125 results on '"Lill, CM"'
Search Results
2. The impact of smoking on genome-wide DNA methylation in two longitudinal datasets from Germany
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Homann, J, Sommerer, Y, Deecke, L, Dobricic, V, Vetter, VM, Demuth, I, Berger, K, Bertram, L, Lill, CM, Homann, J, Sommerer, Y, Deecke, L, Dobricic, V, Vetter, VM, Demuth, I, Berger, K, Bertram, L, and Lill, CM
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- 2023
3. Genome-wide association study identifies TERT as a genetic determinant for skin aging
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Deecke, L, Ohlei, O, Homann, J, Dobricic, V, Hagelstein, V, Stagge, J, Steinhagen-Thiessen, E, Demuth, I, Bertram, L, Lill, CM, Deecke, L, Ohlei, O, Homann, J, Dobricic, V, Hagelstein, V, Stagge, J, Steinhagen-Thiessen, E, Demuth, I, Bertram, L, and Lill, CM
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- 2023
4. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels
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Hong, SJ, Dobricic, V, Ohlei, O, Bos, I, Vos, SJB, Prokopenko, D, Tijms, BM, Andreasson, U, Blennow, K, Vandenberghe, R, Gabel, S, Scheltens, P, Teunissen, CE, Engelborghs, S, Frisoni, G, Blin, O, Richardson, JC, Bordet, R, Lleo, A, Alcolea, D, Popp, J, Clark, C, Peyratout, G, Martinez-Lage, P, Tainta, M, Dobson, RJB, Legido-Quigley, C, Sleegers, K, Van Broeckhoven, C, Tanzi, RE, ten Kate, M, Wittig, M, Franke, A, Lill, CM, Barkhof, F, Lovestone, S, Streffer, J, Zetterberg, H, Visser, PJ, Bertram, L, and Neuroimaging Initiative
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s disease ,wide association study ,chitinase‐ ,like protein 1 ,neurogranin ,neurofilament light ,3‐ ,biomarker ,genome‐ ,Alzheimer&apos ,cerebrospinal fluid - Abstract
Introduction Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively. Methods We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates. Results We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1. Discussion Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD.
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- 2021
5. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility
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Patsopoulos, NA, Baranzini, SE, Santaniello, A, Shoostari, P, Cotsapas, C, Wong, G, Beecham, AH, James, T, Replogle, J, Vlachos, IS, McCabe, C, Pers, TH, Brandes, A, White, C, Keenan, B, Cimpean, M, Winn, P, Panteliadis, IP, Robbins, A, Andlauer, TFM, Zarzycki, O, Dubois, B, Goris, A, Sondergaard, HB, Sellebjerg, F, Sorensen, PS, Ullum, H, Thorner, LW, Saarela, J, Cournu-Rebeix, I, Damotte, V, Fontaine, B, Guillot-Noel, L, Lathrop, M, Vukusic, S, Berthele, A, Pongratz, V, Gasperi, C, Graetz, C, Grummel, V, Hemmer, B, Hoshi, M, Knier, B, Korn, T, Lill, CM, Luessi, F, Muhlau, M, Zipp, F, Dardiotis, E, Agliardi, C, Amoroso, A, Barizzone, N, Benedetti, MD, Bernardinelli, L, Cavalla, P, Clarelli, F, Comi, G, Cusi, D, Esposito, F, Ferre, L, Galimberti, D, Guaschino, C, Leone, MA, Martinelli, V, Moiola, L, Salvetti, M, Sorosina, M, Vecchio, D, Zauli, A, Santoro, S, Mancini, N, Zuccala, M, Mescheriakova, J, van Duijn, C, Bos, SD, Celius, EG, Spurkland, A, Comabella, M, Montalban, X, Alfredsson, L, Bomfim, IL, Gomez-Cabrero, D, Hillert, J, Jagodic, M, Linden, M, Piehl, F, Jelcic, I, Martin, R, Sospedra, M, Baker, A, Ban, M, Hawkins, C, Hysi, P, Kalra, S, Karpe, F, Khadake, J, Lachance, G, Molyneux, P, Neville, M, Thorpe, J, Bradshaw, E, Caillier, SJ, Calabresi, P, Cree, BAC, Cross, A, Davis, M, de Bakker, PWI, Delgado, S, Dembele, M, Edwards, K, Fitzgerald, K, Frohlich, IY, Gourraud, PA, Haines, JL, Hakonarson, H, Kimbrough, D, Isobe, N, Konidari, I, Lathi, E, Lee, MH, Li, T, An, D, Zimmer, A, Madireddy, L, Manrique, CP, Mitrovic, M, Olah, M, Patrick, E, Pericak-Vance, MA, Piccio, L, Schaefer, C, Weiner, H, Lage, K, Scott, RJ, Lechner-Scott, J, Leal, R, Moscato, P, Booth, DR, Stewart, GJ, Vucic, S, Pame, G, BamettO, M, Mason, D, GriffithS, L, Broadley, S, Tajouri, L, Baxter, A, Slee, M, Taylor, BV, Charlesworth, J, Kilpatrick, TJ, Rubio, J, Jokubaitis, V, Wiley, J, Butzkueven, H, Leslie, S, Motyer, A, Stankovich, J, Carroll, WM, Kermode, AG, Edrin, M, Barclay, M, Peyrin-Biroulet, L, Chamaillard, M, Colombe, JF, Cottone, M, Croft, A, D'Inca, R, Halfvarson, J, Hanigan, K, Henderson, P, Hugot, JP, Karban, A, Kennedy, NA, Khan, MA, Lemann, M, Levine, A, Massey, D, Milla, M, Motoey, GW, Ng, SME, Oikonomnou, J, Peeters, H, Proctor, DD, Rahier, JF, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, KM, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, MH, Zhang, H, Zhang, W, Donnelly, P, Barroso, I, Blackwe, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Strange, A, Sul, Z, Vukcevic, DA, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Compston, A, Hafler, D, Harbo, HF, Hauser, SL, Stewart, G, D'Alfonso, S, Hadjigeorgiou, G, Taylor, B, Barcellos, LF, Booth, D, Hintzen, R, Kockum, I, Martinelli-Boneschi, F, McCauley, JL, Oksenberg, JR, Oturai, A, Sawcer, S, Ivinson, AJ, Olsson, T, De Jager, PL, Patsopoulos, Na, Baranzini, Se, Santaniello, A, Shoostari, P, Cotsapas, C, Wong, G, Beecham, Ah, James, T, Replogle, J, Vlachos, I, Mccabe, C, Pers, Th, Brandes, A, White, C, Keenan, B, Cimpean, M, Winn, P, Panteliadis, Ip, Robbins, A, Andlauer, Tfm, Zarzycki, O, Dubois, B, Goris, A, Sondergaard, Hb, Sellebjerg, F, Sorensen, P, Ullum, H, Thorner, Lw, Saarela, J, Cournu-Rebeix, I, Damotte, V, Fontaine, B, Guillot-Noel, L, Lathrop, M, Vukusic, S, Berthele, A, Pongratz, V, Gasperi, C, Graetz, C, Grummel, V, Hemmer, B, Hoshi, M, Knier, B, Korn, T, Lill, Cm, Luessi, F, Muhlau, M, Zipp, F, Dardiotis, E, Agliardi, C, Amoroso, A, Barizzone, N, Benedetti, Md, Bernardinelli, L, Cavalla, P, Clarelli, F, Comi, G, Cusi, D, Esposito, F, Ferre, L, Galimberti, D, Guaschino, C, Leone, Ma, Martinelli, V, Moiola, L, Salvetti, M, Sorosina, M, Vecchio, D, Zauli, A, Santoro, S, Mancini, N, Zuccala, M, Mescheriakova, J, van Duijn, C, Bos, Sd, Celius, Eg, Spurkland, A, Comabella, M, Montalban, X, Alfredsson, L, Bomfim, Il, Gomez-Cabrero, D, Hillert, J, Jagodic, M, Linden, M, Piehl, F, Jelcic, I, Martin, R, Sospedra, M, Baker, A, Ban, M, Hawkins, C, Hysi, P, Kalra, S, Karpe, F, Khadake, J, Lachance, G, Molyneux, P, Neville, M, Thorpe, J, Bradshaw, E, Caillier, Sj, Calabresi, P, Cree, Bac, Cross, A, Davis, M, de Bakker, Pwi, Delgado, S, Dembele, M, Edwards, K, Fitzgerald, K, Frohlich, Iy, Gourraud, Pa, Haines, Jl, Hakonarson, H, Kimbrough, D, Isobe, N, Konidari, I, Lathi, E, Lee, Mh, Li, T, An, D, Zimmer, A, Madireddy, L, Manrique, Cp, Mitrovic, M, Olah, M, Patrick, E, Pericak-Vance, Ma, Piccio, L, Schaefer, C, Weiner, H, Lage, K, Scott, Rj, Lechner-Scott, J, Leal, R, Moscato, P, Booth, Dr, Stewart, Gj, Vucic, S, Pame, G, Bametto, M, Mason, D, Griffiths, L, Broadley, S, Tajouri, L, Baxter, A, Slee, M, Taylor, Bv, Charlesworth, J, Kilpatrick, Tj, Rubio, J, Jokubaitis, V, Wiley, J, Butzkueven, H, Leslie, S, Motyer, A, Stankovich, J, Carroll, Wm, Kermode, Ag, Edrin, M, Barclay, M, Peyrin-Biroulet, L, Chamaillard, M, Colombe, Jf, Cottone, M, Croft, A, D'Inca, R, Halfvarson, J, Hanigan, K, Henderson, P, Hugot, Jp, Karban, A, Kennedy, Na, Khan, Ma, Lemann, M, Levine, A, Massey, D, Milla, M, Motoey, Gw, Ng, Sme, Oikonomnou, J, Peeters, H, Proctor, Dd, Rahier, Jf, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, Km, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, Mh, Zhang, H, Zhang, W, Donnelly, P, Barroso, I, Blackwe, Jm, Bramon, E, Brown, Ma, Casas, Jp, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, H, Mathew, Cg, Palmer, Cna, Plomin, R, Rautanen, A, Sawcer, Sj, Trembath, Rc, Viswanathan, Ac, Wood, Nw, Spencer, Cca, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Strange, A, Sul, Z, Vukcevic, Da, Langford, C, Hunt, Se, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Compston, A, Hafler, D, Harbo, Hf, Hauser, Sl, Stewart, G, D'Alfonso, S, Hadjigeorgiou, G, Taylor, B, Barcellos, Lf, Booth, D, Hintzen, R, Kockum, I, Martinelli-Boneschi, F, Mccauley, Jl, Oksenberg, Jr, Oturai, A, Sawcer, S, Ivinson, Aj, Olsson, T, De Jager, Pl, Neurology, and Immunology
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0301 basic medicine ,Multiple Sclerosis ,Quantitative Trait Loci ,Inheritance Patterns ,Cell Cycle Proteins ,Genome-wide association study ,Biology ,Major histocompatibility complex ,Polymorphism, Single Nucleotide ,Major Histocompatibility Complex ,Transcriptome ,03 medical and health sciences ,0302 clinical medicine ,Immune system ,Gene Frequency ,Autoimmune Process ,medicine ,Humans ,RNA-Seq ,X chromosome ,Genetics ,Chromosomes, Human, X ,Multidisciplinary ,Microglia ,Multiple sclerosis ,GTPase-Activating Proteins ,Chromosome Mapping ,Genomics ,medicine.disease ,3. Good health ,030104 developmental biology ,medicine.anatomical_structure ,Genetic Loci ,Case-Control Studies ,biology.protein ,Genome-Wide Association Study ,030217 neurology & neurosurgery - Abstract
Genetic roots of multiple sclerosis The genetics underlying who develops multiple sclerosis (MS) have been difficult to work out. Examining more than 47,000 cases and 68,000 controls with multiple genome-wide association studies, the International Multiple Sclerosis Genetics Consortium identified more than 200 risk loci in MS (see the Perspective by Briggs). Focusing on the best candidate genes, including a model of the major histocompatibility complex region, the authors identified statistically independent effects at the genome level. Gene expression studies detected that every major immune cell type is enriched for MS susceptibility genes and that MS risk variants are enriched in brain-resident immune cells, especially microglia. Up to 48% of the genetic contribution of MS can be explained through this analysis. Science , this issue p. eaav7188 ; see also p. 1383
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- 2019
6. Critical evaluation of DNA methylation markers for type-2-diabetes risk prediction
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Krause, C, additional, Sievert, H, additional, Grohs, M, additional, Geißler, C, additional, El Gammal, AT, additional, Wolter, S, additional, Lill, CM, additional, Krämer, UM, additional, Kasten, M, additional, Klein, C, additional, Brabant, G, additional, Mann, O, additional, Lehnert, H, additional, and Kirchner, H, additional
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- 2018
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7. Genome-wide meta-analysis associates HLA-DQA1/DRB1 and LPA and lifestyle factors with human longevity
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Joshi, PK, Pirastu, N, Kentistou, KA, Fischer, K, Hofer, E, Schraut, KE, Clark, DW, Nutile, T, Barnes, CLK, Timmers, P, Shen, X, Gandin, I, McDaid, AF, Hansen, TF, Gordon, SD, Giulianini, F, Boutin, TS, Abdellaoui, A, Zhao, W, Medina-Gomez, C, Bartz, TM, Trompet, S, Lange, LA, Raffield, L, van der Spek, Ashley, Galesloot, TE, Proitsi, P, Yanek, LR, Bielak, LF, Payton, A, Murgia, F, Concas, MP, Biino, G, Tajuddin, S M, Seppala, I, Amin, Najaf, Boerwinkle, E, Borglum, AD, Campbell, A (Archie), Demerath, EW, Demuth, I, Faul, JD, Ford, I, Gialluisi, A, Gogele, M, Graff, M, Hingorani, A, Hottenga, JJ, Hougaard, DM, Hurme, MA, Ikram, Arfan, Jylha, M, Kuh, D, Ligthart, L, Lill, CM, Lindenberger, U, Lumley, T, Magi, R, Marques-Vidal, P, Medland, SE, Milani, L, Nagy, R, Ollier, WER, Peyser, PA, Pramstaller, PP, Ridker, PM, Rivadeneira, F, Ruggiero, D, Saba, Y, Schmidt, R, Schmidt, H, Slagboom, PE (Eline), Smith, BH, Smith, JA, Sotoodehnia, N, Steinhagen-Thiessen, E, van Rooij, FJA, Verbeek, AL, Vermeulen, SH, Vollenweider, P, Wang, YP, Werge, T, Whitfield, JB, Zonderman, AB, Lehtimaki, T, Evans, MK, Pirastu, M, Fuchsberger, C, Bertram, L, Pendleton, N, Kardia, SLR, Ciullo, M, Becker, DM, Wong, A, Psaty, BM, Duijn, Cornelia, Wilson, JG, Jukema, JW, Kiemeney, L, Uitterlinden, André, Franceschini, N, North, KE, Weir, DR, Metspalu, A, Boomsma, DI, Hayward, C, Chasman, D, Martin, NG, Sattar, N, Campbell, H, Esko, T, Kutalik, Z, Wilson, JF, Joshi, PK, Pirastu, N, Kentistou, KA, Fischer, K, Hofer, E, Schraut, KE, Clark, DW, Nutile, T, Barnes, CLK, Timmers, P, Shen, X, Gandin, I, McDaid, AF, Hansen, TF, Gordon, SD, Giulianini, F, Boutin, TS, Abdellaoui, A, Zhao, W, Medina-Gomez, C, Bartz, TM, Trompet, S, Lange, LA, Raffield, L, van der Spek, Ashley, Galesloot, TE, Proitsi, P, Yanek, LR, Bielak, LF, Payton, A, Murgia, F, Concas, MP, Biino, G, Tajuddin, S M, Seppala, I, Amin, Najaf, Boerwinkle, E, Borglum, AD, Campbell, A (Archie), Demerath, EW, Demuth, I, Faul, JD, Ford, I, Gialluisi, A, Gogele, M, Graff, M, Hingorani, A, Hottenga, JJ, Hougaard, DM, Hurme, MA, Ikram, Arfan, Jylha, M, Kuh, D, Ligthart, L, Lill, CM, Lindenberger, U, Lumley, T, Magi, R, Marques-Vidal, P, Medland, SE, Milani, L, Nagy, R, Ollier, WER, Peyser, PA, Pramstaller, PP, Ridker, PM, Rivadeneira, F, Ruggiero, D, Saba, Y, Schmidt, R, Schmidt, H, Slagboom, PE (Eline), Smith, BH, Smith, JA, Sotoodehnia, N, Steinhagen-Thiessen, E, van Rooij, FJA, Verbeek, AL, Vermeulen, SH, Vollenweider, P, Wang, YP, Werge, T, Whitfield, JB, Zonderman, AB, Lehtimaki, T, Evans, MK, Pirastu, M, Fuchsberger, C, Bertram, L, Pendleton, N, Kardia, SLR, Ciullo, M, Becker, DM, Wong, A, Psaty, BM, Duijn, Cornelia, Wilson, JG, Jukema, JW, Kiemeney, L, Uitterlinden, André, Franceschini, N, North, KE, Weir, DR, Metspalu, A, Boomsma, DI, Hayward, C, Chasman, D, Martin, NG, Sattar, N, Campbell, H, Esko, T, Kutalik, Z, and Wilson, JF
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- 2017
8. Gene-Environment Interaction in Parkinson's Disease: Coffee, ADORA2A, and CYP1A2
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Chuang, Y-H, Lill, CM, Lee, P-C, Hansen, J, Lassen, CF, Bertram, L, Greene, N, Sinsheimer, JS, and Ritz, B
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Male ,Aging ,Epidemiology ,Denmark ,Parkinson's disease ,Cytochrome P450 1A2 ,Adenosine A2A receptor ,Neurodegenerative ,Coffee ,Cytochrome P450 1A2 (CYP1A2) ,Adenosine A2A ,Cytochrome P-450 CYP1A2 ,Risk Factors ,Caffeine ,Genetics ,Humans ,2.1 Biological and endogenous factors ,Polymorphism ,Aetiology ,Aged ,Prevention ,Neurosciences ,Parkinson Disease ,Single Nucleotide ,Middle Aged ,Brain Disorders ,Meta-analysis ,Neurological ,Public Health and Health Services ,Adenosine A2A receptor (ADORA2A) ,Female ,Gene-Environment Interaction ,Receptor - Abstract
Background and purposeDrinking caffeinated coffee has been reported to provide protection against Parkinson's disease (PD). Caffeine is an adenosine A2A receptor (encoded by the gene ADORA2A) antagonist that increases dopaminergic neurotransmission and Cytochrome P450 1A2 (gene: CYP1A2) metabolizes caffeine; thus, gene polymorphisms in ADORA2A and CYP1A2 may influence the effect coffee consumption has on PD risk.MethodsIn a population-based case-control study (PASIDA) in Denmark (1,556 PD patients and 1,606 birth year- and gender-matched controls), we assessed interactions between lifetime coffee consumption and 3 polymorphisms in ADORA2A and CYP1A2 for all subjects, and incident and prevalent PD cases separately using logistic regression models. We also conducted a meta-analysis combining our results with those from previous studies.ResultsWe estimated statistically significant interactions for ADORA2A rs5760423 and heavy vs. light coffee consumption in incident (OR interaction = 0.66 [95% CI 0.46-0.94], p = 0.02) but not prevalent PD. We did not observe interactions for CYP1A2 rs762551 and rs2472304 in incident or prevalent PD. In meta-analyses, PD associations with daily coffee consumption were strongest among carriers of variant alleles in both ADORA2A and CYP1A2.ConclusionWe corroborated results from a previous report that described interactions between ADORA2A and CYP1A2 polymorphisms and coffee consumption. Our results also suggest that survivor bias may affect results of studies that enroll prevalent PD cases.
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- 2016
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9. Serum iron levels and the risk of Parkinson Disease: a Mendelian randomization study
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Pichler I, Del Greco M. F, Gögele M, Lill CM, Bertram L, Do CB, Eriksson N, Foroud T, Myers RH, PD GWAS Consortium, Nalls M, Keller MF, International Parkinson's Disease Genomics Consortium, Wellcome Trust Case Control Consortium 2, Benyamin B, Whitfield JB, Genetics of Iron Status Consortium, Pramstaller PP, Hicks AA, Thompson JR, Minelli C., Plagnol V, Hernandez DG, Sharma M, Sheerin UM, Saad M, Simón Sánchez J, Schulte C, Lesage S, Arepalli S, Barker R, Ben Shlomo Y, Berendse HW, Berg D, Bhatia K, de Bie RM, Biffi A, Bloem B, Bochdanovits Z, Bonin M, Bras JM, Brockmann K, Brooks J, Burn DJ, Charlesworth G, Chen H, Chinnery PF, Chong S, Clarke CE, Cookson MR, Cooper JM, Corvol JC, Counsell C, Damier P, Dartigues JF, Deloukas P, Deuschl G, Dexter DT, van Dijk KD, Dillman A, Durif F, Dürr A, Edkins S, Evans JR, Foltynie T, Gao J, Gardner M, Gibbs JR, Goate A, Gray E, Guerreiro R, Harris C, van Hilten JJ, Hofman A, Hollenbeck A, Holton J, Hu M, Huang X, Huber H, Hudson G, Hunt SE, Illig T, Lambert JC, Langford C, Lees A, Lichtner P, Limousin P, Lopez G, Lorenz D, McNeill A, Moorby C, Moore M, Morris HR, Morrison KE, Mudanohwo E, O'Sullivan SS, Pearson J, Perlmutter JS, Pollak P, Post B, Potter S, Ravina B, Revesz T, Riess O, Rivadeneira F, Rizzu P, Ryten M, Sawcer S, Schapira A, Scheffer H, Shaw K, Shoulson I, Sidransky E, Smith C, Spencer CC, Stockton JD, Strange A, Talbot K, Tanner CM, Tashakkori Ghanbaria A, Trabzuni D, Traynor BJ, Uitterlinden AG, Velseboer D, Vidailhet M, Walker R, van de Warrenburg B, Wickremaratchi M, Williams N, Williams Gray CH, Winder Rhodes S, Martinez M, Hardy J, Heutink P, Brice A, Gasser T, Singleton AB, Wood NW, Donnelly P, Barroso I, Blackwell JM, Bramon E, Brown MA, Casas JP, Corvin A, Duncanson A, Jankowski J, Markus HS, Mathew CG, Palmer CN, Plomin R, Rautanen A, Sawcer SJ, Trembath RC, Viswanathan AC, Band G, Bellenguez C, Freeman C, Hellenthal G, Giannoulatou E, Pirinen M, Pearson R, Su Z, Vukcevic D, Gwilliam R, Blackburn H, Bumpstead SJ, Dronov S, Gillman M, Hammond N, Jayakumar A, McCann OT, Liddle J, Potter SC, Ravindrarajah R, Ricketts M, Waller M, Weston P, Widaa S, Whittaker P, McCarthy MI, Ouwehand WH, Radhakrishnan A, Sambrook J, Toniolo D, Camaschella C, Metspalu A, Esko T, Gieger C, Ried J, Meitinger T, Oexle K, Winkelmann J, Swinkels D, Vermeulen S, van Duijn C, Broer L, Beilby J, Hui J, Anderson D, Visscher P, Martin N., TRAGLIA, MICHELA, Pichler, Irene, Del Greco M, Fabiola, Gögele, Martin, Lill, Christina M, Benyamin, Beben, Minelli, Cosetta, PD GWAS Consortium, International Parkinson’s Disease Genomics Consortium, Wellcome Trust Case Control Consortium, Genetics of Iron Status Consortium, Pollak, Pierre, Functional Genomics, Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease, Human genetics, NCA - Brain mechanisms in health and disease, ANS - Amsterdam Neuroscience, Neurology, Graduate School, Pichler, I, Del Greco M., F, Gögele, M, Lill, Cm, Bertram, L, Do, Cb, Eriksson, N, Foroud, T, Myers, Rh, PD GWAS, Consortium, Nalls, M, Keller, Mf, International Parkinson's Disease Genomics, Consortium, Wellcome Trust Case Control Consortium, 2, Benyamin, B, Whitfield, Jb, Genetics of Iron Status, Consortium, Pramstaller, Pp, Hicks, Aa, Thompson, Jr, Minelli, C., Plagnol, V, Hernandez, Dg, Sharma, M, Sheerin, Um, Saad, M, Simón Sánchez, J, Schulte, C, Lesage, S, Arepalli, S, Barker, R, Ben Shlomo, Y, Berendse, Hw, Berg, D, Bhatia, K, de Bie, Rm, Biffi, A, Bloem, B, Bochdanovits, Z, Bonin, M, Bras, Jm, Brockmann, K, Brooks, J, Burn, Dj, Charlesworth, G, Chen, H, Chinnery, Pf, Chong, S, Clarke, Ce, Cookson, Mr, Cooper, Jm, Corvol, Jc, Counsell, C, Damier, P, Dartigues, Jf, Deloukas, P, Deuschl, G, Dexter, Dt, van Dijk, Kd, Dillman, A, Durif, F, Dürr, A, Edkins, S, Evans, Jr, Foltynie, T, Gao, J, Gardner, M, Gibbs, Jr, Goate, A, Gray, E, Guerreiro, R, Harris, C, van Hilten, Jj, Hofman, A, Hollenbeck, A, Holton, J, Hu, M, Huang, X, Huber, H, Hudson, G, Hunt, Se, Illig, T, Lambert, Jc, Langford, C, Lees, A, Lichtner, P, Limousin, P, Lopez, G, Lorenz, D, Mcneill, A, Moorby, C, Moore, M, Morris, Hr, Morrison, Ke, Mudanohwo, E, O'Sullivan, S, Pearson, J, Perlmutter, J, Pollak, P, Post, B, Potter, S, Ravina, B, Revesz, T, Riess, O, Rivadeneira, F, Rizzu, P, Ryten, M, Sawcer, S, Schapira, A, Scheffer, H, Shaw, K, Shoulson, I, Sidransky, E, Smith, C, Spencer, Cc, Stockton, Jd, Strange, A, Talbot, K, Tanner, Cm, Tashakkori Ghanbaria, A, Trabzuni, D, Traynor, Bj, Uitterlinden, Ag, Velseboer, D, Vidailhet, M, Walker, R, van de Warrenburg, B, Wickremaratchi, M, Williams, N, Williams Gray, Ch, Winder Rhodes, S, Martinez, M, Hardy, J, Heutink, P, Brice, A, Gasser, T, Singleton, Ab, Wood, Nw, Donnelly, P, Barroso, I, Blackwell, Jm, Bramon, E, Brown, Ma, Casas, Jp, Corvin, A, Duncanson, A, Jankowski, J, Markus, H, Mathew, Cg, Palmer, Cn, Plomin, R, Rautanen, A, Sawcer, Sj, Trembath, Rc, Viswanathan, Ac, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Su, Z, Vukcevic, D, Gwilliam, R, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Hammond, N, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Mccarthy, Mi, Ouwehand, Wh, Radhakrishnan, A, Sambrook, J, Toniolo, D, Traglia, Michela, Camaschella, C, Metspalu, A, Esko, T, Gieger, C, Ried, J, Meitinger, T, Oexle, K, Winkelmann, J, Swinkels, D, Vermeulen, S, van Duijn, C, Broer, L, Beilby, J, Hui, J, Anderson, D, Visscher, P, and Martin, N.
- Subjects
Relative risk reduction ,Iron ,Mendelian randomization analysis ,Physiology ,Genome-wide association study ,Biology ,Bioinformatics ,03 medical and health sciences ,0302 clinical medicine ,SDG 17 - Partnerships for the Goals ,Risk Factors ,Mendelian randomization ,medicine ,Humans ,Genetic Predisposition to Disease ,Iron/blood ,Genetic Association Studies ,030304 developmental biology ,0303 health sciences ,medicine.diagnostic_test ,Parkinson Disease/blood/genetics ,Confounding ,Parkinson Disease ,Mendelian Randomization Analysis ,General Medicine ,Iron metabolism ,3. Good health ,ddc:616.8 ,Parkinson disease ,Meta-analysis ,Hereditary hemochromatosis ,Serum iron ,Medicine ,030217 neurology & neurosurgery ,Research Article - Abstract
In this study, Mendelian randomization was used to study genes known to modify iron levels, and the effect of iron on Parkinson's disease (PD) risk was estimated. Based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date, the findings suggest that increased iron levels in the blood are associated with a 3% reduction in the risk of Parkinson's disease for every 10 µg/dL increase in iron. The results of this analysis have potentially important implications for future research into the prevention of Parkinson's disease. Please see later in the article for the Editors' Summary, Background Although levels of iron are known to be increased in the brains of patients with Parkinson disease (PD), epidemiological evidence on a possible effect of iron blood levels on PD risk is inconclusive, with effects reported in opposite directions. Epidemiological studies suffer from problems of confounding and reverse causation, and mendelian randomization (MR) represents an alternative approach to provide unconfounded estimates of the effects of biomarkers on disease. We performed a MR study where genes known to modify iron levels were used as instruments to estimate the effect of iron on PD risk, based on estimates of the genetic effects on both iron and PD obtained from the largest sample meta-analyzed to date. Methods and Findings We used as instrumental variables three genetic variants influencing iron levels, HFE rs1800562, HFE rs1799945, and TMPRSS6 rs855791. Estimates of their effect on serum iron were based on a recent genome-wide meta-analysis of 21,567 individuals, while estimates of their effect on PD risk were obtained through meta-analysis of genome-wide and candidate gene studies with 20,809 PD cases and 88,892 controls. Separate MR estimates of the effect of iron on PD were obtained for each variant and pooled by meta-analysis. We investigated heterogeneity across the three estimates as an indication of possible pleiotropy and found no evidence of it. The combined MR estimate showed a statistically significant protective effect of iron, with a relative risk reduction for PD of 3% (95% CI 1%–6%; p = 0.001) per 10 µg/dl increase in serum iron. Conclusions Our study suggests that increased iron levels are causally associated with a decreased risk of developing PD. Further studies are needed to understand the pathophysiological mechanism of action of serum iron on PD risk before recommendations can be made. Please see later in the article for the Editors' Summary, Editors' Summary Background Parkinson disease is a degenerative disorder of the central nervous system caused by the death of dopamine-generating cells in the substania nigra, a region of the midbrain. The earliest symptoms are usually movement-related and include tremor, slow movements, and difficulty walking, and later cognitive and behavioral problems may arise, with dementia commonly occurring in the advanced stages of the disease. Parkinson disease affects around ten million people world-wide and incidence increases with age, with men more affected than women. To date, the causes of Parkinson disease remain unknown although a combination of genetic and environmental factors is thought to play a role. Identifying possible modifiable risks is an important step in the possible prevention of Parkinson disease. Why Was This Study Done? Previous studies have shown a possible association between lower blood levels of iron in people with Parkinson disease compared with controls, although the quality of these studies makes this finding difficult to interpret. So in this study, the researchers used a mendelian randomization approach to investigate whether there was any evidence of an effect of blood iron levels on the risk of Parkinson disease and if so to further explore the direction and scale of any link. Mendelian randomization is a method of using measured variation in genes of known function to examine the causal effect of a modifiable exposure on disease in situations where it is inappropriate to perform a randomized controlled trial. What Did the Researchers Do and Find? The researchers estimated the effect of blood iron levels on the risk of Parkinson disease using three polymorphisms in two genes, HFE and TMPRSS6. For each polymorphism, they performed a meta-analysis combining the results of studies investigating the genetic effect on iron levels, which included almost 22,000 people from Europe and Australia, and a meta-analysis of studies investigating the genetic effect on the risk of Parkinson disease, which included a total of 20,809 people with Parkinson disease and 88,892 controls from Europe and North America. They then performed three separate mendelian randomization analyses to estimate the effect of iron on Parkinson disease for the three polymorphisms. By combining the three estimates, they obtained a statistically significant odds ratio of 0.97 for Parkinson disease per 10 µg/dl increase in iron, corresponding to a 3% reduction in the risk of Parkinson disease for every 10 µg/dl increase in blood iron. Since genotype influences on blood iron levels represent differences that generally persist throughout adult life, the combined mendelian randomization estimate reflects an effect of iron over the course of a lifetime. What Do These Findings Mean? These findings suggest that increased iron levels in the blood are associated with a 3% reduction in the risk of Parkinson disease for every 10 µg/dl increase in iron. This finding is important as it suggests that increased blood iron levels may have a protective effect against Parkinson disease, although the underlying mechanism remains unclear. Furthermore, although mendelian randomization is an increasingly used approach to address the issue of classical confounding, there may be remaining confounding factors specific of mendelian randomization that may influence the interpretation of this study. Nevertheless, the results of this analysis have potentially important implications for future research into the prevention of Parkinson disease. Further studies on the underlying mechanisms are needed before any specific treatment recommendations can be proposed. Additional Information Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001462. The National Institutes of Neurological Disorder and Stroke, MedlinePlus, and NHS Choices have several pages with comprehensive information on Parkinson disease Wikipedia gives an explanation of mendelian randomization (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
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- 2013
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10. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
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Beecham, AH, Patsopoulos, NA, Xifara, DK, Davis, MF, Kemppinen, A, Cotsapas, C, Shah, TS, Spencer, C, Booth, D, Goris, A, Oturai, A, Saarela, J, Fontaine, B, Hemmer, B, Martin, C, Zipp, F, D'Alfonso, S, Martinelli-Boneschi, F, Taylor, B, Harbo, HF, Kockum, I, Hillert, J, Olsson, T, Ban, M, Oksenberg, JR, Hintzen, R, Barcellos, LF, Agliardi, C, Alfredsson, L, Alizadeh, M, Anderson, C, Andrews, R, Sondergaard, HB, Baker, A, Band, G, Baranzini, SE, Barizzone, N, Barrett, J, Bellenguez, C, Bergamaschi, L, Bernardinelli, L, Berthele, A, Biberacher, V, Binder, TMC, Blackburn, H, Bomfim, IL, Brambilla, P, Broadley, S, Brochet, B, Brundin, L, Buck, D, Butzkueven, H, Caillier, SJ, Camu, W, Carpentier, W, Cavalla, P, Celius, EG, Coman, I, Comi, G, Corrado, L, Cosemans, L, Cournu-Rebeix, I, Cree, BAC, Cusi, D, Damotte, V, Defer, G, Delgado, SR, Deloukas, P, di Sapio, A, Dilthey, AT, Donnelly, P, Dubois, B, Duddy, M, Edkins, S, Elovaara, I, Esposito, F, Evangelou, N, Fiddes, B, Field, J, Franke, A, Freeman, C, Frohlich, IY, Galimberti, D, Gieger, C, Gourraud, P-A, Graetz, C, Graham, A, Grummel, V, Guaschino, C, Hadjixenofontos, A, Hakonarson, H, Halfpenny, C, Hall, G, Hall, P, Hamsten, A, Harley, J, Harrower, T, Hawkins, C, Hellenthal, G, Hillier, C, Hobart, J, Hoshi, M, Hunt, SE, Jagodic, M, Jelcic, I, Jochim, A, Kendall, B, Kermode, A, Kilpatrick, T, Koivisto, K, Konidari, I, Korn, T, Kronsbein, H, Langford, C, Larsson, M, Lathrop, M, Lebrun-Frenay, C, Lechner-Scott, J, Lee, MH, Leone, MA, Leppa, V, Liberatore, G, Lie, BA, Lill, CM, Linden, M, Link, J, Luessi, F, Lycke, J, Macciardi, F, Mannisto, S, Manrique, CP, Martin, R, Martinelli, V, Mason, D, Mazibrada, G, McCabe, C, Mero, I-L, Mescheriakova, J, Moutsianas, L, Myhr, K-M, Nagels, G, Nicholas, R, Nilsson, P, Piehl, F, Pirinen, M, Price, SE, Quach, H, Reunanen, M, Robberecht, W, Robertson, NP, Rodegher, M, Rog, D, Salvetti, M, Schnetz-Boutaud, NC, Sellebjerg, F, Selter, RC, Schaefer, C, Shaunak, S, Shen, L, Shields, S, Siffrin, V, Slee, M, Sorensen, PS, Sorosina, M, Sospedra, M, Spurkland, A, Strange, A, Sundqvist, E, Thijs, V, Thorpe, J, Ticca, A, Tienari, P, van Duijn, C, Visser, EM, Vucic, S, Westerlind, H, Wiley, JS, Wilkins, A, Wilson, JF, Winkelmann, J, Zajicek, J, Zindler, E, Haines, JL, Pericak-Vance, MA, Ivinson, AJ, Stewart, G, Hafler, D, Hauser, SL, Compston, A, McVean, G, De Jager, P, Sawcer, SJ, McCauley, JL, Beecham, AH, Patsopoulos, NA, Xifara, DK, Davis, MF, Kemppinen, A, Cotsapas, C, Shah, TS, Spencer, C, Booth, D, Goris, A, Oturai, A, Saarela, J, Fontaine, B, Hemmer, B, Martin, C, Zipp, F, D'Alfonso, S, Martinelli-Boneschi, F, Taylor, B, Harbo, HF, Kockum, I, Hillert, J, Olsson, T, Ban, M, Oksenberg, JR, Hintzen, R, Barcellos, LF, Agliardi, C, Alfredsson, L, Alizadeh, M, Anderson, C, Andrews, R, Sondergaard, HB, Baker, A, Band, G, Baranzini, SE, Barizzone, N, Barrett, J, Bellenguez, C, Bergamaschi, L, Bernardinelli, L, Berthele, A, Biberacher, V, Binder, TMC, Blackburn, H, Bomfim, IL, Brambilla, P, Broadley, S, Brochet, B, Brundin, L, Buck, D, Butzkueven, H, Caillier, SJ, Camu, W, Carpentier, W, Cavalla, P, Celius, EG, Coman, I, Comi, G, Corrado, L, Cosemans, L, Cournu-Rebeix, I, Cree, BAC, Cusi, D, Damotte, V, Defer, G, Delgado, SR, Deloukas, P, di Sapio, A, Dilthey, AT, Donnelly, P, Dubois, B, Duddy, M, Edkins, S, Elovaara, I, Esposito, F, Evangelou, N, Fiddes, B, Field, J, Franke, A, Freeman, C, Frohlich, IY, Galimberti, D, Gieger, C, Gourraud, P-A, Graetz, C, Graham, A, Grummel, V, Guaschino, C, Hadjixenofontos, A, Hakonarson, H, Halfpenny, C, Hall, G, Hall, P, Hamsten, A, Harley, J, Harrower, T, Hawkins, C, Hellenthal, G, Hillier, C, Hobart, J, Hoshi, M, Hunt, SE, Jagodic, M, Jelcic, I, Jochim, A, Kendall, B, Kermode, A, Kilpatrick, T, Koivisto, K, Konidari, I, Korn, T, Kronsbein, H, Langford, C, Larsson, M, Lathrop, M, Lebrun-Frenay, C, Lechner-Scott, J, Lee, MH, Leone, MA, Leppa, V, Liberatore, G, Lie, BA, Lill, CM, Linden, M, Link, J, Luessi, F, Lycke, J, Macciardi, F, Mannisto, S, Manrique, CP, Martin, R, Martinelli, V, Mason, D, Mazibrada, G, McCabe, C, Mero, I-L, Mescheriakova, J, Moutsianas, L, Myhr, K-M, Nagels, G, Nicholas, R, Nilsson, P, Piehl, F, Pirinen, M, Price, SE, Quach, H, Reunanen, M, Robberecht, W, Robertson, NP, Rodegher, M, Rog, D, Salvetti, M, Schnetz-Boutaud, NC, Sellebjerg, F, Selter, RC, Schaefer, C, Shaunak, S, Shen, L, Shields, S, Siffrin, V, Slee, M, Sorensen, PS, Sorosina, M, Sospedra, M, Spurkland, A, Strange, A, Sundqvist, E, Thijs, V, Thorpe, J, Ticca, A, Tienari, P, van Duijn, C, Visser, EM, Vucic, S, Westerlind, H, Wiley, JS, Wilkins, A, Wilson, JF, Winkelmann, J, Zajicek, J, Zindler, E, Haines, JL, Pericak-Vance, MA, Ivinson, AJ, Stewart, G, Hafler, D, Hauser, SL, Compston, A, McVean, G, De Jager, P, Sawcer, SJ, and McCauley, JL
- Abstract
Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
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- 2013
11. Severe cardiac failure in a patient with multiple sclerosis following low-dose mitoxantrone treatment.
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Dörr J, Bitsch A, Schmailzl KJ, Chan A, von Ahsen N, Hummel M, Varon R, Lill CM, Vogel HP, Zipp F, Paul F, Dörr, J, Bitsch, A, Schmailzl, K J G, Chan, A, von Ahsen, N, Hummel, M, Varon, R, Lill, C M, and Vogel, H-P
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- 2009
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12. Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis
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Bénédicte Dubois, Lucia Corrado, Deborah F. Mason, Allan G. Kermode, Pentti J. Tienari, Annette Bang Oturai, Charles Hillier, Adrian J. Ivinson, Stephen L. Hauser, Ashley Beecham, Jeannette Lechner-Scott, Vincent Thijs, Jonathan L. Haines, Sarah Edkins, Alexander T. Dilthey, Daniele Cusi, Guy Nagels, David A. Hafler, Mark Slee, Petra Nilsson, James S. Wiley, Lou Brundin, Amy Strange, Elizabeth Visser, Mireia Sospedra, Athena Hadjixenofontos, Sergio E. Baranzini, Jenny Link, Robert Andrews, Viola Biberacher, Helle Bach Søndergaard, Vittorio Martinelli, Tomas Olsson, Gillian L Hall, Stephen Sawcer, Stacy J. Caillier, Per Soelberg Sørensen, Céline Bellenguez, Cornelia M. van Duijn, Frauke Zipp, Nikolaos A. Patsopoulos, Cristin McCabe, Colin Freeman, Simon Broadley, Luisa Bernardinelli, Margaret A. Pericak-Vance, Jan Hillert, Wassila Carpentier, Sandip Shaunak, Anne Spurkland, Barnaby Fiddes, Judith Field, Jan Lycke, Christina M. Lill, Federica Esposito, Ioanna Konidari, Elisabeth Gulowsen Celius, Christian Gieger, Helmut Butzkueven, Ling Shen, James F. Wilson, Magdalena Lindén, Tejas S. Shah, Amie Baker, Dionysia K. Xifara, Hong Quach, Laura Bergamaschi, Rogier Q. Hintzen, Jacob L. McCauley, Janna Saarela, J W Thorpe, Christine Lebrun-Frenay, Felix Luessi, Sandra D'Alfonso, B. E. Kendall, Helga Westerlind, Giancarlo Comi, Nathalie Schnetz-Boutaud, Paola Brambilla, Chris Cotsapas, Anders Hamsten, William Camu, Achim Berthele, Kjell-Morten Myhr, Clive Hawkins, Richard Nicholas, James Harley, Carl A. Anderson, Keijo Koivisto, Irene Coman, Neil Robertson, Hakon Hakonarson, Finn Sellebjerg, Fredrik Piehl, Alessia Di Sapio, Loukas Moutsianas, Mehdi Alizadeh, Lars Alfredsson, Catherine Schaefer, David Rog, Virpi Leppa, C. Martin, Bruce A.C. Cree, Christopher Halfpenny, Irina Elovaara, Filippo Martinelli-Boneschi, Cordelia Langford, Hanne F. Harbo, Wim Robberecht, Isabelle Cournu-Rebeix, Steve Vucic, Izaura Lima Bomfim, Irene Y. Frohlich, Michelle Lee, Bertrand Fontaine, Bernhard Hemmer, Eva Zindler, Chris C. A. Spencer, Malin Larsson, Simon Shields, Ilijas Jelcic, Juliane Winkelmann, Jorge R. Oksenberg, Alastair Wilkins, Silvia Delgado, Volker Siffrin, Helena C. Kronsbein, Bruno Brochet, Panos Deloukas, Daniela Galimberti, Nikos Evangelou, Rebecca C. Selter, Maja Jagodic, Martin Duddy, Timothy Harrower, Per Hall, Nadia Barizzone, Siân Price, Matti Pirinen, Pierre-Antoine Gourraud, Thomas M.C. Binder, Giuseppe Liberatore, Mark Lathrop, M.-M. Hoshi, Garrett Hellenthal, Melissa Sorosina, Thomas Korn, Clara Guaschino, Roland Martin, Jeremy Hobart, Marco Salvetti, Peter Donnelly, Ingrid Kockum, An Goris, Alastair Compston, Mariaemma Rodegher, Dorothea Buck, Clara P. Manrique, Christiane Graetz, Benedicte A. Lie, Trevor J. Kilpatrick, Andrew Graham, Anu Kemppinen, Maria Ban, Gil McVean, John Zajicek, Hannah Blackburn, Mary F. Davis, Emilie Sundqvist, Bruce V. Taylor, Maurizio Leone, Lisa F. Barcellos, Fabio Macciardi, Gilles Defer, Vincent Damotte, Satu Männistö, Graeme J. Stewart, Gordon Mazibrada, Inger Lise Mero, Andre Franke, Philip L. De Jager, Verena Grummel, Mauri Reunanen, David R. Booth, Anna Ticca, Angela Jochim, Leentje Cosemans, Julia Y Mescheriakova, Cristina Agliardi, Paola Cavalla, Jeffrey C. Barrett, Sarah E. Hunt, Gavin Band, School of Life Sciences, University of Technology Sydney (UTS), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Profium Oy [Helsinki], Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institute of Clinical Medicine [Oslo], Faculty of Medicine [Oslo], University of Oslo (UiO)-University of Oslo (UiO), Michigan Technological University (MTU), The Wellcome Trust Centre for Human Genetics [Oxford], University of Oxford [Oxford], The Wellcome Trust Sanger Institute [Cambridge], Génétique épidémiologique et structures des populations humaines (Inserm U535), Epidémiologie, sciences sociales, santé publique (IFR 69), Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-École des hautes études en sciences sociales (EHESS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université Paris 1 Panthéon-Sorbonne (UP1)-Université Paris-Sud - Paris 11 (UP11)-École des hautes études en sciences sociales (EHESS)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), UNIROUEN - UFR Santé (UNIROUEN UFR Santé), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Service de neurologie [Bordeaux], CHU Bordeaux [Bordeaux]-Groupe hospitalier Pellegrin, Karolinska Institutet [Stockholm], Institut des Neurosciences de Montpellier - Déficits sensoriels et moteurs (INM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Montpellier (UM), Plateforme Post-génomique de la Pitié-Salpêtrière (P3S), UMS omique (OMIQUE), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Pierre et Marie Curie - Paris 6 - UFR de Médecine Pierre et Marie Curie (UPMC), Université Pierre et Marie Curie - Paris 6 (UPMC), Centre de Recherche de l'Institut du Cerveau et de la Moelle épinière (CRICM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service de Neurologie [CHU Caen], Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-CHU Caen, Normandie Université (NU)-Tumorothèque de Caen Basse-Normandie (TCBN)-Tumorothèque de Caen Basse-Normandie (TCBN), Department of Statistics [Oxford], Centro Dino Ferrari [Milano], Università degli Studi di Milano [Milano] (UNIMI)-Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, Epidémiologie et Analyses en Santé Publique : risques, maladies chroniques et handicap (LEASP), Institut National de la Santé et de la Recherche Médicale (INSERM), Department of Medical Epidemiology and Biostatistics (MEB), University College of London [London] (UCL), Fondation Jean Dausset CEPH, Centre Hospitalier Universitaire de Nice (CHU Nice), Dublin Institute of Technology (DIT), University of California [Irvine] (UCI), University of California, Géosciences Environnement Toulouse (GET), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Kaiser Permanente, Universität Zürich [Zürich] = University of Zurich (UZH), University Hospitals Leuven [Leuven], Department Biostatistics University of North Carolina, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Institute of Bioinformatics and Systems Biology [München], Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Yale University School of Medicine, Big Data Institute, Department of Clinical Neurosciences [Cambridge], University of Cambridge [UK] (CAM), Faculty of Engineering, Neuroprotection & Neuromodulation, Internal Medicine Specializations, Neurology, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Centre National de la Recherche Scientifique (CNRS), Institut des Neurosciences de Montpellier (INM), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Université Fédérale Toulouse Midi-Pyrénées-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Yale School of Medicine [New Haven, Connecticut] (YSM), University of Oxford, Università degli Studi di Milano = University of Milan (UNIMI)-Fondazione IRCCS Ca' Granda - Ospedale Maggiore Policlinico, University of California [Irvine] (UC Irvine), University of California (UC), Cardiology, Epidemiology, Oral and Maxillofacial Surgery, International Multiple Sclerosis Genetics, Consortium, Beecham, Ah, Patsopoulos, Na, Xifara, Dk, Davis, Mf, Kemppinen, A, Cotsapas, C, Shah, T, Spencer, C, Booth, D, Goris, A, Oturai, A, Saarela, J, Fontaine, B, Hemmer, B, Martin, C, Zipp, F, D'Alfonso, S, Martinelli Boneschi, F, Taylor, B, Harbo, Hf, Kockum, I, Hillert, J, Olsson, T, Ban, M, Oksenberg, Jr, Hintzen, R, Barcellos, Lf, Wellcome Trust Case Control Consortium, 2, International IBD Genetics, Consortium, Agliardi, C, Alfredsson, L, Alizadeh, M, Anderson, C, Andrews, R, Søndergaard, Hb, Baker, A, Band, G, Baranzini, Se, Barizzone, N, Barrett, J, Bellenguez, C, Bergamaschi, L, Bernardinelli, L, Berthele, A, Biberacher, V, Binder, Tm, Blackburn, H, Bomfim, Il, Brambilla, P, Broadley, S, Brochet, B, Brundin, L, Buck, D, Butzkueven, H, Caillier, Sj, Camu, W, Carpentier, W, Cavalla, P, Celius, Eg, Coman, I, Comi, Giancarlo, Corrado, L, Cosemans, L, Cournu Rebeix, I, Cree, Ba, Cusi, D, Damotte, V, Defer, G, Delgado, Sr, Deloukas, P, di Sapio, A, Dilthey, At, Donnelly, P, Dubois, B, Duddy, M, Edkins, S, Elovaara, I, Esposito, F, Evangelou, N, Fiddes, B, Field, J, Franke, A, Freeman, C, Frohlich, Iy, Galimberti, D, Gieger, C, Gourraud, Pa, Graetz, C, Graham, A, Grummel, V, Guaschino, C, Hadjixenofontos, A, Hakonarson, H, Halfpenny, C, Hall, G, Hall, P, Hamsten, A, Harley, J, Harrower, T, Hawkins, C, Hellenthal, G, Hillier, C, Hobart, J, Hoshi, M, Hunt, Se, Jagodic, M, Jelčić, I, Jochim, A, Kendall, B, Kermode, A, Kilpatrick, T, Koivisto, K, Konidari, I, Korn, T, Kronsbein, H, Langford, C, Larsson, M, Lathrop, M, Lebrun Frenay, C, Lechner Scott, J, Lee, Mh, Leone, Ma, Leppä, V, Liberatore, G, Lie, Ba, Lill, Cm, Lindén, M, Link, J, Luessi, F, Lycke, J, Macciardi, F, Männistö, S, Manrique, Cp, Martin, R, Martinelli, V, Mason, D, Mazibrada, G, Mccabe, C, Mero, Il, Mescheriakova, J, Moutsianas, L, Myhr, Km, Nagels, G, Nicholas, R, Nilsson, P, Piehl, F, Pirinen, M, Price, Se, Quach, H, Reunanen, M, Robberecht, W, Robertson, Np, Rodegher, M, Rog, D, Salvetti, M, Schnetz Boutaud, Nc, Sellebjerg, F, Selter, Rc, Schaefer, C, Shaunak, S, Shen, L, Shields, S, Siffrin, V, Slee, M, Sorensen, P, Sorosina, M, Sospedra, M, Spurkland, A, Strange, A, Sundqvist, E, Thijs, V, Thorpe, J, Ticca, A, Tienari, P, van Duijn, C, Visser, Em, Vucic, S, Westerlind, H, Wiley, J, Wilkins, A, Wilson, Jf, Winkelmann, J, Zajicek, J, Zindler, E, Haines, Jl, Pericak Vance, Ma, Ivinson, Aj, Stewart, G, Hafler, D, Hauser, Sl, Compston, A, Mcvean, G, De Jager, P, Sawcer, Sj, and Mccauley, J. L.
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Multiple Sclerosis ,Genotype ,[SDV]Life Sciences [q-bio] ,European Continental Ancestry Group ,Genome-wide association study ,CLEC16A ,Biology ,multiple sclerosis ,Major histocompatibility complex ,Polymorphism, Single Nucleotide ,Article ,White People ,03 medical and health sciences ,0302 clinical medicine ,Research Support, N.I.H., Extramural ,Gene Frequency ,Polymorphism (computer science) ,Journal Article ,Genetics ,medicine ,Humans ,Genetic Predisposition to Disease ,Allele ,Genotyping ,Allele frequency ,030304 developmental biology ,0303 health sciences ,Research Support, Non-U.S. Gov't ,Multiple sclerosis ,Chromosome Mapping ,Genetic Variation ,medicine.disease ,3. Good health ,Genetic Loci ,biology.protein ,030217 neurology & neurosurgery ,[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology ,Genome-Wide Association Study - Abstract
International audience; Using the ImmunoChip custom genotyping array, we analyzed 14,498 subjects with multiple sclerosis and 24,091 healthy controls for 161,311 autosomal variants and identified 135 potentially associated regions (P < 1.0 × 10(-4)). In a replication phase, we combined these data with previous genome-wide association study (GWAS) data from an independent 14,802 subjects with multiple sclerosis and 26,703 healthy controls. In these 80,094 individuals of European ancestry, we identified 48 new susceptibility variants (P < 5.0 × 10(-8)), 3 of which we found after conditioning on previously identified variants. Thus, there are now 110 established multiple sclerosis risk variants at 103 discrete loci outside of the major histocompatibility complex. With high-resolution Bayesian fine mapping, we identified five regions where one variant accounted for more than 50% of the posterior probability of association. This study enhances the catalog of multiple sclerosis risk variants and illustrates the value of fine mapping in the resolution of GWAS signals.
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- 2016
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13. Gut Microbial Metabolites and Future Risk of Parkinson's Disease: A Metabolome-Wide Association Study.
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Zhao Y, Lai Y, Darweesh SKL, Bloem BR, Forsgren L, Hansen J, Katzke VA, Masala G, Sieri S, Sacerdote C, Panico S, Zamora-Ros R, Sánchez MJ, Huerta JM, Guevara M, Vinagre-Aragon A, Vineis P, Lill CM, Miller GW, Peters S, and Vermeulen R
- Abstract
Background: Alterations in gut microbiota are observed in Parkinson's disease (PD). Previous studies on microbiota-derived metabolites in PD were small-scale and post-diagnosis, raising concerns about reverse causality., Objectives: Our goal was to prospectively investigate the association between plasma microbial metabolites and PD risk within a metabolomics framework., Methods: A nested case-control study within the prospective EPIC4PD cohort, measured pre-diagnostic plasma microbial metabolites using untargeted metabolomics., Results: Thirteen microbial metabolites were identified nominally associated with PD risk (P-value < 0.05), including amino acids, bile acid, indoles, and hydroxy acid, although none remained significant after multiple testing correction. Three pathways were implicated in PD risk: valine, leucine, and isoleucine degradation, butanoate metabolism, and propanoate metabolism. PD-associated microbial pathways were more pronounced in men, smokers, and overweight/obese individuals., Conclusion: Changes in microbial metabolites may represent a pre-diagnostic feature of PD. We observed biologically plausible associations between microbial pathways and PD, potentially influenced by individual characteristics. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)
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- 2024
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14. Associations of milk, dairy products, calcium and vitamin D intake with risk of developing Parkinson´s disease within the EPIC4ND cohort.
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Gröninger M, Sabin J, Kaaks R, Amiano P, Aune D, Castro NC, Guevara M, Hansen J, Homann J, Masala G, Nicolas G, Peters S, Sacerdote C, Sánchez MJ, De Magistris MS, Sieri S, Vermeulen R, Zhao Y, Lill CM, and Katzke VA
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- Humans, Male, Female, Middle Aged, Prospective Studies, Aged, Animals, Risk Factors, Diet statistics & numerical data, Adult, Proportional Hazards Models, Europe epidemiology, Cohort Studies, Dairy Products, Vitamin D administration & dosage, Parkinson Disease epidemiology, Parkinson Disease etiology, Calcium, Dietary administration & dosage, Milk
- Abstract
Literature indicates a potential association between dairy consumption and risk of Parkinson´s disease (PD), especially among men, yet the results remain inconclusive. We investigated this association in a large prospective European cohort. Dietary and non-dietary data was collected from 183,225 participants of the EPIC-for-Neurodegenerative-Diseases (EPIC4ND) cohort, a sub-cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Crude and multivariable-adjusted Cox proportional hazards models were employed to examine potential associations between baseline dietary intake of dairy, calcium and vitamin D with incident PD risk. No relationship was observed between dairy consumption (HR 1.07, 95% CI 0.82-1.39), individual dairy products (milk: HR 0.95, 95% CI 0.73-1.23; yogurt: HR 1.03, 95% CI 0.82-1.29; cheese: HR 1.13, 95% CI 0.85-1.51), or vitamin D (HR 1.08, 95% CI 0.80-1.45) with PD risk. However, we observed a risk-increasing association with higher calcium intakes (HR 1.33, 95% CI 1.00-1.78, p for trend = 0.031), which was more pronounced in men (HR 1.50, 95% CI 1.00-2.25, p for trend = 0.044) and in ever smokers (HR 1.64, 95% CI 1.06-2.53, p for trend = 0.014). No compelling evidence was found for an association between dairy products or vitamin D intake and PD risk indicating a potentially limited relevance of dairy intake in PD risk than previously described. Our observations of a positive association between dietary calcium intake and PD risk in men and in ever smokers require further validation., Competing Interests: Declarations. Ethical approval: The studies involving human participants were reviewed and approved by IARC Ethics Committee (IEC). Consent to participate: The patients/participants provided their written informed consent to participate in this study. Disclaimer: Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organisation, the authors alone are responsible for the view expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization. Competing interests: The authors have no competing interests to declare that are relevant to the content of this article., (© 2024. The Author(s).)
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- 2024
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15. There are multiple clocks that time us: Cross-sectional and longitudinal associations among 14 alternative indicators of age and aging.
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Drewelies J, Homann J, Vetter VM, Duezel S, Kühn S, Deecke L, Steinhagen-Thiessen E, Jawinski P, Markett S, Lindenberger U, Lill CM, Bertram L, Demuth I, and Gerstorf D
- Abstract
Aging is a complex process influenced by mechanisms operating at numerous levels of functioning. Multiple biomarkers of age have been identified, yet we know little about how the different alternative age indicators are intertwined. In the Berlin Aging Study II (nmin= 328; nmax= 1,517, women = 51%; 14.27 years of education), we examined how levels and seven-year changes in indicators derived from blood assays, MRI brain scans, other-ratings, and self-reports converge among older adults. We included eight epigenetic biomarkers (incl. five epigenetic "clocks"), a BioAge composite from clinical laboratory parameters, brain age, skin age, subjective age, subjective life expectancy, and future health horizon. We found moderate associations within aging domains, both cross-sectionally and longitudinally over seven years. However, associations across different domains were infrequent and modest. Notably, participants with older BioAge had correspondingly older epigenetic ages. Our results suggest that different aging clocks are only loosely interconnected and that more specific measures are needed to differentiate healthy from unhealthy aging., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.)
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- 2024
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16. Blood-based multivariate methylation risk score for cognitive impairment and dementia.
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Koetsier J, Cavill R, Reijnders R, Harvey J, Homann J, Kouhsar M, Deckers K, Köhler S, Eijssen LMT, van den Hove DLA, Demuth I, Düzel S, Smith RG, Smith AR, Burrage J, Walker EM, Shireby G, Hannon E, Dempster E, Frayling T, Mill J, Dobricic V, Johannsen P, Wittig M, Franke A, Vandenberghe R, Schaeverbeke J, Freund-Levi Y, Frölich L, Scheltens P, Teunissen CE, Frisoni G, Blin O, Richardson JC, Bordet R, Engelborghs S, de Roeck E, Martinez-Lage P, Tainta M, Lleó A, Sala I, Popp J, Peyratout G, Verhey F, Tsolaki M, Andreasson U, Blennow K, Zetterberg H, Streffer J, Vos SJB, Lovestone S, Visser PJ, Lill CM, Bertram L, Lunnon K, and Pishva E
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- Humans, Male, Female, Aged, Risk Factors, Machine Learning, Cross-Sectional Studies, Alzheimer Disease genetics, Alzheimer Disease blood, Alzheimer Disease diagnosis, Prospective Studies, Risk Assessment, Aged, 80 and over, DNA Methylation genetics, Cognitive Dysfunction genetics, Cognitive Dysfunction blood, Cognitive Dysfunction diagnosis, Dementia genetics, Dementia blood, Dementia diagnosis
- Abstract
Introduction: The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection., Methods: In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts., Results: We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P = 2.0 × 10
-3 ). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning = 2.47) and Parkinson's disease (hazard ratio for MCI/dementia- Published
- 2024
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17. Variants in the TERT Gene Increase the Occurrence of Solar Lentigines by Modifying Telomerase Expression Exclusively in the Skin.
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Deecke L, Ohlei O, Homann J, Stagge J, Dobricic V, Steinhagen-Thiessen E, Berger K, Demuth I, Hagelstein V, Bertram L, and Lill CM
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- Humans, Sunlight, Female, Male, Telomerase genetics, Telomerase metabolism, Lentigo genetics, Lentigo pathology, Lentigo metabolism, Skin metabolism, Skin pathology
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- 2024
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18. Genome-wide meta-analysis of short-tandem repeats for Parkinson's disease risk using genotype imputation.
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Ohlei O, Paul K, Nielsen SS, Gmelin D, Dobricic V, Altmann V, Schilling M, Bronstein JM, Franke A, Wittig M, Parkkinen L, Hansen J, Checkoway H, Ritz B, Bertram L, and Lill CM
- Abstract
Idiopathic Parkinson's disease is determined by a combination of genetic and environmental factors. Recently, the first genome-wide association study on short-tandem repeats in Parkinson's disease reported on eight suggestive short-tandem repeat-based risk loci ( α = 5.3 × 10
-6 ), of which four were novel, i.e. they had not been implicated in Parkinson's disease risk by genome-wide association analyses of single-nucleotide polymorphisms before. Here, we tested these eight candidate short-tandem repeats in a large, independent Parkinson's disease case-control dataset ( n = 4757). Furthermore, we combined the results from both studies by meta-analysis resulting in the largest Parkinson's disease genome-wide association study of short-tandem repeats to date ( n = 43 844). Lastly, we investigated whether leading short-tandem repeat risk variants exert functional effects on gene expression regulation based on methylation quantitative trait locus data in human 'post-mortem' brain ( n = 142). None of the eight previously reported short-tandem repeats were significantly associated with Parkinson's disease in our independent dataset after multiple testing correction ( α = 6.25 × 10-3 ). However, we observed modest support for short-tandem repeats near CCAR2 and NCOR1 in the updated meta-analyses of all available data. While the genome-wide meta-analysis did not reveal additional study-wide significant ( α = 6.3 × 10-7 ) short-tandem repeat signals, we identified seven novel suggestive Parkinson's disease short-tandem repeat risk loci ( α = 5.3 × 10-6 ). Of these, especially a short-tandem repeat near MEIOSIN showed consistent evidence for association across datasets. CCAR2 , NCOR1 and one novel suggestive locus identified here ( LINC01012 ) emerged from colocalization analyses showing evidence for a shared causal short-tandem repeat variant affecting both Parkinson's disease risk and cis DNA methylation in brain. Larger studies, ideally using short-tandem repeats called from whole-sequencing data, are needed to more fully investigate their role in Parkinson's disease., Competing Interests: The authors have no conflict of interest to report., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)- Published
- 2024
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19. Association of Coffee Consumption and Prediagnostic Caffeine Metabolites With Incident Parkinson Disease in a Population-Based Cohort.
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Zhao Y, Lai Y, Konijnenberg H, Huerta JM, Vinagre-Aragon A, Sabin JA, Hansen J, Petrova D, Sacerdote C, Zamora-Ros R, Pala V, Heath AK, Panico S, Guevara M, Masala G, Lill CM, Miller GW, Peters S, and Vermeulen R
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- Humans, Coffee, Case-Control Studies, Prospective Studies, Risk Factors, Caffeine metabolism, Parkinson Disease diagnosis, Parkinson Disease epidemiology, Parkinson Disease etiology
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Background and Objectives: Inverse associations between caffeine intake and Parkinson disease (PD) have been frequently implicated in human studies. However, no studies have quantified biomarkers of caffeine intake years before PD onset and investigated whether and which caffeine metabolites are related to PD., Methods: Associations between self-reported total coffee consumption and future PD risk were examined in the EPIC4PD study, a prospective population-based cohort including 6 European countries. Cases with PD were identified through medical records and reviewed by expert neurologists. Hazard ratios (HRs) and 95% CIs for coffee consumption and PD incidence were estimated using Cox proportional hazards models. A case-control study nested within the EPIC4PD was conducted, recruiting cases with incident PD and matching each case with a control by age, sex, study center, and fasting status at blood collection. Caffeine metabolites were quantified by high-resolution mass spectrometry in baseline collected plasma samples. Using conditional logistic regression models, odds ratios (ORs) and 95% CIs were estimated for caffeine metabolites and PD risk., Results: In the EPIC4PD cohort (comprising 184,024 individuals), the multivariable-adjusted HR comparing the highest coffee intake with nonconsumers was 0.63 (95% CI 0.46-0.88, p = 0.006). In the nested case-control study, which included 351 cases with incident PD and 351 matched controls, prediagnostic caffeine and its primary metabolites, paraxanthine and theophylline, were inversely associated with PD risk. The ORs were 0.80 (95% CI 0.67-0.95, p = 0.009), 0.82 (95% CI 0.69-0.96, p = 0.015), and 0.78 (95% CI 0.65-0.93, p = 0.005), respectively. Adjusting for smoking and alcohol consumption did not substantially change these results., Discussion: This study demonstrates that the neuroprotection of coffee on PD is attributed to caffeine and its metabolites by detailed quantification of plasma caffeine and its metabolites years before diagnosis.
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- 2024
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20. No increase of CD8+ TEMRA cells in the blood of healthy adults at high genetic risk of Alzheimer's disease.
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Deecke L, Homann J, Goldeck D, Ohlei O, Dobricic V, Drewelies J, Demuth I, Pawelec G, Bertram L, and Lill CM
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- Adult, Humans, CD8-Positive T-Lymphocytes, Genetic Predisposition to Disease, Alzheimer Disease genetics
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- 2024
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21. Genome-wide QTL mapping across three tissues highlights several Alzheimer's and Parkinson's disease loci potentially acting via DNA methylation.
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Ohlei O, Sommerer Y, Dobricic V, Homann J, Deecke L, Schilling M, Bartrés-Faz D, Cattaneo G, Düzel S, Fjell AM, Lindenberger U, Pascual-Leone Á, Sedghpour Sabet S, Solé-Padullés C, Tormos JM, Vetter VM, Walhovd KB, Wesse T, Wittig M, Franke A, Demuth I, Lill CM, and Bertram L
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DNA methylation (DNAm) is an epigenetic mark with essential roles in disease development and predisposition. Here, we created genome-wide maps of methylation quantitative trait loci (meQTL) in three peripheral tissues and used Mendelian randomization (MR) analyses to assess the potential causal relationships between DNAm and risk for two common neurodegenerative disorders, i.e. Alzheimer's disease (AD) and Parkinson's disease (PD). Genome-wide single nucleotide polymorphism (SNP; ~5.5M sites) and DNAm (~850K CpG sites) data were generated from whole blood (n=1,058), buccal (n=1,527) and saliva (n=837) specimens. We identified between 11 and 15 million genome-wide significant (p<10
-14 ) SNP-CpG associations in each tissue. Combining these meQTL GWAS results with recent AD/PD GWAS summary statistics by MR strongly suggests that the previously described associations between PSMC3 , PICALM , and TSPAN14 and AD may be founded on differential DNAm in or near these genes. In addition, there is strong, albeit less unequivocal, support for causal links between DNAm at PRDM7 in AD as well as at KANSL1/MAPT in AD and PD. Our study adds valuable insights on AD/PD pathogenesis by combining two high-resolution "omics" domains, and the meQTL data shared along with this publication will allow like-minded analyses in other diseases., Competing Interests: Competing interests D.B.F. serves on the scientific advisory board of Linus Health. A.P.L. serves on the scientific advisory boards for Neuroelectrics, Magstim Inc., TetraNeuron, Skin2Neuron, MedRhythms, and Hearts Radiant. He is co-founder of TI solutions and co-founder and chief medical officer of Linus Health. Furthermore, A.P.L. is listed as an inventor on several issued and pending patents on the real-time integration of transcranial magnetic stimulation with electroencephalography and magnetic resonance imaging, and applications of noninvasive brain stimulation in various neurological disorders; as well as digital biomarkers of cognition and digital assessments for early diagnosis of dementia. The remaining authors declare no competing interests.- Published
- 2023
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22. Prediagnostic Blood Metal Levels and the Risk of Parkinson's Disease: A Large European Prospective Cohort.
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Zhao Y, Ray A, Broberg K, Kippler M, Lill CM, Vineis P, Katzke VA, Rodriguez-Barranco M, Chirlaque MD, Guevara M, Gómez JH, Hansen J, Panico S, Middleton LT, Masala G, Pala V, Vinagre-Aragon A, Zibetti M, Vermeulen R, and Peters S
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- Humans, Prospective Studies, Case-Control Studies, Causality, Parkinson Disease diagnosis, Parkinson Disease epidemiology, Parkinson Disease etiology
- Abstract
Background: Metals have been postulated as environmental concerns in the etiology of Parkinson's disease (PD), but metal levels are typically measured after diagnosis, which might be subject to reverse causality., Objective: The aim of this study was to investigate the association between prediagnostic blood metal levels and PD risk., Methods: A case-control study was nested in a prospective European cohort, using erythrocyte samples collected before PD diagnosis., Results: Most assessed metals were not associated with PD risk. Cadmium has a suggestive negative association with PD (odds ratio [95% confidence interval] for the highest quartile, 0.70 [0.42-1.17]), which diminished among never smokers. Among current smokers only, lead was associated with decreased PD risk (0.06 [0.01-0.35]), whereas arsenic showed associations toward an increased PD risk (1.85 [0.45-7.93])., Conclusions: We observe no strong evidence to support a role of metals in the development of PD. In particular, smoking may confound the association with tobacco-derived metals. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society., (© 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.)
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- 2023
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23. Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning.
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Neumann A, Ohlei O, Küçükali F, Bos IJ, Timsina J, Vos S, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Scheltens P, Teunissen CE, Engelborghs S, Frisoni GB, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Marsh TW, Gorijala P, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Van Broeckhoven C, Tanzi RE, Ten Kate M, Lill CM, Barkhof F, Cruchaga C, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Sleegers K, and Bertram L
- Subjects
- Humans, Female, Male, Genome-Wide Association Study, tau Proteins genetics, Biomarkers, Inflammation, Apolipoproteins E genetics, Membrane Proteins genetics, Nerve Tissue Proteins genetics, Receptors, N-Methyl-D-Aspartate genetics, Alzheimer Disease genetics, Alzheimer Disease pathology
- Abstract
Background: Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences., Methods: We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects., Results: Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers., Conclusions: These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine., (© 2023. BioMed Central Ltd., part of Springer Nature.)
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- 2023
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24. Multiomics profiling of human plasma and cerebrospinal fluid reveals ATN-derived networks and highlights causal links in Alzheimer's disease.
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Shi L, Xu J, Green R, Wretlind A, Homann J, Buckley NJ, Tijms BM, Vos SJB, Lill CM, Kate MT, Engelborghs S, Sleegers K, Frisoni GB, Wallin A, Lleó A, Popp J, Martinez-Lage P, Streffer J, Barkhof F, Zetterberg H, Visser PJ, Lovestone S, Bertram L, Nevado-Holgado AJ, Proitsi P, and Legido-Quigley C
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- Humans, Amyloid beta-Peptides cerebrospinal fluid, tau Proteins cerebrospinal fluid, Multiomics, Biomarkers cerebrospinal fluid, Peptide Fragments cerebrospinal fluid, Alzheimer Disease, Cognitive Dysfunction cerebrospinal fluid
- Abstract
Introduction: This study employed an integrative system and causal inference approach to explore molecular signatures in blood and CSF, the amyloid/tau/neurodegeneration [AT(N)] framework, mild cognitive impairment (MCI) conversion to Alzheimer's disease (AD), and genetic risk for AD., Methods: Using the European Medical Information Framework (EMIF)-AD cohort, we measured 696 proteins in cerebrospinal fluid (n = 371), 4001 proteins in plasma (n = 972), 611 metabolites in plasma (n = 696), and genotyped whole-blood (7,778,465 autosomal single nucleotide epolymorphisms, n = 936). We investigated associations: molecular modules to AT(N), module hubs with AD Polygenic Risk scores and APOE4 genotypes, molecular hubs to MCI conversion and probed for causality with AD using Mendelian randomization (MR)., Results: AT(N) framework associated with protein and lipid hubs. In plasma, Proprotein Convertase Subtilisin/Kexin Type 7 showed evidence for causal associations with AD. AD was causally associated with Reticulocalbin 2 and sphingomyelins, an association driven by the APOE isoform., Discussion: This study reveals multi-omics networks associated with AT(N) and causal AD molecular candidates., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
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- 2023
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25. Lipopolysaccharide-binding protein and future Parkinson's disease risk: a European prospective cohort.
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Zhao Y, Walker DI, Lill CM, Bloem BR, Darweesh SKL, Pinto-Pacheco B, McNeil B, Miller GW, Heath AK, Frissen M, Petrova D, Sánchez MJ, Chirlaque MD, Guevara M, Zibetti M, Panico S, Middleton L, Katzke V, Kaaks R, Riboli E, Masala G, Sieri S, Zamora-Ros R, Amiano P, Jenab M, Peters S, and Vermeulen R
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- Male, Humans, Female, Case-Control Studies, Overweight, Prospective Studies, Retrospective Studies, Acute-Phase Proteins, Lipopolysaccharides, Parkinson Disease epidemiology
- Abstract
Introduction: Lipopolysaccharide (LPS) is the outer membrane component of Gram-negative bacteria. LPS-binding protein (LBP) is an acute-phase reactant that mediates immune responses triggered by LPS and has been used as a blood marker for LPS. LBP has recently been indicated to be associated with Parkinson's disease (PD) in small-scale retrospective case-control studies. We aimed to investigate the association between LBP blood levels with PD risk in a nested case-control study within a large European prospective cohort., Methods: A total of 352 incident PD cases (55% males) were identified and one control per case was selected, matched by age at recruitment, sex and study center. LBP levels in plasma collected at recruitment, which was on average 7.8 years before diagnosis of the cases, were analyzed by enzyme linked immunosorbent assay. Odds ratios (ORs) were estimated for one unit increase of the natural log of LBP levels and PD incidence by conditional logistic regression., Results: Plasma LBP levels were higher in prospective PD cases compared to controls (median (interquartile range) 26.9 (18.1-41.0) vs. 24.7 (16.6-38.4) µg/ml). The OR for PD incidence per one unit increase of log LBP was elevated (1.46, 95% CI 0.98-2.19). This association was more pronounced among women (OR 2.68, 95% CI 1.40-5.13) and overweight/obese subjects (OR 1.54, 95% CI 1.09-2.18)., Conclusion: The findings suggest that higher plasma LBP levels may be associated with an increased risk of PD and may thus pinpoint to a potential role of endotoxemia in the pathogenesis of PD, particularly in women and overweight/obese individuals., (© 2023. The Author(s).)
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- 2023
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26. Phenotypic specificity in patients with neurodevelopmental delay does not correlate with diagnostic yield of trio-exome sequencing.
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Baalmann N, Spielmann M, Gillessen-Kaesbach G, Hanker B, Schmidt J, Lill CM, Hellenbroich Y, Greiten B, Lohmann K, Trinh J, and Hüning I
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- Humans, Exome Sequencing, Phenotype, Spastin genetics, Intellectual Disability diagnosis, Intellectual Disability genetics
- Abstract
In this study, we aimed to examine the diagnostic yield achieved by applying a trio approach in exome sequencing (ES) and the interdependency between the clinical specificity in families with neurodevelopmental delay. Thirty-seven families were recruited and trio-ES as well as three criteria for estimating the clinical phenotypic specificity were suggested and applied to the underaged children. All our patients showed neurodevelopmental delay and most of them a large spectrum of congenital anomalies. Applying the pathogenicity guidelines of the American College of Medical Genetics (ACMG), likely pathogenic (29.7%) and pathogenic variants (8.1%) were found in 40,5% of our index patients. Additionally, we found four variants of uncertain significance (VUS; according to ACMG) and two genes of interest (GOI; going beyond ACMG classification) (GLRA4, NRXN2). Spastic Paraplegia 4 (SPG4) caused by a formerly known SPAST variant was diagnosed in a patient with a complex phenotype, in whom a second genetic disorder may be present. A potential pathogenic variant linked to severe intellectual disability in GLRA4 requires further investigation. No interdependency between the diagnostic yield and the clinical specificity of the phenotypes could be observed. In consequence, trio-ES should be used early in the diagnostic process, independently from the specificity of the patient., Competing Interests: Disclosure of conflict of interest On behalf of all authors, the corresponding author states that there is no conflict of interest., (Copyright © 2023 Elsevier Masson SAS. All rights reserved.)
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- 2023
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27. Entorhinal cortex epigenome-wide association study highlights four novel loci showing differential methylation in Alzheimer's disease.
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Sommerer Y, Dobricic V, Schilling M, Ohlei O, Sabet SS, Wesse T, Fuß J, Franzenburg S, Franke A, Parkkinen L, Lill CM, and Bertram L
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- Humans, Epigenesis, Genetic, Entorhinal Cortex, CpG Islands, DNA Methylation, Genome-Wide Association Study, GTP Phosphohydrolases genetics, Tumor Suppressor Proteins genetics, Epigenome, Alzheimer Disease genetics
- Abstract
Background: Studies on DNA methylation (DNAm) in Alzheimer's disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression., Methods: Here, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n = 337)., Results: We identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case-control status or Braak's tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed "epigenetic clock" estimators we found a significant association with accelerated epigenetic aging in the brains of AD patients vs. controls., Conclusion: In summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression., (© 2023. The Author(s).)
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- 2023
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28. Using blood test parameters to define biological age among older adults: association with morbidity and mortality independent of chronological age validated in two separate birth cohorts.
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Drewelies J, Hueluer G, Duezel S, Vetter VM, Pawelec G, Steinhagen-Thiessen E, Wagner GG, Lindenberger U, Lill CM, Bertram L, Gerstorf D, and Demuth I
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- Humans, Aged, Hematologic Tests, Morbidity, Biomarkers, Aging genetics, Birth Cohort
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Biomarkers defining biological age are typically laborious or expensive to assess. Instead, in the current study, we identified parameters based on standard laboratory blood tests across metabolic, cardiovascular, inflammatory, and kidney functioning that had been assessed in the Berlin Aging Study (BASE) (n = 384) and Berlin Aging Study II (BASE-II) (n = 1517). We calculated biological age using those 12 parameters that individually predicted mortality hazards over 26 years in BASE. In BASE, older biological age was associated with more physician-observed morbidity and higher mortality hazards, over and above the effects of chronological age, sex, and education. Similarly, in BASE-II, biological age was associated with physician-observed morbidity and subjective health, over and above the effects of chronological age, sex, and education as well as alternative biomarkers including telomere length, DNA methylation age, skin age, and subjective age but not PhenoAge. We discuss the importance of biological age as one indicator of aging., (© 2022. The Author(s).)
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- 2022
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29. Epigenome-Wide Association Study in Peripheral Tissues Highlights DNA Methylation Profiles Associated with Episodic Memory Performance in Humans.
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Sommerer Y, Dobricic V, Schilling M, Ohlei O, Bartrés-Faz D, Cattaneo G, Demuth I, Düzel S, Franzenburg S, Fuß J, Lindenberger U, Pascual-Leone Á, Sabet SS, Solé-Padullés C, Tormos JM, Vetter VM, Wesse T, Franke A, Lill CM, and Bertram L
- Abstract
The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer’s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 ± 11 years (30−90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p < 1 × 10−5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson’s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p < 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of “epigenetic age acceleration” did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans.
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- 2022
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30. A correlation map of genome-wide DNA methylation patterns between paired human brain and buccal samples.
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Sommerer Y, Ohlei O, Dobricic V, Oakley DH, Wesse T, Sedghpour Sabet S, Demuth I, Franke A, Hyman BT, Lill CM, and Bertram L
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- Humans, DNA, Brain, Phenotype, Genome-Wide Association Study methods, Epigenesis, Genetic, DNA Methylation, Quantitative Trait Loci
- Abstract
Epigenome-wide association studies (EWAS) assessing the link between DNA methylation (DNAm) and phenotypes related to structural brain measures, cognitive function, and neurodegenerative diseases are becoming increasingly more popular. Due to the inaccessibility of brain tissue in humans, several studies use peripheral tissues such as blood, buccal swabs, and saliva as surrogates. To aid the functional interpretation of EWAS findings in such settings, there is a need to assess the correlation of DNAm variability across tissues in the same individuals. In this study, we performed a correlation analysis between DNAm data of a total of n = 120 matched post-mortem buccal and prefrontal cortex samples. We identified nearly 25,000 (3% of approximately 730,000) cytosine-phosphate-guanine (CpG) sites showing significant (false discovery rate q < 0.05) correlations between buccal and PFC samples. Correlated CpG sites showed a preponderance to being located in promoter regions and showed a significant enrichment of being determined by genetic factors, i.e. methylation quantitative trait loci (mQTL), based on buccal and dorsolateral prefrontal cortex mQTL databases. Our novel buccal-brain DNAm correlation map will provide a valuable resource for future EWAS using buccal samples for studying DNAm effects on phenotypes relating to the brain. All correlation results are made freely available to the public online., (© 2022. The Author(s).)
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- 2022
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31. Common signatures of differential microRNA expression in Parkinson's and Alzheimer's disease brains.
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Dobricic V, Schilling M, Farkas I, Gveric DO, Ohlei O, Schulz J, Middleton L, Gentleman SM, Parkkinen L, Bertram L, and Lill CM
- Abstract
Dysregulation of microRNA gene expression has been implicated in many neurodegenerative diseases, including Parkinson's disease. However, the individual dysregulated microRNAs remain largely unknown. Previous meta-analyses have highlighted several microRNAs being differentially expressed in post-mortem Parkinson's disease and Alzheimer's disease brains versus controls, but they were based on small sample sizes. In this study, we quantified the expression of the most compelling Parkinson's and Alzheimer's disease microRNAs from these meta-analyses ('candidate miRNAs') in one of the largest Parkinson's/Alzheimer's disease case-control post-mortem brain collections available ( n = 451), thereby quadruplicating previously investigated sample sizes. Parkinson's disease candidate microRNA hsa-miR-132-3p was differentially expressed in our Parkinson's ( P = 4.89E-06) and Alzheimer's disease samples ( P = 3.20E-24) compared with controls. Alzheimer's disease candidate microRNAs hsa-miR-132-5p ( P = 4.52E-06) and hsa-miR-129-5p ( P = 0.0379) were differentially expressed in our Parkinson's disease samples. Combining these novel data with previously published data substantially improved the statistical support (α = 3.85E-03) of the corresponding meta-analyses, clearly implicating these microRNAs in both Parkinson's and Alzheimer's disease. Furthermore, hsa-miR-132-3p/-5p (but not hsa-miR-129-5p) showed association with α-synuclein neuropathological Braak staging ( P = 3.51E-03/ P = 0.0117), suggesting that hsa-miR-132-3p/-5p play a role in α-synuclein aggregation beyond the early disease phase. Our study represents the largest independent assessment of recently highlighted candidate microRNAs in Parkinson's and Alzheimer's disease brains, to date. Our results implicate hsa-miR-132-3p/-5p and hsa-miR-129-5p to be differentially expressed in both Parkinson's and Alzheimer's disease, pinpointing shared pathogenic mechanisms across these neurodegenerative diseases. Intriguingly, based on publicly available high-throughput sequencing of RNA isolated by cross-linking immunoprecipitation data, hsa-miR-132 may interact with SNCA messenger RNA in the human brain, possibly pinpointing novel therapeutic approaches in fighting Parkinson's disease., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Guarantors of Brain.)
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- 2022
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32. Differential microRNA expression analyses across two brain regions in Alzheimer's disease.
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Dobricic V, Schilling M, Schulz J, Zhu LS, Zhou CW, Fuß J, Franzenburg S, Zhu LQ, Parkkinen L, Lill CM, and Bertram L
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- Animals, Brain metabolism, Gene Expression Profiling, Mice, Mice, Transgenic, Sequence Analysis, RNA, Alzheimer Disease genetics, MicroRNAs genetics, MicroRNAs metabolism
- Abstract
Dysregulation of microRNAs (miRNAs) is involved in the pathogenesis of neurodegenerative diseases, including Alzheimer's disease (AD). Hitherto, sample sizes from differential miRNA expression studies in AD are exceedingly small aggravating any biological inference. To overcome this limitation, we investigated six candidate miRNAs in a large collection of brain samples. Brain tissue was derived from superior temporal gyrus (STG) and entorhinal cortex (EC) from 99 AD patients and 91 controls. MiRNA expression was examined by qPCR (STG) or small RNA sequencing (EC). Brain region-dependent differential miRNA expression was investigated in a transgenic AD mouse model using qPCR and FISH. Total RNA sequencing was used to assess differential expression of miRNA target genes. MiR-129-5p, miR-132-5p, and miR-138-5p were significantly downregulated in AD vs. controls both in STG and EC, while miR-125b-5p and miR-501-3p showed no evidence for differential expression in this dataset. In addition, miR-195-5p was significantly upregulated in EC but not STG in AD patients. The brain region-specific pattern of miR-195-5p expression was corroborated in vivo in transgenic AD mice. Total RNA sequencing identified several novel and functionally interesting target genes of these miRNAs involved in synaptic transmission (GABRB1), the immune-system response (HCFC2) or AD-associated differential methylation (SLC16A3). Using two different methods (qPCR and small RNA-seq) in two separate brain regions in 190 individuals we more than doubled the available sample size for most miRNAs tested. Differential gene expression analyses confirm the likely involvement of miR-129-5p, miR-132-5p, miR-138-5p, and miR-195-5p in AD pathogenesis and highlight several novel potentially relevant target mRNAs., (© 2022. The Author(s).)
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- 2022
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33. Genome-wide analysis furthers decoding of Alzheimer disease genetics.
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Lill CM and Bertram L
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- Genetic Predisposition to Disease genetics, Genome-Wide Association Study, Humans, Alzheimer Disease genetics
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- 2022
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34. Erratum to "Increased Menopausal Age Reduces the Risk of Parkinson's Disease: A Mendelian Approach".
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Kusters CDJ, Paul KC, Duarte Folle A, Keener AM, Bronstein JM, Bertram L, Hansen J, Horvath S, Sinsheimer JS, Lill CM, and Ritz BR
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- 2022
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35. Genetic associations with learning over 100 days of practice.
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Youn C, Grotzinger AD, Lill CM, Bertram L, Schmiedek F, Lövdén M, Lindenberger U, Nivard M, Harden KP, and Tucker-Drob EM
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Cognitive performance is both heritable and sensitive to environmental inputs and sustained practice over time. However, it is currently unclear how genetic effects on cognitive performance change over the course of learning. We examine how polygenic scores (PGS) created from genome-wide association studies of educational attainment and cognitive performance are related to improvements in performance across nine cognitive tests (measuring perceptual speed, working memory, and episodic memory) administered to 131 adults (N = 51, ages = 20-31, and N = 80, ages = 65-80 years) repeatedly across 100 days. We observe that PGS associations with performance on a given task can change over the course of learning, with the specific pattern of change in associations differing across tasks. PGS correlations with pre-test to post-test scores may mask variability in how soon learning occurs over the course of practice. The associations between PGS and learning do not appear to simply reconstitute patterns of association between baseline performance and subsequent learning. Associations involving PGSs, however, were small with large confidence intervals. Intensive longitudinal research such as that described here may be of substantial value for clarifying the genetics of learning when implemented as far larger scale., (© 2022. The Author(s).)
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- 2022
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36. Genome-Wide Association Study of Alzheimer's Disease Brain Imaging Biomarkers and Neuropsychological Phenotypes in the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery Dataset.
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Homann J, Osburg T, Ohlei O, Dobricic V, Deecke L, Bos I, Vandenberghe R, Gabel S, Scheltens P, Teunissen CE, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Wittig M, Franke A, Lill CM, Blennow K, Zetterberg H, Lovestone S, Streffer J, Ten Kate M, Vos SJB, Barkhof F, Visser PJ, and Bertram L
- Abstract
Alzheimer's disease (AD) is the most frequent neurodegenerative disease with an increasing prevalence in industrialized, aging populations. AD susceptibility has an established genetic basis which has been the focus of a large number of genome-wide association studies (GWAS) published over the last decade. Most of these GWAS used dichotomized clinical diagnostic status, i.e., case vs. control classification, as outcome phenotypes, without the use of biomarkers. An alternative and potentially more powerful study design is afforded by using quantitative AD-related phenotypes as GWAS outcome traits, an analysis paradigm that we followed in this work. Specifically, we utilized genotype and phenotype data from n = 931 individuals collected under the auspices of the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery (EMIF-AD MBD) study to perform a total of 19 separate GWAS analyses. As outcomes we used five magnetic resonance imaging (MRI) traits and seven cognitive performance traits. For the latter, longitudinal data from at least two timepoints were available in addition to cross-sectional assessments at baseline. Our GWAS analyses revealed several genome-wide significant associations for the neuropsychological performance measures, in particular those assayed longitudinally. Among the most noteworthy signals were associations in or near EHBP1 (EH domain binding protein 1; on chromosome 2p15) and CEP112 (centrosomal protein 112; 17q24.1) with delayed recall as well as SMOC2 (SPARC related modular calcium binding 2; 6p27) with immediate recall in a memory performance test. On the X chromosome, which is often excluded in other GWAS, we identified a genome-wide significant signal near IL1RAPL1 (interleukin 1 receptor accessory protein like 1; Xp21.3). While polygenic score (PGS) analyses showed the expected strong associations with SNPs highlighted in relevant previous GWAS on hippocampal volume and cognitive function, they did not show noteworthy associations with recent AD risk GWAS findings. In summary, our study highlights the power of using quantitative endophenotypes as outcome traits in AD-related GWAS analyses and nominates several new loci not previously implicated in cognitive decline., Competing Interests: HZ has served at scientific advisory boards and/or as a consultant for Abbvie, Alector, Annexon, Artery Therapeutics, AZTherapies, CogRx, Denali, Eisai, Nervgen, Pinteon Therapeutics, Red Abbey Labs, Passage Bio, Roche, Samumed, Siemens Healthineers, Triplet Therapeutics, and Wave, has given lectures in symposia sponsored by Cellectricon, Fujirebio, Alzecure, Biogen, and Roche, and was a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which was a part of the GU Ventures Incubator Program. FB is supported by the NIHR biomedical research centre at UCLH. JP received consultation honoraria from Nestle Institute of Health Sciences, Ono Pharma, OM Pharma, and Fujirebio, unrelated to the submitted work. CT has a collaboration contract with ADx Neurosciences, Quanterix and Eli Lilly, performed contract research or received grants from AC-Immune, Axon Neurosciences, Biogen, Brainstorm Therapeutics, Celgene, EIP Pharma, Eisai, PeopleBio, Roche, Toyama, Vivoryon. She serves on editorial boards of Medidact Neurologie/Springer, Alzheimer Research and Therapy, Neurology: Neuroimmunology and Neuroinflammation, and was editor of a Neuromethods book Springer. CT also holds a speaker’s contract with Roche, Inc. KB has served as a consultant, at advisory boards, or at data monitoring committees for Abcam, Axon, BioArctic, Biogen, JOMDD/Shimadzu. Julius Clinical, Lilly, MagQu, Novartis, Pharmatrophix, Prothena, Roche Diagnostics, and Siemens Healthineers, and was a co-founder of Brain Biomarker Solutions in Gothenburg AB (BBS), which was a part of the GU Ventures Incubator Program, outside the work presented in this paper. SL is currently an employee at Janssen Medical UK. JS was an employee of Janssen R&D, LLC., and is currently an employee and chief medical officer of AC Immune SA. JR was an employee of Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevenage, UK., (Copyright © 2022 Homann, Osburg, Ohlei, Dobricic, Deecke, Bos, Vandenberghe, Gabel, Scheltens, Teunissen, Engelborghs, Frisoni, Blin, Richardson, Bordet, Lleó, Alcolea, Popp, Clark, Peyratout, Martinez-Lage, Tainta, Dobson, Legido-Quigley, Sleegers, Van Broeckhoven, Wittig, Franke, Lill, Blennow, Zetterberg, Lovestone, Streffer, ten Kate, Vos, Barkhof, Visser and Bertram.)
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- 2022
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37. A common polymorphism in the dopamine transporter gene predicts working memory performance and in vivo dopamine integrity in aging.
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Karalija N, Köhncke Y, Düzel S, Bertram L, Papenberg G, Demuth I, Lill CM, Johansson J, Riklund K, Lövdén M, Bäckman L, Nyberg L, Lindenberger U, and Brandmaier AM
- Subjects
- Aged, Aged, 80 and over, Alleles, Female, Homozygote, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, Raclopride, Aging genetics, Hippocampus diagnostic imaging, Memory, Short-Term physiology, Positron-Emission Tomography, Receptors, Dopamine D2 genetics, Receptors, Dopamine D2 metabolism
- Abstract
Dopamine (DA) integrity is suggested as a potential cause of individual differences in working memory (WM) performance among older adults. Still, the principal dopaminergic mechanisms giving rise to WM differences remain unspecified. Here, 61 single-nucleotide polymorphisms, located in or adjacent to various dopamine-related genes, were assessed for their links to WM performance in a sample of 1313 adults aged 61-80 years from the Berlin Aging Study II. Least Absolute Shrinkage and Selection Operator (LASSO) regression was conducted to estimate associations between polymorphisms and WM. Rs40184 in the DA transporter gene, SLC6A3, showed allelic group differences in WM, with T-carriers performing better than C homozygotes (p<0.01). This finding was replicated in an independent sample from the Cognition, Brain, and Aging study (COBRA; baseline: n = 181, ages: 64-68 years; 5-year follow up: n = 129). In COBRA, in vivo DA integrity was measured with
11 C-raclopride and positron emission tomography. Notably, WM as well as in vivo DA integrity was higher for rs40184 T-carriers at baseline (p<0.05 for WM and caudate and hippocampal D2-receptor availability) and at the 5-year follow-up (p<0.05 for WM and hippocampal D2 availability). Our findings indicate that individual differences in DA transporter function contribute to differences in WM performance in old age, presumably by regulating DA availability., (Copyright © 2021. Published by Elsevier Inc.)- Published
- 2021
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38. Increased Menopausal Age Reduces the Risk of Parkinson's Disease: A Mendelian Randomization Approach.
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Kusters CDJ, Paul KC, Duarte Folle A, Keener AM, Bronstein JM, Bertram L, Hansen J, Horvath S, Sinsheimer JS, Lill CM, and Ritz BR
- Subjects
- Female, Genome-Wide Association Study, Humans, Male, Mendelian Randomization Analysis, Menopause, Polymorphism, Single Nucleotide genetics, Risk Factors, Parkinson Disease epidemiology, Parkinson Disease genetics
- Abstract
Background: Studies of Parkinson's disease (PD) and the association with age at menarche or menopause have reported inconsistent findings. Mendelian randomization (MR) may address measurement errors because of difficulties accurately reporting the age these life events occur., Objective: We used MR to assess the association between age at menopause and age at menarche with PD risk., Methods: We performed inverse variant-weighted (IVW) MR analysis using external genome-wide association study (GWAS) summary data from the United Kingdom biobank, and the effect estimates between genetic variants and PD among two population-based studies (Parkinson's disease in Denmark (PASIDA) study, Denmark, and Parkinson's Environment and Gene study [PEG], United States) that enrolled 1737 female and 2430 male subjects of European ancestry. We, then, replicated our findings for age at menopause using summary statistics from the PD consortium (19 773 women), followed by a meta-analysis combining all summary statistics., Results: For each year increase in age at menopause, the risk for PD decreased (odds ration [OR], 0.84; 95% confidence interval [CI], 0.73-0.98; P = 0.03) among women in our study, whereas there was no association among men (OR, 0.98; 95% CI, 0.85-1.11; P = 0.71). A replication using summary statistics from the PD consortium estimated an OR of 0.94 (95% CI, 0.90-0.99; P = 0.01), and we calculated a meta-analytic OR of 0.93 (95% CI, 0.89-0.98; P = 0.003). There was no indication for an association between age at menarche and PD (OR, 0.75; 95% CI, 0.44-1.29; P = 0.29)., Conclusions: A later age at menopause was associated with a decreased risk of PD in women, supporting the hypothesis that sex hormones or other factors related to late menopause may be neuroprotective in PD. © 2021 International Parkinson and Movement Disorder Society., (© 2021 International Parkinson and Movement Disorder Society.)
- Published
- 2021
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39. TMEM106B and CPOX are genetic determinants of cerebrospinal fluid Alzheimer's disease biomarker levels.
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Hong S, Dobricic V, Ohlei O, Bos I, Vos SJB, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Gabel S, Scheltens P, Teunissen CE, Engelborghs S, Frisoni G, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Sleegers K, Van Broeckhoven C, Tanzi RE, Ten Kate M, Wittig M, Franke A, Lill CM, Barkhof F, Lovestone S, Streffer J, Zetterberg H, Visser PJ, and Bertram L
- Subjects
- Aged, Chitinase-3-Like Protein 1 genetics, Female, Humans, Male, Neurofilament Proteins genetics, Neurogranin cerebrospinal fluid, Alzheimer Disease genetics, Biomarkers cerebrospinal fluid, Genome-Wide Association Study, Membrane Proteins genetics, Nerve Tissue Proteins genetics
- Abstract
Introduction: Neurofilament light (NfL), chitinase-3-like protein 1 (YKL-40), and neurogranin (Ng) are biomarkers for Alzheimer's disease (AD) to monitor axonal damage, astroglial activation, and synaptic degeneration, respectively., Methods: We performed genome-wide association studies (GWAS) using DNA and cerebrospinal fluid (CSF) samples from the EMIF-AD Multimodal Biomarker Discovery study for discovery, and the Alzheimer's Disease Neuroimaging Initiative study for validation analyses. GWAS were performed for all three CSF biomarkers using linear regression models adjusting for relevant covariates., Results: We identify novel genome-wide significant associations between DNA variants in TMEM106B and CSF levels of NfL, and between CPOX and YKL-40. We confirm previous work suggesting that YKL-40 levels are associated with DNA variants in CHI3L1., Discussion: Our study provides important new insights into the genetic architecture underlying interindividual variation in three AD-related CSF biomarkers. In particular, our data shed light on the sequence of events regarding the initiation and progression of neuropathological processes relevant in AD., (© 2021 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)
- Published
- 2021
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40. Replication study of plasma proteins relating to Alzheimer's pathology.
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Shi L, Winchester LM, Westwood S, Baird AL, Anand SN, Buckley NJ, Hye A, Ashton NJ, Bos I, Vos SJB, Kate MT, Scheltens P, Teunissen CE, Vandenberghe R, Gabel S, Meersmans K, Engelborghs S, De Roeck EE, Sleegers K, Frisoni GB, Blin O, Richardson JC, Bordet R, Molinuevo JL, Rami L, Wallin A, Kettunen P, Tsolaki M, Verhey F, Lléo A, Sala I, Popp J, Peyratout G, Martinez-Lage P, Tainta M, Johannsen P, Freund-Levi Y, Frölich L, Dobricic V, Legido-Quigley C, Barkhof F, Andreasson U, Blennow K, Zetterberg H, Streffer J, Lill CM, Bertram L, Visser PJ, Kolb HC, Narayan VA, Lovestone S, and Nevado-Holgado AJ
- Subjects
- Aged, Apolipoprotein E4 blood, Apolipoprotein E4 genetics, Cognitive Dysfunction blood, Cognitive Dysfunction pathology, Europe, Female, Humans, Male, Middle Aged, Alzheimer Disease blood, Alzheimer Disease pathology, Amyloid beta-Peptides blood, Biomarkers blood, Blood Proteins, Proteomics, tau Proteins blood
- Abstract
Introduction: This study sought to discover and replicate plasma proteomic biomarkers relating to Alzheimer's disease (AD) including both the "ATN" (amyloid/tau/neurodegeneration) diagnostic framework and clinical diagnosis., Methods: Plasma proteins from 972 subjects (372 controls, 409 mild cognitive impairment [MCI], and 191 AD) were measured using both SOMAscan and targeted assays, including 4001 and 25 proteins, respectively., Results: Protein co-expression network analysis of SOMAscan data revealed the relation between proteins and "N" varied across different neurodegeneration markers, indicating that the ATN variants are not interchangeable. Using hub proteins, age, and apolipoprotein E ε4 genotype discriminated AD from controls with an area under the curve (AUC) of 0.81 and MCI convertors from non-convertors with an AUC of 0.74. Targeted assays replicated the relation of four proteins with the ATN framework and clinical diagnosis., Discussion: Our study suggests that blood proteins can predict the presence of AD pathology as measured in the ATN framework as well as clinical diagnosis., (© 2021 the Alzheimer's Association.)
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- 2021
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41. MicroRNAs as Molecular Biomarkers for Parkinson's Disease Progression.
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Schilling M and Lill CM
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- Biomarkers, Disease Progression, Humans, MicroRNAs genetics, Parkinson Disease diagnosis, Parkinson Disease genetics
- Published
- 2021
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42. Genotype-Phenotype Relations for the Atypical Parkinsonism Genes: MDSGene Systematic Review.
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Wittke C, Petkovic S, Dobricic V, Schaake S, Respondek G, Weissbach A, Madoev H, Trinh J, Vollstedt EJ, Kuhnke N, Lohmann K, Dulovic Mahlow M, Marras C, König IR, Stamelou M, Bonifati V, Lill CM, Kasten M, Huppertz HJ, Höglinger G, and Klein C
- Subjects
- Genotype, Humans, Levodopa, Phenotype, Parkinson Disease, Parkinsonian Disorders genetics
- Abstract
This Movement Disorder Society Genetic mutation database Systematic Review focuses on monogenic atypical parkinsonism with mutations in the ATP13A2, DCTN1, DNAJC6, FBXO7, SYNJ1, and VPS13C genes. We screened 673 citations and extracted genotypic and phenotypic data for 140 patients (73 families) from 77 publications. In an exploratory fashion, we applied an automated classification procedure via an ensemble of bootstrap-aggregated ("bagged") decision trees to distinguish these 6 forms of monogenic atypical parkinsonism and found a high accuracy of 86.5% (95%CI, 86.3%-86.7%) based on the following 10 clinical variables: age at onset, spasticity and pyramidal signs, hypoventilation, decreased body weight, minimyoclonus, vertical gaze palsy, autonomic symptoms, other nonmotor symptoms, levodopa response quantification, and cognitive decline. Comparing monogenic atypical with monogenic typical parkinsonism using 2063 data sets from Movement Disorder Society Genetic mutation database on patients with SNCA, LRRK2, VPS35, Parkin, PINK1, and DJ-1 mutations, the age at onset was earlier in monogenic atypical parkinsonism (24 vs 40 years; P = 1.2647 × 10
-12 ) and levodopa response less favorable than in patients with monogenic typical presentations (49% vs 93%). In addition, we compared monogenic to nonmonogenic atypical parkinsonism using data from 362 patients with progressive supranuclear gaze palsy, corticobasal degeneration, multiple system atrophy, or frontotemporal lobar degeneration. Although these conditions share many clinical features with the monogenic atypical forms, they can typically be distinguished based on their later median age at onset (64 years; IQR, 57-70 years). In conclusion, age at onset, presence of specific signs, and degree of levodopa response inform differential diagnostic considerations and genetic testing indications in atypical forms of parkinsonism. © 2021 International Parkinson and Movement Disorder Society., (© 2021 International Parkinson and Movement Disorder Society.)- Published
- 2021
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43. Transcriptome-wide Association Study in Frontotemporal Dementia Identifies New Disease Loci by In Silico Analysis.
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Lill CM
- Subjects
- Computer Simulation, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Transcriptome, Frontotemporal Dementia genetics
- Published
- 2021
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44. Corrigendum to "Genetics of Parkinson's disease" [Mol. Cell. Probes (2016) 386-396].
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Lill CM
- Published
- 2020
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45. Genetic risk scores and hallucinations in patients with Parkinson disease.
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Kusters CDJ, Paul KC, Duarte Folle A, Keener AM, Bronstein JM, Dobricic V, Tysnes OB, Bertram L, Alves G, Sinsheimer JS, Lill CM, Maple-Grødem J, and Ritz BR
- Abstract
Objective: We examine the hypothesized overlap of genetic architecture for Alzheimer disease (AD), schizophrenia (SZ), and Parkinson disease (PD) through the use of polygenic risk scores (PRSs) with the occurrence of hallucinations in PD., Methods: We used 2 population-based studies (ParkWest, Norway, and Parkinson's Environment and Gene, USA) providing us with 399 patients with PD with European ancestry and a PD diagnosis after age 55 years to assess the associations between 4 PRSs and hallucinations after 5 years of mean disease duration. Based on the existing genome-wide association study of other large consortia, 4 PRSs were created: one each using AD, SZ, and PD cohorts and another PRS for height, which served as a negative control., Results: A higher prevalence of hallucinations was observed with each SD increase of the AD-PRS (odds ratio [OR]: 1.37, 95% confidence interval [CI]: 1.03-1.83). This effect was mainly driven by APOE (OR: 1.92, 95% CI: 1.14-3.22). In addition, a suggestive decrease and increase, respectively, in hallucination prevalence were observed with the SZ-PRS and the PD-PRS (OR: 0.77, 95% CI: 0.59-1.01; and OR: 1.29, 95% CI: 0.95-1.76, respectively). No association was observed with the height PRS., Conclusions: These results suggest that mechanisms for hallucinations in PD may in part be driven by the same genetic architecture that leads to cognitive decline in AD, especially by APOE ., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)
- Published
- 2020
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46. Relationship between Lipoprotein (a) and cognitive function - Results from the Berlin Aging Study II.
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Röhr F, Bucholtz N, Toepfer S, Norman K, Spira D, Steinhagen-Thiessen E, Lill CM, Bertram L, Demuth I, Buchmann N, and Düzel S
- Subjects
- Adult, Aged, Aging blood, Female, Humans, Male, Memory, Middle Aged, Aging physiology, Cognition, Lipoproteins blood
- Abstract
It has been suggested that an age-related loss of cognitive function might be driven by atherosclerotic effects associated with altered lipid patterns. However, the relationship between Lipoprotein (a) [Lp(a)] and healthy cognitive aging has not yet been sufficiently investigated. For the current analysis we used the cross-sectional data of 1,380 Berlin Aging Study II (BASE-II) participants aged 60 years and older (52.2% women, mean age 68 ± 4 years). We employed the Consortium to Establish a Registry for Alzheimer's Disease (CERAD)-Plus test battery to establish latent factors representing continuous measures of domain specific cognitive functions. Regression models adjusted for APOE genotypes, lipid parameters and other risk factors for cognitive impairment were applied to assess the association between Lp(a) and performance in specific cognitive domains. Men within the lowest Lp(a)-quintile showed better cognitive performance in the cognitive domain executive functions and processing speed (p = 0.027). No significant results were observed in women. The results of the current analysis of predominantly healthy BASE-II participants point towards an association between low Lp(a) concentrations and better cognitive performance. However, evidence for this relationship resulting from the current analysis and the employment of a differentiated cognitive assessment is rather weak.
- Published
- 2020
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47. Is APOE ε4 associated with cognitive performance in early MS?
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Engel S, Graetz C, Salmen A, Muthuraman M, Toenges G, Ambrosius B, Bayas A, Berthele A, Heesen C, Klotz L, Kümpfel T, Linker RA, Meuth SG, Paul F, Stangel M, Tackenberg B, Then Bergh F, Tumani H, Weber F, Wildemann B, Zettl UK, Antony G, Bittner S, Groppa S, Hemmer B, Wiendl H, Gold R, Zipp F, Lill CM, and Luessi F
- Subjects
- Adult, Female, Humans, Longitudinal Studies, Male, Multiple Sclerosis, Relapsing-Remitting complications, Multiple Sclerosis, Relapsing-Remitting genetics, Polymorphism, Single Nucleotide, Apolipoprotein E4 genetics, Cognitive Dysfunction etiology, Cognitive Dysfunction genetics, Demyelinating Diseases complications, Demyelinating Diseases genetics
- Abstract
Objective: To assess the impact of APOE polymorphisms on cognitive performance in patients newly diagnosed with clinically isolated syndrome (CIS) or relapsing-remitting MS (RRMS)., Methods: This multicenter cohort study included 552 untreated patients recently diagnosed with CIS or RRMS according to the 2005 revised McDonald criteria. The single nucleotide polymorphisms rs429358 (ε4) and rs7412 (ε2) of the APOE haplotype were assessed by allelic discrimination assays . Cognitive performance was evaluated using the 3-second paced auditory serial addition test and the Multiple Sclerosis Inventory Cognition (MUSIC). Sum scores were calculated to approximate the overall cognitive performance and memory-centered cognitive functions. The impact of the APOE carrier status on cognitive performance was assessed using multiple linear regression models, also including demographic, clinical, MRI, and lifestyle factors., Results: APOE ε4 homozygosity was associated with lower overall cognitive performance, whereas no relevant association was observed for APOE ε4 heterozygosity or APOE ε2 carrier status. Furthermore, higher disability levels, MRI lesion load, and depressive symptoms were associated with lower cognitive performance. Patients consuming alcohol had higher test scores than patients not consuming alcohol. Female sex, lower disability, and alcohol consumption were associated with better performance in the memory-centered subtests of MUSIC, whereas no relevant association was observed for APOE carrier status., Conclusion: Along with parameters of a higher disease burden, APOE ε4 homozygosity was identified as a potential predictor of cognitive performance in this large cohort of patients with CIS and early RRMS., (Copyright © 2020 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)
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- 2020
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48. WITHDRAWN: Genetics of Parkinson's disease.
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Lill CM
- Abstract
The Publisher regrets that this article is an accidental duplication of an article that has already been published, DOI of original article: https://doi.org/10.1016/j.mcp.2016.11.001. The duplicate article has therefore been withdrawn. The full Elsevier Policy on Article Withdrawal can be found at https://www.elsevier.com/about/our-business/policies/article-withdrawal.
- Published
- 2020
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49. The Rare IL22RA2 Signal Peptide Coding Variant rs28385692 Decreases Secretion of IL-22BP Isoform-1, -2 and -3 and Is Associated with Risk for Multiple Sclerosis.
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Gómez-Fernández P, Lopez de Lapuente Portilla A, Astobiza I, Mena J, Urtasun A, Altmann V, Matesanz F, Otaegui D, Urcelay E, Antigüedad A, Malhotra S, Montalban X, Castillo-Triviño T, Espino-Paisán L, Aktas O, Buttmann M, Chan A, Fontaine B, Gourraud PA, Hecker M, Hoffjan S, Kubisch C, Kümpfel T, Luessi F, Zettl UK, Zipp F, Alloza I, Comabella M, Lill CM, and Vandenbroeck K
- Subjects
- Adult, Amino Acid Sequence, Computer Simulation, Databases, Genetic, Gene Frequency genetics, HEK293 Cells, Humans, Middle Aged, Protein Isoforms genetics, Protein Isoforms metabolism, Receptors, Interleukin chemistry, Risk Factors, Genetic Predisposition to Disease, Multiple Sclerosis genetics, Polymorphism, Single Nucleotide genetics, Protein Sorting Signals genetics, Receptors, Interleukin genetics
- Abstract
The IL22RA2 locus is associated with risk for multiple sclerosis (MS) but causative variants are yet to be determined. In a single nucleotide polymorphism (SNP) screen of this locus in a Basque population, rs28385692, a rare coding variant substituting Leu for Pro at position 16 emerged significantly ( p = 0.02). This variant is located in the signal peptide (SP) shared by the three secreted protein isoforms produced by IL22RA2 (IL-22 binding protein-1(IL-22BPi1), IL-22BPi2 and IL-22BPi3). Genotyping was extended to a Europe-wide case-control dataset and yielded high significance in the full dataset ( p = 3.17 × 10
-4 ). Importantly, logistic regression analyses conditioning on the main known MS-associated SNP at this locus, rs17066096, revealed that this association was independent from the primary association signal in the full case-control dataset. In silico analysis predicted both disruption of the alpha helix of the H-region of the SP and decreased hydrophobicity of this region, ultimately affecting the SP cleavage site. We tested the effect of the p.Leu16Pro variant on the secretion of IL-22BPi1, IL-22BPi2 and IL-22BPi3 and observed that the Pro16 risk allele significantly lowers secretion levels of each of the isoforms to around 50%-60% in comparison to the Leu16 reference allele. Thus, our study suggests that genetically coded decreased levels of IL-22BP isoforms are associated with augmented risk for MS.- Published
- 2020
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50. Alzheimer's disease pathology explains association between dementia with Lewy bodies and APOE-ε4/TOMM40 long poly-T repeat allele variants.
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Prokopenko I, Miyakawa G, Zheng B, Heikkinen J, Petrova Quayle D, Udeh-Momoh C, Claringbould A, Neumann J, Haytural H, Kaakinen MA, Loizidou E, Meissner E, Bertram L, Gveric DO, Gentleman SM, Attems J, Perneczky R, Arzberger T, Muglia P, Lill CM, Parkkinen L, and Middleton LT
- Abstract
Introduction: The role of TOMM40-APOE 19q13.3 region variants is well documented in Alzheimer's disease (AD) but remains contentious in dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD)., Methods: We dissected genetic profiles within the TOMM40-APOE region in 451 individuals from four European brain banks, including DLB and PDD cases with/without neuropathological evidence of AD-related pathology and healthy controls., Results: TOMM 40 -L/ APOE -ε4 alleles were associated with DLB (OR
TOMM40 - L = 3.61; P value = 3.23 × 10-9 ; ORAPOE -ε4 = 3.75; P value = 4.90 × 10-10 ) and earlier age at onset of DLB (HRTOMM40 -L = 1.33, P value = .031; HRAPOE -ε4 = 1.46, P value = .004), but not with PDD. The TOMM40 -L/ APOE -ε4 effect was most pronounced in DLB individuals with concomitant AD pathology (ORTOMM40 -L = 4.40, P value = 1.15 × 10-6 ; ORAPOE - ε 4 = 5.65, P value = 2.97 × 10-8 ) but was not significant in DLB without AD. Meta-analyses combining all APOE -ε4 data in DLB confirmed our findings (ORDLB = 2.93, P value = 3.78 × 10-99 ; ORDLB+AD = 5.36, P value = 1.56 × 10-47 )., Discussion: APOE -ε4/ TOMM 40 -L alleles increase susceptibility and risk of earlier DLB onset, an effect explained by concomitant AD-related pathology. These findings have important implications in future drug discovery and development efforts in DLB., (© 2019 The Authors.)- Published
- 2019
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