Citations

AbstractIntroductionBiomarkers for Alzheimer's disease (AD) pathophysiology have been developed that focus on various levels of brain organization. However, no robust biomarker of large‐scale network failure has been developed. Using the recently introduced cascading network failure model of AD, we developed the network failure quotient (NFQ) as a biomarker of this process.MethodsWe developed and optimized the NFQ using our recently published analyses of task‐free functional magnetic resonance imaging data in clinically normal (n = 43) and AD dementia participants (n = 28) from the Alzheimer's Disease Neuroimaging Initiative. The optimized NFQ (oNFQ) was then validated in a cohort spanning the AD spectrum from the Mayo Clinic (n = 218).ResultsThe oNFQ (d = 1.25, 95% confidence interval [1.25, 1.26]) had the highest effect size for differentiating persons with AD dementia from clinically normal participants. The oNFQ measure performed similarly well on the validation Mayo Clinic sample (d = 1.44, 95% confidence interval [1.43, 1.44]). The oNFQ was also associated with other available key biomarkers in the Mayo cohort.DiscussionThis study demonstrates a measure of functional connectivity, based on a cascading network failure model of AD, and was highly successful in identifying AD dementia. A robust biomarker of the large‐scale effects of AD pathophysiology will allow for richer descriptions of the disease process and its modifiers, but is not currently suitable for discriminating clinical diagnostic categories. The large‐scale network level may be one of the earliest manifestations of AD, making this an attractive target for continued biomarker development to be used in prevention trials.

Numerous pharmacogenetic clinical guidelines and recommendations have been published, but barriers have hindered the clinical implementation of pharmacogenetics. The Translational Pharmacogenetics Program (TPP) of the National Institutes of Health (NIH) Pharmacogenomics Research Network was established in 2011 to catalog and contribute to the development of pharmacogenetic implementations at eight US healthcare systems, with the goal to disseminate real‐world solutions for the barriers to clinical pharmacogenetic implementation. The TPP collected and normalized pharmacogenetic implementation metrics through June 2015, including gene–drug pairs implemented, interpretations of alleles and diplotypes, numbers of tests performed and actionable results, and workflow diagrams. TPP participant institutions developed diverse solutions to overcome many barriers, but the use of Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines provided some consistency among the institutions. The TPP also collected some pharmacogenetic implementation outcomes (scientific, educational, financial, and informatics), which may inform healthcare systems seeking to implement their own pharmacogenetic testing programs.

The psychological treatment of obsessive–compulsive disorder (OCD) with exposure and response prevention (ERP) methods is one of the great success stories within the field of mental health. Within the span of about 20 years, the prognosis for individuals with OCD has changed from poor to very good as a result of the development of ERP. This success not withstanding, the procedures are far from perfect because a substantial minority of patients still either refuse treatment, drop out prematurely, or fail to benefit. I begin this article with a review of the development of ERP from early animal research on avoidance learning conducted during the 1950s. Next, I discuss the mechanisms of ERP. The bulk of the article reviews the treatment-outcome literature on ERP for OCD and includes comparisons with cognitive therapy—the “new kid on the block” with respect to psychological treatments for OCD.

Objective To report a case series of a novel migraine subtype, which we term as episodic status migrainosus (ESM), characterized by attacks of migraine exclusively lasting more than 72 hours. We hypothesized that this would represent a novel nosologic entity, possibly an unstable migraine phenotype with a high conversion rate to chronic migraine (CM). Methods We conducted a retrospective review of patients diagnosed with status migrainosus at the Mayo Clinic, Rochester, between January 2005 and December 2015. All the records were then manually reviewed for patients with migraine headaches exclusively lasting more than 72 hours. Results We identified 18 patients with ESM, with a female predominance (15(83.3%)) and a median age of onset of 16.5 (IQR 13–19) years. The median monthly attack frequency was two (IQR 1–3), with each attack lasting a median duration of seven (IQR 4–12.5) days. Stress was the most commonly reported precipitant (11 (61.1%)). Migraine with aura was common (10 (55.6%)), as was comorbid depression (10 (55.6%)). Fifteen (83.3%) patients developed CM at a median of 7.8 (IQR 2.6–21.9) years from their first attack. There was no significant association between the time to the development of chronic migraine with either attack frequency or duration. Conclusions and relevance We report the existence of a novel migraine subtype, episodic status migrainosus. This migraine subtype appears to have similar clinical characteristics to episodic migraine with or without aura, except for a notably high tendency to progress to chronic migraine.

Abstract Background: Genome-wide association studies (GWAS) have identified multiple loci associated with epithelial ovarian cancer (EOC) susceptibility, but further progress requires integration of epidemiology and biology to illuminate true risk loci below genome-wide significance levels (P < 5 × 10−8). Most risk SNPs lie within non–protein-encoding regions, and we hypothesize that long noncoding RNA (lncRNA) genes are enriched at EOC risk regions and represent biologically relevant functional targets. Methods: Using imputed GWAS data from about 18,000 invasive EOC cases and 34,000 controls of European ancestry, the GENCODE (v19) lncRNA database was used to annotate SNPs from 13,442 lncRNAs for permutation-based enrichment analysis. Tumor expression quantitative trait locus (eQTL) analysis was performed for sub-genome-wide regions (1 × 10−5 > P > 5 × 10−8) overlapping lncRNAs. Results: Of 5,294 EOC-associated SNPs (P < 1.0 × 10−5), 1,464 (28%) mapped within 53 unique lncRNAs and an additional 3,484 (66%) SNPs were correlated (r2 > 0.2) with SNPs within 115 lncRNAs. EOC-associated SNPs comprised 130 independent regions, of which 72 (55%) overlapped with lncRNAs, representing a significant enrichment (P = 5.0 × 10−4) that was more pronounced among a subset of 5,401 lncRNAs with active epigenetic regulation in normal ovarian tissue. EOC-associated lncRNAs and their putative promoters and transcription factors were enriched for biologically relevant pathways and eQTL analysis identified five novel putative risk regions with allele-specific effects on lncRNA gene expression. Conclusions: lncRNAs are significantly enriched at EOC risk regions, suggesting a mechanistic role for lncRNAs in driving predisposition to EOC. Impact: lncRNAs represent key candidates for integrative epidemiologic and functional studies. Further research on their biologic role in ovarian cancer is indicated. Cancer Epidemiol Biomarkers Prev; 26(1); 116–25. ©2016 AACR.

Objective Genome‐wide association studies (GWAS) have been successful at identifying associations with stroke and stroke subtypes, but have not yet identified any associations solely with small vessel stroke (SVS). SVS comprises one quarter of all ischemic stroke and is a major manifestation of cerebral small vessel disease, the primary cause of vascular cognitive impairment. Studies across neurological traits have shown that younger‐onset cases have an increased genetic burden. We leveraged this increased genetic burden by performing an age‐at‐onset informed GWAS meta‐analysis, including a large younger‐onset SVS population, to identify novel associations with stroke. Methods We used a three‐stage age‐at‐onset informed GWAS to identify novel genetic variants associated with stroke. On identifying a novel locus associated with SVS, we assessed its influence on other small vessel disease phenotypes, as well as on messenger RNA (mRNA) expression of nearby genes, and on DNA methylation of nearby CpG sites in whole blood and in the fetal brain. Results We identified an association with SVS in 4,203 cases and 50,728 controls on chromosome 16q24.2 (odds ratio [OR; 95% confidence interval {CI}] = 1.16 [1.10–1.22]; p = 3.2 × 10 −9 ). The lead single‐nucleotide polymorphism (rs12445022) was also associated with cerebral white matter hyperintensities (OR [95% CI] = 1.10 [1.05–1.16]; p = 5.3 × 10 −5 ; N = 3,670), but not intracerebral hemorrhage (OR [95% CI] = 0.97 [0.84–1.12]; p = 0.71; 1,545 cases, 1,481 controls). rs12445022 is associated with mRNA expression of ZCCHC14 in arterial tissues ( p = 9.4 × 10 −7 ) and DNA methylation at probe cg16596957 in whole blood ( p = 5.3 × 10 −6 ). Interpretation 16q24.2 is associated with SVS. Associations of the locus with expression of ZCCHC14 and DNA methylation suggest the locus acts through changes to regulatory elements. Ann Neurol 2017;81:383–394