Citations

AbstractBackgroundDiagnosing gastroesophageal reflux disease (GERD) can be challenging given varying symptom presentations, and complex multifactorial pathophysiology. The gold standard for GERD diagnosis is esophageal acid exposure time (AET) measured by pH‐metry. A variety of additional diagnostic tools are available. The goal of this consensus was to assess the individual merits of GERD diagnostic tools based on current evidence, and provide consensus recommendations following discussion and voting by experts.MethodsThis consensus was developed by 15 experts from nine countries, based on a systematic search of the literature, using GRADE (grading of recommendations, assessment, development and evaluation) methodology to assess the quality and strength of the evidence, and provide recommendations regarding the diagnostic utility of different GERD diagnosis tools, using AET as the reference standard.Key ResultsA proton pump inhibitor (PPI) trial is appropriate for patients with heartburn and no alarm symptoms, but nor for patients with regurgitation, chest pain, or extraesophageal presentations. Severe erosive esophagitis and abnormal reflux monitoring off PPI are clearly indicative of GERD. Esophagram, esophageal biopsies, laryngoscopy, and pharyngeal pH monitoring are not recommended to diagnose GERD. Patients with PPI‐refractory symptoms and normal endoscopy require reflux monitoring by pH or pH‐impedance to confirm or exclude GERD, and identify treatment failure mechanisms. GERD confounders need to be considered in some patients, pH‐impedance can identify supragrastric belching, impedance‐manometry can diagnose rumination.ConclusionsErosive esophagitis on endoscopy and abnormal pH or pH‐impedance monitoring are the most appropriate methods to establish a diagnosis of GERD. Other tools may add useful complementary information.

OBJECTIVE The MHC region harbors the strongest loci for latent autoimmune diabetes in adults (LADA); however, the strength of association is likely attenuated compared with that for childhood-onset type 1 diabetes. In this study, we recapitulate independent effects in the MHC class I region in a population with type 1 diabetes and then determine whether such conditioning in LADA yields potential genetic discriminators between the two subtypes within this region. RESEARCH DESIGN AND METHODS Chromosome 6 was imputed using SNP2HLA, with conditional analysis performed in type 1 diabetes case subjects (n = 1,985) and control subjects (n = 2,219). The same approach was applied to a LADA cohort (n = 1,428) using population-based control subjects (n = 2,850) and in a separate replication cohort (656 type 1 diabetes case, 823 LADA case, and 3,218 control subjects). RESULTS The strongest associations in the MHC class II region (rs3957146, β [SE] = 1.44 [0.05]), as well as the independent effect of MHC class I genes, on type 1 diabetes risk, particularly HLA-B*39 (β [SE] = 1.36 [0.17]), were confirmed. The conditional analysis in LADA versus control subjects showed significant association in the MHC class II region (rs3957146, β [SE] = 1.14 [0.06]); however, we did not observe significant independent effects of MHC class I alleles in LADA. CONCLUSIONS In LADA, the independent effects of MHC class I observed in type 1 diabetes were not observed after conditioning on the leading MHC class II associations, suggesting that the MHC class I association may be a genetic discriminator between LADA and childhood-onset type 1 diabetes.

OBJECTIVELatent autoimmune diabetes in adults (LADA) shares clinical features with both type 1 and type 2 diabetes; however, there is ongoing debate regarding the precise definition of LADA. Understanding its genetic basis is one potential strategy to gain insight into appropriate classification of this diabetes subtype.RESEARCH DESIGN AND METHODSWe performed the first genome-wide association study of LADA in case subjects of European ancestry versus population control subjects (n = 2,634 vs. 5,947) and compared against both case subjects with type 1 diabetes (n = 2,454 vs. 968) and type 2 diabetes (n = 2,779 vs. 10,396).RESULTSThe leading genetic signals were principally shared with type 1 diabetes, although we observed positive genetic correlations genome-wide with both type 1 and type 2 diabetes. Additionally, we observed a novel independent signal at the known type 1 diabetes locus harboring PFKFB3, encoding a regulator of glycolysis and insulin signaling in type 2 diabetes and inflammation and autophagy in autoimmune disease, as well as an attenuation of key type 1–associated HLA haplotype frequencies in LADA, suggesting that these are factors that distinguish childhood-onset type 1 diabetes from adult autoimmune diabetes.CONCLUSIONSOur results support the need for further investigations of the genetic factors that distinguish forms of autoimmune diabetes as well as more precise classification strategies.