Genetic Loci Associated with Alzheimer’s Disease and Cerebrospinal Fluid Biomarkers in a Finnish Case-Control Cohort

Objectives

To understand the relation between risk genes for Alzheimer’s disease (AD) and their influence on biomarkers for AD, we examined the association of AD in the Finnish cohort with single nucleotide polymorphisms (SNPs) from top AlzGene loci, genome-wide association studies (GWAS), and candidate gene studies; and tested the correlation between these SNPs and AD markers Aβ_1–42, total tau (t-tau), and phosphorylated tau (p-tau) in cerebrospinal fluid (CSF).

Methods

We tested 25 SNPs for genetic association with clinical AD in our cohort comprised of 890 AD patients and 701-age matched healthy controls using logistic regression. For the correlational study with biomarkers, we tested 36 SNPs in a subset of 222 AD patients with available CSF using mixed models. Statistical analyses were adjusted for age, gender and APOE status. False discovery rate for multiple testing was applied. All participants were from academic hospital and research institutions in Finland.

Results

APOE-ε4, CLU rs11136000, and MS4A4A rs2304933 correlated with significantly decreased Aβ_1–42 (corrected p<0.05). At an uncorrected p<0.05, PPP3R1 rs1868402 and MAPT rs2435211 were related with increased t-tau; while SORL1 rs73595277 and MAPT rs16940758, with increased p-tau. Only TOMM40 rs2075650 showed association with clinical AD after adjusting for APOE-ε4 (p = 0.007), but not after multiple test correction (p>0.05).

Conclusions

We provide evidence that APOE-ε4, CLU and MS4A4A, which have been identified in GWAS to be associated with AD, also significantly reduced CSF Aβ_1–42 in AD. None of the other AlzGene and GWAS loci showed significant effects on CSF tau. The effects of other SNPs on CSF biomarkers and clinical AD diagnosis did not reach statistical significance. Our findings suggest that APOE-ε4, CLU and MS4A4A influence both AD risk and CSF Aβ_1–42.     

Mycobacterium marinum Causes a Latent Infection that Can Be Reactivated by Gamma Irradiation in Adult Zebrafish

The mechanisms leading to latency and reactivation of human tuberculosis are still unclear, mainly due to the lack of standardized animal models for latent mycobacterial infection. In this longitudinal study of the progression of a mycobacterial disease in adult zebrafish, we show that an experimental intraperitoneal infection with a low dose (∼35 bacteria) of Mycobacterium marinum, results in the development of a latent disease in most individuals. The infection is characterized by limited mortality (25%), stable bacterial loads 4 weeks following infection and constant numbers of highly organized granulomas in few target organs. The majority of bacteria are dormant during a latent mycobacterial infection in zebrafish, and can be activated by resuscitation promoting factor ex vivo. In 5–10% of tuberculosis cases in humans, the disease is reactivated usually as a consequence of immune suppression. In our model, we are able to show that reactivation can be efficiently induced in infected zebrafish by γ-irradiation that transiently depletes granulo/monocyte and lymphocyte pools, as determined by flow cytometry. This immunosuppression causes reactivation of the dormant mycobacterial population and a rapid outgrowth of bacteria, leading to 88% mortality in four weeks. In this study, the adult zebrafish presents itself as a unique non-mammalian vertebrate model for studying the development of latency, regulation of mycobacterial dormancy, as well as reactivation of latent or subclinical tuberculosis. The possibilities for screening for host and pathogen factors affecting the disease progression, and identifying novel therapeutic agents and vaccine targets make this established model especially attractive.     

Structural MRI in Frontotemporal Dementia: Comparisons between Hippocampal Volumetry,Tensor-Based Morphometry and Voxel-Based Morphometry

Background

MRI is an important clinical tool for diagnosing dementia-like diseases such as Frontemporal Dementia (FTD). However there is a need to develop more accurate and standardized MRI analysis methods.

Objective

To compare FTD with Alzheimer’s Disease (AD) and Mild Cognitive Impairment (MCI) with three automatic MRI analysis methods - Hippocampal Volumetry (HV), Tensor-based Morphometry (TBM) and Voxel-based Morphometry (VBM), in specific regions of interest in order to determine the highest classification accuracy.

Methods

Thirty-seven patients with FTD, 46 patients with AD, 26 control subjects, 16 patients with progressive MCI (PMCI) and 48 patients with stable MCI (SMCI) were examined with HV, TBM for shape change, and VBM for gray matter density. We calculated the Correct Classification Rate (CCR), sensitivity (SS) and specificity (SP) between the study groups.

Results

We found unequivocal results differentiating controls from FTD with HV (hippocampus left side) (CCR = 0.83; SS = 0.84; SP = 0.80), with TBM (hippocampus and amygdala (CCR = 0.80/SS = 0.71/SP = 0.94), and with VBM (all the regions studied, especially in lateral ventricle frontal horn, central part and occipital horn) (CCR = 0.87/SS = 0.81/SP = 0.96). VBM achieved the highest accuracy in differentiating AD and FTD (CCR = 0.72/SS = 0.67/SP = 0.76), particularly in lateral ventricle (frontal horn, central part and occipital horn) (CCR = 0.73), whereas TBM in superior frontal gyrus also achieved a high accuracy (CCR = 0.71/SS = 0.68/SP = 0.73). TBM resulted in low accuracy (CCR = 0.62) in the differentiation of AD from FTD using all regions of interest, with similar results for HV (CCR = 0.55).

Conclusion

Hippocampal atrophy is present not only in AD but also in FTD. Of the methods used, VBM achieved the highest accuracy in its ability to differentiate between FTD and AD.     

Predicting AD Conversion: Comparison between Prodromal AD Guidelines and Computer Assisted PredictAD Tool

Purpose

To compare the accuracies of predicting AD conversion by using a decision support system (PredictAD tool) and current research criteria of prodromal AD as identified by combinations of episodic memory impairment of hippocampal type and visual assessment of medial temporal lobe atrophy (MTA) on MRI and CSF biomarkers.

Methods

Altogether 391 MCI cases (158 AD converters) were selected from the ADNI cohort. All the cases had baseline cognitive tests, MRI and/or CSF levels of Aβ1–42 and Tau. Using baseline data, the status of MCI patients (AD or MCI) three years later was predicted using current diagnostic research guidelines and the PredictAD software tool designed for supporting clinical diagnostics. The data used were 1) clinical criteria for episodic memory loss of the hippocampal type, 2) visual MTA, 3) positive CSF markers, 4) their combinations, and 5) when the PredictAD tool was applied, automatically computed MRI measures were used instead of the visual MTA results. The accuracies of diagnosis were evaluated with the diagnosis made 3 years later.

Results

The PredictAD tool achieved the overall accuracy of 72% (sensitivity 73%, specificity 71%) in predicting the AD diagnosis. The corresponding number for a clinician’s prediction with the assistance of the PredictAD tool was 71% (sensitivity 75%, specificity 68%). Diagnosis with the PredictAD tool was significantly better than diagnosis by biomarkers alone or the combinations of clinical diagnosis of hippocampal pattern for the memory loss and biomarkers (p≤0.037).

Conclusion

With the assistance of PredictAD tool, the clinician can predict AD conversion more accurately than the current diagnostic criteria.     

Effects of sugar beet chitinase IV on root-associated fungal community of transgenic silver birch in a field trial

Heterogenous chitinases have been introduced in many plant species with the aim to increase the resistance of plants to fungal diseases. We studied the effects of the heterologous expression of sugar beet chitinase IV on the intensity of ectomycorrhizal (ECM) colonization and the structure of fungal communities in the field trial of 15 transgenic and 8 wild-type silver birch (Betula pendula Roth) genotypes. Fungal sequences were separated in denaturing gradient gel electrophoresis and identified by sequencing the ITS1 region to reveal the operational taxonomic units. ECM colonization was less intense in 7 out of 15 transgenic lines than in the corresponding non-transgenic control plants, but the slight decrease in overall ECM colonization in transgenic lines could not be related to sugar beet chitinase IV expression or total endochitinase activity. One transgenic line showing fairly weak sugar beet chitinase IV expression without significantly increased total endochitinase activity differed significantly from the non-transgenic controls in the structure of fungal community. Five sequences belonging to three different fungal genera (Hebeloma, Inocybe, Laccaria) were indicative of wild-type genotypes, and one sequence (Lactarius) indicated one transgenic line. In cluster analysis, the non-transgenic control grouped together with the transgenic lines indicating that genotype was a more important factor determining the structure of fungal communities than the transgenic status of the plants. With the tested birch lines, no clear evidence for the effect of the heterologous expression of sugar beet chitinase IV on ECM colonization or the structure of fungal community was found.     

Differential Sialylation of Serpin A1 in the Early Diagnosis of Parkinson’s Disease Dementia

The prevalence of Parkinson’s disease (PD) increases with age. Up to 50% of PD show cognitive decline in terms of a mild cognitive impairment already in early stages that predict the development of dementia, which can occur in up to 80% of PD patients over the long term, called Parkinson’s disease dementia (PDD). So far, diagnosis of PD/PDD is made according to clinical and neuropsychological examinations while laboratory data is only used for exclusion of other diseases. The aim of this study was the identification of possible biomarkers in cerebrospinal fluid (CSF) of PD, PDD and controls (CON) which predict the development of dementia in PD. For this, a proteomic approach optimized for CSF was performed using 18 clinically well characterized patients in a first step with subsequent validation using 84 patients. Here, we detected differentially sialylated isoforms of Serpin A1 as marker for differentiation of PD versus PDD in CSF. Performing 2D-immunoblots, all PDD patients could be identified correctly (sensitivity 100%). Ten out of 24 PD patients showed Serpin A1 isoforms in a similar pattern like PDD, indicating a specificity of 58% for the test-procedure. In control samples, no additional isoform was detected. On the basis of these results, we conclude that differentially sialylated products of Serpin A1 are an interesting biomarker to indicate the development of a dementia during the course of PD.     

Schooling affects growth in the three-spined stickleback, Gasterosteus aculeatus

Three-spined stickleback fry (mean length 20 mm, mean weight 14 mg) were reared for 14 days alone and in groups of six in a constant per capita water volume. The fish originated from two habitats (rock-pools, sea) of different predation pressure. The fry were fed nauplii of Artemia and commercial aquarium fish food ad libitum. Specific growth rates of solitary and schooling fry differed and were also affected by their origin. The specific growth rates of solitary fry from the sea averaged 1.0% day⁻¹ (length) and 6.0% day⁻¹ (weight) and those of solitary rock-pool fry 1.1 and 6.7%, respectively. For group-reared fish the corresponding values were 1.2% (length) and 6.6% (weight), and 1.3% (length) and 7.6% (weight). The finding that schooling sticklebacks grow faster than solitary ones implies that grouping enhances fitness in stickleback fry under the conditions of our experiments.     

Amazonian biodiversity and protected areas: do they meet?

Protected areas are crucial for Amazonian nature conservation. Many Amazonian reserves have been selected systematically to achieve biodiversity representativeness. We review the role natural-scientific understanding has played in reserve selection, and evaluate the theoretical potential of the existing reserves to cover a complete sample of the species diversity of the Amazonian rainforest biome. In total, 108 reserves (604,832 km²) are treated as strictly protected and Amazonian; 87 of these can be seen as systematically selected to sample species diversity (75.3% of total area). Because direct knowledge on all species distributions is unavailable, surrogates have been used to select reserves: direct information on some species distributions (15 reserves, 14.8% of total area); species distribution patterns predicted on the basis of conceptual models, mainly the Pleistocene refuge hypothesis, (5/10.3%); environmental units (46/27.3%); or a combination of distribution patterns and environmental units (21/22.9%). None of these surrogates are reliable: direct information on species distributions is inadequate; the Pleistocene refuge hypothesis is highly controversial; and environmental classifications do not capture all relevant ecological variation, and their relevance for species distribution patterns is undocumented. Hence, Amazonian reserves cannot be safely assumed to capture all Amazonian species. To improve the situation, transparency and an active dialogue with the scientific community should be integral to conservation planning. We suggest that the best currently available approach for sampling Amazonian species diversity in reserve selection is to simultaneously inventory indicator plant species and climatic and geological conditions, and to combine field studies with remote sensing.