Genetic Influence on Nociceptive Processing in the Human Brain—A Twin Study

Cerebral Cortex, vol. 32, pp. 266–274

Abstract

Nociceptive processing in the human brain is complex and involves several brain structures and varies across individuals. Determining the structures that contribute to interindividual differences in nociceptive processing is likely to improve our understanding of why some individuals feel more pain than others. Here, we found specific parts of the cerebral response to nociception that are under genetic influence by employing a classic twin-design. We found genetic influences on nociceptive processing in the midcingulate cortex and bilateral posterior insula. In addition to brain activations, we found genetic contributions to large-scale functional connectivity (FC) during nociceptive processing. We conclude that additive genetics influence specific brain regions involved in nociceptive processing. The genetic influence on FC during nociceptive processing is not limited to core nociceptive brain regions, such as the dorsal posterior insula and somatosensory areas, but also involves cognitive and affective brain circuitry. These findings improve our understanding of human pain perception and increases chances to find new treatments for clinical pain.

Authors 10

1. Gránit Kastrati

   Karolinska Institutet · Mid Sweden University

   Affiliation as printed

   Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden

   Department of Psychology and Social Work, Mid Sweden University, SE-831 25, Östersund, Sweden

   Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden,

2. Jörgen Rosén

   Mid Sweden University

   Affiliation as printed

   Department of Psychology and Social Work, Mid Sweden University, SE-831 25, Östersund, Sweden

3. William Hedley Thompson

   Karolinska Institutet

   Affiliation as printed

   Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden

   Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden,

4. Xu Chen Aachen Department of Biomedical Data Sciences

   Leiden University Medical Center

   Affiliation as printed

   Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RA, Leiden, the Netherlands

   Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RA, Leiden, the Netherlands,

5. Henrik Larsson

   Örebro University

   Affiliation as printed

   Department of Medical Sciences, Örebro University, SE--701 82, Örebro, Sweden

6. Thomas E. Nichols

   University of Oxford

   Affiliation as printed

   Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, OX3 7LF, Oxford, UK

   Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, OX3 7LF, Oxford, UK and

7. Irene Tracey

   University of Oxford · Wellcome Centre for Integrative Neuroimaging

   Affiliation as printed

   Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, OX3 9DU, Oxford, UK

8. Peter Fransson

   Karolinska Institutet

   Affiliation as printed

   Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden

   Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden,

9. Fredrik Åhs

   Mid Sweden University

   Affiliation as printed

   Department of Psychology and Social Work, Mid Sweden University, SE-831 25, Östersund, Sweden

10. Karin Birgitta Jensen corresponding

    Karolinska Institutet

    Affiliation as printed

    Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden

    Department of Clinical Neuroscience, Karolinska Institutet, SE-171 77, Stockholm, Sweden,