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4 results on '"Finan C"'

1. Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome

Author

Storm, CS, Kia, DA, Almramhi, MM, Bandres-Ciga, S, Finan, C, Hingorani, AD, Wood, NW, Clarimón, J., Dols-Icardo O., Kulisevsky J., Marín J., Pagonabarraga J., and Lynch, Timothy L.

Abstract

There is currently no disease-modifying treatment for Parkinson's disease, a common neurodegenerative disorder. Here, the authors use genetic variation associated with gene and protein expression to find putative drug targets for Parkinson's disease using Mendelian randomization of the druggable genome. Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.

Published
2021

2. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes

Author

Franceschini, N, Giambartolomei, C, de Vries, PS, Finan, C, Bis, JC, Huntley, RP, Lovering, RC, Tajuddin, SM, Winkler, TW, Graff, M, Kavousi, M, Dale, C, Smith, AV, Hofer, E, van Leeuwen, EM, Nolte, IM, Lu, L, Scholz, M, Sargurupremraj, M, Pitkanen, N, Franzen, O, Joshi, PK, Noordam, R, Marioni, RE, Hwang, S-J, Musani, SK, Schminke, U, Palmas, W, Isaacs, A, Correa, A, Zonderman, AB, Hofman, A, Teumer, A, Cox, AJ, Uitterlinden, AG, Wong, A, Smit, AJ, Newman, AB, Britton, A, Ruusalepp, A, Sennblad, B, Hedblad, B, Pasaniuc, B, Penninx, BW, Langefeld, CD, Wassel, CL, Tzourio, C, Fava, C, Baldassarre, D, O'Leary, DH, Teupser, D, Kuh, D, Tremoli, E, Mannarino, E, Grossi, E, Boerwinkle, E, Schadt, EE, Ingelsson, E, Veglia, F, Rivadeneira, F, Beutner, F, Chauhan, G, Heiss, G, Snieder, H, Campbell, H, Voelzke, H, Markus, HS, Deary, IJ, Jukema, JW, de Graaf, J, Price, J, Pott, J, Hopewell, JC, Liang, J, Thiery, J, Engmann, J, Gertow, K, Rice, K, Taylor, KD, Dhana, K, Kiemeney, LALM, Lind, L, Raffield, LM, Launer, LJ, Holdt, LM, Doer, M, Dichgans, M, Traylor, M, Sitzer, M, Kumari, M, Kivimaki, M, Nalls, MA, Melander, O, Raitakari, O, Franco, OH, Rueda-Ochoa, OL, Roussos, P, Whincup, PH, Amouyel, P, Giral, P, Anugu, P, Wong, Q, Malik, R, Rauramaa, R, Burkhardt, R, Hardy, R, Schmidt, R, de Mutsert, R, Morris, RW, Strawbridge, RJ, Wannamethee, SG, Hagg, S, Shah, S, McLachlan, S, Trompet, S, Seshadri, S, Kurl, S, Heckbert, SR, Ring, S, Harris, TB, Lehtimaki, T, Galesloot, TE, Shah, T, de Faire, U, Plagnol, V, Rosamond, WD, Post, W, Zhu, X, Zhang, X, Guo, X, Saba, Y, Dehghan, A, Seldenrijk, A, Morrison, AC, Hamsten, A, Psaty, BM, van Duijn, CM, Lawlor, DA, Mook-Kanamori, DO, Bowden, DW, Schmidt, H, Wilson, JF, Wilson, JG, Rotter, JI, Wardlaw, JM, Deanfield, J, Halcox, J, Lyytikainen, L-P, Loeffler, M, Evans, MK, Debette, S, Humphries, SE, Voelker, U, Gudnason, V, Hingorani, AD, Bjorkegren, JLM, Casas, JP, O'Donnell, CJ, Franceschini, N, Giambartolomei, C, de Vries, PS, Finan, C, Bis, JC, Huntley, RP, Lovering, RC, Tajuddin, SM, Winkler, TW, Graff, M, Kavousi, M, Dale, C, Smith, AV, Hofer, E, van Leeuwen, EM, Nolte, IM, Lu, L, Scholz, M, Sargurupremraj, M, Pitkanen, N, Franzen, O, Joshi, PK, Noordam, R, Marioni, RE, Hwang, S-J, Musani, SK, Schminke, U, Palmas, W, Isaacs, A, Correa, A, Zonderman, AB, Hofman, A, Teumer, A, Cox, AJ, Uitterlinden, AG, Wong, A, Smit, AJ, Newman, AB, Britton, A, Ruusalepp, A, Sennblad, B, Hedblad, B, Pasaniuc, B, Penninx, BW, Langefeld, CD, Wassel, CL, Tzourio, C, Fava, C, Baldassarre, D, O'Leary, DH, Teupser, D, Kuh, D, Tremoli, E, Mannarino, E, Grossi, E, Boerwinkle, E, Schadt, EE, Ingelsson, E, Veglia, F, Rivadeneira, F, Beutner, F, Chauhan, G, Heiss, G, Snieder, H, Campbell, H, Voelzke, H, Markus, HS, Deary, IJ, Jukema, JW, de Graaf, J, Price, J, Pott, J, Hopewell, JC, Liang, J, Thiery, J, Engmann, J, Gertow, K, Rice, K, Taylor, KD, Dhana, K, Kiemeney, LALM, Lind, L, Raffield, LM, Launer, LJ, Holdt, LM, Doer, M, Dichgans, M, Traylor, M, Sitzer, M, Kumari, M, Kivimaki, M, Nalls, MA, Melander, O, Raitakari, O, Franco, OH, Rueda-Ochoa, OL, Roussos, P, Whincup, PH, Amouyel, P, Giral, P, Anugu, P, Wong, Q, Malik, R, Rauramaa, R, Burkhardt, R, Hardy, R, Schmidt, R, de Mutsert, R, Morris, RW, Strawbridge, RJ, Wannamethee, SG, Hagg, S, Shah, S, McLachlan, S, Trompet, S, Seshadri, S, Kurl, S, Heckbert, SR, Ring, S, Harris, TB, Lehtimaki, T, Galesloot, TE, Shah, T, de Faire, U, Plagnol, V, Rosamond, WD, Post, W, Zhu, X, Zhang, X, Guo, X, Saba, Y, Dehghan, A, Seldenrijk, A, Morrison, AC, Hamsten, A, Psaty, BM, van Duijn, CM, Lawlor, DA, Mook-Kanamori, DO, Bowden, DW, Schmidt, H, Wilson, JF, Wilson, JG, Rotter, JI, Wardlaw, JM, Deanfield, J, Halcox, J, Lyytikainen, L-P, Loeffler, M, Evans, MK, Debette, S, Humphries, SE, Voelker, U, Gudnason, V, Hingorani, AD, Bjorkegren, JLM, Casas, JP, and O'Donnell, CJ

Abstract

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Published
2018

3. Replication of HLA class II locus association with susceptibility to podoconiosis in three Ethiopian ethnic groups.

Author

Gebresilase T, Finan C, Suveges D, Tessema TS, Aseffa A, Davey G, Hatzikotoulas K, Zeggini E, Newport MJ, and Tekola-Ayele F

Subjects
Ethiopia ethnology, Female, Genome-Wide Association Study, Humans, Male, Elephantiasis ethnology, Elephantiasis genetics, Ethnicity genetics, Genetic Predisposition to Disease ethnology, HLA-DRB1 Chains genetics, Polymorphism, Single Nucleotide
Abstract

Podoconiosis, a debilitating lymphoedema of the leg, results from barefoot exposure to volcanic clay soil in genetically susceptible individuals. A previous genome-wide association study (GWAS) conducted in the Wolaita ethnic group from Ethiopia showed association between single nucleotide polymorphisms (SNPs) in the HLA class II region and podoconiosis. We aimed to conduct a second GWAS in a new sample (N = 1892) collected from the Wolaita and two other Ethiopian populations, the Amhara and the Oromo, also affected by podoconiosis. Fourteen SNPs in the HLA class II region showed significant genome-wide association (P < 5.0 × 10 -8 ) with podoconiosis. The lead SNP was rs9270911 (P = 5.51 × 10 -10 ; OR 1.53; 95% CI 1.34-1.74), located near HLA-DRB1. Inclusion of data from the first GWAS (combined N = 2289) identified 47 SNPs in the class II HLA region that were significantly associated with podoconiosis (lead SNP also rs9270911 (P = 2.25 × 10 -12 ). No new loci outside of the HLA class II region were identified in this more highly-powered second GWAS. Our findings confirm the HLA class II association with podoconiosis suggesting HLA-mediated abnormal induction and regulation of immune responses may have a direct role in its pathogenesis.

Published
2021
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4. Improving the odds of drug development success through human genomics: modelling study.

Author

Hingorani AD, Kuan V, Finan C, Kruger FA, Gaulton A, Chopade S, Sofat R, MacAllister RJ, Overington JP, Hemingway H, Denaxas S, Prieto D, and Casas JP

Subjects
Genome-Wide Association Study, Humans, Drug Development, Genomics
Abstract

Lack of efficacy in the intended disease indication is the major cause of clinical phase drug development failure. Explanations could include the poor external validity of pre-clinical (cell, tissue, and animal) models of human disease and the high false discovery rate (FDR) in preclinical science. FDR is related to the proportion of true relationships available for discovery (γ), and the type 1 (false-positive) and type 2 (false negative) error rates of the experiments designed to uncover them. We estimated the FDR in preclinical science, its effect on drug development success rates, and improvements expected from use of human genomics rather than preclinical studies as the primary source of evidence for drug target identification. Calculations were based on a sample space defined by all human diseases - the 'disease-ome' - represented as columns; and all protein coding genes - 'the protein-coding genome'- represented as rows, producing a matrix of unique gene- (or protein-) disease pairings. We parameterised the space based on 10,000 diseases, 20,000 protein-coding genes, 100 causal genes per disease and 4000 genes encoding druggable targets, examining the effect of varying the parameters and a range of underlying assumptions, on the inferences drawn. We estimated γ, defined mathematical relationships between preclinical FDR and drug development success rates, and estimated improvements in success rates based on human genomics (rather than orthodox preclinical studies). Around one in every 200 protein-disease pairings was estimated to be causal (γ = 0.005) giving an FDR in preclinical research of 92.6%, which likely makes a major contribution to the reported drug development failure rate of 96%. Observed success rate was only slightly greater than expected for a random pick from the sample space. Values for γ back-calculated from reported preclinical and clinical drug development success rates were also close to the a priori estimates. Substituting genome wide (or druggable genome wide) association studies for preclinical studies as the major information source for drug target identification was estimated to reverse the probability of late stage failure because of the more stringent type 1 error rate employed and the ability to interrogate every potential druggable target in the same experiment. Genetic studies conducted at much larger scale, with greater resolution of disease end-points, e.g. by connecting genomics and electronic health record data within healthcare systems has the potential to produce radical improvement in drug development success rate.

Published
2019
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