| 1. |
- Heid, Iris M, et al.
(author)
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Meta-analysis identifies 13 new loci associated with waist-hip ratio and reveals sexual dimorphism in the genetic basis of fat distribution
- 2010
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 949-960
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Journal article (peer-reviewed)abstract
- Waist-hip ratio (WHR) is a measure of body fat distribution and a predictor of metabolic consequences independent of overall adiposity. WHR is heritable, but few genetic variants influencing this trait have been identified. We conducted a meta-analysis of 32 genome-wide association studies for WHR adjusted for body mass index (comprising up to 77,167 participants), following up 16 loci in an additional 29 studies (comprising up to 113,636 subjects). We identified 13 new loci in or near RSPO3, VEGFA, TBX15-WARS2, NFE2L3, GRB14, DNM3-PIGC, ITPR2-SSPN, LY86, HOXC13, ADAMTS9, ZNRF3-KREMEN1, NISCH-STAB1 and CPEB4 (P = 1.9 × 10⁻⁹ to P = 1.8 × 10⁻⁴⁰) and the known signal at LYPLAL1. Seven of these loci exhibited marked sexual dimorphism, all with a stronger effect on WHR in women than men (P for sex difference = 1.9 × 10⁻³ to P = 1.2 × 10⁻¹³). These findings provide evidence for multiple loci that modulate body fat distribution independent of overall adiposity and reveal strong gene-by-sex interactions.
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| 2. |
- Speliotes, Elizabeth K., et al.
(author)
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Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index
- 2010
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 42:11, s. 937-948
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Journal article (peer-reviewed)abstract
- Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ~2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10−8), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.
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| 3. |
- Johnson, Toby, et al.
(author)
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Blood Pressure Loci Identified with a Gene-Centric Array.
- 2011
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In: American Journal of Human Genetics. - : Elsevier BV. - 1537-6605 .- 0002-9297. ; 89:6, s. 688-700
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Journal article (peer-reviewed)abstract
- Raised blood pressure (BP) is a major risk factor for cardiovascular disease. Previous studies have identified 47 distinct genetic variants robustly associated with BP, but collectively these explain only a few percent of the heritability for BP phenotypes. To find additional BP loci, we used a bespoke gene-centric array to genotype an independent discovery sample of 25,118 individuals that combined hypertensive case-control and general population samples. We followed up four SNPs associated with BP at our p < 8.56× 10(-7) study-specific significance threshold and six suggestively associated SNPs in a further 59,349 individuals. We identified and replicated a SNP at LSP1/TNNT3, a SNP at MTHFR-NPPB independent (r(2) = 0.33) of previous reports, and replicated SNPs at AGT and ATP2B1 reported previously. An analysis of combined discovery and follow-up data identified SNPs significantly associated with BP at p < 8.56× 10(-7) at four further loci (NPR3, HFE, NOS3, and SOX6). The high number of discoveries made with modest genotyping effort can be attributed to using a large-scale yet targeted genotyping array and to the development of a weighting scheme that maximized power when meta-analyzing results from samples ascertained with extreme phenotypes, in combination with results from nonascertained or population samples. Chromatin immunoprecipitation and transcript expression data highlight potential gene regulatory mechanisms at the MTHFR and NOS3 loci. These results provide candidates for further study to help dissect mechanisms affecting BP and highlight the utility of studying SNPs and samples that are independent of those studied previously even when the sample size is smaller than that in previous studies.
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| 4. |
- Koettgen, Anna, et al.
(author)
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Genome-wide association analyses identify 18 new loci associated with serum urate concentrations
- 2013
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 45:2, s. 145-154
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Journal article (peer-reviewed)abstract
- Elevated serum urate concentrations can cause gout, a prevalent and painful inflammatory arthritis. By combining data from >140,000 individuals of European ancestry within the Global Urate Genetics Consortium (GUGC), we identified and replicated 28 genome-wide significant loci in association with serum urate concentrations (18 new regions in or near TRIM46, INHBB, SEMBT1, TMEM171, VEGFA, BAZ1B, PRKAG2, STC1, HNF4G, A1CF, ATXN2, UBE2Q2, IGF1R, NFAT5, MAF, HLF, ACVR1B-ACVRL1 and B3GNT4). Associations for many of the loci were of similar magnitude in individuals of non-European ancestry. We further characterized these loci for associations with gout, transcript expression and the fractional excretion of urate. Network analyses implicate the inhibins-activins signaling pathways and glucose metabolism in systemic urate control. New candidate genes for serum urate concentration highlight the importance of metabolic control of urate production and excretion, which may have implications for the treatment and prevention of gout.
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| 5. |
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| 6. |
- Lapins, Maris, et al.
(author)
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A Unified Proteochemometric Model for Prediction of Inhibition of Cytochrome P450 Isoforms
- 2013
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In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 8:6, s. e66566-
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Journal article (peer-reviewed)abstract
- A unified proteochemometric (PCM) model for the prediction of the ability of drug-like chemicals to inhibit five major drug metabolizing CYP isoforms (i.e. CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) was created and made publicly available under the Bioclipse Decision Support open source system at www.cyp450model.org. In regards to the proteochemometric modeling we represented the chemical compounds by molecular signature descriptors and the CYP-isoforms by alignment-independent description of composition and transition of amino acid properties of their protein primary sequences. The entire training dataset contained 63 391 interactions and the best PCM model was obtained using signature descriptors of height 1, 2 and 3 and inducing the model with a support vector machine. The model showed excellent predictive ability with internal AUC = 0.923 and an external AUC = 0.940, as evaluated on a large external dataset. The advantage of PCM models is their extensibility making it possible to extend our model for new CYP isoforms and polymorphic CYP forms. A key benefit of PCM is that all proteins are confined in one single model, which makes it generally more stable and predictive as compared with single target models. The inclusion of the model in Bioclipse Decision Support makes it possible to make virtual instantaneous predictions (∼100 ms per prediction) while interactively drawing or modifying chemical structures in the Bioclipse chemical structure editor.
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| 7. |
- Lapins, Maris, et al.
(author)
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Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques
- 2010
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In: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 11, s. 339-
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Journal article (peer-reviewed)abstract
- BackgroundProtein kinases play crucial roles in cell growth, differentiation, and apoptosis. Abnormal function of protein kinases can lead to many serious diseases, such as cancer. Kinase inhibitors have potential for treatment of these diseases. However, current inhibitors interact with a broad variety of kinases and interfere with multiple vital cellular processes, which causes toxic effects. Bioinformatics approaches that can predict inhibitor-kinase interactions from the chemical properties of the inhibitors and the kinase macromolecules might aid in design of more selective therapeutic agents, that show better efficacy and lower toxicity.ResultsWe applied proteochemometric modelling to correlate the properties of 317 wild-type and mutated kinases and 38 inhibitors (12,046 inhibitor-kinase combinations) to the respective combination's interaction dissociation constant (K-d). We compared six approaches for description of protein kinases and several linear and non-linear correlation methods. The best performing models encoded kinase sequences with amino acid physico-chemical z-scale descriptors and used support vector machines or partial least-squares projections to latent structures for the correlations. Modelling performance was estimated by double cross-validation. The best models showed high predictive ability; the squared correlation coefficient for new kinase-inhibitor pairs ranging P-2 = 0.67-0.73; for new kinases it ranged P-kin(2) = 0.65-0.70. Models could also separate interacting from non-interacting inhibitor-kinase pairs with high sensitivity and specificity; the areas under the ROC curves ranging AUC = 0.92-0.93. We also investigated the relationship between the number of protein kinases in the dataset and the modelling results. Using only 10% of all data still a valid model was obtained with P-2 = 0.47, P-kin(2) = 0.42 and AUC = 0.83.ConclusionsOur results strongly support the applicability of proteochemometrics for kinome-wide interaction modelling. Proteochemometrics might be used to speed-up identification and optimization of protein kinase targeted and multi-targeted inhibitors.
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| 8. |
- Nantasenamat, Chanin, et al.
(author)
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Illuminating the Origins of Spectral Properties of Green Fluorescent Proteins via Proteochemometric and Molecular Modeling
- 2014
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In: Journal of Computational Chemistry. - : Wiley. - 0192-8651 .- 1096-987X. ; 35:27, s. 1951-1966
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Journal article (peer-reviewed)abstract
- Green fluorescent protein (GFP) has immense utility in biomedical imaging owing to its autofluorescent nature. In efforts to broaden the spectral diversity of GFP, there have been several reports of engineered mutants via rational design and random mutagenesis. Understanding the origins of spectral properties of GFP could be achieved by means of investigating its structure-activity relationship. The first quantitative structure-property relationship study for modeling the spectral properties, particularly the excitation and emission maximas, of GFP was previously proposed by us some years ago in which quantum chemical descriptors were used for model development. However, such simplified model does not consider possible effects that neighboring amino acids have on the conjugated pi-system of GFP chromophore. This study describes the development of a unified proteochemometric model in which the GFP chromophore and amino acids in its vicinity are both considered in the same model. The predictive performance of the model was verified by internal and external validation as well as gamma-scrambling. Our strategy provides a general solution for elucidating the contribution that specific ligand and protein descriptors have on the investigated spectral property, which may be useful in engineering novel GFP variants with desired characteristics.
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| 9. |
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| 10. |
- Padmanabhan, Sandosh, et al.
(author)
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Genome-Wide Association Study of Blood Pressure Extremes Identifies Variant near UMOD Associated with Hypertension
- 2010
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In: PLoS Genetics. - : Public Library of Science (PLoS). - 1553-7404. ; 6:10
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Journal article (peer-reviewed)abstract
- Hypertension is a heritable and major contributor to the global burden of disease. The sum of rare and common genetic variants robustly identified so far explain only 1%-2% of the population variation in BP and hypertension. This suggests the existence of more undiscovered common variants. We conducted a genome-wide association study in 1,621 hypertensive cases and 1,699 controls and follow-up validation analyses in 19,845 cases and 16,541 controls using an extreme case-control design. We identified a locus on chromosome 16 in the 59 region of Uromodulin (UMOD; rs13333226, combined P value of 3.6x10(-11)). The minor G allele is associated with a lower risk of hypertension (OR [95% CI]: 0.87 [0.84-0.91]), reduced urinary uromodulin excretion, better renal function; and each copy of the G allele is associated with a 7.7% reduction in risk of CVD events after adjusting for age, sex, BMI, and smoking status (H.R. = 0.923, 95% CI 0.860-0.991; p = 0.027). In a subset of 13,446 individuals with estimated glomerular filtration rate (eGFR) measurements, we show that rs13333226 is independently associated with hypertension (unadjusted for eGFR: 0.89 [0.83-0.96], p = 0.004; after eGFR adjustment: 0.89 [0.83-0.96], p = 0.003). In clinical functional studies, we also consistently show the minor G allele is associated with lower urinary uromodulin excretion. The exclusive expression of uromodulin in the thick portion of the ascending limb of Henle suggests a putative role of this variant in hypertension through an effect on sodium homeostasis. The newly discovered UMOD locus for hypertension has the potential to give new insights into the role of uromodulin in BP regulation and to identify novel drugable targets for reducing cardiovascular risk.
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| 11. |
- Prusis, Peteris, et al.
(author)
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Design and evaluation of substrate-based octapeptide and non substrate-based tetrapeptide inhibitors of dengue virus NS2B-NS3 proteases
- 2013
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In: Biochemical and Biophysical Research Communications - BBRC. - : Elsevier BV. - 0006-291X .- 1090-2104. ; 434:4, s. 767-772
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Journal article (peer-reviewed)abstract
- A series of 45 peptide inhibitors was designed, synthesized, and evaluated against the NS2B-NS3 proteases of the four subtypes of dengue virus, DEN-1-4. The design was based on proteochemometric models for Michaelis (K-m) and cleavage rate constants (k(cat)) of protease substrates. This led first to octapeptides showing submicromolar or low micromolar inhibitory activities on the four proteases. Stepwise removal of cationic substrate non-prime side residues and variations in the prime side sequence resulted finally in an uncharged tetrapeptide, WYCW-NH2, with inhibitory K-i values of 4.2, 4.8, 24.4, and 11.2 mu M for the DEN-1-4 proteases, respectively. Analysis of the inhibition data by proteochemometric modeling suggested the possibility for different binding poses of the shortened peptides compared to the octapeptides, which was supported by results of docking of WYCW-NH2 into the X-ray structure of DEN-3 protease.
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| 12. |
- Strömbergsson, Helena, et al.
(author)
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Towards proteome-wide interaction models using the proteochemometrics approach
- 2010
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In: Molecular Informatics. - : Wiley. - 1868-1743 .- 1868-1751. ; 29:6-7, s. 499-508
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Journal article (peer-reviewed)abstract
- A proteochemometrics model was induced from all interaction data in the BindingDB database, comprizing in all 7078 protein-ligand complexes with representatives from all major drug target categories. Proteins were represented by alignment-independent sequence descriptors holding information on properties such as hydrophobicity, charge, and secondary structure. Ligands were represented by commonly used QSAR descriptors. The inhibition constant (pK(i)) values of protein-ligand complexes were discretized into "high" and "low" interaction activity. Different machine-learning techniques were used to induce models relating protein and ligand properties to the interaction activity. The best was decision trees, which gave an accuracy of 80% and an area under the ROC curve of 0.81. The tree pointed to the protein and ligand properties, which are relevant for the interaction. As the approach does neither require alignments nor knowledge of protein 3D structures virtually all available protein-ligand interaction data could be utilized, thus opening a way to completely general interaction models that may span entire proteomes.
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