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2. Personalized Biometrics of Physical Pain Agree with Psychophysics by Participants with Sensory over Responsivity.

Author

Ryu, Jihye, Bar-Shalita, Tami, Granovsky, Yelena, Weissman-Fogel, Irit, and Torres, Elizabeth

Subjects
EEG, micro-movements spikes, pain biometrics, personalized pain, sensory over responsivity, standardized scale, stochastic analyses
Abstract

The study of pain requires a balance between subjective methods that rely on self-reports and complementary objective biometrics that ascertain physical signals associated with subjective accounts. There are at present no objective scales that enable the personalized assessment of pain, as most work involving electrophysiology rely on summary statistics from a priori theoretical population assumptions. Along these lines, recent work has provided evidence of differences in pain sensations between participants with Sensory Over Responsivity (SOR) and controls. While these analyses are useful to understand pain across groups, there remains a need to quantify individual differences more precisely in a personalized manner. Here we offer new methods to characterize pain using the moment-by-moment standardized fluctuations in EEG brain activity centrally reflecting the persons experiencing temperature-based stimulation at the periphery. This type of gross data is often disregarded as noise, yet here we show its utility to characterize the lingering sensation of discomfort raising to the level of pain, individually, for each participant. We show fundamental differences between the SOR group in relation to controls and provide an objective account of pain congruent with the subjective self-reported data. This offers the potential to build a standardized scale useful to profile pain levels in a personalized manner across the general population.

Published
2021

5. What is associated with painful polyneuropathy? A cross-sectional analysis of symptoms and signs in patients with painful and painless polyneuropathy.

Author

Gierthmühlen, Janne, Attal, Nadine, Baskozos, Georgios, Bennedsgaard, Kristine, Bennett, David L., Bouhassira, Didier, Crombez, Geert, Finnerup, Nanna B., Granovsky, Yelena, Jensen, Troels Staehelin, John, Jishi, Kennes, Lieven Nils, Laycock, Helen, Pascal, Mathilde M.V., Rice, Andrew S.C., Shafran-Topaz, Leah, Themistocleous, Andreas C., Yarnitsky, David, and Baron, Ralf

Published
2024
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27. Electroencephalography functional connectivity—A biomarker for painful polyneuropathy

Author

Topaz, Leah Shafran, primary, Frid, Alex, additional, Granovsky, Yelena, additional, Zubidat, Rabab, additional, Crystal, Shoshana, additional, Buxbaum, Chen, additional, Bosak, Noam, additional, Hadad, Rafi, additional, Domany, Erel, additional, Alon, Tayir, additional, Meir Yalon, Lian, additional, Shor, Merav, additional, Khamaisi, Mogher, additional, Hochberg, Irit, additional, Yarovinsky, Nataliya, additional, Volkovich, Zeev, additional, Bennett, David L., additional, and Yarnitsky, David, additional

Published
2022
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28. Brain Connectivity Predicts Chronic Pain in Acute Mild Traumatic Brain Injury

Author

Bosak, Noam, primary, Branco, Paulo, additional, Kuperman, Pora, additional, Buxbaum, Chen, additional, Cohen, Ruth Manor, additional, Fadel, Shiri, additional, Zubeidat, Rabab, additional, Hadad, Rafi, additional, Lawen, Amir, additional, Saadon‐Grosman, Noam, additional, Sterling, Michele, additional, Granovsky, Yelena, additional, Apkarian, Apkar Vania, additional, Yarnitsky, David, additional, and Kahn, Itamar, additional

Published
2022
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30. 'When I’m in Pain, Everything Is Overwhelming': Implications of Pain in Adults With Autism on Their Daily Living and Participation

Author

Kalingel-Levi, Merry, Schreuer, Naomi, Granovsky, Yelena, Bar-Shalita, Tami, Weissman-Fogel, Irit, Hoffman, Tseela, and Gal, Eynat

Subjects
General Psychology
Abstract

Pain sensation in autism spectrum disorder (ASD) has been a growing research field in the last two decades. Existing pain research has focused on pain sensitivity, suggesting either hyposensitivity or hypersensitivity to pain in individuals with ASD. However, research about other aspects of pain experience is scarce. Moreover, most pain-related research in ASD focused on quantitative measures, such as neuroimaging or parental reports. Instead, this paper aimed to illuminate the various aspects of pain experience as perceived by adults with ASD. Its descriptive qualitative research design incorporated semi-structured interviews and deductive thematic analysis. This phenomenological approach captured the subjective pain experience through the lens of people with ASD. Four primary themes emerged from the data: (a) physical pain experience, including the sequence of pain sensitivity, pain awareness, pain-related emotional aspects, and pain communication; (b) direct and indirect coping strategies; (c) function and participation outcomes; and (d) suggestions for Healthcare Providers. The findings echo the crucial role of pain awareness and communication in the pain experience of people with ASD. These two factors have been reported as profoundly influencing coping strategies, function, and participation. The results emphasize the need to expand the exploration of pain in this population, calling for greater understanding, and listening to this population’s unique pain profiles and experiences to promote better-suited evaluation, diagnosis, and intervention in pain conditions.

Published
2022
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36. Prospective Blood Transcriptomics Study in a Motor Vehicle Collision Cohort Identified a Protective Function of the SAMD15Gene Against Chronic Pain

Author

Parisien, Marc, Buxbaum, Chen, Granovsky, Yelena, Yarnitsky, David, and Diatchenko, Luda

Abstract

Traumatic brain injuries following motor vehicle collisions (MVCs) are ubiquitous. Surprisingly, there are no correlates between concussion impact force and long-term pain outcomes. To study the molecular underpinnings of chronic pain after MVC, we assembled a prospective cohort of 36 subjects that experienced MVC and suffered documented mild traumatic brain injuries. For each participant, a first blood sample was drawn within 72 hours of the collision, then a second one at the 6-month mark. Pain was also assessed at the second blood draw to determine if pain became chronic or resolved. Blood samples enabled transcriptomics analyses for immune cells. At the transcriptome-wide level, we found that Sterile Alpha Motif Domain Containing 15 (SAMD15) mRNA was significantly upregulated with time in subjects who resolved their pain whereas unregulated in those with persistent pain. Using several large publicly available datasets, such as the UK Biobank and the GTeX portal, we then linked elevated SAMD15gene expression, elevated neutrophils cell counts, and decreased risk for chronic pain to increased dosage of the T allele at SNP rs4903580, situated within SAMD15’s gene locus. The causality between the components of our model was established and supported by Mendelian randomization. Overall, our results support the role of SAMD15as a potential gene effector for neutrophil-dependent chronic pain development.

Published
2023
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39. Additional file 1 of Classification of painful or painless diabetic peripheral neuropathy and identification of the most powerful predictors using machine learning models in large cross-sectional cohorts

Author

Baskozos, Georgios, Themistocleous, Andreas C., Hebert, Harry L., Pascal, Mathilde M. V., John, Jishi, Callaghan, Brian C., Laycock, Helen, Granovsky, Yelena, Crombez, Geert, Yarnitsky, David, Rice, Andrew S. C., Smith, Blair H., and Bennett, David L. H.

Subjects
Data_FILES
Abstract

Additional file 1. Supplemental figures and tables.

Published
2022
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48. Electroencephalography functional connectivity—A biomarker for painful polyneuropathy.

Author

Topaz, Leah Shafran, Frid, Alex, Granovsky, Yelena, Zubidat, Rabab, Crystal, Shoshana, Buxbaum, Chen, Bosak, Noam, Hadad, Rafi, Domany, Erel, Alon, Tayir, Meir Yalon, Lian, Shor, Merav, Khamaisi, Mogher, Hochberg, Irit, Yarovinsky, Nataliya, Volkovich, Zeev, Bennett, David L., and Yarnitsky, David

Subjects
FUNCTIONAL connectivity, RECEIVER operating characteristic curves, ELECTROENCEPHALOGRAPHY, POLYNEUROPATHIES
Abstract

Background and purpose: Advanced analysis of electroencephalography (EEG) data has become an essential tool in brain research. Based solely on resting state EEG signals, a data‐driven, predictive and explanatory approach is presented to discriminate painful from non‐painful diabetic polyneuropathy (DPN) patients. Methods: Three minutes long, 64 electrode resting‐state recordings were obtained from 180 DPN patients. The analysis consisted of a mixture of traditional, explanatory and machine learning analyses. First, the 10 functional bivariate connections best differentiating between painful and non‐painful patients in each EEG band were identified and the relevant receiver operating characteristic was calculated. Later, those connections were correlated with selected clinical parameters. Results: Predictive analysis indicated that theta and beta bands contain most of the information required for discrimination between painful and non‐painful polyneuropathy patients, with area under the receiver operating characteristic curve values of 0.93 for theta and 0.89 for beta bands. Assessing statistical differences between the average magnitude of functional connectivity values and clinical pain parameters revealed that painful DPN patients had significantly higher cortical functional connectivity than non‐painful ones (p = 0.008 for theta and p = 0.001 for alpha bands). Moreover, intra‐band analysis of individual significant functional connections revealed a positive correlation with average reported pain in the previous 3 months in all frequency bands. Conclusions: Resting state EEG functional connectivity can serve as a highly accurate biomarker for the presence or absence of pain in DPN patients. This highlights the importance of the brain, in addition to the peripheral lesions, in generating the clinical pain picture. This tool can probably be extended to other pain syndromes. [ABSTRACT FROM AUTHOR]

Published
2023
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