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Fu M, Valiente-Banuet L, Wadhwa SS, Pasaniuc B, Vossel K, Chang TS. Improving genetic risk modeling of dementia from real-world data in underrepresented populations. Commun Biol 2024; 7:1049. [PMID: 39183196 PMCID: PMC11345412 DOI: 10.1038/s42003-024-06742-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Accepted: 08/16/2024] [Indexed: 08/27/2024] Open
Abstract
Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. We employ an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compare this model with APOE and polygenic risk score models across genetic ancestry groups (Hispanic Latino American sample: 610 patients with 126 cases; African American sample: 440 patients with 84 cases; East Asian American sample: 673 patients with 75 cases), using electronic health records from UCLA Health for discovery and the All of Us cohort for validation. Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 31-84% (Wilcoxon signed-rank test p-value <0.05) and the area-under-the-receiver-operating characteristic by 11-17% (DeLong test p-value <0.05) compared to the APOE and the polygenic risk score models. We identify shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. Our study highlights the benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
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Affiliation(s)
- Mingzhou Fu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
- Medical Informatics Home Area, Department of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90024, USA
| | - Leopoldo Valiente-Banuet
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Satpal S Wadhwa
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Keith Vossel
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA
| | - Timothy S Chang
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
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Contador I, Buch-Vicente B, del Ser T, Llamas-Velasco S, Villarejo-Galende A, Benito-León J, Bermejo-Pareja F. Charting Alzheimer's Disease and Dementia: Epidemiological Insights, Risk Factors and Prevention Pathways. J Clin Med 2024; 13:4100. [PMID: 39064140 PMCID: PMC11278014 DOI: 10.3390/jcm13144100] [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: 05/23/2024] [Revised: 07/08/2024] [Accepted: 07/09/2024] [Indexed: 07/28/2024] Open
Abstract
Alzheimer's disease (AD), the most common cause of dementia, is a complex and multifactorial condition without cure at present. The latest treatments, based on anti-amyloid monoclonal antibodies, have only a modest effect in reducing the progression of cognitive decline in AD, whereas the possibility of preventing AD has become a crucial area of research. In fact, recent studies have observed a decrease in dementia incidence in developed regions such as the US and Europe. However, these trends have not been mirrored in non-Western countries (Japan or China), and the contributing factors of this reduction remain unclear. The Lancet Commission has delineated a constrained classification of 12 risk factors across different life stages. Nevertheless, the scientific literature has pointed to over 200 factors-including sociodemographic, medical, psychological, and sociocultural conditions-related to the development of dementia/AD. This narrative review aims to synthesize the risk/protective factors of dementia/AD. Essentially, we found that risk/protective factors vary between individuals and populations, complicating the creation of a unified prevention strategy. Moreover, dementia/AD explanatory mechanisms involve a diverse array of genetic and environmental factors that interact from the early stages of life. In the future, studies across different population-based cohorts are essential to validate risk/protective factors of dementia. This evidence would help develop public health policies to decrease the incidence of dementia.
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Affiliation(s)
- Israel Contador
- Department of Basic Psychology, Psychobiology, and Methodology of Behavioral Sciences, Faculty of Psychology, University of Salamanca, 37005 Salamanca, Spain
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, 17117 Stockholm, Sweden
| | - Bárbara Buch-Vicente
- Department of Basic Psychology, Psychobiology, and Methodology of Behavioral Sciences, Faculty of Psychology, University of Salamanca, 37005 Salamanca, Spain
| | - Teodoro del Ser
- Alzheimer Centre Reina Sofia—CIEN Foundation, Institute of Health Carlos III, 28031 Madrid, Spain;
| | - Sara Llamas-Velasco
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), 28041 Madrid, Spain; (S.L.-V.); (A.V.-G.); (J.B.-L.)
- Department of Neurology, University Hospital 12 de Octubre, 28041 Madrid, Spain
| | - Alberto Villarejo-Galende
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), 28041 Madrid, Spain; (S.L.-V.); (A.V.-G.); (J.B.-L.)
- Department of Neurology, University Hospital 12 de Octubre, 28041 Madrid, Spain
| | - Julián Benito-León
- Instituto de Investigación Sanitaria Hospital 12 de Octubre (imas12), 28041 Madrid, Spain; (S.L.-V.); (A.V.-G.); (J.B.-L.)
- Department of Neurology, University Hospital 12 de Octubre, 28041 Madrid, Spain
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Department of Medicine, Faculty of Medicine, Complutense University, 28040 Madrid, Spain
| | - Félix Bermejo-Pareja
- Centro de Investigación Biomédica en Red Sobre Enfermedades Neurodegenerativas (CIBERNED), 28029 Madrid, Spain
- Department of Medicine, Faculty of Medicine, Complutense University, 28040 Madrid, Spain
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Arrotta K, Ferguson L, Thompson N, Smuk V, Najm IM, Leu C, Lal D, Busch RM. Polygenic burden and its association with baseline cognitive function and postoperative cognitive outcome in temporal lobe epilepsy. Epilepsy Behav 2024; 153:109692. [PMID: 38394790 DOI: 10.1016/j.yebeh.2024.109692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 01/29/2024] [Accepted: 02/10/2024] [Indexed: 02/25/2024]
Abstract
OBJECTIVE Demographic and disease factors are associated with cognitive deficits and postoperative cognitive declines in adults with pharmacoresistant temporal lobe epilepsy (TLE), but the role of genetic factors in cognition in TLE is not well understood. Polygenic scores (PGS) for neurological and neuropsychiatric disorders and IQ have been associated with cognition in patient and healthy populations. In this exploratory study, we examined the relationship between PGS for Alzheimer's disease (AD), depression, and IQ and cognitive outcomes in adults with TLE. METHODS 202 adults with pharmacoresistant TLE had genotyping and completed neuropsychological evaluations as part of a presurgical work-up. A subset (n = 116) underwent temporal lobe resection and returned for postoperative cognitive testing. Logistic regression was used to determine if PGS for AD, depression, and IQ predicted baseline domain-specific cognitive function and cognitive phenotypes as well as postoperative language and memory decline. RESULTS No significant findings survived correction for multiple comparisons. Prior to correction, higher PGS for AD and depression (i.e., increased genetic risk for the disorder), but lower PGS for IQ (i.e., decreased genetic likelihood of high IQ) appeared possibly associated with baseline cognitive impairment in TLE. In comparison, higher PGS for AD and IQ appeared as possible risk factors for cognitive decline following temporal lobectomy, while the possible relationship between PGS for depression and post-operative cognitive outcome was mixed. SIGNIFICANCE We did not observe any relationships of large effect between PGS and cognitive function or postsurgical outcome; however, results highlight several promising trends in the data that warrant future investigation in larger samples better powered to detect small genetic effects.
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Affiliation(s)
- Kayela Arrotta
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA; Departments of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Lisa Ferguson
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Nicolas Thompson
- Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Victoria Smuk
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Imad M Najm
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA; Departments of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Costin Leu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA; Department of Clinical and Experimental Epilepsy, Institute of Neurology, University College London, London, UK.
| | - Dennis Lal
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA; Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and M.I.T., Cambridge, MA, USA.
| | - Robyn M Busch
- Epilepsy Center, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA; Departments of Neurology, Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
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Chang T, Fu M, Valiente-Banuet L, Wadhwa S, Pasaniuc B, Vossel K. Improving genetic risk modeling of dementia from real-world data in underrepresented populations. RESEARCH SQUARE 2024:rs.3.rs-3911508. [PMID: 38410460 PMCID: PMC10896371 DOI: 10.21203/rs.3.rs-3911508/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
BACKGROUND Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. METHODS We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation. RESULTS Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOEand the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. CONCLUSIONS Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
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Affiliation(s)
- Timothy Chang
- David Geffen School of Medicine, University of California, Los Angeles
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Fu M, Valiente-Banuet L, Wadhwa SS, Pasaniuc B, Vossel K, Chang TS. Improving genetic risk modeling of dementia from real-world data in underrepresented populations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.05.24302355. [PMID: 38370649 PMCID: PMC10871463 DOI: 10.1101/2024.02.05.24302355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
BACKGROUND Genetic risk modeling for dementia offers significant benefits, but studies based on real-world data, particularly for underrepresented populations, are limited. METHODS We employed an Elastic Net model for dementia risk prediction using single-nucleotide polymorphisms prioritized by functional genomic data from multiple neurodegenerative disease genome-wide association studies. We compared this model with APOE and polygenic risk score models across genetic ancestry groups, using electronic health records from UCLA Health for discovery and All of Us cohort for validation. RESULTS Our model significantly outperforms other models across multiple ancestries, improving the area-under-precision-recall curve by 21-61% and the area-under-the-receiver-operating characteristic by 10-21% compared to the APOE and the polygenic risk score models. We identified shared and ancestry-specific risk genes and biological pathways, reinforcing and adding to existing knowledge. CONCLUSIONS Our study highlights benefits of integrating functional mapping, multiple neurodegenerative diseases, and machine learning for genetic risk models in diverse populations. Our findings hold potential for refining precision medicine strategies in dementia diagnosis.
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Affiliation(s)
- Mingzhou Fu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
- Medical Informatics Home Area, Department of Bioinformatics, University of California, Los Angeles, Los Angeles, CA, 90024, United States
| | - Leopoldo Valiente-Banuet
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Satpal S. Wadhwa
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | | | | | - Bogdan Pasaniuc
- Department of Computational Medicine, David Geffen School of Medicine at UCLA, Los Angeles, CA, 90095, USA
| | - Keith Vossel
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
| | - Timothy S. Chang
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, 90095, United States
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Park DK, Chen M, Kim S, Joo YY, Loving RK, Kim HS, Cha J, Yoo S, Kim JH. Overestimated prediction using polygenic prediction derived from summary statistics. BMC Genom Data 2023; 24:52. [PMID: 37710206 PMCID: PMC10500750 DOI: 10.1186/s12863-023-01151-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Accepted: 08/16/2023] [Indexed: 09/16/2023] Open
Abstract
BACKGROUND When polygenic risk score (PRS) is derived from summary statistics, independence between discovery and test sets cannot be monitored. We compared two types of PRS studies derived from raw genetic data (denoted as rPRS) and the summary statistics for IGAP (sPRS). RESULTS Two variables with the high heritability in UK Biobank, hypertension, and height, are used to derive an exemplary scale effect of PRS. sPRS without APOE is derived from International Genomics of Alzheimer's Project (IGAP), which records ΔAUC and ΔR2 of 0.051 ± 0.013 and 0.063 ± 0.015 for Alzheimer's Disease Sequencing Project (ADSP) and 0.060 and 0.086 for Accelerating Medicine Partnership - Alzheimer's Disease (AMP-AD). On UK Biobank, rPRS performances for hypertension assuming a similar size of discovery and test sets are 0.0036 ± 0.0027 (ΔAUC) and 0.0032 ± 0.0028 (ΔR2). For height, ΔR2 is 0.029 ± 0.0037. CONCLUSION Considering the high heritability of hypertension and height of UK Biobank and sample size of UK Biobank, sPRS results from AD databases are inflated. Independence between discovery and test sets is a well-known basic requirement for PRS studies. However, a lot of PRS studies cannot follow such requirements because of impossible direct comparisons when using summary statistics. Thus, for sPRS, potential duplications should be carefully considered within the same ethnic group.
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Affiliation(s)
- David Keetae Park
- Department of Biomedical Engineering, Columbia University, New York, USA
| | - Mingshen Chen
- Department of Applied Mathematics & Statistics, Stony Brook University, New York, USA
| | - Seungsoo Kim
- Department of Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY, USA
| | - Yoonjung Yoonie Joo
- Samsung Advanced Institute for Health Sciences & Technology (SAHIST), Sungkyunkwan University, Samsung Medical Center, Seoul, South Korea
| | - Rebekah K Loving
- Department of Biology, California Institute of Technology, Pasadena, USA
| | - Hyoung Seop Kim
- Department of Physical Medicine and Rehabilitation, Dementia Center, National Health Insurance Service Ilsan Hospital, Goyang, South Korea
| | - Jiook Cha
- Department of Psychology, Brain and Cognitive Sciences, AI Institute, Seoul National University, Seoul, South Korea
| | - Shinjae Yoo
- Computational Science Initiative, Brookhaven National Lab. Computer Science and Math, Building 725, Room 2-189, Upton, NY, 11973, USA.
| | - Jong Hun Kim
- Department of Neurology, Dementia Center, National Health Insurance Service Ilsan Hospital, 100 Ilsan-ro Ilsandong-gu, Goyang, Gyeonggi-Do, 10444, South Korea.
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Juul Rasmussen I, Frikke-Schmidt R. Modifiable cardiovascular risk factors and genetics for targeted prevention of dementia. Eur Heart J 2023; 44:2526-2543. [PMID: 37224508 PMCID: PMC10481783 DOI: 10.1093/eurheartj/ehad293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 02/22/2023] [Accepted: 05/04/2023] [Indexed: 05/26/2023] Open
Abstract
Dementia is a major global challenge for health and social care in the 21st century. A third of individuals >65 years of age die with dementia, and worldwide incidence numbers are projected to be higher than 150 million by 2050. Dementia is, however, not an inevitable consequence of old age; 40% of dementia may theoretically be preventable. Alzheimer's disease (AD) accounts for approximately two-thirds of dementia cases and the major pathological hallmark of AD is accumulation of amyloid-β. Nevertheless, the exact pathological mechanisms of AD remain unknown. Cardiovascular disease and dementia share several risk factors and dementia often coexists with cerebrovascular disease. In a public health perspective, prevention is crucial, and it is suggested that a 10% reduction in prevalence of cardiovascular risk factors could prevent more than nine million dementia cases worldwide by 2050. Yet this assumes causality between cardiovascular risk factors and dementia and adherence to the interventions over decades for a large number of individuals. Using genome-wide association studies, the entire genome can be scanned for disease/trait associated loci in a hypothesis-free manner, and the compiled genetic information is not only useful for pinpointing novel pathogenic pathways but also for risk assessments. This enables identification of individuals at high risk, who likely will benefit the most from a targeted intervention. Further optimization of the risk stratification can be done by adding cardiovascular risk factors. Additional studies are, however, highly needed to elucidate dementia pathogenesis and potential shared causal risk factors between cardiovascular disease and dementia.
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Affiliation(s)
- Ida Juul Rasmussen
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
| | - Ruth Frikke-Schmidt
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Blegdamsvej 9, DK-2100 Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Shannon OM, Ranson JM, Gregory S, Macpherson H, Milte C, Lentjes M, Mulligan A, McEvoy C, Griffiths A, Matu J, Hill TR, Adamson A, Siervo M, Minihane AM, Muniz-Tererra G, Ritchie C, Mathers JC, Llewellyn DJ, Stevenson E. Mediterranean diet adherence is associated with lower dementia risk, independent of genetic predisposition: findings from the UK Biobank prospective cohort study. BMC Med 2023; 21:81. [PMID: 36915130 PMCID: PMC10012551 DOI: 10.1186/s12916-023-02772-3] [Citation(s) in RCA: 37] [Impact Index Per Article: 37.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 02/07/2023] [Indexed: 03/14/2023] Open
Abstract
BACKGROUND The identification of effective dementia prevention strategies is a major public health priority, due to the enormous and growing societal cost of this condition. Consumption of a Mediterranean diet (MedDiet) has been proposed to reduce dementia risk. However, current evidence is inconclusive and is typically derived from small cohorts with limited dementia cases. Additionally, few studies have explored the interaction between diet and genetic risk of dementia. METHODS We used Cox proportional hazard regression models to explore the associations between MedDiet adherence, defined using two different scores (Mediterranean Diet Adherence Screener [MEDAS] continuous and Mediterranean diet Pyramid [PYRAMID] scores), and incident all-cause dementia risk in 60,298 participants from UK Biobank, followed for an average 9.1 years. The interaction between diet and polygenic risk for dementia was also tested. RESULTS Higher MedDiet adherence was associated with lower dementia risk (MEDAS continuous: HR = 0.77, 95% CI = 0.65-0.91; PYRAMID: HR = 0.86, 95% CI = 0.73-1.02 for highest versus lowest tertiles). There was no significant interaction between MedDiet adherence defined by the MEDAS continuous and PYRAMID scores and polygenic risk for dementia. CONCLUSIONS Higher adherence to a MedDiet was associated with lower dementia risk, independent of genetic risk, underlining the importance of diet in dementia prevention interventions.
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Affiliation(s)
- Oliver M Shannon
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Janice M Ranson
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Sarah Gregory
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Helen Macpherson
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Catherine Milte
- Institute for Physical Activity and Nutrition, School of Exercise and Nutrition Sciences, Deakin University, Geelong, VIC, Australia
| | - Marleen Lentjes
- School of Medical Sciences, Örebro University, Örebro, Sweden
| | - Angela Mulligan
- Nutrition Measurement Platform, MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Claire McEvoy
- Centre for Public Health, The Institute for Global Food Security, Queen's University Belfast, Belfast, UK
| | | | - Jamie Matu
- School of Health, Leeds Beckett University, Leeds, UK
| | - Tom R Hill
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Ashley Adamson
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Mario Siervo
- School of Life Sciences, Queen's Medical Centre, The University of Nottingham Medical School, Nottingham, UK
| | - Anne Marie Minihane
- Nutrition and Preventive Medicine, Norwich Medical School, University of East Anglia, Norwich, UK.,Norwich Institute of Health Ageing (NIHA), Norwich, UK
| | - Graciela Muniz-Tererra
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Heritage College of Osteopathic Medicine, Ohio University, Athens, OH, USA
| | - Craig Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - John C Mathers
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK.
| | - David J Llewellyn
- College of Medicine and Health, University of Exeter, Exeter, UK.,Alan Turing Institute, London, UK
| | - Emma Stevenson
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Newcastle Upon Tyne, UK
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Chen Y, Zhang Y, Li S, Zhou L, Li H, Li D, Wang Y, Yang H. Cardiometabolic diseases, polygenic risk score, APOE genotype, and risk of incident dementia: A population-based prospective cohort study. Arch Gerontol Geriatr 2023; 105:104853. [PMID: 36347157 DOI: 10.1016/j.archger.2022.104853] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/07/2022]
Abstract
Objective We aimed to prospective investigate the association between cardiometabolic diseases (CMDs) with dementia, and to examine whether genetic factors and CMDs jointly contribute to the incidence of dementia. Methods We used data from the UK biobank of 204,646 adults aged 37-73 free of dementia at baseline. Genetic risk for dementia including APOE ε4 status and polygenic risk score (PRS) categorized as low, intermediate, and high. CMDs including ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D) were confirmed by touchscreen questionnaires, medical examinations, and hospital inpatient records. Results Over the follow-up (median: 12.5 years), 5,750 participants developed dementia. The HRs (95% CI) of those with APOE ε4 carriers and high PRS were 3.16 (3.00-3.33) and 1.50 (1.41-1.60), respectively. The risk of dementia was 70% higher among those with CMDs (HR: 1.70; 95% CI: 1.60-1.82). In joint effect analyses, compared to no CMDs and APOE ε4 non-carriers, the HRs (95% CIs) of dementia were 3.53 (3.31-3.76)/2.06 (1.89-2.23) in participants with only APOE ε4 carriers and CMDs, and 5.06 (4.64-5.53) for those with APOE ε4 carriers plus CMDs. Compared to no CMDs and low PRS, the HRs (95% CIs) of dementia were 1.29 (1.19-1.40)/1.60 (1.48-1.73) in participants with only intermediate and high PRS, and 2.00 (1.79-2.23)/2.63 (2.38-2.92) for those with intermediate, and high PRS plus CMDs. Moreover, there were significant additive and multiplication interactions between CMDs and APOE ε4 carriers of dementia, but only multiplication interaction was observed for PRS. Conclusions CMDs were associated with higher risk of dementia regardless of genetic risk for dementia.
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Affiliation(s)
- Yanchun Chen
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yuan Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shu Li
- School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lihui Zhou
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Huiping Li
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Dun Li
- The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China; The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
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Bonnechère B, Liu J, Thompson A, Amin N, van Duijn C. Does ethnicity influence dementia, stroke and mortality risk? Evidence from the UK Biobank. Front Public Health 2023; 11:1111321. [PMID: 37124771 PMCID: PMC10140594 DOI: 10.3389/fpubh.2023.1111321] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 03/10/2023] [Indexed: 05/02/2023] Open
Abstract
Introduction The number of people with dementia and stroke is increasing worldwide. There is increasing evidence that there are clinically relevant genetic differences across ethnicities. This study aims to quantify risk factors of dementia, stroke, and mortality in Asian and black participants compared to whites. Methods 272,660 participants from the UK Biobank were included in the final analysis, among whom the vast majority are white (n = 266,671, 97.80%), followed by Asian (n = 3,790, 1.35%), and black (n = 2,358, 0.84%) participants. Cumulative incidence risk was calculated based on all incident cases occurring during the follow-up of the individuals without dementia and stroke at baseline. We compared the allele frequency of variants in Asian and black participants with the referent ethnicity, whites, by chi-square test. Hierarchical cluster analysis was used in the clustering analysis. Significance level corrected for the false discovery rate was considered. Results After adjusting for risk factors, black participants have an increased risk of dementia and stroke compared to white participants, while Asians has similar odds to the white. The risk of mortality is not different in blacks and white participants but Asians have a decreased risk. Discussion The study provides important insights into the potential differences in the risk of dementia and stroke among different ethnic groups. Specifically, the study found that black individuals had a higher incidence of dementia and stroke compared to white individuals living in the UK. These findings are particularly significant as they suggest that there may be underlying factors that contribute to these differences, including genetic, environmental, and social factors. By identifying these differences, the study helps to inform interventions and policies aimed at reducing the risk of dementia and stroke, particularly among high-risk populations.
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Affiliation(s)
- Bruno Bonnechère
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- REVAL Rehabilitation Research Center, Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium
- Technology-Supported and Data-Driven Rehabilitation, Data Science Institute, Hasselt University, Diepenbeek, Belgium
| | - Jun Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Alexander Thompson
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Najaf Amin
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Cornelia van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
- *Correspondence: Cornelia van Duijn,
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11
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Beydoun MA, Weiss J, Banerjee S, Beydoun HA, Noren Hooten N, Evans MK, Zonderman AB. Race, polygenic risk and their association with incident dementia among older US adults. Brain Commun 2022; 4:fcac317. [PMID: 36569604 PMCID: PMC9772879 DOI: 10.1093/braincomms/fcac317] [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: 04/21/2022] [Revised: 09/26/2022] [Accepted: 11/29/2022] [Indexed: 12/02/2022] Open
Abstract
Dementia incidence increases steadily with age at rates that may vary across racial groups. This racial disparity may be attributable to polygenic risk, as well as lifestyle and behavioural factors. We examined whether Alzheimer's disease polygenic score and race predict Alzheimer's disease and other related dementia incidence differentially by sex and mediation through polygenic scores for other health and behavioural conditions. We used longitudinal data from the nationally representative Health and Retirement Study. We restricted participants to those with complete data on 31 polygenic scores, including Alzheimer's disease polygenic score (2006-2012). Among participants aged 55 years and older in 2008, we excluded those with any memory problems between 2006 and 2008 and included those with complete follow-up on incident Alzheimer's disease and all-cause dementia, between 2010 and 2018 (N = 9683), based on self- or proxy-diagnosis every 2 years (2010, 2012, 2014, 2016 and 2018). Cox proportional hazards and 4-way decomposition models were conducted. Analyses were also stratified by sex and by race. There were racial differences in all-cause dementia incidence (age and sex-adjusted model, per standard deviation: hazard ratio, HR = 1.34, 95% confidence interval, CI: 1.09-1.65, P = 0.007), partially driven by educational attainment and income. We also found independent associations of race (age and sex-adjusted model, African American versus White adults: HR = 2.07, 95% CI: 1.52-2.83, P < 0.001) and Alzheimer's disease polygenic score (age and sex-adjusted model, per SD: HR = 1.37, 95% CI: 1.00-1.87, P < 0.001) with Alzheimer's disease incidence, including sex differences whereby women had a stronger effect of Alzheimer's disease polygenic score on Alzheimer's disease incidence compared with men (P < 0.05 for sex by Alzheimer's disease polygenic score interaction) adjusting for race and other covariates. The total impact of Alzheimer's disease polygenic scores on Alzheimer's disease incidence was mostly direct, while the effect of race on all-cause dementia incidence was mediated through socio-economic, lifestyle and health-related factors. Finally, among the 30 polygenic scores we examined, the total effects on the pathway Alzheimer's disease polygenic score --> Other polygenic score --> Incident Alzheimer's or all-cause dementia, were statistically significant for all, driven primarily by the controlled direct effect (P< 0. 001). In conclusion, both race and Alzheimer's disease polygenic scores were associated independently with Alzheimer's disease and all-cause dementia incidence. Alzheimer's disease polygenic score was more strongly linked to incident Alzheimer's disease among women, while racial difference in all-cause dementia was explained by other factors including socio-economic status.
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Affiliation(s)
- May A Beydoun
- Correspondence to: May A. Beydoun, PhD NIH Biomedical Research Center National Institute on Aging, IRP 251 Bayview Blvd. Suite 100, Room #: 04B118, Baltimore, MD 21224, USA E-mail:
| | | | - Sri Banerjee
- College of Health Professions, School of Health Sciences, Walden University, Baltimore, MD 21202, USA
| | - Hind A Beydoun
- Department of Research Programs, Fort Belvoir Community Hospital, Fort Belvoir, VA 22060, USA
| | - Nicole Noren Hooten
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
| | - Alan B Zonderman
- Laboratory of Epidemiology and Population Sciences, NIA/NIH/IRP, Baltimore, MD 21224, USA
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12
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Mulugeta A, Navale SS, Lumsden AL, Llewellyn DJ, Hyppönen E. Healthy Lifestyle, Genetic Risk and Brain Health: A Gene-Environment Interaction Study in the UK Biobank. Nutrients 2022; 14:nu14193907. [PMID: 36235559 PMCID: PMC9570683 DOI: 10.3390/nu14193907] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/15/2022] [Accepted: 09/20/2022] [Indexed: 11/16/2022] Open
Abstract
Genetic susceptibility and lifestyle affect the risk of dementia but there is little direct evidence for their associations with preclinical changes in brain structure. We investigated the association of genetic dementia risk and healthy lifestyle with brain morphometry, and whether effects from elevated genetic risk are modified by lifestyle changes. We used prospective data from up to 25,894 UK Biobank participants (median follow-up of 8.8 years), and defined healthy lifestyle according to American Heart Association criteria as BMI < 30, no smoking, healthy diet and regular physical activity). Higher genetic risk was associated with lower hippocampal volume (beta −0.16 cm3, 95% CI −0.22, −0.11) and total brain volume (−4.34 cm3, 95% CI −7.68, −1.01) in participants aged ≥60 years but not <60 years. Healthy lifestyle was associated with higher total brain, grey matter and hippocampal volumes, and lower volume of white matter hyperintensities, with no effect modification by age or genetic risk. In conclusion, adverse effects of high genetic risk on brain health were only found in older participants, while adhering to healthy lifestyle recommendations is beneficial regardless of age or genetic risk.
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Affiliation(s)
- Anwar Mulugeta
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
- Department of Pharmacology and Clinical Pharmacy, College of Health Science, Addis Ababa University, Addis Ababa P.O. Box 9086, Ethiopia
| | - Shreeya S. Navale
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5001, Australia
| | - Amanda L. Lumsden
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
| | - David J. Llewellyn
- College of Medicine and Health, University of Exeter, Devon EX1 2LU, UK
- Alan Turing Institute, London NW1 2DB, UK
| | - Elina Hyppönen
- Australian Centre for Precision Health, Unit of Clinical and Health Sciences, University of South Australia, Adelaide, SA 5001, Australia
- South Australian Health and Medical Research Institute, Adelaide, SA 5000, Australia
- Correspondence: ; Tel.: +61-(08)-83022518
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13
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Tin A, Bressler J, Simino J, Sullivan KJ, Mei H, Windham BG, Griswold M, Gottesman RF, Boerwinkle E, Fornage M, Mosley TH. Genetic Risk, Midlife Life's Simple 7, and Incident Dementia in the Atherosclerosis Risk in Communities Study. Neurology 2022; 99:e154-e163. [PMID: 35613930 PMCID: PMC9280991 DOI: 10.1212/wnl.0000000000200520] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 02/28/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Higher scores in Life's Simple 7 (LS7), a metric for cardiovascular and brain health, have been associated with lower risk of dementia. It is uncertain whether this association holds among those with high genetic risk of dementia. Our objective is to evaluate the extent that LS7 may offset dementia risk across the range of genetic risk. METHODS Participants in the Atherosclerosis Risk in Communities (ARIC) Study were followed from 1987-1989 to 2019. We derived midlife LS7 scores and generated genetic risk scores (GRS) using genome-wide summary statistics of Alzheimer disease, which have been used to study the genetic risk for dementia. Incident dementia was ascertained based on the criteria of the National Institute on Aging-Alzheimer's Association workgroups and Diagnostic and Statistical Manual of Mental Disorders. The associations of the GRS and LS7 with incident dementia were evaluated using Cox regression. RESULTS This study included 8,823 European American (EA) and 2,738 African American (AA) participants (mean age at baseline 54 years). We observed 1,603 cases of dementia among EA participants and 631 among AA participants (median follow-up 26.2 years). Higher GRS were associated with higher risk of dementia (EA, hazard ratio [HR] per SD 1.44, 95% CI 1.37, 1.51; AA, HR 1.26, 95% CI 1.16, 1.36). Among EA participants, higher LS7 scores were consistently associated with lower risk of dementia across quintiles of GRS, including the highest quintile (HR per point 0.91, 95% CI 0.87, 0.96). Among AA participants, the associations between LS7 and incident dementia within stratum of GRS had the same direction as among EA participants, although wide CIs and smaller sample sizes limited reliable inferences. DISCUSSION Across strata of GRS, higher midlife LS7 scores were associated with lower risk of dementia. Larger sample sizes from diverse populations are needed to obtain more reliable estimates of the effects of modifiable health factors on dementia risk within genetic risk strata in each ancestry group.
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Affiliation(s)
- Adrienne Tin
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD.
| | - Jan Bressler
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Jeannette Simino
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Kevin J Sullivan
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Hao Mei
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - B Gwen Windham
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Michael Griswold
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Rebecca F Gottesman
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Eric Boerwinkle
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Myriam Fornage
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
| | - Thomas H Mosley
- From the Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine (A.T., K.J.S., B.G.W., M.G., T.H.M.) and Department of Data Science (J.S., H.M.), University of Mississippi Medical Center, Jackson; Department of Epidemiology (A.T.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Human Genetics Center, School of Public Health (J.B., E.B., M.F.), and Institute of Molecular Medicine, McGovern Medical School (M.F.), University of Texas Health Science Center at Houston; and Stroke Branch (R.F.G.), National Institute of Neurological Disorders and Stroke Intramural Program, National Institutes of Health, Bethesda, MD
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14
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Tai XY, Veldsman M, Lyall DM, Littlejohns TJ, Langa KM, Husain M, Ranson J, Llewellyn DJ. Cardiometabolic multimorbidity, genetic risk, and dementia: a prospective cohort study. THE LANCET. HEALTHY LONGEVITY 2022; 3:e428-e436. [PMID: 35711612 PMCID: PMC9184258 DOI: 10.1016/s2666-7568(22)00117-9] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
Background Individual cardiometabolic disorders and genetic factors are associated with an increased dementia risk; however, the relationship between dementia and cardiometabolic multimorbidity is unclear. We investigated whether cardiometabolic multimorbidity increases the risk of dementia, regardless of genetic risk, and examined for associated brain structural changes. Methods We examined health and genetic data from 203 038 UK Biobank participants of European ancestry, aged 60 years or older without dementia at baseline assessment (2006-10) and followed up until March 31, 2021, in England and Scotland and Feb 28, 2018, in Wales, as well as brain structural data in a nested imaging subsample of 12 236 participants. A cardiometabolic multimorbidity index comprising stroke, diabetes, and myocardial infarction (one point for each), and a polygenic risk score for dementia (with low, intermediate, and high risk groups) were calculated for each participant. The main outcome measures were incident all-cause dementia and brain structural metrics. Findings The dementia risk associated with high cardiometabolic multimorbidity was three times greater than that associated with high genetic risk (hazard ratio [HR] 5·55, 95% CI 3·39-9·08, p<0·0001, and 1·68, 1·53-1·84, p<0·0001, respectively). Participants with both a high genetic risk and a cardiometabolic multimorbidity index of two or greater had an increased risk of developing dementia (HR 5·74, 95% CI 4·26-7·74, p<0·0001), compared with those with a low genetic risk and no cardiometabolic conditions. Crucially, we found no interaction between cardiometabolic multimorbidity and polygenic risk (p=0·18). Cardiometabolic multimorbidity was independently associated with more extensive, widespread brain structural changes including lower hippocampal volume (F2, 12 110 = 10·70; p<0·0001) and total grey matter volume (F2, 12 236 = 55·65; p<0·0001). Interpretation Cardiometabolic multimorbidity was independently associated with the risk of dementia and extensive brain imaging differences to a greater extent than was genetic risk. Targeting cardiometabolic multimorbidity might help to reduce the risk of dementia, regardless of genetic risk. Funding Wellcome Trust, Alzheimer's Research UK, Alan Turing Institute/Engineering and Physical Sciences Research Council, the National Institute for Health Research Applied Research Collaboration South West Peninsula, National Health and Medical Research Council, JP Moulton Foundation, and National Institute on Aging/National Institutes of Health.
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Affiliation(s)
- Xin You Tai
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Division of Clinical Neurology, John Radcliffe Hospital, Oxford University Hospitals Trust, Oxford, UK
| | - Michele Veldsman
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Donald M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | | | - Kenneth M Langa
- Department of Internal Medicine, School of Medicine, University of Michigan, Ann Arbor, MI, USA
- Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
- Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA
- Veterans Affairs Ann Arbor Center for Clinical Management Research, Ann Arbor, MI, USA
| | - Masud Husain
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Department of Experimental Psychology, University of Oxford, Oxford, UK
- Division of Clinical Neurology, John Radcliffe Hospital, Oxford University Hospitals Trust, Oxford, UK
| | - Janice Ranson
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - David J Llewellyn
- College of Medicine and Health, University of Exeter, Exeter, UK
- Alan Turing Institute, London, UK
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15
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Genetic risk scores and dementia risk across different ethnic groups in UK Biobank. PLoS One 2022; 17:e0277378. [PMID: 36477264 PMCID: PMC9728885 DOI: 10.1371/journal.pone.0277378] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 10/26/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Genetic Risk Scores (GRS) for predicting dementia risk have mostly been used in people of European ancestry with limited testing in other ancestry groups. METHODS We conducted a logistic regression with all-cause dementia as the outcome and z-standardised GRS as the exposure across diverse ethnic groups. FINDINGS There was variation in frequency of APOE alleles across ethnic groups. Per standard deviation (SD) increase in z-GRS including APOE, the odds ratio (OR) for dementia was 1.73 (95%CI 1.69-1.77). Z-GRS excluding APOE also increased dementia risk (OR 1.21 per SD increase, 95% CI 1.18-1.24) and there was no evidence that ethnicity modified this association. Prediction of secondary outcomes was less robust in those not of European ancestry when APOE was excluded from the GRS. INTERPRETATION z-GRS derived from studies in people of European ancestry can be used to quantify genetic risk in people from more diverse ancestry groups. Urgent work is needed to include people from diverse ancestries in future genetic risk studies to make this field more inclusive.
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16
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Rubin L, Ingram LA, Resciniti NV, Ashford-Carroll B, Leith KH, Rose A, Ureña S, McCollum Q, Friedman DB. Genetic Risk Factors for Alzheimer's Disease in Racial/Ethnic Minority Populations in the U.S.: A Scoping Review. Front Public Health 2021; 9:784958. [PMID: 35004586 PMCID: PMC8739784 DOI: 10.3389/fpubh.2021.784958] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 11/23/2021] [Indexed: 11/13/2022] Open
Abstract
Objectives: As the United States (U.S.) population rapidly ages, the incidence of Alzheimer's Disease and Related Dementias (ADRDs) is rising, with racial/ethnic minorities affected at disproportionate rates. Much research has been undertaken to test, sequence, and analyze genetic risk factors for ADRDs in Caucasian populations, but comparatively little has been done with racial/ethnic minority populations. We conducted a scoping review to examine the nature and extent of the research that has been published about the genetic factors of ADRDs among racial/ethnic minorities in the U.S. Design: Using an established scoping review methodological framework, we searched electronic databases for articles describing peer-reviewed empirical studies or Genome-Wide Association Studies that had been published 2005-2018 and focused on ADRD-related genes or genetic factors among underrepresented racial/ethnic minority population in the U.S. Results: Sixty-six articles met the inclusion criteria for full text review. Well-established ADRD genetic risk factors for Caucasian populations including APOE, APP, PSEN1, and PSEN2 have not been studied to the same degree in minority U.S. populations. Compared to the amount of research that has been conducted with Caucasian populations in the U.S., racial/ethnic minority communities are underrepresented. Conclusion: Given the projected growth of the aging population and incidence of ADRDs, particularly among racial/ethnic minorities, increased focus on this important segment of the population is warranted. Our review can aid researchers in developing fundamental research questions to determine the role that ADRD risk genes play in the heavier burden of ADRDs in racial/ethnic minority populations.
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Affiliation(s)
- Lindsey Rubin
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Lucy A. Ingram
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Nicholas V. Resciniti
- Department of Epidemiology and Biostatistics, University of South Carolina, Columbia, SC, United States
| | - Brianna Ashford-Carroll
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Katherine Henrietta Leith
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Aubrey Rose
- School of Medicine, University of South Carolina, Columbia, SC, United States
| | - Stephanie Ureña
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
| | - Quentin McCollum
- College of Social Work, University of South Carolina, Columbia, SC, United States
| | - Daniela B. Friedman
- Department of Health Promotion, Education, and Behavior, University of South Carolina, Columbia, SC, United States
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17
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Weiss J. Contribution of socioeconomic, lifestyle, and medical risk factors to disparities in dementia and mortality. SSM Popul Health 2021; 16:100979. [PMID: 34977324 PMCID: PMC8683757 DOI: 10.1016/j.ssmph.2021.100979] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Revised: 11/18/2021] [Accepted: 11/22/2021] [Indexed: 11/30/2022] Open
Abstract
Extensive literature in the United States documents racial/ethnic and gender disparities in the incidence and prevalence of dementia yet few studies have examined how race/ethnicity and gender intersect to shape inequalities in the risk of dementia. Moreover, few studies have examined heterogeneity in the contribution of known risk factors to dementia across these demographic strata while properly accounting for the semi-competing risk of death. I calculated the proportion of dementia cases attributable to socioeconomic, lifestyle, and medical risk factors across demographic subgroups using nationally representative data from the US-based Health and Retirement Study for the years 2000-2016 and a multistate framework that accounts for the semi-competing risk of death. Socioeconomic resources contributed to the largest number of dementia cases but the magnitude of this contribution varied across strata defined by race/ethnicity and gender. The greatest potential for dementia prevention was observed among non-Hispanic black and Hispanic men and women, supporting an intersectionality approach, and underscoring the need for culturally sensitive intervention and public health initiatives to address the growing burden of dementia. Taken together, work demonstrates the potential benefit of taking an intersectional approach to understanding disparities in dementia.
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Affiliation(s)
- Jordan Weiss
- University of California, 2232 Piedmont Avenue, Berkeley, CA, 94720, USA
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18
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Brenowitz WD, Zimmerman SC, Filshtein TJ, Yaffe K, Walter S, Hoffmann TJ, Jorgenson E, Whitmer RA, Glymour MM. Extension of Mendelian Randomization to Identify Earliest Manifestations of Alzheimer Disease: Association of Genetic Risk Score for Alzheimer Disease With Lower Body Mass Index by Age 50 Years. Am J Epidemiol 2021; 190:2163-2171. [PMID: 33843952 DOI: 10.1093/aje/kwab103] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 04/06/2021] [Accepted: 04/07/2021] [Indexed: 01/08/2023] Open
Abstract
Weight loss or lower body mass index (BMI) could be an early symptom of Alzheimer disease (AD), but when this begins to emerge is difficult to estimate with traditional observational data. In an extension of Mendelian randomization, we leveraged variation in genetic risk for late-onset AD risk to estimate the causal effect of AD on BMI and the earliest ages at which AD-related weight loss (or lower BMI as a proxy) occurs. We studied UK Biobank participants enrolled in 2006-2010, who were without dementia, aged 39-73, with European genetic ancestry. BMI was calculated with measured height/weight (weight (kg)/height (m)2). An AD genetic risk score (AD-GRS) was calculated based on 23 genetic variants. Using linear regressions, we tested the association of AD-GRS with BMI, stratified by decade, and calculated the age of divergence in BMI trends between low and high AD-GRS. AD-GRS was not associated with BMI in 39- to 49-year-olds (β = 0.00, 95% confidence interval (CI): -0.03, 0.03). AD-GRS was associated with lower BMI in 50- to 59-year-olds (β = -0.03, 95% CI: -0.06, -0.01) and 60- to 73-year-olds (β = -0.09, 95% CI:-0.12, -0.07). Model-based BMI age curves for high versus low AD-GRS began to diverge after age 47 years. Sensitivity analyses found no evidence for pleiotropy or survival bias. Longitudinal replication is needed; however, our findings suggest that AD genes might begin to reduce BMI decades prior to dementia diagnosis.
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Systematic Search for Novel Circulating Biomarkers Associated with Extracellular Vesicles in Alzheimer's Disease: Combining Literature Screening and Database Mining Approaches. J Pers Med 2021; 11:jpm11100946. [PMID: 34683087 PMCID: PMC8538213 DOI: 10.3390/jpm11100946] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 09/13/2021] [Accepted: 09/19/2021] [Indexed: 12/12/2022] Open
Abstract
miRNAs play an important role in neurodegenerative diseases. Many miRNA-target gene interactions (MTI) have been experimentally confirmed and associated with Alzheimer’s disease (AD). miRNAs may also be contained within extracellular vesicles (EVs), mediators of cellular communication and a potential source of circulating biomarkers in body fluids. Therefore, EV-associated miRNAs (EV-miRNAs) in peripheral blood could support earlier and less invasive AD diagnostics. We aimed to prioritize EV-related miRNA with AD-related genes and to identify the most promising candidates for novel AD biomarkers. A list of unique EV-miRNAs from the literature was combined with a known set of AD risk genes and enriched for MTI. Additionally, miRNAs associated with the AD phenotype were combined with all known target genes in MTI enrichment. Expression in different sample types was analyzed to identify AD-associated miRNAs with the greatest potential as AD circulating biomarkers. Four common MTI were observed between EV-miRNAs and AD-associated miRNAs: hsa-miR-375–APH1B, hsa-miR-107–CDC42SE2, hsa-miR-375–CELF2, and hsa-miR-107–IL6. An additional 61 out of 169 unique miRNAs (36.1%) and seven out of 84 unique MTI (8.3%), observed in the body fluids of AD patients, were proposed as very strong AD-circulating biomarker candidates. Our analysis summarized several potential novel AD biomarkers, but further studies are needed to evaluate their potential in clinical practice.
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Zhou X, Li YYT, Fu AKY, Ip NY. Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications. Front Neurosci 2021; 15:650220. [PMID: 33854414 PMCID: PMC8039467 DOI: 10.3389/fnins.2021.650220] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 03/09/2021] [Indexed: 12/13/2022] Open
Abstract
The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.
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Affiliation(s)
- Xiaopu Zhou
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, 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, China
| | - Yolanda Y. T. Li
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, Hong Kong, China
| | - Amy K. Y. Fu
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, 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, China
| | - Nancy Y. Ip
- Division of Life Science, State Key Laboratory of Molecular Neuroscience and Molecular Neuroscience Center, The Hong Kong University of Science and Technology, 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, China
- *Correspondence: Nancy Y. Ip,
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21
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Brenowitz WD, Filshtein TJ, Yaffe K, Walter S, Ackley SF, Hoffmann TJ, Jorgenson E, Whitmer RA, Glymour MM. Association of genetic risk for Alzheimer disease and hearing impairment. Neurology 2020; 95:e2225-e2234. [PMID: 32878991 PMCID: PMC7713783 DOI: 10.1212/wnl.0000000000010709] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2019] [Accepted: 05/12/2020] [Indexed: 01/09/2023] Open
Abstract
OBJECTIVE To test the hypothesis that incipient Alzheimer disease (AD) may adversely affect hearing and that hearing loss may adversely affect cognition, we evaluated whether genetic variants that increase AD risk also increase problem hearing and genetic variants that increase hearing impairment risk do not influence cognition. METHODS UK Biobank participants without dementia ≥56 years of age with Caucasian genetic ancestry completed a Digit Triplets Test of speech-in-noise hearing (n = 80,074), self-reported problem hearing and hearing with background noise (n = 244,915), and completed brief cognitive assessments. A genetic risk score for AD (AD-GRS) was calculated as a weighted sum of 23 previously identified AD-related polymorphisms. A genetic risk score for hearing (hearing-GRS) was calculated using 3 previously identified polymorphisms related to hearing impairment. Using age-, sex-, and genetic ancestry-adjusted logistic and linear regression models, we evaluated whether the AD-GRS predicted poor hearing and whether the hearing-GRS predicted worse cognition. RESULTS Poor speech-in-noise hearing (>-5.5-dB speech reception threshold; prevalence 14%) was associated with lower cognitive scores (ß = -1.28; 95% confidence interval [CI] -1.54 to -1.03). Higher AD-GRS was significantly associated with poor speech-in-noise hearing (odds ratio [OR] 1.06; 95% CI 1.01-1.11) and self-reported problems hearing with background noise (OR 1.03; 95% CI 1.00-1.05). Hearing-GRS was not significantly associated with cognitive scores (ß = -0.05; 95% CI -0.17 to 0.07). CONCLUSIONS Genetic risk for AD also influences speech-in-noise hearing. We failed to find evidence that genetic risk for hearing impairment affects cognition. AD disease processes or a that shared etiology may cause speech-in-noise difficulty before dementia onset.
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Affiliation(s)
- Willa D Brenowitz
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA.
| | - Teresa J Filshtein
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Kristine Yaffe
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Stefan Walter
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Sarah F Ackley
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Thomas J Hoffmann
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Eric Jorgenson
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - Rachel A Whitmer
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
| | - M Maria Glymour
- From the Department of Psychiatry and Behavioral Sciences (W.D.B., K.Y.), Department of Epidemiology and Biostatistics (K.Y., S.F.A., T.J.H., M.M.G.), Department of Neurology (K.Y.), and Institute for Human Genetics (T.J.H.), University of California, San Francisco; 23andMe (T.J.F.), Mountain View; San Francisco VA Health Care System (K.Y.), CA; Department of Medicine and Public Health (S.W.), Rey Juan Carlos University, Madrid, Spain; Kaiser Permanente Northern California Division of Research (E.J.), Oakland; and Public Health Sciences (R.A.W.), Division of Epidemiology, Alzheimer's Disease Research Center, UC Davis School of Medicine, CA
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22
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Karunamuni RA, Huynh-Le MP, Fan CC, Eeles RA, Easton DF, Kote-Jarai ZS, Amin Al Olama A, Benlloch Garcia S, Muir K, Gronberg H, Wiklund F, Aly M, Schleutker J, Sipeky C, Tammela TLJ, Nordestgaard BG, Key TJ, Travis RC, Neal DE, Donovan JL, Hamdy FC, Pharoah P, Pashayan N, Khaw KT, Thibodeau SN, McDonnell SK, Schaid DJ, Maier C, Vogel W, Luedeke M, Herkommer K, Kibel AS, Cybulski C, Wokolorczyk D, Kluzniak W, Cannon-Albright L, Brenner H, Schöttker B, Holleczek B, Park JY, Sellers TA, Lin HY, Slavov C, Kaneva R, Mitev V, Batra J, Clements JA, Spurdle A, Teixeira MR, Paulo P, Maia S, Pandha H, Michael A, Mills IG, Andreassen OA, Dale AM, Seibert TM. The effect of sample size on polygenic hazard models for prostate cancer. Eur J Hum Genet 2020; 28:1467-1475. [PMID: 32514134 PMCID: PMC7608255 DOI: 10.1038/s41431-020-0664-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Revised: 02/27/2020] [Accepted: 05/22/2020] [Indexed: 11/12/2022] Open
Abstract
We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.
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Affiliation(s)
- Roshan A Karunamuni
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
| | - Minh-Phuong Huynh-Le
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA
| | - Chun C Fan
- Healthlytix, 4747 Executive Dr. Suite 820, San Diego, CA, USA
| | - Rosalind A Eeles
- The Institute of Cancer Research, London, SM2 5NG, UK
- Royal Marsden NHS Foundation Trust, London, SW3 6JJ, UK
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, University of Cambridge, Cambridge, CB1 8RN, UK
| | | | - Ali Amin Al Olama
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, University of Cambridge, Cambridge, CB1 8RN, UK
- Department of Clinical Neurosciences, Stroke Research Group, R3, Box 83, Cambridge Biomedical Campus, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Sara Benlloch Garcia
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, Strangeways Research Laboratory, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, University of Manchester, Oxford Road, Manchester, M13 9PL, UK
- Warwick Medical School, University of Warwick, Coventry, UK
| | - Henrik Gronberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden
| | - Markus Aly
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, SE-171 77, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institute, SE-171 77, Stockholm, Sweden
- Department of Urology, Karolinska University Hospital, Stockholm, Sweden
| | - Johanna Schleutker
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20014, Turku, Finland
- Department of Medical Genetics, Genomics, Laboratory Division, Turku University Hospital, PO Box 52, 20521, Turku, Finland
| | - Csilla Sipeky
- Institute of Biomedicine, University of Turku, Kiinamyllynkatu 10, FI-20014, Turku, Finland
| | - Teuvo L J Tammela
- Faculty of Medicine and Health Technology, Prostate Cancer Research Center, Tampere University, FI-33014, Tampere, Finland
- Department of Urology, Tampere University Hospital, Tampere, Finland
| | - Børge G Nordestgaard
- Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, 2200, Copenhagen, Denmark
| | - Tim J Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - David E Neal
- Nuffield Department of Surgical Sciences, University of Oxford, Room 6603, Level 6, John Radcliffe Hospital, Headley Way, Headington, Oxford, OX3 9DU, UK
- Department of Oncology, Box 279, Addenbrooke's Hospital, University of Cambridge, Hills Road, Cambridge, CB2 0QQ, UK
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
| | - Jenny L Donovan
- School of Social and Community Medicine, University of Bristol, Canynge Hall, 39 Whatley Road, Bristol, BS8 2PS, UK
| | - Freddie C Hamdy
- Nuffield Department of Surgical Sciences, University of Oxford, Oxford, OX1 2JD, UK
- Faculty of Medical Science, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Paul Pharoah
- Department of Oncology, Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN, UK
| | - Nora Pashayan
- Department of Oncology, Centre for Cancer Genetic Epidemiology, Strangeways Laboratory, University of Cambridge, Worts Causeway, Cambridge, CB1 8RN, UK
- Department of Applied Health Research, University College London, London, UK
- Department of Applied Health Research, University College London, London, WC1E 7HB, UK
| | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, CB2 2QQ, UK
| | - Stephen N Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Shannon K McDonnell
- Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, 55905, USA
| | - Daniel J Schaid
- Division of Biomedical Statistics & Informatics, Mayo Clinic, Rochester, MN, 55905, USA
| | - Christiane Maier
- Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany
| | - Walther Vogel
- Institute for Human Genetics, University Hospital Ulm, 89075, Ulm, Germany
| | - Manuel Luedeke
- Humangenetik Tuebingen, Paul-Ehrlich-Str 23, D-72076, Tuebingen, Germany
| | - Kathleen Herkommer
- Department of Urology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, München, Germany
| | - Adam S Kibel
- Division of Urologic Surgery, Brigham and Womens Hospital, 75 Francis Street, Boston, MA, 02115, USA
| | - Cezary Cybulski
- Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, 70-115, Szczecin, Poland
| | - Dominika Wokolorczyk
- Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, 70-115, Szczecin, Poland
| | - Wojciech Kluzniak
- Department of Genetics and Pathology, International Hereditary Cancer Center, Pomeranian Medical University, 70-115, Szczecin, Poland
| | - Lisa Cannon-Albright
- Division of Genetic Epidemiology, Department of Medicine, University of Utah School of Medicine, Salt Lake City, UT, 84112, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, 84148, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Im Neuenheimer Feld 460, 69120, Heidelberg, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), D-69120, Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Bernd Holleczek
- Saarland Cancer Registry, D-66119, Saarbrücken, Germany
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jong Y Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL, 33612, USA
| | - Thomas A Sellers
- Department of Cancer Epidemiology, Moffitt Cancer Center, 12902 Magnolia Drive, Tampa, FL, 33612, USA
| | - Hui-Yi Lin
- School of Public Health, Louisiana State University Health Sciences Center, New Orleans, LA, 70112, USA
| | - Chavdar Slavov
- Department of Urology and Alexandrovska University Hospital, Medical University of Sofia, 1431, Sofia, Bulgaria
| | - Radka Kaneva
- Department of Medical Chemistry and Biochemistry, Molecular Medicine Center, Medical University of Sofia, Sofia, 2 Zdrave Str., 1431, Sofia, Bulgaria
| | - Vanio Mitev
- Department of Medical Chemistry and Biochemistry, Molecular Medicine Center, Medical University of Sofia, Sofia, 2 Zdrave Str., 1431, Sofia, Bulgaria
| | - Jyotsna Batra
- Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, 4059, Australia
- Australian Prostate Cancer Research Centre-Qld, Translational Research Institute, Brisbane, QLD, 4102, Australia
| | - Judith A Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Science, Queensland University of Technology, Brisbane, QLD, 4059, Australia
- Translational Research Institute, Brisbane, QLD, 4102, Australia
| | - Amanda Spurdle
- Molecular Cancer Epidemiology Laboratory, QIMR Berghofer Institute of Medical Research, Brisbane, Australia
| | - Manuel R Teixeira
- Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto), 4200-072, Porto, Portugal
- Biomedical Sciences Institute (ICBAS), University of Porto, 4050-313, Porto, Portugal
| | - Paula Paulo
- Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto), 4200-072, Porto, Portugal
- Cancer Genetics Group, IPO-Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO-Porto), Porto, Portugal
| | - Sofia Maia
- Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto), 4200-072, Porto, Portugal
- Cancer Genetics Group, IPO-Porto Research Center (CI-IPOP), Portuguese Oncology Institute of Porto (IPO-Porto), Porto, Portugal
| | - Hardev Pandha
- The University of Surrey, Guildford, Surrey, GU2 7XH, UK
| | | | - Ian G Mills
- Center for Cancer Research and Cell Biology, Queen's University of Belfast, Belfast, UK
- Nuffield Department of Surgical Sciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Ole A Andreassen
- NORMENT, KG Jebsen Centre, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Anders M Dale
- Department of Radiology, University of California San Diego, La Jolla, CA, USA
- Department of Cognitive Science, University of California San Diego, La Jolla, CA, USA
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Tyler M Seibert
- Department of Radiation Medicine and Applied Sciences, University of California San Diego, La Jolla, CA, USA.
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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23
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Armstrong NM, Dumitrescu L, Huang CW, An Y, Tanaka T, Hernandez D, Doshi J, Erus G, Davatzikos C, Ferrucci L, Resnick SM, Hohman TJ. Association of hippocampal volume polygenic predictor score with baseline and change in brain volumes and cognition among cognitively healthy older adults. Neurobiol Aging 2020; 94:81-88. [PMID: 32593031 PMCID: PMC8893954 DOI: 10.1016/j.neurobiolaging.2020.05.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 04/28/2020] [Accepted: 05/10/2020] [Indexed: 11/20/2022]
Abstract
A high hippocampal volume polygenic predictor score (HV-PPS), computed based on GWAS summary statistics (n = 33,536), could be protective against declines in brain volume and cognition in older adults. Linear mixed-effects models with random intercepts and slopes were used to estimate associations of HV-PPS with baseline and annual rate of change in both brain volumes (n = 508) and cognitive performance (n = 1041) in Caucasian Baltimore Longitudinal Study of Aging participants. Higher HV-PPS was associated with greater baseline volumes of the hippocampus and parahippocampal gyrus, and slower rates of ventricular enlargement and volume loss in frontal and parietal white matter, all adjusted for intracranial volume. In addition, higher HV-PPS was associated with better executive function performance and slower rates of decline in verbal fluency scores over time. Individuals with a genetic predisposition toward larger hippocampal volumes show better baseline executive function, slower decline in verbal fluency performance, and slower rates of longitudinal brain atrophy.
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Affiliation(s)
- Nicole M Armstrong
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Chiung-Wei Huang
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA; Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Yang An
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Toshiko Tanaka
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Dena Hernandez
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Jimit Doshi
- Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Guray Erus
- Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Davatzikos
- Department of Radiology, Section of Biomedical Image Analysis, University of Pennsylvania, Philadelphia, PA, USA
| | - Luigi Ferrucci
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA
| | - Susan M Resnick
- National Institute on Aging Intramural Research Program, National Institutes of Health, Baltimore, MD, USA.
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
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Lyngstad SH, Bettella F, Aminoff SR, Athanasiu L, Andreassen OA, Faerden A, Melle I. Associations between schizophrenia polygenic risk and apathy in schizophrenia spectrum disorders and healthy controls. Acta Psychiatr Scand 2020; 141:452-464. [PMID: 32091622 DOI: 10.1111/acps.13167] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/16/2020] [Indexed: 10/24/2022]
Abstract
OBJECTIVE Apathy is a central predictor of a poor functional outcome in schizophrenia. Schizophrenia polygenic risk scores (PRSs) are used to detect genetic associations to key clinical phenotypes in schizophrenia. We explored the associations between schizophrenia PRS and apathy levels in schizophrenia spectrum disorders (n = 281) and matched healthy controls (n = 298), and further how schizophrenia PRS contributed in predicting apathy when added to premorbid and clinical factors in the patient sample. METHOD Schizophrenia PRSs were computed for each participant. Apathy was assessed with the Apathy Evaluation Scale. Bivariate correlation analyses were used to investigate associations between schizophrenia PRS and apathy, and between apathy and premorbid and clinical factors. Multiple hierarchical regression analyses were employed to evaluate the contributions of clinical variables and schizophrenia PRS to apathy levels. RESULTS We found no significant associations between schizophrenia PRS and apathy in patients and healthy controls. Several premorbid and clinical characteristics significantly predicted apathy in patients, but schizophrenia PRS did not. CONCLUSION Since the PRSs are based on common genetic variants, our results do not preclude associations to other types of genetic factors. The results could also indicate that environmentally based biological or psychological factors contribute to apathy levels in schizophrenia.
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Affiliation(s)
- S H Lyngstad
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - F Bettella
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - S R Aminoff
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Early Intervention in Psychosis Advisory Unit for South East Norway, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - L Athanasiu
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - O A Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - A Faerden
- Division of Mental Health and Addiction, Department of Acute Psychiatry, Oslo University Hospital, Oslo, Norway
| | - I Melle
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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Isvoranu AM, Guloksuz S, Epskamp S, van Os J, Borsboom D. Toward incorporating genetic risk scores into symptom networks of psychosis. Psychol Med 2020; 50:636-643. [PMID: 30867074 PMCID: PMC7093319 DOI: 10.1017/s003329171900045x] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 02/14/2019] [Accepted: 02/18/2019] [Indexed: 11/16/2022]
Abstract
BACKGROUND Psychosis spectrum disorder is a heterogeneous, multifactorial clinical phenotype, known to have a high heritability, only a minor portion of which can be explained by molecular measures of genetic variation. This study proposes that the identification of genetic variation underlying psychotic disorder may have suffered due to issues in the psychometric conceptualization of the phenotype. Here we aim to open a new line of research into the genetics of mental disorders by explicitly incorporating genes into symptom networks. Specifically, we investigate whether links between a polygenic risk score (PRS) for schizophrenia and measures of psychosis proneness can be identified in a network model. METHODS We analyzed data from n = 2180 subjects (controls, patients diagnosed with a non-affective psychotic disorder, and the first-degree relatives of the patients). A network structure was computed to examine associations between the 42 symptoms of the Community Assessment of Psychic Experiences (CAPE) and the PRS for schizophrenia. RESULTS The resulting network shows that the PRS is directly connected to the spectrum of positive and depressive symptoms, with the items conspiracy and no future being more often located on predictive pathways from PRS to other symptoms. CONCLUSIONS To our knowledge, the current exploratory study provides a first application of the network framework to the field of behavior genetics research. This allows for a novel outlook on the investigation of the relations between genome-wide association study-based PRSs and symptoms of mental disorders, by focusing on the dependencies among variables.
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Affiliation(s)
- Adela-Maria Isvoranu
- Department of Psychology, Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands
| | - Sinan Guloksuz
- Department of Psychiatry and Neuropsychology, School of Mental Health and Neuroscience, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Sacha Epskamp
- Department of Psychology, Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands
| | - Jim van Os
- Utrecht University Medical Centre, Utrecht, The Netherlands
| | - Denny Borsboom
- Department of Psychology, Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands
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Harrison JR, Mistry S, Muskett N, Escott-Price V. From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review. J Alzheimers Dis 2020; 74:1271-1283. [PMID: 32250305 PMCID: PMC7242840 DOI: 10.3233/jad-191233] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/12/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD. OBJECTIVE This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration. METHODS We searched the literature from July 2008-July 2018 following PRISMA guidelines. RESULTS 57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes. CONCLUSION PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.
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Affiliation(s)
- Judith R. Harrison
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff, UK
- MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
| | - Sumit Mistry
- MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
| | - Natalie Muskett
- Cardiff University Medical School, University Hospital of Wales, Cardiff, UK
| | - Valentina Escott-Price
- Dementia Research Institute & the MRC Centre for Neuropsychiatric Genetics and Genomics, Hadyn Ellis Building, Cardiff University, Cardiff, UK
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Zhang E, Levin AM, Williams LK. How does race and ethnicity effect the precision treatment of asthma? EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2019; 4:337-356. [PMID: 33015363 DOI: 10.1080/23808993.2019.1690396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction Asthma is a common condition that affects large numbers of children and adults, yet the burden of disease is not equally distributed amongst groups. In the United States, African Americans and Puerto Ricans have higher rates of asthma and its complications when compared with European Americans. However, clinical trials and genetic studies have largely focused on the latter group. Areas covered Here we examine what is known regarding differences in asthma treatment response by race-ethnicity. We also review existing genetic studies related to the use of asthma medications, paying special attention to studies that included substantial numbers of non-white population groups. Publicly accessible search engines of the medical literature were queried using combinations of the terms asthma, race, ethnicity, pharmacogenomics, and pharmacogenetics, as well as the names of individual asthma medication classes. The list of articles reviewed was supplemented by bibliographies and expert knowledge. Expert opinion A substantial and coordinated effort is still needed to both identify and validate genetic biomarkers of asthma medication response, as currently there are no clinically actionable genetic markers available for this purpose. The path to identifying such markers in non-white populations is even more formidable, since these groups are underrepresented in existing data.
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Affiliation(s)
- Ellen Zhang
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Albert M Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
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Zhang C, Hu R, Zhang G, Zhe Y, Hu B, He J, Wang Z, Qi X. A Weighted Genetic Risk Score Based on Four APOE-Independent Alzheimer’s Disease Risk Loci May Supplement APOE E4 for Better Disease Prediction. J Mol Neurosci 2019; 69:433-443. [DOI: 10.1007/s12031-019-01372-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Accepted: 06/26/2019] [Indexed: 12/13/2022]
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The Contribution of Genetic Factors to Cognitive Impairment and Dementia: Apolipoprotein E Gene, Gene Interactions, and Polygenic Risk. Int J Mol Sci 2019; 20:ijms20051177. [PMID: 30866553 PMCID: PMC6429136 DOI: 10.3390/ijms20051177] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2019] [Accepted: 02/26/2019] [Indexed: 12/19/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease. Although it has been studied for years, the pathogenesis of AD is still controversial. Genetic factors may play an important role in pathogenesis, with the apolipoprotein E (APOE) gene among the greatest risk factors for AD. In this review, we focus on the influence of genetic factors, including the APOE gene, the interaction between APOE and other genes, and the polygenic risk factors for cognitive function and dementia. The presence of the APOE ε4 allele is associated with increased AD risk and reduced age of AD onset. Accelerated cognitive decline and abnormal internal environment, structure, and function of the brain were also found in ε4 carriers. The effect of the APOE promoter on cognition and the brain was confirmed by some studies, but further investigation is still needed. We also describe the effects of the associations between APOE and other genetic risk factors on cognition and the brain that exhibit a complex gene⁻gene interaction, and we consider the importance of using a polygenic risk score to investigate the association between genetic variance and phenotype.
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Levine ME, Harrati A, Crimmins EM. Predictors and Implications of Accelerated Cognitive Aging. BIODEMOGRAPHY AND SOCIAL BIOLOGY 2018; 64:83-101. [PMID: 31007841 PMCID: PMC6469682 DOI: 10.1080/19485565.2018.1552513] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Aging is a major risk factor for both normal and pathological cognitive decline. However, individuals vary in their rate of age-related decline. We developed an easily interpretable composite measure of cognitive age, and related both the level of cognitive age and cognitive slope to sociodemographic, genetic, and disease indicators and examine its prediction of dementia transition. Using a sample of 19,594 participants from the Health and Retirement Study, cognitive age was derived from a set of performance tests administered at each wave. Our findings reveal different conclusions as they relate to levels versus slopes of cognitive age, with more pronounced differences by sex and race/ethnicity for absolute levels of cognitive decline rather than for rates of declines. We also find that both level and slope of cognitive age are inversely related to education, as well as increased for persons with APOE ε4 and/or diabetes. Finally, results show that the slope in cognitive age predicts subsequent dementia among non-demented older adults. Overall, our study suggests that this measure is applicable to cross-sectional and longitudinal studies on cognitive aging, decline, and dementia with the goal of better understanding individual differences in cognitive decline.
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Affiliation(s)
- Morgan E. Levine
- Department of Pathology, Yale School of Medicine, New Haven, CT 06520, USA
- Department of Epidemiology, Yale School of Public Health, New Haven, CT 06520, USA
| | - Amal Harrati
- Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Eileen M. Crimmins
- Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA
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Cognitive Aging in Black and White Americans: Cognition, Cognitive Decline, and Incidence of Alzheimer Disease Dementia. Epidemiology 2018; 29:151-159. [PMID: 28863046 DOI: 10.1097/ede.0000000000000747] [Citation(s) in RCA: 230] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND US-based studies have reported that older blacks perform worse than older whites on cognitive tests and have higher risk of Alzheimer disease dementia (AD). It is unclear whether these findings reflect differences in cognitive decline. METHODS The Chicago Health and Aging Project followed individuals, 65+ years old (64% black, 36% white), for up to 18 years. Participants underwent triennial cognitive assessments; stratified randomized samples underwent assessments for AD. We compared black and white participants' cognitive performance, cognitive decline rate (N = 7,735), and AD incidence (N = 2,144), adjusting for age and sex. RESULTS Black participants performed worse than white participants on the cognitive tests; 441 participants developed AD. Black participants' incident AD risk was twice that of whites (RR = 1.9; 95% CI, 1.4, 2.7), with 58 excess cases/1,000 occurring among blacks (95% CI, 28, 88). Among noncarriers of APOE ε4, blacks had 2.3 times the AD risk (95% CI, 1.5, 3.6), but among carriers, race was not associated with risk (RR = 1.1; 95% CI, 0.6, 2.0; Pinteraction = 0.05). However, cognitive decline was not faster among blacks: the black-white difference in 5-year change in global cognitive score was 0.007 standard unit (95% CI, -0.034, 0.047). Years of education accounted for a sizable portion of racial disparities in cognitive level and AD risk, in analyses using a counterfactual approach. CONCLUSIONS The higher risk of AD among blacks may stem from lower level of cognitive test performance persisting throughout the observation period rather than faster rate of late-life cognitive decline. Disparities in educational attainment may contribute to these performance disparities. See video abstract at, http://links.lww.com/EDE/B299.
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Oliveira M, Saraiva DP, Cavadas B, Fernandes V, Pedro N, Casademont I, Koeth F, Alshamali F, Harich N, Cherni L, Sierra B, Guzman MG, Sakuntabhai A, Pereira L. Population genetics-informed meta-analysis in seven genes associated with risk to dengue fever disease. INFECTION GENETICS AND EVOLUTION 2018; 62:60-72. [PMID: 29673983 DOI: 10.1016/j.meegid.2018.04.018] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 04/02/2018] [Accepted: 04/13/2018] [Indexed: 12/30/2022]
Abstract
Population genetics theory predicted that rare frequent markers would be the main contributors for heritability of complex diseases, but meta-analyses of genome-wide association studies are revealing otherwise common markers, present in all population groups, as the identified candidate genes. In this work, we applied a population-genetics informed meta-analysis to 10 markers located in seven genes said to be associated with dengue fever disease. Seven markers (in PLCE1, CD32, CD209, OAS1 and OAS3 genes) have high-frequency and the other three (in MICB and TNFA genes) have intermediate frequency. Most of these markers have high discriminatory power between population groups, but their frequencies follow the rules of genetic drift, and seem to have not been under strong selective pressure. There was a good agreement in directional consistency across trans-ethnic association signals, in East Asian and Latin American cohorts, with heterogeneity generated by randomness between studies and especially by low sample sizes. This led to confirm the following significant associations: with DF, odds ratio of 0.67 for TNFA-rs1800629-A; with DHF, 0.82 for CD32-rs1801274-G; with DSS, 0.55 for OAS3-rs2285933-G, 0.80 for PLCE1-rs2274223-G and 1.32 for MICB-rs3132468-C. The overall genetic risks confirmed sub-Saharan African populations and descendants as the best protected against the severer forms of the disease, while Southeast and Northeast Asians are the least protected ones. European and close neighbours are the best protected against dengue fever, while, again, Southeast and Northeast Asians are the least protected ones. These risk scores provide important predictive information for the largely naïve European and North American regions, as well as for Africa where misdiagnosis with other hemorrhagic diseases is of concern.
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Affiliation(s)
- Marisa Oliveira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, 4050-313 Porto, Portugal; Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France
| | - Diana P Saraiva
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France
| | - Bruno Cavadas
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, 4050-313 Porto, Portugal
| | - Verónica Fernandes
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal
| | - Nicole Pedro
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal
| | - Isabelle Casademont
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France; Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
| | - Fanny Koeth
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France; Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
| | - Farida Alshamali
- General Department of Forensic Sciences and Criminology, Dubai Police General Headquarters, PO Box 1493, Dubai, United Arab Emirates
| | - Nourdin Harich
- Laboratoire des Sciences Anthropogénétiques et Biotechnologies, Départment de Biologie, Université Chouaïb Doukkali, El Jadida 24000, Morocco
| | - Lotfi Cherni
- Laboratory of Genetics, Immunology and Human Pathology, Faculté de Sciences de Tunis, Université de Tunis El Manar, Tunis 2092, Tunisia; Tunis and High Institute of Biotechnology, University of Monastir, 5000 Monastir, Tunisia
| | - Beatriz Sierra
- Virology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), 601 Havana, Cuba
| | - Maria G Guzman
- Virology Department, PAHO/WHO Collaborating Center for the Study of Dengue and its Vector, Pedro Kourí Institute of Tropical Medicine (IPK), 601 Havana, Cuba
| | - Anavaj Sakuntabhai
- Institut Pasteur, Functional Genetics of Infectious Diseases Unit, 75724 Paris Cedex 15, France; Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan; CNRS UMR2000: Génomique évolutive, modélisation et santé (GEMS), Paris, France
| | - Luisa Pereira
- i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, 4200-135 Porto, Portugal; Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), 4200-135 Porto, Portugal; Faculdade de Medicina da Universidade do Porto, Portugal.
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Polygenic risk for Alzheimer's disease influences precuneal volume in two independent general populations. Neurobiol Aging 2018; 64:116-122. [DOI: 10.1016/j.neurobiolaging.2017.12.022] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2017] [Revised: 11/27/2017] [Accepted: 12/21/2017] [Indexed: 11/20/2022]
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Oliveira M, Lert-itthiporn W, Cavadas B, Fernandes V, Chuansumrit A, Anunciação O, Casademont I, Koeth F, Penova M, Tangnararatchakit K, Khor CC, Paul R, Malasit P, Matsuda F, Simon-Lorière E, Suriyaphol P, Pereira L, Sakuntabhai A. Joint ancestry and association test indicate two distinct pathogenic pathways involved in classical dengue fever and dengue shock syndrome. PLoS Negl Trop Dis 2018; 12:e0006202. [PMID: 29447178 PMCID: PMC5813895 DOI: 10.1371/journal.pntd.0006202] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2017] [Accepted: 01/02/2018] [Indexed: 11/18/2022] Open
Abstract
Ethnic diversity has been long considered as one of the factors explaining why the severe forms of dengue are more prevalent in Southeast Asia than anywhere else. Here we take advantage of the admixed profile of Southeast Asians to perform coupled association-admixture analyses in Thai cohorts. For dengue shock syndrome (DSS), the significant haplotypes are located in genes coding for phospholipase C members (PLCB4 added to previously reported PLCE1), related to inflammation of blood vessels. For dengue fever (DF), we found evidence of significant association with CHST10, AHRR, PPP2R5E and GRIP1 genes, which participate in the xenobiotic metabolism signaling pathway. We conducted functional analyses for PPP2R5E, revealing by immunofluorescence imaging that the coded protein co-localizes with both DENV1 and DENV2 NS5 proteins. Interestingly, only DENV2-NS5 migrated to the nucleus, and a deletion of the predicted top-linking motif in NS5 abolished the nuclear transfer. These observations support the existence of differences between serotypes in their cellular dynamics, which may contribute to differential infection outcome risk. The contribution of the identified genes to the genetic risk render Southeast and Northeast Asian populations more susceptible to both phenotypes, while African populations are best protected against DSS and intermediately protected against DF, and Europeans the best protected against DF but the most susceptible against DSS.
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Affiliation(s)
- Marisa Oliveira
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto, Portugal
- Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
| | - Worachart Lert-itthiporn
- Bioinformatics and Data Management for Research, Office for Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Bruno Cavadas
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto, Portugal
- Instituto de Ciências Biomédicas Abel Salazar (ICBAS), Universidade do Porto, Porto, Portugal
| | - Verónica Fernandes
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto, Portugal
| | - Ampaiwan Chuansumrit
- Department of Pediatrics, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Orlando Anunciação
- Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto, Portugal
| | - Isabelle Casademont
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
| | - Fanny Koeth
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
| | - Marina Penova
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Kanchana Tangnararatchakit
- Department of Pediatrics, Faculty of Medicine, Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
| | - Chiea Chuen Khor
- Genome Institute of Singapore, A-STAR, Singapore, Singapore
- Department of Biochemistry, National University of Singapore, Singapore, Singapore
| | - Richard Paul
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
- CNRS, Unité de Recherche Associée 3012, Paris, France
| | - Prida Malasit
- Dengue Hemorrhagic Fever Research Unit, Office for Research and Development, Siriraj Hospital, Faculty of Medicine, Mahidol University, Bangkok, Thailand
- Medical Biotechnology Unit, National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, Pathumthani, Thailand
| | - Fumihiko Matsuda
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Etienne Simon-Lorière
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
- CNRS, Unité de Recherche Associée 3012, Paris, France
| | - Prapat Suriyaphol
- Bioinformatics and Data Management for Research, Office for Research and Development, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok, Thailand
| | - Luisa Pereira
- i3S—Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Porto, Portugal
- Instituto de Patologia e Imunologia Molecular da Universidade do Porto (IPATIMUP), Porto, Portugal
- Department of Pathology, Faculty of Medicine, University of Porto, Porto, Portugal
- * E-mail: (LP); (AS)
| | - Anavaj Sakuntabhai
- Functional Genetics of Infectious Diseases Unit, Institut Pasteur, Paris, France
- Pasteur Kyoto International Joint Research Unit for Integrative Vaccinomics, Kyoto, Japan
- CNRS, Unité de Recherche Associée 3012, Paris, France
- * E-mail: (LP); (AS)
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Using an Alzheimer Disease Polygenic Risk Score to Predict Memory Decline in Black and White Americans Over 14 Years of Follow-up. Alzheimer Dis Assoc Disord 2017; 30:195-202. [PMID: 26756387 DOI: 10.1097/wad.0000000000000137] [Citation(s) in RCA: 55] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Evidence on whether genetic predictors of Alzheimer disease (AD) also predict memory decline is inconsistent, and limited data are available for African ancestry populations. For 8253 non-Hispanic white (NHW) and non-Hispanic black (NHB) Health and Retirement Study participants with memory scores measured 1 to 8 times between 1998 and 2012 (average baseline age=62), we calculated weighted polygenic risk scores [AD Genetic Risk Score (AD-GRS)] using the top 22 AD-associated loci, and an alternative score excluding apolipoprotein E (APOE) (AD-GRSexAPOE). We used generalized linear models with AD-GRS-by-age and AD-GRS-by-age interactions (age centered at 70) to predict memory decline. Average NHB decline was 26% faster than NHW decline (P<0.001). Among NHW, 10% higher AD-GRS predicted faster memory decline (linear β=-0.058 unit decrease over 10 y; 95% confidence interval,-0.074 to -0.043). AD-GRSexAPOE also predicted faster decline for NHW, although less strongly. Among NHB, AD-GRS predicted faster memory decline (linear β=-0.050; 95% confidence interval, -0.106 to 0.006), but AD-GRSexAPOE did not. Our nonsignificant estimate among NHB may reflect insufficient statistical power or a misspecified AD-GRS among NHB as an overwhelming majority of genome-wide association studies are conducted in NHW. A polygenic score based on previously identified AD loci predicts memory loss in US blacks and whites.
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Polygenic risk score in postmortem diagnosed sporadic early-onset Alzheimer's disease. Neurobiol Aging 2017; 62:244.e1-244.e8. [PMID: 29103623 DOI: 10.1016/j.neurobiolaging.2017.09.035] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2017] [Revised: 09/27/2017] [Accepted: 09/29/2017] [Indexed: 11/24/2022]
Abstract
Sporadic early-onset Alzheimer's disease (sEOAD) exhibits the symptoms of late-onset Alzheimer's disease but lacks the familial aspect of the early-onset familial form. The genetics of Alzheimer's disease (AD) identifies APOEε4 to be the greatest risk factor; however, it is a complex disease involving both environmental risk factors and multiple genetic loci. Polygenic risk scores (PRSs) accumulate the total risk of a phenotype in an individual based on variants present in their genome. We determined whether sEOAD cases had a higher PRS compared to controls. A cohort of sEOAD cases was genotyped on the NeuroX array, and PRSs were generated using PRSice. The target data set consisted of 408 sEOAD cases and 436 controls. The base data set was collated by the International Genomics of Alzheimer's Project consortium, with association data from 17,008 late-onset Alzheimer's disease cases and 37,154 controls, which can be used for identifying sEOAD cases due to having shared phenotype. PRSs were generated using all common single nucleotide polymorphisms between the base and target data set, PRS were also generated using only single nucleotide polymorphisms within a 500 kb region surrounding the APOE gene. Sex and number of APOE ε2 or ε4 alleles were used as variables for logistic regression and combined with PRS. The results show that PRS is higher on average in sEOAD cases than controls, although there is still overlap among the whole cohort. Predictive ability of identifying cases and controls using PRSice was calculated with 72.9% accuracy, greater than the APOE locus alone (65.2%). Predictive ability was further improved with logistic regression, identifying cases and controls with 75.5% accuracy.
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van Os J, van der Steen Y, Islam MA, Gülöksüz S, Rutten BP, Simons CJ. Evidence that polygenic risk for psychotic disorder is expressed in the domain of neurodevelopment, emotion regulation and attribution of salience. Psychol Med 2017; 47:2421-2437. [PMID: 28436345 DOI: 10.1017/s0033291717000915] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND The liability-threshold model of psychosis risk predicts stronger phenotypic manifestation of the polygenic risk score (PRS) in the healthy relatives of patients, as compared with healthy comparison subjects. METHODS First-degree relatives of patients with psychotic disorder (871 siblings and 812 parents) and healthy comparison subjects (n = 523) were interviewed three times in 6 years. Repeated measures of two psychosis phenotypes, the Community Assessment of Psychic Experiences (CAPE; self-report - subscales of positive, negative and depressive symptoms) and the Structured Interview for Schizotypy - Revised (SIS-R; clinical interview - subscales of positive and negative schizotypy), were examined for association with PRS. Interview-based lifetime rate of depressive and manic episodes were also examined, as was association with repeated measures of intelligence quotient (IQ). RESULTS In the relatives, PRS was associated with CAPE/SIS-R total score (respectively, B = 0.12, 95% CI 0.02-0.22 and B = 0.11, 95% CI 0.02-0.20), the SIS-R positive subscale (B = 0.16, 95% CI 0.04-0.28), the CAPE depression subscale (B = 0.21, 95% CI 0.07-0.34), any lifetime affective episode (OR 3.1, 95% CI 1.04-9.3), but not with IQ (B = -1.8, 95% CI -8.0 to 4.4). In the controls, similar associations were apparent between PRS on the one hand and SIS-R total score, SIS-R positive, SIS-R negative, any lifetime affective episode and, in contrast, lower IQ (B = -8.5, 95% CI -15.5 to -1.6). CONCLUSIONS In non-ill people, polygenic risk for psychotic disorder is expressed pleiotropically in the domain of neurodevelopment, emotion regulation and attribution of salience. In subjects at elevated genetic risk, emerging expression of neurodevelopmental alterations may create floor effects, obscuring genetic associations.
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Affiliation(s)
- J van Os
- Department of Psychiatry and Psychology,Maastricht University Medical Centre,Maastricht,The Netherlands
| | - Y van der Steen
- Department of Psychiatry and Psychology,Maastricht University Medical Centre,Maastricht,The Netherlands
| | - Md A Islam
- University of Groningen, University Medical Center Groningen, University Center for Psychiatry,Groningen,The Netherlands
| | - S Gülöksüz
- Department of Psychiatry and Psychology,Maastricht University Medical Centre,Maastricht,The Netherlands
| | - B P Rutten
- Department of Psychiatry and Psychology,Maastricht University Medical Centre,Maastricht,The Netherlands
| | - C J Simons
- Department of Psychiatry and Psychology,Maastricht University Medical Centre,Maastricht,The Netherlands
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Mez J, Marden JR, Mukherjee S, Walter S, Gibbons LE, Gross AL, Zahodne LB, Gilsanz P, Brewster P, Nho K, Crane PK, Larson EB, Glymour MM. Alzheimer's disease genetic risk variants beyond APOE ε4 predict mortality. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2017; 8:188-195. [PMID: 28983503 PMCID: PMC5604953 DOI: 10.1016/j.dadm.2017.07.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
INTRODUCTION We hypothesized that, like apolipoprotein E (APOE), other late-onset Alzheimer's disease (LOAD) genetic susceptibility loci predict mortality. METHODS We used a weighted genetic risk score (GRS) from 21 non-APOE LOAD risk variants to predict survival in the Adult Changes in Thought and the Health and Retirement Studies. We meta-analyzed hazard ratios and examined models adjusted for cognitive performance or limited to participants with dementia. For replication, we assessed the GRS-longevity association in the Cohorts for Heart and Aging Research in Genomic Epidemiology, comparing cases surviving to age ≥90 years with controls who died between ages 55 and 80 years. RESULTS Higher GRS predicted mortality (hazard ratio = 1.05; 95% confidence interval: 1.00-1.10, P = .04). After adjusting for cognitive performance or restricting to participants with dementia, the relationship was attenuated and no longer significant. In case-control analysis, the GRS was associated with reduced longevity (odds ratio = 0.64; 95% confidence interval: 0.41-1.00, P = .05). DISCUSSION Non-APOE LOAD susceptibility loci confer risk for mortality, likely through effects on dementia incidence.
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Affiliation(s)
- Jesse Mez
- Alzheimer's Disease and Chronic Traumatic Encephalopathy Center, Boston University School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Corresponding author. Tel.: +1 617-414-8384; Fax: +1 617-414-4275.
| | - Jessica R. Marden
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute, Cambridge, MA, USA
| | | | - Stefan Walter
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Laura E. Gibbons
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Alden L. Gross
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health and Johns Hopkins University Center on Aging and Health, Baltimore, MD, USA
| | - Laura B. Zahodne
- Department of Psychology, University of Michigan, Ann Arbor, MI, USA
| | - Paola Gilsanz
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Paul Brewster
- Institute on Aging & Lifelong Health, University of Victoria, Victoria, BC, Canada
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Eric B. Larson
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - M. Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
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Whitlock EL, Diaz-Ramirez LG, Glymour MM, Boscardin WJ, Covinsky KE, Smith AK. Association Between Persistent Pain and Memory Decline and Dementia in a Longitudinal Cohort of Elders. JAMA Intern Med 2017; 177:1146-1153. [PMID: 28586818 PMCID: PMC5588896 DOI: 10.1001/jamainternmed.2017.1622] [Citation(s) in RCA: 191] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
IMPORTANCE Chronic pain is common among the elderly and is associated with cognitive deficits in cross-sectional studies; the population-level association between chronic pain and longitudinal cognition is unknown. OBJECTIVE To determine the population-level association between persistent pain, which may reflect chronic pain, and subsequent cognitive decline. DESIGN, SETTING, AND PARTICIPANTS Cohort study with biennial interviews of 10 065 community-dwelling older adults in the nationally representative Health and Retirement Study who were 62 years or older in 2000 and answered pain and cognition questions in both 1998 and 2000. Data analysis was conducted between June 24 and October 31, 2016. EXPOSURES "Persistent pain," defined as a participant reporting that he or she was often troubled with moderate or severe pain in both the 1998 and 2000 interviews. MAIN OUTCOMES AND MEASURES Coprimary outcomes were composite memory score and dementia probability, estimated by combining neuropsychological test results and informant and proxy interviews, which were tracked from 2000 through 2012. Linear mixed-effects models, with random slope and intercept for each participant, were used to estimate the association of persistent pain with slope of the subsequent cognitive trajectory, adjusting for demographic characteristics and comorbidities measures in 2000 and applying sampling weights to represent the 2000 US population. We hypothesized that persistent pain would predict accelerated memory decline and increased probability of dementia. To quantify the impact of persistent pain on functional independence, we combined our primary results with information on the association between memory and ability to manage medications and finances independently. RESULTS Of the 10 065 eligible HRS sample members, 60% were female, and median baseline age was 73 years (interquartile range, 67-78 years). At baseline, persistent pain affected 10.9% of participants and was associated with worse depressive symptoms and more limitations in activities of daily living. After covariate adjustment, persistent pain was associated with 9.2% (95% CI, 2.8%-15.0%) more rapid memory decline compared with those without persistent pain. After 10 years, this accelerated memory decline implied a 15.9% higher relative risk of inability to manage medications and an 11.8% higher relative risk of inability to manage finances independently. Adjusted dementia probability increased 7.7% faster (95% CI, 0.55%-14.2%); after 10 years, this translates to an absolute 2.2% increase in dementia probability for those with persistent pain. CONCLUSIONS AND RELEVANCE Persistent pain was associated with accelerated memory decline and increased probability of dementia.
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Affiliation(s)
- Elizabeth L Whitlock
- Department of Anesthesia and Perioperative Care, University of California, San Francisco
| | - L Grisell Diaz-Ramirez
- Division of Geriatrics, Department of Medicine, University of California, San Francisco and San Francisco Veterans Affairs Health Care System
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - W John Boscardin
- Division of Geriatrics, Department of Medicine, University of California, San Francisco and San Francisco Veterans Affairs Health Care System.,Department of Epidemiology and Biostatistics, University of California, San Francisco
| | - Kenneth E Covinsky
- Division of Geriatrics, Department of Medicine, University of California, San Francisco and San Francisco Veterans Affairs Health Care System
| | - Alexander K Smith
- Division of Geriatrics, Department of Medicine, University of California, San Francisco and San Francisco Veterans Affairs Health Care System
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Yaffe K, Freimer D, Chen H, Asao K, Rosso A, Rubin S, Tranah G, Cummings S, Simonsick E. Olfaction and risk of dementia in a biracial cohort of older adults. Neurology 2016; 88:456-462. [PMID: 28039314 DOI: 10.1212/wnl.0000000000003558] [Citation(s) in RCA: 83] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2016] [Accepted: 10/31/2016] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Prior studies indicate that olfactory function may be an early marker for cognitive impairment, but the body of evidence has been largely restricted to white populations. METHODS We studied 2,428 community-dwelling black and white older adults (baseline age 70-79 years) without dementia enrolled in the Health, Aging, and Body Composition (Health ABC) study. Olfaction was measured as odor identification (OI) with the 12-item Cross Cultural Smell Identification Test in year 3. We defined incident dementia over 12 years on the basis of hospitalization records, prescription for dementia medication, or 1.5-SD decline in race-stratified global cognition score. We assessed dementia risk associated with OI score (by tertile) using Cox proportional hazards models. All analyses were stratified by race. RESULTS Poorer OI in older adults without dementia was associated with increased risk of dementia. After adjustment for demographics, medical comorbidities, and lifestyle characteristics, white participants in the poor or moderate OI tertile had greater risk of dementia (adjusted hazard ratio [HR] 3.34, 95% confidence interval [CI] 2.45-4.54; and HR 1.84, 95% CI 1.33-2.54, respectively) compared to those in the good tertile of function. Among blacks, worse OI was associated with an increased risk of dementia, but the magnitude of the effect was weaker (p for interaction = 0.04) for the poor OI tertile (adjusted HR 2.03, 95% CI 1.44-2.84) and for the moderate tertile (adjusted HR 1.42, 95% CI 0.97-2.10). There was no interaction between OI and APOE ε4 and risk of dementia. CONCLUSIONS While the magnitude of the association was stronger in whites, we found that poor OI was associated with increased risk of dementia among both black and white older adults.
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Affiliation(s)
- Kristine Yaffe
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Daniel Freimer
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD.
| | - Honglei Chen
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Keiko Asao
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Andrea Rosso
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Susan Rubin
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Greg Tranah
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Steve Cummings
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
| | - Eleanor Simonsick
- From the Departments of Psychiatry (K.Y.), Neurology (K.Y.), and Epidemiology and Biostatistics (K.Y., S.R.), University of California; San Francisco VA Medical Center (K.Y.); NCIRE-The Veterans Health Research Institute (K.Y., D.F.), San Francisco, CA; Epidemiology Branch (H.C.), National Institute of Environmental Health Sciences, Research Triangle Park, NC; Department of Preventive Medicine (K.A.), University of Tennessee Health Science Center, Memphis; Department of Epidemiology (A.R.), Graduate School of Public Health, University of Pittsburgh, PA; California Pacific Medical Center Research Institute (G.T., S.C.), San Francisco; and Translational Gerontology Branch (E.S.), National Institute on Aging, Baltimore, MD
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Chouraki V, Reitz C, Maury F, Bis JC, Bellenguez C, Yu L, Jakobsdottir J, Mukherjee S, Adams HH, Choi SH, Larson EB, Fitzpatrick A, Uitterlinden AG, de Jager PL, Hofman A, Gudnason V, Vardarajan B, Ibrahim-Verbaas C, van der Lee SJ, Lopez O, Dartigues JF, Berr C, Amouyel P, Bennett DA, van Duijn C, DeStefano AL, Launer LJ, Ikram MA, Crane PK, Lambert JC, Mayeux R, Seshadri S. Evaluation of a Genetic Risk Score to Improve Risk Prediction for Alzheimer's Disease. J Alzheimers Dis 2016; 53:921-32. [PMID: 27340842 PMCID: PMC5036102 DOI: 10.3233/jad-150749] [Citation(s) in RCA: 62] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Effective prevention of Alzheimer's disease (AD) requires the development of risk prediction tools permitting preclinical intervention. We constructed a genetic risk score (GRS) comprising common genetic variants associated with AD, evaluated its association with incident AD and assessed its capacity to improve risk prediction over traditional models based on age, sex, education, and APOEɛ4. In eight prospective cohorts included in the International Genomics of Alzheimer's Project (IGAP), we derived weighted sum of risk alleles from the 19 top SNPs reported by the IGAP GWAS in participants aged 65 and older without prevalent dementia. Hazard ratios (HR) of incident AD were estimated in Cox models. Improvement in risk prediction was measured by the difference in C-index (Δ-C), the integrated discrimination improvement (IDI) and continuous net reclassification improvement (NRI>0). Overall, 19,687 participants at risk were included, of whom 2,782 developed AD. The GRS was associated with a 17% increase in AD risk (pooled HR = 1.17; 95% CI = [1.13-1.21] per standard deviation increase in GRS; p-value = 2.86×10-16). This association was stronger among persons with at least one APOEɛ4 allele (HRGRS = 1.24; 95% CI = [1.15-1.34]) than in others (HRGRS = 1.13; 95% CI = [1.08-1.18]; pinteraction = 3.45×10-2). Risk prediction after seven years of follow-up showed a small improvement when adding the GRS to age, sex, APOEɛ4, and education (Δ-Cindex = 0.0043 [0.0019-0.0067]). Similar patterns were observed for IDI and NRI>0. In conclusion, a risk score incorporating common genetic variation outside the APOEɛ4 locus improved AD risk prediction and may facilitate risk stratification for prevention trials.
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Affiliation(s)
- Vincent Chouraki
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
| | | | - Fleur Maury
- Lille University, Inserm, Lille University Hospital, Institut Pasteur de Lille, U1167 - RID-AGE - Risk factors and molecular determinants of aging-related diseases; Labex Distalz, Lille, France
| | | | - Celine Bellenguez
- Lille University, Inserm, Lille University Hospital, Institut Pasteur de Lille, U1167 - RID-AGE - Risk factors and molecular determinants of aging-related diseases; Labex Distalz, Lille, France
| | - Lei Yu
- Rush Alzheimer’s Disease Center, Chicago, IL, USA
| | | | | | | | | | - Eric B. Larson
- University of Washington, Seattle, WA, USA
- Group Health Research Institute, Seattle, WA, USA
| | | | | | | | | | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Oscar Lopez
- Alzheimer’s Disease Research Center, Departments of Neurology, Psychiatry and Psychology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | | | - Claudine Berr
- Inserm U1061 ‘Neuropsychiatry: epidemiological and clinical research’, Université de Montpellier, Monpellier, France
| | - Philippe Amouyel
- Lille University, Inserm, Lille University Hospital, Institut Pasteur de Lille, U1167 - RID-AGE - Risk factors and molecular determinants of aging-related diseases; Labex Distalz, Lille, France
| | | | | | | | | | | | - Paul K. Crane
- University of Washington, Seattle, WA, USA
- Group Health Research Institute, Seattle, WA, USA
| | - Jean-Charles Lambert
- Lille University, Inserm, Lille University Hospital, Institut Pasteur de Lille, U1167 - RID-AGE - Risk factors and molecular determinants of aging-related diseases; Labex Distalz, Lille, France
| | | | - Sudha Seshadri
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- The Framingham Heart Study, Framingham, MA, USA
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Zahodne LB, Manly JJ, Azar M, Brickman AM, Glymour MM. Racial Disparities in Cognitive Performance in Mid- and Late Adulthood: Analyses of Two Cohort Studies. J Am Geriatr Soc 2016; 64:959-64. [PMID: 27225354 PMCID: PMC4883591 DOI: 10.1111/jgs.14113] [Citation(s) in RCA: 33] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Accepted: 09/06/2015] [Indexed: 11/28/2022]
Abstract
OBJECTIVES To examine whether the attenuation of racial disparities observed in physical health outcomes at older ages can be extended to cognitive outcomes in mid- and late-life samples. DESIGN Cross-sectional associations between race and cognitive functioning were examined as a function of age. SETTING The National Survey of Midlife Development in the United States (MIDUS) and the Washington Heights-Inwood Columbia Aging Project (WHICAP). PARTICIPANTS Non-Hispanic African American or white individuals aged 40 and older (MIDUS; n = 3875, 10.5% African American) and non-Hispanic African American or white individuals aged 65 and older without a diagnosis of dementia (WHICAP; n = 2,729, 53.8% African American). MEASUREMENTS Composite scores of executive functioning and episodic memory. RESULTS Independent of main effects of age, birth cohort, sex, education, and chronic health conditions, significant interactions between age and race indicated that racial disparities in episodic memory and executive functioning were larger at younger than older age in both samples. CONCLUSION Attenuation of racial inequalities in older age can be extended to cognitive outcomes, which probably reflects selective survival. Research on cognitive disparities or on race-specific causes of cognitive outcomes in old age must incorporate corrections for selective survival if the goal is to identify causal predictors of cognitive outcomes rather than merely statistical predictors.
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Affiliation(s)
- Laura B Zahodne
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, New York
| | - Jennifer J Manly
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, New York
| | - Martina Azar
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
| | - Adam M Brickman
- Department of Neurology, College of Physicians and Surgeons, Columbia University, New York, New York
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, New York, New York
- Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, New York, New York
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California at San Francisco, San Francisco, California
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Mayeda ER, Glymour MM, Quesenberry CP, Whitmer RA. Inequalities in dementia incidence between six racial and ethnic groups over 14 years. Alzheimers Dement 2016; 12:216-24. [PMID: 26874595 DOI: 10.1016/j.jalz.2015.12.007] [Citation(s) in RCA: 557] [Impact Index Per Article: 69.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2015] [Revised: 11/30/2015] [Accepted: 12/10/2015] [Indexed: 02/06/2023]
Abstract
INTRODUCTION Reducing racial/ethnic disparities is a primary objective of the National Alzheimer's Plan (NAPA), yet direct comparisons within large samples representing diversity of the United States are lacking. METHODS Dementia incidence from January 1, 2000 to December 31, 2013 and a 25-year cumulative risk in 274,283 health care members aged 64+ (n = 18,778 African-American, n = 4543 American Indian/Alaska Native [AIAN], n = 21,000 Latino, n = 440 Pacific Islander, n = 206,490 white, n = 23,032 Asian-Americans). Cox proportional hazard models were adjusted for age, sex, medical utilization, and comorbidities. RESULTS Dementia incidence (n = 59,555) was highest for African-Americans (26.6/1000 person-years) and AIANs (22.2/1000 person-years); intermediate for Latinos (19.6/1000 person-years), Pacific Islanders (19.6/1000 person-years), and whites (19.3/1000 person-years) and lowest among Asian-Americans (15.2/1000 person-years). Risk was 65% greater for African-Americans (hazard ratio = 1.65; 95% confidence interval = 1.58-1.72) versus Asian-Americans. Cumulative 25-year risk at age 65 was as follows: 38% African-Americans, 35% AIANs, 32% Latino, 25% Pacific Islanders, 30% white, and 28% Asian-Americans. DISCUSSION Dementia rates varied over 60% between groups, providing a comprehensive benchmark for the NAPA goal of reducing disparities.
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Affiliation(s)
- Elizabeth Rose Mayeda
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - M Maria Glymour
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | | | - Rachel A Whitmer
- Kaiser Permanente Division of Research, Oakland, CA, USA; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA.
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Abstract
Objective An Alzheimer’s disease (AD) diagnosis is preceded by a long period of cognitive decline. We previously demonstrated increased risk of decline among individuals possessing one or more APOE ε4 alleles together with a family history of AD. The objective of this study is to investigate the possibility that such an increased risk might be due to AD risk genes with small effects in combination with APOE. Methods Participants in the Health and Retirement Study (HRS) over the age of 65, who contributed DNA, and had two or more evaluations with an abbreviated version of the modified Telephone Interview for Cognitive Status (TICS-m) were eligible for the study (n = 7451). A genetic risk score (g-score) was derived using AD risk genes’ meta-analyses data, assigning risk according to the number of risk alleles and summed over all the risk genes. Trajectories of cognitive function were modeled in four groups of Caucasian participants with and without one or more APOE ε4 alleles and either a high or low g-score: APOE ε4-/low g-score; APOE ε4-/high g-score; APOE ε4+/low g-score; and APOE ε4+/high g-score. Post hoc analyses evaluated interactions between individual genes and APOE. Results Individuals in the APOE ε4+/high g-score group exhibited the greatest cognitive decline over time (p<.0001). This risk appeared to be greater than the sum of the effects of either high g-score or APOE ε4 alone. When gene interactions were individually tested with APOE, a statistically significant interaction with CD33 was discovered (p = 0.04) although the interaction was no longer significant when adjusted for multiple comparisons. Conclusions Individuals with multiple AD risk genes in addition to having one or more APOE ε4 alleles are at greater risk of cognitive decline than individuals with either APOE ε4 or a high genetic risk score. Among those with one or more APOE ε4 alleles, having one or more copies of the CD33 C (risk) allele may further increase the risk of cognitive decline.
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Yokoyama JS, Bonham LW, Sears RL, Klein E, Karydas A, Kramer JH, Miller BL, Coppola G. Decision tree analysis of genetic risk for clinically heterogeneous Alzheimer's disease. BMC Neurol 2015; 15:47. [PMID: 25880661 PMCID: PMC4459447 DOI: 10.1186/s12883-015-0304-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 03/12/2015] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Heritability of Alzheimer's disease (AD) is estimated at 74% and genetic contributors have been widely sought. The ε4 allele of apolipoprotein E (APOE) remains the strongest common risk factor for AD, with numerous other common variants contributing only modest risk for disease. Variability in clinical presentation of AD, which is typically amnestic (AmnAD) but can less commonly involve visuospatial, language and/or dysexecutive syndromes (atypical or AtAD), further complicates genetic analyses. Taking a multi-locus approach may increase the ability to identify individuals at highest risk for any AD syndrome. In this study, we sought to develop and investigate the utility of a multi-variant genetic risk assessment on a cohort of phenotypically heterogeneous patients with sporadic AD clinical diagnoses. METHODS We genotyped 75 variants in our cohort and, using a two-staged study design, we developed a 17-marker AD risk score in a Discovery cohort (n = 59 cases, n = 133 controls) then assessed its utility in a second Validation cohort (n = 126 cases, n = 150 controls). We also performed a data-driven decision tree analysis to identify genetic and/or demographic criteria that are most useful for accurately differentiating all AD cases from controls. RESULTS We confirmed APOE ε4 as a strong risk factor for AD. A 17-marker risk panel predicted AD significantly better than APOE genotype alone (P < 0.00001) in the Discovery cohort, but not in the Validation cohort. In decision tree analyses, we found that APOE best differentiated cases from controls only in AmnAD but not AtAD. In AtAD, HFE SNP rs1799945 was the strongest predictor of disease; variation in HFE has previously been implicated in AD risk in non-ε4 carriers. CONCLUSIONS Our study suggests that APOE ε4 remains the best predictor of broad AD risk when compared to multiple other genetic factors with modest effects, that phenotypic heterogeneity in broad AD can complicate simple polygenic risk modeling, and supports the association between HFE and AD risk in individuals without APOE ε4.
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Affiliation(s)
- Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA.
| | - Luke W Bonham
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA.
| | - Renee L Sears
- Semel Institute for Neuroscience and Human Behavior, Departments of Neurology and Psychiatry, The David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Eric Klein
- Semel Institute for Neuroscience and Human Behavior, Departments of Neurology and Psychiatry, The David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, 90095, USA.
| | - Anna Karydas
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA.
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA.
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, 94158, USA.
| | - Giovanni Coppola
- Semel Institute for Neuroscience and Human Behavior, Departments of Neurology and Psychiatry, The David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, 90095, USA.
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