia was observed in a region of linkage disequilibrium on chromosome 6p22.1 (P = 9.54 x 10(-9)). This region includes a histone gene cluster and several immunity-related genes--possibly implicating aetiological mechanisms involving chromatin modification, transcriptional regulation, autoimmunity and/or infection. These results demonstrate that common schizophrenia susceptibility alleles can be detected. The characterization of these signals will suggest important directions for research on susceptibility mechanisms.

Lipid Trajectories Improve Risk Models for Alzheimer's Disease and Mild Cognitive Impairment.

To assess the relationship between lipids and cognitive dysfunction, we retrospectively analyzed blood-lipid levels in clinically well-characterized individuals with stable mild cognitive impairment (MCI) or Alzheimer's disease (AD) over the decade prior to first cognitive symptoms. In this case/control cohort study, AD and MCI cases were diagnosed using DSM-IV criteria; MCI cases had not progressed to dementia for ≥5 years; and controls were propensity matched to cases at age of symptom onset (MCI: 116 cases, 435 controls; AD: 215 cases, 483 controls). Participants were grouped based on longitudinal trajectories and quintile of variability independent of the mean (VIM) for total cholesterol, HDL-C, LDL-C, non-HDL-C and ln(triglycerides). Models for the risk of cognitive dysfunction evaluated trajectory and VIM groups, APOE genotype, polygenic risk scores (PRS) for AD and lipid levels, age, comorbidities, and longitudinal correlates of blood-lipid concentrations. Lower HDL-C trajectories (OR = 3.8, 95% CI = 1.3-11.3) and the lowest VIM quintile of non-HDL-C (OR = 2.2, 95% CI = 1.3-3.0) were associated with higher MCI risk. Lower HDL-C trajectories (OR = 3.0, 95% CI = 1.6-5.7) and the lowest VIM quintile of total cholesterol (OR = 2.4, 95% CI = 1.5-3.9) were associated with higher AD risk. The inclusion of lipid-trajectory and VIM groups improved risk-model predictive performance independent of APOE genotype or PRS for AD and lipid levels. These results provide an important real-world perspective on the influence of lipid metabolism and blood-lipid levels on the development of stable MCI and AD.

Alzheimer's disease risk allele of PICALM causes detrimental lipid droplets in microglia.

Despite genome-wide association studies of late-onset Alzheimer's disease (LOAD) having identified many genetic risk loci1-6, the underlying disease mechanisms remain largely unknown. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Leveraging our approach for identifying functional GWAS risk variants showing allele-specific open chromatin (ASoC)7, we systematically identified putative causal LOAD risk variants in human induced pluripotent stem cells (iPSC)-derived neurons, astrocytes, and microglia (MG) and linked PICALM risk allele to a previously unappreciated MG-specific role of PICALM in lipid droplet (LD) accumulation. ASoC mapping uncovered functional risk variants for 26 LOAD risk loci, mostly MG-specific. At the MG-specific PICALM locus, the LOAD risk allele of rs10792832 reduced transcription factor (PU.1) binding and PICALM expression, impairing the uptake of amyloid beta (Aß) and myelin debris. Interestingly, MG with PICALM risk allele showed transcriptional enrichment of pathways for cholesterol synthesis and LD formation. Genetic and pharmacological perturbations of MG further established a causal link between the reduced PICALM expression, LD accumulation, and phagocytosis deficits. Our work elucidates the selective LOAD vulnerability in microglia for the PICALM locus through detrimental LD accumulation, providing a neurobiological basis that can be exploited for developing novel clinical interventions.

Alzheimer's disease protective allele of Clusterin modulates neuronal excitability through lipid-droplet-mediated neuron-glia communication.

Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified a plethora of risk loci. However, the disease variants/genes and the underlying mechanisms remain largely unknown. For a strong AD-associated locus near Clusterin (CLU), we tied an AD protective allele to a role of neuronal CLU in promoting neuron excitability through lipid-mediated neuron-glia communication. We identified a putative causal SNP of CLU that impacts neuron-specific chromatin accessibility to transcription-factor(s), with the AD protective allele upregulating neuronal CLU and promoting neuron excitability. Transcriptomic analysis and functional studies in induced pluripotent stem cell (iPSC)-derived neurons co-cultured with mouse astrocytes show that neuronal CLU facilitates neuron-to-glia lipid transfer and astrocytic lipid droplet formation coupled with reactive oxygen species (ROS) accumulation. These changes cause astrocytes to uptake less glutamate thereby altering neuron excitability. Our study provides insights into how CLU confers resilience to AD through neuron-glia interactions.

Scaled and Efficient Derivation of Loss of Function Alleles in Risk Genes for Neurodevelopmental and Psychiatric Disorders in Human iPSC.

Translating genetic findings for neurodevelopmental and psychiatric disorders (NPD) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, here we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop-codons (iSTOP) that lead to mRNA nonsense-mediated-decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 NPD genes. Using RNAseq, we confirmed their pluripotency, absence of chromosomal abnormalities, and NMD. Interestingly, for three schizophrenia risk genes (SETD1A, TRIO, CUL1), despite the high efficiency of base editing, we only obtained heterozygous LoF alleles, suggesting their essential roles for cell growth. We replicated the reported neural phenotypes of SHANK3-haploinsufficiency and found CUL1-LoF reduced neurite branches and synaptic puncta density. This iSTOP pipeline enables a scaled and efficient LoF mutagenesis of NPD genes, yielding an invaluable shareable resource.

Scaled and efficient derivation of loss-of-function alleles in risk genes for neurodevelopmental and psychiatric disorders in human iPSCs.

Translating genetic findings for neurodevelopmental and psychiatric disorders (NPDs) into actionable disease biology would benefit from large-scale and unbiased functional studies of NPD genes. Leveraging the cytosine base editing (CBE) system, we developed a pipeline for clonal loss-of-function (LoF) allele mutagenesis in human induced pluripotent stem cells (hiPSCs) by introducing premature stop codons (iSTOP) that lead to mRNA nonsense-mediated decay (NMD) or protein truncation. We tested the pipeline for 23 NPD genes on 3 hiPSC lines and achieved highly reproducible, efficient iSTOP editing in 22 genes. Using RNA sequencing (RNA-seq), we confirmed their pluripotency, absence of chromosomal abnormalities, and NMD. Despite high editing efficiency, three schizophrenia risk genes (SETD1A, TRIO, and CUL1) only had heterozygous LoF alleles, suggesting their essential roles for cell growth. We found that CUL1-LoF reduced neurite branches and synaptic puncta density. This iSTOP pipeline enables a scaled and efficient LoF mutagenesis of NPD genes, yielding an invaluable shareable resource.