Chronic pain is associated with a brain aging biomarker in community-dwelling older adults: PAIN – PAIN: May 2019 – Research Paper
This “finding” doesn’t surprise me one bit; my mental faculties have long been deteriorating faster than others in my cohort.
Chronic pain is associated with brain atrophy with limited evidence on its impact in the older adult’s brain.
We aimed to determine the associations between chronic pain and a brain aging biomarker in persons aged 60 to 83 years old
Individuals with chronic pain (n = 33) had “older” brains for their age compared with those without.
Greater average worst pain intensity was associated with an “older” brain
Among participants with chronic pain, those who reported having pain treatments during the past 3 months had “younger” brains compared with those who did not.
An “older” brain was significantly associated with
- decreased vibratory and thermal detection,
- deficient endogenous pain inhibition
- lower positive affect,
- a less agreeable and less emotionally stable personality.
That’s evidence of something I’ve long suspected: chronic pain eventually results in brain damage, the kind that makes us distracted, irritable, depressed, and anxious – at least that what seems to have happened to me.
Our findings suggest that chronic pain is associated with added “age-like” brain atrophy in relatively healthy, community-dwelling older individuals
A brain aging biomarker may help identify people with chronic pain at a greater risk of functional decline and poorer health outcomes.
These age-like effects of chronic pain are in addition to “normal” aging, which might explain why I feel like I’m aging in fast-forward.
More than 1.5 billion people worldwide experience chronic pain, and more Americans are affected by chronic pain than by diabetes, heart disease, and cancer combined.
In particular, epidemiological evidence suggests an age-related increase in pain prevalence with back and knee pain as the most commonly reported pain in those older than 65 years.
Chronic pain in older individuals is a growing public health problem because effective treatments are lacking, and pain detrimentally impacts physical and cognitive function, ultimately decreasing quality of life and overall well-being.
Pain is associated with both direct (ie, the experience of pain) and indirect effects on the brain
Neuroimaging studies have established the prominent role of the brain in pain perception and modulation and in the integration of sensory, motor, emotional, and cognitive components that give rise to the complex, individualized pain experience.
Although most chronic pain conditions are associated with changes to brain structure and function, these structures are similarly impacted by normal and pathological chronological aging processes.
Indeed, chronological aging has been associated with both global and spatially localized changes to brain structure and function, which may be very similar to brain changes reported in chronic pain states.
In addition, several preliminary investigations in older adults with and without low back pain (n = 8/group) suggest that chronic pain may negatively impact the brain above and beyond age-related effects (ie, accelerated brain aging)
Using machine-learning analysis of structural neuroimaging data, chronological age can be accurately predicted in healthy individuals.
Using this method, older predicted brain age (as compared with chronological age) has been reported in
- Alzheimer disease,
- mild cognitive impairment,
- schizophrenia, and
- after traumatic brain injury.
Furthermore, recent work found that having an older predicted brain age was associated with
- weaker grip strength,
- poorer lung function,
- slower walking speed,
- lower fluid intelligence,
- higher allostatic load, and
- increased overall mortality risk measured prospectively
Consistent with previous work, we estimated a brain-predicted age difference (brain-PAD, calculated as brain-predicted age minus chronological age) using structural neuroimaging (T1-weighted magnetic resonance imaging [MRI]) processed through an established analysis pipeline
The primary hypothesis of the present study was that older adults reporting chronic pain will have a greater brain-PAD (ie, older brain, accelerated brain aging) compared with older adults who did not report chronic pain during the past 3 months.
A clinically relevant, neuroimaging-derived aging biomarker, previously predictive of greater mortality risk during aging, is similarly associated with the complex experience of pain in older individuals.
2.3.5. Conditioned pain modulation procedure
A subset of participants completed a conditioned pain modulation (CPM) paradigm as recommended by Yarnitsky et al.
For the test stimulus, heat was applied to the thenar eminence increasing at a rate of 1°C/second and was discontinued by the subject at pain-40 (pain level of 40/100).
- The temperature required to produce pain-40 was recorded
- A pain inhibition score was calculated
2.5. Brain-predicted age biomarker
The brain aging biomarker used here was derived using a previously established “brain-age” framework.
This involved training a machine-learning model to accurately predict chronological age from neuroimaging data in a training cohort composed of 2646 healthy individuals
So brain age is being determined solely by physical brain imaging qualities, avoiding any reliance on patients’ subjective experiences.
This is significant because almost all aspects of pain can only be subjectively self-reported, while the computations used to determine brain age only involve objective physical brain markers.
The individual participants’ chronological age was then subtracted from this brain-predicted age value to generate a brain-predicted age difference (brain-PAD) score, which was used for further analysis.
Forty-seven older adults ranging in age from 60 to 83 years (mean age = 70.9 ± 6.0; 74.5% female) participated in our study.
3.2. Brain-predicted age difference and presence of pain
There was a significant difference in brain-PAD between older adults who reported chronic pain (1.5 ± 1.6) vs those who did not (−4.0 ± 1.9; F [1,41] = 4.9; P = 0.033; partial eta squared = 0.11, ANCOVA; Fig. 3), which was our main proposed study hypothesis.
3.3. Brain-predicted age difference and worst pain characteristicsWorst pain location within the participants who experienced pain (n = 33) is depicted in Figure 4.
Brain-PAD significantly correlated with average intensity of the worst pain (r = 0.464; P = 0.011; corrected P = 0.033).
3.4. Brain-predicted age difference and psychological function
Spearman correlations were used to determine associations between brain-PAD and psychological variables
No significant associations between brain-PAD and the psychological variables emerged across all participants
3.5. Brain-predicted age difference and quantitative sensory testingGreater vibratory detection thresholds were significantly associated with greater brain-PAD (ie, older brain)
Similarly, greater thermal detection thresholds were also significantly associated with greater brain-PAD (ie, older brain)
3.6. Brain-predicted age difference and conditioned pain modulation
The paper continues with many more categories: