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Sargurupremraj M. Genetic Architecture of Neurological Disorders and Their Endophenotypes: Insights from Genetic Association Studies. Curr Top Behav Neurosci 2024. [PMID: 39138743 DOI: 10.1007/7854_2024_513] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2024]
Abstract
Population-scale genetic association studies of complex neurologic diseases have identified the underlying genetic architecture as multifactorial. Despite the study sample sizes reaching the millions, the identified disease-related genes explain only a small fraction of the phenotypic variance. Notable advancements in statistical methods now enable researchers to gain insights even from genomic regions where genotype-phenotype associations do not reach statistical significance. Such studies confirm a highly interconnected molecular network comprising a core group of genes directly involved in the disease process, alongside an expanded peripheral network, each contributing a small but potentially important (modulatory) effect. Additionally, causal inference methods, utilizing genetic instruments, have shed light on putative causal links between risk factors and clinical endpoints. In light of the pervasive genetic overlap or pleiotropy, however, caution is warranted in interpreting causal relationships inferred from these analyses. In this chapter, I will introduce the genetic association model, provide insights into the current state of genetic association studies, and discuss potential future directions.
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Affiliation(s)
- Muralidharan Sargurupremraj
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA.
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Rajabli F, Emekci A. Addressing overlapping sample challenges in genome-wide association studies: Meta-reductive approach. PLoS One 2024; 19:e0296207. [PMID: 39088468 PMCID: PMC11293628 DOI: 10.1371/journal.pone.0296207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 06/10/2024] [Indexed: 08/03/2024] Open
Abstract
Polygenic risk scores (PRS) are instrumental in genetics, offering insights into an individual level genetic risk to a range of diseases based on accumulated genetic variations. These scores rely on Genome-Wide Association Studies (GWAS). However, precision in PRS is often challenged by the requirement of extensive sample sizes and the potential for overlapping datasets that can inflate PRS calculations. In this study, we present a novel methodology, Meta-Reductive Approach (MRA), that was derived algebraically to adjust GWAS results, aiming to neutralize the influence of select cohorts. Our approach recalibrates summary statistics using algebraic derivations. Validating our technique with datasets from Alzheimer disease studies, we showed that the summary statistics of the MRA and those derived from individual-level data yielded the exact same values. This innovative method offers a promising avenue for enhancing the accuracy of PRS, especially when derived from meta-analyzed GWAS data.
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Affiliation(s)
- Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, United States of America
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, United States of America
| | - Azra Emekci
- Pioneer High School, San Jose, CA, United States of America
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Zhang Q, Chen G, Feng Y, Li M, Liu X, Ma L, Zhang J, Wang S. Association of chrononutrition patterns with biological aging: evidence from a nationally representative cross-sectional study. Food Funct 2024; 15:7936-7950. [PMID: 38980112 DOI: 10.1039/d4fo00147h] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/10/2024]
Abstract
Previous studies mostly focused on the benefits of caloric restriction and fasting on longevity. However, whether the timing and frequency of eating affect aging remains unclear. Here, we investigated the associations between chrononutrition patterns and biological aging, and explored whether and to what extent dietary inflammation mediated this association. 16 531 adults aged 20 to 84 years from the National Health and Nutrition Examination Survey were collected. Chrononutrition patterns were determined with two 24-hour dietary recalls. Phenotypic age was calculated to reflect the biological aging status. The dietary inflammatory index (DII) was used to assess the dietary inflammation. After adjustment of the survey weight and multiple covariates including total energy intake, participants in the third tertile of the time of the first meal (mean 10 : 26) exhibited more advanced biological age (β 0.64; 95% CI, 0.26-1.00) and a higher incidence of accelerated aging (odds ratio (OR) 1.25; 95% CI, 1.06-1.47) compared to those of the first tertile (mean 6 : 14). Higher eating frequency was associated with delayed biological aging in both multivariable linear (β -0.31; 95% CI, -0.44 to -0.19) and logistic regression model (OR 0.90; 95% CI, 0.85-0.95). Furthermore, we found that DII rather than metabolic factors mediated the inverse association between eating frequency and biological aging (mediation proportion 24.67%; 95% CI, 19.83%-32.00%). Our findings demonstrated the association between chrononutrition patterns and biological aging among the US general population and the potential role of dietary inflammation in this association, suggesting that modifying chrononutrition patterns may be a practical and cost-effective strategy for combating aging.
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Affiliation(s)
- Qianyu Zhang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
| | - Gang Chen
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
| | - Yanzhi Feng
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
| | - Mo Li
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
| | - Xingyu Liu
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
| | - Lanfang Ma
- Department of Obstetrics and Gynecology, Guiyang Maternity and Child Health Care Hospital, Guizhou 550003, People's Republic of China
| | - Jinjin Zhang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
| | - Shixuan Wang
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 430030, China.
- National Clinical Research Center for Obstetrical and Gynecological Diseases, Wuhan, Hubei, 430030, China
- Key Laboratory of Cancer Invasion and Metastasis, Ministry of Education, Wuhan, Hubei, 430030, China
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A genome-wide association meta-analysis of all-cause and vascular dementia. Alzheimers Dement 2024. [PMID: 39046104 DOI: 10.1002/alz.14115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 04/30/2024] [Accepted: 05/20/2024] [Indexed: 07/25/2024]
Abstract
INTRODUCTION Dementia is a multifactorial disease with Alzheimer's disease (AD) and vascular dementia (VaD) pathologies making the largest contributions. Yet, most genome-wide association studies (GWAS) focus on AD. METHODS We conducted a GWAS of all-cause dementia (ACD) and examined the genetic overlap with VaD. Our dataset includes 800,597 individuals, with 46,902 and 8702 cases of ACD and VaD, respectively. Known AD loci for ACD and VaD were replicated. Bioinformatic analyses prioritized genes that are likely functionally relevant and shared with closely related traits and risk factors. RESULTS For ACD, novel loci identified were associated with energy transport (SEMA4D), neuronal excitability (ANO3), amyloid deposition in the brain (RBFOX1), and magnetic resonance imaging markers of small vessel disease (SVD; HBEGF). Novel VaD loci were associated with hypertension, diabetes, and neuron maintenance (SPRY2, FOXA2, AJAP1, and PSMA3). DISCUSSION Our study identified genetic risks underlying ACD, demonstrating overlap with neurodegenerative processes, vascular risk factors, and cerebral SVD. HIGHLIGHTS We conducted the largest genome-wide association study of all-cause dementia (ACD) and vascular dementia (VaD). Known genetic variants associated with AD were replicated for ACD and VaD. Functional analyses identified novel loci for ACD and VaD. Genetic risks of ACD overlapped with neurodegeneration, vascular risk factors, and cerebral small vessel disease.
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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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Kiianitsa K, Lukes ME, Hayes BJ, Brutman JN, Valdmanis PN, Bird TD, Raskind WH, Korvatska O. TREM2 variants that cause early dementia and increase Alzheimer's disease risk affect gene splicing. Brain 2024; 147:2368-2383. [PMID: 38226698 PMCID: PMC11224616 DOI: 10.1093/brain/awae014] [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: 09/08/2023] [Revised: 01/02/2024] [Accepted: 01/09/2024] [Indexed: 01/17/2024] Open
Abstract
Loss-of-function variants in the triggering receptor expressed on myeloid cells 2 (TREM2) are responsible for a spectrum of neurodegenerative disorders. In the homozygous state, they cause severe pathologies with early onset dementia, such as Nasu-Hakola disease and behavioural variants of frontotemporal dementia (FTD), whereas heterozygous variants increase the risk of late-onset Alzheimer's disease (AD) and FTD. For over half of TREM2 variants found in families with recessive early onset dementia, the defect occurs at the transcript level via premature termination codons or aberrant splicing. The remaining variants are missense alterations thought to affect the protein; however, the underlying pathogenic mechanism is less clear. In this work, we tested whether these disease-associated TREM2 variants contribute to the pathology via altered splicing. Variants scored by SpliceAI algorithm were tested by a full-size TREM2 splicing reporter assay in different cell lines. The effect of variants was quantified by qRT-/RT-PCR and western blots. Nanostring nCounter was used to measure TREM2 RNA in the brains of NHD patients who carried spliceogenic variants. Exon skipping events were analysed from brain RNA-Seq datasets available through the Accelerating Medicines Partnership for Alzheimer's Disease Consortium. We found that for some Nasu-Hakola disease and early onset FTD-causing variants, splicing defects were the primary cause (D134G) or likely contributor to pathogenicity (V126G and K186N). Similar but milder effects on splicing of exons 2 and 3 were demonstrated for A130V, L133L and R136W enriched in patients with dementia. Moreover, the two most frequent missense variants associated with AD/FTD risk in European and African ancestries (R62H, 1% in Caucasians and T96K, 12% in Africans) had splicing defects via excessive skipping of exon 2 and overproduction of a potentially antagonistic TREM2 protein isoform. The effect of R62H on exon 2 skipping was confirmed in three independent brain RNA-Seq datasets. Our findings revealed an unanticipated complexity of pathogenic variation in TREM2, in which effects on post-transcriptional gene regulation and protein function often coexist. This necessitates the inclusion of computational and experimental analyses of splicing and mRNA processing for a better understanding of genetic variation in disease.
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Affiliation(s)
- Kostantin Kiianitsa
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
| | - Maria E Lukes
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | - Brian J Hayes
- Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Julianna N Brutman
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | - Paul N Valdmanis
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
| | - Thomas D Bird
- Department of Neurology, University of Washington, Seattle, WA 98195, USA
- Geriatric Research, Education and Clinical Center (GRECC), VA Puget Sound Medical Center, Seattle, WA 98108, USA
| | - Wendy H Raskind
- Department of Medicine, Division of Medical Genetics, University of Washington, Seattle, WA 98195, USA
- Mental Illness Research, Education and Clinical Center (MIRECC), VA Puget Sound Medical Center, Seattle, WA 98108, USA
| | - Olena Korvatska
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
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Ray NR, Kunkle BW, Hamilton-Nelson K, Kurup JT, Rajabli F, Qiao M, Vardarajan BN, Cosacak MI, Kizil C, Jean-Francois M, Cuccaro M, Reyes-Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee WP, Martin ER, Wang LS, Beecham GW, Bush WS, Xu W, Jin F, Wang L, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Extended genome-wide association study employing the African genome resources panel identifies novel susceptibility loci for Alzheimer's disease in individuals of African ancestry. Alzheimers Dement 2024. [PMID: 38958117 DOI: 10.1002/alz.13880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 04/03/2024] [Accepted: 04/12/2024] [Indexed: 07/04/2024]
Abstract
INTRODUCTION Despite a two-fold risk, individuals of African ancestry have been underrepresented in Alzheimer's disease (AD) genomics efforts. METHODS Genome-wide association studies (GWAS) of 2,903 AD cases and 6,265 controls of African ancestry. Within-dataset results were meta-analyzed, followed by functional genomics analyses. RESULTS A novel AD-risk locus was identified in MPDZ on chromosome (chr) 9p23 (rs141610415, MAF = 0.002, P = 3.68×10-9). Two additional novel common and nine rare loci were identified with suggestive associations (P < 9×10-7). Comparison of association and linkage disequilibrium (LD) patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 (ASCL1), suggesting that this association is modulated by regional origin of local African ancestry. DISCUSSION These analyses identified novel AD-associated loci in individuals of African ancestry and suggest that degree of African ancestry modulates some associations. Increased sample sets covering as much African genetic diversity as possible will be critical to identify additional loci and deconvolute local genetic ancestry effects. HIGHLIGHTS Genetic ancestry significantly impacts risk of Alzheimer's Disease (AD). Although individuals of African ancestry are twice as likely to develop AD, they are vastly underrepresented in AD genomics studies. The Alzheimer's Disease Genetics Consortium has previously identified 16 common and rare genetic loci associated with AD in African American individuals. The current analyses significantly expand this effort by increasing the sample size and extending ancestral diversity by including populations from continental Africa. Single variant meta-analysis identified a novel genome-wide significant AD-risk locus in individuals of African ancestry at the MPDZ gene, and 11 additional novel loci with suggestive genome-wide significance at P < 9×10-7. Comparison of African American datasets with samples of higher degree of African ancestry demonstrated differing patterns of association and linkage disequilibrium at one of these loci, suggesting that degree and/or geographic origin of African ancestry modulates the effect at this locus. These findings illustrate the importance of increasing number and ancestral diversity of African ancestry samples in AD genomics studies to fully disentangle the genetic architecture underlying AD, and yield more effective ancestry-informed genetic screening tools and therapeutic interventions.
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Affiliation(s)
- Nicholas R Ray
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Brian W Kunkle
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Kara Hamilton-Nelson
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Jiji T Kurup
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Farid Rajabli
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Min Qiao
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Badri N Vardarajan
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | | | - Caghan Kizil
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Melissa Jean-Francois
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Michael Cuccaro
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
| | - Laura Cantwell
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Amanda Kuzma
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Jeffery M Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Sujuan Gao
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Hugh C Hendrie
- Department of Psychiatry, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | | | | | | | - Wan-Ping Lee
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Eden R Martin
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miami, Florida, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Gary W Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - William S Bush
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Biomedical Research, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences and Cleveland Institute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Wanying Xu
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Biomedical Research, Cleveland, Ohio, USA
| | - Fulai Jin
- Department of Genetics and Genome Sciences, School of Medicine, Case Western Reserve University, Biomedical Research, Cleveland, Ohio, USA
- Department of Population and Quantitative Health Sciences and Cleveland Institute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Liyong Wang
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Lindsay A Farrer
- Department of Medicine, Biomedical Genetics Section, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Department of Ophthalmology, Boston University School of Medicine, Boston, Massachusetts, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Jonathan L Haines
- Department of Population and Quantitative Health Sciences and Cleveland Institute for Computational Biology, School of Medicine, Case Western Reserve University, Cleveland, Ohio, USA
| | - Goldie S Byrd
- Maya Angelou Center for Health Equity, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Gerard D Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
- Department of Neurology, Columbia University, New York, New York, USA
- Department of Psychiatry, Columbia University, New York, New York, USA
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
- Dr. John T. MacDonald Foundation Department of Human Genetics, University of Miami, Miami, Florida, USA
| | - Christiane Reitz
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, New York, USA
- Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
- Department of Neurology, Columbia University, New York, New York, USA
- Epidemiology, College of Physicians and Surgeons, Columbia University, New York, New York, USA
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Llibre‐Guerra JJ, Jiang M, Acosta I, Sosa AL, Acosta D, Jimenez‐Velasquez IZ, Guerra M, Salas A, Rodriguez Salgado AM, Llibre‐Guerra JC, Sánchez ND, Prina M, Renton A, Albanese E, Yokoyama JS, Llibre Rodriguez JJ. Social determinants of health but not global genetic ancestry predict dementia prevalence in Latin America. Alzheimers Dement 2024; 20:4828-4840. [PMID: 38837526 PMCID: PMC11247688 DOI: 10.1002/alz.14041] [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: 03/04/2024] [Revised: 05/08/2024] [Accepted: 05/09/2024] [Indexed: 06/07/2024]
Abstract
INTRODUCTION Leveraging the nonmonolithic structure of Latin America, which represents a large variability in social determinants of health (SDoH) and high levels of genetic admixture, we aim to evaluate the relative contributions of SDoH and genetic ancestry in predicting dementia prevalence in Latin American populations. METHODS Community-dwelling participants aged 65 and older (N = 3808) from Cuba, Dominican Republic, Mexico, and Peru completed the 10/66 protocol assessments. Dementia was diagnosed using the cross-culturally validated 10/66 algorithm. Multivariate linear regression models adjusted for SDoH were used in the main analysis. This study used cross-sectional data from the 1066 population-based study. RESULTS Individuals with higher proportions of Native American (>70%) and African American (>70%) ancestry were more likely to exhibit factors contributing to worse SDoH, such as lower educational levels (p < 0.001), lower socioeconomic status (p < 0.001), and higher frequency of vascular risk factors (p < 0.001). After adjusting for measures of SDoH, there was no association between ancestry proportion and dementia probability, and ancestry proportions no longer significantly accounted for the variance in cognitive performance (African predominant p = 0.31 [-0.19, 0.59] and Native predominant p = 0.74 [-0.24, 0.33]). DISCUSSION The findings suggest that social and environmental factors play a more crucial role than genetic ancestry in predicting dementia prevalence in Latin American populations. This underscores the need for public health strategies and policies that address these social determinants to effectively reduce dementia risk in these communities. HIGHLIGHTS Countries in Latin America express a large variability in social determinants of health and levels of admixture. After adjustment for downstream societal factors linked to SDoH, genetic ancestry shows no link to dementia. Population ancestry profiles alone do not influence cognitive performance. SDoH are key drivers of racial disparities in dementia and cognitive performance.
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Affiliation(s)
- Jorge J. Llibre‐Guerra
- Department of NeurologyWashington University School of Medicine in St. LouisSt LouisMissouriUSA
| | - Miao Jiang
- Institute of Public HealthFaculty of Biomedical SciencesUniversità della Svizzera italianaLuganoSwitzerland
| | - Isaac Acosta
- Laboratory of the DementiasNational Institute of Neurology and NeurosurgeryMexico CityMexico
- National Autonomous University of MexicoMexico CityMexico
| | - Ana Luisa Sosa
- Laboratory of the DementiasNational Institute of Neurology and NeurosurgeryMexico CityMexico
- National Autonomous University of MexicoMexico CityMexico
| | - Daisy Acosta
- Internal Medicine DepartmentUniversidad Nacional Pedro Henriquez Ureña (UNPHU), Geriatric SectionSanto DomingoDominican Republic
| | - Ivonne Z. Jimenez‐Velasquez
- Internal Medicine DepartmentGeriatrics Program, School of MedicineMedical Sciences CampusUniversity of Puerto RicoSan JuanPuerto RicoUSA
| | - Mariella Guerra
- Instituto de la Memoria Depresion y Enfermedades de Riesgo IMEDERLimaPerú
| | - Aquiles Salas
- Medicine DepartmentCaracas University Hospital, Faculty of Medicine, Universidad Central de VenezuelaCaracasVenezuela
| | | | | | - Nedelys Díaz Sánchez
- Dementia Research Unit, Facultad de Medicina Finlay‐AlbarranMedical University of HavanaHavanaCuba
| | - Matthew Prina
- Population Health Sciences InstituteFaculty of Medical SciencesNewcastle UniversityNewcastle upon TyneUK
| | - Alan Renton
- Department of NeuroscienceIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Emiliano Albanese
- Institute of Public HealthFaculty of Biomedical SciencesUniversità della Svizzera italianaLuganoSwitzerland
| | - Jennifer S. Yokoyama
- Department of NeurologyUCSF Weill Institute for Neurosciences, University of California, San FranciscoSan FranciscoCaliforniaUSA
- Department of Radiology and Biomedical ImagingUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Juan J. Llibre Rodriguez
- Dementia Research Unit, Facultad de Medicina Finlay‐AlbarranMedical University of HavanaHavanaCuba
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Cruchaga C, Bradley J, Western D, Wang C, Lucio Da Fonseca E, Neupane A, Kurup J, Ray NI, Jean-Francois M, Gorijala P, Bergmann K, Budde J, Martin E, Pericak-Vance M, Cuccaro M, Kunkle B, Morris J, Holtzman D, Perrin R, Naj A, Haines J, Schellenberg G, Fernandez V, Reitz C, Beecham G. Novel early-onset Alzheimer-associated genes influence risk through dysregulation of glutamate, immune activation, and intracell signaling pathways. RESEARCH SQUARE 2024:rs.3.rs-4480585. [PMID: 38883718 PMCID: PMC11177996 DOI: 10.21203/rs.3.rs-4480585/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
Alzheimer Disease (AD) is a highly polygenic disease that presents with relatively earlier onset (≤70yo; EOAD) in about 5% of cases. Around 90% of these EOAD cases remain unexplained by pathogenic mutations. Using data from EOAD cases and controls, we performed a genome-wide association study (GWAS) and trans-ancestry meta-analysis on non-Hispanic Whites (NHW, NCase=6,282, NControl=13,386), African Americans (AA NCase=782, NControl=3,663) and East Asians (NCase=375, NControl=838 CO). We identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL and functional annotations, we nominate four novel genes that are involved in microglia activation, glutamate production, and signaling pathways. These results indicate that EOAD, although sharing many genes with LOAD, harbors unique genes and pathways that could be used to create better prediction models or target identification for this type of AD.
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Affiliation(s)
| | | | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | | | | | | | | | | | | | | | | | | | | | | | - Michael Cuccaro
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida
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Gouveia Roque C, Phatnani H, Hengst U. The broken Alzheimer's disease genome. CELL GENOMICS 2024; 4:100555. [PMID: 38697121 PMCID: PMC11099344 DOI: 10.1016/j.xgen.2024.100555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 02/25/2024] [Accepted: 04/07/2024] [Indexed: 05/04/2024]
Abstract
The complex pathobiology of late-onset Alzheimer's disease (AD) poses significant challenges to therapeutic and preventative interventions. Despite these difficulties, genomics and related disciplines are allowing fundamental mechanistic insights to emerge with clarity, particularly with the introduction of high-resolution sequencing technologies. After all, the disrupted processes at the interface between DNA and gene expression, which we call the broken AD genome, offer detailed quantitative evidence unrestrained by preconceived notions about the disease. In addition to highlighting biological pathways beyond the classical pathology hallmarks, these advances have revitalized drug discovery efforts and are driving improvements in clinical tools. We review genetic, epigenomic, and gene expression findings related to AD pathogenesis and explore how their integration enables a better understanding of the multicellular imbalances contributing to this heterogeneous condition. The frontiers opening on the back of these research milestones promise a future of AD care that is both more personalized and predictive.
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Affiliation(s)
- Cláudio Gouveia Roque
- Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY 10013, USA; The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
| | - Hemali Phatnani
- Center for Genomics of Neurodegenerative Disease, New York Genome Center, New York, NY 10013, USA; Department of Neurology, Center for Translational and Computational Neuroimmunology, Columbia University, New York, NY 10032, USA
| | - Ulrich Hengst
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA; Department of Pathology & Cell Biology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY 10032, USA.
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11
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Lee S, Hecker J, Hahn G, Mullin K, Lutz SM, Tanzi RE, Lange C, Prokopenko D. On the effect heterogeneity of established disease susceptibility loci for Alzheimer's disease across different genetic ancestries. Alzheimers Dement 2024; 20:3397-3405. [PMID: 38563508 PMCID: PMC11095441 DOI: 10.1002/alz.13796] [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: 11/17/2023] [Revised: 02/14/2024] [Accepted: 02/23/2024] [Indexed: 04/04/2024]
Abstract
INTRODUCTION Genome-wide association studies have identified numerous disease susceptibility loci (DSLs) for Alzheimer's disease (AD). However, only a limited number of studies have investigated the dependence of the genetic effect size of established DSLs on genetic ancestry. METHODS We utilized the whole genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP) including 35,569 participants. A total of 25,459 subjects in four distinct populations (African ancestry, non-Hispanic White, admixed Hispanic, and Asian) were analyzed. RESULTS We found that nine DSLs showed significant heterogeneity across populations. Single nucleotide polymorphism (SNP) rs2075650 in translocase of outer mitochondrial membrane 40 (TOMM40) showed the largest heterogeneity (Cochran's Q = 0.00, I2 = 90.08), followed by other SNPs in apolipoprotein C1 (APOC1) and apolipoprotein E (APOE). Two additional loci, signal-induced proliferation-associated 1 like 2 (SIPA1L2) and solute carrier 24 member 4 (SLC24A4), showed significant heterogeneity across populations. DISCUSSION We observed substantial heterogeneity for the APOE-harboring 19q13.32 region with TOMM40/APOE/APOC1 genes. The largest risk effect was seen among African Americans, while Asians showed a surprisingly small risk effect.
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Affiliation(s)
- Sanghun Lee
- Department of Medical Consilience, Division of Medicine, Graduate school, Dankook University, Yongin-si, Gyeonggi-do, South Korea
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Julian Hecker
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Georg Hahn
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Kristina Mullin
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Sharon M Lutz
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Healthcare Institute, Boston, Massachusetts, USA
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Christoph Lange
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
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Andrews SJ, Jonson C, Fulton-Howard B, Renton AE, Yokoyama JS, Yaffe K. The Role of Genomic-Informed Risk Assessments in Predicting Dementia Outcomes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.27.24306488. [PMID: 38903124 PMCID: PMC11188112 DOI: 10.1101/2024.04.27.24306488] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/22/2024]
Abstract
Importance By integrating genetic and clinical risk factors into genomic-informed dementia risk reports, healthcare providers can offer patients detailed risk profiles to facilitate understanding of individual risk and support the implementation of personalized strategies for promoting brain health. Objective To develop a genomic-informed risk assessment composed of family history, genetic, and clinical risk factors and, in turn, evaluate how the risk assessment predicted incident dementia. Design This longitudinal study included data from two clinical case-control cohorts with an average of 6.6 visits. Secondary analyses were conducted from July 2023 - March 2024. Setting Data were previously collected across multiple US locations from 1994 to 2023. Participants Older adults aged 55+ with whole-genome sequencing and dementia-free at baseline. Exposures An additive score comprising the modified Cardiovascular Risk Factors, Aging, and Incidence of Dementia Risk Score (mCAIDE), family history of dementia, APOE genotype, and an AD polygenic risk score. Main Outcomes and Measures The risk of progression to all-cause dementia was evaluated using Cox-proportional hazard models (hazard ratios with 95% confidence intervals [OR 9%CI]). Results A total of 3,429 older adults were included (aged 75 ± 7 years; 59% female; 75% non-Latino White, 15% Black, 5.2% Latino, 3.6% other, and 0.4% Asian; 27% MCI), with 751 participants progressing to dementia. The most common high-risk indicator was a family history of dementia (56%), followed by APOE*ε4 genotype (36%), high mCAIDE score (34%), and high AD-PRS (11%). Most participants had at least one high-risk indicator, with 39% having one, 32% two, 9.8% three, and 1% four. The presence of 1, 2, 3, or 4 risk indicators was associated with a doubling (HR = 1.72, CI: 1.34-2.22, p = 2.5e-05), tripling (HR = 3.09, CI: 2.41-3.95, p = 4.4e-19), quadrupling (HR = 4.46, CI: 3.34-5.94, p = 2.2e-24), and a twelvefold increase (HR = 12.15, CI: 7.33-20.14, p = 3.2e-22) in dementia risk. Conclusion & Relevance We found that most participants in memory and aging clinics had at least one high-risk indicator for dementia. Furthermore, we observed a dose-response relationship where a greater number of risk indicators was associated with an increased risk of incident dementia.
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Affiliation(s)
- Shea J. Andrews
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, USA
| | - Caroline Jonson
- Department of Neurology, University of California San Francisco, San Francisco, USA
- Center for Alzheimer’s and Related Dementias, National Institutes of Health, Bethesda, MD USA 20892
- DataTecnica LLC, Washington, DC USA 20037
| | - Brian Fulton-Howard
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Alan E Renton
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Jennifer S Yokoyama
- Department of Neurology, University of California San Francisco, San Francisco, USA
| | - Kristine Yaffe
- Department of Psychiatry and Behavioral Sciences, University of California San Francisco, San Francisco, USA
- Department of Neurology, University of California San Francisco, San Francisco, USA
- Department of Epidemiology and Biostatistics, University of California
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Seifar F, Fox EJ, Shantaraman A, Liu Y, Dammer EB, Modeste E, Duong DM, Yin L, Trautwig AN, Guo Q, Xu K, Ping L, Reddy JS, Allen M, Quicksall Z, Heath L, Scanlan J, Wang E, Wang M, Linden AV, Poehlman W, Chen X, Baheti S, Ho C, Nguyen T, Yepez G, Mitchell AO, Oatman SR, Wang X, Carrasquillo MM, Runnels A, Beach T, Serrano GE, Dickson DW, Lee EB, Golde TE, Prokop S, Barnes LL, Zhang B, Haroutunian V, Gearing M, Lah JJ, Jager PD, Bennett DA, Greenwood A, Ertekin-Taner N, Levey AI, Wingo A, Wingo T, Seyfried NT. Large-scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.22.590547. [PMID: 38712030 PMCID: PMC11071432 DOI: 10.1101/2024.04.22.590547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Introduction Alzheimer's disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups. Methods Dorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS). Results As a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals. Discussion This comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.
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Affiliation(s)
| | - Edward J Fox
- Emory University School of Medicine, Atlanta, GA USA
| | | | - Yue Liu
- Emory University School of Medicine, Atlanta, GA USA
| | - Eric B Dammer
- Emory University School of Medicine, Atlanta, GA USA
| | - Erica Modeste
- Emory University School of Medicine, Atlanta, GA USA
| | - Duc M Duong
- Emory University School of Medicine, Atlanta, GA USA
| | - Luming Yin
- Emory University School of Medicine, Atlanta, GA USA
| | | | - Qi Guo
- Emory University School of Medicine, Atlanta, GA USA
| | - Kaiming Xu
- Emory University School of Medicine, Atlanta, GA USA
| | - Lingyan Ping
- Emory University School of Medicine, Atlanta, GA USA
| | - Joseph S Reddy
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Mariet Allen
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Zachary Quicksall
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | | | | | - Erming Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | | | | | - Xianfeng Chen
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Saurabh Baheti
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Charlotte Ho
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Thuy Nguyen
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Geovanna Yepez
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | | | | | - Xue Wang
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | | | | | - Thomas Beach
- Banner Sun Health Research Institute, Sun City, AR USA
| | | | - Dennis W Dickson
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
| | - Edward B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelpha, PA, USA
| | - Todd E Golde
- Emory University School of Medicine, Atlanta, GA USA
| | | | - Lisa L Barnes
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Varham Haroutunian
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY USA
| | - Marla Gearing
- Emory University School of Medicine, Atlanta, GA USA
| | - James J Lah
- Emory University School of Medicine, Atlanta, GA USA
| | | | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL USA
| | | | - Nilüfer Ertekin-Taner
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL USA
- Mayo Clinic Florida, Department of Neurology, Jacksonville, FL USA
| | - Allan I Levey
- Emory University School of Medicine, Atlanta, GA USA
| | - Aliza Wingo
- Emory University School of Medicine, Atlanta, GA USA
| | - Thomas Wingo
- Emory University School of Medicine, Atlanta, GA USA
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Brase L, Yu Y, McDade E, Harari O, Benitez BA. Comparative gene regulatory networks modulating APOE expression in microglia and astrocytes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.19.24306098. [PMID: 38699303 PMCID: PMC11065001 DOI: 10.1101/2024.04.19.24306098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
Background Single-cell technologies have unveiled various transcriptional states in different brain cell types. Transcription factors (TFs) regulate the expression of related gene sets, thereby controlling these diverse expression states. Apolipoprotein E ( APOE ), a pivotal risk-modifying gene in Alzheimer's disease (AD), is expressed in specific glial transcriptional states associated with AD. However, it is still unknown whether the upstream regulatory programs that modulate its expression are shared across brain cell types or specific to microglia and astrocytes. Methods We used pySCENIC to construct state-specific gene regulatory networks (GRNs) for resting and activated cell states within microglia and astrocytes based on single-nucleus RNA sequencing data from AD patients' cortices from the Knight ADRC-DIAN cohort. We then identified replicating TF using data from the ROSMAP cohort. We identified sets of genes co-regulated with APOE by clustering the GRN target genes and identifying genes differentially expressed after the virtual knockout of TFs regulating APOE . We performed enrichment analyses on these gene sets and evaluated their overlap with genes found in AD GWAS loci. Results We identified an average of 96 replicating regulators for each microglial and astrocyte cell state. Our analysis identified the CEBP, JUN, FOS, and FOXO TF families as key regulators of microglial APOE expression. The steroid/thyroid hormone receptor families, including the THR TF family, consistently regulated APOE across astrocyte states, while CEBP and JUN TF families were also involved in resting astrocytes. AD GWAS-associated genes ( PGRN , FCGR3A , CTSH , ABCA1 , MARCKS , CTSB , SQSTM1 , TSC22D4 , FCER1G , and HLA genes) are co-regulated with APOE. We also uncovered that APOE-regulating TFs were linked to circadian rhythm ( BHLHE40 , DBP , XBP1 , CREM , SREBF1 , FOXO3 , and NR2F1 ). Conclusions Our findings reveal a novel perspective on the transcriptional regulation of APOE in the human brain. We found a comprehensive and cell-type-specific regulatory landscape for APOE , revealing distinct and shared regulatory mechanisms across microglia and astrocytes, underscoring the complexity of APOE regulation. APOE -co-regulated genes might also affect AD risk. Furthermore, our study uncovers a potential link between circadian rhythm disruption and APOE regulation, shedding new light on the pathogenesis of AD.
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15
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Reddy JS, Heath L, Vander Linden A, Allen M, de Paiva Lopes K, Seifar F, Wang E, Ma Y, Poehlman WL, Quicksall ZS, Runnels A, Wang Y, Duong DM, Yin L, Xu K, Modeste ES, Shantaraman A, Dammer EB, Ping L, Oatman SR, Scanlan J, Ho C, Carrasquillo MM, Atik M, Yepez G, Mitchell AO, Nguyen TT, Chen X, Marquez DX, Reddy H, Xiao H, Seshadri S, Mayeux R, Prokop S, Lee EB, Serrano GE, Beach TG, Teich AF, Haroutunian V, Fox EJ, Gearing M, Wingo A, Wingo T, Lah JJ, Levey AI, Dickson DW, Barnes LL, De Jager P, Zhang B, Bennett D, Seyfried NT, Greenwood AK, Ertekin-Taner N. Bridging the Gap: Multi-Omics Profiling of Brain Tissue in Alzheimer's Disease and Older Controls in Multi-Ethnic Populations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.16.589592. [PMID: 38659743 PMCID: PMC11042309 DOI: 10.1101/2024.04.16.589592] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
INTRODUCTION Multi-omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked African Americans (AA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS To bridge this gap, Accelerating Medicines Partnership in AD (AMP-AD) expanded brain multi-omics profiling to multi-ethnic donors. RESULTS We generated multi-omics data and curated and harmonized phenotypic data from AA (n=306), LA (n=326), or AA and LA (n=4) brain donors plus Non-Hispanic White (n=252) and other (n=20) ethnic groups, to establish a foundational dataset enriched for AA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION Inclusion of traditionally underrepresented groups in multi-omics studies is essential to discover the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD.
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Affiliation(s)
- Joseph S Reddy
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Laura Heath
- Sage Bionetworks, 2901 3rd Ave #330, Seattle, WA 98121
| | | | - Mariet Allen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Katia de Paiva Lopes
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Fatemeh Seifar
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Erming Wang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029
| | - Yiyi Ma
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | | | | | - Alexi Runnels
- New York Genome Center, 101 6th Ave, New York, NY 10013
| | - Yanling Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Duc M Duong
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Luming Yin
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Kaiming Xu
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Erica S Modeste
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | | | - Eric B Dammer
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Lingyan Ping
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | | | - Jo Scanlan
- Sage Bionetworks, 2901 3rd Ave #330, Seattle, WA 98121
| | - Charlotte Ho
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | | | - Merve Atik
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Geovanna Yepez
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | | | - Thuy T Nguyen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Xianfeng Chen
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - David X Marquez
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
- University of Illinois Chicago, 1200 West Harrison St., Chicago, Illinois 60607
| | - Hasini Reddy
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Harrison Xiao
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Sudha Seshadri
- The Glen Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas, 8300 Floyd Curl Drive, San Antonio TX 78229
| | - Richard Mayeux
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | | | - Edward B Lee
- Center for Neurodegenerative Disease Brain Bank at the University of Pennsylvania, 3600 Spruce Street, Philadelphia, PA 19104-2676
| | - Geidy E Serrano
- Banner Sun Health Research Institute, 10515 W Santa Fe Dr, Sun City, AZ 85351
| | - Thomas G Beach
- Banner Sun Health Research Institute, 10515 W Santa Fe Dr, Sun City, AZ 85351
| | - Andrew F Teich
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Varham Haroutunian
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
| | - Edward J Fox
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Marla Gearing
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Aliza Wingo
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Thomas Wingo
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - James J Lah
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Allan I Levey
- Emory University School of Medicine, 1440 Clifton Rd, Atlanta, GA 30322
| | - Dennis W Dickson
- Mayo Clinic Florida, 4500 San Pablo Rd S, Jacksonville, FL 32224
| | - Lisa L Barnes
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
| | - Philip De Jager
- Columbia University Irving Medical Center, 622 W 168th St, New York, NY 10032
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, 1428 Madison Ave, New York, NY 10029
- Mount Sinai Center for Transformative Disease Modeling, Icahn School of Medicine at Mount Sinai, 1 Gustave L. Levy Pl, New York, NY 10029
| | - David Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison St, Chicago, IL 60612
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Gao S, Wang T, Han Z, Hu Y, Zhu P, Xue Y, Huang C, Chen Y, Liu G. Interpretation of 10 years of Alzheimer's disease genetic findings in the perspective of statistical heterogeneity. Brief Bioinform 2024; 25:bbae140. [PMID: 38711368 PMCID: PMC11074593 DOI: 10.1093/bib/bbae140] [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: 08/21/2023] [Revised: 02/22/2024] [Accepted: 03/14/2024] [Indexed: 05/08/2024] Open
Abstract
Common genetic variants and susceptibility loci associated with Alzheimer's disease (AD) have been discovered through large-scale genome-wide association studies (GWAS), GWAS by proxy (GWAX) and meta-analysis of GWAS and GWAX (GWAS+GWAX). However, due to the very low repeatability of AD susceptibility loci and the low heritability of AD, these AD genetic findings have been questioned. We summarize AD genetic findings from the past 10 years and provide a new interpretation of these findings in the context of statistical heterogeneity. We discovered that only 17% of AD risk loci demonstrated reproducibility with a genome-wide significance of P < 5.00E-08 across all AD GWAS and GWAS+GWAX datasets. We highlighted that the AD GWAS+GWAX with the largest sample size failed to identify the most significant signals, the maximum number of genome-wide significant genetic variants or maximum heritability. Additionally, we identified widespread statistical heterogeneity in AD GWAS+GWAX datasets, but not in AD GWAS datasets. We consider that statistical heterogeneity may have attenuated the statistical power in AD GWAS+GWAX and may contribute to explaining the low repeatability (17%) of genome-wide significant AD susceptibility loci and the decreased AD heritability (40-2%) as the sample size increased. Importantly, evidence supports the idea that a decrease in statistical heterogeneity facilitates the identification of genome-wide significant genetic loci and contributes to an increase in AD heritability. Collectively, current AD GWAX and GWAS+GWAX findings should be meticulously assessed and warrant additional investigation, and AD GWAS+GWAX should employ multiple meta-analysis methods, such as random-effects inverse variance-weighted meta-analysis, which is designed specifically for statistical heterogeneity.
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Affiliation(s)
- Shan Gao
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, No. 10, Xitoutiao, You’an Men Wai, Fengtai District, Beijing 100069, China
| | - Tao Wang
- Chinese Institute for Brain Research, No. 26, Kexueyuan Road, Changping District, Beijing 102206, China
| | - Zhifa Han
- State Key Laboratory of Medical Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, No. 5, Dongdan Santichao, Dongcheng District, Beijing 100193, China
| | - Yang Hu
- School of Computer Science and Technology, Harbin Institute of Technology, No. 92, Xidazhi Street, Nangang District, Harbin 150006, China
| | - Ping Zhu
- Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, No. 10, Xitoutiao, You’an Men Wai, Fengtai District, Beijing 100069, China
| | - Yanli Xue
- School of Biomedical Engineering, Capital Medical University, No. 10 Xitoutiao, You'an Men Wai, Fengtai District, Beijing 100069, China
| | - Chen Huang
- Dr. Neher’s Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Avenida WaiLong, Taipa 999078, Macao SAR, China
| | - Yan Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
- Institute of Chronic Disease Prevention and Control, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
| | - Guiyou Liu
- Chinese Institute for Brain Research, No. 26, Kexueyuan Road, Changping District, Beijing 102206, China
- Department of Epidemiology and Biostatistics, School of Public Health, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
- Institute of Chronic Disease Prevention and Control, Wannan Medical College, No. 22, Wenchang Road, Wuhu 241002, Anhui, China
- Key Laboratory of Cerebral Microcirculation in Universities of Shandong, Department of Neurology, Second Affiliated Hospital, Shandong First Medical University and Shandong Academy of Medical Sciences, Taian 271000, Shandong, China
- Beijing Key Laboratory of Hypoxia Translational Medicine, National Engineering Laboratory of Internet Medical Diagnosis and Treatment Technology, Xuanwu Hospital, Capital Medical University, No. 45, Changchun Road, Xicheng District, Beijing 100053, China
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Podleśny-Drabiniok A, Novikova G, Liu Y, Dunst J, Temizer R, Giannarelli C, Marro S, Kreslavsky T, Marcora E, Goate AM. BHLHE40/41 regulate microglia and peripheral macrophage responses associated with Alzheimer's disease and other disorders of lipid-rich tissues. Nat Commun 2024; 15:2058. [PMID: 38448474 PMCID: PMC10917780 DOI: 10.1038/s41467-024-46315-7] [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: 02/10/2023] [Accepted: 02/16/2024] [Indexed: 03/08/2024] Open
Abstract
Genetic and experimental evidence suggests that Alzheimer's disease (AD) risk alleles and genes may influence disease susceptibility by altering the transcriptional and cellular responses of macrophages, including microglia, to damage of lipid-rich tissues like the brain. Recently, sc/nRNA sequencing studies identified similar transcriptional activation states in subpopulations of macrophages in aging and degenerating brains and in other diseased lipid-rich tissues. We collectively refer to these subpopulations of microglia and peripheral macrophages as DLAMs. Using macrophage sc/nRNA-seq data from healthy and diseased human and mouse lipid-rich tissues, we reconstructed gene regulatory networks and identified 11 strong candidate transcriptional regulators of the DLAM response across species. Loss or reduction of two of these transcription factors, BHLHE40/41, in iPSC-derived microglia and human THP-1 macrophages as well as loss of Bhlhe40/41 in mouse microglia, resulted in increased expression of DLAM genes involved in cholesterol clearance and lysosomal processing, increased cholesterol efflux and storage, and increased lysosomal mass and degradative capacity. These findings provide targets for therapeutic modulation of macrophage/microglial function in AD and other disorders affecting lipid-rich tissues.
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Affiliation(s)
- Anna Podleśny-Drabiniok
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Gloriia Novikova
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- OMNI Bioinformatics Department, Genentech, Inc., South San Francisco, CA, USA
| | - Yiyuan Liu
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Josefine Dunst
- Department of Medicine, Division of Immunology and Allergy, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Rose Temizer
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Chiara Giannarelli
- Department of Medicine, Division of Cardiology, NYU Cardiovascular Research Center, New York University School of Medicine, New York, NY, USA
- Department of Pathology, New York University School of Medicine, New York, NY, USA
| | - Samuele Marro
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Taras Kreslavsky
- Department of Medicine, Division of Immunology and Allergy, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden
- Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Edoardo Marcora
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Alison Mary Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Nash Family Department of Neuroscience, Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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Rao Y, Peng B. Allogenic microglia replacement: A novel therapeutic strategy for neurological disorders. FUNDAMENTAL RESEARCH 2024; 4:237-245. [PMID: 38933508 PMCID: PMC11197774 DOI: 10.1016/j.fmre.2023.02.025] [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: 09/17/2022] [Revised: 11/17/2022] [Accepted: 02/19/2023] [Indexed: 03/29/2023] Open
Abstract
Microglia are resident immune cells in the central nervous system (CNS) that play vital roles in CNS development, homeostasis and disease pathogenesis. Genetic defects in microglia lead to microglial dysfunction, which in turn leads to neurological disorders. The correction of the specific genetic defects in microglia in these disorders can lead to therapeutic effects. Traditional genetic defect correction approaches are dependent on viral vector-based genetic defect corrections. However, the viruses used in these approaches, including adeno-associated viruses, lentiviruses and retroviruses, do not primarily target microglia; therefore, viral vector-based genetic defect corrections are ineffective in microglia. Microglia replacement is a novel approach to correct microglial genetic defects via replacing microglia of genetic defects with allogenic healthy microglia. In this paper, we systematically review the history, rationale and therapeutic perspectives of microglia replacement, which would be a novel strategy for treating CNS disorders.
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Affiliation(s)
- Yanxia Rao
- Department of Laboratory Animal Science, MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200032, China
| | - Bo Peng
- Department of Neurosurgery, Huashan Hospital, Institute for Translational Brain Research, State Key Laboratory of Medical Neurobiology, MOE Frontiers Center for Brain Science, MOE Innovative Center for New Drug Development of Immune Inflammatory Diseases, Fudan University, Shanghai 200000, China
- Co-Innovation Center of Neuroregeneration, Nantong University, Nantong, Jiangsu 226001, China
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Cheng F, Wang F, Tang J, Zhou Y, Fu Z, Zhang P, Haines JL, Leverenz JB, Gan L, Hu J, Rosen-Zvi M, Pieper AA, Cummings J. Artificial intelligence and open science in discovery of disease-modifying medicines for Alzheimer's disease. Cell Rep Med 2024; 5:101379. [PMID: 38382465 PMCID: PMC10897520 DOI: 10.1016/j.xcrm.2023.101379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Revised: 08/15/2023] [Accepted: 12/19/2023] [Indexed: 02/23/2024]
Abstract
The high failure rate of clinical trials in Alzheimer's disease (AD) and AD-related dementia (ADRD) is due to a lack of understanding of the pathophysiology of disease, and this deficit may be addressed by applying artificial intelligence (AI) to "big data" to rapidly and effectively expand therapeutic development efforts. Recent accelerations in computing power and availability of big data, including electronic health records and multi-omics profiles, have converged to provide opportunities for scientific discovery and treatment development. Here, we review the potential utility of applying AI approaches to big data for discovery of disease-modifying medicines for AD/ADRD. We illustrate how AI tools can be applied to the AD/ADRD drug development pipeline through collaborative efforts among neurologists, gerontologists, geneticists, pharmacologists, medicinal chemists, and computational scientists. AI and open data science expedite drug discovery and development of disease-modifying therapeutics for AD/ADRD and other neurodegenerative diseases.
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Affiliation(s)
- Feixiong Cheng
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; Department of Molecular Medicine, Cleveland Clinic Lerner College of Medicine, Case Western Reserve University, Cleveland, OH 44195, USA.
| | - Fei Wang
- Department of Population Health Sciences, Weill Cornell Medical College, Cornell University, New York, NY 10065, USA
| | - Jian Tang
- Mila-Quebec Institute for Learning Algorithms and CIFAR AI Research Chair, HEC Montreal, Montréal, QC H3T 2A7, Canada
| | - Yadi Zhou
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Zhimin Fu
- Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH 44195, USA; College of Pharmacy, Northeast Ohio Medical University, Rootstown, OH 44272, USA
| | - Pengyue Zhang
- Department of Biostatistics and Health Data Science, Indiana University, Indianapolis, IN 46037, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, and Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Neurological Institute, Cleveland Clinic, Cleveland, OH 44195, USA
| | - Li Gan
- Helen and Robert Appel Alzheimer's Disease Research Institute, Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY 10021, USA
| | - Jianying Hu
- IBM Research, Yorktown Heights, New York, NY 10598, USA
| | - Michal Rosen-Zvi
- AI for Accelerated Healthcare and Life Sciences Discovery, IBM Research Labs, Haifa 3498825, Israel; Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 9190500, Israel
| | - Andrew A Pieper
- Brain Health Medicines Center, Harrington Discovery Institute, University Hospitals Cleveland Medical Center, Cleveland, OH, 44106, USA; Department of Psychiatry, Case Western Reserve University, Cleveland, OH 44106, USA; Geriatric Psychiatry, GRECC, Louis Stokes Cleveland VA Medical Center, Cleveland, OH 44106, USA; Institute for Transformative Molecular Medicine, School of Medicine, Case Western Reserve University, Cleveland OH 44106, USA; Department of Pathology, Case Western Reserve University, School of Medicine, Cleveland, OH, 44106, USA; Department of Neurosciences, Case Western Reserve University, School of Medicine, Cleveland, OH 44106, USA
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, UNLV, Las Vegas, NV 89154, USA
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20
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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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21
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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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Dalmasso MC, de Rojas I, Olivar N, Muchnik C, Angel B, Gloger S, Sanchez Abalos MS, Chacón MV, Aránguiz R, Orellana P, Cuesta C, Galeano P, Campanelli L, Novack GV, Martinez LE, Medel N, Lisso J, Sevillano Z, Irureta N, Castaño EM, Montrreal L, Thoenes M, Hanses C, Heilmann‐Heimbach S, Kairiyama C, Mintz I, Villella I, Rueda F, Romero A, Wukitsevits N, Quiroga I, Gona C, Lambert J, Solis P, Politis DG, Mangone CA, Gonzalez‐Billault C, Boada M, Tàrraga L, Slachevsky A, Albala C, Fuentes P, Kochen S, Brusco LI, Ruiz A, Morelli L, Ramírez A. The first genome-wide association study in the Argentinian and Chilean populations identifies shared genetics with Europeans in Alzheimer's disease. Alzheimers Dement 2024; 20:1298-1308. [PMID: 37985413 PMCID: PMC10917041 DOI: 10.1002/alz.13522] [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: 01/22/2023] [Revised: 09/28/2023] [Accepted: 10/01/2023] [Indexed: 11/22/2023]
Abstract
INTRODUCTION Genome-wide association studies (GWAS) are fundamental for identifying loci associated with diseases. However, they require replication in other ethnicities. METHODS We performed GWAS on sporadic Alzheimer's disease (AD) including 539 patients and 854 controls from Argentina and Chile. We combined our results with those from the European Alzheimer and Dementia Biobank (EADB) in a meta-analysis and tested their genetic risk score (GRS) performance in this admixed population. RESULTS We detected apolipoprotein E ε4 as the single genome-wide significant signal (odds ratio = 2.93 [2.37-3.63], P = 2.6 × 10-23 ). The meta-analysis with EADB summary statistics revealed four new loci reaching GWAS significance. Functional annotations of these loci implicated endosome/lysosomal function. Finally, the AD-GRS presented a similar performance in these populations, despite the score diminished when the Native American ancestry rose. DISCUSSION We report the first GWAS on AD in a population from South America. It shows shared genetics modulating AD risk between the European and these admixed populations. HIGHLIGHTS This is the first genome-wide association study on Alzheimer's disease (AD) in a population sample from Argentina and Chile. Trans-ethnic meta-analysis reveals four new loci involving lysosomal function in AD. This is the first independent replication for TREM2L, IGH-gene-cluster, and ADAM17 loci. A genetic risk score (GRS) developed in Europeans performed well in this population. The higher the Native American ancestry the lower the GRS values.
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Affiliation(s)
| | - Itziar de Rojas
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative DiseasesNational Institute of Health Carlos IIIMadridSpain
| | - Natividad Olivar
- Center of Neuropsychiatry and Neurology of BehaviorSchool of MedicineUniversity of Buenos AiresBuenos AiresArgentina
| | - Carolina Muchnik
- Center of Neuropsychiatry and Neurology of BehaviorSchool of MedicineUniversity of Buenos AiresBuenos AiresArgentina
| | - Bárbara Angel
- Public Health Nutrition UnitInstitute of Nutrition and Food TechnologyUniversity of ChileSantiagoChile
- Interuniversity Center for Healthy Aging RED21993SantiagoChile
| | - Sergio Gloger
- Biomedica Research GroupCentro de Estudios ClínicosSantiagoChile
- Departamento de Psiquiatría y Salud MentalCampus Oriente, Facultad de MedicinaUniversidad de ChileSantiagoChile
| | | | | | - Rafael Aránguiz
- Biomedica Research GroupCentro de Estudios ClínicosSantiagoChile
- Instituto Nacional de GeriatríaSantiagoChile
| | - Paulina Orellana
- Geroscience Center for Brain Health and MetabolismSantiagoChile
- Latin American Institute for Brain Health (BrainLat)Universidad Adolfo IbanezSantiagoChile
- Center for Social and Cognitive Neuroscience (CSCN)School of PsychologyUniversidad Adolfo IbanezSantiagoChile
| | - Carolina Cuesta
- Hospital Interzonal General de Agudos‐Eva PerónSan MartínArgentina
| | - Pablo Galeano
- Laboratory of Brain Aging and Neurodegeneration, Fundacion Instituto Leloir‐IIBBABuenos AiresArgentina
| | - Lorenzo Campanelli
- Laboratory of Brain Aging and Neurodegeneration, Fundacion Instituto Leloir‐IIBBABuenos AiresArgentina
| | - Gisela Vanina Novack
- Laboratory of Brain Aging and Neurodegeneration, Fundacion Instituto Leloir‐IIBBABuenos AiresArgentina
| | | | - Nancy Medel
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Julieta Lisso
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Zulma Sevillano
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Nicolás Irureta
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Eduardo Miguel Castaño
- Laboratory of Brain Aging and Neurodegeneration, Fundacion Instituto Leloir‐IIBBABuenos AiresArgentina
| | - Laura Montrreal
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
| | - Michaela Thoenes
- Division of Neurogenetics and Molecular PsychiatryDepartment of Psychiatry and PsychotherapyFaculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany
| | - Claudia Hanses
- Department of Psychiatry and PsychotherapyUniversity Hospital of BonnBonnGermany
| | | | | | - Inés Mintz
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Ivana Villella
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Fabiana Rueda
- Imaging Diagnostics ServiceHospital El CruceFlorencio VarelaArgentina
| | - Amanda Romero
- Imaging Diagnostics ServiceHospital El CruceFlorencio VarelaArgentina
| | - Nancy Wukitsevits
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Ivana Quiroga
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Cristian Gona
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | - Jean‐Charles Lambert
- Université de Lille, INSERM, CHU Lille, Institut Pasteur Lille, U1167‐RID‐AGE, Facteurs de risque et déterminants moléculaires des maladies liées au vieillissementLilleFrance
| | - Patricia Solis
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
- Asistencia Medica IntegralHospital El CruceFlorencio VarelaArgentina
| | | | | | - Christian Gonzalez‐Billault
- Geroscience Center for Brain Health and MetabolismSantiagoChile
- Faculty of SciencesUniversity of ChileSantiagoChile
| | - Mercè Boada
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative DiseasesNational Institute of Health Carlos IIIMadridSpain
| | - Lluís Tàrraga
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative DiseasesNational Institute of Health Carlos IIIMadridSpain
| | - Andrea Slachevsky
- Faculty of SciencesUniversity of ChileSantiagoChile
- Neuropsychology and Clinical Neuroscience Laboratory (LANNEC)Physiopathology Department ‐ Intitute of Biomedical Sciences (ICBM)Neuroscience and East Neuroscience DepartmentsFaculty of MedicineUniversity of ChileSantiagoChile
- Memory and Neuropsychiatric Center (CMYN)Memory Unit ‐ Neurology DepartmentHospital del Salvador and Faculty of MedicineUniversity of ChileSantiagoChile
- Departamento de Neurología y PsiquiatríaClínica Alemana‐Universidad del DesarrolloSantiagoChile
| | - Cecilia Albala
- Public Health Nutrition UnitInstitute of Nutrition and Food TechnologyUniversity of ChileSantiagoChile
- Interuniversity Center for Healthy Aging RED21993SantiagoChile
| | - Patricio Fuentes
- Geriatrics Section Clinical Hospital University of ChileSantiagoChile
- Neurology Service Hospital del SalvadorSantiagoChile
| | - Silvia Kochen
- Studies in Neuroscience and Complex Systems Unit‐CONICET‐HEC‐UNAJFlorencio VarelaArgentina
| | - Luis Ignacio Brusco
- Center of Neuropsychiatry and Neurology of BehaviorSchool of MedicineUniversity of Buenos AiresBuenos AiresArgentina
| | - Agustín Ruiz
- Research Center and Memory Clinic, Ace Alzheimer Center Barcelona – Universitat Internacional de CatalunyaBarcelonaSpain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative DiseasesNational Institute of Health Carlos IIIMadridSpain
| | - Laura Morelli
- Laboratory of Brain Aging and Neurodegeneration, Fundacion Instituto Leloir‐IIBBABuenos AiresArgentina
| | - Alfredo Ramírez
- Division of Neurogenetics and Molecular PsychiatryDepartment of Psychiatry and PsychotherapyFaculty of Medicine and University Hospital CologneUniversity of CologneCologneGermany
- University of Bonn Medical CenterDepartment of Neurodegenerative Disease and Geriatric PsychiatryBonnGermany
- German Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Excellence Cluster on Cellular Stress Responses in Aging‐Associated Diseases (CECAD)University of CologneCologneGermany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative DiseasesSan AntonioTexasUSA
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Eissman JM, Archer DB, Mukherjee S, Lee ML, Choi S, Scollard P, Trittschuh EH, Mez JB, Bush WS, Kunkle BW, Naj AC, Gifford KA, Cuccaro ML, Cruchaga C, Pericak‐Vance MA, Farrer LA, Wang L, Schellenberg GD, Mayeux RP, Haines JL, Jefferson AL, Kukull WA, Keene CD, Saykin AJ, Thompson PM, Martin ER, Bennett DA, Barnes LL, Schneider JA, Crane PK, Hohman TJ, Dumitrescu L. Sex-specific genetic architecture of late-life memory performance. Alzheimers Dement 2024; 20:1250-1267. [PMID: 37984853 PMCID: PMC10917043 DOI: 10.1002/alz.13507] [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: 04/04/2023] [Revised: 08/08/2023] [Accepted: 09/07/2023] [Indexed: 11/22/2023]
Abstract
BACKGROUND Women demonstrate a memory advantage when cognitively healthy yet lose this advantage to men in Alzheimer's disease. However, the genetic underpinnings of this sex difference in memory performance remain unclear. METHODS We conducted the largest sex-aware genetic study on late-life memory to date (Nmales = 11,942; Nfemales = 15,641). Leveraging harmonized memory composite scores from four cohorts of cognitive aging and AD, we performed sex-stratified and sex-interaction genome-wide association studies in 24,216 non-Hispanic White and 3367 non-Hispanic Black participants. RESULTS We identified three sex-specific loci (rs67099044-CBLN2, rs719070-SCHIP1/IQCJ-SCHIP), including an X-chromosome locus (rs5935633-EGL6/TCEANC/OFD1), that associated with memory. Additionally, we identified heparan sulfate signaling as a sex-specific pathway and found sex-specific genetic correlations between memory and cardiovascular, immune, and education traits. DISCUSSION This study showed memory is highly and comparably heritable across sexes, as well as highlighted novel sex-specific genes, pathways, and genetic correlations that related to late-life memory. HIGHLIGHTS Demonstrated the heritable component of late-life memory is similar across sexes. Identified two genetic loci with a sex-interaction with baseline memory. Identified an X-chromosome locus associated with memory decline in females. Highlighted sex-specific candidate genes and pathways associated with memory. Revealed sex-specific shared genetic architecture between memory and complex traits.
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Grill JD, Flournoy C, Dhadda S, Ernstrom K, Sperling R, Molina-Henry D, Tranotti K, Harris R, Kanekiyo M, Gee M, Irizarry M, Kramer L, Aisen P, Raman R. Eligibility Rates among Racially and Ethnically Diverse US Participants in Phase 2 and Phase 3 Placebo-Controlled, Double-Blind, Randomized Trials of Lecanemab and Elenbecestat in Early Alzheimer Disease. Ann Neurol 2024; 95:288-298. [PMID: 37830926 DOI: 10.1002/ana.26819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2023] [Revised: 10/08/2023] [Accepted: 10/09/2023] [Indexed: 10/14/2023]
Abstract
OBJECTIVE Many factors contribute to inadequate diversity in Alzheimer disease (AD) clinical trials. We evaluated eligibility rates among racial and ethnic groups at US sites in large global multisite trials in early AD. METHODS Using screening data from 4 randomized, double-blind, placebo-controlled clinical trials in early AD, we assessed rates of eligibility among racial and ethnic groups controlling for other demographic covariates. Each trial incorporated positron emission tomography and/or cerebrospinal fluid to evaluate brain amyloid pathology, as well as typical eligibility criteria used in early AD trials. RESULTS Across the trials, 10,804 US participants were screened: 193 (2%) were of Hispanic ethnicity and Black race, 2,624 (25%) were of Hispanic ethnicity and White race, 118 (1%) were of non-Hispanic ethnicity (NH) and Asian race, 696 (7%) were of NH ethnicity and Black race, and 7,017 (65%) were of NH ethnicity and White race. Data from 156 participants who did not fit into these categories were excluded. Accounting for age, sex, and trial and using NH White participants as a reference group, we observed higher probabilities of ineligibility for amyloid biomarker criteria among Hispanic Black (odds ratio [OR] = 3.20, 95% confidence interval [CI] = 2.11-4.88), Hispanic White (OR = 4.15, 95% CI = 3.58-4.83), NH Asian (OR = 2.35, 95% CI = 1.23-4.55), and NH Black (OR = 3.75, 95% CI = 2.80-5.06) participants. INTERPRETATION Differential eligibility may contribute to underrepresentation of some minoritized racial and ethnic groups in early AD trials. Amyloid biomarker eligibility is a requirement to confirm the diagnosis of AD and for treatment with amyloid-lowering drugs and differed among racial and ethnic groups. ANN NEUROL 2024;95:288-298.
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Affiliation(s)
- Joshua D Grill
- Institute for Memory Impairments and Neurological Disorders, Departments of Psychiatry and Human Behavior and Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Charlene Flournoy
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | | | - Karin Ernstrom
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Reisa Sperling
- Brigham and Women's Hospital, Massachusetts General Hospital, Boston, MA, USA
| | - Doris Molina-Henry
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | | | | | | | | | | | | | - Paul Aisen
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
| | - Rema Raman
- Alzheimer's Therapeutic Research Institute, University of Southern California, San Diego, CA, USA
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Kolpakov S, Yashkin A, Ukraintseva S, Yashin A, Akushevich I. Genome-Related Mechanisms Contributing to Differences in Alzheimer's Disease Incidence Between White and Black Older US Adults. J Racial Ethn Health Disparities 2024:10.1007/s40615-024-01907-3. [PMID: 38273182 PMCID: PMC11269527 DOI: 10.1007/s40615-024-01907-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 12/31/2023] [Accepted: 01/04/2024] [Indexed: 01/27/2024]
Abstract
In this manuscript, we leverage a modified GWAS algorithm adapted for use with multidimensional Cox models and data from the Health and Retirement Study to explore how genetic variation influences the size of the disparity in Alzheimer's disease (AD) incidence between older Black and White US adults. We identified four loci that were associated with higher AD incidence levels in older Black adults: (1) rs11077034 (hazard ratio (HR), 4.98) from the RBFOX1 gene; (2) rs7144494 (HR, 1.68) from the HISLA gene; (3) rs7660552 (HR, 3.07) from the SLC25A4 gene; and (4) rs12599485 (HR, 3.181) from the NIP30 gene. The RBFOX1, HISLA, SLC25A4, and NIP30 genes are known to be associated with AD (RBFOX1, NIP30) directly, and also influence the risk of AD risk-related morbidities such as hypertension (RBFOX1, SLC25A4), depression (SLC25A4), and certain cancers (HISLA, SLC25A4). A likely disparity-generating mechanism may lie in endocytosis and abnormal tissue growing mechanisms, depending on inherited gene mutations and the structure of proxies as well as gene-environment interactions with other risk factors such as lifestyle, education level, and access to adequate medical services.
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Affiliation(s)
- Stanislav Kolpakov
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA.
| | - Arseniy Yashkin
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA
| | | | - Anatoliy Yashin
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA
| | - Igor Akushevich
- Social Science Research Institute, Duke University, Durham, NC, 27710, USA
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26
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Can B, Sanlier N. Alzheimer, Parkinson, dementia, and phytochemicals: insight review. Crit Rev Food Sci Nutr 2024:1-23. [PMID: 38189347 DOI: 10.1080/10408398.2023.2299340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Alzheimer's, Parkinson's, and dementia are the leading neurodegenerative diseases that threaten the world with the aging population. Although the pathophysiology of each disease is unique, the steps to be taken to prevent diseases are similar. One of the changes that a person can make alone is to gain the habit of an antioxidant-rich diet. Phytochemicals known for their antioxidant properties have been reported to prevent neurodegenerative diseases in various studies. Phytochemicals with similar chemical structures are grouped. Accordingly, there are two main groups of phytochemicals, flavonoid and non-flavonoid. Various in vitro and in vivo studies on phytochemicals have proven neuroprotective effects by increasing cognitive function with their anti-inflammatory and antioxidant mechanisms. The purpose of this review is to summarize the in vitro and in vivo studies on phytochemicals with neuroprotective effects and to provide insight.
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Affiliation(s)
- Basak Can
- Nutrition and Dietetics, School of Health Sciences, Istanbul Gelisim University, Istanbul, Turkey
| | - Nevin Sanlier
- School of Health Sciences, Nutrition and Dietetics, Ankara Medipol University, Ankara, Turkey
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27
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Xue D, Blue EE, Conomos MP, Fohner AE. The power of representation: Statistical analysis of diversity in US Alzheimer's disease genetics data. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2024; 10:e12462. [PMID: 38500778 PMCID: PMC10945594 DOI: 10.1002/trc2.12462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 01/31/2024] [Accepted: 02/02/2024] [Indexed: 03/20/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) is a complex disease influenced by genetics and environment. More than 75 susceptibility loci have been linked to late-onset AD, but most of these loci were discovered in genome-wide association studies (GWAS) exclusive to non-Hispanic White individuals. There are wide disparities in AD risk across racially stratified groups, and while these disparities are not due to genetic differences, underrepresentation in genetic research can further exacerbate and contribute to their persistence. We investigated the racial/ethnic representation of participants in United States (US)-based AD genetics and the statistical implications of current representation. METHODS We compared racial/ethnic data of participants from array and sequencing studies in US AD genetics databases, including National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) and NIAGADS Data Sharing Service (dssNIAGADS), to AD and related dementia (ADRD) prevalence and mortality. We then simulated the statistical power of these datasets to identify risk variants from non-White populations. RESULTS There is insufficient statistical power (probability <80%) to detect single nucleotide polymorphisms (SNPs) with low to moderate effect sizes (odds ratio [OR]<1.5) using array data from Black and Hispanic participants; studies of Asian participants are not powered to detect variants OR <= 2. Using available and projected sequencing data from Black and Hispanic participants, risk variants with OR = 1.2 are detectable at high allele frequencies. Sample sizes remain insufficiently powered to detect these variants in Asian populations. DISCUSSION AD genetics datasets are largely representative of US ADRD burden. However, there is a wide discrepancy between proportional representation and statistically meaningful representation. Most variation identified in GWAS of non-Hispanic White individuals have low to moderate effects. Comparable risk variants in non-White populations are not detectable given current sample sizes, which could lead to disparities in future studies and drug development. We urge AD genetics researchers and institutions to continue investing in recruiting diverse participants and use community-based participatory research practices.
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Affiliation(s)
- Diane Xue
- Institute for Public Health GeneticsUniversity of Washington School of Public HealthSeattleWashingtonUSA
| | - Elizabeth E. Blue
- Institute for Public Health GeneticsUniversity of Washington School of Public HealthSeattleWashingtonUSA
- Division of Medical GeneticsDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
- Brotman Baty InstituteSeattleWashingtonUSA
| | - Matthew P. Conomos
- Department of BiostatisticsUniversity of Washington School of Public HealthSeattleWashingtonUSA
| | - Alison E. Fohner
- Institute for Public Health GeneticsUniversity of Washington School of Public HealthSeattleWashingtonUSA
- Department of EpidemiologyUniversity of Washington School of Public HealthSeattleWashingtonUSA
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28
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Nuytemans K, Rajabli F, Jean-Francois M, Kurup JT, Adams LD, Starks TD, Whitehead PL, Kunkle BW, Caban-Holt A, Haines JL, Cuccaro ML, Vance JM, Byrd GS, Beecham GW, Reitz C, Pericak-Vance MA. Genetic analyses in multiplex families confirms chromosome 5q35 as a risk locus for Alzheimer's Disease in individuals of African Ancestry. Neurobiol Aging 2024; 133:125-133. [PMID: 37952397 PMCID: PMC11131578 DOI: 10.1016/j.neurobiolaging.2023.10.010] [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: 04/18/2023] [Revised: 10/23/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023]
Abstract
There is a paucity of genetic studies of Alzheimer Disease (AD) in individuals of African Ancestry, despite evidence suggesting increased risk of AD in the African American (AA) population. We performed whole-genome sequencing (WGS) and multipoint linkage analyses in 51 multi-generational AA AD families ascertained through the Research in African American Alzheimer Disease Initiative (REAAADI) and the National Institute on Aging Late Onset Alzheimer's disease (NIA-LOAD) Family Based Study. Variants were prioritized on minor allele frequency (<0.01), functional potential of coding and noncoding variants, co-segregation with AD and presence in multi-ancestry ADSP release 3 WGS data. We identified a significant linkage signal on chromosome 5q35 (HLOD=3.3) driven by nine families. Haplotype segregation analysis in the family with highest LOD score identified a 3'UTR variant in INSYN2B with the most functional evidence. Four other linked AA families harbor within-family shared variants located in INSYN2B's promoter or enhancer regions. This AA family-based finding shows the importance of diversifying population-level genetic data to better understand the genetic determinants of AD on a global scale.
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Affiliation(s)
- Karen Nuytemans
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Melissa Jean-Francois
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jiji Thulaseedhara Kurup
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Takiyah D Starks
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Patrice L Whitehead
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Brian W Kunkle
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Allison Caban-Holt
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Jonathan L Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Goldie S Byrd
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Taub Institute for Research on the Aging Brain, Departments of Neurology, Psychiatry, and Epidemiology, College of Physicians and Surgeons, Columbia University, New York, NY, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL, USA; Dr. John T. MacDonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, FL, USA.
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Deng J, Sun B, Kavcic V, Liu M, Giordani B, Li T. Novel methodology for detection and prediction of mild cognitive impairment using resting-state EEG. Alzheimers Dement 2024; 20:145-158. [PMID: 37496373 PMCID: PMC10811294 DOI: 10.1002/alz.13411] [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: 04/20/2023] [Revised: 07/05/2023] [Accepted: 07/06/2023] [Indexed: 07/28/2023]
Abstract
BACKGROUND Early discrimination and prediction of cognitive decline are crucial for the study of neurodegenerative mechanisms and interventions to promote cognitive resiliency. METHODS Our research is based on resting-state electroencephalography (EEG) and the current dataset includes 137 consensus-diagnosed, community-dwelling Black Americans (ages 60-90 years, 84 healthy controls [HC]; 53 mild cognitive impairment [MCI]) recruited through Wayne State University and Michigan Alzheimer's Disease Research Center. We conducted multiscale analysis on time-varying brain functional connectivity and developed an innovative soft discrimination model in which each decision on HC or MCI also comes with a connectivity-based score. RESULTS The leave-one-out cross-validation accuracy is 91.97% and 3-fold accuracy is 91.17%. The 9 to 18 months' progression trend prediction accuracy over an availability-limited subset sample is 84.61%. CONCLUSION The EEG-based soft discrimination model demonstrates high sensitivity and reliability for MCI detection and shows promising capability in proactive prediction of people at risk of MCI before clinical symptoms may occur.
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Affiliation(s)
- Jinxian Deng
- Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMichiganUSA
| | - Boxin Sun
- Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMichiganUSA
| | - Voyko Kavcic
- Institute of GerontologyWayne State UniversityDetroitMichiganUSA
- International Institute of Applied GerontologyLjubljanaSlovenia
| | - Mingyan Liu
- Department of Electrical Engineering and Computer ScienceUniversity of MichiganAnn ArborMichiganUSA
| | - Bruno Giordani
- Departments of PsychiatryNeurologyPsychology and School of NursingUniversity of MichiganAnn ArborMichiganUSA
- Michigan Alzheimer's Disease Research CenterAnn ArborMichiganUSA
| | - Tongtong Li
- Department of Electrical and Computer EngineeringMichigan State UniversityEast LansingMichiganUSA
- Michigan Alzheimer's Disease Research CenterAnn ArborMichiganUSA
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Sun Y, Zhu J, Yang Y, Zhang Z, Zhong H, Zeng G, Zhou D, Nowakowski RS, Long J, Wu C, Wu L. Identification of candidate DNA methylation biomarkers related to Alzheimer's disease risk by integrating genome and blood methylome data. Transl Psychiatry 2023; 13:387. [PMID: 38092781 PMCID: PMC10719322 DOI: 10.1038/s41398-023-02695-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Revised: 11/16/2023] [Accepted: 11/29/2023] [Indexed: 12/17/2023] Open
Abstract
Alzheimer disease (AD) is a common neurodegenerative disease with a late onset. It is critical to identify novel blood-based DNA methylation biomarkers to better understand the extent of the molecular pathways affected in AD. Two sets of blood DNA methylation genetic prediction models developed using different reference panels and modelling strategies were leveraged to evaluate associations of genetically predicted DNA methylation levels with AD risk in 111,326 (46,828 proxy) cases and 677,663 controls. A total of 1,168 cytosine-phosphate-guanine (CpG) sites showed a significant association with AD risk at a false discovery rate (FDR) < 0.05. Methylation levels of 196 CpG sites were correlated with expression levels of 130 adjacent genes in blood. Overall, 52 CpG sites of 32 genes showed consistent association directions for the methylation-gene expression-AD risk, including nine genes (CNIH4, THUMPD3, SERPINB9, MTUS1, CISD1, FRAT2, CCDC88B, FES, and SSH2) firstly reported as AD risk genes. Nine of 32 genes were enriched in dementia and AD disease categories (P values ranged from 1.85 × 10-4 to 7.46 × 10-6), and 19 genes in a neurological disease network (score = 54) were also observed. Our findings improve the understanding of genetics and etiology for AD.
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Affiliation(s)
- Yanfa Sun
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P. R. China
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Jingjing Zhu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Yaohua Yang
- Center for Public Health Genomics, Department of Public Health Sciences, UVA Comprehensive Cancer Center, School of Medicine, University of Virginia, Charlottesville, VA, 22093, USA
| | - Zichen Zhang
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Hua Zhong
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA
| | - Guanghua Zeng
- College of Life Science, Fujian Provincial Key Laboratory for the Prevention and Control of Animal Infectious Diseases and Biotechnology, Fujian Provincial Universities Key Laboratory of Preventive Veterinary Medicine and Biotechnology (Longyan University), Longyan University, Longyan, Fujian, 364012, P. R. China
| | - Dan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, 310058, P.R. China
| | - Richard S Nowakowski
- Department of Biomedical Sciences, Florida State University, Tallahassee, FL, 32304, USA
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37203, USA
| | - Chong Wu
- Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Lang Wu
- Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, 96813, USA.
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Malvaso A, Gatti A, Negro G, Calatozzolo C, Medici V, Poloni TE. Microglial Senescence and Activation in Healthy Aging and Alzheimer's Disease: Systematic Review and Neuropathological Scoring. Cells 2023; 12:2824. [PMID: 38132144 PMCID: PMC10742050 DOI: 10.3390/cells12242824] [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: 10/31/2023] [Revised: 12/07/2023] [Accepted: 12/08/2023] [Indexed: 12/23/2023] Open
Abstract
The greatest risk factor for neurodegeneration is the aging of the multiple cell types of human CNS, among which microglia are important because they are the "sentinels" of internal and external perturbations and have long lifespans. We aim to emphasize microglial signatures in physiologic brain aging and Alzheimer's disease (AD). A systematic literature search of all published articles about microglial senescence in human healthy aging and AD was performed, searching for PubMed and Scopus online databases. Among 1947 articles screened, a total of 289 articles were assessed for full-text eligibility. Microglial transcriptomic, phenotypic, and neuropathological profiles were analyzed comprising healthy aging and AD. Our review highlights that studies on animal models only partially clarify what happens in humans. Human and mice microglia are hugely heterogeneous. Like a two-sided coin, microglia can be protective or harmful, depending on the context. Brain health depends upon a balance between the actions and reactions of microglia maintaining brain homeostasis in cooperation with other cell types (especially astrocytes and oligodendrocytes). During aging, accumulating oxidative stress and mitochondrial dysfunction weaken microglia leading to dystrophic/senescent, otherwise over-reactive, phenotype-enhancing neurodegenerative phenomena. Microglia are crucial for managing Aβ, pTAU, and damaged synapses, being pivotal in AD pathogenesis.
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Affiliation(s)
- Antonio Malvaso
- IRCCS “C. Mondino” Foundation, National Neurological Institute, Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy; (A.M.); (A.G.)
| | - Alberto Gatti
- IRCCS “C. Mondino” Foundation, National Neurological Institute, Department of Brain and Behavioral Sciences, University of Pavia, 27100 Pavia, Italy; (A.M.); (A.G.)
| | - Giulia Negro
- Department of Neurology, University of Milano Bicocca, 20126 Milan, Italy;
| | - Chiara Calatozzolo
- Department of Neurology and Neuropathology, Golgi-Cenci Foundation, Abbiategrasso, 20081 Milan, Italy;
| | - Valentina Medici
- Department of Translational Medicine, University of Eastern Piedmont, 28100 Novara, Italy;
| | - Tino Emanuele Poloni
- Department of Neurology and Neuropathology, Golgi-Cenci Foundation, Abbiategrasso, 20081 Milan, Italy;
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Li D, Farrell JJ, Mez J, Martin ER, Bush WS, Ruiz A, Boada M, de Rojas I, Mayeux R, Haines JL, Vance MAP, Wang LS, Schellenberg GD, Lunetta KL, Farrer LA. Novel loci for Alzheimer's disease identified by a genome-wide association study in Ashkenazi Jews. Alzheimers Dement 2023; 19:5550-5562. [PMID: 37260021 PMCID: PMC10689571 DOI: 10.1002/alz.13117] [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: 12/28/2022] [Revised: 03/29/2023] [Accepted: 04/11/2023] [Indexed: 06/02/2023]
Abstract
INTRODUCTION Most Alzheimer's disease (AD) loci have been discovered in individuals with European ancestry (EA). METHODS We applied principal component analysis using Gaussian mixture models and an Ashkenazi Jewish (AJ) reference genome-wide association study (GWAS) data set to identify Ashkenazi Jews ascertained in GWAS (n = 42,682), whole genome sequencing (WGS, n = 16,815), and whole exome sequencing (WES, n = 20,504) data sets. The association of AD was tested genome wide (GW) in the GWAS and WGS data sets and exome wide (EW) in all three data sets (EW). Gene-based analyses were performed using aggregated rare variants. RESULTS In addition to apolipoprotein E (APOE), GW analyses (1355 cases and 1661 controls) revealed associations with TREM2 R47H (p = 9.66 × 10-9 ), rs541586606 near RAB3B (p = 5.01 × 10-8 ), and rs760573036 between SPOCK3 and ANXA10 (p = 6.32 × 10-8 ). In EW analyses (1504 cases and 2047 controls), study-wide significant association was observed with rs1003710 near SMAP2 (p = 1.91 × 10-7 ). A significant gene-based association was identified with GIPR (p = 7.34 × 10-7 ). DISCUSSION Our results highlight the efficacy of founder populations for AD genetic studies.
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Affiliation(s)
- Donghe Li
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - John J Farrell
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Jesse Mez
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Eden R. Martin
- Dr. John T. Macdonald Foundation, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, University of Miami, Miami, FL 33136, USA
| | - William S. Bush
- Department of Population & Quantitative Health Science and Cleveland Institute for Computational Biology, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
| | - Agustin Ruiz
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Itziar de Rojas
- Research Center and Memory Clinic, ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Richard Mayeux
- Taub Institute on Alzheimer's Disease and the Aging Brain, Gertrude H. Sergievsky Center Department of Neurology, Columbia University, 710 West 168th Street, New York, NY 10032, USA
| | - Jonathan L. Haines
- Department of Population & Quantitative Health Science and Cleveland Institute for Computational Biology, Case Western Reserve University, 10900 Euclid Ave, Cleveland, OH 44106, USA
| | - Margaret A. Pericak Vance
- Dr. John T. Macdonald Foundation, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, University of Miami, Miami, FL 33136, USA
- Department of Neurology, University of Miami, Miami, FL 33136, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, University of Pennsylvania, 3400 Spruce Street, Philadelphia, PA 19104, USA
| | - Kathryn L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
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Bettencourt C, Skene N, Bandres-Ciga S, Anderson E, Winchester LM, Foote IF, Schwartzentruber J, Botia JA, Nalls M, Singleton A, Schilder BM, Humphrey J, Marzi SJ, Toomey CE, Kleifat AA, Harshfield EL, Garfield V, Sandor C, Keat S, Tamburin S, Frigerio CS, Lourida I, Ranson JM, Llewellyn DJ. Artificial intelligence for dementia genetics and omics. Alzheimers Dement 2023; 19:5905-5921. [PMID: 37606627 PMCID: PMC10841325 DOI: 10.1002/alz.13427] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Revised: 07/14/2023] [Accepted: 07/18/2023] [Indexed: 08/23/2023]
Abstract
Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.
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Affiliation(s)
- Conceicao Bettencourt
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
| | - Nathan Skene
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Emma Anderson
- Department of Mental Health of Older People, Division of Psychiatry, University College London, London, UK
| | | | - Isabelle F Foote
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Jeremy Schwartzentruber
- Open Targets, Cambridge, UK
- Wellcome Sanger Institute, Cambridge, UK
- Illumina Artificial Intelligence Laboratory, Illumina Inc, Foster City, California, USA
| | - Juan A Botia
- Departamento de Ingeniería de la Información y las Comunicaciones, Universidad de Murcia, Murcia, Spain
| | - Mike Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International LLC, Washington, DC, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
| | - Brian M Schilder
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Jack Humphrey
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Sarah J Marzi
- UK Dementia Research Institute, Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Christina E Toomey
- Queen Square Brain Bank for Neurological Disorders, UCL Queen Square Institute of Neurology, London, UK
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, London, UK
- The Francis Crick Institute, London, UK
| | - Ahmad Al Kleifat
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Eric L Harshfield
- Stroke Research Group, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Victoria Garfield
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Cynthia Sandor
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Samuel Keat
- UK Dementia Research Institute. School of Medicine, Cardiff University, Cardiff, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, Neurology Section, University of Verona, Verona, Italy
| | - Carlo Sala Frigerio
- UK Dementia Research Institute, Queen Square Institute of Neurology, University College London, London, UK
| | | | | | - David J Llewellyn
- University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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Bhuiyan NZ, Hasan MK, Mahmud Z, Hossain MS, Rahman A. Prevention of Alzheimer's disease through diet: An exploratory review. Metabol Open 2023; 20:100257. [PMID: 37781687 PMCID: PMC10539673 DOI: 10.1016/j.metop.2023.100257] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Revised: 08/16/2023] [Accepted: 09/15/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction This exploratory review article describes about the genetic factors behind Alzheimer's disease (AD), their association with foods, and their relationships with cognitive impairment. It explores the dietary patterns and economic challenges in AD prevention. Methods Scopus, PubMed and Google Scholar were searched for articles that examined the relationships between Diets, Alzheimer's Disease (AD), and Socioeconomic conditions in preventative Alzheimer's disease studies. Graphs and Network analysis data were taken from Scopus under the MeSH search method, including words, Alzheimer's, APoE4, Tau protein, APP, Amyloid precursor protein, Beta-Amyloid, Aβ, Mediterranean Diet, MD, DASH diet, MIND diet, SES, Socioeconomic, Developed country, Underdeveloped country, Preventions. The network analysis was done through VOS viewer. Results Mediterranean diet (MD) accurately lowers AD (Alzheimer's Disease) risk to 53% and 35% for people who follow it moderately. MIND scores had a statistically significant reduction in AD rate compared to those in the lowest tertial (53% and 35% reduction, respectively). Subjects with the highest adherence to the MD and DASH had a 54% and 39% lower risk of developing AD, respectively, compared to those in the lowest tertial. Omega-6, PUFA, found in nuts and fish, can play most roles in the clearance of Aβ. Vitamin D inhibits induced fibrillar Aβ apoptosis. However, the high cost of these diet components rise doubt about the effectiveness of AD prevention through healthy diets. Conclusion The finding of this study revealed an association between diet and the effects of the chemical components of foods on AD biomarkers. More research is required to see if nutrition is a risk or a protective factor for Alzheimer's disease to encourage research to be translated into therapeutic practice and to clarify nutritional advice.
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Affiliation(s)
- Nusrat Zahan Bhuiyan
- Department of Biochemistry and Molecular Biology, National University Bangladesh, Gazipur, 1704, Bangladesh
| | - Md. Kamrul Hasan
- Department of Biochemistry and Molecular Biology, National University Bangladesh, Gazipur, 1704, Bangladesh
- Department of Public Health, North South University, Dhaka, 1229, Bangladesh
| | - Zimam Mahmud
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
| | - Md. Sabbir Hossain
- Department of Biochemistry and Molecular Biology, National University Bangladesh, Gazipur, 1704, Bangladesh
| | - Atiqur Rahman
- Department of Biochemistry and Molecular Biology, University of Dhaka, Dhaka, 1000, Bangladesh
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Yu C, Ryan J, Orchard SG, Robb C, Woods RL, Wolfe R, Renton AE, Goate AM, Brodtmann A, Shah RC, Chong TTJ, Sheets K, Kyndt C, Sood A, Storey E, Murray AM, McNeil JJ, Lacaze P. Validation of newly derived polygenic risk scores for dementia in a prospective study of older individuals. Alzheimers Dement 2023; 19:5333-5342. [PMID: 37177856 PMCID: PMC10640662 DOI: 10.1002/alz.13113] [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: 12/18/2022] [Revised: 03/27/2023] [Accepted: 04/03/2023] [Indexed: 05/15/2023]
Abstract
INTRODUCTION Recent genome-wide association studies identified new dementia-associated variants. We assessed the performance of updated polygenic risk scores (PRSs) using these variants in an independent cohort. METHODS We used Cox models and area under the curve (AUC) to validate new PRSs (PRS-83SNP, PRS-SBayesR, and PRS-CS) compared with an older PRS-23SNP in 12,031 initially-healthy participants ≥70 years of age. Dementia was rigorously adjudicated according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. RESULTS PRS-83SNP, PRS-SBayesR, and PRS-CS were associated with incident dementia, with fully adjusted (including apolipoprotein E [APOE] ε4) hazard ratios per standard deviation (SD) of 1.35 (1.23-1.47), 1.37 (1.25-1.50), and 1.42 (1.30-1.56), respectively. The AUC of a model containing conventional/non-genetic factors and APOE was 74.7%. This was improved to 75.7% (p = 0.007), 76% (p = 0.004), and 76.1% (p = 0.003) with addition of PRS-83SNP, PRS-SBayesR, and PRS-CS, respectively. The PRS-23SNP did not improve AUC (74.7%, p = 0.95). CONCLUSION New PRSs for dementia significantly improve risk-prediction performance, but still account for less risk than APOE genotype overall.
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Affiliation(s)
- Chenglong Yu
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Joanne Ryan
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Suzanne G. Orchard
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Catherine Robb
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Robyn L. Woods
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Rory Wolfe
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Alan E. Renton
- Department Genetics and Genomic Sciences and Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Departments of Neurology and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Alison M. Goate
- Department Genetics and Genomic Sciences and Ronald M. Loeb Center for Alzheimer’s Disease, Icahn School of Medicine at Mount Sinai, New York, New York, USA
- Departments of Neurology and Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Amy Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, Melbourne, Victoria, Australia
| | - Raj C. Shah
- Department of Family & Preventive Medicine and the Rush Alzheimer’s Disease Center, Chicago, Illinois, USA
| | - Trevor T.-J. Chong
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Victoria, Australia
- Department of Neurology, Alfred Health, Melbourne, Victoria, Australia
- Department of Clinical Neurosciences, St. Vincent’s Hospital, Melbourne, Victoria, Australia
| | - Kerry Sheets
- Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Geriatrics, Hennepin Healthcare, Minneapolis, Minnesota, USA
| | - Christopher Kyndt
- Department of Neurology, Melbourne Health, Parkville, Victoria, Australia
- Department of Neuroscience, Eastern Health, Box Hill, Victoria, Australia
| | - Ajay Sood
- Department of Neurology and the Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, Illinois, USA
| | - Elsdon Storey
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Anne M. Murray
- Department of Medicine, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Geriatrics, Hennepin Healthcare, Minneapolis, Minnesota, USA
- Berman Center for Outcomes and Clinical Research, Hennepin Healthcare Research Institute, Hennepin Healthcare, and University of Minnesota, Minneapolis, Minnesota, USA
| | - John J. McNeil
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
| | - Paul Lacaze
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
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Yang Z, Cieza B, Reyes-Dumeyer D, Montesinos R, Soto-Añari M, Custodio N, Tosto G. A benchmark study on current GWAS models in admixed populations. Brief Bioinform 2023; 25:bbad437. [PMID: 38037235 PMCID: PMC10689347 DOI: 10.1093/bib/bbad437] [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: 06/21/2023] [Revised: 10/30/2023] [Accepted: 11/08/2023] [Indexed: 12/02/2023] Open
Abstract
OBJECTIVE The performances of popular genome-wide association study (GWAS) models have not been examined yet in a consistent manner under the scenario of genetic admixture, which introduces several challenging aspects: heterogeneity of minor allele frequency (MAF), wide spectrum of case-control ratio, varying effect sizes, etc. METHODS We generated a cohort of synthetic individuals (N = 19 234) that simulates (i) a large sample size; (ii) two-way admixture (Native American and European ancestry) and (iii) a binary phenotype. We then benchmarked three popular GWAS tools [generalized linear mixed model associated test (GMMAT), scalable and accurate implementation of generalized mixed model (SAIGE) and Tractor] by computing inflation factors and power calculations under different MAFs, case-control ratios, sample sizes and varying ancestry proportions. We also employed a cohort of Peruvians (N = 249) to further examine the performances of the testing models on (i) real genetic and phenotype data and (ii) small sample sizes. RESULTS In the synthetic cohort, SAIGE performed better than GMMAT and Tractor in terms of type-I error rate, especially under severe unbalanced case-control ratio. On the contrary, power analysis identified Tractor as the best method to pinpoint ancestry-specific causal variants but showed decreased power when the effect size displayed limited heterogeneity between ancestries. In the Peruvian cohort, only Tractor identified two suggestive loci (P-value $\le 1\ast{10}^{-5}$) associated with Native American ancestry. DISCUSSION The current study illustrates best practice and limitations for available GWAS tools under the scenario of genetic admixture. Incorporating local ancestry in GWAS analyses boosts power, although careful consideration of complex scenarios (small sample sizes, imbalance case-control ratio, MAF heterogeneity) is needed.
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Affiliation(s)
- Zikun Yang
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
| | - Basilio Cieza
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
| | - Dolly Reyes-Dumeyer
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY 10032, USA
| | - Rosa Montesinos
- Unidad de diagnóstico de deterioro cognitivo y prevención de demencia, Instituto Peruano de Neurociencias, Lima, Perú
| | - Marcio Soto-Añari
- Instituto de Neurociencia Cognitiva, Arequipa, Perú
- Laboratorio de Neurociencia, Universidad Católica San Pablo, Arequipa, Perú
| | - Nilton Custodio
- Unidad de diagnóstico de deterioro cognitivo y prevención de demencia, Instituto Peruano de Neurociencias, Lima, Perú
| | - Giuseppe Tosto
- Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- The Gertrude H. Sergievsky Center, College of Physicians and Surgeons, Columbia University, 630 West 168th Street, New York, NY 10032, USA
- Department of Neurology, College of Physicians and Surgeons, Columbia University and the New York Presbyterian Hospital, 710 West 168th Street, New York, NY 10032, USA
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Simmonds E, Levine KS, Han J, Iwaki H, Koretsky MJ, Kuznetsov N, Faghri F, Solsberg CW, Schuh A, Jones L, Bandres-Ciga S, Blauwendraat C, Singleton A, Escott-Price V, Leonard HL, Nalls MA. Sleep disturbances as risk factors for neurodegeneration later in life. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.08.23298037. [PMID: 37986827 PMCID: PMC10659485 DOI: 10.1101/2023.11.08.23298037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The relationship between sleep disorders and neurodegeneration is complex and multi-faceted. Using over one million electronic health records (EHRs) from Wales, UK, and Finland, we mined biobank data to identify the relationships between sleep disorders and the subsequent manifestation of neurodegenerative diseases (NDDs) later in life. We then examined how these sleep disorders' severity impacts neurodegeneration risk. Additionally, we investigated how sleep attributed risk may compensate for the lack of genetic risk factors (i.e. a lower polygenic risk score) in NDD manifestation. We found that sleep disorders such as sleep apnea were associated with the risk of Alzheimer's disease (AD), amyotrophic lateral sclerosis, dementia, Parkinson's disease (PD), and vascular dementia in three national scale biobanks, with hazard ratios (HRs) ranging from 1.31 for PD to 5.11 for dementia. These sleep disorders imparted significant risk up to 15 years before the onset of an NDD. Cumulative number of sleep disorders in the EHRs were associated with a higher risk of neurodegeneration for dementia and vascular dementia. Sleep related risk factors were independent of genetic risk for Alzheimer's and Parkinson's, potentially compensating for low genetic risk in overall disease etiology. There is a significant multiplicative interaction regarding the combined risk of sleep disorders and Parkinson's disease. Poor sleep hygiene and sleep apnea are relatively modifiable risk factors with several treatment options, including CPAP and surgery, that could potentially reduce the risk of neurodegeneration. This is particularly interesting in how sleep related risk factors are significantly and independently enriched in manifesting NDD patients with low levels of genetic risk factors for these diseases. HIGHLIGHTS Sleep disorders, particularly sleep apnea, are associated with the risk of Alzheimer's disease, amyotrophic lateral sclerosis, dementia, Parkinson's disease, and vascular dementia in national scale biobanks.These sleep disorders imparted significant risk up to 15 years before the onset of a neurodegenerative disease.The cumulative number of sleep disorders in the electronic health records were associated with a higher risk of neurodegeneration related to dementia and vascular dementia.Sleep related risk factors are independent of genetic risk for Alzheimer's and Parkinson's, potentially compensating for low genetic risk in overall disease etiology.Significant multiplicative interaction exists regarding the combined risk of sleep disorders and Parkinson's disease.
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Godfrey RK, Alsop E, Bjork RT, Chauhan BS, Ruvalcaba HC, Antone J, Gittings LM, Michael AF, Williams C, Hala'ufia G, Blythe AD, Hall M, Sattler R, Van Keuren-Jensen K, Zarnescu DC. Modelling TDP-43 proteinopathy in Drosophila uncovers shared and neuron-specific targets across ALS and FTD relevant circuits. Acta Neuropathol Commun 2023; 11:168. [PMID: 37864255 PMCID: PMC10588218 DOI: 10.1186/s40478-023-01656-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2023] [Accepted: 09/19/2023] [Indexed: 10/22/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) comprise a spectrum of neurodegenerative diseases linked to TDP-43 proteinopathy, which at the cellular level, is characterized by loss of nuclear TDP-43 and accumulation of cytoplasmic TDP-43 inclusions that ultimately cause RNA processing defects including dysregulation of splicing, mRNA transport and translation. Complementing our previous work in motor neurons, here we report a novel model of TDP-43 proteinopathy based on overexpression of TDP-43 in a subset of Drosophila Kenyon cells of the mushroom body (MB), a circuit with structural characteristics reminiscent of vertebrate cortical networks. This model recapitulates several aspects of dementia-relevant pathological features including age-dependent neuronal loss, nuclear depletion and cytoplasmic accumulation of TDP-43, and behavioral deficits in working memory and sleep that occur prior to axonal degeneration. RNA immunoprecipitations identify several candidate mRNA targets of TDP-43 in MBs, some of which are unique to the MB circuit and others that are shared with motor neurons. Among the latter is the glypican Dally-like-protein (Dlp), which exhibits significant TDP-43 associated reduction in expression during aging. Using genetic interactions we show that overexpression of Dlp in MBs mitigates TDP-43 dependent working memory deficits, conistent with Dlp acting as a mediator of TDP-43 toxicity. Substantiating our findings in the fly model, we find that the expression of GPC6 mRNA, a human ortholog of dlp, is specifically altered in neurons exhibiting the molecular signature of TDP-43 pathology in FTD patient brains. These findings suggest that circuit-specific Drosophila models provide a platform for uncovering shared or disease-specific molecular mechanisms and vulnerabilities across the spectrum of TDP-43 proteinopathies.
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Affiliation(s)
- R Keating Godfrey
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA.
- McGuire Center for Lepidoptera and Biodiversity, Florida Museum of Natural History, University of Florida, 3215 Hull Road, Gainesville, FL, 32611, USA.
| | - Eric Alsop
- Translational Genomics Research Institute, 445 N 5th St., Phoenix, AZ, 85004, USA
| | - Reed T Bjork
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Brijesh S Chauhan
- Cellular and Molecular Physiology, Penn State College of Medicine, 500 University Drive Crescent Building C4605, Hershey, PA, 17033, USA
| | - Hillary C Ruvalcaba
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Jerry Antone
- Translational Genomics Research Institute, 445 N 5th St., Phoenix, AZ, 85004, USA
| | - Lauren M Gittings
- Department of Translational Neuroscience, Barrow Neurological Institute, 350 W Thomas Road, Phoenix, AZ, 85013, USA
| | - Allison F Michael
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Christi Williams
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Grace Hala'ufia
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Alexander D Blythe
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA
| | - Megan Hall
- Translational Genomics Research Institute, 445 N 5th St., Phoenix, AZ, 85004, USA
| | - Rita Sattler
- Department of Translational Neuroscience, Barrow Neurological Institute, 350 W Thomas Road, Phoenix, AZ, 85013, USA
| | | | - Daniela C Zarnescu
- Department of Molecular and Cellular Biology, Life Sciences South, University of Arizona, 1007 E. Lowell St., Tucson, AZ, 85721, USA.
- Cellular and Molecular Physiology, Penn State College of Medicine, 500 University Drive Crescent Building C4605, Hershey, PA, 17033, USA.
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Housini M, Zhou Z, Gutierrez J, Rao S, Jomaa R, Subasinghe K, Reid DM, Silzer T, Phillips N, O'Bryant S, Barber RC. Top Alzheimer's disease risk allele frequencies differ in HABS-HD Mexican- versus Non-Hispanic White Americans. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12518. [PMID: 38155914 PMCID: PMC10752755 DOI: 10.1002/dad2.12518] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 11/13/2023] [Accepted: 11/25/2023] [Indexed: 12/30/2023]
Abstract
INTRODUCTION: Here we evaluate frequencies of the top 10 Alzheimer's disease (AD) risk alleles for late-onset AD in Mexican American (MA) and non-Hispanic White (NHW) American participants enrolled in the Health and Aging Brain Study-Health Disparities Study cohort. METHODS: Using DNA extracted from this community-based diverse population, we calculated the genotype frequencies in each population to determine whether a significant difference is detected between the different ethnicities. DNA genotyping was performed per manufacturers' protocols. RESULTS: Allele and genotype frequencies for 9 of the 11 single nucleotide polymorphisms (two apolipoprotein E variants, CR1, BIN1, DRB1, NYAP1, PTK2B, FERMT2, and ABCA7) differed significantly between MAs and NHWs. DISCUSSION: The significant differences in frequencies of top AD risk alleles observed here across MAs and NHWs suggest that ethnicity-specific genetic risks for AD exist. Given our results, we are advancing additional projects to further elucidate ethnicity-specific differences in AD.
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Affiliation(s)
- Mohammad Housini
- Department of Pharmacology and NeuroscienceSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Zhengyang Zhou
- Department of Biostatistics and EpidemiologySchool of Public HealthUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
| | - John Gutierrez
- Department of Internal MedicineTexas Institute for Graduate Medical Education and ResearchSan AntonioTexasUSA
| | - Sumedha Rao
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Rodwan Jomaa
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Kumudu Subasinghe
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Danielle Marie Reid
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Talisa Silzer
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Nicole Phillips
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
- Department of MicrobiologyImmunology and GeneticsSchool of Biomedical SciencesUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Sid O'Bryant
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
| | - Robert Clinton Barber
- Department of Family Medicine & Manipulative MedicineTexas College of Osteopathic MedicineUniversity of North Texas Health Science CenterFort WorthTexasUSA
- Institute for Translational ResearchUNT Health Science CenterFort WorthTexasUSA
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40
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Doumatey AP, Bentley AR, Akinyemi R, Olanrewaju TO, Adeyemo A, Rotimi C. Genes, environment, and African ancestry in cardiometabolic disorders. Trends Endocrinol Metab 2023; 34:601-621. [PMID: 37598069 PMCID: PMC10548552 DOI: 10.1016/j.tem.2023.07.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/24/2023] [Accepted: 07/25/2023] [Indexed: 08/21/2023]
Abstract
The past two decades have been characterized by a substantial global increase in cardiometabolic diseases, but the prevalence and incidence of these diseases and related traits differ across populations. African ancestry populations are among the most affected yet least included in research. Populations of African descent manifest significant genetic and environmental diversity and this under-representation is a missed opportunity for discovery and could exacerbate existing health disparities and curtail equitable implementation of precision medicine. Here, we discuss cardiometabolic diseases and traits in the context of African descent populations, including both genetic and environmental contributors and emphasizing novel discoveries. We also review new initiatives to include more individuals of African descent in genomics to address current gaps in the field.
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Affiliation(s)
- Ayo P Doumatey
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Rufus Akinyemi
- Neuroscience and Ageing Research Unit, Institute for Advanced Medical Research and Training and Centre for Genomic and Precision Medicine, College of Medicine, University of Ibadan, Ibadan, Nigeria; Department of Neurology, University College Hospital, Ibadan, Nigeria
| | - Timothy O Olanrewaju
- Division of Nephrology, Department of Medicine, University of Ilorin & University of Ilorin Teaching Hospital, Ilorin, Nigeria
| | - Adebowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA.
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Ikanga J, Patel SS, Roberts BR, Schwinne M, Hickle S, Verberk IMW, Epenge E, Gikelekele G, Tshengele N, Kavugho I, Mampunza S, Yarasheski KE, Teunissen CE, Stringer A, Levey A, Alonso A. Association of plasma biomarkers with cognitive function in persons with dementia and cognitively healthy in the Democratic Republic of Congo. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12496. [PMID: 37954546 PMCID: PMC10632676 DOI: 10.1002/dad2.12496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 09/15/2023] [Accepted: 09/26/2023] [Indexed: 11/14/2023]
Abstract
Introduction This study investigates whether plasma biomarkers (Aβ42/40 and p-tau 181), APS, as well as apolipoprotein E (APOE) proteotype predict cognitive deficits in elderly adults from the Democratic Republic of Congo. Methods Forty-four with possible AD (pAD) and 41 healthy control (HC) subjects were screened using CSID and AQ, underwent cognitive assessment with the African Neuropsychology Battery (ANB), and provided blood samples for plasma Aβ42, Aβ40, Aβ42/40, and APOE proteotype. Linear and logistic regression were used to evaluate the associations of plasma biomarkers with ANB tests and the ability of biomarkers to predict cognitive status. Results Patients with pAD had significantly lower plasma Aβ42/40 levels, higher APS, and higher prevalence of APOE E4 allele compared to HC. Groups did not differ in levels of Aβ40, Aβ42, or P-tau 181. Results showed that Aβ42/40 ratio and APS were significantly associated with African Naming Test (ANT), African List Memory Test (ALMT), and African Visuospatial Memory Test (AVMT) scores, while the presence of APOE E4 allele was associated with ANT, ALMT, AVMT, and APT scores. P-tau 181 did not show any significant associations while adjusting for age, education, and gender. APS showed the highest area under the curve (AUC) value (AUC = 0.78, 95% confidence interval [CI]: 0.68-0.88) followed by Aβ42/40 (AUC = 0.75, 95% CI: 0.66-0.86) and APOE E4 (AUC = 0.69 (CI 0.57-0.81) in discriminating pAD from HC. Discussion These results demonstrate associations between select plasma biomarker of AD pathology (Aβ42/40), APS, and APOE E4 allele) and ANB test scores and the ability of these biomarkers to differentiate pAD from cognitively normal SSA individuals, consistent with findings reported in other settings.
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Affiliation(s)
- Jean Ikanga
- Department of Rehabilitation MedicineEmory University School of MedicineAtlantaGeorgiaUSA
- Department of PsychiatrySchool of MedicineUniversity of Kinshasa and Catholic University of CongoKinshasaDemocratic Republic of Congo
| | - Saranya Sundaram Patel
- Department of Rehabilitation MedicineEmory University School of MedicineAtlantaGeorgiaUSA
| | - Blaine R. Roberts
- Department of BiochemistryDepartment of neurologySchool of MedicineEmory UniversityAtlantaGeorgiaUSA
| | - Megan Schwinne
- Department of EpidemiologyRollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
| | - Sabrina Hickle
- Department of Rehabilitation MedicineEmory University School of MedicineAtlantaGeorgiaUSA
| | - Inge M. W. Verberk
- Neurochemistry laboratoryDepartment of Clinical ChemistryAmsterdam Neuroscience, NeurodegenerationAmsterdam University Medical Centers, Vrije UniversitietAmsterdamThe Netherlands
| | - Emmanuel Epenge
- Department of neurologyUniversity of KinshasaKinshasaDemocratic Republic of Congo
| | - Guy Gikelekele
- Department of PsychiatrySchool of MedicineUniversity of Kinshasa and Catholic University of CongoKinshasaDemocratic Republic of Congo
| | - Nathan Tshengele
- Department of PsychiatrySchool of MedicineUniversity of Kinshasa and Catholic University of CongoKinshasaDemocratic Republic of Congo
| | | | - Samuel Mampunza
- Department of PsychiatrySchool of MedicineUniversity of Kinshasa and Catholic University of CongoKinshasaDemocratic Republic of Congo
| | | | - Charlotte E. Teunissen
- Neurochemistry laboratoryDepartment of Clinical ChemistryAmsterdam Neuroscience, NeurodegenerationAmsterdam University Medical Centers, Vrije UniversitietAmsterdamThe Netherlands
| | - Anthony Stringer
- Department of Rehabilitation MedicineEmory University School of MedicineAtlantaGeorgiaUSA
| | - Allan Levey
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Alvaro Alonso
- Department of EpidemiologyRollins School of Public HealthEmory UniversityAtlantaGeorgiaUSA
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Tan L, Shi J, Moghadami S, Parasar B, Wright CP, Seo Y, Vallejo K, Cobos I, Duncan L, Chen R, Deisseroth K. Lifelong restructuring of 3D genome architecture in cerebellar granule cells. Science 2023; 381:1112-1119. [PMID: 37676945 PMCID: PMC11059189 DOI: 10.1126/science.adh3253] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 08/03/2023] [Indexed: 09/09/2023]
Abstract
The cerebellum contains most of the neurons in the human brain and exhibits distinctive modes of development and aging. In this work, by developing our single-cell three-dimensional (3D) genome assay-diploid chromosome conformation capture, or Dip-C-into population-scale (Pop-C) and virus-enriched (vDip-C) modes, we resolved the first 3D genome structures of single cerebellar cells, created life-spanning 3D genome atlases for both humans and mice, and jointly measured transcriptome and chromatin accessibility during development. We found that although the transcriptome and chromatin accessibility of cerebellar granule neurons mature in early postnatal life, 3D genome architecture gradually remodels throughout life, establishing ultra-long-range intrachromosomal contacts and specific interchromosomal contacts that are rarely seen in neurons. These results reveal unexpected evolutionarily conserved molecular processes that underlie distinctive features of neural development and aging across the mammalian life span.
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Affiliation(s)
- Longzhi Tan
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
| | - Jenny Shi
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
- Department of Chemistry, Stanford University, Stanford, CA, 94305
| | - Siavash Moghadami
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Chemical and Systems Biology, Stanford University, Stanford, CA, 94305
| | - Bibudha Parasar
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
| | - Cydney P. Wright
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
- Department of Biology, Stanford University, Stanford, CA, 94305
| | - Yunji Seo
- Department of Neurobiology, Stanford University, Stanford, CA, 94305
| | - Kristen Vallejo
- Department of Pathology, Stanford University, Stanford, CA, 94305
| | - Inma Cobos
- Department of Pathology, Stanford University, Stanford, CA, 94305
| | - Laramie Duncan
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305
| | - Ritchie Chen
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, 94305
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, 94305
- Howard Hughes Medical Institute, Stanford, CA, 94305
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43
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Conceição SDS, de Carvalho DSB, Batista JET, Lyrio AO, Souza ES, de Matos PJDS, Hintz AM, da Cruz SS, Gomes-Filho IS, Figueiredo ACMG. Temporal Trends in Mortality from Alzheimer's Disease in Federal District, Brazil: An Ecological Study (2010-2018). INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6713. [PMID: 37754573 PMCID: PMC10530803 DOI: 10.3390/ijerph20186713] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2023] [Revised: 08/08/2023] [Accepted: 08/29/2023] [Indexed: 09/28/2023]
Abstract
INTRODUCTION Neuropsychiatric diseases, particularly dementias, has become more prominent with a great impact on the quality of life of the elderly population. OBJECTIVE To verify the rate of increase in mortality due to Alzheimer's disease in the Federal District, Brazil from 2010 to 2018. METHOD An ecological study was conducted, with a time series, about the evolution of the mortality coefficient in the Federal District, Brazil carried out at the Federal District State Department of Health. Mortality rates were defined as the dependent variable and years evaluated as the independent variable-from 2010 to 2018. For temporal trend analysis, the Prais-Winsten linear regression model was used and the increment rate with the respective 95% confidence interval was estimated. RESULTS From 2010 to 2018, 1665 deaths which had Alzheimer's disease as the underlying cause were recorded in the Mortality Information System. The results showed an overall mortality rate of 6.55 deaths per 100,000 inhabitants, with a higher predominance in females, non-Black people, and those aged 80 years or older. There was an increase in the annual trend of the overall mortality coefficient in both sexes. CONCLUSION The findings demonstrated a significant increase in the temporal evolution of mortality due to Alzheimer's disease in the Federal District, Brazil. It was recommended to conduct original studies to evaluate the factors that can cause the disease in order to collaborate in the process of formulating policies in the area of public health and improvements in clinical practice.
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Affiliation(s)
| | | | | | | | - Elivan Silva Souza
- Department of Health, University of Brasília, Brasília 70910-900, Brazil
| | | | - Alexandre Marcelo Hintz
- Department of Health, Feira de Santana State University, Feira de Santana 44036-900, Bahia, Brazil
| | - Simone Seixas da Cruz
- Department of Epidemiology, Federal University of Recôncavo of Bahia, Santo Antônio de Jesus 44574-490, Bahia, Brazil
| | - Isaac Suzart Gomes-Filho
- Department of Health, Feira de Santana State University, Feira de Santana 44036-900, Bahia, Brazil
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44
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Le Guen Y, Luo G, Ambati A, Damotte V, Jansen I, Yu E, Nicolas A, de Rojas I, Peixoto Leal T, Miyashita A, Bellenguez C, Lian MM, Parveen K, Morizono T, Park H, Grenier-Boley B, Naito T, Küçükali F, Talyansky SD, Yogeshwar SM, Sempere V, Satake W, Alvarez V, Arosio B, Belloy ME, Benussi L, Boland A, Borroni B, Bullido MJ, Caffarra P, Clarimon J, Daniele A, Darling D, Debette S, Deleuze JF, Dichgans M, Dufouil C, During E, Düzel E, Galimberti D, Garcia-Ribas G, García-Alberca JM, García-González P, Giedraitis V, Goldhardt O, Graff C, Grünblatt E, Hanon O, Hausner L, Heilmann-Heimbach S, Holstege H, Hort J, Jung YJ, Jürgen D, Kern S, Kuulasmaa T, Lee KH, Lin L, Masullo C, Mecocci P, Mehrabian S, de Mendonça A, Boada M, Mir P, Moebus S, Moreno F, Nacmias B, Nicolas G, Niida S, Nordestgaard BG, Papenberg G, Papma J, Parnetti L, Pasquier F, Pastor P, Peters O, Pijnenburg YAL, Piñol-Ripoll G, Popp J, Porcel LM, Puerta R, Pérez-Tur J, Rainero I, Ramakers I, Real LM, Riedel-Heller S, Rodriguez-Rodriguez E, Ross OA, Luís Royo J, Rujescu D, Scarmeas N, Scheltens P, Scherbaum N, Schneider A, Seripa D, Skoog I, Solfrizzi V, Spalletta G, Squassina A, van Swieten J, Sánchez-Valle R, Tan EK, Tegos T, Teunissen C, Thomassen JQ, Tremolizzo L, Vyhnalek M, Verhey F, Waern M, Wiltfang J, Zhang J, Zetterberg H, Blennow K, He Z, Williams J, Amouyel P, Jessen F, Kehoe PG, Andreassen OA, Van Duin C, Tsolaki M, Sánchez-Juan P, Frikke-Schmidt R, Sleegers K, Toda T, Zettergren A, Ingelsson M, Okada Y, Rossi G, Hiltunen M, Gim J, Ozaki K, Sims R, Foo JN, van der Flier W, Ikeuchi T, Ramirez A, Mata I, Ruiz A, Gan-Or Z, Lambert JC, Greicius MD, Mignot E. Multiancestry analysis of the HLA locus in Alzheimer's and Parkinson's diseases uncovers a shared adaptive immune response mediated by HLA-DRB1*04 subtypes. Proc Natl Acad Sci U S A 2023; 120:e2302720120. [PMID: 37643212 PMCID: PMC10483635 DOI: 10.1073/pnas.2302720120] [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: 03/02/2023] [Accepted: 05/18/2023] [Indexed: 08/31/2023] Open
Abstract
Across multiancestry groups, we analyzed Human Leukocyte Antigen (HLA) associations in over 176,000 individuals with Parkinson's disease (PD) and Alzheimer's disease (AD) versus controls. We demonstrate that the two diseases share the same protective association at the HLA locus. HLA-specific fine-mapping showed that hierarchical protective effects of HLA-DRB1*04 subtypes best accounted for the association, strongest with HLA-DRB1*04:04 and HLA-DRB1*04:07, and intermediary with HLA-DRB1*04:01 and HLA-DRB1*04:03. The same signal was associated with decreased neurofibrillary tangles in postmortem brains and was associated with reduced tau levels in cerebrospinal fluid and to a lower extent with increased Aβ42. Protective HLA-DRB1*04 subtypes strongly bound the aggregation-prone tau PHF6 sequence, however only when acetylated at a lysine (K311), a common posttranslational modification central to tau aggregation. An HLA-DRB1*04-mediated adaptive immune response decreases PD and AD risks, potentially by acting against tau, offering the possibility of therapeutic avenues.
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Affiliation(s)
- Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford94305, CA
- Institut du Cerveau–Paris Brain Institute–ICM, Paris75013, France
| | - Guo Luo
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | - Aditya Ambati
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | - Vincent Damotte
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille59000, France
| | - Iris Jansen
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HVAmsterdam, The Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije University, 1081 HVAmsterdam, The Netherlands
| | - Eric Yu
- The Neuro (Montreal Neurological Institute-Hospital), Montreal, QuebecH3A 2B4, Canada
- Department of Human Genetics, McGill University, Montreal, QuebecH3A 0G4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QuebecH3A 0G4, Canada
| | - Aude Nicolas
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille59000, France
| | - Itziar de Rojas
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona08029, Spain
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
| | - Thiago Peixoto Leal
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland44196, OH
| | - Akinori Miyashita
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata950-218, Japan
| | - Céline Bellenguez
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille59000, France
| | - Michelle Mulan Lian
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore308232, Singapore
- Laboratory of Neurogenetics, Genome Institute of Singapore, A*STAR, Singapore138672, Singapore
| | - Kayenat Parveen
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne50937, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn53127, Germany
| | - Takashi Morizono
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu474-8511, Japan
| | - Hyeonseul Park
- Department of Biomedical Science, Chosun University, Gwangju61452, Korea
| | - Benjamin Grenier-Boley
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille59000, France
| | - Tatsuhiko Naito
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita565-0871, Japan
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo192-0982, Japan
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp2610, Belgium
- Laboratory of Neurogenetics, Institute Born–Bunge, Antwerp2610, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp2000, Belgium
| | - Seth D. Talyansky
- Department of Neurology and Neurological Sciences, Stanford University, Stanford94305, CA
| | - Selina Maria Yogeshwar
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
- Department of Neurology, Charité–Universitätsmedizin, Berlin10117, Germany
- Charité–Universitätsmedizin Berlin, Einstein Center for Neurosciences Berlin, Berlin10117, Germany
| | - Vicente Sempere
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | - Wataru Satake
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo192-0982, Japan
| | - Victoria Alvarez
- Laboratorio de Genética, Hospital Universitario Central de Asturias, Oviedo33011, Spain
- Instituto de Investigación Sanitaria del Principado de Asturias, Oviedo33011, Spain
| | - Beatrice Arosio
- Department of Clinical Sciences and Community Health, University of Milan, Milan20122, Italy
| | - Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford94305, CA
| | - Luisa Benussi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia25125, Italy
| | - Anne Boland
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, Evry91057, France
| | - Barbara Borroni
- Department of Clinical and Experimental Sciences, Centre for Neurodegenerative Disorders, Neurology Unit, University of Brescia, Brescia25123, Italy
| | - María J. Bullido
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Centro de Biología Molecular Severo Ochoa (UAM-CSIC), Universidad Autónoma de Madrid, Madrid28049, Spain
- Instituto de Investigacion Sanitaria "Hospital la Paz" (IdIPaz), Madrid48903, Spain
| | - Paolo Caffarra
- Unit of Neurology, University of Parma and AOU, Parma43121, Italy
| | - Jordi Clarimon
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Neurology, II B Sant Pau, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona08193, Spain
| | - Antonio Daniele
- Department of Neuroscience, Università Cattolica del Sacro Cuore, Rome00168, Italy
- Neurology Unit, IRCCS Fondazione Policlinico Universitario A. Gemelli, Rome00168, Italy
| | - Daniel Darling
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | - Stéphanie Debette
- University Bordeaux, Inserm, Bordeaux Population Health Research Center, Bordeaux33000, France
- Department of Neurology, Bordeaux University Hospital, Bordeaux33400, France
| | - Jean-François Deleuze
- Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, Evry91057, France
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, University Hospital, Ludwig Maximilian University of Munich, 81377, Munich, Germany
- German Center for Neurodegenerative Diseases, Munich37075, Germany
- Munich Cluster for Systems Neurology, Munich81377, Germany
| | - Carole Dufouil
- Inserm, Bordeaux Population Health Research Center, UMR 1219, Univ. Bordeaux, ISPED, CIC 1401-EC, Université de Bordeaux, Bordeaux33405, France
- CHU de Bordeaux, Pole santé publique, Bordeaux33400, France
| | - Emmanuel During
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases, Magdeburg39120, Germany
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University, Magdeburg39106, Germany
| | - Daniela Galimberti
- Neurodegenerative Diseases Unit, Fondazione IRCCS Ca’ Granda, Ospedale Policlinico, Milan20122, Italy
- Department of Biomedical, Surgical and Dental Sciences, University of Milan, Milan20122, Italy
| | | | - José María García-Alberca
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Alzheimer Research Center and Memory Clinic, Andalusian Institute for Neuroscience, Málaga29012, Spain
| | - Pablo García-González
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona08029, Spain
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala751 22, Sweden
- Geriatrics, Uppsala University, Uppsala751 22, Sweden
| | - Oliver Goldhardt
- Department of Psychiatry and Psychotherapy, Technical University of Munich, School of Medicine, Klinikum recs der Isar, Munich80333, Germany
| | - Caroline Graff
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital-Solna, Stockholm171 64, Swdeen
| | - Edna Grünblatt
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Hospital of Psychiatry Zurich, University of Zurich, Zurich8032, Switzerland
- Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich8057, Switzerland
- Zurich Center for Integrative Human Physiology, University of Zurich, Zurich8057, Switzerland
| | - Olivier Hanon
- Université de Paris, EA 4468, APHP, Hôpital Broca, Paris75013, France
| | - Lucrezia Hausner
- Department of Geriatric Psychiatry, Central Institute for Mental Health Mannheim, Faculty Mannheim, University of Heidelberg, Heidelberg68159, Germany
| | - Stefanie Heilmann-Heimbach
- Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, Bonn53127, Germany
| | - Henne Holstege
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HVAmsterdam, The Netherlands
- Department of Clinical Genetics, VU University Medical Centre, Amsterdam1081 HV, The Netherlands
| | - Jakub Hort
- Department of Neurology, Memory Clinic, Charles University, 2nd Faculty of Medicine and Motol University Hospital, Prague150 06, Czech Republic
- International Clinical Research Center, St. Anne’s University Hospital Brno, Brno656 91, Czech Republic
| | - Yoo Jin Jung
- Stanford Neurosciences Interdepartmental Program, Stanford University School of Medicine, Stanford94305, CA
| | - Deckert Jürgen
- Department of Psychiatry, Psychosomatics and Psychotherapy, Center of Mental Health, University Hospital of Würzburg, Würzburg97080, Germany
| | - Silke Kern
- Department of Psychiatry and Neurochemistry, Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg405 30, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg413 45, Sweden
| | - Teemu Kuulasmaa
- Institute of Biomedicine, University of Eastern Finland, Joensuu, Kuopio, Eastern Finland80101, Finland
| | - Kun Ho Lee
- Department of Biomedical Science, Chosun University, Gwangju61452, Republic of Korea
- Department of Integrative Biological Sciences, Chosun University, Gwangju61452, Republic of Korea
- Gwangju Alzheimer's and Related Dementias Cohort Research Center, Chosun University, Gwangju61452, Republic of Korea
- Korea Brain Research Institute, Daegu41062, Republic of Korea
- Neurozen Inc., Seoul06236, Republic of Korea
| | - Ling Lin
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | - Carlo Masullo
- Institute of Neurology, Catholic University of the Sacred Heart, Rome20123, Italy
| | - Patrizia Mecocci
- Department of Medicine and Surgery, Institute of Gerontology and Geriatrics, University of Perugia, Perugia06123, Italy
| | - Shima Mehrabian
- Clinic of Neurology, UH “Alexandrovska”, Medical University–Sofia, Sofia1431, Bulgaria
| | | | - Mercè Boada
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona08029, Spain
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
| | - Pablo Mir
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville41013, Spain
| | - Susanne Moebus
- Institute for Urban Public Health, University Hospital of University Duisburg-Essen, Essen45147, Germany
| | - Fermin Moreno
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Department of Neurology, Hospital Universitario Donostia, San Sebastian20014, Spain
- Neurosciences Area, Instituto Biodonostia, San Sebastian20014, Spain
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health University of Florence, Florence50121, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence20162, Italy
| | - Gael Nicolas
- Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Inserm U1245 and CHU Rouen, RouenF-76000, France
| | - Shumpei Niida
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu474-8511, Japan
| | - Børge G. Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital-Herlev Gentofte, Copenhagen2730, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen1172, Denmark
| | - Goran Papenberg
- Department of Neurobiology, Care Sciences and Society, Aging Research Center, Karolinska Institutet and Stockholm University, Stockholm171 77, Sweden
| | - Janne Papma
- Department of Neurology, Alzheimer Center Erasmus MC, Erasmus University Medical Center, Rotterdam3000, The Netherlands
| | - Lucilla Parnetti
- Centre for Memory Disturbances, Lab of Clinical Neurochemistry, Section of Neurology, University of Perugia, Perugia06123, Italy
| | - Florence Pasquier
- Université de Lille, Inserm 1172, CHU Clinical and Research Memory Research Centre of Distalz, Lille59000, France
| | - Pau Pastor
- Fundació Docència i Recerca MútuaTerrassa, Terrassa, Barcelona08221, Spain
- Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona08221, Spain
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin37075, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute of Psychiatry and Psychotherapy, Berlin12203, Germany
| | - Yolande A. L. Pijnenburg
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HVAmsterdam, The Netherlands
| | - Gerard Piñol-Ripoll
- Unitat Trastorns Cognitius, Hospital Universitari Santa Maria de Lleida, Lleida25198, Spain
- Institut de Recerca Biomedica de Lleida, Lleida25198, Spain
| | - Julius Popp
- Department of Psychiatry, Old Age Psychiatry, Lausanne University Hospital, Lausanne1005, Switzerland
- Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich8032, Switzerland
- Institute for Regenerative Medicine, University of Zürich, Zürich8952, Switzerland
| | - Laura Molina Porcel
- Neurological Tissue Bank–Biobanc- Hospital Clinic-Institut d'Investigacions Biomèdiques August Pi i Sunyer, Barcelona08036, Spain
- Alzheimer’s disease and other cognitive disorders Unit, Neurology Department, Hospital Clinic, Barcelona08036, Spain
| | - Raquel Puerta
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona08029, Spain
| | - Jordi Pérez-Tur
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Unitat de Genètica Molecular, Institut de Biomedicina de València-Consejo Superior de Investigaciones CientíficasValencia46010, Spain
- Unidad Mixta de Neurologia Genètica, Instituto de Investigación Sanitaria La Fe, Valencia46026, Spain
| | - Innocenzo Rainero
- Department of Neuroscience “Rita Levi Montalcini”, University of Torino, Torino10126, Italy
| | - Inez Ramakers
- Department of Psychiatry and Neuropsychologie, Alzheimer Center Limburg, Maastricht University, Maastricht6229 GS, The Netherlands
| | - Luis M. Real
- Unidad Clínica de Enfermedades Infecciosas y Microbiología, Hospital Universitario de Valme, Sevilla41014, Spain
- Depatamento de Especialidades Quirúrgicas, Bioquímica e Inmunología, Facultad de Medicina, Universidad de Málaga, Málaga29010, Spain
| | - Steffi Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Leipzig04109, Germany
| | - Eloy Rodriguez-Rodriguez
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Neurology Service, Marqués de Valdecilla University Hospital (University of Cantabria and IDIVAL), Santander39011, Spain
| | - Owen A. Ross
- Department of Neuroscience, Mayo Clinic-Florida, Jacksonville32224, FL
- Department of Clinical Genomics, Mayo Clinic-Florida, Jacksonville32224, FL
| | - Jose Luís Royo
- Depatamento de Especialidades Quirúrgicas, Bioquímica e Inmunología. Facultad de Medicina, Universidad de Málaga, Málaga29010, Spain
| | - Dan Rujescu
- Martin-Luther-University Halle-Wittenberg, University Clinic and Outpatient Clinic for Psychiatry, Psychotherapy and Psychosomatics, Halle (Saale)06120, Germany
| | - Nikolaos Scarmeas
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York10032, NY
- 1st Department of Neurology, Aiginition Hospital, National and Kapodistrian University of Athens, Medical School, Athens106 79, Greece
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HVAmsterdam, The Netherlands
| | - Norbert Scherbaum
- Department of Psychiatry and Psychotherapy, Medical Faculty, LVR-Hospital Essen, University of Duisburg-Essen, 45147Duisberg, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (Deutsches Zentrum für Neurodegenerative Erkrankungen), 37075Göttingen, Germany
- Department for Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn53127, Germany
| | - Davide Seripa
- Department of Hematology and Stem Cell Transplant, Laboratory for Advanced Hematological Diagnostics, Lecce73100, Italy
| | - Ingmar Skoog
- Department of Psychiatry and Neurochemistry, Neuropsychiatric Epidemiology Unit, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg405 30, Sweden
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg405 30, Sweden
| | - Vincenzo Solfrizzi
- Interdisciry Department of Medicine, Geriatric Medicine and Memory Unit, University of Bari “A. Moro, Bari70121, Italy
| | - Gianfranco Spalletta
- Laboratory of Neuropsychiatry, IRCCS Santa Lucia Foundation, Rome00179, Italy
- Department of Psychiatry and Behavioral Sciences, Baylor College of Medicine, Houston77030, TX
| | - Alessio Squassina
- Department of Biomedical Sciences, University of Cagliari, Cagliari09124, Italy
| | - John van Swieten
- Department of Neurology, ErasmusMC, Rotterdam3000CA, Netherlands
| | - Raquel Sánchez-Valle
- Alzheimer's disease and other cognitive disorders unit, Service of Neurology, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer, University of Barcelona, Barcelona08036, Spain
| | - Eng-King Tan
- Department of Neurology, National Neuroscience Institute, Singapore General Hospital, Singapore308433, Singapore
- Duke-National University of Singapore Medical School, Singapore169857, Singapore
| | - Thomas Tegos
- 1st Department of Neurology, Medical school, Aristotle University of Thessaloniki, Thessaloniki541 24, Greece
| | - Charlotte Teunissen
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam1081 HV, Netherlands
| | - Jesper Qvist Thomassen
- Department of Clinical Biochemistry, Copenhagen University Hospital–Rigshospitalet, Copenhagen2100, Denmark
| | - Lucio Tremolizzo
- Neurology, "San Gerardo" hospital, Monza and University of Milano-Bicocca, Monza20900, Italy
| | - Martin Vyhnalek
- Department of Clinical Genetics, VU University Medical Centre, Amsterdam1081 HV, The Netherlands
- Department of Neurology, Memory Clinic, Charles University, 2nd Faculty of Medicine and Motol University Hospital, Prague150 06, Czech Republic
| | - Frans Verhey
- Department of Psychiatry and Neuropsychologie, Alzheimer Center Limburg, Maastricht University, Maastricht6229 GS, Netherlands
| | - Margda Waern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg431 41, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg413 45, Sweden
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen37075, Germany
- German Center for Neurodegenerative Diseases (Deutsches Zentrum für Neurodegenerative Erkrankungen), Goettingen37075, Germany
- Department of Medical Sciences, Neurosciences and Signaling Group, Institute of Biomedicine, University of Aveiro, Aveiro3810-193, Portugal
| | - Jing Zhang
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
| | | | | | | | | | | | | | | | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, MölndalSE-43180, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, LondonWC1E 6BT, United Kingdom
- UK Dementia Research Institute at UCL, LondonWC1E 6BT, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, MölndalSE-43180, Sweden
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford94305, CA
| | - Julie Williams
- UKDRI@Cardiff, School of Medicine, Cardiff University, WalesCF14 4YS, United Kingdom
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff WalesCF14 4XN, United Kingdom
| | - Philippe Amouyel
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille59000, France
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (Deutsches Zentrum für Neurodegenerative Erkrankungen), 37075Göttingen, Germany
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne50937, Germany
- Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases, University of Cologne, Cologne50931, Germany
| | - Patrick G. Kehoe
- Translational Health Sciences, Bristol Medical School, University of Bristol, BristolBS8 1QU, United Kingdom
| | - Ole A. Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital, Oslo0450, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Cornelia Van Duin
- Department of Epidemiology, ErasmusMC, Rotterdam3000 CA, The Netherlands
- Nuffield Department of Population Health Oxford University, OxfordOX3 7LF, United Kingdom
| | - Magda Tsolaki
- 1st Department of Neurology, Medical school, Aristotle University of Thessaloniki, Thessaloniki541 24, Greece
| | - Pascual Sánchez-Juan
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
- Alzheimer’s Centre Reina Sofia-CIEN Foundation, Madrid, Spain
| | - Ruth Frikke-Schmidt
- Department of Clinical Medicine, University of Copenhagen, Copenhagen1172, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital–Rigshospitalet, Copenhagen2100, Denmark
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp2610, Belgium
- Laboratory of Neurogenetics, Institute Born–Bunge, Antwerp2610, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp2000, Belgium
| | - Tatsushi Toda
- Department of Neurology, Graduate School of Medicine, The University of Tokyo, Tokyo192-0982, Japan
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg431 41, Sweden
| | - Martin Ingelsson
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala751 22, Sweden
- Geriatrics, Uppsala University, Uppsala751 22, Sweden
- Krembil Brain Institute, University Health Network, TorontoM5G 2C4, Canada
- Department of Medicine and Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, TorontoM5S 1A8, Canada
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita565-0871, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita565-0871, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita565-0871, Japan
- Center for Infectious Disease Education and Research, Osaka University, Suita565-0871, Japan
| | - Giacomina Rossi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan20133, Italy
| | - Mikko Hiltunen
- Institute of Biomedicine, University of Eastern Finland, Joensuu, Kuopio, Eastern Finland80101, Finland
| | - Jungsoo Gim
- Department of Biomedical Science, Chosun University, Gwangju61452, Korea
- Department of Integrative Biological Sciences, Chosun University, Gwangju61452, Republic of Korea
- Gwangju Alzheimer's and Related Dementias Cohort Research Center, Chosun University, Gwangju61452, Republic of Korea
| | - Kouichi Ozaki
- Medical Genome Center, Research Institute, National Center for Geriatrics and Gerontology, Obu474-8511, Japan
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Rebecca Sims
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, WalesCF14 4YS, United Kingdom
| | - Jia Nee Foo
- Lee Kong Chian School of Medicine, Nanyang Technological University Singapore, Singapore308232, Singapore
- Laboratory of Neurogenetics, Genome Institute of Singapore, A*STAR, Singapore138672, Singapore
| | - Wiesje van der Flier
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1081 HVAmsterdam, The Netherlands
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata950-218, Japan
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne50937, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn53127, Germany
- German Center for Neurodegenerative Diseases (Deutsches Zentrum für Neurodegenerative Erkrankungen), 37075Göttingen, Germany
- Cluster of Excellence Cellular Stress Responses in Aging-associated Diseases, University of Cologne, Cologne50931, Germany
- Department of Psychiatry and Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio78229, TX
| | - Ignacio Mata
- Genomic Medicine, Lerner Research Institute, Cleveland Clinic, Cleveland44196, OH
| | - Agustín Ruiz
- Research Center and Memory clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona08029, Spain
- Networking Research Center on Neurodegenerative Diseases (CIRNED), Instituto de Salud Carlos III, Madrid28029, Spain
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), Montreal, QuebecH3A 2B4, Canada
- Department of Human Genetics, McGill University, Montreal, QuebecH3A 0G4, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QuebecH3A 0G4, Canada
| | - Jean-Charles Lambert
- Université de Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE facteurs de risque et déterminants moléculaires des maladies liés au vieillissement, Lille59000, France
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford94305, CA
| | - Emmanuel Mignot
- Center for Sleep Sciences and Medicine, Stanford University, Palo Alto94304, CA
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Park JY, Lee JJ, Lee Y, Lee D, Gim J, Farrer L, Lee KH, Won S. Machine learning-based quantification for disease uncertainty increases the statistical power of genetic association studies. Bioinformatics 2023; 39:btad534. [PMID: 37665736 PMCID: PMC10539075 DOI: 10.1093/bioinformatics/btad534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Revised: 07/25/2023] [Accepted: 09/01/2023] [Indexed: 09/06/2023] Open
Abstract
MOTIVATION Allowance for increasingly large samples is a key to identify the association of genetic variants with Alzheimer's disease (AD) in genome-wide association studies (GWAS). Accordingly, we aimed to develop a method that incorporates patients with mild cognitive impairment and unknown cognitive status in GWAS using a machine learning-based AD prediction model. RESULTS Simulation analyses showed that weighting imputed phenotypes method increased the statistical power compared to ordinary logistic regression using only AD cases and controls. Applied to real-world data, the penalized logistic method had the highest AUC (0.96) for AD prediction and weighting imputed phenotypes method performed well in terms of power. We identified an association (P<5.0×10-8) of AD with several variants in the APOE region and rs143625563 in LMX1A. Our method, which allows the inclusion of individuals with mild cognitive impairment, improves the statistical power of GWAS for AD. We discovered a novel association with LMX1A. AVAILABILITY AND IMPLEMENTATION Simulation codes can be accessed at https://github.com/Junkkkk/wGEE_GWAS.
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Affiliation(s)
- Jun Young Park
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea
- Neurozen Inc., Seoul 06168, Korea
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju 61452, Korea
| | - Jang Jae Lee
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju 61452, Korea
| | - Younghwa Lee
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea
| | - Dongsoo Lee
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea
| | - Jungsoo Gim
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju 61452, Korea
- Department of Biomedical Science, Chosun University, Gwangju 61452, Korea
| | - Lindsay Farrer
- Departments of Medicine (Biomedical Genetics), Neurology, and Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, United States
- Departments of Epidemiology and Biostatistics, Boston University School of Public Health, Boston, MA 02118, United States
| | - Kun Ho Lee
- Gwangju Alzheimer’s & Related Dementia Cohort Research Center, Chosun University, Gwangju 61452, Korea
- Department of Biomedical Science, Chosun University, Gwangju 61452, Korea
- Korea Brain Research Institute, Daegu 41068, Korea
| | - Sungho Won
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea
- Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 08826, Korea
- Institute of Health and Environment, Seoul National University, Seoul 08826, Korea
- RexSoft Inc, Seoul 08826, Korea
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46
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Cochran JN, Acosta-Uribe J, Esposito BT, Madrigal L, Aguillón D, Giraldo MM, Taylor JW, Bradley J, Fulton-Howard B, Andrews SJ, Acosta-Baena N, Alzate D, Garcia GP, Piedrahita F, Lopez HE, Anderson AG, Rodriguez-Nunez I, Roberts K, Dominantly Inherited Alzheimer Network, Absher D, Myers RM, Beecham GW, Reitz C, Rizzardi LF, Fernandez MV, Goate AM, Cruchaga C, Renton AE, Lopera F, Kosik KS. Genetic associations with age at dementia onset in the PSEN1 E280A Colombian kindred. Alzheimers Dement 2023; 19:3835-3847. [PMID: 36951251 PMCID: PMC10514237 DOI: 10.1002/alz.13021] [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: 10/31/2022] [Revised: 02/03/2023] [Accepted: 02/07/2023] [Indexed: 03/24/2023]
Abstract
INTRODUCTION Genetic associations with Alzheimer's disease (AD) age at onset (AAO) could reveal genetic variants with therapeutic applications. We present a large Colombian kindred with autosomal dominant AD (ADAD) as a unique opportunity to discover AAO genetic associations. METHODS A genetic association study was conducted to examine ADAD AAO in 340 individuals with the PSEN1 E280A mutation via TOPMed array imputation. Replication was assessed in two ADAD cohorts, one sporadic early-onset AD study and four late-onset AD studies. RESULTS 13 variants had p<1×10-7 or p<1×10-5 with replication including three independent loci with candidate associations with clusterin including near CLU. Other suggestive associations were identified in or near HS3ST1, HSPG2, ACE, LRP1B, TSPAN10, and TSPAN14. DISCUSSION Variants with suggestive associations with AAO were associated with biological processes including clusterin, heparin sulfate, and amyloid processing. The detection of these effects in the presence of a strong mutation for ADAD reinforces their potentially impactful role.
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Affiliation(s)
| | - Juliana Acosta-Uribe
- Neuroscience Research Institute, University of California, Santa Barbara, California, and Department of Molecular Cellular and Developmental Biology University of California, Santa Barbara, California, USA
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Bianca T Esposito
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Lucia Madrigal
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - David Aguillón
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Margarita M Giraldo
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Jared W Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Joseph Bradley
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Brian Fulton-Howard
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Shea J Andrews
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Natalia Acosta-Baena
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Diana Alzate
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Gloria P Garcia
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Francisco Piedrahita
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Hugo E Lopez
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | | | | | - Kevin Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | | | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Gary W Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Christiane Reitz
- Department of Epidemiology, Sergievsky Center, Taub Institute for Research on the Aging Brain, Columbia University, New York, New York, USA
| | | | | | - Alison M Goate
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Carlos Cruchaga
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Alan E Renton
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Kenneth S Kosik
- Neuroscience Research Institute, University of California, Santa Barbara, California, and Department of Molecular Cellular and Developmental Biology University of California, Santa Barbara, California, USA
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Celis K, Moreno MDMM, Rajabli F, Whitehead P, Hamilton-Nelson K, Dykxhoorn DM, Nuytemans K, Wang L, Flanagan M, Weintraub S, Geula C, Gearing M, Dalgard CL, Jin F, Bennett DA, Schuck T, Pericak-Vance MA, Griswold AJ, Young JI, Vance JM. Ancestry-related differences in chromatin accessibility and gene expression of APOE ε4 are associated with Alzheimer's disease risk. Alzheimers Dement 2023; 19:3902-3915. [PMID: 37037656 PMCID: PMC10529851 DOI: 10.1002/alz.13075] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 03/03/2023] [Accepted: 03/08/2023] [Indexed: 04/12/2023]
Abstract
INTRODUCTION European local ancestry (ELA) surrounding apolipoprotein E (APOE) ε4 confers higher risk for Alzheimer's disease (AD) compared to African local ancestry (ALA). We demonstrated significantly higher APOE ε4 expression in ELA versus ALA in AD brains from APOE ε4/ε4 carriers. Chromatin accessibility differences could contribute to these expression changes. METHODS We performed single nuclei assays for transposase accessible chromatin sequencing from the frontal cortex of six ALA and six ELA AD brains, homozygous for local ancestry and APOE ε4. RESULTS Our results showed an increased chromatin accessibility at the APOE ε4 promoter area in ELA versus ALA astrocytes. This increased accessibility in ELA astrocytes extended genome wide. Genes with increased accessibility in ELA in astrocytes were enriched for synapsis, cholesterol processing, and astrocyte reactivity. DISCUSSION Our results suggest that increased chromatin accessibility of APOE ε4 in ELA astrocytes contributes to the observed elevated APOE ε4 expression, corresponding to the increased AD risk in ELA versus ALA APOE ε4/ε4 carriers.
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Affiliation(s)
- Katrina Celis
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
| | - Maria DM. Muniz Moreno
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
| | - Farid Rajabli
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
| | - Patrice Whitehead
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
| | - Kara Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
| | - Derek M. Dykxhoorn
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
| | - Karen Nuytemans
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
| | - Liyong Wang
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
| | - Margaret Flanagan
- Northwestern ADC Neuropathology Core, Northwestern University Feinberg School of Medicine, Chicago, IL, USA, 60611
| | - Sandra Weintraub
- Northwestern ADC Neuropathology Core, Northwestern University Feinberg School of Medicine, Chicago, IL, USA, 60611
| | - Changiz Geula
- Northwestern ADC Neuropathology Core, Northwestern University Feinberg School of Medicine, Chicago, IL, USA, 60611
| | - Marla Gearing
- Goizueta Alzheimer’s Disease Research Center, Emory University, Atlanta, GA, USA, 15213
| | - Clifton L. Dalgard
- The American Genome Center, Uniformed Services University, Bethesda, MD, USA, 20814
- Collaborative Health Initiative Research Program, Henry Jackson Foundation, Bethesda, MD, USA, 20817
- Department of Anatomy Physiology & Genetics, Uniformed Services University, Bethesda, MD, USA, 20814
| | - Fulai Jin
- Cleveland Institute for Computational Biology, Case Western Reserve University, Cleveland, Ohio, USA, 44106
| | - David A. Bennett
- Department of Neurological Sciences, Rush University, Chicago, IL, USA, 60612
| | - Theresa Schuck
- The Department of Pathology and Laboratory Medicine, Institute on Aging and Center for Neurodegenerative Disease Research, The Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA,19104
| | - Margaret A. Pericak-Vance
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
| | - Anthony J. Griswold
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
| | - Juan I. Young
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
| | - Jeffery M. Vance
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, Miami, FL, USA, 33136
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA, 33136
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48
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Ray NR, Ayodele T, Jean-Francois M, Baez P, Fernandez V, Bradley J, Crane PK, Dalgard CL, Kuzma A, Nicaretta H, Sims R, Williams J, Cuccaro ML, Pericak-Vance MA, Mayeux R, Wang LS, Schellenberg GD, Cruchaga C, Beecham GW, Reitz C. The Early-Onset Alzheimer's Disease Whole-Genome Sequencing Project: Study design and methodology. Alzheimers Dement 2023; 19:4187-4195. [PMID: 37390458 PMCID: PMC10527497 DOI: 10.1002/alz.13370] [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: 02/07/2023] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 07/02/2023]
Abstract
INTRODUCTION Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations, resulting in a lack of understanding of its molecular etiology. METHODS Whole-genome sequencing and harmonization of clinical, neuropathological, and biomarker data of over 5000 EOAD cases of diverse ancestries. RESULTS A publicly available genomics resource for EOAD with extensive harmonized phenotypes. Primary analysis will (1) identify novel EOAD risk loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. DISCUSSION This novel resource complements over 50,000 control and late-onset AD samples generated through the Alzheimer's Disease Sequencing Project (ADSP). The harmonized EOAD/ADSP joint call will be available through upcoming ADSP data releases and will allow for additional analyses across the full onset range. HIGHLIGHTS Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations. This results in a significant lack of understanding of the molecular etiology of this devastating form of the disease. The Early-Onset Alzheimer's Disease Whole-genome Sequencing Project is a collaborative initiative to generate a large-scale genomics resource for early-onset Alzheimer's disease with extensive harmonized phenotype data. Primary analyses are designed to (1) identify novel EOAD risk and protective loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. The harmonized genomic and phenotypic data from this initiative will be available through NIAGADS.
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Affiliation(s)
- Nicholas R. Ray
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
- Taub Institute for Research on Alzheimer’s Disease
and the Aging Brain, Columbia University, New York, NY 10032, USA
| | - Temitope Ayodele
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
| | - Melissa Jean-Francois
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Penelope Baez
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
| | - Victoria Fernandez
- Department of Psychiatry, Neurology and Genetics,
Washington University School of Medicine, St. Louis, MO 63130, USA
- Neurogenomics and Informatic (NGI) Center, Washington
University School of Medicine, St. Louis, MO 63130, USA
| | - Joseph Bradley
- Department of Psychiatry, Neurology and Genetics,
Washington University School of Medicine, St. Louis, MO 63130, USA
- Neurogenomics and Informatic (NGI) Center, Washington
University School of Medicine, St. Louis, MO 63130, USA
| | - Paul K. Crane
- Division of General Internal Medicine, University of
Washington, Seattle, WA 98195, USA
| | - Clifton L. Dalgard
- Department of Anatomy, Physiology & Genetics,
Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- The American Genome Center, Uniformed Services University
of the Health Sciences, Bethesda, MD 20814, USA
| | - Amanda Kuzma
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Heather Nicaretta
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Rebecca Sims
- Division of Psychological Medicine and Clinical
Neurosciences, School of Medicine, Cardiff University, Cardiff CF10 3AT, UK
| | - Julie Williams
- UK Dementia Research Institute, Cardiff University,
Cardiff CF10 3AT, UK
- Division of Psychological Medicine and Clinical
Neurosciences, School of Medicine, Cardiff University, Cardiff CF10 3AT, UK
| | - Michael L. Cuccaro
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Margaret A. Pericak-Vance
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Richard Mayeux
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
- Taub Institute for Research on Alzheimer’s Disease
and the Aging Brain, Columbia University, New York, NY 10032, USA
- Department of Neurology, Columbia University, New York, NY
10032, USA
- Department of Epidemiology, Columbia University, New York,
NY 10032, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Neurology and Genetics,
Washington University School of Medicine, St. Louis, MO 63130, USA
- Neurogenomics and Informatic (NGI) Center, Washington
University School of Medicine, St. Louis, MO 63130, USA
| | - Gary W. Beecham
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
- Taub Institute for Research on Alzheimer’s Disease
and the Aging Brain, Columbia University, New York, NY 10032, USA
- Department of Neurology, Columbia University, New York, NY
10032, USA
- Department of Epidemiology, Columbia University, New York,
NY 10032, USA
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Sofer T, Kurniansyah N, Granot-Hershkovitz E, Goodman MO, Tarraf W, Broce I, Lipton RB, Daviglus M, Lamar M, Wassertheil-Smoller S, Cai J, DeCarli CS, Gonzalez HM, Fornage M. A polygenic risk score for Alzheimer's disease constructed using APOE-region variants has stronger association than APOE alleles with mild cognitive impairment in Hispanic/Latino adults in the U.S. Alzheimers Res Ther 2023; 15:146. [PMID: 37649099 PMCID: PMC10469805 DOI: 10.1186/s13195-023-01298-3] [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: 05/10/2023] [Accepted: 08/24/2023] [Indexed: 09/01/2023]
Abstract
INTRODUCTION Polygenic Risk Scores (PRSs) are summaries of genetic risk alleles for an outcome. METHODS We used summary statistics from five GWASs of AD to construct PRSs in 4,189 diverse Hispanics/Latinos (mean age 63 years) from the Study of Latinos-Investigation of Neurocognitive Aging (SOL-INCA). We assessed the PRS associations with MCI in the combined set of people and in diverse subgroups, and when including and excluding the APOE gene region. We also assessed PRS associations with MCI in an independent dataset from the Mass General Brigham Biobank. RESULTS A simple sum of 5 PRSs ("PRSsum"), each constructed based on a different AD GWAS, was associated with MCI (OR = 1.28, 95% CI [1.14, 1.41]) in a model adjusted for counts of the APOE-[Formula: see text] and APOE-[Formula: see text] alleles. Associations of single-GWAS PRSs were weaker. When removing SNPs from the APOE region from the PRSs, the association of PRSsum with MCI was weaker (OR = 1.17, 95% CI [1.04,1.31] with adjustment for APOE alleles). In all association analyses, APOE-[Formula: see text] and APOE-[Formula: see text] alleles were not associated with MCI. DISCUSSION A sum of AD PRSs is associated with MCI in Hispanic/Latino older adults. Despite no association of APOE-[Formula: see text] and APOE-[Formula: see text] alleles with MCI, the association of the AD PRS with MCI is stronger when including the APOE region. Thus, APOE variants different than the classic APOE alleles may be important predictors of MCI in Hispanic/Latino adults.
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Affiliation(s)
- Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
| | - Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Einat Granot-Hershkovitz
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Matthew O Goodman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Wassim Tarraf
- Institute of Gerontology, Wayne State University, Detroit, MI, USA
| | - Iris Broce
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
| | | | - Martha Daviglus
- Department of Medicine, Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Melissa Lamar
- Department of Medicine, Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
- Rush Alzheimer's Disease Research Center, Rush University Medical Center, Chicago, IL, USA
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Charles S DeCarli
- Department of Neurology, University of California at Davis, Sacramento, CA, USA
| | - Hector M Gonzalez
- Department of Neurosciences, University of California San Diego, San Diego, CA, USA
- Shiley-Marcos Alzheimer's Disease Center, University of California San Diego, La Jolla, CA, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
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50
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Ray NR, Kunkle BW, Hamilton-Nelson K, Kurup JT, Rajabli F, Cosacak MI, Kizil C, Jean-Francois M, Cuccaro M, Reyes-Dumeyer D, Cantwell L, Kuzma A, Vance JM, Gao S, Hendrie HC, Baiyewu O, Ogunniyi A, Akinyemi RO, Lee WP, Martin ER, Wang LS, Beecham GW, Bush WS, Farrer LA, Haines JL, Byrd GS, Schellenberg GD, Mayeux R, Pericak-Vance MA, Reitz C. Extended genome-wide association study employing the African Genome Resources Panel identifies novel susceptibility loci for Alzheimer's Disease in individuals of African ancestry. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.29.23294774. [PMID: 37693582 PMCID: PMC10491365 DOI: 10.1101/2023.08.29.23294774] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
INTRODUCTION Despite a two-fold increased risk, individuals of African ancestry have been significantly underrepresented in Alzheimer's Disease (AD) genomics efforts. METHODS GWAS of 2,903 AD cases and 6,265 cognitive controls of African ancestry. Within-dataset results were meta-analyzed, followed by gene-based and pathway analyses, and analysis of RNAseq and whole-genome sequencing data. RESULTS A novel AD risk locus was identified in MPDZ on chromosome 9p23 (rs141610415, MAF=.002, P =3.68×10 -9 ). Two additional novel common and nine novel rare loci approached genome-wide significance at P <9×10 -7 . Comparison of association and LD patterns between datasets with higher and lower degrees of African ancestry showed differential association patterns at chr12q23.2 ( ASCL1 ), suggesting that the association is modulated by regional origin of local African ancestry. DISCUSSION Increased sample sizes and sample sets from Africa covering as much African genetic diversity as possible will be critical to identify additional disease-associated loci and improve deconvolution of local genetic ancestry effects.
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