Gene/Protein Disease Symptom Drug Enzyme Compound
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Query: UMLS:C0028754 (obesity)
 124,988 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

The primary cilium is a nexus of cell signaling, and ciliary dysfunction is associated with polycystic kidney disease, retinal degeneration, polydactyly, neural tube defects, and obesity (ciliopathies). Signaling molecules for cilium-associated pathways are concentrated in the cilium, and this is essential for efficient signaling. Cilia are nucleated from centrioles, and aberrant centriole numbers are seen in many cancers and in some ciliopathies. We tested the effect of supernumerary centrioles on cilium function and found that cells with extra centrioles often formed more than one cilium, had reduced ciliary concentration of Smoothened in response to Sonic hedgehog stimulation, and reduced Shh pathway transcriptional activation. This ciliary dilution phenotype was also observed with the serotonin receptor Htr6, fibrocystin PKHD1, and Arl13b. The presence of extra centrioles and cilia disrupted epithelial organization in 3D spheroid culture. Cells mutant for the tuberous sclerosis gene Tsc2 also had extra cilia and diluted ciliary protein. In most cells, extra cilia were clustered and shared the same ciliary pocket, suggesting that the ciliary pocket is the rate-limiting structure for trafficking of ciliary proteins. Thus, extra centrioles and cilia disrupt signaling and may contribute to disease phenotypes.
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PMID:Supernumerary centrosomes nucleate extra cilia and compromise primary cilium signaling. 2284 May 14

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 syndrome-related 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 genome-wide significance (P < 5 x 10(-8)), genes and loci identified in this study are worthy of further replication and investigation.
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PMID:Quantitative candidate gene association studies of metabolic traits in Han Chinese type 2 diabetes patients. 2663 13

The variation in weight within a shared environment is largely attributable to genetic factors. Whilst many genes/loci confer susceptibility to obesity, little is known about the genetic architecture of healthy thinness. Here, we characterise the heritability of thinness which we found was comparable to that of severe obesity (h2 = 28.07 vs 32.33% respectively), although with incomplete genetic overlap (r = -0.49, 95% CI [-0.17, -0.82], p = 0.003). In a genome-wide association analysis of thinness (n = 1,471) vs severe obesity (n = 1,456), we identified 10 loci previously associated with obesity, and demonstrate enrichment for established BMI-associated loci (pbinomial = 3.05x10-5). Simulation analyses showed that different association results between the extremes were likely in agreement with additive effects across the BMI distribution, suggesting different effects on thinness and obesity could be due to their different degrees of extremeness. In further analyses, we detected a novel obesity and BMI-associated locus at PKHD1 (rs2784243, obese vs. thin p = 5.99x10-6, obese vs. controls p = 2.13x10-6 pBMI = 2.3x10-13), associations at loci recently discovered with much larger sample sizes (e.g. FAM150B and PRDM6-CEP120), and novel variants driving associations at previously established signals (e.g. rs205262 at the SNRPC/C6orf106 locus and rs112446794 at the PRDM6-CEP120 locus). Our ability to replicate loci found with much larger sample sizes demonstrates the value of clinical extremes and suggest that characterisation of the genetics of thinness may provide a more nuanced understanding of the genetic architecture of body weight regulation and may inform the identification of potential anti-obesity targets.
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PMID:Genetic architecture of human thinness compared to severe obesity. 3067 29