The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Dissecting the genetic relationship between cardiovascular risk factors and Alzheimer’s disease
Open accessAbstract
Cardiovascular (CV)- and lifestyle-associated risk factors (RFs) are increasingly recognized as important for Alzheimer's disease (AD) pathogenesis. Beyond the ε4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV-associated genes also increase risk for AD. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV-associated RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), triglycerides (TG), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TG, TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 90 SNPs on 19 different chromosomes that were jointly associated with AD and CV-associated outcomes. In meta-analyses across three independent cohorts, we found four novel loci within MBLAC1 (chromosome 7, meta-p = 1.44 × 10-9), MINK1 (chromosome 17, meta-p = 1.98 × 10-7) and two chromosome 11 SNPs within the MTCH2/SPI1 region (closest gene = DDB2, meta-p = 7.01 × 10-7 and closest gene = MYBPC3, meta-p = 5.62 × 10-8). In a large 'AD-by-proxy' cohort from the UK Biobank, we replicated three of the four novel AD/CV pleiotropic SNPs, namely variants within MINK1, MBLAC1, and DDB2. Expression of MBLAC1, SPI1, MINK1 and DDB2 was differentially altered within postmortem AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid-associated RFs. We pinpoint a subset of cardiovascular-associated genes that strongly increase the risk for AD. Our collective findings support a disease model in which cardiovascular biology is integral to the development of clinical AD in a subset of individuals.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“All of these loci are novel pleiotropic loci between AD and the respective cardiometabolic traits, but have previously been identified as genome-wide significant for AD in recent single-trait AD GWAS [4, 17, 31].”
From Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits (2021) · cites this paper as [4]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Due to the epidemiological correlation between AD and cardiometabolic traits, coupled with the fact that many cardiometabolic traits are genetically correlated with one another, additional broader-scale pleiotropic studies are warranted, and recently the field has begun to do so [4, 11].”
From Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits (2021) · cites this paper as [4]
The cited source says what the claim attributes to it.
In the citing paper
“Studies have consistently found a positive epidemiological correlation between Alzheimer’s disease (AD) and cardiometabolic traits, yet the biological mechanisms behind this correlation is not well understood [1–4].”
From Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits (2021) · cites this paper as [4]
The cited source says what the claim attributes to it.
In the citing paper
“Studies have consistently found a positive epidemiological correlation between Alzheimer’s disease (AD) and cardiometabolic traits, yet the biological mechanisms behind this correlation is not well understood [1–4].”
From Multi-trait association studies discover pleiotropic loci between Alzheimer’s disease and cardiometabolic traits (2021) · cites this paper as [4]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Dementia prevention, intervention, and care
Livingston, G., Sommerlad, A., Orgeta, V., Costafreda, S. G., Huntley, J., Ames, D., Ballard, C., Banerjee, S., Burns, A., Cohen-Mansfield, J., et al. (2017) · The Lancet · doi:10.1016/s0140-6736(17)31363-6 · Cited by 6,072
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Self-citationAn atlas of genetic correlations across human diseases and traits
ReproGen Consortium, Bulik-Sullivan, B., Psychiatric Genomics Consortium, Genetic Consortium for Anorexia Nervosa of the Wellcome Trust Case Control Consortium 3, Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P.-R., Duncan, L., et al. (2015) · Nature Genetics · doi:10.1038/ng.3406 · Cited by 4,255
Fagerberg, L., Hallström, B. M., Oksvold, P., Kampf, C., Djureinovic, D., Odeberg, J., Habuka, M., Tahmasebpoor, S., Danielsson, A., Edlund, K., et al. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.035600 · Cited by 3,665
Willer (2013) · doi:10.1038/ng.2797 · Cited by 2,983
The projected effect of risk factor reduction on Alzheimer's disease prevalence
Barnes, D. E., & Yaffe, K. S. (2011) · The Lancet Neurology · doi:10.1016/s1474-4422(11)70072-2 · Cited by 2,846
Self-citationPotential for primary prevention of Alzheimer's disease: an analysis of population-based data
Norton, S., Matthews, F. E., Barnes, D. E., Yaffe, K., & Brayne, C. (2014) · The Lancet Neurology · doi:10.1016/s1474-4422(14)70136-x · Cited by 2,466
Self-citationYengo, L., Sidorenko, J., Kemper, K. E., Zheng, Z., Wood, A. R., Weedon, M. N., Frayling, T. M., Hirschhorn, J. N., Yang, J., & Visscher, P. M. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy271 · Cited by 2,393
Jansen, I. E., Savage, J. E., Watanabe, K., Bryois, J., Williams, D. M., Steinberg, S., Sealock, J., Karlsson, I. K., Hägg, S., Athanasiu, L., et al. (2019) · Nature Genetics · doi:10.1038/s41588-018-0311-9 · Cited by 2,277
Self-citationSystematic identification of trans eQTLs as putative drivers of known disease associations
Westra, H.-J., Peters, M. J., Esko, T., Yaghootkar, H., Schurmann, C., Kettunen, J., Christiansen, M. W., Fairfax, B. P., Schramm, K., Powell, J. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2756 · Cited by 1,658
Research works printed but not linked: 1
- National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Sciences Policy, Committee on Preventing Dementia and Cognitive Impairment (2017) Preventing cognitive decline and dementia: a way forward. In: Downey A, Stroud C, Landis S, Leshner AI (eds) National Academies Press, Washington DC. http://www.ncbi.nlm.nih.gov/books/NBK436397/ . Accessed 17 Apr 2018
Cited by
Sorted by citations
Discovery of shared genomic loci using the conditional false discovery rate approach
Smeland, O. B., Frei, O., Shadrin, A. A., O’Connell, K. S., Fan, C. C., Bahrami, S., Holland, D., Djurovic, S., Thompson, W. K., Dale, A. M., et al. (2019) · Human Genetics · doi:10.1007/s00439-019-02060-2 · Cited by 261
Self-citationHeart-brain connections: Phenotypic and genetic insights from magnetic resonance images
Zhao, B., Li, T., Fan, Z., Yang, Y., Shu, J., Yang, X., Wang, X., Luo, T., Tang, J., Xiong, D., et al. (2023) · Science · doi:10.1126/science.abn6598 · Cited by 235
Combustion- and friction-derived magnetic air pollution nanoparticles in human hearts
Calderón‐Garcidueñas, L., González-Maciel, A., Mukherjee, P. S., Reynoso-Robles, R., Pérez-Guillé, B., Gayosso-Chávez, C., Torres‐Jardón, R., Cross, J. V., Ahmed, I. A. M., Karloukovski, V. V., et al. (2019) · Environmental Research · doi:10.1016/j.envres.2019.108567 · Cited by 204
Impact of High Altitude on Cardiovascular Health: Current Perspectives
Mallet, R. T., Burtscher, J., Richalet, J., Millet, G. P., & Burtscher, M. (2021) · Vascular Health and Risk Management · doi:10.2147/vhrm.s294121 · Cited by 207
Moreno–Grau, S., de Rojas, I., Hernández, I., Quintela, I., Montrreal, L., Alegret, M., Hernández‐Olasagarre, B., Madrid, L., González‐Pérez, A., Maroñas, O., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2019.06.4950 · Cited by 161
A genetic link between risk for Alzheimer's disease and severe COVID-19 outcomes via the OAS1 gene
Magusali, N., Graham, A. C., Piers, T. M., Panichnantakul, P., Yaman, U., Shoai, M., Reynolds, R. H., Botia, J. A., Brookes, K. J., Guetta-Baranes, T., et al. (2021) · Brain · doi:10.1093/brain/awab337 · Cited by 111
“Also in the same locus is OAS2, which was independently shown to be associated with Alzheimer’s disease.(95,96) Recent work has identified other SNPs close to this locus associated with severe”
BackgroundCerebrovascular disease promotes tau pathology in Alzheimer’s disease
Laing, K. K., Simoes, S., Baena-Caldas, G. P., Lao, P. J., Kothiya, M., Igwe, K. C., Chesebro, A. G., Houck, A. L., Pedraza, L., Hernandez, A. I., et al. (2020) · Brain Communications · doi:10.1093/braincomms/fcaa132 · Cited by 94
Polygenic hazard score, amyloid deposition and Alzheimer’s neurodegeneration
Tan, C. H., Bonham, L. W., Fan, C. C., Mormino, E. C., Sugrue, L. P., Broce, I., Hess, C. P., Yokoyama, J. S., Rabinovici, G. D., Miller, B. L., et al. (2018) · Brain · doi:10.1093/brain/awy327 · Cited by 88
Self-citationApolipoprotein E4 and meningeal lymphatics in Alzheimer disease: a conceptual framework
Mentis, A. A., Dardiotis, E., & Chrousos, G. P. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0731-7 · Cited by 83
Complement System in Alzheimer’s Disease
Shah, A., Kishore, U., & Shastri, A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222413647 · Cited by 76
Carmona‐Iragui, M., Videla, L., Lleó, A., & Fortea, J. (2019) · Developmental Neurobiology · doi:10.1002/dneu.22709 · Cited by 68
Gockley, J., Montgomery, K. S., Poehlman, W. L., Wiley, J. C., Liu, Y., Gerasimov, E. S., Greenwood, A. K., Sieberts, S. K., Wingo, A. P., Wingo, T. S., et al. (2021) · Genome Medicine · doi:10.1186/s13073-021-00890-2 · Cited by 60
Rivera‐Rivera, L. A., Cody, K. A., Eisenmenger, L. B., Cary, P., Rowley, H. A., Carlsson, C. M., Johnson, S. C., & Johnson, K. M. (2020) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x20910302 · Cited by 62
Progress in Polygenic Composite Scores in Alzheimer’s and Other Complex Diseases
Chasioti, D., Yan, J., Nho, K. T., & Saykin, A. J. (2019) · Trends in Genetics · doi:10.1016/j.tig.2019.02.005 · Cited by 61
Statins and cognition: Modifying factors and possible underlying mechanisms
Jamshidnejad-Tosaramandani, T., Kashanian, S., Al-Sabri, M. H., Kročianová, D., Clemensson, L. E., Gentreau, M., & Schiöth, H. B. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.968039 · Cited by 60
Li, J., Zhao, R., Jiang, Y., Xu, Y., Zhao, H., Lyu, X., & Wu, T. (2020) · Food & Function · doi:10.1039/c9fo02103e · Cited by 56
Polygenic risk and pleiotropy in neurodegenerative diseases
Bellou, E., Stevenson‐Hoare, J. O., & Escott‐Price, V. (2020) · Neurobiology of Disease · doi:10.1016/j.nbd.2020.104953 · Cited by 59
Lee, A., Raghavan, N. S., Bhattarai, P., Siddiqui, T., Sariya, S., Reyes‐Dumeyer, D., Flowers, X. E., Cardoso, S. A. L., Jager, P. L. D., Bennett, D. A., et al. (2022) · Acta Neuropathologica · doi:10.1007/s00401-022-02431-6 · Cited by 49
Self-citationPahlavian, S. H., Wang, X., Ma, S. J., Zheng, H., Casey, M., D’Orazio, L. M., Shao, X., Ringman, J. M., Chui, H. C., Wang, D. J. J., et al. (2020) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x20927101 · Cited by 44
LDL cholesterol is associated with higher AD neuropathology burden independent of APOE
Wingo, A. P., Vattathil, S., Liu, J., Fan, W., Cutler, D. J., Levey, A. I., Schneider, J. A., Bennett, D. A., & Wingo, T. S. (2022) · Journal of Neurology Neurosurgery & Psychiatry · doi:10.1136/jnnp-2021-328164 · Cited by 46
Self-citationKoskeridis, F., Fancy, N. N., Tan, P. F., Meena, D., Εvangelou, Ε., Elliott, P., Wang, D. Y. Q., Matthews, P. M., Dehghan, A., & Tzoulaki, I. (2024) · Nature Communications · doi:10.1038/s41467-024-53452-6 · Cited by 46
The vascular side of Alzheimer's disease
Liesz, A. (2019) · Science · doi:10.1126/science.aay2720 · Cited by 48
Program, T. V. M. V., Bone, W. P., Siewert, K. M., Jha, A., Klarin, D., Damrauer, S. M., Chang, K.-M., Tsao, P. S., Assimes, T. L., Ritchie, M. D., et al. (2021) · Alzheimer's Research & Therapy · doi:10.1186/s13195-021-00773-z · Cited by 41
Choriocapillaris reduction accurately discriminates against early‐onset Alzheimer's disease
Kwapong, W. R., Tang, F., Liu, P., Zhang, Z., Cao, L., Feng, Z., Yang, S., Shu, Y., Xu, H., Lu, Y., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.13871 · Cited by 39
Influence of genetic and cardiometabolic risk factors in Alzheimer’s disease
Pasqualetti, G., Thayanandan, T., & Edison, P. (2022) · Ageing Research Reviews · doi:10.1016/j.arr.2022.101723 · Cited by 39
Chen, H., Petty, L. E., Sha, J., Zhao, Y., Kuzma, A. B., Valladares, O., Bush, W. S., Naj, A. C., Gamazon, E. R., & Below, J. E. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01677-0 · Cited by 36
Cheng, Y., Yan, M., He, S., Xie, Y., Wei, L., Xuan, B., Shang, Z., Wu, M., Zheng, H., Chen, Y., et al. (2024) · Journal of Cellular and Molecular Medicine · doi:10.1111/jcmm.18321 · Cited by 35
Rizzo, S. J. S., Homanics, G. E., Schaeffer, D. J., Schaeffer, L. K. H., Park, J. E., Oluoch, J., Zhang, T., Haber, A., Seyfried, N. T., Paten, B., et al. (2023) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12417 · Cited by 40
Krahn, A. I., Wells, C. I., Drewry, D. H., Beitel, L. K., Durcan, T. M., & Axtman, A. D. (2020) · ACS Chemical Neuroscience · doi:10.1021/acschemneuro.0c00176 · Cited by 33
Genetic Variability in Molecular Pathways Implicated in Alzheimer's Disease: A Comprehensive Review
Vogrinc, D., Goričar, K., & Dolžan, V. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.646901 · Cited by 32
Unzeta, M., Hernández‐Guillamón, M., Sun, P., & Solé, M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22073365 · Cited by 34
Wang, Q., Zang, F., He, C., Zhang, Z., Xie, C., & Initiative, A. D. N. (2021) · Journal of Translational Medicine · doi:10.1186/s12967-022-03786-w · Cited by 32
Crouch, E. E., Joseph, T., Marsan, E., & Huang, E. J. (2023) · Trends in Neurosciences · doi:10.1016/j.tins.2023.04.007 · Cited by 34
Zhang, J., Lei, H., & Li, X. (2021) · Environmental Toxicology · doi:10.1002/tox.23361 · Cited by 31
Elahi, F. M., Ashimatey, B. S., Bennett, D. J., Walters, S. M., Joie, R. L., Jiang, X., Wolf, A. A., Cobigo, Y., Staffaroni, A. M., Rosen, H. J., et al. (2021) · Alzheimer s & Dementia Diagnosis Assessment & Disease Monitoring · doi:10.1002/dad2.12181 · Cited by 29
Self-citationFominykh, V., Shadrin, A. A., Jaholkowski, P. P., Bahrami, S., Athanasiu, L., Wightman, D. P., Uffelmann, E., Posthuma, D., Selbæk, G., Dale, A. M., et al. (2023) · Neurobiology of Disease · doi:10.1016/j.nbd.2023.106174 · Cited by 28
Self-citationLong runs of homozygosity are associated with Alzheimer’s disease
Moreno–Grau, S., Fernández, M. V., de Rojas, I., García‐González, P., Hernández, I., Farias, F. G., Budde, J., Quintela, I., Madrid, L., González‐Pérez, A., et al. (2021) · Translational Psychiatry · doi:10.1038/s41398-020-01145-1 · Cited by 27
Hou, J., Deng, Q., Guo, X., Deng, X., Zhong, W. H., & Zhong, Z. (2020) · Lipids in Health and Disease · doi:10.1186/s12944-020-01323-6 · Cited by 29
Multimodal hippocampal and amygdala subfield volumetry in polygenic risk for Alzheimer's disease
Murray, A. N., Chandler, H. L., & Lancaster, T. M. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.08.022 · Cited by 25
Huang, L., Ou, Y., Yang, Y., Wang, Z.-T., Tan, L., & Yu, J. (2023) · Translational Psychiatry · doi:10.1038/s41398-023-02553-9 · Cited by 28
Zhao, L., Liu, J., Zhao, W., Chen, J., Fan, J., Ge, T., & Tu, Y. (2024) · Nature Mental Health · doi:10.1038/s44220-024-00223-3 · Cited by 26
The Significance of Vascular Pathogenesis in the Examination of Corticobasal Syndrome
Dunalska, A., Pikul, J., Schok, K., Wiejak, K., & Alster, P. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.668614 · Cited by 23
Ban, Y., Yu, T., Feng, B., Lorenz, C., Wang, X., Baker, C., & Zou, Y. (2021) · Science Advances · doi:10.1126/sciadv.abh2974 · Cited by 23
Grossmann, K. (2022) · Biomedicines · doi:10.3390/biomedicines10081890 · Cited by 24
Zheng, C., Liu, S., Zhang, X., Hu, Y., Shang, X., Zhu, Z., Huang, Y., Wu, G., Xiao, Y., Du, Z., et al. (2022) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2022.880576 · Cited by 24
Lipids and lipoproteins may play a role in the neuropathology of Alzheimer’s disease
Akyol, Ö., Akyol, S., Chou, M., Chen, S., Liu, C., Selek, S., Soares, J. C., & Chen, C. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1275932 · Cited by 27
Li, B., Qu, Y., Fan, Z., Gong, X., Xu, H., Wu, L., & Yan, C. (2023) · BMC Medical Genomics · doi:10.1186/s12920-023-01692-8 · Cited by 22
Peng, X., Yang, Y., Hou, R., Zhang, L., Shen, C., Yang, X., Luo, Z., Yin, Z., & Cao, Y. (2024) · Drug Design Development and Therapy · doi:10.2147/dddt.s460448 · Cited by 23
Liu, Y., Chan, D. K. Y., Crawford, J. D., Sachdev, P. S., & Braidy, N. (2021) · Current Alzheimer Research · doi:10.2174/1567205018666210212160902 · Cited by 23
Adipose tissue as a therapeutic target for vascular damage in Alzheimer's disease
Bettinetti‐Luque, M., Trujillo‐Estrada, L., García‐Fuentes, E., Andreo‐Lopez, J., Sanchez-Varo, R. M., Garrido‐Sánchez, L., Mediavilla, A. G., López, M. G., García‐Caballero, M., Gutiérrez, A., et al. (2023) · British Journal of Pharmacology · doi:10.1111/bph.16243 · Cited by 21
Li, C., Ou, R., Gu, X., Wei, Q., & Shang, H. (2021) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2021.01.023 · Cited by 20
Alzheimer’s Disease—Rationales for Potential Treatment with the Thrombin Inhibitor Dabigatran
Grossmann, K. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094805 · Cited by 20
Cardiovascular diseases and risk of dementia in the general population
Luo, J. M., Rasmussen, I. J., Nordestgaard, B. G., Tybjærg‐Hansen, A., Thomassen, J. Q., & Frikke‐Schmidt, R. (2025) · European Journal of Preventive Cardiology · doi:10.1093/eurjpc/zwaf129 · Cited by 20
Elevated parathyroid hormone levels and cognitive function: A systematic review
Jiang, W., Hu, C., Li, F., Hua, X., Huang, K., & Zhang, X.-J. (2019) · Archives of Gerontology and Geriatrics · doi:10.1016/j.archger.2019.103985 · Cited by 18
Hariharan, P., & Dupuis, J. (2021) · Scientific Reports · doi:10.1038/s41598-021-95637-9 · Cited by 17
Amyloid-beta metabolism in age-related neurocardiovascular diseases
Aivalioti, E., Georgiopoulos, G. A., Tual‐Chalot, S., Bampatsias, D., Delialis, D., Sopova, K., Drakos, S. G., Stellos, K., & Stamatelopoulos, K. S. (2024) · European Heart Journal · doi:10.1093/eurheartj/ehae655 · Cited by 20
Chen, F., Dong, X., Yu, Z., Zhang, Y., & Shi, Y. (2024) · Journal of Affective Disorders · doi:10.1016/j.jad.2024.03.098 · Cited by 16
Rodriguez, P., Kalia, V., Fenollar‐Ferrer, C., Gibson, C. L., Gichi, Z., Rajoo, A., Matier, C. D., Pezacki, A. T., Xiao, T., Carvelli, L., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2320611121 · Cited by 16
Lawingco, T., Chaudhury, S. R., Brookes, K. J., Guetta‐Baranes, T., Guerreiro, R. J., Brás, J., Hardy, J., Francis, P. T., Thomas, A. J., Belbin, O., et al. (2020) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2020.11.009 · Cited by 19
DeepRisk: a deep learning approach for genome-wide assessment of common disease risk
Peng, J., Bao, Z., Li, J., Han, R., Wang, Y., Han, L., Peng, J., Wang, T., Hao, J., Wei, Z., et al. (2024) · Fundamental Research · doi:10.1016/j.fmre.2024.02.015 · Cited by 15
Eisfeldt, J., Schuy, J., Stattin, E., Kvarnung, M., Falk, A., Feuk, L., & Lindstrand, A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23169392 · Cited by 15
Admixture mapping identifies novel Alzheimer's disease risk regions in African Americans
Rajabli, F., Tosto, G., Hamilton‐Nelson, K. L., Kunkle, B. W., Vardarajan, B. N., Naj, A. C., Whitehead, P. G., Gardner, O. K., Bush, W. S., Sariya, S., et al. (2022) · Alzheimer s & Dementia · doi:10.1002/alz.12865 · Cited by 15
Self-citationAssociations of ARHGAP26 Polymorphisms with Alzheimer’s Disease and Cardiovascular Disease
Wang, K., Lu, Y., Morrow, D. F., Xiao, D., Xu, C. D., & Initiative, T. A. D. N. (2022) · Journal of Molecular Neuroscience · doi:10.1007/s12031-022-01972-5 · Cited by 14
Gallego, I., Villate-Beitia, I., Soto‐Sánchez, C., Menéndez, M., Grijalvo, S., Eritja, R., Martı́nez, G., Humphreys, L., López-Méndez, T. B., Puras, G., et al. (2020) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.9b01213 · Cited by 15
Suryadevara, V., Klüppel, M., del Monte, F., & Willis, M. S. (2020) · American Journal Of Pathology · doi:10.1016/j.ajpath.2020.04.013 · Cited by 13
Broce, I., Castruita, P. A., & Yokoyama, J. S. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.639078 · Cited by 14
Self-citationExploring potential shared genetic influences between rheumatoid arthritis and blood lipid levels
Kasher, M., Cherny, S. S., & Livshits, G. (2022) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2022.11.006 · Cited by 15
White Matter Hyperintensity as a Vascular Contribution to the AT(N) Framework
Ng, K. P., shen, J., Chiew, H. J., Ng, A., Kandiah, N., Rosa‐Neto, P., & Gauthier, S. G. (2023) · The Journal of Prevention of Alzheimer s Disease · doi:10.14283/jpad.2023.53 · Cited by 12
Genetic Variants behind Cardiovascular Diseases and Dementia
Ho, W.-M., Wu, Y.-Y., & Chen, Y. (2020) · Genes · doi:10.3390/genes11121514 · Cited by 13
Jaholkowski, P. P., Hindley, G., Shadrin, A. A., Tesfaye, M., Bahrami, S., Nerhus, M., Rahman, Z., O’Connell, K. S., Holen, B., Parker, N., et al. (2023) · Schizophrenia Bulletin · doi:10.1093/schbul/sbad063 · Cited by 11
Self-citationİş, Ö., Min, Y., Wang, X., Oatman, S. R., Daniel, A. A., & Ertekin‐Taner, N. (2024) · Glia · doi:10.1002/glia.24652 · Cited by 13
MAP4K signaling pathways in cancer: roles, mechanisms and therapeutic opportunities
Bunardi, C. S., Yeom, M., Kosasih, P., Han, H., Wang, W., & Seo, G. (2025) · Experimental & Molecular Medicine · doi:10.1038/s12276-025-01544-8 · Cited by 16
Endothelial ether lipids link the vasculature to blood pressure, behavior, and neurodegeneration
Spears, L. D., Adak, S., Dong, G., Wei, X., Spyropoulos, G., Zhang, Q., Li, Y., Chu, F., Hu, D., Lodhi, I. J., et al. (2021) · Journal of Lipid Research · doi:10.1016/j.jlr.2021.100079 · Cited by 14
Chandler, H. L., Wise, R. G., Linden, D. E. J., Williams, J. H., Murphy, K., & Lancaster, T. M. (2022) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2022.08.001 · Cited by 11
Polygenic risk for Alzheimer's disease shapes hippocampal scene-selectivity
Chandler, H. L., Hodgetts, C. J., Caseras, X., Murphy, K., & Lancaster, T. M. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-019-0595-1 · Cited by 12
Jansson, D., Wang, M., Thomas, R. G., Erickson, M. A., Peskind, E. R., Li, G., & Iliff, J. (2022) · Journal of Alzheimer s Disease · doi:10.3233/jad-215400 · Cited by 11
Optical Imaging Reveals Liver Metabolic Perturbations in Mblac1 Knockout Mice
Ceyhan, B., LaMar, J., Nategh, P., Neghabi, M., Konjalwar, S., Rodriguez, P., Hahn, M. K., Blakely, R., & Ranji, M. (2023) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc40787.2023.10341032 · Cited by 10
Plasma Proteomic Biomarkers in Alzheimer’s Disease and Cardiovascular Disease: A Longitudinal Study
Theeke, L. A., Liu, Y., Wang, S., Luο, X., Navia, R. O., Xiao, D., Xu, C. D., Wang, K., & Initiative, T. A. A. D. N. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms251910751 · Cited by 10
Guardiola, M., Muntané, G., Martínez, I., Martorell, L., Girona, J., Ibarretxe, D., Plana, N., Bullido, M. J., Vilella, E., & Ribalta, J. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24087415 · Cited by 11
Optical Imaging Demonstrates Tissue-Specific Metabolic Perturbations in Mblac1 Knockout Mice
Ceyhan, B., Nategh, P., Neghabi, M., LaMar, J., Konjalwar, S., Rodriguez, P., Hahn, M. K., Gross, M., Grumbar, G. J., Salleng, K. J., et al. (2024) · IEEE Journal of Translational Engineering in Health and Medicine · doi:10.1109/jtehm.2024.3355962 · Cited by 8
Kot, A., Koszewska, D., Ochman, B., & Świętochowska, E. (2024) · Current Issues in Molecular Biology · doi:10.3390/cimb46120826 · Cited by 9
Dissecting pleiotropy to gain mechanistic insights into human disease
Jee, Y. H., He, Y., Lu, W., Shi, Y., Lazarev, D., Daly, M. J., Reeve, M. P., & Martin, A. R. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00908-0 · Cited by 12
Influence of cardiovascular risk factors on pre-mild cognitive decline at middle and old age
Koberskaya, N. N., Yakhno, N. N., Гридин, В. Н., & Smirnov, D. S. (2021) · Neurology neuropsychiatry Psychosomatics · doi:10.14412/2074-2711-2021-1-13-17 · Cited by 8
Sink or swim: Does a worm paralysis phenotype hold clues to neurodegenerative disease?
Rodriguez, P., & Blakely, R. (2023) · Journal of Cellular Physiology · doi:10.1002/jcp.31125 · Cited by 7
Gan, C., Zhang, Y., Zhang, X., Huang, Q., & Guo, X. (2023) · International Journal of General Medicine · doi:10.2147/ijgm.s440103 · Cited by 8
Prevalence of cardiovascular drug use before and after diagnosis of Alzheimer's disease
Vu, M., Koponen, M., Taipale, H. T., Tanskanen, A. J., Tiihonen, J., Kettunen, R., Hartikainen, S. A., & Tolppanen, A. (2019) · International Journal of Cardiology · doi:10.1016/j.ijcard.2019.09.036 · Cited by 8
Loika, Y., Loiko, E., Culminskaya, I. V., & Kulminski, A. M. (2023) · Genes · doi:10.3390/genes14101834 · Cited by 6
Parental History of Dementia Is Associated with Increased Small Vessel Cerebrovascular Disease
Stamm, B. C., Lao, P. J., Rizvi, B. M., Colón, J. M., Igwe, K. C., Chesebro, A. G., Maas, B., Schupf, N., Mayeux, R. P., Manly, J. J., et al. (2019) · The Journals of Gerontology Series A · doi:10.1093/gerona/glz291 · Cited by 6
Self-citationTranscriptomic Heterogeneity of Alzheimer’s Disease Associated with Lipid Genetic Risk
Miao, X., Liu, W., Fan, B., & Lin, H. (2020) · NeuroMolecular Medicine · doi:10.1007/s12017-020-08610-6 · Cited by 6
Bridging heterogeneous mutation data to enhance disease gene discovery
Zhou, K., Wang, Y., Cohen, K. B., Kim, J.-D., Ma, X., Shen, Z., Meng, X., & Xia, J. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab079 · Cited by 6
Identification of genetic loci shared between Alzheimer’s disease and hypertension
Sullivan, M., Deng, H., & Greenbaum, J. (2022) · Molecular Genetics and Genomics · doi:10.1007/s00438-022-01949-4 · Cited by 6
Life course plasma metabolomic signatures of genetic liability to Alzheimer’s disease
Compton, H., Smith, M. L., Bull, C. J., Korologou‐Linden, R., Ben‐Shlomo, Y., Bell, J. A., Williams, D. M., & Anderson, E. L. (2024) · Scientific Reports · doi:10.1038/s41598-024-54569-w · Cited by 7
Zhan, K., Zhu, K., Gu, B., Yao, S., Fu, F., Zeng, H., Tian, K., Ji, W., Jin, H., Tong, P., et al. (2024) · International Immunopharmacology · doi:10.1016/j.intimp.2024.112202 · Cited by 5
The biology of mitochondrial carrier homolog 2
Zheng, X., & Chu, B. (2023) · Mitochondrion · doi:10.1016/j.mito.2023.101837 · Cited by 6
Precision health in Alzheimer disease: Risk assessment‐based strategies
Azar, J., Salama, M., Chidambaram, S. B., Al‐Balushi, B., Essa, M. M., & Qoronfleh, M. W. (2021) · Precision Medical Sciences · doi:10.1002/prm2.12036 · Cited by 7
Magusali, N., Graham, A. C., Piers, T. M., Panichnantakul, P., Yaman, Ü., Shoai, M., Reynolds, R. H., Botía, J. A., Brookes, K. J., Guetta‐Baranes, T., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.16.435702 · Cited by 5
Epigenetic Insights into Vascular Cognitive Impairment: DNA Methylation in the Human Brain Tissue
Vishweswaraiah, S., Saiyed, N., Khalid, A., Milčiūtė, M., Gabrielaitė, M., Buyuker, C., Aksakal, B., Gomes, L., Gordevičius, J., Yılmaz, A., et al. (2025) · Molecular Neurobiology · doi:10.1007/s12035-025-05119-6 · Cited by 4
Is the Relationship Between Cardiovascular Disease and Alzheimer’s Disease Genetic? A Scoping Review
Moore, A. K., & Ritchie, M. D. (2024) · Genes · doi:10.3390/genes15121509 · Cited by 5
Exploratory Data Analysis in a Six-Year Longitudinal Study in Healthy Brain AgingPreprint
Gómez-Ramírez, J., Ávila‐Villanueva, M., Payo, B. F., Quijano, T. D. S., Soler, M. V., Sevilla, M. A. Z., & Fernández‐Blázquez, M. A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/674853 · Cited by 4
Genetic influences on the shape of brain ventricular and subcortical structuresPreprint
Zhao, B., Li, T., Yang, X., Shu, J., Wang, X., Luo, T., Yang, Y., Wu, Z., Fan, Z., Jiang, Z., et al. (2022) · medRxiv · doi:10.1101/2022.09.26.22279691 · Cited by 4
Metadata
- Authors
- Broce, I. J., Tan, C. H., Fan, C. C., Jansen, I., Savage, J. E., Witoelar, A., Wen, N., Hess, C. P., Dillon, W. P., Glastonbury, C. M., Glymour, M., Yokoyama, J. S., Elahi, F. M., Rabinovici, G. D., Miller, B. L., Mormino, E. C., Sperling, R. A., Bennett, D. A., McEvoy, L. K., Brewer, J. B., Feldman, H. H., Hyman, B. T., Pericak-Vance, M., Haines, J. L., Farrer, L. A., Mayeux, R., Schellenberg, G. D., Yaffe, K., Sugrue, L. P., Dale, A. M., Posthuma, D., Andreassen, O. A., Karch, C. M., & Desikan, R. S.
- Affiliations
- University of California, San Francisco (US)
- Nanyang Technological University (SG)
- University of California San Diego (US)
- Amsterdam UMC Location Vrije Universiteit Amsterdam (NL)
- University of Oslo (NO)
- Washington University in St. Louis (US)
- Stanford Medicine (US)
- Brigham and Women's Hospital (US)
- Rush University Medical Center (US)
- Harvard University (US)
- Case Western Reserve University (US)
- Boston University (US)
- Columbia University (US)
- University of Pennsylvania (US)
- Corresponding author
- Broce, Iris J.
- Karch, Celeste M.
- Desikan, Rahul S.
- ORCID
- Broce, Iris J.
- Tan, Chin Hong
- Fan, Chun Chieh
- Jansen, Iris
- Savage, Jeanne E.
- Witoelar, Aree
- Wen, Natalie
- Hess, Christopher P.
- Dillon, William P.
- Glastonbury, Christine M.
- Glymour, Maria
- Yokoyama, Jennifer S.
- Elahi, Fanny M.
- Rabinovici, Gil D.
- Miller, Bruce L.
- Mormino, Elizabeth C.
- Sperling, Reisa A.
- Bennett, David A.
- McEvoy, Linda K.
- Feldman, Howard H.
- Hyman, Bradley T.
- Haines, Jonathan L.
- Farrer, Lindsay A.
- Mayeux, Richard
- Schellenberg, Gerard D.
- Yaffe, Kristine
- Sugrue, Leo P.
- Dale, Anders M.
- Andreassen, Ole A.
- Karch, Celeste M.
- Desikan, Rahul S.
- Venue
- Acta Neuropathologica
- Published
- 2018-11-09
- Volume
- 137
- Issue
- 2
- Pages
- 209-226
- ISSN
- 0001-6322 (ISSN-L)
- 1432-0533
- PMC
- PMC6358498
- OpenAlex
- W2899829198
- Cited by
- 140
- References
- 60
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 20 · 2023: 23 · 2022: 20 · 2021: 28 · 2020: 20 · 2019: 10 · 2018: 1
- FWCI
- 10.31
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Acta Neuropathologica (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, other-oa)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- DR-NTU (Nanyang Technological University) (submittedVersion)
- VU Research Portal (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- National Institutes of Health (AG046374, K01AG049152)
- National Alzheimer's Coordinating Center
- Radiological Society of North America
- Foundation of the American Society of Neuroradiology
- Norges Forskningsråd (213837, 225989, 223273, 237250/EU JPND)
- South East Norway Health Authority
- Norwegian Health Association
- KG Jebsen Foundation
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- Alzheimer's disease, cardiovascular risk factors, genetic overlap, pleiotropy, plasma lipids, type 2 diabetes, coronary artery disease, body mass index, waist-to-hip ratio, apolipoprotein E, DDB2, novel genetic loci, postmortem gene expression, polygenic risk
- MeSH terms
- Aged, Aged, 80 and over, Alleles, Alzheimer Disease, Apolipoproteins E, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Female, Humans, Male, Middle Aged, Risk Factors, Cohort Studies, Genetic Predisposition to Disease, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review