GS is commonly self-reported with symptoms suggesting an association with irritable bowel syndrome. The majority of patients have NCGS, an entity which demonstrates clinical and immunologic difference to CD.

Painful diabetic peripheral neuropathy (DPN) is difficult to manage, as treatment response is often varied. The primary aim of this study was to examine differences in pain phenotypes between responders and nonresponders to intravenous lidocaine treatment using quantitative sensory testing. The secondary aim was to explore differences in brain structure and functional connectivity with treatment response. Forty-five consecutive patients who received intravenous lidocaine treatment for painful DPN were screened. Twenty-nine patients who met the eligibility criteria (responders, n = 14, and nonresponders, n = 15) and 26 healthy control subjects underwent detailed sensory profiling. Subjects also underwent multimodal brain MRI. A greater proportion of patients with the irritable (IR) nociceptor phenotype were responders to intravenous lidocaine treatment compared with nonresponders. The odds ratio of responding to intravenous lidocaine was 8.67 times greater (95% CI 1.4–53.8) for the IR nociceptor phenotype. Responders to intravenous lidocaine also had significantly greater mean primary somatosensory cortex cortical volume and functional connectivity between the insula cortex and the corticolimbic circuitry. This study provides preliminary evidence for a mechanism-based approach for individualizing therapy in patients with painful DPN.

Aims/hypothesis The aim of this work was to investigate whether different clinical pain phenotypes of diabetic polyneuropathy (DPN) are distinguished by functional connectivity at rest. Methods This was an observational, cohort study of 43 individuals with painful DPN, divided into irritable (IR, n = 10) and non-irritable (NIR, n = 33) nociceptor phenotypes using the German Research Network of Neuropathic Pain quantitative sensory testing protocol. In-situ brain MRI included 3D T1-weighted anatomical and 6 min resting-state functional MRI scans. Subgroup differences in resting-state functional connectivity in brain regions involved with somatic (thalamus, primary somatosensory cortex, motor cortex) and non-somatic (insular and anterior cingulate cortices) pain processing were examined. Multidimensional reduction of MRI datasets was performed using a machine-learning approach to classify individuals into each clinical pain phenotype. Results Individuals with the IR nociceptor phenotype had significantly greater thalamic–insular cortex (p false discovery rate [FDR] = 0.03) and reduced thalamus–somatosensory cortex functional connectivity (p-FDR = 0.03). We observed a double dissociation such that self-reported neuropathic pain score was more associated with greater thalamus–insular cortex functional connectivity (r = 0.41; p = 0.01) whereas more severe nerve function deficits were more related to lower thalamus–somatosensory cortex functional connectivity (r = −0.35; p = 0.03). Machine-learning group classification performance to identify individuals with the NIR nociceptor phenotype achieved an accuracy of 0.92 (95% CI 0.08) and sensitivity of 90%. Conclusions/interpretation This study demonstrates differences in functional connectivity in nociceptive processing brain regions between IR and NIR phenotypes in painful DPN. We also establish proof of concept for the utility of multimodal MRI as a biomarker for painful DPN by using a machine-learning approach to classify individuals into sensory phenotypes. Graphical abstract

Objective Phaeochromocytomas and paragangliomas (PPGL) are rare, but strongly heritable tumours. Variants in succinate dehydrogenase (SDH) subunits are identified in approximately 25% of cases. However, clinical and genetic information of patients with SDHC variants are underreported. Design This retrospective case series collated data from 18 UK Genetics and Endocrinology departments. Patients Both asymptomatic and disease‐affected patients with confirmed SDHC germline variants are included. Measurements Clinical data including tumour type and location, surveillance outcomes and interventions, SDHC genetic variant assessment, interpretation, and tumour risk calculation. Results We report 91 SDHC cases, 46 probands and 45 non‐probands. Fifty‐one cases were disease‐affected. Median age at genetic diagnosis was 43 years (range: 11–79). Twenty‐four SDHC germline variants were identified including six novel variants. Head and neck paraganglioma (HNPGL, n = 30, 65.2%), extra‐adrenal paraganglioma (EAPGL, n = 13, 28.2%) and phaeochromocytomas (PCC) (n = 3, 6.5%) were present. One case had multiple PPGLs. Malignant disease was reported in 19.6% (9/46). Eight cases had non‐PPGL SDHC‐associated tumours, six gastrointestinal stromal tumours (GIST) and two renal cell cancers (RCC). Cumulative tumour risk (95% CI) at age 60 years was 0.94 (CI: 0.79–0.99) in probands, and 0.16 (CI: 0–0.31) in non‐probands, respectively. Conclusions This study describes the largest cohort of 91 SDHC patients worldwide. We confirm disease‐affected SDHC variant cases develop isolated HNPGL disease in nearly 2/3 of patients, EAPGL and PCC in 1/3, with an increased risk of GIST and RCC. One fifth developed malignant disease, requiring comprehensive lifelong tumour screening and surveillance.

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