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1.  Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples 
Science (New York, N.Y.)  2007;316(5829):1336-1341.
The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1,924 diabetic cases and 2,938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3,757 additional cases and 5,346 controls, and by integration of our findings with equivalent data from other international consortia. We detected diabetes susceptibility loci in and around the genes CDKAL1, CDKN2A/CDKN2B and IGF2BP2 and confirmed the recently described associations at HHEX/IDE and SLC30A8. Our findings provide insights into the genetic architecture of type 2 diabetes, emphasizing the contribution of multiple variants of modest effect. The regions identified underscore the importance of pathways influencing pancreatic beta cell development and function in the etiology of type 2 diabetes.
doi:10.1126/science.1142364
PMCID: PMC3772310  PMID: 17463249
2.  A common variant of HMGA2 is associated with adult and childhood height in the general population 
Nature genetics  2007;39(10):1245-1250.
Human height is a classic, highly heritable quantitative trait. To begin to identify genetic variants influencing height, we examined genome-wide association data from 4,921 individuals. Common variants in the HMGA2 oncogene, exemplified by rs1042725, were associated with height (P = 4 × 10−8). HMGA2 is also a strong biological candidate for height, as rare, severe mutations in this gene alter body size in mice and humans, so we tested rs1042725 in additional samples. We confirmed the association in 19,064 adults from four further studies (P = 3 × 10−11, overall P = 4 × 10−16, including the genome-wide association data). We also observed the association in children (P = 1 × 10−6, N = 6,827) and a tall/short case-control study (P = 4 × 10−6, N = 3,207). We estimate that rs1042725 explains ~0.3% of population variation in height (~0.4 cm increased adult height per C allele). There are few examples of common genetic variants reproducibly associated with human quantitative traits; these results represent, to our knowledge, the first consistently replicated association with adult and childhood height.
doi:10.1038/ng2121
PMCID: PMC3086278  PMID: 17767157
3.  Common Variation in the FTO Gene Alters Diabetes-Related Metabolic Traits to the Extent Expected Given Its Effect on BMI 
Diabetes  2008;57(5):1419-1426.
OBJECTIVE
Common variation in the FTO gene is associated with BMI and type 2 diabetes. Increased BMI is associated with diabetes risk factors, including raised insulin, glucose, and triglycerides. We aimed to test whether FTO genotype is associated with variation in these metabolic traits.
RESEARCH DESIGN AND METHODS
We tested the association between FTO genotype and 10 metabolic traits using data from 17,037 white European individuals. We compared the observed effect of FTO genotype on each trait to that expected given the FTO-BMI and BMI-trait associations.
RESULTS
Each copy of the FTO rs9939609 A allele was associated with higher fasting insulin (0.039 SD [95% CI 0.013–0.064]; P = 0.003), glucose (0.024 [0.001– 0.048]; P = 0.044), and triglycerides (0.028 [0.003– 0.052]; P = 0.025) and lower HDL cholesterol (0.032 [0.008 – 0.057]; P = 0.009). There was no evidence of these associations when adjusting for BMI. Associations with fasting alanine aminotransferase, γ-glutamyl-transferase, LDL cholesterol, A1C, and systolic and diastolic blood pressure were in the expected direction but did not reach P < 0.05. For all metabolic traits, effect sizes were consistent with those expected for the per allele change in BMI. FTO genotype was associated with a higher odds of metabolic syndrome (odds ratio 1.17 [95% CI 1.10 –1.25]; P = 3 × 10−6).
CONCLUSIONS
FTO genotype is associated with metabolic traits to an extent entirely consistent with its effect on BMI. Sample sizes of >12,000 individuals were needed to detect associations at P < 0.05. Our findings highlight the importance of using appropriately powered studies to assess the effects of a known diabetes or obesity variant on secondary traits correlated with these conditions.
doi:10.2337/db07-1466
PMCID: PMC3073395  PMID: 18346983
4.  Type 2 Diabetes Risk Alleles Are Associated With Reduced Size at Birth 
Diabetes  2009;58(6):1428-1433.
OBJECTIVE
Low birth weight is associated with an increased risk of type 2 diabetes. The mechanisms underlying this association are unknown and may represent intrauterine programming or two phenotypes of one genotype. The fetal insulin hypothesis proposes that common genetic variants that reduce insulin secretion or action may predispose to type 2 diabetes and also reduce birth weight, since insulin is a key fetal growth factor. We tested whether common genetic variants that predispose to type 2 diabetes also reduce birth weight.
RESEARCH DESIGN AND METHODS
We genotyped single-nucleotide polymorphisms (SNPs) at five recently identified type 2 diabetes loci (CDKAL1, CDKN2A/B, HHEX-IDE, IGF2BP2, and SLC30A8) in 7,986 mothers and 19,200 offspring from four studies of white Europeans. We tested the association between maternal or fetal genotype at each locus and birth weight of the offspring.
RESULTS
We found that type 2 diabetes risk alleles at the CDKAL1 and HHEX-IDE loci were associated with reduced birth weight when inherited by the fetus (21 g [95% CI 11–31], P = 2 × 10−5, and 14 g [4–23], P = 0.004, lower birth weight per risk allele, respectively). The 4% of offspring carrying four risk alleles at these two loci were 80 g (95% CI 39–120) lighter at birth than the 8% carrying none (Ptrend = 5 × 10−7). There were no associations between birth weight and fetal genotypes at the three other loci or maternal genotypes at any locus.
CONCLUSIONS
Our results are in keeping with the fetal insulin hypothesis and provide robust evidence that common disease-associated variants can alter size at birth directly through the fetal genotype.
doi:10.2337/db08-1739
PMCID: PMC2682672  PMID: 19228808
5.  Type 2 Diabetes Risk Alleles are Associated with Reduced Size at Birth 
Diabetes  2009;58(6):1428-1433.
Objective
Low birth weight is associated with an increased risk of type 2 diabetes. The mechanisms underlying this association are unknown and may represent intrauterine programming or two phenotypes of one genotype. The fetal insulin hypothesis proposes that common genetic variants that reduce insulin secretion or action may predispose to type 2 diabetes and also reduce birth weight, since insulin is a key fetal growth factor. We tested whether common genetic variants that predispose to type 2 diabetes also reduce birth weight.
Research design and methods
We genotyped single nucleotide polymorphisms (SNPs) at five recently identified type 2 diabetes loci (CDKAL1, CDKN2A/B, HHEX-IDE, IGF2BP2 and SLC30A8) in 7986 mothers and 19200 offspring from four studies of white Europeans. We tested the association between maternal or fetal genotype at each locus and birth weight of the offspring.
Results
We found that type 2 diabetes risk alleles at the CDKAL1 and HHEX-IDE loci were associated with reduced birth weight when inherited by the fetus: 21g [95%CI:11-31g], P=2×10-5 and 14g [4-23g], P=0.004 lower birth weight per risk allele, respectively. The 4% of offspring carrying four risk alleles at these two loci were 80g [39-120g] lighter at birth than the 8% carrying none (Ptrend =5×10-7). There were no associations between birth weight and fetal genotypes at the three other loci, or maternal genotypes at any locus.
Conclusions
Our results are in keeping with the fetal insulin hypothesis and provide robust evidence that common disease-associated variants can alter size at birth directly through the fetal genotype.
doi:10.2337/db08-1739
PMCID: PMC2682672  PMID: 19228808
6.  Assessing the Combined Impact of 18 Common Genetic Variants of Modest Effect Sizes on Type 2 Diabetes Risk 
Diabetes  2008;57(11):3129-3135.
OBJECTIVES—Genome-wide association studies have dramatically increased the number of common genetic variants that are robustly associated with type 2 diabetes. A possible clinical use of this information is to identify individuals at high risk of developing the disease, so that preventative measures may be more effectively targeted. Here, we assess the ability of 18 confirmed type 2 diabetes variants to differentiate between type 2 diabetic case and control subjects.
RESEARCH DESIGN AND METHODS—We assessed index single nucleotide polymorphisms (SNPs) for the 18 independent loci in 2,598 control subjects and 2,309 case subjects from the Genetics of Diabetes Audit and Research Tayside Study. The discriminatory ability of the combined SNP information was assessed by grouping individuals based on number of risk alleles carried and determining relative odds of type 2 diabetes and by calculating the area under the receiver-operator characteristic curve (AUC).
RESULTS—Individuals carrying more risk alleles had a higher risk of type 2 diabetes. For example, 1.2% of individuals with >24 risk alleles had an odds ratio of 4.2 (95% CI 2.11–8.56) against the 1.8% with 10–12 risk alleles. The AUC (a measure of discriminative accuracy) for these variants was 0.60. The AUC for age, BMI, and sex was 0.78, and adding the genetic risk variants only marginally increased this to 0.80.
CONCLUSIONS—Currently, common risk variants for type 2 diabetes do not provide strong predictive value at a population level. However, the joint effect of risk variants identified subgroups of the population at substantially different risk of disease. Further studies are needed to assess whether individuals with extreme numbers of risk alleles may benefit from genetic testing.
doi:10.2337/db08-0504
PMCID: PMC2570411  PMID: 18591388
7.  Genome-wide association analysis identifies 20 loci that influence adult height 
Nature genetics  2008;40(5):575-583.
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.
doi:10.1038/ng.121
PMCID: PMC2681221  PMID: 18391952
8.  Common variants in WFS1 confer risk of type 2 diabetes 
Nature genetics  2007;39(8):951-953.
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.
doi:10.1038/ng2067
PMCID: PMC2672152  PMID: 17603484
9.  A Common Variant in the FTO Gene Is Associated with Body Mass Index and Predisposes to Childhood and Adult Obesity 
Science (New York, N.Y.)  2007;316(5826):889-894.
Obesity is a serious international health problem that increases the risk of several common diseases. The genetic factors predisposing to obesity are poorly understood. A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI). An additive association of the variant with BMI was replicated in 13 cohorts with 38,759 participants. The 16% of adults who are homozygous for the risk allele weighed about 3 kilograms more and had 1.67-fold increased odds of obesity when compared with those not inheriting a risk allele. This association was observed from age 7 years upward and reflects a specific increase in fat mass.
doi:10.1126/science.1141634
PMCID: PMC2646098  PMID: 17434869
10.  A Genome-Wide Association Study Identifies Protein Quantitative Trait Loci (pQTLs) 
PLoS Genetics  2008;4(5):e1000072.
There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts – cis effects, and elsewhere in the genome – trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8×10−57), CCL4L1 (p = 3.9×10−21), IL18 (p = 6.8×10−13), LPA (p = 4.4×10−10), GGT1 (p = 1.5×10−7), SHBG (p = 3.1×10−7), CRP (p = 6.4×10−6) and IL1RN (p = 7.3×10−6) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8×10−40), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways.
Author Summary
One of the central dogmas of molecular genetics is that DNA is transcribed to RNA which is translated to protein and alterations to proteins can influence human diseases. Genome-wide association studies have recently revealed many new DNA variants that influence human diseases. To complement these efforts, several genome-wide studies have established that DNA variation influences mRNA expression levels. Loci influencing mRNA levels have been termed “eQTLs”. In this study we have performed the first genome-wide association study of the third piece in this jigsaw – the role of DNA variation in relation to protein levels, or “pQTLs”. We analysed 42 proteins measured in blood fractions from the InCHIANTI study. We identified eight cis effects including common variants in or near the IL6R, CCL4, IL18, LPA, GGT1, SHBG, CRP and IL1RN genes, all associated with blood levels of their respective protein products. Mechanisms implicated included altered transcription (GGT1) but also rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA) and variation in gene copy number (CCL4). Blood levels of many of these proteins are correlated with human diseases and the identification of “pQTLs” may in turn help our understanding of disease.
doi:10.1371/journal.pgen.1000072
PMCID: PMC2362067  PMID: 18464913

Results 1-10 (10)