Anne M. Fagan

64.2k total citations · 15 hit papers
290 papers, 26.3k citations indexed

About

Anne M. Fagan is a scholar working on Physiology, Psychiatry and Mental health and Cognitive Neuroscience. According to data from OpenAlex, Anne M. Fagan has authored 290 papers receiving a total of 26.3k indexed citations (citations by other indexed papers that have themselves been cited), including 177 papers in Physiology, 150 papers in Psychiatry and Mental health and 61 papers in Cognitive Neuroscience. Recurrent topics in Anne M. Fagan's work include Alzheimer's disease research and treatments (167 papers), Dementia and Cognitive Impairment Research (149 papers) and Functional Brain Connectivity Studies (42 papers). Anne M. Fagan is often cited by papers focused on Alzheimer's disease research and treatments (167 papers), Dementia and Cognitive Impairment Research (149 papers) and Functional Brain Connectivity Studies (42 papers). Anne M. Fagan collaborates with scholars based in United States, Germany and Australia. Anne M. Fagan's co-authors include David M. Holtzman, John C. Morris, Tammie L.S. Benzinger, Mark A. Mintun, Chengjie Xiong, Catherine M. Roe, Alison Goate, Richard J. Perrin, Kelly R. Bales and Chengjie Xiong and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Anne M. Fagan

282 papers receiving 25.8k citations

Hit Papers

Blood–brain barrier br... 2000 2026 2008 2017 2019 2005 2011 2000 2007 250 500 750 1000
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Blood–brain barrier breakdown is an early biomarker of human cognitive dysfunction
    2019 1.1k citations Tammie L.S. Benzinger, Anne M. Fagan et al. profile →
  2. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Aβ 42 in humans
    2005 960 citations Anne M. Fagan, Mark A. Mintun et al. profile →
  3. Human apoE Isoforms Differentially Regulate Brain Amyloid-β Peptide Clearance
    2011 887 citations Anne M. Fagan, John C. Morris et al. Science Translational Medicine profile →
  4. Apolipoprotein E isoform-dependent amyloid deposition and neuritic degeneration in a mouse model of Alzheimer's disease
    2000 726 citations David M. Holtzman, Kelly R. Bales et al. profile →
  5. Cerebrospinal Fluid tau/β-Amyloid42 Ratio as a Prediction of Cognitive Decline in Nondemented Older Adults
    2007 687 citations Anne M. Fagan, Catherine M. Roe et al. Archives of Neurology profile →
  6. APOE predicts amyloid‐beta but not tau Alzheimer pathology in cognitively normal aging
    2009 654 citations John C. Morris, Catherine M. Roe et al. profile →
  7. High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis
    2019 551 citations Suzanne E. Schindler, Brian A. Gordon et al. Neurology profile →
  8. Tau and Aβ imaging, CSF measures, and cognition in Alzheimer’s disease
    2016 535 citations Brian A. Gordon, Jason Hassenstab et al. Science Translational Medicine profile →
  9. Sleep Quality and Preclinical Alzheimer Disease
    2013 530 citations Jennifer McLeland, Cristina D. Toedebusch et al. profile →
  10. Multimodal techniques for diagnosis and prognosis of Alzheimer's disease
    2009 519 citations Richard J. Perrin, Anne M. Fagan et al. profile →
  11. Slow wave sleep disruption increases cerebrospinal fluid amyloid-β levels
    2017 425 citations Courtney L. Sutphen, Anne M. Fagan et al. Brain profile →
  12. Preclinical Alzheimer's disease and its outcome: a longitudinal cohort study
    2013 412 citations Chengjie Xiong, Jason Hassenstab et al. profile →
  13. Amyloid β concentrations and stable isotope labeling kinetics of human plasma specific to central nervous system amyloidosis
    2017 386 citations David M. Holtzman, John C. Morris et al. Alzheimer s & Dementia profile →
  14. Current state of Alzheimer’s fluid biomarkers
    2018 375 citations Anne M. Fagan, Leslie M. Shaw et al. profile →
  15. Gut microbiome composition may be an indicator of preclinical Alzheimer’s disease
    2023 180 citations Tammie L.S. Benzinger, David M. Holtzman et al. Science Translational Medicine profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Anne M. Fagan United States 86 15.2k 9.5k 6.1k 5.2k 4.9k 290 26.3k
Ralph N. Martins Australia 88 15.6k 1.0× 8.6k 0.9× 7.1k 1.2× 3.5k 0.7× 4.0k 0.8× 591 29.3k
Steven E. Arnold United States 89 10.1k 0.7× 7.8k 0.8× 5.3k 0.9× 4.6k 0.9× 4.1k 0.9× 344 28.1k
Claudia H. Kawas United States 71 13.7k 0.9× 15.2k 1.6× 4.1k 0.7× 5.7k 1.1× 5.0k 1.0× 242 32.3k
Mony J. de Leon United States 88 13.6k 0.9× 11.8k 1.2× 4.6k 0.8× 6.1k 1.2× 4.6k 0.9× 304 31.0k
Victor L. Villemagne Australia 81 14.4k 0.9× 11.4k 1.2× 4.7k 0.8× 5.4k 1.0× 3.5k 0.7× 538 26.2k
Hilkka Soininen Finland 105 16.8k 1.1× 16.1k 1.7× 6.5k 1.1× 7.7k 1.5× 6.2k 1.3× 680 40.6k
Douglas Galasko United States 82 11.9k 0.8× 11.5k 1.2× 4.7k 0.8× 3.8k 0.7× 4.2k 0.9× 295 25.2k
Eric M. Reiman United States 102 15.1k 1.0× 11.9k 1.3× 5.7k 0.9× 10.5k 2.0× 4.2k 0.9× 469 34.5k
Michelle M. Mielke United States 87 11.4k 0.8× 11.2k 1.2× 4.2k 0.7× 3.9k 0.8× 3.3k 0.7× 586 27.0k
Harald Hampel Germany 98 17.8k 1.2× 13.9k 1.5× 7.6k 1.2× 7.8k 1.5× 6.0k 1.2× 496 35.3k

Countries citing papers authored by Anne M. Fagan

Since Specialization
Citations

This map shows the geographic impact of Anne M. Fagan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Anne M. Fagan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Anne M. Fagan more than expected).

Fields of papers citing papers by Anne M. Fagan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Anne M. Fagan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Anne M. Fagan. The network helps show where Anne M. Fagan may publish in the future.

Co-authorship network of co-authors of Anne M. Fagan

This figure shows the co-authorship network connecting the top 25 collaborators of Anne M. Fagan. A scholar is included among the top collaborators of Anne M. Fagan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Anne M. Fagan. Anne M. Fagan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Aschenbrenner, Andrew J., Jennifer L. Crawford, Jonathan E. Peelle, et al.. (2023). Increased cognitive effort costs in healthy aging and preclinical Alzheimer’s disease.. Psychology and Aging. 38(5). 428–442. 9 indexed citations
2.
Wisch, Julie K., Omar H. Butt, Brian A. Gordon, et al.. (2022). Proteomic clusters underlie heterogeneity in preclinical Alzheimer’s disease progression. Brain. 146(7). 2944–2956. 5 indexed citations
3.
Kothapalli, Satya V. V. N., Tammie L.S. Benzinger, Andrew J. Aschenbrenner, et al.. (2021). Quantitative Gradient Echo MRI Identifies Dark Matter as a New Imaging Biomarker of Neurodegeneration that Precedes Tissue Atrophy in Early Alzheimer’s Disease. Journal of Alzheimer s Disease. 85(2). 905–924. 5 indexed citations
4.
Butt, Omar H., Justin M. Long, Rachel L. Henson, et al.. (2021). Cognitively normal APOE ε4 carriers have specific elevation of CSF SNAP-25. Neurobiology of Aging. 102. 64–72. 10 indexed citations
5.
Millar, Peter R, Beau M. Ances, Brian A. Gordon, et al.. (2020). Evaluating resting-state BOLD variability in relation to biomarkers of preclinical Alzheimer's disease. Neurobiology of Aging. 96. 233–245. 18 indexed citations
6.
Lucey, Brendan P., Austin McCullough, Eric C. Landsness, et al.. (2019). Reduced non–rapid eye movement sleep is associated with tau pathology in early Alzheimer’s disease. Science Translational Medicine. 11(474). 240 indexed citations
7.
Millar, Peter R, David A. Balota, Geoffrey B. Maddox, et al.. (2017). Process dissociation analyses of memory changes in healthy aging, preclinical, and very mild Alzheimer disease: Evidence for isolated recollection deficits.. Neuropsychology. 31(7). 708–723. 8 indexed citations
8.
Deming, Yuetiva, Kathleen Black, David Carrell, et al.. (2016). Chitinase-3-like 1 protein (CHI3L1) locus influences cerebrospinal fluid levels of YKL-40. BMC Neurology. 16(1). 217–217. 12 indexed citations
9.
Harari, Oscar, Carlos Cruchaga, John S. K. Kauwe, et al.. (2014). Phosphorylated Tau-Aβ42 Ratio as a Continuous Trait for Biomarker Discovery for Early-Stage Alzheimer’s Disease in Multiplex Immunoassay Panels of Cerebrospinal Fluid. Biological Psychiatry. 75(9). 723–731. 69 indexed citations
10.
Benítez, Bruno A., Celeste M. Karch, Yefei Cai, et al.. (2013). The PSEN1, p.E318G Variant Increases the Risk of Alzheimer's Disease in APOE-ε4 Carriers. PLoS Genetics. 9(8). e1003685–e1003685. 52 indexed citations
11.
Fagan, Anne M. & Richard J. Perrin. (2012). Upcoming Candidate Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease. Biomarkers in Medicine. 6(4). 455–476. 85 indexed citations
12.
Jackson, Jonathan, Anne M. Fagan, David M. Holtzman, David A. Balota, & John C. Morris. (2012). P2‐070: Detecting preclinical markers of dementia: The power of sustained attention and mind‐wandering. Alzheimer s & Dementia. 8(4S_Part_8). 1 indexed citations
13.
Roe, Catherine M., Anne M. Fagan, Monique Williams, et al.. (2011). Improving CSF biomarker accuracy in predicting prevalent and incident Alzheimer disease. Neurology. 76(6). 501–510. 35 indexed citations
14.
Fagan, Anne M., Leslie M. Shaw, Chengjie Xiong, et al.. (2011). Comparison of Analytical Platforms for Cerebrospinal Fluid Measures of β-Amyloid 1-42, Total tau, and P-tau181 for Identifying Alzheimer Disease Amyloid Plaque Pathology. Archives of Neurology. 68(9). 1137–1137. 137 indexed citations
15.
Kauwe, John, Carlos Cruchaga, Celeste M. Karch, et al.. (2011). Fine Mapping of Genetic Variants in BIN1, CLU, CR1 and PICALM for Association with Cerebrospinal Fluid Biomarkers for Alzheimer's Disease. PLoS ONE. 6(2). e15918–e15918. 45 indexed citations
16.
Galvin, James E., Anne M. Fagan, David M. Holtzman, Mark A. Mintun, & John C. Morris. (2010). Relationship of dementia screening tests with biomarkers of Alzheimer's disease. Brain. 133(11). 3290–3300. 75 indexed citations
17.
Kauwe, John, Carlos Cruchaga, Sarah Bertelsen, et al.. (2010). Validating Predicted Biological Effects of Alzheimer's Disease Associated SNPs Using CSF Biomarker Levels. Journal of Alzheimer s Disease. 21(3). 833–842. 33 indexed citations
18.
Clifford, David B., Anne M. Fagan, David M. Holtzman, et al.. (2009). CSF biomarkers of Alzheimer disease in HIV-associated neurologic disease. Neurology. 73(23). 1982–1987. 134 indexed citations
19.
Kauwe, John, Jun Wang, Kevin H. Mayo, et al.. (2008). Alzheimer’s disease risk variants show association with cerebrospinal fluid amyloid beta. Neurogenetics. 10(1). 13–17. 62 indexed citations
20.
Fagan, Anne M., Jennie Taylor, Maia Parsadanian, et al.. (2004). ApoAI Deficiency Results in Marked Reductions in Plasma Cholesterol But No Alterations in Amyloid-β Pathology in a Mouse Model of Alzheimer's Disease-Like Cerebral Amyloidosis. American Journal Of Pathology. 165(4). 1413–1422. 46 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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