Cerebral atrophy in mild cognitive impairment and Alzheimer disease: rates and acceleration.

OBJECTIVE: To quantify the regional and global cerebral atrophy rates and assess acceleration rates in healthy controls, subjects with mild cognitive impairment (MCI), and subjects with mild Alzheimer disease (AD). METHODS: Using 0-, 6-, 12-, 18-, 24-, and 36-month MRI scans of controls and subjects with MCI and AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, we calculated volume change of whole brain, hippocampus, and ventricles between all pairs of scans using the boundary shift integral. RESULTS: We found no evidence of acceleration in whole-brain atrophy rates in any group. There was evidence that hippocampal atrophy rates in MCI subjects accelerate by 0.22%/year2 on average (p = 0.037). There was evidence of acceleration in rates of ventricular enlargement in subjects with MCI (p = 0.001) and AD (p < 0.001), with rates estimated to increase by 0.27 mL/year2 (95% confidence interval 0.12, 0.43) and 0.88 mL/year2 (95% confidence interval 0.47, 1.29), respectively. A post hoc analysis suggested that the acceleration of hippocampal loss in MCI subjects was mainly driven by the MCI subjects that were observed to progress to clinical AD within 3 years of baseline, with this group showing hippocampal atrophy rate acceleration of 0.50%/year2 (p = 0.003). CONCLUSIONS: The small acceleration rates suggest a long period of transition to the pathologic losses seen in clinical AD. The acceleration in hippocampal atrophy rates in MCI subjects in the ADNI seems to be driven by those MCI subjects who concurrently progressed to a clinical diagnosis of AD

Pilus distribution among lineages of group b <i>streptococcus</i>: an evolutionary and clinical perspective

&lt;b&gt;Background&lt;/b&gt;&lt;p&gt;&lt;/p&gt; Group B Streptococcus (GBS) is an opportunistic pathogen in both humans and bovines. Epidemiological and phylogenetic analyses have found strains belonging to certain phylogenetic lineages to be more frequently associated with invasive newborn disease, asymptomatic maternal colonization, and subclinical bovine mastitis. Pilus structures in GBS facilitate colonization and invasion of host tissues and play a role in biofilm formation, though few large-scale studies have estimated the frequency and diversity of the three pilus islands (PIs) across diverse genotypes. Here, we examined the distribution of pilus islands (PI) 1, 2a and 2b among 295 GBS strains representing 73 multilocus sequence types (STs) belonging to eight clonal complexes. PCR-based RFLP was also used to evaluate variation in the genes encoding pilus backbone proteins of PI-2a and PI-2b.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Results&lt;/b&gt;&lt;p&gt;&lt;/p&gt; All 295 strains harbored one of the PI-2 variants and most human-derived strains contained PI-1. Bovine-derived strains lacked PI-1 and possessed a unique PI-2b backbone protein allele. Neonatal strains more frequently had PI-1 and a PI-2 variant than maternal colonizing strains, and most CC-17 strains had PI-1 and PI-2b with a distinct backbone protein allele. Furthermore, we present evidence for the frequent gain and loss of genes encoding certain pilus types.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt;&lt;p&gt;&lt;/p&gt; These data suggest that pilus combinations impact host specificity and disease presentation and that diversification often involves the loss or acquisition of PIs. Such findings have implications for the development of GBS vaccines that target the three pilus islands

APOE ε4 is associated with disproportionate progressive hippocampal atrophy in AD.

OBJECTIVES: To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates. METHODS: MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into "progressors" (MCI-P) if diagnosed with AD within 36 months or "stable" (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated. RESULTS: Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P. CONCLUSIONS: These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD

A Comparison of Accelerated and Non-accelerated MRI Scans for Brain Volume and Boundary Shift Integral Measures of Volume Change: Evidence from the ADNI Dataset.

The aim of this study was to assess whether the use of accelerated MRI scans in place of non-accelerated scans influenced brain volume and atrophy rate measures in controls and subjects with mild cognitive impairment and Alzheimer's disease. We used data from 861 subjects at baseline, 573 subjects at 6 months and 384 subjects at 12 months from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We calculated whole-brain, ventricular and hippocampal atrophy rates using the k-means boundary shift integral (BSI). Scan quality was visually assessed and the proportion of good quality accelerated and non-accelerated scans compared. We also compared MMSE scores, vascular burden and age between subjects with poor quality scans with those with good quality scans. Finally, we estimated sample size requirements for a hypothetical clinical trial when using atrophy rates from accelerated scans and non-accelerated scans. No significant differences in whole-brain, ventricular and hippocampal volumes and atrophy rates were found between accelerated and non-accelerated scans. Twice as many non-accelerated scan pairs suffered from at least some motion artefacts compared with accelerated scan pairs (p ≤ 0.001), which may influence the BSI. Subjects whose accelerated scans had significant motion had a higher mean vascular burden and age (p ≤ 0.05) whilst subjects whose non-accelerated scans had significant motion had poorer MMSE scores (p ≤ 0.05). No difference in estimated sample size requirements was found when using accelerated vs. non-accelerated scans. Accelerated scans reduce scan time and are better tolerated. Therefore it may be advantageous to use accelerated over non-accelerated scans in clinical trials that use ADNI-type protocols, especially in more cognitively impaired subjects

Predicting Cognitive Decline in Nondemented Elders Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

BACKGROUND AND OBJECTIVES: Dementia is a growing socio-economic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds (CMB), whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI), and those with MCI who later converted to an Alzheimer's disease (AD) diagnosis (MCItoAD). METHODS: Standardised baseline biomarker data from ADNI2/Go, and longitudinal diagnostic data (including ADNI3), were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up timepoints available. Models were fit for biomarkers univariately, and together in a multivariable model. Hazard Ratios (HR) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS: For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = .002; fully-adjusted model: HR 1.98, p = .003), and lower hippocampal volume (individual: HR 0.54, p = .001; fully-adjusted: HR 0.40, p < .001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < .001; fully-adjusted model: HR 0.55, p < .001) and whole-brain volume (individual: HR 0.31, p < .001; fully-adjusted: HR 0.48, p = .02), increased CSF ptau (individual: HR 1.88, p < .001; fully-adjusted: HR 1.61, p < .001), and lower CSF amyloid (individual: HR 0.37, p < .001, fully-adjusted: HR 0.62, p = .008) were most strongly associated with conversion to AD individually and independently. DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, while WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathological pathway, such as vascular cognitive impairment

Patterns of progressive atrophy vary with age in Alzheimer's disease patients.

Age is not only the greatest risk factor for Alzheimer's disease (AD) but also a key modifier of disease presentation and progression. Here, we investigate how longitudinal atrophy patterns vary with age in mild cognitive impairment (MCI) and AD. Data comprised serial longitudinal 1.5-T magnetic resonance imaging scans from 153 AD, 339 MCI, and 191 control subjects. Voxel-wise maps of longitudinal volume change were obtained and aligned across subjects. Local volume change was then modeled in terms of diagnostic group and an interaction between group and age, adjusted for total intracranial volume, white-matter hyperintensity volume, and apolipoprotein E genotype. Results were significant at p < 0.05 with family-wise error correction for multiple comparisons. An age-by-group interaction revealed that younger AD patients had significantly faster atrophy rates in the bilateral precuneus, parietal, and superior temporal lobes. These results suggest younger AD patients have predominantly posterior progressive atrophy, unexplained by white-matter hyperintensity, apolipoprotein E, or total intracranial volume. Clinical trials may benefit from adapting outcome measures for patient groups with lower average ages, to capture progressive atrophy in posterior cortices

Disruption in A-to-I Editing Levels Affects C. elegans Development More Than a Complete Lack of Editing

A-to-I RNA editing, catalyzed by ADAR proteins, is widespread in eukaryotic transcriptomes. Studies showed that, in C. elegans, ADR-2 can actively deaminate dsRNA, whereas ADR-1 cannot. Therefore, we set out to study the effect of each of the ADAR genes on the RNA editing process. We performed comprehensive phenotypic, transcriptomics, proteomics, and RNA binding screens on worms mutated in a single ADAR gene. We found that ADR-1 mutants exhibit more-severe phenotypes than ADR-2, and some of them are a result of non-editing functions of ADR-1. We also show that ADR-1 significantly binds edited genes and regulates mRNA expression, whereas the effect on protein levels is minor. In addition, ADR-1 primarily promotes editing by ADR-2 at the L4 stage of development. Our results suggest that ADR-1 has a significant role in the RNA editing process and in altering editing levels that affect RNA expression; loss of ADR-1 results in severe phenotypes

Predicting Cognitive Decline in Older Adults Using Baseline Metrics of AD Pathologies, Cerebrovascular Disease, and Neurodegeneration

BACKGROUND AND OBJECTIVES: Dementia is a growing socioeconomic challenge that requires early intervention. Identifying biomarkers that reliably predict clinical progression early in the disease process would better aid selection of individuals for future trial participation. Here, we compared the ability of baseline, single time-point biomarkers (CSF amyloid 1-42, CSF ptau-181, white matter hyperintensities (WMH), cerebral microbleeds, whole-brain volume, and hippocampal volume) to predict decline in cognitively normal individuals who later converted to mild cognitive impairment (MCI) (CNtoMCI) and those with MCI who later converted to an Alzheimer disease (AD) diagnosis (MCItoAD). METHODS: Standardized baseline biomarker data from AD Neuroimaging Initiative 2 (ADNI2)/GO and longitudinal diagnostic data (including ADNI3) were used. Cox regression models assessed biomarkers in relation to time to change in clinical diagnosis using all follow-up time points available. Models were fit for biomarkers univariately and together in a multivariable model. Hazard ratios (HRs) were compared to evaluate biomarkers. Analyses were performed separately in CNtoMCI and MCItoAD groups. RESULTS: For CNtoMCI (n = 189), there was strong evidence that higher WMH volume (individual model: HR 1.79, p = 0.002; fully adjusted model: HR 1.98, p = 0.003) and lower hippocampal volume (individual: HR 0.54, p = 0.001; fully adjusted: HR 0.40, p < 0.001) were associated with conversion to MCI individually and independently. For MCItoAD (n = 345), lower hippocampal (individual model: HR 0.45, p < 0.001; fully adjusted model: HR 0.55, p < 0.001) and whole-brain volume (individual: HR 0.31, p < 0.001; fully adjusted: HR 0.48, p = 0.02), increased CSF ptau (individual: HR 1.88, p < 0.001; fully adjusted: HR 1.61, p < 0.001), and lower CSF amyloid (individual: HR 0.37, p < 0.001; fully adjusted: HR 0.62, p = 0.008) were most strongly associated with conversion to AD individually and independently. DISCUSSION: Lower hippocampal volume was a consistent predictor of clinical conversion to MCI and AD. CSF and brain volume biomarkers were predictive of conversion to AD from MCI, whereas WMH were predictive of conversion to MCI from cognitively normal. The predictive ability of WMH in the CNtoMCI group may be interpreted as some being on a different pathologic pathway, such as vascular cognitive impairment