Bidirectional modulation of hyperalgesia via the specific control of excitatory and inhibitory neuronal activity in the ACC

Neurons in the anterior cingulate cortex (ACC) are assumed to play important roles in the perception of nociceptive signals and the associated emotional responses. However, the neuronal types within the ACC that mediate these functions are poorly understood. In the present study, we used optogenetic techniques to selectively modulate excitatory pyramidal neurons and inhibitory interneurons in the ACC and to assess their ability to modulate peripheral mechanical hypersensitivity in freely moving mice. We found that selective activation of pyramidal neurons rapidly and acutely reduced nociceptive thresholds and that this effect was occluded in animals made hypersensitive using Freund's Complete Adjuvant (CFA). Conversely, inhibition of ACC pyramidal neurons rapidly and acutely reduced hypersensitivity induced by CFA treatment. A similar analgesic effect was induced by activation of parvalbumin (PV) expressing interneurons, whereas activation of somatostatin (SOM) expressing interneurons had no effect on pain thresholds. Our results provide direct evidence of the pivotal role of ACC excitatory neurons, and their regulation by PV expressing interneurons, in nociception. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13041-015-0170-6) contains supplementary material, which is available to authorized users

Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

This corrects the article DOI: 10.1038/sdata.2017.179

Rapid Turnover of Cortical NCAM1 Regulates Synaptic Reorganization after Peripheral Nerve Injury

Peripheral nerve injury can induce pathological conditions that lead to persistent sensitized nociception. Although there is evidence that plastic changes in the cortex contribute to this process, the underlying molecular mechanisms are unclear. Here, we find that activation of the anterior cingulate cortex (ACC) induced by peripheral nerve injury increases the turnover of specific synaptic proteins in a persistent manner. We demonstrate that neural cell adhesion molecule 1 (NCAM1) is one of the molecules involved and show that it mediates spine reorganization and contributes to the behavioral sensitization. We show striking parallels in the underlying mechanism with the maintenance of NMDA-receptor- and protein-synthesis-dependent long-term potentiation (LTP) in the ACC. Our results, therefore, demonstrate a synaptic mechanism for cortical reorganization and suggest potential avenues for neuropathic pain treatment

Evaluating the contribution of rare variants to type 2 diabetes and related traits using pedigrees

Significance Contributions of rare variants to common and complex traits such as type 2 diabetes (T2D) are difficult to measure. This paper describes our results from deep whole-genome analysis of large Mexican-American pedigrees to understand the role of rare-sequence variations in T2D and related traits through enriched allele counts in pedigrees. Our study design was well-powered to detect association of rare variants if rare variants with large effects collectively accounted for large portions of risk variability, but our results did not identify such variants in this sample. We further quantified the contributions of common and rare variants in gene expression profiles and concluded that rare expression quantitative trait loci explain a substantive, but minor, portion of expression heritability.</jats:p

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

The genetic architecture of type 2 diabetes

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes