Analysis of subcellular RNA fractions demonstrates significant genetic regulation of gene expression in human brain post-transcriptionally

Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed

Human-lineage-specific genomic elements are associated with neurodegenerative disease and APOE transcript usage

Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer?s disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease.FUNDING: Acknowledgements The authors are grateful to the participants in the Religious Order Study, the Memory and Aging Project. Z.C. and R.H.R. were supported by grants from the Leonard Wolfson Foundation. M.R. was supported by the United Kingdom Medical Research Council (MRC) through the award of a Tenure Track Clinician Scientist Fellowship (MR/ N008324/1). J.H. was supported by the UK Dementia Research Institute which receives its funding from DRI Limited, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK. J.H. has also been funded by the Medical Research Council (award MR/N026004/1), Wellcome Trust (award 202903/Z/16/Z), Dolby Family Fund and National Institute for Health Research University College London Hospitals Biomedical Research Centre. J.B. is supported through the Science and Technology Agency, Séneca Foundation, CARM, Spain (research project 00007/COVI/20)

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Identification of candidate Parkinson disease genes by integrating genome-wide association study, expression, and epigenetic data sets

Importance Substantial genome-wide association study (GWAS) work in Parkinson disease (PD) has led to the discovery of an increasing number of loci shown reliably to be associated with increased risk of disease. Improved understanding of the underlying genes and mechanisms at these loci will be key to understanding the pathogenesis of PD. Objective To investigate what genes and genomic processes underlie the risk of sporadic PD. Design and Setting This genetic association study used the bioinformatic tools Coloc and transcriptome-wide association study (TWAS) to integrate PD case-control GWAS data published in 2017 with expression data (from Braineac, the Genotype-Tissue Expression [GTEx], and CommonMind) and methylation data (derived from UK Parkinson brain samples) to uncover putative gene expression and splicing mechanisms associated with PD GWAS signals. Candidate genes were further characterized using cell-type specificity, weighted gene coexpression networks, and weighted protein-protein interaction networks. Main Outcomes and Measures It was hypothesized a priori that some genes underlying PD loci would alter PD risk through changes to expression, splicing, or methylation. Candidate genes are presented whose change in expression, splicing, or methylation are associated with risk of PD as well as the functional pathways and cell types in which these genes have an important role. Results Gene-level analysis of expression revealed 5 genes (WDR6 [OMIM 606031], CD38 [OMIM 107270], GPNMB [OMIM 604368], RAB29 [OMIM 603949], and TMEM163 [OMIM 618978]) that replicated using both Coloc and TWAS analyses in both the GTEx and Braineac expression data sets. A further 6 genes (ZRANB3 [OMIM 615655], PCGF3 [OMIM 617543], NEK1 [OMIM 604588], NUPL2 [NCBI 11097], GALC [OMIM 606890], and CTSB [OMIM 116810]) showed evidence of disease-associated splicing effects. Cell-type specificity analysis revealed that gene expression was overall more prevalent in glial cell types compared with neurons. The weighted gene coexpression performed on the GTEx data set showed that NUPL2 is a key gene in 3 modules implicated in catabolic processes associated with protein ubiquitination and in the ubiquitin-dependent protein catabolic process in the nucleus accumbens, caudate, and putamen. TMEM163 and ZRANB3 were both important in modules in the frontal cortex and caudate, respectively, indicating regulation of signaling and cell communication. Protein interactor analysis and simulations using random networks demonstrated that the candidate genes interact significantly more with known mendelian PD and parkinsonism proteins than would be expected by chance. Conclusions and Relevance Together, these results suggest that several candidate genes and pathways are associated with the findings observed in PD GWAS studies

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Human-lineage-specific genomic elements are associated with neurodegenerative disease and APOE transcript usage.

Knowledge of genomic features specific to the human lineage may provide insights into brain-related diseases. We leverage high-depth whole genome sequencing data to generate a combined annotation identifying regions simultaneously depleted for genetic variation (constrained regions) and poorly conserved across primates. We propose that these constrained, non-conserved regions (CNCRs) have been subject to human-specific purifying selection and are enriched for brain-specific elements. We find that CNCRs are depleted from protein-coding genes but enriched within lncRNAs. We demonstrate that per-SNP heritability of a range of brain-relevant phenotypes are enriched within CNCRs. We find that genes implicated in neurological diseases have high CNCR density, including APOE, highlighting an unannotated intron-3 retention event. Using human brain RNA-sequencing data, we show the intron-3-retaining transcript to be more abundant in Alzheimer's disease with more severe tau and amyloid pathological burden. Thus, we demonstrate potential association of human-lineage-specific sequences in brain development and neurological disease

Mitochondrial dysfunction is a key pathological driver of early stage Parkinson's

BACKGROUND: The molecular drivers of early sporadic Parkinson’s disease (PD) remain unclear, and the presence of widespread end stage pathology in late disease masks the distinction between primary or causal disease-specific events and late secondary consequences in stressed or dying cells. However, early and mid-stage Parkinson’s brains (Braak stages 3 and 4) exhibit alpha-synuclein inclusions and neuronal loss along a regional gradient of severity, from unaffected-mild-moderate-severe. Here, we exploited this spatial pathological gradient to investigate the molecular drivers of sporadic PD. METHODS: We combined high precision tissue sampling with unbiased large-scale profiling of protein expression across 9 brain regions in Braak stage 3 and 4 PD brains, and controls, and verified these results using targeted proteomic and functional analyses. RESULTS: We demonstrate that the spatio-temporal pathology gradient in early-mid PD brains is mirrored by a biochemical gradient of a changing proteome. Importantly, we identify two key events that occur early in the disease, prior to the occurrence of alpha-synuclein inclusions and neuronal loss: (i) a metabolic switch in the utilisation of energy substrates and energy production in the brain, and (ii) perturbation of the mitochondrial redox state. These changes may contribute to the regional vulnerability of developing alpha-synuclein pathology. Later in the disease, mitochondrial function is affected more severely, whilst mitochondrial metabolism, fatty acid oxidation, and mitochondrial respiration are affected across all brain regions. CONCLUSIONS: Our study provides an in-depth regional profile of the proteome at different stages of PD, and highlights that mitochondrial dysfunction is detectable prior to neuronal loss, and alpha-synuclein fibril deposition, suggesting that mitochondrial dysfunction is one of the key drivers of early disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40478-022-01424-6

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information.

Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/

Regulatory sites for splicing in human basal ganglia are enriched for disease-relevant information

Abstract Genome-wide association studies have generated an increasing number of common genetic variants associated with neurological and psychiatric disease risk. An improved understanding of the genetic control of gene expression in human brain is vital considering this is the likely modus operandum for many causal variants. However, human brain sampling complexities limit the explanatory power of brain-related expression quantitative trait loci (eQTL) and allele-specific expression (ASE) signals. We address this, using paired genomic and transcriptomic data from putamen and substantia nigra from 117 human brains, interrogating regulation at different RNA processing stages and uncovering novel transcripts. We identify disease-relevant regulatory loci, find that splicing eQTLs are enriched for regulatory information of neuron-specific genes, that ASEs provide cell-specific regulatory information with evidence for cellular specificity, and that incomplete annotation of the brain transcriptome limits interpretation of risk loci for neuropsychiatric disease. This resource of regulatory data is accessible through our web server, http://braineacv2.inf.um.es/.International Parkinson’s Disease Genomics Consortium (IPDGC) Alastair J. Noyce1,14, Aude Nicolas8, Mark R. Cookson8, Sara Bandres-Ciga8, J. Raphael Gibbs8, Dena G. Hernandez8, Andrew B. Singleton8, Xylena Reed8, Hampton Leonard8, Cornelis Blauwendraat8,14, Faraz Faghri3,15,16, Jose Bras10, Rita Guerreiro17, Arianna Tucci17, Demis A. Kia17, Henry Houlden17, Helene Plun-Favreau17, Kin Y Mok17, Nicholas W. Wood17, Ruth Lovering17, Lea R’Bibo17, Mie Rizig17, Viorica Chelban17, Manuela Tan12, Huw R. Morris18, Ben Middlehurst19, John Quinn19, Kimberley Billingsley19, Peter Holmans20, Kerri J. Kinghorn21, Patrick Lewis22, Valentina Escott-Price23, Nigel Williams23, Thomas Foltynie24, Alexis Brice25, Fabrice Danjou25, Suzanne Lesage25, Jean-Christophe Corvol25, Maria Martinez25,26, Anamika Giri27,28, Claudia Schulte27,28, Kathrin Brockmann27,28, Javier Simón-Sánchez27,28, Peter Heutink27,28, Thomas Gasser27,28, Patrizia Rizzu28, Manu Sharma29, Joshua M. Shulman30,31, Laurie Robak30, Steven Lubbe32, Niccolo E. Mencacci33, Steven Finkbeiner34,35, Codrin Lungu36, Sonja W. Scholz37, Ziv Gan-Or38, Guy A. Rouleau39, Lynne Krohan40, Jacobus J. van Hilten41, Johan Marinus41, Astrid D. Adarmes-Gómez42, Inmaculada Bernal-Bernal42, Marta Bonilla-Toribio42, Dolores Buiza-Rueda42, Fátima Carrillo42, Mario Carrión-Claro42, Pablo Mir42, Pilar Gómez-Garre42, Silvia Jesús42, Miguel A. Labrador-Espinosa42, Daniel Macias42, Laura Vargas-González42, Carlota Méndez-del-Barrio42, Teresa Periñán-Tocino42, Cristina Tejera-Parrado42, Monica Diez-Fairen43, Miquel Aguilar43, Ignacio Alvarez43, María Teresa Boungiorno43, Maria Carcel43, Pau Pastor43, Juan Pablo Tartari43, Victoria Alvarez44, Manuel Menéndez González44, Marta Blazquez44, Ciara Garcia44, Esther Suarez-Sanmartin44, Francisco Javier Barrero45, Elisabet Mondragon Rezola46, Jesús Alberto Bergareche Yarza47, Ana Gorostidi Pagola47, Adolfo López de Munain Arregui47, Javier Ruiz-Martínez47, Debora Cerdan48, Jacinto Duarte49, Jordi Clarimón50,51, Oriol Dols-Icardo50,51, Jon Infante51,52,53, Juan Marín51,54, Jaime Kulisevsky51,54, Javier Pagonabarraga51,54, Isabel Gonzalez-Aramburu52, Antonio Sanchez Rodriguez52, María Sierra52, Raquel Duran55, Clara Ruz55, Francisco Vives55, Francisco Escamilla-Sevilla56, Adolfo Mínguez56, Ana Cámara57, Yaroslau Compta57, Mario Ezquerra57, Maria Jose Marti57, Manel Fernández57, Esteban Muñoz57, Rubén Fernández-Santiago57, Eduard Tolosa57, Francesc Valldeoriola57, Pedro García-Ruiz58, Maria Jose Gomez Heredia59, Francisco Perez Errazquin59, Janet Hoenicka60, Adriano Jimenez-Escrig60, Juan Carlos Martínez-Castrillo60, Jose Luis Lopez-Sendon60, Irene Martínez Torres61, Cesar Tabernero61, Lydia Vela61, Alexander Zimprich62, Lasse Pihlstrom63, Sulev Koks64,65,66, Pille Taba67, Kari Majamaa68,69, Ari Siitonen68,69, Njideka U. Okubadejo70 & Oluwadamilola O. Ojo70 14Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, QMUL, London, UK. 15National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA. 16Department of Computer Science, University of Illinois at Urbana-Champaign, Urbana, IL, USA. 17Department of Molecular Neuroscience, UCL, London, UK. 18Department of Clinical Neuroscience, University College London, London, UK. 19Institute of Translational Medicine, University of Liverpool, Liverpool, UK. 20Biostatistics & Bioinformatics Unit, Institute of Psychological Medicine and Clinical Neuroscience, MRC Centre for Neuropsychiatric Genetics & Genomics, Cardiff, UK. 21Institute of Healthy Ageing, University College London, London, UK. 22University of Reading, Reading, UK. 23MRC Centre for Neuropsychiatric Genetics and Genomics, Cardiff University School of Medicine, Cardiff, UK. 24UCL Institute of Neurology, London, UK. 25Institut du Cerveau et de la Moelle épinière, ICM, Inserm U 1127, CNRS, UMR 7225, Sorbonne Universités, UPMC University Paris 06, UMR S 1127, AP-HP, Pitié-Salpêtrière Hospital, Paris, France. 26Paul Sabatier University, Toulouse, France. 27Department for Neurodegenerative Diseases, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany. 28DZNE, German Center for Neurodegenerative Diseases, Tübingen, Germany. 29Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Applied Biometry, University of Tubingen, Tübingen, Germany. 30Departments of Neurology, Neuroscience, and Molecular & Human Genetics, Baylor College of Medicine, Houston, TX, USA. 31Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, USA. 32Ken and Ruth Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. 33Northwestern University Feinberg School of Medicine, Chicago, IL, USA. 34Departments of Neurology and Physiology, University of California, San Francisco, CA, USA. 35Gladstone Institute of Neurological Disease; Taube/Koret Center for Neurodegenerative Disease Research, San Francisco, CA, USA. 36National Institutes of Health Division of Clinical Research, NINDS, National Institutes of Health, Bethesda, MD, USA. 37Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA. 38Montreal Neurological Institute and Hospital, Department of Neurology & Neurosurgery, Department of Human Genetics, McGill University, Montréal, QC H3A 0G4, Canada. 39Department of Human Genetics, McGill University, Montréal, QC H3A 0G4, Canada. 40Department of Neurology, Leiden University Medical Center, Leiden, Netherlands. 41Instituto de Biomedicina de Sevilla (IBiS), Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain. 42Fundació Docència i Recerca Mútua de Terrassa and Movement Disorders Unit, Department of Neurology, University Hospital Mutua de Terrassa, Terrassa, Barcelona, Spain. 43Hospital Universitario Central de Asturias, Oviedo, Spain. 44Hospital Universitario Parque Tecnologico de la Salud, Granada, Spain. 45Instituto de Investigación Sanitaria Biodonostia, San Sebastián, Spain. 46Hospital General de Segovia, Segovia, Spain. 47Memory Unit, Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain. 48Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain. 49Hospital Universitario Marqués de Valdecilla-IDIVAL, Santander, Spain. 50University of Cantabria, Santander, Spain. 51Movement Disorders Unit, Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain. 52Centro de Investigacion Biomedica, Universidad de Granada, Granada, Spain. 53Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria de Granada, Granada, Spain. 54Hospital Clinic de Barcelona, Barcelona, Spain. 55Instituto de Investigación Sanitaria Fundación Jiménez Díaz, Madrid, Spain. 56Hospital Universitario Virgen de la Victoria, Malaga, Spain. 57Institut de Recerca Sant Joan de Déu, Barcelona, Spain. 58Hospital Universitario Ramón y Cajal, Madrid, Spain. 59Department of Neurology, Instituto de Investigación Sanitaria La Fe, Hospital Universitario y Politécnico La Fe, Valencia, Spain. 60Hospital General de Segovia, Segovia, Spain. 61Department of Neurology, Hospital Universitario Fundación Alcorcón, Madrid, Spain. 62Department of Neurology, Medical University of Vienna, Vienna, Austria. 63Department of Neurology, Oslo University Hospital, Oslo, Norway. 64Department of Pathophysiology, University of Tartu, Tartu, Estonia. 65Department of Reproductive Biology, Estonian University of Life Sciences, Tartu, Estonia. 66Perron Institute for Neurological and Translational Science, Perth, WA, Australia. 67Department of Neurology and Neurosurgery, University of Tartu, Tartu, Estonia. 68Institute of Clinical Medicine, Department of Neurology, University of Oulu, Oulu, Finland. 69Department of Neurology and Medical Research Center, Oulu University Hospital, Oulu, Finland. 70University of Lago, Lagos State, Nigeria UK Brain Expression Consortium (UKBEC) Paola Forabosco71 & Robert Walker11 71Istituto di Ricerca Genetica e Biomedica, Cittadella Universitaria di Cagliari, 09042 Monserrato, Sardinia, Ital

Neuropeptide Y signalling on hippocampal stem cells in health and disease

Neuropeptides are emerging as key components in the hippocampal neurogenic niche in health and disease, regulating many aspects of neurogenesis and the synaptic integration of newly generated neurons. This review focuses on the role of neuropeptide Y in the control of stem/precursor cells in the postnatal and adult hippocampus. It is likely that neuropeptide Y releasing interneurons are key sensors of neural activity, modulating neurogenesis appropriately. This is likely to be a fruitful area of research for extending our understanding of the control of stem cells in the normal and diseased brain