Breast tumor copy number aberration phenotypes and genomic instability

BACKGROUND: Genomic DNA copy number aberrations are frequent in solid tumors, although the underlying causes of chromosomal instability in tumors remain obscure. Genes likely to have genomic instability phenotypes when mutated (e.g. those involved in mitosis, replication, repair, and telomeres) are rarely mutated in chromosomally unstable sporadic tumors, even though such mutations are associated with some heritable cancer prone syndromes. METHODS: We applied array comparative genomic hybridization (CGH) to the analysis of breast tumors. The variation in the levels of genomic instability amongst tumors prompted us to investigate whether alterations in processes/genes involved in maintenance and/or manipulation of the genome were associated with particular types of genomic instability. RESULTS: We discriminated three breast tumor subtypes based on genomic DNA copy number alterations. The subtypes varied with respect to level of genomic instability. We find that shorter telomeres and altered telomere related gene expression are associated with amplification, implicating telomere attrition as a promoter of this type of aberration in breast cancer. On the other hand, the numbers of chromosomal alterations, particularly low level changes, are associated with altered expression of genes in other functional classes (mitosis, cell cycle, DNA replication and repair). Further, although loss of function instability phenotypes have been demonstrated for many of the genes in model systems, we observed enhanced expression of most genes in tumors, indicating that over expression, rather than deficiency underlies instability. CONCLUSION: Many of the genes associated with higher frequency of copy number aberrations are direct targets of E2F, supporting the hypothesis that deregulation of the Rb pathway is a major contributor to chromosomal instability in breast tumors. These observations are consistent with failure to find mutations in sporadic tumors in genes that have roles in maintenance or manipulation of the genome

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Comparison of glucose metabolism and anthropometry in women with previous gestational diabetes treated with metformin vs. insulin:9-year follow-up of two randomized trials

Abstract Introduction: The main aim was to study whether the long-term incidences of type 2 diabetes, pre-diabetes and metabolic syndrome differed between women who were treated with metformin or insulin for gestational diabetes. Material and methods: This 9-year follow-up study of two open-label randomized trials compares metformin and insulin treatments of gestational diabetes. In all, 165 women, 88 previously treated with insulin and 77 treated with metformin in the index pregnancy, were included in the analyses. An oral glucose tolerance test was performed, and measures of anthropometry, glucose metabolism, serum lipids and inflammatory markers were compared between the treatment groups. Disorders of glucose metabolism (pre-diabetes and type 2 diabetes) at the 9-year follow-up was the primary outcome of this study. This study was registered at ClinicalTrials.gov: NCT02417090. Results: The incidences of pre-diabetes and type 2 diabetes (40.3% vs. 46.6%, odds ratio [OR] 0.77, 95% CI 0.40–1.50, p = 0.51), type 2 diabetes (14.3% vs. 15.9%, OR 0.88, 95% CI 0.34–2.26, p = 0.94), pre-diabetes (26.0% vs. 30.7%, OR 0.79, 95% CI 0.38–1.65, p = 0.62), and metabolic syndrome (45.9% vs. 55.2%, OR 0.69, 95% CI 0.35–1.35, p = 0.31) were comparable between the metformin and insulin groups. Moreover, there were no evident differences in the individual measures of anthropometry, glucose metabolism including HOMA-insulin resistance, serum lipids or inflammatory markers between the two treatment groups. Conclusions: Treatment of gestational diabetes with metformin vs. insulin during pregnancy is unlikely to have diverging long-term effects on maternal anthropometry, glucose metabolism or serum lipids. From this perspective, both treatments may be considered in gestational diabetes

Metformin versus insulin therapy for gestational diabetes:effects on offspring anthropometrics and metabolism at the age of 9 years:a follow-up study of two open-label, randomized controlled trials

Abstract Aims: To compare anthropometrics, and lipid and glucose metabolism in the 9-year-old offspring of mothers treated with metformin or insulin for gestational diabetes mellitus (GDM). Materials and methods: This was a Finnish two-centre, 9-year follow-up study of two open-label, randomized controlled trials comparing the effects observed in the offspring of mothers who received metformin and insulin treatment for GDM. Measurements included anthropometrics, blood pressure, lipoproteins, and oral glucose tolerance tests. This study was registered with ClinicalTrials.gov, number NCT02417090. Results: At the age of 9 years 172 children (55% of the original study cohort, 82 from the metformin and 90 from the insulin group) participated in the study. No differences were found between the 9-year-old offspring groups in anthropometric variables, including body mass index and waist-to-height ratio. The offspring in the metformin group had higher high-density lipoprotein (HDL) cholesterol concentrations (1.72 vs. 1.54 mmol/L; P = 0.039) but lower low-density lipoprotein cholesterol (2.39 vs. 2.58 mmol/L; P = 0.046) and apolipoprotein B concentrations (0.63 vs. 0.67 g/L; P = 0.043) than the offspring in the insulin group. The difference in HDL cholesterol concentration was found to be significant only in boys (P = 0.003). The 2-hour glucose value in the oral glucose tolerance test was 0.6-mmol/L lower in boys from the metformin group than in those from the insulin group (P = 0.015). Conclusions: Metformin treatment for GDM is associated with similar offspring growth and glucose metabolism but a more favourable lipid profile at the age of 9 years as compared to insulin treatment

Metformin versus insulin for gestational diabetes:adiposity variables and adipocytokines in offspring at age of 9 years

Abstract Aims: To compare body composition, visceral adiposity, adipocytokines, and low-grade inflammation markers in prepubertal offspring of mothers who were treated with metformin or insulin for gestational diabetes mellitus (GDM). Methods: 172 offspring of 311 mothers randomized to receive metformin (n = 82) or insulin (n = 90) for GDM were studied at 9 years of age (follow-up rate 55%). Measurements included anthropometrics, adipocytokines, markers of the low-grade inflammation, abdominal magnetic resonance imaging (MRI), magnetic liver spectrometry (MRS), and whole body dual-energy X-ray absorptiometry (DXA). Results: Serum markers of low-grade inflammation, visceral adipose tissue volume, total fat percentage, and liver fat percentage were similar between the study groups. Serum adiponectin concentration was higher in children in the metformin group compared to insulin group (median 10.37 vs 9.50 µg/ml, p = 0.016). This difference between groups was observed in boys only (median 12.13 vs 7.50 µg/ml, p &lt; 0.001). Leptin/adiponectin-ratio was lower in boys in the metformin group than in the insulin group (median 0.30 vs 0.75; p = 0.016). Conclusions: Maternal metformin treatment for GDM had no effects on adiposity, body composition, liver fat, or inflammation markers in prepubertal offspring compared to maternal insulin treatment but was associated with higher adiponectin concentration and lower leptin/adiponectin-ratio in boys

Genome-Wide Significant SNPs from the Sex-Combined Multi-Ethnic Meta-Analysis.

<p>The novel loci identified using Multi-Ethnic Meta-analysis (that were not identified in the European only analysis) are listed in <b>bold</b>.</p>*<p>When possible, plausible biological candidate genes have been listed; otherwise, the closest gene is designated.</p>‡<p>Lead SNP is the SNP with the lowest <i>p</i>-value for each locus.</p>†<p>Positions are relative to Human Genome NCBI Build 36.</p>§<p>log₁₀ Bayes factor (BF) from the MANTRA analysis. A log₁₀ BF of 6 and higher was considered as a conservative threshold for genome-wide significance.</p>††<p>The posterior probability of heterogeneity between studies.</p>¶<p>EA: effect allele, NEA: non-effect allele.</p>¶¶<p>EAF: Frequency of effect allele in CEU, East Asian, and AA, populations respectively.</p

Regional plots of eight newly discovered genome-wide significant chromosomal regions associated with adiponectin concentrations in European populations.

<p>A) chromosome 16q23.2, B) chromosome 19 q13.11 C) Chromosome 3p21.1, D) two loci on chromosome 12q24.31, E) chromosome 8q24.13, F) chromosome 6p21.1, and G) chromosome 1q41. In each panel, purple diamonds indicate the top SNPs, which have the strongest evidence of association. Each circle shows a SNP with a color scale relating the r² value for that SNP and the top SNP from HapMap CEU. Blue lines indicate estimated recombination rates from HapMap. The bottom panels illustrate the relative position of genes near each locus. Candidate genes are indicated by red ovals.</p

The Association of Lead Genome-Wide Significant SNPs for Adiponectin with mRNA Levels of Their Nearest Gene.

‡<p>Lead SNP is the SNP with the lowest <i>p</i>-value for each gene in gene expression data.</p>‡‡<p>Lead SNP is the SNP with the lowest <i>p</i>-value for each locus in meta-analysis from discovery phase.</p>¶<p>EA: Effect allele.</p>¶¶<p>EAF: Frequency of effect allele.</p>§<p>Betas are estimated expression levels of the genes.</p>*<p>P value for lead SNP is the SNP in gene expression data.</p>**<p>P value for lead SNP in meta-analysis from discovery phase.</p>$<p>r² LD between lead SNP from expression and lead SNP from meta-analysis.</p

Flow chart of study design.

<p>Flow chart of study design.</p