McGill University

About: McGill University is a education organization based out in Montreal, Quebec, Canada. It is known for research contribution in the topics: Population & Context (language use). The organization has 72688 authors who have published 162565 publications receiving 6966523 citations. The organization is also known as: Royal institution of advanced learning & University of McGill College.

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

Abstract: Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.

International network of cancer genome projects

Abstract: The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic, epigenomic and transcriptomic levels will reveal the repertoire of oncogenic mutations, uncover traces of the mutagenic influences, define clinically relevant subtypes for prognosis and therapeutic management, and enable the development of new cancer therapies.

Global Mapping of the Yeast Genetic Interaction Network

Abstract: A genetic interaction network containing approximately 1000 genes and approximately 4000 interactions was mapped by crossing mutations in 132 different query genes into a set of approximately 4700 viable gene yeast deletion mutants and scoring the double mutant progeny for fitness defects. Network connectivity was predictive of function because interactions often occurred among functionally related genes, and similar patterns of interactions tended to identify components of the same pathway. The genetic network exhibited dense local neighborhoods; therefore, the position of a gene on a partially mapped network is predictive of other genetic interactions. Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.

Standardized nomenclature, symbols, and units for bone histomorphometry: A 2012 update of the report of the ASBMR Histomorphometry Nomenclature Committee

Abstract: Before publication of the original version of this report in 1987, practitioners of bone histomorphometry communicated with each other in a variety of arcane languages, which in general were unintelligible to those outside the field. The need for standardization of nomenclature had been recognized for many years,(1) during which there had been much talk but no action. To satisfy this need, B Lawrence Riggs (ASBMR President, 1985 to 1986) asked A Michael Parfitt to convene an ASBMR committee to develop a new and unified system of terminology, suitable for adoption by the Journal of Bone and Mineral Research (JBMR) as part of its Instructions to Authors. The resulting recommendations were published in 1987(2) and were quickly adopted not only by JBMR but also by all respected journals in the bone field. The recommendations improved markedly the ability of histomorphometrists to communicate with each other and with nonhistomorphometrists, leading to a broader understanding and appreciation of histomorphometric data. In 2012, 25 years after the development of the standardized nomenclature system, Thomas L Clemens (Editor in Chief of JBMR) felt that it was time to revise and update the recommendations. The original committee was reconvened by David W Dempster, who appointed one new member, Juliet E Compston. The original document was circulated to the committee members and was extensively revised according to their current recommendations. The key revisions include omission of terminology used before 1987, recommendations regarding the parameters and technical information that should be included in all histomorphometry articles, recommendations on how to handle dynamic parameters of bone formation in settings of low bone turnover, and updating of references.

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

Abstract: Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.