Literature DB >> 26608632

Association between the rs12255372 variant of the TCF7L2 gene and obesity in a Cameroonian population.

Elvis Ndonwi Ngwa1,2, Eugene Sobngwi3,4,5, Barbara Atogho-Tiedeu6,7, Jean Jacques N Noubiap8,9, Olivier Sontsa Donfack10,11, Magellan Guewo-Fokeng12,13, Edith Pascale Mato Mofo14,15, Priscille Pokam Fosso16,17, Eric Djahmeni18, Rosine Djokam-Dadjeu19,20, Marie-Solange Evehe21,22, Folefac Aminkeng23, Wilfred F Mbacham24,25, Jean Claude Mbanya26,27,28.   

Abstract

BACKGROUND: The transcription factor 7-like 2 (TCF7L2) is one of the genes that have been identified as possible determinants of diabetes which is associated with obesity. Data on the genetic causes of obesity in sub-Saharan African populations are very scares. The aim of this study was to assess the association between the transcription factor 7-like 2 (TCF7L2) gene polymorphism (rs12255372 G/T) and obesity and weight-related traits in a Cameroonian population.
METHODS: A case-control study was conducted on 35 obese and 30 non-obese Cameroonian adults. TCF7L2 rs12255372 genotypes were determined using PCR-RFLP and correlated with BMI and weight-related traits.
RESULTS: No significant association was observed between the rs12255372 T allele (χ(2) = 0.0684, p = 0.79) or the TT genotype (χ(2) = 0.372, p = 0.54) of the TCF7L2 gene and obesity in the Cameroonian population. However, amongst the weight-related traits, triglycerides were significantly associated with the T risk allele of the TCF7L2 gene (p = 0.012).
CONCLUSION: This study on Cameroonian subjects replicates the absence of association between the TCF7L2 rs12255372 variant and obesity as observed in European and American populations.

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Year:  2015        PMID: 26608632      PMCID: PMC4658796          DOI: 10.1186/s13104-015-1661-3

Source DB:  PubMed          Journal:  BMC Res Notes        ISSN: 1756-0500


Background

The rising prevalence of overweight and obesity constitutes a global pandemic. The number of overweight and obese individuals increased from 857 million in 1980, to 2.1 billion in 2013 [1]. In 2010, overweight and obesity were estimated to cause 3.4 million deaths, 4 % of years of life lost, and 4 % of disability-adjusted life-years (DALYs) worldwide [2]. In Cameroon, the prevalence of overweight or obesity among adults aged ≥15 years increased from 22.5 % in 2002 to 26 % in 2006 [3, 4]. Obesity results from an imbalance between energy intake and expenditure which is influenced by a variety of multiple factors that could be environmental, psychosocial and genetic [5]. Although this epidemic is attributable to the trend of decreased physical activity and increased calorie intake, these external factors play out on a genetic background that determines body mass and susceptibility to obesity-related diseases [6] and so, common forms of obesity have a strong hereditary component. Depending on the population examined, these genetic factors may account for 6–85 % of the cases [7]. However, the genetic pathways that contribute to obesity have not yet been elucidated. The transcription factor 7-like 2 (TCF7L2) gene is one of those that have been identified as possible determinants of type 2 diabetes mellitus (T2DM). It codes for a transcription factor with a high-mobility box which is one of the components of the Wingless type (Wnt) signaling pathway, initially characterized in colon cancer and in the embryonic development of some organisms such as Drosophila [8]. Wnt pathways are a group of signal transduction pathways made of proteins that pass signals from outside of a cell through cell surface receptors to the inside of the cell. Three have been characterized including the canonical Wnt pathway, the non-canonical planar cell polarity pathway and the non-canonical Wnt/calcium pathway. It has been shown that in adipocytes, the canonical Wnt-signaling via TCF7L2 down-regulates adipogenesis [9]. Although TCF7L2 was not identified as a risk factor for obesity in a study involving European populations, its effect on the risk for T2DM was modulated by obesity [10]. Additionally, a study revealed that the rs12255372 variant of TCF7L2 was protective for obesity in Mexican children [11]. These findings warrant further investigation of the role of TCF7L2 in obesity among various ethnic populations. We previously reported on the rs12255372 (G/T) and rs7903146 (C/T) polymorphisms of TCF7L2 as risk factors for type 2 diabetes mellitus in a Cameroonian population [12, 13], however to the best of our knowledge, the association between rs12255372 (G/T) and obesity has not been explored in any African population till date. The aim of this study therefore was to assess the possible association of the TCF7L2 rs12255372 polymorphism with obesity and weight-related traits in a Cameroonian population. Findings may contribute to further investigations for the understanding of the causal role of heredity in obesity which may foster successful interventions and treatments.

Methods

Study population

A case–control study was conducted that involved 35 obese (BMI ≥ 30 kg/m2) and 30 non-obese (18 ≤ BMI < 25 kg/m2) adults of Cameroonian origin, aged 20 years and above. Obese patients were recruited from the Outpatients Clinic of the National Obesity Center of the Yaoundé Central Hospital, and non-obese controls from the general population between February and April 2011. Diabetic patients and pregnant women were excluded from the study. For all participants, data was collected on the sex and age. Height, waist and hip circumference to the nearest 0.5 cm were measured, as well as weight in light clothes to the nearest 0.1 kg. The body mass index (BMI) as weight in kg divided by height in meters squared (m2), and the waist-to-hip ratio as waist circumference (cm) divided by hip circumference (cm) were calculated. Obesity was defined as BMI ≥ 30 kg/m2. The resting blood pressures were measured using standardized procedures with an automatic sphygmomanometer Omron HEM-705 CP (Omron Corporation, Tokyo, Japan).

Biochemical assays

Fasting plasma glucose (glucose oxidase–peroxidase method), serum cholesterol (cholesterol oxidase phenol-4-amino antipyrene peroxidase method), serum triglycerides (glycerol phosphatase oxidase phenol-4-amino antipyrene peroxidase method), and high-density lipoprotein (HDL)-cholesterol (cholesterol oxidase phenol-4-amino antipyrene peroxidase method) were measured on a spectrophotometer (UV Mini 1240) using Chronolab kits (Chronolab Systems, Barcelona, Spain). Low-density lipoprotein (LDL)-cholesterol was calculated using the Friedwald’s formula [14].

DNA extraction and molecular genotyping

DNA was extracted from whole blood on filter paper by the Chelex method. Sixty-five participants (35 obese patients and 30 controls) were genotyped for TCF7L2 rs12255372 by polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP). The TCF7L2 rs12255372 (G/T) polymorphism was genotyped using the following primers: forward 5′-CTG GAA ACT AAG GCG TGA GG-3′, reverse 5′-GGG TCG ATG TTG TTG AGC TT-3′ (SIGMA-ALDRICH, St. Louis, Missouri, USA). A final reaction volume of 15 μL for the PCR was constituted which contained 100 ng of genomic DNA, 5 pmol of each primer, PCR buffer with 1 mmol/L of MgCl2, 100 μmol/L of each deoxynucleotide triphosphate (dNTP), 0.5 U of Hot Star Taq DNA polymerase (QIAGEN) and 7.8 µl of nuclease-free water. The PCR was carried out in a BIOMETRA T3 Thermal Cycler under the following conditions: 95 °C for 15 min, followed by 34 cycles of 95 °C for 30 s, 54 °C for 30 s, 72 °C for 30 s, and a final extension of 72 °C for 9 min. The PCR amplicons (346 bp) were then digested with Thermus species (Tsp 5091) restriction enzyme at 37 °C overnight. The reaction volume was set to 15 μl, containing 7 μl of amplicons, 1× NEB buffer1. The resulting products were separated by electrophoresis on a 3 % agarose gel using a 100 bp DNA ladder and visualized under a UV transilluminator.

Statistical analyses

Allele and genotype frequencies in patients and control subjects were estimated by direct counting. Qualitative variables were analyzed by the Chi Square (χ2) test with Yates’ Continuity correction or the Exact test when appropriate using Epi Info version 6 (USD, Stone Mountain, USA). Quantitative variables were analysed by Mann–Whitney U test statistics using IBM SPSS for Windows version 20.0 (SPSS, Inc., Chicago, IL, USA). P < 0.05 was considered statistically significant and in case of multiple comparisons, the conservative Bonferroni correction was applied. The relative risks (RR) were calculated as odd ratios (OR) with 95 % confidence interval (CI) using Woolf’s formula.

Ethical considerations

The study was granted approval by the National Ethical Review Board of the Cameroon Ministry of Public Health. Written informed consent was obtained from all the participants. The study was conducted in accordance with the Helsinki Declaration.

Results

Characteristics of the study population

Table 1 shows anthropometric features, blood pressure and metabolic profile of the study population. Significant differences between obese patients and health controls were observed for age (median age—46.00 vs 25.00 years, p < 0.0001), waist-to-hip ratio (median value—0.8600 vs 0.8100, p < 0.0001), diastolic blood pressure (median value—80.00 vs 68.00 mmHg, p < 0.0040) and BMI (median value—32.76 vs 22.39 kg/m2, p < 0.0001). All participants were positively genotyped. The respective fragments for the different genotypes were as follows. The wild type homozygote GG genotype had two band appearing at 143 and 104 bp; the mutant homozygote TT had two bands appearing at 126 and 104 bp and the mutant heterozygote GT had three bands appearing at 143, 126 and 104 bp. Fragments smaller than 100 bp migrated out of the gel and were not visualized (Figs. 1, 2).
Table 1

Characteristics of the study population

CharacteristicsNon-obese (n = 30)Obese (n = 35) P value
Demographic
 Sex, % of male33.3 %8.6 %0.028
 Age (years)25.00 (23.00–36.50)46.00 (39.00–53.00)<0.0001
Clinical
 WHR ratio0.81 (0.77–0.84)0.86 (0.83–0.93)<0.0001
 SBP (mmHg)116.00 (106.00–125.00)125.00 (117.00–141.00)0.27
 DBP (mmHg)68.00 (61.75–85.00)80.00 (75.00–88.00)0.004
 BMI (kg/m2)22.39 (21.11–23.93)32.76 (30.94–35.72)<0.0001
Biological
 FPG (g/L)90.00 (83.00–103.25)96.00 (86.00–103.00)0.392
 TC (mg/dL)171.45 (161.46–192.83)181.94 (172.26–208.31)0.093
 HDL-C (mg/dL)46.79 (42.71–50.16)47.96 (43.70–51.72)0.247
 LDL-C (mg/dL)100.05 (92.87–120.24)106.97 (94.08–135.88)0.490
 TG (mg/dL)125.29 (120.50–135.16)131.80 (120.69–144.83)0.193

Data are medians (interquartile range) unless otherwise stated

WHR waist-to-hip ratio, SBP systolic blood pressure, DBP diastolic blood pressure, BMI body mass index, FPG fasting plasma glucose, TC total cholesterol, HDL high density lipoprotein cholesterol, LDL low density lipoprotein cholesterol, TG triglycerides

Fig. 1

Electrophoregram of amplified rs 12255372 portion of the TCF7L2 gene. C negative control, MwM molecular weight marker (100 bp ladder), 1–9 tested samples, bp base pair

Fig. 2

Electrophoregram of digested amplicons with Tsp 5091. C negative control, MwM molecular weight marker (100 bp ladder), 1–6 and 1–7 tested samples, bp base pair

Characteristics of the study population Data are medians (interquartile range) unless otherwise stated WHR waist-to-hip ratio, SBP systolic blood pressure, DBP diastolic blood pressure, BMI body mass index, FPG fasting plasma glucose, TC total cholesterol, HDL high density lipoprotein cholesterol, LDL low density lipoprotein cholesterol, TG triglycerides Electrophoregram of amplified rs 12255372 portion of the TCF7L2 gene. C negative control, MwM molecular weight marker (100 bp ladder), 1–9 tested samples, bp base pair Electrophoregram of digested amplicons with Tsp 5091. C negative control, MwM molecular weight marker (100 bp ladder), 1–6 and 1–7 tested samples, bp base pair

Genetic association assessment

The TCF7L2 rs12255372 (G/T) SNP was in Hardy–Weinberg equilibrium in the general population (χ2 = 0.0500, p = 0.8300). The association between TCF7L2 and obesity in Cameroon was determined by comparing the allele and genotype frequencies of rs12255372 (G/T) in the 35 obese patients and 30 healthy controls (Table 2). The allelic frequencies obtained in the general population were 18.35 % for the T allele and 81.65 % for the G allele. In the case–control analysis, no significant difference was observed in the allelic and genotypic frequencies between the obese and non-obese groups (χ2 = 0.0684, p = 0.7900 for allele and χ2 = 0.3720, p = 0.5400 for genotype).
Table 2

Case–control association analysis of TCF7L2 rs12255372 (G/T) with obesity

TCF7L2 rs12255372 G/TNon-obesea Obesea Test statistics P valueOR (95 % CI)
Alleles
 G50 (83.3)56 (80)χ2 = 0.06840.790.51 (1.25–3.06)
 T10 (16.7)14 (20)χ2 = 0.06840.790.33 (0.80–1.96)
 Total (2n)6070
Genotypes
 G/G21 (70)22 (62.9)χ2 = 0.1180.731.38 (0.49–3.90)
 G/T8 (26.7)12 (34.3)χ2 = 0.1550.690.70 (0.23–2.03)
 T/T1 (3.3)1 (2.9)χ2 = 0.3720.541.17 (0.07–19.59)
 Total (n)3035

RR (relative risks) were calculated as odd ratios (OR) with 95 % CI using Woolf’s formula. When one of the entries was zero, OR was calculated using Woolf’s formula with Haldane’s modification

aData are given as n (%) unless otherwise stated

Case–control association analysis of TCF7L2 rs12255372 (G/T) with obesity RR (relative risks) were calculated as odd ratios (OR) with 95 % CI using Woolf’s formula. When one of the entries was zero, OR was calculated using Woolf’s formula with Haldane’s modification aData are given as n (%) unless otherwise stated

Genotype–phenotype correlation

Genotype–phenotype correlations were performed to investigate the association of TCF7L2 rs12255372 and metabolic parameters in lean and obese individuals. These case–control analyses were performed according to demographic (sex and age at onset), clinical (body mass index, waist-to-hip ratio, systolic and diastolic blood pressure) and biological (fasting plasma glucose, total cholesterol, HDL, LDL and triacylglycerol) characteristics. T allele carriers in the obese group had a significantly higher triglyceride levels when compared to their non-obese counterparts (p < 0.0120).

Discussion

TCF7L2 has been associated with fasting plasma insulin, with glucose levels in type 2 diabetes patients to some extent with BMI [10, 15, 16], and with adipogenesis [9]. It is one of the genes that have been identified as possible determinants of diabetes. Data on genetic susceptibility of African populations to chronic disease are very scarce [17]. The aim of this study was to assess the possible association of the TCF7L2 rs12255372 polymorphism with obesity and weight-related traits in a Cameroonian population. This case–control association analysis demonstrates the absence of association between the polymorphism and obesity. This finding is similar to those of Cauchi et al. [10] and Saxena et al. [18] who also found no genetic association between TCF7L2 and obesity in European and US populations, respectively, especially for the rs7903146 and rs10885406 polymorphisms. However, some other studies reported a tendency for negative association with BMI [10, 19]. Nevertheless, these results are different from those of Klunder et al. that showed a protective association between rs12255372 polymorphism and obesity in Mexican children, while a deleterious effect of this variant was observed in diabetic adults [11]. Moreover, the background frequencies of the TCF7L2 rs12255372 alleles and genotypes were different between the Cameroonian and Mexican populations indicating genetic heterogeneity across populations and ancestries on this locus. The frequency of this risk allele has been observed to be highest in a study in Caucasians (77 %) with 42 % in cases (diabetics) and 35 % in controls [20] and lowest in Asians (1 %) with 0.6 % in cases and 0.4 % in controls [21]. Studies have shown that some variants of TCF7L2 are associated with impaired lipid metabolism, especially a trend towards higher triglycerides, with an adverse effect on cardiovascular risk and stroke incidence [22, 23]. Meta-analyses have been conducted to confirm the association from individual studies. These studies (meta-analyses) further support the association between TCF7L2 gene and metabolic diseases including diabetes and obesity. Among the common studied allele, rs12255372 variant of the TCF7L2 gene is significantly associated with susceptibility to T2DM in the global population [24] while the other allele (rs7903146) is associated with metabolic syndrome [25] of which dyslipidemia is a predictor. TCF7L2 rs12255372 has also been found to be associated with high serum triglycerides and was differentially expressed in adipose tissue in families with familial combined hyperlipidaemia [26]. Genotype–phenotype correlation assessment in our study revealed that the gene was preferentially associated with high triglyceride levels. Carriers of the T risk allele had a significantly higher triglyceride level when compared to carriers of the G allele (p < 0.0120). This finding suggests a possible association between the TCF7L2 rs12255372 variant and cardiovascular risk in the Cameroonian population. Further studies are therefore required to confirm these findings and then investigate the nature of the association.

Conclusion

TCF7L2 rs12255372 was not associated with obesity in this Cameroonian population, but was associated with higher triglyceride levels in obese patients. Due to the small sample size of the study and the lack of power to detect an association, other studies carried with a larger sample size and matched for age and sex are required to confirm these findings.
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Journal:  Clin Transl Med       Date:  2015-04-23

10.  Research capacity. Enabling the genomic revolution in Africa.

Authors:  Charles Rotimi; Akin Abayomi; Alash'le Abimiku; Victoria May Adabayeri; Clement Adebamowo; Ezekiel Adebiyi; Adebowale D Ademola; Adebowale Adeyemo; Dwomoa Adu; Dissou Affolabi; Godfred Agongo; Samuel Ajayi; Sally Akarolo-Anthony; Rufus Akinyemi; Albert Akpalu; Marianne Alberts; Orlando Alonso Betancourt; Ahmed Mansour Alzohairy; Gobena Ameni; Olukemi Amodu; Gabriel Anabwani; Kristian Andersen; Fatiu Arogundade; Oyedunni Arulogun; Danny Asogun; Rasheed Bakare; Naby Balde; Mary Lynn Baniecki; Christine Beiswanger; Alia Benkahla; Lara Bethke; Micheal Boehnke; Vincent Boima; James Brandful; Andrew I Brooks; Frank C Brosius; Chester Brown; Bruno Bucheton; David T Burke; Barrington G Burnett; Stacy Carrington-Lawrence; Nadia Carstens; John Chisi; Alan Christoffels; Richard Cooper; Heather Cordell; Nigel Crowther; Talishiea Croxton; Jantina de Vries; Leslie Derr; Peter Donkor; Seydou Doumbia; Audrey Duncanson; Ivy Ekem; Ahmed El Sayed; Mark E Engel; John C K Enyaru; Dean Everett; Faisal M Fadlelmola; Eyitayo Fakunle; Kenneth H Fischbeck; Anne Fischer; Onikepe Folarin; Junaid Gamieldien; Robert F Garry; Simani Gaseitsiwe; Rasheed Gbadegesin; Anita Ghansah; Maria Giovanni; Parham Goesbeck; F Xavier Gomez-Olive; Donald S Grant; Ravnit Grewal; Mark Guyer; Neil A Hanchard; Christian T Happi; Scott Hazelhurst; Branwen J Hennig; Christiane Hertz-; Winston Hide; Friedhelm Hilderbrandt; Christopher Hugo-Hamman; Muntaser E Ibrahim; Regina James; Yasmina Jaufeerally-Fakim; Carolyn Jenkins; Ute Jentsch; Pan-Pan Jiang; Moses Joloba; Victor Jongeneel; Fourie Joubert; Mukthar Kader; Kathleen Kahn; Pontiano Kaleebu; Saidi H Kapiga; Samar Kamal Kassim; Ishmael Kasvosve; Jonathan Kayondo; Bernard Keavney; Adeodata Kekitiinwa; Sheik Humarr Khan; Paul Kimmel; Mary-Claire King; Robert Kleta; Mathurin Koffi; Jeffrey Kopp; Matthias Kretzler; Judit Kumuthini; Samuel Kyobe; Catherine Kyobutungi; Daniel T Lackland; Karen A Lacourciere; Guida Landouré; Rita Lawlor; Thomas Lehner; Maia Lesosky; Naomi Levitt; Katherine Littler; Zane Lombard; Jeanne F Loring; Sylvester Lyantagaye; Annette Macleod; Ebony B Madden; Chengetai R Mahomva; Julie Makani; Manmak Mamven; Marape Marape; Graeme Mardon; Patricia Marshall; Darren P Martin; Daniel Masiga; Robin Mason; Michael Mate-Kole; Enock Matovu; Mary Mayige; Bongani M Mayosi; Jean Claude Mbanya; Sheryl A McCurdy; Mark I McCarthy; Helen McIlleron; S O Mc'Ligeyo; Corrine Merle; Ana Olga Mocumbi; Charles Mondo; John V Moran; Ayesha Motala; Marva Moxey-Mims; Wata Sununguko Mpoloka; Chisomo L Msefula; Thuli Mthiyane; Nicola Mulder; Gebregziab her Mulugeta; Dieuodonne Mumba; John Musuku; Mo Nagdee; Oyekanmi Nash; Daouda Ndiaye; Anh Quynh Nguyen; Mark Nicol; Oathokwa Nkomazana; Shane Norris; Betty Nsangi; Alexander Nyarko; Moffat Nyirenda; Eileen Obe; Reginald Obiakor; Abraham Oduro; Solomon F Ofori-Acquah; Okechukwu Ogah; Stephen Ogendo; Kwaku Ohene-Frempong; Akinlolu Ojo; Timothy Olanrewaju; John Oli; Charlotte Osafo; Odile Ouwe Missi Oukem-Boyer; Bruce Ovbiagele; Andrew Owen; Mayowa Ojo Owolabi; Lukman Owolabi; Ellis Owusu-Dabo; Guillaume Pare; Rulan Parekh; Hugh G Patterton; Margaret B Penno; Jane Peterson; Rembert Pieper; Jacob Plange-Rhule; Martin Pollak; Julia Puzak; Rajkumar S Ramesar; Michele Ramsay; Rebekah Rasooly; Shiksha Reddy; Pardis C Sabeti; Kwamena Sagoe; Tunde Salako; Oumar Samassékou; Manjinder S Sandhu; Osman Sankoh; Fred Stephen Sarfo; Marie Sarr; Gasnat Shaboodien; Issa Sidibe; Gustave Simo; Martin Simuunza; Liam Smeeth; Eugene Sobngwi; Himla Soodyall; Hermann Sorgho; Oumou Sow Bah; Sudha Srinivasan; Dan J Stein; Ezra S Susser; Carmen Swanepoel; Godfred Tangwa; Andrew Tareila; Ozlem Tastan Bishop; Bamidele Tayo; Nicki Tiffin; Halidou Tinto; Ekaete Tobin; Stephen Meir Tollman; Mahamadou Traoré; Marsha J Treadwell; Jennifer Troyer; Masego Tsimako-Johnstone; Vincent Tukei; Ifeoma Ulasi; Nzovu Ulenga; Beverley van Rooyen; Ablo Prudence Wachinou; Salina P Waddy; Alisha Wade; Misaki Wayengera; James Whitworth; Louise Wideroff; Cheryl A Winkler; Sarah Winnicki; Ambroise Wonkam; Mengistu Yewondwos; Tadase sen; Nathan Yozwiak; Heather Zar
Journal:  Science       Date:  2014-06-20       Impact factor: 47.728

View more
  5 in total

Review 1.  The genomic landscape of African populations in health and disease.

Authors:  Charles N Rotimi; Amy R Bentley; Ayo P Doumatey; Guanjie Chen; Daniel Shriner; Adebowale Adeyemo
Journal:  Hum Mol Genet       Date:  2017-10-01       Impact factor: 6.150

2.  Associations of TCF7L2 rs11196218 (A/G) and GLP-1R rs761386 (C/T) Gene Polymorphisms with Obesity in Chinese Population.

Authors:  Tiantian Xu; Mengmeng Liu; Qingjing Liu; Bian Wang; Min Wang; Minli Qu; Xin Chen; Jing Wu
Journal:  Diabetes Metab Syndr Obes       Date:  2021-06-01       Impact factor: 3.168

3.  Targeted deletion of Tcf7l2 in adipocytes promotes adipocyte hypertrophy and impaired glucose metabolism.

Authors:  Gisela Geoghegan; Judith Simcox; Marcus M Seldin; Timothy J Parnell; Chris Stubben; Steven Just; Lori Begaye; Aldons J Lusis; Claudio J Villanueva
Journal:  Mol Metab       Date:  2019-03-14       Impact factor: 7.422

4.  A Nutrigenetic Approach to Investigate the Relationship between Metabolic Traits and Vitamin D Status in an Asian Indian Population.

Authors:  Buthaina E Alathari; Dhanasekaran Bodhini; Ramamoorthy Jayashri; Nagarajan Lakshmipriya; Coimbatore Subramanian Shanthi Rani; Vasudevan Sudha; Julie A Lovegrove; Ranjit Mohan Anjana; Viswanathan Mohan; Venkatesan Radha; Rajendra Pradeepa; Karani S Vimaleswaran
Journal:  Nutrients       Date:  2020-05-09       Impact factor: 5.717

5.  Associations of TCF7L2 gene polymorphisms with the risk of diabetic nephropathy: A case-control study.

Authors:  Yan Zhuang; Fukun Niu; Defeng Liu; Juanjuan Sun; Xiaowei Zhang; Jian Zhang; Shuxia Guo
Journal:  Medicine (Baltimore)       Date:  2018-10       Impact factor: 1.817

  5 in total

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