These findings provide novel insights into the antidepressant action of PUFAs and further strengthen the link between inflammation and depression.

ObjectiveTo identify plasma uric acid related genes in extremely obese and normal weight individuals using genome wide association studies (GWAS).Design and MethodsUsing genotypes from a GWAS focusing on obesity and thinness, we performed quantitative trait association analyses (PLINK) for plasma uric acid levels in 1,060 extremely obese individuals [body mass index (BMI) >35 kg/m2] and normal-weight controls (BMI<25kg/m2). In 961 samples with uric acid data, 924 were females.ResultsSignificant associations were found in SLC2A9 gene SNPs and plasma uric acid levels (rs6449213, P=3.15×10−12). DIP2C gene SNP rs877282 also reached genome wide significance(P=4,56×10−8). Weaker associations (P<1×10−5) were found in F5, PXDNL, FRAS1, LCORL, and MICAL2genes. Besides SLC2A9, 3 previously identified uric acid related genes ABCG2 (rs2622605, P=0.0026), SLC17A1 (rs3799344, P=0.0017), and RREB1 (rs1615495, P =0.00055) received marginal support in our study.ConclusionsTwo genes/chromosome regions reached genome wide association significance (P< 1× 10−7, 550K SNPs) in our GWAS : SLC2A9, the chromosome 2 60.1 Mb region (rs6723995), and the DIP2C gene region. Five other genes (F5, PXDNL, FRAS1, LCORL, and MICAL2) yielded P<1× 10−5. Four previous reported associations were replicated in our study, including SLC2A9, ABCG2, RREB, and SLC17A1.

ABSTRACT. Recent genome-wide association studies have identified many loci associated with type 2 diabetes mellitus (T2DM), hyperuricemia, and obesity in various ethnic populations. However, quantitative traits have been less well investigated in Han Chinese T2DM populations. We investigated the association between candidate gene single nucleotide polymorphisms (SNPs) and metabolic syndromerelated quantitative traits in Han Chinese T2DM subjects. Unrelated Han Chinese T2DM patients (1975) were recruited. Eighty-six SNPs were genotyped and tested for association with quantitative traits including lipid profiles, blood pressure, body mass index (BMI), serum uric acid (SUA), glycated hemoglobin (HbA1c), plasma glucose [fasting plasma glucose (FPG)], plasma glucose 120 min post-OGTT (P2PG; OGTT = oral glucose tolerance test), and insulin resistance-related traits. We found that CAMTA1, ABI2, VHL, KAT2B, PKHD1, ESR1, TOX, SLC30A8, SFI1, and MYH9 polymorphisms were associated with HbA1c, FPG, and/or P2PG; GCK, HHEX, TCF7L2, KCNQ1, and TBX5 polymorphisms were associated with insulin resistance-related traits; ABCG2, SLC2A9, and PKHD1 polymorphisms were associated with SUA; CAMTA1, VHL, KAT2B, PON1, NUB1, SLITRK5, SMAD3, FTO, FANCA, and PCSK2 polymorphisms were associated with blood lipid traits; CAMTA1, SPAG16, TOX, KCNQ1, ACACB, and MYH9 polymorphisms were associated with blood pressure; and UBE2E3, SPAG16, SLC2A9, CDKAL1, CDKN2A/B, TCF7L2, SMAD3, and PNPLA3 polymorphisms were associated with BMI (all P values <0.05). Some of the candidate genes were associated with metabolic and anthropometric traits in T2DM in Han Chinese. Although none of these associations reached genomewide significance (P < 5 x 10 -8 ), genes and loci identified in this study are worthy of further replication and investigation.

Context: Obesity is a typical complex disorder resulting from behaviors promoted in westernized societies in the presence of a genetic predisposition. We hypothesized that new genes predisposing to obesity can be detected at the mRNA level. Objective: To identify susceptibility genes for obesity. Design: Linkage and expression profile data from different cohorts were combined to select novel candidate genes that were analyzed for association with obesity. Setting and participants: University Hospital in Stockholm. Adipose tissue mRNA levels were quantified in 96 women. Two large cohorts with a wide distribution in body mass index (BMI, n ¼ 1013 and 1423) were genotyped. Main outcome measure: mRNA levels and allelic association with obesity. Results: We confirmed association between candidate gene mRNA levels in adipose tissue and obesity. A total of 118 polymorphisms in 16 genes were analyzed for association with obesity. Single nucleotide polymorphism rs1064891, located in the 3 0 UTR of the 6-phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3) gene, was nominally associated with obesity in combined analysis of cohorts 1 and 2 (P ¼ 0.007) and, in men that were lean or had severe obesity, with BMI (P ¼ o0.005). Conclusion: To combine linkage and expression profile data is valuable in finding new obesity genes. PFKFB3, a potential regulator of glycolysis, displays decreased mRNA levels in adipose tissue of obese women, is associated with obesity and is a new promising candidate gene for obesity warranting further studies.

Pathway-based analysis as an alternative and effective approach to identify disease-related genes or loci has been verified. To decipher the genetic background of plasma adiponectin levels, we performed genome wide pathway-based association studies in extremely obese individuals and normal-weight controls. The modified Gene Set Enrichment Algorithm (GSEA) was used to perform the pathway-based analyses (the GenGen Program) in 746 European American females, which were collected from our previous GWAS in extremely obese (BMI > 35 kg/m2) and never-overweight (BMI<25 kg/m2) controls. Rac1 cell motility signaling pathway was associated with plasma adiponectin after false-discovery rate (FDR) correction (empirical P < 0.001, FDR = 0.008, family-wise error rate = 0.008). Other several Rac1-centered pathways, such as cdc42racPathway (empirical P < 0.001), hsa00603 (empirical P = 0.003) were among the top associations. The RAC1 pathway association was replicated by the ICSNPathway method, yielded a FDR = 0.002. Quantitative pathway analyses yielded similar results (empirical P = 0.001) for the Rac1 pathway, although it failed to pass the multiple test correction (FDR = 0.11). We further replicated our pathway associations in the ADIPOGen Consortium data by the GSA-SNP method. Our results suggest that Rac1 and related cell motility pathways might be associated with plasma adiponectin levels and biological functions of adiponectin.