👤 Jalal Taneera

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Amjad Ali, Hema Unnikannan, Jasmin Shafarin +7 more · 2022 · Endocrine · Springer · added 2026-04-24
Metformin (MF) intake associates with reduced levels of circulating low-density lipoprotein-cholesterol (LDL-C). This has been attributed to the activation of AMPK, which differentially regulates the Show more
Metformin (MF) intake associates with reduced levels of circulating low-density lipoprotein-cholesterol (LDL-C). This has been attributed to the activation of AMPK, which differentially regulates the expression of multiple genes involved in cholesterol synthesis and trafficking. However, the exact mechanism underlying the LDL-C lowering effect of MF remains ambiguous. MF-treated Hep-G2 and HuH7 cells were evaluated for cell viability and the expression status of key lipid metabolism-related genes along with LDL-C uptake efficiency. MF treatment resulted in decreased expression and secretion of PCSK9, increased expression of LDLR and enhanced LDL-C uptake in hepatocytes. It also resulted in increased expression of activated AMPK (p-AMPK) and decreased expression of SREBP2 and HNF-1α proteins. Transcriptomic analysis of MF-treated Hep-G2 cells confirmed these findings and showed that other key lipid metabolism-related genes including those that encode apolipoproteins (APOB, APOC2, APOC3 and APOE), MTTP and LIPC are downregulated. Lastly, MF treatment associated with reduced HMG-CoA reductase expression and activity. These findings suggest that MF treatment reduces circulating LDL-C levels by suppressing PCSK9 expression and enhancing LDLR expression; hence the potential therapeutic utility of MF in hypercholesterolemia. Show less
📄 PDF DOI: 10.1007/s12020-022-03022-x
APOC3
Mahmood Y Hachim, Hayat Aljaibeji, Rifat A Hamoudi +6 more · 2020 · Genes · MDPI · added 2026-04-24
The United Arab Emirates National Diabetes and Lifestyle Study (UAEDIAB) has identified obesity, hypertension, obstructive sleep apnea, and dyslipidemia as common phenotypic characteristics correlated Show more
The United Arab Emirates National Diabetes and Lifestyle Study (UAEDIAB) has identified obesity, hypertension, obstructive sleep apnea, and dyslipidemia as common phenotypic characteristics correlated with diabetes mellitus status. As these phenotypes are usually linked with genetic variants, we hypothesized that these phenotypes share single nucleotide polymorphism (SNP)-clusters that can be used to identify causal genes for diabetes. Materials and We explored the National Human Genome Research Institute-European Bioinformatics Institute Catalog of Published Genome-Wide Association Studies (NHGRI-EBI GWAS) to list SNPs with documented association with the UAEDIAB-phenotypes as well as diabetes. The shared chromosomal regions affected by SNPs were identified, intersected, and searched for Enriched Ontology Clustering. The potential SNP-clusters were validated using targeted DNA next-generation sequencing (NGS) in two Emirati diabetic patients. RNA sequencing from human pancreatic islets was used to study the expression of identified genes in diabetic and non-diabetic donors. Eight chromosomal regions containing 46 SNPs were identified in at least four out of the five UAEDIAB-phenotypes. A list of 34 genes was shown to be affected by those SNPs. Targeted NGS from two Emirati patients confirmed that the identified genes have similar SNP-clusters. Show less
📄 PDF DOI: 10.3390/genes11040461
HSD17B12
Jalal Taneera, Sarah Dhaiban, Abdul Khader Mohammed +5 more · 2019 · Gene · Elsevier · added 2026-04-24
Type 2 diabetes (T2D) is a complex polygenic disease with unclear mechanism. In an attempt to identify novel genes involved in β-cell function, we harness a bioinformatics method called Loss-of-functi Show more
Type 2 diabetes (T2D) is a complex polygenic disease with unclear mechanism. In an attempt to identify novel genes involved in β-cell function, we harness a bioinformatics method called Loss-of-function tool (LoFtool) gene score. RNA-sequencing data from human islets were used to cross-reference genes within the 1st quartile of most intolerant LoFtool score with the 100th most expressed genes in human islets. Out of these genes, GNAS and EEF1A1 genes were selected for further investigation in diabetic islets, metabolic tissues along with their correlation with diabetic phenotypes. The influence of GNAS and EEF1A1 on insulin secretion and β-cell function were validated in INS-1 cells. A comparatively higher expression level of GNAS and EEF1A1 was observed in human islets than fat, liver and muscle tissues. Furthermore, diabetic islets displayed a reduced expression of GNAS, but not of EEF1A, compared to non-diabetic islets. The expression of GNAS was positively correlated with insulin secretory index, GLP1R, GIPR and inversely correlated with HbA LoFtool is a powerful tool to identify genes associated with pancreatic islets dysfunction. GNAS is a crucial gene for the β-cell insulin secretory capacity. Show less
no PDF DOI: 10.1016/j.gene.2019.144028
GIPR
Valeriya Lyssenko, Lena Eliasson, Olga Kotova +36 more · 2011 · Diabetes · added 2026-04-24
The incretin hormone GIP (glucose-dependent insulinotropic polypeptide) promotes pancreatic β-cell function by potentiating insulin secretion and β-cell proliferation. Recently, a combined analysis of Show more
The incretin hormone GIP (glucose-dependent insulinotropic polypeptide) promotes pancreatic β-cell function by potentiating insulin secretion and β-cell proliferation. Recently, a combined analysis of several genome-wide association studies (Meta-analysis of Glucose and Insulin-Related Traits Consortium [MAGIC]) showed association to postprandial insulin at the GIP receptor (GIPR) locus. Here we explored mechanisms that could explain the protective effects of GIP on islet function. Associations of GIPR rs10423928 with metabolic and anthropometric phenotypes in both nondiabetic (N = 53,730) and type 2 diabetic individuals (N = 2,731) were explored by combining data from 11 studies. Insulin secretion was measured both in vivo in nondiabetic subjects and in vitro in islets from cadaver donors. Insulin secretion was also measured in response to exogenous GIP. The in vitro measurements included protein and gene expression as well as measurements of β-cell viability and proliferation. The A allele of GIPR rs10423928 was associated with impaired glucose- and GIP-stimulated insulin secretion and a decrease in BMI, lean body mass, and waist circumference. The decrease in BMI almost completely neutralized the effect of impaired insulin secretion on risk of type 2 diabetes. Expression of GIPR mRNA was decreased in human islets from carriers of the A allele or patients with type 2 diabetes. GIP stimulated osteopontin (OPN) mRNA and protein expression. OPN expression was lower in carriers of the A allele. Both GIP and OPN prevented cytokine-induced reduction in cell viability (apoptosis). In addition, OPN stimulated cell proliferation in insulin-secreting cells. These findings support β-cell proliferative and antiapoptotic roles for GIP in addition to its action as an incretin hormone. Identification of a link between GIP and OPN may shed new light on the role of GIP in preservation of functional β-cell mass in humans. Show less
📄 PDF DOI: 10.2337/db10-1532
GIPR
Rona J Strawbridge, Josée Dupuis, Inga Prokopenko +105 more · 2011 · Diabetes · added 2026-04-24
Rona J Strawbridge, Josée Dupuis, Inga Prokopenko, Adam Barker, Emma Ahlqvist, Denis Rybin, John R Petrie, Mary E Travers, Nabila Bouatia-Naji, Antigone S Dimas, Alexandra Nica, Eleanor Wheeler, Han Chen, Benjamin F Voight, Jalal Taneera, Stavroula Kanoni, John F Peden, Fabiola Turrini, Stefan Gustafsson, Carina Zabena, Peter Almgren, David J P Barker, Daniel Barnes, Elaine M Dennison, Johan G Eriksson, Per Eriksson, Elodie Eury, Lasse Folkersen, Caroline S Fox, Timothy M Frayling, Anuj Goel, Harvest F Gu, Momoko Horikoshi, Bo Isomaa, Anne U Jackson, Karen A Jameson, Eero Kajantie, Julie Kerr-Conte, Teemu Kuulasmaa, Johanna Kuusisto, Ruth J F Loos, Jian'an Luan, Konstantinos Makrilakis, Alisa K Manning, María Teresa Martínez-Larrad, Narisu Narisu, Maria Nastase Mannila, John Ohrvik, Clive Osmond, Laura Pascoe, Felicity Payne, Avan A Sayer, Bengt Sennblad, Angela Silveira, Alena Stancáková, Kathy Stirrups, Amy J Swift, Ann-Christine Syvänen, Tiinamaija Tuomi, Ferdinand M van 't Hooft, Mark Walker, Michael N Weedon, Weijia Xie, Björn Zethelius, DIAGRAM Consortium, GIANT Consortium, MuTHER Consortium, CARDIoGRAM Consortium, C4D Consortium, Halit Ongen, Anders Mälarstig, Jemma C Hopewell, Danish Saleheen, John Chambers, Sarah Parish, John Danesh, Jaspal Kooner, Claes-Göran Ostenson, Lars Lind, Cyrus C Cooper, Manuel Serrano-Ríos, Ele Ferrannini, Tom J Forsen, Robert Clarke, Maria Grazia Franzosi, Udo Seedorf, Hugh Watkins, Philippe Froguel, Paul Johnson, Panos Deloukas, Francis S Collins, Markku Laakso, Emmanouil T Dermitzakis, Michael Boehnke, Mark I McCarthy, Nicholas J Wareham, Leif Groop, François Pattou, Anna L Gloyn, George V Dedoussis, Valeriya Lyssenko, James B Meigs, Inês Barroso, Richard M Watanabe, Erik Ingelsson, Claudia Langenberg, Anders Hamsten, Jose C Florez Show less
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diab Show more
Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis. Show less
no PDF DOI: 10.2337/db11-0415
VPS13C
Richa Saxena, Marie-France Hivert, Claudia Langenberg +153 more · 2010 · Nature genetics · Nature · added 2026-04-24
Richa Saxena, Marie-France Hivert, Claudia Langenberg, Toshiko Tanaka, James S Pankow, Peter Vollenweider, Valeriya Lyssenko, Nabila Bouatia-Naji, Josée Dupuis, Anne U Jackson, W H Linda Kao, Man Li, Nicole L Glazer, Alisa K Manning, Jian'an Luan, Heather M Stringham, Inga Prokopenko, Toby Johnson, Niels Grarup, Trine W Boesgaard, Cécile Lecoeur, Peter Shrader, Jeffrey O'Connell, Erik Ingelsson, David J Couper, Kenneth Rice, Kijoung Song, Camilla H Andreasen, Christian Dina, Anna Köttgen, Olivier Le Bacquer, François Pattou, Jalal Taneera, Valgerdur Steinthorsdottir, Denis Rybin, Kristin Ardlie, Michael Sampson, Lu Qi, Mandy van Hoek, Michael N Weedon, Yurii S Aulchenko, Benjamin F Voight, Harald Grallert, Beverley Balkau, Richard N Bergman, Suzette J Bielinski, Amelie Bonnefond, Lori L Bonnycastle, Knut Borch-Johnsen, Yvonne Böttcher, Eric Brunner, Thomas A Buchanan, Suzannah J Bumpstead, Christine Cavalcanti-Proença, Guillaume Charpentier, Yii-der Ida Chen, Peter S Chines, Francis S Collins, Marilyn Cornelis, Gabriel J Crawford, Jerome Delplanque, Alex Doney, Josephine M Egan, Michael R Erdos, Mathieu Firmann, Nita G Forouhi, Caroline S Fox, Mark O Goodarzi, Jürgen Graessler, Aroon Hingorani, Bo Isomaa, Torben Jørgensen, Mika Kivimaki, Peter Kovacs, Knut Krohn, Meena Kumari, Torsten Lauritzen, Claire Lévy-Marchal, Vladimir Mayor, Jarred B McAteer, David Meyre, Braxton D Mitchell, Karen L Mohlke, Mario A Morken, Narisu Narisu, Colin N A Palmer, Ruth Pakyz, Laura Pascoe, Felicity Payne, Daniel Pearson, Wolfgang Rathmann, Annelli Sandbaek, Avan Aihie Sayer, Laura J Scott, Stephen J Sharp, Eric Sijbrands, Andrew Singleton, David S Siscovick, Nicholas L Smith, Thomas Sparsø, Amy J Swift, Holly Syddall, Gudmar Thorleifsson, Anke Tönjes, Tiinamaija Tuomi, Jaakko Tuomilehto, Timo T Valle, Gérard Waeber, Andrew Walley, Dawn M Waterworth, Eleftheria Zeggini, Jing Hua Zhao, GIANT Consortium, MAGIC Investigators, Thomas Illig, H Erich Wichmann, James F Wilson, Cornelia van Duijn, Frank B Hu, Andrew D Morris, Timothy M Frayling, Andrew T Hattersley, Unnur Thorsteinsdottir, Kari Stefansson, Peter Nilsson, Ann-Christine Syvänen, Alan R Shuldiner, Mark Walker, Stefan R Bornstein, Peter Schwarz, Gordon H Williams, David M Nathan, Johanna Kuusisto, Markku Laakso, Cyrus Cooper, Michael Marmot, Luigi Ferrucci, Vincent Mooser, Michael Stumvoll, Ruth J F Loos, David Altshuler, Bruce M Psaty, Jerome I Rotter, Eric Boerwinkle, Torben Hansen, Oluf Pedersen, Jose C Florez, Mark I McCarthy, Michael Boehnke, Inês Barroso, Robert Sladek, Philippe Froguel, James B Meigs, Leif Groop, Nicholas J Wareham, Richard M Watanabe Show less
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studi Show more
Glucose levels 2 h after an oral glucose challenge are a clinical measure of glucose tolerance used in the diagnosis of type 2 diabetes. We report a meta-analysis of nine genome-wide association studies (n = 15,234 nondiabetic individuals) and a follow-up of 29 independent loci (n = 6,958-30,620). We identify variants at the GIPR locus associated with 2-h glucose level (rs10423928, beta (s.e.m.) = 0.09 (0.01) mmol/l per A allele, P = 2.0 x 10(-15)). The GIPR A-allele carriers also showed decreased insulin secretion (n = 22,492; insulinogenic index, P = 1.0 x 10(-17); ratio of insulin to glucose area under the curve, P = 1.3 x 10(-16)) and diminished incretin effect (n = 804; P = 4.3 x 10(-4)). We also identified variants at ADCY5 (rs2877716, P = 4.2 x 10(-16)), VPS13C (rs17271305, P = 4.1 x 10(-8)), GCKR (rs1260326, P = 7.1 x 10(-11)) and TCF7L2 (rs7903146, P = 4.2 x 10(-10)) associated with 2-h glucose. Of the three newly implicated loci (GIPR, ADCY5 and VPS13C), only ADCY5 was found to be associated with type 2 diabetes in collaborating studies (n = 35,869 cases, 89,798 controls, OR = 1.12, 95% CI 1.09-1.15, P = 4.8 x 10(-18)). Show less
📄 PDF DOI: 10.1038/ng.521
GIPR