Background

Higher Lp-PLA2 activity is associated with increased risk of coronary heart disease (CHD), making Lp-PLA2 a potential therapeutic target. PLA2G7 variants associated with Lp-PLA2 activity could evaluate whether this relationship is causal.

Methods and Results

A meta-analysis including a total of 12 studies (5 prospective, 4 case-control, 1 case-only and 2 cross-sectional, n=26,118) was undertaken to examine the association of: (i) LpPLA2 activity vs. cardiovascular biomarkers and risk factors and CHD events (two prospective studies; n=4884); ii) PLA2G7 SNPs and Lp-PLA2 activity (3 prospective, 2 case-control, 2 cross-sectional studies; up to n=6094); and iii) PLA2G7 SNPs and angiographic coronary artery disease (2 case-control, 1 case-only study; n=4971 cases) and CHD events (5 prospective, 2 case-control studies; n=5523). Lp-PLA2 activity correlated with several CHD risk markers. Hazard ratio for CHD events top vs. bottom quartile of Lp-PLA2 activity was 1.61 (95%CI: 1.31, 1.99) and 1.17 (95%CI: 0.91, 1.51) after adjustment for baseline traits. Of seven SNPs, rs1051931 (A379V) showed the strongest association with Lp-PLA2 activity, VV subjects having 7.2% higher activity than AAs. Genotype was not associated with risk markers, angiographic coronary disease (OR 1.03 (95%CI 0.80, 1.32), or CHD events (OR 0.98 (95%CI 0.82, 1.17).

Conclusions

Unlike Lp-PLA2 activity, PLA2G7 variants associated with modest effects on Lp-PLA2 activity were not associated with cardiovascular risk markers, coronary atheroma or CHD. Larger association studies, identification of SNPs with larger effects, or randomised trials of specific Lp-PLA2 inhibitors are needed to confirm/refute a contributory role for Lp-PLA2 in CHD.

OBJECTIVE

The causal nature of associations between circulating triglycerides, insulin resistance, and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes and raise normal fasting glucose levels and hepatic insulin resistance.

RESEARCH DESIGN AND METHODS

We tested 10 common genetic variants robustly associated with circulating triglyceride levels against the type 2 diabetes status in 5,637 case and 6,860 control subjects and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8,271 nondiabetic individuals from four studies.

RESULTS

Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (SD 0.59 [95% CI 0.52–0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that the carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio [OR] 0.99 [95% CI 0.97–1.01]; P = 0.26). In nondiabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (SD 0.00 per weighted allele [95% CI −0.01 to 0.02]; P = 0.72) or increased fasting glucose levels (0.00 [−0.01 to 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose, or fasting insulin and, for diabetes, showed a trend toward a protective association (OR per 1-SD increase in log10 triglycerides: 0.61 [95% CI 0.45–0.83]; P = 0.002).

CONCLUSIONS

Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes or raise fasting glucose or fasting insulin levels in nondiabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

OBJECTIVE

Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels.

RESEARCH DESIGN AND METHODS

We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening.

RESULTS

Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c.

CONCLUSIONS

GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c.

Objective

The causal nature of associations between circulating triglycerides, insulin resistance and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes, raised normal fasting glucose levels, and hepatic insulin resistance.

Research design and methods

We tested 10 common genetic variants robustly associated with circulating triglyceride levels against type 2 diabetes status in 5637 cases, 6860 controls, and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8271 non-diabetic individuals from four studies.

Results

Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (0.59 SD [95% CI: 0.52, 0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio (OR) 0.99 [95% CI: 0.97, 1.01]; P = 0.26). In non-diabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (0.00 SD per weighted allele [95% CI: −0.01, 0.02]; P = 0.72) or increased fasting glucose levels (0.00 SD per weighted allele [95% CI: −0.01, 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose or fasting insulin, and, for diabetes, showed a trend towards a protective association (OR per 1 SD increase in log10-triglycerides: 0.61 [95% CI: 0.45, 0.83]; P = 0.002).

Conclusion

Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes, or raise fasting glucose or fasting insulin levels in non-diabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

Although experimental studies have suggested that insulin-like growth factor I (IGF-I) and its binding protein IGFBP-3 might have a role in the aetiology of coronary artery disease (CAD), the relevance of circulating IGFs and their binding proteins in the development of CAD in human populations is unclear. We conducted a nested case-control study, with a mean follow-up of six years, within the EPIC-Norfolk cohort to assess the association between circulating levels of IGF-I and IGFBP-3 and risk of CAD in up to 1,013 cases and 2,055 controls matched for age, sex and study enrolment date. After adjustment for cardiovascular risk factors, we found no association between circulating levels of IGF-I or IGFBP-3 and risk of CAD (odds ratio: 0.98 (95% Cl 0.90-1.06) per 1 SD increase in circulating IGF-I; odds ratio: 1.02 (95% Cl 0.94-1.12) for IGFBP-3). We examined associations between tagging single nucleotide polymorphisms (tSNPs) at the IGF1 and IGFBP3 loci and circulating IGF-I and IGFBP-3 levels in up to 1,133 cases and 2,223 controls and identified three tSNPs (rs1520220, rs3730204, rs2132571) that showed independent association with either circulating IGF-I or IGFBP-3 levels. In an assessment of 31 SNPs spanning the IGF1 or IGFBP3 loci, none were associated with risk of CAD in a meta-analysis that included EPIC-Norfolk and eight additional studies comprising up to 9,319 cases and 19,964 controls. Our results indicate that IGF-I and IGFBP-3 are unlikely to be importantly involved in the aetiology of CAD in human populations.

OBJECTIVE

Wolfram syndrome 1 (WFS1) single nucleotide polymorphisms (SNPs) are associated with risk of type 2 diabetes. In this study we aimed to refine this association and investigate the role of low-frequency WFS1 variants in type 2 diabetes risk.

RESEARCH DESIGN AND METHODS

For fine-mapping, we sequenced WFS1 exons, splice junctions, and conserved noncoding sequences in samples from 24 type 2 diabetic case and 68 control subjects, selected tagging SNPs, and genotyped these in 959 U.K. type 2 diabetic case and 1,386 control subjects. The same genomic regions were sequenced in samples from 1,235 type 2 diabetic case and 1,668 control subjects to compare the frequency of rarer variants between case and control subjects.

RESULTS

Of 31 tagging SNPs, the strongest associated was the previously untested 3′ untranslated region rs1046320 (P = 0.008); odds ratio 0.84 and P = 6.59 × 10−7 on further replication in 3,753 case and 4,198 control subjects. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2 = 0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (minor allele frequency [MAF] <0.01) nonsynonymous variants between type 2 diabetic case and control subjects (P = 0.79). Two intermediate frequency (MAF 0.01–0.05) nonsynonymous changes also showed no statistical association with type 2 diabetes.

CONCLUSIONS

We identified six highly correlated SNPs that show strong and comparable associations with risk of type 2 diabetes, but further refinement of these associations will require large sample sizes (>100,000) or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on type 2 diabetes risk in white U.K. populations, highlighting the complexities of undertaking association studies with low-frequency variants identified by resequencing.

OBJECTIVE

WFS1 (Wolfram Syndrome 1) SNPs are associated with risk of type 2 diabetes (T2D). Here, we aimed to refine this association and investigate the role of low frequency WFS1 variants in T2D risk.

RESEARCH DESIGN AND METHODS

For fine-mapping, we sequenced WFS1 exons, splice junctions and conserved non-coding sequences in 24 T2D cases and 68 controls, selected tagging SNPs, and genotyped these in 959 UK T2D cases and 1386 controls. The same genomic regions were sequenced in 1235 T2D cases and 1668 controls to compare the frequency of rarer variants between cases and controls.

RESULTS

Of 31 tagging SNPs, the strongest associated was the previously untested 3′ UTR rs1046320 (P=0.008); OR=0.84, P=6.59 × 10−7 on further replication in 3753 cases and 4198 controls. High correlation between rs1046320 and the original strongest SNP (rs10010131) (r2=0.92) meant that we could not differentiate between their effects in our samples. There was no difference in the cumulative frequency of 82 rare (MAF<0.01) non-synonymous variants between T2D cases and controls (P=0.79). Two intermediate frequency (MAF 0.01-0.05) non-synonymous changes also showed no statistical association with T2D.

CONCLUSION

We identified six highly correlated SNPs that show strong and comparable associations with risk of T2D association but further refinement of these associations will require large sample sizes (>100,000), or studies in ethnically diverse populations. Low frequency variants in WFS1 are unlikely to have a large impact on T2D risk in white UK populations, highlighting the complexities of undertaking association studies with low frequency variants identified by re-sequencing.

Previous studies have reported that shorter mean telomere length in lymphocytes is associated with increased susceptibility to common diseases of aging, and may be predictive of cancer risk. However, most analyses have examined retrospectively-collected case-control studies.

Mean telomere length was measured using high-throughput quantitative Real Time PCR. Blood for DNA extraction was collected after cancer diagnosis in the East Anglian SEARCH Breast (2243 cases, 2181 controls) and SEARCH Colorectal (2249 cases, 2161 controls) studies. Prospective case-control studies were conducted for breast cancer (199 cases) and colorectal cancer (185 cases), nested within the EPIC-Norfolk cohort. Blood has been collected at least 6 months prior to diagnosis, and was matched to DNA from two cancer-free controls per case.

In the retrospective, SEARCH studies, the age-adjusted Odds Ratios for shortest (Q4) vs. longest (Q1) quartile of mean telomere length was 15.5 (95%CI 11.6–20.8), p-het=5.7×10−75; with a ‘per quartile’ p-trend=2.1×10−80 for breast cancer, and 2.14 (95%CI 1.77–2.59), p-het=7.3×10−15; with a ‘per quartile’ p-trend=1.8×10−13 for colorectal cancer. In the prospective, EPIC study, the comparable Odds Ratios [Q4 vs. Q1] were 1.58 (95%CI 0.75–3.31), p-het=0.23 for breast cancer, and 1.13 (95%CI 0.54–2.36), p-het=0.75 for colorectal cancer risk.

Mean telomere length was shorter in retrospectively-collected cases than in controls but the equivalent association was markedly weaker in the prospective studies. This suggests that telomere shortening largely occurs after diagnosis, and may not, therefore, be of value in cancer prediction.

Background:

Cholesteryl ester transfer protein (CETP) inhibitors raise HDL-cholesterol but torcetrapib, the first-in-class inhibitor tested in a large outcome trial caused unexpected blood pressure elevation and increased cardiovascular events. Whether the hypertensive effect resulted from CETP-inhibition or an off-target action of torcetrapib has been debated. We hypothesised that common single nucleotide polymorphisms (SNPs) in the CETP-gene could help distinguish mechanism-based from off-target actions of CETP-inhibitors to inform on the validity of CETP as a therapeutic target.

Methods and Results

We compared the effect of CETP SNPs and torcetrapib treatment on lipid fractions, blood pressure and electrolytes in up to 67,687 individuals from genetic studies and 17,911 from randomised trials. CETP SNPs and torcetrapib treatment reduced CETP activity and had directionally concordant effect on eight lipid and lipoprotein traits (total-, LDL- and HDL-cholesterol, HDL2, HDL3, apolipoproteins A-I, -B, and triglycerides), with the genetic effect on HDL-cholesterol (0.13 mmol/L; 95% CI: 0.11, 0.14) being consistent with that expected of a 10 mg dose of torcetrapib (0.13 mmol/L; 0.10, 0.15). In trials, 60mg torcetrapib elevated systolic and diastolic blood pressure by 4.47mmHg (4.10, 4.84) and 2.08mmHg (1.84, 2.31) respectively. However, the effect of CETP SNPs on systolic 0.16mmHg (−0.28, 0.60) and diastolic blood pressure −0.04mmHg (−0.36, 0.28) was null and significantly different from that expected of 10 mg torcetrapib.

Conclusions:

Discordance in the effects of CETP SNPs and torcetrapib treatment on blood pressure despite the concordant effects on lipids indicates the hypertensive action of torcetrapib is unlikely to be due to CETP-inhibition, or shared by chemically dissimilar CETP inhibitors. Genetic studies could find use in drug development programmes as a new source of randomised evidence for drug target validation in man.

The peroxisome proliferator-activated receptor-γ gene (PPARG) has been implicated in the etiology of type 2 diabetes mellitus and has been investigated in numerous epidemiologic studies. In this Human Genome Epidemiology review, the authors assessed this relation in an updated meta-analysis of 60 association studies. Electronic literature searches were conducted on September 14, 2009. Population-based cohort, case-control, cross-sectional, or genome-wide association studies reporting associations between the PPARG Pro12Ala gene variant (rs1801282) and type 2 diabetes were included. An updated literature-based meta-analysis involving 32,849 type 2 diabetes cases and 47,456 controls in relation to the PPARG Pro12Ala variant was conducted. The combined overall odds ratio, calculated by per-allele genetic model random-effects meta-analysis for type 2 diabetes and the Pro12Ala polymorphism, was 0.86 (95% confidence interval: 0.81, 0.90). The analysis indicated a moderate level of heterogeneity attributable to genuine variation in gene effect size (I2 = 37%). This may reflect the variation observed between ethnic populations and/or differences in body mass index. Work on PPARG Pro12Ala should now focus on the observed heterogeneity in the magnitude of the association between populations. Further investigations into gene-gene and gene-environment interactions may prove enlightening.

Background

Paraoxonase-1 (PON1) is an antioxidant enzyme, that resides on high-density lipoprotein (HDL). PON1-activity, is heavily influenced by the PON1-Q192R polymorphism. PON1 is considered to protect against atherosclerosis, but it is unclear whether this relation is independent of its carrier, HDL. In order to evaluate the atheroprotective potential of PON1, we assessed the relationships among PON1-genotype, PON1-activity and risk of future coronary artery disease (CAD), in a large prospective case-control study.

Methodology/Principal Findings

Cases (n = 1138) were apparently healthy men and women aged 45–79 years who developed fatal or nonfatal CAD during a mean follow-up of 6 years. Controls (n = 2237) were matched by age, sex and enrollment time. PON1-activity was similar in cases and controls (60.7±45.3 versus 62.6±45.8 U/L, p = 0.3) and correlated with HDL-cholesterol levels (r = 0.16, p<0.0001). The PON1-Q192R polymorphism had a profound impact on PON1-activity, but did not predict CAD risk (Odds Ratio [OR] per R allele 0.98[0.84–1.15], p = 0.8). Using conditional logistic regression, quartiles of PON1-activity showed a modest inverse relation with CAD risk (OR for the highest versus the lowest quartile 0.77[0.63–0.95], p = 0.01; p-trend = 0.06). PON1-activity adjusted for Q192R polymorphism correlated better with HDL-cholesterol (r = 0.26, p<0.0001) and more linearly predicted CAD risk (0.79[0.64–0.98], p = 0.03; p-trend = 0.008). However, these relationships were abolished after adjustment for HDL (particles-cholesterol-size) and apolipoproteinA-I (0.94[0.74–1.18], p-trend = 0.3).

Conclusions/Significance

This study, shows that PON1-activity inversely relates to CAD risk, but not independent of HDL, due to its close association with the HDL-particle. These data strongly suggest that a low PON1-activity is not a causal factor in atherogenesis.

Background

Previous studies have suggested that a variant in the melanocortin-4 receptor (MC4R) gene is important in protecting against common obesity. Larger studies are needed, however, to confirm this relation.

Methods

We assessed the association between the V103I polymorphism in the MC4R gene and obesity in three UK population based cohort studies, totalling 8,304 individuals. We also did a meta-analysis of relevant studies, involving 10,975 cases and 18,588 controls, to place our findings in context.

Finding

In an analysis of all studies, individuals carrying the isoleucine allele had an 18% (95% CI 4-30%, p=0·015) lower risk of obesity compared with noncarriers. There was no heterogeneity among studies and no apparent publication bias.

Interpretation

This study confirms that the V103I polymorphism protects against human obesity at a population level. As such it provides proof of principle that specific gene variants may, at least in part, explain susceptibility and resistance to common forms of human obesity. A better understanding of the mechanisms underlying this association will help determine whether changes in MC4R activity have therapeutic potential.

Adult height is a model polygenic trait, but there has been limited success in identifying the genes underlying its normal variation. To identify genetic variants influencing adult human height, we used genome-wide association data from 13,665 individuals and genotyped 39 variants in an additional 16,482 samples. We identified 20 variants associated with adult height (P < 5 × 10−7, with 10 reaching P < 1 × 10−10). Combined, the 20 SNPs explain ~3% of height variation, with a ~5 cm difference between the 6.2% of people with 17 or fewer ‘tall’ alleles compared to the 5.5% with 27 or more ‘tall’ alleles. The loci we identified implicate genes in Hedgehog signaling (IHH, HHIP, PTCH1), extracellular matrix (EFEMP1, ADAMTSL3, ACAN) and cancer (CDK6, HMGA2, DLEU7) pathways, and provide new insights into human growth and developmental processes. Finally, our results provide insights into the genetic architecture of a classic quantitative trait.

We studied genes involved in pancreatic β cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.

Recent genome-wide (GW) scans have identified several independent loci affecting human stature, but their contribution through the different skeletal components of height is still poorly understood. We carried out a genome-wide scan in 12,611 participants, followed by replication in an additional 7,187 individuals, and identified 17 genomic regions with GW-significant association with height. Of these, two are entirely novel (rs11809207 in CATSPER4, combined P-value = 6.1×10−8 and rs910316 in TMED10, P-value = 1.4×10−7) and two had previously been described with weak statistical support (rs10472828 in NPR3, P-value = 3×10−7 and rs849141 in JAZF1, P-value = 3.2×10−11). One locus (rs1182188 at GNA12) identifies the first height eQTL. We also assessed the contribution of height loci to the upper- (trunk) and lower-body (hip axis and femur) skeletal components of height. We find evidence for several loci associated with trunk length (including rs6570507 in GPR126, P-value = 4×10−5 and rs6817306 in LCORL, P-value = 4×10−4), hip axis length (including rs6830062 at LCORL, P-value = 4.8×10−4 and rs4911494 at UQCC, P-value = 1.9×10−4), and femur length (including rs710841 at PRKG2, P-value = 2.4×10−5 and rs10946808 at HIST1H1D, P-value = 6.4×10−6). Finally, we used conditional analyses to explore a possible differential contribution of the height loci to these different skeletal size measurements. In addition to validating four novel loci controlling adult stature, our study represents the first effort to assess the contribution of genetic loci to three skeletal components of height. Further statistical tests in larger numbers of individuals will be required to verify if the height loci affect height preferentially through these subcomponents of height.

Author Summary

The first genetic association studies of adult height have confirmed a role of many common variants in influencing human height, but to date, the genetic basis of differences between different skeletal components of height have not been addressed. Here, we take advantage of recent technical and methodological advances to examine the role of common genetic variants on both height and skeletal components of height. By examining nearly 20,000 individuals from the UK and the Netherlands, we provide statistically significant evidence that 17 genomic regions are associated with height, including four novel regions. We also examine, for the first time, the association of these 17 regions with skeletal size measurements of spine, femur, and hip axis length, a measurement of hip geometry known to influence the risk of osteoporotic fractures. We find that some height loci are also associated with these skeletal components, although further statistical tests will be required to verify if these genetic variants act differentially on the individual skeletal measurements. The knowledge generated by this and other studies will not only inform the genetics of human quantitative variation, but will also lead to the potential discovery of many medically important polymorphisms.

Background

The growth hormone secretagogue receptor type 1a gene (GHSR) encodes the cognate receptor of ghrelin, a gut hormone that regulates food intake and pituitary growth hormone secretion. Previous studies in US families and in a German population suggested GHSR to be a candidate quantitative locus for association with human obesity and growth.

Aim

To test common genetic variation in GHSR for association with body size in children and adults.

Methods

Sequencing was performed to systematically identify novel single nucleotide polymorphisms (SNPs) in GHSR. A set of three haplotype-tagging (ht)SNPs was identified which captured all the genetic variation in GHSR. These three htSNPs were then genotyped in three large population-based UK cohort studies (two adult and one childhood cohort) comprising 5,807 adults and 843 children.

Results

No significant genotype or haplotype associations were found with adult or childhood height, weight or BMI.

Conclusion

Common variation in GHSR is not associated with body size in UK adults or children.

The imprinted insulin-like growth factor 2 (IGF2) gene is expressed predominantly from the paternal allele. Loss of imprinting (LOI) associated with hypomethylation at the promoter proximal sequence (DMR0) of the IGF2 gene was proposed as a predisposing constitutive risk biomarker for colorectal cancer. We used pyrosequencing to assess whether IGF2 DMR0 methylation is either present constitutively prior to cancer or whether it is acquired tissue-specifically after the onset of cancer. DNA samples from tumour tissues and matched non-tumour tissues from 22 breast and 42 colorectal cancer patients as well as peripheral blood samples obtained from colorectal cancer patients [SEARCH (n=case 192, controls 96)], breast cancer patients [ABC (n=case 364, controls 96)] and the European Prospective Investigation of Cancer [EPIC-Norfolk (n=breast 228, colorectal 225, controls 895)] were analysed. The EPIC samples were collected 2–5 years prior to diagnosis of breast or colorectal cancer. IGF2 DMR0 methylation levels in tumours were lower than matched non-tumour tissue. Hypomethylation of DMR0 was detected in breast (33%) and colorectal (80%) tumour tissues with a higher frequency than LOI indicating that methylation levels are a better indicator of cancer than LOI. In the EPIC population, the prevalence of IGF2 DMR0 hypomethylation was 9.5% and this correlated with increased age not cancer risk. Thus, IGF2 DMR0 hypomethylation occurs as an acquired tissue-specific somatic event rather than a constitutive innate epimutation. These results indicate that IGF2 DMR0 hypomethylation has diagnostic potential for colon cancer rather than value as a surrogate biomarker for constitutive LOI.

Background

The association between socioeconomic position in middle age and risk of subsequent, short-term weight gain is unknown. We therefore assessed this association in a prospective population based cohort study in Norfolk, UK.

Methods

We analysed data on 14,619 middle-aged men and women (aged between 40–75 at baseline) with repeated objective measures of weight and height at baseline (1993–1997) and follow up (1998–2000).

Results

During follow up 5,064 people gained more than 2.5 kg. Compared with the highest social class, individuals in the lowest social class had around a 30% greater risk of gaining more than 2.5 kg (OR 1.29; 95% CI 1.11–1.51; p for trend = 0.002). This association remained statistically significant following adjustment for sex, age, baseline BMI, smoking, and follow up time (OR 1.25; CI 1.07–1.46; p for trend <0.001). We also found no material difference between unadjusted models and those including all confounders and potential mediators.

Conclusion

Individuals of low socioeconomic position are at greatest risk of gaining weight during middle age, which is not explained by classical correlates of socioeconomic position and risk factors for obesity.

Summary

Background

LDL cholesterol has a causal role in the development of cardiovascular disease. Improved understanding of the biological mechanisms that underlie the metabolism and regulation of LDL cholesterol might help to identify novel therapeutic targets. We therefore did a genome-wide association study of LDL-cholesterol concentrations.

Methods

We used genome-wide association data from up to 11 685 participants with measures of circulating LDL-cholesterol concentrations across five studies, including data for 293 461 autosomal single nucleotide polymorphisms (SNPs) with a minor allele frequency of 5% or more that passed our quality control criteria. We also used data from a second genome-wide array in up to 4337 participants from three of these five studies, with data for 290 140 SNPs. We did replication studies in two independent populations consisting of up to 4979 participants. Statistical approaches, including meta-analysis and linkage disequilibrium plots, were used to refine association signals; we analysed pooled data from all seven populations to determine the effect of each SNP on variations in circulating LDL-cholesterol concentrations.

Findings

In our initial scan, we found two SNPs (rs599839 [p=1·7×10−15] and rs4970834 [p=3·0×10−11]) that showed genome-wide statistical association with LDL cholesterol at chromosomal locus 1p13.3. The second genome screen found a third statistically associated SNP at the same locus (rs646776 [p=4·3×10−9]). Meta-analysis of data from all studies showed an association of SNPs rs599839 (combined p=1·2×10−33) and rs646776 (p=4·8×10−20) with LDL-cholesterol concentrations. SNPs rs599839 and rs646776 both explained around 1% of the variation in circulating LDL-cholesterol concentrations and were associated with about 15% of an SD change in LDL cholesterol per allele, assuming an SD of 1 mmol/L.

Interpretation

We found evidence for a novel locus for LDL cholesterol on chromosome 1p13.3. These results potentially provide insight into the biological mechanisms that underlie the regulation of LDL cholesterol and might help in the discovery of novel therapeutic targets for cardiovascular disease.

Context

The Insulin-like Growth Factor 2 gene (IGF2) plays a key role in growth and is a candidate for association with obesity. Previous studies have reported that polymorphisms in IGF2 are associated with body weight and body mass index (BMI), but the results have been inconsistent. The primary aim of this study was to confirm the association with BMI, and secondarily to study the associations with other indices of body size.

Methods

In a sample of 2797 women and 2203 men aged 39–79 participating in the Norfolk arm of the European Prospective Investigation of Cancer (EPIC), we genotyped three SNPs in the IGF2 gene that were previously associated with BMI (6815 A/T, 1156 T/C (G/A), 820 G/A (ApaI)).

Results

No significant associations were observed between these SNPs and BMI. However, all three SNPs were significantly associated with height (p=0.03 to 0.001). In a backwards elimination regression analysis, two SNPs 1156 T/C (G/A) and 820 G/A remained independently associated with height (p=0.003 and p=0.038 respectively). Haplotype analysis of these two SNPs showed that carriers of the GA haplotype were shorter than carriers of each of the other three haplotypes (p<0.001 for all comparisons).

Conclusion

We did not confirm the previously reported associations between IGF2 polymorphisms and BMI. However our results suggest that common variation in the IGF2 gene may be associated with adult height. IGF2 could be considered as a candidate gene for future research on mechanisms for the association between height and chronic diseases such as cancer, diabetes and coronary heart disease.