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Saffie Awad P, Makarious MB, Elsayed I, Sanyaolu A, Wild Crea P, Schumacher Schuh AF, Levine KS, Vitale D, Korestky MJ, Kim J, Peixoto Leal T, Perinan MT, Dey S, Noyce AJ, Reyes-Palomares A, Rodriguez-Losada N, Foo JN, Mohamed W, Heilbron K, Norcliffe-Kaufmann L, Rizig M, Okubadejo N, Nalls M, Blauwendraat C, Singleton A, Leonard H, Mata IF, Bandres Ciga S. Insights into Ancestral Diversity in Parkinsons Disease Risk: A Comparative Assessment of Polygenic Risk Scores. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.11.28.23299090. [PMID: 38076954 PMCID: PMC10705647 DOI: 10.1101/2023.11.28.23299090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Objectives To evaluate and compare different polygenic risk score (PRS) models in predicting Parkinsons disease (PD) across diverse ancestries, focusing on identifying the most suitable approach for each population and potentially contributing to equitable advancements in precision medicine. Methods We constructed a total of 105 PRS across individual level data from seven diverse ancestries. First, a cross-ancestry conventional PRS comparison was implemented by utilizing the 90 known European risk loci with weighted effects from four independent summary statistics including European, East Asian, Latino/Admixed American, and African/Admixed. These models were adjusted by sex, age, and principal components (28 PRS) and by sex, age, and percentage of admixture (28 PRS) for comparison. Secondly, a novel and refined multi-ancestry best-fit PRS approach was then applied across the seven ancestries by leveraging multi-ancestry meta-analyzed summary statistics and using a p-value thresholding approach (49 PRS) to enhance prediction applicability in a global setting. Results European-based PRS models predicted disease status across all ancestries to differing degrees of accuracy. Ashkenazi Jewish had the highest Odds Ratio (OR): 1.96 (95% CI: 1.69-2.25, p < 0.0001) with an AUC (Area Under the Curve) of 68%. Conversely, the East Asian population, despite having fewer predictive variants (84 out of 90), had an OR of 1.37 (95% CI: 1.32-1.42) and an AUC of 62%, illustrating the cross-ancestry transferability of this model. Lower OR alongside broader confidence intervals were observed in other populations, including Africans (OR =1.38, 95% CI: 1.12-1.63, p=0.001). Adjustment by percentage of admixture did not outperform principal components. Multi-ancestry best-fit PRS models improved risk prediction in European, Ashkenazi Jewish, and African ancestries, yet didn't surpass conventional PRS in admixed populations such as Latino/American admixed and African admixed populations. Interpretation The present study represents a novel and comprehensive assessment of PRS performance across seven ancestries in PD, highlighting the inadequacy of a 'one size fits all' approach in genetic risk prediction. We demonstrated that European based PD PRS models are partially transferable to other ancestries and could be improved by a novel best-fit multi-ancestry PRS, especially in non-admixed populations.
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Schaffner SL, Casazza W, Artaud F, Konwar C, Merrill SM, Domenighetti C, Schulze-Hentrich JM, Lesage S, Brice A, Corvol JC, Mostafavi S, Dennis JK, Elbaz A, Kobor MS. Genetic variation and pesticide exposure influence blood DNA methylation signatures in females with early-stage Parkinson's disease. NPJ Parkinsons Dis 2024; 10:98. [PMID: 38714693 PMCID: PMC11076573 DOI: 10.1038/s41531-024-00704-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 04/05/2024] [Indexed: 05/10/2024] Open
Abstract
Although sex, genetics, and exposures can individually influence risk for sporadic Parkinson's disease (PD), the joint contributions of these factors to the epigenetic etiology of PD have not been comprehensively assessed. Here, we profiled sex-stratified genome-wide blood DNAm patterns, SNP genotype, and pesticide exposure in agricultural workers (71 early-stage PD cases, 147 controls) and explored replication in three independent samples of varying demographics (n = 218, 222, and 872). Using a region-based approach, we found more associations of blood DNAm with PD in females (69 regions) than in males (2 regions, Δβadj| ≥0.03, padj ≤ 0.05). For 48 regions in females, models including genotype or genotype and pesticide exposure substantially improved in explaining interindividual variation in DNAm (padj ≤ 0.05), and accounting for these variables decreased the estimated effect of PD on DNAm. The results suggested that genotype, and to a lesser degree, genotype-exposure interactions contributed to variation in PD-associated DNAm. Our findings should be further explored in larger study populations and in experimental systems, preferably with precise measures of exposure.
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Affiliation(s)
- S L Schaffner
- Edwin S. H. Leong Centre for Healthy Aging, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
| | - W Casazza
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
| | - F Artaud
- Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, CESP, 94805, Villejuif, France
| | - C Konwar
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada
| | - S M Merrill
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada
| | - C Domenighetti
- Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, CESP, 94805, Villejuif, France
| | - J M Schulze-Hentrich
- Department of Genetics/Epigenetics, Faculty NT, Saarland University, 66041, Saarbrücken, Germany
| | - S Lesage
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Paris, France
| | - A Brice
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Paris, France
| | - J C Corvol
- Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, INSERM, CNRS, Assistance Publique Hôpitaux de Paris, Paris, France
- Sorbonne University, Assistance Publique Hôpitaux de Paris, Paris Brain Insitute - ICM, Inserm, CNRS, Department of Neurology and CIC Neurosciences, Pitié-Salpêtrière Hospital, Paris, France
| | - S Mostafavi
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
- Paul Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA
| | - J K Dennis
- Edwin S. H. Leong Centre for Healthy Aging, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada
- Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada
| | - A Elbaz
- Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, CESP, 94805, Villejuif, France
| | - M S Kobor
- Edwin S. H. Leong Centre for Healthy Aging, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada.
- Centre for Molecular Medicine and Therapeutics, BC Children's Hospital, Vancouver, BC, Canada.
- Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada.
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Trevisan L, Gaudio A, Monfrini E, Avanzino L, Di Fonzo A, Mandich P. Genetics in Parkinson's disease, state-of-the-art and future perspectives. Br Med Bull 2024; 149:60-71. [PMID: 38282031 PMCID: PMC10938543 DOI: 10.1093/bmb/ldad035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 11/30/2023] [Accepted: 12/12/2023] [Indexed: 01/30/2024]
Abstract
BACKGROUND Parkinson's disease (PD) is the second most common neurodegenerative disorder and is clinically characterized by the presence of motor (bradykinesia, rigidity, rest tremor and postural instability) and non-motor symptoms (cognitive impairment, autonomic dysfunction, sleep disorders, depression and hyposmia). The aetiology of PD is unknown except for a small but significant contribution of monogenic forms. SOURCES OF DATA No new data were generated or analyzed in support of this review. AREAS OF AGREEMENT Up to 15% of PD patients carry pathogenic variants in PD-associated genes. Some of these genes are associated with mendelian inheritance, while others act as risk factors. Genetic background influences age of onset, disease course, prognosis and therapeutic response. AREAS OF CONTROVERSY Genetic testing is not routinely offered in the clinical setting, but it may have relevant implications, especially in terms of prognosis, response to therapies and inclusion in clinical trials. Widely adopted clinical guidelines on genetic testing are still lacking and open to debate. Some new genetic associations are still awaiting confirmation, and selecting the appropriate genes to be included in diagnostic panels represents a difficult task. Finally, it is still under study whether (and to which degree) specific genetic forms may influence the outcome of PD therapies. GROWING POINTS Polygenic Risk Scores (PRS) may represent a useful tool to genetically stratify the population in terms of disease risk, prognosis and therapeutic outcomes. AREAS TIMELY FOR DEVELOPING RESEARCH The application of PRS and integrated multi-omics in PD promises to improve the personalized care of patients.
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Affiliation(s)
- L Trevisan
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Largo P. Daneo 3, Genova, 16132, Italy
- IRCCS Ospedale Policlinico San Martino – SS Centro Tumori Ereditari, Largo R. Benzi 10, Genova, 16132, Italy
| | - A Gaudio
- IRCCS Ospedale Policlinico San Martino- UOC Genetica Medica, Largo R. Benzi 10, Genova, 16132, Italy
| | - E Monfrini
- Dino Ferrari Center, Neuroscience Section, Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza 35, Milan, 20122, Italy
- Neurology Unit, Foundation IRCCS Ca’Granda Ospedale Maggiore Policlinico, Via Festa del Perdono 7, Milan, 20122, Italy
| | - L Avanzino
- Department of Experimental Medicine, Section of Human Physiology, University of Genoa, Viale Benedetto XV/3, Genova, 16132, Italy
- IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 3, Genova, 16132, Italy
| | - A Di Fonzo
- Dino Ferrari Center, Neuroscience Section, Department of Pathophysiology and Transplantation, University of Milan, Via Francesco Sforza 35, Milan, 20122, Italy
- Neurology Unit, Foundation IRCCS Ca’Granda Ospedale Maggiore Policlinico, Via Festa del Perdono 7, Milan, 20122, Italy
| | - P Mandich
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Largo P. Daneo 3, Genova, 16132, Italy
- IRCCS Ospedale Policlinico San Martino- UOC Genetica Medica, Largo R. Benzi 10, Genova, 16132, Italy
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Park M, Lee YG. Association of Family History and Polygenic Risk Score With Longitudinal Prognosis in Parkinson Disease. Neurol Genet 2024; 10:e200115. [PMID: 38169864 PMCID: PMC10759146 DOI: 10.1212/nxg.0000000000200115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/02/2023] [Indexed: 01/05/2024]
Abstract
Background and Objectives Evidence suggests that either family history or polygenic risk score (PRS) is associated with developing Parkinson disease (PD). However, little is known about the longitudinal prognosis of PD according to family history and higher PRS. Methods From the Parkinson's Progression Markers Initiative database, 395 patients with PD who followed up for more than 2 years were grouped into those with family history within first-degree, second-degree, and third-degree relatives (N = 127 [32.2%]) vs those without (N = 268 [67.8%]). The PRS of 386 patients was computed using whole-genome sequencing data. Longitudinal assessment of motor, cognition, and imaging based on dopaminergic degeneration was conducted during the regular follow-up period. Effects of family history, PRS, or both on longitudinal changes of cognition, motor severity, and nigrostriatal degeneration were tested using a linear mixed model. The risk of freezing of gait (FOG) according to family history was assessed using the Kaplan-Meier analysis and Cox regression models. Results During a median follow-up of 9.1 years, PD with positive family history showed a slower decline of caudate dopamine transporter uptake (β estimate of family history × time = 0.02, 95% CI = 0.002-0.036, p = 0.027). Family history of PD and higher PRS were independently associated with a slower decline of Montreal Cognitive Assessment (β estimate of family history × time = 0.12, 95% CI = 0.02-0.22, p = 0.017; β estimate of PRS × time = 0.09, 95% CI = 0.03-0.16, p = 0.006). In those 364 patients without FOG at baseline, PD with positive family history had a lower risk of FOG (hazard ratio of family history = 0.57, 95% CI = 0.38-0.84, p = 0.005). Discussion Having a family history of PD predicts slower progression of cognitive decline and caudate dopaminergic degeneration, and less FOG compared with those without a family history independent of PRS. Taken together, information on family history could be used as a proxy for the clinical heterogeneity of PD. Trial Registration Information The study was registered at clinicaltrials.gov (NCT01141023), and the enrollment began June 1, 2010.
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Affiliation(s)
- Mincheol Park
- From the Department of Neurology (M.P.), Gwangmyeong Hospital, Chung-Ang University College of Medicine; and Department of Neurology (Y.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea
| | - Young-Gun Lee
- From the Department of Neurology (M.P.), Gwangmyeong Hospital, Chung-Ang University College of Medicine; and Department of Neurology (Y.L.), Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea
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Lim SY, Klein C. Parkinson's Disease is Predominantly a Genetic Disease. JOURNAL OF PARKINSON'S DISEASE 2024; 14:467-482. [PMID: 38552119 DOI: 10.3233/jpd-230376] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/06/2024]
Abstract
The discovery of a pathogenic variant in the alpha-synuclein (SNCA) gene in the Contursi kindred in 1997 indisputably confirmed a genetic cause in a subset of Parkinson's disease (PD) patients. Currently, pathogenic variants in one of the seven established PD genes or the strongest known risk factor gene, GBA1, are identified in ∼15% of PD patients unselected for age at onset and family history. In this Debate article, we highlight multiple avenues of research that suggest an important - and in some cases even predominant - role for genetics in PD aetiology, including familial clustering, high rates of monogenic PD in selected populations, and complete penetrance with certain forms. At first sight, the steep increase in PD prevalence exceeding that of other neurodegenerative diseases may argue against a predominant genetic etiology. Notably, the principal genetic contribution in PD is conferred by pathogenic variants in LRRK2 and GBA1 and, in both cases, characterized by an overall late age of onset and age-related penetrance. In addition, polygenic risk plays a considerable role in PD. However, it is likely that, in the majority of PD patients, a complex interplay of aging, genetic, environmental, and epigenetic factors leads to disease development.
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Affiliation(s)
- Shen-Yang Lim
- The Mah Pooi Soo and Tan Chin Nam Centre for Parkinson's and Related Disorders, University of Malaya, Kuala Lumpur, Malaysia
- Department of Medicine, Faculty of Medicine, Division of Neurology, University of Malaya, Kuala Lumpur, Malaysia
| | - Christine Klein
- Institute of Neurogenetics, University of Luebeck, Luebeck, Germany
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Tunold JA, Tan MMX, Koga S, Geut H, Rozemuller AJM, Valentino R, Sekiya H, Martin NB, Heckman MG, Bras J, Guerreiro R, Dickson DW, Toft M, van de Berg WDJ, Ross OA, Pihlstrøm L. Lysosomal polygenic risk is associated with the severity of neuropathology in Lewy body disease. Brain 2023; 146:4077-4087. [PMID: 37247383 PMCID: PMC10545498 DOI: 10.1093/brain/awad183] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 05/08/2023] [Accepted: 05/10/2023] [Indexed: 05/31/2023] Open
Abstract
Intraneuronal accumulation of misfolded α-synuclein is the pathological hallmark of Parkinson's disease and dementia with Lewy bodies, often co-occurring with variable degrees of Alzheimer's disease related neuropathology. Genetic association studies have successfully identified common variants associated with disease risk and phenotypic traits in Lewy body disease, yet little is known about the genetic contribution to neuropathological heterogeneity. Using summary statistics from Parkinson's disease and Alzheimer's disease genome-wide association studies, we calculated polygenic risk scores and investigated the relationship with Lewy, amyloid-β and tau pathology. Associations were nominated in neuropathologically defined samples with Lewy body disease from the Netherlands Brain Bank (n = 217) and followed up in an independent sample series from the Mayo Clinic Brain Bank (n = 394). We also generated stratified polygenic risk scores based on single-nucleotide polymorphisms annotated to eight functional pathways or cell types previously implicated in Parkinson's disease and assessed for association with Lewy pathology in subgroups with and without significant Alzheimer's disease co-pathology. In an ordinal logistic regression model, the Alzheimer's disease polygenic risk score was associated with concomitant amyloid-β and tau pathology in both cohorts. Moreover, both cohorts showed a significant association between lysosomal pathway polygenic risk and Lewy pathology, which was more consistent than the association with a general Parkinson's disease risk score and specific to the subset of samples without significant concomitant Alzheimer's disease related neuropathology. Our findings provide proof of principle that the specific risk alleles a patient carries for Parkinson's and Alzheimer's disease also influence key aspects of the underlying neuropathology in Lewy body disease. The interrelations between genetic architecture and neuropathology are complex, as our results implicate lysosomal risk loci specifically in the subset of samples without Alzheimer's disease co-pathology. Our findings hold promise that genetic profiling may help predict the vulnerability to specific neuropathologies in Lewy body disease, with potential relevance for the further development of precision medicine in these disorders.
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Affiliation(s)
- Jon-Anders Tunold
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
| | - Manuela M X Tan
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
| | - Shunsuke Koga
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Hanneke Geut
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
| | - Annemieke J M Rozemuller
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Department of Pathology, Amsterdam UMC, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Program Neurodegeneration, Amsterdam Neuroscience, 1081 HV Amsterdam, The Netherlands
| | - Rebecca Valentino
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Hiroaki Sekiya
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Nicholas B Martin
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Michael G Heckman
- Division of Clinical Trials and Biostatistics, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Jose Bras
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI 49503, USA
| | - Rita Guerreiro
- Department of Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI 49503, USA
- Division of Psychiatry and Behavioral Medicine, Michigan State University College of Human Medicine, Grand Rapids, MI 49503, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
- Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, 0372 Oslo, Norway
| | - Wilma D J van de Berg
- Department of Anatomy and Neurosciences, Amsterdam UMC, Vrije Universiteit, 1081 HV Amsterdam, The Netherlands
- Program Neurodegeneration, Amsterdam Neuroscience, 1081 HV Amsterdam, The Netherlands
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Lasse Pihlstrøm
- Department of Neurology, Oslo University Hospital, 0424 Oslo, Norway
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van Loo HM, de Vries YA, Taylor J, Todorovic L, Dollinger C, Kendler KS. Clinical characteristics indexing genetic differences in bipolar disorder - a systematic review. Mol Psychiatry 2023; 28:3661-3670. [PMID: 37968345 DOI: 10.1038/s41380-023-02297-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 09/29/2023] [Accepted: 10/06/2023] [Indexed: 11/17/2023]
Abstract
Bipolar disorder is a heterogenous condition with a varied clinical presentation. While progress has been made in identifying genetic variants associated with bipolar disorder, most common genetic variants have not yet been identified. More detailed phenotyping (beyond diagnosis) may increase the chance of finding genetic variants. Our aim therefore was to identify clinical characteristics that index genetic differences in bipolar disorder.We performed a systematic review of all genome-wide molecular genetic, family, and twin studies investigating familial/genetic influences on the clinical characteristics of bipolar disorder. We performed an electronic database search of PubMed and PsycInfo until October 2022. We reviewed title/abstracts of 2693 unique records and full texts of 391 reports, identifying 445 relevant analyses from 142 different reports. These reports described 199 analyses from family studies, 183 analyses from molecular genetic studies and 63 analyses from other types of studies. We summarized the overall evidence per phenotype considering study quality, power, and number of studies.We found moderate to strong evidence for a positive association of age at onset, subtype (bipolar I versus bipolar II), psychotic symptoms and manic symptoms with familial/genetic risk of bipolar disorder. Sex was not associated with overall genetic risk but could indicate qualitative genetic differences. Assessment of genetically relevant clinical characteristics of patients with bipolar disorder can be used to increase the phenotypic and genetic homogeneity of the sample in future genetic studies, which may yield more power, increase specificity, and improve understanding of the genetic architecture of bipolar disorder.
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Affiliation(s)
- Hanna M van Loo
- Department of Psychiatry and Interdisciplinary Center Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
| | - Ymkje Anna de Vries
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Jacob Taylor
- Department of Psychiatry, Brigham and Women's Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Luka Todorovic
- Department of Psychiatry and Interdisciplinary Center Psychopathology and Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
- Department of Child and Adolescent Psychiatry, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Camille Dollinger
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Kenneth S Kendler
- Virginia Institute for Psychiatric and Behavioral Genetics and Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
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Shannon ML, Muhammad A, James NT, Williams ML, Breeyear J, Edwards T, Mosley JD, Choi L, Kannankeril P, Van Driest S. Variant-based heritability assessment of dexmedetomidine and fentanyl clearance in pediatric patients. Clin Transl Sci 2023; 16:1628-1638. [PMID: 37353859 PMCID: PMC10499425 DOI: 10.1111/cts.13574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/12/2023] [Accepted: 06/01/2023] [Indexed: 06/25/2023] Open
Abstract
Despite complex pathways of drug disposition, clinical pharmacogenetic predictors currently rely on only a few high effect variants. Quantification of the polygenic contribution to variability in drug disposition is necessary to prioritize target drugs for pharmacogenomic approaches and guide analytic methods. Dexmedetomidine and fentanyl, often used in postoperative care of pediatric patients, have high rates of inter-individual variability in dosing requirements. Analyzing previously generated population pharmacokinetic parameters, we used Bayesian hierarchical mixed modeling to measure narrow-sense (additive) heritability (h SNP 2 ) of dexmedetomidine and fentanyl clearance in children and identify relative contributions of small, moderate, and large effect-size variants toh SNP 2 . We used genome-wide association studies (GWAS) to identify variants contributing to variation in dexmedetomidine and fentanyl clearance, followed by functional analyses to identify associated pathways. For dexmedetomidine, median clearance was 33.0 L/h (interquartile range [IQR] 23.8-47.9 L/h) andh SNP 2 was estimated to be 0.35 (90% credible interval 0.00-0.90), with 45% ofh SNP 2 attributed to large-, 32% to moderate-, and 23% to small-effect variants. The fentanyl cohort had median clearance of 8.2 L/h (IQR 4.7-16.7 L/h), with estimatedh SNP 2 of 0.30 (90% credible interval 0.00-0.84). Large-effect variants accounted for 30% ofh SNP 2 , whereas moderate- and small-effect variants accounted for 37% and 33%, respectively. As expected, given small sample sizes, no individual variants or pathways were significantly associated with dexmedetomidine or fentanyl clearance by GWAS. We conclude that clearance of both drugs is highly polygenic, motivating the future use of polygenic risk scores to guide appropriate dosing of dexmedetomidine and fentanyl.
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Affiliation(s)
| | - Ayesha Muhammad
- School of MedicineVanderbilt UniversityNashvilleTennesseeUSA
| | - Nathan T. James
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
Berry Consultants, LLCAustinTexasUSA
| | - Michael L. Williams
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
Department of Clinical Pharmacology and Quantitative PharmacologyAstraZenecaGothenburgSweden
| | - Joseph Breeyear
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Todd Edwards
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jonathan D. Mosley
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Leena Choi
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Prince Kannankeril
- Center for Pediatric Precision Medicine, Department of PediatricsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Sara Van Driest
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Center for Pediatric Precision Medicine, Department of PediatricsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
All of Us Research ProgramNational Institutes of HealthWashingtonDCUSA
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Czarniak N, Kamińska J, Matowicka-Karna J, Koper-Lenkiewicz OM. Cerebrospinal Fluid-Basic Concepts Review. Biomedicines 2023; 11:biomedicines11051461. [PMID: 37239132 DOI: 10.3390/biomedicines11051461] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2023] [Revised: 05/08/2023] [Accepted: 05/15/2023] [Indexed: 05/28/2023] Open
Abstract
Cerebrospinal fluid plays a crucial role in protecting the central nervous system (CNS) by providing mechanical support, acting as a shock absorber, and transporting nutrients and waste products. It is produced in the ventricles of the brain and circulates through the brain and spinal cord in a continuous flow. In the current review, we presented basic concepts related to cerebrospinal fluid history, cerebrospinal fluid production, circulation, and its main components, the role of the blood-brain barrier and the blood-cerebrospinal fluid barrier in the maintenance of cerebrospinal fluid homeostasis, and the utility of Albumin Quotient (QAlb) evaluation in the diagnosis of CNS diseases. We also discussed the collection of cerebrospinal fluid (type, number of tubes, and volume), time of transport to the laboratory, and storage conditions. Finally, we briefly presented the role of cerebrospinal fluid examination in CNS disease diagnosis of various etiologies and highlighted that research on identifying cerebrospinal fluid biomarkers indicating disease presence or severity, evaluating treatment effectiveness, and enabling understanding of pathogenesis and disease mechanisms is of great importance. Thus, in our opinion, research on cerebrospinal fluid is still necessary for both the improvement of CNS disease management and the discovery of new treatment options.
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Affiliation(s)
- Natalia Czarniak
- Department of Clinical Laboratory Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland
| | - Joanna Kamińska
- Department of Clinical Laboratory Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland
| | - Joanna Matowicka-Karna
- Department of Clinical Laboratory Diagnostics, Medical University of Bialystok, 15-269 Bialystok, Poland
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10
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Zhou X, Chen Y, Ip FCF, Jiang Y, Cao H, Lv G, Zhong H, Chen J, Ye T, Chen Y, Zhang Y, Ma S, Lo RMN, Tong EPS, Mok VCT, Kwok TCY, Guo Q, Mok KY, Shoai M, Hardy J, Chen L, Fu AKY, Ip NY. Deep learning-based polygenic risk analysis for Alzheimer's disease prediction. COMMUNICATIONS MEDICINE 2023; 3:49. [PMID: 37024668 PMCID: PMC10079691 DOI: 10.1038/s43856-023-00269-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/06/2023] [Indexed: 04/08/2023] Open
Abstract
BACKGROUND The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.
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Affiliation(s)
- Xiaopu Zhou
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
| | - Yu Chen
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, Guangdong, 518055, China
| | - Fanny C F Ip
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
| | - Yuanbing Jiang
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
| | - Han Cao
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Ge Lv
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Huan Zhong
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
| | - Jiahang Chen
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Tao Ye
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, Guangdong, 518055, China
| | - Yuewen Chen
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
- Chinese Academy of Sciences Key Laboratory of Brain Connectome and Manipulation, Shenzhen Key Laboratory of Translational Research for Brain Diseases, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, Guangdong, 518055, China
| | - Yulin Zhang
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
| | - Shuangshuang Ma
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
| | - Ronnie M N Lo
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Estella P S Tong
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Vincent C T Mok
- Gerald Choa Neuroscience Centre, Lui Che Woo Institute of Innovative Medicine, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Division of Neurology, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Timothy C Y Kwok
- Therese Pei Fong Chow Research Centre for Prevention of Dementia, Division of Geriatrics, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Kin Y Mok
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Maryam Shoai
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - John Hardy
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- HKUST Jockey Club Institute for Advanced Study, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Lei Chen
- Department of Computer Science and Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
| | - Amy K Y Fu
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China
| | - Nancy Y Ip
- Division of Life Science, State Key Laboratory of Molecular Neuroscience, Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong, China.
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong Science Park, Hong Kong, China.
- Guangdong Provincial Key Laboratory of Brain Science, Disease and Drug Development, HKUST Shenzhen Research Institute, Shenzhen-Hong Kong Institute of Brain Science, Shenzhen, Guangdong, 518057, China.
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11
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Zhang Q, Lin Z, He Y, Jiang J, Hu D. Mendelian Randomization Analysis Reveals No Causal Relationship Between Plasma α-Synuclein and Parkinson's Disease. Mol Neurobiol 2023; 60:2268-2276. [PMID: 36640248 DOI: 10.1007/s12035-023-03206-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 12/29/2022] [Indexed: 01/15/2023]
Abstract
So far, the studies exploring plasma α-synuclein as a biomarker of Parkinson's disease (PD) have provided contradictory results. Here, we first employed the Mendelian randomization (MR) approach to elucidate their potential causal relationship. Five genetic instrumental variables of plasma α-synuclein were acquired from two publicly available datasets. Three independent genome-wide association studies of PD were used as outcome cohorts (PD cohorts 1, 2, and 3). Two-sample MR analyses were conducted using inverse-variance weighted (IVW), MR-Egger, weighted median, simple mode, and leave-one-out methods. Though the IVW approach demonstrated positive plasma α-synuclein effect on the PD risk in three outcome cohorts (OR = 1.134, 1.164, and 1.189, respectively), the P values were all larger than 0.05. The conclusions were robust under complementary sensitivity analyses. Our results did not support the causal relationship between plasma α-synuclein and PD.
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Affiliation(s)
- Qi Zhang
- The Department of Neurology, The Affiliated Taizhou People's Hospital of Nanjing Medical University, Taizhou School of Clinical Medicine, Nanjing Medical University, Taizhou, 225300, Jiangsu, China
| | - Zenan Lin
- Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China
| | - Yan He
- The Molecular Neuropharmacology Laboratory and the Eye-Brain Research Center, The State Key Laboratory of Ophthalmology, Optometry and Vision Science, Wenzhou Medical University, Wenzhou, 325027, Zhejiang, China
| | - Junhong Jiang
- Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200080, China.
| | - Di Hu
- Children's Hospital of Fudan University, No.399 Wanyuan Road, Shanghai, 201102, China.
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12
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Clinical characteristics indexing genetic differences in schizophrenia: a systematic review. Mol Psychiatry 2023; 28:883-890. [PMID: 36400854 DOI: 10.1038/s41380-022-01850-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2022] [Revised: 10/11/2022] [Accepted: 10/20/2022] [Indexed: 11/19/2022]
Abstract
Genome-wide studies are among the best available tools for identifying etiologic processes underlying psychiatric disorders such as schizophrenia. However, it is widely recognized that disorder heterogeneity may limit genetic insights. Identifying phenotypes indexing genetic differences among patients with non-affective psychotic disorder will improve genome-wide studies of these disorders. The present study systematically reviews existing literature to identify phenotypes that index genetic differences among patients with schizophrenia and related disorders. We systematically reviewed family-based studies and genome-wide molecular-genetic studies investigating whether phenotypic variation in patients with non-affective psychotic disorders (according to DSM or equivalent systems) was associated with genome-wide genetic variation (PROSPERO number CRD42019136169). An electronic database search of PubMed, EMBASE, and PsycINFO from inception until 17 May 2019 resulted in 4347 published records. These records included a total of 813 relevant analyses from 264 articles. Two independent raters assessed the quality of all analyses based on methodologic rigor and power. We found moderate to strong evidence for a positive association between genetic/familial risk for non-affective psychosis and four phenotypes: early age of onset, negative/deficit symptoms, chronicity, and functional impairment. Female patients also tended to have more affected relatives. Severity of positive symptoms was not associated with genetic/familial risk for schizophrenia. We suggest that phenotypes with the most evidence for reflecting genetic difference in participating patients should be measured in future large-scale genetic studies of schizophrenia to improve power to discover causal variants and to facilitate discovery of modifying genetic variants.
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13
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Jiang Z, Gu XJ, Su WM, Duan QQ, Ren YL, Li JR, Chi LY, Wang Y, Cao B, Chen YP. Protective effect of antihypertensive drugs on the risk of Parkinson's disease lacks causal evidence from mendelian randomization. Front Pharmacol 2023; 14:1107248. [PMID: 36909159 PMCID: PMC9995445 DOI: 10.3389/fphar.2023.1107248] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2022] [Accepted: 02/13/2023] [Indexed: 02/25/2023] Open
Abstract
Background: Evidence from observational studies concerning the causal role of blood pressure (BP) and antihypertensive medications (AHM) on Parkinson's disease (PD) remains inconclusive. A two-sample Mendelian randomization (MR) study was performed to evaluate the unconfounded association of genetic proxies for BP and first-line AHMs with PD. Methods: Instrumental variables (IV) from the genome-wide association study (GWAS) for BP traits were used to proxy systolic BP (SBP), diastolic BP, and pulse pressure. SBP-associated variants either located within encoding regions or associated with the expression of AHM targets were selected and then scaled to proxy therapeutic inhibition of angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, β-blockers, calcium channel blockers, and thiazides. Positive control analyses on coronary heart disease (CHD) and stroke were conducted to validate the IV selection. Summary data from GWAS for PD risk and PD age at onset (AAO) were used as outcomes. Results: In positive control analyses, genetically determined BP traits and AHMs closely mimicked the observed causal effect on CHD and stroke, confirming the validity of IV selection methodology. In primary analyses, although genetic proxies identified by "encoding region-based method" for β-blockers were suggestively associated with a delayed PD AAO (Beta: 0.115; 95% CI: 0.021, 0.208; p = 1.63E-2; per 10-mmHg lower), sensitivity analyses failed to support this association. Additionally, MR analyses found little evidence that genetically predicted BP traits, overall AHM, or other AHMs affected PD risk or AAO. Conclusion: Our data suggest that BP and commonly prescribed AHMs may not have a prominent role in PD etiology.
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Affiliation(s)
- Zheng Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Lab of Neurodegenerative Disorders, Institute of Inflammation and Immunology (III), Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Centre for Rare Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiao-Jing Gu
- Mental Health Center, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei-Ming Su
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Lab of Neurodegenerative Disorders, Institute of Inflammation and Immunology (III), Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Centre for Rare Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Qing-Qing Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Lab of Neurodegenerative Disorders, Institute of Inflammation and Immunology (III), Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Centre for Rare Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yan-Lin Ren
- Department of Pathophysiology, West China College of Basic medical sciences and Forensic Medicine, Sichuan University, Chengdu, China
| | - Ju-Rong Li
- Department of Geriatrics, Dazhou Central Hospital, Dazhou, Sichuan, China
| | - Li-Yi Chi
- Department of Neurology, Xijing Hospital, Air Force Military Medical University, Xi'an, Shanxi, China
| | - Yi Wang
- Department of Pathophysiology, West China College of Basic medical sciences and Forensic Medicine, Sichuan University, Chengdu, China
| | - Bei Cao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Lab of Neurodegenerative Disorders, Institute of Inflammation and Immunology (III), Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Centre for Rare Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yong-Ping Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Lab of Neurodegenerative Disorders, Institute of Inflammation and Immunology (III), Frontiers Science Center for Disease-Related Molecular Network, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Centre for Rare Diseases, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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14
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van den Hurk M, Lau S, Marchetto MC, Mertens J, Stern S, Corti O, Brice A, Winner B, Winkler J, Gage FH, Bardy C. Druggable transcriptomic pathways revealed in Parkinson's patient-derived midbrain neurons. NPJ Parkinsons Dis 2022; 8:134. [PMID: 36258029 PMCID: PMC9579158 DOI: 10.1038/s41531-022-00400-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 09/28/2022] [Indexed: 11/06/2022] Open
Abstract
Complex genetic predispositions accelerate the chronic degeneration of midbrain substantia nigra neurons in Parkinson’s disease (PD). Deciphering the human molecular makeup of PD pathophysiology can guide the discovery of therapeutics to slow the disease progression. However, insights from human postmortem brain studies only portray the latter stages of PD, and there is a lack of data surrounding molecular events preceding the neuronal loss in patients. We address this gap by identifying the gene dysregulation of live midbrain neurons reprogrammed in vitro from the skin cells of 42 individuals, including sporadic and familial PD patients and matched healthy controls. To minimize bias resulting from neuronal reprogramming and RNA-seq methods, we developed an analysis pipeline integrating PD transcriptomes from different RNA-seq datasets (unsorted and sorted bulk vs. single-cell and Patch-seq) and reprogramming strategies (induced pluripotency vs. direct conversion). This PD cohort’s transcriptome is enriched for human genes associated with known clinical phenotypes of PD, regulation of locomotion, bradykinesia and rigidity. Dysregulated gene expression emerges strongest in pathways underlying synaptic transmission, metabolism, intracellular trafficking, neural morphogenesis and cellular stress/immune responses. We confirmed a synaptic impairment with patch-clamping and identified pesticides and endoplasmic reticulum stressors as the most significant gene-chemical interactions in PD. Subsequently, we associated the PD transcriptomic profile with candidate pharmaceuticals in a large database and a registry of current clinical trials. This study highlights human transcriptomic pathways that can be targeted therapeutically before the irreversible neuronal loss. Furthermore, it demonstrates the preclinical relevance of unbiased large transcriptomic assays of reprogrammed patient neurons.
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Affiliation(s)
- Mark van den Hurk
- grid.430453.50000 0004 0565 2606South Australian Health and Medical Research Institute (SAHMRI), Laboratory for Human Neurophysiology and Genetics, Adelaide, SA Australia
| | - Shong Lau
- grid.250671.70000 0001 0662 7144Laboratory of Genetics, Salk Institute for Biological Studies, La Jolla, CA USA
| | - Maria C. Marchetto
- grid.266100.30000 0001 2107 4242Department of Anthropology, University of California San Diego, La Jolla, CA USA
| | - Jerome Mertens
- grid.250671.70000 0001 0662 7144Laboratory of Genetics, Salk Institute for Biological Studies, La Jolla, CA USA ,grid.5771.40000 0001 2151 8122Neural Aging Laboratory, Institute of Molecular Biology, CMBI, Leopold-Franzens-University Innsbruck, Innsbruck, Tyrol Austria
| | - Shani Stern
- grid.250671.70000 0001 0662 7144Laboratory of Genetics, Salk Institute for Biological Studies, La Jolla, CA USA ,grid.18098.380000 0004 1937 0562Sagol Department of Neurobiology, Faculty of Natural Sciences, University of Haifa, Haifa, Israel
| | - Olga Corti
- grid.425274.20000 0004 0620 5939Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, AP-HP, Hôpital de la Pitié Salpêtrière, DMU BioGeM, Paris, France
| | - Alexis Brice
- grid.425274.20000 0004 0620 5939Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, AP-HP, Hôpital de la Pitié Salpêtrière, DMU BioGeM, Paris, France
| | - Beate Winner
- grid.411668.c0000 0000 9935 6525Department of Stem Cell Biology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany ,grid.411668.c0000 0000 9935 6525Center of Rare Diseases Erlangen (ZSEER), University Hospital Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany ,grid.411668.c0000 0000 9935 6525Department of Molecular Neurology, University Hospital Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Jürgen Winkler
- grid.411668.c0000 0000 9935 6525Department of Stem Cell Biology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany ,grid.411668.c0000 0000 9935 6525Center of Rare Diseases Erlangen (ZSEER), University Hospital Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany ,grid.411668.c0000 0000 9935 6525Department of Molecular Neurology, University Hospital Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Fred H. Gage
- grid.250671.70000 0001 0662 7144Laboratory of Genetics, Salk Institute for Biological Studies, La Jolla, CA USA
| | - Cedric Bardy
- grid.430453.50000 0004 0565 2606South Australian Health and Medical Research Institute (SAHMRI), Laboratory for Human Neurophysiology and Genetics, Adelaide, SA Australia ,grid.1014.40000 0004 0367 2697Flinders Health and Medical Research Institute, Flinders University, Adelaide, SA Australia
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15
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Heinzel S, Mascalzoni D, Bäumer T, Berg D, Kasten M, Brüggemann N. Clinical relevance and translational impact of reduced penetrance in genetic movement disorders. MED GENET-BERLIN 2022. [DOI: 10.1515/medgen-2022-2128] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Abstract
Reduced penetrance is an important but underreported aspect in monogenic diseases. It refers to the phenomenon that carriers of pathogenic variants do not manifest with an overt disease. Clinical expressivity, on the other hand, describes the degree to which certain disease characteristics are present. In this article, we discuss the implications of reduced penetrance on genetic testing and counseling, outline how penetrance can be estimated in rare diseases using large cohorts and review the ethical, legal and social implications of studying non-manifesting carriers of pathogenic mutations. We highlight the interplay between reduced penetrance and the prodromal phase of a neurodegenerative disorder through the example of monogenic Parkinson’s disease and discuss the therapeutic implications.
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Affiliation(s)
- Sebastian Heinzel
- Department of Neurology , Christian-Albrechts University of Kiel , Kiel , Germany
| | - Deborah Mascalzoni
- Institute for Biomedicine , Eurac Research , Affiliated Institute of the University of Lübeck , Bolzano , Italy
- Center for Research Ethics and Bioethics , Department of Public Health and Caring Sciences , Uppsala University , Uppsala , Sweden
| | - Tobias Bäumer
- Institute of Systems Motor Science , University of Lübeck , Lübeck , Germany
| | - Daniela Berg
- Department of Neurology , Christian-Albrechts University of Kiel , Kiel , Germany
| | - Meike Kasten
- Department of Psychiatry and Psychotherapy , University of Lübeck , Lübeck , Germany
- Institute of Neurogenetics , University of Lübeck , Lübeck , Germany
| | - Norbert Brüggemann
- Institute of Neurogenetics , University of Lübeck , Lübeck , Germany
- Department of Neurology, Center for Brain, Behavior and Metabolism , University of Lübeck , Lübeck , Germany
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16
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Schaffner SL, Kobor MS. DNA methylation as a mediator of genetic and environmental influences on Parkinson's disease susceptibility: Impacts of alpha-Synuclein, physical activity, and pesticide exposure on the epigenome. Front Genet 2022; 13:971298. [PMID: 36061205 PMCID: PMC9437223 DOI: 10.3389/fgene.2022.971298] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/25/2022] [Indexed: 12/15/2022] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder with a complex etiology and increasing prevalence worldwide. As PD is influenced by a combination of genetic and environment/lifestyle factors in approximately 90% of cases, there is increasing interest in identification of the interindividual mechanisms underlying the development of PD as well as actionable lifestyle factors that can influence risk. This narrative review presents an outline of the genetic and environmental factors contributing to PD risk and explores the possible roles of cytosine methylation and hydroxymethylation in the etiology and/or as early-stage biomarkers of PD, with an emphasis on epigenome-wide association studies (EWAS) of PD conducted over the past decade. Specifically, we focused on variants in the SNCA gene, exposure to pesticides, and physical activity as key contributors to PD risk. Current research indicates that these factors individually impact the epigenome, particularly at the level of CpG methylation. There is also emerging evidence for interaction effects between genetic and environmental contributions to PD risk, possibly acting across multiple omics layers. We speculated that this may be one reason for the poor replicability of the results of EWAS for PD reported to date. Our goal is to provide direction for future epigenetics studies of PD to build upon existing foundations and leverage large datasets, new technologies, and relevant statistical approaches to further elucidate the etiology of this disease.
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Affiliation(s)
- Samantha L. Schaffner
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Genetics, British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada
| | - Michael S. Kobor
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Genetics, British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada
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17
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Pavelka L, Rauschenberger A, Landoulsi Z, Pachchek S, May P, Glaab E, Krüger R, Acharya G, Aguayo G, Alexandre M, Ali M, Allen D, Ammerlann W, Balling R, Bassis M, Beaumont K, Becker R, Bellora C, Berchem G, Berg D, Bisdorff A, Brockmann K, Calmes J, Castillo L, Contesotto G, Diederich N, Dondelinger R, Esteves D, Fagherazzi G, Ferrand JY, Gantenbein M, Gasser T, Gawron P, Ghosh S, Glaab E, Gomes C, De Lope EG, Goncharenko N, Graas J, Graziano M, Groues V, Grünewald A, Gu W, Hammot G, Hanff AM, Hansen L, Hansen M, Heneka M, Henry E, Herbrink S, Herenne E, Herzinger S, Heymann M, Hu M, Hundt A, Jacoby N, Lebioda JJ, Jaroz Y, Klopfenstein Q, Krüger R, Lambert P, Landoulsi Z, Lentz R, Liepelt I, Liszka R, Longhino L, Lorentz V, Lupu PC, Mackay C, Maetzler W, Marcus K, Marques G, Marques T, May P, Mcintyre D, Mediouni C, Meisch F, Menster M, Minelli M, Mittelbronn M, Mollenhauer B, Mommaerts K, Moreno C, Moudio S, Mühlschlegel F, Nati R, Nehrbass U, Nickels S, Nicolai B, Nicolay JP, Oertel W, Ostaszewski M, Pachchek S, Pauly C, Pauly L, Pavelka L, Perquin M, Lima RR, Rauschenberger A, Rawal R, Bobbili DR, Rosales E, Rosety I, Rump K, Sandt E, Satagopam V, Schlesser M, Schmitt M, Schmitz S, Schneider R, Schwamborn J, Sharify A, Soboleva E, Sokolowska K, Terwindt O, Thien H, Thiry E, Loo RTJ, Trefois C, Trouet J, Tsurkalenko O, Vaillant M, Valenti M, Boas LV, Vyas M, Wade-Martins R, Wilmes P. Age at onset as stratifier in idiopathic Parkinson’s disease – effect of ageing and polygenic risk score on clinical phenotypes. NPJ Parkinsons Dis 2022; 8:102. [PMID: 35945230 PMCID: PMC9363416 DOI: 10.1038/s41531-022-00342-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Accepted: 05/30/2022] [Indexed: 12/23/2022] Open
Abstract
Several phenotypic differences observed in Parkinson’s disease (PD) patients have been linked to age at onset (AAO). We endeavoured to find out whether these differences are due to the ageing process itself by using a combined dataset of idiopathic PD (n = 430) and healthy controls (HC; n = 556) excluding carriers of known PD-linked genetic mutations in both groups. We found several significant effects of AAO on motor and non-motor symptoms in PD, but when comparing the effects of age on these symptoms with HC (using age at assessment, AAA), only positive associations of AAA with burden of motor symptoms and cognitive impairment were significantly different between PD vs HC. Furthermore, we explored a potential effect of polygenic risk score (PRS) on clinical phenotype and identified a significant inverse correlation of AAO and PRS in PD. No significant association between PRS and severity of clinical symptoms was found. We conclude that the observed non-motor phenotypic differences in PD based on AAO are largely driven by the ageing process itself and not by a specific profile of neurodegeneration linked to AAO in the idiopathic PD patients.
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18
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Janahi M, Aksman L, Schott JM, Mokrab Y, Altmann A. Nomograms of human hippocampal volume shifted by polygenic scores. eLife 2022; 11:78232. [PMID: 35938915 PMCID: PMC9391046 DOI: 10.7554/elife.78232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 08/06/2022] [Indexed: 11/25/2022] Open
Abstract
Nomograms are important clinical tools applied widely in both developing and aging populations. They are generally constructed as normative models identifying cases as outliers to a distribution of healthy controls. Currently used normative models do not account for genetic heterogeneity. Hippocampal volume (HV) is a key endophenotype for many brain disorders. Here, we examine the impact of genetic adjustment on HV nomograms and the translational ability to detect dementia patients. Using imaging data from 35,686 healthy subjects aged 44–82 from the UK Biobank (UKB), we built HV nomograms using Gaussian process regression (GPR), which – compared to a previous method – extended the application age by 20 years, including dementia critical age ranges. Using HV polygenic scores (HV-PGS), we built genetically adjusted nomograms from participants stratified into the top and bottom 30% of HV-PGS. This shifted the nomograms in the expected directions by ~100 mm3 (2.3% of the average HV), which equates to 3 years of normal aging for a person aged ~65. Clinical impact of genetically adjusted nomograms was investigated by comparing 818 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database diagnosed as either cognitively normal (CN), having mild cognitive impairment (MCI) or Alzheimer’s disease (AD) patients. While no significant change in the survival analysis was found for MCI-to-AD conversion, an average of 68% relative decrease was found in intra-diagnostic-group variance, highlighting the importance of genetic adjustment in untangling phenotypic heterogeneity.
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Affiliation(s)
- Mohammed Janahi
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Leon Aksman
- Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, United States
| | - Jonathan M Schott
- Dementia Research Centre, University College London, London, United Kingdom
| | - Younes Mokrab
- Human Genetics Department, Sidra Medicine, Doha, Qatar
| | - Andre Altmann
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
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19
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Kocheril PA, Moore SC, Lenz KD, Mukundan H, Lilley LM. Progress Toward a Multiomic Understanding of Traumatic Brain Injury: A Review. Biomark Insights 2022; 17:11772719221105145. [PMID: 35719705 PMCID: PMC9201320 DOI: 10.1177/11772719221105145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 05/17/2022] [Indexed: 12/11/2022] Open
Abstract
Traumatic brain injury (TBI) is not a single disease state but describes an array
of conditions associated with insult or injury to the brain. While some
individuals with TBI recover within a few days or months, others present with
persistent symptoms that can cause disability, neuropsychological trauma, and
even death. Understanding, diagnosing, and treating TBI is extremely complex for
many reasons, including the variable biomechanics of head impact, differences in
severity and location of injury, and individual patient characteristics. Because
of these confounding factors, the development of reliable diagnostics and
targeted treatments for brain injury remains elusive. We argue that the
development of effective diagnostic and therapeutic strategies for TBI requires
a deep understanding of human neurophysiology at the molecular level and that
the framework of multiomics may provide some effective solutions for the
diagnosis and treatment of this challenging condition. To this end, we present
here a comprehensive review of TBI biomarker candidates from across the
multiomic disciplines and compare them with known signatures associated with
other neuropsychological conditions, including Alzheimer’s disease and
Parkinson’s disease. We believe that this integrated view will facilitate a
deeper understanding of the pathophysiology of TBI and its potential links to
other neurological diseases.
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Affiliation(s)
- Philip A Kocheril
- Physical Chemistry and Applied Spectroscopy Group, Chemistry Division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Shepard C Moore
- Physical Chemistry and Applied Spectroscopy Group, Chemistry Division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Kiersten D Lenz
- Physical Chemistry and Applied Spectroscopy Group, Chemistry Division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Harshini Mukundan
- Physical Chemistry and Applied Spectroscopy Group, Chemistry Division, Los Alamos National Laboratory, Los Alamos, NM, USA
| | - Laura M Lilley
- Physical Chemistry and Applied Spectroscopy Group, Chemistry Division, Los Alamos National Laboratory, Los Alamos, NM, USA
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20
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Examples of Inverse Comorbidity between Cancer and Neurodegenerative Diseases: A Possible Role for Noncoding RNA. Cells 2022; 11:cells11121930. [PMID: 35741059 PMCID: PMC9221903 DOI: 10.3390/cells11121930] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/25/2022] [Accepted: 06/13/2022] [Indexed: 02/06/2023] Open
Abstract
Cancer is one of the most common causes of death; in parallel, the incidence and prevalence of central nervous system diseases are equally high. Among neurodegenerative diseases, Alzheimer’s dementia is the most common, while Parkinson’s disease (PD) is the second most frequent neurodegenerative disease. There is a significant amount of evidence on the complex biological connection between cancer and neurodegeneration. Noncoding RNAs (ncRNAs) are defined as transcribed nucleotides that perform a variety of regulatory functions. The mechanisms by which ncRNAs exert their functions are numerous and involve every aspect of cellular life. The same ncRNA can act in multiple ways, leading to different outcomes; in fact, a single ncRNA can participate in the pathogenesis of more than one disease—even if these seem very different, as cancer and neurodegenerative disorders are. The ncRNA activates specific pathways leading to one or the other clinical phenotype, sometimes with obvious mechanisms of inverse comorbidity. We aimed to collect from the existing literature examples of inverse comorbidity in which ncRNAs seem to play a key role. We also investigated the example of mir-519a-3p, and one of its target genes Poly (ADP-ribose) polymerase 1, for the inverse comorbidity mechanism between some cancers and PD. We believe it is very important to study the inverse comorbidity relationship between cancer and neurodegenerative diseases because it will help us to better assess these two major areas of human disease.
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21
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Dehestani M, Liu H, Sreelatha AAK, Schulte C, Bansal V, Gasser T. Mitochondrial and autophagy-lysosomal pathway polygenic risk scores predict Parkinson's disease. Mol Cell Neurosci 2022; 121:103751. [PMID: 35710056 DOI: 10.1016/j.mcn.2022.103751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 06/08/2022] [Accepted: 06/10/2022] [Indexed: 10/18/2022] Open
Abstract
Polygenic Risk Scores (PRS), which allow assessing an individuals' genetic risk for a complex disease, are calculated as the weighted number of genetic risk alleles in an individual's genome, with the risk alleles and their weights typically derived from the results of genome-wide association studies (GWAS). Among a wide range of applications, PRS can be used to identify at-risk individuals and select them for further clinical follow-up. Pathway PRS are genetic scores based on single nucleotide polymorphisms (SNPs) assigned to genes involved in major disease pathways. The aim of this study is to assess the predictive utility of PRS models constructed based on SNPs corresponding to two cardinal pathways in Parkinson's disease (PD) including mitochondrial PRS (Mito PRS) and autophagy-lysosomal PRS (ALP PRS). PRS models were constructed using the clumping-and-thresholding method in a German population as prediction dataset that included 371 cases and 249 controls, using SNPs discovered by the most recent PD-GWAS. We showed that these pathway PRS significantly predict the PD status. Furthermore, we demonstrated that Mito PRS are significantly associated with later age of onset in PD patients. Our results may add to the accumulating evidence for the contribution of mitochondrial and autophagy-lysosomal pathways to PD risk and facilitate biologically relevant risk stratification of PD patients.
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Affiliation(s)
- Mohammad Dehestani
- Department of Neurodegenerative Disease, Her tie Institute for Clinical Brain Research, University of Tübingen, Germany; German Center for Neurodegenerative Diseases DZNE, Tübingen, Germany.
| | - Hui Liu
- Department of Neurodegenerative Disease, Her tie Institute for Clinical Brain Research, University of Tübingen, Germany; German Center for Neurodegenerative Diseases DZNE, Tübingen, Germany
| | - Ashwin Ashok Kumar Sreelatha
- Centre for Genetic Epidemiology, Institute for Clinical Epidemiology and Functional Biometry, University of Tübingen, Germany
| | - Claudia Schulte
- Department of Neurodegenerative Disease, Her tie Institute for Clinical Brain Research, University of Tübingen, Germany; German Center for Neurodegenerative Diseases DZNE, Tübingen, Germany
| | - Vikas Bansal
- German Center for Neurodegenerative Diseases DZNE, Tübingen, Germany
| | - Thomas Gasser
- Department of Neurodegenerative Disease, Her tie Institute for Clinical Brain Research, University of Tübingen, Germany; German Center for Neurodegenerative Diseases DZNE, Tübingen, Germany
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22
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Effects of Alzheimer's genetic risk scores and CSF biomarkers in de novo Parkinson's Disease. NPJ Parkinsons Dis 2022; 8:57. [PMID: 35545633 PMCID: PMC9095668 DOI: 10.1038/s41531-022-00317-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2021] [Accepted: 04/08/2022] [Indexed: 11/08/2022] Open
Abstract
Coexisting Alzheimer's disease (AD) pathology is common in Parkinson's disease (PD). However, the implications of genetic risk scores (GRS) for AD have not been elucidated in PD. In 413 de novo PD and 195 healthy controls from the Parkinson's Progression Marker Initiative database, the effects of GRS for AD (GRS-AD) and PD (GRS-PD) on the risk of PD and longitudinal CSF biomarkers and clinical outcomes were explored. Higher GRS-PD and lower baseline CSF α-synuclein were associated with an increased risk of PD. In the PD group, GRS-AD was correlated positively with CSF p-tau/Aβ and negatively with CSF α-synuclein. Higher GRS-PD was associated with faster CSF p-tau/Aβ increase, and GRS-AD and GRS-PD were interactively associated with CSF α-synuclein. In the PD group, higher GRS-AD was associated with poor visuospatial function, and baseline CSF p-tau/Aβ was associated with faster cognitive decline. Higher GRS-PD was associated with better semantic fluency and frontal-related cognition and motor function given the same levels of CSF biomarkers and dopamine transporter uptake. Taken together, our results suggest that higher GRS-AD and CSF p-tau/Aβ, reflecting AD-related pathophysiology, may be associated with cognitive decline in PD patients.
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23
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Becker S, Sharma MJ, Callahan BL. ADHD and Neurodegenerative Disease Risk: A Critical Examination of the Evidence. Front Aging Neurosci 2022; 13:826213. [PMID: 35145394 PMCID: PMC8822599 DOI: 10.3389/fnagi.2021.826213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 12/28/2021] [Indexed: 11/29/2022] Open
Abstract
In this review, we undertake a critical appraisal of eight published studies providing first evidence that a history of attention-deficit/hyperactivity disorder (ADHD) may increase risk for the later-life development of a neurodegenerative disease, in particular Lewy body diseases (LBD), by up to five-fold. Most of these studies have used data linked to health records in large population registers and include impressive sample sizes and adequate follow-up periods. We identify a number of methodological limitations as well, including potential diagnostic inaccuracies arising from the use of electronic health records, biases in the measurement of ADHD status and symptoms, and concerns surrounding the representativeness of ADHD and LBD cohorts. Consequently, previously reported risk associations may have been underestimated due to the high likelihood of potentially missed ADHD cases in groups used as “controls”, or alternatively previous estimates may be inflated due to the inclusion of confounding comorbidities or non-ADHD cases within “exposed” groups that may have better accounted for dementia risk. Prospective longitudinal studies involving well-characterized cases and controls are recommended to provide some reassurance about the validity of neurodegenerative risk estimates in ADHD.
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Affiliation(s)
- Sara Becker
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Manu J. Sharma
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Brandy L. Callahan
- Department of Psychology, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- *Correspondence: Brandy L. Callahan
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24
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Ho D, Schierding W, Farrow SL, Cooper AA, Kempa-Liehr AW, O’Sullivan JM. Machine Learning Identifies Six Genetic Variants and Alterations in the Heart Atrial Appendage as Key Contributors to PD Risk Predictivity. Front Genet 2022; 12:785436. [PMID: 35047012 PMCID: PMC8762216 DOI: 10.3389/fgene.2021.785436] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/09/2021] [Indexed: 12/14/2022] Open
Abstract
Parkinson's disease (PD) is a complex neurodegenerative disease with a range of causes and clinical presentations. Over 76 genetic loci (comprising 90 SNPs) have been associated with PD by the most recent GWAS meta-analysis. Most of these PD-associated variants are located in non-coding regions of the genome and it is difficult to understand what they are doing and how they contribute to the aetiology of PD. We hypothesised that PD-associated genetic variants modulate disease risk through tissue-specific expression quantitative trait loci (eQTL) effects. We developed and validated a machine learning approach that integrated tissue-specific eQTL data on known PD-associated genetic variants with PD case and control genotypes from the Wellcome Trust Case Control Consortium. In so doing, our analysis ranked the tissue-specific transcription effects for PD-associated genetic variants and estimated their relative contributions to PD risk. We identified roles for SNPs that are connected with INPP5P, CNTN1, GBA and SNCA in PD. Ranking the variants and tissue-specific eQTL effects contributing most to the machine learning model suggested a key role in the risk of developing PD for two variants (rs7617877 and rs6808178) and eQTL associated transcriptional changes of EAF1-AS1 within the heart atrial appendage. Similarly, effects associated with eQTLs located within the Brain Cerebellum were also recognized to confer major PD risk. These findings were replicated in two additional, independent cohorts (the UK Biobank, and NeuroX) and thus warrant further mechanistic investigations to determine if these transcriptional changes could act as early contributors to PD risk and disease development.
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Affiliation(s)
- Daniel Ho
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - William Schierding
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
| | - Sophie L. Farrow
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
| | - Antony A. Cooper
- Australian Parkinsons Mission, Garvan Institute of Medical Research, Sydney, NSW, Australia
- St Vincent’s Clinical School, UNSW Sydney, Sydney, NSW, Australia
| | | | - Justin M. O’Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, United Kingdom
- Brain Research New Zealand, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
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25
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Cross B, Turner R, Pirmohamed M. Polygenic risk scores: An overview from bench to bedside for personalised medicine. Front Genet 2022; 13:1000667. [PMID: 36437929 PMCID: PMC9692112 DOI: 10.3389/fgene.2022.1000667] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Accepted: 10/24/2022] [Indexed: 11/13/2022] Open
Abstract
Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.
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Affiliation(s)
- Benjamin Cross
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Richard Turner
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, Faculty of Health & Life Sciences, University of Liverpool, Liverpool, United Kingdom
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26
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Storm CS, Kia DA, Almramhi MM, Bandres-Ciga S, Finan C, Hingorani AD, Wood NW. Finding genetically-supported drug targets for Parkinson's disease using Mendelian randomization of the druggable genome. Nat Commun 2021; 12:7342. [PMID: 34930919 PMCID: PMC8688480 DOI: 10.1038/s41467-021-26280-1] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 09/14/2021] [Indexed: 12/30/2022] Open
Abstract
Parkinson's disease is a neurodegenerative movement disorder that currently has no disease-modifying treatment, partly owing to inefficiencies in drug target identification and validation. We use Mendelian randomization to investigate over 3,000 genes that encode druggable proteins and predict their efficacy as drug targets for Parkinson's disease. We use expression and protein quantitative trait loci to mimic exposure to medications, and we examine the causal effect on Parkinson's disease risk (in two large cohorts), age at onset and progression. We propose 23 drug-targeting mechanisms for Parkinson's disease, including four possible drug repurposing opportunities and two drugs which may increase Parkinson's disease risk. Of these, we put forward six drug targets with the strongest Mendelian randomization evidence. There is remarkably little overlap between our drug targets to reduce Parkinson's disease risk versus progression, suggesting different molecular mechanisms. Drugs with genetic support are considerably more likely to succeed in clinical trials, and we provide compelling genetic evidence and an analysis pipeline to prioritise Parkinson's disease drug development.
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Affiliation(s)
- Catherine S Storm
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
| | - Demis A Kia
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
| | - Mona M Almramhi
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
- Department of Medical Laboratory Technology, Faculty of Applied Medical Sciences, King Abdulaziz University, Jeddah, Kingdom of Saudi Arabia
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Chris Finan
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London WC1E 6BT, UK
- University College London British Heart Foundation Research Accelerator Centre, New Delhi, India
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Heidelberglaan 100, 3584, CX Utrecht, the Netherlands
| | - Aroon D Hingorani
- Institute of Cardiovascular Science, Faculty of Population Health, University College London, London WC1E 6BT, UK
- University College London British Heart Foundation Research Accelerator Centre, New Delhi, India
- Health Data Research UK, 222 Euston Road, London, UK
| | - Nicholas W Wood
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK.
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27
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Gu L, Guan X, Gao T, Zhou C, Yang W, Lv D, Wu J, Fang Y, Guo T, Song Z, Xu X, Tian J, Yin X, Zhang M, Zhang B, Pu J, Yan Y. The effect of polygenic risk on white matter microstructural degeneration in Parkinson's disease: A longitudinal Diffusion Tensor Imaging study. Eur J Neurol 2021; 29:1000-1010. [PMID: 34882309 DOI: 10.1111/ene.15201] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 11/29/2021] [Indexed: 11/29/2022]
Abstract
BACKGROUND AND PURPOSE This study was undertaken to investigate the effect of genetic risk on whole brain white matter (WM) integrity in patients with Parkinson disease (PD). METHODS Data were acquired from the Parkinson's Progression Markers Initiative (PPMI) database. Polygenic load was estimated by calculating weighted polygenic risk scores (PRS) using (i) all available 26 PD-risk single nucleotide polymorphisms (SNPs) (PRS1) and (ii) 23 SNPs with minor allele frequency (MAF) > 0.05 (PRS2). According to the PRS2, and combined with clinical and diffusion tensor imaging (DTI) data over 3-year follow-up, 60 PD patients were screened and assigned to the low-PRS group (n = 30) and high-PRS group (n = 30) to investigate intergroup differences in clinical profiles and WM microstructure measured by DTI cross-sectionally and longitudinally. RESULTS PRS were associated with younger age at onset in patients with PD (PRS1, Spearman ρ = -0.190, p = 0.003; PRS2, Spearman ρ = -0.189, p = 0.003). The high-PRS group showed more extensive WM microstructural degeneration compared with the low-PRS group, mainly involving the anterior thalamic radiation (AThR) and inferior fronto-occipital fasciculus (IFOF) (p < 0.05). Furthermore, WM microstructural changes in AThR correlated with declining cognitive function (r = -0.401, p = 0.028) and increasing dopaminergic deficits in caudate (r = -0.405, p = 0.030). CONCLUSIONS These findings suggest that PD-associated polygenic load aggravates the WM microstructural degeneration and these changes may lead to poor cognition with continuous dopamine depletion. This study provides advanced evidence that combined with a cumulative PRS and DTI methods may predict disease progression in PD patients.
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Affiliation(s)
- Luyan Gu
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaojun Guan
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Ting Gao
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Cheng Zhou
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenyi Yang
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Dayao Lv
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jingjing Wu
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Fang
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Tao Guo
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhe Song
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaojun Xu
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jun Tian
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xinzhen Yin
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Minming Zhang
- Department of Radiology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Baorong Zhang
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jiali Pu
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yaping Yan
- Department of Neurology, Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
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Polygenic Risk Scores Contribute to Personalized Medicine of Parkinson's Disease. J Pers Med 2021; 11:jpm11101030. [PMID: 34683174 PMCID: PMC8539098 DOI: 10.3390/jpm11101030] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 10/11/2021] [Accepted: 10/12/2021] [Indexed: 12/18/2022] Open
Abstract
Parkinson’s disease (PD) is the second most common neurodegenerative disorder characterized by the loss of dopaminergic neurons. The vast majority of PD patients develop the disease sporadically and it is assumed that the cause lies in polygenic and environmental components. The overall polygenic risk is the result of a large number of common low-risk variants discovered by large genome-wide association studies (GWAS). Polygenic risk scores (PRS), generated by compiling genome-wide significant variants, are a useful prognostic tool that quantifies the cumulative effect of genetic risk in a patient and in this way helps to identify high-risk patients. Although there are limitations to the construction and application of PRS, such as considerations of limited genetic underpinning of diseases explained by SNPs and generalizability of PRS to other populations, this personalized risk prediction could make a promising contribution to stratified medicine and tailored therapeutic interventions in the future.
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Yahalom G, Rigbi A, Israeli-Korn S, Krohn L, Rudakou U, Ruskey JA, Benshimol L, Tsafnat T, Gan-Or Z, Hassin-Baer S, Greenbaum L. Age at Onset of Parkinson's Disease Among Ashkenazi Jewish Patients: Contribution of Environmental Factors, LRRK2 p.G2019S and GBA p.N370S Mutations. JOURNAL OF PARKINSONS DISEASE 2021; 10:1123-1132. [PMID: 32310186 DOI: 10.3233/jpd-191829] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
BACKGROUND Both genetic and environmental factors contribute to Parkinson's disease (PD) risk. OBJECTIVE We investigated the potential association of several relevant variables with PD age at onset (AAO), focusing on LRRK2 p.G2019S and GBA p.N370S mutations. METHODS Ashkenazi Jewish (AJ) PD patients, screened for LRRK2 and GBA mutations, underwent an interview regarding exposure to the following environmental and lifestyle factors: cigarette smoking, consumption of coffee, tea and alcohol, head injury and rural living. Multivariate linear regression (adjusted for sex) was used to examine the association with AAO, and models included LRRK2 p.G2019S and GBA p.N370S mutation status (carrier/non-carriers), single environmental variable and their interactions terms, as independent variables. RESULTS 225 Israeli AJ PD patients were enrolled: 65 LRRK2 p.G2019S mutation carriers, 60 GBA p.N370S carriers and 100 non-carries of these mutations. In the dichotomized exposure/non-exposure analyses, positive LRRK2 p.G2019S status was associated with younger AAO in all models, at nominal or near significant levels (p = 0.033-0.082). Smoking was associated with older AAO (p = 0.032), and the interaction between GBA p.N370S and history of head injury was associated with younger AAO (p = 0.049), both at nominal significance. There was no indication of a consistent main effect for GBA p.N370S status or significant LRRK2 p.G2019S-environmental factor interaction. In the dose-dependent analyses, increased coffee and tea consumption levels were associated with older AAO (p = 0.001 and p = 0.002, respectively). CONCLUSIONS Our results suggest that genetic and environmental factors may affect AAO in PD patients, but validation in additional samples is required.
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Affiliation(s)
- Gilad Yahalom
- Movement Disorders Institute, Sheba Medical Center, Tel Hashomer, Israel.,Department of Neurology, Sheba Medical Center, Tel Hashomer, Israel.,Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel.,Movement Disorders Clinic and Department of Neurology, Shaare Zedek Medical Center, Jerusalem, Israel
| | - Amihai Rigbi
- Faculty of Education, Beit Berl College, Kfar Saba, Israel
| | - Simon Israeli-Korn
- Movement Disorders Institute, Sheba Medical Center, Tel Hashomer, Israel.,Department of Neurology, Sheba Medical Center, Tel Hashomer, Israel.,Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lynne Krohn
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Uladzislau Rudakou
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Jennifer A Ruskey
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada.,Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
| | - Lior Benshimol
- Movement Disorders Institute, Sheba Medical Center, Tel Hashomer, Israel
| | - Tal Tsafnat
- Movement Disorders Institute, Sheba Medical Center, Tel Hashomer, Israel
| | - Ziv Gan-Or
- Montreal Neurological Institute, McGill University, Montréal, QC, Canada.,Department of Human Genetics, McGill University, Montréal, QC, Canada.,Department of Neurology and Neurosurgery, McGill University, Montréal, QC, Canada
| | - Sharon Hassin-Baer
- Movement Disorders Institute, Sheba Medical Center, Tel Hashomer, Israel.,Department of Neurology, Sheba Medical Center, Tel Hashomer, Israel.,Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Lior Greenbaum
- Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel.,Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel.,The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel
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30
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Prediction of Parkinson's Disease Risk Based on Genetic Profile and Established Risk Factors. Genes (Basel) 2021; 12:genes12081278. [PMID: 34440451 PMCID: PMC8393959 DOI: 10.3390/genes12081278] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 08/17/2021] [Accepted: 08/18/2021] [Indexed: 11/17/2022] Open
Abstract
Background: Parkinson’s disease (PD) is a neurodegenerative disorder, and literature suggests that genetics and lifestyle/environmental factors may play a key role in the triggering of the disease. This study aimed to evaluate the predictive performance of a 12-Single Nucleotide Polymorphisms (SNPs) polygenic risk score (PRS) in combination with already established PD-environmental/lifestyle factors. Methods: Genotypic and lifestyle/environmental data on 235 PD-patients and 464 controls were obtained from a previous study carried out in the Cypriot population. A PRS was calculated for each individual. Univariate logistic-regression analysis was used to assess the association of PRS and each risk factor with PD-status. Stepwise-regression analysis was used to select the best predictive model for PD combining genetic and lifestyle/environmental factors. Results: The 12-SNPs PRS was significantly increased in PD-cases compared to controls. Furthermore, univariate analyses showed that age, head injury, family history, depression, and Body Mass Index (BMI) were significantly associated with PD-status. Stepwise-regression suggested that a model which includes PRS and seven other independent lifestyle/environmental factors is the most predictive of PD in our population. Conclusions: These results suggest an association between both genetic and environmental factors and PD, and highlight the potential for the use of PRS in combination with the classical risk factors for risk prediction of PD.
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31
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Wu YC, Sonninen TM, Peltonen S, Koistinaho J, Lehtonen Š. Blood-Brain Barrier and Neurodegenerative Diseases-Modeling with iPSC-Derived Brain Cells. Int J Mol Sci 2021; 22:7710. [PMID: 34299328 PMCID: PMC8307585 DOI: 10.3390/ijms22147710] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 07/11/2021] [Accepted: 07/12/2021] [Indexed: 12/12/2022] Open
Abstract
The blood-brain barrier (BBB) regulates the delivery of oxygen and important nutrients to the brain through active and passive transport and prevents neurotoxins from entering the brain. It also has a clearance function and removes carbon dioxide and toxic metabolites from the central nervous system (CNS). Several drugs are unable to cross the BBB and enter the CNS, adding complexity to drug screens targeting brain disorders. A well-functioning BBB is essential for maintaining healthy brain tissue, and a malfunction of the BBB, linked to its permeability, results in toxins and immune cells entering the CNS. This impairment is associated with a variety of neurological diseases, including Alzheimer's disease and Parkinson's disease. Here, we summarize current knowledge about the BBB in neurodegenerative diseases. Furthermore, we focus on recent progress of using human-induced pluripotent stem cell (iPSC)-derived models to study the BBB. We review the potential of novel stem cell-based platforms in modeling the BBB and address advances and key challenges of using stem cell technology in modeling the human BBB. Finally, we highlight future directions in this area.
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Affiliation(s)
- Ying-Chieh Wu
- Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland; (Y.-C.W.); (T.-M.S.); (S.P.); (J.K.)
| | - Tuuli-Maria Sonninen
- Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland; (Y.-C.W.); (T.-M.S.); (S.P.); (J.K.)
| | - Sanni Peltonen
- Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland; (Y.-C.W.); (T.-M.S.); (S.P.); (J.K.)
| | - Jari Koistinaho
- Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland; (Y.-C.W.); (T.-M.S.); (S.P.); (J.K.)
- A.I.Virtanen Institute for Molecular Sciences, University of Eastern Finland, 70211 Kuopio, Finland
| | - Šárka Lehtonen
- Neuroscience Center, University of Helsinki, 00014 Helsinki, Finland; (Y.-C.W.); (T.-M.S.); (S.P.); (J.K.)
- A.I.Virtanen Institute for Molecular Sciences, University of Eastern Finland, 70211 Kuopio, Finland
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32
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Day JO, Mullin S. The Genetics of Parkinson's Disease and Implications for Clinical Practice. Genes (Basel) 2021; 12:genes12071006. [PMID: 34208795 PMCID: PMC8304082 DOI: 10.3390/genes12071006] [Citation(s) in RCA: 67] [Impact Index Per Article: 22.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 06/21/2021] [Accepted: 06/28/2021] [Indexed: 12/17/2022] Open
Abstract
The genetic landscape of Parkinson’s disease (PD) is characterised by rare high penetrance pathogenic variants causing familial disease, genetic risk factor variants driving PD risk in a significant minority in PD cases and high frequency, low penetrance variants, which contribute a small increase of the risk of developing sporadic PD. This knowledge has the potential to have a major impact in the clinical care of people with PD. We summarise these genetic influences and discuss the implications for therapeutics and clinical trial design.
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Affiliation(s)
- Jacob Oliver Day
- Faculty of Health, University of Plymouth, Plymouth PL4 8AA, UK;
| | - Stephen Mullin
- Faculty of Health, University of Plymouth, Plymouth PL4 8AA, UK;
- Department of Clinical and Movement Neurosciences, University College London Institute of Neurology, London WC1N 3BG, UK
- Correspondence:
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Gialluisi A, Reccia MG, Modugno N, Nutile T, Lombardi A, Di Giovannantonio LG, Pietracupa S, Ruggiero D, Scala S, Gambardella S, Iacoviello L, Gianfrancesco F, Acampora D, D’Esposito M, Simeone A, Ciullo M, Esposito T. Identification of sixteen novel candidate genes for late onset Parkinson's disease. Mol Neurodegener 2021; 16:35. [PMID: 34148545 PMCID: PMC8215754 DOI: 10.1186/s13024-021-00455-2] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/06/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Parkinson's disease (PD) is a neurodegenerative movement disorder affecting 1-5% of the general population for which neither effective cure nor early diagnostic tools are available that could tackle the pathology in the early phase. Here we report a multi-stage procedure to identify candidate genes likely involved in the etiopathogenesis of PD. METHODS The study includes a discovery stage based on the analysis of whole exome data from 26 dominant late onset PD families, a validation analysis performed on 1542 independent PD patients and 706 controls from different cohorts and the assessment of polygenic variants load in the Italian cohort (394 unrelated patients and 203 controls). RESULTS Family-based approach identified 28 disrupting variants in 26 candidate genes for PD including PARK2, PINK1, DJ-1(PARK7), LRRK2, HTRA2, FBXO7, EIF4G1, DNAJC6, DNAJC13, SNCAIP, AIMP2, CHMP1A, GIPC1, HMOX2, HSPA8, IMMT, KIF21B, KIF24, MAN2C1, RHOT2, SLC25A39, SPTBN1, TMEM175, TOMM22, TVP23A and ZSCAN21. Sixteen of them have not been associated to PD before, were expressed in mesencephalon and were involved in pathways potentially deregulated in PD. Mutation analysis in independent cohorts disclosed a significant excess of highly deleterious variants in cases (p = 0.0001), supporting their role in PD. Moreover, we demonstrated that the co-inheritance of multiple rare variants (≥ 2) in the 26 genes may predict PD occurrence in about 20% of patients, both familial and sporadic cases, with high specificity (> 93%; p = 4.4 × 10- 5). Moreover, our data highlight the fact that the genetic landmarks of late onset PD does not systematically differ between sporadic and familial forms, especially in the case of small nuclear families and underline the importance of rare variants in the genetics of sporadic PD. Furthermore, patients carrying multiple rare variants showed higher risk of manifesting dyskinesia induced by levodopa treatment. CONCLUSIONS Besides confirming the extreme genetic heterogeneity of PD, these data provide novel insights into the genetic of the disease and may be relevant for its prediction, diagnosis and treatment.
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Affiliation(s)
- Alessandro Gialluisi
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
| | - Mafalda Giovanna Reccia
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
| | - Nicola Modugno
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
| | - Teresa Nutile
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Alessia Lombardi
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
| | - Luca Giovanni Di Giovannantonio
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Sara Pietracupa
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
| | - Daniela Ruggiero
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Simona Scala
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
| | - Stefano Gambardella
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
- grid.12711.340000 0001 2369 7670Department of Biomolecular Science, University of Urbino Carlo Bò, Urbino, Italy
| | | | - Licia Iacoviello
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
- grid.18147.3b0000000121724807Research Center in Epidemiology and Preventive Medicine (EPIMED), Department of Medicine and Surgery, University of Insubria, Varese, Italy
| | - Fernando Gianfrancesco
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Dario Acampora
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Maurizio D’Esposito
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Antonio Simeone
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Marina Ciullo
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
| | - Teresa Esposito
- grid.419543.e0000 0004 1760 3561IRCCS Istituto Neurologico Mediterraneo Neuromed, Pozzilli, Isernia, Italy
- grid.419869.b0000 0004 1758 2860National Research Council, Institute of Genetics and Biophysics “Adriano Buzzati-Traverso”, Naples, Italy
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Tolosa E, Garrido A, Scholz SW, Poewe W. Challenges in the diagnosis of Parkinson's disease. Lancet Neurol 2021; 20:385-397. [PMID: 33894193 PMCID: PMC8185633 DOI: 10.1016/s1474-4422(21)00030-2] [Citation(s) in RCA: 391] [Impact Index Per Article: 130.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 01/08/2021] [Accepted: 01/14/2021] [Indexed: 12/17/2022]
Abstract
Parkinson's disease is the second most common neurodegenerative disease and its prevalence has been projected to double over the next 30 years. An accurate diagnosis of Parkinson's disease remains challenging and the characterisation of the earliest stages of the disease is ongoing. Recent developments over the past 5 years include the validation of clinical diagnostic criteria, the introduction and testing of research criteria for prodromal Parkinson's disease, and the identification of genetic subtypes and a growing number of genetic variants associated with risk of Parkinson's disease. Substantial progress has been made in the development of diagnostic biomarkers, and genetic and imaging tests are already part of routine protocols in clinical practice, while novel tissue and fluid markers are under investigation. Parkinson's disease is evolving from a clinical to a biomarker-supported diagnostic entity, for which earlier identification is possible, different subtypes with diverse prognosis are recognised, and novel disease-modifying treatments are in development.
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Affiliation(s)
- Eduardo Tolosa
- Parkinson’s disease and Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPS, Universitat de Barcelona, Barcelona, Spain
| | - Alicia Garrido
- Parkinson’s disease and Movement Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), Hospital Clínic, IDIBAPS, Universitat de Barcelona, Barcelona, Spain
| | - Sonja W. Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Werner Poewe
- Department of Neurology, Medical University Innsbruck, Innsbruck, Austria
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Lake J, Storm CS, Makarious MB, Bandres-Ciga S. Genetic and Transcriptomic Biomarkers in Neurodegenerative Diseases: Current Situation and the Road Ahead. Cells 2021; 10:1030. [PMID: 33925602 PMCID: PMC8170880 DOI: 10.3390/cells10051030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 04/21/2021] [Accepted: 04/24/2021] [Indexed: 12/19/2022] Open
Abstract
Neurodegenerative diseases are etiologically and clinically heterogeneous conditions, often reflecting a spectrum of disease rather than well-defined disorders. The underlying molecular complexity of these diseases has made the discovery and validation of useful biomarkers challenging. The search of characteristic genetic and transcriptomic indicators for preclinical disease diagnosis, prognosis, or subtyping is an area of ongoing effort and interest. The next generation of biomarker studies holds promise by implementing meaningful longitudinal and multi-modal approaches in large scale biobank and healthcare system scale datasets. This work will only be possible in an open science framework. This review summarizes the current state of genetic and transcriptomic biomarkers in Parkinson's disease, Alzheimer's disease, and amyotrophic lateral sclerosis, providing a comprehensive landscape of recent literature and future directions.
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Affiliation(s)
- Julie Lake
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA; (J.L.); (M.B.M.)
| | - Catherine S. Storm
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK;
- UCL Movement Disorders Centre, University College London, London WC1E 6BT, UK
| | - Mary B. Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA; (J.L.); (M.B.M.)
| | - Sara Bandres-Ciga
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA; (J.L.); (M.B.M.)
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36
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Li C, Ou R, Chen Y, Gu X, Wei Q, Cao B, Zhang L, Hou Y, Liu K, Chen X, Song W, Zhao B, Wu Y, Li T, Dong X, Shang H. Genetic Modifiers of Age at Onset for Parkinson's Disease in Asians: A Genome-Wide Association Study. Mov Disord 2021; 36:2077-2084. [PMID: 33884653 DOI: 10.1002/mds.28621] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 03/14/2021] [Accepted: 03/25/2021] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Age at onset (AAO) is an essential feature of Parkinson's disease (PD) and can help predict disease progression and mortality. Identification of genetic variants influencing AAO of PD could lead to a better understanding of the disease's biological mechanism and provide clinical guidance. However, genetic determinants for AAO of PD remain mostly unknown, especially in the Asian population. OBJECTIVES To identify genetic determinants for AAO of PD in the Asian population. METHODS We performed a genome-wide association meta-analysis on AAO of PD in 5166 Chinese patients with PD (Ndiscovery = 3628, Nreplication = 1538). We then conducted a further cross-ethnic meta-analysis using our results and summary statistics for the AAO of PD from the European population. RESULTS The total heritability of AAO of PD was around 0.10 ~ 0.14, similar to that (~0.11) estimated in populations of European ancestry. One novel significant intergenic locus rs9783733 (NDN; PWRN4) was identified (P = 3.14E-09, beta = 2.30, SE = 0.39). Remarkably, this variant could delay AAO of PD by ~2.43 years, with a more considerable effect on males (~3.18 years) than females (~1.45 years). The variant was suggestively significant in the cross-ethnic meta-analysis and suggested a positive selection in the East Asian population. Additionally, cross-ethnic meta-analysis identified a significant locus rs356203 in SNCA (P = 2.35E-11, beta = -0.71, SE = 0.01). CONCLUSIONS These findings improve the current understanding of the genetic etiology of AAO of PD in different ethnic groups, and provide a new target for further research on PD pathogenesis and potential therapeutic options. © 2021 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Chunyu Li
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Ruwei Ou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Yongping Chen
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Xiaojing Gu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Qianqian Wei
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Bei Cao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Lingyu Zhang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Yanbing Hou
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Kuncheng Liu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Xueping Chen
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Wei Song
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Bi Zhao
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Ying Wu
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China
| | - Tao Li
- Psychiatric Laboratory and Mental Health Center, The State Key Laboratory of Biotherapy, West China Hospital of Sichuan University, Chengdu, China.,Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
| | - Xianjun Dong
- Genomics and Bioinformatics Hub, Harvard Medical School and Brigham & Women's Hospital, Boston, Massachusetts, USA.,Center for Advanced Parkinson Research, Harvard Medical School and Brigham & Women's Hospital, Boston, Massachusetts, USA
| | - Huifang Shang
- Department of Neurology, Laboratory of Neurodegenerative Disorders, National Clinical Research Center for Geriatrics, West China Hospital of Sichuan University, Chengdu, China.,Huaxi Brain Research Center, West China Hospital of Sichuan University, Chengdu, China
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Oña G, Bouso JC. Therapeutic Potential of Natural Psychoactive Drugs for Central Nervous System Disorders: A Perspective from Polypharmacology. Curr Med Chem 2021; 28:53-68. [PMID: 31830883 DOI: 10.2174/0929867326666191212103330] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2019] [Revised: 10/01/2019] [Accepted: 10/02/2019] [Indexed: 11/22/2022]
Abstract
In the drug development, the formation of highly selective ligands has been unsuccessful in the treatment of central nervous system disorders. Multi-target ligands, from the polypharmacology paradigm, are being proposed as treatments for these complex disorders, since they offer enhanced efficacy and a strong safety profile. Natural products are the best examples of multi-target compounds, so they are of high interest within this paradigm. Additionally, recent research on psychoactive drugs of natural origin, such as ayahuasca and cannabis, has demonstrated the promising therapeutic potential for the treatment of some psychiatric and neurological disorders. In this text, we describe how research on psychoactive drugs can be effectively combined with the polypharmacology paradigm, providing ayahuasca and cannabis research as examples. The advantages and disadvantages are also discussed.
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Affiliation(s)
- Genís Oña
- International Center for Ethnobotanical Education, Research and Service (ICEERS), Barcelona, Spain
| | - José Carlos Bouso
- International Center for Ethnobotanical Education, Research and Service (ICEERS), Barcelona, Spain
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Zhao Y, Qin L, Pan H, Liu Z, Jiang L, He Y, Zeng Q, Zhou X, Zhou X, Zhou Y, Fang Z, Wang Z, Xiang Y, Yang H, Wang Y, Zhang K, Zhang R, He R, Zhou X, Zhou Z, Yang N, Liang D, Chen J, Zhang X, Zhou Y, Liu H, Deng P, Xu K, Xu K, Zhou C, Zhong J, Xu Q, Sun Q, Li B, Zhao G, Wang T, Chen L, Shang H, Liu W, Chan P, Xue Z, Wang Q, Guo L, Wang X, Xu C, Zhang Z, Chen T, Lei L, Zhang H, Wang C, Tan J, Yan X, Shen L, Jiang H, Zhang Z, Hu Z, Xia K, Yue Z, Li J, Guo J, Tang B. The role of genetics in Parkinson's disease: a large cohort study in Chinese mainland population. Brain 2020; 143:2220-2234. [PMID: 32613234 DOI: 10.1093/brain/awaa167] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 03/19/2020] [Accepted: 04/06/2020] [Indexed: 02/05/2023] Open
Abstract
This study aimed to determine the mutational spectrum of familial Parkinson's disease and sporadic early-onset Parkinson's disease (sEOPD) in a mainland Chinese population and the clinical features of mutation carriers. We performed multiplex ligation-dependent probe amplification assays and whole-exome sequencing for 1676 unrelated patients with Parkinson's disease in a mainland Chinese population, including 192 probands from families with autosomal-recessive Parkinson's disease, 242 probands from families with autosomal-dominant Parkinson's disease, and 1242 sEOPD patients (age at onset ≤ 50). According to standards and guidelines from the American College of Medical Genetics and Genomics, pathogenic/likely pathogenic variants in 23 known Parkinson's disease-associated genes occurred more frequently in the autosomal-recessive Parkinson's disease cohort (65 of 192, 33.85%) than in the autosomal-dominant Parkinson's disease cohort (10 of 242, 4.13%) and the sEOPD cohort (57 of 1242, 4.59%), which leads to an overall molecular diagnostic yield of 7.88% (132 of 1676). We found that PRKN was the most frequently mutated gene (n = 83, 4.95%) and present the first evidence of an SNCA duplication and LRRK2 p.N1437D variant in mainland China. In addition, several novel pathogenic/likely pathogenic variants including LRRK2 (p.V1447M and p.Y1645S), ATP13A2 (p.R735X and p.A819D), FBXO7 (p.G67E), LRP10 (c.322dupC/p.G109Rfs*51) and TMEM230 (c.429delT/p.P144Qfs*2) were identified in our cohort. Furthermore, the age at onset of the 132 probands with genetic diagnoses (median, 31.5 years) was about 14.5 years earlier than that of patients without molecular diagnoses (i.e. non-carriers, median 46.0 years). Specifically, the age at onset of Parkinson's disease patients with pathogenic/likely pathogenic variants in ATP13A2, PLA2G6, PRKN, or PINK1 was significantly lower than that of non-carriers, while the age at onset of carriers with other gene pathogenic/likely pathogenic variants was similar to that of non-carriers. The clinical spectrum of Parkinson's disease-associated gene carriers in this mainland Chinese population was similar to that of other populations. We also detected 61 probands with GBA possibly pathogenic variants (3.64%) and 59 probands with GBA p.L444P (3.52%). These results shed insight into the genetic spectrum and clinical manifestations of Parkinson's disease in mainland China and expand the existing repertoire of pathogenic or likely pathogenic variants involved in known Parkinson's disease-associated genes. Our data highlight the importance of genetic testing in Parkinson's disease patients with age at onset < 40 years, especially in those from families with a recessive inheritance pattern, who may benefit from early diagnosis and treatment.
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Affiliation(s)
- Yuwen Zhao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Lixia Qin
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Hongxu Pan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhenhua Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Li Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Yan He
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Qian Zeng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Xun Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Xiaoxia Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Yangjie Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhenghuan Fang
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Zheng Wang
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Yaqin Xiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Honglan Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Yige Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Kailin Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Rui Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Runcheng He
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Xiaoting Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhou Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Nannan Yang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Dongxiao Liang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Juan Chen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Xuxiang Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Yao Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Hongli Liu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Penghui Deng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Kun Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Ke Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Chaojun Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Junfei Zhong
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Qian Xu
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Qiying Sun
- Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Bin Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Guihu Zhao
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Tao Wang
- Department of Neurology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
| | - Ling Chen
- Department of Neurology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510080, China
| | - Huifang Shang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China
| | - Weiguo Liu
- Department of Neurology, Affiliated Brain Hospital of Nanjing Medical University, Nanjing, Jiangsu 210029, China
| | - Piu Chan
- Department of Neurobiology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China.,Parkinson's Disease Center, Beijing Institute for Brain Disorders, Beijing 100101, China
| | - Zheng Xue
- Department of Neurology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
| | - Qing Wang
- Department of Neurology, Zhujiang Hospital of Southern Medical University, Guangzhou, Guangdong 510282, China
| | - Li Guo
- Department of Neurology, The First Affiliated Hospital of Jinan University, Guangzhou, Guangdong 510632, China
| | - Xuejing Wang
- Department of Neurology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan 450047, China
| | - Changshui Xu
- Department of Neurology, Henan provincial people's hospital, Zhengzhou, Henan 450003, China
| | - Zhentao Zhang
- Department of Neurology, Renmin Hospital of Wuhan University, Wuhan, Hubei 430060, China
| | - Tao Chen
- Department of Neurology, Hainan General Hospital, Haikou, Hainan 570311, China
| | - Lifang Lei
- Department of Neurology, The Third Xiangya Hospital, Central South University, Changsha, Hunan 410013, China
| | - Hainan Zhang
- Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
| | - Chunyu Wang
- Department of Neurology, The Second Xiangya Hospital, Central South University, Changsha, Hunan 410011, China
| | - Jieqiong Tan
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Xinxiang Yan
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Lu Shen
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Hong Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Zhuohua Zhang
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Zhengmao Hu
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Kun Xia
- Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Zhenyu Yue
- Departments of Neurology and Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jinchen Li
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China.,Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
| | - Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China
| | - Beisha Tang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.,Centre for Medical Genetics and Hunan Key Laboratory of Medical Genetics, School of Life Sciences, Central South University, Changsha, Hunan 410008, China.,Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
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Hall A, Bandres-Ciga S, Diez-Fairen M, Quinn JP, Billingsley KJ. Genetic Risk Profiling in Parkinson's Disease and Utilizing Genetics to Gain Insight into Disease-Related Biological Pathways. Int J Mol Sci 2020; 21:E7332. [PMID: 33020390 PMCID: PMC7584037 DOI: 10.3390/ijms21197332] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 09/30/2020] [Accepted: 10/01/2020] [Indexed: 12/18/2022] Open
Abstract
Parkinson's disease (PD) is a complex disorder underpinned by both environmental and genetic factors. The latter only began to be understood around two decades ago, but since then great inroads have rapidly been made into deconvoluting the genetic component of PD. In particular, recent large-scale projects such as genome-wide association (GWA) studies have provided insight into the genetic risk factors associated with genetically ''complex'' PD (PD that cannot readily be attributed to single deleterious mutations). Here, we discuss the plethora of genetic information provided by PD GWA studies and how this may be utilized to generate polygenic risk scores (PRS), which may be used in the prediction of risk and trajectory of PD. We also comment on how pathway-specific genetic profiling can be used to gain insight into PD-related biological pathways, and how this may be further utilized to nominate causal PD genes and potentially druggable therapeutic targets. Finally, we outline the current limits of our understanding of PD genetics and the potential contribution of variation currently uncaptured in genetic studies, focusing here on uncatalogued structural variants.
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Affiliation(s)
- Ashley Hall
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular & Integrative Biology, University of Liverpool, L69 7BE, UK; (A.H.); (J.P.Q.)
| | - Sara Bandres-Ciga
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA;
| | - Monica Diez-Fairen
- Neurogenetics Group, University Hospital MutuaTerrassa, Sant Antoni 19, 08221 Terrassa, Barcelona, Spain;
| | - John P. Quinn
- Department of Pharmacology and Therapeutics, Institute of Systems, Molecular & Integrative Biology, University of Liverpool, L69 7BE, UK; (A.H.); (J.P.Q.)
| | - Kimberley J. Billingsley
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA;
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40
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Finkbeiner S. Functional genomics, genetic risk profiling and cell phenotypes in neurodegenerative disease. Neurobiol Dis 2020; 146:105088. [PMID: 32977020 PMCID: PMC7686089 DOI: 10.1016/j.nbd.2020.105088] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 09/11/2020] [Accepted: 09/18/2020] [Indexed: 12/03/2022] Open
Abstract
Human genetics provides unbiased insights into the causes of human disease, which can be used to create a foundation for effective ways to more accurately diagnose patients, stratify patients for more successful clinical trials, discover and develop new therapies, and ultimately help patients choose the safest and most promising therapeutic option based on their risk profile. But the process for translating basic observations from human genetics studies into pathogenic disease mechanisms and treatments is laborious and complex, and this challenge has particularly slowed the development of interventions for neurodegenerative disease. In this review, we discuss the many steps in the process, the important considerations at each stage, and some of the latest tools and technologies that are available to help investigators translate insights from human genetics into diagnostic and therapeutic strategies that will lead to the sort of advances in clinical care that make a difference for patients.
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Affiliation(s)
- Steven Finkbeiner
- Center for Systems and Therapeutics, USA; Taube/Koret Center for Neurodegenerative Disease Research, Gladstone Institutes, San Francisco, CA 94158, USA; Departments of Neurology and Physiology, University of Califorina, San Francisco, CA 94158, USA.
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41
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Bellou E, Stevenson-Hoare J, Escott-Price V. Polygenic risk and pleiotropy in neurodegenerative diseases. Neurobiol Dis 2020; 142:104953. [PMID: 32445791 PMCID: PMC7378564 DOI: 10.1016/j.nbd.2020.104953] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 05/12/2020] [Accepted: 05/18/2020] [Indexed: 12/12/2022] Open
Abstract
In this paper we explore the phenomenon of pleiotropy in neurodegenerative diseases, focusing on Alzheimer's disease (AD). We summarize the various techniques developed to investigate pleiotropy among traits, elaborating in the polygenic risk scores (PRS) analysis. PRS was designed to assess a cumulative effect of a large number of SNPs for association with a disease and, later for disease risk prediction. Since genetic predictions rely on heritability, we discuss SNP-based heritability from genome-wide association studies and its contribution to the prediction accuracy of PRS. We review work examining pleiotropy in neurodegenerative diseases and related phenotypes and biomarkers. We conclude that the exploitation of pleiotropy may aid in the identification of novel genes and provide further insights in the disease mechanisms, and along with PRS analysis, may be advantageous for precision medicine.
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42
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Genetic predispositions of Parkinson's disease revealed in patient-derived brain cells. NPJ PARKINSONS DISEASE 2020; 6:8. [PMID: 32352027 PMCID: PMC7181694 DOI: 10.1038/s41531-020-0110-8] [Citation(s) in RCA: 51] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 03/20/2020] [Indexed: 12/14/2022]
Abstract
Parkinson's disease (PD) is the second most prevalent neurological disorder and has been the focus of intense investigations to understand its etiology and progression, but it still lacks a cure. Modeling diseases of the central nervous system in vitro with human induced pluripotent stem cells (hiPSC) is still in its infancy but has the potential to expedite the discovery and validation of new treatments. Here, we discuss the interplay between genetic predispositions and midbrain neuronal impairments in people living with PD. We first summarize the prevalence of causal Parkinson's genes and risk factors reported in 74 epidemiological and genomic studies. We then present a meta-analysis of 385 hiPSC-derived neuronal lines from 67 recent independent original research articles, which point towards specific impairments in neurons from Parkinson's patients, within the context of genetic predispositions. Despite the heterogeneous nature of the disease, current iPSC models reveal converging molecular pathways underlying neurodegeneration in a range of familial and sporadic forms of Parkinson's disease. Altogether, consolidating our understanding of robust cellular phenotypes across genetic cohorts of Parkinson's patients may guide future personalized drug screens in preclinical research.
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43
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Ohnmacht J, May P, Sinkkonen L, Krüger R. Missing heritability in Parkinson's disease: the emerging role of non-coding genetic variation. J Neural Transm (Vienna) 2020; 127:729-748. [PMID: 32248367 PMCID: PMC7242266 DOI: 10.1007/s00702-020-02184-0] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2020] [Accepted: 03/24/2020] [Indexed: 02/01/2023]
Abstract
Parkinson’s disease (PD) is a neurodegenerative disorder caused by a complex interplay of genetic and environmental factors. For the stratification of PD patients and the development of advanced clinical trials, including causative treatments, a better understanding of the underlying genetic architecture of PD is required. Despite substantial efforts, genome-wide association studies have not been able to explain most of the observed heritability. The majority of PD-associated genetic variants are located in non-coding regions of the genome. A systematic assessment of their functional role is hampered by our incomplete understanding of genotype–phenotype correlations, for example through differential regulation of gene expression. Here, the recent progress and remaining challenges for the elucidation of the role of non-coding genetic variants is reviewed with a focus on PD as a complex disease with multifactorial origins. The function of gene regulatory elements and the impact of non-coding variants on them, and the means to map these elements on a genome-wide level, will be delineated. Moreover, examples of how the integration of functional genomic annotations can serve to identify disease-associated pathways and to prioritize disease- and cell type-specific regulatory variants will be given. Finally, strategies for functional validation and considerations for suitable model systems are outlined. Together this emphasizes the contribution of rare and common genetic variants to the complex pathogenesis of PD and points to remaining challenges for the dissection of genetic complexity that may allow for better stratification, improved diagnostics and more targeted treatments for PD in the future.
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Affiliation(s)
- Jochen Ohnmacht
- LCSB, University of Luxembourg, Belvaux, Luxembourg.,Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Patrick May
- LCSB, University of Luxembourg, Belvaux, Luxembourg
| | - Lasse Sinkkonen
- Department of Life Sciences and Medicine (DLSM), University of Luxembourg, Belvaux, Luxembourg
| | - Rejko Krüger
- LCSB, University of Luxembourg, Belvaux, Luxembourg. .,Luxembourg Institute of Health (LIH), Transversal Translational Medicine, Strassen, Luxembourg. .,Parkinson Research Clinic, Centre Hospitalier de Luxembourg (CHL), Luxembourg, Luxembourg.
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Burholt V, Winter B, Aartsen M, Constantinou C, Dahlberg L, Feliciano V, De Jong Gierveld J, Van Regenmortel S, Waldegrave C. A critical review and development of a conceptual model of exclusion from social relations for older people. Eur J Ageing 2020; 17:3-19. [PMID: 32158368 PMCID: PMC7040153 DOI: 10.1007/s10433-019-00506-0] [Citation(s) in RCA: 40] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
Social exclusion is complex and dynamic, and it leads to the non-realization of social, economic, political or cultural rights or participation within a society. This critical review takes stock of the literature on exclusion of social relations. Social relations are defined as comprising social resources, social connections and social networks. An evidence review group undertook a critical review which integrates, interprets and synthesizes information across studies to develop a conceptual model of exclusion from social relations. The resulting model is a subjective interpretation of the literature and is intended to be the starting point for further evaluations. The conceptual model identifies individual risks for exclusion from social relations (personal attributes, biological and neurological risk, retirement, socio-economic status, exclusion from material resources and migration). It incorporates the evaluation of social relations, and the influence of psychosocial resources and socio-emotional processes, sociocultural, social-structural, environmental and policy contextual influences on exclusion from social relations. It includes distal outcomes of exclusion from social relations, that is, individual well-being, health and functioning, social opportunities and social cohesion. The dynamic relationships between elements of the model are also reported. We conclude that the model provides a subjective interpretation of the data and an excellent starting point for further phases of conceptual development and systematic evaluation(s). Future research needs to consider the use of sophisticated analytical tools and an interdisciplinary approach in order to understand the underlying biological and ecopsychosocial associations that contribute to individual and dynamic differences in the experience of exclusion from social relations.
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Affiliation(s)
- Vanessa Burholt
- Centre for Innovative Ageing, Swansea University, Swansea, Wales UK
| | - Bethan Winter
- Centre for Innovative Ageing, Swansea University, Swansea, Wales UK
| | - Marja Aartsen
- Centre for Welfare and Labour Research, OsloMet Oslo Metropolitan University, Oslo, Norway
| | | | - Lena Dahlberg
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden
- Aging Research Center, Karolinska Institute, Solna, Sweden
| | - Villar Feliciano
- Department of Development and Educational Psychology, University of Barcelona, Barcelona, Spain
| | - Jenny De Jong Gierveld
- Faculty of Social Science, VU University Amsterdam, Amsterdam, The Netherlands
- Netherlands Interdisciplinary Demographic Institute, The Hague, The Netherlands
| | - Sofie Van Regenmortel
- Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium
| | | | - The Working Group on Exclusion from Social Relations, part of the COST-financed Research Network ‘Reducing Old-Age Exclusion: Collaborations in Research and Policy’ (ROSENet)
- Centre for Innovative Ageing, Swansea University, Swansea, Wales UK
- Centre for Welfare and Labour Research, OsloMet Oslo Metropolitan University, Oslo, Norway
- University of Nicosia Medical School, Nicosia, Cyprus
- School of Education, Health and Social Studies, Dalarna University, Falun, Sweden
- Aging Research Center, Karolinska Institute, Solna, Sweden
- Department of Development and Educational Psychology, University of Barcelona, Barcelona, Spain
- Faculty of Social Science, VU University Amsterdam, Amsterdam, The Netherlands
- Netherlands Interdisciplinary Demographic Institute, The Hague, The Netherlands
- Faculty of Psychology and Educational Sciences, Vrije Universiteit Brussel, Brussels, Belgium
- Family Centre Social Policy Research Unit, Lower Hutt, New Zealand
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Gialluisi A, Reccia MG, Tirozzi A, Nutile T, Lombardi A, De Sanctis C, Varanese S, Pietracupa S, Modugno N, Simeone A, Ciullo M, Esposito T. Whole Exome Sequencing Study of Parkinson Disease and Related Endophenotypes in the Italian Population. Front Neurol 2020; 10:1362. [PMID: 31998221 PMCID: PMC6965311 DOI: 10.3389/fneur.2019.01362] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2019] [Accepted: 12/10/2019] [Indexed: 12/30/2022] Open
Abstract
Parkinson Disease (PD) is a complex neurodegenerative disorder characterized by large genetic heterogeneity and missing heritability. Since the genetic background of PD can partly vary among ethnicities and neurological scales have been scarcely investigated in a PD setting, we performed an exploratory Whole Exome Sequencing (WES) analysis of 123 PD patients from mainland Italy, investigating scales assessing motor (UPDRS), cognitive (MoCA), and other non-motor symptoms (NMS). We performed variant prioritization, followed by targeted association testing of prioritized variants in 446 PD cases and 211 controls. Then we ran Exome-Wide Association Scans (EWAS) within sequenced PD cases (N = 113), testing both motor and non-motor PD endophenotypes, as well as their associations with Polygenic Risk Scores (PRS) influencing brain subcortical volumes. We identified a variant associated with PD, rs201330591 in GTF2H2 (5q13; alternative T allele: OR [CI] = 8.16[1.08; 61.52], FDR = 0.048), which was not replicated in an independent cohort of European ancestry (1,148 PD cases, 503 controls). In the EWAS, polygenic analyses revealed statistically significant multivariable associations of amygdala- [β(SE) = -0.039(0.013); FDR = 0.039] and caudate-PRS [0.043(0.013); 0.028] with motor symptoms. All subcortical PRSs in a multivariable model notably increased the variance explained in motor (adjusted-R2 = 38.6%), cognitive (32.2%) and other non-motor symptoms (28.9%), compared to baseline models (~20%). Although, the small sample size warrants further replications, these findings suggest shared genetic architecture between PD symptoms and subcortical structures, and provide interesting clues on PD genetic and neuroimaging features.
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Affiliation(s)
| | | | | | - Teresa Nutile
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
| | | | | | | | | | | | | | - Antonio Simeone
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
| | - Marina Ciullo
- IRCCS Neuromed, Pozzilli, Italy
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
| | - Teresa Esposito
- IRCCS Neuromed, Pozzilli, Italy
- Institute of Genetics and Biophysics, National Research Council, Naples, Italy
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Correia Guedes L, Mestre T, Outeiro TF, Ferreira JJ. Are genetic and idiopathic forms of Parkinson's disease the same disease? J Neurochem 2019; 152:515-522. [PMID: 31643079 DOI: 10.1111/jnc.14902] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2019] [Revised: 10/09/2019] [Accepted: 10/16/2019] [Indexed: 01/02/2023]
Abstract
Genetic forms represent a small fraction of Parkinson's disease (PD) but their discovery has revolutionized research in the field, putting α-synuclein in the spotlight, and uncovering other key neuropathological mechanisms of the disease. The question of whether genetic and idiopathic PD (iPD) correspond to a same disease entity is not simply philosophical, has implications for the discovery of the biological background of PD and for the development of novel therapeutic strategies that may also be applicable to the larger iPD group. Here, we review the current landscape of what has been labeled genetic PD and critically discuss the rational for merging or separating genetic and idiopathic forms of PD as the same or different disease entities. We conclude by addressing the potential implications for future research.
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Affiliation(s)
- Leonor Correia Guedes
- Department of Neuroscience and Mental Health, Neurology, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte, Lisbon, Portugal.,Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal
| | - Tiago Mestre
- Parkinson's disease and Movement Disorders Center, Division of Neurology, Department of Medicine, The Ottawa Hospital Research Institute, University of Ottawa Brain and Research Institute, Ottawa, Canada
| | - Tiago F Outeiro
- Department of Experimental Neurodegeneration, Center for Biostructural Imaging of Neurodegeneration, University Medical Center Göttingen, Göttingen, Germany.,Max Planck Institute for Experimental Medicine, Göttingen, Germany.,Institute of Neuroscience, The Medical School, Newcastle University, Newcastle upon Tyne, UK
| | - Joaquim J Ferreira
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal.,Laboratory of Clinical Pharmacology and Therapeutics, Faculdade de Medicina da Universidade de Lisboa, Lisbon, Portugal.,CNS-Campus Neurológico Sénior, Torres Vedras, Portugal
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47
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Manrique de Lara A, Soto-Gómez L, Núñez-Acosta E, Saruwatari-Zavala G, Rentería ME. Ethical issues in susceptibility genetic testing for late-onset neurodegenerative diseases. Am J Med Genet B Neuropsychiatr Genet 2019; 180:609-621. [PMID: 30525300 DOI: 10.1002/ajmg.b.32699] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 10/16/2018] [Accepted: 10/30/2018] [Indexed: 12/12/2022]
Abstract
Genome-wide association studies have revolutionized our understanding of the genetic architecture of complex traits and diseases over the last decade. This knowledge is enabling clinicians, researchers, and direct-to-consumer genetics companies to conduct disease susceptibility testing based on powerful methods such as polygenic risk scoring. However, these technologies raise a set of complex ethical, legal, social, and policy considerations. Here we review and discuss a series of ethical dilemmas associated with susceptibility genetic testing for the two most common late-onset neurodegenerative diseases, Alzheimer's and Parkinson's disease, including testing in asymptomatic individuals. Among others, these include informed consent, disclosure of results and unexpected findings, mandatory screening, privacy and confidentiality, and stigma and genetic discrimination. Importantly, appropriate counseling is a deciding factor for the ethical soundness of genetic testing, which poses a challenge for the regulation of these tests and the training of healthcare professionals. As genetic knowledge about these diseases continues growing and genetic testing becomes more widespread, it is increasingly important to raise awareness among researchers, medical practitioners, genetic counselors, and decision makers about the ethical, legal, and social issues associated with genetic testing for polygenic diseases.
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Affiliation(s)
- Amaranta Manrique de Lara
- Licenciatura en Ciencias Genómicas, Instituto de Biotecnología y Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Morelos, Mexico
| | - Liliana Soto-Gómez
- Instituto de Investigaciones Jurídicas, Universidad Nacional Autónoma de México, Coyoacán, Ciudad de México, Mexico
| | - Elisa Núñez-Acosta
- Oficina de Información Científica y Tecnológica para el Congreso de la Unión (INCyTU), Foro Consultivo Científico y Tecnológico, A.C., Coyoacán, Ciudad de México, Mexico
| | - Garbiñe Saruwatari-Zavala
- Departamento de Estudios Jurídicos, Éticos y Sociales, Instituto Nacional de Medicina Genómica, Tlalpan, Ciudad de México, Mexico
| | - Miguel E Rentería
- Department of Genetics & Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
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48
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Azizova TV, Bannikova MV, Grigoryeva ES, Rybkina VL, Hamada N. Occupational exposure to chronic ionizing radiation increases risk of Parkinson's disease incidence in Russian Mayak workers. Int J Epidemiol 2019; 49:435-447. [DOI: 10.1093/ije/dyz230] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/17/2019] [Indexed: 12/31/2022] Open
Abstract
Abstract
Background
Patients receiving radiotherapy demonstrate cognitive deficits, impairment of neurogenesis and neurovascular damage developing as late side effects of radiation exposure to the head. In light of the increasing use of diagnostic radiological procedures, epidemiological data raise concerns about possible harmful effects of low-level radiation on the human brain. A series of studies of chronically exposed Russian nuclear workers have provided information on risks of cancer and non-cancer diseases.
Methods
This study aimed to assess the risk of Parkinson’s-disease (PD) incidence in a cohort of workers occupationally exposed to chronic radiation. The cohort comprised workers of a Russian nuclear production facility who were first employed in 1948–1982 and followed up until the end of 2013 (22 377 individuals; 25% female). Using the AMFIT module of EPICURE software, relative risk and excess relative risk per unit dose (ERR/Gy) were calculated based on maximum likelihood.
Results
A linear association was found between PD incidence and cumulative γ-dose after adjusting for sex and attained age [ERR/Gy = 1.02 (95% confidence interval, 0.59 to 1.63, p = 5.44 × 10–5)]. The ERR/Gy of external radiation for PD incidence was stable after adjusting for neutron dose (ERR/Gy = 1.03; 95% confidence interval: 0.59 to 1.67, p = 6.86 × 10–5). The risk increased with increasing lag period and decreased notably after adjusting for body mass index, smoking and alcohol consumption. Additional adjustments for hypertension, gout, gastric ulcer, head injuries with loss of awareness and diabetes mellitus did not affect the risk estimate.
Conclusions
This study is the first to suggest that PD is associated with prolonged occupational external γ-ray exposure.
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Affiliation(s)
- Tamara V Azizova
- Southern Urals Biophysics Institute (SUBI), Ozyorsk Chelyabinsk Region, Russia
| | - Maria V Bannikova
- Southern Urals Biophysics Institute (SUBI), Ozyorsk Chelyabinsk Region, Russia
| | | | - Valentina L Rybkina
- Southern Urals Biophysics Institute (SUBI), Ozyorsk Chelyabinsk Region, Russia
| | - Nobuyuki Hamada
- Radiation Safety Research Center, Nuclear Technology Research Laboratory, Central Research Institute of Electric Power Industry (CRIEPI), Komae, Tokyo, Japan
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49
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Lee MJ, Pak K, Kim JH, Kim YJ, Yoon J, Lee J, Lyoo CH, Park HJ, Lee JH, Jung NY. Effect of polygenic load on striatal dopaminergic deterioration in Parkinson disease. Neurology 2019; 93:e665-e674. [PMID: 31289143 DOI: 10.1212/wnl.0000000000007939] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2018] [Accepted: 03/21/2019] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To investigate the effect of polygenic load on the progression of striatal dopaminergic dysfunction in patients with Parkinson disease (PD). METHODS Using data from 335 patients with PD in the Parkinson's Progression Markers Initiative (PPMI) database, we investigated the longitudinal association of PD-associated polygenic load with changes in striatal dopaminergic activity as measured by 123I-N-3-fluoropropyl-2-β-carboxymethoxy-3β-(4-iodophenyl) nortropane (123I-FP-CIT) SPECT over 4 years. PD-associated polygenic load was estimated by calculating weighted genetic risk scores (GRS) using 1) all available 27 PD-risk single nucleotide polymorphisms (SNPs) in the PPMI database (GRS1) and 2) 23 SNPs with minor allele frequency >0.05 (GRS2). RESULTS GRS1 and GRS2 were correlated with younger age at onset in patients with PD (GRS1, Spearman ρ = -0.128, p = 0.019; GRS2, Spearman ρ = -0.109, p = 0.047). Although GRS1 did not show an association with changes in striatal 123I-FP-CIT availability, GRS2 was associated with a slower decline of striatal dopaminergic activity (interactions with disease duration in linear mixed model; caudate nucleus, estimate = 0.399, SE = 0.165, p = 0.028; putamen, estimate = 0.396, SE = 0.137, p = 0.016). CONCLUSIONS Our results suggest that genetic factors for PD risk may have heterogeneous effects on striatal dopaminergic degeneration, and some factors may be associated with a slower decline of dopaminergic activity. Composition of PD progression-specific GRS may be useful in predicting disease progression in patients.
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Affiliation(s)
- Myung Jun Lee
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea.
| | - Kyoungjune Pak
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
| | - Jong Hun Kim
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
| | - Yun Joong Kim
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
| | - Jeehee Yoon
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
| | - Jinwoo Lee
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea.
| | - Chul Hyoung Lyoo
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
| | - Hyung Jun Park
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
| | - Jae-Hyeok Lee
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea.
| | - Na-Yeon Jung
- From the Departments of Neurology (M.J.L.) and Nuclear Medicine (K.P.), Pusan National University Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Busan; Department of Neurology (J.H.K.), National Health Insurance Service Ilsan Hospital, Goyang; Department of Neurology (Y.J.K.), Hallym University College of Medicine, Anyang; Department of Computer Engineering (J.Y., J.L.), Hallym University, Chuncheon; Department of Neurology (C.H.L.), Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul; Department of Neurology (H.J.P.), Gangneung Asan Hospital, University of Ulsan College of Medicine, Gangneung; and Department of Neurology (J.-H.L., N.-Y.J.), Pusan National University Yangsan Hospital, Pusan National University School of Medicine and Biomedical Research Institute, Yangsan, Republic of Korea
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50
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Guerreiro R, Escott-Price V, Hernandez DG, Kun-Rodrigues C, Ross OA, Orme T, Neto JL, Carmona S, Dehghani N, Eicher JD, Shepherd C, Parkkinen L, Darwent L, Heckman MG, Scholz SW, Troncoso JC, Pletnikova O, Dawson T, Rosenthal L, Ansorge O, Clarimon J, Lleo A, Morenas-Rodriguez E, Clark L, Honig LS, Marder K, Lemstra A, Rogaeva E, St George-Hyslop P, Londos E, Zetterberg H, Barber I, Braae A, Brown K, Morgan K, Troakes C, Al-Sarraj S, Lashley T, Holton J, Compta Y, Van Deerlin V, Serrano GE, Beach TG, Lesage S, Galasko D, Masliah E, Santana I, Pastor P, Diez-Fairen M, Aguilar M, Tienari PJ, Myllykangas L, Oinas M, Revesz T, Lees A, Boeve BF, Petersen RC, Ferman TJ, Graff-Radford N, Cairns NJ, Morris JC, Pickering-Brown S, Mann D, Halliday GM, Hardy J, Trojanowski JQ, Dickson DW, Singleton A, Stone DJ, Bras J. Heritability and genetic variance of dementia with Lewy bodies. Neurobiol Dis 2019; 127:492-501. [PMID: 30953760 PMCID: PMC6588425 DOI: 10.1016/j.nbd.2019.04.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2019] [Revised: 03/23/2019] [Accepted: 04/02/2019] [Indexed: 12/15/2022] Open
Abstract
Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.
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Affiliation(s)
- Rita Guerreiro
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK; UK Dementia Research Institute (UK DRI) at UCL, London, UK
| | - Valentina Escott-Price
- UK Dementia Research Institute (UK DRI) at Cardiff, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK
| | - Dena G Hernandez
- Laboratory of Neurogenetics, National Institutes on Aging, NIH, Bethesda, MD, USA; German Center for Neurodegenerative Diseases (DZNE)-Tubingen, Germany
| | - Celia Kun-Rodrigues
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Tatiana Orme
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK; UK Dementia Research Institute (UK DRI) at UCL, London, UK
| | - Joao Luis Neto
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK; UK Dementia Research Institute (UK DRI) at UCL, London, UK
| | - Susana Carmona
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK; UK Dementia Research Institute (UK DRI) at UCL, London, UK
| | - Nadia Dehghani
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK; UK Dementia Research Institute (UK DRI) at UCL, London, UK
| | - John D Eicher
- Genetics and Pharmacogenomics, Merck Research Laboratories, Boston, MA, USA
| | - Claire Shepherd
- Neuroscience Research Australia, Sydney, Australia and School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia
| | - Laura Parkkinen
- Nuffield Department of Clinical Neurosciences, Oxford Parkinsons Disease Centre, University of Oxford, Oxford, UK
| | - Lee Darwent
- UK Dementia Research Institute (UK DRI) at UCL, London, UK
| | - Michael G Heckman
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Jacksonville, FL, USA
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA; Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Juan C Troncoso
- Department of Pathology (Neuropathology), Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Olga Pletnikova
- Department of Pathology (Neuropathology), Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Ted Dawson
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Liana Rosenthal
- Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, Oxford Parkinsons Disease Centre, University of Oxford, Oxford, UK
| | - Jordi Clarimon
- Memory Unit, Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Alberto Lleo
- Memory Unit, Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Estrella Morenas-Rodriguez
- Memory Unit, Department of Neurology, IIB Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autonoma de Barcelona, Barcelona, Spain; Centro de Investigacion Biomedica en Red en Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Lorraine Clark
- Taub Institute for Alzheimer Disease and the Aging Brain, Department of Pathology and Cell Biology, Columbia University, New York, NY, USA
| | - Lawrence S Honig
- Taub Institute for Alzheimer Disease and the Aging Brain, Department of Pathology and Cell Biology, Columbia University, New York, NY, USA
| | - Karen Marder
- Taub Institute for Alzheimer Disease and the Aging Brain, Department of Pathology and Cell Biology, Columbia University, New York, NY, USA
| | - Afina Lemstra
- Department of Neurology and Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, the Netherlands
| | - Ekaterina Rogaeva
- Tanz Centre for Research in Neurodegenerative Diseases and department of Medicine, University of Toronto, Ontario, Canada
| | - Peter St George-Hyslop
- Tanz Centre for Research in Neurodegenerative Diseases and department of Medicine, University of Toronto, Ontario, Canada; Department of Clinical Neurosciences, Cambridge Institute for Medical Research, University of Cambridge, Cambridge, UK
| | - Elisabet Londos
- Clinical Memory Research Unit, Institution of Clinical Sciences Malmo, Lund University, Sweden
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, London UK, Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK, Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden
| | - Imelda Barber
- Human Genetics, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham, UK
| | - Anne Braae
- Human Genetics, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham, UK
| | - Kristelle Brown
- Human Genetics, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham, UK
| | - Kevin Morgan
- Human Genetics, School of Life Sciences, Queens Medical Centre, University of Nottingham, Nottingham, UK
| | - Claire Troakes
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Safa Al-Sarraj
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, Kings College London, London, UK
| | - Tammaryn Lashley
- Queen Square Brain Bank, Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Janice Holton
- Queen Square Brain Bank, Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Yaroslau Compta
- Queen Square Brain Bank, Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK; Queen Square Brain Bank, Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK, Movement Disorders Unit, Neurology Service, Clinical Neuroscience Institute (ICN), Hospital Clinic, University of Barcelona, IDIBAPS, Barcelona, Catalonia, Spain
| | - Vivianna Van Deerlin
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, 3600 Spruce Street, Philadelphia, USA
| | - Geidy E Serrano
- Banner Sun Health Research Institute, 10515 W Santa Fe Drive, Sun City, AZ 85351, USA
| | - Thomas G Beach
- Banner Sun Health Research Institute, 10515 W Santa Fe Drive, Sun City, AZ 85351, USA
| | - Suzanne Lesage
- Inserm U1127, CNRS UMR7225, Sorbonne Universites, UPMC Univ Paris 06, UMR and S1127, Institut du Cerveau et de la Moelle epiniere, Paris, France
| | - Douglas Galasko
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States, Veterans Affairs San Diego Healthcare System, La Jolla, CA, United States
| | - Eliezer Masliah
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States, Department of Pathology, University of California, San Diego, La Jolla, CA, United States
| | - Isabel Santana
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal; Faculty of Medicine and Centre for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Pau Pastor
- Memory Unit, Department of Neurology,University Hospital Mutua de Terrassa, University of Barcelona, Fundacion de Docencia I Recerca Mutua de Terrassa, Terrassa, Barcelona, Spain. Centro de Investigacion Biomedica en Red Enfermedades Neurdegenerativas (CIBERNED), Madrid, Spain
| | - Monica Diez-Fairen
- Memory Unit, Department of Neurology,University Hospital Mutua de Terrassa, University of Barcelona, Fundacion de Docencia I Recerca Mutua de Terrassa, Terrassa, Barcelona, Spain. Centro de Investigacion Biomedica en Red Enfermedades Neurdegenerativas (CIBERNED), Madrid, Spain
| | - Miquel Aguilar
- Memory Unit, Department of Neurology,University Hospital Mutua de Terrassa, University of Barcelona, Fundacion de Docencia I Recerca Mutua de Terrassa, Terrassa, Barcelona, Spain. Centro de Investigacion Biomedica en Red Enfermedades Neurdegenerativas (CIBERNED), Madrid, Spain
| | - Pentti J Tienari
- Molecular Neurology, Research Programs Unit, University of Helsinki, Department of Neurology, Helsinki University Hospital, Helsinki, Finland
| | - Liisa Myllykangas
- Department of Pathology, University of Helsinki, Helsinki University Hospital, Helsinki, Finland
| | - Minna Oinas
- Department of Neuropathology and Neurosurgery, Helsinki University Hospital, University of Helsinki, Helsinki, Finland
| | - Tamas Revesz
- Queen Square Brain Bank, Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Andrew Lees
- Queen Square Brain Bank, Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Brad F Boeve
- Neurology Department, Mayo Clinic, Rochester, MN, USA
| | | | - Tanis J Ferman
- Department of Psychiatry and Department of Psychology, Mayo Clinic, Jacksonville, FL, USA
| | | | - Nigel J Cairns
- Knight Alzheimers Disease Research Center, Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - John C Morris
- Knight Alzheimers Disease Research Center, Department of Neurology, Washington University School of Medicine, Saint Louis, MO, USA
| | - Stuart Pickering-Brown
- Institute of Brain, Behaviour and Mental Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - David Mann
- Institute of Brain, Behaviour and Mental Health, Faculty of Medical and Human Sciences, University of Manchester, Manchester, UK
| | - Glenda M Halliday
- Neuroscience Research Australia, Sydney, Australia and School of Medical Sciences, Faculty of Medicine, University of New South Wales, Sydney, Australia; Brain and Mind Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - John Hardy
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, Perelman School of Medicine at the University of Pennsylvania, 3600 Spruce Street, Philadelphia, USA
| | | | - Andrew Singleton
- Laboratory of Neurogenetics, National Institutes on Aging, NIH, Bethesda, MD, USA
| | - David J Stone
- Genetics and Pharmacogenomics, Merck Research Laboratories, West Point, PA, USA
| | - Jose Bras
- Department of Neurodegenerative Diseases, UCL Institute of Neurology, London, UK; UK Dementia Research Institute (UK DRI) at UCL, London, UK.
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