Harnessing peripheral DNA methylation differences in the Alzheimer’s Disease Neuroimaging Initiative (ADNI) to reveal novel biomarkers of disease
Open accessAbstract
Background: Alzheimer’s disease (AD) is a chronic progressive neurodegenerative disease impacting an estimated 44 million adults worldwide. The causal pathology of AD (accumulation of amyloid-beta and tau), precedes hallmark symptoms of dementia by more than a decade, necessitating development of early diagnostic markers of disease onset, particularly for new drugs that aim to modify disease processes. To evaluate differentially methylated positions (DMPs) as novel blood-based biomarkers of AD, we used a subset of 653 individuals with peripheral blood (PB) samples in the Alzheimer’s disease Neuroimaging Initiative (ADNI) consortium. The selected cohort of AD, mild cognitive impairment (MCI), and age-matched healthy controls (CN) all had imaging, genetics, transcriptomics, cerebrospinal protein markers, and comprehensive clinical records, providing a rich resource of concurrent multi-omics and phenotypic information on a well-phenotyped subset of ADNI participants. Results: In this manuscript, we report cross-diagnosis differential peripheral DNA methylation in a cohort of AD, MCI, and age-matched CN individuals with longitudinal DNA methylation measurements. Epigenome-wide association studies (EWAS) were performed using a mixed model with repeated measures over time with a P value cutoff of 1 × 10 −5 to test contrasts of pairwise differential peripheral methylation in AD vs CN, AD vs MCI, and MCI vs CN. The most highly significant differentially methylated loci also tracked with Mini Mental State Examination (MMSE) scores. Differentially methylated loci were enriched near brain and neurodegeneration-related genes (e.g., BDNF, BIN1, APOC1 ) validated using the genotype tissue expression project portal (GTex). Conclusions: Our work shows that peripheral differential methylation between age-matched subjects with AD relative to healthy controls will provide opportunities to further investigate and validate differential methylation as a surrogate of disease. Given the inaccessibility of brain tissue, the PB-associated methylation marks may help identify the stage of disease and progression phenotype, information that would be central to bringing forward successful drugs for AD.
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
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 sex-specific meta-analysis included 1284 whole blood samples (632 females and 652 males) from ADNI and AIBL.
“included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males).”
From Distinct sex-specific DNA methylation differences in Alzheimer’s disease (2022) · cites this paper as [38]
Methods > Subjects reports samples from 653 ADNI participants, and Methods > Sample identity checks says 1,707 samples were analyzed after quality control—not 1,284. Methods > Statistical analysis also distinguishes whole blood from buffy coat. The cited paper does not describe the claimed sex-specific ADNI–AIBL meta-analysis or its female–male counts. Page numbers are unavailable in our copy. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe meta-analysis was expected to be underpowered given modest sex-specific sample sizes, so CpGs at P < 1×10−5 were also prioritized.
“Based on our experiences and previous studies in the analysis of EWAS measured in blood [22, 38, 47], we expected our meta-analysis to be underpowered, given the modest sample sizes of the sex-specific analyses. Therefore, we also prioritized CpGs with suggestive significance at the pre-specified significance threshold of P-value < 1×10−5.”
From Distinct sex-specific DNA methylation differences in Alzheimer’s disease (2022) · cites this paper as [38]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
limma powers differential expression analyses for RNA-sequencing and microarray studies
Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458 · see citing works
Molecular signatures database (MSigDB) 3.0
Liberzon, A., Subramanian, A., Pinchback, R., Thorvaldsdóttir, H., Tamayo, P., & Mesirov, J. P. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr260 · Cited by 7,111 · see citing works
Rett syndrome is caused by mutations in X-linked MECP2, encoding methyl-CpG-binding protein 2
Amir, R. E., Van den Veyver, I. B., Wan, M., Tran, C. Q., Francke, U., & Zoghbi, H. Y. (1999) · Nature Genetics · doi:10.1038/13810 · Cited by 4,990 · see citing works
The molecular hallmarks of epigenetic control
Allis, C. D., & Jenuwein, T. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.59 · Cited by 2,809 · see citing works
Alzheimer's Disease Neuroimaging Initiative (ADNI)
Petersen, R. C., Aisen, P. S., Beckett, L. A., Donohue, M. C., Gamst, A. C., Harvey, D. J., Jack, C. R., Jagust, W. J., Shaw, L. M., Toga, A. W., et al. (2010) · Neurology · doi:10.1212/wnl.0b013e3181cb3e25 · Cited by 2,572 · cited 1× · see citing works
“Clinical descriptions of the ADNI cohort have been published [40].”
BackgroundDNA Methylation and Gene Function
Razin, A., & Riggs, A. D. (1980) · Science · doi:10.1126/science.6254144 · Cited by 2,076 · see citing works
Use of within-array replicate spots for assessing differential expression in microarray experiments
Smyth, G. K., Michaud, J., & Scott, H. S. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti270 · Cited by 1,406 · see citing works
A data-driven approach to preprocessing Illumina 450K methylation array data
Pidsley, R., Y Wong, C. C., Volta, M., Lunnon, K., Mill, J., & Schalkwyk, L. C. (2013) · BMC Genomics · doi:10.1186/1471-2164-14-293 · Cited by 1,143 · see citing works
ChAMP: updated methylation analysis pipeline for Illumina BeadChips
Tian, Y., Morris, T. J., Webster, A. P., Yang, Z., Beck, S., Feber, A., & Teschendorff, A. E. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx513 · Cited by 1,091 · see citing works
Phipson, B., Lee, S., Majewski, I. J., Alexander, W. S., & Smyth, G. K. (2016) · The Annals of Applied Statistics · doi:10.1214/16-aoas920 · Cited by 966 · see citing works
Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci
De Jager, P. L., Srivastava, G., Lunnon, K., Burgess, J., Schalkwyk, L. C., Yu, L., Eaton, M. L., Keenan, B. T., Ernst, J., McCabe, C., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3786 · Cited by 956 · see citing works
Self-citationPreprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi
Fortin, J.-P., Triche, T. J., & Hansen, K. D. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw691 · Cited by 867 · see citing works
Aging effects on DNA methylation modules in human brain and blood tissue
Horvath, S., Zhang, Y., Langfelder, P., Kahn, R. S., Boks, M. P., van Eijk, K. R., van den Berg, L. H., & Ophoff, R. A. (2012) · Genome biology · doi:10.1186/gb-2012-13-10-r97 · Cited by 638 · see citing works
Davies, M. N., Volta, M., Pidsley, R., Lunnon, K., Dixit, A., Lovestone, S., Coarfa, C., Harris, R. A., Milosavljevic, A., Troakes, C., et al. (2012) · Genome Biology · doi:10.1186/gb-2012-13-6-r43 · Cited by 630 · see citing works
Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease
Lunnon, K., Smith, R., Hannon, E., De Jager, P. L., Srivastava, G., Volta, M., Troakes, C., Al-Sarraj, S., Burrage, J., Macdonald, R., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3782 · Cited by 574 · see citing works
Self-citationWhy weight? Modelling sample and observational level variability improves power in RNA-seq analyses
Liu, R., Holik, A. Z., Su, S., Jansz, N., Chen, K., Leong, H. S., Blewitt, M. E., Asselin-Labat, M.-L., Smyth, G. K., & Ritchie, M. E. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv412 · Cited by 562 · see citing works
Braun, P. R., Han, S., Hing, B., Nagahama, Y., Gaul, L. N., Heinzman, J. T., Grossbach, A. J., Close, L., Dlouhy, B. J., Howard, M. A., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0376-y · Cited by 467 · see citing works
Hannon, E., Lunnon, K., Schalkwyk, L., & Mill, J. (2015) · Epigenetics · doi:10.1080/15592294.2015.1100786 · Cited by 455 · see citing works
Therapeutic strategies for Alzheimer's disease in clinical trials
Godyń, J., Jończyk, J., Panek, D., & Malawska, B. (2015) · Pharmacological Reports · doi:10.1016/j.pharep.2015.07.006 · Cited by 454 · see citing works
Saykin, A. J., Shen, L., Foroud, T. M., Potkin, S. G., Swaminathan, S., Kim, S., Risacher, S. L., Nho, K., Huentelman, M. J., Craig, D. W., et al. (2010) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2010.03.013 · Cited by 442 · see citing works
Self-citationA DNA methylation fingerprint of 1628 human samplesPreprint
Fernández, A. F., Assenov, Y., Martín-Subero, J. I., Bálint, B., Siebert, R., Taniguchi, H., Yamamoto, H., Hidalgo, M. M., Tan, A. C., Galm, O., et al. (2011) · Genome Research · doi:10.1101/gr.119867.110 · Cited by 415 · see citing works
Mutations in DNMT1 cause hereditary sensory neuropathy with dementia and hearing loss
Klein, C. J., Botuyan, M. V., Wu, Y., Ward, C. J., Nicholson, G. A., Hammans, S. R., Hojo, K., Yamanishi, H., Karpf, A. R., Wallace, D. C., et al. (2011) · Nature Genetics · doi:10.1038/ng.830 · Cited by 407 · see citing works
DNA methylation profiles in cancer diagnosis and therapeutics
Pan, Y., Liu, G., Zhou, F., Su, B., & Li, Y. (2017) · Clinical and Experimental Medicine · doi:10.1007/s10238-017-0467-0 · Cited by 374 · see citing works
Dougherty, J. D., Schmidt, E. F., Nakajima, M., & Heintz, N. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq130 · Cited by 344 · see citing works
Weiner, M. W., Veitch, D. P., Aisen, P. S. S., Beckett, L. A., Cairns, N. J., Green, R. C., Harvey, D. J., Jack, C. R., Jagust, W. J., Morris, J. C., et al. (2017) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2016.11.007 · Cited by 314 · see citing works
Self-citationGenetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans
Saykin, A. J., Shen, L., Yao, X., Kim, S., Nho, K. T., Risacher, S. L., Ramanan, V. K., Foroud, T., Faber, K. M., Sarwar, N., et al. (2015) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2015.05.009 · Cited by 301 · see citing works
Self-citationAryee, M. J., Liu, W., Engelmann, J. C., Nuhn, P., Gurel, M., Haffner, M. C., Esopi, D., Irizarry, R. A., Getzenberg, R. H., Nelson, W. G., et al. (2013) · Science Translational Medicine · doi:10.1126/scitranslmed.3005211 · Cited by 277 · see citing works
Xu, X., Wells, A., O’Brien, D. R., Nehorai, A., & Dougherty, J. D. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.4488-13.2014 · Cited by 271 · see citing works
BECon: a tool for interpreting DNA methylation findings from blood in the context of brain
Edgar, R. D., Jones, M. J., Meaney, M. J., Turecki, G., & Kobor, M. S. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.171 · Cited by 261 · see citing works
Arand, J., Wossidlo, M., Lepikhov, K., Peat, J. R., Reik, W., & Walter, J. (2015) · Epigenetics & Chromatin · doi:10.1186/1756-8935-8-1 · Cited by 213 · see citing works
Epigenetics as a mechanism linking developmental exposures to long-term toxicity
Barouki, R., Melén, E., Herceg, Z., Beckers, J., Chen, J., Karagas, M. R., Puga, A., Xia, Y., Chadwick, L. H., Yan, W., et al. (2018) · Environment International · doi:10.1016/j.envint.2018.02.014 · Cited by 208 · see citing works
Meder, B., Haas, J., Sedaghat‐Hamedani, F., Kayvanpour, E., Frese, K., Lai, A., Nietsch, R., Scheiner, C., Mester, S., Bordalo, D. M., et al. (2017) · Circulation · doi:10.1161/circulationaha.117.027355 · Cited by 192 · see citing works
Longitudinal Change of Biomarkers in Cognitive Decline
Lo, R. Y. (2011) · Archives of Neurology · doi:10.1001/archneurol.2011.123 · Cited by 190 · see citing works
Epigenetics in Alzheimer’s Disease: Perspective of DNA Methylation
Qazi, T. J., Quan, Z., Mir, A., & Qing, H. (2018) · Molecular Neurobiology · doi:10.1007/s12035-016-0357-6 · Cited by 153 · see citing works
Concordant and discordant DNA methylation signatures of aging in human blood and brain
Farré, P., Jones, M. J., Meaney, M. J., Emberly, E. G., Turecki, G., & Kobor, M. S. (2015) · Epigenetics & Chromatin · doi:10.1186/s13072-015-0011-y · Cited by 145 · see citing works
Blood-Derived DNA Methylation Signatures of Crohn's Disease and Severity of Intestinal Inflammation
Somineni, R. P., Venkateswaran, S., Kilaru, V., Marigorta, U. M., Mo, A., Okou, D. T., Kellermayer, R., Mondal, K., Cobb, D. O., Walters, T. D., et al. (2019) · Gastroenterology · doi:10.1053/j.gastro.2019.01.270 · Cited by 134 · see citing works
Maculewicz, J., Kofoed, L. B., & Serafin, S. (2016) · Frontiers in Neurology · doi:10.3389/fneur.2016.00001 · Cited by 123 · see citing works
Associations of the Top 20 Alzheimer Disease Risk Variants With Brain Amyloidosis
Apostolova, L. G., Risacher, S. L., Duran, T., Stage, E., Goukasian, N., West, J. D., Do, T. M., Grotts, J. F., Wilhalme, H. M., Nho, K. T., et al. (2018) · JAMA Neurology · doi:10.1001/jamaneurol.2017.4198 · Cited by 122 · see citing works
Self-citationBlood DNA methylation as a potential biomarker of dementia: A systematic review
Fransquet, P. D., Lacaze, P., Saffery, R., McNeil, J., Woods, R., & Ryan, J. (2018) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2017.10.002 · Cited by 96 · see citing works
Alzheimer’s Disease Biomarkers and Future Decline in Cognitive Normal Older Adults
Dumurgier, J., Hanseeuw, B. J., Hatling, F. B., Judge, K. A., Schultz, A. P., Chhatwal, J. P., Blacker, D., Sperling, R. A., Johnson, K. A., Hyman, B. T., et al. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170511 · Cited by 86 · see citing works
Epigenetics and DNA methylomic profiling in Alzheimer's disease and other neurodegenerative diseases
Roubroeks, J. A. Y., Smith, R. G., van den Hove, D., & Lunnon, K. (2017) · Journal of Neurochemistry · doi:10.1111/jnc.14148 · Cited by 81 · see citing works
Horgusluoglu, E., Nho, K. T., Risacher, S. L., Kim, S., Foroud, T., Shaw, L. M. J., Trojanowski, J. Q., Aisen, P. S. S., Petersen, R. C., Jack, C. R., et al. (2017) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2017.08.010 · Cited by 78 · see citing works
Self-citationDNA methylation as a genomic marker of exposure to chemical and environmental agents
Meehan, R. R., Thomson, J. P., Lentini, A., Nestor, C. E., & Pennings, S. (2018) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2018.02.006 · Cited by 78 · see citing works
Opening up the DNA methylome of dementia
Delgado‐Morales, R., & Esteller, M. (2017) · Molecular Psychiatry · doi:10.1038/mp.2016.242 · Cited by 74 · see citing works
Chouliaras, L., Pishva, E., Haapakoski, R., Zsoldos, E., Mahmood, A., Filippini, N., Burrage, J., Mill, J. S., Mika Kivimaki, B., Lunnon, K., et al. (2018) · Epigenomics · doi:10.2217/epi-2017-0132 · Cited by 70 · see citing works
Jia, T., Chu, C., Liu, Y., van Dongen, J., Papastergios, E., Armstrong, N. J., Bastin, M. E., Carrillo‐Roa, T., den Braber, A., Harris, M. A., et al. (2019) · Molecular Psychiatry · doi:10.1038/s41380-019-0605-z · Cited by 58 · see citing works
Self-citationCiuculete, D. M., Boström, A. E., Voisin, S., Philipps, H., Titova, O. E., Bandstein, M., Nikontovic, L., Williams, M. J., Mwinyi, J., & Schiöth, H. B. (2017) · Translational Psychiatry · doi:10.1038/tp.2016.275 · Cited by 40 · see citing works
Braun, P., Han, S., Nagahama, Y., Gaul, L. N., Heinzman, J. T., Hing, B. W. Q., Grossbach, A. J., Dlouhy, B. J., Howard, M. A., Kawasaki, H., et al. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2017.08.029 · Cited by 28 · see citing works
Åberg, K. A., Shabalin, A. A., Chan, R. F., Zhao, M., Kumar, G., van Grootheest, G., Clark, S. L., Xie, L. Y., Milaneschi, Y., Penninx, B. W. J. H., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-018-0205-8 · Cited by 24 · see citing works
Editorial: Biomarkers of Alzheimer’s Disease: The Present and the Future
Lehmann, S., & Teunissen, C. E. (2016) · Frontiers in Neurology · doi:10.3389/fneur.2016.00158 · Cited by 13 · see citing works
Jia, T., Chu, C., Liu, Y., van Dongen, J., Armstrong, N. J., Bastin, M. E., Carrillo‐Roa, T., den Braber, A., Harris, M. A., Jansen, R., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/460444 · Cited by 12 · see citing works
Self-citation
Flagged first, then by citations
Research works printed but not linked: 1
- [46]Phipson B, Lee S, Majewski IJ, Alexander WS, Smyth G. Robust hyperparameter estimation protects. 2016;10:946–63. PMC5373812 28367255
Cited by
Sorted by citations
Gene–environment interactions in Alzheimer disease: the emerging role of epigenetics
Migliore, L., & Coppedè, F. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-022-00714-w · Cited by 217 · see citing works
Shireby, G. L., Dempster, E. L., Policicchio, S. S. S., Smith, R. G., Pishva, E., Chioza, B. A., Davies, J. P., Burrage, J., Lunnon, K., Vellame, D. S., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-33394-7 · Cited by 125 · see citing works
Baloni, P., Arnold, M., Buitrago, L., Nho, K. T., Moreno, H., Huynh, K., Brauner, B., Louie, G., Kueider‐Paisley, A., Suhre, K., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-04011-6 · Cited by 115 · see citing works
Self-citationSehgal, R., Markov, Y., Qin, C., Meer, M. V., Hadley, C., Shadyab, A. H., Casanova, R., Manson, J. E., Bhatti, P., Moore, A. Z., et al. (2025) · Nature Aging · doi:10.1038/s43587-025-00958-3 · Cited by 105 · see citing works
Ren, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97 · see citing works
The Worldwide Alzheimer's Disease Neuroimaging Initiative: ADNI‐3 updates and global perspectives
Weber, C. J., Carrillo, M. C., Jagust, W. J., Jack, C. R., Shaw, L. M. J., Trojanowski, J. Q., Saykin, A. J., Beckett, L. A., Sur, C., Rao, N. P., et al. (2021) · Alzheimer s & Dementia Translational Research & Clinical Interventions · doi:10.1002/trc2.12226 · Cited by 87 · see citing works
Self-citationAssociation of peripheral blood DNA methylation level with Alzheimer’s disease progression
Li, Q. S., Vasanthakumar, A., Davis, J. W., Idler, K. B., Nho, K. T., Waring, J. F., Saykin, A. J., & Initiative, A. D. N. (2021) · Clinical Epigenetics · doi:10.1186/s13148-021-01179-2 · Cited by 69 · see citing works
Self-citationMayo, S., Benito‐León, J., Peña‐Bautista, C., Baquero, M., & Cháfer‐Pericás, C. (2020) · Current Neuropharmacology · doi:10.2174/1570159x19666201223154009 · Cited by 60 · see citing works
Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease
Silva, T. C., Young, J. I., Zhang, L., Gomez, L., Schmidt, M. A., Varma, A., Chen, X. S., Martin, E. R., & Wang, L. (2022) · Nature Communications · doi:10.1038/s41467-022-32475-x · Cited by 55 · see citing works
Gianattasio, K. Z., Bennett, E. E., Wei, J., Mehrotra, M., Mosley, T. H., Gottesman, R. F., Wong, D. F., Stuart, E. A., Griswold, M. E., Couper, D. J., et al. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12293 · Cited by 51 · see citing works
Role of Mitochondria in Neurodegenerative Diseases: From an Epigenetic Perspective
Xu, S., Zhang, X., Liu, C., Liu, Q., Chai, H., Luo, Y., & Li, S. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.688789 · Cited by 49 · see citing works
One-carbon epigenetics and redox biology of neurodegeneration
Coppedè, F. (2020) · Free Radical Biology and Medicine · doi:10.1016/j.freeradbiomed.2020.12.002 · Cited by 47 · see citing works
Roles of physical exercise in neurodegeneration: reversal of epigenetic clock
Xu, M., Zhu, J., Liu, X.-D., Luo, M.-Y., & Xu, N.-J. (2021) · Translational Neurodegeneration · doi:10.1186/s40035-021-00254-1 · Cited by 46 · see citing works
Wei, S., Tao, J., Xu, J., Chen, X., Wang, Z., Zhang, N., Zuo, L., Jia, Z., Chen, H., Sun, H., et al. (2021) · Advanced Science · doi:10.1002/advs.202100727 · Cited by 42 · see citing works
Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Lukacsovich, D., Varma, A., Chen, X. S., Martin, E. R., & Wang, L. (2023) · Alzheimer s Research & Therapy · doi:10.1186/s13195-023-01216-7 · Cited by 38 · see citing works
Epigenetic Peripheral Biomarkers for Early Diagnosis of Alzheimer’s Disease
Villa, C., & Stoccoro, A. (2022) · Genes · doi:10.3390/genes13081308 · Cited by 37 · see citing works
Treble‐Barna, A., Heinsberg, L. W., Stec, Z., Breazeale, S., Davis, T. S., Kesbhat, A., Chattopadhyay, A., VonVille, H. M., Ketchum, A., Yeates, K. O., et al. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2023.105078 · Cited by 37 · see citing works
Targeting epigenetics: A novel promise for Alzheimer’s disease treatment
Jeremic, D., Jiménez‐Díaz, L., & Navarro‐López, J. D. (2023) · Ageing Research Reviews · doi:10.1016/j.arr.2023.102003 · Cited by 36 · see citing works
Utility of DNA Methylation as a Biomarker in Aging and Alzheimer’s Disease
Milicic, L., Porter, T., Vacher, M. A., & Laws, S. M. (2023) · Journal of Alzheimer s Disease Reports · doi:10.3233/adr-220109 · Cited by 36 · see citing works
Distinct sex-specific DNA methylation differences in Alzheimer’s disease
C. Silva, T., Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Varma, A., Chen, X. S., Martin, E. R., & Wang, L. (2022) · Alzheimer's Research & Therapy · doi:10.1186/s13195-022-01070-z · Cited by 33 · see citing works
“Based on our experiences and previous studies in the analysis of EWAS measured in blood [22, 38, 47], we expected our meta-analysis to be underpowered, given the modest sample sizes of the sex-specific analyses.”
MethodResultInfluentialLiu, M., Liu, R., Wang, R., Ba, Y., Yu, F., Deng, Q., & Huang, H. (2022) · Journal of Applied Toxicology · doi:10.1002/jat.4419 · Cited by 34 · see citing works
Whitman, E. T., Ryan, C. P., Abraham, W. C., Addae, A., Corcoran, D. L., Elliott, M. L., Hogan, S., Ireland, D. R., Keenan, R. J., Knodt, A. R., et al. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2024.01.008 · Cited by 33 · see citing works
Increase in Mitochondrial D-Loop Region Methylation Levels in Mild Cognitive Impairment Individuals
Stoccoro, A., Baldacci, F., Ceravolo, R., Giampietri, L., Tognoni, G., Siciliano, G., Migliore, L., & Coppedè, F. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23105393 · Cited by 30 · see citing works
Chen, L., Saykin, A. J., Yao, B., Zhao, F., & Initiative, A. D. N. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.10.016 · Cited by 29 · see citing works
Self-citationNdhlovu, L. C., Bendall, M. L., Dwaraka, V. B., Pang, A. P. S., Dopkins, N., Carreras-Gallo, N., Smith, R. C., Nixon, D. F., & Corley, M. J. (2024) · Aging Cell · doi:10.1111/acel.14288 · Cited by 33 · see citing works
Epigenetic regulation in Alzheimer’s disease: is it a potential therapeutic target?
Coppedè, F. (2021) · Expert Opinion on Therapeutic Targets · doi:10.1080/14728222.2021.1916469 · Cited by 27 · see citing works
Modeling Alzheimer’s disease using human cell derived brain organoids and 3D models
Fernandes, S., Revanna, J. S., Pratt, J. M., Hayes, N., Marchetto, M. C., & Gage, F. H. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1434945 · Cited by 29 · see citing works
Ulrich, A., Wu, Y., Draisma, H. H. M., Wharton, J., Swietlik, E. M., Cebola, I., Vasilaki, E., Balkhiyarova, Z., Järvelin, M., AUVINEN, J. P., et al. (2024) · Nature Communications · doi:10.1038/s41467-023-44683-0 · Cited by 24 · see citing works
Hu, H., Tan, L., Bi, Y., Xu, W., Tan, L., Shen, X., Hou, X., Ma, Y., Dong, Q., & Yu, J. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01218-9 · Cited by 25 · see citing works
MacBean, L. F., Smith, A. R., & Lunnon, K. (2020) · Current Genetic Medicine Reports · doi:10.1007/s40142-020-00190-y · Cited by 21 · see citing works
Philibert, R. A., Mills, J. A., Long, J. D., Salisbury, S. E., Comellas, A. P., Gerke, A. K., Dawes, K., Weg, M. W. V., & Hoffman, E. A. (2020) · Genes · doi:10.3390/genes11121415 · Cited by 21 · see citing works
Imbimbo, B. P., Ippati, S., & Watling, M. (2020) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2020.1793755 · Cited by 20 · see citing works
Smith, R. G., Pishva, E., Kouhsar, M. P., Imm, J. L., Dobričić, V., Johannsen, P., Wittig, M., Franke, A., Vandenberghe, R. R., Schaeverbeke, J. M., et al. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14098 · Cited by 15 · see citing works
CYP1B1-RMDN2 Alzheimer’s disease endophenotype locus identified for cerebral tau PET
Nho, K. T., Risacher, S. L., Apostolova, L. G., Bice, P. J., Brosch, J. R., Deardorff, R. L., Faber, K. M., Farlow, M. R., Foroud, T., Gao, S., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-52298-2 · Cited by 22 · see citing works
Self-citationZhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Lukacsovich, D., Varma, A., Chen, X. S., Kunkle, B. W., Martin, E. R., & Wang, L. (2024) · Epigenetics · doi:10.1080/15592294.2024.2333660 · Cited by 15 · see citing works
Blood DNA methylation signature for incident dementia: Evidence from longitudinal cohorts
Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Lukacsovich, D., Kunkle, B. W., Chen, X. S., Martin, E. R., & Wang, L. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14496 · Cited by 14 · see citing works
Kim, B., Vasanthakumar, A., Li, Q.-Q. S., Nudelman, K., Risacher, S., Davis, J., Idler, K., Lee, J., Seo, S., Waring, J., et al. (2022) · Alzheimer's & Dementia · doi:10.1002/dad2.12354 · Cited by 15 · see citing works
Self-citationADmeth: A Manually Curated Database for the Differential Methylation in Alzheimer's Disease
Peng, X., Zhang, W., Cui, W., Ding, B., Lyu, Q., & Wang, J. (2022) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2022.3178087 · Cited by 12 · see citing works
Systems biology of Alzheimer’s Disease: a scoping review of key pathways and mechanisms
Bice, P. J., Nho, K. T., Ertekin‐Taner, N., & Saykin, A. J. (2026) · Molecular Neurodegeneration · doi:10.1186/s13024-026-00934-4 · Cited by 13 · see citing works
Self-citationLi, J. Z., Ramalingam, N., & Li, S. (2024) · Neural Regeneration Research · doi:10.4103/nrr.nrr-d-23-01827 · Cited by 11 · see citing works
Hackenhaar, F. S., Study, T. A. I. B. A. L., Josefsson, M., Adolfsson, A. N., Landfors, M., Kauppi, K., Porter, T., Milicic, L., Laws, S. M., Hultdin, M., et al. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-230039 · Cited by 10 · see citing works
Sritana, N., & Phungpinij, A. (2024) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph21091242 · Cited by 10 · see citing works
Wu, S., Yang, F., Shan, C., Wang, B., Wang, W., Li, H., Yu, L., He, L., Li, X., Sun, L., et al. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1175864 · Cited by 10 · see citing works
Lukacsovich, D., O'Shea, D. M., Huang, H.-C., Zhang, W., Young, J., Chen, X., Dietrich, S.-T., Kunkle, B. W., Martin, E., & Wang, L. (2023) · medRxiv · doi:10.1093/database/baae061 · Cited by 12 · see citing works
Epigenome-wide DNA methylation analysis of late-stage mild cognitive impairment
Zhang, Y., & Shen, S. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1276288 · Cited by 9 · see citing works
DNA methylation signature of a lifestyle-based resilience index for cognitive health
Zhang, W. Y., Lukacsovich, D., Young, J. I., Gomez, L., Schmidt, M. A., Martin, E. R., Kunkle, B. W., Chen, X. S., O’Shea, D. M., Galvin, J. E., et al. (2025) · Alzheimer s Research & Therapy · doi:10.1186/s13195-025-01733-7 · Cited by 11 · see citing works
Sehgal, R., Borrus, D. S., González, J. T., Markov, Y., ADNI, & Higgins‐Chen, A. (2026) · Aging Cell · doi:10.1111/acel.70635 · Cited by 8 · see citing works
Albala, B., Appelmans, E., Burress, R., Santi, S. D., Devins, T., Klein, G., Logovinsky, V., Novak, G., Ribeiro, K., Schmidt, M. E., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13483 · Cited by 8 · see citing works
Self-citationMurthy, M. N., Fodder, K., Miki, Y., Rambarack, N., Pablo‐Fernández, E. D., Pihlstrøm, L., Mill, J. S., Warner, T. T., Lashley, T., & Bettencourt, C. (2024) · Acta Neuropathologica · doi:10.1007/s00401-024-02764-4 · Cited by 7 · see citing works
Dhillon, A., Singh, A., & Bhalla, V. K. (2024) · Neural Computing and Applications · doi:10.1007/s00521-023-09359-2 · Cited by 7 · see citing works
Costantini, E., Carrarini, C., Calisi, D., Rosa, M. D., Simone, M., Crosta, A. D., Palumbo, R., Cipollone, A., Aielli, L., Laurentis, M. D., et al. (2024) · Journal of Alzheimer s Disease · doi:10.3233/jad-231471 · Cited by 7 · see citing works
DNA methylation biomarkers for cumulative lead exposures and cognitive impairment
Shao, K., Yu, Y., Ritz, B. R., & Paul, K. C. (2024) · Environmental Research · doi:10.1016/j.envres.2024.120304 · Cited by 6 · see citing works
A Comprehensive Evaluation of Cross-Omics Blood-Based Biomarkers for Neuropsychiatric Disorders
Song, W., Wang, W., Liu, Z., Cai, W., Yu, S., Zhao, M., & Lin, G. N. (2021) · Journal of Personalized Medicine · doi:10.3390/jpm11121247 · Cited by 6 · see citing works
DNA Methylation in Aging and Alzheimer's Disease
Cheng, R., Shu, J., Chen, H., Li, M., Cheng, X., & Liu, L. (2024) · Human Brain · doi:10.37819/hb.3.2027 · Cited by 5 · see citing works
Epigenetics and the gut–brain axis: Insights into DNA methylation, aging, and Alzheimer disease
Kumar, V., Shukla, R., Gangani, S., Joseph, R., Jain, S., & Yadav, H. (2026) · Journal of Pharmacology and Experimental Therapeutics · doi:10.1016/j.jpet.2026.104299 · Cited by 5 · see citing works
The Promise of Epigenetic Editing for Treating Brain Disorders
González-Molina, L. A., Dolga, A. M., Rots, M. G., & Sarno, F. (2025) · Sub-cellular biochemistry/Subcellular biochemistry · doi:10.1007/978-3-031-75980-2_4 · Cited by 5 · see citing works
Zhong, H., Zhu, J., Liu, S., Zhou, D., Long, Q., Wu, C., Zhao, B., Cheng, C., Yang, Y., Wu, Q. F., et al. (2025) · Human Molecular Genetics · doi:10.1093/hmg/ddaf053 · Cited by 5 · see citing works
Epigenetics of Stress in Farmed Fish
Guinand, B., & Σαμαράς, Α. (2023) · Wiley eBooks · doi:10.1002/9781119821946.ch12 · Cited by 5 · see citing works
Ndhlovu, L. C., Bendall, M. L., Dwaraka, V. B., Pang, A. P. S., Dopkins, N., Carreras-Gallo, N., Smith, R. C., Nixon, D. F., & Corley, M. J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.06.570422 · Cited by 5 · see citing works
Karlsson, I., Ploner, A., Wang, Y., Gatz, M., Pedersen, N. L., & Hägg, S. (2022) · Epigenetics · doi:10.1080/15592294.2022.2158285 · Cited by 4 · see citing works
A simple, rapid, interpretable, actionable and implementable digital PCR based mortality index
Philibert, R., Long, J., Mills, J., Beach, S., Gibbons, F., Gerrard, M., Simons, R. L., Pinho, P., Ingle, D., Dawes, K., et al. (2020) · Epigenetics · doi:10.1080/15592294.2020.1841874 · Cited by 4 · see citing works
Nho, K. T., Risacher, S. L., Apostolova, L. G., Bice, P. J., Brosch, J. R., Deardorff, R. L., Faber, K. M., Farlow, M. R., Foroud, T., Gao, S., et al. (2023) · medRxiv · doi:10.1101/2023.02.27.23286048 · Cited by 4 · see citing works
Self-citationSreepada, L. P., Brown, C. A., Das, S. R., Yushkevich, P. A., Wolk, D. A., & McMillan, C. T. (2025) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2025.06.003 · Cited by 3 · see citing works
Multimodal Classification of Alzheimer’s Disease Based on Kolmogorov-Arnold Graph Attention Network
Wu, X., Tian, R., Xu, Z., Wang, S., & Zhang, Y. (2025) · Journal of Bionic Engineering · doi:10.1007/s42235-025-00754-0 · Cited by 3 · see citing works
A penalized integrative deep neural network for variable selection among multiple omics datasets
Li, Y., Ren, X., Yu, H., Sun, T., & Ma, S. (2024) · Quantitative Biology · doi:10.1002/qub2.51 · Cited by 3 · see citing works
Qian, Y., Tang, X., Shen, R., Lu, Y., Ding, J., Qian, X., & Zhang, C. (2024) · The Canadian Journal of Psychiatry · doi:10.1177/07067437241300947 · Cited by 2 · see citing works
Relationship periodontitis and Alzheimer's disease: Relevant aspects from an epigenetic view
Chacón, T., & Hernández, H. G. (2025) · Journal of Alzheimer s Disease · doi:10.1177/13872877251397406 · Cited by 2 · see citing works
Gerlando, R. D., Dragoni, F., Rizzo, B., Ferrari, R. R., Zardini, E., Ramusino, M. C., Perini, G., Costa, A. C., Poloni, T. E., Pansarasa, O., et al. (2024) · Aging and Disease · doi:10.14336/ad.2024.0350 · Cited by 1 · see citing works
Association of blood-based DNA methylation of lncRNAs with Alzheimer’s disease diagnosis
Tian, G., Zheng, D., Zhang, N., Deng, W., Xu, J., Huang, C., Chen, Q., Hu, S., Li, X., Wang, H., et al. (2025) · Clinical Epigenetics · doi:10.1186/s13148-025-02015-7 · Cited by 2 · see citing works
Enduru, N., & Zhao, Z. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71073 · Cited by 1 · see citing works
Main Existing Datasets for Open Brain Research on Humans
Couvy‐Duchesne, B., Bottani, S., Camenen, E., Fang, F., Fikere, M., Gonzalez-Astudillo, J., Harvey, J., Hassanaly, R., Kassam, I., Lind, P. A., et al. (2023) · Neuromethods · doi:10.1007/978-1-0716-3195-9_24 · Cited by 1 · see citing works
Morrow, J. D. (2024) · F1000Research · doi:10.12688/f1000research.140403.2 · Cited by 1 · see citing works
A blood DNA methylation test reveals how quickly each organ system is aging
(2025) · Nature Aging · doi:10.1038/s43587-025-00959-2 · Cited by 1 · see citing works
Hackenhaar, F. S., Josefsson, M., Adolfsson, A. N., Landfors, M., Kauppi, K., Porter, T., Milicic, L., Laws, S. M., Hultdin, M., Adolfsson, R., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-2276882/v2 · Cited by 1 · see citing works
Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Lukacsovich, D., Varma, A., Chen, X. S., Kunkle, B. W., Martin, E. R., & Wang, L. (2023) · Research Square · doi:10.21203/rs.3.rs-3068938/v2 · Cited by 1 · see citing works
Wang, X., & Wang, S. (2021) · Chinese Control Conference (CCC) · doi:10.23919/ccc52363.2021.9549385
Karlsson, I., Ploner, A., Wang, Y., Gatz, M., Pedersen, N. L., & Hägg, S. (2022) · Research Square · doi:10.21203/rs.3.rs-1479093/v1
Hackenhaar, F. S., Josefsson, M., Adolfsson, A. N., Landfors, M., Kauppi, K., Porter, T., Milicic, L., Laws, S. M., Hultdin, M., Adolfsson, R., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-2276882/v1
Hackenhaar, F. S., Josefsson, M., Adolfsson, A. N., Landfors, M., Kauppi, K., Porter, T., Milicic, L., Laws, S. M., Hultdin, M., Adolfsson, R., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2276882/v3
Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Lukacsovich, D., Varma, A., Chen, X. S., Kunkle, B. W., Martin, E. R., & Wang, L. (2023) · Research Square · doi:10.21203/rs.3.rs-3068938/v1
Hackenhaar, F. S., Josefsson, M., Adolfsson, A. N., Landfors, M., Kauppi, K., Porter, T., Milicic, L., Laws, S. M., Hultdin, M., Adolfsson, R., et al. (2023) · Research Square · doi:10.21203/rs.3.rs-2276882/v4
Morrow, J. D. (2023) · F1000Research · doi:10.12688/f1000research.140403.1
Additional file 2 of Distinct sex-specific DNA methylation differences in Alzheimer’s disease
Silva, T. C., Zhang, W. Y., Young, J. I., Gomez, L., Schmidt, M. A., Varma, A., Chen, X. S., Martin, E. R., & Wang, L. (2022) · Figshare · doi:10.6084/m9.figshare.21129954
Emerging Biomarkers for Early Detection of Alzheimer’s Disease: A Systematic ReviewPreprint
Desai, C., Rathod, S., Daulti, T., Prajapati, M., Malkan, S., & Bhamwani, M. (2024) · medRxiv · doi:10.1101/2024.10.16.24315604
Andrews, S. J., Sharma, R. U., Mitchell, B. A., Tong, T., Bonham, L. W., Renton, A. E., Zhang, X., Sirota, M., Tosun, D., Yaffe, K. S., et al. (2025) · medRxiv · doi:10.1101/2025.07.16.25331683
Delineating blood DNA methylation biomarkers for Alzheimer's disease
Pishva, E., Bertram, L., & Lunnon, K. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70646
Xiao, B., Zeng, Y., Klein, K., Granato, B., Blanchette, M., Shao, X., & Greenwood, C. M. T. (2025) · Scientific Reports · doi:10.1038/s41598-025-22004-3
Additional file 1 of Distinct sex-specific DNA methylation differences in Alzheimer’s disease
C. Silva, T., Zhang, W., Young, J. I., Gomez, L., Schmidt, M. A., Varma, A., Chen, X. S., Martin, E. R., & Wang, L. (2022) · Figshare · doi:10.6084/m9.figshare.21129953
Li, Q. S., Vasanthakumar, A., Davis, J. W., Idler, K. B., Nho, K. T., Waring, J. F., & Saykin, A. J. (2021) · Figshare · doi:10.6084/m9.figshare.16821479
Self-citationYao, M., Tian, P., Li, X., Bian, S., Gao, W., Gu, Y., Acien, A. N., Vardarajan, B. N., Belsky, D. W., Miller, G. W., et al. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbaf730
Co-expression network multivariate regression
Lee, H., Pan, Y., & Chen, S. (2026) · Briefings in Bioinformatics · doi:10.1093/bib/bbag125
Age-varying DNA methylation patterns associated with blood pressure in mid-to-late adulthood
Xu, G., Zhuang, X., Amei, A., Wang, Z., & Oh, E. C. T. (2026) · Clinical Epigenetics · doi:10.1186/s13148-026-02092-2
Diagnostic and Prognostic Value of Epigenetic Markers in Neurological Diseases. A Narrative Review
Grodzka, O., Wołos, J., Kupc, M., Ahmadova, S., Eyileten, C., & Domitrz, I. (2026) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-026-01766-y
He, Y., Yi, T., Min, M., Xu, K., Lin, H., Xu, R., Deng, D., & Xiao, X. (2026) · Neuroscience Bulletin · doi:10.1007/s12264-026-01645-y
Blood DNA Methylation Predicts Long-Term Risk of Dementia in Prospective CohortsPreprint
Maihofer, A. X., Mackey, C. E., Robertson, J. A., Marioni, R. E., Nguyen, S., McEvoy, L. K., LaCroix, A. Z., Espeland, M. A., Rapp, S. R., Resnick, S. M., et al. (2026) · medRxiv · doi:10.64898/2026.07.08.26357554
Mitchell, B. A., Hausle, I., Smith, S., Thropp, P., Sirota, M., Tosun, D., & Initiative, A. D. N. (2026) · npj Dementia · doi:10.1038/s44400-026-00100-z
Guo, X., Sun, Y., Chen, Y., Liu, H., Liu, X., & Wang, X. (2026) · Biosensors · doi:10.3390/bios16090514
Self-citationCerebrospinal fluid cell-free DNA methylation captures disease-specific biology in tauopathies
Tian, H., Zhang, J., Zuo, H., Liu, Y., Kim, I.-D., & 桂雅星 (2026) · Journal of Alzheimer s Disease · doi:10.1177/13872877261500498
- Authors
- Vasanthakumar, A., Davis, J. W., Idler, K., Waring, J. F., Asque, E., Riley-Gillis, B., Grosskurth, S., Srivastava, G., Kim, S., Nho, K., Nudelman, K. N. H., Faber, K., Sun, Y., Foroud, T. M., Estrada, K., Apostolova, L. G., Li, Q. S., Saykin, A. J., & (ADNI), F. T. A. D. N. I.
- Affiliations
- AbbVie (United States) (US)
- State University of New York at Oswego (US)
- Indiana University School of Medicine (US)
- Janssen (United States) (US)
- Biogen (United States) (US)
- Corresponding author
- Vasanthakumar, Aparna
- ORCID
- Venue
- Clinical Epigenetics
- Published
- 2020-06-15
- Volume
- 12
- Issue
- 1
- Pages
- 84-84
- ISSN
- 1868-7075 (ISSN-L)
- 1868-7083
- PMC
- PMC7294637
- OpenAlex
- W3035710795
- Cited by
- 98
- References
- 53
- Citations by year
- 2026: 13 · 2025: 14 · 2024: 21 · 2023: 15 · 2022: 17 · 2021: 12 · 2020: 6
- FWCI
- 9.30
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Clinical Epigenetics (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- IUScholarWorks (Indiana University) (submittedVersion, cc-by)
- Funders
- National Institutes of Health (U01 AG024904)
- U.S. Department of Defense (W81XWH-12-2-0012)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease, differentially methylated positions, blood-based biomarkers, mild cognitive impairment, early diagnosis, Mini-Mental State Examination, brain-derived neurotrophic factor, BIN1, APOC1, neurodegeneration, disease progression, epigenetic biomarkers
- MeSH terms
- Mental Status and Dementia Tests, Aged, Aged, 80 and over, Alzheimer Disease, Diagnosis, Differential, Female, Genotype, Humans, Longitudinal Studies, Male, Phenotype, Biomarkers, Case-Control Studies, Disease Progression, DNA Methylation, Early Diagnosis, Epigenomics, Transcriptome, Neuroimaging, Cognitive Dysfunction
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
