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Endocrine, Metabolic & Immune Disorders - Drug Targets

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ISSN (Print): 1871-5303
ISSN (Online): 2212-3873

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Research Article

Potential Association of The Pathogenic Kruppel-like Factor 14 (KLF14) and Adiponectin (ADIPOQ) SNVs with Susceptibility to T2DM

Author(s): Imadeldin Elfaki*, Rashid Mir, Faris Tayeb, Adel I. Alalawy, Jameel Barnawi, Pradeep Kumar Dabla and Mamdoh Shafig Moawadh

Volume 24, Issue 9, 2024

Published on: 28 November, 2023

Page: [1090 - 1100] Pages: 11

DOI: 10.2174/0118715303258744231117064253

Price: $65

Abstract

Aim: To evaluate the associations of the pathogenic variants in Kruppel-like Factor 14 (KLF 14) and Adiponectin (ADIPOQ) with susceptibility to type 2 diabetes mellitus (T2DM).

Background: Type 2 diabetes mellitus (T2DM) is a pandemic metabolic disease characterized by increased blood sugar and caused by resistance to insulin in peripheral tissues and damage to pancreatic beta cells. Kruppel-like Factor 14 (KLF-14) is proposed to be a regulator of metabolic diseases, such as diabetes mellitus (DM) and obesity. Adiponectin (ADIPOQ) is an adipocytokine produced by the adipocytes and other tissues and was reported to be involved in T2DM.

Objectives: To study the possible association of the KLF-14 rs972283 and ADIPOQ-rs266729 with the risk of T2DM in the Saudi population.

Methods: We have evaluated the association of KLF-14 rs972283 C>T and ADIPOQ-rs266729 C>G SNV with the risk to T2D in the Saudi population using the Amplification Refractory Mutation System PCR (ARMS-PCR), and blood biochemistry analysis. For the KLF-14 rs972283 C>T SNV we included 115 cases and 116 healthy controls, and ADIPOQ-rs266729 C>G SNV, 103 cases and 104 healthy controls were included.

Results: Results indicated that the KLF-14 rs972283 GA genotype and A allele were associated with T2D risk with OR=2.14, p-value= 0.014 and OR=1.99, p-value=0.0003, respectively. Results also ADIPOQ-rs266729 CG genotype and C allele were associated with an elevated T2D risk with an OR=2.53, p=0.003 and OR=1.66, p-value =0.012, respectively.

Conclusion: We conclude that SNVs in KLF-14 and ADIPOQ are potential loci for T2D risk. Future large-scale studies to verify these findings are recommended. These results need further verifications in protein functional and large-scale case control studies before being introduced for genetic testing.

« Previous Next »
[1]
Hossain, M.B.; Khan, M.N.; Oldroyd, J.C.; Rana, J.; Magliago, D.J.; Chowdhury, E.K.; Karim, M.N.; Islam, R.M. Prevalence of, and risk factors for, diabetes and prediabetes in Bangladesh: Evidence from the national survey using a multilevel Poisson regression model with a robust variance. PLOS Global Public Health, 2022, 2(6), e0000461.
[http://dx.doi.org/10.1371/journal.pgph.0000461] [PMID: 36962350]
[2]
Nellaiappan, K.; Preeti, K.; Khatri, D.K.; Singh, S.B. Diabetic complications: An update on pathobiology and therapeutic strategies. Curr. Diabetes Rev., 2022, 18(1), e030821192146.
[http://dx.doi.org/10.2174/1573399817666210309104203] [PMID: 33745424]
[3]
Ahsan, K.Z.; Iqbal, A.; Jamil, K.; Haider, M.M.; Khan, S.H.; Chakraborty, N.; Streatfield, P.K. Socioeconomic disparities in diabetes prevalence and management among the adult population in Bangladesh. PLoS One, 2022, 17(12), e0279228.
[http://dx.doi.org/10.1371/journal.pone.0279228] [PMID: 36538534]
[4]
Reed, J.; Bain, S.; Kanamarlapudi, V. A review of current trends with type 2 diabetes epidemiology, aetiology, pathogenesis, treatments and future perspectives. Diabetes Metab. Syndr. Obes., 2021, 14, 3567-3602.
[http://dx.doi.org/10.2147/DMSO.S319895] [PMID: 34413662]
[5]
Li, M.; Chi, X.; Wang, Y.; Setrerrahmane, S.; Xie, W.; Xu, H. Trends in insulin resistance: Insights into mechanisms and therapeutic strategy. Signal Transduct. Target. Ther., 2022, 7(1), 216.
[http://dx.doi.org/10.1038/s41392-022-01073-0] [PMID: 35794109]
[6]
Lv, C.; Sun, Y.; Zhang, Z.Y.; Aboelela, Z.; Qiu, X.; Meng, Z.X. β- cell dynamics in type 2 diabetes and in dietary and exercise interventions. J. Mol. Cell Biol., 2022, 14(7), mjac046.
[http://dx.doi.org/10.1093/jmcb/mjac046] [PMID: 35929791]
[7]
Kyrou, I.; Tsigos, C.; Mavrogianni, C.; Cardon, G.; Van Stappen, V.; Latomme, J.; Kivelä, J.; Wikström, K.; Tsochev, K.; Nanasi, A.; Semanova, C.; Mateo-Gallego, R.; Lamiquiz-Moneo, I.; Dafoulas, G.; Timpel, P.; Schwarz, P.E.H.; Iotova, V.; Tankova, T.; Makrilakis, K.; Manios, Y. Sociodemographic and lifestyle-related risk factors for identifying vulnerable groups for type 2 diabetes: a narrative review with emphasis on data from Europe. BMC Endocr. Disord., 2020, 20(S1)(Suppl. 1), 134.
[http://dx.doi.org/10.1186/s12902-019-0463-3] [PMID: 32164656]
[8]
Elfaki, I.; Mir, R.; Mir, M.M.; AbuDuhier, F.M.; Babakr, A.T.; Barnawi, J. Potential Impact of MicroRNA gene polymorphisms in the pathogenesis of diabetes and atherosclerotic cardiovascular disease. J. Pers. Med., 2019, 9(4), 51.
[http://dx.doi.org/10.3390/jpm9040051] [PMID: 31775219]
[9]
Elfaki, I. Phosphatidylinositol 3-kinase Glu545Lys and His1047Tyr Mutations are not Associated with T2D. Curr. Diabetes Rev., 2020, 16(8), 881-888.
[PMID: 31749428]
[10]
Mir, R. Molecular evaluation of microRNA-146 gene variability (rs2910164 C> G) and its association with increased susceptibility to coronary artery disease. MicroRNA, 2020, 9, 363-372.
[11]
Elfaki, I.; Mir, R.; Almutairi, F.M.; Duhier, F.M.A. Cytochrome P450: Polymorphisms and roles in cancer, diabetes and atherosclerosis. Asian Pac. J. Cancer Prev., 2018, 19(8), 2057-2070.
[PMID: 30139042]
[12]
Elfaki, I. Clinical implications of MiR128, angiotensin i converting enzyme and vascular endothelial growth factor gene abnormalities and their association with T2D. Curr. Issues Mol. Biol., 2021, 43, 1859-1875.
[http://dx.doi.org/10.3390/cimb43030130]
[13]
Elfaki, I.; Mir, R.; Abu-Duhier, F.M.; Jha, C.K. Ahmad, Al-Alawy, A.I.; Babakr, A.T.; Habib, S.A.E.H. Analysis of the potential association of drug-metabolizing enzymes CYP2C9*3 and CYP2C19*3 gene variations with type 2 diabetes: A case-control study. Curr. Drug Metab., 2020, 21(14), 1152-1160.
[http://dx.doi.org/10.2174/1389200221999201027200931] [PMID: 33115391]
[14]
Jha, C.K.; Mir, R.; Elfaki, I.; Javid, J.; Babakr, A.T.; Banu, S.; Chahal, S.M.S. Evaluation of the association of omentin 1 rs2274907 A>T and rs2274908 G>A gene polymorphisms with coronary artery disease in indian population: A case control study. J. Pers. Med., 2019, 9(2), 30.
[http://dx.doi.org/10.3390/jpm9020030] [PMID: 31174318]
[15]
Andrews, S.J.; Fulton-Howard, B.; Goate, A. Interpretation of risk loci from genome-wide association studies of Alzheimer’s disease. Lancet Neurol., 2020, 19(4), 326-335.
[http://dx.doi.org/10.1016/S1474-4422(19)30435-1] [PMID: 31986256]
[16]
Cano-Gamez, E.; Trynka, G. From GWAS to Function: Using functional genomics to identify the mechanisms underlying complex diseases. Front. Genet., 2020, 11, 424.
[http://dx.doi.org/10.3389/fgene.2020.00424] [PMID: 32477401]
[17]
Mir, R.; Elfaki, I.; Javid, J.; Barnawi, J.; Altayar, M.A.; Albalawi, S.O.; Jalal, M.M.; Tayeb, F.J.; Yousif, A.; Ullah, M.F.; AbuDuhier, F.M. Genetic determinants of cardiovascular disease: The endothelial nitric oxide synthase 3 (eNOS3), Krüppel-Like Factor-14 (KLF-14), methylenetetrahydrofolate reductase (MTHFR), MiRNAs27a and their association with the predisposition and susceptibility to coronary artery disease. Life, 2022, 12(11), 1905.
[http://dx.doi.org/10.3390/life12111905] [PMID: 36431040]
[18]
Tcheandjieu, C.; Zhu, X.; Hilliard, A.T.; Clarke, S.L.; Napolioni, V.; Ma, S.; Lee, K.M.; Fang, H.; Chen, F.; Lu, Y.; Tsao, N.L.; Raghavan, S.; Koyama, S.; Gorman, B.R.; Vujkovic, M.; Klarin, D.; Levin, M.G.; Sinnott-Armstrong, N.; Wojcik, G.L.; Plomondon, M.E.; Maddox, T.M.; Waldo, S.W.; Bick, A.G.; Pyarajan, S.; Huang, J.; Song, R.; Ho, Y.L.; Buyske, S.; Kooperberg, C.; Haessler, J.; Loos, R.J.F.; Do, R.; Verbanck, M.; Chaudhary, K.; North, K.E.; Avery, C.L.; Graff, M.; Haiman, C.A.; Le Marchand, L.; Wilkens, L.R.; Bis, J.C.; Leonard, H.; Shen, B.; Lange, L.A.; Giri, A.; Dikilitas, O.; Kullo, I.J.; Stanaway, I.B.; Jarvik, G.P.; Gordon, A.S.; Hebbring, S.; Namjou, B.; Kaufman, K.M.; Ito, K.; Ishigaki, K.; Kamatani, Y.; Verma, S.S.; Ritchie, M.D.; Kember, R.L.; Baras, A.; Lotta, L.A.; Kathiresan, S.; Hauser, E.R.; Miller, D.R.; Lee, J.S.; Saleheen, D.; Reaven, P.D.; Cho, K.; Gaziano, J.M.; Natarajan, P.; Huffman, J.E.; Voight, B.F.; Rader, D.J.; Chang, K.M.; Lynch, J.A.; Damrauer, S.M.; Wilson, P.W.F.; Tang, H.; Sun, Y.V.; Tsao, P.S.; O’Donnell, C.J.; Assimes, T.L. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat. Med., 2022, 28(8), 1679-1692.
[http://dx.doi.org/10.1038/s41591-022-01891-3] [PMID: 35915156]
[19]
Mir, R.; Elfaki, I.; Elangeeb, M.E.; Moawadh, M.S.; Tayeb, F.J.; Barnawi, J.; Albalawi, I.A.; Alharbi, A.A.; Alhelali, M.H.; Alsaedi, B.S.O. Comprehensive molecular evaluation of HNF-1 Alpha, miR-27a, and miR-146 gene variants and their link with predisposition and progression in type 2 diabetes patients. J. Pers. Med., 2023, 13(8), 1270.
[http://dx.doi.org/10.3390/jpm13081270] [PMID: 37623520]
[20]
Yang, Q.; Civelek, M. Transcription factor KLF14 and metabolic syndrome. Front. Cardiovasc. Med., 2020, 7, 91.
[http://dx.doi.org/10.3389/fcvm.2020.00091] [PMID: 32548128]
[21]
Pollak, N.M.; Hoffman, M.; Goldberg, I.J.; Drosatos, K. Krüppel-like factors. JACC Basic Transl. Sci., 2018, 3(1), 132-156.
[http://dx.doi.org/10.1016/j.jacbts.2017.09.001] [PMID: 29876529]
[22]
Achari, A.; Jain, S. Adiponectin, a therapeutic target for obesity, diabetes, and endothelial dysfunction. Int. J. Mol. Sci., 2017, 18(6), 1321.
[http://dx.doi.org/10.3390/ijms18061321] [PMID: 28635626]
[23]
Yanai, H.; Yoshida, H. Beneficial effects of adiponectin on glucose and lipid metabolism and atherosclerotic progression: Mechanisms and perspectives. Int. J. Mol. Sci., 2019, 20(5), 1190.
[http://dx.doi.org/10.3390/ijms20051190] [PMID: 30857216]
[24]
Gamberi, T.; Magherini, F.; Modesti, A.; Fiaschi, T. Adiponectin signaling pathways in liver diseases. Biomedicines, 2018, 6(2), 52.
[http://dx.doi.org/10.3390/biomedicines6020052] [PMID: 29735928]
[25]
Laakso, M. Biomarkers for type 2 diabetes. Mol. Metab., 2019, 27(Suppl.), S139-S146.
[http://dx.doi.org/10.1016/j.molmet.2019.06.016] [PMID: 31500825]
[26]
Christodoulou, M.I.; Avgeris, M.; Kokkinopoulou, I.; Maratou, E.; Mitrou, P.; Kontos, C.K.; Pappas, E.; Boutati, E.; Scorilas, A.; Fragoulis, E.G. Blood-based analysis of type-2 diabetes mellitus susceptibility genes identifies specific transcript variants with deregulated expression and association with disease risk. Sci. Rep., 2019, 9(1), 1512.
[http://dx.doi.org/10.1038/s41598-018-37856-1] [PMID: 30728419]
[27]
Wong, M.K.S. Angiotensin Converting Enzymes; Handbook of Hormones, 2016, pp. 236-294.
[http://dx.doi.org/10.1016/B978-0-12-801028-0.00254-3]
[28]
WHO. HEARTS D: Diagnosis and management of type 2 diabetes; World Health Organization, 2020.
[29]
Medrano, R.F.V.; de Oliveira, C.A. Guidelines for the tetra-primer ARMS-PCR technique development. Mol. Biotechnol., 2014, 56(7), 599-608.
[http://dx.doi.org/10.1007/s12033-014-9734-4] [PMID: 24519268]
[30]
Ahlawat, S.; Sharma, R.; Maitra, A.; Roy, M.; Tantia, M.S. Designing, optimization and validation of tetra-primer ARMS PCR protocol for genotyping mutations in caprine Fec genes. Meta Gene, 2014, 2, 439-449.
[http://dx.doi.org/10.1016/j.mgene.2014.05.004] [PMID: 25606428]
[31]
Zabala, A.S.; Gomez, M.E.V.; Alvarez, M.F.; Siewert, S. Tetra primer ARMS PCR optimization to detect single nucleotide polymorphism of the KLF14 gene. OAlib, 2017, 4(12), 1-14.
[http://dx.doi.org/10.4236/oalib.1104145]
[32]
Alzahrani, O.R.; Mir, R.; Alatwi, H.E.; Hawsawi, Y.M.; Alharbi, A.A.; Alessa, A.H.; Albalawi, E.S.; Elfaki, I.; Alalawi, Y.; Moharam, L.; El-Ghaiesh, S.H. Potential Impact of PI3K-AKT signaling pathway genes, KLF-14, MDM4, miRNAs 27a, miRNA-196a genetic alterations in the predisposition and progression of breast cancer patients. Cancers, 2023, 15(4), 1281.
[http://dx.doi.org/10.3390/cancers15041281] [PMID: 36831624]
[33]
Divella, R.; Daniele, A.; Mazzocca, A.; Abbate, I.; Casamassima, P.; Caliandro, C.; Ruggeri, E.; Naglieri, E.; Sabbà, C.; De Luca, R. ADIPOQ rs266729 G/C gene polymorphism and plasmatic adipocytokines connect metabolic syndrome to colorectal cancer. J. Cancer, 2017, 8(6), 1000-1008.
[http://dx.doi.org/10.7150/jca.17515] [PMID: 28529612]
[34]
Andersson, E.; Persson, S.; Hallén, N.; Ericsson, Å.; Thielke, D.; Lindgren, P.; Steen, C. K.; Jendle, J. Costs of diabetes complications: Hospital-based care and absence from work for 392,200 people with type 2 diabetes and matched control participants in Sweden. Diabetologia, 2020, 63(12), 2582-2594.
[http://dx.doi.org/10.1007/s00125-020-05277-3] [PMID: 32968866]
[35]
Aljulifi, M.Z. Prevalence and reasons of increased type 2 diabetes in gulf cooperation council countries. Saudi Med. J., 2021, 42(5), 481-490.
[http://dx.doi.org/10.15537/smj.2021.42.5.20200676] [PMID: 33896777]
[36]
Khan, M.A.B.; Hashim, M.J.; King, J.K.; Govender, R.D.; Mustafa, H.; Al Kaabi, J. Epidemiology of Type 2 diabetes – global burden of disease and forecasted trends. J. Epidemiol. Glob. Health, 2019, 10(1), 107-111.
[http://dx.doi.org/10.2991/jegh.k.191028.001] [PMID: 32175717]
[37]
Song, C.; Gong, W.; Ding, C.; Wang, R.; Fang, H.; Liu, A. Gene–Environment Interaction on Type 2 diabetes risk among chinese adults born in early 1960s. Genes, 2022, 13(4), 645.
[http://dx.doi.org/10.3390/genes13040645] [PMID: 35456451]
[38]
Sarmento, O.F.; Svingen, P.A. Xiong, Y; Xavier, R.J: McGovern, D: Smyrk, T.C: Papadakis, K.A: Urrutia, R.A.; Faubion, W.A. A novel role for KLF14 in T regulatory cell differentiation. Cell. Mol. Gastroenterol. Hepatol., 2015, 1(2), 188-202.e4.
[http://dx.doi.org/10.1016/j.jcmgh.2014.12.007] [PMID: 25750932]
[39]
Voight, B.F.; Scott, L.J.; Steinthorsdottir, V.; Morris, A.P.; Dina, C.; Welch, R.P.; Zeggini, E.; Huth, C.; Aulchenko, Y.S.; Thorleifsson, G.; McCulloch, L.J.; Ferreira, T.; Grallert, H.; Amin, N.; Wu, G.; Willer, C.J.; Raychaudhuri, S.; McCarroll, S.A.; Langenberg, C.; Hofmann, O.M.; Dupuis, J.; Qi, L.; Segrè, A.V.; van Hoek, M.; Navarro, P.; Ardlie, K.; Balkau, B.; Benediktsson, R.; Bennett, A.J.; Blagieva, R.; Boerwinkle, E.; Bonnycastle, L.L.; Boström, K.B.; Bravenboer, B.; Bumpstead, S.; Burtt, N.P.; Charpentier, G.; Chines, P.S.; Cornelis, M.; Couper, D.J.; Crawford, G.; Doney, A.S.F.; Elliott, K.S.; Elliott, A.L.; Erdos, M.R.; Fox, C.S.; Franklin, C.S.; Ganser, M.; Gieger, C.; Grarup, N.; Green, T.; Griffin, S.; Groves, C.J.; Guiducci, C.; Hadjadj, S.; Hassanali, N.; Herder, C.; Isomaa, B.; Jackson, A.U.; Johnson, P.R.V.; Jørgensen, T.; Kao, W.H.L.; Klopp, N.; Kong, A.; Kraft, P.; Kuusisto, J.; Lauritzen, T.; Li, M.; Lieverse, A.; Lindgren, C.M.; Lyssenko, V.; Marre, M.; Meitinger, T.; Midthjell, K.; Morken, M.A.; Narisu, N.; Nilsson, P.; Owen, K.R.; Payne, F.; Perry, J.R.B.; Petersen, A.K.; Platou, C.; Proença, C.; Prokopenko, I.; Rathmann, W.; Rayner, N.W.; Robertson, N.R.; Rocheleau, G.; Roden, M.; Sampson, M.J.; Saxena, R.; Shields, B.M.; Shrader, P.; Sigurdsson, G.; Sparsø, T.; Strassburger, K.; Stringham, H.M.; Sun, Q.; Swift, A.J.; Thorand, B.; Tichet, J.; Tuomi, T.; van Dam, R.M.; van Haeften, T.W.; van Herpt, T.; van Vliet-Ostaptchouk, J.V.; Walters, G.B.; Weedon, M.N.; Wijmenga, C.; Witteman, J.; Bergman, R.N.; Cauchi, S.; Collins, F.S.; Gloyn, A.L.; Gyllensten, U.; Hansen, T.; Hide, W.A.; Hitman, G.A.; Hofman, A.; Hunter, D.J.; Hveem, K.; Laakso, M.; Mohlke, K.L.; Morris, A.D.; Palmer, C.N.A.; Pramstaller, P.P.; Rudan, I.; Sijbrands, E.; Stein, L.D.; Tuomilehto, J.; Uitterlinden, A.; Walker, M.; Wareham, N.J.; Watanabe, R.M.; Abecasis, G.R.; Boehm, B.O.; Campbell, H.; Daly, M.J.; Hattersley, A.T.; Hu, F.B.; Meigs, J.B.; Pankow, J.S.; Pedersen, O.; Wichmann, H.E.; Barroso, I.; Florez, J.C.; Frayling, T.M.; Groop, L.; Sladek, R.; Thorsteinsdottir, U.; Wilson, J.F.; Illig, T.; Froguel, P.; van Duijn, C.M.; Stefansson, K.; Altshuler, D.; Boehnke, M.; McCarthy, M.I. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet., 2010, 42(7), 579-589.
[http://dx.doi.org/10.1038/ng.609] [PMID: 20581827]
[40]
Small, K.S.; Todorčević, M.; Civelek, M.; El-Sayed Moustafa, J.S.; Wang, X.; Simon, M.M.; Fernandez-Tajes, J.; Mahajan, A.; Horikoshi, M.; Hugill, A.; Glastonbury, C.A.; Quaye, L.; Neville, M.J.; Sethi, S.; Yon, M.; Pan, C.; Che, N.; Viñuela, A.; Tsai, P.C.; Nag, A.; Buil, A.; Thorleifsson, G.; Raghavan, A.; Ding, Q.; Morris, A.P.; Bell, J.T.; Thorsteinsdottir, U.; Stefansson, K.; Laakso, M.; Dahlman, I.; Arner, P.; Gloyn, A.L.; Musunuru, K.; Lusis, A.J.; Cox, R.D.; Karpe, F.; McCarthy, M.I. Regulatory variants at KLF14 influence type 2 diabetes risk via a female-specific effect on adipocyte size and body composition. Nat. Genet., 2018, 50(4), 572-580.
[http://dx.doi.org/10.1038/s41588-018-0088-x] [PMID: 29632379]
[41]
Wang, L.; Tong, X.; Gu, F.; Zhang, L.; Chen, W.; Cheng, X.; Xie, L.; Chang, Y.; Zhang, H. The KLF14 transcription factor regulates hepatic gluconeogenesis in mice. J. Biol. Chem., 2017, 292(52), 21631-21642.
[http://dx.doi.org/10.1074/jbc.RA117.000184] [PMID: 29123026]
[42]
Mir, R.; Saeedi, N.H.; Jalal, M.M.; Altayar, M.A.; Barnawi, J.; Hamadi, A.; Tayeb, F.J.; Alshammari, S.E.; Mtiraoui, N.M.; Ali, M.E.; Abuduhier, F.M.; Ullah, M.F. Clinical implications of krüpple-like transcription factor KLF-14 and certain micro-RNA (miR-27a, miR-196a2, miR-423) gene variations as a risk factor in the genetic predisposition to PCOS. J. Pers. Med., 2022, 12(4), 586.
[http://dx.doi.org/10.3390/jpm12040586] [PMID: 35455702]
[43]
Sangaraju, S.L.; Yepez, D.; Grandes, X.A.; Talanki Manjunatha, R.; Habib, S. Cardio-metabolic disease and polycystic ovarian syndrome (PCOS): A narrative review. Cureus, 2022, 14(5), e25076.
[http://dx.doi.org/10.7759/cureus.25076] [PMID: 35719759]
[44]
Nilsson, P.M.; Tuomilehto, J.; Rydén, L. The metabolic syndrome – What is it and how should it be managed? Eur. J. Prev. Cardiol., 2019, 26(2), 33-46.
[http://dx.doi.org/10.1177/2047487319886404] [PMID: 31766917]
[45]
Wang, J.; Zhang, J.; Shen, J.; Hu, D.; Yan, G.; Liu, X.; Xu, X.; Pei, L.; Li, Y.; Sun, C. Association of KCNQ1 and KLF14 polymorphisms and risk of type 2 diabetes mellitus: A global meta-analysis. Hum. Immunol., 2014, 75(4), 342-347.
[http://dx.doi.org/10.1016/j.humimm.2014.01.008] [PMID: 24486580]
[46]
Gao, K.; Wang, J.; Li, L.; Zhai, Y.; Ren, Y.; You, H.; Wang, B.; Wu, X.; Li, J.; Liu, Z.; Li, X.; Huang, Y.; Luo, X.P.; Hu, D.; Ohno, K.; Wang, C. Polymorphisms in four genes (KCNQ1 rs151290, KLF14 rs972283, GCKR rs780094 and MTNR1B rs10830963) and their correlation with type 2 diabetes mellitus in han chinese in henan province, china. Int. J. Environ. Res. Public Health, 2016, 13(3), 260.
[http://dx.doi.org/10.3390/ijerph13030260] [PMID: 26927145]
[47]
Siitonen, N.; Pulkkinen, L.; Lindström, J.; Kolehmainen, M.; Eriksson, J.G.; Venojärvi, M.; Ilanne-Parikka, P.; Keinänen-Kiukaanniemi, S.; Tuomilehto, J.; Uusitupa, M. Association of ADIPOQ gene variants with body weight, type 2 diabetes and serum adiponectin concentrations: The Finnish Diabetes Prevention Study. BMC Med. Genet., 2011, 12(1), 5.
[http://dx.doi.org/10.1186/1471-2350-12-5] [PMID: 21219602]
[48]
Schwarz, P.; Govindarajalu, S.; Towers, W.; Schwanebeck, U.; Fischer, S.; Vasseur, F.; Bornstein, S.; Schulze, J. Haplotypes in the promoter region of the ADIPOQ gene are associated with increased diabetes risk in a German Caucasian population. Horm. Metab. Res., 2006, 38(7), 447-451.
[http://dx.doi.org/10.1055/s-2006-947842] [PMID: 16933180]
[49]
Sun, P.; Liu, L.; Chen, J.; Chen, Y.; Shi, L.; Imam, M.U.; Chen, Y.; Pei, X.; Xu, Y.; Guo, Y.; Ping, Z.; Fu, X. The polymorphism of rs266729 in adiponectin gene and type 2 diabetes mellitus. Medicine, 2017, 96(47), e8745.
[http://dx.doi.org/10.1097/MD.0000000000008745] [PMID: 29381968]
[50]
de Luis, D.A.; Izaola, O.; Primo, D.; Aller, R. Relation of a variant in adiponectin gene (rs266729) with metabolic syndrome and diabetes mellitus type 2 in adult obese subjects. Eur. Rev. Med. Pharmacol. Sci., 2020, 24(20), 10646-10652.
[PMID: 33155222]
[51]
Zhu, M.; Lv, Y.; Peng, Y.; Wu, Y.; Feng, Y.; Jia, T.; Xu, S.; Li, S.; Wang, W.; Tian, J.; Sun, L. GCKR and ADIPOQ gene polymorphisms in women with gestational diabetes mellitus. Acta Diabetol., 2023, 60(12), 1709-1718.
[http://dx.doi.org/10.1007/s00592-023-02165-1] [PMID: 37524927]
[52]
Wang, Y.; Li, L.; Li, P. Novel single nucleotide polymorphisms in gestational diabetes mellitus. Clin. Chim. Acta, 2023, 538, 60-64.
[http://dx.doi.org/10.1016/j.cca.2022.11.010] [PMID: 36375523]
[53]
Dinh Le, T.; Minh Bui, T.; Hien Vu, T.; Phi Thi Nguyen, N.; Thanh Thi Tran, H.; Nguyen, S.T.; Ho Thi Nguyen, L.; Van Ngo, M.; Huy Duong, H.; Thanh Vu, B.; Dinh, H.T.; Nhu Do, B.; Le, D.C.; Thi Nguyen, H.; Trung Nguyen, K. Insulin resistance in gestational diabetes mellitus and its association with anthropometric fetal indices. Clin. Med. Insights Endocrinol. Diabetes, 2022, 15, 11795514221098403.
[http://dx.doi.org/10.1177/11795514221098403] [PMID: 35601878]
[54]
Hsiao, T.J.; Lin, E. A validation study of adiponectin rs266729 gene variant with type 2 diabetes, obesity, and metabolic phenotypes in a taiwanese population. Biochem. Genet., 2016, 54(6), 830-841.
[http://dx.doi.org/10.1007/s10528-016-9760-y] [PMID: 27388775]
[55]
Mosad, A.S.; Elfadil, G.A.; Gassoum, A.; Elamin, K.M.; Husain, N.E.O.S.A. Adiponectin gene polymorphisms and possible susceptibility to metabolic syndrome among the sudanese population: A case-control study. Int. J. Endocrinol., 2023, 2023, 1-11.
[http://dx.doi.org/10.1155/2023/5527963] [PMID: 37151957]
[56]
Hamidi, Y.; Saki, S.; Afraz, E.S.; Pashapour, S. A Meta-analysis of ADIPOQ rs2241766 polymorphism association with type 2 diabetes. J. Diabetes Metab. Disord., 2022, 21(2), 1895-1901.
[http://dx.doi.org/10.1007/s40200-022-01086-0] [PMID: 36404807]
[57]
Elfaki, I.; Bayer, P.; Mueller, J.W. A potential transcriptional regulator is out-of-frame translated from the metallothionein 2A messenger RNA. Anal. Biochem., 2011, 409(1), 159-161.
[http://dx.doi.org/10.1016/j.ab.2010.10.007] [PMID: 20950582]
[58]
Elfaki, I.; Knitsch, A.; Matena, A.; Bayer, P. Identification and characterization of peptides that bind the PPIase domain of Parvulin17. J. Pept. Sci., 2013, 19(6), 362-369.
[http://dx.doi.org/10.1002/psc.2510] [PMID: 23596087]
[59]
Jubb, H.C.; Pandurangan, A.P.; Turner, M.A.; Ochoa-Montaño, B.; Blundell, T.L.; Ascher, D.B. Mutations at protein-protein interfaces: Small changes over big surfaces have large impacts on human health. Prog. Biophys. Mol. Biol., 2017, 128, 3-13.
[http://dx.doi.org/10.1016/j.pbiomolbio.2016.10.002] [PMID: 27913149]
[60]
Tuomilehto, J.; Uusitupa, M.; Gregg, E.W.; Lindström, J. Type 2 diabetes prevention programs-from proof-of-concept trials to national intervention and beyond. J. Clin. Med., 2023, 12(5), 1876.
[http://dx.doi.org/10.3390/jcm12051876] [PMID: 36902668]

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