A New Approach to Predicting Risk of Alzheimer’s Disease


An individual’s risk for Alzheimer’s disease is affected by a variety of genetic and environmental factors. While the causes of early-onset Alzheimer’s are well understood, the genetic factors underlying late-onset Alzheimer’s disease (LOAD), which makes up 95% of total cases, are less clear. The APOE4 allele is considered the major risk factor for this form of Alzheimer’s, as it can increase your risk by 2-3 times if you have one copy of the allele or up to 15 times if you have two copies. APOE4 does not guarantee that an individual will develop LOAD, and researchers have been searching for other genes that may be involved. (For more background see The Genetics of Alzheimer’s Disease).

Genome-wide association studies, which systematically analyze the 0.1% of DNA sequence that varies between individuals, have linked at least 21 other genes to an increased risk of LOAD. Individually, each of these genes has only a small influence in comparison to APOE4, often increasing one’s risk by only a few percentage points. However, when many of these small genetic risk factors are combined, they can greatly affect an individual’s chances of developing LOAD.

Overall, studies suggest that approximately 33% of an individual’s risk for developing LOAD is attributable to genetics, with the rest being due to lifestyle choices and environmental factors. Of this, APOE and the 21 already-identified genes account for less than 25% of the genetic risk, suggesting that the majority of genetic risk factors for Alzheimer’s disease remain unknown.

New Results

In a recent study published in the journal Neurology, a group of researchers from the Alzheimer’s Disease Neuroimaging Initiative searched for other genes, outside of the 21 already identified, that could also act as slight risk factors for Alzheimer’s. They used data collected from the International Genomics of Alzheimer’s Project to compute polygenetic risk scores, or PGRS, for both young and elderly adults who did not have dementia. Each person’s PGRS was calculated using his or her unique combination of small genetic risk factors (including many that were not statistically significant in genome-wide association studies) in order to estimate the genetic risk for LOAD. The researchers then analyzed whether PGRS were associated with biological markers of preclinical Alzheimer’s disease.

In elderly subjects who did not have dementia, high PGRS was associated with poorer memory, smaller volume of the hippocampus (the part of the brain that helps us form new memories), and increased levels of toxic beta-amyloid in the brain. High PGRS in these individuals also correlated with an increased rate of cognitive decline and a greater probability of later being diagnosed with Alzheimer’s disease. The researchers also computed PGRS for younger subjects under the age of 35. They found that a high PGRS was associated with reduced hippocampal volume, similarly to the older subjects.

Together, these results suggest that more genes besides the currently-identified 21 may need to be considered when evaluating an individual’s risk for LOAD. The researchers plan to repeat this study using a larger sample size to verify the results. Future studies also will track younger subjects to see if PGRS can predict their risk for Alzheimer’s as they age, and compare these results to less comprehensive systems of genetic prediction. The hope is that by refining PGRS, we may one day be able to develop better genetic tests for young people that yield more accurate predictions of future Alzheimer’s risk.


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5 thoughts on “A New Approach to Predicting Risk of Alzheimer’s Disease

  1. Pingback: AlzScience’s Five Most Popular Articles of 2016 | AlzScience

  2. Pingback: The Genetics of Alzheimer’s Disease | AlzScience

  3. kdn026

    This is the nice overview. I would like to point out however that the “recent study” cited has a relatively small sample size and small effect sizes (listed as study limitations in this article).
    Another important factor relating to Alzheimer’s disease is that the regions within the default network (DMN) that show high resting metabolism are those affected in this disease (see: http://www.ncbi.nlm.nih.gov/pubmed/18400922). In other words, the activity within the DMN appears to facilitate disease processes for Alzheimer’s.
    How does the activity of DMN change?
    When engaged in goal-directed active cognitive tasks, the activity of the DMN is less. On the other hand, during undirected thinking (for example when one is anxious and proliferating thoughts, etc.), the DMN activity is elevated. Considering that elevated activity of DMN is significantly associated with amyloid plaque deposition (http://www.ncbi.nlm.nih.gov/pubmed/21532579), engaging in goal-directed active cognitive tasks can potentially decrease the occurrence of Alzheimer’s. Supporting this, one large longitudinal study that followed participants for 21 years found that individuals with high education (i.e., people often engaged in active cognitive tasks) developed significantly less dementia, and also that the presence of ApoE4 allele did not modify this association (see: http://www.ncbi.nlm.nih.gov/pubmed/17909157). The association of high education and less Alzheimer’s is supported by other studies as well (see: http://www.ncbi.nlm.nih.gov/pubmed/19585947)
    Studies have also shown that mindfulness and meditation practices are significantly negatively correlated with rumination, diminish activity in the DMN, and also results in greater functional connectivity within the default-mode network (see: http://www.ncbi.nlm.nih.gov/pubmed/22114193 ; http://www.ncbi.nlm.nih.gov/pubmed/22446298 and http://www.ncbi.nlm.nih.gov/pubmed/21034792
    So, although finding the genes associated with Alzheimer’s can have various applications, considering that even individuals who do not have these genes can get Alzheimer’s, it might be good to investigate the protective role (and perhaps even a treatment role) meditation/mindfulness practises can play for Alzheimer’s. A recent study also showed that meditation leads to reduced activity in the DMN even beyond being engaged in an active task. (http://www.ncbi.nlm.nih.gov/pubmed/25904238 ).
    Perhaps one could investigate the threshold level of DMN activity that leads to plaque formation, and if the DMN activity of uneducated individuals is higher (and whether the activity can be reduced), etc., and if this prevents plaque formation.
    In summary, the influence of genes can happen in the opposite direction (through epigenetic mechanisms) – brain activity patterns can directly modulate the molecular cascades that are relevant to disease.

    Liked by 1 person

    1. AlzScience Post author

      Thank you for this great comment! I am very interested in learning more about the DMN and its role in disease processes. The possibility of DMN activity as an alternative to the cognitive reserve theory is particularly interesting, I wonder if any papers have been written on that subject.
      I have an article in the works covering the effects of stress and relaxation on the aging brain. I will be sure to look more closely at the links you provided and include some information about the DMN, mindfulness, and education in this article. Thanks again for the comment!

      Liked by 1 person

      1. kdn026

        Glad you liked it. I have an interest in this area, although I do not work in the area. So, I just thought of passing along the ideas (notes/bits and pieces I had taken down sometime back), so that someone could make use of it!
        I don’t know much about ‘cognitive reserve theory.’ However, when I read your ‘overview’ link mentioning Dr. Alzheimer, ect., and saw the words “when mind was seen as separate from the physical body,” I thought of passing along the following link that describes an ancient model of the mind. It explains two levels of analyses – if you are interested, you can read it. Here’s the link: http://sgo.sagepub.com/content/5/2/2158244015583860
        Best of luck with your projects!

        Liked by 1 person

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