High-resolution genomic analysis of human mitochondrial RNA sequence variation. Journal: Science| Pages: 413-415 |Date: April 2014 | Authors: Hodgkinson A, Idaghdour Y, Gbeha E, Grenier JC, Hip-Ki E, Bruat V, Goulet JP, de Malliard T, Awadalla P. Mutations in the mitochondrial genome are associated with multiple diseases and biological processes; however, little is known about the extent of sequence variation in the mitochondrial transcriptome. By ultra-deeply sequencing mitochondrial RNA (>6000×) from the whole blood of ~1000 individuals from the CARTaGENE project, we identified remarkable levels of sequence variation within and across individuals, as well as sites that show consistent patterns of posttranscriptional modification. Using a genome-wide association study, we find that posttranscriptional modification of functionally important sites in mitochondrial transfer RNAs (tRNAs) is under strong genetic control, largely driven by a missense mutation in MRPP3 that explains ~22% of the variance. These results reveal a major nuclear genetic determinant of posttranscriptional modification in mitochondria and suggest that tRNA posttranscriptional modification may affect cellular energy production. http://www.ncbi.nlm.nih.gov/pubmed/24763589

Recombination affects accumulation of damaging and disease-associated mutations in human populations. Journal: Nature Genetics| Pages: 400-404 |Date: April 2015 | Authors: Julie G Hussin, Alan Hodgkinson, Youssef Idaghdour, Jean-Christophe Grenier, Jean-Philippe Goulet, Elias Gbeha, Elodie Hip-Ki, Philip Awadalla Many decades of theory have demonstrated that, in non-recombining systems, slightly deleterious mutations accumulate non-reversibly, potentially driving the extinction of many asexual species. Non-recombining chromosomes in sexual organisms are thought to have degenerated in a similar fashion; however, it is not clear the extent to which damaging mutations accumulate along chromosomes with highly variable rates of crossing over. Using high-coverage sequencing data from over 1,400 individuals in the 1000 Genomes and CARTaGENE projects, we show that recombination rate modulates the distribution of putatively deleterious variants across the entire human genome. Exons in regions of low recombination are significantly enriched for deleterious and disease-associated variants, a signature varying in strength across worldwide human populations with different demographic histories. Regions with low recombination rates are enriched for highly conserved genes with essential cellular functions and show an excess of mutations with demonstrated effects on health, a phenomenon likely affecting disease susceptibility in humans. http://www.ncbi.nlm.nih.gov/pubmed/25685891

Cohorts and consortia conference: a summary report (Banff, Canada, June 17-19, 2009) Journal: Cancer Causes Control | Pages: 463-468 | Date: March 2011 | Authors: Boffetta P, Colditz GA, Potter JD, Kolonel L, Robson PJ, Malekzadeh R, Seminara D, Goode EL, Yoo KY, Demers P, Gallagher R, Prentice R, Yasui Y, O’Doherty K, Petersen GM, Ulrich CM, Csizmadi I, Amankwah EK, Brockton NT, Kopciuk K, McGregor SE, Kelemen LE. Epidemiologic studies have adapted to the genomics era by forming large international consortia to overcome issues of large data volume and small sample size. Whereas both cohort and well-conducted case-control studies can inform disease risk from genetic susceptibility, cohort studies offer the additional advantages of assessing lifestyle and environmental exposure-disease time sequences often over a life course. Consortium involvement poses several logistical and ethical issues to investigators, some of which are unique to cohort studies, including the challenge to harmonize prospectively collected lifestyle and environmental exposures validly across individual studies. An open forum to discuss the opportunities and challenges of large-scale cohorts and their consortia was held in June 2009 in Banff, Canada, and is summarized in this report.   http://www.ncbi.nlm.nih.gov/pubmed/21203821

Exploring statistical approaches to diminish subjectivity of cluster analysis to derive dietary patterns: The Tomorrow Project. Journal: Am J Epidemiol | Pages: 956-967 | Date: April 2011 | Authors: Lo Siou G, Yasui Y, Csizmadi I, McGregor SE, Robson PJ. Dietary patterns derived by cluster analysis are commonly reported with little information describing how decisions are made at each step of the analytical process. Using food frequency questionnaire data obtained in 2001-2007 on Albertan men (n = 6,445) and women (n = 10,299) aged 35-69 years, the authors explored the use of statistical approaches to diminish the subjectivity inherent in cluster analysis. Reproducibility of cluster solutions, defined as agreement between 2 cluster assignments, by 3 clustering methods (Ward’s minimum variance, flexible beta, K means) was evaluated. Ratios of between- versus within-cluster variances were examined, and health-related variables across clusters in the final solution were described. K means produced cluster solutions with the highest reproducibility. For men, 4 clusters were chosen on the basis of ratios of between- versus within-cluster variances, but for women, 3 clusters were chosen on the basis of interpretability of cluster labels and descriptive statistics. In comparison with those in other clusters, men and women in the “healthy” clusters by greater proportions reported normal body mass index, smaller waist circumference, and lower energy intakes. The authors’ approach appeared helpful when choosing the clustering method for both sexes and the optimal number of clusters for men, but additional analyses are required to understand why it performed differently for women. http://www.ncbi.nlm.nih.gov/pubmed/21421742

Potential novel candidate polymorphisms identified in genome-wide association study for breast cancer susceptibility. Journal: Hum Genet. | Pages: 529-537 | Date: October 2011 | Authors: Sehrawat B, Sridharan M, Ghosh S, Robson P, Cass CE, Mackey JR, Greiner R, Damaraju S. Previous genome-wide association studies (GWAS) have shown several risk alleles to be associated with breast cancer. However, the variants identified so far contribute to only a small proportion of disease risk. The objective of our GWAS was to identify additional novel breast cancer susceptibility variants and to replicate these findings in an independent cohort. We performed a two-stage association study in a cohort of 3,064 women from Alberta, Canada. In Stage I, we interrogated 906,600 single nucleotide polymorphisms (SNPs) on Affymetrix SNP 6.0 arrays using 348 breast cancer cases and 348 controls. We used single-locus association tests to determine statistical significance for the observed differences in allele frequencies between cases and controls. In Stage II, we attempted to replicate 35 significant markers identified in Stage I in an independent study of 1,153 cases and 1,215 controls. Genotyping of Stage II samples was done using Sequenom Mass-ARRAY iPlex platform. Six loci from four different gene regions (chromosomes 4, 5, 16 and 19) showed statistically significant differences between cases and controls in both Stage I and Stage II testing, and also in joint analysis. The identified variants were from EDNRA, ROPN1L, C16orf61 and ZNF577 gene regions. The presented joint analyses from the two-stage study design were not significant after genome-wide correction. The SNPs identified in this study may serve as potential candidate loci for breast cancer risk in a further replication study in Stage III from Alberta population or independent validation in Caucasian cohorts elsewhere. http://www.ncbi.nlm.nih.gov/pubmed/21424380

Quality, quantity and harmony: the DataSHaPER approach to integrating data across bioclinical studies. Journal: Int J Epidemiol | Pages: 1383-1393 | Date: September 2012 | Authors: Fortier I, Burton PR, Robson PJ, Ferretti V, Little J, L’Heureux F, Deschênes M, Knoppers BM, Doiron D, Keers JC, Linksted P, Harris JR, Lachance G, Boileau C, Pedersen NL, Hamilton CM, Hveem K, Borugian MJ, Gallagher RP, McLaughlin J, Parker L, Potter JD, Gallacher J, Kaaks R, Liu B, Sprosen T, Vilain A, Atkinson SA, Rengifo A, Morton R, Metspalu A, Wichmann HE, Tremblay M, Chisholm RL, Garcia-Montero A, Hillege H, Litton JE, Palmer LJ, Perola M, Wolffenbuttel BH, Peltonen L, Hudson TJ. BACKGROUND: Vast sample sizes are often essential in the quest to disentangle the complex interplay of the genetic, lifestyle, environmental and social factors that determine the aetiology and progression of chronic diseases. The pooling of information between studies is therefore of central importance to contemporary bioscience. However, there are many technical, ethico-legal and scientific challenges to be overcome if an effective, valid, pooled analysis is to be achieved. Perhaps most critically, any data that are to be analysed in this way must be adequately ‘harmonized’. This implies that the collection and recording of information and data must be done in a manner that is sufficiently similar in the different studies to allow valid synthesis to take place. METHODS: This conceptual article describes the origins, purpose and scientific foundations of the DataSHaPER (DataSchema and Harmonization Platform for Epidemiological Research; http://www.datashaper.org), which has been created by a multidisciplinary consortium of experts that was pulled together and coordinated by three international organizations: P³G (Public Population Project in Genomics), PHOEBE (Promoting Harmonization of Epidemiological Biobanks in Europe) and CPT (Canadian Partnership for Tomorrow Project). RESULTS: The DataSHaPER provides a flexible, structured approach to the harmonization and pooling of information between studies. Its two primary components, the ‘DataSchema’ and ‘Harmonization Platforms’, together support the preparation of effective data-collection protocols and provide a central reference to facilitate harmonization. The DataSHaPER supports both ‘prospective’ and ‘retrospective’ harmonization. CONCLUSIONS: It is hoped that this article will encourage readers to investigate the project further: the more the research groups and studies are actively involved, the more effective the DataSHaPER programme will ultimately be. http://www.ncbi.nlm.nih.gov/pubmed/20813861

The Canadian Partnership for Tomorrow Project: building a pan-Canadian research platform for disease prevention. Journal: CMAJ | Pages: 1197-1201 | Date: August 2010 | Authors: Borugian MJ, Robson P, Fortier I, Parker L, McLaughlin J, Knoppers BM, Bédard K, Gallagher RP, Sinclair S, Ferretti V, Whelan H, Hoskin D, Potter JD. As the proportion of the population over age 65 increases in Western countries, the burden of cancer 1 and other chronic diseases is also increasing. If advances in preventing these diseases are to be realized, better information is needed about their causes and the antecedents of the causes. For example, although it is known that many sporadic cancers are caused by a combination of lifestyle factors, exposure to environmental carcinogens and individual genetic makeup, 2,3 detailed knowledge about the interplay among these factors is lacking. Much of our current knowledge about the causes of cancer and most relatively rare chronic diseases has come from retrospective case–control studies, in which the characteristics of patients (cases) are compared with those of age- and sex-matched people who do not have the disease (controls). This design has strengths but also a number of weakneses, including potential recall bias and selection bias 4 (Table 1). To address some of these weaknesses, in particular recall bias and the temporal relation between risk factors and outcomes, prospective cohorts are helpful because participants are enrolled before the onset of disease. In studies with a prospective cohort design, large numbers of participants, who generally have not had cancer or any other significant diagnosis, are recruited and followed over a long time, periodically providing updated health and lifestyle information and biologic samples. Layers of data and samples accumulate over time, allowing an exploration of why cancer develops in some people within the cohort but not others. 6 The disadvantages of such a design (Table 1) are cost and time, as it may be a decade or more before major results are obtained. Fortunately, many shorter-term results are also available, such as information on screening attendance and information on the frequency of major risk factors and health states, as well as environmental and individual determinants of these risk factors, all of which are useful for planning various health services. Furthermore, because many diseases can be studied simultaneously, the cost over time per health outcome studied is substantially lower than the cost of case–control studies for a comparable number of participants. http://www.ncbi.nlm.nih.gov/pubmed/20421354