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Schnitzer, T. J.

Publications and source records attributed to Schnitzer, T. J..

3 recordsLinked to original sources

Identification of traits and functional connectivity-based neuropsychotypes of chronic pain

Psychological and personality factors, socioeconomic status, and brain properties all contribute to chronic pain but have essentially been studied independently. Here, we administered a broad battery of questionnaires to patients with chronic back pain (CBP). Clustering and network analyses revealed four orthogonal dimensions accounting for 60% of the variance, and defining chronic pain traits. Two of these traits - Pain-trait and Emote-trait - were related to back pain characteristics and could be predicted from distinct distributed functional networks in a cross-validation procedure, identifying neurotraits. These neurotraits were relatively stable in time and segregated CBP patients into subtypes showing distinct traits, pain affect, pain qualities, and socioeconomic status (neuropsychotypes). The results unravel the trait space of chronic pain leading to reliable categorization of patients into distinct types. The approach provides metrics aiming at unifying the psychology and the neurophysiology of chronic pain across diverse clinical conditions, and promotes prognostics and individualized therapeutics.

neuroscience

Do mechanical strain magnitude and rate drive bone adaptation in adult women? A 12-month prospective study.

Although there is strong evidence that certain activities can increase bone density and structure in some individuals, it is unclear what specific mechanical factors govern the response. This is important because understanding the effect of mechanical signals on bone could contribute to more effective osteoporosis prevention methods and efficient clinical trial design. The degree to which strain rate and magnitude govern bone adaptation in humans has never been prospectively tested. Here, we studied the effects of a voluntary upper extremity compressive loading task in healthy adult women during a twelve month prospective period. One hundred and two women age 21-40 participated in one of two experiments. (1): low (n=21) and high (n=24) strain magnitude. (2): low (n=21) and high (n=20) strain rate. Control: (n=16): no intervention. Strains were assigned using subject-specific finite element models. Load cycles were recorded digitally. The primary outcome was change in ultradistal integral bone mineral content (iBMC), assessed with QCT. Interim timepoints and secondary outcomes were assessed with high resolution pQCT (HRpQCT). Sixty-six subjects completed the intervention, and interim data were analyzed for 77 subjects. Both the low and high strain rate groups had significant 12-month increases to ultradistal iBMC (change in control: -1.3{+/-}2.7%, low strain rate: 2.7{+/-}2.1%, high strain rate: 3.4{+/-}2.2%), total iBMC, and other measures. \"Loading dose\" was positively related to 12-month change in ultradistal iBMC, and interim changes to total BMD, cortical thickness and inner trabecular BMD. Subjects who gained the most bone completed, on average, 130 loading bouts of (mean strain) 550 {varepsilon} at 1805 {varepsilon}/s. Those with the greatest gains had the highest loading dose. We conclude that signals related to strain magnitude, rate, and number of loading bouts contribute to bone adaptation in healthy adult women, but only explain a small amount of variance in bone changes.

physiology

Brain and psychological determinants of placebo pill response in chronic pain patients

Placebo response is universally observed in randomized controlled trials (RCTs), yet these effects are commonly dismissed as consequences of uncontrollable confounds. In this prospective neuroimaging-based RCT performed in chronic back pain patients, we demonstrate that the intensity, but not quality, of pain is diminished with placebo pill ingestion. The response to placebo pills depended on brain: subcortical limbic volume asymmetry, sensorimotor cortical thickness, and functional coupling of the dorsolateral prefrontal cortex (DLPFC) with the periaqueductal grey (PAG), the rostral anterior cingulate cortex (rACC), and the precentral gyrus (PreCG); and psychological factors. All features were present before exposure to the pill; most remained stable across treatment and washout periods, although specific functional coupling between DLPFC and PAG dissipated with repeated exposure. These brain properties and specific psychological factors, such as interoceptive awareness and openness, were also predictive of the magnitude of response (continuous variable). We used machine learning in a fully cross-validated procedure and demonstrated that psychological factors were sufficient for classifying and predicting response magnitude; and response magnitude could also be predicted from a functional network (nodes mainly located in the limbic community, the DLPFC, the orbitofrontal cortex, and the temporo-parietal junction); the combined model explained 36% of the variance. Together, our results demonstrate that placebo pill analgesia observed in clinical trials depends on a combination of brain properties and specific psychological factors.

neuroscience