Effect Of Pregnancy And Lactation On Lipoprotein And Cholesterol Metabolism In The Rat

Origins of hyperlipidemia and cholestasis that occur during pregnancy were investigated by examining expression of key elements related to plasma and hepatic cholesterol metabolism during pregnancy, lactation, and post-lactation in the rat model. Among major findings were: during pregnancy, the activities of hepatic 3-hydroxy-3-methylglutaryl coenzyme A reductase, acyl coenzyme A:cholesterol acyltransferase, acyl coenzyme A:diacylglycerol acyltransferase, cholesterol 7 alpha-hydroxylase, cholesterol ester hydrolases, low density lipoprotein receptors, LRP, and mdr2 were significantly lower or similar to non-pregnant controls while SR-B1 was elevated. Once lactation began, reductase, cholesterol acyltransferase, 7 alpha-hydroxylase activities, low density lipoprotein receptors, and mdr2 increased while SR-B1 decreased. In later stages of lactation most hepatic elements returned to near control levels. Plasma cholesterol levels were higher than control at birth and during lactation with increase in LDL-size particles. By 24 h post-lactation, plasma triglycerides were 3.7-fold higher while cholesterol remained unchanged. Very large lipoproteins were present while LDL-size particles were now absent. Hepatic cholesterol acyltransferase had decreased to 27% of control while diacylglycerol acyltransferase increased 3-fold and low density lipoprotein receptors doubled. Most elements were normalized 3 weeks after weaning except for LRP and low density lipoprotein receptors which were elevated. These studies provide an integrated picture of expression of key elements of hepatic and plasma cholesterol metabolism during pregnancy and lactation and advance understanding of hyperlipidemia and cholestasis during these states

Joint effects of known type 2 diabetes susceptibility loci in genome-wide association study of Singapore Chinese: The Singapore Chinese health study

Background: Genome-wide association studies (GWAS) have identified genetic factors in type 2 diabetes (T2D), mostly among individuals of European ancestry. We tested whether previously identified T2D-associated single nucleotide polymorphisms (SNPs) replicate and whether SNPs in regions near known T2D SNPs were associated with T2D within the Singapore Chinese Health Study. Methods: 2338 cases and 2339 T2D controls from the Singapore Chinese Health Study were genotyped for 507,509 SNPs. Imputation extended the genotyped SNPs to 7,514,461 with high estimated certainty (r2>0.8). Replication of known index SNP associations in T2D was attempted. Risk scores were computed as the sum of index risk alleles. SNPs in regions ±100 kb around each index were tested for associations with T2D in conditional fine-mapping analysis. Results: Of 69 index SNPs, 20 were genotyped directly and genotypes at 35 others were well imputed. Among the 55 SNPs with data, disease associations were replicated (at p<0.05) for 15 SNPs, while 32 more were directionally consistent with previous reports. Risk score was a significant predictor with a 2.03 fold higher risk CI (1.69-2.44) of T2D comparing the highest to lowest quintile of risk allele burden (p = 5.72×10-14). Two improved SNPs around index rs10923931 and 5 new candidate SNPs around indices rs10965250 and rs1111875 passed simple Bonferroni corrections for significance in conditional analysis. Nonetheless, only a small fraction (2.3% on the disease liability scale) of T2D burden in Singapore is explained by these SNPs. Conclusions: While diabetes risk in Singapore Chinese involves genetic variants, most disease risk remains unexplained. Further genetic work is ongoing in the Singapore Chinese population to identify unique common variants not already seen in earlier studies. However rapid increases in T2D risk have occurred in recent decades in this population, indicating that dynamic environmental influences and possibly gene by environment interactions complicate the genetic architecture of this disease. © 2014 Chen et al

Validation of dual energy X-ray absorptiometry measures of abdominal fat by comparison with magnetic resonance imaging in an Indian population.

OBJECTIVE: Abdominal adiposity is an important risk factor for diabetes and cardiovascular disease in Indians. Dual energy X-ray absorptiometry (DXA) can be used to determine abdominal fat depots, being more accessible and less costly than gold standard measures such as magnetic resonance imaging (MRI). DXA has not been fully validated for use in South Asians. Here, we determined the accuracy of DXA for measurement of abdominal fat in an Indian population by comparison with MRI. DESIGN: 146 males and females (age range 18-74, BMI range 15-46 kg/m(2)) from Hyderabad, India underwent whole body DXA scans on a Hologic Discovery A scanner, from which fat mass in two abdominal regions was calculated, from the L1 to L4 vertebrae (L1L4) and from the L2 to L4 vertebrae (L2L4). Abdominal MRI scans (axial T1-weighted spin echo images) were taken, from which adipose tissue volumes were calculated for the same regions. RESULTS: Intra-class correlation coefficients between DXA and MRI measures of abdominal fat were high (0.98 for both regions). Although at the level of the individual, differences between DXA and MRI could be large (95% of DXA measures were between 0.8 and 1.4 times MRI measures), at the sample level, DXA only slightly overestimated MRI measures of abdominal fat mass (mean difference in L1L4 region: 2% (95% CI:0%, 5%), mean difference in L2L4 region:4% (95% CI: 1%, 7%)). There was evidence of a proportional bias in the association between DXA and MRI (correlation between difference and mean -0.3), with overestimation by DXA greater in individuals with less abdominal fat (mean bias in leaner half of sample was 6% for L1L4 (95%CI: 2, 11%) and 7% for L2L4 (95% CI:3,12%). CONCLUSIONS: DXA measures of abdominal fat are suitable for use in Indian populations and provide a good indication of abdominal adiposity at the population level