Gene Variants Predicting Stroke Recovery Outcomes

Post by Natalia Ladyka-Wojcik

The takeaway

For stroke survivors, factors such as age, baseline health, and stroke severity have been highlighted as important when predicting recovery outcomes, but a key factor – genetics – has received much less attention to date. Yet, there may be specific gene variants that can help to predict the cognitive and emotional trajectories of recovery for stroke survivors, providing instrumental insights into future therapeutic approaches. 

What's the science?

The outcomes of stroke are long-term, with patients often experiencing a range of cognitive and emotional changes that impact quality of life. A wealth of previous research has investigated genetic factors associated with stroke risk and severity, but there has been considerably less exploration into genetic associations with stroke recovery. Although treatments for stroke patients are becoming more targeted, including the promotion of neural repair, we still understand very little in terms of how genetics may interact with the success of these treatments. Importantly, in order to link specific genetic variants to post-stroke outcomes, researchers also need to identify ways of measuring these outcomes beyond a single index of global disability. This week in Stroke, Cramer and colleagues analyzed three candidate gene variants to determine their potential associations with a series of key motor and functional measures in stroke recovery.

How did they do it?

The authors analyzed genetic data and recovery outcomes from a large-scale, prospective cohort study called STRONG (Stroke, sTress, RehabilitatiON, and Genetics) including more than 750 adult patients with stroke across 28 US stroke centers. Specifically, they examined patients for a period of 1-year post-stroke, to identify genetic variants associated with motor and functional outcomes, as well as stress-related outcomes. At the initial timepoint of the study, the authors collected saliva samples for DNA genotyping analysis. This DNA analysis considered the genetic ancestry of patients, and candidate gene variants were selected based on prior research linking them to specific motor, functional, or stress-related outcomes. For motor and functional outcomes, they selected ApoE ε4 carrier status and brain-derived neurotrophic factor (BDNF) polymorphism, which have both been tied to reduced neural repair in past research. They also selected a dopamine polygenic score (i.e., a characteristic influenced by two or more genes) which models the neurotransmission of dopamine in the human brain. Together, these selected gene variants were analyzed in terms of their predictive relationship to longitudinal outcomes in grip strength, global functional daily living, depression, and cognitive status. Finally, for stress-related outcomes, the authors investigated seven additional gene variants in relation to post-traumatic stress disorder (PTSD) and depression across several timepoints of the longitudinal study. To bolster their results, the authors considered stroke subtypes (which can vary in their symptoms and underlying causes) and also conducted a replication analysis to compare their results to two other previously published, large-scale cohort studies. 

What did they find?

For functional outcomes, the authors found that BDNF polymorphism was associated with poorer cognition in stroke patients, as well as reduced grip strength when considering the time from stroke onset to study enrollment. APOE status and dopamine polygenic scores were not found to be related to their measured outcomes, further highlighting the precision with which targeted therapies need to consider whether or not a gene factors into stroke recovery. For stress-related outcomes, the authors identified two of the seven gene variants contributed to poorer outcomes in terms of PTSD and depression, while another one contributed to better outcomes in terms of PTSD and depression. Importantly, stress-related gene variants also broadly varied with the level of post-stroke stress experienced by patients. These genetic associations were found to be important regardless of stroke subtype and most critically, were only evident at 1-year post-stroke but not earlier. As the authors point out, this is why it is important to consider genetic variants not just at the initial stages of recovery but rather in the long term. Finally, their findings successfully replicated results from another large-scale genetic study of post-stroke outcomes, with a genetic variant involved in the expression of a protein associated with brain plasticity predicting global post-stroke outcomes in both studies. 

What's the impact?

This study found that comprehensive genetic phenotyping after stroke holds key insights into predicting long-term outcomes for patients. Notably, this study provides a deeper understanding of post-stroke recovery than mere global outcomes scores, by measuring specific functional, motor, and stress-related outcomes and also by considering how much stress the patients reported experiencing. Altogether, these insights could help develop future tailored therapies for patients and potentially identify patients who may need more support to achieve better post-stroke recovery based on genetic risk.  

Access the original scientific publication here.

What is Cognitive Reserve, Actually?

Post by Anastasia Sares

The takeaway

Cognitive function tends to decline as we age normally or when we are faced with diseases like Alzheimer’s. Cognitive reserve is a form of resilience that allows people to maintain good cognitive functioning—or at least to slow cognitive decline—even as aging and illness progress.

The idea of cognitive reserve

Studies of aging have noted large individual differences in rates of cognitive decline, whether it be in healthy aging or dementias like Alzheimer’s. Cognitive reserve is a concept scientists have proposed to account for this variability. Things like education and occupational complexity may contribute to cognitive reserve, with one study finding that high cognitive reserve reduced the risk of dementia by around 50%. However, to move the research forward, researchers need to first agree on how to define cognitive reserve. Over the past several years there has been an effort to do just that. In this article, we will present the definitions of Stern and colleagues, who are leaders in this field.

Three necessary elements

To show evidence of cognitive reserve at work, you need three elements. First, you need some kind of outcome measure: for example, the presence or absence of an Alzheimer’s diagnosis, or a score on a cognitive test. Second, you need some kind of risk factor. Often, this is brain-related, like the number of accumulated protein plaques or the integrity of white matter in the brain. But the risk factor doesn’t have to be from the brain: for example, a person’s age is, by itself, a risk factor for Alzheimer’s. These first two elements (the outcome and the risk factor) are assumed to have a causal relationship. For example, more plaques in the brain should lead to a greater likelihood of an Alzheimer’s diagnosis.

The third element is where it gets interesting. This is a protective factor that we think might moderate the relationship between the first two elements. For example, perhaps people who have more education can maintain their cognitive functioning for longer and delay their Alzheimer’s diagnosis compared to people with the same number of plaques in their brain but less education. Or perhaps people who are more socially active score higher on cognitive tests for their age than people who are less socially active.

Related concepts

There are a couple of concepts related to cognitive reserve, but slightly different. To differentiate these terms, a hardware/software analogy is sometimes used. Cognitive reserve is the “software” that allows for maintained function despite deteriorating “hardware,” while brain reserve is the pre-existing advantages in the biological “hardware” itself. For example, in a study looking at white matter integrity changes with age, you might find that some individuals just have better white matter integrity, to begin with, before any aging or disease. This means it will take more damage to the white matter to start affecting cognition. The hardware/software analogy is imperfect, and the line between cognitive reserve and brain reserve is fuzzy. After all, cognitive processes are also based in biology.

Brain maintenance, on the other hand, involves stalling the damage to the brain’s “hardware” so that the decline is not so sharp. For example, some people may accumulate white matter damage at a slower rate than others.

All of these elements are most informative when measured longitudinally (using multiple measurements over time), so long-term changes can be tracked. This would allow researchers to pick apart differences between cognitive reserve, brain reserve, and brain maintenance, where a single snapshot might not.

What’s the impact?

Cognitive resilience in the face of aging is increasingly important as populations all over the world grow older on average. Having a consensus on the definition of cognitive reserve allows scientists to move forward studying it, potentially identifying ways to build it up and increase quality of life in old age.

References +

Cabeza, R., Albert, M., Belleville, S., Craik, F. I. M., Duarte, A., Grady, C. L., Lindenberger, U., Nyberg, L., Park, D. C., Reuter-Lorenz, P. A., Rugg, M. D., Steffener, J., & Rajah, M. N. (2018). Maintenance, reserve and compensation: The cognitive neuroscience of healthy ageing. Nature Reviews Neuroscience, 19(11), 701–710. https://doi.org/10.1038/s41583-018-0068-2

Stern, Y., Albert, M., Barnes, C. A., Cabeza, R., Pascual-Leone, A., & Rapp, P. R. (2023). A framework for concepts of reserve and resilience in aging. Neurobiology of Aging, 124, 100–103. https://doi.org/10.1016/j.neurobiolaging.2022.10.015

Stern, Y., Arenaza‐Urquijo, E. M., Bartrés‐Faz, D., Belleville, S., Cantilon, M., Chetelat, G., Ewers, M., Franzmeier, N., Kempermann, G., Kremen, W. S., Okonkwo, O., Scarmeas, N., Soldan, A., Udeh‐Momoh, C., Valenzuela, M., Vemuri, P., Vuoksimaa, E., & and the Reserve, Resilience and Protective Factors PIA Empirical Definitions and Conceptual Frameworks Workgroup. (2020). Whitepaper: Defining and investigating cognitive reserve, brain reserve, and brain maintenance. Alzheimer’s & Dementia, 16(9), 1305–1311. https://doi.org/10.1016/j.jalz.2018.07.219

Nelson, M. E., Jester, D. J., Petkus, A. J., & Andel, R. (2021). Cognitive Reserve, Alzheimer’s Neuropathology, and Risk of Dementia: A Systematic Review and Meta-Analysis. Neuropsychology Review, 31(2), 233–250. https://doi.org/10.1007/s11065-021-09478-4

Contact Sports Associated with Brain Changes and Symptoms of Parkinson’s Disease

Post by Lani Cupo

The takeaway

Repeated head trauma that can occur in contact sports where concussions are common is associated with characteristics of Parkinson’s disease including cellular neuropathology.

What's the science?

Repetitive head trauma (RHT) is associated with parkinsonism (a term referring generally to symptoms such as slowed movements, rigidity, and tremors, most commonly associated with neurodegenerative disorders). Parkinson’s disease is characterized by certain cellular changes confirmed by a pathologist after death, including the presence of Lewy bodies. Past work by Adams et al. showed an increased frequency of neocortical Lewy bodies in association with years of contact sports play. This week in JAMA Neurology, Adams and colleagues studied the brains of male donors who had suffered RHT to find associations with parkinsonism and cellular neuropathologies. 

How did they do it?

The authors assessed samples from 481 male brain donors who had a history of playing contact sports and had received a diagnosis of chronic traumatic encephalopathy (CTE, associated with RHT). Their health history was assessed through a combination of techniques, including interviews with close family members and friends who had known them in life and a review of their medical charts. The substantia nigra (SN) specifically was assessed for neuropathological changes. This region is largely responsible for controlling movement, and pathologies of the SN—such as proteinopathy and cell death—are associated with Parkinson’s. The authors examined several features in the brain tissue. First, they looked for neurofibrillary tangles, abnormal accumulations of the protein tau, the hallmark and diagnostic protein of CTE. Second, they looked for Lewy bodies, deposits of the protein alpha-synuclein and the pathology most commonly associated with Parkinson's disease. Third, they examined neuronal loss, which is thought to be a central contributor to symptoms of movement dysfunction. All three were assessed semi-quantitatively and categorized based on if they were present and how severe they were. The authors used a series of linear models to assess the relationships between the neuropathologies and parkinsonism in CTE. They also used structural equation modelling in the subset of participants who had played American football to examine relationships between age, years playing football, Lewy bodies, neurofibrillary tangles, and arteriolosclerosis on nigral neuronal loss and, ultimately, parkinsonism in CTE. 

What did they find?

Almost 25% (119 people) of the examined sample had evidence of parkinsonism during life. They tended to be older at the time of death, were more likely to have dementia and probable REM sleep behavior disorder, and had higher rates of visual hallucinations than those without parkinsonism. It’s possible that members of the other group would have developed symptoms if they had lived longer. Participants with parkinsonism were also more likely to have played American football although there was no difference in the number of years spent playing sports. Finally, they tended to have more Lewy bodies than participants without parkinsonism; however, the majority of participants with parkinsonism did not have nigral Lewy bodies, indicating other pathology was underlying their symptoms. 

After correcting for age, the authors also found that 8-10 years of contact sport play was associated with a 50% increased risk of pathology in the SN. Lewy bodies, but not neurofibrillary tangles, were associated with parkinsonism, potentially highlighting the specificity of that pathology. Interestingly, the structural equation modelling revealed a small but significant association with RHT and parkinsonism through changes in the SN (neurofibrillary tangles and neuronal loss), highlighting that all three of these metrics may be important to understanding the relationship between head trauma and parkinsonism. Of course, studies that use postmortem tissue can only include a single time point, so it is impossible to track the progression of symptoms and neuropathology over time with these metrics. 

What's the impact?

This study found associations between RHT from contact sports, neuropathology, and parkinsonism symptoms in a group of male participants with CTE. It also highlights how cellular changes beyond Lewy bodies in the SN contribute to parkinsonism symptoms. 

Access the original scientific publication here