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Antibody-LGI 1 autoimmune encephalitis manifesting as rapidly progressive dementia and hyponatremia: a case report and literature review.
Li, X, Yuan, J, Liu, L, Hu, W
BMC neurology. 2019;(1):19
Abstract
BACKGROUND Anti leucine-rich glioma inactivated 1 (LGI1) encephalitis is a rare autoimmune encephalitis (AE), characterized by acute or subacute cognitive impairment, faciobrachial dystonic seizures, psychiatric disturbances and hyponatremia. Antibody-LGI 1 autoimmune encephalitis (anti-LGI1 AE) has increasingly been recognized as a primary autoimmune disorder with favorable prognosis and response to treatment. CASE PRESENTATION Herein, we reported a male patient presenting as rapidly progressive dementia and hyponatremia. He had antibodies targeting LGI1 both in the cerebrospinal fluid and serum, which demonstrated the diagnosis of typical anti-LGI1 AE. The scores of Mini-Mental State Examination and Montreal Cognitive Assessment were 19/30 and 15/30, respectively. Cranial magnetic resonance images indicated hyperintensities in bilateral hippocampus. The findings of brain arterial spin labeling and Fluorine-18-fluorodeoxyglucose positron emission tomography showed no abnormal perfusion/metabolism. After the combined treatment of intravenous immunoglobulin and glucocorticoid, the patient's clinical symptoms improved obviously. CONCLUSIONS This case raises the awareness that a rapid progressive dementia with predominant memory deficits could be induced by immunoreactions against LGI1. The better recognition will be great importance for the early diagnosis, essential treatment, even a better prognosis.
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Effective lead optimization targeting the displacement of bridging receptor-ligand water molecules.
Chen, D, Li, Y, Zhao, M, Tan, W, Li, X, Savidge, T, Guo, W, Fan, X
Physical chemistry chemical physics : PCCP. 2018;(37):24399-24407
Abstract
Enhancing the binding affinities of ligands by means of lead modifications that displace bridging water molecules at protein-ligand interfaces is an important and widely studied lead optimization strategy. However, it is still challenging to ensure the success of this lead optimization strategy. Here we use theoretical derivations, which are then validated using reported experimental data, to identify the major determining factors in lead optimization designed to displace bridging water molecules. Our findings demonstrate that the nature of hydrogen-bond pairing between the ligand and protein polar atom(s) is the principal factor displacing interface water molecules, and not the binding strength of the water molecule. Our results also indicate that all interfacing bridging water molecules can potentially be targeted for displacement using this new approach. In summary, we show that strong-strong/weak-weak hydrogen-bond pairings of ligand atoms with protein atoms may provide useful guidance in lead modifications by designing modified ligands with higher binding affinities than their lead molecules. This study can help to increase the efficiency of rational drug design.
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ComplexContact: a web server for inter-protein contact prediction using deep learning.
Zeng, H, Wang, S, Zhou, T, Zhao, F, Li, X, Wu, Q, Xu, J
Nucleic acids research. 2018;(W1):W432-W437
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Abstract
ComplexContact (http://raptorx2.uchicago.edu/ComplexContact/) is a web server for sequence-based interfacial residue-residue contact prediction of a putative protein complex. Interfacial residue-residue contacts are critical for understanding how proteins form complex and interact at residue level. When receiving a pair of protein sequences, ComplexContact first searches for their sequence homologs and builds two paired multiple sequence alignments (MSA), then it applies co-evolution analysis and a CASP-winning deep learning (DL) method to predict interfacial contacts from paired MSAs and visualizes the prediction as an image. The DL method was originally developed for intra-protein contact prediction and performed the best in CASP12. Our large-scale experimental test further shows that ComplexContact greatly outperforms pure co-evolution methods for inter-protein contact prediction, regardless of the species.
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Rare coding variants and X-linked loci associated with age at menarche.
Lunetta, KL, Day, FR, Sulem, P, Ruth, KS, Tung, JY, Hinds, DA, Esko, T, Elks, CE, Altmaier, E, He, C, et al
Nature communications. 2015;:7756
Abstract
More than 100 loci have been identified for age at menarche by genome-wide association studies; however, collectively these explain only ∼3% of the trait variance. Here we test two overlooked sources of variation in 192,974 European ancestry women: low-frequency protein-coding variants and X-chromosome variants. Five missense/nonsense variants (in ALMS1/LAMB2/TNRC6A/TACR3/PRKAG1) are associated with age at menarche (minor allele frequencies 0.08-4.6%; effect sizes 0.08-1.25 years per allele; P<5 × 10(-8)). In addition, we identify common X-chromosome loci at IGSF1 (rs762080, P=9.4 × 10(-13)) and FAAH2 (rs5914101, P=4.9 × 10(-10)). Highlighted genes implicate cellular energy homeostasis, post-transcriptional gene silencing and fatty-acid amide signalling. A frequently reported mutation in TACR3 for idiopathic hypogonatrophic hypogonadism (p.W275X) is associated with 1.25-year-later menarche (P=2.8 × 10(-11)), illustrating the utility of population studies to estimate the penetrance of reportedly pathogenic mutations. Collectively, these novel variants explain ∼0.5% variance, indicating that these overlooked sources of variation do not substantially explain the 'missing heritability' of this complex trait.
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Insights into the genetic architecture of early stage age-related macular degeneration: a genome-wide association study meta-analysis.
Holliday, EG, Smith, AV, Cornes, BK, Buitendijk, GH, Jensen, RA, Sim, X, Aspelund, T, Aung, T, Baird, PN, Boerwinkle, E, et al
PloS one. 2013;(1):e53830
Abstract
Genetic factors explain a majority of risk variance for age-related macular degeneration (AMD). While genome-wide association studies (GWAS) for late AMD implicate genes in complement, inflammatory and lipid pathways, the genetic architecture of early AMD has been relatively under studied. We conducted a GWAS meta-analysis of early AMD, including 4,089 individuals with prevalent signs of early AMD (soft drusen and/or retinal pigment epithelial changes) and 20,453 individuals without these signs. For various published late AMD risk loci, we also compared effect sizes between early and late AMD using an additional 484 individuals with prevalent late AMD. GWAS meta-analysis confirmed previously reported association of variants at the complement factor H (CFH) (peak P = 1.5×10(-31)) and age-related maculopathy susceptibility 2 (ARMS2) (P = 4.3×10(-24)) loci, and suggested Apolipoprotein E (ApoE) polymorphisms (rs2075650; P = 1.1×10(-6)) associated with early AMD. Other possible loci that did not reach GWAS significance included variants in the zinc finger protein gene GLI3 (rs2049622; P = 8.9×10(-6)) and upstream of GLI2 (rs6721654; P = 6.5×10(-6)), encoding retinal Sonic hedgehog signalling regulators, and in the tyrosinase (TYR) gene (rs621313; P = 3.5×10(-6)), involved in melanin biosynthesis. For a range of published, late AMD risk loci, estimated effect sizes were significantly lower for early than late AMD. This study confirms the involvement of multiple established AMD risk variants in early AMD, but suggests weaker genetic effects on the risk of early AMD relative to late AMD. Several biological processes were suggested to be potentially specific for early AMD, including pathways regulating RPE cell melanin content and signalling pathways potentially involved in retinal regeneration, generating hypotheses for further investigation.
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FTO gene polymorphisms and obesity risk: a meta-analysis.
Peng, S, Zhu, Y, Xu, F, Ren, X, Li, X, Lai, M
BMC medicine. 2011;:71
Abstract
BACKGROUND The pathogenesis of obesity is reportedly related to variations in the fat mass and an obesity-associated gene (FTO); however, as the number of reports increases, particularly with respect to varying ethnicities, there is a need to determine more precisely the effect sizes in each ethnic group. In addition, some reports have claimed ethnic-specific associations with alternative SNPs, and to that end there has been a degree of confusion. METHODS We searched PubMed, MEDLINE, Web of Science, EMBASE, and BIOSIS Preview to identify studies investigating the associations between the five polymorphisms and obesity risk. Individual study odds ratios (OR) and their 95% confidence intervals (CI) were estimated using per-allele comparison. Summary ORs were estimated using a random effects model. RESULTS We identified 59 eligible case-control studies in 27 articles, investigating 41,734 obesity cases and 69,837 healthy controls. Significant associations were detected between obesity risk and the five polymorphisms: rs9939609 (OR: 1.31, 95% CI: 1.26 to 1.36), rs1421085 (OR: 1.43, 95% CI: 1.33 to 1.53), rs8050136 (OR: 1.25, 95% CI: 1.13 to 1.38), rs17817449 (OR: 1.54, 95% CI: 1.41 to 1.68), and rs1121980 (OR: 1.34, 95% CI: 1.10 to 1.62). Begg's and Egger's tests provided no evidence of publication bias for the polymorphisms except rs1121980. There is evidence of higher heterogeneity, with I2 test values ranging from 38.1% to 84.5%. CONCLUSIONS This meta-analysis suggests that FTO may represent a low-penetrance susceptible gene for obesity risk. Individual studies with large sample size are needed to further evaluate the associations between the polymorphisms and obesity risk in various ethnic populations.
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Quantitative prediction of the thermal motion and intrinsic disorder of protein cofactors in crystalline state: a case study on halide anions.
Ren, Y, Chen, X, Li, X, Lai, H, Wang, Q, Zhou, P, Chen, G
Journal of theoretical biology. 2010;(2):291-8
Abstract
The thermal motion and intrinsic disorder of protein cofactors are highly correlated with their biological functions and can be at least in part measured by atomic temperature factor or B-factor. However, this crystallographic parameter, which actually shares the equal importance with the atomic coordinate in describing the complete profile of crystal structures, has long been underappreciated in the field of biology. In the present study, we attempt to put the first step towards the quantitative prediction of the B-factor values of halide anions, which were recently found to play a fundamental role in conferring stability and specificity to the architecture of proteins and their complexes with nucleic acids and small ligands. In this procedure, the local nonbonding landscapes of halide anions bound in proteins are characterized by electrostatic and dispersion potentials, and then the resulting descriptors of the characterization are statistically correlated with experimentally measured B-factors by using both linear and nonlinear machine learning approaches. From the modeling results and the comparison of these results to those obtained previously for predicting protein B-factors, we demonstrate that the dynamic behavior of halide anions in protein crystals is primarily governed by the local features of nonbonding potential landscapes and, owing to the non-ignorable noise existing in experimental data, the relationship between the B-factor values and the local nonbonding landscapes can only be modeled at a moderate level of accuracy even using the complicated nonlinear methods. These findings are consistent well with that concluding from previous studies of protein B-factors.