Presenilin 1 Glu318Gly polymorphism: interpret with caution

Systematic identification of latent disease-gene associations from PubMed articles

Recent scientific advances have accumulated a tremendous amount of biomedical knowledge providing novel insights into the relationship between molecular and cellular processes and diseases. Literature mining is one of the commonly used methods to retrieve and extract information from scientific publications for understanding these associations. However, due to large data volume and complicated associations with noises, the interpretability of such association data for semantic knowledge discovery is challenging. In this study, we describe an integrative computational framework aiming to expedite the discovery of latent disease mechanisms by dissecting 146,245 disease-gene associations from over 25 million of PubMed indexed articles. We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. Our results demonstrate that (1) the LDA-based modeling is able to group similar diseases into disease topics; (2) the disease-specific association networks follow the scale-free network property; (3) certain subnetwork patterns were enriched in the disease-specific association networks; and (4) genes were enriched in topic-specific biological processes. Our approach offers promising opportunities for latent disease-gene knowledge discovery in biomedical research.

Atypical Huntington's disease with the clinical presentation of behavioural variant of frontotemporal dementia

Huntington's disease is an incurable, adult-onset, autosomal dominant inherited disorder caused by an expanded trinucleotide repeat (CAG). In this study, we describe a Huntington's disease patient displaying clinical symptoms of the behavioural variant of frontotemporal dementia in the absence of tremor and ataxia. The clinical onset was at the age of 36 years and the disease progressed slowly (18 years). Genetic testing revealed expanded trinucleotide CAG repeats in the Huntingtin gene, together with a Glu318Gly polymorphism in presenilin 1. Neuropathological assessment revealed extensive amyloid β (Aβ) aggregates in all cortical regions. No inclusions displaying hyperphosphorylated tau or phosphorylated transactive response DNA-binding protein 43 (TDP43) were found. A high number of p62 (sequestosome 1) immunopositive intranuclear inclusions were seen mainly in the cortex, while subcortical areas were affected to a lesser extent. Confocal microscopy revealed that the majority of p62 intranuclear lesions co-localised with the fused-in-sarcoma protein (FUS) immunostaining. The morphology of the inclusions resembled intranuclear aggregates in Huntington's disease. The presented proband suffered from Huntington's disease showed atypical distribution of FUS positive intranuclear aggregates in the cortical areas with concomitant Alzheimer's disease pathology.

Text mining facilitates database curation - extraction of mutation-disease associations from Bio-medical literature

Background

Advances in the next generation sequencing technology has accelerated the pace of individualized medicine (IM), which aims to incorporate genetic/genomic information into medicine. One immediate need in interpreting sequencing data is the assembly of information about genetic variants and their corresponding associations with other entities (e.g., diseases or medications). Even with dedicated effort to capture such information in biological databases, much of this information remains ‘locked’ in the unstructured text of biomedical publications. There is a substantial lag between the publication and the subsequent abstraction of such information into databases. Multiple text mining systems have been developed, but most of them focus on the sentence level association extraction with performance evaluation based on gold standard text annotations specifically prepared for text mining systems.

Results

We developed and evaluated a text mining system, MutD, which extracts protein mutation-disease associations from MEDLINE abstracts by incorporating discourse level analysis, using a benchmark data set extracted from curated database records. MutD achieves an F-measure of 64.3 % for reconstructing protein mutation disease associations in curated database records. Discourse level analysis component of MutD contributed to a gain of more than 10 % in F-measure when compared against the sentence level association extraction. Our error analysis indicates that 23 of the 64 precision errors are true associations that were not captured by database curators and 68 of the 113 recall errors are caused by the absence of associated disease entities in the abstract. After adjusting for the defects in the curated database, the revised F-measure of MutD in association detection reaches 81.5 %.

Conclusions

Our quantitative analysis reveals that MutD can effectively extract protein mutation disease associations when benchmarking based on curated database records. The analysis also demonstrates that incorporating discourse level analysis significantly improved the performance of extracting the protein-mutation-disease association. Future work includes the extension of MutD for full text articles.

The PSEN1, p.E318G variant increases the risk of Alzheimer's disease in APOE-ε4 carriers

The primary constituents of plaques (Aβ42/Aβ40) and neurofibrillary tangles (tau and phosphorylated forms of tau [ptau]) are the current leading diagnostic and prognostic cerebrospinal fluid (CSF) biomarkers for AD. In this study, we performed deep sequencing of APP, PSEN1, PSEN2, GRN, APOE and MAPT genes in individuals with extreme CSF Aβ42, tau, or ptau levels. One known pathogenic mutation (PSEN1 p.A426P), four high-risk variants for AD (APOE p.L46P, MAPT p.A152T, PSEN2 p.R62H and p.R71W) and nine novel variants were identified. Surprisingly, a coding variant in PSEN1, p.E318G (rs17125721-G) exhibited a significant association with high CSF tau (p = 9.2 × 10(-4)) and ptau (p = 1.8 × 10(-3)) levels. The association of the p.E318G variant with Aβ deposition was observed in APOE-ε4 allele carriers. Furthermore, we found that in a large case-control series (n = 5,161) individuals who are APOE-ε4 carriers and carry the p.E318G variant are at a risk of developing AD (OR = 10.7, 95% CI = 4.7-24.6) that is similar to APOE-ε4 homozygous (OR = 9.9, 95% CI = 7.2.9-13.6), and double the risk for APOE-ε4 carriers that do not carry p.E318G (OR = 3.9, 95% CI = 3.4-4.4). The p.E318G variant is present in 5.3% (n = 30) of the families from a large clinical series of LOAD families (n = 565) and exhibited a higher frequency in familial LOAD (MAF = 2.5%) than in sporadic LOAD (MAF = 1.6%) (p = 0.02). Additionally, we found that in the presence of at least one APOE-ε4 allele, p.E318G is associated with more Aβ plaques and faster cognitive decline. We demonstrate that the effect of PSEN1, p.E318G on AD susceptibility is largely dependent on an interaction with APOE-ε4 and mediated by an increased burden of Aβ deposition.

Familial Alzheimer disease-linked mutations specifically disrupt Ca2+ leak function of presenilin 1

Mutations in presenilins are responsible for approximately 40% of all early-onset familial Alzheimer disease (FAD) cases in which a genetic cause has been identified. In addition, a number of mutations in presenilin-1 (PS1) have been suggested to be associated with the occurrence of frontal temporal dementia (FTD). Presenilins are highly conserved transmembrane proteins that support cleavage of the amyloid precursor protein by gamma-secretase. Recently, we discovered that presenilins also function as passive ER Ca(2+) leak channels. Here we used planar lipid bilayer reconstitution assays and Ca(2+) imaging experiments with presenilin-null mouse embryonic fibroblasts to analyze ER Ca(2+) leak function of 6 FAD-linked PS1 mutants and 3 known FTD-associated PS1 mutants. We discovered that L166P, A246E, E273A, G384A, and P436Q FAD mutations in PS1 abolished ER Ca(2+) leak function of PS1. In contrast, A79V FAD mutation or FTD-associated mutations (L113P, G183V, and Rins352) did not appear to affect ER Ca(2+) leak function of PS1 in our experiments. We validated our findings in Ca(2+) imaging experiments with primary fibroblasts obtained from an FAD patient possessing mutant PS1-A246E. Our results indicate that many FAD mutations in presenilins are loss-of-function mutations affecting ER Ca(2+) leak activity. In contrast, none of the FTD-associated mutations affected ER Ca(2+) leak function of PS1, indicating that the observed effects are disease specific. Our observations are consistent with the potential role of disturbed Ca(2+) homeostasis in Alzheimer disease pathogenesis.

Modeling clinically heterogeneous presenilin mutations with transgenic Drosophila

To assess the potential of Drosophila to analyze clinically graded aspects of human disease, we developed a transgenic fly model to characterize Presenilin (PS) gene mutations that cause early-onset familial Alzheimer's disease (FAD). FAD exhibits a wide range in severity defined by ages of onset from 24 to 65 years . PS FAD mutants have been analyzed in mammalian cell culture, but conflicting data emerged concerning correlations between age of onset and PS biochemical activity . Choosing from over 130 FAD mutations in Presenilin-1, we introduced 14 corresponding mutations at conserved residues in Drosophila Presenilin (Psn) and assessed their biological activity in transgenic flies by using genetic, molecular, and statistical methods. Psn FAD mutant activities were tightly linked to their age-of-onset values, providing evidence that disease severity in humans primarily reflects differences in PS mutant lesions rather than contributions from unlinked genetic or environmental modifiers. Our study establishes a precedent for using transgenic Drosophila to study clinical heterogeneity in human disease.

Presenilin-1 mutation E318G and familial Alzheimer's disease in the Italian population

Presenilin-1 (PSEN-1) is a component of the gamma-secretase complex involved in beta-amyloid precursor protein (betaAPP) processing. To date about 140 pathogenic mutations in the PSEN-1 gene have been identified and their main biochemical effect is to increase the production of the fibrillogenic peptide Abeta(1-42). An exception is the PSEN-1 [E318G] mutation that does not alter Abeta(1-42) generation and is generally considered a non-pathogenic polymorphism. Nevertheless, this mutation was reported to be a genetic risk factor for familial Alzheimer's disease (FAD) in the Australian population. To independently confirm this indication, we performed a case-control association study in the Italian population. We found a significant association (p<0.05, Fisher's exact test) between the presence of PSEN-1 [E318G] and FAD. In addition, on measuring the Abeta(1-42) and Abeta(1-40) concentrations in fibroblast-conditioned media cultured from PSEN-1 [E318G] carriers and PSEN-1 [wild type] controls we noted a significant decrease (p<0.05, Mann-Whitney test) in the Abeta(1-42)/Abeta(1-40) ratio in PSEN-1 [E318G] carriers, suggesting a peculiar biochemical effect of this mutation.