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diff --git a/gnqa/paper1_eval/src/data/responses/diabetes/experts/01.json b/gnqa/paper1_eval/src/data/responses/diabetes/experts/01.json new file mode 100644 index 0000000..5b9cc0f --- /dev/null +++ b/gnqa/paper1_eval/src/data/responses/diabetes/experts/01.json @@ -0,0 +1,402 @@ +{ + "created_at": "2024-05-31T23:02:19.686688Z", + "data": { + "amplify": false, + "answer": "The genes associated with diabetes mentioned in the text include PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, CDKAL1, IRS1, CCR5, FTO, NOTCH2, WFS1, JAZF1, ADIPOQ, AHSG, CAPN10, ENPP1, PPARGC1A, SREBF1, PDX1, PFAS, GCK, HNFA4, LOC387761, KCNQ1, MTNR1B, GCKR, BACH2, CTNNB1, CREB5, PARD3B, PARD6G, PRKCZ, EBF1, GIGYF1, ADCY5, PROX1, DGKB-TMEM195, CRY2, FADS1, GLIS3, and C2CD4B.", + "context": { + "2bef9608-4bd6-4252-9fbd-2413b2cad4f8": [ + { + "document_id": "2bef9608-4bd6-4252-9fbd-2413b2cad4f8", + "text": "\n\nTo see which other significant genes were likely to have a role in diabetes we looked at all variant sets with a significant glucose, HbA1c, or T2D association and examined whether they had associations with additional diabetes traits (p ≤ 0.0016, correcting for 32 sets tested).Damaging missense variants in PDX1 and PFAS, which significantly associated with HbA1c levels in our primary analysis, associated with T2D diagnosis using this threshold (Table 3 and Supplementary Table 14)." + }, + { + "document_id": "2bef9608-4bd6-4252-9fbd-2413b2cad4f8", + "text": "Identification of genes with a biological role in diabetes. Variants in two genes, GCK and GIGYF1, significantly associated with glucose, HbA1c and T2D diagnosis, strongly suggesting a biological role in diabetes; GCK is involved in Mendelian forms of diabetes while GIGYF1 has not previously been implicated by genetics in the disease.Both GCK and GIGYF1 are located on chromosome 7 but are 56 Mb apart, strongly suggesting that these signals are independent; this independence was confirmed by conditional analysis (Supplementary Table 13).Two additional variant sets, HNF1A pLOF and TNRC6B pLOF, had genome-wide associations with both T2D diagnosis and HbA1c levels while G6PC2 damaging missense variants associated with decreased levels of both glucose and HbA1c but not T2D diagnosis (Table 3)." + } + ], + "2dade65a-5d31-4839-b2c9-4c6cd3056f58": [ + { + "document_id": "2dade65a-5d31-4839-b2c9-4c6cd3056f58", + "text": "\n\nOne obvious locus to consider is TCF7L2 in the context of type 2 diabetes.Common genetic variation located within the gene encoding transcription factor 7 like 2 (TCF7L2) has been consistently reported to be strongly associated with the disease.Such reports range from 2006, when we first published the association [3], to the recent transethnic meta-analysis GWAS of type 2 diabetes [4]." + } + ], + "31588831-61b3-4018-9962-bd6985c3061b": [ + { + "document_id": "31588831-61b3-4018-9962-bd6985c3061b", + "text": "\n\nTesting of these loci for association with T2D as a dichotomous trait in up to 40,655 cases and 87,022 nondiabetic controls demonstrated that the fasting glucose-raising alleles at seven loci (in or near ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 and the known T2D genes TCF7L2 and SLC30A8) are robustly associated (P < 5 × 10 −8 ) with increased risk of T2D (Table 2).The association of a highly correlated SNP in ADCY5 with T2D in partially overlapping samples is reported by our companion manuscript 29 .We found less significant T2D associations (P < 5 × 10 −3 ) for variants in or near CRY2, FADS1, GLIS3 and C2CD4B (Table 2).These data clearly show that loci with similar fasting glucose effect sizes may have very different T2D risk effects (see, for example, ADCY5 and MADD in Table 2)." + } + ], + "3c35547c-eb9b-470d-b74b-0f9a0529e965": [ + { + "document_id": "3c35547c-eb9b-470d-b74b-0f9a0529e965", + "text": "\n\nAmong the confirmed and potential type 2 diabetes risk genes described in Tables 1 and 2, eight genes influence whole-body or peripheral insulin sensitivity: ADIPOQ (47, 52, 250 -257), AHSG (75, 258), CAPN10 (259 -264), ENPP1 (265)(266)(267)(268)(269)(270)(271), PPARG (272)(273)(274)(275)(276)(277)(278)(279)(280)(281)(282)(283), PPARGC1A (284,285), SREBF1 (65), and TCF7L2 (133,151,286,287)." + } + ], + "45c14654-f263-4031-9941-206d7b6a97f3": [ + { + "document_id": "45c14654-f263-4031-9941-206d7b6a97f3", + "text": "\n\nDespite identification of many putative causative genetic variants, few have generated credible susceptibility variants for type 2 diabetes.Indeed, the most important finding using linkage studies is the discovery that the alteration of TCF7L2 (TCF-4) gene expression or function (33) disrupts pancreatic islet function and results in enhanced risk of type 2 diabetes.Candidate gene studies have also reported many type 2 diabetes-associated loci and the coding variants in the nuclear receptor peroxisome proliferator-activated receptor-g (34), the potassium channel KCNJ11 (34), WFS1 (35), and HNF1B (TCF2) (36) are among the few that have been replicated (Table 2).Recently, there have been great advances in the analysis of associated variants in GWA and replication studies due to highthroughput genotyping technologies, the International HapMap Project, and the Human Genome Project.Type 2 susceptibility loci such as JAZF1, CDC123-CAMK1D, TSPAN8-LGR5, THADA, ADAMTS9, NOTCH2, and ADCY5 (37,38) are among some of the established loci (Table 2).CDKN2A/B, CDKAL1, SLC30A8, IGF2BP2, HHEX/IDE, and FTO are other established susceptibility loci for diabetes (Table 2) (34,39,40).GWA studies have also identified the potassium voltage-gated channel KCNQ1 (32) as an associated gene variant for diabetes.A recent GWA study reporting a genetic variant with a strong association with insulin resistance, hyperinsulinemia, and type 2 diabetes, located adjacent to the insulin receptor substrate 1 (IRS1) gene, is the C allele of rs2943641 (41).Interestingly, the parental origin of the single nucleotide polymorphism is of importance because the allele that confers risk when paternally inherited is protected when maternally transmitted.GWA studies for glycemic traits have identified loci such as MTNR1B (42), GCK (glucokinase) (42), and GCKR (glucokinase receptor) (42); however, further investigation of genetic loci on glucose homeostasis and their impact on type 2 diabetes is needed.Indeed, a recent study by Soranzo et al. (42) using GWA studies identified ten genetic loci associated with HbA 1c .Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin may be associated with changes in levels of HbA 1c ." + } + ], + "4fe0a01d-3be8-4cd5-ac59-8b0ef085b20c": [ + { + "document_id": "4fe0a01d-3be8-4cd5-ac59-8b0ef085b20c", + "text": "\n\nG enome-wide association studies (GWAS) have iden- tified several type 2 diabetes mellitus (T2DM) susceptibility loci including CDKAL1, CDKN2B, IGF2BP2, HHEX, SLC30A8, PKN2, LOC387761 (1)(2)(3)(4)(5), and KCNQ1, which was recently identified by similar GWAS approach in two independent Japanese samples (6,7).Although these associations have been well replicated in Japanese populations (8), the role of these loci in other East Asian populations remains less clear.For example, a study in China by Wu et al. (9) did not find significant associations between single-nucleotide polymorphisms (SNPs) in IGF2BP2 and SLC30A8 with T2DM, whereas an association between SNPs at the HHEX locus and T2DM was reported among Chinese living in Shanghai, but not among Chinese in Beijing.Another study in Hong Kong Chinese (10) also did not find an association with SNPs at the IGF2BP2 locus; however, they reported an association between T2DM with SNPs at the HHEX and SLC30A8 loci." + } + ], + "559a3a15-da15-4132-a8b5-5401bfe770ef": [ + { + "document_id": "559a3a15-da15-4132-a8b5-5401bfe770ef", + "text": "\n\nIn studies where overt T2D has been the phenotype the majority of associated polymorphisms have encoded proteins known to be involved in β-cell metabolism; for example TCF7L2, KCNJ11 and HHEX have shown robust association [170,171].This suggests that these genes could prove useful in predicting β-cell preservation during the course of T2D.The glucokinase gene (GCK) coding for the initial glucose-sensing step in the β-cell can have activating mutations causing hypoglycemia that might provide structural and functional models leading to drug targets for treating T2D [172].In the GoDARTs study, investigators examined the medication response of metformin and sulphonylurea based on the TCF7L2 variants mainly affecting the β-cell.The carriers of the at risk 'T' allele responded less well to sulphonylurea therapy than metformin [173].Also it is of significant public health interest that in the Diabetes Prevention Program, lifestyle modifications were shown to reduce the risk of diabetes conferred by risk variants of TCF7L2 at rs7093146, and in placebo participants who carried the homozygous risk genotype (TT), there was 80% higher risk for developing diabetes compared to the lifestyle intervention group carrying the same risk genotypes [35].These findings could herald significant future progress in the field of T2D pharmacogenomics, possibly leading to the development and use of agents tailored on the basis of genotype." + } + ], + "5d7a863d-1811-4eea-9fb0-fbc3067aa664": [ + { + "document_id": "5d7a863d-1811-4eea-9fb0-fbc3067aa664", + "text": "\n\nDespite sharing only 9 loci (among 26 and 17 total in the two analyses, respectively), the separate analyses both identified genes involved in diabetes-related biological functions, including \"glucose homeostasis,\" \"pancreas development\" and \"insulin secretion\" (Supplementary Tables 3 and 5).Three of the top eleven scoring genes in our independent replication analysis have verified causal links to T2D, as annotated in the OMIM 41 .These include genes encoding transcription factors TCF7L2 (TCF4), which has extensive evidence of being causal in T2D 61,62 , and HNF1B, which is a known cause of maturity onset diabetes of the young 63 .Other high-ranking candidate genes have been identified as therapeutic targets in T2D (for example, CTBP1 (ref.64) and LEP 65 ), and the high-scoring gene HHEX has recently been shown to play a key role in islet function 66 ." + } + ], + "7bd7a98f-955a-4988-8981-a0ff7ab6f7df": [ + { + "document_id": "7bd7a98f-955a-4988-8981-a0ff7ab6f7df", + "text": "\n\nSimilar findings to AMD are now unfolding with type 2 DM.Grant et al. (24) first reported on a variant of the gene TCF7L2, which has been linked to reduced beta cell function and poor insulin response to oral glucose loads (51).Since its first discovery, this gene has been widely confirmed in independent studies as a pivotal susceptibility marker for type 2 DM (23,(25)(26)(27)(28)40).Recently, 6 genome-wide SNP association studies have identified and replicated in separate stages several additional novel genes conferring susceptibility to type 2 DM (23,(25)(26)(27)(28)40) (Table 2).Interestingly, these loci primarily include genes involved in pancreatic beta cell development and function as opposed to insulin resistance-the current accepted mechanism for type 2 DM.This development casts doubt on our traditional pathophysiological modeling of the type 2 diabetic patient and underscores the need for genomic studies to further define pathobiological processes of complex traits." + } + ], + "80500e0d-0e39-4e46-bb60-8721f4f512c0": [ + { + "document_id": "80500e0d-0e39-4e46-bb60-8721f4f512c0", + "text": "\n\nOf the 16 loci that have been associated with type 2 diabetes previously, [8][9][10][11][12][13][14][15] we showed that 11 -TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEXwere associated with an enhanced risk of future diabetes.Many of the variants that we genotyped appear to influence beta-cell function, possibly through effects on proliferation, regeneration, and apoptosis.There was a time-dependent increase in the BMI and a decrease in insulin sensitivity in the subjects from the Botnia study, an increase in insulin resistance that was reflected by an increase in insulin secretion.However, this increase was inadequate to compensate for the increase in insulin resistance in carriers with a high genetic risk, which resulted in a markedly impaired disposition index.Only variants in FTO were associated with an increased BMI.Both FTO and PPARG together with TCF7L2 and KCNJ11 predicted transition from impaired fasting glucose levels or impaired glucose tolerance to manifest diabetes, which suggests that a combination of increased obesity and insulin resistance with a deterioration in beta-cell function contribute to the manifestation of diabetes in these subjects.Collectively, our findings emphasize the critical role of inherited defects in beta-cell function for the development of type 2 diabetes." + }, + { + "document_id": "80500e0d-0e39-4e46-bb60-8721f4f512c0", + "text": "Type 2 Diabetes\n\nCommon variants in 11 genes were significantly associated with the risk of future type 2 diabetes in the MPP cohort, including TCF7L2 (odds ratio, 1.30; P = 9.5×10 −13 ), PPARG (odds ratio, 1.20; P = 4.0×10 −4 ), FTO (odds ratio, 1.14; P = 9.2×10 −5 ), KCNJ11 (odds ratio, 1.13; P = 3.6×10 −4 ), NOTCH2 (odds ratio, 1.13; P = 0.02), WFS1 (odds ratio, 1.12; P = 0.001), CDKAL1 (odds ratio, 1.11; P = 0.004), IGF2BP2 (odds ratio, 1.10; P = 0.008), SLC30A8 (odds ratio, 1.10; P = 0.008), JAZF1 (odds ratio, 1.08; P = 0.03), and HHEX (odds ratio, 1.07; P = 0.03) (Table 2).Although these findings could not be fully replicated in the smaller Botnia study, there was little heterogeneity between the studies with respect to the risk conferred by different genotypes." + } + ], + "8cd81e24-a326-4443-bc37-0e6e421e70b2": [ + { + "document_id": "8cd81e24-a326-4443-bc37-0e6e421e70b2", + "text": "\n\nTo date, more than 70 genes have been identified as involved in T2DM, primarily by association analysis [34].In addition, via GWAS arrays, more than 100 SNPs have been identified for T2DM [35].From the 50 novel loci associated with T2DM previously identified, more than 40 loci have been associated with T2DM-related traits, including fasting proinsulin, insulin and glucose (Table 1) [36][37][38][39].However, for T2DM-related traits, such as the HOMA index or pancreatic β cell function, there are virtually no published data examining the relationship between these traits or the genotype and environment interactions.Clinical investigations of some loci have suggested that the genetic components of T2DM risk act preferentially through β cell function [40].Among all 40 loci associated with T2DM-related traits, only transcription factor-7-like 2 (TCF7L2) was shown to clearly contribute to T2DM risk [41].Several studies in white European [42], Indian [43], Japanese [44], Mexican American [45] and West African [46] individuals have shown a strong association between TCF7L2 and T2DM.It is also noteworthy that these populations represent the major racial groups with a high prevalence of T2DM.In all populations, TCF7L2 showed a strong association, with the odds of developing T2DM increased by 30%-50% for each allele inherited.This finding indicates an approximately double odds ratio compared to most other diabetes susceptibility polymorphisms.TCF7L2 is a transcription factor involved in the Wnt signaling pathway that is ubiquitously expressed, and it has been observed that TCF7L2 risk alleles result in the overexpression of TCF7L2 in pancreatic β cells.This overexpression causes reduced nutrient-induced insulin secretion, which results in a direct predisposition to T2DM as well as an indirect predisposition via an increase in hepatic glucose production [47]." + }, + { + "document_id": "8cd81e24-a326-4443-bc37-0e6e421e70b2", + "text": "Most Relevant T2DM Susceptibility Genes\n\nGene and environment interaction studies have shown a nice association between variants in peroxisome proliferator-activated receptor gamma (PPARG), TCF7L2 and fat mass and obesity-associated protein (FTO) genes, a Western dietary pattern and T2DM." + } + ], + "9b93b4eb-98c2-403f-aea2-6b24399501b8": [ + { + "document_id": "9b93b4eb-98c2-403f-aea2-6b24399501b8", + "text": "\n\nOne of these genes associated with type 2 diabetes is the insulin receptor substrate 1 (IRS1, OMIM association number, 147545) (Alharbi, Khan, Abotalib, & Al-Hakeem, 2014;Alharbi, Khan, Munshi et al., 2014;Brender et al., 2013;Brunetti, Chiefari, & Foti, 2014) and another is the C-C motif chemokine receptor5(CCR5, OMIM association number, 601373) (Balistreri et al., 2007;Mokubo et al., 2006;Muntinghe et al., 2009)." + } + ], + "a579db95-2a40-43ff-b237-d47f90aaf64f": [ + { + "document_id": "a579db95-2a40-43ff-b237-d47f90aaf64f", + "text": "Genes boosted in type 2 diabetes\n\nBefore the Wellcome Trust study, PPARG, KCNJ11, and TCF7L2 had all been identified as genes involved in type 2 diabetes through genome-wide association studies and replicated in follow-up studies (for review, see Bonnefond et al. 2010).The strongest candidate gene for type 2 diabetes, TCF7L2, was also the strongest signal seen in the Wellcome trust study, although the others were not so strong.However, the exact mechanism by which TCF7L2 acts was not entirely clear.In our analysis (Fig. 5), we find it directly connected to the b-catenin/WNT signaling pathway by its functional connection to CTNNB1, as well as to BACH2, a gene that has been repeatedly implicated in type 1 diabetes (e.g., Cooper et al. 2008;Madu et al. 2009), but which has not yet been linked to type 2 diabetes.BACH2 is among the genes most strongly boosted by network linkages, deriving additional signal from CREB5 and PARD3B, which both score highly in the GWAS data.PARD6G, PARD3B, and CDC42 are also emphasized by the method.Notably, these genes form a complex with PRKCZ (Koh et al. 2008), a variant of which correlates with type 2 diabetes in Han Chinese (Qin et al. 2008).EBF1, a known regulator of adipocyte differentiation (Akerblad et al. 2005) is also strongly boosted by the network, supporting a possible role in type 2 diabetes." + } + ], + "b978a189-6fbd-4791-8072-7db79f43746a": [ + { + "document_id": "b978a189-6fbd-4791-8072-7db79f43746a", + "text": "RESULTS-\n\nWe confirmed the associations of TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, and FTO with risk for type 2 diabetes, with odds ratios ranging from 1.13 to 1.35 (1.3 ϫ 10 Ϫ12 Ͻ P unadjusted Ͻ 0.016).In addition, the A allele of rs8050136 at FTO was associated with increased BMI in the control subjects (P unadjusted ϭ 0.008).However, we did not observe significant association of any genetic variants with surrogate measures of insulin secretion or insulin sensitivity indexes in a subset of 2,662 control subjects.Compared with subjects carrying zero, one, or two risk alleles, each additional risk allele was associated with 17% increased risk, and there was an up to 3.3-fold increased risk for type 2 diabetes in those carrying eight or more risk alleles.Despite most of the effect sizes being similar between Asians and Europeans in the metaanalyses, the ethnic differences in risk allele frequencies in most of these genes lead to variable attributable risks in these two populations." + }, + { + "document_id": "b978a189-6fbd-4791-8072-7db79f43746a", + "text": "\nOBJECTIVE-Recent genome-wide association studies have identified six novel genes for type 2 diabetes and obesity and confirmed TCF7L2 as the major type 2 diabetes gene to date in Europeans.However, the implications of these genes in Asians are unclear.RESEARCH DESIGN AND METHODS-We studied 13 associated single nucleotide polymorphisms from these genes in 3,041 patients with type 2 diabetes and 3,678 control subjects of Asian ancestry from Hong Kong and Korea. RESULTS-We confirmed the associations of TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, and FTO with risk for type 2 diabetes, with odds ratios ranging from 1.13 to 1.35 (1.3 ϫ 10 Ϫ12 Ͻ P unadjusted Ͻ 0.016).In addition, the A allele of rs8050136 at FTO was associated with increased BMI in the control subjects (P unadjusted ϭ 0.008).However, we did not observe significant association of any genetic variants with surrogate measures of insulin secretion or insulin sensitivity indexes in a subset of 2,662 control subjects.Compared with subjects carrying zero, one, or two risk alleles, each additional risk allele was associated with 17% increased risk, and there was an up to 3.3-fold increased risk for type 2 diabetes in those carrying eight or more risk alleles.Despite most of the effect sizes being similar between Asians and Europeans in the metaanalyses, the ethnic differences in risk allele frequencies in most of these genes lead to variable attributable risks in these two populations. CONCLUSIONS-Ourfindings support the important but differential contribution of these genetic variants to type 2 diabetes and obesity in Asians compared with Europeans.Diabetes 57: 2226-2233, 2008T ype 2 diabetes is a major health problem affecting more than 170 million people worldwide.In the next 20 years, Asia will be hit hardest, with the diabetic populations in India and China more than doubling (1).Type 2 diabetes is characterized by the presence of insulin resistance and pancreatic -cell dysfunction, resulting from the interaction of genetic and environmental factors.Until recently, few genes identified through linkage scans or the candidate gene approach have been confirmed to be associated with type 2 diabetes (e.g., PPARG, KCNJ11, CAPN10, and TCF7L2).Under the common variant-common disease hypothesis, several genome-wide association (GWA) studies on type 2 diabetes have been conducted in large-scale case-control samples.Six novel genes (SLC30A8, HHEX, CDKAL1, CDKN2A and CDKN2B, IGF2BP2, and FTO) with modest effect for type 2 diabetes (odds ratio [OR] 1.14 -1.20) had been reproducibly demonstrated in multiple populations of European ancestry.Moreover, TCF7L2 was shown to have the largest effect for type 2 diabetes (1.37) in the European populations to date (2-8).Although many of these genes may be implicated in the insulin production/secretion pathway (TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, and IGF2BP2) (6,9 -11), FTO is associated with type 2 diabetes through its regulation of adiposity (8,12,13).Moreover, two adjacent regions near CDKN2A/B are associated with type 2 diabetes and cardiovascular diseases risks, respectively (7,14 -16).Despite the consistent associations among Europeans, the contributions of these genetic variants in other ethnic groups are less clear.Given the differences in environmental factors (e.g., lifestyle), risk factor profiles (body composition and insulin secretion/resistance patterns), and genetic background (linkage disequilibrium pattern and risk allele frequencies) between Europeans and Asians, it is important to understand the role of these genes in Asians.A recent case-control study in 1,728 Japanese subjects revealed nominal association to type 2 diabetes for variants at the SLC30A8, HHEX, CDKAL1, CDKN2B, and FTO genes but not IGF2BP2 (17).In the present large-scale case-control replication study of 6,719 Asians, we aimed to test for the association of six novel genes from GWA studies and TCF7L2, which had the largest effect in Europeans, and their joint effects on type 2 diabetes risk and metabolic traits. RESEARCH DESIGN AND METHODSAll subjects were recruited from Hong Kong and Korea and of Asian ancestry.The subjects in the Hong Kong case-control study were of southern Han Chinese ancestry residing in Hong Kong.Participants for the case cohort consisting of 1,481 subjects with type 2 diabetes were selected from two" + } + ], + "bbb4af44-2659-4207-b9a1-0ff85d379a9f": [ + { + "document_id": "bbb4af44-2659-4207-b9a1-0ff85d379a9f", + "text": "\n\nOBJECTIVE-Common variants in PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 genes have been shown to be associated with type 2 diabetes in European populations by genome-wide association studies.We have studied the association of common variants in these eight genes with type 2 diabetes and related traits in Indians by combining the data from two independent case-control studies." + } + ], + "d9564b3c-efac-42ae-8e15-bf962c0a7a3c": [ + { + "document_id": "d9564b3c-efac-42ae-8e15-bf962c0a7a3c", + "text": "Introduction\n\nMany genes have been evaluated as candidates for T2D susceptibility.However, only variants in the TCF7L2, PPARG, KCNJ11 and HNFA4 genes have been extensively replicated in populations around the world, showing their indisputable association with T2D risk (Zeggini 2007).In the particular case of the HNF4A gene, it has been implicated in maturity-onset diabetes of the young type 1 (MODY 1) (Mitchell and Frayling 2002;Zhu et al. 2003).HNF4A is a member of the nuclear receptor super-family that plays a critical role in embryogenesis and metabolism, by regulating gene expression in pancreatic beta cells, liver and other tissues.The HNF4A gene is localized to chromosome 20q13, a region that has demonstrated evidence for linkage with T2D (Sladek et al. 1990;Ghosh et al. 1999).Several genetic studies, mainly in Caucasian and Asian populations, have provided evidence for the association of the variants in HNF4A with T2D (Ghosh et al. 1999;Silander et al. 2004;Winckler et al. 2005)." + } + ] + }, + "data_source": [ + { + "document_id": "bbb4af44-2659-4207-b9a1-0ff85d379a9f", + "section_type": "main", + "text": "\n\nOBJECTIVE-Common variants in PPARG, KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2A, IGF2BP2, and CDKAL1 genes have been shown to be associated with type 2 diabetes in European populations by genome-wide association studies.We have studied the association of common variants in these eight genes with type 2 diabetes and related traits in Indians by combining the data from two independent case-control studies." + }, + { + "document_id": "5d7a863d-1811-4eea-9fb0-fbc3067aa664", + "section_type": "main", + "text": "\n\nDespite sharing only 9 loci (among 26 and 17 total in the two analyses, respectively), the separate analyses both identified genes involved in diabetes-related biological functions, including \"glucose homeostasis,\" \"pancreas development\" and \"insulin secretion\" (Supplementary Tables 3 and 5).Three of the top eleven scoring genes in our independent replication analysis have verified causal links to T2D, as annotated in the OMIM 41 .These include genes encoding transcription factors TCF7L2 (TCF4), which has extensive evidence of being causal in T2D 61,62 , and HNF1B, which is a known cause of maturity onset diabetes of the young 63 .Other high-ranking candidate genes have been identified as therapeutic targets in T2D (for example, CTBP1 (ref.64) and LEP 65 ), and the high-scoring gene HHEX has recently been shown to play a key role in islet function 66 ." + }, + { + "document_id": "1a93e25f-2a43-49e9-8450-03a57c93e613", + "section_type": "main", + "text": "Relation to human and rodent association and linkage studies\n\nRecently, a total of nine candidate genes for T2DM have been identified and replicated in humans through multi- [5][6][7][8][9][10][11].Interestingly, none of these genes shows a high score in our meta-analysis, although Pparg and Tcf7l2 are significant on the less restrictive 0.01 level.On the other hand, from the data we could infer that Fto and Hhex act in pancreatic islets indicated by the T2DM-GeneMiner result for these genes.Cdkal1 and Cdkn2a are not expressed in the transcriptional studies.These genes show very low expression levels or might be active in tissues not included in our study.Since our meta-analysis approach takes into account several data sets from DNA microarrays, our candidate genes have a bias towards transcripts whose expression is changed in the context of T2DM.Moreover, the gene variants from association studies may not result in altered gene expression and, for most SNPs found in association studies, there is a lack of functional information since the variation mostly occurs in non-coding regions of the genes.In order to correlate the T2DM genes with genetic variation we plotted the number of known SNPs for the genes [see Figure 2 in Additional file 1].No general tendency to highly variable genes is observable.Two genes of the candidate list show high variation, Pgcp (9,098 SNPs) and Sorbs1 (4,130).Particularly interesting is Pgcp, because it has not been related to T2DM before and its functional role is also undetermined." + }, + { + "document_id": "9b93b4eb-98c2-403f-aea2-6b24399501b8", + "section_type": "main", + "text": "\n\nOne of these genes associated with type 2 diabetes is the insulin receptor substrate 1 (IRS1, OMIM association number, 147545) (Alharbi, Khan, Abotalib, & Al-Hakeem, 2014;Alharbi, Khan, Munshi et al., 2014;Brender et al., 2013;Brunetti, Chiefari, & Foti, 2014) and another is the C-C motif chemokine receptor5(CCR5, OMIM association number, 601373) (Balistreri et al., 2007;Mokubo et al., 2006;Muntinghe et al., 2009)." + }, + { + "document_id": "80500e0d-0e39-4e46-bb60-8721f4f512c0", + "section_type": "main", + "text": "\n\nOf the 16 loci that have been associated with type 2 diabetes previously, [8][9][10][11][12][13][14][15] we showed that 11 -TCF7L2, PPARG, FTO, KCNJ11, NOTCH2, WFS1, CDKAL1, IGF2BP2, SLC30A8, JAZF1, and HHEXwere associated with an enhanced risk of future diabetes.Many of the variants that we genotyped appear to influence beta-cell function, possibly through effects on proliferation, regeneration, and apoptosis.There was a time-dependent increase in the BMI and a decrease in insulin sensitivity in the subjects from the Botnia study, an increase in insulin resistance that was reflected by an increase in insulin secretion.However, this increase was inadequate to compensate for the increase in insulin resistance in carriers with a high genetic risk, which resulted in a markedly impaired disposition index.Only variants in FTO were associated with an increased BMI.Both FTO and PPARG together with TCF7L2 and KCNJ11 predicted transition from impaired fasting glucose levels or impaired glucose tolerance to manifest diabetes, which suggests that a combination of increased obesity and insulin resistance with a deterioration in beta-cell function contribute to the manifestation of diabetes in these subjects.Collectively, our findings emphasize the critical role of inherited defects in beta-cell function for the development of type 2 diabetes." + }, + { + "document_id": "3c35547c-eb9b-470d-b74b-0f9a0529e965", + "section_type": "main", + "text": "\n\nAmong the confirmed and potential type 2 diabetes risk genes described in Tables 1 and 2, eight genes influence whole-body or peripheral insulin sensitivity: ADIPOQ (47, 52, 250 -257), AHSG (75, 258), CAPN10 (259 -264), ENPP1 (265)(266)(267)(268)(269)(270)(271), PPARG (272)(273)(274)(275)(276)(277)(278)(279)(280)(281)(282)(283), PPARGC1A (284,285), SREBF1 (65), and TCF7L2 (133,151,286,287)." + }, + { + "document_id": "80500e0d-0e39-4e46-bb60-8721f4f512c0", + "section_type": "main", + "text": "Type 2 Diabetes\n\nCommon variants in 11 genes were significantly associated with the risk of future type 2 diabetes in the MPP cohort, including TCF7L2 (odds ratio, 1.30; P = 9.5×10 −13 ), PPARG (odds ratio, 1.20; P = 4.0×10 −4 ), FTO (odds ratio, 1.14; P = 9.2×10 −5 ), KCNJ11 (odds ratio, 1.13; P = 3.6×10 −4 ), NOTCH2 (odds ratio, 1.13; P = 0.02), WFS1 (odds ratio, 1.12; P = 0.001), CDKAL1 (odds ratio, 1.11; P = 0.004), IGF2BP2 (odds ratio, 1.10; P = 0.008), SLC30A8 (odds ratio, 1.10; P = 0.008), JAZF1 (odds ratio, 1.08; P = 0.03), and HHEX (odds ratio, 1.07; P = 0.03) (Table 2).Although these findings could not be fully replicated in the smaller Botnia study, there was little heterogeneity between the studies with respect to the risk conferred by different genotypes." + }, + { + "document_id": "183f165e-4d5c-4580-9aff-4e6b2e5a6463", + "section_type": "main", + "text": "\n\nIn 2010, a meta-analysis of 21 genome-wide association studies performed by Dupuis and colleagues identified ADCY5, PROX1, GCK, GCKR, and DGKB/TMEM195 as new genetic loci for T2D susceptibility [22].Among these loci, DGKB/TMEM195, GCK, PROX1, and ADCY5 mainly affect -cell functions, whereas the locus mapped in GCKR shows a primary effect on insulin action [22].In the same year, another genome-wide association study by Qi and colleagues discovered new variants near RBMS1 and ITGB6 genes at 2q24, and these variants were found to affect glucose metabolism and insulin resistance [23].In addition, an expanded meta-analysis of existing GWAS by Voight and colleagues identified 12 new signals with a combined < 5 × 10 −8 , including BCL11A, ZBED3, KLF14, TP53INP1, TLE4, CENTD2, HMGA2, HNF1A, PRC1, ZFAND6, DUSP9, and KCNQ1 [24].HNF1A was previously recognized as the causal gene of MODY3 [62] and also harbored the common variant (G319S) that contributes to early-onset T2D [63,64].DUSP9, mapped on chromosome X, encodes a member of the family of mitogen-activated protein kinase phosphatase 4, MKP4, which is important in cell cycle regulation and plays pivotal roles in regulating insulin action [65][66][67]." + }, + { + "document_id": "b978a189-6fbd-4791-8072-7db79f43746a", + "section_type": "main", + "text": "RESULTS-\n\nWe confirmed the associations of TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, and FTO with risk for type 2 diabetes, with odds ratios ranging from 1.13 to 1.35 (1.3 ϫ 10 Ϫ12 Ͻ P unadjusted Ͻ 0.016).In addition, the A allele of rs8050136 at FTO was associated with increased BMI in the control subjects (P unadjusted ϭ 0.008).However, we did not observe significant association of any genetic variants with surrogate measures of insulin secretion or insulin sensitivity indexes in a subset of 2,662 control subjects.Compared with subjects carrying zero, one, or two risk alleles, each additional risk allele was associated with 17% increased risk, and there was an up to 3.3-fold increased risk for type 2 diabetes in those carrying eight or more risk alleles.Despite most of the effect sizes being similar between Asians and Europeans in the metaanalyses, the ethnic differences in risk allele frequencies in most of these genes lead to variable attributable risks in these two populations." + }, + { + "document_id": "2bef9608-4bd6-4252-9fbd-2413b2cad4f8", + "section_type": "main", + "text": "\n\nBecause obesity is linked to the development of T2D, we adjusted for body mass index (BMI) in the regression and found that the association of these genes with diabetes-related traits remained significant (Supplementary Tables 17 and 18).We used the generalized linear mixed model implemented by SAIGE-Gene which accounts for relatedness and adjusts for unbalanced case-control ratios 16 to verify association of our variant sets of interest with glucose, HbA1c, and T2D diagnosis.SAIGE-Gene was run in the European ancestry population including related individuals (n = 398,574).Using the p-value thresholds previously employed, all associations were statistically significant using this method apart from the associations of TNRC6B pLOF with HbA1c (p = 6.85 × 10 -6 ) and T2D diagnosis (p = 4.77 × 10 -5 ) which were less significant (Supplementary Table 19)." + }, + { + "document_id": "8cd81e24-a326-4443-bc37-0e6e421e70b2", + "section_type": "main", + "text": "\n\nTo date, more than 70 genes have been identified as involved in T2DM, primarily by association analysis [34].In addition, via GWAS arrays, more than 100 SNPs have been identified for T2DM [35].From the 50 novel loci associated with T2DM previously identified, more than 40 loci have been associated with T2DM-related traits, including fasting proinsulin, insulin and glucose (Table 1) [36][37][38][39].However, for T2DM-related traits, such as the HOMA index or pancreatic β cell function, there are virtually no published data examining the relationship between these traits or the genotype and environment interactions.Clinical investigations of some loci have suggested that the genetic components of T2DM risk act preferentially through β cell function [40].Among all 40 loci associated with T2DM-related traits, only transcription factor-7-like 2 (TCF7L2) was shown to clearly contribute to T2DM risk [41].Several studies in white European [42], Indian [43], Japanese [44], Mexican American [45] and West African [46] individuals have shown a strong association between TCF7L2 and T2DM.It is also noteworthy that these populations represent the major racial groups with a high prevalence of T2DM.In all populations, TCF7L2 showed a strong association, with the odds of developing T2DM increased by 30%-50% for each allele inherited.This finding indicates an approximately double odds ratio compared to most other diabetes susceptibility polymorphisms.TCF7L2 is a transcription factor involved in the Wnt signaling pathway that is ubiquitously expressed, and it has been observed that TCF7L2 risk alleles result in the overexpression of TCF7L2 in pancreatic β cells.This overexpression causes reduced nutrient-induced insulin secretion, which results in a direct predisposition to T2DM as well as an indirect predisposition via an increase in hepatic glucose production [47]." + }, + { + "document_id": "6b7c6ac7-208d-4942-af31-cc3c37252751", + "section_type": "main", + "text": "\n\nImportantly, our findings demonstrate that more than 50% of the genes in which genetic variants have been known to increase risk of T2DM showed altered expression in different tissues.The perturbation was highest, as expected, in pancreatic islets, where eight genes i.e.HHEX, HNF1B, KCNQ1, NOTCH2, TCF7L2, THADA, TSPAN8 and WFS1, showed aberrant expression.All of these genetic loci, apart from the less studied TSPAN8, have been implicated in pathways primarily involved in insulin secretion, cell proliferation and regeneration [30].Of note, genetic variants in the THADA and WFS1 have recently been shown to impair glucagon-like peptide-1stimulated insulin secretion [31,32].Furthermore, many of these loci have also shown effects on insulin sensitivity [33].In line with this, five genes, i.e.HNF1B, IRS1, KCNJ11, NOTCH2 and WFS1, were also differentially expressed in skeletal muscle.Of all T2DM genes, IRS1 seems to have a clear effect on insulin sensitivity; the T2DM-associated allele was associated with decreased IRS1 protein expression as well as reduced phosphatidylinositol-3-kinase-activity and insulin-stimulated glucose uptake in humans [12]." + }, + { + "document_id": "b978a189-6fbd-4791-8072-7db79f43746a", + "section_type": "abstract", + "text": "\nOBJECTIVE-Recent genome-wide association studies have identified six novel genes for type 2 diabetes and obesity and confirmed TCF7L2 as the major type 2 diabetes gene to date in Europeans.However, the implications of these genes in Asians are unclear.RESEARCH DESIGN AND METHODS-We studied 13 associated single nucleotide polymorphisms from these genes in 3,041 patients with type 2 diabetes and 3,678 control subjects of Asian ancestry from Hong Kong and Korea. RESULTS-We confirmed the associations of TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/CDKN2B, IGF2BP2, and FTO with risk for type 2 diabetes, with odds ratios ranging from 1.13 to 1.35 (1.3 ϫ 10 Ϫ12 Ͻ P unadjusted Ͻ 0.016).In addition, the A allele of rs8050136 at FTO was associated with increased BMI in the control subjects (P unadjusted ϭ 0.008).However, we did not observe significant association of any genetic variants with surrogate measures of insulin secretion or insulin sensitivity indexes in a subset of 2,662 control subjects.Compared with subjects carrying zero, one, or two risk alleles, each additional risk allele was associated with 17% increased risk, and there was an up to 3.3-fold increased risk for type 2 diabetes in those carrying eight or more risk alleles.Despite most of the effect sizes being similar between Asians and Europeans in the metaanalyses, the ethnic differences in risk allele frequencies in most of these genes lead to variable attributable risks in these two populations. CONCLUSIONS-Ourfindings support the important but differential contribution of these genetic variants to type 2 diabetes and obesity in Asians compared with Europeans.Diabetes 57: 2226-2233, 2008T ype 2 diabetes is a major health problem affecting more than 170 million people worldwide.In the next 20 years, Asia will be hit hardest, with the diabetic populations in India and China more than doubling (1).Type 2 diabetes is characterized by the presence of insulin resistance and pancreatic -cell dysfunction, resulting from the interaction of genetic and environmental factors.Until recently, few genes identified through linkage scans or the candidate gene approach have been confirmed to be associated with type 2 diabetes (e.g., PPARG, KCNJ11, CAPN10, and TCF7L2).Under the common variant-common disease hypothesis, several genome-wide association (GWA) studies on type 2 diabetes have been conducted in large-scale case-control samples.Six novel genes (SLC30A8, HHEX, CDKAL1, CDKN2A and CDKN2B, IGF2BP2, and FTO) with modest effect for type 2 diabetes (odds ratio [OR] 1.14 -1.20) had been reproducibly demonstrated in multiple populations of European ancestry.Moreover, TCF7L2 was shown to have the largest effect for type 2 diabetes (1.37) in the European populations to date (2-8).Although many of these genes may be implicated in the insulin production/secretion pathway (TCF7L2, SLC30A8, HHEX, CDKAL1, CDKN2A/B, and IGF2BP2) (6,9 -11), FTO is associated with type 2 diabetes through its regulation of adiposity (8,12,13).Moreover, two adjacent regions near CDKN2A/B are associated with type 2 diabetes and cardiovascular diseases risks, respectively (7,14 -16).Despite the consistent associations among Europeans, the contributions of these genetic variants in other ethnic groups are less clear.Given the differences in environmental factors (e.g., lifestyle), risk factor profiles (body composition and insulin secretion/resistance patterns), and genetic background (linkage disequilibrium pattern and risk allele frequencies) between Europeans and Asians, it is important to understand the role of these genes in Asians.A recent case-control study in 1,728 Japanese subjects revealed nominal association to type 2 diabetes for variants at the SLC30A8, HHEX, CDKAL1, CDKN2B, and FTO genes but not IGF2BP2 (17).In the present large-scale case-control replication study of 6,719 Asians, we aimed to test for the association of six novel genes from GWA studies and TCF7L2, which had the largest effect in Europeans, and their joint effects on type 2 diabetes risk and metabolic traits. RESEARCH DESIGN AND METHODSAll subjects were recruited from Hong Kong and Korea and of Asian ancestry.The subjects in the Hong Kong case-control study were of southern Han Chinese ancestry residing in Hong Kong.Participants for the case cohort consisting of 1,481 subjects with type 2 diabetes were selected from two" + }, + { + "document_id": "2bef9608-4bd6-4252-9fbd-2413b2cad4f8", + "section_type": "main", + "text": "\n\nTo see which other significant genes were likely to have a role in diabetes we looked at all variant sets with a significant glucose, HbA1c, or T2D association and examined whether they had associations with additional diabetes traits (p ≤ 0.0016, correcting for 32 sets tested).Damaging missense variants in PDX1 and PFAS, which significantly associated with HbA1c levels in our primary analysis, associated with T2D diagnosis using this threshold (Table 3 and Supplementary Table 14)." + }, + { + "document_id": "31588831-61b3-4018-9962-bd6985c3061b", + "section_type": "main", + "text": "Box 1: Genes nearest to loci associated with fasting diabetes-related quantitative traits\n\nThe DGKB-TMEM195 locus was recently reported to be associated with fasting glucose 24 ; here we report genome-wide significant replication of that finding and evaluate the genes mapping closest to the lead SNP in further detail.DGKB encodes the β (1 of 10) isotype of the catalytic domain of diacylglycerol kinase, which regulates the intracellular concentration of the second messenger diacylglycerol.In rat pancreatic islets, glucose increases diacylglycerol 49 , which activates protein kinase C (PKC) and thus potentiates insulin secretion 50 .TMEM195 encodes transmembrane protein 195, an integral membrane phosphoprotein highly expressed in liver.ADCY5 encodes adenylate cyclase 5, which catalyzes the generation of cAMP.Upon binding to its receptor in pancreatic beta cells, glucagon-like peptide 1 (GLP-1) induces cAMP-mediated activation of protein kinase A, transcription of the proinsulin gene and stimulation of insulin secretory processes 51 ." + }, + { + "document_id": "16e272af-f687-4261-99cf-8125a9e7cdc7", + "section_type": "main", + "text": "\n\nFigure2| effect sizes of the 11 common variants confirmed to be involved in type 2 diabetes risk.The x axis gives the year that published evidence reached the levels of statistical confidence that are now accepted as necessary for genetic association studies.CDKAL1, CDK5 regulatory subunitassociated protein 1-like 1; CDKN2, cyclin-dependent kinase inhibitor 2A; FTO, fat mass and obesity-associated; HHEX, haematopoietically expressed homeobox; IDE, insulin-degrading enzyme; IGF2BP2, insulin-like growth factor 2 mRNA-binding protein 2; KCNJ11, potassium inwardly-rectifying channel, subfamily J, member 11; PPARG, peroxisome proliferator-activated receptor-γ gene; SLC30A8, solute carrier family 30 (zinc transporter), member 8; TCF2, transcription factor 2, hepatic; TCF7L2, transcription factor 7-like 2 (T-cell specific, HMg-box); WFS1, Wolfram syndrome 1." + }, + { + "document_id": "5564cfa4-6a5c-4328-a0b6-5cd1cc0b2338", + "section_type": "main", + "text": "Box 1: Genes nearest to loci associated with fasting diabetes-related quantitative traits\n\nThe DGKB-TMEM195 locus was recently reported to be associated with fasting glucose 24 ; here we report genome-wide significant replication of that finding and evaluate the genes mapping closest to the lead SNP in further detail.DGKB encodes the β (1 of 10) isotype of the catalytic domain of diacylglycerol kinase, which regulates the intracellular concentration of the second messenger diacylglycerol.In rat pancreatic islets, glucose increases diacylglycerol 49 , which activates protein kinase C (PKC) and thus potentiates insulin secretion 50 .TMEM195 encodes transmembrane protein 195, an integral membrane phosphoprotein highly expressed in liver.ADCY5 encodes adenylate cyclase 5, which catalyzes the generation of cAMP.Upon binding to its receptor in pancreatic beta cells, glucagon-like peptide 1 (GLP-1) induces cAMP-mediated activation of protein kinase A, transcription of the proinsulin gene and stimulation of insulin secretory processes 51 ." + }, + { + "document_id": "9e3a4f4a-24d6-4a12-a798-ca654e225e7e", + "section_type": "main", + "text": "\n\nWhile the above findings show no evidence of association between relevant mitochondrial gene sets and T2D, these genes could still display causal associations with specific intermediate phenotypes linked to the disease.Support for this comes from reported mitochondrial dysfunction in insulin-resistant individuals [8].Therefore, we tested the same three gene sets described above for enrichment of associations with seven different glucose and insulin-related traits characteristic of T2D, using GWA metaanalyses of up to 46,186 non-diabetic individuals [37,38] (Soranzo N. et al., unpublished data).The quantitative traits analyzed include fasting levels of glucose and insulin, glucose and insulin levels 2 hours following a 75-gram oral glucose tolerance test, indices of b-cell function (HOMA-B) and insulin resistance (HOMA-IR) [49], and glycated hemoglobin levels (HbA 1C ), which reflect long-term plasma glucose concentrations (see Materials and Methods)." + }, + { + "document_id": "7bd7a98f-955a-4988-8981-a0ff7ab6f7df", + "section_type": "main", + "text": "\n\nSimilar findings to AMD are now unfolding with type 2 DM.Grant et al. (24) first reported on a variant of the gene TCF7L2, which has been linked to reduced beta cell function and poor insulin response to oral glucose loads (51).Since its first discovery, this gene has been widely confirmed in independent studies as a pivotal susceptibility marker for type 2 DM (23,(25)(26)(27)(28)40).Recently, 6 genome-wide SNP association studies have identified and replicated in separate stages several additional novel genes conferring susceptibility to type 2 DM (23,(25)(26)(27)(28)40) (Table 2).Interestingly, these loci primarily include genes involved in pancreatic beta cell development and function as opposed to insulin resistance-the current accepted mechanism for type 2 DM.This development casts doubt on our traditional pathophysiological modeling of the type 2 diabetic patient and underscores the need for genomic studies to further define pathobiological processes of complex traits." + }, + { + "document_id": "4fe0a01d-3be8-4cd5-ac59-8b0ef085b20c", + "section_type": "main", + "text": "\n\nG enome-wide association studies (GWAS) have iden- tified several type 2 diabetes mellitus (T2DM) susceptibility loci including CDKAL1, CDKN2B, IGF2BP2, HHEX, SLC30A8, PKN2, LOC387761 (1)(2)(3)(4)(5), and KCNQ1, which was recently identified by similar GWAS approach in two independent Japanese samples (6,7).Although these associations have been well replicated in Japanese populations (8), the role of these loci in other East Asian populations remains less clear.For example, a study in China by Wu et al. (9) did not find significant associations between single-nucleotide polymorphisms (SNPs) in IGF2BP2 and SLC30A8 with T2DM, whereas an association between SNPs at the HHEX locus and T2DM was reported among Chinese living in Shanghai, but not among Chinese in Beijing.Another study in Hong Kong Chinese (10) also did not find an association with SNPs at the IGF2BP2 locus; however, they reported an association between T2DM with SNPs at the HHEX and SLC30A8 loci." + }, + { + "document_id": "fdbabc3c-ec60-45ce-9f5c-683f745c4d00", + "section_type": "main", + "text": "\n\nIn addition, these analyses highlighted notable biological connections between sets of genes within confirmed T2D-association regions.For example, HMGA2 emerges as a key transcriptional regulator of IGF2BP2 (refs.53,54).However, because Hmga/Hmg1c knockout mice are deficient in adipocyte differentiation 45 , and the IGF2BP2 risk allele is associated with reduced beta-cell function 55 , further work is required to establish the relevance of this regulatory Each point refers to a single T2D association signal, with colors denoting the strength of the association to either the x-axis variable (lefthand of each pair of plots) or y-axis variable (right-hand of each pair) (red, P < 10 −3 ; orange, 10 −3 < P < 10 −2 ; yellow, 0.01 < P < 0.05; green, 0.05 < P < 0.20; blue, P > 0.20).The two KCNQ1 associations are distinguished by the notation KCNQ1 for rs163184 and KCNQ1* for rs231362.The gene names associated with each signal have been chosen on the basis of proximity to the index SNP and should not be presumed to indicate causality." + }, + { + "document_id": "31588831-61b3-4018-9962-bd6985c3061b", + "section_type": "main", + "text": "\n\nTesting of these loci for association with T2D as a dichotomous trait in up to 40,655 cases and 87,022 nondiabetic controls demonstrated that the fasting glucose-raising alleles at seven loci (in or near ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 and the known T2D genes TCF7L2 and SLC30A8) are robustly associated (P < 5 × 10 −8 ) with increased risk of T2D (Table 2).The association of a highly correlated SNP in ADCY5 with T2D in partially overlapping samples is reported by our companion manuscript 29 .We found less significant T2D associations (P < 5 × 10 −3 ) for variants in or near CRY2, FADS1, GLIS3 and C2CD4B (Table 2).These data clearly show that loci with similar fasting glucose effect sizes may have very different T2D risk effects (see, for example, ADCY5 and MADD in Table 2)." + }, + { + "document_id": "5564cfa4-6a5c-4328-a0b6-5cd1cc0b2338", + "section_type": "main", + "text": "\n\nTesting of these loci for association with T2D as a dichotomous trait in up to 40,655 cases and 87,022 nondiabetic controls demonstrated that the fasting glucose-raising alleles at seven loci (in or near ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 and the known T2D genes TCF7L2 and SLC30A8) are robustly associated (P < 5 × 10 −8 ) with increased risk of T2D (Table 2).The association of a highly correlated SNP in ADCY5 with T2D in partially overlapping samples is reported by our companion manuscript 29 .We found less significant T2D associations (P < 5 × 10 −3 ) for variants in or near CRY2, FADS1, GLIS3 and C2CD4B (Table 2).These data clearly show that loci with similar fasting glucose effect sizes may have very different T2D risk effects (see, for example, ADCY5 and MADD in Table 2)." + }, + { + "document_id": "18a35699-873a-4542-b35a-3a4a14edd628", + "section_type": "main", + "text": "\n\nIn another important study, 12 loci, previously identified by GWAS as predictors of coronary heart disease (CHD) in the general population, were investigated in three CHD case-control studies of diabetic patients.Among them, five variants, rs4977574 (CDKN2A/2B), rs12526453 (PHACTR1), rs646776 (CELSR2-PSRC1-SORT1), rs2259816 (HNF1A), and rs11206510 (PCSK9), showed a significant association with the risk for CHD also in type 2 DM (43).Among the type 2 DM susceptibility genes investigated by GWAS, the transcription factor 7-like 2 gene (TCF7L2) has been identified as one of the most significant (73).TCF7L2 variants have been found to be associated with CVD in some (40,53), but not in all (74) reports, although the association between TCF7L2 risk alleles and CAD was not higher in diabetic individuals.Subsequent studies analyzed the association of three TCF7L2 variants (rs7903146, rs12255372, and rs11196205) with CAD in 1,650 patients that underwent coronary angiography, and found that these variants were more strongly associated with CAD in diabetic patients than in non-diabetics (54)." + }, + { + "document_id": "63752d7d-dfdd-48a2-9f39-e1672255a519", + "section_type": "main", + "text": "Other Association Studies of T2D\n\nAnother strong candidate gene for T2D is ABCC8, which encodes the sulfonylurea receptor (SUR1).This protein is the drug target for a widely used class of hypoglycemic medications, and the ABCC8 gene is also mutated in the monogenic disorder familial hyperinsulinism (168).ABCC8 carries a silent C → T polymorphism in exon 18 (T759T; also reported as \"exon 22\" or T761T), which has been associated with T2D in several populations (3,70,73,92), though not in others (3,63,64,77,103,149).The same gene also harbors an intronic cag → tag polymorphism at the -3 position (variably reported as \"intron 24\" or \"exon 16,\" depending on the gene orientation), with the preponderance of the evidence favoring the c allele as the one conferring risk (92,121), although other groups disagree (3, 70,77,135,149)." + }, + { + "document_id": "45c14654-f263-4031-9941-206d7b6a97f3", + "section_type": "main", + "text": "\n\nDespite identification of many putative causative genetic variants, few have generated credible susceptibility variants for type 2 diabetes.Indeed, the most important finding using linkage studies is the discovery that the alteration of TCF7L2 (TCF-4) gene expression or function (33) disrupts pancreatic islet function and results in enhanced risk of type 2 diabetes.Candidate gene studies have also reported many type 2 diabetes-associated loci and the coding variants in the nuclear receptor peroxisome proliferator-activated receptor-g (34), the potassium channel KCNJ11 (34), WFS1 (35), and HNF1B (TCF2) (36) are among the few that have been replicated (Table 2).Recently, there have been great advances in the analysis of associated variants in GWA and replication studies due to highthroughput genotyping technologies, the International HapMap Project, and the Human Genome Project.Type 2 susceptibility loci such as JAZF1, CDC123-CAMK1D, TSPAN8-LGR5, THADA, ADAMTS9, NOTCH2, and ADCY5 (37,38) are among some of the established loci (Table 2).CDKN2A/B, CDKAL1, SLC30A8, IGF2BP2, HHEX/IDE, and FTO are other established susceptibility loci for diabetes (Table 2) (34,39,40).GWA studies have also identified the potassium voltage-gated channel KCNQ1 (32) as an associated gene variant for diabetes.A recent GWA study reporting a genetic variant with a strong association with insulin resistance, hyperinsulinemia, and type 2 diabetes, located adjacent to the insulin receptor substrate 1 (IRS1) gene, is the C allele of rs2943641 (41).Interestingly, the parental origin of the single nucleotide polymorphism is of importance because the allele that confers risk when paternally inherited is protected when maternally transmitted.GWA studies for glycemic traits have identified loci such as MTNR1B (42), GCK (glucokinase) (42), and GCKR (glucokinase receptor) (42); however, further investigation of genetic loci on glucose homeostasis and their impact on type 2 diabetes is needed.Indeed, a recent study by Soranzo et al. (42) using GWA studies identified ten genetic loci associated with HbA 1c .Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin may be associated with changes in levels of HbA 1c ." + }, + { + "document_id": "559a3a15-da15-4132-a8b5-5401bfe770ef", + "section_type": "main", + "text": "\n\nIn studies where overt T2D has been the phenotype the majority of associated polymorphisms have encoded proteins known to be involved in β-cell metabolism; for example TCF7L2, KCNJ11 and HHEX have shown robust association [170,171].This suggests that these genes could prove useful in predicting β-cell preservation during the course of T2D.The glucokinase gene (GCK) coding for the initial glucose-sensing step in the β-cell can have activating mutations causing hypoglycemia that might provide structural and functional models leading to drug targets for treating T2D [172].In the GoDARTs study, investigators examined the medication response of metformin and sulphonylurea based on the TCF7L2 variants mainly affecting the β-cell.The carriers of the at risk 'T' allele responded less well to sulphonylurea therapy than metformin [173].Also it is of significant public health interest that in the Diabetes Prevention Program, lifestyle modifications were shown to reduce the risk of diabetes conferred by risk variants of TCF7L2 at rs7093146, and in placebo participants who carried the homozygous risk genotype (TT), there was 80% higher risk for developing diabetes compared to the lifestyle intervention group carrying the same risk genotypes [35].These findings could herald significant future progress in the field of T2D pharmacogenomics, possibly leading to the development and use of agents tailored on the basis of genotype." + }, + { + "document_id": "8cd81e24-a326-4443-bc37-0e6e421e70b2", + "section_type": "main", + "text": "Most Relevant T2DM Susceptibility Genes\n\nGene and environment interaction studies have shown a nice association between variants in peroxisome proliferator-activated receptor gamma (PPARG), TCF7L2 and fat mass and obesity-associated protein (FTO) genes, a Western dietary pattern and T2DM." + }, + { + "document_id": "2dade65a-5d31-4839-b2c9-4c6cd3056f58", + "section_type": "main", + "text": "\n\nOne obvious locus to consider is TCF7L2 in the context of type 2 diabetes.Common genetic variation located within the gene encoding transcription factor 7 like 2 (TCF7L2) has been consistently reported to be strongly associated with the disease.Such reports range from 2006, when we first published the association [3], to the recent transethnic meta-analysis GWAS of type 2 diabetes [4]." + }, + { + "document_id": "1a93e25f-2a43-49e9-8450-03a57c93e613", + "section_type": "main", + "text": "\n\nFor eighteen genes only limited functional information is available as a basis for assessing a possible relationship to T2DM: Ccrn4l, Serpina12, Htatip2, Mest, Pgcp, Tmsb4x, Angptl4, Mrpl33, Ndfip1, Yipf5, Tmem30a, Asnsd1, Oact5, Larp5, Thrsp, 1810015C04Rik, 2310003F16Rik, and 2610002J02Rik.High genetic variation is known for Pgcp in mouse.Serpina12, a target of Hnf4a, is massively changed in liver and 1810015C04Rik in pancreatic islets." + }, + { + "document_id": "5293f814-f4a7-48e0-b4e5-b1f13fdc8516", + "section_type": "main", + "text": "\n\nGlucagon receptor.The G 40 S variant has been associated with T2D in some but not all populations. 56sulin.Case-control studies have suggested an association between T2D and variation at a regulatory minisatellite upstream of the insulin gene.Unlike type 1 diabetes, susceptibility to T2D is associated with the larger class III alleles. 30To rule out the possibility of latent population substructure, Huxtable et al applied family-based association methods (using parent ± ospring trios ascertained via individuals with early-onset T2D) to con®rm this class III association and to show that the susceptibility eect is preferentially transmitted via the paternal allele. 31This ®ts neatly with evidence of maternal imprinting in this region during early development." + }, + { + "document_id": "2bef9608-4bd6-4252-9fbd-2413b2cad4f8", + "section_type": "main", + "text": "\n\nWe also examined whether we detect associations for the 8 genes encoding T2D drug targets (GLP1R, IGF1R, PPARG, INSR, SLC5A2, DPP4, KCNJ11, ABCC8).Variant sets in three of these genes, DPP4, GLP1R and KCNJ11 significantly associated with either T2D diagnosis or HbA1c levels (p ≤ 0.003 correcting for 15 variant sets tested) and an additional 4 genes had a nominally significant association with T2D and/or HbA1c (Supplementary Figure 5 and Supplementary Table 27).Table 3. Genes and variant sets associated with multiple diabetes-related traits.Variant sets significant for at least one trait in our primary analysis that are also associated with additional diabetes traits (p ≤ 0.0016, 32 sets tested) are shown.Effect is shown in SD of transformed values or as an odds ratio (OR).www.nature.com/scientificreports/PheWAS of GIGYF1 pLOF reveals associations with cholesterol levels, hypothyroidism and complications of diabetes.The most significant novel associations were seen for GIGYF1 pLOF which associated with increased glucose and HbA1c levels as well as increased incidence of T2D diagnosis.To give additional insight into the biological roles of GIGYF1 we performed a phenome-wide association study (PheWAS) testing GIGYF1 pLOF for association with 142 quantitative traits and 262 ICD10-coded diagnoses (Fig. 3).GIGYF1 pLOF strongly associated with decreased levels of total cholesterol (p = 2.44 × 10 -12 , effect = − 0.61 SD) which was, in large part, driven by LDL cholesterol (p = 2.40 × 10 -10 , effect = − 0.56 SD) although an effect on HDL cholesterol was also observed (Table 4).To understand the extent to which this is influenced by the use of cholesterol-lowering medication in diabetics, we adjusted for medication use in the regression and also performed a separate analysis excluding those on cholesterol-lowering medication.The association between GIGYF1 pLOF and LDL cholesterol levels was significant in both analyses (Supplementary Table 28).GIGYF1 pLOF also associated with decreased grip strength and decreased peak expiratory flow.Notably, GIGYF1 pLOF also associated with increased levels of the kidney injury biomarker cystatin c (p = 6.65 × 10 -6 , effect = 0.36 SD) and increased diagnosis of urinary system disorders (p = 7.32 × 10 -5 , OR = 2.71) (Tables 4 and 5)." + }, + { + "document_id": "553ae95d-0a2b-4f2a-8123-da9a9e9e7a77", + "section_type": "main", + "text": "\n\nMinor susceptibility might operate in some populations from other genes, including insulin receptor substrate 1 ( IRS -1 ), adiponectin ( ACDC ) or ectonucleotide pyrophosphatase/phosphodiesterase 1 enzyme ( ENPP1 ) in a context of obesity or diabesity.• In genome scans of diabetic families, loci for T2DM have been found at several sites, including chromosomes 1q, 2q ( NIDDM1 ), 2p, 3q, 12q, 11q, 10q and 20.NIDDM1 has been identifi ed as coding for calpain 10, a non -lysosomal cysteine protease with actions at the mitochondria and plasma membrane, and also in pancreatic β -cell apoptosis.• In 2007, fi ve large genome -wide association studies in European descent populations have identifi ed new potential T2DM genes, including the Wnt signaling related transcription factors TCF7L2 and HHEX , the zinc transporter ZnT8 ( SLC30A8 ), the CDK5 regulatory subunit -associated protein 1 -like 1 ( CDKAL1 ) and a regulatory protein for IGF2 ( IGF2BP2 ).A consensus of close to 20 confi rmed T2DMsusceptibility loci to date provided novel insights into the biology of T2DM and glucose homeostasis, but individually with a relatively small genetic effect.Importantly, these genes implicate several pathways involved in β -cell development and function.• Compared with clinical risk factors alone, the inclusion of common genetic variants (at least those identifi ed to date) associated with the risk of T2DM has a small effect on the ability to predict future development of T2DM.At the individual level, however, a combined genotype score based on 15 risk alleles confers a 5 -8 fold increased risk of developing T2DM.Identifying the subgroups of individuals at higher risk is important to target these subjects with more effective preventative measures." + }, + { + "document_id": "752b2413-8c90-4af7-b65b-db429145b3bb", + "section_type": "abstract", + "text": "\nThe intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis.However, the specific genes through which these regulatory variants act remain poorly characterized.We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and highdensity genotyping.We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations.At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5.At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1.At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis.Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci." + }, + { + "document_id": "d9564b3c-efac-42ae-8e15-bf962c0a7a3c", + "section_type": "main", + "text": "Introduction\n\nMany genes have been evaluated as candidates for T2D susceptibility.However, only variants in the TCF7L2, PPARG, KCNJ11 and HNFA4 genes have been extensively replicated in populations around the world, showing their indisputable association with T2D risk (Zeggini 2007).In the particular case of the HNF4A gene, it has been implicated in maturity-onset diabetes of the young type 1 (MODY 1) (Mitchell and Frayling 2002;Zhu et al. 2003).HNF4A is a member of the nuclear receptor super-family that plays a critical role in embryogenesis and metabolism, by regulating gene expression in pancreatic beta cells, liver and other tissues.The HNF4A gene is localized to chromosome 20q13, a region that has demonstrated evidence for linkage with T2D (Sladek et al. 1990;Ghosh et al. 1999).Several genetic studies, mainly in Caucasian and Asian populations, have provided evidence for the association of the variants in HNF4A with T2D (Ghosh et al. 1999;Silander et al. 2004;Winckler et al. 2005)." + }, + { + "document_id": "faa23996-65fc-4bc6-938a-c959e981d493", + "section_type": "main", + "text": "\n\nMost (71%) of the 1895 genes had minimal evidence linking them to a causal role in T2D pathogenesis (PCS < 0.05) (Additional file 4: Figure S3).However, 95% of T2D loci included at least one gene (median, 3) with PCS > 0.10, and at 70% of loci, there was at least one gene with PCS > 0.20 (Additional file 4: Figure S3).The top-scoring genes across the 101 loci (such as IRS1 [PCS = 0.69], SLC30A8 [PCS = 0.77], HNF1B [PCS = 0.54]) include many of the genes with the strongest prior claims for involvement in T2D risk, prior claims which arise in part from data used to generate the PCSs.For example, these genes each contain rare coding variants directly implicated in the development of T2D (or related conditions): these rare variants are independent of the common variant GWAS signals, but their relationship to diabetes is likely to have been captured through the semantic mapping.The PCS also highlighted several other highly scoring candidates with known causal roles in relation to diabetes and obesity such as MC4R (PCS = 0.43), WFS1 (0.41), ABCC8 (0.37), LEP (0.27), GCK (0.24) and HNF1A (0.23).At other loci, these analyses highlighted candidates that have received scant attention to date; for example, CENPW (PCS = 0.83) scored highly both in terms of semantic links to T2D-relevant processes and an adipose cis-eQTL linking the T2D GWAS SNP to CENPW expression [21]." + }, + { + "document_id": "a579db95-2a40-43ff-b237-d47f90aaf64f", + "section_type": "main", + "text": "Genes boosted in type 2 diabetes\n\nBefore the Wellcome Trust study, PPARG, KCNJ11, and TCF7L2 had all been identified as genes involved in type 2 diabetes through genome-wide association studies and replicated in follow-up studies (for review, see Bonnefond et al. 2010).The strongest candidate gene for type 2 diabetes, TCF7L2, was also the strongest signal seen in the Wellcome trust study, although the others were not so strong.However, the exact mechanism by which TCF7L2 acts was not entirely clear.In our analysis (Fig. 5), we find it directly connected to the b-catenin/WNT signaling pathway by its functional connection to CTNNB1, as well as to BACH2, a gene that has been repeatedly implicated in type 1 diabetes (e.g., Cooper et al. 2008;Madu et al. 2009), but which has not yet been linked to type 2 diabetes.BACH2 is among the genes most strongly boosted by network linkages, deriving additional signal from CREB5 and PARD3B, which both score highly in the GWAS data.PARD6G, PARD3B, and CDC42 are also emphasized by the method.Notably, these genes form a complex with PRKCZ (Koh et al. 2008), a variant of which correlates with type 2 diabetes in Han Chinese (Qin et al. 2008).EBF1, a known regulator of adipocyte differentiation (Akerblad et al. 2005) is also strongly boosted by the network, supporting a possible role in type 2 diabetes." + }, + { + "document_id": "2bef9608-4bd6-4252-9fbd-2413b2cad4f8", + "section_type": "main", + "text": "Identification of genes with a biological role in diabetes. Variants in two genes, GCK and GIGYF1, significantly associated with glucose, HbA1c and T2D diagnosis, strongly suggesting a biological role in diabetes; GCK is involved in Mendelian forms of diabetes while GIGYF1 has not previously been implicated by genetics in the disease.Both GCK and GIGYF1 are located on chromosome 7 but are 56 Mb apart, strongly suggesting that these signals are independent; this independence was confirmed by conditional analysis (Supplementary Table 13).Two additional variant sets, HNF1A pLOF and TNRC6B pLOF, had genome-wide associations with both T2D diagnosis and HbA1c levels while G6PC2 damaging missense variants associated with decreased levels of both glucose and HbA1c but not T2D diagnosis (Table 3)." + }, + { + "document_id": "b1d09a6d-334a-48f4-b4ed-4754f398d046", + "section_type": "main", + "text": "\n\nThrough genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05).Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance.Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations.This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies.Functional analysis of these newly discovered loci will further improve our understanding of glycemic control." + }, + { + "document_id": "752b2413-8c90-4af7-b65b-db429145b3bb", + "section_type": "main", + "text": "\n\nThe intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis.However, the specific genes through which these regulatory variants act remain poorly characterized.We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and highdensity genotyping.We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations.At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5.At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1.At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis.Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci." + } + ], + "document_id": "8909D2606E33C312F2ECC705FAF65CA2", + "engine": "gpt-4", + "first_load": false, + "focus": "api", + "keywords": [ + "TCF7L2&gene", + "PPARG&gene", + "KCNJ11&gene", + "SLC30A8&gene", + "HHEX&gene", + "CDKAL1&gene", + "CDKN2A&gene", + "IGF2BP2&gene", + "FTO&gene", + "WFS1&gene" + ], + "metadata": [ + { + "object": "he aim of this study was to ascertain the polymorphic markers profile of ADIPOQ, KCNJ11 and TCF7L2 genes in Kyrgyz population and to analyze the association of polymorphic markers and combinations of ADIPOQ gene's G276T locus, KCNJ11 gene's Glu23Lys locus and TCF7L2 gene's VS3C>T locus with type two diabetes T2D in Kyrgyz population", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab334669" + }, + { + "object": "TCF7L2 gene expression was determined using quantitative real-time RT-PCR. Treatment with curcumin significantly increased TCF7L2 gene expression while treatment with LPS decreased TCF7L2 gene expression.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab767034" + }, + { + "object": "Novel mutations were detected in ABCC8 and KCNJ11 gene in Chinese patients with congenital hyperinsulinism CHI. Hotspot mutations such as T1042Qfs*75, I1511K, E501K, G111R in ABCC8 gene, and R34H in KCNJ11 gene are predominantly responsible for Chinese CHI patients.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab535847" + }, + { + "object": "Description of a novel missense mutation of the WFS1 gene in exon 4 of WFS1 gene in two Italian siblings with Wolfram syndrome.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab225713" + }, + { + "object": "Our results indicate that the genetic variation in the FTO gene might be related to single metabolic disturbances. However, the FTO gene polymorphisms are not associated with the risk of MetS [metabolic syndrome ].", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab560870" + }, + { + "object": "Common variations in the FTO gene are associated with hip fracture risk in women and that FTO gene may help improve the predictive value of hip fracture risk.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab150499" + }, + { + "object": "CDKAL1 gene rs7756992 A/G polymorphism was significantly associated with T2DM. The person with G allele of CDKAL1 gene rs7756992 A/G polymorphism might be predisposed to T2DM.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab131436" + }, + { + "object": "This FTO gene variation might influence the baseline lipid oxidation in PCOS patients and might explain the impact of the FTO gene on body weight in PCOS.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab929792" + }, + { + "object": "functionally distinct alleles of the PPARG gene are positioned in different parts of the cell nucleus. This confirms the importance of nuclear architecture to the regulation of PPARG gene transcription, and thus to the fate of the adipose cell.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab307597" + }, + { + "object": "The PPARG gene has been reported to be strongly associated with type-2 diabetes, but the present study did not support the hypothesis that the PPARG gene may also play an important role in the development of schizophrenia.", + "predicate": "http://www.w3.org/2000/01/rdf-schema#comment", + "subject": "ndd791caee50643ad90a986f563d2a0dab847159" + } + ], + "question": "what genes are associated with diabetes?", + "subquestions": null, + "task_id": "8909D2606E33C312F2ECC705FAF65CA2", + "usage": { + "chatgpt": 10960, + "gpt-4": 6551, + "gpt-4-turbo-preview": 5611 + }, + "user_id": 2 + }, + "document_id": "8909D2606E33C312F2ECC705FAF65CA2", + "task_id": "8909D2606E33C312F2ECC705FAF65CA2" +} |