Faculty Bibliography

The corticostriatal circuit plays an important role in the regulation of reward- and aversion-types of behaviors. Specifically, the projection from the prelimbic cortex (PL) to the nucleus accumbens (NAc) has been shown to regulate sensory and affective aspects of pain in a number of rodent models. Previous studies have shown that enhancement of glutamate signaling through the NAc by AMPAkines, a class of agents that specifically potentiate the function of α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) receptors, reduces acute and persistent pain. However, it is not known whether postsynaptic potentiation of the NAc with these agents can achieve the full anti-nociceptive effects of PL activation. Here we compared the impact of AMPAkine treatment in the NAc with optogenetic activation of the PL on pain behaviors in rats. We found that not only does AMPAkine treatment partially reconstitute the PL inhibition of sensory withdrawals, it fully occludes the effect of the PL on reducing the aversive component of pain. These results indicate that the NAc is likely one of the key targets for the PL, especially in the regulation of pain aversion. Furthermore, our results lend support for neuromodulation or pharmacological activation of the corticostriatal circuit as an important analgesic approach.

Chronic pain affects one in four adults, and effective non-sedating and non-addictive treatments are urgently needed. Chronic pain causes maladaptive changes in the cerebral cortex, which can lead to impaired endogenous nociceptive processing. However, it is not yet clear if drugs that restore endogenous cortical regulation could provide an effective therapeutic strategy for chronic pain. Here, we studied the nociceptive response of neurons in the prelimbic region of the prefrontal cortex (PL-PFC) in freely behaving rats using a spared nerve injury (SNI) model of chronic pain, and the impact of AMPAkines, a class of drugs that increase central glutamate signaling, on such response. We found that neurons in the PL-PFC increase their firing rates in response to noxious stimulations; chronic neuropathic pain, however, suppressed this important cortical pain response. Meanwhile, CX546, a well-known AMPAkine, restored the anti-nociceptive response of PL-PFC neurons in the chronic pain condition. In addition, both systemic administration and direct delivery of CX546 into the PL-PFC inhibited symptoms of chronic pain, whereas optogenetic inactivation of the PFC neurons or administration of AMPA receptor antagonists in the PL-PFC blocked the anti-nociceptive effects of CX546. These results indicate that restoration of the endogenous anti-nociceptive functions in the PL-PFC by pharmacological agents such as AMPAkines constitutes a successful strategy to treat chronic neuropathic pain.

Accurate prognostic biomarkers in early-stage melanoma are urgently needed to stratify patients for clinical trials of adjuvant therapy. We applied a previously developed open source deep learning algorithm to detect tumor-infiltrating lymphocytes (TILs) in hematoxylin and eosin (H&E) images of early-stage melanomas. We tested whether automated digital (TIL) analysis (ADTA) improved accuracy of prediction of disease specific survival (DSS) based on current pathology standards. ADTA was applied to a training cohort (n = 80) and a cutoff value was defined based on a Receiver Operating Curve. ADTA was then applied to a validation cohort (n = 145) and the previously determined cutoff value was used to stratify high and low risk patients, as demonstrated by Kaplan-Meier analysis (p ≤ 0.001). Multivariable Cox proportional hazards analysis was performed using ADTA, depth, and ulceration as co-variables and showed that ADTA contributed to DSS prediction (HR: 4.18, CI 1.51-11.58, p = 0.006). ADTA provides an effective and attainable assessment of TILs and should be further evaluated in larger studies for inclusion in staging algorithms.

As pain consists of both sensory and affective components, its management by pharmaceutical agents remains difficult. Alternative forms of neuromodulation, such as electrical stimulation, have been studied in recent years as potential pain treatment options. Although electrical stimulation of the brain has shown promise, more research into stimulation frequency and targets is required to support its clinical applications. Here, we studied the effect that stimulation frequency has on pain modulation in the prefrontal cortex (PFC) and the anterior cingulate cortex (ACC) in acute pain models in rats. We found that low-frequency stimulation in the prelimbic region of the PFC (PL-PFC) provides reduction of sensory and affective pain components. Meanwhile, high-frequency stimulation of the ACC, a region involved in processing pain affect, reduces pain aversive behaviors. Our results demonstrate that frequency-dependent neuromodulation of the PFC or ACC has the potential for pain modulation.

Chronic pain alters cortical and subcortical plasticity, causing enhanced sensory and affective responses to peripheral nociceptive inputs. Previous studies have shown that ketamine had the potential to inhibit abnormally amplified affective responses of single neurons by suppressing hyperactivity in the anterior cingulate cortex (ACC). However, the mechanism of this enduring effect has yet to be understood at the network level. In this study, we recorded local field potentials from the ACC of freely moving rats. Animals were injected with complete Freund's adjuvant (CFA) to induce persistent inflammatory pain. Mechanical stimulations were administered to the hind paw before and after CFA administration. We found a significant increase in the high-gamma band (60-100 Hz) power in response to evoked pain after CFA treatment. Ketamine, however, reduced the high-gamma band power in response to evoked pain in CFA-treated rats. In addition, ketamine had a sustained effect on the high-gamma band power lasting up to five days after a single dose administration. These results demonstrate that ketamine has the potential to alter maladaptive neural responses in the ACC induced by chronic pain.

Pain medication plays an important role in the treatment of acute and chronic pain conditions, but some drugs, opioids in particular, have been overprescribed or prescribed without adequate safeguards, leading to an alarming rise in medication-related overdose deaths. The NIH Helping to End Addiction Long-term (HEAL) Initiative is a trans-agency effort to provide scientific solutions to stem the opioid crisis. One component of the initiative is to support biomarker discovery and rigorous validation in collaboration with industry leaders to accelerate high-quality clinical research into neurotherapeutics and pain. The use of objective biomarkers and clinical trial end points throughout the drug discovery and development process is crucial to help define pathophysiological subsets of pain, evaluate target engagement of new drugs and predict the analgesic efficacy of new drugs. In 2018, the NIH-led Discovery and Validation of Biomarkers to Develop Non-Addictive Therapeutics for Pain workshop convened scientific leaders from academia, industry, government and patient advocacy groups to discuss progress, challenges, gaps and ideas to facilitate the development of biomarkers and end points for pain. The outcomes of this workshop are outlined in this Consensus Statement.

Pain is an integrated sensory and affective experience. Cortical mechanisms of sensory and affective integration, however, remain poorly defined. Here, we investigate the projection from the primary somatosensory cortex (S1), which encodes the sensory pain information, to the anterior cingulate cortex (ACC), a key area for processing pain affect, in freely behaving rats. By using a combination of optogenetics, in vivo electrophysiology, and machine learning analysis, we find that a subset of neurons in the ACC receives S1 inputs, and activation of the S1 axon terminals increases the response to noxious stimuli in ACC neurons. Chronic pain enhances this cortico-cortical connection, as manifested by an increased number of ACC neurons that respond to S1 inputs and the magnified contribution of these neurons to the nociceptive response in the ACC. Furthermore, modulation of this S1→ACC projection regulates aversive responses to pain. Our results thus define a cortical circuit that plays a potentially important role in integrating sensory and affective pain signals.

PURPOSE:To develop criteria to interpret mitochondrial transfer RNA (mt-tRNA) variants based on unique characteristics of mitochondrial genetics and conserved structural/functional properties of tRNA. METHODS:We developed rules on a set of established pathogenic/benign variants by examining heteroplasmy correlations with phenotype, tissue distribution, family members, and among unrelated families from published literature. We validated these deduced rules using our new cases and applied them to classify novel variants. RESULTS:Evaluation of previously reported pathogenic variants found that 80.6% had sufficient evidence to support phenotypic correlation with heteroplasmy levels among and within families. The remaining variants were downgraded due to the lack of similar evidence. Application of the verified criteria resulted in rescoring 80.8% of reported variants of uncertain significance (VUS) to benign and likely benign. Among 97 novel variants, none met pathogenic criteria. A large proportion of novel variants (84.5%) remained as VUS, while only 10.3% were likely pathogenic. Detection of these novel variants in additional individuals would facilitate their classification. CONCLUSION:Proper interpretation of mt-tRNA variants is crucial for accurate clinical diagnosis and genetic counseling. Correlations with tissue distribution, heteroplasmy levels, predicted perturbations to tRNA structure, and phenotypes provide important evidence for determining the clinical significance of mt-tRNA variants.

PURPOSE/OBJECTIVE:Biomarkers for disease specific survival (DSS) in early stage melanoma are needed to select patients for adjuvant immunotherapy and accelerate clinical trial design. We present a pathology-based computational method using a deep neural network architecture for DSS prediction. EXPERIMENTAL DESIGN/METHODS:The model was trained on 108 patients from four institutions and tested on 104 patients from Yale School of Medicine (YSM). A receiver operating characteristic (ROC) curve was generated based on vote aggregation of individual image sequences, an optimized cutoff was selected, and the computational model was tested on a third independent population of 51 patients from Geisinger Health Systems (GHS). RESULTS:Area under the curve (AUC) in the YSM patients was 0.905 (p<0.0001). AUC in the GHS patients was 0.880 (p<0.0001). Using the cutoff selected in the YSM cohort, the computational model predicted DSS in the GHS cohort based on Kaplan-Meier (KM) analysis (p<0.0001). CONCLUSIONS:The novel method presented is applicable to digital images, obviating the need for sample shipment and manipulation and representing a practical advance over current genetic and IHC-based methods.

OBJECTIVE:The primary somatosensory cortex (S1) and the anterior cingulate cortex (ACC) are two most important brain regions encoding the sensory-discriminative and affective-emotional aspects of pain, respectively. However, the functional connectivity of these two areas during cortical pain processing remains unclear. Developing methods to dissect the functional connectivity and directed information flow between cortical pain circuits can reveal insight into neural mechanisms of pain perception. APPROACH/METHODS:We recorded multichannel local field potentials (LFPs) from the S1 and ACC from freely behaving rats under various conditions of pain stimulus (thermal vs. mechanical) and pain state (naive vs. chronic pain). We applied Granger causality (GC) analysis to the LFP recordings and inferred frequency-dependent GC statistics and directed information flow. MAIN RESULTS/RESULTS:We found increased information flow during noxious pain stimulus presentation in both S1-->ACC and ACC-->S1 directions, especially at theta and gamma frequency bands. Similar results were found between thermal and mechanical pain stimuli. The chronic pain state shares common observations, but with elevated GC statistics especially in the gamma band. Furthermore, time-varying GC analysis revealed negative correlation between direction-specific and frequency-dependent GC and animal's paw withdrawal latency. In addition, we used computer simulations to investigate the impact of model mismatch, noise, missing variables, and common input on the conditional GC estimate. We also compared the GC results with the transfer entropy (TE) estimates. SIGNIFICANCE/CONCLUSIONS:Our results reveal functional connectivity and directed information flow between the S1 and ACC during various pain conditions. The time-varying GC analysis support the cortico-cortical information loop consistent with the computational predictive coding paradigm.