Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome.

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer's Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer's disease, 6 genes with Parkinson's disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.

Amino acid residues in five separate HLA genes can explain most of the known associations between the MHC and primary biliary cholangitis.

Primary Biliary Cholangitis (PBC) is a chronic autoimmune liver disease characterised by progressive destruction of intrahepatic bile ducts. The strongest genetic association is with HLA-DQA1*04:01, but at least three additional independent HLA haplotypes contribute to susceptibility. We used dense single nucleotide polymorphism (SNP) data in 2861 PBC cases and 8514 controls to impute classical HLA alleles and amino acid polymorphisms using state-of-the-art methodologies. We then demonstrated through stepwise regression that association in the HLA region can be largely explained by variation at five separate amino acid positions. Three-dimensional modelling of protein structures and calculation of electrostatic potentials for the implicated HLA alleles/amino acid substitutions demonstrated a correlation between the electrostatic potential of pocket P6 in HLA-DP molecules and the HLA-DPB1 alleles/amino acid substitutions conferring PBC susceptibility/protection, highlighting potential new avenues for future functional investigation.

A Bayesian framework for multiple trait colocalization from summary association statistics.

Motivation: Most genetic variants implicated in complex diseases by genome-wide association studies (GWAS) are non-coding, making it challenging to understand the causative genes involved in disease. Integrating external information such as quantitative trait locus (QTL) mapping of molecular traits (e.g. expression, methylation) is a powerful approach to identify the subset of GWAS signals explained by regulatory effects. In particular, expression QTLs (eQTLs) help pinpoint the responsible gene among the GWAS regions that harbor many genes, while methylation QTLs (mQTLs) help identify the epigenetic mechanisms that impact gene expression which in turn affect disease risk. In this work, we propose multiple-trait-coloc (moloc), a Bayesian statistical framework that integrates GWAS summary data with multiple molecular QTL data to identify regulatory effects at GWAS risk loci. Results: We applied moloc to schizophrenia (SCZ) and eQTL/mQTL data derived from human brain tissue and identified 52 candidate genes that influence SCZ through methylation. Our method can be applied to any GWAS and relevant functional data to help prioritize disease associated genes. Availability and implementation: moloc is available for download as an R package (https://github.com/clagiamba/moloc). We also developed a web site to visualize the biological findings (icahn.mssm.edu/moloc). The browser allows searches by gene, methylation probe and scenario of interest. Supplementary information: Supplementary data are available at Bioinformatics online.

Genetic association analysis identifies variants associated with disease progression in primary sclerosing cholangitis.

OBJECTIVE: Primary sclerosing cholangitis (PSC) is a genetically complex, inflammatory bile duct disease of largely unknown aetiology often leading to liver transplantation or death. Little is known about the genetic contribution to the severity and progression of PSC. The aim of this study is to identify genetic variants associated with PSC disease progression and development of complications. DESIGN: We collected standardised PSC subphenotypes in a large cohort of 3402 patients with PSC. After quality control, we combined 130 422 single nucleotide polymorphisms of all patients-obtained using the Illumina immunochip-with their disease subphenotypes. Using logistic regression and Cox proportional hazards models, we identified genetic variants associated with binary and time-to-event PSC subphenotypes. RESULTS: We identified genetic variant rs853974 to be associated with liver transplant-free survival (p=6.07×10-9). Kaplan-Meier survival analysis showed a 50.9% (95% CI 41.5% to 59.5%) transplant-free survival for homozygous AA allele carriers of rs853974 compared with 72.8% (95% CI 69.6% to 75.7%) for GG carriers at 10 years after PSC diagnosis. For the candidate gene in the region, RSPO3, we demonstrated expression in key liver-resident effector cells, such as human and murine cholangiocytes and human hepatic stellate cells. CONCLUSION: We present a large international PSC cohort, and report genetic loci associated with PSC disease progression. For liver transplant-free survival, we identified a genome-wide significant signal and demonstrated expression of the candidate gene RSPO3 in key liver-resident effector cells. This warrants further assessments of the role of this potential key PSC modifier gene.

Generation of primary human intestinal T cell transcriptomes reveals differential expression at genetic risk loci for immune-mediated disease.

OBJECTIVE: Genome-wide association studies (GWAS) have identified genetic variants within multiple risk loci as predisposing to intestinal inflammatory diseases, including Crohn's disease, ulcerative colitis and coeliac disease. Most risk variants affect regulation of transcription, but a critical challenge is to identify which genes and which cell types these variants affect. We aimed to characterise whole transcriptomes for each common T lymphocyte subset resident within the gut mucosa, and use these to infer biological insights and highlight candidate genes of interest within GWAS risk loci. DESIGN: We isolated the four major intestinal T cell populations from pinch biopsies from healthy subjects and generated transcriptomes for each. We computationally integrated these transcriptomes with GWAS data from immune-related diseases. RESULTS: Robust, high quality transcriptomic data were generated from 1 ng of RNA from precisely sorted cell subsets. Gene expression patterns clearly differentiated intestinal T cells from counterparts in peripheral blood and revealed distinct signalling pathways for each intestinal T cell subset. Intestinal-specific T cell transcripts were enriched in GWAS risk loci for Crohn's disease, ulcerative colitis and coeliac disease, but also specific extraintestinal immune-mediated diseases, allowing prediction of novel candidate genes. CONCLUSIONS: This is the first report of transcriptomes for minimally manipulated intestinal T lymphocyte subsets in humans. We have demonstrated that careful processing of mucosal biopsies allows the generation of transcriptomes from as few as 1000 highly purified cells with minimal interindividual variation. Bioinformatic integration of transcriptomic data with recent GWAS data identified specific candidate genes and cell types for inflammatory pathologies.

GWAS findings for human iris patterns: associations with variants in genes that influence normal neuronal pattern development.

Human iris patterns are highly variable. The origins of this variation are of interest in the study of iris-related eye diseases and forensics, as well as from an embryological developmental perspective, with regard to their possible relationship to fundamental processes of neurodevelopment. We have performed genome-wide association scans on four iris characteristics (crypt frequency, furrow contractions, presence of peripupillary pigmented ring, and number of nevi) in three Australian samples of European descent. Both the discovery (n = 2121) and replication (n = 499 and 73) samples showed evidence for association between (1) crypt frequency and variants in the axonal guidance gene SEMA3A (p = 6.6 × 10(-11)), (2) furrow contractions and variants within the cytoskeleton gene TRAF3IP1 (p = 2.3 × 10(-12)), and (3) the pigmented ring and variants in the well-known pigmentation gene SLC24A4 (p = 7.6 × 10(-21)). These replicated findings individually accounted for around 1.5%-3% of the variance for these iris characteristics. Because both SEMA3A and TRAFIP1 are implicated in pathways that control neurogenesis, neural migration, and synaptogenesis, we also examined the evidence of enhancement among such genes, finding enrichment for crypts and furrows. These findings suggest that genes involved in normal neuronal pattern development may also influence tissue structures in the human iris.

Whole-exome sequencing in UK Biobank reveals rare genetic architecture for depression.

Nearly two hundred common-variant depression risk loci have been identified by genome-wide association studies (GWAS). However, the impact of rare coding variants on depression remains poorly understood. Here, we present whole-exome sequencing analyses of depression with seven different definitions based on survey, questionnaire, and electronic health records in 320,356 UK Biobank participants. We showed that the burden of rare damaging coding variants in loss-of-function intolerant genes is significantly associated with risk of depression with various definitions. We compared the rare and common genetic architecture across depression definitions by genetic correlation and showed different genetic relationships between definitions across common and rare variants. In addition, we demonstrated that the effects of rare damaging coding variant burden and polygenic risk score on depression risk are additive. The gene set burden analyses revealed overlapping rare genetic variant components with developmental disorder, autism, and schizophrenia. Our study provides insights into the contribution of rare coding variants, separately and in conjunction with common variants, on depression with various definitions and their genetic relationships with neurodevelopmental disorders.

A versatile gene-based test for genome-wide association studies.

We have derived a versatile gene-based test for genome-wide association studies (GWAS). Our approach, called VEGAS (versatile gene-based association study), is applicable to all GWAS designs, including family-based GWAS, meta-analyses of GWAS on the basis of summary data, and DNA-pooling-based GWAS, where existing approaches based on permutation are not possible, as well as singleton data, where they are. The test incorporates information from a full set of markers (or a defined subset) within a gene and accounts for linkage disequilibrium between markers by using simulations from the multivariate normal distribution. We show that for an association study using singletons, our approach produces results equivalent to those obtained via permutation in a fraction of the computation time. We demonstrate proof-of-principle by using the gene-based test to replicate several genes known to be associated on the basis of results from a family-based GWAS for height in 11,536 individuals and a DNA-pooling-based GWAS for melanoma in approximately 1300 cases and controls. Our method has the potential to identify novel associated genes; provide a basis for selecting SNPs for replication; and be directly used in network (pathway) approaches that require per-gene association test statistics. We have implemented the approach in both an easy-to-use web interface, which only requires the uploading of markers with their association p-values, and a separate downloadable application.

PD-1, PD-L1, IDO, CD70 and microsatellite instability as potential targets to prevent immune evasion in sarcomas.

Background: Soft tissue and bone sarcomas are rare entities, hence, standardized therapeutic strategies are difficult to assess. Materials & methods: Immunohistochemistry was performed on 68 sarcoma samples to assess the expression of PD-1, PD-L1, IDO and CD70 in different tumor compartments and molecular analysis was performed to assess microsatellite instability status. Results: PD-1/PD-L1, IDO and CD70 pathways are at play in the immune evasion of sarcomas in general. Soft tissue sarcomas more often show an inflamed phenotype compared with bone sarcomas. Specific histologic sarcoma types show high expression levels of different markers. Finally, this is the first presentation of a microsatellite instability-high Kaposi sarcoma. Discussion/conclusion: Immune evasion occurs in sarcomas. Specific histologic types might benefit from immunotherapy, for which further investigation is needed.

Sarcomas of the soft tissue and bone are rare cancers. When these cancers spread to other parts of the body, it is hard to find good treatments. Recently, doctors have been using a new type of treatment called immunotherapy to fight several types of cancer. Immunotherapy works by getting one's body's own defense cells to attack the cancer cells. Unfortunately, immunotherapy does not work well for sarcomas and we do not know why. This study was designed to determine if there are certain mechanisms in these tumors that help the cancer cells to hide from defense cells. Determining how to change these mechanisms could make immunotherapy a better treatment for sarcomas in the future.

The impact of rare protein coding genetic variation on adult cognitive function.

Compelling evidence suggests that human cognitive function is strongly influenced by genetics. Here, we conduct a large-scale exome study to examine whether rare protein-coding variants impact cognitive function in the adult population (n = 485,930). We identify eight genes (ADGRB2, KDM5B, GIGYF1, ANKRD12, SLC8A1, RC3H2, CACNA1A and BCAS3) that are associated with adult cognitive function through rare coding variants with large effects. Rare genetic architecture for cognitive function partially overlaps with that of neurodevelopmental disorders. In the case of KDM5B we show how the genetic dosage of one of these genes may determine the variability of cognitive, behavioral and molecular traits in mice and humans. We further provide evidence that rare and common variants overlap in association signals and contribute additively to cognitive function. Our study introduces the relevance of rare coding variants for cognitive function and unveils high-impact monogenic contributions to how cognitive function is distributed in the normal adult population.

No association of candidate genes with cannabis use in a large sample of Australian twin families.

While there is solid evidence that cannabis use is heritable, attempts to identify genetic influences at the molecular level have yielded mixed results. Here, a large twin family sample (n = 7452) was used to test for association between 10 previously reported candidate genes and lifetime frequency of cannabis use using a gene-based association test. None of the candidate genes reached even nominal significance (P < 0.05). The lack of replication may point to our limited understanding of the neurobiology of cannabis involvement and also to potential publication bias and false-positive findings in previous studies.

Improving Timeliness in Surgical Discharge Summary Distribution: A Quality Improvement Initiative.

Objective: To implement a quality improvement initiative to achieve an institutional targeted discharge summary distribution metric of 50% within 48 hours of patient discharge from hospital within an academic tertiary care otolaryngology-head and neck surgery department. Methods: A pre- and postintervention study was conducted. Process mapping was performed. Interventions included education and engagement, implementation of auto-authentication (distribution immediately following transcription without review by the most responsible physician), and audit and feedback. The percentage of discharge summaries dictated with the auto-authentication code was evaluated. Process measures were collected for 12 months pre- and postimplementation. Balancing measures included workload and revisions to auto-authenticated notes. Analysis included summary statistics, statistical process control charting, and unpaired t tests. Results: The mean ± SD percentage of discharge summaries distributed within 48 hours increased from 19% ± 6.4% preintervention to 54% ± 20% postintervention (P < .0001). Seventy-four percent of discharge summaries were dictated via the auto-authentication code. The target metric was met in 71% of discharges with the auto-authentication codes as compared with 26% with non-auto-authentication. The interventions did not result in any change to perceived workload, and the incidence of auto-authentication revisions was <1%. The results were sustained with an increase of 72% the following quarter. For fiscal year 2021-2022, performance remained sustained with an 85% completion rate. Discussion: Our surgical department exceeded and sustained the targeted metric for timely discharge summary distribution using a quality improvement approach. Implications for Practice: Timely distribution of discharge summaries optimizes patients' transitions of care and can be achieved through stakeholder education and engagement, auto-authentication, and audit with feedback.

The burden of rare protein-truncating genetic variants on human lifespan.

Genetic predisposition has been shown to contribute substantially to the age at which we die. Genome-wide association studies (GWASs) have linked more than 20 loci to phenotypes related to human lifespan1. However, little is known about how lifespan is impacted by gene loss of function. Through whole-exome sequencing of 352,338 UK Biobank participants of European ancestry, we assessed the relevance of protein-truncating variant (PTV) gene burden on individual and parental survival. We identified four exome-wide significant (P < 4.2 × 10-7) human lifespan genes, BRCA1, BRCA2, ATM and TET2. Gene and gene-set, PTV-burden, phenome-wide association studies support known roles of these genes in cancer to impact lifespan at the population level. The TET2 PTV burden was associated with a lifespan through somatic mutation events presumably due to clonal hematopoiesis. The overlap between PTV burden and common variant-based lifespan GWASs was modest, underscoring the value of exome sequencing in well-powered biobank cohorts to complement GWASs for identifying genes underlying complex traits.

Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake.

Complex traits are characterized by multiple genes and variants acting simultaneously on a phenotype. However, studying the contribution of individual pairs of genes to complex traits has been challenging since human genetics necessitates very large population sizes, while findings from model systems do not always translate to humans. Here, we combine genetics with combinatorial RNAi (coRNAi) to systematically test for pairwise additive effects (AEs) and genetic interactions (GIs) between 30 lipid genome-wide association studies (GWAS) genes. Gene-based burden tests from 240,970 exomes show that in carriers with truncating mutations in both, APOB and either PCSK9 or LPL ("human double knock-outs") plasma lipid levels change additively. Genetics and coRNAi identify overlapping AEs for 12 additional gene pairs. Overlapping GIs are observed for TOMM40/APOE with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate plasma and cellular lipid levels primarily via AEs and nominates putative drug target pairs for improved lipid-lowering combination therapies.

Genome-wide meta-analysis, fine-mapping and integrative prioritization implicate new Alzheimer's disease risk genes.

Genome-wide association studies have discovered numerous genomic loci associated with Alzheimer's disease (AD); yet the causal genes and variants are incompletely identified. We performed an updated genome-wide AD meta-analysis, which identified 37 risk loci, including new associations near CCDC6, TSPAN14, NCK2 and SPRED2. Using three SNP-level fine-mapping methods, we identified 21 SNPs with >50% probability each of being causally involved in AD risk and others strongly suggested by functional annotation. We followed this with colocalization analyses across 109 gene expression quantitative trait loci datasets and prioritization of genes by using protein interaction networks and tissue-specific expression. Combining this information into a quantitative score, we found that evidence converged on likely causal genes, including the above four genes, and those at previously discovered AD loci, including BIN1, APH1B, PTK2B, PILRA and CASS4.

A map of transcriptional heterogeneity and regulatory variation in human microglia.

Microglia, the tissue-resident macrophages of the central nervous system (CNS), play critical roles in immune defense, development and homeostasis. However, isolating microglia from humans in large numbers is challenging. Here, we profiled gene expression variation in primary human microglia isolated from 141 patients undergoing neurosurgery. Using single-cell and bulk RNA sequencing, we identify how age, sex and clinical pathology influence microglia gene expression and which genetic variants have microglia-specific functions using expression quantitative trait loci (eQTL) mapping. We follow up one of our findings using a human induced pluripotent stem cell-based macrophage model to fine-map a candidate causal variant for Alzheimer's disease at the BIN1 locus. Our study provides a population-scale transcriptional map of a critically important cell for human CNS development and disease.

Liver tumour segmentation using contrast-enhanced multi-detector CT data: performance benchmarking of three semiautomated methods.

OBJECTIVE: Automatic tumour segmentation and volumetry is useful in cancer staging and treatment outcome assessment. This paper presents a performance benchmarking study on liver tumour segmentation for three semiautomatic algorithms: 2D region growing with knowledge-based constraints (A1), 2D voxel classification with propagational learning (A2) and Bayesian rule-based 3D region growing (A3). METHODS: CT data from 30 patients were studied, and 47 liver tumours were isolated and manually segmented by experts to obtain the reference standard. Four datasets with ten tumours were used for algorithm training and the remaining 37 tumours for testing. Three evaluation metrics, relative absolute volume difference (RAVD), volumetric overlap error (VOE) and average symmetric surface distance (ASSD), were computed based on computerised and reference segmentations. RESULTS: A1, A2 and A3 obtained mean/median RAVD scores of 17.93/10.53%, 17.92/9.61% and 34.74/28.75%, mean/median VOEs of 30.47/26.79%, 25.70/22.64% and 39.95/38.54%, and mean/median ASSDs of 2.05/1.41 mm, 1.57/1.15 mm and 4.12/3.41 mm, respectively. For each metric, we obtained significantly lower values of A1 and A2 than A3 (P < 0.01), suggesting that A1 and A2 outperformed A3. CONCLUSIONS: Compared with the reference standard, the overall performance of A1 and A2 is promising. Further development and validation is necessary before reliable tumour segmentation and volumetry can be widely used clinically.

Genome-wide association study of height and body mass index in Australian twin families.

Human height and body mass index are influenced by a large number of genes, each with small effects, along with environment. To identify common genetic variants associated with these traits, we performed genome-wide association studies in 11,536 individuals composed of Australian twins, family members, and unrelated individuals at approximately 550,000 genotyped SNPs. We identified a single genome-wide significant variant for height (P value=1.06x10(-9)) located in HHIP, a well-replicated height-associated gene. Suggestive levels of association were found for other known genes associated with height (P values<1x10(-6)): ADAMTSL3, EFEMP1, GPR126, and HMGA2; and BMI (P values<1x10(-4)): FTO and MC4R. Together, these variants explain less than 2% of total phenotypic variation for height and 0.5% for BMI.

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases.

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here we estimated the effects of 1,002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium is widespread in naïve phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.

Association Between Common Variants in RBFOX1, an RNA-Binding Protein, and Brain Amyloidosis in Early and Preclinical Alzheimer Disease.

Importance: Genetic studies of Alzheimer disease have focused on the clinical or pathologic diagnosis as the primary outcome, but little is known about the genetic basis of the preclinical phase of the disease. Objective: To examine the underlying genetic basis for brain amyloidosis in the preclinical phase of Alzheimer disease. Design, Setting, and Participants: In the first stage of this genetic association study, a meta-analysis was conducted using genetic and imaging data acquired from 6 multicenter cohort studies of healthy older individuals between 1994 and 2019: the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study, the Berkeley Aging Cohort Study, the Wisconsin Registry for Alzheimer's Prevention, the Biomarkers of Cognitive Decline Among Normal Individuals cohort, the Baltimore Longitudinal Study of Aging, and the Alzheimer Disease Neuroimaging Initiative, which included Alzheimer disease and mild cognitive impairment. The second stage was designed to validate genetic observations using pathologic and clinical data from the Religious Orders Study and Rush Memory and Aging Project. Participants older than 50 years with amyloid positron emission tomographic (PET) imaging data and DNA from the 6 cohorts were included. The largest cohort, the Anti-Amyloid Treatment in Asymptomatic Alzheimer Disease Study (n = 3154), was the PET screening cohort used for a secondary prevention trial designed to slow cognitive decline associated with brain amyloidosis. Six smaller, longitudinal cohort studies (n = 1160) provided additional amyloid PET imaging data with existing genetic data. The present study was conducted from March 29, 2019, to February 19, 2020. Main Outcomes and Measures: A genome-wide association study of PET imaging amyloid levels. Results: From the 4314 analyzed participants (age, 52-96 years; 2478 participants [57%] were women), a novel locus for amyloidosis was noted within RBFOX1 (ß = 0.61, P = 3 × 10-9) in addition to APOE. The RBFOX1 protein localized around plaques, and reduced expression of RBFOX1 was correlated with higher amyloid-ß burden (ß = -0.008, P = .002) and worse cognition (ß = 0.007, P = .006) during life in the Religious Orders Study and Rush Memory and Aging Project cohort. Conclusions and Relevance: RBFOX1 encodes a neuronal RNA-binding protein known to be expressed in neuronal tissues and may play a role in neuronal development. The findings of this study suggest that RBFOX1 is a novel locus that may be involved in the pathogenesis of Alzheimer disease.