Running Genome Wide Data Analysis Using a Parallel Approach on a Cloud Platform

Shared genetic etiology underlying Alzheimer's disease and type 2 diabetes

Polymorphisms in PDLIM5 gene are associated with alcohol dependence, type 2 diabetes, and hypertension

Ammonia is a toxic by-product of protein catabolism and is involved in changes in glutamate metabolism. Therefore, ammonia metabolism genes may link a range of diseases involving glutamate signaling such as Alzheimer's disease (AD), major depressive disorder (MDD), and type 2 diabetes (T2D). We analyzed data from a National Institute on Aging study with a family-based design to determine if 45 single nucleotide polymorphisms (SNPs) in glutaminase (GLS), carbamoyl phosphate synthetase 1 (CPS1), or glutamate-ammonia ligase (GLUL) genes were associated with AD, MDD, or T2D using PLINK software. HAPLOVIEW software was used to calculate linkage disequilibrium measures for the SNPs. Next, we analyzed the associated variations for potential effects on transcriptional control sites to identify possible functional effects of the SNPs. Of the SNPs that passed the quality control tests, four SNPs in the GLS gene were significantly associated with AD, two SNPs in the GLS gene were associated with T2D, and one SNP in the GLUL gene and three SNPs in the CPS1 gene were associated with MDD before Bonferroni correction. The in silico bioinformatic analysis suggested probable functional roles for six associated SNPs. Glutamate signaling pathways have been implicated in all these diseases, and other studies have detected similar brain pathologies such as cortical thinning in AD, MDD, and T2D. Taken together, these data potentially link GLS with AD, GLS with T2D, and CPS1 and GLUL with MDD and stimulate the generation of testable hypotheses that may help explain the molecular basis of pathologies shared by these disorders.

Aims/hypothesis: Genome-wide association studies have identified over 50 new genetic loci for type 2 diabetes (T2D). Several studies conclude that higher dietary heme iron intake increases the risk of T2D. Therefore we assessed whether the relation between genetic loci and T2D is modified by dietary heme iron intake.Methods: We used Affymetrix Genome-Wide Human 6.0 array data [681,770 single nucleotide polymorphisms (SNPs)] and dietary information collected in the Health Professionals Follow-up Study (n = 725 cases; n = 1,273 controls) and the Nurses’ Health Study (n = 1,081 cases; n = 1,692 controls). We assessed whether genome-wide SNPs or iron metabolism SNPs interacted with dietary heme iron intake in relation to T2D, testing for associations in each cohort separately and then meta-analyzing to pool the results. Finally, we created 1,000 synthetic pathways matched to an iron metabolism pathway on number of genes, and number of SNPs in each gene. We compared the iron metabolic pathway SNPs with these synthetic SNP assemblies in their relation to T2D to assess if the pathway as a whole interacts with dietary heme iron intake.Results: Using a genomic approach, we found no significant gene–environment interactions with dietary heme iron intake in relation to T2D at a Bonferroni corrected genome-wide significance level of 7.33 ×10-8 (top SNP in pooled analysis: intergenic rs10980508; p = 1.03 × 10-6). Furthermore, no SNP in the iron metabolic pathway significantly interacted with dietary heme iron intake at a Bonferroni corrected significance level of 2.10 × 10-4 (top SNP in pooled analysis: rs1805313; p = 1.14 × 10-3). Finally, neither the main genetic effects (pooled empirical p by SNP = 0.41), nor gene – dietary heme–iron interactions (pooled empirical p-value for the interactions = 0.72) were significant for the iron metabolic pathway as a whole.Conclusions: We found no significant interactions between dietary heme iron intake and common SNPs in relation to T2D.

BackgroundSeveral type 2 diabetes (T2D) susceptibility loci identified via genome-wide association studies were found to be replicated among various populations. However, the influence of these loci on T2D in Thai population is unknown. The aim of this study was to investigate the influence of eight single nucleotide polymorphisms (SNPs) reported in GWA studies on T2D and related quantitative traits in Thai population.MethodsEight SNPs in or near the KCNQ1, CDKN2A/2B, SLC30A8, HHEX, CDKAL1, TCF7L2, MTNR1B, and UBE2E2 genes were genotyped. A case-control association study comprising 500 Thai patients with T2D and 500 ethnically-matched control subjects was conducted. Associations between SNPs and T2D were examined by logistic regression analysis. The impact of these SNPs on quantitative traits was examined by linear regression among case and control subjects.ResultsFive SNPs in KCNQ1 (rs2237892), CDK2A/2B (rs108116610, SLC30A8 (rs13266634), TCF7L2 (rs7903146) and MTNR1B (rs1387153) were found to be marginally associated with risk of developing T2D, with odds ratios ranging from 1.43 to 2.02 (p = 0.047 to 3.0 × 10–4) with adjustments for age, sex, and body mass index. Interestingly, SNP rs13266634 of SLC30A8 gene reached statistical significance after correcting for multiple testing (p = 0.0003) (p < 0.006 after Bonferroni correction). However, no significant association was detected between HHEX (rs1111875), CDKAL1 (rs7756992), or UBE2E2 (rs7612463) and T2D. We also observed association between rs10811661 and both waist circumference and waist-hip ratio (p = 0.007 and p = 0.023, respectively). In addition, rs13266634 in SLC30A8 was associated with glycated hemoglobin (p = 0.018), and rs7903146 in TCF7L2 was associated with high-density lipoprotein cholesterol level (p = 0.023).ConclusionOf the eight genes included in our analysis, significant association was observed between KCNQ1, CDKN2A/2B, SLC30A8, TCF7L2, and MTNR1B loci and T2D in our Thai study population. Of these, CDKN2A/2B, SLC30A8, and TCF7L2 genes were also significantly associated with anthropometric, glycemic and lipid characteristics. Larger cohort studies and meta-analyses are needed to further confirm the effect of these variants in Thai population.

Introduction: Despite the largely reported inverse association between coffee intake and type 2 diabetes (T2D) risk by observational studies, the causality of such association is not well established. Hypothesis: We assessed the hypothesis that the observationally inverse association between coffee intake and T2D risk is causal. Methods: In a nested case-control study within the Singapore Chinese Health Study cohort, we included 2436 T2D cases and 2436 matched controls. At biospecimen collections (1999-2004), participants were free of diagnosed T2D, cardiovascular disease and cancer. Cases were participants who reported to have physician-diagnosed T2D at follow-up visits during 2006-2010. Controls were randomly selected among those who remained free of T2D and were matched to the index cases by age, sex, dialect group and date of biospecimen collection. We 1) tested the association between coffee intake and T2D risk using conditional logistic regression analysis; 2) tested the association of the nine single-nucleotide polymorphisms (SNPs) with coffee intake or risk of T2D; 3) used the instrumental variable (IV) estimators to quantify the strength of the causal association of coffee intake and risk of T2D. The IV estimator (β IV ) which is identical to that derived by the widely used two-stage least squares method, was calculated through dividing the β of the regression coefficients for SNP-T2D by SNP-coffee associations. Results: Median intake (inter quartile range) for coffee intake was 1.00 (0.36-2.51) cups/day in this population. Coffee intake was observationally associated with lower risk of T2D and OR (95% CI) was 0.93 (0.88-0.98) in multivariate adjusted model. We found three SNPs that were significantly associated with higher coffee intake with β coefficients (95% CI) as follows: 0.73 (0.23, 1.24) for rs4410790 (P=0.004), 0.72 (0.22, 1.22) for rs6968554 (P=0.005), and 1.60 (0.28, 2.91) for rs7800944 (P=0.017). Among these tree SNPs, two SNPs were marginally associated with higher T2D risk with OR (95% CI) identically 1.08 (0.99, 1.18) for 7:17284577 and 7:17287106, and the other one was insignificantly associated with lower risk (OR 0.94; 95% CI 0.75, 1.18). The estimated β IV coefficients (95% CI) was not statistically significant for any of the three SNPs: 0.10 (-0.04, 0.25) for rs4410790 (P=0.16), 0.11 (-0.04, 0.25) for rs6968554 (P=0.15), and -0.04 (-0.19, 0.11) for rs7800944 (P=0.60). Conclusions: High coffee intake was observationally associated with lower T2D risk, but our finding does not support a causal association.

Patients with bipolar disorder (BD) show higher frequency of obesity and type 2 diabetes (T2D), but the underlying genetic determinants and molecular pathways are not well studied. Using large publicly available datasets, we (1) conducted a gene-based analysis using MAGMA to identify genes associated with BD and body mass index (BMI) or T2D and investigated their functional enrichment; and (2) performed two meta-analyses between BD and BMI, as well as BD and T2D using Metasoft. Target druggability was assessed using the Drug Gene Interaction Database (DGIdb). We identified 518 and 390 genes significantly associated with BD and BMI or BD and T2D, respectively. A total of 52 and 12 genes, respectively, were significant after multiple testing correction. Pathway analyses conducted on nominally significant targets showed that genes associated with BD and BMI were enriched for the Neuronal cell body Gene Ontology (GO) term (p = 1.0E−04; false discovery rate (FDR) = 0.025) and different pathways, including the Signaling by Hedgehog pathway (p = 4.8E−05, FDR = 0.02), while genes associated with BD and T2D showed no specific enrichment. The meta-analysis between BD and BMI identified 64 relevant single nucleotide polymorphisms (SNPs). While the majority of these were located in intergenic regions or in a locus on chromosome 16 near and in the NPIPL1 and SH2B1 genes (best SNP: rs4788101, p = 2.1E−24), five were located in the ETV5 gene (best SNP: rs1516725, p = 1E−24), which was previously associated with both BD and obesity, and one in the RPGRIP1L gene (rs1477199, p = 5.7E−09), which was also included in the Signaling by Hedgehog pathway. The meta-analysis between BD and T2D identified six significant SNPs, three of which were located in ALAS1 (best SNP: rs352165, p = 3.4E−08). Thirteen SNPs associated with BD and BMI, and one with BD and T2D, were located in genes which are part of the druggable genome. Our results support the hypothesis of shared genetic determinants between BD and BMI and point to genes involved in Hedgehog signaling as promising targets.

High blood pressure is common and comorbid with type 2 diabetes (T2D). Almost 50% of patients with T2D have high blood pressure. Patients with both conditions of hypertension (HTN) and T2D are at risk for cardiovascular diseases and mortality. The study aim was to investigate genetic risk factors for HTN in T2D patients. This study included 999 T2D (cohort 1) patients for the first genome scan stage and 922 T2D (cohort 2) patients for the replication stage. Here, we investigated the genetic susceptibility and cumulative weighted genetic risk score for HTN in T2D patients of Han Chinese descent in Taiwan. Thirty novel genetic single nucleotide polymorphisms (SNPs) were associated with HTN in T2D after adjusting for age and body mass index (P value <1 × 10-4). Eight blood pressure-related and/or HTN-related genetic SNPs were associated with HTN in T2D after adjusting for age and body mass index (P value <0.05). Linkage disequilibrium and cumulative weighted genetic risk score analyses showed that 14 of the 38 SNPs were associated with risk of HTN in a dose-dependent manner in T2D (Cochran-Armitage trend test: P value <0.0001). The 14-SNP cumulative weighted genetic risk score was also associated with increased regression tendency of systolic blood pressure in T2D (SBP = 122.05 + 0.8 × weighted genetic risk score; P value = 0.0001). A cumulative weighted genetic risk score composed of 14 SNPs is important for HTN, increased tendency of systolic blood pressure, and may contribute to HTN risk in T2D in Taiwan.

Tumor necrosis factor (TNF ) locus has been a long-standing type 2 diabetes (T2D) candidate gene. Few studies have been conducted on TNF SNP (single nucleotide polymorphism) as rs1799964 (T-1031C), rs1800630 (A-863C) and rs1799724 (C-857T) in T2D. The purpose of this study is to examine the association of TNF SNP and T2D in a case control study and further explore whether these SNPs influence the clinical efficacy of insulin therapy. A total of 109 newly diagnosed type 2 diabetics and 168 healthy individuals were recruited. Three tag SNPs (rs1799964 (T-1031C), rs1800630 (A-863C), rs1799724 (C-857T)) were selected across the TNF locus and polymerase chain reaction (PCR) directed sequencing was performed. The patients received Lispro 25 twice daily to achieve glycemic control and they were followed up for 1 year. Plasma glucose level, lipid profile, homeostatic model assessment for insulin resistance (HOMA-IR) and homeostatic model assessment for beta-cell function (HOMA-β) were compared among groups with different haplotypes of SNPs. Haplotype of TNF-1031C-863C-857C increased the risk of T2D (OR = 2.7, P < 0.05) . Comparing with homozygote of TNF-1031T-863C-857C diabetics (TCC), those carrying CCC allele had higher fasting serum insulin (16.1(12.0-20.3) mU/L) and HOMA-IR (lnHOMA-IR 1.8 ± 0.4) levels (TCC group: 10.6(8.1-14.3) mU/L and 1.42 ± 0.54 respectively, P < 0.05)). One-year insulin treatment decreased HbA1c effectively in both TCC and CCC groups (P < 0.05). However, higher HOMA-IR was still observed in CCC group than that of TCC after normoglycemia (lnHOMA-IR: 2.5(0.9-3.9) vs 1.1(0.8-1.8) respectively, P < 0.05) . Moreover HOMA-β showed no significant improvement in CCC group as it was in TCC group by the endpoint of follow-up. TNF-1031C-863C-857C is a risk haplotype for T2D. CCC carrying patients failed to achieve HOMA-β improvement. And it might be due to increased endogenous HbOMA-IR level comparing with TCC homozygote.

Coeliac disease (CD) is an immune-mediated enteropathy triggered by gluten in genetically predisposed individuals. Patients with CD have an increased prevalence of other autoimmune disorders, including type 1 diabetes (T1D) and Graves' disease (GD). CD shares with these conditions certain HLA susceptibility alleles. A number of studies have also shown association of autoimmune diseases, including CD, with the CD28-cytotoxic T lymphocyte antigen 4 (CTLA4)-inducible costimulator (ICOS) region of chromosome 2q33, but until recently the precise causal variant has remained unknown. Recently, it was shown that, in GD, CT60 (+6230G>A), a single nucleotide polymorphism (SNP) at the end of the CTLA4 transcript, is associated with an alteration in the ratio of splice forms of the CTLA4 gene and that this ratio affects disease susceptibility. A similar but weaker association was found with T1D. There is also an independent association of GD and T1D with the SNP MH30 (-23 327G>C), which possibly affects promoter region function. Hypothesizing that CT60 and MH30 may be causal variants in other autoimmune disorders, we investigated these SNPs in CD using 149 family trios and 100 unrelated/unaffected controls. No association was detected with either SNP using both the transmission disequilibrium test (TDT) and case-control methods. Our study appears to have good power to detect moderate genetic effects, but possibly these SNPs exert too weak an effect on risk of CD to have been detected in our sample. Alternatively, the previously noted association of CD with the CTLA4 gene region may be due to different causal variants. Unlike T1D and GD, CD is not a true autoimmune disease, and CD has different associations at the CTLA4 exon 1 SNP +49G>A from all other autoimmune disorders. MH30, CT60, and other SNPs in the region may still warrant further investigation in other CD samples.

BackgroundWhilst numerous studies have explored the relationship between Alzheimer’s disease (AD) and diabetes, there remains significant conflicting evidence as to their relationship. Some studies suggest an increased likelihood of developing AD in individuals with diabetes, especially type 2 diabetes (T2D) and that both diseases share pathological features. In contrast, other studies indicate that T2D is more aligned with vascular cognitive impairment and dementia and associated cerebrovascular/white matter pathology. Moreover, there is evidence showing no significant genetic correlation between the two disorders. Understanding the genetic relationship between these potentially comorbid conditions could offer insights into AD’s poorly understood biological mechanisms. This study used two complementary methods to evaluate the genetic relationship between AD and T2D. We hypothesise that both disorders are, to an extent, genetically correlated.MethodWe performed an extensive analysis of large‐scale genome‐wide association summary data using the ‘linkage disequilibrium score regression’ analysis (for global correlation) and ‘single nucleotide polymorphism (SNP) effect concordance analysis’ (SECA, for genetic overlap) methods. We performed several analyses testing our findings’ potential (partial) replications, using several GWAS data for AD (with and without the APOE region) and T2D.ResultWe found a highly significant positive genome‐wide (global) genetic correlation between AD (clinically diagnosed with proxy cases) and all T2D GWAS assessed, with or without the APOE region. We largely replicated the positive and significant results using clinically diagnosed AD GWAS. Utilising SECA, we found robust SNP overlap and strong effect concordance with low permutation p‐value and significant Fisher’s exact test—underscoring the strong association between SNP sets (and association in effect direction) for both disorders. Our SECA results were consistently significant irrespective of whether AD or T2D was dataset 1 or dataset 2. We replicated SECA’s results across clinically diagnosed AD and other T2D GWAS data (with or without the APOE region included).ConclusionOur analyses reveal a notable genetic correlation and overlap between AD and T2D, indicating shared genetic factors (shared genetic foundation) and biological pathways influencing the risk or susceptibility to both conditions.

Hypertension (HTN) and Type 2 Diabetes (T2D) often coexist, therefore understanding the relationship between both diseases is imperative to guide targeted prevention/therapy. This study aims to explore the relationship between HTN and T2D using genome-wide association study (GWAS) analysis and biochemical data to understand the implication of both clinical and genetic factors in these pathologies. A total of 2,876 patients were enrolled. Using GWAS and biochemical data, patients with both T2D and HTN were compared to patients with only HTN. Specificity was confirmed by testing the detected genetic variants for associations with HTN development in T2D patients, or with HTN in healthy subjects. Regression models were applied to examine the association of T2D in patients with HTN with cardiovascular risk factors. Replication was performed using UK Biobank dataset with 31,170 subjects. Data showed that females with HTN are at higher risk of developing T2D due to dyslipidemia, while males faced higher risk due to high BMI (body mass index) and family history of T2D. GWAS identified Single Nucleotide Polymorphisms (SNPs) linked to T2D in patients with HTN. Notably, rs7865889, rs7756992, and rs10896290 were positively associated with T2D, whereas rs12737517 yielded negative association. Three SNPs were replicated in the UK Biobank (rs10896290, rs7865889, and rs7756992). Incorporating clinical and genetic screening into risk assessment is important for the detection and prevention of T2D in patients with HTN. The detected SNPs (rs7865889, rs12737517, and rs10896290), especially the protective SNP (rs12737517), provide an opportunity for better diagnosis, prevention, and therapy of patients with T2D and HTN.

Background: Chronic inflammation is implicated in pancreatic cancer carcinogenesis. Advanced glycation end-products (AGEs), which are rich in cooked red meat and cigarette smoke, can perpetuate inflammation by binding to the receptor for advanced glycation end products (AGER, also known as RAGE). We hypothesized that genetic variation of the AGEs/AGER pathway affects pancreatic cancer risk by modulating chronic inflammation. Methods: We conducted a two-stage case-control study to examine the association between 96 single nucleotide polymorphisms (SNPs) in 21 genes (GLO1, MSR1, PINK1, KIF17, AGPAT1, AKR1B1, DDOST, CD36, SCARB1, AGER, APP, HMGB1, S100A8, S100B, S100P, S100A12, MMP9, ADAM10, PPARG, NOTCH4, and PDGF) of the AGEs/AGER pathway and risk of pancreatic cancer. The discovery study was conducted in 672 pancreatic cancer cases and 1361 controls ascertained from the Women’s Health Initiative (WHI) Study matched on age, race/ethnicity and study arm. The validation study was conducted in a PANC4 pooled hospital-based case-control study of 1,034 women cases and 989 women controls. A pooled analysis of 1706 cases and 2350 controls was also performed. SNP data were obtained or imputed from the previously performed GWASs. Pancreatic cancer risk was calculated as odds ratios (ORs) and 95% confidence intervals (Cis) using logistic regression models adjusting for age, race/ethnicity, body mass index (BMI), type 2 diabetes, and smoking using an additive genetic model. The potential interaction between individual SNP and red meat intake and cigarette smoking was examined. A false discovery rate (FDR) adjusted q value &amp;lt; 0.20 was considered statistically significant in the pooled analyses. We also conducted logistic-Kernel machine (LKM) test to examine the association between sets of SNP and risk of pancreatic cancer in the pooled dataset. Results: We identified 11 SNPs with raw P values &amp;lt; 0.10 in the discovery stage in the WHI study. However, none of the SNPs was validated in the validation and pooled dataset. The LKM test showed that sets of SNPs in CD36 (P = 9.3E-10), GLO1(P =2.0E-7), and DDOST (P = 2.5E-4) were significantly associated with pancreatic cancer risk. We found an interaction effect between the GLO1 SNP rs6932648 and smoking status (never versus ever) in the WHI study (P for interaction = 0.01) and the pooled dataset (P for interaction = 0.049). In the pooled dataset, the variant T allele of rs6932648 (MAF = 0.12) was associated with increased risk of pancreatic cancer among ever smokers (additive OR = 1.26, 95% CI: 1.02-1.55), but not among never smokers (additive OR = 0.94, 95% CI: 0.78-1.14), compared with the C allele. Summary and Conclusion: We did not observe significant association between any of 96 single SNP and pancreatic cancer risk. However, we found combined set of SNPs in the GLO1, DDOST, and CD36 genes were associated with risk of pancreatic cancer. GLO SNP rs6932648 may modify the association between smoking and risk of pancreatic cancer. GLO1, DDOST, and CD36 are involved in detoxification or clearance of AGEs compounds. Further investigation of AGEs and receptors systems in pancreatic cancer is warranted. Citation Format: Guochong Jia, Kathryn Royse, Hongwei Tang, Donghui Li, Liang Chen, Lesley Tinker, Gloria Petersen, Alison Klein, Peter Richardson, Donna White, Haleh Sangi-Haghapeykar, Hashem B. El-Serag, Li Jiao. Genetic variations in the AGEs/AGER pathway and risk of pancreatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-160. doi:10.1158/1538-7445.AM2017-LB-160

The association of tumor necrosis factor alpha, lymphotoxin alpha, tumor necrosis factor receptor 1 and tumor necrosis factor receptor 2 gene polymorphisms and serum levels with periodontitis and type 2 diabetes in Serbian population

ObjectiveTo investigate the parent-of-origin effects (POEs) of genes in the phosphatidyl inositol-bisphosphate (PIP2) hydrolysis pathway on type 2 diabetes (T2D) and preliminarily assess whether environmental factors may modify these effects.MethodsBased on data from an ongoing family-based cohort in Beijing, genetic information of 162 individuals from 53 case-parent triads was used to examine the POE of single nucleotide polymorphisms (SNPs) in the PIP2 pathway on T2D using maximum likelihood estimation based on a log-linear model. Stratified analyses were performed to assess the potential modification of POE by environmental factors, including smoking, drinking, and body mass index (BMI). Further enrichment analysis was conducted based on the POE results.ResultsA total of 214 SNPs from the PIP2 hydrolysis pathway had nominally significant (P < 0.05) POE on T2D, among which rs199684931 (RRm/RRp = 0.28, Pinteraction = 0.03), rs4750491 (RRm/RRp = 4.67, Pinteraction = 0.04), rs1090705 (RRm/RRp = 0.21, Pinteraction = 0.04), rs9663645 (RRm/RRp = 4.75, Pinteraction = 0.04), and rs200488869 (RRm/RRp = 4.75, Pinteraction = 0.04) from PRKCQ exhibited POE–BMI interactions. Specifically, maternal POE was reduced for rs199684931 and rs1090705 in individuals with higher BMI levels, while it increased for rs4750491, rs9663645, and rs200488869 in higher BMI groups. Additionally, 72 of the 214 significant POE SNPs were recognized as methylation quantitative trait loci, hinting at a possible role in regulation. The enrichment analysis validated these findings and the role of the genes in lipid metabolism.ConclusionThe current study provides a preliminary hint that SNPs in the PIP2 pathway genes may exhibit POE on T2D, contributing to its heritability. Notably, five SNPs in the PRKCQ gene demonstrated a potential interaction between POE and BMI on T2D. Further research is necessary to explore the underlying molecular mechanisms and to validate these findings in larger and independent populations.