Background
Increasing scientific evidence has shown that predisposition to a particular health condition is not due to the modification of a single gene but to the variation of multiple genes located in numerous parts, or loci, of the chromosomes that can be affected by the interaction with the surrounding environment. Among the environmental factors, proper nutrition and regular physical activity can improve the quality of life contributing to a good state of health [
1].
Therefore, much of the current biomedical research is based on the expectation that understanding the genetic contribution to health status will revolutionize the diagnosis, treatment, and prevention of diseases [
2].
DNA sequence variation analysis is becoming a prominently important source of information for identifying genes involved in both normal biological and disease processes, such as development, aging, and reproduction. In this context, information about genetic variation is critical for understanding how genes work or malfunction and genetic and functional variation correlate.
In particular, individual lipid profiles appear to be strictly determined by lifestyle (smoking, diet, and physical activity). Family studies suggested that in many populations about half the variation in these traits is genetically determined and the concentrations of LDL cholesterol, HDL cholesterol, and triglycerides are strongly influenced by individuals’ genetic makeup. Indeed, genetic variants represent a substantial fraction of individual variation in lipid concentrations [
3]. However, several articles focusing on the role of genetic variation in anthropometric and body composition parameters have revealed genetic markers that influence the functional response of the human body to regular physical activities [
4,
5], the legacy of these parameters remains unclear.
Lipoprotein lipase (
LPL), fibronectin type III domain containing protein 5 (
FNDC5—precursor of irisin), and peroxisome proliferator-activated receptor gamma (
PPARγ) are well-known candidate genes since the key roles of their products in lipid and energy metabolism and/or their involvement in the pathogenesis of various complications of dyslipidemia has been extensively documented [
6‐
9]. In particular,
LPL encodes the lipoprotein lipase enzyme which hydrolyzes triglycerides and functions as a ligand/bridge factor for receptor-mediated absorption of lipoproteins;
FNDC5 encodes a protein that is released by muscle cells during exercise and regulates energy metabolism by converting white to brown fat, contributing to muscle adipose tissue cross-talk;
PPARγ encodes for a member of PPAR family of nuclear receptors which is an important adipogenic regulator and a modulator of intracellular insulin-signaling events [
10‐
12].
Several traditional SNP genotyping methods based on single traditional PCR or PCR real-time with fluorescent probes are commonly used in genetic research. However, the decreasing cost coupled with rapid progress in Next Generation Sequencing (NGS) and related bioinformatic computing resources have facilitated large-scale discovery of SNPs, genotyping thousands of SNPs in one run. This study aimed at identifying genetic polymorphisms in LPL, FNDC5, and PPARγ, using high-performance technologies combined with the evaluation of biochemical and anthropometric/body composition parameters, in healthy Italian adolescents enrolled in the Mediterranean Diet and Sport research program.
Discussion
In this study, to increase the understanding of the interaction between LPL, PPARγ, and FNDC5 genes with lipid metabolic profile as well as body composition parameters, under non-pathological conditions, we have thoroughly evaluated the presence of novel and already discovered SNPs and their potential associations in young adolescents.
The role of many genetic variations in relation to lipid levels has already extensively been studied [
12,
35,
36]. GWAS studies revealed that SNPs in the
LPL are associated with levels of cholesterol, triglycerides, and more, as well as numerous molecular phenotypes are related to human diseases and diseases risk [
6,
37,
38]. Furthermore, controversial data have been reported on the association (positive, null, or negative) between irisin levels and BMI, body weight and FM in different populations [
39‐
41] and different associations between lipid intake and BMI in carriers and non-carriers of
PPARγ polymorphisms have been observed [
42].
In our cohort, we identified 111 variants, of which 24 were novel. All genotyped variants were in concordance with Hardy–Weinberg equilibrium expectations. The single SNP analysis, performed by linear regression, revealed 26 significant associations (p < 0.05) of which 10 with body composition parameters and 16 with lipid profiles. The best associated PPARγ SNP with FFM was rs3856806 (p = 0.009) while FNDC5 SNPs significantly associated with FFM (rs726344, p = 0.02), FM and WHR (rs3480, p = 0.02; p = 0.03 respectively), and TBW (rs1570569, p = 0.03). A significant association, never previously described, was identified between the intronic variant c.775 + 80A > G in LPL, rs80143795, and FFM, BCM, and BMR.
In this study, the
LPL haplotype association results, largely comparable with the single-site analyses, revealed two main blocks (3 and 4) significantly associated with lipid and body composition parameters never reported before. In addition, considering the explained variance effects of
LPL polymorphisms, physical activity, WHR, and KIDMED score on lipid profile, we discovered that rs316 and rs4922115 were the main factors explaining the variability of triglycerides and total/LDL cholesterol, respectively. The rs316 is a synonymous variant located in exon 8 not in linkage disequilibrium with other identified SNPs, previously described to be associated with HDL cholesterol in a healthy African Black population [
43]. On the other hand, the individual effect of the non-coding rs4922115 on blood lipids has not been previously investigated in other populations except in Asian Indians [
44]. However, this study did not report any statistically significant interaction between this SNP and lipid parameters. In our study rs4922115, such as rs316, was part of haplotype block 3 and was in LD with rs11570892, rs1059507, and rs3866471 (R
2 = 0.58–0.67). In particular, most of these SNPs are located in the 3’UTR of the gene known to be involved in gene regulation, affecting LPL mRNA levels, or post-transcriptional changes [
45].
Several genetic polymorphisms in the 3′-UTR of different genes influencing gene expression, have already been reported in humans relating to various disorders. For example, rs1059611, significantly associated with increased HDL and decreased TG concentrations in patients with coronary heart disease, affects mRNA stability and LPL expression. Specifically, in homozygous and heterozygous states, the C allele carriers show increased gene expression [
46]. In addition, a functional study of rs6773957, strongly associated with plasma adiponectin levels and body weight in patients affected by metabolic syndrome, indicates that this variant may affect mRNA stability influencing the expression of ADIPOQ [
47]. Very often, 3’UTR SNPs influence gene expression by secondary structures, in the form of stem-loops on the mRNA [
48] such as rs27770 of
Polo-like Kinase 1 (
PLK1) which, showing variations in secondary mRNA structures and stability, leads to increased gene expression [
49].
Different studies have been strongly associated these 3’UTR-SNPs with HDL cholesterol and TG levels, especially in Europeans [
50,
51]. Moreover, it has been previously shown that haplotypes in these regions modulate pathologies such as atherosclerosis, insulin resistance, blood pressure, and obesity [
52].
Interestingly, the study of genetic variations identified in the LPL gene on the molecular and/or phenotypic consequences through genome-wide mapping of the eQTL analysis showed the increased expression of rs4922115 and other 4 unique eQTL SNPs (rs11570892, rs3208305, rs1059507, and rs3866471) in thyroid and adipose subcutaneous tissues, supporting the impact of these variants on the lipid parameters examined (Table
4). Among all these eQTL variants, rs3208305, found to be significantly associated with insulin levels in this study, showed a very strong deregulated expression also in other tissues such as adipose visceral and whole blood. However, determining causal variants, molecular mechanisms and relevant tissues contributing to these associations can be difficult, largely due to the ability of numerous tissues to synthesize and metabolize fatty acids [
53]. Furthermore, the concordant deregulated expression of
LPL gene SNPs in the thyroid tissue should not surprise considering the contribution of thyroid hormones to energy expenditure, heat production, and direct regulation of basal metabolism [
54].
Overall, despite recent studies suggest that a high-quality diet affects well-being [
55], a "healthy" lifestyle is not enough to prevent potential conditions “at-risk”. In addition to physical activity and muscle mass, other factors, such as hormonal structure, temperature, and genetics, influence basal metabolism [
56]. Our results showed that SNPs constituting the haplotypes were significantly associated with different lipid parameters (triglycerides, total cholesterol, and LDL cholesterol), while lifestyle habits, such as adherence to MD and physical activity, as well as WHR did have a low or null impact in healthy adolescents, highlighting the important role of genetic variants.
It is worth noting that the importance of diet and exercise in preventing cardiovascular disease among healthy young adults has been recently confirmed [
57,
58]. Therefore, large-scale longitudinal studies evaluating the outcome among these young adults will be helpful for better identification and modification of risk factors in certain high-risk haplotypes.
Several variables influencing the interpretation of data in our cohort and/or explaining different results from previous studies include the use of sampling criteria (e.g. affected population/healthy population; inclusion of very young subjects compared to those predominantly selected, ethnicity, etc.) different software tools and algorithms applied for variant analysis, although the major limitation of this study is the sample size used for association analyses.
Overall, this cohort study of young healthy individuals is of significant importance since it will add new knowledge to the role of genetic factors in maintaining health status. In fact, cataloguing of DNA polymorphisms in different populations is critical to the development of genome-based knowledge about an individual's susceptibility to many common diseases and, at the same time, will be essential to produce a safer and more effective individualized diet.
In future, it is hoped that research will unveil ways to make SNP useful markers for clinical setting. Finding out how SNPs affect the health of an individual and then transforming this knowledge into the development of new drugs will undoubtedly revolutionize the treatments of the most common devastating disorders.
Conclusions
To the best of our knowledge, this study is the first investigation reporting the analysis of sequence variations in the LPL, PPARγ, and FNDC5 genes and their associations with anthropometric/body composition and lipid traits, in young healthy individuals, who adhere to the MD and perform physical activity.
While our results support, even in a young cohort, previously reported data on the association of non-coding SNPs and lipid parameters, on the other hand, it emerges the fundamental contribution in these associations of the genetic component with respect to the environmental factors.
However, despite the large number of significant associations between SNPs and phenotypes, most associations have not yet been replicated, which is why further studies are needed to better elucidate the role of these variants in affecting interindividual variation in plasma lipid phenotypes, leading to improvements in quality of life through better preventive strategies.
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