THE PPARGC1A - GLY482SER POLYMORPHISM (RS8192678) AND THE METABOLIC SYNDROME IN A CENTRAL ROMANIAN POPULATION

• Published in: Acta endocrinologica (Bucharest, Romania : 2005) Vol. 13; no. 2; pp. 161 - 167
• Main Authors: Csép, K, Szigeti, E, Vitai, M, Korányi, L
• Format: Journal Article
• Language: English
• Published: Romania Acta Endocrinologica Foundation 01.04.2017
• Subjects: General Endocrinology; metabolic syndrome; PPARGC1A polymorphism
• ISSN: 1841-0987; 1843-066X
• DOI: 10.4183/aeb.2017.161

The peroxisome proliferator-activated receptor-γ co-activator 1-α (PPARGC1A), a key transcription factor involved in the control of metabolism and energy homeostasis, is an important biological and positional candidate of the metabolic syndrome. Association studies of its polymorphisms, however, yielded inconsistent sometimes conflicting results, pointing to important ethnic differences, which call for replication in various populations. In order to study its most common - potentially functional - polymorphism Gly482Ser (rs8192678), we carried out a case-control study in a central Romanian population. Two hundred and ninety six patients affected by the metabolic syndrome diagnosed according to the International Diabetes Federation proposed criteria and 166 middle-aged control subjects have been investigated. Genotyping was done by PCR-RFLP, using the restriction enzyme MspI. While the G(Gly)/A(Ser) allele frequencies (66.89/33.11 . 71.68/28.31 %) and GG/GA/AA genotype distribution (45.27-43.24-11.48 54.21-34.93-10.84 %) differed in the metabolic syndrome and control group, the risk of developing the metabolic syndrome did not reach the limit of statistical significance (OR=1.43; p=0.06, CI 95%: 0.97-2.09). Metabolic parameters in the two study groups did not show significant differences according to the genotype (p>0.05). rs8192678 could be a functional polymorphism contributing to the development of the metabolic syndrome, but probably its effect is minor, and might depend on gene-gene and gene-environment interactions. Clarification of very small effects would require larger sample sizes.