The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index; none of the 41 sources its claims cite is checked for support yet.
Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes
Open accessAbstract
The molecular mechanisms involved in the development of type 2 diabetes are poorly understood. Starting from genome-wide genotype data for 1924 diabetic cases and 2938 population controls generated by the Wellcome Trust Case Control Consortium, we set out to detect replicated diabetes association signals through analysis of 3757 additional cases and 5346 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 insight 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.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
0 of 41 cited sources checked · 0 supported · 0 flagged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Replication was also obtained for SNPs within the CDKAL1 locus on chromosome 6, including rs9465871 and rs10946398.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The replication signal at rs10946398 was more striking (OR 1.14 [1.07-1.22], p=8.4×10−5) (Tables 1, S2).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Rs8050136 (mapping to the FTO [fat mass associated with obesity] gene region on chr16) was among a cluster of SNPs generating the strongest evidence for association outside TCF7L2 in the original scan (risk allele OR 1.27 [1.16-1.37] p=2.0×10−8) (Figure S1).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Genotyping of 21 representative SNPs generated evidence of replication (p<0.05) for three of these 9 regions (Tables 1, S2).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesNone of the sources cited for this claim could be matched to a paper in Crossref, so there is nothing to check it against.
In the paper
“Here, we describe how integration of data from the WTCCC scan and our own replication studies with similar information generated by the Diabetes Genetics Initiative [DGI] (6) and the Finland-United States Investigation of NIDDM Genetics [FUSION] (7) has identified several additional susceptibility variants for T2D.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not matchedcites [6] Diabetes Genetics Initiative Science this issue
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [7] Scott LJ Science this issue
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“All associated SNPs map to a large (90kb) intron within CDKAL1 (Figure 1).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“This SNP showed strong replication (OR 1.22 [1.12-1.32], p=5.4×10−7).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesThe paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Across all studies, combined evidence for association at CDKAL1 is compelling (p~4.1×10−11).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The third replicated association maps to the HHEX (homeobox, hematopoietically expressed) gene region on chromosome 10.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesA result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 3′ signal maps to sequence with no characterized genes, while the recombination interval enclosing the 5′ signal includes the full coding sequences of CDKN2B and CDKN2A (encoding p15INK4b and p16INK4a respectively).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passes
- It may state two separate claims as one. 23
- Probably not a substantial claim. 5
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We have detected expression of CDKAL1 mRNA in human pancreatic islet and skeletal muscle (Figure S2).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Although rs9465871 generated the stronger signal in the WTCCC scan, replication at this SNP was modest (p=0.023).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“A second signal from the WTCCC scan located ~100kb 5′ (rs564398, OR 1.16 [1.07-1.27], p=3.2×10−4) was weakly supported in the FUSION, but not the DGI scan (Tables 1, S3) and replicated in the UK RS samples (OR 1.12 [1.05-1.19], p=8.6×10−4) (Tables 1, S3).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Both DGI and FUSION studies showed modest, but consistent association signals generating strong combined evidence (p~5.7×10−10) for a role in T2D susceptibility (Tables 1, S3).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, we genotyped rs13266634 independently and obtained replication of the finding (risk allele OR 1.12 [1.05-1.18], p=7.0×10−5 in all UK data) and across all three studies (p~5.3×10−8, Tables 1, S4).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Of the remaining regions selected in the first wave, none showed any evidence of replication in UK samples (Table S2), and for none was there strong support from the DGI and FUSION scans.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Evidence for association in the WTCCC scan (OR 1.16 [1.06-1.27], p=8.6×10−4) is supported by nominal replication in UK samples (1.08 [1.01-1.15], p=0.03) and by DGI scan results (1.17 [1.04-1.32], p=4.4×10−3).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedCausal:correlational· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Replication was observed in UK samples (rs10811661:OR 1.18 [1.08-1.28], p=1.7×10−4), as well as DGI (p=2.2×10−5) and FUSION follow-up studies (rs2383208, p=9.7×10−3).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Rests on an assumption: The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Both CDKN2B and CDKN2A display high levels of expression in pancreatic islets and pituitary (Figure S2).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“As a result of the four GWA studies reported to date (5, 6, 7, 10), the number of genuine, replicated T2D susceptibility signals has climbed from 3 to 9 (adding HHEX/IDE, SLC30A8, CDKAL1, CDKN2A, IGF2BP2 and FTO).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not matchedcites [5] Donnelly P the WTCCC, personal communication Data from the Wellcome Trust Case Control Consortium scan
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [6] Diabetes Genetics Initiative Science this issue
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not matchedcites [7] Scott LJ Science this issue
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- Not checked yetcites [10] Sladek R Nature 2007 445 881 885 17293876 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“However, these loci explain only a small proportion of the observed familiality (the sibling relative risk, λs, attributable to all loci in the UK samples is only ~1.07).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“As we recently reported (9), this effect on T2D risk is mediated through a primary effect on adiposity, and adjustment for BMI abolishes the T2D association.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not matchedcites [9] Frayling TM Science Published online April 12 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
- Not matched
In the paper
“We considered only the 393,453 autosomal SNPs with minor allele frequency (MAF) exceeding 1% in both cases and controls and no extreme departure from Hardy Weinberg equilibrium (HWE) (p<10−4 in cases or controls) (8).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not checked yetcites [8] Materials and methods are available as supporting material on Science Online
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“we first submitted putative signals from the WTCCC study to additional quality control including cluster plot visualization and validation genotyping on a second platform (8).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not checked yetcites [8] Materials and methods are available as supporting material on Science Online
Load-bearingStrength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesProbably not a substantial claim. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“CDK5 has been implicated in the regulation of pancreatic beta cell function, through formation of p35/CDK5 complexes that downregulate insulin expression (11, 12).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
Strength:plain· not yet calibratedCausal:direct· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“analysis of 490,032 autosomal SNPs in 16,179 samples yielded 459,448 SNPs that passed initial quality control (5).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not checked yetcites [5] Donnelly P the WTCCC, personal communication Data from the Wellcome Trust Case Control Consortium scan
Strength:plain· not yet calibratedn = 16,179Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The other three loci (near CDKAL1, IGF2BP2 and CDKN2A), all showing extensive replication across the three studies represent novel T2D susceptibility loci.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Robust identification of variants with such effect sizes is only feasible with large-scale sample sets (13,965 individuals were typed in the present study).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
In the paper
“Cdkn2b overexpression is also causally related to islet hypoplasia and diabetes in murine models (23).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
- Not checked yetcites [23] Moritani M Mol. Cell Endocrinol 2005 229 175 184 15607541 source
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The relatively strict thresholds imposed for SNP selection in the first wave (i.e. point-wise p<10−5) help to limit false discovery, but many genuine susceptibility variants will fail to reach them.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“and is a powerful biological candidate (13, 14).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
Strength:boosted· not yet calibratedTests✓ Asserted: passes✗ Checkable: fails✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. It may be too vague to check against evidence. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“CDKN2A is a known tumour suppressor and its product, p16INK4a, inhibits CDK4 (cyclin-dependent kinase 4), a powerful regulator of pancreatic beta cell replication (19-21).”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
What the sources say
Tests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“While no signal is apparent in the FUSION study, this does not allow us to reject this association.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes? Load-bearing: unclear✓ Based: passesIt may state two separate claims as one.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“For 80% power to detect an OR of 1.11 (α=0.05), over 3,000 case-control pairs are needed.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Strength:plain· not yet calibratedn = 3,000Tests✓ Asserted: passes✓ Checkable: passes✗ Load-bearing: fails✓ Based: passesProbably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“It also generates insights into T2D pathogenesis emphasizing the likely importance of pathways involved in pancreatic beta cell development, regeneration and function.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Load-bearingStrength:hedged· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our study provides an important validation of the genome-wide indirect association mapping approach and a demonstration of the value of aggressive data sharing efforts.”
§ Multiple type 2 diabetes susceptibility genes following genome-wide association scan in UK samples > Abstract
Load-bearingStrength:boosted· not yet calibratedTests✓ Asserted: passes✓ Checkable: passes✓ Load-bearing: passes✓ Based: passesIt may state two separate claims as one.
The paper relies on this without support.
The DGI and FUSION genome-wide association data are comparable enough to the WTCCC and UK replication data to be combined in meta-analysis.
“integration of data from the WTCCC scan and our own replication studies with similar information generated by the Diabetes Genetics Initiative [DGI] (6) and the Finland-United States Investigation of NIDDM Genetics [FUSION] (7)”
“Across all studies, combined evidence for association at CDKAL1 is compelling (p~4.1×10−11).”
The paper relies on this without support.
The replication sets RS1-RS3 are independent of the WTCCC samples and free from population stratification that would bias replication.
“we attempted replication of selected signals in up to 3,757 additional cases and 5,346 controls (replication sets RS1-RS3).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“These studies identified single-nucleotide polymorphisms (SNPs) in the second intron of the IGF2BP2 gene, particularly rs4402960 and rs1470579, as being significantly associated with an increased risk of T2D across various populations.”
From IMPlications of IMP2 in RNA Biology and Disease (2025) · cites this paper as [71]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“This idea, combined with the development of efficient methods for surveying large numbers of SNPs, has led to the many recent genome-wide association (GWA) studies that have detected SNPs that are significantly associated with breast cancer79,80, colorectal cancer81,82, type 2 diabetes83–86 and heart disease87,88, among other diseases.”
From Linkage disequilibrium--understanding the evolutionary past and mapping the medical future. (2008) · cites this paper as [84]
The cited source says what the claim attributes to it.
In the citing paper
“The association between IMP2 and T2D was first identified through genome-wide association studies (GWAS) in 2007, with three independent research groups demonstrating a strong link between genetic variants in the IGF2BP2 gene and T2D risk [69,70,71].”
From IMPlications of IMP2 in RNA Biology and Disease (2025) · cites this paper as [71]
In the citing paper
“Strikingly, recent genome-wide association studies link the cyclin-dependent kinase inhibitors CDKN2A and CDKN2B (encoding p15Ink4b) and the cell cycle regulators CDC123 and CDKAL1 to the risk of type 2 diabetes [34–37].”
From Expansion of β-cell mass in response to pregnancy (2010) · cites this paper as [34]
In the citing paper
“The product of the Ink4a/Arf (Cdkn2a) locus, p16Ink4a (a negative regulator of CDK4 D-type cyclins), is thought to be involved in aging, and in genome-wide studies it has linked with type 2 diabetes (35,36).”
From Age-Dependent Decline in β-Cell Proliferation Restricts the Capacity of β-Cell Regeneration in Mice (2009) · cites this paper as [35]
In the citing paper
“Interestingly, several of the recently discovered risk loci for type 2 diabetes have been implicated in cell cycle control of β-cells and could theoretically influence adult β-cell mass or alter the timing of cell cycle exit of adult β-cells (36–39).”
From Adaptive β-Cell Proliferation Is Severely Restricted With Advanced Age (2009) · cites this paper as [37]
In the citing paper
“2) Most associations do not involve previous candidate genes. In some cases, GWAS results immediately suggest new biological hypotheses— for example, the role of complement factor H in age-related macular degeneration (77–79), FGFR2 in breast cancer (98), and CDKN2A and CDKN2B in T2D (99–101).”
From Genetic Mapping in Human Disease (2008) · cites this paper as [99]
In the citing paper
“Examples include the region at 8q24 associated with prostate, breast, and colon cancer, 300 kb from the nearest gene (103, 104), and the region at 9q21 associated with myocardial infarction and T2D, 150 kb from the nearest genes encoding CDKN2A and CDKN2B (99–101, 105–107).”
From Genetic Mapping in Human Disease (2008) · cites this paper as [99]
In the citing paper
“5) Some regions reveal surprising associations. For example, unexpected connections have emerged among T2D, inflammatory diseases (two loci), and cancer (four loci). A single intron of CDKAL1 was found to contain a SNP associated with T2D and insulin secretion defects (99–101, 116), and another with Crohn’s disease and psoriasis (117).”
From Genetic Mapping in Human Disease (2008) · cites this paper as [99]
Citations
Cites
A haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858
Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., Perry, J. R. B., Elliott, K. S., Lango, H., Rayner, N. W., et al. (2007) · Science · doi:10.1126/science.1141634 · Cited by 4,531
Self-citationA genome-wide association study identifies novel risk loci for type 2 diabetes
Sladek, R., Rocheleau, G., Rung, J., Dina, C., Shen, L., Serre, D., Boutin, P., Vincent, D., Belisle, A., Hadjadj, S., et al. (2007) · Nature · doi:10.1038/nature05616 · Cited by 2,993
Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels
Saxena, R., Voight, B. F., Lyssenko, V., Burtt, N. P., de Bakker, P. I. W., Chen, H., Roix, J. J., Kathiresan, S., Hirschhorn, J. N., Daly, M. J., et al. (2007) · Science · doi:10.1126/science.1142358 · Cited by 2,843
A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants
Scott, L. J., Mohlke, K. L., Bonnycastle, L. L., Willer, C. J., Li, Y., Duren, W. L., Erdos, M. R., Stringham, H. M., Chines, P. S., Jackson, A. U., et al. (2007) · Science · doi:10.1126/science.1142382 · Cited by 2,753
Type 2 diabetes: principles of pathogenesis and therapy
Stumvoll, M., Goldstein, B. J., & van Haeften, T. W. (2005) · The Lancet · doi:10.1016/s0140-6736(05)61032-x · Cited by 2,662
Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes
Grant, S. F. A., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Manolescu, A., Sainz, J., Helgason, A., Stefansson, H., Emilsson, V., Helgadottir, A., et al. (2006) · Nature Genetics · doi:10.1038/ng1732 · Cited by 2,287
The common PPARγ Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes
Altshuler, D., Hirschhorn, J. N., Klannemark, M., Lindgren, C. M., Vohl, M.-C., Nemesh, J., Lane, C. R., Schaffner, S. F., Bolk, S., Brewer, C., et al. (2000) · Nature Genetics · doi:10.1038/79216 · Cited by 1,766
Self-citationAligning Multiple Genomic Sequences With the Threaded Blockset Aligner
Blanchette, M., Kent, W. J., Riemer, C., Elnitski, L., Smit, A. F. A., Roskin, K. M., Baertsch, R., Rosenbloom, K., Clawson, H., Green, E. D., et al. (2004) · Genome Research · doi:10.1101/gr.1933104 · Cited by 1,452
A Fine-Scale Map of Recombination Rates and Hotspots Across the Human Genome
Myers, S., Bottolo, L., Freeman, C., McVean, G., & Donnelly, P. (2005) · Science · doi:10.1126/science.1117196 · Cited by 1,134
Flagged first, then by citations
Research works printed but not linked: 1
- Wellcome Trust Case Control Consortium Nature in press.
Cited by
Sorted by citations
Items 301–400 of 1,004
The Roles of Insulin-Like Growth Factor 2 mRNA-Binding Protein 2 in Cancer and Cancer Stem Cells
Cao, J., Mu, Q., & Huang, H. (2018) · Stem Cells International · doi:10.1155/2018/4217259 · Cited by 159
Grarup, N., Andersen, G., Krarup, N. T., Albrechtsen, A., Schmitz, O., Jørgensen, T., Borch‐Johnsen, K., Hansen, T. F., & Pedersen, O. B. (2008) · Diabetes · doi:10.2337/db08-0436 · Cited by 158
The role of aging upon β cell turnover
Kushner, J. A. (2013) · Journal of Clinical Investigation · doi:10.1172/jci64095 · Cited by 167
Meta-Analysis of Genome-wide Association Studies with Overlapping Subjects
Lin, D.-Y., & Sullivan, P. F. (2009) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2009.11.001 · Cited by 156
Sachdeva, M. M., & Stoffers, D. A. (2009) · Molecular Endocrinology · doi:10.1210/me.2008-0400 · Cited by 162
Major review: Molecular genetics of primary open-angle glaucoma
Liu, Y., & Allingham, R. R. (2017) · Experimental Eye Research · doi:10.1016/j.exer.2017.05.002 · Cited by 156
Transferability of Type 2 Diabetes Implicated Loci in Multi-Ethnic Cohorts from Southeast Asia
Sim, X., Ong, R. T.-H., Suo, C., Tay, W.-T., Liu, J., Ng, D. P.-K., Boehnke, M., Chia, K.-S., Wong, T.-Y., Seielstad, M., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1001363 · Cited by 152
“It is noteworthy that the variants for which we were able to detect an association in our study were mostly discovered in the earlier wave of genome-wide scans for T2D (including CDKAL1, HHEX/IDE/KIF11, IGFBP2, SLC30A8 and FTO) [5–7,51].”
BackgroundResultGuilt beyond a reasonable doubt
Altshuler, D., & Daly, M. (2007) · Nature Genetics · doi:10.1038/ng0707-813 · Cited by 151
Zinc transporter 8 (ZnT8) and β cell function
Davidson, H. W., Wenzlau, J. M., & O’Brien, R. M. (2014) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2014.03.008 · Cited by 151
Lin, D. Y., & Zeng, D. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20435 · Cited by 156
Pathophysiology of Type 2 Diabetes in Children and Adolescents
Valaiyapathi, B., Gower, B. A., & Ashraf, A. P. (2019) · Current Diabetes Reviews · doi:10.2174/1573399814666180608074510 · Cited by 160
The IGF2BP family of RNA binding proteins links epitranscriptomics to cancer
Ramesh-Kumar, D., & Guil, S. (2022) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2022.05.009 · Cited by 155
Inherited basis of visceral, abdominal subcutaneous and gluteofemoral fat depots
Agrawal, S., Wang, M., Klarqvist, M. D. R., Smith, K., Shin, J. H., Dashti, H., Diamant, N., Choi, S. H., Jurgens, S. J., Ellinor, P. T., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30931-2 · Cited by 154
The genetics of diabetic complications
Ahlqvist, E., van Zuydam, N. R., Groop, L., & McCarthy, M. I. (2015) · Nature Reviews Nephrology · doi:10.1038/nrneph.2015.37 · Cited by 153
Self-citationHakonarson, H. H., Qu, H., Bradfield, J. P., Marchand, L., Kim, C., Glessner, J., Grabs, R., Casalunovo, T., Taback, S. P., Frackelton, E. C., et al. (2008) · Diabetes · doi:10.2337/db07-1305 · Cited by 153
Replication of Genome-Wide Association Studies of Type 2 Diabetes Susceptibility in Japan
Horikawa, Y., Miyake, K., Yasuda, K., Enya, M., Hirota, Y., Yamagata, K., Hinokio, Y., Oka, Y., Iwasaki, N., Iwamoto, Y., et al. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-0452 · Cited by 150
Autism genetics: strategies, challenges, and opportunities
O'Roak, B. J., & State, M. W. (2008) · Autism Research · doi:10.1002/aur.3 · Cited by 150
Genome-wide pharmacogenomic analysis of response to treatment with antipsychotics
McClay, J. L., Adkins, D. E., Åberg, K. A., Stroup, T. S., Perkins, D. O., Vladimirov, V. I., Lieberman, J. A., Sullivan, P. F., & van den Oord, E. J. C. G. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.89 · Cited by 150
A Noncoding RNA Antisense to Moesin at 5p14.1 in Autism
Kerin, T., Ramanathan, A., Rivas, K. L., Grepo, N., Coetzee, G. A., & Campbell, D. B. (2012) · Science Translational Medicine · doi:10.1126/scitranslmed.3003479 · Cited by 150
Lewis, J. P., Palmer, N. D., Hicks, P. J., Sale, M. M., Langefeld, C. D., Freedman, B. I., Divers, J., & Bowden, D. W. (2008) · Diabetes · doi:10.2337/db07-1319 · Cited by 149
Beyond odds ratios — communicating disease risk based on genetic profiles
Kraft, P. L., Wacholder, S., Cornelis, M. C., Hu, F. B., Hayes, R. B., Thomas, G. D., Hoover, R. N., Hunter, D. J., & Chanock, S. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2516 · Cited by 149
Pleiotropic genes for metabolic syndrome and inflammation
Kraja, A. T., Chasman, D. I., North, K. E., Reiner, A. P., Yanek, L. R., Kilpeläinen, T. O., Smith, J. A., Dehghan, A., Dupuis, J., Johnson, A. D., et al. (2014) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2014.04.007 · Cited by 149
Self-citationFat Mass–and Obesity-Associated (FTO) Gene Variant Is Associated With Obesity
Qi, L., Kang, K., Zhang, C., van Dam, R. M., Kraft, P. L., Hunter, D., Lee, C., & Hu, F. B. (2008) · Diabetes · doi:10.2337/db08-0006 · Cited by 147
Psoriasis and the risk of diabetes: A prospective population-based cohort study
Wan, M. T., Shin, D. B., Hubbard, R. A., Noe, M. H., Mehta, N. N., & Gelfand, J. M. (2017) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2017.10.050 · Cited by 147
Cornu, M., Yang, J.-Y., Jaccard, E., Poussin, C., Widmann, C., & Thorens, B. (2009) · Diabetes · doi:10.2337/db09-0063 · Cited by 152
Rong, R., Hanson, R. L., Ortiz, D., Wiedrich, C., Kobes, S., Knowler, W. C., Bogardus, C., & Baier, L. J. (2008) · Diabetes · doi:10.2337/db08-0877 · Cited by 146
Type 2 diabetes: genetic data sharing to advance complex disease research
Flannick, J. A., & Florez, J. C. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.56 · Cited by 148
Khoury, M. J., Bertram, L., Boffetta, P., Butterworth, A. S., Chanock, S. J., Dolan, S. M., Fortier, I., García‐Closas, M., GWINN, M. L., Higgins, J. P. T., et al. (2009) · American Journal of Epidemiology · doi:10.1093/aje/kwp119 · Cited by 146
Data Integration in Genetics and Genomics: Methods and Challenges
Hamid, J. S., Hu, P., Roslin, N. M., Ling, V., Greenwood, C. M. T., & Beyene, J. (2009) · Human Genomics and Proteomics · doi:10.4061/2009/869093 · Cited by 151
Age-Related Impairment of Pancreatic Beta-Cell Function: Pathophysiological and Cellular Mechanisms
Tata, V. D. (2014) · Frontiers in Endocrinology · doi:10.3389/fendo.2014.00138 · Cited by 157
What Can Genome-Wide Association Studies Tell Us about the Genetics of Common Disease?
Iles, M. M. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.0040033 · Cited by 145
Osman, W. M., Low, S., Takahashi, A., Kubo, M., & Nakamura, Y. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds103 · Cited by 145
Array-Based DNA Diagnostics: Let the Revolution Begin
Beaudet, A. L., & Belmont, J. W. (2007) · Annual Review of Medicine · doi:10.1146/annurev.med.59.012907.101800 · Cited by 144
Replication Study of Candidate Genes Associated With Type 2 Diabetes Based On Genome-Wide Screening
Tabara, Y., Osawa, H., Kawamoto, R., Onuma, H., Shimizu, I., Miki, T., Kohara, K., & Makino, H. (2008) · Diabetes · doi:10.2337/db07-1785 · Cited by 144
Type 2 Diabetes Risk Alleles Are Associated With Reduced Size at Birth
Freathy, R. M., Bennett, A. J., Ring, S. M., Shields, B. M., Groves, C. J., Timpson, N. J., Weedon, M. N., Zeggini, E., Lindgren, C. M., Allen, H. L., et al. (2009) · Diabetes · doi:10.2337/db08-1739 · Cited by 144
Self-citationGenome-wide association studies: progress and potential for drug discovery and development
Kingsmore, S. F., Lindquist, I. E., Mudge, J., Gessler, D. D. G., & Beavis, W. D. (2008) · Nature Reviews Drug Discovery · doi:10.1038/nrd2519 · Cited by 145
Wallace, D. C. (2008) · Genetics · doi:10.1534/genetics.104.91769 · Cited by 145
Genetic Analysis of Adult-Onset Autoimmune Diabetes
Howson, J. M. M., Rosinger, S., Smyth, D. J., Boehm, B. O., the ADBW-END Study Group, & Todd, J. A. (2011) · Diabetes · doi:10.2337/db11-0364 · Cited by 143
Liu, N., & Pan, T. (2014) · Translational research · doi:10.1016/j.trsl.2014.04.003 · Cited by 146
Schulze, M. B., Weikert, C., Pischon, T., Bergmann, M. M., Al‐Hasani, H., Schleicher, E. D., Fritsche, A., Häring, H., Boeing, H., & Joost, H. (2009) · Diabetes Care · doi:10.2337/dc09-0197 · Cited by 142
Genetic dissection of type 2 diabetes
Ridderstråle, M., & Groop, L. (2008) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2008.10.002 · Cited by 141
O’Donnell, C. J., Cupples, L. A., D’Agostino, R. B., Fox, C. S., Hoffmann, U., Hwang, S., Ingellson, E., Liu, C., Murabito, J. M., Polak, J. F., et al. (2007) · BMC Medical Genetics · doi:10.1186/1471-2350-8-s1-s4 · Cited by 139
Structural forms of the human amylase locus and their relationships to SNPs, haplotypes and obesity
Usher, C. L., Handsaker, R. E., Esko, T., Tuke, M. A., Weedon, M. N., Hastie, A. R., Cao, H., Moon, J. E., Kashin, S., Fuchsberger, C., et al. (2015) · Nature Genetics · doi:10.1038/ng.3340 · Cited by 139
Self-citationNutrigenomics research for personalized nutrition and medicine
Kaput, J. (2008) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2008.02.005 · Cited by 138
Simonis-Bik, A. M. C., Nijpels, G., van Haeften, T. W., Houwing‐Duistermaat, J. J., Boomsma, D. I., Reiling, E., van Hove, E. C., Diamant, M., Kramer, M. H. H., Heine, R. J., et al. (2009) · Diabetes · doi:10.2337/db09-1048 · Cited by 139
Detecting rare variants for complex traits using family and unrelated data
Zhu, X., Feng, T., Li, Y., Lu, Q. L., & Elston, R. C. (2009) · Genetic Epidemiology · doi:10.1002/gepi.20449 · Cited by 135
Molecular genetics in glaucoma
Liu, Y., & Allingham, R. R. (2011) · Experimental Eye Research · doi:10.1016/j.exer.2011.08.007 · Cited by 136
Worldwide population differentiation at disease-associated SNPs
Myles, S., Davison, D., Barrett, J. C., Stoneking, M., & Timpson, N. J. (2008) · BMC Medical Genomics · doi:10.1186/1755-8794-1-22 · Cited by 137
Self-citationBoesgaard, T. W., Zilinskaite, J., Vänttinen, M., Laakso, M., Jansson, P., Hammarstedt, A., Smith, U., Stefan, N., Fritsche, A., Häring, H., et al. (2008) · Diabetologia · doi:10.1007/s00125-008-0955-6 · Cited by 133
Pathomechanisms of Type 2 Diabetes Genes
Staiger, H., Machicao, F. E., Fritsche, A., & Häring, H.-U. (2009) · Endocrine Reviews · doi:10.1210/er.2009-0017 · Cited by 141
McClay, J. L., Shabalin, A. A., Dozmorov, M. G., Adkins, D. E., Kumar, G., Nerella, S., Clark, S. L., Bergen, S. E., Hultman, C. M., Magnusson, P. K. E., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0842-7 · Cited by 141
Recent advances in the molecular genetics of type 2 diabetes mellitus
Brunetti, A., CHIEFARI, E. D., & FOTI, D. P. (2014) · World Journal of Diabetes · doi:10.4239/wjd.v5.i2.128 · Cited by 137
How to Use an Article About Genetic Association
Attia, J., Ioannidis, J. P. A., Thakkinstian, A., McEvoy, M., Scott, R. J., Minelli, C., Thompson, J. R., Infante‐Rivard, C., & Guyatt, G. H. (2009) · JAMA · doi:10.1001/jama.2008.946 · Cited by 131
Genomewide Association Study of Movement-Related Adverse Antipsychotic Effects
Åberg, K., Adkins, D. E., Bukszár, J., Webb, B. T., Caroff, S. N., Miller, D. D., Sebat, J., Stroup, S., Fanous, A. H., Vladimirov, V. I., et al. (2010) · Biological Psychiatry · doi:10.1016/j.biopsych.2009.08.036 · Cited by 130
Genetics and Genomics for the Prevention and Treatment of Cardiovascular Disease: Update
Ganesh, S. K., Arnett, D. K., Assimes, T. L., Basson, C. T., Chakravarti, A., Ellinor, P. T., Engler, M. B., Goldmuntz, E., Herrington, D. M., Hershberger, R. E., et al. (2013) · Circulation · doi:10.1161/01.cir.0000437913.98912.1d · Cited by 130
Learning From Molecular Genetics
McCarthy, M. I., & Hattersley, A. T. (2008) · Diabetes · doi:10.2337/db08-0343 · Cited by 132
Self-citationJustice, J. N., Gregory, H., Tchkonia, T., LeBrasseur, N. K., Kirkland, J. L., Kritchevsky, S. B., & Nicklas, B. J. (2018) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glx134 · Cited by 129
Bioenergetics, the origins of complexity, and the ascent of man
Wallace, D. C. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914635107 · Cited by 134
Identification of Type 2 Diabetes Genes in Mexican Americans Through Genome-Wide Association Studies
Hayes, M. G., Pluzhnikov, A., Miyake, K., Sun, Y., Ng, M. C. Y., Roe, C. A., Below, J. E., Nicolae, R. I., Konkashbaev, A. I., Bell, G. I., et al. (2007) · Diabetes · doi:10.2337/db07-0482 · Cited by 129
Insights into pancreatic islet cell dysfunction from type 2 diabetes mellitus genetics
Krentz, N. A. J., & Gloyn, A. L. (2020) · Nature Reviews Endocrinology · doi:10.1038/s41574-020-0325-0 · Cited by 129
Parra, E. J., Below, J. E., Krithika, S., Valladares, A., Barta, J. L., Cox, N. J., Hanis, C. L., Wacher, N. H., Garcı́a-Mena, J., Hu, P., et al. (2011) · Diabetologia · doi:10.1007/s00125-011-2172-y · Cited by 128
A variant in FTO shows association with melanoma risk not due to BMI
Iles, M. M., Harland, M., Taylor, J., Randerson‐Moor, J. A., Snowden, H. H., Bishop, D. T., Newton‐Bishop, J., Barrett, J. H., Law, M. H., MacGregor, S., et al. (2013) · Nature Genetics · doi:10.1038/ng.2571 · Cited by 136
Self-citationDoria, A. (2008) · JAMA · doi:10.1001/jama.2008.649 · Cited by 127
Timpson, N. J., Lindgren, C. M., Weedon, M. N., Randall, J. C., Ouwehand, W. H., Strachan, D. P., Rayner, N. W., Walker, M., Hitman, G. A., Doney, A. S. F., et al. (2008) · Diabetes · doi:10.2337/db08-0906 · Cited by 128
Self-citationZinc, pancreatic islet cell function and diabetes: new insights into an old story
Chimienti, F. (2013) · Nutrition Research Reviews · doi:10.1017/s0954422412000212 · Cited by 125
At-Risk Variant in TCF7L2 for Type II Diabetes Increases Risk of Schizophrenia
Hansen, T. F., Ingason, A., Djurovic, S., Melle, I. S., Fenger, M., Gústafsson, Ó., Jakobsen, K. D., Rasmussen, H. B., Tosato, S., Rietschel, M., et al. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.01.031 · Cited by 129
Wallace, D. C. (2013) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2012.0267 · Cited by 131
Wen, J., Rönn, T., Olsson, A., Yang, Z., Lu, B., Du, Y., Groop, L., Ling, C., & Ren-ming, H. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009153 · Cited by 124
Rafiq, S., Frayling, T. M., Murray, A., Hurst, A. J., Stevens, K. N., Weedon, M. N., Henley, W., Ferrucci, L., Bandinelli, S., Corsi, A.-M., et al. (2007) · Genes and Immunity · doi:10.1038/sj.gene.6364414 · Cited by 124
Self-citationHan, X., Luo, Y., Ren, Q., Zhang, X., Wang, F., Sun, X., Zhou, X., & Ji, L. (2010) · BMC Medical Genetics · doi:10.1186/1471-2350-11-81 · Cited by 126
Martino, T. A., & Sole, M. J. (2009) · Circulation Research · doi:10.1161/circresaha.109.206201 · Cited by 126
Jansen, J., Rosenkranz, E., Overbeck, S., Warmuth, S., Mocchegiani, E., Giacconi, R., Weiskirchen, R., Karges, W., & Rink, L. (2012) · The Journal of Nutritional Biochemistry · doi:10.1016/j.jnutbio.2011.09.008 · Cited by 124
Type 2 diabetes: pathogenesis and treatment
Stümvoll, M., Goldstein, B. J., & van Haeften, T. W. (2008) · The Lancet · doi:10.1016/s0140-6736(08)60932-0 · Cited by 127
Irizar, P. A., Schäuble, S., Esser, D., Groth, M., Frahm, C., Priebe, S., Baumgart, M., Hartmann, N., Marthandan, S., Menzel, U., et al. (2018) · Nature Communications · doi:10.1038/s41467-017-02395-2 · Cited by 127
Gaulton, K. J., Willer, C. J., Li, Y., Scott, L. J., Conneely, K. N., Jackson, A., Duren, W. L., Chines, P. S., Narisu, N., Bonnycastle, L. L., et al. (2008) · Diabetes · doi:10.2337/db07-1731 · Cited by 125
How to Use an Article About Genetic Association
Attia, J., Ioannidis, J. P. A., Thakkinstian, A., McEvoy, M., Scott, R. J., Minelli, C., Thompson, J. R., Infante‐Rivard, C., & Guyatt, G. H. (2009) · JAMA · doi:10.1001/jama.2008.901 · Cited by 124
Moragues, M., Comadran, J., Waugh, R., Milne, I., Flavell, A. J., & Russell, J. (2010) · Theoretical and Applied Genetics · doi:10.1007/s00122-010-1273-1 · Cited by 121
SNP-based pathway enrichment analysis for genome-wide association studies
Weng, L., Macciardi, F. M., Subramanian, A., Guffanti, G., Potkin, S. G., Yu, Z., & Xie, X. S. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-99 · Cited by 121
Yaghootkar, H., Lamina, C., Scott, R. A., Dastani, Z., Hivert, M., Warren, L. L., Stančáková, A., Buxbaum, S. G., Lyytikäinen, L., Henneman, P., et al. (2013) · Diabetes · doi:10.2337/db13-0128 · Cited by 121
Self-citationTargeting Insulin-Degrading Enzyme to Treat Type 2 Diabetes Mellitus
Tang, W. (2015) · Trends in Endocrinology and Metabolism · doi:10.1016/j.tem.2015.11.003 · Cited by 126
Cruz, M., Valladares‐Salgado, A., Garcı́a-Mena, J., Ross, K., Edwards, M., Ángeles-Martínez, J., Ortega‐Camarillo, C., Escobedo, J., Burguete-García, A. I., Wacher, N. H., et al. (2010) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.1082 · Cited by 119
Strategies and issues in the detection of pathway enrichment in genome-wide association studies
Hong, M., Yudi Pawitan, Y., Magnusson, P. K. E., & Prince, J. A. (2009) · Human Genetics · doi:10.1007/s00439-009-0676-z · Cited by 120
Wing, M. R., Ziegler, J. T., Langefeld, C. D., Ng, M. C. Y., Haffner, S. M., Norris, J. M., Goodarzi, M. O., & Bowden, D. W. (2009) · Human Genetics · doi:10.1007/s00439-009-0656-3 · Cited by 119
New gene variants alter type 2 diabetes risk predominantly through reduced beta-cell function
Perry, J. R. B., & Frayling, T. M. (2008) · Current Opinion in Clinical Nutrition & Metabolic Care · doi:10.1097/mco.0b013e32830349a1 · Cited by 119
Self-citationGenome-wide association studies and type 2 diabetes
Wheeler, E., & Barroso, I. (2011) · Briefings in Functional Genomics · doi:10.1093/bfgp/elr008 · Cited by 119
The Genetics of Type 2 Diabetes: A Realistic Appraisal in 2008
Florez, J. C. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-1345 · Cited by 118
Lin, X., Song, K. S., Lim, N., Yuan, X., Johnson, T., Abderrahmani, A., Vollenweider, P., Stirnadel-Farrant, H. A., Sundseth, S. S., Lai, E., et al. (2009) · Diabetologia · doi:10.1007/s00125-008-1254-y · Cited by 118
Self-citationBellomo, E. A., Meur, G., & Rutter, G. A. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.246082 · Cited by 119
Genetics Insights in the Relationship Between Type 2 Diabetes and Coronary Heart Disease
Goodarzi, M. O., & Rotter, J. I. (2020) · Circulation Research · doi:10.1161/circresaha.119.316065 · Cited by 119
Siontis, K. C. M., Patsopoulos, N. A., & Ioannidis, J. P. A. (2010) · European Journal of Human Genetics · doi:10.1038/ejhg.2010.26 · Cited by 117
Polymorphisms within the Novel Type 2 Diabetes Risk Locus MTNR1B Determine β-Cell Function
Staiger, H., Machicao, F. E., Schäfer, S., Kirchhoff, K., Kantartzis, K., Guthoff, M., Silbernagel, G., Stefan, N., Häring, H., & Fritsche, A. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003962 · Cited by 116
Developmental neuroscience perspectives on emotion regulation
Goldsmith, H. H., Pollak, S. D., & Davidson, R. J. (2008) · Child Development Perspectives · doi:10.1111/j.1750-8606.2008.00055.x · Cited by 114
Correlations between Psoriasis and Inflammatory Bowel Diseases
Skroza, N., Proietti, I., Pampena, R., Viola, G. L., Bernardini, N., Nicolucci, F., Tolino, E., Zuber, S., Soccodato, V., & Potenza, C. (2013) · BioMed Research International · doi:10.1155/2013/983902 · Cited by 114
Orchestration of Glucose Homeostasis
Bergman, R. N. (2007) · Diabetes · doi:10.2337/db07-9903 · Cited by 115
The Diverse Functions of IMP2/IGF2BP2 in Metabolism
Dai, N. (2020) · Trends in Endocrinology & Metabolism · doi:10.1016/j.tem.2020.05.007 · Cited by 114
Keck, M. E., Kern, N., Erhardt, A., Unschuld, P. G., Ising, M., Salyakina, D., Müller, M. B., Knorr, C. C., Lieb, R., Hohoff, C., et al. (2008) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.30750 · Cited by 117
Genetics and visceral leishmaniasis: of mice and man
Blackwell, J. M., Fakiola, M., Ibrahim, M. E., Jamieson, S. E., Jerônimo, S. M. B., Miller, E. N., Mishra, A., Mohamed, H. S., Peacock, C. S., RAJU, M., et al. (2009) · Parasite Immunology · doi:10.1111/j.1365-3024.2009.01102.x · Cited by 116
Senescent Cells and Their Secretory Phenotype as Targets for Cancer Therapy
Velarde, M. C., Demaria, M., & Campisi, J. (2013) · Interdisciplinary Topics in Gerontology and Geriatrics · doi:10.1159/000343572 · Cited by 112
SLC30A8 mutations in type 2 diabetes
Rutter, G. A., & Chimienti, F. (2014) · Diabetologia · doi:10.1007/s00125-014-3405-7 · Cited by 112
Brown, M. J. (2008) · Circulation · doi:10.1161/circulationaha.108.787630 · Cited by 112
Metadata
- Authors
- Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., Barrett, J. C., Shields, B., Morris, A. P., Ellard, S., Groves, C. J., Harries, L. W., Marchini, J. L., Owen, K. R., Knight, B., Cardon, L. R., Walker, M., Hitman, G. A., Morris, A. D., Doney, A. S. F., McCarthy, M. I., & Hattersley, A. T.
- Affiliations
- Centre for Human Genetics (GB)
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford, OX3 7LJ, UK.
- Corresponding author
- Zeggini, Eleftheria
- Weedon, Michael N.
- Lindgren, Cecilia M.
- Frayling, Timothy M.
- McCarthy, Mark I.
- Hattersley, Andrew T.
- ORCID
- Zeggini, Eleftheria
- Weedon, Michael N.
- Lindgren, Cecilia M.
- Frayling, Timothy M.
- Elliott, Katherine S.
- Timpson, Nicholas J.
- Perry, John R. B.
- Freathy, Rachel M.
- Barrett, Jeffrey C.
- Shields, Beverley
- Morris, Andrew P.
- Ellard, Sian
- Harries, Lorna W.
- Marchini, Jonathan L.
- Owen, Katharine R.
- Walker, Mark
- Hitman, Graham A.
- Morris, Andrew D.
- Doney, Alex S. F.
- McCarthy, Mark I.
- Hattersley, Andrew T.
- Venue
- Science
- Published
- 2007-06
- Volume
- 316
- Issue
- 5829
- Pages
- 1336-1341
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC3772310
- OpenAlex
- W1944558458
- Semantic Scholar
- 3acd41eeafe82b68094fdf0a487d8781b01fb790
- Cited by
- 2,194
- References
- 24
- Citations by year
- 2026: 13 · 2025: 32 · 2024: 36 · 2023: 28 · 2022: 29 · 2021: 51 · 2020: 56 · 2019: 52 · 2018: 66 · 2017: 78 · 2016: 80 · 2015: 108 · 2014: 121 · 2013: 121 · 2012: 159
- FWCI
- 178.50
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Discovery Research Portal (University of Dundee) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- Research Portal (Queen's University Belfast) (submittedVersion)
- Explore Bristol Research (submittedVersion)
- UEA Digital Repository (University of East Anglia) (submittedVersion)
- Newcastle University ePrints (Newcastle Univesity)
- Funders
- Wellcome Trust (090532, 518153, 083948)
- Leverhulme Trust
- Diabetes UK
- Research Councils UK
- European Commission
- Medical Research Council (G0000934)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Diabetes and associated disorders
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- type 2 diabetes, genetic susceptibility loci, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, SLC30A8, beta-cell function, genetic architecture, Wellcome Trust Case Control Consortium
- MeSH terms
- Adult, Aged, Chromosome Mapping, Diabetes Mellitus, Type 2, Female, United Kingdom, Humans, Introns, Male, Middle Aged, Transcription Factors, Meta-Analysis as Topic, Genome, Human, Case-Control Studies, Homeodomain Proteins, Insulin-Like Growth Factor Binding Proteins, Genes, p16, Genetic Predisposition to Disease, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
A language model drew the claims from the paper on 2026-10-06, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).
A second model labelled each claim on 2026-10-06 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
