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 401–500 of 1,004
Genetics of Type 2 Diabetes: Insights into the Pathogenesis and Its Clinical Application
Sun, X., Yu, W., & Hu, C. (2014) · BioMed Research International · doi:10.1155/2014/926713 · Cited by 117
Mitochondrial dysfunction in pancreatic β-cells in Type 2 Diabetes
Mulder, H., & Ling, C. (2008) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2008.05.015 · Cited by 115
Becker, F., van El, C. G., Ibarreta, D., Zika, E., Hogarth, S., Borry, P., Cambon‐Thomsen, A., Cassiman, J. J., Evers‐Kiebooms, G., Hodgson, S. V., et al. (2011) · European Journal of Human Genetics · doi:10.1038/ejhg.2010.249 · Cited by 110
Gamboa-Meléndez, M. A., Huerta‐Chagoya, A., Moreno-Macías, H., Vázquez-Cárdenas, P., Ordóñez-Sánchez, M. L., Rodríguez-Guillén, R., Riba, L., Rodríguez-Torres, M., Guerra-García, M. T., Guillén-Pineda, L. E., et al. (2012) · Diabetes · doi:10.2337/db11-0550 · Cited by 111
Environmental Health and Long Non-coding RNAs
Karlsson, O., & Baccarelli, A. (2016) · Current Environmental Health Reports · doi:10.1007/s40572-016-0092-1 · Cited by 114
Association of Type 2 Diabetes Candidate Polymorphisms in KCNQ1 With Incretin and Insulin Secretion
Müssig, K., Staiger, H., Machicao, F. E., Kirchhoff, K., Guthoff, M., Schäfer, S., Kantartzis, K., Silbernagel, G., Stefan, N., Holst, J. J., et al. (2009) · Diabetes · doi:10.2337/db08-1589 · Cited by 110
Patel, C. J., Chen, R., Kodama, K., Ioannidis, J. P. A., & Butte, A. J. (2013) · Human Genetics · doi:10.1007/s00439-012-1258-z · Cited by 110
Imamura, M., Maeda, S., Yamauchi, T., Hara, K., Yasuda, K., Morizono, T., Takahashi, A., Horikoshi, M., Nakamura, M., Fujita, H., et al. (2012) · Human Molecular Genetics · doi:10.1093/hmg/dds113 · Cited by 112
Enrichment of sequencing targets from the human genome by solution hybridization
Tewhey, R., Nakano, M., Wang, X., Pabón-Peña, C., Novak, B. A., Giuffre, A. C., Lin, E., Happe, S., Roberts, D. N., LeProust, E. M., et al. (2009) · Genome biology · doi:10.1186/gb-2009-10-10-r116 · Cited by 119
Genetic Markers for Prediction of Normal Tissue Toxicity After Radiotherapy
Alsner, J., Andreassen, C. N., & Overgaard, J. (2008) · Seminars in Radiation Oncology · doi:10.1016/j.semradonc.2007.10.004 · Cited by 111
Support for Neuregulin 1 as a Susceptibility Gene for Bipolar Disorder and Schizophrenia
Georgieva, L., Dimitrova, A., Ivanov, D. K., Nikolov, I., Williams, N. M., Grozeva, D., Zaharieva, I. T., Toncheva, D. I., Owen, M. J., Kirov, G., et al. (2008) · Biological Psychiatry · doi:10.1016/j.biopsych.2008.03.025 · Cited by 109
Palmer, N., Goodarzi, M., Langefeld, C., Ziegler, J., Norris, J., Haffner, S., Bryer-Ash, M., Bergman, R., Wagenknecht, L., Taylor, K., et al. (2008) · Diabetes · doi:10.2337/db07-1169 · Cited by 124
The success of the genome-wide association approach: a brief story of a long struggle
Seng, K. C., & Seng, C. K. (2008) · European Journal of Human Genetics · doi:10.1038/ejhg.2008.12 · Cited by 111
Abnormal glucose tolerance and insulin secretion in pancreas-specific Tcf7l2-null mice
Xavier, G. D. S., Mondragon, A., Sun, G., Chen, L., McGinty, J., French, P. M. W., & Rutter, G. A. (2012) · Diabetologia · doi:10.1007/s00125-012-2600-7 · Cited by 111
Teo, Y. Y. (2008) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e3282f5dd77 · Cited by 110
Postolache, T. T., del Bosque‐Plata, L., Jabbour, S. A., Vergare, M. J., Wu, R., & Gragnoli, C. (2019) · American Journal of Medical Genetics Part B Neuropsychiatric Genetics · doi:10.1002/ajmg.b.32712 · Cited by 110
Gene–Environment Interactions and Susceptibility to Metabolic Syndrome and Other Chronic Diseases
Ordovás, J. M., & Shen, J. (2008) · Journal of Periodontology · doi:10.1902/jop.2008.080232 · Cited by 109
ATP-sensitive K + channels and disease: from molecule to malady
Ashcroft, F. M. (2007) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00348.2007 · Cited by 107
Liu, Y., Liu, Z., Song, Y., Zhou, D., Zhang, D., Zhao, T., Chen, Z., Yu, L., Yang, Y., Feng, G., et al. (2010) · Obesity · doi:10.1038/oby.2009.469 · Cited by 109
Investigation of Transport Mechanisms and Regulation of Intracellular Zn2+ in Pancreatic α-Cells
Gyulkhandanyan, A. V., Lu, H., Lee, S. C., Bhattacharjee, A., Wijesekara, N., Fox, J. E. M., MacDonald, P. E., Chimienti, F., Dai, F. F., & Wheeler, M. B. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m707005200 · Cited by 106
Required sample size and nonreplicability thresholds for heterogeneous genetic associations
Moonesinghe, R., Khoury, M. J., Liu, T., & Ioannidis, J. P. A. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0705554105 · Cited by 107
Zhai, G., Teumer, A., Stolk, L., Perry, J. R. B., Vandenput, L., Coviello, A. D., Koster, A., Bell, J. T., Bhasin, S., Eriksson, J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002025 · Cited by 107
Self-citationHromatka, B. S., Tung, J. Y., Kiefer, A. K., Do, C. B., Hinds, D. A., & Eriksson, N. (2015) · Human Molecular Genetics · doi:10.1093/hmg/ddv028 · Cited by 105
Wojciechowski, P., Lipowska, A. M., Rys, P., Ewens, K. G., Franks, S., Tan, S., Lerchbaum, E., Včelák, J., Attaoua, R., Strączkowski, M., et al. (2012) · Diabetologia · doi:10.1007/s00125-012-2638-6 · Cited by 107
Self-citationIwata, M., Maeda, S., Kamura, Y., Takano, A., Kato, H., Murakami, S., Higuchi, K., Takahashi, A., Fujita, H., Hara, K., et al. (2012) · Diabetes Care · doi:10.2337/dc11-2006 · Cited by 105
Tissue-specific alternative splicing of TCF7L2
Prokunina‐Olsson, L., Welch, C., Hansson, O., Adhikari, N., Scott, L. J., Usher, N., Tong, M., Sprau, A. G., Swift, A. J., Bonnycastle, L. L., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp321 · Cited by 105
Diabetes in China: epidemiology, pathophysiology and multi-omics
Jia, W., Chan, J. C. N., Wong, T. Y., & Fisher, E. B. (2025) · Nature Metabolism · doi:10.1038/s42255-024-01190-w · Cited by 108
Ruchat, S.-M., Elks, C. E., Loos, R. J. F., Vohl, M., Weisnagel, S. J., Rankinen, T., Bouchard, C., & Përusse, L. (2008) · Acta Diabetologica · doi:10.1007/s00592-008-0080-5 · Cited by 107
Progress in the genetics of common obesity and type 2 diabetes
Vimaleswaran, K. S., & Loos, R. J. F. (2010) · Expert Reviews in Molecular Medicine · doi:10.1017/s1462399410001389 · Cited by 108
Gonzalez, R., Jennings, L. L., Knuth, M. W., Orth, A. P., Klock, H. E., Ou, W., Feuerhelm, J., Hull, M. V., Koesema, E., Wang, Y., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0914019107 · Cited by 104
Steneberg, P., Bernardo, L. M. D., Edfalk, S., Lundberg, L. A. C., Backlund, F., Östenson, C., & Edlund, H. (2013) · Diabetes · doi:10.2337/db12-1045 · Cited by 107
LncRNAs: key players and novel insights into diabetes mellitus
He, X., Ou, C., Xiao, Y., Han, Q., Li, H., & Zhou, S. (2017) · Oncotarget · doi:10.18632/oncotarget.19921 · Cited by 103
Hurst, C. D., Tomlinson, D. C., Williams, S. V., Platt, F. M., & Knowles, M. A. (2007) · Oncogene · doi:10.1038/sj.onc.1210934 · Cited by 108
Mitchell, R. K., Mondragon, A., Chen, L., McGinty, J., French, P. M. W., Ferrer, J. P., Thorens, B., Hodson, D. J., Rutter, G. A., & Xavier, G. D. S. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu553 · Cited by 103
Nutrient Sensing, Signaling and Ageing: The Role of IGF-1 and mTOR in Ageing and Age-Related Disease
Johnson, S. C. (2018) · Sub-cellular biochemistry/Subcellular biochemistry · doi:10.1007/978-981-13-2835-0_3 · Cited by 104
Little, J., Higgins, J. P. T., Ioannidis, J. P. A., Moher, D., Gagnon, F., von Elm, E. B., Khoury, M. J., Cohen, B. J., Smith, G. D., Grimshaw, J., et al. (2009) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2008.12.004 · Cited by 102
Hirschhorn, J. N., & Gajdos, Z. K. Z. (2010) · Annual Review of Medicine · doi:10.1146/annurev.med.091708.162036 · Cited by 105
Extension of Type 2 Diabetes Genome-Wide Association Scan Results in the Diabetes Prevention Program
Moore, A. F., Jablonski, K. A., McAteer, J. B., Saxena, R., Pollin, T. I., Franks, P. W., Hanson, R. L., Shuldiner, A. R., Knowler, W. C., Altshuler, D., et al. (2008) · Diabetes · doi:10.2337/db08-0284 · Cited by 101
Interrogating Type 2 Diabetes Genome-Wide Association Data Using a Biological Pathway-Based Approach
Perry, J. R. B., McCarthy, M. I., Hattersley, A. T., Zeggini, E., Weedon, M. N., & Frayling, T. M. (2009) · Diabetes · doi:10.2337/db08-1378 · Cited by 101
Self-citationGenetics of Cardiovascular Diseases
Cambien, F., & Tiret, L. (2007) · Circulation · doi:10.1161/circulationaha.106.661751 · Cited by 103
Short Telomeres Compromise β-Cell Signaling and Survival
Guo, N., Parry, E. M., Li, L.-S., Kembou, F., Lauder, N., Hussain, M. A., Berggren, P.-O., & Armanios, M. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017858 · Cited by 100
Paré, G., Chasman, D. I., Parker, A. N., Nathan, D. M., Miletich, J. P., Zee, R. Y. L., & Ridker, P. M. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000312 · Cited by 104
Problems with Genome-Wide Association Studies
Shriner, D., Vaughan, L. K., Padilla, M. A., & Tiwari, H. K. (2007) · Science · doi:10.1126/science.316.5833.1840c · Cited by 100
Wiederkehr, A., & Wollheim, C. B. (2008) · Cell Calcium · doi:10.1016/j.ceca.2007.11.004 · Cited by 102
Long Non-coding RNA ANRIL and Polycomb in Human Cancers and Cardiovascular Disease
Aguiló, F., Cecilia, S. D., & Walsh, M. J. (2015) · Current topics in microbiology and immunology · doi:10.1007/82_2015_455 · Cited by 99
Torrens, C., Poston, L., & Hanson, M. A. (2008) · British Journal Of Nutrition · doi:10.1017/s0007114508921747 · Cited by 99
Total Zinc Intake May Modify the Glucose-Raising Effect of a Zinc Transporter (SLC30A8) Variant
Kanoni, S., Nettleton, J. A., Hivert, M., Ye, Z., van Rooij, F. J. A., Shungin, D., Sonestedt, E., Ngwa, J. S., Wojczynski, M. K., Lemaître, R. N., et al. (2011) · Diabetes · doi:10.2337/db11-0176 · Cited by 100
Self-citationShan, Z., Bao, W., Zhang, Y., Rong, Y., Wang, X., Jin, Y., Song, Y., Yao, P., Sun, C., Hu, F. B., et al. (2013) · Diabetes · doi:10.2337/db13-0606 · Cited by 99
Cheng, C., Reich, D., Haiman, C. A., Tandon, A., Patterson, N. J., Selvin, E., Akylbekova, E. L., Brancati, F. L., Coresh, J., Boerwinkle, E., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0032840 · Cited by 104
Jonsson, A. E., Ladenvall, C., Ahluwalia, T. S., Kravić, J., Krus, U., Taneera, J., Isomaa, B., Tuomilehto, J., Renström, E., Groop, L., et al. (2013) · Diabetes · doi:10.2337/db12-1627 · Cited by 98
Hanson, R. L., Bogardus, C., Duggan, D. J., Kobes, S., Knowlton, M., Infante, A. M., Marovich, L., Benitez, D. S., Baier, L. J., & Knowler, W. C. (2007) · Diabetes · doi:10.2337/db07-0462 · Cited by 98
Precision medicine in diabetes prevention, classification and management
Xie, F., Chan, J. C. N., & Ronald, C. W. (2018) · Journal of Diabetes Investigation · doi:10.1111/jdi.12830 · Cited by 99
Disease-Associated SNPs in Inflammation-Related lncRNAs
Castellanos–Rubio, A., & Ghosh, S. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.00420 · Cited by 98
Gene Set Enrichment in eQTL Data Identifies Novel Annotations and Pathway Regulators
Wu, C., Delano, D. L., Mitro, N., Su, S. V., Janes, J. O., McClurg, P., Batalov, S., Welch, G. L., Zhang, J., Orth, A. P., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000070 · Cited by 97
Genetic Variants at 6p21.1 and 7p15.3 Are Associated with Risk of Multiple Cancers in Han Chinese
Jin, G., Ma, H., Wu, C. H., Dai, J., Zhang, R., Shi, Y., Lü, J., Miao, X., Wang, M., Zhou, Y., et al. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.09.009 · Cited by 97
Hertel, J. K., Johansson, S., Ræder, H., Midthjell, K., Lyssenko, V., Groop, L., Molven, A., & Njølstad, P. R. (2008) · Diabetologia · doi:10.1007/s00125-008-0982-3 · Cited by 97
Pancreatic islet inflammation in type 2 diabetes: From α and β cell compensation to dysfunction
Ehses, J. A., Ellingsgaard, H., Böni-Schnetzler, M., & Donath, M. Y. (2009) · Archives of Physiology and Biochemistry · doi:10.1080/13813450903025879 · Cited by 97
Pharmacogenetics of Anti-Diabetes Drugs
DiStefano, J. K., & Watanabe, R. M. (2010) · Pharmaceuticals · doi:10.3390/ph3082610 · Cited by 96
Gembillo, G., Ingrasciotta, Y., Crisafulli, S., Luxi, N., Siligato, R., Santoro, D., & Trifirò, G. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22094824 · Cited by 104
Rees, S. D., Hydrie, M. Z. I., Shera, A. S., Kumar, S., O’Hare, J. P., Barnett, A. H., Basit, A., & Kelly, M. A. (2011) · Diabetologia · doi:10.1007/s00125-011-2063-2 · Cited by 96
Stark, K. J., Reinhard, W., Neureuther, K., Wiedmann, S., Sedláček, K., Baessler, A., Fischer, M., Weber, S., Kaess, B. M., Erdmann, J., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0001948 · Cited by 96
Successful Versus Failed Adaptation to High-Fat Diet–Induced Insulin Resistance
Matveyenko, A. V., Gurlo, T., Daval, M., Butler, A. E., & Butler, P. C. (2009) · Diabetes · doi:10.2337/db08-1464 · Cited by 98
Successful design and conduct of genome-wide association studies
Amos, C. I. (2007) · Human Molecular Genetics · doi:10.1093/hmg/ddm161 · Cited by 97
Patients with psoriasis are insulin resistant
Gyldenløve, M., Storgaard, H., Holst, J. J., Vilsbøll, T., Knop, F. K., & Skov, L. (2015) · Journal of the American Academy of Dermatology · doi:10.1016/j.jaad.2015.01.004 · Cited by 103
A New Statistic to Evaluate Imputation Reliability
Lin, P., Hartz, S. M., Zhang, Z., Saccone, S. F., Wang, J., Tischfield, J. A., Edenberg, H. J., Kramer, J., Goate, A., Bierut, L. J., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009697 · Cited by 97
A 100K Genome-Wide Association Scan for Diabetes and Related Traits in the Framingham Heart Study
Florez, J. C., Manning, A. K., Dupuis, J., McAteer, J. B., Irenze, K., Gianniny, L., Mirel, D. B., Fox, C. S., Cupples, L. A., & Meigs, J. B. (2007) · Diabetes · doi:10.2337/db07-0451 · Cited by 95
Power to Detect Risk Alleles Using Genome-Wide Tag SNP Panels
Eberle, M. A., Ng, P. C., Kuhn, K. M., Zhou, L., Peiffer, D. A., Galver, L., Viaud‐Martinez, K. A., Lawley, C., Gunderson, K. L., Shen, R., et al. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030170 · Cited by 97
β-Cell deterioration during diabetes: what’s in the gun?
Robertson, R. P. (2009) · Trends in Endocrinology & Metabolism · doi:10.1016/j.tem.2009.05.004 · Cited by 93
Bench-to-bedside review: Association of genetic variation with sepsis
Sutherland, A. M., & Walley, K. R. (2009) · Critical Care · doi:10.1186/cc7702 · Cited by 93
Cropano, C. M., Santoro, N., Groop, L., Man, C. D., Cobelli, C., Galderisi, A., Kursawe, R., Pierpont, B. M., Goffredo, M., & Caprio, S. (2017) · Diabetes Care · doi:10.2337/dc17-0290 · Cited by 94
Psoriasis and Other Complex Trait Dermatoses: From Loci to Functional Pathways
Capon, F., Burden, A. D., Trembath, R. C., & Barker, J. N. (2011) · Journal of Investigative Dermatology · doi:10.1038/jid.2011.395 · Cited by 93
Islet biology, the CDKN2A/B locus and type 2 diabetes risk
Kong, Y., Sharma, R. B., Nwosu, B. U., & Alonso, L. C. (2016) · Diabetologia · doi:10.1007/s00125-016-3967-7 · Cited by 97
Wnt Signaling in Pancreatic Islets
Liu, Z., & Habener, J. F. (2010) · Advances in experimental medicine and biology · doi:10.1007/978-90-481-3271-3_17 · Cited by 94
Cluett, C., McDermott, M. M., Guralnik, J. M., Ferrucci, L., Bandinelli, S., Miljkovic, I., Zmuda, J. M., Li, R., Tranah, G. J., Harris, T. B., et al. (2009) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.108.825935 · Cited by 93
Self-citationThe pathogenetic role of β-cell mitochondria in type 2 diabetes
Fex, M., Nicholas, L. M., Vishnu, N., Medina, A., Sharoyko, V. V., Nicholls, D. G., Spégel, P., & Mulder, H. (2018) · Journal of Endocrinology · doi:10.1530/joe-17-0367 · Cited by 93
Huang, C., Chen, W., & Wang, X. (2022) · Genes & Diseases · doi:10.1016/j.gendis.2022.04.014 · Cited by 103
Genomics of type 2 diabetes mellitus: implications for the clinician
Stolerman, E. S., & Florez, J. C. (2009) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2009.129 · Cited by 91
Zinc signalling and subcellular distribution: emerging targets in type 2 diabetes
Mocchegiani, E., Giacconi, R., & Malavolta, M. (2008) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2008.08.002 · Cited by 91
Stergiakouli, E., Gaillard, R., Tavaré, J. M., Balthasar, N., Loos, R. J., Taal, H. R., Evans, D. M., Rivadeneira, F., St Pourcain, B., Uitterlinden, A. G., et al. (2014) · Obesity · doi:10.1002/oby.20840 · Cited by 90
Self-citationFoxM1 Is Up-Regulated by Obesity and Stimulates β-Cell Proliferation
Davis, D. B., Lavine, J. A., Suhonen, J. I., Krautkramer, K. A., Rabaglia, M. E., Sperger, J. M., Fernandez, L. A., Yandell, B. S., Keller, M. P., Wang, I., et al. (2010) · Molecular Endocrinology · doi:10.1210/me.2010-0082 · Cited by 90
Pharmacogenetics: data, concepts and tools to improve drug discovery and drug treatment
Brockmöller, J., & Tzvetkov, M. V. (2008) · European Journal of Clinical Pharmacology · doi:10.1007/s00228-007-0424-z · Cited by 91
Smidt, K., Jessen, N., Petersen, A. B., Larsen, A., Magnusson, N. E., Jeppesen, J. B., Stoltenberg, M., Culvenor, J. G., Tsatsanis, A., Brock, B., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005684 · Cited by 90
Wang, Y., Nie, M., Li, W., Ping, F., Hu, Y., Ma, L., Gao, J., & Liu, J. (2011) · PLoS ONE · doi:10.1371/journal.pone.0026953 · Cited by 91
TCF7L2 genetic defect and type 2 diabetes
Cauchi, S., & Froguel, P. (2008) · Current Diabetes Reports · doi:10.1007/s11892-008-0026-x · Cited by 91
Bis, J. C., Heckbert, S. R., Smith, N. L., Reiner, A. P., Rice, K. M., Lumley, T., Hindorff, L. A., Marciante, K. D., Enquobahrie, D. A., Monks, S. A., et al. (2007) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2007.09.031 · Cited by 89
Palmer, N. D., Hester, J. M., An, S. S., Adeyemo, A., Rotimi, C. N., Langefeld, C. D., Freedman, B. I., Ng, M. C. Y., & Bowden, D. W. (2010) · Diabetes · doi:10.2337/db10-0134 · Cited by 88
Cohort Profile: Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS)
Hébert, H. L., Shepherd, B., Milburn, K., Veluchamy, A., Meng, W., Carr, F., Donnelly, L. A., Tavendale, R., Leese, G., Colhoun, H. M., et al. (2017) · International Journal of Epidemiology · doi:10.1093/ije/dyx140 · Cited by 89
Self-citationGenetics of Type 2 Diabetes: Past, Present, and Future
Laakso, M., & Silva, L. F. (2022) · Nutrients · doi:10.3390/nu14153201 · Cited by 95
Chang, M., Lindegren, M. L., Butler, M. A., Chanock, S. J., Dowling, N. F., Gallagher, M., Moonesinghe, R., Moore, C. A., Ned, R. M., Reichler, M. R., et al. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwn286 · Cited by 88
Hong, H., Su, Z., Ge, W., Shi, L. M., Perkins, R., Fang, H., Xu, J., Chen, J. J., Han, T., Kaput, J., et al. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s9-s17 · Cited by 89
Leahy, J. L. (2008) · Yearbook of Endocrinology · doi:10.1016/s0084-3741(08)79224-2 · Cited by 88
The Myocardial Infarction Genetics Consortium, Shea, J., Agarwala, V., Philippakis, A. A., Maguire, J., Banks, E., DePristo, M., Thomson, B., Guiducci, C., Onofrio, R. C., et al. (2011) · Nature Genetics · doi:10.1038/ng.871 · Cited by 87
Perspectives in polycystic ovary syndrome: From hair to eternity
Dunaif, A. (2016) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2015-3780 · Cited by 87
Haplotypic Background of a Private Allele at High Frequency in the Americas
Schroeder, K. B., Jakobsson, M., Crawford, M. H., Schurr, T. G., Boca, S. M., Conrad, D. F., Tito, R. Y., Osipova, L. P., Tarskaia, L. A., Жаданов, С. И., et al. (2009) · Molecular Biology and Evolution · doi:10.1093/molbev/msp024 · Cited by 89
Stančáková, A., Pihlajamäki, J., Kuusisto, J., Stefan, N., Fritsche, A., Häring, H. U., Andreozzi, F., Succurro, E., Sesti, G., Boesgaard, T. W., et al. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2007-2218 · Cited by 87
Bressler, J., Kao, W. H. L., Pankow, J. S., & Boerwinkle, E. (2010) · PLoS ONE · doi:10.1371/journal.pone.0010521 · Cited by 87
Lin, Y., Li, P., Li, C., Zhang, B., Tang, X., Zhang, X., Li, Y., Yang, X. Q., Yang, Y., Wang, L., et al. (2010) · BMC Medical Genetics · doi:10.1186/1471-2350-11-97 · Cited by 87
Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes
Padilla-Martínez, F., Collin, F., Kwaśniewski, M., & Kretowski, A. J. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21051703 · Cited by 93
Weedon, M. N. (2007) · Diabetic Medicine · doi:10.1111/j.1464-5491.2007.02258.x · Cited by 87
Self-citationPettersen, E., Skorpen, F., Kvaløy, K., Midthjell, K., & Grill, V. (2009) · Diabetes · doi:10.2337/db09-0923 · Cited by 87
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
