Genome-wide linkage analysis of 972 bipolar pedigrees using single-nucleotide polymorphisms.

Because of the high costs associated with ascertainment of families, most linkage studies of Bipolar I disorder (BPI) have used relatively small samples. Moreover, the genetic information content reported in most studies has been less than 0.6. Although microsatellite markers spaced every 10 cM typically extract most of the genetic information content for larger multiplex families, they can be less informative for smaller pedigrees especially for affected sib pair kindreds. For these reasons we collaborated to pool family resources and carried out higher density genotyping. Approximately 1100 pedigrees of European ancestry were initially selected for study and were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel 12 set of 6090 single-nucleotide polymorphisms. Of the ~1100 families, 972 were informative for further analyses, and mean information content was 0.86 after pruning for linkage disequilibrium. The 972 kindreds include 2284 cases of BPI disorder, 498 individuals with bipolar II disorder (BPII) and 702 subjects with recurrent major depression. Three affection status models (ASMs) were considered: ASM1 (BPI and schizoaffective disorder, BP cases (SABP) only), ASM2 (ASM1 cases plus BPII) and ASM3 (ASM2 cases plus recurrent major depression). Both parametric and non-parametric linkage methods were carried out. The strongest findings occurred at 6q21 (non-parametric pairs LOD 3.4 for rs1046943 at 119 cM) and 9q21 (non-parametric pairs logarithm of odds (LOD) 3.4 for rs722642 at 78 cM) using only BPI and schizoaffective (SA), BP cases. Both results met genome-wide significant criteria, although neither was significant after correction for multiple analyses. We also inspected parametric scores for the larger multiplex families to identify possible rare susceptibility loci. In this analysis, we observed 59 parametric LODs of 2 or greater, many of which are likely to be close to maximum possible scores. Although some linkage findings may be false positives, the results could help prioritize the search for rare variants using whole exome or genome sequencing

Genome-wide parametric linkage analyses of 644 bipolar pedigrees suggest susceptibility loci at chromosomes 16 and 20

OBJECTIVE: Our aim is to map chromosomal regions that harbor loci that increase susceptibility to bipolar disorder. METHODS: We analyzed 644 bipolar families ascertained by the National Institute of Mental Health Human Genetics Initiative for bipolar disorder. The families have been genotyped with microsatellite loci spaced every approximately 10 cM or less across the genome. Earlier analyses of these pedigrees have been limited to nonparametric (model-free) methods and thus, information from unaffected subjects with genotypes was not considered. In this study, we used parametric analyses assuming dominant and recessive transmission and specifying a maximum penetrance of 70%, so that information from unaffecteds could be weighed in the linkage analyses. As in previous linkage analyses of these pedigrees, we analyzed three diagnostic categories: model 1 included only bipolar I and schizoaffective, bipolar cases (1565 patients of whom approximately 4% were schizoaffective, bipolar); model 2 included all individuals in model 1 plus bipolar II patients (1764 total individuals); and model 3 included all individuals in model 2 with the addition of patients with recurrent major depressive disorder (2046 total persons). RESULTS: Assuming dominant inheritance the highest genome-wide pair-wise logarithm of the odds (LOD) score was 3.2 with D16S749 using model 2 patients. Multipoint analyses of this region yielded a maximum LOD score of 4.91. Under recessive transmission a number of chromosome 20 markers were positive and multipoint analyses of the area gave a maximum LOD of 3.0 with model 2 cases. CONCLUSION: The chromosome 16p and 20 regions have been implicated by some studies and the data reported herein provide additional suggestive evidence of bipolar susceptibility genes in these regions

Panel Discussion: Missing Pieces in the ACA Puzzle

Ronald Bloom, PhD (Moderator)Professor and Acting Dean, School of Health Sciences and Human Services Hofstra University Deborah Bae, MPA, MBA Senior Program Officer Robert Wood Johnson Foundation Joel Weintraub, MD, JD Special Professor of Law Maurice A. Deane School of Law at Hofstra University Assistant Professor of Ophthalmology Hofstra North Shore-LIJ School of Medicine Brad Wright, PhD Assistant Professor, Department of Health Management and Policy The University of Iowa Victor Badner, DMD, MPH Chairman, Department of Dentistry, Oral and Maxillofacial Surgery Jacobi Medical Center and North Central Bronx Hospita

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

The use of intraoperative nitrous oxide leads to postoperative increases in plasma homocysteine

Hyperhomocysteinemia is an independent risk factor for coronary artery and cerebrovascular disease, but its significance in the perioperative period is unknown. Nitrous oxide inhibits methionine synthase, which aids in the conversion of homocysteine to methionine. In this prospective, controlled, randomized study, we determined the effect of intraoperative nitrous oxide exposure on postoperative plasma homocysteine concentrations. Twenty ASA physical status I-III patients, aged \u3e18 yr, presenting for elective craniotomy, were randomized to receive general anesthesia with or without nitrous oxide (inspired nitrous oxide \u3e50%). Plasma was sampled before the induction of anesthesia, on arrival in the postanesthesia care unit (PACU) after discontinuation of nitrous oxide, and 24 h after induction. There was a significant increase (22.6 ± 11.4 vs 13.0 ± 4.7 μmol/L; P = 0.0038 for postoperative versus preinduction values) in plasma homocysteine concentrations in the nitrous oxide group on arrival in the PACU and for 24 h. In the nonnitrous oxide group, mean plasma homocysteine concentrations did not change (9.5 ± 1.9 vs 9.8 ± 1.6 μmol/L; P = 0.86 for postoperative versus preinduction values). The change in plasma homocysteine concentrations in the nitrous oxide group was significantly different from that in the nonnitrous group (P = 0.0031). We conclude that the use of intraoperative nitrous oxide leads to significant increases in perioperative plasma homocysteine concentrations. Implications: Short-term exposure to nitrous oxide led to significant increases in plasma homocysteine. Further investigations are required to determine the clinical significance of this change

Anesthesiologists' and surgeons' perceptions about routine pre-operative testing in low risk patients: application of the Theoretical Domains Framework to identify factors that influence physicians' decisions to order pre-operative tests

Background Routine pre-operative tests for anesthesia management are often ordered by both anesthesiologists and surgeons for healthy patients undergoing low-risk surgery. The Theoretical Domains Framework (TDF) was developed to investigate determinants of behaviour and identify potential behaviour change interventions. In this study, the TDF is used to explore anaesthesiologists’ and surgeons’ perceptions of ordering routine tests for healthy patients undergoing low-risk surgery. Conclusion We identified key factors that anesthesiologists and surgeons believe influence whether they order pre-operative tests routinely for anesthesia management for a healthy adults undergoing low-risk surgery. These beliefs identify potential individual, team, and organisation targets for behaviour change interventions to reduce unnecessary routine test ordering. Methods Sixteen clinicians (eleven anesthesiologists and five surgeons) throughout Ontario were recruited. An interview guide based on the TDF was developed to identify beliefs about preoperative testing practices. Content analysis of physicians’ statements into the relevant theoretical domains was performed. Specific beliefs were identified by grouping similar utterances of the interview participants. Relevant domains were identified by noting the frequencies of the beliefs reported, presence of conflicting beliefs, and perceived influence on the performance of the behaviour under investigation. Results Seven of the twelve domains were identified as likely relevant to changing clinicians’ behaviour about pre-operative test ordering for anesthesia management. Key beliefs were identified within these domains including: conflicting comments about who was responsible for the test-ordering (Social/professional role and identity); inability to cancel tests ordered by fellow physicians (Beliefs about capabilities and social influences); and the problem with tests being completed before the anesthesiologists see the patient (Beliefs about capabilities and Environmental context and resources). Often, tests were ordered by an anesthesiologist based on who may be the attending anesthesiologist on the day of surgery while surgeons ordered tests they thought anesthesiologists may need (Social influences). There were also conflicting comments about the potential consequences associated with reducing testing, from negative (delay or cancel patients’ surgeries), to indifference (little or no change in patient outcomes), to positive (save money, avoid unnecessary investigations) (Beliefs about consequences). Further, while most agreed that they are motivated to reduce ordering unnecessary tests (Motivation and goals), there was still a report of a gap between their motivation and practice (Behavioural regulation)

Comparison of Inter and Intra-Operator Differences for Cephalometric Landmark Identification on Three-Dimensional CBCT Images using Pro Plan CMF

Objective: To establish reliability of cephalometric landmark identification in threedimensions using ProPlan CMF software. Methods: Two orthodontist identified a series of 33 cephalometric landmarks on 20 CBCT scans of Class I, pre-orthodontic patients and repeated the landmark identification about two months later. Intraclass correlations (ICC) were calculated by landmark in the X, Y, and Z dimensions and F-test were used to assess difference in landmark location in the X, Y, and Z dimensions. Results: The majority of landmarks had good to excellent ICC for both inter- and intraobserver reliability. F-test also showed the majority of landmarks had no significant difference between the observers. Conclusion: Most landmarks showed good to very good reliability and reproducibility using ProPlan CMF, with some landmarks proving more reliable than others and further research is needed to establish the utility and practicality of three-dimensional cephalometrics as a common diagnostic tool in orthodontics

Removing Batch Effects in Analysis of Expression Microarray Data: An Evaluation of Six Batch Adjustment Methods

The expression microarray is a frequently used approach to study gene expression on a genome-wide scale. However, the data produced by the thousands of microarray studies published annually are confounded by “batch effects,” the systematic error introduced when samples are processed in multiple batches. Although batch effects can be reduced by careful experimental design, they cannot be eliminated unless the whole study is done in a single batch. A number of programs are now available to adjust microarray data for batch effects prior to analysis. We systematically evaluated six of these programs using multiple measures of precision, accuracy and overall performance. ComBat, an Empirical Bayes method, outperformed the other five programs by most metrics. We also showed that it is essential to standardize expression data at the probe level when testing for correlation of expression profiles, due to a sizeable probe effect in microarray data that can inflate the correlation among replicates and unrelated samples