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2. Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

Author

Sugier, Pierre-Emmanuel, Lucotte, Elise A., Domenighetti, Cloé, Law, Matthew H., Iles, Mark M., Brown, Kevin, Amos, Christopher, McKay, James D., Hung, Rayjean J., Karimi, Mojgan, Bacq-Daian, Delphine, Boland-Augé, Anne, Olaso, Robert, Deleuze, Jean-François, Lesueur, Fabienne, Ostroumova, Evgenia, Kesminiene, Ausrele, de Vathaire, Florent, Guénel, Pascal, consortium, The Epithyr, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimios, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Nakayama, Akiyoshi, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart P. C., Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Guedes, Leonor Correia, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy, Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Rödström, Emil Ygland, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Landoulsi, Zied, consortium, Courage-PD, Truong, Thérèse, Elbaz, Ales, JPND Courage-PD [sponsor], Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], and Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center]

Subjects
Male, Lung Neoplasms, Parkinson's disease, Neurology [D14] [Human health sciences], RESEARCH ARTICLES, RESEARCH ARTICLE, SDG 3 - Good Health and Well-being, genetics [Parkinson Disease], Risk Factors, pleiotropy, Humans, cancer, ddc:610, genetics [Genetic Predisposition to Disease], Ovarian Neoplasms, Neurologie [D14] [Sciences de la santé humaine], Prostatic Neoplasms, Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3], genetic correlation, parkinson's disease, polygenic risk score, epidemiology [Melanoma], Neurology, genetics [Melanoma], genetics [Polymorphism, Single Nucleotide], Female, epidemiology [Parkinson Disease], Genetics & genetic processes [F10] [Life sciences], Neurology (clinical), Génétique & processus génétiques [F10] [Sciences du vivant], Genome-Wide Association Study
Abstract

BackgroundEpidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties.ObjectiveWe used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors.MethodsWe used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses.ResultsWe confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31).ConclusionsWe show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Published
2023
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3. Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], JPND Courage-PD [sponsor], Sugier, Pierre-Emmanuel, Lucotte, Elise A., Domenighetti, Cloé, Law, Matthew H., Iles, Mark M., Brown, Kevin, Amos, Christopher, McKay, James D., Hung, Rayjean J., Karimi, Mojgan, Bacq-Daian, Delphine, Boland-Augé, Anne, Olaso, Robert, Deleuze, Jean-François, Lesueur, Fabienne, Ostroumova, Evgenia, Kesminiene, Ausrele, de Vathaire, Florent, Guénel, Pascal, consortium, The Epithyr, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimios, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Nakayama, Akiyoshi, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart P. C., Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Guedes, Leonor Correia, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy, Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Rödström, Emil Ygland, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Landoulsi, Zied, consortium, Courage-PD, Truong, Thérèse, Elbaz, Ales, Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], JPND Courage-PD [sponsor], Sugier, Pierre-Emmanuel, Lucotte, Elise A., Domenighetti, Cloé, Law, Matthew H., Iles, Mark M., Brown, Kevin, Amos, Christopher, McKay, James D., Hung, Rayjean J., Karimi, Mojgan, Bacq-Daian, Delphine, Boland-Augé, Anne, Olaso, Robert, Deleuze, Jean-François, Lesueur, Fabienne, Ostroumova, Evgenia, Kesminiene, Ausrele, de Vathaire, Florent, Guénel, Pascal, consortium, The Epithyr, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimios, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Nakayama, Akiyoshi, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart P. C., Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Guedes, Leonor Correia, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy, Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Rödström, Emil Ygland, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Landoulsi, Zied, consortium, Courage-PD, Truong, Thérèse, and Elbaz, Ales

Abstract

Background Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. Objective We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. Methods We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. Results We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly dri

Published
2023

6. Parkinson’s disease-associated alterations of the gut microbiome predict disease-relevant changes in metabolic functions

Author

Baldini, Federico, Hertel, Johannes, Sandt, Estelle, Thinnes, Cyrille C., Neuberger-Castillo, Lorieza, Pavelka, Lukas, Betsou, Fay, Krüger, Rejko, Thiele, Ines, Aguayo, Gloria, Allen, Dominic, Ammerlann, Wim, Aurich, Maike, Balling, Rudi, Banda, Peter, Beaumont, Katy, Becker, Regina, Berg, Daniela, Binck, Sylvia, Bisdorff, Alexandre, Bobbili, Dheeraj, Brockmann, Kathrin, Calmes, Jessica, Castillo, Lorieza, Diederich, Nico, Dondelinger, Rene, Esteves, Daniela, Ferrand, Jean-Yves, Fleming, Ronan, Gantenbein, Manon, Gasser, Thomas, Gawron, Piotr, Geffers, Lars, Giarmana, Virginie, Glaab, Enrico, Gomes, Clarissa P. C., Goncharenko, Nikolai, Graas, Jérôme, Graziano, Mariela, Groues, Valentin, Grünewald, Anne, Gu, Wei, Hammot, Gaël, Hanff, Anne-Marie, Hansen, Linda, Hansen, Maxime, Haraldsdöttir, Hulda, Heirendt, Laurent, Herbrink, Sylvia, Herzinger, Sascha, Heymann, Michael, Hiller, Karsten, Hipp, Geraldine, Hu, Michele, Huiart, Laetitia, Hundt, Alexander, Jacoby, Nadine, Jarosław, Jacek, Jaroz, Yohan, Kolber, Pierre, Kutzera, Joachim, Landoulsi, Zied, Larue, Catherine, Lentz, Roseline, Liepelt, Inga, Liszka, Robert, Longhino, Laura, Lorentz, Victoria, Mackay, Clare, Maetzler, Walter, Marcus, Katrin, Marques, Guilherme, Martens, Jan, Mathay, Conny, Matyjaszczyk, Piotr, May, Patrick, Meisch, Francoise, Menster, Myriam, Minelli, Maura, Mittelbronn, Michel, Mollenhauer, Brit, Mommaerts, Kathleen, Moreno, Carlos, Mühlschlegel, Friedrich, Nati, Romain, Nehrbass, Ulf, Nickels, Sarah, Nicolai, Beatrice, Nicolay, Jean-Paul, Noronha, Alberto, Oertel, Wolfgang, Ostaszewski, Marek, Pachchek, Sinthuja, Pauly, Claire, Perquin, Magali, Reiter, Dorothea, Rosety, Isabel, Rump, Kirsten, Satagopam, Venkata, Schlesser, Marc, Schmitz, Sabine, Schmitz, Susanne, Schneider, Reinhard, Schwamborn, Jens, Schweicher, Alexandra, Simons, Janine, Stute, Lara, Trefois, Christophe, Trezzi, Jean-Pierre, Vaillant, Michel, Vasco, Daniel, Vyas, Maharshi, Wade-Martins, Richard, and Wilmes, Paul

Subjects
Male, Systemic disease, Parkinson's disease, Physiology, Luxembourg, Plant Science, Disease, Transsulfuration pathway, Biology, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Structural Biology, RNA, Ribosomal, 16S, Pantothenic acid, medicine, Humans, Microbiome, lcsh:QH301-705.5, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Aged, Metabolic modelling, 0303 health sciences, Gut microbiome, Methionine, Dopaminergic, Parkinson Disease, Cell Biology, Middle Aged, medicine.disease, 3. Good health, Gastrointestinal Microbiome, RNA, Bacterial, chemistry, Computational modelling, lcsh:Biology (General), Case-Control Studies, Parkinson’s disease, Female, General Agricultural and Biological Sciences, 030217 neurology & neurosurgery, Developmental Biology, Biotechnology, Research Article
Abstract

Background Parkinson’s disease (PD) is a systemic disease clinically defined by the degeneration of dopaminergic neurons in the brain. While alterations in the gut microbiome composition have been reported in PD, their functional consequences remain unclear. Herein, we addressed this question by an analysis of stool samples from the Luxembourg Parkinson’s Study (n = 147 typical PD cases, n = 162 controls). Results All individuals underwent detailed clinical assessment, including neurological examinations and neuropsychological tests followed by self-reporting questionnaires. Stool samples from these individuals were first analysed by 16S rRNA gene sequencing. Second, we predicted the potential secretion for 129 microbial metabolites through personalised metabolic modelling using the microbiome data and genome-scale metabolic reconstructions of human gut microbes. Our key results include the following. Eight genera and seven species changed significantly in their relative abundances between PD patients and healthy controls. PD-associated microbial patterns statistically depended on sex, age, BMI, and constipation. Particularly, the relative abundances of Bilophila and Paraprevotella were significantly associated with the Hoehn and Yahr staging after controlling for the disease duration. Furthermore, personalised metabolic modelling of the gut microbiomes revealed PD-associated metabolic patterns in the predicted secretion potential of nine microbial metabolites in PD, including increased methionine and cysteinylglycine. The predicted microbial pantothenic acid production potential was linked to the presence of specific non-motor symptoms. Conclusion Our results suggest that PD-associated alterations of the gut microbiome can translate into substantial functional differences affecting host metabolism and disease phenotype.

Published
2020
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7. The Interaction between HLA-DRB1 and Smoking in Parkinson's Disease Revisited

Author

Domenighetti, Cloé, Douillard, Venceslas, Sugier, Pierre-Emmanuel, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Gourraud, Pierre-Antoine, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimos, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Nakayama, Akiyoshi, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart P. C., Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Correia Guedes, Leonor, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy L., Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Ygland Rödström, Emil, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, KraincMD, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Vince, Nicolas, Elbaz, Alexis, Genetics, Comprehensive Unbiased Risk Factor Assessment For, Consortium, Environment In Parkinson S Disease Courage-P. D., Fonds National de la Recherche - FnR [sponsor], Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], and Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center]

Subjects
Neurologie [D14] [Sciences de la santé humaine], genetics [HLA-DRB1 Chains], Neurology [D14] [Human health sciences], Parkinson's disease, Smoking, Parkinson Disease, genetics [Smoking], Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3], Polymorphism, Single Nucleotide, smoking, gene-environment interaction, HLA, Neurology, genetics [Parkinson Disease], genetics [Polymorphism, Single Nucleotide], Humans, Genetic Predisposition to Disease, ddc:610, Genetics & genetic processes [F10] [Life sciences], Neurology (clinical), Génétique & processus génétiques [F10] [Sciences du vivant], HLA-DRB1 Chains
Abstract

Contains fulltext : 282469.pdf (Publisher’s version ) (Open Access) BACKGROUND: Two studies that examined the interaction between HLA-DRB1 and smoking in Parkinson's disease (PD) yielded findings in opposite directions. OBJECTIVE: To perform a large-scale independent replication of the HLA-DRB1 × smoking interaction. METHODS: We genotyped 182 single nucleotide polymorphism (SNPs) associated with smoking initiation in 12 424 cases and 9480 controls to perform a Mendelian randomization (MR) analysis in strata defined by HLA-DRB1. RESULTS: At the amino acid level, a valine at position 11 (V11) in HLA-DRB1 displayed the strongest association with PD. MR showed an inverse association between genetically predicted smoking initiation and PD only in absence of V11 (odds ratio, 0.74, 95% confidence interval, 0.59-0.93, P(Interaction) = 0.028). In silico predictions of the influence of V11 and smoking-induced modifications of α-synuclein on binding affinity showed findings consistent with this interaction pattern. CONCLUSIONS: Despite being one of the most robust findings in PD research, the mechanisms underlying the inverse association between smoking and PD remain unknown. Our findings may help better understand this association. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Published
2022
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8. Dairy Intake and Parkinson's Disease: A Mendelian Randomization Study

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], Fonds National de la Recherche - FnR [sponsor], JPND Courage-PD [sponsor], Domenighetti, Cloé, Sugier, Pierre-Emmanuel, Ashok Kumar Sreelatha, Ashwin, Schulte, Claudia, Grover, Sandeep, Mohamed, Océane, Portugal, Berta, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimos, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Kawamura, Yusuke, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart P. C., Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Correia Guedes, Leonor, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy L., Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Hellberg, Clara, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Elbaz, Alexis, Genetics, The Comprehensive Unbiased Risk Factor Assessment For, Consortium, Environment In Parkinson S Disease Courage-P. D., Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], Fonds National de la Recherche - FnR [sponsor], JPND Courage-PD [sponsor], Domenighetti, Cloé, Sugier, Pierre-Emmanuel, Ashok Kumar Sreelatha, Ashwin, Schulte, Claudia, Grover, Sandeep, Mohamed, Océane, Portugal, Berta, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimos, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Kawamura, Yusuke, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart P. C., Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Correia Guedes, Leonor, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy L., Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Hellberg, Clara, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Elbaz, Alexis, Genetics, The Comprehensive Unbiased Risk Factor Assessment For, and Consortium, Environment In Parkinson S Disease Courage-P. D.

Abstract

Background Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained by reverse causation or confounding. Objective The aim is to examine the association between genetically predicted dairy intake and PD using two-sample Mendelian randomization (MR). Methods We genotyped a well-established instrumental variable for dairy intake located in the lactase gene (rs4988235) within the Courage-PD consortium (23 studies; 9823 patients and 8376 controls of European ancestry). Results Based on a dominant model, there was an association between genetic predisposition toward higher dairy intake and PD (odds ratio [OR] per one serving per day = 1.70, 95 confidence interval = 1.12–2.60, P = 0.013) that was restricted to men (OR = 2.50 [1.37–4.56], P = 0.003; P-difference with women = 0.029). Conclusions Using MR, our findings provide further support for a causal relationship between dairy intake and higher PD risk, not biased by confounding or reverse causation. Further studies are needed to elucidate the underlying mechanisms. © 2022 International Parkinson and Movement Disorder Society

Published
2022

9. Dairy Intake and Parkinson's Disease: A Mendelian Randomization Study

Author

Domenighetti, Cloé, Sugier, Pierre-Emmanuel, Lichtner, Peter, Singleton, Andrew B, Hernandez, Dena Michelle Godwin, Edsall, Connor, Mellick, George D, Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E, Koks, Sulev, Ashok Kumar Sreelatha, Ashwin, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B, Hadjigeorgiou, Georges M, Dardiotis, Efthimos, Schulte, Claudia, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Grover, Sandeep, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Kawamura, Yusuke, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, Mohamed, Océane, van de Warrenburg, Bart P C, Bloem, Bastiaan R, Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Correia Guedes, Leonor, Ferreira, Joaquim J, Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Portugal, Berta, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy L, Ran, Caroline, Belin, Andrea C, Puschmann, Andreas, Hellberg, Clara, Clarke, Carl E, May, Patrick, Morrison, Karen E, Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F, Farrer, Matt J, Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Elbaz, Alexis, Genetics, and the Comprehensive Unbiased Risk Factor Assessment for, Bobbili, Dheeraj R, Disease, Environment in Parkinson's, Radivojkov-Blagojevic, Milena, and Repositório da Universidade de Lisboa

Subjects
Male, dairy intake, Parkinson's disease, Mendelian randomization, Parkinson Disease, Dairy intake, Mendelian Randomization Analysis, Disorders of movement Donders Center for Medical Neuroscience [Radboudumc 3], Polymorphism, Single Nucleotide, Neurology, genetics [Parkinson Disease], Risk Factors, adverse effects [Dairy Products], genetics [Polymorphism, Single Nucleotide], Humans, Genetic Predisposition to Disease, Female, Dairy Products, Neurology (clinical), ddc:610, epidemiology [Parkinson Disease], genetics [Genetic Predisposition to Disease], Genome-Wide Association Study
Abstract

© 2022 International Parkinson and Movement Disorder Society, Background: Previous prospective studies highlighted dairy intake as a risk factor for Parkinson's disease (PD), particularly in men. It is unclear whether this association is causal or explained by reverse causation or confounding. Objective: The aim is to examine the association between genetically predicted dairy intake and PD using two-sample Mendelian randomization (MR). Methods: We genotyped a well-established instrumental variable for dairy intake located in the lactase gene (rs4988235) within the Courage-PD consortium (23 studies; 9823 patients and 8376 controls of European ancestry). Results: Based on a dominant model, there was an association between genetic predisposition toward higher dairy intake and PD (odds ratio [OR] per one serving per day = 1.70, 95% confidence interval = 1.12-2.60, P = 0.013) that was restricted to men (OR = 2.50 [1.37-4.56], P = 0.003; P-difference with women = 0.029). Conclusions: Using MR, our findings provide further support for a causal relationship between dairy intake and higher PD risk, not biased by confounding or reverse causation. Further studies are needed to elucidate the underlying mechanisms. © 2022 International Parkinson and Movement Disorder Society., This study used data from the Courage-PD consortium, conducted under a partnership agreement among 35 studies. The Courage-PD consortium is supported by the EU Joint Program for Neurodegenerative Disease research (JPND; https://www.neurodegenerationresearch.eu/initiatives/annual-calls-for-proposals/closed-calls/risk-factors-2012/risk-factor-call-results/courage-pd/). C.D. is the recipient of a doctoral grant from Université Paris-Saclay, France. P.M. was funded by the Fonds National de Recherche (FNR), Luxembourg, as part of the National Centre of Excellence in Research on Parkinson's Disease (NCER-PD, FNR11264123) and the DFG Research Units FOR2715 (INTER/DFG/17/11583046) and FOR2488 (INTER/DFG/19/14429377). A.B.S., D.G.H., and C.E. are funded by the Intramural Research Program of the National Institute on Aging, National Institutes of Health, Department of Health and Human Services, project ZO1 AG000949. E.R. is funded by the Canadian Consortium on Neurodegeneration in Aging. S.K. is funded by MSWA. P.T. is the recipient of an Estonian Research Council Grant PRG957. E.M.V. is funded by the Italian Ministry of Health (Ricerca Corrente 2021). S.B. and J.C. are supported by grants from the National Research Foundation of South Africa (grant number: 106052); the South African Medical Research Council (Self-Initiated Research Grant); and Stellenbosch University, South Africa; they also acknowledge the support of the NRF-DST Centre of Excellence for Biomedical Tuberculosis Research; South African Medical Research Council Centre for Tuberculosis Research; and Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town. P.P. and M.D.-F. have received funding from the Spanish Ministry of Science and Innovation (SAF2013-47939-R). K.W. and N.L.P. are funded by the Swedish Research Council, grant numbers K2002-27X-14056-02B, 521-2010-2479, 521-2013-2488, and 2017-02175. N.L.P. is funded by the National Institutes of Health, grant numbers ES10758 and AG 08724. C.R. is funded by the Märta Lundkvist Foundation, Swedish Brain Foundation, and Karolinska Institutet Research Fund. A.C.B. is funded by the Swedish Brain Foundation, Swedish Research Council, and Karolinska Institutet Research Funds. M.T. (M. Tan) is funded by the Parkinson's UK. M.S. was supported by grants from the German Research Council (DFG/SH 599/6-1), MSA Coalition, and The Michael J. Fox Foundation (USA Genetic Diversity in PD Program: GAP-India Grant ID: 17473). PG GEN sample collection was funded by the MRC and UK Medical Research Council (C.E.C. and K.E.M.).

Published
2022
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10. Mendelian randomization study of smoking, alcohol, and coffee drinking in relation to Parkinso's disease

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], JPND [sponsor], Domenighetti, Cloe, Sugier, Pierre Emmanuel, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, Mohamed, Oceane, Portugal, Berta, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaieva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Hardin, Marie-Christophe, Mutez, Eugenie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimos, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza-Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotak, Kawamura, Yusuke, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart Pc, Bloom, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrom, Lasse, Guedes, Leonor Correia, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Farien, Monica, Wirdefeldt, Karin, Pedersen, Nancy L., Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Hellberg, Clara, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, DImitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, Elbaz, Alexis, Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group) [research center], Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], JPND [sponsor], Domenighetti, Cloe, Sugier, Pierre Emmanuel, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, Mohamed, Oceane, Portugal, Berta, May, Patrick, Bobbili, Dheeraj Reddy, Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaieva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Hardin, Marie-Christophe, Mutez, Eugenie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimos, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza-Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotak, Kawamura, Yusuke, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart Pc, Bloom, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrom, Lasse, Guedes, Leonor Correia, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Farien, Monica, Wirdefeldt, Karin, Pedersen, Nancy L., Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Hellberg, Clara, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, DImitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, and Elbaz, Alexis

Abstract

Background:Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson’s disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation. Objective:To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases. Methods:We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017). Results:We found a significant inverse association between smoking initiation and PD (ORIVW per 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60–0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking. Conclusion:Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.

Published
2021

11. Gene-environment interaction and Mendelian randomisation

Author

Krüger, Rejko and Kolber, Pierre Luc

Subjects
Neurologie [D14] [Sciences de la santé humaine], Parkinson's disease, Neurology [D14] [Human health sciences], Mendelian randomisation, Gene-environment interaction
Abstract

Genetic factors only account for up to a third of the cases of Parkinson's disease (PD), while the remaining cases are of unknown aetiology. Environmental exposures (such as pesticides or heavy metals) and the interaction with genetic susceptibility factors (summarized in the concept of impaired xenobiotic metabolism) are believed to play a major role in the mechanisms of neurodegeneration. Beside of the classical association studies (e.g. genome-wide association studies), a novel approach to investigate environmental risk factors are Mendelian randomisation studies. This review explores the gene-environment interaction and the gain of Mendelian randomisation studies in assessing causalities of modifiable risk factors for PD.

Published
2019

12. Connecting environmental exposure and neurodegeneration using cheminformatics and high resolution mass spectrometry: potential and challenges

Author

Schymanski, Emma, Baker, Nancy C., Williams, Antony J, Singh, Randolph, Trezzi, Jean-Pierre, Kolber, Pierre Luc, Wilmes, Paul, Krüger, Rejko, Paczia, Nicole, Linster, Carole, and Balling, Rudi

Subjects
neurodegenerative diseases, Biochemistry, biophysics & molecular biology [F05] [Life sciences], Biochimie, biophysique & biologie moléculaire [F05] [Sciences du vivant], chemical exposures, mass spectrometry
Abstract

Connecting chemical exposures over a lifetime to complex chronic diseases with multifactorial causes such as neurodegenerative diseases is an immense challenge requiring a long-term, interdisciplinary approach. Rapid developments in analytical and data technologies, such as non-target high resolution mass spectrometry (NT-HR-MS), have opened up new possibilities to accomplish this, inconceivable 20 years ago. While NT-HR-MS is being applied to increasingly complex research questions, there are still many unidentified chemicals and uncertainties in linking exposures to human health outcomes and environmental impacts. In this perspective, we explore the possibilities and challenges involved in using cheminformatics and NT-HR-MS to answer complex questions that cross many scientific disciplines, taking the identification of potential (small molecule) neurotoxicants in environmental or biological matrices as a case study. We explore capturing literature knowledge and patient exposure information in a form amenable to high-throughput data mining, and the related cheminformatic challenges. We then briefly cover which sample matrices are available, which method(s) could potentially be used to detect these chemicals in various matrices and what remains beyond the reach of NT-HR-MS. We touch on the potential for biological validation systems to contribute to mechanistic understanding of observations and explore which sampling and data archiving strategies may be required to form an accurate, sustained picture of small molecule signatures on extensive cohorts of patients with chronic neurodegenerative disorders. Finally, we reflect on how NT-HR-MS can support unravelling the contribution of the environment to complex diseases.

Published
2019

13. A 'kissing lesion': In-vivo 7T evidence of meningeal inflammation in early multiple sclerosis

Author

Kolber, Pierre, Kolber, Pierre, Droby, Amgad, Roebroeck, Alard, Goebel, Rainer, Fleischer, Vinzenz, Groppa, Sergiu, Zipp, Frauke, Kolber, Pierre, Kolber, Pierre, Droby, Amgad, Roebroeck, Alard, Goebel, Rainer, Fleischer, Vinzenz, Groppa, Sergiu, and Zipp, Frauke

Abstract

BACKGROUND: The role of cortical lesions (CLs) in disease progression and clinical deficits is increasingly recognized in multiple sclerosis (MS); however the origin of CLs in MS still remains unclear.OBJECTIVE: Here, we report a para-sulcal CL detected two years after diagnosis in a relapsing-remitting MS (RRMS) patient without manifestation of clinical deficit.METHODS: Ultra-high field (7T) MR imaging using magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence was performed.RESULTS: A para-sulcal CL was detected which showed hypointense rim and iso- to hyperintense core. This was detected in the proximity of the leptomeninges in the left precentral gyrus extending to the adjacent postcentral gyrus.CONCLUSION: This finding indicates that inflammatory infiltration into the cortex through the meninges underlies cortical pathology already in the early stage of disease and in mild disease course.

Published
2017

14. Characterizing microstructural tissue properties in multiple sclerosis with diffusion MRI at 7 T and 3 T: The impact of the experimental design

Author

European Research Council, Brain and Behavior Research Foundation, Federal Ministry of Education and Research (Germany), Netherlands Organization for Scientific Research, De Santis, Silvia, Bastiani, Matteo, Droby, Amgad, Kolber, Pierre, Zipp, Frauke, Pracht, Eberhard, Stoecker, Tony, Groppa, Sergiu, Roebroeck, Alard, European Research Council, Brain and Behavior Research Foundation, Federal Ministry of Education and Research (Germany), Netherlands Organization for Scientific Research, De Santis, Silvia, Bastiani, Matteo, Droby, Amgad, Kolber, Pierre, Zipp, Frauke, Pracht, Eberhard, Stoecker, Tony, Groppa, Sergiu, and Roebroeck, Alard

Abstract

The recent introduction of advanced magnetic resonance (MR) imaging techniques to characterize focal and global degeneration in multiple sclerosis (MS), like the Composite Hindered and Restricted Model of Diffusion, or CHARMED, diffusional kurtosis imaging (DKI) and Neurite Orientation Dispersion and Density Imaging (NODDI) made available new tools to image axonal pathology non-invasively in vivo. These methods already showed greater sensitivity and specificity compared to conventional diffusion tensor-based metrics (e.g., fractional anisotropy), overcoming some of its limitations. While previous studies uncovered global and focal axonal degeneration in MS patients compared to healthy controls, here our aim is to investigate and compare different diffusion MRI acquisition protocols in their ability to highlight microstructural differences between MS and control tissue over several much used models. For comparison, we contrasted the ability of fractional anisotropy measurements to uncover differences between lesion, normal-appearing white matter (WM), gray matter and healthy tissue under the same imaging protocols. We show that: (1) focal and diffuse differences in several microstructural parameters are observed under clinical settings; (2) advanced models (CHARMED, DKI and NODDI) have increased specificity and sensitivity to neurodegeneration when compared to fractional anisotropy measurements; and (3) both high (3 T) and ultra-high fields (7 T) are viable options for imaging tissue change in MS lesions and normal appearing WM, while higher b-values are less beneficial under the tested short-time (10 min acquisition) conditions.

Published
2019

15. Mendelian Randomisation Study of Smoking, Alcohol, and Coffee Drinking in Relation to Parkinson’s Disease

Author

Domenighetti, Cloé, Sugier, Pierre-Emmanuel, Sreelatha, Ashwin Ashok Kumar, Schulte, Claudia, Grover, Sandeep, Mohamed, Océane, Portugal, Berta, May, Patrick, Bobbili, Dheeraj R., Radivojkov-Blagojevic, Milena, Lichtner, Peter, Singleton, Andrew B., Hernandez, Dena G., Edsall, Connor, Mellick, George D., Zimprich, Alexander, Pirker, Walter, Rogaeva, Ekaterina, Lang, Anthony E., Koks, Sulev, Taba, Pille, Lesage, Suzanne, Brice, Alexis, Corvol, Jean-Christophe, Chartier-Harlin, Marie-Christine, Mutez, Eugénie, Brockmann, Kathrin, Deutschländer, Angela B., Hadjigeorgiou, Georges M., Dardiotis, Efthimos, Stefanis, Leonidas, Simitsi, Athina Maria, Valente, Enza Maria, Petrucci, Simona, Duga, Stefano, Straniero, Letizia, Zecchinelli, Anna, Pezzoli, Gianni, Brighina, Laura, Ferrarese, Carlo, Annesi, Grazia, Quattrone, Andrea, Gagliardi, Monica, Matsuo, Hirotaka, Kawamura, Yusuke, Hattori, Nobutaka, Nishioka, Kenya, Chung, Sun Ju, Kim, Yun Joong, Kolber, Pierre, van de Warrenburg, Bart PC, Bloem, Bastiaan R., Aasly, Jan, Toft, Mathias, Pihlstrøm, Lasse, Guedes, Leonor Correia, Ferreira, Joaquim J., Bardien, Soraya, Carr, Jonathan, Tolosa, Eduardo, Ezquerra, Mario, Pastor, Pau, Diez-Fairen, Monica, Wirdefeldt, Karin, Pedersen, Nancy L., Ran, Caroline, Belin, Andrea C., Puschmann, Andreas, Hellberg, Clara, Clarke, Carl E., Morrison, Karen E., Tan, Manuela, Krainc, Dimitri, Burbulla, Lena F., Farrer, Matt J., Krüger, Rejko, Gasser, Thomas, Sharma, Manu, and Elbaz, Alexis

Abstract

Previous studies showed that lifestyle behaviors (cigarette smoking, alcohol, coffee) are inversely associated with Parkinson’s disease (PD). The prodromal phase of PD raises the possibility that these associations may be explained by reverse causation. To examine associations of lifestyle behaviors with PD using two-sample Mendelian randomisation (MR) and the potential for survival and incidence-prevalence biases. We used summary statistics from publicly available studies to estimate the association of genetic polymorphisms with lifestyle behaviors, and from Courage-PD (7,369 cases, 7,018 controls; European ancestry) to estimate the association of these variants with PD. We used the inverse-variance weighted method to compute odds ratios (ORIVW) of PD and 95%confidence intervals (CI). Significance was determined using a Bonferroni-corrected significance threshold (p = 0.017). We found a significant inverse association between smoking initiation and PD (ORIVWper 1-SD increase in the prevalence of ever smoking = 0.74, 95%CI = 0.60–0.93, p = 0.009) without significant directional pleiotropy. Associations in participants ≤67 years old and cases with disease duration ≤7 years were of a similar size. No significant associations were observed for alcohol and coffee drinking. In reverse MR, genetic liability toward PD was not associated with smoking or coffee drinking but was positively associated with alcohol drinking. Our findings are in favor of an inverse association between smoking and PD that is not explained by reverse causation, confounding, and survival or incidence-prevalence biases. Genetic liability toward PD was positively associated with alcohol drinking. Conclusions on the association of alcohol and coffee drinking with PD are hampered by insufficient statistical power.

Published
2022
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16. Connecting environmental exposure and neurodegeneration using cheminformatics and high resolution mass spectrometry: potential and challenges

Author

Schymanski, Emma L., primary, Baker, Nancy C., additional, Williams, Antony J., additional, Singh, Randolph R., additional, Trezzi, Jean-Pierre, additional, Wilmes, Paul, additional, Kolber, Pierre L., additional, Kruger, Rejko, additional, Paczia, Nicole, additional, Linster, Carole L., additional, and Balling, Rudi, additional

Published
2019
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18. The Luxembourg Parkinson’s Study: A Comprehensive Approach for Stratification and Early Diagnosis

Author

Hipp, Geraldine, primary, Vaillant, Michel, additional, Diederich, Nico J., additional, Roomp, Kirsten, additional, Satagopam, Venkata P., additional, Banda, Peter, additional, Sandt, Estelle, additional, Mommaerts, Kathleen, additional, Schmitz, Sabine K., additional, Longhino, Laura, additional, Schweicher, Alexandra, additional, Hanff, Anne-Marie, additional, Nicolai, Béatrice, additional, Kolber, Pierre, additional, Reiter, Dorothea, additional, Pavelka, Lukas, additional, Binck, Sylvia, additional, Pauly, Claire, additional, Geffers, Lars, additional, Betsou, Fay, additional, Gantenbein, Manon, additional, Klucken, Jochen, additional, Gasser, Thomas, additional, Hu, Michele T., additional, Balling, Rudi, additional, and Krüger, Rejko, additional

Published
2018
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19. The Luxembourg Parkinson’s Study: A Comprehensive Approach for Stratification and Early Diagnosis

Author

Luxembourg Centre for Systems Biomedicine (LCSB) [research center], Hipp Epouse D'amico, Géraldine, Vaillant, Michel, Diederich, Nico J., Roomp, Kirsten, Satagopam, Venkata, Banda, Peter, Sandt, Estelle, Mommaerts, Kathleen, Schmitz, Sabine, Longhino, Laura, Schweicher, Alexandra, Hanff, Anne-Marie, Nicolai, Béatrice, Kolber, Pierre Luc, Reiter, Dorothea, Pavelka, Lukas, Binck, Sylvia, Pauly, Claire, Geffers, Lars, Betsou, Fay, Gantenbein, Manon, Klucken, Jochen, Gasser, Thomas, Hu, Michele, Balling, Rudi, Krüger, Rejko, Luxembourg Centre for Systems Biomedicine (LCSB) [research center], Hipp Epouse D'amico, Géraldine, Vaillant, Michel, Diederich, Nico J., Roomp, Kirsten, Satagopam, Venkata, Banda, Peter, Sandt, Estelle, Mommaerts, Kathleen, Schmitz, Sabine, Longhino, Laura, Schweicher, Alexandra, Hanff, Anne-Marie, Nicolai, Béatrice, Kolber, Pierre Luc, Reiter, Dorothea, Pavelka, Lukas, Binck, Sylvia, Pauly, Claire, Geffers, Lars, Betsou, Fay, Gantenbein, Manon, Klucken, Jochen, Gasser, Thomas, Hu, Michele, Balling, Rudi, and Krüger, Rejko

Abstract

While genetic advances have successfully defined part of the complexity in Parkinson’s disease (PD), the clinical characterization of phenotypes remains challenging. Therapeutic trials and cohort studies typically include patients with earlier disease stages and exclude comorbidities, thus ignoring a substantial part of the real-world PD population. To account for these limitations, we implemented the Luxembourg PD study as a comprehensive clinical, molecular and device-based approach including patients with typical PD and atypical parkinsonism, irrespective of their disease stage, age, comorbidities, or linguistic background. To provide a large, longitudinally followed, and deeply phenotyped set of patients and controls for clinical and fundamental research on PD, we implemented an open-source digital platform that can be harmonized with international PD cohort studies. Our interests also reflect Luxembourg-specific areas of PD research, including vision, gait, and cognition. This effort is flanked by comprehensive biosampling efforts assuring high quality and sustained availability of body liquids and tissue biopsies. We provide evidence for the feasibility of such a cohort program with deep phenotyping and high quality biosampling on parkinsonism in an environment with structural specificities and alert the international research community to our willingness to collaborate with other centers. The combination of advanced clinical phenotyping approaches including device-based assessment will create a comprehensive assessment of the disease and its variants, its interaction with comorbidities and its progression. We envision the Luxembourg Parkinson’s study as an important research platform for defining early diagnosis and progression markers that translate into stratified treatment approaches.

Published
2018

20. Lateralisation in Parkinson disease.

Author

Riederer, P., Jellinger, K. A., Kolber, Pierre Luc, Hipp, G., Sian-Hulsmann, J., Krüger, Rejko, Riederer, P., Jellinger, K. A., Kolber, Pierre Luc, Hipp, G., Sian-Hulsmann, J., and Krüger, Rejko

Abstract

Asymmetry of dopaminergic neurodegeneration and subsequent lateralisation of motor symptoms are distinctive features of Parkinson's disease compared to other forms of neurodegenerative or symptomatic parkinsonism. Even 200 years after the first description of the disease, the underlying causes for this striking clinicopathological feature are not yet fully understood. There is increasing evidence that lateralisation of disease is due to a complex interplay of hereditary and environmental factors that are reflected not only in the concept of dominant hemispheres and handedness but also in specific susceptibilities of neuronal subpopulations within the substantia nigra. As a consequence, not only the obvious lateralisation of motor symptoms occurs but also patterns of associated non-motor signs are defined, which include cognitive functions, sleep behaviour or olfaction. Better understanding of the mechanisms contributing to lateralisation of neurodegeneration and the resulting patterns of clinical phenotypes based on bilateral post-mortem brain analyses and clinical studies focusing on right/left hemispheric symptom origin will help to develop more targeted therapeutic approaches, taking into account subtypes of PD as a heterogeneous disorder.

Published
2018

21. Structural Brain Network Characteristics Can Differentiate CIS from Early RRMS

Author

Muthuraman, Muthuraman, Fleischer, Vinzenz, Kolber, Pierre, Lüssi, Felix, Zipp, Frauke, and Groppa, Sergiu

Subjects
610 Medical sciences, connectivity, 610 Medizin, cortical thickness, multiple sclerosis, diffusion tensor imaging, lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry, support vector machines, lcsh:RC321-571, Neuroscience, Original Research
Abstract

Focal demyelinated lesions, diffuse white matter (WM) damage and grey matter (GM) atrophy influence directly the disease progression in patients with multiple sclerosis. The aim of this study was to identify specific characteristics of GM and WM structural networks in subjects with clinically isolated syndrome (CIS) in comparison to patients with early relapsing-remitting multiple sclerosis (RRMS).Twenty patients with CIS, thirty three with RRMS and forty healthy subjects were investigated using 3 T-MRI. Diffusion tensor imaging was applied, together with probabilistic tractography and fractional anisotropy (FA) maps for WM and cortical thickness correlation analysis for GM, to determine the structural connectivity patterns. A network topology analysis with the aid of graph theoretical approaches was used to characterize the network at different community levels (modularity, clustering coefficient, global and local efficiencies). Finally, we applied support vector machines (SVM) to automatically discriminate the two groups. .In comparison to CIS subjects, patients with RRMS were found to have increased modular connectivity and higher local clustering, highlighting increased local processing in both GM and WM. Both groups presented increased modularity and clustering coefficients in comparison to healthy controls. SVM algorithms achieved 97% accuracy using the clustering coefficient as classifier derived from GM and 65% using WM from probabilistic tractography and 67 % from modularity of FA maps to differentiate between CIS and RRMS patients. We demonstrate a clear increase of modular and local connectivity in patients with early RRMS in comparison to CIS and healthy subjects. Based only on a single anatomic scan and without a priori information, we developed an automated and investigator-independent paradigm that can accurately discriminate between patients with these clinically similar disease entities, and could thus complement the current dissemination-in-time criteria for clinical diagnosis.

Published
2016

24. Classification of advanced stages of Parkinson's disease: translation into stratified treatments.

Author

Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], Fonds National de la Recherche - FnR [sponsor], European Commission - EC [sponsor], Krüger, Rejko, Klucken, Jochen, Weiss, Daniel, Tonges, Lars, Kolber, Pierre Luc, Unterecker, Stefan, Lorrain, Michael, Baas, Horst, Muller, Thomas, Riederer, Peter, Luxembourg Centre for Systems Biomedicine (LCSB): Clinical & Experimental Neuroscience (Krüger Group) [research center], Fonds National de la Recherche - FnR [sponsor], European Commission - EC [sponsor], Krüger, Rejko, Klucken, Jochen, Weiss, Daniel, Tonges, Lars, Kolber, Pierre Luc, Unterecker, Stefan, Lorrain, Michael, Baas, Horst, Muller, Thomas, and Riederer, Peter

Abstract

Advanced stages of Parkinson's disease (advPD) still impose a challenge in terms of classification and related stage-adapted treatment recommendations. Previous concepts that define advPD by certain milestones of motor disability apparently fall short in addressing the increasingly recognized complexity of motor and non-motor symptoms and do not allow to account for the clinical heterogeneity that require more personalized approaches. Therefore, deep phenotyping approaches are required to characterize the broad-scaled, continuous and multidimensional spectrum of disease-related motor and non-motor symptoms and their progression under real-life conditions. This will also facilitate the reasoning for clinical care and therapeutic decisions, as neurologists currently have to refer to clinical trials that provide guidance on a group level; however, this does not always account for the individual needs of patients. Here, we provide an overview on different classifications for advPD that translate into critical phenotypic patterns requiring the differential therapeutic adjustments. New concepts refer to precision medicine approaches also in PD and first studies on genetic stratification for therapeutic outcomes provide a potential for more objective treatment recommendations. We define novel treatment targets that align with this concept and make use of emerging device-based assessments of real-life information on PD symptoms. As these approaches require empowerment of patients and integration into treatment decisions, we present communication strategies and decision support based on new technologies to adjust treatment of advPD according to patient demands and safety.

Published
2017

25. Device-based assessment through a mobile application in the Luxembourg Parkinson Cohort

Author

Stallinger, Christian, Satagopam, Venkata, Banda, Peter, Kolber, Pierre, Suver, Christine, Trister, Andrew, Friend, Stephen, Rejko, Krüger, Stallinger, Christian, Satagopam, Venkata, Banda, Peter, Kolber, Pierre, Suver, Christine, Trister, Andrew, Friend, Stephen, and Rejko, Krüger

Abstract

Introduction: The project focuses on the integration device-based assessment (DBA) with a mobile application (mPower) into the longitudinal deeply-phenotyped HELP-PD (Health in the Elderly Luxembourgish Population with a focus on Parkinson’s disease) cohort for patients with Parkinsonism in Luxembourg and the Greater Region to monitor frequency and degree of variation in symptoms of Parkinsonism, to identify potential sources and modulators of variation and to evaluate how symptoms are correlated with these modulators across patients. Methods: We integrate for the first time the mPower iOS app into a deeply phenotyped cohort. mPower is one of the first apps to use Apple’s Research Kit framework and combines a traditional survey-based approach with more granular and precise data gained from a person’s iPhone related to sensor- (e.g. step count, GPS-tracking) or task-based assessments (e.g. finger tapping, tremor detection, sustained phonation, simple gait analysis, memory test). Anonymized longitudinal data is sent to a repository, then retrieved, matched, and correlated with conventional HELP-PD data from a total of 47 screening instruments for motor and non-motor functions in Parkinsonism obtained from annual visits of study participants. 14 patients with clinically confirmed IPD are currently included in the pilot phase. Results/Discussion: We modified the mPower app and successfully integrated it into HELP-PD’s novel database infrastructure, allowing for a wide variety of analyses. The reporting system is able to handle multiple DBAs, with the implementation of an in-depth gait analysis system currently pending. Considerable attention was given to data protection. The system is currently fully functional with the pilot phase having started in June 2016. First correlations with traditional clinical data are planned for early 2017.

Published
2017

28. Increased structural white and grey matter network connectivity compensates for functional decline in early multiple sclerosis.

Author

Fleischer, Vinzenz, Gröger, Adriane, Koirala, Nabin, Droby, Amgad, Muthuraman, Muthuraman, Kolber, Pierre, Reuter, Eva, Zipp, Frauke, Groppa, Sergiu, and Meuth, Sven G.

Subjects
MULTIPLE sclerosis diagnosis, MULTIPLE sclerosis treatment, GRAY matter (Nerve tissue), WHITE matter (Nerve tissue), CENTRAL nervous system diseases, MAGNETIC resonance imaging
Abstract

Background: The pathology of multiple sclerosis (MS) consists of demyelination and neuronal injury, which occur early in the disease; yet, remission phases indicate repair. Whether and how the central nervous system (CNS) maintains homeostasis to counteract clinical impairment is not known. Objective: We analyse the structural connectivity of white matter (WM) and grey matter (GM) networks to understand the absence of clinical decline as the disease progresses. Methods: A total of 138 relapsing–remitting MS patients (classified into six groups by disease duration) and 32 healthy controls were investigated using 3-Tesla magnetic resonance imaging (MRI). Networks were analysed using graph theoretical approaches based on connectivity patterns derived from diffusion-tensor imaging with probabilistic tractography for WM and voxel-based morphometry and regional-volume-correlation matrix for GM. Results: In the first year after disease onset, WM networks evolved to a structure of increased modularity, strengthened local connectivity and increased local clustering while no clinical decline occurred. GM networks showed a similar dynamic of increasing modularity. This modified connectivity pattern mainly involved the cerebellum, cingulum and temporo-parietal regions. Clinical impairment was associated at later disease stages with a divergence of the network patterns. Conclusion: Our findings suggest that network functionality in MS is maintained through structural adaptation towards increased local and modular connectivity, patterns linked to adaptability and homeostasis. [ABSTRACT FROM AUTHOR]

Published
2017
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29. Genome-wide association study of copy number variations in Parkinson's disease.

Author

Landoulsi Z, Sreelatha AAK, Schulte C, Bobbili DR, Montanucci L, Leu C, Niestroj LM, Hassanin E, Domenighetti C, Pavelka L, Sugier PE, Radivojkov-Blagojevic M, Lichtner P, Portugal B, Edsall C, Kru Ger J, Hernandez DG, Blauwendraat C, Mellick GD, Zimprich A, Pirker W, Tan M, Rogaeva E, Lang AE, Koks S, Taba P, Lesage S, Brice A, Corvol JC, Chartier-Harlin MC, Mutez E, Brockmann K, Deutschländer AB, Hadjigeorgiou GM, Dardiotis E, Stefanis L, Simitsi AM, Valente EM, Petrucci S, Straniero L, Zecchinelli A, Pezzoli G, Brighina L, Ferrarese C, Annesi G, Quattrone A, Gagliardi M, Burbulla LF, Matsuo H, Nakayama A, Hattori N, Nishioka K, Chung SJ, Kim YJ, Kolber P, van de Warrenburg BP, Bloem BR, Singleton AB, Toft M, Pihlstrom L, Guedes LC, Ferreira JJ, Bardien S, Carr J, Tolosa E, Ezquerra M, Pastor P, Wirdefeldt K, Pedersen NL, Ran C, Belin AC, Puschmann A, Clarke CE, Morrison KE, Krainc D, Farrer MJ, Lal D, Elbaz A, Gasser T, Krüger R, Sharma M, and May P

Abstract

Objective: Our study investigates the impact of copy number variations (CNVs) on Parkinson's disease (PD) pathogenesis using genome-wide data, aiming to uncover novel genetic mechanisms and improve the understanding of the role of CNVs in sporadic PD., Methods: We applied a sliding window approach to perform CNV-GWAS and conducted genome-wide burden analyses on CNV data from 11,035 PD patients (including 2,731 early-onset PD (EOPD)) and 8,901 controls from the COURAGE-PD consortium., Results: We identified 14 genome-wide significant CNV loci associated with PD, including one deletion and 13 duplications. Among these, duplications in 7q22.1, 11q12.3 and 7q33 displayed the highest effect. Two significant duplications overlapped with PD-related genes SNCA and VPS13C , but none overlapped with recent significant SNP-based GWAS findings. Five duplications included genes associated with neurological disease, and four overlapping genes were dosage-sensitive and intolerant to loss-of-function variants. Enriched pathways included neurodegeneration, steroid hormone biosynthesis, and lipid metabolism. In early-onset cases, four loci were significantly associated with EOPD, including three known duplications and one novel deletion in PRKN . CNV burden analysis showed a higher prevalence of CNVs in PD-related genes in patients compared to controls (OR=1.56 [1.18-2.09], p=0.0013), with PRKN showing the highest burden (OR=1.47 [1.10-1.98], p=0.026). Patients with CNVs in PRKN had an earlier disease onset. Burden analysis with controls and EOPD patients showed similar results., Interpretation: This is the largest CNV-based GWAS in PD identifying novel CNV regions and confirming the significant CNV burden in EOPD, primarily driven by the PRKN gene, warranting further investigation.

Published
2024
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30. Association of Body Mass Index and Parkinson Disease: A Bidirectional Mendelian Randomization Study.

Author

Domenighetti C, Sugier PE, Ashok Kumar Sreelatha A, Schulte C, Grover S, Portugal B, Lee PC, May P, Bobbili D, Radivojkov Blagojevic M, Lichtner P, Singleton AB, Hernandez D, Edsall C, Mellick GD, Zimprich AA, Pirker W, Rogaeva EA, Lang AE, Koks S, Taba P, Lesage S, Brice A, Corvol JC, Chartier-Harlin MC, Mutez E, Brockmann K, Deutschlander AB, Hadjigeorgiou GM, Dardiotis E, Stefanis L, Simitsi AM, Valente EM, Petrucci S, Straniero L, Zecchinelli AL, Pezzoli G, Brighina L, Ferrarese C, Annesi G, Quattrone A, Gagliardi M, Matsuo H, Nakayama A, Hattori N, Nishioka K, Chung SJ, Kim YJ, Kolber P, Van De Warrenburg BPC, Bloem BR, Toft M, Pihlstrøm L, Correia Guedes L, Ferreira JJ, Bardien S, Carr J, Tolosa E, Ezquerra M, Pastor P, Diez-Fairen M, Wirdefeldt K, Pedersen NL, Ran C, Belin AC, Puschmann A, Hellberg C, Clarke CE, Morrison KE, Tan MM, Krainc D, Burbulla LF, Farrer M, Kruger R, Gasser T, Sharma M, and Elbaz A

Subjects
Humans, Female, Male, Middle Aged, Aged, Risk Factors, Mendelian Randomization Analysis, Parkinson Disease genetics, Parkinson Disease epidemiology, Body Mass Index, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study
Abstract

Background and Objectives: The role of body mass index (BMI) in Parkinson disease (PD) is unclear. Based on the Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in PD (Courage-PD) consortium, we used 2-sample Mendelian randomization (MR) to replicate a previously reported inverse association of genetically predicted BMI with PD and investigated whether findings were robust in analyses addressing the potential for survival and incidence-prevalence biases. We also examined whether the BMI-PD relation is bidirectional by performing a reverse MR., Methods: We used summary statistics from a genome-wide association study (GWAS) to extract the association of 501 single-nucleotide polymorphisms (SNPs) with BMI and from the Courage-PD and international Parkinson Disease Genomics Consortium (iPDGC) to estimate their association with PD. Analyses are based on participants of European ancestry. We used the inverse-weighted method to compute odds ratios (OR IVW per 4.8 kg/m 2 [95% CI]) of PD and additional pleiotropy robust methods. We performed analyses stratified by age, disease duration, and sex. For reverse MR, we used SNPs associated with PD from 2 iPDGC GWAS to assess the effect of genetic liability toward PD on BMI., Results: Summary statistics for BMI are based on 806,834 participants (54% women). Summary statistics for PD are based on 8,919 (40% women) cases and 7,600 (55% women) controls from Courage-PD, and 19,438 (38% women) cases and 24,388 (51% women) controls from iPDGC. In Courage-PD, we found an inverse association between genetically predicted BMI and PD (OR IVW 0.82 [0.70-0.97], p = 0.012) without evidence for pleiotropy. This association tended to be stronger in younger participants (≤67 years, OR IVW 0.71 [0.55-0.92]) and cases with shorter disease duration (≤7 years, OR IVW 0.75 [0.62-0.91]). In pooled Courage-PD + iPDGC analyses, the association was stronger in women (OR IVW 0.85 [0.74-0.99], p = 0.032) than men (OR IVW 0.92 [0.80-1.04], p = 0.18), but the interaction was not statistically significant ( p -interaction = 0.48). In reverse MR, there was evidence for pleiotropy, but pleiotropy robust methods showed a significant inverse association., Discussion: Using an independent data set (Courage-PD), we replicate an inverse association of genetically predicted BMI with PD, not explained by survival or incidence-prevalence biases. Moreover, reverse MR analyses support an inverse association between genetic liability toward PD and BMI, in favor of a bidirectional relation.

Published
2024
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31. Luxembourg Parkinson's study -comprehensive baseline analysis of Parkinson's disease and atypical parkinsonism.

Author

Pavelka L, Rawal R, Ghosh S, Pauly C, Pauly L, Hanff AM, Kolber PL, Jónsdóttir SR, Mcintyre D, Azaiz K, Thiry E, Vilasboas L, Soboleva E, Giraitis M, Tsurkalenko O, Sapienza S, Diederich N, Klucken J, Glaab E, Aguayo GA, Jubal ER, Perquin M, Vaillant M, May P, Gantenbein M, Satagopam VP, and Krüger R

Abstract

Background: Deep phenotyping of Parkinson's disease (PD) is essential to investigate this fastest-growing neurodegenerative disorder. Since 2015, over 800 individuals with PD and atypical parkinsonism along with more than 800 control subjects have been recruited in the frame of the observational, monocentric, nation-wide, longitudinal-prospective Luxembourg Parkinson's study., Objective: To profile the baseline dataset and to explore risk factors, comorbidities and clinical profiles associated with PD, atypical parkinsonism and controls., Methods: Epidemiological and clinical characteristics of all 1,648 participants divided in disease and control groups were investigated. Then, a cross-sectional group comparison was performed between the three largest groups: PD, progressive supranuclear palsy (PSP) and controls. Subsequently, multiple linear and logistic regression models were fitted adjusting for confounders., Results: The mean (SD) age at onset (AAO) of PD was 62.3 (11.8) years with 15% early onset (AAO < 50 years), mean disease duration 4.90 (5.16) years, male sex 66.5% and mean MDS-UPDRS III 35.2 (16.3). For PSP, the respective values were: 67.6 (8.2) years, all PSP with AAO > 50 years, 2.80 (2.62) years, 62.7% and 53.3 (19.5). The highest frequency of hyposmia was detected in PD followed by PSP and controls (72.9%; 53.2%; 14.7%), challenging the use of hyposmia as discriminating feature in PD vs. PSP. Alcohol abstinence was significantly higher in PD than controls (17.6 vs. 12.9%, p  = 0.003)., Conclusion: Luxembourg Parkinson's study constitutes a valuable resource to strengthen the understanding of complex traits in the aforementioned neurodegenerative disorders. It corroborated several previously observed clinical profiles, and provided insight on frequency of hyposmia in PSP and dietary habits, such as alcohol abstinence in PD. Clinical trial registration : clinicaltrials.gov, NCT05266872., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2023 Pavelka, Rawal, Ghosh, Pauly, Pauly, Hanff, Kolber, Jónsdóttir, Mcintyre, Azaiz, Thiry, Vilasboas, Soboleva, Giraitis, Tsurkalenko, Sapienza, Diederich, Klucken, Glaab, Aguayo, Jubal, Perquin, Vaillant, May, Gantenbein, Satagopam, Krüger and on behalf of the NCER-PD Consortium.)

Published
2023
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