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Discoveries that used Samples at BioSEND

Explore research articles and studies that have harnessed the resources and support provided by BioSEND. These publications represent significant strides in biomarker research for neurodegenerative and neuropsychiatric diseases and conditions. Discover our diverse sample services to see how BioSEND can support your research endeavors.

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Samples from the BioSpecimen Exchange for Neurological Disorders (BioSEND), which receives government support under a cooperative agreement grant (U24 NS095871) awarded by the National Institute of Neurological Disorders and Stroke (NINDS), were utilized for the publications below. We thank contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible.

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Publication Highlights

Groundbreaking discovery

Chia, R., Sabir, M.S., Bandres-Ciga, S. et al. Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture. Nat Genet 53, 294–303 (2021)

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milestone Research

Middleton JS, et al. (2023) Seed amplification assay results illustrate discrepancy in Parkinson's disease clinical diagnostic accuracy and error rates. J Neurol. 2023 Dec;270(12):5813-5818.

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latest publication

McGarry A et al. (2024). An exploratory metabolomic comparison of participants with fast or absent functional progression from 2CARE, a randomized, double-blind clinical trial in Huntington's disease. Scientific reports, 14(1), 1101.

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Witness the progress researchers achieve by accessing BioSEND's diverse sample
repository. These publications represent collaborative efforts involving contributors, patients, and families.

Full List of Publications

Samples from the BioSpecimen Exchange for Neurological Disorders (BioSEND), which receives government support under a cooperative agreement grant (U24 NS095871) awarded by the National Institute of Neurological Disorders and Stroke (NINDS), were utilized for the publications below.

We thank contributors who collected samples used in this study, as well as patients and their families, whose help and participation made this work possible.

scientific Reports

An exploratory metabolomic comparison of participants with fast or absent functional progression from 2CARE, a randomized, double-blind clinical trial in Huntington's disease

McGarry A, Hunter K, Gaughan J, Auinger P, Ferraro TN, Pradhan B, Ferrucci L, Egan JM, Moaddel R.

2024 Volume 14 Issue 1 Pages 88-97

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Huntington's disease (HD) is increasingly recognized for diverse pathology outside of the nervous system. To describe the biology of HD in relation to functional progression, we previously analyzed the plasma and CSF metabolome in a cross-sectional study of participants who had various degrees of functional impairment. Here, we carried out an exploratory study in plasma from HD individuals over a 3-year time frame to assess whether differences exist between those with fast or absent clinical progression. There were more differences in circulating metabolite levels for fast progressors compared to absent progressors (111 vs 20, nominal p < 0.05). All metabolite changes in faster progressors were decreases, whereas some metabolite concentrations increased in absent progressors. Many of the metabolite levels that decreased in the fast progressors were higher at Screening compared to absent progressors but ended up lower by Year 3. Changes in faster progression suggest greater oxidative stress and inflammation (kynurenine, diacylglycerides, cysteine), disturbances in nitric oxide and urea metabolism (arginine, citrulline, ornithine, GABR), lower polyamines (putrescine and spermine), elevated glucose, and deficient AMPK signaling. Metabolomic differences between fast and absent progressors suggest the possibility of predicting functional decline in HD, and possibly delaying it with interventions to augment arginine, polyamines, and glucose regulation.
Nature Genetics

Genome sequencing analysis identifies new loci associated with Lewy body dementia and provides insights into its genetic architecture

Ruth Chia, Marya S. Sabir, Sara Bandres-Ciga, Sara Saez-Atienzar, Regina H. Reynolds, Emil Gustavsson, Ronald L. Walton, Sarah Ahmed, Coralie Viollet, Jinhui Ding, Mary B. Makarious, Monica Diez-Fairen, Makayla K. Portley, Zalak Shah, Yevgeniya Abramzon, Dena G. Hernandez, Cornelis Blauwendraat, David J. Stone, John Eicher, Laura Parkkinen, Olaf Ansorge, Lorraine Clark, Lawrence S. Honig, Karen Marder, Afina Lemstra, Peter St George-Hyslop, Elisabet Londos, Kevin Morgan, Tammaryn Lashley, Thomas T. Warner, Zane Jaunmuktane, Douglas Galasko, Isabel Santana, Pentti J. Tienari, Liisa Myllykangas, Minna Oinas, Nigel J. Cairns, John C. Morris, Glenda M. Halliday, Vivianna M. Van Deerlin, John Q. Trojanowski, Maurizio Grassano, Andrea Calvo, Gabriele Mora, Antonio Canosa, Gianluca Floris, Ryan C. Bohannan, Francesca Brett, Ziv Gan-Or, Joshua T. Geiger, Anni Moore, Patrick May, Rejko Krüger, David S. Goldstein, Grisel Lopez, Nahid Tayebi, Ellen Sidransky, The American Genome Center, Lucy Norcliffe-Kaufmann, Jose-Alberto Palma, Horacio Kaufmann, Vikram G. Shakkottai, Matthew Perkins, Kathy L. Newell, Thomas Gasser, Claudia Schulte, Francesco Landi, Erika Salvi, Daniele Cusi, Eliezer Masliah, Ronald C. Kim, Chad A. Caraway, Edwin S. Monuki, Maura Brunetti, Ted M. Dawson, Liana S. Rosenthal, Marilyn S. Albert, Olga Pletnikova, Juan C. Troncoso, Margaret E. Flanagan, Qinwen Mao, Eileen H. Bigio, Eloy Rodríguez-Rodríguez, Jon Infante, Carmen Lage, Isabel González-Aramburu, Pascual Sanchez-Juan, Bernardino Ghetti, Julia Keith, Sandra E. Black, Mario Masellis, Ekaterina Rogaeva, Charles Duyckaerts, Alexis Brice, Suzanne Lesage, Georgia Xiromerisiou, Matthew J. Barrett, Bension S. Tilley, Steve Gentleman, Giancarlo Logroscino, Geidy E. Serrano, Thomas G. Beach, Ian G. McKeith, Alan J. Thomas, Johannes Attems, Christopher M. Morris, Laura Palmer, Seth Love, Claire Troakes, Safa Al-Sarraj, Angela K. Hodges, Dag Aarsland, Gregory Klein, Scott M. Kaiser, Randy Woltjer, Pau Pastor, Lynn M. Bekris, James B. Leverenz, Lilah M. Besser, Amanda Kuzma, Alan E. Renton, Alison Goate, David A. Bennett, Clemens R. Scherzer, Huw R. Morris, Raffaele Ferrari, Diego Albani, Stuart Pickering-Brown, Kelley Faber, Walter A. Kukull, Estrella Morenas-Rodriguez, Alberto Lleó, Juan Fortea, Daniel Alcolea, Jordi Clarimon, Mike A. Nalls, Luigi Ferrucci, Susan M. Resnick, Toshiko Tanaka, Tatiana M. Foroud, Neill R. Graff-Radford, Zbigniew K. Wszolek, Tanis Ferman, Bradley F. Boeve, John A. Hardy, Eric J. Topol, Ali Torkamani, Andrew B. Singleton, Mina Ryten, Dennis W. Dickson, Adriano Chiò, Owen A. Ross, J. Raphael Gibbs, Clifton L. Dalgard, Bryan J. Traynor and Sonja W. Scholz

2021 Volume 53 Issue 3 Pages 294-303

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The genetic basis of Lewy body dementia (LBD) is not well understood. Here, we performed whole-genome sequencing in large cohorts of LBD cases and neurologically healthy controls to study the genetic architecture of this understudied form of dementia, and to generate a resource for the scientific community. Genome-wide association analysis identified five independent risk loci, whereas genome-wide gene-aggregation tests implicated mutations in the gene GBA. Genetic risk scores demonstrate that LBD shares risk profiles and pathways with Alzheimer's disease and Parkinson's disease, providing a deeper molecular understanding of the complex genetic architecture of this age-related neurodegenerative condition.
Annals of Clinical and Translational Neurology

A rapid a-synuclein seed assay of Parkinson’s disease CSF panel shows high diagnostic accuracy

Christina D. Orr, Thong C. Ma, Andrew G. Hughson, Bradley R. Groveman, Ankit Srivastava, Douglas Galasko, Rachel Angers, Patrick Downey, Karen Crawford, Samantha J. Hutten, Un Jung Kang & Byron Caughey

2021 Volume 8 Issue 2 Pages 374-384

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Background: Assays that specifically measure α-synuclein seeding activity in biological fluids could revolutionize the diagnosis of Parkinson's disease. Recent improvements in α-synuclein real-time quaking-induced conversion assays of cerebrospinal fluid have dramatically reduced reaction times from 5-13 days down to 1-2 days. Objective: To test our improved assay against a panel of cerebrospinal fluid specimens from patients with Parkinson's disease and healthy controls from the MJ Fox Foundation/NINDS BioFIND collection. Methods: Specimens collected from healthy controls and patients with clinically typical moderate-to-advanced Parkinson's disease were tested without prior knowledge of disease status. Correlative analyses between assay parameters and clinical measures were performed by an independent investigator. Results: BioFIND samples gave positive signals in 105/108 (97%) Parkinson's disease cases versus 11/85 (13%) healthy controls. Receiver operating characteristic analyses of diagnosis of cases versus healthy controls gave areas under the curve of 95%. Beyond binary positive/negative determinations, only weak correlations were observed between various assay response parameters and Parkinson's disease clinical measures or other cerebrospinal fluid analytes. Of note, REM sleep behavioral disorder questionnaire scores correlated with the reaction times needed to reach 50% maximum fluorescence. Maximum fluorescence was inversely correlated with Unified Parkinson's Disease Rating Scale motor scores, which was driven by the patients without REM sleep behavioral disorder. Conclusions: Our improved α-synuclein seed amplification assay dramatically reduces the time needed to diagnose Parkinson's disease while maintaining the high-performance standards associated with previous α-synuclein seed assays, supporting the clinical utility of this assay for Parkinson's disease diagnosis.
Nature Genetics

Genome-wide survival study identifies a novel synaptic locus and polygenic score for cognitive progression in Parkinson’s disease

Ganqiang Liu, Jiajie Peng, Zhixiang Liao, Joseph J. Locascio, Jean-Christophe Corvol, Frank Zhu, Xianjun Dong, Jodi Maple-Grødem, Meghan C. Campbell, Alexis Elbaz, Suzanne Lesage, Alexis Brice, Graziella Mangone, John H. Growdon, Albert Y. Hung, Michael A. Schwarzschild, Michael T. Hayes, Anne-Marie Wills, Todd M. Herrington, Bernard Ravina, Ira Shoulson, Pille Taba, Sulev Kõks, Thomas G. Beach, Florence Cormier-Dequaire, Guido Alves, Ole-Bjørn Tysnes, Joel S. Perlmutter, Peter Heutink, Sami S. Amr, Jacobus J. van Hilten, Meike Kasten, Brit Mollenhauer, Claudia Trenkwalder, Christine Klein, Roger A. Barker, Caroline H. Williams-Gray, Johan Marinus, International Genetics of Parkinson Disease Progression (IGPP) Consortium and Clemens R. Scherzer

2021 Volume 53 Issue 6 Pages 787-793

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A key driver of patients'well-being and clinical trials for Parkinson's disease (PD) is the course that the disease takes over time (progression and prognosis). To assess how genetic variation influences the progression of PD over time to dementia, a major determinant for quality of life, we performed a longitudinal genome-wide survival study of 11.2 million variants in 3,821 patients with PD over 31,053 visits. We discover RIMS2 as a progression locus and confirm this in a replicate population (hazard ratio (HR) = 4.77, P = 2.78 × 10-11), identify suggestive evidence for TMEM108 (HR = 2.86, P = 2.09 × 10-8) and WWOX (HR = 2.12, P = 2.37 × 10-8) as progression loci, and confirm associations for GBA (HR = 1.93, P = 0.0002) and APOE (HR = 1.48, P = 0.001). Polygenic progression scores exhibit a substantial aggregate association with dementia risk, while polygenic susceptibility scores are not predictive. This study identifies a novel synaptic locus and polygenic score for cognitive disease progression in PD and proposes diverging genetic architectures of progression and susceptibility.
Frontiers in Neurology

Collaborative Efforts for Spinocerebellar Ataxia Research in the United States: CRC-SCA and READISCA

Chih-Chun Lin, Tetsuo Ashizawa and Sheng-Han Kuo

2020 Volume 11 Pages 902

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spinocerebellar ataxias are progressive neurodegenerative disorders primarily affecting the cerebellum. Although the first disease-causing gene was identified nearly 30 years ago, there is no known cure to date, and only a few options exist for symptomatic treatment, with modest effects. The recently developed tools in molecular biology, such as CRISPR/Cas9 and antisense oligonucleotides, can directly act on the disease mechanisms at the genomic or RNA level in disease models. In a nutshell, we are finally just one step away from clinical trials with therapies targeting the underlying genetic cause. However, we still face the challenges for rare neurodegenerative diseases: difficulty in obtaining a large cohort size for sufficient statistical power and the need for biomarkers and clinical outcome assessments (COA) with adequate sensitivity to reflect progression or treatment responses. To overcome these obstacles, ataxia experts form research networks for clinical trial readiness. In this review, we retrace our steps of the collaborative efforts among ataxia researchers in the United States over the years to study and treat these relentless disorders and the future directions of such research networks.
Movement Disorders

Magnetic Resonance Imaging and Neurofilament Light in the Differentiation of Parkinsonism

Derek B. Archer, PhD, Trina Mitchell, MS, Roxana G. Burciu, PhD, Jing Yang, MD, Salvatore Nigro, PhD, Aldo Quattrone, MD, Andrea Quattrone, MD, Andreas Jeromin, PhD, Nikolaus R. McFarland, MD, PhD, Michael S. Okun, MD, and David E. Vaillancourt, PhD

2020 Volume 35 Issue 8 Pages 1388-1395

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OBJECTIVE: Accurate diagnosis is particularly challenging in Parkinsons disease (PD), multiple system atrophy (MSAp), and progressive supranuclear palsy (PSP). We compare the utility of 3 promising biomarkers to differentiate disease state and explain disease severity in parkinsonism: the Automated Imaging Differentiation in Parkinsonism (AID-P), the Magnetic Resonance Parkinsonism Index (MRPI), and plasma-based neurofilament light chain protein (NfL). METHODS: For each biomarker, the area under the curve (AUC) of receiver operating characteristic curves were quantified for PD versus MSAp/PSP and MSAp versus PSP and statistically compared. Unique combinations of variables were also assessed. Furthermore, each measures association with disease severity was determined using stepwise multiple regression. RESULTS: For PD versus MSAp/PSP, AID-P (AUC, 0.900) measures had higher AUC compared with NfL (AUC, 0.747) and MRPI (AUC, 0.669), P < 0.05. For MSAp versus PSP, AID-P (AUC, 0.889), and MRPI (AUC, 0.824) measures were greater than NfL (AUC, 0.537), P < 0.05. We then combined measures to determine if any unique combination provided enhanced accuracy and found that no combination performed better than the AID-P alone in differentiating parkinsonisms. Furthermore, we found that the AID-P demonstrated the highest association with the MDS-UPDRS (R(adj) (2) -AID-P, 26.58%; NfL,15.12%; MRPI, 12.90%). CONCLUSIONS: Compared with MRPI and NfL, AID-P provides the best overall differentiation of PD versus MSAp/PSP. Both AID-P and MRPI are effective in differentiating MSAp versus PSP. Furthermore, combining biomarkers did not improve classification of disease state compared with using AID-P alone. The findings demonstrate in the current sample that the AID-P and MRPI are robust biomarkers for PD, MSAp, and PSP. © 2020 International Parkinson and Movement Disorder Society.
Neurology

β-Glucocerebrosidase activity in GBA-linked Parkinson disease: The type of mutation matters

Young Eun Huh, MD, PhD, Ming Sum Ruby Chiang, BS, Joseph J. Locascio, PhD, Zhixiang Liao, MS, Ganqiang Liu, PhD, Karbi Choudhury, BS, Yuliya I. Kuras, PhD, Idil Tuncali, BS, Aleksandar Videnovic, MD, Ann L. Hunt, DO, Michael A. Schwarzschild, MD, PhD, Albert Y. Hung, MD, PhD, Todd M. Herrington, MD, PhD, Michael T. Hayes, MD, Bradley T. Hyman, MD, PhD, Anne-Marie Wills, MD, Stephen N. Gomperts, MD, PhD, John H. Growdon, MD, PDBP, HBS, Sergio Pablo Sardi, PhD, Clemens R. Scherzer, MD

2020 Volume 95 Issue 6 Pages e685-e696

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OBJECTIVE: To test the relationship between clinically relevant types of GBA mutations (none, risk variants, mild mutations, severe mutations) and β-glucocerebrosidase activity in patients with Parkinson disease (PD) in cross-sectional and longitudinal case-control studies. METHODS: A total of 481 participants from the Harvard Biomarkers Study (HBS) and the NIH Parkinson's Disease Biomarkers Program (PDBP) were analyzed, including 47 patients with PD carrying GBA variants (GBA-PD), 247 without a GBA variant (idiopathic PD), and 187 healthy controls. Longitudinal analysis comprised 195 participants with 548 longitudinal measurements over a median follow-up period of 2.0 years (interquartile range, 1-2 years). RESULTS: β-Glucocerebrosidase activity was low in blood of patients with GBA-PD compared to healthy controls and patients with idiopathic PD, respectively, in HBS (p < 0.001) and PDBP (p < 0.05) in multivariate analyses adjusting for age, sex, blood storage time, and batch. Enzyme activity in patients with idiopathic PD was unchanged. Innovative enzymatic quantitative trait locus (xQTL) analysis revealed a negative linear association between residual β-glucocerebrosidase activity and mutation type with p < 0.0001. For each increment in the severity of mutation type, a reduction of mean β-glucocerebrosidase activity by 0.85 μmol/L/h (95% confidence interval, -1.17, -0.54) was predicted. In a first longitudinal analysis, increasing mutation severity types were prospectively associated with steeper declines in β-glucocerebrosidase activity during a median 2 years of follow-up (p = 0.02). CONCLUSIONS: Residual activity of the β-glucocerebrosidase enzyme measured in blood inversely correlates with clinical severity types of GBA mutations in PD. β-Glucocerebrosidase activity is a quantitative endophenotype that can be monitored noninvasively and targeted therapeutically.
Annals of Clinical and Translational Neurology

α-Synuclein in blood cells differentiates Parkinson's disease from healthy controls

suaad Abd Elhadi, Jessica Grigoletto, Maura Poli, Paolo Arosio, David Arkadir & Ronit Sharon

2019 Volume 6 Issue 12 Pages 2426-2436

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OBJECTIVE: To determine whether blood cells expressed α-Syn can differentiate Parkinson's disease (PD) from healthy controls (HC). METHODS: The concentrations of α-Syn were determined in samples of blood cell pellets using a quantitative Lipid-ELISA assay. In addition, the levels of total protein, hemoglobin, iron and H-ferritin were determined. The study includes samples from the Biofind cohort (n = 46 PD and 45 HC) and results were validated with an additional cohort (n = 35 PD and 28 HC). RESULTS: A composite biomarker consisting of the concentrations of total α-Syn, proteinase-K resistant (PK(res) ) α-Syn and phospho-Serine 129 α-Syn (PSer 129), is designed based on the analysis of the discovery BioFIND cohort. This composite biomarker differentiates a PD subgroup, presenting motor symptoms without dementia from a HC group, with a convincing accuracy, represented by an AUC = 0.81 (95% CI, 0.71 to 0.92). Closely similar results were obtained for the validation cohort, that is, AUC = 0.81, (95% CI, 0.70 to 0.94). INTERPRETATION: Our results demonstrate the potential usefulness of blood cells expressed α-Syn as a biomarker for PD.
Journal of the International Neuropsychological Society

Cognitive Indicators of Preclinical Behavioral Variant Frontotemporal Dementia in MAPT Carriers

Gayathri Cheran, Liwen Wu, Seonjoo Lee, Masood Manoochehri, Sarah Cines, Emer Fallon, Timothy Lynch, Judith Heidebrink, Henry Paulson, Jill Goldman, Edward Huey, and Stephanie Cosentino

2019 Volume 25 Issue 2 Pages 184-194

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OBJECTIVES: The cognitive indicators of preclinical behavioral variant Frontotemporal Dementia (bvFTD) have not been identified. To investigate these indicators, we compared cross-sectional performance on a range of cognitive measures in 12 carriers of pathogenic MAPT mutations not meeting diagnostic criteria for bvFTD (i.e., preclinical) versus 32 demographically-matched familial non-carriers (n = 44). Studying preclinical carriers offers a rare glimpse into emergent disease, environmentally and genetically contextualized through comparison to familial controls. METHODS: Evaluating personnel blinded to carrier status administered a standardized neuropsychological battery assessing attention, speed, executive function, language, memory, spatial ability, and social cognition. Results from mixed effect modeling were corrected for multiplicity of comparison by the false discovery rate method, and results were considered significant at p &lt; .05. To control for potential interfamilial variation arising from enrollment of six families, family was treated as a random effect, while carrier status, age, gender, and education were treated as fixed effects. RESULTS: Group differences were detected in 17 of 31 cognitive scores and spanned all domains except spatial ability. As hypothesized, carriers performed worse on specific measures of executive function, and social cognition, but also on measures of attention, speed, semantic processing, and memory storage and retrieval. CONCLUSIONS: Most notably, group differences arose on measures of memory storage, challenging long-standing ideas about the absence of amnestic features on neuropsychological testing in early bvFTD. Current findings provide important and clinically relevant information about specific measures that may be sensitive to early bvFTD, and advance understanding of neurocognitive changes that occur early in the disease. (JINS, 2019, 25, 184-194).
Neurology: Genetics

Genetic risk of Parkinson disease and progression:: An analysis of 13 longitudinal cohorts

Hirotaka Iwaki, MD, Cornelis Blauwendraat, PhD, Hampton L. Leonard, MS, Ganqiang Liu, PhD, Jodi Maple-Grødem, PhD, Jean-Christophe Corvol, MD, PhD, Lasse Pihlstrøm, MD, PhD, Marlies van Nimwegen, PhD, Samantha J. Hutten, PhD, Khanh-Dung H. Nguyen, PhD, Jacqueline Rick, PhD, Shirley Eberly, MS, Faraz Faghri, MS, Peggy Auinger, MS, Kirsten M. Scott, MRCP, MPhil, Ruwani Wijeyekoon, MRCP, Vivianna M. Van Deerlin, MD, PhD, Dena G. Hernandez, PhD, Aaron G. Day-Williams, PhD, Alexis Brice, MD, Guido Alves, MD, PhD, Alastair J. Noyce, MRCP, PhD, Ole-Bjørn Tysnes, MD, PhD, Jonathan R. Evans, MRCP, PhD, David P. Breen, MRCP, PhD, Karol Estrada, PhD, Claire E. Wegel, MPH, Fabrice Danjou, MD, PhD, David K. Simon, MD, PhD, Bernard Ravina, MD, Mathias Toft, MD, PhD, Peter Heutink, PhD, Bastiaan R. Bloem, MD, PhD, Daniel Weintraub, MD, Roger A. Barker, MRCP, PhD, Caroline H. Williams-Gray, MRCP, PhD, Bart P. van de Warrenburg, MD, PhD, Jacobus J. Van Hilten, MD, PhD, Clemens R. Scherzer, MD, Andrew B. Singleton, PhD, and Mike A. Nalls, PhD

2019 Volume 5 Issue 4 Pages e348

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OBJECTIVE: To determine if any association between previously identified alleles that confer risk for Parkinson disease and variables measuring disease progression. METHODS: We evaluated the association between 31 risk variants and variables measuring disease progression. A total of 23,423 visits by 4,307 patients of European ancestry from 13 longitudinal cohorts in Europe, North America, and Australia were analyzed. RESULTS: We confirmed the importance of GBA on phenotypes. GBA variants were associated with the development of daytime sleepiness (p.N370S: hazard ratio [HR] 3.28 [1.69-6.34]) and possible REM sleep behavior (p.T408M: odds ratio 6.48 [2.04-20.60]). We also replicated previously reported associations of GBA variants with motor/cognitive declines. The other genotype-phenotype associations include an intergenic variant near LRRK2 and the faster development of motor symptom (Hoehn and Yahr scale 3.0 HR 1.33 [1.16-1.52] for the C allele of rs76904798) and an intronic variant in PMVK and the development of wearing-off effects (HR 1.66 [1.19-2.31] for the C allele of rs114138760). Age at onset was associated with TMEM175 variant p.M393T (-0.72 [-1.21 to -0.23] in years), the C allele of rs199347 (intronic region of GPNMB, 0.70 [0.27-1.14]), and G allele of rs1106180 (intronic region of CCDC62, 0.62 [0.21-1.03]). CONCLUSIONS: This study provides evidence that alleles associated with Parkinson disease risk, in particular GBA variants, also contribute to the heterogeneity of multiple motor and nonmotor aspects. Accounting for genetic variability will be a useful factor in understanding disease course and in minimizing heterogeneity in clinical trials.