Bowdoin Science Journal

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The Association Between Tooth Loss and Cognitive Decline

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Imaging of a vertical (coronal) slice through the brain of an Alzheimer patient (left) compared with a normal brain ( right).
“Could Magnetic Brain Stimulation Help People with Alzheimer’s? | Scientific American.” n.d. Accessed May 4, 2026. https://www.scientificamerican.com/article/could-magnetic-brain-stimulation-help-people-with-alzheimer-rsquo-s/.

Cognitive decline with age is a major concern in medicine and public health. In 2021, the World Health Organization reported 57 million people were affected by dementia worldwide (World Health Organization, 2023). Well-established risk factors include alcohol intake, lower education level, physical inactivity, obesity, and diabetes, and preventive strategies have developed steadily. However, one potential contributor is often overlooked in major dementia research: tooth loss. Galindo-Moreno et al. (2022) examined this relationship through a large-scale analysis of over 100,000 US Americans, making a case for oral health as an underrecognized factor in cognitive decline. 

Edentulism refers to the partial or complete loss of permanent teeth. Edentulism can be caused by a multitude of factors, including biological processes such as caries (tooth decay) and periodontal disease (infection or inflammation of gums and bone), pulpal pathologies (damage to nerves, tissue, and blood vessels in the center of a tooth), trauma, or oral cancer. In addition to biological causes, edentulism can result from factors affecting dental care: patient preference, access to care, treatment options, and health insurance (Felton 2009). A study found 37% of edentulism cases were due to extraction from caries, 29% from periodontal diseases, and 12% due to trauma (Al-Rafee 2020).  

Although oral health care has developed significantly in the last few decades, edentulism remains a prevalent and irreversible condition (Al-Rafee 2020). It can occur at all ages, but the highest incidence occurs between the ages of 75-79 [Figure 1] (Chen et al. 2025). Those most affected by tooth loss typically have a lower socioeconomic standing, which makes health care less affordable and accessible [Figure 2] (Vemulapalli et al. 2024)  

Graph of global incidence and prevalence of edentulism per 100,000 across all ages. Highest incidence rate at ages 75-79. Prevalence per 100,000 gradually increases as age increases.
Figure 1: Global prevalence and incidence rates of edentulism in 2021. Chen, Hui Min, Kuo Shen, Ling Ji, Colman McGrath, and Hui Chen. 2025. “Global and Regional Patterns in Edentulism (1990-2021) With Predictions to 2040.” International Dental Journal 75 (2): 735–43. https://doi.org/10.1016/j.identj.2024.11.022. December 31, 2024: 738

 

Prevalence rate of complete edentulism in US adults 65 years and older across different socio-economic status'. As income increases, the rate of complete edentulism decreases.
Figure 2: Prevalence rate of complete edentulism in US adults 65 years and older according to demographic characteristics: Behavioral Risk Factor Surveillance System 2012-2020. Income level. Vemulapalli, Abhilash, Surendra Reddy Mandapati, Anusha Kotha, Hemanth Rudraraju, and Subhash Aryal. 2024. “Prevalence of Complete Edentulism among US Adults 65 Years and Older.” The Journal of the American Dental Association 155 (5): 399–408. https://doi.org/10.1016/j.adaj.2024.02.002. May 6, 2024: 407

Galindo-Moreno et al. proposed multiple pathways by which tooth loss can lead to cognitive decline. Two that play directly into known factors are the “diet and nutrition mechanism” and the masticatory mechanism. The number of teeth and which teeth are present affect what we can eat and how we eat. Mastication — chewing of food (Xu et al. 2008) — is directly influenced by edentulism due to the reduced bite force one can exert with missing teeth or dentures (Galindo-Moreno et al. 2022; Weijenberg et al. 2011). Changes to mastication may impact cognition by decreasing sensory input, which would reduce cell growth and development, impairing the cholinergic neurotransmitter system responsible for regulating memory, muscles, and attention, and reducing the generation of new neurons triggered by exercise (Weijenberg et al. 2011). Mastication additionally restricts our diet and therefore directly plays into the diet and nutrition mechanism. Often, with altered dentition, chewing can be an immense hurdle, for which the solution is a softer yet less nutritious diet.Nutrients such as omega-3 fatty acids, B vitamins, and antioxidants have important neuroprotective properties that help preserve the blood brain barrier, an essential layer that prevents toxins from entering the brain,additionally reducing inflammation, lowering the risk of cognitive decline (Power et al. 2019). Both the masticatory and diet and nutrition mechanisms are intertwined with diabetes and obesity, which are known risk factors for cognitive decline (Galindo-Moreno et al. 2022). 

Another pathway this study mentions is the inflammation/infection mechanism. A leading cause of edentulism is periodontitis, a severe gum infection often driven by the bacterium Porphyromonas gingivalis. This bacterium induces the local release of cytokines, proinflammatory proteins (Galindo-Moreno et al. 2022). Once in the bloodstream, cytokines promote the production of amyloid-β, a peptide whose accumulation is associated with Alzheimer’s disease (Leira et al. 2020). Simultaneously, Porphyromonas gingivalis increases the permeability of the blood-brain barrier (Lei et al. 2023). The heightened permeability of the BBB causes accumulation of overproduced amyloid-β in the brain tissue [Figure 3] (Galindo-Moreno et al. 2022; Leira et al. 2020)  

Amyloid PET scan of patient with Alzheimer's Disease (right), and patient without Alzheimer's (left). Patient with Alzheimer's Disease shows higher detection of Amyloid plaques.
Figure 3: Amyloid PET scan comparison of healthy brain and Alzheimer’s disease. Chapleau, Marianne, Leonardo Iaccarino, David Soleimani-Meigooni, and Gil D. Rabinovici. 2022. “The Role of Amyloid PET in Imaging Neurodegenerative Disorders: A Review.” Clinical Investigation. Journal of Nuclear Medicine 63 (Supplement 1): 13S-19S. https://doi.org/10.2967/jnumed.121.263195.

To investigate the relationship between tooth loss and cognitive decline, the researchers analyzed data from over 100,000 Americans drawn from two large national health surveys, NHIS (2014-2017) and NHANES (2005-2018). The NHIS survey was particularly well-suited for assessing cognitive state, as it included four questions on concentration and memory. However, the survey included only one binary dental question asking whether the participants had a complete dentition or had lost ≥1 teeth. The NHANES survey complemented this with a thorough section on dental records. The exact number and location of lost teeth were documented. However, it assessed cognitive state with only one question on memory and confusion (Galindo-Moreno et al. 2022).   

Their primary statistical tool was multinomial logistic regression, a method used when an outcome has more than two categories. In this case, the categories were cognitive difficulty, ranging from “none” to “some” to “a lot.” By using this model, the researchers simultaneously accounted for other factors known to affect cognitive health, including age, income, education level, depression, anxiety, cardiovascular health, and lifestyle habits such as smoking and exercise, which were included in the health surveys. By modeling these variables together, the researchers could estimate the independent contribution of tooth loss to cognitive decline.  

The results were expressed as odds ratios (ORs), which indicate how much more likely a given outcome is in one group than in a reference group. Here, the reference was a fully toothed person reporting no cognitive difficulties. An OR above 1.0 indicated higher odds of cognitive problems among people with missing teeth. This held true even after the other variables were statistically accounted for. The researchers also used a technique called ROC curve analysis on the NHANES data that included exact tooth counts, allowing them to identify a meaningful threshold below which cognitive risk measurably increased (Galindo-Moreno et al. 2022).  

The researchers found that, overall, the presence of teeth was statistically associated with a better cognitive state. The NHIS data showed that people with edentulism (partial or complete) had an OR > 1 across all cognitive categories, especially memory, even after accounting for other risk factors. This trend was also observed across categories of gender, socio-economic status (SES), education, and cardiovascular risk — all of which negatively impact cognition. Notably, socioeconomic status emerged as one of the strongest predictors, alongside edentulism, reflecting how directly financial circumstances shape access to dental care and, through it, long-term cognitive health. 

Using ROC curve analysis of the NHANES data, they determined the threshold for cognitive risk to be 20.5 teeth, indicating that a person with fewer than 21 teeth has an increased risk of cognitive decline compared to a fully dentulous person (Galindo-Moreno et al. 2022). Importantly, the study analyzed the NHANES survey and found a gradient effect: the fewer teeth a person had, the worse their cognitive outcomes tended to be, which strengthens the case that the association is meaningful rather than coincidental. Furthermore, a threshold could be determined for each individual tooth category: 5.5, 5.5, 3.5, 4.5, respectively, for molars, premolars, canines, and incisors. The multinomial regression of the NHANES data determined molars had the highest OR. The researchers linked this to the masseter, an important masticatory muscle supported by molars, which may, through its activity, stimulate the release of neurotrophic factors that support brain health. 

The link between edentulism and cognitive decline is still scarcely researched. As of March 2026, there are only 66 results on PubMed, 142 on ScienceDirect, and 148 on Wiley on the correlation between edentulism and cognitive decline. To put this into perspective, there are 2,277 results on PubMed, 18,967 on ScienceDirect, and 10,546 on Wiley on the relationship between diet and cognitive decline. The discussed research article combines two USA national health surveys with diverse samples, NHIS and NHANES, making it one of the largest in scope to date on tooth loss and cognitive decline. Although Galindo-Moreno and his team compellingly demonstrate the correlation, they recognize that their findings cannot answer whether edentulism leads to poorer cognition or rather poor cognition leads to edentulism (Galindo-Moreno et al. 2022, 3498). Some of the issues the researchers faced were the binary assessment of dentition in the NHIS survey, the single question on cognitive condition in the NHANES survey, and the overall lack of records on the reasons for tooth loss (Galindo-Moreno et al. 2022).   

Nevertheless, this study is a step in the right direction. Galindo-Moreno et al. showed that edentulism is correlated with cognition, thereby providing meaningful epidemiological evidence for a relatively young field. Consequently, this study and further research could have great clinical implications for cognitive health, not only in cost-effective treatment and prevention, but also in an important personal impact for those struggling with cognitive impairments and dental hygiene. 

Al-Rafee, Mohammed A. 2020. “The Epidemiology of Edentulism and the Associated Factors: A Literature Review.” Journal of Family Medicine and Primary Care 9 (4): 1841–43. https://doi.org/10.4103/jfmpc.jfmpc_1181_19.  

Chapleau, Marianne, Leonardo Iaccarino, David Soleimani-Meigooni, and Gil D. Rabinovici. 2022. “The Role of Amyloid PET in Imaging Neurodegenerative Disorders: A Review.” Clinical Investigation. Journal of Nuclear Medicine63 (Supplement 1): 13S-19S. https://doi.org/10.2967/jnumed.121.263195.  

Chen, Hui Min, Kuo Shen, Ling Ji, Colman McGrath, and Hui Chen. 2025. “Global and Regional Patterns in Edentulism (1990-2021) With Predictions to 2040.” International Dental Journal 75 (2): 735–43. https://doi.org/10.1016/j.identj.2024.11.022.  

“Dementia.” n.d. Accessed March 27, 2026. https://www.who.int/news-room/fact-sheets/detail/dementia.  

Felton, David A. 2009. “Edentulism and Comorbid Factors.” Journal of Prosthodontics 18 (2): 88–96. https://doi.org/10.1111/j.1532-849X.2009.00437.x.  

Galindo-Moreno, Pablo, Lucia Lopez-Chaichio, Miguel Padial-Molina, et al. 2022. “The Impact of Tooth Loss on Cognitive Function.” Clinical Oral Investigations 26 (4): 3493–500. https://doi.org/10.1007/s00784-021-04318-4.  

Lei, Shuang, Jian Li, Jingjun Yu, et al. 2023. “Porphyromonas Gingivalis Bacteremia Increases the Permeability of the Blood-Brain Barrier via the Mfsd2a/Caveolin-1 Mediated Transcytosis Pathway.” International Journal of Oral Science15 (January): 3. https://doi.org/10.1038/s41368-022-00215-y.  

Leira, Yago, Álvaro Carballo, Marco Orlandi, et al. 2020. “Periodontitis and Systemic Markers of Neurodegeneration: A Case–Control Study.” Journal of Clinical Periodontology 47 (5): 561–71. https://doi.org/10.1111/jcpe.13267.  

Power, Rebecca, Alfonso Prado-Cabrero, Ríona Mulcahy, Alan Howard, and John M. Nolan. 2019. “The Role of Nutrition for the Aging Population: Implications for Cognition and Alzheimer’s Disease.” Annual Review of Food Science and Technology 10 (1): 619–39. https://doi.org/10.1146/annurev-food-030216-030125. 

Vemulapalli, Abhilash, Surendra Reddy Mandapati, Anusha Kotha, Hemanth Rudraraju, and Subhash Aryal. 2024. “Prevalence of Complete Edentulism among US Adults 65 Years and Older.” The Journal of the American Dental Association 155 (5): 399–408. https://doi.org/10.1016/j.adaj.2024.02.002.  

Weijenberg, R. A. F., E. J. A. Scherder, and F. Lobbezoo. 2011. “Mastication for the Mind—The Relationship between Mastication and Cognition in Ageing and Dementia.” Neuroscience & Biobehavioral Reviews 35 (3): 483–97. https://doi.org/10.1016/j.neubiorev.2010.06.002.  

World Health Organization. 2023. “Dementia” Fact Sheets. https://www.who.int/news-room/fact-sheets/detail/dementia 

Xu, W. L., J. E. Bronlund, J. Potgieter, et al. 2008. “Review of the Human Masticatory System and Masticatory Robotics.” Mechanism and Machine Theory 43 (11): 1353–75. https://doi.org/10.1016/j.mechmachtheory.2008.06.003. 

Philip Spyrou in the Spotlight

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“The lab and the art studio are fundamentally the same space; you have a material, a question you want to answer, and you experiment” – Philip Spyrou

Give a teen unfettered access to the internet and they might transform into a brain-rotten screenager. Luckily, in Philip Spyrou’s case, hours spent looking at Reddit feeds and YouTube videos did not translate into cognitive decline. In fact, quite the opposite was true; he used his internet privileges to teach himself how to cultivate life. As a high school sophomore, Philip experimented with hydroponics and tried to grow mushrooms using soil he made with whole grains and a pressure cooker. His resourceful and creative fascination with life led him to a chemistry and visual arts double major at Bowdoin College. He now studies the role of proteins in neuron function as a senior researcher in Professor Henderson’s chemistry lab.

When Philip showed me around the Henderson lab, he explained that proteins play a near-infinite number of crucial roles in biological processes. One such process is the formation of synapses in the brain. In simple terms, a synapsis is the coming together of two neurons to exchange information – a crucial mechanism for routine brain function. However, neurons need the ability to “crawl” around brain tissue before they can find other neurons and form synapses. SRGAP proteins enable neurons to develop finger-like protrusions from the cell membrane with which they can “crawl”. Philip studies how the membrane attracts these proteins.

Though one might think studying neurons requires a lab furnished with preserved brains in glass jars, Philip’s research (disappointingly) does not involve Frankensteinian techniques. In fact, Philip works with model cells called Giant Unilamellar Vesicles (GUVs), which are artificial membrane systems used to study cell functions. By modifying the GUV’s membrane, he observes how different membrane compositions attract SRGAP proteins. These observations can then be mapped onto neurons to understand how they develop the ability to “crawl” through brain tissue.
 

To study this neuron crawling mechanism, Philip has to think beyond the two dimensions of a textbook. After all, a protein’s three-dimensional structure is key to its function. In this regard, his time in the art studio has proven valuable to his work in the lab. Philip believes the lab and the studio aren’t all that different, and that working with clay and ceramics has trained him on how to gather materials, ask questions, and design experiments with a three-dimensional mindset.

 
 

“I like thinking visually, structurally, and three-dimensionally about the biological processes I study”

 

 
 
 

The three-dimensionality of Philip’s research unfolds at the molecular scale. It requires him to spend most of his time thinking about intangible processes. But, he says, it helps him to think of the applications of his research. For example, loss of proteins that enable neuron cells to crawl around the brain might be implicated in cognitive disabilities and memory loss. This is something he hopes to continue researching by earning a PhD with the goal of eventually becoming a full-time researcher.

As Philip continues on this path toward becoming a scientist, he finds it important to keep reminding himself of where his passion for science comes from. His love for understanding life originated in his backyard when he figured out how to grow plants and mushrooms. Though he does not foresee himself going back to researching those forms of life any time soon, he does want to keep tapping in to his fifteen-year-old self’s creative fascination for life.

Distributions, not Differentiation: New Studies Find Cell Proportions at the Heart of Neurological Specialization

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The human brain is organized into cortices, lobes, hemispheres, and more, with every designation serving as a location where a particular function necessary for survival is hosted. In understanding the cell types of the brain, scientists can further shape the understanding of the nature of human life. Current work strives toward comprehending the functions and capacities of the brain and developing stronger foundations for modeling brain physiology to support future research and medical applications. All of the advancements discussed originated from Alyssa Weninger and Paola Arlotta’s Science review article, A family portrait of human brain cells, which compiles recent findings in brain mapping research as aligned with the National Institute of Health’s BRAIN Initiative. In the article, Weninger and Arlotta summarize and discuss the work of multiple groups of neuroscientists that have developed new findings about the brain’s composition and variability across regions, individuals, and species (specifically five primates of interest and mice).

As suggested by the article, recent research from multiple teams of neuroscientists utilized a variety of study mechanisms to compare the composition of the brain. One of the most important tools used in the studies included single-cell profiling. This profiling technique analyzes cellular behavior through multiple methods that include their transcriptome (range of genetic information produced to control cell behavior), proteome (range of proteins produced by the cell), and epigenome (range of modifications and markings that control the genetic information expressed by a cell) to organize them into groups based on their functional similarities. Models that encompass these methods and human organoids (structures of organs derived from STEM cells that mimic organ tissue) are developed to model the brain and its cells. They are also used in mapping and developing comparative analyses to determine significant findings and understanding of the brain organization.

Comparisons of cell composition in regions across the brain resulted in findings from researchers under Siletti from the University of North Carolina at Chapel Hill and Jorstad from Harvard University. The two groups found that rather than mainly having different types of cells in different parts of the brain, some different parts of the brain shared the same cells but had different proportions of these cells. There were some exceptions, such as inhibitory neurons in the primary visual cortex, although the explanation of this finding is unclear. Such results change the understanding of evolutionary diversity in that diversification does not depend heavily on having many different cell types, but rather on having varying proportions of cells with small differences.

Jorstad’s group also developed a significant result in identifying differences in brain composition between human individuals. One cell type from 75 individuals was profiled and resulted in different classes of cells bearing contrasting levels of variability among individuals. Most of the explanatory factors were beyond demographic differences, such as gender, ancestry, or age. The reason for such differences is still unclear. Scientists are further encouraged to study bigger cohorts of people to further examine the origin of differences in variability across humans.

The finding of varying cell proportions held as Jorstad’s group conducted interspecies comparisons, comparing human compositions with other primates (specifically chimpanzees, gorillas, rhesus macaques, and marmosets). The exceptional cognitive ability found in humans was largely supported by differences in proportions of brain cell types rather than the variability of cell types. Additionally, faster evolutionary divergence may explain the differences in gene expression found between supportive tissue, known as glial cells, in the brain. This allowed for further species-specific development across primates. Only a limited number of gene patterns specific to humans were found, most of them concentrated in parts of the brain with human evolutionary change. As such, scientists have come to understand that attributes of the human brain are derived from very few cellular or molecular changes, leaving differences in cell proportions as the most prominent explanatory factory for human brain development. Furthermore, understanding the brains of related primates and their relation to human brains will help scientists develop new models for brain pathways and understand the kinds of questions that they will be able to answer with such knowledge in the future.

Neuroscientists today continue to work hard toward developing human brain models. Current studies are focusing on developing accurate organoids – three-dimensional tissue models of stem cells developed to mimic organs in structure and function. Velmeshev’s group of researchers worked towards profiling different cortical (outer layers of the upper brain) areas and related areas in fetuses to track developments across human births. Kim’s group of researchers investigated single-cell transcriptomes of the thalamus (the processor of sensory data) during its development but was missing an investigation of the thalamus cellular compositions. The work of these scientists contributes to the idea of molecular mechanisms as the driver of cellular diversity in the brain, but also calls for more innovation in external biological investigations to better model the brain and further study its composition. In doing so, neuroscientists will come even closer to understanding one of the most complex systems in the human body and develop more answers for current-day neurological problems.

Bibliography

Weninger, Alyssa, and Paola Arlotta. “A Family Portrait of Human Brain Cells.” Science, vol. 382, no. 6667, Oct. 2023, pp. 168–69, https://doi.org/10.1126/science.adk4857.