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1. Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Author

Nalls, Mike A, Blauwendraat, Cornelis, Vallerga, Costanza L, Heilbron, Karl, Bandres-Ciga, Sara, Chang, Diana, Tan, Manuela, Kia, Demis A, Noyce, Alastair J, Xue, Angli, Bras, Jose, Young, Emily, von Coelln, Rainer, Simón-Sánchez, Javier, Schulte, Claudia, Sharma, Manu, Krohn, Lynne, Pihlstrøm, Lasse, Siitonen, Ari, Iwaki, Hirotaka, Leonard, Hampton, Faghri, Faraz, Gibbs, J Raphael, Hernandez, Dena G, Scholz, Sonja W, Botia, Juan A, Martinez, Maria, Corvol, Jean-Christophe, Lesage, Suzanne, Jankovic, Joseph, Shulman, Lisa M, Sutherland, Margaret, Tienari, Pentti, Majamaa, Kari, Toft, Mathias, Andreassen, Ole A, Bangale, Tushar, Brice, Alexis, Yang, Jian, Gan-Or, Ziv, Gasser, Thomas, Heutink, Peter, Shulman, Joshua M, Wood, Nicholas W, Hinds, David A, Hardy, John A, Morris, Huw R, Gratten, Jacob, Visscher, Peter M, Graham, Robert R, Singleton, Andrew B, Team, 23andMe Research, Consortium, System Genomics of Parkinson's Disease, Consortium, International Parkinson's Disease Genomics, Adarmes-Gómez, Astrid D, Aguilar, Miquel, Aitkulova, Akbota, Akhmetzhanov, Vadim, Alcalay, Roy N, Alvarez, Ignacio, Alvarez, Victoria, Barrero, Francisco Javier, Yarza, Jesús Alberto Bergareche, Bernal-Bernal, Inmaculada, Billingsley, Kimberley, Blazquez, Marta, Bonilla-Toribio, Marta, Botía, Juan A, Boungiorno, María Teresa, Brockmann, Kathrin, Bubb, Vivien, Buiza-Rueda, Dolores, Cámara, Ana, Carrillo, Fátima, Carrión-Claro, Mario, Cerdan, Debora, Chelban, Viorica, Clarimón, Jordi, Clarke, Carl, Compta, Yaroslau, Cookson, Mark R, Craig, David W, Danjou, Fabrice, Diez-Fairen, Monica, Dols-Icardo, Oriol, Duarte, Jacinto, Duran, Raquel, Escamilla-Sevilla, Francisco, Escott-Price, Valentina, Ezquerra, Mario, Feliz, Cici, Fernández, Manel, Fernández-Santiago, Rubén, and Finkbeiner, Steven

Subjects
Neurosciences, Parkinson's Disease, Brain Disorders, Aging, Biotechnology, Prevention, Genetics, Human Genome, Neurodegenerative, 2.1 Biological and endogenous factors, Aetiology, Neurological, Databases, Genetic, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Parkinson Disease, Risk Factors, 23andMe Research Team, System Genomics of Parkinson's Disease Consortium, International Parkinson's Disease Genomics Consortium, Clinical Sciences, Neurology & Neurosurgery
Abstract

BackgroundGenome-wide association studies (GWAS) in Parkinson's disease have increased the scope of biological knowledge about the disease over the past decade. We aimed to use the largest aggregate of GWAS data to identify novel risk loci and gain further insight into the causes of Parkinson's disease.MethodsWe did a meta-analysis of 17 datasets from Parkinson's disease GWAS available from European ancestry samples to nominate novel loci for disease risk. These datasets incorporated all available data. We then used these data to estimate heritable risk and develop predictive models of this heritability. We also used large gene expression and methylation resources to examine possible functional consequences as well as tissue, cell type, and biological pathway enrichments for the identified risk factors. Additionally, we examined shared genetic risk between Parkinson's disease and other phenotypes of interest via genetic correlations followed by Mendelian randomisation.FindingsBetween Oct 1, 2017, and Aug 9, 2018, we analysed 7·8 million single nucleotide polymorphisms in 37 688 cases, 18 618 UK Biobank proxy-cases (ie, individuals who do not have Parkinson's disease but have a first degree relative that does), and 1·4 million controls. We identified 90 independent genome-wide significant risk signals across 78 genomic regions, including 38 novel independent risk signals in 37 loci. These 90 variants explained 16-36% of the heritable risk of Parkinson's disease depending on prevalence. Integrating methylation and expression data within a Mendelian randomisation framework identified putatively associated genes at 70 risk signals underlying GWAS loci for follow-up functional studies. Tissue-specific expression enrichment analyses suggested Parkinson's disease loci were heavily brain-enriched, with specific neuronal cell types being implicated from single cell data. We found significant genetic correlations with brain volumes (false discovery rate-adjusted p=0·0035 for intracranial volume, p=0·024 for putamen volume), smoking status (p=0·024), and educational attainment (p=0·038). Mendelian randomisation between cognitive performance and Parkinson's disease risk showed a robust association (p=8·00 × 10-7).InterpretationThese data provide the most comprehensive survey of genetic risk within Parkinson's disease to date, to the best of our knowledge, by revealing many additional Parkinson's disease risk loci, providing a biological context for these risk factors, and showing that a considerable genetic component of this disease remains unidentified. These associations derived from European ancestry datasets will need to be followed-up with more diverse data.FundingThe National Institute on Aging at the National Institutes of Health (USA), The Michael J Fox Foundation, and The Parkinson's Foundation (see appendix for full list of funding sources).

Published
2019

2. Identification of novel risk loci, causal insights, and heritable risk for Parkinson's disease: a meta-analysis of genome-wide association studies

Author

Adarmes-Gómez, Astrid D, Aguilar, Miquel, Aitkulova, Akbota, Akhmetzhanov, Vadim, Alcalay, Roy N, Alvarez, Ignacio, Alvarez, Victoria, Bandres-Ciga, Sara, Barrero, Francisco Javier, Bergareche Yarza, Jesús Alberto, Bernal-Bernal, Inmaculada, Billingsley, Kimberley, Blauwendraat, Cornelis, Blazquez, Marta, Bonilla-Toribio, Marta, Botía, Juan A, Boungiorno, María Teresa, Bras, Jose, Brice, Alexis, Brockmann, Kathrin, Bubb, Vivien, Buiza-Rueda, Dolores, Cámara, Ana, Carrillo, Fátima, Carrión-Claro, Mario, Cerdan, Debora, Chelban, Viorica, Clarimón, Jordi, Clarke, Carl, Compta, Yaroslau, Cookson, Mark R, Corvol, Jean-Christophe, Craig, David W, Danjou, Fabrice, Diez-Fairen, Monica, Dols-Icardo, Oriol, Duarte, Jacinto, Duran, Raquel, Escamilla-Sevilla, Francisco, Escott-Price, Valentina, Ezquerra, Mario, Faghri, Faraz, Feliz, Cici, Fernández, Manel, Fernández-Santiago, Rubén, Finkbeiner, Steven, Foltynie, Thomas, Gan-Or, Ziv, Garcia, Ciara, García-Ruiz, Pedro, Gasser, Thomas, Gibbs, J Raphael, Gomez Heredia, Maria Jose, Gómez-Garre, Pilar, González, Manuel Menéndez, Gonzalez-Aramburu, Isabel, Guelfi, Sebastian, Guerreiro, Rita, Hardy, John, Hassin-Baer, Sharon, Hernandez, Dena G, Heutink, Peter, Hoenicka, Janet, Holmans, Peter, Houlden, Henry, Infante, Jon, Iwaki, Hirotaka, Jesús, Silvia, Jimenez-Escrig, Adriano, Kaishybayeva, Gulnaz, Kaiyrzhanov, Rauan, Karimova, Altynay, Kia, Demis A, Kinghorn, Kerri J, Koks, Sulev, Krohn, Lynne, Kulisevsky, Jaime, Labrador-Espinosa, Miguel A, Leonard, Hampton L, Lesage, Suzanne, Lewis, Patrick, Lopez-Sendon, Jose Luis, Lovering, Ruth, Lubbe, Steven, Lungu, Codrin, Macias, Daniel, Majamaa, Kari, Manzoni, Claudia, Marín, Juan, Marinus, Johan, Marti, Maria Jose, Martinez, Maria, Martínez Torres, Irene, Martínez-Castrillo, Juan Carlos, Mata, Marina, Mencacci, Niccolo E, Méndez-del-Barrio, Carlota, Middlehurst, Ben, Mínguez, Adolfo, Mir, Pablo, Mok, Kin Y, Morris, Huw R, Muñoz, Esteban, Nalls, Mike A, Narendra, Derek, Noyce, Alastair J, Ojo, Oluwadamilola O, Okubadejo, Njideka U, Pagola, Ana Gorostidi, Pastor, Pau, Perez Errazquin, Francisco, Periñán-Tocino, Teresa, Pihlstrom, Lasse, Plun-Favreau, Helene, Quinn, John, R'Bibo, Lea, Reed, Xylena, Rezola, Elisabet Mondragon, Rizig, Mie, Rizzu, Patrizia, Robak, Laurie, Rodriguez, Antonio Sanchez, Rouleau, Guy A, Ruiz-Martínez, Javier, Ruz, Clara, Ryten, Mina, Sadykova, Dinara, Scholz, Sonja W, Schreglmann, Sebastian, Schulte, Claudia, Sharma, Manu, Shashkin, Chingiz, Shulman, Joshua M, Sierra, María, Siitonen, Ari, Simón-Sánchez, Javier, Singleton, Andrew B, Suarez-Sanmartin, Esther, Taba, Pille, Tabernero, Cesar, Tan, Manuela X, Tartari, Juan Pablo, Tejera-Parrado, Cristina, Toft, Mathias, Tolosa, Eduard, Trabzuni, Daniah, Valldeoriola, Francesc, van Hilten, Jacobus J, Van Keuren-Jensen, Kendall, Vargas-González, Laura, Vela, Lydia, Vives, Francisco, Williams, Nigel, Wood, Nicholas W, Zharkinbekova, Nazira, Zharmukhanov, Zharkyn, Zholdybayeva, Elena, Zimprich, Alexander, Ylikotila, Pauli, Shulman, Lisa M., von Coelln, Rainer, Reich, Stephen, Savitt, Joseph, Agee, Michelle, Alipanahi, Babak, Auton, Adam, Bell, Robert K., Bryc, Katarzyna, Elson, Sarah L., Fontanillas, Pierre, Furlotte, Nicholas A., Huber, Karen E., Hicks, Barry, Jewett, Ethan M., Jiang, Yunxuan, Kleinman, Aaron, Lin, Keng-Han, Litterman, Nadia K., McCreight, Jennifer C., McIntyre, Matthew H., McManus, Kimberly F., Mountain, Joanna L., Noblin, Elizabeth S., Northover, Carrie A.M., Pitts, Steven J., Poznik, G. David, Sathirapongsasuti, J. Fah, Shelton, Janie F., Shringarpure, Suyash, Tian, Chao, Tung, Joyce, Vacic, Vladimir, Wang, Xin, Wilson, Catherine H., Anderson, Tim, Bentley, Steven, Dalrymple-Alford, John, Fowdar, Javed, Gratten, Jacob, Halliday, Glenda, Henders, Anjali K., Hickie, Ian, Kassam, Irfahan, Kennedy, Martin, Kwok, John, Lewis, Simon, Mellick, George, Montgomery, Grant, Pearson, John, Pitcher, Toni, Sidorenko, Julia, Silburn, Peter A., Vallerga, Costanza L., Visscher, Peter M., Wallace, Leanne, Wray, Naomi R., Xue, Angli, Yang, Jian, Zhang, Futao, Vallerga, Costanza L, Heilbron, Karl, Chang, Diana, Tan, Manuela, Young, Emily, Pihlstrøm, Lasse, Leonard, Hampton, Botia, Juan A, Jankovic, Joseph, Shulman, Lisa M, Sutherland, Margaret, Tienari, Pentti, Andreassen, Ole A, Bangale, Tushar, Hinds, David A, Hardy, John A, Visscher, Peter M, and Graham, Robert R

Published
2019
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3. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis

Author

Nabais, Marta F., Lin, Tian, Benyamin, Beben, Williams, Kelly L., Garton, Fleur C., Vinkhuyzen, Anna A. E., Zhang, Futao, Vallerga, Costanza L., Restuadi, Restuadi, Freydenzon, Anna, Zwamborn, Ramona A. J., Hop, Paul J., Robinson, Matthew R., Gratten, Jacob, Visscher, Peter M., Hannon, Eilis, Mill, Jonathan, Brown, Matthew A., Laing, Nigel G., Mather, Karen A., Sachdev, Perminder S., Ngo, Shyuan T., Steyn, Frederik J., Wallace, Leanne, Henders, Anjali K., Needham, Merrilee, Veldink, Jan H., Mathers, Susan, Nicholson, Garth, Rowe, Dominic B., Henderson, Robert D., McCombe, Pamela A., Pamphlett, Roger, Yang, Jian, Blair, Ian P., McRae, Allan F., and Wray, Naomi R.

Published
2020
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4. Epigenetic and Metabolomic Biomarkers for Biological Age: A Comparative Analysis of Mortality and Frailty Risk

Author

Kuiper, Lieke M, primary, Polinder-Bos, Harmke A, additional, Bizzarri, Daniele, additional, Vojinovic, Dina, additional, Vallerga, Costanza L, additional, Beekman, Marian, additional, Dollé, Martijn E T, additional, Ghanbari, Mohsen, additional, Voortman, Trudy, additional, Reinders, Marcel J T, additional, Verschuren, W M Monique, additional, Slagboom, P Eline, additional, van den Akker, Erik B, additional, and van Meurs, Joyce B J, additional

Published
2023
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5. Analysis of DNA methylation associates the cystine–glutamate antiporter SLC7A11 with risk of Parkinson’s disease

Author

Vallerga, Costanza L., Zhang, Futao, Fowdar, Javed, McRae, Allan F., Qi, Ting, Nabais, Marta F., Zhang, Qian, Kassam, Irfahan, Henders, Anjali K., Wallace, Leanne, Montgomery, Grant, Chuang, Yu-Hsuan, Horvath, Steve, Ritz, Beate, Halliday, Glenda, Hickie, Ian, Kwok, John B., Pearson, John, Pitcher, Toni, Kennedy, Martin, Bentley, Steven R., Silburn, Peter A., Yang, Jian, Wray, Naomi R., Lewis, Simon J. G., Anderson, Tim, Dalrymple-Alford, John, Mellick, George D., Visscher, Peter M., and Gratten, Jacob

Published
2020
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8. Improved precision of epigenetic clock estimates across tissues and its implication for biological ageing

Author

Zhang, Qian, Vallerga, Costanza L., Walker, Rosie M., Lin, Tian, Henders, Anjali K., Montgomery, Grant W., He, Ji, Fan, Dongsheng, Fowdar, Javed, Kennedy, Martin, Pitcher, Toni, Pearson, John, Halliday, Glenda, Kwok, John B., Hickie, Ian, Lewis, Simon, Anderson, Tim, Silburn, Peter A., Mellick, George D., Harris, Sarah E., Redmond, Paul, Murray, Alison D., Porteous, David J., Haley, Christopher S., Evans, Kathryn L., McIntosh, Andrew M., Yang, Jian, Gratten, Jacob, Marioni, Riccardo E., Wray, Naomi R., Deary, Ian J., McRae, Allan F., and Visscher, Peter M.

Published
2019
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9. Evaluation of epigenetic and metabolomic biomarkers indicating biological age

Author

Kuiper, Lieke M., primary, Polinder-Bos, Harmke A., additional, Bizzarri, Daniele, additional, Vojinovic, Dina, additional, Vallerga, Costanza L., additional, Beekman, Marian, additional, Dollé, Martijn E.T., additional, Ghanbari, Mohsen, additional, Voortman, Trudy, additional, Reinders, Marcel J.T., additional, Verschuren, W.M. Monique, additional, Slagboom, P. Eline, additional, van den Akker, Erik B., additional, and van Meurs, Joyce B.J., additional

Published
2022
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11. Plasma proteomics identifies CRTAC1 as a biomarker for osteoarthritis severity and progression.

Author

Szilagyi, Ingrid A, Vallerga, Costanza L, Boer, Cindy G, Schiphof, Dieuwke, Ikram, M Arfan, Bierma-Zeinstra, Sita M A, and Meurs, Joyce B J van

Subjects
*BIOMARKERS, *PROTEINS, *KNEE osteoarthritis, *HIP osteoarthritis, *CONFIDENCE intervals, *INFLAMMATION, *MULTIVARIATE analysis, *METABOLISM, *REGRESSION analysis, *CELL receptors, *PROTEOMICS, *SEVERITY of illness index, *RISK assessment, *OSTEOARTHRITIS, *HAND, *GLYCOPROTEINS, *DESCRIPTIVE statistics, *LIGANDS (Biochemistry), *JOINTS (Anatomy), *BLOOD
Abstract

Objectives The aim of this study was to identify biomarkers for radiographic OA severity and progression acting within the inflammation and metabolic pathways. Methods For 3517 Rotterdam Study participants, 184 plasma protein levels were measured using Olink inflammation and cardiometabolic panels. We studied associations with severity and progression of knee, hip and hand OA and a composite overall OA burden score by multivariable regression models, adjusting for age, sex, cell counts and BMI. Results We found 18 significantly associated proteins for overall OA burden, of which 5 stayed significant after multiple testing correction: circulating cartilage acidic protein 1 (CRTAC1), cartilage oligomeric matrix protein (COMP), thrombospondin 4, IL-18 receptor 1 (IL-18R1) and TNF ligand superfamily member 14. These proteins were also associated with progression of knee OA, with the exception of IL-18R1. The strongest association was found for the level of CRTAC1, with 1 s. d. increase in protein level resulting in an increase of 0.09 (95% CI 0.06, 0.12) in the overall OA Kellgren–Lawrence sum score (P  = 2.9 × 10−8) in the model adjusted for age, sex, BMI and cell counts. This association was also present with the severity of OA in all three joints and progression of knee OA and was independent of BMI. We observed a stronger association for CRTAC1 with OA than for the well-known OA biomarker COMP. Conclusion We identified several compelling biomarkers reflecting the overall OA burden and the increased risk for OA progression. CRTAC1 was the most compelling and robust biomarker for OA severity and progression. Such a biomarker may be used for disease monitoring. [ABSTRACT FROM AUTHOR]

Published
2023
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12. Examining the Impact of Imputation Errors on Fine-Mapping Using DNA Methylation QTL as a Model Trait

Author

Chundru, V Kartik, Marioni, Riccardo E, Prendergast, James G D, Vallerga, Costanza L, Lin, Tian, Berveridge, Allan J, Consortium, Sgpd, Gratten, Jacob, Hume, David A, Deary, Ian J, Wray, Naomi R, Visscher, Peter M, and McRae, Allan F

Subjects
Linkage disequilibrium, Quantitative Trait Loci, Bayesian probability, imputation, Investigations, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Quantitative Trait, Heritable, Genetics, Humans, 1000 Genomes Project, Allele, Association mapping, 030304 developmental biology, 0303 health sciences, Whole Genome Sequencing, 030305 genetics & heredity, Haplotype, Reproducibility of Results, DNA Methylation, Reference Standards, fine-mapping, CpG-SNPs, CpG Islands, DNA-methylation, Statistical Genetics and Genomics, Imputation (genetics), Genome-Wide Association Study
Abstract

This study highlights dangers in over-interpreting fine-mapping results. Chundru et al. show that genotype imputation accuracy has a large impact on fine-mapping accuracy. They used DNA methylation at CpG-sites with a variant..., Genetic variants disrupting DNA methylation at CpG dinucleotides (CpG-SNP) provide a set of known causal variants to serve as models to test fine-mapping methodology. We use 1716 CpG-SNPs to test three fine-mapping approaches (Bayesian imputation-based association mapping, Bayesian sparse linear mixed model, and the J-test), assessing the impact of imputation errors and the choice of reference panel by using both whole-genome sequence (WGS), and genotype array data on the same individuals (n = 1166). The choice of imputation reference panel had a strong effect on imputation accuracy, with the 1000 Genomes Project Phase 3 (1000G) reference panel (n = 2504 from 26 populations) giving a mean nonreference discordance rate between imputed and sequenced genotypes of 3.2% compared to 1.6% when using the Haplotype Reference Consortium (HRC) reference panel (n = 32,470 Europeans). These imputation errors had an impact on whether the CpG-SNP was included in the 95% credible set, with a difference of ∼23% and ∼7% between the WGS and the 1000G and HRC imputed datasets, respectively. All of the fine-mapping methods failed to reach the expected 95% coverage of the CpG-SNP. This is attributed to secondary cis genetic effects that are unable to be statistically separated from the CpG-SNP, and through a masking mechanism where the effect of the methylation disrupting allele at the CpG-SNP is hidden by the effect of a nearby SNP that has strong linkage disequilibrium with the CpG-SNP. The reduced accuracy in fine-mapping a known causal variant in a low-level biological trait with imputed genetic data has implications for the study of higher-order complex traits and disease.

Published
2019

14. Moving beyond neurons: the role of cell type-specific gene regulation in Parkinson's disease heritability

Author

Reynolds, Regina H, Botía, Juan, Gibbs, J Raphael, Duarte, Jacinto, Clarimón, Jordi, Dols-Icardo, Oriol, Infante, Jon, Marín, Juan, Kulisevsky, Jaime, Pagonabarraga, Javier, Gonzalez-Aramburu, Isabel, Rodriguez, Antonio Sanchez, Sierra, María, Hernandez, Dena G, Duran, Raquel, Ruz, Clara, Vives, Francisco, Escamilla-Sevilla, Francisco, Mínguez, Adolfo, Cámara, Ana, Compta, Yaroslau, Ezquerra, Mario, Marti, Maria Jose, Fernández, Manel, Singleton, Andrew B, Muñoz, Esteban, Fernández-Santiago, Rubén, Tolosa, Eduard, Valldeoriola, Francesc, García-Ruiz, Pedro, Heredia, Maria Jose Gomez, Errazquin, Francisco Perez, Hoenicka, Janet, Jimenez-Escrig, Adriano, Martínez-Castrillo, Juan Carlos, Reed, Xylena, Lopez-Sendon, Jose Luis, Torres, Irene Martínez, Tabernero, Cesar, Vela, Lydia, Zimprich, Alexander, Pihlstrom, Lasse, Koks, Sulev, Taba, Pille, Majamaa, Kari, Siitonen, Ari, Leonard, Hampton, Okubadejo, Njideka U, Ojo, Oluwadamilola O, Pitcher, Toni, Anderson, Tim, Bentley, Steven, Fowdar, Javed, Mellick, George, Dalrymple-Alford, John, Henders, Anjali K, Kassam, Irfahan, Blauwendraat, Cornelis, Montgomery, Grant, Sidorenko, Julia, Zhang, Futao, Xue, Angli, Vallerga, Costanza L, Wallace, Leanne, Wray, Naomi R, Yang, Jian, Visscher, Peter M, Gratten, Jacob, Faghri, Faraz, Silburn, Peter A, Halliday, Glenda, Hickie, Ian, Kwok, John, Lewis, Simon, Kennedy, Martin, Pearson, John, Bras, Jose, Guerreiro, Rita, Tucci, Arianna, Nalls, Mike A, Kia, Demis A, Houlden, Henry, Plun-Favreau, Helene, Mok, Kin Y, Wood, Nicholas W, Lovering, Ruth, R'Bibo, Lea, Rizig, Mie, Chelban, Viorica, Trabzuni, Daniah, Hardy, John, Tan, Manuela, Morris, Huw R, Middlehurst, Ben, Quinn, John, Billingsley, Kimberley, Holmans, Peter, Kinghorn, Kerri J, Lewis, Patrick, Escott-Price, Valentina, Williams, Nigel, Gagliano Taliun, Sarah A, Foltynie, Thomas, Brice, Alexis, Danjou, Fabrice, Lesage, Suzanne, Corvol, Jean-Christophe, Martinez, Maria, Giri, Anamika, Schulte, Claudia, Brockmann, Kathrin, Simon Sanchez, Javier, Ryten, Mina, Heutink, Peter, Gasser, Thomas, Rizzu, Patrizia, Sharma, Manu, Shulman, Joshua M, Robak, Laurie, Lubbe, Steven, Mencacci, Niccolo E, Finkbeiner, Steven, Lungu, Codrin, Noyce, Alastair J, Scholz, Sonja W, Gan-Or, Ziv, Rouleau, Guy A, Krohan, Lynne, van Hilten, Jacobus J, Marinus, Johan, Adarmes-Gómez, Astrid D, Bernal-Bernal, Inmaculada, Bonilla-Toribio, Marta, Buiza-Rueda, Dolores, Nicolas, Aude, Carrillo, Fátima, Carrión-Claro, Mario, Mir, Pablo, Gómez-Garre, Pilar, Jesús, Silvia, Labrador-Espinosa, Miguel A, Macias, Daniel, Vargas-González, Laura, Méndez-Del-Barrio, Carlota, Periñán-Tocino, Teresa, Cookson, Mark R, Tejera-Parrado, Cristina, Diez-Fairen, Monica, Aguilar, Miquel, Alvarez, Ignacio, Boungiorno, María Teresa, Carcel, Maria, Pastor, Pau, Tartari, Juan Pablo, Alvarez, Victoria, González, Manuel Menéndez, Bandres-Ciga, Sara, Blazquez, Marta, Garcia, Ciara, Suarez-Sanmartin, Esther, Barrero, Francisco Javier, Rezola, Elisabet Mondragon, Yarza, Jesús Alberto Bergareche, Pagola, Ana Gorostidi, de Munain Arregui, Adolfo López, Ruiz-Martínez, Javier, and Cerdan, Debora

Subjects
Regulation of gene expression, 0303 health sciences, Cell type, Parkinson's disease, Microglia, Dopaminergic, Genomics, Disease, Biology, medicine.disease, Article, 03 medical and health sciences, 0302 clinical medicine, medicine.anatomical_structure, medicine, ddc:610, Neuroscience, Gene, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

Parkinson’s disease (PD), with its characteristic loss of nigrostriatal dopaminergic neurons and deposition of α-synuclein in neurons, is often considered a neuronal disorder. However, in recent years substantial evidence has emerged to implicate glial cell types, such as astrocytes and microglia. In this study, we used stratified LD score regression and expression-weighted cell-type enrichment together with several brain-related and cell-type-specific genomic annotations to connect human genomic PD findings to specific brain cell types. We found that PD heritability attributable to common variation does not enrich in global and regional brain annotations or brain-related cell-type-specific annotations. Likewise, we found no enrichment of PD susceptibility genes in brain-related cell types. In contrast, we demonstrated a significant enrichment of PD heritability in a curated lysosomal gene set highly expressed in astrocytic, microglial, and oligodendrocyte subtypes, and in LoF-intolerant genes, which were found highly expressed in almost all tested cellular subtypes. Our results suggest that PD risk loci do not lie in specific cell types or individual brain regions, but rather in global cellular processes detectable across several cell types.

Published
2019

15. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders.

Author

Nabais, Marta F., Laws, Simon M., Lin, Tian, Vallerga, Costanza L., Armstrong, Nicola J., Blair, Ian P., Kwok, John B., Mather, Karen A., Mellick, George D., Sachdev, Perminder S., Wallace, Leanne, Henders, Anjali K., Zwamborn, Ramona A. J., Hop, Paul J., Lunnon, Katie, Pishva, Ehsan, Roubroeks, Janou A. Y., Soininen, Hilkka, Tsolaki, Magda, and Mecocci, Patrizia

Published
2021
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17. Plasma biomarkers of endothelial dysfunction and cognition: an IPD meta-analysis of cross- sectional data from 9,344 individuals from seven Dutch cohorts

Author

Beran, Magdalena, Jansen, Willemijn J., Oomens, Julie E., Moonen, Justine E.F., Visser, Pieter Jelle, Huisman, Martijn A., Kok, Almar A.L., Nooyens, Astrid C.J., Verschuren, W.M. Monique, Stehouwer, Coen D.A., Schalkwijk, Casper, Köhler, Sebastian, van Boxtel, Martin, Beekman, Marian, Slagboom, P. Eline, Wolters, Frank J., Ikram, M. Arfan, Vallerga, Costanza L., van Meurs, Joyce B.J., Ghanbari, Mohsen, Vonk, Jet M.J., Geerlings, Mirjam I., van Sloten, Thomas T., and Schram, Miranda T.

Abstract

Endothelial dysfunction has various detrimental effects on the brain that may lead to cognitive decline. However, data on the direct association between endothelial dysfunction and cognitive performance in humans are scarce. The aim of the present study was to assess the cross-sectional association between plasma biomarkers of endothelial dysfunction and cognitive performance.

Published
2024
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18. Parkinson's disease age at onset genome-wide association study: Defining heritability, genetic loci, and α-synuclein mechanisms.

Author

Blauwendraat, Cornelis, Heilbron, Karl, Vallerga, Costanza L., Bandres‐Ciga, Sara, von Coelln, Rainer, Pihlstrøm, Lasse, Simón‐Sánchez, Javier, Schulte, Claudia, Sharma, Manu, Krohn, Lynne, Siitonen, Ari, Iwaki, Hirotaka, Leonard, Hampton, Noyce, Alastair J., Tan, Manuela, Gibbs, J. Raphael, Hernandez, Dena G., Scholz, Sonja W., Jankovic, Joseph, and Shulman, Lisa M.

Subjects
AGE factors in disease, ALLELES, DATABASES, DISEASE susceptibility, GENETIC polymorphisms, GENOMES, GLYCOSIDASES, NERVE tissue proteins, PARKINSON'S disease, RESEARCH funding, SEQUENCE analysis
Abstract

Background: Increasing evidence supports an extensive and complex genetic contribution to PD. Previous genome-wide association studies (GWAS) have shed light on the genetic basis of risk for this disease. However, the genetic determinants of PD age at onset are largely unknown.Objectives: To identify the genetic determinants of PD age at onset.Methods: Using genetic data of 28,568 PD cases, we performed a genome-wide association study based on PD age at onset.Results: We estimated that the heritability of PD age at onset attributed to common genetic variation was ∼0.11, lower than the overall heritability of risk for PD (∼0.27), likely, in part, because of the subjective nature of this measure. We found two genome-wide significant association signals, one at SNCA and the other a protein-coding variant in TMEM175, both of which are known PD risk loci and a Bonferroni-corrected significant effect at other known PD risk loci, GBA, INPP5F/BAG3, FAM47E/SCARB2, and MCCC1. Notably, SNCA, TMEM175, SCARB2, BAG3, and GBA have all been shown to be implicated in α-synuclein aggregation pathways. Remarkably, other well-established PD risk loci, such as GCH1 and MAPT, did not show a significant effect on age at onset of PD.Conclusions: Overall, we have performed the largest age at onset of PD genome-wide association studies to date, and our results show that not all PD risk loci influence age at onset with significant differences between risk alleles for age at onset. This provides a compelling picture, both within the context of functional characterization of disease-linked genetic variability and in defining differences between risk alleles for age at onset, or frank risk for disease. © 2019 International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

Published
2019
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