Citations

We describe the case of a 59-year-old woman who presented with progressive bilateral vestibidar hypofunction and who was found to have bilateral granulomatous mass lesions of the mesial temporal lobe. Initially, her condition stabilized neurologically with corticosteroids, but a diagnosis of neurosarcoidosis was delayed because of the unusual presentation and persistently normal chest imaging results and serum angiotensin-converting enzyme (ACE) levels. Approximately 1 year after her initial presentation, the patient died of complications of a myocardial infarction and pulmonary embolism. Sarcoidosis should be considered in the differential diagnosis of idiopathic bilateral vestibular hypofunction even if the chest imaging and serum ACE levels are normal, particularly when there is evidence of a multisystem process.

Abstract Background: To evaluate the association between opioid use and treatment outcome (symptom severity, quality of life [QOL]) after a brief interdisciplinary fibromyalgia treatment program (FTP). Method: Subjects (n = 971) with fibromyalgia participated in the FTP. They filled out the Fibromyalgia Impact Questionnaire (FIQ) and the Short Form-36 Health Status Questionnaire (SF-36) at baseline and 6 to 12 months after the FTP. Post-treatment changes in FIQ and SF-36 scores were compared after stratifying the participants into opioid user and non-opioid user groups. Results: A total of 236 patients (24.3%) were opioid users. Compared with non-opioid users, the opioid users had worse symptom severity measured using FIQ total score (p < .001) and all subscales at baseline and post treatment, as well as worse QOL measured using all SF-36 subscales and physical and mental components. Comparison of least-square means of mean change of QOL between opioid users and non-opioid users after analysis of covariance adjusted patient characteristics and baseline scores showed that the FIQ subscale scores of physical impairment (p < .05), job ability (p < .05), and fatigue (p < .05) were significantly less improved in the opioid users compared with the non-opioid users. Moreover, the SF-36 subscale score of general health perception (p < .05) was significantly less improved in the opioid users compared with non-opioid users. However, post-treatment changes in mean scores for QOL subscale generally did not significantly differ in both groups. Conclusions: Opioid use did not affect response to the FTP, as measured using the FIQ total score or SF-36 physical and mental component summary scores. Furthermore, the opioid user group showed less improvement in the FIQ subscale scores of physical impairment, job ability, and fatigue and in the SF-36 subscale scores of general health perception.

The lack of reliable, noninvasive methods to diagnose early nonalcoholic steatohepatitis (NASH) is a major unmet need. We aimed to determine the diagnostic accuracy of three‐dimensional magnetic resonance elastography (3D‐MRE), with shear stiffness measured at 60 Hz, damping ratio at 40 Hz, and magnetic resonance imaging proton density fat fraction (MRI‐PDFF) in the detection of NASH in individuals undergoing bariatric surgery. Obese adults at risk for NASH were enrolled between 2015 and 2017 (prospective cohort, n = 88) and 2010 and 2013 (retrospective cohort, n = 87). The imaging protocol consisted of multifrequency 3D‐MRE (mf3D‐MRE) with shear waves delivered at different frequencies to explore parameters that best correlated with histologic NASH, and MRI‐PDFF to estimate steatosis. The prospective cohort was used to establish the optimal mf3D‐MRE technical parameters for NASH detection. The two cohorts were then combined to derive predictive models of NASH and disease activity by nonalcoholic fatty liver disease activity score (NAS) using the three imaging parameters that correlated with NASH. A total of 175 patients (median age 45, 81% women, and 81 [46%] with histologic NASH) were used for model derivation. From the complex shear modulus output generated by mf3D‐MRE, the damping ratio at 40 Hz and shear stiffness at 60 Hz best correlated with NASH. The fat fraction obtained from MRI‐PDFF correlated with steatosis ( P < 0.05 for all). These three parameters were fit into a logistic regression model that predicted NASH with cross‐validated area under the receiver operating characteristic curve (AUROC) = 0.73, sensitivity = 0.67, specificity = 0.80, positive predictive value = 0.73 and negative predictive value = 0.74, and disease activity by NAS with cross‐validated AUROC = 0.82. Conclusion: The mf3D‐MRE allows identification of imaging parameters that predict early NASH and disease activity. This imaging biomarker represents a promising alternative to liver biopsy for NASH diagnosis and monitoring. The results provide motivation for further studies in nonbariatric cohorts.

Despite much attention to the use of biomarkers for predicting Alzheimer disease, little information is available at the individual level. We used the population‐based Mayo Clinic Study of Aging to estimate absolute risk of cognitive impairment by biomarker group. Risk increased with age and any biomarker abnormality. For example, a 75‐year‐old with abnormal amyloid and cortical thinning biomarkers has about a 20% chance of cognitive impairment by age 80 years, whereas with normal biomarkers the chance is <10%. Persons with only one abnormal biomarker had similar intermediate risks. ANN NEUROL 2019;85:155–160.

As a follow‐up to genome‐wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well‐known ovarian cancer risk factors and their interactions with 28 genome‐wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case–control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10−4). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46–0.60) compared to 0.71 (95%CI = 0.66–0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1–5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene–environment analysis in ovarian cancer.

Abstract Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, BNC2 was established as the most likely target gene. We determined the consensus binding sequence for BNC2 in vitro, verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. Significance: Mapping the 9p22.2 ovarian cancer risk locus identifies BNC2 as an ovarian cancer risk gene. See related commentary by Choi and Brown, p. 439