Quality control parameters on a large dataset of regionally dissected human control brains for whole genome expression studies
Open accessAbstract
We are building an open-access database of regional human brain expression designed to allow the genome-wide assessment of genetic variability on expression. Array and RNA sequencing technologies make assessment of genome-wide expression possible. Human brain tissue is a challenging source for this work because it can only be obtained several and variable hours post-mortem and after varying agonal states. These variables alter RNA integrity in a complex manner. In this report, we assess the effect of post-mortem delay, agonal state and age on gene expression, and the utility of pH and RNA integrity number as predictors of gene expression as measured on 1266 Affymetrix Exon Arrays. We assessed the accuracy of the array data using QuantiGene, as an independent non-PCR-based method. These quality control parameters will allow database users to assess data accuracy. We report that within the parameters of this study post-mortem delay, agonal state and age have little impact on array quality, array data are robust to variable RNA integrity, and brain pH has only a small effect on array performance. QuantiGene gave very similar expression profiles as array data. This study is the first step in our initiative to make human, regional brain expression freely available.
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Expression profiling during human brain aging is challenging because postmortem tissue can take hours to days to stabilize.
“Expression profiling during human brain aging is particularly challenging since it can take hours to days before postmortem tissue is stabilized (Melé et al., 2015; Soreq et al., 2017; Trabzuni et al., 2011).”
From Atlas of the aging mouse brain reveals white matter as vulnerable foci (2023) · cites this paper as Trabzuni et al., 2011
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Cites
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Self-citationThe <i>MS4A</i> gene cluster is a key modulator of soluble TREM2 and Alzheimer’s disease risk
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“…affiliate of Sun Health Corporation, USA.12 A full description of the samples used and the methods of RNA isolation and processing can be found in Trabzuni et al., 2011.13 As previously described, all arrays were preprocessed with robustmultiarray-average quantile normalization with GC…”
MethodInfluentialSelf-citationMutations in the histone methyltransferase gene KMT2B cause complex early-onset dystonia
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Atlas of the aging mouse brain reveals white matter as vulnerable foci
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“Braineac eQTL Data The UK Brain Expression Consortium Braineac data set contains data from 10 brain regions obtained from 134 control individuals: frontal cortex, temporal cortex,occipital cortex,hippocampus, thalamus, putamen, substantia nigra, medulla, cerebellum, andwhitematter, togetherwith themeanexpression acros…”
MethodSelf-citationInsights into TREM2 biology by network analysis of human brain gene expression data
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InfluentialSelf-citationAlpha‐synuclein mRNA expression in oligodendrocytes in MSA
Asi, Y. T., Simpson, J. E., Heath, P. R., Wharton, S. B., Lees, A. J., Révész, T., Houlden, H., & Holton, J. L. (2014) · Glia · doi:10.1002/glia.22653 · Cited by 191 · see citing works
“The expression trend found in MSA and control cases used in this study is similar to that documented in expression databases such as UKBEC and Allen Brain Atlas, which analyze gene expression in control human brains (Hawrylycz et al. 2012; Trabzuni et al. 2011).”
ResultMutations in the autoregulatory domain of β‐tubulin 4a cause hereditary dystonia
Hersheson, J., Mencacci, N. E., Davis, M. B., MacDonald, N., Trabzuni, D., Ryten, M., Pittman, A. M., Paudel, R., Kara, E., Fawcett, K. A., et al. (2012) · Annals of Neurology · doi:10.1002/ana.23832 · Cited by 179 · see citing works
“See Trabzuni et al for detailed methods.(23) CRBL 5 cerebellum; FCTX 5 frontal cortex; HIPP 5 hippocampus; MEDU 5 medulla; OCTX 5 occipital cortex; PUTM 5 putamen; SNIG 5 substantia nigra; TCTX 5 temporal cortex.”
BackgroundSelf-citationCellular correlates of cortical thinning throughout the lifespan
Vidal-Pineiro, D., Parker, N., Shin, J., French, L., Grydeland, H., Jackowski, A. P., Mowinckel, A. M., Patel, Y., Pausova, Z., Salum, G., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-78471-3 · Cited by 154 · see citing works
Recursive splicing in long vertebrate genes
Sibley, C. R., Emmett, W., Blázquez, L., Faro, A., Haberman, N., Briese, M., Trabzuni, D., Ryten, M., Weale, M. E., Hardy, J., et al. (2015) · Nature · doi:10.1038/nature14466 · Cited by 165 · see citing works
Self-citationThe clinical and genetic heterogeneity of paroxysmal dyskinesias
Gardiner, A., Jaffer, F., Dale, R. C., Labrum, R. W., Erro, R., Meyer, E., Xiromerisiou, G., Stamelou, M., Walker, M. C., Kullmann, D. M., et al. (2015) · Brain · doi:10.1093/brain/awv310 · Cited by 158 · see citing works
“Regional distribution of PRRT2, SLC2A1, PNKD, KCN1A, SNAP25 and CACNA1A mRNA expression in the normal human brain was determined using microarray analysis of human post-mortem brain tissue from the UK Human Brain Expression Consortium (Trabzuni et al., 2011).”
MethodPRRT2 Is a Key Component of the Ca2+-Dependent Neurotransmitter Release Machinery
Valente, P., Castroflorio, E., Rossi, P. I. A., Fadda, M., Sterlini, B., Cervigni, R. I., Prestigio, C., Giovedı̀, S., Onofri, F., Mura, E., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.03.005 · Cited by 153 · see citing works
A Missense Mutation in KCTD17 Causes Autosomal Dominant Myoclonus-Dystonia
Mencacci, N. E., Rubio‐Agusti, I., Zdebik, A. A., Asmus, F., Ludtmann, M. H. R., Ryten, M., Plagnol, V., Hauser, A., Bandrés‐Ciga, S., Bettencourt, C., et al. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.04.008 · Cited by 147 · see citing works
“0 ST Arrays and brain and CNS tissue originating from 134 control individuals, collected by the Medical Research Council (MRC) Sudden Death Brain and Tissue Bank, and the Sun Health Research Institute (SHRI), an affiliate of Sun Health Corporation, USA.(27) The plot shows significant variation in KCTD17 transcript exp…”
MethodSelf-citationSalpietro, V., Malintan, N. T., Llano-Rivas, I., Spaeth, C. G., Efthymiou, S., Striano, P., Vandrovcova, J., Cutrupi, M. C., Chimenz, R., David, E., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.02.016 · Cited by 134 · see citing works
Hernandez, D. G., Nalls, M. A., Moore, M., Chong, S., Dillman, A., Trabzuni, D., Gibbs, J. R., Ryten, M., Arepalli, S., Weale, M. E., et al. (2012) · Neurobiology of Disease · doi:10.1016/j.nbd.2012.03.020 · Cited by 128 · see citing works
Self-citationSmeland, O. B., Frei, O., Kauppi, K., Hill, W. D., Li, W., Wang, Y., Krull, F., Bettella, F., Eriksen, J. A., Witoelar, A., et al. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.1986 · Cited by 133 · see citing works
Hall, J., Taylor, J., Valentine, H. R., Irlam, J. J., Eustace, A. J., Hoskin, P., Miller, C. J., & West, C. (2012) · British Journal of Cancer · doi:10.1038/bjc.2012.294 · Cited by 130 · see citing works
“Figure 1A shows that neither RNA yield nor RIN correlated with %DABG, which measures array performance (Linton et al, 2008; Trabzuni et al, 2011).”
BackgroundResultInfluentialErzurumluoglu, A. M., Liu, M., Jackson, V. E., Barnes, D. R., Datta, G., Melbourne, C., Young, R., Batini, C., Surendran, P., Jiang, T., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0313-0 · Cited by 122 · see citing works
De Novo Mutations in PDE10A Cause Childhood-Onset Chorea with Bilateral Striatal Lesions
Mencacci, N. E., Kamsteeg, E.-J., Nakashima, K., R’Bibo, L., Lynch, D. S., Balint, B., Willemsen, M. A. A. P., Adams, M. E., Wiethoff, S., Suzuki, K., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.02.015 · Cited by 120 · see citing works
“0 ST arrays and brain tissue originating from 134 control individuals, collected by the Medical Research Council Sudden Death Brain and Tissue Bank and the SunHealth Research Institute, an affiliate of SunHealth Corporation.(20) This plot shows significant variation in PDE10A expression across the ten brain regions an…”
MethodResultSelf-citationGenome-wide association study of cerebral small vessel disease reveals established and novel loci
Chung, J., Marini, S., Pera, J., Norrving, B., Jiménez-Conde, J., Roquer, J., Fernández‐Cadenas, I., Tirschwell, D., Selim, M. H., Brown, D. L., et al. (2019) · Brain · doi:10.1093/brain/awz233 · Cited by 115 · see citing works
“eQTL) using the GTEx Portal (Consortium, 2015) and the Brain eQTL Almanac (Braineac) (Trabzuni et al., 2011).”
Krishnan, M. L., Van Steenwinckel, J., Schang, A.-L., Yan, J., Arnadottir, J., Le Charpentier, T., Csaba, Z., Dournaud, P., Cipriani, S., Auvynet, C., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00422-w · Cited by 105 · see citing works
Truncating and Missense Mutations in IGHMBP2 Cause Charcot-Marie Tooth Disease Type 2
Cottenie, E., Kochański, A., Jordanova, A., Bánsági, B., Zimon, M., Horga, A., Jaunmuktane, Z., Saveri, P., Rašić, V. M., Baets, J., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.002 · Cited by 113 · see citing works
“The mRNA expression of IGHMBP2 in six brain regions was assessed in humans during development.(42) After birth,”
Sousa, S. B., Jenkins, D., Chanudet, E., Tasseva, G., Ishida, M., Anderson, G., Docker, J., Ryten, M., Sa, J., Saraiva, J. M., et al. (2014) · Nature Genetics · doi:10.1038/ng.2829 · Cited by 115 · see citing works
Self-citationA FreeSurfer view of the cortical transcriptome generated from the Allen Human Brain Atlas
French, L., & Paus, T. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00323 · Cited by 105 · see citing works
“To reduce the complexity of the Allen data, we have summarized the data into the Desikan– Killiany cortical atlas built into the FreeSurfer software for automatic labeling of regions of interest (Desikan et al., 2006).”
BackgroundMethodMutations in HPCA Cause Autosomal-Recessive Primary Isolated Dystonia
Charlesworth, G., Angelova, P. R., Bartolomé, F. B., Ryten, M., Trabzuni, D., Stamelou, M., Abramov, A. Y., Bhatia, K. P., & Wood, N. W. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2015.02.007 · Cited by 103 · see citing works
Self-citationThomas, A. C., Williams, H. J., Setó‐Salvia, N., Bacchelli, C., Jenkins, D., O’Sullivan, M. E., Mengrelis, K., Ishida, M., Ocaka, L., Chanudet, E., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.10.007 · Cited by 102 · see citing works
“This was supported by data from both the human UK Brain Expression Consortium (UKBEC) and the Human Brain Transcriptome database.(34,35) SNX14 is expressed in all brain regions, with generally increasing levels during prenatal development and then plateauing.”
MethodSelf-citationYin, H., Pantazatos, S. P., Galfalvy, H., Huang, Y., Rosoklija, G. B., Dwork, A. J., Burke, A., Arango, V., Oquendo, M. A., & Mann, J. J. (2016) · American Journal of Medical Genetics Part B: Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32423 · Cited by 91 · see citing works
ADCY5 mutations are another cause of benign hereditary chorea
Mencacci, N. E., Erro, R., Wiethoff, S., Hersheson, J., Ryten, M., Balint, B., Ganos, C., Stamelou, M., Quinn, N. P., Houlden, H., et al. (2015) · Neurology · doi:10.1212/wnl.0000000000001720 · Cited by 95 · see citing works
“Regional distribution of ADCY5 and NKX2-1 messenger RNA (mRNA) expression in the normal adult human brain was determined using microarray analysis of human postmortem brain tissue from the UK Human Brain Expression Consortium as previously described.(13) This dataset is based on exon array profiling of 1,231 samples f…”
MethodSelf-citationHypermethylation in the ZBTB20 gene is associated with major depressive disorder
Davies, M. N., Krause, L., Bell, J. T., Gao, F., Ward, K. J., Wu, H., Lu, H., Liu, Y., Tsai, P.-C., Collier, D. A., et al. (2014) · Genome biology · doi:10.1186/gb-2014-15-4-r56 · Cited by 96 · see citing works
“UK Brain Expression Consortium provided gene expression brain data.”
MethodInfluentialGenome-wide association study in essential tremor identifies three new loci
Müller, S. H., Girard, S. L., Hopfner, F., Merner, N. D., Bourassa, C. V., Lorenz, D., Clark, L. N., Tittmann, L., Soto-Ortolaza, A. I., Klebe, S., et al. (2016) · Brain · doi:10.1093/brain/aww242 · Cited by 88 · see citing works
“0008) in cerebellar cortex but not in other brain regions (Trabzuni et al., 2011) (Supplementary Fig.”
BackgroundInfluentialThe endocytic membrane trafficking pathway plays a major role in the risk of Parkinson's disease
Bandres‐Ciga, S., Saez‐Atienzar, S., Bonet‐Ponce, L., Billingsley, K., Vitale, D., Blauwendraat, C., Gibbs, J. R., Pihlstrøm, L., Gan‐Or, Z., The International Parkinson's Disease Genomics Consortium (IPDGC), et al. (2019) · Movement Disorders · doi:10.1002/mds.27614 · Cited by 90 · see citing works
Hancock, D. B., Reginsson, G. W., Gaddis, N. C., Chen, X., Saccone, N. L., Lutz, S. M., Qaiser, B., Sherva, R., Steinberg, S., Zink, F., et al. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.149 · Cited by 85 · see citing works
Huang, Y., Skwarek‐Maruszewska, A., Horré, K., Vandewyer, E., Wolfs, L., Snellinx, A., Saito, T., Radaelli, E., Corthout, N., Colombelli, J., et al. (2015) · Science Translational Medicine · doi:10.1126/scitranslmed.aab3492 · Cited by 90 · see citing works
Self-citationde Vargas, D. M., Bastiani, M. A. D., Zimmer, E. R., & Klamt, F. (2018) · Alzheimer s Research & Therapy · doi:10.1186/s13195-018-0394-7 · Cited by 88 · see citing works
“Table 1 Gene expression microarray data used to infer human hippocampus transcriptional network and AD MR candidates GEO ID Description Samples (n) Reference GSE60862 Gene expression data of 10 regions of postmortem brains originating from 134 neurologically and neuropathologically normal Caucasian individuals Hippoca…”
BackgroundMethodInfluentialTranscriptomic signatures of brain regional vulnerability to Parkinson’s disease
Keo, A., Mahfouz, A. E., Ingrassia, A. M. T., Meneboo, J., Villenet, C., Mutez, E., Comptdaer, T., Lelieveldt, B. P. F., Figeac, M., Chartier‐Harlin, M., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-0804-9 · Cited by 84 · see citing works
Parker, N., Patel, Y., Jackowski, A. P., Pan, P. M., Salum, G. A., Pausová, Z., & Paus, T. (2020) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2020.1495 · Cited by 81 · see citing works
White, K., Yang, P., Li, L., Farshori, A., Medina, A. E., & Zielke, H. R. (2018) · Biopreservation and Biobanking · doi:10.1089/bio.2017.0099 · Cited by 82 · see citing works
“As reported by others, shorter PMI values do not correlate with a high RIN value.(6,8,10,38) Indeed, neural tissue with a longer PMI may have high RIN values, indicating the overall tissue integrity even with longer death to freezing intervals.”
Ramasamy, A., Trabzuni, D., Gibbs, J. R., Dillman, A., Hernandez, D. G., Arepalli, S., WALKER, R. E., Smith, C., Ilori, G. P., Shabalin, A. A., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt069 · Cited by 77 · see citing works
“Briefly, the Illumina HT12 data set consists of 304 individuals profiled by the North American Brain Expression Consortium (NABEC) (15–17), whereas the Affymetrix Human Exon data set consists of 134 individuals profiled by the UK Brain Expression Consortium (UKBEC) (18).”
MethodInfluentialSelf-citationGhosh, A., Mizuno, K., Tiwari, S. S., Proitsi, P., Gomez Perez-Nievas, B., Glennon, E., Martinez-Nunez, R. T., & Giese, K. P. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00882-7 · Cited by 78 · see citing works
PRRT2: from Paroxysmal Disorders to Regulation of Synaptic Function
Valtorta, F., Benfenati, F., Zara, F., & Meldolesi, J. (2016) · Trends in Neurosciences · doi:10.1016/j.tins.2016.08.005 · Cited by 78 · see citing works
Pergola, G., Carlo, P. D., D’Ambrosio, E., Gelao, B., Fazio, L., Papalino, M., Monda, A., Scozia, G., Pietrangelo, B., Attrotto, M. T., et al. (2017) · Translational Psychiatry · doi:10.1038/tp.2016.253 · Cited by 75 · see citing works
Advances in protein-protein interaction network analysis for Parkinson's disease
Tomkins, J. E., & Manzoni, C. (2021) · Neurobiology of Disease · doi:10.1016/j.nbd.2021.105395 · Cited by 76 · see citing works
“…splicing analysis with a combination of Coloc and transcriptome-wide association study (TWAS) analyses applied to expression data from Braineac (Ramasamy et al., 2014; Trabzuni et al., 2011), the Genotype-Tissue Expression (GTEx) portal (GTEx Consortium, 2013), and CommonMind (Dobbyn et al., 2018).”
Age-associated changes in gene expression in human brain and isolated neurons
Kumar, A., Gibbs, J. R., Beilina, A. G., Dillman, A., Kumaran, R., Trabzuni, D., Ryten, M., WALKER, R. E., Smith, C., Traynor, B. J., et al. (2012) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2012.10.021 · Cited by 73 · see citing works
“These brain samples have previously been examined by microarrays [20,24], but on different platforms.”
BackgroundMethodInfluentialSelf-citationGenetic comorbidities in Parkinson's disease
Nalls, M. A., Saad, M., Noyce, A. J., Keller, M. F., Schrag, A. E., Bestwick, J., Traynor, B. J., Gibbs, J. R., Hernandez, D. G., Cookson, M., et al. (2013) · Human Molecular Genetics · doi:10.1093/hmg/ddt465 · Cited by 72 · see citing works
Self-citationUKBEC, Murthy, M. N., IPDGC, Blauwendraat, C., Guelfi, S., Hardy, J., Lewis, P. A., & Trabzuni, D. (2017) · Neurogenetics · doi:10.1007/s10048-017-0514-8 · Cited by 73 · see citing works
“12) using the Braineac microarray dataset [17]; a recent CAGEseq dataset [21]; GTEx Portal, which uses RNA sequence platform [22]; and NCBI’s Phenotype-Genotype Integrator (PheGenI) [6].”
Self-citationBrain expression of inflammatory mediators in Mesial Temporal Lobe Epilepsy patients.
Leal, B., Chaves, J., Carvalho, C., Rangel, R., Santos, A., Bettencourt, A., Lopes, J., Ramalheira, J., Silva, B., da Silva, A. D., et al. (2017) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2017.10.014 · Cited by 67 · see citing works
MIR-NATs repress MAPT translation and aid proteostasis in neurodegeneration
Simone, R., Javad, F., Emmett, W., Wilkins, O. G., Almeida, F., Barahona‐Torres, N., Zarȩba-Pasławska, J., Ehteramyan, M., Zuccotti, P., Modelska, A., et al. (2021) · Nature · doi:10.1038/s41586-021-03556-6 · Cited by 69 · see citing works
Self-citationPrediction of Alzheimer's disease using multi-variants from a Chinese genome-wide association study
Jia, L., Li, F., Wei, C., Zhu, M., Qu, Q., Qin, W., Tang, Y., Shen, L., Wang, Y., Shen, L., et al. (2021) · Brain · doi:10.1093/brain/awaa364 · Cited by 67 · see citing works
“…presented by Ramasamy et al. (2014), COLOC analysis (http:// coloc.cs.ucl.ac.uk) (Giambartolomei et al. , 2014) using the brain-eQTL datasets (Trabzuni et al. , 2011; Ramasamy et al. , 2013), and summary Mendelian randomization-Heidi analysis (https://cnsgenomics.com/software/smr/) (Zhu et…”
Periyasamy, S., John, S., Padmavati, R., Rajendren, P., Thirunavukkarasu, P., Gratten, J., Vinkhuyzen, A. A. E., McRae, A. F., Holliday, E. G., Nyholt, D. R., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.1335 · Cited by 65 · see citing works
Microglia recapitulate a hematopoietic master regulator network in the aging human frontal cortex
Wehrspaun, C. C., Haerty, W., & Ponting, C. P. (2015) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2015.04.008 · Cited by 64 · see citing works
Transcriptomic and genetic analyses reveal potential causal drivers for intractable partial epilepsy
Guelfi, S., Botía, J. A., Thom, M., Ramasamy, A., Perona, M., Stanyer, L., Martinian, L., Trabzuni, D., Smith, C., WALKER, R. E., et al. (2019) · Brain · doi:10.1093/brain/awz074 · Cited by 60 · see citing works
Self-citationAssociation of a Schizophrenia-Risk Nonsynonymous Variant With Putamen Volume in Adolescents
Luo, Q., Chen, Q., Wang, W., Desrivières, S., Quinlan, E. B., Jia, T., Macare, C., Robert, G. H., Cui, J., Guedj, M., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2018.4126 · Cited by 62 · see citing works
The Spectrum of PRRT2-Associated Disorders: Update on Clinical Features and Pathophysiology
Landolfi, A., Barone, P., & Erro, R. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.629747 · Cited by 58 · see citing works
“The observed dissociation in terms of age at onset between the epilepsy and PKD phenotypes might in fact suggest an expression pattern shift across different brain regions during development (57).”
BackgroundFerrari, R., Forabosco, P., Vandrovcová, J., Botía, J. A., Guelfi, S., Warren, J. D., Momeni, P., Weale, M. E., Ryten, M., & Hardy, J. (2016) · Molecular Neurodegeneration · doi:10.1186/s13024-016-0085-4 · Cited by 58 · see citing works
“We assessed expression for FTD-genes in different brain areas by means of the Human Brain Atlas (HBA; [46]) and Braineac [47, 48].”
BackgroundMethodInfluentialSelf-citationInsights From Cerebellar Transcriptomic Analysis Into the Pathogenesis of Ataxia
Bettencourt, C., Ryten, M., Forabosco, P., Schorge, S., Hersheson, J., Hardy, J., & Houlden, H. (2014) · JAMA Neurology · doi:10.1001/jamaneurol.2014.756 · Cited by 56 · see citing works
Self-citationMok, K. Y., Schneider, S. A., Trabzuni, D., Stamelou, M., Edwards, M. J., Kasperavičiūtė, D., Pickering-Brown, S. M., Silverdale, M., Hardy, J., & Bhatia, K. P. (2013) · Movement Disorders · doi:10.1002/mds.25732 · Cited by 56 · see citing works
Self-citationThomas, R. S., Henson, A., Gerrish, A., Jones, L., Williams, J., & Kidd, E. J. (2016) · BMC Neuroscience · doi:10.1186/s12868-016-0288-1 · Cited by 55 · see citing works
“[31] eQTL dataset (150 healthy brains) and the UK Brain Expression Consortium eQTL dataset [32] (134 healthy brains) we found that the risk (major, G) allele of the most significant SNP in PICALM rs3851179 [2], and the risk allele (major, G) of the most significant SNP in PICALM from IGAP rs10792832 [4], are both asso…”
BackgroundMethodMarshe, V. S., Maciukiewicz, M., Rej, S., Tiwari, A. K., Sibille, E. L., Blumberger, D. M., Karp, J. F., Lenze, E. J., Reynolds, C. F., Kennedy, J. L., et al. (2017) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.16050617 · Cited by 54 · see citing works
Bampton, A., Gatt, A. P., Humphrey, J., Cappelli, S., Bhattacharya, D., Foti, S. C., Brown, A., Asi, Y. T., Low, Y. H., Foiani, M., et al. (2021) · Acta Neuropathologica · doi:10.1007/s00401-021-02340-0 · Cited by 52 · see citing works
“HnRNP K is widely expressed in multiple brain regions [63, 64] and has been specifically implicated in the post-transcriptional regulation of genes essential for maintaining ATP levels during cellular stress [22], axogenesis [41], myelination [37] and synaptic plasticity [19].”
BackgroundRare variants in SQSTM1 and VCP genes and risk of sporadic inclusion body myositis
Gang, Q., Bettencourt, C., Machado, P. M., Brady, S., Holton, J. L., Pittman, A. M., Hughes, D., Healy, E., Parton, M., Hilton-Jones, D., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.07.024 · Cited by 51 · see citing works
“Total RNA was isolated from muscle tissue using the miRNeasy kit (Qiagen, Crawley, UK), and the concentration, purity, and integrity of each RNA sample were assessed as previously described (Trabzuni et al., 2011).”
MethodLorenzi, M., Altmann, A., Gutman, B. A., Wray, S., Arber, C., Hibar, D. P., Jahanshad, N., Schott, J. M., Alexander, D. C., Thompson, P. M., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1706100115 · Cited by 51 · see citing works
“org/) (19), facilitate the quantification of effects of SNPs on gene expression in numerous tissues, including various brain tissues.”
BackgroundPatani, R., Lewis, P. A., Trabzuni, D., Puddifoot, C. A., Wyllie, D. J. A., WALKER, R. E., Smith, C., Hardingham, G. E., Weale, M. E., Hardy, J., et al. (2012) · Journal of Neurochemistry · doi:10.1111/j.1471-4159.2012.07825.x · Cited by 52 · see citing works
Self-citationFine-Mapping, Gene Expression and Splicing Analysis of the Disease Associated LRRK2 Locus
Trabzuni, D., Ryten, M., Emmett, W., Ramasamy, A., Lackner, K. J., Zeller, T., WALKER, R. E., Smith, C., Lewis, P. A., Mamais, A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0070724 · Cited by 50 · see citing works
“Further details regarding sample processing for this section are reported in Trabzuni et al., 2011 [22].”
BackgroundMethodResultInfluentialSelf-citationRamasamy, A., Trabzuni, D., Forabosco, P., Smith, C., WALKER, R. E., Dillman, A., Sveinbjörnsdóttir, S., Hardy, J., Weale, M. E., & Ryten, M. (2013) · Multiple Sclerosis and Related Disorders · doi:10.1016/j.msard.2013.08.009 · Cited by 50 · see citing works
“Prior to use in eQTL analyses, the expression data was corrected for gender and batch effects (date of hybridization and brain bank or collection sites), as described previously (Trabzuni et al., 2011).”
InfluentialSelf-citationNovel C12orf65 mutations in patients with axonal neuropathy and optic atrophy
Tucci, A., Liu, Y., Preza, E., Pitceathly, R. D. S., Chalasani, A., Plagnol, V., Land, J. M., Trabzuni, D., Ryten, M., UKBEC, O. B. O., et al. (2013) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2013-306387 · Cited by 49 · see citing works
“12 A full description of the samples used and the methods of RNA isolation and processing can be found in Trabzuni et al , 13 and Trabzuni et al .”
MethodSelf-citationFerrari, R., Ryten, M., Simone, R., Trabzuni, D., Nicolaou, N., Hondhamuni, G., Ramasamy, A., Vandrovcová, J., Weale, M. E., Lees, A. J., et al. (2014) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2014.01.010 · Cited by 44 · see citing works
“Further details regarding RNA isolation, quality control, and processing are reported in (Trabzuni et al., 2011).”
Self-citationWang, X., Campbell, M. R., Lacher, S. E., Cho, H.-Y., Wan, M., Crowl, C. L., Chorley, B. N., Bond, G. L., Kleeberger, S. R., Slattery, M., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.03.068 · Cited by 49 · see citing works
“Association of SNP genotype and MAPT expression The MAPT gene expression and SNP genotyping data were downloaded from the UK Brain Expression Consortium (UKBEC, http://www.braineac.org) (Ramasamy et al., 2014; Trabzuni et al., 2011).”
MethodPhysiological and Pathological Ageing of Astrocytes in the Human Brain
Verkerke, M., Hol, E. M., & Middeldorp, J. (2021) · Neurochemical Research · doi:10.1007/s11064-021-03256-7 · Cited by 49 · see citing works
Alterations in cholesterol metabolism–related genes in sporadic Alzheimer's disease
Picard, C., Julien, C., Frappier, J., Miron, J., Théroux, L., Dea, D., Breitner, J. C. S., & Poirier, J. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.01.018 · Cited by 60 · see citing works
Limited predictability of postmortem human brain tissue quality by RNA integrity numbers
Sonntag, K., Tejada, G., Subburaju, S., Berretta, S., Benes, F. M., & Woo, T.-U. W. (2016) · Journal of Neurochemistry · doi:10.1111/jnc.13637 · Cited by 48 · see citing works
“A number of studies, including our own, have shown that good-quality RNA can be derived from postmortem human brain tissue and that samples with varying RINs can successfully be assessed using biochemical and molecular assays, such as microarrays, qPCR, or RNA-Seq (Gilbert et al. 1981; Sajdel-Sulkowska et al. 1988; Be…”
BackgroundMethodResultInfluentialMolecular mechanisms underlying noncoding risk variations in psychiatric genetic studies
Xiao, X., Chang, H., & Li, M. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.241 · Cited by 47 · see citing works
Lyu, Y., Zauhar, R. J., Dana, N., Strang, C. E., Hu, J., Wang, K., Liu, S., Pan, N., Gamlin, P. D., Kimble, J. A., et al. (2021) · Scientific Reports · doi:10.1038/s41598-021-95122-3 · Cited by 47 · see citing works
Gene expression in the Parkinson's disease brain
Lewis, P. A., & Cookson, M. (2011) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2011.11.016 · Cited by 45 · see citing works
Wingo, A. P., Almli, L. M., Stevens, J. S., Jovanović, T., Wingo, T. S., Tharp, G. K., Li, Y., Lori, A., Briscione, M. A., Jin, P., et al. (2016) · Molecular Psychiatry · doi:10.1038/mp.2016.143 · Cited by 43 · see citing works
“Affymetrix GeneChip Human Exon 1.0 ST arrays were used to obtain whole transcriptome profiling 20 .”
InfluentialLongevity‐related molecular pathways are subject to midlife “switch” in humans
Timmons, J. A., Volmar, C., Crossland, H., Phillips, B. E., Sood, S., Janczura, K. J., Törmäkangas, T., Kujala, U. M., Kraus, W. E., Atherton, P. J., et al. (2019) · Aging Cell · doi:10.1111/acel.12970 · Cited by 43 · see citing works
“For human brain, the only sufficiently sized older age‐range exon‐based dataset was from Hardy and colleagues (Trabzuni et al., 2011).”
BackgroundStudy, T. C. F. A. A., Bury, J. J., Chambers, A., Heath, P. R., Ince, P. G., Shaw, P. J., Matthews, F. E., Brayne, C., Simpson, J. E., & Wharton, S. B. (2021) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-01109-y · Cited by 43 · see citing works
Multi-omic insights into Parkinson's Disease: From genetic associations to functional mechanisms
Schilder, B. M., Navarro, E., & Raj, T. (2021) · Neurobiology of Disease · doi:10.1016/j.nbd.2021.105580 · Cited by 42 · see citing works
Initial Assessment of the Pathogenic Mechanisms of the Recently Identified Alzheimer Risk Loci
Holton, P., Ryten, M., Nalls, M., Trabzuni, D., Weale, M. E., Hernandez, D., Crehan, H., Gibbs, J. R., Mayeux, R., Haines, J. L., et al. (2013) · Annals of Human Genetics · doi:10.1111/ahg.12000 · Cited by 48 · see citing works
“Human post-mortem brain tissue collection and mRNA extraction A detailed description of the samples used in the study, tissue processing and dissection is provided in Trabzuni et al. (2011).”
Self-citationPergola, G., Carlo, P. D., Jaffe, A. E., Papalino, M., Chen, Q., Hyde, T. M., Kleinman, J. E., Shin, J. H., Rampino, A., Blasi, G., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.03.981 · Cited by 36 · see citing works
- Authors
- Trabzuni, D., Ryten, M., Walker, R., Smith, C., Imran, S., Ramasamy, A., Weale, M. E., & Hardy, J.
- Affiliations
- UCL Queen Square Institute of Neurology (GB)
- University of Edinburgh (GB)
- Guy's Hospital (GB)
- Corresponding author
- Hardy, John
- ORCID
- Venue
- Journal of Neurochemistry
- Publisher
- Wiley
- Published
- 2011-09-20
- Volume
- 119
- Issue
- 2
- Pages
- 275-282
- ISSN
- 0022-3042 (ISSN-L)
- 1471-4159
- PMC
- PMC3664422
- OpenAlex
- W2066399252
- Cited by
- 229
- References
- 36
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 4 · 2023: 10 · 2022: 10 · 2021: 22 · 2020: 13 · 2019: 24 · 2018: 23 · 2017: 25 · 2016: 24 · 2015: 20 · 2014: 16 · 2013: 14 · 2012: 9
- FWCI
- 5.45
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Neurochemistry (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Research Portal (King's College London) (publishedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Funders
- Wellcome Trust (089698)
- King Faisal Specialist Hospital and Research Centre
- Medical Research Council (MC_G1000735)
- Army Research Office
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Keywords
- postmortem delay, agonal state, brain age, RNA integrity number, brain pH
- MeSH terms
- Adolescent, Adult, Aged, Aging, Brain Chemistry, Cause of Death, Exons, Female, United Kingdom, Humans, Hydrogen-Ion Concentration, Male, Middle Aged, Quality Control, RNA, Sex Characteristics, Tissue Banks, United States, Reproducibility of Results, DNA, Complementary, Reverse Transcriptase Polymerase Chain Reaction, Oligonucleotide Array Sequence Analysis, Gene Expression Profiling, Databases, Genetic, Microarray Analysis, Young Adult
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