Citations

Abstract A missense single-nucleotide polymorphism (SNP) in the immune modulatory gene IL1A has been associated with ovarian cancer risk (rs17561). Although the exact mechanism through which this SNP alters risk of ovarian cancer is not clearly understood, rs17561 has also been associated with risk of endometriosis, an epidemiologic risk factor for ovarian cancer. Interleukin-1α (IL1A) is both regulated by and able to activate NF-κB, a transcription factor family that induces transcription of many proinflammatory genes and may be an important mediator in carcinogenesis. We therefore tagged SNPs in more than 200 genes in the NF-κB pathway for a total of 2,282 SNPs (including rs17561) for genotype analysis of 15,604 cases of ovarian cancer in patients of European descent, including 6,179 of high-grade serous (HGS), 2,100 endometrioid, 1,591 mucinous, 1,034 clear cell, and 1,016 low-grade serous, including 23,235 control cases spanning 40 studies in the Ovarian Cancer Association Consortium. In this large population, we confirmed the association between rs17561 and clear cell ovarian cancer [OR, 0.84; 95% confidence interval (CI), 0.76–0.93; P = 0.00075], which remained intact even after excluding participants in the prior study (OR, 0.85; 95% CI, 0.75–0.95; P = 0.006). Considering a multiple-testing–corrected significance threshold of P < 2.5 × 10−5, only one other variant, the TNFSF10 SNP rs6785617, was associated significantly with a risk of ovarian cancer (low malignant potential tumors OR, 0.85; 95% CI, 0.79–0.91; P = 0.00002). Our results extend the evidence that borderline tumors may have a distinct genetic etiology. Further investigation of how these SNPs might modify ovarian cancer associations with other inflammation-related risk factors is warranted. Cancer Res; 74(3); 852–61. ©2013 AACR.

To assess the possible role of increased insulin clearance in the pathogenesis of the dawn phenomenon, we compared plasma free-insulin concentrations, free-insulin clearance rates, and plasma glucose concentrations in eight subjects with insulin-dependent diabetes mellitus (IDDM) during infusion of insulin from midnight to 0800 h (0.15 mU · kg−1 · min−1) with a Biostator and a Harvard pump. During infusion of insulin with the Biostator, plasma free insulin decreased 40% (from 14 ± 1 to 9 ± 1 μU/ml, P < .01), insulin clearance increased 54% (from 11 ± 1 to 17 ± 2 ml/min, P < .05), and plasma glucose increased from 101 ± 4 to 217 ± 27 mg/dl, P < .01. During infusion of insulin with the Harvard pump, neither plasma free insulin (14 ± vs. 13 ± 1 μU/ml) nor free-insulin clearance (12 ± 2 vs. 13 ± 2 ml/min) changed significantly, but plasma glucose increased from 100 ± 3 to 167 ± 21 mg/dl, P < .01. The increases in plasma glucose during infusion of insulin with the Biostator and the Harvard pump were not significantly different (t = 1.44, P = .19). When insulin was delivered directly into test tubes with the Biostator and the Harvard pump, insulin concentrations in the test tubes decreased 46% over 8 h (P < .05) with the Biostator, whereas no decrease was observed with the Harvard pump. We conclude that the dawn phenomenon can occur without an increase in insulin clearance and that the apparent overnight increase in insulin clearance observed in studies with the Biostator iS artifactual.

To compare glucose counter regulatory mechanisms during short-term hypoglycemia and prolonged hypoglycemia, insulin was infused either intravenously (160 mil · M−2 · min) for 10 min or subcutaneously (15 mU · M−2 · min) for 12 h in normal volunteers. With each type of insulin infusion, hypoglycemia (∼50 mg/dl) was either allowed to develop or was prevented (control experiments) by the glucose-clamp technique. During prolonged hypoglycemia, both increased glucose production (1.55 ± 0.05 versus 0.33 ± 0.14 mg · kg−1 · min in control experiments at 12 h, P < 0.01) and suppressed glucose utilization (1.55 ± 0.06 versus 3.17 ± 0.15 mg · kg−1 · min in control studies at 12 h, P < 0.01) were involved in counterregulation. During short-term hypoglycemia, only increased glucose production (3.23 ± 0.33 versus 0.06 ± 0.03 mg · kg−1 · min in control experiments at 60 min) was involved, since glucose clearance actually increased (3.99 ± 0.20 versus 2.88 ± 0.02 ml · kg−1 · min in control experiments at 60 min, P < 0.01). Estimated portal venous insulin concentrations decreased 40% (basal 24 ± 3 versus 14 ± 1 mU/ml at 60 min, P < 0.01) in the short-term hypoglycemia experiments but remained at basal levels (basal 25 ± 1 versus ∼26 μU/min between 1 and 12 h) during prolonged hypoglycemia. Despite the fact that hypoglycemia was more gradually induced in the prolonged hypoglycemia model, peak counterregulatory hormone responses were at least as great as those during short-term hypoglycemia. Plasma free fatty acids and ketone bodies increased 150–200% above basal (both P < 0.01) with counterregulation during prolonged hypoglycemia but did not increase above basal levels with counterregulation during short-term hypoglycemia. Finally, plasma alanine remained unchanged during short-term hypoglycemia but decreased nearly 40% during prolonged hypoglycemia (basal 327 ± 20 versus 208 ± 21 μM at 12 h, P < 0.01). We conclude that glucose counterregulatory mechanisms differ during short-term and prolonged hypoglycemia. In the former, only an increase in glucose production mediated by suppression of insulin secretion and increased glucagon secretion is involved, whereas during prolonged hypoglycemia, both a suppression of glucose utilization, and an increase in glucose production are important. These latter changes in glucose production and utilization may be influenced by changes in circulating nonglucose substrates (e.g., alanine, free fatty acids, and ketone bodies) as well as by hormonal factors acting on both hepatic and extrahepatic tissues.

To ascertain whether the dawn phenomenon occurs in nondiabetic individuals and, if so, whether it is due to an increase in glucose production or a decrease in glucose utilization, we determined plasma concentrations of glucose, insulin, C-peptide, and counter regulatory hormones, as well as rates of glucose production, glucose utilization, and insulin secretion at one-halfhourly intervals between 1:00 and 9:00 a.m. in eight normal volunteers. After 5:30 a.m., plasma glucose, insulin, and C-peptide concentrations all increased significantly; rates of glucose production, glucose utilization, and insulin secretion also increased (all P < 0.05). Plasma cortisol, epinephrine, and norepinephrine increased significantly from nocturnal nadirs between 4:00 and 6:30 a.m. Plasma growth hormone, which had increased episodically between 1:00 and 4:30 a.m., decreased thereafter nearly 50% (P < 0.05). Plasma glucagon did not change significantly throughout the period of observation. These results indicate that a dawn-like phenomenon, initiated by an increase in glucose production, occurs in nondiabetic individuals. Thus, early morning increases in plasma glucose concentrations and insulin requirements observed in IDDM and NIDDM may be an exaggeration of a physiologic circadian variation in hepatic insulin sensitivity induced by antecedent changes in catecholamine and/or growth hormone secretion.

Recent advances in the burgeoning field of genome engineering are accelerating the realization of personalized therapeutics for cardiovascular disease. In the postgenomic era, sequence-specific gene-editing tools enable the functional analysis of genetic alterations implicated in disease. In partnership with high-throughput model systems, efficient gene manipulation provides an increasingly powerful toolkit to study phenotypes associated with patient-specific genetic defects. Herein, this review emphasizes the latest developments in genome engineering and how applications within the field are transforming our understanding of personalized medicine with an emphasis on cardiovascular diseases.

Objective Genome-wide association studies have identified a large number of single nucleotide polymorphisms (SNPs) associated with a wide array of cancer sites. Several of these variants demonstrate associations with multiple cancers, suggesting pleiotropic effects and shared biological mechanisms across some cancers. We hypothesised that SNPs previously associated with other cancers may additionally be associated with colorectal cancer. In a large-scale study, we examined 171 SNPs previously associated with 18 different cancers for their associations with colorectal cancer. Design We examined 13 338 colorectal cancer cases and 40 967 controls from three consortia: Population Architecture using Genomics and Epidemiology (PAGE), Genetic Epidemiology of Colorectal Cancer (GECCO), and the Colon Cancer Family Registry (CCFR). Study-specific logistic regression results, adjusted for age, sex, principal components of genetic ancestry, and/or study specific factors (as relevant) were combined using fixed-effect meta-analyses to evaluate the association between each SNP and colorectal cancer risk. A Bonferroni-corrected p value of 2.92×10 −4 was used to determine statistical significance of the associations. Results Two correlated SNPs—rs10090154 and rs4242382—in Region 1 of chromosome 8q24, a prostate cancer susceptibility region, demonstrated statistically significant associations with colorectal cancer risk. The most significant association was observed with rs4242382 (meta-analysis OR=1.12; 95% CI 1.07 to 1.18; p=1.74×10 −5 ), which also demonstrated similar associations across racial/ethnic populations and anatomical sub-sites. Conclusions This is the first study to clearly demonstrate Region 1 of chromosome 8q24 as a susceptibility locus for colorectal cancer; thus, adding colorectal cancer to the list of cancer sites linked to this particular multicancer risk region at 8q24.

Genetic College Many genomic elements in humans are associated with behavior, including educational attainment. In a genome-wide association study including more than 100,000 samples, Rietveld et al. (p. 1467 , published online 30 May; see the Perspective by Flint and Munafò ) looked for genes related to educational attainment in Caucasians. Small genetic effects at three loci appeared to impact educational attainment.