Citations

ObjectiveIn observational epidemiologic studies, higher plasma high‐density lipoprotein cholesterol (HDL‐C) has been associated with increased risk of intracerebral hemorrhage (ICH). DNA sequence variants that decrease cholesteryl ester transfer protein (CETP) gene activity increase plasma HDL‐C; as such, medicines that inhibit CETP and raise HDL‐C are in clinical development. Here, we test the hypothesis that CETP DNA sequence variants associated with higher HDL‐C also increase risk for ICH.MethodsWe performed 2 candidate‐gene analyses of CETP. First, we tested individual CETP variants in a discovery cohort of 1,149 ICH cases and 1,238 controls from 3 studies, followed by replication in 1,625 cases and 1,845 controls from 5 studies. Second, we constructed a genetic risk score comprised of 7 independent variants at the CETP locus and tested this score for association with HDL‐C as well as ICH risk.ResultsTwelve variants within CETP demonstrated nominal association with ICH, with the strongest association at the rs173539 locus (odds ratio [OR] = 1.25, standard error [SE] = 0.06, p = 6.0 × 10−4) with no heterogeneity across studies (I2 = 0%). This association was replicated in patients of European ancestry (p = 0.03). A genetic score of CETP variants found to increase HDL‐C by ∼2.85mg/dl in the Global Lipids Genetics Consortium was strongly associated with ICH risk (OR = 1.86, SE = 0.13, p = 1.39 × 10−6).InterpretationGenetic variants in CETP associated with increased HDL‐C raise the risk of ICH. Given ongoing therapeutic development in CETP inhibition and other HDL‐raising strategies, further exploration of potential adverse cerebrovascular outcomes may be warranted. Ann Neurol 2016;80:730–740

Freely available software, derived from the past 2 decades of neuroimaging research, is significantly more flexible for research purposes than presently available clinical tools. Here, we describe and demonstrate the utility of rapidly deployable analysis software to facilitate trainee-driven translational neuroimaging research. A recipe and video tutorial were created to guide the creation of a NeuroDebian-based virtual computer that conforms to current neuroimaging research standards and can exist within a HIPAA-compliant system. This allows for retrieval of clinical imaging data, conversion to standard file formats, and rapid visualization and quantification of individual patients’ cortical and subcortical anatomy. As an example, we apply this pipeline to a pediatric patient’s data to illustrate the advantages of research-derived neuroimaging tools in asking quantitative questions “at the bedside.” Our goal is to provide a path of entry for trainees to become familiar with common neuroimaging tools and foster an increased interest in translational research.

AbstractBackgroundInvasive candidiasis (IC) is a common cause of mortality in solid organ transplant recipients (OTRs), but knowledge of epidemiology in this population is limited.MethodThe present analysis describes data from 15 US centers that prospectively identified IC from nearly 17 000 OTRs. Analyses were undertaken to determine predictors of infection and mortality.ResultsA total of 639 cases of IC were identified. The most common species was Candida albicans (46.3%), followed by Candida glabrata (24.4%) and Candida parapsilosis (8.1%). In 68 cases >1 species was identified. The most common infection site was bloodstream (44%), followed by intra‐abdominal (14%). The most frequently affected allograft groups were liver (41.1%) and kidney (35.3%). All‐cause mortality at 90 days was 26.5% for all species and was highest for Candida tropicalis (44%) and C. parapsilosis (35.2%). Non‐white race and female gender were more commonly associated with non‐albicans species. A high rate of breakthrough IC was seen in patients receiving antifungal prophylaxis (39%). Factors associated with mortality include organ dysfunction, lung transplant, and treatment with a polyene antifungal. The only modifiable factor identified was choice of antifungal drug class based upon infecting Candida species.ConclusionThese data highlight the common and distinct features of IC in OTRs.

Key Points Under current treatment approaches, patients with LA GVHD have poor overall and failure-free survival. Levels of AREG are elevated in LA GVHD, and the AREG/EGF ratio is predictive of overall survival and nonrelapse mortality in LA GVHD.

This special issue surveys recent work and underscores the challenges of psychiatric brain stimulation research with child and adolescent populations. The field of child and adolescent psychopharmacology is replete with examples of potential pitfalls in the assumption that “children are little adults.” Arguably, younger age portends more neurobiological and descriptive heterogeneity in research pursuits and clinical practice. For existing brain stimulation modalities, there are a paucity of translational models to design studies for youth and no well-studied dosing schemes. The long-term positive and negative effects of neuromodulation interventions in youth are unknown. Inherent pragmatic and ethical limitations often present barriers for participant recruitment and will necessitate innovative approaches to study design and team efforts. These challenges are not insurmountable, and sustained efforts will advance the growing field of pediatric neuromodulation.

Background The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study. Methods We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T>G and c.3113G>A, CHEK2 c.349A>G, c.538C>T, c.715G>A, c.1036C>T, c.1312G>T, and c.1343T>G and ATM c.7271T>G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant. Results For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G>A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T>G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A>G OR 2.26 (95% CI 1.29 to 3.95), c.1036C>T OR 5.06 (95% CI 1.09 to 23.5) and c.538C>T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T>G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G>T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants. Conclusions This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.

Abstract Background: The strongest known risk factor for endometrial cancer is obesity. To determine whether SNPs associated with increased body mass index (BMI) or waist–hip ratio (WHR) are associated with endometrial cancer risk, independent of measured BMI, we investigated relationships between 77 BMI and 47 WHR SNPs and endometrial cancer in 6,609 cases and 37,926 country-matched controls. Methods: Logistic regression analysis and fixed effects meta-analysis were used to test for associations between endometrial cancer risk and (i) individual BMI or WHR SNPs, (ii) a combined weighted genetic risk score (wGRS) for BMI or WHR. Causality of BMI for endometrial cancer was assessed using Mendelian randomization, with BMIwGRS as instrumental variable. Results: The BMIwGRS was significantly associated with endometrial cancer risk (P = 3.4 × 10−17). Scaling the effect of the BMIwGRS on endometrial cancer risk by its effect on BMI, the endometrial cancer OR per 5 kg/m2 of genetically predicted BMI was 2.06 [95% confidence interval (CI), 1.89–2.21], larger than the observed effect of BMI on endometrial cancer risk (OR = 1.55; 95% CI, 1.44–1.68, per 5 kg/m2). The association attenuated but remained significant after adjusting for BMI (OR = 1.22; 95% CI, 1.10–1.39; P = 5.3 × 10−4). There was evidence of directional pleiotropy (P = 1.5 × 10−4). BMI SNP rs2075650 was associated with endometrial cancer at study-wide significance (P < 4.0 × 10−4), independent of BMI. Endometrial cancer was not significantly associated with individual WHR SNPs or the WHRwGRS. Conclusions: BMI, but not WHR, is causally associated with endometrial cancer risk, with evidence that some BMI-associated SNPs alter endometrial cancer risk via mechanisms other than measurable BMI. Impact: The causal association between BMI SNPs and endometrial cancer has possible implications for endometrial cancer risk modeling. Cancer Epidemiol Biomarkers Prev; 25(11); 1503–10. ©2016 AACR.

Key Clinical MessageA de novo GFAP variant, p.R376W, was identified in a child presenting with hypotonia, developmental delay, and abnormal brain MRI. Following the 2015 ACMG variant classification guidelines and the functional studies showing protein aggregate formation in vitro, p.R376W should be classified as a pathogenic variant, causative for Alexander disease.