Leptin receptor polymorphisms interact with polyunsaturated fatty acids to augment risk of insulin resistance and metabolic syndrome in adults.

The leptin receptor (LEPR) is associated with insulin resistance, a key feature of metabolic syndrome (MetS). Gene-fatty acid interactions may affect MetS risk. The objective was to investigate the relationship among LEPR polymorphisms, insulin resistance, and MetS risk and whether plasma fatty acids, a biomarker of dietary fatty acids, modulate this. LEPR polymorphisms (rs10493380, rs1137100, rs1137101, rs12067936, rs1805096, rs2025805, rs3790419, rs3790433, rs6673324, and rs8179183), biochemical measurements, and plasma fatty acid profiles were determined in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1754). LEPR rs3790433 GG homozygotes had increased MetS risk compared with the minor A allele carriers [odds ratio (OR) = 1.65; 95% CI: 1.05–2.57; P = 0.028], which may be accounted for by their increased risk of elevated insulin concentrations (OR 2.40; 95% CI: 1.28–4.50; P = 0.006) and insulin resistance (OR = 2.15; 95% CI: 1.18–3.90; P = 0.012). Low (less than median) plasma (n-3) and high (n-6) PUFA status exacerbated the genetic risk conferred by GG homozygosity to hyperinsulinemia (OR 2.92–2.94) and insulin resistance (OR 3.40–3.47). Interestingly, these associations were abolished against a high (n-3) or low (n-6) PUFA background. Importantly, we replicated some of these findings in an independent cohort. Homozygosity for the LEPR rs3790433 G allele was associated with insulin resistance, which may predispose to increased MetS risk. Novel gene-nutrient interactions between LEPR rs3790433 and PUFA suggest that these genetic influences were more evident in individuals with low plasma (n-3) or high plasma (n-6) PUFA.

Gene-nutrient interactions with dietary fat modulate the association between genetic variation of the ACSL1 gene and metabolic syndrome

Long-chain acyl CoA synthetase 1 (ACSL1) plays an important role in fatty acid metabolism and triacylglycerol (TAG) synthesis. Disturbance of these pathways may result in dyslipidemia and insulin resistance, hallmarks of the metabolic syndrome (MetS). Dietary fat is a key environmental factor that may interact with genetic determinants of lipid metabolism to affect MetS risk. We investigated the relationship between ACSL1 polymorphisms (rs4862417, rs6552828, rs13120078, rs9997745, and rs12503643) and MetS risk and determined potential interactions with dietary fat in the LIPGENE-SU.VI.MAX study of MetS cases and matched controls (n = 1,754). GG homozygotes for rs9997745 had increased MetS risk {odds ratio (OR) 1.90 [confidence interval (CI) 1.15, 3.13]; P = 0.01}, displayed elevated fasting glucose (P = 0.001) and insulin concentrations (P = 0.002) and increased insulin resistance (P = 0.03) relative to the A allele carriers. MetS risk was modulated by dietary fat, whereby the risk conferred by GG homozygosity was abolished among individuals consuming either a low-fat (<35% energy) or a high-PUFA diet (>5.5% energy). In conclusion, ACSL1 rs9997745 influences MetS risk, most likely via disturbances in fatty acid metabolism, which was modulated by dietary fat consumption, particularly PUFA intake, suggesting novel gene-nutrient interactions.

A two-locus forensic match probability for subdivided populations

A two-locus match probability is presented that incorporates the effects of within-subpopulation inbreeding (consanguinity) in addition to population subdivision. The usual practice of calculating multi-locus match probabilities as the product of single-locus probabilities assumes independence between loci. There are a number of population genetics phenomena that can violate this assumption: in addition to consanguinity, which increases homozygosity at all loci simultaneously, gametic disequilibrium will introduce dependence into DNA profiles. However, in forensics the latter problem is usually addressed in part by the careful choice of unlinked loci. Hence, as is conventional, we assume gametic equilibrium here, and focus instead on between-locus dependence due to consanguinity. The resulting match probability formulae are an extension of existing methods in the literature, and are shown to be more conservative than these methods in the case of double homozygote matches. For two-locus profiles involving one or more heterozygous genotypes, results are similar to, or smaller than, the existing approaches.