Genomics & Genetics

A Whole-Genome Association Study of Major Determinants for Host Control of HIV-1.

Fellay, J et al., 2007.  Science 317(5840):944-947.

Abstract

Understanding why some people establish and maintain effective control of HIV-1 and others do not is a priority in the effort to develop new treatments for HIV/AIDS. Using a whole-genome association strategy, we identified polymorphisms that explain nearly 15% of the variation among individuals in viral load during the asymptomatic set-point period of infection. One of these is found within an endogenous retroviral element and is associated with major histocompatibility allele human leukocyte antigen (HLA)B*5701, whereas a second is located near the HLA-C gene. An additional analysis of the time to HIV disease progression implicated two genes, one of which encodes an RNA polymerase I subunit. These findings emphasize the importance of studying human genetic variation as a guide to combating infectious agents.

Journal Link | PMID

Burkitt's Lymphoma -- The Message from Microarrays

Harris, NL & Horning, SJ, 2006. N. Eng. J. Med. 354(23):2495-2498

Intro. Paragraph

Two articles in this issue of the Journal, by Dave et al. and Hummel et al., report on the use of gene-expression microarray technology to improve the accuracy of the diagnosis of Burkitt's lymphoma. The two studies differ in many important ways, but both reach the same conclusion: the gene-expression profiling of cases classified as Burkitt's lymphoma by expert pathologists identifies a characteristic genetic signature that clearly distinguishes this tumor from cases of diffuse large-B-cell lymphoma. Furthermore, the microarray method seems to outperform the expert pathologists: 17 percent and 34 percent of cases with the gene-expression signature of Burkitt's lymphoma had been called diffuse large-B-cell lymphoma or unclassifiable high-grade B-cell lymphoma; 0.4 percent and 4 percent of cases without the Burkitt's signature had been called classic or atypical Burkitt's lymphoma; and 3 percent and 8 percent of cases diagnosed as diffuse large-B-cell lymphoma or unclassifiable high-grade B-cell lymphoma had a Burkitt's signature. . . .

Journal Link | PMID

Old Suspects Found Guilty -- The First Genome Profile of Multiple Sclerosis.

Peltonen, L, 2007. N. Engl. J. Med. (in press); editorial for following article.

High-resolution genomewide association studies using panels of 300,000 to 1 million single-nucleotide polymorphisms (SNPs) aim to define genetic risk profiles of common diseases. These studies herald a fundamentally new opportunity to explore human biology and medicine, since they are unbiased by previous hypotheses or assumptions about the nature of genes that influence complex diseases. Underscoring the importance of this approach is the fact that many genetic variants identified as risk factors in type 2 diabetes and Crohn's disease by such studies have been localized to previously unsuspected pathways, to genes without a known function, or to noncoding regions of genes.

Since 1868, when multiple sclerosis was first described as a clinical entity by Charcot, scientists have tried to identify the underlying causal factors. Studies of twins, adopted children, and the epidemiology of multiple sclerosis indicate a complex set of causative factors — both genetic predisposition and largely unknown environmental factors are required to cause the disease. The importance of the genetic background is obvious from the concordance rate of multiple sclerosis in monozygotic twins of nearly 30%; siblings or dizygotic twins have a risk of 2%, still higher than the risk of 0.1% in the average Northern European population. A biologically significant genetic component is also implied by familial aggregation of patients and by incidence rates that vary among different ethnic groups, independently of geographic location. The prevalence of multiple sclerosis is high among Northern Europeans but low in African, Chinese, Japanese, and Saami populations.

Journal Link | PMID

Risk Alleles for Multiple Sclerosis Identified by a Genomewide Study.

Hafler, DA et al. & The International Multiple Sclerosis Genetics Consortium, 2007. N. Engl. J. Med. (in press)

Abstract

Background Multiple sclerosis has a clinically significant heritable component. We conducted a genomewide association study to identify alleles associated with the risk of multiple sclerosis. Methods We used DNA microarray technology to identify common DNA sequence variants in 931 family trios (consisting of an affected child and both parents) and tested them for association. For replication, we genotyped another 609 family trios, 2322 case subjects, and 789 control subjects and used genotyping data from two external control data sets. A joint analysis of data from 12,360 subjects was performed to estimate the overall significance and effect size of associations between alleles and the risk of multiple sclerosis. Results A transmission disequilibrium test of 334,923 single-nucleotide polymorphisms (SNPs) in 931 family trios revealed 49 SNPs having an association with multiple sclerosis (P<1x104); of these SNPs, 38 were selected for the second-stage analysis. A comparison between the 931 case subjects from the family trios and 2431 control subjects identified an additional nonoverlapping 32 SNPs (P<0.001). An additional 40 SNPs with less stringent P values (<0.01) were also selected, for a total of 110 SNPs for the second-stage analysis. Of these SNPs, two within the interleukin-2 receptor {alpha} gene (IL2RA) were strongly associated with multiple sclerosis (P=2.96x108), as were a nonsynonymous SNP in the interleukin-7 receptor {alpha} gene (IL7RA) (P=2.94x107) and multiple SNPs in the HLA-DRA locus (P=8.94x1081). Conclusions Alleles of IL2RA and IL7RA and those in the HLA locus are identified as heritable risk factors for multiple sclerosis.

Journal Link | PMID

Microarray Analysis and Tumor Classification

Quackenbush, J, 2006, N. Engl. J. Med. 354(23):2463-2472

Intro Paragraphs

DNA microarray analysis was first described in the mid-1990s as a means to probe the expression of thousands of genes simultaneously and was quickly adopted by the research community for the study of a wide range of biologic processes. Most of the early studies had a simple and powerful design: to compare two biologic classes in order to identify the differential expression of the genes in them — genes with potential relevance to a wide range of biologic processes, such as the progression of cancer, the causes of asthma, heart disease, and neuropsychiatric disorders and the analysis of factors associated with infertility.

Soon after microarrays were introduced, many researchers realized that the technique could be used to find new subclasses in disease states and identify biologic markers (biomarkers) associated with disease and that even the expression patterns of the genes could be used to distinguish subclasses of disease. This realization resulted in a proliferation of searches for patterns of expression that could be used to classify types of tumors and predict the outcome and response to chemotherapy. An example is the Netherlands breast-cancer study, which sought to distinguish between patients who had the same stage of disease but a different response to treatment and a different overall outcome. The study was motivated by the observation that the best clinical predictors of metastasis, including lymph-node status and histologic grade, did not adequately predict clinical outcome, with the result that many patients receive chemotherapy or hormonal therapy regardless of whether they need this additional treatment. The study searched for gene-expression signatures that would indicate which patients would benefit from adjuvant chemotherapy. By profiling tumors of young patients who had received only surgical treatment and searching for correlations with clinical outcome, a signature of poor prognosis consisting of 70 genes was identified and was predictive of a short interval to distant metastasis in patients with tumors that were lymph-node–negative. The analysis showed that microarray-based signatures could outperform clinically based predictions of outcome in identifying patients who would benefit most from adjuvant therapy. These initial results led to a more extensive study that showed that the 70-gene classification profile was a more powerful predictor of disease outcome in young patients with breast cancer than were standard systems based on clinical and histologic criteria.

Journal Link | PMID

Comments

This is an excellent, well-illustrated review of the use of gene expression microarrays in the diagnosis and staging of cancers.  In addition to figures which give a good technical overview there is a glossary table defining the various types of 'omics' and the differences in their applications to clinical situations.

Cancer Treatment Gets Personal: An Interactive Poster

Ramaswamy, S & the editorial staff, 2006. Science 312(5777):1162a

Intro. Paragraph

Science, with the assistance of scientific advisor Sridhar  of the Center for Cancer Research, Massachusetts General Hospital, has created a poster to accompany its 26 May 2006 special issue on the new science of cancer. The poster is designed to help readers understand the conceptual framework of the new, patient-centered model of cancer care that is emerging, and how it might ultimately be implemented. This interactive online version of the poster includes additional topics and Web links not covered in the print version, and is available free to all site visitors. (A PDF version of the print poster is available to individual and institutional subscribers to Science.)  There is also a link to related cancer resources printed in Science.

Journal Link

Comments

This poster is a good summary in itself but the interactive website is a very good at illustrating the application of genomics to the clinical aspects of cancer.  The points covered include the technical aspects of cancer diagnosis and staging plus the clinical approaches, both 'classical' and molecular.  The interactive nature of the website allows the viewer to follow one's interest in proceeding through the material.  In addition to the references included in the interactive video the link to cancer resources provide a wealth of documentation and details for the presented material.