The DOI matches its Crossref record; 48 of the 48 references it cites were found in a registry or an index.
Body mass index and magnetic resonance markers of brain integrity in adults
Open accessAbstract
Objective: Obesity and being overweight during adulthood have been consistently linked to increased risk for development of dementia later in life, especially Alzheimer's disease. They have also been associated with cognitive dysfunction and brain structural alterations in otherwise healthy adults. Although proton magnetic resonance spectroscopy may distinguish between neuronal and glial components of the brain and may point to neurobiological mechanisms underlying brain atrophy and cognitive changes, no spectroscopic studies have yet assessed the relationships between adiposity and brain metabolites. Methods: We have utilized magnetic resonance imaging and proton magnetic resonance spectroscopic imaging data from 50 healthy middle‐aged participants (mean age, 41.7 ± 8.5 years; 17 women), who were scanned as control subjects for another study. Results: After adjustment for age and sex, greater body mass indices (BMIs) correlated with: (1) lower concentrations of N‐acetylaspartate (spectroscopic marker of neuronal viability) in frontal (p = 0.001), parietal (p = 0.006), and temporal (p = 0.008) white matter; (2) lower N‐acetylaspartate in frontal gray matter (p = 0.01); and (3) lower concentrations of choline‐containing metabolites (associated with membrane metabolism) in frontal white matter (p = 0.05). Interpretation: These results suggest that increased BMI at midlife is associated with neuronal and/or myelin abnormalities, primarily in the frontal lobe. Because white matter in the frontal lobes is more prone to the effects of aging than in other lobes, our results may reflect accelerated aging in individuals with high levels of adiposity. Thus, greater BMI may increase the odds of developing an age‐related disease, such as Alzheimer's disease. Ann Neurol 2008
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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?
In the citing paper
“Similarly, a nuclear magnetic resonance spectroscopic study in healthy middle age and elderly controls showed that BMI was negatively associated with the levels of N-acetyl-aspartate (a marker of neuronal integrity) in frontal cortex and ACC (98,127).”
From Obesity and addiction: Neurobiological overlaps (2013) · cites this paper as [127]
In the citing paper
“Similarly, an NMR spectroscopic study of healthy middle age and elderly controls showed that BMI was negatively associated with the levels of N-acetyl-aspartate (a marker of neuronal integrity) in frontal cortex and ACC (Gazdzinski et al 2008;Volkow et al 2009c).”
From Food and Drug Reward: Overlapping Circuits in Human Obesity and Addiction (2011) · cites this paper as Gazdzinski et al 2008
Citations
Cites
Prevalence and trends in obesity among US adults, 1999–2000
Flegal, K. M. (2002) · JAMA · doi:10.1001/jama.288.14.1723 · Cited by 6,190
Sobell, L. C., & Sobell, M. B. (1992) · Measuring Alcohol Consumption · doi:10.1007/978-1-4612-0357-5_3 · Cited by 4,110
Prevalence and Trends in Overweight Among US Children and Adolescents, 1999-2000
Ogden, C. L. (2002) · JAMA · doi:10.1001/jama.288.14.1728 · Cited by 4,060
N-Acetylaspartate in the CNS: From neurodiagnostics to neurobiology
MOFFETT, J., Ross, B., Arun, P., Madhavarao, C. N., & Namboodiri, A. M. (2007) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2006.12.003 · Cited by 1,443
Obesity and Vascular Risk Factors at Midlife and the Risk of Dementia and Alzheimer Disease
Kivipelto, M., Ngandu, T., Fratiglioni, L., Viitanen, M., Kåreholt, I., Winblad, B., Helkala, E.-L., Tuomilehto, J., Soininen, H., & Nissinen, A. (2005) · Archives of Neurology · doi:10.1001/archneur.62.10.1556 · Cited by 1,291
Axonopathy and Transport Deficits Early in the Pathogenesis of Alzheimer’s Disease
Stokin, G. B., Lillo, C., Falzone, T. L., Brusch, R. G., Rockenstein, E., Mount, S. L., Raman, R., Davies, P., Masliah, E., Williams, D. S., et al. (2005) · Science · doi:10.1126/science.1105681 · Cited by 1,214
The worldwide obesity epidemic
James, P. T., Leach, R., Kalamara, E., & Shayeghi, M. (2001) · Obesity Research · doi:10.1038/oby.2001.123 · Cited by 1,201
Differential aging of the brain: Patterns, cognitive correlates and modifiers
Raz, N., & Rodrigue, K. M. (2006) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2006.07.001 · Cited by 1,195
Obesity in middle age and future risk of dementia: a 27 year longitudinal population based study
Whitmer, R. A., Gunderson, E. P., Barrett-Connor, E., Quesenberry, C. P., & Yaffe, K. (2005) · BMJ · doi:10.1136/bmj.38446.466238.e0 · Cited by 1,090
Age-related myelin breakdown: a developmental model of cognitive decline and Alzheimer’s disease
Bartzokis, G. (2004) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2003.03.001 · Cited by 968
Research works printed but not linked: 1
- Beck AT, 1978, Depression Inventory
Cited by
Sorted by citations
Reward, dopamine and the control of food intake: implications for obesity
Volkow, N. D., Wang, G.-J., & Baler, R. D. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.11.001 · Cited by 1,400
Obesity and addiction: Neurobiological overlaps
Volkow, N. D., Wang, G. ‐., Tomasi, D., & Baler, R. D. (2013) · Obesity Reviews · doi:10.1111/j.1467-789x.2012.01031.x · Cited by 800
Obesity and neuroinflammation: A pathway to cognitive impairment
Miller, A. A., & Spencer, S. J. (2014) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2014.04.001 · Cited by 834
Raji, C. A., Ho, A. J., Parikshak, N., Becker, J. T., López, O. L., Kuller, L. H., Hua, X., Leow, A., Toga, A. W., & Thompson, P. M. (2009) · Human Brain Mapping · doi:10.1002/hbm.20870 · Cited by 685
Cognitive impairment following high fat diet consumption is associated with brain inflammation
Pistell, P. J., Morrison, C. D., Gupta, S., Knight, A. G., Keller, J. N., Ingram, D. K., & Bruce‐Keller, A. J. (2009) · Journal of Neuroimmunology · doi:10.1016/j.jneuroim.2009.11.010 · Cited by 623
Metadata
- Authors
- Gazdzinski, S., Kornak, J., Weiner, M. W., & Meyerhoff, D. J.
- Affiliations
- San Francisco VA Medical Center (US)
- University of California, San Francisco (US)
- Corresponding author
- Gazdzinski, Stefan
- Venue
- Annals of Neurology
- Publisher
- Wiley
- Published
- 2008-05
- Volume
- 63
- Issue
- 5
- Pages
- 652-657
- ISSN
- 0364-5134 (ISSN-L)
- 1531-8249
- PMC
- PMC2542059
- OpenAlex
- W1995987678
- Cited by
- 191
- References
- 48
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 4 · 2023: 9 · 2022: 4 · 2021: 9 · 2020: 9 · 2019: 8 · 2018: 7 · 2017: 6 · 2016: 6 · 2015: 14 · 2014: 13 · 2013: 20 · 2012: 12
- FWCI
- 13.75
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Annals of Neurology (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Alcohol Abuse and Alcoholism (P01AA011493, R01AA010788)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- body mass index, obesity, adiposity, brain metabolites, N-acetylaspartate, choline-containing compounds, proton magnetic resonance spectroscopic imaging, white matter, gray matter, frontal lobe, brain aging, Alzheimer's disease, dementia risk, myelin abnormalities, middle-aged adults
- MeSH terms
- Adult, Aspartic Acid, Cerebral Cortex, Female, Humans, Magnetic Resonance Imaging, Male, Myelin Sheath, Statistics as Topic, Biomarkers, Body Mass Index
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
