Molecular Basis of Individual Differences in Pain and Addiction

Dear Colleagues,

Pain and addiction are complex and heterogeneous conditions in which individuals differ substantially in vulnerability, clinical presentation, disease progression, and therapeutic response. These differences arise from dynamic interactions among genetic variation, epigenetic regulation, molecular and cellular signaling, neural circuit function, environmental exposures, life experiences, and psychosocial factors. Recent advances in human genetics, pharmacogenomics, molecular imaging, single-cell and spatial technologies, multi-omics analysis, and circuit-level neuroscience now provide unprecedented opportunities to connect these mechanisms with clinically meaningful variation. In parallel, experimental models allow genetic background and environmental conditions to be manipulated systematically and individual behavioral and physiological responses to be quantified. Paradigms involving early-life adversity, chronic stress, social isolation or defeat, sleep or circadian disruption, diet and metabolic state, inflammatory or toxic exposures, previous pain or injury, and prior exposure to addictive substances or analgesic drugs can therefore help identify molecular, cellular, and circuit mechanisms that confer susceptibility or resilience.

This Special Issue aims to present and disseminate recent advances concerning the molecular basis of individual differences in pain and addiction. We welcome basic, translational, and clinical studies addressing variation in pain perception, chronic pain susceptibility, analgesic response, substance use disorders, and behavioral addictions. Relevant contributions may examine genetic and epigenetic factors; receptor and intracellular signaling; neurotransmitter and neuropeptide systems; neuroimmune and glial mechanisms; neural circuits; brain–body and brain–gut interactions; molecular imaging; pharmacokinetics and pharmacodynamics; biomarkers; and precision medicine. In addition, studies utilizing preclinical animal models that incorporate environmental exposures and psychosocial stress paradigms—such as early-life adversity, social defeat or isolation, variable chronic stress, and environmental enrichment—to dissect molecular, cellular, and circuit-level outcomes are highly encouraged. Because pain and addiction share systems involved in reward, aversion, stress, learning, motivation, endogenous opioid signaling, and neuroimmune regulation, we also welcome studies at their interface, including opioid analgesia and misuse, pain-related vulnerability to substance use, stress-induced changes in pain or drug seeking, placebo analgesia, craving, relapse, and individualized treatment response. Reverse-translational studies linking human observations to mechanistic animal models, and preclinical studies that generate hypotheses for human stratification, are particularly relevant.

Topics of interest for publication include, but are not limited to, the following:

• Genetic and epigenetic determinants of pain and addiction vulnerability;
• Gene–environment interactions and mechanisms of susceptibility or resilience;
• Animal models of inter-individual variability in pain and addictive behaviors;
• Environmental exposures and psychosocial stressors affecting pain and addiction;
• Molecular and circuit mechanisms of chronic pain and substance use disorders;
• Neurotransmitter, neuropeptide, neuroimmune, and glial mechanisms;
• Pharmacogenomics and individual differences in analgesic or addiction-treatment response;
• Molecular imaging, single-cell, spatial, and multi-omics approaches;
• Brain–body and brain–gut interactions;
• Biomarkers, patient stratification, reverse translation, and precision medicine.

Dr. Yilong Cui
Dr. Daisuke Nishizawa
Dr. Soichiro Ide
Dr. Kazutaka Ikeda
Guest Editors

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• pain
• addiction
• individual differences
• precision medicine
• pharmacogenomics
• genetics
• epigenetics
• molecular imaging
• neural circuits
• opioids
• reward
• craving
• placebo analgesia
• neuroinflammation
• brain–gut interaction
• biomarkers
• single-cell analysis
• multi-omics